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Expanding the Characterization of Microbial Ecosystems using DIA-PASEF Metaproteomics

Gomez-Varela, D.; Xian, F.; Grundtner, S.; Sondermann, J. R.; Carta, G.; Schmidt, M.

2023-03-16 microbiology
10.1101/2023.03.16.532922 bioRxiv
Show abstract

Metaproteomics is gaining momentum in microbiome research due to the multi-dimensional information it provides. However, current approaches have reached their detection limits. We present a highly-sensitive metaproteomic workflow using the extra information captured by Parallel Accumulation-Serial Fragmentation (PASEF) technology. The comparison of different acquisition modes and data analysis software packages showed that DIA-PASEF and DIA-NN doubled protein identifications of mouse gut microbiota and, importantly, also of the host proteome. DIA-PASEF significantly improved peptide detection reproducibility and quantification accuracy, which resulted in more than twofold identified taxa, reaching depths comparable to metagenomic studies. Consequently, DIA-PASEF exhibited improved coverage of functional networks revealing 131 additional pathways compared to DDA-PASEF. We applied our optimized workflow to a pre-clinical mouse model of chronic pain, in which we deciphered novel host-microbiome interactions. In summary, we present here a metaproteomic approach that paves the way for increasing the functional characterization of microbiome ecosystems and is applicable to diverse fields of biological research.

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