Microbial communities are integral for the survival of organisms and ecosystems. Anthropogenic influences like pollution and climate change drastically impact their environment, and microbial responses to these phenomena are uncertain. My dissertation investigates microbial functional and genetic variation with climate change. I aimed to address the following objectives, 1) determine how microbial community extracellular enzyme activity varied during a reciprocal transplant that simulated climate change; 2) assess the evolutionary history, phylogeny, and habitat preference in a comparative genomic analysis of publicly available Sphingomonas genomes found worldwide; 3) uncover how Sphingomonas clade and functional distribution vary under simulated climate change. To address these objectives, I used computational, statistical, and bioinformatic techniques to analyze proteomic, genomic, and metagenomic data.
In my first chapter, I investigated the variation in extracellular enzyme activity and litter decomposition of microbial communities from a Southern California climate gradient after an 18-month reciprocal transplant. Communities were from five sites that varied inversely with temperature and precipitation (desert, grassland, mountains, etc.), and the reciprocal transplant simulated future climate change conditions. During the reciprocal transplantation, microbial communities from each site were inoculated onto sterile grassland leaf litter, placed in bags that allowed for the transfer of nutrients, and distributed back into each site. Enzyme activity suggested microbial communities were not specialized to their native environment. Additionally, there was rarely a reduction in enzyme function after microbial communities were transplanted into new climate conditions. I found significant differences in decomposition rates; however, they were not related to enzyme activities. These results suggest that direct, physiological impacts of climate are potentially important for enzyme-mediated decomposition, but climate specialization will not constrain the microbial response to climate change in our system.
In my second chapter, I used the bacterium Sphingomonas to explore why certain bacteria are present in specific habitats, by analyzing how microbial traits vary with evolutionary history. The Sphingomonas genus inhabits a wide variety of environments and hosts, making it ideal for examining the distribution of habitat preference traits. Furthermore, with appropriate management and manipulation, Sphingomonas can rehabilitate polluted locations. In this project, I downloaded publicly available Sphingomonas genomes, quality filtered them, curated them into eight habitat categories based on their isolation source (plants, animals, contaminated sites, etc.), analyzed their gene content, and assessed their evolutionary history. I found that closely related Sphingomonas genomes shared similar accessory genes, and genomes from similar habitats clustered together in phylogenetic clades. Moreover, the frequencies of functional genes significantly varied by habitat, suggesting habitat preference. Understanding environmental and host influence on Sphingomonas evolutionary history at a genomic level will aid future functional predictions and restoration of polluted habitats.
In my third chapter, I expand on my previous findings to inspect the clade and functional distribution of Sphingomonas along the Southern California climate gradient, before and after the reciprocal transplantation. Using metagenomic data, I trimmed and quality filtered sequences, extracted Sphingomonas core genes, determined Sphingomonas clade composition, and inferred the distribution of gene-based functional traits. I confirmed that prior to transplantation, sites have distinct Sphingomonas clade compositions. The clade and functional composition shift after the 18-month transplant, and site conditions had the most significant effect on both clade and functional composition. In combination with previous research from the Southern California climate gradient, these findings support consistent bacterial response to climate change at multiple phylogenetic levels. In summary, this work will help assess and predict microbial response to climate change.