Optimal protein production by a synthetic microbial consortium: Coexistence, distribution of labor, and syntrophy

The bacterium E. coli is widely used to produce recombinant proteins such as growth hormone and insulin. One inconvenience with E. coli cultures is the secretion of acetate through overflow metabolism. Acetate inhibits cell growth and represents a carbon diversion, which results in several negative effects on protein production. One way to overcome this problem is the use of a synthetic consortium of two different E. coli strains, one producing recombinant proteins and one reducing the acetate concentration. In this paper, we study a chemostat model of such a synthetic community where both strains are allowed to produce recombinant proteins. We give necessary and sufficient conditions for the existence of a coexistence equilibrium and show that it is unique. Based on this equilibrium, we define a multi-objective optimization problem for the maximization of two important bioprocess performance metrics, process yield and productivity. Solving numerically this problem, we find the best available trade-offs between the metrics. Under optimal operation of the mixed community, both strains must produce the protein of interest, and not only one (distribution instead of division of labor). Moreover, in this regime acetate secretion by one strain is necessary for the survival of the other (syntrophy). The results thus illustrate how complex multi-level dynamics shape the optimal production of recombinant proteins by synthetic microbial consortia.

Universality of evolutionary dynamics with arbitrary demography

The assumption of constant population size is central in population genetics. It led to a large body of results, which have proven successful to understand evolutionary dynamics. Part of this success is due to their robustness to modeling choices. On the other hand, allele frequencies and population size are both determined by the interaction between a population and the environment. Including explicitly the demographic factors and life-history traits that determine the eco-evolutionary dynamics makes the analysis difficult and the results dependent on model details. Here, we develop a framework that encompasses a great variety of systems with arbitrary population dynamics and competition between species. By using techniques based on scale separation for stochastic processes, we are able to compute evolutionary properties, such as the invasion probability. Remarkably, these properties assume a universal form with respect to our framework, which depends on only three life-history traits related to the exponential fitness, the invasion fitness, and the carrying capacity of the alleles. In other words, different systems, such as Lotka-Volterra or a chemostat model, share the same evolutionary outcomes after the correct remapping of the parameters of the models into three effective life-history traits. An important and surprising consequence of our results is that the direction of selection can be inverted, with a population evolving to reach lower values of fitness. This can happen because the obtained frequency-dependent noise (affected by the three life-history traits) can generate an effective force that counterbalance classical selection.