Literature DB >> 19390987

Bacterial growth properties at low optical densities.

Maja Novak1, Thomas Pfeiffer, Martin Ackermann, Sebastian Bonhoeffer.   

Abstract

A method for accurate quantification of growth rate and yield of bacterial populations at low densities was developed with a modified version of a stepwise linear model for fitting growth curves based on optical density measurements, and adapted to measurements at low optical densities in 96-well microtiter plates. The method can be used for rapid and precise estimates of growth rate and yield, based on optical density measurements of large numbers of cultures of Escherichia coli. E. coli B lines were serially propagated at low glucose concentration during a long-term evolution experiment. Growth rate and yield of populations sampled from each of 12 lines that evolved for 20,000 generations under these conditions and two ancestral clones was measured. Populations were grown at three different glucose concentrations. Consistent with earlier findings, statistical analysis showed that both exponential growth rate and yield per unit of glucose differed significantly between the three glucose concentrations tested. Significant adaptation of the evolved populations to the nutrient conditions in which they evolved for 20,000 generations was observed.

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Year:  2009        PMID: 19390987     DOI: 10.1007/s10482-009-9342-7

Source DB:  PubMed          Journal:  Antonie Van Leeuwenhoek        ISSN: 0003-6072            Impact factor:   2.271


  3 in total

1.  Malthusian Parameters as Estimators of the Fitness of Microbes: A Cautionary Tale about the Low Side of High Throughput.

Authors:  Jeniffer Concepción-Acevedo; Howard N Weiss; Waqas Nasir Chaudhry; Bruce R Levin
Journal:  PLoS One       Date:  2015-06-26       Impact factor: 3.240

2.  Growthcurver: an R package for obtaining interpretable metrics from microbial growth curves.

Authors:  Kathleen Sprouffske; Andreas Wagner
Journal:  BMC Bioinformatics       Date:  2016-04-19       Impact factor: 3.169

3.  PRECOG: a tool for automated extraction and visualization of fitness components in microbial growth phenomics.

Authors:  Luciano Fernandez-Ricaud; Olga Kourtchenko; Martin Zackrisson; Jonas Warringer; Anders Blomberg
Journal:  BMC Bioinformatics       Date:  2016-06-23       Impact factor: 3.169

  3 in total

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