The authors would like to acknowledge Marcos Di Falco for his expertise and advice with the preparation of the samples for nano-LC MS/MS as well as Dr. Zoran Minic from the University of Regina for the LC MS/MS analysis. This work was supported by NSERC (DG402214-2011) and CRC (950-221184) funding. D.C. was supported by Concordia Institute for Water, Energy, and Sustainable Systems and FQRNT.

1.准备试剂<ol><li>制备的SDS-萃取溶液:0.1M的Tris-HCl pH为7.5，5％甘油，10mM EDTA的和1％SDS。过滤消毒使用0.22微米的过滤器，并储存在4℃。 </li><li>备所需的聚丙烯酰胺凝胶的库存试剂。 <ol><li>准备1.5米的Tris-HCl pH值8.8。过滤消毒使用0.22微米的过滤器，并在室温下储存。 </li><li>的0.5M的Tris-HCl pH 6.8的。过滤消毒使用0.22微米的过滤器，并在室温下储存。 </li><li>准备10％SDS。过滤消毒使用0.22微米的过滤器，并在室温下储存。 </li></ol></li><li>需要准备在凝胶胰蛋白酶消化和肽的提取解决方案。 <ol><li>制备100mM碳酸氢铵。过滤消毒使用0.22微米的过滤器，并储存在4℃。 </li><li>准备1 M DTT股票。在-80℃下悬浮于100mM碳酸氢铵和存储。 </li><li>准备550毫米碘乙酰胺的股票。悬浮在100mM碳酸氢铵和储存在-80℃。 </li><li>准备100毫微克/微升胰蛋白酶的股票。分装60微升到的1.5 ml离心管中，并储存在-80℃。 </li><li>制备提取溶液:1％甲酸，2％乙腈。 </li><li>制备悬浮液:5％乙腈和0.1％甲酸。 </li></ol></li></ol> 2.执行细胞裂解插装过滤单元与单元格保存在RNA稳定的解决方案<ol><li>排出从盒滤波器单元（1.5毫升）并进入使用60毫升注射器附接在过滤器的路厄氏锁端2ml微量离心管中的RNA的稳定溶液。 </li><li>离心2 ml离心管10分钟，在17000×g离心以沉淀任何细胞碎片。这样做是使得在步骤2.3的过滤器不堵塞。 </li><li>转移上清液至10 K时超离心过滤器单元以捕获任何蛋白质从细胞中始发，从冻结/ THA已经裂解W精品样品。不要弃沉淀。它将在步骤2.5中使用。在3270×g离心30分钟，或直到体积进行超离心过滤装置的离心分离降低至约600微升。 </li><li>熔化P10尖端的尖端和与尖端的开口端阻塞筒式过滤器单元的非鲁尔锁边。这将确保没有提取缓冲液和生物质在步骤2.5-2.7逸出。 </li><li>暂停沉淀在1毫升SDS-提取解决方案，并吸取其插入原装墨盒过滤装置。以吸管进筒式过滤器单元的最简单方法是叠加P200的尖端到P1000的提示，并用这双尖移液。 </li><li>加入1毫升的SDS提取溶液的筒式过滤器单元，以便总体积是约2ml孵育在室温下10分钟，同时在一个杂交炉旋转。放置3皱实验室湿巾在50ml锥形管的底部。封口膜筒式过滤器单元的封闭两端并把滤芯过滤单元进50毫升管。盖上盖子，把试管放入杂交炉。 </li><li> 10分钟后，代替STERIVEX筛选泡沫浮子和用5毫升注射器的鲁尔锁端将其固定在适当位置。 Float和孵育在95℃水浴15分钟。 </li><li>让暗盒滤波器单元凉爽并旋转在室温下进行1小时（如在步骤2.6）。 </li><li>驱逐SDS提取溶液/细胞裂解物从过滤器与一个60毫升注射器到相同的超离心过滤器单元如前（步骤2.3）。加入1毫升新鲜SDS提取溶液到盒过滤器单元，并用手混合30秒钟，然后使用60毫升注射器的驱逐进入超离心过滤器单元。这是为了冲洗筒式过滤器单元，以确保所有的蛋白质已被除去。 </li><li>该超离心过滤单元上，在3270×g离心，或直到在过滤器单元中的体积进行离心45分钟，小于600微升。 </li><li>弃流过加满油的超离心过滤装置用新鲜的SDS萃取液。 </li><li>离心过滤器单元，用于在3270×g下另外45分钟。 </li><li>重复步骤2.11和2.12两次。确保在超离心过滤单元中的最终体积为至多600微升在最后的旋转的末端。 </li><li>在这一点上，一分为二的浓缩物。一小部分将被用于DNA沉淀，另一个用于蛋白质沉淀。 注意:分馏量取决于生物质的过滤的量和产品的预定用途。在我们的例子中，我们拆分精矿对DNA沉淀10％，对蛋白质沉淀的90％。 </li></ol> 3.蛋白沉淀<ol><li>添加4体积的甲醇:丙酮（50:50），以浓缩物和涡流一体积为10秒。孵育过夜，在-20℃下。 </li><li>降速在17000 XG 30分钟。倒出上清液并让沉淀（可以是不可见的）的干燥在speedvac中1小时（或直到干）。 注意:不要过度干燥沉淀，因为这可能使其难以悬浮。 </li><li>暂停在25微升的SDS-萃取溶液沉淀。让我们坐1小时，然后通过上下吹打重悬。 </li><li>使用蛋白质检测试剂盒和制造商的说明定量蛋白质。 </li></ol> 4. DNA沉淀<ol><li>加入SDS-提取液到浓缩馏分可以用于DNA沉淀，直至500微升标记。这个步骤是简单地增加溶液的体积，使之更易于使用。 </li><li>添加0.583体积的蛋白质沉淀试剂（如MPC的蛋白质沉淀试剂），涡旋10秒。你应该会看到一个白色的沉淀物的形式。 注意:我们也使用苯酚:氯仿提取DNA的方法，但它更困难的，由于低的卷。我们利用获得更好的DNA产量MPC蛋白沉淀试剂。 </li><li>离心机在17000×g离心4℃10分钟。 </li><li>上清转移到另一个的1.5 ml离心管中，加入0.95倍体积的异丙醇。倒置30-40倍。 </li><li>离心机在4℃下10分钟，在最大速度。 </li><li>小心倒出并弃去上清液。 </li><li>用750微升的70％乙醇冲洗两次。 </li><li>除去尽可能多的乙醇可以通过吸液，然后让空气干燥。 注意:不要过度干燥的DNA，因为这可能使其难以悬浮。 </li><li>重悬在25微升的TE低缓冲液，pH 8中（10mM的Tris-HCl，0.1mM的EDTA）中的。 </li><li>量化使用双链DNA测定试剂盒和制造商的说明将DNA。上3微升的DNA进行琼脂糖凝胶（1％）电泳以检查其质量。 </li></ol>蛋白质5. SDS-PAGE凝胶<ol><li>制备样品缓冲液（950微升Laemmli样品缓冲液和50微升β巯基乙醇）。&lt;/ LI&gt; <li>添加了15微克蛋白的相应量，或20微升max与样品缓冲液等体积​​和煮沸4分钟。样品现在可以储存在-80℃直至SDS-PAGE上可以执行。 </li><li>准备用5％丙烯酰胺积层凝胶10％丙烯酰胺分辨凝胶。 </li><li>加载样品和4微升的蛋白质梯的凝胶。运行在恒定的120 V的凝胶，直到250 kDa的阶梯标志刚刚达成的解决凝胶。 </li><li>染色使用根据制造商的说明书基于污渍考马斯凝胶。 </li></ol> 6.在凝胶胰蛋白酶消化和肽提取注:在生物安全柜中进行所有从这里步骤，直到6.10，以减少污染。 <ol><li>在10 kDa的阶梯大关每个车道切掉多余的凝胶。每个线将会在MS / MS分别进行分析。切割每个泳道成1mm×1mm的正方形以增加表面面积，并放置所有SQUA水库从车道进入低结合微离心管中。重复此为所有车道。 （1％乙酸可以用来防止凝胶干涸，成为难以切割）。 注意:最小化污染是非常关键的，在这个阶段，所以凝胶切片在上用于制造凝胶的玻璃SDS-PAGE凝胶铸型生物安全柜内进行。 </li><li>去色斑<ol><li>分配50微升100mM碳酸氢铵成每个低结合管，靠近帽孵育在37℃下进行10分钟。 </li><li>免除50微升的乙腈，接近上限，37℃下5分钟。 </li><li>吸并丢弃150微升。 </li><li>重复步骤6.2.1和6.2.2。 </li><li>吸并丢弃95微升。 </li></ol></li><li>脱水<ol><li>免除50微升乙腈，接近上限，并等待5分钟。吸并丢弃45微升，并等待10分钟。 </li></ol></li><li>减少<ol><li>免除加入50μlDTT（10mM的，稀释在100mM AMM鎓碳酸氢盐），关闭盖子，等待30分钟，在37℃。 </li></ol></li><li>烷基化<ol><li>分配50μl的碘乙酰胺（55毫，稀释在100mM碳酸氢铵），靠近帽和等待20分钟，在37℃。 </li><li>免除100微升乙腈，靠近帽和孵化5分钟，在37℃。吸并丢弃195微升。 </li></ol></li><li>洗刷<ol><li>分配50μl的碳酸氢铵，靠近帽并孵育10分钟，在37℃。 </li><li>免除50微升的乙腈，接近上限，37℃下5分钟。吸并丢弃120微升。 </li></ol></li><li>脱水<ol><li>免除50微升乙腈，接近上限，并等待5分钟。吸并丢弃45微升。 </li><li>免除50微升乙腈，等待5分钟。 </li><li>吸并丢弃75微升，并等待5分钟。 </li></ol></li><li>消化<ol><li>免除微升6月25日至三十○号纳克/μL胰蛋白酶（UNTIL所有凝胶碎片覆盖）。关闭帽并等待30分钟，在室温下进行。 </li><li>孵育过夜（4.5小时最小值），在37℃。 </li><li>让在室温下坐30分钟。 </li></ol></li><li>提取和肽转移<ol><li>免除30微升的提取液，盖上盖子，在冰上30分钟。 </li><li>吸取30微升，并分配一个新的标记低结合管吸气量。 </li><li>分配12微升提取液和12微升乙腈成原管（凝胶）。关闭盖子，并培育在冰上30分钟。 </li><li>吸取15微升并存入新的管。 </li><li>重复步骤（6.9.3和6.9.4）。 </li></ol></li><li>将新管在Speed​​Vac中待干。 </li><li>重悬在50μl再悬浮溶液。涡流的培养基上10分钟以悬浮。 </li><li>吸管肽溶液进入任一纳米/ LC小瓶或96孔板适于纳米/ LCMS / MS的工作。 </li></ol>

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H., Olsen, J., Mann, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In-gel+digestion+for+mass+spectrometric+characterization+of+proteins+and+proteomes.">In-gel digestion for mass spectrometric characterization of proteins and proteomes.</a> Nature protocols. 1 (6), 2856-2860 (2007).</li><li>Thomas, T., Gilbert, J., Meyer, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Metagenomics+-+a+guide+from+sampling+to+data+analysis.">Metagenomics - a guide from sampling to data analysis.</a> Microbial Informatics and Experimentation. 2 (1), 3 (2012).</li><li>Huson, D. H., Auch, A. F., Qi, J., Schuster, S. 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The authors have nothing to disclose.

