A major unresolved question in microbiome research is whether the complex taxonomic architectures observed in surveys of natural communities can be explained and predicted by fundamental, quantitative principles. Bridging theory and experiment is hampered by the multiplicity of ecological processes that simultaneously affect community assembly in natural ecosystems. We addressed this challenge by monitoring the assembly of hundreds of soil- and plant-derived microbiomes in well-controlled minimal synthetic media. Both the community-level function and the coarse-grained taxonomy of the resulting communities are highly predictable and governed by nutrient availability, despite substantial species variability. By generalizing classical ecological models to include widespread nonspecific cross-feeding, we show that these features are all emergent properties of the assembly of large microbial communities, explaining their ubiquity in natural microbiomes.

By consuming and producing environmental resources, organisms inevitably change their habitat. The consequences of such environmental modifications can be detrimental or beneficial not only to the focal organism but also to other organisms sharing the same environment. Social evolution theory has been very influential in studying how social interactions mediated by public goods or bads evolve by emphasising the role of spatial structure. The environmental dimensions driving these interactions, however, are typically abstracted away. Here we propose a new, environmentally-mediated taxonomy of social behaviours where organisms are categorised by their production or consumption of environmental factors that help or harm others in the environment. We discuss microbial examples of our classification and highlight the importance of environmental intermediates more generally.

Microbes perform many costly biological functions that benefit themselves, and may also benefit neighbouring cells. Losing the ability to perform such functions can be advantageous due to cost savings, but when they are essential for growth, organisms become dependent on ecological partners to compensate for those losses. When multiple functions may be lost, the ecological outcomes are potentially diverse, including independent organisms only; one-way dependency, where one partner performs all functions and others none; or mutual interdependency where partners perform complementary essential functions. What drives these different outcomes? We develop a model where organisms perform 'leaky' functions that provide both private and public benefits to explore the consequences of privatization level, costs and essentiality on influencing these outcomes. We show that mutual interdependency is favoured at intermediate levels of privatization for a broad range of conditions. One-way dependency, in contrast, is only favoured when privatization is low and loss-of-function benefits are accelerating. Our results suggest an interplay between privatization level and shape of benefits from loss in driving microbial dependencies. Given the ubiquity of microbial functions that are inevitably leaked and the ease of mutational inactivation, our findings may help to explain why microbial interdependencies are common in nature.

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Directed evolution has been used for decades to engineer biological systems from the top-down. Generally, it has been applied at or below the organismal level, by iteratively sampling the mutational landscape in a guided search for genetic variants of higher function. Above the organismal level, a small number of studies have attempted to artificially select microbial communities and ecosystems, with uneven and generally modest success. Our theoretical understanding of artificial ecosystem selection is still limited, particularly for large assemblages of asexual organisms, and we know little about designing efficient methods to direct their evolution. To address this issue, we have developed a flexible modeling framework that allows us to systematically probe any arbitrary selection strategy on any arbitrary set of communities and selected functions, in a wide range of ecological conditions. By artificially selecting hundreds of in-silico microbial metacommunities under identical conditions, we examine the fundamental limits of the two main breeding methods used so far, and prescribe modifications that significantly increase their power. We identify a range of directed evolution strategies that, particularly when applied in combination, are better suited for the top-down engineering of large, diverse, and stable microbial consortia. Our results emphasize that directed evolution allows an ecological structure-function landscape to be navigated in search for dynamically stable and ecologically and functionally resilient high-functioning communities.1 .