Bioinformatics-based strategies for rapid microorganism identification by mass spectrometry

Plamen A. Demirev, Andrew B. Feldman, Jeffrey S. Lin

Research output: Contribution to journalReview articlepeer-review

32 Scopus citations


We review approaches for microorganism identification that exploit the wealth of information in constantly expanding proteome databases. Masses of an organism's protein biomarkers are experimentally determined and matched against sequence-derived masses of proteins, found together with their source organisms in proteome databases. The source organisms are ranked according to the matches, resulting in microorganism identification. Statistical analysis of proteome uniqueness across organisms in a database enables evaluation of the probability of false identifications based on protein mass assignments alone. Biomarkers likely to be observed can be identified based solely on microbial genome sequence information. Protein identification methodologies allow assignment of detected proteins to specific microorganisms and, by extension, allow identification of the microorganism from which those proteins originate.

Original languageEnglish (US)
Pages (from-to)27-37
Number of pages11
JournalJohns Hopkins APL Technical Digest (Applied Physics Laboratory)
Issue number1
StatePublished - Jan 1 2004

ASJC Scopus subject areas

  • Engineering(all)
  • Physics and Astronomy(all)


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