liquid chromatography/mass spectrometry for metabonomics investigation of the biochemical effects...

RAPID COMMUNICATIONS IN MASS SPECTROMETRY

Rapid Commun. Mass Spectrom. 2008; 22: 873–880

) DOI: 10.1002/rcm.3438
Published online in Wiley InterScience (www.interscience.wiley.com
Liquid chromatography/mass spectrometry for

metabonomics investigation of the biochemical effects

induced by aristolochic acid in rats: the use of

information-dependent acquisition for biomarker

identification

Wan Chan1, Kim-Chung Lee1, Ning Liu1, Ricky N. S. Wong2, Huwei Liu3and Zongwei Cai1*1Department of Chemistry, Hong Kong Baptist University, Hong Kong SAR, China2Department of Biology, Hong Kong Baptist University, Hong Kong, SAR, China3Department of Chemistry, Peking University, Beijing, China

Received 30 October 2007; Revised 17 January 2008; Accepted 17 January 2008

*CorrespoKong BapE-mail: zContract/Grants CHKBU24Contract/Kong BapII-56.

The toxic effects of oral administrations of nephrotoxic and carcinogenic aristolochic acid (AA) to

male Sprague-Dawley rats were investigated by using high-performance liquid chromatography

coupled with a quadrupole time-of-flight mass spectrometer. Analysis of the urine and plasma

samples revealed distinct changes in the biochemical patterns in the AA-dosed rats. After peak

finding and alignment, principal component analysis (PCA) and partial least-squares discriminant

analysis (PLS-DA) were used for multivariate data analysis. Potential biomarkers were studied by

high-resolution mass spectrometry (MS) and tandemmass spectrometry (MS/MS) analyses. TheMS/

MS spectra of all endogenousmetabolites satisfying the pre-defined criteria were acquired in a single

information-dependent acquisition (IDA) analysis, demonstrating that IDA was an efficient

approach for structural elucidation inmetabonomic studies. Citric acid and a glucuronide-containing

metabolite were observed as potential biomarkers in rat urine. A significant increase in plasma

creatinine concentrationwas also observed in theAA-dosed rats, which indicated that AA induced an

adverse effect on the renal clearance function. Copyright # 2008 John Wiley & Sons, Ltd.

The use of biomarkers is becoming increasingly important in

risk assessment. Metabonomics, which has been defined as

‘‘the quantitative measurement of the dynamic multi-

parametric metabolic response of living organisms to

pathophysiological stimulation or genetic modifications’’,1

is emerging as an alternative approach to deal with changes

in endogenous metabolites following toxic exposure, disease

or variation in gene function. Metabonomics, in which

metabolic profiling is used in combination with chemo-

metrics, is considered important for toxicology studies in the

‘‘post-genomic’’ era.2 In combination with proteomics,

transcriptomics and genomics, metabonomics is emerging

as a key technology in pharmaceutical discovery and

development.3 In drug discovery laboratories, metabo-

nomics facilitates target identification, phenotyping and

understanding the biochemical basis of disease and toxicity.

ndence to: Z. W. Cai, Department of Chemistry, Hongtist University, Kowloon, Hong [email protected] sponsor: Research Grant Council, Universityommittee of Hong Kong; contract/grant number:59/06M.grant sponsor: Faculty Research Grant from Hongtist University; contract/grant number: FRG/06-07/

Metabolic profiling of endogenous metabolites in bio-fluids

such as urine, plasma or tissue extracts have been

reported.1,2,4–10 Because urinary metabolite analysis is one

of the few non-invasive toxicology approaches and urine

shows rapid changes in metabolite profile in response to

toxic or disease-induced stress, urine is the most widely used

bio-fluid for metabonomic studies.

High-field proton nuclear magnetic resonance (NMR)

spectroscopy has been used extensively in the early

published metabonomic studies.1,4–9 Recently, mass spec-

trometry (MS)-based techniques have been applied for

metabonomics research. Because urinary metabolites are of

moderate to high polarity and liquid chromatography (LC)/

MS has demonstrated to be efficient for polar compound

analysis, LC/MS is now playing an increasing role in

metabonomic studies.2,8–11 While high-performance liquid

chromatography (HPLC) provides separation thus reducing

spectra overlap and mass spectrometry is a sensitive

detector, LC/MS allows the detection of endogenous

metabolites at low concentrations.

