基因组重排筛选高产谷氨酰胺转胺酶菌株

谷氨酰胺转胺酶(TGase)的产量不足的问题一直限制其工业化生产规模,故采用基因组重排的方法,筛选高产谷氨酰胺转胺酶菌株。通过对不同制备条件下原生质体纯度和形成率的考量,获得制备原生质体的最优条件为以6mg/ml的溶菌酶浓度进行酶解,酶解时间2h。再优化融合条件,以2min紫外灭活和40min热灭活结合的方法挑选出融合子。通过两轮基因组重排,经过96孔板发酵高通量筛选和摇瓶发酵复筛验证,获得了一株产酶达7.12U/ml的茂源链霉菌,相比最初选用菌株的平均酶活提高65.5%。发酵结果显示,酶活提高的原因可能是在重组后原酶成熟更快、更彻底,且得到的菌株遗传稳定性良好。证明基因组重排能够有效提高菌株的产酶水平,同时为谷氨酰胺转胺酶产量提高提供理论依据。     

基因组重排筛选高产谷氨酰胺转胺酶菌株

谷氨酰胺转胺酶(TGase)的产量不足的问题一直限制其工业化生产规模,故采用基因组重排的方法,筛选高产谷氨酰胺转胺酶菌株。通过对不同制备条件下原生质体纯度和形成率的考量,获得制备原生质体的最优条件为以6mg/ml的溶菌酶浓度进行酶解,酶解时间2h。再优化融合条件,以2min紫外灭活和40min热灭活结合的方法挑选出融合子。通过两轮基因组重排,经过96孔板发酵高通量筛选和摇瓶发酵复筛验证,获得了一株产酶达7.12U/ml的茂源链霉菌,相比最初选用菌株的平均酶活提高65.5%。发酵结果显示,酶活提高的原因可能是在重组后原酶成熟更快、更彻底,且得到的菌株遗传稳定性良好。证明基因组重排能够有效提高菌株的产酶水平,同时为谷氨酰胺转胺酶产量提高提供理论依据。     

酿酒酵母和克鲁维酵母发酵菊芋生产燃料乙醇

为获得菌株发酵菊芋生产燃料乙醇的最佳方案,首先选取实验室保存的重组菌株R32对其产酶条件进行优化,其最高产菊粉酶活性为298.8 U· mL-1,此时的最佳培养基配方为:YPG培养基为酵母粉1％ (w/v),蛋白胨2％ (w/v),甘油0.5％ (v/v);YPM培养基为酵母粉1％ (w/v),蛋白胨2％ (w/v),甲醇1％(v/v);培养基pH为自然初始pH.然后选取酿酒酵母S.c和克鲁维酵母Klu,比较是否在添加重组菌株R32粗酶液条件下,两株酵母菌分别进行单独发酵和混合发酵时的产乙醇能力,以获得最佳的发酵组合.结果表明,酿酒酵母S.c和克鲁维酵母Klu在未添加重组菌株R32粗酶液时,混合一步发酵获得的乙醇含量较高,发酵84 h时乙醇含量为11.37％.添加重组菌株R32粗酶液进行两步发酵时,2株酵母菌混合发酵72 h时,乙醇含量为11.43％.2种发酵组合的最高乙醇含量以及各个发酵参数基本相同,虽然一步法发酵时间延长,但节省成本,操作简单,更适宜工业生产应用.最后对其进行正交试验优化,培养条件为菊粉浓度225 g· L-1,脲素浓度40 g·L-1,接种量15％,pH为5时,酿酒酵母菌S.c和克鲁维酵母Klu混合一步发酵法的最高乙醇体积比达11.82％.     

内切葡聚糖酶高产菌株的诱变选育

【目的】建立里氏木霉(Trichoderma reesei)高产突变菌株的快速筛选方法,选育出高产内切葡聚糖酶的突变株。【方法】对里氏木霉T306菌株的初筛培养基进行优化,建立快速筛选方法;通过紫外诱变手段选育内切葡聚糖酶高产突变菌株,并对突变菌株的产酶培养基进行优化。【结果】在初筛培养基中添加浓度为0.1%(W/V)的乳糖、蛋白胨及脱氧胆酸钠有利于菌株的筛选。诱变后筛选出菌落形态发生明显变化的内切葡聚糖酶高产突变株0516,其羧甲基纤维素酶活力(CMC酶)较出发菌株提高了38.9%。其产酶培养基经优化后,得到最适碳、氮源分别为:乳糖1.50%、硫酸铵0.14%、尿素0.05%、蛋白胨0.10%,优化后CMC酶活力达64.2 U/mL,较优化前提高了2.3倍。【结论】建立了里氏木霉高产突变菌株的快速筛选方法,通过紫外诱变育种获得了产内切葡聚糖酶能力高且遗传稳定的突变株0516。     

