HAL Id: hal-02293580
https://hal.archives-ouvertes.fr/hal-02293580
Submitted on 2 Jun 2020
HAL is a multi-disciplinary open access
archive for the deposit and dissemination of
sci-entific research documents, whether they are
pub-lished or not. The documents may come from
teaching and research institutions in France or
L’archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d’enseignement et de
recherche français ou étrangers, des laboratoires
From Molecular Profiling to Precision Medicine in
Metabolic Syndrome
Blandine Comte, Stéphanie Monnerie, Marion Brandolini-Bunlon, Cécile
Canlet, Florence Castelli, Benoit Colsch, Francois Fenaille, Charlotte Joly,
Natacha Lenuzza, Bernard Lyan, et al.
To cite this version:
Blandine Comte, Stéphanie Monnerie, Marion Brandolini-Bunlon, Cécile Canlet, Florence Castelli, et
al.. From Molecular Profiling to Precision Medicine in Metabolic Syndrome. 15th Annual Conference
of the Metabolomics Society (Metabolomics 2019), Jun 2019, La Haye, Netherlands. 300 p., 2019.
�hal-02293580�
Biomedical
Plant, Food, Environmental and Microbial
Technology New Frontiers
SUNDAY, JUNE 23
Atlantic Alexia Ariane Oceania Foyer 11:00 a.m. REGISTRATION OPEN
12:30 p.m. – 2:15 p.m. W1: EMN – Data Fusion W2: Mining the Metabolome W3: Multi-Omics Integration
& Systems Metabolomics Intro to the Field 1: Data Acquisition 2:30 p.m. – 4:15 p.m. W4: Application of Graphical
Models to Metabolomics W5: Plant Metabolomes: Natural & Generated Variability W6: How to Link Metabolome & Genome Mining Intro to the Field 1: Data Acquisition 4:30 p.m. – 6:15 p.m. W7: EMN – Professional Career
Development W8: Putting Metabolomic Data into Context W9: An Open-Source Pipeline for Appraisal of NMR Datasets Intro to the Field 1: Data Acquisition 6:30 p.m. – 8:30 p.m. Career Night – Pacific
MONDAY, JUNE 24
Atlantic Alexia Ariane Oceania Foyer 7:30 a.m. REGISTRATION / INFO DESK OPEN
8:30 a.m. – 10:15 a.m. W10: The Importance of Quality
Assurance & Quality Control W11: Towards FAIR Spectral Libraries W12: EMN – Stable Isotope-Resolved Metabolomics Intro to the Field 2: Data (pre) Processing and Biostatistics 10:30 a.m. – 12:15 p.m. W13: Beyond pathway mapping W14: Standardizing the
Fluxomics Workflows Microbiome-Metabolome Interplay W15: Tools to Study the Intro to the Field 2: Data (pre) Processing and Biostatistics 12:15 p.m. – 1:30 p.m. LUNCH BREAK – ON YOUR OWN
1:30 p.m. – 3:15 p.m. W16: Application Metabolomics
in Industry W17: Dynamic Modeling of Human Metabolism W18: EMN – Volatomics in Human Health Intro to the Field 2: Data (pre) Processing and Biostatistics 3:30 p.m. – 5:00 p.m. Opening Ceremony | Plenary Session 1 – Joshua Rabinowitz – King Willem-Alexander Hall
5:15 p.m. – 6:45 p.m. Welcome Reception – Poster Session 1 – Odd Numbers – Exhibit Foyer 7:00 p.m. – 8:00 p.m. Metabolomics Society Town Hall Meeting – Atlantic
TUESDAY, JUNE 25
Atlantic King Willem-Alexander Alexia Ariane 7:45 a.m. REGISTRATION / INFO DESK OPEN
8:30 a.m. – 9:30 a.m. Plenary Session 2 – Dorret Boomsma – King Willem-Alexander Hall 9:30 a.m. – 10:15 a.m. BREAK – EXHIBIT FOYER
10:15 a.m. – 12:00 p.m. 1. Cancer 2. Plant Applications 1 3. Data Integration & Data Basing 1 4. Novel Technologies 12:00 p.m. – 1:30 p.m. LUNCH – IN FOYER WITH EXHIBITS – PLATINUM SPONSOR PRESENTATIONS
12:20 p.m. – 1:20 p.m. Sponsor Pres: SCIEX Sponsor Pres: Waters Corporation 1:30 p.m. – 3:15 p.m. 5. Metabolic Disease 6. Food Applications 1 7. Flux Studies 8. Novel Instruments,
Tools and Services 3:15 p.m. – 3:45 p.m. BREAK – EXHIBIT FOYER
3:45 p.m. – 5:30 p.m. 9. Epidemiology 10. Microbial Applications 11. Metabolite Identification 1 12. Stem Cells, Organoids 5:30 p.m. – 7:00 p.m. Poster Session 2 – Odd Numbers – Exhibit Foyer
7:00 p.m. – 8:30 p.m. EMN Reception – Pacific
WEDNESDAY, JUNE 26
Atlantic King Willem-Alexander Alexia Ariane 8:00 a.m. REGISTRATION / INFO DESK OPEN
8:30 a.m. – 9:30 a.m. Plenary Session 3 – Cathie Martin – King Willem-Alexander Hall 9:30 a.m. – 10:15 a.m. BREAK – EXHIBIT FOYER
10:15 a.m. – 12:00 p.m. 13. Lipidomics and
Cardiovascular Disease 14. Plant Defense 15. Data Analysis & Statistics 16. Single Cell 12:00 p.m. – 1:30 p.m. LUNCH – IN FOYER WITH EXHIBITS – PLATINUM SPONSOR PRESENTATIONS
12:20 p.m. – 1:20 p.m. Sponsor Pres:
Thermo Fisher Scientific Shimadzu Europa GmbHSponsor Pres: 1:30 p.m. – 3:15 p.m. 17. Ageing and Disease 18. Food Applications 2 19. Data Integration & Data Basing 2 20. Regulatory Session 3:15 p.m. – 3:45 p.m. BREAK – EXHIBIT FOYER
3:45 p.m. – 5:30 p.m. 21. Infection and Immunity 22. Environment & Toxicology 23. New Instrumentation 24. Novel Applications 5:30 p.m. – 7:00 p.m. Poster Session 3 – Even Numbers – Exhibit Foyer
7:30 p.m. – 10:30 p.m. Conference Dinner – Xiringuito
THURSDAY, JUNE 27
Atlantic King Willem-Alexander Alexia Ariane
15th Annual Conference of the Metabolomics Society Page 3
CONTENTS
AGENDA
Page 2PLENARY ABSTRACTS
Page 4ORAL ABSTRACTS
Page 11POSTER ABSTRACTS
Page 68BIOMEDICAL
Page 69NEW FRONTIERS
Page 157PLANT, FOOD, ENVIRONMENTAL AND MICROBIAL
Page 171TECHNOLOGY
Page 224AUTHOR INDEX
Page 274SPONSORS
Agilent Technologies Page 17 Bruker Daltonics/Bruker BioSpin Page 23 Sciex Page 29 Shimadzu Page 35 Waters Corporation Page 42 Thermo Fisher Scientific Page 47 Cambridge Isotope Laboratories, Inc Page 113 Human Metabolome Technologies Page 113 Metabolites Page 120 Metabolon Page 120 Biocrates Life Sciences AG Page 130
15th Annual Conference of the Metabolomics Society Page 5
PLENARY SESSION 1
The marriage of technology development and biological discovery
Monday, June 24, 4:00 p.m. – 5:00 p.m.PRESENTING AUTHOR: Joshua Rabinowitz, Lewis-Sigler Institute, United States
Today, 20 years after sequencing of the first human chromosome, we now have powerful tools for measuring all of the fundamental classes of biomolecules, including metabolites While the data gathering capacity of these tools is inspiring, the complexity of biology remains humbling The failure of these tools to substantially eliminate major diseases, including metabolic disease, is self-evident In this lecture, I will describe our past and ongoing efforts to bridge metabolomic technology development and biological discovery I will provide examples of how intensive biological focus improved our metabolomic pipelines, and of how isotope tracing illuminated otherwise obscure aspects of metabolism Examples will be drawn from microbiology, cell biology, and cancer A major focus will be on our recent efforts to revisit quantitatively mammalian metabolism, with an eye towards better understanding of both basic metabolic principles and the intersection of diet, metabolism, and disease
PLENARY SESSION 2
Twin and SNP-based studies of metabolomics traits
Tuesday, June 25, 8:30 a.m. – 9:30 a.m.PRESENTING AUTHOR: Dorret I Boomsma, Netherlands Twin Register, Vrije Universiteit, Netherlands
