Authors would like to thank Andrew Bird for the silage samples and Audrey Farbos of the Exeter Sequencing Service for her assistance in preparing DNA sequencing libraries. Exeter Sequencing Service and Computational core facilities at the University of Exeter. Medical Research Council Clinical Infrastructure award (MR/M008924/1). Wellcome Trust Institutional Strategic Support Fund (WT097835MF), Wellcome Trust Multi User Equipment Award (WT101650MA) and BBSRC LOLA award (BB/K003240/1).

1.工地位置<ol><li>收集合适的站点青贮样本，如一个农场。在这里，农场位于Ballydulea，公司科克，爱尔兰（51°51&#39;58.4"N 8°16&#39;48.7"W）。 </li></ol> 2. DNA提取使用商业试剂盒按照制造商的说明进行DNA提取:注。阴性对照，它不含样品，在整个文库制备方法中使用。 <ol><li>添加100 - 400毫克样品以978微升磷酸钠缓冲液和122微升土壤裂解缓冲液中提供的裂解管。 </li><li>通过将裂解管放入均化40秒在6.0米/秒的速度均匀的样品。 </li><li>离心裂解物在14000×g离心15分钟，将上清转移到含有250微升蛋白沉淀溶液（PPS）干净的微离心管中。通过颠倒10次和离心机混合溶液以14,000 xg离心5分钟。 </li><li>上清液加至1mL DNA结合基质在一个干净的15毫升离心管中。通过不断地颠倒试管3分钟混合溶液。使混合物沉降3分钟，然后弃上清的500微升。混合剩余的上清液。 </li><li>转移悬浮液600μL到一个旋转过滤器和离心机在14,000rpm xg离心1分钟。弃去滤液，并与其余的悬浮液重复上述过程。 </li><li>添加洗涤缓冲液500微升的DNA结合矩阵的旋转过滤器内，通过移液混合，然后以14,000 xg离心离心1分钟。 </li><li>弃去滤液和在14000 xg离心再次离心旋转过滤器2分钟，以确保所有的洗涤缓冲液被除去。干燥在23℃的旋转过滤器5分钟。 </li><li>预温热（70℃）的游离DNA酶的水（DES）和重新悬浮于100微升的DES的自旋过滤器内的DNA结合基质。旋转过滤器转移到一个干净的1.5毫升微型离心机涂是和在14000×g离心1分钟以洗脱DNA的离心机。在-20℃保存纯化的DNA，直到进行进一步的分析。 </li></ol> 3. DNA纯化利用DNA纯化珠注:宏基因组文库的制备在此之前，用纯化珠，以确保一个纯DNA样品纯化提取的DNA而获得。 <ol><li>孵育小珠在23℃下在使用前30分钟。 2体积的珠添加到DNA样品孵育在23℃的溶液中5分钟。 </li><li>放置样品到分离磁体5分钟，然后弃上清。用200微升新鲜的80％乙醇（EtOH中）洗涤珠两次。空气干燥该珠10分钟。 </li><li>从分离磁铁取出样品，并添加洗脱缓冲液（EB）的50μL，吹打混匀。 </li><li>孵育在23℃的悬浮液5分钟，之后放置样品放回3分钟分离磁体。 </li><li> TRansfer上清，包含所述DNA，到一个干净的试管中。丢弃的珠子。 </li><li>量化DNA纯化按照四节。 </li></ol> 4.纯化的DNA的定量注意:使用荧光并按照制造商的说明双链（dsDNA）的高灵敏度（HS）测定试剂盒纯化的DNA进行定量。 <ol><li>准备用199工作解决方案:1的比例缓冲区的试剂。 </li><li>将每个DNA标准10μL到工作液190微升。 </li><li>加入纯化DNA的10微升至工作液190微升。最终的体积应为200微升。在23℃孵育标准和DNA样品2分钟。 </li><li>分析使用屏幕上的说明上荧光DNA样本之前的标准。 </li></ol> 5.鸟枪法测序文库制备注意:使用制备鸟枪测序文库使用制造商的说明商业文库制备试剂盒。 <ol><li>稀释DNA样本至0.2纳克/μL使用EB。任何样品这已经是这个浓度以下， 即阴性对照，在其目前的浓度离开了。 </li><li>混合5微升的纯化的DNA与10微升缓冲液和5微升酶混合物。在55℃孵育样品5分钟。 </li><li>添加5μL的中和缓冲液中孵育在23℃的溶液中5分钟。 </li><li>将每个样本特异性测序指数的5μL和15 PCR的μL母液。 </li><li>在热循环仪，孵育样品在72℃3分钟，95℃30秒，前95℃12个循环保持10秒，55℃30秒和72℃30秒。孵育样品最后于72℃5分钟。 </li><li>净化用珠纯化如以前但通过EB的30微升的最终洗脱制备的DNA。 </li></ol> 6.大号ibrary数量与质量检查注:制备的库的数量和质量都使用商业试剂盒和仪器评估。 <ol><li>孵育在23℃的试剂盒组分对于在使用前30分钟。 </li><li>加入DNA 2μL，以缓冲和旋涡2微升1分钟在2000转。 </li><li>降速样品，以确保它在管的底部。 </li><li>将样品管，分析磁带和提示放入仪器，并指示由软件进行分析。 </li></ol> 7. DNA测序<ol><li>利用传送300 bp的配对末端测序45准备和量化的DNA测序文库样品测序服务和顺序。 </li></ol> 8.原始序列数据分析注:使用Linux操作系统，每个程序的命令显示协议的步骤如下。为S管道equence数据分析示于图1。该程序是由分析前的用户安装。这个过程应该单独对每个样品进行。 <ol><li>分析并通过命令行/路径到文件/ fastqc键入可视使用FastQC 46 DNA序列数据，其次是正向和反向原始读取raw_read1.fastq raw_read2.fastq。 </li><li>通过键入-o output_fastqc和-f FASTQ原始读取文件的文件格式指定输出文件夹。 </li><li>查看输出文件（ 图2）。 路径到文件/ fastqc raw_read1.fastq raw_read2.fastq -o OUTPUT_DIRECTORY -f FASTQ。 </li></ol> 9.质量控制微调和过滤数据序列<ol><li>通过键入到命令行Java的罐子/路径到文件/ trimmomatic-0.35.jar运行修整程序，Trimmomatic 28。 </li><li>指定的文件通过键入&#39;PE&#39;配对末端文件。该国16家央公关ocessing单元（CPU）应通过键入-threads 16被用于通过该程序。 </li><li>通过键入原始前锋的名字列出两个文件QC检查和反向读取。输出文件的前缀是键入-baseout青贮确定。 </li><li>通过键入ILLUMINACLIP定义程序的选项:NexteraPE-PE.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:20 CROP:200 HEADCROP:15 MINLEN:36。 </li><li>一旦完成，分析使用FastQC修整序列作为前和输出比较的原始序列数据，以确保修剪已经成功执行。 注:该软件工具，Trimmomatic，修剪去除导致低质量或N基地进一步读取（以下质量3），消除拖尾低质量或N基地（以下质量3）和扫描每读一个4基底较宽滑动窗口。该参数为每个时基的平均质量低于20，然后将降大任读数低于36个碱基长切割设置。最后，15个碱基FR裁剪OM读取每个的头和读了裁剪，以保持200个碱基从读取的开始。进行最后一步测序时长克服一些质量问题（&gt; 200 bp）的读取。这些可用于特定的样品28进行调整。 Java的罐子/path-to-file/trimmomatic-0.35.jar PE -threads 16 raw_read1.fastq raw_read2.fastq -baseout青贮ILLUMINACLIP:NexteraPE-PE.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4 20 CROP:200 HEADCROP:15 MINLEN:36 </li></ol> 10.宏基因组大会<ol><li>合并未成，修整通过输入cat其次未成读取读取; silage_read1_unpaired.fastq silage_read2_unpaired.fastq。通过键入写入文件到一个新的文件&gt; silage_merged_unpaired.fastq 猫silage_read1_unpaired.fastq silage_read2_unpaired.fastq&gt; silage_merged_unpaired.fastq </li><li>要从头组装测序的DNA，通过键入/路径使用铁锹（圣彼得堡基因组汇编）30-file / spades.py。指定16个CPU是通过输入-t 16和宏基因组参数一起使用应适用通过键入--meta。 </li><li>确定修剪向前读取使用-1 silage_read1_paired.fastq和反向由-2 silage_read2_paired.fastq读取。合并后的未成读取由-s silage_merged_unpaired.fastq指定。 </li><li>通过键入-o silage_spades定义输出文件夹。 路径到文件/ spades.py -t 16 --meta -1 -2 silage_read1_paired.fastq -s silage_read2_paired.fastq -o silage_merged_unpaired.fastq silage_spades </li></ol> 11.配对末端读重叠<ol><li>合并对DNA序列的读取采用FLASH（短的快速长度调整读取）29键入到命令行/路径到文件/闪光灯。指定16个CPU应该使用-t 16和输出前缀键入-o青贮饲料中使用。 </li><li>确定修剪通过键入silage_trimmed_R1.fastq silage_trimmed_R2.fastq读 路径到文件/闪光-t 16 -o闪过silage_read1_paired.fastq silage_read2_paired.fastq </li></ol> 12.