Engineering microbial communities for distributed computation using bacterial micro compartments.

Lead Research Organisation: University College London
Department Name: Cell and Developmental Biology

Abstract

Building distributed biological systems is an attractive prospect for synthetic biology as it
alleviates the constraints associated with engineering single strains and allows us to expand
the applications of our systems into areas including complex biosensing and diagnostic tools,
bioprocess control and the monitoring of industrial processes. The Barnes group has been
working towards the engineering of bacterial communities to serve as distributed
biocomputing systems capable of integrating signal information and decision making (eg
logic gates, neural networks). Using mathematical modelling we have designed microbial
interactions and then constructed communities either within bioreactors or in spatial
"computational biofilms".
Bacterial microcompartments (BMCs) are selectively permeable shells in prokaryotic cells
that are analogous to organelles in eukaryotes. Many BMCs enable microbes to utilize specific
energy, carbon, and nitrogen sources that are niche specific and therefore contribute to both
forming and distorting bacterial communities. BMCs architectures are also attractive as
nanotechnology platforms with applications in metabolic engineering and biomedicine. The
Frank group have been working on the design and production of recombinant BMCs with
specified properties.
This project will build on the knowledge of both groups and bring together different aspects
of engineering microbial communities and bacterial microcompartments. There are three
main strands:
Aim 1) the use of BMCs as an additional part in the synthetic biology toolkit for the
construction of microbial communities that form distributed computing systems.
Aim 2) apply machine learning approaches to the optimisation of nanoparticle production. We
will build on our existing reinforcement learning framework for control of microbial
populations in bioreactors.
Aim 3) the use of BMCs to develop novel therapeutic bacteria that can manipulate extant
microbiomes
These approaches have the potential to revolutionise how we engineer microbial
communities with new functionalities in biocomputing and therapeutics.

Publications

10 25 50

Studentship Projects

Project Reference Relationship Related To Start End Student Name
BB/T008709/1 01/10/2020 30/09/2028
2546732 Studentship BB/T008709/1 01/10/2021 14/11/2025 Chania Livesey-Clare