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Poster Abstracts- Metabomeeting 2011, 25th

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September 2011, Helsinki, Finland

Poster Abstracts


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POSTER 1

USING METABOLOMICS TO IDENTIFY PRE-

SYMPTOMATIC BIOMARKERS OF TYPE 1 DIABETES

Steven Murfitt, Paola Zaccone, Anne Cooke and

Julian L. Griffin

Department of Biochemistry and the Cambridge Systems

Biology Centre, University of Cambridge, UK Department

of Pathology, University of Cambridge, UK

It is known that the autoimmune destruction of

pancreatic beta cells may have been occurring for a

number of years prior to the onset of the clinical

symptoms of type 1 diabetes. To prevent

irrevocable beta cell destruction, and the serious

complications that this causes, it would therefore be

advantageous to be able to fully identify susceptible

individuals and intervene as early as possible. We

are using the established non-obese diabetic (NOD)

mouse model of type 1 diabetes, as well as the

genetically congenic NODE mouse that does not go

on to develop type 1 diabetes. The aim of the study

is to identify biomarkers of underlying pathological

processes at the pre-symptomatic stage of the

disease and to determine whether these provide

accurate markers of predisposition to the

destruction of beta cells. This could represent a

considerable advance in the treatment of type 1

diabetes. Pancreas and plasma samples were taken

from female NOD and NODE mice at 4-6, 11-12, and

16-32 weeks of age, with the NODE mice

representing the control group of the study. These

age ranges represent animals which have not

developed diabetes, those in a pre-diabetic state,

and those which have the full symptoms of

glucosuria, respectively. We report our findings

from the analysis of fatty acid methyl esters (FAME)

by Gas Chromatography - Flame Ionization

Detection (GC-FID), aqueous metabolites by high

resolution 1H Nuclear Magnetic Resonance (NMR)

spectroscopy and Gas Chromatography - Mass

Spectrometry (GC-MS), and in particular

perturbations in amino acid metabolism in the NOD

mice prior to overt diabetes.

POSTER 2

IDENTIFICATION OF DISCRIMINATING MARKERS IN

HUMAN PLASMA AFTER A HIGH DIETARY FIBER

INTAKE

Anna Johansson(1), Matilda Ulmius(1), Thaer

Barri(2), Lars O. Dragsted(2) and Gunilla Önning(1)

(1) Biomedical Nutrition, Pure and Applied Biochemistry,

Lund University, PO Box 124, SE-221 00 Lund, Sweden;

[email protected] (2) Institute of Human

Nutrition, Faculty of Life Sciences, University of

Copenhagen, Rolighedsvej 30, DK-1958 Frederiksberg C,

Denmark.

Objectives: The aims of the study were to identify

unique biomarkers after a high dietary fiber

exposure and to search for early biochemical

changes in plasma metabolites related to this

exposure. Method: In a randomized cross-over five

week intervention study, 25 subjects were given a

high fiber diet (HF) and a low fiber diet (LF). Dietary

fibers from rye bran, oat bran and sugar beet fiber

was added to the food products in the HF diet.

Fasting plasma samples were collected and

separated by an UPLC system followed by high mass

resolution and accuracy QTOF-MS detection in

positive and negative electrospray ionization modes.

Raw QTOF-MS data were aligned and normalised in

MarkerLynx (Waters, Milford, MA, USA) and

exported to Excel to find discriminating markers

between diets. Identification of these metabolites

included library search in Human Metabolome

DataBase, Metlin and ChemSpider with verification

using chemical authentic standards combined with

mass spectrometry fragmentation patterns. Results:

Analyses of the metabolome in fasting plasma, using

QTOF-MS in positive and negative mode, gave 25

and 33 features, respectively, that were significantly

different after the HF compared to the LF diet

(p<0.01, q<0.25). Several features were overlapping

between positive and negative mode, which

strengthen the evidence that this is important

markers for the HF diet. After re-analysis of plasma

samples by MSE and MSMS fragmentation of the

significant masses, a number of glucuronide


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conjugates were observed. This observation was

confirmed after hydrolysis of plasma samples with

beta-glucuronidase. Some of the masses have been

tentatively identified and are reflecting part of the

endogenous biochemical response to a high intake

of dietary fiber from rye bran, oat bran and sugar

beet fiber.

POSTER 3

DAIRY PROTEINS’ EFFECT ON METABOLISM IN

OBESE NON-DIABETICS

Jan Stanstrup(1), Daniela Rago(1), Jens Holmer-

Jensen(2), Kjeld Hermansen(2), Lars O. Dragsted(1)

1. Department of Human Nutrition, Faculty of Life

Sciences, University of Copenhagen, Frederiksberg C,

Denmark. 2. Department of Endocrinology and

Metabolism MEA, Aarhus University Hospital, Aarhus,

Denmark.

Background Protein has been demonstrated to play

a prominent role in weight loss [1,2] although their

mechanism of action is so far unknown. Whey

proteins have received particular attention since

they have superior effect on appetite control

compared to other proteins [3]. However, the role

of individual whey proteins, sub-fractions or

individual peptides remains unclear. The aim of this

study is to investigate the metabolic fate of whey

proteins at a molecular level by analysing

postprandial plasma samples and identify protein

specific markers. Method A randomized single-

blinded intervention study with crossover design

was conducted. Eleven obese non-diabetic subjects

ingested, on four different days, a high fat meal

containing 80 g of fat, 45 g of carbohydrate and 45 g

of protein. The protein source was either Î±-

lactalbumin, whey isolate, whey hydrolysate or

caseinoglycomacropeptide. Blood samples were

drawn at five time points during the 8-h

postprandial period. UPLC-MS analysis was

conducted and peaks for the resulting 220 LC-MS

profiles were aligned and quantified using

MarkerLynx (Waters). After data reduction the

remaining 597 mass features were analyzed using a

mixed-linear model with protein source and time as

fixed effects and subject as random effect followed

by t-tests between individual meals and individual

time points. Significant difference in the mixed-

linear model was determined by applying a

Bonferroni corrected p-value cutoff level. A Matlab

function was created to automatically group mass

features originating from the same compound

based on similarity in retention time and correlation

across samples. About 40 % of the significantly

different features (between meals or time points)

could be grouped by this algorithm. An in-house LC-

MS database was used to aid identification of

features. Results The statistical analysis revealed

that 28 features had different levels between

protein sources and 106 features had different

levels between time points. The features with

different levels between meals were dominated by

mass fragments from the three naturally occurring

aromatic amino acids: phenylalanine, tryptophan

and tyrosine. The features having different levels

between time points included a greater variety of

compounds among these lysophosphatidylcholines

involved in postprandial lipaemia. Conclusion This

study shows that a number of amino acids are

present at different levels following ingestion of

different whey-derived proteins and concomitantly

illustrates the use of automated methods for more

rapid identification of mass features. Previous

studies have been unable to measure a difference in

total content of amino acids in blood following

ingestion of native whey protein, hydrolyzed whey

protein and hydrolyzed casein [4]. The use of this

untargeted approach enables the detection of

changes in the plasma levels of individual amino

acids. These findings may possess the potential to

improve our understanding of proteinsâ€™ role in

weight loss.

References: 1. Larsen TM, Dalskov S-M, van Baak M, Jebb SA, Papadaki

A, Pfeiffer AFH, et al. Diets with high or low protein content and

glycemic index for weight-loss maintenance. N. Engl. J. Med. 2010 Nov

25;363(22):2102-2113. 2. Skov AR, Toubro S, RÃ¸nn B, Holm L, Astrup A.

Randomized trial on protein vs carbohydrate in ad libitum fat reduced

diet for the treatment of obesity. Int. J. Obes. Relat. Metab. Disord.

1999 May;23(5):528-536. 3. Luhovyy BL, Akhavan T, Anderson GH.

Whey Proteins in the Regulation of Food Intake and Satiety. J. Am. Coll.


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Nutr. 2007 Dec 1;26(6):704S-712. 4. Calbet JAL, Holst JJ. Gastric

emptying, gastric secretion and enterogastrone response after

administration of milk proteins or their peptide hydrolysates in humans.

Eur. J. Nutr. 2004 Jun;43(3):127-139.

POSTER 4

INVESTIGATION OF TRANS FATTY ACID INTAKE

WITH UNTARGETED LIQUID CHROMATOGRAPHY

MASS SPECTROMETRY (LC-MS) BASED

METABOLOMICS

Gözde Gürdeniz, Daniela Rago, Nathalie Tommerup

Bendsen, Arne Astrup, Rasmus Bro and Lars O.

Dragsted

Department of Human Nutrition and Faculty of Life

Sciences, University of Copenhagen, Rolighedsvej 30,

1958, Frederiksberg C, Denmark

The association of industrial trans fatty acid intake

(TFA) with increased risk of cardiovascular disease

and/or type 2 diabetes has received considerable

attention over many years. In many of the studies

plasma lipoproteins levels were increased with a

higher TFA intake and it has been demonstrated

that total cholesterol (TC) to high-density

lipoprotein cholesterol (HDL-C) in the blood

increases with the TFA intake. Untargeted

metabolomics in nutritional studies offers the

opportunity to have a broader picture of

biochemical variation with respect to a specific diet

intake and may lead to identification of novel

biomarkers and/or reveal which pathways have

been affected. We have therefore applied an

untargeted liquid chromatography mass

spectrometry (LC-MS) based metabolomics

approach for the investigation of metabolite

patterns in relation to TFA intake. The data is

obtained from a 8-week double-blind, parallel

dietary intervention study. A total of 52 healthy

overweight postmenopausal women were

randomized to receive either partially hydrogenated

soybean oil providing 15.7 g day-1 of TFA or a

control oil with mainly oleic and palmitic acid. The

plasma samples were analyzed with liquid

chromatography quadrupole-time-of-flight mass

spectrometry (LC-QTOF). The raw data was

processed by MZmine and analyzed by multivariate

data analysis methods (PCA and PLS-DA). The two

groups could be separated by PCA and further

analysis by PLS-DA revealed an increased amount of

long-chain unsaturated phosphatidylcholines in the

TFA group. We are further investigating the possible

mobilization of long-chain PCs from the plasma

membranes by TFA.

POSTER 5

TIME-OF-DAY VARIATION IN HUMAN PLASMA

METABOLITES USING LIQUID CHROMATOGRAPHY-

MASS SPECTROMETRY (LC-MS)

Florence Raynaud(1), Joo Ern Ang(1), Anuska

Mann(2), Simone Mäntele(2), Danni Otway(2),

Jonathan Johnston(2), Victoria Revel(2), Alfred

Thumser(2), Debra J. Skene(2)

1. Cancer Research UK Cancer Therapeutics Unit, The

Institute of Cancer Research, Sutton, SM2 5NG, UK

2. Chronobiology, Faculty of Health and Medical Sciences,

University of Surrey, Guildford, GU2 7XH, UK

Background: The definition of plasma metabolites

that do and do not exhibit 24 h rhythms will provide

an essential baseline and valuable resource for all

future metabolomic studies in humans. This

knowledge will also be critical in guiding the proper

design and interpretation of biomarker and

therapeutic studies. In this project, we characterised

the 24 h variation in the human metabolome using

liquid chromatography-mass spectrometry (LC-MS).

Proof of principle, pilot data are presented here.

Methods: Eight lean, healthy men, with a mean age

of 53.8 years (SEM 2.1) followed a strict sleep-wake

and dietary regime for 1 week prior to the

laboratory study. During the 25 h laboratory

sampling period, these participants were kept under

controlled light-dark conditions, semi-recumbent

posture and fed hourly isocaloric drinks (Fortisip)

during the wake period (07:00-23:00 h), as per

previously published conditions [1]. Plasma was

collected hourly and stored at -80ï‚°C. Samples from

selected time points (07:00 h, 10:00 h, 16:00 h,

22:00 h, 04:00 h and 07:00 h (day 2)) were


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subsequently prepared using methanol/ethanol-

liquid phase extraction at the ICR, prior to

independent analysis at both the ICR and Surrey

using identical analytical conditions of reverse phase

LC coupled to Waters Micromass UPLC-QTOF

Premier system. Data alignment, peak detection,

quantification of features (peak heights) and

modelling of discrimination between time-points

were as previously described [2]. Cosinor analysis by

the method of least squares (period of 24 h) was

used to derive estimates of amplitude, acrophase

time, mesor, rhythm and p-value. Thresholds for a

good fit were rhythm â‰¥ 0.7 and p < 0.05 [3].

Results: The variability of endogenous metabolites

in pooled plasma samples (including carnitine,

creatine and hydrocortisone) was less than 10% at

both study sites (ICR and Surrey). A total of 1069

metabolite features were detected; of these, 46

metabolite features (4.3%) demonstrated significant

time-of-day rhythmicity (significant fit to cosine

curve). For example, the metabolite, m/z 480.31 Da

with a putative identitification of a

phosphoethanolamine, had a rhythmicity > 0.9 and

p < 0.05 in the cosinor analysis while the intra-run

coefficient of variation of this metabolite feature

within the pooled plasma samples was 2.2%.

Conclusions: These preliminary results provide clear

evidence that, under strictly controlled laboratory

conditions, certain metabolites in human plasma

exhibit significant time-of-day variation which

exceed the analytical variation in the metabolomic

analysis. Future LC-MS analysis will provide a

detailed characterisation of 24 h rhythms in the

human metabolome. Funded by Diabetes-UK (grant

08/0003607) and BBSRC (grant BB/I019405/1).

References: [1] Otway et al. Diabetes 2011; 60: 1577-81. [2] Pandher et

al. J Chromatogr B 2009; 877: 1352-8. [3] Nelson et al. Chronobiologia

1979; 6: 305-23.

POSTER 6

METABOLIC PROFILING BY SERUM NMR

SPECTROSCOPY IMPROVES PREDICTION OF

SUBCLINICAL ATHEROSCLEROSIS

Peter Würtz(1), Juho Raiko(3), Costan G.

Magnussen(3,4), Pasi Soininen(1,5), Antti J. Kangas(1),

Tuulia Tynkkynen(1,5), Russell Thomson(4), Reino

Laatikainen(5), Markku J. Savolainen(1), Antti Jula(6),

Jorma S. Viikari(7), Mika Kähönen(8), Terho Lehtimäki(8),

Markus Juonala(3,6), Mika Ala-Korpela(1,5), and Olli T.

Raitakari(3,7)

1. Computational Medicine, University of Oulu, Finland;

2. Institute for Molecular Medicine, University of Helsinki,

Finland; 3. Cardiovascular Research Centre, University of

Turku, Finland; 4. Menzies Research Institute, University

of Tasmania, Hobart, Australia; 5. NMR Metabonomics

Laboratory, University of Eastern Finland, Finland; 6.

National Institute for Health and Welfare, Finland; 7.

Turku University Hospital, Finland; 8. Tampere University

Hospital, Finland

Background: Comprehensive metabolic profiling

holds promise for cardiovascular risk assessment.

We evaluated whether high-throughput profiling

improves prediction of subclinical atherosclerosis as

compared to conventional lipid testing in young

adults. Methods: Serum lipids, lipoprotein

subclasses, and small molecule metabolites were

quantified by NMR spectroscopy for 1570

individuals aged 24-39 years in the population-

based Cardiovascular Risk in Young Finns Study.

Carotid intima-media thickness, a marker of

subclinical atherosclerosis, was measured in 2001

and 2007. Baseline conventional risk factors and

circulating metabolites were used to predict 6-year

incidence of high intima-media thickness (â‰¥90th

percentile) or plaque. Results: The best prediction of

high intima-media thickness was achieved when

NMR-based lipoprotein lipids, docosahexaenoic acid

and tyrosine replaced conventional LDL-C and HDL-C

in models including established risk factors. This

model improved risk stratification beyond

established risk factors alone; area under the ROC

curve 0.77 vs. 0.74, P=0.03; net reclassification

improvement 15%, P=0.003. Tyrosine was


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associated with incident high intima-media

thickness. independent of lipid measures (OR: 1.34;

95% CI: 1.11-1.62; P=0.002) and validated in an

independent population. Conclusions: Metabolic

profiling improved risk stratification for subclinical

atherosclerosis over and above conventional lipids,

and could be useful for biomarker discovery and

early cardiovascular risk assessment.

POSTER 7

BUILDING AN ANNOTATION TOOL DEDICATED TO

PHYTOCHEMICALS AND THEIR METABOLITES IN

HUMANS.

Franck Giacomoni, Daniel Cesaire, Mercedes

Quintana, Noura Meklat, Estelle Pujos-Guillot,

Claudine Manach

INRA, UMR 1019, Human Nutrition Unit, Clermont-

Ferrand, France

The "Food metabolome" comprises all the

metabolites present in biological fluids that are

directly derived from the digestion of food. A large

part of the food metabolome consists of

phytochemical metabolites (polyphenols, terpenes,

alkaloids, etc ...) produced by intestinal and hepatic

enzymes and by the microbiota after plant food

ingestion. Analysis of the food metabolome is thus

likely to provide a wealth of information on

individual exposure to phytomicronutriments

metabolites after consumption of various foods or

diets. It may help identify new phytochemical

metabolites, identify new biomarkers of intake, as

well as study correlations between complex

phytochemical exposure and biological effects

observed in intervention studies, possibly leading to

identification of new bioactives. Our objective is to

develop a database on phytochemical metabolites

to facilitate the annotation of the food metabolome.

Part of the approach is an inventory of known

metabolites described in the literature for the most

important dietary phytochemicals. In parallel, an in

silico prediction of the metabolism of each

compound is performed from the native chemical

structure using the expert system Meteor (Lhasa

Ltd, Leeds). Known and predicted metabolites are

then annotated via a dedicated pipeline of

automatic annotation. Physico-chemical data are

added, as well as experimental data acquired with

high resolution mass spectrometry on available

standards, and predicted CID fragmentation using

the MassFrontier6.0 software (Thermo Scientific).

The implementation of this relational database will

use the technology of MySQL. The processing chains

will be developed in Perl. A web interface will be

developed to make the database in open access.

The developed database compiles information on

dietary phytochemicals, their physicochemical

properties, spectral data, and known or predicted

metabolism in humans. It will be the first public

database which gathers knowledge about the

metabolism of phytochemicals and which is suitable

for use in metabolomics studies. Funding ANR

(PhenoMeNEpALIA-2010-007-01)

POSTER 8

COMMON METABOLITES RESPONDING TO

ANTIHYTENSIVE MEDICATION IN YOUNG-ONSET

HYPERTENSION PATIENTS

Wen-Harn Pan(1), Chia-Min Chung(1,2),Ke-Shyuan

Lynn(3), Hsin-Chou Yang(4), Yu-Jen Liang4, Ming-Shi

Shiao(5), Mei-Ling Cheng(6)

1. Division of Preventive Medicine and Health

Service Research, National Health Research

Institutes, Miaoli, Taiwan 2. Institute of Biomedical

Sciences, Academia Sinica, Taipei, Taiwan 3.

Institute of Information Sciences, Academia Sinica,

Taipei, Taiwan 4. Institute of Statistical Science,

Academia Sinica, Taipei, Taiwan 5. Department of

Biomedical Sciences, College of Medicine, Chang

Gung University, Tao-Yuan, Taiwan 6. Graduate

Institute of Medical Biotechnology, College of

Medicine, Chang Gung University, Tao-Yuan, Taiwan

Hypertension is an important public health issue not

only in Taiwan, but also in most parts of the world.

One thirds of Taiwanese adult males and one fifths


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of adult females are hypertensive in Taiwan. In

comparative metabolomics, although a global

difference may be observed between patients and

healthy controls, it is likely that difficulty lies at how

to distinguish upstream causal agents and

downstream metabolites. Noises introduced by

daily variations from foods and from varied health

conditions may hinder discoveries. Therefore, it is

crucial to compare metabolomics profiles with and

without antihypertensive medications to find shared

and unique changes of different medications in

order to pinpoint major pathways of blood pressure

control. METHODS: We have collected serum

samples from around 250 hypertensive patients.

Phamacometabolomics study comparing

metabolomes with and without antihypertensive

treatments with 4 kinds of anti-hypertensive

medications: (thiazides, angiotensive converting

enzyme inhibitor, angiotensin receptor blocker, and

calcium channel blockers) were carried out. We had

five groups of patients including 50 subjects in each

medication group and one without medication. A

group of age- and sex matched normotensive

people was also included. Metabolic profiles of

plasma from patients with different category of

antihypertensives, were investigated using an

untargeted approach with LC-MS fingerprinting of

serum coupled with analysis of variance (ANOVA)

using the GLM procedure of the Statistical Analysis

System(SAS version 9.2) Results We found over 72

metabolites to be significantly associated between

with and without the antihypertensive treatments

(p value <10-6). Among them, concentrations of two

metabolites decreased in all treatment groups (p

value <10-10). This metabolite was also lower in

concentration in the 50 normotensive controls.

CONCLUSIONS: We demonstrated that a

metabolomics approach is effective in discovering

metabolites involved in blood pressure related

mechanism. Further analysis is needed to determine

the metabolite structure and to verify it through

pre- and post- medication comparison.

POSTER 9

HUMAN ISLET METABOLIC PROFILES IN

PROGRESSION TO TYPE 1 DIABETES

Erno Lindfors(1), Ismo Mattila (1) Sandra Castillo (1)

Teemu Smurra (2) Petri Ylipaasto (2) Tuulikki

Seppänen-Laakso (1) Tuulia Hyötyläinen (1) Matej

Orešič (1) Merja Roivainen (2)

(1) VTT Technical Research Centre of Finland, Espoo,

Finland (2) National Institute for Health and Welfare,

Helsinki, Finland.

Type 1 Diabetes (T1D) results from destruction of

pancreatic beta cells in islets. This happens years

before the onset of the disease, and is characterized

by the appearance of autoantibodies in circulation

[1]. T1D incidence has increased rapidly worldwide

during the last few years, which can only partially be

explained by genetic factors. Instead, environmental

factors seem to have important role in this disease,

essentially infections caused by human

enteroviruses (HEVs) have been shown to have

associations with the autoantibody appearance and

beta cell destruction [2-4]. We have recently

performed human islet experiments from antibody

positive and negative donors infected in vitro with

HEV Coxsackie B5 virus (CVB-5-virus), and from each

donor we had a non-infected islet as control. From

each islet we took 3 replicates at 3 and 24 hours

after the start of infection. We took all samples

separately from primary human islets, culture

medium and MIN6 cell lines, and analyzed them by

UPLC-MS lipidomics and GCxGC-TOFMS techniques.

In order to study how virus infection and antibody

effects are associated with changes in

concentrations of lipids and metabolites, we

performed a variance analysis method called

(ANOVA) on pre-processed data obtained from the

samples. As a preliminary result, we found large

antibody and virus related changes. Most

interestingly, the virus infection seems to lead to

diminished ether lipids in the medium but not in the

primary islets, which may be a sign that the

infection is detectable only in circulation. Also,

interestingly ether lipids were diminished in children


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who later progressed to T1D in our previous case

study[1].

References:

[1] Orešič et al., Dysregulation of lipid and amino acid metabolism

precedes islet autoimmunity in children who later progress to type 1

diabetes, J. Exp. Med. 205(13), 2975-2984 (2008). [2] Hyöty et al., A

prospective study of the role of coxsackie B and other enterovirus

infections in the pathogenesis of IDDM. Childhood Diabetes in Finland

(DiMe) Study Group, Diabetes, 44(6):652-657 (1995). [3] Hiltunen et al.,

Islet Cell Antibody Seroconversion in Children Is Temporally Associated

with Enterovirus Infections, Journal of Infectious Diseases, 175, (3):554-

560 (1997). [4] Ylipaasto et al., Enterovirus infection in human

pancreatic islet cells, islet tropism in vivo and receptor involvement in

cultured islet beta cells, Diabetologia, 47:225–239 (2004).

POSTER 10

A NMR METABONOMIC APPROACH TO EXPLORE

EARLY BIOMARKERS OF PANCREATIC CANCER IN

THE EUROPEAN PROSPECTIVE INVESTIGATION

INTO CANCER AND NUTRITION (EPIC).

Anne Fages (1), Clément Pontoizeau (1), Pietro

Ferrari (2), Veronika Fedirkov (2) Pierre Hainaut (2),

Bénédicte Elena-Herrmann (1) and Mazda Jenab (2)

(on behalf of the EPIC group).

1 Université de Lyon (CNRS/ENS Lyon/UCB Lyon 1),

Centre de RMN à très hauts champs, 5 rue de la Doua,

69100 Villeurbanne, France. 2 International Agency for

Research in Cancer (IARC-WHO), 150 Cours Albert

Thomas, 69372 Lyon CEDEX 08, France.

Pancreatic cancer has one of the highest mortality

rates worldwide, with a poor prognosis and five-

year survival rate below 5%. It is aggressive and

characterised by rapid progression, propensity to

metastasize and resistance to treatment. Thus,

major challenges are pancreatic cancer early

detection/diagnosis and prevention. The purpose of

this NMR metabonomic study is to prospectively

investigate the aetiology of pancreatic cancer in

relation to diet and lifestyle, within the framework

of the European Prospective Investigation into

Cancer and Nutrition (EPIC). In the EPIC cohort

(over 520,000 subjects enrolled between 1992 and

2000 in 23 centres from 10 European countries),

more than 500 individuals developed pancreatic

cancer. For each subject, blood samples were

collected and individual dietary and lifestyle habits

were recorded through questionnaires and cancer

onset was ascertained through cancer registries or

active follow-up. Analysis of this data led to the

identification of pancreatic cancer risk factors such

as smoking or obesity. We report here the first

high-field NMR metabonomic study based on serum

samples from an EPIC pancreatic case-control study.

Serum samples from 317 EPIC pancreatic cancer

prospective cases and 317 controls (matched on

gender, age, centres) were analyzed by high-field 1H

NMR spectroscopy. Our main objective is to detect

early predictive biomarkers of pancreatic cancer by

following a metabonomic approach and to detect

biomarkers of dietary or lifestyle patterns. The study

is also suitable for identifying biomarkers related to

risk factors exposure, which if successful could have

a relevant potential impact in the understanding of

pancreatic cancer aetiology. We present here the

NMR metabonomic study conducted on the 634

EPIC samples at high-field. High-resolution one-

dimensional 1H NMR (NOESY and CPMG) spectral

profiles for the individual EPIC serum samples were

recorded at 800MHz. Additional 2D 1H-1H (Jres,

TOCSY) and 1H-13C (HSQC) data were recorded at

1GHz. Detecting cancer onset or diet-related

metabolic signature in this large-scale study would

be very challenging without identifying first the

factors that can impact the data without a priori

information on the disease indicator. We present

the first results of the metabonomic analysis of the

case-control study where the identification of the

main sources of systematic variation has been

investigated by multivariate analysis. Identification

of the detected metabolites from EPIC serum

samples will also be presented, while further

analysis of the data is currently in progress.


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POSTER 11

PRELIMINARY TITLE: THE EFFECT OF CHEESE AND

BUTTER INTAKE WITH EQUAL FAT CONTENT ON

SERUM METABOLOMICS IN ADULTS.

Julie Hjerpsted, Tine Tholstrup and Lars Ove

Dragsted

Department of Human Nutrition, Faculty of Life Sciences,

University of Copenhagen, 1958 Frederiksberg, Denmark

Background: Despite the high content of saturated

fat, cheese seems not to increase cholesterol

concentrations when compared to butter of equal

fat content. The physiological mechanism behind

this â€œneutralâ€• effect of cheese on cholesterol

concentrations is not known. The aim of the study is

to investigate how cheese and butter intake affect

serum metabolomics in adults. Method: The study

was part of a controlled randomized 2x6 weeks

cross-over dietary intervention study with a

fourteen days run-in period on habitual diet. The

study included 49 men and women who daily

replaced part of their habitual dietary fat intake

with approximately 13 energy percent (E%) from

cheese or butter. No other dairy products were

allowed. Cholesterol was determined in all

participants. Twenty-three of these 49 men and

women agreed to hand in serum samples for

metabolomic analyses. Fasting serum samples were

taken in duplicate at 0, 3 and 6 weeks of

intervention and analyzed using ultra performance

liquid chromatography coupled to electrospray

ionization time-of-flight mass spectrometry in

positive ionization mode. Data were preprocessed in

MZmine. A mixed linear univariate analysis, paired t-

tests and PCA were performed using MATLAB (The

Mathworks, Inc., MA, USA). Only features found

significantly different at both 3 and 6 weeks were

regarded valid. PCA was performed on features

found significant by univariate analyses after

autoscaling. Results: An isocaloric diet with cheese

was found to lower cholesterol compared with

butter. PCA of raw serum data, showed no obvious

separation of the two treatments. However, a

complete separation could be observed when

including only compounds found significantly

changed at both time points after intervention. A

total of 16 metabolites were found different

between treatments at both 3 and 6 weeks. Among

these, some long-chained unsaturated

phosphatidylcholines were decreased with cheese

intake compared to butter intake and also betaine

decreased with cheese intake. Conclusion: We

conclude that long-chained phosphatidylcholines

seems to be unique markers being decreased with

cheese intake compared to butter intake. As

phosphatidylcholines are a part of lipoproteins it

supports the difference in cholesterol

concentrations between cheese and butter intake of

equal fat content. A possible relation between the

metabolism of phosphatidylcholines and betaine

will be explored.

POSTER 12

APPLICATION OF A METABOLOMIC APPROACH TO

FIND BIOMARKERS OF PLANT FOOD INTAKE IN THE

SU.VI.MAX2 COHORT

Claudine Manach(1), E. Pujos-Guillot(1), J.F.

Martin(1), M. Touvier(3), B. Lyan(1), M. Quintana(1),

F. Giacomoni(1), N. Meklat(1), A. Scalbert(2), S.

Hercberg(3), P. Galan(3) and B. Comte(1).

1. INRA, UMR 1019, Human Nutrition Unit, Clermont-

Ferrand, France; 2. Nutrition and Metabolism Section,

International Agency for Research on Cancer, Lyon,

France; 3. UREN, U1125/INRA/INSERM/CNAM/UP13,

SMBH, Bobigny, France.

Introduction: Nutritional epidemiology needs

specific and robust biomarkers for dietary

assessment, covering a large range of foods and

dietary patterns. Metabolomics has emerged as a

promising approach to discover such biomarkers. In

controlled intervention studies, comparison of

plasma or urine metabolomes of subjects before

and after consumption of selected foods has led to

the identification of candidate biomarkers of intake.

The objective of this work is to apply a metabolomic

approach directly on samples from a cohort study.


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Methods: Two groups of SU.VI.MAX2 subjects were

selected according to their usual intake of Citrus

assessed by a FFQ and six 24h recalls between 1994

and 2009. Low and high consumers (2x40 subjects)

declared a mean Citrus intake below 1.5 g/d and

above 25g/d, respectively. Spot urines were

analyzed with high resolution mass spectrometry

(UPLC-ESI+-QTof). Identification of discriminant

markers revealed by multivariate statistical analyses

was performed with ultra high resolution LTQ-

Orbitrap analysis, query of online and in-house

databases, and laboratory expertise on

phytochemicals and their metabolites in humans.

Results: The urine metabolomes from the two

groups were clearly discriminated. Among the 868

ions detected, 14 were selected as key discriminant

markers on the basis of their contribution in the PLS

model, their ANOVA P-value, and their intensity

distribution across the dataset. Four of the most

discriminant markers were unambiguously

identified using Orbitrap analysis and comparison

with pure standards: proline betaine, hesperetin 3’-

glucuronide, naringenin 7-glucuronide, and

naringenin 4’-glucuronide. These identifications

support the validity of the approach as the

compounds were expected markers of Citrus intake.

Other markers have been tentatively identified as

secondary plant metabolites or their digestion

products. Interestingly, the most discriminant

markers were already found significant in controlled

intervention studies with Citrus, but were frequently

not among the most important markers in these

previous studies. Conclusion: This study confirmed

the value of using a metabolomic approach to

identify new biomarkers of intake. It showed for the

first time that application of metabolomics directly

on a cohort study rather than on samples from

controlled intervention studies may be

advantageous with respect to the lower cost and

higher robustness of biomarkers of intake. The

project PhenoMeNEp will use the same approach in

the SU.VI.MAX2 cohort to search biomarkers of

intake for diets rich in fruit and vegetables as well as

for a dozen of selected plant foods. Fundings: INRA

AlimH, ANR PhenoMeNEp ALIA2010.

POSTER 13

1H NMR-BASED METABOLOMICS REVEALS A

SERUM METABOLIC SIGNATURE OF ADVANCED

METASTATIC BREAST CANCER

Elodie Jobard (1,2), Clément Pontoizeau (1),

Benjamin Blaise (1), Lyndon Emsley (1), Thomas

Bachelot (2), Bénédicte Elena-Herrmann (1) and

Olivier Trédan (2).

1. Université de Lyon, CNRS/ENS Lyon/UCB-Lyon-1,

Centre de RMN à Très Hauts Champs, Villeurbanne,

France 2. Université de Lyon, Département

d’oncologie médicale, Centre Léon Bérard, Lyon,

France

Breast cancer (BC) is one the most common cancers

among women worldwide. BC displays a high

heterogeneity from histology to prognosis,

metastatic evolution and treatment responses.

Deciphering this heterogeneity is a major challenge,

aiming at a comprehensive cancer characterization

for risk stratification, therapeutic target

identification and appropriate treatment selection.

We report here a 1H-NMR-based metabolomic study

aiming at deciphering metabolic serum changes

associated with advanced metastatic breast cancer

by comparison to the localized disease. This work

presents a metabolic signature derived from serum

samples discriminating patients with metastatic

breast cancer from the ones with localized tumors.

52 serum samples were collected from 23 female

patients suffering from early breast cancer (EBC)

and 29 female patients suffering from metastatic

breast cancer (MBC). We first show a comparison of

metabolic profiles obtained by high-field 1H-NMR

spectroscopy (800 MHz) for patients with either EBC

or MBC. NMR data were exploited using supervised

multivariate statistical analyses (O-PLS) and revealed

a metabolic signature discriminating EBC from MBC

patients. The obtained statistical model was further

validated by exploiting additional NMR data from a

second, independent, cohort of 32 female patients.

This validation protocol demonstrated a sensibility


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of 71% and a specificity of 89%. The obtained

metabolic fingerprint discriminating EBC and MBC

subjects was further interpreted using statistical

recoupling of variables associated to significance

testing protocols (1). 10 statistically significant

metabolites (biomarkers) were disclosed by this

procedure. Meanwhile, available metadata for the

enrolled patients (demography, medical history,

treatments, etc..) was inspected in order to

eliminate any possible bias in this analysis.

This study opens perspectives for further

applications of NMR metabolomics to diagnosis,

prognosis and management of cancer patients.

Reference: 1. Blaise, B.J. et al. Anal. Chem. 81(15), 6242-6251 (2009).

POSTER 14

PROFILING AND QUANTITATION OF

METABOLOMIC “SIGNATURES” FOR BREAST

CANCER CELL PROGRESSION

Simon Cubbon(1), Henry Shion (1); Irwin Kurland(3);

Sumanta Goswami(4); Haitao Luo(3); Evan

Bernier(2); David Kusin(4); Bhavapriya

Vaitheesvaran(3); Alan Millar(1)

1. Waters Corp., Milford , MA; 2. Waters Corporation,

Beverly, MA; 3. Albert Einstein College of Medicine of

Yeshiva Un, Bronx, NY; 4Yeshiva University, New York, NY

Metabolic reprogramming is required both during

the initial breast cancer transformation process

(primary tumor) and during the acquisition of

metastatic potential (metastases). The initial

process includes altered glycolysis, pentose

phosphate pathway (PPP), and fatty acid synthesis,

as well as decreased GSH/GSSG redox pool. While

the second step is correlated with the gain of the

general metastatic ability and includes further

changes in glycolysis and tricarboxylic acid cycle

(TCA cycle), further depletion of the glutathione

species, and increased nucleotides. Staging of the

metabolic reprogramming using metabolomics,

could pinpoint metabolic processes essential for

transformation and invasiveness that could yield

biomarkers and new directions for therapeutics. We

present here a study of combining targeted and

untargeted approach for cancer biomarkers

analysis. Methods 2 rodent breast cancer cell lines

MTLn3 (highly metastatic) and MTC (poorly

metastatic) used were cultured in Eagle's minimal

essential medium supplemented with 5% Fetal

bovine serum (Invitrogen). Experiments were

performed using a UPLC coupled either with a triple

quadrupole (Xevo TQS) for targeted (± MRM)

analysis or a hybrid quadrupole Time-of-Flight mass

spectrometer (Synapt G2 HDMS) for untargeted

(±MSE) analysis. The column used was a a Bridged

Ethyl Hybrid (BEH) column 2.1 X 100 mm, 1.7 µm

kept at 40 ˚C. Mobile phases used were for A, Water

with 0.1% FA and for B, Acetonitrile with 0.1% FA. A

linear gradient of 1% B – 50 % B in 8 mins was used

for the study. Preliminary Data Targeted analysis

was used to survey known markers of cancer

aggressiveness. Experiment data shown clear

biomarkers for the “warburg effect” with high

cytosolic NADH and high glycolysis. For glycolysis

process, markers for increased flux from pyruvate to

the TCA cycle and for amno acid synthesis, which

are necessary for cell growth, and for shuttles

carrying NADH in for ATP synthesis, along with high

AMP, showing that energy generation can’t keep up

with cell growth well when the cancer cell is

aggressive. For untargeted analysis, markers from

MarkerLynx statistic analysis are validated, in part,

by identifying hits in pathways complementary to

those found in targeted analysis, and builds belief in

new untargeted hits found. For instance, untargeted

analysis indicated high AMP, high PEP along with

high cis-aconitate in aggressive cells. AMP was

identified from targeted analysis, cis-aconitate

supports targeted analysis finding for increased flux

into the TCA cycle, and PEP for increased glycolysis.

