这项工作由国家科学技术发展委员会（CNPq，巴西）[资助号428048/2018-8和402556/2022-4]和巴西利亚大学（巴西）资助。作者感谢 Duarte Nuno Carvalho 博士和 Evelyn Santos 博士（i3s，葡萄牙波尔图）提供对他们在本研究中使用的智能手机的访问。

1. Bradford蛋白测定试剂的制备
<ol><li>将 100 mg 考马斯亮蓝 G 溶解在 50 mL 95% （w/v） 乙醇中。混合至考马斯亮蓝G完全溶解。 注意:乙醇易燃，会引起眼睛刺激。避免火焰并使用护目镜。</li>
	<li>在前面的溶液中，小心地加入 100 mL 85% （w/v） 磷酸。 注意: 磷酸对金属有腐蚀性，会导致皮肤腐蚀、严重的眼睛损伤和急性口腔毒性。戴上手套和护目镜。</li>
	<li>将含有考马斯亮蓝 G、乙醇和磷酸的溶液缓慢加入 600 mL 去离子水中。</li>
	<li>将溶液稀释至最终体积为 1,000 mL。根据要分析的样品数量扩大或缩小规模。如原始方法7所述，工作Bradford试剂中的终浓度应为0.01%（w/v）考马斯亮蓝G、4.7%（w/v）乙醇和8.5%（w/v）磷酸。</li>
	<li>通过滤纸（Whatman #1 纸或同等纸）去除任何不溶性物质过滤。</li>
	<li>该试剂在室温 （RT） 下储存并避光时可稳定数周。必要时过滤，因为沉淀物可能会随着时间的推移而形成。 注意:或者，市售的即用型 Bradford 试剂也可随手使用。按照制造商的说明制备试剂，然后继续下一步。</li>
</ol>2.蛋白质标准溶液的制备
<ol><li>制备分离蛋白质的储备溶液（参见步骤2.4）作为标准品使用。牛血清白蛋白 （BSA） 是一种经济实惠且常用的蛋白质。其他选择是卵清蛋白和牛丙种球蛋白。</li>
	<li>如果已知用作标准品的蛋白质的摩尔吸收率，请在分光光度计中检查储备溶液的浓度。</li>
	<li>对于 BSA，常用的公式是 BSA （mg/mL） = （A280/6.6） × 10，其中 A280 是相对于适当空白（即ε 2801% = 6.6）7 处的吸光度，光程长度为 1 cm。例如，0.8 mg/mL BSA 在 280 nm 处的吸光度为 0.528。</li>
	<li>为了生成标准曲线，在0.025 mg / mL和1.0 mg / mL内制备几种稀释的BSA。在每孔添加 10 μL 的样品体积后，每孔将获得 0.25-10 μg BSA。 注意:蛋白质标准溶液应在与用于制备样品的培养基具有相同成分（终浓度）的培养基中制备。</li>
</ol>3. 测定
<ol><li>稀释样品，使蛋白质浓度达到0.025-1.0mg/mL的标准曲线范围内。在该范围内进行多次（至少 3 次）样品稀释。 注意:样品可以用磷酸盐缓冲盐水 （PBS） 或任何其他与 Bradford 试剂兼容的培养基/缓冲液组合物稀释。标准品和样品之间培养基组分的最终浓度不应有差异。</li>
	<li>将 10 μL 每种蛋白质标准溶液加入 96 孔微孔板的三个孔（即一式三份）中。对于 0（零）蛋白点，加入 10 μL 用于制备标准溶液和样品稀释液的缓冲液/培养基。</li>
	<li>在另一组孔中，将每个样品稀释度的 10 μL 加入到相同 96 孔微孔板的三个孔（即一式三份）中。一种方法是添加不同体积的样品，并完成每孔最多 10 μL 的培养基（例如，0.5 μL、1 μL、2 μL、4 μL 和 8 μL 样品加上 9.5 μL、9 μL、8 μL、6 μL 和 2 μL 培养基）。</li>
	<li>向所有孔中加入 250 μL Bradford 蛋白测定试剂。典型的微孔板设置如 图2所示。在本例中，包括一组含有 260 μL（每孔最终体积）水的空白孔，作为酶标仪中的空白孔（步骤 4.5）。仅当还将收集吸光度数据时，才需要这样做。 注意:每次进行测定时，在同一样品微孔板中制备标准曲线。换言之，如果样品数量需要另一块板，则在第二块板中准备另一条标准曲线，依此类推。</li>
	<li>在 5-15 分钟内记录结果（第 4 节）。</li>
</ol><img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/65547/65547fig02v2.jpg"> 图 2:Bradford 蛋白检测的典型板布局。 空白是指在酶标仪中用作空白的三孔，其中含有 260 μL 水。STD是指蛋白质标准品。S1-S6 是六个不同的样品。SX_1-SX_4是每个样品的四种不同的样品稀释度。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65547/65547fig02large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
4. 记录结果
<ol><li>在光线充足的房间内，用一只手将微孔板平行于工作台，放在均匀的白色背景（例如，纸张）上。通过在板上放置气泡水平仪来确保准确对齐。</li>
