我们感谢安妮·德容和西热Holsappel的帮助，DNA微阵列幻灯片制作。安妮·德容的生物信息学分析的支持表示赞赏。我们也感谢耶勒Slager审查的文件。穆罕默德·阿夫扎尔和伊尔凡曼苏尔是由GC大学，费萨拉巴德，巴基斯坦在巴基斯坦HEC的师资队伍建设项目的支持。

1.制备媒体，以及细胞培养<ol><li>成长S.如先前所描述的11 肺炎 D39野生型菌株21。接种储存在-80℃下在10％的甘油（以1/100的比例在50毫升无菌试管中）的50ml化学定义的培养基（CDM）为6.4 15最终pH的细胞，但是从氨基酸省略L-丝氨酸混合。 注:两个不同的是存款机使用;一种含含L-丝氨酸（10毫米）的最大浓度的L-丝氨酸（150μM），而另一个的最小浓度。该最小浓度基本上是L-丝氨酸在人血浆中的浓度，目的是比较S的基因表达这两个条件下，肺炎 D39应变。 </li></ol> 2.提取总RNA <ol><li>物料<ol><li>使用酸性酚，核糖核酸级总RNA的分离。 </li><li> Macaloid: <ol><li>暂停2克macaloid在100毫升TE煮5分钟。冷却至RT，并声处理直至macaloid gels.Centrifuge在50毫升的TE pH为8，并储存在4℃下将溶液在2000×g下5分钟，在室温，重悬。 </li></ol></li><li>解决方案: <ol><li>治疗用焦碳酸二乙酯（DEPC）所有的解决方案。添加100微升DEPC / 100ml的溶液，孵育O / N在37℃和高压釜15分钟。 </li></ol></li></ol></li><li>方法<ol><li>增长50毫升S.在50毫升管肺炎 D39细胞培养在37℃（无抖动），直到指数中期阶段（OD〜0.3）。离心培养物在4℃下10,000×g下 2分钟。丢弃媒体并立即冷冻在液氮中的细胞沉淀。 </li><li>预混物加入300μl氯仿:IAA（24:1）和300μl的苯酚（酸苯酚，RNA级）。用500微升的有机相在步骤2.2.3。 </li><li>预先在无RNA螺旋盖管中制备下列混合物:00.5克玻璃珠，50微升10％SDS，500微升酚/氯仿:IAA（如制备步骤2.2.2），macaloid层（150-175微升，不准确的，因为它是非常粘稠）。悬浮于400μl的TE（DEPC）的细胞沉淀并加入再悬浮细胞进入螺旋帽试管中。 </li><li>以破碎细胞，将螺旋帽试管中一个珠打浆机为2×60"的脉冲（&#39;均质&#39;）用1分钟的时间间隔在冰上。离心机的样品在10000×g下（4℃）10分钟。 </li><li>上层相转移至新管中，加入500μl氯仿:IAA（24:1）和离心5分钟，以10,000×g下（4℃）。 </li><li>转移500μl的上层相的至新管中，添加的裂解/结合缓冲液2倍体积（1ml）中，并通过上下抽吸混合。分离总RNA使用RNA分离试剂盒，并按照制造商推荐的协议。 </li></ol></li></ol> 3. R​​NA清理 &lt;<html> OL&gt; <li>从总RNA去除DNA的污染，加上100微升DNA酶I混合（90微升DNA酶缓冲和10μLDNA酶I）和孵育20-30分钟，在15-25ºC。 </li><li>使用RNA酶试剂盒洗干净RNA。获得50微升洗脱体积。 </li></ol> RNA 4.分析<ol><li>确定的分光光度计RNA的浓度。通过使用分析如下（ 图2）确定RNA的质量。 <ol><li>稀释1μl的样品用50微升DEPC水来获得20-200纳克/微升的浓度。 </li><li>使用1微升稀释的RNA试样根据制造商的说明来检查质量上的生物分析仪。 </li></ol></li><li>注:23S的比例约为2.0 16S被认为是好的1 A260单位RNA相当于40微克/毫升。推荐的量标注为10-20微克。 </li></ol> 5. cDNA的制备和标签ntent"&gt;注:以下协议之后进行的cDNA的准备和标签。 <ol><li>退火<ol><li>进行退火反应在300微升的PCR管，保持总RNA 10-15微克的浓度为自制幻灯片或5微克为公司制造的幻灯片。混合的RNA与2微升随机九（1.6微克/微升），并添加无核酸酶水，如果必要，以保持退火混合物的终体积为18微升。 </li><li>保持在退火混合物在70℃下5分钟。此后，冷却该混合物至室温10分钟（退火）和如果需要的话，降速反应到管的底部。将反应管在冰上至少1分钟。 </li></ol></li><li>反转录<ol><li>准备逆转录酶结构如下:18微升退火混合，加入12微升主结构（包括6微升5X第一链缓冲液，3微升0.1M的DDT，1.2微升25X AA-的dUTP /核苷酸混合物和1.8微升倒Transcriptase（1微升的公司制造的幻灯片）。保持反应混合物为2-16小时，在42℃。 </li></ol></li></ol> 6.降解mRNA和cDNA的纯化<ol><li>以从反应混合物中降低的mRNA，加入3微升的2.5M NaOH和地点，在37℃下进行约15分钟。接着，加入15微升2M HEPES游离酸，以中和氢氧化钠。 </li><li>通过PCR清理列净化的cDNA混合，并按照制造商的协议。 </li></ol> 7.测量基因浓度<ol><li>衡量一个分光光度计的cDNA浓度。要继续使用标签，检查的cDNA的浓度至少为60纳克/微升（自制幻灯片）或20毫微克/μL（公司制作的幻灯片）。 </li></ol> 8.标签的cDNA与胺活性染料与纯化<ol><li>使用胺反应性染料来标记的cDNA。