The evolutionary web of life

Published on December 2, 2014   30 min

Other Talks in the Series: Evolution and Medicine

0:00
The title of this talk is "The Evolutionary Web of Life." My name is John Torday. I'm a Professor of Pediatrics and Obstetrics and I also am in the Evolutionary Medicine Program at University of California-Los Angeles.
0:14
The rationale for this presentation is rather unconventional in that I'm using homeostasis as the selection pressure for evolution. So I'm going to go through that rationale. Homeostasis is the mechanistic basis for physiology. Homeostasis be traced all the way back to unicellular organisms. Unicellular organisms are the bauplan, or the blueprint for metazoans, or multicellular organisms. And homeostasis is a mechanism for monitoring of the environment, both internal, that is, physiology, and external, which is the physical environment. Homeostatic set-points can be changed through cellular-molecular remodeling, providing a mechanism for structural/functional change in adaptation to the environment. Or, as we recognize it, evolution.
0:60
So a historic perspective is of use here for this homeostatic approach. The concept of homeostasis was first formulated by Claude Bernard in the 19th Century. And then, a term was coined by Walter Canon in the 20th Century. Homeostasis is not part of the evolutionary biology domain per se, but probably because it was focused on fossilized material as the ultimate evidence for its relevance. The agents that mediate homeostasis do not fossilize, though it may be argued that their remains are embedded in molecular structure and function. For example, Conrad Bloch, the discoverer of cholesterol synthesis, reasoned that since it took 6 oxygen molecules to generate 1 cholesterol molecule, that cholesterol was actually a molecular fossil. We've extended that concept by reducing complex physiologic principles to molecular phenotypes, and then reverse-engineered their evolutionary history using their ontogeny, phylogeny, and pathophysiology as algorithms to understand their forward and reverse histories.