036 Specific growth rate control in fed-batch baker's yeast fermentation

1994 ◽  
Vol 2 (6) ◽  
pp. 1066
1993 ◽  
Vol 26 (2) ◽  
pp. 185-188
Author(s):  
M. Keulers ◽  
L. Ariaans ◽  
M. Giuseppin ◽  
R. Soeterboek

2004 ◽  
Vol 37 (3) ◽  
pp. 499-504 ◽  
Author(s):  
E. Picó-Marco ◽  
J. Picó ◽  
H. DeBattista ◽  
J.L. Navarro

2017 ◽  
Vol 83 (16) ◽  
Author(s):  
Jasmine M. Bracher ◽  
Erik de Hulster ◽  
Charlotte C. Koster ◽  
Marcel van den Broek ◽  
Jean-Marc G. Daran ◽  
...  

ABSTRACT Biotin prototrophy is a rare, incompletely understood, and industrially relevant characteristic of Saccharomyces cerevisiae strains. The genome of the haploid laboratory strain CEN.PK113-7D contains a full complement of biotin biosynthesis genes, but its growth in biotin-free synthetic medium is extremely slow (specific growth rate [μ] ≈ 0.01 h−1). Four independent evolution experiments in repeated batch cultures and accelerostats yielded strains whose growth rates (μ ≤ 0.36 h−1) in biotin-free and biotin-supplemented media were similar. Whole-genome resequencing of these evolved strains revealed up to 40-fold amplification of BIO1, which encodes pimeloyl-coenzyme A (CoA) synthetase. The additional copies of BIO1 were found on different chromosomes, and its amplification coincided with substantial chromosomal rearrangements. A key role of this gene amplification was confirmed by overexpression of BIO1 in strain CEN.PK113-7D, which enabled growth in biotin-free medium (μ = 0.15 h−1). Mutations in the membrane transporter genes TPO1 and/or PDR12 were found in several of the evolved strains. Deletion of TPO1 and PDR12 in a BIO1-overexpressing strain increased its specific growth rate to 0.25 h−1. The effects of null mutations in these genes, which have not been previously associated with biotin metabolism, were nonadditive. This study demonstrates that S. cerevisiae strains that carry the basic genetic information for biotin synthesis can be evolved for full biotin prototrophy and identifies new targets for engineering biotin prototrophy into laboratory and industrial strains of this yeast. IMPORTANCE Although biotin (vitamin H) plays essential roles in all organisms, not all organisms can synthesize this vitamin. Many strains of baker's yeast, an important microorganism in industrial biotechnology, contain at least some of the genes required for biotin synthesis. However, most of these strains cannot synthesize biotin at all or do so at rates that are insufficient to sustain fast growth and product formation. Consequently, this expensive vitamin is routinely added to baker's yeast cultures. In this study, laboratory evolution in biotin-free growth medium yielded new strains that grew as fast in the absence of biotin as in its presence. By analyzing the DNA sequences of evolved biotin-independent strains, mutations were identified that contributed to this ability. This work demonstrates full biotin independence of an industrially relevant yeast and identifies mutations whose introduction into other yeast strains may reduce or eliminate their biotin requirements.


1993 ◽  
Vol 24 (11) ◽  
pp. 1973-1985 ◽  
Author(s):  
F. Y. ZENG ◽  
B. DAHHOU ◽  
M. T. NIHTILÄ ◽  
G. GOMA

Processes ◽  
2019 ◽  
Vol 7 (11) ◽  
pp. 810 ◽  
Author(s):  
Vytautas Galvanauskas ◽  
Rimvydas Simutis ◽  
Vygandas Vaitkus

This article presents a comparative study on the development and application of two distinct adaptive control algorithms for biomass specific growth rate control in fed-batch biotechnological processes. A typical fed-batch process using Escherichia coli for recombinant protein production was selected for this research. Numerical simulation results show that both developed controllers, an adaptive PI controller based on the gain scheduling technique and a model-free adaptive controller based on the artificial neural network, delivered a comparable control performance and are suitable for application when using the substrate limitation approach and substrate feeding rate manipulation. The controller performance was tested within the realistic ranges of the feedback signal sampling intervals and measurement noise intensities. Considering the efforts for controller design and tuning, including development of the adaptation/learning algorithms, the model-free adaptive control algorithm proves to be more attractive for industrial applications, especially when only limited knowledge of the process and its mathematical model is available. The investigated model-free adaptive controller also tended to deliver better control quality under low specific growth rate conditions that prevail during the recombinant protein production phase. In the investigated simulation runs, the average tracking error did not exceed 0.01 (1/h). The temporary overshoots caused by the maximal disturbances stayed within the range of 0.025–0.11 (1/h). Application of the algorithm can be further extended to specific growth rate control in other bacterial and mammalian cell cultivations that run under substrate limitation conditions.


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