Development of the method presented here has been carried out with various sources of funding, including Genome Canada and Genome Quebec, Environment Canada STAGE program and internal NRC funds.

1，16S rRNA基因扩增子文库制备的融合方法<ol><li>解冻的引物（正向，F343-IONA-MIDXX:5&#39;-CCA TCT CAT CCC TGC GTG TCT CCG交流 牛逼的CAG XXX XXX XXX XTA CGG鲁尔GCA GCA的G-3&#39;;反转，R533-IonP1:5&#39;-CCT四氯化碳达GGG CAG TCG GTG AT A TTA CCG CGG CTG CTG的GC-3&#39;;大胆:离子激流专用适配器;斜体字:排序键校准信号强度的测序运行的开始;字体:模板的特异性引物，X ... ×:10碱基对的条形码， 如表1一些条形码序列），2倍HotStartTaq加上主混合物和样品。使用前调匀，除了主结构应该轻轻混合。 </li><li>准备PCR混合物（20微升反应）与0.5微米的反向引物，0.4毫克/毫升牛血清白蛋白（BSA）和1个HotStartTaq加上主结构。加入预混的18.5微升至eACH PCR管。 </li><li>添加一个正向引物（0.5微升20毫米），不同的条形码为每个将要一起测序样品。加入1μl样品（1-10纳克/微升）的PCR管。 </li><li>发生在PCR仪的管子，然后运行以下程序:5分钟预变性95℃; 95℃，25个循环，30秒，55℃30秒，72℃45秒;在72℃下进行10分钟的最终延伸。 PCR产物可以保持在4℃的CO / N或冷冻直至使用。 </li></ol> 2，扩增子的分离纯化，定量和池<ol><li>使用最大可用梳子准备了2％琼脂糖凝胶。加入5微升的6倍的凝胶上样染料对凝胶反应和负载，每个样品通过一个空的分离良好。运行在70 V凝胶50分钟。 </li><li>以凝胶的图片和削减波段（预计规模约250基点:190 bp的产品加63个基点适配器和条形码）用干净的手术刀。 </li><lI&gt;称量切除乐队，并继续与凝胶的提取和纯化的PCR产物（ 如与QIAquick凝胶提取试剂盒）。 </li><li>量化每个PCR产物用的PicoGreen和使稀释液，得到储备液以5×10 9个分子/微升（约1毫微克/微升）。如果一些样品显示出较低的放大，调整稀释至较低浓度，牢记适于后续程序的最低浓度是1.57×10 7个分子/μl的（26点）。 </li><li>池10微升的每个稀释的PCR产物以获得样本的等摩尔池。准备为每个​​计划的测序运行的一个独立的游泳池。汇集的PCR产物可以保存在冰箱中直到使用。 </li></ol> 3，乳液PCR和测序<ol><li>执行乳液PCR方法: <ol><li>淡化汇集PCR产物26日下午在25微升的体积。解冻剂从离子PGM模板套件。 </li><li>准备乳液PCR混合物（试剂盒提供的试剂）在PCR罩和板凳上添加汇集PCR产物与球体颗粒（提供）。调匀，并在过滤器滤芯插入混合物中，用乳化油仔细TOP（提供）。 </li><li>缓慢反向滤筒和负载上的自动乳剂PCR设备（ 例如，离子单键2仪器）。选择合适的方案，并启动程序。 </li></ol></li><li>自动化的乳液PCR完成后，除去从集合管的上清液，并在管的底部取回球体颗粒。悬浮在100μl的洗涤液（试剂盒提供）的领域和需要2.0微升等分图书馆量化。 </li><li>执行库量化。 <ol><li>混合100μl的SSPE缓冲液（150 mM氯化钠，10mM的磷酸钠4，1mM的娜2 -EDTA）与2微升适配器B&#39;秘境（5&#39;-FAM -CTğAGA CTG CCA AGG CAC ACA GGG GAT AGG-3&#39;）探头和2微升适配器A-Cy5信号（5&#39;-Cy5的 -CCA TCT CAT CCC TGC GTG TCT CCG ACT CAG-3&#39;）的探针。加入52微升该混合物到在步骤3.2所采取的2.0微升等分试样，并添加2微升的洗涤溶液中（从模板试剂盒）对剩余的52微升作为空白进行定量。 </li><li>孵育在95℃下2分钟，然后在37℃下持续2分钟。转让1.5 ml离心管的混合物。 </li><li>添加1.0 TEX缓冲液（10毫米的Tris，1 mM的EDTA，0.01％的Triton X-100，pH值8.0）毫升，混匀并离心15,500 xg离心3分钟在室温。除去上清液，留下20微升在每个管中。重复此洗涤步骤两次。 </li><li>加入180微升TEX缓冲区，悬浮沉淀的颗粒转移到500微升量子比特管。 </li><li>使用量子比特装置，测量荧光的FAM和Cy5和计算使用可用的离子社群网站上的计算器正球体的比例。 </li></ol></li><li>丰富的球体颗粒使用自动化富集系统（ 例如，离子一键捕获系统）正球（含扩增DNA）的剩余部分。 <ol><li>移液管的试剂在所提供的8孔条中的适当的孔中:好1:从步骤3.2球形颗粒;以及2:预洗MyOne链霉亲和C1珠（13微升）;以及3，4和5:洗涤溶液（在模板试剂盒中提供）;以及6:空;以及7:熔断溶液（125mM的氢氧化钠，0.1％吐温20）;以及8:空。 </li><li>安装在移液臂尖和0.2 ml管的样品采集。启动仪器。在浓缩的结尾，加10微升中和液（提供）。富集的颗粒可以保存4℃下15天。 </li></ol></li><li>初始化测序仪: <ol><li>连接到测序仪，并准备测序运行计划，指定测序运行的详细信息。 </li><li> INSTAL升的洗涤溶液＃2（在Ion PGM测序试剂盒提供）中，洗涤溶液＃1（350微升的100mM NaOH）和自动pH缓冲溶液（设置）。 </li><li>启动初始化程序，并在出现提示时在各自的50ml试管中添加的dATP，三磷酸dCTP和dTTP的核苷酸（提供）。拧管到测序仪，并继续初始化程序。当初始化完成后，立即开始运行程序。 </li></ol></li><li>制备的样品进行测序，并加载芯片: <ol><li>通过在15,500 XG离心1.5分钟收集来自步骤3.4在管底部的富氧球体。除去上清液离开正好3微升。 </li><li>加入3μL测序引物（在测序试剂盒提供），吹打起来调匀上下悬浮颗粒。孵育在95℃下2分钟，然后在37℃下持续2分钟。 </li><li>加入1μl聚合酶（提供），拌匀incub的吃在RT 5分钟。继续加载在30分钟内对测序芯片酶球体混合物。 </li><li>在培养过程中，加载的编曲测序芯片进行芯片的质量检查。通过离心除去从芯片的液体和通过缓慢移液向下酶球体混合物（7微升），并避免在芯片中引入的气泡的加载在芯片中的样本。 </li><li>离心芯片三次，在微量离心1分钟。改变芯片在每个离心的方向和通过上下吹打在每次运行之间混合。 </li><li>装载仪器的芯片，并开始运行。 </li></ol></li></ol> 4，基本序列数据分析<ol><li>连接到定序的数据服务器并下载fastq文件。创建一个制表符分隔的"寡"含底漆和条形码信息（参见示例见表1）文件。从MOT下载Greengenes参考文件许网站（ <a href="http://www.mothur.org/wiki/Taxonomy_outline">http://www.mothur.org/wiki/Taxonomy_outline</a> ）。 </li><li>启动Mothur并进行分析: <ol><li>使用下面的命令转换为fastq文件到FASTA和质量文件:fastq.info（fastq = test.fastq） </li><li>确定每个序列的组成员，并使用以下命令修剪的顺序:trim.seqs（FASTA = test.fasta，寡= barcode.txt，QFile时= test.qual，qwindowaverage = 20，qwindowsize = 50，= MINLENGTH 150， keepforward = T） </li><li>各种选项可根据所需的严格性来修改</li><li>使用下面的命令进行分类的greengenes分类序列:classify.seqs（FASTA = test.trim.fasta，方法=旺，组= test.groups，模板= gg_99_otus.fasta，分类= gg_99_otus.tax，截止= 50） </li></ol></li></ol>

