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Phenotypic signatures arising from unbalanced bacterial growth.

Publication ,  Journal Article
Tan, C; Smith, RP; Tsai, M-C; Schwartz, R; You, L
Published in: PLoS computational biology
August 2014

Fluctuations in the growth rate of a bacterial culture during unbalanced growth are generally considered undesirable in quantitative studies of bacterial physiology. Under well-controlled experimental conditions, however, these fluctuations are not random but instead reflect the interplay between intra-cellular networks underlying bacterial growth and the growth environment. Therefore, these fluctuations could be considered quantitative phenotypes of the bacteria under a specific growth condition. Here, we present a method to identify "phenotypic signatures" by time-frequency analysis of unbalanced growth curves measured with high temporal resolution. The signatures are then applied to differentiate amongst different bacterial strains or the same strain under different growth conditions, and to identify the essential architecture of the gene network underlying the observed growth dynamics. Our method has implications for both basic understanding of bacterial physiology and for the classification of bacterial strains.

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Published In

PLoS computational biology

DOI

EISSN

1553-7358

ISSN

1553-734X

Publication Date

August 2014

Volume

10

Issue

8

Start / End Page

e1003751

Related Subject Headings

  • Systems Biology
  • Signal Transduction
  • Phenotype
  • Bioinformatics
  • Bioengineering
  • Bacterial Physiological Phenomena
  • Bacteria
  • Algorithms
  • 08 Information and Computing Sciences
  • 06 Biological Sciences
 

Citation

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Tan, C., Smith, R. P., Tsai, M.-C., Schwartz, R., & You, L. (2014). Phenotypic signatures arising from unbalanced bacterial growth. PLoS Computational Biology, 10(8), e1003751. https://doi.org/10.1371/journal.pcbi.1003751
Tan, Cheemeng, Robert Phillip Smith, Ming-Chi Tsai, Russell Schwartz, and Lingchong You. “Phenotypic signatures arising from unbalanced bacterial growth.PLoS Computational Biology 10, no. 8 (August 2014): e1003751. https://doi.org/10.1371/journal.pcbi.1003751.
Tan C, Smith RP, Tsai M-C, Schwartz R, You L. Phenotypic signatures arising from unbalanced bacterial growth. PLoS computational biology. 2014 Aug;10(8):e1003751.
Tan, Cheemeng, et al. “Phenotypic signatures arising from unbalanced bacterial growth.PLoS Computational Biology, vol. 10, no. 8, Aug. 2014, p. e1003751. Epmc, doi:10.1371/journal.pcbi.1003751.
Tan C, Smith RP, Tsai M-C, Schwartz R, You L. Phenotypic signatures arising from unbalanced bacterial growth. PLoS computational biology. 2014 Aug;10(8):e1003751.

Published In

PLoS computational biology

DOI

EISSN

1553-7358

ISSN

1553-734X

Publication Date

August 2014

Volume

10

Issue

8

Start / End Page

e1003751

Related Subject Headings

  • Systems Biology
  • Signal Transduction
  • Phenotype
  • Bioinformatics
  • Bioengineering
  • Bacterial Physiological Phenomena
  • Bacteria
  • Algorithms
  • 08 Information and Computing Sciences
  • 06 Biological Sciences