**Poster 094: P094 Technological developments and opportunities with Workflow4Metabolomics[1]**

Mélanie PÉTÉRA<fnref n="1" />; Cécile CANLET4,5; Romain DALLET<fnref n="3" />; Yann GUITTON<fnref n="2" />; Gildas LE CORGUILLÉ<fnref n="3" />; Jean-François MARTIN4,5; Stéphanie MONNERIE<fnref n="1" />; Estelle PUJOS-GUILLOT<fnref n="1" />; Julien SAINT-VANNE<fnref n="2" />; Marie TREMBLAY-FRANCO4,5; W4M Core Team; Franck GIACOMONI<fnref n="1" />

**Introduction**

Metabolomics data analysis is a complex, multistep process, which is constantly evolving with the development of new analytical technologies, mathematical methods, bioinformatics tools and databases. The latest online Workflow4Metabolomics infrastructure [1] provides new upgrades for LC-MS, GC-MS and NMR pipelines, including preprocessing, quality control, statistical analysis and annotation tools. W4M also proposes new community resources promoting open science in metabolomics.

**Technological and methodological innovation**

W4M major updates include: a new MSMS pipeline; MS extraction workflows based on the XCMS3.0 R package[2]; data filtering and visualization steps based on Analytic Correlation Filtration[3] and Between-table correlation tools; metabolite databases downloaded; a contaminant identifier, and utilitarian tools. New training resources through the Galaxy Training Network (GTN) are proposed and W4M is announcing the opening of its GitHub repository to gather metabolomics tools and libraries.

**Results and impact**

W4M's improvements increase raw data input management and LC/GC-MS workflow efficiency. We highlight how current advances contribute to open data analysis practices worldwide. In addition the W4M organization on Github repository aims to review code, annotate tool and propose a showcase for contributors from the metabolomics world.

**References**

[1] Giacomoni F., Le Corguillé et al (2014). Workflow4Metabolomics: A collaborative research infrastructure for computational metabolomics. Bioinformatics

[2] Smith, Colin A. et al (2006). XCMS: Processing Mass Spectrometry Data for Metabolite Profiling Using Nonlinear Peak Alignment, Matching, and Identification. In *Analytical Chemistry*, **78** (3), pp. 779-787.

[3] Monnerie, S. et al Analytic Correlation Filtration: A New Tool to Reduce Analytical Complexity of Metabolomic Datasets. *Metabolites* 2019, **9**, 250.

<footnote n="1">¹Université Clermont Auvergne, INRAE, UNH, Plateforme d'Exploration du Métabolisme, MetaboHUB Clermont, F-63000 Clermont-Ferrand, France</footnote>

<footnote n="2">²Laboratoire d'Étude des Résidus et Contaminants dans les Aliments (LABERCA), Oniris, INRAE, UMR 1329, 44307, Nantes, France</footnote>

<footnote n="3">³ABiMS, FR2424 CNRS-UPMC, Station Biologique, Place Georges Teissier, 29680, Roscoff, France</footnote>

<footnote n="4">⁴Toxalim – Research Center in Food Toxicology, Toulouse University, INRAE UMR 1331, ENVT, INP-Purpan, Paul Sabatier University, F-31027 Toulouse, France</footnote>

<footnote n="5">⁵Metatoul-AXIOM platform, National Infrastructure for Metabolomics and Fluxomics, MetaboHUB, Toxalim, INRAE UMR 1331, F-31027 Toulouse, France</footnote>
**Poster 095: P095 Taxonomically informed metabolite annotation enhances confidence in specialized metabolomes annotation**

Adriano RUTZ<fnref n="1" />, Miwa DOUNOUE-KUBO<fnref n="1" />,², Simon OLLIVIER<fnref n="1" />, Jonathan BISSON<fnref n="3" />,<fnref n="4" />, Mohsen BAGHERI<fnref n="1" />,<fnref n="5" />, Tongchai SAESONG<fnref n="6" />, Jean-Luc WOLFENDER<fnref n="1" /> and Pierre-Marie ALLARD<fnref n="1" />

**Introduction**

Specialized metabolites, are by definition strongly linked to the taxonomical position of the producing organisms. Considering taxonomy when exploring natural products thus appears as an evidence. In 1804 De Candolle postulated that 1) *Plant taxonomy would be the most useful guide to man in his search for new industrial and medicinal plants and 2) Chemical characteristics of plants will be most valuable to plant taxonomy in the future.* [1] We adhere to De Candolle’s postulate and propose computational solutions to establish their validity.

**Technological and methodological innovation**

We build a benchmarking dataset constituted by >2000 entries composed of structures, their biological source and associated experimental MS fragmentation spectra. This dataset encompasses structures and biological sources representative of the known specialized metabolome space. Experimental spectra were acquired on the main MS platforms (Orbitrap, ToF, QQQ, etc.) We wrote a set of scripts allowing to proceed to the automated taxonomically informed metabolite annotation process.

**Results and impact**

We show that the consideration of taxonomic position in the metabolite annotation process leads to a systematic improvement (x1.5 to 7 fold increase in the F1 score) of state-of-the-art in silico metabolite annotation solutions (ISDB-DNP, Sirius, MSFinder) outputs.[2] This increased confidence in metabolite annotation efficiently improves the natural products drug discovery process. We will discuss the principles and implementation as well as practical applications of such approach.

**References Max 5**

[1] Augustin Pyramus de Candolle. 1804. *Essai sur les propriétés médicales des plantes comparées avec leurs formes extérieurs et leur classification naturelle*. (https://gallica.bnf.fr/ark:/12148/bpt6k8511237)

[2] Adriano Rutz et al. 2019. Front. Plant Sci. (https://doi.org/10.3389/fpls.2019.01329)

<footnote n="1">¹Institute of Pharmaceutical Sciences of Western Switzerland (ISPSO), University of Geneva, Centre Médical Universitaire (CMU), Geneva, Switzerland
²Faculty of Pharmaceutical Sciences, Tokushima Bunri University, Tokushima, Japan</footnote>

<footnote n="3">³Center for Natural Product Technologies, Program for Collaborative Research in the Pharmaceutical Sciences (PCRPS), University of Illinois at Chicago, Chicago, IL, United States</footnote>

<footnote n="4">⁴Department of Pharmaceutical Sciences, College of Pharmacy, University of Illinois at Chicago, Chicago, IL, United States</footnote>

<footnote n="5">⁵Department of Phytochemistry, Medicinal Plants and Drugs Research Institute, Shahid Beheshti University, G.C., Evin, Tehran, Iran</footnote>

<footnote n="6">⁶Department of Pharmaceutical Chemistry and Pharmacognosy, Faculty of Pharmaceutical Sciences and Center of Excellence for Innovation in Chemistry,</footnote>

<footnote>Naresuan University, Phitsanulok, Thailand</footnote>
**Poster 096: P096 Improving prediction of essential genes using context-specific metabolic network ensembles**

Pablo RODRIGUEZ¹, Nathalie POUPIN¹, Carlo DE BLASIO², Laurent LE CAM², Fabien JOURDAN¹

¹Toxalim (Research Center in Food Toxicology), Université de Toulouse, INRAE, ENVT, INP-Purpan, UPS, 31300 Toulouse, France

{pablo.rodriguez-mier, nathalie.poupin, fabien.jourdan}@inra.fr

² Institut de Recherche en Cancérologie de Montpellier, Campus Val d'Aurelle, 34298 Montpellier, France
{carlo.de-blasio, laurent.lecam}@inserm.fr

**Introduction**

Context specific metabolic networks [1] are automatically reconstructed networks based on experimental (mainly transcriptomic data) with the aim of modeling and predicting the specific metabolic behavior of different tissues, cells or conditions [2]. However, some of the limitations of the techniques are: 1) there is no single resulting network which best fits the data in contrary to what is returned by most methods; and 2) different parameters can generate slightly different networks with no objective way to assess which one is better. We hypothesize that predictions using the ensemble of the best fitted networks can improve on average the predictions made by a single model.

**Technological and methodological innovation**

In order to validate this hypothesis, we developed an extension of iMAT [3] that allows us to explore in a flexible way the set of optimal networks that can be generated from a given transcriptomics dataset. Using data from Yeast under aerobic conditions, we generated thousands of optimal metabolic networks for different parameter settings. We used the ensemble of networks to predict gene essentiality and we evaluated the precision and recall with different network ensemble strategies.

**Results and impact**

Analysis of the predictions made with the ensemble of networks show that ensembles can improve precision and recall of the predicted essential genes. In addition, different trade-offs between precision and recall can be achieved using different ensemble strategies.

**References**

1. Hyduke D.R, Lewis N.E, Palsson B.Ø. Analysis of omics data with genome-scale models of metabolism. Mol. Biosyst. 2013; 9: 167-174.

2. Becker S.A, Palsson B.O. Context-specific metabolic networks are consistent with experiments. PLoS Comput. Biol. 2008; 4: e1000082.

3. Zur H, Ruppin E, Shlomi T. iMAT: an integrative metabolic analysis tool. Bioinformatics. 2010; 26: 3140-3142.
**Poster 097: P097 Showcasing Longitudinal Metabolomic Datasets: Accessible, Fast and Simple**

Patrick DREHER¹; Johannes RAFFLER¹; Gabi KASTENMÜLLER¹

¹ Helmholtz Zentrum München

**Introduction**

The increasing number of longitudinal metabolomics studies enable time-resolved exploration of individual molecular changes over days, weeks, or even years, as well as insights into metabolic responses to specific perturbations. Adding the dimension of time significantly increases the complexity of metabolomics data. For an in-depth exploration of these time-resolved datasets, tools for comprehensive presentation and visualization of data and statistical results are crucial.

**Technological and methodological innovation**

To this end, we are developing a reusable computational framework, which integrates a pipeline covering the steps from time-course data pre-processing to interactive visualization of results. This R-based framework enables efficient data exploration of time-resolved metabolic features for non-data scientists and can be easily customized to any longitudinal metabolomics study. The output is depicted within an intuitive web-based graphical user interface, which can be accessed through any browser.

**Results and impact**

Our framework combines multiple modules to visualize data and statistical results. Within our advanced search module, the user can discover metabolites of their interest or find similar metabolic temporal patterns. Further modules facilitate a quick interactive visualization of molecular dynamics by time course plots, as well as providing a systems overview of metabolic changes in dynamic networks. An example use case of our framework can be found at http://humet.helmholtz-muenchen.de/.
Poster 098: P098 Developing methods for targeted metabolomics by LC-MS

Virag SAGI-KISS¹; Matthew R CAREY¹; Jacob G BUNDY¹

¹ Imperial College London, Department of Metabolism, Digestion and Reproduction, Sir Alexander Fleming Building, London SW7 2AZ, UK

**Introduction**

Mass spectrometry is increasingly used as the key metabolomic profiling technology. Hyphenation with an appropriate separation method increases sensitivity and the ability to discriminate metabolites. Liquid chromatography has many advantages, but also one key disadvantage – highly polar metabolites are challenging to retain well. Reversed-phase chromatography is best for non-polar or semi-polar metabolites; HILIC is also widely used, but is less robust than RPLC.

**Technological and methodological innovation**

We have evaluated in depth combining existing LC-MS techniques: reversed-phase, ion-pairing, and amine derivatization. While these techniques have all been used for metabolomics, we have carried out an exhaustive comparison of retention times and effects on sensitivity for a direct comparison of these techniques, for a library of around 500 metabolites.

**Results and impact**

We have developed methods for targeted metabolomics, but the data about the chromatographic properties would also be relevant to untargeted profiling. We have established recommendations for combinations of the different LC-MS approaches; using all three gives maximum coverage, but ion-pairing LC-MS and amine derivatization and RPLC-MS are clearly complementary, and combining just these two covers a wide range. We demonstrate the method in a biological model of healthy ageing.
**Poster 099: P099** *The SMRT dataset for machine learning-based metabolite retention time prediction.*

Xavier DOMINGO-ALMENARA<fnref n="1" />; Carlos GUIJAS<fnref n="2" />; Elizabeth BILLINGS<fnref n="2" />; J. Rafael MONTENEGRO-BURKE<fnref n="2" />; Winnie URITBOONTHAI<fnref n="2" />; Aries E. AISPORNA<fnref n="2" />; Emily CHEN³; H. Paul BENTON<fnref n="2" />; Gary SIUZDAK<fnref n="2" />,⁴.

**Introduction**

Retention time (RT) is an orthogonal property that enables confident metabolite annotation when combined with mass spectrometry information [1]. However, current approaches for RT prediction in liquid chromatography–mass spectrometry (LC-MS) lack sufficient accuracy due to limited available experimental data [2].

**Technological and methodological innovation**

We introduce the METLIN's [3] small molecule retention time (SMRT) dataset [4], a publicly available dataset covering the experimentally acquired retention time of 80,038 small molecules using reverse-phase LC. We assessed the potential of the SMRT dataset by applying machine learning to predict and use RT for metabolite annotation.

**Results and impact**

Results showed a good capability to rank the correct molecular identity among the top 3 candidates based on predicted RT. Results also showed that machine learning-based prediction is limited by the number and similarity level of molecules in the training set to those in the validation or a real case set. We anticipate that the SMRT dataset will enable the community to apply machine learning or first principles strategies to generate better models for RT prediction.

**References**

[1] Sumner, L. W. et al. 2007. Metabolomics. 3, 211-221.

[2] Domingo-Almenara, X. et al. 2018. Anal. Chem. 90, 480-489.

[3] Guijas, C. et al. 2018. Anal. Chem. 90, 3156-3164.

[4] Domingo-Almenara, X. et al. 2019. Nat. Commun. 10, 5811.

<footnote n="1">¹ Centre for Omic Sciences, EURECAT - Technology Centre of Catalonia & Rovira i Virgili University joint unit, Reus, Catalonia, Spain.</footnote>

<footnote n="2">² Scripps Center for Metabolomics, ³ California Institute for Biomedical Research (Calibr) & ⁴ Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA.</footnote>
**Poster 100: P100 LC-MS/MS data analysis with xcms**

Johannes RAINER¹; Michael WITTING²,³; Steffen NEUMANN⁴,⁵

¹Institute for Biomedicine, Eurac Research, 39100 Bolzano, Italy

²Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, 85764 Neuherberg, Germany

³Chair of Analytical Food Chemistry, Technische Universität München, 85354 Weihenstephan, Germany

⁴Bioinformatics and Scientific Data, IPB Halle, 06120 Halle, Germany

⁵German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Germany

**Introduction**

The xcms software [1] is a well established R package for the preprocessing of LC-MS-based untargeted metabolomics data. By extensive refactoring the package and re-using functionality and mass spectrometry (MS) data representation strategies from the MSnbase package [2] for proteomics data analysis, xcms gained native MS/MS support.

**Technological and methodological innovation**

We recently added support for LC-MS/MS data in xcms: for data dependent acquisition (DDA) data, MS2 spectra can be identified and extracted for each detected chromatographic peak or feature. For data independent acquisition (DIA) data such as SWATH data, xcms allows to perform chromatographic peak detection on MS2 data and reconstruct MS2 spectra. MS1 chromatographic peaks are matched to MS2 based on peak shape correlations.

**Results and impact**

The recent changes in xcms, particularly the support for LC-MS/MS data analysis, facilitate an improved compound annotation for untargeted metabolomics experiments.

**References**

[1] Smith CA et al. 2006. Anal. Chem.. 78:779-87

[2] Gatto L et al. 2012. Bioinformatics. 28:288-9
**Poster 101: P101 Targeting MDM2-dependent serine metabolism as a new therapeutic strategy for liposarcoma**

Madi CISSE<fnref n="1" />; Laetitia LINARES<fnref n="2" />

**Introduction**

Well-differentiated and de-differentiated liposarcomas (LPS) are characterized by a systematic amplification of the MDM2 oncogene that encodes a key negative regulator of the p53 pathway. The molecular mechanisms underlying MDM2 overexpression, but sparing wild-type p53, in LPS remain poorly understood. Here, we show that the p53-independent metabolic functions of chromatin-bound MDM2 are exacerbated in LPS and mediate an addiction to serine metabolism that sustains nucleotide synthesis and tumor growth.

**Technological and methodological innovation**

To investigate the role of MDM2-mediated regulation of serine metabolism in liposarcoma cells, we performed stable isotope tracing experiments to determine the metabolic fate of exogenous serine or glucose. Our data indicate that pharmacological and genetic inhibition of MDM2 impairs de novo serine synthesis and impacts on nucleotide metabolism in LPS cells.

**Results and impact**

Treatment of LPS cells with Nutlin-3A, stabilized p53 but unexpectedly enhanced MDM2-mediated control of serine metabolism by increasing its recruitment to chromatin, likely explaining the poor clinical efficacy of this class of MDM2 inhibitors. In contrast, inhibition of chromatin-bound MDM2 or interfering with de novo serine synthesis, impaired LPS growth both in vitro and in clinically-relevant Patient-Derived Xenograft models. Our data indicate that targeting MDM2 functions in serine metabolism represents an efficient therapeutic strategy for LPS.

**References**

Cissé et al. 2019. Science translational Medicine. Under review.

<footnote n="1">¹ INSERM / Université de Montpellier / Institut de Recherche en Cancérologie de Montpellier</footnote>

<footnote n="2">² INSERM / Institut de Recherche en Cancérologie de Montpellier</footnote>
**Poster 102: P102 Biofluid Applications in Benchtop Low-frequency 60 MHz NMR: A Metabolomics Investigation**

Justine Leenders¹, Benita Percival¹, Miles Gibson¹, Martin Grootveld¹, Philippe Wilson¹

¹De Montfort University [Leicester, United Kingdom] – United Kingdom

**Introduction**

High-frequency (HF) ¹H NMR analysis has been successfully developed to be applied in metabolomics investigations, and offers significant bioanalytical advantages for such applications. However, HF NMR analysis also presents some disadvantages such as high cost and size, which limits their accessibility to many researchers and precludes regular use in health centres. Surprisingly, few metabolomics studies using low-field spectrometers (LF) have been published to this day and remains to explore¹,².

**Technological and methodological innovation**

The objective of this work was to apply and compare LF and HF 1H-NMR metabolomics approaches to the study of type 2 diabetics (T2D) urine samples versus controls, as well as evaluates the capabilities of LF 2D cosy spectra on urine samples in term of metabolites resolution.

**Results and impact**

T2D samples distinguish from controls and several metabolites are linked to this separation. These results are observable with both HF and LF spectra. We concluded that under the same preprocessing conditions, it is possible to attain comparable results for both HF and LF. Linear correlations were then performed between 1D and 2D intensities of several metabolites and led to good coefficients values attesting of the validity of 2D LF spectra. LF spectrometers could make for excellent tools to perform metabolomics analyses.

**References**

[1] Gouilleux B. et al. 2018. Food Chem. 244:153-158

[2] Percival B.C et al. 2019. High Throughput. 8(1): 2
**Poster 103: P103 Analysis of Penillium sclerotiorum metabolome by molecular networking**

Téo HEBRA¹; Véronique EPARVIER¹; David TOUBOUL¹

¹ CNRS-ICSN, Institut de Chimie des Substances Naturelles, UPR 2301, Université Paris Saclay, 91198 Gif-sur-Yvette, France

**Introduction**

Insects are the most represented and diversified living organisms on earth.¹ They are associated with a very large diversity of microorganisms. Whereas associations are well studied within the Apocrites,² few publications are dedicated to termites/microorganism interactions outside of trophobiosis context³. A collection of 130 microorganisms isolated from 12 species of termite workers collected in French Guiana was studied and the metabolome of each strain has been explored.

**Technological and methodological innovation**

The ethyl acetate crude extracts (1 mg/mL) from each strain were separated by RPLC on a C18 column and a water/acetonitrile gradient. The metabolites were analyzed using data dependent analysis mode on a Q-ToF (Agilent Technologies). Each crude extract was also tested for their antimicrobial activity on human and insects pathogens. Both information was combined in MetGem software⁴ to construct a molecular network allowing the annotation of metabolites family with potent antimicrobial activity.

**Results and impact**

The crude extract of the fungus BSNB-CN111, identified as Penicillium sclerotiorum, showed an activity of 32 µg/mL against a human pathogen (Tricophyton rubrum, fungus) and showed a unique metabolite cluster of interest. Two metabolites were identified through the MS2 pattern as ochrephilone and sclerotiorin.⁵ In-depth analysis of molecular network from BSNB-CN111 specific molecules allows us to identify several other known compounds as well as new putative analogues.

**References**

Purvis, A. & Hector, A. 2000. Nature. 405, 212

Beemelmanns et al., J. Org. Chem. 2016, 12, 314-327

Cantlay, A.M. & Clardy. 2015. J. Nat. Prod. Rep. 32, 888-892.

Olivon, F et al. 2018. Anal Chem. 90(23), 13900-13908

Germain A et al. 2011. J. Org. Chem. 76, 8, 2577-2584
Poster 104: P104 FoodomicsGR

National research infrastructure for the comprehensive characterisation of Foods

Georgios THEODORIDIS¹, ², ³

¹ Dept. Chemistry Aristotle University Thessaloniki, Greece ² Biomic_AUTH, Center for Interdisciplinary Research and Innovation (CIRI-AUTH), Balkan Center, B1.4, 57001, Thessaloniki, Greece

³

FoodOmicsGR Research Infrastructure

**Introduction**

National infrastructure FoodOmicsGR RI aims to coordinate the work of 17 research teams from 8 Greek Universities/Research Centers in a network that aims toward 1) method development and protocol validation for the comprehensive characterization of foods and 2) support intervention studies that will provide data on health claims/nutritional value of foods. FoodOmicsGR RI combines food/nutrition science with the most advanced analytical techniques, bioinformatics and field/application sciences.

**Technological and methodological innovation**

Key objective is the generation of databases of food content to promote the assessment of nutritional value, geographical origin and traceability of local produce. Key to these, is the establishment of protocols for metabolomics and proteomics analysis and omics data combination. State of the art UPLCHR-MS, UPLC-MS(MS), GC-MS(MS), NMR, ICP-MS, NGS technologies are employed to map unique sample sets (various vintages, experimental cultivations etc) with detailed metadata and background knowledge.

**Results and impact**

FoodOmicsGR RI has so far established 14 protocols [1-5] for the analysis of wine, olive oil, honey, dairy and other food products. Metabolomics (both un-targeted and targeted modes) along with proteomics, genomics and metallomics data classify foods according to geographical origin (various products), vintage, cultivation methods (e.g. wild vs fed fish, game vs bred animal, bee products by feeding modes) authenticity/quality (adulteration) control and assisted numerous nutritional studies.

**References**

[1] G. Theodoridis et al 2012, Metabolomics 8 (2), 175-185

[2] H. Gika et al., 2012, J. Chromatogr. A 1259, 121-127

[3] M. Amargianitaki et al, 2017, Chemical and Biological Technologies in Agriculture, 9.

[4] M. Dasenaki et al 2019, Foods 8 212.

[5] A. Pina et.al., 2018, J. Chromatography A 1531, 53-63

www.foodomics.gr
**Poster 105: P105 Bioavailability of dietary long chain-PUFAs in the rat retina: mapping by MALDI imaging mass spectrometry**

Elisa VIDAL<fnref n="1" />,<fnref n="2" />; Bokkyoo JUN<fnref n="4" />; William C. GORDON<fnref n="4" />; Marie-Annick MAIRE<fnref n="1" />; Lucy MARTINE<fnref n="1" />; Stéphane GREGOIRE<fnref n="1" />; Spiro KHOURY<fnref n="3" />; Stephanie CABARET<fnref n="3" />; Niyazi ACAR<fnref n="1" />; Lionel BRETILLON<fnref n="1" />; Nicolas G. BAZAN<fnref n="4" />

**Introduction**

Dietary EPA and DHA are recommended to protect against age effects in the retina<fnref n="1" />. Therein, these PUFAs are elongated into very long chain PUFAs (VLC-PUFAs; C ≥28), allowing normal retinal functions and structure<fnref n="2" />. Nevertheless the spatial distribution of fatty acids in the retina in response to dietary omega-3 supplementation has never been explored thoroughly, although it would participate to the prevention of neuroinflammatory diseases.

