Partner dependency alters patterns of coevolutionary selection in mutualisms

Coevolution is a ubiquitous driver of diversification in both mutualistic and antagonistic interactions between species. In mutualisms, coevolution can result in trait complementarity between partners that facilitates their persistence. Despite its importance, most of what we know about coevolution in mutualism comes from obligate interactions, whereas we know comparatively little about facultative interactions, arguably the most common type of mutualism. To evaluate coevolutionary dynamics in facultative mutualism and test how it compares with obligate mutualisms, we used a synthetic yeast mutualism where the partners exchange essential nutrient resources. We manipulated mutualism dependency by controlling the availability of mutualistic resources in the environment and measured coevolution via time-shift assays and tracking the evolution of mutualistic traits over time. In addition, we genotyped the evolved and ancestral mutualists to test for differences in the strength of coevolutionary selection between facultative and obligate mutualisms. We found evidence of coevolution in both facultative and obligate mutualisms, but coevolution was weaker and slower in facultative mutualisms. We also found evidence for evolution of trait complementarity in obligate mutualisms but not in facultative mutualisms. Furthermore, obligate mutualists had more SNPs under positive selection than facultative mutualists. Together, these results provide strong evidence that mutualism dependency impacts both the strength of coevolution and the rate of trait evolution.

A new flavor of synthetic yeast communities sees the light

No organism is an island: organisms of varying taxonomic complexity, including genetic variants of a single species, can coexist in particular niches, cooperating for survival while simultaneously competing for environmental resources. In recent years, synthetic biology strategies have witnessed a surge of efforts focused on creating artificial microbial communities to tackle pressing questions about the complexity of natural systems and the interactions that underpin them. These engineered ecosystems depend on the number and nature of their members, allowing complex cell communication designs to recreate and create diverse interactions of interest. Due to its experimental simplicity, the budding yeast Saccharomyces cerevisiae has been harnessed to establish a mixture of varied cell populations with the potential to explore synthetic ecology, metabolic bioprocessing, biosensing, and pattern formation. Indeed, engineered yeast communities enable advanced molecule detection dynamics and logic operations. Here, we present a concise overview of the state-of-the-art, highlighting examples that exploit optogenetics to manipulate, through light stimulation, key yeast phenotypes at the community level, with unprecedented spatial and temporal regulation. Hence, we envision a bright future where the application of optogenetic approaches in synthetic communities (optoecology) illuminates the intricate dynamics of complex ecosystems and drives innovations in metabolic engineering strategies.

The Identification of Patterns in the Relation Between Biodiversity and Mutualistic Ecosystem Function Based on Network Resilience

Identifying the relation between biodiversity and mutualistic ecosystem function has been a longstanding concern. In this study, we present an interpretive model to evaluate the impact of each species on mutualistic ecosystem functions. By analyzing network resilience, we derive the average abundance and tipping point of the ecosystem to represent ecosystem functions. Based on the order of species collapse, each species is classified according to the F-core. The model quantitatively evaluates the influence of species on mutualistic ecosystem functions in scenarios where species are removed from ecosystems. We propose a criterion for identifying redundant species: a species is considered redundant if its removal negatively impacts average abundance without affecting the tipping point. To validate the model, we introduce twenty-four mutualistic ecosystems. Our numerical simulations and analytical analyses reveal two distinct patterns: one indicating the presence of redundancy and the other suggesting that each species is essential. Additionally, in mutualistic ecosystems characterized by redundancy, specialist species are more likely to be identified as redundant.