直接混合的cDNA用的一个等分试样（5微升）胺反应性染料。 </li><li>在RT孵育该混合物中，在黑暗中，60至90分钟，并直接进行染料标记的cDNA的纯化。通过使用PCR净化柱并按照生产商的方案纯化染料标记的cDNA。在50μl的洗脱缓冲液洗脱的cDNA。 </li></ol> 9.测量标记的cDNA的<ol><li>使用分光光度计来测量的胺反应性染料入的cDNA掺入。检查的胺 - 反应性染料的浓度为至少0.5皮摩尔/微升在50微升的总体积。 </li></ol> 10.混合标记的基因样品<ol><li>自制幻灯片，使用所有的标记cDNA杂交在cDNA的浓度不大于30％的差异。对于公司制造的幻灯片，使用基因与不低于基因浓度为2倍的差异等等。 注意:通常情况下，约300纳克的cDNA，需要对公司制造的幻灯片，相比于REQ这是非常小uired cDNA的量自制的幻灯片。 </li></ol> 11.杂交和洗涤<ol><li>使用以下试剂:半幅水，乙醇99％，SHY缓冲（自制;用40微升酵母RNA）。准备最多1毫升害羞。 </li><li>设备和解决方案的准备<ol><li>干燥前打开真空浓缩和加热器至少1小时。接通杂交炉，用调整到正确的杂交温度设定点（对于肺炎链球菌 DNA微阵列，使用45℃）。同样，预热杂交录像带和烤箱30-60分钟。 </li><li>预热SHY缓冲器在68℃至少30分钟。 </li></ol></li><li>样品制备（标记的cDNA） <ol><li>结合等量标记的cDNA（最多30％差）。使用真空浓缩，在高温（约40分钟），直到体积小于7微升干燥样品。 </li></ol></li><li>升降滑<ol><li>用干净的升降杆单。注意:±30微升可以在滑动加载。 </li><li>清洁挺杆-卡瓦用肥皂，大量的自来水和100％的乙醇。注:脏升降机单给予很高的背景。 </li><li>空气干燥升降，单用气手枪吹走灰尘颗粒。广场上，在两侧的白色聚四氟乙烯衬里朝下幻灯片干净的升降滑。 </li></ol></li><li>加入杂交缓冲液（以标记的cDNA） <ol><li>溶解在干燥的染料样品在7微升的H 2 O和孵育在94℃进行2分钟。 </li><li>随即，加入35微升预热SHY缓冲液（68°C），轻轻混匀，在最大速度为1分钟摆脱沉淀。预热探针在68℃，大约5分钟，直到加载。 </li></ol></li><li>上滑升降滑装配和预热。 <ol><li>将热块的杂交幻灯片固定在50℃。将DNA微阵列载玻片上加热杂交滑座和P的升降滑再热与升降滑了一分钟的幻灯片。执行下面的步骤，尽快。 </li><li>添加40微升样品靶到滑动的末端。允许流体通过毛细力在玻璃表面之间流动。缓慢而仔细地执行所有的移液。 </li><li>保持与升降滑水平的幻灯片在任何时候，慢慢地移动，确保了升降滑不动了。 </li><li>就拿预热杂交纸盒拉出杂交炉并关闭机器。代替滤纸浸泡用3ml 2×SSC（标准柠檬酸盐）中的杂交盒。 </li><li>轻轻将杂交滑套与杂交录像带的幻灯片。关闭杂交录像带，并把在杂交炉试（约16-18小时）。 </li></ol></li><li>滑洗<ol><li>制备新鲜洗涤缓冲液I，II和III（每次洗涤步骤750毫升）中。对于500毫升洗缓冲I，用2×SSC / 0.5％SDS。对于500毫升洗的buff呃II，使用1×SSC / 0.25％SDS。对于500毫升洗缓冲III，使用1×SSC / 0.1％SDS（可选） </li><li>将洗涤缓冲剂在30℃下（以确保SDS溶解）。 </li><li>淹没的幻灯片尽快，但很平缓，在Falcon管填充用50ml洗涤缓冲液I，直到玻璃靠在管的圆锥形底部。 </li><li>几秒钟后，当升降器滑汇到管的底部，取出用镊子滑动而不刮伤阵列和放入所述洗涤台的齿条之后。继续没有时间差的清洗。 </li><li>为5分钟，在500洗载玻片毫升洗涤缓冲液I（同一个清洗站）。给它的第二洗涤20-30分钟在500毫升洗涤缓冲液II（在洗涤站）。同样，在500洗幻灯片5分钟毫升洗缓冲III（可选）（在清洗站）。 </li><li>干燥载玻片2分钟以2000rpm。 </li></ol></li></ol> 12.微阵列分析<ol><li>扫描图像在扫描仪的各波长和保存文件夹"朱庇特工程"。 </li><li>使用软件最初分析扫描文件如前所述22.运行该软件后，选择"打开图像"选项卡中的红色映像文件（-.550）加载为"红色"和绿色的图像文件（-.635）作为"绿色"。通过选择"加载数组列表"选项卡22载有图像文件肺炎链球菌数组列表中的文件加仑（.gal）。 注:此数组列表包括48格的，对每个网格有16列和15列。在网格上每个点代表一个单独的基因和现货信息，包括基因名是通过现货描述文件添加。当场号码从左边给出向右，从上到下。 </li><li>经过仔细察觉的网格，选择选项卡"查找阵列，查找模块，对齐功能"对齐点。对准所有功能后，分析图像通过选择"分析"TAB。创建具有效果，直方图和散射图的新文件。保存从标签文件"保存结果"作为.gpr文件作进一步的分析。 </li><li>所描述的9与内部开发Microprep软件包进行进一步正常化和数据处理。 </li><li>使用独立的生物复制的DNA微阵列数据这是染料交换。执行CyberT实施T-test1的一个变种，并计算假发现率（一级亲属）所描述的9。 </li><li>差异表达基因，以P &lt;0.001和FDR &lt;0.05为标准。 </li><li>上传NCBI上提交页面DNA微阵列数据得到GEO（基因表达总括）登录号。 </li></ol>

