We are grateful to Hannah Kleinschmidt for excellent technical support. This paper was funded by the Open Access support program of the Deutsche Forschungsgemeinschaft and the publication fund of the Georg August Universita&#776;t Go&#776;ttingen.

1.考虑生物安全条件准备一个安全的工作环境<ol><li>熟悉实验室和安全法规的相关性与微生物工作。大多数人类病原微生物必须在生物安全水平进行处理2的条件，但一些，如伤寒沙门菌，需要生物安全3级上处理每一病原体可在www.cdc.gov/biosafety访问级别的信息。 </li><li>不管具体微生物的生物危害的分类，把中随附传染性废物传染性病原体必须在处置前进行高压灭菌接触的所有材料。尊重有害物质和生物物质的区域安全指导。确保立即和妥善处置可能受污染的材料（生物危害）的那个合适的容器可用。 </li><li>确保无菌器械（接种环路），解决方案和文化传媒（琼脂平板）的细菌开始培养前可用。 </li><li>处理感染性微生物后，立即用抗菌肥皂和温水手。 </li></ol> 2.选择参考与收藏株<ol><li>选择并获得一个标准的基因组测序的参考隔离随着编码蛋白质的序列，最好是在FASTA格式。如果有更多的基因组测序的菌株是可用的，包括这些在分析中。 注意:此分离物/这些菌株稍后将被用来预测在质谱中观察到的质量峰的标识（见第7）。 </li><li>选择并在它们覆盖的种类或感兴趣的亚种的系统发育这样的方式获得各种不同的潜在菌株。 注意:这些菌株稍后将被用来证明在人群中的生物标志物的变化（见第8节）。 </li><li>确保整个收集和参考株（S）是亲20 -佩尔利由各自的黄金标准这个特殊的有机体18类型。 注意:这可能包括各种（分）-typing方法，但是很可能会采取MLST，这仍然是为了阐明最微生物物种的遗传多样性的标准方法。 </li><li>推断集合中的发展史，从打字数据， 例如计算系统发生，使用与MEGA6软件MLST数据21算术平均（UPGMA）的加权对群法。对于MLST数据，也请教MLST数据库和分配序列类型和各自的克隆物22。 注意:这将稍后被用来分析MSPP的一致性与早期金标准打字方法（见第9节）。 </li></ol> 3.准备一个MALDI靶板小心:TFA为强酸。使用不当TFA负有严重的皮肤灼伤，眼部损害和严重的刺激邻风险F中的上呼吸道吸入。因此，严格的安全措施必须得到尊重和适当的个人防护装备（PPE），包括护目镜，面罩，适当的手套，靴子，甚至是一个完整的防护服是必要的，在处理TFA。可能接触TFA必须具有有效的排风系统处理下足够的通风物质进行控制。在通风不良的情况下，必须使用经批准的过滤器的呼吸器。此外，TFA是有害的水生生物具有长期持续影响。必须避免TFA的废水中的任何释放到环境中。 注:斑点样到MALDI目标之前，彻底清洁目标板，如果板使用过。 <ol><li>制备，用30毫升去离子水和70ml纯100ml乙醇70％含水乙醇溶液中。 </li><li>通过混合50制备250μl的80％的含水三氟乙酸（TFA）溶液的去离子水和200微升100％TFA的反应管和涡旋管1分钟微升。 </li><li>通过将其放入一个玻璃盘和浸没它在70％含水乙醇中约5分钟，在室温下清洗MALDI靶。 </li><li>冲洗下热水目标。 </li><li>用纸巾，擦拭深入靶板用70％的乙醇水溶液，除去所有以前的样本和其他潜在的杂物。 </li><li>如果需要进一步清洁，在热水冲洗一边用纸巾擦拭。 </li><li>除去残留的和潜在的隐形，污染物，通过覆盖目标表面用80％的薄层TFA水溶液（〜每96点100微升）和擦拭干净的纸巾所有目标位置。 </li><li>最后，冲洗目标除去酸，擦干用纸巾，并使其保持至少15分钟，在室温下蒸发残留液体。 </li></ol> 4.一个制备45;氰基-4-羟基 - 肉桂酸矩阵解法含有内校准物<ol><li>通过在1ml的50％乙腈，47.5％水和2.5％TFA的混合物中溶解10毫克α氰基-4-羟基肉桂酸（HCCA）制备的饱和基质溶液。残留未溶解的HCCA仍将如果溶液是饱和的。 </li><li>加入重组人胰岛素作为内部校准。对于这一点，在-20℃用于进一步使用制备于50％乙腈水溶液，等分试样并储存原液至10微克/微升的最终浓度。 </li></ol> 5. MALDI-TOF质谱注意:特异于感兴趣的生物的培养条件必须被使用。对于MALDI-TOF MS的样品可以通过涂抹标本制作或萃取来制备，这取决于有机体（见8.4.1）。而乙醇甲酸提取方法提供的病原体足够失活，涂抹标本制作具有下SUFF要执行icient生物安全条件的要求（见第1节）。通常，有基体的涂布后没有感染的危险性，但对于具体病原体所需的特定灭活协议。因此，例如诺卡物种的MALDI-TOF MS需要在沸水中，通过蛋白23的乙醇沉淀后的细菌的先前裂解。 EIKhéchine 等 。开发了一种程序分枝杆菌的失活，在含有水和0.5％吐温20 24螺旋盖试管在95℃下加热该细菌菌落1小时。 <ol><li>涂片标本<ol><li>散布细菌菌落的针头大小的量直接在MALDI靶板位置（&#39;发现&#39;）。 </li><li>覆盖每个点用1微升含有内部校准HCCA常规基质或基质的，并留下在室温下crystalize。为确定校准峰的精确质量，覆盖控制SPOT 1微升试验标准和1微升含内部校准HCCA基质。 注意:在此，作为试验标准大肠杆菌 DH5阿尔法的提取物被用于演示在MALDI-TOF MS的特性的蛋白质的指纹。它已与延伸的可检测质量范围的上限两种蛋白质掺入它。 </li></ol></li><li>提取方法<ol><li>收获来自琼脂板培养大约五菌落接种环，并在300微升完全暂停双蒸水在1.5ml反应管中。加入900微升无水乙醇，直到细菌菌落完全暂停反复吹打调匀。 注意:在这个步骤是可能的，并且很好地建立到样品存储在-20℃。此外，病原体灭活可以通过划线1-10微升提取物的上下面在最佳生长条件孵育合适的琼脂平板进行测试。成功激活是由没有微生物生长的指示。 </li><li>离心样品以13,000rpm xg离心1分钟，弃去上清液，并干燥在室温下沉淀10分钟。吹打在50μl的70％甲酸向上和向下彻底重悬沉淀。 </li><li>加入50微升乙腈混匀。离心13,000 XG 2分钟取出碎片。转移1μl的上清液到上的MALDI靶盘一个样本位置和离开干燥，在室温下5分钟。 </li><li>覆盖每个点用1微升含有内部校准HCCA矩阵的和离开在室温下crystalize。 </li></ol></li><li>质谱记录 注意:峰采集从质谱是使用标准程序建议进行（质心算法; S / N比:2;相对强度阈:2％;峰宽3米/ Z，基线减法:顶帽） <ol><li>根据制造商的protoc校准仪器醇。 </li><li>对于每一个点，聚集在100射击步600谱。 <ol><li>进入质谱仪的组态软件的"AutoXecute"选项卡。打开"方法"通过左键点击到"方法"按钮，选择方法如 "MBT_AutoX"从下拉菜单。 </li><li>左键单击"方法"菜单的"编辑"按钮右侧，打开"AutoXecute法编辑器"。转到"积累"选项卡。将"总结"的值改为"600"和_x_"的拍摄步骤"的值改为"100"，"令人满意枪"。 </li></ol></li></ol></li><li>内置频谱校准程序 注意:一分钟的测量误差是固有的质谱。根据间歇仪器的使用，仪器的温度和重新校准，所获得的测量值可以实验之间变化。继前测量仪器校准和<html>测量后的频谱校准内部校准是确保频谱之间的可比性最精确的方法。 <ol><li>执行每次校准峰值列表以下程序: <ol><li>启动频谱浏览器（ 例如 ，flexAnalysis和开放频谱:菜单"文件"→"打开..."） </li><li>与校准峰创建质量控制列表:菜单中的"方法"→"打开..."