Functional assignment of the 20 S proteasome from Trypanosoma brucei usingmass spectrometry and new bioinformatics approaches

As experimental technologies for characterization of proteomes emerge, bioi nformatic analysis of the data becomes essential. Separation and identifica tion technologies currently based on two-dimensional gels/mass spectrometry provide the inherent analytical power required. This strategy involves pro tein spot digestion and accurate mass mapping together with computational i nterrogation of available data bases for protein functional identification. When either no exact match is found or when the possible matches only part ially account for molecular weights actually observed, peptide sequencing b y tandem mass spectrometry has emerged as the methodology of choice to prov ide the basic additional information required. To evaluate the capabilities of bioinformatics methods employed for identifying homologs of a protein o f interest, we attempted to identify the major proteins from the 20 S prote asome of Trypanosoma brucei using sequence information determined using mas s spectrometry. The results suggest that neither the traditional query engi nes, BLAST and FASTA, nor specialized software developed for analysis of se quence information obtained by mass spectrometry are able to identify even closely related sequences at statistically significant scores. To address t his deficit, new bioinformatics approaches were developed for concomitant u se of the multiple fragments of short sequence typically available from met hods of tandem mass spectrometry. These approaches rely on the occurrence o f congruence across searches of multiple fragments from a single protein. T his method resulted in sharply better statistical significance values for c orrect hits in the data base output relative to that achieved for independe nt searches using single sequence fragments.