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.
| Original language | American English |
|---|---|
| Article number | e1003751 |
| Journal | PLoS Computational Biology |
| Volume | 10 |
| Issue number | 8 |
| DOIs | |
| State | Published - Aug 7 2014 |
Bibliographical note
Publisher Copyright:© 2014 Tan et al.
Funding
Funding: This work was partially supported by a National Science Foundation CAREER Award (CBET-0953202, LY), the National Institutes of Health (1RO1GM098642 (LY), 1R01AI076318 (RS), 1R01CA140214 (RS), the Office of Naval Research (N00014-12-1-0631), a DuPont Young Professorship (LY), a David and Lucile Packard Fellowship (LY), a Medtronic Fellowship (CT), a Lane Fellowship (CT), and a Branco-Weiss Fellowship (CT).The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
| Funders | Funder number |
|---|---|
| National Science Foundation | CBET-0953202 |
| National Institutes of Health | 1RO1GM098642, 1R01AI076318, 1R01CA140214 |
| Office of Naval Research | N00014-12-1-0631 |
| National Institute of Biomedical Imaging and Bioengineering | T32EB009403 |
| DuPont |
ASJC Scopus Subject Areas
- Ecology, Evolution, Behavior and Systematics
- Modeling and Simulation
- Ecology
- Molecular Biology
- Genetics
- Cellular and Molecular Neuroscience
- Computational Theory and Mathematics
Keywords
- Bacterial Genetics
- Bacterial Growth
- Bacterial Pathogens
- Bacterial Physiology
- Cell Signaling
- Gene Expression
- Perturbation (geology)
- Wavelet Transforms
- Bacteria/growth & development
- Bioengineering
- Signal Transduction
- Bacterial Physiological Phenomena
- Phenotype
- Algorithms
- Systems Biology/methods
Disciplines
- Biology
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