Phenotypic Signatures Arising from Unbalanced Bacterial Growth

Cheemeng Tan, Robert Phillip Smith, Ming-Chi Tsai, Russell Schwartz and Lingchong You

PLOS Computational Biology, 2014, vol. 10, issue 8, 1-10

Abstract: 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.Author Summary: The measurement of bacterial growth in batch cultures is a routine practice in microbiology. In these cultures, bacterial growth rates drastically fluctuate over time due to the continuously changing growth environment: changing population size, accumulation of waste products, and depletion of nutrients. Such “unbalanced” growth is normally considered undesirable, which has led to the design of methods to achieve balanced growth environments (i.e., chemostats). However, we have discovered that unbalanced growth dynamics contain rich information that can be exploited to deduce regulatory functions or to classify cell strains or growth conditions. We further show that this approach is generally applicable to temporal gene expression data. Taken together, our method and results have broad implications for system identification, experimental design, and the study of cellular growth.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1003751

DOI: 10.1371/journal.pcbi.1003751

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