Markers / carriers (malate/aspartate shuttle) for

high cytosolic NADH from targeted analysis are

complementary to untargeted finding of high

Nicotinamide-D-ribonucleotide, a step in NAD

synthesis degradation products of amino acids

found to be elevated by targeted analysis. Targeted

analysis found high levels of aspartate, isoleucine,

tyrosine and arginine, among others. Untargeted


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analysis showed markers for amino acid degradation

with high 2-oxo-5-aminovalerate, a breakdown

product of arginine; 1,4 dihydroxy-2-napthoate, a

breakdown product of tyrosine; alpha-

hydroxyisovalerate, a marker for branched chain

amino acid (isoleucine) breakdown and homoserine,

a breakdown product of aspartate. New pathways

discovered by untargeted analysis will be also

presented in this study. In summary, we found that

targeted and untargeted approaches are

complementary to each other in breast cancer

aggression study.

POSTER 15

METABONOMIC PROFILING OF CANCER CELLS BY

QUANTITATIVE 1H INADEQUATE 2D NMR

Estelle Martineau, Illa Tea, Patrick Giraudeau, Serge

Akoka

CEISAM, UniversitÃ© de Nantes,BP 92208 2 rue de

la HoussiniÃ¨re, 44322, Nantes Cedex 3, France

Quantitative analysis of metabolic mixtures by 1D 1H

NMR is a limited tool for precise quantification of

biomarkers because of strong peak overlap. 2D NMR

presents a high potential to unambiguously measure

a large number of metabolite contributions.

Recently, a 2D 1H INADEQUATE NMR method has

been developed for a fast determination of

metabolite concentrations in a standard metabolite

mixture. 1H INADEQUATE 2D spectra are obtained in

7 minutes with a repeatability better than 2%. This

protocol has been evaluated in terms of precision

and linearity on metabolite mixtures with

concentrations as small as 0.1 mM, forming thus a

promising tool for metabonomic studies. The

objective of this work is to evaluate the

potentialities of the 1H INADEQUATE 2D NMR

method for differentiating the concentrations of a

large number of metabolites from breast cancer cell

lines. Four breast cancer cell lines (MDA-MB-468,

MCF-7, ZR75-1 and SKBR3) are grown and quenched

with methanol. A methanol/chloroform/water

procedure extraction has been optimized to obtain a

maximum amount of metabolites. In order to

quantify intracellular metabolites from cells, a

standard mixture of 15 metabolites of different

concentrations is added to each extracted

metabolite sample. These samples are prepared in

triplicate. Five 1H INADEQUATE 2D spectra are

recorded to evaluate the repeatability of our

experiments. . A repeatability better than 5% is

obtained for the most of metabolites over the range

of concentration (0.15 mM-2 mM). Moreover,

establishment of calibration curves for each

metabolite underlined the good linearity of our

method and the possibility to determine

concentration of metabolites extracted from cancer

cells. These results highlight the potentialities of 2D 1H INADEQUATE NMR method to a precise

quantification of metabolites, differentiating cancer

cell lines, representing a promising tool to uncover

quantitative biomarkers.

POSTER 16

A 1H NMR APPROACH REVEALED SUBTLE

DIFFERENCES IN THE SERUM LIPID PROFILE OF

HEALTHY SUBJECTS AFTER A SHORT-TERM INTAKE

OF A HIGH-LYCOPENE TOMATO SAUCE

Isabel Bondia-Pons(1), Miguel Ángel Rodríguez(2),

Roger Mallol(2), Itziar Abete(1), Santiago Navas-

Carretero(1), Aurora Pérez-Cornago(1), Maria

Vinaixa(2), Xavier Correig(2), M. Ángeles Zulet(1), J.

Alfredo Martínez(1)

(1)Department of Food Science and Nutrition. Research

Building. University of Navarra. C/ Irunlarrea 1, 31008

Pamplona, Spain. (2) Metabolomics Platform, CIBER de

Diabetes y Enfermedades Metabólicas Asociadas

(CIBERDEM), IISPV, Universitat Rovira i Virgili, Avda.

Països Catalans 26, 43007 Tarragona, Spain.

There is still limited support concerning the in vivo

antioxidant potential of lycopene, the predominant

carotenoid in tomatoes. An 8 week-cross-over

nutritional intervention with two tomato sauces

differing in their (high- vs. normal-) lycopene

content in healthy subjects resulted in a significant

decrease in the subjects’ oxidized LDL after the high-

lycopene period (-9.3 ± 16.8%; p< 0.05). The aim of


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the present study was to characterize by 1H NMR

possible metabolic changes that accompanied the

observed oxidation of the LDL-cholesterol to better

understand how the nutritional intervention might

produce a beneficial effect in healthy subjects. The

1H-NMR approach was helpful to reveal few but

significant differences that were otherwise not

captured with the traditional biochemical analyses

in the subjects’ serum lipid profile after the intake of

both tomato sauces. The 1H NMR characterization of

the lipid serum profile revealed significant

differences for cholesterol (CHOL), phospholipids

(PL), triglycerides (TG), plasmalogens and several

fatty acids signals due to the nutritional

intervention. Total and free CHOL signals

significantly decreased after the high lycopene

sauce period in comparison to the increased signals

observed after the non-enriched tomato sauce

period. The same trend was observed for the total

PL and plasmalogen signals. TG signals were

significantly higher after the normal- than after the

high-lycopene sauce intervention. Oleic acid, linoleic

acid and omega-3 fatty acids signals increased after

both intervention periods, but significantly much

more after the intervention with normal- than with

high-lycopene sauce. Polyunsaturated fatty acid

(PUFA) and C20:4 n-6 (AA) + C20:5 n-3 (EPA) signals

significantly increased after the intervention period

with the tomato sauce with normal lycopene levels

while slightly decreased after the period with the

high-lycopene sauce. According to our results, we

speculate that the synergic antioxidant effect of

both plasmalogens (as endogenous antioxidant) and

high-lycopene levels coming from the nutritional

intervention (as exogenous antioxidant) might be

responsible for the protection during lipoprotein

oxidation.

POSTER 17

MASS SPECTROMETRY BASED INVESTIGATION OF

THE PHOSPHOLIPID CONTENT OF CELLS INFECTED

WITH THE OBLIGATE INTRACELLULAR PATHOGEN

CHLAMYDIA

Constanze Mueller(1), Agathe Subtil (2), Paul

Lazarow (2), Philippe Schmitt-Kopplin (1)

(1) Department of BioGeoChemistry and Analytics,

Helmholtz Zentrum München, München, Germany (2)

Department of Cell Biology and Infection, Institut Pasteur,

Paris, France

According to WHO, infections with Chlamydia

trachomatis are an enormous public health problem

worldwide. Common consequences are short- and

long-term health problems like urethritis, chronic

pain, ectopic pregnancy and infertility.

Unfortunately only little is known about the

influence of these intracellular growing bacteria on

human metabolism and there has been no detailed

analysis of phospholipid content with modern

techniques. In this study we investigated changes in

phospholipids that occur during the infection,

hopefully leading to a better understanding of

molecular mechanisms and new strategies for

diagnosis and therapy. A role of peroxisomes during

the Chlamydia infection was recently discovered by

Agathe Subtil’s group. Since peroxisomes are

involved in many aspects of cell metabolism, but

especially in lipid metabolism, they hypothesized

that Chlamydia might use peroxisomal activity to

make specific lipids (e.g. plasmalogens) or to modify

some host lipids. We now present a mass

spectrometry based approach to analyse the lipid

composition of the infected human host cell and the

possible contributions of peroxisomes. Human

fibroblasts and peroxisome deficient PEX19 cells

were infected for 24 and 48 hours with Chlamydia

trachomatis. The methanol extracts of the infected

and non-infected cells were analysed using a 12

Tesla Fourier Transform Ion Cyclotron Resonance

Mass Spectrometer (FT-ICR/MS). The differences in

lipid composition among the samples were

systematically investigated and the results were

confirmed by statistical analysis. The focus fell on 16

masses, which were specific for infected cells and

their elemental compositions suggested some

possible plasmalogen structures. For structure

elucidation we applied in-cell fragmentation (SORI)

in positive and negative electrospray mode. The


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combination of the data led to identification of the

most abundant isomers. To also elucidate the

structure of less abundant isomers the addition of a

separation step prior to MS or rather MS² was

indispensible. Applying ultra performance liquid

chromatography coupled to time-of-flight mass

spectrometry (UPLC-TOF-MS) confirmed most of the

candidates. Furthermore the separation of the

isomers prior to detection reduces suppression

effects and gives us the opportunity to do deeper

structure investigations.

POSTER 18

EFFECTS OF DIOXINS ON HEPG2 CELLS: AN

UNTARGETED METABOLOMICS STUDY

Ainhoa Ruiz Aracama, Ad Peijnenburg, Arjen

Lommen

(1)RIKILT-Institute of Food Safety, Wageningen, The

Netherlands. (2) Netherlands Toxicogenomics

Centre

There is an increased need to develop alternatives

to classical toxicity testing using animals. In vitro cell

systems, together with ‘omics techniques, represent

promising alternatives to those classical tests. Much

work has been done using transcriptomics and

proteomics. However, there are still not many

studies where metabolomics has been used to study

in vitro systems. The main goal of this work is to

study the usefulness of an untargeted metabolomics

approach in providing information on the toxicity of

a well known toxic model compound, TCDD, in an in

vitro test system such as HepG2 cells. In order to

determine robustness and reproducibility,

exposures were done using five biological replicates

and different passage numbers. After 48 h of

exposure, the metabolism was quenched and two

fractions were extracted from the cells: a polar

fraction (analyzed by means of 1H-NMR and UPLC-

TOF-MS) and an apolar fraction (analyzed by 1H-

NMR and GC-MS). All obtained data were

preprocessed and aligned using specialized in house

developed software. Resulting spreadsheets were

then analyzed in a non-targeted way using

multivariate analysis. Several metabolites were

detected to be significantly affected as a result of

the TCDD exposure in both polar and apolar

fractions and were identified. The changes in the

level of metabolites due to the exposure to TCDD

were interpreted with the help of what it is already

known for TCDD in literature.

POSTER 19

METABOLIC FINGERPRINTING OF HIGH-FAT

PLASMA SAMPLES PROCESSED BY

CENTRIFUGATION- AND FILTRATION-BASED

PROTEIN PRECIPITATION DELINEATES SIGNIFICANT

DIFFERENCES IN METABOLITE INFORMATION

COVERAGE

Thaer Barri(1), Jens Holmer-Jensen(2), Kjeld

Hermansen(2), and Lars O. Dragsted(1)


Sciences, University of Copenhagen,Rolighedsvej 30,

DK-1958 Frederiksberg, Denmark. 2. Department of

Endocrinology and Metabolism MEA, Aarhus

University Hospital, Tage-Hansens gade 2, DK-8000

Aarhus C, Denmark

Metabolomics and metabolic fingerprinting are

being extensively employed for improved

understanding of biological changes induced by

endogenous or exogenous factors. Blood serum or

plasma samples are often employed for

metabolomics studies. Protein precipitation by

adding organic solvent followed by centrifugation is

currently performed in most laboratories before LC-

MS analysis. However, the impact of fat content in

the plasma samples on metabolite recovery has not

previously been investigated. Consequently, we

have investigated whether plasma protein

precipitation (PPP) procedures influence the

recovery of plasma metabolites from high-fat

plasma samples. An optimized UPLC-QTOF-MS

metabolic fingerprinting approach and multivariate

modeling (PCA and OPLS-DA) were utilized for

finding characteristic metabolite changes induced by

two PPP procedures, centrifugation (cPPP) or

filtration (fPPP), both carried out in 96-well plates.


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We used samples collected after a 12-hour fasting

period and postprandial samples collected at 2 hrs

after a standardized high-fat meal in obese non-

diabetic subjects participated in a human dietary

intervention study. Remarkably and sometimes

uniquely, the fPPP, but not the cPPP approach,

recovered not only high molecular weight (HMW)

lipophilic metabolites, but also small molecular

weight (SMW) relatively polar metabolites.

Characteristic SMW markers of postprandial

samples were aromatic and branched-chain amino

acids, which were significantly elevated (p<0.001).

In contrast, some HMW lipophilic species e.g.

acylcarnitines were moderately and significantly

lower (p<0.001) in postprandial samples.

Lysophospholipids were largely unaffected. In

conclusion, the fPPP procedure is recommended for

processing high-fat plasma samples in untargeted

metabolomics and metabolic fingerprinting studies.

POSTER 20

METABOLIC SIGNATURES OF LUNG CANCER IN

BIOFLUIDS: AN NMR-BASED METABONOMICS

STUDY.

Joana Carrola(1), Cláudia M. Rocha(1), António S.

Barros(1), Ana M. Gil(1), Brian J. Goodfellow(1),

Isabel M. Carreira(2), João Bernardo(3), Ana

Gomes(3), Vitor Sousa(3,4), Lina Carvalho(3,4) and

Iola F. Duarte(1)

1. Department of Chemistry, CICECO/QOPNA,

University of Aveiro, Campus Universitário de

Santiago, 3810-193 Aveiro, Portugal. 2. Cytogenetics

Laboratory and CNC, Faculty of Medicine, University

of Coimbra, 3000 Coimbra, Portugal. 3. University

Hospitals of Coimbra, 3000-075 Coimbra, Portugal.

4. Institute of Pathological Anatomy, Faculty of

Medicine, University of Coimbra, 3000 Coimbra,

Portugal.

This work evaluates the potential of NMR-based

metabonomics of biofluids for the development of

new lung cancer screening methods to improve

early diagnosis. Multivariate modeling of plasma 1H

NMR spectra allowed cancer patients to be

discriminated from healthy subjects with sensitivity

and specificity levels of about 90%, as determined

by Monte Carlo Cross Validation.[1] Relatively lower

HDL and higher VLDL+LDL in the patients’ plasma,

together with increased lactate and pyruvate and

decreased levels of glucose, citrate, formate,

acetate, several amino acids (alanine, glutamine,

histidine, tyrosine, valine) and methanol could be

detected. Notably, these changes were found to be

present at initial disease stages and could be related

to known cancer biochemical hallmarks, such as

enhanced glycolysis, glutaminolysis and

gluconeogenesis, together with suppressed Krebs

cycle and reduced lipid catabolism, thus supporting

the hypothesis of a systemic metabolic signature for

lung cancer. An equally good discrimination

between lung cancer and healthy subjects was

obtained by NMR profiling of urine samples [2],

highlighting a number of consistently altered

metabolites, such as hippurate and trigonelline

(reduced in patients), and β-hydroxyisovalerate, α-

hydroxyisobutyrate, N-acetylglutamine and

creatinine (elevated in patients relatively to

controls). The influence of possible counfounders

(age, gender, smoking habits) has also been

assessed and found to have a lower impact on the

biofluids’ profiles than the presence of the disease.

References: 1. Rocha CM, Carrola J, Barros AS, Gil AM, Goodfellow BJ,

Carreira IM, Bernardo J, Gomes A, Sousa V, Carvalho L, Duarte IF.

Metabolic signatures of lung cancer in biofluids: NMR-based

metabonomics of blood plasma. J. Proteome Res. 2011 (in press). 2.

Carrola J, Rocha CM, Barros AS, Gil AM, Goodfellow BJ, Carreira IM,

Bernardo J, Gomes A, Sousa V, Carvalho L, Duarte IF. Metabolic

signatures of lung cancer in biofluids: NMR-based metabonomics of

urine. J. Proteome Res. 2011, 10, 221-230.

POSTER 21

LIPID PROFILES IN BREAST CANCER SAMPLES:

CHARACTERIZATION OF GLYCOSYLATED

CERAMIDES ASSOCIATED TO ESTROGEN RECEPTOR

NEGATIVE TUMORS

Heli Nygren, Mika Hilvo, Tuulikki Seppänen-Laakso,

Tuulia Hyötyläinen and Matej Orešič

VTT Technical Research Centre of Finland, Tietotie 2,

Espoo, FI-02044 VTT, Finland


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Activation of lipid metabolism is an early event in

carcinogenesis implying that lipids may have

potential as diagnostic biomarkers and modulation

of lipid metabolism may provide therapeutic

opportunities in cancer treatment. Certain

glycosphingolipids, associated to cancer, have

already been studied as therapeutic targets of

cancers. In this study, global lipidomic analysis

(including phospholipids, glycerolipids and

sphingolipids such as sphingomyelins, ceramides

and simple neutral glycosphingolipids) was

performed on 257 breast cancer samples and 10

samples from adjacent non-malignant breast tissue.

Samples were histologically well characterized and

clinicopathological information, including tumor

grade, estrogen receptor and progesterone receptor

status, was available. For determination of

molecular lipids, ultra high performance liquid

chromatography-quadrupole-time-of-flight mass

spectrometry (UPLC-QTOFMS) was applied. For

further identification of unknown lipids, fractions

collected from UPLC run were infused to a LTQ-

Orbitrap mass spectrometer by a TriVersa

Nanomate using chip-based nanoelectrospray in

negative and positive ion modes. Identifications

were based on the exact mass and MS2 and MS3

spectra. Glycosylated ceramides were identified in

negative ion mode using target mass resolution of R

= 60000. Normalized collision energies of 30 and

35% were applied. In tumors, the altered lipid

metabolism was most prominently related to

estrogen receptor status. Interestingly, some lipids

were highly downregulated in estrogen receptor

negative tumors. Two most prominent

downregulated lipids, m/z 828.6886 (Lipid 1) and

826.6786 (Lipid 2) were identified by LTQ-Orbitrap

in negative ion mode. In the MS2 product ion spectra

of both Lipid 1 and 2 showed the neutral loss of

hexose moiety (162 amu) while the MS3 analysis

elucidated the composition of ceramide backbone.

MS3 analysis showed Lipid 1 to be composed of fatty

acid 24:0 and long chain base (LCB) part of molecule

was revealed to be phytoceramide t18:0

(trihydroxy). Lipid 2 was composed of

monohydroxylated fatty acid 24:0 and LCB of d18:1.

Thus the lipids downregulated in hormone receptor

negative tumors were unusual

monohexosylceramides, HexCer(t18:0/24:0) and

HexCer(d18:1/24:0(OH)).

POSTER 22

A COMPREHENSIVE UNTARGETED METABONOMIC

ANALYSIS OF HUMAN STEATOTIC LIVER TISSUE BY

RP AND HILIC CHROMATOGRAPHY COUPLED TO

MASS SPECTROMETRY REVEALS IMPORTANT

METABOLIC ALTERATIONS

Juan C. García-Cañaveras(1, 2), M. Teresa Donato(1,

2, 3), José V. Castell(1,2, 3) and Agustín Lahoz(1).

(1) Unidad de Hepatología Experimental, Instituto

de Investigación Sanitaria - Fundación Hospital La

Fe,Valencia, Spain. (2) Departamento de

Bioquímica y Biología Molecular, Facultad de

Medicina, Universidad de Valencia, Spain. (3)

CIBERehd, Centro de Investigaciones Biomédicas en

Red de Enfermedades Hepáticas y Digestivas, FIS,

Spain.

Steatosis, or excessive accumulation of lipids in the

liver, is a generally accepted previous step to the

development of more severe conditions like non-

alcoholic steatohepatitis, fibrosis and cirrhosis. We

aimed to characterize the metabolic profile that

defines simple steatosis in human tissue and to

identify potential disturbances in the hepatic

metabolism that could favour the switch to

progressive liver damage. A total of 46 samples, 23

from steatotic and 23 from non-steatotic human

livers, were analyzed following a holistic LC-MS-

based metabonomic analysis that combines RP and

HILIC chromatographic separations. Multivariate

statistical data analysis satisfactorily classified

samples and revealed steatosis-associated

biomarkers. Increased levels of bile acids and

phospholipid degradation products, and decreased

levels of antioxidant species, were found in steatotic

livers, indicating disturbances in lipid and bile acid

homeostasis and mitochondrial dysfunction.

Changes in hypoxanthine, creatinine, glutamate,

glutamine or g-glutamyl-dipeptides concentrations,


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suggestive of alterations in energy metabolism and

amino acid metabolism and transport, were also

found. The results show that the proposed analytical

strategy is suitable to achieve a comprehensive

metabolic profile of steatotic human liver tissue and

provides new insights into the metabolic alterations

occurring in fatty liver that could contribute to its

predisposition to damage evolution.

POSTER 23

REGULATION OF LIPID METABOLISM IN BREAST

CANCER

Mika Hilvo, Carsten Denkert, Kristiina Iljin, Tuulikki

Seppänen-Laakso, Laxman Yetukuri, Elmar Bucher,

Laura Lehtinen, Marko Sysi-Aho, Tuulia Hyötyläinen,

Matej Oresic

VTT Technical Research Centre of Finland, Espoo and

Turku, Finland; Charite University Hospital, Berlin,

Germany

Previous studies have shown that specific changes in

lipid metabolism at the gene expression level are a

prominent feature in many tumors. However, very

few studies so far have investigated the lipid

molecular composition in tumor cells and tissues.

Here we applied the lipidomic approach to

characterize the lipidome in breast cancer tissues, as

part of the METAcancer EU project. Global

lipidomics using UPLC/MS was performed on a

series of 267 breast cancer samples, divided into

discovery and validation series. The data were

processed with MZmine 2 software and the peaks

identified by tandem MS. Large differences between

tumors and normal breast tissue were observed for

specific classes of membrane lipids. Generally,

phospholipid concentrations were elevated in

malignant tissue, with the highest concentrations

found especially in grade 3 and estrogen receptor

negative tumors. The specific enrichment of

palmitate in phospholipids, indicative of increased

de novo synthesis of fatty acids, was a prominent

feature of these aggressive tumors. Several related

lipids were also associated with poorer survival of

the patients. Motivated by the observed

phospholipid changes, we performed

comprehensive mining of published cancer gene

expression data for selected genes of potential

relevance to the findings. The lipid metabolism

genes found specifically overexpressed in breast

cancer tissues or cells were then silenced using RNAi

in multiple breast cancer cell lines. In agreement

with the tumor lipidomics results, for most genes

the silencing affected cell viability as well as

lipidomic profiles of the cancer cells. Together, our

results are consistent with earlier studies

highlighting the increased de novo fatty acid

synthesis in tumors. Our study may also provide a

basis for better understanding of upstream

regulation of lipid metabolism in cancer cells.

POSTER 24

HOW TO DEAL WITH DIFFERENT URINE

CONCENTRATIONS IN NUTRITIONAL

METABOLOMICS

Maj-Britt Schmidt Andersen(1), Helene Christine

Reinbach (2), Charlotte Elisabeth Mithril (1), Daniela

Rago (1), Lars Ove Dragsted (1)

1) Department of Human Nutrition, Faculty of Life

Sciences, University of Copenhagen 2) Department of

Food Science, Faculty of Life Sciences, University of

Copenhagen

Urine is an interesting biofluid for nutritional

metabolomics studies. The metabolites found in

urine are mainly dietary waste products which make

urine a promising source to discover potential

exposure markers for specific foods or dietary

patterns. The most common sampling procedure for

urine in nutrition studies is to collect 24 hour urine

samples. Such samples can easily vary in volume

between persons with several liters and this

complicates the data analysis, as variation in sample

concentration can obscure the true differences

between levels of urine metabolites caused by a

dietary intervention. In a cross-over meal-study

comparing three different Nordic meals, 144 twenty

four hour urine samples from 17 subjects were

analysed by UPLC-MS and 5 different methods were


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applied to adjust for differences in urine

concentration and compared with unadjusted data.

In four of the methods, the data were normalized

post-sample analysis according to 1) creatinine

levels; 2) osmolality; 3) total ion current intensity;

and 4) urine volume. In the last method, the

samples were run a second time on UPLC-MS and

for each sample, the injection volume was adjusted

according to sample osmolality. This was done in

order to investigate the effect of adjusting for

differences in urine concentration before sample

analysis. The results from the five methods were

evaluated by comparing the standard deviation of

features between the methods and the meal

separation in PCA. We report here on the findings

from the study.

POSTER 25

IS SERUM OR PLASMA MORE APPROPRIATE FOR

INTER-SUBJECT COMPARISONS IN METABOLOMIC

STUDIES? AN ASSESSMENT IN PATIENTS WITH

SMALL-CELL LUNG CANCER

James William Allwood(1), David C. Wedge (1),

Warwick Dunn( 1,2,3), Andrew A. Vaughan (1),

Kathryn Simpson (4), Marie Brown (3), Lynsey Priest

(4), Fiona H. Blackhall (4), Anthony D. Whetton (5),

Caroline Dive (4) and Royston Goodacre (1,2)

1. School of Chemistry, Manchester Interdisciplinary

Biocentre, University of Manchester, 131 Princess Street,

Manchester, M1 7DN, UK. 2. Manchester Centre for

Integrative Systems Biology, Manchester Interdisciplinary

Biocentre, University of Manchester, 131 Princess Street,

Manchester, M1 7DN, UK. 3. Centre for Advanced

Discovery & Experimental Therapeutics (CADET), Central

Manchester NHS Foundation Trust and School of

Biomedicine, University of Manchester, Manchester

Academic Health Sciences Centre (MAHSC); York Place,

Oxford Road, Manchester, M13 9WL, UK. 4. Clinical and

Experimental Pharmacology Group, Paterson Institute for

Cancer Research and Manchester Cancer Research Centre

(MCRC), Manchester Academic Health Science Centre,

University of Manchester, Wilmslow Road, Withington,

Manchester, M20 4BX, UK. 5. School of Cancer and

Enabling Sciences, Manchester Academic Health Science

Centre, University of Manchester, Manchester, M20 3LJ,

UK

In clinical analyses, optimal assay performance is

often based upon selection of the most appropriate

and readily available biofluid. The most readily

accessible biofluids for clinical analyses are urine or

alternatively blood. Blood is known to be

particularly effective in clinical diagnosis since it

circulates the body and thus is metabolically

effected by many disease manifestations regardless

of tissue localisation, although it is also recognised

in the field that a biofluid which is more closely

located to the disease manifestation may in fact

have a greater diagnostic ability. Classically,

metabolomic analyses have been performed upon

either plasma or serum, although applications of

serum have been more common in the field. To

determine the optimal blood based fluid for

analysis, metabolic profiles of matched human

serum and plasma were assessed by Gas

Chromatography - Time of Flight / Mass

Spectrometry (GC-TOF/MS) and Ultra High

Performance Liquid Chromatography - Mass

Spectrometry (UHPLC-MS) in both positive and

negative electrospray ionisation modes. It was

discovered that serum yielded more metabolic

features in ESI- mode UHPLC-MS, whereas plasma

yielded more features through ESI+ mode UHPLC-

MS and GC-TOF/MS. A statistical comparison of the

two metabolomes, in terms of reproducibility,

discriminative ability and coverage, indicated that

serum and plasma offered similar analytical

opportunities and that neither was superior for

metabolic analysis. A statistical analysis of the

variation between 29 small-cell lung cancer (SCLC)

patients, revealed that the differences between

individuals are markedly similar regardless of

whether serum or plasma is employed for analysis.

However, significant differences between plasma

and serum were found in the levels of some specific

metabolites, as were differences in the inter-subject

variability of some metabolite levels.

Glycerophosphocholines, erythritol, creatinine,

hexadecanoic acid and glutamine in plasma, but not


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in serum, were shown to correlate with increased

life expectancy for SCLC patients following

chemotherapeutic treatment, therefore indicating

the utility of metabolomic analyses in clinical

prognosis and the particular utility of plasma in

relation to the clinical management of SCLC.

POSTER 26

IMPACT OF PRENATAL DISORDERS ON MATERNAL

URINE COMPOSITION- AN NMR METABONOMIC

STUDY

Sílvia O. Diaz(1), Gonçalo Graça(1), Joana Pinto(1),

António S. Barros(2), Iola F. Duarte(1), Brian J.

Goodfellow(1), Isabel M. Carreira(3), Eulália

Galhano(4), M. Céu Almeida(4), Cristina Pita(4) and

Ana M. Gil(1)

1 CICECO, Department of Chemistry, University of

Aveiro, Campus Universitário de Santiago, 3810-193

Aveiro, Portugal. 2. QOPNA, Department of

Chemistry, University of Aveiro Campus

Universitário de Santiago, 3810-193 Aveiro,

Portugal. 3 Cytogenetics and Genomics Laboratory,

Faculty of Medicine, University of Coimbra, Portugal

and CENCIFOR - Forensic Science Centre, Portugal.

4. Bissaya Barreto Maternity, Hospital Center of

Coimbra, Portugal.

NMR-based metabonomics has been explored in

pregnancy research, namely through the study of

amniotic fluid [1,2] and maternal blood serum or

plasma [3]. This work describes an NMR

metabonomic study of maternal urine to probe the

metabolic effects of fetal malformations (FM),

chromosomal disorders (CD), gestational diabetes

mellitus (GDM), at pre- and post-diagnostic states,

preterm delivery (PTD) and premature rupture of

membranes (PROM). Urine samples were collected,

at the time of amniocentesis (14-22 gestational

weeks), and pregnancies were followed until birth

so that several groups were defined: controls

(healthy pregnancies), pre-diagnostic GDM, pre-

PTD, pre-PROM, FM and CD. Post-diagnostic GDM

urine samples were collected, upon diagnosis (14-39

gestational weeks) and compared to a gestational

age-matched control group. 1D 1H NMR (500 MHz)

spectra of all samples were acquired and

multivariate analysis and Monte-Carlo cross-

validation was carried out. Metabolite assignment

was done through 2D NMR and, in some cases,

Statistical Total Correlation Spectroscopy. FM were

found to have a significant impact on maternal urine

composition, suggesting enhanced Krebbs cycle

demand, possibly as a result of gluconeogenesis,

and fetal hypoxia (increased hypoxanthine).

Increased excretion of N-methylnicotinamide

(NMND) and N-methyl-2-pyridone-5-carboxamide

(2PY) suggested alterations in nucleotide

metabolism and higher choline excretion may

reflect imbalanced methionine-homocysteine

conversion, as previously reported for neural-tube

defects [4]. For the CD group, increased choline

indicates altered choline metabolism and a further

distinction between trisomy 21 cases from other

CDs was noted. The pre-PTD group exhibited altered

choline and amino acid metabolism (increased 2-

hydroxyisobutyrate) whilst for the pre-PROM group

no differences were found. Pre-diagnostic GDM

subjects showed altered nucleotide (increased

NMND and 2PY) and choline (increased choline)

metabolisms in tandem with increased 3-

hydroxyisovalerate and 2-hydroxyisobutyrate,

suggesting altered biotin status, amino acids and/or

gut metabolism. Post-diagnostic GDM urine

revealed a distinct profile based on increased amino

acids, choline and 2-hydroxyisobutyrate and

decreased p-cresol sulphate, succinate, carnitine,

creatinine and allantoin, some common features

having been detected in the pre-diagnostic group

(increased choline and 2-hydroxyisobutyrate). The

above results show the potential of exploring

maternal urine to study the metabolic changes

underlying prenatal disorders and thus search for

possible early and non-invasive biomarkers.

References: 1. Bock, J. Clinical Chemistry 1994, 40, (1), 56-61. 2. Graça,

G.; Duarte, I. F.; Barros, A. S.; et al. Journal of Proteome Research 2010,

9, (11), 6016-6024. 3. Turner, E.; Brewster, J. A.; Simpson, N. A. B.; et al.

Reproductive Sciences 2009, 16 (11), 1040-1051. 4. Zhao, W.; Mosley, B.

S.; Cleves, M. A.; et al. Clinical and Molecular Teratology 2006, 76, (4),

230-236. This work has been supported by Fundação para a Ciência e


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Tecnologia - FCT (PTDC/QUI/66523/2006, SFRH/BD/41869/2007 and

SFRH/BD/64159/2009)

POSTER 27

OPTIMIZATION OF PROCEDURES FOR COLLECTING

AND STORING OF CSF FOR STUDYING THE

METABOLOME IN HEALTH AND DISEASE.

Anna Wuolikainen(1), Hedenström, M.(1), Moritz,

T.(2), Marklund, SL.(3), Antti, H.(1) & Andersen,

PM.(4).

1. Department of Chemistry, Umeå University,

Umeå. 2. Department of Forest Genetics and Plant

Physiology, Swedish University of Agricultural

Sciences, Umeå. 3. Department of Medical

Biosciences, Clinical Chemistry, Umeå University

Hospital, Umeå, Sweden. 4. Department of

Neurology, Umeå University Hospital, Umeå

Initial metabolomic studies of cerebrospinal fluid

(CSF) samples showed large diversity in the

concentrations of metabolites. Some variability

could not be explained, but some could be related

to the genotype/phenotype of the patients and drift

during the analysis. Indications were evident that

the storage time span of the samples may be of

importance, but many parameters had not been

investigated, only suspected. In order to develop

manageable protocols for collecting comparable

samples for research in the clinic, there is a value of

knowing which the most influencing factors are and

their effects in both size and action on the results.

The study aimed to investigate if pre-analytical

factors could induce artefacts in metabolomic data

of CSF from patients with ALS and controls. CSF from

16 patients was studied using a statistical

experimental design protocol with parameters:

storage temperature (-80°C/-20°C), type of

collection tube (polypropylene/polystyrene), time

delay from collecting to freezing (0, 10, 30, 90, 150

min) taking into account a possible gradient of early

to late collected tubes during the spinal tap. Gas

chromatography-mass spectrometry was used to

analyze the CSF from 12 of the patients while CSF

from one patient was analyzed using nuclear

magnetic resonance spectroscopy. The extent of

CO2 evaporization from CSF collected in tubes of

different sizes at different temperatures and

with/without lid was studied in three additional

patients. Alterations of metabolite concentrations

were found for all the studied parameters. Storage

temperature had the largest effect on the

metabolite composition of the studied variables. A

possible explanation of the alterations could be CO2

evaporization from samples that induce artefacts in

the metabolome by increasing the pH in samples

stored at higher temperatures. In conclusion,

collecting the CSF directly into tubes with tightly

sealed lids in N2(l) and transferring tubes to -80°C

directly would minimize the evaporation of CO2.

This may however not be a plausible methodology

to use in the clinic. Therefore we are currently

discussing and developing a consensus protocol that

can be implemented worldwide for collecting and

storing CSF from ALS patients and controls.

Reference: Wuolikainen A., Hedenström M., Moritz T., Marklund S. L.,

Antti H. and Andersen P. M. (2009). "Optimization of procedures for

collecting and storing of CSF for studying the metabolome in ALS."

Amyotrophic Lateral Sclerosis 10: 229-236.

POSTER 28

METABOLIC PROFILING OF 2ND TRIMESTER

MATERNAL BLOOD PLASMA FOR THE STUDY OF

PRENATAL DISORDERS

Joana Pinto(1), G. Graça(1), S. O. Diaz(1), A. S.

Barros(2), I. F. Duarte(1), B. J. Goodfellow(1), I. M.

Carreira(3), E. Galhano(4), M. C. Almeida(4), C.

Pita(4) and A. M. Gil(1)

1. CICECO, Department of Chemistry, University of

Aveiro, Campus Universitário de Santiago, 3810-193

Aveiro, Portugal. 2. QOPNA, Department of Chemistry,

University of Aveiro, Campus Universitário de Santiago,

3810-193 Aveiro, Portugal. 3. Cytogenetics and Genomics

Laboratory, Faculty of Medicine, University of Coimbra,

3004-504 Coimbra, Portugal and CENCIFOR Forensic

Science Centre, Portugal. 4. Bissaya Barreto Maternity,

Hospital Center of Coimbra, 3000-061 Coimbra, Portugal.

This work comprises a metabonomic study of

prenatal disorders through Nuclear Magnetic


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Resonance (NMR) of 2nd trimester maternal blood

plasma to search for metabolite markers of prenatal

disorders. Several attempts have been made to

correlate the metabolic composition of amniotic

fluid[1,2] and the occurrence of the same prenatal

diseases. To our knowledge, the use of blood

plasma metabonomics for prediction/diagnosis of

prenatal disorders by NMR has only been explored

in relation to preeclampsia (PE)[3,4], comprising a

low cohort of PE samples (n=11). In this work, blood

samples were collected under non-fasting

conditions at the time of amniocentesis (14-25

gestational weeks). All pregnancies were followed

up until birth, defining 5 samples groups: controls,

fetal malformations, chromosomal disorders, pre-

diagnostic gestational diabetes (GD) (for women

later diagnosed with GD) and premature rupture of

membranes (PROM) (for women who gave birth

after 37 gestational weeks). Standard 1D 1H-NMR

spectra, T2 relaxation-edited (CPMG) spectrum and

diffusion-edited spectrum of all samples were

acquired. Multivariate analysis was then applied in

order to search for consistent statistical correlations

between maternal plasma composition and the

occurrence of the diseases. Fetal malformations

were found to have the highest impact on the

metabolic profile of 2nd trimester plasma showing an

increase in lipids and ketone bodies, and decrease in

betaine and methanol. Small metabolite changes

were also found for pre-diagnostic GD,

chromosomal disorders and pre-PROM conditions,

thus unveiling the potential for the early prediction

of these disorders.

References: [1]. Graça, G., et al., Journal of Proteome Research, 2009.

8(8): p. 4144-4150. [2]. Graça, G., et al., Journal of Proteome Research,

2010. 9(11): p. 6016-6024. [3]. Turner, E., et al., Hypertension in

Pregnancy, 2007. 26(3): p. 329-342. [4]. Turner, E., et al., Hypertension

in Pregnancy, 2008. 27(3): p. 225-235. This work has been supported by

Fundação para a Ciência e Tecnologia - FCT (PTDC/QUI/66523/2006,

SFRH/BD/41869/2007, SFRH/BD/64159/2009 and

SFRH/BD/73343/2010).

POSTER 29

CAN PRENATAL DISORDERS BE DETECTED AND

MONITORED THROUGH 2ND TRIMESTER BIOFLUIDS

METABOLIC PROFILING?

G Graça(1), S Diaz(1), J Pinto(1), AS Barros(2), IF

Duarte(1), BJ Goodfellow(1), E Galhano(3), C Pita(3),

IM Carreira(4) and AM Gil(1)

1. CICECO, Departamento de Química, Universidade de

Aveiro, 3810-193 Aveiro Portugal. 2. QOPNAA,

Departamento de Química, Universidade de Aveiro, 3810-

193 Aveiro Portugal. 3. Maternidade Bissaya Barreto,

Coimbra, Portugal. 4. Instituto de Biologia Médica,

Centro de Citogenética, Universidade de Coimbra,

Portugal.

