DOI: 10.25345/c5z02zm6h
title: MassIVE MSV000096205 - Activity-Targeted SIP-Metaproteomics of a Full-Scale Biogas Facility
title: In this work, two BONCAT enrichment techniques were evaluated against a conventional untargeted metaproteomics approach for their ability to enrich the SIP signal of SAOB in metaproteomics data from an anaerobic microbiome. The first BONCAT enrichment was based on sorting active cells using fluorescent activated cell sorting (FACS) prior to protein extraction for mass spectrometry. The second BONCAT technique involved protein extraction from bulk biomass followed by purification of newly-translated proteins using click chemistry and a biotin-streptavidin bead pulldown assay prior to preparation for mass spectrometry. We found that both of these techniques improved detection of a highly-active and low-abundance syntrophic bacterium that was responsible for significant acetate turnover within the study full-scale biogas facility. The BONCAT-SIP approaches described here therefore represent a powerful toolbox for unraveling the contributions of active microorganisms to microbial communities--a facet of microbial ecology that holds great potential for improving our comprehension of the untapped metabolic potentials contained within microbiomes. Mass spectra data were processed using quantms v1.3.1 of the nf-core collection of workflows, utilizing reproducible software environments from the Bioconda and Biocontainers projects and tools from OpenMS v3.2.0. The workflow was executed with Nextflow v24.04.4. Both 12C-acetate (non-SIP) and 13C-acetate (SIP) samples from all metaproteomic methods were treated identically for peptide identification. Mass spectra were searched against the metagenome-derived protein database using both MSGF+ v2021.03.22 and Comet v2023.01. A target-decoy competition strategy was employed to estimate the rate of false positive peptide-spectrum matches (PSMs). Mass tolerances were set to 5 ppm for precursor (peptide) ions and 0.03 Da for fragment ions. Up to two missed cleavages were allowed and peptide termini were required to match the tryptic cleavage conditions fully. The precursor charge was limited to 2-4 and the peptide length was limited to 6-40. The PSMs were then rescored using Percolator v3.05.0. The two search engine results were combined by retaining only the peptide sequence with the highest E-value for each spectrum and the consensus list of PSMs was filtered with a false discovery rate (FDR) threshold of 10% to reduce decoy and false positive matches. Quantification of peptides was performed on the 12C-acetate (non-SIP) samples using the OpenMS tool, proteomicsLFQ. Peptide intensities were scaled such that the median peptide intensity in every sample was equal. The peptides are then evaluated for uniqueness and used for protein inference. The quantification results were filtered with a protein FDR of 1% and a PSM FDR of 1%. Detection of isotopically labeled peptides in the labeled condition (13C-acetate) was performed using MetaProSIP v2.3.0 as implemented in OpenMS v2.8.0 in a KNIME Analytics Platform v4.6.3 workflow. The unlabeled condition (12C-acetate) paired samples were used to identify coeluting isotopologues in the labeled condition (13C-acetate).