Issue 2 - September 2011


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Welcome to the second issue of MetaboNews, a monthly newsletter for the worldwide metabolomics community. In this month's Statistical Spotlight article, we feature a commentary on Statistical Analysis of Metabolomic Data, based largely on a lecture given by Dr. David Wishart of the University of Alberta. 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 (

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1) Statistical Spotlight

Commentary on Statistical Analysis of Metabolomic Data

Feature article contributed by Jianguo Xia, Postdoctoral Research Fellow, Biostatistician, Dept of Computing Science, University of Alberta, Edmonton, Canada

Metabolomics is a relatively new omics technology. Both its analytical platforms and bioinformatics tools are being rapidly developed. In this commentary, the author briefly summarizes current concepts and progress in metabolomic data analysis. The content is based mainly on the lectures given by Dr. David Wishart during the Canadian Bioinformatics Workshop on Informatics and Statistics for Metabolomics (June 16-17, 2011, Edmonton, Canada).

Data normalization is necessary
There are two types of normalizations—biological normalization and statistical normalization. Biological normalization aims to reduce the biological variances unrelated to the conditions of interest, e.g., variance introduced during sample preparation (i.e., differences in sample volumes) or different dilution factors in urine samples. Researchers understand that it is necessary to address this difference before proceeding to the next level of data analysis. Statistical normalization aims to reduce the statistical variances that may obscure the discovery of small, but potentially significant signals. For instance, metabolite concentrations usually span several orders of magnitude (submicromolar to millimolar) and the effects from the highly abundant metabolites tend to dominate. However, as we know, a compound’s biological significance is not proportional to its concentration. Therefore, it is important to perform appropriate data transformations to make metabolites more comparable to each other (i.e., to obtain a homogenous data set).

Data visualization is critical
Intuitive data visualization is critical for data exploration and quality assurance. As metabolomic data usually contains over hundreds of features, numerical summaries can often hide important messages which can be easily picked up through graphical presentation. Fig.1 illustrates such a case. An outlier (indicated by a red arrow) is obvious to any examiner. Is it caused by some measurement error or typographical error? Addressing such an issue (i.e., through removal of the outlier) may significantly improve the results of the downstream data analysis.

Data visualization for outlier detection

Figure 1.
Data visualization for outlier detection.

Combining univariate and multivariate methods to achieve better understanding

Identification of significant metabolites is usually the first step towards finding useful biomarkers or identifying associated biological processes. Univariate approaches are widely used in this regard. Many well-established approaches (e.g., t-tests, ANOVA) are available. The main advantages of univariate methods are easy to understand and support for very flexible experimental designs.

Multivariate statistics involves the simultaneous analysis of more than two statistical variables. Because metabolomic data usually contains hundreds of metabolite concentrations, multivariate data analysis is considered ideal for such data sets. The most widely used multivariate methods in metabolomics are probably principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). Both of them are capable of projecting high-dimensional data into two or three dimensions that can be conveniently visualized for pattern discovery. PCA is an unsupervised method, suitable to see if natural clusters form or if data separates well. Fig. 2 illustrates a PCA result which forms three natural clusters. PLS-DA is a supervised method that uses group information to help improve the class separation and is often used when PCA shows little separation.

PCA visualization
          of natural clustering pattern

Figure 2.
PCA visualization of natural clustering pattern.

Is there an overall significant difference between the metabolomic profiles?
For univariate analysis such as t-tests, researchers can judge whether a given metabolite is significant based on its p-value. For multivariate approaches, calculating a p-value is difficult as we do not know the characteristics of the underlying distribution. However, we can calculate an empirical p-value using a non-parametric approach such as a permutation test. This approach involves randomly reassigning the class labels and performing the analysis on the newly labeled data set. The process is repeated hundreds or thousands of times and the performance measures are plotted on a histogram for visual assessment. From the resulting histogram it is possible to determine if the of the original class assignment is significantly different from or a part of the distribution based on the permuted class assignments. The empirical p-value is calculated as the proportion of times that the permuted data yielded a better result than the one using the original labels. For example, if none of the permuted classes is better than the observed one in 2000 permutations, the p-value is reported as p<0.0005 (less than 1/2000). With more permutations, the empirical p-value will be very close to the real p-value. The process is illustrated in Fig. 3.

