Literature DB >> 28994811

Precise, High-throughput Analysis of Bacterial Growth.

Masaomi Kurokawa1, Bei-Wen Ying2.   

Abstract

Bacterial growth is a central concept in the development of modern microbial physiology, as well as in the investigation of cellular dynamics at the systems level. Recent studies have reported correlations between bacterial growth and genome-wide events, such as genome reduction and transcriptome reorganization. Correctly analyzing bacterial growth is crucial for understanding the growth-dependent coordination of gene functions and cellular components. Accordingly, the precise quantitative evaluation of bacterial growth in a high-throughput manner is required. Emerging technological developments offer new experimental tools that allow updates of the methods used for studying bacterial growth. The protocol introduced here employs a microplate reader with a highly optimized experimental procedure for the reproducible and precise evaluation of bacterial growth. This protocol was used to evaluate the growth of several previously described Escherichia coli strains. The main steps of the protocol are as follows: the preparation of a large number of cell stocks in small vials for repeated tests with reproducible results, the use of 96-well plates for high-throughput growth evaluation, and the manual calculation of two major parameters (i.e., maximal growth rate and population density) representing the growth dynamics. In comparison to the traditional colony-forming unit (CFU) assay, which counts the cells that are cultured in glass tubes over time on agar plates, the present method is more efficient and provides more detailed temporal records of growth changes, but has a stricter detection limit at low population densities. In summary, the described method is advantageous for the precise and reproducible high-throughput analysis of bacterial growth, which can be used to draw conceptual conclusions or to make theoretical observations.

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Year:  2017        PMID: 28994811      PMCID: PMC5752254          DOI: 10.3791/56197

Source DB:  PubMed          Journal:  J Vis Exp        ISSN: 1940-087X            Impact factor:   1.355


  17 in total

1.  On the lag phase and initial decline of microbial growth curves.

Authors:  George T Yates; Thomas Smotzer
Journal:  J Theor Biol       Date:  2006-09-01       Impact factor: 2.691

2.  Growth rates made easy.

Authors:  Barry G Hall; Hande Acar; Anna Nandipati; Miriam Barlow
Journal:  Mol Biol Evol       Date:  2013-10-28       Impact factor: 16.240

3.  Specific growth rate dependent transcriptome profiling of Escherichia coli K12 MG1655 in accelerostat cultures.

Authors:  Ranno Nahku; Kaspar Valgepea; Petri-Jaan Lahtvee; Sten Erm; Kristo Abner; Kaarel Adamberg; Raivo Vilu
Journal:  J Biotechnol       Date:  2010-01-01       Impact factor: 3.307

Review 4.  Growth kinetics of suspended microbial cells: from single-substrate-controlled growth to mixed-substrate kinetics.

Authors:  K Kovárová-Kovar; T Egli
Journal:  Microbiol Mol Biol Rev       Date:  1998-09       Impact factor: 11.056

5.  r- and K-selection in fluctuating populations is determined by the evolutionary trade-off between two fitness measures: Growth rate and lifetime reproductive success.

Authors:  Steinar Engen; Bernt-Erik Saether
Journal:  Evolution       Date:  2016-11-29       Impact factor: 3.694

6.  Reduction of translating ribosomes enables Escherichia coli to maintain elongation rates during slow growth.

Authors:  Xiongfeng Dai; Manlu Zhu; Mya Warren; Rohan Balakrishnan; Vadim Patsalo; Hiroyuki Okano; James R Williamson; Kurt Fredrick; Yi-Ping Wang; Terence Hwa
Journal:  Nat Microbiol       Date:  2016-12-12       Impact factor: 17.745

7.  Growth rate-coordinated transcriptome reorganization in bacteria.

Authors:  Yuki Matsumoto; Yoshie Murakami; Saburo Tsuru; Bei-Wen Ying; Tetsuya Yomo
Journal:  BMC Genomics       Date:  2013-11-20       Impact factor: 3.969

8.  Microbial growth and physiology: a call for better craftsmanship.

Authors:  Thomas Egli
Journal:  Front Microbiol       Date:  2015-04-14       Impact factor: 5.640

9.  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

10.  Correlation between genome reduction and bacterial growth.

Authors:  Masaomi Kurokawa; Shigeto Seno; Hideo Matsuda; Bei-Wen Ying
Journal:  DNA Res       Date:  2016-07-03       Impact factor: 4.458

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  9 in total

1.  Method for reproducible automated bacterial cell culture and measurement.

Authors:  David Ross; Peter D Tonner; Olga B Vasilyeva
Journal:  Synth Biol (Oxf)       Date:  2022-08-10

2.  A decay effect of the growth rate associated with genome reduction in Escherichia coli.

Authors:  Kouhei Tsuchiya; Yang-Yang Cao; Masaomi Kurokawa; Kazuha Ashino; Tetsuya Yomo; Bei-Wen Ying
Journal:  BMC Microbiol       Date:  2018-09-03       Impact factor: 3.605

3.  Correlation between the spatial distribution and colony size was common for monogenetic bacteria in laboratory conditions.

Authors:  Heng Xue; Masaomi Kurokawa; Bei-Wen Ying
Journal:  BMC Microbiol       Date:  2021-04-15       Impact factor: 3.605

4.  Experimental Evolution Expands the Breadth of Adaptation to an Environmental Gradient Correlated With Genome Reduction.

Authors:  Masaomi Kurokawa; Issei Nishimura; Bei-Wen Ying
Journal:  Front Microbiol       Date:  2022-01-26       Impact factor: 5.640

5.  Contribution of the genomic and nutritional differentiation to the spatial distribution of bacterial colonies.

Authors:  Kenya Hitomi; Jieruiyi Weng; Bei-Wen Ying
Journal:  Front Microbiol       Date:  2022-08-23       Impact factor: 6.064

6.  Machine learning-assisted discovery of growth decision elements by relating bacterial population dynamics to environmental diversity.

Authors:  Honoka Aida; Takamasa Hashizume; Kazuha Ashino; Bei-Wen Ying
Journal:  Elife       Date:  2022-08-26       Impact factor: 8.713

7.  Global coordination of the mutation and growth rates across the genetic and nutritional variety in Escherichia coli.

Authors:  Zehui Lao; Yuichiro Matsui; Shinya Ijichi; Bei-Wen Ying
Journal:  Front Microbiol       Date:  2022-09-20       Impact factor: 6.064

8.  The highly conserved chromosomal periodicity of transcriptomes and the correlation of its amplitude with the growth rate in Escherichia coli.

Authors:  Motoki Nagai; Masaomi Kurokawa; Bei-Wen Ying
Journal:  DNA Res       Date:  2020-06-01       Impact factor: 4.458

9.  Correlated chromosomal periodicities according to the growth rate and gene expression.

Authors:  Liu Liu; Masaomi Kurokawa; Motoki Nagai; Shigeto Seno; Bei-Wen Ying
Journal:  Sci Rep       Date:  2020-09-23       Impact factor: 4.379

  9 in total

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