Indirect monitoring of acetate exhaustion and cell recycle improve lactate production by non-growing Escherichia coli

A two-phase, lactate fermentation by Escherichia coli ALS974 generates succinate and ethanol anaerobically from acetate. These by-products can be minimized by monitoring acetate concentration indirectly with dissolved O₂ (DO) during the initial aerobic cell-growth phase. Without DO monitoring, 3 g succinate/l and 1 g ethanol/l were generated while, with monitoring, less than 1 g succinate/l and no detectable ethanol were generated with 130 g lactate/l being produced. Furthermore, using a cell-recycle fermentation with ultrafiltration prolonged the anaerobic lactate production phase from 22 to 34 h, thereby achieving a lactate productivity of 4.2 g/l h, nearly 20% greater than the productivity of the fed-batch process.     

Biosynthesis of poly (γ-glutamic acid) from l-glutamine,citric acid and ammonium sulfate in Bacillus subtilis IFO3335

Poly(-glutamic acid) (PGA) production in Bacillus subtilis IFO3335 was studied. PGA was only slightly produced from medium (100 ml) containing 2 g citric acid and 0.5 g ammonium sulfate in B. subtilis IFO3335. When 0.01 g/100 ml l-glutamine was added to this medium, a large amount of PGA (0.45 g/100 ml), without any by-products such as polysaccharides, was produced. The changes in cell growth, and PGA, glutamic acid, citric acid and ammonium sulfate concentrations in this medium during cultivation were investigated. It was found that PGA was effectively produced for the short time of 20 h after an induction period and that glutamic acid was scarcely excreted during PGA production. PGA could be effectively produced using this medium containing l-glutamine, citric acid and ammonium sulfate. It is suggested that a small amount of l-glutamine added to the medium activated enzymes in the pathway of PGA synthesis in B. subtilis IFO3335. It can be presumed that the enzyme catalyzing the reaction from 2-oxoglutaric acid to l-glutamic acid was glutamate synthase in this bacterium.     

Lactic acid production by batch fermentation of whey permeate: A mathematical model

Summary The batch fermentation of whey permeate to lactic acid was improved by supplementing the broth with enzyme-hydrolyzed whey protein. A mathematical model based on laboratory results predicts to a 99% confidence limit the kinetics of this fermentation. Cell growth, acid production and protein and sugar use rates are defined in quantifiable terms related to the state of cell metabolism. The model shows that the constants of the Leudeking-Piret model are not true constants, but must vary with the medium composition, and especially the peptide average molecular weight. The kinetic mechanism on which the model is based also is presented.Nomenclature K _i lactic acid inhibition constant (g/l) - K _pr protein saturation constant during cell growth (g/l) - K _pr protein saturation constant during maintenance (g/l) - K _s lactose saturation constant (g/l) - [LA] lactic acid concentration (g/l) - [PR] protein concentration (g/l) - [S] lactose concentration (g/l) - t time (h) - [X] cell mass concentration (g/l) - , fermentation constants of Leudeking and Piret - specific growth rate (l/h) - Y _{g, LA/S} acid yield during cell growth (g acid/g sugar) - Y _{m, LA/S} acid yield during maintenance (g acid/g sugar) - Y _x/pr yield (g cells/g protein) - specific sugar use rate during cell growth (g sugar/h·g cell) - specific sugar use rate during maintenance (g sugar/h·cell)     

Influence of growth conditions on production of capsular and extracellular polysaccharides byRhizobium leguminosarum

The influence of growth rate and medium composition on exopolymer production byRhizobium leguminosarum was studied. When grown in medium containing 10g/l mannitol and 1g/l glutamic acid,Rhizobium leguminosarum biovartrifolii TA-1 synthesized up to 2.0g/l of extracellular polysaccharide (EPS), and up to 1.6g/l of capsular polysaccharide (CPS). Under non-growing cell conditions in medium without glutamic acid, CPS synthesis by strain TA-1 could proceed to 2.1g/l, while EPS-production remained relatively low (0.8g/l). Maximal CPS-yield was 2.9g CPS/l medium in a medium containing 20g/l mannitol and 2g/l glutamic acid. TheEPS-deficient strain R. leguminosarum RBL5515,exo4::Tn5 was able to produce CPS to similar levels as strain TA-1, but CPS-recovery was easier because of the low viscosity of the medium and growth of the cells in pellets. With strain TA-1 in nitrogen-limited continuous cultures with a constant biomass of 500mg cell protein/l, EPS was the most abundant polysaccharide present at every dilution rate D (between 0.12 and 0.02 h^–1). The production rates were 50–100mg/g protein/h for EPS and 15–20mg/g protein/h for CPS. Only low amounts of cyclic -(1,2)-glucans were excreted (10–30 mg/l) over the entire range of growth rates.Abbreviations bv biovar - CPS capsular polysaccharide - EPS extracellular polysaccharide - HM_r high molecular mass - LM_r low molecular mass - YEMCR Yeast Extract-Mannitol-Congo Red agar     

