十三碳二元酸发酵过程产酸期拟均相动力学模型及其应用

分析了十三碳二元酸发酵过程中产酸期的代谢特点,对产酸期四相体系发酵动力学进行了研究。提出了菌体生长、产物形成及底物消耗的动力学模型,对模型参数进行了回归估值,并对产酸期进行了拟合,结果表明,模型的计算值和实测值较为吻合,平均相对偏差为3．6％。利用所建模型对产酸期进行了多种操作条件下的模拟计算,结果表明,提高进入产酸期的菌体浓度、缩短菌体生长期时间及降低发酵液中产物浓度具有提高产物形成速率的有效途径。     

甲醇产纤维素菌株的静态发酵动力学研究

目的:为实现甲醇资源化产细菌纤维素发酵过程的优化,研究纤维素生产菌株一木醋杆菌(Gluconacetobacter χγlinus)的静态发酵动力学特性.方法:将木醋杆菌接入甲醇浓度分别为2.7%和4.5%的培养基中驯化,根据Logistic方程和LuedekingPiret方程,研究周期为13d的静态发酵动力学过程.结果:确定静态发酵过程的菌体生长、细菌纤维素合成、底物消耗的动力学参数,得到动力学方程,拟合试验值与模型值,得到甲醇模拟废水培养基平均拟合误差为16%,略高于基础培养基的14%.结论:利用甲醇产纤维索的模型方程可预测菌浓、产物浓度及底物消耗规律,实现静态发酵过程的优化.     

Kinetic model for nuclease P1fermentation by Penicillium citrinum

研究了桔青霉发酵生产核酸酶P1的发酵动力学特性:以Logistic方程和Luedeking-Piret方程为基础,进行最优参数估计和非线性拟合,得到了描述整个发酵过程中的菌体生长、产物合成和基质消耗的动力学模型.对实验数据与模型预测值进行比较,发现模型预测值与实验数据能较好地拟合,基本上反映了桔青霉发酵过程的动力学特征,为以后进一步研究和预测核酸酶P1发酵过程奠定了理论基础.     

桔青霉摇瓶发酵生产核酸酶P1的动力学研究

研究了桔青霉发酵生产核酸酶P1的发酵动力学特性：以Logistic方程和Luedeking—Piret方程为基础,进行最优参数估计和非线性拟合,得到了描述整个发酵过程中的茵体生长、产物合成和基质消耗的动力学模型。对实验数据与模型预测值进行比较,发现模型预测值与实验数据能较好地拟合,基本上反映了桔青霉发酵过程的动力学特征,为以后进一步研究和预测核酸酶P1发酵过程奠定了理论基础。     

超高浓度培养基条件下酵母细胞生长及酒精生成的准稳态动力学研究

在1．5L搅拌式发酵罐中,使用葡萄糖质量浓度分别为120、200、280g／L的培养基进行酿酒酵母Saccharomyces cerevisiae连续发酵生成酒精的动力学研究。研究发现,当培养基中葡萄糖浓度为200和280g／L时,发酵液中残糖浓度、酒精浓度以及菌体生物量从小幅度波动的准稳态发展到大幅度波动的振荡状态。提出了伴有周期性振荡现象准稳态过程的概念,并针对该过程,建立了兼有底物和产物抑制的酵母细胞生长和产物酒精生成动力学模型。     

赖氨酸分批发酵动力学的研究

在着重考虑基质浓度对发酵过程影响的基础上,结合黄色短杆菌ＦＢ４２发酵的具体特点,建立了一组描述赖氨酸分批发酵过程的动力学模型。结果该组模型能很好的拟合发酵过程,并在初糖浓度变化较大的范围内表现出适用性。用该组模型对赖氨酸发酵过程进行分析得到了和实际发酵相一致的结果     

苏云金芽孢杆菌蛋白酶发酵动力学模型的构建

对苏云金芽孢杆菌FS140蛋白酶分枇发酵的代谢特性进行了研究.首先描述了FS140分枇发酵过程中细胞生长、产物积累、糖消耗的变化规律.基于Logistic方程和Luedeking-Piret方程,建立了苏云金芽孢杆菌蛋白酶发酵过程细胞生长、产物合成及基质消耗随时间变化的数学模型.动力学模型计算值结果与实验值拟合良好,较好反映了苏云金芽孢杆菌分批发酵过程的动力学特征.     

