经济科学中心的科学活动在北威州-Strategieprojekt BioSC (No. 313/323-400-002 13) 框架内由创新、科学和研究部资助。作者感谢北莱茵-威斯特伐利亚和 Heine 大学的创新、科学和研究部, 在 CLIB 研究生集群工业生物技术领域获得了 Freier 的奖学金。从德国亥姆霍兹协会的 "亥姆霍兹创新实验室" 的 "授权空间计划" 中获得了进一步的资金支持 "微生物生物实验室--亥姆霍兹创新实验室"。

作者没有什么可透露的。

所提出的协议的一般性质允许各种适应,例如, 用于研究其他微生物表达式主机9,47,48,49,50,51, 或优化目标蛋白的其他属性, 如糖基化模式或二硫化物键。该议定书也可能需要适应现有的实验室设备。MBR 系统的集成允许增加实验吞吐量, 从而节省了大量时间。然而, 当用 MBR 系统替换完全检测和可控的生物反应器时, 结果的可伸缩性必须考虑8、37、52、53。使用 DOE 方法和数学建模有助于通过有效的实验规划和基于模型的数据解释15, 将测量数据的信息内容与所研究的目标54最大化。
对方法的修改 在这项研究中使用的多用途和可扩展的机器人液体处理系统旁边, 应该提到的是, 有几个较小的可供商业使用的液体处理系统, 它们能够执行这项任务, 并且可以放在层流工作台。如果没有自动移系统, 则根据 DOE 计划的不同媒体组合也可以通过使用单声道和/或多渠道管的手动移实现。由于手工准备更容易出错, 并且需要高度集中的工作很长一段时间, 建议准备较低数量的不同媒体组合。
根据被雇用的 MBR 系统的能力, 相应的耕种协议将变化。例如, 如果没有在线测量生物量的形成, 它可能就足以在生长试验完成后测量生物量的浓度。与 pH 值和溶解氧的在线监测相结合, 在几个 MBR 系统中实现, 可以安全地确定生长饱和度。原则上, 生长实验可以进行台胞单独放置在震动孵化器内, 而不使用一个 MBR 系统。在这种情况下, 必须确保适当的耕作条件: (1) 使用适当的几何台胞, 结合适当的震动频率和震动直径, 可以避免氧气有限的耕作,例如, 正方形96或24深井板操作在1000转每分钟在3毫米投掷或在250转每分钟在25毫米投掷, 分别。重要的是, 可实现的最大氧转移率越低, 主要碳源的浓度越低。如上所述, 在本研究中, 10 克/L 葡萄糖的使用适合于防止受雇的耕作条件的氧气限制;(2) 对生物量和产品定量的中期培养的抽样应减少到最低限度。每次将中期计划从摇箱中移除时, 氧气转移会立即分解, 从而导致不利的耕作条件;(3) 作者认为, 不建议使用中期计划读者作为培养设备, 因为这些设备不是为此目的开发的。例如, 振动力学是为偶尔混合板后的试剂添加, 因此, 往往缺乏鲁棒性长期连续晃动持续数天。此外, 这些读者无法实现微生物培育所需的足够功率输入。光密度读数在短时间间隔内的积分需要停止震动运动, 从而导致重复的氧限制周期。此外, 这种系统在长时间耕作期间的蒸发会扭曲结果。有关使用台胞进行微生物培育的令人惊讶的复杂主题的详细信息, 读者可以参考引用的文献22,23,24,25,26和其中的引用。
进一步考虑 为了加速迭代优化步骤, 建议仔细选择产品量化的分析方法。由于迭代实验设计策略容忍实验误差, 因此, 快速、简单的方法应以精度和精确度为代价。然而, 最终的结果必须得到验证, 以充分准确和准确的产品量化方法, 可能会更复杂。一般来说, 仔细的评估和决策的研究程序需要努力在开始的研究, 但长期支付, 在常规的方法已经建立。
强烈建议定义一个参照实验, 它与在优化过程中的所有实验进行比较。即, 所应用的介质成分浓度和测量输出均通过参考值进行归一化。这样, 每个应用和测量值都可以被解释为参考值的 x-fold。考虑到板块之间的变化, 每个板块都进行五参考实验。度量结果的平均值用于规范化。
一般不保证所开发的培养基对其他菌株也是最佳的。然而, 改良后的培养基也很可能适合培养具有小遗传差异的表达菌株,例如, 当产生由诱变研究获得的单一氨基酸替代品的酶变体时 (虽然单点突变已被描述为影响细胞代谢和外源表达性能55,56)。在这种情况下, 所提出的协议可以是第一步, 其次是高通量表达式筛选的协议57。如果协议被用于中等发展与随后扩大到哺养的分批耕种, 优选的媒介应该被核实为对应的生物条件, 当克隆筛选运动在微尺度辨认了不同的顶端执行者为不同的哺养的战略和耕种媒介52,58。此外, 引入的 KriKit36通常可以促进改进的整体生物优化。直到最近, 工具能力也被扩展到支持多目标优化40, 这对于优化上游和下游进程都很重要59,60。