Osmotically-regulated trehalose accumulation and cyclic β-(1,2)-glucan excretion by Rhizobium leguminosarum biovar trifolii TA-1

Rhizobium leguminosarum biovar trifolii TA-1 produced high molecular weight extracellular (EPS) and capsular polysaccharides (CPS) as the main carbohydrate products in a medium (10 g of mannitol and 1 g of glutamic acid per liter) with low osmotic pressure of 0.20 MPa. By increasing the osmotic pressure of the medium with the addition of NaCl or other osmolytes up to 1.44 MPa, the synthesis of EPS and CPS was suppressed. Cyclic -(1,2)-glucans were excreted instead. Concentrations of over 1500 mg of glucans/l medium were produced by a biomass of 520 mg protein at 200 mM NaCl (1.20 MPa). Intracellular cyclic -(1,2)-glucan concentrations remained at 45 to 100 mg/g protein during the stationary phase, independent of the osmotic strength of the medium. Parallel to the increasing osmotic pressure of the medium, the disaccharide trehalose accumulated in the cells as osmo-protectant. Concentrations of up to 130 mg/g protein were reached. Strain TA-1 could tolerate 350 mM NaCl.Abbreviations CPS capsular polysaccharide - EPS extracellular polysaccharide - LM_r low molecular weight - HM_r high molecular weight     

A High Performance Fermentation Process for Citric Acid Production by Aspergillus niger NGGCB-101, Using Vermiculite as an Additive in a Stirred Bioreactor

The present study describes the use of vermiculite for enhanced citric acid productivity by a mutant strain of Aspergillus niger NG^GCB-101 in a stirred bioreactor of 15.0 l capacity. The maximum amount of citric acid (96.10 g/l) was obtained with the control 144 h after mycelial inoculation. To enhance citric acid production, varying levels of vermiculite were added as an additive into the fermentation medium. The best results were observed when 0.20 g/l vermiculite was added into the medium 24 h after inoculation resulting in the production of 146.88 g citric acid monohydrate/l. The dry cell mass and residual sugar were 11.75 and 55.90 g/l, respectively. Mixed mycelial pellets (1.08–1.28 mm, dia) were observed in the fermented culture broth. When the culture grown at different vermiculite levels was monitored for Q _p , Q _s and q _p , there was a significant enhancement (P 0.05) in these variables over the control (vermiculite-free). Based on these results, it is concluded that vermiculite might affect mycelial morphology and subsequent TCA cycle performance to improve carbon source utilization by the mould, basic parameters for high performance citric acid fermentation.     

A fuzzy expert system for the optimization of glutamic acid production

A fuzzy expert system was developed to allow the effective use of semi-quantitative or imprecise information in the determination of the optimal operating conditions of a fermentation process. The system incorporated fuzzy relations representing both the trends of experimental data and semi-quantitative information obtained from the literature. The inference method used consisted primarily of search and reasoning based on fuzzy set theory. The resulting expert system incorporated a generalized inference engine designed to deal with various types of fermentation processes, it only being necessary to alter the knowledge database in order to adapt the system to process modifications. The construction of the knowledge database from experimental data or semi-quantitative information was designed to be carried out semi-automatically using a graphic computer tool.The expert system was applied to the optimization of glutamic acid production by fermentation. The optimal conditions predicted by the expert system were found experimentally to give maximum production.List of Symbols A, B names of objects - A _i , B _i linguistic level of A and B, respectively - E₁, E₂ ordinary sets - I depth of search for inference - I _M maximum of I - M, X, Y names of sets - R ₁, R ₂ fuzzy relations - P_total g amount of glutamic acid production - Pen⁺ h penicillin addition time - S_vp1 h^–1 specific rate of glutamic acid production in 1st production phase - S_vp2 h^–1 specific rate of glutamic acid production in 2nd production phase - T _growth h growth period - T _lag h lag time - T _plag h lag time of production defined in Fig. 6 - T _p1 h period of 1st production - T _p2 h period of 2nd production - T _total h total production time - X _p g average cell mass of production phase - x, y, z real numbers - max(x, y) or x y maximum of x and y - min(x, y) or x y minimum of x and y     