**Technological and methodological innovation**

In this study, Wistar rats were fed with equivalent doses of EPA-containing phospholipids (PL), EPA containing triglycerides (TG), DHA containing PL and DHA-containing TG incorporated in their diets as source of lipids during 8 weeks. Quantitative and spatial organization changes in phosphatidylcholine (PC) and phosphatidylethanolamine (PE) species in the retina were determined by LC-MS/MS and MALDI-ToF-MS imaging following the different dietary intakes.

**Results and impact**

We found an increase in DHA content in the retina, particularly double DHA-containing PC and PE and an increase in VLCPUFAs following PL-EPA and TG-DHA rich diets. VLC-PUFAs-containing PC were detected in the photoreceptor layer. All supplemented diets triggered spatial organization changes of DHA in the photoreceptor layer around the optic nerve. These data provide new insights in fatty acids distribution in the rat retina after dietary omega-3 PUFA supplementation.

**References**

[1] AFSSA – saisine no 2006-SA-0359

[2] Hopiavuori et al. 2019. Progress in retinal and eye research. 69: 137–158

<footnote n="1">¹ Eye and Nutrition Research Group, Centre des Sciences du Goût et de l'Alimentation, AgroSup Dijon, INRA, CNRS, Université Bourgogne Franche-Comté, 17 rue Sully, 21065 Dijon, France</footnote>

<footnote n="2">² Horus Pharma Laboratories, 148 Avenue Georges Guynemer, 06700 Saint Laurent du Var, France</footnote>

<footnote n="3">³ Chemosens Group, Centre des Sciences du Goût et de l'Alimentation, AgroSup Dijon, CNRS, INRA, Université Bourgogne Franche-Comté, 17 rue Sully, 21065 Dijon, France</footnote>

<footnote n="4">⁴ Neuroscience Center of Excellence, School of Medicine, Louisiana State University Health New Orleans, 2020 Gravier St, New Orleans, LA 70112, USA.</footnote>
**Poster 106: P106 Colorectal Cancer: Biomarkers and Effect Size**

Nicolas DI GIOVANNI<fnref n="1" />, Marie-Alice Meuwis<fnref n="2" />, Edouard Louis<fnref n="2" />, Jean-François Focant<fnref n="1" />

**Introduction**

Colorectal cancer kills more than 700.000 persons each year worldwide<fnref n="1" />. Nevertheless, its diagnosis is still largely based on invasive tissue sampling and gaps remain in the understanding of its pathogenesis, with complex combinations between lifestyle, genetics, epigenetics, chronic inflammation (IBD) and microbiota. In addition to existing screening methods, global metabolic profiling can help both to diagnose and to understand the various states of the disease<fnref n="2" />,³.

**Technological and methodological innovation**

We studied the active and remission states (n=17 each) of colorectal cancer by comparing them to respective healthy control samples (n=19 and n=17). To do so, an optimized and validated (NIST SRM 1950) comprehensive GC×GC-(HR)TOFMS method we developed was used. It includes an in-house QC system, data processing and identification. We looked for potential biomarkers and applied a measure called effect size⁴,⁵.

**Results and impact**

We found 22 significantly altered metabolites in the active state that were able to discriminate efficiently (ROC AUC of 0.86, sensitivity and specificity of 0.78 and 0.73). 10 of them had signals significantly returning to normal, healthy levels in the remission samples and were therefore specific to the active state. Since it is rarely employed in metabolomics and separation science, we discuss the interest and methodological aspects of effect size.

**References**

(1) Bray, F.; Ferlay, J.; Soerjomataram, I.; Siegel, R. L.; Torre, L. A.; Jemal, A. Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. *CA. Cancer J. Clin.* **2018**, *68* (6), 394–424. https://doi.org/10.3322/caac.21492.

(2) Zhang, A.; Sun, H.; Yan, G.; Wang, P.; Han, Y.; Wang, X. Metabolomics in Diagnosis and Biomarker Discovery of Colorectal Cancer. *Cancer Lett.* **2014**, *345* (1), 17–20. https://doi.org/10.1016/j.canlet.2013.11.011.

(3) Zhang, F.; Zhang, Y.; Zhao, W.; Deng, K.; Wang, Z.; Yang, C.; Ma, L.; Openkova, M. S.; Hou, Y.; Li, K. Metabolomics for Biomarker Discovery in the Diagnosis, Prognosis, Survival and Recurrence of Colorectal Cancer: A Systematic Review. *Oncotarget* **2017**, *8* (21), 35460–35472. https://doi.org/10.18632/oncotarget.16727.

(4) Kelley, K.; Preacher, K. J. On Effect Size. *Psychol. Methods* **2012**, *17* (2), 137–152. https://doi.org/10.1037/a0028086.

Sun, S.; Pan, W.; Wang, L. L. A Comprehensive Review of Effect Size Reporting and Interpreting Practices in Academic Journals in Education and Psychology. *Journal of Educational Psychology*. American Psychological Association: Sun, Shuyan: Educational Studies Program, University of Cincinnati, Dyer Hall 409A, P.O. Box 210049, Cincinnati, OH, US, 45221, sunsn@mail.uc.edu 2010, pp 989–1004. https://doi.org/10.1037/a0019507.

<footnote n="1">¹ Organic and Biological Analytical Chemistry Group, MS Lab, Université de Liège</footnote>

<footnote n="2">² Translationnal Gastroenterology Unit, GIGA-R, CHU (University Hospital), Liège</footnote>
**Poster 107: P107 Inflammation signaling by cardiac stromal exosomes**

Nathalie PIZZINAT, Florence BOURGAILH-TORTOSA and Verena POINSOT *

I2MC, UMR 1078 INSERM/UPS, 1 avenue Jean Poulhès. BP 84225 F-31432 Toulouse-Cedex.

**Introduction**

Cardiac remodeling changes the interactions between myocytes and stromal cells. Polyunsaturated fatty acids (PUFAs) regulate the post-myocardial infarct inflammation (1) or remodeling (2). PUFAs give rise to inflammatory or resolving mediators (3). Exosomes are important paracrine vectors, exerting a therapeutic effect on the damaged heart (4). Few is known about the lipid mediator content in exosomes. We analyzed in depth the PUFAs contents in cells and in exosomes of the cardiac stroma.

**Technological and methodological innovation**

To identify the mechanisms of macrophage polarization by cardiac stromal cells, we analyzed in depth the PUFA contents in cells and in exosomes of the cardiac stroma. As clinical trials assessed the effects of supplementation with PUFAs in secondary prevention of cardiovascular disease (5), we used conditioned media of cultured heart fibroblasts and Mesenchymal Stem Cells (BM-MSC) supplemented with EPA and DHA. The inflammatory and pro-resolving lipids were analyzed by MRM HPLC-MSMS.

**Results and impact**

We analyzed the lipid mediator signature of the cardiac stromal cells (fibroblasts, myoblasts) or BM-MSC and of the exosomes released by them. We studied the impact of EPA and DHA supplementation on these signatures. The two PUFAs strongly modified the mediator profiles in different ways. The differences between these cells and exosomes fingerprints associated to their high sensitivity to PUFA supplementation, make exosomes to a probable inflammatory regulator involved in the heart remodeling.

**References**

[1] Kain V et al. J Mol Cell Cardiol. 2018, 118:70-80.

[2] Sandstedt M et al. PLoS One. 2018, 13:e0202693

[3] Serhan C.N. et al. Biochim Biophys Acta. 2015, 1851:397-413

[4] Liu B et al. Nat Biomed Eng. 2018, 2:293-303

[5] Siscovick D.S. et al. Circulation. 2017, 135:e867-e884
# Poster 108: P108 Assessment of Preterm Infant's Nutrition by Untargeted Human Milk Lipidomics

Julia KULIGOWSKI<fnref n="1" />; Anna PARRA-LLORCA<fnref n="1" />; Isabel TEN-DOMENECH<fnref n="1" />; María GORMAZ<fnref n="1" />,<fnref n="2" />; Marta MORENO-TORRES<fnref n="3" />; Guillermo QUINTÁS<fnref n="4" />,<fnref n="5" />; Máximo VENTO<fnref n="1" />,<fnref n="2" />

## Introduction

Human Milk (HM) is the gold standard for newborn nutrition. Preterm infants whose mothers are unable to provide sufficient own mother's milk (OMM), receive pasteurized donor human milk (DHM). We hypothesize that storage, processing, and differences due to gestational age and between individuals are reflected in compositional changes of HM. In an untargeted liquid chromatography-mass spectrometry based approach we assess the lipidomic signatures of OMM and DHM before/after pasteurization.

## Technological and methodological innovation

An experimental procedure was developed for achieving an adequate sample throughput suitable for clinical studies including a single phase extraction using methanol and methyl tert-butyl ether [1] followed by UPLC-TOFMS analysis of milk extracts with a total runtime of 16 min. The suitability of Quality Control - Support Vector Regression for batch effect compensation was demonstrated for lipidomics applications and a novel strategy for data-dependent acquisition of MS/MS spectra was developed.

## Results and impact

The experimental procedure allowed the identification of 280 lipids and metabolites of different classes including DAGs, TAGs, oligosaccharides, FAs, and PCs in HM collected at different gestational ages and lactation periods. We identified significant changes in HM fingerprints before and after pasteurization as well as between DHM and OMM. Results will be useful to adjust DHM treatment and storage protocols for Human Milk Banks to optimize nutrition for preterm infants receiving DHM.

## References

[1] A. Villaseñor et al. 2014. *Anal Chem.* 86:8245-8252

<footnote n="1">¹ Neonatal Research Group; Health Research Institute La Fe; Valencia; Spain</footnote>

<footnote n="2">² Division of Neonatology; La Fe University and Polytechnic Hospital; Valencia; Spain</footnote>

<footnote n="3">³ Experimental Hepatology and Hepatic Transplant, Health Research Institute La Fe; Valencia; Spain</footnote>

<footnote n="4">⁴ Health & Biomedicine, Leitat Technological Center; Barcelona; Spain</footnote>

<footnote n="5">⁵ Analytical Unit, Health Research Institute Hospital La Fe; Valencia; Spain</footnote>
**Poster 109: P109 Exploring the use of GC-CI-MS for stable isotope labeling in metabolomics**

Jordi CAPELLADES¹⁻³, Alexandra JUNZA²,³ and Oscar YANES¹⁻³

1. Institut d'Investigació Sanitària Pere Virgili (IISPV), Tarragona, Spain

2. Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), Madrid, Spain

3. Metabolomics Platform, Department of Electronic Engineering (DEEEA), Universitat Rovira i Virgili, Tarragona, Spain

**Introduction**

Metabolomics is nowadays a well-established branch of the omics field. Due to the chemical diversity of naturally occurring metabolites, metabolomics is rich in analytical instrumentation and configurations, being GC-MS and LC-MS the most common techniques.

With the introduction of chemical derivatization, its high chromatographic resolution and low background noise, GC-MS-based metabolomics has evolved into a powerful analytical platform for multiple types of targeted and untargeted metabolomic experiments, and fluxomics.[1,2]

**Technological and methodological innovation**

The most widely used ionisation method in GC-MS is electron impact ionization (EI), a hard ionisation strategy that generates highly reproducible fragmentation spectra. However, softer ionization techniques based on chemical ionisation (CI) are alternative methods, where molecular ions of analysed compounds are kept (mostly) intact. GC-EI MS has become a platform of choice for stable isotope tracing studies and fluxomics approaches. [2] The coverage of GC-EI MS is comprehensive enough to cover most central carbon metabolism thanks to the use of chemical derivatization. Interestingly, the use of GC-CI MS for stable-isotope tracing is largely unexplored. [3]

**Results and impact**

In here, we have studied the suitability of GC-CI-MS for stable-isotope tracing using multiple analytical configurations based on low-resolution and high-resolution mass spectrometry. We prove that isobutane is an ideal ionization gas by its ability to yield intact protonated molecular ions [4], and coupled to cutting-edge high-resolution GC-MS instruments, currently provide the best configuration for isotopologue quantification. In addition, we have developed an R-package called isoSCAN capable of processing GC-CI MS data from stable-isotope labeling studies.

**References**

* Fiehn O. 2016. Curr. Protoc. Mol. Biol., 114, 30.4.1–30.4.32.

* Jang C et al. 2018. Cell, 173 (4), 822–837

* Mairinger T, et al. 2019. Anal. Bioanal. Chem., 411 (8), 1495–1502.

* Newsome, G. A et al. 2016. J. Am. Soc. Mass Spectrom., 27 (11), 1789–1795
**Poster 110: P110** *Development of a targeted urinary metabolic profiling technique for inflammatory bowel disease using Liquid Chromatography Mass Spectrometry with Electrospray Ionization Quantification.*

Miss Kate GALLAGHER¹, Dr Jia LI¹, Professor Mark THURSZ¹,², Professor Elaine HOLMES¹,³, Dr Horace WILLIAMS¹,²

1.Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Imperial College London, United Kingdom, 2. Department of Gastroenterology, St Mary's Hospital, Imperial College Healthcare NHS Trust, London, United Kingdom, 3. Australian National Phenome Centre, Murdoch University, Australia.

**Introduction:**

The inflammatory bowel diseases (IBD), ulcerative colitis (UC) and Crohn's disease (CD) are characterised by chronic gastrointestinal inflammation. Both of which may cause debilitating symptoms. Diagnosis involves radiological and endoscopic procedures. In the last decade, multiple metabolomic studies have given insights into both UC and CD; several biofluids have been studied¹,². However, findings have been inconsistent, and few offer clinically useful quantitative data.

**Technological and Methodological Innovation:**

A comprehensive literature review (with the expansion of relevant biochemical pathways) was carried out to identify consistently reported metabolites for incorporation into a fully quantifiable and targeted assay. A selection of these metabolites was validated for use in predicting IBD with a combination of univariate and multivariate techniques using 1H-NMRacquired urine data. A finalised panel was then taken forward for UPLC assay development and validation in a clinical cohort.

**Results and Impact:**

42 metabolites were identified for the IBD metabolite panel: these have been taken forward for assay development. Analysis of existing urinary data from IBD patients/controls showed that the specified panel of metabolites improved the predictive score and significance of the models when compared to global profiling (from p=1 to p=0.003). Following development, the assay will be validated on a de novo cohort of IBD patients to quantify metabolic perturbations associated with disease and therapy.

**References:**

Fakhoury, M., et al., Inflammatory bowel disease: clinical aspects and treatments. Journal of inflammation research, 2014. 7(1): p. 113.

Franzosa, E.A., et al., Gut microbiome structure and metabolic activity in inflammatory bowel disease. Nature Microbiology, 2019. 4(2): p. 293-305.
# Poster 111: P111 CEU MASS MEDIATOR: THE TOOL TO ANNOTATE COMPOUNDS IN CE-MS FOR METABOLOMICS

Alberto Gil-de-la-Fuente<fnref n="1" />,<fnref n="2" />; Maricruz Mamani-Huanca<fnref n="2" />; Víctor González-Ruíz<fnref n="3" />,<fnref n="4" />; Santiago Codesido<fnref n="3" />; Nicolas Drouin<fnref n="3" />; Ángeles López-Gonzálvez<fnref n="2" />; Ana Gradillas<fnref n="2" />; Serge Rudaz<fnref n="3" />,<fnref n="4" />; Abraham Otero<fnref n="1" />,<fnref n="2" />; Coral Barbas<fnref n="2" />

## Introduction

CEU Mass Mediator (CMM) is an online tool that provides services for metabolite annotation and identification such as the simultaneous querying of metabolomic databases and the subsequent scoring of the query results using an expert system<fnref n="1" />. Capillary electrophoresis coupled to mass spectrometry (CE-MS) is a complementary tool to add to the toolkit of multiplatform untargeted metabolomics<fnref n="2" />. This technique is ideal for the analysis of ionic and polar compounds in complex sample matrices<fnref n="3" />.

## Technological and methodological innovation

Recently, ROMANCE software tool allowed to convert migration time (MT) into the effective mobility (μEff)<fnref n="4" />. However, there are no on-line databases providing services to annotate compounds from CE using MT or μEff. A new service to provide a search over the databases using m/z and MT or μEff values has been created. Experimental data from 500 compounds both pure reference standards or spiked into human plasma has been collected using a CE system coupled to a TOF-MS equipped with an ESI source.

## Results and impact

The new service allows users to annotate compounds from CE-MS experiments⁵. The database contains experimental data obtained in CEU-San Pablo and Geneva University. It is designed to enable the incorporation of new data (submissions are welcome). It is prepared to process information from different polarities (direct and inverse), internal standards (paracetamol and methionine sulfone by now) and buffers (formic and acetic acid by now). It intends to be the main database for CE-MS annotation.

## References

[1] Gil-de-la-Fuente et al. 2019. Journal of Proteome Research, 18(2), 797-802

[2] García, A. et al. 2017. Bioanalysis, 9, 99-130.

[3] Voeten, R.L.C. et al. 2018. Analytical Chemistry, 90, 1464-148

[4] González-Ruiz, V. et al. 2018. Electrophoresis, 39(9-10), 1222-1232

[5] http://ceumass.eps.uspceu.es/cems_rmt_cesearch.xhtml

<footnote n="1">¹ Department of Information Technology, Escuel, Universidad San Pablo-CEU, CEU Universities, Campus Montepríncipe, Boadilla del Monte, Madrid 28668, Spain</footnote>

<footnote n="2">² Centre for Metabolomics and Bioanalysis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Campus Montepríncipe, Boadilla del Monte, Madrid 28668, Spain</footnote>

<footnote n="3">³ Analytical Sciences, Institute of Pharmaceutical Sciences of Western Switzerland (ISPSO), University of Geneva, Switzerland</footnote>

<footnote n="4">⁴ Swiss Centre for Applied Human Toxicology, 4055 Basel, Switzerland</footnote>
# Poster 112: P112 Improved Metabolite Identification in a Single Injection with SWATH® Acquisition for Untargeted Metabolomics Workflow

Marialuce Maldini1; Robert Proos2; Khatereh Motamedchaboki3

1AB SCIEX, Darmstadt, Germany; 2AB SCIEX, Framingham, USA; 3AB SCIEX, Redwood City, USA...

## Introduction

Comprehensive metabolite identification with MS/MS library spectral matching can be problematic for data dependent acquisition (DDA) workflows as it often requires multiple injections for each sample. SWATH® Acquisition, a Data Independent Acquisition (DIA) method, with optimized variable windows, provides a powerful workflow requiring only a single injection per sample for each polarity. In addition to capturing product ion spectra for all ionizing analytes, SWATH Acquisition also provides the option of quantitation at either the MS or MS/MS level allowing a comprehensive qualitative and quantitative analysis of metabolites in complex biological samples like plasma.

Both the DDA and SWATH Acquisition methods compared in this study were single injection workflows, using the same simple RP chromatography with a 20 minute run time per injection. The speed of the TripleTOF® 6600 QTOF system allows for the top 20 selection in DDA or 20 variable SWATH acquisition windows in DIA analysis with a cycle time of 651 msec for both the DDA and SWATH Acquisition methods. The choice of top 20 or 20 SWATH Acquisition windows has previously been demonstrated to provide high quality comprehensive coverage1. In the trade off of cycle time with comprehensive coverage and data quality this cycle time still permits for quantitation with more than 9 points across a peak of 6 seconds providing accurate and reproducible integration.

## CONCLUSIONS

A simple 20 minute RP-LC method was used to acquire DDA and SWATH acquisition data on an extracted human plasma sample using a TripleTOF 6600 System. The top 20 DDA method was able to identify 476 of the features on the basis of precursor mass and MS/MS spectral matching. The 20 variable window SWATH acquisition method resulted in an additional 215 features being identified, a 45% increase, for a total of 671 compounds identified in a single injection. This study has shown that variable window SWATH acquisition can be a useful for improving compound identification in untargeted metabolomics.

## REFERENCES

1. SWATH® Acquisition Improves Metabolite Coverage over Traditional Data Dependent Techniques for Untargeted Metabolomics, SCIEX Technical Note RUO-MKT-02-7128A
**Poster 113: P113 High-throughput single-step sample preparation coupled to targeted LC-MS/MS approach for extended coverage of human plasma metabolome and lipidome**

Hector GALLART-AYALA<fnref n="1" />, Jessica MEDINA<fnref n="1" />, Vera VAN DER VELPEN<fnref n="1" />, Tony TEAV<fnref n="1" />, Yann GUITTON<fnref n="2" />, Julijana IVANISEVIC<fnref n="1" />

**Introduction**

Expanding coverage of the polar metabolome and lipidome essential for generation of well-founded hypotheses from untargeted assays. Traditionally, polar metabolite extraction is performed using methanol and lipid extraction using biphasic liquid-liquid extraction either with MTBE, chloroform or dichloromethane. In this work, we evaluated single-step extraction methods for polar metabolome and complex lipid profiling, using high-coverage targeted LC-MS/MS methodology.

**Technological and methodological innovation**

Single step methods using isopropanol (IPA) and butanol:methanol (BuMe) solvent mixtures were compared against the goldstandards for lipid (biphasic MTBE) and for polar metabolite (MeOH:H2O) extraction. The polar metabolome and complex lipids coverage, signal intensity, reproducibility and protein removal efficiency were used as criteria to evaluate the method performances. HILIC-based ESI-MS/MS approach targeting complex lipids and polar metabolites was used for the analysis.

**Results and impact**

The developed high-throughput single step sample preparation (IPA or BuMe) using HILIC-MS/MS profiling has allowed for the detection of 600 lipid species (glycerolipids, cholesterol esters, sphingolipids, glycerophospholipids, free fatty acids) and 140 polar metabolites (including amino acids, carboxylic acids, nucleotides, etc) in human plasma, in a reproducible manner. The high coverage and reproducibility of this single-step approach permits its application in large-scale population studies.

**Reference**

Matyash, V., et al. 2008. Journal of Lipid Research, 49(5), 1137-1146.

Sarafian, M. H., et al. 2014, Analytical Chemistry 86, 5766-5774.

Löfgren, L. et al. 2012. Journal of Lipid Research. 53, 1690-1700.

<footnote n="1">¹Metabolomics Platform, Faculty of Biology and Medicine, University of Lausanne, Quartier UNIL-CHUV, Rue du Bugnon
19, CH-1005, Lausanne, Switzerland</footnote>

<footnote n="2">² Laboratoire d'Etude des Résidus et Contaminants dans les Aliments (LABERCA), Oniris, INRA UMR
1329, Route de Gachet - CS 50707 - F-44307 Nantes Cedex 3, France</footnote>
**Poster 114: P114 In vivo isotopic tracing experiments reveal lactate as an oxidative substrate for brown/beige adipose tissues**

Yannick JEANSON1*, Damien LAGARDE1*, Isabelle ADER1, Floriant BELLVERT2, Christophe GUISSARD1, Lindsay PEYRIGA2, Lara GALES2, Anne GALINIER1, Luc PENICAUD1, Cédric MORO3, Luc PELLERIN4, Anne-Karine BOUZIER SORE5, Louis CASTEILLA1, Jean-Charles PORTAIS1,2, Audrey CARRIERE1

1 STROMALab Université de Toulouse, CNRS ERL5311, EFS, INP-ENVT, Inserm U1031, UPS, TOULOUSE, FRANCE

2 MetaToul-MetaboHUB, Toulouse Biotechnology Institute (ex. LISBP), Université de Toulouse - CNRS 5504 - INRA 792 - INSA Toulouse, 135 avenue de Rangueil, 31077, TOULOUSE, FRANCE

3 I2MC, Institut des Maladies Métaboliques et Cardiovasculaires I2MC, UMR1048, TOULOUSE, France

4 Département de Physiologie, Université de Lausanne, Lausanne, Suisse.

5 DUA UMR5536, Centre RMSB, 146 rue Léo Saignat, case 93, 33076 Bordeaux Cedex, France

**Introduction**

Activation of “healthy” energy dissipating brown/beige adipose tissues represents attractive therapeutic strategy against obesity and age-related metabolic disorders1. Traditionally described for their ability to burn glucose and lipids, our previous work suggested that lactate may constitute an alternative substrate for brown/beige adipose tissues 2-4, opening a novel field in the control of their metabolic activity. We herein aim at finely characterizing lactate utilization in these tissues.

