Evidence map›Paper›PMID 28406609›Full record

ArticleAnalytical chemistry2017

Top-Down Proteomics of Large Proteins up to 223 kDa Enabled by Serial Size Exclusion Chromatography Strategy.

Wenxuan Cai, Trisha Tucholski, Bifan Chen, Andrew J Alpert, Sean McIlwain, Takushi Kohmoto, Song Jin, Ying Ge

Abstract read
In one paragraph

Article in Analytical chemistry, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 82 papers.

0numbers the graph read from it
0cells of the map it votes in
82citing papers in PubMed
8.8field-weighted citation impact, top 1% 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

82 citing papers in PubMed, 128 citations in OpenAlex.

  1. A Draft Map of E. coli Proteoforms.Analytical chemistry · 2026
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  5. A Novel Compact Multi-Reflecting Time-of-Flight Mass Spectrometer.Journal of the American Society for Mass Spectrometry · 2026
    Article
  6. Review
  7. Article
  8. Methods for the Investigation of Protein-Ligands Interactions.Advances in experimental medicine and biology · 2026
    Review
  9. Article
  10. Review
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Article
  20. Top-down proteomics.Nature reviews. Methods primers · 2024
    Article

22 more citing papers are in PubMed but not listed here.

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 1 institution in 1 country.

Wenxuan CaiDepartment of Cell and Regenerative Biology, University of Wisconsin-Madison , Madison, Wisconsin 53705, United States.
Trisha TucholskiDepartment of Chemistry, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States.ORCID 0000-0003-1407-6922
Bifan ChenDepartment of Chemistry, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States.
Andrew J AlpertDepartment of Cell and Regenerative Biology, University of Wisconsin-Madison , Madison, Wisconsin 53705, United States.
Sean McIlwainDepartment of Biostatistics and Medical Informatics, University of Wisconsin-Madison , Madison, Wisconsin 53705, United States.
Takushi KohmotoDepartment of Surgery, School of Medicine and Public Health, University of Wisconsin-Madison , Madison, Wisconsin 53705, United States.
Song JinDepartment of Chemistry, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States.ORCID 0000-0001-8693-7010
Ying GeDepartment of Cell and Regenerative Biology, University of Wisconsin-Madison , Madison, Wisconsin 53705, United States.ORCID 0000-0001-5211-6812
University of Wisconsin–Madison · US

Funding

UW COMPREHENSIVE CANCER CENTER SUPPORTP30CA014520 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI AMY TRENTHAM-DIETZ · 1985 to 2026
$142.6M
Institutional Clinical and Translational Science AwardUL1TR000427 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI DREZNER, MARC KENNETH · 2012 to 2016
$32.2M
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
Ultra High Resolution Mass Spectrometer for Biomedical ResearchS10OD018475 · OD · UNIVERSITY OF WISCONSIN-MADISON · PI GE, YING · 2015 to 2015
$2.0M
NCATS NIH HHS UL1 TR000427NCI NIH HHS P30 CA014520NHLBI NIH HHS R01 HL096971NHLBI NIH HHS R01 HL109810NIGMS NIH HHS R01 GM117058NIGMS NIH HHS T32 GM008505NIH HHS S10 OD018475
6 · The paper itself

Abstract

Mass spectrometry (MS)-based top-down proteomics is a powerful method for the comprehensive analysis of proteoforms that arise from genetic variations and post-translational modifications (PTMs). However, top-down MS analysis of high molecular weight (MW) proteins remains challenging mainly due to the exponential decay of signal-to-noise ratio with increasing MW. Size exclusion chromatography (SEC) is a favored method for size-based separation of biomacromolecules but typically suffers from low resolution. Herein, we developed a serial size exclusion chromatography (sSEC) strategy to enable high-resolution size-based fractionation of intact proteins (10-223 kDa) from complex protein mixtures. The sSEC fractions could be further separated by reverse phase chromatography (RPC) coupled online with high-resolution MS. We have shown that two-dimensional (2D) sSEC-RPC allowed for the identification of 4044 more unique proteoforms and a 15-fold increase in the detection of proteins above 60 kDa, compared to one-dimensional (1D) RPC. Notably, effective sSEC-RPC separation of proteins significantly enhanced the detection of high MW proteins up to 223 kDa and also revealed low abundance proteoforms that are post-translationally modified. This sSEC method is MS-friendly, robust, and reproducible and, thus, can be applied to both high-efficiency protein purification and large-scale proteomics analysis of cell or tissue lysate for enhanced proteome coverage, particularly for low abundance and high MW proteoforms.

Indexed as

Chromatography, GelChromatography, High Pressure LiquidChromatography, Reverse-PhaseCreatine Kinase, MM FormHumansMolecular WeightMyocardiumProteinsProteomicsTandem Mass SpectrometryCreatine Kinase, MM FormProteins

Identifiers

PMID28406609
PMCPMC5511113
OpenAlexW2606061971

What OpenQuestion holds

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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.