Name: quantitative localization of a golgi protein by imaging its center of fluorescence mass
Uploaded: 2017-08-10T13:00:00.000+00:00
Duration: 13 min 8 s
Description: Watch this Scientific Journal Video about Quantitative Localization of a Golgi Protein by Imaging Its Center of Fluorescence Mass at JoVE.com

我们要感谢 d. 斯蒂芬斯 (布里斯托尔大学, 布里斯托尔, 英国) 的 TPST1-EGFP DNA 质粒, 以及纳史木汗戈文达拉扬为帮助软件优化。这项工作得到了国家医学研究理事会 (NMRC/CBRG/007/2012)、教育部 (AcRF Tier1 rg 18/11、rg 48/13 和 RG132/15 和 AcRF Tier2 MOE2015-T2-2-073) 的资助, 以法学

注: 下面是 GLIM 的 step-by 步协议, 用于确定 EGFP 标记的 tyrosylprotein 3-o 1 (TPST1) 的 LQ, 在 HeLa 细胞中是高尔基体的驻留酶。
1. 荧光标记高尔基体微型叠的制备
<ol><li>
准备玻璃片
	<ol>
<li>分0.3 毫升无菌 Dulbecco 改良鹰的培养基 (DMEM) 到一个24井板在一个组织培养罩的井。</li>
		<li>将Φ 12 mm no. 1.5 玻璃片用用70% 乙醇轻擦的软组织纸擦拭, 去除玻璃表面的碎片片。用一双锋利的镊子简单地浸泡在70% 乙醇中的片, 将其转移到24井板中, 并将其沉入含有无菌 DMEM 的井底。 注: 玻璃片被燃烧的常规消毒。然而, 片在这种处理下容易破裂在随后处理。70% 乙醇浸泡对玻璃片灭菌效果良好, 无损伤。</li>
		<li>盖上盖子, 离开24井板在37° c CO2孵化器直到使用。</li>
	</ol>
</li>
	<li>
种子细胞
	<ol>
<li>培养 HeLa 细胞 (以下细胞) 在 T-25 烧瓶中的 DMEM 补充10% 胎牛血清 (FBS) (以下完整培养基) 在一个37° c co2孵化器提供 5% co2。这里不需要抗生素。</li>
		<li>当细胞达到〜 80% 70-100, 吸取培养基。在烧瓶中加入1毫升的0.25% 胰蛋白酶-EDTA, 并在37° c CO2孵化器中孵育细胞2分钟. 将1毫升的完整培养基放入烧瓶中, 然后用移轻轻冲洗瓶壁上的细胞。</li>
		<li>将分离的细胞转移到一个不育的离心管中, 在 500 x g 上旋转2分钟以使细胞颗粒。在1毫升完全培养基中, 吸取上清和悬浮细胞颗粒。</li>
		<li>在井中吸出含有灭菌玻璃片和种子 ~ 1 x 105细胞的24井板井中的培养基。用完整的培养基到0.5 毫升的井容量。孵育在一个37° c co2孵化器提供 5% co2。培养细胞到〜 80% 70-100。</li>
	</ol>
</li>
	<li>
染细胞 注: 良好的扩散细胞有利于成像分散的高尔基 mini-stacks。<ol>
<li>染 ~ 80% 汇合细胞与 80 ng mCherry7和 320 ng TPST1-EGFP (参见材料目录) 脱氧核糖核酸质粒使用转染试剂根据制造商提供的协议。孵育在一个37° c CO2孵化器。4-6 h 潜伏期后改变培养基。细胞准备好了 ~ 12 小时后</li>
	</ol>
</li>
	<li>
Nocodazole 治疗产生高尔基体 mini-stacks
	<ol>
<li>在1毫升二甲基亚砜中溶解10毫克 nocodazole 粉末, 制备 nocodazole 的溶液 (33 毫米)。分库存解决方案和存储在-20 ° c 的长期存储。</li>
		<li>稀释1µL nocodazole 溶液 (33 毫米) 在1毫升37° c 完全介质 (最终浓度33µM)。离心机在最高速度, 以消除颗粒物质。</li>
		<li>在井中吸入培养基, 加入0.5 毫升的33µM nocodazole 含有完整培养基。孵育37° c CO2孵化器中的细胞 3 h. 进行免疫荧光标记 (1.5 节)。</li>
	</ol>
</li>
	<li>
免疫荧光标记 注意: 保持细胞在黑暗中避免漂白 mCherry 和 TPST1-EGFP。<ol>
<li>
制备免疫荧光标记试剂
		<ol>
<li>准备4% 甲醛溶液, 溶解 4% (w/v) 甲醛粉末在热1X 磷酸盐缓冲盐水 (PBS) 和过滤解决方案通过0.45 µm 过滤器。溶液可贮存在-20 ° c。 注意: 甲醛是有毒和致癌的, 它会引起皮肤刺激。穿戴适当的个人防护设备 (PPE)。</li>
			<li>在 1x PBS 中制备荧光稀释缓冲液 (FDB), 混合 5% (v/v) FBS 和 2% (含五) 牛血清白蛋白 (BSA)。通过0.45 µm 过滤器过滤解决方案, 并将解决方案存储在-20 ° c。</li>
			<li>在1升水中溶解5.35 克 nh4cl 粉末, 以准备 100 mM nh4cl, 并在室温下存储该溶液。</li>
			<li>在水中溶解 10% (含钒) 皂苷粉, 制备10% 皂素, 分, 并在-20 ° c 贮存溶液。</li>
		</ol>
</li>
		<li>
固定
		<ol>
<li>冲洗井一次与0.5 毫升 1x PBS 解决方案, 并添加0.5 毫升4% 甲醛解决方案。室温孵育20分钟。冲洗井两次与0.5 毫升 1x pbs 和两次与0.5 毫升 100 mM NH4Cl. 冲洗两次与0.5 毫升 1x pbs。细胞可在4° c 的 1x PBS 在黑暗中过夜。</li>
		</ol>
</li>
		<li>
荧光标记
		<ol>
<li>在500µL FDB 中稀释1µL 小鼠 anti-GM130 主抗体, 含有0.1% 的皂苷。翻转24井板的盖子, 并在盖子上应用10µL 主抗体混合物。</li>
			<li>用一双锋利的镊子将玻璃片到抗体混合物的下落, 确保细胞侧与混合物接触。在室温下, 用主抗体混合物孵育1小时的细胞。 注: 与片的盖子可以放在一个湿的塑料袋在黑暗中。</li>
			<li>使用一对锋利的镊子提取和转移片到井与细胞侧向上和冲洗它在0.5 毫升 1x PBS 三次在≥ 30 min. 摇晃是不必要的。</li>
			<li>稀释1µL 荧光共轭山羊 anti-mouse IgG (二次抗体) 在500µL FDB 中含有0.1% 的皂甙。</li>
			<li>清洗和清洁24井板盖的背面。在盖子上应用10µL 远红色二级抗体混合物。重复步骤 1.5.3.2-1.5.3.3。</li>
		</ol>
</li>
		<li>
安装
		<ol>
<li>通过混合1克甘油, 2.2 克聚 (乙烯醇) (兆瓦〜 3.1万 Da), 1.2 毫升 1 M 三 (pH 8) 和8.8 毫升 H2o 在60° c 水浴中溶解混合物, 偶尔涡流。将解决方案存储在-20 ° c。</li>
