Issue 6 - January 2012


Online version of this newsletter:

Welcome to the sixth issue of MetaboNews, a monthly newsletter for the worldwide metabolomics community. In this month's issue,
we feature a Research Spotlight article on a paper entitled "Understanding and Classifying Metabolite Space and Metabolite-Likeness." This newsletter is being produced by The Metabolomics Innovation Centre (TMIC,, and is intended to keep metabolomics researchers and other professionals informed about new technologies, software, databases, events, job postings, conferences, training opportunities, interviews, publications, awards, and other newsworthy items concerning metabolomics. We hope to provide enough useful content to keep you interested and informed and appreciate your feedback on how we can make this newsletter better (

Note: Our subscriber list is managed using Mailman, the GNU Mailing List Manager. To subscribe or unsubscribe, please visit

Current and back issues of this newsletter can be viewed from the newsletter archive (

Software/Stat Spotlight

1) Research Spotlight

TNO Logo
Universiteit Leiden Logo
Netherlands Metabolomics Centre Logo
Understanding and Classifying Metabolite Space and Metabolite-Likeness

Feature article contributed by Julio E. Peironcely, PhD student on Computational Metabolomics and Metabolite Identification, at TNO, Leiden University and the Netherlands Metabolomics Centre, The Netherlands

Original article: Peironcely JE, Reijmers T, Coulier L, Bender A, Hankemeier T. Understanding and classifying metabolite space and metabolite-likeness. PLoS One. 2011;6(12):e28966. Epub 2011 Dec 14. [PMID: 22194963]

In metabolomics there is a recurrent bottleneck: metabolite identification.  Knowing the identity, i.e., the chemical structure, of the detected compounds is essential to interpret the experimental results.

Candidate structures that match experimental data are proposed either by querying molecular databases or by using chemical structure generators. In either case, the expert can face a large list of compounds, from which to chose the correct structure. This list could be ranked according to the metabolite-likeness of the compounds.

With this work we wanted to answer two questions:
  1. What are the common characteristics of human metabolites?
  2. Can we predict the metabolite-likeness of a chemical structure?
This work describes the application of computational tools to predict the metabolite-likeness score of a molecule, i.e., how much it resembles a metabolite, and to acquire a global understanding of how the space of human metabolites is organized.


Since we wanted to compare metabolites with non-metabolites, two molecular datasets were selected.  Human metabolites from the HMDB were used as the metabolite set and commercially available compounds listed in ZINC database were the non-metabolite dataset.

Molecules present in both datasets were removed, as well as molecules in the HMDB that were described as drugs.

What are the common characteristics of human metabolites?

Physicochemical properties

Several physicochemical properties were calculated for the HMDB and ZINC datasets. Principal component analysis (PCA) was performed. The result of this PCA (Figure 1) reveals that both datasets cannot be completely separated on the basis of physicochemical properties. This lack of separation observed in the PCA, made us think that the utilization of more sophisticated methods was required.

Principal component analysis of HMDB and
          ZINC datasets

Figure 1.
Principal component analysis of the HMDB and ZINC datasets.

By looking at the properties that contributed the most to the slight separation in the PCA (Figure 2), we concluded that metabolites are more soluble in water, have a lower molecular weight, have less complex structures, and fewer carbon atoms than non-metabolites. Furthermore, Polar Surface Area (PSA) tends to be larger in metabolites, suggesting that they do not penetrate cell membranes as efficiently as non-metabolites.

          properties contributing most to the variance in the first two
          principal components of the PCA
Figure 2.
Physicochemical properties contributing most to the variance in the first two principal components of the PCA.

Fingerprint Features and Frequent Fragments

Molecules from the HMDB and ZINC were described using ECFP_4 features, which can be seen as substructures, and partitioned using a Classification Tree (Figure 3).  At each branching point of the tree, a feature is chosen when it maximizes the split between metabolites and non-metabolites.

Click on the thumbnail below to view a larger version of the image

Classification tree of the ECFP_4
              features of HMDB and ZINC datasets

Figure 3.
Classification tree of the ECFP_4 features of the HMDB and ZINC datasets.

From this we learn that hydroxyl groups are characteristic of metabolites. Also, nitrogen-containing moieties correlate with non-metabolites. Acyclic molecules lacking hydroxyls are likely to be metabolites.