	<li>另一方面，将智能手机平行握住（某些相机应用程序可以有效地指示设备的倾斜度）到工作台和微孔板上，并拍摄整个微孔板的一张或几张照片（图 3）。在 iOS 设备中，通过启用 网格 选项在相机设置中打开相机电平指示器。在 Android 设备中，通过启用 取景提示来打开相机设置中的相机电平指示器。</li>
	<li>不需要特殊的照明设备，但要注意避免阴影和反射。例如，避免使用智能手机对印版或背景进行着色，并避免使用微孔板对背景进行着色。井区边缘的小反射不是问题;颜色数据可以从每个孔中心的一个非常小的区域中提取。</li>
	<li>简要检查图片的背景均匀性、阴影和反射。另外，看看井的角度;每个井的中心应该是直接可见的（即，而不是在井壁后面）。</li>
	<li>如果需要比较微孔板吸光度读数和图片颜色数据，请在酶标仪21中读取590nm和450nm处的微孔板。</li>
</ol><img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/65547/65547fig03v2.jpg"> 图 3:捕获 Bradford 蛋白检测的结果。 在光线充足的房间中，用一只手将微孔板平行放置在均匀的背景下。另一方面，智能手机平行于工作台和微孔板。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65547/65547fig03large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
5.自动提取颜色数据
<ol><li>下载 ImageJ 和 ReadPlate22，ImageJ 插件可在 https://imagej.nih.gov/ij/plugins/readplate/index.html 获得（这是一个.txt文件）。</li>
	<li>打开 ImageJ，单击 Plugins > Install ，然后选择在步骤 6.1 中下载的文件。</li>
	<li>通过单击 "分析">"设置测量 值"来设置测量参数，然后选中以下选项: 面积;标准差;最小和最大灰度值;平均灰度值;模态灰度值。在窗口底部，将 "重定向为:无 "和 "小数位 （0-9）:3"设置为"重定向"。</li>
	<li>转到 "文件>"打开 "，然后选择步骤4中拍摄的微孔板的图片。</li>
	<li>转到 ReadPlate >插件。阅读说明，然后单击 "确定"。</li>
	<li>选择孔数: 96。</li>
	<li>使用插件自动加载的 矩形选择 工具，制作一个从 A1 孔中心开始到 H12 孔中心结束的矩形。然后，单击 "确定"。</li>
	<li>选择 "蓝色 "通道，然后单击 "确定"。</li>
	<li>单击 "确定"确认默认参数。</li>
	<li>检查软件是否在每个孔内划定了一个区域，以及所选区域是否没有覆盖具有异常阴影或反射的区域。单击 "确定"。</li>
	<li>保存结果，然后对绿色通道重复步骤 5.8-5.10。</li>
	<li>使用每种颜色的模式计算蓝绿比。 注意:计算可以手动完成，也可以使用读者首选项的软件完成，例如 R、Microsoft Excel 或 GraphPad Prism。</li>
</ol>6. 手动提取颜色数据
<ol><li>下载 Inkscape，一个免费的开源图形编辑器。 注意:任何带有颜色选择器工具（通常描述为滴管）的软件都可用于识别颜色并提取 RGB 数据。</li>
	<li>打开 Inkscape，转到 "文件">"打开"。 选择 在步骤4中拍摄的微孔板的图片。</li>
	<li>选择 选择和变换对象 （S） 工具，该工具在左上角显示为箭头，然后单击图片。虚线边框将指示选择。</li>
	<li>选择 从图像中选取颜色 （D） 工具，该工具在左侧显示为吸管。</li>
	<li>点击一口井的中心。底部面板上的颜色（"填充:"）将相应更改。单击颜色，右侧将弹出" 填充和描边 "选项卡。</li>
	<li>将 "纯色 "下拉菜单更改为 "RGB"。记录每个孔的蓝色和绿色通道显示的值。</li>
	<li>使用记录的值计算蓝绿比。 注意:计算可以手动完成，也可以使用读者首选项的软件完成，例如 R、Microsoft Excel 或 GraphPad Prism。</li>
</ol>7. 构建标准曲线并推断未知数
<ol><li>绘制平均绿色与蓝色强度比作为蛋白质标准浓度的函数。 注意:手动绘制数据或使用阅读器首选项的软件，例如 R、Microsoft Excel 或 GraphPad Prism。</li>
	<li>计算每个样品的平均绿蓝强度比和稀释度。</li>
	<li>检查样品获得的信号是否在蛋白质标准品的线性范围内。</li>
	<li>忽略低于或高于标准曲线的最小值或最大值的任何值。</li>
	<li>使用描述标准曲线的线性方程来推断样品中的蛋白质量。相应地将计算值乘以稀释系数。</li>
</ol>

