非常感谢 Tanveer Batth 和同事在建立预分馏法方面的建议。
这项工作得到了瑞典研究理事会、Wallström 和 Sjöblom 基金会、枪支和 Bertil Stohne 基金会 Stiftelse、马格努斯 Bergwall 基金会、Åhlén 基金会、Alzheimerfonden、Demensförbundet、Stiftelsen för 的资助。格姆拉斯坦 Tjänarinnor, 克努特和爱丽丝的基础, Frimurarestiftelsen, 和 Västra Götalandsregionen。
这个项目的主要资助对象是 Kaj Blennow, 亨利 Zetterberg 和约翰 Gobom。

下面所述的协议是在以前的研究中使用的一个精炼版本, 其中大量的内源性多肽在人类 CSF15中被识别出来。对原始协议的更新包括对脑脊液化学预处理的细微改动, 以及用于离线高 pH 反相高效 HPLC 预分馏的梯度优化。
道德考虑
所有关于瑞典病人和控制材料的研究都得到了伦理委员会的批准: St. 约兰·佩尔松 (文献 2005-554-31/3)。来自阿姆斯特丹痴呆症患者的脑脊液样本和在国立神经病学和神经外科医院采集的样本被用于研究, 得到所有参与的病人的书面同意, 并得到区域伦理委员会的批准。这里所用的材料主要是从为诊断目的而抽取的样品中提取的左脑脊液, 在被纳入我们的研究之前就已被识别。没有可能将样本追溯到任何个别捐助者或捐助国集团。
1. 人体脑脊液的提取:
<ol><li>使用标准的协议22, 通过腰椎穿刺提取脑脊液 (必须由训练有素的医生执行)。</li>
	<li>通过离心 2500 x g 去除细胞碎片和其他非水溶性物质20分钟。</li>
	<li>目测检查脑脊液样本中是否有可能显示穿刺出血导致的血液污染的变色。血液中蛋白质浓度的升高和蛋白酶的存在会对分析结果产生很大影响。</li>
</ol>2. 脑脊液预处理 (1.5 毫升样本量, 无量化):
<ol><li>室温 (RT) 解冻1.5 毫升脑脊液等分, 将内容转移到10毫升聚丙烯管, 并将80µL 1 米乙碳酸氢盐 (TEAB) 作为缓冲剂。</li>
	<li>添加0.65 毫升8米胍盐酸盐 (GdnHCl) (活性浓度 GdnHCl: 2.4 米) 和涡旋轻轻在 RT 为10分钟。 注: chaotropic 剂, GdnHCl, 都影响溶剂粘度和与多肽链的相互作用, 这导致蛋白质的展开是积极有利的23。因此, GdnHCl 在随后的过滤过程中溶解蛋白质聚合体并增加内源性肽的回收。</li>
	<li>添加60µL 200 毫米水三 (2-乙) 膦盐酸盐 (TCEP) (活性浓度 TCEP: 6 毫米) 和孵育55° c 1 小时, 以减少半胱氨酸 disulphides。</li>
	<li>添加35µL 400 毫米碘 (iaa) (活性浓度 iaa: 4 毫米) 和孵化在 RT 在黑暗中为30分钟到烷基化胱氨酸。在随后的样品制备过程中, 添加烷基基团可确保半胱氨酸残留物在任何时候都不能自发形成新的二硫化物桥。</li>
	<li>在分子过滤之前, 加入3.25 毫升的 de 电离水和涡旋来稀释样品, 导致样品总量为5.5 毫升。这一步的作用是稀释 GdnHCl 到低于1米, 因为较高的浓度已被观察到有时会导致从过滤器设备的聚合物物质浸出。</li>
</ol>3. 脑脊液的预治疗 (10 x 150 µL 样本量, 等压标签-定量):
<ol><li>将150µL 的脑脊液等分从10人的 RT 中解冻, 然后将内容转移到单个1.5 毫升低束缚微离心管, 并将8µL 1 M TEAB 作为缓冲剂。</li>
	<li>添加65µL 8 米 GdnHCl (活性浓度 GdnHCl: 2.4 米) 和涡旋轻轻在 RT 为10分钟。</li>
	<li>添加6µL 200 毫米的水 TCEP (活性浓度 TCEP: 6 毫米) 和孵化在55° c 为 1 h, 以减少半胱氨酸 disulphides。</li>
	<li>添加3.5 µL 400 毫米水性 iaa (活性浓度 iaa: 6 mm), 在 RT 和黑暗中孵育30分钟至烷基化胱氨酸。</li>
	<li>准备等压标签套件 (e. g, 串联质量标签10plex 等压标签试剂)。允许等压标记试剂瓶在打开前达到 RT, 以避免不必要的试剂水化, 加入41µL 的 HPLC 级乙腈 (AcN), 用温和的搅拌溶解5分钟。</li>
