Salivary Metaproteomics: A two-step workflow for analyzing oral microbiome in a high-density human saliva dataset and its clinical significance.

摘要

Salivary proteome was analyzed using search algorithms for high mass accuracy datasets to generate a confident list of proteins and peptides. We searched high-mass accuracy peaklists against large databases using a two-step approach. More spectra, distinct sequences (both human and microbial), proteins (both human and microbial) and microbial strains (with at least one unique peptide; Pep2Pro) were identified with the two-step approach. Bacteria from whole salivary dataset and on pre-malignant oral datasets were identified with the two-step approach. 123 bacterial species and 2 viral species were identified using MEGAN analysis. Most bacterial species (except six) were listed in current version of HOMD database. Genus level reads may provide a better representation of taxonomic prevalence patterns within the whole salivary metaproteome dataset. Pathway analysis offers an insight into the functional role of microbial proteins expressed in the salivary microbiome. For clinical exudate dataset, pilot study in a single patient shows differences in species using the two-step approach; additional studies in more patients is needed to determine significance.