**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

*AWARD WINNERS

BIOMEDICAL

P-250 Longitudinal metabolite fluctuations in urine reveal individual variations and responses to rhinovirus challenge (BIOFLUC study)

PRESENTING AUTHOR: Romanas Chaleckis, Gunma University Initiative for Advanced Research (GIAR), Japan

CO-AUTHORS: Anirban Sinha, Isabel Meister, Pei Zhang, Craig Wheelock, Rene Lutter, Peter J. Sterk

Asthma is one of the major chronic noncommunicable diseases affecting over 300 million people worldwide. Exacerbations are the major burden in asthma management which are primarily triggered by rhinovirus exposures. Temporal metabolite fluctuations in biofluids could be used to monitor and predict the disease exacerbations. However, little is known on the individual variation of the metabolome, especially on the scale of weeks-to-months which is important to monitor health trajectories. Here we present the temporal dynamics of urinary metabolites from BIOFLUC study (Netherlands trial register: NL5317) in healthy and asthmatic subjects before and after a rhinovirus challenge. This a prospective longitudinal follow-up study in 12 healthy and 12 asthmatics over a period of 3 months with an experimental rhinovirus intervention after 2 months. Multiple samples were collected from different sources 3 times a week amounting to more than 35 samples per subject. Urine LC-MS metabolomic profiling of polar metabolites on zic-HILIC column using all ion fragmentation data acquisition was performed. Data was processed with MS-DIAL software and metabolite identities confirmed by accurate mass, retention time and MS spectra. Metabolite clustering by the CVs (coefficients of correlation) revealed several groups, with amino acid metabolites being less and food/drug metabolites being most variable. Individual responses were observed after rhinovirus challenge with spikes of cytosine levels in many, but not all study participants. Urinary metabolomics provides an accessible avenue to characterize individual baseline urine metabolites in healthy and asthmatic subjects thereby helping to identify compounds associated with disease presentation.

P-251 Urinary metabolomics identifies molecular signatures associated with bronchopulmonary dysplasia (BPD) and birth-term

PRESENTING AUTHOR: Craig Wheelock, Karolinska Institute, Sweden

CO-AUTHORS: Isabel Meister, Romanas Chaleckis, Pei Zhang, Takashi Izumi, Marika Ström, Petra Um-Bergström, Eva Berggren Broström, Erik Melén, Magnus Sköld, Åsa M. Wheelock

Chronic obstructive pulmonary disease (COPD) is a rising global health problem, currently affecting >10% of the global population. While smoking is the major risk factor for developing COPD, 20% of COPD patients have never smoked. Prematurely born, particularly those who developed bronchopulmonary dysplasia (BPD) in the neonatal period, are a growing group of subjects at-risk of developing early-onset COPD. BPD affects 10-30% of premature children, corresponding to 1% of all newborns. We present here the urine metabolomics of young adults from the LUNAPRE cohort (n=96; www.clinicaltrials.gov/ct2/show/NCT02923648), consisting of 4 non-smoking groups, age 18-23: i) prematurely born (<32 weeks of gestation) BPD survivors (n=26); ii) healthy born preterm (<32 weeks, n=23), iii) healthy born at term (>37 weeks, n=24), and iv) mild asthmatics born at term (>37 weeks, n=23). We performed LC-HRMS-based urinary metabolomics in combination with targeted quantification of the urinary eicosanoid profiles. Metabolomics identified 68 AMRT-confirmed metabolites, of which 39 were also MS/MS confirmed. We observed a 2.4-fold increase in carnitine levels and a 0.6-fold decrease in acetyl-glucosamine levels in the pre-term BPD survivors compared to healthy pre-term group. Multivariate analysis found that urinary eicosanoid profiles differed between the BPD survivor group relative to both the healthy pre-term group (p=0.007) and the asthma group (p=0.02). The separation with both groups was primarily driven by downregulation of the thromboxane and prostaglandin D2 pathways. These preliminary analyses suggest that molecular signatures associated with BPD and birth-term persist into adulthood and may be useful for understanding this unique sub-group of COPD patients.

P-252 High power vaping modifies cardiorespiratory parameters and urine metabolome: a randomized crossover trial in heavy ecigarette users

PRESENTING AUTHOR: Vanessa Tagliatti, University of Mons, Belgium

CO-AUTHORS: Martin Chaumont

The use of electronic cigarettes has increased since its marketing. However, health effects remain largely unknown due to its newness. In the present study, effect of propylene-glycol and glycerol, e-cigarette constituents that facilitate liquid vaporization and nicotine transport, is evaluated in short-term cessation of e-cigarette vaping in regular-users. Subjects were enrolled in a randomized investigator-blinded crossover-three-period study for five days before the experimental session (nicotine e-cigarettes: nicotine-session; nicotine-free vaping: nicotine-free-session; complete cessation of e-cigarette vaping: stop-session). Metabolomic analysis, by proton nuclear magnetic resonance, was performed on urine samples and baseline clinical/biological cardiorespiratory parameters were assessed at the beginning of each experimental session. In comparison to nicotine- and nicotine-free-session, stop-session was characterized by a specific urine metabolomic signature (increase in hippurate and decrease in hydroxyisovalerate). This modified baseline urine metabolome sustained by an increase of serum CC16 concentration suggesting an improvement in lung inflammatory profile.
<figure><img src="image_73.png" /></figure>

**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

*AWARD WINNERS

BIOMEDICAL

P-253

1H NMR metabolomics of serum and EBC for understanding the pathophysiology of COPD associated PH

PRESENTING AUTHOR: Priyanka Choudhury, School of Medical Science and Technology, Indian Institute of Technology Kharagpur, India

CO-AUTHORS: Nilanjana Ghosh, Mamata Joshi, Parthasarathi Bhattacharyya, Sushmita Roy Chowdhury, Koel Chaudhury

Group III pulmonary hypertension (PH), considered to be a delayed complication of hypoxic lung diseases has a major burden of chronic obstructive pulmonary disease (COPD). COPD associated PH (COPD-PH) often gets overshadowed by the symptoms of COPD and is associated with shorter survival and worse clinical outcomes. Understanding of the etiopathogenic mechanisms responsible for PH development in COPD remains incomplete. In this study, we hypothesize that 1H nuclear magnetic resonance (NMR) based metabolomics will provide an insight into the pathophysiology of COPD-PH and will also be able to differentiate it from COPD alone at a metabolic level. Two biofluids serum and exhaled breath condensate (EBC) are explored in the present study. Paired serum and EBC samples were collected from patients with pure COPD (n=47), COPD-PH (n=31) and healthy controls (n=39). NMR spectra of the samples were acquired using 800 MHz BrukerAvance III spectrometer equipped with a cryoprobe and the data subjected to univariate and multivariate analysis. On comparing COPD-PH with COPD and controls, distinct metabolic differentiation was observed between the groups. The OPLS-DA models generated for COPD-PH vs. COPD showed good R2 and Q2 values [(a) Serum: R2Y (0.902) and Q2 (0.755) (b) EBC: R2Y (0.901) and Q2 (0.715)] indicating the robustness of the model. The identified metabolites were found to be majorly associated with glycolysis pathway, amino acid and lipid metabolism. The distinct metabolic signatures suggest that the two study groups are distinguishable from each other and also give us a preliminary idea about the pathophysiology of the disease.

P-254

Lipidomic Quantitation of Respiratory Disease: A Rapid and Comprehensive HILIC-Based Targeted Approach

PRESENTING AUTHOR: Giorgis Isaac, Waters Corporation, United States

CO-AUTHORS: Nyasha Munjoma, Lee A. Gethings, Robert S. Plumb

Respiratory linked conditions associated with chronic obstructive pulmonary disease (COPD), asthma, and infection are increasing. The analyses of plasma samples from three biological states of varying phenotype (control, COPD and asthma patients) were conducted. Sample extraction was performed using a simple protein precipitation with a pre-cooled isopropanol. Lipid analysis was performed using a fast (<8min), comprehensive and high-throughput targeted method which is based on UPLC-HILIC lipid class separation followed by MRM quantitation of individual lipid species. It is integrated workflow for accurate and robust measurement of a carefully selected more than 500 lipid species. Data were processed using TargetLynx and Skyline. The biological samples were randomised and two technical replicates per sample were acquired. Statistical analysis of the data revealed clear separation between the various cohorts. Unsupervised PCA resulted in the separation of healthy controls, COPD and asthma patients. Application of the metadata also revealed significant differences between smoking status, with subsets readily observed within the COPD population. Loadings plot analysis revealed that FFA, LPC, PC and SM lipid classes to be the main contributors to sample type clustering. Additional ANOVA/t-test and hierarchical clustering showed all the lipid classes referenced to be up-regulated except for PC's. A decrease in the level of PC's was observed as significant for subjects associated with smoking. Overall, PCs are a potential marker for oxidative stress (immune activation). Pathway analysis revealed several components related to inflammation, oxidative and immunity processes were identified as significant and associated with signalling, metabolic and regulatory pathways.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

*AWARD WINNERS

NEW FRONTIERS

P-255

Integrating expression data into metabolome-wide GWAS suggests candidate genes modulating metabolite concentration

PRESENTING AUTHOR: Reyhan Sonmez Flitman, University of Lausanne, Switzerland

CO-AUTHORS: Rico Rueedi, Sven Bergmann

Metabolome-wide GWAS (mGWAS) search for associations between metabolites and common genetic variants within large collections of samples. NMR spectral intensities reflect metabolite concentrations, which in targeted NMR are combined to quantify a limited set of metabolites. In order to avoid the often imperfect identification and quantification of metabolites, we designed a different type of mGWAS called untargeted mGWAS, that directly tests metabolome features for association with genetic variants, not discarding any data that may have eluded identification. The effect of a genetic variant on the concentration of a metabolite tends to translate, in an untargeted mGWAS, to associations with all or some of the features corresponding to the pure NMR spectrum of the metabolite. The association profile can therefore allow for identification of the underlying metabolite using a method we call metabomatching (Rueedi et al., PLoS Genetics 2014). Here, we apply metabomatching to associations with gene expression rather than genotypic variation. To this end we used RNAseq profiles of lymphoblastoid cell lines derived from 555 CoLaus subjects for which we had also urine NMR data. Specifically, we investigated the genes whose expression levels showed strong association with metabolome features. We found that ALMS1 gene expression is strongly associated to the concentration of N-Acetyl L-Aspartate (NAA) making ALMS1 the most likely candidate gene for modulating this metabolite. In summary our study provides evidence that the integration of metabolomics with gene expression data can support mQTL analysis, helping to identify the most likely gene involved in the modulation of the metabolite concentration.

P-256

The application of artificial neural networks and deep learning to metabolomics

PRESENTING AUTHOR: Kevin Mendez, Edith Cowan University, Australia

CO-AUTHORS: Stacey Reinke, Leighton Pritchard, David Broadhurst

Metabolomics data are highly complex, both in terms of the number of variables and the high degree of multicollinearity between variables. As such, multivariate machine learning methods that project the data into a smaller linear "latent" space before classification are routinely used, with Partial Least Squares Discriminant Analysis (PLS-DA) being by far the most popular approach. However, it is generally observed that biological processes are nonlinear. As such, it is fair to hypothesise that linear projection techniques may not be optimal. Artificial Neural Networks (ANNs) are a class of nonlinear models introduced into the metabolomics community over 20 years ago, which failed to gain momentum due to computational requirements for optimisation, and the difficulty of interpretation. Here we present a comparison of the standard back-propagation ANN against PLS-DA and other popular machine learning algorithms (RBF-Support Vector Machines, Random Forrest, Logistic Regression) across 8 data sets of various complexity and instrumentation. All data sets were open access, downloaded from public online repositories (Metabolights & Metabolomics Workbench). All models were implemented in the Python 3 scripting language, presented using Jupyter Notebooks, and freely available on GitHub and mybinder.org. Results show that ANNs generally outperform the alternatives, particularly when the applied data sets are large. The ability to interpret ANNs have greatly improved since their first introduction thanks to advances in computer technology that allows the rapid use of methods such as network pruning and bootstrap resampling sensitivity analysis.

P-257

Retip: Increasing compound identification rate in metabolomics with a new Retention Time Prediction software in R

PRESENTING AUTHOR: Paolo Bonini, NGAlab, Spain

CO-AUTHORS: Tobias Kind, Hiroshi Tsugawa, Dinesh Kumar Barupal and Oliver Fiehn

**Background:** Untargeted metabolomics datasets in LC-MS/MS present a large number of unidentified peaks. Usually, less than 10% of all deconvoluted metabolic peak clusters are identified. Using retention times as orthogonal information is important in workflows for compound annotations because each orthogonal parameter increases the confidence level in compound identification. Methods: Five different machine learning algorithms have been employed and integrated into the Retip method: Random Forest, Bayesian Regularized Neural Network, Keras, XGBoost and LightGBM. Retention time prediction models have been developed for the two most common separation principles, reversed phase (RP) and hydrophilic interaction liquid chromatography (HILIC). We utilized two large publicly available dataset for training, the FiehnLab HILIC (n=981) and RIKEN PlaSMA (n=852) retention time databases. Results: For both chromatographic databases the XGBoost method was the most accurate with a root-mean-square error (RMSE) on the testing set of 1.14 min for HILIC and 0.69 min for RP. The Retip R package also significantly reduces the numbers of false positive compound's by 26.5% and increases the correct identification rate by 21%. Retip has been integrated into the mass spectrometry software tools MS-DIAL and MS-FINDER allowing for a complete compound annotation workflow. Retip can be freely downloaded from the CRAN repository as an R package. Conclusion: Predicted retention times increase the confidence for peak annotations in liquid chromatography and subsequently lead to improved biological interpretations in metabolomics.
<figure><img src="image_74.png" /></figure>

**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

*AWARD WINNERS

NEW FRONTIERS

**P-258**
A single high-resolution mass spectrometry platform for targeted and untargeted lipid analysis revealed modification of lipids and discovery of novel lipids in Barley roots response to salt stress

PRESENTING AUTHOR: Thusitha Rupasinghe, Metabolomics Australia, Australia

CO-AUTHORS: Dingyi Yu, Berin A. Boughton, Siria H.A. Natera, Camilla B. Hill, Pablo Tarazona, Ivo Feussner, Ute Roessner

Untargeted and targeted lipidomics are two complementary approaches, which when combined can achieve in-depth and comprehensive lipidome characterisation and quantification. The two approaches are usually performed on two different Mass Spectrometer platforms, triple-quadrupole (QqQ) type MS and high-resolution MS. Here, we developed a robust lipidomics workflow merging both targeted and untargeted approaches on a single liquid chromatography coupled to quadrupole-time of flight system (LC-QqTOF) platform with scheduled parallel reaction monitoring (sPRM). sPRM assays integrate both untargeted profiling from MS1 scan and targeted quantification obtained from MS/MS data. With scheduled algorithm and maximum 100 precursors multiplexed per duty cycle, sPRM assay can achieve a high-throughput targeted monitoring of more than 250 lipid species within a single injection. This workflow enabled the identification and quantification of more than 700 lipid species from 25 lipid classes at the level of fatty acid/long chain base/sterol composition with three injections in a barley root extract. To further demonstrate the workflow, a study on salt stress induced changes in the barley root lipidome was initiated as well as the discovery of novel lipid species in the group of oligohexosylceramides. Results show that 232 targeted compounds and 888 unknown features were found to have significantly responded to salt stress. This emerging targeted and untargeted lipidomics strategy combined in a single workflow provides novel insights into lipidomics and its applications in addressing biological questions.

**P-259**
DIMEdb: A database/web service for metabolite identification in direct infusion mass spectrometry

PRESENTING AUTHOR: Keiron O'Shea, Institute of Biological, Environmental & Rural Sciences (IBERS), Aberystwyth University, United Kingdom

CO-AUTHORS: Divya Kattupalli, Luis AJ Mur, Nigel W Hardy, Biswapriya B Misra, Chuan Lu

Direct infusion mass spectrometry (DIMS) is a widely used platform that is capable of producing a global fingerprint of the metabolome, without prior requirement of a chromatographic step - making it ideal for wide scale high-throughput metabolomics analyses. Metabolite identification is an arduous task that involves the querying of masses against a metabolite database in order to retrieve putative metabolite annotations. Each existing metabolite database differs in a number of aspects including coverage, format, and accessibility - often limiting the user to a rudimentary web interface with no means of programmatically interfacing with the database. Consequently, researchers often manually combine multiple search results for a single experiment in which the exploration of potentially hundreds of masses becomes an incredibly arduous task – and infeasible for many projects. To facilitate unified access to metabolite information we have created the Direct Infusion MEabolite database (DIMEdb), a comprehensive web-based programmatic metabolite database that contains over 80,000 metabolites sourced from a number of renowned metabolite databases of which can be utilised in the analysis and annotation of DIMS data. DIMEdb is freely available at https://dimedb.ibers.aber.ac.uk.

**P-260**
Optimization of Caenorhabditis Elegans Homogenization and Extraction Methods for Non-targeted Metabolomics using Orbitrap and FT-ICR Mass Spectrometry

PRESENTING AUTHOR: Brianna Garcia, University of Georgia, United States

CO-AUTHORS: Goncalo J. Gouveia, Bennett Fox, Franklin E. Leach III, Facundo M. Fernández, Frank Schroeder, I. Jonathan Amster, Arthur S. Edison

Metabolomics commonly uses analytical techniques such as NMR and LC-MS to quantify and identify metabolites related to biological alterations. Metabolome coverage from non-targeted LC-MS studies relies heavily on the pre-analytical protocols used. These protocols impact which metabolites are successfully measured and thus, the biological conclusions drawn. Protocol standardization remains a challenge in the metabolomics community due to the variety of sample types analyzed and workflows used. Previous studies have demonstrated that homogenization and extraction methods can produce large variations in the total number of metabolites detected, precision and yield. To systematically determine the effects on metabolome coverage, artifact production, and experimental variation, different homogenization methods and extraction solvents (i.e. methanol, ethanol, 2:1 cholorform:methanol, and 9:1 ethylacetate:ethanol) have been examined using a mixed-stage C. elegans population. Sample preparation was completed by two individuals in triplicate and ran in each laboratory using an Orbitrap Q-Exactive HF to showcase both the intra-analyst and instrumental variance. This initial factorial design was used to narrow down the parameters that largely contribute to extraction efficiency. Using a Taguchi Design of Experiments method these parameters were further analyzed to determine the pre-analytical sample preparation that minimized artifact production, produced the highest metabolome coverage and the highest reproducibility. An L9-orthogonal array was used where extraction solvent, volume ratio, method of extraction, and reconstitution solvent represented the four factors. Future work includes MS/MS experiments utilizing Orbitrap and FT-ICR mass spectrometers to test the resolving power limits of the Orbitrap, establishing the minimum requirements for FT-ICR analysis of metabolomics samples.
<figure><img src="image_75.png" /></figure>

POSTER SESSIONS 1 AND 2 – Monday and Tuesday – all odd number posters will be on display.

POSTER SESSIONS 3 AND 4 – Wednesday and Thursday – all even number posters will be on display.

*AWARD WINNERS

NEW FRONTIERS

P-261*

A high-throughput method for obtaining microbial exometabolomics data using a 3D printed platform

PRESENTING AUTHOR: Caroline Birer, University of Pittsburgh, United States

CO-AUTHORS: Rosalie K. Chu, Christopher R. Anderton, Erik S. Wright

Microbial interactions are governed by an immense variety of small molecules. To date, our understanding of microbial communication is largely based on a small number of molecules used for quorum sensing. This limitation is partly explained by the low-throughput and high cost of most experimental approaches using mass spectrometry (MS). Here, we engineered a 3D-printed device for eavesdropping on the exometabolome of pairs of microorganisms grown in interconnected environments. Our device can be used to easily co-culture microorganisms with or without additional stimuli (e.g. nutrients, drugs, etc.). Coupled with high-throughput robotics (e.g., Triversa Nanomate robot) and MS, the platform can be used to measure an exometabolome in 4 minutes at a cost of only US$2. We have validated our approach with mixtures of 27 known compounds at decreasing concentrations, where we were able to detect 79% and 17% of known compounds 10 nmol and 10 pmol, respectively. Furthermore, we applied the platform to study co-cultures of 5 soil microbes at different time points after growth. Principle coordinates analysis (PCoA) revealed a high degree of repeatability, a transition of the exometabolome over time, and a clear signal species domination within the exometabolome. After subtracting mass spectrometry features related to media, we were able to pinpoint small molecules excreted by each individual microbe. This approach enables us to process an immense number of samples, unlocking previously insurmountable problems such as decrypting the higher-order principles of inter-cellular communication. Interpreting the language of the microbiome may bring us one step closer to manipulating microorganisms by communicating through small molecules.

