这项研究得到了美国国家心肺血液研究所 （NHLBI） （HL169522） 的支持。

材料表中列出了用于研究的所有试剂和设备的详细信息。
1.读板分光光度计高通量测定
<ol><li>在 96 孔板中用 cADDis BacMam 载体接种 HEK-293 细胞（第 1 天）<ol><li>在病毒罩中分裂和感染细胞。<ol><li>在37°C水浴中加热HEK培养基（表1）和0.25%胰蛋白酶-EDTA。</li>
			<li>用 EtOH 浸泡的纸巾擦拭抽油烟机和材料，对它们进行消毒。</li>
			<li>用血清移液管从烧瓶中取出并丢弃 HEK 培养基。</li>
			<li>用血清移液管加入5mL Mg2+ 和Ca2+ 游离DPBS（37°C）。来回倾斜烧瓶，用 DPBS 清洗底部。用血清移液管取出并丢弃 DPBS。</li>
			<li>通过加入 3 mL 加热的 0.25% 胰蛋白酶-EDTA 和血清移液管来胰蛋白酶化细胞。倾斜烧瓶，确保试剂完全覆盖烧瓶底部。盖上烧瓶盖，让试剂静置 3-5 分钟，让细胞从烧瓶中分离出来。 注意:该实验针对 75 cm2 烧瓶进行了优化;如果使用不同大小的培养器具，则可能需要对试剂进行体积调整。</li>
			<li>吸取 5 mL 含有抗生素的新鲜培养基。排出并抽取烧瓶的体积，以清洗烧瓶的壁并物理分离细胞。</li>
			<li>收集烧瓶的总体积（8mL），并在15mL管中以200× g 离心（25°C）5分钟。</li>
			<li>离心后，用血清移液管除去上清液，注意不要干扰沉淀。</li>
			<li>为了在不干扰沉淀的情况下洗涤细胞，将 500 μL 不含 Mg2+ 和 Ca2+ DPBS 的 DPBS 添加到 15 mL 试管的一侧。轻轻加入 DPBS 后，在不干扰沉淀的情况下，尽可能多地去除并丢弃缓冲液。再重复一次。</li>
			<li>对细胞进行计数，并将细胞密度调整为 250,000 个细胞/mL 细胞。</li>
			<li>根据黑色透明底部 96 孔板每孔所需的试剂量制备预混液。这被称为"组织板"。请参阅以下各卷: 注:1 孔示例（总体积 200 μL）:40 μL 生物传感器 BacMam 载体（2 x 1010 个 病毒基因储备液/mL）、2 μL 曲古抑菌素 A（储备液 100 μM;终浓度 1 μM）、158 μL 250,000 个细胞/mL 细胞密度。10 孔（总体积 2 mL）的示例:400 μL 生物传感器 BacMam 载体（2 x 1010 个 病毒基因储备液/mL）、20 μL 曲古抑菌素 A（100 μM 储备液）、1,580 μL 培养基，密度为 250,000 个细胞/mL 细胞密度。</li>
			<li>每孔加入 200 μL 预混液。将细胞在37°C和5%CO2 的培养箱中孵育24小时，然后在板读数分光光度计上运行。</li>
		</ol></li>
	</ol></li>
	<li>在酶标仪上运行<ol><li>在工作台上，小心地除去每个孔中的所有培养基，并在37°C下用Mg2+ 和Ca2+ 替换180μL DPBS。</li>
		<li>在显微镜上检查细胞以确认细胞健康状况。</li>
		<li>将板包裹在铝箔中，并在37°C下孵育30分钟-1小时。</li>
		<li>孵育时，准备以 1:10 稀释度（也称为 10 倍）读取所需的最终剂量。因此，制备100μM毛喉素和100nM异丙肾上腺素。</li>
		<li>将 60 μL 每种药物以柱状方式加入透明的 96 孔板（称为"药物板"）中。 注:通过适当的药物稀释并优化读数，将药物添加到透明的 96 孔板中，称为"药物板"，在读数时使用 96-multi 移液器转移到"组织板"，允许药物同时添加到所有孔中并由荧光分光光度计快速读取。</li>
	</ol></li>
	<li>荧光酶标仪设置<ol><li>调整荧光酶标仪的设置。<ol><li>读取模式: 荧光。读取类型: 动力学。波长读数: 494 nm 和 522 nm。</li>
			<li>读取时间:输入基线荧光读数 3 分钟 ，给药后添加 7 分钟 。Interval" 输入为 00:00:30 ，每次读取之间为 30 秒。 注意: 读取时间可以根据所需的时间进行优化和增加。</li>
		</ol></li>
	</ol></li>
	<li>数据采集<ol><li>从培养箱中取出组织板，取下铝箔和板盖，然后将组织板放入酶标仪中。关闭读数器抽屉，让组织板静置并与读数仪的温度 （37 °C） 保持平衡。</li>
		<li>将装有药物稀释液的透明 96 孔板（药物板）置于 96-multi 移液器下，并练习从孔中吸取 20 μL。确保在移液器吸头中吸入的药物体积均匀。</li>
		<li>启动"基线"测量运行。 注意:40 RFU 或更高被认为是可行的数据。如果数据低于此值，则应停止并丢弃实验。</li>
		<li>组织板将在基线运行结束时从读数器中弹出。迅速而小心地将 20 μL 从透明药物板添加到黑色组织板中。然后，快速开始"治疗"运行。加入药物后，组织板不应离开读数器超过 30 秒。 注意:如果药物添加得太快，细胞会从组织板上脱落，从而产生无法使用的实验。此外，细胞被光敏绿色荧光蛋白感染;因此，迅速而迅速地添加药物并开始第二次阅读对于避免错过反应的早期部分至关重要。</li>
		<li>第二次读数完成后，确保将组织板从读数器中弹出并结束数据收集。 注意:在处理组织板之前，最佳做法是确认细胞仍附着在板上。在显微镜下观察细胞。如果细胞分离，则结果无效，应丢弃。需要重复该实验。</li>
		<li>将结果数据导出为 Excel 文件。</li>
		<li>从酶标仪中打开导出的Excel可读数据，将相关信息复制粘贴到Excel转换模板中。数据将从酶标仪设置转换为单孔，列读数位于复制数据的右侧。 注:孔随时间变化的荧光柱列列在RFU（标题为柱变换）中，并作为相对于初始读数时RFU读数的小数变化（t0 ，标题为Delta F）。在 Excel 模板中，Delta F 表设置为药物添加前的最后一个基线读数。这是第 6 个 数据收集点。</li>
		<li>数据转换后，从Delta F复制数据，并将其粘贴到数据分析软件中，作为荧光随时间推移的衰减或相对衰减。</li>
		<li>将 X 标题更改为"time （s）"，将 Y 标题更改为"ΔF/F0"，以获得相对十进制值。</li>