	<li>将30µL 等压标签试剂溶液转移到相应的样品中, 并在温和搅拌下孵育1小时。等压标签试剂包括一个琥珀酰亚胺-酯基团, 它与在多肽 N 总站和赖氨酸残留物中存在的主要氨基酸反应。</li>
	<li>加8µL 5% 羟胺 (活性浓度羟胺: 0.16%), 在 RT 处轻轻摇动20分钟, 以熄灭标签反应。由于分开地被标记的样品将被结合, 保证标签反应被淬火。通过添加大量的胺类以羟胺的形式, 其余的等压标签试剂可以作出反应, 从而使惰性。</li>
	<li>结合每一个10单独标签的样品在一个单一的15毫升聚丙烯管的内容。</li>
	<li>将6.4 毫升的 de 电离水添加到组合样品和涡流中, 以减少 AcN 浓度从12% 到 3%, 到 GdnHCl 浓度 GdnHCl 到1米以下, 这是由于较高浓度, 有时会导致聚合物物质的浸出。从过滤器设备。</li>
</ol>4. 分子量切断过滤
<ol><li>为了去除潜在的污染物, 条件分子过滤器通过装载10毫升水 1 M GdnHCl, 25 毫米 TEAB 并且离心为 15 min 在 2500 x g 和 RT, 放弃流经 (FT)。</li>
	<li>在过滤器上加载整个样本量 (5 毫升无标签的 csf (步骤 2.5) 或10毫升压标记的 csf (步骤 3.9)), 并在 30 x g 和 RT 上离心2500分钟, 在集合容器中留出流量 (FT)。过滤的结果是多肽和小蛋白质分离从更大的蛋白质和残余细胞残骸。这一步可以被看作是 peptidomic 等同于使用蛋白水解蛋白质来产生肽在蛋白质组实验。</li>
	<li>负载5毫升的25毫米 TEAB (水) 的过滤器和离心机为15分钟, 2500 x g 和 RT, 以增加恢复肽。</li>
	<li>从前两个步骤 (总共10毫升的非标签或15毫升压标签的样本) 的组合罚球, 并进行样品酸化。</li>
</ol>5. 固相萃取--盐析和样品清理
<ol><li>酸化在固相萃取 (SPE) 之前从步骤4.4 中筛选出的样品。酸化是为了改善溶质 (肽) 相互作用与固定相的固相的 SPE 墨盒。</li>
	<li>对于无标签的样品 (容量10毫升): 添加550µL 1% 乙酸酸 (TFA)-样品总体积: 10.55 毫升与 0.05% TFA。</li>
	<li>为等压标记的样品 (容量15毫升): 增加20毫升 0.1% TFA 到酸化和更低的 AcN 集中从3% 到 1%-样品的总容量:30 毫升与 0.066% TFA。 注: TFA 还添加了它作为离子配对试剂的功能, 它可以提高多肽的保留能力, 而不能够与 SPE 墨盒的包装材料保持足够强的疏水作用。</li>
	<li>如果 ph > 3, 滴定样品与20% 磷酸, 直到样品 ph 值是 < 3。</li>
	<li>通过添加1毫升的 84% AcN, 0.1% 甲酸 (FA), 并放弃 FT. 重复一次。在随后的步骤中, 需要对滤筒过滤器进行调理, 以去除不需要的物质, 否则洗与肽一起;进一步, 调节增加过滤器的渗透性。</li>
	<li>平衡的 SPE 墨盒加1毫升的 0.1% TFA, 丢弃 FT. 重复一次。确保过滤器在最后一个平衡步骤后不会运行干燥-在过滤器的顶部保持一个小体积。为了使过滤器能够通过去除从调理步骤中留下的疏水物质 (乙腈) 来准备滤池以保持多肽的平衡。</li>
	<li>加载整个样本量 (10.55 毫升为非标签样本或30毫升压标签的样品), 在几个部分, 如果必要的, 让 FT 运行成废物。确保墨盒在取样加载轮或最后一个取样卷加载后不会运行干燥, 请在过滤器顶部保留一小卷。</li>
	<li>通过1毫升的 0.1% TFA 的过滤器, 以消除盐和试剂和丢弃的 FT. 重复一次。确保墨盒在每次洗涤步骤后不会运行干燥-在墨盒顶部保持少量液体。</li>
	<li>放置1.5 毫升低束缚微离心管下的墨盒和洗的样品通过1毫升 84% AcN, 0.1% FA 超过墨盒。</li>
	<li>在真空离心机中, 在干燥、贮存于-80 ° c 或立即进行高 pH 分馏时, 将溶剂从脱盐试样中蒸发。</li>
</ol>6. 离线高 pH 反相 HPLC 样品分离
<ol><li>
制备水基高 pH (HpH) 流动相: HpH 缓冲器 A: 纯净水 HpH 缓冲器 B: 84% AcN HpH 缓冲器 C:25 mM NH4哦 HpH 加载缓冲区: 2.5 mM NH4哦, 2% AcN 注意: HpH 加载缓冲区用作传输解决方案和示例缓冲区</li>
	<li>16µL HpH 加载缓冲液中的样品再溶解20分钟</li>
