基于DoseResp模型的角蛋白酶发酵策略研究及其在血栓降解中的应用
作者:
基金项目:

国家自然科学基金(32301283, 21978116);中央高校基本科研业务费专项资金(JUSRP22047)


Keratinase: fermentation optimization based on DoseResp model and application in thrombolysis
Author:
  • 摘要
  • | |
  • 访问统计
  • |
  • 参考文献 [18]
  • |
  • 相似文献 [20]
  • | | |
  • 文章评论
    摘要:

    【目的】角蛋白酶是一类具有高效降解角蛋白纤维特性的丝氨酸蛋白酶,角蛋白酶的高效工业化生产有利于促进其在制革、纺织、饲料、肥料、日化、医疗等领域的广泛应用。本研究以课题组前期自主构建的重组角蛋白酶工程菌枯草芽孢杆菌(Bacillus subtilis) WB600-pMA5-KerBv为研究对象,通过系统的发酵优化提升工程菌的产酶能力,并创新探究角蛋白酶在降解血栓纤维蛋白中的应用潜力。【方法】通过单因素试验确定发酵培养基成分,随后借助响应面分析方法优化产角蛋白酶的发酵培养基,确定对菌体生长和产酶具有显著影响的因素及最优浓度。基于DoseResp模型通过预测菌种最佳生长点指导其在5 L发酵罐水平的扩大产酶。最后通过血栓以及纤维蛋白原降解试验探究角蛋白酶对血栓纤维蛋白的降解能力。【结果】经优化确定重组菌产角蛋白酶的最佳发酵培养基为(g/L):葡萄糖25.0,酵母粉25.0,豆粕15.0,磷酸氢二钾14.04,磷酸二氢钾2.58,氯化镁0.3;基于DoseResp模型通过预测菌种最佳生长点指导5 L发酵罐水平扩大生产,在优化条件下,细菌浓度OD600从摇瓶的2.45提高至77.80,酶活从摇瓶的4 471 U/mL升至21 301.67 U/mL,提高约4.76倍。该角蛋白酶对纤维蛋白原以及血液凝块均表现出显著的降解能力。【结论】本研究通过系统的发酵优化以及基于模型预测的罐上产酶研究,有效提高了角蛋白酶在枯草芽孢杆菌中的发酵产量,并为该酶在血栓降解领域的应用提供了研究基础,同时拓展了角蛋白酶的应用价值。

    Abstract:

    [Objective] Keratinases, a class of serine proteases capable of degrading keratin, have important application potential and research value in the utilization of keratin resources. The efficient industrial production of keratinase is helpful to promoting its application in leather, textiles, feed, chemical fertilizers, daily chemicals, and medicine. In this study, we optimized the fermentation conditions of Bacillus subtilis WB600-pMA5-KerBv, a recombinant keratinase-producing strain constructed in our laboratory, to improve the enzyme production. Furthermore, we explored the potential application of keratinase in the degradation of fibrin. [Methods] First, the composition of the fermentation medium was determined by single factor experiments. Then, response surface methodology was employed to optimize the medium formula for producing keratinase, and the factors significantly affecting the growth and enzyme production of bacteria and the optimum concentrations were determined. Subsequently, the DoseResp model was adopted to predict the optimal growth point of the strain and thus guide the expansion of enzyme production in a 5 L fermenter. Finally, the blood clot and fibrinogen degradation experiments were carried out to evaluate the degradation performance of the keratinase. [Results] The formula of the fermentation medium for producing keratinase by the recombinant strain was optimized as follows (g/L): glucose 25.0, yeast powder 25.0, soybean meal 15.0, dipotassium phosphate 14.04, potassium dihydrogen phosphate 2.58, and magnesium chloride 0.3. The optimal growth point of the strain was predicted based on the DoseResp model to guide the expansion of production in a 5 L fermenter. Under the optimized conditions, the OD600 (bacterial biomass) increased from 2.45 in a shake flask to 77.80, and the enzyme activity increased by about 4.76 times from 4 471 U/mL in a shake flask to 21 301.67 U/mL. In addition, the keratinase showcased remarkable degradation ability on fibrinogen and blood clots. [Conclusion] The systematic fermentation optimization and model-based prediction of enzyme production in fermenters improved the production of keratinase in Bacillus subtilis. The findings provided a research basis for the application of keratinase in thrombolysis.