Initial metabonomic studies of prenatal biofluids (1-

3), pursued by NMR spectroscopy, have unveiled

significant promise for eventual improved methods

of diagnosis, monitoring and even prediction of

prenatal disorders. Although conditions such as fetal

malformations (FM) or chromosomal disorders (CD)

are routinely diagnosed by increasingly

sophisticated methods (e.g. ultrasound, detection of

maternal serum markers, chorionic vilus sampling,

amniocentesis, cordocentesis), they still call for

improved less-invasive approaches. Also, disorders

such as gestational diabetes mellitus (GDM),

preeclampsia (PE) and preterm delivery (PTD), which

may pose serious complications later in pregnancy,

still lack adequate predictive methods, thus

justifying a continuing research effort towards new

and improved diagnostic methods. In this context,

results will be presented on the metabolic profiling

of 2nd trimester amniotic fluid and maternal urine

and plasma, collected for women whose

pregnancies were then accompanied to their term

(4-7). In this way, different subgroups became

defined, according to the outcome of their

pregnancies: controls, FM, CD, pre-diagnostic GDM,

pre-PTD and pre-premature rupture of membranes

(PROM) (PE was not included at this stage due to

insufficient number of samples). The effects of each

condition on the metabolic profile of each biofluid

were measured by NMR and, in some cases, Mass


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spectrometry (MS), the resulting data having been

analysed by a set of multivariate analysis tools (e.g.

Partial Least Squares-Discriminant Analysis (PLS-DA)

and Orthogonal-PLS-DA (O-PLS-DA) methods) and

statistical validation by Monte Carlo calculations and

significance evaluation (p value). The

complementarity of NMR and MS methods was

exploited for urine and amniotic fluid, in order to

improve metabolite information density, and use

was made of Statistical Total Correlation

Spectroscopy (STOCSY) to improve metabolite

assignment and identification of metabolite

correlations (positive or negative) which may aid in

the enlightening of specific disturbed metabolic

pathways. An overall picture of each disease will be

given, considering the interplay of the three

biofluids and the complementary information that

they carry. Here, STOCSY was also employed to help

identifying correlated variations within distinct

biofluids. Generally, results show that fetal

malformations have the strongest effects in all three

biofluids, however, the sensitivity of each biofluid to

malformation type (namely to central nervous

system FM) seems to vary. The metabolite changes

detected suggest changes in energy, protein and

nucleotide metabolisms and kidney

underdevelopment6. Weaker but detectable effects

are observed for the pre-diagnostic GDM group,

identifying interesting early indications of the

condition. In addition, smaller metabolite changes

were also observed for chromosome disorders (also

exhibiting distinct effects according to disorder type

e.g. for trissomy 21) and pre-PTD. A picture of the

relative impact of each disorder on the three

biofluids will be given, thus identifying specific

biofluids and compound families of interest for

research follow-up through targeted analysis

methods. These results demonstrate the enticing

potential of NMR and MS metabonomics towards

the development of improved clinical methods in

prenatal health and future interesting aspects such

as extrapolation to 1st trimester monitoring or

impact on newborn health will be discussed.

References: 1.Bock JL, Metabolic profiling of amniotic fluid by proton

nuclear magnetic resonance spectroscopy: correlation with fetal

maturation and other clinical variables. Clin Chem 1994, 40, (1), 56-61.

2. McGowan PE et al, H-1 NMR as a non-invasive probe of amniotic fluid

in insulin dependant diabetes mellitus. J Perinatal Med 1999, 27, (5),

404-408. 3. Groenen PMW et al, High-resolution H-1 NMR spectroscopy

of amniotic fluids from spina bifida fetuses and controls. Eur J Obst

Gynecol Reproduct Biol 2004, 112, (1), 16-2 4.Graça G et al, Potential of

NMR Spectroscopy for the Study of Human Amniotic Fluid. Anal. Chem.

2007, 79, (21), 8367-8375. 5.Graça et al, Metabolite Profiling of Human

Amniotic Fluid by Hyphenated Nuclear Magnetic Resonance

Spectroscopy. Anal. Chem. 2008, 80, (15), 6085-6092. 6.Graça et al, H-1

NMR Based Metabonomics of Human Amniotic Fluid for the Metabolic

Characterization of Fetus Malformations. J Proteome Res 2009, 8, (8),

4144-4150. 7. Graça G et al, “The Impact of Prenatal Disorders on the

Metabolic Profile of 2nd Trimester Amniotic Fluid: A Nuclear Magnetic

Resonance (NMR) Metabonomic Study”, J Proteome Res 2010, 9(11),

6016-6024.

POSTER 30

DETECTION OF MR METABOLIC BIOMARKERS FOR

BREAST CANCER PROGNOSIS

Guro Giskeødegård(1), Steinar Lundgren(1,2,3),

Beathe Sitter(1), Hans E. Fjøsne(4), Geert Postma(5),

Lutgarde M.C. Buydens(5), Ingrid S. Gribbestad(1),

Tone F. Bathen(1)

1. Department of Circulation and Medical Imaging,

Norwegian University of Science and Technology (NTNU),

Trondheim, Norway. 2.Department of Oncology, St Olavs

University Hospital, Trondheim, Norway. 3.Department

of Cancer Research and Molecular Medicine, NTNU,

Trondheim, Norway. 4.Department of Surgery, St. Olavs

University Hospital, Trondheim, Norway 5.Radboud

University Nijmegen, Institute for Molecules and

Materials, The Netherlands

Breast cancer is a heterogeneous disease with

varying prognosis. The prognosis and treatment plan

for a breast cancer patient is based on clinical

assessment; however there is a need for additional

information to further stratify patients for improved

and more individualized treatment. Previous studies

have shown different metabolic patterns to be

related to prognostic factors of breast cancer(1,2).

In this study, the relationship between the

metabolic profiles of breast cancer tissue and

survival was examined by multivariate analysis.

Predictions of 5-year survival using metabolic

profiles were compared to predictions using

standard clinical parameters. Tumor biopsies from

estrogen receptor positive breast cancer patients (n


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= 71) were analysed by high resolution magic angle

spinning (HR MAS) MR spectroscopy. The spectra

were analysed by principal component analysis

(PCA), and the patients were divided in two

prognostic groups based on a cut-off value of the

4th PC as chosen by 4-fold cross-validation of the

data set and receiver operating characteristics. To

further examine differences in the metabolic

profiles, partial least squares discriminant analysis

(PLS-DA) was used for classification of 5-year breast

cancer survival. PLS-DA was performed both by

using metabolic profiles and by using clinical

parameters as input, and 30% of the samples were

kept out as an independent validation set. The

significance of the PLS-DA classification was

evaluated by permutation testing. PCA revealed a

clear difference in the spectra of survivors and non-

survivors, and the survival rates of the defined

prognostic groups were significantly different (log

rank, p = 0.024). Higher levels of glycine and lactate

were found to be associated with lower survival

rates, and are suggested as biomarkers for breast

cancer prognosis. By using PLS-DA, the patients

were classified as 5-year survivors or non-survivors

with 72 % correct classification of the validation set

(p < 0.001 by permutation testing) based on their

metabolic profiles. PLS-DA predictions of 5-year

survival using metabolic profiles gave better and

more robust prediction results than using traditional

clinical parameters. In conclusion, the metabolic

state of a tumor provides information concerning

breast cancer prognosis beyond that of clinical

parameters. Metabolomics may be an additional

tool for determining the prognosis and treatment

strategy of breast cancer patients.

References: Giskeødegård et al, 2010. J Proteome Res, 9(2): 972-979

Sitter et al, 2006. NMR Biomed, 19(1): 30-40

POSTER 31

DEVELOPING A DATA-DRIVEN FRAMEWORK FOR

DISCOVERY AND USE OF DIETARY EXPOSURE

BIOMARKERS IN HUMAN EPIDEMIOLOGICAL

STUDIES

Amanda Lloyd(1), Manfred Beckmann(1), Gaëlle

Favé(2), Sumanto Haldar(2), Chris Seal(2), John C

Mathers(2), John Draper(1)

1. Aberystwyth University. 2. Newcastle University

Western diets are generally complex and

conventional methods of measuring habitual dietary

exposure such as Food Frequency Questionnaires

(FFQs) depend upon food intake estimates and are

subject to errors, which can confound interpretation

of subsequent data. Descriptors of individual FFQ

food components vary in degree of distinctiveness

and consumption patterns of each food component

generally display great variability, including effects

of seasonality. Against this background we have

been exploring the use of metabolomics to help

validate FFQ dietary component descriptors without

prior knowledge of biochemical markers potentially

indicative of habitual exposure to specific foods.

Initially we demonstrated that non-targeted

metabolite fingerprinting using Flow Infusion ESI-MS

(FIE-MS) in conjunction with machine learning data

analysis can be used to explore relationships

between the chemical content of overnight or

fasting urine and reported levels of citrus exposure

in 24 humans consuming a freely-chosen diet.

Fourier-Transform Ion Cyclotron Resonance MS (FT-

MS) and tandem MS, followed by signal annotation

using MZedDB suggested that correlated

explanatory signals indicative of high citrus

consumption were ionisation adducts of proline

betaine (stachydrine) and hydroxyproline betaine. In

an expansion of this preliminary study we describe a

high throughput, data-driven approach to explore

the food consumption habits (>130 standard food

components) of a larger cohort of free-living

humans. Using FFQ information and FIE-MS analysis

of fasting and/or overnight urines we identify food


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components that are well discriminated between

groups of individuals reporting either high or low

habitual consumption. Ultra-high accurate mass

analysis and tandem MS has revealed potential

biomarkers for a range of foods of high public heath

significance (including red and white meats, specific

fruit/vegetables and dairy products). The likely role

and impact of the use of biomarkers on future

dietary exposure monitoring in human

epidemiological studies will be discussed.

POSTER 32

A DETAILED METABOLOMIC CHARACTERIZATION

OF HIGH GRADE GLIOMAS WITH RESPECT TO TYPE,

GRADE AND SURVIVAL

Lina Mörén(1), Carl Wibom2, Beatrice Melin2,

Mikael Johansson2, Jerker Fick1, Tommy

Bergenheim3 and Henrik Antti1

1. Department of Chemistry, Umeå University, SE 901 87

Umeå, Sweden. 2. Department of Radiation Sciences,

Oncology, University Hospital, SE 901 85 Umeå, Sweden.

3. Department of Neurosurgery, University Hospital, SE

901 85 Umeå, Sweden.

High grade glioma is the most common brain tumor

in adults. The prognosis for patients diagnosed with

this type of cancer is still poor even with all available

treatments such as surgery, radiotherapy and

chemotherapy. Their invasive growth makes them

one of the major causes of cancer death. The

survival time varies between patients; some can live

with the tumor for years while others die just weeks

after diagnosis. Thus, there is an urgent need to

improve treatment and develop new treatment

modalities for these types of tumors. Our belief is

that the use of metabolomics in combination with

sophisticated bioinformatics strategies could

provide novel hypothesis for understanding tumor

development and for developing new treatments.

We have previously reported interesting results in a

study in patients of response to radiation treatment

in irresectible glioblastoma where we detected

multivariate correlations between the GC/TOFMS

metabolic profiles in tumor extracellular fluid,

sampled by microdialysis, and treatment response1.

Here we present a detailed metabolomics

characterization of blood samples collected from

135 fasting patients and tumor tissue from 90

patients with different glioma diagnosis

(glioblastoma, oligodendroglioma and astrocytoma)

and grade (WHO grade II, III and IV). This include a

global screening approach using GC/TOFMS as well

as a targeted strategy involving high resolution

LC/MSMS quantification of a battery of metabolites

identified by means of pathway associations to

confirmed risk genes. The acquired data has been

modeled and evaluated by chemometrics based

bioinformatics methods revealing specific metabolic

patterns related to tumor type and grade. We are

also evaluating metabolic patterns associated with

survival, which can be of clinical importance and aid

the decision making of treatment and extent of

treatment.

References: 1. Wibom W, Surowiec I, Mörén L, Bergström P,

Johansson M, Antti H‡, Bergenheim AT. Metabolomic patterns in

glioblastoma and changes during radiotherapy – a clinical microdialysis

study, Journal of Proteome Research, 2010 Jun 4;9(6):2909-19.

POSTER 33

METABOLIC PROFILING OF URINE FROM PATIENTS

WITH URINARY TRACT INFECTION BY 1H NMR:

DISEASE AND RECOVERY

Ekaterina Nevedomskaya(1), Axel Meissner(1), Sibel

Goraler(1), Monique de Waard(2), Yanto Ridwan(3),

Gerben Zondag(3), Ingrid van der Pluijm(3), André

M. Deelder(1), Oleg A. Mayboroda(1)

1. Biomolecular Mass Spectrometry Unit, Dept.

Parasitology, Leiden University Medical Center, Leiden,

the Netherlands. 2. Erasmus Medical Center, Rotterdam,

Netherlands. 3. DNage BV, Leiden, the Netherlands.

Aging is a fundamental biological process for which

the mechanisms are still largely unknown due to its

complex and multifactorial nature. Moreover, since

aging is a process that unfolds in time, it has to be

studied in its dynamics. Consequently, because

aging affects all organs and tissues, its complexity

suggests that different biological levels should be


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investigated. A direct application of this strategy to

humans has certainly its limits; therefore, the

animal models play an essential part in the aging

research. As there are many causative links between

DNA repair deficiency and aging, one of the

proposed models is ERCC1d/- mouse. These animals

have a modified ERCC1 gene, involved in the

Nucleotide Excision Repair, and as a result exhibit an

accelerated-aging phenotype. To get an insight into

the biochemical processes underlying aging in fast-

aging ERCC1d/- mice we applied a metabolic

profiling strategy. We analyzed metabolic

trajectories over time in serum and compared the

results to profiling of urine, thus fulfilling the two

necessities proposed for studying aging. Wild type

and ERCC1d/- animals have similar changes in

profiles preceding maturity and diverge after, which

suggests that the model is valuable for studying

accelerated aging, not accelerated maturity. The

main differences between these two genetically

diverse groups of mice were found to be associated

with altered lipid and energy metabolism, transition

to ketosis and attenuated functions of liver and

kidney. Another important observation is that

metabolic signatures of the studied fast-aging mice

resemble very much the alterations in profiles of

calorically restricted animals, which are known to be

long-lived. This data may suggest that genetic and

adaptive stress possibly activate similar metabolic

response.

POSTER 34

CHARACTERIZATION OF HUMAN PROSTATE

CANCER BONE METASTASES

Elin Thysell(1), Emma Hörnberg (2), Henrik Antti (1),

Pernilla Wikström (2)

1. Department of Chemistry, Umeå University, Umeå,

Sweden. 2. Department of Medical Biosciences, Umeå

University, Umeå, Sweden.

Metastasis to the bone is one clinically important

features of prostate cancer (PCa). Current diagnostic

methods cannot predict metastatic PCa at a curable

stage of the disease. Identification of metabolic

pathways involved in the growth of bone

metastases therefore has the potential to improve

PCa prognostication as well as therapy. A

metabolomics methodology was applied for the

study of PCa bone metastases in comparison with

corresponding normal bone and furthermore of

malignant and benign prostate tissue and

corresponding plasma samples obtained from

patients with and without diagnosed metastases

and from men with benign prostate disease. This

was done using gas chromatography-mass

spectrometry for sample characterization, and

chemometric bioinformatics for data analysis. The

results were verified in a separate test set including

metastatic and normal bone tissue from patients

with other cancers. Significant differences were

found between PCa bone metastases, bone

metastases of other cancers, and normal bone.

Furthermore, we identified metabolites in primary

tumor tissue and in plasma which were significantly

associated with metastatic disease. Among the

metabolites in PCa bone metastases especially

cholesterol was noted. In a test set the mean

cholesterol level in PCa bone metastases was 127.30

mg/g as compared to 81.06 and 35.85 mg/g in bone

metastases of different origin and normal bone,

respectively (P = 0.0002 and 0.001).

Immunohistochemical staining of PCa bone

metastases showed intense staining of the low

density lipoprotein receptor and variable levels of

the scavenger receptor class B type 1 and 3-

hydroxy-3-methylglutaryl-coenzyme reductase in

tumor epithelial cells, indicating possibilities for

influx and de novo synthesis of cholesterol. We have

identified metabolites associated with PCa

metastasis and specifically identified high levels of

cholesterol in PCa bone metastases. To obtain a

more comprehensive picture of the complex

mechanisms behind bone metastasis development

in PCa we are now relating genomic differences to

the existing metabolomics data and additionally to

pathway guided selections of metabolites. Further,

the aim is also to probe mechanisms associated with

resistance to castration treatment by studying


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differences in hormone-naïve and castration

resistant patients.

POSTER 35

ADVANCED ODOUR ANALYTICAL TOOLS FOR

ELUCIDATION OF THE DIAGNOSTIC POTENTIAL OF

ODOROUS SUBSTANCES IN HUMAN URINE

Maria Wagenstaller(1), Andrea Buettner(1,2)

1. Department of Chemistry and Pharmacy - Emil

Fischer Center, University of Erlangen-Nuremberg,

91052 Erlangen, Germany. 2. Fraunhofer Institute

for Process Engineering and Packaging (IVV), 85354

Freising, Germany.

The volatile and odorous profile of human urine

seems to be a rich source for information with

regard to several aspects. First of all, it opens a

window for our understanding of metabolization

and excretion processes both of low-molecular

weight compounds originating from e.g. dietary or

endogenous sources [1,2,3,4]. Also, changes from

common profiles serve us as potential indicators

and mechanistic clues for changes in the respective

physiological conditions e.g. being induced by

diseases or hormonal changes [5,6,7]. Still, the

diagnostic potential of urinary odorants is not yet

fully established. Accordingly, the aim of the present

study was to evaluate a combination of

comprehensive chemo-analytical and human-

sensory characterization with regard to its

applicability to human urine odorant

characterization. To achieve this goal we applied

one- and two-dimensional high resolution gas

chromatography-olfactometry (HRGC-O) in

combination with mass spectrometry to identify

commonly occurring and potent odorants in human

urine. The studies were both carried out on native

urine from healthy human subjects, as well as urine

that had been treated by glucuronidase assays, with

further analytical focus on the liberated odour-

active compounds using the specified techniques.

Quantification of selected odour-active constituents

was accomplished by means of two-dimensional

HRGC-MS utilizing stable isotope dilution assays. It

was shown that application of these techniques led

to the successful detection of a range of substances,

some of them being identified for the first time as

urine constituents of healthy adults. These findings

offer the possibility to further explore changes of

odorous urinary constituents with highly selective

and sensitive analytical tools.

References [1] Zeller, A., K. Horst, et al. (2009). "Study of the

Metabolism of Estragole in Humans Consuming Fennel Tea." Chemical

Research in Toxicology 22(12): 1929-1937 [2] Stevens, P. (2008).

"Detection of sulfur-containing metabolites of asparagus in urine by

SBSE-GCxGC-TOFMS." American Laboratory 40(6): 28-30 [3] Mitchell, S.

C. (2001). "Food idiosyncrasies: Beetroot and asparagus." Drug

Metabolism and Disposition 29(4): 539-543 [4] Pysanenko, A., T. Wang,

et al. (2009). "Acetone, butanone, pentanone, hexanone and heptanone

in the headspace of aqueous solution and urine studied by selected ion

flow tube mass spectrometry." Rapid Communications in Mass

Spectrometry 23(8): 1097-1104 [5] Podebrad, F., M. Heil, et al. (1999).

"4,5-dimethyl-3-hydroxy-2[5H]-furanone (sotolone) - The odour of

maple syrup urine disease." J. Inher. Metab. Dis. 22: 107-114 [6] Weber,

C. M., M. Cauchi, et al. (2011). "Evaluation of a gas sensor array and

pattern recognition for the identification of bladder cancer from urine

headspace." Analyst 136(2): 359-364 [7] Smith, D., K. M. K. Ismail, et al.

(2006). "Increase of acetone emitted by urine in relation to ovulation."

Acta Obstetricia Et Gynecologica Scandinavica 85(8): 1008-1011

POSTER 36

METABOLOMICS AS A TOOL FOR A BETTER

UNDERSTANDING OF DRUG-INDUCED

PHOSPHOLIPIDOSIS

Emmanuelle Lecommandeur(1), David Baker(2),

Andrew W. Nicholls(2), Julian L. Griffin(1)

1. Department of Biochemistry, University of Cambridge,

Cambridge, CB2 1GA, UK. 2. GlaxoSmithKline, Park Road,

Ware, SG12 0DP, UK.

Drug-induced phospholipidosis (DIPL) is a lysosomal

storage disorder caused by treatments using

cationic amphiphilic drugs, drugs designed to

specifically cross biological membranes. It is

characterised by an increase in the cellular

phospholipid content and the observation of

lamellar bodies by electron microscopy. Different

organs are affected depending on the drug inducing

the disorder. The presence of DIPL during a

treatment with this type of drug is therefore a

concern for pharmaceutical industries. Lamellar

bodies, the hallmark for the condition, are spherical


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structures composed of an accumulation of

phospholipids and drugs in the lysosome. The

observation of these bodies in tissues is the gold

standard for the diagnosis of DIPL but this is time

consuming, invasive and expensive. This is why

finding a biomarker is currently the focus of much

research into the condition. In this study,

metabolomics has been applied to better

understand the mechanisms and toxicity of DIPL. An

open profiling approach was used to analyse

samples from rats, using nuclear magnetic

resonance spectroscopy, gas chromatography-mass

spectrometry and liquid chromatography-mass

spectrometry. Rats were divided into four groups

(n=9 for each group): a control group and three

groups treated individually with either amiodarone

(300 mg/kg/day), chloroquine (300 mg/kg/day), or

tamoxifen (130 mg/kg/day); all of which are drugs

known to cause DIPL. Liver, lung, brain, kidney,

heart and whole blood were analysed to provide a

global perspective of the effects of DIPL. DIPL

affected each tissue in a different manner

dependent on the nature of the tissue and of the

drug. However, common patterns were detected,

particularly in lung and liver tissues, which may be

indicative of common mechanisms for the

development of DIPL. Future work includes

comparing the alterations of the metabolome in

DIPL to those in lysosomal storage diseases, which

could help to elucidate mechanisms associated with

the potential toxicity of DIPL.

POSTER 37

USING METABOLOMICS TO UNDERSTAND THE

INDUCTION OF FATTY LIVER DISEASE IN A RAT

MODEL OF HEPATOCELLULAR CARCINOGENESIS

Yajing Chu(1), Aalim M Weljie(2), Luigi Atzori(3),

Jules L Griffin(1)

(1) Department of Biochemistry, University of Cambridge,

UK (2) Department of Biological Sciences, University of

Calgary, Canada (3) Department of Toxicology, Oncology

Molecular Pathology Unit, University of Cagliari, Italy

As the most common etiology of chronic liver

disease in clinical practice in developed countries,

the pathologies of nonalcoholic fatty liver disease

(NAFLD) and the associated nonalcoholic

steatohepatitis (NASH) are rapidly increasing. It has

been demonstrated that NASH can induce the

development of further cirrhosis, including

hepatocellular carcinoma (HCC). However, the

multiple pathogenic mechanisms underlying such

pathologies are still to be fully elucidated for either

better diagnostic procedures of the disease

progression or the identification of subsequent

targets for treatment. Complementary to

conventional methods, metabolomics has

demonstrated capacity for obtaining a global view

of endogenous metabolites changes in response to

perturbations. Liver, muscle and adipose tissues

from a choline deficient (CD) diet induced NAFLD rat

model together with contrasting samples treated

with an analogue of the thyroid hormone, GC-1,

were used in this study as part of a metabolomic

approach to fatty liver disease. In order to maximise

the coverage of the metabolome, 1H nuclear

magnetic resonance (NMR) spectroscopy, gas

chromatography-mass spectrometry (GC-MS) and

ultra performance liquid chromatography-mass

spectrometry (UPLC-MS) were employed to

investigate metabolite changes from both organic

and aqueous extracts. The data generated to date

were subjected to multivariate analysis methods

including principal components analysis (PCA) and

partial least squares discriminant analysis (PLS-DA).

This demonstrated perturbations of fatty acid and

amino acid metabolism. In addition, oxidative stress

changes were also observed in the CD diet model.

POSTER 38

AN UNTARGETED METABOLIC PROFILING STUDY

OF PLASMA COMPOUNDS AFFECTED BY APPLE

INTAKE IN FASTED AND UNFASTED RATS.

Daniela Rago, Gözde Gürdeniz, Mette Kristensen

and Lars O. Dragsted


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Department of Human Nutrition, Faculty of Life Sciences,

University of Copenhagen, Frederiksberg, Denmark.

“One apple a day keeps the doctor away!?” It has

been shown that fruit consumption has preventive

effects on degenerative diseases, as, for instance

cardiovascular disease but it is not well known

which compounds might be the protective factors.

The research presented here aims, therefore, to

investigate whether raw apple possesses health

effects by identifying potential biomarkers reflecting

these properties. The study was conducted on 80

young male rats divided into three groups, controls

and two intervention groups, receiving daily 0, 5 and

10g fresh apple slices, respectively, for 13 weeks.

Among all groups, about half the animals were

sacrificed after a 12 hrs fast, the others were not

fasted. Plasma samples were taken at the end of the

intervention and analysed by Ultra Performance

Liquid Chromatography-Quadrupole/Time of Flight

mass spectrometry analysis (UPLC-qTOF). The UPLC-

qTOF raw data were converted to NetCDF files, pre-

processed by MZmine and, successively, exported to

MATLAB (MathWorks). Multivariate analysis (PCA)

was used initially to investigate whether groups

could be discriminated according to apple intake.

Univariate statistical tests (ANOVA and t-Test) and

supervised multivariate analysis (PLSDA) were used

for selection of discriminative features. By PCA a

separation between the control and the

intervention groups was observed. Among the

compounds responsible for the separation

epicatechin glucoronide was identified , a known

exposure marker of fruit intake. By univariate

analysis more than 30 markers were found with

false discovery rates below 0.05 in the unfasted

animals whereas 145 such markers were found in

the fasting state. This difference was mainly due to

larger variability in the detector response for

features in the samples from unfasted animals,

however a number of features were only significant

in the fasted or non-fasted animals. Levels of citrate

and leucine were significantly higher whereas some

free fatty acids were lower in apple-fed rats in the

fasted state as compared with controls. In the

postprandial state some compounds tentatively

identified as hydroxylated medium-chain fatty acids

were observed to be at higher plasma levels in the

apple-fed rats. Further investigations will be

performed to identify additional markers of intake

and markers related to altered health status after

consumption of fresh apples.

POSTER 39

LC-ESI-FT/MS METABOLOMIC ANALYSIS REVEALS

MOLECULAR CHANGES ASSOCIATED WITH THE

BLOOD-BRAIN BARRIER NANO-TIO2 EXPOSURE

Geoffrey Madalinski(1), Emilie Brun(2), Denis

Desoubzdanne(1), Stéphanie Oursel(1), Victor

Sabarly(1), Benoit Colsch(2), Christophe Junot(2)

and Aloïse Mabondzo(2)

(1) Profilomic, Centre du CEA Saclay, 91191, Gif-sur-

Yvette, France. (2) CEA, Direction des Sciences du Vivant,

iBiTec-S, Service de Pharmacologie et d’Immunoanalyse,

91191, Gif-sur-Yvette, France.

The ability of metabolomics to discover acute and

chronic toxicological effects of nanoparticles (NPs) is

unexplored. Among the wide diversity of

nanomaterials, titanium dioxide (TiO2) nanoparticles

are produced on a large industrial scale and can be

found in commercial products like paints and food

additives, but also in cosmetics and environmental

decontamination systems. While TiO2 NPs induced-

toxicity is well established on various cell lines few

have focused on the central nervous system. Here,

we studied the molecular responses of the in-vitro

blood-brain barrier (BBB) exposed during 4 hours

and 24 hours to 25 nm TiO2 NPs at 0, 5, 20 and 100

µg/mL. Metabolic profiles of BBB components

(endothelial and astrocyte cells) were acquired by

high resolution mass spectrometry (Orbitrap

technology) and electrospray ionization coupled to a

liquid chromatography device. Positive and negative

data sets were thus obtained. Multivariate analyses

(PCA, PLS) showed a clusterization of the smaller

concentrations (0 and 5 µg/mL) versus the higher

concentrations (20 and 100µg/mL) at 24 hours. A

discrimination was also observed at 100 µg/mL for


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the groups 4 hours and 24 hours. Analyses of

variance (ANOVA) were realized on both positive

and negative data sets. Several hundreds robust

variables were found to significantly discriminate

between concentration and time factors. The

characterization of the corresponding metabolites is

under progress.

POSTER 40

INFLUENCE OF CYCLOSPORIN A ON HEPATIC VLDL

TRIGLYCERIDE ENRICHMENT MEASURED BY 2H-

NMR ANALYSIS OF PLASMA TRIGLYCEDRIDES

Ivana Jarak, Patrícia Lopes, Ludgero Tavares,

Eugénia Carvalho, Rui C. Carvalho, John jones

The Centre for Neuroscience and Cell Biology, Coimbra,

Portugal

Cyclosporine (CsA) is an immunosuppressive agent

frequently used in the clinic for prevention of

allograft rejection and for the treatment of

autoimmune diseases(1). Despite its desired action

on the immune system, CsA treatment has been

identified as a risk factor in post-transplant

hyperlypidemia and in development of post-

transplant metabolic syndrome and new-onset

diabetes, and eventually leads to cerebro and

cardiovascular complications in transplant

recipients. Although CsA has been strongly

associated with hypertriglyceridemia little is known

about its influence on hepatic de novo lipogenesis

(DNL) and DNL contribution to the VLDL

triglycerides. Thus, 16 non-transplanted Wistar rats

were treated for 2 weeks with vehicle or 15 mg/kg

CsA (n = 8/group) by gavage administration. Under

the fasting conditions where the VLDL is the only

source of plasma TG, the rate of TG accumulation in

blood is the indicator for hepatic VLDL production

rate. The property of non-ionic detergent Pluronic F-

124 to inhibit TG hydrolysis by lipoprotein lipase and

which results in a progressive increase in the

concentration of lipids in the blood was used to

determine the rate of VLDL synthesis(2). The

contribution of DNL to the blood and liver lipid

content was evaluated using the stable isotopic

tracer (2H2O) after the IP injection of detergent

(1g/kg), followed by the analysis of isolated lipid

fractions by 1H and 2H NMR spectroscopy.3 The

fraction of DNL was estimated from TG methyl

group 2H enrichment resulting from 2H2O body

water enrichment. 2H enrichment of TG methyl

hydrogens was quantified against an internal

pyrazine–d4 standard. Significant increase in blood

TG concentrations following the detergent injection

was found in both groups of animals. Although the

hepatic VLDL synthesis rate and release was

significantly higher in CsA treated rats (25.58 ± 3.87

mg kg-1 h-1) than in the control group (13.23 ± 3.31

mg kg-1 h-1), the DNL contribution to the released

VLDL triglycerides was determined to be the same in

CsA treated (9.55 ± 3.38) and control (10.08 ± 2.31)

animals, and was found to be a good marker for the

liver DNL (control: 9.18 ± 2.21; CsA treated: 6.84 ±

1.41). The liver TG concentration was found

significantly higher in control animals (20.49 ± 5.78

mg/dl, 7.39 ± 1.10 mg/dl in CsA treated animals)

supporting the increased VLDL production rate in

the CsA treated. On the other hand, blood TG

concentrations prior to detergent injection (control:

7.91 ± 1.38 mg/dl; CsA treated: 9.62 ± 1.62 mg/dl)

suggest that VLDL TG are hydrolysed and taken up

by the tissues or remain in blood as free fatty acids. 1H NMR spectroscopy and principal component

analysis (PCA) of perchloric acid liver extracts reveal

further changes in liver metabolism. Reduced body

weight of CsA treated animals associated with

depleted glycogen pools and increased acetate

levels indicate the shift of energy related

metabolism towards keton body metabolism. CsA

treated animals showed decreased levels of

phosphocoline and glycerophosphocholine followed

by the increase of trimethylamine nitric-oxide levels.

Increased levels of alanine suggest CsA related

oxidative stress.

References: 1 Akhlaghi, F., Jackson, C.H., Parameshwar, J., Sharples,

L.D., Trull, A.K., Transplantation, 73 (2002) 1258–1264. 2 Millar, J.S.,

Cromley, D.A., McCoy, M.G., Rader, D.J., Billheimer, J.T., J. Lipid Res. 46

(2005) 2023-2028 3 Delgado, T. C., Pinheiro, D., Caldeira, M., Castro, M.

M. C. A., Geraldes, C. F. G. C., Lopez-Larrubia, P., Cerdan, S., Jones, J. G.,

NMR Biomed. 22 (2009) 310–317.


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POSTER 41

METABOLOMIC STUDY OF URINARY

INFLAMMATORY MEDIATORS BY HIGH

RESOLUTION MASS SPECTROMETRY-BASED

METHOD IN A MODEL OF CYCLOPHOSPHAMIDE-

INDUCED ACUTE BLADDER CYSTITIS

Denis Desoubzdanne(1), Stéphanie Oursel(1),

Geoffrey Madalinski(1), Christophe Junot(2), Anne-

Marie Coelho(3), Philippe Lluel(3), Bruno Corman(1)

1. Profilomic, Centre du CEA Saclay, 91191, Gif-sur-

Yvette, France. 2. CEA, Direction des Sciences du Vivant,

iBiTec-S, Service de Pharmacologie et d’Immunoanalyse,

91191, Gif-sur-Yvette, France. 3. Urosphere, 35 chemin

des Maraîchers, 31062, Toulouse, France.

Cyclophosphamide (CYP)-induced acute bladder

cystitis is a pathophysiological model of bladder pain

syndrome, a chronic clinical syndrome affecting the

urinary tract. In a first series, urinary inflammatory

biomarkers of this model in conscious female rat

were investigated. In a second series, the effects of

different analgesics or anti-inflammatory drugs

(aspirin, ibuprofen or morphine) after CYP injection

were evaluated. Adult female Sprague Dawley rats

were treated with aspirin (300 mg/kg oral),

ibuprofen (300 mg/kg oral) or morphine (3 mg/kg

subcutaneous) 5 minutes prior to a single injection

of CYP (150 mg/kg intraperitoneal). Urines were

then collected over 4 hours using metabolic cages.

The acquisition of urinary metabolic profiles was

performed by high resolution mass spectrometry

(Orbitrap technology) and electrospray ionization

fitted with a fast liquid chromatography device.

Multivariate statistical analyses (PCA, PLS-DA)

revealed obvious discriminations among the

different experimental groups. A modification of the

tryptophan metabolism was observed for CYP-

induced acute bladder hypersensitivity, as shown by

the signal decrease of metabolites such as 5-

hydroxy-tryptophan, 3-indole-acetic acid and

homovanillic acid. Cyclic-AMP and N-acetyl-cysteine

were also found to be affected by the CYP induction.

Morphine treatment was the most effective to

reverse signal responses of specific metabolites,

such as cyclic-AMP or 6-hydroxymelatonin. In

summary, significant alterations were detectable in

some urinary metabolites of an experimental model

of CYP-induced acute visceral cystitis using high

resolution Fourier transform mass spectrometry.

Some of these alterations were reversed by two

non-steroidal anti-inflammatory drugs or morphine

treatments, showing that these metabolites could

be considered as interesting biomarkers of visceral

hypersensitivity in this experimental model.

POSTER 42

NMR-BASED STABLE ISOTOPE PROFILING [U-13C]

ACETATE INCORPORATION INTO HEPG2 LIPIDIC

METABOLISM

Sara Samino(1), Miguel A. Rodríguez(1), Maria

Vinaixa(1), Xavier Correig(1), Cinta Bladé(2)

1. Metabolomics Platform, CIBER de Diabetes y

Enfermedades Metabólicas Asociadas (CIBERDEM), IISPV,

Universitat Rovira i Virgili, Avda. Països Catalans 26,

43007 Tarragona, Spain. 2. Department of Biochemistry

and Biotechnology, Universitat Rovira i Virgili, Avda.

Països Catalans 26, 43007 Tarragona, Spain.

Metabolomics enables high-throughput

interrogation of low molecular weight compounds

present biological samples. However, most of the

current work deals with static views of metabolite

rearrangements produced upon a certain effect. The

steady-state profiling of metabolites does not

provide information on fluxes through metabolic

networks. Stable isotope labeling based studies

allow a dynamic view of changes and

transformations of metabolites. Isotopomer

distribution information related to the incorporation

of different labeled positions is an advantage of

NMR stable isotope tracing studies. Besides, NMR

encompasses a global metabolic profiling in complex

mixtures such as cell cultures. Thus, in order to

study hepatocyte lipidic metabolism, we performed

NMR [U-13C] acetate tracing of the de-novo lipidic

synthesis in HepG2 cell cultures. HepG2 cells were

grown to 70 % confluence in DMEM supplemented

with 10% FBS. After confluence, 4mM of [U-13C]


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acetate was added. Cultures were subsequently

extracted after 0, 5, 24 and 29 hours acetate

addition. A biphasic extraction (CHCl3/MeOH/H2O)

(2:1) was performed. Lipidic fraction was dried

under N2 stream and pellets were reconstituted in

deuterated solvents (CDCl3/MeOD) (2:1) to futher

NMR analysis. 1D NMR spectra were recorded on

cell extracts at 310 K on a Bruker Avance III 600

spectrometer operating at a proton frequency of

600.20 MHz using a 5 mm CPTCI triple resonance

(1H, 13C, 31P). Besides, 2-D NMR editing experiments 1H{13C}-HSQC, 1H{13C}-HMBC, 1H{13C}-HMQC and 13C–13C INADEQUATE were also acquired. A preliminary

study of 1D 13C NMR-lipidic pattern demonstrates

not only the incorporation of [U-13C] acetate to fatty

acids but also to cholesterol. Further work is in

progress to elucidate and determine positional

isotopomers distribution of metabolites identified in

the 2D NMR experiments. This would form the basis

to metabolic flux modeling.

POSTER 43

CAN METABOLOMICS BE USED TO IDENTIFY NEW

MARKERS OF HEPATIC INSULIN RESISTANCE?