样品保存的关键是metaproteomic研究和以往的研究显示一种RNA稳定的解决方案是之前的蛋白质提取28存储单元一个有用的存储缓冲器。理想情况下，样品将在原地保留处理33,34中否定蛋白表达变化。事实上，原位采样和固定技术已经发展，其允许自主收集和保存的样品的由船部署仪器。但是，获得这些技术并不总是可行的。在于它是不常见的情况下，样品应尽快采集后保?...

微生物是无处不在，发挥在地球的生物地球化学循环1重要作用。目前，可用于表征微生物群落结构和功能众多的分子生物学方法。最常见的是16S rRNA基因的序列分析PCR扩增从环境的DNA 2 - 4。的16S rRNA基因分析的缺点在于，它仅提供了有关系统发育特征和社区结构信息，具有信息很少代谢功能。与此相反，方法，如宏基因组学，metatranscriptomics和metaproteomics提供群落结构和新陈代谢的信息。宏基因组学，或生物体的集合体的基因含量的分析，提供了有关社区5的结构和功能的潜在的信息- 8。虽然功能强大，该功能的潜在可能与代谢生物体的活动。一个生物体的基因型是由它的基因，其每一个可以被转录为RNA和进一步翻译为蛋白质，从而导致表型来表示。因此，为了在微生物的功能活性的理解有助于在一个环境，后基因组分析应进行9。因为它揭示了哪些基因被转录，在任何给定的环境Metatranscriptomics，或RNA转录物的分析是有用的。然而，mRNA水平并不总是与它们相应的蛋白质水平由于翻译调控，核糖核酸半衰期，并且可以为每10 mRNA的生成的多个蛋白副本的事实。 由于这些原因metaproteomics现已被公认为对环境微生物学的重要工具。常见metaproteomic分析用散弹枪蛋白质组学的方法，其中的蛋白质在复杂样品的近满装被纯化，并同时进行分析，通常是通过连接zymatic消化成肽和分析质谱仪。随后的串联质谱（MS / MS）"肽指纹识别"用于确定肽序列和原籍潜在蛋白由蛋白质数据库中搜索（综述见11）。蛋白质组的工作已经走过了漫长的道路，在过去25年由于增加的基因组数据的可用性和增加灵敏度和质谱仪，可用于高通量蛋白质鉴定和定量11,12的准确性。因为蛋白质是基因表达的终产物，metaproteomic数据可以帮助确定哪些生物体是活性，在任何给定的环境，什么蛋白他们表达。试图确定一组特定的环境变量会影响生物或社区的表型时，这是有利的。在早期，在海洋中的MS / MS基于metaproteomic研究中使用，以确定在目标特异性蛋白微生物谱系，与第一项研究聚焦在光驱动质子泵遗传工程中SAR11海洋细菌13。最近，比较metaproteomic分析已经阐明复杂的群体之间的差异蛋白质表达谱。例子包括代谢时间的变化在沿海西北大西洋14或南极半岛5的识别 。其他的研究已经在蛋白表达模式描述的变化跨越空间尺度，例如，沿一个地理断面从一个低营养海洋环流到高生产力的沿海上升流系统 15。对于metaproteomics进一步审查建议施奈德等人（2010）9和威廉姆斯等人 （2014）16。目标蛋白质组也已应用在近几年来量化在环境17,18特定的代谢途径的表达。 疗法e为在metaproteomic分析三个主要阶段。第一阶段是样品制备，其包括样品收集，细胞裂解和蛋白的浓度。海洋微生物学样品收集往往造成工作海水的过滤通过一个预过滤器，以去除较大的真核细胞，颗粒和微粒相关的细菌，然后进行过滤的游离活的微生物细胞的捕获，一般与使用0.22μm的盒的过滤单元19,20。这些过滤器incased在一个塑料缸和细胞裂解和蛋白提取协议，可以在过滤器单元内执行将是有价值的工具。一旦获得生物量，将细胞必须被裂解，以允许蛋白质提取。几种方法可以采用，包括盐酸胍裂解21和十二烷基硫酸钠（SDS）基裂解的方法。尽管像SDS洗涤剂非常有效地破坏细胞膜和溶解许多蛋白质​​种类，concentratiONS低至0.1％，可与下游的蛋白质的消化和质谱分析22干扰。主要关注的是SDS对胰蛋白酶消化效率的负面影响，解决的反相液相色谱法和离子抑制或堆积在离子源23中的电力。 第二阶段是分馏和分析，其中将蛋白进行酶消化，随后通过LC MS / MS分析，结果，可用于确定初始胰蛋白酶肽的一级氨基酸序列上午/ Z裂解谱。各种消化方法可根据所用洗涤剂的类型，以及下游质谱工作流来执行。在我们的协议，1-D PAGE电泳随后从凝胶去除SDS的被利用，以除去任何污染的洗涤剂。蛋白质，是难以溶解，如膜蛋白的分析，需要使用高concen的SDS或其他洗涤剂trations。这导致带SDS-凝胶电泳兼容性问题。如果研究的目标需要的这些坚硬的溶解以溶解的蛋白质，管-凝胶系统可以用来22,24。管 - 凝胶法结合了凝胶基质内的蛋白质，而无需使用电泳的。随后用于溶解任何洗涤剂蛋白质消化之前被除去。 第三个阶段是生物信息学分析。在这个阶段，MS / MS的肽数据被搜索对翻译的核苷酸序列的数据库，以确定哪些肽和蛋白质都存在于样品中。肽的识别取决于其搜索对数据库。海洋metaproteomic数据针对由参考基因组，宏基因组的数据，如全球海洋采样数据集25，以及从未开垦利单细胞扩增的基因组数据库搜索的结果通常neages 26,27。蛋白质鉴定也可以从同一个样品增加通过包含宏基因组序列作为metaproteomic数据推导5。 在这里，我们提供了一个协议，用于通过过滤收集并存储在一个稳定的RNA溶液的肽适用于MS / MS为基础的分析从微生物生物质的产生。这里所描述的协议允许DNA和蛋白质也可以从相同的样品，使所有的步骤导致到蛋白质和DNA沉淀是相同的分离。从实践的角度，需要更少的过滤，因为只有一个过滤器所需的蛋白质和DNA提取。我们还要承认，该协议是通过两个先前公布的协议相结合，改编和修改创建。细胞溶解步骤适于从齐藤等人 （2011）28和在凝胶胰蛋白酶消化成分适于从ShevcheNKO等。 （2007年）29。