P-262

Focused metabolomics based on TMT labeling for improving throughput and quantification

PRESENTING AUTHOR: Yoshiya Oda, The University of Tokyo, Japan

CO-AUTHORS: Suzumi M Tokuoka, Yoshihiro Kita

In metabolomics, the importance is placed on quantification rather than identification. Then, performing quantitative analysis of many hundreds of samples is more important in metabolomics than identifying thousands of molecules in a single experiment, though proteomics often put emphasis on the latter. In quantitative analysis, stable isotope labeled substances are commonly used as internal standards for the target molecules to correct for variations during ionization. However, when there are many targets, it is not practical to prepare such internal standards for all targets. Improving multi-sample processing capacity and quantification in proteomics, isobaric tagging method so called iTRAQ or TMT method have been developed, in which MS/MS spectrum is used for relative quantification, iTRAQ/TMT is capable of relative quantification between the samples without isotope labeled internal standards by constantly adding one of the samples as a control. Despite this excellent method, it has hardly been used in metabolomics. One of the reasons is that the derivatization reaction is limited for the metabolite having a specific functional group such as a primary amine group. Metabolites having a carboxy group is preferred for derivatization, but in order to label the carboxy group, it has to be activated before labeling. Therefore, we investigated various derivatization conditions suitable for metabolomics. While finding some problems which have not been reported in proteomics, we came to apply to human plasma sample analysis. Our approach is not comprehensive metabolomics, but it is more practical method to perform quantitative analysis of hundreds of samples.

P-263

Single-platform metabolomic and proteomic profiling of human liver tissue

PRESENTING AUTHOR: Thierry Schmidlin, Dr. Margarete Fischer-Bosch - Institut für Klinische Pharmakologie, Germany

CO-AUTHORS: Thierry Schmidlin, Kathrin Klein, Matthias Schwab, Thomas E. Mürdter, Ute Hofmann, Mathias Haag

Metabolomic and proteomic profiling of liver tissue represents a powerful approach for the functional characterization of molecular processes underlying drug uptake and metabolism. However, the heterogeneous nature of tissue and the limited availability of biopsies demand for protocols that utilize samples in an economic fashion by simultaneously increasing information yield through recovering metabolites and proteins from a single sample. Here we demonstrate a strategy for the quantitative assessment of metabolites and proteins recovered from the very same liver tissue analyzed on the same MS platform. Samples were sequentially subjected to metabolite extraction and urea-based protein extraction protocols followed by tryptic digest. Metabolites were analyzed after HILIC separation in positive and negative ionization mode whereas peptides were monitored by C18-RP LC-MS/MS. Fragment spectra, acquired by data-dependent MS/MS measurements, enabled the structural assignment and identification of a broad range of metabolite classes and >1000 proteins, respectively. Over 75% of the annotated metabolic features exhibited CVs <25% in both ionization modes across replicates of independently prepared samples. Proteome quantification likewise showed high quantitative reproducibility, evidenced by a median intra-run correlation coefficient of 0.96 across all measurements. The approach allowed us to accurately monitor clinically relevant metabolites and related proteins such as bile acids and cytochrome P450 enzymes (CYPs) involved in their synthesis (e. g. CYP8B1 and CYP27A1). Applied to clinical cohorts the multi-OMICS approach will enable a deeper understanding of the interplay between proteins and metabolites associated with pharmacologically important phenotypes and hepatic diseases including non-alcoholic fatty liver disease.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

*AWARD WINNERS

NEW FRONTIERS

P-264

Continuous in vivo metabolism by NMR

PRESENTING AUTHOR: Michael Judge, University of Georgia, United States

CO-AUTHORS: Yue Wu, Fariba Tayyari, Ayuna Hattori, John Glushka, Takahiro Ito, Jonathan Arnold, Arthur S. Edison

Dense time-series metabolomics data are essential for unraveling the underlying dynamic properties of metabolism. Here we extend high-resolution-magic angle spinning (HR-MAS) to enable continuous in vivo monitoring of metabolism by NMR (CIVM-NMR) and provide analysis tools for these data. First, we reproduced a result in human chronic lymphoid leukemia cells by using isotope-edited CIVM-NMR to rapidly and unambiguously demonstrate unidirectional flux in branched-chain amino acid metabolism. We then collected untargeted CIVM-NMR datasets for Neurospora crassa, a classic multicellular model organism, and uncovered dynamics between central carbon metabolism, amino acid metabolism, energy storage molecules, and lipid and cell wall precursors. As an exploration of real-time perturbation of metabolism, we are also conducting aerobic-to-anaerobic shifts. Virtually no sample preparation is required to yield a dynamic metabolic fingerprint at ~1-min temporal resolution with little noise. CIVM-NMR is simple and readily adapted to different types of cells and microorganisms, offering an experimental complement to kinetic models of metabolism for diverse biological systems.

P-265

Discovery and identification of novel biomarkers for vitamin B6-dependent epilepsy through the combination of Next Generation Metabolic Screening and Infrared Ion Spectroscopy

PRESENTING AUTHOR: Karlien Coene, Radboud UMC Nijmegen, Translational Metabolic Laboratory, Netherlands

CO-AUTHORS: Jonathan Martens, Giel Berden, Rianne E van Outersterp, Udo FH Engelke, Leo AJ Kluijtmans, Marleen CDG Huigen, Siebolt de Boer, Ed van der Heeft, Clara DM van Karnebeek, Ron A Wevers, Jos Oomens

Antiquitin deficiency, also known as vitamin B6-dependent epilepsy, is an inborn error of metabolism affecting the degradation of lysine, which presents with severe epilepsy in newborns. The accumulating metabolite piperidine-6-carboxylate (P6C) complexes with active vitamin B6, causing a secondary deficiency of this co-factor for many enzymatic processes in the human body. Supplementation with large doses of vitamin B6 can overcome this problem in patients and resolve the epilepsy. However, treatment should start as early as possible to prevent irreversible damage to the neonate. Currently, no stable biomarkers in blood are available to include this disease in newborn screening. Using an untargeted metabolomics approach on a UHPLC-QTOF-MS set-up, which we have coined 'Next Generation Metabolic Screening', we have now identified novel biomarkers in plasma for antiquitin deficiency. However, for two of these markers, both with a neutral mass of 185.1052 but different retention times, chemical identity could not be established using the currently available metabolite databases. Through the application of infrared ion spectroscopy (IRIS)-MS, we were able to deduce the chemical structure of these unknown biomarkers, which were predicted to be two diastereomers of 6-(2-oxopropyl)piperidine-2-carboxylic acid. This identification could be confirmed by measurement of synthesized model compounds, which showed a perfect match to IR spectra and NGMS profiles of patient-samples. These novel markers are promising for application in neonatal screening to diagnose antiquitin-deficiency as early as possible. Our study has shown the power of untargeted metabolomics in combination with IRIS-MS to discover and identify novel biomarkers in inborn errors of metabolism.

P-266

CCSPredict: Using a machine learning approach for higher confidence in Lipid identification

PRESENTING AUTHOR: Ulrike Schweiger-Hufnagel, Chemist, Germany

CO-AUTHORS: Sebastian Wehner, Heiko Neuweger, Sven Meyer, Aiko Barsch, Nikolas Kessler, Lucy A. Woods

The use of ion mobility-featured mass spectrometers offers new options for higher confidence in annotations of target molecules. First, with the additional separation dimension compounds co-eluting from LC columns can be separated. The benefit is that a subsequent fragmentation will result in cleaner MS/MS spectra – crucial for any ID in lipidomics or other small molecule workflows. Moreover, ion mobility enables the determination of the collisional cross sections of ions. These values are specific properties for any ion species under given conditions (type of gas, pressure, temperature). Therefore, acquired values can be used for identification if they are compared to in-silico generated data or used in a library-based approach. We present a new tool for the prediction of lipid CCS values. It is fully integrated in MetaboScape 4.0 and is based on a machine learning approach that was extended significantly to cover a wider range of lipid structures. Predicted values can be compared with the ones measured on a Bruker timsTOF Pro instrument. The Trapped Ion Mobility Spectrometry technology enables the exact measurement of CCS values at a very high reproducibility and TIMS resolving power. Both are critical pre-requisites to make full use of the increased confidence by CCSPredict. This workflow helps to assign the structural classes of lipids.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

*AWARD WINNERS

NEW FRONTIERS

P-267

A novel integrative approach combining intelligent imaging acquisition and metabolomics reveals chemical signatures of human colon organoids.

PRESENTING AUTHOR: Josep Rubert, University of Trento. CIBIO - Dept. of Cellular, Computational and Integrative Biology, Italy

CO-AUTHORS: Andrea Lunardi

Colorectal cancer (CRC) is one of the most common cancers in the western world. On top of that, the forecasts show that the global burden of CRC is expected to increase by 60%, to over 2.2 million new cases and 1.1 million deaths by 2030, due to an aging population and western dietary patterns. Research has suggested that dietary patterns, dysbiosis, and microbial metabolites may play a pivotal role in CRC, leading to increasing interest among scientists. However, adequate in vitro models for deciphering the relationship between diet-microbiome-host are not yet available. The most common approach to study microbes and nutrients have involved the use of 2D cell lines. However, immortalized 2D cell lines differ metabolically from in vivo cells. Recently, human intestinal organoids have offered a better model system than 2D cell lines for cancer studies, providing 3D organization, multicellularity, and function. In spite of this, protocols are non-existent for organoids. We have recently outlined a novel integrative approach combining intelligent imaging acquisition and metabolomics. With this approach, colon organoids/tumoroids are seeded in µ-plate 96 well (Ibidi). This plate is suitable for growing 3D cell cultures, quantifying features such as the number, shape, texture, and size of organoids, and basic measurements, such as proliferation, DNA content (Hoechst 33342), viability and apoptosis. Subsequently, the media is aspirated and intracellular metabolites of human intestinal organoids/tumoroids are extracted and further analyzed by UHPLC-HRMS. In the future, we plan to investigate human colon organoid and tumoroid responses to gut microbial metabolites.

P-268

Characterisation of metabolically perturbed human stem cell derived dopaminergic neurons

PRESENTING AUTHOR: Alissa Schurink, Student at the LACDR, Netherlands

CO-AUTHORS: Edinson Lucumi, Cornelius Willacey, Agnieszka Wegrzyn, Alida Kindt, Noëlle Bakker, Lalithasushma Chakravadhanula, Javier Jarazo, Jens Schwamborn, Amy Harms, Thomas Hankemeier, Ronan M.T. Fleming

In Parkinson's Disease, it has been hypothesized that mitochondrial dysfunction leads to an imbalance in energy metabolism resulting in degeneration of substantia nigra dopaminergic neurons. We metabolically characterised the response of dopaminergic neurons, derived from human neuroepithelial stem cells, to chemical perturbations that targeted glycolysis and complex V of the electron transport chain. Exo- and endo-metabolomic samples were analysed with UPLC-MS/MS applying a novel targeted method based on the derivatization of amine, carboxy, and thiol groups. The inhibition of complex V resulted in a depletion of malate and succinate indicating a decrease in the TCA cycle. A significant increase in myristoylcarnitine levels indicated an increase in beta-oxidation, which may compensate for impaired ATP synthesis through complex V.

P-269

Bioengineering of Artificial Thymoma Spheroids as a 3D model for ex vivo/in vitro 3D drug investigation of toxicity employing novel microslot nuclear magnetic resonance technique

PRESENTING AUTHOR: Mohammad AlWahsh, Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V., Germany

CO-AUTHORS: Jörg Lambert, Ahmad Telfah, Mikheil Gogiashvili, Djeda Belharazem, Rosemarie Marchan, Alexander Marx, Roland Hergenröder

The metabolic alteration of thymic epithelial tumors is poorly understood on both the tissue level and in vitro cell culture. The known potential of thymomas to undergo toxicity on exposure to chemotherapeutic agents may result in therapy failure. We are focusing on the pharmacokinetics and pharmacodynamics of anticancer drug therapy via metabolic profiling on living cells. Our special interest is the development of a 3D model of thymic carcinoma and life drug toxicity testing: The analysis of tumor self protection mechanisms will open new paradigms in cancer treatment. For metabolic profiling, we apply microstrip Nuclear Magnetic Resonance (NMR), suitable for ultra-small volume samples like 3D tumor models. We could successfully establish a dedicated microstrip detector for in vitro metabolic profiling of the spheroid cells as a function of their spatial position. We custom designed a Special microfluidic device, ensuring the viability of the cells. The metabolic variation of the well characterized thymic carcinoma cell line is determined using spheroids with and without drug anti-cancer drug treatment treatment. We could successfully establish 3D tumor models from thymic cell lines, using the "simple rotation technique". We here show the very first noninvasive toxicity testing employing NMR. We could visualize the penetration of the anti-cancer drug in a 3D tumor model. Even more, we were able to determine the concomitant response on a cellular level and we could deduce details on the drug transport efficiency and on drug target modifications from these measurements.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

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<table><tr><td>P-270</td><td>Discovery of discriminative MR biomarkers from organoids for stratification of patients with gastrointestinal cancer</td></tr></table>

**PRESENTING AUTHOR:** Maria Tunset Grinde, Dept. of Circulation and Medical Imaging, Norwegian University of Science and Technology, Norway

**CO-AUTHORS:** Maria T. Grinde, Wybe J.M. van der Kemp, Boudewijn M.T. Burgering, Siver A. Moestue, Madelaine van Macklenbergh, Hanneke van Laarhoven, Dennis Klomp, Hans Wienk, Jeanine Prompers, Tone Frost Bathen

**Introduction:** Advances in in vitro 3D culture technologies, like organoids, have opened new opportunities for the development of physiologically relevant human cancer models. The aim of this study was to evaluate the quality of MR spectra acquired directly from organoids, thereby qualifying organoids as a tool for determination of discriminative metabolic biomarkers potentially transferable to the clinic. Materials and methods: Gastrointestinal cancer organoids (primary colon cancer, liver metastasis from esophageal cancer) were established as described [1]. Treatment of organoids with clinically relevant cytotoxic agents (Oxaliplatin, Fluorouracil, SN-38 or combinations of these), is ongoing. Organoids are analyzed with High Resolution Magic Angle Spinning (HR MAS) MRS, and by traditional HR MRS of the polar fraction after methanol/chloroform/water extraction. Results: We were able to identify approximately 40 metabolites from organoids and polar extracts. Metabolite concentrations in organoids and cell extracts were highly correlated (R2>0.91). 2D 31P/1H HSQC MR spectra from organoids and cell extracts display potential discriminative biomarkers like phosphocholine, glycerophosphocholine, phosphoethanolamine and glycerophosphoethanolamine. Discussion: The results from this study show that we are able to acquire high quality MR spectra from organoids. MR spectra from organoids and polar cell extracts were highly correlated, indicating that metabolite extraction is not required to achieve high quality spectra. Use of 1D 1H and 2D 31P/1H HSQC MR spectra from organoids enables identification of potential discriminative biomarkers that can be used for stratification of patients with gastrointestinal cancer. References: 1. Sato, T., et al., Gastroenterology, 2011. 141(5): p. 1762-72.

<table><tr><td>P-271</td><td>Space-resolved sampling and metabolomics analysis of the oral cavity</td></tr></table>

**PRESENTING AUTHOR:** Alessio Ciurli, LUMC, Netherlands

Saliva is a complex Biofluid that serves to maintain oral health through lubrication, clearance, buffering, antibacterial activity, taste, and digestion. Nowadays, high sensitivity of advanced analytical techniques, such as mass spectrometry, facilitate the analysis of saliva. Such analysis offers an enviable number of insights into health and disease of the oral cavity as well as into systematic alterations as for example hormone level. Saliva can be easily collected through non-invasive procedures such as direct split or use of swabs. Saliva is a mixture of different fluids secreted from three distinct salivary glands, namely, the parotids, the submandibulars, and the sublingual glands. Here we developed a novel sampling method with spatial sampling capability, allowing for the comprehensive metabolomics analysis of different oral biofilms originated from saliva secreted of different glands. In the present study, saliva samples were collected using micro-cellulose swabs in 5 different oral locations. Absorbed saliva was extracted and, subsequently, analyzed by our LC-MS/MS-based metabolomics platform (HILIC on Shimazdu Nexera LC-30 HPLC system – TripleTOF 6600 system ABSciex). Finally, the raw data were processed using MSDIAL and R Studio for further analyses and visualizations. PCA analysis displayed a peculiar metabolic profiling depending the oral location. The present outcomes display the potential of space-resolved metabolomic profiling in order to achieve a deeper understanding of the biochemical environment of the oral cavity and the distribution of oral disease, such as head & neck cancer or periodontal disease.

<table><tr><td>P-272</td><td>Use of metabolomics for exploring early mechanisms of hepatotoxicity triggered by amphetamine-like drugs</td></tr></table>

**PRESENTING AUTHOR:** Ana Margarida Araújo, UCIBIO, REQUIMTE, Faculty of Pharmacy of University of Porto (FFUP), Portugal

**CO-AUTHORS:** Ana Margarida Araújo, Eduarda Fernandes, Maria de Lourdes Bastos, Félix Carvalho, Paula Guedes de Pinho, Márcia Carvalho

Hepatic injury associated with amphetamine-like drugs has been extensively reported, but the mechanisms underlying liver damage caused at human relevant concentrations have not been fully elucidated. In this work, we used a sensitive non-target metabolomic approach based on gas chromatography-mass spectrometry (GC-MS) to identify the early adverse events caused by amphetamine-like drugs (MDMA, MDPV and methylone) in primary mouse hepatocytes (PMH). Intracellular metabolome analysis of PMH exposed for 24h to two subtoxic concentrations of each drug (corresponding to LC01 and LC10 levels) was performed. In order to establish the value of metabolomics to reveal drug toxicity mechanisms, traditional toxicological endpoints (i.e. MTT and LDH cell viability, GSH and ATP assays) were also evaluated. The results obtained by the multivariate analysis showed that each drug induces metabolome alterations in a concentration-dependent manner. Most of the altered metabolites belong to the class of amino acids, fatty acids, carbohydrates and carboxylic acids. The combination of metabolites and their respective levels was unique for each tested drug, being therefore useful in understanding their specific toxicological outcome and mechanisms of toxicity. Most importantly, our data provide compelling evidence that metabolomics is a suitable and even more sensitive approach when compared to conventional toxicological assays, as significant alterations in metabolite levels were already found at the lowest concentration tested. To the best of our knowledge, this is the first study highlighting the potential of the intracellular metabolome analysis to assess the early adverse events of drugs of abuse, providing new insights into their mechanisms of toxicity.
POSTER SESSIONS 1 AND 2 – Monday and Tuesday – all odd number posters will be on display.

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P-273 NMR-based metabolomics: a novel tool to study stress in wild bird

PRESENTING AUTHOR: Karen Machin, University of Saskatchewan, Canada

CO-AUTHORS: Asha Perera, Catherine Soos

Metabolomics examines fluctuations in small metabolite levels in biological systems. An important application of metabolomics is the study of effects of natural and anthropogenic environmental stressors on organisms. The vertebrate stress response functions to re-route energy typically utilized for maintaining homeostasis, toward metabolic processes that provide energy available for immediate survival functions, thus affecting the metabolome at the cellular level. While multiple studies have successfully applied metabolomics techniques in invertebrate and mammalian species, the use of this technique in wild birds is still in its infancy. Our main objective was to validate the use of metabolomics in evaluating effects of stress on the metabolome of waterfowl. Captive lesser scaup (Aythya affinis) were implanted with either a biodegradable corticosterone pellet to mimic effects of chronic stress, or a placebo pellet. H1 Nuclear Magnetic Resonance (NMR) spectroscopy was performed on serum samples collected during the active implant period. We hypothesized that metabolomics can be used to differentiate ducks that received exogenous corticosterone from placebo (control). We found that serum metabolite profiles could be successfully used to differentiate ducks with higher serum corticosterone from control individuals. We further identified multiple key metabolites that varied between the two groups, all of which play important roles in energy metabolism. To our knowledge, this is the first study to investigate the use of NMR-based metabolomics techniques to study stress responses in a wild bird species. Metabolomic techniques may be a potential tool in identifying and characterizing metabolic responses associated with environmental stressors in wild birds.

P-274 Metabolic changes in murine hair follicles treated with procyanidin-B2 nutraceuticals by DI-MRMS

PRESENTING AUTHOR: Matthias Witt, Bruker Daltonik GmbH, Germany

CO-AUTHORS: Eduardo Sommella, Emanuela Salviati, Christopher Thomson, Pietro Campiglia

Known for anti-inflammatory and antioxidant properties, nutraceuticals enriched in Procyanidin-B2 promote hair growth both in vitro and in vivo. However, the metabolic changes associated with the treatment have not been elucidated. In this study, direct infusion magnetic resonance mass spectrometry (DI-MRMS) was employed to understand the metabolic shift produced by treatment with Procyanidin-B2 nutraceuticals (Annurca apple extract) in murine models. DI-MRMS allowed the identification of several metabolites using ultra-high mass accuracy and fast analysis time, glutaminolysis, pentose phosphate pathway, glutathione, citrulline and nucleotide synthesis derived metabolite were detected. The metabolic profile revealed that the treatment with Procyanidin-B2 results in the early exit of hair follicles from telogen phase and increased keratin biosynthesis.