**Technological and methodological innovation**

Metabolomics experiments were performed on the supernatant of primary adipocytes using nuclear magnetic resonance, to determine kinetic variations in metabolite concentrations. In vivo isotopic tracing experiments using 13C-lactate intra-peritoneal injection in mice and analyses of 13C incorporation in metabolites by mass spectrometry enabled us to trace lactate utilization and its metabolic fate in brown/beige adipose tissues.

**Results and impact**

We demonstrated that brown/beige adipocytes can uptake lactate through the monocarboxylate transporter-1 and oxidize it. In vivo 13C-tracing experiments reveal that circulating lactate significantly feeds the oxidative metabolism of brown adipose tissues, more importantly than in white adipose tissues. These findings open novel perspectives for the control of brown/beige adipose tissues activity and for their role in systemic lactate homeostasis that may be disturbed in age-associated diseases.

**References**

1. Betz et al. 2018. Nat Rev Endocrinol 14, 77-87

2. Carriere et al. 2014. Diabetes. 63, 3253-3265

3. Jeanson et al. 2016. The Biochemical journal 473, 685-692

4. Jeanson et al. 2015. Frontiers in endocrinology 6, 158

<footnote>* Both authors equally contribute to this work</footnote>
# Poster 115: P115 LipostarMSI: Comprehensive and Vendor-Neutral Data Analysis Platform for Mass Spectrometry Imaging

Sara TORTORELLA<fnref n="1" />; Paolo TIBERI<fnref n="2" />; Andrew P. BOWMAN; Britt S. R. CLAES; Klára ŠČUPÁKOVÁ<fnref n="3" />; Ron M. A. HEEREN<fnref n="3" />; Shane R. ELLIS<fnref n="3" />; Gabriele CRUCIANI<fnref n="4" />

## Introduction

Mass spectrometry imaging (MSI) is used for studying the distribution and alterations of the metabolome within biological tissues [1, 2]. The rich, multidimensional data produced by MSI, combined with the lack of comprehensive software solutions that cover the entire workflow needed for a complete MSI data analysis, poses a major challenge preventing its full exploitation. Here we introduce LipostarMSI: new vendor-neutral software for comprehensive targeted and untargeted MSI data analysis [3].

## Technological and methodological innovation

To evaluate the image analysis and automated identification capabilities of LipostarMSI, data (MSI and MS/MS) was acquired from rat liver and human biopsies using the innovative DDA-imaging method recently described [4]. All data analysis and identification was performed using LipostarMSI (Molecular Horizon Srl, IT). LipostarMSI is the only integrated software package to-date capable of supporting both comprehensive high-resolution MSI data analysis and analytes identification.

## Results and impact

Applications to human biopsies enabled lipid species accumulation within tissues to be visualised and unambiguously identified, providing insight into the metabolic hallmarks of different tumours. LipostarMSI provides a powerful platform for comprehensive MSI data analysis, greatly streamlining biochemical data interpretation. Its use will pave the way to establish a data-driven histology exploitation of high resolution MSI omics and to achieve unprecedented functional interpretation.

## References

[1] Schwamborn K et al. 2010. Nature Reviews Cancer. 10 (9), 639–646.

[2] Spengler B et al. 2015. Analytical Chemistry. 87 (1), 64–82.

[3] Tortorella et al. 2019. Journal of the American Society for Mass Spectrometry. Accepted. 10.1021/jasms.9b00034 [4] Ellis SR et al. 2018. Nature Methods. 15 (7), 515-518.

<footnote n="1">¹ Molecular Horizon Srl, Via Montelino 30, 06084 Perugia, Italy</footnote>

<footnote n="2">² Molecular Discovery Ltd, Centennial Park, WD6 3FG, Borehamwood, Hertfordshire, United Kingdom</footnote>

<footnote n="3">³ Maastricht MultiModal Molecular Imaging (M4I) Institute, Maastricht University, Universiteitssingel 50, 6229 ER, Maastricht, The Netherlands</footnote>

<footnote n="4">⁴ Department of Chemistry, Biology and Biotechnology, University of Perugia, Via Elce di Sotto 8, 06123 Perugia, Italy</footnote>
# Poster 116: P116 SWATH® Acquisition Allows a Deeper Level of Comprehensive Metabolite Quantitation

Baljit Ubhi and Zuzana Demianova

SCIEX, USA

## Introduction

The field of metabolomics and metabolic profiling faces a large challenge, in accurately identifying and quantifying hundreds to thousands of metabolites in a single run. Generally, quantitative metabolomics is performed on triple quadrupole or QTRAP® systems in a targeted manner by multiple reaction monitoring (MRM) for enhanced sensitivity and selectivity. Internal standards are often used to enhance quantitative accuracy. SWATH acquisition, a data independent acquisition (DIA) technique, is well adopted in quantitative proteomics¹, but still not commonly used in quantitative profiling of metabolome. Variable window SWATH acquisition has been shown to identify a higher number of metabolites compared to the traditional data dependent acquisition (DDA) approach, thus enabling broader metabolome coverage². Here, SWATH acquisition is used for quantitation of selected metabolites using the MS/MS data, for reduced interferences, improved signal-to-noise and deeper metabolite quantitation (Figure 1). The use of MS/MS fragments for metabolite quantitation provides better selectivity, and ultimately increased sensitivity compared to simply relying on the precursor ion for quantitation. A SWATH acquisition map contains MS and MS/MS information of every detectable metabolite in the sample and is therefore a digital archive of the sample. This reduces the need to go back and re-run samples; data can just be re-mined as the hypothesis evolves.

## CONCLUSIONS

Variable window SWATH Acquisition provides good quality quantitative data for metabolites in complex matrices. Using the full scan MS/MS data provides both confidence in identification and quantitation data that is less prone to issues with interferences.

SWATH acquisition measures MS and MS/MS spectra of every detectable metabolite in the sample, providing a digital archive of the sample that can be easily remined.

Due to many coeluting species in complex matrices, using only the MS spectrum and retention time is often not sufficient for metabolite identification. MS/MS information is necessary to obtain further structural knowledge about the metabolite. MS/MS quantitation of metabolites often leads to lower detection limits due to significantly improved signal to noise ratios vs MS data. Measuring the whole MS/MS spectrum allows selection of the best fragments for metabolite quantitation.

SCIEX OS software combines comprehensive qualitative and quantitative data analysis, making data processing easier and more efficient.

## REFERENCES

Gillet LC et al. Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis. (2012) Mol. Cell. Prot. 11(6), 1-17.

SWATH Acquisition Improves Metabolite Coverage over Traditional Data Dependent Techniques for Untargeted Metabolomics, SCIEX Technical Note RUO-MKT-02-7128A.

Vuckovic, D. Current trends and challenges in sample preparation for global metabolomics using liquid chromatography-mass spectrometry, (2012) Anal Bioanal Chem 403, 1523.

SWATH Variable Window Calculator - Excel tool. Download from http://sciex.com/support/software-downloads

Improved Data Quality Using Variable Q1 Window Widths in SWATH Acquisition, SCIEX Technical Note RUO-MKT022879-B430
**Poster 117: P117 Community-based urine sampling methodology and biomarker
technology for assessment of dietary exposure**

A J. LLOYD<fnref n="1" />, T. WILSON<fnref n="1" />, N.D. WILLIS<fnref n="2" />, L. LYONS<fnref n="1" />, H. PHILLIPS<fnref n="1" />, H.G. JANSSEN<fnref n="3" />, M. STIEGLER<fnref n="2" />, L. XIE<fnref n="2" />, K. TAILLIART<fnref n="1" />, M. BECKMANN<fnref n="1" />, L. STEVENSON<fnref n="3" />, J.C. MATHERS<fnref n="2" />, J. DRAPER<fnref n="1" />

**Introduction**

Obtaining objective, self-reported dietary exposure information from individuals is challenging due to the complexity of food eating patterns and the limitations of self-reported monitoring tools (1). This hinders research to associate dietary intakes with health outcomes. Measurement of biomarkers in urine samples can provide additional objective estimates of food intake (2). We developed methodologies for home urine collection, yielding samples rich in terms of targeted biomarker measurements.

**Technological and methodological innovation**

Urine samples were collected at home using a postal bespoke urine collection kit. We used flow infusion electrospray ionisation high resolution MS to generate a non-targeted metabolome fingerprints. Random forest (RF) classification models were used to determine the extent of sample stability. Targeted metabolite quantification was performed using Ultra-High Performance Liquid Chromatography MS using reverse phase (C18) and ZIC-pHILIC columns (3-4).

**Results and impact**

The home collection and postal transport method was highly acceptable by free-living volunteers. Statistical analysis of both metabolome and selected dietary exposure biomarkers in spot urines collected and stored under different temperature regimes showed that they were compositionally similar to control urines with immediate freezing. This urine sampling methodology and biomarker technology appeared to be suitable for routine use and may provide a scalable, cost-effective means to assess diet.

**References**

1. Bingham, S.A., et al., 1994. Br J Nut. **72**(4): p. 619-643.

2. Brouwer-Brolsma, E.M., et al., 2017. Proc. Nutr. Soc. **76**(4): p. 619-627.

3. Lloyd, A.J., et al., 2019. Metabolomics. **15** (5): p. 72.

4. Lloyd, A.J., et al., 2019. Mol. Nutr. Food Res. **63**. p

<footnote n="1">¹ Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, SY23 3DA, UK</footnote>

<footnote n="2">² Human Nutrition Research Centre, Institute of Cellular Medicine, William Leech Building, Newcastle University,
Newcastle-upon-Tyne, NE2 4HH, UK</footnote>

<footnote n="3">³ Faculty of Education, Health & Community, Liverpool John Moores University, IM Marsh Campus, Barkhill Road,
Liverpool, L17 6BD, UK</footnote>
**Poster 118: P118 Simultaneous quantification of urine metabolites to allow comprehensive assessment of dietary exposure**

T. WILSON<fnref n="1" />, M. BECKMANN<fnref n="1" />, A.J. LLOYD<fnref n="1" />, L. LYONS<fnref n="1" />, H. PHILLIPS<fnref n="1" />, K. TAILLIART<fnref n="1" />, E. HOLMES<fnref n="3" />, G. FROST<fnref n="3" />, J.C. MATHERS<fnref n="2" />, J. DRAPER<fnref n="1" />

**Introduction**

Metabolites derived from foods are found in human urine after consumption and their measurement could provide objective indicators of dietary intake (1). For comprehensive dietary exposure assessment, analytical methods will need to provide quantification simultaneously of the structurally diverse mixture of target metabolites present at a wide range of concentrations. We developed an extendable biomarker panel allowing simultaneous quantification of a comprehensive panel of dietary biomarkers.

**Technological and methodological innovation**

Urine sample analysis was performed by liquid chromatography triple quadrupole mass spectrometry (LC-QqQ-MS) with HILIC (Hydrophilic Interaction Liquid Chromatography) and Reverse Phase (RP) chromatography. Initial analysis of analytical characteristics (ie, peak shake, asymmetry, ionisation efficiency) allowed for selected reaction monitoring parameters for 59 biomarkers to be optimised. The selected biomarker panel has been used in a series of dietary intervention and nutritional epidemiological studies to report on dietary behaviour.

**Results and impact**

We established and validated a dietary exposure biomarker analytical panel by extensive analysis of analytical characteristics, which can be extended in the future to cover further food items.

We demonstrated a quantitative relationship between biomarker concentration in urine and exposure levels for commonly consumed foods in the UK. Integration of self-reported dietary recording tools with biomarker technology will allow more accurate assessment of dietary exposure.

**References**

1. Brouwer-Brolsma, E.M., et al., 2017. Proc. Nutr. Soc. 76(4): p. 619-627.

<footnote n="1">¹Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, SY23 3DA, UK</footnote>

<footnote n="2">²Human Nutrition Research Centre, Institute of Cellular Medicine, William Leech Building, Newcastle University, Newcastle-upon-Tyne, NE5 4HH, UK</footnote>

<footnote n="3">³Nutrition and Dietetic Research Group, Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Hammersmith Hospital Campus, Imperial College London, W12 0NN, UK</footnote>
**Poster 119: P119** *Utilizing the semantic web for kinetic modeling of metabolic disease pathways*

Denise SLENTER ; Egon WILLIGHAGEN

¹ Dept of Bioinformatics - BiGCaT, NUTRIM, Maastricht University, The Netherlands

**Introduction**

Currently, a vast amount of biomedical data is captured in various databases, which have limited capabilities to interact with each other. The knowledge in these databases could be used to explore if existing drugs can be repurposed for (rare) metabolic diseases, or if the synergies of drug combinations could lead to fewer side effects for patients [1]. Both of these use cases could be modeled in silico with the appropriate kinetic data, by applying semantic web technologies (e.g. RDF).

**Technological and methodological innovation**

Here, we present our approach to create pharmacologically compatible pathway for metabolic disorders. First, machine readable pathway models were created [2], which were uploaded to WikiPathways [3] converting the pathway data to the RDF format [4]. Next, we visited four kinetics databases and literature to identify relevant kinetic parameters and two drug-target databases to find corresponding inhibitors. Last, we created an RDF model for this data, compatible with the pathway models.

**Results and impact**

Our approach led to five new pathways relevant for metabolic disorders, which are supported by kinetic and drug-target information. Unfortunately, kinetic data could not be obtained for all metabolic interactions. However, when relevant data is captured in a semantic model, researchers can easily assess which interactions are missing data, shortening wet-lab time. Furthermore, adding data for other pathways is user-friendly, allowing others to extend and utilize our method.

**References**

- Benson et al. 2017. Br. J. Pharmacol. 174(23), 4362-4382.

- Kutmon et al. 2015. PLoS Comput. Biol. 11(2), e1004085.

- Slenter et al. 2018. Nucleic Acids Res., 46(D1), D661-D667.

- Waagmeester et al. 2016. PLoS Comput. Biol. 12(6), e1004989.
**Poster 120: P120 Untargeted Lipidomic analysis of bioactive lipids in epicardial adipose tissue and the effect of coronary artery disease status**

Magali BARCHUK<fnref n="1" />, Anne DUTOUR<fnref n="2" />, Patricia ANCEL<fnref n="2" />, Ljubica SVILAR<fnref n="2" />,<fnref n="3" />, Veronica MIKSZTOWICZ<fnref n="1" />,<fnref n="4" />, Graciela LOPEZ<fnref n="1" />, Miguel RUBIO<fnref n="5" />, Laura SCHREIER<fnref n="1" />, Juan Patricio NOGUEIRA<fnref n="1" />, René VALERO<fnref n="2" />, Sophie BELIARD<fnref n="2" />, Jean Charles MARTIN<fnref n="2" />, Gabriela BERG<fnref n="1" />,<fnref n="4" />, Bénédicte GABORIT<fnref n="2" />

**Introduction**

Epicardial adipose tissue (EAT) is an active endocrine organ that could contribute to the pathophysiology of coronary artery disease (CAD) through the paracrine release of proatherogenic mediators. We aimed to identify the specific untargeted lipidomic signature of EAT in CAD.

**Technological and methodological innovation**

Subcutaneous and EAT untargeted lipidomic analysis was performed in 25 CAD and 14 non CAD patients and compared to paired plasma lipidomic analysis of isolated VLDL and HDL. Lipidomics was carried out on a LC C18 column hyphenated to a Q-Exactive plus mass spectrometer, using both positive and negative ionization mode.

**Results and impact**

EAT and SAT had an independent lipidomic profile, with 95 lipid species differentially expressed and PE 18:1p/22:6 20-fold more expressed in EAT compared to SAT. CAD patients exhibited more ceramides(p=0.01), diglycerides(p=0.004), monoglycerides(p=0.013) in EAT than non CAD patients. Conversely, they had lesser unsaturated TG(p=0.02). Only 51 species were found in common between EAT and plasma lipoproteins. CAD is associated with specific lipidomic signature of EAT, unlike SAT.

**References**

[1] Chaurasia, B et al. 2015. Trends Endocrinol. Metab. 26: 538-550 [2] Gaborit, B. 2017. Compr Physiol. 7: 1051-1082.

<footnote n="1">1. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Fisiopatología y Bioquímica Clínica (INFIBIOC). Departamento de Bioquímica Clínica. Laboratorio de Lípidos y Aterosclerosis. Buenos Aires, Argentina</footnote>

<footnote n="2">2. Aix Marseille Univ, INSERM, INRA, C2VN, Marseille, France</footnote>

<footnote n="3">3. CRIBIOM, Criblage Biologique Marseille, Faculté de Medecine de la Timone, Marseille, France</footnote>

<footnote n="4">4. Universidad de Buenos Aires. CONICET. Facultad de Farmacia y Bioquímica. Buenos Aires, Argentina</footnote>

<footnote n="5">5. Universidad de Buenos Aires. Hospital de Clínicas “José de San Martín”. División de Cirugía Cardiovascular. Buenos Aires, Argentina</footnote>
**Poster 121: P121** *Using metabolomics to investigate the role of the gut microbiota in mediating the effects of diet on appetite in humans*

Hannah STEPHENS¹, Anya RAMGULAM², Georgia FRANCO-BECKER³, Maeve O'DRISCOLL⁴, Martina TASHKOVA⁵, Jesus MIGUENS BLANCO⁶, Julian MARCHESI⁷, Elaine Holmes⁸, Dominic Blunt⁹, Isabel GARCIA PEREZ¹⁰, Gary FROST¹¹, Kevin MURPHY¹².

**Introduction**

Obesity is a major global health issue; a third of the world is overweight or obese1. Using functional foods to enhance levels of satiating hormones glucagon-like peptide 1 (GLP-1) and peptide YY (PYY) is a promising therapeutic avenue. The gut metabolome largely mediates this hormonal response, but the role of the gut microbiota in generating this metabolome is largely unknown. Understanding how the microbiota influences the metabolome and thus appetite will facilitate targeted diet therapies.

**Technological and methodological innovation**

Gut fluid was collected from human volunteers using nasointestinal tubes after feeding a high protein and high fibre meal. Multiplatform analytical techniques generated metabolic profiles of the hydrophilic and the hydrophobic portion of the distal ileum and the proximal colon contents. This will be integrated with 16-S gut microbiome data, in-house gut hormone assays2 and visual analogue scales to measure appetite, investigating the role of the microbiota on diet-induced physiological changes.

**Results and impact**

The integration of metabolomic, microbiomic and gut hormone data provides a deeper understanding of the relationship between diet and the gut metabolome, and their combined impact on appetite. As well as providing novel insights into the therapeutic potential of appetite manipulation in antiobesity interventions, these results also highlight the importance of microbiota-directed patient stratification to maximise efficiency of treatment programs.

**References**

1. CHOOI, Y. C., DING, C. & MAGKOS, F. 2019. The epidemiology of obesity. Metabolism, 92, 6-10.

2. KREYMANN, B., GHATEI, M., WILLIAMS, G. & BLOOM, S. 1987. Glucagon-like peptide-1 7-36: a physiological incretin in man. The Lancet, 330, 1300-1304.

<footnote>1-8, 10-12 Department of Metabolism, Digestion and Reproduction, Imperial College London</footnote>

<footnote>5, 9 Imperial College Healthcare NHS Trust</footnote>
# Poster 122: P122 Seeking new biomarkers of atherogenesis in an atherogenic-prone down-sized pig model and their relevance in a cardiometabolic risk human cohort using LC-MS/MS lipidomics

Jean-Charles MARTIN<fnref n="1" />, Marion PRADEAU<fnref n="1" />, Imene BOUSAHBA<fnref n="2" />, Catherine TARDIVEL<fnref n="1" />, Ljubica SVILAR<fnref n="1" />, Habib HAMOU<fnref n="2" />, Denis LAIRON<fnref n="1" />, Jean-Marie BARD³, Claire BAL DIT SOLLIER<fnref n="4" />, Ludovic DROUET<fnref n="4" />

## Introduction

The study aimed to specify the role of various dairy fats on the etiology of atherosclerosis, a vascular disease leading to myocardium infarct or stroke. This was evaluated both in an atherogenic-prone minipig model and in an at-risk cardiometabolic cohort of human volunteers given the same kind of fats for 2 years and 2 months, respectively. Plasma LC/MS untargeted lipidomics was used to identify predictive disease biomarkers in pigs relevant for humans, and dairy fat consumption indicators.

## Technological and methodological innovation

43 atherogenic-prone minipigs and 169 human volunteers with a cardiometabolic risk (LDL-chol >1.6g/L) were divided into 4 groups. They were given respectively for 2 years (pigs) and 2 months (humans) 3 kinds of dairy fats or a control plant-fat diet. Untargeted LC-MS/MS lipidomics was performed on plasma collected at 0, 6, 12, 18 and 24 months in pigs, and 2 months in humans. Bifactorial statistical analyses were performed, and multiplex biomarker combination calculated with the NIPALS algorithm.

## Results and impact

> 300 lipid species in both pigs and humans scattered in >21 lipid classes were found. In pigs, a lipidome subset sensitive to diet peaked after 1 year, then partially returned to starting conditions, showing a resilience to the dietary intervention. We found 4 lipids in pigs that in combination were predictive of the atherogenic outcome both in pigs and humans, irrespective of time and diet. In humans, a dairy fat intake score using 16 lipids was calculated that could help in epidemiological studies.

<footnote n="1">¹ C2VN, BIOMET, Aix-Marseille Université, Marseille, France</footnote>

<footnote n="2">² 2M, Université Oran 1 Ahmed Benbella, Oran, Algérie
3CRNH Ouest, CNRS, Nantes, France</footnote>

<footnote n="4">4 IVS, Hôpital Lariboisière, Paris, France</footnote>
# Poster 123: P123 MS-based targeted metabolomics of eicosanoids and other oxylipins: analytical variability and interlaboratory comparison

Céline Dalle¹, Malwina Mainka², Jessica Dalloux-Chioccioli³, Annika I. Ostermann⁴, Michael Rothe⁵,
John W. Newman⁶,⁷, Justine Bertrand-Michel³, Cécile Gladine¹, Nils Helge Schebb²,⁴ 1

Université Clermont Auvergne, INRA, UNH, Unité de Nutrition Humaine, CRNH Auvergne, ClermontFerrand,
France 2

Chair of Food Chemistry, Faculty of Mathematics and Natural Sciences, University of Wuppertal, Wuppertal,
Germany 3

MetaToul, Inserm/UPS UMR 1048 - I2MC, Institut des Maladies Métaboliques et Cardiovasculaires, Toulouse,
France 4 Institut of Food Toxicology, University of Veterinary Medicine Hannover, Germany 5
Lipidomix, Berlin, Germany 6

United States Department of Agriculture - Agricultural Research Service - Western Human Nutrition Research Service, Davis CA, USA 7 Department of Nutrition, University of California - Davis, Davis CA, USA

## Introduction

Oxylipins are potent lipid mediators involved in numerous physiological and pathological processes and their quantitative profiling has gained a lot of attention [1]. To maximize the utility of the oxylipin profiling in clinical research it is now crucial (i) to assess its analytical variability; (ii) to determine its comparability between laboratories and (iii) to identify putative critical oxylipins. These three main challenges are addressed within the EU JPI HDHL*-Oxygenate project.

