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ARS Home » Midwest Area » Columbia, Missouri » Plant Genetics Research » Research » Publications at this Location » Publication #397996
Research Project: Soybean Seed Improvement Through Translational Genomics, Assessments of Elemental Carbon Metabolism, and Lipid Profiles

Location: Plant Genetics Research

Title: Program for integration and rapid analysis of mass isotopomer distributions (PIRAMID)

Author
item GOMEZ CASTRO, JAVIER - Vanderbilt University
item WALL, MARTHA - Vanderbilt University
item RAHIM, MOHSIN - Vanderbilt University
item KAMBHAMPATI, SHRIKAAR - Donald Danforth Plant Science Center
item EVANS, BRADLEY - Donald Danforth Plant Science Center
item Allen, Douglas - Doug
item ANTONIEWICZ, MACIEK - University Of Michigan
item YOUNG, JAMEY - Vanderbilt University

Submitted to: Bioinformatics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/14/2023
Publication Date: 10/27/2023
Citation: Gomez Castro, J.D., Wall, M.L., Rahim, M., Kambhampati, S., Evans, B.S., Allen, D.K., Antoniewicz, M.R., Young, J. 2023. Program for integration and rapid analysis of mass isotopomer distributions (PIRAMID). Bioinformatics. 39(11). Article btad661. https://doi.org/10.1093/bioinformatics/btad661.
DOI: https://doi.org/10.1093/bioinformatics/btad661

Interpretive Summary: Isotopic tracers (e.g., 13C) provide a way to assess the interchange of elements through metabolism. Ultimately the partitioning of molecules through metabolism produces the compounds that we value in seeds such as oil, protein or carbohydrate. Mass spectrometers measure the distribution of isotopes in molecules, but there are not good analytical tools for analyzing the resulting data. Here, we created a tool to enable this process and automate aspects to quantify isotopes from isotopic labeling studies. Such tools will speed up the analysis of data which is a bottleneck currently. In addition to being laborious, the evaluation of isotopes manually, is prone to user error and biases which can jeopardize the experiment. Therefore, this tool will help make analyses more rigorous and time-efficient.

Technical Abstract: The analysis of stable isotope labeling experiments requires accurate, efficient, and reproducible quantification of mass isotopomer distributions (MIDs), which is not a core feature of general-purpose metabolomics software tools that are optimized to quantify metabolite abundance. Here, we present PIRAMID (Program for Integration and Rapid Analysis of Mass Isotopomer Distributions), a MATLAB-based tool that addresses this need by offering a user-friendly, graphical user interface-driven program to automate the extraction of isotopic information from mass spectrometry (MS) datasets. This tool can simultaneously extract ion chromatograms for various metabolites from multiple data files in common vendor–agnostic file formats, locate chromatographic peaks based on a targeted list of characteristic ions and retention times, and integrate MIDs for each target ion. These MIDs can be corrected for natural isotopic background based on the user-defined molecular formula of each ion. PIRAMID offers support for datasets acquired from low- or high-resolution MS, and single (MS) or tandem (MS/MS) instruments. It also enables the analysis of single or dual labeling experiments using a variety of isotopes (i.e. 2H, 13C, 15N, 18O, 34S). Data availability and implementation: MATLAB p-code files are freely available for non-commercial use and can be downloaded from https://mfa.vueinnovations.com/. Commercial licenses are also available. All the data presented in this publication are available under the “Help_menu” folder of the PIRAMID software.