Growth of Dioscorea deltoidea at high sugar concentrations

Dioscorea deltoidea cell suspension cultures were grown at initial sucrose concentrations of 35 to 200 g/L. The growth rates were similar (about 0.50 day^–1) with all of the initial sugar concentrations examined. The ratio of fresh weight to dry weight of cells was dependent on the initial sugar concentration, however, it remained fairly constant as long as the sugar was present in the growth medium. These results are different from results recently published, claiming that the growth rate of D. deltoidea cells is dependent on sugar concentration and the fresh weight to dry weight ratio increases throughout growth.     

Linear growth in microbial cultures limited by accumulated substrate

Summary The linear growth phase in cultures limited by intracellular (conservative) substrate is represented by a flat exponential curve. Within the range of experimental errors, the presented model fits well the data from both batch and continuous cultures ofEscherichia coli, whose growth is limited in that way.List of symbols D dilution rate, h^–1 - K_S saturation constant, g.L^–1 - S concentration of the limiting substrate, g.L^–1 - S_i concentration of the limiting substrate accumulated in the cells, g.g^–1 - S_o initial concentration of the limiting substrate, g.L^–1 - t time of cultivation, h - t₁ time of exhaustion of the limiting substrate from medium, h - t_o beginning of exponential phase, h - X biomass concentration, g.L^–1 - X₁ biomass concentration at the time of exhaustion of the limiting substrate from the medium, g.L^–1 - X_o biomass concn. at the beginning of exponential phase, g.L^–1 - biomass concn. at steady-state, g.L^–1 - Y growth yield coefficient (biomass/substrate) - specific growth rate, h^–1 - _m maximum specific growth rate, h^–1     

Optimization of Nutritional Factors for Exopolysaccharide Production by Submerged Cultivation of the Medicinal Mushroom Oudemansiella radicata

Summary Effects of nutritional factors on exopolysaccharide production by submerged cultivation of the medicinal mushroom Oudemansiella radicata were investigated in shake flasks. Sucrose and peptone were optimal carbon and nitrogen sources for cell growth and exopolysaccharide production. The exopolysaccharide production was increased with an increase in initial sucrose concentration within the range of 10–40 g l⁻¹ and initial peptone concentration within the range of 1–3 g l⁻¹. To enhance further exopolysaccharide production, the effect of carbon/nitrogen ratios was studied using central composite design (CCD) and response surface analysis. The maximum exopolysaccharide production of 2.67 ± 0.15 g l⁻¹ was achieved in medium with optimized carbon and nitrogen sources, i.e. 39.3 g sucrose l⁻¹ and 3.16 g peptone l⁻¹ in the same cultivation conditions. The information obtained is helpful for the hyperproduction of exopolysaccharide by submerged cultivation of O. radicata on a large scale.     

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.     

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     

Mathematical modeling of production of microbial lipids

In the microbial lipid production system using the yeast Rhodotorula gracilis, CFR-1, kinetics of lipid accumulation and substrate utilisation at initial substrate concentrations in the range of 20–100 kg/m³ were investigated using shake flask experiments. A mathematical representation based on logistic model for biomass and Luedeking-Piret model for lipid accumulation gave reasonably good agreement between the theoretical and experimental values for substrate concentration less than 60 kg/m³. The kinetic expressions and parameters obtained through shake flask studies were directly applied to experiments in the laboratory fermentors also and the models were found to hold good for the prediction of the change of biomass, product as well as substrate with time. The attainment of a saturation in the intracellular lipid accumulation with time, however, was not predicted by the model which was shown to be an inherent feature of the Luedeking-Piret model.List of Symbols S ₀, P ₀ kg/m³ Initial concentrations of sugar and lipid respectively - S, S(t) kg/m³ Concentrations of sugar and lipid respeclively at any timet - p,p(t) L kg/m³ Maximum concentration of lipid produced - E % Maximum sugar utilised - dP/dt kg/(m³ · h) Rate of lipid production - -dS/dt kg/(m³ · h) Rate of sugar utilisation - _max h^–1 Maximum specific growth rate - X _max kg/m³ Maximum biomass reached in a run - P _max kg/m³ Maximum product concentration - m, n Constants used in Luedeking-Piret model in eq. (7) - , Constants used to predict residual sugar - k _e maintainance coefficient - Y _x g/g Biomass yield based on sugar consumed - Y _p g/g Lipid yield based on sugar consumed - (dP/d t)_stat kg/(m³ · h) Rate of lipid production at stationary phase - (dS/dt)_stat kg/(m³ · h) Rate of sugar utilisation at stationary phase     