## Technological and methodological innovation

To address the challenges stated above, a SOP was established by a reference laboratory for the MS-based targeted metabolomics of total oxylipins (free + esterified, ~160 oxylipins) in human plasma [2]. The intra- and inter-day variabilities of each oxylipin were assessed. Then, the SOP was transferred to 4 independent laboratories together with mixtures of internal standards, calibrants and 7 different pools of plasma to determine the comparability of oxylipin profiles between labs.

## Results and impact

The cumulated intra-/inter-day variabilities revealed that 68 % of oxylipins (>LLOQ) have a CV<20%. The interlab- variability was low and dependent on the type of plasma analyzed. Overall, our results show that the MS-based profiling of total oxylipins in human plasma is a robust tool for clinical research. Moreover, the comparability of oxylipin profiles will allow generating large-scale databases allowing a better understanding of the relationships between oxylipins and human health.

## References

[1] Gladine C. et al. 2019. Free Radical Biology and Medicine 144 (2019) 72–89 Ostermann et al. 2019. Prostag Oth Lipid M. DOI: 10.1016/j.prostaglandins.2019.106384 *Joint Programming Initiative “A healthy diet for a healthy life”
# Poster 124: P124 Migrating from PLS to Artificial Neural Networks – Adapting Interpretation Strategies

Stacey REINKE¹; Kevin MENDEZ¹; David BROADHURST¹;

¹Centre for Integrative Metabolomics & Computational Biology, School of Science, Edith Cowan University, Perth, Australia

## Introduction

Highly covariate data necessitates the use of machine learning (ML) methods for analysing metabolomics data. While PLS is most commonly used, in part due to its interpretability, nonlinear methods such as artificial neural networks (ANNs) are gaining traction. Historically, ANNs have been considered uninterpretable ‘black boxes’, yet their simplest architecture is structurally equivalent to PLS¹. AIM: To migrate data visualisation techniques from PLS to ANNs and directly assess utility.

## Technological and methodological innovation

Migration included both direct and adapted approaches. Model optimisation strategies were adapted to improve simultaneous interpretation of >1 hyperparameter. Visualisations of model scores and evaluation were directly migrated. Finally, variable contribution assessment was adapted, comparing the ANN Connection Weight Approach (CWA)² and Garson’s Algorithm³ to PLS coefficients and VIP, respectively. All workflows were developed in Jupyter Notebooks, ensuring transparency and interoperability⁴.

## Results and impact

All visualisation techniques successfully migrated to ANNs. The hyperparameter optimisation adaptation provided an additional strategy for PLS and greatly improved interpretation for ANNs. PLS coefficients and ANN CWA scores were highly correlated, providing similar results; however, VIP and Garson scores showed less alignment. These results not only open the door for ANNs to be directly applied to metabolomics analysis, but also more complex architectures such as multiblock integration.

## References

[1] Mendez et al. 2019. Metabolomics. 15(11): 142

[2] Mendez et al. 2019. Metabolomics. 15(10): 125

[3] Olden and Jackson. 2002. Ecological Modelling. 154:135-150.

[4] Garson. 1991. AI Expert. 6:47-51.
# Poster 125: P125 Identification of biomarkers in Attention Deficit with Hyperactivity Disorder (ADHD)

Camille DUPUY<fnref n="1" />; Antoine LEFEVRE<fnref n="2" />; Sylvie BODARD<fnref n="1" />; Pierre CASTELNAU<fnref n="1" />,<fnref n="3" />; Patrick EMOND<fnref n="1" />,<fnref n="2" />,<fnref n="3" />; Laurent GALINEAU<fnref n="1" />;

## Introduction

Attention Deficit Disorder with Hyperactivity Disorder (ADHD) is a heterogeneous neurodevelopmental disorder affecting 35% of school-aged children and characterized by attention deficit, hyperactivity, and impulsivity.<fnref n="1" /> Currently, the diagnosis is made mainly using cognitive tests with a significant risk of diagnostic errors.<fnref n="2" />

To date, no reliable biomarkers of ADHD were identified but such issue remains an important challenge for early diagnosis and appropriate patients follow-up.

## Technological and methodological innovation

The use of animal models is relevant to study cerebral metabolome. One of the best-characterized and mostly used model is the comparison between SHR/NCrl rats (n=8) and WKY/NHsd rats (n=8).

The objective of this study is to identify metabolic biomarkers, centrally and peripherally, in SHR / NCrl rats. For this, ten brain regions were taken, as well as peripheral samples (blood, urine, and feces), then analyzed in LC-HRMS.

## Results and impact

Multivariate analyses revealed that it was possible to discriminate each rats strain from the other based on their peripheral and central metabolomes. Based on the discriminant metabolites, we found alterations in specific metabolic pathways (lysine degradation pathway) in the brain metabolome but also in the periphery (arginine and proline metabolic pathway). In the future, metabolomics studies on clinical peripheral samples (urine and blood) will be carried out.

## References

[1] Polanczyk et al. 2007. AM J Psychiatry. 164 – 942-8

[2] Faraone et al. 2015. Nat Rev Dis Primers. 1 - 15020

[3] Sagvolden et al. 2000. Neursoci Biobehav Rev. 24 – 31-9

<footnote n="1">¹ UMR 1253, iBrain, Université de Tours, Inserm, Tours, France</footnote>

<footnote n="2">² PST-ASB, Université de Tours, France</footnote>

<footnote n="3">³ CHRU Tours, Tours, France</footnote>
**Poster 126: P126 Metabolic signatures of urinary schistosomiasis and pharmacometabolomics of praziquantel treatment efficacy in children from rural Côte d'Ivoire**

**Gordana PANIC**<fnref n="1" />, Jiangming ZHONG<fnref n="1" />, Julia CAI<fnref n="1" />, Jean T. COULIBALY<fnref n="2" />,<fnref n="3" />,<fnref n="4" />,<fnref n="5" />, Beatrice BARDA<fnref n="6" />, Jana KOVAČ<fnref n="2" />,<fnref n="3" />, Jennifer KEISER<fnref n="2" />,<fnref n="3" />, Jonathan R. SWANN<fnref n="1" />

**Introduction**

Urinary schistosomiasis is a neglected tropical disease that affects millions of children in the rural tropics. It results in fibrotic abnormalities in urogenital organs and impaired childhood development. The metabolic links between infection and morbidity have not been studied. Moreover, current efforts to create a pediatric formulation of praziquantel, the sole treatment, are complicated by the drug's inconsistent bioavailability, which may be impacted by host metabolic predispositions[1].

**Technological and methodological innovation**

We employed untargeted 1H NMR spectroscopy to investigate metabolic effects of urinary schistosomiasis and associated pathology in 344 infected and 42 uninfected children from rural Côte d'Ivoire[2]. Urinary profiles were analysed with infection, clinical examination and bladder ultrasound data[3] using standard multivariate statistics[4]. Analysis with matched praziquantel pharmacokinetic data[5] was used to identify host metabolic factors associated with praziquantel ADME and efficacy.

**Results and impact**

Infection resulted in a depletion in TCA cycle and microbial co-metabolites, which in turn were associated with infection-induced bladder thickening. Pharmacometabolomic profiling demonstrated that both CYP-associated and microbial-metabolites predicted variation in bioavailability praziquantel for both enantiomers and the main drug metabolite and overall treatment efficacy. This suggests a role for gut microbial modulations to ameliorate both infection and praziquantel treatment outcomes.

**References**

[1] Olliaro *et al*. 2014. J Antimicrob Chemother. 69, 863-870

[2] Coulibaly *et al*. 2018. BMC Medicine. 16, 81-91

[3] Barda *et al*. 2017. PLoS NTD. 11, e0005400

[4] Bylesjö. 2015. Methods Mol. Biol. 1277, 134-146

[5] Kovac *et al*. 2018. Antimicrob Agents Ch. 62, e02253-17

<footnote n="1">¹Imperial College London, United Kingdom</footnote>

<footnote n="2">²Swiss Tropical and Public Health Institute, Switzerland</footnote>

<footnote n="3">³University of Basel, Switzerland</footnote>

<footnote n="4">⁴Unité de Formation et de Recherche Biosciences, Université Félix Houphouët-Boigny, Abidjan, Côte d'Ivoire.</footnote>

<footnote n="5">⁵Centre Suisse de Recherches Scientifiques en Côte d'Ivoire, Abidjan, Côte d'Ivoire</footnote>

<footnote n="6">⁶San Raffaele Scientific Institute, Milan, Italy</footnote>
**Poster 127: P127 Metabolomics at the top: Characterizing hypoxic responses and chronic mountain sickness in the highest city of the world**

Catherine TARDIVEL<fnref n="1" />, Aissatou CISSE<fnref n="1" />, Catherine DEFOORT<fnref n="1" />, Jean-Charles MARTIN<fnref n="1" />, Baninia HABCHI<fnref n="1" />, Ivan HANCCO<fnref n="2" />, Emeric STAUFFER<fnref n="2" />, Stéphane DOUTRELEAU<fnref n="2" />, Philippe CONNES<fnref n="2" />, Julien BRUGNIAUX<fnref n="2" />, Aurélien PICHON<fnref n="2" />, Samuel VERGES<fnref n="2" />

**Introduction**

A significant proportion (5-10%) of individuals living at high altitude develops signs of maladaptation generally encompassed within the syndrome of chronic mountain sickness (CMS) which frequently terminates in cardiorespiratory diseases such as pulmonary hypertension and right or left heart failure. Our aim was to characterize metabolic adaptation to high-altitude including signs of CMS using LC-MS plasma metabolomics.

**Technological and methodological innovation**

Plasma from 19 individual living permanently at Lima (see level), 13 at Puno (3500m) and 29 at La Riconada (5100-5300m) were collected. 3 and 19 suffered from CMS in Puno and La Riconada, respectively. Untargeted plasma LC-MS metabolomics was performed, followed by PLS-DA statistical analyses to extract relevant features linked to altitude and CMS. Metabolites annotation was performed using our in-house database and MS/MS fragmentation.

**Results and impact**

Metabolomics profiles distinguished see level, intermediate and high-altitude dwellers. Preliminary results showed an impact of altitude on metabolites linked to NO metabolism, energy production, proteinogenesis and (mainly at 5300m) the redox status. CMS seemed to relate to various metabolic deregulations mainly related to vascular health, oxidative stress, proteinogenesis, muscle metabolism and possible neuronal function. Red blood cells lipidomics is under way to complete these first results.

<footnote n="1">¹ C2VN, BIOMET, Aix Marseille Université, France</footnote>

<footnote n="2">² HP2 Laboratory, INSERM, Grenoble Alpes Université, Grenoble, France</footnote>
**Poster 128: P128 INPUT OF DEEP PHENOTYPING IN THE METABOLIC SYNDROME**
**STRATIFICATION**

Stéphanie MONNERIE¹; Mélanie PETERA²; Cécile CANLET³; Florence CASTELLI⁴; Benoit COLSCH⁴; François FENAILLE⁴; Charlotte JOLY²; Fabien JOURDAN³; Natacha LENUZZA⁵; Bernard LYAN²; Jean-François MARTIN³; Carole MIGNE²; José A. MORAIS⁶; Nathalie POUPIN³; Florence VINSON³; Etienne THEVENOT⁵; Christophe JUNOT⁴; Pierrette GAUDREAU⁷; Blandine COMTE¹*; Estelle PUJOS-GUILLOT*¹,²

1 Université Clermont Auvergne, INRA, UNH, mapping, Clermont-Ferrand, France;

2 Université Clermont Auvergne, INRA, UNH, Plateforme d'Exploration du Métabolisme, MetaboHUB Clermont, Clermont-Ferrand, France;

3 Toxalim (Research Centre in Food Toxicology), Université de Toulouse, INRA, ENVT, INP-Purpan, UPS, MetaboHUB, Toulouse, France;

4 Service de Pharmacologie et Immunoanalyse (SPI), Laboratoire d'Etude du Métabolisme des Médicaments, CEA, INRA, Université Paris Saclay, MetaboHUB, F-91191 Gif-sur-Yvette, France;

5 CEA, LIST, Laboratory for Data Analysis and Systems' Intelligence, MetaboHUB, Gif-sur-Yvette, France;

6 Division de Gériatrie, McGill University, Centre de recherche du Centre universitaire de santé McGill, Montreal, Canada;
7 Centre de Recherche du Centre hospitalier de l'Université de Montréal, Montreal, Canada; Département de médecine, Université de Montréal, Montreal, Canada.

...

**Introduction**

Metabolic syndrome (MetS), defined as a cluster of cardiometabolic factors, is a public health challenge because of its growing prevalence. In the context of personalized medicine, new tools are necessary to bring additional knowledge about MetS etiology, better stratify populations and customise strategies for prevention. The objective of this study was to characterize the MetS phenotypic spectrum using complementary untargeted metabolomics platforms (HRMS, RMN).

**Technological and methodological innovation**

A case-control study was designed within the Quebec NuAge cohort1. Six complementary untargeted metabolomic/lipidomic approaches were performed on serum samples collected at recruitment and 3 years later. Procedures were set up to guaranty the inter-laboratory standardisation from sample preparation to data processing, performed using reproducible online Galaxy workflows. A full feature selection strategy was developed to build a comprehensive molecular MetS signature, stable over time.

**Results and impact**

A wide range of metabolites (lipids, carbohydrates, amino-acids, peptides...) reflecting subject stability and providing new insights about underlying mechanisms, were found to be modulated. An optimized reduced signature was proposed, allowing good prediction performances (12% misclassification, AUC=0.95, CI:[0.92-0.98]). These results demonstrated the interest of a multidimensional molecular phenotyping as part of the next generation of medicine tools in the frame of non-communicable diseases.

**References**

[1] Gaudreau P et al., 2007. Rejuvenation Res.10(3):377-386.
**Poster 129: P129** *The circulating metabolites in the progression to islet autoimmunity and type 1 diabetes*

Santosh Lamichhane, Partho Sen, Heli Siljander, Heikki Hyöty, Jorma Ilonen, Jorma Toppari, Riitta Veijola, Tuulia

Hyötyläinen, Mikael Knip, Matej Oresic

Email: Santosh.lamichhane@utu.fi

Type 1 diabetes (T1D) is a chronic autoimmune disease caused by specific destruction of the insulinproducing beta cell. Clinically pre-diabetic period in T1D is characterized by presence of beta cell specific autoantibodies. Earlier metabolomics study suggests specific metabolic disturbances before individuals precede to auto-immunity.

Here, we analyze circulating metabolites in a prospective series of plasma samples from children who progressed to T1D, children who developed islet autoantibody but did not progress to T1D during the follow-up (P1Ab) and matched controls (CTR) in the subset of samples from internationally recognized DIPP and DIABIMMUNE study cohorts. We found sphingomyelins and methionine to be persistently dysregulated in PT1D when compared to the P1Ab and CTR groups. Additionally, bile acids were found to be dysregulated in cases than the CTR during early infancy. We also found potential microbial metabolites including hydroxyphenyllactic acid, indole acetic acid, and 11-eicosenoic acid to be significantly downregulated at early age (3 and 6 months) preceding clinical T1D. Microbial community modelling obtained from the shotgun metagenomics data showed significant differences in microbial metabolic pathways such as fatty acids, Lmethionine, bile acids and amino acid biosynthesis among the cases.

Taken together, our study support findings from earlier studies and suggests novel metabolic signatures that characterize children who progressed to islet autoimmunity or overt T1D, which may be helpful in the identification of at-risk children before the initiation of autoimmunity.
**Poster 130: P130 Milk molecular species of triacylglycerols characterized by lipidomic approach in cows and goats fed diets supplemented with various lipid sources**

Hélène FOUGERE1; Carole DELAVAUD1; Sylvain EMERY1; Justine BERTRAND-MICHEL2; Laurence BERNARD1.

1Université d'Auvergne, INRA, Vetagro Sup, UMR12133 Herbivores, 63122 St-Genès-Champanelle, France
2Institut des Maladies Métaboliques et Cardiovasculaires (I2MC), Inserm/Université Paul Sabatier UMR1048, 1 Avenue Jean Poulhes F-31432 Toulouse

**Introduction**

Lipid fraction is a major determinant of milk nutritional quality that can be modulated by nutritional factors such as lipid supplementation.

In a comparative study between cows and goats fed similar diets supplemented in lipids, we characterized the triacylglycerols (TAG) composition by lipidomic. This study was part of a trial aiming at characterizing milk lipid responses to diets inducing either milk fat depression or increase in milk fat secretion, with species-specific responses [1].

**Technological and methodological innovation**

The effects of diets containing no additional lipids (CTL) or supplemented with corn oil and wheat starch (COS), marine algae powder (MAP), or hydrogenated palm oil (HPO), on milk fat content and composition were studied in 12 cows and 12 goats conducted simultaneously in a replicated 4x4 Latin square design. Milk samples were collected over 2 consecutive milkings on d24 of each period. Lipids were extracted before TAG determination by LC-HR/MS. Data were subjected to ANOVA using R software.

**Results and impact**

In cows, milk fat content was lowered by COS (-45%) and MAP (-22%) and increased by HPO (+13%) whereas in goats, only MAP decreased milk fat content (-15%). Lipidomic analysis revealed TAG differences among species: 1/irrespective of diets, 16 were more abundant in cows and 23 in goats, 2/on COS, 28 were modulated in cows but not in goats and 3/on MAP, 13 were modulated in cows and 8 in goats. These new data demonstrate the TAG species specificities and their nutritional regulation.

**References**

[1] Fougère et al. 2018. Journal of Dairy Science. 101:8429-8445
**Poster 131: P131 Genome-scale metabolic modeling of human CD4+ T cells reveals ceramides as metabolic signature of Th17 and regulatory T-cell differentiation**

Partho SEN<fnref n="1" />, Alex M DICKENS<fnref n="1" />, Ubaid ULLAH<fnref n="1" />, Syed Bilal Ahmad ANDRABI<fnref n="1" />, Mohd Moin KHAN<fnref n="1" />, Tanja BUCHACHER<fnref n="1" />, Tuomas LINDEMAN<fnref n="1" />, Marjo HAKKARINEN<fnref n="1" />, Esko KEMPPAINEN<fnref n="1" />, Omid RASOOL<fnref n="1" />, Tuulia HYÖTYLÄINEN<fnref n="2" />, Riitta LAHESMAA<fnref n="1" />, Matej ORESIC<fnref n="1" />

**Introduction**

T helper (Th) cells play a pivotal role in cell-mediated immunity. During the development, T cells undergo metabolic remodeling that is essential for orchestrating the action of other immune cells.

**Technological and methodological innovation**

In order to understand global metabolism during T-cell development, we developed genome-scale metabolic models (GEMs) for human Th1, Th2 and Th17 subsets and T-regulatory cells (iTreg) [1].

**Results and impact**

Meta-analysis of T-cell specific human transcriptomics datasets have identified 72 novel metabolic genes, corresponding to 355 reactions spanning various metabolic pathways. Reporter metabolites and pathway overrepresentation analysis suggested that T-cell activation induces gluconeogenesis, glutaminolysis, and lipid biosynthesis. Moreover, ganglioside (GA1, GMb) and N-acetylneuraminate (NANA) associated with sialyl-T antigen were significantly up-regulated in Th17 cells at 72 hours of initiation, while the glucosyl-, lactosyl- and galactosyl ceramides were down-regulated. On contrary, such trends were either reversed or absent in iTregs at this time-point. These results have been validated by LC-MS-based lipidomics. Our findings suggest that, ceramides are involved in the metabolic regulations and functioning of T-cells. It was also found that, Th subsets exhibit unique metabolic phenotype, already during early stages (72 h) of specification, thus playing a central role in guiding the fate of the cells. The findings from this study, provide a basis for modulation of human Th subsets crucial for immune responses under metabolically aberrant conditions and in immune-mediated disorders.

**References**

[1] Sen, P., Kemppainen, E. & Orešič, M. Perspectives on Systems Modelling of Human Peripheral Blood Mononuclear Cells. *Frontiers Mol Biosci* 4, 96 (2017).

<footnote n="1">¹Turku Bioscience, University of Turku and Åbo Akademi University, Turku, Finland</footnote>

<footnote n="2">²Department of Chemistry, Örebro University, 702 81 Örebro, Sweden</footnote>
**Poster 132: P132 How metabolomic data support an innovative read across approach for safety assessment in cosmetics**

Carine Jacques<fnref n="1" />, Emilien Jamin²,<fnref n="3" />, Isabelle Jouanin²,<fnref n="3" />, Cécile Canlet²,<fnref n="3" />, Marie Tremblay-Franco²,<fnref n="3" />, Jean-François Martin²,<fnref n="3" />, Daniel Zalko<fnref n="3" />, Yves Brunel<fnref n="1" />, Sandrine Bessou-Touya<fnref n="1" />, Laurent Debrauwer²,<fnref n="3" />, Pierre-Jacques Ferret<fnref n="1" /> & Hélène Duplan<fnref n="1" />

**Introduction**

In toxicology, read-across is one of the most commonly used alternative approaches for data gap filling in registrations submitted under REACH Regulation. However, a level of uncertainty remains present with current read-across approaches compared with traditional testing of the substance. Metabolomics is the -omics discipline, that is more closely related to biochemical pathways, and therefore could be helpful to fill the gap during read-across analysis for safety assessment.

**Technological and methodological innovation**

A new approach using metabolomics for read-across between a candidate molecule A only studied in vitro, and a reference molecule B previously investigated using traditional in vivo toxicity methods. Two in vitro models (Skinethic model and HepaRg cell line) were treated and studied by metabolomics. Extracts were then analyzed by NMR and UHPLC-HRMS, and data were processed using W4M[1]. Metabolic pathways were highlighted with Metexplore[2] and confronted with other toxicological data.

**Results and impact**

Molecule A yielded similar metabolomic profiles to reference molecule B in both models underlining similar mode of action. Indeed, metabolic networks minor modifications are purine catabolism, nucleotide interconversion, glycerophospholipid metabolism, valine, leucine, and isoleucine metabolism pathways. Metabolomics data obtained allow us getting a better understanding of the biological impact of both molecules on skin and liver and permit to validate this innovative read-across approach.

**References**

[1] Giacomoni, F. et al. 2015. Bioinformatics. 31 1493-1495

[2] Cottret, L et al. 2018. Nucleic Acids Research. 46 W495-W502

<footnote n="1">¹ Pierre Fabre Dermo-cosmétique, Centre R&D Pierre Fabre, Avenue Hubert Curien, Cedex 01, 31025 Toulouse, France
² Metatoul-AXIOM platform, National Infrastructure for Metabolomics and Fluxomics: MetaboHUB, Toxalim, INRA, F31027 Toulouse, France</footnote>

<footnote n="3">³ UMR1331 Toxalim (Research Centre in Food Toxicology), Université de Toulouse, INRA, ENVT, INP-Purpan, UPS, 31027 Toulouse, France.</footnote>
**Poster 133: P133 LC-MS-based semi-targeted lipidomics method: Application to the discovery of lipid biomarkers in diabetes**

Ke LIU<fnref n="1" />; Catharine A. ORTORI<fnref n="1" />; Kostas TSINTZAS<fnref n="2" />; David A. BARRETT<fnref n="1" />* and Dong-Hyun KIM<fnref n="1" />*

**Introduction**

Diabetes has been reported with significant lipid alterations, but potential lipid biomarkers are still unknown due to the limitation of analyzing method for lipids. To investigate different classes of lipidomic changes in diabetes patients, a LC-MS-based semi-targeted lipidomics was developed to monitor concentration changes in 273 lipids with confirmed identification. Time restricted feeding (TRF) and daily caloric restriction (CR) study was compared to explore biomarkers related to diabetes.

**Technological and methodological innovation**

In TRF study, participants were asked to restrict eating between 8am and 4pm whereas in CR study, participants were asked not to alter the temporal distribution of energy intake. Plasma from pre and post-intervention were extracted with chloroform: methanol (2:1) with 13C-labelled internal standards added. Samples were loaded on LC-MS with the developed method. Statistical analysis such as uni- and multivariate analysis was used to discover concentration changes in various lipids and potential biomarkers.

