纤维素酶液体发酵最佳培养基的确定

用响应面法对里氏木霉WX—112液体发酵产纤维素酶的培养基进行了优化。首先用快速登高路径逼近最大产酶区域,然后根据快速登高法的实验结果进行响应面实验。运用逐步回归分析法,获得滤纸酶活与豆饼粉、麸皮、KH2PO4、微晶纤维素粉（Avicel）的最优回归方程,且分析了各因子间的交互效应。最后,通过岭脊分析确定了滤纸酶活达最大值10．53IU／mL时的最佳组合条件：豆饼粉3．18％、麸皮2．95％、KH2PO4 0．25％、Avicel 3．79％。     

Optimization of polysaccharide and ergosterol production from Agaricus brasiliensis by fermentation process

Statistically based experimental designs were applied for the fermentation optimization of polysaccharide and ergosterol production from Agaricus brasiliensis in a stirred-fermenter. Culture temperature, agitation speed and initial pH were identified to have significant effects on polysaccharide and ergosterol production by a Plackett–Burman design. These three significant factors were subsequently optimized using steepest ascent method and Box–Behnken design. The validity of the optimum conditions was verified by separate experiments in which the polysaccharide and ergosterol yields were increased by 57% and 43%, respectively, as compared to those under unoptimized fermentation conditions.     

洋葱伯克霍尔德菌（Burkholderia cepacia）CF-66发酵生产新型抗菌物质CF66I培养基的优化

利用基于统计学的实验设计RSM（Response surface methodology）优化了Burkholderia cepacia CF-66产新型抗菌活性物质CF66I的发酵培养基组成。首先,用部分重复因子实验对培养基组分NH4Cl,MgSO4·7H2O,柠檬酸钠及酵母粉浓度对菌株产CF66I的影响进行评价,找出主要影响因子为柠檬酸钠和酵母粉。两者均为正影响,其他组分对CF66I活性的影响不显著。其次用最陡爬坡路径逼近最大响应区域。最后用中心组合设计及响应面分析确定主要影响因子的最佳浓度。菌株在优化培养基中培养较初始培养基CF66I活性提高了约两倍。     

响应面法优化弗氏链霉菌S-221变种发酵培养基

用响应面法对弗氏链霉菌S-221变种液体发酵生产氨基酸的培养基进行了优化。首先,用全因子试验方法对相关影响因素的效应进行评价,并筛选出有显著效应的羽毛胨和蛋白胨两个因素,第2步用最陡爬坡实验逼近以上两因素最优水平。最后由中心组合设计法及响应面分析确定主要影响因素的最佳条件。在优化培养条件下,发酵液中氨基酸浓度从4.1g／100mL提高到6.412g／100mL。     

产朊假丝酵母全细胞转化合成谷胱甘肽的营养条件

为了进一步提高产朊假丝酵母全细胞转化生物合成谷胱甘肽(GSH)的能力,利用响应面分析方法对酵母培养的发酵培养基进行优化。在单因素实验的基础上,通过Plackett-Burman设计筛选出显著影响GSH转化力的2个主要因素:葡萄糖和KH2PO4。采用最陡爬坡试验和响应面设计预测了葡萄糖和KH2PO4的最佳质量浓度分别为58.5和17.2 g/L。验证实验结果表明,在该优化培养基条件下,酵母细胞的GSH转化力为1.54 mg/(g·h),比优化前提高了1倍。该结果为类似的采用全细胞转化法高效合成有用化学品的研究与开发提供了可行的优化思路。     

Molecular modeling of proteins: a strategy for energy minimization by molecular mechanics in the AMBER force field.