智能手机作为使用 Bradford 分析定量蛋白质的分析设备

<ol>
	<li>Zaguri, M., Kandel, S., Rinehart, S. A., Torsekar, V. R., Hawlena, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Protein+quantification+in+ecological+studies:+A+literature+review+and+empirical+comparisons+of+standard+methodologies.">Protein quantification in ecological studies: A literature review and empirical comparisons of standard methodologies.</a> Methods in Ecology and Evolution. 12 (7), 1240-1251 (2021).</li><li>Koga, T., 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=Mild+electrical+stimulation+and+heat+shock+ameliorates+progressive+proteinuria+and+renal+inflammation+in+mouse+model+of+Alport+syndrome.">Mild electrical stimulation and heat shock ameliorates progressive proteinuria and renal inflammation in mouse model of Alport syndrome.</a> PLoS One. 7 (8), e43852 (2012).</li><li>Peterson, G. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Determination+of+total+protein.">Determination of total protein.</a> Methods in Enzymology. 91, 95-119 (1983).</li><li>Goldfarb, A. R., Saidel, L. J., Mosovich, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+ultraviolet+absorption+spectra+of+proteins.">The ultraviolet absorption spectra of proteins.</a> The Journal of Biological Chemistry. 193 (1), 397-404 (1951).</li><li>Lowry, O. H., Rosebrough, N. J., Farr, A. L., Randall, R. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Protein+measurement+with+the+Folin+phenol+reagent.">Protein measurement with the Folin phenol reagent.</a> The Journal of Biological Chemistry. 193 (1), 265-275 (1951).</li><li>Smith, P. 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=Measurement+of+protein+using+bicinchoninic+acid.">Measurement of protein using bicinchoninic acid.</a> Analytical Biochemistry. 150 (1), 76-85 (1985).</li><li>Bradford, 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=A+rapid+and+sensitive+method+for+the+quantitation+of+microgram+quantities+of+protein+utilizing+the+principle+of+protein-dye+binding.">A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding.</a> Analytical Biochemistry. 72 (1-2), 248-254 (1976).</li><li>Datki, Z., 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=Application+of+BisANS+fluorescent+dye+for+developing+a+novel+protein+assay.">Application of BisANS fluorescent dye for developing a novel protein assay.</a> PLoS One. 14 (4), e0215863 (2019).</li><li>Van Noorden, R., Maher, B., Nuzzo, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+top+100+papers.">The top 100 papers.</a> Nature. 514 (7524), 550-553 (2014).</li><li>. Scopus Available from: <a target="_blank" href="https://www.scopus.com/">https://www.scopus.com/</a> (2022)</li><li>Compton, S. J., Jones, C. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mechanism+of+dye+response+and+interference+in+the+Bradford+protein+assay.">Mechanism of dye response and interference in the Bradford protein assay.</a> Analytical Biochemistry. 151 (2), 369-374 (1985).</li><li>Chial, H. J., Thompson, H. B., Splittgerber, A. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+spectral+study+of+the+charge+forms+of+Coomassie+Blue+G.">A spectral study of the charge forms of Coomassie Blue G.</a> Analytical Biochemistry. 209 (2), 258-266 (1993).</li><li>Pande, S. V., Murthy, M. S. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+modified+micro-Bradford+procedure+for+elimination+of+interference+from+sodium+dodecyl+sulfate,+other+detergents,+and+lipids.">A modified micro-Bradford procedure for elimination of interference from sodium dodecyl sulfate, other detergents, and lipids.</a> Analytical Biochemistry. 220 (2), 424-426 (1994).</li><li>Gogstad, G. O., Krutnes, M. -. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measurement+of+protein+in+cell+suspensions+using+the+Commassie+brilliant+blue+dye-binding+assay.">Measurement of protein in cell suspensions using the Commassie brilliant blue dye-binding assay.</a> Analytical Biochemistry. 126 (2), 355-359 (1982).</li><li>Friedenauer, S., Berlet, H. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sensitivity+and+variability+of+the+Bradford+protein+assay+in+the+presence+of+detergents.">Sensitivity and variability of the Bradford protein assay in the presence of detergents.</a> Analytical Biochemistry. 178 (2), 263-268 (1989).</li><li>Stoscheck, C. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Increased+uniformity+in+the+response+of+the+Coomassie+blue+G+protein+assay+to+different+proteins.">Increased uniformity in the response of the Coomassie blue G protein assay to different proteins.</a> Analytical Biochemistry. 184 (1), 111-116 (1990).</li><li>Zor, T., Selinger, Z. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Linearization+of+the+Bradford+protein+assay+increases+its+sensitivity:+Theoretical+and+experimental+studies.">Linearization of the Bradford protein assay increases its sensitivity: Theoretical and experimental studies.</a> Analytical Biochemistry. 236 (2), 302-308 (1996).</li><li>Gee, C. T., Kehoe, E., Pomerantz, W. C. K., Penn, R. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantifying+protein+concentrations+using+smartphone+colorimetry:+A+new+method+for+an+established+test.">Quantifying protein concentrations using smartphone colorimetry: A new method for an established test.</a> Journal of Chemical Education. 94 (7), 941-945 (2017).</li><li>de Camargo, C., Vicentini, M., Gobbi, A., Martinez, D., Lima, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Smartphone+for+point-of-care+quantification+of+protein+by+Bradford+assay.">Smartphone for point-of-care quantification of protein by Bradford assay.</a> Journal of the Brazilian Chemical Society. 28 (4), 689-693 (2016).</li><li>Moreira, D. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=RGBradford:+Accurate+measurement+of+protein+concentration+using+a+smartphone+camera+and+the+blue+to+green+intensity+ratio.">RGBradford: Accurate measurement of protein concentration using a smartphone camera and the blue to green intensity ratio.</a> Analytical Biochemistry. 655, 114839 (2022).</li><li>Ernst, O., Zor, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Linearization+of+the+Bradford+Protein+Assay.">Linearization of the Bradford Protein Assay.</a> Journal of Visualized Experiments. (38), 1918 (2010).</li><li>Angelani, C. R., 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+metabolic+control+analysis+approach+to+introduce+the+study+of+systems+in+biochemistry:+the+glycolytic+pathway+in+the+red+blood+cell:+Metabolic+control+analysis+and+the+glycolytic+pathway.">A metabolic control analysis approach to introduce the study of systems in biochemistry: the glycolytic pathway in the red blood cell: Metabolic control analysis and the glycolytic pathway.</a> Biochemistry and Molecular Biology Education. 46 (5), 502-515 (2018).</li></ol>

作者没有利益冲突需要声明。

本文描述了RGBradford，这是一种使用智能手机摄像头记录来自Bradford蛋白质测定的数据，提取颜色数据并准确定量生物样品中的蛋白质水平的方法，如最近最初描述的那样20。与原始RGBradford方法的一个区别是，这里使用了使用ImageJ插件22 自动获取颜色数据的过程。RGBradford方法的主要新颖之处在于使用RGB数据作为分析信号;因此，人们可以使用实验室中使用的任何常规方案来测定考马斯亮蓝G的蛋白质，然后拍摄照片并提取颜色数据。换句话说，协议的步骤1-3可以根据给定实验室中使用的通常程序进行修改。鉴于原始 Bradford 蛋白测定存在多种修改，可以使用更适合其样品类型/性质的修改，然后进行数据记录。
该协议有两个关键步骤，图片捕获和颜色数据提取。在这里和之前的20个，不需要特殊的照明设备，并且获得了令人满意的结果（即，吸光度读数的结果与从图片中提取的颜色数据之间没有差异）。然而，人们可能会选择使用平台来优化图像采集，例如，使用透射仪19,22。主要问题是确保均匀的背景和照明。此外，使用不同的智能手机型号可以获得相同的结果。尽管每款手机获得的信号略有不同，但测试的四款智能手机机型（三星 S22 Ultra、苹果 iPhone 11、苹果 iPhone 14 Pro 和小米红米 Note 9 Pro）之间存在很强的相关性（皮尔逊的 r > 0.99）和显着的相关性（p < 0.0001）。从它们获得的信号与来自酶标仪的信号之间也存在显着相关性（补充图1）。在颜色数据提取的情况下，使用 ReadPlate 插件时必须小心，尤其是在网格检查步骤中，此时必须检查网格是否适合每个孔的位置。应确保网格圆不包括井壁或异常区域（例如，具有光反射的区域）。如果图片中的板不垂直于背景，则网格对齐可能特别困难，这将使正确绘制中心到中心的矩形井选择（从左上角到右下角）变得困难。
与传统的光谱读数相比，RGBradford方法的优点与其他使用智能手机而不是专用设备（例如酶标仪）的方法相同。智能手机随处可见，比分光光度计便宜，电池供电数小时，具有数据存储容量，并与其他设备进行无线和远程通信。总而言之，这些允许在偏远地区或非标准实验室条件下使用布拉德福德蛋白检测，例如护理点病房、教室、野外考察和资源匮乏的社区。然后，可以对捕获的图片进行进一步分析和解释。