。 </li><li>选择方法:MBT_Standard.FAMSMethod→"打开"。 </li><li>编辑质量控制列表:取消所有校准物。 </li><li>在底部新增校准物峰:峰标签:"Insulin_HIStag [M + H] + _魅力"; m_z:"5808.29";公差[PPM]:"50";检查校准物复选框。 </li><li>另存为， 例如 ，"MSPP校准表"。 </li></ol></li><li>对于每一个光谱，从列表中选择的校准高峰，单击"自动分配"，然后按"确定"。 </li></ol></li></ol>ove_title"&gt; 6。检查内部校准程序<ol><li>实验确定校准峰的精确质量。 <ol><li>准备两个点与1微升测试标准（每步5.1.1）。叠加先用1微升定期HCCA矩阵，第二次用1微升校准-飙升矩阵。 </li><li>获得各点（5.3节）质谱，并在内部校准的测试标准峰（第5.4节）。 </li><li>通过与频谱浏览器中打开它们（ 例如，flexAnalysis和开放频谱:菜单"文件"→"打开..."）叠加两种光谱的预期质量，并找到峰（胰岛素m / z = 5,808.29），这应该是目前在校准物-掺入谱，但不与常规的矩阵得到的频谱。 </li></ol></li><li>检查校准物山顶不是由利益的有机体的任何其他生物标志物遮蔽。 <ol><li>与基准应变和奥雅纳准备两个点（5.1节）rlay先用1微升正规矩阵，第二次用1微升校准-飙升矩阵。 </li><li>收购点都质谱（第5.3节），并通过与频谱浏览器中打开它们叠加所产生的光谱（ 例如，flexAnalysis和开放频谱:菜单"文件"→"打开..."）。确保校准峰是清晰可见与尖刺矩阵获得，而不是由另一相邻信号遮蔽的频谱。如果不是这种情况下，选择另一校准了特定生物体。 注意:使用尖刺内部校准显著提高精度，以确定生物标志物群众的变化。采用这种方法，下至1大质量的差异可以被检测出来。或者，从生物体始发也不变群众可以用作校准物。然而，根据定义，所有的生物衍生群众必须考虑潜在变量，除非证明并非如此。 </li></ol></li></ol><ol><li>测量参考应变的质谱，使用矩阵尖刺与内部校准物。 <ol><li>散布细菌菌落（第5.1节）或1微升细菌蛋白提取物（第5.2节）的一个针头大小的量直接在MALDI靶板位置（&#39;发现&#39;）。 </li><li>覆盖用1微升含有内部校准HCCA矩阵的各点，并保持目标盘在室温（5.1.2节/ 5.2.4）至crystalize。 </li><li>参考株的记录质谱（第5.3节）。 </li></ol></li><li>内部校准参考频谱的校准质量（这里:在m / z = 5,806.29胰岛素），并随后通过基线减法（高顶礼帽）和平滑（参数:SavitzkyGolay;宽度:2 M / Z，10个循环）前处理。 <ol><li>启动频谱浏览器（ 例如，flexAnalysis和开放频谱:菜单"文件"→"打开...;"）。 </li><li>选择方法:下拉菜单"方法"→"打开..."，左键单击选择的方法， 例如，"MBT_Standard.FAMSMethod"→"打开"。 </li><li>从下拉菜单中选择"校准"选择"内部......"校准光谱。打开一个窗口，列出校准峰（S）（第5.4节）。左键单击校准峰（胰岛素）→左键单击"确定"。从"过程"下拉菜单中选择"过程谱"。 </li><li>为基线减法激活在右侧在光谱列表中的光谱。从"过程"下拉菜单中选择"减质谱基线"。 </li><li>平滑频谱，激活在光谱列表中的光谱在右侧。从"过程"下拉菜单中选择"平稳质谱基线"。 </li></ol></li><li>从参考菌株的基因组测序数据，计算出theoretica升单同位素通过使用序列比对编辑翻译的DNA序列插入相应的氨基酸序列的分子量每个编码的蛋白质的。复制粘贴在ExPASy生物信息资源门户网站（http://web.expasy.org/compute_pi/）这种蛋白质序列在输入框中。按"点击这里"来计算的pI / MW。在C的情况下杆菌 SSP。doylei计算的14检测的生物标志物的质量。 </li><li>将结果复制到电子表格中，随着含有该基因标识符的一列和下一个的分子量。排序方式计算分子量行，方便群众更容易查找。注:其他栏目都是可选的;功能注释以后可能会进行解释特别有用。 </li><li>插入第二列到电子表格的脱methioninated形式的分子量，从单同位素分子量减去135道尔顿。注:这是因为一些蛋白质经过交通过蛋白水解除去N-末端蛋氨酸的翻译后修饰。 </li><li>通过查找从上述（ 表1）中制备的基因组表中的测量的质量的每个主要测量生物标志物的质量分配给从基准应变算出的质量。 </li><li>如果生物标记离子不能被分配到预测的基因产物，可以考虑其他的翻译后修饰（甲基化，乙酰化，异戊烯等 ;参见http://www.abrf.org/delta-mass进行修改的汇编和相关的质量变化）。对于在感兴趣的生物体中经常观察到任何其它已知的翻译后修饰的另一列添加到表并重新计算分子量与对于去methioninated形式的过程。 </li><li>设置其他电子表格选项卡，并记录每个生物标记离子在一个单独的表列中的质量和标识符。 </li></ol> 8.评估变异生物标志物人口<ol><li>从校准获得收集质谱分离，作为参照株（S）（5.4.2节）来完成。 </li><li>确定在质谱变体的生物标志物。变体的质量的特征在于不存在从参考光谱和新型质量在基准不存在的外观已知质量的。的质量差必须符合的单个氨基酸交换（ 表2），或它们的组合。 </li><li>在每行一个分离物，记录每个生物标记，并在各自的表列中的预测的同种型的测量的质量。 注意:很少，一些质量偏移可能归因于几个不同的氨基酸交换， 例如，两个，N-交换用D和Q用E交换，并且反之亦然，导致0.985达（ 表2）的质量转变。这种内在的问题不能由质谱单独解决。因此，具有相同质量的蛋白质序列水平不同亚型必须被视为单个MSPP类型。在特定生物标记基因离子并行Sanger测序证实，虽然MSPP，键入C.没有发生问题杆菌 SSP。doylei隔离在该研究中使用的集合。 </li><li>确认新颖MSPP类型通过PCR放大和测序的各个生物标志物的基因。反过来，这也可作为该生物标记的身份已被正确地分配的确认。 <ol><li>培养细菌的最佳生长条件下，分离物。 C.文化杆菌 SSP。doylei在37℃下微需氧条件下（5％O 2，10％的CO 2，85％N 2）根据补充有5％绵羊血的哥伦比亚琼脂菌株。孵育约48小时。使用单独的琼脂平板上的每个隔离，避免交叉污染。 </li><li>提取根据制造商的说明使用适当的DNA提取试剂盒/自动化机械的细菌分离株的基因组DNA。 </li> &lt;利&gt;扩增使用表3中所列的引物的各自的生物标志物的基因进行下列的条件下所有的PCR反应:在94℃变性30秒;退火在55℃持续30秒;延伸在72℃30秒。 </li><li>确定使用的基因组DNA的适当量由Sanger测序每个扩增子的DNA序列（通常600-700纳克的DNA是在约100毫微克/微升的浓度足够）和扩增引物之一（通常这是通过使用的服务提供者的）。 </li></ol></li><li>在一个单独的表（ 见表4），通过使用适当的翻译工具（ 例如 ，Transseq:http://www.ebi.ac.uk/Tools/st/）记录每个新颖亚型的推导蛋白质序列25。 </li></ol> 9.计算基于MSPP，系统发育和比较黄金标准<ol><li>串联的特定生物标记的氨基酸序列属于到t他MSPP型菌株成一个连续序列使用序列比对编辑器，如BIOEDIT（http://www.mbio.ncsu.edu/bioedit/bioedit.html）26或生物标志物的电子表格。 </li><li>作为金标准分型数据， 例如 ，UPGMA聚类21完成由集群计算系统发育。 </li><li>基于MSPP，系统发育比较与黄金标准4，13所获得的之一。 </li></ol>