P-276 Comprehensive Metabolomic and Lipidomic Profiling in Formalin-Fixed Paraffin-Embedded Human Kidney Tissue

PRESENTING AUTHOR: Sylvia Karin Neef, Margarete Fischer-Bosch-Institute of Clinical Pharmacology Stuttgart, Germany

CO-AUTHORS: Heike Horn, Stefan Winter, Ute Hofmann, Thomas E. Muerdter, Elke Schaeffeler, German Ott, Matthias Schwab, Mathias Haag

Nontargeted tissue metabolomics is a promising approach for the assessment of tumor-specific alterations and biomarker identification. In this regard, molecular profiling experiments could benefit from the opportunity to use clinical specimens archived as formalin-fixed, paraffin embedded (FFPE) tissue. We developed a method for nontargeted metabolomic and lipidomic profiling of FFPE tissue samples and carried out protocol optimization by systematic assessment of assay reproducibility (analytical precision and technical reproducibility) for structurally annotated metabolites. Comparison of porcine FFPE tissue with fresh-frozen samples revealed high overlap of metabolic features in organic (>90%) and in aqueous (>85%) extracts indicating high preservation of polar and nonpolar metabolites in FFPE tissue. Notably, a considerable proportion of features were exclusively detected in FFPE tissue which could in part be assigned as N-methylated and N-formylated phosphatidylethanolamine species indicating headgroup-specific modifications of lipids during fixation. Further assessment of tissue size and fixation time on analyte recovery revealed metabolite class-specific differences in their detection abundance. In this regard, the recovery of specific lipids (e.g. phosphatidylinositol es and acylcarnitines) remained largely unaffected thus rendering these molecules as potential biomarkers useful for future diagnostic applications. Finally, the applicability of the protocol was demonstrated by analyzing a set of clear cell renal cell carcinoma (ccRCC) and corresponding nontumorous FFPE tissue samples, achieving clear phenotypic distinction on the basis of their metabolomic profiles. Notably, metabolites found to be significantly altered between ccRCC and nontumorous FFPE samples showed considerable overlap (>20%) with metabolites previously identified to differ between ccRCC and nontumorous in fresh-frozen kidney tissue.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

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P-277 Semi-Targeted Metabolite Profiling for Improved Cellular Bioprocessing Outcomes Utilizing a Dual Separation/Mass Spectrometer with Intelligent MSn Acquisition

PRESENTING AUTHOR: Amanda Souza, Thermo Fisher Scientific, United States

CO-AUTHORS: Ioanna Ntai, Anson Pierce, Paul Gulde, Martin Samonig, John Brann, Christopher Elicone, Ralf Tautenhahn, Daniel Lopez Ferrer, Andreas Huhmer

Chinese hamster ovary (CHO) cells are often used for commercial production of recombinant therapeutic proteins. Optimization of cell culture medium and feeds is required to obtain maximum product yield. Metabolomics analysis allows for quick determination of nutrient limitations or metabolite buildup during cell culture. To better understand the metabolic events affecting cell biomass and antibody titer, we designed a semi-targeted workflow to confidently measure critical nutrients while allowing for the discovery of previously unidentified metabolites that affect growth and antibody yield. Separate cultures of CHO cells expressing the same recombinant antibody were supplemented with 6 different feeds and extracellular metabolites were sampled at different timepoints. Our analytical platform comprised of a dual UHPLC system for RP and HILIC separation of the same sample enabling increased analysis throughput while improving metabolome coverage, and the Thermo Scientific Orbitrap ID-X Tribrid MS, with AcquireX intelligent acquisition software, for maximizing the number of metabolites interrogated by MS/MS resulting in confident metabolite annotations. An in-house spectral library of 60 metabolites was constructed from authentic standards to ensure confident identification. Differential analysis of cell media provided robust metabolic indicators of cell growth and antibody yield. The semi-targeted approach rapidly detected amino acid and vitamin depletion for some of the feeds correlating to improved titer in shorter times. Overlapping two LC separations resulted in a 30% decrease in analysis time without compromising reproducibility or compound detection. This high-throughput semi-targeted workflow provided greater understanding for the rational design of cell media and feeds for improved commercial biopharmaceutical production.

P-278 An iterative approach integrating metabolomics with sensory science to improve the horticultural quality

PRESENTING AUTHOR: Victor Castro-Alves, Örebro University, Sweden

CO-AUTHORS: Irina Kalbina, Åsa Öström, Åke Strid, Tuulia Hyötyläinen

The integration between metabolomics with sensory studies can be a powerful tool to improve the overall taste and aroma of horticultural produce; however, improvements in sensory quality have been inferred mostly on changes of specific metabolites. It also is not entirely clear what is the relationship between what consumers regard as a crop with increased sensory quality and potential metabolites that influences its sensory attributes. Thus, we propose an iterative approach to increase the sensory quality of horticultural produce by applying comprehensive metabolic characterization by GC-Orbitrap and LC-QTOFMS and integrating the data both with sensory data and growing conditions using advanced bioinformatics tools. Each round of data correlation leads to suggestions of improvements in crop production, which were taken through cycles to arrive at an improved production protocol. To show the feasibility of this approach, we addressed the reduction of quality in herbs grown at greenhouses caused by the lack of UV exposure. Results show that when the herb dill is grown for 2 weeks with daily 4-hour supplementary UV-light, the horticultural produce improved 30% of its sensory quality from the situation at the outset towards the 'gold standard'. This data was linked with the phenolic compounds profile in the dill, thereby revealing the potential of integrating metabolomics with highly innovative testing for culinary aspects. Overall, this approach can lead to practical applications for the horticultural industry that benefits both producers and consumers, while also contributing to the basic understanding of the concept of crop quality.

P-279 Metabolomics analysis of high cell density erythroblast cultures: Small molecules trigger cellular oxidative stress

PRESENTING AUTHOR: Joan S. Gallego M., Delft University of Technology - Sanquin, Netherlands

CO-AUTHORS: Joan S. Gallego M., Nurcan Yagci, Angelo D'Alessandro, Emile van den Akker, Aljoscha Wahl, Marieke von Lindern

Transfusion-ready erythrocytes can be cultured from hematopoietic progenitors but at market-incompatible high costs. A limitation in maximum cell density, 2 x 10^6 cells/mL, has been observed during in vitro erythroblast expansion. Understanding the origin of this cell density limitation may provide strategies, both at media composition and feeding regime levels, to facilitate economically feasible upscaling. Growth-limiting conditioned media from proliferating cells cultured with varying levels of cell densities, 0.7 - 15 x 10^6 cells/mL, were generated. Media reconstitution experiments, performed by separating fresh media and growth-limiting supernatants using a 3kDa cut-off, and testing the effect of the filtrates and retentates on expanding erythroblasts, indicated that small molecules (<3kDa) are responsible for growth limitation. Targeted and untargeted metabolomics measurements during 36 hours of culture, for both the intra- and extracellular compartments, indicated progressive degradation of nucleosides and a strong depletion of essential lipids and amino acids in the medium, and an intracellular decrease in intermediates of the glutathione-ascorbate, γ-glutamyl and cysteine-methionine cycles. The latter pathways are involved in glutathione metabolism, a key intracellular antioxidant. Dilution of growth-limiting media suggests that, in addition to potential inhibitors, depletion of nutrients could be limiting growth. To identify potential depleted metabolites, growth-limiting media was supplemented with the components of fresh medium. Following a one-factor-at-a-time experimental design, components in the basal media IMDM were found to partially restore growth. Current experiments aim to optimize the medium and/or genetically adapt metabolic pathways to enable erythroblasts to grow at high cell density, and at low cost.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

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P-280

Ion mobility - MS based workflow for fast untargeted metabolite profiling

PRESENTING AUTHOR: Endre Laczko, FGCZ / ETH Zurich, Switzerland

CO-AUTHORS: Junmin Hu, Sebastian Streb

The potential of metabolomics to support personalised and translational, evidence based medicine is anticipated for quite some time. A variety of research laboratories have already demonstrated successfully that metabolomics can provide data to support personalized and evidence based medical decisions. However, no workflow was presented by the metabolomics research community yet which has the quality of point-of-care analytical testing approved and in use all over the world in medical practice. The lack of robust, reproducible and fast metabolite quantification workflows from start to end prevents metabolomics to step into day to day clinical applications. In this applied context, a metabolomics methodology has to fulfil several criteria: 1) Fast and robust metabolite extractions. 2) Fast and robust metabolite measurements and quantifications. 3) Fast and standardized data analysis. 4) Simple and intuitive data documentation. We have investigated in our laboratory the potential of ion mobility - mass spectrometry (IM-MS) workflows to close this quality gap. Here we like to present a point-of-care compatible IM-MS workflow as well as experimental data to demonstrate the speed and robustness of metabolite quantification by an untargeted metabolomics method.

P-281

A skin secretion metabolomic profiling of endemic Aegean species of Lyciasalamandra

PRESENTING AUTHOR: Sotirios Katsikis, University of Athens, Greece

CO-AUTHORS: Karolos Eleftherakos, Eleftherios A. Petrakis, Leandros A. Skaltsounis, Maria Halabalaki

Skin secretions of Amphibians are a unique and fascinating source of various bioactive natural compounds, like small peptides, alkaloids, and biogenic amines. In order to describe and explain differences between species, populations and specimens but also to find specific biomarkers, a metabolomics profiling of the skin secretion of the Greek endemic Lyciasalamandra helverseni and Lyciasalamandra luschani basoglui (Salamandridae family) was carried out. These species are found in the Aegean islands of Karpathos, Kasos and Kastellorizo, from where the samples were sourced. The metabolomics analysis was carried out using LC-HRMS (Orbitrap) and the pre-processing of data was performed with mzMine v.2.39 and XCMS v.1.5 with IPO parameter optimization. The preprocessed data were then used to create multivariate statistical models using SIMCA (v14.1). An evident separation in all taxon subdivisions was observed by employing unsupervised PCA. The supervised PLS-DA, OPLS-DA and O2PLS-DA models built were also able to reveal markers for identifying population differences. MS^n experiments of a selection of m/z were further utilized to assist with compound annotation, along with 2D NMR (HSQC and HMBC) of selected pooled samples. Evidence concerning novel elements of the species alkaloid arsenal is also presented. Acknowledgment: The present work was co-funded by the European Union (ERDF) and Greek national funds through the Operational Program "Competitiveness, Entrepreneurship and Innovation", under the call "STRENGTHENING RESEARCH AND INNOVATION INFRASTRUCTURES" (project code: 5002803).

P-282

Assessing the use of Dried Blood Spot technologies for metabolomics research

PRESENTING AUTHOR: Nathan Lawler, Edith Cowan University, Australia

CO-AUTHORS: Mary C Boyce, Stacey N Reinke, David I Broadhurst

Typically, for blood-based metabolomics studies, whole blood is collected via venepuncture with plasma or serum being processed and biobanked for later analysis. This approach requires trained personnel and specialised laboratory equipment, so is generally limited to the laboratory or clinical setting. Moreover, venepuncture is often considered too invasive for applications requiring multiple repeat sampling within a short time. The use of dried blood spots (DBS) as an alternative collection method provides the advantage of reducing invasiveness, collection volume, and allowing collection to take place outside of the laboratory. Despite these advantages, there has been very limited adoption of DBS technology due to limited metabolite coverage, together with poor analytical stability and reproducibility. Recently, some of these limitations have potentially been resolved with improved collection technology; however, these methods have not yet been rigorously tested using high-resolution platforms. In this study, two different DBS technologies (hemaPen™ and hemaSpot™) were compared against traditional venepuncture. Blood samples were collected, using the three different methods, from six healthy adult participants. Samples were prepared and data were acquired using a standard blood LC-Orbitrap-MS workflow. Raw files were processed using Thermo Compound Discoverer v3.0. Metabolite coverage was assessed based on the number of identifications made using an in-house authentic chemical reference library as well as open-access spectral databases. Metabolite stability was assessed based on the percentage of metabolites present in DBS samples versus venepuncture samples. Analytical reproducibility was assessed using calculation of relative standard deviation of signal. The results of these comparisons will be presented.
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P-283

NMR in large-scale epidemiology

PRESENTING AUTHOR: Heli Salmela, Nightingale Health, Finland

CO-AUTHORS: Salla Ruosaari, Peter Würtz

**Background:** Advances in metabolomics now allow comprehensive biomarker profiling of entire biobanks and clinical trials. This provides a plethora of scientific opportunities such as discovery of novel biomarkers for onset of cardiovascular diseases and tracking their progression, as well as etiological insights into established cardiometabolic risk factors. **Methods:** Nightingale Health Ltd has developed a high-throughput metabolomics platform for population-wide initiatives and screening programs, and it is now being applied to profile close to 1,000,000 biobanked blood samples with extensive electronic health care records, including the entire collection of the UK Biobank with 500,000 samples. While reflecting the combined effects of lifestyle, environment and genetics, metabolomics provides a powerful tool for monitoring the health of individual patients or study participants over time. Here, we display the selection of the established and the most promising novel NMR biomarkers for disease events and risk prediction, focusing on how analyzing large cohorts facilitates biomarker discovery. We highlight cardiovascular diseases and diabetes, but also demonstrate how NMR metabolomics can be used in various smaller intervention studies and, for example, in research on gut microbiome and gut diseases. **Conclusions:** Here we showcase the benefits of metabolomic profiling in large-scale epidemiological settings for improved risk stratification. These results demonstrate how NMR metabolomics produces enhanced cardiovascular and diabetes risk prediction, allows novel means to track effectiveness of interventions and gives promise of future biomarker discovery for several chronic diseases.

P-284

Metabolites from human odour and textiles applying thermal desorption and GC×GC-TOFMS

PRESENTING AUTHOR: Paulina de la Mata, University of Alberta, Canada

CO-AUTHORS: Sara Vaezafshar, Rachel H. McQueen, James J. Harynuk

The relationship between human odour on different types of fabric is important in the textile industry because if differences in the generation and retention of body odour on fabrics can be controlled, it will be possible to make high performance garments that will require less frequent washing. Reduced laundering will extend the lifetime of the garment, and reduce the consumption of water and energy. The retention of molecules (metabolites) by fabrics depends on the distinct properties of the fabric, including its type and any applied finishes. Performance apparel is designed to draw moisture from the inside to the outside of the fabric for quick drying and wearer comfort. This study presents the results of an extensive investigation into the chemical analysis of metabolites of human body odour. T-shirt samples of five different fabric types worn by volunteers during at least one hour of physical activity for up to 20 wear and wash cycles were studied. Fabric samples were analyzed by direct thermal desorption (TD) of the fabric with separation and detection of the molecules effected by comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC TOFMS). Chemometric tools were used to study the differences observed between fabric types (cotton, polyester, and a cotton/polyester blend) and finishes on cotton fabrics.

P-285

Metabolic systems analysis of shock-induced endotheliopathy (SHINE) in Trauma – A new research paradigm

PRESENTING AUTHOR: Hanne Hee Henriksen, Section for Transfusion Medicine, Capital Region Blood Bank, Copenhagen University Hospital, Denmark

CO-AUTHORS: Sarah McGarritty, Rósa S. Sigurðardóttir, Travis Nemkov, Angelo D'Alessandro, Bernhard O. Palsson, Jakob Stensballe, Charles E. Wade, Óttar Rolfsson, Pär I. Johansson

**Objective:** Investigate the endothelial cell phenotype(s) that causes Shock-Induced Endotheliopathy (SHINE) in trauma. **Background:** We have studied more than 2,750 trauma patients and identified that patients with high circulating syndecan-1(endothelial glycocalyx damage marker) in plasma have an increased mortality rate compared to patients with lower levels. Notably, we found that patients suffering from the same trauma severity could develop significantly different degrees of endothelial dysfunction as measured by syndecan-1. **Methods:** Prospective observational study of 20 trauma patients admitted to a Level 1 Trauma Centre and 20 healthy controls. Admission plasma syndecan-1 level and mass spectrometry were measured and analyzed by computational network analysis of our genome-scale metabolic model (GEM) of the microvascular endothelial cell function. **Results:** Trauma patients had a significantly different endothelial metabolic profile compared to controls. Among the patients, four phenotypes were identified. Three phenotypes were independent of syndecan-1 levels. We developed GEMs representative of the observed phenotypes. Within these phenotypes, we observed differences in the cell fluxes from glucose and palmitate to produce Acetyl-CoA, and secretion of heparan sulfate proteoglycan (component of syndecan-1). **Conclusions:** We confirm that trauma patients have a significantly different metabolic profile compared to controls. A minimum of four SHINE phenotypes were identified, which were independent of syndecan-1-level (except one phenotype) verifying that the endothelial response to trauma is heterogeneous and most likely driven by a genetic component. Moreover, we introduced a new research tool in trauma by using metabolic systems biology, laying the foundation for personalized medicine.
<figure><img src="image_76.png" /></figure>

**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

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P-286

Advances and future perspectives in Eco-Metabolomics: From fingerprints to molecular mechanisms

PRESENTING AUTHOR: Kristian Peters, Biochemistry of Plant Interactions, IPB Halle, Germany

CO-AUTHORS: Treutler H, Marr S, Balcke G, Döll S, Gorzolka K, van Dam NM, Neumann S

Eco-Metabolomics is the application of metabolomics to ecology and biodiversity research to understand fundamental mechanisms regarding interactions of organisms with the environment, other organisms and within species communities. Ecological experiment designs that are often carried out in fields require a large number of samples to control the high variability of metabolite profiles. The focus on a broad range of non-model species that may never have been subjected to metabolite profiling before results in biochemically highly diverse profiles. Thus, major challenges include a wealth of data resulting from multi-level experiment design factors and a multitude of novel substances ("unknown unknowns"). Here, we give an overview on current challenges in Eco-Metabolomics and present major advances. The large data generated by Eco-Metabolomics experiments necessitate the integration of advanced statistical approaches to pinpoint metabolite features that explain the underlying research question most significantly. Feature selection methods can be used to perform subsequent identification only of the most relevant features using targeted in vitro methods like MS2/MS3, NMR or by applying in silico tools like MetFrag. Finally, we explain how annotating compound classes (e.g. using MetFamily and ClassyFire) represents a major breakthrough to describe molecular mechanisms in ecology and biodiversity research.

P-288

Ion Mobility Spectrometry paired with 13C Enrichment Strategies for Improved Metabolite Identification

PRESENTING AUTHOR: Robin Kemperman, University of Florida, United States

CO-AUTHORS: Chris W.W. Beecher, Timothy J. Garrett, Richard A. Yost

Ion mobility (IM) is a rapid gas-phase separation technique that can separate isobars that are unresolved by LC-MS. The combination of LC-IM-MS has shown great potential for metabolomics applications because of the ability to deconvolute complex samples and perform structure elucidation, in addition to calculate collision cross sections (CCS) of each metabolite based on their measured IM drift times (DT). In this study we have implemented a unique isotopic labeling technique into our LC-IM-MS metabolomics workflow for higher accuracy and confidence in metabolite identification. Isotopic ratio outlier analysis (IROA) uses the 13C enriched signal of all biochemically-synthesized metabolites in yeast, using a 5% or 95% 13C randomly labeled glucose in the cell media. IROA produces characteristic isotopologues which confirm biological origin, number of carbons, and removes artifacts. IROA is a powerful method for metabolic profiling; however, many isobars and isomers remain unresolved and the addition of numerous isotope signals increases the complexity of spectra. IM helps resolve overlapping IROA patterns and increases the confidence in metabolite identification; moreover, mass spectra show increased S/N ratios in the LC-IM-MS scans compared to LC-MS scans. Fragments of IROA-labeled metabolites maintain the IROA signature which aids in identification, however, due to low abundances are not always detected. For example, Arginine eluted at RT=0.7 min, with an appropriate IROA pattern (m/z range of 175.1196-181.1401); however, it's in-source fragments were hidden in the noise. After IM-filtering at DT=16.1 ms, 5 different IROA patterns belonging to arginine fragments were detected.

