Evidence map›Paper›PMID 37126723›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2023

High sensitivity top-down proteomics captures single muscle cell heterogeneity in large proteoforms.

Jake A Melby, Kyle A Brown, Zachery R Gregorich, David S Roberts, Emily A Chapman, Lauren E Ehlers, Zhan Gao, Eli J Larson, Yutong Jin, Justin R Lopez and 7 more

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

42 citing papers in PubMed.

  1. Review
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  4. Subcellular localization as a driver of protein function.Nature reviews. Molecular cell biology · 2026
    Review
  5. Article
  6. Article
  7. Article
  8. Review
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  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Review
  19. Capillary Electrophoresis-Mass Spectrometry for Top-Down Proteomics.Annual review of analytical chemistry (Palo Alto, Calif.) · 2025
    Review
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Jake A MelbyDepartment of Chemistry, University of Wisconsin-Madison, Madison, WI 53706.ORCID 0000-0003-1499-9508
Kyle A BrownDepartment of Chemistry, University of Wisconsin-Madison, Madison, WI 53706.
Zachery R GregorichDepartment of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI 53706.ORCID 0000-0002-4013-4869
David S RobertsDepartment of Chemistry, University of Wisconsin-Madison, Madison, WI 53706.ORCID 0000-0002-0478-4987
Emily A ChapmanDepartment of Chemistry, University of Wisconsin-Madison, Madison, WI 53706.ORCID 0000-0003-1110-8984
Lauren E EhlersDepartment of Chemistry, University of Wisconsin-Madison, Madison, WI 53706.ORCID 0009-0004-8156-1973
Zhan GaoDepartment of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, WI 53705.
Eli J LarsonDepartment of Chemistry, University of Wisconsin-Madison, Madison, WI 53706.ORCID 0000-0002-1354-0722
Yutong JinDepartment of Chemistry, University of Wisconsin-Madison, Madison, WI 53706.
Justin R LopezDepartment of Kinesiology, University of Wisconsin-Madison, Madison, WI 53706.ORCID 0009-0006-3086-0935
Jared HartungDepartment of Kinesiology, University of Wisconsin-Madison, Madison, WI 53706.
Yanlong ZhuDepartment of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, WI 53705.
Sean J McIlwainDepartment of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53705.
Daojing WangNewomics Inc., Berkeley, CA 94710.
Wei GuoDepartment of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI 53706.ORCID 0000-0002-9158-8107
Gary M DiffeeDepartment of Kinesiology, University of Wisconsin-Madison, Madison, WI 53706.ORCID 0009-0002-2515-6434
Ying GeDepartment of Chemistry, University of Wisconsin-Madison, Madison, WI 53706.ORCID 0000-0001-5211-6812

Funding

Training Program in Translational Cardiovascular Science (TPTCS)T32HL007936 · NHLBI · UNIVERSITY OF WISCONSIN-MADISON · PI Lee Lochbaum Eckhardt, Gail A Robertson · 2001 to 2026
$11.6M
Chemistry-Biology Interface Training ProgramT32GM008505 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI BLACKWELL, HELEN E. · 1993 to 2023
$9.8M
Deciphering Myofilament Modifications in Ischemic CardiomyopathyR01HL109810 · NHLBI · UNIVERSITY OF WISCONSIN-MADISON · PI GE, YING · 2013 to 2024
$3.5M
Top Down Proteomics Of Myofilaments In Heart FailureR01HL096971 · NHLBI · UNIVERSITY OF WISCONSIN-MADISON · PI GE, YING · 2011 to 2021
$3.3M
Enabling Top-Down Proteomics through Materials Chemistry and NanotechnologyR01GM117058 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI GE, YING, JIN, SONG · 2015 to 2023
$2.7M
Vascular Surgery Research Training ProgramT32HL110853 · NHLBI · UNIVERSITY OF WISCONSIN-MADISON · PI MATSUMURA, JON STEVEN · 2012 to 2021
$2.6M
Ultra High Resolution Mass Spectrometer for Biomedical ResearchS10OD018475 · OD · UNIVERSITY OF WISCONSIN-MADISON · PI GE, YING · 2015 to 2015
$2.0M
Posttranscriptional Regulation of RNA Binding Proteins in Heart FailureR01HL148733 · NHLBI · UNIVERSITY OF WISCONSIN-MADISON · PI GUO, WEI · 2020 to 2023
$1.5M
MASH Explorer, a Comprehensive Software Environment for Top-Down ProteomicsR01GM125085 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI GE, YING · 2018 to 2021
$1.2M
American Heart Association-American Stroke Association 19TPA34830072NHLBI NIH HHS R01 HL096971NHLBI NIH HHS R01 HL109810NHLBI NIH HHS R01 HL148733NHLBI NIH HHS T32 HL007936NHLBI NIH HHS T32 HL110853NIGMS NIH HHS R01 GM117058NIGMS NIH HHS R01 GM125085NIGMS NIH HHS T32 GM008505NIH HHS S10 OD018475
6 · The paper itself

Abstract

Single-cell proteomics has emerged as a powerful method to characterize cellular phenotypic heterogeneity and the cell-specific functional networks underlying biological processes. However, significant challenges remain in single-cell proteomics for the analysis of proteoforms arising from genetic mutations, alternative splicing, and post-translational modifications. Herein, we have developed a highly sensitive functionally integrated top-down proteomics method for the comprehensive analysis of proteoforms from single cells. We applied this method to single muscle fibers (SMFs) to resolve their heterogeneous functional and proteomic properties at the single-cell level. Notably, we have detected single-cell heterogeneity in large proteoforms (>200 kDa) from the SMFs. Using SMFs obtained from three functionally distinct muscles, we found fiber-to-fiber heterogeneity among the sarcomeric proteoforms which can be related to the functional heterogeneity. Importantly, we detected multiple isoforms of myosin heavy chain (~223 kDa), a motor protein that drives muscle contraction, with high reproducibility to enable the classification of individual fiber types. This study reveals single muscle cell heterogeneity in large proteoforms and establishes a direct relationship between sarcomeric proteoforms and muscle fiber types, highlighting the potential of top-down proteomics for uncovering the molecular underpinnings of cell-to-cell variation in complex systems.

Indexed as

Protein Processing, Post-TranslationalProteomicsMuscle Fibers, SkeletalProtein IsoformsProteomeReproducibility of ResultsProtein IsoformsProteomemass spectrometryproteoformproteomicssingle cellsingle muscle fiber

Identifiers

PMID37126723
PMCPMC10175728

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.