Updated model of the batch acetone-butanol fermentation

Summary The recent models of the Acetone-Butanol fermentation did not adequately describe the culture inhibition by the accumulating metabolites and were unable to simulate the acidogenic culture dynamics at elevated pH levels. The present updated modification of the model features a generalised inhibition term and a pH dependent terms for intracellular conversion of undissociated acids into solvent products. The culture dynamics predictions by the developed model compared well with experimental results from an unconventional acidogenic fermentation ofC. acetobutylicum.Nomenclature A acetone concentration in the fermentation broth, [g/L] - AA total concentration of dissociated and undissociated acetic acid, [g/L] - AA _undiss concentration of undissociated acetic acid, [g/L] - APS Absolute Parameter Sensitivity - AT acetoin concentration in the fermentation broth, [g/L] - B butanol concentration in the fermentation broth, [g/L] - BA total concentration of dissociated and undissociated butyric acid, [g/L] - BA _undiss concentration of undissociated butyric acid, [g/L] - E ethanol concentration in the fermentation broth, [g/L] - f(T) inhibition function as defined in Equation (2) - k ₁ constant in Equation (4), [g substrate/g biomass] - k ₂ constant in Equation (4), [g substrate/(g biomass.h)] - k ₁ constant in Equation (5), [g substrate/(g biomass] - k ₂ constant in Equation (5), [g substrate/(g biomass.h)] - k ₃ constant in Equation (6), [g butyric acid/g substrate] - k ₄ constant in Equation (6), [g butyric acid/(g biomass.h)] - k ₅ constant in Equation (7), [g butanol/g substrate] - k ₆ constant in Equation (8), [g acetic acid/g substrate] - k ₇ constant in Equation (8), [g acetic acid/(g biomass.h)] - k ₈ constant in Equation (9), [g acetone/g substrate] - k ₉ constant in Equation (10), [g ethanol/g substrate] - k ₁₀ constant in Equation (11), [g acetoin/g substrate] - k ₁₁ constant in Equation (12), [g lactic acid/g substrate] - K _I Inhibition constant, [g inhibitory products/L] - ke maintenance energy requirement for the cell, [g substrate/(g biomass.h)] - K _AA acetic acid saturation constant, [g acetic acid/L] - K _BA butyric acid saturation constant, [g butyric acid/L] - K _S Monod's saturation constant, [g substrate/L] - LA lactic acid concentration in the fermentation broth, [g/L] - m _i ,n _i constants in Equation (14) - n empirical constant, dependent on degree of inhibition. - P concentration of inhibitory products (B+BA+AA), [g/L] - P _max maximum value of product concentration to inhibit the fermentation, [g/L] - pK_a equilibrium constant - r _A rate of acetone production, [g acetone/L.h] - r _AA rate of acetic acid production, [g acetic acid/L.h] - r _AT rate of acetoin production, [g acetoin/L.h] - r _B rate of butanol production, [g butanol/L.h] - r _BA rate of butyric acid production, [g butyric acid/L.h] - r _E rate of ethanol production, [g ethanol/L.h] - RPS Relative Parameter Sensitivity - r _LA rate of lactic acid production, [g lactic acid/L.h] - r _S dS/dt=total substrate consumption rate, [g substrate/L.h] - r _S substrate utilization rate, [g substrate/L.h] - S substrate concentration in the fermentation broth, [g substrate/L] - S ₀ initial substrate concentration, [substrate/L] - t time, [h] - X biomass concentration, [g/L] - Y _X yield of biomass with respect to substrate, [g biomass/g substrate] - Y _{P i} yield of metabolic product with respect to substrate, [g product/g substrate] Derivatives dX/dt rate of biomass production, [g biomass/L.h] - dP _i /dt rate of product formation, [g product/L.h] Greek letters specific growth rate of the culture, [h^–1] - I specific growth rate of the culture in the presence of the inhibitory products, [h^–1] - µ_max maximum specific growth rate of the culture, [h^–1]     

Evaluation of butanoic,pentanoic and hexanoic acids as internal standards for analysis of acidic fermentation end-products from Bacillus stearothermophilus by gas-liquid chromatography

The use of butanoic, pentanoic and hexanoic acids as internal standards for chromatographic analysis of complex mixtures of by-products from acidic fermentation, produced by Bacillus stearothermophilus grown in xylose-containing medium, was evaluated. After addition of the internal standards, the aqueous supernatant microbial fermentation fluids were submitted to the derivatisation process with methanol and sulphuric acid at 50° C. Injection of 1-l aliquots of the lower chloroform layer was carried out. The esterified compounds were separated in approximately 14 min by temperature programming on a glass column packed with 10% (w/w) diethyleneglycol adipate and 2% phosphoric acid, and analysed with a flame ionisation detector. Chromatograms of the methyl esters derivates have shown that both pentanoic and hexanoic acids can be used as internal standards for gas-chromatographic analysis of acidic fermentation end-products, since they are well separated and resolved. Under the experimental conditioss established, the methyl ester of butanoic acid was masked by the chloroform peak and so is not a convenient compound for further use.     