<table><tbody><tr><td>Sterivex -GP 0.22 &amp;mu;m filter unit</td><td>Millipore</td><td>SVGP01050</td><td>Sampling</td></tr><tr><td>RNAlater Stabilization Solution</td><td>Ambion</td><td>AM7021</td><td>Sampling</td></tr><tr><td>Tris&amp;nbsp;</td><td>Bio Basic</td><td>77-86-1 or TB0196-500G</td><td>Protein Extraction/ SDS PAGE gel</td></tr><tr><td>DTT</td><td>Sigma-Aldrich</td><td>D0632-1G</td><td>Protein Extraction</td></tr><tr><td>SDS</td><td>Bio Basic</td><td>15-21-3</td><td>Protein Extraction/ SDS PAGE gel</td></tr><tr><td>EDTA</td><td>Bio Basic</td><td>6381-92-6</td><td>Protein Extraction</td></tr><tr><td>Glycerol</td><td>Fisher Scientific</td><td>56-81-5</td><td>Protein Extraction</td></tr><tr><td>10K Amicon Filter</td><td>Millipore</td><td>UFC801024</td><td>Protein Extraction</td></tr><tr><td>Methanol</td><td>Sigma-Aldrich</td><td>179337-4L</td><td>Protein Precipitation</td></tr><tr><td>Acetone</td><td>Fisher Scientific</td><td>67-64-1</td><td>Protein Precipitation</td></tr><tr><td>MPC Protein Precipitation reagent</td><td>Epicenter</td><td>mmP03750</td><td>DNA Precipitation</td></tr><tr><td>2-Propanol</td><td>Fisher Scientific</td><td>67-63-0</td><td>DNA Precipitation</td></tr><tr><td>Qubit dsDNA BR Assay kit</td><td>Life Technologies</td><td>Q32850</td><td>DNA Quantification</td></tr><tr><td>Qubit Protein Assay kit</td><td>Life Technologies</td><td>Q33211</td><td>Protein Quantification</td></tr><tr><td>Sucrose</td><td>Bio Basic</td><td>57-50-1</td><td>SDS PAGE gel</td></tr><tr><td>TEMED</td><td>Bio Rad</td><td>161-0800</td><td>SDS PAGE gel</td></tr><tr><td>APS</td><td>Bio Rad</td><td>161-0700</td><td>SDS PAGE gel</td></tr><tr><td>30% Acrylamide</td><td>Bio Rad</td><td>161-0158</td><td>SDS PAGE gel</td></tr><tr><td>SimplyBlue SafeStain</td><td>Invitrogen</td><td>LC6060</td><td>SDS PAGE gel</td></tr><tr><td>Glycine</td><td>Bio Rad</td><td>161-0718</td><td>SDS PAGE gel</td></tr><tr><td>B-mercaptoethanol</td><td>Bio Basic</td><td>60-24-2</td><td>SDS PAGE gel</td></tr><tr><td>Laemmli Sample Buffer</td><td>Bio Rad</td><td>161-0737</td><td>SDS PAGE gel</td></tr><tr><td>Precision Plus Protein Kaleidoscope Ladder</td><td>Bio Rad</td><td>161-0375EDU</td><td>SDS PAGE gel</td></tr><tr><td>Acetonitrile</td><td>VWR</td><td>CABDH6044-4</td><td>In-gel Trypsin digest</td></tr><tr><td>NH4HCO3</td><td>Bio Basic</td><td>1066-33-7</td><td>In-gel Trypsin digest</td></tr><tr><td>DTT</td><td>Sigma-Aldrich</td><td>D0632-1G</td><td>In-gel Trypsin digest</td></tr><tr><td>Formic Acid</td><td>Sigma-Aldrich</td><td>F0507-500ML</td><td>In-gel Trypsin digest</td></tr><tr><td>HPLC grade H2O</td><td>Sigma-Aldrich</td><td>270733-4L</td><td>In-gel Trypsin digest</td></tr><tr><td>Iodoacetamide</td><td>Bio Basic</td><td>144-48-9</td><td>In-gel Trypsin digest</td></tr><tr><td>Trypsin</td><td>Promega</td><td>V5111</td><td>In-gel Trypsin digest</td></tr><tr><td>Protein LoBind Tube 1.5 ml</td><td>Eppendorf</td><td>22431081</td><td>In-gel Trypsin digest</td></tr><tr><td>2 ml ROBO vial 9 mm</td><td>Candian Life Science</td><td>VT009/C395SB</td><td>In-gel Trypsin digest</td></tr><tr><td>PP BM insert, No spring</td><td>Candian Life Science</td><td>4025P-631</td><td>In-gel Trypsin digest</td></tr></tbody></table>