Aristolochic acid (AA) is a mixture of structurally

related nitrophenanthrene carboxylic acid derivatives

found primarily in the genus Aristolochia and Asarum.12,13

Major components of AA include aristolochic acid I

(AA-I, 8-methoxy-6-nitro-phenanthro(3,4-d)-1,3-dioxolo-5-

Copyright # 2008 John Wiley & Sons, Ltd.

Figure 1. Chemical structures of aristolochic acid I and aris-

tolochic acid II.

874 W. Chan et al.

carboxylic acid) and aristolochic acid II (AA-II, 6-nitro-

phenanthro(3,4-d)-1,3-dioxolo-5-carboxylic acid) that differ

by a methoxy group (Fig. 1). AA is a known nephrotoxin and

is also one of themost potent carcinogens in the Carcinogenic

Potency Database.14–16 During a slimming regimen in

Belgium in the early 1990s, because of accidental replacement

of Stephania tetrandra by AA-containing aristolochia fangchi,

about 100 cases of renal disease were reported.15 Some of the

patients died and most of them required dialysis or kidney

transplant. DNA-AA adducts were detected in laboratory

rodents after AA exposure and in patients suffering from

aristolochic acid nephropathy (AAN).17–21 Though being

banned in many countries, AA-containing herbs were still

available on the internet and AAN cases were continuously

reported worldwide.22,23 The most recent case of AAN

associated with the use of Chinese herbal preparations,

which was reported in the UK (2006), once again heightened

the concern about the presence of AA in botanical products

and its high nephrotoxicity.23

The purposes of this study were to investigate the toxic

effects induced by nephrotoxic and carcinogenic AA and to

identify potential biomarkers. High-performance liquid

chromatography coupled with high-resolution quadrupole

time-of-flight (Qq-TOF) MS was used for the metabolic

profiling. Principal component analysis (PCA) was per-

formed for the separation and identification of different

groups (time- and dose-dependence) of the experimental

animals. Partial least-squares discriminant analysis

(PLS-DA) was used for the identification of biomarker

related to AA exposure. Potential biomarkers were identified

from the high-resolution MS and MS/MS analyses.

EXPERIMENTAL

ChemicalsAristolochic acid, mixture of AA-I and AA-II (approx. 1:1),

was purchased from Acros (Morris Plains, NJ, USA). Renin

substrate tetradecapeptide was purchased from Sigma (St.

Louis, MO, USA). Formic acid and sodium hydrogen

carbonate were obtained from Panreac (Barcelona, Spain).

HPLC-grade acetonitrile was obtained from Tedia (Fairfield,

OH, USA). Water was produced using a Milli-Q Ultrapure

water system (Millipore, Billerica, MA, USA) with the water

outlet operating at 18.2MV.


Animal and sample collectionMale Sprague-Dawley rats (n¼ 20) weighing 200–220 g were

used in this study and were acclimatized for 5 days prior to

dosing. The rats were divided into four groups and kept in a

temperature and humidity controlled room with artificial

dark/light cycles. While the control group received 1mL of

the dosing vehicle, the dosed groups received 2 (low-dose),

10 (medium-dose) or 30mgkg�1 day�1 (high-dose) of AA in

0.5% NaHCO3 solution for three consecutive days. Food and

water was provided ad libitum throughout the study. Urine

samples from 8–24 h (night time) on the day prior to dosing

(day 0) and at days 1, 3, 5, 7 of the study were collected and

kept at �208C until sample pre-treatment. Body weights of

individual rats were recorded at days 0, 3, 5 and 7 of the

study. Rats were sacrificed at day 7 by decapitation. The

blood samples were collected and centrifuged at 9000 g for

15min at 48C. The plasma samples were then stored at –208Cuntil analysis.