Metabolite profiling allows for an increased understanding of behavioral and psychiatric phenotypes We hypothesized that promising metabolites in this respect include those for which a genetic component is present estimated heritability (h2: standardized estimate of genetic variance) based on the different genetic relatedness of mono- and dizygotic twin pairs
Metabolomics data from 4 different platforms for up to 5,117 individuals, including some family members of twins We estimated that ~50% of variation is due to genetic variation, but heritability estimates differed across metabolite classes and lipid species
Heritability also can be estimated from genotype data (SNPs: Single Nucleotide Polymorphisms) by quantifying the genetic similarity of ‘unrelated’ individuals and comparing it to their trait similarity (h2SNP) To elucidate the genomic architecture of blood metabolites, we simultaneously estimated total heritability (h2total), SNP heritability (h2SNP) and the proportion of heritability captured by known metabolite loci (h2GW-loci) We reviewed all association studies of SNPs and blood metabolites, retrieving 241,965 associations for which all associated metabolites were classified For the estimation of h2GW-loci we aggregated > 800 class-specific metabolite loci for 309 lipids and 52 organic acids This revealed significant differences in h2SNP and h2GW-loci among different classes of lipids and organic acids Phosphatidylcholines with a higher degree of unsaturation had higher h2GW-loci estimates
This study highlights the genetic architecture of metabolite classes and lipid species, with genes explaining on average 50% of variation in metabolites, and common genetic variants influencing metabolites This knowledge can be used in construction of polygenic scores and causal modeling
PLENARY SESSION 3
The future for food may be in our past: the importance of plants in our diets.
Wednesday, June 26, 8:30 a.m. – 9:30 a.m.PRESENTING AUTHOR: Cathie Martin, John Innes Centre, Colney Research Park, UK
The appreciation of the challenges of achieving global food security has matured to include nutritional security, as scientists have realised that not only calorie content but food and colonic microbial composition impact our health and well-being, dramatically The ways that the nutrients we consume affect our health are highly complex due to the diversity of what we eat, the varying digestibility of what we eat, the changing composition and functioning of each individual’s gut microbiota, the differences in absorption and bioavailability of the nutrients we eat, the differences in responses between individuals to what they eat and the multi-fold mechanisms of action that nutrients have on our health It has been accepted for more than 50 years that diets rich in plants, particularly fruit and vegetables, protect health, and yet diets have declined, with lower fruit and vegetable content replaced by more cheap, sugary, oily processed foods These dietary shifts have had a marked impact on the incidence of chronic diseases; obesity, metabolic diseases, type2 diabetes and cardiovascular diseases
Only by understanding how phytonutrients improve our health by reducing risks of chronic disease and which phytonutrients confer greatest benefits in protecting against specific diseases (a process termed comparative nutrition) can we hope to achieve dietary improvements at all levels in society By describing examples of preclinical comparative nutritional analyses, I hope to illustrate the potential of dietary improvement using plant-based foods to improve our health and quality of life and to reduce the economic burden on our health-care systems
PLENARY SESSION 4
Comprehensive investigations of cancer cell metabolism using 13C-fluxomics
Thursday, June 27, 1:30 p.m. – 2:30 p.m.PRESENTING AUTHOR: Jean-Charles Portais, University Toulouse, France
Metabolism is a basic cellular function that sustains survival, growth and adaptation of living organisms At the cellular level,
metabolism is organized as a network, ie a complex set of biochemical reactions that are tightly interconnected To investigate such complex systems, powerful tools are required, and a broad range of approaches (metabolomics, fluxomics) have been developed over the past decade to provide detailed and quantitative measurement of the operation of metabolic networks These methods can be combined with other omics tools (eg transcriptomics, proteomics, etc) and to metabolic modelling to provide systems biology approaches for in-depth, comprehensive understanding of the organization, functioning and adaptation of cellular metabolism This understanding can provide the rationale for efficient and cost-effective optimization of production systems (knowledge-based metabolic optimization) in biotechnology, or to characterize the metabolic dysfunctions associated with pathologies, or to identify and validate new therapeutic targets or strategies In this lecture, particular emphasis will be made on 13C-fluxomics, with selected illustrations in the field of cancer metabolism, and how this can help in designing improved therapeutical strategies
15th Annual Conference of the Metabolomics Society Page 7
SESSION 8: NOVEL INSTRUMENTATIONS, TOOLS AND SERVICES
Presented by Platinum and Gold Sponsors
Tuesday, June 25 | 1:30 p.m. – 3:15 p.m.
Princess Ariane
By participating in this session you will get an overview of the latest developments in instrumentation and tools (from our 6 platinum sponsors) and services (from our 4 gold sponsors). Each company will highlight their latest developments in a 7-minute flash presentation. The session is scheduled at the start of the conference, allowing you to determine which exhibitors will provide the most valuable follow-up visit at their booth during the event. The interactive session also has 2 panel discussions, moderated by Thomas Hankemeier and David Wishart.
VENDOR SESSION
Agilent Technologies
Christine Miller, Omics Market Manager, USA
A New LC/Q-TOF Platform for Metabolomics Analysis
Innovations in LC/MS and GC/MS have driven the field of metabolomics Speed, sensitivity, resolution, dynamic range, and isotopic fidelity are all important MS attributes for metabolomics research This presentation will describe some of the innovative technologies that are in the new Agilent 6546 LC/Q-TOF platform which is designed with metabolomics research in mind
Bruker Daltonics/Bruker BioSpin
Lucy Woods, phD, Product Manager QTOF, Germany
New ground-breaking releases to advance 4D Metabolomics and Lipidomics
Get to know Brukers´ latest innovations for 4D metabolomics and lipidomics research We cordially invite you learn more about our newest developments for SpatialOMx and NMR-based metabolic fingerprinting Be ready to get surprised!
