Developing Novel Optofluidics Approaches for Single-Cell Sequencing - Biosciences - EPSRC DTP funded PhD Studentship

Location: Streatham and St Lukes Campuses, Exeter

Project Description

Aim: The aim of this project is to develop novel technologies for measuring gene expression profiles in individual cells. The developed techniques will be applied to two important health problems: the analysis of persister bacterial cells linked to antibiotic resistance as well as the influence of cell clustering in the development of diabetes.

Background: The cell is the building block of life. However, despite two centuries of intense investigation, cells remain enigmatic. Thus, we have recognised a pressing need to perform single-cell studies among cell populations as opposed to standard ensemble analysis. For example, in the context of disease, a single cell can lead to tuberculosis, cancer or neurological disorders (Macaulayet al, Trends in Genetics 2017). Therefore, in order to advance our technological capabilities to investigate cells and to shed light on some of the most fundamental processes in biology it is paramount that expertise from physics and engineering is combined with that in biology and medicine.

Project: This PhD studentship will allow you to take advantage of the expertise available in Physics, Biosciences and the Medical School at Exeter to develop a novel technology platform to investigate gene expression with single-cell precision. Drs Pagliara and Gielen have recently established an experimental platform for single cell sequencing and will provide training on microfluidics, microscopy and microbiology. Prof Morgan and Dr Richardson are studying the heterogeneity among the cell populations present in islets of Langerhans to better understand the factors influencing the development of diabetes.

Specifically, you will investigate changes in the gene expression profile of single Escherichia coli bacteria and of single beta cells. On one hand, this will open the way for the investigation of the mechanisms underlying bacterial responses to antibiotic drugs which is paramount given the current antibiotic resistance crisis (Martens et al, The Journal of Antibiotics 2017).

In addition, you will begin to unravel the complexities associated with the formation of the cell aggregates which comprise the islets of Langerhans in mammals. Cells behave very differently when in close contact in 3D structures rather than when they exist as monolayers but the reasons for this are not understood. Importantly, there is also evidence that loss of the normal cellular heterogeneity occurs in islet cells during the development of diabetes and gaining a more complete understanding of this process is critical.

In order to perform gene expression profiling on single cells, you will design, fabricate and operate microfluidic devices that allow thousands of cells to be confined and manipulated, each in a tiny separate compartment (a few picoliters in volume). You will optimise the device geometry and the experimental parameters according to the cell type under investigation. You will manipulate the environment around each cell both in the bulk phase and in microfluidics, thus allowing you to study cellular responses to specific changes in the environment around the cells. Taking advantage of the microfluidic compartmentalisation you will extract RNA from individual cells and prepare it for next generation sequencing (Zilionis, Nature Protocols 2017).

You will then analyse sequencing data from single cells exposed to different environments to identify the molecular mechanisms underlying cellular response to external cues such as antibiotic exposure. For islets of Langerhans, you will study the differentiation status of the individual endocrine cell types to establish how cell differentiation is maintained and why it may become dysregulated when islet cells lose close contact and/or are exposed to incubation conditions reminiscent of those found in patients with diabetes (e.g. elevated concentrations of glucose and free fatty acids).

Core techniques: nanotechnology, droplet microfluidics, microscopy, cell culture, sequencing, single-cell analysis, big data analysis, microfabrication.