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We have known for a long time that we are not equally susceptible to diseases. More generally, the hosts of pathogens, according to their genetic characteristics or the quality of their diet, can be more or less resistant. In many cases, however, individuals resist infection where other genetically identical individuals (e.g., twins) and sharing the same environment die. Duneau et al. show that minor variations (eg, having eaten or slept before infection), which may be considered random, may in fact significantly affect how an individual's immune system interacts with the infection and thus chances of recovery.

Two trajectories of infection

Duneau et al. studied how fruit flies (Drosophila melanogaster) that are genetically identical and that were raised in the same laboratory environment respond to bacterial infections. They studied bacterial proliferation in the host by injecting bacterial suspensions into 136 flies, sampling 8 flies every hour from injection until 16 hours later. The flies being similar and having received an inoculum of the same bacterial culture, each sample of eight flies allowed the quantification of the infection at sampling time, and thus the monitoring of the average evolution of an infection hour by hour.

In a mathematical model using this data, they found that the infection developed in three possible phases. First, bacteria proliferated freely in the host as in an in vitro medium. In a second, so-called resolution [conflict] phase, if the immune defenses were activated in time, the number of bacteria in the fly decreased and stabilized, the infection then entering in a chronic phase. But, if during the resolution phase the host did not manage to control bacterial growth before density reaches a certain threshold, called "tipping point", the infection entered a terminal phase during which the host although still alive is unavoidably going towards death. The model fitted to the experimental data predicts for a given level of infection the probability that a host will control the infection and thus survive to it.

« Time to control »

The model also reveals that the precise timing at which the host's immune system starts controlling the bacterial population - termed "time to control" - is the primary determinant of the probability of survival to infection. Since a difference of control of a few hours is enough to lead to survival or death, there should be very strong selection in nature for controlling bacterial growth as quickly as possible. However, on the other hand, too strong or too fast responses can also be at the cost of causing autoimmune diseases even in the absence of infection. The authors propose that this trade-off context is probably at the origin of the evolution of the acquired immune response of vertebrates, which is exploited in vaccines and by which the immune system learns from previous encounters with pathogens in order to respond faster but in a controlled way to infection.

Understanding the mechanisms controlling the variation of symptoms between individuals is key in a context of personalized medicine. Duneau et al. show that apparently innocuous actions occurring at the time of infection and that are often considered as "noise" in experiments, may have major effects on the severity of symptoms. This represents both an important discovery for the understanding of diseases but also a challenge to determine which are the best personalized treatments.

A TULIP story

Ph.D. in Evolutionary Parasitology from the University of Basel (Switzerland) under the direction of Dieter Ebert, David Duneau then joined Brian Lazzaro's laboratory at Cornell University (USA). Thanks to his collaboration with B. Lazzaro as well as with the functional genetics laboratory of Nicolas Buchon (Cornell, USA), he learnt how to use Drosophila melanogaster as a powerful model of genetics to study the evolution of host-parasites interactions. Integrated in the "Evolution and Biological Diversity" (EDB) laboratory on a TULIP "Young Scientist for the future" postdoc grant, he developped a project at the interface between molecular and evolutionary biology, in perfect ad equation with TULIP whose goal is to mix integrative biology and ecology. By integrating EDB's collaborative environment, David was able to add an extra approach by working with Jean-Baptiste Ferdy on a mathematical and statistical analysis. Thus, owing to the TULIP grant, David developed a transdisciplinary project showing that variation in the immune mechanisms reducing bacterial growth early after infection can explain the drastic variation in infection consequences.