<ol>
	<li>Kayala, M. A., Baldi, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cyber-T+web+server:+differential+analysis+of+high-throughput+data.">Cyber-T web server: differential analysis of high-throughput data.</a> Nucleic Acids Res. 40, W553-W559 (2012).</li><li>Chang, T. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Binding+of+cells+to+matrixes+of+distinct+antibodies+coated+on+solid+surface.">Binding of cells to matrixes of distinct antibodies coated on solid surface.</a> J. Immunol. Methods. 65, 217-223 (1983).</li><li>Schena, M., Shalon, D., Davis, R. W., Brown, P. O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+monitoring+of+gene+expression+patterns+with+a+complementary+DNA+microarray.">Quantitative monitoring of gene expression patterns with a complementary DNA microarray.</a> Science. 270, 467-470 (1995).</li><li>Galau Levi, A., A, G., Wetzstein, H. Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+rapid+procedure+for+the+isolation+of+RNA+from+high-phenolic-containing+tissues+of+pecan.">A rapid procedure for the isolation of RNA from high-phenolic-containing tissues of pecan.</a> 27 (12), 1316-1318 (1992).</li><li>Lopez-Gomez, R., Gomez-Lim, M. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+method+for+extraction+of+intact+RNA+from+fruits+rich+in+polysaccharides+using+ripe+mango+mesocarp.">A method for extraction of intact RNA from fruits rich in polysaccharides using ripe mango mesocarp.</a> (5), 440-442 (1992).</li><li>Salzman, R. A., Fujita, T., Salzman, Z., Hasegawa, P. M., Bressan, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+improved+RNA+isolation+method+for+plant+tissues+containing+high+levels+of+phenolic+compounds+or+carbohydrates.">A improved RNA isolation method for plant tissues containing high levels of phenolic compounds or carbohydrates.</a> Plant Molecular Biology Report. 17, 11-17 (1999).</li><li>Kiefer, E., Heller, W., Ernst, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+simple+and+efficient+protocol+for+isolation+of+functional+RNA+from+plant+tissues+rich+in+secondary+metabolites.">A simple and efficient protocol for isolation of functional RNA from plant tissues rich in secondary metabolites.</a> Plant Mol. Biol. Report. 18, 33-39 (2000).</li><li>Tattersall, E. A. R., Ergul, A., Alkayal, F., Deluc, L., Cushman, J. C., Cramer, G. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparison+of+methods+for+isolating+high-quality+RNA+from+leaves+of+grapevine.">Comparison of methods for isolating high-quality RNA from leaves of grapevine.</a> Am. J. Enol. Vitic. 56, 400-406 (2005).</li><li>Van Hijum, S. A. F. T., Garcia de la Nava, J., Trelles, O., Kok, J., Kuipers, O. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MicroPreP:+a+cDNA+microarray+data+pre-processing+framework.">MicroPreP: a cDNA microarray data pre-processing framework.</a> Appl.Bioinformatics. 2, 241-244 (2003).</li><li>Kadioglu, A., Weiser, J. N., Paton, J. C., Andrew, P. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+role+of+Streptococcus+pneumoniae+virulence+factors+in+host+respiratory+colonization+and+disease.">The role of Streptococcus pneumoniae virulence factors in host respiratory colonization and disease.</a> Nat.Rev.Microbiol. 6, 288-301 (2008).</li><li>Afzal, M., Shafeeq, S., Kuipers, O. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=LacR+is+a+repressor+of+lacABCD+and+LacT+is+an+activator+of+lacTFEG,+constituting+the+lac+gene+cluster+in+Streptococcus+pneumoniae.">LacR is a repressor of lacABCD and LacT is an activator of lacTFEG, constituting the lac gene cluster in Streptococcus pneumoniae.</a> Appl. Environ. Microbiol. 80, 5349-5358 (2014).</li><li>Afzal, M., Shafeeq, S., Henriques-Normark, B., Kuipers, O. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=UlaR+activates+the+expression+of+the+ula+operon+in+Streptococcus+pneumoniae+in+the+presence+of+ascorbic+acid.">UlaR activates the expression of the ula operon in Streptococcus pneumoniae in the presence of ascorbic acid.</a> Microbiol. Read. Engl. , (2014).</li><li>Hendriksen, W. T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Site-specific+contributions+of+glutamine-dependent+regulator+GlnR+and+GlnR-regulated+genes+to+virulence+of+Streptococcus+pneumoniae.">Site-specific contributions of glutamine-dependent regulator GlnR and GlnR-regulated genes to virulence of Streptococcus pneumoniae.</a> Infect. Immun. 76, 1230-1238 (2008).</li><li>Kloosterman, T. G., Kuipers, O. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Regulation+of+arginine+acquisition+and+virulence+gene+expression+in+the+human+pathogen+Streptococcus+pneumoniae+by+transcription+regulators+ArgR1+and+AhrC.">Regulation of arginine acquisition and virulence gene expression in the human pathogen Streptococcus pneumoniae by transcription regulators ArgR1 and AhrC.</a> J. Biol. Chem. 286, 44594-44605 (2011).</li><li>Kloosterman, T. G., Bijlsma, J. J. E., Kok, J., Kuipers, O. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=To+have+neighbour's+fare:+extending+the+molecular+toolbox+for+Streptococcus+pneumoniae.">To have neighbour's fare: extending the molecular toolbox for Streptococcus pneumoniae.</a> Microbiol. Read. Engl. 152, 351-359 (2006).</li><li>Blom, E. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=FIVA:+Functional+Information+Viewer+and+Analyzer+extracting+biological+knowledge+from+transcriptome+data+of+prokaryotes.">FIVA: Functional Information Viewer and Analyzer extracting biological knowledge from transcriptome data of prokaryotes.</a> Bioinforma. Oxf. Engl. 23, 1161-1163 (2007).</li><li>Blom, E. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Prosecutor:+parameter-free+inference+of+gene+function+for+prokaryotes+using+DNA+microarray+data,+genomic+context+and+multiple+gene+annotation+sources.">Prosecutor: parameter-free inference of gene function for prokaryotes using DNA microarray data, genomic context and multiple gene annotation sources.</a> BMC Genomics. 9, 495 (2008).</li><li>Blom, E. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=DISCLOSE+:+DISsection+of+CLusters+Obtained+by+SEries+of+transcriptome+data+using+functional+annotations+and+putative+transcription+factor+binding+sites.">DISCLOSE : DISsection of CLusters Obtained by SEries of transcriptome data using functional annotations and putative transcription factor binding sites.</a> BMC Bioinformatics. 9, 535 (2008).</li><li>Baerends, R. J. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genome2D:+a+visualization+tool+for+the+rapid+analysis+of+bacterial+transcriptome+data.">Genome2D: a visualization tool for the rapid analysis of bacterial transcriptome data.</a> Genome Biol. 5 (5), R37 (2004).</li><li>De Jong, A., Pietersma, H., Cordes, M., Kuipers, O. P., Kok, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=PePPER,+a+webserver+for+prediction+of+prokaryote+promoter+elements+and+regulons.">PePPER, a webserver for prediction of prokaryote promoter elements and regulons.</a> BMC Genomics. 13, 229 (2012).</li><li>Lanie, J. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genome+sequence+of+Avery's+virulent+serotype+2+strain+D39+of+Streptococcus+pneumoniae+and+comparison+with+that+of+unencapsulated+laboratory+strain+R6.">Genome sequence of Avery's virulent serotype 2 strain D39 of Streptococcus pneumoniae and comparison with that of unencapsulated laboratory strain R6.</a> J. Bacteriol. 189, 38-51 (2007).</li><li>Molecular Devices, Corp. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> GenePix Pro 6.0 Microarray Acquisition and Analysis Software for GenePix Microarray Scanners-Use's Guide and Tutorial. , (2005).</li></ol>