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</ol>

The authors have nothing to disclose.

在建立MSPP计划的最关键的一步是生物标志物离子身份的明确的遗传决定。如果它是不可能无疑鉴定的生物标记，那么它应该被排除在方案13。 C.在菌 SSP。doylei方案包括14种不同的生物标志物离子。这些都是5少比C.在检测到C之间杆菌 SSP。 杆菌 MSPP方案13。最显著差异菌 SSP。 菌和C.杆菌 SSP。doylei生物标志物是L31（-M）和L35（-M）13的情况下，翻译后去除氨基末端蛋氨酸。 如图中测试C.菌 SSP。doylei分离收集，MSPP能够区分所有七种不同MLST序列类型。这意味着，每个测试的分离属于一个特定的色曲MSPPENCE类型。此外，MSPP允许C之间亚种分化菌 SSP。 菌和C.菌 SSP。doylei。 在一般情况下，以鉴别潜在于通过MSPP下述的应变水平分离为低级相比像MLST的DNA序列为基础的方法。假设一套行之有效的亚型数据库，细菌分离株的子类型是更快，更便宜相比，DNA测序方法4,13。 MSPP的相比ICMS谱的分级聚类方法，例如利用主成分分析（PCA）4，10，28或二进制峰匹配的比较导致的数学矩阵UPGMA分析型材29，30中的最大的优点是它的高的固有重复性。虽然不同的文化条件，如不同的文化性e媒体，不同琼脂收费，不同孵化温度，和不同的孵育时间显著影响由PCA计算phyloproteomic关系，只要不影响MSPP推导关系6,13。此高再现性的主要原因是在峰强度和质谱质量一般13的独立性。如果在一个分离的质谱一个MSPP相关峰不能无疑识别，有必要再次录制个人分离物的质谱。 该MSPP方法可以适应，原则上每一个微生物物种。尤其，临床相关的微生物物种如艰难梭菌 ， 大肠杆菌 ， 金黄色葡萄球菌 ，和沙门氏菌 SSP。 肠炎的亚型是潜在的未来的应用程序。如果致病因子或抗性基因的表达与菲儿相关oproteomic关系，MSPP可以成为临床常规诊断的创新工具。可检测的峰，并由此包括在MSPP方案的生物标志物的离子的数量的数量可能被增加，通过使用特定的提取和/或裂解的协议，特别是在真菌31的情况下。 最近使用MALDI-TOF技术可以主要仅检测高丰度的核糖体蛋白。这些高丰度的蛋白质干扰与几乎所有的其他较小的蛋白质，如在质谱毒力因子。较小的蛋白质可通过将ESI-TOF-MS（飞行质谱电喷雾电离时间）和HPLC（高效液相色谱法）32来检测。但是，目前这种方法太劳动力和成本密集的表征分离较大的同伙。

