作者感谢肯特西利，该中心药物发现与创新（CDDI）蛋白质组学核心设施在南佛罗里达大学使用该设施的主任医师。这项工作是由美国国立卫生研究院/ NIDCD授予R01 DC004295到BHAS支持

操守准则利用小鼠体内实验已获南佛罗里达大学实验动物管理和使用委员会（协议3931R，3482R）作为载下美国国立卫生研究院的指导方针。 1。蛋白抽提<ol><li>在-80°C隔离耳蜗感觉上皮从16 30日龄（P30）CBA / J小鼠和存储</li><li>在实验当天，用500μl1X磷酸盐缓冲盐水（PBS）中洗涤组织。离心3分钟，在1000×g离心，去除上清。重复总共3次洗涤。 </li><li> 30秒在冰上于含有50mM的Tris-HCl，pH值8.0，120 mM氯化钠，50mM的氟化钠，5mM的EDTA，500微克/毫升AEBSF，10微克/毫升亮肽素，100微克/ 100微升裂解缓冲液中超声处理组织毫升胃蛋白酶，2微克/毫升抑肽酶和0.5微克/毫升的微囊藻毒素使用声波dismembrator（型号100，赛默飞世尔）。冰酷裂解液每个超声处理之间1分钟。超声处理共3倍的。 </li><li>离心提取物，在750×g离心在4℃下持续2分钟，去除上清至新的微管中。通过超声处理30秒，在冰上提取沉淀中加入50μl裂解缓冲液。离心提取物，在750×g离心在4℃下持续2分钟。在28,600 XG结合这两种裂解液和离心机在4℃下60分钟。除去上清液至新的微管中，并加入含0.1％ASB-14至沉淀20微升裂解缓冲液。涡旋混合1分钟，孵育60分钟，在4℃下</li><li>加热该样品在95℃下5分钟，然后冷却，在4℃下进行60分钟。用离心跟随在16000 XG在25°C下10分钟。收集上清液并转移到新管中。 </li><li>离心悬浮液以16,000×g离心在4℃下5分钟，并保留上清液进行消化。 </li></ol> 2。全裂解液的使用FASP双胰蛋白酶消化蛋白质<ol><li>添加30μ耳蜗蛋白提取物，含有4％十二烷基硫酸钠（SDS）的升等分试样（≤400微克），100mM的Tris-盐酸，pH值7.6和0.1M二硫苏糖醇（DTT）直接到30K自旋过滤器和混合用200μl的8尿素的Tris-HCl中。离心机以14,000×g离心15分钟。 </li><li>稀释该浓缩物用200μl的在14,000 xg离心15分钟，8M尿素溶液和离心机。 </li><li>在8M尿素溶液中，以该浓缩物在过滤器中并涡旋混合1分钟加入10μl的10倍碘乙酰胺（IAA）。孵育自旋过滤器在室温（RT）下在黑暗中20分钟，然后离心，14,000 xg离心10分钟。 </li><li>加入100微升的8M尿素溶液的浓缩物以14,000×g离心15分钟，过滤器单元和离心分离机上。重复此步骤2倍。加入100微升的50mM的碳酸氢铵（ABC）的溶液于14,000 xg离心10分钟，过滤器单元和离心分离机。重复此步骤2倍。 </li><li>添加0.4微克/微升的胰蛋白酶在1:100（W​​ / W）的酶，以蛋白质比例孵育过夜（O / N）在37°C </li><li>温育后，加入40微升50mM的ABC溶液过滤单元和离心机以14,000×g离心10分钟。重复此步骤1X。 </li><li>加入50微升0.5M的NaCl溶液以14,000×g离心10分钟自旋过滤器和离心机。含有胰蛋白酶肽的滤液转移到一个新的微管中，用甲酸（FA）酸化至1.0％，以终止消化。 </li><li>用40微升8M尿素冲洗过滤器单元，然后用40微升18兆欧水清洗2倍。 </li><li>用100μl50mM的ABC溶液冲洗过滤器单元3倍。经过最后一次洗涤加0.4微克/微升胰蛋白酶1:100（W​​ / W）的酶与蛋白质的比例和孵化O / N为37°C。 </li><li>通过加入40微升50mM的ABC溶液以14,000×g离心，过滤器单元和离心分离10分钟，洗脱胰蛋白酶肽从第二消化。重复此步骤1X。 </li><li>加入50微升0.5M的NaCl溶液对以14,000×g离心10分钟过滤器单元和离心分离机。含有胰蛋白酶肽的滤液转移到一个新的微管，并与FA酸化到1.0％。 </li><li>样品可以使用牛血清白蛋白作为标准，使用微孔板比色测定法进行定量。 </li></ol> 3。全裂解液的使用FASP内蛋白酶LYSC和胰蛋白酶消化蛋白质<ol><li>添加的含有4％SDS，100mM的Tris-盐酸，pH值7.6和0.1 M DTT直接到30K自旋过滤器耳蜗蛋白提取物的30微升等分试样（≤400微克），并用200μl的8M尿素中的Tris-HCl混合。离心机以14,000×g离心15分钟。 </li><li>稀释该浓缩物用200μl的在14,000 xg离心15分钟，8M尿素溶液和离心机。 </li><li>加入10μl的10倍IAA在8M尿素溶液中，以该浓缩物在过滤器中并涡旋混合1分钟。孵育自旋过滤器在室温20分钟，在黑暗中，然后离心，14,000 xg离心10分钟。 </li><li>加入100μl的8M尿素溶胶ution到该浓缩物以14,000×g离心15分钟，过滤器单元和离心分离机上。重复此步骤2倍。加入100微升100mM的ABC溶液以14,000×g离心10分钟，过滤器单元和离心分离机。重复此步骤2倍。 </li><li>添加0.1微克/微升内蛋白酶LYSC在1:50（W / W）的酶与蛋白质的比例和孵化O / N为30°C。 </li><li>温育后，加入40微升100mM ABC溶液以14,000×g离心10分钟，过滤器单元和离心分离机。重复此步骤1X。 </li><li>加入50微升0.5M的NaCl溶液以14,000×g离心10分钟自旋过滤器和离心机。含LYSC肽滤液转移到一个新的微管，并与FA酸化到1.0％，停止消化。 </li><li>用40微升8M尿素冲洗过滤器单元，然后用40微升18兆欧水清洗2倍。 </li><li>用100μl50mM的ABC溶液冲洗过滤器单元3倍。后在最后一次洗涤中添加0.4微克/微升的胰蛋白酶在1:100的酶对亲蛋白质比例和孵化O / N为37°C。 </li><li>通过加入40微升50mM的ABC溶液以14,000×g离心10分钟，过滤器单元和离心分离机中洗脱胰蛋白酶肽。重复此步骤1X。 </li><li>加入50微升0.5M的NaCl溶液，以在14,000×g离心10分钟，过滤器单元和离心分离机。含有胰蛋白酶肽的滤液转移到一个新的微管和酸化用1.0％FA。 </li><li>样品可以用微孔板比色法用BSA为标准进行定量。 </li></ol> 4。脱盐肽使用离心柱<ol><li>通过加入500μl的乙腈（ACN）和离心机在1100×g离心1分钟，激活一个C 18 MacroSpin列。离心后丢弃的流量通过。 </li><li>用500μl0.1％甲酸和离心机的平衡色谱柱在1100×g离心1分钟。丢弃的流量通过并重复此步骤1X。 </li><li>最多可添加500微升肽的消化到列的ð离心机在1100×g离心1分钟。如果样品体积大于500微升然后重复此步骤。 </li><li>用500微升0.1％FA和离心机在1100×g离心1分钟洗柱。弃去流过。重复此步骤1X。 </li><li>加入250μl的90:10的乙腈 - 水比例在1100×g离心1分钟，柱和离心机。