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。

<table><tbody><tr><td>FastDNA SPIN Kit for Soil</td><td>MP Bio</td><td>116560200</td><td>DNA Extraction</td></tr><tr><td>DNA FastPrep</td><td>MP Bio</td><td>116004500</td><td>DNA Extraction</td></tr><tr><td>Agencourt AMPure XP beads</td><td>Beckman Coulter</td><td>A63880</td><td>DNA Purification</td></tr><tr><td>Elution Buffer</td><td>Qiagen</td><td>19806</td><td>DNA Purification</td></tr><tr><td>Qubit Fluorometer</td><td>Thermo Fisher</td><td>Q33216</td><td>DNA Quantification</td></tr><tr><td>Qubit dsDNA HS Assay Kit</td><td>Thermo Fisher</td><td>Q32854</td><td>DNA Quantification</td></tr><tr><td>Nextera XT DNA Library Prep Kit</td><td>Illumina</td><td>FC-131-1024</td><td>Library Preparation</td></tr><tr><td>Nextera XT Index Kit</td><td>Illumina</td><td>FC-131-1001</td><td>Library Preparation</td></tr><tr><td>TapeStation 2200</td><td>Agilent</td><td>G2964AA</td><td>DNA Quantification</td></tr><tr><td>HS D100 ScreenTape</td><td>Agilent</td><td>5067-5584</td><td>DNA Quantification</td></tr><tr><td>HS D100 ScreenTape Reagents</td><td>Agilent</td><td>5067-5585</td><td>DNA Quantification</td></tr><tr><td>TapeStation Tips</td><td>Agilent</td><td>5067-5153</td><td>DNA Quantification</td></tr><tr><td>TapeStation Tubes</td><td>Agilent</td><td>401428 and 401425</td><td>DNA Quantification</td></tr><tr><td>HiSeq 2500</td><td>Illumina</td><td></td><td>DNA Sequencing - provided by a sequencing service</td></tr><tr><td>High Power Analysis Workstation</td><td>Various</td><td></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="https://ecsource-jove-com.remotexs.ntu.edu.sg/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="https://ecsource-jove-com.remotexs.ntu.edu.sg/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="https://ecsource-jove-com.remotexs.ntu.edu.sg/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="https://ecsource-jove-com.remotexs.ntu.edu.sg/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="https://ecsource-jove-com.remotexs.ntu.edu.sg/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 ...

Nanyang Technological University

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

Empirical, Metagenomic, and Computational Techniques Illuminate the Mechanisms by which Fungicides Compromise Bee Health

Growers often use fungicide sprays during bloom to protect crops against disease, which exposes bees to fungicide residues. Although considered &#34;bee-safe,&#34; there is mounting evidence that fungicide residues in pollen are associated with bee declines (for both honey and bumble bee species). While the mechanisms remain relatively unknown, researchers have speculated that bee-microbe symbioses are involved. Microbes play a pivotal role in the preservation and/or processing of pollen, which serves as nutrition for larval bees. By altering the microbial community, it is likely that fungicides disrupt these microbe-mediated services, and thereby compromise bee health. This manuscript describes the protocols used to investigate the indirect mechanism(s) by which fungicides may be causing colony decline. Cage experiments exposing bees to fungicide-treated flowers have already provided the first evidence that fungicides cause profound colony losses in a native bumble bee (Bombus impatiens). Using field-relevant doses of fungicides, a series of experiments have been developed to provide a finer description of microbial community dynamics of fungicide-exposed pollen. Shifts in the structural composition of fungal and bacterial assemblages within the pollen microbiome are investigated by next-generation sequencing and metagenomic analysis. Experiments developed herein have been designed to provide a mechanistic understanding of how fungicides affect the microbiome of pollen-provisions. Ultimately, these findings should shed light on the indirect pathway through which fungicides may be causing colony declines.