Exocellular polysaccharide production by isolates ofEpicoccum purpurascens

Of 102 naturally occuring isolates of the fungusEpicoccum purpurascens screened for exopolysaccharide production, 51 proved positive. The product is a -glucan; yields were up to 0.36 kg kg^–1 d.wt mycelium, depending on culture conditions.     

Culture medium optimization for improved puerarin production by cell suspension cultures of Pueraria tuberosa (Roxb. ex Willd.) DC.

The effects of carbon, nitrogen, phosphate, and copper on cell growth and production of the isoflavone puerarin by suspension cultures of Pueraria tuberosa (Roxb. ex. Willd.) DC were investigated. Among the various sugars evaluated (glucose, galactose, fructose, maltose, and sucrose), use of sucrose in the medium led to the maximum accumulation of puerarin. A sucrose-feeding strategy in which additional sucrose was added to the flasks 15?d into the culture cycle stimulated both cell biomass and puerarin production. The maximum production of puerarin was obtained when a concentration balance of 20:60?mM NH ₄ ⁺ /NO ₃ ^? was used as the nitrogen source. Alteration in the concentration balance of nitrogen components (NH ₄ ⁺ /NO ₃ ^? 60:20?mM) or the use of either NH ₄ ⁺ or NO ₃ ^? alone decreased biomass production and puerarin accumulation compared with the control culture (NH ₄ ⁺ /NO ₃ ^? 20:20?mM). High amounts of phosphate (2.5 and 5?mM) in the medium inhibited puerarin production whereas 0.625?mM phosphate promoted puerarin production (68.3???g/g DW on day?25). An increase in Cu²⁺ concentration from 0.025 to 0.05?mg/l in the P. tuberosa cell culture medium resulted in a 2.2-fold increase in puerarin production (up to 141???g/g DW on day?25) but reduced cell culture biomass.     

The effect of pH on kinetic and yield parameters during the ethanolic fermentation of D-xylose with Pachysolen tannophilus

We have studied the ethanolic fermentation of D-xylose with Pachysolen tannophilus in batch cultures. We propose a model to predict variations in D-xylose consumed, and biomass and ethanol produced, in which we include parameters for the specific growth rate, for the consumption of D-xylose and production of ethanol either related or not to growth.The ideal initial pH for ethanol production turned out to be 4.5. At this pH value the net specific growth rate was 0.26 h^–1, biomass yield was 0.16 g.g^–1, the cell-maintenance coefficient was 0.073 g.g^–1.h^–1, the parameter for ethanol production non-related to growth was 0.064 g.g^–1,h^–1 and the maximum ethanol yield was 0.32 g.g^–1.List of Symbols A _c Carbon atomic weight - a _d1/h Specific cell-maintenance rate defined in Eq. (8) - c Mass fraction of carbon in the biomass - E g/l Ethanol concentration - f _x Correction factor defined in Eq. (13) - f _x Correction factor defined in Eq. (13) - f _xi Correction factor defined in Eq. (14) - k _d1/h Death constant - M _E Ethanol molecular weight - M _s Xylose molecular weight - M _xi Xylitol molecular weight - m g xylose/g biomass Maintenance coefficient for substrate - m _dg xylose/g biomass Maintenance coefficient when k _d - q _Eg ethanol/g biomass. Specific ethanol production rate - s g/l Residual xylose concentration - s ₀ g/l Initial xylose concentration - t h Time - x g/l Biomass concentration - x ₀ g/l Initial biomass concentration - Y _E/sg ethanol/g xylose Instantaneous ethanol yield - ¯Y _E/sg ethanol/g xylose Mean ethanol yield - Y _E ^s/T g ethanol/g xylose Theoretical ethanol yield - Y _E ^s/* g ethanol/g xylose Corrected instantaneous ethanol yield - ¯Y _E ^s/* g ethanol/g xylose Corrected mean ethanol yield - Y _x/sg biomass/g xylose Biomass yield - ¯Y _xi/sg xylitol/g xylose Mean xylitol yield Greek Letters g ethanol/g biomass Growth-associated product formation parameter - g ethanol/g biomass.h Non-growth-associated product formation parameter - _dg ethanol/g biomass.h Non-growth-associated product formation parameter when k _d0 - h Variable defined in Eq. (6) or Eq. (7) - 1/h Specific growth rate - _m1/h Maximum specific growth rate     

