我们感谢 Emma Chory 和 Kevin Esvelt 在硬件和软件设置方面的帮助和建议。Samir Aoudjane、Osaid Ather 和 Erika DeBenedictis 得到了 Steel Perlot 早期调查员补助金的支持。这项工作得到了弗朗西斯·克里克研究所的支持，该研究所的核心资金来自英国癌症研究中心（CC2239），英国医学研究委员会（CC2239）和惠康信托基金会（CC2239）。

1. 硬件设置
注意：有关PRANCE系统的硬件组件的概述，请参阅 图 2，有关物理组装的这些组件的照片，请参见 图3 。
<ol><li>获取PRANCE系统的主要硬件，包括液体处理仪表、读板器和辅助泵。 注：迄今为止，所有PRANCE系统均已在中型到大型液体处理仪器上实施，这些仪器配备了8通道、可单独寻址的移液臂、单活塞96吸头移液臂、用于移动板的机器人夹持器、用于吸头灭菌的集成洗涤站以及能够测量吸光度和发光的集成读板器。</li>
	<li>根据液体处理机器人的型号和功能配置加热策略。使用加热板架或加热器介导的机器人气候控制。</li>
	<li>建立吸头清洗站，以便吸头重复使用。 注意：迄今为止，PRANCE系统一直使用现成的清洗站，尽管原则上，该组件可以很容易地由低成本组件制成。</li>
	<li>通过设置在37°C下运行的实时生物反应器作为化学恒温器/涡轮抑制器，建立维持在对数期的细菌培养物来源。或者，在附近的冰箱中，在4°C下，在37°C的对数相（OD600 在0.25和0.45之间）中预先生长的至少1L体积的对数期细菌培养物。确保培养物，无论是冷藏的还是温热的，都使用摇床板或搅拌板定期搅拌，以防止沉淀。</li>
	<li>配置首选泵，以便机器人与必要的软件和驱动程序集成。实施软件，使泵能够输送 10-100 mL 量级的液体。 注意：请参阅此实施中使用的泵 的材料表 和制造商的网站，了解用于操作这些泵的软件以及如何配置它们的文档。本手稿中所示的PRANCE设置中使用的泵的此类软件在以下GitHub存储库中提供开源，https://github.com/dgretton/std-96-pace PRANCE需要至少一个能够泵送三个独立通道的三泵歧管（将细菌输送到细菌储存器，将漂白剂输送到细菌储存器，并将细菌储存器排入废物），每个泵的速度独立校准和控制。过去，人们使用鱼缸泵和水培泵阵列，尽管原则上可以使用任何蟒蛇控制的蠕动泵。基本功能包括使用机器人夹持器将板移入或移出读板器、启动读板器测量以及访问测量值。</li>
	<li>3D打印PRANCE系统所需的定制甲板组件，至少包括细菌储存器/分配歧管（“华夫饼”），如 补充文件1 （https://drive.google.com/file/d/16ELcvfFPzBzNSto0xUrBe-shi23J9Na7/view?usp=share_link）所示。将这些容器固定在甲板上，并使用标准的液体处理机器人软件校准其位置。将储液罐连接到泵阵列。 注意： 有关如何执行校准的详细信息，请参阅机器人制造商的文档，因为它将依赖于机器人。基于树脂的3D打印机是最合适的; 材料表中给出了所用打印机类型的示例;标准透明树脂与默认打印机设置一起使用。</li>
	<li>为系统配备符合当地生物安全建议的排水管。</li>
	<li>将实验室器皿放在液体处理机器人的甲板上，如 图 4 所示。</li>
	<li>遵循标准安全程序，包括使用标准实验室个人防护设备（即实验室外套、手套和护目镜）。</li>
</ol>2. 软件准备
<ol><li>使用 python11 安装用于控制液体处理机器人的开源软件，该软件可从开源 PyHamilton 存储库获得。https://github.com/dgretton/pyhamilton</li>
	<li>修改和校准液体处理机器人软件的实验室布局文件，以准确反映机器人平台上的实验室器皿位置，如图 4 所示。 注意： 根据提供的文档，此处使用的设置使用液体处理机器人制造商提供的软件。</li>
	<li>在 模拟模式下运行PRANCE机器人方法程序。<ol><li>使用以下命令（在 Windows 操作系统中）打开命令行，如 图 5 所示。 Windows 键 + R 输入：cmd</li>
		<li>将父目录更改为机器人方法程序的目录。输入如下命令，路径正确，如 图 5 所示。 光盘 c：\Robot_methods_directory\PRANCE</li>
		<li>使用 Python 调用带有模拟模式标志的机器人方法程序，如 图 5 所示。 py robot_method.py --模拟</li>
		<li>选择 Robot Run Control 窗口左上角的 PLAY 按钮，该按钮将在程序执行时打开（图 5）。 注意：在继续之前，请确保 PRANCE 方法可以在模拟中无错误地运行。很明显，脚本是否能够在模拟模式下运行而不会出错，因为它将在不调用系统错误处理的情况下完成主程序的多个循环，从而终止主程序循环。</li>
	</ol></li>
	<li>在禁用模拟模式的情况下运行PRANCE机器人方法程序。<ol><li>在相应的目录中打开命令行（图 5）。 Windows 键 + R 输入：cmd 光盘 c：\Robot_methods_directory\PRANCE</li>
		<li>使用 Python 调用机器人方法程序，不带标志： py robot_method.py</li>
		<li>选择机器人运行控制窗口左上角的“播放”按钮，该按钮将在执行程序时打开。</li>
		<li>确认 PyHamilton 可以控制仪器并使其初始化。</li>
	</ol></li>
	<li>建立实时数据同步。 注意：迄今为止，PRANCE系统已使用联网计算机，允许用户通过远程文件共享软件或远程桌面监控日志文件和实时板读取器测量图。</li>
	<li>关闭自动更新。</li>
</ol>3. 运行前准备