Microbial consortia within bumble bee hives enrich and preserve pollen for bee larvae. Using next generation sequencing, along with laboratory and field-based experiments, this manuscript describes protocols used to test the hypothesis that fungicide residues alter the pollen microbiome, and colony demographics, ultimately leading to colony loss.

经验、基因和计算技术阐明了杀菌剂危害蜜蜂健康的机制

Growers often use fungicide sprays during bloom to protect crops against disease, which exposes bees to fungicide residues. Although considered ...

科研

环境科学

Exploring the Root Microbiome: Extracting Bacterial Community Data from the Soil, Rhizosphere, and Root Endosphere

The intimate interaction between plant host and associated microorganisms is crucial in determining plant fitness, and can foster improved tolerance to abiotic stresses and diseases. As the plant microbiome can be highly complex, low-cost, high-throughput methods such as amplicon-based sequencing of the 16S rRNA gene are often preferred for characterizing its microbial composition and diversity. However, the selection of appropriate methodology when conducting such experiments is critical for reducing biases that can make analysis and comparisons between samples and studies difficult. This protocol describes in detail a standardized methodology for the collection and extraction of DNA from soil, rhizosphere, and root samples. Additionally, we highlight a well-established 16S rRNA amplicon sequencing pipeline that allows for the exploration of the composition of bacterial communities in these samples, and can easily be adapted for other marker genes. This pipeline has been validated for a variety of plant species, including sorghum, maize, wheat, strawberry, and agave, and can help overcome issues associated with the contamination from plant organelles.

Here, we describe a protocol to obtain amplicon sequence data of soil, rhizosphere, and root endosphere microbiomes. This information can be used to investigate the composition and diversity of plant-associated microbial communities, and is suitable for the use with a wide range of plant species.

从土壤、根际和根 Endosphere 提取细菌群落数据的根菌群探析

The intimate interaction between plant host and associated microorganisms is crucial in determining plant fitness, and can foster improved tolerance to ...

遗传学

Nanopore DNA Sequencing for Metagenomic Soil Analysis

This article describes the steps for construction of a DNA library from soil, preparation and use of the nanopore flow cell, and analysis of the DNA sequences identified using computer software. Nanopore DNA sequencing is a flexible technique that allows for rapid microbial genome sequencing to identify bacterial and viral species, to characterize bacterial strains, and to detect genetic mutations that confer resistance to antibiotics. The advantages of nanopore sequencing (NS) for life sciences include its low complexity, reduced cost, and rapid real-time sequencing of purified genomic DNA, PCR amplicons, cDNA samples, or RNA. NS is an example of "strand sequencing" which involves sequencing DNA by guiding a single stranded DNA molecule through a nanopore that is inserted into a synthetic polymer membrane. The membrane has an electrical current applied across it, so as the individual bases pass through the nanopore the electrical current is disrupted to varying degrees by the four nucleotide bases. The identification of each nucleotide occurs by detecting the characteristic modulation of the electrical current by the different bases as they pass through the nanopore. The NS system consists of a handheld, USB powered portable device and a disposable flow cell that contains a nanopore array. The portable device plugs into a standard laptop computer that reads and records the DNA sequence using computer software.

Nanopore technology for sequencing biomolecules has wide applications in the life sciences, including identification of pathogens, food safety monitoring, genomic analysis, metagenomic environmental monitoring, and characterization of bacterial antibiotic resistance. In this article, the procedure for metagenomic soil DNA sequencing for species identification using the nanopore sequencing technology is demonstrated.

基因土壤分析的纳米 DNA 测序

This article describes the steps for construction of a DNA library from soil, preparation and use of the nanopore flow cell, and analysis of the DNA ...