Modeling of the pyruvate production with<Emphasis Type="Italic"> Escherichia coli</Emphasis> in a fed-batch bioreactor

A family of 10 competing, unstructured models has been developed to model cell growth, substrate consumption, and product formation of the pyruvate producing strain Escherichia coli YYC202 ldhA::Kan strain used in fed-batch processes. The strain is completely blocked in its ability to convert pyruvate into acetyl-CoA or acetate (using glucose as the carbon source) resulting in an acetate auxotrophy during growth in glucose minimal medium. Parameter estimation was carried out using data from fed-batch fermentation performed at constant glucose feed rates of q_VG=10 mL h^–1. Acetate was fed according to the previously developed feeding strategy. While the model identification was realized by least-square fit, the model discrimination was based on the model selection criterion (MSC). The validation of model parameters was performed applying data from two different fed-batch experiments with glucose feed rate q_VG=20 and 30 mL h^–1, respectively. Consequently, the most suitable model was identified that reflected the pyruvate and biomass curves adequately by considering a pyruvate inhibited growth (Jerusalimsky approach) and pyruvate inhibited product formation (described by modified Luedeking–Piret/Levenspiel term).List of symbols c_A acetate concentration (g L^–1) - c_A,0 acetate concentration in the feed (g L^–1) - c_G glucose concentration (g L^–1) - c_G,0 glucose concentration in the feed (g L^–1) - c_P pyruvate concentration (g L^–1) - c_P,max critical pyruvate concentration above which reaction cannot proceed (g L^–1) - c_X biomass concentration (g L^–1) - K_I inhibition constant for pyruvate production (g L^–1) - K_I^A inhibition constant for biomass growth on acetate (g L^–1) - K_P saturation constant for pyruvate production (g L^–1) - K_P inhibition constant of Jerusalimsky (g L^–1) - K_S^A Monod growth constant for acetate (g L^–1) - K_S^G Monod growth constant for glucose (g L^–1) - m_A maintenance coefficient for growth on acetate (g g^–1 h^–1) - m_G maintenance coefficient for growth on glucose (g g^–1 h^–1) - n constant of extended Monod kinetics (Levenspiel) (–) - q_V volumetric flow rate (L h^–1) - q_VA volumetric flow rate of acetate (L h^–1) - q_VG volumetric flow rate of glucose (L h^–1) - r_A specific rate of acetate consumption (g g^–1 h^–1) - r_G specific rate of glucose consumption (g g^–1 h^–1) - r_P specific rate of pyruvate production (g g^–1 h^–1) - r_P,max maximum specific rate of pyruvate production (g g^–1 h^–1) - t time (h) - V reaction (broth) volume (L) - Y_P/G yield coefficient pyruvate from glucose (g g^–1) - Y_X/A yield coefficient biomass from acetate (g g^–1) - Y_X/A,max maximum yield coefficient biomass from acetate (g g^–1) - Y_X/G yield coefficient biomass from glucose (g g^–1) - Y_X/G,max maximum yield coefficient biomass from glucose (g g^–1) - growth associated product formation coefficient (g g^–1) - non-growth associated product formation coefficient (g g^–1 h^–1) - specific growth rate (h^–1) - _max maximum specific growth rate (h^–1)     

