Through complex interspecies interactions, microbial processes drive nutrient cycling and biogeochemistry. However, we still struggle to predict specifically which organisms, communities and biotic and abiotic processes are determining ecosystem function and how environmental changes will alter their roles and stability. While the tools to create such a predictive microbial ecology capability exist, cross-disciplinary integration of high-resolution field measurements, detailed laboratory studies and computation is essential. In this perspective, we emphasize the importance of pursuing a multiscale, systems approach to iteratively link ecological processes measured in the field to testable hypotheses that drive high-throughput laboratory experimentation. Mechanistic understanding of microbial processes gained in controlled lab systems will lead to the development of theory that can be tested back in the field. Using N₂ O production as an example, we review the current status of field and laboratory research and layout a plausible path to the kind of integration that is needed to enable prediction of how N-cycling microbial communities will respond to environmental changes. We advocate for the development of realistic and predictive gene regulatory network models for environmental responses that extend from single-cell resolution to ecosystems, which is essential to understand how microbial communities involved in N₂ O production and consumption will respond to future environmental conditions.

Microbial populations can withstand, overcome and persist in the face of environmental fluctuation. Previously, we demonstrated how conditional gene regulation in a fluctuating environment drives dilution of condition-specific transcripts, causing a population of Desulfovibrio vulgaris Hildenborough (DvH) to collapse after repeatedly transitioning from sulfate respiration to syntrophic conditions with the methanogen Methanococcus maripaludis. Failure of the DvH to successfully transition contributed to the collapse of this model community. We investigated the mechanistic basis for loss of robustness by examining whether conditional gene regulation altered heterogeneity in gene expression across individual DvH cells. We discovered that robustness of a microbial population across environmental transitions was attributable to the retention of cells in two states that exhibited different condition-specific gene expression patterns. In our experiments, a population with disrupted conditional regulation successfully alternated between cell states. Meanwhile, a population with intact conditional regulation successfully switched between cell states initially, but collapsed after repeated transitions, possibly due to the high energy requirements of regulation. These results demonstrate that the survival of this entire model microbial community is dependent on the regulatory system's influence on the distribution of distinct cell states among individual cells within a clonal population.

Early evolution of mutualism is characterized by big and predictable adaptive changes, including the specialization of interacting partners, such as through deleterious mutations in genes not required for metabolic cross-feeding. We sought to investigate whether these early mutations improve cooperativity by manifesting in synergistic epistasis between genomes of the mutually interacting species. Specifically, we have characterized evolutionary trajectories of syntrophic interactions of Desulfovibrio vulgaris (Dv) with Methanococcus maripaludis (Mm) by longitudinally monitoring mutations accumulated over 1000 generations of nine independently evolved communities with analysis of the genotypic structure of one community down to the single-cell level. We discovered extensive parallelism across communities despite considerable variance in their evolutionary trajectories and the perseverance within many evolution lines of a rare lineage of Dv that retained sulfate-respiration (SR+) capability, which is not required for metabolic cross-feeding. An in-depth investigation revealed that synergistic epistasis across pairings of Dv and Mm genotypes had enhanced cooperativity within SR- and SR+ assemblages, enabling their coexistence within the same community. Thus, our findings demonstrate that cooperativity of a mutualism can improve through synergistic epistasis between genomes of the interacting species, enabling the coexistence of mutualistic assemblages of generalists and their specialized variants.