	<li>负载15µL 的样品的 HPLC 系统与内部分数收集器的 96-深井板配置根据 Batth et al.20 , 但有少量更改。分级在100µL/分钟的流量超过 pH 稳定的分离柱 (C18 3.5 µm, 2.1 毫米 x 250 毫米) 和收集一小部分每分钟在线性 60 min 梯度。</li>
	<li>使用以下渐变时间点: t = 0 分钟, B = 1%, C = 10%;t = 4 分钟, B = 1%, C = 10%, 开始分数集合;t = 76 分钟, B = 70%, C = 10%;结束分数收集;t = 76.5 分钟, B = 85%, C = 10%;t = 80 分钟, B = 85%, C = 10%;t = 80.5 分钟, b = 1%, c = 10% 和 t = 90 min, b = 1%, c = 10%。</li>
	<li>在12口井中重复地收集分数, 从而在一个圆的模式中, 使分数间隔12分钟, 产生12分, 每个分数包含6串联的子分数。</li>
	<li>在 RT 和 3000 rpm 之前, 用真空离心法除去样品中的溶剂, 直到干燥为止, 并在-80 ° c 之前将样品储存在 LC-质谱分析之前。</li>
</ol>7. LC-质谱
<ol><li>
准备水的流动阶段: 缓冲器 A: 0.1% FA 缓冲器 B: 0.1% FA, 84% AcN 装货缓冲: 0.05% TFA, 2% AcN 注: 装载缓冲器用作装载泵的传输方案、采样缓冲器和移动相位。</li>
	<li>通过增加6µL 加载缓冲器并在 RT 处晃动20分钟来重新溶解每个12馏分</li>
	<li>负载5µL 样品的纳米流高效液相色谱, 操作在陷井专栏配置 (陷井专栏:75 µm x 2 cm, C18, 100 Å孔大小, 3 µm 微粒大小; 分离专栏: C18, 75 µm x 500 毫米, 100 Å孔大小, 2 µm 微粒大小, 以 150 nL/分钟的流速进行多肽分离, 使用以下梯度: t = 0 min, B = 2%;t = 10 分钟, B = 2%;t = 11 分钟, B = 7%;t = 100 分钟, B = 26%;t = 170 分钟, B = 45%;t = 175 分钟, B = 80%;t = 181 分钟, b = 2%, t = 210 分钟, b = 2%。</li>
	<li>
在高分辨率混合质谱仪上, 通过纳米电喷雾界面进行高效液相色谱联用。在m/z范围 350-1400 的分辨率设置下, 以 MS 模式记录全扫描频谱 (2.0e5 AGC 目标) 12万。
	<ol>
<li>在数据相关的采集模式下操作质谱仪, 从前十最强峰值的m/z > 150, 并在1.0e4-1 的强度范围内选择 ms/毫秒谱. 0e5 用于片段离子分析。使用 1 m/z的四极隔离窗口隔离前体离子, 最大注射时间为100毫秒, RF 镜头在60%。</li>
		<li>将动态排除应用于十五年代的排除时间和± ppm 的m/z公差。在高碰撞能量分解 (HCD) 单元中执行碎片, 并在 orbitrap 的分辨率设置为 5万 (5.0e4 AGC 目标值) 记录 ms/ms 收购。</li>
	</ol>
</li>
</ol>8. 多肽识别
<ol><li>
为肽鉴定提交结果. 原始文件从质谱分析到蛋白质组学搜索引擎应用以下设置: 注: 在我们以前的研究中15, 三搜索引擎;吉祥物 v2.4, Sequest HT, 和峰值 v7.5 是并行使用, 这里指定的设置是为所有三搜索引擎, 除非另有规定。大多数可调节的设置是普遍的多肽/蛋白质识别和应该有相应的设置在任何给定的搜索引擎。 频谱选择器: 最小前体质量: 350 Da 最大.前体质量: 5000 Da 扫描类型: 完全 信号/噪声阈值: 1。5 序列数据库搜索 数据库: UniProt_SwissProt [version2015_11] 分类学: 智人 酶: 无 最大.错过分裂: 0 仪器 (仅吉祥物): ESI 陷阱 最小肽长度 (仅 SequestHT): 6 最大.多肽长度 (仅 SequestHT): 144 前体质量公差:15 ppm 碎片质量公差: 0.05 Da 静态修改: Carbamidomethyl (C);[如果标签]TMT10plex (N 期) 动态修改: 氧化 (M);[如果标签]TMT10plex (K) 多肽谱匹配 (PSM) 验证器 过滤 (仅限吉祥物和 Sequest) 或诱饵融合 (仅限峰值) 目标罗斯福: 0.01 基于: q 值的验证</li>
</ol>

