World Journal of Microbiology and Biotechnology

, 24:2377

Methods for the bioinformatic identification of bacterial lipoproteins encoded in the genomes of Gram-positive bacteria

Authors

  • Obaidur Rahman
    • Northumbria University
  • Stephen P. Cummings
    • Northumbria University
  • Dean J. Harrington
    • University of Bradford
    • Northumbria University
    • Biomolecular and Biomedical Research Centre, School of Applied ScienceNorthumbria University
Review

DOI: 10.1007/s11274-008-9795-2

Cite this article as:
Rahman, O., Cummings, S.P., Harrington, D.J. et al. World J Microbiol Biotechnol (2008) 24: 2377. doi:10.1007/s11274-008-9795-2

Abstract

Bacterial lipoproteins are a diverse and functionally important group of proteins that are amenable to bioinformatic analyses because of their unique signal peptide features. Here we have used a dataset of sequences of experimentally verified lipoproteins of Gram-positive bacteria to refine our previously described lipoprotein recognition pattern (G+LPP). Sequenced bacterial genomes can be screened for putative lipoproteins using the G+LPP pattern. The sequences identified can then be validated using online tools for lipoprotein sequence identification. We have used our protein sequence datasets to evaluate six online tools for efficacy of lipoprotein sequence identification. Our analyses demonstrate that LipoP (http://www.cbs.dtu.dk/services/LipoP/) performs best individually but that a consensus approach, incorporating outputs from predictors of general signal peptide properties, is most informative.

Keywords

Lipoproteins Signal peptides Bioinformatics Genomics Firmicutes Actinobacteria

Supplementary material

11274_2008_9795_MOESM1_ESM.pdf (59 kb)
(PDF 60 kb)

Copyright information

© Springer Science+Business Media B.V. 2008