Permutation tests to evaluate the significance of

Figure 3. Permutation tests to evaluate the significance of separation. Panel 1 shows the overview by principal component analysis (PCA). Panel 2 shows the same PCA result colored by group labels. Only slight separation can be seen between the two groups. Panel 3 shows the supervised methods PLS-DA/SVM (partial least squares-discriminant analysis/support vector machines) on the same dataset with much better separation. Panels 4 and 5 shows the separations using the permuted datasets. The histogram in Panel 6 shows the comparison between the results using permuted datasets and the one using original data (indicated by a black arrow). In this case, the separation is clearly significant.

Metabolomics is a recent addition to the omics family. There are certain advantages to being the last to arrive. Many of the statistical and computational methods are borrowed from other omics platforms and adapted to the specific needs of metabolomic data, allowing metabolomics to quickly catch up to its more mature cousins. Another important source of concepts grew from the field of chemometrics such as the use of PCA and PLS-DA. Most of the approaches discussed here are freely available online through the MetaboAnalyst ( web application.

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 Rupasri Mandal, Research Associate, Mass Spectrometry/Separations, 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), the use of metabolomics allows information about multiple compounds to be used together to make better medical decisions. Global metabolic profiling has now been 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 diagnosis of malignancy in adrenal tumours and hepatocellular carcinoma, respectively.

1. Wiebke Arlt, Michael Biehl, Angela E. Taylor, Stefanie Hahner, Rossella Libe, Beverly A. Hughes et al., Urine Steroid Metabolomics as a Biomarker Tool for Detecting Malignancy in Adrenal Tumors, J Clin Endocrin Metab, 2011 Sep 14, doi:10.1210/jc.2011-1565. Epub ahead of print. [PMID: 21917861]

This paper presents a metabolomics-based biomarker approach for the differential diagnosis of adrenal tumors. The objective was to develop a novel mass spectrometry based urinary steroid profiling approach and to investigate whether, after combining with computational data analysis tool, this metabolomic approach could be used to diagnose adrenal malignancy. Urinary steroid profiles of 102 ACA patients (with benign adrenocortical adenoma) and 45 ACC patients (with malignant) was performed using gas chromatography-mass spectrometry (GC-MS). Data strongly suggest that the urine steroid metabolomics could be used as a specific biomarker tool for the differential diagnosis of adrenal tumors. After validating for large cohorts of patients, this approach could potentially be used as a diagnostic test in routine clinical practice.

2. Tianlu Chen, Guoxiang Xie, Xiaoying Wang, Jia Fan, Yunping Qiu,  Xiaojiao Zheng et al., Serum and urine metabolite profiling reveals potential biomarkers of human hepatocellular carcinoma, Mol Cell Proteomics. 2011 Jul;10(7):M110.004945. Epub 2011 Apr 25. [PMID: 21518826]

Serum and urine metabolomics approach was used to investigate potential metabolite biomarker for human hepatocellular carcinoma (HCC). Serum and urine metabolic profiles of 177 subjects (71 healthy individuals, 24 benign liver tumor patients, and 82 HCC patients) were performed using two analytical methods—GC-TOFMS and UPLC-QTOFMS—followed by univariate and multivariate statistical analyses. A significant number of serum and urine metabolite markers relevant to HCC were identified that are involved in several key metabolic pathways such as bile acids, free fatty acids, urea cycle, and methionine metabolism. Bile acids, histidine, and inosine were shown to be of greatest statistical significance. This global metabolomics profiling approach could be used as a screening tool for diagnosing HCC.

Metabolomics Current Contents

3) Metabolomics Current Contents

Recently published papers in metabolomics:


4) MetaboNews

28 Sep 2011

MetaMap® Tox - a Novel Technology for Early Safety Enablement in Pharmaceutical Development Successfully Evaluated by Industry Consortium - The Drug Safety Executive Council (DSEC), an industry membership run by Cambridge Healthtech Associates (CHA), together with Metanomics Health GmbH, a BASF Group company, and leader in offering targeted and non-targeted metabolite profiling to healthcare customers, today announced the results of the technology assessment of MetaMap® Tox conducted by DSEC’s Technology Evaluation Consortium.

The consortium concluded that besides identifying key adverse events in test compounds comparable to the gold standard histopathology, MetaMap Tox® , a platform that uses metabolite patterns of rat plasma for early toxicity recognition of new drugs, provides significant additional value beyond results typically received from a 28-day Good Laboratory Practice (GLP) tox study.

