The importance of microbial communities (MCs) cannot be overstated. MCs underpin the biogeochemical cycles of the earth's soil, oceans and the atmosphere, and perform ecosystem functions that impact plants, animals and humans. Yet our ability to predict and manage the function of these highly complex, dynamically changing communities is limited. Building predictive models that link MC composition to function is a key emerging challenge in microbial ecology. Here, we argue that addressing this challenge requires close coordination of experimental data collection and method development with mathematical model building. We discuss specific examples where model–experiment integration has already resulted in important insights into MC function and structure. We also highlight key research questions that still demand better integration of experiments and models. We argue that such integration is needed to achieve significant progress in our understanding of MC dynamics and function, and we make specific practical suggestions as to how this could be achieved.

The health of the honeybee and, indirectly, global crop production are threatened by several biotic and abiotic factors, which play a poorly defined role in the induction of widespread colony losses. Recent descriptive studies suggest that colony losses are often related to the interaction between pathogens and other stress factors, including parasites. Through an integrated analysis of the population and molecular changes associated with the collapse of honeybee colonies infested by the parasitic mite Varroa destructor, we show that this parasite can de-stabilise the within-host dynamics of Deformed wing virus (DWV), transforming a cryptic and vertically transmitted virus into a rapidly replicating killer, which attains lethal levels late in the season. The de-stabilisation of DWV infection is associated with an immunosuppression syndrome, characterized by a strong down-regulation of the transcription factor NF-κB. The centrality of NF-κB in host responses to a range of environmental challenges suggests that this transcription factor can act as a common currency underlying colony collapse that may be triggered by different causes. Our results offer an integrated account for the multifactorial origin of honeybee losses and a new framework for assessing, and possibly mitigating, the impact of environmental challenges on honeybee health.

Antivirulence drugs are a new type of therapeutic drug that target virulence factors, potentially revitalising the drug-development pipeline with new targets. As antivirulence drugs disarm the pathogen, rather than kill or halt pathogen growth, it has been hypothesized that they will generate much weaker selection for resistance than traditional antibiotics. However, recent studies have shown that mechanisms of resistance to antivirulence drugs exist, seemingly damaging the 'evolution-proof' claim. In this Opinion article, we highlight a crucial distinction between whether resistance can emerge and whether it will spread to a high frequency under drug selection. We argue that selection for resistance can be reduced, or even reversed, using appropriate combinations of target and treatment environment, opening a path towards the development of evolutionarily robust novel therapeutics.