作者宣称，他们有没有竞争的财务权益。

我们描述了可应用到执行的细菌的全转录组分析一个用户友好的协议。有关此特定技术的关键点是，在其下收获细胞的情况会有所不同。后收获细胞并分离RNA，该技术变得等于对所有类型的细菌的样品，并遵循完全相同的步骤，因此，可以适用于任何类型的细菌培养物。该协议是很简单的，方便的，并开始从RNA分离。我们的RNA分离协议（使用Macaloid和RNA分离试剂盒）是时间效益，因为相比于传统?...

整套的mRNA的丰度（转录组）的在特定时间或在特定条件下的编码通过单细胞生物体或真核细胞的基因组中，包括基因过表达或敲除的研究中，被称为转录。转录使我们能够观察到什么程度的基因都在一个时间点X的特定条件下进行表达，并给了我们如何强烈的基因表达相对于参考信息。 微阵列是在固体基材上的二维阵列（通常是载玻片或硅薄膜电池），它可以被用于使用高通量筛选以测定大量的生物材料，和小型化，复用和并行处理和检测方法。芯片有各种型号，包括DNA，基因芯片，蛋白质芯片，芯片肽，组织芯片，​​抗体芯片，细胞芯片等。 DNA微阵列是基本上微观DNA斑点的组件固定在固体表面上，通常是玻璃。 DNA微阵列被用于测量的基因的表达水平或一组基因的同时或基因型基因组2,3的多个区域。探针的皮摩尔（10 -12摩尔）的每一个DNA斑点代表特定的DNA序列，也被称为记者中存在。从样品中所述标记的mRNA分子被称为"目标"。荧光团可用于测量探针 - 靶杂交和检测的荧光团标记靶确定靶核酸序列的相对丰度。微阵列实验可以完成多个基因测试在并行，因为数组可能包含探头数以万计。一个简单的微阵列实验的布局示于图1。最近，它建立在我们和其他实验室，这些阵列是可重复使用的，这使得该技术相当高性价比即不同的RNA的分离和纯化技术已开发多年，包括C-TAB，SDS和GT方法4 - 8。此外，一些商业工具包也可提供。用于基因表达的高品质的RNA是非常重要的。因此，RNA分离方法被修改，以获得RNA的最大数量。同样，步骤进行cDNA制备cDNA的和标签被最小化。还通过内部内置软件包和工具进行9有效扫描后的数据正常化。 肺炎链球菌是一种革兰氏阳性的人类病原体是定植鼻咽和是多重感染，如肺炎，败血症，中耳炎的病因和脑膜炎10。该细菌可以利用各种所需的生长和存活11,12的营养素。大量的研究已经进行了对肺炎球菌氮代谢和调节强调氨基酸的重要性及其在毒力13,14作用。在这项研究中，S的转录反应肺炎改变L-丝氨酸，氨基酸大量存在的人血浆中的浓度，使用DNA微阵列的报道。 S的 ​​转录反应肺炎在L-丝氨酸（150μM）的最低浓度生长进行比较，在最大浓度（10毫米）的丝氨酸的生长。化学上确定的培养基（CDM或基本培养基）15被用于该研究，以控制丝氨酸的浓度。本研究的焦点是使该技术的用户友好的，并提供对数据归一化和分析不同的工具。因此，许多工具用于分​​析和数据解释被开发。 FIVA（函数信息查看器和分析器）提供了包含在集群有基因的信息处理平台相似的基因表达模式和构建功能简16。检察官是另一个软件包，有助于推测功能和基因17的注解标识。通过利用聚类方法公开提供了一种DNA结合位点的检测算法。基因的顺 -regulatory图案可以通过使用这种算法18进行投影。 Genome2D通过提供不同颜色范围来表征上的基因组中的地图19中的变化，基因表达水平提供了一个基于Windows的平台，可视化和转录组数据的分析。辣椒Web服务器提供，除了所有功能于一身的分析方法，一个工具箱开采调节子，推动者和转录因子结合位点20。间区域中的细菌基因组完整注释可以通过使用这个包来实现。生物学家可以大大辣椒中受益，因为它为他们提供了一个平台，设计性实验S以便虚拟信息可以在体外 20来确认。这些软件包显著有助于微阵列分析，其中大部分都是免费提供的，使数据标准化和分析非常可靠。

