Metabolic activity affects response of single cells to a nutrient switch in structured populations, bioRxiv, 2019-03-18

AbstractMicrobes live in ever-changing environments where they need to adapt their metabolism to different nutrient conditions. Many studies have characterized the response of genetically identical cells to nutrient switches in homogenous cultures, however in nature microbes often live in spatially structured groups such as biofilms where cells can create metabolic gradients by consuming and releasing nutrients. Consequently, cells experience different local microenvironments and vary in their phenotype. How does this phenotypic variation affect the ability of cells to cope with nutrient switches? Here we address this question by growing dense populations of Escherichia coli in microfluidic chambers and studying a switch from glucose to acetate at the single cell level. Before the switch, cells vary in their metabolic activity some grow on glucose while others cross-feed on acetate. After the switch, only few cells can resume growth after a period of lag. The probability to resume growth depends on a cells’ phenotype prior to the switch it is highest for cells crossfeeding on acetate, while it depends in a non-monotonic way on growth rate for cells growing on glucose. Our results suggest that the strong phenotypic variation in spatially structured populations might enhance their ability to cope with fluctuating environments.

biorxiv systems-biology 100-200-users 2019

PlotsOfDifferences – a web app for the quantitative comparison of unpaired data, bioRxiv, 2019-03-18

AbstractThe quantitative comparison of data acquired under different conditions is an important aspect of experimental science. The most widely used statistic for quantitative comparisons is the p-value. However, p-values suffer from several shortcomings. The most prominent shortcoming that is relevant for quantitative comparisons is that p-values fail to convey the magnitude of differences. The differences between conditions are best quantified by the determination of effect size. To democratize the calculation of effect size, we have developed a web-based tool. The tool uses bootstrapping to resample mean or median values for each of the conditions and these values are used to calculate the effect size and their compatibility interval. The web tool generates a graphical output, showing the bootstrap distribution of the difference next to the actual data for optimal interpretation. A tabular output with statistics and effect sizes is also generated and the table can be supplemented with p-values that are calculated with a randomization test. The app that we report here is dubbed PlotsOfDifferences and is available at <jatsext-link xmlnsxlink=httpwww.w3.org1999xlink ext-link-type=uri xlinkhref=httpshuygens.science.uva.nlPlotsOfDifferences>httpshuygens.science.uva.nlPlotsOfDifferences<jatsext-link><jatsfig id=ufig1 position=float fig-type=figure orientation=portrait><jatsgraphic xmlnsxlink=httpwww.w3.org1999xlink xlinkhref=578575_ufig1 position=float orientation=portrait >

biorxiv scientific-communication-and-education 200-500-users 2019

 

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