High Throughput Analysis of Gene Function in Mammalian Cells

Despite the considerable success in sequencing the human genome and other genomes, the function of many thousands of genes in humans remains unknown. Development of techniques which can screen thousands of genes simultaneously for their effect on the biological processes in living cells – cell division, signaling pathways and gene expression, for example – would result in major benefits to both the basic biomedical sciences and the pharmaceutical industry.

Future Deliverables
Improved tools for handling, analysing and storing the complex data sets generated by the automated imaging

Professor Mike White at the University of Liverpool is leading a multi-site collaborative Beacon Project which aims to use an innovative approach based on cell imaging to tackle these challenges in large-scale functional gene analysis. He is joined by colleagues from Liverpool, the University of Manchester and UMIST in a programme of research which blends expertise in a number of key disciplines – non-invasive imaging, genomics and genetic computing.

The team’s ultimate goal is to subject living mammalian cells, microarrayed in their thousands on a microscope slide, to a variety of inputs (e.g. drugs, hormones, genes of unknown function) and visualise the dynamic changes that subsequently occur inside the cells using state-of-the-art non-invasive imaging technology. The team already has considerable expertise in automated multiparameter imaging of live cells and in developing the equipment and conditions necessary to observe cells long-term.

Early Achievement
An unanticipated discovery of the team is that their expertise in genetic algorithms, originally intended for use in the processing of imaging data, has enabled significant improvements in transfection efficiency to be made.

The Beacon project, however, will require a huge scaling up of previous work, presenting challenges in the genetic manipulation of cells, automated imaging and informatics. High throughput delivery of genes to cells is being tackled by the novel application of a technique known as ‘reverse transfection’ to study living cells; this has the potential to deliver a different gene or set of genes to each spot of cells on an array.

With an array of IPR and key developments in science as possible outcomes a comprehensive review of the emergent and future IPR is underway

Pharmaceutical Applications

  • Assistance in the discovery of new therapeutic targets and new therapeutic compounds
  • Faster and more efficient drug development process

A high-throughput platform for functional gene analysis would undoubtedly be a very attractive tool for basic and applied biomedical scientists. Users would be able to build up a ‘fingerprint’ for the agent that they have applied to the cells (a drug or a novel gene for example), which would provide a huge amount of functional information about the effects of that agent on diverse biological processes. The project team has already established collaborations with a number of companies who will make available materials and instrumentation to help in the project’s development.

Industrial Interaction
This project has established a wide range of industrial relationships extending to companies in the pharmaceutical, instrumentation and software sectors

The project has started to make a significant inroad into its many objectives. On the biological side, the behaviour of one protein in a key signaling pathway has been shown using imaging to be unexpectedly complex. This demonstrates the real value of developing a system that can observe subtle dynamic changes inside the cell.

Significant Achievement
A collaborating company, supplying customized instrumentation has been able to improve its product as a direct result of method development work on this project.

For further details on this project please see the project website or contact the team leader Professor Michael White The University of Liverpool,School of Biological Sciences, E-mail: M.White@liv.ac.uk Tel: 0151 795 4424

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