系统分类<ol><li>类型/路径到文件/海妖，并指定通过键入--db /路径到文件/标准数据库。 </li><li>定义了16个CPU应该通过键入--threads 16中使用，并通过使用--output FLASHed_silage_extendedFrags_kraken.txt确定一个输出文件夹。键入输入文件名; FLASHed_silage.extendedFrags.fastq 路径到文件/海妖--db标准--thread 16 --output FLASHed_silage_extendedFrags_kraken.txt FLASHed_silage.extendedFrags.fastq 注:使用海妖7组装的DNA序列支架的分类主要是针对完成包含所有可用的原核生物基因组序列最近，标准海妖数据库。 </li><li>从输出文件和一个新的文件通过键入切-f2,3 FLASHed_silage_extendedFrags_kraken.txt&gt; FLASHed_silage_extendedFrags_kraken.int转移2和3列</li><li&gt;打开网络浏览器的输出文件。 切-f2,3 FLASHed_silage_extendedFrags_kraken.txt&gt; FLASHed_silage_extendedFrags_kraken.int </li><li>通过键入ktImportTaxonomy导入新的文件到克朗12。通过键入FLASHed_silage_extendedFrags_kraken.int指定输入文件。通过键入-o FLASHed_silage_extendedFrags_kraken.out.html确定输出文件。 路径到文件/ ktImportTaxonomy FLASHed_silage_extendedFrags_kraken.int -o FLASHed_silage_extendedFrags_kraken.out.html </li></ol> 13.功能注释<ol><li>前往MG-RAST 47网站，http://metagenomics.anl.gov/。如果需要注册成为新用户。登录后，点击"上传"按钮。从第10步上传组装支架。 </li><li>一旦文件上传后，点击"提交"，并按照指示，等待分析完成。 </li><li>分析完成后，查看通过 EM发送的链接AIL来自MG-RAST，或者，点击"进步"。目前已完成的作业列表。点击相关作业ID，然后链接到"下载页面"。 </li><li>在下载页面，标题"蛋白质群集90％"下，点击蛋白按钮下载预测蛋白质文件，550.cluster.aa90.faa。 </li><li>作为推定属于特定CAZy酶类蛋白质进行分类，将下载的蛋白质进行比较，以在CAZy数据库48。从文件下载碳水化合物，活性酶数据库（CAZy）为:AA.zip，CE.zip，GH.zip，GT.zip和PL.zip。这些文件分别代表下列酶的类:辅助活动（AA），糖酯酶（CE）糖苷水解酶（GH），糖基转移酶（GT）和多糖裂解酶（PL）。 </li><li>解压缩数据库文件，并通过确定蛋白质相似使用USEARCH UBLAST ALGOR的CAZy数据库的蛋白质注释蛋白质ithm 49。要使用一个bash循环（对于我在* .TXT）通过5数据库.txt文件类型迭代"，在* .TXT为我;做"。 </li><li>通过键入/路径到文件/ usearch8与参数-ublast为了使用ublast算法运行USEARCH。然后在来自MG-RAST"mgmXXXXXX.3.550.cluster.aa90.faa"下载的蛋白质序列文件的名称键入。 </li><li>为了表示对数据库文件中使用类型"-db $ i"和在1E -5指定E-值阈值，键入"-evalue 1E-5"。 </li><li>要终止靶序列后发现搜索和归类，因此蛋白质序列属于靶酶类， 如生长激素，键入"-masaccepts 1"。 </li><li>要定义16个CPU应该使用类型"-threads 16"，并指定输出文件ATAB分隔文本类型"-blast6out"的格式。要确定输出文件类型"$ i.ublast"。要终止在bash循环，TYPE"做" 因为我在* .TXT; 做/路径到文件/ usearch8 -ublast ../mgmXXXXXX.3.550.cluster.aa90.faa -db $ I -evalue 1E-5 -maxaccepts 1 -threads 16 -blast6out $ i.ublast; DONE </li></ol> 14.可视化CAZy注解<ol><li>为了显现从CAZy注解的输出作为一个维恩图，生成蛋白质ID列表用于使用一个bash循环每种酶类。 "在* .ublast为我;做"类型。 </li><li>从输出文件和一个新的文件传输1列，输入"猫$ I |削减-f 1&gt; $ i.list"。 </li><li>终止循环和类型";完成"。 </li><li>在文本编辑器中打开文件.LIST。登陆网站，选择的组数为5，并粘贴到一个单独的盒子每个列表文件的内容。下载所产生的图作为.svg文件。 因为我在* .ublast; 做猫$ I |切-f 1&gt; $ i.list; DONE </li></ol>

