这项研究是由健康研究补助金FRQ-S加拿大学院（CIHR MOP-115195）和IT，谁也是CIHR青年研究者奖的获得者的支持;和瑞典研究委员会和瑞典癌症协会OL

1，蔗糖梯度准备<ol><li>制备100ml的60％（重量/体积）在DDH 2 O蔗糖溶液溶液应通过一个0.22微米的过滤器进行过滤，以防止在分馏步骤（步骤3.5）的管道的堵塞。 </li><li>配制成5毫升10X蔗糖梯度缓冲液：200毫米HEPES（pH值7.6），1米氯化钾，50毫米氯化镁2，100微克/毫升酮，1蛋白酶抑制剂混合物（不含EDTA），100单位/ ml RNA酶抑制剂。 </li><li>使用如在步骤1.1所述制备的60％的溶液，使加入40ml 5％和在1x蔗糖梯度缓冲液的50％蔗糖溶液。 </li><li>使用随机提供的梯度制造商的标记块，以纪念半满点上的每个异质同超速离心管分层（共6个离心管）。使用设置有梯度厂商的层叠装置中，添加5％的蔗糖溶液，直到它到达半满点。然后，从下添加50％的蔗糖溶液，直到友谊赛这两个解决方案之间王牌达到半满点。应特别注意在此步骤中应采取使梯度尽可能相似，因为这是用于获得高重现必需（参见下文）。 </li><li>密封管中设置有梯度壶率纬向帽和密封的管传送到所述管支架上的梯度壶。 </li><li>运行梯度厂商得到线性的5％至50％的梯度。 6线性渐变将在高倾角旋转形成的几分钟。 注意：蔗糖梯度可以立即使用或储存于-80℃下进行6个月。 </li></ol> 2，分离和多聚核糖体的沉降<ol><li>取决于细胞类型，细胞播种到1-5 15厘米的培养皿中（〜15×10 6个细胞）至少一天裂解之前。在实验的当天细胞应为〜80％汇合。 <!-- 注：由于翻译和增殖率是直接最优融合是关键比例8，因此，多聚核糖体应在活跃增殖细胞进行分析（即换算率将显著下降超过汇合的细胞，而细胞的汇合度低可能无法提供足够的材料，以便进一步分析）。此规则的例外可以举例来说如果实验者有兴趣学习接触抑制对翻译的影响作出。然而，细胞不应该被保持在了融合的条件太久，因为这可能对translatome无意影响。 如果转染是必需的，大多数的市售试剂盒的不影响核糖体的水平。因为在转染细胞的天必须在80-90％汇合时，建议繁殖细胞24小时后转染，并从细胞中分离出核糖体48小时转染后约80％汇合。 </li><li>培养细胞用放线菌酮，在100微克/毫升的生长培养基中进行5分钟，在37℃和5的最终浓度％的CO 2;并用含有100微克/毫升放线菌酮溶于10ml冰冷的1×PBS洗涤细胞两次。放线菌酮是一种翻译延伸抑制剂“冻结”在mRNA的核糖体，从而阻止核糖体流失20。 </li><li>刮去细胞轻轻地，在5毫升冰冷的1×PBS中含有100微克/毫升放线菌酮和它们收集在一个50毫升管。重要的是合理地快，而使细胞在冰上的长时间会大幅减少的多核糖体制剂的质量进行此步骤。 </li><li>通过离心分离，在200×g离心5分钟收集细胞，在4℃下</li><li>弃上清，重悬细胞于425微升的低渗缓冲液[（5毫摩的Tris-HCl（pH为7.5），2.5毫摩尔MgCl 2，1.5mM的氯化钾和1x蛋白酶抑制剂混合物（无EDTA）]，加入5微升10毫克/ CHX毫升，1微升的1M DTT，100单位RNA酶抑制剂和涡流5秒，然后加入25μl的10％Trito的Ñ​​X-100（最终浓度0.5％）和25微升10％脱氧胆酸钠（最终浓度0.5％）和涡旋5秒。由于细胞肿胀，在低渗缓冲液将破坏细胞膜，而温和的洗涤剂条件，用于溶解细胞质和内质网相关的核糖体，而不破坏核膜。 </li><li>离心裂解物在16,000 xg下在4℃下7分钟，并转移上清液（约500微升）到一个新的预冷的1.5mL管中。测量OD 260nm处为使用分光光度计每个样品和保持将被用于确定细胞内稳态mRNA水平的裂解物作为输入的10％。淡化输入750μl，以无RNA酶H 2 O，加入750μLTrizol法和液氮冷冻闪光灯。 </li><li>传输包含在预先冷却的转子轮叶蔗糖梯度超速离心管。从蔗糖梯度的顶部取下500微升。调整裂解物，使它们包含相同的外径（10-20 OD在260nm）于500μl的裂解缓冲液（在步骤2.5中所述），并将它们加载到每个蔗糖梯度。 注：重要的是要立即加载裂解液的梯度是很重要的，因为这将提高批判性核糖体制剂的质量。 </li><li>权衡和超离心平衡之前，每个梯度。 </li><li>离心机以222228×g离心（36000转），2小时，在4℃下用SW41Ti转子。 注：为了不破坏蔗糖梯度，应选择“低”刹车选项。 </li></ol> 3，多聚核糖体分离和RNA提取<ol><li>用温暖的RNA酶含有RNA酶ZAP（几喷雾剂）自由水清洗它准备馏分收集器。只有温无RNA酶的水重复此步骤。切换紫外线灯，等待出现绿灯。 </li><li>小心地从转子取出试管，并将其放置在冰上。打开电脑，泵，紫外检测器和馏分收集器。 3毫升/分钟和过滤设置泵升管与追溶液[60％（重量/体积）含0.02％的蔗糖（重量/体积）溴酚蓝]，直到它到达针。一定要看到至少一滴出来的针，并确定了无气泡泵注射器或管进行了介绍。 </li><li>将2ml管中的一小部分收集器。启动分析程序，并设置灵敏度为+ / - 10兆电子伏。设置“时基”为100秒。 </li><li>每个离心管放置到紫外检测器，同时确保该管是在正交的位置。通过扭转管夹持器下方的旋钮刺穿管与针。 </li><li>设置泵以1.5毫升/分钟，收集馏分的时间设定为30秒的馏分收集器（这将导致在〜750μl的各馏分）。把泵在“远程位置”，启动水泵和馏分收集器，并在同一时间开始使用数据采集示踪记录。这将启动蔗糖梯度的向上位移dient和在254纳米的同时检测的UV吸光度。停止尽快的追逐解的首次下降下降在2 ml收集管收集。 </li><li>除跟踪以CSV格式和（一旦步骤3.7完成），在电子表格应用程序，请执行以下操作以确定在紫外吸光度配置文件的每个部分的定位。： <ol><li>选择包含​​相应的吸光度在254 nm处值的列（通道0）。 </li><li>建立吸光度的流畅的线条散点图。 </li><li>在X轴的主单元设置为通过每一级分（30秒）的收集时间的5％-50％蔗糖梯度（〜12ml）中的体积除以得到300（数值。 </li></ol></li><li>加入750微升的Trizol的每个部分和闪光灯冷冻在液氮中的级分。 </li><li>根据制造商的说明书用Trizol协议隔离多核糖体相关和细胞质（2.6）+ RNA。为了提高RNA的产量，进行RNA的PRECIpitation在-80℃30分钟或-20℃过夜。 注：由于RNA的多核糖体组分的析出量可能无法清晰可见，建议添加的载体。加入1μl载体与管的Trizol协议中的RNA沉淀步骤之前。 </li><li>确定（使用方法说明3.6），该部分对应于与&gt; 3核糖体相关的基因，集中这些分数。使用RNA净化试剂盒进行的汇集多核糖体相关和细胞质的RNA（2.6）清理。提交样本的设施使用微阵列或深度测序，以确定全基因组mRNA水平。 如果特定mRNA的翻译需要通过RT-qPCR的被监测，它是推荐使用500ng的RNA（来自含有&gt; 3核糖体或总RNA汇集部分）合成cDNA。 注：与&gt; 3核糖体相关的mRNA被任意设定来表示有效转化基因和含有超过80％的新SYNTHE大小的多肽28,29。包括对应于光（1-2）组分，中等（2-3）和重的多核糖体（&gt; 3）将是有利的，但是这些将增加样本数由2倍（4比2％的条件），从而使实验的成本。尽管它预计该减少深测序和基因芯片分析的成本在未来，应该有利于后者的方式，它是表示，在验证过程中，个别mRNA的分布在各个部分进行监控。 </li></ol> 4，全基因组mRNA翻译的分析<ol><li>安装R，Bioconductor的和anota包： <ol><li>安装R（从r-project.org下载），并开始一个R会话。 