**Results and impact**

A new LC-MS-based semi-targeted lipidomics method was developed with good reproducibility and repeatability. The method is sensitive enough to detect subtle changes in 18 lipid classes, including TG, DG, Ceramides and so on. 273 lipids were identified in two studies with this method. Based on t-test (FDR corrected), PCA and OPLS-DA results, a number of significantly changed lipids were determined in two studies, and these can be potential biomarkers for type 2 diabetes.

**References**

[1] New, M. I. et al. 1963. Diabetes.12, 208-212

[2] Wenk, M. R. et al. 2010. Cell.143, 888-895

<footnote n="1">¹ Centre for Analytical Bioscience, Division of Advanced Materials and Healthcare Technologies, School of Pharmacy, University of Nottingham</footnote>

<footnote n="2">² School of Medicine, University of Nottingham</footnote>
**Poster 134: P134 Optimization of fecal NMR-based metabolomics to study the developing infant gut**

Liene BERVOETS¹; Hans IPPEL²; Niels VAN BEST¹,³; Paul H.M. SAVELKOUL¹,⁴; Monique A.H. MOMMERS⁵; John PENDERS¹

¹School of Nutrition and Translational Research in Metabolism (NUTRIM), Dept. Medical Microbiology, Maastricht University Medical Centre, Maastricht, The Netherlands; ²Dept. Biochemistry, Maastricht University, Maastricht, The Netherlands; ³Institute of Medical Microbiology, RWTH University Hospital Aachen, Aachen, Germany; ⁴Dept. Medical Microbiology & Infection Control, Amsterdam Medical Center, Location VUMC, Amsterdam, The Netherlands; ⁵Dept. Epidemiology, Maastricht University, Maastricht, The Netherlands.

**Introduction**

While substantial efforts have been made to optimize and standardize fecal metabolomics for studies in adults¹, the development of a standard protocol to analyze infant feces is still lagging behind. Research of the infant fecal metabolome is gaining interest since it contributes to our functional understanding of the complex diet-microbiota interactions in the gastrointestinal tract, and its impact on host health².

**Technological and methodological innovation**

Fecal samples from five infants were subjected to different preparation conditions in order to examine the impact of extraction solvent, dilution ratio, homogenization method, filtration and duration of centrifugation on the 1H NMR metabolite profile3,4. An optimized protocol for 1H NMR spectroscopic analyses was defined and directly implemented on samples collected from infants at 8 weeks, 4 and 9 months postpartum.

**Results and impact**

Diet has a profound impact on the gut metabolome, with mostly milk oligosaccharides derivatives present in 8 weeks and 4 months samples, and short-chain fatty acids in 9 months samples. The application of the proposed protocol developed for NMR-based metabolomics of infant feces will ensure robust data generation and improve comparability between laboratories. In combination with microbiome research, this can provide further inside in the influence of nutrition on the infant gut health.

**References**

[1] N. Karu, et al. 2018. Analytica Chimica Acta. 1030: 1-24.

[2] J. Zierer, et al. 2018. Nature Genetics. 50: 790-95.

[3] A. Amiot, et al. 2015. Journal of Proteome Research. 14: 3871-81.

[4] S. Lamichhane, et al. 2015. Analytical Chemistry. 87: 5930-37.
**Poster 135: P135 Biomarkers involved in glioma development in Drosophila melanogaster model**

Marion Maravat, <u>Marylène Bertrand</u>¹, Martine Decoville¹, Céline Landon¹, Séverine Morisset-Lopez¹, Franck Fayon², Vincent Sarou-Kanian²

1 Centre de Biophysique Moléculaire CNRS UPR 4301 – Univ. Orléans, F-45071, Orléans, France

2 Conditions Extrêmes et Matériaux: Haute Température et Irradiation CNRS UPR 3079 – Orléans, France,

With a prevalence of about 5 to 8 cases a year per 100,000 people, human malignant glioma is the most common type of primary brain tumors in adults. They represent 2,000 to 3,000 new cases a year in France and constitute an important cause of suffering and mortality. If genetic alterations involving signaling pathways or epigenetic processes have been identified as causing gliomas, few effective therapies are currently available which leads to a poor prognosis. Tumor cells reprogram their metabolism to ensure their energy demands and molecules necessary for their proliferation (nucleotides, lipids, amino acids ...). These metabolic pathways may constitute new therapeutic targets.

In order to study these brain tumors, we have developed in the laboratory a model of glioma in Drosophila melanogaster that results from the activation of two signaling pathways (PI3K and EGFR) known for their involvement in glioma. The metabolic signatures of third instar larvae dissected brains developing a glioma were analyzed by NMR spectroscopy in liquid phase and HR-MAS and by multivariate statistical analyzes and compared to controls. Our original approach, combining solution state NMR and HR-MAS NMR, successfully identified several glioma biomarkers. Some of them are involved in the Krebs cycle and in the biosynthesis of amino acids. Some metabolites have already been demonstrated in studies of human oncogenesis or glial cell proliferation, which supports the use of the Drosophila melanogaster model to study human glioma.
**Poster 136: P136 Differential Mobility Separation Enhances the Quantification of Lysophosphatidic Acid in Plasma**

Cyrus Papan; SCIEX GmbH, Darmstadt, Germany
Email: cyrus.papan@sciex.com

**Introduction**

Lysophosphatidic acid (LPA) is a phospholipid signaling molecule in the class of lipid mediators, functioning by signaling through G-Protein coupled receptors or nuclear receptor proteins. LPA has been associated with a wide range of biological processes.

Accurate LPA measurement in plasma has proven difficult. A bottleneck for accurate quantitation of LPA in plasma using current analytical methods is the chemical interferences. The most abundant LPA fragments are typically the best fragments for quantification, however the most intense MRM transitions for LPA have strong matrix interferences when monitored in plasma. There is an MRM transition that has good specificity in plasma however it has much lower signal intensity.

Here, SelexION Technology is used for the quantification of LPA 18:1 in plasma which removes the matrix interferences observed when measuring plasma sample, allowing the use of the higher intensity MRM transitions for quantitation of LPA with much greater confidence.

**Conclusions**

A method has been developed here for the quantitation of Lysophosphatidic acid (LPA) in plasma using SelexION Technology for reducing matrix interferences and increasing method robustness. The method was applied to measure endogenous LPA in a series of plasma samples. With this method, a concentration of ca 60 mM in human plasma samples was determined, which is in line with the reported values in the literature.
**Poster 137: P137 The Ichem'Algae ANR project: Untargeted chemotyping of algae bank by GC-MS and non invasive vibrational spectroscopy**

Rémy Coat<fnref n="1" />; Sébastien Chollet<fnref n="2" />; Ganesh Sockalingum<fnref n="3" />, Luc Marchal<fnref n="1" />,<fnref n="2" />, Olivier Gonçalves<fnref n="1" />, Jean Hugues Renault<fnref n="4" />

**Introduction**

The Ichem'Algae research project aims to develop an integrated analytical methodology to investigate the poorly known microalgae chemical diversity. The main objectives consist in a rapid fractionation approach combined with non-invasive and highly resolutive signatures methods for the development of a descriptive/predictive model and a rapid screening of the partner algae bank.

**Technological and methodological innovation**

The analytical approach will combine non-invasive (FTIR/Raman spectroscopy, HRMAS) and highly resolutive methods (GCMS, HR NMR). The fractionation process will be performed using centrifugal partition chromatography, the produced fractions will be selected by GCMS [1] according to their metabolic signatures. The selected fractions (presenting high diversity or specific fractionation profiles) will be extensively explored using CPC-NMR based CARAMEL approach [2].

**Results and impact**

First results have demonstrated the ability of the GCMS to snapshot the chemical diversity of the analyzed strains, before and after dereplication using simple extraction methods (solvents with a gradient scale of polarity). The resulting fractions could be classified according to the solvent polarity. It also appeared clearly that most of the chemical diversity could only be characterized after dereplication (many signals were detectable only when investigated in contrasted polarity fractions).

**References**

[1] Phélippé, M., Coat, R., Le Bras, C., Perrochaud, L., Peyretaillade, E., Kucma, D., ... & Gonçalves, O. (2018). Characterization of an easy-to-use method for the routine analysis of the central metabolism using an affordable lowresolution GC-MS system: application to Arthrospira platensis. Analytical and bioanalytical chemistry, 410(4), 1341-1361. [2] Hubert, J., Chollet, S., Purson, S., Reynaud, R., Harakat, D., Martinez, A., ... & Renault, J. H. (2015). Exploiting the Complementarity between Dereplication and computer-assisted structure elucidation for the chemical profiling of natural cosmetic ingredients: Tephrosia purpurea as a case study. Journal of natural products, 78(7), 1609-1617.

<footnote n="1">¹ GEPEA UMR CNRS 6144, Université de Nantes</footnote>

<footnote n="2">² Capacité SAS, CPC Engineering, Nantes</footnote>

<footnote n="3">³ MEDyC UMR CNRS 7369, Université de Reims Champagne-Ardenne</footnote>

<footnote n="4">⁴ ICMR UMR CNRS 7312, Université de Reims Champagne-Ardenne</footnote>
# Poster 138: P138 Prolonged Exposure to Milk Casein Results in Depressive Behaviour, Impaired Brian Development and Altered Metabolism in Wistar Rats

Simone Zuffa<fnref n="1" />; Aya Osman<fnref n="2" />; Jonathan Swann<fnref n="1" /> and Alexis Bailey<fnref n="3" />

## Introduction

Early-life nutrition influences brain development and gut microbiota composition with health repercussions later in life. Cow formula milk contains high concentrations of A1 b-casein and its proteolytic breakdown releases bcasomorphin 7, a peptide with morphine like properties<fnref n="1" />. Longer exposures to dietary casein, with delayed weaning, induce depressive phenotypes in rats, altering the gut microbiota and urinary metabolic profiles<fnref n="2" />. A nonbCM7 releaser (A2 b-casein) can potentially prevent this.

## Technological and methodological innovation

Rats were fed different concentrations of casein from postnatal day 21 to 26. Depressive behavior was evaluated with the forced swim test (FST)<fnref n="3" />. Urine, brain and gastrointestinal contents were collected for metabolic and microbial analyses on PND26. In a second study, animals were fed for the same period either with water, commercialized cow milk (A1 b-casein) or A2 b-casein milk. Depression was again evaluated with the FST, while metabolic profiles of brain and urine were measured by 1H NMR.

## Results and impact

The administration of casein-rich milk resulted in increased immobility time in rats, indicating depressive phenotypes. Urinary metabolic profiles reveal distinct metabolic phenotypes with major differences in bacterial metabolism. A2 b-casein milk appears to attenuate the development of depressive behaviours and to induce different brain and urinary metabolic profiles, stressing the importance of bCM7. This study can impact how current formula milk is designed and improve long term infant health.

## References

* Noni, I. De. Release of β-casomorphins 5 and 7 during simulated gastro-intestinal digestion of bovine βcasein variants and milk-based infant formulas. Food Chem. 110, 897-903 (2008).

* Farshim, P. et al. Maternal Weaning Modulates Emotional Behavior and Regulates the Gut-Brain Axis. Sci. Rep. 6, 1-13 (2016).

* Porsolt, R. D., Le Pichon, M. & Jalfre, M. Depression: A new animal model sensitive to antidepressant treatments [27]. Nature vol. 266 730-732 (1977).

<footnote n="1">¹ Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK</footnote>

<footnote n="2">² Department of Psychiatry, Ichan School of Medicine at Mount Sinai, New York, US</footnote>

<footnote n="3">³ Institute of Medical and Biomedical Education, St George's University of London, London, UK</footnote>
**Poster 139: P139** *Assessment of the Substrate Biodegradability in Anaerobic Co-digestion using a Metabolomic Approach*

Francesc PUIG-CASTELLVÍ<fnref n="1" />,<fnref n="2" />; Laëtitia CARDONA<fnref n="2" />; Delphine JOUAN-RIMBAUD BOUVERESSE<fnref n="3" />; Christophe B. Y. CORDELLA<fnref n="3" />; Laurent MAZÉAS<fnref n="2" />; Douglas N. RUTLEDGE<fnref n="1" />,<fnref n="4" />; and Olivier CHAPLEUR<fnref n="2" />

**Introduction**

Anaerobic digestion (AD) is a sustainable process for the treatment of wastewater sludge (WAS) by the action of microorganisms[1]. WAS degradability can be enhanced by mixing it with other substrates richer in carbon, such as garden grass (GG) or fish waste (FW)[2]. Typically, AD performance is assessed by indirect measurements (i.e., pH, biogas production)[3], while the direct monitoring of metabolite degradation in AD using metabolomics instrumentation has never been used.

**Technological and methodological innovation**

Mixtures of WAS with either FW or GG (0/100, 25/75, 50/50, 75/25, and 100/0) were prepared and digested in batch reactors for one month. Samples were collected at 3 time-points and analysed with HPLC-MS spectrometry. The acquired data were processed with XCMS Online[4], and further analysed with Principal Components Analysis (PCA) and Common Components Analysis (CCA)[5]. This is the first time AD is monitored using untargeted HPLC-MS metabolomics and chemometrics.

**Results and impact**

Relevant metabolites were descriptive of FW or GG rather than WAS, and mainly corresponded to modified metabolites, such as decarboxylated amino acids and oxidized fatty acids. In both digestion experiments, concentrations for most metabolites were found to decrease over time. Finally, GG did not improve the biodegradability of WAS, whereas a synergistic effect was observed for FW, this effect being the highest for 25% FW. In conclusion, metabolomics results a promising tool to monitor AD.

**References**

Céline Madigou et al. 2019. Chemical Engineering Journal. 361, 266-277.

Laëtitia Cardona et al. 2019. Waste Management. 87, 772-781.

Jay N. Meegoda et al. 2018. International Journal or Environmental Research and Public Health. 15, 2224.

Ralf Tautenhahn et al. 2012. Analytical Chemistry. 84, 5035-5039.

Jihène Bouhlel et al. 2018. Talanta. 178, 854-863.

<footnote n="1">¹ Ingénierie Procédés Aliments, AgroParisTech, INRA, Université Paris-Saclay, F-91300, Massy, France</footnote>

<footnote n="2">² Irstea, 1 rue Pierre Gilles de Gennes, 92160 Antony, France</footnote>

<footnote n="3">³ Physiologie de la Nutrition et du Comportement Alimentaire, AgroParisTech, INRA, Université Paris-Saclay, 75005 Paris, France</footnote>

<footnote n="4">⁴ National Wine and Grape Industry Centre, Charles Sturt University, Wagga Wagga, Australia</footnote>
# Poster 140: P40 Comparative metabolomics in Mamiellales

Rémy MARCELLIN-GROS<fnref n="1" />; Gwenaël PIGANEAU<fnref n="1" />; Didier STIEN<fnref n="2" />

## Introduction

Mamiellales are cosmopolitan marine photosynthetic unicellular eukaryotes that dominate the picoeukaryotic plankton in coastal areas. Theses picoalgae exemplify the ecological success of miniaturized eukaryotic cells, displaying a simple cellular organization and a high surface-volume ratio, which is likely to confer advantages in nutrient poor environment. Phytoplanktonic eukaryotes have representatives in five of the six super-groups found in eukaryotes [1] where Chromalveolates dominate in terms of diversity and abundance over Archaeplastida [2], the green lineage to which Mamiellales and land plants also belong. Considering the diversity and the pivotal ecological role of the pico-phytoplankton they have been extensively studied to understand their past evolutionary history. However, how their ancient genetic divergence and ecological features correlate to their metabolomic profiles remains unknown.

## Technological and methodological innovation

Here, we provide a straightforward approach to compare metabolomes of divergent algae, among which six Mamiellales (Ostreococcus, Bathycoccus, Micromonas and Mantoniella) three Prasinophytes (Pyramimonas and Nephroselmis) a core Chlorophyte (Picochlorum) and two Chromalveolates (Pavlova and Phaeodactylum), with a last common ancestor tracing back to the last common eukaryotic ancestor. Algae cells were collected on filters and solubilized in ethyl acetate for analysis by UHPLC/ESI-MS<fnref n="2" /> (Orbitrap). Metabolite polarity ranges from polar to neutral lipids and pigments. Top ten most abundant metabolites from each species were identified on the basis of MS<fnref n="2" /> spectra. Comparison and multivariate analyses were performed to identify Mamiellales specific metabolites.

## Results and impact

We developed a simple workflow for lipids and pigments analysis, the method appeared to be suited to discriminate algae at the species and order level on the basis of lipid content. The method covers a broad range of lipids from neutral (TAG, DAG, MAG) to polar lipids (MGDG, DGDG, SQDG, DGTA/S, PG, PI, PC, PE). Chemotaxonomic analyses performed both on total ions and on top 10 metabolites exhibit the same pattern indicating most abundant constituents of algae are also robust biomarkers of algae delineation. Chemotaxonomies were surprisingly consistent with gene phylogenies suggesting metabolome divergence reflects evolutionary divergence [3].

## References

- Piganeau et al. 2008 Genome Biology. 9 (1): R5

- Dorrell et al. 2011. ASM Journal. 10 (7): 856-868 [3] Marcellin-Gros et al. 2019 (submission). Marin Drugs.

<footnote n="1">¹ UMR 7232 – Laboratoire de Biologie Intégrative des Organismes Marins – Observatoire Océanologique de Banyuls-sur-Mer – 1, Avenue Pierre Fabre 66650 Banyuls-sur-Mer, France</footnote>

<footnote n="2">² USR 3579 – Laboratoire de Biodiversité et Biotechnologies Microbiennes – Observatoire Océanologique de Banyuls-sur-Mer – 1, Avenue Pierre Fabre 66650 Banyuls-sur-Mer, France</footnote>
# Poster 141: P141 Deciphering *B.methanolicus* metabolism for a one carbon-based production platform

Cláudia M. VICENTE<fnref n="1" />, Baudoin DELÉPINE<fnref n="2" />, Marina G. LÓPEZ<fnref n="3" />, Marc CARNICER⁴, Volker F. WENDISCH<fnref n="5" />, Stéphanie HEUX<fnref n="6" />

## Introduction

One-carbon (C1) compounds such as methanol, with its low price and the possibility to be produced from renewable energy sources, are attractive feedstock alternatives for microbial fermentation. The gram-positive Bacillus methanolicus is a natural methylotroph (i.e. able to grown on a C1 compound as its sole energy and carbon source) and it has been described to produce large quantities of glutamate and lysine in methanol at high temperature, making it a good candidate for biotech applications.

## Technological and methodological innovation

Here we conducted a system level analysis of *B. methanolicus* to understand its highly efficient methylotrophic metabolism, using modelling and omics analysis, particularly an instationary 13C-metabolic flux analysis using intra and extracellular pools of central metabolites in both methylotrophic and non-methylotrophic conditions.

## Results and impact

Overall we have obtained insight into the metabolism and underlined key pathways that characterize this decisive C1 catabolism. Broadening the knowledge on natural methylotrophy will lead to metabolism improvement and to establish *B. methanolicus* as a promising cell factory, as well as help build synthetic methylotrophy in other model organisms.

## References

- Heux et al. 2017. Current Opinion in Biotechnology. 43:104-109

- Carnicer et al. 2016. Microbial Cell Factories. 15:92

- Müller et al. 2015. Applied Microbiology and Biotechnology. 99:535-551

<footnote n="1">¹ TBI, Université de Toulouse, CNRS, INRA, INSA, Toulouse, France</footnote>

<footnote n="2">² TBI, Université de Toulouse, CNRS, INRA, INSA, Toulouse, France</footnote>

<footnote n="3">³ Genetics of Prokaryotes, Faculty of Biology & CeBiTec, Bielefeld University, Bielefeld, Germany ⁴ TBI, Université de Toulouse, CNRS, INRA, INSA, Toulouse, France</footnote>

<footnote n="5">⁵ Genetics of Prokaryotes, Faculty of Biology & CeBiTec, Bielefeld University, Bielefeld, Germany</footnote>

<footnote n="6">⁶ TBI, Université de Toulouse, CNRS, INRA, INSA, Toulouse, France</footnote>
# Poster 142: P142 A Community-led Initiative to Develop and Promote Quality Assurance and Quality Control in Untargeted Metabolomics Research: the metabolomics Quality Assurance and quality Control Consortium (mQACC)

metabolomics Quality Assurance and quality Control Consortium (mQACC)

## Introduction

mQACC [1] was established in February 2018 and has a central mission to communicate and promote the development, dissemination, and harmonization of best practices in quality assurance (QA) and quality control (QC) in untargeted metabolomics. The formation of the consortium was a result of the National Institutes of Health-funded Think Tank on Quality Assurance and Quality Control for Untargeted Metabolomics Studies meeting in 2017, where participants identified long-term priorities for QA/QC efforts.

## Technological and methodological innovation

Three key priorities are being driven forward: 1) publish a workshop report [2]; 2) document the complete experimental procedure for untargeted metabolomics; and 3) identify 2-3 reference materials to be developed. The consortium currently comprises over 65 representatives from North America, South America, Europe, and Asia, including instrument manufacturers, commercial laboratories, and government/academic stakeholders. mQACC is currently addressing its initial priorities and expanding these efforts.

## Results and impact

mQACC pursues the following objectives: 1) to identify, catalog, harmonize, and disseminate QA/QC best practices; 2) to establish mechanisms to enable the metabolomics community to adopt QA/QC best practices; 3) to promote and support systematic training in QA/QC best practices; and 4) to encourage the prioritization and development of reference materials applicable to metabolomics research. We will discuss current progress in relation to the objectives and will also highlight how the metabolomics community can get involved in this important initiative.

## References

[1] https://epi.grants.cancer.gov/Consortia/mQACC/ [2] R.D. Beger et al. 2019. Metabolomics. 15:4
**Poster 143: P43 Analysis of Endophytic Colletotrichum sp. strains by MALDI-TOF mass spectrometry and t-SNE Molecular Networking**

Morgane BARTHELEMY<fnref n="1" />; Vincent GUERINEAU<fnref n="1" />; Grégory GENTA-JOUVE<fnref n="2" />,<fnref n="3" />; Jean-Luc WOLFENDER<fnref n="4" />; Didier STIEN<fnref n="5" />; Véronique EPARVIER<fnref n="1" />; David TOUBOUL<fnref n="1" />

**Introduction**

From the 197 endophytes cultivated endophytic microorganisms from 6 species of the French Guianese palm tree Astrocaryum sciophilum, 42 strains were genetically identified as Colletotrichum. Protein fingerprints by MALDI-TOF allowed deciphering species variability. LC-MS2 data were processed to generate a Molecular Network (MN) using MetGem software to explore chemical diversity. Complete structural identification led to an unprecedented series of new metabolites designated as Colletamide.

**Technological and methodological innovation**

Protein fingerprints were acquired by MALDI-TOF after optimization of extraction method, clustered and were highly correlated to cytotoxic activities of respective ethyl acetate extracts whereas no correlation with ITS sequencing was obtained. MetGem software [1] was designed to generate MN using innovative t-SNE visualization preserving the local distances between related groups of spectra (clusters). Combination of NMR, CD and DP4 calculations [2] were used for complete structural analysis.

**Results and impact**

Protein fingerprints were precisely reported on the variability between strains at sub-species level and were fully correlated to the cytotoxicity. MN predictions were fully confirmed after isolation of cytotoxic pentacyclopentides and cytochalasins (µM range). Isolation and complete identification of four new metabolites bearing the identical decadienamide moiety were performed. This methodology allows targeting interesting microbial extracts in the search for new bioactive metabolites.