Erik Wahlström(1), Kamal Yassin(1), Claes-Göran

Östensson(1), Gunnar Norstedt(1), Johan

Lindberg(2) and Petra Tollet-Egnell(1)

1. The Department of Molecular Medicine and Surgery,

Karolinska Institute, Stockholm, Sweden 2. Molecular

Toxicology, Safety Assessment, Astra Zeneca R&D,

Sweden.

Various challenges such as high-fat feeding, toxins,

viral infections or surgery-induced metabolic

overload can induce the formation of reactive

oxygen species within the liver and lead to insulin

resistance. Since hepatic insulin resistance is

associated with an increased risk of developing

metabolic disorders, such as diabetes and the

metabolic syndrome, a non-invasive serum-based

diagnostic marker for fatty liver and/or hepatic

insulin resistance is much sought after. The aim of

the present study was to explore the utility of 1H-

NMR-based metabolite profiling on rat liver

perfusates in the search for new markers of hepatic

insulin resistance. Three days of high-fat feeding in

Sprague-Dawley rats (hf-SD) lead to increased

accumulation of hepatic triglycerides and increased

expression of Nrf2-regulated genes, indicating

increased activity of the antioxidant response

pathway, as compared to rats fed regular chow (c-

SD). Insulin responses within the liver were altered

as assessed by transcript profiling and quantitative

RT-PCR analysis. Furthermore, when liver enzymes

were analysed in rat liver perfusates, an insulin-

dependent increase in aspartate aminotransferase

(AST) and lactate dehydrogenase (LDH) was

observed in hf-SD, but not in c-SD. The most

abundant liver-derived metabolites (1 - 500 µM)

were next quantitated with 1H-NMR and Chenomx

NMR Suite followed by uni- and multivariate

analysis. Many of the metabolites identified in liver

perfuastes from hf-SD were increased in reponse to

insulin, whereas the opposite effect was observed in

c-SD. After correcting for this systematic effect, we

identified several metabolites with differential

responses to insulin treatment for the two diets.

Among those, betaine, glucose, histidine, lactate,

leucine, succinate and threonine were identified by

uni-variate statistics. Multivariate analysis further

identified groups of metabolites that differentiated

the treatment groups. Betaine and acetoacetate

differed the most between hf-SD and c-SD, in the

absence (3.1-fold) and presence (7.6-fold) of insulin,

respectively. We conclude that three days of high-

fat feeding in rats lead to impaired insulin-

dependent suppression of hepatic glucose output, in

line with previous reports. Novel effects of insulin

on liver-derived enzymes and metabolites were

discovered, and many of these were different

between rats fed regular or high-fat diets.

Metabolite profiling of liver perfusates can be used

to increase our understanding of the development

of fatty liver and insulin resistance. 1H-NMR was

effectively used to quantify several metabolites

relevant to the energy metabolism, but orthogonal

MS-based techniques should be used to further

clarify the picture.


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POSTER 44

MULTIPLEX PROFILING OF BOAR TAINT BY

NONTARGETED METABOLOMICS

Malin Olson(1), Endre Laczko(2), Fraser Lewis(3),

Silvia Ampuero(4), Giuseppe Bee(4), Hanspeter

Naegeli(1)

1. Institute of Veterinary Pharmacology and Toxicology,

Zurich, Switzerland. 2, Functional Genomics Center

Zurich, Zurich, Switzerland. 3. Institute of Veterinary

Epidemiology, Zurich, Switzerland. 4. Agroscope

Liebefeld-Posieux, Posieux, Switzerland.

In many countries, male piglets are castrated shortly

after birth because a proportion of un-castrated

male pigs produce meat with an unpleasant odor

and flavor. Main compounds held responsible for

boar taint are androstenone, skatol and indole.

However, there are indications that some other

factors could be involved in causing boar taint, since

a significant portion of tainted pigs cannot be

explained solely by their levels of androstenone,

skatol and indole. Indeed, the level of these

compounds correlates badly with results from

classical sensory panels. The aim of this nontargeted

metabolomics study was, therefore, to identify new

biomarkers in the adipose tissue of male pigs that

are highly correlated with the appearance of boar

taint determined in an earlier sensory panel

analysis. The adipose tissue from 16 non-tainted and

16 strongly tainted pigs, divergent for

androstenone, skatol and indole concentration, was

homogenized together with methanol prior to a

solid-phase extraction using a C-18 sorbent material.

The extracts were then analyzed using a nano-UPLC-

ESI-QTOF-MS system. This new high-resolution

technology (HDMS) allowed us to monitor up to

40,000 different masses, with an accuracy of 0.2

mDa. The Masslynx raw data files were processed

using MarkerLynx software (Waters, Inc., Milford,

MA) and multivariate data analysis was performed

using SIMCA-P+ 11 (Umetrics AB, Umeå, Sweden)

Preliminary results confirm that a metabolic pattern

can be used to distinguish between non-tainted and

tainted pigs. Exactly what metabolites are

responsible for these differences is currently being

investigated. This metabolomics strategy presents a

unique opportunity to explore the biological

mechanisms underpinning boar taint and supports

further efforts in the development of a fast and

effective biomarker-based assay for the

identification of affected animals before and after

slaughter.

POSTER 45

COMPREHENSIVE METABOLOMIC PROFILING OF

ZUCKER RAT PLASMA USING LC AND GC ULTRA

HIGH RESOLUTION TIME-OF-FLIGHT MASS

SPECTROMETRY AND GCXGC-TOFMS.

Jürgen Wendt(1), Jeffrey S. Patrick(1); Kevin Siek(1);

Joe Binkley(2)

1. LECO Instrumente GmbH, Mönchengladbach,

Germany. 2. LECO Corporation, St. Joseph, MI, USA

Rodents represent a common model animal used in

studying disease. UHPLC and GC are combined with

high resolution time-of-flight mass spectrometry

and utilized in the comparative analysis of

metabolomic profiles of plasma from three strains

of Zucker rats. Specifically, metabolite profiles for

lean, obese, and fatty animals are differentially

compared and statistically-significant features are

identified. Differences in profiles for amino acid,

ketone bodies, lipids and carbohydrates were

observed. UPLC with ESI was utilized for non-volatile

analyte identification. GC with EI ionization provided

data on volatile and semi-volatile analytes after

analyte derivatization. Protein was removed by

acetonitrile precipitation or size-based filtration.

Samples were analyzed at acquisition rates up to 40

spectra/s. The high speed acquisition capability

facilitates faster analysis times for serum

metabolomics with little compromise to coverage.

The benefit of the complementary nature of the GC

and LC data from high resolution MS are clearly

demonstrated. Metabolites in the plasma from

three phenotypes of Zucker rat were analyzed by a

battery of complementary techniques which

included GC and LC with high resolution (HRT) MS


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detection, GCxGC with TOFMS detection. LC-HRT

identified several compounds and compound classes

which changed in correlation with the phenotype.

These included acyl carnitines and amino acids,

among others. GC-HRT and GCxGC-TOFMS provided

the identification of additional compounds from the

same and related compound classes. These include

short chain fatty acids, fatty acids, glycerol, amino

acids and monosaccharides. Each of these showed a

unidirectional change from Lean to Fatty to Obese.

Each of these analytes also has a physiological

relationship to fat and lipid processing. The high

performance mass spectrometry provided typical

mass accuracies of less than 1 ppm and resolving

power of approximately 50,000 above 600 m/z. The

combination of these complementary techniques

provided a set of related but complementary

metabolites and indicate the increased information

content offered by this approach.

POSTER 46

EVALUATION OF THE IMPACT OF FOOD AND TIME-

OF-DAY ON PLASMA METABOLITES IN A MOUSE

MODEL USING LIQUID CHROMATOGRAPHY-MASS

SPECTROMETRY (LC-MS)

Joo Ern Ang(1), Alan Henley(1), Victoria Revell(2),

Debra J. Skene(2), Florence Raynaud(1)

1. Cancer Research UK Cancer Therapeutics Unit,

The Institute of Cancer Research, Sutton, SM2 5NG,

UK. 2. Chronobiology, Faculty of Health and Medical

Sciences, University of Surrey, Guildford, GU2 7XH,

UK

Background: LC-MS metabolomics offers high levels

of sensitivity and specificity in plasma metabolite

profiling, has potential in pharmacodynamic marker

discovery and can accelerate the development of

novel therapies. Clinical translation of a

metabolomic approach in this context presents

unique challenges. Studies of novel

pharmacodynamic markers in early phase clinical

trials require treated individuals to be their own

control but the plasma metabolome is known to

sensitively reflect changes in the organism’s internal

homeostatic and circadian systems, as well as

external influences such as food and disease. In this

study, we used a global, untargeted approach in a

NCr mouse model kept under normal light/dark

(L/D) conditions and identified plasma metabolites

that vary significantly with time of day and food

availability. Methods: Seven time-points (06:00h,

08:00h, 12:00h, 18:00h, 21:00h, 24:00h and 30:00h

(06:00h of day 2)) were assessed (each with four

biological replicates) over a 24-hour period (12:12

LD, lights on 07:00h) in two groups of NCr-nu/nu

mice: one fed ad libitum and the other food-

deprived for six hours prior to plasma sampling.

Samples were prepared using methanol/ethanol-

liquid phase extraction prior to injection into a

Waters Micromass UPLC-QTOF Premier system.

Data alignment, peak detection, quantification of

features and modelling of discrimination between

time-points were as previously described [1].

Cosinor analysis by the method of least squares

(period of 24h) was used to derive estimates of

amplitude, acrophase time, mesor, rhythm and p-

value. Thresholds for a good fit were rhythm≥0.7

and p<0.05 [2]. Results: Overall, 176 (13%) out of a

total of 1337 detected metabolite features exhibited

significant fluctuations across time-of-day. In 76 ions

oscillations were detected with a median amplitude-

mesor ratio of 25% (range 1.2-81%), indicating the

presence of significant diurnal variability. Of these,

the rhythmicities of 63 ions were dampened in

either the fed or fasted condition. A further 100

metabolites exhibited significant fluctuation across

time of day (p<0.05) but the temporal patterns did

not regress well to a cosinor function (rhythm <0.5).

Of these, 8 fluctuated significantly under fed and

fasted conditions, 55 under the fasted condition

only, and 37 under the fed condition only. The

identified ions (via MS/MS studies coupled to online

database searches) are chemically diverse, and

include amino acids and phospholipids (e.g.

lysophosphatidylcholines and

lysophosphatidylethanolamines). Finally, these data

were in agreement with previously published data

[3]. Conclusions: Novel 24h oscillatory plasma

metabolites and the impact of food on them were


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characterised in a mouse model using a LC-MS

platform.

References: [1] J Chromatogr B 2009; 877(13): 1352-8. [2]

Chronobiologia 1979; 6: 305-23. [3] PNAS 2009; 106(24): 9890-5.

POSTER 47

A TECHNOLOGICALLY DESIGNED DAIRY-FAT

IMPROVED THE ATHEROGENIC OUTCOME IN

HAMSTER AND IS RELATED TO A SPECIFIC

METABOLOMIC SIGNATURE

Jean-Charles Martin(1), Daniel Dalemans(2), Bernard

Poullain(3), Bernadette Delplanque(4), Romain

Bott(1), Nathalie Banzet(1)

1. Plateau BioMeT, Nutrition Lipidiques et

Prévention des Maladies Métaboliques, Marseille,

France. 2. Société Corman, Liège, Belgium. 3.

Groupe Bongrain, Versailles, France. 4. NMPA,

Orsay, France

Introduction Cholesterol and saturated fatty acids in

dairy fats are frequently accused to promote

atherosclerosis. Dairy fats can be technologically

designed to improve health outcome. Objective We

evaluated the atherogenicity of various fat designs.

We also hypothesized that the atherogenic potential

of edible fats can be ‘read’ as a metabolic signature.

Method/Design Hamsters were fed for 12 weeks

high fat diets (60% energy as fat): standard butter

(G9), standard butter with 50% plant oil mix (G10),

decholesterolized G10 (G12) , G9 with 50% canola

(G11), decholesterolized/desaturated butter (G13),

G13 with 50% plant oil mix (G14), native palm oil

with 30% canola (G16). The severity of

atherosclerosis was determined by the cholesteryl

ester deposition in the aortic tree. Fatty acid

analysis was performed in each plasma lipid classes

and liver total lipids. LCMS metabolomics was

performed on plasma and urines. Results The

standard butter (G9) induced the greatest

atherogenic outcomes ( P < 0.05) , and the plant oil

mix (G16) the least ( P < 0.05). The

decholesterolized/desaturated butter (G13)

exhibited the lowest atherogenic severity among

the dairy fats (P < 0.05; 1.9 fold less than the

standard butter (G9)). Among the 124 diagnostic

fatty acids used, a subset of 46, almost all in plasma,

were especially predictive of atherosclerosis

(prediction value of 65%), except for hamsters

receiving the G13-diet. LCMS metabolomics was

comparatively better to predict the dietary influence

of all diets on the atherogenic outcome, especially

in urines samples. Conclusion Decholesterolization /

desaturation of dairy fat bring a clear atherogenic

benefit. Fatty acid profiling coupled with

multivariated statistical methods permit to predict

atherogenesis to some extent, whereas a

metabolomic fingerprinting was of better accuracy.

The predicting LCMS analytes are currently being

determined in a biomarker perspective.

POSTER 48

METABOLIC PROFILING OF BRAIN TISSUE OF THE

DOUBLE-TRANSGENIC APPSWE/PS1∆E9 MURINE

MODEL OF AMYLOIDOSIS.

Philippine C Geiszler (1,3) Nazia Maroof(2), Marie-

Christine Pardon(2), David A. Kendall(2), Dorothee P.

Auer(1), Clare A. Daykin(3)

1. Division of Radiological and Imaging Sciences, School of

Clinical Sciences, 2. School of Biomedical Sciences, 3.

School of Pharmacy, University of Nottingham, UK.

INTRODUCTION and MOTIVATION. Alzheimer's

disease (AD) is the most common form of dementia

[1]. Current research focuses on early disease stages

to support the development of treatment strategies

decelerating neurodegenerative processes in AD.

APP/PS1 transgenic mice model early-onset familial

AD by exhibiting age-dependent amyloid-β

accumulations, astrocytosis and dystrophic

modifications of cortical, hippocampal and striatal

neurons in the brain as well as cognitive

impairments that are relevant to AD [2-7]. Since

these models of amyloidosis do not show gross

neuronal cell loss [2], they may offer a possibility to

investigate metabolic pathologies preceding overt

neurodegeneration and, hence, aid the search for

markers indicating AD onset and progression. To


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support the search for a biomarker of early

pathologies in AD, this metabolic profiling study

aimed for the investigation of the cerebral

metabolism of the double-transgenic

APPswe/PS1∆E9 mouse model. This study (i)

screened for biochemical markers to highlight

metabolic alterations that are linked to beginning

amyloidosis. (ii) assessed the potential of μ-inositol

levels (indicative of astrocytosis) as predictor of

genotype membership in early amyloid pathology.

This was proposed by Chen et al. [8] who examined

the cerebral metabolism under the influence of the

APPswe/PS1∆E9 mutation using in vivo MR

spectroscopy. (iii) tested whether the concentration

of the neuronal marker N-acetylaspartate decreased

in this model, as seen in AD. METHODS. The cortex,

hippocampus, striatum and cerebellum were

collected from APPswe/PS1∆E9 (tg) and control (wt)

mice which were sacrificed at 4, 6 (female and male)

and 8 (male only) months of age. At these ages,

early amyloid deposition and cognitive deficits have

been reported [2,7]. The number of animals was 7-

10 per genotype-, sex- and age-group. 1H NMR

spectra were acquired from methanolic extracts

using a standard 1D sequence with water

suppression (Bruker Avance, 600 MHz, PABBO BB

probe). The bucketed spectral data was assessed by

pattern recognition analysis methods, including

principal component analysis (for the data

overview) and PLS discriminant analysis (to

investigate genotype differences). Due to the

occurrence of post-mortem degradation effects in a

sample sub-set (“B”), metabolic profiles were

created for this data set separately from unaffected

samples (“A”). Unlike in the sub-set B, all age and

sex sub-groups were pooled in data set A for its

relatively small total sample size (n=17 per brain

region). Signals of the metabolites N-acetylaspartate

plus acetate (indicative of the maximum N-

acetylaspartate levels in vivo), μ-inositol and

glutamine were quantified from A and the total data

set, and tested for genotype differences using the

Mann-Whitney U test. RESULTS (i) The metabolic

profiles established for all brain regions and age

groups were not specific to the APPswe/PS1∆E9

mutation. However, reduced glutamine levels (p <

0.001) were found in the cortex of the transgenic

animals compared to the controls (using subset A).

(ii) The concentration of μ-inositol was not

indicative of the APPswe/PS1∆E9 mutation at 4, 6

or/ and 8 months of age. (iii) N-acetylaspartate plus

acetate levels did not differ between transgenic and

wild-type samples. DISCUSSION. These results were

in clear contrast to previous preclinical studies

which had shown that the metabolic profiles of

APP/PS1 mutants differed from wild-type results in

vivo, including an N-acetylaspartate reduction and a

µ-inositol increase [8-10], as found in AD.

Specifically, the proposition that an age-related µ-

inositol increase would classify the animals by their

genetic background (APPswe/PS1∆E9 vs. wild-type)

with 82, 94 and 95% accuracy at 3, 5 and 8 months,

respectively [8], could not be confirmed by the

present data. The discrepancy may lie in the analysis

(e.g. the definition of the µ-inositol signal) and/ or

sample preparation (alive organism vs. tissue

extract). Disagreeing with the results by Chen et al.

[8] are also studies of other APP/PS1 mutants that

reported decreased µ-inositol levels in 3-month old

mutants which normalised with increasing age [9]

and statically higher µ-inositol levels in APP/PS1

mutants irrespective of their age [10]. This raises the

question of the significance of µ-inositol as marker

of glial activation in this model [8], since widespread

gliosis has not been shown in APP/PS1 mutations at

this age [3,11]. Normal N-acetylaspartate levels in

the APPswe/PS1∆E9 mice of the present study may

be explained by their age [12] or the post-mortem

degradation processes that occurred in the samples

of the present study. Besides the N-acetylaspartate

and µ-inositol findings, the glutamine reduction in

the cortex is relevant, given that altered

glutamatergic neurotransmission – which may be

represented by glutamine quantities [13] – has been

reported for AD [14-17]. CONCLUSION. The results

of this study did not support the proposition that

early amyloid deposition is reflected by gross

changes of the metabolic profiles as determined by

NMR spectroscopy based metabolic profiling.

However, alterations of the glutamatergic


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neurotransmission appeared possible in the

APPswe/PS1∆E9 model. These results require

confirmation as the presence of post-mortem

degradation effects could not be excluded.

References: [1] Alzheimer's Association (2010) www.alz.org, [2] Manaye

et al. (2007) Age, [3] Howlett et al. (2004) Brain Res, [4] Liu et al. (2008)

J Neurosci, [5] Richner et al. (2009) Brain Res, [6] Rattray et al. (2008)

Behav Brain Res, [7] Bonardi et al. (2011) Behav Brain Res, [8] Chen et

al. (2009) Dement Geriatr Cognit Disord, [9] Oberg et al. (2008)

Neurobiology of Aging, [10] Forster et al. (2010) Proc. Intl. Soc. Mag.

Reson. Med. 18, [11] Maheswaran et al. (2009) Brain Res, [12]

Marjanska et al. (2005) PNAS, [13] Kanamori et al. (2002) J Neurochem,

[14] Lin et al. (2003) Magma Magn Reson Mater Phys Biol Med, [15]

Hattori et al. (2002) Neuroreport, [16] Moats et al. (1994) Magn Reson

Med, [17] Antuono et al. (2001) Neurology.

POSTER 49

CORRELATION OF CYTOCHROME P450 MRNA

EXPRESSION AND METABONOMIC PROFILES TO

IDENTIFY ENDOGENOUS BIOMARKERS OF

INDUCTION IN RAT

Perrine Masson(1), Vincent Croixmarie(2), Catherine

Spire(3), Claire Boursier-Neyret(2), Olivier

Cloarec(4), Jeremy K. Nicholson(1), Elizabeth J.

Want(1)

1. Biomolecular Medicine, Imperial College London, UK.

2. Technologie Servier, Orleans, France. 3. Biologie

Servier, Gidy, France. 4. Korrigan Sciences Ltd,

Maidenhead, UK.

Early determination of the impact of a new drug

candidate on cytochrome P450 (CYP)-mediated

metabolism is crucial during drug development, as

CYP induction or inhibition can alter the exposure of

co-administered drugs. In addition to drug

metabolism, CYPs act on many endogenous

metabolites and are regulated by nuclear receptors

involved in biochemical pathways. Metabonomics,

which enables the determination of urine and

serum metabolic fingerprints, could therefore

represent a powerful tool to assess CYP expression.

We have investigated the effect of phenobarbital, a

well-known CYP-inducer, on rat CYP and

endogenous metabolic profiles, with the aim of

discovering early metabolic biomarkers of

cytochrome P450 induction. Phenobarbital (80

mg/kg/day) was administered intraperitoneally to

20 male and 20 female Wistar rats for one or four

days. Livers were collected for CYP quantification

and metabolic profiling, and urine and serum were

collected at three time points for metabolic

profiling. 81 CYP isoforms were quantified at the

mRNA level by quantitative real time polymerase

chain reaction (qRT-PCR) and CYP-related activities

were measured for isoforms 1a1/2, 2b1, 2d1, 2e1

and 3a1/2 in microsomal incubations with specific

substrates. Urine, serum and liver metabolic profiles

were established by UPLC-MS with untargeted

methods and methods targeting triglycerides and

fatty acids, and multivariate techniques, such as

principal components analysis (PCA) and orthogonal

projection to latent structures (OPLS), were used to

analyze the resulting data. At the mRNA level, a

marked induction by phenobarbital was observed

for CYPs 2b1, 2b2, 3a1 in both genders and for Cyp

2a3a in females only. Induction was also observed,

to a lesser extent, for CYPs 3a2, 2c22, 2c37 and 51,

while mRNA levels of CYPs 8b1, 17a1 and 4a1 were

reduced. In addition, activities of CYPs 2b1, 1a1/2

and 3a1/2 were induced by phenobarbital. PCA of

urine metabolic profiles resulted in a clear

separation between control and dosed animals,

illustrating differences in endogenous metabolic

profiles between both groups. Integration of

metabolic profiles together with CYP profiles was

then performed via OPLS-based approaches and

allowed identification of metabolite features linked

to CYP induction. These promising findings show

the potential of metabonomics to identify

endogenous biomarkers of CYP induction in a non-

invasive manner.

POSTER 50

METABONOMIC FINDING OF SERUM BIOMARKER

RECOVERABLE BY CONSUMPTION OF FERMENTED

AND GREEN TEAS IN HIGH-FAT DIET INDUCED

OBESE MICE

Bum-jin Lee(1), Hyun-Jung Shin(1), Jin-Oh Chung(1),

Hae-Young Hong(2), Eun-Hee Kim(2), Kwan-Soo

Hong(2), Sang-Jun Lee(1), Young-Shick Hong(3)


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1 Health and Science Research Institute, AmorePacific

R&D Center, Yongin-si, Gyeonggi-do 446-729, Republic of

Korea. 2. Division of Magnetic Resonance, Korea Basic

Science Institute, Cheongwon 363-883, Republic of Korea.

3. School of Life Science and Biotechnology, Korea

University, Seoul 136-701, Republic of Korea.

In order to determine the anti-obesity effects of

both fermented and green teas in diet-induced

obesity, perturbations of serum metabolites in a

high-fat diet (HFD) induced obese mice were

investigated through 1H NMR-based metabolomic

approach. Male obese mice were given a HFD plus

fermented tea (FT) and green tea (GT), separately,

at the dose of each 400 mg extract/kg of body

weight for 8 weeks. Both teas significantly reduced

body weight gain by 22% compared to the HFD

group. Multivariate statistical modeling of 1H NMR

serum spectra revealed that normal diet and HFD

groups were clearly differentiated on pattern

recognition methods such as principal component

analysis (PCA) and orthogonal partial least square

(O-PLS) models and major metabolites responsible

for the differentiation were mainly identified as lipid

metabolites. Serum glycerophospholine, choline,

and many lipoprotein subclasses levels were

elevated in the HFD induced obese mice,

demonstrating that the HFD causes to fat

accumulation via reduced β-oxidation. Moreover,

interestingly, specific subclass of the lipoprotein

subclasses elevated by HFD were significantly

decreased both in obese mice who consumed

extracts of FT and GT, consistent with a reduction in

hepatic triglyceride levels. This indicated that a

distinct lipid metabolism in liver would be

differently influenced by tea consumption and used

as a potential biomarker to assess an effect of

biologically active or functional compound on

obesity.

POSTER 51

METABOLIC DISRUPTION IN MALE CD-1 MICE

PERINATALLY EXPOSED TO LOW DOSES OF

BISPHENOL A (BPA)

Cécile Canlet(1), Marie Tremblay-Franco(1), Nicolas

J. Cabaton(2), Perinaaz R. Wadia(3), Jean-Pierre

Cravedi(2), Roselyne Gautier(1), Jérôme Molina(1),

Beverly S. Rubin(3), Ana M. Soto(3) and Daniel

Zalko(2)

1. Axiom-Metatoul INRA, UMR 1331 TOXALIM

(Research Center in Food Toxicology); 180 Chemin

de Tournefeuille, F-31027 Toulouse, France. 2.

Xenobiotic Metabolism Team (MeX), INRA, UMR

1331 TOXALIM (Research Center in Food

Toxicology); 180 Chemin de Tournefeuille, F-31027

Toulouse, France. 3. Tufts University School of

Medicine, 136 Harrison Avenue, Boston (MA) 02111,

USA.

BPA is a well-known endocrine disruptor used to

manufacture polycarbonate plastics and epoxy

resins. Exposure of pregnant female rodents to low

doses of BPA results in pleiotropic effects in

offspring. Alterations in body weight, mammary

gland development, reproductive tissues and

hypothalamus have already been reported in

offspring exposed perinatally to BPA. The use of

metabolomics to examine metabolic shifts induced

in vivo by endocrine disruptors is expected to

contribute to a better understanding of their

capability to disrupt metabolic pathways, with

possible consequences in adult life. In this study, we

examined the ability of perinatal exposure to low

doses of BPA to affect global metabolism in CD1

male mice. Pregnant CD1 mice were exposed to 50%

DMSO (vehicle-control), 25 ng, 250 ng or 25 µg

BPA/kg BW/day, from the afternoon of gestational

day 8 through post-natal day (PND) 17. F1 males (n=

11 to 20- 1 male per litter) were killed on PND2 or

PND 21. PND2 newborns (whole body), livers and

brains from PND21 pups were extracted. Serum

samples and aqueous extracts were submitted to 1H

NMR spectroscopy. NMR spectra were phased and

baseline corrected, and data were reduced to

integrate 0.01 ppm wide regions within the 10.0-0.5

ppm region. NMR data were analyzed by

multivariate statistical methods. First, data were

filtered using OSC method to remove variability not

correlated to the treatment. PLS-DA was then


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applied to attempt to discriminate groups according

to the level of BPA exposure through the perinatal

period. Then, VIP (Variable Importance in the

Projection) and Kruskal-Wallis test were used to

determine what variables were responsible for the

discrimination between groups. The results

obtained from PND2 extracts demonstrated a clear

distinction between the control group and BPA-

exposed groups. These results strongly suggest a

modulation of global metabolism in the exposed

animals. Likewise, for PND 21 pups, statistical

analyses were able to successfully discriminate

between the control group, and the 250 ng and the

25 µg BPA/kg BW/day groups (based on serum and

aqueous liver samples). Moreover, the results of the

analysis of brain extracts showed a good

discrimination between all 4 experimental groups.

Taken together, our results suggest that low doses

of BPA may disrupt global metabolism in perinatally

exposed CD1 mice. These findings could be related

to a disruption of energy, glucose and amino-acid

metabolism.

POSTER 52

A MATHEMATCAL MODEL OF METABOLISM AND

AUTOIMMUNE RESPONSE IN PROGRESSION TO

TYPE 1 DIABETES

Tijana Marinković, Marko Sysi-Aho, Matej Orešič

VTT Technical Research Centre of Finland, Tietotie 2,

Espoo, P.O. Box – 1000, 02044 VTT, Finland

Recent studies have shown that autoimmunity

protects against damages on the central nervous

system (CNS). Also, studies on pre-diabetic children

and non-obese pre-diabetic (NOD) mice support the

hypothesis that metabolism and immune response

are interconnected in the early stages of T1D

progression. We develop a model which aims to

describe interaction between the metabolism and

the immune system in the early stages of T1D. It is

assumed that beta cell loss follows two paths: a self

perpetuating “negative” degenerative path of loss

and an autoimmune-induced “positive” path of loss.

The “negative” path of loss in the model is

presented by the Copenhagen model, a pathogenic

model of insulin dependent diabetes mellitus. The

“positive” path of loss is represented by a protective

metabolic pathway which is associated with the

seroconversion to autoantibody positivity. The

autoimmune-induced loss is triggered by the self-

perpetuating loss through activation of a danger

signal and the autoimmune response. The two paths

of loss are competing with each other leading to

termination of the self perpetuating path of loss and

further to elimination of the danger signal and the

autoimmune response. As a consequence the

autoimmune induced path of loss will be terminated

as well and the beta cell loss will be minimized. The

profile of the protective metabolic pathway is

simulated by comparison with pancreatic islet

metabolomics data on metabolites of the central

carbon metabolism (e.g. TCA cycle metabolites)

from non-obese pre-diabetic (NOD) mice. The

profile of beta cell mass is simulated by comparison

with data of glucose levels from NOD mice. An

additional part of the model which connects the

beta cell mass with glucose levels is developed

because of lack of beta cell mass data. The profile of

the autoimmune response is then obtained with the

parameters which are set by simulated protective

metabolic pathway and beta cell mass profiles. The

aim of our model is to survey the hypothesis that

the rate of beta cell loss depends on the amplitude

and timing of autoimmune response.

POSTER 53

CHARACTERIZATION OF RENAL CRYSTALLINE

DEPOSITS IN RAT TOXICITY STUDIES USING NMR,

LC/MS AND MALDI MS IMAGING.

Benita Forngren(1), Anna Nilsson(2), Sivert

Bjurström(1), Ingela Gustafsson(1), Jesper Lind(1),

Elisa Basmaci(1), , Håkan Andersson(1), Anita

Annas(1), Alexander Svanhagen(1), Per Andren(2),

Johan Lindberg(1)

1. Molecular Toxicology, Safety Assessment, AstraZeneca

R&D Södertälje Sweden. 2. Medical Mass Spectrometry,

Pharmaceutical Biosciences, Uppsala University, Sweden.


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A 7-day dose finding study in Wistar rats, where the

rats were administered with a discovery compound,

resulted in kidney toxicity showing crystals deposits

in the tissue. Rats administered with vehicle served

as controls. One hypothesis was that toxicity was

caused by precipitation of the metabolite

bisulphonamide which is formed by hydrolysis of the

parent compound, while other ideas were also

considered. The chemical identity of these crystal

deposits was determined by a combination of

analyses using nuclear magnetic resonance (NMR),

liquid chromatography/mass spectrometry (LC/MS)

and matrix- assisted laser desorption ionization

mass spectrometry imaging (MALDI MSI). Analysis

was performed by extraction of kidney tissue,

manual dissection of precipitated crystals from

kidney tissue sections and MALDI MSI of kidney

sections. Analysis of crystals that were dissected

directly from kidney sections and analyzed with

LC/MS and NMR, clearly showed that the crystals

contained bisulfonamide in all investigated samples.

In addition, frozen kidney sections analyzed by

MALDI MSI also showed a correlation between

crystal deposits and bisulfonamide detected at m/z

(mass to charge ratio) 234.98 directly on tissue

sections. A few other compounds detected in MSI

analysis, might serve as potential biomarkers as

their distribution correlated well with kidney

pathology . Structure elucidation on one of those

compounds was performed by running LC/MS/MS.

The results from the present study shows that, in

addition to confirming identity of crystal deposits,

the direct and in situ identification of endogenous

compounds by MALDI MS imaging can add critical

pieces of in vivo biological information and provide

potential biomarkers.

POSTER 54

URINE METABOLOME OF PRETERM NEONATES

WITH TREATMENT OF ANTIBIOTICS

Pingping Jiang(1), Thaer Berri(2), Michael Ladegaard

Jensen(2), Jan Stanstrup(2), Jennifer Man-Fan

Wan(1), Lars Ove Dragsted(2), Per T. Sangild(1)

1. School of Biological Sciences, The University of Hong

Kong, Hong Kong, P.R. China; 2. Department of Human

Nutrition, Faculty of Life Sciences, University of

Copenhagen, Frederiksberg, Denmark

Antibiotics (AB) treatment is commonly used to

prevent and treat necrotizing enterocolitis (NEC), a

severe microbiota-dependent gut disorder in

preterm infants. We hypothesized that reduced

bacterial colonization following AB treatment of

newborns would be reflected in the nature of the

urine metabolome and thus, reveal biomarkers of

NEC. Methods: Preterm pigs, used as infant models,

were given control treatment (n=13) or broad-

spectrum antibiotics (n=11) just after birth by

caesarean section. After five days, the gut was

collected and the metabolite profile of urine was

analyzed with ultra-performance liquid

chromatography-mass spectrometry. Potential

biomarker metabolite candidates were identified

based on mass spectral information and verified

with commercial chemical standards. Results: AB

treatment prevented NEC development, relative to

control (0/11 versus 11/13, P<0.001), and had

significant effects on the urine metabolome

(principle component analysis). Among the

candidate metabolites, 2-aminoadipic acid (a

possible lysine oxidation product), 3-methyladipic

acid (a metabolite of the catabolism of phytanic

acid), pimelic acid (a dicarboxylic fatty acids),

phenylacetylglycine (a metabolite of fatty acids), 3-

phenyllactic acid (an intermediate in phenylalanine

metabolism) showed decreased level in the urine

from the antibiotic-treated pigs. Conversely,

hydroxykynurenine (involved in the tryptophan

catabolism pathway) showed elevated level in the

AB pigs. Conclusion: The close connection among

the AB treatment, the presence of NEC disease, and

the identified urinary metabolites, make it possible

to use the urine metabolome in the search for

biomarkers of NEC progression in preterm neonates.

More research is required to understand how the

affected metabolites relate to gut microbial

colonization and NEC pathology.


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POSTER 55

MULTICOMPARTMENTAL LC-Q-TOF-BASED

METABONOMICS AS A TOOL TO IDENTIFY NOVEL

FUNCTIONAL PROPERTIES OF NUTRIENTS

Mariona Jové(1), Jose CE Serrano(1), Nadia

Ortega(2), Victoria Ayala(1), Neus Angles(3), Jordi

Reguant(3), Jose R Morello(3), Maria Paz Romero(2),

Maria Jose Motilva(2), Joan Prat(1), Reinald

Pamplona(1) and Manuel Portero-Otin(1)

1. Institut de Recerca Biomedica de Lleida-Universitat de

Lleida-Parc Cientific i Agroalimentari Tecnologic de Lleida

(IRBLLEIDA-UdL-PCiTAL). c/Montserrat Roig 2, 25008

Lleida, Spain. 2. Departament de Tecnologia dels

Aliments, XaRTA-TPV, Escola Tecnica Superior d’

Enginyeria Agraria, Universitat de Lleida, Av/Alcalde

Rovira Roure 191, 25198 Lleida, Spain. 3. La Morella Nuts,

SA. Apel.les Mestres, S/N 43006 Reus, Spain.

Polyphenol intake has been related to changes in

host physiology, though the mechanisms behind are

by far more complex than expected. Metabonomics

has been thoroughly used to study these

mechanisms, but such studies have usually been

restricted to changes in either plasma or urine. In

the present study, we demonstrate that the use of

LC-Q-ToF-based metabolome analyses (foodstuff,

plasma, urine and caecal content metabolomes)

offer higher order information, including intra- and

intercompartment relationships. To illustrate this,

we performed an intervention study with three

different phenolic-rich extracts in mice over 3

weeks. Both unsupervised (PCA) and supervised

(PLS-DA) multivariate analyses used for pattern

recognition revealed marked effects of diet in each

compartment (plasma, urine and caecal contents).

Specifically, dietary intake of phenolic-rich extract

affected a priori unsuspected pathways such as bile

acid and taurine metabolism. LC-Q-ToF-based

metabonomics demonstrated that the number of

correlations is higher in caecal contents and urine

than in plasma. Moreover, intercompartment

correlations showed that caecal contents-plasma

correlations are the most frequent, followed by

plasma-urine ones. The number of inter- and

intracompartment correlations is significantly

affected by diet. These analyses suggest that

decoding the complexity of interorgan metabolic

relationships and the changes induced by nutrient

intake would benefit from LC-Q-ToF analyses.

POSTER 56

LC-Q-TOF-BASED LIPID ANALYSIS REVEALS A

LONGEVITY-RELATED LIPIDOME SIGNATURE IN

CENTRAL NERVOUS SYSTEM FROM MICE

Mariona Jové(1), Victòria Ayala(1),Omar Ramírez(1),

Alba Naudí(1), Corinne Spickett(2), Manuel Portero-

Otín(1) and Reinald Pamplona(1)

1. Department of Experimental Medicine, Faculty of

Medicine, University of Lleida-IRBLleida, 25008

Lleida, Spain. 2. School of Life and Health Sciences,

Aston University, UK.