The authors have nothing to disclose.

而一个在硅片分析可以得到优异的洞察力是环境样品中存在的微生物群落，这是至关重要的分类学分类表现在与相关的控制关联，并且测序的一个合适的深度已经实现捕获整个执行目前人口51。 对于任何计算分析，有很多途径来实现类似的目标。我们在这项研究中所使用的方法是合适的，简单的方法，已汇聚，实现了一系列的青贮微生物分析的例子 。多种和不断增加数目的生物信息学工具和技术可用来分析宏基因组数据，例如Phylosift 8和MetaPhlAn2 52，这些应之前，调查其相关性样品和分析REQ评价uired 53。宏基因组分析方法是由数据库为可用于分类，测序深度和测序的质量的限制。 在当地，大功率的计算机上执行这里展示的生物信息学处理;然而，基于云的系统，也可提供。这些基于云的服务允许进行必要的计算能力的租金，而无需一个合适的强大的本地工作站的高成本投入。这种方法的一个潜在的应用是其在农业使用前评估青贮以确保没有潜在的有害细菌的存在，因此阻止它们进入食物链。

宏基因组学是从环境样品1中发现的生物群落纯化的DNA的直接分析，最初用于检测沉积物中发现的2培养的细菌。宏基因组已被广泛地用于许多应用，如识别人类微生物3，海洋4内，并且即使对于在咖啡机5开发细菌群落的分析微生物种群进行分类。引进新一代测序技术，造成了更大的测序通量和输出。因此，DNA测序变得更经济6和能够进行测序的深度大大增加，从而使宏基因组学，成为一个强大的，分析工具。 在宏基因组测序的实际，分子方面"前端"的增强推动了中成长可用于系统分类7-9，功能注释10,11和DNA序列数据的可视化表示12,13硅片生物信息学工具。越来越多的使用，测序的原核和真核基因组14允许进一步精度在微生物群落，这是针对测序的基因组15的"后端"参考数据库总是进行的分类。两种主要的方法可以为宏基因组分析通过。 更传统的方法是16S rRNA基因编码细菌基因组的区域的分析。该的16S rRNA高度保守原核生物物种之间呈现，但9超可变区（V1 - V9），它可以用于物种鉴定16所利用。引入再测序（≤300bp的配对末端）允许跨越两个超变区的DNA序列的分析，特别是在V3 - V4区17。在其它测序技术，如牛津纳米孔18和PacBIO 19，进展就允许整个16S rRNA基因被连续测序。 而基于16S rDNA的库提供有针对性的方法来物种鉴定和使低拷贝数的DNA的检测天然纯化的样品内发生，鸟枪测序文库允许检测物种的可能含有要么不是由16S扩增DNA区rRNA基因标记的引物序列使用的，或者是因为模板序列和放大引物序列之间的差异太大20,21。此外，虽然DNA聚合酶有DNA复制的一个高的保真度，可仍然PCR扩增过程中发生基误差，并可能导致在始发物种22的不正确分类这些并入的错误。在模板序列的PCR扩增偏差uences也可以发生;具有高GC含量的DNA序列可以根据在最终的扩增子池表示23和类似人工碱基修饰，如胸腺嘧啶二醇，可以阻止DNA聚合酶导致故障中DNA的扩增序列24。相反，鸟枪测序DNA文库是已经制备使用所有已经从样品中提取并随后进行测序制备之前裂成较短的DNA链长度的纯化的DNA的DNA文库。通过鸟枪测序产生的DNA序列的系统分类更准确相比的16S rRNA扩增子测序25时，虽然所需要的财务成本达成可靠测序深度比扩增子测序26的更大。鸟枪法测序宏基因组学的主要好处是，在样品中的各种基因组测序的区域可用于基因勘探一旦它们已经已分类学分类的27。 宏基因组序列数据由不断增加的生物信息学工具范围进行分析。这些工具能够执行的各种应用中，例如，原始序列数据28的质量控制分析，重叠配对末端的读取29， 从头序列的组件读取到重叠群和支架30,31，分类学分类和可视化顺序读取和顺序组装和7,12,32,33组装序列34,35的功能注释。 青贮，农民从谷类发酵，如玉米（ 玉米 ）生产遍布世界各地，主要是被用作牛饲料。青贮饲料与SP 乳杆菌属细菌治疗。以帮助发酵36但到目前为止，没有在青贮饲料中发现的其他微生物种群的了解有限。该fermentatioÑ过程可导致不希望的和潜在有害的微生物的青贮37内变得普遍。除了酵母和霉菌，细菌在发酵青贮特别适合于厌氧环境，并且更频繁地用在牲畜疾病而非青贮38的降解有关。丁酸菌可从土壤中被无意添加填充青贮筒仓并能够乳酸，厌氧消化的产物进行转换，以丁酸，从而增加了青贮39的pH值时仍然存在。这种增加pH值可导致腐败菌的高涨，通常会是无法维持最佳青贮发酵条件38下的生长。 梭状芽孢杆菌。 ， 李斯特菌。和芽孢杆菌 。值得特别关注的，尤其是在青贮奶牛饲料，作为生存了gastr细菌孢子ointestinal道40可以进入食物链，导致食品变质，并在极少数情况下，动物和人类死亡37,39,41-44。此外，虽然它是难以估计引起青贮变质兽医治疗和牲畜损失的准确的经济影响，它可能是有害的一个农场如果爆发是发生。 这是假设，通过使用宏基因组的方法，我们可以在微生物群体中存在青贮样品中分类和进一步识别与青贮腐败相关的微生物群落将反过来，可能对家畜有不利的影响，使补救行动是青贮前服用是用作食物来源。

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			<td height="21" style="height:21px;width:216px;">FastDNA SPIN Kit for Soil</td>
			<td style="width:128px;">MP Bio</td>
			<td style="width:120px;">116560200</td>
			<td style="width:301px;">DNA Extraction</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">DNA FastPrep</td>
			<td style="width:128px;">MP Bio</td>
			<td style="width:120px;">116004500</td>
			<td>DNA Extraction</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Agencourt AMPure XP beads</td>
			<td style="width:128px;">Beckman Coulter</td>
			<td style="width:120px;">A63880</td>
			<td>DNA Purification</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Elution Buffer</td>
			<td style="width:128px;">Qiagen</td>
			<td style="width:120px;">19806</td>
			<td>DNA Purification</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Qubit Fluorometer</td>
			<td style="width:128px;">Thermo Fisher</td>
			<td style="width:120px;">Q33216</td>
			<td>DNA Quantification</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Qubit dsDNA HS Assay Kit</td>
			<td style="width:128px;">Thermo Fisher</td>
			<td style="width:120px;">Q32854</td>
			<td>DNA Quantification</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Nextera XT DNA Library Prep Kit</td>
			<td style="width:128px;">Illumina</td>
			<td style="width:120px;">FC-131-1024</td>
			<td>Library Preparation</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Nextera XT Index Kit</td>
			<td style="width:128px;">Illumina</td>
			<td style="width:120px;">FC-131-1001</td>
			<td>Library Preparation</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">TapeStation 2200</td>
			<td style="width:128px;">Agilent</td>
			<td style="width:120px;">G2964AA</td>
			<td>DNA Quantification</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">HS D100 ScreenTape</td>
			<td style="width:128px;">Agilent</td>
			<td style="width:120px;">5067-5584</td>
			<td>DNA Quantification</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">HS D100 ScreenTape Reagents</td>
			<td style="width:128px;">Agilent</td>
			<td style="width:120px;">5067-5585</td>
			<td>DNA Quantification</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">TapeStation Tips</td>
			<td style="width:128px;">Agilent</td>
			<td style="width:120px;">5067-5153</td>
			<td>DNA Quantification</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">TapeStation Tubes</td>
			<td style="width:128px;">Agilent</td>
			<td style="width:120px;">401428 and 401425</td>
			<td>DNA Quantification</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">HiSeq 2500</td>
			<td style="width:128px;">Illumina</td>
			<td style="width:120px;"></td>
			<td>DNA Sequencing - provided by a sequencing service</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">High Power Analysis Workstation</td>
			<td style="width:128px;">Various</td>
			<td style="width:120px;"></td>
			<td>Local or cloud based, user preferred system</td>
		</tr>
	</tbody>
</table>