<ol><li>确保对数期细菌培养源可用于计划运行所需的所有培养物，并且正在积极搅拌以防止沉淀。使用活性化学恒温器/浊度恒温器或生长停滞的冷藏预生长培养物。</li>
	<li>更新控制器清单文件，详细说明每个程序周期将哪种细菌培养物泵入 96 孔泻湖的每个孔中。这样可以精确控制有效的泻湖稀释率。如 图 6 所示。<ol><li>使用DilutionCalculator.xlsx电子表格（作为 补充文件 2 提供）计算泻湖的稀释率，如 图 7 所示。</li>
	</ol></li>
	<li>将robot_method.py文件更新为预期的泻湖高度。要遵循此协议，请使用 14（以毫米为单位）作为程序中变量fixed_lagoon_height的默认值。这相当于系统上 550 μL 的泻湖体积，但可能因所使用的特定 96 深孔板而异。</li>
	<li>将干净过滤的移液器吸头放在机器人甲板上的指定位置，并将吸头架粘在吸头支架上，以确保运行过程中的稳定性。</li>
	<li>将干净的 96 深孔板放在机器人甲板上的指定位置。</li>
	<li>将干净的 96 孔读板放在机器人甲板上的指定位置。</li>
	<li>确保读板器托盘未被预先存在的板占用。</li>
	<li>确保泵已连接到计算机并分配到正确的地址。</li>
	<li>通过激活泵来清洁泵管路，然后泵送漂白剂，然后泵送水。</li>
	<li>将泵管路连接到适当的源和输出，密切注意确保正确的管路连接到相关的细菌培养物。</li>
	<li>装有漂白剂/水的罐/桶，用于细菌储液罐和移液器吸头清洗。</li>
	<li>确保甲板上的所有部件，尤其是移动元件，都稳定在指定位置。</li>
	<li>根据当地实施激活加热器以达到目标温度（即 37 °C; 图8）。</li>
	<li>运行紫外线杀菌协议文件 10 分钟，以操作制造商提供的液体处理机器人中的内置紫外线杀菌灯（图 9）。<ol><li>选择机器人运行控制窗口左上角的“播放”按钮，该按钮将在执行程序时打开。</li>
		<li>使用参数化选项运行文件 600 秒。</li>
	</ol></li>
	<li>确保机器人运行控制软件已关闭。 注意：如果运行控制软件的任何现有实例正在运行，机器人方法程序将崩溃。</li>
</ol>4、软硬件集成
<ol><li>进行“水运行”，其中PRANCE机器人方法程序在一夜之间运行，用水代替所有培养物和湿试剂。 注意： 此测试可以在室温下运行。<ol><li>使用controller_manifest完成如上所述的运行前准备工作，并robot_method设置为1体积/小时的有效泻湖稀释率，如图5和图6所示。</li>
		<li>将“细菌进入”管线连接到装水容器，以替换对数相细菌进行水流。 注意：可以将食用色素添加到水源中，以跟踪液体在实验过程中的运动。</li>
		<li>在相应的目录中打开命令行。</li>
		<li>使用 Python 调用机器人方法程序，并使用新的运行标志 （py robot_method.py --new） 并输入请求的参数，包括 日志文件名 （TestRun）、泻湖孔数 （16）、 循环持续时间 （30）、 每个阅读器板测量的循环数 （4） 和 诱导器体积 （诱导器体积为 0 μL 对于该测试运行，在用阿拉伯糖诱导诱变的进化过程中，该值可能为 10 μL），如 图 5 所示。</li>
		<li>选择“机器人运行控制”窗口左上角的“播放”按钮，该按钮将在提供参数后执行程序时打开。 注意：PRANCE方法可以使用空泻湖板启动，泻湖的液体体积将在前六个循环中平衡到最终体积。</li>
	</ol></li>
	<li>进行“仅细菌运行”，其中PRANCE方案仅在目标温度下进行细菌培养过夜，但不使用噬菌体。<ol><li>使用controller_manifest完成如上所述的运行前准备工作，并robot_method设置为1体积/小时的有效泻湖稀释率，如图5和图6所示。确保加热器在目标温度为 37 °C 时打开。</li>
		<li>将“细菌”线连接到所选的对数相细菌源。</li>
		<li>在相应的目录中打开命令行。</li>
		<li>使用 Python 调用带有新运行标志 （py robot_method.py --new） 的机器人方法程序并输入请求的参数，如前面的第 4.1.4 节所述。</li>
		<li>选择“机器人运行控制”窗口左上角的“播放”按钮，一旦提供了参数，该窗口将在程序执行时打开。</li>
	</ol></li>
	<li>进行“感染测试”，其中携带进化蛋白质的噬菌体受到挑战，以在需要该蛋白质的细菌上繁殖。 注意：提前决定哪些泻湖将接种噬菌体，哪些泻湖将不接种，从而作为无噬菌体控制泻湖以检测交叉污染。<ol><li>如图5和图6所示，使用controller_manifest完成如上所述的运行前准备工作，并robot_method设置为1体积/小时的有效稀释率。确保加热器在目标温度为 37 °C 时打开。</li>
		<li>将“细菌”线连接到所选的对数相细菌源。</li>
		<li>在相应的目录中打开命令行。</li>
		<li>使用 Python 调用带有新运行标志 （py robot_method.py --new） 的机器人方法程序，并输入请求的参数，如前面第 4.1.4 节中所述。</li>
		<li>选择“机器人运行控制”窗口左上角的“播放”按钮，该按钮将在提供参数后执行程序时打开。</li>
		<li>在添加噬菌体之前，运行该方法2-3小时以平衡泻湖板中的体积和细菌OD。</li>
		<li>当程序处于睡眠状态时，在运行周期结束时用 106 pfu/mL 噬菌体接种噬菌体泻湖（例如，通过斑块测定或 qPCR 测定的 108 pfu/mL 的 5.5 μL噬菌体等分试样）接种到 550 μL 泻湖中。</li>
		<li>运行程序过夜，然后通过斑块测定或qPCR检查泻湖孔中的噬菌体滴度。</li>
	</ol></li>
</ol>