	</ol></li>
</ol>2. 使用倒置荧光显微镜进行单细胞测定
<ol><li>在 35 mm 培养皿中使用 cADDis BacMam 载体接种 （HASM） 细胞（第 1 天）<ol><li>在病毒罩中分裂和感染细胞。<ol><li>温热的HASM培养基（表1），0.25%胰蛋白酶-EDTA在37°C水浴中。</li>
			<li>对抽油烟机和材料进行消毒，并用 EtOH 浸泡的纸巾擦拭抽油烟机。</li>
			<li>用血清移液管从烧瓶中取出并丢弃 HASM 培养基。</li>
			<li>用新的血清移液管加入5mL Mg2+ 和Ca2 + 游离DPBS（37°C），并倾斜烧瓶以用DPBS洗涤底部。</li>
			<li>通过用血清移液管加入 3 mL 加热的 0.25% 胰蛋白酶-EDTA 来胰蛋白酶化细胞。倾斜烧瓶，确保试剂完全覆盖烧瓶底部。让试剂静置 3-5 分钟，让细胞从烧瓶中分离出来。</li>
			<li>吸取 5 mL 含有抗生素的新鲜培养基，然后排出移液管以从烧瓶底部除去细胞。</li>
			<li>将烧瓶（8mL）的总体积收集在离心管中以200×g离心5分钟。</li>
			<li>离心后，用血清移液管除去上清液，注意不要干扰沉淀。</li>
			<li>在不干扰沉淀的情况下，将 500 μL 不含 Mg2+ 和 Ca2+ DPBS 的 DPBS 添加到离心管的一侧。取出并丢弃尽可能多的液体，然后再重复一次。 注意:该实验针对 75 cm2 烧瓶进行了优化;如果使用不同大小的培养器具，则可能需要对试剂进行体积调整。</li>
			<li>对细胞进行计数并调整至 40,000 个细胞/mL 细胞密度。</li>
			<li>根据 35 mm 培养皿中每孔所需的试剂体积制备预混液。请参阅以下各卷: 注:1 孔示例（总体积 500 μL）:20 μL 生物传感器 BacMam 载体（2 x 1010 个 病毒基因储备液/mL）、5 μL 曲古抑菌素 A（储备液 100 μM，终浓度 1 μM）、500 μL 40,000 个细胞/mL 细胞密度。4 孔（总体积 2 mL）的示例:80 μL 生物传感器 BacMam 载体（病毒基因储备液/mL）、20 μL 曲古抑菌素 A（储备液 100 μM，终浓度 1 μM）、2000 μL 培养基 40,000 个细胞/mL 细胞密度。</li>
			<li>每孔加入 500 μL 预混液。将细胞在37°C和5%CO2 下孵育24小时，然后再继续实验。 注:细胞数量可能因细胞系而异。为避免分析中的像元重叠，请使用较少的像元数。</li>
		</ol></li>
	</ol></li>
	<li>准备药理学药物（第 2 天）<ol><li>小心地去除每个孔中的培养基，并在37°C下用Mg2+ 和Ca2+ 替换450μL DPBS。</li>
		<li>将板包裹在铝箔中，并将35mm圆盘在37°C孵育30分钟-1小时。</li>
		<li>在显微镜上检查细胞以确认细胞健康状况。</li>
		<li>同时，准备药物，使读数高于所需最终浓度（10倍高）1个对数单位。因此，制备100μM毛喉素和100nM异丙肾上腺素。</li>
		<li>对于对数剂量滴度，以 10 mM 制备药物并使用连续稀释以获得 100 μM 毛喉素和 100 nM 异丙肾上腺素。</li>
	</ol></li>
	<li>数据采集 注意:以下设置适用于荧光倒置显微镜。每台显微镜随附的软件可能不同;此处介绍了当前协议中使用的常规设置。<ol><li>打开中央集线器，然后打开倒置荧光显微镜。</li>
		<li>打开将用于捕获的软件，然后选择 延时捕获 选项。</li>
		<li>将35mm培养皿样品架放在显微镜载物台上。</li>
		<li>将物镜设置为 x20。</li>
		<li>使用 自动对焦 并获得尽可能清晰的图片。如果很难找到单个细胞，请从 4 倍物镜开始，然后移至 20 倍物镜。如果显微镜缺少自动对焦功能，请手动对样品进行对焦。 注意:如果需要更重要的细胞形态细节，可以使用 40 倍的放大倍数。</li>
		<li>调整以下设置以获得最佳数据采集: 自动亮度 （曝光）、 激发波长、 黑平衡 （以减少背景噪声）、 自动对焦。</li>
		<li>在找到具有几个细胞质荧光细胞的视野区域后，使用延时捕获每 30 秒 20 分钟获取数据。</li>
		<li>单击 "转到 "开始阅读。</li>
		<li>运行 3 分钟以收集基线。一旦捕获 3 分钟，轻轻地将 50 μL 药物加入适当的孔中。当加入药物时，培养皿上的最终浓度将是 10 μM 毛喉素和 10 nM 异丙肾上腺素。 注意:必须小心添加药物;请勿用移液器吸头触摸板，因为这可能会移动视野 view 所做的并使 sample 无法分析。</li>
		<li>让实验再运行 17 分钟，每 30 秒捕获一次数据。</li>
		<li>测试完成后，请确保数据已准备好进行分析。 注意:虽然目前的协议没有包含焦点漂移的控制，但在实验中包含一个可能是有益的。例如，在显微镜分析过程中，使用核染料可以帮助管理焦点漂移，特别是在长时间捕获活细胞图像时。cADDis 生物传感器通常广泛分布在细胞内，使宽焦平面成为最有效的捕获方式，并减少了控制焦距漂移的需要9。</li>
	</ol></li>
	<li>分析数据 注意:每台显微镜随附的软件可能不同，因此此处介绍了应用于分析捕获图像的一般设置。<ol><li>打开实验期间捕获的图像文件。</li>
		<li>使用 面 或 圆圈 工具选择每个像元的感兴趣区域以执行分析。分析应给出每个时间点每个单元格的亮度。 注意:最佳做法是选择单个细胞，而不是接触培养皿壁或其他细胞壁的细胞。这确保了最佳的数据收集。在每个条件下选择至少 5 个细胞进行分析，并至少重复实验 3 次。</li>
		<li>分析数据后，在Excel表格中打开数据，并计算每张照片中每种条件的平均亮度，从图片开始，然后再添加药理学试剂或载体。在此示例中，在显微镜上拍摄的第 3 分钟标记或第 6 张照片，因为每张照片每 30 秒拍摄一次。</li>
		<li>计算每个条件下每个平均值的 ΔF/F0 。</li>
		<li>加载到统计分析软件中，并以 s 为单位绘制 ΔF/F0 与时间的关系图。 注: 图 1 提供了协议主要步骤的示意图。</li>
	</ol></li>
</ol>