收集含有脱盐肽洗脱液，转移到一个新的微管。重复此步骤1X。 </li><li>干燥脱盐肽样品在真空离心机和完全避免让样品干燥。 </li></ol> 5。离子交换色谱<ol><li>注入50-100消化蛋白质样品微克到200×2.1毫米，5微米SCX柱（聚磺A）分离肽。 </li><li>使用2-40％B，用50分钟的梯度为250微升/分钟的流速。溶剂A为5 mM甲酸铵，pH值3.0在25％乙腈和75％的双蒸2 O。溶剂B为500 mM甲酸铵，pH值6.0在25％乙腈和75％的双蒸2 O。 </li><li>监视肽组分在280nm处，并用流分收集器收集在2分钟间隔的级分。 </li><li>干燥的部分在真空浓缩，重悬在500微升50％乙腈在DDH 2 O含5％FA协助盐去除。 </li><li> Redry分数和储存在-80°C，直到准备使用纳米LC-MS/MS分析。 </li></ol> 6。丙酮沉淀前GELFrEE分离耳蜗蛋白的上清液，必须脱盐。丙酮沉淀法可用于脱盐和浓缩的蛋白质。 <ol><li>添加三卷冰冷的丙酮耳蜗上清液。轻轻振荡后，在-20°CO / N。 </li><li>以15,000×g离心离心样品混合物15分钟，在4℃下，去除上清。 </li><li>用冷丙酮和离心机在14,000 XG在4清洗蛋白沉淀3次5分钟°C。 </li><li>空气干燥沉淀，溶解于112微升的18MΩ水。 </li><li>使用酶标仪比色法测定蛋白质浓度。 </li></ol> 7。人工耳蜗感觉上皮的GELFrEE分馏<ol><li>加入30微升的5×样品缓冲液（0.25M的Tris-HCl pH 6.8的10％（重量/体积）SDS，50％甘油，0.5％（重量/体积）溴酚蓝）的脱盐的蛋白质悬浮在112微升18MΩ水。 </li><li>添加8微升1M的DTT和热量在95℃下5分钟，以减少蛋白质二硫键。加热后允许冷却到室温。 </li><li>加8毫升运行缓冲液，以阳极槽，150微升缓冲液样品收集室的，和6ml缓冲液至阴极贮存。 </li><li>除去可能已使用移液管流入试样装填室的任何缓冲液。 </li><li>负载耳蜗蛋白质混合物的150微升（≤1毫克），进入试样装填室使用8％蒸腾是醋酸盒和3.5-150 kDa的质量范围。 </li><li>下电极和关闭仪器盖子开始运行。 </li><li>在第一次暂停的时间在仪器上加入2ml缓冲液的阴极槽和恢复运行。 </li><li>在仪器上的每一暂停的时间间隔，用移液管收集来自样本的收集腔室中的样品，并加入到一个新鲜标记的微管中。用150微升运行缓冲液冲洗收集室2倍，并丢弃。 </li><li>加入150μl新鲜运行缓冲液的样品收集腔，恢复运行。收集的蛋白组分过2.6小时，在150微升/分的总体积的时间段。 </li></ol> 8。 GELFrEE分数的1D凝胶电泳 1D凝胶电泳可用于可视化之前的酶消化和质谱分析结果从GELFrEE分馏。 GELFrEE蛋白组分可以分离在4-15％的Tris-HCl的凝胶。 </p&gt; <ol><li>混合每GELFrEE部分的5微升等份与5微升的样品稀释缓冲液（350 mM的DTT在样品缓冲液）。 </li><li>加热该样品在95℃下3分钟。 </li><li>凉爽的样品至室温。 </li><li>负载10微升每个GELFrEE分数在个别胶道和负载5微升的最后一个未使用的车道分子量标准。 </li><li>运行该凝胶在125 V 1.5小时或直至染料前沿到达凝胶的底部。 </li><li>小心取出凝胶，并用银染染色加上可视化的蛋白质分离。 </li></ol> 9。使用专上学生资助GELFrEE部分的蛋白质消化一种改性FASP程序是用于洗涤剂除去GELFrEE馏分和消化。 <ol><li>每个单独的馏分直接添加到30K滤波器单元;用200μl8M尿素的Tris-HCl和离心机以14,000×g离心25分钟混合。 </li><li>稀释该浓缩物用200μl的尿素溶液和离心机以14,000×g离心12分钟。重复此步骤1X。 </li><li>加入10μl的10倍IAA在每个滤波器单元中，涡旋混合1分钟尿素溶液浓缩物中，并孵育在室温下30分钟，在黑暗中。 </li><li>加入100微升的尿素溶液以14,000×g离心15分钟，将浓缩物在过滤器单元和离心分离机。重复此步骤2倍。加入100微升100mM的ABC溶液至过滤器单元和离心机以14,000×g离心10分钟。重复此步骤2倍。 </li><li>为1:50（W / W）的酶与蛋白质之比加入0.1微克/微升的lysC的向过滤器单元和孵育O / N在30℃下</li><li>温育后，加入40微升100mM ABC溶液的自旋过滤器和离心机以14,000×g离心10分钟。重复此步骤1X。 </li><li>加入50微升0.5M的NaCl溶液，以自旋过滤器和离心机以14,000×g离心10分钟。包含从每个自旋过滤器的LYSC肽滤液转移到一个新的微管和酸化与trifluoroac客位乙酸（TFA）。 </li><li>用40微升8M尿素洗涤离心过滤，然后用40微升18兆欧水清洗2倍。 </li><li>洗自旋过滤器3倍用100μl50mM的ABC溶液。经过最后一次洗涤加0.4微克/微升胰蛋白酶在1:100（W​​ / W）的酶与蛋白质的比例和孵化O / N为37°C。 </li><li>加入40微升的50毫米农行的解决方案和离心14,000×g离心10分钟洗脱肽段从每个过滤单元。重复此步骤1X。 </li><li>加入50微升0.5M的NaCl溶液的过滤器单元和离心机以14,000×g离心10分钟。包含从每个过滤单元胰蛋白酶肽的滤液转移到一个新的微管和酸化与TFA。 </li><li>干全部精华在真空浓缩。 </li></ol> 10。样品制备LC-MS/MS <ol><li>重组干LYSC和胰蛋白酶消化肽组分在20微升0.1％FA和旋涡。 </li><li>离心样品以20,000×g离心10分钟，除去顶部95％的样本的一个新的样品瓶。 </li><li>注入5μl的每种肽馏分到100微米×25毫米的样品阱，以除去盐和污染物，并以75微米×10厘米-C 18柱进行色谱分离。 </li><li>使用2-40％B，历经100分钟的梯度为200升/分钟的流速。溶剂A为95％，双蒸水和5％乙​​腈含0.1％FA。溶剂B为80％乙腈和20％的双蒸水含0.1％FA。 </li><li>收集10串联质谱对每个MS扫描的高分辨率质谱仪。一个LTQ的Orbitrap质谱仪被用于本实验。 </li></ol> 11。蛋白质鉴定<ol><li>使用包含的UniProt数据库鼠标向前识别蛋白质和反向蛋白序列和常见污染物。与福星搜索引擎MaxQuant软件是用来搜索蛋白质数据库。 </li><li>搜索参数，可用于包括;固定modific半胱氨酸的脲基甲基的振动性，蛋氨酸的氧化变量的修改，蛋白质N-末端乙酰化，最大为2遗漏乳沟。最小肽的长度如何考虑的识别是6个氨基酸。 输入±8 ppm或1.2大（质量误差是依赖于所使用的质谱仪）的片段质量误差肽质量浓度的错误。 </li><li>在MaxQuant软件，用1％的假发现率（FDR）的肽和蛋白质鉴定。蛋白质鉴定中列出具有匹配的肽，该蛋白的百分比序列覆盖率，并且所述肽序列的数量。 </li></ol>