设置 PRANCE：机器人加速进化的综合指南

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作者没有要披露的冲突。

尽管努力实现设备标准化，但实际上，由于设备供应、硬件和软件版本控制的变化，每个 PRANCE 设置都会有所不同。因此，每个PRANCE设置都表现出独特的设置挑战，需要全面了解每个组件的用途，以便进行有效的模块化故障排除。
该方法描述了用于设置和测试已建立的PRANCE系统的分步协议。我们首先关注硬件和软件的关键要素，然后详细说明准备和执行一系列测试运行的基本步骤，这些步骤确定系统已准备好进行 PRANCE。
硬件的一个基本特征是优化，以降低使用噬菌体的多重实验期间样品交叉污染的风险。建议使用具有机器人吸头技术的专用过滤吸头，该技术与吸头重复使用兼容，并且被认为通过避免强制配合吸头来最大限度地减少吸头弹出过程中产生的气溶胶。根据该协议，可靠的吸头清洗允许吸头重复使用，但必须将其充分性作为每个系统感染测试的一部分进行验证。自我灭菌还取决于系统持续供应水和漂白剂。这些储存在水箱/桶中，如果耗尽将导致自我消毒受损和快速交叉污染。可以在程序运行之前和之后拍摄水箱/水桶的照片，以基准测试洗涤设备在特定泵设置下消耗水和漂白剂的速度。
该系统的另一个关键要素是维持细菌生长阶段和温度。使用 S2060 大肠杆菌 菌株 （Addgene： #105064） 进行 PRANCE 实验。这是一种 K12 衍生的含 F 质粒的菌株，经过优化可减少生物膜7。此外，该菌株中的 F 质粒已通过添加用于质粒维持的四环素耐药盒、 luxCDE 和 luxR 进行编辑以补充 luxAB 介导的发光监测，以及噬菌体休克启动子下的 lacZ 以允许斑块的比色可视化。F-质粒编码的F-菌毛是M13噬菌体感染所必需的。因此，PACE中使用的细菌必须在37°C和中期对数期培养，此时F-pilus12 表达并且M13噬菌体感染，繁殖和进化是可能的。对于静态温度调节，可以使用现成的加热板架。另一种方法是简单地使用廉价的加热器加热进入HEPA过滤器的空气，但不建议这样做，因为它可能会导致硬件加速磨损。此外，使用时，这会加速甲板上辅助流体的蒸发，例如漂白剂/水桶和诱导剂。
软件包的校准对于正常的系统功能也是必不可少的。软件甲板布局与实际机器人甲板之间的差异是运行过程中系统故障的最常见原因。定期校准供应细菌培养、漂白和排水系统的辅助泵至关重要，因为蠕动泵的使用会导致管道磨损和流体体积变化。
水运行测试将快速揭示许多常见的设置问题，包括不正确的液体处理设置、流体泄漏/连接错误以及软件不稳定。成功的水运行不会出现意外的液体泄漏，并在一夜之间稳定运行而不会出现错误。在水运行过程中可能会出现许多常见问题，例如无法执行某些液体处理步骤、移液器滴落以及方案在运行过程中停止。如果无法执行某些液体处理步骤，请确认已安装所有液体类别。这些列出了适当的粘度和移液速度，并在制造商提供的机器人控制软件中进行了调整。如果移液器滴落，机器人移液臂设置正确，以实现清洁移液并消除噬菌体交叉污染，这一点很重要。成功的自动移液除了需要正确的液体类别外，还需要所有实验室器皿的正确台面布局高度，以及PRANCE机器人方法程序中指定的适当移液高度偏移。这些高度偏移可能需要直接调整。如果协议在运行过程中停止，这通常是由一系列错误生成的，这些错误表明卡组布局文件可能与实际的卡组配置不匹配。
仅细菌运行测试将揭示酶标仪设置和实时数据可视化的问题、漂白剂浓度过高或冲洗不足的问题以及温度稳定性。成功的纯细菌运行将在前三个周期中表现出泻湖吸光度的平衡，然后在运行期间表现出稳定的吸光度。此外，它还可能揭示几个常见问题。这是绘制读板仪生成的数据的第一步。酶标仪数据库中的数据可能无法正确保存或绘制。如果细菌的吸光度无法平衡，这可能表明漂白剂浓度过高。过量的漂白剂或洗涤不足会对整个实验进行消毒，而不仅仅是对实验室器皿进行消毒。如果怀疑有这种情况，可以使用漂白剂检测条来测试泻湖。可以用温度计枪检查培养物温度的稳定性。
成功的感染测试表明系统已准备好运行 PRANCE。可以通过接种含有细菌培养物的泻湖子集来进行感染测试。当这些细菌被缺乏pIII（ΔgIII）基因的适当噬菌体感染时，这些细菌将表达pIII，从而允许噬菌体繁殖。一种可能的测试组合是将 S2060 细菌与任何 ΔgIII 噬菌体一起使用在噬菌体休克启动子下用表达 pIII 的质粒转化。我们建议使用携带野生型 T7 RNA 聚合酶的 ΔgIII 噬菌体，其中 S2060 细菌用辅助质粒转化，其中 pIII 和 luxAB 由 T7 启动子（质粒 pJC173b13）驱动，如 图 1 所示。这也允许在测试运行期间由酶标仪介导的感染监测。感染测试成功和缺乏交叉污染的明确证据将来自测试和对照泻湖的噬菌体滴度。在使用荧光素酶报告基因的情况下，仅在测试孔中发光的增加（ 如图3所示）也是噬菌体感染和繁殖成功的指标。噬菌体滴度定量的金标准是噬菌斑测定7。还有一种通过qPCR7 定量M13的方案可能更快，尽管这不能区分感染性和非感染性噬菌体颗粒，因此可能会高估滴度。
主程序引用一个清单文件，这是一个纯文本数据库文件，它规定了每个繁殖培养物的每个循环的稀释体积以及任意数量的潜在细菌培养原料的选择，这些原料的选择严格性可能不同。以这种方式，清单文件定义了 PRANCE 运行的许多参数。需要注意的是，操作员或系统可以在运行过程中编辑此文件，这意味着可以进行手动或自动反馈控制。
功能齐全的PRANCE装置的效用在于它能够在仔细监测和控制的环境中快速进化大量种群。基于板的形式将PRANCE与其他技术区分开来，例如使用较小的现成的基于涡轮涛力的系统14,15。基于板的设置不仅有助于与其他机器人处理步骤轻松集成，而且还与其他实验室仪器（如离心机）兼容。此外，跨多个实例同时进行加速进化的能力为实验引入了额外的维度，增强了实现多样化和稳健结果的前景。PRANCE中集成的精细控制和反馈系统进一步增强了实验的可预测性和可靠性，标志着定向进化技术领域的重大进步。然而，这种技术在它可以进行的平行实验数量上是有限的。根据配置的不同，PRANCE设置通常受到机器人移液速度或可用甲板空间的限制。
用于PRANCE的相同硬件和软件也可以应用于不涉及噬菌体的进化方法。正如多涡轮机方法11所证明的那样，该仪器可以专门用于细菌，从而实现全基因组适应性进化实验。这种适应性拓宽了该仪器的范围，为机器人加速进化的新形式铺平了道路。

PRANCE是两种强大的定向进化技术的结合。首先是 PACE1，这是一种分子技术，可将多轮基因多样化和选择与 M13 噬菌体的快速生命周期相结合，从而在液体噬菌体培养物中连续发生快速进化轮次。这种选择是由使用质粒编码的基因回路驱动的，该回路将进化蛋白的功能与噬菌体繁殖所需的 M13 尾壳蛋白 pIII 的表达偶联，如图 1 所示。在实验水平上，液体噬菌体培养物的连续稀释允许连续选择。因此，通过控制噬菌体培养稀释率，可以在基因回路水平和实验水平上调节选择严格性。因此，PACE可以应用于任何生物分子工程挑战，其中有一种分子传感器可以检测大肠杆菌中诱导pIII表达的所需活性。应用包括蛋白质-蛋白质结合 2,3,4、蛋白质-DNA 结合 5、蛋白质溶解度6 和许多特定酶功能的进化 7。第二个是机器人加速进化8,9，它使用反馈控制器来消除定向进化的两种常见故障模式：灭绝，当环境过于严格时发生，以及缺乏进化，当环境过于宽松时发生。与PANT（噬菌体辅助非连续进化）7,10中完成的噬菌体连续传代不同，机器人加速的“近连续”进化涉及快速移液，将培养物维持在对数中期，使种群能够经历连续的感染和繁殖周期。当这两种技术一起使用时，它们被称为 PRANCE，即噬菌体和机器人辅助的近连续进化8，它能够实现稳健、多路复用和快速的持续进化。PRANCE 已被用于进化聚合酶、tRNA 和氨酰基 tRNA 合成酶，并在这些进化过程中进行反馈控制，以提高其速度和可靠性8。
PRANCE的硬件和软件设置有几个细节，可以在液体处理机器人上使用噬菌体。我们没有使用机器人制造商提供的默认软件，而是使用基于 python 的开源软件包11，它能够实现快速、并发的执行，从而能够将半连续生物反应器保持在中对数阶段。通过定期对甲板上的几个组件进行自我消毒，研究人员的不干涉时间可以延长到几天，这是通过自动控制可以漂白和冲洗这些组件的泵来实现的。噬菌体交叉污染可以通过使用不使用强制配合尖端的液体处理机器人和仔细调整液体处理设置来消除。