使用 cADDis 进行 cAMP 分析:单细胞到高通量筛选

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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=Agonist-specific+desensitization+of+PGE(2)-stimulated+cAMP+signaling+due+to+upregulated+phosphodiesterase+expression+in+human+lung+fibroblasts.">Agonist-specific desensitization of PGE(2)-stimulated cAMP signaling due to upregulated phosphodiesterase expression in human lung fibroblasts.</a> Naunyn Schmiedebergs Arch Pharmacol. 393 (2), 843-856 (2020).</li><li>Ojiaku, C. 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=Transforming+growth+factor-beta1+decreases+beta(2)-agonist-induced+relaxation+in+human+airway+smooth+muscle.">Transforming growth factor-beta1 decreases beta(2)-agonist-induced relaxation in human airway smooth muscle.</a> Am J Respir Cell Mol Biol. 61 (2), 209-218 (2019).</li><li>Zuo, H., 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=Cigarette+smoke+up-regulates+pde3+and+pde4+to+decrease+cAMP+in+airway+cells.">Cigarette smoke up-regulates pde3 and pde4 to decrease cAMP in airway cells.</a> Br J Pharmacol. 175 (14), 2988-3006 (2018).</li><li>Cullum, S. A., Veprintsev, D. B., Hill, S. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Kinetic+analysis+of+endogenous+beta(2)+-adrenoceptor-mediated+cAMP+glosensor+responses+in+hek293+cells.">Kinetic analysis of endogenous beta(2) -adrenoceptor-mediated cAMP glosensor responses in hek293 cells.</a> Br J Pharmacol. 180 (2), 1304-1315 (2023).</li><li>Liu, X., Sun, S. Q., Ostrom, R. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fibrotic+lung+fibroblasts+show+blunted+inhibition+by+cAMP+due+to+deficient+cAMP+response+element-binding+protein+phosphorylation.">Fibrotic lung fibroblasts show blunted inhibition by cAMP due to deficient cAMP response element-binding protein phosphorylation.</a> J Pharmacol Exp Ther. 315 (2), 678-687 (2005).</li><li>Bogard, A. S., Birg, A. V., Ostrom, R. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Non-raft+adenylyl+cyclase+2+defines+a+cAMP+signaling+compartment+that+selectively+regulates+il-6+expression+in+airway+smooth+muscle+cells:+Differential+regulation+of+gene+expression+by+ac+isoforms.">Non-raft adenylyl cyclase 2 defines a cAMP signaling compartment that selectively regulates il-6 expression in airway smooth muscle cells: Differential regulation of gene expression by ac isoforms.</a> Naunyn Schmiedebergs Arch Pharmacol. 387 (4), 329-339 (2014).</li><li>Schmidt, M., Cattani-Cavalieri, I., Nunez, F. J., Ostrom, R. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phosphodiesterase+isoforms+and+cAMP+compartments+in+the+development+of+new+therapies+for+obstructive+pulmonary+diseases.">Phosphodiesterase isoforms and cAMP compartments in the development of new therapies for obstructive pulmonary diseases.</a> Curr Opin Pharmacol. 51, 34-42 (2020).</li><li>Ostrom, K. F., 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=Physiological+roles+of+mammalian+transmembrane+adenylyl+cyclase+isoforms.">Physiological roles of mammalian transmembrane adenylyl cyclase isoforms.</a> Physiol Rev. 102 (2), 815-857 (2022).</li><li>Auld, D. 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=Characterization+of+chemical+libraries+for+luciferase+inhibitory+activity.">Characterization of chemical libraries for luciferase inhibitory activity.</a> J Med Chem. 51 (8), 2372-2386 (2008).</li><li>De Logu, F., 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=Schwann+cell+endosome+CGRP+signals+elicit+periorbital+mechanical+allodynia+in+mice.">Schwann cell endosome CGRP signals elicit periorbital mechanical allodynia in mice.</a> Nat Commun. 13 (1), 646 (2022).</li><li>Wray, N. H., Schappi, J. M., Singh, H., Senese, N. B., Rasenick, M. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=NMDAR-independent,+cAMP-dependent+antidepressant+actions+of+ketamine.">NMDAR-independent, cAMP-dependent antidepressant actions of ketamine.</a> Mol Psychiatry. 24 (12), 1833-1843 (2019).</li><li>Thornquist, S. C., Pitsch, M. J., Auth, C. S., Crickmore, M. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biochemical+evidence+accumulates+across+neurons+to+drive+a+network-level+eruption.">Biochemical evidence accumulates across neurons to drive a network-level eruption.</a> Mol Cell. 81 (4), 675-690 (2021).</li><li>Zhang, S. X., 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=Hypothalamic+dopamine+neurons+motivate+mating+through+persistent+cAMP+signalling.">Hypothalamic dopamine neurons motivate mating through persistent cAMP signalling.</a> Nature. 597 (7875), 245-249 (2021).</li><li>Lutas, A., Fernando, K., Zhang, S. X., Sambangi, A., Andermann, M. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=History-dependent+dopamine+release+increases+cAMP+levels+in+most+basal+amygdala+glutamatergic+neurons+to+control+learning.">History-dependent dopamine release increases cAMP levels in most basal amygdala glutamatergic neurons to control learning.</a> Cell Rep. 38 (4), 110297 (2022).</li><li>Zhang, C., 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=Area+postrema+cell+types+that+mediate+nausea-associated+behaviors.">Area postrema cell types that mediate nausea-associated behaviors.</a> Neuron. 109 (3), 461-472 (2021).</li></ol>

提交人没有相互竞争的经济利益。

准确、灵敏地测量 cAMP 对于了解其在各种细胞过程中的作用以及研究 cAMP 依赖性信号通路的活性至关重要。通常采用几种方法测量 cAMP 水平，包括 ELISA、放射免疫测定、FRET 生物传感器和 GloSensor cAMP 测定 14,15,16,17,18。每种 cAMP 检测都有其优点和缺点。该协议允许实时检测和?...

