这项工作得到了来自犹他州大学病理学系 j.c.s. B 的启动补助金的支持。

1. 通过重叠的2方法, 从化学遗传学数据集确定协同预测突变体 (O2M)
注意: 这是使用尼科尔斯et发布的数据集来识别协同预测突变体的方法。大肠杆菌中的17 。然而, 这可以在任何化学遗传学数据集和微生物。这些数据集包含一个在100多个小分子存在下的挖空突变体库, 为每个小分子中的每个突变体提供定量的生长评分。必须知道一个协同对, 并且在数据集中包含的两个小分子应该有增长分数。
<ol><li>
计算每个小分子在单个浓度下生长的所有突变体的平均生长分数和标准偏差。 注意: 这可以使用任何电子表格软件完成。棕色实验室使用 Excel 和函数 = 平均值 (B3: B3981) 和 = STDEV (B3: B3981) 为小分子的每列的计算。<ol>
<li>计算每列小分子的方法和标准偏差, 但如果使用不同的数据集, 这个方向可能会有所不同。</li>
	</ol>
</li>
	<li>使用来自尼科尔斯et al的相同数据集计算每个小分子浓度的 Z 分数。电子表格程序中的17 。为此, 负 z 分数将是 z (2.5) = 平均-2.5 * 标准偏差, 和正 z 分数将 z (2.5) = 平均值 + 2.5 * 标准偏差。</li>
	<li>确定哪些基因突变体在组成已知协同对的小分子中含有显著的 Z 分数, 一定要观察这些分子的所有浓度。如果突变体的生长评分小于负 z (2.5) 评分或大于正 z (2.5) 分数的小分子, 它被认为是重要的。</li>
	<li>确定是否有任何重要的基因突变体属于操纵。 注: 对于大肠杆菌, 作者建议检查 "Ecoli wiki", 以了解有关基因是否转录为 polycistronic RNA 的一部分的信息。</li>
	<li>在不同浓度的小分子中, 发现基因/操纵突变体 (e. g), 在寻找与抗生素甲氧苄啶协同的分子时, 识别出显着 Z 的突变体。在甲氧苄啶的存在和其已知的协同合作伙伴如 sulfamethizole 或磺胺) 中生长时得分。这些都是假定的协同预测突变体。</li>
</ol>2. 通过 O2M 预测化学遗传学数据集内的 Synergizers
<ol><li>返回到数据集17, 确定每个小分子的浓度, 从协同预测突变体中引出显著的生长分数。这是通过观察计算每个小分子浓度的 Z 分数来完成的。同样, 一个显著的增长分数小于负 z 分数或大于正 z 分数为该浓度的小分子。 注: 如果一个分子出现在其浓度的一个, 分子被认为是预测的 synergizer。任何不引起显著生长评分的分子都是预测的非 synergizer。</li>
</ol>3. 预测的协同相互作用的验证
<ol><li>寻找预测 synergizers 的最小抑制浓度 (MIC)。
	<ol>
<li>在 M9 最小介质中, 在摄氏37摄氏度处生长一夜之间的大肠杆菌文化。 注意: 任何隔夜文化都可以用适当定义的培养基为感兴趣的有机体生长。布朗实验室不推荐像 LB 或 YPD 这样的富媒体。M9 最小介质包括10.5 克/升 M9 汤, 0.2% casamino 酸, 0.1 米 CaCl2, 0.4% 葡萄糖, 1 m MgSO4, 0.25% 烟酸, 0.33% 硫胺在 H2O。</li>
		<li>如果在接受小分子时, 在文献中没有发现感兴趣的病菌的 MIC 数据, 则在高浓度 (> 10 毫克/毫升) 中溶解二甲基亚砜 (亚砜)。</li>
		<li>使用96井板, 添加100µL 的 M9 介质到每个井。在1栏中添加额外的100µL M9 介质, 因此它总共包含200µL。</li>
		<li>在1栏中添加任意量 (~ 10 µL) 的浓缩小分子溶液。一个小分子每井专栏 1 (8 个小分子每板材)。 注: 这些是感兴趣的小分子, 预测协同。布朗实验室通常增加10µL 的高度集中的小分子溶液, 它低于100% 亚砜的数量, 可以抑制大肠杆菌。</li>
		<li>一旦添加了小分子, 就会将小分子分散在平板的 x 轴上。采取100µL 的解决方案从1栏, 地方在2栏和混合。从2栏中取100µL, 在3栏中放置并混合。继续此过程, 直到将100µL 放在11列中。混合11列, 然后从该列中取100µL 并丢弃。将12栏与仅介质保持在一起, 使数据正常化。</li>
		<li>给盘子接种疫苗。从隔夜文化中获取光学密度 (OD600)。用区域性和 M9 介质准备一个解决方案, 使其达到600的 0.002 (或适当的浓度, 表示所需的感兴趣的有机体的500个单元格/µL)。吸管2µL 的培养溶液到每一个井的板块, 所以有1000个细胞每井。</li>
		<li>轻轻摇动盘子, 获得0小时读数的 OD600 。让板材生长在37°c 为 24 h. 获取 24 h 读数的 OD600 。 注: 对其他感兴趣的生物体使用适当的生长条件。</li>
		<li>使用电子表格程序计算每个井的净增长。</li>
		<li>平均12栏净增长, 获得平均无药物增长。使用电子表格软件将其他油井正常化为无药物增长的平均值。寻找任何与少于10% 的增长, 以确定 MIC90 的好。任何低于50% 生长的井表明 MIC50。计算小分子在这些油井中的浓度。</li>
	</ol></li>
	<li>协同作用的棋盘测定方法
	<ol>
<li>像以前一样, 在 M9 最小的介质中长出一夜之间的大肠杆菌文化。 注: 对其他生物体使用适当的生长条件。</li>
		<li>将100µL M9 介质添加到96井板的每一个井中, 在1列中增加100µL。</li>
		<li>将测试小分子 (8 x 麦克风) 添加到1列中的每个井中, 并增加两个浓度 (~ 16 x 麦克风) 到良好的 A1 (每板测试一个小分子)。 注: 这笔金额是从麦克风测试完成之前, 并不同的每一个潜在的 synergizer。</li>
		<li>通过从1列中取100µL 并转移到2列, 在 x 轴上创建渐变稀释。继续此过程, 直到将100µL 添加到11列。混合, 然后采取100µL 从11栏和处置。不要将任何药物添加到12栏 (图 1A)。</li>
		<li>为输入药物在 y 轴上设置第二个药物梯度。添加100µL, 其中包含输入分子的2x 麦克风在 a 行混合和稀释为以前, 采取100µL 从 a 行和放置在 b. 继续直到100µL 放在列 g 混合, 采取100µL 和处置, 确保不添加任何输入药物在行 H。这允许行 H 和12列包含测试的药物对的单个麦克风 (图 1B)。</li>