an aquatic microbial metaproteomics workflow: from cells to tryptic peptides suitable for tandem mass spectrometry-based analysis

Meta-omic technologies such as metagenomics, metatranscriptomics and metaproteomics can aid in the understanding of microbial community structure and metabolism. Although powerful, metagenomics alone can only elucidate functional potential. On the other hand, metaproteomics enables the description of the expressed in situ metabolism and function of a community. Here we describe a protocol for cell lysis, protein and DNA isolation, as well as peptide digestion and extraction from marine microbial cells collected on a cartridge filter unit (such as the Sterivex filter unit) and preserved in an RNA stabilization solution (like RNAlater). In mass spectrometry-based proteomics studies, the identification of peptides and proteins is performed by comparing peptide tandem mass spectra to a database of translated nucleotide sequences. Including the metagenome of a sample in the search database increases the number of peptides and proteins that can be identified from the mass spectra. Hence, in this protocol DNA is isolated from the same filter, which can be used subsequently for metagenomic analysis.

作为示范，我们进行从表面和叶绿素最大的近海在加拿大北部收集2海水样品的协议。在海上，6-7大号海水通过一个3微米的GF / D预滤器被传递，然后下面的沃尔什等人 20的协议的微生物细胞被收集到0.22微米的筒式过滤器单元。细胞立即储存在RNA稳定溶液直至进一步处理。在返回到实验室，我们执行的协议，因为它是这里提出。将浓缩的细胞裂解物分成;蛋白从90％的体积的沉淀，而DN...

Watch this Scientific Journal Video about An Aquatic Microbial Metaproteomics Workflow: From Cells to Tryptic Peptides Suitable for Tandem Mass Spectrometry-based Analysis at JoVE.com

An Aquatic Microbial Metaproteomics Workflow: From Cells to Tryptic Peptides Suitable for Tandem Mass Spectrometry-based Analysis

This protocol is for the extraction and concentration of protein and DNA from microbial biomass collected from seawater, followed by the generation of tryptic peptides suitable for tandem mass spectrometry-based proteomic analysis.

水生微生物Metaproteomics工作流程:从细胞对胰蛋白酶肽适合串联质谱为基础的分析

Meta-omic technologies such as metagenomics, metatranscriptomics and metaproteomics can aid in the understanding of microbial community structure and ...

an-aquatic-microbial-metaproteomics-workflow-from-cells-to-tryptic

Universidad San Sebastian

Research

JoVE Journal

Environment

8.7K 次观看.  Concordia University. This protocol is for the extraction and concentration of protein and DNA from microbial biomass collected from seawater, followed by the generation of tryptic peptides suitable for tandem mass spectrometry-based proteomic analysis.

视频: An Aquatic Microbial Metaproteomics Workflow: From Cells to Tryptic Peptides Suitable for Tandem Mass Spectrometry-based Analysis

Resolving Affinity Purified Protein Complexes by Blue Native PAGE and Protein Correlation Profiling

Most proteins act in association with others; hence, it is crucial to characterize these functional units in order to fully understand biological processes. Affinity purification coupled to mass spectrometry (AP-MS) has become the method of choice for identifying protein-protein interactions. However, conventional AP-MS studies provide information on protein interactions, but the organizational information is lost. To address this issue, we developed a strategy to unravel the distinct functional assemblies a protein might be involved in, by resolving affinity-purified protein complexes prior to their characterization by mass spectrometry. Protein complexes isolated through affinity purification of a bait protein using an epitope tag and competitive elution are separated through blue native electrophoresis. Comparison of protein migration profiles through correlation profiling using quantitative mass spectrometry allows assignment of interacting proteins to distinct molecular entities. This method is able to resolve protein complexes of close molecular weights that might not be resolved by traditional chromatographic techniques such as gel filtration. With little more work than conventional AP-geLC-MS/MS, we demonstrate this strategy may in many cases be adequate for obtaining protein complex topological information concomitantly to identifying protein interactions.

Here we present protocols for affinity purification of protein complexes and their separation by blue native PAGE, followed by protein correlation profiling using label free quantitative mass spectrometry. This method is useful to resolve interactomes into distinct protein complexes.

解决由蓝变性PAGE和蛋白质相关剖析亲和纯化的蛋白复合物

Most proteins act in association with others; hence, it is crucial to characterize these functional units in order to fully understand biological ...