在过去十年中，时间飞行基质辅助激光解吸电离质谱（MALDI-TOF MS）已经发展到在临床微生物学1,2微生物属和种鉴定高度评价标准方法。物种鉴定是基于完整细胞或细胞裂解物的小蛋白指纹记录。在常规的临床微生物学中使用的质谱仪的典型质量范围是2-20 kDa的。此外，所得的光谱可以被用于鉴别在下面种菌株和低于亚种级别3。创业初期的研究已经确定了具体的生物标志物离子来株的空肠弯曲菌 4特定亚型， 难辨梭状芽孢杆菌 5， 沙门氏菌 SSP。 伤寒 沙门菌 6， 金黄色葡萄球菌 7 - 9，和Escherichia大肠杆菌10 - 12。 对应等位基因亚型几个变量的生物标记物群众相结合，提供了更深层次的子类型的选项。此前，我们成功地实施大规模型材这些变化转换成一个叫做C.质谱法基于phyloproteomics（MSPP）有意义的和可重复的phyloproteomic关系的方法菌 SSP。 杆菌菌株收集13。 MSPP可以使用质谱等同于基于DNA序列分型技术如多位点序列分型（MLST）。 弯曲杆菌是细菌性胃肠炎的全球领先的原因14，15。作为弯曲菌病感染后后遗症的结果，即，格林-巴利综合症，反应性关节炎和炎症性肠病可能出现16。感染的主要来源是从鸡，火鸡，猪，牛，羊，鸭，牛奶及地表水15,17污染畜肉。因此，在食品安全的背景下定期流行病学监测研究是必要的。 MLST是"黄金标准"的分子分型弯曲杆菌种18。因为基于MLST方法桑格测序是劳动密集，耗时且相对昂贵的，MLST打字被限制为相对小的分离同伙。因此，有必要更便宜和更快的子类型的方法。这种需要可以通过质谱方法，如MSPP得到满足。 本文介绍用空肠弯曲菌 SSP的集合MSPP打字了详细的方案。doylei株及其与MLST潜力比较。

<table><tbody><tr><td>acetonitrile</td><td>Sigma-Aldrich, Taufkirchen, Germany</td><td>34967</td><td></td></tr><tr><td>Autoflex III TOF/TOF 200 system</td><td>Bruker Daltonics, Bremen, Germany</td><td>GT02554 G201</td><td>Mass spectrometer</td></tr><tr><td>bacterial test standard BTS</td><td>Bruker Daltonics, Bremen, Germany</td><td>604537</td><td></td></tr><tr><td>BioTools 3.2 SR1</td><td>Bruker Daltonics, Bremen, Germany</td><td>263564</td><td>Software Package</td></tr><tr><td>Bruker IVD Bakterial Test Standard</td><td>Bruker Daltonics, Bremen, Germany</td><td>8290190</td><td>5 tubes</td></tr><tr><td>&lt;em&gt;Campylobacter jejuni&lt;/em&gt; subsp. &lt;em&gt;doylei&lt;/em&gt; isolate&amp;nbsp;</td><td>Belgium coordinated collection of microorganisms/Laboratory of Microbiology UGent BCCM/LMG Ghent, Belgium</td><td>LMG8843</td><td>ATCC 49349;IMVS 1141;NCTC 11951;strain 093</td></tr><tr><td>&lt;em&gt;Campylobacter jejuni&lt;/em&gt; subsp. &lt;em&gt;doylei&lt;/em&gt; isolate&amp;nbsp;</td><td>Belgium coordinated collection of microorganisms/Laboratory of Microbiology UGent BCCM/LMG Ghent, Belgium</td><td>LMG9143</td><td>Goossens Z90</td></tr><tr><td>&lt;em&gt;Campylobacter jejuni&lt;/em&gt; subsp. &lt;em&gt;doylei&lt;/em&gt; isolate&amp;nbsp;</td><td>Belgium coordinated collection of microorganisms/Laboratory of Microbiology UGent BCCM/LMG Ghent, Belgium</td><td>LMG7790</td><td>ATCC 49350;CCUG 18265;Kasper 71;LMG 8219;NCTC 11847</td></tr><tr><td>&lt;em&gt;Campylobacter jejuni&lt;/em&gt; subsp. &lt;em&gt;doylei&lt;/em&gt; isolate&amp;nbsp;</td><td>Belgium coordinated collection of microorganisms/Laboratory of Microbiology UGent BCCM/LMG Ghent, Belgium</td><td>LMG9243</td><td>Goossens N130</td></tr><tr><td>&lt;em&gt;Campylobacter jejuni&lt;/em&gt; subsp. &lt;em&gt;doylei&lt;/em&gt; isolate&amp;nbsp;</td><td>Belgium coordinated collection of microorganisms/Laboratory of Microbiology UGent BCCM/LMG Ghent, Belgium</td><td>LMG8871</td><td>NCTC A603/87</td></tr><tr><td>&lt;em&gt;Campylobacter jejuni&lt;/em&gt; subsp. &lt;em&gt;doylei&lt;/em&gt; isolate&amp;nbsp;</td><td>Belgium coordinated collection of microorganisms/Laboratory of Microbiology UGent BCCM/LMG Ghent, Belgium</td><td>LMG9255</td><td>Goossens B538</td></tr><tr><td>&lt;em&gt;Campylobacter jejuni&lt;/em&gt; subsp. &lt;em&gt;doylei&lt;/em&gt; isolate&amp;nbsp;</td><td>Belgium coordinated collection of microorganisms/Laboratory of Microbiology UGent BCCM/LMG Ghent, Belgium</td><td>LMG8870</td><td>NCTC A613/87</td></tr><tr><td>Columbia agar base&amp;nbsp;</td><td>Merck, Darmstadt, Germany</td><td>1.10455 .0500</td><td>500 g</td></tr><tr><td>Compass for FlexSeries 1.2 SR1</td><td>Bruker Daltonics, Bremen, Germany</td><td>251419</td><td>Software Package</td></tr><tr><td>defibrinated sheep blood&amp;nbsp;</td><td>Oxoid Deutschland GmbH, Wesel, Germany</td><td>SR0051</td><td></td></tr><tr><td>ethanol</td><td>Sigma-Aldrich, Taufkirchen, Germany</td><td>02854 Fluka</td><td></td></tr><tr><td>formic acid</td><td>Sigma-Aldrich, Taufkirchen, Germany</td><td>F0507</td><td></td></tr><tr><td>HCCA matrix</td><td>Bruker Daltonics, Bremen, Germany</td><td>604531</td><td></td></tr><tr><td>Kimwipes paper tissue</td><td>Kimtech Science via Sigma-Aldrich, Taufkirchen, Germany</td><td>Z188956</td><td></td></tr><tr><td>MALDI Biotyper 2.0</td><td>Bruker Daltonics, Bremen, Germany</td><td>259935</td><td>Software Package</td></tr><tr><td>Mast Cryobank vials</td><td>Mast Diagnostica, Reinfeld, Germany</td><td>CRYO/B</td><td></td></tr><tr><td>MSP 96 polished steel target</td><td>Bruker Daltonics, Bremen, Germany</td><td>224989</td><td></td></tr><tr><td>QIAamp DNA Mini Kit&amp;nbsp;</td><td>Qiagen, Hilden, Germany</td><td>51304</td><td></td></tr><tr><td>recombinant human insulin</td><td>Sigma-Aldrich, Taufkirchen, Germany</td><td>I2643</td><td></td></tr><tr><td>trifluoroacetic acid</td><td>Sigma-Aldrich, Taufkirchen, Germany</td><td>T6508</td><td></td></tr><tr><td>water, molecular biology-grade</td><td>Sigma-Aldrich, Taufkirchen, Germany</td><td>W4502</td><td></td></tr></tbody></table>

subtyping of campylobacter jejuni ssp. doylei isolates using mass spectrometry-based phyloproteomics (mspp)

