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LC/MS Q-TOF-Based Structure
Elucidation and Profiling in Food
and Agricultural Sciences
Luigi Lucini
Università Cattolica del Sacro Cuore
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Presentation outline
i. General concepts on QTOF analysis:
High resolution MS
Principles of compound mining
ii. Create a dataset
Alignment and filtering
Recursive analysis
Data interpretation
iii. Some examples from recent research
Physiology
Food technology
Traceability of productions
Compound ID (Molecular Structure Correlation)
Screening of contaminants (All Ions MS/MS)
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Accurate mass HRMS
High Resolution Mass Spectrometry (HRMS)
Average mass: isotope-abundance averaged
molecular weight
Accurate mass +high resolution: monoisotopic
actual mass measured with
high accuracy (ppm compared
to nominal)
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Why HRMS?
Compound identification increases
at increasing mass accuracy and resolution
Isotopic mass No. compounds Resolution
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Monoisotopic mass
(varies in ppm)
Isotope spacing
(varies in ppm)
Isotope distribution
(varies in %)
Scoring based on:
5
Identification / screening
Mass Match +
Abund. Match +
Spacing
Match =
Overall Score
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Q-ToF Chemometrics workflow
Run Sample
& Control in
MS mode
Inclusion list / Preferred list
for tandem MS
Run Sample
in MS/MS
mode
Find Compounds
- MFE or FBF
Statistically Filter
Compounds - Recursive
Analysis
Identify Compounds
- Database Search
- MFG
Find Compounds
- Auto or Targeted MS/MS
Confirm structure
-Molecular Structure Correlation
(MSC)
Identify Compounds
- Library Search
- MFG
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Identification / screening
Isotopic profile:
- Accurate mass
- Accurate isotope
spacing
- Isotopes ratio
Peak volume:
- Extracted ion current from total
signal
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Naive vs forced approach
Forced: Find-by-Formula
Needs a formula or a source of formula (database)
Deeper in compounds fishing
Higher number of false positive
Naive: Find-by-Molecular-Feature
Needs an isotopic model (e.g. glycans, peptides, common organic molecules)
Often requires a following identification step
Lower number of false positives, higher number of false negative
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From meaningless to
meaningfull data
Raw data
• Huge amount of information
• Redundancy? False positive?
dataset
• Data gathering
• Alignment and filtering
Interpret.
• Statistics
• Chemometrics & bioinformatics
Answer(s) to a biological problem?
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Alignment and filtering by
MassHunter Profinder
1- Review compounds at a
glance:
- Check presence/absence
across treatments
- Preliminary investigate
alignment and check for
peak shape
2- Align and filter
3- Export for recursive
analysis
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Choosing thresholds in Profinder
Area: min, max and
med
Mass: med and RSD
Retention time
difference, span and
max width
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Alignment and filtering in
Mass Profiler Professional
1. Alignment (optionally using
internal standards) - Retention
time tolerance
2. Filter by mass tolerance
3. Remove irreproducible
compounds – Filter by
Frequency
4. Remove weak compounds –
Filter by Abundance
5. Remove highly variable
compounds – Filter by Sample
Variability
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Recursive analysis
Feature Extractor in MassHunter qualitative
Mass & Rt alignment, filtering
Find by Ion in MassHunter qualitative
Mass & Rt alignment, filtering and
chemometrics
1
2
3
4
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Recursion
Before recursion
After recursion
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Cluster analysis of
artichoke genotypes
Differences in phytochemical profile
were correlated to different radical
scavenging activities
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Comparison of different
thermal treatments on tomato sauce
Analysis of variance and fold-change
were combined to highlight the most
important compounds
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PCA on Aloe gel based
commercial products
• All samples 99% Aloe gel as
minimum
• Cosmetics and food
supplements clearly
distinguished
• Products from lyophilized aloe
gel could be identified
Oral administration
Topic application lyophilized
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Effect of abiotic stress on plant metabolism
(Zn vs salinity vs control)
Fold-change analysis let to perform:
• Unsupervised cluster analysis
• Venn diagrams
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Effect of abiotic stress on plant metabolism
(Zn vs salinity vs control)
K-means clustering helps to
identify compounds co-varying
across treatments
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Assure POD Italian cheese authenticity
via PLS-DA
Abroad
POD Italy
bactofugation
100% accuracy in PLS-DA class prediction
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Assure POD Italian cheese authenticity
via PLS-DA
I. Compounds weight in PLS-DA
model formula can be seen «at a
glance» in the loading view
II. The most important compounds
can be exported as a list, to be
further verified as markers
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Pathways analysis of differential
compounds after Aloe administration
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Pathways analysis
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Molecular Structure Correlator
• “Systematic bond-
breaking” approach
[Hill and Mortishire-
Smith, 2005] to
correlate tandem MS
data with chemical
structures
• Scores are generated from each product ion,
the mass accuracy of the fragments, and the
overall percentage of ions intensity being
plausibly explained with sub-structures
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Structural
elucidation to
discriminate
isobaric
compounds
Structure elucidation &
metabolite ID
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Structural confirmation
Confirm structure of
selected differential
metabolites
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From totally unknown to structures
Identification of
compounds in inks
for food packaging
material has been
possible using MSC
interfaced to
ChemSpider
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All Ions MS/MS acquisition:
combining MS and MS/MS data
• Different experiments in the same
acquisition using
o No collision energy
o Low, middle and high collision energy
• Get MS/MS information using scan rates of
MS-only analysis
• Needs a library for comparison (e.g. PCDL)
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• Uses a modified find-by-formula algorithm enabled for
fragment confirmation
• Correlates parent and daughter ions, then calculates a co-
elution score for the latter ones
• Enhanced specificity = false positives are removed
All Ions MS/MS acquisition:
combining MS and MS/MS data
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THANKS FOR ATTENTION!
The work referred herein was carried out at the
Faculty of Environmental, Food and Agricultural
Sciences: Institute of Environmental and Agricultural Chemistry
PRONUTRIGEN – Research Centre for Nutrigenomics and
Proteomics