现代重组基因技术能够广泛应用于制药工业、动物饲养、有机化学和食品加工等各种用途的技术酶1,2,3。大量生产技术酶是工业生物技术和优化重组蛋白生产的重要课题, 需要应变和生物工程。为产生高效的工程生产菌株, 可提供不同的遗传库,例如, 用于平衡基因表达式4或提高分泌效率5。
杆菌谷氨酸是一个主要的氨基酸生产者在工业规模的6,7和代表一个有吸引力的非常规表达载体的分泌生产重组蛋白8 ,9。一般分泌 (Sec) 和双精氨酸易位 (达) 通路均存在于C. 谷氨酸中, 并成功应用于重组蛋白分泌物10。广泛的经验, 在生物工程的氨基酸生产在工业规模, 以及能力分泌蛋白质的 g/L 金额11和强大的鲁棒性有关生物均匀发现大规模培育12,13, 使C. 谷氨酸成为在工业规模上分泌生产异源蛋白质的有前途的平台有机体。
营养培养基优化是已知的以微生物系统改善重组蛋白的生产14,15,16,17 , 因此, 介质的调整组合是在生物开发方面的一个值得一步, 关于最佳生产率18,19,20,21。孔板 (台胞) 在微生物培养中的应用研究22,23,24为微生物培养台胞的开发和设计铺平了道路25 ,26和开发具有在线监视和环境控制的 MTP-based microbioreactor (MBR) 系统27,28。MBRs 能显著提高实验培养的产量。此外, MBR 系统从其他类型的生物反应器,例如, 气泡柱或搅拌槽反应器, 可用于微生物生物优化29,30,31, 32。
一般而言, 优化研究得益于增加的实验吞吐量, 这与 DOE 的方法结合起来更加强大, 例如评估设计变量之间的交互或减少高维搜索空间。因此, MBR 系统、实验室自动化和 DOE 的联合使用证明是生物技术中的一种强有力的方法8,16,33,34,35。
本文将先进的实验室自动化、MBR 技术与在线过程监控、Kriging-based 数据分析/实验设计相结合, 提出了一种媒体优化协议。克里格方法是在 MATLAB 工具箱 ("KriKit") 中实现的, 它可以下载并免费使用36。以应用实例为例, 通过优化 CgXII 最小介质的组成, 展示了利用C. 谷氨酸分泌的绿色ﬂuorescent 蛋白 (GFP) 的生产。选用 GFP 滴度作为最优化的目标, 可以方便地进行量化, 并广泛应用于 MBR 系统的模型蛋白质研究37,38,39。
所介绍的框架分为四步骤, 如图 1所示。这些步骤由方框框表示, 对应于协议的各个部分。第一步 (图 1A) 是定义项目目标并确定所需的方法。DOE 方法学、MBR 技术和实验室自动化的结合使得实验吞吐量增加, 需要强大的数据处理能力。第二步 (图 1B) 旨在检测对优化目标有很高影响的敏感设计变量 (即、中等组件)。这导致了设计变量的数量减少的利益。第三步 (图 1C) 包括一个迭代优化, 用于更详细地调查剩余的设计变量与感兴趣的目标之间的函数关系。利用逐次扩展的数据集, 应用克里格方法对未测地点的实验结果进行预测。当克里格模型预测到一个最优或高精度时, 迭代周期就会停止。在第四步 (图 1D) 中对结果进行了验证, 并开始对确定的最佳值进行进一步的灵敏度分析。如果最初, 不敏感的组件被发现在最佳区域也不敏感, 在第三步的迭代优化过程中假设这是正确的, 这是合理的。然后, 建议通过应用正交试验方法, 如活性分析或 SDS 页, 对优化结果进行验证。
所提出的协议的一般性质, 允许易于适应不同的实验室设备, 其他表达主机, 和目标蛋白的选择, 以及进一步的生物变量, 如 pH 值或培养温度。此外, 其他优化目标, 如蛋白质的生产率, 特定的产量, 或产品质量可以选择, 以适应范围的其他优化研究。
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/56234/56234fig1.jpg" style="font-size: 14px;"> 
图 1: 优化研究的工作流程.四帧框对应于协议的各节, "构思方法的研究和定义" (第1节), "灵敏度分析" (第2节), "迭代优化" (第3节) 和 "验证" (第4节)。<a href="//ecsource.jove.com/files/ftp_upload/56234/56234fig1large.jpg" style="font-size: 14px;" target="_blank">请单击此处查看此图的较大版本.</a>

<table><tbody><tr><td>BioLector</td><td>m2p-labs</td><td>G-BL-100</td><td></td></tr><tr><td>Flowerplate</td><td>m2p-labs</td><td>MTP-48-BOH</td><td>For cultivation in the BioLector device</td></tr><tr><td>Sealing foil</td><td>m2p-labs</td><td>F-GP-10</td><td>Sterile sealing for Flowerplate</td></tr><tr><td>MATLAB</td><td>Mathworks</td><td>2016b</td><td></td></tr><tr><td>KriKit</td><td>Forschungszentrum J&amp;uuml;lich</td><td>n/a</td><td>Freely available, MATLAB installation required</td></tr><tr><td>Janus pipetting robot</td><td>Perkin Elmer</td><td>n/a</td><td>Includes &quot;WinPrep&quot; software installation</td></tr><tr><td>12-column deep well microplate</td><td>E&amp;amp;K Scientific</td><td>EK-2034</td><td>Container for medium stock solutions</td></tr><tr><td>96 well microplates, transparent, F-bottom</td><td>Greiner</td><td>655101</td><td>For Bradford protein assay</td></tr><tr><td>&amp;micro;clear 96 well microplates, black body, transparent F-bottom</td><td>Greiner</td><td>655087</td><td>For flourescence measurement in cell-free supernatants</td></tr><tr><td>Pipette Research&amp;nbsp;plus multi-channel pipettes</td><td>Eppendorf</td><td>n/a</td><td>Facilitates manual liquid handling with microplates</td></tr><tr><td>TruPAG&amp;nbsp;Precast Gels</td><td>Sigma</td><td>PCG2002</td><td>For SDS-Page analysis of cell-free supernantants</td></tr><tr><td>Bradford Reagent</td><td>Sigma</td><td>B6916</td><td></td></tr><tr><td>&lt;em&gt;C. glutamicum&lt;/em&gt; pCGPhoD&lt;sup&gt;Bs&lt;/sup&gt;-GFP</td><td>n/a</td><td>n/a</td><td>Carries pEKEx2 plasmid with fusion of GFP gene and PhoD signal peptide from B.subtilis as expression insert. Plasmid provides kanamycin resistance. Described and published by Meissner et al.&lt;em&gt; &lt;/em&gt;&lt;em&gt;Appl Microbiol Biotechnol&lt;/em&gt; &lt;strong&gt;76&lt;/strong&gt; (3), 633&amp;ndash;42 (2007)</td></tr></tbody></table>

generic protocol for optimization of heterologous protein production using automated microbioreactor technology