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>3D printed bacterial reservoir &#34;waffle&#34;</td>
			<td>-</td>
			<td>-</td>
			<td>https://drive.google.com/file/d/16ELcvfFPzBzNSto0xUrBe-shi23J9Na7/view; For Robot deck</td>
		</tr>
		<tr>
			<td>3D printer</td>
			<td>FormLabs</td>
			<td>Form 3B+</td>
			<td>3D printer components</td>
		</tr>
		<tr>
			<td>3D printer resin (clear)</td>
			<td>FormLabs</td>
			<td>RS-F2-GPCL-04</td>
			<td>consumable for 3D printer</td>
		</tr>
		<tr>
			<td>8-1,000 &#181;L head</td>
			<td>Hamilton</td>
			<td>10140943</td>
			<td>For Liquid handling robot</td>
		</tr>
		<tr>
			<td>96-1,000 &#181;L pipetting head</td>
			<td>Hamilton</td>
			<td>10120001</td>
			<td>For Liquid handling robot</td>
		</tr>
		<tr>
			<td>Black polystyrene plate reader microplates</td>
			<td>Millipore Sigma</td>
			<td>CLS3603</td>
			<td>For Robot deck</td>
		</tr>
		<tr>
			<td>BMG Labtech Spectrostar FLuorstar Omega</td>
			<td>BMG Labtech</td>
			<td>10086700</td>
			<td>For Liquid handling robot</td>
		</tr>
		<tr>
			<td>Cleaning solution</td>
			<td>Fluorochem Limited</td>
			<td>F545154-1L</td>
			<td>used to clean the liquid handling parts of the robot</td>
		</tr>
		<tr>
			<td>Deep Well plates</td>
			<td>Appleton Woods</td>
			<td>ACP006</td>
			<td>these are used to contain evolving bacteria on the deck of the robot</td>
		</tr>
		<tr>
			<td>encolsure heater</td>
			<td>Stego</td>
			<td>13060.0-01</td>
			<td>heats inside robot enclosure</td>
		</tr>
		<tr>
			<td>Hamilton STAR</td>
			<td>Hamilton</td>
			<td>870101</td>
			<td>For Liquid handling robot</td>
		</tr>
		<tr>
			<td>Heater</td>
			<td>Erbauer</td>
			<td>BGP2108-25</td>
			<td>For Liquid handling robot</td>
		</tr>
		<tr>
			<td>HIG Bionex centrifuge</td>
			<td>Hamilton</td>
			<td>10086700</td>
			<td>For Liquid handling robot</td>
		</tr>
		<tr>
			<td>iSWAP plate gripper</td>
			<td>Hamilton</td>
			<td>190220</td>
			<td>For Liquid handling robot</td>
		</tr>
		<tr>
			<td>laboratory tubing</td>
			<td>Merck</td>
			<td>Z280356</td>
			<td>to construct liquid handling manifold</td>
		</tr>
		<tr>
			<td>luer to barb connector</td>
			<td>AIEX</td>
			<td>B13193/B13246</td>
			<td>for connectorizing tubing</td>
		</tr>
		<tr>
			<td>Magnetic stir plate</td>
			<td>Camlab</td>
			<td>SKU - 1189930</td>
			<td>For Auxiliary Fridge</td>
		</tr>
		<tr>
			<td>Molcular pipetting arm</td>
			<td>Hamilton</td>
			<td>173051</td>
			<td>For Liquid handling robot</td>
		</tr>
		<tr>
			<td>Omega</td>
			<td>BMG labtech</td>
			<td>5.7</td>
			<td>plate reader control software</td>
		</tr>
		<tr>
			<td>One way Check Valves</td>
			<td>Masterflex</td>
			<td>MFLX30505-91</td>
			<td>to one way sections of liquid handling manifold</td>
		</tr>
		<tr>
			<td>pyhamilton</td>
			<td>MIT/Open source</td>
			<td>https://github.com/dgretton/std-96-pace%20PRANCE</td>
			<td>open source python robot control software</td>
		</tr>
		<tr>
			<td>pymodbus</td>
			<td>opensource</td>
			<td>3.5.2</td>
			<td>python pump software interface</td>
		</tr>
		<tr>
			<td>Refrigetator</td>
			<td>Tefcold</td>
			<td>FSC175H</td>
			<td>allows cooled bacteria to be used instead of turbidostat</td>
		</tr>
		<tr>
			<td>S2060 Bacterial strain</td>
			<td>Addgene</td>
			<td>Addgene: #105064</td>
			<td>E. coli</td>
		</tr>
		<tr>
			<td>temperature controller</td>
			<td>Digiten</td>
			<td>DTC102UK</td>
			<td>Used to control heaters thermostatically</td>
		</tr>
		<tr>
			<td>Thermostat switch controller</td>
			<td>WILLHI</td>
			<td>WH1436A</td>
			<td>WILLHI WH1436A 10 A Temperature Controller 110 V Digital Thermostat Switch Sous Vide Controller NTC 10K Sensor Improved Version; for Liquid handling robot</td>
		</tr>
		<tr>
			<td>Venus</td>
			<td>Hamilton</td>
			<td>4.6</td>
			<td>proprietary robot control software</td>
		</tr>
		<tr>
			<td>Wash Station for MPH 96/384</td>
			<td>Hamilton</td>
			<td>190248</td>
			<td>For Liquid handling robot</td>
		</tr>
		<tr>
			<td>Suggested pump manufacturers</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Company</td>
			<td>Catalog number</td>
			<td>Notes</td>
			<td>Documentation</td>
		</tr>
		<tr>
			<td>Agrowtek</td>
			<td>AD6i Hexa Pump</td>
			<td></td>
			<td>https://www.agrowtek.com/doc/im/IM_ADi.pdf</td>
		</tr>
		<tr>
			<td>Amazon</td>
			<td>INTLLAB 12V DC</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Cole-Parmer</td>
			<td>EW-07522-3</td>
			<td>Masterflex L/S Digital Drive, 100 RPM, 115/230 VAC</td>
			<td>https://pim-resources.coleparmer.com/instruction-manual/a-1299-1127b-en.pdf</td>
		</tr>
		<tr>
			<td>Cole-Parmer</td>
			<td>EW-07554-80</td>
			<td>Masterflex L/S Economy variable-speed drive, 7 to 200 rpm, 115 VAC</td>
			<td>https://pim-resources.coleparmer.com/instruction-manual/a-1299-1127b-en.pdf</td>
		</tr>
	</tbody>
</table>

a practical guide to phage- and robotics-assisted near-continuous evolution

机器人加速进化技术使用反馈控制提高进化的可靠性和速度，改善蛋白质和生物体进化实验的结果。在本文中，我们介绍了设置实现噬菌体和机器人辅助近连续进化 （PRANCE） 所需的硬件和软件的指南。PRANCE将基于噬菌体的快速分子进化与同时运行数百个独立的、反馈控制的进化实验的能力相结合。本文将介绍PRANCE的硬件要求和设置，包括液体处理仪器、酶标仪、辅助泵、加热器和3D打印容器。我们描述了如何配置液体处理机器人以与基于 Python 的开源软件兼容。最后，我们为前两个实验提供了建议，这些实验可以使用新构建的PRANCE系统进行，该系统可以锻炼其功能并验证系统是否准备好进行多路复用演化。本指南旨在作为一本手册，用于导航与进行机器人加速进化相关的大量设备设置。

