Evolutionary consequences of feedbacks between within-host competition and disease control

Pathogen evasion of social immunity

Treating sick group members is a hallmark of collective disease defence in vertebrates and invertebrates alike. Despite substantial effects on pathogen fitness and epidemiology, it is still largely unknown how pathogens react to the selection pressure imposed by care intervention. Using social insects and pathogenic fungi, we here performed a serial passage experiment in the presence or absence of colony members, which provide social immunity by grooming off infectious spores from exposed individuals. We found specific effects on pathogen diversity, virulence and transmission. Under selection of social immunity, pathogens invested into higher spore production, but spores were less virulent. Notably, they also elicited a lower grooming response in colony members, compared with spores from the individual host selection lines. Chemical spore analysis suggested that the spores from social selection lines escaped the caregivers' detection by containing lower levels of ergosterol, a key fungal membrane component. Experimental application of chemically pure ergosterol indeed induced sanitary grooming, supporting its role as a microbe-associated cue triggering host social immunity against fungal pathogens. By reducing this detection cue, pathogens were able to evade the otherwise very effective collective disease defences of their social hosts.

Modeling transmission of pathogens in healthcare settings

PURPOSE OF REVIEW

Mathematical, statistical, and computational models provide insight into the transmission mechanisms and optimal control of healthcare-associated infections. To contextualize recent findings, we offer a summative review of recent literature focused on modeling transmission of pathogens in healthcare settings.

RECENT FINDINGS

The COVID-19 pandemic has led to a dramatic shift in the modeling landscape as the healthcare community has raced to characterize the transmission dynamics of SARS-CoV-2 and develop effective interventions. Inequities in COVID-19 outcomes have inspired new efforts to quantify how structural bias impacts both health outcomes and model parameterization. Meanwhile, developments in the modeling of methicillin-resistant Staphylococcus aureus, Clostridioides difficile, and other nosocomial infections continue to advance. Machine learning continues to be applied in novel ways, and genomic data is being increasingly incorporated into modeling efforts.

SUMMARY

As the type and amount of data continues to grow, mathematical, statistical, and computational modeling will play an increasing role in healthcare epidemiology. Gaps remain in producing models that are generalizable to a variety of time periods, geographic locations, and populations. However, with effective communication of findings and interdisciplinary collaboration, opportunities for implementing models for clinical decision-making and public health decision-making are bound to increase.

Host Specialisation, Immune Cross-Reaction and the Composition of Communities of Co-circulating Borrelia Strains

We use mathematical modelling to examine how microbial strain communities are structured by the host specialisation traits and antigenic relationships of their members. The model is quite general and broadly applicable, but we focus on Borrelia burgdorferi, the Lyme disease bacterium, transmitted by ticks to mice and birds. In this system, host specialisation driven by the evasion of innate immunity has been linked to multiple niche polymorphism, while antigenic differentiation driven by the evasion of adaptive immunity has been linked to negative frequency dependence. Our model is composed of two host species, one vector, and multiple co-circulating pathogen strains that vary in their host specificity and their antigenic distances from one another. We explore the conditions required to maintain pathogen diversity. We show that the combination of host specificity and antigenic differentiation creates an intricate niche structure. Unequivocal rules that relate the stability of a strain community directly to the trait composition of its members are elusive. However, broad patterns are evident. When antigenic differentiation is weak, stable communities are typically composed entirely of generalists that can exploit either host species equally well. As antigenic differentiation increases, more diverse stable communities emerge, typically around trait compositions of generalists, generalists and very similar specialists, and specialists roughly balanced between the two host species.

Locally adapted gut microbiomes mediate host stress tolerance

While evidence for the role of the microbiome in shaping host stress tolerance is becoming well-established, to what extent this depends on the interaction between the host and its local microbiome is less clear. Therefore, we investigated whether locally adapted gut microbiomes affect host stress tolerance. In the water flea Daphnia magna, we studied if the host performs better when receiving a microbiome from their source region than from another region when facing a stressful condition, more in particular exposure to the toxic cyanobacteria Microcystis aeruginosa. Therefore, a reciprocal transplant experiment was performed in which recipient, germ-free D. magna, isolated from different ponds, received a donor microbiome from sympatric or allopatric D. magna that were pre-exposed to toxic cyanobacteria or not. We tested for effects on host life history traits and gut microbiome composition. Our data indicate that Daphnia interact with particular microbial strains mediating local adaptation in host stress tolerance. Most recipient D. magna individuals performed better when inoculated with sympatric than with allopatric microbiomes. This effect was most pronounced when the donors were pre-exposed to the toxic cyanobacteria, but this effect was also pond and genotype dependent. We discuss how this host fitness benefit is associated with microbiome diversity patterns.

Facilitative priority effects drive parasite assembly under coinfection

Host individuals are often coinfected with diverse parasite assemblages, resulting in complex interactions among parasites within hosts. Within hosts, priority effects occur when the infection sequence alters the outcome of interactions among parasites. Yet, the role of host immunity in this process remains poorly understood. We hypothesized that the host response to the first infection could generate priority effects among parasites, altering the assembly of later-arriving strains during epidemics. We tested this by infecting sentinel host genotypes of Plantago lanceolata with strains of the fungal parasite Podosphaera plantaginis and measuring susceptibility to subsequent infection during experimental and natural epidemics. In these experiments, prior infection by one strain often increased susceptibility to other strains, and these facilitative priority effects altered the structure of parasite assemblages, but this effect depended on host genotype, host population and parasite genotype. Thus, host genotype, spatial structure and priority effects among strains all independently altered parasite assembly. Using a fine-scale survey and sampling of infections on wild hosts in several populations, we then identified a signal of facilitative priority effects, which altered parasite assembly during natural epidemics. Together, these results provide evidence that within-host priority effects of early-arriving strains can drive parasite assembly, with implications for how strain diversity is spatially and temporally distributed during epidemics.