Can we predict the metabolite-likeness of a chemical structure?

Building the model

When classifying molecules in silico, different accuracies are obtained for each representation and algorithm used. Thus, we selected five different molecular representations (Atom Counts, Physicochemical Properties, MDL Public Keys, ECFP_4 and FCFP_4 fingerprints) and three different classification algorithms (Support Vector Machines (SVM), Random Forest (RF), Naïve Bayes Classifier (NB)). Our aim was to employ as our model of Metabolite-Likeness the combination reporting the highest accuracy in the predictions.

The process of model building is depicted in Figure 4. A standardization process cleans the molecules from both databases. Diversity selection is performed to reduce the impact that overrepresented families of metabolites, for instance lipids, might have in the model. This involved clustering each dataset, where the cluster centers were collected as the training set and the other compounds were used as the test set.

Model building workflow
Figure 4.
Model building workflow.

Since SVM and RF classifiers require the tuning of some metaparameters, we performed a five-fold cross validation to select their optimal values. Once we had the metaparameters, fifteen models (five representations x three classifiers) were built. These models were used to classify the molecules in the test set and, as a result, the best performing model was the one built with Random Forest and MDL Public Keys. It classified correctly 99.84% of the metabolites and 88.79% of the non-metabolites.

Prospective validation of the model

A common problem of predictive models is how they perform when predicting new objects. Hence we compiled three prospective validation sets to test the quality of our best model. The first dataset contained 457 metabolites that had not yet been included in the HMDB. The second dataset represented non-metabolites and included molecules from ChEMBL, which can be seen as background dataset alternative to ZINC. The third dataset were drugs from DrugBank. These were selected to test the hypothesis that many drugs tend to mimic metabolites, or at least they are more metabolite-like than screening compounds.

The results (Figure 5) showed that 95.84% of the new metabolites were predicted correctly. Concerning drugs, 54.3% obtained a metabolite-likeness of 50% or higher, which was in accordance with our assumption that many drugs resemble metabolites. For the ChEMBL compounds, only 22.29% were predicted as metabolites.

 Metabolite-likeness distribution of the
          prospective validation sets

Figure 5.
Metabolite-likeness distribution of the prospective validation sets.

Molecules of the three different classes, which fall into different bins of metabolite-likeness scores, are presented in Figure 6. The first noticeable feature is the absence of a metabolite with a predicted metabolite-likeness smaller than 10%, underlining the homogeneity of metabolites as a class. Metabolite HMDB13193 obtained the lowest metabolite-likeness, 17%, and contains two chlorine atoms, which is not common in metabolites. Another interesting situation occurs with molecules that have a steroid scaffold, a common fragment in endogenous metabolites. Drug DB00180 (flunisolide) obtains a metabolite-likeness value of 52%. It possesses a fluorine atom, which is not frequent in metabolites, and which might have reduced its metabolite-likeness score. Conversely, ChEMBL compound CHEMBL1163241 also has the steroid scaffold but obtains a score of just 35.2% on the metabolite-likeness scale, due to having two fluorine atoms and a secondary amine, features that the classification tree revealed to be common in non-metabolites. Compounds with high-predicted metabolite-likeness are DB00131 (adenosine monophosphate), DB00125 (L-arginine), CHEMBL6422, and CHEMBL14568, which receive 84.2%, 99%, 82.8%, and 96.8%, respectively. Adenosine monophosphate includes the phosphate group, frequently found in metabolites together with two hydroxyl groups. Metabolite-like features of L-arginine, like linearity and a carboxylic group, outweigh the non-metabolite features like the nitrogen-containing functional groups. While compound CHEMBL6422 possesses carboxylic acid and hydroxyl functionalities, CHEMBL14568 is small, linear, and also exhibits a hydroxyl group, leading to a very high metabolite-likeness score.

Click on the thumbnail below to view a larger version of the image

Molecules of the prospective validation sets with
                different predicted metabolite-likeness values

Figure 6. Molecules of the prospective validation sets with different predicted metabolite-likeness values.

These results demonstrate that our model is successful at identifying whether a molecule is a metabolite or not. We expect metabolite-likeness prediction to help studies that involve metabolite identification in the future, when no database match is found for the unknown compound. Then the candidate structures are generated based on mass spectrometry data, e.g., elemental composition, using a structure generation tool. These output molecules would be ranked according to their metabolite-likeness.