			<li>将安装介质解冻, 并将10µL 转到玻璃滑梯上。将片 (单元侧向下) 叠加到安装介质的下落上。将玻璃玻片在37° c 下孵育30分钟或室温1小时, 以硬化安装介质。用无色指甲油封住片, 在-20 ° c 的时候将玻片储存起来。</li>
		</ol>
</li>
	</ol>
</li>
</ol>2. 用于色移校正的荧光微珠的制备
<ol><li>
片清洗
	<ol>
<li>小心地将一块25毫米 no. 1.5 玻璃片放在塑料架上。</li>
		<li>将机架与片到一个400毫升的烧杯中, 用300毫升1米的氢氧化钠和几种在浴缸 sonicator (35 瓦特) 中进行15分钟的清洗, 用400毫升去离子水冲洗一个300毫升烧杯中的机架。将机架转到400毫升的烧杯中, 300 毫升99% 乙醇和几种在浴 sonicator 中, 15 分钟用400毫升去离子水冲洗货架。</li>
		<li>重复步骤2.1.2 两次。</li>
		<li>用300毫升去离子水在400毫升的烧杯中用片冲洗机架10分钟. 重复两次步骤。将机架转至60° c 烘箱, 干燥片1小时, 将干燥的片在无尘培养皿中贮存。</li>
	</ol>
</li>
	<li>
玻璃片上的荧光珠固定
	<ol>
<li>稀释 110 nm 多色荧光珠80倍, 在 1x PBS 含有0.1 µg/µL BSA。简要地涡流管分散珠团聚体。将60µL 稀释的珠子涂在清洗过的Φ 25 mm no. 1.5 玻璃片上 (见第2.1 节) 使用吸管尖端。干燥片在一个干燥连接到一个真空泵在黑暗中, 并安装在50µL 安装媒体的玻璃幻灯片 (见步骤 1.5.4.2) 的片。</li>
	</ol>
</li>
</ol>3. 图像采集
注: GLIM 需要高信噪比 (SNR) 的高精度质心计算图像。该图像可由传统的显微镜, 如激光扫描共焦, 旋转圆盘共聚焦或广域显微镜。可使用具有计划物镜物镜和低噪声图像传感器 (如电荷耦合器件 (CCD) 和科学互补金属氧化物半导体 (sCMOS)) 的广域显微镜。对图像传感器的参数进行了调整, 以确保低读噪声和高动态范围。该显微镜必须配有绿色、mCherry 和远红荧光的荧光过滤器的最佳配置, 并且必须有可忽略的荧光相声。理想情况下, 成像系统在 x、y 和 z 轴上实现奈奎斯特采样率, 这通常要求像素的 x、y 和 z 大小分别小于100、100和 200 nm。体素的 x 和 y 大小总是相等的, 被称为 pixel_size。pixel_size 可以通过将相机传感器大小除以系统放大率来计算。
<ol><li>
图像多色珠
	<ol>
<li>图像多色珠在绿色, 红色和远红色的渠道在开始和每一个影像会议结束。 注: 在这里, 图像是通过一个传统的广域 epi 荧光显微镜 (倒置), 配备 100X NA 1.4 计划-物镜目标, 机动阶段, 200 瓦特金属卤化物光源和16位 sCMOS 相机。绿色通道过滤器立方体的励磁滤波器 (带通)、分色镜 (长传球) 和发射滤波器 (带通) 的波长为 465-495、505和 515-555 nm;那些为红色渠道过滤器立方体是 528-553, 565 和 578-633 毫微米;并且那些为远的红色渠道过滤器立方体是 590-650, 660 和 663-738 毫微米。在获取过程中, 沿 x、y 和 z 轴的体素大小分别为64、64和 200 nm。</li>
		<li>找到一个视野良好的珠密度。</li>
		<li>获取绿色、红色和远红色通道中的3D 图像堆栈 (通道G、通道R、通道B分别)。在最佳焦平面上方和下方3节 (每栈7节)。将三堆栈保存为三 TIFF 文件。 注意: 每个通道的曝光时间是根据经验确定的, 以最大化动态范围, 避免像素饱和和最小化漂白。其他参数, 如滤镜和体素的 x、y 和 z 大小, 都是在上面所讨论的选择。</li>
	</ol>
</li>
	<li>
图像高尔基 mini-stacks
	<ol>
<li>使用 TPST1-EGFP 和高尔特-mCherry 转染和荧光标记 (1.5 节) 的幻灯片, 以找到表达 TPST1-EGFP 和低或中级高级别 mCherry 的细胞。获取3D 图像堆栈, 如步骤3.1.3 中所述。</li>
	</ol>
</li>
</ol>4. 图像分析
<ol><li>获取荧光珠的中心
	<ol>
<li>在 ImageJ 中, 打开一组由三 TIFF 文件 (文件 > 图像 > 打开) 组成的珠子图像。</li>
		<li>通过图像 > 堆栈 > Z 项目, 在通道R中的最佳聚焦截面上平均连续3节。输入 "开始切片" 和 "停止切片" 的节数, 并在 "投影类型" 的选项中选择 "平均强度"。</li>
		<li>使用 "多边形选择" 绘制图像中不含珠子的感兴趣区域 (roi)。在 "分析 > 设置测量" 中, 只检查 "平均灰度值" 和 "标准偏差"。然后执行 "分析 > 测量" 以获得 ROI 的平均值和 SD。</li>
		<li>将背景强度计算为 "mean+6×SD".通过 "过程 > 数学 > 减法", 用相应的背景强度值减去图像, 输入对应于该通道的背景强度值。</li>
		<li>通过使用相同的开始和停止切片以及相同的背景 ROI, 对通道G和通道B图像堆栈重复步骤4.1.2 到4.1.4。请注意, 步骤4.1.3 中使用的 ROI 可以复制到通道G和通道B图像.
</li>
		<li>通过选择频道R为红色, 将通道G作为绿色和通道B作为蓝色, 合并三背景减去图像 (图像 > 颜色 > 合并通道)。将获得由三通道组成的单个复合图像。</li>
		<li>启动 roi 管理器 (分析 > 工具 > roi 管理器)。在单个珠子周围画一个正方形的 roi, 确保每个 roi 中只有一个珠子。通过在键盘上按 "t", 将 roi 添加到 roi 管理器中。重复此过程并添加尽可能多的 roi。</li>
		<li>在 "分析 > 设置测量" 中, 只检查 "质量中心"。</li>
		<li>选择频道R, 在 ROI 管理器中, 单击 "测量" 以获取中心;两列对应于 roi 中心的 x 和 y 坐标将显示在 "结果" 窗口中。将两列复制并粘贴到电子表格中。</li>
		<li>对通道G和通道B重复步骤4.1.9。</li>
		<li>按以下顺序排列单个电子表格中中心的坐标: xr、yr、xg、yg、xb和 yb。将 ". csv" 格式的电子表格保存为 "珠. csv"。在文件名中不留空格。</li>
	</ol></li>
	<li>选择和测量高尔基体 mini-stacks
	<ol>
<li>在 ImageJ 中安装两个宏 (附加在补充材料中), "宏高尔基 ROI 检测" 和 "宏输出3通道数据", 通过插件 > 安装 "。清除 ROI 管理器和结果窗口。</li>
		<li>打开一组高尔基体 mini-stack 图像, 由三 TIFF 文件 (文件 > 图像 > 打开) 组成。</li>
