Peptides panned from a phage-displayed random peptide library are useful for the detection of Bacillus anthracis surrogates B. cereus 4342 and B. anthracis Sterne
- PMID: 20350526
- DOI: 10.1016/j.bbrc.2010.03.145
Peptides panned from a phage-displayed random peptide library are useful for the detection of Bacillus anthracis surrogates B. cereus 4342 and B. anthracis Sterne
Abstract
Recent use of Bacillus anthracis as a bioweapon has highlighted the need for a sensitive monitoring system. Current bacterial detection tests use antibodies as bio-molecular recognition elements which have limitations with regard to time, specificity and sensitivity, creating the need for new and improved cost-effective high-affinity detection probes. In this study, we screened a commercially available bacteriophage-displayed random peptide library using Bacillus cereus 4342 cells as bait to identify peptides that could be used for detection of Bacillus. The method enabled us to identify two 12-amino acid consensus peptide sequences that specifically bind to B. cereus 4342 and B. anthracis Sterne, the nonpathogenic surrogates of B. anthracis strain. The two Bacillus-binding peptides (named BBP-1 and BBP-2) were synthesized with biotin tag to confirm their binding by four independent detection assays. Dot-blot analysis revealed that the peptides bind specifically to B. cereus 4342 and B. anthracis Sterne. Quantitative analysis of this interaction by ELISA and fluorometry demonstrated a detection sensitivity of 10(2) colony forming U/ml (CFU/ml) by both assays. When the peptides were used in combination with Qdots, the sensitivity was enhanced further by enabling detection of even a single bacterium by fluorescence microscopy. Immunoblot analysis and protein sequencing showed that BBP-1 and BBP-2 bound to the S-layer protein of B. anthracis Sterne. Overall, our findings validate the usefulness of synthetic versions of phage-derived peptides in combination with Qdot-liquid nanocrystals as high sensitivity bioprobes for various microbial detection platforms.
Published by Elsevier Inc.
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