Single-throughput Complementary High-resolution Analytical Techniques for Characterizing Complex Natural Organic Matter Mixtures

Natural organic matter (NOM) is composed of a highly complex mixture of thousands of organic compounds which, historically, proved difficult to characterize. However, to understand the thermodynamic and kinetic controls on greenhouse gas (carbon dioxide [CO2] and methane [CH4]) production resulting from the decomposition of NOM, a molecular-level characterization coupled with microbial proteome analyses is necessary. Further, climate and environmental changes are expected to perturb natural ecosystems, potentially upsetting complex interactions that influence both the supply of organic matter substrates and the microorganisms performing the transformations. A detailed molecular characterization of the organic matter, microbial proteomics, and the pathways and transformations by which organic matter is decomposed will be necessary to predict the direction and magnitude of the effects of environmental changes. This article describes a methodological throughput for comprehensive metabolite characterization in a single sample by direct injection Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS), gas chromatography mass spectrometry (GC-MS), nuclear magnetic resonance (NMR) spectroscopy, liquid chromatography mass spectrometry (LC-MS), and proteomics analysis. This approach results in a fully-paired dataset which improves statistical confidence for inferring pathways of organic matter decomposition, the resulting CO2 and CH4 production rates, and their responses to environmental perturbation. Herein we present results of applying this method to NOM samples collected from peatlands; however, the protocol is applicable to any NOM sample (e.g., peat, forested soils, marine sediments, etc.).

This protocol describes a single throughput for complementary analytical and omics techniques culminating in a fully-paired characterization of natural organic matter and microbial proteomics in different ecosystems. This approach permits robust comparisons for identifying metabolic pathways and transformations important for describing greenhouse gas production and predicting responses to environmental change.

用于表征复杂天然有机物混合物的单吞吐量互补高分辨率分析技术

Natural organic matter (NOM) is composed of a highly complex mixture of thousands of organic compounds which, historically, proved difficult to ...

Evaluating the Impact of Hydraulic Fracturing on Streams using Microbial Molecular Signatures

Hydraulic fracturing (HF), commonly called &#34;fracking&#34;, uses a mixture of high-pressure water, sand, and chemicals to fracture rocks, releasing oil and gas. This process revolutionized the U.S. energy industry, as it gives access to resources that were previously unobtainable and now produces two-thirds of the total natural gas in the United States. Although fracking has had a positive impact on the U.S. economy, several studies have highlighted its detrimental environmental effects. Of particular concern is the effect of fracking on headwater streams, which are especially important due to their disproportionately large impact on the health of the entire watershed. The bacteria within those streams can be used as indicators of stream health, as the bacteria present and their abundance in a disturbed stream would be expected to differ from those in an otherwise comparable but undisturbed stream. Therefore, this protocol aims to use the bacterial community to determine if streams have been impacted by fracking. To this end, sediment, and water samples, from streams near fracking (potentially impacted) and upstream or in a different watershed of fracking activity (unimpacted) must be collected. Those samples are then subjected to nucleic acid extraction, library preparation, and sequencing to investigate microbial community composition. Correlational analysis and machine learning models can subsequently be employed to identify which features are explanative of variation in the community, as well as identification of predictive biomarkers for fracking&#39;s impact. These methods can reveal a variety of differences in the microbial communities among headwater streams, based on the proximity to fracking, and serve as a foundation for future investigations on the environmental impact of fracking activities.

Here, we present a protocol to investigate the impacts of hydraulic fracturing on nearby streams by analyzing their water and sediment microbial communities.

使用微生物分子特征评估水力压裂对溪流的影响

Hydraulic fracturing (HF), commonly called &#34;fracking&#34;, uses a mixture of high-pressure water, sand, and chemicals to fracture rocks, releasing oil ...