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The authors have nothing to disclose.

<html>这里介绍的方法是简单的和便宜的，并允许许多实验室访问宏基因组测序的能力。虽然它取决于所采用的测序平台，一旦文库构建很少的手工操作时间是必需的，与大多数的过程中被自动化。对于这里所用的测序平台（离子洪流PGM），该完整的程序可以在工作两天进行。在编写（2013年9月）的那一刻，与上文所详述的例子中，试剂成本如下:PCR检测36个样品的扩增:25元，凝胶净化和的PicoGreen的DNA的36个样品定量:125美元，乳液PCR方法一池扩增子样品:$ 150测序试剂:250元，共计550元或15元的样品或0.0015美元每质量过滤读取。此价格不包含仪器的服务合同，仪器折旧，技术人员的工资和实验室空间使用情况。 帐篷"&gt;其中最重要的步骤是泳池的所有产品的等摩尔比，以便检索相似数目的读取为各样品。的PicoGreen定量在这里使用的，但其他的方法可能是合适的，但较不准确（ 例如，紫外定量，基于凝胶的量化），即使这样做是最精确的定量和池，有在每个样品中读取数一些可变性，并在典型的运行在表2中详述的，其范围是从4380到32750读出，以平均10338读取，如果处理大量样品（大于40-50）的，单柱凝胶纯化可以通过凝胶纯化来代替在使用平板或纯化珠用严格的尺寸切断（ 例如，AMPure珠） 。 到目前为止，最常用的下一代测序技术的16S rRNA基因是454在这个协议中所使用的离子激流测序技术是概念上非常类似到454和这两种技术都容易产生相同类型的排序错误。不足为奇的是，它表明，离子激流测序导致测序结果非常相似，454测序10。近年来，许多研究人员研究利用Illumina的技术的16S rRNA基因扩增子测序18,19。在任何情况下，这将是很容易通过改变融合引物的序列以匹配所需要的这些测序技术的适配器和条形码一样，在该方法中最近描述的，以适应当前的协议，用于其他的台式测序仪一样的Illumina MiSeq或454 GS小型对于Illumina的MiSeq 19。另外，研究人员可以按照步骤1和2在这里详细的协议，并发送汇集扩增到乳液PCR和测序将进行测序中心。 16S rRNA基因的读取进行修整和归类使用Mothur，但许多其它的分析，可以执行上16S rRNA基因的扩增子。例如，β多样性可以通过计算在使用中列出的步骤每个样本对之间的Unifrac距离进行评估<a href="http://unifrac.colorado.edu/">http://unifrac.colorado.edu/</a> 20。阿尔法多样性指数和各样品的业务分类学单元的数目可以使用工具内QIIME像AmpliconNoise 21或使用由Huse 等22和可用的内Mothur概述的过程来计算。 这里所用的引物扩增的可变区3和4的16S rRNA基因，但是许多其他区域可以被定位的。在本研究中，16S rRNA基因是从植物材料中扩增和引物的选择是为了避免叶绿体16S rRNA基因23,24的扩增。有各种各样的变化是在产品长度，分类能力和有效性25,26的术语可用的其它引物。然而，在所有的情况下200-400 bp的读出的16S rRNA基因不能可靠归类在种的水平，并分析仅限于属和更高的分类学水平。如果需要物种水平上的信息，如cpn60和的rpoB基因27,28其它基因可能是更合适的。未来大幅下降的测序，并增加对分析工具的权力的成本可能会使得人们能够通过元基因组鸟枪取代16S rRNA基因序列，但在那之前的16S rRNA基因测序仍然环境微生物的黄金标准。