SCIEX
Baljit Ubhi, Market Manager - Metabolomics Business, USA
Technology Innovations for Advancing Metabolomics at SCIEX
Technology advancements will be presented highlighting SCIEX’s innovation in improving healthcare and wellness Analytical hardware and software tools for metabolomics and lipidomics highlight their utility for enabling precision medicine
Shimadzu
Emily Armitage, Research Scientist, UK
Driving data-driven decision making just a little bit quicker…
For many metabolomics workflows, there is a need for a smarter path to data-driven decision-making and to help find actionable data This headline overview will highlight the way in which high resolution accurate mass with data independent acquisition methods can make a difference to metabolomic workflows The talk will focus on the Shimadzu LCMS-9030 QTOF platform and software tools to help accelerate data-driven decision making in metabolomics using DIA and a research application to find components and help verify identification
Thermo Fisher Scientific
Amanda Souza, Manager, Product Marketing, USA
7 Minutes of mzCloud Spectral Library: We’ll Leave You Begging for More
Unknown annotation is one of the most difficult challenges for untargeted metabolomics researchers Learn how the mzCloud spectral library accelerates the unknown annotation process using more spectral information across diverse chemical classes to ultimately annotate more with greater confidence
Waters Corporation
David Heywood, Senior Manager Omics Business Development, United Kingdom
From out of the box methods to structural characterization. Solutions for metabolomics research
To fully understand the complex relationship between biology and the compounds we measure, multiple approaches and workflows need to be considered Discovery workflows provide indications of metabolic perturbation often needing supplemental measurements across large cohorts, measurement of metabolic flux or even clarification of compound structure This presentation will discuss how Waters innovates with purpose to address the challenges in Metabolomics research
SESSION 8: NOVEL INSTRUMENTATIONS, TOOLS AND SERVICES
Presented by Platinum and Gold Sponsors
Tuesday, June 25 | 1:30 p.m. – 3:15 p.m.
Princess Ariane
By participating in this session you will get an overview of the latest developments in instrumentation and tools (from our 6 platinum sponsors) and services (from our 4 gold sponsors). Each company will highlight their latest developments in a 7-minute flash presentation. The session is scheduled at the start of the conference, allowing you to determine which exhibitors will provide the most valuable follow-up visit at their booth during the event. The interactive session also has 2 panel discussions, moderated by Thomas Hankemeier and David Wishart.
VENDOR SESSION
CONTINUED
Biocrates Life Sciences AG
Therese Koal, PhD, Head of Research & Development, Austria
Unlock Nutrition-Microbiome-Host Interaction with Metabolomics
Intestinal bacteria influence a vast range of biological processes and have been associated with the pathogenesis and the course of many diseases However, establishing associations is not sufficient to understand the functional interaction between nutrition, microbiota and the host organism As metabolic processes are a key element of this interaction, metabolomics has evolved as an important tool for functional microbiomics studies This talk will be discussing the relevance of selected metabolic pathways in this context It will also present the new MxP® Quant 500 Kit as an analytical tool to assess a variety of microbiota-derived metabolites, including bile acids, indoles and TMAO The MxP® Quant 500 Kit is the most comprehensive solution within Biocrates’ portfolio of kits for Targeted Metabolic Profiling, covering up to 630 compounds from 26 metabolite and lipid classes It enables researchers to obtain detailed information about endogenous metabolism as well as the systemic impact of microbial activity
Cambridge Isotope Laboratories, Inc.
Krista Backiel, Marketing Manager and Metabolomics Manager, USA
Stable Isotope-Labeled Mixes for Multiplexed Metabolomics: Production and Application
One of the aims of metabolomics research is to quantitatively measure metabolites in biosamples The impetus is to better understand disease mechanisms and to identify or validate candidate biomarkers toward improved personalized medicine The field has made significant progress over the past decade in addressing these aims Efforts of which have been aided by advancements in analytical methodology, technology, software, as well as reagents (eg, stable isotope-labeled standards) To assist in the high throughput and multiplexed analysis of metabolites, we have formulated (and are in the process of formulating) an array of isotope-enriched, multi-component mixtures This presentation will chronicle the process of producing multi-component mixtures, from standard preparation at our production facility through to the assembly of the isotope-enriched mix at our chemical formulations laboratory Additionally to be discussed is the application of our isotopically labeled mix in targeted or untargeted MS metabolomic studies
Human Metabolome Technologies
Tom Hoshiba, Managing Director, NetherlandsHMT Europe
Japanese biotech company Human Metabolome Technologies (HMT) opened an European Office in Leiden, Netherlands
Metabolon
Alex Forrest-Hay, VP Population Health, USA
Delivering Actionable Insights with Metabolomics
There are 4 CORE capabilities essential to insight-deriving metabolomics
15th Annual Conference of the Metabolomics Society Page 9
REGULATORY SESSION
SESSION 20: REGULATORY SESSION
Translating metabolomics from academic science into regulatory practice:
challenges and progress in pharmacology and toxicology
Wednesday, June 26 | 1:30 p.m. – 3:15 p.m.
While metabolomics has become a mature and widely used technology in academic research, its application to regulatory science has been limited to date. Several factors contribute to this slow uptake, the most commonly cited roadblocks are the lack of standardisation, validation and reporting formats for metabolomics. Recently, progress has been made in translating ‘omics technologies (including metabolomics) from academic science towards regulatory practice in the fields of pharmacology and toxicology, specifically for drug and chemical safety, respectively. This timely session at Metabolomics-2019 will introduce and review some of the opportunities, challenges and recent progress in this translational activity. While focused on drug and chemical safety legislation in Europe, the progress reported will have much wider implications for metabolomics in international regulatory practice. Talks will be presented by regulators, industry and academic scientists to provide a balanced perspective, and include a panel discussion chaired by Dr. Pim Leonards (Vrije Universiteit Amsterdam).
An Overview of the 21st Century Cures Act: Opportunities for Biomarkers and Precision Medicine
Dr. Rick Beger, National Center for Toxicological Research, US FDA, United StatesA biomarker is defined as a characteristic that is measured as an indicator of normal biological processes, pathogenic processes, or responses to an exposure, or therapeutic intervention There are seven BEST biomarker categories; diagnostic, monitoring, pharmacodynamic response, predictive, prognostic, safety, and susceptibility/risk The 21st Century Cures Act establishes a biomarker “qualification” process for drug development tools that can then be used for particular context of use (COU) in a regulatory submission The submission of a biomarker for regulatory use under the 21st Century Cures Act, is a three-stage submission process and builds on the existing biomarker submission process The first Stage is a letter of intent (LOI), that includes the drug development need the biomarker is intended to address, biomarker information The intended context of use (COU), and information on how the biomarker will be measured If the FDA accepts the LOI, a qualification plan (QP) describing the information including the analytical method and performance characteristics that will qualify the biomarker for the proposed COU in drug development is submitted The third step is a full qualification package (FQP) that contains all accumulated information on the biomarker, organized by topic area The FDA will make a final decision about whether the biomarker is qualified based on the FQP The 21st Century Cures Act and metabolomics ability to capture phenotype information on a patient provides opportunities and for biomarkers and precision medicine Examples of potential metabolomics biomarkers will be provided
Big Data “Omics” – Challenges and Opportunities in Regulation
Dr. Renate König, Paul-Ehrlich-Institut, Federal Institute for Vaccines and Biomedicines, Germany
A new Joint HMA/EMA Task Force was established, initiated by EU Heads of Medicines Agencies (HMA) in collaboration with the European Medicines Agency (EMA), to explore how medicines regulators can use Big Data to support research, innovation and robust medicines development to benefit human health
This talk will focus on the identification of the emerging challenges from the use of Big Data, with the focus on Bioanalytical Omics, to prepare the European regulatory system for the future, on establishing recommendations for use of “Omics” big data in assessment of medicines as well highlight the opportunities for “Omics” in the regulation of medicines
Various Applications of Metabolomics in Toxicology
Prof Hennicke Kamp, BASF, GermanyBASF and its daughter company metanomics established the database MetaMap®Tox containing the plasma metabolome of more than 1000 compounds derived from 28-day studies in rats Approximately 250 different endogenous metabolites are measured and more than 100 patterns for different toxicological modes of action are available MetaMap®Tox is nowadays routinely used at BASF to support systemic toxicity testing in terms of identification of target organs and modes of action or for read-across applications (Kamp at al, 2012; van Ravenzwaay et al, 2016) Over the last years, we have broadened this approach to identify maternal toxicity in reproductive toxicity studies (Keller et al, 2018) Additionally, a highly stable and reproducible liver in vitro model was established, in which the intracellular metabolome of HepG2 cells can be specifically altered through treatment with different hepatotoxicants (Ramirez et al, 2017) So far more than 90 different treatments have been analysed with this setup In this presentation, examples will be shown how metabolomics can be used for the purposes mentioned above Since the acceptance of such approaches in the regulatory community is somehow limited, also concepts for increasing regulatory acceptance will be discussed