		<li>给盘子接种疫苗。将 OD 600 0.002 的大肠杆菌区域性的2µL 添加到每个井 (每井1000个单元格)。</li>
		<li>测量0小时读数板中每个井的 OD600 。</li>
		<li>在37摄氏度孵育24小时的盘子。</li>
		<li>在24小时测量每个井的 OD600 。</li>
	</ol></li>
	<li>棋盘中分数抑制浓度指数 (五指) 的计算
	<ol>
<li>通过在电子表格程序中, 从外径600的 od600减去0小时, 计算板中每个井的净增长。</li>
		<li>通过 H12, 不包含小分子的井分, 使软件的增长正常化。</li>
		<li>找出12栏中输入分子的 MIC90 和 MIC90 中潜在增效剂的产生。</li>
		<li>寻找所有能抑制90% 增长的水井。</li>
		<li>计算 FICI90 的井, 这是最低以下 (协同) 或最高以上 (对抗性) 两个 MIC90 值, 使用等式: <img alt="Equation 1" src="/files/ftp_upload/57241/57241eq1.jpg">
</li>
		<li>考虑任何五指≤0.5 作为协同作用和五指≥4作为对抗性 (图 2)。 注: 这也可以做与 MIC50 (50% 抑制增长) 得到一个 FICI50 基于这些麦克风的价值。</li>
	</ol></li>
	<li>极乐独立化验 注: 极乐独立是运行与任何潜在的增效剂, 没有麦克风本身。<ol>
<li>像以前一样, 在 M9 介质中, 在37摄氏度的环境中生长出一夜之间的大肠杆菌文化。 注意: 再一次, 在这个步骤中可以使用适合其他感兴趣有机体的适当生长条件。</li>
		<li>准备96井板, 用于测试潜在的协同分子、输入分子、组合和未处理的控制。</li>
		<li>通过增加50µL 的 M9 介质, 创造潜在的增效剂板块。添加50µL 的介质, 其中包含集浓度 (10 µM 或100µM) 的潜在增效剂的每一个井。每板测试8个分子。</li>
		<li>通过将50µL 的介质添加到每个井中, 创建输入分子板。在1栏中添加50µL 包含输入药物的4x 麦克风。沿 x 轴创建渐变稀释, 类似于 MIC 板, 从1列中取50µL, 在2列中分散和混合。继续此过程直到12栏, 从12列中处理50µL。增加一个额外的50µL 的介质, 每一个井, 所以每个井的结束总数是100µL。</li>
		<li>使用96井板创建组合板, 每井添加50µL 介质。在1栏中添加50µL 包含输入药物的4x 麦克风。沿 x 轴稀释类似于 MIC 板, 从1列中取50µL, 在2列中分散和混合。继续这整个方式到专栏 12, 处理50µL 从专栏12。添加50µL 的介质, 其中含有10µM 或100µM 的潜在增效剂。同样, 每排应该有一个浓度或药物。</li>
		<li>通过将100µL M9 介质添加到板的所有井中, 创建未处理的控制。</li>
		<li>通过添加2µL 的细菌培养, 将所有的盘子接种到0.002 或1000细胞的 OD600 , 并与以前一样。</li>
		<li>在0和 24 h 测量每个井的 OD600 。</li>
	</ol></li>
	<li>计算极乐独立评分
	<ol>
<li>通过使用电子表格程序, 从 24 h 的增长中减去0小时的 OD600 , 计算板中每个井的净增长。</li>
		<li>将油井正常化为电子表格程序中没有药物板块的平均生长。</li>
		<li>使用电子表格软件, 通过减去1的净增长来计算抑制。</li>
		<li>平均控制板中仅包含电子表格软件中的输入渐变的列。</li>
		<li>用等式计算每个井的极乐分数: 极乐评分= (井 x + 输入列 x) -组合井 x
</li>
		<li>在输入的 MIC90 下面寻找井下的负分数。 注意: 跨多个浓度的负分数将表明协同作用。</li>
	</ol></li>
</ol>4. 具有协同预测突变体的高通量屏幕, 以识别新的协同对
<ol><li>
识别协同预测突变体 注: 步骤1.5 确定了假定的协同预测突变体。在这里, 我们确定哪些突变体将在高通量屏幕中发挥最佳作用, 用于协同用药。我们在 Bioscreen 机上进行了这种检测, 但是96台平板阅读器也应该是可以接受的。<ol>
<li>在 M9 极小的培养基中生长每个假定的协同预测突变体和野生型细胞。</li>
		<li>建立100井蜂窝板 (或96井板) 与适当的生长培养基, 生长培养基 + 输入药物, 生长培养基 + 已知的协同合作伙伴的输入药物, 和生长培养基 + 已知的非协同用药。确保包括车辆控制。 注: 我们建议每种应变/药物/浓度的四个复制井。</li>
		<li>每井接种1000个细胞, 包括空白控制井。</li>
		<li>增长48小时在37°c, 与震动, 并且读 OD600每20分钟。</li>
		<li>确定药物浓度和时间点, 表明在输入药物及其已知的协同伙伴存在下, 野生型和协同预测突变细胞之间最大的生长差异。在最佳的时间点和浓度, 野生类型和协同预测突变细胞之间不应该有太大的增长差异, 在已知的药物存在不与输入药物协同作用 (图 3)。</li>
	</ol>
</li>
	<li>
用于协同用药的高通量屏幕
	<ol>
<li>在 M9 最小介质中生长野生型细胞和协同预测突变细胞。 注: 为感兴趣的生物体使用适当的生长培养基。</li>
		<li>将药物从库中添加到介质中, 每一个井中都含有100µL 介质, 在设定浓度上有小分子, 在上一步中确定。包括空白井 (无单元格) 和与车辆控制 (e. g, 亚砜) 的水井, 以说明药物稀释车的任何生长抑制。<ol>
<li>每板至少准备四辆车辆控制井, 理想情况下分散在板上, 以说明井位效应。如果检测是可变的, 那么每行/列至少包含一个车辆控制井, 并使用每行/列控件以及控件来计算每行/列的 Z 分数, 而不是整个板块 (步骤 4.2.5)。</li>
		</ol>
</li>
		<li>将2µL 的文化添加到以前的井中。(一盘为野生类型细菌和一个板材为预测的协同突变细菌)。</li>
		<li>评估大肠杆菌或 48 h 用于C. 隐球菌的 OD600为0和 18 h。</li>
		<li>使用电子表格软件, 通过从车辆控制井中减去空白井的 OD600计算净增长。识别与 z 评分为-2.5 的井 (z 分数 = 平均 2.5 * 标准偏差)。这些井含有一个潜在的增效剂小分子。</li>
		<li>使用步骤3中概述的方法验证屏幕命中。</li>
	</ol>
</li>
</ol>

