Constraint-based modelling of host–microbiome co-metabolism in Alzheimer’s and Parkinson’s disease

The human gut microbiome is a complex microbial ecosystem with essential functions in human health. Alterations in gut microbiome compositions have been implicated in neurodegenerative diseases, including Alzheimer’s disease (AD) and Parkinson’s disease (PD). While these associations are well established, the underlying metabolic mechanisms remain poorly understood. However, computational modelling approaches that utilise constraint-based metabolic network models have provided promising methods for producing mechanistic hypotheses on host-microbiome co-metabolism in health and disease. This thesis aimed to investigate the mechanistic roles of the gut microbiome in the onset and progression of AD and PD pathology by developing and applying novel computational methods for analysing person-specific, microbiome-personalised whole-body metabolic models. To that end, a targeted, literature-informed analytical workflow and new algorithms for identifying microbe-metabolite interactions were introduced. Using these methods, novel mechanistic associations were identified between gut microbiota and metabolic disruptions in AD and PD. The in silico analyses predicted increased microbial contributions to circulating secondary bile acids in individuals at higher risk of AD dementia, and implicated Eggerthella lenta as a potential driver of these changes. In PD, reduced Faecalibacterium prausnitzii relative abundances were associated with diminished host-microbiome production capacities of branched-chain amino acids, short-chain fatty acids, and B vitamins. Furthermore, Bacteroides uniformis was identified as a potential driver of predicted increased microbiome-driven contributions to arginine and methionine metabolism in AD dementia patients. Collectively, these findings provide new insights into how gut microbes may influence neurodegenerative processes and the corresponding metabolic shifts. This work further established computational methods that could aid future developments towards targeted and personalised microbiome-based therapies for Alzheimer’s and Parkinson’s disease.

Publisher

University of Galway

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CC BY-NC-ND

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University of Galway Theses (PhD Theses)