metagenomic analysis of silage

Metagenomics is defined as the direct analysis of deoxyribonucleic acid (DNA) purified from environmental samples and enables taxonomic identification of the microbial communities present within them. Two main metagenomic approaches exist; sequencing the 16S rRNA gene coding region, which exhibits sufficient variation between taxa for identification, and shotgun sequencing, in which genomes of the organisms that are present in the sample are analyzed and ascribed to "operational taxonomic units"; species, genera or families depending on the extent of sequencing coverage. 
In this study, shotgun sequencing was used to analyze the microbial community present in cattle silage and, coupled with a range of bioinformatics tools to quality check and filter the DNA sequence reads, perform taxonomic classification of the microbial populations present within the sampled silage, and achieve functional annotation of the sequences. These methods were employed to identify potentially harmful bacteria that existed within the silage, an indication of silage spoilage. If spoiled silage is not remediated, then upon ingestion it could be potentially fatal to the livestock.

生物信息学处理之前，原始序列读取修整，并使用Trimmomatic软件28被拆除适配器。修剪和过滤步骤后，读取减少到该序列的50％的读取数（ 见表1）。平均基地PHRED得分&gt; 30后的质量控制（ 图2）。 其中有采用FLASH软件29，以产生单个较长的读取重叠区被合并的DNA序列对，非重叠读取被保存在单独的文件中。 45.47％读取（105343）成功地结合。以下的重叠读取采用FLASH的读取，将所得延伸片段使用海妖软件7行细菌系统分类并随后用克朗软件（ 图3）可视化。 图4中可以看到。在宏基因组中最丰富的物种是乳酸杆菌 。 （24％;厚壁菌）， 棒状杆菌属。 （8％;放线菌）， 丙酸杆菌属。 （3％;放线菌）和普雷沃氏菌。 （3％;拟杆菌）。在疾病相关物种动物的健康重要，也观察; 梭状芽孢杆菌。 （1％） 芽孢杆菌属。 （0.6％）， 李斯特菌。 （0.2％）被预测为存在所述青贮样本。 于组装读取进行了功能注释。宏基因组用铲子汇编30使用修剪和过滤装配配对末端和不成读取产生92284支架。为了鉴定纤维素酶，蛋白用的MG-RAST预测并使用碳水化合物-活性酶数据库（CAZy）注释。在97562预测蛋白质，6357被注解为在五个酶类组成CAZy数据库（ 图5）中的一个推定的碳水化合物活性酶。结果显现为使用InteractiVenn软件50表示蛋白质注释包括含有一个以上CAZy酶类注解那些分布的维恩图。这些中，3861被预测具有糖苷水解酶活性，将其进一步的特征，在实验室进行确认的功能。 <img alt="图1" src="/files/ftp_upload/54936/54936fig1.jpg" /> 图1: 生物信息学宏基因组学管道青贮的分析。两种主要的方法是用于调查青贮，系统分类和功能注释的微生物。 <a href="http://ecsource.jove.com/files/ftp_upload/54936/54936fig1large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图2" src="/files/ftp_upload/54936/54936fig2.jpg" /> 图2: 序列质量每基之前和切边适配器去除后。从FASTQC的每个碱基序列的质量的图显示在整个序列的长度的平均PHRED得分读取之前和之后的质量控制。 <a href="http://ecsource.jove.com/files/ftp_upload/54936/54936fig2large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图3" src="/files/ftp_upload/54936/54936fig3.jpg" /> 图3: 分类Classifica固体青贮的细菌微生物组和灰。修剪和重叠序列分类读取FLASH用海妖7进行，随后与瑞典克朗可视化。 <a href="http://ecsource.jove.com/files/ftp_upload/54936/54936fig3large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图4" src="/files/ftp_upload/54936/54936fig4.jpg" /> 图 4: 固体青贮的细菌微生物组的4个最丰富的门类分类级分配。每个班的四个最丰富的门类中的细菌的百分比。厚壁菌门: 梭状芽胞杆菌 （红色）和芽孢杆菌 （深蓝色）;变形菌: 增量/小量 （粉红色），α（淡蓝色）， 伽玛 （橙色）和β（绿松石）;拟杆菌:Flavobacteriia（深蓝色），并Bacteroidia（浅绿色）;放线菌:Coriobacteriia（暗紫色）等放线菌 （深绿色）。 <a href="http://ecsource.jove.com/files/ftp_upload/54936/54936fig4large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图5" src="/files/ftp_upload/54936/54936fig5.jpg" /> 图5: 在Solid青贮微生物组的预测蛋白质组CAZy诠释。维恩图显示CAZy注释五酶类固体微生物青贮的预测蛋白质的分布。 <a href="http://ecsource.jove.com/files/ftp_upload/54936/54936fig5large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always"><tbody><tr><td> ＃读生</td><td rowspan="2"> ＃过滤读取（配对） </TD&gt; <td> ＃过滤读</td><td rowspan="2"> ＃读闪现</td></tr><tr><td> （配对） </td><td> （未成） </td></tr><tr><td> 2374949 X2 </td><td> 231679 X2 </td><td> 1892534 </td><td> 105343 </td></tr></tbody></table> 表1:排序汇总表读。