P-289

Derivatization of central metabolites in SUIT-2 cells using dimethylaminophenacyl bromide enabling LC-MS/MS energy-state analysis

PRESENTING AUTHOR: Cornelius Willacey, Analytical BioSciences and Metabolomics, Leiden University, Netherlands

CO-AUTHORS: Martijn Naaktgeboren, Edinson Lucumi Moreno, Daan van der Es, Naama Karu, Ronan M. T. Fleming, Amy C. Harms, Thomas Hankemeier

Recent advances in metabolomics have enabled larger proportions of the human metabolome to be analyzed quantitatively. A significant contribution to this field includes the chemical derivatization of metabolites and the use of isotope-coded derivatization (ICD). Chemical derivatization allows in principle a wide coverage in a single method, as it affects both the separation and detection of metabolites: it increases retention, stabilizes and improves the sensitivity of the analytes. Here, we describe a derivatization technique which simultaneously labels carboxylic acids, thiols and amines using the reagent dimethylaminophenacyl bromide (DmPABr). We further improve the quantitation by employing ICD, which uses internal standards derivatized with an isotopically-labelled reagent (DmPABr-D6). We demonstrate the ability to measure and quantify 64 central carbon and energy-related metabolites including amino acids, N-acetylated amino acids, metabolites from the TCA cycle and pyruvate metabolism, acylcarnitines and medium-/long-chain fatty acids. To demonstrate the applicability of the analytical approach, we analyzed SUIT-2 cells utilizing a 15-minute single UPLC-MS/MS method in positive ionization mode. SUIT-2 cells exposed to rotenone showed definitive changes in 28 out of the 64 metabolites, including metabolites from all 7 classes mentioned. This method provides broad coverage of the human metabolome and quantification of amines, carboxylic acids and thiol-containing metabolites.
<figure><img src="image_77.png" /></figure>

**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

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P-290

Educating the Next Generation – a Framework for Introducing HRMS and Metabolomics into Undergraduate Curricula

PRESENTING AUTHOR: Stacey Reinke, Edith Cowan University, Australia

CO-AUTHORS: Nathan G Lawler, Yingqi Tu, Mary C Boyce

Over the last decade the growth in metabolomics research has been exponential. This has been paralleled by increased educational opportunities at and above the postgraduate level. However, any acceleration in the knowledge economy inevitably creates a vacuum of essential skills in the next generation of potential scientists. Currently, topics such as high-resolution mass spectrometry (HRMS), cheminformatics and data science are extremely limited in most undergraduate education curricula. This needs to be rectified to ensure the stable growth of metabolomics. Implementing metabolomics content into curricula is challenging as it must both meet certain pedagogical requirements, whilst being integrated into a diverse number of existing undergraduate courses. For example, understanding HRMS needs to be embedded into chemistry curricula; pathway mapping into biochemistry curricula; spectral deconvolution and database searching into data science curricula. As a first step to addressing these issues, an authentic learning framework for the metabolomic analysis of blood, using HRMS, has been developed and effectively integrated into an undergraduate analytical chemistry course. The pedagogical aims were to (1) introduce students to the field of metabolomics and (2) enhance their understanding of HRMS, specifically the differences in processing and interpreting untargeted vs targeted data. A simple, easily replicated, experiment was devised to investigate the effects of hemolysis on the plasma metabolome, using horse blood to simulate human blood. Data were acquired using an LC-Orbitrap-MS, then processed and interpreted using XCMS-Online. This presentation will focus on the challenges and insights we gained in delivering complex, multi-disciplinary content at an undergraduate level.

P-291

Untargeted Metabolomics of Urine from Opium Users and Non-Users: A Golestan Cohort Study

PRESENTING AUTHOR: Susan Sumner, UNC Chapel Hill, Nutrition Research Institute, United States

CO-AUTHORS: Reza Ghanbari, Wimal Pathmasiri, Susan McRitchie, Yuan Li, Arash Etemadi, Christian Abnet, Jonathan Pollock, Reza Malekzadeh

The United Nations Office on Drugs and Crime estimated 34 million opioid users, and 19 million opiate users worldwide. Opiates are associated with health outcomes such as cancers, infectious diseases and psychological disorders. In the 1960s, research by Dole and Nyswander theorized that addiction is initiated through a metabolic disruption. Opium and derivatives can modulate gene expression, and impact neural and hormonal mechanisms, which can be reflected by metabolites excreted in urine. The Golestan Cohort Study, established in the northeast of Iran, includes more than 8,000 individuals who reported opium use with a mean duration of 12.7 years. For our study, over 500 urine biospecimens were selected for individuals who either reported no opium use (control), or reported opium use (maximum amount of opium eaten or inhaled per week), with/without tobacco. Untargeted analysis of urine was conducted using a UPLC-Q-Exactive-HFx-Orbitrap-MS. NMR data was acquired on a Bruker 700 MHz NMR. Data were modelled using logistic regression, multivariate analysis, and hypothesis testing with the phenotypes of non-user vs user, route and level of use, tobacco use, and opioid use disorder (OUD). Metabolite identifications and annotations were made using our RT, Mass, MS/MS in-house experimental physical standards library (Orbitrap data), Chenomx library (NMR), and Public Databases. We found perturbations in endogenous metabolites involved in one carbon metabolism, Krebs cycle, tryptophan metabolism, mediation of cell signal transduction, and neuroexcitatory activity. Metabolites of illicit drugs, tobacco products, carcinogens, phthalates, and plants also contributed to the phenotypes investigated. [Funding: 1U24DK097193, Sumner; NIDA INVEST Fellow, Ghanbari]

P-292

Coupling DAD and MS data in untargeted metabolomics

PRESENTING AUTHOR: Ron Wehrens, Wageningen University & Research, Netherlands

CO-AUTHORS: Ron Wehrens, Jasper Engel, Rob van Treuren, Ric de Vos, Kenneth Haug and Philippe Rocca-Serra

In untargeted metabolomics it is not uncommon to record UV/Vis absorbance data using a photodiode array detector (DAD) in addition to the mass spectrometry detector. DAD data can contain key information on the biochemical class or even structural identity of compounds exhibiting specific UV/Vis absorbance characteristics, like benzenes, plant pigments and Maillard reaction products. DAD data nowadays are typically used in a quality control context and are rarely seen as an autonomous source of information. As a result, no accepted standards for storing and exchanging data exist yet. Here we report on an open and general format for LC-DAD data based on the ISATAB standard, used in repositories like MetaboLights. This format allows the DAD data to be uploaded as a separate experiment assay. Motivating examples of multivariate DAD analyses and couplings with corresponding MS data are shown for a large LC-DAD-Orbitrap FTMS metabolomics data set on lettuce samples, available through MetaboLights. There are many possibilities for exploiting synergy between the two data layers. Since the chromatography of the two data layers is identical the DAD data can help in a better alignment of the more complex MS data, absorbance characteristics can be used to help annotating MS features, and in some cases quantitation of compounds may be easier in DAD data, too. When more and more DAD data sets become available, including injections of pure standards, multivariate analyses will become easier and more reliable, further enhancing the value of data dissemination through open platforms like MetaboLights.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

*AWARD WINNERS

NEW FRONTIERS

P-293

A Room Temperature Metabolism Quenching Method for Automated Metabolomics Sample Preparation

PRESENTING AUTHOR: Genevieve Van de Bittner, Agilent Technologies, United States

CO-AUTHORS: Alex Apffel, Kristin B. Bernick, Manuel Gomez, Brian P. Smart, Christine Miller, Steven Fischer, Laurakay Bruhn

Many existing methods for cell-based metabolomic sample preparation require low-temperature metabolism quenching procedures to prevent interconversion of metabolites in a rapid, controlled manner. The low temperatures required to quench metabolism often utilize cold liquids, such as liquid nitrogen, which are difficult to handle and store. Additionally, low temperatures complicate automation of metabolism quenching steps, since they promote collection of condensation on robotic components, which can hinder robotic movement and cause rusting. We developed a mass-spectrometry-compatible method for room temperature metabolism quenching and simultaneous cell lysis to avoid the issues associated with low temperature quenching. A metabolic flux analysis utilizing this room temperature quenching method confirmed rapid metabolism quenching with no detectable conversion of 13C-labeled glutamine, added in the quenching and lysis buffer, to glutamate or other TCA cycle intermediates. Adenosine triphosphate stability testing indicated metabolite stability was maintained for at least a day at room temperature. We have integrated the room temperature quenching method into a complete sample preparation workflow that includes protein and lipid removal steps, which have been optimized for metabolite recovery, to provide a clean metabolite sample for LC/MS analysis. Targeted and untargeted LC/QTOF analyses of mammalian-cell-derived samples indicate our new sample preparation workflow extracts key central carbon metabolites and provides a wide coverage of the metabolome. Our room temperature quenching method simplifies the time-critical portion of the metabolomics sample preparation process, enables robust automation, and fills an important need in the metabolomics community.

P-294

Novel MALDI imaging solution empowered by a MALDI-Q-TOF and dedicated bioinformatics pipeline for identification of metabolites and lipids from tissue

PRESENTING AUTHOR: Alice Ly, Bruker Daltonik GmbH, Germany

CO-AUTHORS: Janina Oetjen, Michael Becker, Richard R. Drake, Anand Mehta, Lucy Woods, Shannon Cornett, Alice Ly

MALDI Mass Spectrometry Imaging (MALDI-MSI) has emerged as a technique to spatially resolve different metabolic processes in tissue sections. We present a novel workflow solution consisting of a high spatial resolution MALDI source and stage mounted on a commercially available QTOF. A range of metabolomics imaging applications will be highlighted. This includes measurements of endogenous metabolites; typically these measurements were previously performed using extremely high mass resolving instruments. Measurements of mouse intestine sections revealed differential abundance of multiple endogenous metabolites localized to different anatomical regions. Kidneys from rats treated with substance Factor Xa antagonist and untreated rats were analyzed for the distribution of the compound, compound metabolites and lipid signals. The compound (m/z 432.15) and associated metabolites were detected in the renal medulla; neither were detected in the non-treated samples. A number of lipid signals were increased or decreased in both the renal cortex and medulla of compound-treated animals when compared to those not receiving treatment. When combined with a software processing pipeline for automatically annotating measured ions, this enabled generation of annotated images from MALDI-imaging data. Glycoconjugates can be measured as metabolic endpoints of glucose metabolism. N-glycan imaging was conducted on human liver carcinoma sections and results compared against a list of glycans generated using a high-mass-resolving MRMS system. 61 out of 61 N-linked glycans signals were detected in the sample measured on the MALDI-QTOF, with clear differences in tumor versus non-tumor regions. These results demonstrate the capability of our MALDI-QTOF instrument for the MALDI-MSI of different metabolomics applications.

P-295

New discovery from CE-FTMS based metabolome profiling applied into fasting rat

PRESENTING AUTHOR: MOON-IL KANG, Human Metabolome Technologies, Japan

CO-AUTHORS: Kazunori Sasaki, Kaori Abe, Makoto Suzuki, Satoshi Ito, Tsutomu Negama, Kenjiro Kami

New unique platform, CE-FTMS, Capillary Electrophoresis coupled with a Fourier Transform Mass Spectrometer, been established recently by our patent electrospray ionization (ESI) source adaptation. In the application study with metabolomic profiling of multiple organ samples of fasted rats, we aimed to evaluate analytical performance whether CE-FTMS can be used as improved method compare to CE-MS for the purpose of analyzing charged metabolites comprehensively. Here we report an overall appearance for plasma and soleus muscles in collected all 5 different organs with 5 time-course points for 24 hours (n=5, each for 0, 4, 8, 16, and 24-hr) from fasted rats. CE-FTMS platform resulted in successful detection of 323 and 395 metabolites in plasma and soleus muscle separately, showed the increased detection number more than 1.7-fold or 1.8-fold compared to CE-MS. Especially, 2-fold increase of detection number in anion mode of CE-FTMS at both plasma and soleus samples. In spite of the significant difference in detection numbers between CE-FTMS and CE-MS, the movement of samples from starvation start (0 hr) to 24 hrs by CE-FTMS is pretty much the same as the CE-MS in PCA plot analysis, considering contribution of PC1 and PC2. Moreover, one third of metabolites within top or bottom 30 list of factor loading of PC1 and PC2 in CE-FTMS has not identified in CE-MS. We also confirmed that several metabolites showing partly in CE-MS at the start or end of fasting time such as cytosine, S-methylmethionine, spermidine, and thymidine are identified every samples in CE-FTMS measurement.
POSTER SESSIONS 1 AND 2 – Monday and Tuesday – all odd number posters will be on display.

POSTER SESSIONS 3 AND 4 – Wednesday and Thursday – all even number posters will be on display.

*AWARD WINNERS

NEW FRONTIERS

<table><tr><td>P-296</td><td>The NIH Metabolomics Consortium</td></tr><tr><td colspan="2">PRESENTING AUTHOR: Mike Conlon, University of Florida, United States</td></tr><tr><td colspan="2">CO-AUTHORS: Padma Maruvada, Richard A. Yost</td></tr><tr><td colspan="2">The NIH Common Fund Metabolomics Program has established a new consortium with the overall goal to realize the potential of metabolomics to inform basic, translational, and clinical research by (1) establishing an enduring national public repository for metabolomic data, (2) overcoming technical hurdles in analyzing and interpreting metabolomics data, including the ability to determine metabolite identities, and (3) developing consensus for, and promoting adoption of, best practices and guidelines to promote accuracy, reproducibility, and re-analysis of metabolomics data in collaboration with the national and international communities. This presentation will provide a perspective on the consortium, and explore the opportunities to engage stakeholders and the international metabolomics community.</td></tr><tr><td>P-297</td><td>In silico metabolite property libraries and quantitative chemical space analysis: a path toward novel molecule identification and false discovery assessment</td></tr></table>

PRESENTING AUTHOR: Ryan Renslow, Pacific Northwest National Laboratory, United States

CO-AUTHORS: Sean Colby, Jamie Nuñez, Yasemin Yesiltepe, Niranjan Govind, Dennis Thomas, John Cort, Justin Teeguarden, Karen Wahl, David Wunschel, Thomas O. Metz

Characterization of chemical "dark matter" is critical for human metabolome and exposure assessment, but the identity of many biologically-active compounds will remain unknown until analytical chemistry approaches are developed that (i) can identify compounds without reliance on data from analysis of authentic reference materials, (ii) have resolving power sufficient to resolve chemically similar compounds and (iii) have methods for comparing experimental data to reference libraries of chemical properties while accounting for the inherent accuracies in aspects of all associated analytical and computational pipelines. To begin addressing this need, our team has developed a suite of tools that collectively assembles evidence for the presence of small molecules in complex samples through the use of libraries containing multiple measured and calculated chemical properties. Here, we discuss the advancement of these tools and a current evaluation of this suite of standards-free identification methods on a set of natural products and microbial toxins. Furthermore, we evaluated four existing and new methods for quantifying chemical space: (i) principal components calculated from over 50 chemical properties, (ii) K-means clustering on these properties, (iii) distribution of ClassyFire superclasses, and (iv) relative location in deep learning latent space. The results show that compounds with similar behavior (e.g. detectable via MS) are best grouped using clustering, rather than by overall chemical class. Finally, we discuss how these methods may enable determination of a conservative false discovery rate for molecular identification and lead to generation of novel candidate molecules that do not correspond to any currently known molecules.

<table><tr><td>P-298</td><td>High speed untargeted 4D-lipidomics and -metabolomics LC-MS/MS workflows with Parallel Accumulation Serial Fragmentation (PASEF)</td></tr><tr><td colspan="2">PRESENTING AUTHOR: Sven Meyer, Bruker Daltonik GmbH, Germany</td></tr><tr><td colspan="2">CO-AUTHORS: Ulrike Schweiger-Hufnagel, Aiko Barsch</td></tr><tr><td colspan="2">A crucial step in lipidomics and metabolomics studies is the acquisition of MS/MS data. To reliably identify analytes, the MS/MS fragmentation has to be fast enough to generate a reasonable number of high quality spectra over a chromatographic peak. This becomes even more complicated if the LC run times are very short. While there is an in-depth oriented approach to ID as many lipids as possible, clinically-oriented projects often demand a high-throughput for large sample cohorts. Therefore, a short cycle time per sample is needed to realize studies with hundreds or even more samples in a reasonable time frame. In order to keep up with this, the analytical instrumentation needs to deliver a high data quality at high acquisition speeds. This is realized by the PASEF (Parallel Accumulation Serial Fragmentation) acquisition mode. For this presentation, extracts of the NIST reference standard SRM 1950 were investigated for the number of identified lipids using different LC run times. The benefit of the additional ion mobility separation is to get clean MS/MS spectra of co-eluting compounds, e.g. isobaric lipids. This is demonstrated on PC / PE lipids. Furthermore, the ability to reliably identify differences between sample groups, even at short LC run times will be presented.</td></tr></table>
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

*AWARD WINNERS

PLANT, FOOD, ENVIRONMENTAL AND MICROBIAL

P-299

Cytoprotective Effects of Wheat Sprout Extracts on tert-Butyl Hydroperoxide-Induced Oxidative Stress in HepG2 Cells

PRESENTING AUTHOR: Hyeonmi Ham, National Institute of Crop Science, Rural Development Administration, South Korea

CO-AUTHORS: Hye-Young Seo, Hyun Young Kim, Woo Duck Seo, Mi Ja Lee, Ki-Chang Jang

Wheat sprout contains various ingredients that are beneficial to health. It is reported that wheat sprout has antioxidant, hypoglycemic, anticarcinogenic, and anti-inflammatory effects. Because of these health-promoting properties, wheat sprout is widely used in juice or tablet form. However, the intracellular antioxidant mechanisms of wheat sprout are still poorly understood. The objective of this study was to evaluate the protective effects of wheat sprout extracts against tert-butyl hydroperoxide (TBHP)-induced oxidative stress in HepG2 cells. The levels of cellular reactive oxygen species (ROS), glutathione (GSH), malondialdehyde (MDA), and antioxidant enzyme activities were investigated as biomarkers of cellular oxidative status. HepG2 cells were treated with various concentrations of wheat sprout extracts (0~50 µg/ml) prior to treatment with TBHP for 4 h. The incubation of HepG2 cells with TBHP led to decrease in cell viability. However, pretreatment of the cells with the wheat sprout extracts rescued cell viability in a dose-dependent manner. Generation of reactive oxygen species (ROS) induced by TBHP treatment in HepG2 cells was markedly ameliorated after treatment with wheat sprout extracts. Cellular depletion of GSH and formation of MDA were reduced by wheat sprout extracts. Moreover, pretreatment of wheat sprout extracts prevented a significant increase in catalase and glutathione reductase induced by TBHP. These results showed that treatments with wheat sprout extracts protect the cells against oxidative stress by modulating ROS production, GSH level, MDA generation, and antioxidant enzyme activities in HepG2 cells.

P-300

NMR-based Metabolomics: A More Sensitive Bioindicator of Stream Ecosystem Health

PRESENTING AUTHOR: Robert Brua, Environment and Climate Change Canada, Canada

CO-AUTHORS: Adam G. Yates, Joseph M. Culp

Human modification of landscapes and subsequent degradation of aquatic ecosystems is a global threat to the ecological integrity of waterways. This pervasive threat is evident in southern Manitoba, Canada where intensive agriculture has led to nutrient enrichment and habitat degradation of waterways. In highly modified landscapes, there is great difficulty in assessing the ecological health of aquatic systems as few unimpaired sites exist and stream communities, such as benthic macorinvertebrates, traditionally used in biomonitoring have become more homogeneous. Indeed, traditional bioassessment approaches have been unable to link human activities, such as the extent of agriculture in the watershed, and ecological condition of streams in southern Manitoba. Therefore, a critical need exists to identify alternative techniques for assessing stream ecosystem health. We used NMR-based metabolomics to evaluate the suitability of the metabolome of northern crayfish (Faxonius virilis) as a bioindicator of environmental exposure to stressors associated with agricultural and rural land use activities. In contrast to past assessments using benthic macroinvertebrate composition, the metabolome of crayfish tail tissue was able to differentiate among streams with high, medium and low amounts of agriculture in the watershed. Moreover, metabolite changes indicated stressor exposure altered energy metabolism pathways. These results suggest the metabolome of crayfish tail tissue is a more sensitive indicator of human impacts on stream ecosystem condition in highly altered landscapes. We conclude the use of NMR-based metabolomics to assess aquatic ecosystem condition should be encouraged. We also recommend additional research to develop protocols and assessment models for aquatic biomonitoring using metabolomics.