C．shehatae TZ8耐乙醇菌株的筛选及发酵性能研究

以C.shehataeTZ8为出发茵株,利用1％溶壁酶和1％蜗牛酶酶解1．5h,制备成C.shehataeTZ8原生质体,并对原生质体进行紫外诱变,以含不同浓度乙醇的木糖液体培养基培养进行初筛和复筛,获得一株遗传性能稳定、耐乙醇能力达5．5％（v／v）的蕾株C．shehataeTZ8-4,比初始菌株耐乙醇能力提高了2％。对突变株C．shehataeTZ8-4发酵性能的研究结果表明：C．shehataeTZ8-4发酵糖能力从80g/L（葡糖糖和木糖比为2：1）提高到120g／L,最大乙醇产量从27．41g／L提高到43．12g／L。     

提高展青霉(Penicillium patulum)产灰黄霉素效价的诱变育种研究

为进一步筛选高产灰黄霉素的工业生产菌株,分别对前期采用紫外线-氯化锂（UV-LiCl）、半导体激光（LD laser）及CO2激光（CO2laser）对展青霉FS80-1复合诱变获得三株高产菌株进行液体发酵和固体培养比较。结果表明,通过UV-LiCl复合诱变获得突变菌株GM120-43的液体发酵产灰黄霉素效价11 982μg/mL,比出发菌株提高37.52%,固体培养效价为89 496μg/g（干重）,比出发菌株提高80.04%。;半导体激光诱变获得突变株LD100-1的液体发酵效价9 440μg/mL,固体培养效价119 766μg/g干重,比出发菌株FS80-1提高了140%;两个突变株的生物学特性均发生不同程度的变化,突菌株GM120-43适合于液体发酵生产,突变株LD100-1适合于固体发酵培养。     

米根霉乙醇脱氢酶(ADH)突变菌株的诱变选育

米根霉发酵生产L-乳酸过程中,由于丙酮酸在丙酮酸脱羧酶、乙醇脱氢酶(ADH)催化下生成乙醇,使得丙酮酸向乳酸转化的流量减少。采用亚硝基胍(NTG)诱变米根霉AS3．3462孢子液,诱变剂量为0．15 mg/ mL时,致死率为70%～80%。在含丙烯醇的YPD筛选培养基上筛选获得两株ADH活力降低的突变株mut-1和mut-2,检测突变株mut-1和mut-2的最大ADH活力分别为35．67和43．09U/mL,是原始菌株的41．63%和50．29%。发酵72h后,原始菌株的乙醇与乳酸浓度分别为28．9g/L和40．31g/L,而mut-1和mut-2突变株的乙醇产量分别为4．87g/L和6．56g/L,乳酸产量为54．45g/L和44．07g/L。在相同的发酵条件下,米根霉ADH突变株mut-1和mut-2对还原糖的利用速率高于出发菌株,其生物量积累亦高于出发菌株。     

产氢菌的复合诱变选育及突变株HCM-23的产氢特性

以厌氧产氢细菌Clostridium sp. H-61为原始菌株, 先后经亚硝基胍(NTG)、紫外(UV)诱变, 选育得到1株高产突变株HCM-23。在葡萄糖浓度为10 g/L的条件下, 其产氢量为3024 mL/L, 比原始菌株提高了69.89%; 其最大产氢速率为33.19 mmol H2/g DW·h, 比原始菌株(19.74 mmol H2/g DW·h)提高了68.14%。经过多次传代试验, 稳定性良好。其发酵末端产物以乙醇和乙酸为主, 属于典型乙醇型发酵代谢类型。其最适产氢初始pH为6.5, 最适生长温度为36℃, 以蔗糖为最佳碳源。与原始菌株相比, 突变株HCM-23的产氢特性发生了改变, 如生长延滞期延长, 可利用无机氮源等。     

基因组重排与传统育种相结合选育大观霉素高产菌株

以壮观链霉菌(Streptomyces spectabilis)为研究对象,采用基因组重排技术与传统诱变育种相结合的方法选育大观霉素的高产菌株.通过原生质体紫外诱变获得壮观链霉菌突变体群体,高产突变菌株间进行两轮的基因组重排,筛选的高产菌株用NTG诱变得新霉素和链霉素的抗性突变菌株,抗性突变菌株间进行两轮基因组重排,从...     