无论下游用途如何（例如 ELISA、酶动力学、蛋白质印迹、蛋白质纯化和质谱），蛋白质定量对于生命科学实验室的准确分析都至关重要。除了用作辅助读数（即计算每质量蛋白质的分析物的相对水平）外，样品中的蛋白质水平本身也可以是所需的输出。例如，人们可能对食物资源1 或尿液2 中的蛋白质水平感兴趣。有许多方法可用于测量样品3中的蛋白质浓度，包括直接紫外吸光度读数4、蛋白质-铜螯合5,6、蛋白质-染料结合比色法7和蛋白质-染料结合荧光试验8。在引用次数最多的文献9,10的前三名中，有两篇描述蛋白质测量方法的论文5,7证明了蛋白质定量的相关性。尽管许多作者通过引用非主要参考文献或根本没有引用任何内容而忽略了他们的实际引用，但描述Lowry蛋白测定和Bradford蛋白测定的原始论文各有>200,000次引用10次。
Bradford 检测的受欢迎程度源于其经济性、简单性、速度和灵敏度。该测定基于蛋白质与染料考马斯亮蓝G在酸性条件下的相互作用。在测定条件下（即低pH值），染料以三种形式存在:红色阳离子形式，λmax为470nm;在650 nm处具有λmax的绿色中性形式;以及在590nm处λmax为11,12的蓝色阴离子形式（图1）。阳离子形式在没有蛋白质的情况下占主导地位。当蛋白质与染料相互作用时，它们会稳定蓝色阴离子形式，导致溶液颜色发生明显变化，从棕色变为蓝色。通常，通过分光光度法定量染料蓝色形式浓度的变化，其在590-595nm处的吸光度与测定中的蛋白质量成正比。
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/65547/65547fig01v2.jpg"> 图 1:Bradford 测定条件下的考马斯亮蓝 G 吸收光谱。 三个主峰用箭头标记，表示染料的红色（470 nm）、绿色（650 nm）和蓝色（590 nm）形式的λmax。在没有蛋白质（黄线）和存在 3 μg（灰线）和 10 μg（蓝线）牛血清白蛋白的情况下记录光谱。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65547/65547fig01large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
Bradford测定法的广泛使用导致了几个局限性的识别（例如，对不同蛋白质11的可变反应，以及脂质13和洗涤剂7的干扰）以及改进其性能的修饰（例如，添加洗涤剂14,15，碱化14,16和使用吸光度比率17).除了对测定本身的修改外，还描述了使用替代设备（例如智能手机或相机）来捕获分析信号18,19,20。事实上，利用智能手机作为便携式化学分析仪的方法的开发一直是一个活跃的研究领域。使用智能手机的动机源于这些设备的可负担性、便携性、易用性和广泛可用性。
本文提供了一种使用 RGBradford assay20 进行蛋白质定量的方案，该检测使用智能手机作为分析设备。与最初的 RGBradford 出版物20 相比，这里引入了简化颜色提取过程的程序。它涉及使用免费提供的软件应用程序从微孔板图片的每个孔中自动提取颜色信息，从而节省大量时间和精力。这是使用图形编辑器软件应用程序20从每个孔逐个手动获取颜色数据的先前方法的替代方法。最终，可以使用从智能手机拍摄的微孔板图片中提取的颜色数据来量化样品中的蛋白质水平。

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>96-well flat-bottom polystyrene microtiter plates&#160;</td>
			<td>Jet Biofil, Guangzhou, China</td>
			<td>TCP011096</td>
			<td>Any flat-bottom microplate compativle with optical reading will suffice.&#160;</td>
		</tr>
		<tr>
			<td>Bovine serum albumin</td>
			<td>Sigma-Aldrich, St. Louis, MO</td>
			<td>A2153</td>
			<td></td>
		</tr>
		<tr>
			<td>Coomassie Brilliant Blue G</td>
			<td>Sigma-Aldrich, St. Louis, MO</td>
			<td>B0770</td>
			<td></td>
		</tr>
		<tr>
			<td>Ethyl alcohol</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>iPhone 11</td>
			<td>Apple</td>
			<td>MWM02BR/A</td>
			<td>Can be substituted with other smartphone equiped with a camera</td>
		</tr>
		<tr>
			<td>iPhone 14 Pro</td>
			<td>Apple</td>
			<td>N/A</td>
			<td></td>
		</tr>
		<tr>
			<td>Phosphoric acid</td>
			<td>Sigma-Aldrich, St. Louis, MO</td>
			<td>695017</td>
			<td></td>
		</tr>
		<tr>
			<td>Redmi Note 9 Pro</td>
			<td>XIAOMI&#160;</td>
			<td>N/A</td>
			<td></td>
		</tr>
		<tr>
			<td>S22 Ultra</td>
			<td>Samsung&#160;</td>
			<td>N/A</td>
			<td></td>
		</tr>
		<tr>
			<td>SpectraMax 384 Plus. Microplate reader.</td>
			<td>Molecular Devices, San Jose, CA</td>
			<td>PLUS 384</td>
			<td>Any microplate reader capable of reading at 450 nm and 590 nm will work. This is optional. The method was actually created to dismiss the need of a microplate reader.</td>
		</tr>
	</tbody>
</table>

rgbradford: protein quantitation with a smartphone camera

蛋白质定量是生命科学研究中必不可少的程序。在其他几种方法中，布拉德福德测定法是最常用的方法之一。由于其广泛应用，Bradford测定法的局限性和优点已被详尽报道，包括对原始方法的多次修改以提高其性能。原始方法的改变之一是使用智能手机相机作为分析仪器。利用Bradford测定条件下存在的三种形式的考马斯亮蓝染料，本文描述了如何使用从单张微孔板图片中提取的颜色数据准确定量样品中的蛋白质。在微孔板中进行测定后，使用智能手机相机拍摄照片，并使用免费的开源图像分析软件应用程序从图片中提取RGB颜色数据。然后，使用未知蛋白质浓度样品的蓝色与绿色强度之比（在RGB标度中）基于标准曲线计算蛋白质含量。使用RGB颜色数据计算的值与使用常规吸光度数据计算的值之间没有显著差异。

