Host–pathogen immune feedbacks can explain widely divergent outcomes from similar infections

Abstract

A long-standing question in infection biology is why two very similar individuals, with very similar pathogen exposures, may have very different outcomes. Recent experiments have found that even isogenic Drosophila melanogaster hosts, given identical inoculations of some bacterial pathogens at suitable doses, can experience very similar initial bacteria proliferation but then diverge to either a lethal infection or a sustained chronic infection with much lower pathogen load. We hypothesized that divergent infection outcomes are a natural result of mutual negative feedbacks between pathogens and the host immune response. Here, we test this hypothesis in silico by constructing process-based dynamic models for bacterial population growth, host immune induction and the feedbacks between them, based on common mechanisms of immune system response. Mathematical analysis of a minimal conceptual model confirms our qualitative hypothesis that mutual negative feedbacks can magnify small differences among hosts into life-or-death differences in outcome. However, explaining observed features of chronic infections requires an extension of the model to include induced pathogen modifications that shield themselves from host immune responses at the cost of reduced proliferation rate. Our analysis thus generates new, testable predictions about the mechanisms underlying bimodal infection outcomes.

A within-host infection model to explore tolerance and resistance

“…2B) increases with x, bistability cannot occur unless ψ > 0 (Supplementary Material S1.2). Situations where F decreases when x gets large imply that pathogens have a direct negative effect on defense production, as Ellner et al (2021) assumed in their model. Positive values of ψ mean that damage hinders the production of defense.…”

“…Positive values of ψ mean that damage hinders the production of defense. We therefore propose that empirical data indicating bistability, such as those presented in figure 1, suggests that the infection lowers the immune defense either directly, as in Ellner et al (2021), or indirectly, through damage accumulation or resource diversion, as in van Leeuwen et al (2019).…”

“…Recently, van Leeuwen et al (2019) demonstrated that a LV model which explicitly describes the amount of resource diverted from the host by intestinal pathogens can be bistable. Ellner et al (2021) showed that situations where pathogens actively destroy defenses also create bistability in disease outcome. These two models have in common the fact that pathogen proliferation negatively impacts immune defense.…”

“…Most importantly, all these models allow bifurcations only between clearance and chronic equilibrium. Ellner et al (2021) may be the exception but they considered the infection as being almost cleared, as they found that immunity stabilizes pathogen loads at very low levels. In an older work, Mayer et al (1995) demonstrated that non-linear functional responses for both pathogen dynamics and host defense regulation could yield bifurcations between chronic infections with high and low equilibrium pathogen load.…”

Longitudinal monitoring of individual infection progression in Drosophila melanogaster

“…melanogaster lines also display variability in infection response within genetically identical individuals. This variation has been indirectly linked to stochastic differences in bacterial growth within the colonized host early in the infection process and variation in the onset of the animal's immune response (Duneau et al, 2017;Ellner, Buchon, Dörr, & Lazzaro, 2021).The exact source of stochasticity has yet to be directly observed, largely due to a lack of tools capable of providing information on bacterial load noninvasively over time. Characterization of infection progression in flies has typically relied on destructive methods to establish bacterial loads at static time points, e.g.…”