Dietary methionine restriction (MetR), like caloric

restriction, increases life expectancy and maximum

lifespan in mammals. Since tissue lipid composition

is an important variable associated with the rate of

aging of animal species we investigated whether

MetR induced changes in tissue lipidome. In this

work we demonstrate that: i) 80% MetR induces

marked changes in brain, spinal cord and liver

lipidomic profiles, ii) at least 50% of the lipids

changed by MetR were common in brain and spinal

cord, but not in liver, suggesting the existence of a

nervous system specific lipidomic signature of MetR;

iii) these differential lipids include specific

phospholipid species, suggesting an adaptive

membrane response; sphingolipids, which are

compatible with changes in ceramide signalling

pathways, and the redox physiologically relevant

ubiquinone 9 (with a concurrent loss of the

ubiquinone 9 dependent NQO1 oxidase enzyme),

and iv) oxidation products derived from cholesterol,

phosphatidylcholine and phosphatidylethanolamine

were significantly decreased in brain, spinal cord

and liver from MetR mice. These results reinforce

the importance of the adaptive responses of

membrane lipids in terms of stress resistance as

major mechanistic contributors to the lowered rate


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of ageing in MetR mice and reveals the potential

existence of an age-protecting lipidome signature

POSTER 57

LC-MS METABONOMICS OF PLASMA SAMPLES

FROM CATHETERISED PIGS FED THREE DIFFERENT

DIETS CONTAINING WHOLE GRAIN CEREALS

Natalja Noerskov, Mette Skou Hedemann Peter K.

Theil Knud Erik Bach Knudsen

Aarhus University, Denmark

Wholegrain foods have gained considerable interest

in human nutrition due to the beneficial health

effects. However, the beneficial effects of whole

grains are not caused by a single dietary component

but are most likely a concerted action of numerous

metabolites. Since metabonomics in combination

with multivariate data analysis enables

measurements and data analysis of hundreds to

thousands of metabolites, it should be ideally suited

for identification of underlying metabolites that is

causing changes in biologic systems. In this study,

we have used LC-MS metabonomics to study the

biological changes in plasma following dietary

interventions with whole grain wheat and wheat

and rye ingredients. As an experimental model, we

used pigs with permanent catheters in the portal

vein and mesenteric artery, which allows studying

the apparent absorption of water-soluble

components from the gastrointestinal tract. The

plasma samples were extracted with ethylacetate,

taken to dryness under the flow of nitrogen gas,

redissolved in 60 % of MeOH and analyzed on HPLC

system with C18 column using acetonitrile-water

system as the mobile fase. The HPLC system was

connected to the mass spectrometer (ESI-qTOF

instrument) which operated in negative and positive

ion mode. The quadrupole was conditioned to mass

range from 50 to 1000 mass-to-charge-ratio. All

spectra were mass corrected by reference to

external standard, induced in the beginning of the

each chromatogram. Alignment of the spectra,

chromatogram builder, deconvolution and

normalization were performed in mzMine.

Multivariate data analysis revealed significant

differences between the artery and vein samples

and minor differences between the diets.

Conjugated bile acids were responsible for the

difference between artery and vein samples while

fatty acids were responsible for the differences

between the diets. Identified metabolites were

characterized by their mass-to-charge ratio,

fragmentation pattern and retention time using LC-

MS/MS and standards.

POSTER 58

A LIQUID CHROMATOGRAPHY MASS

SPECTROMETRY-BASED METABOLOMICS STUDY OF

CLONED VERSUS NORMAL OUTBRED PIGS

Kirstine Lykke Christensen(1), Mette Skou

Hedemann (1), Henry Jørgensen (1), Knud Erik Bach

Knudsen (1), Jan Stagsted (2)

1. Aarhus University, Department of Animal

Science, 8830 Tjele, Denmark; 2. Aarhus University,

Department of Food Science, 8830 Tjele, Denmark.

The pig has become an attractive model for

nutritional intervention studies, as it displays

comparable nutritional and digestive aspects with

humans. In this respect, cloned pigs are suggested

to be advantageous, since they potentially may

demonstrate less variation than normal outbred

lines. A small inter-individual variation is of

importance to document a pronounced effect of a

dietary intervention as fewer animals are required.

However, little is known about how phenotype and

phenotypic variation is affected by cloning.

Therefore, an untargeted metabolomics analysis of

a cloned pig model compared to outbred control

pigs has been performed to elucidate possible

differences in the metabolic phenotypes. A total of

19 normal and 17 cloned pigs were from 3 months

of age given the same high energy dense diets (high

in fat, refined carbohydrates and low in fibre) either

Ad libitum or in a restricted manner to test the

effect of overeating in both clones and controls.

Plasma was collected at 8½ months of age and

analysed by reversed-phase liquid chromatography


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mass spectrometry (RP-HPLC-ESI-qTOF-MS) in

positive and negative ionization modes. Data was

pre-treated and subjected to multivariate analysis

(MVA). MVA included principal components

analysis, linear discriminant analysis and a between

groups analysis to locate possible alterations in

metabolite levels between the groups. The MVA

showed significant discrimination in the

metabolomes both within and between clones and

controls when fed either Ad libitum or being

restricted. Metabolites accounting for the

discrimination between feed amounts were not the

same for clones and controls. This suggests that the

clones are phenotypically different from normal

outbred pigs. In this connection a smaller inter-

individual variation among clones do not seem to be

evident from PCA scores plots, but a smaller

variation was observed for restricted animals

compared to the Ad libitum fed. Metabolites

accounting for the separation into classes were

identified by tandem mass spectrometry (LC-

MS/MS), database search and standards.

POSTER 59

ALTERED FATTY ACID METABOLISM IN LONG

DURATION ROAD TRANSPORT: AN NMR-BASED

METABONOMICS STUDY IN SHEEP

Horst Joachim Schirra(1), Juan Li (2,3), Gene Wijffels

(2), Yihua Yu (3), Dominic O. Niemeyer (4), Andrew

D. Fisher (4,5), Drewe M. Ferguson (4)

1. The University of Queensland, School of

Chemistry and Molecular Biosciences, St Lucia, Qld

4072, Australia. 2. CSIRO Livestock Industries, 306

Carmody Road, St Lucia, Qld 4067, Australia. 3.

Shanghai Key Laboratory of Magnetic Resonance,

Department of Physics, East China Normal

University, 3663 North Zhongshan Road, Shanghai

200062, P.R. China. 4. F.M. McMaster Laboratory,

CSIRO Livestock Industries, Armidale, NSW 2350,

Australia. 5. current address: Faculty of Veterinary

Science, The University of Melbourne, Parkville, Vic

3052, Australia.

The metabolic and endocrine changes experienced

by ruminants during and after transport are due to a

combination of deprivation of food and water prior

to and during transport and the stress response to

the social and physical impacts of loading/unloading

activities, transport conditions and duration. The

extent of metabolic change, time to recovery, and

interventions to improve recovery are of interest to

the livestock industries and their regulators.

However, traditional clinical indicators are relatively

insensitive to subtle metabolic adaptations. We

investigated metabolic responses of merino ewes

(n=80) allocated to 12 and 48 h road transport

under standard industry conditions. NMR-based

metabolomics was applied to assess system-wide

metabolic responses as expressed in urine and

serum collected at pre-transport, on arrival and 24

h, 48 h, 72 h post-transport. Principle Component

Analyses of the NMR spectra revealed that changes

in concentrations of several metabolites in sera and

urine were responsible for clear separation of

treatment groups and time points. The metabolic

responses to transport and recovery events involved

metabolites associated with several metabolic

pathways especially carbohydrate, lipid and

glycerolipid and glycerophospholipid metabolism.

The transported animals also experienced altered in

gut metabolism, protein catabolism and possibly a

renal response. The amplified metabolic trajectory

of animals transported for 48 h revealed that longer

transport duration caused different perturbation of

both serum and urinary profiles. During the

recovery period, animals’ metabolism returned to a

new and different state, after 72 h off-truck and

with ad libitum water and feed. Intriguingly,

excretion of acyl glycines and a dicarboxylic acid was

observed after transport and during recovery,

implicated peroxisomal fatty acid oxidation as a

metabolic response to transport induced stress.


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POSTER 60

1H NMR BASED METABONOMICS REVEALS

DIFFERENT METABOLIC RESPONSE TO DIETARY

INTAKE OF WHEAT ALEURONE COMPARED TO

WHOLE-WHEAT GRAIN AND RYE ALEURONE IN

CATHETERIZED PIGS

Christian Clement Yde (1,3), Jeroen Jasper Jansen

(2), Peter Kappel Theil (1), Hanne Christine Bertram

(3) and Knud Erik Bach Knudsen (1)

1. Department of Animal Health and Bioscience,

Aarhus University, Denmark. 2. Swammerdam

Institute for Life Sciences, University of Amsterdam,

The Netherlands. 3. Department of Food Sciences,

Aarhus University, Denmark.

In the present study a novel method of measuring

the uptake of nutrients by NMR spectroscopy was

performed to determine dietary effects of whole-

wheat grain compared to aleurone fractions of

wheat and rye. Six pigs catheterized in the portal

vein and mesentery artery were fed breads made

from whole-wheat grain (WWG), wheat aleurone

flour (WAF) or rye aleurone flour (RAF) in a repeated

3x3 crossover design. Three meals were provided

daily (at 09.00, 14.00 and 19.00 hours), and each

period comprised of a week. Portal and arterial

blood samples were collected at fasting (-30 min) on

day 4-7 and on day 7 pooled samples were collected

to represent 0-150, 150-300, 300-450 and 450-600

min blood profiles. Using the arterial-venous

difference and ANOVA-simultaneous component

analysis (ASCA) showed plasma betaine to

accumulate during the week and was higher when

feeding the WAF diet compared to RAF and WWG.

However, no absorption of betaine was found in the

absorption phases but the time profile of betaine

resembled the choline moiety and high plasma

betaine levels corresponded to low creatine of

endogenous origin. The findings suggest that the

bioavailability of betaine can be a factor of

nutritional importance.

POSTER 61

A NOVEL METABOLOMICS APPROACH FOR

LEGUME BREEDING

Michael Dickinson(1), Donarski J A (1), McKensie J

(2) and Charlton A J(1)

1. The Food and Environment Research Agency (FERA),

Sand Hutton, York, YO41 1LZ, UK 2. University of York,

York, UK.

The objective of this work is to apply both Mass

Spectrometry (MS) and 2D Nuclear Magnetic

Resonance Spectroscopy (NMR) techniques, with a

common sample extraction strategy, to obtain

increased compound information on different pea

species. Using both MS and NMR in a

complementary “data fusion” basis should give

more metabolomic information than using each

technique in a singular fashion. Agriculture

contributes approximately 75% of EU N2O emission

(Crutzen et al 2007), and nitrogen fertiliser accounts

for at least 40% of the energy demand of crop

production. In replace of fertilisers, a greater use of

pulse crops in rotations (i.e. encouraging “climate

smart” agriculture) would reduce N2O emissions.

Currently, pulse crops are a “low value” crop.

Motivation for growing more legume based crops

must coincide with an increase in quality and

therefore an improved profit margin for the grower.

Linking quality characteristics with biochemical and

genetic information will facilitate the more robust

and rapid identification of superior lines, by

enabling the deployment of genetic markers in

marker assisted selection. Here we describe a

metabolomic approach to identify quality

characteristics of different pea species collected at

contrasting harvesting time points. When MS and

NMR techniques are combined to give metabolomic

information a more complete picture can be

obtained of the sample. A methanol based

extraction strategy was developed that is

compatible with both proton NMR and Liquid

Chromatography-High Resolution-MS (LC-HR-MS). A

number of LC and ionisation strategies were

evaluated to obtain the most complete chemical


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information possible of the sample by full scan LC-

HR-MS. After data analysis from the complementary

techniques of NMR and MS, a Principal Component

Analysis (PCA) and the production of a Projection to

Latent Structures Linear Discriminate Analysis model

(PLS-LDA) identified 11 compounds that directly

correlate to the tenderness (a generic quality factor)

of peas. A data fusion approach of the two

techniques allow us to confirm the identity of one of

these as an α amino acid. Overall this work shows

that a metabolomics approach to identify legume

quality characteristics offers a more objective

approach than conventional subjective means such

as taste panels and tenderometer readings.

Reference: Crutzen PJ, Mosier AR, Smith KA, Winiwarter W (2007)

Atmos Chem Physic Disc, 7, 11191–205

POSTER 62

MERY-B: A WEB KNOWLEDGEBASE FOR THE

STORAGE, VISUALIZATION, ANALYSIS AND

ANNOTATION OF PLANT NMR METABOLOMIC

PROFILES.

Catherine Deborde(1), Hélène Ferry-Dumazet (2),

Laurent Gil(2), Stéphane Bernillon(1), Dominique

Rolin(1), Macha Nikolski (2), Antoine de Daruvar (2),

Annick Moing (1) and Daniel Jacob (1,2)

1. PMFB, Centre INRA de Bordeaux, IBVM, BP81, 33140

Villenave d’Ornon, France. 2. Centre de Bioinformatique

de Bordeaux, Génomique Fonctionnelle Bordeaux,

Université de Bordeaux F-33076 Bordeaux, France.

Background: The combination of improved

analytical capabilities with newly designed

dedicated statistical, bioinformatics and data mining

strategies have boosted the number of metabolic

profiles. To ensure the interoperability of analytical

processes provided by complementary equipments

and their deliverables, more efforts have to be

dedicated to a web shared platform to store and

analyse metabolomics data in order to promote

data sharing among laboratories. Various databases

have been created, including organism-specific

knowledgebases and analytical technique-specific

spectral databases. However, there is currently no

platform meeting the requirements for both profile

management and metabolite identification for

nuclear magnetic resonance (NMR) experiments [1].

Description: MeRy-B [2], the first platform for plant

1H-NMR metabolomic profiles, is designed (i) to

provide a knowledgebase of curated plant profiles

and metabolites obtained by NMR, together with

the corresponding experimental and analytical

metadata, (ii) for queries and visualization of the

data, (iii) to discriminate between profiles with

spectrum visualization tools and statistical analysis,

(iv) to facilitate compound identification. It contains

lists of plant metabolites and unknown compounds,

with information about experimental conditions, the

factors studied and metabolite concentrations for

several plant species, compiled from more than one

thousand annotated NMR profiles for various organs

or tissues. Conclusion: MeRy-B manages all the data

generated by NMR-based plant metabolomics

experiments, from description of the biological

source to identification of metabolites and

determinations of their concentrations. It is the first

database allowing the display and overlay of NMR

metabolomic profiles selected through queries on

data or metadata. MeRy-B is available from

http://bit.ly/meryb. In this poster, we will provide

an overview of the major features of MeRy-B and of

some examples of datasets deposited (Tomato: [3];

Melon: [4,5]; Oil palm and date palm: [6]).

References: [1] Kim et al. (2011) Trends Biotech. 29 : 267 [2] Ferry-

Dumazet et al. (2011) BMC Plant Biol. 11:104 [3] Mounet et al. (2007)

Metabolomics 3:273-88 [4] Biais et al. (2009) Anal. Chem. 15:2884-94

[5] Moing et al. (2011) New Phytol. 190:683-696 [6] Bourgis et al. (2011)

PNAS in press.

POSTER 63

DETERMINATION OF SECONDARY METABOLITES IN

THE RHIZOSPHERE MICROBIAL COMMUNITY USING

ICR-FT/MS

Jenny Westphal(1), Rainer Borriss (2) Soumitra Paul

Chowdhury (3) Kristin Dietel (2) Anton Hartmann (3)

Michael Schmid (3) Philippe Schmitt-Kopplin (1)

1. Helmholtz Zentrum München, Research Unit

BioGeoChemistry and Analytics, Ingolstädter Landstr. 1,


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85764 Neuherberg, Germany. 2. ABiTEP GmbH, Glienicker

Weg 185, 12489 Berlin, Germany. 3. Helmholtz Zentrum

München, Research Unit Microbe-Plant Interactions,

Ingolstädter Landstr. 1, 85764 Neuherberg, Germany

Rhizoctonia solani represents world-wide

distributed phytopathogens, which affects

important agricultural and horticultural crops.

Diseases caused by isolates of R. solani, e. g. bottom

rot of Lactuca sativa, have been yet suppressed

using fungicides. To limit chemical pesticides from

industrial agriculture, examination of new fungicide

compositions by replacing chemopesticides by

bioformulations became urgently needed. The

reduction of lettuce bottom rot caused by R. solani

in a degree comparable with treatment of chemical

fungicides has been achieved using formulations

with Bacillus amyloliquefaciens FZB42 (DLR

Rheinpfalz). As the impact of B. amyloliquefaciens

on R. solani and the rhizosphere microbial

community of lettuce has not been determined yet,

the Cluster PATHCONTROL of the GenoMik-Transfer

project analyses these interactions to develop an

efficient biocontrol agent. Therefore, extensive

analysis of the metagenome and metabolome to

identify functional genes and metabolites are

necessary. Such high resolution analysis within very

complex matrices has become possible by means of

appropriate sample preparation followed by high

resolution technologies, like Ion Cyclotron

Resonance Fourier Transform Mass Spectrometry

(ICR-FT/MS). To differentiate metabolites within the

complexity of natural soils, a chemically defined

axenic system was established with lettuce grown

for two weeks on quartz sand. A successful

inoculation with B. amyloliquefaciens FZB42 and R.

solani was verified, so four different categories of

plants were cultivated: lettuce only (control), lettuce

inoculated with FZB42, lettuce inoculated with R.

solani and lettuce co-inoculated. The plants were

prepared by extracting roots in methanol and

performing solid phase extraction. In order to

maximize the recovery of metabolites for analysis,

different solid phase cartridges were tested.

Afterwards the analyses have been carried out using

a 12 Tesla ICR-FT/MS, coupled with an Apollo II ESI

source (Bruker) in positive and negative ionization

mode. Statistical interpretation of received data

combined with database search (e. g. MassTRIX,

KNApSAcK) will identify relevant features, including

specific secondary metabolites. The differentiation

of each sample category will be decisive for

identification of metabolites involved in an

interaction of B. amyloliquefaciens, R. solani and the

microbial community of lettuce roots.

POSTER 64

MONITORING CHANGES IN BARLEY (HORDEUM

VULGARE) LEAF METABOLOME UNDER DROUGHT

STRESS

Barbara Swarcewicz, Maciej Stobiecki

Institute of Bioorganic Chemistry PAS, Noskowskiego

12/14, 61-704 Poznań, Poland

Barley (Hordeum vulgare) is an important cereal

grown for food, animal feed and as a material for

making malt used in production of alcohol. In a

ranking of the cereal crops in the world, barley is in

fourth place after wheat, rice and maize. Drought is

a major environmental factor affecting plant growth

and development, contributing to yield loss.

Therefore it is interesting to understand the

mechanism underlying abiotic stress tolerance. Two

varieties of barley (cv. Lubuski and Maresi) were

grown in greenhouse under controlled watering

conditions. Drought was applied at different growth

stages in three different variants: (1) 10-day long

drought introduced 3 weeks after sprouting; (2)

drought for the same period of time introduced 6

weeks after sprouting; (3) the third one was realized

when both periods of drought stress were

introduced during barley vegetation. The stressed

and control barley plantlets were collected in two

time points after beginning of corresponding

drought period (on day 6 and 10). Leaf tissue

samples were immediately frozen in liquid nitrogen

and stored at ‒80 °C for further analysis. Qualitative

and quantitative analysis of plant extracts were

performed using GC/MS method, according to

procedure described in the literature. Four


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biological samples were collected for each object

ant two technical repetitions were prepared. We

were able to identify different classes of compounds

in leaf extract samples: amino acids, organic acids,

sugars, sugar alcohols, fatty acids and sterols.

Among the identified metabolites the most

abundant were sugars, especially sucrose, which

high overall content in samples caused detector

saturation and therefore made quantitative analysis

inaccurate. Plants exposed to water deficit revealed

changes in metabolite profiles in comparison with

control plants, particularly in abundances of some

amino acids and sugars. Principal component

analysis (PCA) was performed based on GC/MS data,

which demonstrated differences in compound

composition. Variations originating from the age of

barley plants were also demonstrated. This project

is supported with grant from EU funds (grant no.

WND-POIG.01.03.01-00-101/08: POLAPGEN-BD).

POSTER 65

USE OF 1H-NMR BASED METABOLOMICS FOR

VARIETY SELECTION OF FLAXSEED

Aina Ramsay(1,2,3), Roland Molinie(1), Ophelie

Fliniaux(1), Cyril Jousse(1), Xavier Guillot(4),

Albrecht Roscher(2), Eric Grand(3), Jose

Kovensky(3), Eric Gontier(1), Francois Mesnard(1)

(1) EA 3900 Biologie des plantes et contrôle des insectes

ravageurs, Faculté de Pharmacie, 1, rue des Louvels et

Faculté des Sciences, 33, rue Saint Leu, 80000 Amiens,

France, [email protected] (2) Génie Enzymatique

et Cellulaire, UMR CNRS 6022, Université de Picardie, 33

rue St. Leu, 80039 Amiens Cedex, France (3) Laboratoire

des Glucides CNRS FRE 2779, Faculté des Sciences,

Université de Picardie Jules Verne, 33 rue Saint-Leu,

80039 Amiens, France (4) Laboulet Semences S.A., BP5,

80270 Airaines

Since the last decade, there is an increasing interest

in the use of flaxseed (Linum usitatissimum) in

relation to human health. The seedcoat of flaxseed

is rich in lignans and the embryo is rich in oil with a

high omega-3 fatty acid content. The beneficial

effects of these compounds on human health are

now well recognised. Lignans - and other

phenylpropanoid derivatives - appear to be

anticarcinogenic compounds, whereas omega-3

fatty acids are known to reduce heart desease and

would be helpful in the case of inflammatory

deseases such as rheumatoid arthritis. Besides

applications of flaxseed components reported in

pharmaceutical, food and cosmetic products, it can

be used to feed animals and poultry, once

processed. It is therefore of interest to have a

variety selection tool of flaxseed based on its

metabolite content. Here we report the

development of such a method by using NMR-based

metabolomics after optimisation of the extraction

process. It was indeed necessary to adapt the

analytical constraints to those of the plant material.

This step was achieved using an experimental design

analysis. 1H NMR spectra of flaxseed extracts

coupled with multivariate data analysis were

applied to investigate the metabolite variations of

the polar fraction - containing the phenylpropanoid

derivatives - in varieties of flaxseed different in fatty

acid content.

POSTER 66

IDENTIFICATION AND AUTHENTIFICATION OF

TERMINALIA SPECIES BY COMPREHENSIVE

PROFILING NOVEL CHEMICAL MARKERS USING

METABOLOMICS STRATEGY WITH UPLC/TOF MSE

Cristian Cojocariu(1), Bharathi Avula(2), Kate Yu(3),

Yan-Hong Wang(2), Alan Millar(3), and Ikhlas A

Khan(2,4)

1. Waters Corporation, Manchester, UK, M22 5PP. 2.

National Center for Natural Products Research,

School of Pharmacy, University of Mississippi, MS

38677, USA. 3. Waters Corporation, Milford, MA

01757, USA. 4. Department of Pharmacognosy,

School of Pharmacy, University of Mississippi,

University, MS 38677, USA.

Terminalia is plant family Combretaceae, comprising

around 100 species distributed in tropical regions of

the world. Some of its species have been used in

Ayurvedic formulations either as single herb or as


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multiple herbal formulations. Triphala is an

Ayurveda (Traditional Indian Medicine) formulation

made in combination with fruits of Terminalia

chebula, Terminalia bellerica and Emblica officinalis

in equal proportions. Triphala is used as laxative,

detoxifying and rejuvenator in Ayurveda. It is

important to have a suitable analytical method to

distinguish individual herb, to allow adequate

quality control (QC) of raw materials and

standardization of finished products. We report

here the first Metabolomics approach for a

comprehensive chemical profiling of the Terminalia

species using UPLC/TOF MSE coupled with Multi-

Variate Statistical Analysis.

POSTER 67

METABOLIC PROFILING OF IRON-CONTAINING

METABOLITES SECRETED BY TRICHODERMA USING

LC-HR-MS/MS

Sylvia M. Lehner (1), Neumann N.K.N.(1), Atanasova

L.(2), Krska R.(1), Lemmens M.(3), Druzhinina I.(2),

Schuhmacher R.(1).

1. Center for Analytical Chemistry, Department for

Agrobiotechnology, IFA-Tulln, University of Natural

Resources and Life Sciences Vienna, Konrad Lorenz

Strasse 20, 3430 Tulln, Austria. 2. Institute of Chemical

Engineering, Vienna University of Technology,

Getreidemarkt 9/1665A, 1060 Vienna, Austria. 3.Institute

for Biotechnology in Plant Production, Department for

Agrobiotechnology, IFA-Tulln, University of Natural

Resources and Life Sciences Vienna, Konrad Lorenz

Strasse 20, 3430 Tulln, Austria.

Iron is the fourth most abundant element in earth’s

crust and is essential for almost all organisms. Due

to the low solubility of Fe(III) at neutral to alkaline

pH it is not easily available in aerobic environments

including many soil types. Therefore

microorganisms and plants absorb iron by producing

siderophores (from the Greek: sideros “iron”,

phorein “to carry sth.”) that are ferric-iron-

chelating, low-molecular-weight compounds (500-

1500 Da).

The current diversity of microbial siderophores

consists of 200 characterized compounds [1].

Interestingly, fungal siderophores have not only

been described for the transportation and storage

of iron, but also for the interaction with plants and

other fungi. For instance, siderophores are involved

in the suppression of the growth of plant pathogenic

fungi by competition for iron in natural habitats

what has been demonstrated for example for the

control of Fusarium wilt disease by Trichoderma

asperellum [2]. However our knowledge on the

chemical structure and diversity of siderophores

produced by the mycoparasitic fungus Trichoderma

spp. is scarce.

The aim of the present study was to characterize the

diversity of siderophores produced by Trichoderma

spp. using liquid chromatography – high-resolution

mass spectrometry (LC-HR-MS). For this purpose,

Trichoderma spp. were grown on a synthetic

medium under low-iron conditions and the culture

filtrates have been sampled. After addition of iron

to the samples, aliquots of the samples were

analyzed by LC-HR-MS. HR-MS full scan data were

screened for accurate masses of known

siderophores. Additionally, HR-MS full scan data

were automatically searched for the occurrence of

the characteristic natural isotopologue ratio of 54Fe:56Fe in order to detect putatively novel

siderophores that were then analyzed via MS/MS in

order to gain structural information.

This project is funded by the Federal Country Lower

Austria and co-financed by the European Regional

Development Fund (ERDF) of the European Union.

References: [1] Renshaw, J. et al., Mycol. Res. 2002, 106: 1123-1142 [2]

Segarra, G. et al., Microb. Ecol. 2010, 59: 141-149.


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POSTER 68

LC-QTOF-MS-BASED METABOLOMICS TO STUDY

EFFECTS OF CLIMATE CONDITIONS ON THE

PHYTOCHEMICAL CONTENT AND COMPOSITION IN

BRASSICA SPECIES

Gesine Schmidt, Sidsel F. Hagen, Grethe Iren A.

Borge

Nofima AS, Norwegian Institute for Food, Fisheries and

Aquaculture Research, Osloveien 1, 1430 Ås, Norway

Vegetables of the cabbage family (Brassica) like

broccoli, cauliflower, kale, kohlrabi, turnips, and

rapeseed are an important dietary element for

people living in the northern hemisphere. Brassica

vegetables are rich in potentially health-promoting

phytochemicals such as vitamin C, glucosinolates,

flavonoids, hydroxycinnamic acids, and carotenoids.

Many members of the Brassica family are cool-

weather crops that grow best at temperatures

between 18 and 23 °C. In addition to genetic

variation, the plants show large variations in the

development of their phytochemicals depending on

climate factors such as light intensity, length of day,

effective UV radiation, air and soil temperature, and

water availability. The Nordic countries have an

interest in utilizing their long photoperiods and

special solar radiation to produce local foods with

optimized health and sensory quality traits. This

interest has initialized several research programs to

study the effects of climate on the phytochemical

content and composition in various fruits and

vegetables, especially of the Brassica family. In

order to explore these effects, a metabolomics

approach will be used. We are currently establishing

protocols for high-throughput analyses of a wide

range of phytochemicals in Brassica vegetables and

other fruits and vegetables relevant to the Nordic

diet. Optimal sample (plant material) storage and

processing, extraction procedure, UHPLC-qToF-MS,

HPLC-(IonTrap)-MS/MS and GC-MS/MS

methodology, the reproducibility and comparability

of different instruments, as well as compound

identification and quantification are currently being

investigated and will be presented.

POSTER 69

PLANT METABOLOMICS AT BORDEAUX

METABOLOME-FLUXOME FACILITY (PMFB) : TOOLS

AND APPLICATIONS

Catherine Deborde, Stéphane Bernillon, Mickaël

Maucourt, Cécile Cabasson, Benoît Biais, Patricia

Ballias, Duyen Prodhomme, Guillaume Ménard,

Frédérique Andrieu, Daniel Jacob, Yves Gibon,

Dominique Rolin and Annick Moing

PMFB, Centre INRA de Bordeaux, IBVM, BP81, 33140

Villenave d’Ornon, France

Main collaborations: in Japan (Tsukuba Univ., C.

Matsukura), in Israel (Volcani Center, A. Schaffer;

Ben Gourion Univ., A. Fait), in UK (Manchester Univ.;

R. Goodacre and JW. Allwood; Oxford Univ, L.

Sweetlove; Oxford Brookes Univ, D. Fell) in France

(INRA Avignon, M. Causse, M. Génard, JL. Poëssel;

INRA Bordeaux, D. Thiéry ; INRA Montpellier, F.

Tardieu ; INRA Sophia Antipolis, P. Frendo). The

Bordeaux Metabolome-Fluxome Facility (PMFB)

develops and applies plant metabolomics and high-

throughput metabolic phenotyping for local,

national and international projects. Applications

range from the characterization of plant derived

extracts to systems biology: 1- Quantitative

metabolic profiling of plant organs or tissues by 1H-

NMR [1, 2, 3, 4], 2- Plant metabolomics by LC-HRMS,

3- Robotised high-throughput measurements of

metabolite concentrations and enzyme activities

and kinetics [5], 4- Storage of metadata and raw

data and biostatistical analysis through a web-based

application, “MeRy-B” (for Metabolomics Repository

of Bordeaux) (http://bit.ly/meryb) [6], 5-

Identification of metabolic markers for biotic or

abiotic environmental changes [7] or agricultural

practices [8], 6- Characterization of plant extracts

having bioactive properties (JL. Poëssel INRA

Avignon and D. Thiery INRA Bordeaux), 7-

Characterization of mutants [9] or transformants

[10,11] for candidate genes for grain or fruit quality,


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8- Screening of genetic resources or offsprings for

fruit composition (A. Schaffer, Bet Dagan, Israel and

META-PHOR consortium http://www.meta-

phor.eu/; ISAFRUIT consortium

http://www.isafruit.org) or resistance to water

stress (F. Tardieu, INRA Montpellier, FP7 DROPS

project), 9- Integrative modelling of tomato fruit

metabolism (ERASysBio FRIM project), 10-

Integration of metabolomics data with other ‘omics

data for the study of fleshy fruit development and

metabolism [10,12]. In this poster, we will provide

an overview of the major features of some of these

metabolomics studies and tools developed at

Bordeaux. References: 1 Moing et al. (2004) Funct.

Plant Biol. 31:889–902. 2 Mounet et al. (2007)

Metabolomics 3:273-88. 3 Biais et al. (2009) Anal.

Chem. 15:2884-94 4 Moing et al. (2011) New Phytol.

190:683-696 5 Gibon et al. (2004) Plant Cell.

16:3304-25 6 Ferry-Dumazet et al. (2011) BMC Plant

Biol. 11:104 7 Pereira et al. (2006) Anal. Chim. Acta

563:346-52 8 Deborde et al. (2009) Metabolomics

5:183-98 9 Cossegal et al. (2008) Plant Physiol.

146:1553-70 10 Garcia et al. (2009) C. R. Biologies

332:1007-21 11 Neily et al. (2011) J. Plant Physiol.

168: 242-252 12 Mounet et al. (2009) Plant Physiol.

149: 1505-28.

POSTER 70

DIURNAL COMPOSITIONAL CHANGES IN PERICARP

OF TOMATO FRUIT

Camille Bénard(1), Benoît Biais(2), Stéphane

Bernillon(2*), Mickaël Maucourt(3*), Sonia Osorio-

Algar(4), Emilie Labadie-Lemière(2), Patricia

Ballias(2*), Catherine Deborde(2*), Cécile

Cabasson(3*), Michel Génard(1), Alisdair Fernie(4),

Dominique Rolin(3*), Hélène Gautier(1), Annick

Moing(2*), Yves Gibon(2*).

1. INRA UR 1115 Plantes et Systèmes de Culture

Horticoles, Domaine St Paul, Site Agroparc, 84914

Avignon, France. 2. INRA UMR 1332, Biologie du Fruit et

Pathologie, 71 av Edouard Bourlaux, 33140 Villenave

d’Ornon, France. 3. Université de Bordeaux, UMR 1332,

Biologie du Fruit et Pathologie, 71 av Edouard Bourlaux,

33140 Villenave d’Ornon, France * Metabolome Facility

of Bordeaux Functional Genomics Centre, IBVM, Centre

INRA Bordeaux, 71 av Edouard Bourlaux, 33140 Villenave

d’Ornon, France. 4. Max-Planck-Institut für Molekulare

Pflanzenphysiologie, 14476 Potsdam-Golm, Germany

This work is part of the Eranet EraSysBio+ FRuit

Integrative Modelling project, aimed at

characterizing and modelling the effect of

environmental factors on carbon metabolism of

tomato fruit during its development. Whereas

diurnal changes in the biochemical composition of

leaves have been described for a long time and a

range of species, very few studies describe diurnal

changes in fleshy fruit. We studied the diurnal

compositional changes in tomato (Solanum

lycopersicum L. cv Money Maker) pericarp of fruit at

two stages of development (expansion phase and

ripening). Greenhouse-grown tomato fruit at 30

days post-anthesis and at maturity were harvested

throughout a day and night cycle. Metabolites were

determined using targeted and untargeted analyses

(enzymatic, GC-TOF-MS, LC-QqTOF-MS or 1H-RMN)

of polar or semi-polar extracts. Multivariate

analyses allowed separating harvest times and

highlighting discriminant analytes. Mean

comparison of each identified compound revealed

that the absolute or relative concentration of

several metabolites was significantly modified

during the photoperiod. However, diurnal changes

were much more limited in fruits than those usually

found in leaves, and could be ignored when building

a model for the changes of metabolic composition

across fruit ripening. This work will be

complemented with the study of mature leaves

close to the harvested fruit cluster for plants grown

under usual commercial conditions or under carbon

stress.

POSTER 71

BROWNING IN APPLE: A METABOLOMICS

APPROACH FOR BIOMARKER IDENTIFICATION

Darwish Hatoum, Buts K., Baggerman, G., Hertog M.,

Geeraerd A., Nicolaï B.


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Division Mechatronics, Biostatistics and Sensors

(MeBioS), Faculty of Bioscience Engineering, Catholic

University of Louvain, Belgium.

Apple is amongst the major cultivated fruit trees

around the world, and it is of high economic

importance in Flanders, Belgium as well. Apples are

stored under controlled atmosphere conditions

which is a way to ensure out-of-season market

availability to consumers. However, the

susceptibility of apple to internal browning is

responsible for large economic storage losses. The

occurrence and intensity of this physiological

disorder varies with apple cultivar, batch and

growing season. The aim of this study is to offer a

better understanding of browning in apple by using

a metabolomic approach. This will be an essential

step in a larger study to identify a biomarker for

internal browning of apples during long term

storage. Two apple cultivars were used in this study:

Jonagold (browning resistant) and Braeburn

(browning sensitive). Different pre- and post-harvest

conditions were applied to the apples to identify the

main factors influencing browning incidence and

development. Apples from all treatments were

checked regularly through visual assessments and

metabolite analyses. Samples from healthy, sound

(healthy tissue from a brown fruit) and brown

tissues were extracted (methanol), methoxymated

and derivatized (trimethylsilylated) prior to the

untargeted metabolic profiling via GC-MS (Gas

Chromatography – Mass Spectrometry). GC-MS was

the method of choice for our analyses owing to its

high sensitivity and excellent separation

reproducibility. All the protocols were optimized for

apple to be able to deal with the very high sugar

(sucrose, glucose, fructose, sorbitol) content as

compared to other metabolites. The metabolomics

data were compiled and modelled using

multivariate data-mining techniques (PCA, PLS) to

reveal the most significant metabolites

characterising the process of internal browning.

Eventually, once a biomarker is identified, it will be

tested for its early screening capabilities of

commercial apple batches susceptible to browning.

If successful, the development of a low-cost

diagnostic assay will be the final step for

implementation in practice by the growers and

auctions.

POSTER 72

COMPARING APPLES AND PEARS: ASSOCIATIONS

OF METABOLIC PROFILES AND BODY FAT

DISTRIBUTION IN HEALTHY OVERWEIGHT

SUBJECTS

Ewa Szymanska(1), Jildau Bouwman(1,3), Katrin

Strassburg(1,4), Jacques Vervoort(1,5), Johan

Westerhuis(1,2), John P.M. van Duynhoven(1,6,7),

Rob J. Vreeken(1,4), Age K. Smilde(1,2), Doris M.

Jacobs(1,6)

1. Netherlands Metabolomics Centre, Leiden, the

Netherlands. 2. Biosystems Data Analysis, Swammerdam

Institute for Life Sciences, University of Amsterdam, the

Netherlands. 3. TNO Quality of Life, Zeist, the

Netherlands. 4. LACDR, Leiden University, Leiden, the

Netherlands. 5.Plant Research International, Wageningen

UR, Wageningen, the Netherlands. 6. Unilever R&D,

Vlaardingen, the Netherlands. 7. Laboratory of

Biophysics, Wageningen University, Wageningen, the

Netherlands.

Obesity is a risk factor of cardiovascular diseases

and type 2 diabetes especially when the extra fat is

accumulated to central and intra-abdominal depots.