Circadian rhythmicity in a fermentation process?

Summary An idea is proposed for the role of the circadian rhythmicity in the control of the oscillatory behavior observed in the growth and product formation during the cell-retention continuous culture of Clostridium acetobutylicum. C. acetobutylicum is highly sensitive to the permeability of the cell membrane. A physical mechanism for the variability of the cytoplasmic membrane has been proposed suggesting that the performance of the cell membrane, due to its liquid crystalline structure, is influenced by the external forces (e.g. earth's magnetic field). A previously developed Physiological State Model was extended by incorporating the effect of external forces on the cell membrane permeability. The new mathematical model could simulate the observed oscillatory behavior of the microbial culture. Some experimental results in support of the theoretical predictions have been presented.Nomenclature a Anisotropy - B Butanol concentration in the fermentation broth (g/l) - B _i Intracellular butanol concentration (g/l) - B _ex Extracellular butanol concentration (g/l) - Mean value of the butyric acid solution concentration (g/l) - BA _i Intracellular butyric acid concentration (g/l) - BA _ex Extracellular butyric acid concentration (g/l) - D Dilution rate (l/h) - H Magnetizing force (oersted) - K Constant in Equation (1) - k B Constant in Equation (15) - K _BA Saturation constant - k _{BA 1} Constant in Equation (13) - k _{BA 2} Constant in Equation (13) - K _D Constant in Equation (13) - k _{G 1} Constant in Equation (8) - k _{G 2} Constant in Equation (8) - k _{G 3} Constant in Equation (9) - K _I Inhibition Constant - k _p Constant in Eq. (11) - K _S Monod constant - n Number of the active sugar transport sites - P Cellular membrane permeability (l/g wet cell·h) - q _S Specific rate of substrate utilization (g substrate/g biomass·h) - S Substrate concentration in the fermentation broth (g/l) - S _O Substrate concentration in the feed solution (g/l) - t Time (h) - X Total biomass concentration (g/l) - X ₁ Active biomass concentration (g/l) - X ₂ Non-active biomass concentration (g/l) Greek Letters Ratio of the dry to wet cell weight (g dry cell/g wet cell) - ₁ Constant in Equation (6) - ₂ Constant in Equation (6) - ₃ Constant in Equation (6) - Specific culture growth rate (1/h)     

Interrelation between penicillin productivity and growth rate

Summary Fermentations were carried out in an 801 tower-loop reactor with pellets of Penicillium chrysogenum. The development of the inner structure of the pellets with regard to various fermentation conditions was observed by means of histological preparations of the pellets. Under conditions of energy-source-limitation mycelial tip growth and lysis of other mycelial parts exist simultaneously. Thus the net growth rate (formation rate of cell mass) is higher than the gross growth rate (multiplication rate of cell mass). Under conditions of nitrogen limitation, gross growth rate and net growth rate are identical. A very strict correlation between gross growth rate and penicillin production rate was found as long as sufficient oxygen supply could be maintained and carbon catabolite repression was avoided. The energy source requirement of the biomass can be described with the sum of three terms that correspond to gross growth, lysis compensation growth and maintenance.Symbols a Constant 1/l h - b Constant - K Decay rate constant for product 1/h - K ₁ Substrate inhibition constant g/l - K _op Controls saturation constant for oxygen g/l - K _p Saturation constant for substrate g/l - m Maintenance coefficient 1/h - ms Apparent maintenance coefficient 1/h - O Dissolved oxygen concentration g/l - P Product concentration g/l - p Exponent of O - q Specific productivity 1/h - S Substrate concentration g/l - t Time h - t ₁ Beginning of production phase h - t ₂ Time of pellet dissolution h - V Liquid volume of fermentation broth l - X Dry cell mass concentration g/l - Y Yield of dry cell mass from energy substrate - g Specific gross growth rate of biomass 1/h - l Specific lysis rate of cell mass 1/h - n Specific net growth rate of cell mass 1/h - p Maximum specific rate of product formation 1/h     

