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ARS Home » Pacific West Area » Albany, California » Western Regional Research Center » Produce Safety and Microbiology Research » Research » Publications at this Location » Publication #231683
Title: Web-based software for rapid "top-down" proteomic identification of protein biomarkers with implications for bacterial identification

Author
item Fagerquist, Clifton - Keith
item Garbus, Brandon
item WILLIAMS, KATHERINE - University Of California
item Bates, Anne
item Boyle, Siobhan
item Harden, Leslie - Les

Submitted to: Applied and Environmental Microbiology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/26/2009
Publication Date: 7/1/2009
Citation: Fagerquist, C.K., Garbus, B.R., Williams, K., Bates, A.H., Boyle, S., Harden, L.A. 2009. Web-based software for rapid "top-down" proteomic identification of protein biomarkers with implications for bacterial identification. Applied and Environmental Microbiology. 75(13):4341-4353.

Interpretive Summary: Rapid detection and identification of bacterial microorganisms is a critical element of protecting the safety and security of the Nation's food supply. We have developed web-based software for the rapid "top-down" proteomic identification of protein biomarkers of bacterial microorganisms including food-borne pathogens. Bacterial proteins from cell lysates were ionized by matrix-assisted laser desorption/ionization (MALDI). Intact protein ions were individually selected according to their mass-to-charge (m/z), fragmented and the fragment ions detected using a tandem time-of-flight/time-of-flight (TOF-TOF) mass spectrometer. The sequence-specific fragment ions generated were compared to a database of theoretical fragment ions derived from amino acid sequences of bacterial proteins whose molecular weights have the same nominal mass as that of the protein biomarker. Identification of a specific protein allowed concomitant identification of the source microorganism. The speed and accuracy of the software were tested by identification of ten protein biomarkers from three species/strains of Campylobacter (an important foodborne pathogen) that had been identified previously by "bottom-up" proteomics techniques.

Technical Abstract: We have developed web-based software for the rapid identification of protein biomarkers of bacterial microorganisms. Proteins from bacterial cell lysates were ionized by matrix-assisted laser desorption/ionization (MALDI), mass-isolated and fragmented using a time-of-flight/time-of-flight (TOF-TOF) mass spectrometer. The sequence-specific fragment ions generated were compared to a database of in silico fragment ions derived from bacterial protein sequences whose molecular weights have the same nominal mass as that of the protein biomarker. A simple peak matching/scoring algorithm was developed to compare MS/MS fragment ions to in silico fragment ions. In addition, a probability-based significance testing algorithm (p-value), developed previously by other researchers, was incorporated into the software for the purpose of comparison. The speed and accuracy of the software were tested by identification of ten protein biomarkers from three species/strains of Campylobacter that had been identified previously by "bottom-up" proteomics techniques. Protein biomarkers were identified from: 1. their peak matching scores and/or p-values from a comparison of MS/MS fragment ions to all possible in silico n- and c-terminus fragment ions (i.e. a, b, b-18, y, y-17, y-18); 2. their peak matching scores and/or p-values from a comparison of MS/MS fragment ions to residue-specific in silico fragment ions, i.e. in silico fragment ions resulting from polypeptide backbone fragmentation adjacent to specific residues (aspartic acid, glutamic acid, proline, etc.); 3. fragment ion error analysis which distinguished systematic fragment ion error of a correct identification (caused by calibration drift of the TOF mass analyzer) versus random fragment ion error of an incorrect identification.