Please note: If you know of any metabolomics research programs, software, databases, statistical methods, meetings, workshops, or training sessions that we should feature in future issues of this newsletter, please email Ian Forsythe at

Biomarker Beacon

2) Biomarker Beacon

Feature article contributed by Ian Forsythe, Editor, MetaboNews, Dept of Computing Science, University of Alberta, Edmonton, Canada

Metabolomics is an emerging field that is complementary to other omics sciences and that is gaining increasing interest across all disciplines. Because of metabolomics' unique advantages, it is now being applied in functional genomics, integrative and systems biology, pharmacogenomics, and biomarker discovery for drug development and therapy monitoring. More than 95% of today's biomarkers are small molecules or metabolites (MW <1500 Da), which can be used for disease testing, drug testing, toxic exposure testing, and food consumption tracking. While standard clinical assays are limited in the number and type of compounds that can be detected, metabolomics measures many more compounds. Since a single compound is not always the best biomarker (diagnostic, prognostic or predictive), healthcare practitioners can use metabolomics information about multiple compounds to make better medical decisions. Global metabolic profiling is now being used to determine clinical biomarkers in assessing the pathophysiological health status of patients.

In the following two recent studies, metabolomics approaches were used to develop biomarker tools for the identification of biomarkers associated with diabetic kidney disease and ovarian cancer, respectively.

1. van der Kloet FM, Tempels FWA, Ismail N, van der Heijden R, Kasper PT, Rojas-Cherto M, van Doorn R, Spijksma G, Koek M, van der Greef J, Mäkinen VP, Forsblom C, Holthöfer H, Groop PH, Reijmers TH, Hankemeier T. Discovery of early-stage biomarkers for diabetic kidney disease using ms-based metabolomics (FinnDiane study). Metabolomics. 2012 March, Volume 8, Number 1, 109-119, DOI: 10.1007/s11306-011-0291-6 [Metabolomics]

In this paper, the research team performed metabolite profiling to identify early-stage biomarkers for diabetic kidney disease (DKD) using gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS). A clinical indicator of DKD is abnormally high urinary albumin excretion rates. The goal of the study was to uncover urinary biomarkers that allow one to differentiate between the progressive and non-progressive forms of albuminuria in humans. As a result of this work, the researchers pinpointed acyl-carnitines, acyl-glycines, and metabolites related to tryptophan metabolism as the differentiating biomarkers.

2. Fong MY, McDunn J, Kakar SS. Identification of metabolites in the normal ovary and their transformation in primary and metastatic ovarian cancer. PLoS One. 2011;6(5):e19963. Epub 2011 May 19. [PMID: 21625518]

This research team sought to characterize the human ovarian metabolome and identify disease-associated changes due to primary epithelial ovarian cancer (EOC) and metastatic ovarian cancer (MOC). The team used three analytical platforms: 1. gas chromatography mass spectrometry (GC/MS), 2. liquid chromatography tandem mass spectrometry (LC/MS/MS) set up to catalog positive ions, and 3. LC/MS/MS set up to catalog negative ions. According to this paper, the human ovarian metabolome consists of 364 biochemicals. Upon transformation of the ovary, two energy utilization pathways were perturbed, namely β-oxidation of fatty acids and glycolysis, and the following metabolites were present at increased levels in EOC and MOC: carnitine, acetylcarnitine, and  butyrylcarnitine. In EOC, there were significant increases in phenylpyruvate and phenyllactate. In both EOC and MOC, the research team also found increased levels of 2-aminobutyrate. Metabolites found at increased levels in various disease states may serve as candidate biomarkers for the progression of ovarian cancer.

Metabolomics Current Contents

3) Metabolomics Current Contents

Recently published papers in metabolomics:


4) MetaboNews

30 Jan 2012

Genetic regulation of metabolomic biomarkers – paths to cardiovascular diseases and type 2 diabetes - The research group at the Institute for Molecular Medicine Finland (FIMM) has revealed eleven new genetic regions associated with the blood levels of the metabolites, including new loci affecting well-established risk markers for cardiovascular disease and potential biomarkers for type 2 diabetes. The findings may help in elucidating the processes leading to common diseases. The study will be published in Nature Genetics.