注：R是适用于所有操作系统和anota将运行于所有的人。 </li><li> Bioconductor的安装（bioconductor.org）。这是由DO推出的- R的代码是通过R-端子（ 如在R控制台在Windows解释朔伊布勒一下在R快捷键）。 Bioconductor的安装通过键入（在R-末端）： 源（“http://bioconductor.org/biocLite.R”） biocLite（） </li><li>通过键入（在R-端子）安装anota Bioconductor的包（和qvalue包anota需要）： 源（“http://bioconductor.org/biocLite.R”） biocLite（C（“anota”，“qvalue”）） </li><li>测试已成功安装的软件包，并通过键入（在R-端子）打开anota说明书： 库（“anota”） 小插曲（“anota”） </li><li>注意：对于那些在anota包使用的所有功能的更多帮助可以在anota网页（http://www.bioconductor.org/packages/release/bioc/html/anota.html）或使用被发现在河的帮助功能，例如，以取得该anotaPerformQc功能的帮助去到R-TErminal和类型（注意，这本anota包被加载时，只适用）： 库（“anota”）＃加载anota包 ？anotaPerformQc＃这个函数打开的帮助 </li></ol></li><li>进口数据为R： <ol><li>准备表达数据进行分析。数据应预先进行处理（ 例如，归一化和质量控制）相对于被用于测量mRNA水平的技术。输入的值必须登入改造，最常见的为log 2。编译一个表的所有的多核糖体相关的RNA样品，我为人人胞浆RNA样品的数据。第一栏应包含基因标识符后跟每个样本的一个数据列;在第一行应包含名称为样品。该表具有相同的采样顺序和相同的基因顺序是至关重要的。将文件保存为名为“myPolysom​​eData.txt”和“myCytosolicData.txt”制表符分隔的文本文件。 </li><li>在这个例子中两个示例类使用（控制或患病），每类3个重复，从而产生6个样品用这个命令：C1，C2，C3，D1，D2，D3在这两个myCytosolicData.txt和myPolysom​​eData.txt文件。 Anota要求每个条件至少重复3次，当有两个示例类。这些应该是独立的生物学重复。 </li><li>创建一个包含数据输入文件（myPolysom​​eData.txt和myCytosolicData.txt）的目录。从这个目录开放R。在Windows / Mac上，这可以通过复制一个R快捷键进入该目录，并使用该快捷方式启动R上进行（直接工作，也可以使用下拉菜单更改）。 </li><li>新创建的目录中创建一个名为myCode.R文件，并用文本编辑软件打开它。写的代码在这个文件中。 </li><li>为了将数据加载到R写入如下代码到myCode.R文件（记得每次添加代码后重新保存该文件）。下面是一个循序渐进的-S的代码，但所有代码的TEP的解释也可以写成最初和源函数（运行代码，见下文）只能使用一次： ＃＃加载了anota库 库（anota） ＃＃这将加载输入数据成R dataCyto &lt; - as.matrix（读取read.table（“myCytosolicData.txt”，标题= TRUE，row.names = 1，九月=“ t”的）） dataPoly &lt; - as.matrix（读取read.table（“myPolysom​​eData.txt”，标题= TRUE，row.names = 1，九月=“ t”的）） </li><li>运行代码R中直接输入到R端子： 源（“myCode.R”） </li><li>检查是否已成功通过输入（到R-端子）加载数据： 头（dataCyto）＃将显示dataCyto榜榜首 头（dataPoly） </li></ol></li><li>鉴定差异基因的翻译： <ol><li>生成一个描述矢量样品类别（向量在R中是一个类型的对象）。这个载体应该反映在myPolysom​​eData.txt和myCytosolicData.txt样品秩序，使三个对象有样品的相同顺序。指示anota样品来比较哪个当矢量将被使用。添加以下到myCode.R文件： ＃＃请注意，重复样品具有相同的示例类 ＃＃说明（ 即 “C”或“D”）在此向量。 myPhenotypes &lt; - C（“C”，“C”，“C”，“D”，“D”，“D”） </li><li>执行数据集的质量控制。还有一些需要之前anota可用于分析，以评估质量的措施。这些中详细的anota手册论述。将此代码添加到myCode.R文件并保存： anotaQcOut &lt; - anotaPerformQc（dataT = dataCyto，DATAP = dataPoly，phenoVec = myPhenotypes） anotaResidOut &lt; - anotaResidOutlierTest（anotaQcObj = anotaQcOut） </li><li>通过输入到R端子运行的代码： 源（“myCode.R”） 这会产生一些输出文件，它可以检查的指示，在anota手册。 </li><li>找出差异翻译基因。样品将基于除非它们是由用户（使用“对比度”参数）指定提供给“phenoVec”参数（ 即 “myPhenotypes”矢量）的名称的字母顺序进行比较。添加以下代码，使用里面的“源”命令myCode.R文件，并完成对R-端子，如上所述： anotaSigOut &lt; - anotaGetSigGenes（dataT = dataCyto，DATAP = dataPoly，phenoVec = myPhenotypes，anotaQcObj = anotaQcOut） </li><li>使用帮助anotaGetSigGenes了解如何邻安输出的格式，看看如何选择样本类别键入（在R-端子）来比较： ？anotaGetSigGenes </li><li>过滤器和情节基因中差异翻译。有迹象表明，可以在anotaPlotSigGenes函数内申请办理，并使用帮助将简化这种阈值的自定义组合多个阈值。要选择可靠的基因分析应用minSlope（-0.5），maxSlope（1.5）和slopeP（0.01）的设置。 注意：另外，设置施加到RVM 23,26,30假发现率（FDR）（0.15）和倍数变化（LOG2 [1.5]）可以例如被用于识别差异翻译的基因。其他过滤器，如“selDeltaPT”可以是一个严格的筛选（ 例如，设置selDeltaPT到log2 [1.5]）是有用的。还需要指定哪个比较应进行过滤（通过使用selCont参数）。通过添加下面一行到myCode.R应用所描述的设置文件： anotaSigFiltered &lt; - anotaPlotSigGenes（anotaSigObj = anotaSigOut，selContr = 1，minSlope =（-0.5），maxSlope = 1.5，slopeP = 0.01，maxRvmPAdj = 0.15，minEff = LOG2（1.5），selDeltaPT = LOG2（1.5）） </li><li>通过使用源函数从执行分析的R端子，如上所述。这也将产生一个图形输出。检查这个输出是一个很好的起点，以评估分析的性能和识别任何必要的更改设置。 </li><li>产生一个输出表。下面的代码添加到myCode.R文件： write.table（anotaSigFiltered $ selectedRvmData，文件=“MySignificantGenes.txt”，九月=“ t”的） </li><li>用在R-端子源函数运行的代码。在结果表中的列在帮助中anotaPlotSigGenes功能进行了说明。 </li></ol></li></ol>