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R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mass+spectrometry+for+proteomics.">Mass spectrometry for proteomics.</a> Curr. Opin. Chem. Biol. 12, 483-490 (2008).</li><li>Thalmann, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Inner+ear+proteomics:+A+fad+or+hear+to+stay.">Inner ear proteomics: A fad or hear to stay.</a> Brain Res. 1091, 103-112 (2006).</li><li>Lang, F., Vallon, V., Knipper, M., Wangemann, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Functional+significance+of+channels+and+transporters+expressed+in+the+inner+ear+and+kidney.">Functional significance of channels and transporters expressed in the inner ear and kidney.</a> Am. J. Physiol. Cell Physiol. 293, (2007).</li><li>Wisniewski, J. R., Zougman, A., Nagaraj, N., 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=Universal+sample+preparation+method+for+proteome+analysis.">Universal sample preparation method for proteome analysis.</a> Nat. Meth. 6, 359-362 (2009).</li><li>Wisniewski, J. R., Zielinska, D. F., 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=Comparison+of+ultrafiltration+units+for+proteomic+and+N-glycoproteomic+analysis+by+the+filter-aided+sample+preparation+method.">Comparison of ultrafiltration units for proteomic and N-glycoproteomic analysis by the filter-aided sample preparation method.</a> Anal. Biochem. 410, 307-309 (2011).</li><li>Darville, L. N., Sokolowski, B. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In-depth+Proteomic+Analysis+of+Mouse+Cochlear+Sensory+Epithelium+by+Mass+Spectrometry.">In-depth Proteomic Analysis of Mouse Cochlear Sensory Epithelium by Mass Spectrometry.</a> J Proteome Res. 12 (8), 3620-3630 (2013).</li><li>Vizcaino, J. A., Cote, R. G., Csordas, A., Dianes, J. A., Fabregat, A., Foster, J. M., Griss, J., Alpi, E., Birim, M., Contell, J., O'Kelly, G., Schoenegger, A., Ovelleiro, D., Perez-Riverol, Y., Reisinger, F., Rios, D., Wang, R., Hermjakob, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+PRoteomics+IDEntifications+(PRIDE)+database+and+associated+tools:+status+in+2013.">The PRoteomics IDEntifications (PRIDE) database and associated tools: status in 2013.</a> Nucleic Acids Res. 41, 1063-1069 (2013).</li></ol>