REGULATORY SESSION
CONTINUED
Best Practice Guidelines and Reporting Standards for Applications of Metabolomics in Regulatory
Toxicology: the International MERIT Project
Prof. Mark Viant, University of Birmingham, UK
During the last two decades metabolomics has become a very widely used technology in academic research, yet its application to regulatory science, including regulatory toxicology, has been limited While several factors contribute to this slow translation into regulatory practice, the most commonly cited roadblock by chemical regulators, government and industry scientists is the lack of standardisation, best practice guidelines and data and metadata reporting formats Here we will describe the final report of the MEtabolomics standaRds Initiative in Toxicology (MERIT) project, which brought together a team of international experts from multiple sectors to address this need MERIT sought to define best practice guidelines and minimal reporting standards for designing, undertaking, reporting and assessing the quality of both untargeted metabolomics and targeted metabolite analyses in the context of regulatory toxicology To provide context, the most relevant use cases for metabolomics in toxicology were also identified, including for example chemical grouping based upon metabolic phenotypes The MERIT guidelines included experimental design; QA/QC; sampling and extraction; data acquisition and processing of mass spectrometry and NMR spectroscopy assays; data processing and statistical analysis; and metabolite identification A strategy and architecture for integrated data management, sharing and exploitation in regulatory toxicology was also developed We concluded that most steps in the application of untargeted metabolomics and targeted metabolite assays to regulatory toxicology are well established, including significant recent progress in QA/QC We recommend that the MERIT minimal reporting standards and data management strategy are tested as multi-stakeholder use cases
SESSION 20: REGULATORY SESSION
Translating metabolomics from academic science into regulatory practice:
challenges and progress in pharmacology and toxicology
BIOMEDICAL
1A Session Keynote
10:15 a.m. – 10:45 a.m. Metabolomics Applications for Oncology and Immunology in Drug Discovery PRESENTING AUTHOR: Thomas Roddy, Agios Pharmaceuticals, United States
Metabolomics data from in vitro and in vivo studies is more comprehensive and in depth than ever Large data sets from metabolomics and flux studies are often daunting to analyze and interpret, especially when projects move quickly A major focus of our lab has been in developing workflows and data analytics to allow rapid turnaround of data and fast iteration of biological experiments Our goal is to quickly learn from one experiment, to design the next, and to iterate this process in a way that effectively impacts our projects, allowing us to identify novel biological mechanisms and pharmacodynamic biomarkers for our oncology and rare genetic disease programs In this presentation, I will briefly discuss our multidisciplinary MS lab (metabolomics, lipidomics, fluxomics, and proteomics) and data systems I will also present examples when metabolomics gave us unique insights into biological
processes, including the development of a pharmacodynamic marker for a cholesterol pathway oncology target, an analysis of the tumor microenvironment across several models, and the modulation of metabolism in immunological models (in vitro and in vivo)
SESSION 1: CANCER
Tuesday, June 25
10:15 a.m. – 12:00 p.m.
1B 10:45 a.m. – 11:05 a.m. Multi-omic discovery of metabolic rewiring in triple-negative breast cancer following mitochondrial folate transport ablation
PRESENTING AUTHOR: Steven Gross, Weill Cornell Medicine, United States
CO-AUTHORS: Qiuying Chen, Joshua B. Zuk, Chris A. Miller, Steve M. Fischer, Steven S. Gross
Mitochondrial tetrahydrofolate (THF)-mediated reactions provide one-carbon units for synthesis of purines, thymidine, and methylation of DNA, RNA, proteins, and lipids Inhibition of THF-mediated reactions (ie, antifolates) have been a staple of cancer chemotherapy, including triple-negative breast cancer (TNBC) The present study sought to broadly discover how TNBC cells retaliate to knockout of the mitochondrial THF transporter (MFT/ slc25a32), and consequent loss of mitochondria-dependent one-carbon trafficking reactions Using untargeted metabolomics, discovery proteomics and untargeted stable isotope tracing strategy, we discover that mitochondria folate transporter (slc25a32) gene deletion in TNBC cells elicits a profound rewiring of glucose to polyol pathway, concomitant with delayed cell cycle and a 6-10-fold increase in several aldo-keto reductases (AKRs) - enzymes that consume NADPH to facilitate cytosolic one carbon reaction that generates NADPH Activation of polyol pathway and switch of serine-derived one carbon metabolism from mitochondria to cytosol were similarly observed in methotrexate treated TNBC cells Our findings nominate these upregulated AKR enzymes as chemotherapeutic targets, for inhibition in combination with antifolate drugs Additionally, multi-omics studies revealed that loss of slc25a32 increases TNBC cell dependence on purine salvage, and TGF-β signaling with evidence of epithelial-mesenchymal-transition (ie, increased cell migration/invasion) Dependence of upregulated polyol pathway, purine salvage, cytosolic one carbon reaction and TGF-β signaling was supported by downregulation in slc25a32 protein-restored KO cells Taken together, multi-omic findings provide unexpected insights into how TNBC cells adapt to disabled mitochondrial folate-dependent one-carbon metabolism, and suggest novel therapeutic targets for combined intervention with antifolate drugs
1C 11:05 a.m. – 11:20 a.m. Investigating the metabolic response of cancer cells to indisulam PRESENTING AUTHOR: Lili Herendi, PhD student, United Kingdom
CO-AUTHORS: Anke Nijhuis, Arti Sikka, Eirini Koulura, Orli Yogev, Louis Chesler, Gerald Larrouy-Maumus, Hector Keun
Neuroblastoma (NB) is one of the most common type of solid tumour in infants Currently there are no reliable biomarkers identified predicting disease outcome in patients within the high-risk group highlighting the acute need for novel therapies Indisulam (E7070) an aryl sulphonamide, a carbonic anhydrase IX (CAIX) inhibitor currently in Phase II clinical trials for the treatment of patients with solid tumours has recently been connected with pre-mRNA splicing factor RNA binding protein 39 (RBM39) Recruitment of RBM39 by indisulam to the DCAF15/CUL4/E3 complex promotes proteasomal degradation These findings connect cancer cell line sensitivity to indisulam with stability of RBM39 and high expression of DCAF15 Our data confirmed sensitivity of IMR32 human NB cells to indisulam both in vitro and in vivo In IMR32, the DCAF15 dependent RBM39 degradation and mis-splicing were necessary, but not sufficient for the full cytotoxic response to indisulam Using LC-MS and GC-MS metabolomics analysis together with stable isotope labelling we have identified the activity of indisulam to be associated with alterations in metabolite pools connected with NADH production and changes in redox balance Furthermore, as mitochondrial respiration was also impaired after indisulam treatment, these metabolic alterations observed imply that neither CAIX nor RBM39 are the sole targets of indisulam Overall, these results provide insights into the contribution of metabolism to the mechanism of action of indisulam and suggest that metabolic subtypes of tumours may respond differently to therapy Such knowledge will improve our understanding of which patients would benefit from indisulam treatment
BIOMEDICAL
15th Annual Conference of the Metabolomics Society Page 13 1D 11:20 a.m. – 11:40 a.m. Rewiring of energy metabolism drives resistance to the proteasome inhibitor bortezomib
PRESENTING AUTHOR: Esther Zaal, Biomolecular Mass Spectrometry and Proteomics, Utrecht University, Netherlands CO-AUTHORS: Harm-Jan de Grooth, Pieter Langerhorst, Haley Baptist, Wei Wu, Celia R. Berkers
The proteasome inhibitor bortezomib is successfully applied in the treatment of multiple myeloma, but its efficacy is restricted by the wide-spread occurrence of resistance Metabolic alterations play an important role in cancer development and aid in the cellular adaptation to pharmacologically changed environments Metabolic changes may therefore also play an essential role in the development of drug resistance Interestingly, cells could become reliant on such drug-induced metabolic reprogramming, a vulnerability that could be exploited for therapy Here, the metabolic pathways involved in resistance to bortezomib were elucidated using a mass spectrometry-based metabolomics approach To this end, bortezomib-sensitive and -resistant cell lines were profiled using a combination of steady-state metabolomics experiments and stable isotope labelling approaches These metabolomics studies were complemented with a metabolism-oriented targeted proteomics approach We demonstrate that BTZ-resistant cells extensively rewire their mitochondrial energy metabolism and identify metabolic drugs that could overcome bortezomib resistance By investigating gene expression patterns of metabolic genes in genome-wide data of MM patient samples, we show that rewiring of mitochondrial metabolism correlates to drug response and survival In conclusion, we provide novel mechanistic insights in the role of mitochondrial energy production in mediating bortezomib resistance Our data indicate that this metabolic rewiring correlates to drug response in MM patients and provide rationale for combining bortezomib with metabolic drugs to increase treatment efficacy
SESSION 1: CANCER
Tuesday, June 25
10:15 a.m. – 12:00 p.m.
