Alan Pacheco Successfully Defends His Thesis

Congratulations to Alan Pacheco on the successful defense of his thesis, "Environmental Modulation of Microbial Ecosystems." Great job Alan!

To learn more about Alan's thesis, read his abstract below:

ABSTRACT

Natural microbiota are essential to the health of living systems - from the human gut to coral reefs. Although advances in DNA sequencing have allowed us to catalogue many of the different organisms that make up these microbial communities, significant challenges remain in understanding the complex networks of interspecies metabolic interactions they exhibit. These interactions are crucial to community stability and function, and are highly context-dependent: the availability of different nutrients can determine whether a set of microbes will interact cooperatively or competitively, which can drastically change a community’s structure. Disentangling the environmental factors that determine these behaviors will not only fundamentally enhance our knowledge of their ecological properties, but will also bring us closer to the rational engineering of synthetic microbiomes with novel functions. Here, I integrate modeling and experimental approaches to quantify the dependence of microbial communities on environmental composition. I then show how this relationship can be leveraged to facilitate the design of synthetic consortia.

The first chapter of this dissertation is a review article that introduces a framework for cataloguing interaction mechanisms, which enables quantitative comparisons and predictive models of these complex phenomena. The second chapter is a computational study that explores one such attribute – metabolic cost – in high detail. It demonstrates how a large variety of molecules can be secreted without imposing a fitness cost on microbial organisms, allowing for the emergence of beneficial interspecies interactions. The third chapter is an experimental study that determines how the number of unique environmental nutrients affects microbial community growth and taxonomic diversity. The integration of stoichiometric and consumer resource models enabled the discovery of basic ecological principles that govern this environment phenotype relationship. The fourth chapter applies these principles to the design of engineered communities via a search algorithm that identifies environmental compositions that yield specific ecosystem properties. This dissertation then concludes with extensions of the modeling methods used throughout this work to additional model systems.

Future work could further quantify how microbial community phenotypes depend on each of the individual factors explored in this thesis, while also leveraging emerging knowledge on interaction mechanisms to design synthetic consortia.

Major Professor: Daniel Segre