法夫酵母分批发酵虾青素动力学研究

通过三联30L全自动发酵罐对虾青素产生菌法夫酵母的分批发酵动力学进行了研究,结果表明,法夫酵母的生长与限制性基质葡萄糖浓度之间符合Logistic方程,建立了细胞生长、产物合成和基质消耗随时间变化的数学模型。应用MATLAB软件对发酵动力学模型进行最优参数估计和非线性拟和,获得最大比生长速率（umax）和产物得率（Yp/x）分别为0.1829/h、0.1524g/g,虾青素分批发酵中细胞生长与产物合成属于偶联型,模型模拟计算结果和实验值能较好地吻合,动力学研究结果表明该模型能较好地反映细胞的生长、底物消耗和产物合成过程机制。     

产弹性蛋白酶细菌的发酵动力学研究

基于14L的发酵罐分批发酵实验数据,建立了发酵过程菌体生长、产物生成及基质消耗随时间变化的数学模型。Logistic方程、Luedeking—Piret方程能够很好地分别描述产弹性蛋白酶菌体生长;发酵产酶过程和基质消耗过程。并将3个动力学模型的预测值和实验值进行了比较,所建立的分批发酵动力学模型能较好地反映弹性蛋白酶分批发酵过程。     

柠檬酸发酵的数学模型研究

对柠檬酸发酵过程中菌体生长、基质消耗及产物生成的动力学进行了研究,得到了描述柠檬酸发酵过程的数学模型,并蹦实验统计数据为基础,通过对模型进行分析,推断了模型参数,同时用实验结果对模型进行了验证,结果表明模型计算与实测结果拟合良好,从而显示所建立的模型基本正确地描述了柠檬酸发酵过程,这对应用电子计算机控制发酵过程,实现发酵过程的最佳化有着重要意义。     

The use of automated parameter searches to improve ion channel kinetics for neural modeling

The voltage and time dependence of ion channels can be regulated, notably by phosphorylation, interaction with phospholipids, and binding to auxiliary subunits. Many parameter variation studies have set conductance densities free while leaving kinetic channel properties fixed as the experimental constraints on the latter are usually better than on the former. Because individual cells can tightly regulate their ion channel properties, we suggest that kinetic parameters may be profitably set free during model optimization in order to both improve matches to data and refine kinetic parameters. To this end, we analyzed the parameter optimization of reduced models of three electrophysiologically characterized and morphologically reconstructed globus pallidus neurons. We performed two automated searches with different types of free parameters. First, conductance density parameters were set free. Even the best resulting models exhibited unavoidable problems which were due to limitations in our channel kinetics. We next set channel kinetics free for the optimized density matches and obtained significantly improved model performance. Some kinetic parameters consistently shifted to similar new values in multiple runs across three models, suggesting the possibility for tailored improvements to channel models. These results suggest that optimized channel kinetics can improve model matches to experimental voltage traces, particularly for channels characterized under different experimental conditions than recorded data to be matched by a model. The resulting shifts in channel kinetics from the original template provide valuable guidance for future experimental efforts to determine the detailed kinetics of channel isoforms and possible modulated states in particular types of neurons.     

Molecular characterization of Lactobacillus curvatus and Lact. sake isolated from sauerkraut and their application in sausage fermentations

Lactobacillus curvatus and Lact. sake are best adapted to meat fermentations and dominate the flora during the whole process. In fermenting sauerkraut, Leuconostoc mesenteroides subsp. mesenteroides is the major organism only during the early phase. In this environment Lact. curvatus and Lact. sake provide up to 50% of the microbial flora especially of the later phase, depending on the process conditions. Strains of Lact. curvatus and Lact. sake isolated from fermenting sauerkraut were identified by hybridization with species specific 23S rRNA-targeted oligonucleotide probes and further characterized. In 59 of 72 strains, plasmid DNA was detected. Small cryptic plasmids of 20 strains were found to be homologous with pLc2, a 2·6 kb plasmid from Lact. curvatus LTH683, which was originally isolated from meat. The ability to compete was investigated in fermenting sausages of two strains each of Lact. curvatus and Lact. sake isolated from sauerkraut. One strain each of Lact. curvatus and Lact sake was found to outnumber the meat-borne flora and govern the process.     