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A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Systematic+discovery+of+multicomponent+therapeutics.">Systematic discovery of multicomponent therapeutics.</a> Proc Natl Acad Sci USA. 100 (13), 7977-7982 (2003).</li><li>Tang, J., Wennerberg, K., Aittokallio, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=What+is+synergy?+The+Saariselk&#228;+agreement+revisited.">What is synergy? The Saariselk&#228; agreement revisited.</a> Front Pharmacol. 6, 181 (2015).</li><li>Hsieh, M. H., Yu, C. M., Yu, V. L., Chow, J. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Synergy+assessed+by+checkerboard.+A+critical+analysis.">Synergy assessed by checkerboard. A critical analysis.</a> Diagn Microbiol Infect Dis. 16 (4), 343-349 (1993).</li><li>Nichols, R. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phenotypic+Landscape+of+a+Bacterial+Cell.">Phenotypic Landscape of a Bacterial Cell.</a> Cell. 144 (1), 143-156 (2011).</li><li>Chandrasekaran, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chemogenomics+and+orthology-based+design+of+antibiotic+combination+therapies.">Chemogenomics and orthology-based design of antibiotic combination therapies.</a> Mol Syst Biol. 12 (5), (2016).</li><li>Pradhan, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chemogenomic+profiling+of+Plasmodium+falciparum+as+a+tool+to+aid+antimalarial+drug+discovery.">Chemogenomic profiling of Plasmodium falciparum as a tool to aid antimalarial drug discovery.</a> Sci Rep. 5, 15930 (2015).</li><li>Pethe, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+chemical+genetic+screen+in+Mycobacterium+tuberculosis+identifies+carbon-source-dependent+growth+inhibitors+devoid+of+in+vivo+efficacy.">A chemical genetic screen in Mycobacterium tuberculosis identifies carbon-source-dependent growth inhibitors devoid of in vivo efficacy.</a> Nat Commun. 1 (5), 1-8 (2010).</li><li>Diezmann, S., Michaut, M., Shapiro, R. S., Bader, G. D., Cowen, L. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mapping+the+Hsp90+Genetic+Interaction+Network+in+Candida+albicans+Reveals+Environmental+Contingency+and+Rewired+Circuitry.">Mapping the Hsp90 Genetic Interaction Network in Candida albicans Reveals Environmental Contingency and Rewired Circuitry.</a> PLoS Genetics. 8 (3), e1002562 (2012).</li><li>Robbins, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+Antifungal+Combination+Matrix+Identifies+a+Rich+Pool+of+Adjuvant+Molecules+that+Enhance+Drug+Activity+Against+Diverse+Fungal+Pathogens.">An Antifungal Combination Matrix Identifies a Rich Pool of Adjuvant Molecules that Enhance Drug Activity Against Diverse Fungal Pathogens.</a> Cell reports. 13 (7), 1481-1492 (2015).</li><li>Wildenhain, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Prediction+of+Synergism+from+Chemical-Genetic+Interactions+by+Machine+Learning.">Prediction of Synergism from Chemical-Genetic Interactions by Machine Learning.</a> Cell Syst. 1 (6), 383-395 (2015).</li><li>Spitzer, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cross-species+discovery+of+syncretic+drug+combinations+that+potentiate+the+antifungal+fluconazole.">Cross-species discovery of syncretic drug combinations that potentiate the antifungal fluconazole.</a> Mol Syst Biol. 7, 499-499 (2011).</li></ol>