    参考文献
    [1] 叶金鹏, 龚劲松, 陈霞, 蒋敏, 李恒, 李会, 许正宏, 史劲松. 微生物角蛋白酶在纳米粒子制备中的应用[J]. 化工进展, 2020, 39(11): 4575-4580. YE JP, GONG JS, CHEN X, JIANG M, LI H, LI H, XU ZH, SHI JS. Application of microbial keratinase in biopreparation of AuNPs[J]. Chemical Industry and Engineering Progress, 2020, 39(11): 4575-4580 (in Chinese).
    [2] SU C, GONG JS, WU ZX, LIU YL, LI H, SHI JS, XU ZH. Development of a growth-dependent system to regulate cell growth and keratinase production in B. subtilis[J]. Journal of Agricultural and Food Chemistry, 2023, 71(5): 2421-2429.
    [3] NNOLIM N, NWODO U. Abstract 1184: utilization of keratinous chicken feathers for the extracellular production of keratinase by Bacillus sp. CSK2: keratinolytic enzyme characterization[J]. Journal of Biological Chemistry, 2023, 299(3): 103686.
    [4] LI QX. Structure, application, and biochemistry of microbial keratinases[J]. Frontiers in Microbiology, 2021, 12: 674345.
    [5] SU C, GONG JS, SUN YX, QIN JF, ZHAI S, LI H, LI H, LU ZM, XU ZH, SHI JS. Combining pro-peptide engineering and multisite saturation mutagenesis to improve the catalytic potential of keratinase[J]. ACS Synthetic Biology, 2019, 8(2): 425-433.
    [6] AKRAM F, AQEEL A, SHOAIB M, HAQ IU, SHAH FI. Multifarious revolutionary aspects of microbial keratinases: an efficient green technology for future generation with prospective applications[J]. Environmental Science and Pollution Research, 2022, 29(58): 86913-86932.
    [7] 利刚慧, 刘俊杰, 彭帅英, 梁颖茵, 鄢陆琪, 李昆太. 重组枯草芽孢杆菌产角蛋白酶的发酵培养基及发酵条件优化[J]. 中国饲料, 2023(19): 29-36. LI GH, LIU JJ, PENG SY, LIANG YY, YAN LQ, LI KT. Optimization of fermentation medium and fermentation conditions for keratinase production by recombinant Bacillus subtilis[J]. China Feed, 2023(19): 29-36 (in Chinese).
    [8] 蒋彪, 王常高, 杜馨, 林建国, 蔡俊. 响应面法优化芽孢杆菌CJPE209产角蛋白酶发酵培养基的研究[J]. 中国酿造, 2017, 36(5): 76-80. JIANG B, WANG CG, DU X, LIN JG, CAI J. Optimization of fermentation medium for keratinase production from Bacillus sp. CJPE209 using response surface methodology[J]. China Brewing, 2017, 36(5): 76-80 (in Chinese).