Energy minimization is an important step in molecular modeling of proteins. In this study, we sought to develop a minimization strategy which would give the best final structures with the shortest computer time in the AMBER force field. In the all-atom model, we performed energy minimization of the melittin (mostly alpha-helical) and cardiotoxin (mostly beta-sheet and beta-turns) crystal structures by both constrained and unconstrained pathways. In the constrained path, which has been recommended in the energy minimization of proteins, hydrogens were relaxed first, followed by the side chains of amino acid residues, and finally the whole molecule. Despite the logic of this approach, however, the structures minimized by the unconstrained path fit the experimental structures better than those minimized by constrained paths. Moreover, the unconstrained path saved considerable computer time. We also compared the effects of the steepest descents and conjugate gradients algorithms in energy minimization. Previously, steepest descents has been used in the initial stages of minimization and conjugate gradients in the final stages of minimization. We therefore studied the effect on the final structure of performing an initial minimization by steepest descents. The structures minimized by conjugate gradients alone resembled the structures minimized initially by the steepest descents and subsequently by the conjugate gradients algorithms. Thus an initial minimization using steepest descents is wasteful and unnecessary, especially when starting from the crystal structure. Based on these results, we propose the use of an unconstrained path and conjugate gradients for energy minimization of proteins. This procedure results in low energy structures closer to the experimental structures, and saves about 70-80% of computer time. This procedure was applied in building models of lysozyme mutants. The crystal structure of native T4 lysozyme was mutated to three different mutants and the structures were minimized. The minimized structures closely fit the crystal structures of the respective mutants (less than 0.3 A root-mean-square, RMS, deviation in the position of all heavy atoms). These results confirm the efficiency of the proposed minimization strategy in modeling closely related homologs. To determine the reliability of the united atom approximation, we also performed all of the above minimizations with united atom models. This approximation gave structures with similar but slightly higher RMS deviations than the all-atom model, but gave further savings of 60-70% in computer time. However, we feel further investigation is essential to determine the reliability of this approximation.(ABSTRACT TRUNCATED AT 400 WORDS)     

酶法合成2-氧-α-D-葡萄糖基-L-抗坏血酸(AA-2G)条件的研究

采用单因素优化法对环糊精葡萄糖苷转移酶(CGTase)合成糖基抗坏血酸(AA-2G)条件进行优化,AA-2G的产量为2.76 g/L,比未优化前0.46g/L提高了500%。再采用响应面法对AA-2G合成条件进行优化。由Plackett-Burman法筛选出三个主要因素为:pH、V_C和麦芽糊精浓度;由最陡爬坡实验得出最佳响应面区域;最后由Box-Behnken实验,得到最优条件为:pH 5.51,V_C36.16g/L,麦芽糊精28.54 g/L,转化时间24 h,温度37℃。在此条件下,AA-2G的理论产量为3.15 g/L,通过验证实验,得出AA-2G的产量为3.13 g/L,与预测的理论值接近,比单因素优化的结果(2.76g/L)提高了14%。     

耐底物腈水合酶融合子的产酶条件优化

采用正交设计法对耐底物腈水合酶融合子的发酵条件进行优化,以发酵液起始pH,发酵周期,接种量,装料系数作为考察因素,最终确定最佳发酵条件为:起始pH8.0、发酵周期54h、接种量12％、装液系数12％.在此优化条件下融合子腈水合酶的活力达到1100万U/ml,较优化前提高了83.3％.通过响应面法对发酵培养基配方进行优化研究,采用Plackett-Burman法对8个因素进行了筛选,结果表明,葡萄糖、尿素、磷酸氢二钾、磷酸二氢钾是影响发酵液腈水合酶产量的主效应因子.用最陡爬坡试验及Central composite design设计进一步优化,利用Design-Expert软件进行二次回归分析,得到各因素的最佳浓度为:葡萄糖22.62g/L、尿素9.76g/L、K2HP04 1.22g/L、KH2PO41.268g/L.在此培养基优化配方下融合子腈水合酶的活力达到1280万U/ml,较原配方的酶活提高了16.4％.     

响应面法优化Burkholderiasp．SYBCLIP—Y发酵产低温脂肪酶条件的研究

用响应面法对Burkholderiasp．SYBCLIP—Y液体发酵产低温脂肪酶的发酵条件进行了快速优化。首先利用Plackett—Burman设计对影响其产酶相关因素进行评估并筛选出具有显著效应的三个因素：牛肉膏,橄榄油,TritonX-100;用最陡爬坡路径逼近最大产酶区域后,利用响应面中心组合设计对显著因素进行优化,确定出牛肉膏,橄榄油,TritonX-100的最佳浓度分别为：牛肉膏31．8g／L、橄榄油21mL／L、TritonX-10036．55mL／L,优化后脂肪酶的酶活达到61．52U／mL,是优化前的2．62倍。     