**References**

Olivon et al. 2018. Anal. Chem. 90(23) 13900-13908

Smith et al. 2010 J. Am. Chem. Soc. 132(37) 12946-12959

<footnote n="1">¹ CNRS – Institut de Chimie des Substances Naturelles, UPR2301, Université Paris – Saclay, 91198 Gif-sur-Yvette cedex, France</footnote>

<footnote n="2">² UMR 8038 CiTCOM, Faculté de Pharmacie de Paris, Université Paris Descartes, 75006 Paris, France</footnote>

<footnote n="3">³ Molecules of Communication and Adaptation of Microorganisms (UMR 7245), National Museum of Natural History, CNRS, Paris, France</footnote>

<footnote n="4">⁴ School of Pharmaceutical Sciences, EPGL, University of Geneva, University of Lausanne, CH-1211, Geneva, Switzerland</footnote>

<footnote n="5">⁵ Sorbonne Université, CNRS, Laboratoire de Biodiversité et Biotechnologies Microbiennes, Observatoire Océanologique, Banyuls/Mer.</footnote>
**Poster 144: P44** *Fungal endophyte exo-metabolites alter the morphology and metabolome of the plant pathogen Fusarium graminearum: an LC-MS based metabolomics approach to unravel the biocontrol effect*

Mohamed F. ABDALLAH<fnref n="1" />,<fnref n="2" />; Gerard Bryan GONZALES<fnref n="3" />; Maarten AMEYE<fnref n="2" />; Geert HAESAERT<fnref n="2" />; Kris AUDENAERT<fnref n="2" />,⁵; Sarah DE SAEGER<fnref n="1" />,⁵

**Introduction**

Fusarium graminearum (FG) is a predominant fungal pathogen of cereals, which also produces secondary metabolites, i.e. mycotoxins, that harm human and animal health [1]. We previously showed the potential of two endophytic fungi: Epicoccum nigrum (EG) and Sordaria fimicola (SF) to inhibit growth and mycotoxin production of FG [2]. In this study, we used metabolomics to elucidate the potential mechanisms involved in their biological control.

**Technological and methodological innovation**

We optimized an in vitro assay using tissue plate inserts to assess the biological effects of EG and SF exo-metabolites on FG. Changes in growth characteristics of FG exposed to the exo-metabolites were monitored using automated high-resolution multispectral imaging. We further investigated the metabolome profile changes of FG after exposure to the exo-metabolites using untargeted metabolomics on both reversed-phase and HILIC to elucidate potential mechanisms of action.

**Results and impact**

We showed that EG and SF exo-metabolites altered the morphological and growth characteristics, as well as the overall metabolome of FG. Using multivariate analyses, we selected metabolic features that could potentially elucidate the biochemical changes undergone by FG in response to the presence of exo-metabolites. This study shows that apart from competition of live fungi, EG and SF exo-metabolites themselves exert metabolic action against FG which could explain their biocontrol activity.

**References**

Abdallah, M. F., Ameye, M., De Saeger, S., Audenaert, K., & Haesaert, G. (2019). Biological Control of Mycotoxigenic Fungi and Their Toxins: An Update for the Pre-Harvest Approach. In Mycotoxins - Impact and Management Strategies. IntechOpen. doi:10.5772/intechopen.76342

Abdallah, M. F., De Boevre, M., Landschoot, S., De Saeger, S., Haesaert, G., & Audenaert, K. (2018). Fungal endophytes control fusarium graminearum and reduce trichothecenes and zearalenone in maize. Toxins, 10(12), 493. doi:10.3390/toxins10120493

<footnote n="1">¹Centre of Excellence in Mycotoxicology and Public Health, Ghent University, Belgium</footnote>

<footnote n="2">²Laboratory of Applied Mycology and Phenomics, Faculty Bioscience Engineering, Ghent University, Belgium</footnote>

<footnote n="3">³Group of Gastroenterology, Faculty of Medicine and Health Sciences, Ghent University, Belgium and VIB Inflammation Research Centre, Ghent, Belgium</footnote>

<footnote>$ equally contributed</footnote>
# Poster 145: P145 Evaluation of micro Pillar Array Columns (μPAC™) Combined with High Resolution Mass Spectrometry for Lipidomics

Gilles Jaouen², Koen Sandra¹, Jonathan Vandenbussche¹, Ruben ‘t Kind¹, Bo Claerebout², Jeff Op de Beeck², Wim De Malsche³, Gert Desmet²,³ and Pat Sandra¹

1Research Institute for Chromatography (RIC) and Metablys, Kortrijk, Belgium.

2PharmaFluidics, Technologiepark-Zwijnaarde 82, 9052 Ghent, Belgium.

3Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium

## Introduction

As an alternative to conventional packed bed nano LC columns, micromachined chip columns known as micro Pillar Array Columns (μPAC™) are emerging. Their separation capacities are illustrated here in the context of a lipidomics workflow.

## Technological and methodological innovation

The high permeability and low ‘on-column’ dispersion obtained by the perfect order of the separation bed makes μPAC™ chromatography specific. The peak dispersion coming from heterogeneous flow paths in separation bed is eliminated, therefore components remain more concentrated during separation resulting in better separation performance (1). The freestanding nature of the pillars also leads to lower backpressure, allowing a high operational flow rate flexibility with good peak capacities (2).

## Results and impact

Performance of the column is illustrated with the analysis of human blood plasma lipids.

Using a 200cm long μPAC™ column in combination with HRMS high lipidome coverage can be obtained. All major lipid classes are detected and their locations are shown on the chromatograms. Next to the inter-class separation, the methodology provides intra-class separation based on number of carbons and degree of saturation in the fatty acid side chains. Furthermore, isomeric lipids can be resolved(3).

## References

W. De Malsche, H. Gardeniers, G. Desmet: Experimental Study of Porous Silicon Shell Pillars under Retentive Conditions. Anal. Chem. 80 (2008) 5391-5400.

W. De Malsche, J. Op de Beeck, S. De Bruyne, H. Gardeniers, G. Desmet: Realization of 1 × 10E6 Theoretical Plates in Liquid Chromatography Using Very Long Pillar Array Columns. Anal. Chem. 84 (2012) 1214-1219.

K. Sandra, J. Vandenbussche, R. ‘t Kindt, B. Claerebout, J. Op de Beeck, W. De Malsche, G. Desmet, P. Sandra:

Evaluation of Micro-Pillar Array Columns (μPAC) Combined with High Resolution Mass Spectrometry for Lipidomics.

LC

GC Spec. Issues 30.6 (2017) 6-13. [1] First author et al. YEAR. Journal. Volume and pages
# Poster 146: P146 Chemical mappings for the flowers of Abeliophyllum distichum using metabolomics tools

Yeong-Geun LEE¹; Seung-Ok YANG²; Won-Sil CHOI²; Yun Hee KIM²;
Jeon HWANG-BO³; Hyoung-Geun KIM¹; Trong Nguyen NGUYEN¹; Nam-In BAEK¹

## Introduction

Protection of the sovereignty of biological resources in each country is important due to the recent entry into force of the Nagoya protocol. The purpose of this protocol is the fair and equitable sharing of benefits arising from the use of genetic resources [1], thereby contributing to the conservation and sustainable use of biodiversity. With this protocol in force, research using domestic native species became a key issue.

Among the various Korean's plants, Abeliophyllum distichum (Oleaceae), which comprise of not only one species but also one genus and grown only in the Korean Peninsula, has high scarcity value [2]. Due to the effectuation of the Nagoya Protocol, value of this plant increases in process of time. But to date, no study has been reported for metabolites and the activities of A. distichum flowers. At the present, five variants have been reported; white miseon (A. distichum Nakai); pink miseon (A. distichum for. lilacinum Nakai); ivory miseon (A. distichum for. eburneum T. B. Lee); blue miseon (A. distichum for. viridicalycinum T. B. Lee); round miseon (A. distichum var. rotundicarpum T. B. Lee) [3]. The variants were classified based on only morphological characteristics especially on the color of petals and sepals or shape of fruits. Accordingly phytochemical investigation and chemical mapping for the variants should be valuable.

## Technological and methodological innovation

NMR spectroscopy, LC-MS, GC/MS, and IR are mainly used as metabolomics tools. Each analytical method has its own advantages as well as disadvantages such as limitation of target analysis, reproducibility, sensitivity, and so on. This study conjugated NMR, LC/MS, and GC/MS to reinforce each strength and make up for each weakness in complete identification of all metabolites and quantification [4]. And major metabolites of A. distichum flowers were isolated through repeated SiO2, ODS, and Sephadex LH-20 column chromatography and identified based on extensive analysis of 1D- and 2D-NMR and MS. Also Head Space-Solid Phase Micro Extraction-Gas Chromatography/Mass Spectrometry (HS-SPME-GC-MS) analysis was performed to profile volatiles for chemical mapping.

## Results and impact

Twenty-nine metabolites including four new ones were isolated from A. distichum flowers through repeated normal, reverse-phase, and Sephadex LH-20 column chromatographies and their structures were determined using classical spectroscopic methods such as NMR, IR, MS.

NMR, UHPLC-tripleTOF-ESI-MSMS, and GC/MS based metabolomics study was performed to understand chemical differentiation among five variants of this flowers. From NMR, LC/MS, and GC/MS analyses, 50 primary metabolites, 58 secondary metabolites, and 145 hydrophobic primary metabolites were identified, respectively. As a result, primary and secondary metabolites showed different patterns among all variants according to morphological characteristics. Also metabolic flux analysis of five variants was confirmed through correlation analyses of the primary and secondary metabolites.

From this results, it was confirmed that various patterns of morphological characteristics such as the shape of fruits and color of sepals and petals were derived from the variety of primary and secondary metabolites. Especially, relative contents of flavonoids and phenylethanoid glycosides of two colored variants (pink and ivory miseon) are much higher than those of white variants (white and round miseon). Among colored flowers, pink miseon has more phenylethanoid glycosides and fewer flavonoids than pink miseon. It suggested that phenylethanoid glycosides and flavonoids get involved in color of petals. In addition, 66 volatile components of this plant identified by HS-SPME-GC/MS also showed unique patterns according to morphological characteristics, especially color of petals.

Metabolomics, NMR, LC/MS, and GC/MS data, showed high significance to understand chemical differentiation of the morphological characteristics among five variants of this flowers.
# Poster 147: P147 METABOLOMIC INSIGHT IN THE RESPONSES OF STREAM BIOFILMS TO THE HERBICIDE DIURON AND ITS MODULATION BY ENVIRONMENTAL FACTORS

Nicolas CREUSOT¹, Soizic MORIN¹, Betty CHAUMET¹, Mélissa EON¹, Nicolas MAZZELLA¹

¹ INRAE, UR EABX, 50 avenue de Verdun Gazinet, F-33612 Cestas, France

## Introduction

In the context of global change, aquatic ecosystems face multiple stressors that may endanger their sustainability and associated ecosystem services. It is therefore crucial to better understand how these pressures interact and modulate the responses and further the tolerance of aquatic organisms, in order to gain knowledge on the resilience of these ecosystems. In particular, regarding the increasing aquatic pollution, there is a need to establish the causality link between the exposure to chemicals and the effect(s) in order to propose monitoring and remediation solutions [1]. To tackle this challenge, the (xeno)metabolomic approach aims to characterize all (chemical) exposures (i.e. xeno-metabolome, xenobiotics as well as their products from phase I and/or II metabolism) in addition to exposure-induced effects on cellular biomolecules (i.e. endo-metabolome) [2,3]. In this global change context, stream biofilms -as a complex assemblage of algae, fungi, bacteria, protozoa - are increasingly used because of their relevance to investigate the impact of multiple environmental stressors at the community level (function and structure), as they also play a key role in aquatic ecosystems (e.g.primary production) [4].

## Technological and methodological innovation

By using a (xeno)metabolomic approach, this study aims to investigate the influence of environmental confounding factors (temperature, seasonality, flow, photoperiod) on the impact of the chemical stress on stream biofilms. To this end, stream biofilms colonized at a reference site were exposed to the herbicide diuron - a model compound for photosynthesis inhibition- at the laboratory under different controlled conditions. The metabolomics responses were assessed for the different tested conditions through organic extraction by using accelerated solvent extraction followed by injection on UPLC-ToF system (Ultra-Performance Liquid Chromatography — Time of Flight Mass Spectrometry, Xevo G2-S ToF, Waters). As a first step, data were processed in MzMine2 in order to identify relevant features regarding exposure to diuron. The modulation of these signals by environmental confounding factors will be soon investigated. In addition, the photosynthetic activity was also assessed as a functional response of the biofilms supported by the metabolic changes triggered by diuron.

## Results and impact

The data analysis is still ongoing. Nevertheless, by using the PlantCyc database, the first processing of the data in Mzmine2 allowed the identification of two plant-specific fatty acids, the docosapentaenoic acid and the eicosapentaenoic acid. These are two omega-3 fatty acids that play a major in the sustainability of the trophic chain and so ecossystemic services since they are difficult to produce by higher trophic level (i.e. high metabolic cost). Although their identities remain to be confirmed through the injection of the standards, our result showed a strong inhibition of the production of the docosapentaenoic acid in the exposed biofilms (500 fold).

This study will provide a better understanding of the metabolic alteration associated with the inhibition of the photosynthesis activity, as increasing knowledge on the metabolic responses of heterotrophic communities (bacteria, fungi) following diuron exposure. By investigating confounding factors, it would help to identify metabolic pathways that might be involved in the adaptation/tolerance of autotrophic and heterotrophic aquatic communities. It will finally support the discovery of biomarkers for the monitoring of water quality in the global change context.

## References

[1] Ankley et al. 2010. Environmental Toxicology and Chemistry, Vol. 29, No. 3, pp. 730-741

[2] Bonvallot et al 2018 Current Opinion in Toxicology, 8:48 – 56

[3] Al-sahli et al. 2012. Environmental Science and Technology, 46, 9080-9088

[4] Morin et al. 2017. Journal of Hazardous Materials 334, 223-232
# Poster 148: P148 The Power of MS/MSALL Acquisition for High-Throughput Metabolomics Studies

Mariateresa Maldini¹; Eva Duchoslav²; Cyrus Papan³; Khatereh Motamedchaboki⁴

...

## Introduction

One of the main goals of researchers in the field of untargeted metabolomics is to analyze a large number of samples and obtain the most useful information in the shortest time with limited sample preparation. The utility of the direct infusion or “shotgun” approach for high-throughput metabolomic and lipidomic profiling analyses using the infusion MS/MSALL acquisition approach in conjunction with fast sample introduction by flow injection analysis (FIA) has been demonstrated¹,².

This work investigates the performance of an automated processing for semi-quantitation and direct structural identification utilizing the MS/MSALL data, in support of metabolomics studies.

## CONCLUSIONS

Earlier FIA-based metabolomic profiling⁵ approaches utilized just the HR MS scans and therefore they were not sufficient for a successful metabolite identification. The shotgun direct infusion approach combined with the data independent acquisition strategy collecting HR MS/MS from all precursors makes a more specific identification of analytes and the quantitation at the MS and MS/MS levels possible.

Curated and annotated Accurate Mass Metabolite Spectral Library provided unique conditions for a quantitation method as well as served as a reference source for an automated library search. Forty three endogenous metabolites were studied to establish the precision and accuracy of the method comprising both MS and MS/MS data. With the low CV values (around 3%), the MS/MSALL technique allows to uncover small changes in the metabolome.¹⁶² metabolites were identified in urine sample through the automated spectral processing and library search pipeline.

The MS/MSALL data collection strategy is well suited for high-throughput metabolomic profiling studies since it is fast and it offers semi-quantitative results complemented with a compound identification based on HR MS/MS spectral match.

## REFERENCES

* M Maldini; C Papan; B K Ubhi, Proceedings from the ASMS Conference 2018.

* B Simons, D Kauhanen, T Sylvänne, K Tarasov, E Duchoslav, and K Ekroos. “Shotgun Lipidomics by Sequential

Precursor Ion Fragmentation on a Hybrid Quadrupole Time-of-Flight Mass Spectrometer.” Metabolites 2, no. 1 (February 20, 2012): 195–213.

* T Bruderer, E Varesio, A O Hidasi, E Duchoslav, L Burton, R Bonner, G Hopfgartner. Anal Bioanal Chem. 2018 Mar;410(7):1873-1884. doi: 10.1007/s00216-018-0860-x

* Wishart DS, Feunang YD, Marcu A, Guo AC, Liang K, et al., HMDB 4.0 — The Human Metabolome Database for 2018. Nucleic Acids Res. 2018. Jan 4;46(D1):D608-17.

* T Fuhrer, D Heer, B Begemann, N Zamboni. 2011. “High-Throughput, Accurate Mass Metabolome Profiling of Cellular Extracts by Flow Injection–Time-of-Flight Mass Spectrometry.” Analytical Chemistry 83 (18): 7074-80.2
# Poster 149: P149 Exploring a volatomic-based strategy to study Lavendula semiochemicals

Émilie STIERLIN<fnref n="1" />, Florence NICOLE<fnref n="2" />, Thomas COSTES<fnref n="3" />, Xavier FERNANDEZ, Thomas MICHEL<fnref n="1" />*

Manosque, France

## Introduction

Lavender (Lavandula angustifolia) and lavandin (Lavandula x intermedia) are emblematic plants of Provence and are widely used for their essential oils in perfumery, cosmetics and aromatherapy [1]. However, since few years, lavender fields suffered from a severe decline in France due to the propagation of yellow disease. This disease is associated with the presence of stolbur phytoplasma, which is transmitted by Hyalesthes obsoletus, a sap-sucking insect [2]. Consequently, a dramatic decrease has been seen in the production of French lavender and in essential oil yields.

## Technological and methodological innovation

To better understand chemical defenses of Lavendula species, we proposed a volatomic approach. To highlight changes in Volatile Organic Compounds (VOCs), we developed an analytical strategy based on dynamic headspace extraction (DHS), followed by Automated Thermal Desorber-Gas Chromatography-Mass Spectrometry (ATD-GC-MS) to characterize VOCs emitted by lavender aerial parts. In addition, stored VOCs were extracted with hexane and then analyzed by GC-MS.

## Results and impact

This is the first time such an approach has been used to study emitted and stored VOCs from lavender in open field. Several compounds were found as metabolomic markers of yellow disease infection. For instance, the PLS-DA score plot performed on lavandin plants showed a significant separation on two groups (13.3% of misclassification and P-value < 0.05). Among the discriminating compounds, lavandulyl acetate and (E)-β-farnesene were significantly more emitted by asymptomatic plants, while (Z)-3-hexen-1-ol acetate and 1,8-cineole were significantly more emitted by symptomatic plants.

## References

[1] Lis-Balchin M. 2002. Lavender: The Genus Lavandula. Taylor & Francis, p.296. [2] Sémétey O. et al. 2018. Applied and Environmental Microbiology, 84(24), e01507-18.

<footnote n="1">¹ Université Côte d'Azur, Institut de chimie de Nice, UMR 7272, 28 avenue Valrose, 06108 NICE Cedex 2, France</footnote>

<footnote n="2">² Université de Lyon, Université Jean Monnet, Laboratoire BVPAM, EA2061, 23 rue du Dr Paul Michelon, 42000 SaintÉtienne, France</footnote>

<footnote n="3">³ CRIEPPAM (Centre Régionalisé Interprofessionnel d'Expérimentation en PPAM), Route de Volx - Les Quintrands, 04100</footnote>
# Poster 150: P150 Plasma metabolomics to identify biomarkers of foie gras quality in mule duck

Zohre Mozduri<fnref n="1" />,<fnref n="2" />; Nathalie MARTY-GASSET<fnref n="1" />; Agnès BONNET<fnref n="1" />, Mireille MORISSON<fnref n="1" />, Ali Akbar Masoudi<fnref n="2" />, Cécile MD. BONNEFONT<fnref n="1" />

## Introduction

"Foie gras" of duck is a traditional product in France. The liver weight (LW) and the technological yield (TY) when cooking are the main characteristics of liver quality. The TY must be greater than 70% [1]. The LW was previously modeled with body weight and feed intake [2]. The TY was already modeled but the predictors required analyzing liver characteristics [2 and 3]. The objective of this study is to identify non-invasive biomarkers of the TY with 1H-NMR analysis of mule duck plasma.

## Technological and methodological innovation

The experimental design is clearly described in [2]. Briefly 65 mule ducks were overfed during 6 to 12 days. Plasmas and livers were sampled every two days. The LW and TY were measured. 1H-NMR spectra of plasma were acquired on a NMR 600 MHz Bruker Avance III HD. The spectra were transformed into a table of 239 buckets with WorkFlow4Metabolomics [4] and into a table of 87 metabolites with ASICS [5]. Then O-PLS regressions were performed with SIMCA-P+ software to identify the biomarkers of LW and TY.

## Results and impact

With bucket data, the individual plots of O-PLS drew good regression of LW (R2X=0.795, R2Y= 0.314) and TY (R2X= 0.805, R2Y= 0.979). In the axes that were correlated to LW and TY, respectively 12 and 13 buckets had a VIP-value up to 1.5. The identification of peaks and the analyses of metabolite data are in progress. The non-invasive biomarkers that will be identified will have to be validated with other lab methodology with the same samples and with other animals.

## References

[1] JORF. 1993. Décret n° 93-999 du 9 août 1993

[2] Bonnefont CMD. et al. 2019. Poultry Science. 0:1–10

[3] Théron L. et al. 2012. J. Anim. Sci. 90:3312–3317

[4] Giacomoni F. et al. 2014. Bioinformatics. 31(9):1493–1495

[5] Lefort G. et al. 2019. Bioinformatics. 35(21):4356-4363

<footnote n="1">¹ GenPhySE, Université de Toulouse, INRA, ENVT, Castanet Tolosan, France</footnote>

<footnote n="2">² Department of Animal Science, Faculty of Agriculture, Tarbiat Modares University, Iran, Tehran</footnote>
# Poster 151: P151 Effect of organic fertiliser on metabolic profile of hydroponically cultivated tomato

Dmitry KECHASOV<fnref n="1" />; Roald KOMMEDAL²; Michel VERHEUL<fnref n="1" /> and Ivan PAPONOV<fnref n="1" />

## Introduction

Global production of tomatoes is growing rapidly. Simultaneously, organic waste from farms and greenhouses accumulates and pollutes aquatic ecosystems and atmosphere [1]. Recycling of waste fractions might reduce environmental impact of food production industry. However, an effect of organic fertilization on tomato fruit quality and plant development on metabolite level is not fully investigated. Former studies focused on answering how organic fertilizers affect biomass production and classic fruit quality parameters [2,3]. Metabolic status of roots receiving organic fertilizer has not been explored comprehensively, primarily because of difficulties during root extraction from soil. Hydroponic cultivation allows assessment of root metabolic and ionic status through analysis of root tissue and xylem sap. Xylem sap is a rare target for metabolomic studies of tomato [4,5]. However, it can reflect metabolic processes taking place in roots.

## Technological and methodological innovation

We developed hydroponic cultivation system allowing growth of tomato plant on organic and mineral fertilizers with recirculation of nutrient solution. Influence of fertilizer composition on tomato fruit quality and metabolic profile of mature tomato plants were investigated.

The study is distinctive in terms of combination of cultivation aspects such as hydroponic growing, organic fertilization, and research subjects – root, xylem sap and fruit metabolomes.

## Results and impact

We performed metabolomic and ionic analysis (by GC-MS and IC) of fruits, leaves, roots and xylem sap of tomato plants growing in hydroponic cultivation system with recirculation of nutrient solution. Organic and mineral fertilizers were used in combination with specific plant growth promoting bacteria culture. Results shows that organic waste can be used as fertilizer in tomato production for long-term cultivation. Presence of organic fertilizer enhanced nitrogen and amino acid metabolism in tomato roots, but reduces content of antioxidants (e.g., ascorbate, chlorogenate). Addition of the plant growth promoting bacteria positively affected content of sugars in xylem sap and fruits. Combination of the bacteria and the organic fertilizer resulted in a distinct metabolic profile, which was supplemented by an increased fruit yield.

Our results contribute to the limited knowledge of tomato root metabolism and provide a ground for further discussions.