解脂耶氏酵母诱变育种及发酵产α-酮戊二酸条件优化

对具有发酵产α-酮戊二酸能力的解脂耶氏酵母(Yarrowia Lipolytica)ZY-4进行了紫外诱变和NTG诱变育种,筛选得到产量提高的突变株,并对突变株的发酵培养基进行了优化,结果表明,紫外诱变和NTG诱变后筛选到的突变株分别比原始出发菌株产量提高了67.8%和110%。优化后发酵培养基成分为甘油8%,氯化铵5.0 g/L,硫胺素1.0μg/L,磷酸二氢钾1.0 g/L,七水硫酸镁0.5 g/L,培养基优化后α-酮戊二酸产量比原始出发菌株提高了232.4%。     

Genome shuffling to improve thermotolerance,ethanol tolerance and ethanol productivity of <Emphasis Type="Italic">Saccharomyces cerevisiae</Emphasis>

Genome shuffling is a powerful strategy for rapid engineering of microbial strains for desirable industrial phenotypes. Here we improved the thermotolerance and ethanol tolerance of an industrial yeast strain SM-3 by genome shuffling while simultaneously enhancing the ethanol productivity. The starting population was generated by protoplast ultraviolet irradiation and then subjected for the recursive protoplast fusion. The positive colonies from the library, created by fusing the inactivated protoplasts were screened for growth at 35, 40, 45, 50 and 55°C on YPD-agar plates containing different concentrations of ethanol. Characterization of all mutants and wild-type strain in the shake-flask indicated the compatibility of three phenotypes of thermotolerance, ethanol tolerance and ethanol yields enhancement. After three rounds of genome shuffling, the best performing strain, F34, which could grow on plate cultures up to 55°C, was obtained. It was found capable of completely utilizing 20% (w/v) glucose at 45–48°C, producing 9.95% (w/v) ethanol, and tolerating 25% (v/v) ethanol stress.     

Improved ethanol production by a xylose-fermenting recombinant yeast strain constructed through a modified genome shuffling method

ABSTRACT: BACKGROUND: Xylose is the second most abundant carbohydrate in the lignocellulosic biomass hydrolysate. The fermentation of xylose is essential for the bioconversion of lignocelluloses to fuels and chemicals. However the wild-type strains of Saccharomyces cerevisiae are unable to utilize xylose. Many efforts have been made to construct recombinant yeast strains to enhance xylose fermentation over the past few decades. Xylose fermentation remains challenging due to the complexity of lignocellulosic biomass hydrolysate. In this study, a modified genome shuffling method was developed to improve xylose fermentation by S. cerevisiae. Recombinant yeast strains were constructed by recursive DNA shuffling with the recombination of entire genome of P. stipitis with that of S. cerevisiae. RESULTS: After two rounds of genome shuffling and screening, one potential recombinant yeast strain ScF2 was obtained. It was able to utilize high concentration of xylose (100 g/L to 250 g/L xylose) and produced ethanol. The recombinant yeast ScF2 produced ethanol more rapidly than the naturally occurring xylose-fermenting yeast, P. stipitis, with improved ethanol titre and much more enhanced xylose tolerance. CONCLUSION: The modified genome shuffling method developed in this study was more effective and easier to operate than the traditional protoplast fusion based method. Recombinant yeast strain ScF2 obtained in this was a promising candidate for industrial cellulosic ethanol production. In order to further enhance its xylose fermentation performance, ScF2 needs to be additionally improved by metabolic engineering and directed evolution.     