Derivatization and Separation of Barley Flour Metabolites into Four Fractions

Metabolomic Analysis of Barley by Gas Chromatography/Mass Spectrometry

Climate change increases drought risk to agriculture and impacts both food nutrient content and overall food security. Metabolomics is one way to observe and quantify the impacts of drought on grain and other agricultural products. The identified metabolites may allow for the identification of the biochemical response that allows the plant to tolerate stressful environments. The methodology presented herein allowed for the total metabolomic analysis of barley flour using gas chromatography/mass spectrometry (GC/MS). 
Barley flour metabolite extracts were fractionated into four fractions based on polarity. To allow for analysis by GC/MS, metabolites were derivatized to increase volatility and metabolite separation: fatty acids esters were derivatized into fatty acid methyl esters; sugars were oximated into their straight chain form; and metabolites with hydroxyl groups were converted to their corresponding silyl ethers. The derivatized samples were injected into the GC/MS and the generated mass spectra were used for metabolite identification by comparing the generated spectra to the National Institute of Standards and Technology (NIST) Tandem Mass Spectra library. The method described here can also be used to examine the total metabolome for other plants, furthering our understanding of the biochemical responses of stressed plants.

A method for metabolomic analysis of barley is presented. The method entails fractionation and derivatization of metabolites and analysis thereof by gas chromatography/mass spectrometry (GC/MS). Metabolomic analysis can be used to determine the effect of intercropping and drought stress on the grain.

Climate change increases drought risk to agriculture and impacts both food nutrient content and overall food security. Metabolomics is one way to observe ...

Microarray Analysis for Saccharomyces cerevisiae

In this protocol, gene expression in yeast (Saccharomyces cerevisiae) is changed after exposure to oxidative stress induced by the addition of hydrogen peroxide (H2O2), an oxidizing agent. In the experiment, yeast is grown for 48 hours in 1/2X YPD broth containing 3X glucose. The culture is split into a control and treated group. The experiment culture is treated with 0.5 mM H2O2 in Hanks Buffered Saline (HBSS) for 1 hour. The control culture is treated with HBSS only. Total RNA is extracted from both cultures and is converted to a biotin-labeled cRNA product through a multistep process. The final synthesis product is taken back to the UVM Microarray Core Facility and hybridized to the Affymetrix yeast GeneChips. The resulting gene expression data are uploaded into bioinformatics data analysis software.

Microarray Analysis for Saccharomyces cerevisiae

In this protocol, gene expression in yeast (Saccharomyces cerevisiae) is changed after exposure to oxidative stress induced by the addition of hydrogen peroxide (H2O2), an oxidizing agent.

微阵列分析FOR酿酒酵母</em

In this protocol, gene expression in yeast (Saccharomyces cerevisiae) is changed after exposure to oxidative stress induced by the addition of hydrogen ...

生物学

Purifying the Impure: Sequencing Metagenomes and Metatranscriptomes from Complex Animal-associated Samples

The accessibility of high-throughput sequencing has revolutionized many fields of biology. In order to better understand host-associated viral and microbial communities, a comprehensive workflow for DNA and RNA extraction was developed. The workflow concurrently generates viral and microbial metagenomes, as well as metatranscriptomes, from a single sample for next-generation sequencing. The coupling of these approaches provides an overview of both the taxonomical characteristics and the community encoded functions. The presented methods use Cystic Fibrosis (CF) sputum, a problematic sample type, because it is exceptionally viscous and contains high amount of mucins, free neutrophil DNA, and other unknown contaminants. The protocols described here target these problems and successfully recover viral and microbial DNA with minimal human DNA contamination. To complement the metagenomics studies, a metatranscriptomics protocol was optimized to recover both microbial and host mRNA that contains relatively few ribosomal RNA (rRNA) sequences. An overview of the data characteristics is presented to serve as a reference for assessing the success of the methods. Additional CF sputum samples were also collected to (i) evaluate the consistency of the microbiome profiles across seven consecutive days within a single patient, and (ii) compare the consistency of metagenomic approach to a 16S ribosomal RNA gene-based sequencing. The results showed that daily fluctuation of microbial profiles without antibiotic perturbation was minimal and the taxonomy profiles of the common CF-associated bacteria were highly similar between the 16S rDNA libraries and metagenomes generated from the hypotonic lysis (HL)-derived DNA. However, the differences between 16S rDNA taxonomical profiles generated from total DNA and HL-derived DNA suggest that hypotonic lysis and the washing steps benefit in not only removing the human-derived DNA, but also microbial-derived extracellular DNA that may misrepresent the actual microbial profiles.

