pyMS-Vis, an Open-Source Python Application for Visualizing and Investigating Deconvoluted Top-Down Mass Spectrometric Experiments: A Histone Proteoform Case Study

We report the development of an open-source Python application that provides quantitative and qualitative information from deconvoluted liquid-chromatography top-down mass spectrometry (LC-TDMS) data sets. This simple-to-use program allows users to search masses-of-interest across multiple LC-TDMS runs and provides visualization of their ion intensities and elution characteristics while quantifying their abundances relative to one another. Focusing on proteoform-rich histone proteins from the green microalga <i>Chlamydomonas reinhardtii</i>, we were able to quantify proteoform abundances across different growth conditions and replicates in minutes instead of hours typically needed for manual spreadsheet-based analysis. This resulted in extending previously published qualitive observations on Chlamydomonas histone proteoforms into quantitative ones, leading to an exciting new discovery on alpha-amino termini processing exclusive to histone H2A family members. Lastly, the script was intentionally developed with readability and customizability in mind so that fellow mass spectrometrists can modify the code to suit their lab-specific needs.

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Publication Details

Journal
Analytical Chemistry
Published
2024-08-30
DOI
https://doi.org/10.1021/acs.analchem.4c02650
Citations
2
Primary Topic
Mass Spectrometry Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.48

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article

pyMS-Vis, an Open-Source Python Application for Visualizing and Investigating Deconvoluted Top-Down Mass Spectrometric Experiments: A Histone Proteoform Case Study

Mowei Zhou, Ljiljana Paša‐Tolić, James Umen, Sarah R. Rommelfanger et al.
2 citations
Analytical Chemistry
Mass Spectrometry Techniques and Applications
0.48
article

pyMS-Vis, an Open-Source Python Application for Visualizing and Investigating Deconvoluted Top-Down Mass Spectrometric Experiments: A Histone Proteoform Case Study

Mowei Zhou, Ljiljana Paša‐Tolić, James Umen, Sarah R. Rommelfanger, James J. Pesavento, Megan S. Bindra, Udayan Das
article en
2 citations

Abstract

We report the development of an open-source Python application that provides quantitative and qualitative information from deconvoluted liquid-chromatography top-down mass spectrometry (LC-TDMS) data sets. This simple-to-use program allows users to search masses-of-interest across multiple LC-TDMS runs and provides visualization of their ion intensities and elution characteristics while quantifying their abundances relative to one another. Focusing on proteoform-rich histone proteins from the green microalga <i>Chlamydomonas reinhardtii</i>, we were able to quantify proteoform abundances across different growth conditions and replicates in minutes instead of hours typically needed for manual spreadsheet-based analysis. This resulted in extending previously published qualitive observations on Chlamydomonas histone proteoforms into quantitative ones, leading to an exciting new discovery on alpha-amino termini processing exclusive to histone H2A family members. Lastly, the script was intentionally developed with readability and customizability in mind so that fellow mass spectrometrists can modify the code to suit their lab-specific needs.

Analytical ChemistryVol. 96(37)
Pacific Northwest National Laboratory (US), Saint Mary's College of California (US), Washington University in St. Louis (US), Donald Danforth Plant Science Center (US), Environmental Molecular Sciences Laboratory (US)
Environmental Molecular Sciences Laboratory, National Institutes of Health, Division of Molecular and Cellular Biosciences
Openalex Percentile: Top 41%
Mass Spectrometry Techniques and Applications
0.48
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