腺苷 3′，5′-环磷酸 （cAMP） 在细胞通讯和各种生理过程的协调中起着核心作用。cAMP 充当第二信使，传递来自激素、神经递质或其他细胞外分子的外部信号，以启动细胞内事件的级联反应1。此外，cAMP 错综复杂地参与各种信号通路，包括与 G 蛋白偶联受体 （GPCR） 和腺苷酸环化酶相关的信号通路。了解 cAMP 在细胞信号转导中的作用对于揭示正常细胞功能背后的复杂机制和开发针对各种疾病的潜在疗法至关重要2.
过去，已经采用各种方法直接或间接地测量 cAMP。这些包括细胞 ATP 池的放射性标记，然后进行色谱柱纯化、HPLC、放射免疫测定和酶联免疫测定 1,2。这些传统检测方法受到限制，因为它们是终点测量，需要大量样本来构建时间依赖性响应。最近，荧光共振能量转移 （FRET） 传感器被开发出来，用于在活细胞中创建检测，产生实时、动态的数据，并允许传感器在不同的亚细胞位置进行靶向3。FRET利用两个荧光团，一个荧光供体和一个荧光受体，当靠近时，受体荧光团将被供体荧光输出激发。最常用的两种荧光基团是青色荧光蛋白 （CFP） 和黄色荧光蛋白 （YFP），因为它们具有相容的激发和发射特性。除CFP和YFP外，绿色荧光蛋白（GFP）和红色荧光蛋白（RFP）的利用也常用于FRET生物传感器。cAMP FRET生物传感器通过在Epac2 cAMP结合蛋白的两端具有供体和受体来操作。cAMP 结合改变了 Epac 的确认，并增加了供体和受体荧光基团之间的距离 3,4。这种构象变化是通过FRET的损失来检测的，即受体荧光团通过从供体荧光团液滴转移的能量激发3。虽然这是一个看似简单的过程，但用于 cAMP 研究的 FRET 生物传感器存在大量限制和问题5.其中之一是荧光蛋白的选择，例如GFP，它可以自然二聚化，从而降低灵敏度6。基于 FRET 的 cAMP 生物传感器已靶向特定微结构域7，但由于具有两个荧光基团的构建体尺寸大，可能存在局限性6。另一个重要问题是，由于荧光团的激发和发射之间的重叠，导致FRET信号的信噪比低，导致采样频率高，结果分析复杂化4,5。
最近，新型生物传感器（cAMP Difference Detector In Situ）cADDis 在研究 cAMP 信号传导的调节时解决了这些和其他限制8。一个重要的改进是对单一荧光基团的依赖性。这样可以获得快速高效的信号，具有更宽的动态范围和高信噪比。因此，可以有更高的准确性，因为要梳理的波长范围较小8.与FRET探针一样，该生物传感器已靶向亚细胞位置，从而可以研究脂质筏和非筏以及其他亚细胞结构域中的分隔理论和探索9。也许最重要的是单一荧光团生物传感器适用于高通量筛选，与基于 FRET 的生物传感器相比，它提高了灵敏度和可重复性。该生物传感器被封装到 BacMam 载体中，便于转导多种细胞类型并精确控制蛋白质表达。
通过 BacMam 载体进行表达控制在使用来自不同物种的 GPCR 直系同源物的测定中特别有用，以促进动物研究数据的解释。此外，控制受体表达对于测量不同程度的药物疗效（例如，反向激动剂和部分激动剂）至关重要，而低水平的受体表达有助于模拟动物组织中发现的低水平。BacMam 是一种杆状病毒载体，已被修饰以转导哺乳动物细胞，例如原代细胞培养物和 HEK-293 系10。显性可选标记物使 BacMam 比传统质粒感染具有更高的稳定性11。这种选择性启动子允许更有效的基因递送和表达。此外，添加曲古抑菌素 A（一种组蛋白脱乙酰酶抑制剂）可增强报告蛋白水平11。表达水平可以通过所用 BacMam 病毒的滴度来控制，并且应针对每种细胞类型进行优化。在这种生物传感器的情况下，红色或绿色荧光蛋白与N端和C端的Epac相连。当 cAMP 结合时，生物传感器的构象变化会移动与荧光蛋白相邻的氨基酸。这种位移使吸光度从阴离子态移动到400nm处的中性态，从而降低了荧光。
在单个细胞中有 90-120 个 GPCR 表达，对多种神经体液信号有反应12。因此，可以假设每个细胞至少有几十个GPCRs可以分别通过Gs或Gi偶联刺激或抑制cAMP。虽然在实时监测第二个信使（例如FRET）方面取得了进展，但需要更有效的方法。本文介绍了使用cADDis实时监测cAMP信号合成和降解的方法。可以使用荧光酶标仪进行高通量检测或使用荧光显微镜进行单细胞检测，实时监测荧光的变化。这些方法对于 通过 cAMP进行GPCR信号转导的广泛生物学问题非常有用。

