Evidence map›Paper›PMID 35934336›Full record

ArticleAnalytica chimica acta2022

Optimization of protein-level tandem mass tag (TMT) labeling conditions in complex samples with top-down proteomics.

Yanting Guo, Dahang Yu, Kellye A Cupp-Sutton, Xiaowen Liu, Si Wu

Abstract read
In one paragraph

Article in Analytica chimica acta, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
–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

18 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Top-down proteomics.Nature reviews. Methods primers · 2024
    Article
  11. Article
  12. Article
  13. Article
  14. Multidimensional Separations in Top-Down Proteomics.Analytical science advances · 2023
    Article
  15. Article
  16. Review
  17. Article
  18. 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

5 authors.

Yanting GuoDepartment of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, 73019, USA.
Dahang YuDepartment of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, 73019, USA.
Kellye A Cupp-SuttonDepartment of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, 73019, USA.
Xiaowen LiuJohn W. Deming Department of Medicine, Tulane University, New Orleans, LA, 70112, USA.
Si WuDepartment of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, 73019, USA. Electronic address: si.wu@ou.edu.

Funding

Translation of immunologic technologies from basic research into pre-clinical nonU19AI062629 · NIAID · OKLAHOMA MEDICAL RESEARCH FOUNDATION · PI COGGESHALL, KENNETH MARK · 2004 to 2023
$56.2M
Computational tools for top down mass spectrometry based proteoform identification and proteogenomicsR01GM118470 · NIGMS · TULANE UNIVERSITY OF LOUISIANA · PI Xiaowen Liu · 2016 to 2026
$2.7M
Quantitative Analysis of Serum Autoantibody Repertories in Systemic Lupus ErythematosusR01AI141625 · NIAID · UNIVERSITY OF OKLAHOMA · PI SINGH, SHANTERI, SMITH, KENNETH MICHAEL · 2019 to 2023
$2.1M
NIAID NIH HHS R01 AI141625NIAID NIH HHS U19 AI062629NIGMS NIH HHS R01 GM118470
6 · The paper itself

Abstract

Isobaric chemical tag labels (e.g., iTRAQ and TMT) have been extensively utilized as a standard quantification approach in bottom-up proteomics, which provides high multiplexing capacity and enables MS2-level quantification while not complicating the MS1 scans. We recently demonstrated the feasibility of intact protein TMT labeling for the identification and quantification with top-down proteomics of smaller intact proteoforms (<35 kDa) in complex biological samples through the removal of large proteins prior to labeling. Still, the production of side products during TMT labeling (i.e., incomplete labeling or labeling of unintended residues) complicated the analysis of complex protein samples. In this study, we systematically evaluated the protein-level TMT labeling reaction parameters, including TMT-to-protein mass ratio, pH/concentration of quenching buffer, protein concentration, reaction time, and reaction buffer. Our results indicated that: (1) high TMT-to-protein mass ratio (e.g., 8:1, 4:1), (2) high pH/concentration of quenching buffer (pH > 9.1, final hydroxylamine concentration >0.3%), and (3) high protein concentration (e.g., > 1.0 μg/μL) resulted in optimal labeling efficiency and minimized production of over/underlabeled side products. >90% labeling efficiency was achieved for E. coli cell lysate after optimization of protein-level TMT labeling conditions. In addition, a double labeling approach was developed for efficiently labeling limited biological samples with low concentrations. This research provides practical guidance for efficient TMT labeling of complex intact protein samples, which can be readily adopted in the high-throughput quantification top-down proteomics.

Indexed as

ProteomeProteomicsEscherichia coliProteomeIsobaric labelingQuantitative proteomicsTandem mass tags (TMT)Top-down proteomics

Identifiers

PMID35934336
PMCPMC9371347

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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.