Metagenomics uses gene expression patterns to understand the taxonomy and metabolic activities of microbial communities. Metaproteomics applies the same approach to community proteomes. Previously, we used a novel three-dimensional peptide separation method to identify over 2000 salivary proteins. This study used those data to carry out the first metaproteomic analysis of the human salivary microbiota. The metagenomic software MEGAN generated a phylogenetic tree, which was checked against the Human Oral Microbiome Database (HOMD). Pathway analyses were performed with the Clusters of Orthologous Groups and MetaCyc databases. Thirty-seven per cent of the peptides were identifiable only at the level of cellular organisms or bacteria. The rest were distributed among five bacterial phyla (61%), archea (0.5%), and viruses (0.8%); 29% were assignable at the genus level, and most belonged to Streptococcus (17%). Eleven per cent of all peptides could be assigned to species. Most taxa were represented in HOMD and they included well-known species such as periodontal pathogens. However, there also were 'exotic' species including aphid endosymbionts; plant, water, and soil bacteria; extremophiles; and archea. The pathway analysis indicated that peptides were linked to translation (37%), followed by glycolysis (19%), amino acid metabolism (8%), and energy production (8%). The taxonomic structure of the salivary metaproteome is very diverse but is dominated by streptococci. 'Exotic' species may actually represent close relatives that have not yet been sequenced. Salivary microbes appear to be actively engaged in protein synthesis, and the pathway analysis is consistent with the metabolism of salivary glycoproteins.