		<li>重复步骤 4.1.2-4.1.5 并保存三背景减去的图像以备以后使用。将通道R、通道G和通道b的背景 SDs 分别记录为 sdr、sdg和 sdb, 供以后使用。</li>
		<li>复制由步骤4.2.3 生成的三背景减去的图像 (ctrl+ Shift + D)。</li>
		<li>在 "过程 > 图像计算器" 中, 首先添加背景减去通道G以通道R图像。将生成的图像添加到背景减去通道B图像中。对于生成的图像, 在 "图像 > 调整 > 阈值" 中, 选择 "设置" 以输入 "1" 为 "最低阈值级别"。按下 "应用" 后, 产生黑白二进制图像。</li>
		<li>在 "分析 > 分析粒子", 输入大小范围为 "大小 (pixel^2)"。输入 "50-无穷大"。检查 "在边上排除" 和 "添加到管理器"。包含高尔基 mini-stacks 的 roi 现在添加到 ROI 管理器中。 注意: 大小范围必须是经验主义地确定排除通常小的噪声。</li>
		<li>通过选择频道R为红色, 将通道G作为绿色和通道B作为蓝色, 将步骤4.2.3 中的三背景减去图像 (图像 > 颜色 > 合并通道) 合并。生成由三通道组成的单个复合图像。</li>
		<li>通过选择 "插件 > 宏观-高尔基的 roi 检查" 来运行宏观的 "宏观-高尔基 roi 检测"。在 "交互式" 对话框中, 直观地检查每个 ROI 以保留或拒绝它。在所有三通道中选择包含单个对象的 roi。 注意: 在运行此工具后, 被拒绝的 roi 将从 ROI 管理器中删除。</li>
		<li>在 "分析 > 设置测量" 中只检查 "区域"、"平均灰度值" 和 "质量中心"。通过启动宏工具 "宏输出3通道数据" (插件 > 宏输出3通道数据) 获取数据。 注意: 在 "结果" 窗口中显示通道R、通道G和通道B中的 roi 的区域、平均强度和中心 (x 和 y)。</li>
		<li>将中心的 x 和 y 坐标复制到电子表格中, 并按以下顺序排列: xr、yr、xg、yg、xb和 yb。将电子表格保存为 ". csv" 文件 (ministacks. csv)。在文件名中不留空格。进行中心的色移校正 (4.3 节) 和 LQ 计算 (第4.4 节)。</li>
	</ol></li>
	<li>中心的色移校正
	<ol>
<li>安装 Matlab 编译器运行时 (MCR)。</li>
		<li>在专用工作文件夹中安装以下文件: my_train 和 my_test. exe。在同一个文件夹中复制并粘贴 "珠. csv" 和 "ministacks. csv" 文件。</li>
		<li>通过键入以下命令 " cd path_of_working_folder"启动 Windows 的 "命令提示符" 并转到工作文件夹。</li>
		<li>使用珠的中心生成色移校准文件。键入以下命令 "my_train 珠子. csv校准. 垫1。在工作文件夹中创建名为 "校准. 席子" 的文件。忽略生成的其他文件。</li>
		<li>通过键入以下命令 "my_test. exe ministacks. csv corrected_ministacks. csv校准. 垫1 注意: 在工作文件夹中创建名为 "corrected_ministacks. csv" 的文件。它包含了中心的色移校正坐标, 它们按 xg、yg、xb和 yb的顺序排列。忽略创建的其他文件。请注意, 红色通道定义为无色差, 因此 xr和 yr与原始数据相同。</li>
	</ol></li>
	<li>LQs 的计算
	<ol>
<li>启动数据分析软件, 并复制和粘贴, 在下面的序列中, 平均灰度值, 区域, 从步骤4.2.3 获得的背景 SDs (放置在1行) 和彩色移位校正的 x 和 y 高尔基体 mini-stacks 在通道R中的坐标转换为以列 A 到 E 的工作表。同样, 分别将信道G和通道B的相应数据传送到 F 到 J 和 K 到 O 的列。</li>
		<li>添加八新的 P 到 W, 命名为 "综合强度的通道 R", "综合强度的通道 G", "综合强度的通道 B", d1, dx, abs (棕褐色), abs (tan B) 和 LQ。<ol>
<li>右键单击相应列的顶部, 然后选择 "设置列值" 以计算每列的值。对于 P 列, 输入 "(a) 上校 (B)";对于列 Q, 输入 "(F) 上校 (G)";对于 R 列, 输入 "(K) 上校 (L)";对于列 S, 输入 "pixel_size * 距离 (D), 上校 (E), 上校 (N), 上校 (O))", 其中 "pixel_size" 是像素的大小在 nm;对于 T 列, 输入 "pixel_size" ((距离 (I), (J), (n), 上校 (o)) ^ 2 + 距离 (d), 上校 (E), 上校 (N), 上校 (o)) ^ 2 距离 (d), (e)、(I)、(J)) ^ 2)/(2 距离 (D)、(e)、上校 (N)、上校 (O))) ";对于 U 型, 输入 "Abs (助理 ((距离 (I), 上校 (J), 上校 (n), 上校 (O)) ^ 2 + 距离 (上校 (D), 上校 (E), 上校 (n), (O)) ^ 2 距离 (D), 上校 (E), 上校 (I), 上校 (J)) ^ 2)/(2 距离 (i), 上校 (J), 上校 (N), (O) 距离 (D)、(E)、(N)、上校 (O)))) ";对于第 V, 输入 "Abs" (助理 ((d), (四), 上校 (e), (i), 上校 (J)) ^ 2 + 距离 ((d), 上校 (e), 上校 (N), (o) ^ 2-距离 (I), 上校 (J), 上校 (N), 上校 (o)) ^ 2)/(2 距离 (d)、(E)、上校 (i)、上校 (J) 距离 (d)、(E)、(N)、上校 (O)))) ";对于 W 列, 输入 "(T)/上校 (S)"。</li>
		</ol>
</li>
		<li>按简介中描述的三标准筛选高尔基 mini-stacks。<ol>
<li>在数据分析软件中, 转到 "工作表 > 工作表查询", 并为 "If" 测试选择列变量。将下列别名分别分配给 I1、I2、I3、d1、a 和 B, 用于列 "通道 R 的综合强度"、"通道 G 的综合强度"、"通道 B 的综合强度"、"d1"、"abs" (tan a) 和 abs (tan b)。在 "If 条件" 框中, 输入 "I1 > = 30 * 单元 (13) 和 I2 > = 30 * 单元 (18) 和 I3 > = 30 * 单元 (113) 和 d1 > = 70 和 (一个 < = 0.3 或 B < = 0.3)"。</li>
			<li>选择 "提取到新工作表", 单击 "应用"。柱分析高尔基体 mini-stacks 被提取到一个新的工作表。</li>
		</ol>
</li>
		<li>在新工作表中, 右键单击列 W 的顶部, 选择 "列 > 打开对话框上的统计信息"。检查 "N 总计", "平均值", "SE", "直方图"。然后显示 LQs 的统计分析。</li>
	</ol></li>
</ol>