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本文介绍了一种行之有效的多聚核糖体分馏协议随后在哺乳动物细胞捕获在基因组范围内的平移活动的质变和量变的内部开发的分析方法。在成功完成该协议特别要注意：1）细胞融合（如增殖率和养分的有效性与相关mRNA的翻译活性，可影响translatome的组成，细胞汇合应该是跨重复，实验条件一致）， 2）迅速裂解细胞（尽管放线菌酮和RNA酶抑制剂的缓冲液的存在下，裂解应该是迅速和裂解，以防止RNA降解和多核糖体的解离后立即细胞提取物应覆盖在蔗糖梯度），3）梯度制剂（以确保高重复性的数据，蔗糖梯度应采用梯度壶和SPE准备CIAL护理应处理它们时）服用。 除了研究的变化平移活动，该协议可以用于分离的核糖体相关蛋白复合物，并建立它们的生理功能。为此，水平和各种核糖体相关蛋白的磷酸化状态可通过TCA沉淀测定，随后通过Western印迹法，而核糖体相关蛋白复合物可从梯度级分进行免疫沉淀和Western印迹或质谱分析。这种技术的缺点是速度慢梯度分数的方法可能会导致甚至紧紧结合蛋白的结合动力学都在快速关联/解离解离。关联到新合成的多肽的因素是典型的例子。新合成的多肽的新兴构成的核糖体可以使用化学交联剂如3核糖体相关的蛋白质复合物被固定-1,3&#39; -二硫代双[sulfosuccinimidylpropionate]（DTSSP）31。这种方法，发现该受体的活化的蛋白激酶C 1（RACK1）/ C-Jun N-末端激酶（JNK）/真核翻译延伸因子1A2（EEF1A2）络合物调控新合成的多肽的降解响应于强调27。此外，类似的方法在研究显示，蛋白激酶C BII（PKCbII）是由RACK1 32和活化的mTOR复合物2（mTORC2的）招募到核糖体上出现的地方磷酸新合成的多肽的AKT和调节核糖体，使用其稳定性33,34。 多核糖体分离方法接着anota分析的主要限制是：1）为一个相对高数量的细胞（〜15×10 6细胞），2）缺乏的位置信息有关的核糖体上给定的mRNA分子的定位，和3有关细胞和分子杂）问题均质性正常和肿瘤组织。有关所需细胞数量的问题可以通过调整相应monosomes细胞，其数额限制与那些从高丰度细胞中获得（ 例如 HeLa细胞），35（80S）吸收光谱峰得到解决。核糖体剖析技术（见下文）可以被用来确定在给定的mRNA分子的核糖体的确切位置，而与组织异质性对从复杂的系统，例如人类组织获得的基因表达变化的解释混杂影响的问题进行讨论详细...发布的韭菜和楼层36。 最近，一种新的核糖体分析技术的开发，其中核糖体保护的片段（补遗）是由RNA酶I处理生成和深度测序分析22。这种技术允许确定在一个单核苷酸分辨率核糖体的位置，从而提供前所未有UNPRecedented见解核糖体的生物。例如，核糖体分析可以被用于测定核糖体密度对一个给定的mRNA分子或分子的鉴定是影响翻译起始速率，例如替代的起始位点，起始于非八月密码子和调控元件如uORFs。不过，也有限制核糖体分析的准确估计mRNA的翻译效率的能力，一些方法学的限制。这些包括通过随机片段化和RNA酶I消化引入独立的偏差，由翻译抑制剂（ 如伸长抑制剂如依米丁和放线菌酮有可能诱发在翻译起始位点的核糖体积累）引入偏倚，有大量的假阳性和假阴性的结果相关联的用TE分数以及它们的预测不准确的读取从蛋白质编码mRNA的37，其起源。也许是最重要的，而核糖体仿形允许直接识别一个给定的mRNA分子的核糖体的位置，即与给定的mRNA相关的核糖体的数目进行标准化超过那些在随机分散的mRNA的观察读取补遗（核糖体相关的基因）（总频率间接估计的mRNA）。例如，在4“B”的mRNA分子（BA，BB，BC和BD）是由4核糖体在位置1，2，3和4中，在核糖体分析技术的一个固有缺点占用一个简单的设置将不会允许这样一个场景，所有4核糖体与mRNA的巴关联只在位置1，2，3，4和地方BA，BB，BC和BD的mRNA分别在位置1，2占用一个核糖体的方案之间的区别，3，和4，分别为。相反，在多核糖体分馏，多核糖体的完整性被保留，从而允许具有定义的核糖体的数目（ 图1）相关联的mRNA池隔离。此导入多核糖体分馏和核糖体仿形之间蚂蚁区别表明，而前者的方法可以用来直接在MRNP比较的mRNA，轻和重的多核糖体级分，后一方法可能会失败，以捕获由mRNA的变化所引起的translatome，从过渡轻到重多聚核糖体，而高估了那些从MRNP部分转向沉重多聚核糖体的贡献。上述方法之间的这些差异的生物学意义是通过展示的mRNA，如那些eIF4E的敏感的一个子集的翻译激活大量数据中强调，从光过渡到重多聚核糖体，而另一些，比如那些窝藏5&#39;TOP元素，是直接从核糖自由表达6个游泳池招募到重多聚核糖体。有趣的是，mTOR途径已经显示出伴随的调制“的eIF4E敏感”和5&#39;TOP的mRNAs 1翻译1，因此，在上面讨论的方法上的差异可以解释用核糖体分析38,39和多核糖体分馏24，评估抑制mTOR信号通路对translatome影响的研究之间缔结的明显不一致。 总之，多核糖分馏和核糖体的剖面是主要提供关于与mRNA与核糖体的位置上的mRNA，分别相关的核糖体的数目的信息互补的方法。重要的是，尽管这些方法的缺点和优点，但它仍然重要的是，通过这两种方法获得的全基因组数据被充分分析和功能上和生物化学上进行验证。

