In partial fulfillment of the requirements for the degree of

Doctor of Philosophy in Quantitative Biosciences
in the School of Biological Sciences

Hayley B. Hassler

Defends her thesis:
Bacterial systems across scales: quantitative frameworks for within-host, ecological, and evolutionary dynamics

Friday, April 3, 2026
1:00pm Eastern
Location: IBB Suddath Seminar Room (1128)
Zoom:  https://gatech.zoom.us/j/94408297865?pwd=OY25pGlaYyh8ul1Tw0nrBsh7eeYO9S…

Thesis Advisor: 
Dr. Loren Dean Williams
School of Chemistry and Biochemistry
Georgia Institute of Technology

Committee: 
Dr. Gregory P. Fournier
Earth, Atmospheric, and Planetary Sciences
Massachusetts Institute of Technology

Dr. Eberhard O. Voit
School of Natural Sciences and Mathematics
University of Texas, Dallas

Dr. William C. Ratcliff
School of Biological Sciences
Georgia Institute of Technology

Dr. Amit R. Reddi
School of Chemistry and Biochemistry
Georgia Institute of Technology

Dr. Claudia Alvarez-Carreño
Structural and Molecular Biology
University College London

Abstract:
Bacteria are shaped by forces operating across vastly different scales: within-host population dynamics, ecological pressures on trait maintenance, and evolutionary history that fixed core cellular machinery billions of years ago. This dissertation develops quantitative frameworks across all three scales, arguing that understanding bacterial behavior requires integrating all three together. 
A mathematical model of Clostridioides difficile infection, calibrated on murine microbiome data, reveals that susceptibility arises from a dual-insult mechanism: reduced commensal carrying capacity and increased commensal susceptibility to C. difficile inhibition. Neither perturbation alone causes infection, but together they create a permissive state. Spore formation allows C. difficile to persist through antibiotics and reestablish once commensals are suppressed, explaining why antibiotics alone fail. FMT following antibiotics breaks this cycle, accelerating commensal recovery threefold. 
Reanalysis of Type VI Secretion System prevalence across 44,160 genomes revises the canonical estimate from 25% to approximately 40% of Gram-negative genera. The T6SS carries no detectable metabolic cost, so its highly patchy distribution at every taxonomic level implicates ecological context, specifically competitor identity and density, as the dominant selective force governing weapon maintenance. 
Evolutionary rate analysis across 528 Last Bacterial Common Ancestor genes reveals a continuous temporal gradient of peak evolutionary activity. Genetic Information Processing genes peak earliest, while Metabolic genes peak latest. Earlier-peaking genes are also significantly more likely to occupy central positions in the protein interaction network. This gradient is framed within Earth's geobiological record, consistent with environmental transitions having shaped when different cellular systems were free to diversify.

Across all three chapters, bacterial behavior emerges as a product of immediate community context, the selective pressures that favor or disfavor particular traits, and the deep evolutionary history that constrains what options are available. Together, these chapters demonstrate how quantitative approaches can move bacterial research from description to mechanism, and from mechanism toward prediction.