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Scientists offer way to address 'age-old' questions
Date:9/7/2011

werful ways. For instance, we found that how frequently a given age is observed along lineages is a direct reporter of how important that age is to the population's growth rate. This would allow us to predict the success or failure of mutant bacteria, which age differently from normal ones."

Using experimental data from laboratory populations of E. coli, the researchers confirmed several theoretical predictions. The article's other co-authors were Yuichi Wakamoto of the University of Tokyo and the Japan Science and Technology Agency and Alexander Grosberg, a professor in NYU's Department of Physics and its Center for Soft Matter Research.

The work builds upon a previously published paper in the Proceedings of the National Academy of Sciences, in which Kussell and co-author Stanislas Leibler of Rockefeller University offered a way to infer the behavior of individual cells from population-level measurements.

One of the behaviors they considered is known as stochastic switching, a strategy in which cells randomly activate certain genes in order to survive. Notably, pathogenic bacteria, which cause disease in both humans and animals, engage in stochastic switching, resulting in alternative cellular states that improve the bacteria's ability to survive. The cells best suited for given conditions survive while others die offanother example of selection within populations. Understanding what prompts this type of cellular change in bacteria, and which strains are more sustainable than others, could then lead to alternative methods to curb bacterial growth.

The study centered on understanding two types of cellular strategiesresponsive switching, in which cells change their state by reacting to environmental change, and stochastic switching, in which cells randomly activate certain genes, independent of external forces. Within a population, however, it is difficult to detect which strategy is being usedwhen cells change behavior, are they
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Contact: James Devitt
james.devitt@nyu.edu
212-998-6808
New York University
Source:Eurekalert

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