的调控网络控制基因表达已被广泛研究，在过去的二十年。绝大多数集中在转录调控，从而改变在基因组范围内的稳态mRNA水平来确定所谓的“基因表达”这些配置文件的研究工作。最近的研究表明，稳定状态的mRNA水平仅松散地对应于蛋白质组1,2的组合物，从而表明转录后机制，包括mRNA的翻译，在基因表达3,4的调节中发挥着重要作用。事实上，已经估计〜蛋白水平的50％，则按mRNA翻译在永生化小鼠成纤维5的电平来确定。 mRNA的翻译是一个高度管制的过程中，它的mRNA通过核糖体，转运RNA（tRNA基因）的精心策划的行动和辅助因子协同翻译成蛋白质mmonly称为平移因子（TF）6。蛋白质的合成是在哺乳动物细胞中7最耗能的过程，因此全球mRNA翻译速率调整，以适应养分有效性和细胞增殖率8。除了 ​​在全球mRNA的翻译速率，各种细胞外刺激（ 例如，激素和生长因子），细胞内的线索（ 例如氨基酸水平）和不同类型的压力（ 例如，ER应激）诱导的mRNA是的池选择性的变化改变正在翻译（translatome）6。取决于刺激的类型，一些翻译活性，但并不是所有的mRNA表达被显着地受到影响，从而导致所需要的装载了快速的细胞反应6变化的蛋白质组。在translatome这些定性和定量的变化被认为是通过反式作用因子之间的相互作用（介导如 </em&gt;的平移机械，辅助因子或微RNA）与顺式元件（RNA元件或特征）中存在的mRNA 6,9的选定的子集的部件。例如，改变在水平和/或限速翻译起始的活性因子eIF4E与的eIF2基于特定的5&#39;UTR特征6选择性地调节转录物的翻译。 eIF4E与的eIF2所需的mRNA和起始tRNA招募到核糖体，分别为6。在eIF4E的活性增加选择性地支持了mRNA的窝藏长，高度结构化的5&#39;UTRs包括那些编码细胞增殖和存活刺激蛋白，包括细胞周期蛋白，c-myc和Bcl-xL的10的平移。反过来的eIF2的失活导致了全球蛋白质合成关机，同时选择性地向上调节含有短抑制上游开放阅读框架（uORFs）在他们的5&#39;UTRs，如那些编码主吨mRNA的翻译未折叠蛋白反应（ 如 ATF4）的ranscriptional监管。响应于各种刺激，包括营养物，生长因子和激素，雷帕霉素的机械/靶蛋白（mTOR）途径刺激的eIF4E的活性失活的4E-结合蛋白（4E-BP）家族的翻译抑制的，而MAPK途径直接磷酸EIF4E 6,11。反过来，eIF2α蛋白激酶（ 即 PERK，PKR，HRI和GCN2）抑制的eIF2通过磷酸化eIF2α蛋白及其调节亚基响应营养匮乏，ER应激和病毒感染6,12。在转录因子的活性和/或表达的改变，所述平移机械和调控因子包括miRNA的其它组件已经在各种病理状态，包括癌症，代谢综合征，神经和精神疾病以及肾和心血管疾病的13-19观察。总的来说，这些数据表明，转化我chanisms在维持细胞内环境稳定，他们的废止起着多种人类疾病的病因核心作用发挥了举足轻重的作用。 本文中，通过蔗糖密度梯度离心中的哺乳动物细胞，它是用来从多核糖monosomes，核糖体亚基和信使核糖核蛋白颗粒（mRNPs）分开一个协议，用于多核糖体的分馏进行说明。这使得转换效率之间的歧视从翻译很差（带灯光多聚核糖体相关）的mRNA（与重多聚核糖体相关）。在该试验中，核糖体使用的是翻译延伸抑制剂，例如放线菌酮20和胞质提取物通过超离心分离5〜50％线性蔗糖密度梯度固定在所述mRNA的表达。随后的蔗糖梯度分级分离可根据它们结合到核糖体的数目的mRNA的分离。从各馏分中提取的RNA可以被用来确定不同状态之间变化的mRNA的整个梯度分布，由此从顶部到梯度的底部翻译效率增加。 Northern印迹或定量逆转录聚合酶链反应（定量RT-PCR）用于确定mRNA的各馏分的水平。 另外，含重金属多聚核糖体（通常超过3核糖体）组分合并和全基因组多核糖体相关的mRNA水平正在使用微阵列或深度测序来确定。这是最重要强调的是多核糖体相关的mRNA的水平，除了翻译，受影响细胞内的mRNA水平21转录和转录后机制。因此，为了确定使用从多核糖体相关的基因的全基因组数据中换算差异，有必要校正用于从在基因表达途径步骤是transla上游的效果化21。为了允许这样的校正，胞质RNA的制备与来自各样品的多核糖体相关的RNA和基因组范围内的稳态mRNA水平平行被确定21。目前，所谓的“翻译效率”（TE）的分数（ 即多核糖体相关的mRNA的数据和胞质mRNA的数据之间的对数比率），通常采用来校正变化胞质mRNA水平上的翻译效率的影响给出的mRNA 22。然而，在使用TE分数，以确定差分翻译与输入大量的假阳性和假阴性结果因TE分数通常被称为伪相关27的一个数学属性相关联。事实上，从多个实验室的数据集的一项调查表明，这种虚假的相关性分析似乎在变化的translatomes 23时是不可避免的。这促使“分析差分TR的发展<html> anslation“（anota）算法，它也不会从上述缺点23受损。在anota分析回归模型用于计算平移活动的独立胞质RNA水平的措施。然后条件和统计计算之间相比，这种措施。用户具有施加方差收缩的方法，从而提高了统计功效和降低了假阳性结果的发生中具有几个重复24个研究的方案。显著，最近证实，在translatome扰动抓获​​anota，但不TE的分数，关联与变化中的蛋白质25。因此，强烈建议申请anota分析鉴定在基因组范围内的变化在翻译。而anota算法的理论基础进行了详细先前21,23,26讨论，这里重点是如何将它应用在实践中。 ve_content“&gt;除了研究改变在细胞mRNA的翻译活性，这核糖体分馏协议可以被用来分离和生化和功能表征核糖体和多核糖体相关蛋白复合物，这种方法已经被成功地部署在过去，以确定调控新合成的多肽的27和/或所涉及的平移机械部件的磷酸化的稳定络合物。多核糖体分离方法本申请也将被简要地讨论。