Ethanol fermentation using a glucose negative mutant ofZymomonas mobilis

Summary The fermentation of an equimolar mixture of glucose and fructose into ethanol and sorbitol by a glucose negative mutant ofZymomonas mobilis was monitored. The results were analyzed using a recently described method based on polynomial fitting and calculation of intantaneous and overall parameters. These parameters described well the physiology of this mixed-substrate mixed-product fermentation. Growth of the mutant was greatly inhibited on this medium. Fructose was quantitatively converted into sorbitol while glucose was oxidized into gluconic acid .This latter product was utilized as substrate for cell growth and ethanol production.Nomenclature X biomass concentration, g/l - S total sugar concentration, g/l - Glu glucose concentration, g/l - Fru fructose concentration, g/l - Sor sorbitol concentration, g/l - P ethanol concentration, g/l - t fermentation time, h - specific growth rate, h^-1 - q_s specific sugar uptake rate, g/g.h - q_G specific glucose uptake rate, g/g.h - q_F specific fructose uptake rate, g/g.h - q_P specific ethanol productivity, g/g.h - q_Sor specific sorbitol productivity, g/g.h - Y_X/S biomass yield on total sugar, g/g - Y_P/S ethanol yield on total sugar, g/g - Y_Sor/S sorbitol yield on total sugar, g/g - y_Sor/f sorbitol yield on fructose, g/g - Y_P/G ethanol yield on glucose, g/g     

Continuous production of itaconic acid by Aspergillus terreus immobilized in a porous disk bioreactor

Summary Aspergillus terreus NRRL 1960 was grown on porous disks rotating intermittently in and out of the liquid phase. This immobilized fungal cell bioreactor was used to produce itaconic acid from glucose in a continuous operation. The effect of temperature, pH, disk rotation speed, and feed rate on the itaconic acid concentration and volumetric productivity were studied. The highest itaconic acid concentration and volumetric productivity obtained were 18.2 g/l and 0.73 g/l·h, respectively, under the following conditions: temperature at 36°C, pH 3.0, disk rotation speed at 8 rpm, and feed rate at 60 ml/h. These results are better than those by conventional fermentation or by other immobilized method.Nomenclature F feed rate (l/h) - K _1s saturation constant for immobilized cells (g/l) - K _2s saturation constant for suspended cells (g/l) - M ₁ increased mass of immobilized cells (g) - M ₂ total mass of immobilized cells (g) - P concentration of itaconic acid (g/l) - S substrate concentration in and out of the reactor (g/l) - S ₀ substrate concentration in the feed (g/l) - V liquid volume of the reactor (1) - X concentration of the suspended cells (g/l) - Y ₁ apparent yield of the immobilized cells (g cells/g substrate) - Y ₂ apparent yield of the suspended cells (g cell/g substrate) - Y ₃ apparent yield of itaconic acid (g itaconic acid/g substrate) - m ₁ maintenance and by-products coefficient of the immobilized cells (g substrate/g cell·h) - m ₂ maintenance and by-products coefficient of the suspended cells (g substrate/g cell·h) - µ_1max maximum specific growth rate of the immobilized cells (h^-1) - µ_2max maximum specific growth rate of the suspended cells (h^-1)     

Diagnosing lactic acid fermentation based on specific rates of growth,substrate consumption and product formation

The on-line calculated specific rates of growth, substrate consumption and product formation were used to diagnose microbial activities during a lactic acid fermentation. The specific rates were calculated from on-line measured cell mass, and substrate and product concentrations. The specific rates were more sensitive indicators of slight changes in fermentation conditions than such monitored data as cell mass or product concentrations.List of Symbols 1/h specific rate of cell growth - 1/h specific rate of substrate consumption - 1/h specific rate of product formation - ^* dimensionless specific rate of cell growth - ^* dimensionless specific rate of substrate consumption - ^* dimensionless specific rate of product formation - _max 1/h maximum specific rate of cell growth - _max 1/h maximum specific rate of substrate consumption - _max 1/h maximum specific rate of product formation - X g/l cell mass concentration - S g/l substrate concentration - S ^* dimensionless substrate concentration - S ₀ g/l initial substrate concentration - P g/l product concentration     

Physiological control and process kinetics of clavine alkaloid production byClaviceps purpurea

