Balancing Scales in Biological Models
ADAM PAUL ARKIN
Howard Hughes Medical Institute
Department of Bioengineering, University of California, Berkeley
Physical Biosciences Division,
E.O. Lawrence Berkeley National Laboratory
Berkeley, California
I cannot doubt but that these things, which now seem to us so mysterious, will be no mysteries at all; that the scales will fall from our eyes; that we shall learn to look on things in a different way—when that which is now a difficulty will be the only commonsense and intelligible way of looking at the subject
Lord Kelvin
Presidential Address to the Institution of Electrical Engineers, 1889
Almost all of biology is about evolution. On short time scales, biologists study the kinetics of single enzymes and the temporal evolution of a product from a substrate. On longer time scales, they study the evolution of cellular behaviors that result from the integrated dynamics of the network of nonlinear, and possibly stochastic, chemical reactions that link genome to physiology and respond to environmental signals. On even longer time scales, they study how cells develop—changing their overall functions in response to the genetic program and organizing groups of cells into functional units, such as spore stalks, organs, and sometimes human beings. Scaling up even further, organisms operate as populations that spread beyond their niches in the world and compete with other organisms for resources to survive. This leads to the final scale, the true genetic evolutionary time scale, in which life emerges from the proverbial primordial soup and, on a time scale that defies intuition or complete conception,
rewrites itself over and over with mistakes enough that new forms are born and old forms die on the shorter time scales just described.
To reconstruct the tree of life from the first bacterium, currently dated about 3.5 billion years ago, to modern metazoans like you and me, we peer as “through a glass, darkly” at the striking similarities among phylogenies of fossils and genetic sequences and infer the historical dynamics that created them and us.
From fossil evidence to functional genomics, the purpose of biological models has always been to make sense of these complex data and to follow the implications of conceptual theories.
Models generally play three roles in biology: to demonstrate or explain a physical effect or elucidate a principle (such as the Mendelian sorting of traits via the gene theory or the Hodgkins-Huxley model of signal propagation in neurons); to demonstrate consistency, as when a number of assertions in the form of biochemical reactions in a cell are combined into an integrated model of a process, such as bacterial chemotaxis, to show that these reactions are sufficient to explain a cellular behavior, such as exact adaptation to a step of chemoattractant; and to explore teleology, that is, to demonstrate why something is the way it is. For example, models may be used to explain why an integral feedback is necessary for small, free-swimming cells, such as flagellated bacteria, to sense and follow a chemical gradient.
In this talk, I discuss biological models at each time scale and how they are being linked through improved measurement technology and genetic sequencing. I then demonstrate the theoretical and computational challenges presented by all of these inherently multiscale models, such as time-scale separations, high dimensionality, and differing levels of detail about different parts of the system.
I also discuss the effects of choosing different physical pictures—macroscopic or mesoscopic kinetics—on the computational feasibility of asking certain questions of the model and on predicting behavior. I also discuss the particular challenges in the analysis (rather than simulation) of these systems, comparisons of models to data, and the visualizations of the results. Examples in this presentation include a model of the control and evolution of stress response in Bacillus subtilis and models of spatial signaling in immune-cell chemotaxis.