MALDI-TOF MS提供不仅在种和亚种水平，但甚至低于，在应变水平区分某些细菌的可能性。可检测生物标志物离子的等位基因亚型产生具体的分离质量的变化。质谱为基础的phyloproteomics（MSPP）是一种新技术，它结合了质谱检测生物标志物的群众一个方案，允许从比较基因组分离特定质量偏移phyloproteomic关系扣除测序参考株。然后将推断的氨基酸序列被用于计算基于MSPP-系统树图。 在这里，我们通过键入空肠弯曲杆菌 SSP描述MSPP的工作流程。doylei的7株分离的集合。这七株人类起源和多位点序列分（MLST）的展示了其遗传多样性。 MSPP打字造成了七种不同的MSPP序列类型，充分反映他们的PHYlogenetic关系。 C.在菌 SSP。doylei MSPP方案包括14个不同的生物标志物离子，主要是核糖体蛋白在2至11 kDa的质量范围。 MSPP可以在原则上，可以适用于其他质谱平台具有延伸的质量范围。因此，这种技术有可能成为应变水平的微生物类型的有用工具的潜力。

此前，我们成功地建立了一个C. MSPP方案菌 SSP。 空肠弯曲菌 13。在这里，我们的目的是同级亚种C.延长方法菌 SSP。doylei。在这个特定的设置，七C.菌 SSP。doylei株微生物微生物学根特大学BCCM / LMG比利时根特/实验室比利时集合收购。用于我们的分析所有7株均来源于人。基因组测序菌株ATCC 49349（LMG 8843），最初是从一个2岁的澳大利亚孩子的粪便腹泻担任参考隔离。从集合，另外六个株可供选择:LMG 9143，LMG 9243和9255 LMG儿童患腹泻和生活在比利时布鲁塞尔的粪便中分离; LMG 7790（ATCC 49350）从德国的个体的胃活检样品中分离;和LMG 8870（NCTC A613 / 87）以及LMG 8871（NCTC A603 / 87），无论是从南非儿童绘制不同的血液样本隔离。 所有C.杆菌 SSP。doylei菌株储存在-80℃下作为cryobank股票，刚解冻的每个分析和培养，通过使用在37℃下微需氧条件下（5％氧气下补充了5％绵羊血的孵育48小时:Columbia琼脂基2，10％的CO 2，85％N 2）。 与此相反的建立MSPP技术的C.杆菌 SSP。 杆菌 13不可能至基部从较大的序列集合衍生的同种型数据库上的方法。只有一个单C.杆菌 SSP。doylei条目存在于rMLST数据库，并且这对应于基准应变C.杆菌 SSP。doylei ATCC 49349 27，因此，每个生物在比较紧张C.检测标志物质量转变杆菌 SSP。doylei ATCC 49349在同种型数据库中的新条目，并需要由Sanger测序来确认。 分析所得的C的多样性菌 SSP。doylei株，MLST进行和基于MLST-UPGMA-树状图，包括七个检查C.菌 SSP。doylei分离株和C.杆菌 SSP。作为外群计算（ 图1） 空肠弯曲杆菌菌株81-176。每个C.菌 SSP。doylei菌株属于一个不同的MLST序列型，日久成两个子集群。应变LMG7790具有最长系统发育距离相比，剩余的C.菌 SSP。doylei株。 C.可录制MALDI-TOF参考质谱菌 SSP。doylei </em&gt; ATCC 49349含有14可由计算分子量与参考光谱（ 图2）的比较来确定的奇异带电生物标志物的离子。 152939117，S20-M，和S15-M（ 图3）|内的收集，为L32-M，L33，由GI编码的假定蛋白检测不同同种型。分配到生物标记物离子其余群众分别在测试C.不变菌 SSP。doylei株。对应于该质量偏移氨基酸取代已经鉴定通过PCR扩增，并使用在表3中 。 表4列出了所有生物标志物离子的氨基酸序列包括在MSPP方案中所列的引物的特定基因的Sanger测序以及检测出的等位基因亚型。 基于MSPP，phyloproteomic UPGMA-树（ 图4），计算出同样的7℃。菌 SSP。doylei分离株和C.菌 SSP。由于使用全部14个生物标志物离子的级联氨基酸序列在参考菌株其分子量顺序外群菌菌株81-176。每个隔离代表个人MSPP序列类型。虽然所获得的phyloproteomic关系是不被MLST， 梭菌获得的那些完全相同杆菌 SSP。doylei菌株再次排列成两子群集。第一子集群是由LMG 8843，8870 LMG和LMG 9243，第二个由LMG 9255，LMG 9143形成，LMG 8871和LMG 7790.由于与MLST分析可见，隔离LMG7790显示，在MSPP-最长phyloproteomic距离分析。 <img alt="图1" src="/files/ftp_upload/54165/54165fig1.jpg" /> 图 1:MLST-BASED进化UPGMA树。基于平衡MLST-UPGMA-树状图从七个C.构建菌 SSP。doylei分离株和C.菌 SSP。 空肠弯曲菌菌株81-176。应变颜色代码:LMG 8843（黑色），LMG 8870（灰色），LMG 9243（蓝色），LMG 9255（绿松石），LMG 9143（绿色）和LMG 8871（粉红色），LMG 7790（黄色），和81- 176（白色）。该MLST序列类型各菌株名称后面给出。每C.杆菌 SSP。doylei隔离属于不同MLST序列类型。 X轴表示联动距离。应变LMG 7790示出了相对于其余六个菌株最长系统发育距离。菌株LMG 8843，8870 LMG和LMG 9243以及9255 LMG，LMG 9143和LMG 8871的形式两个C.内部不同子群集菌 SSP。doylei集群。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54165/54165fig1large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> </一&gt; <img alt="图2" src="/files/ftp_upload/54165/54165fig2.jpg" /> 图 2:C的基因组相互关联的初步分配 菌 SSP。doylei ATCC 49349（LMG 8843）观察到的生物标记物质量的基础上，从C的全基因组序列预测ORF的计算质量（平均同位素组成） 杆菌 SSP。doylei菌株ATCC 49349，生物标志物群众被分配到相应的蛋白质编码序列。然而，测量范围内，为对核糖体亚基L31生物标记块（MW = 7,315道尔顿），S17（MW = 9549道尔顿）和S18（MW = 10,285道尔顿）以及它们的脱methioninated亚型（插图M / Z = 7,000-7,200道尔顿）不能被明确地分配。因此，L31，S17，和S18中未包括在C.菌 SSP。doylei MSPP方案。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54165/54165fig2large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> <img alt="图3" src="/files/ftp_upload/54165/54165fig3.jpg" /> 图 3:C的特定生物标记的质量峰 菌 SSP。doylei MSPP方案。在每个面板的质谱的所有七个测试C. 。 杆菌 SSP doylei菌株对应于特定MSPP类型（颜色代码作为图1）已被覆盖，以指示生物标志物质量偏移由于等位基因亚型:（A）L36 + H +; （B）L34 + H +; （C）的L32-M + H +; （D </strong&gt;）L33 + H +; （E），S14-M + H +; （F）的 L29 + H +，L28-M + H +，和L35-M + H +; （G）L24-M + H +; （H）GI | 152939117 + H +; （Ⅰ）L27-M + H +; （J）S20-M + H +; （K）的S15-M + H +; （L）的S19-M + H +; （M）强烈的质量模糊核糖体蛋白S18的可变潜在生物标志物的峰值; （N），S20-M + 2H +; （O）L15-M + 2H +;的X轴:质量[大]·费比1的比例，规模达200。 Y轴:强度[任意单位]，光谱单独调节为低强度峰的更好的可视化相当的噪音水平。 "-M"一个核糖体亚单位的名称后表示去methioninated亚型。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54165/54165fig3large.jpg" target="_blank">请点击她的</a>E要查看此图的放大版本。 <img alt="图4" src="/files/ftp_upload/54165/54165fig4.jpg" /> 图 4:基于MSPP-phyloproteomic UPGMA树所描绘phyloproteomic UPGMA树包括同样的7℃。菌 SSP。doylei分离株和C.杆菌亚种。如在图1 菌株81-176。一种着色斑点（颜色代码作为图1）表示各菌株。为更好的比较菌株被布置在输入顺序中，为从基于MLST树获得的订单。树形图下方的轴表示联动距离。虽然所获得的phyloproteomic关系不完全等同于亲缘基于MLST树，全局图像是可比的。人口分成两组:3株LMG 8843，8870 LMG和LMG 9243形成一个clust呃，而LMG 9255，LMG 9143，LMG 8871和7790 LMG形成第二集群。在这个集群LMG 7790显示相比于LMG 9255，LMG 9143和LMG 8871.在这个子集群LMG形成了子集群最长phyloproteomic距离9143交换机相对于LMG 9255.位置。然而，即使采用MSPP法分离每一个代表个人MSSP序列类型。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54165/54165fig4large.jpg" target="_blank">请点击此处查看该图的放大版本。</a> 表 1:C的所有注释的ORF的计算质量 杆菌 SSP。doylei ATCC 49349 菌株。列出每种蛋白在C.编码的所有计算单同位素分子量菌 SSP。doylei ATCC 49349基因组。该ExPASy生物信息学资源门户网站被用于特定分子量的计算。 B栏列出了methioninated亚型，而C列列出了去methioninated亚型。包括在C.生物标记群众菌 SSP。doylei MSPP方案以红色突出显示。注:生物标志物蛋白L36不在C的基因组序列注解菌 SSP。doylei ATCC49349。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54165/Table1_calculated_masses.xlsx" target="_blank">请点击此处下载此文件。</a> 表 2:通过由于单个SNP的氨基酸变化引起的质量变化的所有潜在的单核苷酸多态性进行了检查，使用标准遗传密码所得氨基酸交换。所有的沉默突变被废除，非同义突变与地区环境部门一道共同编译lting质量变化。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54165/Table2_mass_changes.xlsx" target="_blank">请点击此处下载此文件。</a> 表 3:用于 C 的测序的寡核苷酸引 菌 SSP。doylei 列入MSPP-方案基因 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54165/Table3_Cjd_MSPP_Primer02.xlsx" target="_blank">请点击这里下载此文件。</a> 表 4:所有同种型的概述包括在 C.菌 SSP。doylei MSPP-方案，该表列出了包含在C中的所有生物标志物离子菌 SSP。doylei MSPP SC血红素。参考菌株ATCC 49349的氨基酸序列被完全给出。为进一步检测的同种型中，只有特定的氨基酸取代中列出。氨基酸编号始终包括起始甲硫氨酸;如果质谱表明它的缺席，它是写在括号（M）。对于每个亚型分子质量，质量差的参考菌株ATCC 49349亚型和频率亚型数据集内表示。 <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54165/Table4_MSPP_Cjd-isoforms_V03.xlsx" target="_blank">请点击此处下载此文件。</a>

