RT Journal Article
SR Electronic
T1 Metaproteomics boosted up by untargeted data-independent acquisition data analysis framework
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.12.21.423800
DO 10.1101/2020.12.21.423800
A1 Pietilä, Sami
A1 Suomi, Tomi
A1 Elo, Laura L.
YR 2020
UL http://biorxiv.org/content/early/2020/12/22/2020.12.21.423800.abstract
AB Mass spectrometry based metaproteomics is a relatively new field of research that provides the ability to characterize the functionality of microbiota. Recently, we were the first to demonstrate the applicability of data-independent acquisition (DIA) mass spectrometry to the analysis of complex metaproteomic samples. This allowed us to circumvent many of the drawbacks of the conventionally used data-dependent acquisition (DDA) mass spectrometry, mainly the limited reproducibility when analyzing samples with complex microbial composition. However, the previous method still required additional DDA data on the samples to assist the DIA analysis. Here, we introduce, for the first time, a DIA metaproteomics approach that does not require any DDA data, but instead replaces a spectral library generated from DDA data with a pseudospectral library generated directly from the metaproteomics DIA samples. We demonstrate that using the new DIA-only approach, we can achieve higher peptide yields than with the DDA-assisted approach, while the amount of required mass spectrometry data is reduced to a single DIA run per sample. The new DIA-only metaproteomics approach is implemented as open-source software package DIAtools 2.0, which is freely available from DockerHub.Competing Interest StatementThe authors have declared no competing interest.