Homofermentative production of d-lactic acid from sucrose by a metabolically engineered Escherichia coli

Escherichia coli W, a sucrose-positive strain, was engineered for the homofermentative production of d-lactic acid through chromosomal deletion of the competing fermentative pathway genes (adhE, frdABCD, pta, pflB, aldA) and the repressor gene (cscR) of the sucrose operon, and metabolic evolution for improved anaerobic cell growth. The resulting strain, HBUT-D, efficiently fermented 100?g?sucrose?l^?1 into 85?g?d-lactic acid?l^?1 in 72–84?h in mineral salts medium with a volumetric productivity of ~1?g?l^?1?h^?1, a product yield of 85?% and d-lactic acid optical purity of 98.3?%, and with a minor by-product of 4?g?acetate?l^?1. HBUT-D thus has great potential for production of d-lactic acid using an inexpensive substrate, such as sugar cane and/or beet molasses, which are primarily composed of sucrose.     

Development of a structured model for biopolymer synthesis in the fungus Aureobasidium pullulans

Previous modelling of the pullulan fermentation is discussed and found to lack any mechanistic basis. It is concluded that predictive ability can only be conferred by a structured model with at least two compartments, based upon the best available knowledge of the physiology of the microorganism. Such a model is constructed and compared with experimental data.List of Symbols A (gdm^–3)(g/l) Ammonium ion concentration - B (gdm^–3)(g/l) Concentration of balanced growth compartment of biomass - G (gdm^–3)(g/l) Glucose concentration - k _A (gdm^–3)(g/l) Saturation constant for ammonium - k _G (gdm^–3)(g/l) Saturation constant for glucose - k _S (gdm^–3)(g/l) Saturation constant for sucrose - P (gdm^–3)(g/l) Pullulan concentration - Q Quality of biomass=U/(U+B) - r _G (gdm^–1h^–1)(g/l/h) Rate of removal of glucose from broth - r _GB (gdm^–3h^–1)(g/l/h) Rate of incorporation of glucose into balanced compartment - r _GB (gdm^–3h^–1)(g/l/h) Rate of utilisation of glucose for energy production and cell maintenance - r _GP (gdm^–3h^–1)(g/l/h) Rate of conversion of glucose to pullulan - r _GU (gdm^–3h^–1)(g/l/h) Rate of incorporation of glucose into unbalanced compartment - r _s (gdm^–3h^–1)(g/l/h) Rate of conversion of sucrose to glucose - S (gdm^–3)(g/l) Concentration of sucrose - U (gdm^–3)(g/l) Concentration of unbalanced growth compartment of biomass - X (gdm^–3)(g/l) Biomass concentration - Y _G/A Grams of glucose consumed per gram of ammonium consumed - Y _G/B Grams of glucose consumed per gram of balanced biomass produced - Y _G/U Grams of glucose consumed per gram of unbalanced biomass produced - Y _G/P Grams of glucose consumed per gram of pullulan produced - Rate constant for conversion of sucrose to glucose - Rate constant for uptake of glucose by the cells - Model parameter governing inhibition of sucrose conversion and glucose utilisation - Model parameter denoting fraction of glucose uptake devoted to cell maintenance and energy production - Model parameter governing apportionment of glucose between pseudo-growth and pullulan production This work was funded by the National Engineering Laboratory (NEL) through the Bioreactor Design Club. The authors would like to express their gratitude to the NEL for this generous support.     