Summary Kinetic parameters of production of clavine alkaloids were evaluated in twoClaviceps purpurea strains. Mutagenesis brought about enhanced resistance of the biosynthetic system towards alkaloids. Addition of glucose into the fermentation medium altered the zero order kinetics of production to activation-inhibition kinetics. The glucose treatment allowed performance of both elymoclavine-inhibitionless and clavine alkaloid-decompositionless fermentations if a combination of fermentation and separation units in a closed loop was used.Nomenlacture k ₁ rate constant of agroclavine synthesis (mg Agro · mg Elymo/l·g DW·day for stage 1, mg Agro/g DW·day for stage 2) - k ₂ parameter describing inhibition of agroclavine formation rate by elymoclavine (mg Elymo/l) - k ₃ specific rate of agroclavine decay (l/g DW·day) - k ₄ maximal specific rate of elymoclavine synthesis (stage 1, 1/g DW·day, stage 2, mg Elymo/g DW·day) - k ₄ ^– maximal specific rate of elymoclavine synthesis in stage 1 (inhibition-activation mechanism) (mg Elymo/g DW·day) - k ₅ physiological constant describing the elymoclavine decay rate (l²/g DW·day·mg Elymo) - k ₅ ^– physiological constant describing the activation of elymoclavine biosynthesis by elymoclavine (mg Elymo/l) - k ₆ physiological constant describing the repression of elymoclavine biosynthesis by elymoclavine (mg Elymo/l) - k ₇ maximal specific growth rate (1/day) - k ₈ specific rate of biomass decay (l/g DW·day) - A agroclavine concentration (mg/l) - E elymoclavine concentration (mg/l) - r _A specific rate of agroclavine biosynthesis (mg Agro/g DW·day) - r _E specific rate of elymoclavine biosynthesis (mg Elymo/g DW·day) - r _i specific rate of alkaloid biosynthesis (mg alkaloid/g DW·day) - X dry biomass concentration (g/l) - specific growth rate (1/day) Abbreviations Agro agroclavine - Elymo elymoclavine - Chano chanoclavine - DW dry weight of biomass     

Lactose continuous fermentation with cells recycled by ultrafiltration and lactate separation by electrodialysis: model identification

Summary An off-line parameter estimation method has been developed to predict the dynamic behaviour of a continuous lactose fermentation system. The model used is an unstructured model taking into account cell growth, substrate consumption, and metabolite production (lactic acid). This method, based on the Hooke-Jeeves non-linear-programming technique, results in a good estimation of the biological parameters of the model, and so gives a better understanding of the different phenomena involved in lactose fermentation.Nomenclature Cp, Cs, Cz, Dp, Ds, Dz coefficients in system (A) - Fe bioreactor influent flow rate (1/h) - I current in the ED unit (A) - J lactate flux in the ED unit (g/h) - Kd mortality constant (h^-1) - Kp product inhibition constant (g/l) - Ks strbstrate saturation constant (g/l) - P ₀ product concentration in the bioreactor (g/l) - P ₁ product concentration in the D tank (g/l) - P _0r estimation of P ₀ (g/l) - Q ₀ retentate flow rate (UF influent) (1/h) - Q ₁ permeate flow rate (1/h) - Q ₂₂ cell bleed flow rate (1/h) - Q ₃ recycling flow rate in the ED (influent) (1/h) - Se substrate concentration in the influent (g/l) - S ₀ supstrate concentration in the bioreactor (g/l) - S ₁ substrate concentration in tank D (g/l) - S _0r estimation of S ₀ (g/l) - t time (h) - V ₀ fermentation broth volume (1) - V ₁ tank D volume (1) - X ₀ biomass concentration in the bioreactor (g/l) - Y _P/S (=1/Y _S/P) lactic acid yield coefficient (g lactic acid/g lactose consumed) - Y _X/S (=1/Y _S/X) cell yield coefficient (g cells produced/g lactose consumed) - Y _X/Z (=1/Y _Z/X) second cell yield coefficient (g cells produced/g nitrogen consumed) - Y _x, Y _m input mathematical parameters of the linear system (M ₂) - Ze nitrogen concentration in the influent (g/l) - Z ₀ nitrogen concentration in the bioreactor (g/l) - Z ₁ nitrogen concentration in tank D (g/l) - Z _0r estimation of Z ₀ (g/l) - , constants of the Luedeking and Piret's model - specific growth rate (h^-1) - _max maximum specific growth rate (h^-1)     

Enzyme production in a cell recycle fermentation system evaluated by computer simulations

