MetaPilot: genome-aware adaptive search-space refinement for unified DDA and DIA metaproteomics
Cheng, K.; Figeys, D.
Show abstract
Metaproteomic peptide identification is constrained by the structure and size of the protein search space. Pooled gene catalogues provide coverage but obscure genome-level evidence, and current workflows for data-dependent (DDA) and data-independent (DIA) acquisition diverge in their database strategies. We present MetaPilot, a genome-aware software platform that uses conserved marker-protein evidence to rank candidate genomes from MGnify catalogues and construct adaptive, sample-specific search spaces. Applied to paired DDA/DIA datasets of defined mixtures and faecal samples, MetaPilot adapted genome selection to community complexity and reproduced published peptide evidence while expanding the detectable peptide space. In DDA-independent reanalysis of Orbitrap human gut DIA data, MetaPilot identified 24.4% more peptides than the published DDA-derived library and 2.06-fold more than the matched DDA-assisted DIA search. On timsTOF DIA-PASEF mouse intestinal data, it outperformed uMetaP by 41.8 to 119.7%, enabling genome-resolved functional interpretation without DDA-PASEF input.
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