宏基因组测序是一个非常强大的技术，因为它的目标包含了环境样品中的遗传信息的全部内容。有不同口味的宏基因组测序，包括鸟枪法测序，大插入库和扩增子测序。扩增子的测序提供了相对便宜，快速，能够产生读取从可大致排列的单个基因组区域的优点。此外，数据分析的工作流程的扩增子测序大多标准化。然而，因为它是基于PCR技术，它具有所有相关的不完全特异性的，不完整的覆盖和引物的偏见施力1,2，这使得该方法的半定量的最好的。几个基因组区域可以有针对性的扩增子测序，包括功能基因，但最流行的选择是使用标记基因如16S rRNA基因生成的社区形象。传统上，16S rRNA基因的扩增子sequencing进行了使用劳动力密集的技术，其中包括克隆在大肠杆菌大肠杆菌 ，菌落采摘和质粒提取，随后用Sanger测序对分离的质粒，并因此，大多数研究分析每个样品少于100个克隆。下一代测序带来两个主要的进步:大规模并行化的测序反应，而最重要的是，对模板的克隆分离，而无需插入的基因片段在宿主中。这极大地简化了16S rRNA基因扩增子测序，这是现在回来许多环境微生物学研究的常规功能，造成了"复兴"的16S rRNA基因扩增子测序3。 由于罗氏454测序于2005年4问世，其他几个新一代测序技术已经出现在市场上（ 如 Illumina公司，实心，PacBio）。最近，推出台式序列RS带到小型实验室的测序能力以前仅限于大测序中心。五台式机是目前可供选择:454 GS少年，离子激流个人基因组机（PGM）和质子，以及Illumina的MiSeq和NextSeq 500虽然所有这些音序器提供每少跑和每美元减少基地读取比大多数全大规模测序仪，它们更灵活，快速，而且其低购置和运行成本，使他们负担得起的小型学术实验室。台式测序仪特别适合于扩增子，小基因组和低复杂度的宏基因组测序在环境微生物学研究好，因为这种类型的研究，一般不需要测序的一个极端的深度。例如，人们普遍认为，对于16S rRNA基因测序研究的读取次数，每个样品是不是最重要的，因为〜1,000读取可以生成相同的图案作为多亿读取数据集5。话虽如此，台面下generatio<html> Ñ​​音序器仍然会产生大量的序列数据，以最大产量〜35 MBP（454 GS初级）〜2 GBP（离子洪流PGM），〜10-15 GBP（离子激流腾）〜10 GBP（Illumina的MiSeq）和〜100 GBP（Illumina公司下一步SEQ 500），这是以上对于大多数环境微生物学研究不够。 使用台式测序仪16S rRNA基因扩增新一代测序最近已经应用于各种环境中。例如，所述离子洪流PGM已用于社会铀尾矿该过再循环油砂开采影响沉积物的水产养殖系统的烃污染北极土壤8,9 7，特别高的pH值和低渗透性6，分析和从阿萨巴斯卡河10,11生物膜柳树种植的人类和动物的尸体13-16的污染土壤12和厌氧沼气池17的根际。 jove_content"&gt;在这方面的贡献，我们详细我们的方法使用台式下一代定序（离子激流PGM）进行排序内部16S rRNA基因扩增的DNA提取后，16S rRNA基因使用包含域级细菌引物扩增测序接头和独特，样本特异性序列（条码）的扩增子进行纯化，定量并汇集在等摩尔比的混合样品然后被克隆扩增以乳液PCR和测序。结果序列是使用公开可用的生物信息学工具（分析例如，Mothur）。