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			<td style="width:84px;">MicroDAQ</td>
			<td style="width:119px;">USB-1208FS</td>
			<td>Analysis software attachment</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:269px;">Measurement Computing Data Acquisition Software</td>
			<td style="width:84px;">MicroDAQ</td>
			<td style="width:119px;">TracerDAQ Pro</td>
			<td>Analysis software (Download only)</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:269px;"></td>
			<td style="width:84px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:269px;">Buffers</td>
			<td style="width:84px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:269px;">10X buffer for sucrose gradients:</td>
			<td style="width:84px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">200 mM HEPES (pH7.6)</td>
			<td style="width:84px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">1 M KCl</td>
			<td style="width:84px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">50 mM MgCl2</td>
			<td style="width:84px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">100 &#181;g/ml cycloheximide</td>
			<td style="width:84px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">1x protease inhibitor cocktail (EDTA-free)</td>
			<td style="width:84px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">100 units/ml RNase inhibitor</td>
			<td style="width:84px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:269px;"></td>
			<td style="width:84px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:269px;">Lysis buffer</td>
			<td style="width:84px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">5 mM Tris-HCl (pH7.5)</td>
			<td style="width:84px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="25">
			<td height="25" style="height:25px;">2.5 mM MgCl2</td>
			<td style="width:84px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">1.5 mM KCl&#160;</td>
			<td style="width:84px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">1x protease inhibitor cocktail (EDTA-free)]</td>
			<td style="width:84px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="84">
			<td height="84" style="height:84px;width:269px;">Then add cycloheximide (CHX), DTT, RNAse inhibitor, Triton and Sodium Deoxycholate as indicated in the main text</td>
			<td style="width:84px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
	</tbody>
</table>

polysome fractionation and analysis of mammalian translatomes on a genome-wide scale

mRNA的翻译起着核心作用，基因表达调控和代表在哺乳动物细胞中最耗能的过程。因此，mRNA翻译的调节异常被认为在各种病理状态，包括癌症中发挥了重要作用。核糖体还举办伴侣，这有利于新生多肽的折叠，从而调节功能和新合成的多肽的稳定性。此外，新出现的数据表明，核糖体作为信号分子，它有牵连的各种新合成的多肽的翻译后修饰的，因为它们从核糖体的出现，和/或翻译机器的部件的剧目的平台。本文所用的行之有效的利用蔗糖密度梯度离心法分离的核糖体的方法进行说明。与内部开发的“anota”算法相结合这种方法可以直接测定迪菲的个别的mRNA上的全基因组规模rential翻译。此外，该多功能的协议可以被用于各种生化研究，旨在解剖的核糖体相关蛋白复合物，包括那些在折叠新合成的多肽的降解中发挥中心作用的功能。

mTOR是，负责协调全球蛋白质合成率与养分有效性19蜂窝网络的主要节点。 mRNA翻译主要调节在限速引发步骤6。从事多聚核糖体的核糖体中的比重正与翻译起始率28相关。应用多核糖分馏方法来调查mTOR信号在介导胰岛素对mRNA翻译的作用的作用的一个实例。为此，MCF7人乳腺癌细胞保持在低血清，然后用单独的或与活性位点mTOR抑制剂Torin1组合胰岛素刺激。非刺激的细胞连续保持在低血清，作为对照。 mRNPs，monosome（80S）和多核糖体级分，使用多核糖体分馏法分离。相对于对照细胞，胰岛素诱导的相应梯度组分吸光度的增加到多核糖体，并伴有相应减少的吸光度在monosome分数（ 图1）。这些结果表明，从事多聚核糖体核糖体的比例在胰岛素治疗相比，对照组细胞增加，因此这表明，正如所料，胰岛素刺激全球翻译起始速率。 Torin1逆转胰岛素对吸光度访问的影响（ 图1），从而确证了研究结果，即mTOR信号在介导胰岛素对翻译机器19的影响起主要作用。 在此基础上无法避免的梯度准备不一致为宗旨，提出了问题就用多核糖体分离方法22获得的数据的可重复性。为了实证检验这种潜在的有害的问题，细胞质和重型多核糖体相关的RNA（带4多核糖体相关基因）进行分离<html>从单独用胰岛素或胰岛素与Torin1由4个独立的生物学重复（ 图2）的组合处理过的MCF7细胞。胰岛素和Torin1对胞质和在每个重复沉重的多核糖体相关的mRNA的组合物的效果是在使用微阵列的方法全基因组规模来确定。以确定的多核糖体分离方法的主要成分分析（PCA）是适用的可重复性。这种分析表明，属于各条件的样品紧密地定位在所述两个第一部件内，而不同的条件下进行良好的分离（ 图2）。这些结果表明，此处所述的多核糖体分离方法是高度可重复性，因此适合研究在全基因组水平的翻译数量和质量的变化。 ad/51455/51455fig1highres.jpg“SRC =”/ files/ftp_upload/51455/51455fig1.jpg“/&gt; 图1。多核糖体访问表示血清饥饿，胰岛素和mTOR信号对MCF7细胞全局翻译的影响。MCF7细胞被剥夺了营养物（保持在0.1％FBS）中的16小时，并用5nM胰岛素（INS）单独使用或处理与250纳米Torin1（INS + Torin1）4小时组合。该连续剥夺营养物质（0.1％FBS）中的未经处理的细胞被用作对照。对应的胞质提取物的5-50％蔗糖梯度沉淀离心。游离核糖体亚基（40S和60S），monosomes（80S），并在多核糖体的核糖体的级分的数目表示。 <img alt="图2" fo:content-width="5in" fo:src="/files/ftp_upload/51455/51455fig2highres.jpg" src="/files/ftp_upload/51455/51455fig2.jpg" /> 图2：采用对获得全基因组数据olysome分析是高度可重复的。MCF7细胞进行处理， 如图1。胞质和多核糖体相关的RNA（&gt; 3核糖体）是由4个独立的生物学重复和它们的基因组范围的表达水平提取使用GeneTitan阵列（Affymetrix公司）进行测定。 PCA被用来评估所得到的数据的可再现性。显示的是前两个主成分分析组件所有的治疗（T1 =托林1; CTRL =控制;文件=胰岛素），RNA的起源（C =胞浆，P =多核糖体相关）和复制。从相同的条件和RNA的起源样本被紧密定位的指示高的重现性。

Watch this Scientific Journal Video about Polysome Fractionation and Analysis of Mammalian Translatomes on a Genome-wide Scale at JoVE.com

Polysome Fractionation and Analysis of Mammalian Translatomes on a Genome-wide Scale

核糖体蛋白质合成中发挥核心作用。用蔗糖密度梯度离心多核糖体（核糖体）分离可直接测定在基因组范围内个人mRNA的翻译效率。此外，可用于核糖体和多核糖体相关的因素，例如伴侣分子和信号转导分子生化分析此方法。

