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 past 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 <i>Escherichia coli</i> K-12 MG1655 cells and demonstrated that TD-DIA-MS with TopDIA increased proteoform and protein identifications compared with TD-DDA-MS.
Authors
- Yong Zang (ORCID: https://orcid.org/0000-0003-0572-4756)
- Tian Xu (ORCID: https://orcid.org/0000-0003-1464-6008)
- Xingzhao Xiong (ORCID: https://orcid.org/0000-0002-9384-4573)
- Liangliang Sun (ORCID: https://orcid.org/0000-0001-8939-5042)
- Abdul Rehman Basharat (ORCID: https://orcid.org/0000-0002-4675-5375)
- Xiaowen Liu (ORCID: https://orcid.org/0000-0003-4139-1127)
Institutions
- Tulane University (US)
- Cancer Research And Biostatistics (US)
- University School (US)
- Institute for Medical Informatics and Biostatistics (CH)
- Data Management (Italy) (IT)
- Indiana University School of Medicine
- Indiana University – Purdue University Indianapolis (US)
- Indiana University (US)
- Michigan State University (US)
Publication Details
- Journal
- Journal of Proteome Research
- Published
- 2024-12-06
- DOI
- https://doi.org/10.1021/acs.jproteome.4c00293
- Citations
- 5
- Primary Topic
- Advanced Proteomics Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 1.20
Funders
- National Institutes of Health