Competition for hosts modulates vast antigenic diversity to generate persistent strain structure in Plasmodium falciparum

Abstract

In their competition for hosts, parasites with antigens that are novel to the host immune system will be at a competitive advantage. The resulting frequency-dependent selection can structure parasite populations into strains of limited genetic overlap. For the causative agent of malaria, Plasmodium falciparum , the high recombination rates and associated vast diversity of its highly antigenic and multicopy var genes preclude such clear clustering in endemic regions. This undermines the definition of strains as specific, temporally persisting gene variant combinations. We use temporal multilayer networks to analyze the genetic similarity of parasites in both simulated data and in an extensively and longitudinally sampled population in Ghana. When viewed over time, populations are structured into modules (i.e., groups) of parasite genomes whose var gene combinations are more similar within than between the modules and whose persistence is much longer than that of the individual genomes that compose them. Comparison to neutral models that retain parasite population dynamics but lack competition reveals that the selection imposed by host immunity promotes the persistence of these modules. The modular structure is, in turn, associated with a slower acquisition of immunity by individual hosts. Modules thus represent dynamically generated niches in host immune space, which can be interpreted as strains. Negative frequency-dependent selection therefore shapes the organization of the var diversity into parasite genomes, leaving a persistence signature over ecological time scales. Multilayer networks extend the scope of phylodynamics analyses by allowing quantification of temporal genetic structure in organisms that generate variation via recombination or other non-bifurcating processes. A strain structure similar to the one described here should apply to other pathogens with large antigenic spaces that evolve via recombination. For malaria, the temporal modular structure should enable the formulation of tractable epidemiological models that account for parasite antigenic diversity and its influence on intervention outcomes.

The network structure and eco-evolutionary dynamics of CRISPR-induced immune diversification

“…Its emergence from immune selection was demonstrated here. It is consistent with existing strain theory developed mostly for human infections and pathogens with multilocus encoding of antigens, when evolution is considered explicitly [11,12,15,54]. Immune selection acts as a form negative frequency-dependent selection creating groups of pathogens with limiting overlap in antigenic space.…”

“…In contrast to strain theory [12,15], here the persistence of the modular structure in the infection network and the coexistence of a diverse community of viral strains is only transitory. The number of susceptible hosts available to all viruses declines very rapidly, so that no virus is able to infect all hosts.…”

“…In the absence of data on immunity of hosts, this pattern has been described as modules, or clusters, in networks that depict genetic similarity between the pathogens themselves [11,12]. This outcome is conceptually analogous to groups of species or microbes coexisting under frequency-dependent competition for resources [55].…”

“…Infection structure should critically depend however on the genetic basis of resistance of hosts to pathogens [10]. The emergence of network structure from immune selection has been shown in pathogens of humans such as Plasmodium falciparum [11,12]. In particular, strain theory developed for pathogens with multilocus encoding of antigens posits that negative frequency dependent selection, mediated by competition for hosts through cross-immunity, can structure pathogen populations into clusters of strains with limited overlap of antigenic repertoires [11][12][13][14][15].…”

Identifying flow modules in ecological networks using Infomap

“…Infomap minimises an objective function known as the 'map equation', which measures how much a modular partition of a network can compress a description of flows on the network (Rosvall and Bergstrom, 2008). Infomap has been thoroughly described mathematically and computationally (Rosvall and Bergstrom, 2008;Rosvall et al, 2010;Rosvall and Bergstrom, 2011;Rosvall et al, 2014) and is widely used in non-ecological disciplines, but only in a handful of papers in ecology (Pilosof et al, 2019;Bernardo-Madrid et al, 2019;Pilosof et al, 2020). Instead of comparing or benchmarking Infomap against other methods, which has already been done (Lancichinetti and Fortunato, 2009;Aldecoa and Marín, 2013), we explain how Infomap works on ecological networks and provide several hands-on examples using empirical data.…”