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     

Kinetics of batch-wise enzymatic cycling system for mass production of chiral compound

Kinetics of batch-wise enzymatic cycling system (oxidoreductase-catalyzed reaction system involving enzyme-coupled cofactor regeneration) has been studied covering a broad range of the conserved total cofactor concentration, [C]₀ (=NAD(P)⁺?+?NAD(P)H), based on reasonable several assumptions. It is composed of two elementary reactions, i.e. product synthesis reaction and cofactor regeneration reaction, both of which have been expressed by Michaelis–Menten type rate equations. A novel dimensionless variable, r, has been introduced, which is defined as the concentration of one of the two cofactor components, [X] (NADH⁺ or NADPH⁺), divided by [C]₀, i.e. r .e[X]/[C]₀. The following results have been obtained. (1) The fundamental equation of the batch-wise enzymatic cycling system has been transformed to a differential equation whose formula is: dr/dT?=?N(r)/D(r) (N(r) and D(r) are quadratic equations of r having different coefficients). (2) It has been elucidated that the batch-wise enzymatic cycling system has two phases, an early short transient phase followed by a long phase in quasi-steady state (QSS). (3) In the enzymatic cycling system, r converges to a definite level regardless of any initial value of r. (4) In QSS, the definite level of r nearly equals the singular solution, r_singular, of the differential equation. (5) The actual rate of the targeted product (chiral compound) formation can be calculated by Michaelis–Menten equation in which the cofactor concentration is [C]₀×r_singular instead of [C]₀. r_singular has been proposed to name “redistribution factor”. (6) It is recommended that the “unit” of the cofactor regeneration enzyme be 2–3 times more used than the “unit” of the synthesis enzyme and that [C]₀ be 15–25 times more than the K_m value. Four special cases relating to the batch-wise enzymatic cycling system have been discussed.     

Applications of modelling for bioprocess design and control in industrial production

The on-line measurement of the relevant parameters and the control conception for three production processes for fine chemicals by fermentation and biotransformation at the 15 m³ scale were developed. The models describe the bioprocesses which successfully result in fully automated manufacturing steps. Modelling also proved to be a valuable tool for a better insight into biochemical fundamentals of the processes. Moreover, proper use of data logging, modelling and process control was important for quality, since two processes were controlled on-line and quality relevant deviations were registered early. Finally, combining modelling with simulation, we could drastically reduce both development time and cost.List of Symbols F l/h flux - V l volume - U ₀ g/l nicotinonitrile concentration influx - U g/l actual nicotinonitrile concentration - q _ug/gh specific educt (=nicotinonitrile) transformation rate - x g/l biocatalyst concentration - p ₀ g/l nicotinamide concentration influx - p g/l actual nicotinamide concentration - q _pg/gh specific product (=nicotinamide) formation rate - k parameter loss of activity - q _{u, max}g/gh max. specific educt transformation rate - K _ug/l saturation constant for nicotinonitrile - K _ig/l inhibition constant for nicotinonitrile - K _iig/l inhibition constant for nicotinamide - MW _Ag/mol molecular weight for nicotinonitrile - MW _Bg/mol molecular weight for nicotinamide - NS Nicotinic acid - 6-HNS 6-Hydroxynicotinic acid - r _{NS, 6HNS} g/lh 6-HNS production rate - r _{6HNS, X} g/lh biomass production rate - r _{NS, 6HNS, max} g/lh max. 6-HNS production rate - S _NS g/l actual NS concentration - K _{S, NS} g/l saturation constant for NS - K _{i, 6HNS} g/l inhibition constant for 6-HNS - K _o2 g/l saturation constant for oxygen - r _{6HNS, X, max} g/lh max. biomass production rate - S _6HNS g/l actual 6-HNS concentration - K _{ii, NS} g/l inhibition constant for NS - RQ mol/mol respiration quotient - S _xylg/l actual xylene concentration - K _{i, xyl}g/ inhibition constant for xylene - K _{i, DMPY}g/ inhibition constant for 2,5-dimethylpyrazine - r _Xg/lh biomass production rate - r _{X, max}g/lh max. biomass production rate - K _{s, xyl}g/l saturation constant for xylene - S _DMPYg/l actual concentration of DMPY - K _{i, MPCA}g/ inhibition constant for MPCA - K _O2g/ saturation constant for oxygen - S _MPCAg/l actual MPCA concentration - S _O2g/l actual oxygen concentration - r _MPCAg/lh MPCA production rate - r _{MPCA, max}g/lh max. MPCA production rate - k _lgl inhibition constant for the intermediates - k _{s, DMPY}gl saturation constant for DMPY     