感染检测结果 该测试将揭示细菌培养、噬菌体克隆和滴度、设备温度稳定性、液体处理设置和酶标仪集成方面的问题。成功的噬菌体感染测试将揭示接种噬菌体的泻湖中清晰而快速的噬菌体感染，而在无噬菌体泻湖中没有信号。 图10 显示了噬菌体感染试验的一些代表性结果。实验结果也可以与PRANCE论文8的图1d和图1c进行比较，这取决于是否实施了“热PRANCE”（由活细菌涡旋器喂养）或“冷PRANCE”（由冷却的中对数阶段培养物喂养）配置。此测试可能会揭示几个常见问题。细菌培养制备问题通常会导致感染较弱或不存在感染。只有当细菌处于对数期中期和37°C时，它们才能被M13噬菌体最佳感染。 在其他温度和生长阶段，它们表现出较弱的菌毛表达，因此不太容易受到噬菌体感染12。接种低滴度噬菌体或具有骨架突变的噬菌体可导致信号延迟或缺失。该测试将揭示荧光或发光的酶标仪增益设置问题。
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/65974/65974fig01v4.jpg"> 图1：PRANCE设备感染测试运行期间运行的遗传回路示意图。 当编码在噬菌体基因组上的 T7 RNA 聚合酶感染 大肠杆菌 宿主时，它被转录并在 T7 启动子的 AP 上结合，这导致 pIII 噬菌体蛋白和 luxAB 蛋白的转录，这反过来又促进噬菌体繁殖和发光的产生。缩写：PRANCE = 噬菌体和机器人辅助的近连续进化;AP = 辅助质粒。 <a href="https://www.jove.com/files/ftp_upload/65974/65974fig01large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/65974/65974fig02.jpg"> 图2：PRANCE系统的物理组件示意图。 冰箱储存搅拌培养物，然后通过一系列泵将其移动到机器人甲板上，进入细菌储存库“华夫饼”。液体处理机器人用于使用移液头将细菌培养物从“华夫饼”移动到保温孔以预热至孵育温度，然后移动到主要孵育发生的泻湖。保温井和泻湖都是标准的 2 mL 深孔板。机器人将样品放入一次性读板中，然后将其移动到读板器进行测量。缩写：PRANCE = 噬菌体和机器人辅助的近连续进化。 <a href="https://www.jove.com/files/ftp_upload/65974/65974fig02large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/65974/65974fig03.jpg"> 图3：PRANCE机器人设备。 （A） PRANCE设置。（一）HEPA过滤器和外部加热器。（二）培养冰箱。（三）主机器人外壳。 （四） 读板仪。 （五） 水泵和储罐。（B） 机器人外壳。 （六） 主培养泵。 （七） 水、废水、漂白剂罐。 （八） 清洗泵。（C） 机器人外壳。（IX） 机器人移液臂和夹持器。（X） 移液器吸头。（XI） 3D打印组件，允许将培养物分发到机器人上（“华夫饼”）。（XII） 在读板器中取样的印版。（XIII） 用于清洗吸头的水桶。（XIV） “泻湖”：进行进化培养的养殖容器。缩写：PRANCE = 噬菌体和机器人辅助的近连续进化;HEPA = 高效微粒空气。 <a href="https://www.jove.com/files/ftp_upload/65974/65974fig03large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/65974/65974fig04.jpg"> 图 4：甲板布局。 （A） 机器人控制软件中甲板布局的 3D 表示。（B） 甲板组件的照片。 <a href="https://www.jove.com/files/ftp_upload/65974/65974fig04large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/65974/65974fig05.jpg"> 图 5：带有示例参数（上图）和运行控制软件（下图）的命令行屏幕截图。 播放按钮位于左上角，可以用鼠标单击或用触摸屏启动，具体取决于本地实现。 <a href="https://www.jove.com/files/ftp_upload/65974/65974fig05large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/65974/65974fig06.jpg"> 图 6：为测试运行配置的控制器清单文件。 含有培养物 #0 的泻湖将位于 96 深孔板的第 1 列和第 3 列中。其余列将为空。96 深孔板的 A、B、D 和 E 行在右列标记为噬菌体感染 （1），其他行 （0） 是无噬菌体对照。控制器清单的这个实例将导致程序在每个循环中用 210 μL 培养物稀释泻湖。 <a href="https://www.jove.com/files/ftp_upload/65974/65974fig06large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/65974/65974fig07.jpg"> 图 7：使用 DilutionCalculator 电子表格计算有效泻湖稀释率。请参阅 DilutionCalculator 电子表格的补充文件 2。如图所示，每 30 分钟循环用 210 μL 新鲜培养物稀释 550 μL 泻湖，每四个循环采集 150 μL 样品用于读板测量，对应于 1.0 泻湖体积/h 的有效稀释率（每 1 小时后，一小时开始时将保留 50% 的原始泻湖液体） <a href="https://www.jove.com/files/ftp_upload/65974/65974fig07large.jpg" target="_blank">请点击这里查看此内容的较大版本数字。</a>
<img alt="Figure 8" class="xfigimg" src="/files/ftp_upload/65974/65974fig08.jpg"> 图 8：机器人加热器系统。 加热器通过插入电源来激活，如红色圆圈所示。 <a href="https://www.jove.com/files/ftp_upload/65974/65974fig08large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
<img alt="Figure 9" class="xfigimg" src="/files/ftp_upload/65974/65974fig09.jpg"> 图 9：紫外线去污协议的设置。 <a href="https://www.jove.com/files/ftp_upload/65974/65974fig09large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
<img alt="Figure 10" class="xfigimg" src="/files/ftp_upload/65974/65974fig10.jpg"> 图10：在PRANCE系统上运行的感染测试的测量值。 在运行过程中取样并测量发光度和吸光度。对于每个泻湖，发光测量值除以相应的吸光度测量值，并绘制为时间的函数。被噬菌体感染的泻湖被涂成绿色，而未感染的对照泻湖被涂成黑色。缩写：PRANCE = 噬菌体和机器人辅助的近连续进化。 <a href="https://www.jove.com/files/ftp_upload/65974/65974fig10large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
补充文件1：用于3D打印PRANCE系统所需的定制甲板组件的STL文件，至少包括细菌储存器/分配歧管（“华夫饼”）。<a href="https://www.jove.com/files/ftp_upload/65974/waffle_mini%20(1).zip" target="_blank">请点击此处下载此文件。</a>
补充文件 2：稀释计算器电子表格。<a href="https://www.jove.com/files/ftp_upload/65974/65974_SI%20DilutionCalculator.zip" target="_blank">请点击此处下载此文件。</a>

