Defining the shape of disease space across individuals, genetic strains, and diverse populations [electronic resource]

The outcome of infectious disease depends on the ability of the pathogen to grow, the effectiveness of the host immune response, and the degree of damage the host incurs. A considerable number of the molecular components that participate in host-microbe interactions have been identified, yet the dynamics of the interactions between these components remain unclear. In this thesis, I explore various aspects of infection dynamics by examining a lethal-septic disease in Drosophila melanogaster caused by Listeria monocytogenes infection. By leveraging a combination of experimental approaches and mathematical modeling, I determined how varying the magnitude of individual parameters such as immune induction, microbe load, and damage production leads to changes in overall host health. Experimental measurement of the in-host bacterial growth, the dose response curves of antimicrobial peptide expression relative to bacterial loads, and the dose response curve of host survival relative to bacterial loads, defined as tolerance, informed the logic of the mathematical model. The dynamics of these parameters are best described by four-parameter (baseline, maximal, slope, and half-maximal concentration (EC50)) sigmoid functions. Given that microbe growth, immune induction and tolerance follows sigmoid dynamics, we inferred that host damage also follows sigmoid dynamics. These findings suggest that there are four general classes of variation in microbe growth, immune induction, host damage, and tolerance to infection. The mechanisms underlying each individual class of variation likely differ, and this implies that patients suffering from infection encounter different dynamical problems. To improve the efficacy of treatment, the dynamical problem must be identified, and the treatment strategy should be tailored accordingly. To understand the molecular underpinnings of different dynamical problems during infection, I compared the gene expression profiles across infection, antibiotic treatment, and recovery of fly lines that varied in the ability to control bacterial growth, defined as resistance, and tolerance. A mutation in CG2247 leads to a resistance defect to L. monocytogenes infection. CG2247 mutants have a 10-fold greater decrease in proPhenoloxidase-A1 (proPO-A1) expression compared to wild type, and the expression of proPO-A1 fails to return to baseline upon antibiotic treatment. proPO-A1 is a critical mediator of melanization induced by the immune response. Melanization both isolates and destroys invading microbes. Loss of CG2247 leads to an impaired melanization response, which explains the resistance defect. I also examined the gene expression profiles of the RAL359 line, which has a tolerance defect (decreased EC50) and a Pcmt mutant line, which has a defect in both resistance and tolerance (decreased EC50). The molecular mechanisms underlying the phenotypes of these two fly lines remain unclear. The molecular details underlying these different dynamical problems will inform the development of strategies for controlling the parameters of the sigmoid relationships we observe during infection.

Advisor: Schneider David (David Samuel)
Chien Yueh-Hsiu
Martinez Olivia
Sonnenburg Justin