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ARS Home » Midwest Area » Columbia, Missouri » Plant Genetics Research » Research » Publications at this Location » Publication #395968
Research Project: Soybean Seed Improvement Through Translational Genomics, Assessments of Elemental Carbon Metabolism, and Lipid Profiles

Location: Plant Genetics Research

Title: SIMPEL: using stable isotopes to elucidate dynamics of context specific metabolism

Author
item KAMBHAMPATI, SHRIKAAR - Donald Danforth Plant Science Center
item HUBBARD, ALLEN - Donald Danforth Plant Science Center
item KOLEY, SOMNATH - Donald Danforth Plant Science Center
item GOMEZ, JAVIER - Vanderbilt University
item MARSOLAIS, FRÉDÉRIC - University Of Western Ontario
item EVANS, BRADLEY - Danforth Plant Science Center
item YOUNG, JAMEY - Vanderbilt University
item Allen, Douglas - Doug

Submitted to: Communications Biology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/23/2024
Publication Date: 2/12/2024
Citation: Kambhampati, S., Hubbard, A.H., Koley, S., Gomez, J.D., Marsolais, F., Evans, B.S., Young, J.D., Allen, D.K. 2024. SIMPEL: using stable isotopes to elucidate dynamics of context specific metabolism. Communications Biology. 7. Article 172. https://doi.org/10.1038/s42003-024-05844-z.
DOI: https://doi.org/10.1038/s42003-024-05844-z

Interpretive Summary: The flows of metabolite through plant cells result in the production of valuable products including protein and oil, and also accommodate environmental conditions that allow plants to grow. Analyzing the many metabolites in a cell is challenging and laborious without the aid of tools to automate the process. Here, we developed a tool to automate the peak selection and identification process for cellular metabolites. The tool brings to bear the capacity of cutting edge instruments to sensitively identify and quantify peaks that correspond to metabolites with isotopic labeling that is an important experimental tool to analyze cell products. Leveraging these tools with genetic experiments will improve our capacity to understand plant metabolism and augment plants to make products for human needs.

Technical Abstract: The capacity to leverage high resolution mass spectrometry (HRMS) with transient isotope labeling experiments is an untapped opportunity to derive insights on context-specific metabolism, that is difficult to assess quantitatively. Tools are needed to comprehensively mine isotopologue information in an automated, high-throughput way without errors. We describe a tool, Stable Isotope-assisted Metabolomics for Pathway Elucidation (SIMPEL), to simplify analysis and interpretation of isotope-enriched HRMS datasets. The efficacy of SIMPEL is demonstrated through examples of central carbon and lipid metabolism. In the first description, a dual-isotope labeling experiment is paired with SIMPEL and isotopically nonstationary metabolic flux analysis (INST-MFA) to resolve fluxes in central metabolism that would be otherwise challenging to quantify. In the second example, SIMPEL was paired with HRMS-based lipidomics data to describe lipid metabolism based on a single labeling experiment. Available as an R package, SIMPEL extends metabolomics analyses to include isotopologue signatures necessary to quantify metabolic flux.