title: A two-step database search method improves sensitivity in peptide sequence matches for metaproteomics and proteogenomics studies.
abstract: Large databases (>10(6) sequences) used in metaproteomic and proteogenomic studies present challenges in matching peptide sequences to MS/MS data using database-search programs. Most notably, strict filtering to avoid false-positive matches leads to more false negatives, thus constraining the number of peptide matches. To address this challenge, we developed a two-step method wherein matches derived from a primary search against a large database were used to create a smaller subset database. The second search was performed against a target-decoy version of this subset database merged with a host database. High confidence peptide sequence matches were then used to infer protein identities. Applying our two-step method for both metaproteomic and proteogenomic analysis resulted in twice the number of high confidence peptide sequence matches in each case, as compared to the conventional one-step method. The two-step method captured almost all of the same peptides matched by the one-step method, with a majority of the additional matches being false negatives from the one-step method. Furthermore, the two-step method improved results regardless of the database search program used. Our results show that our two-step method maximizes the peptide matching sensitivity for applications requiring large databases, especially valuable for proteogenomics and metaproteomics studies.
authors: Minnesota Supercomputing Institute, Minneapolis, MN, USA. pratik@msi.umn.edu
authors: Pratik
authors: P
authors: Jagtap
authors: Jill
authors: J
authors: Goslinga
authors: Joel A
authors: JA
authors: Kooren
authors: Thomas
authors: T
authors: McGowan
authors: Matthew S
authors: MS
authors: Wroblewski
authors: Sean L
authors: SL
authors: Seymour
authors: Timothy J
authors: TJ
authors: Griffin
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D030562:Databases, Protein; D020224:Expressed Sequence Tags; D023281:Genomics / Q000379:methods; D006801:Humans; D054892:Metagenome; D009061:Mouth Mucosa / Q000378:metabolism; D010455:Peptides / Q000737:chemistry*; D040901:Proteomics / Q000379:methods*; D012463:Saliva / Q000378:metabolism; D057386:Search Engine; D012680:Sensitivity and Specificity; D012984:Software; D053719:Tandem Mass Spectrometry / Q000379:methods
chemical_list: D010455:Peptides