    [9] 廖朝勇, 张铁鹰, 刘俊丽, 隋景巍. 枯草芽孢杆菌WB600角蛋白酶重组菌发酵条件优化[J]. 中国畜牧兽医, 2020, 47(1): 44-52. LIAO CY, ZHANG TY, LIU JL, SUI JW. Optimization of the fermentation conditions of recombinant B. subtilis WB600 produced keratinase[J]. China Animal Husbandry & Veterinary Medicine, 2020, 47(1): 44-52 (in Chinese).
    [10] 袁梦婷, 闫志英, 吕青阳, 刘杨, 杜亚玲, 宾石玉. CRISPR/Cas9介导的芽孢杆菌基因编辑及其在发酵菌种改造中的应用[J]. 应用与环境生物学报, 2023, 29(5): 1279-1288. YUAN MT, YAN ZY, LV QY, LIU Y, DU YL, BIN SY. CRISPR/Cas9-mediated gene editing in Bacillus and its application in the development of strains for industrial fermentation[J]. Chinese Journal of Applied & Environmental Biology, 2023, 29(5): 1279-1288 (in Chinese).
    [11] ZHANG JY, YANG YJ, LV RZ, ZHAN KH, CHANG XL, ZHANG CY. Sugar reduction process of purple sweet potato concentrated juice by microbial fermentation for improved performance of natural pigments[J]. Biochemical Engineering Journal, 2023, 191: 108781.
    [12] WANG ZJ, WANG ZY, WANG GX, ZHOU Z, HAO SM, WANG LL. Microalgae cultivation using unsterilized cattle farm wastewater filtered through corn stover[J]. Bioresource Technology, 2022, 352: 127081.
    [13] LI LH, LI N, WANG XL, GAO S, ZHANG J, ZHOU JW, WU ZM, ZENG WZ. Metabolic engineering combined with enzyme engineering for overproduction of ectoine in Escherichia coli[J]. Bioresource Technology, 2023, 390: 129862.
    [14] SU C, GONG JS, QIN JF, LI H, LI H, XU ZH, SHI JS. The tale of a versatile enzyme: molecular insights into keratinase for its industrial dissemination[削剝????副????佮卯?乯?????潶摡敮汣楥湳本?漲砰礲朰攬渠?搵椺猠猱漰氷甶琵椵漮渼?慲渾摛?戵楝漠汋潅杌楌挠慄求?甠灌瑁慕歂敓?摈畅牒椠湇杊?瀠畐汒獅敔?潒硉祕杓攠湅?愠摁搠楣瑥楮潴湲獡?椠湲?潬敥渠潦汯潲朠楡捭慹汬?晩敤爠浦敩湢瑲慩瑮椠潭湩獣孲?嵣???楳漠灩牮漠捬敯獮獧?慃湏摖??椯潐獁祓獃琺攠浯獲??湩杮楳渠敡敮牤椠湴杨???ば??????????????????????戠牔?孥㈠?嵩?卣??剭???剬????噲??卬??嘲攰爲猲愬琠椴氷椹琨礴?愺渠搵″挷漭洵洵改爮挼楢慲氾?猱琶慝琠畔獁?漠晌?洬椠捇牏潎扇椠慊汓?欠敓牕愠瑃椬渠慊獉敁獎??慍?爠敌癉椠效眬嬠?嵉??刬攠癌楕攠睚獍?椠湘??湚癈椬爠潓湈浉攠湊瑓愮氠?卩据楩敮湧挠敡?慤渠摥??楲潥?味敩捯桮渠潯汦漠条礠???ち??????????????????