It is well known at this point that humans host trillions of microbes, many of which actively contribute to human biological processes (e.g. gut bacteria involved in digestion), in various ecological niches around the body. These communities can be very dynamic, even volatile, especially when their host is undergoing a major change. Research into the relationship between the microbiome and human outcomes has increasingly focused on investigating the dynamics of these communities, moving away from the more static, “composition-based” conception of the microbiome more typical of earlier efforts.
A new method for inferring microbial dynamics is to compute peak-to-trough ratios (PTRs), the ratio between metagenomic read coverage at the origin of replication and the replication terminus. PTRs have been shown to be related to bacterial growth rates, uncorrelated with relative abundances, and associated with various outcomes of interest. However, this is a new metric and PTR behavior has not yet adequately been characterized under different conditions of interest. In particular, natural sources of variation in PTR arising to individual differences, site effects, or other sources of randomness in healthy individuals are not yet understood. A natural question to ask is whether some PTR signatures which appear pathological in one case might be acceptable in another.
Preliminary work has been completed computing PTRs for healthy samples in nose and mouth communities and exploring relationships to abundance values. Further work on this project will involve refining PTR prediction models, exploring PTRs stratified by species, and expanding inquiry to more body sites and disease states. Further investigation into individual effects would be a plus. This project is suitable for an advanced undergraduate and will require familiarity with Python or a willingness to learn.
Lab: Computational Genomics
Direct Supervisor: Philippe Chlenski
Position Dates: 6/1/2021 - 7/28/2021
Hours per Week: 40
Paid Position: Yes
Number of positions: 1
Qualifications: Python, probability & statistics
Eligibility: Sophomore, Junior, Senior, Master's