Basharat, A. R. | Search bioRxiv

bioRxiv2024

TopDIA: A Software Tool for Top-Down Data-Independent Acquisition Proteomics

Top-down mass spectrometry is widely used for proteoform identification, characterization, and quantification owing to its ability to analyze intact proteoforms. In the last decade, top-down proteomics has been dominated by top-down data-dependent acquisition mass spectrometry (TD-DDA-MS), and top-down data-independent acquisition mass spectrometry (TD-DIA-MS) has not been well studied. While TD-DIA-MS produces complex multiplexed tandem mass spectrometry (MS/MS) spectra, which are challenging to confidently identify, it selects more precursor ions for MS/MS analysis and has the potential to increase proteoform identifications compared with TD-DDA-MS. Here we present TopDIA, the first software tool for proteoform identification by TD-DIA-MS. It generates demultiplexed pseudo MS/MS spectra from TD-DIA-MS data and then searches the pseudo MS/MS spectra against a protein sequence database for proteoform identification. We compared the performance of TD-DDA-MS and TD-DIA-MS using Escherichia coli K-12 MG1655 cells and demonstrated that TD-DIA-MS with TopDIA increased proteoform and protein identifications compared with TD-DDA-MS.

bioinformatics↗

bioRxiv2022

TopFD - A Proteoform Feature Detection Tool for Top-Down Proteomics

Top-down liquid chromatography-mass spectrometry (LC-MS) analyzes intact proteoforms and generates mass spectra containing peaks of proteoforms with various isotopic compositions, charge states, and retention times. An essential step in top-down MS data analysis is proteoform feature detection, which aims to group these peaks into peak sets (features), each containing all peaks of a proteoform. Accurate protein feature detection enhances the accuracy in MS-based proteoform identification and quantification. Here we present TopFD, a software tool for top-down MS feature detection that integrates algorithms for proteoform feature detection, feature boundary refinement, and machine learning models for proteoform feature evaluation. We performed extensive benchmarking of TopFD, Promex, FlashDeconv, and Xtract using five top-down MS data sets and demonstrated that TopFD outperforms other tools in feature accuracy, reproducibility, and feature abundance reproducibility.

bioinformatics↗