工业生物技术的核心业务是利用微生物生产细胞工厂, 是应变工程的迭代过程和生物条件的优化。一个重要的方面是改善培养培养基, 为微生物形成的利益的产品提供一个最佳的环境。这是公认的媒体组成可以戏剧性地影响整体生物性能。营养培养基优化是已知的, 以改善重组蛋白生产与微生物系统, 因此, 这是一个值得一步的生物发展。然而, 通常标准的媒体食谱是取自文学, 因为 tailor-made 设计的培养介质是一个繁琐的任务, 要求 microbioreactor 技术, 以充分的种植吞吐量, 快速产品分析, 以及支持通过实验室机器人, 使液体处理步骤的可靠性。此外, 还需要有先进的数学方法来合理地分析测量数据, 并有效地设计并行实验, 以达到最佳的信息内容。
所提出的协议的一般性质允许容易适应不同的实验室设备, 其他表达主机, 和目标蛋白的兴趣, 以及进一步的生物参数。此外, 其他优化目标, 如蛋白质的生产率, 特定的产量, 或产品质量可以选择, 以适应范围的其他优化研究。应用的克里格工具箱 (KriKit) 是一个通用的工具设计的实验 (DOE), 有助于改进整体生物优化。它还支持多目标优化, 这对于优化上游和下游进程都是非常重要的。