图4是微孔板的图片，从中提取颜色数据，并记录了450nm和590nm处的吸光度。此处报告的代表性 RGB 颜色数据是自动获取的，如第 5 节所述。颜色数据的典型模式是蓝色值的增加和红色和绿色值的减少（图 5）。请注意，尽管所有孔中都有明显的反射，并且微孔板未完全对齐（图4），但从图片中提取的颜色数据准确地反映了吸光度读数（图6）。对于吸光度读数和颜色数据，样品稀释度和信号之间也存在线性关系（图7）。对于这些代表性结果，使用了两个样品，BV-2细胞裂解物（B001）和如前所述的 美洛氏菌 匀浆物（G001）20，其中每个孔使用0.5μL，1μL，2μL，4μL和8μL。在加入 250 μL Bradford 试剂之前，用缓冲液将体积调节至 10 μL。
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/65547/65547fig04v2.jpg"> 图 4:Bradford 检测微孔板的代表性图片。 注意每个孔上的灯反射和孔的错位（即板的右侧向下倾斜）。这些应尽可能减少，但不需要完美的对齐和照明（参见代表性结果）。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65547/65547fig04large.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/65547/65547fig05v2.jpg"> 图 5:三个 RGB 通道的颜色强度与蛋白质浓度的关系。 每个点代表微孔板中标准曲线的一个孔，如 图4所示。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65547/65547fig05large.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/65547/65547fig06v2.jpg"> 图 6:从图片中提取的吸光度读数与 RGB 颜色数据 的关系 。 每个点代表微孔板中标准曲线的一个孔，如 图4所示。黄色阴影表示 95% 置信区间。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65547/65547fig06large.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/65547/65547fig07v2.jpg"> 图 7:信号强度 与 样品体积的关系。 色谱柱是来自不同方法的不同信号:吸光度读数（吸光度）和提取的RGB颜色数据（RGB数据）。行是不同的样品:BV-2 细胞裂解物 （B001） 和 Galleria mellonella 匀浆物 （G001）。每个点是给定样品体积的三个孔的平均值。黄色阴影表示 95% 置信区间。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65547/65547fig07large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
标准曲线（信号 与 BSA浓度）应严格线性，如BSA浓度为0.025 mg/mL、0.05 mg/mL、0.1 mg/mL、0.2 mg/mL、0.4 mg/mL、0.6 mg/mL、0.8 mg/mL和1.0 mg/mL的代表性标准曲线所示（图8）。
<img alt="Figure 8" class="xfigimg" src="/files/ftp_upload/65547/65547fig08v2.jpg"> 图 8:典型的标准曲线，说明了蓝绿比与牛血清白蛋白 （BSA） 浓度的线性关系。 用于典型标准曲线的浓度为 0 mg/mL、0.025 mg/mL、0.05 mg/mL、0.1 mg/mL、0.2 mg/mL、0.4 mg/mL、0.6 mg/mL、0.8 mg/mL 和 1.0 mg/mL。每个点是每个 BSA 浓度的三个孔的平均值。误差线表示标准差。黄色阴影表示 95% 置信区间。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65547/65547fig08large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
在这个代表性结果的例子中，一些稀释度不在标准曲线的线性范围内（图9）。对于样品 B001,8 μL 的信号高于标准曲线的最高点。在 G001 的情况下，0.5 μL 和 1 μL 导致信号低于标准曲线的最低点。对于这两种样品，应丢弃这些位于标准曲线线性范围之外的稀释液。在忽略标准曲线范围之外的读数后，使用吸光度读数计算的蛋白质水平与使用两种样品的RGB数据计算的蛋白质水平没有差异（图10）。使用 t 检验比较吸光度数据和RGB数据，结果为样品B001的p = 0.63，样品G001的p = 0.17。
<img alt="Figure 9" class="xfigimg" src="/files/ftp_upload/65547/65547fig09v2.jpg"> 图 9:使用 RGBradford 方法 获得的蓝 绿比与样品体积的关系。 水平线划定了标准曲线的最小和最大蓝绿比（图8）。蓝色圆圈表示 BV-2 细胞裂解物 （B001），红色符号表示 Galleria mellonella 匀浆物 （G001）。误差线表示标准差。请注意，某些样品稀释度超出了标准曲线的范围。黄色阴影表示 95% 置信区间。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65547/65547fig09large.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/65547/65547fig10v2.jpg"> 图 10:使用常规吸光度读数 （ABS） 和 RGBradford 方法 （RGB） 通过 Bradford 蛋白质测定定量的两个生物样品中的蛋白质浓度。 蓝色符号表示 BV-2 细胞裂解物 （B001），红色符号表示 Galleria mellonella 匀浆物 （G001）。每个圆圈代表从中获取数据的单个孔。菱形表示平均值，垂直线从每个样品/方法的最小值到最大值。方法之间没有差异（B001，t检验，p = 0.63;G001，t 检验，p = 0.17）。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65547/65547fig10large.jpg" target="_blank">请点击这里查看此图的较大版本.</a>
补充图1:使用不同智能手机获得的信号。 使用不同智能手机型号获得的信号（蓝绿比）和 Spectramax iD3 酶标仪获得的信号 （A590/A450） 的 Pearson 相关系数。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/65547/65547_Supplementary%20Figure%201.pdf" target="_blank">请点击此处下载此文件。</a>

Watch this Scientific Journal Video about An Alternative Approach to Protein Quantification by Bradford Assay Using a Smartphone at JoVE.com

作者聚焦:使用智能手机通过 Bradford 分析进行蛋白质定量的另一种方法 

本文提供了一种使用 Bradford 测定法和智能手机作为分析设备进行蛋白质定量的方案。样品中的蛋白质水平可以使用从智能手机拍摄的微孔板图片中提取的颜色数据进行量化。

RGBradford:使用智能手机相机进行蛋白质定量

Protein quantitation is an essential procedure in life sciences research. Amongst several other methods, the Bradford assay is one of the most used. ...