Enzyme production in a cell recycle fermentation system was studied by computer simulations, using a mathematical model of -amylase production by Bacillus amyloliquefaciens. The model was modified so as to enable simulation of enzyme production by hypothetical organisms having different production kinetics at different fermentation conditions important for growth and production. The simulations were designed as a two-level factorial assay, the factor studied being fermentation with or without cell recycling, repression of product synthesis by glucose, kinetic production constants, product degradation by a protease, mode of fermentation, and starch versus glucose as the substrate carbon source.The main factor of importance for ensuring high enzyme production was cell recycling. Product formation kinetics related to the stationary growth phase combined with continuous fermentation with cell recycling also had a positive impact. The effect was greatest when two or more of these three factors were present in combinations, none of them alone guaranteeing a good result. Product degradation by a protease decreased the amount of product obtained; however, when combined with cell recycling, the protease effect was overshadowed by the increased production. Simulation of this type should prove a useful tool for analyzing troublesome fermentations and for identifying production organisms for further study in integrated fermentation systems.List of Symbols a proportionality constant relating the specific growth rate to the logarithm of G (h) - a ₁ reaction order with respect to starch concentration - a ₂ reaction order with respect to glucose concentration - c starch concentration (g/l) - c ₀ starch concentration in the feed (g/l) - D dilution rate (h^–1) - e intrinsic intracellular amylase concentration (g product/g cell mass) - E extracellular amylase concentration (g/l) - F volumetric flow rate (l/h) - G average number of genome equivalents of DNA/cell - K ₁ intracellular repression constant - K ₂ intracellular repression constant - K _s Monod saturation constant (g/l) - k ₃ product excretion rate constant (h^–1) - k _I translation constant (g product/g mRNA/h) - k _d first order decay constant (h^–1) - k _dw first order decay constant (h^–1) - k _gl rate constant for glucose production (g/l/h) - k _{m, dgr} saturation constant for product degradation (g/l) - k _st rate constant for starch hydrolysis (g/l/h) - k _t1 proportionality constant for amylase production (g mRNA/g substrate) - k _t2 proportionality constant for amylase production (g mRNA *h/g substrate) - k _w protease excretion rate constant (h^–1) - k _wt1 proportionality constant for protease production (g mRNA/g substrate) - k _wt2 proportionality constant for protease production (g mRNA *h/g substrate) - k _wI translation constant (g protease/g mRNA/h) - m maintenance coefficient (g substrate/g cell mass/h) - n number of binding sites for the co-repressor on the cytoplasmic repressor - Q repression function, K₁/K₂ less than or equal to 1.0 - Q _w repression function, K₁/K₂ less than or equal to 1.0 - r intrinsic amylase mRNA concentration (g mRNA/g cell mass) - r _m intrinsic protease mRNA concentration (g mRNA/g cell mass) - R _ex retention by the filter of the compounds x=: C starch, E amylase, or S glucose - R _t amylase transport rate (g product/g cell mass/h) - R _wt protease transport rate (g protease/g cell mass/h) - R _s rate of glucose production (g/l/h) - R _c rate of starch hydrolysis (g/l/h) - S ₀ feed concentration of free reducing sugar (g/l) - s extracellular concentration of reducing sugar (g/l) - t time (h) - V volume (1) - w intracellular protease concentration (g/l) - W extracellular protease concentration (g/l) - X cell mass concentration (dry weight) (g/l) - Y yield coefficient (g cell mass/g substrate) - substrate uptake (g substrate/g cell mass/h) - specific growth rate of cell mass (h^–1) - _d specific death rate of cells (h^–1) - _m maximum specific growth rate of cell mass (h^–1) - _m,dgr maximum specific rate of amylase degradation (h^–1) This study was supported by the Nordic Industrial Foundation Bioprocess Engineering Programme and the Center for Process Biotechnology, The Technical University of Denmark.     

Production of optically pure d-lactic acid from brown rice using metabolically engineered Lactobacillus plantarum

Simultaneous saccharification and fermentation (SSF) of d-lactic acid was performed using brown rice as both a substrate and a nutrient source. An engineered Lactobacillus plantarum NCIMB 8826 strain, in which the ʟ-lactate dehydrogenase gene was disrupted, produced 97.7 g/L d-lactic acid from 20% (w/v) brown rice without any nutrient supplementation. However, a significant amount of glucose remained unconsumed and the yield of lactic acid was as low as 0.75 (g/g-glucose contained in brown rice). Interestingly, the glucose consumption was significantly improved by adapting L. plantarum cells to the low-pH condition during the early stage of SSF (8–17 h). As a result, 117.1 g/L d-lactic acid was produced with a high yield of 0.93 and an optical purity of 99.6% after 144 h of fermentation. SSF experiments were repeatedly performed for ten times and d-lactic acid was stably produced using recycled cells (118.4–129.8 g/L). On average, d-lactic acid was produced with a volumetric productivity of 2.18 g/L/h over 48 h.