作者没有什么可透露的。

协同小分子对是治疗微生物感染的有力工具, 但由于协同对识别的挑战, 它们尚未达到充分的临床潜力。本文介绍了一种比简单配对组合更快地识别协同副的方法。通过使用化学遗传学数据集, O2M 识别突变体的基因敲除, 然后可以用来作为一个读数, 以筛选大型图书馆的小分子, 以预测协同对。预测小分子的能力允许屏幕的高可伸缩性, 这反过来又使得对协同合作伙伴的大规模识别。在确定协同对的?...

根据 CDC1, 耐药性细菌每年在美国造成200万多人感染和2.3万例死亡。需要新的治疗方法来克服这些感染。确定这些新治疗方法的策略包括开发新的抗菌药物或为其他条件批准的小分子重新调整用途, 以治疗微生物感染2,3,4。然而, 新药的发现是非常昂贵和耗时的。重新用途药物可能不确定新的药物或药物目标5,6。我们的实验室专注于第三种称为协同组合疗法的策略。当两个小分子在一起的功效大于其个体功效7的附加效果时, 协同组合就会发生。此外, 协同组合可以有效对抗抗性的病原体中的一个小分子, 除了有较少的不必要的离靶效果, 使他们很大的潜力8,9, 10。
协同对是罕见的, 发生在大约4-10% 的药物组合中11,12,13。因此, 传统的技术, 如配对屏幕是挑战和耗时, 数以千计的潜在组合, 从一个小图书馆的100分子。此外, 协同作用通常不能从化合物的活动中预测14。但是, 作者开发了一种高吞吐量的方法来筛选协同对, 称为重叠2方法 (O2M)12。这里描述的这种方法允许更快、更有效地识别这些协同对。O2M 需要使用已知的协同对和化学遗传学数据集。化学遗传学数据集是在许多不同的小分子存在的情况下产生的。如果一个已知的协同配对中的一个分子诱导相同的表型从一个特定的淘汰赛突变体作为第二个协同分子, 任何其他小分子, 诱发表型从同一变种人也应该协同与每个成员的已知协同对。这一基本原理已用于布朗实验室, 以确定协同抗菌对大肠杆菌(大肠杆菌)和协同抗真菌药物对致病性真菌隐球菌(C。隐球菌)11,12。O2M 不仅能适应各种病原体, 而且可以方便快速地筛选大型分子库, 以识别协同对。通过 O2M 识别的基因突变体进行筛选, 我们可以只验证那些预测协同作用的小分子。因此, 测试一个2000分子的图书馆配对将需要几个月, 而如果只有20分子在该库预测协同, 现在的协同测试需要几天时间。O2M 不需要编程技能, 在大多数实验室或核心设施中都可以使用所需的设备。除了对药物组合感兴趣的研究人员之外, O2M 分析对于所有已经完成了药物筛选并希望通过确定重要的药物-药物相互作用来扩大其命中范围的人感兴趣。下面是识别细菌中的协同小分子的协议, 以及验证已知化验中预测的协同作用15,16。

