Metabolic cybernetics

“Cybernetics” is another term for systems biology. Originally coined by Norbert Weiner in the 1940s, it refers to “the scientific study of control and communication in the animal and the machine”. Cybernetics aptly describes our efforts to understand metabolic homeostasis. We seek to understand how systems (cells, organs or animals) respond to perturbations, such as hormones like insulin, exercise or different diets. We are also interested in defining the impact of the genome on these different effects. To achieve this we have developed ways of studying the transcriptome, the metabolome, the proteome and the phosphoproteome as well as other post translational changes since these factors work together to govern the behavior of the system in response to perturbations. Our ultimate goal is to delineate the key control points that are likely to be the targets of disease and more importantly the targets of optimal future therapeutic intervention.

Insulin and exercise are two of the most physiologically relevant modulators of metabolism in mammals that affect how we sense and respond to environmental challenges. Our goal is to understand how insulin and exercise change our body at the molecular level so that we can harness this information to improve health. Most notably, insulin resistance, or impaired insulin action, is one of the earliest detectable defects associated with metabolic diseases like type 2 diabetes and so to understand this it is essential to understand how insulin works under normal conditions. To do this we are conducting both fundamental biochemical and cell biological studies as well as more global systematic analyses of system behaviour such as analysis of the cellular phosphoproteome. These experiments often generate a reasonable amount of data and to decrypt this we utilise mathematical skills. For this, we collaborate with our learned mathematical colleagues like Jean Yang at the School of Mathematics and Statistics at University of Sydney. The end goal is to build a complete dynamic map of organismal health at the molecular level with integrated knowledge from each of the component systems including the genome, the transcriptome and the proteome. An essential feature of all of this is to establish new visualisation methods so that this can all be conveyed to the community.

Find out more on the various projects we are currently working on from here!