Watch this Scientific Journal Video about Metagenomic Analysis of Silage at JoVE.com

Metagenomic Analysis of Silage

Metagenomics was used to investigate the microbiome of silage cattle feed. Analysis was performed by shotgun sequencing. This approach was used to characterize the composition of the microbial community within the cattle feed.

青贮的宏基因组学分析

Metagenomics is defined as the direct analysis of deoxyribonucleic acid (DNA) purified from environmental samples and enables taxonomic identification of ...

Research

JoVE Journal

Genetics

18.0K 次观看.  University of Exeter. Metagenomics was used to investigate the microbiome of silage cattle feed. Analysis was performed by shotgun sequencing. This approach was used to characterize the composition of the microbial community within the cattle feed.

视频: Metagenomic Analysis of Silage

Sequential Salt Extractions for the Analysis of Bulk Chromatin Binding Properties of Chromatin Modifying Complexes

Elucidation of the binding properties of chromatin-targeting proteins can be very challenging due to the complex nature of chromatin and the heterogeneous nature of most mammalian chromatin-modifying complexes. In order to overcome these hurdles, we have adapted a sequential salt extraction (SSE) assay for evaluating the relative binding affinities of chromatin-bound complexes. This easy and straightforward assay can be used by non-experts to evaluate the relative difference in binding affinity of two related complexes, the changes in affinity of a complex when a subunit is lost or an individual domain is inactivated, and the change in binding affinity after alterations to the chromatin landscape. By sequentially re-suspending bulk chromatin in increasing amounts of salt, we are able to profile the elution of a particular protein from chromatin. Using these profiles, we are able to determine how alterations in a chromatin-modifying complex or alterations to the chromatin environment affect binding interactions. Coupling SSE with other in vitro and in vivo assays, we can determine the roles of individual domains and proteins on the functionality of a complex in a variety of chromatin environments.

Sequential salt extraction of chromatin bound proteins is a useful tool for determining the binding properties of large protein complexes. This method can be employed to evaluate the role of individual subunits or domains in the overall affinity of a protein complex to bulk chromatin.

序贯盐萃取法分析染色质修饰配合物的体染色质结合特性

Elucidation of the binding properties of chromatin-targeting proteins can be very challenging due to the complex nature of chromatin and the heterogeneous ...

科研

遗传学

Analysis of Termination of Transcription Using BrUTP-strand-specific Transcription Run-on (TRO) Approach

This manuscript describes a protocol for detecting transcription termination defect in vivo. The strand-specific TRO protocol using BrUTP described here is a powerful experimental approach for analyzing the transcription termination defect under physiological conditions. Like the traditional TRO assay, it relies on the presence of a transcriptionally active polymerase beyond the 3&#8242; end of the gene as an indicator of a transcription termination defect1. It overcomes two major problems encountered with the traditional TRO assay. First, it can detect if the polymerase reading through the termination signal is the one that initiated transcription from the promoter-proximal region, or if it is simply representing a pervasively transcribing polymerase that initiated non-specifically from somewhere in the body or the 3&#8242; end of the gene. Secondly, it can distinguish if the transcriptionally active polymerase signal beyond the terminator region is truly the readthrough sense mRNA transcribing polymerase or a terminator-initiated non-coding anti-sense RNA signal. Briefly, the protocol involves permeabilizing the exponentially growing yeast cells, allowing the transcripts that initiated in vivo to elongate in the presence of the BrUTP nucleotide, purifying BrUTP-labelled RNA by the affinity approach, reverse transcribing the purified nascent RNA and amplifying the cDNA using strand-specific primers flanking the promoter and the terminator regions of the gene2.

Analysis of Termination of Transcription Using BrUTP-strand-specific Transcription Run-on TRO Approach

We describe a basic experimental approach for analysis of termination of transcription by RNA polymerase II in vivo using BrUTP by the strand-specific transcription run-on (TRO) approach in budding yeast. This protocol can be extended to study transcription termination by other RNA polymerases both in yeast and higher eukaryotes.

使用BrUTP链特异性转录运行的（TRO）方法终止转录分析

This manuscript describes a protocol for detecting transcription termination defect in vivo. The strand-specific TRO protocol using BrUTP described here ...

Single Molecule Analysis of Laser Localized Psoralen Adducts

The DNA Damage Response (DDR) has been extensively characterized in studies of double strand breaks (DSBs) induced by laser micro beam irradiation in live cells. The DDR to helix distorting covalent DNA modifications, including interstrand DNA crosslinks (ICLs), is not as well defined. We have studied the DDR stimulated by ICLs, localized by laser photoactivation of immunotagged psoralens, in the nuclei of live cells. In order to address fundamental questions about adduct distribution and replication fork encounters, we combined laser localization with two other technologies. DNA fibers are often used to display the progress of replication forks by immunofluorescence of nucleoside analogues incorporated during short pulses. Immunoquantum dots have been widely employed for single molecule imaging. In the new approach, DNA fibers from cells carrying laser localized ICLs are spread onto microscope slides. The tagged ICLs are displayed with immunoquantum dots and the inter-lesion distances determined. Replication fork collisions with ICLs can be visualized and different encounter patterns identified and quantitated.

