9.3: Interaction networks and model systems

Interaction networks are a universal feature of biological systems, from the molecular to the mental and social. These are organized in a hierarchical and bidirectional manner, involving various forms of "feedback". So what exactly does that mean? Most obviously, at the macroscopic level, the behavior of ecosystems depends upon the interactions between organisms. As we move down the size scale the behavior of individual organisms is based on the interactions between the cells and tissues formed during the process of embryonic development or the building of social communities. Gene expression also involves interaction networks; genes express polypeptides and regulatory RNAs that influence the expression of other genes, often including themselves. Multiple gene products are involved in the regulation of any particular gene. Since many of the interactions involved have a stochastic nature, chance plays a role in generating variation and outcomes. At the same time there are regulatory interactions and feedback loops that act to control stochastic effects and to ensure that biological behaviors are robust and (often) predictable. All of the interactions and processes that underlie biological systems are the result of evolutionary processes and historical situations, including past adaptations and non-adaptive events in ancestral populations.

Scientific studies of biological systems are driven by the desire to understand how it is that such systems came to be and how they behave the way they do. Such knowledge is helpful, particularly in the age of precision medicine and genetic engineering, in order to identify, treat and/or avoid a disease. But there are a number of reasons that some questions cannot be answered directly; one is that it may not be possible (or ethical) to carry out necessary experiments. But here the evolutionary relationships between organisms come to our aid. We can choose organisms that are easier to study, develop faster, or are “simpler” in some way. By studying various “model” organisms we can hope to identify common and relevant mechanisms. At the same time, it is important to recognize that the various “types” of experimentally useful organisms are each adapted to their own environmental niche, evolving independently of others for millions to hundreds of millions of years. Even the most closely related of organisms, such as the great apes, a group that includes humans, display multiple functionally significant differences. Once isolated, and maintained in the laboratory, we put organisms in an unnatural situation, a situation that subjects them to different adaptive and selective pressures. At the same time, isolated organisms are often maintained under conditions that reduce genetic variation - they become inbred. Inbreeding can be desirable (for science), since it reduces variability and makes experiments more interpretable; it also makes the organisms studied less relevant to “real” (wild) organisms. An example of this is the fact that different in-bred lines of mice can respond differently to different experimental and therapeutic interventions.^[379]

Notwithstanding the complexities of biological systems, we can approach them at various levels of resolution through a systems perspective, using specific organisms to study specific processes andbehaviors. At each level, there are objects that interact with one another in various ways to produce specific behaviors. Many of these systems are conserved, related to one another evolutionarily. To analyze a system we need to define, identify, and appreciate the nature of the objects involved, how they interact, and the behaviors that emerge from such interactions; how such interactions influence the system. Does the system move to a new state or does it return, after a perturbation, to its original state? There are many ways to illustrate this way of thinking. We will get concrete by looking at a (relatively) simple system and consider how it behaves at the molecular, cellular, and social levels. The model system we consider here is the bacterium Escherichia coli (E. coli), how it behaves in isolation, in social groups, and how it metabolizes the milk sugar lactose.^[380] Together these illustrate a number of common regulatory principles that apply more or less universally to biological systems at all levels of organization.

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