Watch this Scientific Journal Video about Author Spotlight: Advancing Protein Engineering â€“ Harnessing Evolution Through PRANCE and Lab Automation at JoVE.com

作者聚焦：推进蛋白质工程 – 通过 PRANCE 和实验室自动化驾驭进化

噬菌体和机器人辅助近连续进化 （PRANCE） 是一种快速、稳健的蛋白质进化技术。机器人技术允许实验的并行化、实时监控和反馈控制。

噬菌体和机器人辅助的近乎连续进化的实用指南

Robotics-accelerated Evolution techniques improve the reliability and speed of evolution using feedback control, improving the outcomes of protein and ...

我们正试图使神秘的进化过程具有足够的可预测性，可以用于工程。PRANCE使我们能够通过并行化将演化带入实验室时间尺度，以更好地理解它。实验室自动化正在将更通用的软件工程（包括人工智能）的概念引入到控制代码的开发中。人们还将机械臂和多向输送系统集成到液体处理平台中。总体而言，自动化包括更先进的仪器和工作流程。反馈控制通过防止常见的故障模式（如灭绝）来提高持续进化的成功率。这在分子具有不同起始活性的多重进化过程中至关重要，动态进化的严格性对于所需的结果至关重要。新的科学问题包括探索不同条件如何影响进化，以及研究对噬菌体繁殖和进化电路效率的影响。通过这些改进的蛋白质工程工具，我们希望设计出更复杂的蛋白质，这些蛋白质对其环境敏感且功能动态。

a-practical-guide-to-phage-robotics-assisted-near-continuous

Research

JoVE Journal

Bioengineering

A Practical Guide to Phage- and Robotics-Assisted Near-Continuous Evolution

1.3K 次观看.  The Francis Crick Institute. 我们正试图使神秘的进化过程具有足够的可预测性，可以用于工程。PRANCE使我们能够通过并行化将演化带入实验室时间尺度，以更好地理解它。实验室自动化正在将更通用的软件工程（包括人工智能）的概念引入到控制代码的开发中。人们还将机械臂和多向输送系统集成到液体处理平台中。总体而言，自动化包括更先进的仪器和工作流程。反馈控制通过防止常见的故障?...

视频: 作者聚焦：推进蛋白质工程 – 通过 PRANCE 和实验室自动化驾驭进化

Design of a Cyclic Pressure Bioreactor for the Ex Vivo Study of Aortic Heart Valves

The aortic valve, located between the left ventricle and the aorta, allows for unidirectional blood flow, preventing backflow into the ventricle. Aortic valve leaflets are composed of interstitial cells suspended within an extracellular matrix (ECM) and are lined with an endothelial cell monolayer. The valve withstands a harsh, dynamic environment and is constantly exposed to shear, flexion, tension, and compression. Research has shown calcific lesions in diseased valves occur in areas of high mechanical stress as a result of endothelial disruption or interstitial matrix damage1-3. Hence, it is not surprising that epidemiological studies have shown high blood pressure to be a leading risk factor in the onset of aortic valve disease4. 
The only treatment option currently available for valve disease is surgical replacement of the diseased valve with a bioprosthetic or mechanical valve5. Improved understanding of valve biology in response to physical stresses would help elucidate the mechanisms of valve pathogenesis. In turn, this could help in the development of non-invasive therapies such as pharmaceutical intervention or prevention. Several bioreactors have been previously developed to study the mechanobiology of native or engineered heart valves6-9. Pulsatile bioreactors have also been developed to study a range of tissues including cartilage10, bone11 and bladder12. The aim of this work was to develop a cyclic pressure system that could be used to elucidate the biological response of aortic valve leaflets to increased pressure loads. 
The system consisted of an acrylic chamber in which to place samples and produce cyclic pressure, viton diaphragm solenoid valves to control the timing of the pressure cycle, and a computer to control electrical devices. The pressure was monitored using a pressure transducer, and the signal was conditioned using a load cell conditioner. A LabVIEW program regulated the pressure using an analog device to pump compressed air into the system at the appropriate rate. The system mimicked the dynamic transvalvular pressure levels associated with the aortic valve; a saw tooth wave produced a gradual increase in pressure, typical of the transvalvular pressure gradient that is present across the valve during diastole, followed by a sharp pressure drop depicting valve opening in systole. The LabVIEW program allowed users to control the magnitude and frequency of cyclic pressure. The system was able to subject tissue samples to physiological and pathological pressure conditions. This device can be used to increase our understanding of how heart valves respond to changes in the local mechanical environment.

Design of a Cyclic Pressure Bioreactor for the Ex Vivo Study of Aortic Heart Valves

A cyclic pressure bioreactor capable of subjecting heart valve tissue to physiological and pathological pressure conditions has been designed. A LabVIEW program allows users to control pressure magnitude, amplitude and frequency. This device can be used to study the mechanobiology of heart valve tissue or isolated cells.

循环压力为生物反应器的设计体外主动脉心脏瓣膜的研究

The aortic valve, located between the left ventricle and the aorta, allows for unidirectional blood flow, preventing backflow into the ventricle. Aortic ...

科研

生物工程

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Modern 3D electron microscopy approaches have recently allowed unprecedented insight into the 3D ultrastructural organization of cells and tissues, enabling the visualization of large macromolecular machines, such as adhesion complexes, as well as higher-order structures, such as the cytoskeleton and cellular organelles in their respective cell and tissue context. Given the inherent complexity of cellular volumes, it is essential to first extract the features of interest in order to allow visualization, quantification, and therefore comprehension of their 3D organization. Each data set is defined by distinct characteristics, e.g., signal-to-noise ratio, crispness (sharpness) of the data, heterogeneity of its features, crowdedness of features, presence or absence of characteristic shapes that allow for easy identification, and the percentage of the entire volume that a specific region of interest occupies. All these characteristics need to be considered when deciding on which approach to take for segmentation.
The six different 3D ultrastructural data sets presented were obtained by three different imaging approaches: resin embedded stained electron tomography, focused ion beam- and serial block face- scanning electron microscopy (FIB-SEM, SBF-SEM) of mildly stained and heavily stained samples, respectively. For these data sets, four different segmentation approaches have been applied: (1) fully manual model building followed solely by visualization of the model, (2) manual tracing segmentation of the data followed by surface rendering, (3) semi-automated approaches followed by surface rendering, or (4) automated custom-designed segmentation algorithms followed by surface rendering and quantitative analysis. Depending on the combination of data set characteristics, it was found that typically one of these four categorical approaches outperforms the others, but depending on the exact sequence of criteria, more than one approach may be successful. Based on these data, we propose a triage scheme that categorizes both objective data set characteristics and subjective personal criteria for the analysis of the different data sets.