1E 11:40 a.m. – 11:55 a.m. Understanding metabolite heterogeneity in pancreatic ductal adenocarcinoma, and the role of adaptive metabolic reprogramming in chemotherapy resistance PRESENTING AUTHOR: Sarah Hancock, University of New South Wales, Australia
CO-AUTHORS: Jesse Estoque, Nigel Turner
Pancreatic ductal adenocarcinoma (PDAC) has one of the most dismal prognoses in modern medicine with a 5-year survival of just 77% Contributing to the poor survivability of PDAC is its highly aggressive and chemoresistant nature, which is driven by extreme genetic and phenotypic heterogeneity Mutations in oncogenes result in wide-ranging effects on cell metabolism, allowing the cells to acquire metabolites necessary for rapid growth and proliferation Cellular heterogeneity can aid the cancer cells in acquiring chemoresistance through adaptive metabolic reprogramming, in which chemotherapy action is circumvented by engaging pro-survival metabolic pathways In this study, we use an untargeted metabolomics approach to determine the breadth of metabolite heterogeneity across four PDAC cells lines (MiaPaCa2, Panc1, BxPC3 and AsPC1) and one non-cancerous immortalised human pancreatic ductal epithelial (HPDE) cell line Approximately 800 features (ie unique combinations of retention time and mass-to-charge, m/z) were detected across these four pancreatic cell lines and a number of metabolic pathways were found to be altered compared with noncancerous pancreatic cells, including metabolites involved in central carbon metabolism, glycolysis, glutaminolysis, nucleotide synthesis, and lipid synthesis Metabolite profiling of gemcitabine-treated PDAC cells has uncovered several potential adaptive metabolic pathways, many of which centre around non-essential amino acid metabolism Work is ongoing to elucidate mechanisms of chemoresistance in PDAC, including the use of stably labelled isotope tracing to further characterise mechanisms of chemoresistance in these cells
PLANT, FOOD, ENVIRONMENTAL AND MICROBIAL
2B 10:45 a.m. – 11:05 a.m. Developing Advanced and Integrated Metabolomics Technologies to Address the Grand Challenges of Metabolite Identification and Depth of Coverage
PRESENTING AUTHOR: Lloyd Sumner, University of Missouri, United States
CO-AUTHORS: Lloyd W. Sumner, Feng Qiu, Dennis Fine, Daniel Wherritt, Zhentian Lei, Anil Bhatia, Mark Schroeder, Aiko Barsch, Sven Meyer
The vast utility of metabolomics is well documented in the literature; however, its full scientific promise has not yet been realized due to multiple technical challenges These grand challenges include large-scale confident chemical identification of metabolites and greater depth of coverage We have developed sophisticated spectral, computational and integrated experimental metabolomics tools for the systematic and biologically directed annotation of plant metabolomes and for greater metabolome depth of coverage UHPLC-QTOF-MS/MS metabolite profiling was first performed using Medicago truncatula methanol extracts, and the data processed by peak deconvolution and formula prediction Metabolite identifications were first attempted through spectral matching with custom MS and MS/MS libraries of 222 plant specialized metabolites Additional identifications were predicted using novel software entitled ‘Plant Metabolite Annotation Toolbox’ (PlantMAT) that generates in-silico prediction of metabolite structures based upon orthogonal empirical data PlantMAT includes both GC-MS and LC-MS modules The data was imported into PlantMAT and structures for approximately 100 saponins and polyphenolic glycosides were predicted Approximately 80 of these were isolated, purified and concentrated by UHPLC-MS-SPE The SPE isolated compounds were eluted and 1D and 2D NMR spectra acquired The results demonstrated that the cumulative platforms allow for higher-throughput and high confidence metabolite identifications UHPLC-timsTOF-MS/MS analyses were performed to discover potentially coeluting compounds and to increase our metabolomics depth of coverage for isobaric compounds not readily separated by UHPLC Examples are provided for hydroxylated flavonoids A library of CCS values are being measured and compiled for added confidence in metabolite identification
SESSION 2: PLANT APPLICATIONS 1
Tuesday, June 25
10:15 a.m. – 12:00 p.m.
