In nature, microorganisms do not exist in isolation but interact and cooperate in complex ecosystems, a phenomenon which synthetic biological systems have yet to fully harness. Technologies that enable the engineering of synthetic ecosystems, or co-cultures, are crucial not only for the study of these natural systems but also for the advancement of synthetic biology. Developments that enable this foundational leap in how we engineer biology will allow the creation of synthetic populations that grow together and work together, unlocking the full potential of multicellular engineering in synthetic biology. From creating antibiotic-free human therapeutics and chemical-free biofertilizer based on microbiome engineering, to reprogrammable and dynamic biomaterials, engineering cooperation into synthetic ecosystems and co-cultures has the potential to change how we use biology forever.
To determine why more labs aren’t using co-cultures, we visited Imperial College London's Centre for Synthetic Biology. We found that many researchers find it too difficult to determine conditions under which multiple cell types would survive. Different cell types grow best at different conditions and there are few established protocols that tell you exactly how you should grow them together. If conditions are not carefully balanced, one cell type tends to out-compete the other. Currently, this problem is addressed by various population control methods, such as auxotrophic cross-feeding and toxin-antitoxin systems. However, these techniques are neither robust, nor portable across different organisms, nor do they allow precise ratiometric control of the different populations of cells.
We have set out to engineer a genetic circuit that allows ratiometric control of populations in a co-culture to allow future synthetic biologists to realise the full potential of synthetic ecosystems.
Our genetic circuit employs three modules. The first is the communication module, which utilises two orthogonal quorum sensing systems to allow our E. coli populations to detect their own population density, as well as that of the other population.
In order to allow for different quorum sensing systems to be utilised in the circuit, we chose to work with four possible systems: Las, Rhl, Lux, and Cin. The Las, Rhl, and Lux transcriptional activators, LasR, RhlR, and LuxR, are fairly well characterised in the Biobrick registry. However, the Cin transcriptional activator is not.
As a result, crosstalk characterisation for LasR, RhlR, and LuxR did not include Cin 3O-C14 AHL. Therefore, to improve the characterisation of these parts, we performed cross talk experiments with Cin 3O-C14 AHL. Additionally, while a part for CinR does exist in the registry, it has an LVA tag and is uncharacterised. We made a new part for CinR without an LVA tag, and are working to characterise it, and perform crosstalk experiments for CinR with the AHLs associated with Las, Rhl, and Lux.
Our second module, the comparator module, links quorum sensing signals to RNA logic so that the bacteria can compare their own population to the population of the other cell line.
The final module is a growth regulation module which allows our cell lines to respond to the signal relayed by the comparator module. If its population is too large, a growth inhibiting protein is expressed, allowing the population ratios to balance once again.
In addition to the circuit, we have produced a software tool, A.L.I.C.E, which helps scientists design their own co-culture experiments. We have worked with other iGEM teams to generate the preliminary data for A.L.I.C.E. Our project aims to provide a framework to advance the use of co-cultures in synthetic biology and in research of microbial consortia.