Journal Article

Stochastic variation in the initial phase of bacterial infection predicts the probability of survival in D. melanogaster

Kondolf, Hannah, Ortiz, Gerardo A, Revah, Jonathan, Duneau, David, Ferdy, Jean-Baptiste, Lazzaro, Brian P, Buchon, Nicolas

2017

Overview

A central problem in infection biology is understanding why two individuals exposed to identical infections have different outcomes. We have developed an experimental model where genetically identical, co-housed Drosophila given identical systemic infections experience different outcomes, with some individuals succumbing to acute infection while others control the pathogen as an asymptomatic persistent infection. We found that differences in bacterial burden at the time of death did not explain the two outcomes of infection. Inter-individual variation in survival stems from variation in within-host bacterial growth, which is determined by the immune response. We developed a model that captures bacterial growth dynamics and identifies key factors that predict the infection outcome: the rate of bacterial proliferation and the time required for the host to establish an effective immunological control. Our results provide a framework for studying the individual host-pathogen parameters governing the progression of infection and lead ultimately to life or death. Sick individuals do not all respond to an infection in the same way. One individual may experience mild symptoms and recover easily, while another may suffer devastating illness or even death. A number of factors are often assumed to account for these differences, including the sex, age and genes of the individuals, and differences in the environments the individuals have been exposed to. However, random variations in how an individual’s immune system interacts with the infection could also play an important role in recovery. Duneau et al. have now studied how genetically identical fruit flies who were raised in the same environment respond to different bacterial infections. This enabled them to develop a mathematical model that describes how a bacterial infection develops in an individual. In an initial phase, the bacteria proliferate freely. If the immune defenses activate in time to control the infection, the number of bacteria in the fly decreases to a constant level and the infection enters a long-term, or chronic, phase. The sooner this happens the more likely it is that the fly will survive. If the immune control happens too late, the infection enters a terminal phase and the fly will die once the number of bacteria increases to a certain level. The model therefore reveals that the precise time at which the immune system takes control of the bacterial population – termed the “Time to Control” – determines the outcome of the infection. Duneau et al. confirmed this by injecting bacteria into identical flies. A small variation in the Time to Control was sometimes the difference between a fly living or dying. Understanding what controls this apparently random variation is key to understanding infection and potentially developing more efficient treatments for a wide range of diseases – not just those caused by bacteria, but also those caused by viruses and parasites, like HIV and malaria.

• Publisher: eLife Sciences Publications Ltd,eLife Sciences Publications, Ltd
• Subject: Animals / Bacteria / Bacterial infections / Bacterial Infections - immunology / Bacterial Infections - pathology / Disease Models, Animal / Drosophila / Drosophila melanogaster / Drosophila melanogaster - immunology / Drosophila melanogaster - microbiology / Drosophila melanogaster - physiology / Enterococcus faecalis / Growth rate / Host-Pathogen Interactions / Imd pathway / Immune response / Infections / innate immunity / Insects / inter-individual variation / Microbiology and Infectious Disease / mixture modelling / Parasites / Pathogens / Random variables / Standard deviation / stochasticity / Survival / Survival Analysis