2C 11:05 a.m. – 11:20 a.m. From MS peak to unambiguous metabolite identification using the WeizMass spectral library and LC-MS-SPE-NMR system PRESENTING AUTHOR: Adam Jozwiak, Weizmann Institute of Science, Israel
CO-AUTHORS: Nir Shahaf, Prashant D. Sonawane, Tali Scherf, Ilana Rogachev, Asaph Aharoni
Despite rapid advances in MS-based methods, unambiguous and high-confidence metabolite annotation is hitherto a significant concern in
metabolomics experiments One of several complementary approaches that might assist in tackling this intricate issue is the usage of a comprehensive, reference compound-based spectral library We recently generated the WeizMass LC-MS based library composed of more than 6,000 spectra and representing diverse chemicals structures We also developed the MatchWeiz software that allows matching of experimental data to the WeizMass library Using such approach we significantly raised our confidence in metabolite identification, carrying out de-replication of known metabolites in diverse plant species and identifying in high confidence metabolites not reported previously from plants Direct coupling of LC-MS with Solid Phase Extraction (SPE) and NMR spectroscopy represents a complementary approach The main advantage of this set-up is its simplicity and low amount of material necessary for metabolite identification It is especially advantageous in case of amphipathic substances, eg saponins, requiring high quantities for NMR analysis In my presentation, I will demonstrate how hyphenated analytical techniques (ie LC-MS-SPE-NMR) facilitate saponin pathway discovery by providing structural data of complex metabolites and generating substrates for enzyme- and bio- activity assays Combination of high-resolution MS and several 2D-NMR techniques allowed unambiguous identification of novel acetylated medicagenic acid derived saponins from spinach Finally, we utilized the LC-MS-SPE-NMR system for an unequivocal annotation of biosynthetic intermediates produced by partial reconstruction of the biosynthetic pathway in heterologous system
2A Session Keynote
10:15 a.m. – 10:45 a.m. The volatile flavor composition network in tomato and its modification PRESENTING AUTHOR: Antonio Granell, CSIC, Spain
Tomato is a model for fruit ripening and more recently also for the identification of the molecular genetic basis of what makes fruit healthy and palatable Organoleptic and nutritional quality in this climacteric fruit is regulated at different levels and metabolites associated with organoleptic and nutritional composition are part of the ripening process and increasingly the target/focus of geneticists and breeders The nutritional value of tomato fruit is not based on calories but on the healthy compounds they provide to our diet (main source of antioxidants and vitC in Western diets) Many of the plant/ tomato nutritional and healthy compounds are often precursors of compounds that contribute to flavour what supports the contention that good flavour and healthy compounds are part of the mechanism plants use to reward frugivors for dispersing the seed contained in their fruits Breeding or Biotech approaches aimed to higher nutritional content should go hand with hand with good flavour in order to really have an impact on consumers In my presentation I will illustrate examples were the use of genetic resources in combination with high throughput genotyping and phenotyping and biotech approaches is contributing to identifying genomic regions, markers and genes associated /underlying the variation in compounds of organoleptic or nutritional value I will also present how Plant Biotechnology and Synthetic Biology approaches are used in our lab to further expand the natural variation in metabolites either to increase the levels of nutritional or good flavor compounds or to eliminate anti nutritional compounds
PLANT, FOOD, ENVIRONMENTAL AND MICROBIAL
15th Annual Conference of the Metabolomics Society Page 15 2D 11:20 a.m. – 11:40 a.m. Chocolate metabolomics
PRESENTING AUTHOR: Robert Hall, Wageningen UR, Netherlands
CO-AUTHORS: Ric CH de Vos, Isabelle Privat, Maud Lepelley, Roland Mumm, Marco CAM Bink, Jos A Hageman, Jwanro Husson, Veronique Maffone, Philippe Pollien, Jean-Claude Spadone, Susan Strickler, Dominique Crouzillat, Robert D Hall
Optimising and securing sustainable cacao production is hampered by a lack of knowledge of the chemical and genetic factors controlling the yield and quality of the beans used for preparing chocolate liquor We have used an integrated, multi-omics approach to genotype and chemically phenotype a dedicated F2 segregating population of a high yielding and a high quality Theobroma cacao parental cross Fermented beans and cocoa liquors obtained following standard industrial procedures were subjected to comprehensive metabolite profiling (LCMS pos/neg modes, GCTOFMS of (derivatised) polar compounds, and GCMS of volatile components) In parallel, sensory (taste) panel evaluations were performed on the chocolate liquors Dedicated statistics was applied to model sensory scores based on metabolite profiles and to select a small set of marker compounds predicting sensory quality scores based on either liquor or bean metabolites Subsequently, genetic mapping of the population was performed using co-dominant molecular markers and this map was used for large-scale Quantitative Trait Loci (QTL) analysis We identified 1760 traits (metabolites) in beans or liquors and these metabolites concerned many different chemical groups including amino acids, sugars, polyphenols and aromatic components 484 QTLs were also identified controlling either cocoa quality traits or individual metabolites indicating that 275% of the cocoa traits analysed is genetically controlled Further use of cacao fruit transcriptome data and gene mining of potential candidate genes co-localizing with QTLs controlling key cocoa quality parameters has given us for the first time deep insights into the genetic basis of cocoa (chocolate) quality
SESSION 2: PLANT APPLICATIONS 1
Tuesday, June 25
10:15 a.m. – 12:00 p.m.
2E 11:40 a.m. – 11:55 a.m. A tissue specific metabolomic study in hybrid aspen PRESENTING AUTHOR: Ilara Budzinski, Swedish University of Agricultural Sciences (SLU), Sweden CO-AUTHORS: Ilka N Abreu, Thomas Moritz
Hybrid aspen is a commercially fast-growing tree, used in short rotation wood production in many countries As a renewable natural resource, providing timber, fibers and energy, wood is important for the environmental and economic perspective Wood formation is a complex process, subject to multiple levels of regulation (from cell division through programmed cell death) Despite its importance, the metabolic profile underlying wood formation still poorly understood To overcome this, we present a tissue specific metabolomics study in hybrid aspen (Populus tremula x P tremuloides), using cryosectioning We used four-month-old trees cultivated under greenhouse conditions and supplied with different levels of fertilization solution (low, adequate and high) for controlling growth The stems were 20 µm thick tangential cryo-sectioned in: bark, inner bark, phloem, expanding phloem, cambium, expanding xylem, xylem and mature xylem Target and untargeted metabolomics (GC and LC-MS) was performed, including lipidomics analysis Trees treated with higher fertilization doses showed higher diameter and biomass, compared to the lower treatment By OPLS-DA we discriminate tissues and treatments Differentially abundant metabolites (VIP ≥10 and P ≤ 005) were identified from bark towards xylem As an example, proline, rhamnose, trehalose, sucrose exhibited a similar distribution pattern along the tissues, when comparing trees with contrasting stem diameter However, other metabolites were significant only in trees with smaller (fructose and glucose) or higher (arginine, methionine, salicin, stearyl acid) stem diameter The results obtained here represent the metabolic overview from bark towards wood-forming tissues, and highlighted the powerful combination of cryosectioning and metabolomics analysis
TECHNOLOGY
3A Session Keynote
10:15 a.m. – 10:45 a.m. The Internet for Social Machines PRESENTING AUTHOR: Barend Mons, GO FAIR, Netherlands
We are in a transition phase of science, where machines (mainly computers) have become our major research assistants Humans and computers increasingly work together as ‘social machines’ to makes sense of complex natural phenomena However, computers need a very different input as compared to people and the way we adapt the communication and reuse of our research results is adopting to this new situation only at glacial speed Still, the 15 FAIR Principles, publsihed in 2016, dealing with machine actionable data and services, have found unusually rapid uptake among a broad spectrum of stakeholders, from research scientists who create and reuse data, to publishers who distribute data, to science funders who track impact of data Barend will describe the FAIR Principles and show examples of how they have been implemented He will also present a set of core FAIR Metrics that can help gauge the level of FAIRness of any digital resource Of particular interest is how additional FAIR Metrics can (and should) be defined to address community-specific data structures and analytic requirements This discussion, and these examples will be presented in the context of the International GO FAIR Initiative GO FAIR is a voluntary community of stakeholders devoted to implementation solutions of an emerging Internet of FAIR Data and Services
SESSION 3: DATA INTEGRATION & DATA BASING 1
Tuesday, June 25
10:15 a.m. – 12:00 p.m.
