Literature DB >> 21095113

Measuring growth rate in high-throughput growth phenotyping.

Anders Blomberg1.   

Abstract

Growth rate is an important variable and parameter in biology with a central role in evolutionary, functional genomics, and systems biology studies. In this review the pros and cons of the different technologies presently available for high-throughput measurements of growth rate are discussed. Growth rate can be measured in liquid microcultivation of individual strains, in competition between strains, as growing colonies on agar, as division of individual cells, and estimated from molecular reporters. Irrespective of methodology, statistical issues such as spatial biases and batch effects are crucial to investigate and correct for to ensure low false discovery rates. The rather low correlations between studies indicate that cross-laboratory comparison and standardization are pressing issue to assure high-quality and comparable growth-rate data.
Copyright © 2010 Elsevier Ltd. All rights reserved.

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Year:  2010        PMID: 21095113     DOI: 10.1016/j.copbio.2010.10.013

Source DB:  PubMed          Journal:  Curr Opin Biotechnol        ISSN: 0958-1669            Impact factor:   9.740


  29 in total

Review 1.  Experimental evolution and the dynamics of genomic mutation rate modifiers.

Authors:  Y Raynes; P D Sniegowski
Journal:  Heredity (Edinb)       Date:  2014-05-21       Impact factor: 3.821

2.  Competitive Growth Enhances Conditional Growth Mutant Sensitivity to Antibiotics and Exposes a Two-Component System as an Emerging Antibacterial Target in Burkholderia cenocepacia.

Authors:  April S Gislason; Matthew Choy; Ruhi A M Bloodworth; Wubin Qu; Maria S Stietz; Xuan Li; Chenggang Zhang; Silvia T Cardona
Journal:  Antimicrob Agents Chemother       Date:  2016-12-27       Impact factor: 5.191

3.  Resolving the Complex Genetic Basis of Phenotypic Variation and Variability of Cellular Growth.

Authors:  Naomi Ziv; Bentley M Shuster; Mark L Siegal; David Gresham
Journal:  Genetics       Date:  2017-05-11       Impact factor: 4.562

4.  Phenomic assessment of genetic buffering by kinetic analysis of cell arrays.

Authors:  John Rodgers; Jingyu Guo; John L Hartman
Journal:  Methods Mol Biol       Date:  2014

5.  The details in the distributions: why and how to study phenotypic variability.

Authors:  K A Geiler-Samerotte; C R Bauer; S Li; N Ziv; D Gresham; M L Siegal
Journal:  Curr Opin Biotechnol       Date:  2013-04-06       Impact factor: 9.740

6.  Pyphe, a python toolbox for assessing microbial growth and cell viability in high-throughput colony screens.

Authors:  Stephan Kamrad; María Rodríguez-López; Cristina Cotobal; Clara Correia-Melo; Markus Ralser; Jürg Bähler
Journal:  Elife       Date:  2020-06-16       Impact factor: 8.140

7.  A new stoichiometric miniaturization strategy for screening of industrial microbial strains: application to cellulase hyper-producing Trichoderma reesei strains.

Authors:  Etienne Jourdier; Laurent Poughon; Christian Larroche; Frédéric Monot; Fadhel Ben Chaabane
Journal:  Microb Cell Fact       Date:  2012-05-30       Impact factor: 5.328

8.  Development of an optimized medium, strain and high-throughput culturing methods for Methylobacterium extorquens.

Authors:  Nigel F Delaney; Maria E Kaczmarek; Lewis M Ward; Paige K Swanson; Ming-Chun Lee; Christopher J Marx
Journal:  PLoS One       Date:  2013-04-30       Impact factor: 3.240

9.  A quantitative fitness analysis workflow.

Authors:  A P Banks; C Lawless; D A Lydall
Journal:  J Vis Exp       Date:  2012-08-13       Impact factor: 1.355

10.  Simultaneous saccharification and fermentation of steam exploded duckweed: Improvement of the ethanol yield by increasing yeast titre.

Authors:  X Zhao; G K Moates; A Elliston; D R Wilson; M J Coleman; K W Waldron
Journal:  Bioresour Technol       Date:  2015-07-02       Impact factor: 9.642

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