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Biology LibreTexts

9.13: Network interactions

As we come to analyze the regulation of gene expression, we recognize that they represent an interaction network. A common feature of all biological systems, from the molecular to the ecological and evolutionary, are networks of interactions. These are generally organized in a hierarchical and bidirectional manner. So what exactly does that mean? Most obviously, at the macroscopic level, the behavior of ecosystems depends upon the interactions of organisms with one another. As we move down the size scale the behavior of individual organisms is based on the interactions between cells and tissues formed during the process of embryonic development and maturation. Since many of these interactions have a stochastic nature, chance also plays a role. At the same time there are regulatory interactions and feed-back loops that can act to suppress some of these stochastic effects and serve to smake biological behaviors more predictable. All of these interactions (and the processes that underlie particular biological systems) are the result of evolutionary mechanisms and historical situations, including past adaptations and non-adaptive events.

Not withstanding the complexity of biological systems, we can approach them at various levels through a systems perspective. At each level, there are objects that interact with one another in various ways to produce specific behaviors. To analyze a system at the molecular, cellular, tissue, organismic, social, or ecological level we need to define (and understand and appreciate) the nature of the interacting objects, how they interact with one another, and what emerges from such interactions. There are many ways to illustrate this way of thinking but we think that it is important to get concrete by looking at a (relatively) simple system by considering how it behaves at the molecular, cellular, and social levels. Our model system will be the bacterium E. coli and some of its behaviors, in particular how it behaves in isolation and in social groups and how it metabolizes the milk sugar lactose290. Together these illustrate a number of common regulatory principles that apply more or less universally to biological systems at all levels of organization.


290 The Lac Operon: A Short History of a Genetic Paradigm


  • Michael W. Klymkowsky (University of Colorado Boulder) and Melanie M. Cooper (Michigan State University) with significant contributions by Emina Begovic & some editorial assistance of Rebecca Klymkowsky.