<table border="0" cellpadding="0" cellspacing="0" width="544">
	<tbody>
		<tr height="20">
			<td height="20" style="height:20px;width:271px;">Reagent</td>
			<td style="width:145px;">Company</td>
			<td style="width:128px;">Catalog Number</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:271px;">Ion 314 Chip Kit v2</td>
			<td>Life Technologies</td>
			<td style="width:128px;">4482261</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:271px;">Ion PGM Sequencing 200 Kit v2</td>
			<td>Life Technologies</td>
			<td style="width:128px;">4482006</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:271px;">Ion PGM Template OT2 200 Kit</td>
			<td>Life Technologies</td>
			<td style="width:128px;">4480974</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">HotStarTaq Plus Master Mix Kit</td>
			<td>Qiagen</td>
			<td>203646</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Primers and probes</td>
			<td style="width:145px;">IDT</td>
			<td>NA</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Qiaquick Gel Extraction Kit</td>
			<td>Qiagen</td>
			<td>28704</td>
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		<tr height="21">
			<td height="21" style="height:21px;">BSA 20 mg/ml</td>
			<td>Roche</td>
			<td>10,711,454,001</td>
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		<tr height="21">
			<td height="21" style="height:21px;">Dynabeads MyOne Streptavidin C1</td>
			<td>Life Technologies</td>
			<td>65001</td>
		</tr>
	</tbody>
</table>

next-generation sequencing of 16s ribosomal rna gene amplicons

其中在微生物生态学中的主要问题是"谁在那里？"这个问题可以使用各种工具来回答，但对长期的黄金标准之一，是由序列域级别的PCR产生16S核糖体RNA（rRNA）的基因扩增反应，从基因组DNA扩增。传统上，这是通过克隆和桑格（毛细管电泳）的PCR扩增子的测序进行。新一代测序技术的出现，极大地简化并提高了测序深度16S rRNA基因测序。台式测序仪的引入，现在允许小型实验室进行内部的16S rRNA基因序列在几天之内。这里，使用台式下一代定序为16S rRNA基因的扩增子测序的方法详述。对环境的DNA首先通过PCR，使用含有序列适配器和条形码引物进行扩增。然后它们被耦合到通过乳液PCR方法的球形颗粒。颗粒是升oaded一次性芯片上和芯片插入后进行测序的测序机。的序列的检索fastq格式，过滤，条形码是用来建立样本成员的读取。该过滤和分级读取，然后使用公开可用的工具进一步分析。一个例子的分析，其中读出进行分类的软件包Mothur被赋予在一个分类寻找算法。这里介绍的方法简单，价格低廉，简单，应该帮助小型实验室，以利用从正在进行的基因组革命。

纯化的凝胶后，用PCR扩增25个循环，扩增产物通常是在0.2-10.0的浓度纳克于50μl水中。这可能会发生变化很大，这取决于起始的DNA浓度，样品的类型和所用的纯化试剂盒上。它建议保持PCR循环数，以最低可能的，以避免嵌合体的形成，并降低扩增偏倚，牢记，所有样品应使用周期相同数量的扩增。以最小化多克隆读取数和空球和最大化的读取次数，量子比特率应介于0.1和0.3和FAM荧光应高于200使用314芯片上的离子洪流PGM，平均输出大约是结果在Mothur的滤波后0.3-0.5拿手质量的读取。 表2示出了一些典型的故障的过程的每个步骤中为含36多路复用ENVIRON运行后读取心理样品扩增引物靶向16S的V3-4地区和分析使用Mothur。在Mothur的trim.seqs程序生成一个包含通过质量过滤器和一个"* .scrap.fasta"包含该序列没有随着原因通过质量过滤器的序列的"* .trim.fasta"文件为抑制在序列标题。当条形码中的"寡"的文件提供，该命令也将产生一个"* .groups"文件，该文件包含基于条形码序列中的每个序列的组成员。该classify.seqs过程生成一个".tax.summary"，可以在Excel中打开。此文件包含的分类单位（以行为单位）对每个样品的摘要（中柱）。此文件可用于下游的统计分析和可视化的群落组成在不同分类级别。在".taxonomy"文件中包含了详细的分类归属于每个序列。在所有36个样品的语系/一流水平的平均社会组成如图1所示。 <img alt="图1" fo:content-width="5in" src="/files/ftp_upload/51709/51709fig1highres.jpg" width="500" /> 图1:平均群落组成，在所有样品中的动物门/一流水平。 <table border="0" cellpadding="0" cellspacing="0" width="248"><colgroup><col /><col /><col /></colgroup><tbody><tr height="20"><td height="20" style="height:20px;width:64px;">前进</td><td style="width:139px;"> TACGGRAGGCAGCAG </td><td style="width:47px;"></td></tr><tr height="20"><td height="20" style="height:20px;">条形码</td><td> CTAAGGTAAC </td><td> Sample01 </td></tr><tr height="20"><td height="20" style="height:20px;">条形码</td><td> TAAGGAGAAC </td><td> Sample02 </td></tr><tr heighT ="20"&gt; <td height="20" style="height:20px;">条形码</td><td> AAGAGGATTC </td><td> Sample03 </td></tr><tr height="20"><td height="20" style="height:20px;">条形码</td><td> TACCAAGATC </td><td> Sample04 </td></tr><tr height="20"><td height="20" style="height:20px;">条形码</td><td> CAGAAGGAAC </td><td> Sample05 </td></tr><tr height="20"><td height="20" style="height:20px;">条形码</td><td> CTGCAAGTTC </td><td> Sample06 </td></tr><tr height="20"><td height="20" style="height:20px;">条形码</td><td> TTCGTGATTC </td><td> Sample07 </td></tr><tr height="20"><td height="20" style="height:20px;">条形码</td><td> TTCCGATAAC </td><td> Sample08 </td></tr><tr height="20"><td height="20" style="height:20px;">条形码</td><td> TGAGCGGAAC </td><td> Sample09 </td></tr><tr height="20"><td height="20" style="height:20px;">条形码</td><td> CTGACCGAAC </td><td> Sample10 </td></tr></tbody></table> 表1。实施"寡"的文件中Mothur使用 。 <table border="0" cellpadding="0" cellspacing="0" width="660"><colgroup><col /><col /><col /><col /></colgroup><tbody><tr height="20"><td height="20" style="height:20px;width:363px;"></td><td style="width:67px;"> ＃的读取</td><td style="width:123px;"> ％上一步</td><td style="width:107px;">平均。每个样品</td></tr><tr height="20"><td height="20" style="height:20px;width:363px;">井数</td><td align="center"> 1262519 </td><td> - </td><td align="center"> 35070 </td></tr><tr height="20"><td height="20" style="height:20px;width:363px;">井珠</td><td align="center"> 1114108 </td><td align="center"> 88.20％ </td><td align="center"> 30947 </td></tr><tr height="20"><td height="20" style="height:20px;width:363px;">珠模板</td><td align="center"> 1112746 </td><td align="center"> 99.90％ </td><td align="center"> 30910 </td></tr><tr height="20"><td height="20" style="height:20px;width:363px;">单克隆珠</td><td align="center"> 826805 </td><td align="center"> 74.30％ </td><td align="center"> 22967 </td></tr><tr height="20"><td height="20" style="height:20px;width:363px;">质量好读（输出的音序） </td><td align="center"> 782204 </td><td align="center"> 94.60％ </td><td align="center"> 21728 </td></tr><tr height="40"><td height="40" style="height:40px;width:363px;">通Mothur过滤器（分平均20质量分数超过50个基点的窗口，最小150个基点的长度） </td><td align="center"> 372168 </td><td align="center"> 47.60％ </td><td align="center"> 10,338 </td></tr><tr height="40"><td height="40" style="height:40px;width:363px;">在GreenGenes的动物门级分类（50％置信度阈值） </td><td align="center"> 342171 </td><td align="center"> 91。90％ </td><td align="center"> 9505 </td></tr><tr height="40"><td height="40" style="height:40px;width:363px;">在GreenGenes家庭一级分类（50％置信度阈值） </td><td align="center"> 316512 </td><td align="center"> 92.50％ </td><td align="center"> 8792 </td></tr><tr height="40"><td height="40" style="height:40px;width:363px;">在GreenGenes属级分类（50％置信度阈值） </td><td align="center"> 289899 </td><td align="center"> 91.60％ </td><td align="center"> 8053 </td></tr></tbody></table> 读取从一个典型的奔跑为36环境样品复用在一个离子洪流314芯片产生的表2编号。