P-301

Prenatal chemical exposure modifies neonatal metabolome and type 1 diabetes risk

PRESENTING AUTHOR: Tuulia Hyötyläinen, Örebro University, Sweden

CO-AUTHORS: Aidan McGlinchey, Tim Sinioja, Santosh Lamichhane, Johanna Bodin, Heli Siljander, Dawei Geng, Cecilia Carlsson, Daniel Duberg, Jorma Ilonen, Suvi M. Virtanen, Hubert Dirven, Hanne Friis Berntsen, Karin Zimmer, Unni C. Nygaard, Matej Orešič, Mikael Knip

In the last decade, the increasing incidence of type 1 diabetes (T1D) stabilized in Finland, coinciding with tighter regulation of per- and polyfluoroalkyl substances (PFAS). In a mother-infant cohort study (n=264), we analyzed metabolite profiles of pregnant mothers and their offspring at birth with UHPLC-QTOFMS and GC-QTOFMS (260 identified lipids and metabolites) and quantified 22 PFAS in maternal samples during pregnancy (UHPLC-QqQMS). We then further examined the impact of PFAS exposure on metabolome in non-obese diabetic mouse (NOD) model. High PFAS exposure during pregnancy was associated with altered metabolic profiles, particularly with decreased phospholipids in the offspring. This association was exacerbated with increased human leukocyte antigen-conferred risk of T1D in infants. Importantly, we observed a remarkable similarity between the metabolic signature observed in the current study and the known signature associated with progression to T1D (Oresic et al, 2013). The NOD model verified our findings showing that prenatal exposure to PFAS resulted in a similar decrease in phospholipids also in the mice offsprings. We conclude that high PFAS exposure may alter sphingolipid levels during fetal development which may then go on to play a pathogenic role in the development of T1D later in life. Our data also highlight a potential role for a gene-environment interaction, which may lead to altered lipid profiles in newborn infants at-risk of developing T1D. Taken together, our findings suggest that high PFAS exposure during pregnancy contributes to risk and pathogenesis of T1D in children.
*AWARD WINNERS

PLANT, FOOD, ENVIRONMENTAL AND MICROBIAL

P-302 Xenometabolome of Mussel Exposed to Environmental Contaminants Mixtures in Field Conditions

PRESENTING AUTHOR: Diana Álvarez-Muñoz, Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Spain

CO-AUTHORS: Álvarez-Muñoz Diana, Lidia Molina, Marinella Farré

In our daily life activities, thousands of chemicals compounds are released to aquatic the environment. They can make their way first to river water and later on to sea water. An interaction between the contaminants present in the aquatic media and the resident organisms may occur and some of them can be bioaccumulated. Besides the importance of analyzing changes in the metabolome for understanding the effects of contaminants mixtures, it is also important to identify the xenobiotics accumulated that might be responsible of these alterations. In order to study this a metabolomics approach was undertaken in mussels collected from Ebro Delta (Spain). The approach followed has allowed profiling the xenometabolome or exposome. A field experiment was carried out and mussels from a shellfish farm allocated outside the Delta were transplanted into several sampling points for 1 month. After this period, they were collected, haemolymph was extracted, centrifuged, snap frozen and kept at -80 °C until its analysis. Prior injection in Orbitrap-Q-Exactive it was diluted 1:1 with methanol and filtered through a phospholipid removal plate. A non-target approach was followed by using Compound Discoverer 2.1. The differential analysis was carried out by using the organisms from the "clean site" as a control group, and the organisms from the other sampling points as exposed groups. Data sets were also exported to the statistical software "R" for multivariate analysis. Preliminary results show bioaccumulation of pesticides such as bentazone, pharmaceutical compounds like venlafaxine, and other compounds with endocrine disrupting properties (i.e. triclosan and methylparaben).

P-303 Metabolic foot-printing approach to study long term environmental impacts of biological and synthetic insecticides

PRESENTING AUTHOR: Cédric BERTRAND, AKINAO / CRIOBE / UPVD /, France

CO-AUTHORS: Chandrashekhar Patil, Amani Ben Jrad, Hikmat Ghosson, Delphine Raviglione, Marie-Virginie

Mosquitoes can carry infectious diseases from person to person and from place to place. Presence and establishment of invasive mosquito species such as Aedes aegypti and Aedes albopictus is rapidly increasing in the European environment. The European Directive in 1998 led to the increasing use of biological insecticides such as cry proteins produced by the bacterium Bacillus thuringiensis israelensis (Bti) that kill mosquito larvae after being ingested. Considering the interest in Bti as more environmentally sustainable bioinsecticide, it is important to examine in detail environmental fate and impact of Bti. The available tool such as half-life, t1/2, does not considers the biodegradation and biotransformation phenomenon of complex formulations. To address this challenge, 'Environmental Metabolic Footprinting' (EMF), giving an idea of the resilience time was recently developed in the laboratory (Patil et al. 2016; Salvia et al, 2017) to evaluate the impact of synthetic, botanical and microbial insecticides on soil and sediment matrix. The project 'EnvFate' aims to employ an EMF approach, to dynamically characterize environmental markers of Bti pollution found among the sediment matrix meta-metabolome. Metabolome characterization will require to develop and optimize extraction and detection protocols using LC-MS platform. In addition, metabarcoding approach will allow to understand microbial community responses to the Bti pollution. We performed a year long experiment to know the changes in the meta-metabolome after Bti and α-cypermethrin treatment in the three different sediment matrix. These activities pave the way for the development and adaptation of new environmental monitoring tools.

P-304 Integration of non-target screening and effect-based monitoring to assess OMP related water quality changes in drinking water treatment

PRESENTING AUTHOR: Andrea Mizzi Brunner, KWR Watercycle Research Institute, Netherlands

CO-AUTHORS: Cheryl Bertelkamp, Milou Dingemans, Annemieke Kolkman, Bas Wols, Bram Martijn, Ton Knol, Thomas ter Laak

The ever increasing production and use of chemicals augment their occurrence in drinking water and its sources so that monitoring using targeted chemical analyses alone is no longer sufficient. High-resolution mass spectrometry (HRMS) based non-target screening (NTS) has therefore become a promising tool to assess chemical water quality as well as the changes thereof during water treatment. However, to date the high number of features, i.e. unique combinations of accurate mass and retention time, resulting from NTS renders structural identification virtually impossible and prioritization is required. Here, we developed an approach to interpret and prioritize features based on the integration of chemical and effect-based data with data science methods, and applied it to the assessment of water quality changes in drinking water treatment trains at three pilot installations. These installations included advanced oxidation processes, ultrafiltration with reverse osmosis, and granular active carbon filtration. A selection of organic micro-pollutants relevant for the drinking water sector was spiked into the water treated in these installations. LC-HRMS based NTS and bioassays that enable the monitoring of biological effects of complex mixtures of chemicals were performed. NTS data was screened for predicted and known transformation products of the spike-in compounds. Patterns and trends were evaluated using multivariate analysis methods. This allowed for efficient visualization of the complex data. By integrating the chemical NTS data with the biological effect-based results potential toxicity was accounted for during prioritization. Together, the developed workflows allowed to monitor water quality and changes in water quality during water treatment.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

*AWARD WINNERS

PLANT, FOOD, ENVIRONMENTAL AND MICROBIAL

P-305

Integrative omics analysis reveals resource partitioning strategies during toxin production in Microcystis aeruginosa

PRESENTING AUTHOR: Shruti Pavagadhi, National University of Singapore, Singapore

CO-AUTHORS: Di Pan, Shivshankar Umashankar, Amit Rai, Peter I. Benke, Megha Rai, Gourvendu Saxena, Vamshidhar Gangu, Sanjay Swarup

Rapid urbanization and climate change have contributed to an increased incidence of harmful algal blooms (HABs) in natural waters. HABs caused by Microcystis aeruginosa produce toxic secondary metabolites, such as microcystins (MCs). To understand resource partitioning strategies between cell growth and MCs production in response to environmental triggers, we tested the effect of interactions between light and nitrogen on Microcystis aeruginosa PCC 7806 using integrative omics. We measured the molecular changes to light and nitrogen combinations at the transcriptome and metabolome levels. We mapped these to networks of cellular processes thereby identifying overall strategy for resource reallocation. Statistical models revealed that both light and nitrogen affected the transcriptome and metabolome, however, light was the major factor driving the changes at transcriptome level, when compared to nitrogen. On the contrary, effects at metabolome level were less pronounced and were restricted to a few inter-related networks that share rate-limiting substrates and pathway intermediates. Through the integrative systems level approach, we found certain networks belonging to cellular growth, cellular scavenging and secondary metabolite metabolism that drive the overall resource partitioning strategy in Microcystis. Additionally, two rate limiting metabolites (malonyl-CoA and metabolite couplet SAM; S-adenosyl methionine-SAH; S-S-Adenosyl-L-homocysteine) that occur at the crossroads of the light and nitrogen dependent pathways were identified, thus controlling the metabolic flux and resource allocation in Microcystis cultures. Through these observations, we provide a conceptual model for environmental responses of Microcystis. This model could be validated through controlled feeding experiments and specific genetic mutants to obtain further insights.

P-306

Combining acute toxicity, toxicokinetics and metabolomics approaches for comprehensive toxicity assessment of xenobiotics in aquatic organisms - Zebrafish embryos exposed to triclosan as a case study

PRESENTING AUTHOR: Dimitrios Damalas, Laboratory of Analytical Chemistry, University of Athens, Greece

CO-AUTHORS: E. Panagopoulou, M. Agalou, D. Beis, M.H. Lamoree, P.E.G. Leonards, N.S. Thomaidis

The ever increasing contamination of the aquatic environment from xenobiotics has raised concerns, regarding their adverse effects on aquatic organisms. To evaluate the impact of toxicants in depth, the whole xenometabolome and endometabolome of aquatic organisms should be studied. Zebrafish provides a promising alternative model for toxicological studies. The overall goal of this study was to highlight a high-throughput testing strategy, incorporating data from different approaches (fish embryo toxicity, toxicokinetics and metabolomics) for a comprehensive toxicity assessment of xenobiotics in aquatic organisms. Zebrafish embryos exposed to triclosan (TCS) were used as a case study. Initially, potential acute toxicity of TCS in zebrafish embryos was assessed. Afterwards, the uptake and biotransformation of TCS by zebrafish embryos were evaluated. The final objective was to establish a wide-scope targeted metabolomics screening workflow to investigate the induced toxicity in a biochemical perspective and associate the observed toxicity/phenotype with changes at molecular level. To cover the wide polarity range of xeno- and endometabolome, a platform with broad analytical coverage was developed, combining RPLC and HILIC with ESI-HRMS. Suspect and non-target screening workflows were applied for the identification of biotransformation products. Regarding the metabolomics part of the study, a database of 600 endogenous metabolites was established, covering a broad range of primary metabolism. This approach is an alternative strategy to the classic targeted methods, as it did not focus on a few metabolic pathways, for which we already know that are affected by the specific stimulant. The proposed strategy unravels the involvement of unexpected metabolic pathways.

P-307

An Omics Approach Towards Identification of Unknown Emerging Pollutants in Marine Waters

PRESENTING AUTHOR: Steve Huysman, Ghent University, Belgium

CO-AUTHORS: Francis Vanryckeghem, Kristof Demeestere, Lynn Vanhaecke

The potential prevalence of emerging organic micropollutants in the aquatic environment has become a significant risk for public and ecological health, which is stressed by different regulatory bodies. Despite this, legislation so far mainly focuses on a few priority pollutants, thereby missing a substantial fraction of the known and unknown compounds occurring in water. Hence, the prevalence and identity of most compounds remains unexplored. Therefore, this study presents a novel analytical strategy for elucidating structurally related emerging organic pollutants in the aquatic environment. In-house developed and validated UHPLC-HR-Q-Orbitrap-MS methods targeting 70 steroids (Huysman et al., 2017) and 27 plasticizers (Huysman et al., 2019) were used to enable the detection of 1292 unique unknown emerging organic pollutants in 24 seawater samples (obtained from the Belgian part of the North Sea). To elucidate typical fragmentation profiles and identify characteristic fragments of the above-mentioned chemical pollutants, the target standards were respectively fragmented at 35 and 20 eV. As a result, typical fragmentation profiles were obtained for the steroids and plasticizers. The generated fragments of the unknowns were screened – using a newly written Python code – on their agreement with characteristic fragments and neutral losses obtained from the target standards. In total, 13% (n=173) of the unknowns present in water could be tentatively identified, i.e. 125 steroids, 21 alkylphenols and 27 phthalates, at a confidence level of Tier 3. Finally, during untargeted screening of seawater samples, all target analytes were successfully detected, confirming that fragmentation occurred also in a salty matrix.
POSTER SESSIONS 1 AND 2 – Monday and Tuesday – all odd number posters will be on display.

POSTER SESSIONS 3 AND 4 – Wednesday and Thursday – all even number posters will be on display.

*AWARD WINNERS

PLANT, FOOD, ENVIRONMENTAL AND MICROBIAL

P-309 Lipid changes in different tissues of rats after chronic exposure to ambient fine particulate matter

PRESENTING AUTHOR: Ting-Zhen Chen, Institute of Environmental Health, National Taiwan University, Taiwan

CO-AUTHORS: Hao-Jan Liang, Sheng-Han Lee, Wen-Ling Chen, Tsun-Jen Cheng, Ching-Yu Lin

Fine particulate matter (PM2.5) is able to pass the respiratory barrier and further enter the circulatory system, and consequently spread to the whole body. PM2.5-induced toxicity has been correlated with oxidative stress, which may lead to lipid perturbation. Our previous studies have applied a lipidomic platform to investigate the effects of PM2.5 exposure on the pulmonary lipids in rats inhaled ambient air, and found significantly altered phosphatidylcholine (PC) levels might impair pulmonary surfactant functions. However, the lipid effects of PM2.5 on other organs have not been fully elucidated yet. In this study, we examined the lipid effects of chronic PM2.5 exposure on various organs using a rat inhalation model. Five male rats were continually whole-body exposed to ambient air containing PM2.5 from the outside of the Public Health building in Taipei city for 8 months, while five rats were inhaled filtered air. Blood samples and various tissues, including heart, liver, kidney, pancreas, spleen, testis and epididymis were collected. Then the phosphorylcholine-containing lipids from each organ were extracted for further ultra-performance liquid chromatography system coupled with triple quadrupole mass spectrometry (UPLC-MS/MS) analysis and partial least squares discriminant analysis (PLS-DA). In our PLS-DA models, the patterns of phosphorylcholine-containing lipid were altered in the testis, pancreas, heart, liver and kidney of rats exposed to PM2.5. Numerous phosphorylcholine-containing lipid species associated with exposure were identified. Results also showed decreased PC(16:0/18:1) was both observed in the serum and testis. Further studies to verify potential biomarkers for PM2.5 exposure are needed.

P-310 Metabolomics-based biomarker discovery for bee health monitoring: A proof of concept study concerning diagnosis of nutritional stress in Bombus terrestris

PRESENTING AUTHOR: Luoluo Wang, Ghent University, Belgium

CO-AUTHORS: Ivan Meeus, Caroline Rombouts, Lieven Van Meulebroek, Lynn Vanhaecke, Guy Smaghe

Bee pollinators are exposed to multiple natural and anthropogenic stressors. Understanding the effects of a single stressor in the complex environmental context of antagonistic/synergistic interactions, is critical to pollinator monitoring and may serve as early warning system before a pollination crisis. This study aimed at methodically improving the diagnosis of bee stressors using a simultaneous untargeted and targeted metabolomics-based approach. Analysis of 84 Bombus terrestris hemolymph samples selected 8 metabolites retained as potential biomarkers that showed excellent discrimination for nutritional stress. In parallel, 8 significantly altered metabolites, as revealed by targeted profiling, were also assigned as candidate biomarkers. Furthermore, machine learning algorithms were applied on the above-described two biomarker sets, whereby the untargeted eight components showed the best classification performance with sensitivity and specificity up to 99 and 100%, respectively. Besides, based on pathway and biochemistry analysis, we propose that gluconeogenesis contributed significantly to blood sugar stability in bumblebees maintained on a low carbohydrate diet. Taken together, this study demonstrates that metabolomics-based biomarker discovery holds promising potential for improving bee health monitoring and to identify stressor related to energy intake and other environmental stressors.

P-311 iNVERTOX: Characterising background metabolomic variability and subsequent alteration in the freshwater invertebrate, Gammarus pulex, upon exposure to psychoactive pharmaceuticals

PRESENTING AUTHOR: Thomas Miller, King's College London, United Kingdom

CO-AUTHORS: James I. MacRae, Nicolas R. Bury, Stewart F. Owen, Leon P. Barron

The (pseudo) persistence of emerging contaminants in the environment represents a risk for the organisms that are exposed to them. 'Omics technologies are providing a powerful tool within environmental toxicology to better understand the effects of these exposure scenarios. However, interpretation of metabolite data to understand toxicological responses is challenging. The variability in individual metabolomes for a species, or a "background metabolome" should be established to determine possible confounding factors such as age, sex and moulting (among others) that may influence data interpretation. Thus, we have characterised the effect of these factors on the metabolic variability in the freshwater invertebrate, G. pulex. Herein, an analytical method is presented for the extraction and non-target analysis of the metabolome in G. pulex. Briefly, a dual phase liquid extraction was used followed by HILIC-HRMS to enable detection of metabolic features extracted from individual animals. Animals collected from the field were analysed immediately and compared to animals that were extracted after a fixed period of acclimatisation to laboratory conditions or exposure to environmentally relevant concentrations of antidepressants. The results indicated that biological sex, moulting stage and acclimatisation period affected the metabolic variability and should be investigated to aid understanding of pathways involved in effect-based studies. Furthermore, it may be prudent to pre-select animals based on these factors to reduce inherent variability in the data. Overall, the characterisation of metabolic variance for invertebrates along with the use of metabolomics shows a very powerful approach for understanding adverse effects that may be associated with environmental contaminants.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

*AWARD WINNERS

PLANT, FOOD, ENVIRONMENTAL AND MICROBIAL

**P-312**

**Characterization of aerosol deposition on human organotypic respiratory epithelial tissue exposed at the air-liquid interface and metabolism assessment**

**PRESENTING AUTHOR:** Sandra Sendyk, Associate Scientist, Switzerland

**CO-AUTHORS:** Jesea Sabaratnam, Shoaib Majeed, Laura Ortega Torres, Stefan Frentzel, Anita Iskandar, Julia Hoeng, Arno Knorr, Catherine Goujon

Human organotypic respiratory epithelial tissue cultures are routinely used for in vitro toxicological assessment of biological impact upon exposure to cigarette smoke (CS) and aerosol from smoke-free products at the air-liquid interface. Metabolism of deposited compounds is a critical parameter to be considered for their bioavailability and assessment of potential toxicity. Nicotine is commonly used as a marker of exposure, and its metabolism pathway is well established. CS is a complex mixture of more than 6,000 compounds, a significant number of which have known toxicological effects and are associated with various smoking-related diseases. As CS or aerosol from smoke-free products represent a challenging matrix for in vitro testing and metabolite screening, a multi-compound method using dual-column liquid chromatography coupled to high-resolution accurate mass spectrometry was established. Nicotine and its major metabolites were quantified in extracts of organotypic respiratory epithelial tissue cultures following exposure to CS and aerosol from smoke-free products for 112 puffs. Quantification was performed by stable isotope-labeled internal standards for each analyte or analyte group. In total, three major metabolites of nicotine were identified, representing approximately 1% of the nicotine deposited on the investigated tissues. Additional exposure markers correlated with nicotine were investigated to better understand the deposition of aerosols and CS on organotypic respiratory epithelial tissue cultures.

**P-313**

**Toxicity and metabolomics of zebrafish exposed to per- and polyfluorinated alkylated substances and alternatives to select more environmentally compounds**

**PRESENTING AUTHOR:** Pim Leonards, Vrije Universiteit, Netherlands

**CO-AUTHORS:** Jessica Legradi

Per- and polyfluorinated alkylated substances (PFASs) have been widely used as organic surfactants in industrial and consumer products. While these applications made PFASs very appealing their properties make PFAS very persistent in the environment. In this study we performed a chemical alternatives assessment using metabolomics between PFOA and PFOS and alternative chemicals to be able to select environmentally friendly compounds. Zebrafish embryos (Danio rerio) were chronically and acutely exposed (0.1 µM, 1 µM, 10 µM) to PFOA and PFOs and its alternatives PFHxS, PFBS, siloxanes (D4, D5 and TMS), and GenX to study the mechanism of toxicity. No significant effects on mortality, visual developmental abnormalities, and swimming activity were observed for all compounds. Embryos were subjected to further investigation in an attempt to address potential genetic and metabolomic effects. Transcription of the DNA damage gene was significantly up-regulated by over 2-fold relative to the control vs. PFOA, PFHxS, PFOS and Genx. Interestingly, the lipid metabolism gene was up-regulated by over 2-fold in the embryos exposed to PFOS and GenX. These observations correspond well with the metabolomics data that showed the regulation of many lipids (PC, PE, TAG, SM). Based on the results of this study, alterations in lipid metabolism (glycerophospholipids) may be a metabolic pathway affected by both PFASs and their alternatives. GENX, as alternative to PFOA, displayed a pattern of similar activity as the PFASs. The alternatives D4, D5 and TMS appears to have a lower impact on metabolic pathways (e.g. lipids) than PFOA.