Hyaluronan-mediated protective effect against cell damage caused by enzymatically produced hydroxyl (OH·) radicals is dependent on hyaluronan molecular mass

Hyaluronan (HA) protected tendon fibroblasts against cell damage mediated by hydroxyl radicals (OH·) as demonstrated by release of ⁵¹Cr from labelled cells. Protection afforded by high molecular mass (M_r) HA (1218 kDa) was much more effective than that provided by lower (176 kDa and 668 kDa) M_r HA. OH· was generated by coupling H₂O₂ produced by glucose oxidase: glucose to [Fe²⁺-EDTA] chelate in a Fenton-type system. The flux of OH· was measured by a spectrofluorimetric assay of salicylate produced by the reaction of benzoate with OH·. Cell damage caused by the OH· generating system was prevented in the presence of catalase, which destroyed H₂O₂. Damage caused in a standard incubation time increased with increased amounts of glucose oxidase. Protection against OH·-mediated cell damage increased with increasing concentration of HA. The presence of HA did not interfere with the enzyme-Fenton system, as monitored by production of gluconate. On the other hand, HA scavenged OH· produced by the enzyme-Fenton system, as shown by competition with benzoate, which produced less salicylate in the spectrofluorimetric assay in the presence of HA. The reaction of OH· with HA was measured directly by a pulse radiolysis technique in which a hydrated electron (e) produced OH· by the reaction with nitrous oxide. Second order rate constants obtained in distilled H₂O or in phosphate buffer showed no dependence on HA M_r. Similarly, fluorimetric assay of the flux of in the enzyme-Fenton system confirmed that HA competed with benzoate, thus lowering salicylate production, and the flux was also independent of the molecular mass of HA. These results demonstrate that part of the HA-mediated protection against enzyme-Fenton produced OH· and other reactive oxygen-derived toxic species was not a consequence of either the primary or secondary structure of HA, but rather depends on higher order HA organization. Some aspects of the formation of the HA meshwork (tertiary structure) are M_r dependent. We therefore propose that cell-anchored HA meshworks excluded relatively large enzyme molecules from the immediate environment of the cell, thus reducing the flux of OH· etc. at the cell surface and diminishing cell damage.     

Anaerobic digestion of palm oil mill effluent and condensation water waste: an overall kinetic model for methane production and substrate utilization

The process of anaerobic digestion is viewed as a series of reactions which can be described kinetically both in terms of substrate utilization and methane production. It is considered that the rate limiting factor in the digestion of complex wastewaters is hydrolysis and this cannot be adequately described using a Monod equation. In contrast readily assimilable wastewaters conform well to this approach. A generalized equation has thus been derived, based on both the Monod and Contois equations, which serves extreme cases. The model was verified experimentally using continuous feed anaerobic digesters treating palm oil mill effluent (POME) and condensation water from a thermal concentration process. POME represents a complex substrate comprising of unhydrolyzed materials whereas the condensation water is predominantly short chain volatile fatty acids. Substrate removal and methane production in both cases could be predicted accurately using the generalized equation presented.List of Symbols A (=K_skY/K_h) Kinetic parameter - B Specific methane yield, 1 of CH₄/g of substrate added B₀ Maximum specific methane yield, 1 of CH₄/g of substrate added at infinity - C Empirical constant in Contois equation - F Volumetric substrate removal rate, g/l day - k Hydrolysed substrate transport rate coefficient, 1/days - K (=YC) Kinetic parameter in Chen-Hashimoto equation - K _h Substrate hydrolysis rate coefficient, 1/days - K _s Half-saturation constant for hydrolysed substrate, g/l - M _v Volumetric methane production rate, 1 of CH₄/l day - MS Mineral solids, g/l - MSS Mineral suspended soilds, g/l - POME Palm oil mill effluent - R (=S_r/S_T0) Refractory coefficient - S _h Concentration of hydrolysed substrate, g/l - S _u Intracellular concentration of hydrolysed substrate, g/l - S ₀ Input biodegradable substrate concentration, g/l - S Biodegradable substrate concentration in the effluent or in the digester, g/l - S _r Refractory feed substrate concentration, g/l - S _T0 (=S₀+S_r) Total feed substrate concentration, g/l - S _T (S+S_r) Total substrate concentration in the effluent, g/l - TS Total solids, g/l - TSS Total suspended solids, g/l - VFA Total volatile fatty acids, g/l - VS Volatile solids, g/l - VSS Volatile suspended solids, g/l - X Biomass concentration, g/l - Y Biomass yield coefficient, biomass/substrate mass - Hydraulic retention time, days. - Specific growth rate of microorganisms, l/days - _m Maximum specific growth rate of microorganisms, l/days The authors wish to express their gratitude to the Departamento de Postgrado y Especialización del CSIC and to the Consejería de Educación y Ciencia de la Junta de Andalucia for their financial support of this work.     