作者宣称没有利益冲突。

<html>的关键步骤，从耳蜗感觉上皮最大化蛋白质鉴定是:1）使用多个endoproteinases的消化，2）使用多个分离技术，以及3）利用高分辨率质谱仪。多种酶的应用增加了肽的数目，提高了蛋白质序列覆盖率，从而提高识别的蛋白的数量从耳蜗组织。胰蛋白酶，最常用的蛋白酶提供蛋白质的效率和特异性裂解，产生的肽，是良好的MS电离和碎裂。然而，使用前胰蛋白酶另一种酶，如LYSC，这还能断裂在赖氨...

蛋白质组学是复杂的生物系统，通过分析蛋白的表达，功能，修改和相互作用1的研究。几种方法已用于内耳，包括抗体微阵列2，二维凝胶电泳3-5，和DIGE 6的蛋白质组分析。然而，蛋白质的仅有限数量已被鉴定和表征2,7-10相比，在内耳11,12确定了超过10,000个基因和表达序列标签（ESTs），MS是最常用的和全面的技术蛋白质组学中蛋白质特征。复杂蛋白质样品，例如耳蜗的分析，是具有挑战性的。然而，多个分离技术与MS的结合，使更多数量的肽和蛋白质的鉴定，由于增加了动态范围的浓度和峰容量13。多维chromatograPHY通过允许使用不同的吸附机理降低高度复杂的蛋白质混合物。有两种常用的MS蛋白质组分析方法，猎枪和自下而上的蛋白质组学研究。在鸟枪蛋白质组学，完整蛋白质的混合物酶促消化，并且使用多维色谱用强阳离子交换色谱法（SCX），随后通过反相液相色谱法（RPLC）14,15分离。分离的肽进行串联质谱和数据库搜索15。这种技术的一个主要优点是，成千上万的蛋白质可以在一次分析中被识别和技术更适合于膜蛋白。 在自下而上的方法，所述蛋白质混合物分离，通常是由一维或二维电泳，并且单个蛋白质条带或斑点切出和消化酶如胰蛋白酶，通常会导致多种肽。然而，另一个更近LY开发的电泳方法，在自下而上的蛋白质组学使用，是GELFrEE。这种技术分馏蛋白质样品在液相，使它们较少分析前复杂。这种技术是可重复的，具有高的蛋白回收率，并降低高丰度蛋白的复杂蛋白样品16中的分布情况。肽，从分离的蛋白质产生的，是由MS分析，利用肽质量指纹或串联质谱（MS / MS），创建序列标签数据库搜索17-19。一些使用自底向上方法的主要优点是能够获得高分辨率的分离和蛋白质的全面覆盖的能力。自下而上蛋白质组学是蛋白质组学20的最广泛使用的技术，因此，一些生物信息学工具是可用的。此外，蛋白质可以被分离在消化之前的复杂混合物，所以鉴定的机会较大。 其中一个主要的挑战使用内耳的蛋白质组学分析是它的体积小，限制可访问性和细胞类型的多样性21。此外，区分它的功能的关键的蛋白质，如离子通道，转运蛋白和受体，是膜蛋白，它可以是难以分离22。因此，过滤器辅助样品制备（FASP）是有利的组织，这对于蛋白提取有限的蛋白质组学分析，并要求清洁剂来溶解膜23。该滤波可用于膜和可溶性蛋白的质谱分析和对从低分子量的污染物23,24分离的肽的能力。 本协议描述了常用的蛋白质组的方法，它们被组合和修改，以分析可溶性蛋白和膜蛋白，并从耳蜗感觉上皮蛋白最大化ID的数目。我们将介绍使用鸟枪蛋白质组学与FASP多消化离子，离子交换色谱法，高分辨质谱和数据分析。此外，我们将描述自下而上的蛋白质组学与GELFrEE，FASP多的消化，高分辨率质谱和数据分析。

