Evolutionary genomics of the human parasite Schistosoma mansoni and its hosts
Abstract
Traditionally, genomes were perceived as stagnant and passive entities, whereby genes occupied specific locations along the chromosomes. This idea was later challenged by the identification of mobile genes (e.g., transposable elements or TEs). By the process of transposition, TEs are able to move between loci and modify the resulting genomic environment. Such movements create large scale changes in genomes and transcriptomes, through chromosomal re-arrangements and the modification of gene expression patterns. The main objective of my thesis research is to analyze TE dynamics of the genome and transcriptome of Schistosoma mansoni, a human parasite that has a genome laden with TEs. Parasites of the genus Schistosoma are the causative agents of schistosomiasis, a widespread tropical disease infecting over 200 million people worldwide. S. mansoni is the most widespread species of schistosome, distributed in both the Old and the New world. Having an Old world origin, S. mansoni reportedly invaded the New World through the trans-Atlantic slave trade during last 500 years and quickly became established. I quantified TE copy number in the genomes and transcriptomes of Old world and New world strains of the parasite using a custom qPCR assay. Compared to the Old world strains, New world strains of S. mansoni appear to carry more copies of TEs in their genome, possible genomic signatures of its New world invasion. This work provides empirical data to support the hypothesis that TEs proliferate extensively upon genomic stress (such as habitat invasion). The genomic dynamism caused by such proliferations may have enabled parasite to evolve adaptations to thrive in the New world. TEs can also introduce adaptive advantages through the process of Horizontal Gene Transfer (HGT), the movement of genes between distinct biological lineages. The literature suggests that HGTs often occur between hosts and parasites, presumably facilitated by the intimate nature of the host-parasite interaction. As HGTs provide novel adaptations to the gene recipients, the identification of HGTs will provide new insights to host-parasite co-evolution. In Schistosoma-host systems, several published reports suggested the possibility of HGT between schistosomes and hosts, and that some HGTs assist the parasite in evasion of the host immune system. However, most of these reports are based on circumstantial evidence and have not been critically and independently validated. I used molecular and bioinformatics approaches to analyze 13 published claims of HGTs between schistosomes and their hosts. My research revealed that most supposed schistosome-host HGTs are false positives and affirm the importance of using multiple methodologies to validate HGTs, as both DNA samples and next-generation sequencing (NGS) datasets are prone to contamination. Specifically, sequence data from hosts that are infected with parasites often contain spurious parasite DNA as technical artifacts (“xenobiotics”) that are not indicative of HGT between hosts and parasites. Next, I explored the signatures of NGS contamination while studying changes in host gene expression in response to parasitic infection. I sequenced, assembled and annotated the liver transcriptomes of uninfected and S. mansoni infected mice to a) trace the effect of xenobiotics on transcriptome assembly and b) identify global changes in host gene expression related to parasite infection. I found that xenobiotic transcripts can falsely appear as differentially expressed, significantly affecting downstream analysis. I also identified genes associated with metabolic, immunological and inflammatory responses that were differentially expressed in infected mice. These findings enhance our understanding of the host immunological repertoire involved in response to S. mansoni infections, providing insights into host-parasite interplay at the transcript level.
Degree
Ph.D.
Advisors
DeWoody, Purdue University.
Subject Area
Molecular biology|Genetics|Bioinformatics
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