**P-314***

**Pre- and postnatal exposure to environmental pollutants alters lipid and polar metabolites profiles in non-obese diabetic mice**

**PRESENTING AUTHOR:** Tim Sinioja, Örebro University, Sweden

**CO-AUTHORS:** Johanna Bodin, Aidan McGlinchey, Daniel Duberg, Hubert Dirven, Hanne Friis Berntsen, Karin Zimmer, Unni Cecilie Nygaard, Matej Orešić, Tuulia Hyötyläinen

According to the World Health Organization, chronic non-communicable diseases, such as heart disease, stroke and diabetes, are causing up to 60% of annual global mortality. The incidence of these diseases is not only due to genetic factors, but also to, or in combination with, the environmental factors, which comprise both external and internal exposures. External exposure, for instance to environmental contaminants, affects the internal exposure, i.e. biological factors, such as metabolism, which in turn mediate risks of various diseases. However, little is known how the exposure to chemical pollutants affects the metabolome. In this project, we explored the lipid and metabolic changes in mice following exposure to a mixture of persistent organic pollutants (POPs) containing organochlorides, organobromides, and per- and polyfluoroalkyl substances. Prior to blood collection, non-obese diabetic mice were pre- and postnatally exposed to two different concentration levels of POPs. Lipidomic profiling of mice blood serum samples was carried out on UPLC-Q-TOF/MS, while polar metabolite profiling was conducted on GC-Q-TOF/MS. Significant changes in lipid and polar metabolite profiles were observed between mice in the control and treatment groups. The largest difference in metabolite regulation was detected between control and the high exposure group. In particular, many phospholipids and several triglycerides containing polyunsaturated fatty acids were down regulated, while tricarboxylic acid cycle metabolites were upregulated. Our findings suggest that alteration of the lipid profile in mice exposed to the POP mixture is similar to previously reported metabolic changes associated with higher risk of type 1 diabetes.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

*AWARD WINNERS

PLANT, FOOD, ENVIRONMENTAL AND MICROBIAL

P-315 High-resolution Mass Spectrometry for Monitoring Physiological Impacts and Biotransformation Products in Fish Exposed to Wastewater Effluent

PRESENTING AUTHOR: Ioanna Ntai, Thermo Fisher Scientific, United States

CO-AUTHORS: Jonathan Mosley, Marina Evich, Drew Ekman, Jenna Cavallin, Dan Villeneuve, Gerald Ankley, Tim Collette

High-resolution mass spectrometry is advantageous for both metabolomics analyses and monitoring contaminant biotransformation products in fish exposed to wastewater effluent. For the current study, we conducted exposures of male and female fathead minnows to wastewater effluent using an onsite, flow-through system providing real-time exposure at the Western Lake Superior Sanitary District (WLSSD) wastewater treatment plant in Duluth, MN, USA. Metabolomic changes in liver tissue and skin mucus were measured for fish exposed for 21 days to control water or control water mixed with treated wastewater effluent at levels of 5%, 20% or 100% effluent. Skin mucus metabolomic changes reflected, in part, processes by which the fish biotransformed xenobiotics in the effluent. Regression models built with liver data provide additional evidence that xenobiotic transformation processes are induced, while also shedding light on the sex-specific nature of these responses. The detection of sex-specific phase II transformation products (e.g., glucuronidated bisphenol A) of chemicals from the effluent in the fish skin mucus led to the development of a novel untargeted method to identify glucuronidated biotransformation products in fish bile. Utilizing traditional enzyme hydrolysis, high-resolution mass spectrometry-based untargeted metabolomics methods, and a structure-specific neutral loss-dependent MS3 fragmentation method with a Thermo Scientific Orbitrap ID-X Tribrid mass spectrometer, we demonstrate this method using bile from these treated wastewater effluent-exposed fish as a potential means of screening for relevant contaminants found in complex environmental mixtures.

P-316 1H-NMR Metabolomics Study of Arabidopsis Thaliana Exposure to PFOA and PFOS

PRESENTING AUTHOR: Liam O'Hara, University of Guelph, Canada

CO-AUTHORS: Julie Konzuk, James Longstaffe

Perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) are environmental contaminants originating from their use in industrial surfactants, textile finishes and flame retardants. Their widespread use has resulted in these compounds becoming ubiquitous environmental contaminants. The persistence of PFOA and PFOS poses an ecological and health risk due to movement up the food web through bioaccumulation. Non-targeted metabolomics provides an avenue to determine the subtle responses by plants when exposed to these compounds at environmental levels. This poster presents new work exploring the application of non-targeted metabolomics using nuclear magnetic resonance (NMR) to understand the effect of PFOA and PFOS contamination on plants. Arabidopsis thaliana was been chosen as the model organism, as previous studies have shown signs of oxidative stress at high concentrations of PFOA. Non-targeted metabolomics provided insight into changes expressed in the metabolism of the plants when exposed to environmentally relevant contamination. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to determine the variation in the metabolic profiles in A. thaliana as a response to PFOA and PFOS contamination. This method could potentially be used on a wide range of species to determine whether they show signs of exposure to PFOA or PFOS contamination at levels that may otherwise be difficult to monitor.

P-317 Quantitation of glyphosate and AMPA from microbiome reactor fluids

PRESENTING AUTHOR: Beatrice Engelmann, Department of Molecular Systems Biology, Helmholtz Centre for Environmental Research-UFZ, Germany

CO-AUTHORS: Katarina Fritz-Wallace, Stephanie S. Schäpe, Jannike L. Krause, Judith Pöppe, Gunda Herberth, Uwe Rösler, Nico Jehmlich, Martin v. Bergen, Ulrike Rolle-Kampczyk

Glyphosate is one of the most widely used herbicides and potentially able to affect the intestinal microbiota, since it inhibits the aromatic amino acid synthesis via the shikimate pathways which is also used by bacteria. Chemostat cultivation of intestinal microbiota is increasingly used as a model system and consequently methods for quantitation of glyphosate and its degradation product AMPA in microbiome model systems are needed. Hence, an optimized protocol for the analysis of both glyphosate and AMPA by simple extraction with methanol:acetonitrile:water (2:3:1), while omitting further enrichment steps, was established. Glyphosate and AMPA were separated by hydrophilic interaction chromatography (HILIC) and identified with a targeted MS/MS method on a QTRAP 5500 system (AB Sciex). The limit of detection (LOD) in extracted water samples was < 2 ng/ mL for both, glyphosate and AMPA. In complex intestinal medium the LOD was 2 ng/mL and 5 ng/mL for glyphosate and AMPA, respectively. The method was used to determine the glyphosate concentration in a bioreactor model of swine colon. Furthermore this method is compatible with the extraction protocol for an untargeted metabolomics analysis and feasible for different media used in microbiome reactors. The approach presented here allows the quantitation of glyphosate and AMPA in bioreactor fluids and thus enables studies on the metabolization of glyphosate and its impact on the intestinal microbiota.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

*AWARD WINNERS

PLANT, FOOD, ENVIRONMENTAL AND MICROBIAL

**P-318*** **Metabolomics approach to study the environmental impact and residues of biocontrol products (BP)**

**PRESENTING AUTHOR:** Mélina Ramos, PLS Université Paris: EPHE-UPVD-CNRS, USR 3278 CRIOBE, Université de Perpignan, France

**CO-AUTHORS:** Marie-Virginie Salvia, Delphine Raviglione, Mercè Llugany, Esther Badosa, Emilio Montesinos, Cédric Bertrand

Biopesticides or Biocontrol Products (BP) represents an interesting alternative to the conventional pesticides. However, there is a need of technical efficacy studies and ecotoxicological profile references. To date, the half-life, t1/2, was often used to study the fate of pesticides in environmental matrices. However, this value doesn't give any information regarding the formation of by-products and the effect on biodiversity. Consequently, an innovative approach based on metabolomics (LC-MS), the Environmental Metabolic Footprinting (EMF), was recently developed in the lab. On one hand, the EMF gives rise to a new integrative proxy, the resilience that corresponds to the time needed for the compound dissipation and its effects on the matrix (meta-metabolome). On the other hand, the EMF can be used in order to determine the preharvest interval (PHI) that corresponds to the time needed to have no residue (xenometabolome) difference between the treated sample and the control. The degradation of the BP on vine leaves was monitored. Vines were treated against powdery mildew with 2 fungicides BPs. The vine leaves were sampled at different time points between 2 treatments in order to study the BP degradation (kinetics). The extraction steps were optimized and the extracts were analyzed using a UHPLC-HRMS instrument. For now, only the xenometabolome was studied and the preliminary results showed a degradation kinetics for the 2 fungicides BP with a PHI between 4 and 10 days. The endometabolome is currently analyzed. The project lasts 3 years therefore the same study will be repeated and extended to other matrices.

**P-319*** **Characterization of aerosol-derived water-insoluble organonitrates collected during wintertime at urban sites in China and Korea**

**PRESENTING AUTHOR:** Kyoung-Soon Jang, Korea Basic Science Institute, South Korea

**CO-AUTHORS:** Mira Choi, Minhan Park, A Young Choi, Moon Hee Park, Gun Wook Park, Young Hwan Kim, Yujue Wang, Min Hu, Kihong Park

In this study, ambient fine particles (diameter less than 2.5 µm; PM2.5) were collected at urban cities in China and Korea (i.e., Beijing and Gwangju, respectively) during January 2018, and the dichloromethane (DCM) extracts of the PM2.5 samples were analyzed using an ultrahigh-resolution (UHR) Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometer to identify the molecular characteristics of organic aerosols collected during wintertime at both urban cities. The FT-ICR MS analysis of the water-insoluble organic fractions (WIOCs) revealed that CHO and CHON class species were occupied more than 90% of the total WIOCs. The haze events with high organonitrate proportions were observed at both sites, but the CHON proportions at Beijing site have no correlation with secondary ionic species and gaseous components, implying that the nitrogen-containing organics originate from primary sources. We also found that the proportion of CHON class species at Gwangju site positively correlates with the concentrations of gaseous nitric acid and ammonia, indicating that ambient nitrate and ammonia has a role in the atmospheric formation of nitrogen-containing organic compounds at the Gwangju site. Particularly, significant proportions of CHN compounds were observed at Beijing site, while negligible amounts of CHN was detected at Gwangju site. Following two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS) analysis identified the quinoline class compounds and the corresponding -CH2 homologous series from the WIOC at Beijing site. Interpretation of molecular changes of urban organic aerosols using an ultrahigh-resolution mass spectrometer and meteorological information could provide broad insight for understanding ambient organic aerosols.

**P-320*** **Equine atypical myopathy: Targeted metabolomic study**

**PRESENTING AUTHOR:** Radana Karlíková, IMTM, Palacky University, Olomouc, Czech Republic

**CO-AUTHORS:** Petr Jahn, Jitka Široká, David Friedecký, Marek Mech, Lucie Mádrová, Hana Janečková, Františka Hrdinová, Tomáš Adam

Equine multiple acyl-CoA dehydrogenase deficiency also known as atypical myopathy (AM), is a highly fatal muscle disease of grazing horses. This syndrome is accompanied by muscular weakness, acute myonecrosis and myoglobinuria, which in at least 75% of cases leads to death within 72 h. It is caused by ingestion of Acer Pseudoplatanus seeds containing hypoglycin A, whose active metabolite, the MCPA-CoA, is responsible for inhibition of FAD-dependent acyl-CoA dehydrogenases. The aim of this work was to compare the serum metabolomic profile of horses suffering from AM and controls and to confirm AM diagnosis in blood of newborn foal. Metabolomic analysis was performed using liquid chromatography with aminopropyl column coupled to tandem mass spectrometry (QTRAP 5500, AB Sciex). The metabolites were detected by multiple reaction monitoring in both positive and negative mode and statistically evaluated in R software. Analysis of specific biomarker MCPA-carnitine was performed by liquid chromatography-tandem mass spectrometry using the UltiMate 3000 system with BEH C18 column (50 mm, 1.7 µm, 2.1 mm) coupled to a triple-quadrupole mass spectrometer (Triple Quad 6500; SCIEX, Framingham, MA, USA). Significant differences were demonstrated in the concentrations of various glycine conjugates and acylcarnitines (C2–C26). Moreover, the concentrations of purine and pyrimidine metabolites, vitamins and selected organic and amino acids were altered in horses with AM. Metabolomic analysis of the foal's blood revealed increased concentrations of acylcarnitines and MCPA-carnitine consistent with metabolic profiles of blood from AM affected horses. The work was supported by the Czech Science Foundation Grant [18-12204S] and NPU I (LO1304)
*AWARD WINNERS

PLANT, FOOD, ENVIRONMENTAL AND MICROBIAL

P-321

Optimization of comprehensive two-dimensional liquid chromatography (LCxLC) for the lipidomic analysis of zebrafish

PRESENTING AUTHOR: mengmeng xu, VU University, Netherlands

CO-AUTHORS: Pim Leonards

Background: Liquid chromatography (LC) coupled to mass spectrometry (MS) has become state of the art in lipid analysis. Reverse-phase (RP) LC, normal-phase (NP) LC, and hydrophilic interaction (HILIC) phases are often used. However, one-dimensional LC (1DLC) is not sufficient to cover the lipidome because of co-elution. Two-dimensional LC (2DLC) improves the separation power before detection with MS. Methods: The orthogonality of separation mechanisms is an important aspect in 2DLC (LC×LC). HILIC and RPLC were selected due to their solvent compatibility. A RPLC C18 column (2.1 mm × 100 mm, 2.6 µm) as the first dimension column, and a HILIC column (2.1 mm × 50 mm, 1.7 µm) as second dimension column were optimized for the separation of lipids. The combination of HILIC×RPLC was tested as well. A QTOF MS system was used for the detection of the lipids. Zebrafish eggs and larvae were analysed. Result: RPLC separated the lipids depending on the hydrophobic character and the lipids were separated based on the fatty acyl chain length and the number and positions of double bonds. In contrast, the separation of lipids by HILIC was based on the differences in the polar head groups of the specific lipid classes. The 2DLC analysis of zebrafish samples showed the separation of various classes of lipids (e.g. LPC, PC, PE, PI, PA, PS, DAG, TAG), and more than 1000 lipids were detected. The separation was much improved compared to 1DLC. Comprehensive 2DLC is a promising method for lipid characterizations of complex biological samples.

P-322

Insights into the toxicity of propazine on freshwater microalgae Chlorella Vulgaris (CV) and Scenedesmus Obliquus (SO):
Untargeted Metabolomics via LC-QTOF

PRESENTING AUTHOR: Hiranya Dayal, National University of Singapore, Singapore

CO-AUTHORS: Sam Li Fong Yau

This study aims to utilize untargeted metabolomics using LC-QTOF to elucidate the impact of propazine, on freshwater microalgae. Freshwater microalgae are a group of phytoplanktons, popularly employed in biomonitoring and ecotoxicology studies. The toxicity of propazine was studied at a range of 10 µg/l -10 mg/l over 5 days on two freshwater microalgae, Chlorella vulgaris (CV) and Scenedesmus obliquus (SO). The growth rate of CV showed a gradual dose-dependent decline, while that of SO was significantly inhibited from 5 mg/l of propazine. Preliminary results reveal that in CV, the exposure resulted in a slow increase of monogalactosyldiacylglycerol (MDCG) and digitalactosyldiacylglycerol (DDCG) levels with time, that may be attributed to enhanced membrane lipid synthesis. However, there was an observed decrease in MDCG and DDCG in SO from 100 µg/l that reached significance at 5 mg/l, which can be correlated with the observed growth inhibition at the same exposure level. Fluorescence-based assay for reactive oxygen species (ROS) further showed a gradual decrease in cellular ROS for CV with propazine exposure indicating that while growth rate of CV was slow with propazine exposure, some protection from further oxidative stress was provided with reinforcement of their cell membrane. Meanwhile, a significant increase in ROS was observed in SO from 5 mg/l propazine implying its limitations in tolerating environmental stress due to propazine. The results demonstrate that different microalgae have differing tolerances to propazine exposure, and reveal metabolomics as a tool to complement biochemical assays in assessing the environmental impact of herbicides on microalgae.

P-323

Framework for damage assessment of oryza sativa after chemical accident using metabolic effect level

PRESENTING AUTHOR: Woojung Kim, School of Earth Sciences and Environmental Engineering, Gwangju Institute of Science and Technology,
South Korea

CO-AUTHORS: Sangdon Kim

As the changes in metabolome reflect mode of action specific cellular responses after chemical exposure, post-accident damage assessment based on metabolomics approaches emerged as a better alternative compared with physiologic approaches. The ministry of environment tried to characterize of plant damage by introducing metabolomics. However, target metabolite selection process was unclear and the exposure method did not reflect the chemical accident scenario, so the results had not been put to practical use. Thus, untargeted metabolomics and vapor exposure chamber were introduced in this study to overcome the limitations of existing research. Toluene was selected by taking into account both accident frequency and hazards. The oryza sativa was exposed in vapor exposure chamber. The metabolic responses of plants were analyzed by LC-QTOF-MS based untargeted metabolic profiling and evaluated by multivariate statistical analysis and readable endpoints. The exposed concentration-based and recovery time-based metabolic response patterns were analyzed by principal component analysis and partial least squares discriminant analysis. In addition, the weight of shoot and root, the chlorophyll contents of leaves were assessed. Overall, the results of multivariate statistical analysis demonstrated a number of potential biomarkers that were characterized by metabolomic approach and provided an insight into quantitative chemical accident damage assessment.
*AWARD WINNERS

PLANT, FOOD, ENVIRONMENTAL AND MICROBIAL

**P-324** Metabolomics reveals kidney damage in mice exposed to thirdhand smoke

PRESENTING AUTHOR: Carla Merino Ruiz, MIL@B - CIBERDEM - URV, Spain

CO-AUTHORS: Sara Samino, Beatrix Paton, Neema Adhami, Manuela Martins-Green, Xavier Correig, Noelia Ramírez

Thirdhand smoke (THS) is a poorly understood pathway of tobacco exposure that is produced by the deposition and ageing of tobacco smoke particles and toxicants on surfaces, becoming progressively more toxic. Recent studies revealed the harmful health effects of THS exposure, but its effects on the kidney have not been studied yet. We applied untargeted metabolomics and lipidomics of the kidney and metabolomics of urine from mice exposed to THS under conditions that mimic the exposure in smokers' homes, using a multiplatform approach (UHPLC-QTOF and GC-QTOF). Kidneys from THS-exposed mice had significantly lower levels of betaine, which is a well-known kidney osmoprotectant. Additionally, different metabolites from pyrimidine metabolism and intermediates of alanine, aspartate and glutamate metabolism were also depleted in THS-exposed kidneys. Besides, several metabolites of the kynurenine pathway related to chronic kidney disease were found upregulated in urine of THS-exposed mice. Lipidomics analysis of kidneys showed that levels of different acylcarnitines, which together with carnitine are important in energy metabolism, and several lipids, such as glycerophosphocholines and sphingomyelins, were considerably lower in kidneys of THS exposed mice, leaving an impairment in energetic lipid metabolism. Interestingly, not all the metabolites altered as a result of THS exposure returned to near-control levels after an antioxidant treatment, indicating that the harmful effect of THS cannot easily be reverted. This study demonstrates for the first time that THS exposure is a latent risk to the development of kidney disease and, if confirmed in humans, would provide major evidence to enforce tobacco control policies.

**P-325** Metabolic effects of a perinatal exposure to a low-dose pesticide cocktail in mice: sexual dimorphism and impact on the gut microbiota

PRESENTING AUTHOR: Lorraine Smith, INRA Toxalim, France

CO-AUTHORS: Smith Lorraine, Klement Wendy, Barretto Sharon, Lasserre Frederic, Lukowicz Celine, De-Bock Frederic, Maillard Benjamen, Patris Bruno, Jamin Emilien, Debrauwer Laurent, Mselli-Lakhal Laila, Guillou Herve, Marchi Nicolas, Gamet-Payrastre Laurence, Ellero-Simatos Sandrine

Epidemiological evidence suggests a link between pesticide exposure and development of metabolic diseases. We have shown a sexual dimorphic impact of a chronic dietary exposure to a low-dose cocktail of 6 pesticides (boscalid, captan, chlorpyrifos, thiofanate, thiacloprid, and ziram) on glucose homeostasis and gut microbiota in adult mice. Here, we aimed to investigate the consequences of a perinatal exposure to the same cocktail. Pesticides were incorporated in a standard chow at doses exposing mice to the tolerable daily intake of each pesticide. C57BL6J female mice were exposed during gestation and lactation. After weaning, pups were fed a standard chow diet for 4 months, and then challenged or not with a high-fat for 2 months. We assessed metabolic parameters throughout the experiment. After 6 months, we evaluated host metabolism as well as gut microbiota metabolism using 1H-NMR-based metabolomics. Before the metabolic challenge, no difference was observed in metabolic parameters between exposed and non-exposed pups. However, the urinary and fecal metabolomic profiles were distinct and pesticide-induced perturbations were sex-specific. Trimethylamine, a host-gut microbiota cometabolite, was lower in urine of exposed, compared to unexposed males, while it was higher in urine of exposed females. Fecal metabolic profiles were also significant different in exposed vs. non-exposed males. After HFD, no difference was observed anymore in urinary metabolic profiles. However, fecal metabolic profiles were strongly altered in exposed vs. non-exposed females. Our results suggest that a perinatal exposure to pesticides could influence the gut microbiota metabolism with a significant diet-pesticide-sex interaction.