引入的协议, 以最大限度地提高分泌 GFP 的效价。具体而言, 选择 17 h 培养后的 GFP 效价作为优化目标。在线荧光检测 GFP 允许简单的产品量化。然而, 从参考培养数据中获得 GFP 信号的规范化是确保结果的重现性和可比的必要条件。如1节所述, 对媒体组成部分的预选是在合理基础上进行的。根据1节的说明进行了实验: 为整个研究确定了湿实验室程序的参数, 以确保结果的一致性和重现性。
如2节所述, 进行了初步筛选, 以确定有关的成分对进一步、更详细的研究的优化目标有重大影响。MTP-based MBR 系统允许48实验并行执行。考虑到在一个中期计划 (48) 上最大可能的并行实验次数和媒体组件 (11) 的总数, 使得 2IV11-6小数设计成为一个合适的选择。该实验设计包括32实验, 并允许对每一个被调查的媒体组件的主要效果的估计。其余的培养井 (16) 用于多次复制的实验与参考介质, 以评估再现性和位置效应。即, 每个实验进行一次 (没有复制), 除了参考实验 (五复制)。
表 1总结了筛选分析的结果。在被考虑的集中范围, 变化多数媒介组分没有显示对目标的一个引人注目的作用。组件 NH4+显示了强烈的负面影响, 而 Ca2 +和 Mg2 +显示了最强的正向趋势。Mg2 +对当前浓度范围的影响并不显著, 但可能是因为浓度范围更广。因此, 决定从介质中省略 NH4+ , 并在进一步的实验中研究 Ca2 +和 Mg2 +的效果。
3节描述了用于最大化 GFP 荧光信号的迭代优化过程, 同时改变了 Ca2 +和 Mg2 +的浓度。在迭代1中, 测试了可以省略 NH4+的假设。筛选分析采用了 Ca2 +和 Mg2 +的浓度范围。将 NH4+的最小浓度设置为零, 并从筛选实验中采用最大浓度。在下面的实验中, 组分浓度分布在 3 x 3 x 3 格栅内的定义浓度范围, 导致27实验。在所有的耕种过程中, 都包括了五复制的参考培养基, 作为内部标准, 并确保没有在中期计划的位置影响发生。对于余下的16口井, NH4+、Ca2 +和 Mg2 +的浓度在给定范围内随机分布。
图 5A可视化第一次迭代的结果。轴标签指的是原始参考介质中使用的成分浓度, 由 x Ref. 表示蓝色曲面表示使用 KriKit 软件计算的克里格插。每个曲面与 NH4+ (深蓝色: 0 x ref, 方格: 1 x ref, 浅蓝色: 2 x ref) 的相对浓度水平相关联。这种可视化表示形式表明, 省略 NH4+是有利的。插值曲面还显示了 Mg2 +和 Ca2 +的正面效果, 因为所有的平面都随着浓度的增加而上升。
根据迭代1的结果, 决定将 Ca2 +和 Mg2 +的浓度范围扩大一倍, 并将实验设计窗口移到右上角, 请参阅图 5B. 在这个范围内, 浓度分布在 6 x 6 的网格上。这保证了均匀分布在充分的集中范围, 导致最佳的克里格插值结果。图 5B显示基于两次迭代 (红点和黄色正方形) 中的组合数据的克里格插值图。对于两者, Ca2 +和 Mg2 +, 增加其浓度的积极作用继续。因此, 该过程通过加倍的最大浓度重复, 从而, 实验设计窗口的移动, 以探索的边界右上角。
图 6A提供了剩余优化过程的概览。对迭代3所收集的数据的分析显示了 mg2 +的正效应的限制,即, 确定了 mg2 +的最佳浓度范围。因此, 决定只为 Ca2 + (迭代 4) 进一步扩展集中范围。此过程重复了两次 (迭代5和 6), 直到发现了 GFP 信号的饱和度。这种饱和度是由钙盐的沉淀所解释的, 适用浓度为 ca2 +, 这些单元格不可用。
由于实验结果总是被噪声干扰, 由此产生的克里格插值出现不规则和目视检查可能导致错误的结论。然而, 通过统计的z测试, 可以可靠地识别出饱和 GFP 信号的培养基组分的最佳浓度范围, 并在 KriKit 中实现。z测试直接使用克里格方法提供的内部统计信息,即即、预测值和预测不确定性。图 6B显示已标识的高原, 使用 KriKit 工具箱确定和可视化。KriKit 工具箱是免费提供的36 , 并附带了详细的教程, 说明如何使用其功能。
如果找到两个以上的相关组件, 3 d-可视化达到其极限。KriKit 提供了其他几种可能的可视化表示方法, 如电影或 "筛选情节"。如果潜在的优化位于定义的浓度范围内, 则将使用预期的改进4046自动设计新的实验。基于期望改进的实验设计集成在 KriKit 工具箱中。在软件文档中可以找到更详细的信息。
在迭代过程之后, 对结果进行了验证, 如第 D 部分所述。通过使用最佳介质组成进行附加灵敏度分析, 对初始假设的有效性进行了检验。即, 所有的初始媒体组件的兴趣是不同的, 但 Ca2 +和 Mg2 +被设置为其最佳浓度水平。在本研究中, 选择了最佳浓度 = 32 x ref 和 = 6.8 x ref. <img alt="Equation 8" src="/files/ftp_upload/56234/56234eq8v2.jpg"> <img alt="Equation 9" src="/files/ftp_upload/56234/56234eq9v2.jpg">表 2显示验证筛选的结果。与初始灵敏度筛选类似 (cf 表 1), NH4+仍有显著的负面影响, 剩余的影响仍然可以忽略不计。
由于容易获得, 从培养悬浮液中的 gfp 荧光信号被用来量化的细胞外 gfp 的效价在所有的实验。为了验证的原因, GFP 荧光验证了其他测量。由于 gfp 是通过达通路分泌的, 荧光信号不能区分和胞外 gfp。因此, 利用参考介质和优化培养基对栽培进行了复制。除了荧光测量从无细胞培养清, 蛋白质含量是量化的布拉德福德检测和 (半) 定性 GFP 改善可视化 SDS 页15。与参考介质相比, 所得到的优化培养基的所有结果测量信号大约为两倍, 并验证了优化培养基分泌性能的大约100% 的改善。因此, gfp 特异荧光的培养悬浮可以被认为是一个合适的指标的优化目标,即, 胞外 gfp 滴度。
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/56234/56234fig2.jpg"> 
图 2: 从卷移列表中进行敏感度分析的屏幕快照.第一列中的条目为一行的所有卷分配唯一标识符;此标识符是在液体处理程序工作台上的目标培养计划的中期计划井号,参见图 4C。剩余的列为不同的解决方案 ("Sln-01" 到 "Sln-15") 编码卷以 pipetted。一排的累计容积对应于相应井的最终栽培量。<a href="//ecsource.jove.com/files/ftp_upload/56234/56234fig2large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/56234/56234fig3.jpg"> 
图 3: 从液体处理控制软件 "WinPREP" 中截屏.左: 行顺序命令, 包括每个股票解决方案的转移命令 pipetted。在接种添加的最后一个命令之前, 将插入一个用户提示, 以确保种子区域性刚好放在表中。右: 工作台的示意图, 包括变异种群的源实验室 (两个深孔板, 有12柱状井), 用于休息库存的试剂槽, 水和接种, 以及培养基制备靶向培养中期计划。<a href="//ecsource.jove.com/files/ftp_upload/56234/56234fig3large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/56234/56234fig4.jpg"> 
图 4: 为库存解决方案的移设置详细截图的编译.(A) 移铁库存的非包装命令。在工作台上用相应的深井板的读框和红柱标记出源实验室和源井。目标实验室和目的井内的标志是蓝框周围和蓝水井的靶培养中期计划。(B) 有关此步骤 (Fe 库存解决方案) 的移卷分配的详细示例视图。从具有48行的移列表中读取目标的数量。移列表中的4栏中找到了所有用于 Fe 库存解决方案的目的井的免除量。请注意, 移列表中的第一列包含标识符, 而不是要传输的卷, 请参见图 2。(C) 有关目标井编号的详细信息。在相应的移列表的行 #1 中写入的卷将 pipetted 为 #1 等标记。井 #01, #08, #41 和 #48 对应于井 A01, A08, F01 并且 F08 为α数字编码, 也打印入耕种中期计划本身。<a href="//ecsource.jove.com/files/ftp_upload/56234/56234fig4large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/56234/56234fig5.jpg"> 
图 5: 第一次迭代的详细结果.(A) 基于迭代1的实验数据的克里格插值。红色点表示数据集。为比较, 所有三插值表面是堆在一个情节 (深蓝: 0 x 参考, 格子: 1 x 参考, 浅蓝色: 2 x 参考)。可以在其他15中找到结果的替代表示形式。(B) 克里格插值基于在迭代 1 (红点) 和迭代 2 (黄色正方形) 中执行的实验。此图中显示的部分数据以前已发布15。<a href="//ecsource.jove.com/files/ftp_upload/56234/56234fig5large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/56234/56234fig6.jpg"> 
图 6: 迭代收集的优化结果的描述.(A) 最后的克里格模型预测。(B) 基于统计的z测试的最佳区域 (red) 的统计标识 (由 KriKit 提供)。方框表示迭代设计和实验执行的连续步骤。此图中显示的部分数据以前已发布15。<a href="//ecsource.jove.com/files/ftp_upload/56234/56234fig6large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<table fo:keep-together.within-page="1">
	<tbody>
		<tr>
			<td>组件</td>
			<td>归一化系数均值</td>
		</tr>
		<tr>
			<td>Fe2 +</td>
			<td>-0.08</td>
		</tr>
		<tr>
			<td>锰2 +</td>
			<td>-0.05</td>
		</tr>
		<tr>
			<td>Zn2 +</td>
			<td>-0.21</td>
		</tr>
		<tr>
			<td>Cu2 +</td>
			<td>-0.21</td>
		</tr>
		<tr>
			<td>NH4+</td>
			<td>-2.04</td>
		</tr>
		<tr>
			<td>Ni2 +</td>
			<td>-0.11</td>
		</tr>
		<tr>
			<td>Co2 +</td>
			<td>-0.10</td>
		</tr>
		<tr>
			<td>MoO42-</td>
			<td>0.03</td>
		</tr>
		<tr>
			<td>BO33-</td>
			<td>0.06</td>
		</tr>
		<tr>
			<td>Ca2 +</td>
			<td>1.00</td>
		</tr>
		<tr>
			<td>Mg2 +</td>
			<td>0.45</td>
		</tr>
	</tbody>
</table>
表 1: 灵敏度分析的结果.系数值表示平均效果时, 增加各自的媒体组件集中从它的中心值, 以其最大值。对于最优化的实验设计, 如标准文献中所示, 标准偏差直接表现为参考实验的复制所引起的实验变化。系数值由最大值 (0.0422 用于组件 Ca2 +) 进行规范化。归一化和绝对系数标准差分别为0.54 和0.0226。
<table fo:keep-together.within-page="1">
	<tbody>
		<tr>
			<td>组件</td>
			<td>归一化系数均值</td>
		</tr>
		<tr>
			<td>Fe2 +</td>
			<td>-1.00</td>
		</tr>
		<tr>
			<td>锰2 +</td>
			<td>1.00</td>
		</tr>
		<tr>
			<td>Zn2 +</td>
			<td>-3.48</td>
		</tr>
		<tr>
			<td>Cu2 +</td>
			<td>-0.52</td>
		</tr>
		<tr>
			<td>NH4+</td>
			<td>-15.95</td>
		</tr>
		<tr>
			<td>Ni2 +</td>
			<td>0.69</td>
		</tr>
		<tr>
			<td>Co2 +</td>
			<td>-0.51</td>
		</tr>
		<tr>
			<td>MoO42-</td>
			<td>-0.45</td>
		</tr>
		<tr>
			<td>BO33-</td>
			<td>-1.11</td>
		</tr>
	</tbody>
</table>
表 2: 最终灵敏度分析的结果.系数值表示平均效果时, 增加各自的媒体组件集中从它的中心值, 以其最大值。由于采用了最佳的实验设计, 标准差只取决于实验的变化, 采用优化的介质组成。实验变异比使用参考介质的变异略有增加。系数值由最大值 (0.0106 用于组件锰2 +) 进行规范化。归一化和绝对系数标准差分别为3.63 和0.0385。

