 A key original motivation of the experiment was to learn more about the long-term dynamics of adaptation and diversification by studying evolution in real time, in a controlled setting. Because the populations started out exactly the same and live in identical environments, any differences in fitness, physiology or morphology that arise over time are due entirely to new mutations in clonal lineages (not prone to recombination). Many insights have arisen from the long-term evolution experiment, including inferences about the dynamics of mutation, the role of chance in evolutionary trajectories, and the evolutionary origin of complex novel features (Fox and Lenski 2015). While in a few cases these findings are restricted to inferences specifically about E. coli and similar bacteria (e.g., Sniegowski et al. 1997), most are considered to apply to the processes and dynamics of long-term evolution in general. In other words, the microbes in the laboratory are not modelling microbes exclusively, but rather serving as a lens through which to understand more generally the phenomena of evolving life. In some important respects, these experimental systems are run like algorithms: exact iterative procedures that lead to various outcomes, and which can be looped and rerun at various points in the overall procedure.