Bacteria may acquire novel DNA from other bacteria in their environment through the process of horizontal gene transfer (HGT). This transferred DNA often encodes new functions that expand an organism's niche, change its relationships with its host or provide a competitive edge against other organisms within its environment. For example, antibiotic resistance genes are frequently observed to be transferred between organisms. New high-throughput DNA sequencing technologies now allow researchers to simultaneously sequence data from millions of different bacterial species in a single sample, called metagenome sequencing. Thousands of publicly available metagenomic sequence datasets exist for samples from very diverse ecologies, including: gut microbiomes from humans, animals and insects, soil and root communities, surfaces in built environments, hydrothermal mats and vents, wastewater treatment plants, freshwater sources and marine ecosystems. Using these datasets, the research team will develop a suite of computational tools for examining the mobile gene content of these datasets, to identify those genes that may shape the response of microbial communities to stress. Graduate students will carry out the research under the direction of the PI, while undergraduates will be trained to use the resulting methods through a series of hackathons aimed at building the computational science community focused on microbial community research. Recruiting efforts will be aimed at measurably increasing the diversity in computational biology throughout the greater Finger Lakes region.
Functional characterization of microbial communities is often performed using metagenomic shotgun data, obtained by sequencing microbial samples in their entirety. Yet, despite its importance, few methods exist to distinguish genes that are inherited versus those genes which have been mobilized and transferred between organisms in this type of short-read sequence data. By providing new computational methods for reconstructing mobile genetic elements in short-read data, researchers can tap into the huge resource of existing metagenomic data to examine the role of HGT in shaping the functions of natural microbial communities. This research will be transformative for all fields of microbiology, including clinical microbiology, microbiome research, environmental microbiology, and microbial engineering.