Watch this Scientific Journal Video about Subtyping of Campylobacter jejuni ssp. doylei Isolates Using Mass Spectrometry-based PhyloProteomics MSPP at JoVE.com

Subtyping of Campylobacter jejuni ssp. doylei Isolates Using Mass Spectrometry-based PhyloProteomics MSPP

基于质谱的phyloproteomics（MSPP）用于键入空肠弯曲杆菌过磷酸钙的集合。doylei隔离在相比于多位点序列分型（MLST）的应变水平。

器的子类型<em&gt;空肠弯曲菌</em&gt; SSP。<em&gt; doylei</em&gt;分离株使用基于光谱质谱PhyloProteomics（MSPP）

MALDI-TOF MS offers the possibility to differentiate some bacteria not only at the species and subspecies level but even below, at the strain level. ...

subtyping-campylobacter-jejuni-ssp-doylei-isolates-using-mass

Nanyang Technological University

Research

JoVE Journal

Genetics

Subtyping of Campylobacter jejuni ssp. doylei Isolates Using Mass Spectrometry-based PhyloProteomics (MSPP)

8.6K 次观看.  Universitätsmedizin Göttingen. 基于质谱的phyloproteomics（MSPP）用于键入空肠弯曲杆菌过磷酸钙的集合。doylei隔离在相比于多位点序列分型（MLST）的应变水平。 

视频: Subtyping of Campylobacter jejuni ssp. doylei Isolates Using Mass Spectrometry-based PhyloProteomics MSPP

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

Identification of Antibacterial Immunity Proteins in Escherichia coli using MALDI-TOF-TOF-MS/MS and Top-Down Proteomic Analysis

This protocol identifies the immunity proteins of the bactericidal enzymes: colicin E3 and bacteriocin, produced by a pathogenic Escherichia coli strain using antibiotic induction, and identified by MALDI-TOF-TOF tandem mass spectrometry and top-down proteomic analysis with software developed in-house. The immunity protein of colicin E3 (Im3) and the immunity protein of bacteriocin (Im-Bac) were identified from prominent b- and/or y-type fragment ions generated by the polypeptide backbone cleavage (PBC) on the C-terminal side of aspartic acid, glutamic acid, and asparagine residues by the aspartic acid effect fragmentation mechanism. The software rapidly scans in silico protein sequences derived from the whole genome sequencing of the bacterial strain. The software also iteratively removes amino acid residues of a protein sequence in the event that the mature protein sequence is truncated. A single protein sequence possessed mass and fragment ions consistent with those detected for each immunity protein. The candidate sequence was then manually inspected to confirm that all detected fragment ions could be assigned. The N-terminal methionine of Im3 was post-translationally removed, whereas Im-Bac had the complete sequence. In addition, we found that only two or three non-complementary fragment ions formed by PBC are necessary to identify the correct protein sequence. Finally, a promoter (SOS box) was identified upstream of the antibacterial and immunity genes in a plasmid genome of the bacterial strain.

