Reconciling Pasteur and Darwin to control infectious diseases

Abstract

The continual emergence of new pathogens and the increased spread of antibiotic resistance in bacterial populations remind us that microbes are living entities that evolve at rates that impact public health interventions. Following the historical thread of the works of Pasteur and Darwin shows how reconciling clinical microbiology, ecology, and evolution can be instrumental to understanding pathology, developing new therapies, and prolonging the efficiency of existing ones.

Fig 1. Charles Darwin the naturalist and Louis Pasteur the microbiologist.

Charles Darwin's painting is from George Richmond in the late 1830s after his return from his voyage on HMS Beagle, and the painting of Louis Pasteur in his laboratory is from Albert Edelfelt in 1885 (Museé d'Orsay, Paris, France).

Fig 2. Combining the epidemiology and evolution of infectious diseases.

(A) Evolutionary rescue of a parasite population via mutation, (B) representation of the SI epidemiological model, and (C) virulence evolution in response to different types of interventions. In panel A, the resident strain (in black) cannot generate a large outbreak (its R₀ < 1), but it can still persist long enough for a mutation event to occur that can lead to a well-adapted mutant (in red) [26]. In panel C, the predictions are obtained using the Price equation formalism and the assumptions from Fig 2 in [30]. The colour of the curves corresponds to the arrows in panel B (black is the untreated case). Even in absence of treatment, the virulence evolves in the short term because its initial value is far from its optimal value. The virulence-blocking treatment (in yellow) leads to the highest increase virulence, whereas the treatment-blocking (in green) first favours less virulent strains. Increasing host recovery rate (in grey) also increases virulence. SI, Susceptible-Infected.

Fig 3. How high drug doses can lead to selection of preexisting drug-resistant mutants via 'competitive release'.

Charts show the within-host growth rate of drug-susceptible (in cyan) and -resistant (in red) bacteria populations at three time points using a high (top) or a low (bottom) drug dose. Population sizes and the fraction of resistant bacteria are shown between the bars. Note that depending on the fitness landscape, there might not always exist a dose that prevents the spread of both bacterial populations (for details, see [68]). R, Resistant; S, Susceptible.