Within-Host Priority Effects Systematically Alter Pathogen Coexistence

Clay, P. A.; Dhir, Kailash L; Rudolf, Volker H. W.; Duffy, Meghan A.

doi:10.1086/701126

Cited by 53 publications

(94 citation statements)

References 59 publications

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“…For instance, in the absence of priority effects (scenario I and IV), interference between two parasites within hosts is predicted to lead to a negative prevalence relationship at the host population‐scale, after controlling for other factors. With priority effects, however, parasites that always decrease each other's fitness within hosts may still have a partially positive relationship at the host population‐scale if parasites gain a fitness advantage from secondary arrival in coinfected hosts (scenario VI), a scenario observed in coinfected frogs, Daphnia , and moths (Jackson et al , Lohr et al 2010, Hoverman et al , Sandoval‐Aguilar et al ). Ultimately, our results suggest that coinfection models may benefit from incorporating priority effect data.…”

Section: Discussionmentioning

confidence: 99%

“…Our study adds to a growing body of evidence that it is difficult to infer within‐host interactions from population‐level observations of parasite prevalence (Fenton et al 2010). Past studies have used correlations between parasite prevalence data across time or space to infer within‐host parasite interactions (Behnke et al 2005, Keeling and Rohani , Shrestha et al ). For instance, relationships between the prevalence of the influenza virus and Streptococcus pneumoniae over time have been used to infer the within‐host interactions between these two pathogens (Shrestha et al ).…”

Section: Discussionmentioning

confidence: 99%

“…Past studies have used correlations between parasite prevalence data across time or space to infer within‐host parasite interactions (Behnke et al 2005, Keeling and Rohani , Shrestha et al ). For instance, relationships between the prevalence of the influenza virus and Streptococcus pneumoniae over time have been used to infer the within‐host interactions between these two pathogens (Shrestha et al ). When paired with mechanistic models, these studies can give valuable insights into the likelihood that pathogens are facilitating or repressing one another.…”

Section: Discussionmentioning

confidence: 99%

“…By specifying the observed fitness outcomes of within‐host interactions rather than within‐host interactions themselves, our results are more likely to apply broadly to systems with different underlying mechanisms. We set the mortality rate of coinfected hosts to be the same as in singly infected hosts because whether coinfections decrease, increase, or do not change host mortality is system specific (Alizon et al ). Further, parasite fitness in our model is a function of propagule production rate ( β i ( j ) ) and parasite induced mortality ( m ).…”

Section: Methodsmentioning

confidence: 99%

“…Consequently, priority effects may change the relationship between the prevalence of coinfecting parasites, changing host population‐scale infection patterns. If within‐host priority effects do change host population‐scale infection patterns, then we may need to adjust how we infer within‐host interactions from prevalence data in coinfected systems (as in Behnke et al 2005, Shrestha et al ), and how we predict prevalence dynamics in coinfected systems from within‐host interactions (as in Abu‐Raddad et al , Ezenwa and Jolles ).…”

Section: Introductionmentioning

confidence: 99%

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Priority effects within coinfected hosts can drive unexpected population‐scale patterns of parasite prevalence

Clay

Cortez

Duffy

et al. 2018

Oikos

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Organisms are frequently coinfected by multiple parasite strains and species, and interactions between parasites within hosts are known to influence parasite prevalence and diversity, as well as epidemic timing. Importantly, interactions between coinfecting parasites can be affected by the order in which they infect hosts (i.e. within‐host priority effects). In this study, we use a single‐host, two‐pathogen, SI model with environmental transmission to explore how within‐host priority effects scale up to alter host population‐scale infection patterns. Specifically, we ask how parasite prevalence changes in the presence of different types of priority effects. We consider two scenarios without priority effects and four scenarios with priority effects where there is either an advantage or a disadvantage to being the first to infect in a coinfected host. Models without priority effects always predict negative relationships between the prevalences of both parasites. In contrast, models with priority effects can yield unimodal prevalence relationships where the prevalence of a focal parasite is minimized or maximized at intermediate prevalences of a coinfecting parasite. The mechanism behind this pattern is that as the prevalence of the coinfecting parasite increases, most infections of the focal parasite change from occurring as solo infections, to first arrival coinfections, to second arrival coinfections. The corresponding changes in parasite fitness as the focal parasite moves from one infection class to another then map to changes in focal parasite prevalence. Further, we found that even when parasites interact negatively within a host, they still can have positive prevalence relationships at the population scale. These results suggest that within‐host priority effects can change host population‐scale infection patterns in systematic (and initially counterintuitive) ways, and that taking them into account may improve disease forecasting in coinfected populations.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Priority effects within coinfected hosts can drive unexpected population‐scale patterns of parasite prevalence