<ol>
	<li>Wimo, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+worldwide+costs+of+dementia+2015+and+comparisons+with+2010.">The worldwide costs of dementia 2015 and comparisons with 2010.</a> Alzheimers Dement. 13 (1), 1-7 (2017).</li><li>Scheltens, P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Alzheimer's+disease.">Alzheimer's disease.</a> Lancet. 388 (10043), 505-517 (2016).</li><li>Dubois, B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Advancing+research+diagnostic+criteria+for+Alzheimer's+disease:+the+IWG-2+criteria.">Advancing research diagnostic criteria for Alzheimer's disease: the IWG-2 criteria.</a> Lancet Neurol. 13 (6), 614-629 (2014).</li><li>Olsson, B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=CSF+and+blood+biomarkers+for+the+diagnosis+of+Alzheimer's+disease:+a+systematic+review+and+meta-analysis.">CSF and blood biomarkers for the diagnosis of Alzheimer's disease: a systematic review and meta-analysis.</a> Lancet Neurol. 15 (7), 673-684 (2016).</li><li>Spellman, D. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Development+and+evaluation+of+a+multiplexed+mass+spectrometry+based+assay+for+measuring+candidate+peptide+biomarkers+in+Alzheimer's+Disease+Neuroimaging+Initiative+(ADNI)+CSF.">Development and evaluation of a multiplexed mass spectrometry based assay for measuring candidate peptide biomarkers in Alzheimer's Disease Neuroimaging Initiative (ADNI) CSF.</a> Proteomics Clin Appl. 9 (7-8), 715-731 (2015).</li><li>H&#246;glund, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Alzheimer's+disease&#8212;Recent+biomarker+developments+in+relation+to+updated+diagnostic+criteria.">Alzheimer's disease&#8212;Recent biomarker developments in relation to updated diagnostic criteria.</a> Clin Chim Acta. 449, 3-8 (2015).</li><li>Stark, M., Danielsson, O., Griffiths, W. J., Jornvall, H., Johansson, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Peptide+repertoire+of+human+cerebrospinal+fluid:+novel+proteolytic+fragments+of+neuroendocrine+proteins.">Peptide repertoire of human cerebrospinal fluid: novel proteolytic fragments of neuroendocrine proteins.</a> J Chromatogr B Biomed Sci Appl. 754 (2), 357-367 (2001).</li><li>Yuan, X., Desiderio, D. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Human+cerebrospinal+fluid+peptidomics.">Human cerebrospinal fluid peptidomics.</a> J Mass Spectrom. 40 (2), 176-181 (2005).</li><li>Berven, F. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Pre-analytical+influence+on+the+low+molecular+weight+cerebrospinal+fluid+proteome.">Pre-analytical influence on the low molecular weight cerebrospinal fluid proteome.</a> Proteomics Clin Appl. 1 (7), 699-711 (2007).</li><li>Zougman, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Integrated+analysis+of+the+cerebrospinal+fluid+peptidome+and+proteome.">Integrated analysis of the cerebrospinal fluid peptidome and proteome.</a> J Proteome Res. 7 (1), 386-399 (2008).</li><li>Holtta, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Peptidome+analysis+of+cerebrospinal+fluid+by+LC-MALDI+MS.">Peptidome analysis of cerebrospinal fluid by LC-MALDI MS.</a> PLoS One. 7 (8), e42555 (2012).</li><li>Holtta, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+integrated+workflow+for+multiplex+CSF+proteomics+and+peptidomics-identification+of+candidate+cerebrospinal+fluid+biomarkers+of+Alzheimer's+disease.">An integrated workflow for multiplex CSF proteomics and peptidomics-identification of candidate cerebrospinal fluid biomarkers of Alzheimer's disease.</a> J Proteome Res. 14 (2), 654-663 (2015).</li><li>Hansson, K. T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Expanding+the+cerebrospinal+fluid+endopeptidome.">Expanding the cerebrospinal fluid endopeptidome.</a> Proteomics. 17 (5), (2017).</li><li>Guldbrandsen, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In-depth+characterization+of+the+cerebrospinal+fluid+(CSF)+proteome+displayed+through+the+CSF+proteome+resource+(CSF-PR).">In-depth characterization of the cerebrospinal fluid (CSF) proteome displayed through the CSF proteome resource (CSF-PR).</a> Mol Cell Proteomics. 13 (11), 3152-3163 (2014).</li><li>Kroksveen, A. C., Opsahl, J. A., Aye, T. T., Ulvik, R. J., Berven, F. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Proteomics+of+human+cerebrospinal+fluid:+discovery+and+verification+of+biomarker+candidates+in+neurodegenerative+diseases+using+quantitative+proteomics.">Proteomics of human cerebrospinal fluid: discovery and verification of biomarker candidates in neurodegenerative diseases using quantitative proteomics.</a> J Proteomics. 74 (4), 371-388 (2011).</li><li>H&#246;ltt&#228;, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+single+dose+of+the+&#947;-secretase+inhibitor+semagacestat+alters+the+cerebrospinal+fluid+peptidome+in+humans.">A single dose of the &#947;-secretase inhibitor semagacestat alters the cerebrospinal fluid peptidome in humans.</a> Alzheimers Res Ther. 8 (1), 11 (2016).</li><li>Cao, Z., Tang, H. Y., Wang, H., Liu, Q., Speicher, D. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Systematic+Comparison+of+Fractionation+Methods+for+In-depth+Analysis+of+Plasma+Proteomes.">Systematic Comparison of Fractionation Methods for In-depth Analysis of Plasma Proteomes.</a> J Proteome Res. 11 (6), 3090-3100 (2012).</li><li>Chiu, C. W., Chang, C. L., Chen, S. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evaluation+of+peptide+fractionation+strategies+used+in+proteome+analysis.">Evaluation of peptide fractionation strategies used in proteome analysis.</a> J Sep Sci. 35 (23), 3293-3301 (2012).</li><li>Gilar, M., Olivova, P., Daly, A. E., Gebler, J. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Orthogonality+of+separation+in+two-dimensional+liquid+chromatography.">Orthogonality of separation in two-dimensional liquid chromatography.</a> Anal Chem. 77 (19), 6426-6434 (2005).</li><li>Batth, T. S., Francavilla, C., Olsen, J. V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Off-line+high-pH+reversed-phase+fractionation+for+in-depth+phosphoproteomics.">Off-line high-pH reversed-phase fractionation for in-depth phosphoproteomics.</a> J Proteome Res. 13 (12), 6176-6186 (2014).</li><li>Yang, F., Shen, Y., Camp, D. G., Smith, R. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-pH+reversed-phase+chromatography+with+fraction+concatenation+for+2D+proteomic+analysis.">High-pH reversed-phase chromatography with fraction concatenation for 2D proteomic analysis.</a> Expert Rev Proteomics. 9 (2), 129-134 (2012).</li><li>Blennow, K., Hampel, H., Weiner, M., Zetterberg, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cerebrospinal+fluid+and+plasma+biomarkers+in+Alzheimer+disease.">Cerebrospinal fluid and plasma biomarkers in Alzheimer disease.</a> Nat Rev Neurol. 6 (3), 131-144 (2010).</li><li>Moglich, A., Krieger, F., Kiefhaber, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Molecular+basis+for+the+effect+of+urea+and+guanidinium+chloride+on+the+dynamics+of+unfolded+polypeptide+chains.">Molecular basis for the effect of urea and guanidinium chloride on the dynamics of unfolded polypeptide chains.</a> J Mol Biol. 345 (1), 153-162 (2005).</li><li>Ho&#776;ltta&#776;, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+Integrated+Workflow+for+Multiplex+CSF+Proteomics+and+Peptidomics+Identification+of+Candidate+Cerebrospinal+Fluid+Biomarkers+of+Alzheimer&#8217;s+Disease.">An Integrated Workflow for Multiplex CSF Proteomics and Peptidomics Identification of Candidate Cerebrospinal Fluid Biomarkers of Alzheimer&#8217;s Disease.</a> J Proteome Res. 14 (2), 654-663 (2014).</li></ol>