<table border="0" cellpadding="0" cellspacing="0" width="520">
	<tbody>
		<tr height="22">
			<td height="22" style="height:22px;width:179px;">Bioscreen C</td>
			<td style="width:88px;">instrument</td>
			<td style="width:136px;">Growth Curves USA</td>
			<td style="width:117px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Synergy H1</td>
			<td>instrument</td>
			<td>BioTek</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">M9 broth</td>
			<td>reagent</td>
			<td>Amresco</td>
			<td>J863-500G</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Casamino Acids</td>
			<td>reagent</td>
			<td>Fisher Scientific</td>
			<td>BP1424-500</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Glucose</td>
			<td>reagent</td>
			<td>Sigma</td>
			<td>G7021-10KG</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Nicotinic Acid</td>
			<td>reagent</td>
			<td>Alfa Aesar</td>
			<td>A12683</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Thiamine</td>
			<td>reagent</td>
			<td>Acros Organics</td>
			<td>148991000</td>
		</tr>
		<tr height="25">
			<td height="25" style="height:25px;">CaCl2 Dihydrate</td>
			<td>reagent</td>
			<td>Fisher</td>
			<td>C79-500</td>
		</tr>
		<tr height="25">
			<td height="25" style="height:25px;">MgSO4 Heptahydrate</td>
			<td>reagent</td>
			<td>Fisher</td>
			<td>M63-500</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">chemical-genetics dataset</td>
			<td>dataset</td>
			<td>examples include Nichols et al., Cell, 2011, Brown et al, Cell, 2014, and others cited in the text.</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">trimethoprim (example input drug; any can be used)</td>
			<td>reagent</td>
			<td>Fisher Scientific</td>
			<td>ICN19552701</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">sulfamethoxazole (example test drug; any can be used)</td>
			<td>reagent</td>
			<td>Fisher Scientific</td>
			<td>ICN15671125</td>
		</tr>
	</tbody>
</table>

high-throughput identification of synergistic drug combinations by the overlap2 method

虽然抗菌药物大大提高了 20th世纪的寿命和生活质量, 但抗菌素耐药性威胁着我们整个社会治疗全身性感染的能力。仅在美国, 耐药性感染每年会杀死大约2.3万人, 额外的医疗费用约为200亿美元。一种对抗抗菌素耐药性的方法是组合疗法, 在感染性机体及其耐药性剖面确定之前, 这在早期的传染性疾病中特别有用。许多抗菌治疗使用组合疗法。然而, 这些组合的大部分是添加剂, 这意味着联合功效是相同的总和的个别抗生素功效。一些组合疗法是协同作用的: 联合功效远远大于添加剂。协同组合特别有用, 因为它们可以抑制抗菌耐药性菌株的生长。然而, 这些组合是罕见的和难以辨认。这是由于需要以配对的方式测试的分子数量太多: 1000 个分子的库有100万种潜在的组合。因此, 已作出努力预测分子的协同作用。本文介绍了用于预测协同小分子对 (称为重叠2方法 (O2M)) 的高通量方法。O2M 使用化学遗传数据集的模式来识别对协同对中的每个分子都敏感的突变体, 而不是其他分子。布朗实验室通过为抑制突变体而非野型细胞的生长而对分子进行高通量筛查来利用这种生长差异。实验室的工作以前确定的分子, 协同与抗生素甲氧苄啶和抗真菌药物氟康唑使用此策略。在此, 作者提出了一种新的协同组合的筛选方法, 可以改变多种微生物。

棋盘检测是一种测量协同相互作用的半定量方法。最后的分数输出, 五指, 确定药物组合是否被认为是协同的 (五指≤0.5), 不相互作用 (0.5 < 五指 < 4), 或拮抗 (五指≥4.0)。图 1阐释了如何在棋盘分析中设置药物渐变。图 2说明了常见的结果。考虑生长不到90% 的生长抑制 (紫色井)。在测量每一个盘子中每个井的 OD600后, 我们?...

Watch this Scientific Journal Video about High-throughput Identification of Synergistic Drug Combinations by the Overlap2 Method at JoVE.com

High-throughput Identification of Synergistic Drug Combinations by the Overlap2 Method

协同药物组合是困难和耗时的鉴定经验。在这里, 我们描述了一种识别和验证协同小分子的方法。

通过重叠2方法高通量识别协同药物组合

Although antimicrobial drugs have dramatically increased the lifespan and quality of life in the 20th century, antimicrobial resistance threatens our ...

high-throughput-identification-synergistic-drug-combinations-overlap2

Research

JoVE Journal

Genetics

High-throughput Identification of Synergistic Drug Combinations by the Overlap2 Method

11.6K 次观看.  University of Utah. 协同药物组合是困难和耗时的鉴定经验。在这里, 我们描述了一种识别和验证协同小分子的方法。

视频: High-throughput Identification of Synergistic Drug Combinations by the Overlap2 Method

A Robotic Platform for High-throughput Protoplast Isolation and Transformation

Over the last decade there has been a resurgence in the use of plant protoplasts that range from model species to crop species, for analysis of signal transduction pathways, transcriptional regulatory networks, gene expression, genome-editing, and gene-silencing. Furthermore, significant progress has been made in the regeneration of plants from protoplasts, which has generated even more interest in the use of these systems for plant genomics. In this work, a protocol has been developed for automation of protoplast isolation and transformation from a &#39;Bright Yellow&#39; 2 (BY-2) tobacco suspension culture using a robotic platform. The transformation procedures were validated using an orange fluorescent protein (OFP) reporter gene (pporRFP) under the control of the Cauliflower mosaic virus 35S promoter (35S). OFP expression in protoplasts was confirmed by epifluorescence microscopy. Analyses also included protoplast production efficiency methods using propidium iodide. Finally, low-cost food-grade enzymes were used for the protoplast isolation procedure, circumventing the need for lab-grade enzymes that are cost-prohibitive in high-throughput automated protoplast isolation and analysis. Based on the protocol developed in this work, the complete procedure from protoplast isolation to transformation can be conducted in under 4 hr, without any input from the operator. While the protocol developed in this work was validated with the BY-2 cell culture, the procedures and methods should be translatable to any plant suspension culture/protoplast system, which should enable acceleration of crop genomics research.

