Building a cell history recorder using synthetic biology for longitudinal patient monitoring

Project Type

  • PhD and Graduate Research Masters
  • Honours

Project details

Cells are exquisite sensing ‘machines’ that continuously monitor their environment for signals. These signals dictate cell differentiation, division and/or biological function, with major implications in health and disease. Unfortunately, there is no ‘recording’ left behind to correlate a cell’s past with its current state.

Very recently, genome engineering technologies based on CRISPR and Prime Editing have enabled cells to record biological processes into their DNA, so-called ‘cell recorders’ (Choi, Nature 2022). However, they are currently limited in the frequency and amount of information that can be recorded over time.

In this project, a novel synthetic biology approach is optimised to overcome these limitations using sequential insertion of DNA barcodes (produced in response to cellular events) into a defined locus. This creates a continuous DNA record of expression of multiple genes over time, that is inherited across cellular generations, and that can be read out via sequencing.

This technology is anticipated to become a powerful synthetic biology tool for patient monitoring, disease prediction, and basic science. This project suits someone with strong interests in synthetic biology, protein engineering, molecular biology and DNA sequencing.

About our research group

The Clonal Systems Biology laboratory focuses on understanding development at a single cell or ‘clonal’ level. Our biological interests are focused on haematopoiesis (in both the steady-state and after perturbation with inflammation or during leukemia). We have a particular interest in the development of the dendritic cell subtypes of the immune system.

We both adopt and develop our own genome engineering tools including cellular barcoding for clonal lineage tracing, as well as single cell ‘multi-omics’. Depending on interests and skills, students in the lab are encouraged and supported in learning both the laboratory techniques to generate new data and create new technologies, as well as the computational tools to analyse and interpret the results.

Education pathways