     

Start-up sensitivity to the initial state of a batch bioreactor for a recombinant Escherichia coli in a complex medium

The sensitivities with respect to the initial state of five key variables describing the performance of a batch bioreactor have been computed from an experimentally validated kinetic model. The system has a recombinant Escherichia coli strain containing the plasmid pBR Eco gap, which codes for glyceraldehyde-3-phosphate dehydrogenase (GAPDH) in a complex medium. Since previous studies have shown the start-up sensitivities to be particularly important, the initial 10% of the duration of fermentation was chosen as the time span. The sensitivities of the cell mass, GAPDH and acetate increased with time while those of glucose and yeast extract remained practically constant.Acetate has a crucial role as it functions as both a product and a reactant. With no acetate in the inoculum, the sensitivities of acetate increased an order of magnitude faster than other sensitivities. However, upon addition of acetate through the inoculum, its sensitivities decreased the fastest and stabilised beyond a starting concentration of about 1 g/l whereas other sensitivities stabilised after 5 to 6 g/l of initial acetate. A three-dimensional envelope in the space of acetate concentration-time-relative sensitivity shows a locus of concentrations for minimum time-dependent acetate sensitivity; this may be maintained through fed-batch operation.List of Symbols a A/A₀ - A g/l initial concentration at any time - A ₀ g/l initial acetate concentration - e E/E₀ - E g/l yeast extract concentration at any time - E ₀ g/l initial yeast extract concentration - g G/G₀ - G g/l glucose concentration at any time - G ₀ g/l initial glucose concentration - k _A ^A g/l inhibition constant for acetate-dependent growth during the acetate phase - k _A ^G g/l inhibition constant for acetate-dependent growth during the glucose phase - k _M ^A 1/h rate constant for acetate phase - k _M ^G 1/h rate constant for glucose phase - K _A g/1 affinity constant for acetate - K _G g/1 affinity constant for glucose - m ^A 1/h coefficient of maintenance in acetate - m _m ^A 1/h maximum value of m ^A - m ^G 1/h coefficient of maintenance in glucose - m _m ^G 1/h maximum value of m ^G - n empirical constant - P P/P₀ - P U/ml GAPDH concentration at any time - P ₀ U/ml initial GAPDH concentration - s _c (i,j) sensitivity of y _i to y _j(0) for A ₀=c - t h time - x X/X₀ - X g/l cell mass concentration at any time - X ₀ g/l initial cell mass concentration - y ₁ x - y₂ g - y₃ a - y₄ e - y ₅ p - y _x/A ^A g/g yield coefficient for cell mass per unit mass of acetate during acetate phase - y _x/A ^G g/g yield coefficient for cell mass per unit mass of acetate during glucose phase - y _x/G g/g yield coefficient for cell mass per unit mass of glucose - y _E/x ^A g/g yield coefficient for yeast extract per unit cell mass during acetate phase - y _P/x ^A g/g yield coefficient for yeast extract per unit cell mass during glucose phase - y _P/x ^A U/g yield coefficient for GAPDH per unit cell mass during acetate phase - y _P/x ^G U/g yield coefficient for GAPDH per unit cell mass during glucose phase Greek Letters ₀ proportionality constant for plasmid loss probability - ₁ 1/h maximum rate of plasmid replication - ₂ 1/h saturation constant of the host component of plasmid replication - regulation function (0 or 1) - regulation function (0 or 1) - exponent of growth inhibition term for acetate during the acetate phase - exponent of growth inhibition term for acetate during the glucose phase - ^A 1/h specific growth rate during acetate phase - _m ^A 1/h maximum value of ^A - ^G 1/h specific growth rate during glucose phase - _m ^G 1/h maximum value of ^G - _c (i,j) ratio of sensitivities, s _c (i,j)/s ₀(i,j) - nondimensional time, t _m ^G      

Ethanol fermentation using a fructose-negative mutant of Zymomonas mobilis

Summary The fermentation of an equimolar mixture of glucose and fructose into ethanol and sorbitol by a fructose negative mutant of Zymomonas mobilis is analysed using a recently described methodology (Ait-Abdelkader and Baratti, Biotechnol. Tech. 1993,329–334) based on polynomial fitting and calculation of instantaneous and overall parameters. These parameters are utilized to describe this mixed-substrate mixed-product fermentation.Nomenclature X biomass concentration, g/l - S total sugar concentration, g/l - Glu glucose concentration, g/l - Fru fructose concentration, g/l - Sor sorbitol concentration, g/l - P ethanol concentration, g/l - t fermentation time, h - specific growth rate, h^-1 - q_s specific sugar uptake rate, g/g.h - q_g specific glucose uptake rate, g/g.h - q_F specific fructose uptake rate, g/g.h - q_P specific ethanol productivity, g/g.h - q_Sor specific sorbitol productivity, g/g.h - Y_X/S biomass yield on total sugar, g/g - Y_P/S ethanol yield on total sugar, g/g - Y_Sor/S sorbitol yield on total sugar, g/g - Y_Sor/F sorbitol yield on fructose, (g/g) - Y_P/G ethanol yield on glucose, (g/g)