A high-throughput, automated, tobacco protoplast production and transformation methodology is described. The robotic system enables massively parallel gene expression and discovery in the model BY-2 system that should be translatable to non-model crops.

机器人平台的高通量原生质体分离和转型

Over the last decade there has been a resurgence in the use of plant protoplasts that range from model species to crop species, for analysis of signal ...

科研

遗传学

High-Throughput Robotically Assisted Isolation of Temperature-sensitive Lethal Mutants in Chlamydomonas reinhardtii

Systematic identification and characterization of genetic perturbations have proven useful to decipher gene function and cellular pathways. However, the conventional approaches of permanent gene deletion cannot be applied to essential genes. We have pioneered a unique collection of ~70 temperature-sensitive (ts) lethal mutants for studying cell cycle regulation in the unicellular green algae Chlamydomonas reinhardtii1. These mutations identify essential genes, and the ts alleles can be conditionally inactivated by temperature shift, providing valuable tools to identify and analyze essential functions. Mutant collections are much more valuable if they are close to comprehensive, since scattershot collections can miss important components. However, this requires the efficient collection of a large number of mutants, especially in a wide-target screen. Here, we describe a robotics-based pipeline for generating ts lethal mutants and analyzing their phenotype in Chlamydomonas. This technique can be applied to any microorganism that grows on agar. We have collected over 3000 ts mutants, probably including mutations in most or all cell-essential pathways, including about 200 new candidate cell cycle mutations. Subsequent molecular and cellular characterization of these mutants should provide new insights in plant cell biology; a comprehensive mutant collection is an essential prerequisite to ensure coverage of a broad range of biological pathways. These methods are integrated with downstream genetics and bioinformatics procedures for efficient mapping and identification of the causative mutations that are beyond the scope of this manuscript.

High-Throughput Robotically Assisted Isolation of Temperature-sensitive Lethal Mutants in Chlamydomonas reinhardtii

Temperature-sensitive (ts) lethal mutants are valuable tools to identify and analyze essential functions. Here we describe methods to generate and classify ts lethal mutants in high throughput.

温度敏感致死突变体的高通量机器人辅助隔离<em&gt;莱茵衣藻</em

Systematic identification and characterization of genetic perturbations have proven useful to decipher gene function and cellular pathways. However, the ...

Controllable Ion Channel Expression through Inducible Transient Transfection

Transfection, the delivery of foreign nucleic acids into a cell, is a powerful tool in protein research. Through this method, ion channels can be investigated through electrophysiological analysis, biochemical characterization, mutational studies, and their effects on cellular processes. Transient transfections offer a simple protocol in which the protein becomes available for analysis within a few hours to days. Although this method presents a relatively straightforward and time efficient protocol, one of the critical components is calibrating the expression of the gene of interest to physiological relevant levels or levels that are suitable for analysis. To this end, many different approaches that offer the ability to control the expression of the gene of interest have emerged. Several stable cell transfection protocols provide a way to permanently introduce a gene of interest into the cellular genome under the regulation of a tetracycline-controlled transcriptional activation. While this technique produces reliable expression levels, each gene of interest requires a few weeks of skilled work including calibration of a killing curve, selection of cell colonies, and overall more resources. Here we present a protocol that uses transient transfection of the Transient Receptor Potential cation channel subfamily V member 1 (TRPV1) gene in an inducible system as an efficient way to express a protein in a controlled manner which is essential in ion channel analysis. We demonstrate that using this technique, we are able to perform calcium imaging, whole cell, and single channel analysis with controlled channel levels required for each type of data collection with a single transfection. Overall, this provides a replicable technique that can be used to study ion channels structure and function.

Studying ion channels through a heterologously expressing system has become a core technique in biomedical research. In this manuscript, we present a time efficient method to achieve tightly controlled ion channel expression by performing transient transfection under the control of an inducible promoter.

通过诱导瞬时转染可控离子通道表达

Transfection, the delivery of foreign nucleic acids into a cell, is a powerful tool in protein research. Through this method, ion channels can be ...

Generation of Native Chromatin Immunoprecipitation Sequencing Libraries for Nucleosome Density Analysis

We present a modified native chromatin immunoprecipitation sequencing (ChIP-seq) experimental protocol compatible with a Gaussian mixture distribution based analysis methodology (nucleosome density ChIP-seq; ndChIP-seq) that enables the generation of combined measurements of micrococcal nuclease (MNase) accessibility with histone modification genome-wide. Nucleosome position and local density, and the posttranslational modification of their histone subunits, act in concert to regulate local transcription states. Combinatorial measurements of nucleosome accessibility with histone modification generated by ndChIP-seq allows for the simultaneous interrogation of these features. The ndChIP-seq methodology is applicable to small numbers of primary cells inaccessible to cross-linking based ChIP-seq protocols. Taken together, ndChIP-seq enables the measurement of histone modification in combination with local nucleosome density to obtain new insights into shared mechanisms that regulate RNA transcription within rare primary cell populations.

We present a modified native chromatin immunoprecipitation sequencing (ChIP-seq) methodology for the generation of sequence datasets suitable for a nucleosome density ChIP-seq analytical framework integrating micrococcal nuclease (MNase) accessibility with histone modification measurements.