Watch this Scientific Journal Video about Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology at JoVE.com

Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology

利用自动 Microbioreactor 技术优化异种蛋白质生产的通用协议

这份手稿描述了 tailor-made 设计微生物培养介质的通用方法。这是由一个迭代工作流, 结合 Kriging-based 实验设计和 microbioreactor 技术的充分栽培吞吐量, 这是支持的实验室机器人, 以提高可靠性和速度在液体处理介质制备.

A core business in industrial biotechnology using microbial production cell factories is the iterative process of strain engineering and optimization of ...

generic-protocol-for-optimization-heterologous-protein-production

Universidad de Cartagena UDEC

Research

JoVE Journal

Bioengineering

9.9K 次观看.  Forschungszentrum Jülich. 这份手稿描述了 tailor-made 设计微生物培养介质的通用方法。这是由一个迭代工作流, 结合 Kriging-based 实验设计和 microbioreactor 技术的充分栽培吞吐量, 这是支持的实验室机器人, 以提高可靠性和速度在液体处理介质制备.

视频: Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology

A High-throughput Automated Platform for the Development of Manufacturing Cell Lines for Protein Therapeutics

The fast-growing biopharmaceutical industry demands speedy development of highly efficient and reliable production systems to meet the increasing requirement for drug supplies. The generation of production cell lines has traditionally involved manual operations that are labor-intensive, low-throughput and vulnerable to human errors. We report here an integrated high-throughput and automated platform for development of manufacturing cell lines for the production of protein therapeutics.
The combination of BD FACS Aria Cell Sorter, CloneSelect Imager and TECAN Freedom EVO liquid handling system has enabled a high-throughput and more efficient cell line development process. In this operation, production host cells are first transfected with an expression vector carrying the gene of interest 1, followed by the treatment with a selection agent. The stably-transfected cells are then stained with fluorescence-labeled anti-human IgG antibody, and are subsequently subject to flow cytometry analysis 2-4. Highly productive cells are selected based on fluorescence intensity and are isolated by single-cell sorting on a BD FACSAria. Colony formation from single-cell stage was detected microscopically and a series of time-laps digital images are taken by CloneSelect Imager for the documentation of cell line history. After single clones have formed, these clones were screened for productivity by ELISA performed on a TECAN Freedom EVO liquid handling system. Approximately 2,000 - 10,000 clones can be screened per operation cycle with the current system setup.
This integrated approach has been used to generate high producing Chinese hamster ovary (CHO) cell lines for the production of therapeutic monoclonal antibody (mAb) as well as their fusion proteins. With the aid of different types of detecting probes, the method can be used for developing other protein therapeutics or be applied to other production host systems. Comparing to the traditional manual procedure, this automated platform demonstrated advantages of significantly increased capacity, ensured clonality, traceability in cell line history with electronic documentation and much reduced opportunity in operator error.