**P-326** Advancing on the Chemical Characterization and Health Effects Associated to House Dust Exposure: Thirdhand Tobacco Smoke as Case Study

PRESENTING AUTHOR: Noelia Ramirez, Institut d'Investigacio Sanitaria Pere Virgili-URV-CIBERDEM, Spain

CO-AUTHORS: Sonia Torres, Carla Merino, Beatrix Paton, Sara Samino, Neema Adhami, Manuela Martins-Green, Emma L. Schymanski, Xavier Correig

House dust acts as a sink and a repository of toxicants, which persist during long periods of times or react with atmospheric oxidants to form secondary toxicants. Given people expend over 90% of their time indoors, a more accurate characterization of house dust chemical composition might provide valuable information about human exposome. A particular case of dust contamination is thirdhand tobacco smoke (THS), a novel and poorly understood pathway of tobacco exposure that is produced by the deposition and ageing of tobacco smoke particles and toxicants in surfaces and dust. This aged tobacco smoke becomes increasingly toxic with age, re-emitted into the air or react with other chemicals in the environment to yield new toxicants, including carcinogens. Although the increasing evidences of THS hazards, their accurate chemical characterization and the specific cellular and molecular consequences of THS exposure remain to be fully elucidated. We have analyzed smoker' and non-smokers' house dust samples using metabolomics-style non-target identification to identify masses with significant difference between the sample groups, followed by annotation using the in silico fragmenter MetFrag coupled to the CompTox Chemicals Dashboard and PubChem. Further, we have combined non-targeted metabolomics applied to two THS-exposed animal models (C57BL/6 mice exposed to THS under conditions that mimic exposure of humans in homes of smokers, and zebrafish embryos exposed to tobacco-specific nitrosamines), as well as, targeted analysis of neurotransmitters and specific biomarkers of tobacco exposure in children's urine exposed and non-exposed to THS. The results presented here provide key evidences about THS health hazards.
PLANT, FOOD, ENVIRONMENTAL AND MICROBIAL

P-327 **Metabolomics in Industrial Research**

**PRESENTING AUTHOR:** Regine Fuchs, BASF Metabolome Solutions GmbH, Germany

**CO-AUTHORS:** Thomas Ehrhardt, Volker Haake, Tilmann Walk

BASF Metabolome Solutions GmbH - formerly known as metabolomics GmbH - provides mass spectrometry-based analytics, data interpretation and plant testing in the BASF Bioscience research platform since more than 20 years. With our competence in metabolomics, biological analytics and plant technologies we support innovation in agriculture, nutrition and industrial applications with mode of action analysis, biomarker identification and special metabolite analytics like volatile or wax analytics. Here we present how this integrated platform is applied for the toxicological evaluation of industrial chemicals.

P-329 **Development of a food exposure and urine sampling strategy for dietary exposure biomarkers in free-living individuals using high resolution metabolite fingerprinting and targeted quantification**

**PRESENTING AUTHOR:** Amanda Lloyd, Aberystwyth University, United Kingdom

**CO-AUTHORS:** A.J. Lloyd, T. Wilson, N.D. Willis, L. Lyons, H. Phillips, L. Xie, E. Holmes, G. Frost, K. Tailliart, M. Beckmann, J.C. Mathers, J. Draper

Dietary choices modulate the risk of chronic diseases and improving diet is a central component of public health strategies. Food-derived metabolites present in urine could provide objective biomarkers of dietary exposure when coupled with self-reported diet records. To assist biomarker validation we developed a food intervention strategy mimicking a typical diet with different food presentations, cooking methods and processing within complex meals and assessed urine sampling protocols potentially suitable for future deployment of biomarker technology. Six different menu plans representing comprehensively a typical diet that were split into two dietary experimental periods. Free-living adult participants (n=15 and n=36, respectively) were provided with all their food over a period of 3 consecutive days. Multiple spot urine samples were collected and stored at home. Flow Infusion-High Resolution Fingerprinting using Orbitrap MS coupled with High Performance Computer-enabled multivariate classification and feature selection were used to explore the composition of spot urine samples collected throughout the day. Biomarkers were validated using Ultra High Performance Liquid Chromatography quantification, using chemical standards. We successfully implemented a food exposure and urine sampling strategy for dietary exposure biomarker validation in free-living individuals. Biomarker performance was tested with different food formulations and processing methods involving meat, wholegrain and fruits/vegetables. Additionally, novel biomarkers were identified for foods where biomarkers have yet to be discovered in relation to the UK government healthy eating policies. Spot urine samples, together with robust dietary biomarkers that report multiple components of the UK diet should allow routine dietary exposure monitoring in large epidemiological studies.

P-330 **Investigation of compounds responsible for the flavor of Peruvian chocolate from fine flavor cocoa**

**PRESENTING AUTHOR:** Stephanie Michel, ICOBA - PUCP, Peru

**CO-AUTHORS:** Alfredo Ibañez Gabilondo, Madina Mansurova

Flavor is one of the most important characteristics of chocolate, besides being a key aspect to determine the price that the consumer is willing to pay. Currently, two types of cocoa beans have been characterized according to their profile of flavor and aroma, (1) the ordinary and (2) the fine flavor cocoa (FFC). In this project we have investigated how the flavor precursors presented in Peruvian FFC chocolate are transformed during each of the stages of chocolate manufacturing. We have identified eleven chemical compounds responsible for the fine flavor of Peruvian chocolate, and have analyzed their development during the main stages of chocolate manufacture using solid phase microextraction coupled to gas chromatography (HS-SPME-GC-MS) and direct analysis in real time (DART-MS). With this knowledge we can understand the chemistry of the Peruvian chocolate manufacturing, and establish a standardized manufacturing quality control protocol, that allows to local producers to improve the quality of their production.

P-331 **High-efficient and High-throughput volatile flavor analysis of fermented seasonings using SA-SBSE**

**PRESENTING AUTHOR:** YOKO IJIMA, Kanagawa Institute of Technology, Japan

**CO-AUTHORS:** Azusa Miwa, Hikaru Inagaki, Yusuke Ito, Kikuo Sasamoto, Takeharu Nakahara, Nobuo Ochiai

In food metabolomics, specific food samples are frequently analyzed to determine the relationship between metabolome and sensory evaluation data, thereby establishing their flavor or nutritional properties, and optimal processing conditions. In Japan, fermented seasonings, such as soy sauce, miso paste and mirin (sweet rice wine), are very popular and have become particularly indispensable for the traditional Japanese cuisine. These seasonings have complex flavor properties, which are determined using several parameters derived from their materials, microorganism strains, fermentation conditions and maturation periods. Further, headspace analysis using direct extraction or solid-phase microextraction is a well-known, high-throughput, analytical method for volatile metabolomics. However, fermented seasonings contain several semipolar, odor-active volatiles that cannot be efficiently extracted from the headspace vapor phase, indicating that the volatile composition obtained from headspace extraction does not sufficiently reflect actual odor profiles. In the present study, we developed a new high-efficiency and high-throughput volatile flavor analysis using SA-SBSE (solvent-assisted stir bar sorptive extraction) for fermented seasonings. First, flavor volatiles were extracted from each sample using SAFE (solvent-assisted flavor evaporation), which is known as the most reliable flavor analysis extraction method. Odor-active volatiles were then screened using GC-Olfactometry. Next, we confirmed that SA-SBSE could extract the volatiles with high-efficiency, recovering >80% of the compounds detected using SAFE. Therefore, we suggest that SA-SBSE is suitable for flavor metabolomics of fermented seasonings owing to its extraction reproducibility and quantitativity.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

*AWARD WINNERS

PLANT, FOOD, ENVIRONMENTAL AND MICROBIAL

P-332 Discovery of Intake Biomarkers for Different Heat-Processed Potato Products by Metabolomics

PRESENTING AUTHOR: Xiaomin Zhou, University of Copenhagen, Denmark

CO-AUTHORS: Cătălina S. Cuparencu, Natalia Vazquez Manjarrez, Gözde Gürdeniz, Lars Ove Dragsted

**Background:** Potato is an important staple food in human nutrition, however, except for its contribution to energy and effects related to resistant starch the role of potato in human health is still debated. Biomarkers of food intake (BFIs) may be viewed as complementary tools for traditional dietary assessment tools. Therefore, we aimed to identify urinary exposure markers of potato products (cooked potato, chips and French fries). **Methods:** A randomized controlled single-blinded cross-over meal study was conducted. Four different intervention meals were prepared: boiled rice, boiled potato, chips and French fries. Discriminating features in urine were selected by the use of ANOVA and PLSDA as well as kinetics of excretion. **Results:** Thirty putative BFIs were found for heat-processed potato products which can differentiate between cooking and deep-cooking methods, two putative BFIs for potato in general and one for rice. Five of the 30 BFIs were identified or putatively annotated as conjugates of furaneol and 2,4-dihydroxy-2,5-dimethyl-3(2H)-furanone and hippuric acid. Among the rest were a range of conjugated compounds from Maillard reactions, and the proposed precursors were furans, pyrroles or pyridines. **Conclusion:** The study demonstrates that it is possible to find biomarkers for intake of potato products in urine samples. Combinations of identified or putatively annotated markers are proposed as potentially specific for intake of potato differentiated by different cooking processes. **Perspective:** Further studies are needed to identify the unknown biomarkers and to assess the robustness, reliability and repeatability in cross-sectional settings of the candidate heat-processed potato intake biomarkers identified in this study.

P-333 Metabolic profiling for utilization of soybean residues after protein extraction with different temperatures

PRESENTING AUTHOR: Hyejin Hyeon, Incheon National University, South Korea

CO-AUTHORS: Cheol Woo Min, Sun Tae Kim, Jaeho Cha, Keumok Moon, Jae Kwang Kim

Soybean is well known as one of the most important ingredients due to their enriched nutritional compounds such as functional peptides, carbohydrates, fatty acids and flavonoids. In order to use soybeans as principal sources of protein, novel aqueous processes for protein purification have been developed. However, these techniques have to be simultaneously concerned about the use of remained residues after protein extractions. The aim of this study is to reveal availability of soybean residues extracted at three different temperatures; 4°C, 25 °C and 55°C. Metabolic profiling with gas chromatography-mass spectrometry (GC-MS), GC-time of flight (TOF) MS and GC-flame ionization detector (FID) was conducted to investigate nutritional quality analysis of soybean residues. As a result, 64 metabolites including lipophilic compounds (policosanols, tocopherols and sterols), hydrophilic compounds (organic acids, amino acids, sugars and amine) and fatty acids were identified. Univariate and multivariate statistical analysis such as partial least-squares discriminate analysis (PLS-DA), hierarchical cluster analysis (HCA) and analysis of variance (ANOVA) showed that soybeans extracted at 55°C were notably distinguished with 4°C and 25°C. The significantly contributed metabolites for the discriminations were 8 amino acids, 7 organic acids, 3 sugars and 2 other compounds. This study represented that lots of essential and nonessential amino acids were accumulated by warm water extraction and galactose was interestingly increased by degradation of oligosaccharides known as anti-nutrients. Considering the nutritional effects of 55 °C extracted soybean residues, they expected to be used as feed for livestock to increase their market value.

P-334 Metabolite characterization for fermented rice koji by DOM (degree of milling)

PRESENTING AUTHOR: Sunmin Lee, Konkuk University, South Korea

CO-AUTHORS: Da Eun Lee, Digar Singh, Choong Hwan Lee

Koji, being an essential component or starter for numerous fermented foods and beverages, was utilized largely in food fermentative bioprocesses. A time-correlated metabolomic profiling was performed for fermented rice koji made using substrates with varying degree of milling (DOM). Overall, 54 primary and 13 secondary metabolites were selected significantly discriminant (VIP > 1, p < 0.05) among different koji samples by GC-MS and LC-MS. A higher abundance of carbohydrate (sugars, sugar alcohols, organic acids, phenolic acids) and lipid (fatty acids, lysophospholipids) metabolic intermediates with enhanced hydrolytic enzymes were observed for koji with rice's DOM 5-7. Conversely, functional metabolites such as flavonoids and phenolic acids, were relatively higher in koji with substrate's DOM 0, followed by DOM 5 > DOM 7 > DOM 9, 11, at 96 h. The grain milling significantly affected titratable acidity (DOM 0, 5 > DOM 7 > DOM 9, 11) and amino type nitrogen contents (DOM 5, 7 > DOM 0, 9, 11) in koji. In conclusion, the rice substrate preprocessing between DOM 5-7 was potentially ideal, with the end product being rich in distinctive nutritional and functional metabolites. The study rationalizes the grain preprocessing steps vital for commercial koji making.
PLANT, FOOD, ENVIRONMENTAL AND MICROBIAL

P-335
Mass Spectrometry-Based Untargeted Metabolomics and Alpha-glucosidase Inhibitory Activity of Reishi (Ganoderma lingzhi) during Growth Stages

PRESENTING AUTHOR: Dedi Satria, Kyushu University, Japan

CO-AUTHORS: Dedi Satria, Sonam Tamrakar, Hiroto Suhara, Shuhei Kaneko, Kuniyoshi Shimizu

Lingzhi (Chinese) or reishi (Japanese) is a Ganoderma mushroom species which has wide range of bioactivities. Analysis of metabolites changes during growth stages of lingzhi are important to understand underlying mechanism of its biosynthesis as well as bioactivity. It may provide valuable information for cultivation efficiency of lingzhi. In this study, mass spectrometry based untargeted metabolomics was carried out to analyze the alteration of metabolites during subsequent growth stages of lingzhi. Eight growth stages were categorized on the basis of morphological changes, starting from mycelium stage to post-mature stage of lingzhi. GC-MS and LC-MS analyses along with multivariate analysis of lingzhi growth stages were performed. Amino acids, organic acids, sugars, polyols, fatty acids, fatty alcohols, and some small polar metabolites were extracted as chemical markers from GC-MS analysis; while, lanostane-type triterpenoids were annotated from LC-MS analysis of lingzhi. The markers from untargeted analysis of lingzhi growth stages were correlated with alpha-glucosidase inhibitory activity. The current result shows that some metabolites are involved in the growth process and alpha-glucosidase inhibitory activity of lingzhi.

P-336 Comprehensive metabolomic analysis of sesame seeds

PRESENTING AUTHOR: Bo Mi Lee, Kookmin University, South Korea

CO-AUTHORS: Eun Mi Lee, Byeung Kon Shin, Dong Jin Kang, Do Yup Lee

Sesames are enriched with amino acid, essential fatty acids, carbohydrates, and hydroxy acid. The nutritional characteristics are mainly influenced by a range of environmental factors (e.g. climate and soil) as well as genetic factors. In current study, we analyzed the integrated metabolic profiles of sesame seeds grown in 29 Korean domestic provinces, 5 Chinese provinces, and 4 other countries (Nigeria, Ethiopia, India, and Pakistan). A total of 243 primary and secondary metabolites were acquired using gas-chromatography time-of-flight mass spectrometry (GC-TOF MS) and liquid-chromatography Orbitrap mass spectrometry (LC-Orbitrap MS). PLS-DA model primarily discriminated the sesames cultivated in Korea from Chinese one and those of 5 other countries. Based on the model, variable importance in projection (VIP) analysis prioritized 7 metabolites; glycerol, D-raffinose, DL-carnitine, histamine, 9-oxo-10(E), 12(E)-octadecadienoic acid, glycerophospho-N-palmitoyl ethanolamine, and palmitic acid. Receiver operating characteristic (ROC) analysis validated the discriminant power in area under the curve (AUC) ranged from 0.916 – 0.996. Particularly, the Korean sesames were best featured by higher abundances in a range of amino acids relative to Chinese and other countries’ sesame. Further detailed interrogation was performed on 29 Korean sesames to examine if metabolomic profiles can distinguish the subtle regional differences. Hierarchical clustering analysis (HCA) proposed unbiased clusters of the sesames according to longitudinal coordination. The pathway overrepresentation analysis identified region-specific chemical categories as follows: aminoacyl-tRNA biosynthesis, galactose metabolism, alanine-aspartate-glutamate metabolism, and pentose-glucuronate interconversions. This study can be generalized under more controlled experiment, and applied to authentic decisions for cultivation origin of domestic agricultural products.

P-337 Pigmented sorghum polyphenols as potential inhibitors of amylolytic enzymes: An in vitro study combining starch digestion and untargeted metabolomics

PRESENTING AUTHOR: Gabriele Rocchetti, Università Cattolica del Sacro Cuore, Italy

CO-AUTHORS: Gianluca Giuberti, Marco Trevisan, Luigi Lucini

Polyphenols characterizing pigmented sorghum (PS) flours were in vitro evaluated as possible modulators of the activity of starch digestive enzymes. Flours from five PS varieties were analyzed after cooking and compared to white sorghum (WS) flour. An untargeted metabolomic approach comprehensively depicted the bound and free phenolic composition of each flour, highlighting a high distribution of flavonoids (i.e., anthocyanins, flavanol and flavone equivalents) and phenolic acids, with differences across samples. All PS flours were characterized by greater tannin and kafirin contents when compared to WS. Following in vitro digestion, all cooked PS flours showed greater resistant starch (RS) (from 4.2 to 21.4 g/100 g dry matter), as well as lower starch hydrolysis index (HI) when compared to WS. Multivariate statistics following untargeted metabolomics showed that anthocyanins and flavanol equivalents characterizing PS were the most discriminant compounds during the in vitro digestion. In addition, kafirin and total tannin contents (on raw ingredients) along with the anthocyanin profiles and the RS (on cooked samples) were negative correlated with HI. Therefore, PS flours might be useful in the formulation of foods characterized by likely functional properties.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

*AWARD WINNERS

PLANT, FOOD, ENVIRONMENTAL AND MICROBIAL

P-339

Untargeted metabolomics for the investigation of fish intake biomarkers

PRESENTING AUTHOR: Xiaofei Yin, University College Dublin, Ireland

CO-AUTHORS: Helena Gibbons, Gary Frost, Lorraine Brennan

Background: Fish intake has been reported to associate with certain health benefits; however accurate assessment of fish intake is still problematic. The objective of this study was to identify fish intake biomarkers and examine their potential for quantifying intake. Materials and methods: In the NutriTech study, ten participants were randomized into fish group and consumed increasing quantities (88 to 412 g/day) of fish for three days/ week during three weeks. Fasting and postprandial urine samples were analyzed by 1H NMR spectroscopy and LC-MS. Dietary biomarkers were identified by multivariate data analysis and confirmed in National Adult Nutrition Survey (NANS) cohort. A calibration curve was developed and used to determine fish intake based on urinary biomarker levels. Results: Multivariate data analysis of fasting urine samples collected in NutriTech study revealed good discrimination between high (412 g/day) and low (88 g/day) fish intakes. Trimethylamine-N-oxide (TMAO), dimethylamine and dimethyl sulfone were identified and displayed significant dose response with fish intake (P < 0.05). Furthermore fish consumption yielded greater increase in urinary TMAO compared to red meat. In the NANS cohort, urinary TMAO levels were significantly higher in fish consumers compared to non-consumer (P < 0.01). However, the overall correlation between fish intake and TMAO (0.148, P < 0.01) were poor. LC-MS analysis revealed prominent increases in indoxyl sulfate and p-cresol sulfate excretion after high fish intake. Conclusion: Urinary TMAO displayed strong dose-response relationship with fish intake; however, use of TMAO alone is insufficient to determine fish intake in a free living population.

P-340

Screening of Biomarkers of Citrus unshiu Consumption Using Metabolomics

PRESENTING AUTHOR: Hisami Yamanaka-Okumura, Tokushima University, Japan

CO-AUTHORS: Hisami Yamanaka-Okumura, Akiyoshi Hirayama, Aina Imai, Hiroshi Tatano, Daisuke Kajiura, Tomoyoshi Soga, Masaru Tomita

Citrus unshiu is the most popular citrus in Japan. There are still no study biomarkers of the consumption of citrus using Citrus unshiu, necessitating their further screening. The present study aimed to investigate biomarkers and compare metabolites in plasma and urine following the consumption of several foods. The subjects were eight healthy men (age: 23.9 ± 1.1 years, BMI: 21.1 ± 2.6 kg/m²) who participated in a randomized crossover trial. The test foods were apple, Citrus unshiu, broccoli, and seaweed (100g of each) that were consumed a single time a week. Metabolomic analysis was conducted on plasma samples from before consuming the test food and from 2 h after consumption and on urine samples from before consumption, 2 h and 4 h after consumption using CE-TOFMS. On analyzing the test foods, concentrations of Proline betaine were significantly higher in Citrus unshiu compared with concentrations following the consumption of the other foods in both of the plasma samples and urine samples. Of these, concentrations of Proline betaine and trans-Aconitate were significantly increased following the consumption of Citrus unshiu compared with those following the consumption of the other foods at 2h and 4h in urine. Candidate biomarkers of Citrus unshiu consumption were Proline betaine in plasma samples and urine samples. We showed that Proline betaine was a biomarker of Citrus.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

*AWARD WINNERS

PLANT, FOOD, ENVIRONMENTAL AND MICROBIAL

P-341 Identification of Flavonoid Metabolites in Urine and Plasma of Korean Fermented Soybean using an untargeted Metabolomic Approach

PRESENTING AUTHOR: Hwan-hee Jang, National Institute of Agricultural Sciences, South Korea

CO-AUTHORS: Hwan-hee Jang, Heon-woong Kim, Hwayoung Noh, Su-yeon Cho, Hyeon-jeong Kim, Sung-Hyun Lee, Marc Gunter, Heinz Freisling, Jeong Sook Choe, Augustin Scalbert, Jung-bong Kim

Fermentation may enhance nutritional and functional properties of food by increase of bioactivity or bioavailability during the process, which may have preventive effects on human disease. The study aimed to identify flavonoid metabolites of fermented soybean using an untargeted metabolomic approach and to investigate the effect of fermentation on bioavailability of flavonoids. In the cross-over intervention study with 10 study participants, standardized meals with fermented soybean (Cheonggukjang, fermented by Bacillus subtilis) and non-fermented soybean were served with a 1-week wash-out period in a randomized controlled trial. Flavonoids in each freeze-dried tested meal and flavonoid metabolites in 24-hour urine and blood samples collected before and after the consumption of each tested meal were measured by UPLC-DAD-QTOF/MS. Eighteen isoflavones, including genistein, daidzein, glycetein, and its glycosides, were identified in both tested meals. In the fermented food, levels of simple glycoside forms (e.g. daidzin and genistin) with high bioavailability were higher than those in the non-fermented food, which might be explained by the degradation of malonylglucosides during the fermentation of soybean. Fourteen metabolites including 7 glucuronides, 4 sulfates, and 3 sulfoglucuronides formed by conjugating enzymes were identified in urine and plasma, but equol and equol conjugated metabolites were not detected. The level of genistein 4',7-di-O-glucuronide was higher in the plasma collected after intake of fermented soybean when compared to non-fermented soybean. The results of the study may contribute to understanding the potential health effects of fermented foods by modifying the bioavailability and biological activity of soybean bioactive compounds.