Sample preparationPrior to the analysis, urine samples were thawed and

centrifuged at 13 000 rpm for 3min to aid settling of coarse

material. From the supernatant 200mL were removed,

diluted with 600mL of Milli-Q water and vortex-mixed for

LC/MS or LC/MS/MS analyses. Plasma samples were

processed for creatinine concentration analysis. After thaw-

ing at room temperature, 700mL of acetonitrile were added to

300mL of plasma samples and vortex-mixed. The mixtures

were stored at �208C for 10min and centrifuged at 13 000 g

for 5min. From the supernatant 800mL were removed,

evaporated to dryness under a stream of nitrogen and

reconstituted in 50mL of acetonitrile.

LC/MS and LC/MS/MS analysesThe diluted urine sampleswere analyzed as onewhole batch,

from one group to another. Rats in the same group were

analyzed one following another, from day 0 to day 7

sequentially. A blank run was performed for every ten

samples analyzed, which was followed by a performance

check analysis of a caffeine standard solution at 0.5 ppm

prior to the next batch of the urinary sample analysis.

Chromatographic separation was performed on an

HP1100 HPLC system (Agilent Technologies, Palo Alto,

CA, USA) equipped with a 15 cm� 2.1mm Symmetry C18

3.5mm reversed-phase column (Milford, MA, USA). The

compartment of the autosampler was set at 48C throughout

the analysis. Aliquots of 8mL each sample were injected onto

the HPLC column for analysis. A linear gradient at a flow

rate of 0.3mLmin�1 was used for the elution, in which

solvent A was 0.1% formic acid and solvent B was

acetonitrile. Initial conditions were 5% B, increased to 95%

B in 10min, and held for 5min followed by re-conditioning in

8min to the initial conditions.

ESI-MS analysis was performed on a Qq-TOF tandem

mass spectrometer (API Q-STAR Pulsar i, MDS Sciex,

Toronto, Canada) with a TurboIonspray source. The entire

HPLC eluent was delivered to the mass spectrometer.

TurboIonspray parameters for positive ion mode ESI-MS

were optimized as follows: ionspray voltage (IS) 4500V,


DOI: 10.1002/rcm

Figure 2. Relative body weight of Sprague-Dawley rats trea-

ted with AA for 3 days (days 1, 2 and 3). The relative body

weight was calculated as the ratio of the body weight of rats

during the seven days of the experiment to that of rats at the

initiation of the treatments (day 0).

LC/MS for metabonomic studies of aristolochic acids 875

declustering potential I (DPI) 30V, declustering potential II

(DPII) 15V, focusing potential (FP) 80V. The mass range was

from m/z 50 to 800. The ion source gas I (GSI), gas II (GSII),

curtain gas (CUR) and collision gas (CAD) were set at 30, 15,

30 and 3, respectively. The temperature of GSII was set at

3508C. Renin substrate tetradecapeptide at 10 pmolmL�1 was

used for the calibration of the mass spectrometer. Data

acquisition and processing was performed on a personal

computer with Analyst QS software (service pack 7).

Information-dependent acquisition (IDA) mode was used

to acquire the MS/MS spectra of the metabolites in rat urine

samples. The HPLC and ESI-MS parameters used in the IDA

experiments were identical to that used in the LC/MS

experiment. Using the IDA functionality in Analyst QS, the

combination of a TOF-MS survey scan and three MS/MS

scans with different collision energies (CEs) were performed

in each analysis. For the product ion scans, the resolution of

the mass resolving quadrupole (Q1) was set low (4 amu

window) and the CEs used were 15, 20 and 30 eV. The ion

peaks with peak intensity exceeding 50 counts in the survey

scan triggered MS/MS analyses. Former target ions that had

been selected for MS/MS analyses were excluded from MS/

MS analyses for 30 s.

