Evidence map›Paper›PMID 27090236›Full record

ArticleJournal of muscle research and cell motility2016

Comprehensive analysis of tropomyosin isoforms in skeletal muscles by top-down proteomics.

Yutong Jin, Ying Peng, Ziqing Lin, Yi-Chen Chen, Liming Wei, Timothy A Hacker, Lars Larsson, Ying Ge

Abstract read
In one paragraph

Article in Journal of muscle research and cell motility, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
3.6field-weighted citation impact, top 7% of its field
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

24 citing papers in PubMed, 39 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
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  5. Top-down proteomics.Nature reviews. Methods primers · 2024
    Article
  6. Review
  7. High sensitivity top-down proteomics captures single muscle cell heterogeneity in large proteoforms.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
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  10. Review
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  14. Review
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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

8 authors at 2 institutions in 3 countries.

Yutong JinDepartment of Chemistry, University of Wisconsin-Madison, 1101 University Ave., Madison, WI, 53706, USA.
Ying PengDepartment of Cell and Regenerative Biology, University of Wisconsin-Madison, 1111 Highland Ave., Madison, WI, 53705, USA.
Ziqing LinDepartment of Cell and Regenerative Biology, University of Wisconsin-Madison, 1111 Highland Ave., Madison, WI, 53705, USA.
Yi-Chen ChenDepartment of Chemistry, University of Wisconsin-Madison, 1101 University Ave., Madison, WI, 53706, USA.
Liming WeiDepartment of Cell and Regenerative Biology, University of Wisconsin-Madison, 1111 Highland Ave., Madison, WI, 53705, USA.
Timothy A HackerDepartment of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, 1111 Highland Ave., Madison, WI, 53705, USA.
Lars LarssonDepartment of Physiology and Pharmacology, Department of Clinical Neuroscience, Clinical Neurophysiology Section, Karolinska Institutet, 171 77, Stockholm, Sweden.
Ying GeDepartment of Chemistry, University of Wisconsin-Madison, 1101 University Ave., Madison, WI, 53706, USA. ying.ge@wisc.edu.
University of Wisconsin–Madison · USKarolinska Institutet · SE

Funding

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
Ultra High Resolution Mass Spectrometer for Biomedical ResearchS10OD018475 · OD · UNIVERSITY OF WISCONSIN-MADISON · PI GE, YING · 2015 to 2015
$2.0M
NHLBI NIH HHS R01 HL096971NHLBI NIH HHS R01 HL109810NIGMS NIH HHS R01 GM117058NIH HHS S10 OD018475
6 · The paper itself

Abstract

Mammalian skeletal muscles are heterogeneous in nature and are capable of performing various functions. Tropomyosin (Tpm) is a major component of the thin filament in skeletal muscles and plays an important role in controlling muscle contraction and relaxation. Tpm is known to consist of multiple isoforms resulting from different encoding genes and alternative splicing, along with post-translational modifications. However, a systematic characterization of Tpm isoforms in skeletal muscles is still lacking. Therefore, we employed top-down mass spectrometry (MS) to identify and characterize Tpm isoforms present in different skeletal muscles from multiple species, including swine, rat, and human. Our study revealed that Tpm1.1 and Tpm2.2 are the two major Tpm isoforms in swine and rat skeletal muscles, whereas Tpm1.1, Tpm2.2, and Tpm3.12 are present in human skeletal muscles. Tandem MS was utilized to identify the sequences of the major Tpm isoforms. Furthermore, quantitative analysis revealed muscle-type specific differences in the abundance of un-modified and modified Tpm isoforms in rat and human skeletal muscles. This study represents the first systematic investigation of Tpm isoforms in skeletal muscles, which not only demonstrates the capabilities of top-down MS for the comprehensive characterization of skeletal myofilament proteins but also provides the basis for further studies on these Tpm isoforms in muscle-related diseases.

Indexed as

ProteomicsAnimalsHumansMuscle, SkeletalProtein IsoformsRatsSpecies SpecificitySwineTropomyosinProtein IsoformsTropomyosinIsoformPost-translational modificationSkeletal muscleTop-down mass spectrometryTropomyosin

Identifiers

PMID27090236
PMCPMC4955698
OpenAlexW2335819561

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.