Identification of Antibacterial Immunity Proteins in Escherichia coli using MALDI-TOF-TOF-MS/MS and Top-Down Proteomic Analysis

Here we present a protocol for the rapid identification of proteins produced by genomically sequenced pathogenic bacteria using MALDI-TOF-TOF tandem mass spectrometry and top-down proteomic analysis with software developed in-house. Metastable protein ions fragment because of the aspartic acid effect and this specificity is exploited for protein identification.

使用MALDI-TOF-TOF-MS/MS和自上而下的蛋白质组学分析鉴定 大肠杆菌 中的抗菌免疫蛋白

This protocol identifies the immunity proteins of the bactericidal enzymes: colicin E3 and bacteriocin, produced by a pathogenic Escherichia coli strain ...

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

A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions

Mass spectrometry (MS)-based proteomics enables comprehensive proteome analysis across a wide range of biological samples, including cells, tissues, and body fluids. Formalin-fixed, paraffin-embedded (FFPE) tissue sections, commonly used for long-term archiving, have emerged as valuable resources for proteomic studies. Beyond their storage benefits, researchers can isolate regions of interest (ROIs) from normal tissue regions through collaborative efforts with pathologists. Despite this potential, a streamlined approach for proteomic experiments encompassing ROI isolation, proteomic sample preparation, and MS analysis remains lacking. In this protocol, an integrated workflow that combines macrodissection of ROIs, suspension trapping-based sample preparation, and high-throughput MS analysis is presented. Through this approach, the ROIs of patients' FFPE tissues, consisting of benign serous cystic neoplasms (SCN) and precancerous intraductal papillary mucinous neoplasms (IPMN) diagnosed by pathologists, were macrodissected, collected, and analyzed, resulting in high proteome coverage. Furthermore, molecular differences between the two distinct pancreatic cystic neoplasms were successfully identified, thus demonstrating the applicability of this approach for advancing proteomic research with FFPE tissues.

Here, we establish a mass spectrometry-based proteomic method using isolated regions of interest in formalin-fixed, paraffin-embedded tissue sections. This protocol is used to analyze proteome from specific tissue areas in archived formalin-fixed, paraffin-embedded tissue sections.

使用选定组织区域进行基于质谱的蛋白质组学的简化方法

Mass spectrometry (MS)-based proteomics enables comprehensive proteome analysis across a wide range of biological samples, including cells, tissues, and ...

Identification of Protein Complexes in Escherichia coli using Sequential Peptide Affinity Purification in Combination with Tandem Mass Spectrometry

Since most cellular processes are mediated by macromolecular assemblies, the systematic identification of protein-protein interactions (PPI) and the identification of the subunit composition of multi-protein complexes can provide insight into gene function and enhance understanding of biological systems1, 2. Physical interactions can be mapped with high confidence vialarge-scale isolation and characterization of endogenous protein complexes under near-physiological conditions based on affinity purification of chromosomally-tagged proteins in combination with mass spectrometry (APMS). This approach has been successfully applied in evolutionarily diverse organisms, including yeast, flies, worms, mammalian cells, and bacteria1-6. In particular, we have generated a carboxy-terminal Sequential Peptide Affinity (SPA) dual tagging system for affinity-purifying native protein complexes from cultured gram-negative Escherichia coli, using genetically-tractable host laboratory strains that are well-suited for genome-wide investigations of the fundamental biology and conserved processes of prokaryotes1, 2, 7. Our SPA-tagging system is analogous to the tandem affinity purification method developed originally for yeast8, 9, and consists of a calmodulin binding peptide (CBP) followed by the cleavage site for the highly specific tobacco etch virus (TEV) protease and three copies of the FLAG epitope (3X FLAG), allowing for two consecutive rounds of affinity enrichment. After cassette amplification, sequence-specific linear PCR products encoding the SPA-tag and a selectable marker are integrated and expressed in frame as carboxy-terminal fusions in a DY330 background that is induced to transiently express a highly efficient heterologous bacteriophage lambda recombination system10. Subsequent dual-step purification using calmodulin and anti-FLAG affinity beads enables the highly selective and efficient recovery of even low abundance protein complexes from large-scale cultures. Tandem mass spectrometry is then used to identify the stably co-purifying proteins with high sensitivity (low nanogram detection limits).
Here, we describe detailed step-by-step procedures we commonly use for systematic protein tagging, purification and mass spectrometry-based analysis of soluble protein complexes from E. coli, which can be scaled up and potentially tailored to other bacterial species, including certain opportunistic pathogens that are amenable to recombineering. The resulting physical interactions can often reveal interesting unexpected components and connections suggesting novel mechanistic links. Integration of the PPI data with alternate molecular association data such as genetic (gene-gene) interactions and genomic-context (GC) predictions can facilitate elucidation of the global molecular organization of multi-protein complexes within biological pathways. The networks generated for E. coli can be used to gain insight into the functional architecture of orthologous gene products in other microbes for which functional annotations are currently lacking.

Identification of Protein Complexes in Escherichia coli using Sequential Peptide Affinity Purification in Combination with Tandem Mass Spectrometry

Affinity purification of tagged proteins in combination with mass spectrometry (APMS) is a powerful method for the systematic mapping of protein interaction networks and for investigating the mechanistic basis of biological processes. Here, we describe an optimized sequential peptide affinity (SPA) APMS procedure developed for the bacterium Escherichia coli that can be used to isolate and characterize stable multi-protein complexes to near homogeneity even starting from low copy numbers per cell.

蛋白复合物的鉴定<em&gt;大肠杆菌</em使用顺序肽亲和纯化技术相结合串联质谱法

Since most cellular processes are mediated by macromolecular assemblies, the systematic identification of protein-protein interactions (PPI) and the ...