<table><tbody><tr><td>96-well plate (clear)</td><td>Fisherbrand</td><td>21-377-203</td><td></td></tr><tr><td>35 mm dish</td><td>Greiner Bio-One</td><td>627870</td><td>Cell culture dishes with glass bottom</td></tr><tr><td>96-well plate&amp;nbsp;</td><td>Corning</td><td>3904</td><td>Black with clear flat bottom</td></tr><tr><td>Antibiotic-Antimycotic (100x)</td><td>Gibco</td><td>15240062</td><td>For HEK and HASM media</td></tr><tr><td>BZ-X fluorescence microscope</td><td>Keyence</td><td></td><td></td></tr><tr><td>Calcium chloride (IM)</td><td>Quality Biological Inc</td><td>E506</td><td>For HASM media</td></tr><tr><td>Centrifuge tube (15 mL)</td><td>Thermo Scientific</td><td>339651</td><td></td></tr><tr><td>DMEM (1x)</td><td>Gibco</td><td>11965092</td><td>HEK media</td></tr><tr><td>DPBS with Mg&lt;sup&gt;2+&lt;/sup&gt; and Ca&lt;sup&gt;2+&lt;/sup&gt;&amp;nbsp;</td><td>Gibco</td><td>14040-133</td><td></td></tr><tr><td>DPBS without Mg&lt;sup&gt;2+&lt;/sup&gt; and Ca&lt;sup&gt;2+&lt;/sup&gt;</td><td>Corning</td><td>14040-133</td><td></td></tr><tr><td>Fetal Bovine Serum (FBS)</td><td>R&amp;amp;D systems</td><td>S11195</td><td>For HEK and HASM media</td></tr><tr><td>Forskolin</td><td>Millipore</td><td>344270</td><td>Drug</td></tr><tr><td>Green Down cADDis cAMP Assay Kit</td><td>Montana Molecular</td><td>#D0200G</td><td>Reagent</td></tr><tr><td>Ham&#039;s F-12K&amp;nbsp;</td><td>Gibco</td><td>21127022</td><td>For HASM media</td></tr><tr><td>HEPES (1M)</td><td>Gibco</td><td>15630080</td><td>For HASM media</td></tr><tr><td>Isoproterenol</td><td>Sigma</td><td>I6504</td><td>Drug</td></tr><tr><td>L-glutamine 200 mM (100x)</td><td>Gibco</td><td>25030-081</td><td>For HASM media</td></tr><tr><td>Microcentrifuge tube (2 mL)</td><td>Eppendorf</td><td>22363352</td><td></td></tr><tr><td>Primocin</td><td>Invitrogen</td><td>ant-pm-1</td><td>Antibiotic for HASM media</td></tr><tr><td>RNAse away</td><td>Thermo Scientific</td><td>700511</td><td>Reagent</td></tr><tr><td>Sodium hydroxide solution</td><td>Sigma</td><td>S2770</td><td>For HASM media</td></tr><tr><td>Spectrmax M5 plate reader</td><td>Molecular Devices</td><td></td><td></td></tr><tr><td>Trichostatin A</td><td>TCI America</td><td>T2477</td><td>Reagent</td></tr><tr><td>Trypsin EDTA</td><td>Gibco</td><td>25200-056</td><td>Reagent</td></tr></tbody></table>

real-time camp dynamics in live cells using the fluorescent camp difference detector in situ

cAMP原 位 差异检测器（cADDis）是一种新型生物传感器，可以连续测量活细胞中的cAMP水平。该生物传感器由与Epac2的铰链区域相连的环状置换荧光蛋白制成。这创建了一个单一的荧光团生物传感器，在结合 cAMP 时显示荧光增加或减少。生物传感器有红色和绿色的向上版本，以及绿色的向下版本，以及针对亚细胞位置的几种红色和绿色版本。为了说明生物传感器的有效性，使用了绿色的向下版本，该版本在cAMP结合时荧光减少。演示了使用该传感器的两种方案:一种利用与高通量筛选兼容的 96 孔板读取分光光度计，另一种利用荧光显微镜上的单细胞成像。在酶标仪上，用 10 μM 毛喉素或 10 nM 异丙肾上腺素刺激在 96 孔板中培养的 HEK-293 细胞，其诱导绿色向下版本的荧光快速且大幅减少。该生物传感器用于测量在荧光显微镜下监测的单个人体气道平滑肌 （HASM） 细胞中的 cAMP 水平。当用毛喉素或异丙肾上腺素刺激时，绿色向下的生物传感器对细胞群表现出类似的反应。这种单细胞测定允许在 20 倍和 40 倍放大下可视化生物传感器的位置。因此，这种 cAMP 生物传感器具有灵敏和灵活性，可以实时测量永生化细胞和原代细胞中的 cAMP，以及单细胞或细胞群的 cAMP。这些特性使cADD成为研究活细胞中cAMP信号动力学的宝贵工具。

本研究在酶标仪和显微镜检测中验证了胞质生物传感器。一旦细胞表达生物传感器，它们就会用10μM毛喉素（腺苷酸环化酶的直接激活剂），10nM异丙肾上腺素（ß1AR和ß2AR的激动剂）或载体（图1）刺激。每 30 秒捕获一次荧光的后续变化，表明 cAMP 的产生。
数据被转换为荧光相对于初始荧光的变化 （ΔF/F0）。将单位点衰变模型应?...

Read this Scientific Article Protocol about Author Spotlight: Advancing Real-Time cAMP Detection in Cells Using cADDis Biosensor at JoVE.com

作者聚焦:使用 cADDis 生物传感器推进细胞实时 cAMP 检测

本研究中提出的协议说明了cAMP原位差动检测器通过两种方法测量cAMP的有效性。一种方法使用带有 HEK-293 细胞的 96 孔板读数分光光度计。另一种方法在荧光显微镜下展示单个HASM细胞。

使用荧光 cAMP 原位差检测器在活细胞中实时 cAMP 动力学

cAMP Difference Detector In Situ (cADDis) is a novel biosensor that allows for the continuous measurement of cAMP levels in living cells. The biosensor is ...

我们为循环 KP 微域的组织提供服务，重点是阐明这些区室是如何形成和维持的。我们试图揭示使细胞能够辨别这些域内的空间信号的关键组成部分，探索其解释的变化，以及这些特征在哮喘和慢性阻塞性肺病等疾病中是如何改变的。使用Beckman载体感染原代细胞具有挑战性。为此，应针对单个细胞类型优化条件，以实现生物传感器的充分表达。该协议允许实时检测和监测，范围从几分钟到几小时，并测量活细胞内的环形营地动力学。因此，本文产生的信号与环状P水平直接相关，大大减少了来自其他细胞成分的潜在干扰，并提供了可靠的结果。

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Biochemistry

Real-Time cAMP Dynamics in Live Cells Using the Fluorescent cAMP Difference Detector In Situ

762 次观看.  Chapman University School of Pharmacy. 我们为循环 KP 微域的组织提供服务，重点是阐明这些区室是如何形成和维持的。我们试图揭示使细胞能够辨别这些域内的空间信号的关键组成部分，探索其解释的变化，以及这些特征在哮喘和慢性阻塞性肺病等疾病中是如何改变的。使用Beckman载体感染原代细胞具有挑战性。为此，应针对单个细胞类型优化条件，以实现生物传感器的充分表达。该协议允许实时检测和监?...