Lasers are frequently used in studies of the cellular response to DNA damage. However, they generate lesions whose spacing, frequency, and collisions with replication forks are rarely characterized. Here, we describe an approach that enables the determination of these parameters with laser localized interstrand crosslinks.

激光局部补骨脂素加合物的单分子分析

The DNA Damage Response (DDR) has been extensively characterized in studies of double strand breaks (DSBs) induced by laser micro beam irradiation in live ...

Analysis of the c-KIT Ligand Promoter Using Chromatin Immunoprecipitation

Multiple cellular processes, including DNA replication and repair, DNA recombination, and gene expression, require interactions between proteins and DNA. Therefore, DNA-protein interactions regulate multiple physiological, pathophysiological, and biological functions, such as cell differentiation, cell proliferation, cell cycle control, chromosome stability, epigenetic gene regulation, and cell transformation. In eukaryotic cells, the DNA interacts with histone and nonhistone proteins and is condensed into chromatin. Several technical tools can be used to analyze DNA-protein interactions, such as the Electrophoresis (gel) Mobility Shift Assay (EMSA) and DNase I footprinting. However, these techniques analyze the protein-DNA interaction in vitro, not within the cellular context. Chromatin immunoprecipitation (ChIP) is a technique that captures proteins at their specific DNA binding sites, thereby allowing for the identification of DNA-protein interactions within their chromatin context. It is done by fixation&#160;of the DNA-protein interaction, followed by&#160;immunoprecipitation of the protein of interest. Subsequently, the genomic site that the protein was bound to is characterized. Here, we describe and discuss ChIP and demonstrate its analytical value for the identification of the Transforming Growth Factor-&#946; (TGF-&#946;)-induced binding of the transcription factor SMAD2 to SMAD Binding Elements (SBE) within the promoter region of the tyrosine-protein kinase Kit (c-KIT) receptor ligand Stem Cell Factor (SCF).

DNA-protein interactions are essential for multiple biological processes. During the evaluation of cellular functions, the analysis of DNA-protein interactions is indispensable for understanding gene regulation. Chromatin immunoprecipitation (ChIP) is a powerful tool to analyze such interactions in vivo.

使用染色质免疫沉淀分析c-KIT配体启动子

Multiple cellular processes, including DNA replication and repair, DNA recombination, and gene expression, require interactions between proteins and DNA. ...

Generation of Native Chromatin Immunoprecipitation Sequencing Libraries for Nucleosome Density Analysis

We present a modified native chromatin immunoprecipitation sequencing (ChIP-seq) experimental protocol compatible with a Gaussian mixture distribution based analysis methodology (nucleosome density ChIP-seq; ndChIP-seq) that enables the generation of combined measurements of micrococcal nuclease (MNase) accessibility with histone modification genome-wide. Nucleosome position and local density, and the posttranslational modification of their histone subunits, act in concert to regulate local transcription states. Combinatorial measurements of nucleosome accessibility with histone modification generated by ndChIP-seq allows for the simultaneous interrogation of these features. The ndChIP-seq methodology is applicable to small numbers of primary cells inaccessible to cross-linking based ChIP-seq protocols. Taken together, ndChIP-seq enables the measurement of histone modification in combination with local nucleosome density to obtain new insights into shared mechanisms that regulate RNA transcription within rare primary cell populations.

We present a modified native chromatin immunoprecipitation sequencing (ChIP-seq) methodology for the generation of sequence datasets suitable for a nucleosome density ChIP-seq analytical framework integrating micrococcal nuclease (MNase) accessibility with histone modification measurements.

核密度分析的天然染色质沉淀测序文库的生成

We present a modified native chromatin immunoprecipitation sequencing (ChIP-seq) experimental protocol compatible with a Gaussian mixture distribution ...

Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish

The analysis of global gene expression changes is a valuable tool for identifying novel pathways underlying observed phenotypes. The zebrafish is an excellent model for rapid assessment of whole transcriptome from whole animal or individual cell populations due to the ease of isolation of RNA from large numbers of animals. Here a protocol for global gene expression analysis in zebrafish embryos using RNA sequencing (RNASeq) is presented. We describe preparation of RNA from whole embryos or from cell populations obtained using cell sorting in transgenic animals. We also describe an approach for analysis of RNASeq data to identify enriched pathways and Gene Ontology (GO) terms in global gene expression data sets. Finally, we provide a protocol for validation of gene expression changes using quantitative reverse transcriptase PCR (qRT-PCR). These protocols can be used for comparative analysis of control and experimental sets of zebrafish to identify novel gene expression changes, and provide molecular insight into phenotypes of interest.

This protocol presents an approach for whole transcriptome analysis from zebrafish embryos, larvae, or sorted cells. We include isolation of RNA, pathway analysis of RNASeq data, and qRT-PCR-based validation of gene expression changes.

斑马鱼 RNASeq-based 基因表达数据的样品制备与分析

The analysis of global gene expression changes is a valuable tool for identifying novel pathways underlying observed phenotypes. The zebrafish is an ...