## References

- Woodward, G., et al. 2012. Science 336(6087): 1438-1440

- Mitchell, A. E., et al. 2007. Journal of agricultural and food chemistry 55(15): 6154-6159

- Oliveira, A. B., et al. 2013. PLOS ONE 8(2): e56354

- Lowe-Power, T. M., et al. 2018. Environmental Microbiology 20(4): 1330-1349

- Rellán-Álvarez R., et al. 2011. Frontiers in Plant Science 2 (66): 1-18

<footnote n="1">¹ Norwegian Institute of Bioeconomy</footnote>

<footnote>Research ² University of Stavanger</footnote>
# Poster 152: P152 TACKLING THE ANTIOXIDANT METABOLOME OF WHITE WINE

Régis GOUGEON<fnref n="1" />; Rémy ROMANET<fnref n="1" />; Chloé ROULLIER-GALL<fnref n="1" />, Florian BAHUT<fnref n="1" />, Basem KANAWATI<fnref n="2" />, Daniel HEMMLER<fnref n="2" />, Greg DRUSCHEL<fnref n="3" />, Philippe SCHMITT-KOPPLIN<fnref n="2" />,<fnref n="4" />, Maria NIKOLANTONAKI<fnref n="1" />

## Introduction

The reputation of great wines is synonym to the stability of their aroma flavour of young wines while developing specific varietal nuances during aging. For dry white wines, oxidation further relates to the actual worldwide problem of premature oxidation, which concerns cellar worthy white wines within just a few years after the vintage. However, understanding the various molecular mechanisms potentially involved, which can impact the transient wine composition, requires that top-down analytical strategies are implemented.

## Technological and methodological innovation

In this presentation, we will show how two sets of combined analytical strategies involving on the one hand FT-ICR-MS and electrochemical oxidation of bottled wines, and on the other hand LC-QToF-MS of quinone-derivatized wines can bring unprecedented molecular signatures of dry white wines antioxidant metabolome.

## Results and impact

FTICR-MS revealed the broad diversity of sulfur-containing compounds, which appear to be the most sensitive to oxidation, whereas nitrogen-containing compounds were mostly formed upon oxidation [1]. The electrophilic derivatization of up to 92 wines specifically unravelled the pool of native nucleophilic compounds potentially involved in the trapping of transient oxidized species, which include an important proportion of amino acids and peptides containing amino acids that are known to have antioxidant properties (Val, Leu, Ile, Pro, Trp, Cys and Met) [2].

## References

- Roullier-Gall et al. 2019. Food Chemistry. 286, 64-70

- Romanet et al. 2019. Talanta. submitted

<footnote n="1">¹ UMR PAM Université de Bourgogne/Agrosup Dijon, Institut Universitaire de la Vigne et du Vin, Jules Guyot, Rue Claude Ladrey, 21000 Dijon, France</footnote>

<footnote n="2">² Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Ingolstaedter Landstrasse 1, 85764 Neuherberg, Germany</footnote>

<footnote n="3">³ Department of Earth Sciences, Indiana University – Purdue University Indianapolis, IN 46202, United States</footnote>

<footnote n="4">⁴ Chair of Analytical Food Chemistry, Technical University of Munich, Alte Akademie 10, D-85354 Freising, Germany</footnote>
**Poster 153: P153 Metabolomics approach reveals disruption of metabolic pathways in the marine bivalve Mytilus galloprovincialis exposed to WWTP effluent**

Thibaut DUMAS<fnref n="1" />; Bénilde BONNEFILLE<fnref n="1" />; Elena GOMEZ<fnref n="1" />; Julien BOCCARD<fnref n="2" />; Hélène FENET<fnref n="1" />; Frédérique COURANT<fnref n="1" />

...

**Introduction**

Conventional wastewater treatment plants (WWTP) discharge multiple organic contaminants in aquatic environments [1]. A current challenge in ecotoxicology is to assess the effects of such multi-contamination on marine organisms. Environmental metabolomics can be helpful to meet these expectations [2]. In this study, we elucidated the effects of a WWTP effluent on the marine mussel Mytilus galloprovincialis through a non-targeted metabolomics approach.

**Technological and methodological innovation**

Mussels were exposed for 7 days in controlled laboratory conditions to a vehicle or to a WWTP effluent extract (WEE) corresponding to an environmental dilution of 5%. Metabolic fingerprints were generated by LC-HRMS and processed to highlight the impacted metabolites in male and female mussels. The WWTP effluent extract was characterized, based on a suspect screening approach of 80 contaminants, in an attempt to provide a first understanding of the relationship between observed effects and contaminants.

**Results and impact**

We highlighted key molecular events triggered by the WEE exposure (modulation of amino acids, purine and pyrimidine metabolism, Krebs cycle, etc.) which could lead to adverse outcomes on individual (reproduction, energy metabolism, osmoregulation, etc.). A sex-specific response was also demonstrated showing the importance to consider sex in the experimental design. Finally, 42 contaminants were detected in the WWTP effluent extract and could be related to the observed effects.

**References**

[1] R. Loos et al. 2013. Water Res. 47, 6475-6487 [2] C. Y. Lin et al. 2006. J. Pestic. Sci. 31, 245-251

<footnote n="1">¹ HydroSciences Montpellier, Université de Montpellier, 15 avenue Charles Flahault, 34093 Montpellier, France</footnote>

<footnote n="2">² School of Pharmaceutical Sciences, University of Geneva, 1 rue Michel Servet, 1211 Geneva, Switzerland</footnote>
**Poster 154: P154 Molecular networking as a novel approach to unravel chemical diversity of Dinophysis spp. from French coastal waters**

Manoëlla Sibat¹*, Damien Réveillon¹, Chloé Antoine¹², Liliane Carpentier¹, Georges Augustin Rovillon¹, Véronique Sechet¹, Samuel Bertrand²

¹ Ifremer, Phycotoxins Laboratory, rue de l'île d'Yeu, BP 21105, 44311 Nantes Cedex 03, France.
manoella.sibat@ifremer.fr; damien.reveillon@ifremer.fr, chloe.antoine@ifremer.fr, liliane.carpentier@ifremer.fr, Georges.Augustin.Rovillon@ifremer.fr, veronique.sechet@ifremer.fr

² University of Nantes, Laboratoire MMS (Mer, Molécules, Santé), UFR sciences pharmaceutiques et biologiques, 9 rue bias, BP 53508, 44035 Nantes cedex I, France. samuel.bertrand@univ-nantes.fr

**Introduction**

The dinoflagellate Dinophysis is the main threat to shellfish farming in France, as it is responsible for gastrointestinal illness (Diarrhetic Shellfish Poisoning) caused by the consumption of shellfish contaminated by two families of the toxins it produces: okadaic acid (OA) and their analogues dinophysistoxins (DTXs) and pectenotoxins (PTXs). Only four regulated toxins are routinely monitored by targeted chemical analysis by LC-MS/MS while Dinophysis spp. produce many other toxins[1].

**Technological and methodological innovation**

To identify unknown toxin analogues, we used a novel approach (Molecular Networking, MN) based on the untargeted analysis of mass spectrometry fragmentation data obtained by liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS/MS)[2]. In this study, MNs were created from cultures of several species of Dinophysis isolated from French coastal waters. Before obtaining informative networks, an optimization of data-dependent LC-HRMS acquisition conditions was conducted [3].

**Results and impact**

The comparison of 42 different conditions allowed us to focus on maximizing know-toxin detection with characteristic MS² and to provide a global overview of Dinophysis spp. metabolic diversity[4]. The peak picking step (MZmine 2) was mandatory to visualize well-resolved isomers. MN revealed the presence of new putative analogues of PTXs in some species of Dinophysis. Thus, MN provided a more complete and structured overview of the chemical and toxin diversity produced by harmful algae.

**References**

M. Garcia-Portela, B. Reguera, M. Sibat, A. Altenburger, F. Rodriguez, P. Hess, Mar Drugs 2018, 16.

R. A. Quinn, L. F. Nothias, O. Vining, M. Meehan, E. Esquenazi, P. C. Dorrestein, Trends Pharmacol Sci 2017, 38, 143.

F. Olivon, F. Roussi, M. Litaudon, D. Touboul, Anal Bioanal Chem 2017, 409, 5767.

J. L. Wolfender, J. M. Nuzillard, J. J. J. van der Hooft, J. H. Renault, S. Bertrand, Anal Chem 2019, 91, 704.
**Poster 155: P155 Fast quantitative 2D NMR for targeted and untargeted lipidomics and metabolomics.**

Estelle MARTINEAU<fnref n="1" />,<fnref n="2" />; Tangi JEZEQUEL<fnref n="2" />; Catherine DEBORDE<fnref n="3" />; Mickaël MAUCOURT<fnref n="3" />; Vanessa ZHENDRE<fnref n="3" />; Annick MOING<fnref n="3" />; Jérémy MARCHAND<fnref n="2" />,<fnref n="4" />; Yann GUITTON<fnref n="4" />; Bruno LE BIZEC<fnref n="4" />; Gaud DERVILLY-PINEL<fnref n="4" />; Jean-Nicolas DUMEZ<fnref n="2" />; Patrick GIRAUDEAU<fnref n="2" />

**Introduction**

Nuclear magnetic resonance (NMR) is a well-known and powerful analytical technique for the analysis of metabolic mixtures, both for untargeted studies involving a bucketing approach and for the targeted quantification of well-defined metabolites. Commonly, all studies are carried out relying on 1D 1H NMR, however sample complexity often limits the efficiency of 1D NMR in such applications, due to ubiquitous peak overlap.

**Technological and methodological innovation**

Using 2D NMR experiments overcomes this problem as it allows a better separation between overlapped resonances while yielding quantitative data, provided that appropriate analytical protocols are used. Besides, the experiment duration can be reduced by applying fast acquisition methods [1]. The general workflow to acquire fast quantitative 2D data in the “omics” context will be illustrated on three representative experiments: UF COSY, ZF-TOCSY with non-uniform sampling (NUS), and HSQC with NUS.

**Results and impact**

After providing some recommendations on how to apply this protocol [2], its implementation in the case of both targeted and untargeted metabolomic studies will be illustrated through recent examples. These include the absolute quantification of major metabolites in plant extracts with ultrafast COSY [3] or an untargeted lipidomic study of animal biofluid extracts with a variety of fast 2D methods [4].

**Funding:**

The authors acknowledge support of the European Research Council under the European Union's Horizon 2020 research and innovation program (ERC Grant Agreements n° 814747/SUMMIT and 801774/DINAMIX). Funding from the Region Pays de la Loire (RFI Food 4.2/Lipidotool), from MetaboHUB (ANR-11-INBS-0010 project) and from European project Eranet EraSysBio + “FRuit Integrative Modelling” are also acknowledged, as well as support from the Corsaire metabolomics core facility (Biogenouest).

**References**

Rouger et al. 2016. Encyclopedia of Spectroscopy and Spectrometry. 3rd edition. 588.

Martineau et al. 2019. Magnetic Resonance in Chemistry. 1-15.

Jézéquel et al. 2015. Metabolomics. 11. 1231-1242.

Marchand et al. 2018. Metabolomics. 14.60.

<footnote n="1">¹ SpectroMaitrise, CAPACITES SAS, Nantes, France</footnote>

<footnote n="2">² CEISAM, CNRS UMR 6230, Université de Nantes, Nantes, France</footnote>

<footnote n="3">³ Plateforme Métabolome Bordeaux – MetaboHUB, Centre INRA de Nouvelle Aquitaine Bordeaux, Villenave d'Ornon, France</footnote>

<footnote n="4">⁴ Laberca, Oniris, INRA, Nantes, France</footnote>
**Poster 156: P156 4D-Lipidomics investigation of in C. elegans daf-2 mutants related to ageing and longevity**

Aiko BARSCH¹; Sven W. MEYER¹; Ulrike SCHWEIGER-HUFNAGEL¹; Philipp SCHMITT-KOPPLIN²,³; Michael WITTING²,³

¹ Bruker Daltonics, Bremen, Germany

² Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Neuherberg, Germany

³ Chair of Analytical Food Chemistry, TU München, Weihenstephan, Germany

**Introduction**

The gene daf-2 was one of the first genes described to extend the lifespan in the model organism Caenorhabditis elegans. daf-2 encodes for the sole homologue of the insulin-like growth factor 1 (IGF-1) receptor in C. elegans. daf-2 mutants show different metabolic adaptations, including changes in lipid metabolism. Here, a 4D-Lipidomics workflow was applied to investigate characteristic changes in the complex lipidome of C. elegans wildtype vs. daf-2 mutants.

**Technological and methodological innovation**

Comprehensive coverage of detected lipids with a corresponding MS/MS spectrum is required for confident lipidome characterization. With the timsTOF Pro system (Bruker) utilized here, this is realized by the unique PASEF (Parallel Accumulation Serial Fragmentation) acquisition mode. This scan mode offers the possibility to generate clean MS/MS spectra by trapped ion mobility separation (TIMS) of chromatographically non-resolved isobaric lipids at high acquisition speeds.

**Results and impact**

An integrated workflow for evaluating 4D-Lipidomics data will be presented. Comparing lipid extracts from C. elegans wild type and mutants enabled the pinpointing of characteristic lipids and their confident identification. Merging information from PASEF MS/MS spectra acquired in positive and negative mode provided complementary information on lipid headgroups and fatty acid side chains. By matching measured CCS values to predicted values increased confidence in lipid assignment even further.
**Poster 157: P157 Lipid profiling to identify changes in lipid metabolism in
Caenorhabditis elegans upon starvation**

Kathrine B. DALL<fnref n="1" />, Jesper HAVELUND<fnref n="1" />, Eva Bang HARVALD<fnref n="1" />, Nils J. FAERGEMAN<fnref n="1" />, Michael WITTING<fnref n="2" />,<fnref n="3" />

**Introduction**

One of the most fundamental challenges for all living organisms is to sense and respond to alternating nutritional conditions in order to adapt their metabolism and physiology to promote survival and achieve balanced growth. We used UPLC-UHR-ToFMS based lipid profiling to examine temporal regulation of metabolism during starvation in wildtype Caenorhabditis elegans and in animals lacking the transcription factor HLH-30.

**Technological and methodological innovation**

We performed lipid profiling on a UPLC-UHR-ToF-MS using a previously described RP based method [1]. Employing data dependent acquisition (DDA) we collected over 150.000 MS2 spectra across the entire sample set. In order to be able to annotate lipids we created a workflow within the R statistical language, which performs exact mass searches, library MS2 matching using in silico databases as well as other functions to annotate detected lipid features.

**Results and impact**

We detected 4063 lipid features in positive and 2258 in negative ionization mode, which remained after normalization and filtering (detected in all QCs and RSD < 30%). Out of these 2068 were putatively annotated on the MS1 level and 427 on the MS2 level in positive ionization mode, and 955 and 118 in negative mode respectively. Our findings show that starvation alters the abundance of hundreds of lipid species in a temporal and HLH-30-dependent manner. Specifically, cardiolipins show changes exclusively in wildtype animals but not in hlh-30 mutants.

**References**

[1] Witting M., et al. 2014. J Chromatogr A. 1359.91-9

<footnote n="1">¹ Department of Biochemistry and Molecular Biology, Villum Center for Bioanalytical Sciences, University of Southern Denmark, Campusvej 55, 5230 Odense M, Denmark</footnote>

<footnote n="2">² Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Ingolstädter Landstraße 1, 85674 Neuherberg, Germany</footnote>

<footnote n="3">³ Chair of Analytical Food Chemistry, Technische Universität München, Maximus-von-Imhof-Forum 2, 85354 Freising, Germany</footnote>
**Poster 158: P158 High speed untargeted 4D-Lipidomics**
**LC-MS/MS workflows with Parallel Accumulation Serial Fragmentation**
**(PASEF)**

Aiko Barsch, Sven Meyer ¹, Ulrike Schweiger-Hufnagel ¹

¹ Bruker Daltonik GmbH – Germany

**Keywords:** Lipidomics, SRM 1950, Plasma, LC, MS, IMS, CCS
# Poster 159: P159 Electrospray Ionization and samples complexity in Meta-metabolomics: a biomarker or a suppressed ion?

Hikmat Ghosson<fnref n="1" />,<fnref n="2" />,*, Chandrashekhar Patil<fnref n="1" />, Amani Ben Jrad<fnref n="1" />,<fnref n="2" />, Delphine Raviglione<fnref n="1" />,<fnref n="2" />, Marie-Virginie Salvia<fnref n="1" />,<fnref n="2" />,<fnref n="3" />, Cédric Bertrand<fnref n="1" />,<fnref n="2" />,<fnref n="3" />,<fnref n="4" />

## Introduction

Electrospray Ionization is one of the most used ionization techniques for LC-MS-based metabolomics[1]. However, it presents several drawbacks, e.g. the ion suppression phenomenon, causing ion intensity decrease[2]. More the sample is complex, higher is the occurrence of the phenomenon. Thus, studying samples with different complexities may lead to consider some biologically non-significant molecular traces as markers of discrimination. This is due to ion suppression occurring in complex samples.

## Material and Methods

The issue is reported in an environmental context[3,4]. The study is performed on control non-spiked sediment samples and sediments spiked with a complex biopesticide; Bacillus thuringiensis israelensis. Meta-metabolome (endometabolome + xenometabolome) is extracted with QuEChERS method, then analyzed by LC-QToF in order to perform untargeted metabolic profiling, to discover the biomarkers of exposure. This to understand the pesticide impact on spiked sediments compared to control sediments.

## Results and Discussion

Results revealed several markers with lower intensity in the spiked group. They were co-eluting with multi-charged xenometabolites. Hence, these markers are either less concentrated due to a biological impact, or suppressed by the co-eluted molecules. Thus, to discriminate between biomarkers and suppressed ions, samples are diluted and analyzed. In fact, as dilution decreases the ion suppression, suppressed features are no more significantly discriminant between the two groups of samples.

## Keywords

Meta-metabolomics; Electrospray Ionization; Ion suppression; Biomarker; Liquid Chromatography-Mass Spectrometry

## References

Bedair et al. 2008. Trends Anal. Chem. 27(3):238-250

Antignac et al. 2005. Anal. Chim. Acta. 529(1-2):129-136

Patil et al. 2016. Sci. Total Environ. 566-567:552-558

Salvia et al. 2018. Environ. Sci. Pollut. Res. 25(30):29841-29847

<footnote n="1">¹ PSL Université Paris: EPHE-UPVD-CNRS, USR 3278 CRIOBE, Université de Perpignan, 52 Avenue Paul Alduy, 66860 Perpignan Cedex, France</footnote>

<footnote n="2">² UFR Sciences Exactes et Expérimentales, Université de Perpignan Via Domitia, 52 Avenue Paul Alduy, 66860 Perpignan Cedex, France</footnote>

<footnote n="3">³ Laboratoire d'Excellence « CORAIL », Université de Perpignan, 52 Avenue Paul Alduy, 66860 Perpignan Cedex, France</footnote>

<footnote n="4">⁴ S.A.S. AkiNaO, Université de Perpignan, 52 Avenue Paul Alduy, 66860 Perpignan Cedex, France</footnote>

<footnote>* hikmat.ghosson@univ-perp.fr</footnote>
**Poster 160: P160** *Experimental strategy to discover new bioactive lipopeptides produced by gut microbiota: unknown unknown approach by LC-HRMS.*

Amandine HUEBER<sup>ab</sup>, Camille PETITFILS<sup>ab</sup>, Pauline LE-FAOUDER<sup>a</sup>, Jean-Marie GALANO<sup>c</sup>, Alexandre GUY<sup>c</sup>, Thierry DURAND<sup>c</sup>, Nicolas CENAC<sup>b</sup> and Justine BERTRAND-MICHEL<sup>a</sup>

(a) MetaToul-Lipidomic, MetaboHUB, Inserm I2MC/université Paul Sabatier Toulouse III, Toulouse, France, MetaboHUB-ANR-11-INBS-0010

(b) IRSD, Université de Toulouse, INSERM, INRA, INP-ENVT, Université de Toulouse 3 Paul Sabatier, 31024 Toulouse, France.

(c) Institut des Biomolecules Max Mousseron, IBMM, UMR CNRS 5247, Université Montpellier I, Université Montpellier II, Faculte de Pharmacie, Montpellier, France

***Introduction***

An irritable bowel syndrome is the most common gastrointestinal disorders and is characterized by visceral pain. An alteration of the interactions between the microbiota, the colon and the nervous system has been described. Due to the lack of a clear gut microbiota dysbiosis profile and a functional redundancy of bacteria within the microbiota, our main goal is to identify the bacterial compounds involved in pain regulation.

***Technological and methodological innovation, results and impact***

In a previous study we demonstrated that a probiotic bacteria, Escherichia coli Nissle 1917, produced analgesic lipopeptides related to GABA1. The aim of our current study is to identify lipopeptides from the gut microbiota and not only from a single bacteria using an unknown-known approach by LCHRMS. First, we developed a lipopeptide-specific extraction method using synthesized lipopeptide standards. Extraction of the standards with or without mouse colonic tissue as a matrix revealed that the method previously described to extract endocannabinoids2 by solid phase extraction with addition of heptane lavage and ethyl acetate liquid/liquid extraction possessed the best yield with a minimal matrix effect. Extracts were analyzed on a LC-QTOF Xevo G2XS system (Waters) using positive- and negative-ionization mode. The mass accuracy and the study of the fragmentation spectra will allow us to identify new families of lipopeptides. We will present in details our experimental strategy, the different soft used, their benefits and limits.

***References***

1-Teresa Pérez-Berezo, et al. (2017). Identification of an analgesic lipopeptide produced by the probiotic Escherichia coli strain Nissle 1917. Nature communication8:1314

2- Aida Habib, et al. (2018) Inhibition of monoacylglycerol lipase, an anti-inflammatory and antifibrogenic strategy in the liver. Gut 68:522-532
**Poster 161: P161 Novel UHPLC-MS method for detailed analysis of lipid species using a scheduled MS/MS acquisition approach for improved metabolite annotation**

Lukáš NAJDEKR<fnref n="1" />,<fnref n="2" />, Amelia JENKINS<fnref n="1" />, Warwick B. DUNN<fnref n="1" />,<fnref n="2" />,<fnref n="3" />

**Introduction**

Lipids are a vast group of biologically important molecules, which are structurally very similar within its classes. Despite the demand for fast UHPLC assays, long separation times decrease ion suppression occurring during the ionisation process, thus increasing sensitivity and specificity of the analytical assay. This approach allows the discovery of new molecules normally masked or eliminated by ion suppression and provides a greater number of MS/MS mass spectra for lipid annotation.

**Technological and methodological innovation**

We developed a new UHPLC reversed-phase assay utilizing C30 stationary resins for the analysis of lipids present in biofluids and tissues. To maximise the number of compounds with MS/MS data we introduced a ‘Scheduled MS/MS acquisition approach’. This utilized several m/z windows spread over the chromatogram. As a comparison, a 15-minute reversed-phase C18 assay was applied with multiple biofluids and mammalian liver samples. Data were processed using Compound Discoverer 3.1 and LipidSearch 4.2.

**Results and impact**

A 30-minute C30 assay showed a 2.4x increase in the number of compounds detected compared to the 15-minute C18 assay. Using a single MS/MS file 15,000 compounds were detected and 1100 compounds were annotated applying LipidSearch on average for 30 min C30 assay. Using this novel assay will maximize the amount of data gathered from a single injection analysis and reduces the time required to collect these data compared to the commonly applied multiple injections with unique precursor windows [1].

**References**

[1] Mullard et al. 2015. Metabolomics. 11:1068–1080

<footnote n="1">¹ School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom</footnote>

<footnote n="2">² Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom</footnote>

<footnote n="3">³ Institute of Metabolism and Systems Research, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom</footnote>
**Poster 162: P162 Ammonium fluoride as suitable additive for HILIC-based LC-HRMS**
**metabolomics**

Luca NARDUZZI<fnref n="1" />; Anne-Lise ROYER<fnref n="1" />; Emanuelle BICHON<fnref n="1" />; Yann GUITTON<fnref n="1" />; Bruno LE BIZEC<fnref n="1" />; Corinne BUISSON<fnref n="2" />; Gaud DERVILLY<fnref n="1" />.

