Evidence map›Paper›PMID 37728997›Full record

ArticleJournal of proteome research2023

Characterization of Proteoform Post-Translational Modifications by Top-Down and Bottom-Up Mass Spectrometry in Conjunction with Annotations.

Wenrong Chen, Zhengming Ding, Yong Zang, Xiaowen Liu

Abstract 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 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Wenrong ChenDepartment of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, Indiana 46202, United States.ORCID 0000-0002-0621-4128
Zhengming DingDepartment of Computer Science, Tulane School of Science and Engineering, Tulane University, New Orleans, Louisiana 70118, United States.
Yong ZangDepartment of Biostatics and Health Data Sciences, Indiana University School of Medicine, Indianapolis, Indiana 46202, United States.
Xiaowen LiuTulane Center for Biomedical Informatics and Genomics, Tulane University, New Orleans, Louisiana 70112, United States.ORCID 0000-0003-4139-1127

Funding

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
Quantitative top-down proteomics of human colorectal cancer cells and tumorsR01CA247863 · NCI · MICHIGAN STATE UNIVERSITY · PI HUMMON, AMANDA B., LIU, XIAOWEN · 2021 to 2025
$1.9M
NCI NIH HHS R01 CA247863NIAID NIH HHS R01 AI141625NIGMS NIH HHS R01 GM118470
6 · The paper itself

Abstract

Many proteoforms can be produced from a gene due to genetic mutations, alternative splicing, post-translational modifications (PTMs), and other variations. PTMs in proteoforms play critical roles in cell signaling, protein degradation, and other biological processes. Mass spectrometry (MS) is the primary technique for investigating PTMs in proteoforms, and two alternative MS approaches, top-down and bottom-up, have complementary strengths. The combination of the two approaches has the potential to increase the sensitivity and accuracy in PTM identification and characterization. In addition, protein and PTM knowledge bases, such as UniProt, provide valuable information for PTM characterization and verification. Here, we present a software pipeline PTM-TBA (PTM characterization by Top-down and Bottom-up MS and Annotations) for identifying and localizing PTMs in proteoforms by integrating top-down and bottom-up MS as well as PTM annotations. We assessed PTM-TBA using a technical triplicate of bottom-up and top-down MS data of SW480 cells. On average, database search of the top-down MS data identified 2000 mass shifts, 814.5 (40.7%) of which were matched to 11 common PTMs and 423 of which were localized. Of the mass shifts identified by top-down MS, PTM-TBA verified 435 mass shifts using the bottom-up MS data and UniProt annotations.

Indexed as

ProteomicsTandem Mass SpectrometryHistonesProtein Processing, Post-TranslationalSoftwareHistonesbottom-up mass spectrometrypost-translational modificationtop-down mass spectrometry

Identifiers

PMID37728997
PMCPMC10563160

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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.