In a study to the genetic variance of human metabolism, researchers have identified thirty one regions of the genome that were associated with levels of circulating metabolites, i.e., small molecules that take part in various chemical reactions of human body. Many of the studied metabolites are biomarkers for cardiovascular disease or related disorders, thus the loci uncovered may provide valuable insight into the biological processes leading to common diseases.
Laboratory tests used in the clinic typically monitor one or few circulating metabolites. The researchers at the Institute for Molecular Medicine Finland (FIMM) used a high throughput method called nuclear magnetic resonance (NMR) that can measure more than hundred different metabolites in one assay. This provides a much more in-depth picture of circulating metabolic compounds.

Paper: Kettunen J, Tukiainen T, Sarin A-P, Ortega-Alonso A, Tikkanen E, Lyytikäinen L-P, Kangas AJ, Soininen P, Würtz P, Silander K, Dick DM, Rose RJ, Savolainen MJ, Viikari J, Kähönen M, Lehtimäki T, Pietiläinen KH, Inouye M, McCarthy MI, Jula A, Eriksson J, Raitakari OT, Salomaa V, Kaprio J, Järvelin M-R, Peltonen L, Perola M, Freimer NB, Ala-Korpela M, Palotie A, Ripatti S. Genome-wide association study identifies multiple loci influencing human serum metabolite levels. Nature Genetics, 29th January, 2012 (online).

27 Jan 2012

Giant Cell Reveals Metabolic Secrets - Chemical reactions within the cell produce intermediate and end products in the form of small molecules called metabolites. Using an approach called metabolomics, a research team led by Kazuki Saito of the RIKEN Plant Science Center, Yokohama and Tsuruoka, has elucidated the localization and dynamics of 125 metabolites within a single giant cell of the freshwater alga Chara australis. The team's findings provide important insights into the fundamental processes of cells in general.

Metabolites play important roles in the regulation of critical biological processes, such as growth, differentiation, and, in the case of so-called 'secondary metabolites', chemical defense. "Metabolomics is the systematic study of these unique chemical footprints, and involves identifying and characterizing the many metabolites found in a cell, tissue, organ or organism, as well as their production, distribution and dynamics," explains Saito.
Because the enzymes involved in producing and converting different metabolites are often localized within subcellular structures called organelles, biologists generally assumed that metabolites are also highly compartmentalized within the cell, but none had demonstrated this comprehensively.
"Understanding the compartmentalization and dynamics of metabolites within single organelles represents an enormous technical challenge, not least because of the tiny size of these structures in most cells," says Saito.
Paper: Oikawa A, Matsuda F, Kikuyama M, Mimura T, Saito K. Metabolomics of a Single Vacuole Reveals Metabolic Dynamism in an Alga Chara australis. Plant Physiology, 2011; 157 (2): 544 DOI: 10.1104/pp.111.183772

Source: ScienceDaily
24 Jan 2012

Upregulated Metabolite May Be Target for Neuropathic Pain Therapy - Blocking overproduction of the metabolite N,N-dimethylsphingosine (DMS) in the spinal cord could feasibly represent a therapeutic option for treating neuropathic pain, researchers claim. A team at Washington University School of Medicine, St. Louis, and The Scripps Research Institute used an MS-based metabolomics approaches to compare metabolite levels in specific tissues of tibial nerve-transacted (TNT) experimental rats and sham-operated control rats. Tissues analyzed included spinal cord dorsal horn and dorsal root ganglia, damaged tibial nerve, and blood plasma.
Their results, reported in Nature Chemical Biology by Gary Siuzdak, Ph.D., and colleagues, demonstrated that 94% of metabolite differences between TNT rats and control rats occurred in the ipsilateral dorsal horn, rather than in the damaged nerve itself. When the team further characterized dysregulated metabolites in the dorsal horn tissue, they identified multiple alterations in sphingomyelin-ceramide metabolism 21 days after TNT injury. “We therefore hypothesized that dysregulated metabolites in this pathway may be linked to the physiological changes underlying neuropathic pain and represent possible new targets for therapeutic intervention,” they state.
The changes in dorsal horn metabolite concentrations were consistent with degradation of sphingomyelin, and included significant upregulation of DMS, which hasn’t previously been investigated in the context of neuropathic pain, the authors add. Of significant interest was the finding that intrathecal injections of DMS in healthy rats led to the animals developing mechanical allodynia (pain resulting from a stimulus that wouldn’t normally be painful) in the hind paw. This effect occurred at injected concentrations of DMS that resulted in similar dorsal horn levels of the metabolite that were found in the TNT experimental mice.