Improvement of robustness and ethanol production of ethanologenic Saccharomyces cerevisiae under co-stress of heat and inhibitors

Bioethanol is an attractive alternative to fossil fuels. Saccharomyces cerevisiae is the most important ethanol producer. However, yeast cells are challenged by various environmental stresses during the industrial process of ethanol production. The robustness under heat, acetic acid, and furfural stresses was improved for ethanologenic S. cerevisiae in this work using genome shuffling. Recombinant yeast strain R32 could grow at 45°C, and resist 0.55% (v/v) acetic acid and 0.3% (v/v) furfural at 40°C. When ethanol fermentation was conducted at temperatures ranging from 30 to 42°C, recombinant strain R32 always gave high ethanol production. After 42 h of fermentation at 42°C, 187.6 ± 1.4 g/l glucose was utilized by recombinant strain R32 to produce 81.4 ± 2.7 g/l ethanol, which were respectively 3.4 and 4.1 times those of CE25. After 36 h of fermentation at 40°C with 0.5% (v/v) acetic acid, 194.4 ± 1.2 g/l glucose in the medium was utilized by recombinant strain R32 to produce 84.2 ± 4.6 g/l of ethanol. The extent of glucose utilization and ethanol concentration of recombinant strain R32 were 6.3 and 7.9 times those of strain CE25. The ethanol concentration produced by recombinant strain R32 was 8.9 times that of strain CE25 after fermentation for 48 h under 0.2% (v/v) furfural stress at 40°C. The strong physiological robustness and fitness of yeast strain R32 support its potential application for industrial production of bioethanol from renewable resources such as lignocelluloses.     

Genome shuffling enhanced L-lactic acid production by improving glucose tolerance of Lactobacillus rhamnosus

Genome shuffling is a powerful strategy for rapid engineering of microbial strains for desirable industrial phenotypes. Here we applied the genome shuffling to improve the glucose tolerance of Lactobacillus rhamnosus ATCC 11443 while simultaneously enhancing the L-lactic acid production. The starting population was generated by ultraviolet irradiation and nitrosoguanidine mutagenesis and then subjected for the recursive protoplast fusion. The positive colonies from library created by fusing the inactivated protoplasts were more likely to be screened on plates containing different concentrations of high glucose and 2% CaCO(3). Characterization of all mutants and wild-type strain in the shake flask indicated the compatibility of two optimal phenotypes of glucose tolerance and lactic acid enhancement. The lactic acid production, cell growth and glucose consumption of the best performing strain from the second round genome shuffled populations were 71.4%, 44.9% and 62.2% higher than those of the wild type at the initial glucose concentration of 150 g/l in the 16l bioreactor. Furthermore, the higher lactic acid concentrations were obtained when the initial glucose concentrations increased to 160 and 200 g/l in batch fermentation.     

Strain improvement of the pentose-fermenting yeast Pichia stipitis by genome shuffling

Genome shuffling based on cross mating was used to improve the tolerance of the pentose-fermenting yeast Pichia stipitis towards hardwood spent sulphite liquor (HW SSL). Six UV-induced mutants of P. stipitis were used as the starting strains, and they were subjected to 4 rounds of genome shuffling. After each round, improved strains were selected based on their growth on HW SSL gradient plates. Mutant libraries were established after each round and these improved mutant strains served as the starting pool for the next round of shuffling. Apparent tolerance to HW SSL on the gradient plate increased progressively with each round of shuffling up to 4 rounds. Selected improved mutants were further tested for tolerance to liquid HW SSL. After 4 rounds of shuffling, 4 mutants, two from the third round (designated as GS301 and GS302) and two from the fourth round (designated as GS401 and GS402), were selected that could grow in 80% (v/v) HW SSL. GS301 and GS302 grew also in 85% (v/v) HW SSL. GS301 was viable in 90% (v/v) HW SSL, although no increase in cell number was seen. The P. stipitis wild type strain (WT) could not grow on HW SSL unless it was diluted to 65% (v/v) or lower. Genome-shuffled strains with improved tolerance to HW SSL retained their fermentation ability. Fermentation performance of GS301 and GS302, the 2 strains that exhibited the best tolerance to liquid HW SSL, was assessed in defined media and in HW SSL. Both strains utilized 4% (w/v) of xylose or glucose more efficiently and produced more ethanol than the WT. They also utilized 4% (w/v) of mannose or galactose and produced ethanol to the same extent as the WT. GS301 and GS302 were able to produce low levels of ethanol in undiluted HW SSL.     