3B 10:45 a.m. – 11:05 a.m. Matching Untargeted Liquid Chromatography – Mass Spectrometry Features Across Multiple Cohorts: Finding the Same Needles in Several Haystacks Via Networks
PRESENTING AUTHOR: Rui Climaco Pinto, Imperial College London, United Kingdom
CO-AUTHORS: Ibrahim Karaman, Matt R. Lewis, Jenny Hällqvist, Manuja Kaluarachchi, Gonçalo Graça, Elena Chekmeneva, Mohammad Arfan Ikram, Abbas Dehghan, Paul Elliott, Ioanna Tzoulaki, David Herrington, Timothy Ebbels
In untargeted metabolomics, accurate within-dataset feature matching is aided by accessing large amounts of chromatographic/spectral information in each sample In contrast, when matching features from multiple cohorts/batches that used the same analytical method but were acquired and peak-picked separately, only limited information is available - often only retention time and m/z (RT-MZ) medians We propose a new cross-cohort matching method which uses the RT-MZ median values of each feature (plus optionally feature intensity and other feature-quality measures) Initially matches within manually-defined RT-MZ thresholds between all one-to-one dataset combinations are detected In the next - key - step it builds a network of features (nodes) based on those matches (edges) Only matches in subnetworks (connected components) in which all nodes are connected to all other nodes (maximal cliques) are accepted, which removes features that matched by chance As some features may present multiple matching possibilities, a third step using RT-MZ differences to define a match-quality score is then used to decide the best single matches We illustrate the method’s performance by matching thousands of features from large studies of serum samples and inspecting the matching accuracy of hundreds of manually annotated metabolites, and by looking at several feature-quality metrics The method is not computationally intensive – eg matching 3 cohorts, each with 1000s of features, takes less than a minute on a typical desktop machine The new approach addresses a key problem in metabolomics studies and promises to make analysis of large untargeted multi-cohort data sets a viable option
3C 11:05 a.m. – 11:20 a.m. Visualizing metabolomics data in directed biological networks PRESENTING AUTHOR: Denise Slenter, Maastricht University, Netherlands
CO-AUTHORS: Martina Kutmon, Jonathan Mélius, Ryan Miller, Georg Summer, Chris T. Evelo, Egon L. Willighagen
Metabolomics data describes the state of a biological system at a phenotypic level Unfortunately, not all measured metabolites can be linked to metabolite identities present in biological pathway models The resulting sparseness makes it more complicated to use metabolomics data in pathway and network analysis By creating networks from existing pathways, the metabolic data sparseness can be overcome, by calculating the shortest path between metabolites To upscale this approach, we need to be able to combine different pathway knowledge bases and introduce detailed directionality information, ensuring the shortest paths follow one-directional biological cause-and-effect paths The presented work creates subnetworks of shortest, directed pathways between active metabolites First, with the WikiPathways RDF, we created a directed network of all metabolic reactions from the WikiPathways and Reactome pathway knowledgebase In the next step, we identified the location(s) of the active metabolites in the network, in which we match data with nodes in the network using knowledge from Wikidata Finally, using the cyNeo4j app for Cytoscape we extracted the smallest connected subnetwork between the changed metabolites using the functionality of the graph database Neo4j We developed a new solution to visualize the biological pathways involved in sparse metabolomics data Using knowledge from two pathway resources, we can show the directed networks between active metabolites from metabolomics data By using Neo4j and Cytoscape, we ensure the computational calculation environment for larger networks as well as advanced visualization functionality to investigate the identified subnetworks This approach can be extended with proteomics and transcriptomics data
Is Your Lab Up to Speed?
Today’s analytical labs face dynamic challenges. You need the right tools and instruments to keep your lab up to speed.
The Agilent 6546 LC/Q-TOF provides a faster path to rock solid yes/no answers, with the ability to look deeper into complex samples than ever before. With simultaneous high sensitivity, high resolution, and wide dynamic range offered all in one instrument, you no longer have to accept compromises.
Accelerate your capabilities and keep your lab up to speed with the Agilent 6546 LC/Q-TOF. www.agilent.com/chem/6546
TECHNOLOGY
SESSION 3: DATA INTEGRATION & DATA BASING 1
Tuesday, June 25
10:15 a.m. – 12:00 p.m.
3D 11:20 a.m. – 11:40 a.m. High-throughput metabolomics identifies substrate-enzyme relationships in a metabolism-wide CRISPR interference library PRESENTING AUTHOR: Hannes Link, Max Planck Institute for Terrestrial Microbiology, Germany
CO-AUTHORS: Stefano Donati, Vanessa Pahl, Timo Glatter
Construction of large genetic variant libraries has become very fast and versatile The current challenge is measuring molecular phenotypes of large strain libraries with high-throughput Here, we show that high-throughput metabolomics identifies metabolic phenotypes in a CRISPR interference library in Escherichia coli We have recently created a metabolism-wide CRISPR interference (CRISPRi) library that targets all genes in the metabolic network of E coli and characterized growth of the strains with next generation sequencing (1) Now we measured the metabolome of 118 CRISPRi strains, which have targets in central metabolism, and in biosynthesis pathways of cofactors, nucleotides and amino acids By using a quantitative and fast (2 min) isotope ratio LC–MS/MS method (2), we quantified about 150 primary metabolites in the CRISPRi strains In many strains we observed specific increases of substrates of the targeted enzymes Especially downregulation of enzymes in biosynthetic pathways resulted in an accumulation of intermediates, which are under normal conditions undetectable in E coli These substrate-enzyme relationships suggest that biosynthetic enzymes in wild-type cells operate far away from their maximal capacity, and therefore biosynthetic intermediates are often very low abundant Finally, by integrating the metabolome data with proteome data we show how metabolite concentration changes affect enzyme-level regulation and the global proteome of CRISPRi strains
3E 11:40 a.m. – 11:55 a.m. Weighting strategies for the analysis of secondary outcomes in nested case-control metabolomics data PRESENTING AUTHOR: Gerard Gonzales, Ghent University, Belgium
CO-AUTHORS: Vladimer Kobayashi
Freely available metabolomics datasets in public repositories allow us to investigate other biological questions without necessarily recruiting new cohorts of human volunteers However, considering that the data was selected for a different purpose, it may potentially introduce bias when analysing secondary outcomes of interest We propose to remedy this problem by introducing weights to observations In this study, we tested various weighting strategies namely, inverse probability weighting and the ones derived from boosting and neural network We then illustrate their uses to investigate the urinary metabolomic signature specifically associated with smoking by using available data from a case-control urinary metabolomics study where the participants were originally selected for presence or absence of lung cancer (MTBLS28) We show that directly using the dataset without weighting resulted to biomarkers of lung cancer being strongly associated to smoking This distorts the biological interpretation of metabolites and pathways associated with smoking and does not generalize to new population of non-cancer patients The combination of weighting strategies with popular analytical models (ie PLS-DA, generalized linear models with regularization, and random forest) has the effect of not only leading to statistically valid models with good predictive ability, but also, the extracted biomarkers are independent of the primary outcome In short, the extracted urinary biomarkers were more specifically associated with smoking than with lung cancer status Consequently, we developed a framework for introducing weights to guide researchers in choosing an appropriate weighting method Finally, we discuss the application of the framework to metabolomics studies using secondary data
NEW FRONTIERS
15th Annual Conference of the Metabolomics Society Page 19 4A Session Keynote
10:15 a.m. – 10:45 a.m. Improving Technologies for High Throughput and Miniaturized Metabolomics for Precision Medicine PRESENTING AUTHOR: Thomas Hankemeier, Leiden University, Netherlands
Where genomics has proven to be successful to predict disease risk, metabolomics can assess the actual health state and monitor disease development and treatment response Large-scale metabolomics studies are necessary for better and more specific prognosis of chronic diseases For this efficient and quantitative metabolomics methods are necessary Novel technologies to enable this will be discussed in this lecture We have developed a hanging droplet evaporator that allows innovative workflows for high throughput (HT) and miniaturized sample preparation We have developed electrodriven sample preparation technologies for metabolomics Next, the use of microfluidic-based advanced in-vitro models with organotypic characteristics will be introduced, and how this platform can be used to study disease mechanisms and disease pathways identified using metabolomics This requires miniaturized metabolomics methods and technologies Actually, similar innovations for HT metabolomics can be used for miniaturized metabolomics An outlook will be given how metabolomics will impact clinical research and ultimately clinical decision support
SESSION 4: NOVEL TECHNOLOGIES
Tuesday, June 25
10:15 a.m. – 12:00 p.m.
