Abstract

The human body hosts an abundance of microbial communities that, through complex and multi-faceted interactions, interface with host physiology and help govern health and disease. Many of these interactions are beneficial and help maintain host homeostasis or contribute to the metabolic capacity of the host. Some are detrimental, potentially inducing or further exacerbating disease. All are complicated by the vast diversity of microbes that comprise the microbiota at any given site. Identifying microbes or microbial functions that influence health and disease for study and potential use as biomarkers is tantalizing, though difficult. The vast diversity of potential community compositions, redundancy in metagenomically-encoded microbial functions, and the ability of a microbiota at one site to exert influence on distal tissues complicate the identification of biomarkers. In this thesis, I study how microbiota may influence other microbiota at distant sites or the host to develop tools and biomarkers for describing these interactions. To accomplish this goal, I start by exploring the relationship between two neighboring microbiotas to determine whether the microbial composition of the upper airway provides important information about the microbes colonizing the lower respiratory tract in healthy individuals. I then investigate the interactions between the gut microbiota and the lung in the context of asthma to identify new xvii mechanisms that support distal microbial influences on host tissues. Finally, I develop a basis for estimating gut microbial composition by characterizing the its contribution to the metabolic profile of exhaled breath. To study the relationship between the community compositions of the upper and lower airway I acquired nasopharyngeal swabs and tracheal aspirates from a convenience cohort of 184 children undergoing various elective surgeries. These samples acquired from invasive methods, are rare, challenging to acquire, and represent an opportunity to understand to what degree upper airway sampling can inform us about the lower airway microbiota. The samples were sequenced using V4 16S rDNA sequencing and contaminant sequences were filtered out using published analytical tools. In the resulting data I found that the upper and lower airway do not seem to share taxa more frequently than by chance alone, but networks of taxa in the upper airway correlate with networks of taxa in the lower airway. These results suggest that the upper and lower airways, while surprisingly dissimilar in taxonomic composition, are likely to share a factor responsible for the correlation and motivate future study. In my exploration of the gut-lung axis, I sampled the stool of 95 subjects with asthma and healthy controls. While studies of the microbiota and asthma have focused extensively on early childhood where the gut microbiota composition is linked to the development of airway allergy, evidence suggests that the composition of the gut microbiota of patients with asthma remains different into adulthood. Unlike many previous studies, our sampling criteria collected both children and adults in hopes of identifying features of the microbiota that may affect the disease phenotypes throughout life. By coupling our analysis of V4 16S rDNA sequencing data with a gnotobiotic mouse model of allergic airway inflammation I found that the bacteria, Bacteroides fragilis, encoding the enterotoxin fragilysin increased gut barrier permeability which, in the xviii context of allergic airway inflammation, increased pulmonary oxidative stress. By comparing back to human subjects, I found that B. fragilis encoding bftP was enriched among subjects with asthma compared to healthy controls, suggesting that the effects observed in mice may play an important role in humans. Moreover, our findings suggested a phenotype in the lungs associated with gut microbiota composition that was only observable in the context of allergic airway inflammation. These data support that the gut microbiota may harbor latent functions that can modify the pathophysiology of disease. By identifying these functions, we can develop tools to take advantage of them through vaccination, probiotics, or prebiotics to shift the course of disease towards more tolerable or treatable states. Finally, to further make microbiota-directed therapeutics more relevant in a clinical setting, we need tools to rapidly sample patients and estimate the state of their microbiota. The gut microbiota in humans typically displays the greatest diversity in microbial genes and the greatest biomass. The array of microbial functions encoded by gut bacteria provides an extensive auxiliary metabolism to the host. I hypothesized that a fraction of these metabolites represents volatile organic compounds that were likely to be emitted in the breath of the host. Thus, by measuring and quantifying these volatiles, we may be able to infer important information about the gut microbiota. To catalog the contribution of the gut microbiota to host breath I needed a system that would allow me to measure of the breath of gnotobiotic animals. I developed a protocol for capturing the breath of anesthetized mice using a murine ventilator and measuring the captured breath using GCxGC-MS. By colonizing gnotobiotic mice with various microbiota I was able to demonstrate that the composition of the gut microbiota influences the composition of volatiles in host breath. I further investigated the contribution of specific gut microbes to host breath by comparing the volatiles measured in the headspace of anaerobic culture against the volatile xix measured in the breath of mice monocolonized with the same microbe. These experiments revealed a volatile organic compound, ethyl acetate, that was enriched in both the breath of mice and the headspace of culture colonized with a clinical isolate of Escherichia coli. This compound is likely produced by the bacteria in the gut, absorbed by the host, and emitted in host breath. With a well developed understanding of how the gut microbiota influences host breath, we can devise a point of-care diagnostic device that can be used in a clinical setting to determine the state of patients’ gut microbiota. In this thesis I explore the interactions between distinct microbial communities in close anatomical proximity, the mechanisms by which the gut microbiota may exert an influence on distal tissues such as the lung, and methods by which we can measure the effect of the gut microbiota on the lung to infer information about its state. Ultimately, these disparate efforts contribute to the ever-growing body of knowledge concerning how interactions between the host and its microbiota can influence health and disease. Translating this body of knowledge to a clinical setting will ultimately require a development of microbiota-based diagnostic tools. While sequencing and culture will remain the gold standard for characterizing the microbiota of an individual patient, tools that can rapidly measure features of the microbiota and an understanding of the principles that drive microbiota composition and its influence on disease will be essential to making the microbiota accessible to medicine.

Committee Chair

Andrew Kau

Committee Members

Gautam Dantas; Jeffrey Henderson; Megan Baldridge; S. Joshua Swamidass

Degree

Doctor of Philosophy (PhD)

Author's Department

Biology & Biomedical Sciences (Computational & Systems Biology)

Author's School

Graduate School of Arts and Sciences

Document Type

Dissertation

Date of Award

4-21-2026

Language

English (en)

Author's ORCID

https://orcid.org/0000-0003-2427-3727

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Microbiology Commons

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