Trait and plasticity evolution under competition and mutualism in evolving pairwise yeast communities

Although we have a good understanding of how phenotypic plasticity evolves in response to abiotic environments, we know comparatively less about responses to biotic interactions. We experimentally tested how competition and mutualism affected trait and plasticity evolution of pairwise communities of genetically modified brewer's yeast. We quantified evolutionary changes in growth rate, resource use efficiency (RUE), and their plasticity in strains evolving alone, with a competitor, and with a mutualist. Compared to their ancestors, strains evolving alone had lower RUE and RUE plasticity. There was also an evolutionary tradeoff between changes in growth rate and RUE in strains evolving alone, suggesting selection for increased growth rate at the cost of efficiency. Strains evolving with a competitive partner had higher growth rates, slightly lower RUE, and a stronger tradeoff between growth rate and efficiency. In contrast, mutualism had opposite effects on trait evolution. Strains evolving with a mutualist had slightly lower growth rates, higher RUE, and a weak evolutionary tradeoff between growth rate and RUE. Despite their different effects on trait evolution, competition and mutualism had little effect on plasticity evolution for either trait, suggesting that abiotic factors could be more important than biotic factors in generating selection for plasticity.

Dispersal promotes stability and persistence of exploited yeast mutualisms

Multispecies mutualistic interactions are ubiquitous and essential in nature, yet they face several threats, many of which have been exacerbated in the Anthropocene era. Understanding the factors that drive the stability and persistence of mutualism has become increasingly important in light of global change. Although dispersal is widely recognized as a crucial spatially explicit process in maintaining biodiversity and community structure, knowledge about how the dispersal of mutualists contributes to the persistence of mutualistic systems remains limited. In this study, we used a synthetic mutualism formed by genetically modified budding yeast to investigate the effect of dispersal on the persistence and stability of mutualisms under exploitation. We found that dispersal increased the persistence of exploited mutualisms by 80% compared to the isolated systems. Furthermore, our results showed that dispersal increased local diversity, decreased beta diversity among local communities, and stabilized community structure at the regional scale. Our results indicate that dispersal can allow mutualisms to persist in meta-communities by reintroducing species that are locally competitively excluded by exploiters. With limited dispersal, e.g. due to increased fragmentation of meta-communities, mutualisms might be more prone to breakdown. Taken together, our results highlight the critical role of dispersal in facilitating the persistence of mutualism.

Symbiotic Electromagnetic Shadow for Regional Invisibility and Camouflage

Low detectability and camouflage skills in the electromagnetic wave and light frequency range provide survival advantages for natural creatures and are essential for understanding the operational principles of the biosphere. Taking inspiration from natural mutualistic symbiosis, this paper proposes a symbiotic electromagnetic shadow camouflage mechanism based on a superdispersive surface, aiming to investigate its impact on the observability of specific objects. The design and experimental results indicate that the symbiotic shadow dihedral can significantly reduce overall scattering quantity, which reaches at least 10 dB shrink in the 12-18 GHz frequency range compared to the contrast object. Unlike known camouflage methods, the electromagnetic shadow technology shrinks the overall scattering without any coating and shield metal target while probably offering extensive functional design freedom for the concealed object, creature, or equipment. This also provides a hint to explore symbiosis-related camouflage phenomena in nature.

Quantifying microbial guilds

The ecological role of microorganisms is of utmost importance due to their multiple interactions with the environment. However, assessing the contribution of individual taxonomic groups has proven difficult despite the availability of high throughput data, hindering our understanding of such complex systems. Here, we propose a quantitative definition of guild that is readily applicable to metagenomic data. Our framework focuses on the functional character of protein sequences, as well as their diversifying nature. First, we discriminate functional sequences from the whole sequence space corresponding to a gene annotation to then quantify their contribution to the guild composition across environments. In addition, we identify and distinguish functional implementations, which are sequence spaces that have different ways of carrying out the function. In contrast, we found that orthology delineation did not consistently align with ecologically (or functionally) distinct implementations of the function. We demonstrate the value of our approach with two case studies: the ammonia oxidation and polyamine uptake guilds from the Malaspina circumnavigation cruise, revealing novel ecological dynamics of the latter in marine ecosystems. Thus, the quantification of guilds helps us to assess the functional role of different taxonomic groups with profound implications on the study of microbial communities.