Data analysisThe peak finding, peak alignment, and peak filtering of the

LC/MS chromatograms were carried out with ‘Metabolo-

mics Export Script’ (Applied Biosystems/MDS Sciex). LC/

MS data were processed by using the criteria as follows:

minimum retention time 0.5min, maximum retention time

15min, noise threshold 30 counts s�1, minimum spectra

peak width 100 ppm, minimum retention time peak width

5 scans, maximum retention time peak width 150 scans,

retention time tolerance 0.5min, and maximum number of

peaks 500. A list of the peak areas of all components with

their corresponding retention time andm/z as identifier was

generated. The peak areas for each peak detected were then

normalized to the sum of the peak areas in that sample.11

The resulting three-dimensional data set (retention time/

m/z, area, and sample identifier) was then exported for

chemometric analyses by using PCA or PLS-DA in the

software SIMCA-P 11 (Umetrics, Umea, Sweden).

Figure 3. Relative peak area and retention time of the repli-

cated caffeine analysis (once for every ten urine samples

analyzed) over the entire LC/MS analysis.

RESULTS AND DISCUSSION

Growth of rats after AA treatmentAA was administered to male Sprague-Dawley rats for

three consecutive days and the body weights at days 0, 3, 5

and 7 of the study were recorded. The rats in the control,

low- and medium-dosed groups gained body weight

steadily in the study (Fig. 2). However, no weight gain

was observed for the high-dosed group of rats during the

study. The weights of the medium- and high-AA-dosed rats

were significantly lower than that in the control group

throughout the study. No significant difference in relative

weights was observed for the control group and the

low-dosed group. By the end of the study, the mean body

weights of medium- and high-dosed rats were 5% and 18%

less than the controls, respectively.


Creatinine analysisBlood creatinine concentration is commonly used as an

indicator of renal function. The Jaffe method is widely used

for the determination of creatinine concentration in body

fluids.14,24 However, because of the very low creatinine levels

in blood samples and the frequent overestimation with the

Jaffe method, an LC/MS method has recently been devel-

oped for creatinine analysis.25

Increase in blood creatinine concentration was observed in

patients suffering from AAN and in laboratory animals after

AA dosing.14,24 In this study, the collected plasma samples

were analyzed by using LC/MS to determine the creatinine

concentration. The peak areas of the extracted ion chromato-

grams of the [MþH]þ ion of creatinine at m/z 114.1 in

different samples were analyzed. It was found that all the

AA-dosed rats had higher creatinine concentration than that

of the control rats. The low- and medium-dosed rats had

similar creatinine concentration, which was about 50%

higher than that of the control rats. The high-dosed rats


DOI: 10.1002/rcm

876 W. Chan et al.

had the highest creatinine concentration, which was

approximately double that in the control group. The

creatinine analysis indicated that the renal function of

the AA-dosed rats was significantly affected at the end of the

experiment.

Metabolic profiling of rat urine by LC/MSanalysisThe nephrotoxicity and carcinogenicity induced by AA has

attracted the interest of toxicologists for more than two

decades. Previous toxicology studies of AA at the molecular

level focused mainly on the metabolites and DNA adducts

formed.17–21,26–29 Recently, Chen et al.30 and Ni et al.31 in the

Figure 4. Typical LC/MS chromatograms of a control rat

experiment (% relative intensity).


same group reported the identification of some potential

biomarkers as a consequence of AA exposure. However,

biomarkers were identified solely based on m/z values

obtained from low-resolution MS while confirmation with

authentic standards and MS/MS analysis were not per-

formed. In this study, HPLC coupled with high-resolution

Qq-TOF MS/MS was used for the profiling of rat urine for

the changes in metabolic response in the face of AA

exposure.

The reproducibility of the developed LC/MS method for

the present study was determined from seven replicated

analyses of the same urine sample. With hippuric acid as the

model compound, the chromatographic retention time and

(a) and a high-dosed rat (b) at different days of the


DOI: 10.1002/rcm


peak area were measured with variations of 0.63% and 4.76%

relative standard deviation (RSD), respectively, indicating

that the LC/MS determination was reproducible. The

method performance throughout the entire LC/MS analysis

was further tested by replicated analysis of caffeine (0.5 ppm)

for every ten urine samples analyzed. RSDs of 0.18% and

3.46% were attained for the retention time and peak area,

respectively. Figure 3 shows the variation in peak area and

retention time of the caffeine analyses.