在作者之间没有任何竞争的利益, 财务或其他, 报告。

采用高效液相色谱法预分馏步骤, 采用分子量超滤法回收内源性多肽11降低了相对样本复杂度, 从而使5倍大要研究的样本量。这反过来增加了每个分数中所含的肽子集的浓度, 从而提高了检测低丰肽的几率。
通过对三种蛋白质组软件并行使用的内源肽进行识别, 可以扩大已知的脑脊液 endopeptidome 超过10倍。共16395内源性多肽在一个合并脑脊液标本的初步试验中?...

脑脊液中的生物标志物目前正转化为神经退行性疾病的研究。在阿尔茨海默氏病, 最常见的神经退行性疾病, 影响超过6000万人的全球1,2, 一个生物标记三重组成的肽淀粉样β, 微管稳定蛋白 tau, 和磷酸化 tau 形态, 能检测出高灵敏度和特异性的疾病, 并已纳入诊断研究标准3。在其他神经退行性疾病, 如帕金森氏病和多发性硬化症, 蛋白质组研究发现了许多生物标记候选, 其中一些目前正在评估临床研究4,5 ,6。
除了蛋白质, CSF 还含有丰富的内源性多肽7,8,9,1011.这些肽构成了许多脑源性蛋白质的裂解产物, 同时也代表了一种潜在的重要的疾病生物标志物来源。为了增加人类脑脊液中已识别的内源性多肽的库存, 并在临床研究中进行 csf endopeptidomic 分析, 开发了用于样品制备和 LC-MS 分析的方法 (在图 1中包含了一个简短的协议方案).该方法在最近的一项研究中的应用, 导致了来自几个非特定诊断个体的汇集脑脊液样本中的近16400内源性脑脊液肽的鉴定, 扩大已知 csf endopeptidome 十倍13。该方法可选择与等压标签法结合使用, 以量化。
样品制备
脑脊液中蛋白质质量的主要来源是血浆成分 (如白蛋白和免疫球蛋白) 通过血脑屏障14,15。它们的高丰度阻碍了对低丰度脑源样件的检测。内源性肽可以很容易地与高丰度的蛋白质分离, 从而允许大量的脑脊液肽提取物用于 LC-MS 分析, 从而能够检测到低丰度的肽。
在这里提出的协议中, 分子量的分子过滤是用来分离脑脊液肽的蛋白质部分;已在以前的几项研究中使用的方法8、9、10、11、12、16。过滤步骤之后是一个离线反相高效液相色谱预分馏步骤, 在高 pH 移动相位梯度。通过串联两个反相 HPLC 步骤, 以 pH 值为主要区别, 两个步骤的选择性差异主要是由于不同的肽电荷状态而导致的多肽潴留。在酸性条件下, 高 pH 肽预分馏在 LC-MS 的应用在增加肽识别17,18, 甚至是在复杂生物的优势样品比较正交分离模式19, 如强 cat 离子交换 (SCX) 和 RP20。为了缩短分析时间, 使用了串联方案, 将每12个th分数 (例如、分数1、13、25、37和 49) 汇集在一起, 由于反相高效色谱法的高分辨力, 仍然很大程度上避免了不同的肽的共洗LC-MS 步骤20,21中的分数。
肽鉴定
peptidomic 研究中的肽鉴定与蛋白质组学研究不同, 因为在数据库搜索中不能指定酶解理, 因此, 识别率通常低于11。最近的一项研究13表明, Sequest 和吉祥物获得的内源性多肽的识别率在使用自适应评分法修改相应软件程序的默认评分算法时得到了显著改善算法过滤, 表明内源肽的最佳评分算法与胰肽13不同。在这项研究中, 基于自动肽从头测序使用软件峰值 (BSI) 被发现是互补的两个片段离子指纹为基础的搜索引擎, 导致了显着更大的一套识别肽.

<table><tbody><tr><td>&amp;nbsp;1 M Triethylammonium bicarbonate</td><td>Fluka, Sigma-Aldrich</td><td>17902-100ML</td><td>TEAB</td></tr><tr><td>&amp;nbsp;8 M Guanidinium hydrochloride</td><td>Sigma-Aldrich</td><td>G7294-100ML</td><td>GdnHCl</td></tr><tr><td>Tris(2-carboxyethyl)phosphine hydrochloride</td><td>Pierce</td><td>20490</td><td>TCEP</td></tr><tr><td>Iodoacetamide</td><td>SIGMA</td><td>I1149-5G</td><td>IAA</td></tr><tr><td>Hydroxylamine 50% (w/w)</td><td>Sigma-Aldrich</td><td>457804-50ML</td><td></td></tr><tr><td>Acetonitrile, Far UV, HPLC gradient grade</td><td>Sigma-Aldrich</td><td>271004-2L</td><td>AcN</td></tr><tr><td>Formic acid</td><td>Fluka, Sigma-Aldrich&amp;nbsp;</td><td>56302-1mL-F</td><td>FA</td></tr><tr><td>Triflouroacetic acid</td><td>Sigma-Aldrich</td><td>T6508-10AMP</td><td>TFA</td></tr><tr><td>Ammonium hydroxide solution</td><td>Sigma-Aldrich&amp;nbsp;</td><td>30501-1L-1M</td><td>NH&lt;sub&gt;4&lt;/sub&gt;OH</td></tr><tr><td>Amicon Ultra-15 Centrifugal Filter Unit with Ultracel-30 membrane</td><td>Merck Millipore</td><td>UFC903024</td><td>MWCO-filter</td></tr><tr><td>Sep-Pak C18, 100 mg</td><td>Waters</td><td>WAT023590</td><td>SPE-column</td></tr><tr><td>Resprep 12-port SPE Manifold&amp;nbsp;</td><td>Restek</td><td>26077</td><td>Vacuum manifold</td></tr><tr><td>TMT10plex Isobaric Label Reagent Set</td><td>Thermo Fisher Scientific</td><td>90110</td><td>TMT10plex</td></tr><tr><td>UltiMate 3000 RSLCnano LC System</td><td>Dionex</td><td>5200.0356</td><td>Online sample separation</td></tr><tr><td>Ultimate 3000 RPLC Rapid Separation Binary System</td><td>Dionex</td><td>IQLAAAGABHFAPBMBEZ</td><td>Offline high-pH fractionation</td></tr><tr><td>Orbitrap Fusion Tribrid mass spectrometer</td><td>Thermo Scientific</td><td>IQLAAEGAAPFADBMBCX</td><td>Mass spectrometer for sample analysis</td></tr><tr><td>Proteome Discoverer 2.0&amp;nbsp;</td><td>Thermo Fisher Scientific</td><td>IQLAAEGABSFAKJMAUH</td><td>Proteomics search platform</td></tr><tr><td>Mascot v2.4</td><td>Matrix Science</td><td>&amp;nbsp;-&amp;nbsp;</td><td>Proteomics search engine</td></tr><tr><td>Sequest HT</td><td>Thermo</td><td>&amp;nbsp;-&amp;nbsp;</td><td>Proteomics search engine</td></tr><tr><td>PEAKS v7.5&amp;nbsp;</td><td>Bioinformatic Solutions Inc.)</td><td>&amp;nbsp;-&amp;nbsp;</td><td>Proteomics search engine</td></tr><tr><td>Acclaim PepMap 100, 75 &amp;micro;m x 2 cm, C&lt;sub&gt;18&lt;/sub&gt;, 100 &amp;Aring; pore size, 3 &amp;micro;m particle size</td><td>Thermo Fisher Scientific</td><td>164535</td><td>Trap column (nano HPLC)</td></tr><tr><td>Acclaim PepMap C18, 75 &amp;micro;m x 500 mm, 100&amp;Aring; pore size,&amp;nbsp;2 &amp;micro;m particle size</td><td>Thermo Fisher Scientific</td><td>164942</td><td>Separation Column (nano HPLC)</td></tr><tr><td>Savant SpeedVac High Capacity Concentrators</td><td>Thermo Fisher Scientific</td><td>SC210A-230</td><td>SpeedVac/Vacuum concentrator</td></tr><tr><td>XBridge Peptide BEH C18 Column, 130&amp;Aring;, 3.5 &amp;micro;m, 2.1 mm X 250 mm</td><td>Waters</td><td>186003566</td><td>Separation Column (micro HPLC)</td></tr></tbody></table>