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作者声明他们没有竞争的金融利益。

以前, 在光显微镜下的高尔基体蛋白的定位, 主要是通过与已知的高尔基体标记的图像相关或重叠程度的蛋白质的图像进行量化,15,16, 17。由此产生的相关或重叠系数反映了测试蛋白在空间上对高尔基标记的接近程度。此方法至少有三警告。首先, 相关或重叠系数是非线性的, 不直接表示空间距离。第二, 相关性的程度严重依赖于显微系统的分辨率。因此, 两个高尔基蛋白之间的系数不是一个系统无关的常数。三、两种具有相同轴向定位但沿泡不同侧向分布的高尔基体蛋白质具有明显的系数。因此, 相关或重叠系数并不表示高尔基蛋白的轴向定位。在 Dejgaard et al提出的另一种方法中, cis、反式高尔基体标记物和感兴趣的蛋白在 nocodazole 治疗的高尔基体 mini-stacks 中是三重标记的, 类似于 GLIM。在每个高尔基 mini-stack 中, 获得三最大强度像素的位置, 并将测试蛋白的相对位置计算为距离比18。然而, 它们的方法无法实现亚像素的分辨率, 这极大地限制了它的应用。与以前的定量方法相比, GLIM, 它是独立开发的, 但与 Dejgaard et al具有相似的概念, 能够量化的高尔基体蛋白质的轴向定位, 具有空前的准确性和一致性。
我们提出了 GLIM 的协议, 以获得外部表达的 GFP 标记蛋白 TPST1-EGFP。内源蛋白的 LQ 可以确定其抗体是否可用。根据主要抗体的种类、小鼠或小白兔, 然后分别用兔子或老鼠 anti-GM130 抗体, 可以在三重标记协议中使用。无论是兔和小鼠 anti-GM130 抗体免疫荧光标记是商业可用。我们以前已经证明, 兔子和小鼠 anti-GM130 抗体在 GLIM7中提供相同的结果。如果测试蛋白在荧光发射中本质上是红色的, 如 mCherry 融合, 一个已知的 LQ 标记的高尔基体标记蛋白与 GM130 抗体标记结合可用于三重标签细胞和间接地推断测试蛋白的 LQ。假设标记蛋白的 lq 为 lqm , 从标记蛋白中心到 GM130 的距离为 dm, 则测试蛋白 x 的 lq 可以计算为 (dx/dm) ×LQm。与超分辨率显微镜相比, GLIM 的最大优点之一是它可以很容易地应用于常规显微设置中的活细胞成像。我们已经尝试了三荧光蛋白, GFP-Golgin84, mCherry-GM130 和 GalT-iRFP670 的组合, 以动态监测 GFP-Golgin84 在单一高尔基体 mini-stacks7的 LQ。
在 GLIM, 最耗时的步骤是后分析, 特别是在分析高尔基 mini-stacks 的选择。由于高尔基 mini-stacks 在大小和分子组成上都是异构的19, 所以不清楚 LQs (图 3F) 的分布是否代表高尔基 mini-stacks 的异构体系结构, 也不确定我们计算lq.不管原因是什么, 我们发现有大量的分析高尔基体 mini-stacks (n) 来保证 LQ 的精确性是很重要的, 因为它在 n 很小的时候就被破坏了。通常, 来自多个单元的 n ≥100的数据产生可靠的 LQs。因此, GLIM 给出了集合平均的定位数据, 遮蔽了高尔基 mini-stacks 的个性。GLIM 的另一个限制是, 它假设所有高尔基蛋白在一个中心周围都有一个狭窄的分布。一些高尔基蛋白, 如 COPI 亚基、ARF1 和可溶性 n-ethylmaleimide 敏感因子附着蛋白受体 (圈套)20,21, 已报告从cis到跨的广泛分布高尔基和 TGN。这可能是不适当的研究他们的高尔基定位的 LQ。由于 GLIM 目前涉及手动选择高尔基体 mini-stacks, 这既费力又主观, 未来的发展 GLIM 将是实施一个软件工具, 自动选择高尔基体 mini-stacks, 人的干扰最小。
GLIM 的空间分辨率是多少？因为 LQ 是一个比率, 是单位, 它不表明空间距离。在这里, 我们试图给出一个非常粗略的估计。GLIM 的空间分辨率可以定义为两个可分辨的高尔基体蛋白质之间的最小轴向距离。研究了各种高尔基体蛋白的 LQs7, 发现具有 n ≥100范围的数据集的中小企业在0.03 左右。假设两个高尔基蛋白具有相同的 n = 100 和 SEM = 0.03, 两个高尔基体蛋白有显著不同的定位, 通过t 检验(p < 0.05),即, 可解析, 如果他们的 LQs 是≥ 3 x sem = 0.09。从 EM 数据, 我们可以估计, 高尔基 mini-stack 的轴向长度, 这也是距离从 GM130 到高尔 mCherry 在 GLIM, 是〜 300 nm8。因此, GLIM 的分辨率估计为 0.09 x 300 = 30 nm 沿高尔基轴。在 GLIM, 一个较大的 n 一般产生较小的 SEM, 这反过来导致更高的分辨率。
直接比较 GLIM 与免疫金 EM 的分辨率可能不合适, 因为后者的技术不能直接产生定量的定位数据。与 GLIM 类似, 在高尔基轴上的免疫金 EM 的分辨率可以定义为两个可分辨的高尔基标记之间的最小距离。为了测量它的分辨率, 需要研究两个高尔基体蛋白质的双免疫金标记, 它们在高尔基轴上相邻。根据我们的知识, 这样的系统性研究可能是不可用的。正如导言中所讨论的, 免疫金 EM 的空间分辨率的限制因素之一是抗体复合体的大尺寸, 这使得分辨率比 ~ 20 nm 差。图像分辨率的另一个重要限制因素是抗原分子的标记密度。根据奈奎斯特抽样理论, 每个分辨率单位必须至少有两个金粒子。在大多数免疫金 EM 研究, 相邻金粒子之间的距离是不 < 15 纳米由于非常低的标记效率;这使得这种技术难以实现图像分辨率小于 30 nm。从这个角度来看, 我们估计 GLIM 的分辨率至少与免疫金 EM 的分辨力相当。
GLIM 是一种健壮的方法, 它提供了高度一致的结果。它独立于所使用的显微镜类型。我们已经测试了广域和旋转圆盘共焦显微镜产生了同样的结果。在不同批次实验中获得的高尔基体蛋白的 LQs 也有很好的一致性。一个 LQ 数据库由不同范围的高尔基体的居民蛋白质产生, 以供比较和解释。我们预计, 更多的 GLIM 在研究领域的使用将大大扩展数据库。因此, 一个更完整的数据库定量地描述了大量的高尔基体蛋白质的本地化将大大有助于了解的组织和功能的高尔基复合体。

高尔基复合体在哺乳动物细胞分泌/吞的蛋白质和脂质 (以下) 的贩运中起着重要作用1,2,3。在高尔基, 货物不仅排序到各种细胞舱室, 但也修改了不同类型的糖基化。哺乳动物高尔基复合体包括许多侧向连接的高尔基栈, 通常由 4-11 紧密相邻和扁平膜囊称为泡。连续堆叠高尔基体泡进一步分类, 从一端到另一个, 作为cis, 内侧和反式-泡。在高尔基体的反式一侧,反式-大多数膜囊发展成管状和网状膜网络, 称为反式-高尔基网络 (TGN)4。在分泌通路中, 来自内质网 (ER) 的货物在其cis端进入高尔基体, 然后依次通过内侧和反式-泡。货物最终退出高尔基体在反式-高尔基或 TGN 注定的细胞膜, 体或分泌颗粒。
的分子和细胞机制如何运输的高尔基体和高尔基体保持其池组织仍然神秘, 目前仍在激烈辩论1。这一领域的难点之一是, 高尔基泡只能在电子显微镜下解决 (EM), 因为光学显微镜 (200 nm) 的分辨率不足以解决单个高尔基泡 (< 100 纳米池厚度和距离)。因此, 亚高尔基定位的居民蛋白和转运货物是常规确定的免疫金 EM。然而, 免疫金 EM 是非常严格的技术要求, 它是超出了能力的大多数细胞生物学实验室。虽然 em 的分辨率可以 sub-nanometer, 免疫金 em 所提供的分辨率很大程度上受阻于抗体复合体 (主辅抗体) 和金粒子的大小, 而且可能比 20 nm 差。此外, EM 图像是从2D 薄剖面, 而不是一个3D 的全球视野的高尔基, 这可能导致错误的结论取决于相对位置和方向的2D 节5。例如, 研究 EM 开路不能可靠地区分一个小泡从一个小管的正交视图, 因为两者都可以显示相同的圆形膜剖面。最近出现的超分辨率显微镜技术, 如 3 d 结构照明显微镜 (3 d SIM), 刺激发射损耗 (STED), 光定位显微镜 (手掌) 和随机光学重建显微镜 (风暴), 使得有可能解决亚高尔基体在光显微镜下的结构6。然而, 至少有四缺点, 可以极大地限制他们的使用在细胞生物学研究高尔基。1) 目前超分辨率技术需要昂贵和特殊的硬件配置, 这是超出大多数细胞生物学实验室。2) 某些超分辨率技术需要特殊的荧光标记协议。3) 虽然在最佳条件下, 这些技术在空间分辨率上要求 20-110 nm, 但实际样品中获得的实用分辨率可能更差。4) 与常规显微镜相比, 这些超分辨率技术在进行多色、3D 或活细胞成像方面仍有困难, 无论是单独还是联合进行。可能最重要的是, 免疫金 EM 和超分辨显微镜技术的产生定性而不是定量的本地化数据。
试图部分解决上述问题, 我们最近开发了一个传统的光学显微镜的方法, 这是命名为高尔基体蛋白质的成像中心的质量 (GLIM), 系统和定量本地化高尔基蛋白质的分辨率相当于免疫金 EM7。在这种方法中, 高尔基体在培养的哺乳动物细胞被分散作为高尔基体 mini-stacks 通过治疗 nocodazole, 一个微管聚药物。广泛的研究表明, nocodazole 诱导高尔基 mini-stacks (以下高尔基体 mini-stacks) 在组织和细胞功能上都与本机的基尔基体紧密类似8,9,10, 11。测试蛋白的定位商 (LQ) 可以通过 GLIM 获得, 它表示定量的亚尔基体定位。对 LQs 的数值进行了比较, 得到了超过25高尔基标记的 LQ 数据库。
在 GLIM, 高尔基 mini-stacks 是三重标记的内生或外部表达 GM130, 高尔特 mCherry 和测试蛋白 (x)。GM130 和高尔特-mCherry, cis-和反式-高尔基标记分别12,13, 提供参考点。三重荧光, 红色 (R), 绿色 (G) 和远红色 (B), 被人为地显示红色, 绿色和蓝色, 分别。采用荧光质量中心 (以下简称中心) 实现亚像素分辨率。高尔基轴被定义为从 GM130 中心到高尔 mCherry 的向量。高尔基 mini-stack 被建模为一个圆柱形结构, 在高尔基轴周围有无限的旋转对称。因此, 高尔基体 mini-stack 可以被进一步建模为沿高尔基轴的 one-dimensional 结构。测试蛋白 x 的 LQ 定义为 dx/d1, 其中 dx是从 x 中心到 GM130 的距离, 而 d1是从 mCherry 中心到 GM130 的距离。如果 x 轴的中心是轴向的, 它的投影轴线距离用于计算。变量, 包括高尔基轴, 轴向角, dx, d1, 角α和角β, 为 GLIM 的示意图在图 1中说明。LQ 是独立的高尔基轴向角, 虽然高尔基 mini-stacks 东方随机在一个细胞。
高尔基体 mini-stacks 在图像中呈现不均匀。我们制定了三标准, 以选择分析高尔基 mini-stacks GLIM。1) 信噪比判据, 在每个通道中, 高尔基体 mini-stack 的总强度与背景的标准差 (SD) 的比值为≥30。这一标准是确保质量中心的定位精度, 这取决于高尔基体 mini-stacks 的信噪比。2) 轴向角度或距离标准, 要求 d1≥ 70 nm。d1随着高尔基轴向角的增大而减小。当轴向角度接近90°或垂直方向时, mini-stack 变为 non-resolvable, 因为 d1接近0。d1≥ 70 nm 可以有效地排除垂直高尔基体附近的 mini-stacks。3) co-linearity 标准, 其中任一 | tan α |或 | tan β |≤0.3。这一标准确保了 mini-stack 的三中心足以共我们的 one-dimensional 模型的高尔基 mini-stack。所有的光显微镜都有色差, 严重地扭曲了红色、绿色和远红光荧光中心的相对位置。对显微镜系统的色差进行了实验标定, 成像110纳米珠, 这是红, 绿和远红色荧光三标。对于每个珠子图像, 红色中心被定义为珠的真实位置, 绿色和远红色中心的色移由一阶多项式函数拟合。高尔基体 mini-stacks 的中心受多项式函数的作用, 以纠正绿色和远红通道中的色移。
通过 GLIM, 我们可以在标准条件下在高尔基轴上实现约 30 nm 的分辨率。重要的是, 它提供了一种系统的方法来定量绘制任何高尔基蛋白。GLIM 可由常规显微镜 (如广域或共聚焦显微镜) 使用普通荧光标记协议进行。图像处理和数据处理可能会缩短一小时。通过 GLIM, 我们直接演示了分泌货物从cis-到高尔基体7的跨端的逐步过渡。

