Identifying bacterial species using CE-MS and SEQUEST with an empirical scoring function.
CE-MS/MS analysis of proteolytic digests of bacterial cell extracts was combined with SEQUEST searching and a new scoring system to identify bacteria species in bacterial mixtures. Searches of MS/MS spectra against protein databases enabled the identification of bacterial species by the matching of the proteins associated with the corresponding species. An empirical scoring function was obtained by evaluating the SEQUEST search results of 38 samples that contained single bacterial species. The scoring by the empirical function helped move up the positive identification results from their original positions in the ranking based on Xcorr values alone. Therefore, the identification of bacteria in the samples that contained bacterial mixtures was improved. Bacterial species in 20 bacterial mixtures, including one real sample, were correctly identified by database searches and the new scoring function.
Hu
Anren
A
Department of Chemistry, National Dong Hwa University, Hualien, Taiwan.
Lo
Alan A-L
AA
Chen
Cheng-Tung
CT
Lin
Kuo-Chih
KC
Ho
Yen-Peng
YP
D000465:Algorithms; D001419:Bacteria / Q000145:classification*; D002457:Cell Extracts / Q000032:analysis*; D019295:Computational Biology / Q000379:methods; D016208:Databases, Factual; D019075:Electrophoresis, Capillary; D036262:Empirical Research; D010455:Peptides / Q000032:analysis* / Q000737:chemistry; D011506:Proteins / Q000737:chemistry; D020539:Sequence Analysis, Protein; D053719:Tandem Mass Spectrometry; D014357:Trypsin / Q000737:chemistry; D000095983:Bacterial Lysates
D002457:Cell Extracts; D010455:Peptides; D011506:Proteins; D014357:Trypsin; C030259:Broncho-Vaxom; D000095983:Bacterial Lysates