Understanding the impact of agricultural runoff on the microbiomes of marine mammals
Stephen Gaughran, Professor
Integrative Biology
Applications for Spring 2025 are closed for this project.
The California coast is home to more than two dozen marine mammal species. Our state is also a highly productive agricultural center for the country, producing not just food but also agricultural runoff that flows into the ocean. This runoff carries nutrients and microbes from fertilizer and livestock waste, which end up distributed heterogeneously along the coast. Environmental disturbances like this have been shown to affect gut microbiome composition of humans and animals, often with downstream consequences for health. The goal of this project is to assess the impact of agricultural runoff on coastal marine mammals in California through metagenomic sequencing analysis. Students will come away from the project with skills in bioinformatics and data analysis as well as a deeper understanding of host-microbe-environment interactions.
Role: Students will analyze a large metagenomic data set, representing gut microbiomes from hundreds of seals and sea lions collected along the California coast. This will involve assembling bacterial and fungal genomes from the sequencing data, creating a reference database of microbial genomes for each marine mammal host species, assessing differences in microbial composition and relative abundance across individuals, and looking for correlations between those patterns and environmental variables (especially relating to local human population density and agriculture). Students may also look for presence of antibiotic-resistance genes and pathogenic microbial species in the data. Additionally, there could be opportunities for ecological and evolutionary modeling in microbiome and host sequence data. Students will be trained to use several command-line programs for sequence analysis. Depending on research interests, students may be encouraged to further explore the data by writing custom scripts in python, R, or a language of their choosing.
Qualifications: Student should have some background in biology or computer science, but must have a strong interest in both. Competitive applicants will feel comfortable working independently, show an interest in animal health and/or conservation biology, and be open to asking new questions with a complex data set.
Hours: to be negotiated
Biological & Health Sciences