多聚核糖体分离和哺乳动物Translatomes分析在基因组范围内

mRNA translation plays a central role in the regulation of gene expression and represents the most energy consuming process in mammalian cells. ...

polysome-fractionation-analysis-mammalian-translatomes-on-genome-wide

Research

JoVE Journal

Biology

68.0K 次观看.  McGill University. 核糖体蛋白质合成中发挥核心作用。用蔗糖密度梯度离心多核糖体（核糖体）分离可直接测定在基因组范围内个人mRNA的翻译效率。此外，可用于核糖体和多核糖体相关的因素，例如伴侣分子和信号转导分子生化分析此方法。 

视频: Polysome Fractionation and Analysis of Mammalian Translatomes on a Genome-wide Scale

Intranuclear Microinjection of DNA into Dissociated Adult Mammalian Neurons

Primary neuronal cell cultures are valuable tools to study protein function since they represent a more biologically relevant system compared to immortalized cell lines. However, the post-mitotic nature of primary neurons prevents effective heterologous protein expression using common procedures such as electroporation or chemically-mediated transfection. Thus, other techniques must be employed in order to effectively express proteins in these non-dividing cells.
In this article, we describe the steps required to perform intranuclear injections of cDNA constructs into dissociated adult sympathetic neurons. This technique, which has been applied to different types of neurons, can successfully induce heterologous protein expression. The equipment essential for the microinjection procedure includes an inverted microscope to visualize cells, a glass injection pipet filled with cDNA solution that is connected to a N2(g) pressure delivery system, and a micromanipulator. The micromanipulator coordinates the injection motion of microinjection pipet with a brief pulse of pressurized N2 to eject cDNA solution from the pipet tip. 
This technique does not have the toxicity associated with many other transfection methods and enables multiple DNA constructs to be expressed at a consistent ratio. The low number of injected cells makes the microinjection procedure well suited for single cell studies such as electrophysiological recordings and optical imaging, but may not be ideal for biochemical assays that require a larger number of cells and higher transfection efficiencies. Although intranuclear microinjections require an investment of equipment and time, the ability to achieve high levels of heterologous protein expression in a physiologically relevant environment makes this technique a very useful tool to investigate protein function.

Direct intranuclear injection of cDNA is an effective transfection technique for post-mitotic cells. This method provides high levels of heterologous protein expression from single or multiple cDNA constructs and enables protein function to be studied in a physiologically relevant environment with a variety of single cell assays.

游离成年哺乳动物元DNA的细胞核内内微量注射

Primary neuronal cell cultures are valuable tools to study protein function since they represent a more biologically relevant system compared to ...

科研

生物学

In situ Subcellular Fractionation of Adherent and Non-adherent Mammalian Cells

Protein function is intimately coupled to protein localization. Although some proteins are restricted to a specific location or subcellular compartment, many proteins are present as a freely diffusing population in free exchange with a sub-population that is tightly associated with a particular subcellular domain or structure. In situ subcellular fractionation allows the visualization of protein compartmentalization and can also reveal protein sub-populations that localize to specific structures. For example, removal of soluble cytoplasmic proteins and loosely held nuclear proteins can reveal the stable association of some transcription factors with chromatin. Subsequent digestion of DNA can in some cases reveal association with the network of proteins and RNAs that is collectively termed the nuclear scaffold or nuclear matrix. 
Here we describe the steps required during the in situ fractionation of adherent and non-adherent mammalian cells on microscope coverslips. Protein visualization can be achieved using specific antibodies or fluorescent fusion proteins and fluorescence microscopy. Antibodies and/or fluorescent dyes that act as markers for specific compartments or structures allow protein localization to be mapped in detail. In situ fractionation can also be combined with western blotting to compare the amounts of protein present in each fraction. This simple biochemical approach can reveal associations that would otherwise remain undetected.

In situ Subcellular Fractionation of Adherent and Non-adherent Mammalian Cells

In situ subcellular fractionation of mammalian cells on microscope coverslips allows the visualisation of protein localisation.

原位贴壁和非贴壁的哺乳动物细胞的亚细胞分馏

Protein function is intimately coupled to protein localization. Although some proteins are restricted to a specific location or subcellular compartment, ...

Genome-wide Analysis of Aminoacylation (Charging) Levels of tRNA Using Microarrays

tRNA aminoacylation, or charging, levels can rapidly change within a cell in response to the environment[1]. Changes in tRNA charging levels in both prokaryotic and eukaryotic cells lead to translational regulation which is a major cellular mechanism of stress response. Familiar examples are the stringent response in E. coli and the Gcn2 stress response pathway in yeast ([2-6]). Recent work in E. coli and S. cerevisiae have shown that tRNA charging patterns are highly dynamic and depends on the type of stress experienced by cells [1, 6, 7]. The highly dynamic, variable nature of tRNA charging makes it essential to determine changes in tRNA charging levels at the genomic scale, in order to fully elucidate cellular response to environmental variations. In this review we present a method for simultaneously measuring the relative charging levels of all tRNAs in S. cerevisiae . While the protocol presented here is for yeast, this protocol has been successfully applied for determining relative charging levels in a wide variety of organisms including E. coli and human cell cultures[7, 8].

Genome-wide Analysis of Aminoacylation Charging Levels of tRNA Using Microarrays

We describe a method for microarray analysis to determine relative aminoacylation levels of all tRNAs from S. cerivisiae.

（充电）酰化tRNA的使用微阵列技术水平的全基因组分析

tRNA aminoacylation, or charging, levels can rapidly change within a cell in response to the environment[1]. Changes in tRNA charging levels in both ...

Genome-wide Analysis using ChIP to Identify Isoform-specific Gene Targets

Recruitment of transcriptional and epigenetic factors to their targets is a key step in their regulation. Prominently featured in recruitment are the protein domains that bind to specific histone modifications. One such domain is the plant homeodomain (PHD), found in several chromatin-binding proteins. The epigenetic factor RBP2 has multiple PHD domains, however, they have different functions (Figure 4). In particular, the C-terminal PHD domain, found in a RBP2 oncogenic fusion in human leukemia, binds to trimethylated lysine 4 in histone H3 (H3K4me3)1. The transcript corresponding to the RBP2 isoform containing the C-terminal PHD accumulates during differentiation of promonocytic, lymphoma-derived, U937 cells into monocytes2. Consistent with both sets of data, genome-wide analysis showed that in differentiated U937 cells, the RBP2 protein gets localized to genomic regions highly enriched for H3K4me33. Localization of RBP2 to its targets correlates with a decrease in H3K4me3 due to RBP2 histone demethylase activity and a decrease in transcriptional activity. In contrast, two other PHDs of RBP2 are unable to bind H3K4me3. Notably, the C-terminal domain PHD of RBP2 is absent in the smaller RBP2 isoform4. It is conceivable that the small isoform of RBP2, which lacks interaction with H3K4me3, differs from the larger isoform in genomic location. The difference in genomic location of RBP2 isoforms may account for the observed diversity in RBP2 function. Specifically, RBP2 is a critical player in cellular differentiation mediated by the retinoblastoma protein (pRB). Consistent with these data, previous genome-wide analysis, without distinction between isoforms, identified two distinct groups of RBP2 target genes: 1) genes bound by RBP2 in a manner that is independent of differentiation; 2) genes bound by RBP2 in a differentiation-dependent manner.
To identify differences in localization between the isoforms we performed genome-wide location analysis by ChIP-Seq. Using antibodies that detect both RBP2 isoforms we have located all RBP2 targets. Additionally we have antibodies that only bind large, and not small RBP2 isoform (Figure 4). After identifying the large isoform targets, one can then subtract them from all RBP2 targets to reveal the targets of small isoform. These data show the contribution of chromatin-interacting domain in protein recruitment to its binding sites in the genome.

