Mechanistic determinants of bacterial growth, death, and spread within mammalian hosts cannot be fully resolved studying a single bacterial population. They are also currently poorly understood. Here, we report on the application of sophisticated experimental approaches to map spatiotemporal population dynamics of bacteria during an infection. We analyzed heterogeneous traits of simultaneous infections with tagged Salmonella enterica populations (wild-type isogenic tagged strains [WITS]) in wild-type and gene-targeted mice. WITS are phenotypically identical but can be distinguished and enumerated by quantitative PCR, making it possible, using probabilistic models, to estimate bacterial death rate based on the disappearance of strains through time. This multidisciplinary approach allowed us to establish the timing, relative occurrence, and immune control of key infection parameters in a true host–pathogen combination. Our analyses support a model in which shortly after infection, concomitant death and rapid bacterial replication lead to the establishment of independent bacterial subpopulations in different organs, a process controlled by host antimicrobial mechanisms. Later, decreased microbial mortality leads to an exponential increase in the number of bacteria that spread locally, with subsequent mixing of bacteria between organs via bacteraemia and further stochastic selection. This approach provides us with an unprecedented outlook on the pathogenesis of S. enterica infections, illustrating the complex spatial and stochastic effects that drive an infectious disease. The application of the novel method that we present in appropriate and diverse host–pathogen combinations, together with modelling of the data that result, will facilitate a comprehensive view of the spatial and stochastic nature of within-host dynamics.

Recent experiments on plant defenses against pathogens or herbivores have shown various patterns of the association between resistance, which reduces the probability of being infected or attacked, and tolerance, which reduces the loss of fitness caused by the infection or attack. Our study describes the simultaneous evolution of these two strategies of defense in a population of hosts submitted to a pathogen. We extended previous approaches by assuming that the two traits are independent (e.g., determined by two unlinked genes), by modeling different shapes of the costs of defenses, and by taking into account the demographic and epidemiological dynamics of the system. We provide novel predictions on the variability and the evolution of defenses. First, resistance and tolerance do not necessarily exclude each other; second, they should respond in different ways to changes in parameters that affect the epidemiology or the relative costs and benefits of defenses; and third, when comparing investments in defenses among different environments, the apparent associations among resistance, tolerance, and fecundity in the absence of parasites can lead to the false conclusion that only one defense trait is costly. The latter result emphasizes the problems of estimating trade-offs and costs among natural populations without knowledge of the underlying mechanisms.

Progress in combatting zoonoses that emerge from wildlife is often constrained by limited knowledge of the biology of pathogens within reservoir hosts. We focus on the host–pathogen dynamics of four emerging viruses associated with bats: Hendra, Nipah, Ebola, and Marburg viruses. Spillover of bat infections to humans and domestic animals often coincides with pulses of viral excretion within bat populations, but the mechanisms driving such pulses are unclear. Three hypotheses dominate current research on these emerging bat infections. First, pulses of viral excretion could reflect seasonal epidemic cycles driven by natural variations in population densities and contact rates among hosts. If lifelong immunity follows recovery, viruses may disappear locally but persist globally through migration; in either case, new outbreaks occur once births replenish the susceptible pool. Second, epidemic cycles could be the result of waning immunity within bats, allowing local circulation of viruses through oscillating herd immunity. Third, pulses could be generated by episodic shedding from persistently infected bats through a combination of physiological and ecological factors. The three scenarios can yield similar patterns in epidemiological surveys, but strategies to predict or manage spillover risk resulting from each scenario will be different. We outline an agenda for research on viruses emerging from bats that would allow for differentiation among the scenarios and inform development of evidence-based interventions to limit threats to human and animal health. These concepts and methods are applicable to a wide range of pathogens that affect humans, domestic animals, and wildlife.

Most models concerning the evolution of a parasite's virulence and its host's resistance assume that each component of the relationship (transmission, virulence, recovery, etc.) is controlled by either the host or the parasite but not by both. We present a model that describes the coevolution of host and parasite, assuming that the rate of transmission or the virulence depends on both genotypes. The evolution of these traits is constrained by trade-offs that account for costs of defense and attack strategies, in line with previous studies on the separate evolution of the host and the parasite. Considering shared control by the host and the parasite in determining the traits of the relationship leads to several novel predictions. First, the host should evolve maximal investment in defense against parasites with an intermediate replication rate. Second, the evolution of the parasite strongly depends on the way the host's defense is described. Third, the coevolutionary process may lead to decreasing the parasite's virulence as a response to a rise in the host's background mortality, contrary to classical predictions.