BACKGROUND: Leptospirosis is the most common zoonotic disease worldwide. The diagnostic performance of a serological test for human leptospirosis is mainly influenced by the antigen used in the test assay. An ideal serological test should cover all serovars of pathogenic leptospires with high sensitivity and specificity and use reagents that are relatively inexpensive to produce and can be used in tropical climates. Peptide-based tests fulfil at least the latter two requirements, and ORFeome phage display has been successfully used to identify immunogenic peptides from other pathogens.
METHODOLOGY/PRINCIPAL FINDINGS: Two ORFeome phage display libraries of the entire Leptospira spp. genomes from five local strains isolated in Malaysia and seven WHO reference strains were constructed. Subsequently, 18 unique Leptospira peptides were identified in a screen using a pool of sera from patients with acute leptospirosis. Five of these were validated by titration ELISA using different pools of patient or control sera. The diagnostic performance of these five peptides was then assessed against 16 individual sera from patients with acute leptospirosis and 16 healthy donors and was compared to that of two recombinant reference proteins from L. interrogans. This analysis revealed two peptides (SIR16-D1 and SIR16-H1) from the local isolates with good accuracy for the detection of acute leptospirosis (area under the ROC curve: 0.86 and 0.78, respectively; sensitivity: 0.88 and 0.94; specificity: 0.81 and 0.69), which was close to that of the reference proteins LipL32 and Loa22 (area under the ROC curve: 0.91 and 0.80; sensitivity: 0.94 and 0.81; specificity: 0.75 and 0.75).
CONCLUSIONS/SIGNIFICANCE: This analysis lends further support for using ORFeome phage display to identify pathogen-associated immunogenic peptides, and it suggests that this technique holds promise for the development of peptide-based diagnostics for leptospirosis and, possibly, of vaccines against this pathogen.
* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.