A high-throughput, automated platform of manufacturing cell line development for producing protein therapeutics is described. Implementation of BD FACS Aria Cell Sorter, CloneSelect Imager and TECAN Freedom EVO liquid handling system has demonstrated significantly increased processing capacity in cell line development with improved cell line quality and high reproducibility.

一种高通量自动化的平台，制造蛋白质治疗的细胞系发展

The fast-growing biopharmaceutical industry demands speedy development of highly efficient and reliable production systems to meet the increasing ...

科研

医学

Immobilization of Multi-biocatalysts in Alginate Beads for Cofactor Regeneration and Improved Reusability

We have recently developed a simple, reusable and coupled whole-cell biocatalytic system with the capability of cofactor regeneration and biocatalyst immobilization for improved production yield and sustained synthesis. Described herewith is the experimental procedure for the development of such a system consisting of two E. coli strains that express functionally complementary enzymes. Together, these two enzymes can function co-operatively to mediate the regeneration of expensive cofactors for improving the product yield of the bioreaction. In addition, the method of synthesizing an immobilized form of the coupled biocatalytic system by encapsulation of whole cells in calcium alginate beads is reported. As an example, we present the improved biosynthesis of L-xylulose from L-arabinitol by coupling E. coli cells expressing the enzymes L-arabinitol dehydrogenase or NADH oxidase. Under optimal conditions and using an initial concentration of 150 mM L-arabinitol, the maximal L-xylulose yield reached 96%, which is higher than those reported in the literature. The immobilized form of the coupled whole-cell biocatalysts demonstrated good operational stability, maintaining 65% of the yield obtained in the first cycle after 7 cycles of successive re-use, while the free cell system almost completely lost the catalytic activity. Therefore, the methods reported here provides two strategies that could help improve the industrial production of L-xylulose, as well as other value-added compounds requiring the use of cofactors in general.

Presented is the protocol for co-immobilizing whole-cell biocatalysts for cofactor regeneration and improved reusability, using the production of L-xylulose as an example. The cofactor regeneration is achieved by coupling two Escherichia coli strains expressing functionally complementary enzymes; the whole-cell biocatalyst immobilization is achieved by cell encapsulation in calcium alginate beads.

藻酸盐珠多生物催化剂辅因子再生和可重用性改进的固定化

We have recently developed a simple, reusable and coupled whole-cell biocatalytic system with the capability of cofactor regeneration and biocatalyst ...

化学

Design and Implementation of an Automated Illuminating, Culturing, and Sampling System for Microbial Optogenetic Applications

Optogenetic systems utilize genetically-encoded proteins that change conformation in response to specific wavelengths of light to alter cellular processes. There is a need for culturing and measuring systems that incorporate programmed illumination and stimulation of optogenetic systems. We present a protocol for building and using a continuous culturing apparatus to illuminate microbial cells with programmed doses of light, and automatically acquire and analyze images of cells in the effluent. The operation of this apparatus as a chemostat allows the growth rate and the cellular environment to be tightly controlled. The effluent of the continuous cell culture is regularly sampled and the cells are imaged by multi-channel microscopy. The culturing, sampling, imaging, and image analysis are fully automated so that dynamic responses in the fluorescence intensity and cellular morphology of cells sampled from the culture effluent are measured over multiple days without user input. We demonstrate the utility of this culturing apparatus by dynamically inducing protein production in a strain of Saccharomyces cerevisiae engineered with an optogenetic system that activates transcription.

We designed a continuous culturing apparatus for use with optogenetic systems to illuminate cultures of microbes and regularly image cells in the effluent with an inverted microscope. The culturing, sampling, imaging, and image analysis are fully automated so that dynamic responses to illumination can be measured over several days.

设计和自动照明，培养和取样系统实现微生物光遗传学的应用

Optogenetic systems utilize genetically-encoded proteins that change conformation in response to specific wavelengths of light to alter cellular ...

生物工程

Use of High-Throughput Automated Microbioreactor System for Production of Model IgG1 in CHO Cells

Automated microscale bioreactors (15 mL) can be a useful tool for cell culture engineers. They facilitate the simultaneous execution of a wide variety of experimental conditions while minimizing potential process variability. Applications of this approach include: clone screening, temperature and pH shifts,&#160;media and supplement optimization. Furthermore, the small reactor volumes are conducive to large Design of Experiments that investigate a wide range of conditions. This allows upstream processes to be significantly optimized before scale-up where experimentation is more limited in scope due to time and economic constraints. Automated microscale bioreactor systems offer various advantages over traditional small scale cell culture units, such as shake flasks or spinner flasks. However, during pilot scale process development&#160;significant care must be taken to ensure that these advantages are realized. When run with care, the system can enable high level automation, can be programmed to run DOE&#39;s with a higher number of variables&#160;and can reduce sampling time when integrated with a nutrient analyzer or cell counter. Integration of the expert-derived heuristics presented here, with current automated microscale bioreactor experiments can minimize common pitfalls that hinder meaningful results. In the extreme, failure to adhere to the principles laid out here can lead to equipment damage that requires expensive repairs. Furthermore, the microbioreactor systems have small culture volumes&#160;making characterization of cell culture conditions difficult. The number and amount of samples taken in-process in batch mode culture is limited as operating volumes cannot fall below 10 mL. This method will discuss the benefits and drawbacks of microscale bioreactor systems.

A detailed protocol for the concurrent operation of 48 parallel cell cultures under varied conditions in a microbioreactor system is presented. Cell culture process, harvest and subsequent antibody titer analysis are described.

高通量自动 Microbioreactor 系统在 CHO 细胞模型 IgG1 生产中的应用

Automated microscale bioreactors (15 mL) can be a useful tool for cell culture engineers. They facilitate the simultaneous execution of a wide variety of ...