sample preparation for endopeptidomic analysis in human cerebrospinal fluid

本协议描述了一种用于识别人脑脊液中内源性多肽的方法。为此, 本文提出了一种基于分子量分子过滤和质谱分析的方法, 并结合离线高 pH 反相高效液相色谱预分馏步骤。
脑脊液分泌是去除中枢神经系统细胞分子的主要途径。因此, 中枢神经系统中的许多过程都反映在脑脊液中, 使它成为一种有价值的诊断液。CSF 有一个复杂的组成, 包含的蛋白质的浓度范围为 8-9 的数量级。除了蛋白质, 以前的研究还表明存在大量的内源性多肽。虽然不像蛋白质那样广泛研究, 但它们也可能作为生物标志物而具有潜在的兴趣。
内源性肽通过分子过滤与脑脊液蛋白含量分离。通过去除样品中的大多数蛋白质含量, 可以增加研究的样品体积, 从而也能提高内源性多肽的总量。在 LC-质谱分析之前, 通过在碱性 pH 值上采用反相 (RP) HPLC 预分馏步骤, 解决了过滤肽混合物的复杂性。分馏与一个简单的串联方案结合在一起, 其中60个分数被汇集到 12, 分析时间消耗量可以从而减少, 当仍然主要避免 co 洗脱。
通过使用三种不同的肽/蛋白质识别软件程序, 并结合结果进行了自动肽鉴定。不同的方案是互补的, 而不是可比的, 少于15% 的标识重叠之间的三。

本文介绍的方法已在三项研究中应用和评价前的样品前分馏 (表 1)。第一项研究使用离线 LC 在 MALDI 靶板上发现脑脊液分数, 并导致730已确定内源性肽11。在以下两项研究中, 使用了等压标签。主要在病例/对照研究中, 对 CSF endopeptidome 和蛋白质组中的潜在生物标志物进行鉴定和描述, 同时24, 并在第二项研究中使用等压标记用于监测治疗效果体内γ-分泌抑制?...

Watch this Scientific Journal Video about Sample Preparation for Endopeptidomic Analysis in Human Cerebrospinal Fluid at JoVE.com

Sample Preparation for Endopeptidomic Analysis in Human Cerebrospinal Fluid

提出了一种人脑脊液内源性多肽的质谱分析方法。通过采用分子量切断过滤、色谱预分馏、质谱分析以及随后的多肽识别策略组合, 就可以将已知的脑脊液 peptidome 扩大近十倍以前的研究。

人脑脊液 Endopeptidomic 分析的样品制备

This protocol describes a method developed to identify endogenous peptides in human cerebrospinal fluid (CSF). For this purpose, a previously developed ...

sample-preparation-for-endopeptidomic-analysis-human-cerebrospinal

Research

JoVE Journal

Neuroscience

8.9K 次观看.  Sahlgrenska Academy at University of Gothenburg. 提出了一种人脑脊液内源性多肽的质谱分析方法。通过采用分子量切断过滤、色谱预分馏、质谱分析以及随后的多肽识别策略组合, 就可以将已知的脑脊液 peptidome 扩大近十倍以前的研究。

视频: Sample Preparation for Endopeptidomic Analysis in Human Cerebrospinal Fluid

MALDI Imaging Mass Spectrometry of Neuropeptides in Parkinson's Disease

MALDI imaging mass spectrometry (IMS) is a powerful approach that facilitates the spatial analysis of molecular species in biological tissue samples2 (Fig.1). A 12 &mu;m thin tissue section is covered with a MALDI matrix, which facilitates desorption and ionization of intact peptides and proteins that can be detected with a mass analyzer, typically using a MALDI TOF/TOF mass spectrometer. Generally hundreds of peaks can be assessed in a single rat brain tissue section. In contrast to commonly used imaging techniques, this approach does not require prior knowledge of the molecules of interest and allows for unsupervised and comprehensive analysis of multiple molecular species while maintaining high molecular specificity and sensitivity2. Here we describe a MALDI IMS based approach for elucidating region-specific distribution profiles of neuropeptides in the rat brain of an animal model Parkinson's disease (PD). 
PD is a common neurodegenerative disease with a prevalence of 1% for people over 65 of age3,4. The most common symptomatic treatment is based on dopamine replacement using L-DOPA5. However this is accompanied by severe side effects including involuntary abnormal movements, termed L-DOPA-induced dyskinesias (LID)1,3,6. One of the most prominent molecular change in LID is an upregulation of the opioid precursor prodynorphin mRNA7. The dynorphin peptides modulate neurotransmission in brain areas that are essentially involved in movement control7,8. However, to date the exact opioid peptides that originate from processing of the neuropeptide precursor have not been characterized. Therefore, we utilized MALDI IMS in an animal model of experimental Parkinson's disease and L-DOPA induced dyskinesia. 
MALDI imaging mass spectrometry proved to be particularly advantageous with respect to neuropeptide characterization, since commonly used antibody based approaches targets known peptide sequences and previously observed post-translational modifications. By contrast MALDI IMS can unravel novel peptide processing products and thus reveal new molecular mechanisms of neuropeptide modulation of neuronal transmission. While the absolute amount of neuropeptides cannot be determined by MALDI IMS, the relative abundance of peptide ions can be delineated from the mass spectra, giving insights about changing levels in health and disease. In the examples presented here, the peak intensities of dynorphin B, alpha-neoendorphin and substance P were found to be significantly increased in the dorsolateral, but not the dorsomedial, striatum of animals with severe dyskinesia involving facial, trunk and orolingual muscles (Fig. 5). Furthermore, MALDI IMS revealed a correlation between dyskinesia severity and levels of des-tyrosine alpha-neoendorphin, representing a previously unknown mechanism of functional inactivation of dynorphins in the striatum as the removal of N-terminal tyrosine reduces the dynorphin's opioid-receptor binding capacity9. This is the first study on neuropeptide characterization in LID using MALDI IMS and the results highlight the potential of the technique for application in all fields of biomedical research.