An investigation of cell density effects on hybridoma metabolism in a homogeneous perfusion reactor

In this work, metabolite and antibody production kinetics of hybridoma cultures were investigated as a function of cell density and growth rate in a homogeneous perfusion reactor. Hydrophilized hollow fiber polypropylene membranes with a pore size of 0.2 m were used for medium perfusion. Oxygen was supplied to the cells through thin walled silicone tubing. The mouse-mouse hybridoma cells were grown in three identical bioreactors at perfusion rates of 1.1, 2.0, and 3.2/day for a period of eight days during which the viable cell concentrations reached stable values of 2.6×10⁶, 3.5×10⁶, and 5.2×10⁶ cells/ml, respectively. Total cell densities reached values ranging from 8×10⁶ to 1×10⁶ cells/ml. Specific substrate consumption and product formation rates responded differently to changes in cell density and apparent specific growth rate, which were not varied independently. Using multiple regression analysis, the specific glucose consumption rate was found to vary with viable cell density while the specific glutamine uptake and lactate production rates varied with both viable cell density and apparent specific growth rate. These results suggest that cell density dictates the rate of glucose consumption while the cell growth rate influences how glucose is metabolized, i.e., through glycolysis or the TCA cycle. The specific antibody production rate was found to be a strong function of cell density, increasing as cell density increased, but was essentially independent of the specific growth rate for the cell line under study.List of Symbols MAb monoclonal antibody - X _v viable cell density (cells/ml) - X _d nonviable cell density (cells/ml) - specific growth rate (1/day) - k _d specific death rate (1/day) - D dilution rate (1/day) - S _f substrate concentration in feed (g/l or mM) - S substrate concentration (g/l or mM) - P _f product concentration in feed (g/l or g/ml) - P product concentration (g/l or ug/ml) - q _s specific consumption rate of substrate (g/hr/cell or mmol/hr/cell) - q _p specific production rate of product (g/hr/cell) - q _MAb specific production rate of monoclonal antibody (g/hr/cell) This work was supported in part by a grant for the National Science Foundation (BCS-9157851) and by matching funds from Merck and Monsanto. We sincerely thank Mr. Roland Buchele of Akzo Inc. (Germany) for donation of the polypropylene membranes, Dr. Michael Fanger (Dartmouth Medical School) for the hybridoma cell line, Dr. Sadettin Ozturk (Verax Corp., Lebanon, NH) for technical discussions regarding reactor design, and Dr. Derrick Rollins (Iowa State University) for advice on statistical methods.     

Formal kinetics of poly-β-hydroxybutyric acid (PHB) production in Alcaligenes eutrophus H 16 and Mycoplana rubra R 14 with respect to the dissolved oxygen tension in ammonium-limited batch cultures

Summary Under chemolithoautotrophic growth conditions with the organism Alcaligenes eutrophus H16 the exponential growth phase is characterized by two different growth rates, each associated with different specific rates of ammonium consumption. On the basis of the analytical determination of Poly--hydroxybutyric acid (PHB), it can be conclusively shown that PHB is synthesized even during the exponential growth phase at a specific rate proportional to the specific growth rates of total biomass. After complete consumption of ammonium, the increase of biomass is exclusively due to PHB synthesis, whereas protein and rest biomass (cell dry weight minus PHB) remain constant. After an extended period of fermentation, the PHB content reaches a saturation value. The transient phase between the growth and the storage phase is very short in comparison to the duration of the whole fermentation. In the case of Alcaligenes eutrophus, strain H 16, high concentrations of dissolved oxygen strongly influence growth as well as PHB synthesis.Abbrevations ^cO₂,L concentration of oxygen in the liquid phase (dissolved oxygen tension: d.o.t) - ^cH₂,L concentration of hydrogen in the liquid phase - ^cCO₂,L concentration of carbon dioxide in the liquid phase - S limiting substrate, concentration of - X total biomass, concentration of; total cell dry weight - P product; PHB, concentration of - R rest biomass: X-P, concentration of - ^rX dX/dt growth rate - ^rP dP/dt rate of PHB synthesis - ^rR dR/dt rate of rest biomass production - ^r0 ^dcO₂,L/dt rate of oxygen consumption - X dX/dt·1/X=r_X·1/X specific growth rate - P dP/dt·1/P=r_P·1/P specific rate of product formation - R dR/dt·1/R=r_R·1/R specific rate of rest biomass formation - r₀/R specific respiration rate     

A modified unstructured mathemathical model for the penicillin G fed-batch fermentation