<table><tbody><tr><td>fluorescence beads. Commercial name: TetraSpeck beads</td><td>Invitrogen</td><td>T7279</td><td>As multi-color beads to calibrate chromatic-shift of the microscope</td></tr><tr><td>Glass coverslip &amp;Phi; 12 mm (No. 1.5)</td><td>Menzel</td><td>CB00120RAC</td><td></td></tr><tr><td>Glass coverslip &amp;Phi; 25 mm (No. 1.5)</td><td>Menzel</td><td></td><td></td></tr><tr><td>DMEM</td><td>Capricon</td><td>DMEM-HPA-P50</td><td></td></tr><tr><td>Trypsin-EDTA</td><td></td><td></td><td></td></tr><tr><td>FBS</td><td>GE Hyclone</td><td>SV30160.03</td><td></td></tr><tr><td>Nocodazole</td><td>Merck</td><td>487928</td><td></td></tr><tr><td>transfection reagent. Commercial name: Lipofectamine 2000</td><td>Invitrogen</td><td>11668-019</td><td></td></tr><tr><td>transfection medium. Commercial name: OptiMEM</td><td>Invitrogen</td><td>31985070</td><td></td></tr><tr><td>TPST1-EGFP</td><td>Addgene</td><td>66617</td><td>A gift from D. Stephens (University of Bristol, Bristol, United Kingdom)</td></tr><tr><td>GalT-mCherry</td><td></td><td></td><td>Made in our lab</td></tr><tr><td>paraformaldehyde</td><td>Merck</td><td>1.04005.1000</td><td></td></tr><tr><td>saponin</td><td>Sigma-Aldrich</td><td>47036</td><td></td></tr><tr><td>poly(vinyl alcohol) (Mw ~31,000). Commercial name: Mowiol-488</td><td>CALBIOCHEM</td><td>475904</td><td></td></tr><tr><td>BSA</td><td>Sigma-Aldrich</td><td>A9647</td><td></td></tr><tr><td>Mouse anti-GM130</td><td>BD Biosciences</td><td>610823</td><td>Primary antibody for human GM130</td></tr><tr><td>far-red fluorescence conjugated goat anti-mouse IgG. Commercial name: Alexa Fluor 647 conjugated goat anti-mouse IgG</td><td>Invitrogen</td><td>A-21235</td><td>Far red fluorescence conjugated secondary antibody</td></tr></tbody></table>

quantitative localization of a golgi protein by imaging its center of fluorescence mass

高尔基复合体由连续堆积的膜泡组成, 可进一步划分为亚高尔基区, 包括cis-高尔基体、中高尔基、反式-高尔基和反式-高尔基网络。高尔基体的细胞功能由其驻留蛋白的特征分布决定。传统光学显微镜的空间分辨率过低, 无法解决亚高尔基结构或泡。因此, 免疫金电子显微镜是一种选择的方法, 本地化的蛋白质在亚高尔基水平。然而, 该技术和仪器超出了大多数细胞生物学实验室的能力。我们在这里描述我们最近开发的超分辨率的方法称为高尔基蛋白的成像中心的质量 (GLIM) 系统和定量本地化高尔基体蛋白。GLIM 是基于标准荧光标记协议和传统的广域或共聚焦显微镜。它涉及对显微系统的色移像差的标定、图像采集和后分析。将测试蛋白的亚尔基体定位定量地表达为定位商。GLIM 有四主要优点;它是快速的, 根据传统的方法和工具, 本地化的结果是定量的, 它提供了〜 30 nm 的实际分辨率沿高尔基轴。在这里, 我们描述了 GLIM 的详细协议, 本地化一个测试高尔基蛋白。