The precompetitive consortium consisting of 12 leading biopharmaceutical companies evaluated and determined that there is value and utility in the use of MetaMap® Tox. In particular, the following areas are complementary to standard 28 day GLP tox studies: assessment of toxicity mechanisms of action and target organs, evaluation of systemic toxicity reactions, lead compound selection and toxicity differentiation for compounds with similar chemical structure and pharmacology.

The platform has been developed by Metanomics Health GmbH, a BASF Group company, and leader in offering targeted and non-targeted metabolite profiling to healthcare customers, and is already in routine use within the BASF Group.

22 Sep 2011

21st century vaccines -- innovation in design and rational use - Innovation in the design of vaccines is rapidly expanding their use, safety, and effectiveness for disease prevention and therapeutic interventions. The enormous potential of OMICS sciences for global health and vaccine design is examined in "Vaccines of the 21st Century and Vaccinomics," a special issue of OMICS: A Journal of Integrative Biology, the peer-reviewed journal published by Mary Ann Liebert, Inc. The issue is available free online.

"Truly a fresh new look at how we design vaccines and apply them judiciously to benefit global health is essential and timely in the present age of data enabled science and postgenomics integrative biology," writes Eugene Kolker, PhD, Editor-in-Chief of OMICS, and Chief Data Officer, Seattle Children's Hospital, and Head, Bioinformatics & High-Throughput Analysis Laboratory, Seattle Children's Research Institute, and the Special Issue Guest Editor Vural Ozdemir (Associate Professor, McGill University, Canada), and co-authors of the Introductory Editorial, Tikki Pang (World Health Organization, Geneva, Switzerland), Bartha M. Knoppers, Denise Avard, Ma'n H. Zawati (Centre of Genomics and Policy, Department of Human Genetics, Faculty of Medicine, McGill University), and Samer A. Faraj (Desautels Faculty of Management, McGill University).

Despite advances in public health in the 21th century, we still lack safe and highly effective vaccines against the common pathogens seriously affecting global society such as neglected tropical diseases and helminth infections, tuberculosis, HIV, and malaria. These gaps in global health are deepened further by the lack of development of new antimicrobial drugs. The new field of vaccinomics relies on the integrated use of multi-omics data intensive biotechnologies (e.g., genomics, proteomics, metabolomics) to understand individual and population differences in immune responses to vaccines. Vaccinomics holds great promise for the design of safer and more effective vaccines, and their targeted rational use via novel postgenomics diagnostics to prevent and combat infectious diseases, and to intervene in chronic non-communicable diseases such as cancer, diabetes, and obesity.

Featuring global contributions from leading experts in Australia, Asia, Europe, and North America, "Vaccines of the 21st Century: Vaccinomics for Global Public Health" includes a series of articles on cutting-edge topics such as the conceptual basis of vaccinomics; high throughput ''game changing'' experimental approaches for 21st century vaccine design; case studies including previously neglected tropical diseases vastly affecting the developing countries (e.g., vaccinomics for helminth infections); the new therapeutic cancer vaccines; social science and policy analyses on vaccinomics and global health convergence, and the current strategies for vaccinomics-enabled rational vaccine design deployed by the vaccine industry.

Source: EurekAlert!

13 Sep 2011

MetaboLab - advanced NMR data processing and analysis for metabolomics

Background: Despite wide-spread use of Nuclear Magnetic Resonance (NMR) in metabolomics for the analysis of biological samples there is a lack of graphically driven, publicly available software to process large one and two-dimensional NMR data sets for statistical analysis.

Results: Here we present MetaboLab, a MATLAB based software package that facilitates NMR data processing by providing automated algorithms for processing series of spectra in a reproducible fashion. A graphical user interface provides easy access to all steps of data processing via a script builder to generate MATLAB scripts, providing an option to alter code manually. The analysis of two-dimensional spectra (1H,13C-HSQC spectra) is facilitated by the use of a spectral library derived from publicly available databases which can be extended readily. The software allows to display specific metabolites in small regions of interest where signals can be picked. To facilitate the analysis of series of two-dimensional spectra, different spectra can be overlaid and assignments can be transferred between spectra. The software includes mechanisms to account for overlapping signals by highlighting neighboring and ambiguous assignments.