Using the cystic fibrosis airway as an example, the manuscript presents a comprehensive workflow comprising a combination of metagenomic and metatranscriptomic approaches to characterize the microbial and viral communities in animal-associated samples.

从复杂的动物相关样品测序宏基因组和Metatranscriptomes:净化不纯

The accessibility of high-throughput sequencing has revolutionized many fields of biology. In order to better understand host-associated viral and ...

A Hybrid DNA Extraction Method for the Qualitative and Quantitative Assessment of Bacterial Communities from Poultry Production Samples

The efficacy of DNA extraction protocols can be highly dependent upon both the type of sample being investigated and the types of downstream analyses performed. Considering that the use of new bacterial community analysis techniques (e.g., microbiomics, metagenomics) is becoming more prevalent in the agricultural and environmental sciences and many environmental samples within these disciplines can be physiochemically and microbiologically unique (e.g., fecal and litter/bedding samples from the poultry production spectrum), appropriate and effective DNA extraction methods need to be carefully chosen. Therefore, a novel semi-automated hybrid DNA extraction method was developed specifically for use with environmental poultry production samples. This method is a combination of the two major types of DNA extraction: mechanical and enzymatic. A two-step intense mechanical homogenization step (using bead-beating specifically formulated for environmental samples) was added to the beginning of the &#8220;gold standard&#8221; enzymatic DNA extraction method for fecal samples to enhance the removal of bacteria and DNA from the sample matrix and improve the recovery of Gram-positive bacterial community members. Once the enzymatic extraction portion of the hybrid method was initiated, the remaining purification process was automated using a robotic workstation to increase sample throughput and decrease sample processing error. In comparison to the strict mechanical and enzymatic DNA extraction methods, this novel hybrid method provided the best overall combined performance when considering quantitative (using 16S rRNA qPCR) and qualitative (using microbiomics) estimates of the total bacterial communities when processing poultry feces and litter samples.

A novel semi-automated hybrid DNA extraction method for use with environmental poultry production samples was developed and demonstrated improvements over a common mechanical and enzymatic extraction method in terms of the quantitative and qualitative estimates of the total bacterial communities.

一种混合DNA提取方法细菌群落的定性和定量评估，从家禽生产样品

The efficacy of DNA extraction protocols can be highly dependent upon both the type of sample being investigated and the types of downstream analyses ...

Quasi-metagenomic Analysis of Salmonella from Food and Environmental Samples

Quasi-metagenomics sequencing refers to the sequencing-based analysis of modified microbiomes of food and environmental samples. In this protocol, microbiome modification is designed to concentrate genomic DNA of a target foodborne pathogen contaminant to facilitate the detection and subtyping of the pathogen in a single workflow. Here, we explain and demonstrate the sample preparation steps for the quasi-metagenomics analysis of Salmonella enterica from representative food and environmental samples including alfalfa sprouts, ground black pepper, ground beef, chicken breast and environmental swabs. Samples are first subjected to the culture enrichment of Salmonella for a shortened and adjustable duration (4&#8211;24 h). Salmonella cells are then selectively captured from the enrichment culture by immunomagnetic separation (IMS). Finally, multiple displacement amplification (MDA) is performed to amplify DNA from IMS-captured cells. The DNA output of this protocol can be sequenced by high throughput sequencing platforms. An optional quantitative PCR analysis can be performed to replace sequencing for Salmonella detection or assess the concentration of Salmonella DNA before sequencing.

Quasi-metagenomic Analysis of Salmonella from Food and Environmental Samples

Here, we present a protocol to prepare DNA samples from food and environmental microbiomes for concerted detection and subtyping of Salmonella through quasimetagenomic sequencing. The combined use of culture enrichment, immunomagnetic separation (IMS), and multiple displacement amplification (MDA) allows effective concentration of Salmonella genomic DNA from food and environmental samples.&#160;

青贮的宏基因组学分析

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