我们的研究重点是在生化水平上了解动物如何适应极端环境条件。我们探讨了它们对缺氧和抑制代谢率的反应问题。具体来说，我们研究了动物在不利环境中使用的内源性抗氧化剂、氧化应激和细胞应激反应。为此，我们经常量化样品中的蛋白质水平。该协议解决了在资源有限的情况下获得蛋白质定量数据的替代方法的需求，使其成为教育和研究环境中的宝贵工具。RG Bradford 检测试剂盒为蛋白质浓度测量提供了一种实用且可靠的解决方案，在无法使用酶标仪等传统设备的情况下，该解决方案易于访问、简单且准确。

rgbradford-protein-quantitation-with-a-smartphone-camera

Nanyang Technological University

Research

JoVE Journal

Biochemistry

RGBradford: Protein Quantitation with a Smartphone Camera

2.7K 次观看.  University of Brasilia. 我们的研究重点是在生化水平上了解动物如何适应极端环境条件。我们探讨了它们对缺氧和抑制代谢率的反应问题。具体来说，我们研究了动物在不利环境中使用的内源性抗氧化剂、氧化应激和细胞应激反应。为此，我们经常量化样品中的蛋白质水平。该协议解决了在资源有限的情况下获得蛋白质定量数据的替代方法的需求，使其成为教育和研究环境中的宝贵工具。RG B...

视频: 作者聚焦:使用智能手机通过 Bradford 分析进行蛋白质定量的另一种方法 

Fluorescence Anisotropy as a Tool to Study Protein-protein Interactions

Protein-protein interactions play an essential role in the function of a living organism. Once an interaction has been identified and validated it is necessary to characterize it at the structural and mechanistic level. Several biochemical and biophysical methods exist for such purpose. Among them, fluorescence anisotropy is a powerful technique particularly used when the fluorescence intensity of a fluorophore-labeled protein remains constant upon protein-protein interaction. In this technique, a fluorophore-labeled protein is excited with vertically polarized light of an appropriate wavelength that selectively excites a subset of the fluorophores according to their relative orientation with the incoming beam. The resulting emission also has a directionality whose relationship in the vertical and horizontal planes defines anisotropy (r) as follows: r=(IVV-IVH)/(IVV+2IVH), where IVV and IVH are the fluorescence intensities of the vertical and horizontal components, respectively. Fluorescence anisotropy is sensitive to the rotational diffusion of a fluorophore, namely the apparent molecular size of a fluorophore attached to a protein, which is altered upon protein-protein interaction. In the present text, the use of fluorescence anisotropy as a tool to study protein-protein interactions was exemplified to address the binding between the protein mutated in the Shwachman-Diamond Syndrome (SBDS) and the Elongation factor like-1 GTPase (EFL1). Conventionally, labeling of a protein with a fluorophore is carried out on the thiol groups (cysteine) or in the amino groups (the N-terminal amine or lysine) of the protein. However, SBDS possesses several cysteines and lysines that did not allow site directed labeling of it. As an alternative technique, the dye 4&#39;,5&#39;-bis(1,3,2 dithioarsolan-2-yl) fluorescein was used to specifically label a tetracysteine motif, Cys-Cys-Pro-Gly-Cys-Cys, genetically engineered in the C-terminus of the recombinant SBDS protein. Fitting of the experimental data provided quantitative and mechanistic information on the binding mode between these proteins.

Protein interactions are at the heart of a cell&#39;s function. Calorimetric and spectroscopic techniques are commonly used to characterize them. Here we describe fluorescence anisotropy as a tool to study the interaction between the protein mutated in the Shwachman-Diamond Syndrome (SBDS) and the Elongation factor-like 1 GTPase (EFL1).

荧光各向异性作为一种工具来研究蛋白质相互作用

Protein-protein interactions play an essential role in the function of a living organism. Once an interaction has been identified and validated it is ...

科研

生物化学

Using Scaffold Liposomes to Reconstitute Lipid-proximal Protein-protein Interactions In Vitro

Studies of integral membrane proteins in vitro are frequently complicated by the presence of a hydrophobic transmembrane domain. Further complicating these studies, reincorporation of detergent-solubilized membrane proteins into liposomes is a stochastic process where protein topology is impossible to enforce. This paper offers an alternative method to these challenging techniques that utilizes a liposome-based scaffold. Protein solubility is enhanced by deletion of the transmembrane domain, and these amino acids are replaced with a tethering moiety, such as a His-tag. This tether interacts with an anchoring group (Ni2+ coordinated by nitrilotriacetic acid (NTA(Ni2+)) for His-tagged proteins), which enforces a uniform protein topology at the surface of the liposome. An example is presented wherein the interaction between Dynamin-related protein 1 (Drp1) with an integral membrane protein, Mitochondrial Fission Factor (Mff), was investigated using this scaffold liposome method. In this work, we have demonstrated the ability of Mff to efficiently recruit soluble Drp1 to the surface of liposomes, which stimulated its GTPase activity. Moreover, Drp1 was able to tubulate the Mff-decorated lipid template in the presence of specific lipids. This example demonstrates the effectiveness of scaffold liposomes using structural and functional assays and highlights the role of Mff in regulating Drp1 activity.

Using Scaffold Liposomes to Reconstitute Lipid-proximal Protein-protein Interactions In Vitro

This paper describes a method for assessing the interactions and assemblies of integral membrane proteins in vitro with various partner factors in a lipid-proximal environment.