视频: 作者聚焦:使用 cADDis 生物传感器推进细胞实时 cAMP 检测

Live-cell Imaging of Migrating Cells Expressing Fluorescently-tagged Proteins in a Three-dimensional Matrix

Traditionally, cell migration has been studied on two-dimensional, stiff plastic surfaces. However, during important biological processes such as wound healing, tissue regeneration, and cancer metastasis, cells must navigate through complex, three-dimensional extracellular tissue. To better understand the mechanisms behind these biological processes, it is important to examine the roles of the proteins responsible for driving cell migration. Here, we outline a protocol to study the mechanisms of cell migration using the epithelial cell line (MDCK), and a three-dimensional, fibrous, self-polymerizing matrix as a model system. This optically clear extracellular matrix is easily amenable to live-cell imaging studies and better mimics the physiological, soft tissue environment. This report demonstrates a technique for directly visualizing protein localization and dynamics, and deformation of the surrounding three-dimensional matrix. 
Examination of protein localization and dynamics during cellular processes provides key insight into protein functions. Genetically encoded fluorescent tags provide a unique method for observing protein localization and dynamics. Using this technique, we can analyze the subcellular accumulation of key, force-generating cytoskeletal components in real-time as the cell maneuvers through the matrix. In addition, using multiple fluorescent tags with different wavelengths, we can examine the localization of multiple proteins simultaneously, thus allowing us to test, for example, whether different proteins have similar or divergent roles. Furthermore, the dynamics of fluorescently tagged proteins can be quantified using Fluorescent Recovery After Photobleaching (FRAP) analysis. This measurement assays the protein mobility and how stably bound the proteins are to the cytoskeletal network.
By combining live-cell imaging with the treatment of protein function inhibitors, we can examine in real-time the changes in the distribution of proteins and morphology of migrating cells. Furthermore, we also combine live-cell imaging with the use of fluorescent tracer particles embedded within the matrix to visualize the matrix deformation during cell migration. Thus, we can visualize how a migrating cell distributes force-generating proteins, and where the traction forces are exerted to the surrounding matrix. Through these techniques, we can gain valuable insight into the roles of specific proteins and their contributions to the mechanisms of cell migration.

Cellular processes such as cell migration have traditionally been studied on two-dimensional, stiff plastic surfaces. This report describes a technique for directly visualizing protein localization and analyzing protein dynamics in cells migrating in a more physiologically relevant, three-dimensional matrix.

活细胞成像的移植细胞在一个三维矩阵表示荧光标记的蛋白质

Traditionally, cell migration has been studied on two-dimensional, stiff plastic surfaces. However, during important biological processes such as wound ...

科研

生物工程

An Optogenetic Method to Control and Analyze Gene Expression Patterns in Cell-to-cell Interactions

Cells should respond properly to temporally changing environments, which are influenced by various factors from surrounding cells. The Notch signaling pathway is one of such essential molecular machinery for cell-to-cell communications, which plays key roles in normal development of embryos. This pathway involves a cell-to-cell transfer of oscillatory information with ultradian rhythms, but despite the progress in molecular biology techniques, it has been challenging to elucidate the impact of multicellular interactions on oscillatory gene dynamics. Here, we present a protocol that permits optogenetic control and live monitoring of gene expression patterns in a precise temporal manner. This method successfully revealed that intracellular and intercellular periodic inputs of Notch signaling entrain intrinsic oscillations by frequency tuning and phase shifting at the single-cell resolution. This approach is applicable to the analysis of the dynamic features of various signaling pathways, providing a unique platform to test a functional significance of dynamic gene expression programs in multicellular systems.

Here, we present a protocol to analyze cell-to-cell transfer of oscillatory information by optogenetic control and live monitoring of gene expression. This approach provides a unique platform to test a functional significance of dynamic gene expression programs in multicellular systems.

细胞间相互作用中基因表达模式的控制与分析的 Optogenetic 方法

Cells should respond properly to temporally changing environments, which are influenced by various factors from surrounding cells. The Notch signaling ...

遗传学

Real-time Live Imaging of T-cell Signaling Complex Formation

Protection against infectious diseases is mediated by the immune system 1,2. T lymphocytes are the master coordinators of the immune system, regulating the activation and responses of multiple immune cells 3,4. T-cell activation is dependent on the recognition of specific antigens displayed by antigen presenting cells (APCs). The T-cell antigen receptor (TCR) is specific to each T-cell clone and determines antigen specificity 5. The binding of the TCR to the antigen induces the phosphorylation of components of the TCR complex. In order to promote T-cell activation, this signal must be transduced from the membrane to the cytoplasm and the nucleus, initiating various crucial responses such as recruitment of signaling proteins to the TCR;APC site (the immune synapse), their molecular activation, cytoskeletal rearrangement, elevation of intracellular calcium concentration, and changes in gene expression 6,7. The correct initiation and termination of activating signals is crucial for appropriate T-cell responses. The activity of signaling proteins is dependent on the formation and termination of protein-protein interactions, post translational modifications such as protein phosphorylation, formation of protein complexes, protein ubiquitylation and the recruitment of proteins to various cellular sites 8. Understanding the inner workings of the T-cell activation process is crucial for both immunological research and clinical applications.
Various assays have been developed in order to investigate protein-protein interactions; however, biochemical assays, such as the widely used co-immunoprecipitation method, do not allow protein location to be discerned, thus precluding the observation of valuable insights into the dynamics of cellular mechanisms. Additionally, these bulk assays usually combine proteins from many different cells that might be at different stages of the investigated cellular process. This can have a detrimental effect on temporal resolution. The use of real-time imaging of live cells allows both the spatial tracking of proteins and the ability to temporally distinguish between signaling events, thus shedding light on the dynamics of the process 9,10. We present a method of real-time imaging of signaling-complex formation during T-cell activation. Primary T-cells or T-cell lines, such as Jurkat, are transfected with plasmids encoding for proteins of interest fused to monomeric fluorescent proteins, preventing non-physiological oligomerization 11. Live T cells are dropped over a coverslip pre-coated with T-cell activating antibody 8,9, which binds to the CD3/TCR complex, inducing T-cell activation while overcoming the need for specific activating antigens. Activated cells are constantly imaged with the use of confocal microscopy. Imaging data are analyzed to yield quantitative results, such as the colocalization coefficient of the signaling proteins.

We describe a live-cell imaging method that provides insight into protein dynamics during the T-cell activation process. We demonstrate the combined usage of the T-cell spreading assay, confocal microscopy and imaging analysis to yield quantitative results to follow signaling complex formation throughout T-cell activation.

T细胞实时成像实时信号复合物的形成

Protection against infectious diseases is mediated by the immune system 1,2. T lymphocytes are the master coordinators of the immune system, regulating ...