Comments on the “Maintenance coefficient” changes during alcohol fermentation

Summary The concept of maintenance is discussed in terms of the biological meaning and the applicability of the maintenance coefficient, m, in bioengineering for optimization of yields in fermentation. A method of calculation is proposed for the evaluation of m in the course of fermentation in the case of a metabolite (e.g, ethanol). During alcoholic fermentation m is not constant and decreases with the growth rate.The phenomena involved in maintenance are numerous and complex and there is a semantic problem in its definition which can be generalized by the apparently non-finalized substrate consumption.Nomenclature a specific maintenance rate (defined by eq. (9)) - m maintenance coefficient - X cell mass concentration (as a dry weight) - S substrate concentration - P product concentration - r rate of reaction - r_x,r_s,r_p rate of reaction related to biomass, substrate and product - r_sm,r_sg,r_spi rate of reaction related only to the consumption by maintenance, growth and the synthesis of the ith product - r_xe maintenance rate defined by eq. (10) - q_s,q_Pi specific rate of substrate consumption and i^th product production - Y yield coefficient - Y^o, Y^o apparent yield coefficient related to the cell and i^th product - Y _xs ^xs , Y _Pis ^Pis maximum theoretical yield coefficient related to the cell and i^th - specific growth rate produce 420     

Cell recycling studies for α-amylase production by Bacillus amyloliquefaciens

Production of -amylase by a strain of Bacillus amyloliquefaciens was investigated in a cell recycle bioreactor incorporating a membrane filtration module for cell separation. Experimental fermentation studies with the B. amyloliquefaciens strain WA-4 clearly showed that incorporating cell recycling increased -amylase yield and volumetric productivity as compared to conventional continuous fermentation. The effect of operating conditions on -amylase production was difficult to demonstrate experimentally due to the problems of keeping the permeate and bleed rates constant over an extended period of time. Computer simulations were therefore undertaken to support the experimental data, as well as to elucidate the dynamics of -amylase production in the cell recycle bioreactor as compared to conventional chemostat and batch fermentations. Taken together, the simulations and experiments clearly showed that low bleed rate (high recycling ratio) various a high level of -amylase activity. The simulated fermentations revealed that this was especially pronounced at high recycling ratios. Volumetric productivity was maximum at a dilution rate of around 0.4 h^–1 and a high recycling ratio. The latter had to exceed 0.75 before volumetric productivity was significantly greater than with conventional chemostat fermentation.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 - B bleed rate (h^–1) - C starch concentration (g/l) - C ₀ starch concentration in the feed (g/l) - D dilution rate (h^–1) - D _E volumetric productivity (KNU/(mlh)) - e intracellular -amylase concentration (g/g cell mass) - E extracellular -amylase concentration (KNU/ml) - F volumetric flow rate (l/h) - G average number of genome equivalents of DNA per cell - k _l intracellular equilibrium constant - k ₂ intracellular equilibrium constant - k _s Monod saturation constant (g/l) - k ₃ excretion rate constant (h^–1) - k _d first order decay constant (h^–1) - k _gl rate constant for glucose production - k _st rate constant for starch hydrolysis - k _t1 proportionality constant for -amylase production (gmRNA/g substrate) - k ₁ translation constant (g/(g mRNAh)) - KNU kilo Novo unit - m maintenance coefficient (g substrate/(g cell massh)) - n number of binding sites for the co-repressor on the cytoplasmic repressor - Q repression function K₁/K₂Q1.0 - R ratio of recycling - R _s rate of glucose production (g/lh) - r _c rate of starch hydrolysis (g/(lh)) - R _eX retention by the filter of the compounds X: starch or -amylase - r intracellular -amylase mRNA concentration (g/g cell mass) - r _C volumetric productivity of starch (g/lh) - r _E volumetric productivity of intracellular -amylase (KNU/(g cell massh)) - r _r volumetric productivity of intracellular mRNA (g/(g cell massh)) - r _e volumetric productivity of extracellular -amylase (KNU/(mlh)) - r _s volumetric productivity of glucose (g/(lh)) - r _X volumetric productivity of cell mass (g/(lh)) - S ₀ free reducing sugar concentration in the feed (g/l) - S extracellular concentration of reducing sugar (g/1) - t time (h) - V volume (l) - X cell mass concentration (g/l) - Y yield coefficient (g cell mass/g substrate) - Y _E/S yield coefficient (KNU -amylase/g substrate) - Y _E total amount of -amylase produced (KNU) - substrate uptake (g substrate/(g cell massh)) - 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) This study was supported by Bioprocess Engineering Programme of the Nordic Industrial Foundation and the Center for Process Biotechnology, the Technical University of Denmark.     