现代研究级光学显微镜配有计划物镜透镜, 如我们实验室使用的, 显示最小色差 (图 2a)。然而, 仔细检查多色荧光珠图像可以揭示同一珠子的不同颜色图像的移位 (图 2B)。我们定义红色通道没有色差, 因此红色荧光的中心是珠的真实位置。绿色和远红光荧光的相对色位移可以用来自红色荧光中心的绿色和蓝色向量来表示 (图 2C)。在成像平面内的色移由每个珠子的绿色和蓝色矢量 (图 2D) 进行了经验说明。对于我们的显微镜, 色位移不均匀, 因为大小和方向的变化, 根据 x 和 y 的立场。由于远红中心的位移可高达 50 nm, 因此色移可以显著影响 GLIM 的准确度。因此, 必须纠正色移。一旦获得了中心的珠子, 我们采用一阶多项式拟合, 以校准和随后纠正的色转移中心。这种方法 (图 2 D-G) 大大提高了色移位差。
在哺乳动物细胞中, 高尔基体聚集在周区域, 通常在传统光学显微镜下 (图 3a) 无法解析。nocodazole 治疗3小时后, 周高尔基复合体消失, 几十个高尔基体 mini-stacks 聚集在细胞质中的内质网出口部位 (图 3B)。大块高尔基膜和聚合高尔基 mini-stacks 存在, 并没有选择进行分析。在图 3C中显示了一个说明高尔基 mini-stacks 选择的示例图像。在图 3D中列出了40选择的高尔基体 mini-stacks。在应用三标准后, 21 高尔基 mini-stacks 被分析, 并选择用于计算 TPST1-EGFP 的 LQs (图 3D; 标记为 "L"), 其统计信息显示在图 3E中。总共有111分析高尔基 mini-stacks 从12个细胞中选择, TPST1-EGFP 的 LQ 被测量为 0.76 0.04 (平均± SEM; n = 111) (图 3F)。TPST1-EGFP 的 lq 位置介于 giantin (lq = 0.59) 和 EGFP-Rab6 (lq = 1.04)7之间。它是近 GS15 (lq = 0.83) 和 ST6GalT1-AcGFP1 (lq = 0.82)。我们根据 LQs 定义了亚高尔基区域, 从文献中考虑定性的本地化数据: 爪牙/能, <-0.25;cis, 0.00 ± 0.25;内侧, 0.50 ± 0.25;反式-高尔基体, 1.00 ±0.25 和 TGN, 1.25-2.00。因此, TPST1-EGFP 的 LQ 表示它的反式-高尔基定位, 这与先前的研究14是一致的。
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/55996/55996fig1.jpg"> 图 1.示意图, 显示用于计算 GLIM 的变量.(a) 高尔基体的 mini-stack, 有轴中心的 GM130, mCherry 和蛋白 x 荧光显示高尔基轴, 轴向角, dx和 d1。高尔基 mini-stack 的图像是投射到图像平面上的。(B) 高尔基体 mini-stack 的 xy 视图, 带轴向中心的蛋白 x 显示角度α、角度β和投影轴向距离 dx。A和B分别适用于我们以前的出版物7的图 1E和图 1F 。<a href="//cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55996/55996fig1large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/55996/55996fig2.jpg"> 图 2.校正色移.(a) 由广域显微镜获得的 110 nm 多色珠子的三色合并图像。每个珠子都发出绿色、红色和远红色 (人工上色为蓝色) 荧光。缩放栏, 10 µm. (B) 合并 single-bead 图像的放大视图, 具有明显的色位移。刻度条, 200 nm。(C) 一个示意图, 显示绿色和远红的珠子图像的变化可以由来自红珠图像中心 (00) 的向量表示, 分别为绿色 (绿色矢量) 和远红 (蓝色矢量) 珠形图像的中心。(D, E)色移校正的效果。在相同的图像域中, 在移位校正前后绘制绿色和蓝色向量。为了可视化微小的移位, 每个向量的大小被放大200倍。(F, G)散布图显示绿色 (绿点) 和远红 (蓝点) 珠的中心, 在换班前后。<a href="//cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55996/55996fig2large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/55996/55996fig3.jpg"> 图 3.GLIM 的一个典型例子, 这里获得了 TPST1-EGFP 的 LQ.TPST1-EGFP (绿色) 和 mCherry (红色) 的 HeLa 细胞染色为内生 GM130 (蓝色)。(a) 一个典型的单元格。(B、C、D、E)用 nocodazole 处理的细胞被成像 (B)。从图像中, 分析高尔基体 mini-stacks 被选中, 如C所示。选定的高尔基 mini-stacks 被标识号标记。这些蒙面高尔基 mini-stacks 的图像在D中显示, 其标识号如下。"L" 表示高尔基 mini-stack 对 LQ (分析高尔基 mini-stacks) 的计算是有效的。从单元格中 LQs 21 mini-stacks 的直方图显示在E中。(F) 从12个单元格中 LQs 111 mini-stacks 的直方图。直方图中显示的值是平均的± SEM.<a href="//cloudflare-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/55996/55996fig3large.jpg" target="_blank">请单击此处查看此图的较大版本.</a>
补充材料:宏观-高尔基的 ROI 检测. ijm, 宏输出3通道数据. ijm、Matlab 代码、My_train .exe、My_test .exe 和电子表格模板. opj。

Watch this Scientific Journal Video about Quantitative Localization of a Golgi Protein by Imaging Its Center of Fluorescence Mass at JoVE.com

Quantitative Localization of a Golgi Protein by Imaging Its Center of Fluorescence Mass

高尔基体的精确定位对于了解高尔基体的细胞功能是至关重要的。然而, 传统的光学显微镜无法解决亚尔基体的结构。在这里, 我们描述了一个传统的基于显微镜的超分辨率方法的协议, 定量地确定蛋白质的亚高尔基体定位。

高尔基蛋白质荧光质量中心的定量定位

The Golgi complex consists of serially stacked membrane cisternae which can be further categorized into sub-Golgi regions, including the cis-Golgi, ...

quantitative-localization-golgi-protein-imaging-its-center

Universidad San Sebastian

Research

JoVE Journal

Biology

10.7K 次观看.  Nanyang Technological University. 高尔基体的精确定位对于了解高尔基体的细胞功能是至关重要的。然而, 传统的光学显微镜无法解决亚尔基体的结构。在这里, 我们描述了一个传统的基于显微镜的超分辨率方法的协议, 定量地确定蛋白质的亚高尔基体定位。

视频: Quantitative Localization of a Golgi Protein by Imaging Its Center of Fluorescence Mass

Isolation and Quantitative Immunocytochemical Characterization of Primary Myogenic Cells and Fibroblasts from Human Skeletal Muscle

The repair and regeneration of skeletal muscle requires the action of satellite cells, which are the resident muscle stem cells. These can be isolated from human muscle biopsy samples using enzymatic digestion and their myogenic properties studied in culture. Quantitatively, the two main adherent cell types obtained from enzymatic digestion are: (i) the satellite cells (termed myogenic cells or muscle precursor cells), identified initially as CD56+ and later as CD56+/desmin+ cells and (ii) muscle-derived fibroblasts, identified as CD56&#8211; and TE-7+. Fibroblasts proliferate very efficiently in culture and in mixed cell populations these cells may overrun myogenic cells to dominate the culture. The isolation and purification of different cell types from human muscle is thus an important methodological consideration when trying to investigate the innate behavior of either cell type in culture. Here we describe a system of sorting based on the gentle enzymatic digestion of cells using collagenase and dispase followed by magnetic activated cell sorting (MACS) which gives both a high purity (&#62;95% myogenic cells) and good yield (~2.8 x 106 &#177; 8.87 x 105 cells/g tissue after 7 days in vitro) for experiments in culture. This approach is based on incubating the mixed muscle-derived cell population with magnetic microbeads beads conjugated to an antibody against CD56 and then passing cells though a magnetic field. CD56+ cells bound to microbeads are retained by the field whereas CD56&#8211; cells pass unimpeded through the column. Cell suspensions from any stage of the sorting process can be plated and cultured. Following a given intervention, cell morphology, and the expression and localization of proteins including nuclear transcription factors can be quantified using immunofluorescent labeling with specific antibodies and an image processing and analysis package.

The main adherent cell types derived from human muscle are myogenic cells and fibroblasts. Here, cell populations are enriched using magnetic-activated cell sorting based on the CD56 antigen. Subsequent immunolabelling with specific antibodies and use of image analysis techniques allows quantification of cytoplasmic and nuclear characteristics in individual cells.

从人类骨骼肌成肌原细胞和成纤维细胞的分离和定量免疫细胞化学表征

The repair and regeneration of skeletal muscle requires the action of satellite cells, which are the resident muscle stem cells. These can be isolated ...

科研

发育生物学

Quantitative Immunofluorescence to Measure Global Localized Translation

The mechanisms regulating mRNA translation are involved in various biological processes, such as germ line development, cell differentiation, and organogenesis, as well as in multiple diseases. Numerous publications have convincingly shown that specific mechanisms tightly regulate mRNA translation. Increased interest in the translation-induced regulation of protein expression has led to the development of novel methods to study and follow de novo protein synthesis in cellulo. However, most of these methods are complex, making them costly and often limiting the number of mRNA targets that can be studied. This manuscript proposes a method that requires only basic reagents and a confocal fluorescence imaging system to measure and visualize the changes in mRNA translation that occur in any cell line under various conditions. This method was recently used to show localized translation in the subcellular structures of adherent cells over a short period of time, thus offering the possibility of visualizing de novo translation for a short period during a variety of biological processes or of validating changes in translational activity in response to specific stimuli.

