Corynebacterium glutamicum - JUWEL - Forschungszentrum Jülich

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G. Alternative Off-line Optimized Production Experiments The experiment in paragraph 5.2.6 on page 116 was designed by optimizing the expected total volumetric productivity with an extra limitation with respect to the maximal biomass concentration: the OD600 should stay below 70. Without this extra limitation, much higher biomass concentration were expected, as shown in paragraph G.1. Besides the total volumetric productivity, also other criteria could be of interest for process optimization. For instance a maximal final product concentration or the absence of problematic by-products are often of interest to facilitate the down-stream processing. The overall yield of product on substrate can be of interest when substrate costs form a significant part of the production costs. As another example, this overall yield is also optimized off-line just like the total volumetric productivity. The suggested experiment is mentioned in paragraph G.2. G.1. Total Volumetric Productivity The optimized process with respect to the total volumetric productivity, without the extra limitation on the maximal optical density, is shown in figure G.1, together with the expected results. This experiment could not be performed due to limitations with respect to the oxygen transfer between the gas phase and the liquid phase in the used fermentation equipment. The expected maximal total volumetric productivity was with 14.0 mM.h −1 higher than the expected value with the extra limitation on the biomass concentration, which was 10.2 mM.h −1 . 173
G. Alternative Off-line Optimized Production Experiments feed [L.h −1 ] 0.08 0.06 0.04 0.02 0 0 5 10 15 20 25 time [h] 0 0 5 10 15 20 25 time [h] (a) Suggested experiment. Feed rates of a 500 (b) Expected results of the suggested experiment. g/L glucose solution as a solid line and of a Biomass in OD600 as ×, glucose in mM as ∗ and 55 mM L-isoleucine solution as a dashed line. Ini- L-valine in mM as +. tial concentrations were 50 g/L glucose, 10 mM L-isoleucine and 4.60 µM pantothenic acid. No further feed of pantothenic acid was needed. Figure G.1.: Suggested experiment for a maximized TVP, without limitations with respect to the biomass concentration. G.2. Overall Yield of Product on Substrate Optimization of the yield of product on substrate suffers from the risk of suggesting very low final product concentrations because of the positive effect of using little substrate for biomass production. Since this can not be a realistic optimal process, a penalty function was introduced to prevent such very low final product concentrations. The used optimization criterion was ξ ∗ =argmax ξ Pend Sused,int biomass [OD 600 ], glc [mM], val [mM] 400 300 200 100 � fs · (Pmin − Pend) : Pend
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Lebenswissenschaften Life Sciences
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Forschungszentrum Jülich GmbH Inst
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’Therefore, mathematical modeling
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Contents 3.4. Application: L-Valine
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Contents 4
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1. Introduction need for improved m
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2. Theory In a batch process, all s
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2. Theory 1997; Goncalves et al., 2
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2. Theory For batch fermentations,
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2. Theory with Yps being the yield
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2. Theory Inhibition Some catalytic
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2. Theory The method of least squar
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2. Theory evaluation can be made by
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2. Theory We define the measured or
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2. Theory build in the model. An ob
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2. Theory nations, the researcher i
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2. Theory W = J · Covθ · J T (2.
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2. Theory arg max ξ � m� m�
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2. Theory with all measured values
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2. Theory which can be estimated us
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2. Theory One option to account for
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2. Theory θ 2 $θ 2 0 area ≅ det
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2. Theory designed using a paramete
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2. Theory proteome14 (Hermann et al
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2. Theory 44
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3. Dynamic Modeling Framework itera
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3. Dynamic Modeling Framework 3.3.
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3. Dynamic Modeling Framework 3.3.3
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3. Dynamic Modeling Framework 52 du
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3. Dynamic Modeling Framework the c
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3. Dynamic Modeling Framework For d
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3. Dynamic Modeling Framework subse
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3. Dynamic Modeling Framework 60
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4. Simulative Comparison of Model D
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5. L-Valine Production Process Deve
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Page 129 and 130: 5. L-Valine Production Process Deve
Page 140 and 141: A. Nomenclature Table A.1.: Symbols
Page 142 and 143: Table A.1.: Symbols and Abbreviatio
Page 144 and 145: Table A.1.: Symbols and Abbreviatio
Page 146 and 147: B. Ratio between OD600 and Dry Weig
Page 148 and 149: C. The Influence of the Oxygen Supp
Page 150 and 151: The measurements of amino acids and
Page 152 and 153: kiv [mM] lac [mM] 15 10 5 0 0 10 20
Page 154 and 155: OTR, CTR 0.06 0.04 0.02 0 0 10 20 3
Page 156 and 157: DO properly at a low value in dynam
Page 158 and 159: D. Dilution for Measurement of Amin
Page 160 and 161: E. Models used in the First Model D
Page 162 and 163: Model 1.6 Model 1.6 is similar to m
Page 164 and 165: Table E.1: Model Parameters of the
Page 166 and 167: Table E.2: Model Parameters of the
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Page 170 and 171: Model 2.2 Model 2.2 is similar to m
Page 172 and 173: Table F.1.: Model Parameters of the
Page 174 and 175: Table F.2.: Estimated Lag-Times of
Page 176 and 177: Table F.3: Model Parameters of the
Page 178 and 179: Table F.4.: Estimated Lag-Times of
Page 182 and 183: G.2. Overall Yield of Product on Su
Page 184 and 185: Summary Fast development of product
Page 186 and 187: Zusammenfassung Es ist wichtig, die
Page 188 and 189: Acknowledgements This thesis result
Page 190 and 191: Bibliography K. Akashi, H. Shibai,
Page 192 and 193: Bibliography A. Bodalo-Santoyo, J.L
Page 194 and 195: Bibliography A.J. Cooper, J.Z. Gino
Page 196 and 197: Bibliography A.G. Fredrickson, R.D.
Page 198 and 199: Bibliography W.G. Hunter and A.M. R
Page 200 and 201: Bibliography A.C. McHardy, A. Tauch
Page 202 and 203: Bibliography E. Radmacher, A. Vaits
Page 204 and 205: Bibliography K.J. Versyck, J.E. Cla
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Corynebacterium glutamicum - JUWEL - Forschungszentrum Jülich

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