On a logical difficulty in the directed mutation debate

What are we missing in teaching the Luria-Delbrück experiment?

The importance of teaching the Luria-Delbrück experiment to biology students is increasingly recognized by educators, and improved pedagogical methods for teaching the classic experiment have been proposed and tested in the classroom. However, there are still obstacles that impede the proper teaching of the classic experiment. This note proposes two strategies to further improve the teaching of the classic experiment. The first strategy is to be frank with an inherent limitation of the classic experiment, and instructors should explain from a logical point of view why the classic experiment cannot be used to refute the possibility of directed mutation. The second strategy is to emphasize the pioneering work of Delbrück on developing the mutant distribution that enables researchers to estimate microbial mutation rates using data generated by fluctuation experiments, and instructors should shift their attention to the overlooked essential role of the mutant distribution.

Estimation of Rates of Non-neutral Mutations When Bacteria are Exposed to Subinhibitory Levels of Antibiotics

The increasingly widespread use of antibiotics has raised an urgent public health question: how does nonlethal exposure of antibiotics increase rates of bacterial mutations that confer antibiotic resistance? Quantitative studies of this sort are rare, and interested investigators tend to neglect scenarios where the mutation inducer and the selective agent are the same. One possible reason for this puzzling neglect is that such an investigation may lead to results that are prone to a Lamarckian interpretation, but a more tangible reason is that successful estimation of mutation rates in such scenarios requires new computational methods. This study presents computational methods tailored for a mutation model in which some wide-type cells may be killed by nonlethal exposure to an antibiotic, but in which mutants proliferate unimpeded. Methods for computing maximum likelihood estimates of mutation rates and their corresponding confidence intervals are devised and evaluated by simulations.