Syntrophic exchange in synthetic microbial communities

Metabolic crossfeeding is an important process that can broadly shape microbial communities. However, little is known about specific crossfeeding principles that drive the formation and maintenance of individuals within a mixed population. Here, we devised a series of synthetic syntrophic communities to probe the complex interactions underlying metabolic exchange of amino acids. We experimentally analyzed multimember, multidimensional communities of Escherichia coli of increasing sophistication to assess the outcomes of synergistic crossfeeding. We find that biosynthetically costly amino acids including methionine, lysine, isoleucine, arginine, and aromatics, tend to promote stronger cooperative interactions than amino acids that are cheaper to produce. Furthermore, cells that share common intermediates along branching pathways yielded more synergistic growth, but exhibited many instances of both positive and negative epistasis when these interactions scaled to higher dimensions. In more complex communities, we find certain members exhibiting keystone species-like behavior that drastically impact the community dynamics. Based on comparative genomic analysis of >6,000 sequenced bacteria from diverse environments, we present evidence suggesting that amino acid biosynthesis has been broadly optimized to reduce individual metabolic burden in favor of enhanced crossfeeding to support synergistic growth across the biosphere. These results improve our basic understanding of microbial syntrophy while also highlighting the utility and limitations of current modeling approaches to describe the dynamic complexities underlying microbial ecosystems. This work sets the foundation for future endeavors to resolve key questions in microbial ecology and evolution, and presents a platform to develop better and more robust engineered synthetic communities for industrial biotechnology.Microbes are abundantly found in almost every part of the world, living in communities that are diverse in many facets. Although it is clear that cooperation and competition within microbial communities is central to their stability, maintenance, and longevity, there is limited knowledge about the general principles guiding the formation of these intricate systems. Understanding the underlying governing principles that shape a microbial community is key for microbial ecology but is also crucial for engineering synthetic microbiomes for various biotechnological applications (1–3). Numerous such examples have been recently described including the bioconversion of unprocessed cellulolytic feedstocks into biofuel isobutanol using fungal–bacterial communities (4) and biofuel precursor methyl halides using yeast–bacterial cocultures (5). Other emerging applications in biosensing and bioremediation against environmental toxins such as arsenic (6) and pathogens such as Pseudomonas aeruginosa and Vibrio cholerae have been demonstrated using engineered quorum-sensing Escherichia coli (7, 8). These advances paint an exciting future for the development of sophisticated multispecies microbial communities to address pressing challenges and the crucial need to understand the basic principles that enables their design and engineering.An important process that governs the growth and composition of microbial ecosystems is the exchange of essential metabolites, known as metabolic crossfeeding. Entomological studies have elucidated on a case-by-case basis the importance of amino acids in natural interkingdom and interspecies exchange networks (9–11). Recent comparative analyses of microbial genomes suggest that a significant proportion of all bacteria lack essential pathways for amino acid biosynthesis (2). These auxotrophic microbes thus require extracellular sources of amino acids for survival. Understanding amino acid exchange therefore presents an opportunity to gain new insights into basic principles in metabolic crossfeeding. Recently, several studies have used model systems of Saccharomyces cerevisiae (12), Saccharomyces enterica (13), and E. coli (14–16) to study syntrophic growth of amino acid auxotrophs in coculture environments. Numerous quantitative models have also been developed to describe the behavior of these multispecies systems, including those that integrate dynamics (17, 18), metabolism (19–21), and spatial coordination (22). Although these efforts have led to an improved understanding of the dynamics of syntrophic pairs and the energetic and benefits of cooperativity in these simple systems (23), larger more complex syntrophic systems have yet to be explored.Here, we use engineered E. coli mutants to study syntrophic crossfeeding, scaling to higher-dimensional synthetic ecosystems of increasing sophistication. We first devised pairwise syntrophic communities that show essential and interesting dynamics that can be predicted by simple kinetic models. We then increased the complexity of the interaction in three-member synthetic consortia involving crossfeeding of multiple metabolites. To further increase the complexity of our system, we devised a 14-member community to understand key drivers of population dynamics over short and evolutionary timescales. Finally, we provide evidence for widespread trends of metabolic crossfeeding based on comparative genomic analysis of amino acid biosynthesis across thousands of sequenced genomes. Our large-scale and systematic efforts represent an important foray into forward and reverse engineering synthetic microbial communities to gain key governing principles of microbial ecology and systems microbiology.