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Cytauxzoonosis is an emerging infectious disease of domestic cats (Felis catus) caused by the apicomplexan protozoan parasite Cytauxzoon felis. The growing epidemic, with its high morbidity and mortality points to the need for a protective vaccine against cytauxzoonosis. Unfortunately, the causative agent has yet to be cultured continuously in vitro, rendering traditional vaccine development approaches beyond reach. Here we report the use of comparative genomics to computationally and experimentally interpret the C. felis genome to identify a novel candidate vaccine antigen for cytauxzoonosis. As a starting point we sequenced, assembled, and annotated the C. felis genome and the proteins it encodes. Whole genome alignment revealed considerable conserved synteny with other apicomplexans. In particular, alignments with the bovine parasite Theileria parva revealed that a C. felis gene, cf76, is syntenic to p67 (the leading vaccine candidate for bovine theileriosis), despite a lack of significant sequence similarity. Recombinant subdomains of cf76 were challenged with survivor-cat antiserum and found to be highly seroreactive. Comparison of eleven geographically diverse samples from the south-central and southeastern USA demonstrated 91-100% amino acid sequence identity across cf76, including a high level of conservation in an immunogenic 226 amino acid (24 kDa) carboxyl terminal domain. Using in situ hybridization, transcription of cf76 was documented in the schizogenous stage of parasite replication, the life stage that is believed to be the most important for development of a protective immune response. Collectively, these data point to identification of the first potential vaccine candidate antigen for cytauxzoonosis. Further, our bioinformatic approach emphasizes the use of comparative genomics as an accelerated path to developing vaccines against experimentally intractable pathogens.

Bartonella henselae is the zoonotic agent of cat scratch disease and causes potentially fatal infections in immunocompromised patients. Understanding the complex interactions between the host's immune system and bacterial pathogens is central to the field of infectious diseases and to the development of effective diagnostics and vaccines.We report the development of a microarray comprised of proteins expressed from 96% (1433/1493) of the predicted ORFs encoded by the genome of the zoonotic pathogen Bartonella henselae. The array was probed with a collection of 62 uninfected, 62 infected, and 8 "specific-pathogen free" naïve cat sera, to profile the antibody repertoire elicited during natural Bartonella henselae infection.We found that 7.3% of the B. henselae proteins on the microarray were seroreactive and that seroreactivity was not evenly distributed between predicted protein function or subcellular localization. Membrane proteins were significantly most likely to be seroreactive, although only 23% of the membrane proteins were reactive. Conversely, we found that proteins involved in amino acid transport and metabolism were significantly underrepresented and did not contain any seroreactive antigens. Of all seroreactive antigens, 52 were differentially reactive with sera from infected cats, and 53 were equally reactive with sera from infected and uninfected cats. Thirteen of the seroreactive antigens were found to be differentially seroreactive between B. henselae type I and type II. Based on these results, we developed a classifier algorithm that was capable of accurately discerning 93% of the infected animals using the microarray platform. The seroreactivity and diagnostic potential of these antigens was then validated on an immunostrip platform, which correctly identified 98% of the infected cats. Our protein microarray platform provides a high-throughput, comprehensive analysis of the feline humoral immune response to natural infection with the alpha-proteobacterium B. henselae at an antigen-specific, sera-specific, and genome-wide level. Furthermore, these results provide novel insight and utility in diagnostics, vaccine development, and understanding of host-pathogen interaction.