Paper: Patti GJ, Yanes O, Shriver LP, Courade JP, Tautenhahn R, Manchester M, Siuzdak G. Metabolomics implicates altered sphingolipids in chronic pain of neuropathic origin. Nat Chem Biol. 2012 Jan 22. doi: 10.1038/nchembio.767. [Epub ahead of print] [PMID: 22267119]

Source: Genetic Engineering & Biotechnology News

Please note: If you know of any metabolomics news that we should feature in future issues of this newsletter, please email Ian Forsythe (

Metabolomics Events

5) Metabolomics Events

3 Feb 2012

Cancer Metabolomics: Elucidating the Biochemical Programs that Support Cancer Initiation and Progression
Venue: New York, New York, USA

Since the 1920s, it has been recognized that cancer cells exhibit metabolic features that are distinct from those of 'normal' cells. However, a comprehensive picture of cancer metabolism and its molecular underpinnings has been essentially unapproachable—that is, until very recently. With the emergence of effective analytical strategies for broad-based metabolite profiling (both targeted and untargeted), the cancer cell 'metabolome' has now come into sight. Taking advantage of LC-MS-based analytical platforms, the participating speakers will describe new knowledge of metabolic pathways that distinguish cancer cells, signaling cascades that drive cancer-selective metabolic pathways and implications for the development of novel cancer chemotherapies.

Call for Poster Abstracts
A poster session will be held and a selected number of presenters will be asked to give brief oral presentations. The deadline for abstract submission is Friday, January 27, 2012. For abstract instructions, send an email to with the words "Abstract Information" in the subject line. Instructions will be forwarded automatically. For questions, please call 212.298.8618.

20-22 Feb 2012

International Conference and Exhibition on Metabolomics & Systems Biology
Venue: San Francisco, USA

OMICS Group invites you to attend the International Conference and Exhibition on Metabolomics & Systems Biology which is going to be held during 20-22 February 2012 San Francisco, USA.   

Metabolomics-2012 will serve as a catalyst for the advances in the study of Metabolomics & Systems Biology by connecting scientists within and across disciplines at sessions and exhibition held at the venue, creates an environment conducive to information exchange, generation of new ideas, and acceleration of applications that benefit Research in Metabolomics & Systems Biology.
Conference Highlights the following topics:
  • Proteomics & Genomics     
  • Transcriptomics & Metabolomics
  • Bioinformatics    
  • Gene expression Profiling
  • Immunology    
  • Microbiology & Biochemistry
  • Computational Biology    
  • Genetics and Metabolism
  • Glycomics & Lipidomics    
For more information, please visit

21-22 Feb 2012

7th Annual Biomarkers Conference
Venue: Manchester, UK

The pharmaceutical industry is facing high clinical development costs and declining drug discovery success rates. To stay competitive companies are re-evaluating their drug development process to reduce attrition rates. Biomarkers promise to transform drug discovery, clinical development and diagnostics in the R&D process as effective use of biomarkers at each stage of R&D can improve decision-making, increase clinical trial success rates and productivity.
The 7th Annual Biomarkers Congress 2012 presented by Oxford Global Conferences provides a first class educational and networking opportunity for over 250 attendees to gain knowledge and insights into the Biomarkers marketplace.
Do not miss out on the opportunity to learn how you can streamline your R&D process and identify potential cost savings through successful biomarker discovery, validation and clinical development.
Our CNS Biomarkers Congress 2012 which will be co-located with the 7th Annual Biomarkers Congress on the 21- 22 February will provide the opportunity for two days worth of deep analysis and insight into this growing CNS Biomarkers market.

For more information, visit

12-14 Mar 2012

Metabolic Leaders' Forum 2012
Venue: San Francisco, California

Phacilitate’s inaugural Metabolic Leaders’ Forum takes a timely look at the decisions facing senior R&D executives following the tightening up of requirements for approving new drugs for adult-onset diabetes coupled with the FDA’s more recent rejection of three separate drugs to treat obesity. What are your peers doing to establish appropriate CV benefits profiles to demonstrate positive outcomes without incurring exploding costs? How are companies large and small rethinking and restructuring to optimize their ability to compete in diabetes and obesity, and the emerging cardiometabolic health field?