P-342 Effects of organic acid salts and light treatment on policosanol concentration in Oat Sprouts (Avena sativa. L): development of a potent functional food

PRESENTING AUTHOR: Hyun Young Kim, National Institute of Crop Science, South Korea

CO-AUTHORS: Hyeonmi Ham, Woo Duck Seo, Mi Ja Lee, Ji-Eun Ra, Hye-Young Seo, Kwang-Sik Lee, Ki-Chang Jang, Ki Do Park

Elicitors are agents, such as chemical compounds, that trigger defense responses in plants, including the synthesis of secondary metabolites, such as policosanol. Policosanol consumption has various positive physiological effects in humans such as antioxidant capabilities, cholesterol-lowering activities, and improved liver function. Oat sprouts are a natural source of policosanol, making them a popular health food. The objective of this study was to test whether treatment of oat sprouts with organic acid salts and UV as an elicitor increases policosanol content compared with a control group of sprouts grown in water. During the growing phase, oat sprouts were treated with 0.1% sodium chloride (NaCl), 0.1% acetic acid, and UV360 bulbs at a wavelength of; samples were analyzed for policosanol content 10 days after germination using GC/MS. Results showed that 0.1% sodium chloride and 0.1% acetic acid treatments produced a policosanol concentration of 681.84 mg / 100 g and 736.4 mg / 100 g, respectively, compared with a water-grown control concentration of 554.8 mg / 100 g. The policosanol content in UV360-treated oat sprouts was also higher than that of the control sprouts at 651.4 mg / 100 g. In conclusion, cultivation of oat sprouts with organic acid salt supplementation and UV light treatment can significantly increase the levels of policosanol. This protocol could be used to develop a potent functional food with increased market value.

P-343 Spot and cumulative urine samples are suitable replacement sample types for 24-hour urine samples for objective measures of dietary exposure using metabolite biomarkers

PRESENTING AUTHOR: Thomas Wilson, IBERS, Aberystwyth University, United Kingdom

CO-AUTHORS: Isabel Garcia-Perez, Joram M Posma, Amanda Lloyd, Edward S Chambers, Kathleen Tailliart, Hassan Zubair, Manfred Beckmann, John C Mathers, Elaine Holmes, Gary Frost, John Draper

Self-reporting of dietary intake can be inaccurate and is prone to inherent bias. Measurement of multiple food intake biomarkers in urine may offer an objective method for monitoring dietary intake when used in conjunction with self-reported measures. In a randomised, controlled, crossover trial; participants four different diets (one per stay) over a 72 hour period, each with a stepwise variance in concordance with the World Health Organisation (WHO) healthy eating guidelines. Spot urine samples and cumulative urine samples were collected daily for the duration of the intervention. Urine samples were analysed using metabolite fingerprinting by both high-resolution flow infusion mass spectrometry (FIE-HRMS) and proton nuclear magnetic resonance spectroscopy (1H NMR). Absolute concentrations of selected dietary intake biomarkers were measured using liquid chromatography triple quadrupole mass spectrometry (LC-QqQ-MS) and by integration of 1 H-NMR data. Classification models for diet discrimination in spot, cumulative and 24-hour urine samples predicted dietary intake for all urine sampling time points. Cross validation modelling using 1H NMR and FIE-HRMS data also demonstrated the power of spot and cumulative urine samples in predicting dietary patterns in 24-hour urines. There was no significant loss of information when spot or cumulative samples were substituted for 24-hour urine samples. The combination of high dimensional classification modelling and quantitative analysis shows that when using urinary metabolic profiles and biomarkers for assessment of dietary patterns, spot samples are suitable replacements for 24-hour urine samples.
*AWARD WINNERS

PLANT, FOOD, ENVIRONMENTAL AND MICROBIAL

P-344

An integrated metabolomic and metagenomic analysis of Korean traditional alcoholic beverages using Nuruk

PRESENTING AUTHOR: Jang Eun Lee, Korea Food Research Institute, South Korea

CO-AUTHORS: Jae Ho Kim

Nuruk is a fermentation starter used for brewing alcoholic beverages. It is a kind of dough made from grains, such as wheat, barley, or rice, which are germinated by enzyme-releasing microorganisms. Since Nuruk mainly consists of starch, microorganisms that are capable of degrading β-starch are prominent in Nuruk. Specifically, various types of fungi, yeast and bacteria that cause alcoholic fermentation are present in Nuruk. Thus, it is important to understand how they affect the quality of the alcoholic beverages during fermentation. In this study, an integrated metabolomic and metagenomic approaches were used to generate the comprehensive metabolite and microbial profiles of Korean traditional alcoholic beverages produced by three different types of Nuruks selected from fifty-eight types of restored traditional Nuruk. Different analytical techniques such as GC-MS and 1H NMR in combination with multivariate analyses were used to obtain the metabolomic profile of each alcoholic beverage as well as that of the fermentation process. In addition, microbial communities were monitored to identify the correlative relationship between metabolites and microbes. The results indicated that the volatile metabolites of Nuruk-based alcoholic beverages are likely to be affected by microbial diversity in Nuruk, whereas the non-volatile metabolites are affected by the ingredients of Nuruk. These metabolomic profiles will be useful to identify how the metabolites and microorganisms of Nuruk affect the quality of alcoholic beverages. Furthermore, these results will be of great significance towards forming the basis of further research to scientifically establish the values of fermented foods.

P-345

Effects of estrogen deficiency on metabolic markers and gut microbiota in ovariectomized mice fed normal-fat diet

PRESENTING AUTHOR: Youngmin Lee, Department of Food and Nutrition, Seoul Women's University, South Korea

CO-AUTHORS: Jieun Jeong, Chi Young Yun

Estrogen deficiency is associated with obesity, dyslipidemia, and increased insulin resistance, yet underlying mechanisms remain poorly understood. This study was performed to investigate effects of estrogen deficiency on metabolic markers and gut microbiota in ovariectomized mice fed normal-fat diet. C57BL/6J mice (7 weeks old) were sham operated or ovariectomized and after 3 weeks, assigned to the following groups: sham-operated mice fed with normal fat diet (S-NF); ovariectomized mice fed with normal fat diet (OVX-NF). Experimental diets were fed for 5 weeks. At the end of the treatment, liver was isolated and serum was collected for biochemical analysis. Total DNA from fecal samples was extracted. Although there was no significant difference in food intake and weight gain due to ovariectomy in normal fat diet-fed mice, we observed a significant increase of liver weight and abdominal fat weight in OVX-NF group compared with S-NF group. No significant difference was observed in relative abundance of Bacteroidetes, Verrucomicrobia, Proteobacteria, and Deferribacteres among group. However, we observed that OVX-NF group had increased the phylum Actinobacteria, and decreased the phylum Firmicutes compare to S-NF group (P<0.05). In our results, there is a negative correlation between adiponectin level and Firmicutes, and a positive correlation between abdominal fat weight and Actinobacteria (P<0.05). This study suggested that changes in the gut microbiota may be related to estrogen deficiency-induced metabolic disorders in postmenopausal women. This study was carried out with the support of the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (NRF-2017R1C1B5018328).

P-346

Targeted phenolic metabolites of purple potatoes in plasma and urine of healthy men

PRESENTING AUTHOR: Johanna Jokioja, University of Turku, Finland

CO-AUTHORS: Johanna Jokioja, Kaisa M. Linderborg, Mark Philo, Jasmine Percival, Paul Kroon, Baoru Yang

The purple hue of the coloured potatoes is derived from natural polyphenolic colorants called anthocyanins. Anthocyanins have a flavylium cation structure substituted with mono- or oligomeric sugars and in case of acylated anthocyanins, aliphatic or aromatic acids. Interestingly, anthocyanin-rich foods, such as berries, may be beneficial for health[1, 2]. Our recent study showed that purple potatoes may decrease human postprandial blood glycaemia compared to yellow potatoes [3]. The health effects of anthocyanin-rich foods may be contributed by their phenolic metabolites. However, the metabolic fate of dietary anthocyanins is still relatively unknown. Non-acylated anthocyanins are reported to be converted into glucuronide and sulphate conjugates and small phenolics[4]. The metabolites of acylated anthocyanins have been scarcely studied. Therefore, a cross-over clinical study was organized to investigate the phenolic metabolites in plasma and urine of healthy men after a meal rich in purple potato acylated anthocyanins. The samples were cleaned using solid-phase extraction, and the targeted metabolites were detected using mass spectrometry in multiple reaction monitoring mode. The anthocyanins were mainly of petunidin and peonidin glycosides acylated to hydroxycinnamic acids. Our results suggest that purple potato anthocyanins are metabolized into phenolic metabolites, such as phloroglucinaldehyde, hydroxybenzoic acids and hydroxycinnamic acids, and to their glucuronides and sulfates. [1] Li D et al (2015) J Nutr. 145, 742-748 [2] Törrönen R et al (2010) Br J Nutr. 103, 1094-1097 [3] Linderborg KM et al (2016) Int J Food Sci Nutr. 67, 581-591 [4] deFerrars RM et al (2014) Mol Nutr Food Res. 58, 490-502
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

*AWARD WINNERS

PLANT, FOOD, ENVIRONMENTAL AND MICROBIAL

P-347 Urinary food intake and microbiome-related biomarkers in lactating mothers and term and preterm infants

PRESENTING AUTHOR: Victoria Ramos-Garcia, IIS La Fe, Spain

CO-AUTHORS: Jose David Piñeiro-Ramos, María Gormaz, Anna Parra-Llorca, Guillermo Quintás, Izaskun Garcia-Mantrana, María Carmen Collado, Máximo Vento, Julia Kuligowski

The gut microbiota, host organism, and diet trialogue in lactating mothers and its impact on early nutrition programming of their infants is spotlighted in nutrition research. The analysis of the urinary metabolome provides a non-invasive means to determine a range of food intake and microbiome-specific biomarkers. In this study, liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) is proposed as a tool to study urinary metabolic biomarkers in lactating mothers and their term or preterm infants. Urine samples were collected from 27 lactating mothers (M), 29 term infants (TI) (25 receiving own mother's milk, OMM; 4 formula), and 47 preterm infants (PI) (20 receiving OMM, 20 donor human milk, DHM, and 7 formula). An untargeted LC-time-of-flight-MS assay was used for a comprehensive analysis of the urinary metabolome. Metabolite annotation and integration was performed matching against an in-house library containing 41 food intake and microbiome-related biomarkers described in the literature. Principal Component Analysis revealed characteristic patterns differentiating samples from M, PI, and TI. Employing Partial Least Squares Discriminant Analysis, significant differences between relative urinary biomarker concentrations of (i) M and TI, finding significant correlations for three food intake biomarkers, (ii) PI and TI and (iii) infants receiving OMM and formula were detected. No difference was observed between PI fed with OMM and DHM. The obtained results will be used for the development of a quantitative LC-MS-based method for studying the correlation between biomarkers and Food Frequency Questionnaires, as well as the composition of the gut microbiome.

P-348 Metabolomic Profiling of Superfood Seeds in bakery products using a Benchtop GC Time-of-Flight Mass Spectrometer

PRESENTING AUTHOR: Stefan Vinnenberg, LECO Instrumente GmbH, Germany

CO-AUTHORS: Juergen Wendt

Around 20 years ago "superfood" started to be used as a marketing tool for selling specific foods, dietary supplements and food additives. Although there is no exact definition of superfoods, one can be classified as food considered exceptionally good for one's health and for boosting the immune system. In the past few years chia seeds became one of the most popular superfoods. As a result of the rapidly increasing demand for superfoods, the market is flooded with counterfeits. In bakery products more expensive chia seeds are often replaced by cheaper flaxseed. The aim of this study was to evaluate the metabolomic profile of chia, flax and sesame seeds, looking for chemical markers, which allow confirming the presence of such seeds in food products. For sample preparation a well established derivatization protocol was applied, including a methoxymation step, followed by a silylation. The samples were analyzed using a LECO Benchtop GC-Time-of-Flight Mass Mass Spectrometer. A new TOF design has significantly improved the detection capability of the system, allowing for the safe identification and quantification of analytes, even at ultra-trace level. Different strategies for data evaluation were compared. Rosmarinic acid is best suited to distinguish between chia and other seeds. The marker was identified by the usage of the Golm Metabolome Database. By using this marker, alterations to bakery products can be easily uncovered.

P-349 Truffle aroma characterisation of Australia grown black Périgord truffle (Tuber melanosporum) during shelf life

PRESENTING AUTHOR: Maike Bollen, Metabolomics Australia, UWA, Australia

CO-AUTHORS: Kenny Choo, Gary Dykes, Joshua Ravensdale, Ranil Coorey

Truffles (Tuber melanosporum) are a high value commercial fungi traditionally produced in the northern hemisphere. The unique flavour and its rarity is due to the short growing season and relative difficulty for mass cultivation, making the truffle one of the most highly prized, edible fungi. Although truffles have been cultivated for decades, little is known of the ecology of truffle bacterial microbiome and the role it plays in the aroma development and spoilage during post-harvest storage. The main objective of this study was to determine the effects on the truffle aroma profile after chilled storage for extended periods of time using solid-phase micro extraction (SPME), together with gas chromatograph mass spectrometry (GCMS). Black Périgord truffle samples (N=14) were provided by Australian Truffle Traders from Manjimup, Western Australia, during the truffle season. The fresh truffle samples were assessed at three time intervals; 0, 7 and 14 days to monitor the changes in the metabolite profile of the truffles during storage. The results showed that 64 compounds were identified in all of the truffle samples at all time points. 11 key compounds showed significant changes between time points including dimethyl sulfoxide (DMSO) and 2,4-dithiapentane. In addition, dimethyl sulfoxide (DMSO) as well as 2,4-dithiapentane are compounds only found in white truffles (Tuber Magnatum). The findings of this study will provide truffle growers an insight on the impact of truffle aging on the aromatic qualities of truffles. Further studies are currently in progress to improve the preservation of the truffle aroma.
**POSTER SESSIONS 1 AND 2 – Monday and Tuesday –** all odd number posters will be on display.

**POSTER SESSIONS 3 AND 4 – Wednesday and Thursday –** all even number posters will be on display.

*AWARD WINNERS

PLANT, FOOD, ENVIRONMENTAL AND MICROBIAL

P-350 Exploratory analysis of commercial olive-based dietary supplements

PRESENTING AUTHOR: Mar Garcia-Aloy, Fondazione Edmund Mach, Italy

CO-AUTHORS: Mar Garcia-Aloy, Nelli Groff, Domenico Masuero, Antonio Franco, Furio Battolini, Massimo Fia, Urska Vrhovsek, Fulvio Mattivi

During the production of olive oil an important amount of wastes are generated. In last few years, their reutilization via recovery of polyphenolic fraction has attracted an increasing attention. Currently, the market of olive-based dietary supplements is composed of a broad range of natural extracts claiming different health effects and often sold without a clear statement on their chemical composition. The aim of the present study was to characterize the chemical profiles of a range of different olive-based dietary supplements. Such products were analyzed via untargeted metabolomics, using liquid chromatography coupled to high-resolution mass spectrometry (Orbitrap LTQ-XL), in order to explore their composition. PCA revealed a clear separation of samples according to the type of product (first component, 40% variance) and also according to the part of the olive-plant used (17% variance). The first component clearly divided gemotherapy products from the other ones. Most of phenolics were present in these products in lower concentration (or not present). The second component was the one that separated the products according to the part of the olive plant used in their formulation, the fruits from the leaves. A Student's t-test was performed in order to select the putative biomarkers discriminating among the observed classes. Finally, most promising biomarkers were annotated, and the ones identified at level 1 were also quantified via HPLC Alliance DAD-QDa MS (Waters). The data produced with this study is suitable to support the unambiguous classification of the olive-based dietary supplements. Funding: Operational Plan "POFESR 2014/20" (Autonomous Province of Trento).

P-351

Food Intake Biomarkers for Increasing the Efficiency of Dietary Pattern Assessment through the Use of Metabolomics: Unforeseen Research Requirements for Addressing Current Gaps

PRESENTING AUTHOR: Cristina Andres-Lacueva, University of Barcelona, Spain

CO-AUTHORS: Mar Garcia-Aloy, Raul González-Domínguez

Current research on nutritional sciences depends upon the precise measurement of food intake. Despite being the most widely used dietary measurement tools, self-reported surveys are not exempt from already recognized limitations1,2,3. Low dietary assessment accuracy contributes to the inconsistency of results already observed in many instances when trying to understand the connections between diet and healthiness or disease risk, thereby weakening their potential translation to clinical and public health applications.2 The drawbacks of conventional instruments have encouraged research on food intake biomarkers (FIBs) as a complementary or alternative measure of dietary intake, being one of the cornerstones of nutritional epidemiology.2 Accurate dietary assessment is a challenge in nutritional research, needing powerful and robust tools for reliable measurement of food intake biomarkers. In this work, we have developed a novel quantitative dietary fingerprinting (QDF) approach, which enables for the first time the simultaneous quantitation of about 350 urinary food-derived metabolites, Thus, this metabolomic approach represents one-step further toward precision nutrition and the objective of improving the accurateness and comprehensiveness in the assessment of dietary patterns and lifestyles 1 J. Agric. Food Chem. 2018, 66, 5-7 2 Trends Food Sci. Technol. 2017, 69, 220-229. 3 Curr. Opin. Food Sci. 2017, 16, 96-994 4 J Agric Food Chem. 2019 Mar 1. doi: 10.1021/acs.jafc.8b07023 Funding: DiGuMet-PCIN-2017-076 CIBERFES 2017SGR1546 & ICREA Academia 2018

P-352

The effects of a brain-friendly diet on metabolic and physiological parameters and cognitive performance (Brave study)

PRESENTING AUTHOR: Johanna Koponen, Nightingale Health Ltd., Finland

CO-AUTHORS: Marika Laaksonen, Sanna-Maria Hongisto, Juuso Parkkinen, Emmi Tikkanen, Juhani Sibakov, Jussi Loponen, Heli Diaz, Leila Fogelholm, Jukka Rantala, Harri Lindholm

Cognitive performance is related to glucose metabolism and metabolic activation that are regulated by diet. We studied the effects of a brain-friendly diet (Brainfood) on metabolic and physiological parameters and cognitive performance in office workers at assumed metabolic risk. We conducted a diet-switch, 4-week intervention study on 84 volunteers with elevated plasma LDL levels in pre-screening. The Brainfood diet focused on regular meal frequency and optimal intake of polyunsaturated fats, fibre and salt, whereas the control diet was a typical western diet. Plasma samples were collected at the end of the lead-in, control and intervention periods, and analysed using high-throughput NMR spectrometry for quantification of lipoprotein subclasses and particle sizes, cholesterol, glycerides, phospholipids, apolipoproteins, fatty acids, amino acids, ketone bodies, fluid balance, glycolysis and inflammation markers. A non-commercial mobile healthcare device recorded ECG, optical pulse plethysmography, accelerometric signal and thoracic impedance. Cognition was measured with standardized neuropsychological tests (Bourdon-Wiersma, FAT, N-Back, NASA-TLX, KSS, RAVLT, Stroop, WMS-III, Task-switching) under a psychologist's supervision and as tablet, PC or online tests. Brainfood reduced saturated fat and salt intakes and increased polyunsaturated fat, fibre, vitamin C and D, iron and magnesium intakes. Favourable effects were seen in the atherogenic lipid measurements, such as fatty acids, LDL, IDL and small VLDL, as well as fatty acids, phospholipids and glutamine. Intervention did not affect the physiological or cognitive parameters except for a decrease in inaccuracy of visual attention (p=0.027). The Brainfood diet could be recommended for office workers as a healthy diet following Nordic Nutrition recommendations.