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|Title:||Ringtailed lemur social networks and their role in pathogen transmission|
|Authors:||Dykhuizen, Daniel E.|
Sbeglia, Gena Christine
Department of Ecology and Evolution.
Wright, Patricia C.
Dávalos, Liliana M.
Hollister, Jesse D.
|Abstract:||Many of the pathogens that cause disease are transmitted through physical contact, which makes patterns of social behavior potential routes of transmission. Questions about socially facilitated transmission are best addressed by combining data on the observed contacts of the host and the haplotype-level genetic differentiation of the pathogen because individuals must harbor the same or related haplotypes of a particular pathogen for transmission to be deduced. However, few studies simultaneously collect data on both the behavior of the host and the genetics of the pathogen and those that do are limited by their use of culture-based methods. Culture-based methods involve growing a sample on a nutrient plate and identifying the genetic variation in each bacterial isolate across multiple loci. These methods are time- and labor-intensive and unrealistic to accurately differentiate the multiple bacterial haplotypes of the same species that can reside within an infected host. One-locus methods do not require a culturing step and allow sequencing of every amplified haplotype in a sample. Such an approach is used in the microbiome literature via the 16S gene, which can differentiate species or genera of bacteria, but is not appropriate for the haplotype-level differentiation that is necessary to identify incidences of transmission. In this dissertation, I determined patterns of association in wild ringtailed lemurs and developed a one-locus, culture-independent approach for the differentiation of E. coli haplotypes that could be used to test hypothesized routes of pathogen movement. Although not usually pathogenic, E. coli is valuable as a model “pathogenic” organism for social transmission studies because its ubiquity and within-host diversity in mammals allows for the inference of fine-scale patterns of transmission among all individuals, instead of just those infected by an occasional pathogen. Furthermore, its well-known genetics makes it suitable for the development of a novel approach to haplotype differentiation because it is possible to assess the haplotype diversity that is and is not captured by this new method. I collected over 1000 hours of detailed social behavior data on 29 individually identifiable ringtailed lemurs living in three sympatric social groups in Beza Mahafaly Specieal Reserve in south western Madagascar from March–September 2015. Active and passive affiliation had different temporal patterns with individuals decreasing the overall time in active affiliation and increasing the time in passive affiliation from the pre- to the post-mating season. Further, there was substantial variation across individuals in their network centrality for both affiliative and agonistic interactions, but sex and dominance did not explain this pattern for active or passive affiliation, which are the behavior modes most likely to cause pathogen transmission. I also found that social groups differed in their connectedness and that living in degraded habitat may coincide with properties of the social network that could cause heightened pathogen transmission. Animals living in degraded habitat are often expected to have a higher rate of infection because of the increased exposure to pathogens from humans and livestock, but the results presented here suggest a possible amplification of these effects by an increase in network connectedness. To test these hypothesized patterns of transmission, I developed the first one-locus, culture-independent approach for the differentiation of E. coli haplotypes. I identified and tested primers at the FumC locus that target a single, highly variable 294-bp region and found it could differentiate 91-172% of the haplotype diversity as compared to standard multi-locus methods. When applying this method to wild-collected feces sampled bi-weekly throughout the observation period, the results demonstrated its potential to capture much more within-host E. coli haplotype diversity than previously identified in any study to date. When coupled with detailed data on social contact patterns, this method can revolutionize our ability to determine fine-scale transmission dynamics and assess E. coli population genetics within a wild host.|
|Appears in Collections:||Stony Brook Theses and Dissertations Collection|
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