Optimization and scale up of industrial fermentation processes
Abstract
To increase product yields and to ensure consistent product quality, key issues of industrial fermentations, process optimization and scale up are aimed at maintaining optimum and homogenous reaction conditions minimizing microbial stress exposure and enhancing metabolic accuracy. For each individual product, process and facility, suitable strategies have to be elaborated by a comprehensive and detailed process characterization, identification of the most relevant process parameters influencing product yield and quality and their establishment as scale-up parameters to be kept constant as far as possible. Physical variables, which can only be restrictedly kept constant as single parameters, may be combined with other pertinent parameters to appropriate mathematical groups or dimensionless terms. Process characterization is preferably based on real-time or near real-time data collected by in situ and on-line measurements and may be facilitated by supportive approaches and tools like neural network based chemometric data analysis and modelling, clarification of the mixing and stream conditions through computational fluid dynamics and scale-down simulations. However, as fermentation facilities usually are not strictly designed according to scale-up criteria and the process conditions in the culture vessels thus may differ significantly and since any strategy and model can only insufficiently consider and reflect the highly complex interdependence and mutual interaction of fermentation parameters, successful scale up in most cases is not the result of a conclusive and straight-lined experimental strategy, but rather will be the outcome of a separate process development and optimization on each scale. This article gives an overview on the problems typically coming along with fermentation process optimization and scale up, and presents currently applied scale-up strategies while considering future technologies, with emphasis on Escherichia coli as one of the most commonly fermented organisms.
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In a 1997 study, E. coli was evolved in chemostat cultures in order to select for improved growth on glycerol; the authors reported phenotypic changes in terms of colony morphology accompanied with increased growth rate and biomass yield and decreased acetate formation.
“In a 1997 study, E. coli was evolved in chemostat cultures in order to select for improved growth on glycerol. The authors reported phenotypic changes in terms of colony morphology accompanied with increased growth rate and biomass yield and decreased acetate formation [50].”
From Adaptive laboratory evolution—Principles and applications for biotechnology (2013) · cites this paper as [50]
Glycerol-limited growth led to stable mutants in a single E. coli population; one mutant showed increased growth in glycerol-sufficient batch cultures and a second mutant did not; the mutant with increased batch growth also showed increased fitness under general nutrient limitation, heat and osmotic stress.
“Glycerol-limited growth led to stable mutants in a single E. coli population, where one mutant showed increased growth in glycerol-sufficient batch cultures and a second mutant did not. Furthermore, the mutant that showed increased growth in batch culture also showed increased fitness under general nutrient limitation, heat and osmotic stress [50].”
From Adaptive laboratory evolution—Principles and applications for biotechnology (2013) · cites this paper as [50]
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- Authors
- Schmidt, F. R.
- Affiliations
- Sanofi (Germany) (DE)
- Corresponding author
- Schmidt, F. R.
- Venue
- Applied Microbiology and Biotechnology
- Published
- 2005-07-07
- Volume
- 68
- Issue
- 4
- Pages
- 425-435
- ISSN
- 0175-7598 (ISSN-L)
- 1432-0614
- OpenAlex
- W2024244058
- Cited by
- 362
- References
- 100
- Citations by year
- 2026: 23 · 2025: 37 · 2024: 29 · 2023: 25 · 2022: 20 · 2021: 18 · 2020: 24 · 2019: 19 · 2018: 26 · 2017: 18 · 2016: 19 · 2015: 12 · 2014: 12 · 2013: 12 · 2012: 17
- FWCI
- 0.67
- Type
- journal article
- Language
- en
- Update notices
- erratum (2005-10-01)
- Open access
- closed
- Locations
- Applied Microbiology and Biotechnology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Fluid Dynamics and Mixing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Viral Infectious Diseases and Gene Expression in Insects
- Keywords
- industrial fermentation, process optimization, scale-up, process characterization, microbial stress, product yield, product quality, in situ monitoring, online measurement, chemometrics, artificial neural networks, computational fluid dynamics, Escherichia coli, dimensionless parameters
- MeSH terms
- Computer Simulation, Facility Design and Construction, Fermentation, Industrial Microbiology, Cell Culture Techniques, Bioreactors
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