SLIDER: a generic metaheuristic for the discovery of correlated motifs in protein-protein interaction networks

Correlated motif mining (cmm) is the problem of finding overrepresented pairs of patterns, called motifs, in sequences of interacting proteins. Algorithmic solutions for cmm thereby provide a computational method for predicting binding sites for protein interaction. In this paper, we adopt a motif-driven approach where the support of candidate motif pairs is evaluated in the network. We experimentally establish the superiority of the Chi-square-based support measure over other support measures. Furthermore, we obtain that cmm is an np-hard problem for a large class of support measures (including Chi-square) and reformulate the search for correlated motifs as a combinatorial optimization problem. We then present the generic metaheuristic slider which uses steepest ascent with a neighborhood function based on sliding motifs and employs the Chi-square-based support measure. We show that slider outperforms existing motif-driven cmm methods and scales to large protein-protein interaction networks. The slider-implementation and the data used in the experiments are available on http://bioinformatics.uhasselt.be.     

单因子-响应面法优化白地霉Y162产脂肪酶条件

对白地霉Y162液体发酵产脂肪酶的条件进行了优化。首先采用单因子实验筛选出最适碳源为橄榄油,氮源为黄豆粉和NH4Cl,无机盐为BaCl2和MgCl2。在此基础上,利用Plackett-Burman设计对影响产酶因素的效应进行评价,筛选出具有显著效应的橄榄油、BaCl2和NH4Cl三个最显著的因素。用最陡爬坡路径逼近最大产酶区域后,利用响应面中心组合设计对显著因素进行优化,得出橄榄油、BaCl2和NH4Cl最佳浓度分别为2.35％,0.36％,1.35％。优化后液体发酵液中脂肪酶活力提高到31.85 U/mL,比初始酶活力14.16 U/mL提高了2.25倍,表明单因子-响应面结合法可显著优化白地霉Y162液体发酵产脂肪酶条件。     

响应面法优化枯草芽孢杆菌产脂肪酶的合成培养基

对枯草芽孢杆菌(Bacillus subtilis)CICC20034利用合成培养基液体发酵产脂肪酶的条件进行了优化。首先采用单因子实验筛选出最适诱导剂为三丁酸甘油酯,氮源为尿素,碳源为葡萄糖,无机盐为MgSO4。在此基础上,利用Plackett-Burman设计对影响产酶因素的效应进行评价,筛选出具有显著效应的三丁酸甘油酯、尿素、KH2PO4和培养基起始pH值4个最显著的因素。用最陡爬坡路径逼近最大产酶区域后,利用响应面中心组合设计对显著因素进行优化,获得最适合成培养基组分为:葡萄糖8g/L,尿素8.57g/L,三丁酸甘油酯2.62%,KH2PO42.59g/L,MgSO4.7H2O0.5g/L,TritonX-1000.5g/L,pH9.47。优化后的B.subtilis CICC 20034胞外脂肪酶活力达0.483U/ml,比初始酶活力0.072U/ml提高了6.7倍。     

响应面法优化酿酒酵母产油脂条件

运用响应面法对酿酒酵母(Saccharomyces cerevisiae)产油脂以及发酵条件优化进行了研究。首先根据单因素实验结果,利用Plackett-Burman设计对影响其产油脂相关因素进行评估并筛选出具有显著效应的3个因素:柠檬酸,CaCl2和初始pH值。接着用最陡爬坡试验逼近以上3个因子的最大响应区域后,采用Box-Behnken设计以及响应面分析法,确定其优化后发酵条件为(w/v):葡萄糖15%,蛋白胨0.2%,酵母浸粉0.4%,柠檬酸0.471%,MgSO4·7H2O0.1%,ZnSO4·7H2O0.2%,CaCl20.025%,FeSO4·7H2O0.005%,初始pH值为6.74,180r/min,30°C培养96h。优化后的油脂产率(干重)达到14.55%,比在种子培养基中油脂产率4.76%提高了2倍左右。     