Conclusions: The MetaboLab software is an integrated software package for NMR data processing and analysis, closely linked to the previously developed NMRLab software. It includes tools for batch processing and gives access to a wealth of algorithms available in the MATLAB framework. Algorithms within MetaboLab help to optimize the flow of metabolomics data preparation for statistical analysis. The combination of an intuitive graphical user interface along with advanced data processing algorithms facilitates the use of MetaboLab in a broader metabolomics context.

Source: C. Ludwig and U. Günther, BMC Bioinformatics 2011, 12:366

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

30 Sep-
4 Oct 2011

ASMS Asilomar Metabolomics meeting
Venue: Pacific Grove, California, USA

The upcoming ASMS Asilomar Metabolomics meeting will promote an in-depth discussion of current problems and perspectives of mass spectrometry-based metabolomics. The meeting is endorsed by the Metabolomics Society.

We will challenge ideas and concepts throughout the conference and have allocated ample time for discussions, e.g., during evening receptions. In addition to invited speakers, there will be poster sessions and oral contributions based on abstract submissions. We will focus on a range of hot  topics, including:  databases; metabolite/gene annotations; fluxes; compound identifications; metabolite imaging; secondary metabolism; metabolomics in human diseases; and quality control for high-throughput metabolomic quantifications.

Download conference brochure

Nov 2011

7th annual Advances in Metabolic Profiling
Venue: Dublin, Ireland

Welcome to the 7th annual Advances in Metabolic Profiling conference and exhibition. This year's event will be held in the dynamic city of Dublin, economic and cultural centre of Ireland.

The conference will be co-located with Mass Spec Europe. Registered delegates will have access to both meetings ensuring a very cost-effective trip.

For more information, please visit

Nov 2011

International Conference on Natural Products (ICNP2011) - Metabolomics A New Frontier in Natural Products Science
Venue: Palm Garden Hotel, Putrajaya, Malaysia

On behalf of the Organising Committee you are invited to participate in the next International Conference on Natural Products (ICNP2011) - Metabolomics A New Frontier in Natural Products Science.

The conference is being organised by the Universiti Putra Malaysia and Malaysian Natural Products Society. The conference will be held at Palm Garden Hotel, IOI Resort, PUTRAJAYA from 13th -16th November 2011.

For more information, please visit

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    
Avail the early bird discounts and register on/before 14 November 2011.
For more information, please visit

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.

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 Metabolomics Society is pleased to announce the location and dates for our next annual meeting 'METABOLOMICS 2012'. We will host a program full of practical workshops and parallel sessions covering the broad range of biological and technological metabolomics topics as well as provide rich opportunities for networking. Prominent scientists will speak on the state-of-the-art in a number of leading disciplines to kick off each session, after which, we will have a full agenda of innovative speakers with specific oral presentation opportunities provided for younger researchers. We invite you to reserve the above dates in your calendar and follow our website for further details,

Local Organisers: Dan Bearden, Rick Beger, Rima Kaddurah-Daouk, Lloyd W. Sumner, Don Robertson, Padma Maruvada and Donna Kimball.

For more information, please visit

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
Business Development Manager
BASF – The Chemical Company
Florham Park, New Jersey
Metabolomics Society Jobs
Director, R&D Long Term Research Exercise Biology & Metabolism Job
New Haven, CT
(Greater New York City Area)
LinkedIn Jobs
Assoc Director - Bioinformatics
United States
LinkedIn Jobs
Senior Scientist 208819 (NCI) Job
Frederick, MD, US
(Washington D.C. Metro Area)
LinkedIn Jobs
Principal Scientist, Metabolomics Platform Job
PepsiCo New Haven, CT
(Greater New York City Area)
LinkedIn Jobs
Mass Spectrometry Sales Specialist
(Montreal, Canada Area)
LinkedIn Jobs
Postdoctoral Research Associate position to analyze plant composition
Iowa State University
Ames, Iowa
Metabolomics Society Jobs
Postdoctoral Fellow in Metabolomics
Duke University
Durham, NC
Metabolomics Society Jobs
Post-Doctoral Fellow: Biomarkers of Disease in Dairy Cows
University of Alberta
Edmonton, AB
University of Alberta

Jobs Wanted
Very highly qualified individuals (e.g., lab managers, professors, directors, executives with extensive experience) seeking employment in metabolomics are encouraged 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.

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