The chemical compounds that determine growth decisions in bacterial colonies vary according to the growth stage.
Colonies of bacteria are highly complex systems, making it challenging to untangle the contributions of the various components of the environments to their growth.
Now, aided by machine learning, four researchers from the University of Tsukuba in Japan have conducted a massive study of the growth of the bacterium Escherichia coli in media containing different amounts of 44 chemical compounds.
They analysed nearly 13,000 growth curves for almost 1,000 media. The results revealed that the decision-making components were distinct for each growth phase: glucose was critical during the stationary phase, sulfate during the exponential phase, and serine during the lag phase.
This differentiation between the three phases of growth helps to diversify risk and thereby protect the population from extinction.