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Applied and Environmental Microbiology, July 2009, p. 4341-4353, Vol. 75, No. 13
0099-2240/09/$08.00+0     doi:10.1128/AEM.00079-09
Copyright © 2009, American Society for Microbiology. All Rights Reserved.

Web-Based Software for Rapid Top-Down Proteomic Identification of Protein Biomarkers, with Implications for Bacterial Identification{triangledown} ,{dagger}

Clifton K. Fagerquist,1* Brandon R. Garbus,1 Katherine E. Williams,2 Anna H. Bates,1 Síobhán Boyle,1 and Leslie A. Harden1

Western Regional Research Center, Agricultural Research Service, U.S. Department of Agriculture, 800 Buchanan Street, Albany, California 94710,1 University of California, San Francisco, School of Medicine, Department of Obstetrics, Gynecology and Reproductive Sciences, 505 Parnassus, San Francisco, California 941432

Received 13 January 2009/ Accepted 26 April 2009

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 tandem 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 are the same as the nominal molecular weights of the protein biomarkers. A simple peak-matching and scoring algorithm was developed to compare tandem mass spectrometry (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 10 protein biomarkers from three Campylobacter strains that had been identified previously by bottom-up proteomics techniques. Protein biomarkers were identified using (i) their peak-matching scores and/or P values from a comparison of MS-MS fragment ions with all possible in silico N and C terminus fragment ions (i.e., ions a, b, b-18, y, y-17, and y-18), (ii) 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.]), and (iii) fragment ion error analysis, which distinguished the systematic fragment ion error of a correct identification (caused by calibration drift of the second TOF mass analyzer) from the random fragment ion error of an incorrect identification.

* Corresponding author. Mailing address: Western Regional Research Center, Agricultural Research Service, U.S. Department of Agriculture, 800 Buchanan Street, Albany, CA 94710. Phone and fax: (510) 559-5691. E-mail: clifton.fagerquist{at}ars.usda.gov

{triangledown} Published ahead of print on 1 May 2009.

{dagger} Supplemental material for this article may be found at http://aem.asm.org/.

Applied and Environmental Microbiology, July 2009, p. 4341-4353, Vol. 75, No. 13
0099-2240/09/$08.00+0     doi:10.1128/AEM.00079-09
Copyright © 2009, American Society for Microbiology. All Rights Reserved.





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