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.     

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)     

Modelling of alcohol fermentation in a tubular reactor with high biomass recycle

Fermentation in tubular recycle reactors with high biomass concentrations is a way to boost productivity in alcohol production. A computer model has been developed to investigate the potential as well as to establish the limits of this process from a chemical engineering point of view. The model takes into account the kinetics of the reaction, the nonideality of flow and the segregation in the bioreactor. In accordance with literature, it is shown that tubular reactors with biomass recycle can improve productivity of alcohol fermentation substantially.With the help of the computer based reactor model it was also possible to estimate the detrimental effects of cell damage due to pumping. These effects are shown to play a major role, if the biomass separation is performed by filtration units which need high flow rates, e.g. tangential flow filters.List of Symbols Bo d Bodenstein number - c kg/m³ concentration of any component - CPFR continuous plug flow reactor - CSTR continuous stirred tank reactor - d _h m hydraulic diameter - D _eff m²/s dispersion coefficient - f residence time distribution function - K _s kg/m³ monod constant for biomass production - K _s kg/m³ monod constant for alcohol production - p kg/m³ product concentration - P _i kg/m³ lower inhibition limit concentration for biomass production - p _i kg/m³ lower inhibition limit concentration for alcohol production - p _m kg/m³ maximum inhibition limit concentration for biomass production - p _m kg/m³ maximum inhibition limit concentration for alcohol production - q _p h^–1 specific production rate - q _p,max h^–1 maximum specific production rate for alcohol production - q _s h^–1 specific substrate consumption rate - Q _L m _gas ³ /m³h specific gas rate - r _p , r _s , r _x kg/(m³ · h) reaction rate for ethanol production substrate consumption and cell growth, respectively - S _F kg/m³ substrate concentration in feed stream - s kg/m³ substrate concentration - t h time - x kg/m³ biomass concentration - x _max kg/m³ maximum biomass concentration for biomass production - Y _p/s yield coefficient - h^–1 specific growth rate - _max h^–1 maximum specific growth rate - dimensionless time (t/) - h mean residence time - _s glucose conversion     

The Effects of Clofentezine on Life-table Parameters in Two-spotted Spider Mite Tetranychus urticae

Sublethal effects of the growth inhibitor, clofentezine, on life-table parameters of Tetranychus urticae Koch females treated at different developmental stages with a concentration causing ≥90% mortality were investigated. Females which survived treatment as ‘early’ (0–24 h old) eggs produced 12% more offspring than the untreated females during the first five days of oviposition. This resulted in a significant rise in the intrinsic rate of increase (r _j ): 0.324, compared to 0.299 in the untreated females. This effect may be interpreted as hormoligosis. Clofentezine treatment at any other developmental stage of T. urticae significantly decreased both longevity and fertility of female survivors. Females which survived treatment either as ‘late’ (72–96 h old) eggs or larvae had 2.6 times lower net reproductive rate (R ₀) than the untreated females, and the r _j values were significantly lower: 0.242 and 0.215, respectively (0.285 in the untreated females). Females which survived treatment either as protonymphs or deutonymphs had 3.9 times and 6 times lower R ₀, respectively. Corresponding r _j values were 0.178 and 0.146, respectively (0.247 in the untreated females). The clofentezine treatment at all stages influenced the age distribution of survivors. The sublethal effects of clofentezine and their impact on T. urticae management are discussed. This revised version was published online in July 2006 with corrections to the Cover Date.     