For more information, visit

17-20 Apr 2012

analytica Conference 2012
Venue: Munich, Germany

For the classical exhibition area, the analytica Conference provides the perfect complement. It has been a decisive factor in establishing analytica as the pre-eminent meeting point for the industry.

In various symposiums, leading scientists from all over the world report on the latest developments, current trends and visions of the future. Analytic, diagnostic, biochemical and molecular biological methods and procedures are discussed here. On the last occasion, 140 well-known experts gave talks in 23 different thematic symposiums.

Main subject emphases/highlights of the analytica Conference 2010
  • Presentation of the Gerstel Award and the Bunsen-Kirchhoff Award
  • Patient-oriented laboratory diagnostics
  • Separation techniques in the life sciences
  • Doping analytics
  • Proteome research
  • Measurement and toxicology of particulate matter
  • Modern analytical methods for the chemical analysis of art objects
  • Analytical contributions to the treatment of diabetes
The 2012 event will focus on topics such as acute diagnostics and clinical metabolomics.

7-8 May 2012

LIPID MAPS Annual Meeting 2012: Lipidomics Impact on Cell Biology, Metabolomics and Translational Medicine
Venue: La Jolla, CA, USA

This is an exciting time for the emerging field of lipidomics. With the development and evolution of sophisticated mass spectrometers linked to highly efficient liquid chromatography systems, individual molecular species of lipids can now be isolated and identified, allowing us to begin to understand lipid metabolism and the treatment of lipid-based diseases (atherosclerosis and inflammatory disease as well as arthritis, cancer, diabetes and Alzheimer's disease). Recent awareness that each category of lipid consists of thousands if not tens of thousands of individual molecular species requires sophisticated informatics to ensure consistent databasing and annotation of the numerous lipid molecular species and analysis of tremendous quantities of experimental data. The goal of this meeting is to bring together biological and biomedical scientists in a wide range of fields to share new findings and methods in the broader lipidomics field and to explore joint efforts to extend the use of these powerful new methods to new applications. Presentations will provide an excellent introduction for scientists new to these methods, and are sure to be of interest to lipidomics veterans to learn about latest techniques and research results.
The meeting program tentatively features the following six sessions:
  • Cancer
  • Inflammation
  • Macrophage Biology
  • Metabolic Disease
  • Metabolomics
  • Translational Medicine
For more information, please visit

20-24 May 2012

60th ASMS Conference on Mass Spectrometry and Allied Topics
Venue: Vancouver, BC, Canada

The conference and short courses will be held at the Vancouver Convention Centre, 1055 Canada Place, Vancouver, BC V6C 0C3, Canada.  All oral sessions, poster sessions, exhibit booths, and corporate hospitality suites will be located in the Convention Centre.

Important Dates:
Jan 9, 2012:  Conference registration and lodging opens online
Feb 3, 2012:  Deadline for submission of abstracts
Apr 14, 2012:  Conference program online
Apr 30, 2012:  Deadline for advance registration

21-23 May 2012

Les 6èmes Journées Scientifiques du Réseau Français de Métabolomique et Fluxomique (JS 6 RFMF)
Venue: Nantes, France

The 6th Scientific Days of the French Network of Metabolomics and Fluxome will be held in Nantes from 21 May 2012 to May 23, 2012, organized by the platform Corsaire, the platform of Metabolomics Biogenouest. Corsair includes eight technical support centers located throughout Western France (Brest, Nantes, Rennes, and Roscoff).
The main topics selected for JS 6 RFMF are:

  • Applications of metabolomics and fluxomics in the areas of the sea, agronomy and health.
  • Technological developments, bioinformatics, and statistical processing

For more information, please visit

25-28 June 2012

METABOLOMICS 2012: Breakthroughs in plant, microbial and human biology, clinical and nutritional research, and biomarker discovery
Venue: Washington Marriott Wardman Park Hotel, Washington, DC, USA

The annual meeting of the Metabolomics Society brings together metabolomics researchers from around the world to discuss their most recent achievements as they work to harness the power of metabolomics. Gathering together in a hospitable venue is key to developing the collegial interactions that can build a successful community that advances together.
The 2012 meeting promises a program full of practical workshops and parallel sessions covering the broad range of biological and technological metabolomics topics as well as providing rich opportunities for networking. Join us as we gather together to share ideas, insights, advances and obstacles in the multi-faceted world of metabolomics.