利用响应面法优化ε-聚赖氨酸发酵培养基

采用响应面法对白色链霉菌ZC7发酵合成ε-聚赖氨酸的培养基进行优化研究。采用Plackett-Burman法对8个因素进行了筛选,结果表明,葡萄糖、酵母膏和硫酸铵的浓度对ε-聚赖氨酸产量影响较大。用最陡爬坡试验及Box-Behnken设计进一步优化,利用Design-Expert软件进行二次回归分析,得到各因素的最佳浓度为:葡萄糖37.22 g/L,酵母膏6.9 g/L,硫酸铵6.55 g/L。在此优化条件下ε-聚赖氨酸的产量达到8.11 g/L,较单因素试验最高值提高24.6%。     

Galactomyces geotrichum Y25产脂肪酶条件的优化

应用响应面法对Galactomyces geotrichumY25液体发酵产脂肪酶的条件进行了优化。首先采用Plackett-Burman设计对影响产酶因素的效应进行评价,筛选出黄豆粉、玉米浆和发酵时间3个对产酶影响显著的因素。用最陡爬坡路径逼近最大产酶区域后,利用响应面设计对显著因素进行优化,得出黄豆粉、玉米浆最佳质量分数分别为2.51%、2.12%,最佳发酵时间101.95 h。优化后液体发酵液中脂肪酶活力提高到34.65 U/mL,比初始酶活力9.6 U/mL提高了3.61倍。表明响应面法可显著优化Galactomyces geotrichumY25液体发酵产脂肪酶条件。     

响应面分析法优化耐高温假黄色单胞菌硫氧化性能

【目的】采用响应面分析法对耐高温假黄色单胞菌的硫氧化性能进行优化。【方法】利用Plackett-Burman试验筛选影响菌株硫氧化性能的关键因子。通过最陡爬坡试验逼近最佳值区域,确定响应面试验中心轴,利用Box-Behnken设计和响应面分析法获得关键因素的最佳浓度。采用经典的改良硫酸钡比浊法测定硫酸根含量。【结果】牛肉膏、麦芽糖、镁离子(Mg~(2+))3个因素是影响菌株硫氧化性能的关键因素。响应面分析表明牛肉膏和镁离子的交互作用对硫酸根转化率的影响最大,优化后的结果为:麦芽糖(%)=0.07,牛肉膏(%)=0.11,Mg~(2+)(%)=0.04时,模型有最大值。模型的F值为52.60(P0.000 1),相关系数R2=0.980 2,说明该二次方程是显著的,该模型在整个回归区域内的拟合较好。经模拟堆肥试验验证该菌株可以有效增加堆肥中硫酸根含量。【结论】该模型可用于分析和预测耐高温假黄色单胞菌优化培养基配方,经优化后该菌株硫氧化性能大幅提升,硫酸根转化率由36.89%提高到80%以上,加入堆肥后与基础发酵条件下菌液相比更加有效增加了堆肥中SO_4~(2-)的含量,具有较好的应用前景。     

Molecular Modeling of Proteins: A Strategy for Energy Minimization by Molecular Mechanics in the AMBER Force Field