<table border="0" cellpadding="0" cellspacing="0">
	<tbody>
		<tr>
			<td>Acid phenol</td>
			<td>SigmaAldrich</td>
			<td>P4682</td>
			<td></td>
		</tr>
		<tr>
			<td>Roche RNA isolation kit</td>
			<td>Roche Applied Science</td>
			<td>11828665001</td>
			<td></td>
		</tr>
		<tr>
			<td>Glass beads</td>
			<td></td>
			<td>105015</td>
			<td></td>
		</tr>
		<tr>
			<td>Chloroform</td>
			<td>Boom</td>
			<td>92013505.1000.</td>
			<td></td>
		</tr>
		<tr>
			<td>IAA</td>
			<td></td>
			<td>106630</td>
			<td></td>
		</tr>
		<tr>
			<td>Nanodrop</td>
			<td>Nanodrop</td>
			<td>ND-100</td>
			<td></td>
		</tr>
		<tr>
			<td>Agilent BioAnalyser</td>
			<td>Agilent</td>
			<td>G2940CA</td>
			<td></td>
		</tr>
		<tr>
			<td>Superscript III</td>
			<td>Life technologies Invitrogen</td>
			<td>18080044</td>
			<td></td>
		</tr>
		<tr>
			<td>AA-dUTP</td>
			<td>Life technologies Invitrogen</td>
			<td>AM8439</td>
			<td></td>
		</tr>
		<tr>
			<td>DDT</td>
			<td>Life technologies Invitrogen</td>
			<td>18080044</td>
			<td></td>
		</tr>
		<tr>
			<td>First Strand buffer</td>
			<td>Life technologies Invitrogen</td>
			<td>18080044</td>
			<td></td>
		</tr>
		<tr>
			<td>NaOH</td>
			<td>SigmaAldrich</td>
			<td>S8045-1KG</td>
			<td></td>
		</tr>
		<tr>
			<td>HEPES</td>
			<td>SigmaAldrich</td>
			<td>H4034-500G</td>
			<td></td>
		</tr>
		<tr>
			<td>DyLight-550</td>
			<td>Thermoscientiffic</td>
			<td>62262</td>
			<td></td>
		</tr>
		<tr>
			<td>DyLight-650</td>
			<td>Thermoscientiffic</td>
			<td>62265</td>
			<td></td>
		</tr>
		<tr>
			<td>SHY Buffer</td>
			<td>SigmaAldrich</td>
			<td>H7033-125ML</td>
			<td></td>
		</tr>
		<tr>
			<td>Speedvac cooler</td>
			<td>Eppendorf</td>
			<td>RUGNE3140</td>
			<td>Speedvac concentrator plus</td>
		</tr>
		<tr>
			<td>Hybridization oven</td>
			<td>Grant Boekel</td>
			<td>Iso-20</td>
			<td></td>
		</tr>
		<tr>
			<td>Lifter-slips</td>
			<td>Erie Scientific</td>
			<td>25x60I-M-5439</td>
			<td></td>
		</tr>
		<tr>
			<td>Wipe</td>
			<td>KIMTECH</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>SDS</td>
			<td>SigmaAldrich</td>
			<td>L3771-100g</td>
			<td></td>
		</tr>
		<tr>
			<td>SSC</td>
			<td>SigmaAldrich</td>
			<td>W302600-1KG-K</td>
			<td></td>
		</tr>
		<tr>
			<td>Genpix autoloader 4200A1</td>
			<td>MSD analytical technologies</td>
			<td></td>
			<td>Microarray scanner</td>
		</tr>
		<tr>
			<td>Sodium bicarbonate</td>
			<td>SigmaAldrich</td>
			<td>104766</td>
			<td></td>
		</tr>
	</tbody>
</table>

a fast and reliable pipeline for bacterial transcriptome analysis case study: serine-dependent gene regulation in streptococcus pneumoniae