PCA, being an unsupervised method (no prior knowledge

concerning groups or tendencies within the data sets was

Figure 5. PCA scores plots of the normalized LC

AA-dosed rats. PCA scores plot showing the tim

group (a). The numbers following the letters H an

rats within the group and the day of the study,

dose-dependent separation of the control and AA-t

in the control, low-dosed, medium-dosed and high

C, L, M and H, respectively.


necessary) for pattern recognition, was performed for the

separation and identification of different groups of animals

in this study, while PLS-DA, which is a supervised method,

was used for the identification of biomarker related to AA

exposure.25

Over the 7 days of the study, no observable changes in the

concentration of urinary endogenous metabolites were

observed in the control group (Fig. 4(a)). The PCA plots

among the data set (days 0, 1, 3, 5 and 7) showed no

separation of the control group throughout the study (data

not shown). However, dose-dependent changes in the

/MS data obtained from the control and the

e-dependent separation of the high-dosed

d D refer to the random number assigned to

respectively. PCA scores plot showing the

reated animals at day 7 of the study (b). Rats

-dosed group are represented by the letters


DOI: 10.1002/rcm

878 W. Chan et al.

urinary metabolic profile were observed in the AA-dosed

groups and significant changes were observed in the

metabolic profile of the high-dosed group (Fig. 4(b)). The

metabolites with retention times of 6.6 and 7.6min showed

significant decreases in concentration after the AA dosing.

This effect was most pronounced on day 3 of the study and

returned to the initial level at the end of the experiment. The

PCA scores plot clearly illustrates the time-dependent

separation in the high-dosed group (Fig. 5(a)). The ellipse

in the PCA plot marks the 95% Hotelling T2 control chart.

PC1 accounts for 38.7% of the total variance and PC2 for

20.8%. LC/MS analysis revealed the metabolites with

retention times of 6.6 and 7.6min had [MþH]þ ion peaks at

m/z 180.0672 and 194.0828, respectively. [2MþH]þ dimer ions

Figure 6. PLS-DA scores (a) and loadings (b) plots

the control and the high-dosed groups at day 7 of t

group are represented by the letters C and H, res

expressed as m/z/retention time in the loading plo


were also observed for thesemetabolites. MS/MS analyses of

the [MþH]þ ions atm/z 180 and 194 revealed their identity to

be hippuric acid and phenylacetylglycine, respectively.

PCA was also performed for the dose-dependent meta-

bolic response of rats after AA exposure. When the data from

LC/MS analysis of rat urine at the end of the experiment

(day 7) were analyzed by PCA, it was found that the control

and the low-dosed group clustered together while the

medium- and high-dosed group could be separated easily

(Fig. 5(b)). PC1 and PC2 account for 31.8% and 9.3% of the

total variance, respectively. The PCA indicated that no

significant changes in metabolic profile were induced by the

lowdosage of AA,while obvious physiological changeswere

induced in the medium- and high-dosed rats.

of the normalized LC/MS data obtained from

he study. Rats in the control- and high-dosed

pectively (a). Endogenerous metabolites are

t (b).


DOI: 10.1002/rcm

Figure 7. Relative peak areas of the ion peaks at m/z 175.0

(a) and 447.1 (b).Figure 8. MS/MS spectra of the potential biomarkers at m/z

193 (a), 447 (b) at 20 eV collision energy, and MS3 spectra

(c) of the potential biomarkers at m/z 447 (447> 271) on a

Bruker Esquire-4000 ion trap mass spectrometer.


To further the investigation of the toxicity induced by AA,

the data sets from the control and the high-dosed groups at

the end of the study (day 7) were subjected to PLS-DA.

Figures 6(a) and 6(b) show the scores and the loadings plots

of PLS-DA, respectively. From the scores plot (Fig. 6(a)), it

can be observed that the two groups of rats were well

separated. PC1 accounts for 40.3% of the total variance and

PC2 for 9.3%. The loadings plot of the data unequivocally

shows the ion peaks at m/z 175.0300, 193.0366 and 447.0893

as potential biomarkers (Fig. 6(b)). While the ion peak

at m/z 175.0300 is the [M–H2OþH]þ fragment ion of the

metabolite at m/z 193.0366 ([MþH]þ), ion peaks at

m/z 210.0673 ([MþNH4]þ), 215.0232 ([MþNa]þ), 230.9934

([MþK]þ) and 385.0691 ([2MþH]þ) were also detected in the

LC/MS analysis.

