Inter- and intra-species cooperation in natural and synthetic microbial communities

Abstract

Naturally occurring microbial communities are able to cooperate to complete complex functions by splitting tasks between organisms and reducing the metabolic burden placed on each individual strain. The ability to distribute tasks and the metabolic load is of interest for biotechnology applications, where dividing labor between populations can allow one to take advantage of the natural strengths of a specific strain and increase production. The potential benefits of creating synthetic microbial communities capable of sharing metabolic load for biotechnology are challenged by the difficulty in co-culturing microbes. One way to combat this challenge is to engineer the microbes to require each other for growth, using approaches such as trading essential nutrients, or cross-feeding. Cross-feeding commonly occurs between auxotrophic microbes, or microbes that lack the ability to produce an essential biomolecule. Cross-feeding has been studied in intra-species pairs of E. coli auxotrophs¸ and less commonly, in inter-species pairs of engineered auxotrophs. Here, we set out to characterize inter- and intra-species cross-feeding in pairs of two industrially relevant bacteria, E. coli and B. megaterium. First, we examined cross-feeding dependent growth in inter- and intra-species pairs of 14 amino acid auxotrophs of E. coli with six amino acid auxotrophs of B. megaterium. We found that 72% of auxotrophic pairs tested demonstrated cross-feeding dependent growth, a much larger proportion than was reported in previous studies of cross-feeding in intra-species pairs of auxotrophs. In addition, we developed a semi-solid plate assay capable of screening large numbers of auxotrophic pairs for cross-feeding dependent growth. We used the growth data from the single amino acid auxotroph co-cultures to successfully predict cross-feeding dependent growth of four B. megaterium strains that are auxotrophic for two amino acids with several single amino acid E. coli auxotrophs. Next, we set out to understand how gene expression in bacteria was changed by co-culture growth. To do this, we used transcriptomic analysis to quantify the changes in gene expression of three of the best cross-feeding pairs of E. coli and B. megaterium grown in co-culture as compared to the same strains grown in a supplemented monoculture. We found that each auxotrophic strain responded differently to co-culture growth. Our work to this point focused on one specific interaction between a specific pair of microbes. However, microbes in naturally occurring communities are subject to interactions both between the members of the community and with their environment. In order to understand how abiotic factors impact community composition, we evaluated microbial communities found at the Cerro Negro Volcano in Nicaragua. The environments from which these microbes were found ranged in temperature from 45 °C to 98 °C and in pH from less than 1 to 5.1. Through community detection analysis using a Euclidean distance algorithm and edge betweeness to define communities we found that pH was a greater influence on community composition than temperature. Overall, our work examines the interactions between bacteria and shows that cross-feeding can be used as a tool in the design of synthetic microbial communities for use in bioproduction. In addition our findings from synthetic communities can inform our understanding of the prevalence and mechanisms of specific ecological interactions.