Watch this Scientific Journal Video about Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons at JoVE.com

Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons

Characterizing microbial community has been a longstanding goal in environmental microbiology. Next-generation sequencing methods now allow for the characterization of microbial communities at an unprecedented depth with minimal cost and labor. We detail here our approach to sequence bacterial 16S ribosomal RNA genes using a benchtop sequencer.

的16S核糖体RNA基因的扩增子的新一代测序

One of the major questions in microbial ecology is &#8220;who is there?&#8221; This question can be answered using various tools, but one of the ...

next-generation-sequencing-of-16s-ribosomal-rna-gene-amplicons

Research

JoVE Journal

Biology

83.2K 次观看.  National Research Council Canada. Characterizing microbial community has been a longstanding goal in environmental microbiology. Next-generation sequencing methods now allow for the characterization of microbial communities at an unprecedented depth with minimal cost and labor. We detail here our approach to sequence bacterial 16S ribosomal RNA genes using a benchtop sequencer. 

视频: Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons

Fluorescence-microscopy Screening and Next-generation Sequencing: Useful Tools for the Identification of Genes Involved in Organelle Integrity

This protocol describes a fluorescence microscope-based screening of Arabidopsis seedlings and describes how to map recessive mutations that alter the subcellular distribution of a specific tagged fluorescent marker in the secretory pathway. Arabidopsis is a powerful biological model for genetic studies because of its genome size, generation time, and conservation of molecular mechanisms among kingdoms. The array genotyping as an approach to map the mutation in alternative to the traditional method based on molecular markers is advantageous because it is relatively faster and may allow the mapping of several mutants in a really short time frame. This method allows the identification of proteins that can influence the integrity of any organelle in plants. Here, as an example, we propose a screen to map genes important for the integrity of the endoplasmic reticulum (ER). Our approach, however, can be easily extended to other plant cell organelles (for example see1,2), and thus represents an important step toward understanding the molecular basis governing other subcellular structures.

A fundamental quest in cell biology is to define the mechanisms that underlie the identity of the organelles that make eukaryotic cells. Here we propose a method to identify the genes responsible for the morphological and functional integrity of plant organelles using fluorescence microscopy and next-generation sequencing tools.

荧光显微镜筛选和新一代测序:参与细胞器完整性的基因鉴定的有用工具

This protocol describes a fluorescence microscope-based screening of Arabidopsis seedlings and describes how to map recessive mutations that alter the ...