科研

生物化学

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

Many exceptional advances have been made in mass spectrometry (MS)-based proteomics, with particular technical progress in liquid chromatography (LC) coupled to tandem mass spectrometry (LC-MS/MS) and isobaric labeling multiplexing capacity. Here, we introduce a deep-proteomics profiling protocol that combines 10-plex tandem mass tag (TMT) labeling with an extensive LC/LC-MS/MS platform, and post-MS computational interference correction to accurately quantitate whole proteomes. This protocol includes the following main steps: protein extraction and digestion, TMT labeling, 2-dimensional (2D) LC, high-resolution mass spectrometry, and computational data processing. Quality control steps are included for troubleshooting and evaluating experimental variation. More than 10,000 proteins in mammalian samples can be confidently quantitated with this protocol. This protocol can also be applied to the quantitation of post translational modifications with minor changes. This multiplexed, robust method provides a powerful tool for proteomic analysis in a variety of complex samples, including cell culture, animal tissues, and human clinical specimens.

We present a protocol to accurately quantitate proteins with isobaric labelling, extensive fractionation, bioinformatics tools, and quality control steps in combination with liquid chromatography interfaced to a high-resolution mass spectrometer.

用等压标记、广泛的液相色谱法、质谱法和软件辅助定量技术进行深层蛋白质组分析

Many exceptional advances have been made in mass spectrometry (MS)-based proteomics, with particular technical progress in liquid chromatography (LC) ...

2 in 1: One-step Affinity Purification for the Parallel Analysis of Protein-Protein and Protein-Metabolite Complexes

Cellular processes are regulated by interactions between biological molecules such as proteins, metabolites, and nucleic acids. While the investigation of protein-protein interactions (PPI) is no novelty, experimental approaches aiming to characterize endogenous protein-metabolite interactions (PMI) constitute a rather recent development. Herein, we present a protocol that allows simultaneous characterization of the PPI and PMI of a protein of choice, referred to as bait. Our protocol was optimized for Arabidopsis cell cultures and combines affinity purification (AP) with mass spectrometry (MS)-based protein and metabolite detection. In short, transgenic Arabidopsis lines, expressing bait protein fused to an affinity tag, are first lysed to obtain a native cellular extract. Anti-tag antibodies are used to pull down protein and metabolite partners of the bait protein. The affinity-purified complexes are extracted using a one-step methyl tert-butyl ether (MTBE)/methanol/water method. Whilst metabolites separate into either the polar or the hydrophobic phase, proteins can be found in the pellet. Both metabolites and proteins are then analyzed by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS or UPLC-MS/MS). Empty-vector (EV) control lines are used to exclude false positives. The major advantage of our protocol is that it enables identification of protein and metabolite partners of a target protein in parallel in near-physiological conditions (cellular lysate). The presented method is straightforward, fast, and can be easily adapted to biological systems other than plant cell cultures.

Protein-protein and protein-metabolite interactions are crucial for all cellular functions. Herein, we describe a protocol that allows parallel analysis of these interactions with a protein of choice. Our protocol was optimized for plant cell cultures and combines affinity purification with mass spectrometry-based protein and metabolite detection.

2在 1: 一步亲和纯化为蛋白质蛋白质和蛋白质代谢物的平行的分析

Cellular processes are regulated by interactions between biological molecules such as proteins, metabolites, and nucleic acids. While the investigation of ...

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 ...

环境科学

Fast Enzymatic Processing of Proteins for MS Detection with a Flow-through Microreactor

The vast majority of mass spectrometry (MS)-based protein analysis methods involve an enzymatic digestion step prior to detection, typically with trypsin. This step is necessary for the generation of small molecular weight peptides, generally with MW &#60; 3,000-4,000 Da, that fall within the effective scan range of mass spectrometry instrumentation. Conventional protocols involve O/N enzymatic digestion at 37 &#186;C. Recent advances have led to the development of a variety of strategies, typically involving the use of a microreactor with immobilized enzymes or of a range of complementary physical processes that reduce the time necessary for proteolytic digestion to a few minutes (e.g., microwave or high-pressure). In this work, we describe a simple and cost-effective approach that can be implemented in any laboratory for achieving fast enzymatic digestion of a protein. The protein (or protein mixture) is adsorbed on C18-bonded reversed-phase high performance liquid chromatography (HPLC) silica particles preloaded in a capillary column, and trypsin in aqueous buffer is infused over the particles for a short period of time. To enable on-line MS detection, the tryptic peptides are eluted with a solvent system with increased organic content directly in the MS ion source. This approach avoids the use of high-priced immobilized enzyme particles and does not necessitate any aid for completing the process. Protein digestion and complete sample analysis can be accomplished in less than ~3 min and ~30 min, respectively.

A quick protocol for proteolytic digestion with an in-house built flow-through tryptic microreactor coupled to an electrospray ionization (ESI) mass spectrometer is presented. The fabrication of the microreactor, the experimental setup and the data acquisition process are described.

蛋白质的MS检测快速酶法处理与流通型微反应器

The vast majority of mass spectrometry (MS)-based protein analysis methods involve an enzymatic digestion step prior to detection, typically with trypsin. ...

生物工程

Cell-Lineage Guided Mass Spectrometry Proteomics in the Developing (Frog) Embryo

Characterization of molecular events as cells give rise to tissues and organs raises a potential to better understand normal development and design efficient remedies for diseases. Technologies enabling accurate identification and quantification of diverse types and large numbers of proteins would provide still missing information on molecular mechanisms orchestrating tissue and organism development in space and time. Here, we present a mass spectrometry-based protocol that enables the measurement of thousands of proteins in identified cell lineages in Xenopus laevis (frog) embryos. The approach builds on reproducible cell-fate maps and established methods to identify, fluorescently label, track, and sample cells and their progeny (clones) from this model of vertebrate development. After collecting cellular contents using microsampling or isolating cells by dissection or fluorescence-activated cell sorting, proteins are extracted and processed for bottom-up proteomic analysis. Liquid chromatography and capillary electrophoresis are used to provide scalable separation for protein detection and quantification with high-resolution mass spectrometry (HRMS). Representative examples are provided for the proteomic characterization of neural-tissue fated cells. Cell-lineage-guided HRMS proteomics is adaptable to different tissues and organisms. It is sufficiently sensitive, specific, and quantitative to peer into the spatio-temporal dynamics of the proteome during vertebrate development.

