Modular assembly of synthetic microbial communities

Hypothesis
Our hypothesis is that arbitrary microbial communities can be modularly assembled using a set of
"plug-and-play" interactions between the constituent populations. This will provide a foundational
platform for future bio-industry, enabling the distribution of biological systems - so called division-
of-labour - opening up the possibility of more efficient and effective industrial bioprocesses.

Background
Over the last few decades, we have made astounding leaps in improving our ability to engineer a
range of organisms to perform a variety of tasks - from production of fine chemicals to the
detection of tumours. However, there are fundamental limits to what we can ask particular cells to
do - whether that be due to metabolic burden, toxicity of by-products, and inaccessibility of
substrates among other considerations. In recent years, in order to overcome these limits, it has
repeatedly been proposed that we must divide complex tasks into simpler sub-tasks, distributing
these functions across a community.

To date, only small ad hoc synthetic microbial communities have been demonstrated. Even though
the field of synthetic biology has shown how quickly we can advance when we embrace the
principles of standardisation and modularisation, this approach has been sorely lacking when we
move beyond the molecular scale to the community scale.
Here, we aim to make microbial communities as composable as genetic circuits are. Fedorec and
Barnes previously demonstrated a computational framework for the design of synthetic
communities [10.1038/s41467-020-20756-2] and validated it through the construction of a two
strain E. coli consortia [10.1038/s41467-021-22240-x]. This work was limited in scope; relying only
on interactions through inter-cellular toxins. To move beyond ad hoc community assembly, and
move towards a true design-build-test-learn cycle for microbial communities, we require a library
of inter-cellular interaction mechanisms from which we can build new communities, the
experimental protocols with which we can test community behaviour, the mathematical
framework through which we can learn from unexpected outcomes, and computational tools that
allow us to navigate the vast possible design space.

Aim
Development of a platform for the design and assembly of arbitrary synthetic microbial
communities.

Objectives
WP1: Construct a library of modular interaction "devices"
WP2: Develop a computational and methodological pipeline for community design and
validation
WP3: Demonstrate the approach by building a library of stable communities