Methanol Independent Expression by Pichia Pastoris Employing De-repression Technologies

Methanol is a well-established carbon source and inducer for efficient protein production employing Pichia pastoris (P. pastoris) as a host on micro-, lab and industrial scale. However, due to its toxicity and flammability, there is a desire to avoid methanol while maintaining the high productivity of P. pastoris. Small scale bioreactor cultivations (0.5-5 L working volume) are commonly used to evaluate a strain and its protein production characteristics since microscale cultivation in deep well plates can be hardly controlled or relies on expensive equipment. Furthermore, traditional protocols for the cultivation and induction of P. pastoris were established for constitutive expression or methanol induction and so far, no reliable protocols were described to screen P. pastoris expression strains with derepressible promoters in (controlled and monitored) parallel cultivations. To simplify such initial cultivations to characterize and compare new protein production strains, we established a simple shake flask cultivation system for methanol free expression that simulates bioreactor conditions including a constant slow glycerol feed and online monitoring, thereby coming closer to the real conditions in bioreactors compared to mostly applied small scale batch cultivations. To drive recombinant protein expression in P. pastoris, the carbon source repressed promoters PDC and PDF were applied. Polymer discs with embedded carbon source, releasing a constant amount of glycerol, assured a feed rate delivering the necessary energy for maintaining the promoters active while keeping the biomass generation low.

Methanol Independent Expression by Pichia Pastoris Employing De-repression Technologies

This method for the first time describes reliable experimental procedures for efficient inducible methanol-free recombinant protein production in Pichia pastoris (Komagataella phaffii), employing the carbon source regulated promoters PDCand PDF in small scale experiments while cultivation parameters can be monitored online, and a constant glycerol feed is applied.

多夏巴氏杆菌自主表达采用除抑制技术

Methanol is a well-established carbon source and inducer for efficient protein production employing Pichia pastoris (P. pastoris) as a host on micro-, lab ...

Purification and Analytics of a Monoclonal Antibody from Chinese Hamster Ovary Cells Using an Automated Microbioreactor System

Monoclonal antibodies (mAbs) are one of the most popular and well-characterized biological products manufactured today. Most commonly produced using Chinese hamster ovary (CHO) cells, culture and process conditions must be optimized to maximize antibody titers and achieve target quality profiles. Typically, this optimization uses automated microscale bioreactors (15 mL) to screen multiple process conditions in parallel. Optimization criteria include culture performance and the critical quality attributes (CQAs) of the monoclonal antibody (mAb) product, which may impact its efficacy and safety. Culture performance metrics include cell growth and nutrient consumption, while the CQAs include the mAb's N-glycosylation and aggregation profiles, charge variants, and molecular weight. This detailed protocol describes how to purify and subsequently analyze HCCF samples produced by an automated microbioreactor system to gain valuable performance metrics and outputs. First, an automated protein A fast protein liquid chromatography (FPLC) method is used to purify the mAb from harvested cell culture samples. Once concentrated, the glycan profiles are analyzed by mass spectrometry using a specific platform (refer to the Table of Materials). Antibody molecular weights and aggregation profiles are determined using size exclusion chromatography-multiple angle light scattering (SEC-MALS), while charge variants are analyzed using microchip capillary zone electrophoresis (mCZE). In addition to the culture performance metrics captured during the bioreactor process (i.e., culture viability, cell counts, and common metabolites including glutamine, glucose, lactate, and ammonia), spent media is analyzed to identify limiting nutrients to improve the feeding strategies and overall process design. Therefore, a detailed protocol for the absolute quantification of amino acids by liquid chromatography-mass spectrometry (LC-MS) of spent media is also described. The methods used in this protocol take advantage of high-throughput platforms that are compatible for large numbers of small-volume samples.

A detailed protocol for the purification and subsequent analysis of a monoclonal antibody from harvested cell culture fluid (HCCF) of automated microbioreactors has been described. Use of analytics to determine critical quality attributes (CQAs) and maximizing limited sample volume to extract vital information is also presented.

使用自动微生物反应器系统从中国仓鼠卵巢细胞中纯化和分析单克隆抗体

Monoclonal antibodies (mAbs) are one of the most popular and well-characterized biological products manufactured today. Most commonly produced using ...

Process Optimization using High Throughput Automated Micro-Bioreactors in Chinese Hamster Ovary Cell Cultivation

Optimization of bioprocesses to increase the yield of desired products is of importance in the biopharmaceutical industry. This can be achieved by strain selection and by developing bioprocess parameters. Shake flasks have been used for this purpose. They, however, lack the capability to control the process parameters such as pH and dissolved oxygen (DO). This limitation can be overcome with the help of an automated micro-bioreactor. These bioreactors mimic cultivation at a larger scale. One of the major advantages of this system is the integration of the Design of Experiment (DOE) in the software. This integration enables establishing a design where multiple process parameters can be varied simultaneously. The critical process parameters and optimum bioprocess conditions can be analyzed within the software. The focus of the work presented here is to introduce the user to the steps involved in process design in the software and incorporation of the DOE within the cultivation run.

Here, we present a detailed procedure to run a Design of Experiment in an automated micro-bioreactor followed by cell harvest and protein quantification using a Protein A column.

中国仓鼠卵巢细胞培养中高通量自动化微生物反应器工艺优化

Optimization of bioprocesses to increase the yield of desired products is of importance in the biopharmaceutical industry. This can be achieved by strain ...