扡牴?孮??嵥?偲????????呬?传?卯佲丠??????乴啨乥?卩??????乩????删???呯?????乣????告???摁敃?嘠?????剴卥?坩?卬??摓散????剥??????丠????剮???呩?????????????倩刺?吱伳到?唭匱″???匼敢牲甾浛?愷浝礠汚潈楁摎???戬椠湓摕猠?琬漠?晏楎扇爠楘湌?漠杇敏湎???灓爬漠浌潉瑕椠湙杌?映楌扉爠楈測?慑浉祎氠潊楆搬?晘潕爠浚慈琬椠潓湈孉?嵊??匠捄楩敲湥瑣楴晥楤挠?剶敯灬潵牴瑩獯???ひ?????????????扥牲?孴??嵮???丠??娠??婦??乩???????啡??????唠????????乴?????楩潬摩整条牴慥搠慴瑨楥漠湦?潡晴?睥潲漠汤?睧慲獡瑤敡?慩湯摮?歊敝爮愠瑂楩湯慲獥敳?灵牲潣摥畳挠瑡楮潤渠?楩湯?獲捯慣汥敳?畩灮?昬攠爲洰攲渲琬攠爹?眱椩琺栠″搸椮昼晢敲爾敛渱琸?猠瑁牓慔瑒敕材椠敔猬?才祕??楅?協瑚攠湓漮琠牔潨灥栠潦浩潢湲慩獮?浰慬污瑴潥瀠桭楥汴楨慯??楦?????????孴?嵮???楩潢牲敩獮潯畬特捴敩?吠敡捣桴湩潶汩潴杹祛??金???????づ???????????扭物?孴??崠????佂?奯兰??塳?佣乳????‵???伴‰娨儲???匳??儭″?刱??婢??乛????????????娠??乕?奌奆??????????奉?乌??婌??????乚???????丬?卒坅???漬搠畗汕愠牌?攮渠李楥湷攠敭牥楴湨杯?琠潯?攠湴桨慲湯捭敢?歳攠牰慲瑥楰湡慲獡整?灯牮漠摵畳捩瑮楧漠湡?晦潬牵?扤椠潭瑯牤慥湬猠晦潯牲洠慥瑶楡潬湵?潴晩?摮椠獯捦愠牴摨敲摯?晢敥慣瑴桯敭特猠孤?嵶???灳瀠汩楮攠摡??楷潩据桥攠浭楯獤瑥牬祛?慝渮搠??楲潯瑭敢捯桳湩潳氠潒来祳???っ???′????????ㄨ??呼???????戰爹?嬮监?嵲 ̄??唰?????婎??乏??????啃?????唬????????乊???????佒?塁剕???潅洬瀠慎爦慅瑡楣癵整?愻湍慅汔祈猠椦獁?潣晵?扥愻挮琠敐牲楥慤汩?整硩灯牮攠獯獦椠潳湵?獦祡獣瑴敩浮猠?晥潲牭?歮整牡慴瑩楯湮愠獷敩?灨爠漼摩甾捂瑡楣潩湬孬?嵳???灢灴汩楬敩摳??楩漾挠桄敓浍椱猰琠牢祹?慲湥摳??楮潳瑥攠捳桵湲潦污潣来礠???と?????????????????ㄠ????ficial neural network[J]. Cell Biochemistry and Function, 2023, 41(2): 234-242.
    [21] MOHAMAD NL, MUSTAPA KAMAL SM, MOKHTAR MN, HUSAIN SA, ABDULLAH N. Dynamic mathematical modelling of reaction kinetics for xylitol fermentation using Candida tropicalis[J]. Biochemical Engineering Journal, 2016, 111: 10-17.
    [22] XU H, TIAN YJ, WANG SS, ZHU KF, ZHU L, HE QZ, LI WJ, LIU JJ. Batch fermentation kinetics of acetoin produced by Bacillus subtilis HB-32[J]. Preparative Biochemistry & Biotechnology, 2021, 51(10): 1004-1007.
    [23] SIBLEY M, WARD JM. A cell engineering approach to enzyme-based fed-batch fermentation[J]. Microbial Cell Factories, 2021, 20(1): 146.
    [24] SAA PA, MOENNE MI, PÉREZ-CO
    引证文献
    网友评论
    网友评论
    分享到微博
    发 布
引用本文

刘燕凌,苏畅,龚劲松,陈玉新,李恒,许正宏,史劲松. 基于DoseResp模型的角蛋白酶发酵策略研究及其在血栓降解中的应用[J]. 微生物学报, 2024, 64(9): 3330-3344

复制
分享
文章指标
  • 点击次数:156
  • 下载次数: 607
  • HTML阅读次数: 468
  • 引用次数: 0
历史
  • 收稿日期:2024-02-27
  • 最后修改日期:2024-04-11
  • 在线发布日期: 2024-08-30
  • 出版日期: 2024-09-04
文章二维码