Document Type
Article
Publication Date
2-2-2023
Original Citation
Yu Q,
Liu X,
Keller M,
Navarrete-Perea J,
Zhang T,
Fu S,
Vaites L,
Shuken S,
Schmid E,
Keele G,
Li J,
Huttlin E,
Rashan E,
Simcox J,
Churchill G,
Schweppe D,
Attie A,
Paulo J,
Gygi S.
Sample multiplexing-based targeted pathway proteomics with real-time analytics reveals the impact of genetic variation on protein expression. Nat Commun. 2023;14(1):555
Keywords
JMG, Animals, Mice, Proteomics, Proteins, Mass Spectrometry, Peptides, Genetic Variation
JAX Source
Nat Commun. 2023;14(1):555
ISSN
2041-1723
PMID
36732331
DOI
https://doi.org/10.1038/s41467-023-36269-7
Grant
This work was funded in part by NIH grants GM67945 (S.P.G.), GM132129 (J.A.P.), GM070783 (G.A.C.), DK101573 (A.D.A.), DK125961 (A.D.A.), and the Mexican Council for Science and Technology grant 289937 (J.N.-P.)
Abstract
Targeted proteomics enables hypothesis-driven research by measuring the cellular expression of protein cohorts related by function, disease, or class after perturbation. Here, we present a pathway-centric approach and an assay builder resource for targeting entire pathways of up to 200 proteins selected from >10,000 expressed proteins to directly measure their abundances, exploiting sample multiplexing to increase throughput by 16-fold. The strategy, termed GoDig, requires only a single-shot LC-MS analysis, ~1 µg combined peptide material, a list of up to 200 proteins, and real-time analytics to trigger simultaneous quantification of up to 16 samples for hundreds of analytes. We apply GoDig to quantify the impact of genetic variation on protein expression in mice fed a high-fat diet. We create several GoDig assays to quantify the expression of multiple protein families (kinases, lipid metabolism- and lipid droplet-associated proteins) across 480 fully-genotyped Diversity Outbred mice, revealing protein quantitative trait loci and establishing potential linkages between specific proteins and lipid homeostasis.
Comments
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