Meeting Abstract

55.1  Sunday, Jan. 5 13:30  Mosaic physiology from developmental stochasticity: an alternative to phenotypic plasticity WOODS, H. A.; Univ. of Montana art.woods@mso.umt.edu

A key problem in organismal biology is to understand the origins of functional diversity. Modern biology proposes two general mechanisms. The first is developmental programs, by which single cells diversify into the organized diversity of cell types, tissues, and organs that we see in almost all multicellular organisms. The second general mechanism is phenotypic modification stemming from interactions between organisms and their environments – known as phenotypic plasticity or phenotypic flexibility. I propose a third fundamental mechanism: stochastic events during development that give rise to mosaics of physiological diversity within individual organisms. In biological systems, stochasticity stems from the inherently random actions of small numbers of molecules interacting with one another. Although stochastic effects occur in many contexts, available evidence suggests that important kinds of stochasticity can arise in gene networks specifically as a consequence of low transcript numbers in individual cells. I briefly review mechanisms by which organisms control such stochasticity, and how they may use it to create adaptive functional diversity. I then fold this idea into modern thinking on phenotypic plasticity, proposing that multicellular organisms exhibit mosaic physiology. Mosaic physiology refers to sets of diversified phenotypes that carry out related functions at the same time, but that are distributed in space, within individual organisms. Mosaic physiology arises from stochasticity-driven cell differentiation, early during cell diversification, which is then amplified by cell division and growth into macroscopic phenotypic modules making up the physiological systems of later life stages. Mosaic physiology provides a set of standing, diversified phenotypes, within single organisms, that raise the likelihood of coping well with novel environments.