科研

生物学

Depletion of Ribosomal RNA for Mosquito Gut Metagenomic RNA-seq

The mosquito gut accommodates dynamic microbial communities across different stages of the insect's life cycle. Characterization of the genetic capacity and functionality of the gut community will provide insight into the effects of gut microbiota on mosquito life traits. Metagenomic RNA-Seq has become an important tool to analyze transcriptomes from various microbes present in a microbial community. Messenger RNA usually comprises only 1-3% of total RNA, while rRNA constitutes approximately 90%. It is challenging to enrich messenger RNA from a metagenomic microbial RNA sample because most prokaryotic mRNA species lack stable poly(A) tails. This prevents oligo d(T) mediated mRNA isolation. Here, we describe a protocol that employs sample derived rRNA capture probes to remove rRNA from a metagenomic total RNA sample. To begin, both mosquito and microbial small and large subunit rRNA fragments are amplified from a metagenomic community DNA sample. Then, the community specific biotinylated antisense ribosomal RNA probes are synthesized in vitro using T7 RNA polymerase. The biotinylated rRNA probes are hybridized to the total RNA. The hybrids are captured by streptavidin-coated beads and removed from the total RNA. This subtraction-based protocol efficiently removes both mosquito and microbial rRNA from the total RNA sample. The mRNA enriched sample is further processed for RNA amplification and RNA-Seq.

A ribosomal RNA (rRNA) depletion protocol was developed to enrich messenger RNA (mRNA) for RNA-seq of the mosquito gut metatranscriptome. Sample specific rRNA probes, which were used to remove rRNA via subtraction, were created from the mosquito and its gut microbes. Performance of the protocol can result in the removal of approximately 90-99% of rRNA.

核糖体RNA的蚊子肠道宏基因组RNA-seq的枯竭

The mosquito gut accommodates dynamic microbial communities across different stages of the insect's life cycle. Characterization of the genetic capacity ...

Targeted DNA Methylation Analysis by Next-generation Sequencing

The role of epigenetic processes in the control of gene expression has been known for a number of years. DNA methylation at cytosine residues is of particular interest for epigenetic studies as it has been demonstrated to be both a long lasting and a dynamic regulator of gene expression. Efforts to examine epigenetic changes in health and disease have been hindered by the lack of high-throughput, quantitatively accurate methods. With the advent and popularization of next-generation sequencing (NGS) technologies, these tools are now being applied to epigenomics in addition to existing genomic and transcriptomic methodologies. For epigenetic investigations of cytosine methylation where regions of interest, such as specific gene promoters or CpG islands, have been identified and there is a need to examine significant numbers of samples with high quantitative accuracy, we have developed a method called Bisulfite Amplicon Sequencing (BSAS). This method combines bisulfite conversion with targeted amplification of regions of interest, transposome-mediated library construction and benchtop NGS. BSAS offers a rapid and efficient method for analysis of up to 10 kb of targeted regions in up to 96 samples at a time that can be performed by most research groups with basic molecular biology skills. The results provide absolute quantitation of cytosine methylation with base specificity. BSAS can be applied to any genomic region from any DNA source. This method is useful for hypothesis testing studies of target regions of interest as well as confirmation of regions identified in genome-wide methylation analyses such as whole genome bisulfite sequencing, reduced representation bisulfite sequencing, and methylated DNA immunoprecipitation sequencing.

Bisulfite amplicon sequencing (BSAS) is a method for quantifying cytosine methylation in targeted genomic regions of interest. This method uses bisulfite conversion paired with PCR amplification of target regions prior to next-generation sequencing to produce absolute quantitation of DNA methylation at a base-specific level.

有针对性的DNA甲基化分析通过新一代测序

The role of epigenetic processes in the control of gene expression has been known for a number of years. DNA methylation at cytosine residues is of ...

Amplification, Next-generation Sequencing, and Genomic DNA Mapping of Retroviral Integration Sites

Retroviruses exhibit signature integration preferences on both the local and global scales. Here, we present a detailed protocol for (1) generation of diverse libraries of retroviral integration sites using ligation-mediated PCR (LM-PCR) amplification and next-generation sequencing (NGS), (2) mapping the genomic location of each virus-host junction using BEDTools, and (3) analyzing the data for statistical relevance. Genomic DNA extracted from infected cells is fragmented by digestion with restriction enzymes or by sonication. After suitable DNA end-repair, double-stranded linkers are ligated onto the DNA ends, and semi-nested PCR is conducted using primers complementary to both the long terminal repeat (LTR) end of the virus and the ligated linker DNA. The PCR primers carry sequences required for DNA clustering during NGS, negating the requirement for separate adapter ligation. Quality control (QC) is conducted to assess DNA fragment size distribution and adapter DNA incorporation prior to NGS. Sequence output files are filtered for LTR-containing reads, and the sequences defining the LTR and the linker are cropped away. Trimmed host cell sequences are mapped to a reference genome using BLAT and are filtered for minimally 97% identity to a unique point in the reference genome. Unique integration sites are scrutinized for adjacent nucleotide (nt) sequence and distribution relative to various genomic features. Using this protocol, integration site libraries of high complexity can be constructed from genomic DNA in three days. The entire protocol that encompasses exogenous viral infection of susceptible tissue culture cells to integration site analysis can therefore be conducted in approximately one to two weeks. Recent applications of this technology pertain to longitudinal analysis of integration sites from HIV-infected patients.

We describe a protocol for amplifying retroviral integration sites from the genomic DNA of infected cells, sequencing the amplified virus-host junctions, and then mapping these sequences to a reference genome. We also describe techniques to quantify the distribution of integration sites relative to various genomic annotations using BEDTools.

逆转录病毒整合位点的扩增，新一代测序和基因组DNA制图

Retroviruses exhibit signature integration preferences on both the local and global scales. Here, we present a detailed protocol for (1) generation of ...

