Research

Elucidating microbial community dynamics in diverse environments using metagenomics

Abstract

Microbes are the most abundant and ubiquitous living things on earth and have a key role in the Earth’s biogeochemical cycles, in human and animal health and in a wide array of biotechnological applications. Metagenomics has evolutionized the field of microbiology by allowing the direct analysis of microbiomes sampled from the environment and the survey of microorganisms that cannot be grown in laboratory conditions. Moreover, the combination of recent advances in high-throughput sequencing and the growing suite of computational tools being created to aid analyses of metagenomic data has positioned microbiome research in the spotlight. The work conducted in this PhD thesis made use of these available tools to in situ interrogate microbiota recovered from diverse habitats, with the staggering complexity and breadth that they occur and function in their source environments. A wide range of ecological niches was sampled including industrial fermenters, the human gut and soil and the dynamics occurring in the corresponding microbiomes were explored under novel contexts, such as medication or functional screening systems. The investigations presented in this thesis provide insights into different aspects of these dynamics. The first study involved the characterization of the landscape of inter- and intra-species dynamics of microbial communities that form in a controlled environment such as bioethanol fermenters. Using shotgun metagenomic sequencing combined with industrial metadata we showed that patterns of these dynamics throughout the process are shared by microbiomes of different facilities and that the impact of contaminants on industrial performance is strain-dependent, suggesting selective strain removal could be an effective, non-invasive method of improving industrial process performance. The next investigation focused on the more complex interactions that exist between the human microbiome and human physiology in the context of statins, a cholesterol-lowering medication, using fecal metagenomic sequencing and plasma bile acids measurements. The complex dynamics between the gut microbiota and host were reflected in the associations we discovered between changes in bile acids (affected by statins) and specific bacterial species, as well as the type 2 diabetes-characteristic shifts in the gut microbiome composition that might explain the diabetogenic effect observed for this medication. The next part of the research deals with data from another human study, this time focusing on the dynamics between the bacterial and viral fraction of the human gut microbiome under the stress of antibiotic exposure. Following whole metagenome and virome analysis, it was revealed that genes conferring resistance to administered antibiotics offered a competitive advantage to their bacterial hosts and were actively transferred between bacteria and bacteriophages, leading to their long-term expansion and persistence in the gut microbiome. The last chapter zooms into the arms-race between bacteriophages and bacteria as it is reflected in the co-evolution of CRISPR-Cas systems and anti-CRISPR proteins. Using functional metagenomics four new anti-CRISPR proteins were mined from environmental samples, and their characterization showed widespread dissemination across bacterial phylogeny, with evidence of horizontal transfer between bacterial and viral genomes. These findings highlight that we have only started to scratch the surface of understanding the full complexity of bacterial-viral population dynamics. In conclusion, the work conducted in this PhD thesis demonstrates that metagenomic methods, either following or preceded by experimental results, can enhance our understanding of how natural microbial communities form and function, including underlying associations, traits and principles that govern their dynamics and evolution. Such efforts are essential towards determining how these communities shape their surrounding environments and harnessing them for the benefit of society.

Info

Thesis PhD, 2019

UN SDG Classification
DK Main Research Area

    Science/Technology

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