核密度分析的天然染色质沉淀测序文库的生成

We present a modified native chromatin immunoprecipitation sequencing (ChIP-seq) experimental protocol compatible with a Gaussian mixture distribution ...

G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome

Numerous techniques have been developed to follow the progress of DNA replication through the S phase of the cell cycle. Most of these techniques have been directed toward elucidation of the location and timing of initiation of genome duplication rather than its completion. However, it is critical that we understand regions of the genome that are last to complete replication, because these regions suffer elevated levels of chromosomal breakage and mutation, and they have been associated with both disease and aging. Here we describe how we have extended a technique that has been used to monitor replication initiation to instead identify those regions of the genome last to complete replication. This approach is based on a combination of flow cytometry and high throughput sequencing. Although this report focuses on the application of this technique to yeast, the approach can be used with any cells that can be sorted in a flow cytometer according to DNA content.

We describe a technique for combining flow cytometry and high throughput sequencing to identify late replicating regions of the genome.

G2-seq: 一种基于高通量测序技术的基因组晚期复制区域识别方法

Numerous techniques have been developed to follow the progress of DNA replication through the S phase of the cell cycle. Most of these techniques have ...

Robust DNA Isolation and High-throughput Sequencing Library Construction for Herbarium Specimens

Herbaria are an invaluable source of plant material that can be used in a variety of biological studies. The use of herbarium specimens is associated with a number of challenges including sample preservation quality, degraded DNA, and destructive sampling of rare specimens. In order to more effectively use herbarium material in large sequencing projects, a dependable and scalable method of DNA isolation and library preparation is needed. This paper demonstrates a robust, beginning-to-end protocol for DNA isolation and high-throughput library construction from herbarium specimens that does not require modification for individual samples. This protocol is tailored for low quality dried plant material and takes advantage of existing methods by optimizing tissue grinding, modifying library size selection, and introducing an optional reamplification step for low yield libraries. Reamplification of low yield DNA libraries can rescue samples derived from irreplaceable and potentially valuable herbarium specimens, negating the need for additional destructive sampling and without introducing discernible sequencing bias for common phylogenetic applications. The protocol has been tested on hundreds of grass species, but is expected to be adaptable for use in other plant lineages after verification. This protocol can be limited by extremely degraded DNA, where fragments do not exist in the desired size range, and by secondary metabolites present in some plant material that inhibit clean DNA isolation. Overall, this protocol introduces a fast and comprehensive method that allows for DNA isolation and library preparation of 24 samples in less than 13 h, with only 8 h of active hands-on time with minimal modifications.

This article demonstrates a detailed protocol for DNA isolation and high-throughput sequencing library construction from herbarium material including rescue of exceptionally poor-quality DNA.

植物标本标本的鲁棒 DNA 分离与高通量测序库建设

Herbaria are an invaluable source of plant material that can be used in a variety of biological studies. The use of herbarium specimens is associated with ...

The Replica Set Method: A High-throughput Approach to Quantitatively Measure Caenorhabditis elegans Lifespan

The Replica Set method is an approach to quantitatively measure lifespan or survival of Caenorhabditis elegans nematodes in a high-throughput manner, thus allowing a single investigator to screen more treatments or conditions over the same amount of time without loss of data quality. The method requires common equipment found in most laboratories working with C. elegans and is thus simple to adopt. The approach centers on assaying independent samples of a population at each observation point, rather than a single sample over time as with traditional longitudinal methods. Scoring entails adding liquid to the wells of a multi-well plate, which stimulates C. elegans to move and facilitates quantifying changes in healthspan. Other major benefits of the Replica Set method include reduced exposure of agar surfaces to airborne contaminants (e.g. mold or fungus), minimal handling of animals, and robustness to sporadic mis-scoring (such as calling an animal as dead when it is still alive). To appropriately analyze and visualize the data from a Replica Set style experiment, a custom software tool was also developed. Current capabilities of the software include plotting of survival curves for both Replica Set and traditional (Kaplan-Meier) experiments, as well as statistical analysis for Replica Set. The protocols provided here describe the traditional experimental approach and the Replica Set method, as well as an overview of the corresponding data analysis.

The Replica Set Method: A High-throughput Approach to Quantitatively Measure Caenorhabditis elegans Lifespan

Here we describe the Replica Set method, an approach to quantitatively measure C. elegans lifespan/survival and healthspan in a high-throughput and robust manner, thus allowing screening of many conditions without sacrificing data quality. This protocol details the strategy and provides a software tool for analysis of Replica Set data.

复制集方法: 一种高通量方法定量测量秀丽线虫寿命

The Replica Set method is an approach to quantitatively measure lifespan or survival of Caenorhabditis elegans nematodes in a high-throughput manner, thus ...

