Journal
IET SYSTEMS BIOLOGY
Volume 14, Issue 2, Pages 68-74Publisher
INST ENGINEERING TECHNOLOGY-IET
DOI: 10.1049/iet-syb.2018.5125
Keywords
microorganisms; temperature; environmental factors; mean square error methods; parameter estimation; bacterial growth rate; dynamic temperature changes; bacterial species; bacterial growth profiles; generalised logistic growth model; escherichia coli; model parameter estimation; coefficient of determination; mean square error; environmental conditions
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Funding
- Science and Engineering Research Board [SB/FTP/ETA-0152/2013]
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Temperature is an important determinant of bacterial growth. While the dependence of bacterial growth on different temperatures has been well studied for many bacterial species, prediction of bacterial growth rate for dynamic temperature changes is relatively unclear. Here, the authors address this issue using a combination of experimental measurements of the growth, at the resolution of 5min, of Escherichia coli and mathematical models. They measure growth curves at different temperatures and estimate model parameters to predict bacterial growth profiles subject to dynamic temperature changes. They compared these predicted growth profiles for various step-like temperature changes with experimental measurements using the coefficient of determination and mean square error and based on this comparison, ranked the different growth models, finding that the generalised logistic growth model gave the smallest error. They note that as the maximum specific growth increases the duration of this growth predominantly decreases. These results provide a basis to compute the dependence of the growth rate parameter in biomolecular circuits on dynamic temperatures and may be useful for designing biomolecular circuits that are robust to temperature.
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