The Microbiota Multiverse: From Gut to Brain and Beyond
This work explores the microbiomes of diverse biological contexts with various stakeholders and collaborators. It consists of six objectives: the first two relate to interaction between the gut microbiome and host health, the second two investigate the microbiota-gut-brain axis and the last two move beyond the host to consider the microbiomes of the external environment and controversy in the enterotype hypothesis, a major conceptual framework in human gut microbiome research. The first objective confirms findings in previous research by providing further evidence as to the lack of strong microbial associations seen in the healthy aging of the gastrointestinal tract in a non-human primate. The second objective contributes a negative finding to the discussion of an area of gut health where previous studies claimed to have found associations, but themselves had problems in study design, cohort size, or flawed reporting of statistics. In the third objective, a small anorexia nervosa cohort revealed the persistence of individualized microbiome characteristics even in the course of recovery from severe illness. The findings of a sex-stress interaction in the fourth objective underscore the need for future experiments involving the microbiota-gut-brain axis to use mixed-sex cohorts to yield results suitable for translational research, but also provides further evidence of associations of differentially abundant microbes with stress and anxiety which correspond well with other studies in this field. The evaluation of wastewater processing treatment plants in the fifth objective showed that such facilities are effective in removing pathogens and many genes associated with antibiotic resistance, but may elevate concentrations of antibiotics during the treatment process. The last objective has found that algorithmic methods of determining enterotypes are not robust or consistent subject to dataset choice, normalization strategy and corrections for compositional data. This research is unified through its investigations into what constitutes the proper statistical treatment of metagenomics data, especially in the light of its nature as compositional data, and how this may interact with the creation of meaningful benchmarks and "gold standards" which remain to be discovered or invented for this field in order to support reproducible research.