Emerging metabolomics platforms provide extensive

information about systemic metabolic phenotypes

which are expected to be related to obesity. The aim

of this study is to evaluate the associations between

metabolic profiles and body fat distribution

parameters and differences in these associations

between “apples” and “pears” types of fat

distribution. Investigated metabolic profiles are

composed of 136 lipid metabolites, 12 lipoprotein

subclasses, 17 low-molecular weight metabolites

including amino acids and 12 clinical parameters

such as insulin and free fatty acids levels. Body fat

composition is described by 28 parameters such as

anthropometric measurements, total fat content by

DEXA and abdominal fat distribution by MRI. The


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group of healthy overweight subjects with central

obesity includes 215 subjects: 157 females and 58

males. Statistical analysis focused on the analysis of

relationships between single metabolic and body fat

distribution variables (correlation analysis and

partial correlation analysis) as well as evaluation of

multivariate relationships (multivariate regression

and canonical correlation). Relationships of interest

were studied separately for males and females and

distinct gender differences were observed. Many

statistically relevant relationships were revealed e.g.

between selected subgroups of triacylglycerols and

android/gynoid fat ratio or intra-abdominal

(visceral) fat. Most of found associations were

biologically valid and can be explained by changes in

lipid metabolism and body fat distribution in

overweight/obese subjects differently for women

and men. The relationships explored here can be

easily used in the future studies for extensive

assessment of cardiovascular risk in overweight

subjects.

POSTER 73

A SYSTEMS BIOLOGY APPROACH TO STUDYING

GLOBAL RESPONSES TO OXIDATIVE STRESS IN

POPULUS

Ogonna Obudulu, Vaibhav Shrivastava, Torgeir R.

Hvidsten, Patrik Ryden, Robert Nilsson, Eva Freyhult,

Joakim Bygdell, Johana Quanstrom, Thomas Moritz,

Jan Karlsson, Johan Trygg and Gunnar Wingsle

1. Umeå Plant Science Centre, Department of Forest

Genetics and Plant Physiology, Swedish University of

Agricultural Sciences, SE-90183 Umeå, Sweden. 2. Umeå

Plant Science Centre, Department of Plant Physiology,

Umeå University, SE-90187 Umea, Sweden. 3.

Department of Chemistry, Umeå University, SE-90187

Umea, Sweden. 4. Computational Life Science Cluster

(CLIC), KBC, Umeå University, SE-90187 Umeå, Sweden. 5.

Department of Mathematics and Mathematical statistic,

Umeå University, Sweden. 6. Department of Statistics,

Umea University. 7. Department of Clinical Microbiology,

Clinical Bacteriology, Umeå University.

Reactive oxygen species (ROS) are involved in the

regulation of diverse physiological processes in

Plants, including various biotic and abiotic stress

responses, but oxidative stress can also have

severely deleterious effects, including growth

inhibition and ultimately mortality. Thus oxidative

stress tolerance mechanisms in plants are complex,

and to elucidate them diverse responses at multiple

levels need to be Characterized. Here we present

the first investigation, to our knowledge, of global

responses to oxidative stress in Populus by

integrated genomic, proteomic and metabolomic

analysis of cambial region from wild-type controls

and plants expressing hipl-SOD transcripts in

antisence orientation (in which the ROS levels are

elevated, growth is affected and there are both

anatomical and physiological disturbances). A

multivariate regression method, O2PLS, was used to

integrate data on differences between the

transgenic and controls at the three investigated

levels. The results provide system-level information

on ROS metabolism and responses to oxidative

stress, including changes in phenylpropanoid

metabolism, primary metabolism and redox

regulation, with indications that some of the initial

responses to oxidative stress caused by the various

factors may share common pathways. The findings

may facilitate the development of stress-tolerant

plants with improved survival rates and yields under

stressed conditions.

POSTER 74

METABOLITE ANALYSIS OF ESCHERICHIA COLI IN

RESPONSE TO OXYGEN LEVEL

Nur Adeela Yasid, Jeffrey Green and Mike P

Williamson

Department of Molecular Biology and Biotechnology,

University of Sheffield, Sheffield, S10 2TN, UK.

E. coli is a versatile bacterium that has three

metabolic modes: aerobic, anaerobic and

fermentation. The major environmental factor that

controls the switching between these metabolic

modes is oxygen availability. E. coli in intestinal tract

is completely anaerobic, but certain parts of the

intestinal tract close to the gut are microaerobic.


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The change from anaerobic to aerobic or

microaerobic is very rapid and leads to major

metabolic change. The changes have been

characterized by using NMR spectroscopy. We have

developed a quenching technique using

ethanol/NaCl. This technique cools the cells very

rapidly after removal from the chemostat (less than

30 seconds) to inactivate the metabolic activity.

Results have shown that the measurement error

from most sources is small with acceptable error

from extraction of intracellular metabolites. The

technique is being used to studying the transition

from anaerobic to aerobic and WT on different level

of oxygen. The change to aerobic condition showed

the decrease in pyruvate, since the pyruvate

dehydrogenase complex (PDHC) is activated with

the presence of oxygen. An unknown peak (1.53

ppm) was detected during the switch and

identification of the peak was carried out by using

HPLC.

POSTER 75

1H NMR-BASED METABOLOMIC

CHARACTERIZATION OF CHAMPAGNE BASE WINE

AS MODIFIED BY BOTRYTIS CINEREA INFECTION

Young Shick Hong(1), Clara Cilindre(1), Gérard Liger-

Belair(1, 2), Philippe Jeandet(1), Norbert

Hertkorn(3), and Philippe Schmitt-Kopplin(3)

1. Laboratoire d’Oenologie et Chimie Appliquée, URVVC

UPRES EA 2069, UFR Sciences, Université de Reims, BP

1039, 51687 Reims Cedex 2, France. 2. Equipe

Effervescence, GSMA, UMR CNRS 6089, UFR Sciences,

Université de Reims, BP 1039, 51687 Reims Cedex 2,

France. 3. Helmholtz-Zentrum Muenchen-German

Research Center for Environmental Health, Institute for

Ecological Chemistry, Neuherberg, Germany

Botrytis cinerea infection of grape berry, a

widespread fungus in grapevine, leads to changes in

the chemical composition of grape and the

corresponding wine, and thus affects wine quality.

We investigated the metabolic influence of Botrytis

infection in Champagne base wine through 1H NMR-

based metabolomic approach. Amino acids and

their derivatives, organic acids, oligosaccharides,

and phenylpropanoids were identified by 800 MHz 1H NMR spectroscopy and contributed to metabolic

differentiations between healthy and botrytized

wines by using a multivariate statistical analysis such

as the principal component analysis (PCA). Lowered

levels of glycerol, 2,3-butanediol, succinate,

tyrosine, valine derivative, 2-phenylethanol, and

phenylpropanoids but higher levels of

oligosaccharides in the botrytized wines were main

discriminant metabolites between healthy and

botrytized wines. Our results showed that Botrytis

infection of grape caused the fermentative

retardation during alcoholic fermentation because

these discriminant metabolites are all fermentative

products. Moreover, higher levels of several

oligosaccharides in the botrytized wine also

indicated the less fermentative behaviour of yeast in

the botrytized wine.

POSTER 76

SPECIFIC BIOMARKERS FOR STOCHASTIC DIVISION

PATTERNS AND STARVATION-INDUCED

QUIESCENCE UNDER LIMITED GLUCOSE LEVELS IN

FISSION YEAST

Tomas Pluskal(1), Takeshi Hayashi(1,2) Shigeaki

Saitoh(3) Asuka Fujisawa(2) Mitsuhiro Yanagida(1,2)

1. G0 Cell Unit, Okinawa Institute and Science Technology

Promotion Corporation, Japan. 2. CREST Research

Project, Japan Science and Technology Corporation (JST),

Graduate School of Biostudies, Kyoto University, Japan.

3. Division of Cell Biology, Institute of Life Science,

Kurume University, Japan.

Glucose as a source of energy is centrally important

to our understanding of life. We investigated cell

division- quiescence behavior of the fission yeast

Schizosaccharomyces pombe under a wide range of

glucose concentrations (0- 111 mM). The mode of S.

pombe cell division under microfluidic perfusion

system was surprisingly normal under highly diluted

glucose concentrations (5.6 mM, 1/20 of the


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standard medium, within the human blood sugar

levels). Division became stochastic, accompanied by

a curious division-timing inheritance in 2.2-4.4 mM

glucose. A critical transition from division to

quiescence occurred within a narrow range of

concentrations (2.2-1.7 mM). Under starvation (1.1

mM), cells were mostly quiescent and only a small

population of cells divided. Under fasting (0 mM)

condition, division was immediately arrested with a

short chronological lifespan (16 h). When cells were

first glucose starved prior to fasting, cells possessed

a substantially extended lifespan (~14 days). We

employed quantitative metabolomic approach for S.

pombe cell extracts, and identified specific

metabolites (e.g., biotin, trehalose, ergothioneine,

S-adenosyl methionine, and CDP-choline), which

increased or decreased at different glucose

concentrations, while nucleotide triphosphates such

as ATP kept high concentrations even under

starvation. Under starvation, the level of S-adenosyl

methionine sharply increased, accompanied by the

increase in methylated amino acids and nucleotides.

Under fasting, cells rapidly lost antioxidant and

energy compounds such as glutathione and ATP, but

in fasting cells after starvation, these and other

metabolites ensuring longevity remained abundant.

POSTER 77

COMPARATIVE ANALYSIS BETWEEN TWO

DIFFERENT QUENCHING METHODS FOR YEAST

METABOLOMICS STUDIES

Fredoen Valianpour(1), Lodewijk de Jonge(2),

Wouter van Winden(1), Mickel Jansen(1), Walter

van Gulik(2), Reza Seifar(2), Angela ten Pierick(2),

Renger Jellema(1), Dick Schipper(1), Maurien

Olsthoorn(1), Marcel van Tilborg(1) and Joseph J.

Heijnen(2)

1. DSM Biotechnology Center, Alexander Fleminglaan 1,

2613 AX, Delft, The Netherlands, 2, Department of

Biotechnology, Faculty of Applied Sciences, Technical

University of Delft, Julianalaan 67, 2628 BC, Delft, The

Netherlands,

Development of a generic workflow for intracellular

metabolomics which can handle a high stream of

samples is strongly required for rapid phenotyping

as tools for improved strain desing and faster

construction. One of the key steps of sample

preparation is quenching of the biological samples.

Many methods have been developed before using a

cold (-20 to -40°C) methanol. However, processing

of a high number of samples could be impractical

when one uses -40°C methanol in view of

maintaining samples at such a low temperature

during treatment and workers’ safety and health

issues. Therefore we studied the impact of

quenching using ice water (0°C), on yeast

metabolomics, compared to a dedicated method

based on cold methanol. We studied the

quantitative recovery of intermediates of glycolysis,

PPP, TCA cycle, nucleotides and free amino acids.

We measured the metabolites in total broth, and

separated supernatant and cell pellets and

calculated the mass balances for each intermediate.

Results showed that the quenching impact is

depending on metabolite properties and pool sizes.

We found that the ice water method may be used

for quantitative and qualitative metabolomics of

free amino acids in steady state cultures. In addition

only the methanol quenching can be used for the

quantitative analysis of the intermediates of the

central metabolic pathways and the nucleotides.

The variation among replicate samples within the

same quenching method was within the acceptable

range. This means that changes in the metabolite

levels caused by experimental variations were of the

same magnitudes. If it is realized that the metabolic

state in other cultivation conditions and in other

strains can lead to different metabolite level

changes during sample treatment, then, the ice

water quenching method may be suitable for

qualitative purposes of some compounds after a

dedicated validation procedure.

References: De Koning and Van Dam (1992) and Canelas et al (2008).


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POSTER 78

IMPROVING COMPREHENSIVE ANALYSIS FOR

MYXOBACTERIAL METABOLIC PROFILING

Aiko Barsch(1), Thomas Hoffmann(2,3) , Daniel

Krug(2,3) and Rolf Müller(2,3)

1. Bruker Daltonik GmbH, Bremen, Germany. 2.

Pharmaceutical Biotechnology, Saarland University,

Saarbruecken/Germany. 3. Helmholtz-Institute for

Pharmaceutical Research Saarland (HIPS),

Saarbruecken/Germany.

As stated by many researchers, extracting relevant

information from complex data sets is an important

bottleneck in (microbial) metabolomics research.

Compared to a focused targeted approach this is

even more important in untargeted metabolomics,

aiming for the identification of all compounds

produced by a particular bacterial strain. Many of

these compounds are part of primary metabolism

and therefore out of scope when research

concentrates on secondary metabolites. Other

metabolites may be very common for a certain

genus of bacteria and already well known but the

large subset of compounds that is “really new” is

hard to identify. By combining targeted and

untargeted metabolomics approaches, including

searches in freely available data bases, it is possible

to narrow down and identify numerous features

derived from HPLC-high resolution MS/MS

measurements. An automated feature finding

algorithm extracted around 2000 – 5000 features

within one HPLC-MS chromatogram. In a first step

these features were subjected to a search against an

in-house database using accurate mass, isotope

pattern fit, and retention time in order to identify

already known compounds. Untargeted metabolite

profiling, using statistical methods such as ANOVA,

t-test as well as PCA analysis, could identify features

related to the growth of the bacteria by comparing

myxobacterial extracts to blank samples (growth

medium). These features were automatically added

to a scheduled precursor list (SPL) to focus

fragmentation experiments to the relevant subset of

compounds within the complex mixture. This

enabled a fragmentation of even low abundant

features which might have been missed during an

automatic precursor selection without predefined

compounds of interest. High resolution full scan MS

and MS/MS spectra were used to identify target

metabolites by queries in open source libraries (e.g.

METLIN). Remaining unidentified features were

subsequently compared to an in-house database to

identify putative derivatives of known compounds

based on a similar fragmentation pattern.

POSTER 79

OSMOTIC STRESS RESPONSE IN BACILLUS SUBTILIS

- A COMBINED “OMICS” STUDY -

Hanna Meyer(1), M. Kohlstedt (3), S. Maaß (1), P. K.

Sappa (1), T. Hoffman (4), U. Völker(2), C. Wittmann

(3), E. Bremer (4), M. Lalk (1)

1. Ernst-Moritz-Arndt-University of Greifswald, Institute

of Pharmacy, Greifswald, Germany. 2. Interfaculty

Institute for Genetics and Functional Genomics, Ernst-

Moritz-Arndt-University Greifswald, Greifswald,

Germany. 3. Technical University Braunschweig, Institut

für Bioverfahrenstechnik, Braunschweig, Germany. 4.

Philipps-University Marburg, Department of Biology,

Microbiology, Marburg, Germany.

The soil bacterium Bacillus subtilis is able to adapt

to various environmental changes and stresses in its

natural habitat. It is exposed to changing osmolarity,

necessitating adaptive stress responses. Several

regulatory systems are necessary for the adaptation

to these stressors. To gain a global insight into the

physiological adaptation to osmotic stress,

transcriptome, proteome, fluxome as well as

metabolome analyses were performed. In the

present study the main focus will be the

presentation of the metabolome data. Besides non-

stressed and continuous salt stress chemostat

cultivations in parallel bioreactor systems, B. subtilis

was cultivated in salt and glycine betaine containing

medium. Since glycine betaine is known as

compatible solute like e.g. proline, a protection

against the salt stress was expected. In response to

salt stress an assumed increase in the intracellular


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concentration of the osmoprotectant proline could

be observed. Additionally, an unexpected increase

in the amount of several other metabolites was

found. Moreover, when Bacillus subtilis was

cultivated in the presence of glycine betaine the

amount of proline dropped to the level found in

unstressed cells.

POSTER 80

EFFECT OF MICROBIOTA ON THE RYE BRAN

METABOLOME IN AN IN VITRO FERMENTATION

MODEL AS EXAMINED BY NON-TARGETED UPLC-

QTOF-MS METABOLITE PROFILING

Kati Hanhineva(1), Anna-Marja Aura(2), Ilana

Rogachev(3), Sanni Matero(4), Thomas Skov(4),

Asaph Aharoni(3), Kaisa Poutanen(1,2), Hannu

Mykkänen(1)

1. University of Eastern Finland, POBox 1627, FIN-70211

Kuopio, Finland. 2. VTT Technical Research Centre,

POBox 1000, FI-02044 VTT, Finland. 3. Weizmann

Institute of Science, POBox 26, 76100 Rehovot, Israel.

4.University of Copenhagen, Faculty of Life Sciences,

Department of Food Science, Spectroscopy and

Chemometrics group, Rolighedsvej 30, DK-1958

Frederiksberg-C, Denmark.

Diets rich in whole grain products are associated

with reduced incidence of chronic diseases such as

cardiovascular disease and diabetes. One of the

frequently consumed grains in Northern Europe is

whole grain rye (Secale cereale, L.). The bran layer

of rye is known to be a very rich source of

phytochemicals like phenolic compounds, which are

suggested to play a role in the health protective

effects of whole grain rye. The dietary

phytochemicals are only partially absorbed in the

upper gut, and they are subjected to metabolism by

the commensal microbiota in the lower gut,

resulting in altered bioavailability and bioactivity of

the ingested compounds. The impact of microbial

conversions of the phytochemicals is increasingly

pointed out in research related to diet and health,

but relatively little is known so far about the

different metabolite classes on molecular level

produced by the microbial conversions. The effect of

colonic microbiota on rye bran phytochemical

extracts was examined in an in vitro model. The

semi-polar metabolite pool of the samples taken at

timed intervals (0, 4, 12, 48 h) from the microbiota

fermentation were analysed by non-targeted UPLC-

qTOF-MS metabolite profiling. The fermentation

caused a nearly complete turnover in the metabolite

composition of the different sample types, including

the extractable soluble phytochemicals, as well as

those released from the residual matrix of the rye

bran. The phytochemical groups that were degraded

in the in vitro processing include benzoxazinoids,

oligomeric lignans, and flavonols. The most

prominent end products from the incubation were

small phenolic metabolites, although also various

abundant metabolite markers were detected that

represent unknown metabolites emerging during

the incubation. The effect of microbiota on

structure and chemical properties of food borne

phytochemicals is remarkable and may have major

impact on the bioactivities of these compunds. In

our analysis the extensive production of metabolites

derived from dietary phytochemicals was

demonstrated and clearly warrants further study to

determine their chemical structure, absorbability,

and eventually site-of-action as well as bioactivity.

POSTER 81

METABOLIC PROFILING OF A CORYNEBACTERIUM

GLUTAMICUM PRPD2 BY GC-APCI HIGH

RESOLUTION Q-TOF ANALYSIS

Aiko Barsch(1), Marcus Persicke (1), Jens Plassmeier

(1), Karsten Niehaus (1), Gabriela Zurek (2)

1. Centrum für Biotechnologie, Universität Bielefeld,

Germany. 2. Bruker Daltonik GmbH, Bremen, Germany.

Metabolomics studies based on Gas

chromatography – Mass spectrometry (GC-MS) are

well established and typically employ electron

impact (EI) ionisation. Target compounds of interest

can be identified by comparison to commercial or

public databases. Unfortunately, many possible

biomarkers detected in metabolic profiling


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experiments cannot be identified due to the lack of

reference spectra for a majority of biologically

relevant compounds. Therefore, many possible

biomarkers remain “unknowns” up till now.

Hyphenating gas chromatography with high

resolution TOF-MS technology with soft

atmospheric pressure ionisation (APCI) can preserve

the molecular ion information and delivers accurate

mass and isotopic pattern information. This data

enables a sum formula generation for known and

unknown target compounds. Additionally, optionally

acquired MS/MS data can extend the capabilities for

structural elucidation. Mass accuracy, resolution

and isotopic fidelity are independent of the TOF-MS

acquisition rate. Therefore, these instruments can

be coupled to gas chromatography, which typically

delivers narrow peak width requiring fast MS scan

speeds. Corynebactrium glutamicum, a gram

positive, non-toxic bacterium, is used in the

industrial production of amino acids like lysine and

glutamate. C. glutamicum can be grown on different

carbon sources. Glucose is metabolised via glycolysis

and the tricarboxylic acid (TCA) cycle, whereas

propionate is catabolised through the methylcitric

acid pathway. The prpD2 gene encodes a 2-

methylcitrate dehydratase which is involved in the

degradation of propionate. Metabolic profiling of

Corynebacterium glutamicum delta-prpD2 extracts

of cells grown on glucose or glucose and propionate

analyzed by GC-APCI-TOF-MS revealed several

compounds elevated in cells grown on propionate.

Identification of 2-methylcitric acid and alanine

using accurate mass and isotopic pattern

information in MS and MS/MS spectra provided a

proof of concept for the identification of target

compounds using high resolution MS technology.

POSTER 82

IDENTIFICATION OF THE MODE OF ACTION OF

TRYPANOCIDAL DRUGS BY METABOLOMICS

Darren Creek, Isabel Vincent, Karl Burgess, Michael

Barrett

College of Medical, Veterinary and Life Sciences,

University of Glasgow, Glasgow, UK

Human African trypanosomiasis (HAT) is a

potentially fatal infectious disease of sub-Saharan

Africa, caused by the Trypanosoma brucei parasite.

Existing HAT treatment options are unsatisfactory,

primarily due to toxicity and resistance, and

discovery of new trypanocidal drugs is urgently

required. Metabolomics may be used to investigate

the modes of action for existing trypanocidal

compounds, thus providing a basis for rational

development of new drugs against this disease. In

this study, test compounds were incubated with T.

brucei cell cultures, and metabolites were extracted

by cold organic solvent and analysed by hydrophilic

(ZIC-HILIC) liquid chromatography coupled to high

resolution (Orbitrap) mass spectrometry. A novel

data analysis method was developed to allow

simultaneous targeted (based on accurate mass and

retention time of standards) and untargeted (using

an extensive metabolite database and predicted

retention times) putative identification of

metabolites. The metabolomics platform

successfully detected a wide range of metabolites in

each sample, and the data analysis method allowed

rapid investigation of metabolic changes from either

a chemometric and/or biochemical pathway

perspective. Eflornithine, the only clinically used

trypanocidal drug with a known mechanism of

action, was investigated as a proof of principle and

successfully identified a series of changes associated

with action of that drug, as well as some novel

aspects of trypanosome biochemistry. The approach

is now being applied to trypanocidal drugs with

unknown modes of action, with the hope of

identifying novel drug targets for the treatment of

HAT.


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POSTER 83

TOWARDS THE QUANTIFICATION OF THE VOLATILE

METABOLOME OF FUSARIUM GRAMINEARUM PH-

1 USING HS SPME GC-MS

Denise Schöfbeck(1), Fiebrich Alexandra(1),

Wiesenberger Gerlinde(2), Adam Gerhard(2), Krska

Rudolf(1), Schuhmacher Rainer(1)

1. University of Natural Resources and Life Sciences

Vienna, Department IFA-Tulln, Center for Analytical

Chemistry, Konrad-Lorenz-Strasse 20, 3430 Tulln, Austria.

2. University of Natural Resources and Life Sciences

Vienna, Department of Applied Genetics and Cell Biology,

UFT-Tulln, Austria.

Headspace Solid Phase Microextraction coupled to

gas chromatography-mass spectrometry (HS SPME

GC-MS) is an efficient and well established

extraction technique for the comprehensive

determination of volatiles of various samples. The

study of living organisms at certain time points

during cultivation is possible without major

interferences in the biological system. However,

accurate quantification of volatile metabolites using

HS SPME remains a challenge. This is mainly due to

non-exhaustive extraction during SPME and non-

predictable matrix effects caused by e.g.

competition of volatiles for binding sites on the

fibre´s stationary phase or the relative effect of

headspace constituents on the analyte(s) of interest.

Additionally, in case of living organisms, spiking

experiments for standard addition or addition of

internal standards are not possible without

perturbation of the biological system. Hence, only

external calibration and matrix calibration offer

appropriate alternatives for quantification. The main

focus of this study was to evaluate various factors

affecting absolute and relative quantification of

volatile metabolites produced by Fusarium

graminearum PH-1. The fungus was cultivated on

potato dextrose agar (PDA) at 22°C in 20-ml

headspace vials. To investigate matrix effects

caused by nutrition medium (PDA) and the volatiles

present in the headspace above the investigated

culture, mixtures of pure standard compounds were

analyzed. These mixtures included alcohols,

monoterpenes, sesquiterpenes and C8-compounds.

Since the sesquiterpenes were shown to dominate

the volatile profiles of F. graminearum PH-1 with

respect to relative peak intensity of the obtained

GC-MS chromatograms, special focus was laid on

this substance class. Different aspects of matrix

effects were investigated: a) constant number and

concentration of standard compounds in the

headspace (representing the matrix) and their

influence on the SPME efficiency of different single

analytes, b) defined variation of the concentrations

of “matrix-compounds” and the effect on extraction

of single target analytes, and c) the influence of PDA

medium on the extraction of these compounds. The

poster will present a detailed illustration of the

matrix effects which were observed for the different

compound classes as well as for the nutrition

medium. Additionally an experimental approach will

be suggested how to deal with these effects during

quantification of individual target volatiles.

POSTER 84

STUDY OF THE VOLATILE METABOLOME OF

DIFFERENT SPECIES OF THE FILAMENTOUS FUNGUS

TRICHODERMA

Alexandra Parich(1), Bernhard Kluger(1), Susanne

Zeilinger(2), Prasun Mukherjee(3), Frankie

Crutcher(4), Charles Kenerley(4), Rainer

Schuhmacher(1)


Agrobiotechnology (IFA-Tulln), University of Natural

Resources and Life Sciences Vienna, Konrad Lorenz Straße

20, A-3430 Tulln, Austria. 2. Institute of Chemical

Engineering, Vienna University of Technology,

Getreidemarkt 9/1665A, 1060 Vienna, Austria. 3. Central

Institute for Cotton Research, Shankarnagar, Nagpur

4400085, India. 4. Department of Plant Pathology and

Microbiology, Texas A&M University, College Station, TX

77843, USA.

Filamentous fungi produce and release microbial

volatile organic compounds (MVOCs) which are

frequently involved in self signalling as well as the


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interaction with other organisms such as plants and

microbes. Because of their volatile nature, these

compounds can easily be transported through air

and can act over relatively long distances. Also,

these MVOCs are often composed of complex

mixtures. In the presented work, we aimed to

investigate and compare the MVOCs produced by

different species of the filamentous fungus

Trichoderma. For this purpose a recently established

method, which is based on headspace solid phase

microextraction (SPME) coupled to gas

chromatography – mass spectrometry, (GC-MS) was

applied [1]. In brief, different Trichoderma strains,

namely T. virens GV29-8, T. atroviride IMI 206040, T.

atroviride ATCC 74058 and T. reesei QM6a were

cultivated on potato dextrose medium (PDA) in

headspace vials in the dark at 28°C and 70% rel.

humidity. At selected time points after inoculation,

cultures were purged with a stream of air to remove

accumulated volatiles, tightly sealed and analysed

by GC-MS after 6 hours of additional incubation. GC

chromatograms were deconvoluted by the AMDIS

software, and MVOCs were annotated/identified by

comparison to measured mass spectra and LTPRIs

with database entries. For each of the tested

Trichoderma strains, the formation of MVOCs was

monitored over a time period of 5 days. The study

showed that the fungi produced distinct and

complex mixtures of MVOCs. The profiles were

dominated by terpenoids, such as mono-, sesqui-

and diterpenes, but short chain alcohols, and C8-

compounds were also identified. The poster will

present a detailed comparison of the MVOC profiles

and will discuss the potential of the individual

substances to be used for the differentiation

between fungal species.

Reference: [1] Stoppacher, N., Kluger, B., Zeilinger, S., Krska, R.,

Schuhmacher, R., 2010. Identification and profiling of volatile

metabolites of the biocontrol fungus Trichoderma atroviride by HS-

SPME-GC-MS. J. Microbiol. Methods 81: 187-193.

POSTER 85

A METABOLOMICS WORKFLOW FOR THE

AUTOMATED ASSIGNMENT OF FUNGAL

METABOLITES BY IN VIVO STABLE ISOTOPE

LABELLING AND LC/MS ANALYSIS

Rainer Schuhmacher(1), Christoph Büschl(1),

Bernhard Kluger(1), Franz Berthiller(1), Roman

Labuda(2), Georg Häubl(2), Gerald Lirk(3), Stephan

Winkler(3), Rudolf Krska(1)




20, A-3430 Tulln, Austria. 2. Romer Labs Diagnostic

GmbH, Technopark 1, A-3430 Tulln, Austria. 3. School of

Informatics/Communications/Media, FH OÖ Upper

Austria University of Applied Sciences, Softwarepark 11,

A-4232 Hagenberg, Austria.

This work presents an efficient approach for the

assignment of fungal metabolomes by LC-high

resolution MS. The assignment of true metabolites

contained in complex biological samples is still a

major challenge in non-targeted LC/MS based

metabolomics. This limitation can largely be

attributed to the non-specific nature of the

electrospray ionisation (ESI) process in LC/MS. Thus,

ESI-LC/MS full scan spectra tend to contain up to

more than 90% background signals compared to

signals from true metabolites [1]. In vivo stable

isotopic labelling offers a powerful tool to

circumvent these limitations by introducing a

spectral feature that is only observable for true

metabolites of the investigated organism [2]. In our

approach the studied organism is cultivated in

parallel on similar nutrition media, which only differ

in the isotopic composition of the carbon energy

source (e.g. glucose), either solely in form of native 12C glucose or U-13C6 glucose. A 1+1 mixture of these

biological samples are then measured with LC/MS.

The workflow makes use of an algorithm and

software programme, which was recently developed

in our laboratory. It automatically detects MS signals

originating from isotopically labelled metabolites

using a brute force approach. The isotope patterns

for monoisotopic and fully labelled ion molecules

are confirmed and EIC-chromatograms of these

isotoplogues are compared by means of the Pearson

correlation coefficient. After several further fully


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automated data processing steps, the developed

programme offers a list of m/z values which were

identified to represent true biological metabolites.

The final output specifies binned m/z values,

corresponding number of atoms of the labelling

element X (here we carbon was used) together with

retention time and found adduct-, fragment- and

polymer ions. If feasible, database entries matching

the selected assignment criteria can also be used.

The presentation will illustrate the complete

methodical approach from cultivation of biological

samples to data interpretation. The workflow is

exemplified with the plant pathogenic fungus

Fusarium graminearum, for which several hundred

metabolites have been assigned and partly

identified or annotated.

Reference: [1] Keller, B. O., Sui, J., Young, A. B., and Whittal, R. M.

(2008). Interferences and contaminants encountered in modern mass

spectrometry. Anal Chim Acta, 627(1), 71–81. [2] Giavalisco, P., Köhl, K.,

Hummel, J., Seiwert, B., and Willmitzer, L. (2009). 13C Isotope-Labeled

Metabolomes Allowing for Improved Compound Annotation and

Relative Quantification in Liquid Chromatography-Mass Spectrometry-

based Metabolomic Research. Anal Chem, 81(15), 6546–6551.

POSTER 86

USE OF IN-VIVO 13C STABLE ISOTOPIC LABELLING

FOR THE STUDY OF METABOLITE PROFILES OF

EPIGENETICALLY MODIFIED STRAINS OF FUSARIUM

GRAMINEARUM BY LC/MS

Bernhard Kluger(1), Stefan Bödi(2), Christoph

Büschl(1), Michael Sulyok(1), Rudolf Krska(1), Joseph

Strauss(2), Rainer Schuhmacher(1)




20, A-3430 Tulln, Austria. 2. Fungal Genomics Unit, UFT-

Tulln, University of Natural Resources and Life Sciences

Vienna, Konrad Lorenz Straße 24, A-3430 Tulln, Austria

Non-targeted metabolomics based on ESI-LC/MS is a

major challenge due to the fact that full scan spectra

contain a lot of unspecified background noise in

addition to mass peaks originating from true

metabolites. This study focused on the assignment

of true biological metabolites an the differential

comparison of metabolic profiles of three different

strains of the plant pathogen Fusarium

graminearum. We made use of in vivo stable

isotopic labelling of the filamentous fungus F.

graminearum for the unambiguous assignment of

metabolites of true biological origin. Spores of F.

graminearum PH-1 and two epigenetic mutants

were cultivated under identical conditions on the

same nutrition media containing either 12C- or 13C6

glucose as sole carbon source. A 1+1 mixture of

both cultures (non-labelled and fully labelled) was

prepared and analysed by LC/MS analysis with the

LTQ-Orbitrap XL mass spectrometer in both positive

and negative ionisation mode. For each detected

metabolite the obtained high resolution mass

spectra simultaneously contained mass peaks of

both non-labelled and corresponding fully labelled

isotopologues, which were automatically detected

by an in house developed algorithm and software

program. As a result, a list of true metabolites

originating from the fungi was created which

contained accurate molecular masses, adduct ions

and number of carbon atoms allowing the

postulation of molecular formulas and a comparison

of the metabolite profiles. For the assigned

metabolites data were further evaluated with the

aim to identify substances differentially expressed

by the wildtype F. graminearum PH-1 (parent strain)

and two epigenetic mutants.

POSTER 87

FROM SHOTGUN LIPIDOMICS TO KIT ASSAY:

DIFFERENT STRATEGIES TO EVALUATE HUMAN

PLASMA SAMPLES

Axel Besa(1), Reinaldo Almeida(2), Markus

Langsdorf(3), Michael Daxboeck(3), Denise

Sonntag(3) and Matthias Glueckmann(1)

1. AB SCIEX Germany GmbH, Landwehrstrasse 54, D-

64293 Darmstadt, Germany. 2. Advion BioSciences Ltd.,

Harlow Enterprise Hub, Kao Hockham Building, Harlow,

Essex CM20 2NQ, UK. 3. BIOCRATES Life Sciences AG,

Innrain 66, A-6020 Innsbruck, Austria.


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Recently, a powerful technique for direct analysis of

global cellular lipidomes i.e. shotgun lipidomics

using intrasource separation and electrospray

ionization (ESI) mass spectrometry (MS)) has

emerged [see review 1]. The idea of shotgun

lipidomics is to generate high throughput data in

conjunction with global analysis of cellular lipids

directly from biological extracts to investigate

biological functions, monitor diversifications and

profile lipid metabolism. Although this powerful

approach is well established, alternative workflows

can bring important (additional) information related

to the nature of lipids e.g. isomeric/isobaric

compounds within a diversity of concentrations. The

shotgun approach itself is basically infusion of the

whole extract at one time, which itself can cause ion

suppression. Hence, fastLC separation in

combination with fraction collection will avoid

sensitivity issues of Shotgun only approach, while

infusion of fractions using semi-targeted MS

experiments will resolve complex lipid mixtures. As

Shotgun approach is clearly untargeted workflow,

there is a clearly targeted workflow in using a

validated kit assay like AbsoluteIDQ™ p150 Kit

(Biocrates, Innsbruck, Austria) to evaluate same kind

of human plasma samples. While Shotgun lipidomics

requires selectivity in detecting and differentiating

the lipid precursors from background interferences,

high resolution MS instrument are beneficial. On the

contrary the kit assay approach benefits from

selectivity of specificity of triple quadrupole MS scan

mode, the multiple reaction monitoring, MRM. In

this work both are demonstrated to be

complementary strategies with distinct advantages

for shotgun lipidomics but at the expense of

laborious instrumentation and complexity of sample

evaluation, respectively. Within samples from

human plasma distinct differences in the lipid

classes and lipid species are found as evaluated

using statistical and special lipid ID software for

HRMS and HRMS/MS data and dedicated software

solution to handle specific triple quad kit assay data.

POSTER 88

QUANTITATIVE LC/MS ANALYSIS OF

INTRACELLULAR METABOLITES OF CENTRAL

PATHWAYS IN YEAST: A TOOL FOR STUDY OF MPE

Fredoen Valianpour, Olaf Schouten, Burhan Ozalp,

Coralie Selin, Diana Pronk, Renger Jellema, Maurien

Olsthoorn, Hans Roubos, Rob van der Hoeven and

Marcel van Tilborg

DSM Biotechnology Center, Alexander Fleminglaan 1,

2613 AX, Delft, The Netherlands

For metabolic pathway engineering (MPE) it is

relevant to analyze both extracellular and

intracellular levels of the desired metabolite and its

intermediates. Introduction of the new pathways

will also affect central pathways such as glycolysis,

TCA and the energy balance of the microorganism.

Data on the levels and the fluxes of the metabolites

involved in these pathways are rich of information

and may help to give leads to improve the genetic

engineering (e.g. by comparative strain analysis, and

integration with TX and PX data). Development of a

generic workflow for intracellular metabolomics

which can handle a high stream of samples is

strongly required for rapid phenotyping as tools for

improved strain design and faster construction. We

aimed to have a fast method without loss of

separation to measure compounds from the central

metabolic pathways with different chemical and

physical properties among which ATP, ADP, AMP,

succinic acid, malic acid, fumaric acid, Citric acid,

isocitric acid, Glucose 1-phosphate, Glucose 2-

phosphate, Glucose 3-phosphate, fructose

biphosphate, fructose 6-phosphate and nucleotides.

In addition we adapted the method published by

Ewald et al (2008) and adjusted to develop a

straightforward generic workflow to profile strains

by (semi)-quantitative analysis of intracellular

metabolites from the central metabolic pathways of

yeast. This workflow aims to handle 96 MTP

fermentation, quenching, washing and extraction of

lager numbers of samples. Cells were grown in a

fritted bottom MTP and quenched directly into -40


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°C methanol, centrifuged and washed (when

necessary). Metabolites were then extracted by hot

water after adding whole 13C labelled yeast extract

as internal standard. Primary results showed

variations in the range of 10% to 35% depending on

the concentration and nature of metabolites (48

samples).

References: De Koning and Van Dam (1992), Canelas et al (2008) and

Ewald et al (2009), Buescher et al (2010)

POSTER 89

STRATEGY FOR CHOOSING EXTRACTION

PROCEDURES FOR NMR-BASED METABOLOMIC

ANALYSIS OF MAMMALIAN CELLS

Illa Tea, Estelle Martineau, Gregory Loaëc, Patrick

Giraudeau and Serge Akoka

Université de Nantes, CNRS, Chimie et Interdisciplinarité:

Synthèse, Analyse, Modélisation (CEISAM) UMR 6230, BP

92208, 2 rue de la Houssinière, F–44322 Nantes Cedex

03, France.

