Jennifer Hallinan

View all speakers
Newcastle University
Hallinan, Jennifer

Jennifer Hallinan completed a First Class Honours degree in molecular biology at the Australian National University, followed by a PhD in computer science at the University of Queensland. She was a Group Leader at the Institute for Molecular Biosciences at the University of Queensland before moving to the United Kingdom in 2006 to take up a position with the Centre for the Integrated Systems Biology of Ageing and Nutrition at Newcastle University.

Jennifer is currently a lecturer in bioinformatics and synthetic biology at Newcastle. She is interested in the application of computational intelligence techniques to the design and analysis of synthetic genetic circuits.

Tue July 9 | 2:00 - 4:00
ABSTRACT: Tuning Receiver Characteristics in Bacterial Quorum Communication

Quorum communication is the process by which bacteria communicate, allowing them to modify the transcriptome in response to the nature and number of other bacteria in their environment. In Gram-positive bacteria, quorum communication commonly occurs via the production and sensing of small peptides by two-component systems, each of which consists of a membrane-bound response regulator and a protein kinase which triggers a phosphorylation relay leading to the activation or repression of suites of genes. The engineering of quorum communication systems permits synthetic biologists to manipulate the behaviour of entire populations of bacteria as well as that of individual cells.  In synthetic biology, as in electrical engineering, we need to be able to control the receiver response characteristics in order to ensure that the system of which they are part performs in a predictable, desired manner. In this work we apply computational design approaches, incorporating an evolutionary algorithm, to the modification of the receiver response characteristics of the SpaR/K two-component system of B. subtilis. This system produces and responds to subtilin, a lantibiotic produced by only some strains of the bacterium. The evolutionary algorithm builds simulateable models of the subtilin system using Standard Virtual Parts (SVPs), which can be swapped in and out of the model. The algorithms draws upon our extensive repository of SVPs: small SBML models of biological parts such as promoters, RBSs and CDSs. Both the kinetic parameters and the circuit topology can be modified. Manipulation of the subtilin system will allow us to control the behaviour of a mixed bacterial population. We demonstrate the application of our computational design system to the production of subtilin receiver response curves with a variety of shapes different from the sigmoid response of the wild type receiver.