Systems biology met epigenetics two decades ago (not two days ago)
December 5, 2012 | James Kohl
Excerpt: “Epigenetics and systems biology are two disciplines that created a lot of excitement in the research community in the last decade. It is widely believed that an even bigger potential lies in the combination of both fields, yet experimental and computational scientists have to join forces.”
My comment: In our 1996 Hormones and Behavior review article, we linked molecular epigenetics to systems biology and detailed the links From fertilization to adult sexual behavior. In context, our representation linked the sense of smell to hormonal organization and activation of vertebrate behavior. The model was subsequently extended to invertebrates and their life history transitions. The epigenetic effects of social stress in mammals were also further detailed.
Yet, here we are, with a computational model at the same time the honeybee model organism exemplifies the epigenetic effects of nutrient chemicals and pheromones across species. Had I not presented (on November 9, 2012) an updated version of the model I’ve used to link the sensory environment to behavior since 1992, it would be less frustrating to see others offering a computational model instead of extending works with model organisms from microbes to man.
You can’t feed sugar to a computational model of epigenetic cause and effect to arrive at an acceptable model for behavior. You can, however, feed glucose to any organism on the planet and quickly see that it is largely responsible for all epigenome dynamics, and that the metabolism of glucose and other nutrient chemicals to species-specific pheromones controls adaptive evolution via ecological, social, neurogenic, and socio-cognitive niche construction. Thus, while a computational model may help to explain epigenome dynamics during differentiation of cells and species, model organisms will continue to explain the epigenetic effects of sensory input on the development of behavior and species survival.
The computational model may, however, help to compute what will happen when an organism runs out of food.