The ECR Perspective on Metabolomics: Interview with Dr. Vanessa Phelan
Beyond the realms of genetic material that we living beings have, there is a complex chemistry of life in the form of organic molecules which connect our genotype (DNA) to our phenotypes (health and disease). The study of these small organic molecules, known as metabolites, from cells, tissues, fluids, whole organisms, and the environment is known as metabolomics. Metabolomics is a nascent field, yet in my opinion it is already the most complex of all recent -omics (i.e., genomics, transcriptomics, proteomics, metagenomics etc.). As a highly interdisciplinary science, metabolomics warrants expertise in analytical and physical chemistry, biology, computational biology, mathematics, statistics, bioinformatics, computer and data science among others.
Thanks to metabolomics, we have now ‘sequenced’ human blood, and urine metabolomes, are thriving for metabolomics at single cell levels and are using it as a tool for systems biology understanding of life. Metabolomics is now considered an integral tool/ approach for personalized precision with human blood metabolites as predictors of the genome or through the wellness study of individuals based on personal, dense, dynamic data clouds.
As a metabolomics researcher myself, I am not only fascinated by the science of it, but have always wondered how other early career researchers (ECRs) have approached the challenges or imbibed the technology. With that in mind, I recently caught up with a successful ECR leading a team of metabolomics and microbiology researchers, Dr. Vanessa Phelan. Dr. Phelan is an L.S. Skaggs Assistant Professor in the Department of Pharmaceutical Sciences at the University of Colorado. Here’s her take on her journey through an academic career in metabolomics:
1. What skill sets, expertise, and connections helped you reach where you are currently in the field of metabolomics?
The training I received in mass spectrometry during my graduate work at Vanderbilt University and my postdoctoral work at University of California, San Diego provided much of the experimental groundwork for my current expertise. The specific niche I occupy in metabolomics is largely due to the interdisciplinary nature of my training in mass spectrometry, natural products, and microbiology. In terms of connections and opportunities, the NIH Metabolomics Initiative provided both funding and networking opportunities that have greatly influenced my position in the field.
2. How do you think you are impacting our world and people (i.e., community, colleagues etc.) through your journey?
I think that I bring a chemical expertise to the microbiology community. In many cases, microbiologists have evidence that there is a small molecule driven phenotype, but don’t know how to pursue the identity or structure of the chemical(s) of interest. My group fills the need for that chemical expertise.
3. What is your most important contribution to the field of metabolomics as an ECR?
Global Natural Products Social Molecular Networking, otherwise known as GNPS (gnps.ucsd.edu). GNPS is a bioinformatics platform that uses tandem mass spectrometry MS/MS data as a proxy for chemical structure. This workflow allows researchers to organize their data into molecular families allowing for easier metabolite annotation and analogue discovery. GNPS was definitely a large group effort and required the cooperation from people with very different areas of expertise. I think the coolest aspect of this platform is how research groups from around the world are integrating a number of different platforms with GNPS. It is amazing to experience how the global metabolomics community is working together to provide open-source tools and platforms.
4. What is that moment or work which helped you transition from an ECR to a pro? Basically, that career defining moment of yours?
I don’t consider myself a “pro” as there are always new tools, methods, and techniques emerging from the work of the metabolomics community.
5. Can you point to some resources which would help refine the skills of any ECR in metabolomics to excel?
If you want to excel in metabolomics, you have to perform metabolomics –from sample preparation to data acquisition, feature finding, annotation, and statistical analysis. Many academic centers have courses and workshops in metabolomics which can provide insight into the workflows. In addition, reviews and manuscripts have been published detailing experimental workflows. However, dozens of tools have been individually developed and the community does not yet have any sort of consensus for which tools are best. The metabolomics workbench has a list of available database and tools, although this list is not exhaustive. The metabolomics society also has tutorials and links to available software, databases, and standards.
6. How can metabolomics reshape the world?
Metabolomics has certainly provided another dimension to understanding biological processes and, in some cases, insight into metabolic diseases. Together with basic and clinical research including other omics technologies, I think that metabolomics will continue to add to our understanding of our world.
To my knowledge, metabolomics has been successful in welcoming experts from almost all domains of scientific and basic research very successfully. Her story is another excellent example as to how one can find success using metabolomics as a tool in their armory. For amateurs venturing into metabolomics research, I have catalogued additional resources here, and the Metabolomics Society has guidelines for conducting and standards for reporting metabolomics research as well. With Dr. Phelan’s insight and these tools, ECRs have the ability to enrich their own work with metabolomics.
Psychogios, N., Hau, D.D., Peng, J., Guo, A.C., Mandal, R., Bouatra, S., Sinelnikov, I., Krishnamurthy, R., Eisner, R., Gautam, B. and Young, N., 2011. The human serum metabolome. PLoS One, 6(2), p.e16957.
Bouatra, S., Aziat, F., Mandal, R., Guo, A.C., Wilson, M.R., Knox, C., Bjorndahl, T.C., Krishnamurthy, R., Saleem, F., Liu, P. and Dame, Z.T., 2013. The human urine metabolome. PLoS one, 8(9), p.e73076.
Fessenden, M., 2016. Metabolomics: Small molecules, single cells. Nature, 540(7631), pp.153-155.
May, M., 2017. Big data, big picture: Metabolomics meets systems biology. Science, 356(6338), pp.646-648.
Misra, B.B., 2016. Quick tips to perform a metabolomics study (No. e2002v1). PeerJ Preprints.
Fiehn, O., Robertson, D., Griffin, J., van der Werf, M., Nikolau, B., Morrison, N., Sumner, L.W., Goodacre, R., Hardy, N.W., Taylor, C. and Fostel, J., 2007. The metabolomics standards initiative (MSI). Metabolomics, 3(3), pp.175-178.
Long, T., Hicks, M., Yu, H.C., Biggs, W.H., Kirkness, E.F., Menni, C., Zierer, J., Small, K.S., Mangino, M., Messier, H. and Brewerton, S., 2017. Whole-genome sequencing identifies common-to-rare variants associated with human blood metabolites. Nature Genetics, 49(4), pp.568-578.
Price, N.D., Magis, A.T., Earls, J.C., Glusman, G., Levy, R., Lausted, C., McDonald, D.T., Kusebauch, U., Moss, C.L., Zhou, Y. and Qin, S., 2017. A wellness study of 108 individuals using personal, dense, dynamic data clouds. Nature biotechnology, 35(8), p.747.
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