Dopamine replacement pharmacotherapy using L-DOPA is the most commonly used symptomatic treatment of Parkinson&#x2019;s disease, but is accompanied by side effects including involuntary abnormal movements, termed dyskinesia 1. Here, a protocol for MALDI imaging mass spectrometry is presented that detects changes in rat brain neuropeptide levels related to dyskinesia.

MALDI成像帕金森病的神经肽质谱

MALDI imaging mass spectrometry (IMS) is a powerful approach that facilitates the spatial analysis of molecular species in biological tissue samples2 ...

科研

医学

Proteomic Profile of EPS-Urine through FASP Digestion and Data-Independent Analysis

Filter-aided sample protocol (FASP) is widely used for proteomics sample preparation because it allows to concentrate diluted samples and it is compatible with a wide variety of detergents. Bottom-up proteomics workflows like FASP increasingly rely on LC-MS/MS methods performed in data-independent analysis (DIA) mode, a scanning method that allows deep proteome coverage and low incidence of missing values. 
In this report, we will provide the details of a workflow that combines a FASP protocol, a double StageTip purification step and LC-MS/MS in DIA mode for urinary proteome mapping. As a model sample, we analyzed expressed prostatic secretions (EPS)-urine, a sample collected after a digital rectal exam (DRE), which is of interest in prostate cancer biomarker discovery studies.

Here, we present an optimized on-filter digestion protocol with detailed information about the following: protein digestion, peptide purification and data independent acquisition analysis. This strategy is applied to the analysis of expressed prostatic secretions-urine samples and allows high proteome coverage and low missing value label-free profiling of the urinary proteome.

通过 FASP 消化和数据独立分析，EPS-尿液的蛋白质配置文件

Filter-aided sample protocol (FASP) is widely used for proteomics sample preparation because it allows to concentrate diluted samples and it is compatible ...

生物化学

Consensus Brain-derived Protein, Extraction Protocol for the Study of Human and Murine Brain Proteome Using Both 2D-DIGE and Mini 2DE Immunoblotting

Two-dimensional gel electrophoresis (2DE) is a powerful tool to uncover proteome modifications potentially related to different physiological or pathological conditions. Basically, this technique is based on the separation of proteins according to their isoelectric point in a first step, and secondly according to their molecular weights by SDS polyacrylamide gel electrophoresis (SDS-PAGE). In this report an optimized sample preparation protocol for little amount of human post-mortem and mouse brain tissue is described. This method enables to perform both two-dimensional fluorescence difference gel electrophoresis (2D-DIGE) and mini 2DE immunoblotting. The combination of these approaches allows one to not only find new proteins and/or protein modifications in their expression thanks to its compatibility with mass spectrometry detection, but also a new insight into markers validation. Thus, mini-2DE coupled to western blotting permits to identify and validate post-translational modifications, proteins catabolism and provides a qualitative comparison among different conditions and/or treatments. Herein, we provide a method to study components of protein aggregates found in AD and Lewy body dementia such as the amyloid-beta peptide and the alpha-synuclein. Our method can thus be adapted for the analysis of the proteome and insoluble proteins extract from human brain tissue and mice models too. In parallel, it may provide useful information for the study of molecular and cellular pathways involved in neurodegenerative diseases as well as potential novel biomarkers and therapeutic targets.

A common protein extraction protocol using urea/thiourea/SDS buffer for human and mice brain tissue allows indentification of proteins by 2D-DIGE and their subsequent characterization by mini 2DE immunoblotting. This method enables one to obtain more reproducible and reliable results from human biopsies and experimental models.

共识脑源性蛋白，人类和小鼠脑蛋白质组使用两个2D-DIGE和Mini双向电泳免疫印迹法研究提取协议

Two-dimensional gel electrophoresis (2DE) is a powerful tool to uncover proteome modifications potentially related to different physiological or ...

神经科学

Multi-Faceted Mass Spectrometric Investigation of Neuropeptides in Callinectes sapidus

Neuropeptides are signaling molecules that regulate almost all physiological and behavioral processes, such as development, reproduction, food intake, and response to external stressors. Yet, the biochemical mechanisms and full complement of neuropeptides and their functional roles remain poorly understood. Characterization of these endogenous peptides is hindered by the immense diversity within this class of signaling molecules. Additionally, neuropeptides are bioactive at concentrations 100x - 1000x lower than that of neurotransmitters and are prone to enzymatic degradation after synaptic release. Mass spectrometry (MS) is a highly sensitive analytical tool that can identify, quantify, and localize analytes without comprehensive a priori knowledge. It is well-suited for globally profiling neuropeptides and aiding in the discovery of novel peptides. Due to the low abundance and high chemical diversity of this class of peptides, several sample preparation methods, MS acquisition parameters, and data analysis strategies have been adapted from proteomics techniques to allow optimal neuropeptide characterization. Here, methods are described for isolating neuropeptides from complex biological tissues for sequence characterization, quantitation, and localization using liquid chromatography (LC)-MS and matrix-assisted laser desorption/ionization (MALDI)-MS. A protocol for preparing a neuropeptide database from the blue crab, Callinectes sapidus, an organism without comprehensive genomic information, is included. These workflows can be adapted to study other classes of endogenous peptides in different species using a variety of instruments.