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]     

Genetic analysis of photosynthetic variation in hexaploid and tetraploid wheat and their interspecific hybrids

Intra- and inter-specific variation in CO₂ assimilation rate (A) in Triticum spp. is well documented for reproductive growth stages. Research was conducted to characterize early vegetative photosynthetic variation in a diverse set of cultivated hexaploid wheat (T. aestivum L.) germplasm and in wild tetraploid (T. dicoccoides Korn) and hexaploid x tetraploid populations. Choice of hexaploid genotypes was based on maximum genetic distance between cultivars within the HRW and SRW wheat classes of the USA. The tetraploid material was produced by hybridizing two accessions of T. dicoccoides previously shown to differ widely in A and A/Chl but with similar leaf morphology. Genetic variability in the HRW and SRW gene pools was attributed to more recently developed descendent lines and unrelated lines rather than parental lines. Phenotypic distributions for A, stomatal conductance (gs), and internal CO₂ concentration (Ci) in the F₂ tetraploid population were continuous and showed transgressive segregation, reflecting quantitative inheritance with intermediate heritability. Variability in A was not associated with chlorophyll content or CO₂ supply to the mesophyll measured as Ci. Genetic variability in A was also observed in the interspecific backcross population, 2*TAM W-101/PI 428109, thereby providing a germplasm pool to select for high A while restoring the D genome of hexaploid wheat. These results suggest that genetic improvement of vegetative assimilation rate is feasible in hexaploid wheat via homologous transfer from an alien source.Abbreviations HRW hard red winter - LA leaf area - r_G genotypic correlation - r_P phenotypic correlation - SRW soft red winter     

Intermediate filament proteins in echinoderm coelomocytes

The presence and organization of intermediate filament (IF) proteins in petaloid coelomocytes from two species of echinoderms, the sea urchin Strongylocentrotus droebachiensis and the sea cucumber Cucumaria frondosa, were studied. Two monoclonal antibodies (IFA and Ah6) and one polyclonal antibody (W3-1) that together recognize invertebrate as well as vertebrate IF proteins were used to probe coelomocytes by immunofluorescence and immunoblotting methods. All three antibodies cross-reacted with a single M_r 68 000 sea urchin lamin, as well as two putative lamin isoforms of approximately M_r 70 000 and 68 000 in sea cucumber coelomocytes. Both IFA and Ah6 labeled granular material in the cytoplasm of sea urchin coelomocytes; by contrast, IFA labeling revealed a striking network of reticular material irregularly arrayed within the central regions of the sea cucumber coelomocyte cytoplasm. In addition, foci of Ah6-positive material were present in coelomocyte nuclei from both species. Comparison of immunoblotting patterns among whole cell and isolated nuclear preparations suggest that the cytoplasmic IF-like material is composed of M_r 46 000 and 58 000 polypeptides, while M_r 215 000 and 185 000 proteins are candidates for the immunoreactive nuclear foci. Further study of the functions of these non-filamentous arrays of IF proteins may furnish valuable insights into the evolution of IF function within vertebrate cells, particularly with respect to certain cytoplasmic and nuclear regulatory functions with which IF proteins have been speculated to be involved.     

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.     

Influence of different vitamin-nitrogen sources on cell growth and propionic acid production from sucrose by Propionibacterium shermanii

Cell growth and organic acid production by Propionibacteria are dependent on the vitamin-nitrogen source in the culture medium. Final cell and propionic acid concentrations produced by Propionibacterium shermanii, using corn-steep liquor, were higher than those obtained utilizing yeast extracts. Since corn-steep liquor is much cheaper than yeast extract, the process becomes more attractive. By calculating the specific growth rates, it was observed that the critical propionic acid concentration, that prevents all growth (μ_X = 0), is different depending on the vitamin-nitrogen source used and its concentration. For example, for 5.0 and 15.0 g/l Oxoid yeast extract, those critical propionic acid concentrations were 16.0 and 27.0 g/l, respectively. Such propionic acid concentrations inhibit the cell growth, but not the formation of acid. The specific propionic acid production rate also indicates that the critical concentration for metabolic activity, when propionic acid is no longer produced (μ_P = 0), varies according to the vitamin-nitrogen source and its concentration in the medium. For 5.0 and 15.0 g/l Oxoid yeast extract, those concentrations were 22.1 and 30.1 g/l, respectively.     