This manuscript describes a method to visualize and quantify localized translation events in subcellular compartments. The approach proposed in this manuscript requires a basic confocal imaging system and reagents and is rapid and cost-effective.

定量荧光测量全球本地化翻译

The mechanisms regulating mRNA translation are involved in various biological processes, such as germ line development, cell differentiation, and ...

生物化学

Automated Quantification of Synaptic Fluorescence in C. elegans

Synapse strength refers to the amplitude of postsynaptic responses to presynaptic neurotransmitter release events, and has a major impact on overall neural circuit function. Synapse strength critically depends on the abundance of neurotransmitter receptors clustered at synaptic sites on the postsynaptic membrane. Receptor levels are established developmentally, and can be altered by receptor trafficking between surface-localized, subsynaptic, and intracellular pools, representing important mechanisms of synaptic plasticity and neuromodulation. Rigorous methods to quantify synaptically-localized neurotransmitter receptor abundance are essential to study synaptic development and plasticity. Fluorescence microscopy is an optimal approach because it preserves spatial information, distinguishing synaptic from non-synaptic pools, and discriminating among receptor populations localized to different types of synapses. The genetic model organism Caenorhabditis elegans is particularly well suited for these studies due to the small size and relative simplicity of its nervous system, its transparency, and the availability of powerful genetic techniques, allowing examination of native synapses in intact animals.
Here we present a method for quantifying fluorescently-labeled synaptic neurotransmitter receptors in C. elegans. Its key feature is the automated identification and analysis of individual synapses in three dimensions in multi-plane confocal microscope output files, tabulating position, volume, fluorescence intensity, and total fluorescence for each synapse. This approach has two principal advantages over manual analysis of z-plane projections of confocal data. First, because every plane of the confocal data set is included, no data are lost through z-plane projection, typically based on pixel intensity averages or maxima. Second, identification of synapses is automated, but can be inspected by the experimenter as the data analysis proceeds, allowing fast and accurate extraction of data from large numbers of synapses. Hundreds to thousands of synapses per sample can easily be obtained, producing large data sets to maximize statistical power. Considerations for preparing C. elegans for analysis, and performing confocal imaging to minimize variability between animals within treatment groups are also discussed. Although developed to analyze C. elegans postsynaptic receptors, this method is generally useful for any type of synaptically-localized protein, or indeed, any fluorescence signal that is localized to discrete clusters, puncta, or organelles.
The procedure is performed in three steps: 1) preparation of samples, 2) confocal imaging, and 3) image analysis. Steps 1 and 2 are specific to C. elegans, while step 3 is generally applicable to any punctate fluorescence signal in confocal micrographs.

Automated Quantification of Synaptic Fluorescence in C. elegans

The abundance of neurotransmitter receptors clustered at synapses strongly influences synaptic strength. This method quantifies fluorescently-labeled neurotransmitter receptors in three dimensions with single-synapse resolution in C. elegans, allowing hundreds of synapses to be rapidly characterized within a single sample without distortions introduced by z-plane projection.

突触荧光自动定量<em&gt; C。线虫</em

Synapse strength refers to the amplitude of postsynaptic responses to presynaptic neurotransmitter release events, and has a major impact on overall ...

神经科学

Nano-fEM: Protein Localization Using Photo-activated Localization Microscopy and Electron Microscopy

Mapping the distribution of proteins is essential for understanding the function of proteins in a cell. Fluorescence microscopy is extensively used for protein localization, but subcellular context is often absent in fluorescence images. Immuno-electron microscopy, on the other hand, can localize proteins, but the technique is limited by a lack of compatible antibodies, poor preservation of morphology and because most antigens are not exposed to the specimen surface. Correlative approaches can acquire the fluorescence image from a whole cell first, either from immuno-fluorescence or genetically tagged proteins. The sample is then fixed and embedded for electron microscopy, and the images are correlated 1-3. However, the low-resolution fluorescence image and the lack of fiducial markers preclude the precise localization of proteins. 
Alternatively, fluorescence imaging can be done after preserving the specimen in plastic. In this approach, the block is sectioned, and fluorescence images and electron micrographs of the same section are correlated 4-7. However, the diffraction limit of light in the correlated image obscures the locations of individual molecules, and the fluorescence often extends beyond the boundary of the cell. 
Nano-resolution fluorescence electron microscopy (nano-fEM) is designed to localize proteins at nano-scale by imaging the same sections using photo-activated localization microscopy (PALM) and electron microscopy. PALM overcomes the diffraction limit by imaging individual fluorescent proteins and subsequently mapping the centroid of each fluorescent spot 8-10. 
We outline the nano-fEM technique in five steps. First, the sample is fixed and embedded using conditions that preserve the fluorescence of tagged proteins. Second, the resin blocks are sectioned into ultrathin segments (70-80 nm) that are mounted on a cover glass. Third, fluorescence is imaged in these sections using the Zeiss PALM microscope. Fourth, electron dense structures are imaged in these same sections using a scanning electron microscope. Fifth, the fluorescence and electron micrographs are aligned using gold particles as fiducial markers. In summary, the subcellular localization of fluorescently tagged proteins can be determined at nanometer resolution in approximately one week.

We describe a method to localize fluorescently tagged proteins in electron micrographs. Fluorescence is first localized using photo-activated localization microscopy on ultrathin sections. These images are then aligned to electron micrographs of the same section.

纳米有限元分析：蛋白质定位的光激活定位显微镜和电子显微镜

Mapping the distribution of proteins is essential for understanding the function of proteins in a cell. Fluorescence microscopy is extensively used for ...

生物学

Studying Organelle Dynamics in B Cells During Immune Synapse Formation

Recognition of surface-tethered antigens&#160;by the B cell receptor (BCR)&#160;triggers the formation of an immune synapse (IS), where both signaling&#160;and antigen uptake are coordinated. IS formation involves dynamic actin remodeling accompanied by the polarized recruitment to the synaptic membrane of the centrosome and associated intracellular organelles such as lysosomes and the Golgi apparatus. Initial stages of actin remodeling allow B cells to increase their cell surface and maximize the quantity of antigen-BCR complexes gathered at the synapse. Under certain conditions, when B cells recognize antigens associated to rigid surfaces, this process is coupled to the local recruitment and secretion of lysosomes, which can facilitate antigen extraction. Uptaken antigens&#160;are internalized into specialized endo-lysosome compartments for processing into peptides, which are loaded onto major histocompatibility complex II (MHC-II) molecules for further presentation to T helper cells. Therefore, studying organelle dynamics associated with the formation of an IS is crucial to understanding how B cells are activated. In the present article we will discuss both imaging and a biochemical technique used to study changes in intracellular organelle positioning and cytoskeleton rearrangements that are associated with the formation of an IS in B cells.

Herein we describe two approaches to characterize cell polarization events in B lymphocytes during the formation of an IS. The first, involves quantification of organelle recruitment and cytoskeleton rearrangements at the synaptic membrane. The second is a biochemical approach, to characterize changes in composition of the centrosome, which undergoes polarization to the immune synapse.

研究免疫突触形成过程中B细胞中的细胞动力学

Recognition of surface-tethered antigens&#160;by the B cell receptor (BCR)&#160;triggers the formation of an immune synapse (IS), where both ...