Summary In this paper, an updated unstructured mathematical model for the penicillin G fed-batch fermentation is proposed, in order to correct some physical and biochemical shortcomings in the model of Heijnen et al. (1979,Biotechnol. Bioeng.,21, 2175–2201) and the model of Bajpai and Reuß (1980,J. Chem. Tech. Biotechnol.,30, 332–344). Its main features are the consistency for all values of the variables, and the ability to adequately describe different metabolic conditions of the mould. The model presented here can be considered as the translation of the latest advances in the biochemical knowledge of the penicillin biosynthesis.Nomenclature t time (h) - S amount of substrate in broth (g) - X amount of cell mass in broth (g) - P amount of product in broth (g) - V fermentor volume (L) - F input substrate feed rate (L/hr) - C _s S/V substrate concentration in broth (g/L) - C _x X/V cell mass concentration in broth (g/L) - C _P P/V product concentration in broth (g/L) - s _F substrate concentration in feed stream (g/L) - E _m parameter related to the endogenous fraction of maintenance (g/L) - E _p parameter related to the endogenous fraction of production (g/L) - K _x Contois saturation constant for substrate limitation of biomass production (g/g DM) - K _s Monod saturation constant for substrate limitation of biomss production (g/L) - K _p saturation constant for substrate limitation of product formation (g/L) - K _i substrate inhibition constant for product formation (g/L) - m _s maintenance constant (g/g DM hr) - k _h penicillin hydrolysis or degradation constant (hr^–1) - Y _x/s cell mass on substrate yield (g DM/g) - Y _p/s product on substrate yield (g/g) - specific substrate consumption rate (g/g DM hr) - specific growth rate (hr^–1) - _substr specific substrate to biomass conversion rate (hr^–1) - _x maximum specific substrate to biomass conversion rate (hr^–1) - specific production rate (g/g DM hr) - _p specific production constant (g/g DM hr)     

Simulation of the dynamics in the Baker's yeast process

Simulation of the dynamics in a fed batch process for production of Baker's yeast is discussed and applied. Experimental evidences are presented for a model of the energy metabolism. The model involves the concept of a maximum respiratory capacity of the cell. If the sugar concentration is increased above a critical value, corresponding to a critical rate of glycolysis and a maximum rate of respiration, then all additional sugar consumed at higher sugar concentrations is converted into ethanol.In a fed batch process with constant sugar feed the sugar concentration declines slowly. If ethanol is present when the sugar concentration declines below the critical value of 110 mg/dm³ fructose +glucose the metabolism switches rapidly into combined oxidation of sugar and ethanol. Thus, no diauxic growth is involved under process conditions. The rate of ethanol consumption is determined by the free capacity of respiration under these conditions. The invertase activity of the cells was found to be so high that mainly fructose and glucose were present in the medium, typically in the concentration range around 100 mg/dm³. These components are consumed at the same rate but with fructose at a higher concentration, indicating a higher K _s for fructose consumption.The model was used in simulation experiments to demonstrate the dynamics of the Baker's yeast process and the influence of different process conditions.List of Symbols DOT % air sat dissolved oxygen tension - F dm³/h rate of inlet medium flow - H kg/(dm³ % air sat.) oxygen solubility - K kg/m³ saturation constant specified by index - K _L a 1/h volumetric oxygen transfer coefficient - m g/(g · h) maintenance coefficient specified by index - P kg/(m³ · h) mean productivity of biomass in the process - q g/(g · h) specific consumption or production rate - S kg/m³ concentration of sugar in reactor - S ₀ kg/m³ concentration of inlet medium sugar medium t h process time - V dm³ medium volume - X kg/m³ concentration of biomass - Y g/g yield coefficient specified by index - 1/h specific growth rate Index aa anaerobic condition - c critical value - e ethanol - ec ethanol consumption - ep ethanol production - max maximum value - o oxygen - oe oxygen for growth on ethanol - os oxygen for growth on sugar - s sugar - x biomass     

Spore production ofPenicillium roqueforti by simulated solid state fermentation

Summary A culture technique, based on the growth of a microorganism on inert porous particles (e. g. pozzolano) impregnated and continuously fed with substrate is applied to the growth and spore production ofPenicillium roqueforti. The composition and the feed rate of the medium can be controlled, and the biomass is directly estimated.P. roqueforti exhibits a diauxic growth on the medium containing sucrose and malt extract used, and 1.5 10⁹ spores/g pozzolano may be obtained.     