免疫与感染

Dual-Color Fluorescence Cross-Correlation Spectroscopy to Study Protein-Protein Interaction and Protein Dynamics in Live Cells

We present a protocol and workflow to perform live cell dual-color fluorescence cross-correlation spectroscopy (FCCS) combined with F&#246;rster Resonance Energy transfer (FRET) to study membrane receptor dynamics in live cells using modern fluorescence labeling techniques. In dual-color FCCS, where the fluctuations in fluorescence intensity represent the dynamic &#34;fingerprint&#34; of the respective fluorescent biomolecule, we can probe co-diffusion or binding of the receptors. FRET, with its high sensitivity to molecular distances, serves as a well-known &#34;nanoruler&#34; to monitor intramolecular changes. Taken together, conformational changes and key parameters such as local receptor concentrations and mobility constants become accessible in cellular settings.
Quantitative fluorescence approaches are challenging in cells due to high noise levels and the vulnerability of the sample. Here we show how to perform this experiment, including the calibration steps using dual-color labeled &#946;2-adrenergic receptor (&#946;2AR) labeled with eGFP and SNAP-tag-TAMRA. A step-by-step data analysis procedure is provided using open-source software and templates that are easy to customize.
Our guideline enables researchers to unravel molecular interactions of biomolecules in live cells in situ with high reliability despite the limited signal-to-noise levels in live cell experiments. The operational window of FRET and particularly FCCS at low concentrations allows quantitative analysis at near-physiological conditions.

We present an experimental protocol and data analysis workflow to perform live cell dual-color fluorescence cross correlation spectroscopy (FCCS) combined with F&#246;rster Resonance Energy transfer (FRET) to study membrane receptor dynamics in live cells using modern fluorescence labeling techniques.

双色荧光互相关光谱研究活细胞中蛋白质-蛋白质相互作用和蛋白质动力学

We present a protocol and workflow to perform live cell dual-color fluorescence cross-correlation spectroscopy (FCCS) combined with F&#246;rster Resonance ...

生物化学

Monitoring Kinase and Phosphatase Activities Through the Cell Cycle by Ratiometric FRET

F&ouml;rster resonance energy transfer (FRET)-based reporters1 allow the assessment of endogenous kinase and phosphatase activities in living cells. Such probes typically consist of variants of CFP and YFP, intervened by a phosphorylatable sequence and a phospho-binding domain. Upon phosphorylation, the probe changes conformation, which results in a change of the distance or orientation between CFP and YFP, leading to a change in FRET efficiency (Fig 1). Several probes have been published during the last decade, monitoring the activity balance of multiple kinases and phosphatases, including reporters of PKA2, PKB3, PKC4, PKD5, ERK6, JNK7, Cdk18, Aurora B9 and Plk19. Given the modular design, additional probes are likely to emerge in the near future10. 
Progression through the cell cycle is affected by stress signaling pathways 11. Notably, the cell cycle is regulated differently during unperturbed growth compared to when cells are recovering from stress12.Time-lapse imaging of cells through the cell cycle therefore requires particular caution. This becomes a problem particularly when employing ratiometric imaging, since two images with a high signal to noise ratio are required to correctly interpret the results. Ratiometric FRET imaging of cell cycle dependent changes in kinase and phosphatase activities has predominately been restricted to sub-sections of the cell cycle8,9,13,14.
Here, we discuss a method to monitor FRET-based probes using ratiometric imaging throughout the human cell cycle. The method relies on equipment that is available to many researchers in life sciences and does not require expert knowledge of microscopy or image processing.

FRET-based reporters are increasingly used to monitor kinase and phosphatase activities in live cells. Here we describe a method on how to use FRET-based reporters to assess cell cycle-dependent changes in target phosphorylation.

通过细胞周期激酶和磷酸酶活性成比例的FRET监测

F&ouml;rster resonance energy transfer (FRET)-based reporters1 allow the assessment of endogenous kinase and phosphatase activities in living cells. Such ...

生物学

FRET Microscopy for Real-time Monitoring of Signaling Events in Live Cells Using Unimolecular Biosensors

F&ouml;rster resonance energy transfer (FRET) microscopy continues to gain increasing interest as a technique for real-time monitoring of biochemical and signaling events in live cells and tissues. Compared to classical biochemical methods, this novel technology is characterized by high temporal and spatial resolution. FRET experiments use various genetically-encoded biosensors which can be expressed and imaged over time in situ or in vivo1-2. Typical biosensors can either report protein-protein interactions by measuring FRET between a fluorophore-tagged pair of proteins or conformational changes in a single protein which harbors donor and acceptor fluorophores interconnected with a binding moiety for a molecule of interest3-4. Bimolecular biosensors for protein-protein interactions include, for example, constructs designed to monitor G-protein activation in cells5, while the unimolecular sensors measuring conformational changes are widely used to image second messengers such as calcium6, cAMP7-8, inositol phosphates9 and cGMP10-11. Here we describe how to build a customized epifluorescence FRET imaging system from single commercially available components and how to control the whole setup using the Micro-Manager freeware. This simple but powerful instrument is designed for routine or more sophisticated FRET measurements in live cells. Acquired images are processed using self-written plug-ins to visualize changes in FRET ratio in real-time during any experiments before being stored in a graphics format compatible with the build-in ImageJ freeware used for subsequent data analysis. This low-cost system is characterized by high flexibility and can be successfully used to monitor various biochemical events and signaling molecules by a plethora of available FRET biosensors in live cells and tissues. As an example, we demonstrate how to use this imaging system to perform real-time monitoring of cAMP in live 293A cells upon stimulation with a &beta;-adrenergic receptor agonist and blocker.

F&#246;rster resonance energy transfer (FRET) microscopy is a powerful technique for real-time monitoring of signaling events in live cells using various biosensors as reporters. Here we describe how to build a customized epifluorescence FRET imaging system from commercially available components and how to use it for FRET experiments.

FRET显微镜在活细胞单分子生物传感器的信号事件的实时监测

F&ouml;rster resonance energy transfer (FRET) microscopy  continues to gain increasing interest as a technique for real-time monitoring  of biochemical ...

Single-molecule Imaging of Gene Regulation In vivo Using Cotranslational Activation by Cleavage (CoTrAC)

We describe a fluorescence microscopy method, Co-Translational Activation by Cleavage (CoTrAC) to image the production of protein molecules in live cells with single-molecule precision without perturbing the protein's functionality. This method makes it possible to count the numbers of protein molecules produced in one cell during sequential, five-minute time windows. It requires a fluorescence microscope with laser excitation power density of ~0.5 to 1 kW/cm2, which is sufficiently sensitive to detect single fluorescent protein molecules in live cells. The fluorescent reporter used in this method consists of three parts: a membrane targeting sequence, a fast-maturing, yellow fluorescent protein and a protease recognition sequence. The reporter is translationally fused to the N-terminus of a protein of interest. Cells are grown on a temperature-controlled microscope stage. Every five minutes, fluorescent molecules within cells are imaged (and later counted by analyzing fluorescence images) and subsequently photobleached so that only newly translated proteins are counted in the next measurement.
Fluorescence images resulting from this method can be analyzed by detecting fluorescent spots in each image, assigning them to individual cells and then assigning cells to cell lineages. The number of proteins produced within a time window in a given cell is calculated by dividing the integrated fluorescence intensity of spots by the average intensity of single fluorescent molecules. We used this method to measure expression levels in the range of 0-45 molecules in single 5 min time windows. This method enabled us to measure noise in the expression of the &lambda; repressor CI, and has many other potential applications in systems biology.