基因表达及其调控是了解细胞在不同条件下的行为非常重要。使用各种技术现今研究基因表达，但大部分是在提供全转录的表达的总体图象方面受到限制。 DNA微阵列提供了快速和经济研究的技术，这给全局基因表达的全面概述，并且具有的大量应用，包括鉴定新基因和转录因子结合位点，该细胞的转录活性的表征以及在分析数千个帮助基因（在单次实验）。在本研究中，从细胞收获到DNA微阵列分析细菌转录组分析的条件进行了优化。考虑到时间，成本和实验的精度，该技术平台被证明是非常有用的和普遍applicabale用于研究细菌transcriptoMES。在这里，我们通过对比S的转录反应进行DNA微阵列分析与肺炎链球菌作为一个案例研究肺炎生长在不同的L-丝氨酸的浓度在培养基中的存在。分离总RNA通过使用使用RNA分离试剂盒和RNA的质量Macaloid方法通过使用RNA质量检查试剂盒检查。制备cDNA用逆转录酶和该cDNA样品使用两个胺反应性荧光染料1标记。自制DNA微阵列载玻 ​​片用于标记的cDNA样品和微阵列数据的杂交通过使用cDNA微阵列数据前处理框架（Microprep）进行了分析。最后，网络-T是用来分析使用Microprep为统计学显著差异表达的基因的识别生成的数据。此外，在公司内部建立软件包（辣椒，FIVA，披露，检察官，Genome2D）被用来分析数据。

RNA，基因隔离和分析 L-丝氨酸是必需的氨基酸之一，其在人类血浆浓度从60-150微米的儿童和成人不相同。其中嘌呤和嘧啶的生物合成作用凸显其重要性在代谢和它的前体，以数个氨基酸（甘氨酸，半胱氨酸和色氨酸）。以研究L-丝氨酸对S的全转录的影响肺炎 D39野生型菌株，生长在CDM与针对该中的最大浓度（10毫米），在相同的培养基中生长的L-丝氨...

Watch this Scientific Journal Video about A Fast and Reliable Pipeline for Bacterial Transcriptome Analysis Case study: Serine-dependent Gene Regulation in Streptococcus pneumoniae at JoVE.com

A Fast and Reliable Pipeline for Bacterial Transcriptome Analysis Case study: Serine-dependent Gene Regulation in Streptococcus pneumoniae

This manuscript describes the use of state-of-the-art technology provided by DNA-microarrays. Microarrays provide an overview of the transcriptomic changes in bacteria incurred under a specific condition. Moreover, we highlight the ease by which large amounts of data can be analyzed by using convenient in-house developed software packages.

在丝氨酸依赖的基因调控:一个快速和可靠的管道细菌转录组分析案例研究<em&gt;肺炎链球菌</em

Gene expression and its regulation are very important to understand the behavior of cells under different conditions. Various techniques are used nowadays ...

a-fast-reliable-pipeline-for-bacterial-transcriptome-analysis-case

Research

JoVE Journal

Biology

A Fast and Reliable Pipeline for Bacterial Transcriptome Analysis Case study: Serine-dependent Gene Regulation in Streptococcus pneumoniae

10.3K 次观看.  University of Groningen. This manuscript describes the use of state-of-the-art technology provided by DNA-microarrays. Microarrays provide an overview of the transcriptomic changes in bacteria incurred under a specific condition. Moreover, we highlight the ease by which large amounts of data can be analyzed by using convenient in-house developed software packages. 

视频: A Fast and Reliable Pipeline for Bacterial Transcriptome Analysis Case study: Serine-dependent Gene Regulation in Streptococcus pneumoniae

Bacterial Gene Expression Analysis Using Microarrays

使用微阵列的细菌基因表达分析

科研

生物学

In vitro Reconstitution of the Active T. castaneum Telomerase

Efforts to isolate the catalytic subunit of telomerase, TERT, in sufficient quantities for structural studies, have been met with limited success for more than a decade. Here, we present methods for the isolation of the recombinant Tribolium castaneum TERT (TcTERT) and the reconstitution of the active T. castaneum telomerase ribonucleoprotein (RNP) complex in vitro.
Telomerase is a specialized reverse transcriptase1 that adds short DNA repeats, called telomeres, to the 3' end of linear chromosomes2 that serve to protect them from end-to-end fusion and degradation. Following DNA replication, a short segment is lost at the end of the chromosome3 and without telomerase, cells continue dividing until eventually reaching their Hayflick Limit4. Additionally, telomerase is dormant in most somatic cells5 in adults, but is active in cancer cells6 where it promotes cell immortality7.
The minimal telomerase enzyme consists of two core components: the protein subunit (TERT), which comprises the catalytic subunit of the enzyme and an integral RNA component (TER), which contains the template TERT uses to synthesize telomeres8,9. Prior to 2008, only structures for individual telomerase domains had been solved10,11. A major breakthrough in this field came from the determination of the crystal structure of the active12, catalytic subunit of T. castaneum telomerase, TcTERT1.
Here, we present methods for producing large quantities of the active, soluble TcTERT for structural and biochemical studies, and the reconstitution of the telomerase RNP complex in vitro for telomerase activity assays. An overview of the experimental methods used is shown in Figure 1.

