Evidence map›Paper›PMID 36603205›Full record

ArticleJournal of proteome research2023

Optimization of Higher-Energy Collisional Dissociation Fragmentation Energy for Intact Protein-Level Tandem Mass Tag Labeling.

Yanting Guo, Trishika Chowdhury, Meena Seshadri, Kellye A Cupp-Sutton, Qingyu Wang, Dahang Yu, Si Wu

Open access · greenAbstract read
In one paragraph

Article in Journal of proteome research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.4field-weighted citation impact, top 12% 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

12 citing papers in PubMed, 16 citations in OpenAlex.

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

7 authors at 1 institution in 1 country.

Yanting GuoDepartment of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States.
Trishika ChowdhuryDepartment of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States.
Meena SeshadriDepartment of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States.
Kellye A Cupp-SuttonDepartment of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States.
Qingyu WangSchool of Meteorology, University of Oklahoma, Norman, Oklahoma 73019, United States.
Dahang YuDepartment of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States.
Si WuDepartment of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States.ORCID 0000-0002-6346-7359
University of Oklahoma · US

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 labeling (e.g., TMT) is a commonly used approach in quantitative proteomics, and quantification is enabled through detection of low-mass reporter ions generated after MS2 fragmentation. Recently, we have introduced and optimized an intact protein-level TMT labeling platform that demonstrated >90% labeling efficiency in complex samples with top-down proteomics. Higher-energy collisional dissociation (HCD) is commonly utilized for isobaric tag-labeled peptide fragmentation because it produces accurate reporter ion intensities and avoids loss of low mass ions. HCD energies have been optimized for isobaric tag labeled-peptides but have not been systematically evaluated for isobaric tag-labeled intact proteins. In this study, we report a systematic evaluation of normalized HCD fragmentation energies (NCEs) on TMT-labeled HeLa cell lysate using top-down proteomics. Our results suggested that reporter ions often result in higher ion intensities at higher NCEs. Optimal fragmentation of intact proteins for identification, however, required relatively lower NCE. We further demonstrated that a stepped NCE scheme with energies from 30% to 50% resulted in optimal quantification and identification of TMT-labeled HeLa proteins. These parameters resulted in an average reporter ion intensity of ∼4E4 and average proteoform spectrum matches (PrSMs) of >1000 per RPLC-MS/MS run with a 1% false discovery rate (FDR) cutoff.

Indexed as

PeptidesTandem Mass SpectrometryHeLa CellsHumansIndicators and ReagentsIonsProteinsIndicators and ReagentsIonsPeptidesProteinshigher-energy collisional dissociationprotein-level TMT labelingquantitative proteomicsstepped HCD schemetop-down proteomics

Identifiers

PMID36603205
PMCPMC10164041
OpenAlexW4313537730

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.