Studying the evolutionary history of human microbiome members is indispensable to understanding how our microbiota complexity has been shaped over time. While recent decades have witnessed remarkable progress in investigation of the human microbiome within different evolutionary contexts, reconstructing a time-resolved divergence history for human microbiome members is still extremely challenging. Longitudinal metagenomics studies have shown the potential of addressing such challenges, but it is limited in tracking the evolutionary change in a short term. By contrast, leveraging the microbial genomic information preserved in the ancient metagenomic samples from the long past is emerging as a powerful strategy to study the long-established evolutionary history of the human microbiome. In this thesis, I aimed to devise a novel methodology that allows for efficiently reconstructing a time-resolved evolutionary history of human microbiome species using ancient metagenomic data. To this end, I firstly started from comparing four newly excavated paleofeces samples to a large body of contemporary metagenomic datasets. I observed that our human gut microbiota has diverged from its ancestral state in both microbial composition and metabolic pathways. This could be related to the change of lifestyle during human history. To better understand the divergence time of microbiome members, I secondly developed a novel computational pipeline which can precisely reconstruct and date strain-level phylogenies for microbiome species using carbon dated ancient metagenomic samples as calibration under Bayesian molecular clocking framework. The application of this tool has uncovered the unprecedented evolutionary diversity, in the context of geography and time period, of three Methanobrevibacter species from the human oral microbiome, and reconstructed a delicate time-resolved evolutionary history for common gut microbial species, such as Prevotella copri, Eubacterium rectale, Methanobrevibacter smithii and others mainly populating in the human gut microbiota. This approach promises that more underlying evolutionary history about the human microbiome will be unveiled in the foreseen future.

Evolutionary analysis of the human microbiome using ancient metagenomic samples / Huang, Kun. - (2021 Oct 15), pp. 1-180. [10.15168/11572_318833]

Evolutionary analysis of the human microbiome using ancient metagenomic samples

Huang, Kun
2021-10-15

Abstract

Studying the evolutionary history of human microbiome members is indispensable to understanding how our microbiota complexity has been shaped over time. While recent decades have witnessed remarkable progress in investigation of the human microbiome within different evolutionary contexts, reconstructing a time-resolved divergence history for human microbiome members is still extremely challenging. Longitudinal metagenomics studies have shown the potential of addressing such challenges, but it is limited in tracking the evolutionary change in a short term. By contrast, leveraging the microbial genomic information preserved in the ancient metagenomic samples from the long past is emerging as a powerful strategy to study the long-established evolutionary history of the human microbiome. In this thesis, I aimed to devise a novel methodology that allows for efficiently reconstructing a time-resolved evolutionary history of human microbiome species using ancient metagenomic data. To this end, I firstly started from comparing four newly excavated paleofeces samples to a large body of contemporary metagenomic datasets. I observed that our human gut microbiota has diverged from its ancestral state in both microbial composition and metabolic pathways. This could be related to the change of lifestyle during human history. To better understand the divergence time of microbiome members, I secondly developed a novel computational pipeline which can precisely reconstruct and date strain-level phylogenies for microbiome species using carbon dated ancient metagenomic samples as calibration under Bayesian molecular clocking framework. The application of this tool has uncovered the unprecedented evolutionary diversity, in the context of geography and time period, of three Methanobrevibacter species from the human oral microbiome, and reconstructed a delicate time-resolved evolutionary history for common gut microbial species, such as Prevotella copri, Eubacterium rectale, Methanobrevibacter smithii and others mainly populating in the human gut microbiota. This approach promises that more underlying evolutionary history about the human microbiome will be unveiled in the foreseen future.
XXXIII
2019-2020
CIBIO (29/10/12-)
Biomolecular Sciences
Segata, Nicola
Rota Stabelli, Omar
no
Inglese
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Descrizione: Final version of the PhD Thesis
Tipologia: Tesi di dottorato (Doctoral Thesis)
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11572/318833
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