Study of the Solute Flows of Multicomponent and Heterogeneous Non-Ionic Solutions in Double-Membrane System

The solute flows were studied in a double-membrane osmotic-diffusive cell, in which two membranes mounted in horizontal planes separate three compartments (l,m,r) containing the non-homogeneous, non-electrolytic binary and ternary solutions. The volume of inter-membrane compartment (m), which is the infinitesimally layer of solution, and volume of external compartments (l and r) fulfill the conditions V _m 0 and V _l =V _r , respectively. In an initial moment, the solution concentrations satisfy the condition (C ^o _s ) _l < (C ^o _s ) _m >(C ^o _s ) _r. The double-membrane osmotic-diffusive cell is composed of two complexes: boundary layer/membrane/boundary layer, mounted in horizontal planes. In the cell, solute flux was measured as a function of concentration and gravitational configuration. The linear dependencies of the solute flux on concentration difference in binary solutions and nonlinear – in ternary solutions were obtained. It was shown that the double-membrane osmotic-diffusive cell has rectifying and amplifying properties of solute flows.     

Influence of substrate transport on the activity of immobilized Papaver somniferum cells

Summary Intraparticle diffusion resistance was studied for Papaver somniferum cells immobilized by Ca alginate gel. In callus tissue, these plant cells convert codeinone to codeine. First, the diffusion rates of substrates in the gel were measured, followed by investigation of the consumption rates of the substrates by free cells. The consumption rate of sucrose was zero order in relation to sucrose concentration, whereas that of codeinone was first order in relation to its concentration. The oxygen consumption rate obeyed Michaelis-Menten type kinetics with respect to dissolved oxygen concentration. Combining the reaction rates and diffusion rates allows calculation of the extent of the effect of diffusion limitation on the overall reaction rates. The analysis showed that the effectiveness factor for each substrate was about unity and that the influence of diffusion resistance was negligible. However, the oxygen concentration decreased considerably inside the particle, and this may affect the activity of the plant cell for repeated use over a long time period. Thus, deactivation proceeds due to the oxygen deficit although the temporal reaction rate is not affected.Abbreviations C _c cell concentration (g/l) - C _cod codeinone concentration (g/l) - c _{O 2} dissolved oxygen concentration (g/l) - K _m constant in Eq. (3) (g/l) - K _cod rate constant in Eq. (1) (l/g of cells per second) - k _suc rate constant in Eq. (2) (g sucrose/g of cells per second) - R radius of particles (mm) - r distance from the centre of the particle (mm) - r _cod consumption rate of codeinone (g codeinone/g of cells per second) - r _{O 2} consumption rate of O₂ (g oxygen/g of cells per second) - r _suc consumption rate of sucrose (g sucrose/g of cells per second) - V _m maximum respiration rate (g oxygen/g of cells per second) T. Nozawa is now with the Department of Agricultural Chemistry, University of TokyoT. Isohara is now with the Nippon Steel Corporation     

Simultaneous estimation ofV max,Km, and the rate of endogenous substrate production (R) from substrate depletion data

The nonlinear and 3 linearized forms of the integrated Michaelis-Menten equation were evaluated for their ability to provide reliable estimates of uptake kinetic parameters, when the initial substrate concentration (S₀) is not error-free. Of the 3 linearized forms, the one where t/(S₀–S) is regressed against ln(S₀/S)/(S₀–S) gave estimates ofV _max and K_m closest to the true population means of these parameters. Further, this linearization was the least sensitive of the 3 to errors (±1%) in S₀. Our results illustrate the danger of relying on r² values for choosing among the 3 linearized forms of the integrated Michaelis-Menten equation. Nonlinear regression analysis of progress curve data, when S₀ is not free of error, was superior to even the best of the 3 linearized forms. The integrated Michaelis-Menten equation should not be used to estimateV _max and K_m when substrate production occurs concomitant with consumption of added substrate. We propose the use of a new equation for estimation of these parameters along with a parameter describing endogenous substrate production (R) for kinetic studies done with samples from natural habitats, in which the substrate of interest is an intermediate. The application of this new equation was illustrated for both simulated data and previously obtained H₂ depletion data. The only means by whichV _max, K_m, and R may be evaluated from progress curve data using this new equation is via nonlinear regression, since a linearized form of this equation could not be derived. Mathematical components of computer programs written for fitting data to either of the above nonlinear models using nonlinear least squares analysis are presented.     

A Secondary Processing Site in the Precursor of the Small Subunit of Ribulose Bisphosphate Carboxylase of Chlamydomonas reinhardtii y-1

When the precursor of ribulose bisphosphate carboxylase of Chlamydomonas reinhardtii y-1 is bound to antibodies and treated with the soluble cell fraction, it is cleaved to the mature form (M_r 16,500) via an intermediate of M_r 18,500. Although this intermediate has only been observed in vitro, it may be produced during processing of the precursor in vivo.