Here we are presenting a chromatin immunoprecipitation (ChIP) procedure for genome-wide location analysis of protein isoforms that differ in a histone-binding domain. We are applying it to ChIP-Seq analysis to identify the targets of the KDM5A/JARID1A/RBP2 histone demethylase.

采用芯片识别亚型特定的靶基因的全基因组分析

Recruitment of transcriptional and epigenetic factors to their targets is a key step in their regulation. Prominently featured in recruitment are the ...

Mutagenesis and Functional Analysis of Ion Channels Heterologously Expressed in Mammalian Cells

We will demonstrate how to study the functional effects of introducing a point mutation in an ion channel. We study G protein-gated inwardly rectifying potassium (referred to as GIRK) channels, which are important for regulating the excitability of neurons. There are four different mammalian GIRK channel subunits (GIRK1-GIRK4) - we focus on GIRK2 because it forms a homotetramer. Stimulation of different types of G protein-coupled receptors (GPCRs), such as the muscarinic receptor (M2R), leads to activation of GIRK channels. Alcohol also directly activates GIRK channels. We will show how to mutate one amino acid by specifically changing one or more nucleotides in the cDNA for the GIRK channel. This mutated cDNA sequence will be amplified in bacteria, purified, and the presence of the point mutation will be confirmed by DNA sequencing. The cDNAs for the mutated and wild-type GIRK channels will be transfected into human embryonic kidney HEK293T cells cultured in vitro. Lastly, whole-cell patch-clamp electrophysiology will be used to study the macroscopic potassium currents through the ectopically expressed wild-type or mutated GIRK channels. In this experiment, we will examine the effect of a L257W mutation in GIRK2 channels on M2R-dependent and alcohol-dependent activation.

We will demonstrate how to study the effect of a single point mutation on the function of an ion channel.

异源表达在哺乳动物细胞离子通道的突变和功能分析

We will demonstrate how to study the functional effects of introducing a point mutation in an ion channel. We study G protein-gated inwardly rectifying ...

Scale-Up of Mammalian Cell Culture using a New Multilayered Flask

A growing number of cell-based applications require large numbers of cells. Usage of single layer T-flasks, that are adequate during small-scale expansion, may become cumbersome, laborious and time-consuming when large numbers of cells are required. To address this need, the performance of a new multi-layered cell culture vessel to facilitate easy scale up of cells from single layered T-flasks will be discussed. The flasks tested are available in 3- and 5-layer format and enable culture and complete recovery of three and five times the number of cells respectively, compared to T-175 flasks. A key feature of the BD Multi-Flask is a mix/equilibration port that allows rapid in-vessel mixing as well as uniform distribution of cells and reagents within and 
between layers of each vessel and consistently produce cells that can be cultured in an environment that is congruent to T-175 flasks.
The design of these Multi-Flasks also allows for convenient pipette access for adding reagents and cells directly into the flasks as well as efficient recovery of valuable cells and reagents and reduces risk of contamination due to pouring. For applications where pouring is preferred over pipetting, the design allows for minimal residual liquid retention so as to reduce wastage of valuable cells and reagents.

Cells play an instrumental and increasing role in research, and the discovery and development of new therapeutics. With this increasing need for greater number of cells we need more efficient and effective ways for growing and harvesting attachment dependent cells. A Multilayered flask with the right features can serve this purpose.

哺乳动物细胞培养，使用一种新的多层瓶中的比例增加

A growing number of cell-based applications require large numbers of cells. Usage of single layer T-flasks, that are adequate during small-scale ...

Analysis of Cell Cycle Position in Mammalian Cells

The regulation of cell proliferation is central to tissue morphogenesis during the development of multicellular organisms. Furthermore, loss of control of cell proliferation underlies the pathology of diseases like cancer. As such there is great need to be able to investigate cell proliferation and quantitate the proportion of cells in each phase of the cell cycle. It is also of vital importance to indistinguishably identify cells that are replicating their DNA within a larger population. Since a cell&prime;s decision to proliferate is made in the G1 phase immediately before initiating DNA synthesis and progressing through the rest of the cell cycle, detection of DNA synthesis at this stage allows for an unambiguous determination of the status of growth regulation in cell culture experiments.
DNA content in cells can be readily quantitated by flow cytometry of cells stained with propidium iodide, a fluorescent DNA intercalating dye. Similarly, active DNA synthesis can be quantitated by culturing cells in the presence of radioactive thymidine, harvesting the cells, and measuring the incorporation of radioactivity into an acid insoluble fraction. We have considerable expertise with cell cycle analysis and recommend a different approach. We Investigate cell proliferation using bromodeoxyuridine/fluorodeoxyuridine (abbreviated simply as BrdU) staining that detects the incorporation of these thymine analogs into recently synthesized DNA. Labeling and staining cells with BrdU, combined with total DNA staining by propidium iodide and analysis by flow cytometry1 offers the most accurate measure of cells in the various stages of the cell cycle. It is our preferred method because it combines the detection of active DNA synthesis, through antibody based staining of BrdU, with total DNA content from propidium iodide. This allows for the clear separation of cells in G1 from early S phase, or late S phase from G2/M. Furthermore, this approach can be utilized to investigate the effects of many different cell stimuli and pharmacologic agents on the regulation of progression through these different cell cycle phases.
In this report we describe methods for labeling and staining cultured cells, as well as their analysis by flow cytometry. We also include experimental examples of how this method can be used to measure the effects of growth inhibiting signals from cytokines such as TGF-&beta;1, and proliferative inhibitors such as the cyclin dependent kinase inhibitor, p27KIP1. We also include an alternate protocol that allows for the analysis of cell cycle position in a sub-population of cells within a larger culture5. In this case, we demonstrate how to detect a cell cycle arrest in cells transfected with the retinoblastoma gene even when greatly outnumbered by untransfected cells in the same culture. These examples illustrate the many ways that DNA staining and flow cytometry can be utilized and adapted to investigate fundamental questions of mammalian cell cycle control.

Determining the cell cycle position of a population of cells, or understanding how signals affect proliferation, can be readily measured by flow cytometry using this protocol. We report a simple experimental approach to staining cells and quantifying their position in the cell cycle.

