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




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

PublisherAmerican Chemical Society

2020

Journal of Proteome Research

19

1

432

436

5

1535-3893

1535-3893

DOIhttps://doi.org/10.1021/acs.jproteome.9b00606(external)

https://pubs.acs.org/doi/10.1021/acs.jproteome.9b00606(external)

https://research.utu.fi/converis/portal/detail/Publication/44884900(external)



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. 


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