Cell-Lineage Guided Mass Spectrometry Proteomics in the Developing Frog Embryo

Here we describe a mass spectrometry-based proteomic characterization of cell lineages with known tissue fates in the vertebrate Xenopus laevis embryo.

发育（青蛙）胚胎中的细胞谱系引导质谱蛋白质组学

Characterization of molecular events as cells give rise to tissues and organs raises a potential to better understand normal development and design ...

化学

Profiling of Methyltransferases and Other S-adenosyl-L-homocysteine-binding Proteins by Capture Compound Mass Spectrometry (CCMS)

There is a variety of approaches to reduce the complexity of the proteome on the basis of functional small molecule-protein interactions such as affinity chromatography 1 or Activity Based Protein Profiling 2. Trifunctional Capture Compounds (CCs, Figure 1A) 3 are the basis for a generic approach, in which the initial equilibrium-driven interaction between a small molecule probe (the selectivity function, here S-adenosyl-L-homocysteine, SAH, Figure 1A) and target proteins is irreversibly fixed upon photo-crosslinking between an independent photo-activable reactivity function (here a phenylazide) of the CC and the surface of the target proteins. The sorting function (here biotin) serves to isolate the CC - protein conjugates from complex biological mixtures with the help of a solid phase (here streptavidin magnetic beads). Two configurations of the experiments are possible: "off-bead" 4 or the presently described "on-bead" configuration (Figure 1B). The selectivity function may be virtually any small molecule of interest (substrates, inhibitors, drug molecules).
S-Adenosyl-L-methionine (SAM, Figure 1A) is probably, second to ATP, the most widely used cofactor in nature 5, 6. It is used as the major methyl group donor in all living organisms with the chemical reaction being catalyzed by SAM-dependent methyltransferases (MTases), which methylate DNA 7, RNA 8, proteins 9, or small molecules 10. Given the crucial role of methylation reactions in diverse physiological scenarios (gene regulation, epigenetics, metabolism), the profiling of MTases can be expected to become of similar importance in functional proteomics as the profiling of kinases. Analytical tools for their profiling, however, have not been available. We recently introduced a CC with SAH as selectivity group to fill this technological gap (Figure 1A).
SAH, the product of SAM after methyl transfer, is a known general MTase product inhibitor 11. For this reason and because the natural cofactor SAM is used by further enzymes transferring other parts of the cofactor or initiating radical reactions as well as because of its chemical instability 12, SAH is an ideal selectivity function for a CC to target MTases. Here, we report the utility of the SAH-CC and CCMS by profiling MTases and other SAH-binding proteins from the strain DH5&alpha; of Escherichia coli (E. coli), one of the best-characterized prokaryotes, which has served as the preferred model organism in countless biochemical, biological, and biotechnological studies. Photo-activated crosslinking enhances yield and sensitivity of the experiment, and the specificity can be readily tested for in competition experiments using an excess of free SAH.

Profiling of Methyltransferases and Other S-adenosyl-L-homocysteine-binding Proteins by Capture Compound Mass Spectrometry CCMS

Capture Compounds are trifunctional small molecules to reduce the complexity of the proteome by functional reversible small molecule-protein interaction followed by photo-crosslinking and purification. Here we use a Capture Compound with S-adenosyl-L-homocysteine-binding as selectivity function to isolate methyltransferases from an Escherichia coli whole cell lysate and identify them by MS.

分析甲基化和其他 S腺苷 L</sub捕捉复合质谱（CCMS）>同型半胱氨酸结合蛋白

There is a variety of approaches to reduce the complexity of the proteome on the basis of functional small molecule-protein interactions such as affinity ...

生物学

Metabolic Labeling and Membrane Fractionation for Comparative Proteomic Analysis of Arabidopsis thaliana Suspension Cell Cultures

Plasma membrane microdomains are features based on the physical properties of the lipid and sterol environment and have particular roles in signaling processes. Extracting sterol-enriched membrane microdomains from plant cells for proteomic analysis is a difficult task mainly due to multiple preparation steps and sources for contaminations from other cellular compartments. The plasma membrane constitutes only about 5-20% of all the membranes in a plant cell, and therefore isolation of highly purified plasma membrane fraction is challenging. A frequently used method involves aqueous two-phase partitioning in polyethylene glycol and dextran, which yields plasma membrane vesicles with a purity of 95% 1. Sterol-rich membrane microdomains within the plasma membrane are insoluble upon treatment with cold nonionic detergents at alkaline pH. This detergent-resistant membrane fraction can be separated from the bulk plasma membrane by ultracentrifugation in a sucrose gradient 2. Subsequently, proteins can be extracted from the low density band of the sucrose gradient by methanol/chloroform precipitation. Extracted protein will then be trypsin digested, desalted and finally analyzed by LC-MS/MS. Our extraction protocol for sterol-rich microdomains is optimized for the preparation of clean detergent-resistant membrane fractions from Arabidopsis thaliana cell cultures.
We use full metabolic labeling of Arabidopsis thaliana suspension cell cultures with K15NO3 as the only nitrogen source for quantitative comparative proteomic studies following biological treatment of interest 3. By mixing equal ratios of labeled and unlabeled cell cultures for joint protein extraction the influence of preparation steps on final quantitative result is kept at a minimum. Also loss of material during extraction will affect both control and treatment samples in the same way, and therefore the ratio of light and heave peptide will remain constant. In the proposed method either labeled or unlabeled cell culture undergoes a biological treatment, while the other serves as control 4.

