Immune selection suppresses the emergence of drug resistance in malaria parasites but facilitates its spread

Abstract

Although drug resistance in Plasmodium falciparum typically evolves in regions of low transmission, resistance spreads readily following introduction to regions with a heavier disease burden. This suggests that the origin and the spread of resistance are governed by different processes, and that high transmission intensity specifically impedes the origin. Factors associated with high transmission, such as highly immune hosts and competition within genetically diverse infections, are associated with suppression of resistant lineages within hosts. However, interactions between these factors have rarely been investigated and the specific relationship between adaptive immunity and selection for resistance has not been explored. Here, we developed a multiscale, agent-based model of Plasmodium parasites, hosts, and vectors to examine how host and parasite dynamics shape the evolution of resistance in populations with different transmission intensities. We found that selection for antigenic novelty (“immune selection”) suppressed the evolution of resistance in high transmission settings. We show that high levels of population immunity increased the strength of immune selection relative to selection for resistance. As a result, immune selection delayed the evolution of resistance in high transmission populations by allowing novel, sensitive lineages to remain in circulation at the expense of the spread of a resistant lineage. In contrast, in low transmission settings, we observed that resistant strains were able to sweep to high population prevalence without interference. Additionally, we found that the relationship between immune selection and resistance changed when resistance was widespread. Once resistance was common enough to be found on many antigenic backgrounds, immune selection stably maintained resistant parasites in the population by allowing them to proliferate, even in untreated hosts, when resistance was linked to a novel epitope. Our results suggest that immune selection plays a role in the global pattern of resistance evolution.

Genomic epidemiological models describe pathogen evolution across fitness valleys

“…This allows us to better understand how pathogens acquire new fitness-conferring traits that require multiple, separate epistatic mutations, a process known as stochastic tunneling ( 39, 41 ). We confirm that competition between pathogens in settings with high disease prevalence can pose a significant barrier to evolution in certain adaptive landscapes, as suggested by others ( 37 ). We establish the potential of genomic epidemiological models to provide more complete descriptions of simulated evolution.…”

“…Although these may be adapted to use in epidemiology, this requires significant work and setup, especially when tailoring to different kinds of disease transmission and intervention. Further recent work has been done to explore evolving epidemiological models in a custom, disease-specific context ( 37 ). Nevertheless, there currently is no out-of-the-box solution for building flexible, easy-to-use simulations of disease spread with pathogens capable of evolving and influencing their epidemiology through natural selection.…”

“…We began by examining whether competition for transmission between pathogens in high transmission environments can inhibit stochastic tunneling. This hypothesis has been proposed as a partial explanation for why antimalarial resistance repeatedly emerges outside of the high-transmission environments in sub-Saharan Africa that contribute the bulk of global malaria cases and treatment ( 37, 48, 49 ).…”

“…However, immune selection plays a central role in pathogen evolution by shifting the fitness landscape over time. This has been proposed in the context of the evolution of malaria parasites ( 37 ) and is doubtless a crucial factor in the emergence of SARS-CoV-2 variants that evade acquired immune responses ( 62 ). Finally, we chose to explore idealized disease models rather than fit a specific disease both for generalizability and computational feasibility.…”

Xeno-monitoring of molecular drivers of artemisinin and partner drug resistance in P. falciparum populations in malaria vectors across Cameroon

“…This could account for the dominance of the 184F resistant allele present in P. falciparum infected mosquitoes and reveals that this allele is under transmission-driven positive selection. This suggests that mosquito immune selection may be shaping the local pattern of drug resistance evolution and spread once resistance is widespread ( Whitlock et al, 2021 ). This agrees with a previous study demonstrating that mosquitoes play a significant role in determining the frequency of drug resistant P. falciparum population in natural ( Mharakurwa, 2013 , Mharakurwa, 2011 , Temu, 2006 ) and experimental ( Berry, 2021 ) settings.…”