发酵中含氮类原料对保加利亚乳杆菌活菌数的影响

目的研究生产发酵过程中培养基含氮原料与发酵的相关性。方法实验通过对不同生产厂家三种原料进行理化指标检测,并通过正交试验,比较不同原料发酵后保加利亚乳杆菌发酵液活菌数。结果最佳条件为酪蛋白胨氨基氮含量高,酵母浸粉的炽灼残渣低,牛肉粉总氮含量高。结论经过相同原料不同生产厂家的配方发酵后的发酵液活菌数存在差异,其理化指标对发酵有一定影响。     

Estimation of ionic channel surface density from relaxation ionic and gating currents

It is shown that excitable membrane surface density of channels can be estimated from ionic and gating current relaxations. The gating currents are determined thermodynamically from a multistate kinetic model. The parameters of the kinetic model are derived from ionic current relaxations. The assumptions regarding the gating process made here are the same as those made in fluctuation analysis previously regarded as the only method that may yield channel density from membrane currents.     

Bioproduction of butanol from biomass: from genes to bioreactors

Butanol is produced chemically using either the oxo process starting from propylene (with H2 and CO over a rhodium catalyst) or the aldol process starting from acetaldehyde. The key problems associated with the bioproduction of butanol are the cost of substrate and butanol toxicity/inhibition of the fermenting microorganisms, resulting in a low butanol titer in the fermentation broth. Recent interest in the production of biobutanol from biomass has led to the re-examination of acetone-butanol-ethanol (ABE) fermentation, including strategies for reducing or eliminating butanol toxicity to the culture and for manipulating the culture to achieve better product specificity and yield. Advances in integrated fermentation and in situ product removal processes have resulted in a dramatic reduction of process streams, reduced butanol toxicity to the fermenting microorganisms, improved substrate utilization, and overall improved bioreactor performance.     

Modeling kinetics of a large‐scale fed‐batch CHO cell culture by Markov chain Monte Carlo method

Markov chain Monte Carlo (MCMC) method was applied to model kinetics of a fed‐batch Chinese hamster ovary cell culture process in 5,000‐L bioreactors. The kinetic model consists of six differential equations, which describe dynamics of viable cell density and concentrations of glucose, glutamine, ammonia, lactate, and the antibody fusion protein B1 (B1). The kinetic model has 18 parameters, six of which were calculated from the cell culture data, whereas the other 12 were estimated from a training data set that comprised of seven cell culture runs using a MCMC method. The model was confirmed in two validation data sets that represented a perturbation of the cell culture condition. The agreement between the predicted and measured values of both validation data sets may indicate high reliability of the model estimates. The kinetic model uniquely incorporated the ammonia removal and the exponential function of B1 protein concentration. The model indicated that ammonia and lactate play critical roles in cell growth and that low concentrations of glucose (0.17 mM) and glutamine (0.09 mM) in the cell culture medium may help reduce ammonia and lactate production. The model demonstrated that 83% of the glucose consumed was used for cell maintenance during the late phase of the cell cultures, whereas the maintenance coefficient for glutamine was negligible. Finally, the kinetic model suggests that it is critical for B1 production to sustain a high number of viable cells. The MCMC methodology may be a useful tool for modeling kinetics of a fed‐batch mammalian cell culture process. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2010     

Occurence of a Phosphodiesterase in the Insoluble Fractions from Wheat Seedlings

The volume of carbon dioxide evolved in a shaking apparatus was measured at fixed intervals, and it was confirmed that the fermentation of dry yeast generally depends on three factors and that they are represented with an initial fermenting activity, a power which recovers fermenting activity, and a maximum fermenting activity. This expression of fermenting power was compared with usual expressions and it was proved to be more reasonable, particularly, for deciding the initial fermenting activity.     

Yeast population dynamics of industrial fuel-ethanol fermentation process assessed by PCR-fingerprinting

Yeast population used in industrial production of fuel-ethanol may vary according to the plant process condition and to the environmental stresses imposed to yeast cells. Therefore, yeast strains isolated from a particular industrial process may be adapted to such conditions and should be used as starter strain instead of less adapted commercial strains. This work reports the use of PCR-fingerprinting method based on microsatellite primer (GTG)₅ to characterize the yeast population dynamics along the fermentation period in six distilleries. The results show that indigenous fermenting strains present in the crude substrate can be more adapted to the industrial process than commercial strains. We also identified new strains that dominate the yeast population and were more present either in molasses or sugar cane fermenting distilleries. Those strains were proposed to be used as starters in those industrial processes. This is the first report on the use of molecular markers to discriminate Saccharomyces cerevisiae strains from fuel-ethanol producing process.