Statistical comparison between the control and high-dosed

groups was made by independent sample T-test using the

SPSS software. The significance was set as a probability value

of P <0.05. Statistically significant differences were observed

for the two groups of rats, with the P values for ion peaks at

m/z 175.0 and 447.1 being 0.041 and 0.036, respectively.

Figures 7(a) and 7(b) show the relative peak areas of the ion

peaks at m/z 175.0 and 447.1, respectively.

IDA for structural elucidation of endogenousmetabolitesConstant neutral loss (CNL) scanning techniques on a linear

ion trap mass spectrometer have recently been demonstrated

to be an effective approach to detect pre-selected classes of

metabolites.25,32 However, only the specific class of metab-

olites was focused on and thus rendered the developed

method suitable for target analysis. The MS/MS data were


also obtained without the advantage of high-resolution mass

spectrometry (HRMS).

In this study, IDA experiments were performed on a

Qq-TOF mass spectrometer to obtain MS/MS spectra of the

metabolites in rat urine samples. By using the IDA

functionality, theMS/MS spectra of all metabolites satisfying

the pre-defined criteria (see Experimental section) were

acquired in a single injection. Because urine consists of a

wide variety of metabolites and they show different

stabilities in their gaseous phase, product ion scans with

different CE (15, 20 and 30 eV) were used for the analysis. A

total number ofmore than 450MS/MS spectra were acquired

in a single analytical run.

The MS/MS spectra of the potential biomarkers at m/z 193

and 447 are shown in Fig. 8. Comparison of the MS and MS/

MS spectra of the biomarker at m/z 193.0366 with an

authentic standard revealed its identity to be citric acid.

Analysis of the LC/MS chromatograms revealed that the

high-dosed rats had urinary citric acid concentrations

significantly lower than that in the control group. While

citric acid is one of the key compounds in the Krebs

cycle (citric acid cycle), the identification of citric acid as one

of the potential biomarkers (decline of Krebs cycle) was in

line with our observation that a decrease in growth rate was

observed in the AA-dosed rats. Citric acid was also identified

as a potential biomarker for nephrotoxicity when mercuric

chloride and cyclosporine A were studied.8,9 The absolute

identity of the ion peak atm/z 447 could not be determined in


DOI: 10.1002/rcm

880 W. Chan et al.

the present study, but neutral loss of 176 Da in MS/MS

analysis suggested that it might be a glucuronide-containing

endogenous metabolite (Fig. 8(b)).4,27,29,33 The MS3 spectra of

the metabolite at m/z 447 acquired on an ion trap mass

spectrometer is shown in Fig. 8(c).

While the construction of an LC/MS database for the

catabolic metabolites is in progress, we believe that the

combination of IDA experiments on the developed Qq-TOF

MS system in combination with the reported CNL scanning

technique may serve as a valuable tool for the development

of a library-search database for LC/MS.25,32

CONCLUSIONS

The time- and dose-dependent toxic effects induced by AA

were studied by using LC/MS. An increase in plasma

creatinine concentration and decrease in growth rate were

observed in the AA-dosed rats. The study indicated that AA

induced an adverse effect on the renal clearance function in

the AA-dosed rats. The chemometric methodologies PCA

and PLS-DAwere used for the separation of different groups

of rats. The information-dependent acquisition functionality

of a Qq-TOF instrument was demonstrated to be an efficient

approach for biomarker identification in a complex matrix.

Potential biomarkers for AA exposure included citric acid

and a glucuronide-containing metabolite.

AcknowledgementsThis work was financially supported by the Research Grant

Council, University Grants Committee of Hong Kong

(HKBU2459/06M) and a Faculty Research Grant from Hong

Kong Baptist University (FRG/06-07/II-56).

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DOI: 10.1002/rcm

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