Renaissance of Kinetic Studies in Modern Microbiology

Dear Colleagues,

Kinetic studies deal with process rates, aiming for a better understanding of underlying mechanisms and developing optimal control. It implies a combination of experimental studies with mechanistic mathematical models. This approach is widely accepted in enzymology, where nearly every study requires the fitting of measured reaction rates to one of the alternative kinetic equations (e.g., Michaelis–Menten, Hill, Morrison); as a result, enzymologists can distinguish between different types of inhibition or activation, test various hypotheses, and confidently predict reaction progress. Microbial growth is more complex, encompassing cell multiplication (could be exponential, linear, oscillatory, or decaying), survival and death under stresses, product formation, mutations and genetic sweeps, cell cycles, differentiations (active–dormant, motile–sessile), and other phenomena. Unlike enzymes preserving their kinetic characteristics during reactions, microbial growth is manifested as quantitative (biomass concentration) and qualitative changes (conditional expression of proteins and other cellular constituents). That is why using enzyme kinetics (e.g., the unstructured Monod-type models) started in the last century remains productive only under a narrow range and brings limited success. The proteogenomic revolution offers a promising opportunity to address this drawback and comprehensively incorporate self-regulatory mechanisms in kinetic studies.

This Special Issue is open to a wide range of contributions, including but not limited to the following:

• Development of a methodology to monitor microbial growth dynamics in various cultivation systems, from nano-devices to industrial bioreactors. Especially valuable are the automatic or semi-automatic techniques to record cell biomass, metabolic products, nutrient uptake, and environmental conditions;
• Mathematical simulations of microbial growth using simple and comprehensive models, including genome-scale dynamic reconstructions. Both successful and unsuccessful simulations are acceptable, based on the principle that discarding incorrect hypotheses is the most definite outcome;
• Experimental dynamic studies of microbial growth in batch or continuous cultures, accompanied by transcriptomic, proteomic, and other omics data, with and without parallel mathematical simulations;
• Opinion-style commentaries discussing the philosophy and modern trends in fundamental biokinetic research and its applications in health care and biotechnology.

Dr. Nicolai S. Panikov
Guest Editor

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• growth curves
• kinetics
• latent and stationary phase
• survival and death
• product formation
• spontaneous mutations
• genetic sweeps
• cell cycles
• differentiation into subpopulations
• mathematical simulations
• genome-scale models
• transcriptomics
• proteomics