Abstract

Energy minimization is an important step in molecular modeling of proteins. In this study, we sought to develop a minimization strategy which would give the best final structures with the shortest computer time in the AMBER force field. In the all-atom model, we performed energy minimization of the melittin (mostly α-helical) and cardiotoxin (mostly β-sheet and β-turns) crystal structures by both constrained and unconstrained pathways. In the constrained path, which has been recommended in the energy minimization of proteins, hydrogens were relaxed first, followed by the side chains of amino acid residues, and finally the whole molecule. Despite the logic of this approach, however, the structures minimized by the unconstrained path fit the experimental structures better than those minimized by constrained paths. Moreover, the unconstrained path saved considerable computer time. We also compared the effects of the steepest descents and conjugate gradients algorithms in energy minimization. Previously, steepest descents has been used in the initial stages of minimization and conjugate gradients in the final stages of minimization. We therefore studied the effect on the final structure of performing an initial minimization by steepest descents. The structures minimized by conjugate gradients alone resembled the structures minimized initially by the steepest descents and subsequently by the conjugate gradients algorithms. Thus an initial minimization using steepest descents is wasteful and unnecessary, especially when starting from the crystal structure. Based on these results, we propose the use of an unconstrained path and conjugate gradients for energy minimization of proteins. This procedure results in low energy structures closer to the experimental structures, and saves about 70–80% of computer time. This procedure was applied in building models of lysozyme mutants. The crystal structure of native T₄ lysozyme was mutated to three different mutants and the structures were minimized. The minimized structures closely fit the crystal structures of the respective mutants (< 0.3 Å root-mean-square, RMS, deviation in the position of all heavy atoms). These results confirm the efficiency of the proposed minimization strategy in modeling closely related homologs. To determine the reliability of the united atom approximation, we also performed all of the above minimizations with united atom models. This approximation gave structures with similar but slightly higher RMS deviations than the all-atom model, but gave further savings of60-70% in computer time. However, we feel further investigation is essential to determine the reliability of this approximation. Finally, to determine the limitation of the procedure, we built the melittin molecule interactively in an α-helical conformation and this model showed an RMS deviation greater than 2.8 Å when compared to the melittin crystal structure. This model was minimized by various strategies. None of the minimized structures converged towards the crystal structure. Thus, although the proposed method seems to give valid structures starting from closely related crystal structures, it cannot predict the native structure when the starting structure is far from the native structure. From these results, we recommend the use of the proposed strategy of minimizing by an unconstrained path using the conjugate gradients algorithm, but only for modeling of closely related structural homologs of proteins.     

Optimization of inclusive fitness

The first fully explicit argument is given that broadly supports a widespread belief among whole-organism biologists that natural selection tends to lead to organisms acting as if maximizing their inclusive fitness. The use of optimization programs permits a clear statement of what this belief should be understood to mean, in contradistinction to the common mathematical presumption that it should be formalized as some kind of Lyapunov or even potential function. The argument reveals new details and uncovers latent assumptions. A very general genetic architecture is allowed, and there is arbitrary uncertainty. However, frequency dependence of fitnesses is not permitted. The logic of inclusive fitness immediately draws together various kinds of intra-genomic conflict, and the concept of 'p-family' is introduced. Inclusive fitness is thus incorporated into the formal Darwinism project, which aims to link the mathematics of motion (difference and differential equations) used to describe gene frequency trajectories with the mathematics of optimization used to describe purpose and design. Important questions remain to be answered in the fundamental theory of inclusive fitness.     

侧孢短芽胞杆菌产生线虫侵染性蛋白酶的优化

采用单因素试验确定侧孢短芽胞杆菌G4产线虫侵染性蛋白酶的最佳碳氮源,通过Placket-Burman设计筛选影响蛋白酶活力的主效因子,最陡坡试验和Box-Behnken设计获得主效因子的最佳水平,建立线虫侵染性蛋白酶的最佳生产体系:葡萄糖9.78 g/L、牛肉膏16.65 g/L、磷酸氢二钾0.75 g/L、可溶性淀粉12.5 g/L、氯化钠0.75 g/L、硫酸镁0.5 g/L、初始pH值自然、装液量50 mL,37℃摇瓶培养32 h,蛋白酶活力可达12 379.41 U/mL,较优化前的2 476.3 U/mL提高了4倍。     

响应面法优化甘蔗糖蜜发酵产丁醇

以甘蔗糖蜜为底物,用响应面法对高丁醇比突变菌株拜氏梭菌(Clostridium beijerinckii)ART124发酵生产丁醇的培养条件进行优化.首先利用Plackett - Burman试验设计筛选出影响丁醇生产的3个重要因素CaCO3和NH4 HCO3和K2HPO4的用量,再通过最陡爬坡路径逼近最大向应区域,最后根据响应面中心组合设计理论,确定主要影响因素的最佳条件:CaCO3、NH4HCO3和K2HPO4的质量浓度分别为2.65、2.16和0.43 g/L.利用数学模型分析预测得甘蔗糖蜜质量浓度为30 g/L时,最佳的丁醇产量为8.10 g/L,比优化前提高了53.14％.在最佳工艺条件下得到的实验结果与模型预测值很吻合,说明所建立的模型是有效的.