For more information, please visit

10 July 2012

Merck Deep Dive: Translational Technologies for Basic and Clinical Scientists
Venue: Ocean Place Resort and Spa, Long Branch, New Jersey, USA

Join us for another in this quarterly unique series that brings together about 150 Merck subject experts and key vendors. Sponsors and Exhibitors can display products and services to a very focused set of the Merck community leaders. Select exhibitors are given an opportunity to privately present upcoming product development and get instant feedback from Merck on where they would like to see development go to meet their upcoming needs. Topic for this event: Translational Technologies for Basic and Clinical Scientists. Molecular BioMarkers (Proteomics/Genomics/Metabolomics) is a key part of this event.

Please note: If you know of any metabolomics lectures, meetings, workshops, or training sessions that we should feature in future issues of this newsletter, please email Ian Forsythe (

Metabolomics Jobs

6) Metabolomics Jobs

This is a resource for advertising positions in metabolomics. If you have a job you would like posted in this newsletter, please email Ian Forsythe ( Job postings will be carried for a maximum of 4 issues (8 weeks) unless the position is filled prior to that date.

Jobs Offered

Job Title Employer Location Date Posted Source
Senior Principal Scientist, PepsiCo R&D Long Term Research Biology Innovation Lab
700 Anderson Hill Road Purchase, New York 10577 27-Jan-2012
Metabolomics Society Jobs
Senior Specialist in Metabolomics instrumental analysis
IMDEA Food Institute
Madrid, Spain 16-Jan-2012 European Commission Jobs
Postdoctoral Research Fellow in the Sumner lab focused on Metabolomics to Elucidate Genes of Unknown Function funded by NSF 2010 (PB-S095-570) The Samuel Roberts Noble Foundation Ardmore, OK 73401, USA 5-Jan-2012 Metabolomics Society Jobs
Postdoctoral Research Fellow in the Sumner lab focused on Computational Annotation of the Medicago and Arabidopsis Plant Metabolomes funded by a collaborative award from NSF & JST (PB-S095-700) The Samuel Roberts Noble Foundation Ardmore, OK 73401, USA 5-Jan-2012 Metabolomics Society Jobs
Postdoctoral Research Fellow in the Sumner lab focused on Empirical Annotation of the Medicago and Arabidopsis Plant Metabolomes funded by a collaborative award from NSF & JST (PB-S095-701) The Samuel Roberts Noble Foundation Ardmore, OK 73401, USA 5-Jan-2012 Metabolomics Society Jobs
Research Associate in the Analytical Chemistry Core Facility focused on GCMS Metabolomics Applications (PB-S070-125) The Samuel Roberts Noble Foundation Ardmore, OK 73401, USA 5-Jan-2012 Metabolomics Society Jobs
NMR Instrument Coordinator in the Sumner lab focused upon the successful installation and integration of a new NMR with UHPLC-MS and automated solid phase extraction (i.e., UHPLC-MS-SPE-NMR) The Samuel Roberts Noble Foundation Ardmore, OK 73401, USA 5-Jan-2012 Metabolomics Society Jobs
Postdoctoral Researcher in Molecular (Omics) Nanotoxicology University of Birmingham Birmingham, UK 4-Jan-2012 Metabolomics Society Jobs
Metabolomics Tenured Faculty Position UNC Chapel Hill Kannapolis, North Carolina 4-Jan-2012 Scientific American Jobs
Postdoctoral researcher in environmental metabolomics University of Birmingham Birmingham, UK 15-Dec-2011
Metabolomics Society Jobs
Post-doctoral position (18 months) - Cancer, Environment and Metabolomics LABERCA
Nantes, France
Réseau Français de Métabolomique et Fluxomique

Jobs Wanted

This section is intended for very highly qualified individuals (e.g., lab managers, professors, directors, executives with extensive experience) who are seeking employment in metabolomics. We encourage these individuals to submit their position requests to Ian Forsythe ( Upon review, a limited number of job submissions will be selected for publication in the Jobs Wanted section.

Note: There are no postings at this time.

Free Subscription

To subscribe/unsubscribe, simply visit Please forward this newsletter to any interested colleagues or collaborators. Send your comments and feedback about this newsletter to

Back issues of this newsletter can be viewed from the newsletter archive (