SPS22-7GL

Low Single Nucleotide Polymorphism Density of Archaea may Suggest Low Population Diversity of Other Microorganisms in a Community of Hot Spring in Northern Spain

By: Daniel R Hogan

Department: Cellular & Molecular Biology

Faculty Advisor: Dr. José R. de la Torre

The use of next generation sequencing in microbiology is opening previously closed doors in our understanding of the microbial world. With Metagenome-Assembled Genomes (MAGs) obtained directly from environmental samples instead of traditionally used pure cultures, scientists are able to better understand microbes that have proven difficult or even impossible to cultivate in the laboratory. Many of these microbes are key contributors to geochemical cycles, making a clearer understanding of their biology paramount to understanding global biological processes. A group of chemolithoautotrophic, thermophilic ammonia-oxidizing archaea (ThAOA) found exclusively in terrestrial hot spring sediments are a varied and interesting subject for this novel approach. This project aims to use metagenomics to examine the patterns of genetic diversity and evolution in natural populations of ammonia-oxidizing archaea. Work by a previous student in our lab examined the genetic diversity of a population of ThAOA in a hot spring in northern Spain. By mapping individual metagenomic reads to the genome of the ThAOA Nitrosocaldus islandicus 3F, and quantifying the number of single nucleotide polymorphisms (SNPs), we found that this population of ThAOA had dramatically reduced SNP density, with the vast majority of reads having 100% sequence identity to the reference. To determine if this pattern is unique to the ThAOA in this spring, I have examined the SNP density of other microorganisms with significant abundance in this spring. Here, I will present a holistic view of the genetic diversity of microorganisms in this spring and discuss ecological and evolutionary implications. In the future, I will also incorporate new long-read sequencing technology, with individual reads longer than 10,000-20,000 base pairs, to further explore population-level genetic variation in natural hot spring microbial communities.