Metabolomic analysis of mammalian cells can be

applied across multiple fields including medicine

and toxicology. It requires the acquisition of

reproducible, robust, reliable, and homogeneous

biological data sets. Particular attention must be

paid to the efficiency and reliability of the extraction

procedure. Even though a number of recent studies

have dealt with optimizing a particular protocol for

specific matrices and analytical techniques, there is

no universal method to allow the detection of the

entire cellular metabolome. Here, we present a

strategy for choosing extraction procedures from

adherent mammalian cells for the global NMR

analysis of the metabolome. After the quenching of

cells, intracellular metabolites are extracted from

the cells using one of the following solvent systems

of varying polarities: perchloric acid,

acetonitrile/water, methanol, methanol/water and

methanol/chloroform/water. The hydrophilic

metabolite profiles are analysed using 1H nuclear

magnetic resonance (NMR) spectroscopy. We

propose an original geometric representation of

metabolites reflecting the efficiency of extraction

methods. In the case of NMR-based analysis of

mammalian cells, this methodology demonstrates

that a higher portion of intracellular metabolites are

extracted by using methanol or

methanol/chloroform/water. The preferred method

is evaluated in terms of biological variability for

studying metabolic changes caused by the

phenotype of four different human breast cancer

cell lines, showing that the selected extraction

procedure is a promising tool for metabolomic and

metabonomic studies of mammalian cells. The

strategy proposed to compare extraction

procedures is applicable to NMR-based

metabolomic studies of various systems.

POSTER 90

METABOLOMIC PROFILING IN DRUG DISCOVERY:

UNDERSTANDING THE FACTORS THAT INFLUENCE

A METABOLOMICS STUDY AND STRATEGIES TO

REDUCE BIOCHEMICAL AND CHEMICAL NOISE

Anthony Taylor(1), Mark Sanders(1), Serhiy

Hnatyshyn(2), Don Robertson(2), Michael Reily(2),

Thomas McClure(1), Michael Athanas(3), Jessica

Wang(1), Pengxiang Yang(1) and David Peake(1)

1. Thermo Fisher Scientific, San Jose, CA, USA. 2. Bristol

Myers Squibb, Princeton, NJ, USA. 3. Vast Scientific,

Boston, MA, USA.

Novel Aspect: New hardware, software and

database of rat metabolic responses to external

stimuli to reduce noise in metabolomics studies

Introduction Within the pharmaceutical industry,

metabolomics is used to investigate biochemical

changes that result from pharmacological responses

to potential drug candidates. The ability to identify

markers of toxicity or efficacy can significantly

accelerate a drug discovery program and help define

the appropriate clinical plan. While LC-MS

metabolomic profiling has been employed

successfully to identify putative biomarkers, these

experiments contain a large amount of chemical and

biochemical noise, which can confound biomarker

discovery. In this study, new mass spectrometer

technology and data processing software were


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utilized to reduce chemical noise, and experiments

to understand the influence of animal age and

nutrition were undertaken in an attempt to

contextualize drug-induced changes in the presence

of other factors, in effect reducing the biochemical

noise. Methods Blood samples from different

groups of male rats (fully satiated, acute fasting,

chronic fasting, and different age groups) were

analyzed using LC-MS. Protein was removed from

the plasma samples (50uL) by the addition of 100uL

of cold methanol with 0.1% formic acid. Samples

were dried down and reconstituted in 200uL of

H2O/MeOH 90:10. LC-MS analyses were performed

on an benchtop Orbitrap mass spectrometer

capable of fast scanning at >50K resolution, using a

12 minute UHPLC gradient at 600 uL/min on a

1.9µm, 150x2.1 mm Hypersil Gold AQ column. The

data was analyzed using the Component Elucidator

algorithm in a beta version of SIEVE 2.0 software to

determine the metabolic effects of food deprivation

and age. Preliminary Data In a typical LC-MS

metabolomics data set, much of the data is

redundant (multiple ions per component), and much

of the data is irrelevant (chemical noise). In

addition, external factors that influence metabolic

profiles such as animal age and level of nutrition

increase the level of biological noise. Hence, it is

tremendously challenging to discover reliable

markers for drug efficacy and/or toxicity. As the

majority of chemical entities observed are unknown,

it is especially important to filter out false positives

before valuable resources are spent on extensive

structure elucidation studies. Instruments capable

of ultra high resolution (>50K) at an acquisition

speed compatible with UHPLC addresses the issues

of chemical noise and redundancy by providing the

appropriate resolution that is required in a complex

biological matrix to distinguish the different

components. Such data allows sophisticated data

reduction and processing software to more reliably

recognize related signals. This approach not only

leads to a massive reduction in data size which in

turn removes noise from statistical analyses used to

ascertain differences between treatments, but it

also provides higher fidelity quantitation for

targeted analysis as analytes are distinct from other

chemical interferences. On the biological side, other

factors such as nutrition and animal age have a

profound impact on metabolic profiles. Most

metabolic changes are modest in extent, but can

exacerbate or obscure drug induced metabolic

effects and are therefore a significant variable in

model design. Understanding and cataloging these

changes in normal rat helps to minimize “biological

noise” and provides more confidence in assigning

drug related metabolic changes.

POSTER 91

MILK METABONOMICS: IMPACT OF SAMPLE

PREPARATION AND PREPROCESSING ON MODEL

ROBUSTNESS ELUCIDATED ON 400 MILK SAMPLES

Ulrik Sundekilde(1), Clausen MR(1), Larsen LB(2)

and Bertram HC(1)

1. Department of Food Science, Årslev, Science and

Technology, Aarhus University, Denmark. 2. Department

of Food Science, Foulum, Science and Technology, Aarhus

University, Denmark.

The use of nuclear magnetic resonance (NMR)

based metabonomics in assessing milk quality is an

attractive approach as it is rapid, non-destructive

and gives reproducible results. However, whole milk

is an emulsion of high- and low-molecular-weight

constituents, some of which give rise to broad NMR

peaks, and thus, care must be taken in order to get

high-quality data. In a joint Danish-Swedish Milk

Genomics Initiative, milk from 1200 cows originating

from different farms in Denmark and Sweden

comprising three different breeds have been

sampled and screened. This large-scale screening of

milk phenotypes includes many different analyses

including metabolic profiling, mineral and fatty acid

composition and assessment of functional

properties of the milk. The present study

encompasses skimmed milk samples from 400

Danish Holstein-Friesian cows. Proton NMR is

applied for metabonomic profiling of these

individual milk samples using a high-resolution 600

MHz NMR spectrometer. The present study aims at


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optimizing sample preparation by elucidating

whether centrifugation or filtration of samples

selectively removes important metabolites from the

NMR profile. In addition, the aim is to investigate

the ability of different preprocessing steps to

highlight significant metabolites that are related to

either cow breed and/or functional properties (e.g.

cheese-making properties) of the milk. A number of

preprocessing steps must be performed in order to

obtain reliable data, including alignment, data

reduction, normalization, and scaling. Alignment can

either be done by shifting the entire spectrum (1) or

by interval Correlation Optimized shifting (2). Small

shifts can also be dealt with by data reduction

methods such as binning. Thus, we have evaluated

the use of the entire resolution i.e. no binning, using

fixed width bins of varying size (3) and by using

adaptive, intelligent binning algorithms (4).

Normalization is another crucial preprocessing step.

In the present study we have tested absence of

normalization, normalization to TSP, integral

normalization, and probabilistic quotient

normalization (5). The final step before multivariate

data analysis is the data scaling, which enables non

dominant metabolites to influence the model

behavior. Hence, we also test pareto scaling, unit

variance scaling, range scaling (6), VAST scaling (7),

and log or power transformations (8). Furthermore,

useful techniques for variable selection are

elucidated. In summary, this study aims at

maximizing the output of NMR-based metabolite

profiling of milk samples using a number of different

sample preparation and preprocessing techniques.

Acknowledgements The present Ph.d.-project is part

of a joint Swedish/Danish ”Milk Genomics Initiative”

funded by FØSU, Danish Cattle Federation and

Faculty of Agricultural Sciences, Aarhus University.

References: 1. G. Tomasi, F. van den Berg, C. Andersson, J.

Chemometrics 18, 231 (2004). 2. F. Savorani, G. Tomasi, S. B. Engelsen,

Journal of Magnetic Resonance 202, 190 (2010). 3. A. Craig, O. Cloarec,

E. Holmes, J. K. Nicholson, J. C. Lindon, Analytical Chemistry 78, 2262

(2006). 4. T. De Meyer et al., Analytical Chemistry 80, 3783 (2008). 5. F.

Dieterle, A. Ross, G. Schlotterbeck, H. Senn, Analytical Chemistry 78,

4281 (2006). 6. A. K. Smilde, M. t. J. van der Werf, S. Bijlsma, B. van der

Werff-van der Vat, R. H. Jellema, Analytical Chemistry 77, 6729 (2005).

7. H. C. Keun et al., Analytica Chimica Acta 490, 265 (2003). 8. O. M.

Kvalheim, F. Brakstad, Y. Liang, Analytical Chemistry 66, 43 (1994).

POSTER 92

COMPARISON OF HILIC PHASE VERSUS REVERSED

PHASE ION PAIR SEPARATION OF 1,4-METHYL -

IMIDAZOLEACETIC ACID IN THE DEVELOPMENT OF

A TARGETED SCREENING METHOD OF HISTAMINE

RELEASE IN CLINICAL SAFETY ASSESSMENT

Johan Kolmert, Benita Forngren, Johan Lindberg

AstraZeneca R&D, Innovative Medicines, Global Safety

Assessment, Sodertalje, Sweden

The triggering of an immune response in vivo can be

vital for animals and patients, especially for patients

suffering from idiosyncratic immune onset.

Determination of endogenous histamine release in

plasma is challenged by the short half-life of

histamine in the blood stream, approximately 10-30

min. We have therefore developed a simple LC/MS

method for the determination of 1,4-methyl

imidazoleacetic acid (tele-MIAA), a metabolite of

histamine excreted to 70-80 % (1), in urine. First we

developed a HILIC method using a BEH Amide

(Waters) column in which we obtained good

retention of this small polar molecule. The method

was evaluated using more than 300 clinical samples.

Two unfavorable chromatographic properties were

discovered, peak division of our target analyte and

an inconsistent peak shape across several samples.

It could be shown that salts are retained on the

HILIC column and co-elute in the chromatography.

Therefore this methods performance also suffers

from ion suppression. Standard addition calibration

curves based on human urine samples with various

salt concentrations showed very different linear

coefficients effecting the quantification. In an

attempt to find a more stable method we started

with a published method for amino acid analysis (2)

and developed it further for the quantification of

tele-MIAA. This method is based on

tridecaflouroheptanoic acid as ion-pairing agent

used on a BEH C18 column (Waters). The

reproducibility of the standard addition was


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assessed and validated using the same urine

samples as in the HILIC method. Target analyte

(tele-MIAA) and internal standard CV´s are below 6

% during long term analysis, i.e 5 days of continuous

injection of clinical samples. The ion-pairing based

chromatographic method has an LOQ of 43 nM

using an UPLC-ESI-QTOF instrument with a linear

standard curve in the range of 30-1000 ng/mL. Even

though the ion-pairing agent is used in as low

concentration as 0.5 mM, with the benefit of

maintaining good electrospray sensitivity (3), the

contamination of the ion source is prominent and

background ions are still present after rigorous

cleaning of the ion source using organic and acidic

solvents. Despite the background issues from the

ion-pair seen in negative ion mode we choose to use

this method as routine because of the high

robustness seen after more than 700 clinical

samples analysed.

References: 1 Granerus. G, Scand J clin Lab Invest 1968; 22 Suppl 104:

59–68. Urinary excretion of histamine, methylhistamine and

methylimidazoleacetic acids in man under standardized dietary

conditions. 2 Waterval. W, Scheijen. J, Ortmans-Ploemen. M, Habets-

van der Poel. C, Bierau. J, Clinica Chimica Acta 407 (2009) 36-42.

Quantitative UPLC-MS/MS analysis of underivatised amino acids in body

fluids is a reliable tool for the diagnosis and follow-up of patients with

inborn errors of metabolism. 3 Gustavsson. S-Å, Samskog. J, Markides. K

E, Långström. B, Journal of Chromatography A, 937 (2001) 41–47.

Studies of signal suppression in liquid chromatography–electrospray

ionization mass spectrometry using volatile ion-pairing reagents.

POSTER 93

A NOVEL GLOBAL LIPID BIOMARKER WORKFLOW

Lucy Fernandes, Giorgis Isaac Mezengie, Stephen

McDonald, John P. Shockcor, Alan Millar

Waters Corporation, Manchester, UK/ Milford, MA, USA

Lipids are the building blocks and main source of

energy in a cell membrane. Recent studies showed

that lipids can also play essential roles as signaling

molecules and have the potential to revolutionize

biomarker discovery and future diagnostic testing

for various diseases. Currently, mass spectrometric

based global lipid profiling involves two

complementary approaches: liquid chromatography

and direct infusion coupled with mass spectrometry

(MS). When choosing a sample introduction

technique it is important to consider the complexity

of the biological sample and the interest in

detecting minor and isobaric lipid species. In this

study a simple and fast UPLC/MSE global lipid

biomarker workflow was developed from bovine

liver total lipid extract to maximise the amount of

information gained from MS analysis. We report

here a simple, rapid and reproducible UPLC/MSE

method has been developed for global lipid profiling

from a complex biological sample.

POSTER 94

A MALDI-FT-ICR MS BASED WORKFLOW FOR

METABOLIC PROFILING AND UNAMBIGUOUS

DETERMINATION OF ELEMENTAL COMPOSITIONS

FOR TARGET COMPOUNDS

Kazunori Saito(1), Tatsuhiko Nagao(2), Daisuke

Miura (2), Aiko Barsch(3), Takashi Nirasawa(1),

Hiroyuki Wariishi(2)

1. Bruker Daltonics K.K., Yokohama, Japan. 2.

Kyushu University, Fukuoka, Japan. 3. Bruker

Daltonik GmbH, Bremen, Germany.

Mass spectrometry (MS) is a standard technique

used in metabolomics applications. Although liquid

chromatography or capillary electrophoresis

coupled to MS have been widely used for this

purpose, this methodology often depends on

spectral databases for compound identification. This

approach is hampered by the fact that only ~20% of

biologically relevant metabolites are commercially

available. Here we present an MS-based

metabolomics workflow which employs matrix

assisted laser desorption ionization (MALDI)-Fourier

transform ion cyclotron resonance (FT-ICR) MS.

HepG2 human liver carcinoma cells were

administered with different concentrations of the

anti cancer drug 5-fluorouracil (5FU). Intracellular

metabolites of treated cells and a control group (five

biological replicates each) were extracted by a

biphasic extraction with

methanol/water/chloroform=2/2/1. The extracts

were analyzed by MALDI-FT-ICR MS using 9-


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aminoacridine as matrix in negative ion mode.

Spectral data was acquired within 30 seconds per

spectrum and the obtained spectral resolution was

typically >400,000 (FWHM). Acquired data was

evaluated using multivariate statistical analysis.

Principal component analysis (PCA) showed a clear

separation between dosed and control cell groups.

Additionally, orthogonal partial least-squares

discriminant analysis (OPLS-DA) could discriminate

these groups and indicated several loadings

contributing to this separation. Subsequently,

elemental compositions were calculated for these

compounds. The ultrahigh resolution data enabled

to enhance the confidence for the formula

assignment by comparing measured isotope fine

structures with theoretical ones. A query of these

sum formulae in public databases indicated that

those compounds correspond to nucleotides and

amino acids. Two of these analytes showed a clear

dose-dependent reduction in peak intensities. The

present study shows that 5FU seems to inhibit the

biosynthesis of several nucleotides and amino acids

in HepG2 cells. Acquired ultrahigh resolution could

separate both monoisotopic peaks close to each

other as well as isotope fine structures. This

methodology enables non-targeted metabolites

profiling and biomarker discovery with high

throughput capabilities.

POSTER 95

DEVELOPMENT OF A GC-MS METABONOMIC

METHOD FOR METABOLITE PROFILING OF

STREPTOZOTOCIN INDUCED DIABETES IN RAT

LIVER

Per Thomsen(1), Garth L. Maker(1,2) Timothy

Fairchild(3) Robert Trengove(2) Ian Mullaney(1)

1. School of Pharmacy, Murdoch University, South

Street, Murdoch. Western Australia 6150, Australia.

2. Murdoch University Separation Science and

Metabolomics Laboratory, Murdoch University,

South Street, Murdoch, Western Australia 6150,

Australia. 3. School of Chiropractic and Sports

Science. Murdoch University, South Street,

Murdoch, Western Australia, Australia

Diabetes results in hyperglycaemia, due to

decreased/absent insulin production or decreased

insulin sensitivity. The lack of cellular glucose

absorption induces compensatory mechanisms

involving carbohydrate and nitrogen metabolism

and oxidative stress mechanisms. Metabolomics can

provide comprehensive characterisation of

molecular pathways and may contribute to

understanding metabolic changes in diabetes. The

present study aims to combine experimental design

optimisation with multivariate statistical analysis to

validate a liver metabolite extraction protocol for

the assessment of biomarkers of streptozotocin

(STZ)-induced diabetes. Metabolic profiles of livers

from STZ-induced diabetic rats and controls (n=8)

were investigated with gas chromatography mass

spectrometry (GC-MS). The data was further

analysed by Principal Component Analysis to

compare the metabolite profiles of diabetic and

control rats. The analysis revealed an average of

143 ± 12.5 metabolites from the analysed livers. Of

these 78 metabolites were positively identified. The

two groups showed significant differences in

metabolite profiles, including carbohydrates, amino

acids, and organic acids. We have identified several

relevant metabolites significantly altered in STZ-

induced diabetes. These represent metabolites from

key metabolic pathways, including gluconeogenesis

and the tricarboxylic acid cycle. Metabolites that

display significant and specific up or down

regulation correspond well to existing data on

diabetic metabolism. We have shown that GC-MS is

a useful tool for characterising metabolic changes in

diabetes. Understanding the biochemical changes

occurring in diabetes will aid in the discovery and

evaluation of possible treatments and provide a

mechanism for further study of the disease itself.


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POSTER 96

STRUCTURE ELUCIDATION AND CONFIRMATION

FOR PLANT METABOLOMICS: NOVEL APPROACHES

Sven Heiling (1), Gabriela Zurek (2), Friederike

Teichert (2), Emmanuel Gaquerel (1), Matthias

Schöttner (1), Bernd Schneider (1), Aiko Barsch (2),

Jens Fuchser (2), Ian Baldwin (2)

1. MPI Chemical Ecology, Jena, Germany. 2. Bruker

Daltonik GmbH, Bremen, Germany

Presently, the key bottleneck of (plant)

metabolomics is structural confirmation and

elucidation of secondary metabolites. Nicotiana

attenuata is a well-established model system to

monitor plant-herbivore interactions with

metabolomics being a novel approach to investigate

the underlying biology [1]. 17-

Hydroxygeranyllinallool diterpene glycosides (HGL-

DTGs) are abundant direct defense compounds with

their mode of action being largely unknown [1-3].

New acyclic HGL-DTGs were characterized using MS

and NMR after extraction of several hundred grams

of raw plant material [2, 3]. Such scale is not

compatible to the analytical scope of metabolomics.

Here, we present novel solutions facilitating the

identification and fast dereplication process of

natural products when mass spectral libraries are

not yet available and the sample amount is limited.

Plant samples were prepared as described

previously [1]. Chromatographic separation was

carried out using an UHPLC system combined with

ultra high resolution (UHR) Q-TOF MS detection.

Selected plant samples were fractionated. Peaks

enriched in HGL-DTGs were subjected to detailed

fragmentation studies by means of direct infusion

measurements. The dereplication of HGL-DTGs is

rendered difficult by the large number of in-source

fragments and adduct formation, and their

molecular weight of 800-1000m/z. Novel algorithms

were applied for deconvolution of LC-MS

chromatograms by correlation analysis to safely

determine the molecular ion in the presence of

adducts and in-source CID fragments. Molecular

formula determination was carried out by combined

evaluation of mass accuracy, isotopic patterns,

adduct and fragment information. The diagnostic

fragments for the HGL-DTG backbone and

successive sugar units, such as [M+H]+ =

271.2420m/z = C20H31+ and 417.2999m/z =

C26H41O4+ enabled the rapid identification of the

entire compound family, which is subsequently

characterized in more detail. For this, the

fragmentation results have been combined with the

structural information to visualize the

interpretation. Simultaneously the necessary

validation prior submission to a mass spectral library

is achieved.

References [1] Gaquerel, E., J. Agric. Food Chem. 58 (2010), 9418-9427.

[2] Jassbi, A., Z. Naturforsch. 61b (2006), 1138-1142. [3] Heiling, S., Plant

Cell 22 (2010), 273-292.

POSTER 97

ORTHOGONAL SEPARATIONS FOR METABOLOMICS

- APPLICATION OF A SUB-MICROBORE ION

CHROMATOGRAPHY SYSTEM AND FIELD

ASSYMETRIC ION MOBILITY SPECTROMETRY TO

METABOLOMICS

Karl Burgess(1), Mike Barrett (1), Darren Creek (1),

Ken Cook (2), Paul Dewsbury (2), Andrew Pitt (3)

1. Infection and Immunity, University of Glasgow,

Glasgow, UK. 2. Dionex UK, Camberley, UK. 3.

Aston University, Birmingham, UK.

Metabolomic analysis by mass spectrometry is a

relatively new discipline that aims to study, in an

unbiased manner, the metabolite milieu of a cell,

tissue or secretion, and to provide quantitative

comparison between different states, feeding this

information back into informatics approaches for

biomedical profiling and metabolic pathway

analysis. Metabolic profiling is commonly

performed by mass spectrometry, often using a

direct infusion approach. While this methodology is

rapid, ion suppression leads to loss of many ions of

importance. While maintaining speed of analysis,

we have applied field assymetric ion mobility

spectrometry [FAIMS] to the purpose of rapid


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metabolite profiling, providing additional separation

and therefore feature detection capability.

Detection and quantitation of metabolites are

enhanced by effective separation prior to their

detection, especially using HILIC (emphasising polar

compounds) and C18 (emphasising non-polar

compounds) resins. While these stationary phases

provide coverage of the majority of central

metabolism, several classes of charged compounds

are not observed using this type of analysis. We

have performed a comparison of ion

chromatography/mass spectrometry [ICMS] in the

submicrobore scale, a methodology that allows the

combination of ion exchange liquid chromatography

with mass spectrometry separation. Trypanosome

extracts under different growth conditions were

subjected to separation using ZIC-HILIC (Merck) and

ICMS (Dionex submicrobore scale) techniques. Data

was collected on an LTQ Orbitrap Velos (Thermo)

and Orbitrap Exactive (Thermo) in both positive ion

mode and negative ion modes. We present a

comparison of these results demonstrating the

additional information that can be gained by using

ICMS. We also present the use of field-assymetric

ion mobility spectrometry [FAIMS] for rapid profiling

of trypanosome extracts.

POSTER 98

LC-MS ANALYSIS BASED ON PROBABILISTIC

APPROACH

Jan Urban, Jan Vanek, Dalibor Stys.

Institute of Physical Biology, Zamek 136, Nove Hrady

CZ37333, Czech Republic

Mass spectrometers are sophisticated, fine

instruments which are essential in a variety

applications. There were already developed

methods for processing and analysis of measured

data sets. However, only partial problems of

processing/analysis task were handled

independently. The data they produce are usually

interpreted in a rather primitive way, without

considering the accuracy of this data and the

potential errors in identifying peaks. Our new

approach corrects this situation by dividing the LC-

MS output into three components: (a) signature of

the analyte as useful output, (b) random noise and

(c) systemic noise of the instrument related to the

particular experiment. Our novel approach based

on the theory of systems is used for description of

abstract model above the measured data. This

model encapsulated all processing/analysis steps

into appropriate and consistent mathematical

space. The creation of this model via description of

the measurement device and data outputs is

introduced. Abstract model of LC-MS data set is

used to decompose the measurement into three

partial contributions. The separation process of the

signal could be estimated using the probabilistic

approach. The characteristics of the systematic

noise change in time and depend on the analyzed

substance. Working with these components allows

us to quantify the probability of error and, at the

same time, retrieve some peaks which get lost in the

noise when using the existing methods. Our

software tool, Expertomica metabolite profiling,

automatically evaluates the given instrument,

detects compounds and calculates the probability of

individual peaks. It does not need any artificial user-

defined parameters or thresholds. The program not

only quanti es the accuracy of the interpretation,

but it also detects many peaks which, using the

existing methods, are not distinguished from the

noise. Exactly the same algorithm is used to

evaluate the preliminary blank run, and the peaks

detected in this mea surement. Our approach is

focused on proper characterization of presended

noise. Noise produced by mobile phase is

characterised separately to random noise

contribution. Information about the both of noise

characterizations were integrated into the

probability factor.


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POSTER 99

LC-MS BASED GLOBAL METABOLITE PROFILING OF

GRAPES EXTRACTION PROTOCOL OPTIMISATION

Urska Vrhovsek, Georgios Theodoridis, Helen Gika,

Pietro Franceschi, Lorenzo Caputi, Panagiotis

Arapitsas, Mattias Scholz, Domenico Masuero, Ron

Wehrens, Fulvio Mattivi

Fondazione Edmund Mach, IASMA Research and

Innovation Centre, Food Quality and Nutrition

Department, Via E. Mach 1, 38010 S. Michele all'Adige,

Italy

Optimal solvent conditions for grape sample

preparation were investigated for the purpose of

metabolite profiling studies, with the aim of

obtaining as many features as possible with the best

analytical repeatability. Mixtures of water, methanol

and chloroform in different combinations were

studied as solvents for the extraction of ground

grapes. The experimental design used a two stage

study to find the optimum extraction medium. The

extracts obtained were further purified using solid

phase extraction and analysed using a UPLC full scan

TOF MS with both reversed phase and hydrophilic

interaction chromatography. The data obtained

were processed using data extraction algorithms

and advanced statistical software for data mining.

The results obtained indicated that a fairly broad

optimal area for solvent composition could be

identified, containing approximately equal amounts

of methanol and chloroform and up to 20% water.

Since the water content of the samples was

variable, the robustness of the optimal conditions

suggests these are appropriate for large scale

profiling studies for characterisation of the grape

metabolome.

POSTER 100

A HIGH-RESOLUTION NMR TECHNIQUE FOR

MICROSCOPIC BIOPSIES

Alan Wong, Pedro M. Aguiar and Dimitris Sakellariou

CEA Saclay, DSM, IRAMIS, UMR CEA/CNRS no 3299 –

SIS2M, Laboratoire Structure et Dynamique par

Résonance Magnétique, F-91191, Gif-sur-Yvette Cedex,

France

One of the main analytical techniques for

metabonomic studies is High-Resolution Magic-

Angle spinning (HR-MAS) 1H NMR spectroscopy. It is

known that some biological samples (e.g biopsies)

are classified as semi-solids, and can exhibit line

broadening in 1H NMR induced by magnetic

susceptibility. This effect can be averaged by Magic-

Angle Spinning: the faster the sample spinning

frequency the larger the susceptibility gradient can

be averaged. However, fast sample MAS can lead to

a series of problems for ‘soft’ materials such as cells

and tissues [1-3] because of the large centrifugal

forces upon the samples and can damage their

integrity. One approach would be to use of a

microscopic sample volume (i.e. small diameter) to

minimize the centrifugal force. More importantly,

the high degree of homogeneity in microscopic

samples could lead to simpler chemometric, and

give a direct specimen-specific NMR analysis.

Unfortunately today, microscopic samples cannot

be routinely analysed using HR-MAS because of

their low sensitivity due to the inadequate size of

commercial detectors (i.e. poor filling factor).

However, sensitivity can be regained by the use of

resonant micro-detectors [4], which can be

inductively coupled to any standard commercial HR-

MAS probe, without any probe modifications. This

technique is known as Magic-Angle Coil Spinning

(MACS). Here, we present a variety of results, from

MACS spectroscopy of biopsies [5] to microscopic

imaging of phantoms. MRI microscopy presented

here does not require a standard multi-axes pulsed

gradient system, but instead, it uses the stray-field

z-gradient from a standard NMR magnet and the

continuous sample reorientation from a commercial

MAS probe [6]. This enables ultra high-resolution

multi-dimensional MRI microscopy with z-gradient

as large as 10 T/m or even higher.

References: [1] Taylor JL, Wu CL, Cory D, Gonzalez RG, Bielecki A, Cheng

LL. High-resolution magic angle spinning proton NMR analysis of human

prostate tissue with slow spinning rates. Magn Reson Med 2003;50:627-


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632. [2] Wind RA, Hu JZ. In vivo and ex vivo high-resolution 1H NMR in

biological systems using low-speed magic angle spinning. Prog Nucl

Magn Reson Spectro 2006;49:207-259. [3] Martinez-Bisbal C, Esteve V,

Martinez-Granados B, Celda B. Magnetic Resonance Microscopy

contribution to interpret high-resolution magic angle spinning

metabolomic data of human tumor tissue. J Biomed Biotech 2011;article

ID 763684. [4] Sakellariou D, Goff GL, Jacquinot JF. High-resolution,

high-sensitivity NMR of nanolitre anisotropic samples by coil spinning.

Nature 2007;447:694-697. [5] Wong A, Aguiar PM, Sakellariou D. Slow

magic-angle coil spinning: A high-sensitivity and high-resolution NMR

strategy for microscopic biological specimens. Magn Reson Med

2010;63:269-274. [6] Wong A, Sakellariou D. 2D and 3D multinuclear

stray-field imaging of rotating samples with magic-angle spinning

(STRAFI-MAS): from bio to inorganic materials. J Magn Reson

2010;206:264-268.

POSTER 101

INFLUENCE OF FREEZING AND STORAGE

PROCEDURE ON THE METABOLITE PROFILE OF

URINE SAMPLES IN NMR-BASED METABOLOMICS

Manuela J. Rist(1), Benjamin Görling(2), Martin

Koos(2), Claudia Muhle-Goll(2), Achim Bub(1),

Bernhard Watzl(1), Burkhard Luy(2)

1. Max Rubner-Institut, Department of Physiology and

Biochemistry of Nutrition, Karlsruhe, Germany. 2.

Karlsruhe Institute of Technology (KIT), Institute for

Organic Chemistry and Institute for Biological Interfaces

II, Karlsruhe, Germany.

Most publications in metabolomics note the storage

temperature of the samples prior to analysis, but for

practical reasons the freezing procedure may

require conditions that are different from long-term

storage. Several publications investigated the effect

of storage temperature on urine samples [1,2] but

found no significant effect. Recently, Bernini et al.

found a difference in urine NMR spectra depending

on the freezing and storage temperature [3].

Therefore, the aim of this work was to test different

realistic combinations of freezing procedures and

storage temperatures and their effect on NMR

spectra to develop a standard operating procedure

that is practical in our hands. Mid-stream spot urine

samples were collected from healthy volunteers,

centrifuged at 3000 rpm for 10 min at 4°C, and

divided into aliquots. Urine aliquots were frozen

either at -20°C, on dry ice, at -80°C, or in liquid

nitrogen and then stored at -20°C, -80°C or in liquid

nitrogen for 1 – 4 weeks. For NMR analysis, thawed

urine samples were centrifuged at 4000 rpm for 10

min at 20°C, and 540 µL of the supernatant were

mixed with 60 µL NMR buffer and measured in a

Bruker 600 MHz NMR spectrometer equipped with a

TCI cryoprobe at 300K using a 1D NOESY experiment

with presaturation for water suppression.

Preliminary results indicate that there are

differences in spectra depending on the freezing

procedure. In part, these differences seem to be

based on pH variations. These clear differences

weakened after longer storage time dependent on

the type of long-term storage. In metabolomics

studies the actual freezing procedure might involve

different conditions (e. g. temperature) from long-

term storage. It should be noted that such freezing

conditions can have an influence on NMR spectra. A

minimum requirement for metabolomics studies

therefore is that all samples are treated identical

and that the freezing procedure is part of the

publication protocol.

Reference: 1 Lauridsen M, et al., Analytical Chemistry 2007;79:1181-6. 2

Maher AD, et al., Analytical Chemistry 2007;79:5204-11. 3 Bernini P, et

al., J Biomol NMR 2011;49:231-43.

POSTER 102

STRUCTURAL CHARACTERIZATION OF ISOMERIC

AND ISOBARIC NATURAL PRODUCTS DURING

LC/ESI/MSN PROFILING IN FABACEAE

Anna Staszkow(1), Anna Piasecka(2), Piotr

Kachlicki(2), Maciej Stobiecki(1)

1. Institute of Bioorganic Chemistry PAS, Poland. 2.

Institute of Plant Genetics PAS, Poland.

Flavonoid glycoconjugates constitute an abundant

class of secondary metabolites that are ubiquitous

in the plant kingdom. These natural products

represent numerous structures as a consequence

of the phenolic ring B position as well as various

substitutions of hydroxyl groups. Polyphenolic core

compounds occurring in plant tissues are

substituted with different glycosidic, alkyl or acyl

moieties giving rise to more than 9000 metabolites.

Proï¬•ling of secondary metabolites is a challenging


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task from an analytical point of view. The

application of liquid chromatography systems

hyphenated to mass spectrometers allows to

separate and identify numerous isomeric and

isobaric flavonoid glycoconjugates. The need of a

proper identification of different substituents such

as sugars consisting of simple hexoses and pentoses

(glucose or xylose), deoxysugars (e.g. rhamnose) or

sugar acids (glucuronic acid), acyls (aliphatic and

aromatic) and alkyls, demands for a use of special

MS instrumentation. Fast and high resolution mass

spectrometers with the collision induced

dissociation (CID), preferably with the MSn function,

are the instruments of choice. Due to

complementary information achieved from the

mass spectra recorded for positive and negative ions

of flavonoids, separate chromatographic

experiments for each sample with both types of

ionization are recommended. The registered high

resolution CID MS/MS spectra permit to establish

elemental composition of the whole glycoconjugate

molecules from exact m/z values of

protonated/deprotonated molecules ([M+H]+/[M-

H] ) as well as their fragment ions registered to

fourth decimal point. This allows to distinguish

molecules substituted with rhamnose, hexose or

glucuronic acid from those with phenylpropenoic

acids (p-coumaric, caffeic or ferulic) with the same

nominal masses. The elucidation of the MSn spectra

enables location of substituents on different parts of

the molecule and the identification of the flavonoid

aglycone on the basis of its fragmentation pattern.

In most cases the positive or negative charge of the

flavonoid glycoconjugates remains on the aglycone

part of the molecule during the CID reactions.

However, in some cases it may be placed on the

glycosidic part providing diagnostic ions allowing its

structural identification. This may be achieved

during the analysis of flavonoid glucuronates

holding acidic sugar moieties or by the post-column

treatment of the eluate with metal salts prior to the

ionization process. The analysis of such

fragmentation patterns provides structural

information concerning the sugar moieties.

Unfortunately, in most cases information from the

LC/MS experiments is sufficient only for a tentative

identification of the flavonoid structures. Full

structural information may be achieved from the

LC/NMR analysis of these compounds. However,

due to a large number of different flavonoids

present in many plants, the low concentration of

certain compounds and a high cost of those

analyses, the LC/MS remains the method of choice

for the studies of this group of secondary

metabolites.

POSTER 103

OPTIMIZATION OF MOUSE LIPIDOMIC ANALYSIS: A

FAST AND ACCURATE METHOD

Sakda Khoomrung, Intawat Nookaew, Pramote

Chumnanpuen, Jens Nielsen

Systems and Synthetic Biology, Department of Chemical

and Biological Engineering Chalmers University of

Technology Kemivägen 10, SE-41296 Göteborg, Sweden.

Lipids are class of biomolecules that play many

important rules in cells such as energy storage,

cellular support and signal transduction. The

progress on lipid research is majorly driven by the

development of analytical methods mainly by

chromatography and mass spectrometric

techniques. We present here, a work described

several optimized analytical methods for global

analysis of all lipid classes in mouse tissues. The aim

of this work is to provide simple, fast and reliable

methods, which able to handle several samples in a

shorter time. All lipid classes in mouse tissues were

first extracted by chloroform/methanol. Then the

extracted lipids were separated in to neutral and

poplar lipids by HPLC coupled with charged aerosol

detector (CAD) for the detection and fraction

collector for further analysis of individual fatty acid

(60 min). For the total fatty acid analysis, the sample

preparation was performed based on direct

transesterification using BF3 in MeOH as the

reagent. We reduced time consuming of sample

preparation by using microwave digestion instated

of conventional heating. With this approach, the

sample preparation for the total fatty acids analysis


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can be performed within 15 min. We also optimized

chromatographic separation and all necessary

parameters for the GC-MS analysis, in order to

obtain highest sensitivity of the instrument.

Following the determination of the optimal

conditions for GC-MS, we are able to separate and

analyze at least 24 fatty acids from mouse tissues

within 30 min. The accuracy and precision of the

optimized method were validated with standard

reference material 3275 (omega-3 and omega-6

fatty acids in fish oil) from National Institute of

Standards and Technologies, USA. The results from

validation of our method were in good agreement

with certified values from the standard reference

material.

POSTER 104

METABOLIGHTS - METABOLOMICS DATABASE

Kenneth Haug (1), R. Alcántara (1), H. Cao (1), P.

Conesa (1), P. de Matos (1), M. Rijnbeek (1) and C.

Steinbeck (1), R. Salek (1,2) and J. Griffin (2).

1. European Bioinformatics Institute, Wellcome

Trust Genome Campus, Hinxton, Cambridgeshire,

CB10 1SD. 2. University of Cambridge, Department

of Biochemistry, Building O, Downing Site,

Cambridge CB2 1QW.

MetaboLights is a database for Metabolomics

experiments and derived information. It is the first

comprehensive, cross-species, cross-technique

database which combines curated reference data of

pure metabolites, curated information about their

occurrence and concentration in species, organs,

tissues and cell types under various condition with

data characterizing the experiment which lead to

these findings. Protocols documenting how

metabolomics experiments were conducted will also

be made available. Like all other EBI resources, the

MetaboLights databases will be completely open to

the public, including open access to the data. Data

will be made available in publicly accepted open

standards. The software will be open source. One of

the main submission channels for MetaboLights will

use the ISA Tools Suite1 MetaboLights is not meant

to replace specialist resources for Metabolomics.

