Data-Independent Acquisition Mass Spectrometry as a Tool for Metaproteomics: Interlaboratory Comparison Using a Model Microbiome.

Autor:	Rajczewski AT; Department of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota, Minneapolis MN USA., Blakeley-Ruiz JA; Department of Plant and Microbial Biology, North Carolina State University, Raleigh NC USA., Meyer A; MIT-WHOI Joint Program in Oceanography/Applied Ocean Science and Engineering, Department of Chemistry, Woods Hole Oceanographic Institution, Woods Hole MA USA, Department of Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology, Cambridge MA USA., Vintila S; Department of Plant and Microbial Biology, North Carolina State University, Raleigh NC USA., McIlvin MR; Department of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, Woods Hole MA USA., Van Den Bossche T; VIB-UGent Center for Medical Biotechnology, VIB, Ghent Belgium.; Department of Biomolecular Medicine, Faculty of Medicine and Health Sciences, Ghent University, Ghent Belgium., Searle BC; Department of Chemistry and Biochemistry, The Ohio State University, Columbus OH USA., Griffin TJ; Department of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota, Minneapolis MN USA., Saito MA; Department of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, Woods Hole MA USA., Kleiner M; Department of Plant and Microbial Biology, North Carolina State University, Raleigh NC USA., Jagtap PD; Department of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota, Minneapolis MN USA.
Jazyk:	angličtina
Zdroj:	BioRxiv : the preprint server for biology [bioRxiv] 2024 Sep 22. Date of Electronic Publication: 2024 Sep 22.
DOI:	10.1101/2024.09.18.613707
Abstrakt:	Mass spectrometry (MS)-based metaproteomics is used to identify and quantify proteins in microbiome samples, with the frequently used methodology being Data-Dependent Acquisition mass spectrometry (DDA-MS). However, DDA-MS is limited in its ability to reproducibly identify and quantify lower abundant peptides and proteins. To address DDA-MS deficiencies, proteomics researchers have started using Data-Independent Acquisition Mass Spectrometry (DIA-MS) for reproducible detection and quantification of peptides and proteins. We sought to evaluate the reproducibility and accuracy of DIA-MS metaproteomic measurements relative to DDA-MS using a mock community of known taxonomic composition. Artificial microbial communities of known composition were analyzed independently in three laboratories using DDA- and DIA-MS acquisition methods. DIA-MS yielded more protein and peptide identifications than DDA-MS in each laboratory. In addition, the protein and peptide identifications were more reproducible in all laboratories and provided an accurate quantification of proteins and taxonomic groups in the samples. We also identified some limitations of current DIA tools when applied to metaproteomic data, highlighting specific needs to improve DIA tools enabling analysis of metaproteomic datasets from complex microbiomes. Ultimately, DIA-MS represents a promising strategy for MS-based metaproteomics due to its large number of detected proteins and peptides, reproducibility, deep sequencing capabilities, and accurate quantitation. Competing Interests: Authors disclose that there are no conflicts of interest.
Databáze:	MEDLINE
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