National Center for Quantitative Biology of Complex Systems

NIH RePORTER · NIH · P41 · $355,628 · view on reporter.nih.gov ↗

Abstract

PROJECT SUMMARY – TR&D 3 MS is a popular and powerful technique for measuring proteomes, metabolomes, and lipidomes. For each of these classes, the MS analysis is remarkably similar, consisting of chromatographic separation, mass measurement, and tandem MS. Despite this commonality, nearly all MS laboratories specialize in analysis of a single ome, at the exclusion of the others. The integrated workflow we describe will overcome this limitation by providing a chromatography and MS technology capable of separating and characterizing a complex mixture containing peptides, metabolites, and lipids. We envision this to happen in a few hours of analysis time and to provide comprehensive coverage across omes. Here we lay the foundation for this work by eliminating existing shortcomings in proteomics and lipidomic technologies and commence work on an integrated multi-omic platform that allows for simultaneous analysis of peptides, lipids, and metabolites. First, work by us and others has demonstrated that with the latest high MS/MS sampling rates, the primary limitation preventing deeper single- shot proteome analysis is peptide separations. Second, we have identified two primary obstacles limiting lipidomic analyses: (1) Poor separation of isomeric and isobaric lipid species, which often co-elute such that the number of unique lipid species and their quantities cannot be determined. (2) MS/MS bandwidth is limited and often consumed by redundant sampling of in-source fragments, adducts, and dimers. Finally, presently, most multi-omic studies split biological samples so that each omic analysis is conducted separately – from sample preparation to data analysis – by different people with different MS systems. This fragmentation results in substantial hands-on sample preparation labor and instrument acquisition time. Sample-to-sample heterogeneity, independent sample handling, and instrument-to-instrument variance all contribute noise, thereby obscuring otherwise strong biomolecular associations.

Key facts

NIH application ID
10089072
Project number
2P41GM108538-06
Recipient
UNIVERSITY OF WISCONSIN-MADISON
Principal Investigator
Joshua J Coon
Activity code
P41
Funding institute
NIH
Fiscal year
2021
Award amount
$355,628
Award type
2
Project period
2016-07-05 → 2026-06-30