免疫与感染

Quantifying the Heterogeneous Distribution of a Synaptic Protein in the Mouse Brain Using Immunofluorescence

The presence, absence, or levels of specific synaptic proteins can severely influence synaptic transmission. In addition to elucidating the function of a protein, it is vital to also determine its distribution. Here, we describe a protocol employing immunofluorescence, confocal microscopy, and computer-based analysis to determine the distribution of the synaptic protein Mover (also called TPRGL or SVAP30). We compare the distribution of Mover to that of the synaptic vesicle protein synaptophysin, thereby determining the distribution of Mover in a quantitative manner relative to the abundance of synaptic vesicles. Notably, this method could potentially be implemented to allow for comparison of the distribution of proteins using different antibodies or microscopes or across different studies. Our method circumvents the inherent variability of immunofluorescent stainings by yielding a ratio rather than absolute fluorescence levels. Additionally, the method we describe enables the researcher to analyze the distribution of a protein on different levels: from whole brain slices to brain regions to different subregions in one brain area, such as the different layers of the hippocampus or sensory cortices. Mover is a vertebrate-specific protein that is associated with synaptic vesicles. With this method, we show that Mover is heterogeneously distributed across brain areas, with high levels in the ventral pallidum, the septal nuclei, and the amygdala, and also within single brain areas, such as the different layers of the hippocampus.

Here, we describe a quantitative approach to determining the distribution of a synaptic protein relative to a marker protein using immunofluorescence staining, confocal microscopy, and computer-based analysis.

免疫荧光定量小鼠脑突触蛋白的异种分布

The presence, absence, or levels of specific synaptic proteins can severely influence synaptic transmission. In addition to elucidating the function of a ...

Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy

Localization-based super resolution microscopy can be applied to obtain a spatial map (image) of the distribution of individual fluorescently labeled single molecules within a sample with a spatial resolution of tens of nanometers. Using either photoactivatable (PAFP) or&#160;photoswitchable (PSFP) fluorescent proteins fused to proteins of interest, or organic dyes conjugated to antibodies or other molecules of interest, fluorescence photoactivation localization microscopy (FPALM) can simultaneously image multiple species of molecules within single cells. By using the following approach, populations of large numbers (thousands to hundreds of thousands) of individual molecules are imaged in single cells and localized with a precision of ~10-30 nm. Data obtained can be applied to understanding the nanoscale spatial distributions of multiple protein types within a cell. One primary advantage of this technique is the dramatic increase in spatial resolution: while diffraction limits resolution to ~200-250 nm in conventional light microscopy, FPALM can image length scales more than an order of magnitude smaller. As many biological hypotheses concern the spatial relationships among different biomolecules, the improved resolution of FPALM can provide insight into questions of cellular organization which have previously been inaccessible to conventional fluorescence microscopy. In addition to detailing the methods for sample preparation and data acquisition, we here describe the optical setup for FPALM. One additional consideration for researchers wishing to do super-resolution microscopy is cost: in-house setups are significantly cheaper than most commercially available imaging machines. Limitations of this technique include the need for optimizing the labeling of molecules of interest within cell samples, and the need for post-processing software to visualize results. We here describe the use of PAFP and PSFP expression to image two protein species in fixed cells. Extension of the technique to living cells is also described.

We demonstrate the use of fluorescence photo activation localization microscopy (FPALM) to simultaneously image multiple types of fluorescently labeled molecules&#160;within cells. The techniques described yield the localization of thousands to hundreds of thousands of individual fluorescent labeled proteins, with a precision of tens of nanometers&#160;within single cells.

Localization-based super resolution microscopy can be applied to obtain a spatial map (image) of the distribution of individual fluorescently labeled ...

Quantitative Immunofluorescence Assay to Measure the Variation in Protein Levels at Centrosomes

Centrosomes are small but important organelles that serve as the poles of mitotic spindle to maintain genomic integrity or assemble primary cilia to facilitate sensory functions in cells. The level of a protein may be regulated differently at centrosomes than at other .cellular locations, and the variation in the centrosomal level of several proteins at different points of the cell cycle appears to be crucial for the proper regulation of centriole assembly. We developed a quantitative fluorescence microscopy assay that measures relative changes in the level of a protein at centrosomes in fixed cells from different samples, such as at different phases of the cell cycle or after treatment with various reagents. The principle of this assay lies in measuring the background corrected fluorescent intensity corresponding to a protein at a small region, and normalize that measurement against the same for another protein that does not vary under the chosen experimental condition. Utilizing this assay in combination with BrdU pulse and chase strategy to study unperturbed cell cycles, we have quantitatively validated our recent observation that the centrosomal pool of VDAC3 is regulated at centrosomes during the cell cycle, likely by proteasome-mediated degradation specifically at centrosomes.

Here, a novel quantitative fluorescence assay is developed to measure changes in the level of a protein specifically at centrosomes by normalizing that protein&#8217;s fluorescence intensity to that of an appropriate internal standard.

定量免疫检测，以衡量在中心体的变异蛋白水平

Centrosomes are small but important organelles that serve as the poles of mitotic spindle to maintain genomic integrity or assemble primary cilia to ...

Multi-color Localization Microscopy of Single Membrane Proteins in Organelles of Live Mammalian Cells

Knowledge about the localization of proteins in cellular subcompartments is crucial to understand their specific function. Here, we present a super-resolution technique that allows for the determination of the microcompartments that are accessible for proteins by generating localization and tracking maps of these proteins. Moreover, by multi-color localization microscopy, the localization and tracking profiles of proteins in different subcompartments are obtained simultaneously. The technique is specific for live cells and is based on the repetitive imaging of single mobile membrane proteins. Proteins of interest are genetically fused with specific, so-called self-labeling tags. These tags are enzymes that react with a substrate in a covalent manner. Conjugated to these substrates are fluorescent dyes. Reaction of the enzyme-tagged proteins with the fluorescence labeled substrates results in labeled proteins. Here, Tetramethylrhodamine (TMR) and Silicon Rhodamine (SiR) are used as fluorescent dyes attached to the substrates of the enzymes. By using substrate concentrations in the pM to nM range, sub-stoichiometric labeling is achieved that results in distinct signals. These signals are localized with ~15&#8211;27 nm precision. The technique allows for multi-color imaging of single molecules, whereby the number of colors is limited by the available membrane-permeable dyes and the repertoire of self-labeling enzymes. We show the feasibility of the technique by determining the localization of the quality control enzyme (Pten)-induced kinase 1 (PINK1) in different mitochondrial compartments during its processing in relation to other membrane proteins. The test for true physical interactions between differently labeled single proteins by single molecule FRET or co-tracking is restricted, though, because the low labeling degrees decrease the probability for having two adjacent proteins labeled at the same time. While the technique is strong for imaging proteins in membrane compartments, in most cases it is not appropriate to determine the localization of highly mobile soluble proteins.

Here, we present a protocol for multi-color localization of single membrane proteins in organelles of live cells. To attach fluorophores, self-labeling proteins are used. Proteins, located in different membranes compartments of the same organelle, can be localized with a precision of ~18 nm.

活体哺乳动物细胞器中单膜蛋白的多色定位显微术

Knowledge about the localization of proteins in cellular subcompartments is crucial to understand their specific function. Here, we present a ...

研究 ATG9A 在细胞中的定位

Imaging ATG9A, a Multi-Spanning Membrane Protein

Autophagy is a highly conserved pathway that the cell uses to maintain homeostasis, degrade damaged organelles, combat invading pathogens, and survive pathological conditions. A set of proteins, called ATG proteins, comprise the core autophagy machinery and work together in a defined hierarchy. Studies in recent years have improved our knowledge of the autophagy pathway. Most recently, it has been proposed that ATG9A vesicles are at the heart of autophagy, as they control the rapid de novo synthesis of an organelle called the phagophore. The study of ATG9A has proven challenging, since ATG9A is a transmembrane protein, and it is present in different membrane compartments. As such, understanding its trafficking is an important element for understanding autophagy. Here, detailed methods are presented that can be used to study ATG9A and, in particular, its localization using immunofluorescence techniques, which can be assessed and quantified. The pitfalls of transient overexpression are also addressed. The correct characterization of ATG9A function and the standardization of techniques to analyze its trafficking are crucial to further characterize the events governing autophagy initiation.

作者聚焦:成像 ATG9A，一种多跨膜蛋白  

This protocol describes various methods that can help in the study of ATG9A biology, including immunofluorescence followed by image analysis, transient overexpression considerations, and investigating the ATG9A glycosylation status using western blot.

成像 ATG9A，一种多跨膜蛋白

Autophagy is a highly conserved pathway that the cell uses to maintain homeostasis, degrade damaged organelles, combat invading pathogens, and survive ...