Efficient Nucleic Acid Extraction and 16S rRNA Gene Sequencing for Bacterial Community Characterization

There is a growing appreciation for the role of microbial communities as critical modulators of human health and disease. High throughput sequencing technologies have allowed for the rapid and efficient characterization of bacterial communities using 16S rRNA gene sequencing from a variety of sources. Although readily available tools for 16S rRNA sequence analysis have standardized computational workflows, sample processing for DNA extraction remains a continued source of variability across studies. Here we describe an efficient, robust, and cost effective method for extracting nucleic acid from swabs. We also delineate downstream methods for 16S rRNA gene sequencing, including generation of sequencing libraries, data quality control, and sequence analysis. The workflow can accommodate multiple samples types, including stool and swabs collected from a variety of anatomical locations and host species. Additionally, recovered DNA and RNA can be separated and used for other applications, including whole genome sequencing or RNA-seq. The method described allows for a common processing approach for multiple sample types and accommodates downstream analysis of genomic, metagenomic and transcriptional information.

We describe an efficient, robust, and cost effective method for extracting nucleic acid from swabs for characterization of bacterial communities using 16S rRNA gene amplicon sequencing. The method allows for a common processing approach for multiple sample types and accommodates a number of downstream analytic processes.

高效的核酸提取和16S rRNA基因序列的细菌群落特征

There is a growing appreciation for the role of microbial communities as critical modulators of human health and disease. High throughput sequencing ...

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

RNA sequencing (RNAseq) is a versatile method that can be utilized to detect and characterize gene expression, mutations, gene fusions, and noncoding RNAs. Standard RNAseq requires 30 - 100 million sequencing reads and can include multiple RNA products such as mRNA and noncoding RNAs. We demonstrate how targeted RNAseq (capture) permits a focused study on selected RNA products using a desktop sequencer. RNAseq capture can characterize unannotated, low, or transiently expressed transcripts that may otherwise be missed using traditional RNAseq methods. Here we describe the extraction of RNA from cell lines, ribosomal RNA depletion, cDNA synthesis, preparation of barcoded libraries, hybridization and capture of targeted transcripts and multiplex sequencing on a desktop sequencer. We also outline the computational analysis pipeline, which includes quality control assessment, alignment, fusion detection, gene expression quantification and identification of single nucleotide variants. This assay allows for targeted transcript sequencing to characterize gene expression, gene fusions, and mutations.

We describe a targeted RNA sequencing-based method that includes preparation of indexed cDNA libraries, hybridization and capture with custom probes and data analysis to interrogate selected transcripts for gene expression, mutations, and gene fusions. Targeted RNAseq permits cost-effective, rapid evaluation of selected transcripts on a desktop sequencer.

有针对性的RNA测序分析表征基因表达和基因组改变

RNA sequencing (RNAseq) is a versatile method that can be utilized to detect and characterize gene expression, mutations, gene fusions, and noncoding ...

Guided Protocol for Fecal Microbial Characterization by 16S rRNA-Amplicon Sequencing

The human intestinal microbiome plays a central role in protecting cells from injury, in processing energy and nutrients, and in promoting immunity. Deviations from what is considered a healthy microbiota composition (dysbiosis) may impair vital functions leading to pathologic conditions. Recent and ongoing research efforts have been directed toward the characterization of associations between microbial composition and human health and disease.
Advances in high-throughput sequencing technologies enable characterization of the gut microbial composition. These methods include 16S rRNA-amplicon sequencing and shotgun sequencing. 16S rRNA-amplicon sequencing is used to profile taxonomical composition, while shotgun sequencing provides additional information about gene predictions and functional annotation. An advantage in using a targeted sequencing method of the 16S rRNA gene variable region is its substantially lower cost compared to shotgun sequencing. Sequence differences in the 16S rRNA gene are used as a microbial fingerprint to identify and quantify different taxa within an individual sample.
Major international efforts have enlisted standards for 16S rRNA-amplicon sequencing. However, several studies report a common source of variation caused by batch effect. To minimize this effect, uniformed protocols for sample collection, processing, and sequencing must be implemented. This protocol proposes the integration of broadly used protocols starting from fecal sample collection to data analyses. This protocol includes a column-free, direct-PCR approach that enables simultaneous handling and DNA extraction of large numbers of fecal samples, along with PCR amplification of the V4 region. In addition, the protocol describes the analysis pipeline and provides a script using the latest version of QIIME (QIIME 2 version 2017.7.0 and DADA2). This step-by-step protocol is aimed to guide those interested in initiating the use of 16S rRNA-amplicon sequencing in a robust, reproductive, easy to use, detailed way.

This manuscript describes a detailed standardized protocol of high-throughput 16S rRNA-amplicon sequencing. The protocol introduces an integrated, uniformed, feasible, and inexpensive protocol starting from fecal sample collection through data analyses. This protocol enables analysis of large numbers of samples with rigorous standards and several controls.

16S rRNA-扩增子测序法对粪便微生物特性的指导协议

The human intestinal microbiome plays a central role in protecting cells from injury, in processing energy and nutrients, and in promoting immunity. ...