Clay

Cortez

Duffy

et al. 2018

Oikos

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Coinfecting parasites can modify fluctuating selection dynamics in host–parasite coevolution

Seppälä

Lively

Jokela

2020

Ecology and Evolution

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Genetically specific interactions between hosts and parasites can lead to coevolutionary fluctuations in their genotype frequencies over time. Such fluctuating selection dynamics are, however, expected to occur only under specific circumstances (e.g., high fitness costs of infection to the hosts). The outcomes of host–parasite interactions are typically affected by environmental/ecological factors, which could modify coevolutionary dynamics. For instance, individual hosts are often infected with more than one parasite species and interactions between them can alter host and parasite performance. We examined the potential effects of coinfections by genetically specific (i.e., coevolving) and nonspecific (i.e., generalist) parasite species on fluctuating selection dynamics using numerical simulations. We modeled coevolution (a) when hosts are exposed to a single parasite species that must genetically match the host to infect, (b) when hosts are also exposed to a generalist parasite that increases fitness costs to the hosts, and (c) when coinfecting parasites compete for the shared host resources. Our results show that coinfections can enhance fluctuating selection dynamics when they increase fitness costs to the hosts. Under resource competition, coinfections can either enhance or suppress fluctuating selection dynamics, depending on the characteristics (i.e., fecundity, fitness costs induced to the hosts) of the interacting parasites.

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Transgenerational plasticity in a zooplankton in response to elevated temperature and parasitism

Sun

Dziuba

Jaye

et al. 2023

Ecology and Evolution

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Organisms are increasingly facing multiple stressors, which can simultaneously interact to cause unpredictable impacts compared with a single stressor alone. Recent evidence suggests that phenotypic plasticity can allow for rapid responses to altered environments, including biotic and abiotic stressors, both within a generation and across generations (transgenerational plasticity). Parents can potentially “prime” their offspring to better cope with similar stressors or, alternatively, might produce offspring that are less fit because of energetic constraints. At present, it remains unclear exactly how biotic and abiotic stressors jointly mediate the responses of transgenerational plasticity and whether this plasticity is adaptive. Here, we test the effects of biotic and abiotic environmental changes on within‐ and transgenerational plasticity using a Daphnia – Metschnikowia zooplankton‐fungal parasite system. By exposing parents and their offspring consecutively to the single and combined effects of elevated temperature and parasite infection, we showed that transgenerational plasticity induced by temperature and parasite stress influenced host fecundity and lifespan; offsprings of mothers who were exposed to one of the stressors were better able to tolerate elevated temperature, compared with the offspring of mothers who were exposed to neither or both stressors. Yet, the negative effects caused by parasite infection were much stronger, and this greater reduction in host fitness was not mitigated by transgenerational plasticity. We also showed that elevated temperature led to a lower average immune response, and that the relationship between immune response and lifetime fecundity reversed under elevated temperature: the daughters of exposed mothers showed decreased fecundity with increased hemocyte production at ambient temperature but the opposite relationship at elevated temperature. Together, our results highlight the need to address questions at the interface of multiple stressors and transgenerational plasticity and the importance of considering multiple fitness‐associated traits when evaluating the adaptive value of transgenerational plasticity under changing environments.

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Within-Host Priority Effects Systematically Alter Pathogen Coexistence

Cited by 53 publications

References 59 publications

Priority effects within coinfected hosts can drive unexpected population‐scale patterns of parasite prevalence

Priority effects within coinfected hosts can drive unexpected population‐scale patterns of parasite prevalence

Coinfecting parasites can modify fluctuating selection dynamics in host–parasite coevolution

Transgenerational plasticity in a zooplankton in response to elevated temperature and parasitism

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