Microbes have been surfing the planet for roughly 3.5 billion years and are ubiquitous in our world today.  Researchers have demonstrated substantial evidence of their profound impact on human life (e.g., disease and wellness, climate and the environment, the economy, etc.).

One instance of particular interest is the gut microbiome which has the potential to be used as a diagnostic tool.  However, traditional culture-based methods are no longer sufficient to answer modern inquiries regarding microbial metrology. 

Advances in methods that accurately measure and analyze microbes and microbial communities are crucial for areas such as the human microbiome, precision medicine, biomanufacturing, agriculture, climate, and biosurveillance. Metabolomics is a powerful approach to understanding microbial function and interaction and discovering new biomarkers. 

This suite of projects seeks to advance the microbial metabolomics infrastructure through the development of new analytical methods, including data analysis and novel statistical approaches. We are particularly interested in characterizing microbial cells in the planktonic state as well as communities of cells. We are seeking researchers interested in developing analytical strategies for the characterization of metabolic profiles of microbial communities, identification of unknown metabolites, and development of reference materials, all based on nuclear magnetic resonance (NMR) spectroscopy- and mass spectrometry (MS)-based metabolomics. 

We work in an interdisciplinary environment; a successful candidate should be interested in navigating between experiments (wet lab) and data analysis with a focus on either aspect of the work. Proposals describing research that leads to new tools and/or methods for improving confidence in microbial measurement are strongly encouraged. Candidates interested in acquiring experience with chemometrics and multivariate statistics are highly desired. Feel free to reach out to learn more about this opportunity.

Keywords: Microbiome; Bacteria; Microbiology; Metabolites; Nuclear Magnetic Resonance, Mass-spectrometry, Chemometrics; Multivariate statistics; Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL).

1 - Cumeras, R., T. Shen, L. Valdiviez, Z. Tippins, B. D. Haffner and O. Fiehn (2023). "Differences in the Stool Metabolome between Vegans and Omnivores: Analyzing the NIST Stool Reference Material." Metabolites 13(8).

2 - Emwas, A. H., R. Roy, R. T. McKay, L. Tenori, E. Saccenti, G. A. N. Gowda, D. Raftery, F. Alahmari, L. Jaremko, M. Jaremko and D. S. Wishart (2019). "NMR Spectroscopy for Metabolomics Research." Metabolites 9(7).

3 - https://doi.org/10.6028/NIST.IR.8451

Researchers: Aaron Urbas (aaron.urbas@nist.gov), Sandra Da Silva (sandra.dasilva@nist.gov), Ben Place (benjamin.place@nist.gov) and Anthony Kearsley (anthony.kearsley@nist.gov).

key words

Microbiome; Bacteria; Microbiology; Metabolites; Nuclear Magnetic Resonance, Mass-spectrometry, Chemometrics; Multivariate statistics; Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL)

Citizenship:  Open to U.S. citizens

Level:  Open to Postdoctoral applicants