A holistic high-throughput screening framework for biofuel feedstock assessment that characterises variations in soluble sugars and cell wall composition in <Emphasis Type="Italic">Sorghum bicolor</Emphasis>

Background

A major hindrance to the development of high yielding biofuel feedstocks is the ability to rapidly assess large populations for fermentable sugar yields. Whilst recent advances have outlined methods for the rapid assessment of biomass saccharification efficiency, none take into account the total biomass, or the soluble sugar fraction of the plant. Here we present a holistic high-throughput methodology for assessing sweet Sorghum bicolor feedstocks at 10 days post-anthesis for total fermentable sugar yields including stalk biomass, soluble sugar concentrations, and cell wall saccharification efficiency.

Results

A mathematical method for assessing whole S. bicolor stalks using the fourth internode from the base of the plant proved to be an effective high-throughput strategy for assessing stalk biomass, soluble sugar concentrations, and cell wall composition and allowed calculation of total stalk fermentable sugars. A high-throughput method for measuring soluble sucrose, glucose, and fructose using partial least squares (PLS) modelling of juice Fourier transform infrared (FTIR) spectra was developed. The PLS prediction was shown to be highly accurate with each sugar attaining a coefficient of determination (R ² ) of 0.99 with a root mean squared error of prediction (RMSEP) of 11.93, 5.52, and 3.23 mM for sucrose, glucose, and fructose, respectively, which constitutes an error of <4% in each case. The sugar PLS model correlated well with gas chromatography–mass spectrometry (GC-MS) and brix measures. Similarly, a high-throughput method for predicting enzymatic cell wall digestibility using PLS modelling of FTIR spectra obtained from S. bicolor bagasse was developed. The PLS prediction was shown to be accurate with an R ² of 0.94 and RMSEP of 0.64 μg.mgDW^-1.h^-1.

Conclusions

This methodology has been demonstrated as an efficient and effective way to screen large biofuel feedstock populations for biomass, soluble sugar concentrations, and cell wall digestibility simultaneously allowing a total fermentable yield calculation. It unifies and simplifies previous screening methodologies to produce a holistic assessment of biofuel feedstock potential.

     

A two stage continuous process for the production of thermogelable curdlan-type exopolysaccharide

Summary A laboratory-scale, two-stage continuous process for the production of curdlan-type exopolysaccharide has been operated in steady-state for 500hr. Two continuous flow, constant volume fermenters are connected in series. A stable, curdlan-producing strain of Alcaligenes faecalis var myxogenes ATCC 31749 is grown aerobically in a nitrogen-limited chemostat operating near D_max at 0.24 hr^–1. The effluent is introduced directly into a second larger constant volume fermenter which is being simultaneously fed a glucose solution at a fixed rate. Under sub-optimal conditions associated with curdlan production, the observed Qp was 0.05 g curdlan/g cell/hr. At a biomass level of 4 g/L in the second stage, curdlan was present at 10 g DW/L and the volumetric productivity was 0.2 g/g cell/hr. The substrate (glucose) conversion efficiency was 42%. The process is described in patents applied for on behalf of George Weston Ltd. (Toronto, Canada).     

Alcoholic fermentation by Zymomonas mobilis: Effect of initial substrate on physiological parameters

Summary The influence of initial substrate concentration on fermentation kinetics of Zymomonas mobilis on glucose has been studied in batch cultures over the range 50–190 gl^-1 glucose. With increasing glucose, parameters relative to growth ( and R_GX) are more rapidly and more noticeably affected than those connected with ethanol production (p and R_GP). The water content of the cells is also affected.