The bottleneck for cellular 3D electron microscopy is feature extraction (segmentation) in highly complex 3D density maps. We have developed a set of criteria, which provides guidance regarding which segmentation approach (manual, semi-automated, or automated) is best suited for different data types, thus providing a starting point for effective segmentation.

从体素知识：实用指南复电镜三维数据的分割

Modern 3D electron microscopy approaches have recently allowed unprecedented insight into the 3D ultrastructural organization of cells and tissues, ...

A Guide to Structured Illumination TIRF Microscopy at High Speed with Multiple Colors

Optical super-resolution imaging with structured illumination microscopy (SIM) is a key technology for the visualization of processes at the molecular level in the chemical and biomedical sciences. Although commercial SIM systems are available, systems that are custom designed in the laboratory can outperform commercial systems, the latter typically designed for ease of use and general purpose applications, both in terms of imaging fidelity and speed. This article presents an in-depth guide to building a SIM system that uses total internal reflection (TIR) illumination and is capable of imaging at up to 10 Hz in three colors at a resolution reaching 100 nm. Due to the combination of SIM and TIRF, the system provides better image contrast than rival technologies. To achieve these specifications, several optical elements are used to enable automated control over the polarization state and spatial structure of the illumination light for all available excitation wavelengths. Full details on hardware implementation and control are given to achieve synchronization between excitation light pattern generation, wavelength, polarization state, and camera control with an emphasis on achieving maximum acquisition frame rate. A step-by-step protocol for system alignment and calibration is presented and the achievable resolution improvement is validated on ideal test samples. The capability for video-rate super-resolution imaging is demonstrated with living cells.

This article provides an in depth guide for the assembly and operation of a structured illumination microscope operating with total internal reflection fluorescence illumination (TIRF-SIM) to image dynamic biological processes with optical super-resolution in multiple colors.

指南结构照明显微镜TIRF在高速，多种颜色

Optical super-resolution imaging with structured illumination microscopy (SIM) is a key technology for the visualization of processes at the molecular ...

Techniques for the Evolution of Robust Pentose-fermenting Yeast for Bioconversion of Lignocellulose to Ethanol

Lignocellulosic biomass is an abundant, renewable feedstock useful for production of fuel-grade ethanol and other bio-products. Pretreatment and enzyme saccharification processes release sugars that can be fermented by yeast. Traditional industrial yeasts do not ferment xylose (comprising up to 40% of plant sugars) and are not able to function in concentrated hydrolyzates. Concentrated hydrolyzates are needed to support economical ethanol recovery, but they are laden with toxic byproducts generated during pretreatment. While detoxification methods can render hydrolyzates fermentable, they are costly and generate waste disposal liabilities. Here, adaptive evolution and isolation techniques are described and demonstrated to yield derivatives of the native Scheffersomyces stipitis strain NRRL Y-7124 that are able to efficiently convert hydrolyzates to economically recoverable ethanol despite adverse culture conditions. Improved individuals are enriched in an evolving population using multiple selection pressures reliant on natural genetic diversity of the S. stipitis population and mutations induced by exposures to two diverse hydrolyzates, ethanol or UV radiation. Final evolution cultures are dilution plated to harvest predominant isolates, while intermediate populations, frozen in glycerol at various stages of evolution, are enriched on selective media using appropriate stress gradients to recover most promising isolates through dilution plating. Isolates are screened on various hydrolyzate types and ranked using a novel procedure involving dimensionless relative performance index (RPI) transformations of the xylose uptake rate and ethanol yield data. Using the RPI statistical parameter, an overall relative performance average is calculated to rank isolates based on multiple factors, including culture conditions (varying in nutrients and inhibitors) and kinetic characteristics. Through application of these techniques, derivatives of the parent strain had the following improved features in enzyme saccharified hydrolyzates at pH 5-6: reduced initial lag phase preceding growth, reduced diauxic lag during glucose-xylose transition, significantly enhanced fermentation rates, improved ethanol tolerance and accumulation to 40 g/L.

Adaptive evolution and isolation techniques are described and demonstrated to yield derivatives of Scheffersomyces stipitis strain NRRL Y-7124 that are able to rapidly consume hexose and pentose mixed sugars in enzyme saccharified undetoxified hydrolyzates and to accumulate over 40 g/L ethanol.

鲁棒戊糖发酵酵母的木质纤维素生物转化的演进技术乙醇

Lignocellulosic biomass is an abundant, renewable feedstock useful for production of fuel-grade ethanol and other bio-products. Pretreatment and enzyme ...

A Guide to Build a Highly Inclined Swept Tile Microscope for Extended Field-of-view Single-molecule Imaging

Single-molecule imaging has greatly advanced our understanding of molecular mechanisms in biological studies. However, it has been challenging to obtain large field-of-view, high-contrast images in thick cells and tissues. Here, we introduce highly inclined swept tile (HIST) microscopy that overcomes this problem. A pair of cylindrical lenses was implemented to generate an elongated excitation beam that was scanned over a large imaging area via a fast galvo mirror. A 4f configuration was used to position optical components. A scientific complementary metal-oxide semiconductor camera detected the fluorescence signal and blocked the out-of-focus background with a dynamic confocal slit synchronized with the beam sweeping. We present a step-by-step instruction on building the HIST microscope with all basic components.

A detailed instruction is described on how to build a highly inclined swept tile (HIST) microscope and its usage for single-molecule imaging.

构建用于扩展视场单分子成像的高倾角扫描磁贴显微镜的指南

Single-molecule imaging has greatly advanced our understanding of molecular mechanisms in biological studies. However, it has been challenging to obtain ...

Generation of Heterogeneous Drug Gradients Across Cancer Populations on a Microfluidic Evolution Accelerator for Real-Time Observation

Conventional cell culture remains the most frequently used preclinical model, despite its proven limited ability to predict clinical results in cancer. Microfluidic cancer-on-chip models have been proposed to bridge the gap between the oversimplified conventional 2D cultures and more complicated animal models, which have limited ability to produce reliable and reproducible quantitative results. Here, we present a microfluidic cancer-on-chip model that reproduces key components of a complex tumor microenvironment in a comprehensive manner, yet is simple enough to provide robust quantitative descriptions of cancer dynamics. This microfluidic cancer-on-chip model, the &#34;Evolution Accelerator,&#34; breaks down a large population of cancer cells into an interconnected array of tumor microenvironments while generating a heterogeneous chemotherapeutic stress landscape. The progression and the evolutionary dynamics of cancer in response to drug gradient can be monitored for weeks in real time, and numerous downstream experiments can be performed complementary to the time-lapse images taken through the course of the experiments.

We present a microfluidic cancer-on-chip model, the &#34;Evolution Accelerator&#34; technology, which provides a controllable platform for long-term real-time quantitative studies of cancer dynamics within well-defined environmental conditions at the single-cell level. This technology is expected to work as an in vitro model for fundamental research or pre-clinical drug development.

