A1 Refereed original research article in a scientific journal

Data-Independent Acquisition Mass Spectrometry in Metaproteomics of Gut Microbiota—Implementation and Computational Analysis




AuthorsJuhani Aakko, Sami Pietilä, Tomi Suomi, Mehrad Mahmoudian, Raine Toivonen, Petri Kouvonen, Anne Rokka, Arno Hänninen, Laura L. Elo

PublisherAmerican Chemical Society

Publication year2020

JournalJournal of Proteome Research

Volume19

Issue1

First page 432

Last page436

Number of pages5

ISSN1535-3893

eISSN1535-3893

DOIhttps://doi.org/10.1021/acs.jproteome.9b00606

Web address https://pubs.acs.org/doi/10.1021/acs.jproteome.9b00606

Self-archived copy’s web addresshttps://research.utu.fi/converis/portal/detail/Publication/44884900


Abstract

Metagenomic approaches focus on
taxonomy or gene annotation but lack power in defining functionality of gut
microbiota. Therefore, metaproteomics approaches have been introduced to
overcome this limitation. However, the common metaproteomics approach uses
data-dependent acquisition mass spectrometry, which is known to have limited
reproducibility when analyzing samples with complex microbial composition. In
this work, we provide a proof-of-concept for data-independent acquisition (DIA)
metaproteomics. To this end, we analyze metaproteomes using DIA mass
spectrometry and introduce an open-source data analysis software package diatools, which enables accurate and
consistent quantification of DIA metaproteomics data. We demonstrate the
feasibility of our approach in gut microbiota metaproteomics using laboratory
assembled microbial mixtures as well as human fecal samples. 


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Last updated on 2024-26-11 at 18:47