High-throughput Purification of Affinity-tagged Recombinant Proteins

X-ray crystallography is the method of choice for obtaining a detailed view of the structure of proteins. Such studies need to be complemented by further biochemical analyses to obtain detailed insights into structure/function relationships. Advances in oligonucleotide- and gene synthesis technology make large-scale mutagenesis strategies increasingly feasible, including the substitution of target residues by all 19 other amino acids. Gain- or loss-of-function phenotypes then allow systematic conclusions to be drawn, such as the contribution of particular residues to catalytic activity, protein stability and/or protein-protein interaction specificity.
In order to attribute the different phenotypes to the nature of the mutation - rather than to fluctuating experimental conditions - it is vital to purify and analyse the proteins in a controlled and reproducible manner. High-throughput strategies and the automation of manual protocols on robotic liquid-handling platforms have created opportunities to perform such complex molecular biological procedures with little human intervention and minimal error rates1-5.
Here, we present a general method for the purification of His-tagged recombinant proteins in a high-throughput manner. In a recent study, we applied this method to a detailed structure-function investigation of TFIIB, a component of the basal transcription machinery. TFIIB is indispensable for promoter-directed transcription in vitro and is essential for the recruitment of RNA polymerase into a preinitiation complex6-8. TFIIB contains a flexible linker domain that penetrates the active site cleft of RNA polymerase9-11. This linker domain confers two biochemically quantifiable activities on TFIIB, namely (i) the stimulation of the catalytic activity during the 'abortive' stage of transcript initiation, and (ii) an additional contribution to the specific recruitment of RNA polymerase into the preinitiation complex4,5,12 . We exploited the high-throughput purification method to generate single, double and triple substitution and deletions mutations within the TFIIB linker and to subsequently analyse them in functional assays for their stimulation effect on the catalytic activity of RNA polymerase4. Altogether, we generated, purified and analysed 381 mutants - a task which would have been time-consuming and laborious to perform manually. We produced and assayed the proteins in multiplicates which allowed us to appreciate any experimental variations and gave us a clear idea of the reproducibility of our results.
This method serves as a generic protocol for the purification of His-tagged proteins and has been successfully used to purify other recombinant proteins. It is currently optimised for the purification of 24 proteins but can be adapted to purify up to 96 proteins.

We describe a method for the affinity-tagged purification of recombinant proteins using liquid-handling robotics. This method is generally applicable to the small-scale purification of soluble His-tagged proteins in a high-throughput format.

高通量的亲和标签的重组蛋白的纯化

X-ray crystallography is the method of choice for obtaining a detailed view of the structure of proteins. Such studies need to be complemented by further ...

生物学

Automated Microbial Cultivation and Adaptive Evolution using Microbial Microdroplet Culture System (MMC)

Conventional microbial cultivation methods usually have cumbersome operations, low throughput, low efficiency, and large consumption of labor and reagents. Moreover, microplate-based high-throughput cultivation methods developed in recent years have poor microbial growth status and experiment parallelization because of their low dissolved oxygen, poor mixture, and severe evaporation and thermal effect. Due to many advantages of micro-droplets, such as small volume, high throughput, and strong controllability, the droplet-based microfluidic technology can overcome these problems, which has been used in many kinds of research of high-throughput microbial cultivation, screening, and evolution. However, most prior studies remain&#160;at the stage of laboratory construction and application. Some key issues, such as high operational requirements, high construction difficulty, and lack of automated integration technology, restrict the wide application of droplet microfluidic technology in microbial research. Here, an automated Microbial Microdroplet Culture system (MMC) was successfully developed based on droplet microfluidic technology, achieving the integration of functions such as inoculation, cultivation, online monitoring, sub-cultivation, sorting, and sampling required by the process of microbial droplet cultivation. In this protocol, wild-type Escherichia coli (E. coli) MG1655 and a methanol-essential E. coli strain (MeSV2.2) were taken as examples to introduce how to use the MMC to conduct automated and relatively high-throughput microbial cultivation and adaptive evolution in detail. This method is easy to operate, consumes less labor and reagents, and has high experimental throughput and good data parallelity, which has great advantages compared with conventional cultivation methods. It provides a low-cost, operation-friendly, and result-reliable experimental platform for scientific researchers to conduct related microbial research.

Automated Microbial Cultivation and Adaptive Evolution using Microbial Microdroplet Culture System MMC

This protocol describes how to use the Microbial Microdroplet Culture system (MMC) to conduct automated microbial cultivation and adaptive evolution. MMC can cultivate and sub-cultivate microorganisms automatically and continuously and monitor online their growth with relatively high throughput and good parallelization, reducing labor and reagent consumption.

使用微生物滴培养系统（MMC）的自动微生物培养和适应性进化

Conventional microbial cultivation methods usually have cumbersome operations, low throughput, low efficiency, and large consumption of labor and ...

Light-Controlled Fermentations for Microbial Chemical and Protein Production

Microbial cell factories offer a sustainable alternative for producing chemicals and recombinant proteins from renewable feedstocks. However, overburdening a microorganism with genetic modifications can reduce host fitness and productivity. This problem can be overcome by using dynamic control: inducible expression of enzymes and pathways, typically using chemical- or nutrient-based additives, to balance cellular growth and production. Optogenetics offers a non-invasive, highly tunable, and reversible method of dynamically regulating gene expression. Here, we describe how to set up light-controlled fermentations of engineered Escherichia coli and Saccharomyces cerevisiae for the production of chemicals or recombinant proteins. We discuss how to apply light at selected times and dosages to decouple microbial growth and production for improved fermentation control and productivity, as well as the key optimization considerations for best results. Additionally, we describe how to implement light controls for lab-scale bioreactor experiments. These protocols facilitate the adoption of optogenetic controls in engineered microorganisms for improved fermentation performance.

Optogenetic control of microbial metabolism offers flexible dynamic control over fermentation processes. The protocol here shows how to set up blue light-regulated fermentations for chemical and protein production at different volumetric scales.