Label-Free Quantitative Proteomics Workflow for Discovery-Driven Host-Pathogen Interactions

The technological achievements of mass spectrometry (MS)-based quantitative proteomics opens many undiscovered avenues for analyzing an organism&#8217;s global proteome under varying conditions. This powerful strategy applied to the interactions of microbial pathogens with the desired host comprehensively characterizes both perspectives towards infection. Herein, the workflow describes label-free quantification (LFQ) of the infectome of Cryptococcus neoformans, a fungal facultative intracellular pathogen that is the causative agent of the deadly disease cryptococcosis, in the presence of immortalized macrophage cells. The protocol details the proper protein preparation techniques for both pathogen and mammalian cells within a single experiment, resulting in appropriate peptide submission for liquid-chromatography (LC)-MS/MS analysis. The high throughput generic nature of LFQ allows a wide dynamic range of protein identification and quantification, as well as transferability to any host-pathogen infection setting, maintaining extreme sensitivity. The method is optimized to catalogue extensive, unbiased protein abundance profiles of a pathogen within infection-mimicking conditions. Specifically, the method demonstrated here provides essential information on C. neoformans pathogenesis, such as protein production necessary for virulence and identifies critical host proteins responding to microbial invasion.

Here, we present a protocol to profile the interplay between host and pathogen during infection by mass spectrometry-based proteomics. This protocol uses label-free quantification to measure changes in protein abundance of both host (e.g., macrophages) and pathogen (e.g., Cryptococcus neoformans) in a single experiment.

无标签定量蛋白经济学工作流程，用于发现驱动的宿主-病原体交互

The technological achievements of mass spectrometry (MS)-based quantitative proteomics opens many undiscovered avenues for analyzing an organism&#8217;s ...

免疫与感染

Capture Compound Mass Spectrometry - A Powerful Tool to Identify Novel c-di-GMP Effector Proteins

Considerable progress has been made during the last decade towards the identification and characterization of enzymes involved in the synthesis (diguanylate cyclases) and degradation (phosphodiesterases) of the second messenger c-di-GMP. In contrast, little information is available regarding the molecular mechanisms and cellular components through which this signaling molecule regulates a diverse range of cellular processes. Most of the known effector proteins belong to the PilZ family or are degenerated diguanylate cyclases or phosphodiesterases that have given up on catalysis and have adopted effector function. Thus, to better define the cellular c-di-GMP network in a wide range of bacteria experimental methods are required to identify and validate novel effectors for which reliable in silico predictions fail.
We have recently developed a novel Capture Compound Mass Spectrometry (CCMS) based technology as a powerful tool to biochemically identify and characterize c-di-GMP binding proteins. This technique has previously been reported to be applicable to a wide range of organisms1. Here we give a detailed description of the protocol that we utilize to probe such signaling components. As an example, we use Pseudomonas aeruginosa, an opportunistic pathogen in which c-di-GMP plays a critical role in virulence and biofilm control. CCMS identified 74% (38/51) of the known or predicted components of the c-di-GMP network. This study explains the CCMS procedure in detail, and establishes it as a powerful and versatile tool to identify novel components involved in small molecule signaling.

The ubiquitous second messenger c-di-GMP controls growth and behavior of many bacteria. We have developed a novel Capture Compound Mass Spectrometry based technology to biochemically identify and characterize c-di-GMP binding proteins in virtually any bacterial species.

捕获复合质谱 - 一个强大的工具来确定新型C-二GMP效应蛋白

Considerable progress has been made during the last decade towards the identification and characterization of enzymes involved in the synthesis ...

Use of MALDI-TOF Mass Spectrometry and a Custom Database to Characterize Bacteria Indigenous to a Unique Cave Environment (Kartchner Caverns, AZ, USA)

MALDI-TOF mass spectrometry has been shown to be a rapid and reliable tool for identification of bacteria at the genus and species, and in some cases, strain levels. Commercially available and open source software tools have been developed to facilitate identification; however, no universal/standardized data analysis pipeline has been described in the literature. Here, we provide a comprehensive and detailed demonstration of bacterial identification procedures using a MALDI-TOF mass spectrometer. Mass spectra were collected from 15 diverse bacteria isolated from Kartchner Caverns, AZ, USA, and identified by 16S rDNA sequencing. Databases were constructed in BioNumerics 7.1. Follow-up analyses of mass spectra were performed, including cluster analyses, peak matching, and statistical analyses. Identification was performed using blind-coded samples randomly selected from these 15 bacteria. Two identification methods are presented: similarity coefficient-based and biomarker-based methods. Results show that both identification methods can identify the bacteria to the species level.

Use of MALDI-TOF Mass Spectrometry and a Custom Database to Characterize Bacteria Indigenous to a Unique Cave Environment Kartchner Caverns, AZ, USA

This work details procedures for rapid identification of bacteria using MALDI-TOF MS. The identification procedures include spectrum acquisition, database construction, and follow up analyses. Two identification methods, similarity coefficient-based and biomarker-based methods, are presented.

使用MALDI-TOF质谱和自定义数据库的表征细菌土著一个独特的洞穴环境（卡切内岩洞，AZ，USA）

MALDI-TOF mass spectrometry has been shown to be a rapid and reliable tool for identification of bacteria at the genus and species, and in some cases, ...

<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.

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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

使用MALDI-TOF-TOF-MS/MS和自上而下的蛋白质组学分析鉴定大肠杆菌中的抗菌免疫蛋白

分析甲基化和其他 S腺苷_{L同型半胱氨酸结合蛋白}

使用选定组织区域进行基于质谱的蛋白质组学的简化方法

蛋白复合物的鉴定

无标签定量蛋白经济学工作流程，用于发现驱动的宿主-病原体交互

捕获复合质谱 - 一个强大的工具来确定新型C-二GMP效应蛋白

使用MALDI-TOF质谱和自定义数据库的表征细菌土著一个独特的洞穴环境（卡切内岩洞，AZ，USA）

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

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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

使用MALDI-TOF-TOF-MS/MS和自上而下的蛋白质组学分析鉴定 大肠杆菌 中的抗菌免疫蛋白

分析甲基化和其他 S腺苷 L同型半胱氨酸结合蛋白

使用选定组织区域进行基于质谱的蛋白质组学的简化方法

蛋白复合物的鉴定

无标签定量蛋白经济学工作流程，用于发现驱动的宿主-病原体交互

捕获复合质谱 - 一个强大的工具来确定新型C-二GMP效应蛋白

使用MALDI-TOF质谱和自定义数据库的表征细菌土著一个独特的洞穴环境（卡切内岩洞，AZ，USA）

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

使用MALDI-TOF-TOF-MS/MS和自上而下的蛋白质组学分析鉴定大肠杆菌中的抗菌免疫蛋白

分析甲基化和其他 S腺苷_{L同型半胱氨酸结合蛋白}