Bioinformatics approaches for assessing microbial communities in the surface ocean

Martin, Kara (2018) Bioinformatics approaches for assessing microbial communities in the surface ocean. Doctoral thesis, University of East Anglia.

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Abstract

Microbes are vital for life on Earth. Within the oceans, they are the major primary producers of oxygen and contribute greatly to the other biogeochemical cycling of the elements which in turn influence the global climate. These microbes can be found inhabiting the oceans throughout the world and they cover over ~70% of the surface of the Earth.

Microbes have evolved in different environments in the oceans and in different ways. To gain an understanding of the microbial communities in the surface oceans in the Arctic and Atlantic oceans environmental scientists based at the University of East Anglia, the University of Groningen and Royal Netherlands Institute for Sea Research collected ocean samples from 68 stations along a transect of the Arctic Ocean, North Atlantic Ocean and South Atlantic Ocean. In addition, they recorded environmental data at the time of sampling, such as temperature and salinity. Genomic DNA from filtered samples was sequenced using high-throughput sequencing.

This thesis contains a comprehensive analysis of this sequencing data with the aim of understanding the composition and distribution of microbial communities in the surface of the ocean. To this end, we designed bioinformatic pipelines in order to analyse metatranscriptome, 18S and 16S rDNA datasets from the set of stations. In addition, we developed a novel methodology for normalising 18S and 16S rDNA copy numbers. This enabled us to perform additional analyses such as biodiversity, co-occurrence and breakpoint analyses. The breakpoint analysis is the first of this type performed for microbes in the ocean across a temperature gradient.

In our results, we observed a greater diversity of 18S and 16S rDNA taxa in the tropical regions of the South Atlantic Ocean, versus the polar regions of the Arctic Ocean. Moreover, in the co-occurrence analysis of the 18S and 16S rDNA datasets, we found two community networks, one positively correlated to temperature and the other negatively. We also performed a breakpoint analysis on our metatranscriptome, 18S and 16S rDNA datasets and found a shift in diversity occurring in the North Atlantic Ocean. In particular, the shift occurs in the temperate region of the North Atlantic Ocean, between the polar Arctic Ocean and tropical South Atlantic Ocean.

These results are important because the co-occurrence analysis enables us to hypothesise that different microbial communities have different preferences for temperature. Moreover, as global warming is predicted to raise the temperatures in the ocean, our results could potentially enable forecasts of how climate change will affect these microbial communities using climate models underpinned by genetic information.

Item Type: Thesis (Doctoral)
Faculty \ School: Faculty of Science > School of Computing Sciences
Depositing User: Stacey Armes
Date Deposited: 27 Nov 2019 17:23
Last Modified: 27 Nov 2019 17:23
URI: https://ueaeprints.uea.ac.uk/id/eprint/73181
DOI:

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