Metabolic Labeling and Membrane Fractionation for Comparative Proteomic Analysis of Arabidopsis thaliana Suspension Cell Cultures

Here we describe a robust method for the fractionation of plant plasma membranes into detergent resistant and detergent soluble membranes based on a mixture of unlabeled and in vivo fully 15N labeled Arabidopsis thaliana cell cultures. The procedure is applied for comparative proteomic studies to understand signaling processes.

代谢标记和膜分馏的比较蛋白质组学分析<em&gt;拟南芥</em&gt;悬浮细胞培养

Plasma membrane microdomains are features based on the physical properties of the lipid and sterol environment and have particular roles in signaling ...

<meta charset="utf8"></head><body>Galaxy-Enabled Metaprote组学:深入了解宿主-微生物组相互作用

A Clinical Metaproteomics Workflow Implemented within Galaxy Bioinformatics Platform to Analyze Host-Microbiome Interactions Underlying Human Disease

Clinical metaproteomics reveals host-microbiome interactions underlying diseases. However, challenges to this approach exist. In particular, the characterization of microbial proteins present in low abundance relative to host proteins is difficult. Other significant challenges are attributed to using very large protein sequence databases, which impedes sensitivity and accuracy during peptide and protein identification from mass spectrometry data in addition to retrieving taxonomy and functional annotations and performing statistical analysis. To address these problems, we present an integrated bioinformatics workflow for mass spectrometry-based metaproteomics that combines custom protein sequence database generation, peptide-spectrum match generation and verification, quantification, taxonomic and functional annotations, and statistical analysis. This workflow also offers characterization of human proteins (while prioritizing microbial proteins), thus offering insights into host-microbe dynamics in disease. The tools and workflow are deployed in the Galaxy ecosystem, enabling the development, optimization, and dissemination of these computational resources. We have applied this workflow for metaproteomic analysis of numerous clinical sample types, such as nasopharyngeal swabs and bronchoalveolar lavage fluid. Here, we demonstrate its utility via the analysis of residual fluid from cervical swabs. The complete workflow and accompanying training resources are accessible on the Galaxy Training Network to equip non-experts and experienced researchers with the necessary knowledge and tools to analyze their data.

<meta charset="utf8"></head><body>在 Galaxy Bioinformatics Platform 中实施的临床宏蛋白质组学工作流程，用于分析人类疾病背后的宿主-微生物组相互作用

Clinical metaproteomics offers insights into the human microbiome and its contributions to disease. We harnessed the computational power of the Galaxy platform to develop a modular bioinformatics workflow that facilitates complex mass spectrometry-based metaproteomic analysis and characterization of diverse clinical sample types relevant to studies of disease.

水生微生物Metaproteomics工作流程:从细胞对胰蛋白酶肽适合串联质谱为基础的分析

摘要

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此视频中的章节

解决由蓝变性PAGE和蛋白质相关剖析亲和纯化的蛋白复合物

用等压标记、广泛的液相色谱法、质谱法和软件辅助定量技术进行深层蛋白质组分析

2在 1: 一步亲和纯化为蛋白质蛋白质和蛋白质代谢物的平行的分析

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

蛋白质的MS检测快速酶法处理与流通型微反应器

发育（青蛙）胚胎中的细胞谱系引导质谱蛋白质组学

分析甲基化和其他 S腺苷_{L同型半胱氨酸结合蛋白}

代谢标记和膜分馏的比较蛋白质组学分析

在 Galaxy Bioinformatics Platform 中实施的临床宏蛋白质组学工作流程，用于分析人类疾病背后的宿主-微生物组相互作用

在 Galaxy Bioinformatics Platform 中实施的临床宏蛋白质组学工作流程，用于分析人类疾病背后的宿主-微生物组相互作用

水生微生物Metaproteomics工作流程:从细胞对胰蛋白酶肽适合串联质谱为基础的分析

摘要

探索更多视频

此视频中的章节

解决由蓝变性PAGE和蛋白质相关剖析亲和纯化的蛋白复合物

用等压标记、广泛的液相色谱法、质谱法和软件辅助定量技术进行深层蛋白质组分析

2在 1: 一步亲和纯化为蛋白质蛋白质和蛋白质代谢物的平行的分析

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

蛋白质的MS检测快速酶法处理与流通型微反应器

发育（青蛙）胚胎中的细胞谱系引导质谱蛋白质组学

分析甲基化和其他 S腺苷 L同型半胱氨酸结合蛋白

代谢标记和膜分馏的比较蛋白质组学分析

在 Galaxy Bioinformatics Platform 中实施的临床宏蛋白质组学工作流程，用于分析人类疾病背后的宿主-微生物组相互作用

在 Galaxy Bioinformatics Platform 中实施的临床宏蛋白质组学工作流程，用于分析人类疾病背后的宿主-微生物组相互作用

分析甲基化和其他 S腺苷_{L同型半胱氨酸结合蛋白}