The
Understanding the complex growth and metabolic dynamics in microorganisms requires advanced kinetic models containing both metabolic reactions and enzymatic regulation to predict phenotypic behaviors under different conditions and perturbations. Most current kinetic models lack gene expression dynamics and are separately calibrated to distinct media, which consequently makes them unable to account for genetic perturbations or multiple substrates. This challenge limits our ability to gain a comprehensive understanding of microbial processes towards advanced metabolic optimizations that are desired for many biotechnology applications. Here, we present an integrated computational and experimental approach for the development and optimization of mechanistic kinetic models for microbial growth and metabolic and enzymatic dynamics. Our approach integrates growth dynamics, gene expression, protein secretion, and gene‐deletion phenotypes. We applied this methodology to build a dynamic model of the growth kinetics in batch culture of the bacterium
- Award ID(s):
- 1726023
- NSF-PAR ID:
- 10236001
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Biotechnology and Bioengineering
- Volume:
- 117
- Issue:
- 12
- ISSN:
- 0006-3592
- Page Range / eLocation ID:
- p. 3876-3890
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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