在微流体进化加速器上生成跨癌症人群的异构药物梯度，用于实时观察

Conventional cell culture remains the most frequently used preclinical model, despite its proven limited ability to predict clinical results in cancer. ...

Screening and Identification of Small Peptides Targeting Fibroblast Growth Factor Receptor2 using a Phage Display Peptide Library

The human Fibroblast Growth Factor Receptor (FGFR) family comprises four members, namely, FGFR1, FGFR2, FGFR3, and FGFR4, that are involved in various biological activities including cell proliferation, survival, migration and differentiation. Several aberrations in the FGFR signaling pathway, owing to mutations or gene amplification events, have been identified in various types of cancers. Hence, recent research has focused on developing strategies involving therapeutic targeting of FGFRs. Current FGFR inhibitors at various stages of pre-clinical and clinical development include either small molecule inhibitors of tyrosine kinases or monoclonal antibodies, with only a few peptide- based inhibitors in the pipeline. Here, we provide a protocol using phage display technology to screen small peptides as antagonists of FGFR2. Briefly, a library of phage-displayed peptides was incubated in a plate coated with FGFR2. Subsequently, unbound phage was washed off by TBST (TBS + 0.1% [v/v] Tween-20), and bound phage was eluted with 0.2 M glycine-HCl buffer (pH 2.2). The eluted phage was further amplified and used as input for the next round of biopanning. Following three rounds of biopanning, the peptide sequences of individual phage clones were identified by DNA sequencing. Finally, the screened peptides were synthesized and analyzed for affinity and biological activity.

Herein, we present a detailed protocol for screening small peptides that bind to FGFR2 using a phage display peptide library. We further analyze the affinity of the selected peptides toward FGFR2 in vitro and its ability to suppress cell proliferation.

使用噬菌体显示肽库筛选和识别针对纤维细胞生长因子受体2的小肽

The human Fibroblast Growth Factor Receptor (FGFR) family comprises four members, namely, FGFR1, FGFR2, FGFR3, and FGFR4, that are involved in various ...

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 ...

Residue-Specific Exchange of Proline by Proline Analogs in Fluorescent Proteins: How "Molecular Surgery" of the Backbone Affects Folding and Stability

Replacement of proline (Pro) residues in proteins by the traditional site-directed mutagenesis by any of the remaining 19 canonical amino acids is often detrimental to protein folding and, in particular, chromophore maturation in green fluorescent proteins and related variants. A reasonable alternative is to manipulate the translation of the protein so that all Pro residues are replaced residue-specifically by analogs, a method known as selective pressure incorporation (SPI). The built-in chemical modifications can be used as a kind of &#34;molecular surgery&#34; to finely dissect measurable changes or even rationally manipulate different protein properties. Here, the study demonstrates the usefulness of the SPI method to study the role of prolines in the organization of the typical &#946;-barrel structure of spectral variants of the green fluorescent protein (GFP) with 10-15 prolines in their sequence: enhanced green fluorescent protein (EGFP), NowGFP, and KillerOrange. Pro residues are present in connecting sections between individual &#946;-strands and constitute the closing lids of the barrel scaffold, thus being responsible for insulation of the chromophore from water, i.e., fluorescence properties. Selective pressure incorporation experiments with (4R)-fluoroproline (R-Flp), (4S)-fluoroproline (S-Flp), 4,4-difluoroproline (Dfp), and 3,4-dehydroproline (Dhp) were performed using a proline-auxotrophic E. coli strain as expression host. We found that fluorescent proteins with S-Flp and Dhp are active (i.e., fluorescent), while the other two analogs (Dfp and R-Flp) produced dysfunctional, misfolded proteins. Inspection of UV-Vis absorption and fluorescence emission profiles showed few characteristic alterations in the proteins containing Pro analogs. Examination of the folding kinetic profiles in EGFP variants showed an accelerated refolding process in the presence of S-Flp, while the process was similar to wild-type in the protein containing Dhp. This study showcases the capacity of the SPI method to produce subtle modifications of protein residues at an atomic level (&#34;molecular surgery&#34;), which can be adopted for the study of other proteins of interest. It illustrates the outcomes of proline replacements with close chemical analogs on the folding and spectroscopic properties in the class of &#946;-barrel fluorescent proteins.

To overcome the limitations of classical site-directed mutagenesis, proline analogs with specific modifications were incorporated into several fluorescent proteins. We show how the replacement of hydrogen by fluorine or of the single by double bonds in proline residues ("molecular surgery") affects fundamental protein properties, including their folding and interaction with light.

荧光蛋白中脯氨酸类似物对脯氨酸的残基特异换：骨架的“分子手术”如何影响折叠和稳定性

Replacement of proline (Pro) residues in proteins by the traditional site-directed mutagenesis by any of the remaining 19 canonical amino acids is often ...

Experimental Quantification of Interactions Between Drug Delivery Systems and Cells In Vitro: A Guide for Preclinical Nanomedicine Evaluation

A major component of designing drug delivery systems concerns how to amplify or attenuate interactions with specific cell types. For instance, a chemotherapeutic might be functionalized with an antibody to enhance binding to cancer cells (&#34;targeting&#34;) or functionalized with polyethylene glycol to help evade immune cell recognition (&#34;stealth&#34;). Even at a cellular level, optimizing the binding and uptake of a drug carrier is a complex biological design problem. Thus, it is valuable to separate how strongly a new carrier interacts with a cell from the functional efficacy of a carrier&#39;s cargo once delivered to that cell.
To continue the chemotherapeutic example, &#34;how well it binds to a cancer cell&#34; is a separate problem from &#34;how well it kills a cancer cell&#34;. Quantitative in vitro assays for the latter are well established and usually rely on measuring viability. However, most published research on cell-carrier interactions is qualitative or semiquantitative. Generally, these measurements rely on fluorescent labeling of the carrier and, consequently, report interactions with cells in relative or arbitrary units. However, this work can be standardized and be made absolutely quantitative with a small number of characterization experiments. Such absolute quantification is valuable, as it facilitates rational, inter- and intra-class comparisons of various drug delivery systems-nanoparticles, microparticles, viruses, antibody-drug conjugates, engineered therapeutic cells, or extracellular vesicles.
Furthermore, quantification is a prerequisite for subsequent meta-analyses or in silico modeling approaches. In this article, video guides, as well as a decision tree for how to achieve in vitro quantification for carrier drug delivery systems, are presented, which take into account differences in carrier size and labeling modality. Additionally, further considerations for the quantitative assessment of advanced drug delivery systems are discussed. This is intended to serve as a valuable resource to improve rational evaluation and design for the next generation of medicine.

Experimental Quantification of Interactions Between Drug Delivery Systems and Cells In Vitro: A Guide for Preclinical Nanomedicine Evaluation

A workflow is demonstrated for the absolute quantification of drug carrier-cell interactions using flow cytometry to allow better rational evaluation of novel drug delivery systems. This workflow is applicable to drug carriers of any type.