Immunostaining for DNA Modifications: Computational Analysis of Confocal Images

For several decades, 5-methylcytosine (5mC) has been thought to be the only DNA modification with a functional significance in metazoans. The discovery of enzymatic oxidation of 5mC to 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC) and 5-carboxylcytosine (5caC) as well as detection of N6-methyladenine (6mA) in the DNA of multicellular organisms provided additional degrees of complexity to the epigenetic research. According to a growing body of experimental evidence, these novel DNA modifications may play specific roles in different cellular and developmental processes. Importantly, as some of these marks (e. g. 5hmC, 5fC and 5caC) exhibit tissue- and developmental stage-specific occurrence in vertebrates, immunochemistry represents an important tool allowing assessment of spatial distribution of DNA modifications in different biological contexts. Here the methods for computational analysis of DNA modifications visualized by immunostaining followed by confocal microscopy are described. Specifically, the generation of 2.5 dimension (2.5D) signal intensity plots, signal intensity profiles, quantification of staining intensity in multiple cells and determination of signal colocalization coefficients are shown. Collectively, these techniques may be operational in evaluating the levels and localization of these DNA modifications in the nucleus, contributing to elucidating their biological roles in metazoans.

Newly discovered oxidized forms of 5-methylcytosine (oxi-mCs), 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC) and 5-carboxylcytosine (5caC) may represent distinct DNA modifications with unique functional roles. Here a semi-quantitative workflow for visualization of oxi-mCs' spatial distribution, signal intensity profiling and colocalization is described.

DNA 修饰的免疫: 共焦图像的计算分析

For several decades, 5-methylcytosine (5mC) has been thought to be the only DNA modification with a functional significance in metazoans. The discovery of ...

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

We have adapted the yeast 2-hybrid assay to simultaneously uncover dozens of transient and static protein interactions within a single screen utilizing high-throughput short-read DNA sequencing. The resulting sequence datasets can not only track what genes in a population that are enriched during selection for positive yeast 2-hybrid interactions, but also give detailed information about the relevant subdomains of proteins sufficient for interaction. Here, we describe a full suite of stand-alone software programs that allow non-experts to perform all the bioinformatics and statistical steps to process and analyze DNA sequence fastq files from a batch yeast 2-hybrid assay. The processing steps covered by these software include: 1) mapping and counting sequence reads corresponding to each candidate protein encoded within a yeast 2-hybrid prey library; 2) a statistical analysis program that evaluates the enrichment profiles; and 3) tools to examine the translational frame and position within the coding region of each enriched plasmid that encodes the interacting proteins of interest.

Deep sequencing of yeast populations selected for positive yeast 2-hybrid interactions potentially yields a wealth of information about interacting partner proteins. Here, we describe the operation of specific bioinformatics tools and customized updated software to analyze sequence data from such screens.

间歇酵母 2-混合筛序列数据的信息化分析

We have adapted the yeast 2-hybrid assay to simultaneously uncover dozens of transient and static protein interactions within a single screen utilizing ...

Antibody-Free Assay for RNA Methyltransferase Activity Analysis

There are more than 100 chemically distinct modifications of RNA, two thirds of which consist of methylations. Interest in RNA modifications, and especially methylations, has re-emerged due to the important roles played by the enzymes that write and erase them in biological processes relevant to disease and cancer. Here, a sensitive in vitro assay for accurate analysis of RNA methylation writer activity on synthetic or in vitro transcribed RNAs is provided. This assay uses a tritiated form of S-adenosyl-methionine, resulting in direct labeling of methylated RNA with tritium. The low energy of tritium radiation makes the method safe, and pre-existing methods of tritium signal amplification, make it possible to quantify and to visualize the methylated RNA without the use of antibodies, which are commonly prone to artifacts. While this method is written for RNA methylation, few tweaks make it applicable to the study of other RNA modifications that can be radioactively labeled, such as RNA acetylation with 14C acetyl coenzyme A. Overall, this assay allows to quickly assess RNA methylation conditions, inhibition with small molecule inhibitors, or the effect of RNA or enzyme mutants, and provides a powerful tool to validate and expand results obtained in cells.

Here, an antibody-free in vitro assay for direct analysis of methyltransferase activity on synthetic or in vitro transcribed RNA is described.

RNA甲基转移酶活性分析的无抗体测定

There are more than 100 chemically distinct modifications of RNA, two thirds of which consist of methylations. Interest in RNA modifications, and ...

Single-cell RNA Sequencing and Analysis of Human Pancreatic Islets

Pancreatic islets comprise of endocrine cells with distinctive hormone expression patterns. The endocrine cells show functional differences in response to normal and pathological conditions. The goal of this protocol is to generate high-quality, large-scale transcriptome data of each endocrine cell type with the use of a droplet-based microfluidic single-cell RNA sequencing technology. Such data can be utilized to build the gene expression profile of each endocrine cell type in normal or specific conditions. The process requires careful handling, accurate measurement, and rigorous quality control. In this protocol, we describe detailed steps for human pancreatic islets dissociation, sequencing, and data analysis. The representative results of about 20,000 human single islet cells demonstrate the successful application of the protocol.

Here, we present a protocol to generate high-quality, large-scale transcriptome data of single cells from isolated human pancreatic islets using a droplet-based microfluidic single-cell RNA sequencing technology.

人类胰腺胰岛的单细胞RNA测序与分析

Pancreatic islets comprise of endocrine cells with distinctive hormone expression patterns. The endocrine cells show functional differences in response to ...