Metabolic efficiency reshapes the seminal relationship between pathogen growth rate and virulence.

A cornerstone of classical virulence evolution theories is the assumption that pathogen growth rate is positively correlated with virulence, the amount of damage pathogens inflict on their hosts. Such theories are key for incorporating evolutionary principles into sustainable disease management strategies. Yet, empirical evidence raises doubts over this central assumption underpinning classical theories, thus undermining their generality and predictive power. In this paper, we identify a key component missing from current theories which redefines the growth-virulence relationship in a way that is consistent with data. By modifying the activity of a single metabolic gene, we engineered strains of Magnaporthe oryzae with different nutrient acquisition and growth rates. We conducted in planta infection studies and uncovered an unexpected non-monotonic relationship between growth rate and virulence that is jointly shaped by how growth rate and metabolic efficiency interact. This novel mechanistic framework paves the way for a much-needed new suite of virulence evolution theories.

Would that it were so simple: Interactions between multiple traits undermine classical single-trait-based predictions of microbial community function and evolution.

Understanding how microbial traits affect the evolution and functioning of microbial communities is fundamental for improving the management of harmful microorganisms, while promoting those that are beneficial. Decades of evolutionary ecology research has focused on examining microbial cooperation, diversity, productivity and virulence but with one crucial limitation. The traits under consideration, such as public good production and resistance to antibiotics or predation, are often assumed to act in isolation. Yet, in reality, multiple traits frequently interact, which can lead to unexpected and undesired outcomes for the health of macroorganisms and ecosystem functioning. This is because many predictions generated in a single-trait context aimed at promoting diversity, reducing virulence or controlling antibiotic resistance can fail for systems where multiple traits interact. Here, we provide a much needed discussion and synthesis of the most recent research to reveal the widespread and diverse nature of multi-trait interactions and their consequences for predicting and controlling microbial community dynamics. Importantly, we argue that synthetic microbial communities and multi-trait mathematical models are powerful tools for managing the beneficial and detrimental impacts of microbial communities, such that past mistakes, like those made regarding the stewardship of antimicrobials, are not repeated.

Chronic bee paralysis as a serious emerging threat to honey bees.

Chronic bee paralysis is a well-defined viral disease of honey bees with a global distribution that until recently caused rare but severe symptomatology including colony loss. Anecdotal evidence indicates a recent increase in virus incidence in several countries, but no mention of concomitant disease. We use government honey bee health inspection records from England and Wales to test whether chronic bee paralysis is an emerging infectious disease and investigate the spatiotemporal patterns of disease. The number of chronic bee paralysis cases increased exponentially between 2007 and 2017, demonstrating chronic bee paralysis as an emergent disease. Disease is highly clustered spatially within most years, suggesting local spread, but not between years, suggesting disease burnt out with periodic reintroduction. Apiary and county level risk factors are confirmed to include scale of beekeeping operation and the history of honey bee imports. Our findings offer epidemiological insight into this damaging emerging disease.

Fipronil pesticide as a suspect in historical mass mortalities of honey bees.

Mass mortalities of honey bees occurred in France in the 1990s coincident with the introduction of two agricultural insecticides, imidacloprid and fipronil. Imidacloprid, a neonicotinoid, was widely blamed, but the differential potency of imidacloprid and fipronil has been unclear because of uncertainty over their capacity to bioaccumulate during sustained exposure to trace dietary residues and, thereby, cause time-reinforced toxicity (TRT). We experimentally quantified the toxicity of fipronil and imidacloprid to honey bees and incorporated the observed mortality rates into a demographic simulation of a honey bee colony in an environmentally realistic scenario. Additionally, we evaluated two bioassays from new international guidance for agrochemical regulation, which aim to detect TRT. Finally, we used analytical chemistry (GC-MS) to test for bioaccumulation of fipronil. We found in demographic simulations that only fipronil produced mass mortality in honey bees. In the bioassays, only fipronil caused TRT. GC-MS analysis revealed that virtually all of the fipronil ingested by a honey bee in a single meal was present 6 d later, which suggests that bioaccumulation is the basis of TRT in sustained dietary exposures. We therefore postulate that fipronil, not imidacloprid, caused the mass mortalities of honey bees in France during the 1990s because it is lethal to honey bees in even trace doses due to its capacity to bioaccumulate and generate TRT. Our results provide evidence that recently proposed laboratory bioassays can discriminate harmful bioaccumulative substances and, thereby, address evident shortcomings in a regulatory system that had formerly approved fipronil for agricultural use.