<table><tbody><tr><td>8% Tris-acetate cartridge&amp;nbsp;</td><td>Protein Discovery</td><td>42103</td><td></td></tr><tr><td>Acetone</td><td>Sigma-Aldrich</td><td>179124</td><td></td></tr><tr><td>Acetonitrile</td><td>Honeywell</td><td>015-1L</td><td></td></tr><tr><td>AEBSF</td><td>Calbiochem</td><td>101500</td><td></td></tr><tr><td>Ammonium formate</td><td>Fisher Scientific</td><td>AC16861</td><td></td></tr><tr><td>Aprotinin</td><td>Calbiochem</td><td>616370</td><td></td></tr><tr><td>ASB-14&amp;nbsp;</td><td>Calbiochem</td><td>182750-5GM</td><td></td></tr><tr><td>Bovine serum albumin</td><td>BioRad</td><td>500-0112</td><td></td></tr><tr><td>C&lt;sub&gt;18&lt;/sub&gt; column&amp;nbsp;</td><td>New Objective</td><td>A25112</td><td>75 &amp;mu;m x 10 cm&amp;nbsp;</td></tr><tr><td>DC Protein Assay</td><td>BioRad</td><td>500-0116</td><td>Microplate Assay Protocol</td></tr><tr><td>EDTA</td><td>Sigma-Aldrich</td><td>E9884</td><td></td></tr><tr><td>Endoproteinase Lys-C</td><td>Sigma-Aldrich</td><td>P3428</td><td></td></tr><tr><td>FASP Protein Digestion Kit</td><td>Protein Discovery</td><td>44250</td><td></td></tr><tr><td>Formic acid&amp;nbsp;</td><td>Fluka</td><td>94318</td><td></td></tr><tr><td>GELFrEE Fractionation System</td><td>Protein Discovery</td><td>42001</td><td>GELFrEE 8100</td></tr><tr><td>Leupeptin</td><td>Calbiochem</td><td>108975</td><td></td></tr><tr><td>MacroSpin Column</td><td>The Nest Group</td><td>SMM SS18V</td><td>Silica C18</td></tr><tr><td>Microcystin</td><td>Calbiochem</td><td>475815</td><td></td></tr><tr><td>Pepstatin</td><td>Sigma-Aldrich</td><td>P5318</td><td></td></tr><tr><td>Polysulfoethyl A Column</td><td>The Nest Group</td><td>202SE0503</td><td></td></tr><tr><td>Sodium dodecyl sulfate (SDS)</td><td>Sigma-Aldrich</td><td>L3771</td><td></td></tr><tr><td>Sonic Dismembrator&amp;nbsp;</td><td>Thermo Fisher</td><td>15-338-53</td><td>Model 100</td></tr><tr><td>Trypsin</td><td>Sigma-Aldrich</td><td>T6567</td><td>Proteomics Grade</td></tr></tbody></table>

bottom-up and shotgun proteomics to identify a comprehensive cochlear proteome

蛋白质组学是一种常用的方法，可以提供深入了解复杂的生物系统。耳蜗感觉上皮包含转导声音的机械能转换成由外周和中枢神经系统处理的电化学能量受体。几种蛋白质组技术已经发展到研究耳蜗内耳，如二维差异凝胶电泳（2D-DIGE），抗体微阵列，和质谱（MS）。 MS在蛋白质组学研究中最全面，最灵活的工具，并与分离方法结合使用可以提供一个深入蛋白质组生物样品。分离方法结合MS具有丰富的蛋白质样品，检测低分子量和疏水性蛋白质，并通过降低蛋白质的动态范围确定的低丰度蛋白的能力。不同消化策略可以应用到整个溶胞产物或分馏的蛋白裂解液来提高多肽和蛋白质序列覆盖率。不同的分离技术，包括强阳离子交换（SCX），反相（RP），和凝胶洗脱液体馏分包封电泳（GELFrEE）利用可应用于降低样品的复杂性之前MS分析蛋白质鉴定。

取得耳蜗感觉上皮的最全面的蛋白质组，快速组织解剖先于蛋白提取和样品制备要求。两种蛋白质组技术都可以使用，猎枪和自下而上蛋白质组学。以制备样品鸟枪蛋白质组学，FASP消化过程被用作如图1所示。该FASP方法允许浓度的蛋白质，除去洗涤剂，并用多种酶蛋白的消化。有两个双重消化过程中使用时，首先是胰蛋白酶消化接着进行第二用胰蛋白酶消化，这被汇集，分级分离的SC...

Watch this Scientific Journal Video about Bottom-up and Shotgun Proteomics to Identify a Comprehensive Cochlear Proteome at JoVE.com

Bottom-up and Shotgun Proteomics to Identify a Comprehensive Cochlear Proteome

耳蜗感觉上皮蛋白质组分析可能是由于其体积小和具有挑战性的，因为膜蛋白很难分离和鉴定。两膜和可溶性蛋白质可以通过组合多个的制备方法和分离技术随着高分辨率质谱来识别。

自下而上和猎枪蛋白质组学鉴定一个全面的蛋白质组耳蜗

Proteomics is a commonly used approach that can provide insights into complex biological systems. The cochlear sensory epithelium contains receptors that ...

bottom-up-shotgun-proteomics-to-identify-comprehensive-cochlear

Research

JoVE Journal

Biology

18.6K 次观看.  University of South Florida. 耳蜗感觉上皮蛋白质组分析可能是由于其体积小和具有挑战性的，因为膜蛋白很难分离和鉴定。两膜和可溶性蛋白质可以通过组合多个的制备方法和分离技术随着高分辨率质谱来识别。 

视频: Bottom-up and Shotgun Proteomics to Identify a Comprehensive Cochlear Proteome

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) ...

