Unmasking the Microbiome

: Revealing Novel Trends in Longitudinal Microbiome Dynamics, with a Spotlight on Divergence

Abstract

Research on gut microbiome has accelerated significantly, suggesting a central role in host health and physiology. In livestock agriculture, this has spurred interest in manipulating the microbiota to enhance productivity, welfare and disease resistance. Deterministic factors — diet, genetics, and environment — are well-recognized in shaping microbial communities, the influence of stochastic processes remains underexplored, particularly in small, isolated groups of hosts.

In Chapter 2, we examined the impact of parasite infection on the faecal microbiomes of lambs. The primary determinant of gut microbiome composition was not the infection but the specific pens in which the lambs were housed. Despite similar rearing conditions, lambs in separate pens developed distinct microbiota. These compositional differences corresponded to variations in predicted microbiome metabolic pathways, indicating potential functional differences between hosts. We termed this phenomenon "microbiome divergence," reflecting the apparent stochastic variation across pens.

To better understand random microbial shifts, in Chapter 3 we developed TaxTrack—a novel software tool designed to analyse population-level trends through unsupervised clustering of microbial presence/absence data. TaxTrack simplifies complex microbiome datasets and identified key acquisition and loss events associated with microbiome divergence.

In Chapter 4, we directly tested the hypothesis that faecal microbiome divergence would recur in isolated lamb groups. We found that this divergence is a repeatable phenomenon, associated with predicted functional differences. Notably, certain deterministic factors appeared to modulate this divergence: antibiotic interventions seemed to facilitate it, while low-energy diets appeared to constrain it. Furthermore, mixing previously diverged communities resulted in distinct microbiome compositions, suggesting the emergence of new microbial trajectories post-mixing.

This thesis highlights the critical but overlooked role of microbiome divergence, emphasizing how random variation can lead to divergent microbial communities. These findings may explain the variability seen in repeated experiments and microbiome intervention outcomes, advancing our understanding of microbiome dynamics in real-world settings.

Date of Award	30 Sept 2025
Original language	English
Awarding Institution	University of Bristol
Supervisor	Laura Peachey (Supervisor), Mick Bailey (Supervisor), Andrew Dowsey (Supervisor) & Sion C Bayliss (Supervisor)