**Introduction**

The use of Hydrophilic Interaction LIquid Chromatography (HILIC) in metabolomics still does not reach the level of reliability of reverse phase (RP) chromatography. One of the main limitation is compound ionization, due to the limited ionization properties of the common additives used in this chromatography (ammonium formiate/acetate). Further additives are reported in literature to improve compound ionization in both RP [1] and HILIC [2, 3], for example, ammonium fluoride (AF).

**Technological and methodological innovation**

In this work, we tested the use of AF as additive for HILIC chromatography in a metabolomics framework. A concentration of 2 mM of AF was added in both HILIC mobile phases (ACN and H2O); its performance has been evaluated performing multiple comparative tests [4] versus a well-established ammonium acetate HILIC method. We, then, used the AF method in two real-case metabolomics experiments (urine and blood), to verify also the repeatability and the robustness of the approach.

**Results and impact**

AF showed sharp ionization and signal-to-noise increase in analytical standards' injections. Peak shape and repeatability improved in all tested conditions. The HILIC AF metabolomics experiment resulted in more discriminant performances than their RP counterparts [5], concluding to its relevance for urine/serum applications. Using stronger additives (like AF) improves the performance and applicability of HILIC's methods in metabolomics for extended metabolome coverage.

**References**

Yanes et al. 2011 *Anal Chem.* 83, 2152-2161.

Pesek et al. 2015 *Journal of chromatography A.* 1401, 69-74.

Spalding et al. 2018 *Journal of Proteome Research.* Just accepted, 2-37.

Pezzatti et al. 2018 *Journal of Chromatography A.* 1592, 47-54.

Narduzzi et al. *SUBMITTED*

<footnote n="1">¹ Laboratoire d'Etude des Résidus et Contaminants dans les Aliments (LABERCA), Oniris, INRA,
Nantes F-44307, France</footnote>

<footnote n="2">² Département des analyses, Agence Française de Lutte contre le Dopage (AFLD), ChâtenayMalabry, France</footnote>
**Poster 163: P163 Metabolomics profiles of Annona species cultivated in Egypt by using bioassay-guided fractionation process as antiproliferative agent.**

Mona A. Mohammed¹,², Piotr Kachlicki², Anna Piasecka²,³, Nahla Elzefzafy⁴

¹Medicinal and Aromatic Plants Research Department, pharmaceutical and Drugs industries Division, National Research Centre, Dokki, Giza, Egypt

²Institute of Plant Genetics Polish Academy of Sciences, Poznan, Poland

³Institute of Bioorganic Chemistry Polish Academy of Sciences, Poznan, Poland

⁴Cancer Biology Department, National Cancer Institute Cairo University, Cairo, Egypt

**Introduction**

Tropical and subtropical trees of *Annona* sp. have constituents of high medicinal value for pharmacological research and drug development and show many characteristic features such as antitumor, antioxidant and antimicrobial activities. Metabolomics was employed to functionally characterize natural products to distinguish differences between varieties[1]. Natural products are therefore encoded to be bioactive and of high interest in the drug discovery field[2].

**Technological and methodological innovation**

The present study was carried out on *Annona* tree species collected in Giza governorate, Egypt: *A. atemoya*; *A. glabra*; *A. muricata*; *A. squamosa* and *A. Abdel razek*. Screening of *Annona* sps. samples of was determined by MTT assay on five cancer cell lines (MCF-7, HepG2, HCT, Caco, and T47D) which revealed a varied potency (IC₅₀) amongst them [1,3]. Then, further assays such as cell cycle analysis were performed to investigate the anti-cancer effect. Metabolomic analyses were performed using LC-MS/MS systems[4].

**Results and impact**

Our study was aimed to assess the inter-relationships among six *Annona* species by using 6 SCoT and 6 ISSRs primers were taken for DNA fingerprinting were polymorphic having 45.16 and 35.29 % polymorphism, respectively. GC-MS-based plant metabolomics was employed to compare 78 differential chemical volatile oil profiles of six *Annona* sps and metabolomics bioassay-guided fractionation process by structural analysis via HPLC-ESI-MSn, UPLC-HESI-MS/MS as antiproliferative activities of five cell lines.

**Acknowledgment**

This work is funded by STDF project No. 25249 and Institute of Plant Genetics PAS Poznan under the cooperation with STDF program

**References**

[1] Jacobo-Herrera N. et al. 2019. Frontiers in Pharmacology.10: 783.

[2] Feng J. et al. 2018. YEAR.Frontiers in Endocrinology.9:678.

[3] Al-ghazzawi. A. M. 2019. BMC Chemistry. 13: 2-6.

[4] Wilmes P. et al. 2010. Observation. 1 and 1-5.
# Poster 164: P164 Targeting Esterified Oxylipins – Optimized Sample Preparation for LC-MS Analysis

Elisabeth KOCH; Annika I. OSTERMANN; Nils Helge SCHEBB

Chair of Food Chemistry, Faculty of Mathematics and Natural Sciences, University of Wuppertal, Wuppertal, Germany

## Introduction

Several eicosanoids and other oxylipins are potent lipid mediators and are believed to act predominantly in their free, i.e. non-esterified, form. However, a major portion of oxylipins is found to be bound in lipids, e.g. phospholipids. Only little is known about the biological activity of these esterified oxylipins. To understand their role in health and diseases wellcharacterized, reliable and reproducible sample preparation procedures for their quantitative determination are needed.

## Technological and methodological innovation

Esterified oxylipins are commonly quantified as a sum of free and bound oxylipins by means of liquid chromatography-mass spectrometry, however, current sample preparation procedures differ considerably and optimization data are missing. We present a detailed procedure for quantification of total oxylipins in biological samples, comprising extraction of lipids and removal of proteins, base hydrolysis to saponify lipids and solid phase extraction using a C8/anion exchange mixed mode cartridge [1].

## Results and impact

It is highlighted that each sample preparation step has a direct impact on the apparent oxylipin concentration and the optimization of each step is crucial to ensure reproducibility and reliability. Moreover, special attention has to be paid to artificial formation of epoxy fatty acids through autoxidative processes. Based on the presented methodology the biological role of esterified oxylipins can be reliable investigated and could pave the route for their use as biomarkers for diseases.

## References

[1] Ostermann and Koch et al. 2019. Prostag Oth Lipid M. DOI: 10.1016/j.prostaglandins.2019.106384
# Poster 165: P165 Stability of total oxylipins – influence of plasma generation and long-term storage

Malwina MAINKA<fnref n="1" />, Elisabeth KOCH<fnref n="1" />, Céline DALLE<fnref n="2" />, Justine BERTRAND-MICHEL³, Cécile GLADINE<fnref n="2" />, Nils Helge SCHEBB<fnref n="1" />

## Introduction

Eicosanoids and other oxylipins have raised strong interest in clinical studies regarding their potential use as biomarkers in health and disease [1]. The modulation of the oxylipin profile is commonly investigated in response to pharmaceutical or dietary intervention. However, the outcome of such clinical results can be influenced by (unsuitable) sample handling, e.g. sample generation, storage and sample preparation, leading to artificial formation or degradation of oxylipins.

## Technological and methodological innovation

We employed a comprehensive liquid chromatography-tandem mass spectrometry (LC-MS/MS) method covering over 160 analytes [2,3] to investigate the effects of sample generation and storage on the pattern of total (free + esterified) plasma oxylipins [4]. We examined the impact of different storage temperatures and times which are present in routine clinical practice on the total oxylipin levels in plasma and assessed the long-term stability of total oxylipins at -80°C during a period of 15 months.

## Results and impact

We show that the levels of total oxylipins are stable during the transitory stage of plasma generation and only long delays increase the concentrations. The storage of plasma at -80°C for 15 months merely increased oxylipins formed autoxidatively. Conclusively, total oxylipins are robust during plasma generation and long-term storage allowing the generation of biologically meaningful oxylipin patterns.

## References

Gladine et al. 2019. Free Radical Bio Med. 144, 72-89

Rund et al. 2018. Anal Chim Acta. 1037, 63-74

Kutzner et al. 2019. Front Pharmacol. 10, 169

Ostermann et al. 2019. Prostag Oth Lipid M. DOI: 10.1016/j.prostaglandins.2019.106384

<footnote n="1">¹ Chair of Food Chemistry, Faculty of Mathematics and Natural Sciences, University of Wuppertal, Wuppertal, Germany</footnote>

<footnote n="2">² Université Clermont Auvergne, INRA, UNH, Unité de Nutrition Humaine, CRNH Auvergne, Clermont-Ferrand, France
MetaToul-Lipidomic Facility, MetaboHUB, Inserm/UPS UMR 1048 - I2MC, Institut des Maladies Métaboliques et Cardiovasculaires, Toulouse, France</footnote>
**Poster 166: P166 Understand the metabolic crosstalk in photosymbiosis**

Charlotte LeKieffre¹; Cyrille Botté²; Yoshiki Yamaryo-Botté², Juliette Jouhet³, Valérie Gros³, Benoît Gallet⁴, Fabien Chevalier¹, Johan Decelle¹

¹ Cell & Plant Physiology Laboratory, University of Grenoble Alpes, CNRS UMR 5168, INRA, CEA, Grenoble, France

² ApicoLipid Team, Institute for Advanced Biosciences, CNRS UMR5309, Université Grenoble Alpes, INSERM U1209, Grenoble, France

³ Cell & Plant Physiology Laboratory, University of Grenoble Alpes, CNRS UMR 5168, INRA, CEA, IRTSV, Grenoble, France

⁴ Institut de Biologie Structurale, University of Grenoble Alpes, CNRS, CEA, Grenoble, France

**Introduction**

Symbiosis between single-cell heterotrophic hosts and microalgae is a widespread and ecologically important lifestyle in the oceanic plankton 1,2. Yet, the functioning of this interaction, specifically metabolite exchanges between the photosynthetic symbionts and their host, remains largely unexplored; mainly because of the technical challenges inherent to the study of these microorganisms. Our main objective is to elucidate the metabolic services provided by the symbionts and highlight the metabolic controls exerted by the host.

**Technological and methodological innovation**

We propose an approach involving the use of stable isotopes coupled with metabolomics (fluxomics) to identify the photosynthesates produced by microalgae, in their free-living stage and in symbiosis. Combining these data with subcellular imaging is crucial for deciphering the metabolic crosstalk between partners. Thus, we chose to couple fluxomics analysis with nanoscale isotope imaging (NanoSIMS) to visualize and quantify the flux of 13C-labeled carbon at the subcellular scale between the host and microalgal cells.

**Results and impact**

Two symbiotic models involving two different types of symbionts are presented here: the freshwater Paramecium and the marine radiolarians, respectively. First results suggest both active 13C-metabolite transfer from the photosynthetic symbionts to the host, but also host de novo synthesis based on these transferred C-compounds. These new data will be of major interest as the knowledge derived from these model organisms can be applied to better understand other associations found in diverse environments.

**References**

Decelle et al. 2015. Marine Protists. Springer, Tokyo. 465-500.

Novack and Melkonian. 2010, Phil. Trans. R. Soc. B. 365, 699-712.
**Poster 167: P167 Molecular networks as a metabolomic tool to link traditional uses to biological activities and potential valuation of Polynesian plants**

Kristelle HUGHES<fnref n="1" />; Raimana HO<fnref n="1" />; Jean-Francois BUTAUD<fnref n="2" />, Stéphane GREFF<fnref n="3" />, Gaëtan HERBETTE<fnref n="4" />, Edwige RANOUILLE<fnref n="5" />, Edith FILAIRE<fnref n="5" />,<fnref n="6" />, Jean-Yves BERTHON<fnref n="5" />, and Phila RAHARIVELOMANANA<fnref n="1" />

**Introduction**

Cosmetopoeia regards the traditional use of plants for body care [1]. In French Polynesia, plant-based preparations like monoi are used for hair and skin care [2] Six extracts of differing polarity from plants Bidens pilosa L., Calophyllum inophyllum L., and Fagraea berteroana A. Gray ex Benth. were chosen for having interesting cultural uses and in vitro biological activities [3]. The extracts chemical composition was studied by UHPLC-ESI-HRMS to find correlations with observed bioactivities.

**Technological and methodological innovation**

The combined ethnobotanical, biological, cosmetic and metabolomic data of this study enables a dual analysis of the molecular network obtained. Firstly, by tentatively matching regions of the network to common bioactivities of the phytoextracts, in vitro and in cellulo. Secondly, by comparing the mass spectra of known and active compounds from B. pilosa, with that of a less studied plant species, F. berteroana to enrich its known phytochemistry.

**Results and impact**

Preliminary results showed a hundred metabolites common to all three species, such as flavonoids, as well as compounds known for possessing cosmetic activities of interest to this study. The former could partially explain the extracts in vitro anti-inflammatory and antioxidant activities.

Thus, this metabolomic data gives further insight into the mode of action of the phytoextracts on cellular targets, justifying their traditional Polynesian use and stating hopeful future cosmetic valuation.

**References**

Ansel et al. 2016. Comptes Rendus Chimie. 19, pp 1035-1048.

Jost et al. 2016. Journal of Ethnobiology and Ethnomedicine. 12.

Hughes et al. 2019. Journal of Ethnopharmacology. 245.

<footnote n="1">¹ EIO, UMR 241, University of French Polynesia, BP 6570, 98702 Faa'a, Tahiti, French Polynesia</footnote>

<footnote n="2">² Consultant in forestry and Polynesian botany, BP 52832, 98716 Pirae, Tahiti, French Polynesia</footnote>

<footnote n="3">³ Institut Méditerranéen de Biodiversité et d'Ecologie Marine et Continentale (IMBE), UMR 7263 CNRS, IRD, Aix Marseille Université, Avignon Université, Station Marine d'Endoume, rue de la Batterie des Lions, 13007 Marseille, France</footnote>

<footnote n="4">⁴ Aix Marseille Université, CNRS, Centrale Marseille, FSCM, Spectropole, Service 511, Campus Saint-Jérôme, 13397 Marseille, France</footnote>

<footnote n="5">⁵ Greentech SA, Biopôle Clermont-Limagne, 63360 Saint-Beauzire, France</footnote>

<footnote n="6">⁶ Université Clermont Auvergne, UMR 1019 INRA-UcA, UNH (Human Nutrition Unity), ECREIN Team, 63000 Clermont-Ferrand, France</footnote>
# Poster 168: P168 A New Tool in Metabolomics: SWATH® Acquisition Analysis for Global Profiling and Quantitation

Joerg SCHLOTTERBECK<fnref n="1" />, Marialuce MALDINI<fnref n="1" />, Zuzana DEMIANOVA<fnref n="2" />, Cyrus PAPAN<fnref n="1" />, Joerg DOJAHN<fnref n="1" />
and Baljit K. UBHI<fnref n="1" />

## Introduction

Data independent acquisition (DIA) workflows are well adopted in quantitative discovery proteomics, but still not commonly used in discovery metabolomics. Data dependent acquisition (DDA) techniques are heavily employed in the field of metabolomics and workflows on mass spectrometers have been adapted so that as much data as possible can be captured. Researchers were limited by the speed of their QTOF mass spectrometers meaning a multiple injection workflow. Also, the stochastic nature of data dependent workflows often means MSMS of low abundant metabolites are often missed. Here, it is described how DIA enables the identification of a higher number of metabolites for untargeted metabolomics workflows compared to traditional DDA approaches thus enabling a broader profile of the metabolome.

## Technological and methodological innovation

Urine and plasma were processed according to standard extraction protocols. Urine was diluted with water at a ratio of 1:4 (v/v) and centrifuged for prior analysis, whilst plasma was extracted 1:4 (v/v) with ice-cold methanol allowing for protein precipitation. Separation was performed on reverse phase chromatography.

DDA and DIA specific settings were chosen and evaluated. The data were acquired on a QqTOF mass analyzer. For the DDA acquisition, we selected the top 5, 10, 15, 20 and 25 precursor ions for MSMS. For DIA, we applied 15, 20 and 30 mass windows with either fixed window (fw) or variable window (vw) widths. Results were evaluated by the highest number of identifications and coverage of metabolites in plasma and urine extracts.

## Results and impact

At the DDA level, the data demonstrate a significant improvement of metabolite coverage at the MSMS level when comparing the top5 to the top25 DDA method. We show over 100% increase of metabolite coverage in plasma extracts by increasing the number of selected precursor ions for DDA acquisition from top5 to top25. This result highlights the capability of the QqTOF mass analyzer for fast MSMS acquisition, which allows for the fragmentation of a large number of precursors in a single DDA cycle, leading to a larger number of metabolites identified.

In the second part of this study, we evaluated the DIA strategy with various fixed (fw) and variable window (vw) sizes with similar cycle time in a plasma extract. Increasing the number of fixed windows resulted in ~30% gain in metabolite coverage. Using the variable window method resulted in a ~70% gain in metabolite coverage.

We finally applied these experimental approaches to common matrices used in metabolomics studies, namely urine and extracted plasma. We show that a DIA approach applying 20 variable windows can identify up to 55% more metabolites than a traditional top20 DDA acquisition (in a urine extract). More confident MSMS based identifications lead to higher quantifiable metabolites in a metabolite expression experiment, which at the end allows better understanding of the biology. When comparing the performance in extracted plasma it can be observed that applying a DIA approach with 20 variable windows allows significant gains in metabolite coverage (around 55%) versus the top20 DDA acquisition, similar gains as seen in the urine extract.

Data Independent Acquisition Improves Metabolite Coverage over Traditional Data Dependent Techniques for Untargeted Metabolomics

<footnote n="1">¹ SCIEX, Germany</footnote>

<footnote n="2">² SCIEX, USA</footnote>
**Poster 169: P169 How to automate boring lipidomic extraction?**

Julia SOULLIER¹, Aurélie BATUT¹, Anthony TOURNADRE¹, Pauline LE FAOUDER¹, Justine BERTRAND MICHEL¹

¹I2MC, Inserm, MetaToul-Lipidomic Core Facility, MetaboHUB, Toulouse, France

**Introduction**

Lipids are ubiquitous biomolecules essential to all life, found in every cellular type, ranging from the human body and vegetal organisms, down to bacteria. They have many different functions in cell structuration, energy storage and signalling. Mass spectrometry (MS) coupled with liquid chromatography or gas chromatography is mainly used for global and specific analysis of lipids. But before their analysis, there is an important and time consuming step of sample preparation including liquid-liquid extraction (LLE) and solid phase extraction (SPE).

**Technological and methodological innovation**

To circumvent this point, a TECAN robot has been acquired to automate the sample preparation. Due to the specificity of lipid extraction, the robot needs a lot of optimisation. The optimisation was done on three major points: water contamination, accuracy and repeatability of dispense volume and the loss of lipids. Two systems have been set up on the robot and different parameters have been tested with these systems. In order to determine which, one was more appropriate for our uses, depending on the previous key points.

**Results and impact**

This presentation will show part of adaptation we had to perform to validate fatty acid, neutral lipid and phospholipid profiling. Lipidomic's results obtained with a complete automated sample preparation, including LLE steps, will be presented for liver and plasma sample. This process can be applied on large cohort of clinical samples.
**Poster 170: P170 Development of lipidomic profiling by SFC-HRMS**

Pauline Le Faouder¹, Anthony Tournadre¹, Jean-François Martin², Marion Regnier³, Hervé Guillou³, Yann Guitton⁴, Justine Bertrand-Michel¹

1. MetaToul-Lipidomic core facility, MetaboHUB, Inserm I2MC, Toulouse France

2. MetaToul-Axiom, MetaboHUB, INRA Toxalim, Toulouse France

3. UMR 1331 TOXALIM INRA - Equipe de Toxicologie Intégrative & Métabolisme 4. LABERCA, ONIRIS, Nantes

**Introduction**

Lipids are essential cellular constituents that have many critical roles in physiological functions. They are involved in energy storage, cell signaling as second messengers, and are major constituents of cell membranes including lipid rafts. Their crucial role is highlighted by their involvement in a large number of heterogeneous diseases such as cancer, diabetes, neurological disorders and inherited metabolic diseases2,3.

**Technological and methodological innovation**

Due to the high structural diversity of lipid, a complete lipidomic profiling of biological matrices remains a challenge. In this context, we develop an untargeted lipidomic approach by using supercritical fluid chromatography high resolution mass spectrometry. The optimization of the separation and the detection of lipid species were performed on pure standards and then on liver lipid extract from mice exposed to a control or a high fat diet.

**Results and impact**

These analyses allowed the building of a homemade lipid data bank. An automatic process was then developed using MSDial software to produce the relative quantification of lipids species belonging to the 18 class of lipids. The optimization of this method will be present with the first results obtained on liver disease model and the limit of the use of MSDial will be exposed. First results obtained reveal the high efficiency of this method for the profiling of more than 600 lipids.

**References**

Simons, K., & Toomre, D. (2000). Nature Reviews Molecular Cell Biology, 1(1), 1-39.

Wenk, M. (2005). Nature Reviews Drug Discovery, 4(9), 594-610.

Lamari, F., (2013). Journal of Inherited Metabolic Disease, 36(3), 411-425.
**Poster 171: P171 Parsimonious ¹³C Metabolic Flux Analysis**

Carles Foguet¹,², Anusha Jayaraman¹, Silvia Marin¹,², Vitaly A. Selivanov¹,², Pablo Moreno¹, Ramon Messeguer¹, Pedro de Atauri¹,³, Marta Cascante¹,²

¹Department of Biochemistry and Molecular Biomedicine & Institute of Biomedicine of University of Barcelona, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain

²Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD) and Metabolomics node at Spanish National Bioinformatics Institute (INB-ISCIII-ES-ELIXIR), Instituto de Salud Carlos III (ISCIII), Madrid, Spain³

European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, United Kingdom
⁴LEITAT Technological Center, Health & Biomedicine Unit, Barcelona, Spain

**Introduction:**

When a biological system is incubated with a ¹⁸C-labeled substrate, ¹⁸C propagates to metabolites throughout the metabolic network in a flux and pathway-dependent manner. ¹⁸C Metabolic Flux Analysis (¹⁸C MFA) integrates measurements of ¹⁸C enrichment in metabolites to identify the flux distributions consistent with the measured ¹⁸C propagation. However, there is often a range of flux values that can lead to the observed ¹⁸C distribution. Hence, ¹⁸C MFA might be unable to reduce the solution space towards a unique solution either in large metabolic networks or when small sets of measurements are integrated.

**Technological and methodological innovation:**

We developed parsimonious ¹⁸C MFA (p¹CMFA), an approach that runs a secondary optimization in the ¹⁸C MFA solution space to identify the solution that minimizes the total reaction flux. Furthermore, flux minimization can be weighted by gene expression measurements¹.

**Results and impact:**

As proof of concept, we demonstrated the potential of p¹CMFA by estimating intracellular flux distributions from ¹C-resolved metabolomics and transcriptomics data in a Human Umbilical Vein Endothelial Cells (HUVECs). p¹CMFA allows for the first time a seamless integration of ¹C data with transcriptomics data. Even more, p¹CMFA potentially paves the way for integrating ¹C resolved metabolomics with multiple layers of omics to compute genome-scale flux maps.

**References:**

1. Balcells, C. et al. Tracing metabolic fluxes using mass spectrometry: Stable isotope-resolved metabolomics in health and disease. *TrAC Trends Anal. Chem.* (2019). doi:10.1016/j.trac.2018.12.025

2. Niedenführ, S., Wiechert, W. & Nöh, K. How to measure metabolic fluxes: A taxonomic guide for 13C fluxomics. *Current Opinion in Biotechnology* 34, 82–90 (2015).

3. Foguet, C. et al. p13CMFA: Parsimonious 13C metabolic flux analysis. *PLoS Comput. Biol.* 15, e1007310 (2019).