Genome shuffling of marine derived bacterium <Emphasis Type="Italic">Nocardia</Emphasis> sp. ALAA 2000 for improved ayamycin production

Genome shuffling is a recent development in microbiology. The advantage of this technique is that genetic changes can be made in a microorganism without knowing its genetic background. Genome shuffling was applied to the marine derived bacterium Nocardia sp. ALAA 2000 to achieve rapid improvement of ayamycin production. The initial mutant population was generated by treatment with ethyl methane sulfonate (EMS) combined with UV irradiation of the spores, resulting in an improved population (AL/11, AL/136, AL/213 and AL/277) producing tenfold (150 μg/ml) more ayamycin than the original strain. These mutants were used as the starting strains for three rounds of genome shuffling and after each round improved strains were screened and selected based on their ayamycin productivity. The population after three rounds of genome shuffling exhibited an improved ayamycin yield. Strain F3/22 yielded 285 μg/ml of ayamycin, which was 19-fold higher than that of the initial strain and 1.9-fold higher than the mutants used as the starting point for genome shuffling. We evaluated the genetic effect of UV + EMS-mutagenesis and three rounds of genome shuffling on the nucleotide sequence by random amplified polymorphic DNA (RAPD) analysis. Many differences were noticed in mutant and recombinant strains compared to the wild type strain. These differences in RAPD profiles confirmed the presence of genetic variations in the Nocardia genome after mutagenesis and genome shuffling.     

Evolution of Streptomyces pristinaespiralis for resistance and production of pristinamycin by genome shuffling

Improvement of pristinamycin production by Streptomyces pristinaespiralis was performed by using recursive protoplast fusion and selection for improved resistance to the product antibiotic in a genome shuffling format. A 100-mug/ml pristinamycin resistant recombinant, G 4-17, was obtained after four rounds of protoplast fusion, and its production of pristinamycin reached 0.89 g/l, which was increased by 89.4% and 145.9% in comparison with that of the highest parent strain M-156 and the original strain CGMCC 0957, respectively. The subculture experiments indicated that the hereditary character of high producing S. pristinaespiralis G 4-17 was stable. It is concluded that genome shuffling improves the production of pristinamycin by enhancing product-resistance in a stepwise manner. Pristinamycin fermentation experiments by recombinant G 4-17 were carried out in a 5-l fermentor, and its production of pristinamycin reached 0.90 g/l after 60 h of fermentation.     

Drug resistance marker-aided genome shuffling to improve acetic acid tolerance in <Emphasis Type="Italic">Saccharomyces cerevisiae</Emphasis>

Acetic acid existing in a culture medium is one of the most limiting constraints in yeast growth and viability during ethanol fermentation. To improve acetic acid tolerance in Saccharomyces cerevisiae strains, a drug resistance marker-aided genome shuffling approach with higher screen efficiency of shuffled mutants was developed in this work. Through two rounds of genome shuffling of ultraviolet mutants derived from the original strain 308, we obtained a shuffled strain YZ2, which shows significantly faster growth and higher cell viability under acetic acid stress. Ethanol production of YZ2 (within 60 h) was 21.6% higher than that of 308 when 0.5% (v/v) acetic acid was added to fermentation medium. Membrane integrity, higher in vivo activity of the H⁺-ATPase, and lower oxidative damage after acetic acid treatment are the possible reasons for the acetic acid-tolerance phenotype of YZ2. These results indicated that this novel genome shuffling approach is powerful to rapidly improve the complex traits of industrial yeast strains.     

Genome Shuffling of Clostridium acetobutylicum CICC 8012 for Improved Production of Acetone–Butanol–Ethanol (ABE)

Genome shuffling was applied to increase ABE production of the strict anaerobe C. acetobutylicum CICC 8012. By using physical and chemical mutagenesis, strains with superior streptomycin sulfate, 2-deoxy-D-glucose and butanol tolerance levels were isolated. These strains were used for genome shuffling. The best performing strain F2-GA was screened after two rounds of genome shuffling. With 55 g glucose/l as carbon source, F2-GA produced 22.21 g ABE/l in 72 h and ABE yield reached 0.42 g/g which was about 34.53 % improvement compared to the wild type. Fermentation parameters and gene expression of several key enzymes in ABE metabolic pathways were varied significantly between F2-GA and the wild type. These results demonstrated the potential use of genome shuffling to microbial breeding which were difficult to deal with traditional methods.