科研

生物化学

Dynamic Proteomic and miRNA Analysis of Polysomes from Isolated Mouse Heart After Langendorff Perfusion

Studies in dynamic changes in protein translation require specialized methods. Here we examined changes in newly-synthesized proteins in response to ischemia and reperfusion using the isolated perfused mouse heart coupled with polysome profiling. To further understand the dynamic changes in protein translation, we characterized the mRNAs that were loaded with cytosolic ribosomes (polyribosomes or polysomes) and also recovered mitochondrial polysomes and compared mRNA and protein distribution in the high-efficiency fractions (numerous ribosomes attached to mRNA), low-efficiency (fewer ribosomes attached) which also included mitochondrial polysomes, and the non-translating fractions. miRNAs can also associate with mRNAs that are being translated, thereby reducing the efficiency of translation, we examined the distribution of miRNAs across the fractions. The distribution of mRNAs, miRNAs, and proteins was examined under basal perfused conditions, at the end of 30 min of global no-flow ischemia, and after 30 min of reperfusion. Here we present the methods used to accomplish this analysis&#8212;in particular, the approach to optimization of protein extraction from the sucrose gradient, as this has not been described before&#8212;and provide some representative results.

Here we present a protocol to perform polysome profiling on the isolated perfused mouse heart. We describe methods for heart perfusion, polysome profiling, and analysis of the polysome fractions with respect to mRNAs, miRNAs, and the polysome proteome.

Langendorff 灌注后离体小鼠心脏 Polysomes 的动态蛋白质组学及 miRNA 分析

Studies in dynamic changes in protein translation require specialized methods. Here we examined changes in newly-synthesized proteins in response to ...

Mass Spectrometry-Based Proteomics Analyses Using the OpenProt Database to Unveil Novel Proteins Translated from Non-Canonical Open Reading Frames

Genome annotation is central to today's proteomic research as it draws the outlines of the proteomic landscape. Traditional models of open reading frame (ORF) annotation impose two arbitrary criteria: a minimum length of 100 codons and a single ORF per transcript. However, a growing number of studies report expression of proteins from allegedly non-coding regions, challenging the accuracy of current genome annotations. These novel proteins were found encoded either within non-coding RNAs, 5' or 3' untranslated regions (UTRs) of mRNAs, or overlapping a known coding sequence (CDS) in an alternative ORF. OpenProt is the first database that enforces a polycistronic model for eukaryotic genomes, allowing annotation of multiple ORFs per transcript. OpenProt is freely accessible and offers custom downloads of protein sequences across 10 species. Using OpenProt database for proteomic experiments enables novel proteins discovery and highlights the polycistronic nature of eukaryotic genes. The size of OpenProt database (all predicted proteins) is substantial and need be taken in account for the analysis. However, with appropriate false discovery rate (FDR) settings or the use of a restricted OpenProt database, users will gain a more realistic view of the proteomic landscape. Overall, OpenProt is a freely available tool that will foster proteomic discoveries.

OpenProt is a freely accessible database that enforces a polycistronic model of eukaryotic genomes. Here, we present a protocol for the use of OpenProt databases when interrogating mass spectrometry datasets. Using OpenProt database for analysis of proteomic experiments allows for discovery of novel and previously undetectable proteins.

基于质谱的蛋白质组学分析, 利用 OpenProt 数据库揭开从非规范开放阅读框架翻译的新蛋白质

Genome annotation is central to today's proteomic research as it draws the outlines of the proteomic landscape. Traditional models of open reading frame ...

遗传学

Quantitative Analysis of Chromatin Proteomes in Disease

In the nucleus reside the proteomes whose functions are most intimately linked with gene regulation. Adult mammalian cardiomyocyte nuclei are unique due to the high percentage of binucleated cells,1 the predominantly heterochromatic state of the DNA, and the non-dividing nature of the cardiomyocyte which renders adult nuclei in a permanent state of interphase.2 Transcriptional regulation during development and disease have been well studied in this organ,3-5 but what remains relatively unexplored is the role played by the nuclear proteins responsible for DNA packaging and expression, and how these proteins control changes in transcriptional programs that occur during disease.6 In the developed world, heart disease is the number one cause of mortality for both men and women.7 Insight on how nuclear proteins cooperate to regulate the progression of this disease is critical for advancing the current treatment options.
Mass spectrometry is the ideal tool for addressing these questions as it allows for an unbiased annotation of the nuclear proteome and relative quantification for how the abundance of these proteins changes with disease. While there have been several proteomic studies for mammalian nuclear protein complexes,8-13 until recently14 there has been only one study examining the cardiac nuclear proteome, and it considered the entire nucleus, rather than exploring the proteome at the level of nuclear sub compartments.15 In large part, this shortage of work is due to the difficulty of isolating cardiac nuclei. Cardiac nuclei occur within a rigid and dense actin-myosin apparatus to which they are connected via multiple extensions from the endoplasmic reticulum, to the extent that myocyte contraction alters their overall shape.16 Additionally, cardiomyocytes are 40% mitochondria by volume17 which necessitates enrichment of the nucleus apart from the other organelles. Here we describe a protocol for cardiac nuclear enrichment and further fractionation into biologically-relevant compartments. Furthermore, we detail methods for label-free quantitative mass spectrometric dissection of these fractions-techniques amenable to in vivo experimentation in various animal models and organ systems where metabolic labeling is not feasible.

Advances in mass spectrometry have allowed the high throughput analysis of protein expression and modification in a host of tissues. Combined with subcellular fractionation and disease models, quantitative mass spectrometry and bioinformatics can reveal new properties in biological systems. The method described herein analyzes chromatin-associated proteins in the setting of heart disease and is readily applicable to other in vivo models of human disease.

