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Using evolutionary genomics to elucidate parasite biology and host-pathogen interactions

Posted on:2010-11-25Degree:Ph.DType:Dissertation
University:University of PennsylvaniaCandidate:Peixoto, LuciaFull Text:PDF
GTID:1448390002486860Subject:Biology
Abstract/Summary:
This dissertation exploits phylogenomic approaches to identify genes and gene families likely to be important in the biology of apicomplexan parasites, including Plasmodium (the causative agent of malaria) and Toxoplasma (a leading source of congenital neurological birth defects, and a prominent opportunistic infection in immunosuppressed individuals). In particular, we have explored the significance of lateral gene transfer and gene duplication as sources of evolutionary novelty. Genomic-scale phylogenetic tree comparison identifies surprisingly extensive lateral gene transfer (LGT), including plant-like genes presumably acquired from the algal source of the apicomplexan plastid (apicoplast), and animal-like genes that may have been acquired from these parasites' host species. Studies on apicomplexan-specific expanded gene families indicate that kinases are a probable source of functional innovation. The T. gondii kinome displays previously under-appreciated diversity in parasite-specific secreted kinases associated with the rhoptry organelles required for host cell invasion. Evolutionary analysis points to the importance of this ‘ROPK’ family, and functional genomics datasets were employed to prioritize family members for further investigation, including sub cellular localization and over expression in transgenic parasites. Transcriptional profiling of host-cell responses to infection, coupled with functional clustering, reveals pathways likely to be regulated by the parasite and a role for ROP38 in controlling this process. Our studies highlight the potential of combining phylogenetics with genome-scale analysis and experimental manipulation to elucidate biological function; similar strategies should be generally useful in integrating the diverse range of genomic-scale datasets that increasingly characterizes modern biomedical research.
Keywords/Search Tags:Gene, Evolutionary
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