Syntrophic exchange in synthetic microbial communities

Abstract

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.synthetic ecosystem | amino acid exchange | population modeling M icrobes 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 ...

Microbial mutualism dynamics governed by dose-dependent toxicity of cross-fed nutrients

“…Development of an ecological model capable of predicting coculture behavior Mathematical modeling of synthetic communities is a powerful tool for generating experimentallytestable predictions of what controls mutualism dynamics and stability (Klitgord and Segrè, 2010;Mee et al, 2014;Zomorrodi and Segrè, 2015;Zelezniak et al, 2015). We therefore developed an ecological model (Figure 4) based on previously described interactions for mutualistic systems with Monod uptake kinetics (Meyer et al, 1975;Lee et al, 1976).…”

“…As an alternative, synthetic microbial communities (cocultures) have been developed in which two or more species are cultivated together under laboratory conditions. Cocultures preserve core aspects of natural systems while offering greater practical experimental control (Shou et al, 2007;Hillesland and Stahl, 2010;Summers et al, 2010;Harcombe, 2010;Momeni et al, 2011;Hom and Murray, 2014;Mee et al, 2014). They are also more amenable to modeling than are natural systems and facilitate the development, experimental testing and refining of models for predicting community behavior (Zomorrodi and Segrè, 2015;Johns et al, 2016;Lindemann et al, 2016;Widder et al, 2016).…”

Genome reduction in an abundant and ubiquitous soil bacterium ‘Candidatus Udaeobacter copiosus’

“…Furthermore, many of the amino acids and vitamins Ca. U copiosus appears unable to synthesize are involved in synergistic growth 47 and may be supplied by other microbes as common community goods 48 . Based on the few spartobacterial isolates that have been cultivated 11 , culture-independent studies 10,49 and the genomic data presented here, we speculate that Ca.…”

Oscillatory dynamics in a bacterial cross-protection mutualism

“…So far, the majority of studies of microbial mutualisms have focused on cross-feeding, the mutually beneficial exchange of metabolites (10)(11)(12)(13)(14)(15)). Studies involving cross-feeding amino acid auxotrophs (10)(11)(12) found that the division of labor within the mutualism can increase the fitness of cross-feeding cocultures compared with a self-sufficient strain (10). The greatest gains seem to emerge when amino acids are costly to produce (11).…”

“…Studies involving cross-feeding amino acid auxotrophs (10)(11)(12) found that the division of labor within the mutualism can increase the fitness of cross-feeding cocultures compared with a self-sufficient strain (10). The greatest gains seem to emerge when amino acids are costly to produce (11). These mutualisms can even form immediately when complementary strains encounter each other and without a period of coevolution, although allowing time for adaptation may increase their resilience (12).…”