在疾病的染色质蛋白质组的定量分析

In the nucleus reside the proteomes whose functions are most intimately linked with gene regulation. Adult mammalian cardiomyocyte nuclei are unique due ...

医学

Large-scale Top-down Proteomics Using Capillary Zone Electrophoresis Tandem Mass Spectrometry

Capillary zone electrophoresis-electrospray ionization-tandem mass spectrometry (CZE-ESI-MS/MS) has been recognized as a useful tool for top-down proteomics that aims to characterize proteoforms in complex proteomes. However, the application of CZE-MS/MS for large-scale top-down proteomics has been impeded by the low sample-loading capacity and narrow separation window of CZE. Here, a protocol is described using CZE-MS/MS with a microliter-scale sample-loading volume and a 90-min separation window for large-scale top-down proteomics. The CZE-MS/MS platform is based on a linear polyacrylamide (LPA)-coated separation capillary with extremely low electroosmotic flow, a dynamic pH-junction-based online sample concentration method with a high efficiency for protein stacking, an electro-kinetically pumped sheath flow CE-MS interface with extremely high sensitivity, and an ion trap mass spectrometer with high mass resolution and scan speed. The platform can be used for the high-resolution characterization of simple intact protein samples and the large-scale characterization of proteoforms in various complex proteomes. As an example, a highly efficient separation of a standard protein mixture and a highly sensitive detection of many impurities using the platform is demonstrated. As another example, this platform can produce over 500 proteoform and 190 protein identifications from an Escherichia coli proteome in a single CZE-MS/MS run.

A detailed protocol is described for the separation, identification, and characterization of proteoforms in protein samples using capillary zone electrophoresis-electrospray ionization-tandem mass spectrometry (CZE-ESI-MS/MS). The protocol can be used for the high-resolution characterization of proteoforms in simple protein samples and the large-scale identification of proteoforms in complex proteome samples.

利用毛细管区电泳串联质谱技术进行大尺度自上而下蛋白质组学

Capillary zone electrophoresis-electrospray ionization-tandem mass spectrometry (CZE-ESI-MS/MS) has been recognized as a useful tool for top-down ...

化学

Carrier-assisted One-pot Sample Preparation for Targeted Proteomics Analysis of Small Numbers of Human Cells

Protein analysis of small numbers of human cells is primarily achieved by targeted proteomics with antibody-based immunoassays, which have inherent limitations (e.g., low multiplex and unavailability of antibodies for new proteins). Mass spectrometry (MS)-based targeted proteomics has emerged as an alternative because it is antibody-free, high multiplex, and has high specificity and quantitation accuracy. Recent advances in MS instrumentation make MS-based targeted proteomics possible for multiplexed quantification of highly abundant proteins in single cells. However, there is a technical challenge for effective processing of single cells with minimal sample loss for MS analysis. To address this issue, we have recently developed a convenient protein carrier-assisted one-pot sample preparation coupled with liquid chromatography (LC) - selected reaction monitoring (SRM) termed cLC-SRM for targeted proteomics analysis of small numbers of human cells. This method capitalizes on using the combined excessive exogenous protein as a carrier and low-volume one-pot processing to greatly reduce surface adsorption losses as well as high-specificity LC-SRM to effectively address the increased dynamic concentration range due to the addition of exogeneous carrier protein. Its utility has been demonstrated by accurate quantification of most moderately abundant proteins in small numbers of cells (e.g., 10-100 cells) and highly abundant proteins in single cells. The easy-to-implement features and no need for specific devices make this method readily accessible to most proteomics laboratories. Herein we have provided a detailed protocol for cLC-SRM analysis of small numbers of human cells including cell sorting, cell lysis and digestion, LC-SRM analysis, and data analysis. Further improvements in detection sensitivity and sample throughput are needed towards targeted single-cell proteomics analysis. We anticipate that cLC-SRM will be broadly applied to biomedical research and systems biology with the potential of facilitating precision medicine.

A protein carrier-assisted one-pot sample preparation coupled with liquid chromatography (LC) - selected reaction monitoring (SRM) termed cLC-SRM is a convenient method for multiplexed targeted proteomics analysis of small numbers of cells, including single cells. It capitalizes on using excessive exogenous protein as a carrier and high-specificity LC-SRM for targeted quantification.

Protein analysis of small numbers of human cells is primarily achieved by targeted proteomics with antibody-based immunoassays, which have inherent ...

Shotgun Proteomics Sample Processing Automated by an Open-Source Lab Robot

Mass spectrometry-based shotgun proteomics experiments require multiple sample preparation steps, including enzymatic protein digestion and clean-up, which can take up significant person-hours of bench labor and present a source of batch-to-batch variability. Lab automation with pipetting robots can reduce manual work, maximize throughput, and increase research reproducibility. Still, the steep starting prices of standard automation stations make them unaffordable for many academic laboratories. This article describes a proteomics sample preparation workflow using an affordable, open-source automation system (The Opentrons OT-2), including instructions for setting up semi-automated protein reduction, alkylation, digestion, and clean-up steps; as well as accompanying open-source Python scripts to program the OT-2 system through its application programming interface.

Detailed protocol and three Python scripts are provided for operating an open-source robotic liquid handling system to perform semi-automated protein sample preparation for mass spectrometry experiments, covering detergent removal, protein digestion, and peptide desalting steps.

Shotgun 蛋白质组学 样品处理 由开源实验室机器人自动执行

Mass spectrometry-based shotgun proteomics experiments require multiple sample preparation steps, including enzymatic protein digestion and clean-up, ...

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 ...