Interactome-Seq: A Protocol for Domainome Library Construction, Validation and Selection by Phage Display and Next Generation Sequencing

Folding reporters are proteins with easily identifiable phenotypes, such as antibiotic resistance, whose folding and function is compromised when fused to poorly folding proteins or random open reading frames. We have developed a strategy where, by using TEM-1 &#946;-lactamase (the enzyme conferring ampicillin resistance) on a genomic scale, we can select collections of correctly folded protein domains from the coding portion of the DNA of any intronless genome. The protein fragments obtained by this approach, the so called &#34;domainome&#34;, will be well expressed and soluble, making them suitable for structural/functional studies.
By cloning and displaying the &#34;domainome&#34; directly in a phage display system, we have showed that it is possible to select specific protein domains with the desired binding properties (e.g., to other proteins or to antibodies), thus providing essential experimental information for gene annotation or antigen identification.
The identification of the most enriched clones in a selected polyclonal population can be achieved by using novel next-generation sequencing technologies (NGS). For these reasons, we introduce deep sequencing analysis of the library itself and the selection outputs to provide complete information on diversity, abundance and precise mapping of each of the selected fragment. The protocols presented here show the key steps for library construction, characterization, and validation.

The protocols described allow the construction, characterization and selection (against the target of choice) of a &#34;domainome&#34; library made from any DNA source. This is achieved by a research pipeline that combines different technologies: phage display, a folding reporter and next generation sequencing with a web tool for data analysis.

Interactome: Domainome 图书馆建设、噬菌体展示和下一代测序的验证与选择协议

Folding reporters are proteins with easily identifiable phenotypes, such as antibiotic resistance, whose folding and function is compromised when fused to ...

Tick Microbiome Characterization by Next-Generation 16S rRNA Amplicon Sequencing

In recent decades, vector-borne diseases have re-emerged and expanded at alarming rates, causing considerable morbidity and mortality worldwide. Effective and widely available vaccines are lacking for a majority of these diseases, necessitating the development of novel disease mitigation strategies. To this end, a promising avenue of disease control involves targeting the vector microbiome, the community of microbes inhabiting the vector. The vector microbiome plays a pivotal role in pathogen dynamics, and manipulations of the microbiome have led to reduced vector abundance or pathogen transmission for a handful of vector-borne diseases. However, translating these findings into disease control applications requires a thorough understanding of vector microbial ecology, historically limited by insufficient technology in this field. The advent of next-generation sequencing approaches has enabled rapid, highly parallel sequencing of diverse microbial communities. Targeting the highly-conserved 16S rRNA gene has facilitated characterizations of microbes present within vectors under varying ecological and experimental conditions. This technique involves amplification of the 16S rRNA gene, sample barcoding via PCR, loading samples onto a flow cell for sequencing, and bioinformatics approaches to match sequence data with phylogenetic information. Species or genus-level identification for a high number of replicates can typically be achieved through this approach, thus circumventing challenges of low detection, resolution, and output from traditional culturing, microscopy, or histological staining techniques. Therefore, this method is well-suited for characterizing vector microbes under diverse conditions but cannot currently provide information on microbial function, location within the vector, or response to antibiotic treatment. Overall, 16S next-generation sequencing is a powerful technique for better understanding the identity and role of vector microbes in disease dynamics.

Here we present a next-generation sequencing protocol for 16S rRNA sequencing which enables identification and characterization of microbial communities within vectors. This method involves DNA extraction, amplification and barcoding of samples through PCR, sequencing on a flow-cell, and bioinformatics to match sequence data to phylogenetic information.

下一代 16S rRNA 扩增子测序的蜱菌群鉴定

In recent decades, vector-borne diseases have re-emerged and expanded at alarming rates, causing considerable morbidity and mortality worldwide. Effective ...

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

The human gut is colonized by trillions of bacteria that support physiologic functions such as food metabolism, energy harvesting, and regulation of the immune system. Perturbation of the healthy gut microbiome has been suggested to play a role in the development of inflammatory diseases, including multiple sclerosis (MS). Environmental and genetic factors can influence the composition of the microbiome; therefore, identification of microbial communities linked with a disease phenotype has become the first step towards defining the microbiome&#8217;s role in health and disease. Use of 16S rRNA metagenomic sequencing for profiling bacterial community has helped in advancing microbiome research. Despite its wide use, there is no uniform protocol for 16S rRNA-based taxonomic profiling analysis. Another limitation is the low resolution of taxonomic assignment due to technical difficulties such as smaller sequencing reads, as well as use of only forward (R1) reads in the final analysis due to low quality of reverse (R2) reads. There is need for a simplified method with high resolution to characterize bacterial diversity in a given biospecimen. Advancements in sequencing technology with the ability to sequence longer reads at high resolution have helped to overcome some of these challenges. Present sequencing technology combined with a publicly available metagenomic analysis pipeline such as R-based Divisive Amplicon Denoising Algorithm-2 (DADA2) has helped advance microbial profiling at high resolution, as DADA2 can assign sequence at the genus and species levels. Described here is a guide for performing bacterial profiling using two-step amplification of the V3-V4 region of the 16S rRNA gene, followed by analysis using freely available analysis tools (i.e., DADA2, Phyloseq, and METAGENassist). It is believed that this simple and complete workflow will serve as an excellent tool for researchers interested in performing microbiome profiling studies.

Described here is a simplified standard operating procedure for microbiome profiling using 16S rRNA metagenomic sequencing and analysis using freely available tools. This protocol will help researchers who are new to the microbiome field as well as those requiring updates on methods to achieve bacterial profiling at a higher resolution.

使用两步PCR和下一代16S rRNA基因测序进行微生物群分析

The human gut is colonized by trillions of bacteria that support physiologic functions such as food metabolism, energy harvesting, and regulation of the ...