4B 10:45 a.m. – 11:05 a.m. Investigation of host-microbiota co-metabolism as a new strategy for biomarker discovery – New Chemical Biology tools for Metabolomics analysis
PRESENTING AUTHOR: Daniel Globisch, Uppsala University, Sweden
CO-AUTHORS: Mário S.P. Correia, Louis P. Conway, Weifeng Lin, Abhishek Jain, Caroline Ballet, Neeraj Garg
The detailed investigation of metabolites in human samples has been termed metabolomics and carries a great potential for the discovery of unknown biomarkers Metabolomics still requires advanced chemical tools compared to other ‘omics areas One of the most exciting scientific developments in the past decade has been the understanding that gut microbiota profoundly impact human physiology The complex consortium of trillions of microbes possesses a wide range of metabolic activity Only limited information on this interspecies co-metabolism has been elucidated on a molecular level We have developed new state-of-the-art Chemical Biology techniques for an enhanced metabolomics analysis using liquid chromatography-coupled with tandem mass spectrometry (UPLC-MS/MS) A unique chemoselective probe immobilized to magnetic beads was prepared for analysis of human fecal samples This complex probe allows for facile extraction of metabolites and led to increased mass spectrometric sensitivity by a factor of 2000 In another new methods, we utilized selective enzymatic treatment of metabolites in human samples to easily identify converted metabolites and elucidate their chemical formula using mass spectrometry We chemically synthesized each identified molecule to unequivocally validate the molecular structure Using this specific workflow, we have successfully identified three times as many sulfated metabolites than reported in the Human Metabolome Database Our unique metabolite-analyzing methodologies at the interface of Chemistry and Biology are aimed at overcoming limitations in mass spectrometry-based metabolomics research We are applying these methods for the discovery of unknown metabolites in medical relevant samples to evaluate their potential as biomarkers for pancreatic cancer
4C 11:05 a.m. – 11:20 a.m. GC×GC-TOFMS and SIFT-MS approaches for clinical breath-based asthma phenotyping PRESENTING AUTHOR: Pierre-Hugues Stefanuto, Liège University, Belgium
CO-AUTHORS: Delphine Zanella, Joeri Vercammen, Florence Schleich, Renaud Louis, Jean-François Focant
The ballistic rise of analytical technologies has opened a large playground for all type of “omics” screening On one side, separation science based on multidimensional methods such as comprehensive two-dimensional gas chromatography (GC×GC) appeared as one of the methods of choice for the characterization complex mixtures On the other side, direct introduction instruments such as single ion flow tube mass spectrometry (SIFT-MS) offered the capacity to perform both targeted and non-targeted analyses within a few minutes At the price of high cost equipment and limited adaptability to routine medical usage, GC×GC-HRTOFMS offers the possibility to almost completely characterize a sample composition This is of prime importance when systems biology are considered For large scale screening, SIFT-MS can generate compositional patterns from direct sample introduction at the same time than other routine medical actions These two orthogonal approaches for pathology screening should ideally conduct to identical sample classifications but have never been directly compared over an identical set of patients In this study, breath from 50 asthmatic patients were analyzed by both techniques As a reference, asthma phenotypes were established using sputum analysis Breath samples were collected using TedlarÒ bags For GC×GC-HRTOFMS analyses, the bags were transferred onto thermal desorption tubes prior to injection For SIFT-MS, the bags were directly emptied into the instrument Next, data were analyzed using identical processing workflow We observed that both approaches offered similar classification capacities GC×GC-HRTOFMS allowed identifying the putative markers for comparison with previous studies and metabolic interpretation while SIFT-MS offered a faster screening-capacity
NEW FRONTIERS
4D 11:20 a.m. – 11:40 a.m. Mathematical modelling of metabolism: a driver for developing personalized and precision medicine PRESENTING AUTHOR: Natal van Riel, Eindhoven University of Technology, Netherlands
Metabolic derailments associated with metabolic syndrome and type 2 diabetes can be studied with mixed meal tests (MTT’s) The plasma metabolome enriched with measurements of hormones and cytokines, provide valuable information about the physiological state of an individual An increasingly important, but complex task is to extract biomedical parameters with diagnostic value from large and multivariate datasets We applied model-based data processing and analysis, combining computer simulation models, stochastic models of uncertainties and machine learning of time-series data obtained from repeated blood sampling during MTT’s In a mouse model of metabolic syndrome we identified differences in lipid metabolism to be associated with variation in weight gain and development of NAFLD (fatty liver disease) The computational model predicted the progression of dyslipidemia to be linked to bile acids, which was confirmed in a validation study To investigate the role of bile acids in humans with metabolic syndrome a detailed simulation model of bile acid metabolism and physiology was developed Model-based analysis of plasma bile acids provides a metabolic ‘window’ on the gut microbiome and other digestive processes in the gastrointestinal tract The model was applied to simulate bariatric surgery in patients with metabolic syndrome The model predicts changes in dynamics in the small intestine to result in a stronger and faster GLP-1 response, hence insulin secretion, explaining observations of rapid glycemic improvement after surgery The simulation model turned out to be sufficiently robust that personalized variants for individual patients could be made, using MTT plasma bile acid metabolomics as input
SESSION 4: NOVEL TECHNOLOGIES
Tuesday, June 25
10:15 a.m. – 12:00 p.m.
4E 11:40 a.m. – 11:55 a.m. TIMS and PASEF multiply speed and sensitivity in lipidomics PRESENTING AUTHOR: Catherine G. Vasilopoulou, Max Planck Institute of Biochemistry, Germany
CO-AUTHORS: Karolina Sulek, Andreas-David Brunner, Dmitry Voytik, Aiko Barsch, Sven Meyer, Ulrike Schweiger-Hufnagel, Ningombam Sanjib Meitei, Matthias Mann, Florian Meier
We have recently introduced a novel scan mode termed ‘parallel accumulation – serial fragmentation’ (PASEF), which promises to overcome longstanding limitations in throughput and sensitivity of mass spectrometry-based proteomics (Meier et al, PMID:26538118; Meier et al, PMID:6283298) PASEF synchronizes precursor selection with trapped ion mobility spectrometry (TIMS) and achieves over ten-fold increased sequencing rates without loss in sensitivity Here we explore the benefits of PASEF for lipidomics We analyzed lipid extracts from human plasma (SRM 1950), mouse liver and HeLa cells via nanoflow LC coupled to a high resolution TIMS-QTOF mass spectrometer (Bruker timsTOF Pro) Raw data were processed with MetaboScape (Bruker) and MS/MS spectra were annotated with SimLipid (PREMIER Biosoft) As compared with conventional TIMS-MS/MS, we acquired six times more MS/MS scans with PASEF, which translated into about twice as many lipid identifications The PASEF speed allowed us to reduce the LC analysis time from 90 to 30 min, while still covering over 90% of the lipids identified with the longer gradient Comparison to community efforts reveals an excellent coverage of all major lipid classes from just 1 μL plasma The ion mobility dimension further allows separation of isomeric species and provides a high-precision measure of lipid collisional cross sections (CCS) with CVs <1% In a single experiment, we compiled a CCS library of over 1000 lipids and show high correlation with literature as well as predictions based on machine learning (R2>098) We anticipate that accurate CCS measurements in conjunction with PASEF acquisition will greatly benefit metabolomics and lipidomics