High-throughput DNA Extraction and Genotyping of 3dpf Zebrafish Larvae by Fin Clipping

Zebrafish (Danio rerio) possess orthologues for 84% of the genes known to be associated with human diseases. In addition, these animals have a short generation time, are easy to handle, display a high reproductive rate, low cost, and are easily amenable to genetic manipulations by microinjection of DNA in embryos. Recent advances in gene editing tools are enabling precise introduction of mutations and transgenes in zebrafish. Disease modeling in zebrafish often leads to larval phenotypes and early death which can be challenging to interpret if genotypes are unknown. This early identification of genotypes is also needed in experiments requiring sample pooling, such as in gene expression or mass spectrometry studies. However, extensive genotypic screening is limited by traditional methods, which in most labs are performed only on adult zebrafish or in postmortem larvae. We addressed this problem by adapting a method for the isolation of PCR-ready genomic DNA from live zebrafish larvae that can be achieved as early as 72 h post-fertilization (hpf). This time and cost-effective technique, improved from a previously published genotyping protocol, allows the identification of genotypes from microscopic fin biopsies. The fins quickly regenerate as the larvae develop. Researchers are then able to select and raise the desired genotypes to adulthood by utilizing this high-throughput PCR-based genotyping procedure.

Zebrafish have been used as reliable genetic model organisms in biomedical research, especially with the advent of gene-editing technologies. When larval phenotypes are expected, DNA extraction and genotype identification can be challenging. Here, we describe an efficient genotyping procedure for zebrafish larvae, by tail clipping, as early as 72-h post-fertilization.

3dpf 斑马鱼幼虫的高通量 DNA 提取及基因分型研究

Zebrafish (Danio rerio) possess orthologues for 84% of the genes known to be associated with human diseases. In addition, these animals have a short ...

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture (4C-seq)

The identification of regulatory elements for a given target gene poses a significant technical challenge owing to the variability in the positioning and effect sizes of regulatory elements to a target gene. Some progress has been made with the bioinformatic prediction of the existence and function of proximal epigenetic modifications associated with activated gene expression using conserved transcription factor binding sites. Chromatin conformation capture studies have revolutionized our ability to discover physical chromatin contacts between sequences and even within an entire genome. Circular chromatin conformation capture coupled with next-generation sequencing (4C-seq), in particular, is designed to discover all possible physical chromatin interactions for a given sequence of interest (viewpoint), such as a target gene or a regulatory enhancer. Current 4C-seq strategies directly sequence from within the viewpoint but require numerous and diverse viewpoints to be simultaneously sequenced to avoid the technical challenges of uniform base calling (imaging) with next generation sequencing platforms. This volume of experiments may not be practical for many laboratories. Here, we report a modified approach to the 4C-seq protocol that incorporates both an additional restriction enzyme digest and qPCR-based amplification steps that are designed to facilitate a greater capture of diverse sequence reads and mitigate the potential for PCR bias, respectively. Our modified 4C method is amenable to the standard molecular biology lab for assessing chromatin architecture.

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture 4C-seq

The identification of physical interactions between genes and regulatory elements is challenging but has been facilitated by chromosome conformation capture methods. This modification to the 4C-seq protocol mitigates PCR bias by minimizing over-amplification of PCR templates and maximizes the mappability of reads by incorporating an addition restriction enzyme digest step.

利用下一代序列染色体构象捕获 (4 c 序列) 的高通量识别基因调控数列

The identification of regulatory elements for a given target gene poses a significant technical challenge owing to the variability in the positioning and ...

Identification of Footprints of RNA:Protein Complexes via RNA Immunoprecipitation in Tandem Followed by Sequencing (RIPiT-Seq)

RNA immunoprecipitation in tandem (RIPiT) is a method for enriching RNA footprints of a pair of proteins within an RNA:protein (RNP) complex. RIPiT employs two purification steps. First, immunoprecipitation of a tagged RNP subunit is followed by mild RNase digestion and subsequent non-denaturing affinity elution. A second immunoprecipitation of another RNP subunit allows for enrichment of a defined complex. Following a denaturing elution of RNAs and proteins, the RNA footprints are converted into high-throughput DNA sequencing libraries. Unlike the more popular ultraviolet (UV) crosslinking followed by immunoprecipitation (CLIP) approach to enrich RBP binding sites, RIPiT is UV-crosslinking independent. Hence RIPiT can be applied to numerous proteins present in the RNA interactome and beyond that are essential to RNA regulation but do not directly contact the RNA or UV-crosslink poorly to RNA. The two purification steps in RIPiT provide an additional advantage of identifying binding sites where a protein of interest acts in partnership with another cofactor. The double purification strategy also serves to enhance signal by limiting background. Here, we provide a step-wise procedure to perform RIPiT and to generate high-throughput sequencing libraries from isolated RNA footprints. We also outline RIPiT&#39;s advantages and applications and discuss some of its limitations.

Identification of Footprints of RNA:Protein Complexes via RNA Immunoprecipitation in Tandem Followed by Sequencing RIPiT-Seq

Here, we present a protocol to enrich endogenous RNA binding sites or &#34;footprints&#34;&#160;of RNA:protein (RNP) complexes from mammalian cells. This approach involves two immunoprecipitations of RNP subunits and is therefore dubbed RNA immunoprecipitation in tandem (RIPiT).

RNA足迹的识别:通过RNA免疫沉淀在串联中的蛋白质复合物,然后测序(RIPiT-Seq)

RNA immunoprecipitation in tandem (RIPiT) is a method for enriching RNA footprints of a pair of proteins within an RNA:protein (RNP) complex. RIPiT ...

通过重叠²方法高通量识别协同药物组合

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