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Research Fellows Directory

Christopher Thompson

Professor Christopher Thompson

Research Fellow

Organisation

University of Manchester

Research summary

How can random differentiation be harnessed during embryonic development?

Researchers have long sought to understand the molecular mechanisms underlying embryonic development and have generally assumed them to be exact. However, it is now becoming apparent that embryonic pattern can begin with seemingly chaotic salt and pepper differentiation, followed by sorting out into ordered patterns. Our work addresses the molecular basis of this poorly understood mode of patterning using genetic manipulation, biochemical analysis and live imaging in a simple developmental system, the social amoeba D. discoideum. Our studies will have major implications on our understanding of stem cell differentiation and developmental patterning.

Cheaters and the evolution of cooperation

The evolution of cooperative behaviour remains a challenge because ‘cheaters’ that pay fewer costs than cooperating altruists should be favoured. To understand this problem we are using D. discoideum, which forms fruiting bodies consisting stalk cells that sacrifice themselves to enable the dispersal of spores. Stalk production is therefore considered to be a 'common good' that is costly to produce but benefits the group. This raises the question of why selection does not lead to selfish ‘cheater’ strains that do not become stalk cells, which in turn will ultimately collapse the cooperative system. We have recently found that Dictyostelium strains can avoid some of these problems, because they have the ability to recognise other cooperative strains and selectively engage in cooperation with these. Such a recognition mechanism has previously been termed a 'greenbeard', although few examples exist.

Interests and expertise (Subject groups)

Grants awarded

Using Dictyostelium to understand cell signaling during growth and development

Scheme: Wolfson Research Merit Awards

Dates: Apr 2013 - Mar 2018

Value: £50,000