In vitro Reconstitution of the Active T. castaneum Telomerase

Efforts to isolate the catalytic subunit of telomerase, TERT, in sufficient quantities for structural studies, have been met with limited success for more than a decade. Here, we present methods for the isolation of the recombinant Tribolium castaneum TERT (TcTERT) and the reconstitution of the active T. castaneum telomerase ribonucleoprotein (RNP) complex in vitro.

在体外重组活跃T。谷盗端粒酶

Efforts to isolate the catalytic subunit of telomerase, TERT, in sufficient quantities for structural studies, have been met with limited success for more ...

Isolation of Ribosome Bound Nascent Polypeptides in vitro to Identify Translational Pause Sites Along mRNA

The rate of translational elongation is non-uniform. mRNA secondary structure, codon usage and mRNA associated proteins may alter ribosome movement on the messagefor review see 1. However, it's now widely accepted that synonymous codon usage is the primary cause of non-uniform translational elongation rates1. Synonymous codons are not used with identical frequency. A bias exists in the use of synonymous codons with some codons used more frequently than others2. Codon bias is organism as well as tissue specific2,3. Moreover, frequency of codon usage is directly proportional to the concentrations of cognate tRNAs4. Thus, a frequently used codon will have higher multitude of corresponding tRNAs, which further implies that a frequent codon will be translated faster than an infrequent one. Thus, regions on mRNA enriched in rare codons (potential pause sites) will as a rule slow down ribosome movement on the message and cause accumulation of nascent peptides of the respective sizes5-8. These pause sites can have functional impact on the protein expression, mRNA stability and protein foldingfor review see 9. Indeed, it was shown that alleviation of such pause sites can alter ribosome movement on mRNA and subsequently may affect the efficiency of co-translational (in vivo) protein folding1,7,10,11. To understand the process of protein folding in vivo, in the cell, that is ultimately coupled to the process of protein synthesis it is essential to gain comprehensive insights into the impact of codon usage/tRNA content on the movement of ribosomes along mRNA during translational elongation.
Here we describe a simple technique that can be used to locate major translation pause sites for a given mRNA translated in various cell-free systems6-8. This procedure is based on isolation of nascent polypeptides accumulating on ribosomes during in vitro translation of a target mRNA. The rationale is that at low-frequency codons, the increase in the residence time of the ribosomes results in increased amounts of nascent peptides of the corresponding sizes. In vitro transcribed mRNA is used for in vitro translational reactions in the presence of radioactively labeled amino acids to allow the detection of the nascent chains. In order to isolate ribosome bound nascent polypeptide complexes the translation reaction is layered on top of 30% glycerol solution followed by centrifugation. Nascent polypeptides in polysomal pellet are further treated with ribonuclease A and resolved by SDS PAGE. This technique can be potentially used for any protein and allows analysis of ribosome movement along mRNA and the detection of the major pause sites. Additionally, this protocol can be adapted to study factors and conditions that can alter ribosome movement and thus potentially can also alter the function/conformation of the protein.

Isolation of Ribosome Bound Nascent Polypeptides in vitro to Identify Translational Pause Sites Along mRNA

A technique to identify translational pause sites on mRNA is described. This procedure is based on isolation of nascent polypeptides accumulating on ribosomes during in vitro translation of a target mRNA, followed by the size analysis of the nascent chains using a denaturing gel electrophoresis.

核糖体束缚新生多肽的分离<em&gt;在体外</em&gt;确定沿mRNA的翻译暂停网站

The rate of translational elongation is non-uniform. mRNA secondary structure, codon usage and mRNA associated proteins may alter ribosome movement on the ...

Using SecM Arrest Sequence as a Tool to Isolate Ribosome Bound Polypeptides

Extensive research has provided ample evidences suggesting that protein folding in the cell is a co-translational process1-5. However, the exact pathway that polypeptide chain follows during co-translational folding to achieve its functional form is still an enigma. In order to understand this process and to determine the exact conformation of the co-translational folding intermediates, it is essential to develop techniques that allow the isolation of RNCs carrying nascent chains of predetermined sizes to allow their further structural analysis.
SecM (secretion monitor) is a 170 amino acid E. coli protein that regulates expression of the downstream SecA (secretion driving) ATPase in the secM-secA operon6. Nakatogawa and Ito originally found that a 17 amino acid long sequence (150-FSTPVWISQAQGIRAGP-166) in the C-terminal region of the SecM protein is sufficient and necessary to cause stalling of SecM elongation at Gly165, thereby producing peptidyl-glycyl-tRNA stably bound to the ribosomal P-site7-9. More importantly, it was found that this 17 amino acid long sequence can be fused to the C-terminus of virtually any full-length and/or truncated protein thus allowing the production of RNCs carrying nascent chains of predetermined sizes7. Thus, when fused or inserted into the target protein, SecM stalling sequence produces arrest of the polypeptide chain elongation and generates stable RNCs both in vivo in E. coli cells and in vitro in a cell-free system. Sucrose gradient centrifugation is further utilized to isolate RNCs.
The isolated RNCs can be used to analyze structural and functional features of the co-translational folding intermediates. Recently, this technique has been successfully used to gain insights into the structure of several ribosome bound nascent chains10,11. Here we describe the isolation of bovine Gamma-B Crystallin RNCs fused to SecM and generated in an in vitro translation system.

We describe here a technique that is now routinely used to isolate stably bound ribosome nascent chain complexes (RNCs). This technique takes advantage of the discovery that a 17 amino acid long SecM "arrest sequence" can halt translation elongation in a prokaryotic (E. coli) system, when inserted into (or fused to the C-terminus) of virtually any protein.

作为一种工具来隔离核糖体的束缚多肽SECM逮捕序列

Extensive research has provided ample evidences suggesting that protein folding in the cell is a co-translational process1-5. However, the exact pathway ...

