Using extremely simple models of cell physiology, Scott and colleagues are able to predict how unnecessary gene expression reduces bacterial fitness, how growth rate changes due to nutrient quality, and how growth rate is reduced by sublethal concentrations of antibiotics that inhibit translation. They also derive the classic Michaelis-Menten equation for growth rate as a function of resource concentration. Their models assume that growth is linearly proportional to translation rate and that there are three classes of proteins: those used to acquire nutrients, those used to make more protein, and a class that is unaffected by nutrient availability. With this, tons of results pretty much just fall out. The paper is a great example of how systems biology links molecular details to whole-cell phenotypes.
“Like Ohm’s law, which greatly expedited the design of electrical circuits well before electricity was understood microscopically, the empirical correlations described here may be viewed as microbial ‘growth laws,’ the use of which may facilitate our understanding of the operation and design of complex biological systems well before all the underlying regulatory circuits are elucidated at the molecular level.”