在哺乳动物细胞中细胞周期位置分析

The regulation of cell proliferation is central to tissue morphogenesis during the development of multicellular organisms. Furthermore, loss of control of ...

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

ChIPseq is a widely used technique for investigating protein-DNA interactions. Read density profiles are generated by using next-sequencing of protein-bound DNA and aligning the short reads to a reference genome. Enriched regions are revealed as peaks, which often differ dramatically in shape, depending on the target protein1. For example, transcription factors often bind in a site- and sequence-specific manner and tend to produce punctate peaks, while histone modifications are more pervasive and are characterized by broad, diffuse islands of enrichment2. Reliably identifying these regions was the focus of our work.
Algorithms for analyzing ChIPseq data have employed various methodologies, from heuristics3-5 to more rigorous statistical models, e.g. Hidden Markov Models (HMMs)6-8. We sought a solution that minimized the necessity for difficult-to-define, ad hoc parameters that often compromise resolution and lessen the intuitive usability of the tool. With respect to HMM-based methods, we aimed to curtail parameter estimation procedures and simple, finite state classifications that are often utilized.
Additionally, conventional ChIPseq data analysis involves categorization of the expected read density profiles as either punctate or diffuse followed by subsequent application of the appropriate tool. We further aimed to replace the need for these two distinct models with a single, more versatile model, which can capably address the entire spectrum of data types.
To meet these objectives, we first constructed a statistical framework that naturally modeled ChIPseq data structures using a cutting edge advance in HMMs9, which utilizes only explicit formulas-an innovation crucial to its performance advantages. More sophisticated then heuristic models, our HMM accommodates infinite hidden states through a Bayesian model. We applied it to identifying reasonable change points in read density, which further define segments of enrichment. Our analysis revealed how our Bayesian Change Point (BCP) algorithm had a reduced computational complexity-evidenced by an abridged run time and memory footprint. The BCP algorithm was successfully applied to both punctate peak and diffuse island identification with robust accuracy and limited user-defined parameters. This illustrated both its versatility and ease of use. Consequently, we believe it can be implemented readily across broad ranges of data types and end users in a manner that is easily compared and contrasted, making it a great tool for ChIPseq data analysis that can aid in collaboration and corroboration between research groups. Here, we demonstrate the application of BCP to existing transcription factor10,11 and epigenetic data12 to illustrate its usefulness.

Our Bayesian Change Point (BCP) algorithm builds on state-of-the-art advances in modeling change-points via Hidden Markov Models and applies them to chromatin immunoprecipitation sequencing (ChIPseq) data analysis. BCP performs well in both broad and punctate data types, but excels in accurately identifying robust, reproducible islands of diffuse histone enrichment.

一种新型的全基因组分析的贝叶斯变点算法的多元ChIPseq数据类型

ChIPseq is a widely used technique for investigating protein-DNA interactions. Read density profiles are generated by using next-sequencing of ...

Genome-wide Gene Deletions in Streptococcus sanguinis by High Throughput PCR

Transposon mutagenesis and single-gene deletion are two methods applied in genome-wide gene knockout in bacteria 1,2. Although transposon mutagenesis is less time consuming, less costly, and does not require completed genome information, there are two weaknesses in this method: (1) the possibility of a disparate mutants in the mixed mutant library that counter-selects mutants with decreased competition; and (2) the possibility of partial gene inactivation whereby genes do not entirely lose their function following the insertion of a transposon. Single-gene deletion analysis may compensate for the drawbacks associated with transposon mutagenesis. To improve the efficiency of genome-wide single gene deletion, we attempt to establish a high-throughput technique for genome-wide single gene deletion using Streptococcus sanguinis as a model organism. Each gene deletion construct in S. sanguinis genome is designed to comprise 1-kb upstream of the targeted gene, the aphA-3 gene, encoding kanamycin resistance protein, and 1-kb downstream of the targeted gene. Three sets of primers F1/R1, F2/R2, and F3/R3, respectively, are designed and synthesized in a 96-well plate format for PCR-amplifications of those three components of each deletion construct. Primers R1 and F3 contain 25-bp sequences that are complementary to regions of the aphA-3 gene at their 5' end. A large scale PCR amplification of the aphA-3 gene is performed once for creating all single-gene deletion constructs. The promoter of aphA-3 gene is initially excluded to minimize the potential polar effect of kanamycin cassette. To create the gene deletion constructs, high-throughput PCR amplification and purification are performed in a 96-well plate format. A linear recombinant PCR amplicon for each gene deletion will be made up through four PCR reactions using high-fidelity DNA polymerase. The initial exponential growth phase of S. sanguinis cultured in Todd Hewitt broth supplemented with 2.5% inactivated horse serum is used to increase competence for the transformation of PCR-recombinant constructs. Under this condition, up to 20% of S. sanguinis cells can be transformed using ~50 ng of DNA. Based on this approach, 2,048 mutants with single-gene deletion were ultimately obtained from the 2,270 genes in S. sanguinis excluding four gene ORFs contained entirely within other ORFs in S. sanguinis SK36 and 218 potential essential genes. The technique on creating gene deletion constructs is high throughput and could be easy to use in genome-wide single gene deletions for any transformable bacteria.

Genome-wide Gene Deletions in Streptococcus sanguinis by High Throughput PCR

An efficient genome-wide single gene mutation method has been established using Streptococcus sanguinis as a model organism. This method has achieved via high throughput recombinant PCRs and transformations.

全基因组基因缺失<em&gt;链球菌血统</em通过高通量PCR

Transposon  mutagenesis and single-gene deletion are two methods applied in genome-wide  gene knockout in bacteria 1,2. Although transposon mutagenesis is ...

Assessment of Selective mRNA Translation in Mammalian Cells by Polysome Profiling

Regulation of protein synthesis represents a key control point in cellular response to stress. In particular, discreet RNA regulatory elements were shown to allow to selective translation of specific mRNAs, which typically encode for proteins required for a particular stress response. Identification of these mRNAs, as well as the characterization of regulatory mechanisms responsible for selective translation has been at the forefront of molecular biology for some time. Polysome profiling is a cornerstone method in these studies. The goal of polysome profiling is to capture mRNA translation by immobilizing actively translating ribosomes on different transcripts and separate the resulting polyribosomes by ultracentrifugation on a sucrose gradient, thus allowing for a distinction between highly translated transcripts and poorly translated ones. These can then be further characterized by traditional biochemical and molecular biology methods. Importantly, combining polysome profiling with high throughput genomic approaches allows for a large scale analysis of translational regulation.

The ability of cells to adapt to stress is crucial for their survival. Regulation of mRNA translation is one such adaptation strategy, providing for rapid regulation of the proteome. Here, we provide a standardized polysome profiling protocol to identify specific mRNAs that are selectively translated under stress conditions.

选择性的mRNA翻译在哺乳动物细胞中的核糖体性能分析评估

Regulation of protein synthesis represents a key control point in cellular response to stress. In particular, discreet RNA regulatory elements were shown ...