使用脚手架脂质体重构脂质近端蛋白质 - 蛋白质相互作用<em&gt;体外</em

Studies of integral membrane proteins in vitro are frequently complicated by the presence of a hydrophobic transmembrane domain. Further complicating ...

Assaying Protein Kinase Activity with Radiolabeled ATP

Protein kinases are able to govern large-scale cellular changes in response to complex arrays of stimuli, and much effort has been directed at uncovering allosteric details of their regulation. Kinases comprise signaling networks whose defects are often hallmarks of multiple forms of cancer and related diseases, making an assay platform amenable to manipulation of upstream regulatory factors and validation of reaction requirements critical in the search for improved therapeutics. Here, we describe a basic kinase assay that can be easily adapted to suit specific experimental questions including but not limited to testing the effects of biochemical and pharmacological agents, genetic manipulations such as mutation and deletion, as well as cell culture conditions and treatments to probe cell signaling mechanisms. This assay utilizes radiolabeled [&#947;-32P] ATP, which allows for quantitative comparisons and clear visualization of results, and can be modified for use with immunoprecipitated or recombinant kinase, specific or typified substrates, all over a wide range of reaction conditions.

Protein kinases are highly evolved signaling enzymes and scaffolds that are critical for inter- and intracellular signal transduction. We present a protocol for measuring kinase activity through the use of radiolabeled adenosine triphosphate ([&#947;-32P] ATP), a reliable method to aid in elucidation of cellular signaling regulation.

用放射性标记的ATP测定蛋白激酶活性

Protein kinases are able to govern large-scale cellular changes in response to complex arrays of stimuli, and much effort has been directed at uncovering ...

Investigating Protein Sequence-structure-dynamics Relationships with Bio3D-web

We demonstrate the usage of Bio3D-web for the interactive analysis of biomolecular structure data. The Bio3D-web application provides online functionality for: (1) The identification of related protein structure sets to user specified thresholds of similarity; (2) Their multiple alignment and structure superposition; (3) Sequence and structure conservation analysis; (4) Inter-conformer relationship mapping with principal component analysis, and (5) comparison of predicted internal dynamics via ensemble normal mode analysis. This integrated functionality provides a complete online workflow for investigating sequence-structure-dynamic relationships within protein families and superfamilies.

A protocol for the online investigation of protein sequence-structure-dynamics relationships using Bio3D-web is presented.

研究与Bio3D-web的蛋白质序列 - 结构 - 动力学关系

We demonstrate the usage of Bio3D-web for the interactive analysis of biomolecular structure data. The Bio3D-web application provides online functionality ...

Real-time Tracking of DNA Fragment Separation by Smartphone

Slab gel electrophoresis (SGE) is the most common method for the separation of DNA fragments; thus, it is broadly applied to the field of biology and others. However, the traditional SGE protocol is quite tedious, and the experiment takes a long time. Moreover, the chemical consumption in SGE experiments is very high. This work proposes a simple method for the separation of DNA fragments based on an SGE chip. The chip is made by an engraving machine. Two plastic sheets are used for the excitation and emission wavelengths of the optical signal. The fluorescence signal of the DNA bands is collected by smartphone. To validate this method, 50, 100, and 1,000 bp DNA ladders were separated. The results demonstrate that a DNA ladder smaller than 5,000 bp can be resolved within 12 min and with high resolution when using this method, indicating that it is an ideal substitute for the traditional SGE method.

Traditional slab gel electrophoresis (SGE) experiments require a complicated apparatus and high chemical consumption. This work presents a protocol that describes a low-cost method to separate DNA fragments within a short timeframe.

通过智能手机实时跟踪DNA片段分离

Slab gel electrophoresis (SGE) is the most common method for the separation of DNA fragments; thus, it is broadly applied to the field of biology and ...

A Yeast 2-Hybrid Screen in Batch to Compare Protein Interactions

Screening for protein-protein interactions using the yeast 2-hybrid assay has long been an effective tool, but its use has largely been limited to the discovery of high-affinity interactors that are highly enriched in the library of interacting candidates. In a traditional format, the yeast 2-hybrid assay can yield too many colonies to analyze when conducted at low stringency where low affinity interactors might be found. Moreover, without a comprehensive and complete interrogation of the same library against different bait plasmids, a comparative analysis cannot be achieved. Although some of these problems can be addressed using arrayed prey libraries, the cost and infrastructure required to operate such screens can be prohibitive. As an alternative, we have adapted the yeast 2-hybrid assay to simultaneously uncover dozens of transient and static protein interactions within a single screen utilizing a strategy termed DEEPN (Dynamic Enrichment for Evaluation of Protein Networks), which incorporates high-throughput DNA sequencing and computation to follow the evolution of a population of plasmids that encode interacting partners. Here, we describe customized reagents and protocols that allow a DEEPN screen to be executed easily and cost-effectively.

Batch processing of yeast 2-hybrid screens allows for direct comparison of the interaction profiles of multiple bait proteins with a highly complex set of prey fusion proteins. Here, we describe refined methods, new reagents, and how to implement their use for such screens.

酵母 2-混合筛在批次中比较蛋白质相互作用

Screening for protein-protein interactions using the yeast 2-hybrid assay has long been an effective tool, but its use has largely been limited to the ...

High Sensitivity Measurement of Transcription Factor-DNA Binding Affinities by Competitive Titration Using Fluorescence Microscopy

Accurate quantification of transcription factor (TF)-DNA interactions is essential for understanding the regulation of gene expression. Since existing approaches suffer from significant limitations, we have developed a new method for determining TF-DNA binding affinities with high sensitivity on a large scale. The assay relies on the established fluorescence anisotropy (FA) principle but introduces important technical improvements. First, we measure a full FA competitive titration curve in a single well by incorporating TF and a fluorescently labeled reference DNA in a porous agarose gel matrix. Unlabeled DNA oligomer is loaded on the top as a competitor and, through diffusion, forms a spatio-temporal gradient. The resulting FA gradient is then read out using a customized epifluorescence microscope setup. This improved setup greatly increases the sensitivity of FA signal detection, allowing both weak and strong binding to be reliably quantified, even for molecules of similar molecular weights. In this fashion, we can measure one titration curve per well of a multi-well plate, and through a fitting procedure, we can extract both the absolute dissociation constant (KD) and active protein concentration. By testing all single-point mutation variants of a given consensus binding sequence, we can survey the entire binding specificity landscape of a TF, typically on a single plate. The resulting position weight matrices (PWMs) outperform those derived from other methods in predicting in vivo TF occupancy. Here, we present a detailed guide for implementing HiP-FA on a conventional automated fluorescent microscope and the data analysis pipeline.

