With increasing efficiency, accuracy, and speed we can access complete genome sequences from thousands of infectious microorganisms; however, the ability to predict antigenic targets of the immune system based on amino acid sequence alone is still needed. Here we use a Leptospira interrogans microarray expressing 91% (3359) of all leptospiral predicted ORFs (3667) and make an empirical accounting of all antibody reactive antigens recognized in sera from naturally infected humans; 191 antigens elicited an IgM or IgG response, representing 5% of the whole proteome. We classified the reactive antigens into 26 annotated COGs (clusters of orthologous groups), 26 JCVI Mainrole annotations, and 11 computationally predicted proteomic features. Altogether, 14 significantly enriched categories were identified, which are associated with immune recognition including mass spectrometry evidence of in vitro expression and in vivo mRNA up-regulation. Together, this group of 14 enriched categories accounts for just 25% of the leptospiral proteome but contains 50% of the immunoreactive antigens. These findings are consistent with our previous studies of other Gram-negative bacteria. This genome-wide approach provides an empirical basis to predict and classify antibody reactive antigens based on structural, physical-chemical, and functional proteomic features and a framework for understanding the breadth and specificity of the immune response to L. interrogans.
Keywords: antibody response; enrichment analysis; leptospirosis; protein microarray.