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

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

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

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

全基因组基因缺失<em&gt;链球菌血统</em通过高通量PCR

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

Analysis of Global RNA Synthesis at the Single Cell Level following Hypoxia

Hypoxia or lowering of the oxygen availability is involved in many physiological and pathological processes. At the molecular level, cells initiate a particular transcriptional program in order to mount an appropriate and coordinated cellular response. The cell possesses several oxygen sensor enzymes that require molecular oxygen as cofactor for their activity. These range from prolyl-hydroxylases to histone demethylases. The majority of studies analyzing cellular responses to hypoxia are based on cellular populations and average studies, and as such single cell analysis of hypoxic cells are seldom performed. Here we describe a method of analysis of global RNA synthesis at the single cell level in hypoxia by using Click-iT RNA imaging kits in an oxygen controlled workstation, followed by microscopy analysis and quantification.&nbsp; Using cancer cells exposed to hypoxia for different lengths of time, RNA is labeled and measured in each cell. This analysis allows the visualization of temporal and cell-to-cell changes in global RNA synthesis following hypoxic stress.

We describe a technique for analysis of global RNA synthesis in hypoxia using imaging. Click-chemistry labeling of RNA has not previously been performed under hypoxia and allows visualization of global RNA changes at the single cell level. This approach complements the existing averaged RNA techniques, allowing direct visualization of cell-to-cell changes in global RNA synthesis.

全球合成的RNA在单细胞水平以下的低氧分析

Hypoxia or lowering of the oxygen availability is involved in many physiological and pathological processes. At the molecular level, cells initiate a ...

siRNA Screening to Identify Ubiquitin and Ubiquitin-like System Regulators of Biological Pathways in Cultured Mammalian Cells

Post-translational modification of proteins with ubiquitin and ubiquitin-like molecules (UBLs) is emerging as a dynamic cellular signaling network that regulates diverse biological pathways including the hypoxia response, proteostasis, the DNA damage response and transcription.&#160; To better understand how UBLs regulate pathways relevant to human disease, we have compiled a human siRNA &#8220;ubiquitome&#8221; library consisting of 1,186 siRNA duplex pools targeting all known and predicted components of UBL system pathways. This library can be screened against a range of cell lines expressing reporters of diverse biological pathways to determine which UBL components act as positive or negative regulators of the pathway in question.&#160; Here, we describe a protocol utilizing this library to identify ubiquitome-regulators of the HIF1A-mediated cellular response to hypoxia using a transcription-based luciferase reporter.&#160; An initial assay development stage is performed to establish suitable screening parameters of the cell line before performing the screen in three stages: primary, secondary and tertiary/deconvolution screening. &#160;The use of targeted over whole genome siRNA libraries is becoming increasingly popular as it offers the advantage of reporting only on members of the pathway with which the investigators are most interested.&#160; Despite inherent limitations of siRNA screening, in particular false-positives caused by siRNA off-target effects, the identification of genuine novel regulators of the pathways in question outweigh these shortcomings, which can be overcome by performing a series of carefully undertaken control experiments.

Here, we describe a methodology to perform a targeted siRNA &#8220;ubiquitome&#8221; screen to identify novel ubiquitin and ubiquitin-like regulators of the HIF1A-mediated cellular response to hypoxia.&#160; This can be adapted to any biological pathway where a robust read out of reporter activity is available.

siRNA的筛选识别泛素和泛素样系统压力表生物学途径在培养的哺乳动物细胞

Post-translational modification of proteins with ubiquitin and ubiquitin-like molecules (UBLs) is emerging as a dynamic cellular signaling network that ...

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 ...

Genetic and Biochemical Approaches for In Vivo and In Vitro Assessment of Protein Oligomerization: The Ryanodine Receptor Case Study

Oligomerization is often a structural requirement for proteins to accomplish their specific cellular function. For instance, tetramerization of the ryanodine receptor (RyR) is necessary for the formation of a functional Ca2+ release channel pore. Here, we describe detailed protocols for the assessment of protein self-association, including yeast two-hybrid (Y2H), co-immunoprecipitation (co-IP) and chemical cross-linking assays. In the Y2H system, protein self-interaction is detected by &#946;-galactosidase assay in yeast co-expressing GAL4 bait and target fusions of the test protein. Protein self-interaction is further assessed by co-IP using HA- and cMyc-tagged fusions of the test protein co-expressed in mammalian HEK293 cells. The precise stoichiometry of the protein homo-oligomer is examined by cross-linking and SDS-PAGE analysis following expression in HEK293 cells. Using these different but complementary techniques, we have consistently observed the self-association of the RyR N-terminal domain and demonstrated its intrinsic ability to form tetramers. These methods can be applied to protein-protein interaction and homo-oligomerization studies of other mammalian integral membrane proteins.

Genetic and Biochemical Approaches for In Vivo and In Vitro Assessment of Protein Oligomerization: The Ryanodine Receptor Case Study

Oligomerization of the ryanodine receptor, a homo-tetrameric ion channel mediating Ca2+ release from intracellular stores, is critical for skeletal and cardiac muscle contraction. Here, we present complementary in vivo and in vitro methods to detect protein self-association and determine homo-oligomer stoichiometry.

遗传和生物化学方法<em&gt;在体内</em&gt;和<em&gt;体外</em&gt;蛋白齐聚评估:兰尼碱受体案例研究

Oligomerization is often a structural requirement for proteins to accomplish their specific cellular function. For instance, tetramerization of the ...

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 ...