Here we present a novel method for determining binding affinities at equilibrium and in solution with high sensitivity on a large scale. This improves the quantitative analysis of transcription factor-DNA binding. The method is based on automated fluorescence anisotropy measurements in a controlled delivery system.

荧光显微镜竞争滴定法测定转录机-dna 结合感的高灵敏度

Accurate quantification of transcription factor (TF)-DNA interactions is essential for understanding the regulation of gene expression. Since existing ...

Analysis of Protein Folding, Transport, and Degradation in Living Cells by Radioactive Pulse Chase

Radioactive pulse-chase labeling is a powerful tool for studying the conformational maturation, the transport to their functional cellular location, and the degradation of target proteins in live cells. By using short (pulse) radiolabeling times (&lt;30 min) and tightly controlled chase times, it is possible to label only a small fraction of the total protein pool and follow its folding. When combined with nonreducing/reducing SDS-polyacrylamide gel electrophoresis (SDS-PAGE) and immunoprecipitation with (conformation-specific) antibodies, folding processes can be examined in great detail. This system has been used to analyze the folding of proteins with a huge variation in properties such as soluble proteins, single and multi-pass transmembrane proteins, heavily N- and O-glycosylated proteins, and proteins with and without extensive disulfide bonding. Pulse-chase methods are the basis of kinetic studies into a range of additional features, including co- and posttranslational modifications, oligomerization, and polymerization, essentially allowing the analysis of a protein from birth to death. Pulse-chase studies on protein folding are complementary with other biochemical and biophysical methods for studying proteins in vitro by providing increased temporal resolution and physiological information. The methods as described within this paper are adapted easily to study the folding of almost any protein that can be expressed in mammalian or insect-cell systems.

Here we describe a protocol for a general pulse-chase method that allows the kinetic analysis of folding, transport, and degradation of proteins to be followed in live cells.

放射性脉冲追逐对活细胞蛋白质折叠、迁移和降解的分析

Radioactive pulse-chase labeling is a powerful tool for studying the conformational maturation, the transport to their functional cellular location, and ...

Detection of Protein Ubiquitination Sites by Peptide Enrichment and Mass Spectrometry

The posttranslational modification of proteins by the small protein ubiquitin is involved in many cellular events. After tryptic digestion of ubiquitinated proteins, peptides with a diglycine remnant conjugated to the epsilon amino group of lysine (&#39;K-&#949;-diglycine&#39; or simply &#39;diGly&#39;) can be used to track back the original modification site. Efficient immunopurification of diGly peptides combined with sensitive detection by mass spectrometry has resulted in a huge increase in the number of ubiquitination sites identified up to date. We have made several improvements to this workflow, including offline high pH reverse-phase fractionation of peptides prior to the enrichment procedure, and the inclusion of more advanced peptide fragmentation settings in the ion routing multipole. Also, more efficient cleanup of the sample using a filter-based plug in order to retain the antibody beads results in a greater specificity for diGly peptides. These improvements result in the routine detection of more than 23,000 diGly peptides from human cervical cancer cells (HeLa) cell lysates upon proteasome inhibition in the cell. We show the efficacy of this strategy for in-depth analysis of the ubiquitinome profiles of several different cell types and of in vivo samples, such as brain tissue. This study presents an original addition to the toolbox for protein ubiquitination analysis to uncover the deep cellular ubiquitinome.

We present a method for the purification, detection, and identification of diGly peptides that originate from ubiquitinated proteins from complex biological samples. The presented method is reproducible, robust, and outperforms published methods with respect to the level of depth of the ubiquitinome analysis.

通过肽浓缩和质谱检测蛋白质泛化位点检测

The posttranslational modification of proteins by the small protein ubiquitin is involved in many cellular events. After tryptic digestion of ...

Creating Highly Specific Chemically Induced Protein Dimerization Systems by Stepwise Phage Selection of a Combinatorial Single-Domain Antibody Library

Protein dimerization events that occur only in the presence of a small-molecule ligand enable the development of small-molecule biosensors for the dissection and manipulation of biological pathways. Currently, only a limited number of chemically induced dimerization (CID) systems exist and engineering new ones with desired sensitivity and selectivity for specific small-molecule ligands remains a challenge in the field of protein engineering. We here describe a high throughput screening method, combinatorial binders-enabled selection of CID (COMBINES-CID), for the de novo engineering of CID systems applicable to a large variety of ligands. This method uses the two-step selection of a phage-displayed combinatorial nanobody library to obtain 1) &#34;anchor binders&#34; that first bind to a ligand of interest and then 2) &#34;dimerization binders&#34; that only bind to anchor binder-ligand complexes. To select anchor binders, a combinatorial library of over 109 complementarity-determining region (CDR)-randomized nanobodies is screened with a biotinylated ligand and hits are validated with the unlabeled ligand by bio-layer interferometry (BLI). To obtain dimerization binders, the nanobody library is screened with anchor binder-ligand complexes as targets for positive screening and the unbound anchor binders for negative screening. COMBINES-CID is broadly applicable to select CID binders with other immunoglobulin, non-immunoglobulin, or computationally designed scaffolds to create biosensors for in vitro and in vivo detection of drugs, metabolites, signaling molecules, etc.

Creating chemically induced protein dimerization systems with desired affinity and specificity for any given small molecule ligand would have many biological sensing and actuation applications. Here, we describe an efficient, generalizable method for de novo engineering of chemically induced dimerization systems via the stepwise selection of a phage-displayed combinatorial single-domain antibody library.

RGBradford:使用智能手机相机进行蛋白质定量

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