Single-molecule Imaging of Gene Regulation In vivo Using Cotranslational Activation by Cleavage CoTrAC

We describe a fluorescence microscopy method, Co-Translational Activation by Cleavage (CoTrAC), to image the production of protein molecules in live cells with single-molecule precision without perturbing the protein's functionality. This method has been used to follow the stochastic expression dynamics of a transcription factor, the &lambda; repressor CI 1.

单分子成像的基因调控<em在体内</em使用转位激活裂解（CoTrAC）

We describe a fluorescence microscopy method, Co-Translational Activation by Cleavage (CoTrAC) to image the production of protein molecules in live cells ...

Temporal Quantification of MAPK Induced Expression in Single Yeast Cells

The quantification of gene expression at the single cell level uncovers novel regulatory mechanisms obscured in measurements performed at the population level. Two methods based on microscopy and flow cytometry are presented to demonstrate how such data can be acquired. The expression of a fluorescent reporter induced upon activation of the high osmolarity glycerol MAPK pathway in yeast is used as an example. The specific advantages of each method are highlighted. Flow cytometry measures a large number of cells (10,000) and provides a direct measure of the dynamics of protein expression independent of the slow maturation kinetics of the fluorescent protein. Imaging of living cells by microscopy is by contrast limited to the measurement of the matured form of the reporter in fewer cells. However, the data sets generated by this technique can be extremely rich thanks to the combinations of multiple reporters and to the spatial and temporal information obtained from individual cells. The combination of these two measurement methods can deliver new insights on the regulation of protein expression by signaling pathways.

Two complementary methods based on flow cytometry and microscopy are presented which enable the quantification, at the single cell level, of the dynamics of gene expression induced by the activation of a MAPK pathway in yeast.

在单酵母细胞MAPK诱导表达的时空定量

The quantification of gene expression at the  single cell level uncovers novel regulatory mechanisms obscured in measurements  performed at the population ...

Live Cell Fluorescence Microscopy to Observe Essential Processes During Microbial Cell Growth

Core cellular processes such as DNA replication and segregation, protein synthesis, cell wall biosynthesis, and cell division rely on the function of proteins which are essential for bacterial survival. A series of target-specific dyes can be used as probes to better understand these processes. Staining with lipophilic dyes enables the observation of membrane structure, visualization of lipid microdomains, and detection of membrane blebs. Use of fluorescent-d-amino acids (FDAAs) to probe the sites of peptidoglycan biosynthesis can indicate potential defects in cell wall biogenesis or cell growth patterning. Finally, nucleic acid stains can indicate possible defects in DNA replication or chromosome segregation. Cyanine DNA stains label living cells and are suitable for time-lapse microscopy enabling real-time observations of nucleoid morphology during cell growth. Protocols for cell labeling can be applied to protein depletion mutants to identify defects in membrane structure, cell wall biogenesis, or chromosome segregation. Furthermore, time-lapse microscopy can be used to monitor morphological changes as an essential protein is removed and can provide additional insights into protein function. For example, the depletion of essential cell division proteins results in filamentation or branching, whereas the depletion of cell growth proteins may cause cells to become shorter or rounder. Here, protocols for cell growth, target-specific labeling, and time-lapse microscopy are provided for the bacterial plant pathogen Agrobacterium tumefaciens. Together, target-specific dyes and time-lapse microscopy enable characterization of essential processes in A. tumefaciens. Finally, the protocols provided can be readily modified to probe essential processes in other bacteria.

Understanding the function of essential processes in bacteria is challenging. Fluorescence microscopy with target-specific dyes can provide key insights into microbial cell growth and cell cycle progression. Here, Agrobacterium tumefaciens is used as a model bacterium to highlight methods for live cell imaging for characterization of essential processes.

活体细胞荧光显微镜观察微生物细胞生长过程中的基本过程

Core cellular processes such as DNA replication and segregation, protein synthesis, cell wall biosynthesis, and cell division rely on the function of ...

Real-Time Monitoring of Aurora kinase A Activation using Conformational FRET Biosensors in Live Cells

Epithelial cancers are often hallmarked by the overexpression of the Ser/Thr kinase Aurora A/AURKA. AURKA is a multifunctional protein that activates upon its autophosphorylation on Thr288. AURKA abundance peaks in mitosis, where it controls the stability and the fidelity of the mitotic spindle, and the overall efficiency of mitosis. Although well characterized at the structural level, a consistent monitoring of the activation of AURKA throughout the cell cycle is lacking. A possible solution consists in using genetically-encoded F&#246;rster&#8217;s Resonance Energy Transfer (FRET) biosensors to gain insight into the autophosphorylation of AURKA with sufficient spatiotemporal resolution. Here, we describe a protocol to engineer FRET biosensors detecting Thr288 autophosphorylation, and how to follow this modification during mitosis. First, we provide an overview of possible donor/acceptor FRET pairs, and we show possible cloning and insertion methods of AURKA FRET biosensors in mammalian cells. Then, we provide a step-by-step analysis for rapid FRET measurements by fluorescence lifetime imaging microscopy (FLIM) on a custom-built setup. However, this protocol is also applicable to alternative commercial solutions available. We conclude by considering the most appropriate FRET controls for an AURKA-based biosensor, and by highlighting potential future improvements to further increase the sensitivity of this tool.

The activation of the multifunctional Ser/Thr kinase AURKA is hallmarked by its autophosphorylation on Thr288. Fluorescent probes relying on FRET can discriminate between its inactive and activated states. Here, we illustrate some strategies for probe engineering, together with a rapid FRET protocol to follow the kinase activation throughout mitosis.

使用活细胞中的构象FRET生物传感器实时监测极光激酶A活化

Epithelial cancers are often hallmarked by the overexpression of the Ser/Thr kinase Aurora A/AURKA. AURKA is a multifunctional protein that activates upon ...