Rather, it will build on prior art and collaborate. We

are dedicated to close collaboration with all major

parties involved in the creation of this prior art, such

as the Metabolomics Society, Metabomeeting and

the Metabolomics Standards Initiative (MSI). The

MetaboLights project group has taken the initiative

to formally reform the MSI. MetaboLights aim to

agree on formal data sharing agreements with

major resources such as the Human Metabolome

Database, the Golm Metabolome Database and the

Rikken Metabolomics Platform. MetaboLights is

funded by the BBSRC as a joint project between The

Chemoinformatics and Metabolism team at EMBL-

EBI (Christoph Steinbeck) and The Department of

Biochemistry at the University of Cambridge (Jules

Griffin).

POSTER 105

CHEMOMETRIC APPROACHES TO IMPROVE PLSDA

MODEL OUTCOME FOR PREDICTING HUMAN NON-

ALCOHOLIC FATTY LIVER DISEASE USING UPLC-MS

AS A METABOLIC PROFILING TOOL.

Agustín Lahoz (1), Guillermo Quintás (4), Nuria

Portillo (5), Juan C. García-Cañaveras (1,2), José V.

Castell (1,2, 3) and Alberto Ferrer (5)

1. Unidad de Hepatología Experimental, Instituto de

Investigación Sanitaria - Fundación Hospital La

Fe,Valencia, Spain. 2. Departamento de Bioquímica y

Biología Molecular, Facultad de Medicina, Universidad de

Valencia, Spain. 3. CIBERehd, Centro de Investigaciones

Biomédicas en Red de Enfermedades Hepáticas y

Digestivas, FIS, Spain. 4. Unidad Analítica Mixta Instituto

de Investigación Sanitaria-Fundación Hospital La Fe,

Valencia, Spain. 5. Department of Applied Statistics,

Operations Research and Quality, Universidad Politécnica

of Valencia, Valencia, Spain.

An MS-based metabolomics strategy including

variable selection and PLSDA analysis has been

assessed as a tool to discriminate between non-

steatotic and steatotic human liver profiles.

Different chemometric approaches for

uninformative variable elimination were performed

by using two of the most common software


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packages employed in the field of metabolomics

(i.e., MATLAB and SIMCA-P). The first considered

approach was performed with MATLAB where the

PLS regression vector coefficient values were used

to classify variables as informative or not. The

second approach was run under SIMCA-P, where

variable selection was performed according to both

the PLS regression vector coefficients and VIP

scores. PLSDA models performance features, such as

model validation, variable selection criteria, and

potential biomarker output, were assessed for

comparison purposes. One interesting finding is that

variable selection improved the classification

predictiveness of all the models by facilitating

metabolite identification and providing enhanced

insight into the metabolic information acquired by

the UPLC-MS method. The results prove that the

proposed strategy is a potentially straightforward

approach to improve model performance. Among

others, GSH, lysophospholipids and bile acids were

found to be the most important altered metabolites

in the metabolomic profiles studied. However,

further research and more in-depth biochemical

interpretations are needed to unambiguously

propose them as disease biomarkers.

POSTER 106

ROBUST METABOLITE PROFILING AND

IDENTIFICATION EMPLOYING HIGH RESOLUTION

MS STRATEGIES AND DEDICATED SOFTWARE

Madalina Oppermann (1), Helen Welchman (1),

David Portwood(2), Mark Earll(2), Mark Seymour(2),

Charles Baxter (2), Martin Hornshaw (1), Graham

Seymour(3), Charlie Hodgman(3),

(1) Thermo Fisher Scientific, UK (2) Syngenta, UK (3)

Nottingham University, UK

Introduction: Metabolomics has been identified as a

key mass spectrometry-based approach in the

analysis of cultivars that contribute to a sustained

agro development, by detecting plant varieties

which are robust, healthy and nutrition-rich.

Syngenta’s world-leading agribusiness has a

particular interest in seeds and crop protection.

High resolution/accurate mass LC-MS analyses

provide outstanding sensitivity, accuracy and wide

dynamic range while strong performance for high

throughput is enabled. However, huge amounts of

information are generated, and the automated, fast

and reliable extraction of relevant information is

essential before launching costly metabolite

identification efforts. Herewith, results from HR/AM

tomato metabolite profiling experiments followed

by intelligent, automated data mining and

reduction, will be presented. Method: Tomato

samples were extracted as follows: triplicate

biological replicates of two tomato cultivars were

analyzed at four time points of fruit development

stages using fast reversed-phase chromatography

prior to mass spectrometric analysis, carried out on

a hybrid high resolution mass spectrometer

instrument. Strategies for metabolite profiling, data

mining and metabolite identification were

successfully applied and encompassed sample

measurement in positive and negative ion mode

electrospray ionization in conjunction with multiple

dissociation techniques and data processing with a

dedicated, novel software package. Preliminary

data: Hundreds of components were profiled at

resolutions up to 100,000 useful for accurate and

sensitive relative quantification experiments. Using

external instrument calibration analyte masses were

measured with high, sub-ppm to max 2ppm

accuracy, leading to strongly suggestive

identifications based on elemental composition

analysis. Data processing includes the reduction of

millions of data points to hundreds of bona-fide

“components” by eliminating noise, performing

peak filtering and by combining information from

isotopic peak profiles, adducts and dimers into a

single accurate mass and retention time

corresponding to a unique analyte. Based on the

HR/AM data generated, components are identified

in either proprietary or public access databases.

Data processing continues with a sophisticated

alignment procedure to generate an output table of

annotated components along with their relative

abundance measured in each sample. Finally,

univariate or multivariate statistics are applied


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across the samples, to reveal changes and trends

that can be correlated to biochemical events.

Different MS/MS fragmentation regimes, resonance

excitation CID or higher energy collisional activation

(HCD) experiments, were employed to further

confirm the identification of metabolites of interest.

POSTER 107

METFUSION: INTEGRATION OF LIBRARY- AND IN-

SILICO COMPOUND IDENTIFICATION STRATEGIES

Michael Gerlich, Steffen Neumann

Department of Stress- and Developmental Biology Leibniz

Institute of Plant Biochemistry

Mass spectrometry (MS) has been established as the

standard identification method for metabolomics.

Tandem-MS provides valuable information for

compound identification, but spectral interpretation

is still a tedious task and remains the main

bottleneck metabolomics experiments. Spectral

libraries like MassBank (Horai et al, 2010) provide

reference spectra for many compounds, but still

their chemical coverage is far from complete,

especially in the light of (estimated) 200.000

compounds in the plant kingdom (Dixon and Strack,

2003). Compound libraries such as KEGG or

PubChem on the other hand contain 15,000 and 28

million compounds respectively, but do not allow to

search with tandem-MS peak lists directly. With

computational mass spectrometry tools such as

MetFrag (Wolf et al, 2010) it is possible to perform

in silico fragmentation of structures and search

compound libraries with tandem-MS peak lists.

These in-silico searches are more specific than

simple exact mass queries, but less reliable

compared to experimentally determined reference

spectra. We present MetFusion as a new method to

combine the search results from MassBank with

those from MetFrag, to obtain improved

identification results from tandem-MS data. We

evaluate the approach on a set of 1100 spectra from

MassBank, and simulate the real-world case where

the measured compound (or even chemically similar

ones) are not present in the reference library.

References: Horai, H. et el. MassBank: a public repository for sharing

mass spectral data for life sciences. J Mass Spectrom, 2010, 45, 703-714

Dixon, R. A. & Strack, D. Phytochemistry meets genome analysis, and

beyond. Phytochemistry, 2003, 62, 815-816 Wolf, S.; Schmidt, S.;

Müller-Hannemann, M. & Neumann, S. In silico fragmentation for

computer assisted identification of metabolite mass spectra BMC

Bioinformatics, 2010, 11, 148.

POSTER 108

NEW TOOL FOR ANALYSIS OF GC-FID DATA

Lea Johnsen

Copenhagen University, Life / Chr. Hansen, Copenhagen,

Denmark.

When analysing GC-FID data with standard GC-

manufacturing software only peaks in specified

windows is extracted, if the retention time drifts or

new peaks occur the user have to redo the setup.

The presented tool identifies all peaks which fulfil

the specifications set by the user, it also gives the

possibility to use retention index and in this way

minimise the problem with changes in retention

time (e.g. due to column change). An algorithm for

Matlab (Mathworks) has been developed which

extract the heights, widths and retention times. The

user is offered the option to change a set of

parameters in order to adjust the algorithm to

match the actual dataset (i.e. threshold for

noise/baseline estimation, min/max peak width,

maximum retention time shift during the run, and

minimum peak height). In order to improve the

user-friendliness a graphical user interface has also

been developed. The interface makes it easy to

change settings and inspect the raw chromatograms

and the extracted features in different plots. The

interface can also export the result to Excel

(Microsoft) along with the specific settings used in

the calculations. Another possibility is to use PLS-

toolbox (Eigenvector) to inspect the results (heights)

with e.g. PCA.


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POSTER 109

A KNOWLEDGE BASED STRATEGY FOR EXTRACTION

OF METABOLIC INFORMATION IN GC/MS DATA

SETS.

Pär Jonsson, Henrik Antti

Department of Chemistry, Computational Life Science

Cluster, Umeå University, SE-901 87 Umeå, Sweden

In metabolomics the same type of samples (CSF,

plasma or urine) are often used in several studies

using the same or similar instrumental setup. Thus,

in theory the same metabolites should be detected

each time. Data processing methods (Peak detection

algorithms and curve resolution strategies) are

aiming to detect all peaks (metabolites) present in a

samples or a set of samples given that a multi

sample processing strategy is used. This type of

processing methods is very useful for collecting

knowledge regarding the metabolite content.

However, a drawback is that they do not take prior

knowledge about sample composition into account.

In addition problems with detecting and quantifying

minor components in data especially if the elute in

the same region as some major components i.e.

sugars or urea, are also a reality using peak

detection and curve resolution strategies. We

believe that a targeted or knowledge based

approach could handle such situations with much

more consistency and with a higher quality output

as an end result. We here present a strategy for

using prior knowledge when extracting metabolic

information from metabolomic GC/MS data. The

strategy include five steps; i) building up a

knowledge database ii) metabolite detection, iii)

metabolite quantification, iv) validation and v)

residual analysis (for handling new compounds e.g.

drug metabolites). We will also discuss how this this

prior knowledge can be incorporated in the

hierarchical multivariate curve resolution (HMCR)

strategy [1,2] and how to cope with analytical drifts

using nonlinear alignment. The strategy is

exemplified with a standard mix data set (spiked

with known metabolite concentrations) and a

clinical data set acquired for human cerebrospinal

fluid (CSF) samples.

References: 1. Jonsson P, Johansson AI, Gullberg J, Trygg J, A J, Grung

B, Marklund S, Sjöström M, Antti H, Moritz T (2005) High-throughput

data analysis for detecting and identifying differences between samples

in GC/MS-based metabolomic analyses. Anal Chem 77: 5635-5642. 2.

Jonsson P, Johansson ES, Wuolikainen A, Lindberg J, Schuppe-Koistinen

I, Kusano M, Sjöström M, Trygg J, Moritz T, Antti H (2006) Predictive

metabolite profiling applying hierarchical multivariate curve resolution

to GC-MS data - A potential tool for multi-parametric diagnosis. J Prot

Res 5: 1407-1414.

POSTER 110

VARIABLE SELECTION METHODS IN PLS

REGRESSION - A COMPARISON STUDY ON

METABOLOMICS DATA

İbrahim Karaman (1), Mette S. Hedemann (1), Knud

E. Bach Knudsen (1), Achim Kohler (2, 3)

1. Aarhus University, Dept. of Animal Science, P.O.

Box 50, 8830 Tjele, Denmark. 2. Centre for

Integrative Genetics (CIGENE), Department of

Mathematical Sciences and Technology (IMT),

Norwegian University of Life Sciences, 1432 Ås,

Norway. 3. Nofima Mat AS, Osloveien 1, N-1430 Ås,

Norway.

Partial least squares regression (PLSR) has been

applied to various fields such as psychometrics,

consumer science, econometrics and process

control. Recently it has been applied to

metabolomics based data sets (GC/LC-MS, NMR)

and proven to be a very powerful in situations with

many variables for the purpose of reducing over-

fitting problems and providing useful interpretation

tools. It has excellent possibilities for giving a

graphical overview of sample and variation patterns.

It can handle co-linearity in an efficient way and

make it possible to use different highly correlated

data sets in one integrated approach. Due to the

high number of variables in data sets (both raw data

and after peak picking) the selection of important

variables in an explorative analysis is difficult,

especially when different data sets of metabolomics

data need to be related. Variable selection (or

removal of irrelevant variables) aids the model by


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improving predictions, providing better

interpretation and decreasing measurement costs.

In addition, overfitting is an issue when we are

dealing with high number of variables. To overcome

this, we used cross-model-validation in order to

validate the models. In this paper different

strategies for variable selection on PLSR method

were considered and compared with respect to

selected subset of variables and the possibility for

biological validation. Sparse PLSR [1] as well as PLSR

with Jack-knifing [2] was applied to data in order to

achieve variable selection prior to comparison.

Sparse PLSR is based on penalization of the loading

weights (by elastic net, soft/hard thresholding etc.)

on a PLSR model. In PLSR with Jack-knifing,

significance of variables are calculated by

uncertainty test. The data set used in this study is

LC-MS data from an animal intervention study. The

aim of the metabolomics study was to investigate

the metabolic profile in pigs fed various cereal

fractions with special attention to the metabolism of

lignans using LC-MS based metabolomic approach.

References 1. Lê Cao KA, Rossouw D, Robert-Granié C, Besse P: A Sparse

PLS for Variable Selection when Integrating Omics data. Statistical

Applications in Genetics and Molecular Biology, 7:Article 35, 2008. 2.

Martens H and Martens M. Modified Jack-knife estimation of parameter

uncertainty in bilinear modelling by partial least squares regression

(PLSR). Food Quality and Preference, 11:5-16, 2000.

POSTER 111

DOUBLE-CHECK: VALIDATION OF DIAGNOSTIC

STATISTICS FOR PLS-DA MODELS IN

METABOLOMICS STUDIES

Ewa Szymanska(1), Edoardo Saccenti(2), Age K.

Smilde(2), Johan A. Westerhuis(2)

1. Netherlands Metabolomics Centre, Einsteinweg 55,

2333 CC Leiden, the Netherlands 2. Biosystems Data

Analysis, Swammerdam Institute for Life Sciences,

University of Amsterdam, Science Park 904, 1098 XH,

Amsterdam, The Netherlands.

Partial Least Squares – Discriminant Analysis (PLS-

DA) is a PLS regression method with a special binary

‘dummy’ y-variable and it is commonly used for

classification purposes in metabolomics studies.

Several statistical approaches to validate outcomes

of PLS-DA analyses are currently in use e.g. double

cross validation procedures or permutation testing.

However, there is a great inconsistency in the

optimization and the assessment of performance of

PLS-DA models due to many different diagnostic

statistics currently employed in metabolomics data

analyses. In this study, properties of four diagnostic

statistics of PLS-DA, namely the number of

misclassifications (NMC), the Area Under the

Receiver Operating Characteristic (AUROC), Q2 and

Discriminant Q2 (DQ2) were discussed. All four

diagnostic statistics were used in the optimization

and the performance assessment of PLS-DA models

of three different-size metabolomics data sets

obtained with two different types of analytical

platforms and with different levels of known

differences between groups. Statistical significance

of obtained PLS-DA models was evaluated with

permutation testing. NMC and AUROC used in PLS-

DA models were more powerful in detecting very

small differences between groups than Q2 and

Discriminant Q2 (DQ2). Reproducibility of PLS-DA

models outcomes, models complexity and

permutation test distributions were also

investigated to explain this phenomenon. Lower

complexity of models and higher number of

permutation tests and submodels required to

accurately estimate statistical significance of the

model performance was observed for DQ2 or Q2 as

diagnostic statistics. NMC and AUROC seem more

efficient and more reliable diagnostic statistics and

should be recommended in all types of metabolomic

studies.

POSTER 112

KEGG AND GENOMENET RESOURCES FOR

INTERPRETING METABOLOMIC DATA

Susumu Goto, Masaaki Kotera Toshiaki Tokimatsu

Yuki Moriya Zen-ichi Nakagawa Craig Wheelock

Minoru Kanehisa

Bioinformatics Center, Institute for Chemical Research,

Kyoto University


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The KEGG (Kyoto Encyclopedia of Genes and

Genomes) project has produced and is maintaining a

reference data for biological systems information in

the form of pathway diagrams and hierarchical texts

of functional classification. The reference data is

associated with genomic and chemical information,

e.g. by relating the protein-coding genes in the

pathways to the data produced by genome and

metagenome projects. As of August 2011, over

1,500 complete genomes and 100 metagenome

samples have been applied to the reconstruction of

pathways. Similarly, metabolomics data can be

applied to the interpretation by means of pathway

mapping and we have been developing several tools

and resources. KegArray and KEGG Mapper are

simple mapping tools for quantitatively measured

metabolomic, transcriptomic and proteomic data.

They search the corresponding objects in KEGG

pathway diagrams and color them according to the

measurements. If the corresponding chemical

compounds are not found in KEGG, it might be

necessary to search structurally similar compounds

or new possible biochemical pathways for the target

compounds. GenomeNet provides genomic and

chemical data analysis tools for such purposes by

integrating KEGG and other resources. One such

tool is SIMCOMP, a graph-based structural similarity

search tool for a query compound structure,

searches KEGG COMPOUND for metabolic and other

chemical compounds, KEGG DRUG for marketed

drugs and KNApSAcK for plant secondary

metabolites. Another tool PathPred computes

possible novel reaction pathways using reaction

patterns extracted from the biochemical reactions in

known metabolic pathways. We believe that those

tools integrated with various KEGG databases

should be a useful resource for interpreting

metabolomic data.

POSTER 113

DEVELOPMENT OF AN INTEGRATED STRATEGY FOR

THE HANDLING AND MANAGEMENT OF GC/MS

AND LC/MS(MS) DERIVED METABOLOMICS DATA

Nora Katharina, Nicole Neumann, Büschl Christoph,

Schöfbeck Denise, Kluger Bernhard, Lehner Sylvia,

Krska Rudolf, Schuhmacher Rainer.

University of Natural Resources and Life Sciences

Vienna, Department IFA-Tulln, Center for Analytical

Chemistry, Konrad-Lorenz-Strasse 20, 3430 Tulln,

Austria.

Metabolomics tries to measure the entirety of all

low molecular weight metabolites which are

produced by a living organism at a certain time

point. As a consequence of the large diversity of the

physical properties of these metabolites not a single

analytical technique but a combination of several

are required, each producing large amounts of raw

data, which have to be processed in various ways.

As a consequence efficient and integrated data

handling strategies are needed to process and

analyse metabolomics data appropriately. In this

poster we present an integrated strategy for the

handling of GC-MS and LC-high resolution MS(/MS)

data which is currently established in our

laboratory. Different steps of data handling such as

data pre-processing, data processing and

subsequent data analysis will be covered. Moreover,

as we intend to do both non-targeted as well as

targeted metabolomics of fungi and plants,

comprehensive metabolite databases have to be

established for the organisms of interest. These

aspects of the strategy, as well as the in-house

database are being implemented on an in-house

server that has to be suited to handle the

computational extensive parts of the presented

approach. This will also be illustrated on the poster.

In our approach the measured data is processed to

extract only peaks of true metabolites without prior

knowledge of the dataset and eliminate peaks

originating from sample preparation, analytical

devices or even so called pseudo ions that are


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associated with certain analytical techniques.

Subsequently chromatographic peaks and

corresponding mass spectra which have been

assigned to true metabolites are then investigated

and attempted to further characterize and identify

the respective metabolites by MS/MS

measurements and comparison with existing

metabolite databases. This will lead to a

comprehensive in-house database which will not

only contain chromatographic data and MS(/MS)

spectra. Besides its use for the identification of

metabolites the database shall be used to collect

further relevant biological and chemical

information, such as pathway links, to generate a

more complete biological view of the investigated

organism. Therefore the possibility to connect to

online resources to gather this additional

information programmatically is being

implemented. Characterised datasets are further

analysed with statistical methods to identify shared

metabolites that are up – or downregulated

between different sample groups and to generate

distinct sample profiles to be further used for data

interpretation.

POSTER 114

GUINEU: LC-MS DATA PREPROCESSING AND

ANALYSIS

Sandra Castillo, Tuulikki Seppänen-Laakso, Tuulia

Hyötyläinen, Matej Orešič

VTT Technical Research Centre of Finland, Espoo, FI-

02044 VTT, Finland

Guineu is a modular open source software written in

Java for preprocessing and analysis of high

throughput metabolomics data. The Liquid

Chromatography coupled with Mass Spectrometry

(LC-MS) data preprocessed with MZmine software is

the input for Guineu. The output of Guineu can be

exported to comma separated value (CSV) files,

Excel sheets or to a relational database. It has

functions for peak list alignment, normalization,

identification, and data analysis of LC-MS data. It

allows normalization of data using internal

standards, or linear factors such as average intensity

or maximum intensity. Data analysis functions

include hypothesis tests (T-test, ANOVA), computing

several statistics (fold changes, medians, coefficient

of variation) dimensionality reduction (Principal

component analysis, Sammon's mapping,

Curvilinear distance analysis), clustering (density

based clustering, k-means, and hierarchical

clustering), visualization of the data (heatmaps). An

interface to R has been incorporated in Guineu,

which allows it to use functions from R.

POSTER 115

GUINEU: GC×GC/TOFMS DATA PREPROCESSING

AND ANALYSIS

Sandra Castillo, Ismo Mattila, Tuulia Hyötyläinen,

Matej Orešič

VTT Technical Research Centre of Finland, Espoo, FI-

02044 VTT, Finland

We developed a software called Guineu for efficient

treatment of large data sets produced by two-

dimensional gas chromatography combined with

time-of-flight mass spectrometry (GC×GC/TOFMS).

Guineu uses GCxGC/TOFMS data preprocessed by

instrument vendor software as a starting point for

further processing. Guineu has methods for

alignment of the data, normalization, data filtering,

verification of identification using retention indexes,

and automated group-type identification of the

compounds. Guineu also has methods for data

analysis (e.g. significance tests to compare means,

dimensionality reduction, clustering and

visualization), and for exporting the data to files or

relational databases.

POSTER 116

METABOLIC PHENOTYPING OF CAENORHABDITIS

ELEGANS BY WHOLE ORGANISM NMR

SPECTROSCOPY: APPLICATIONS TO FUNCTIONAL

GENOMICS IN AGING AND TOXICOLOGY

Bénédicte Elena-Herrmann(1), Clément Pontoizeau

(1), Andrei Bunescu (1), Laurent Mouchiroud (2),


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Linh-Chi Bui (3), Nicolas Dallière (2), Pierre Toulhoat

(1), Lyndon Emsley (1), Robert Barouki (3), Xavier

Coumoul (3), Florence Solari (2).

1. Université de Lyon, CNRS/ENS Lyon/UCB-Lyon 1,

Centre de RMN à Très Hauts Champs, Villeurbanne,

France. 2. Université de Lyon, CNRS, UMR5201,

Centre Léon Bérard, Lyon, France. 3. INSERM UMR-

S 747, Université René Descartes, Paris, France.

The model organism Caenorhabditis elegans (C.

elegans) is widely used to investigate biological

processes and disease mechanisms. We developed a

robust protocol based on 1H High Resolution Magic

Angle Spinning (HR-MAS) Nuclear Magnetic

Resonance (NMR) spectroscopy for studying the

metabolism of intact C. elegans worms. We

demonstrated its potential for the characterization

of metabolic signatures induced by genetic

mutations allowing functional genomics at the

system level (1). Here, we present metabolic

signatures of a range of C. elegans mutants that

provide insight into molecular mechanisms of aging

and toxicology. Beforehand, we analyse the impact

of bacterial diet on C. elegans whole organism

metabolic fingerprints that may alter the course of

many C. elegans studies First, we show how C.

elegans metabolic profiles can be modulated by the

OP50 bacterial diet, as exogenous cyclopropane

fatty acids (CFA) that are synthetized by the bacteria

at saturation, are integrated into the worm lipid

profiles. The CFA level can exceed 30% of the total

amount of fatty acids in the worm. We then

investigate aging processes in C. elegans by

monitoring the metabolic perturbations linked to

caloric restriction (CR), a well-known process

responsible for lifespan increase in various

organisms. We compare metabolic profiles obtained

by 1H HR-MAS NMR spectroscopy for wild type

nematodes and CR mutants during ageing (3-day old

and 7-day old): eat-2 mutants, established model of

CR, and slcf-1 mutants, which mimic caloric

restriction when fed ad libitum (2). Metabolic

signatures of both ageing and dietary restriction in

intact C. elegans are found to share similarities with

signatures previously described from the plasma of

non-human primates. Furthermore, we found that

the difference between the metabolic profiles of

wild-type worms and CR mutants increases with

age. 7-day old CR mutants appear metabolically

younger than their wild type counterparts. Finally,

we characterize metabolic fingerprints of C.elegans

mutants lacking the aryl hydrocarbon receptor

(AhR), which plays a central role in xenobiotic-

induced toxicity and carcinogenesis.

References: 1. Blaise B. J. et al. Proc. Natl. Ac. Sci. USA 104, 19808

(2007). 2. Mouchiroud L. et al. Aging Cell 10, 39 (2011).

POSTER 117

PREDICTION OF FOOD-RELATED MICROBIAL

METABOLOME DERIVED FROM POLYPHENOL-RICH

FOODS

Anna-Marja Aura, Ismo Mattila, Tuulia Hyötyläinen,

Gopal Peddinti and Matej Orešič

VTT Technical Research Centre of Finland, P.O.Box 1000,

Tietotie 2, Espoo, FI-02044 VTT, Finland.

Dietary recommendations define a healthy diet as

one containing a substantial amount of plant foods.

Plant foods are rich in polyphenols and their known

circulating metabolites are mostly those derived

from colonic microbial action. Thus the consumption

of dietary polyphenols correlates with both the

plant food intake and the circulating metabolites.

The known circulating metabolites consist of the

transiently appearing plant derived compounds and

their microbial metabolites originated from the

colon. Plant foods contain also other

phytochemicals, which diversifies the food-related

metabolome formed under microbial interaction. It

is challenging to distinguish the connection between

the foods and their metabolome without exclusion

of the other sites of metabolism (intestine, liver).

The solution to this challenge is an application of the

in vitro colon model. The VTT colon model applies

human faecal suspension in vitro in strictly

anaerobic conditions in the body temperature. The

food is incubated with the faecal suspension and a

comprehensive two-dimensional gas

chromatography with a time-of-flight mass


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spectrometry (GCxGC-TOFMS) is used for the

metabolomic analysis. The technique is coupled

with a compound library, but also authentic

standards are used to quantitatively indicate known

metabolites. Quantitative results show similar

metabolites at different relative proportions

depending on foods. Systems biological tools are

applied on semi-quantitative data to find novel

metabolites at different time points by comparison

with a control faecal suspension or the buffer alone.

The microbial metabolome is displayed as heat

maps of fold changes against the controls during the

24 h incubation. Several vegetables, fruits and

beverages were investigated. The connection with

human data will be discussed.

The work presented here was supported by project

ETHERPATHS (EC Contract no: FP7-KBBE-222639).

POSTER 118

EXPLORING PLASMA MARKERS OF COFFEE INTAKE

BY UNTARGETED PROFILING OF SAMPLES

COLLECTED FROM A COHORT STUDY

Lars Ove Dragsted(1), Bibiana Garcia Bailo(2), Louise

Hansen(3), Jane Christensen(3), Thaer Barri(1),

Ahmed El-Sohemy(2), Klaus Kaae Andersen(3), Kim

Overvad(4), Anne Tjønneland(1)


Sciences, University of Copenhagen, 1958 Frederiksberg,

Denmark. 2. Department of Nutritional Sciences,

University of Toronto, Toronto, Ontario. 3. Danish Cancer

Society, Institute of Cancer Epidemiology, Copenhagen,

Denmark. 4. Department of Epidemiology, School of

Public Health, Aarhus University, Aarhus, Denmark. 5.

Department of Cardiology, Aalborg Hospital, Aarhus

University Hospital, Aalborg, Denmark.

Background: Untargeted metabolic profiling has a

great potential for identification of new markers of

exposure or effect. However the analysis of samples

from complex settings such as those collected for

epidemiological study biobanks present a challenge

because there is usually only one sample per

individual leaving little room for control of variations

and because there is usually no control of time since

last meal, life style factors or personal habits. On the

other hand, these studies often contain a wealth of

information on dietary and life style habits,

genotypes etc. that could prove useful to evaluate

whether useful information can be retrieved from

metabolic profiles. We used here a subset of 322

colon cancer cases and controls from the Danish

branch of the European Prospective study into

Cancer (EPIC) study, to investigate the feasibility of

metabolic profiles to look for markers related to

self-reported coffee intake and to the measured

CYP1A2 genotype.

Method: A cross-sectional study of reported coffee

consumption-related markers and markers of the

CYP1A2 fast metabolizer genotype was conducted in

a subset of 322 plasma samples from the Danish

Diet , Cancer and Health cohort, a branch of EPIC .

The subset represents a pilot case-referent study on

colorectal cancer among females and half of the

subjects were diagnosed with CRC 2-8 yrs after

enrolment, while the referents did not have cancer

up until 8 yrs after enrolment. The aim was to

evaluate whether markers of life-style and dietary

habits or phenotypic markers of gene

polymorphisms can be identified by untargeted

metabolic profiling in a setting with minimal control

of individual variation and sampling time. Each

volunteer answered a questionnaire including a

question on their regularity of coffee drinking. This

question was translated into the approximate intake

of coffee in ml/day. The volunteers had also been

genotyped by RFLP for the number of alleles of the

fast allele of the CYP1A2 gene. Plasma samples were

retrieved from 11-15 years of liquid nitrogen

storage, deproteinized and profiled by a 6 min ultra-

high pressure linear polarity gradient (0.01% formic

acid – 80%acetonitril, 20% acetone) on a C18 BEH

column with a mass detector. A quadropole allowed

masses from 50-1000 (m/z) to pass on to a time-of-

flight detector which was set to scan every 0.08 s.

Energies were set low to avoid excessive

fragmentation and all samples were profiled twice

with the mass detector set to positive or negative


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mode, respectively. The centroided data were

aligned and normalized to total sample intensity

using Markerlynx software (Waters). Data reduction

was performed by selecting only data where at least

80% of the samples in one quartile of reported

habitual coffee intake or at least 80% of the samples

in one allelic group intake had a recorded value. The

remaining data points were set to missing. A general

linear model was used with these features to

identify potential markers of coffee intake. Features

with a false discovery rate (q-value) below 0.05

were assumed to represent markers of coffee

intake.

Findings: The coffee intake in the subset was 0-1600

ml/d and quartiles were approximately equal to <1 ,

1-2, 2-3 and >3 cups/d. A total of 1072 features

were observed in positive mode and 642 in negative

mode. Using univariate marker selection we found

19 features in positive mode and 17 features in

negative mode which had a false discovery rate of

q<0.05. Several of these were mother- and daughter

ions of the same compounds and could be observed

both in positive and in negative mode. The markers

include exposure-related compounds such as

caffeine and cafestol and their metabolites. Caffeine

metabolites include paraxanthine,

monomethylxanthines, and methyluric acids.

Tetrahydrocafestol glucuronide was tentatively

identified as a human cafestol metabolite. Other

coffee-exposure related plasma metabolites include

hippuric acid, a metabolite related to the high

exposure to coffee phenols. Other markers related

to coffee consumption include cotinine, a marker

reflecting the higher level of tobacco use among

high coffee consumers (Q1 vs. Q4, P<0.001). Eight

features so far remain unidentified, among them

two features that decrease with coffee intake.In

contrast, markers related to the number of fast

CYP1A2 alleles was scarce, no markers had q<0.05

and only four markers had q<0.25. None of these

formed clusters of related compounds indicating

that a general phenotypic fingerprint of this

genotype could not be identified. We conclude that

the markers identified by our untargeted approach

are highly likely to represent true markers related to

coffee drinking in human populations where no

control over personal or sampling variables has

been exercised, however no markers could be found

for the more objective genotype groups. While the

single coffee markers may be useful at the group

level to identify coffee intake, none of them could

be used at the individual level as evaluated by the

questionnaire. Cafestol and its metabolite were the

markers that came closest to be actual coffee

exposure markers. Combination of the markers

could partially separate the first and the fourth

quartile using principal components analysis,

indicating that chemometrics could be used to

predict coffee intake. Further investigations are on-

going to evaluate possible interactions between

CYP1A2 genotype and markers of coffee

consumption in individuals with a high coffee intake.

POSTER 119

INFLUENCE OF SAMPLE COLLECTION AND STORAGE

TO THE METABOLIC PROFILE OF BLOOD

Tuulia Hyötyläinen(1), Sirkku Jäntti(1), Maren

Pflueger(2), Ismo Mattila(2), Tuulikki Seppänen-

Laakso(1), Anna-Liisa Ruskeepää(1), Ulla

Lahtinen(1), Leena Öhrnberg(1), Hannele Yki-

Järvinen(3), Anette-G. Ziegler(2), Matej Orešič(1)

1. VTT Technical Research Centre of Finland, Espoo, FI-

02044 VTT, Finland. 2. Forschergruppe Diabetes e.V. at

Helmholtz Zentrum, Munich, Germany. 3. Division of

Diabetes, Department of Medicine, Helsinki University

Central Hospital, Helsinki, Finland

In most metabolomic studies, blood is used as the

sample as it reflects systemic changes in the

metabolome. Whole blood is seldom used in the

studies, as it is more convenient to use plasma or

serum. However, the critical role of the sampling,

storage and sample preparation is often neglected

even though any error made in these steps will lead

to biased results due to conversion or degradation

of metabolites, or due to contamination or loss of

compounds. In this study, the influence of sampling

and storage on the metabolic profiles of serum and


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plasma samples was studied. The blood samples

were collected either in tubes containing EDTA,

citrate or heparin, and treated and stored in

different ways after the collection. The samples

were then analysed with two highly efficient

platforms, namely UPLC-QTOFMS and GCxGC-

TOFMS, covering both nonpolar lipids and polar

metabolites. Altogether over 2000 metabolites in

serum and plasma samples can be detected with the

two platforms. The method of clinical preparation of

human blood samples has no major effects on

comprehensive lipidomic analyses of circulating

lipids, however, major effect on the levels of polar

metabolites was observed. EDTA as anticoagulant is

poorly suited for the analysis of polar metabolites.

Sodium citrate causes problems in determination of

citric acid and its derivatives, and as these

compounds are important metabolites in TCA cycle,

the suitability of sodium citrate is limited. Also the

storage conditions had an effect on the metabolic

profiles. Serum proved to be the best option for the

metabolic profiling of polar compounds.

POSTER 120

METABOLIC PROFILING OF SERUM AND ADIPOSE

TISSUE OF MONOZYGOTIC TWINS AFTER HIGH-FAT

MEAL

Sirkku Jäntti(1), Maarit Kivilompolo(1), Ismo

Mattila(1), Tuulikki Seppänen-Laakso(1), Heli

Nygren(1), Anna-Liisa Ruskeepää(1), Ulla Lahtinen,

Jaakko Kaprio(3), Jing Tang1(1), Kirsi Pietiläinen (2,3)

Tuulia Hyötyläinen(1) and Matej Orešič(1)

1. VTT Technical Research Centre of Finland, Espoo, FI-

02044 VTT, Finland. 2. Department of Psychiatry, Helsinki

University Central Hospital, Helsinki, Finland. 3.

Department of Public Health, University of Helsinki,

Finland.

A huge number of metabolic pathways are involved

in the regulation of human health. Obesity can

cause severe changes in the metabolic balance,

however, the exact mechanisms by which obesity

contributes to various disturbances is poorly

characterised. A viable approach to study the

effects of obesity in the absence of confounding due

to genetic effects is to study monozygotic twins

discordant for obesity. The obese and the non-

obese co-twins share the same genes and differ only

by environmental exposures and the resultant

acquired obesity. In this study, the effect of high-fat

meal on the metabolic balance of obese adults was

studied, using a group of healthy monozygotic twins

discordant for obesity as a study group. Serum

samples were collected before and after the meal (0

to 120 min), and also adipose tissue biopsies were

collected. For the detailed characterisation of

changes in the metabolic profiles, both non-

targeted and targeted methodologies, utilising

several chromatographic methodologies combined

with mass spectrometry were applied. The global

lipid profiles in serum and adipose tissue were

profiled with UPLC-QTOFMS, while polar small

metabolites were determined by GCxGC-TOFMS.

Targeted methods using UPLC-QQQMS were

developed for the analysis of bile acids in serum and

eicosanoids and steroids in adipose tissue. The

metabolic profiles of the twin pairs were compared

in baseline and after the meal. The results showed

that in baseline, the levels of large number of

metabolites in serum were clearly different for

obese and lean twins, as could be expected. After

the meal, the change in the levels of the metabolites

in serum was different but, interestingly, during the

study period of 2 hours, a large number of

metabolites reached the same level.

POSTER 121

STRATEGIES FOR SELECTING BIOMARKERS FROM

SPECTRAL AND CHROMATOGRAPHIC PROFILES

Tarja Rajalahti(1), Johan Westerhuis(2), Reidar

Arnerberg(3), Age K. Smilde(2) and Olav M.

Kvalheim(4)

1. Department of Neurology, Haukeland University

Hospital, Bergen, Norway. 2. Biosystems Data Analysis,

Swammerdam Institute for Life Sciences, University of

Amsterdam, The Netherlands. 3. Pattern Recognition

Systems AS, Bergen, Norway. 4. Department of

Chemistry, University of Bergen, Norway.


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A general recipe for revealing predictive biomarkers

in a multicomponent profile is presented. The

approach goes through the following sequence: i)

Chromatographic or spectroscopic profiling of

samples, ii) Partial least squares discriminant

analysis (PLS-DA) using double cross validation

together with other validation techniques, iii)

Finding a single predictive latent-variable

component using target projection (TP), and, iv)

Construction of selectivity ratio (SR) plot with

flexible boundary calculated from Wilcoxon rank

sum concept for selection of biomarker candidates.

The boundary has a one-to-one correspondence

with Wilcoxon nonparametric test providing a

probability measure for the biomarker selection.

The approach is illustrated with examples.


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