Cross-feeding interactions, in which bacterial cells exchange costly metabolites to the benefit of both interacting partners, are very common in the microbial world. However, it generally remains unclear what maintains this type of interaction in the presence of non-cooperating types. We investigate this problem using synthetic cross-feeding interactions: by simply deleting two metabolic genes from the genome of Escherichia coli, we generated genotypes that require amino acids to grow and release other amino acids into the environment. Surprisingly, in a vast majority of cases, cocultures of two cross-feeding strains showed an increased Darwinian fitness (that is, rate of growth) relative to prototrophic wild type cells—even in direct competition. This unexpected growth advantage was due to a division of metabolic labour: the fitness cost of overproducing amino acids was less than the benefit of not having to produce others when they were provided by their partner. Moreover, frequency-dependent selection maintained cross-feeding consortia and limited exploitation by non-cooperating competitors. Together, our synthetic study approach reveals ecological principles that can help explain the widespread occurrence of obligate metabolic cross-feeding interactions in nature.

Bacteria frequently exchange metabolites by diffusion through the extracellular environment, yet it remains generally unclear whether bacteria can also use cell–cell connections to directly exchange nutrients. Here we address this question by engineering cross-feeding interactions within and between Acinetobacter baylyi and Escherichia coli, in which two distant bacterial species reciprocally exchange essential amino acids. We establish that in a well-mixed environment E. coli, but likely not A. baylyi, can connect to other bacterial cells via membrane-derived nanotubes and use these to exchange cytoplasmic constituents. Intercellular connections are induced by auxotrophy-causing mutations and cease to establish when amino acids are externally supplied. Electron and fluorescence microscopy reveal a network of nanotubular structures that connects bacterial cells and enables an intercellular transfer of cytoplasmic materials. Together, our results demonstrate that bacteria can use nanotubes to exchange nutrients among connected cells and thus help to distribute metabolic functions within microbial communities.

Metabolic cross-feeding interactions are ubiquitous in natural microbial communities. However, it remains generally unclear whether the production and exchange of metabolites incurs fitness costs to the producing cells and if so, which ecological mechanisms can facilitate a cooperative exchange of metabolites among unrelated individuals. We hypothesized that positive assortment within structured environments can maintain mutualistic cross-feeding. To test this, we engineered Acinetobacter baylyi and Escherichia coli to reciprocally exchange essential amino acids. Interspecific coculture experiments confirmed that non-cooperating types were selectively favoured in spatially unstructured (liquid culture), yet disfavoured in spatially structured environments (agar plates). Both an individual-based model and experiments with engineered genotypes indicated that a segregation of cross-feeders and non-cooperating auxotrophs stabilized cooperative cross-feeding in spatially structured environments. Chemical imaging confirmed that auxotrophs were spatially excluded from cooperative benefits. Together, these results demonstrate that cooperative cross-feeding between different bacterial species is favoured in structured environments such as bacterial biofilms, suggesting this type of interactions might be common in natural bacterial communities.

Bacterial communities are taxonomically highly diverse, yet the mechanisms that maintain this diversity remain poorly understood. We hypothesized that an obligate and mutual exchange of metabolites, as is very common among bacterial cells, could stabilize different genotypes within microbial communities. To test this, we developed a cellular automaton to model interactions among six empirically characterized genotypes that differ in their ability and propensity to produce amino acids. By systematically varying intrinsic (i.e. benefit-to-cost ratio) and extrinsic parameters (i.e. metabolite diffusion level, environmental amino acid availability), we show that obligate cross-feeding of essential metabolites is selected for under a broad range of conditions. In spatially structured environments, positive assortment among cross-feeders resulted in the formation of cooperative clusters, which limited exploitation by non-producing auxotrophs, yet allowed them to persist at the clusters’ periphery. Strikingly, cross-feeding helped to maintain genotypic diversity within populations, while amino acid supplementation to the environment decoupled obligate interactions and favored auxotrophic cells that saved amino acid production costs over metabolically autonomous prototrophs. Together, our results suggest that spatially structured environments and limited nutrient availabilities should facilitate the evolution of metabolic interactions, which can help to maintain genotypic diversity within natural microbial populations. Natural bacterial communities are usually very species-rich and bacterial cells within these communities often exchange metabolites with each other. Whether and to which extent obligate metabolic interactions can contribute to maintaining the observed bacterial diversity, however, is not known. In this study, we address this question computationally, by simulating populations of six different bacterial strains that differ in their requirement to obtain amino acids from the environment as well as their propensity to release other amino acids. By systematically varying key variables such as the cost of metabolite production, the speed with which metabolites diffuse in the environment, as well as the amino acid availability in the environment, we show that a cooperative exchange of essential amino acids is evolutionary stable over a broad range of biologically realistic conditions. In particular spatially structured environments, such as bacterial biofilms, and moderate costs of metabolite production favored metabolic interactions. Finally, our work identifies obligate metabolic interactions as a powerful ecological mechanism to maintain different bacterial genotypes with microbial communities.