Microbial experimental evolution in a massively multiplexed and high-throughput era

Experimental evolution with microbial model systems has transformed our understanding of the basic rules underlying ecology and evolution. Experiments leveraging evolution as a central feature put evolutionary theories to the test, and modern sequencing and engineering tools then characterized the molecular basis of adaptation. As theory and experimentations refined our understanding of evolution, a need to increase throughput and experimental complexity has emerged. Here, we summarize recent technologies that have made high-throughput experiments practical and highlight studies that have capitalized on these tools, defining an exciting new era in microbial experimental evolution. Multiple research directions previously limited by experimental scale are now accessible for study and we believe applying evolutionary lessons from in vitro studies onto these applied settings has the potential for major innovations and discoveries across ecology and medicine.

Competition dynamics in long-term propagations of Schizosaccharomyces pombe strain communities

Experimental evolution studies with microorganisms such as bacteria and yeast have been an increasingly important and powerful tool to draw long-term inferences of how microbes interact. However, while several strains of the same species often exist in natural environments, many ecology and evolution studies in microbes are typically performed with isogenic populations of bacteria or yeast. In the present study, we firstly perform a genotypic and phenotypic characterization of two laboratory and eight natural strains of the yeast Schizosaccharomyces pombe. We then propagated, in a rich resource environment, yeast communities of 2, 3, 4, and 5 strains for hundreds of generations and asked which fitness-related phenotypes-maximum growth rate or relative competitive fitness-would better predict the outcome of a focal strain during the propagations. While the strain's growth rates would wrongly predict long-term coexistence, pairwise competitive fitness with a focal strain qualitatively predicted the success or extinction of the focal strain by a simple multigenotype population genetics model, given the initial community composition. Interestingly, we have also measured the competitive fitness of the ancestral and evolved communities by the end of the experiment (≈370 generations) and observed frequent maladaptation to the abiotic environment in communities with more than three members. Overall, our results aid establishing pairwise competitive fitness as good qualitative measurement of long-term community composition but also reveal a complex adaptive scenario when trying to predict the evolutionary outcome of those communities.

The variable effects of global change on insect mutualisms

Insect mutualisms are essential for reproduction of many plants, protection of plants and other insects, and provisioning of nutrients for insects. Disruption of these mutualisms by global change can have important implications for ecosystem processes. Here, we assess the general effects of global change on insect mutualisms, including the possible impacts on mutualistic networks. We find that the effects of global change on mutualisms are extremely variable, making broad patterns difficult to detect. We require studies focusing on changes in cost-benefit ratios, effects of partner dependency, and degree of specialization to further understand how global change will influence insect mutualism dynamics. We propose that rapid coevolution is one avenue by which mutualists can ameliorate the effects of global change.

Coevolved mutualists experience fluctuating costs and benefits over time

Understanding how mutualisms persist over time requires investigations of how mutualist species coevolve and adapt to the interaction. In particular, the key factors in the evolution of mutualisms are the costs and benefits mutualists experience during the interaction. Here, we used a yeast nutritional mutualism to test how mutualists coevolve and adapt in an obligate mutualism. We allowed two yeast mutualists to evolve together for 15 weeks (about 150 generations), and then we tested if the mutualists had coevolved using time-shift assays. We also examined two mutualistic traits associated with the costs and benefits: resource use efficiency and commodity production. We found that the mutualists quickly coevolved. Furthermore, the changes in benefits and costs were nonlinear and varied with evolutionary changes occurring in the mutualist partner. One mutualist initially evolved to reduce mutualistic commodity production and increase efficiency in mutualistic resource use; however, this negatively affected its mutualist partner that evolved reduced commodity production and resource use efficiency. As a result, the former increased commodity production, resulting in an increase in benefits for its partner. The quick, nonlinear, and asynchronous evolution of yeast mutualists closely resembles antagonistic coevolutionary patterns, supporting the view that mutualisms should be considered as reciprocal exploitation.