High Resolution Quantitative Synaptic Proteome Profiling of Mouse Brain Regions After Auditory Discrimination Learning

The molecular synaptic mechanisms underlying auditory learning and memory remain largely unknown. Here, the workflow of a proteomic study on auditory discrimination learning in mice is described. In this learning paradigm, mice are trained in a shuttle box Go/NoGo-task to discriminate between rising and falling frequency-modulated tones in order to avoid a mild electric foot-shock. The protocol involves the enrichment of synaptosomes from four brain areas, namely the auditory cortex, frontal cortex, hippocampus, and striatum, at different stages of training. Synaptic protein expression patterns obtained from trained mice are compared to na&#239;ve controls using a proteomic approach. To achieve sufficient analytical depth, samples are fractionated in three different ways prior to mass spectrometry, namely 1D SDS-PAGE/in-gel digestion, in-solution digestion and phospho-peptide enrichment. 
High-resolution proteomic analysis on a mass spectrometer and label-free quantification are used to examine synaptic protein profiles in phospho-peptide-depleted and phospho-peptide-enriched fractions of synaptosomal protein samples. A commercial software package is utilized to reveal proteins and phospho-peptides with significantly regulated relative synaptic abundance levels (trained/na&#239;ve controls). Common and differential regulation modes for the synaptic proteome in the investigated brain regions of mice after training were observed. Subsequently, meta-analyses utilizing several databases are employed to identify underlying cellular functions and biological pathways.

The identification of molecules and pathways controlling synaptic plasticity and memory is still a major challenge in neuroscience. Here, a workflow is described addressing the relative quantification of synaptic proteins supposedly involved in the molecular reorganization of synapses during learning and memory consolidation in an auditory learning paradigm.

鼠脑区的高分辨率定量突触蛋白质双向听觉辨别学习后

The molecular synaptic mechanisms underlying auditory learning and memory remain largely unknown. Here, the workflow of a proteomic study on auditory ...

神经科学

High-throughput and Deep-proteome Profiling by 16-plex Tandem Mass Tag Labeling Coupled with Two-dimensional Chromatography and Mass Spectrometry

Isobaric tandem mass tag (TMT) labeling is widely used in proteomics because of its high multiplexing capacity and deep proteome coverage. Recently, an expanded 16-plex TMT method has been introduced, which further increases the throughput of proteomic studies. In this manuscript, we present an optimized protocol for 16-plex TMT-based deep-proteome profiling, including protein sample preparation, enzymatic digestion, TMT labeling reaction, two-dimensional reverse-phase liquid chromatography (LC/LC) fractionation, tandem mass spectrometry (MS/MS), and computational data processing. The crucial quality control steps and improvements in the process specific for the 16-plex TMT analysis are highlighted. This multiplexed process offers a powerful tool for profiling a variety of complex samples such as cells, tissues, and clinical specimens. More than 10,000 proteins and posttranslational modifications such as phosphorylation, methylation, acetylation, and ubiquitination in highly complex biological samples from up to 16 different samples can be quantified in a single experiment, providing a potent tool for basic and clinical research.

Presented here is an optimized high-throughput protocol developed with 16-plex tandem mass tag reagents, enabling quantitative proteome profiling of biological samples. Extensive basic pH fractionation and high-resolution LC-MS/MS mitigate ratio compression and provide deep proteome coverage.

Isobaric tandem mass tag (TMT) labeling is widely used in proteomics because of its high multiplexing capacity and deep proteome coverage. Recently, an ...

自下而上和猎枪蛋白质组学鉴定一个全面的蛋白质组耳蜗

摘要

探索更多视频

此视频中的章节

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

Langendorff 灌注后离体小鼠心脏 Polysomes 的动态蛋白质组学及 miRNA 分析

基于质谱的蛋白质组学分析, 利用 OpenProt 数据库揭开从非规范开放阅读框架翻译的新蛋白质

在疾病的染色质蛋白质组的定量分析

利用毛细管区电泳串联质谱技术进行大尺度自上而下蛋白质组学

Carrier-assisted One-pot Sample Preparation for Targeted Proteomics Analysis of Small Numbers of Human Cells

Shotgun 蛋白质组学样品处理由开源实验室机器人自动执行

发育（青蛙）胚胎中的细胞谱系引导质谱蛋白质组学

鼠脑区的高分辨率定量突触蛋白质双向听觉辨别学习后

High-throughput and Deep-proteome Profiling by 16-plex Tandem Mass Tag Labeling Coupled with Two-dimensional Chromatography and Mass Spectrometry

自下而上和猎枪蛋白质组学鉴定一个全面的蛋白质组耳蜗

摘要

探索更多视频

此视频中的章节

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

Langendorff 灌注后离体小鼠心脏 Polysomes 的动态蛋白质组学及 miRNA 分析

基于质谱的蛋白质组学分析, 利用 OpenProt 数据库揭开从非规范开放阅读框架翻译的新蛋白质

在疾病的染色质蛋白质组的定量分析

利用毛细管区电泳串联质谱技术进行大尺度自上而下蛋白质组学

Carrier-assisted One-pot Sample Preparation for Targeted Proteomics Analysis of Small Numbers of Human Cells

Shotgun 蛋白质组学 样品处理 由开源实验室机器人自动执行

发育（青蛙）胚胎中的细胞谱系引导质谱蛋白质组学

鼠脑区的高分辨率定量突触蛋白质双向听觉辨别学习后

High-throughput and Deep-proteome Profiling by 16-plex Tandem Mass Tag Labeling Coupled with Two-dimensional Chromatography and Mass Spectrometry

Shotgun 蛋白质组学样品处理由开源实验室机器人自动执行