Multi-Faceted Mass Spectrometric Investigation of Neuropeptides in Callinectes sapidus

Mass spectrometric characterization of neuropeptides provides sequence, quantitation, and localization information. This optimized workflow is not only useful for neuropeptide studies, but also other endogenous peptides. The protocols provided here describe sample preparation, MS acquisition, MS analysis, and database generation of neuropeptides using LC-ESI-MS, MALDI-MS spotting, and MALDI-MS imaging.

卡利内克特氏菌中神经肽的多方面质谱研究

Neuropeptides are signaling molecules that regulate almost all physiological and behavioral processes, such as development, reproduction, food intake, and ...

化学

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 ...

A High Throughput, Multiplexed and Targeted Proteomic CSF Assay to Quantify Neurodegenerative Biomarkers and Apolipoprotein E Isoforms Status

Many neurodegenerative diseases are&#160;still lacking effective treatments. Reliable biomarkers for identifying and classifying these diseases will be important in the development of future novel therapies. Often&#160;potential new biomarkers do not make it&#160;into the clinic&#160;due to limitations&#160;in their development and&#160;high costs.&#160;However,&#160;targeted proteomics using Multiple Reaction Monitoring Liquid Chromatography-tandem/Mass Spectrometry (MRM LC-MS/MS), specifically using triple quadrupole mass spectrometers, is one method that can be used to rapidly evaluate and validate biomarkers&#160;for clinical translation into diagnostic laboratories. Traditionally, this platform has been used extensively for measurement of small molecules&#160;in clinical laboratories, but it is the potential to analyze proteins, that makes it an attractive alternative to ELISA (Enzyme-Linked Immunosorbent Assay)-based methods. We describe here how targeted proteomics can be used to measure multiplexed markers of dementia, including the detection and quantitation of the known risk factor apolipoprotein E isoform 4 (ApoE4).
In order to make the assay suitable for translation, it is designed to be rapid, simple, highly specific and cost effective. To achieve this, every step in the development of the assay must be optimized for the individual proteins and tissues they are analyzed in. This method describes a typical workflow including various tips and tricks to developing a targeted proteomics MRM LC-MS/MS for translation.
The method development is optimized using custom synthesized versions of tryptic quantotypic peptides, which calibrate&#160;the MS for detection and then spiked into CSF to determine correct identification of the endogenous peptide in the chromatographic separation prior to analysis in the MS. To achieve absolute quantitation, stable isotope-labeled internal standard versions of the peptides with short amino acid sequence tags and containing a trypsin cleavage site, are included in the assay.

We describe a high-throughput, multiplex, and targeted proteomic cerebrospinal fluid (CSF) assay developed with potential for clinical translation. The test can quantitate potential markers and risk factors for neurodegeneration, such as the apolipoprotein E variants (E2, E3 and E4), and measure their allelic expression.

高通量，复用和有针对性的蛋白质组学分析脑脊液量化神经退行性生物标志物和载脂蛋白E亚型状态

Many neurodegenerative diseases are&#160;still lacking effective treatments. Reliable biomarkers for identifying and classifying these diseases will be ...

Proteomic Sample Preparation from Formalin Fixed and Paraffin Embedded Tissue

Preserved clinical material is a unique source for proteomic investigation of human disorders. Here we describe an optimized protocol allowing large scale quantitative analysis of formalin fixed and paraffin embedded (FFPE) tissue. The procedure comprises four distinct steps. The first one is the preparation of sections from the FFPE material and microdissection of cells of interest. In the second step the isolated cells are lysed and processed using 'filter aided sample preparation' (FASP) technique. In this step, proteins are depleted from reagents used for the sample lysis and are digested in two-steps using endoproteinase LysC and trypsin. 
After each digestion, the peptides are collected in separate fractions and their content is determined using a highly sensitive fluorescence measurement. Finally, the peptides are fractionated on 'pipette-tip' microcolumns. The LysC-peptides are separated into 4 fractions whereas the tryptic peptides are separated into 2 fractions. In this way prepared samples allow analysis of proteomes from minute amounts of material to a depth of 10,000 proteins. Thus, the described workflow is a powerful technique for studying diseases in a system-wide-fashion as well as for identification of potential biomarkers and drug targets.

Archival formalin fixed and paraffin embedded (FFPE) clinical samples are valuable material for investigation of diseases. Here we demonstrate a sample preparation workflow allowing in-depth proteomic analysis of microdissected FFPE tissue.

修正了福尔马林蛋白质组学样品的制备和石蜡包埋组织

Preserved clinical material is a unique source for proteomic investigation of human disorders. Here we describe an optimized protocol allowing large scale ...

生物学

Biochemical Purification and Proteomic Characterization of Amyloid Fibril Cores from the Brain

Proteinaceous fibrillar inclusions are key pathological hallmarks of multiple neurodegenerative diseases. In the early stages of Alzheimer&#39;s disease (AD), amyloid-beta peptides form protofibrils in the extracellular space, which act as seeds that gradually grow and mature into large amyloid plaques. Despite this basic understanding, current knowledge of the amyloid fibril structure, composition, and deposition patterns in the brain is limited. One major barrier has been the inability to isolate highly purified amyloid fibrils from brain extracts. Affinity purification and laser capture microdissection-based approaches have been previously used to isolate amyloids but are limited by the small quantity of material that can be recovered. This novel, robust protocol describes the biochemical purification of amyloid plaque cores using sodium dodecyl sulfate (SDS) solubilization with sucrose density gradient ultracentrifugation and ultrasonication and yields highly pure fibrils from AD patients and AD model brain tissues. Mass spectrometry (MS)-based bottom-up proteomic analysis of the purified material represents a robust strategy to identify nearly all the primary protein components of amyloid fibrils. Previous proteomic studies of proteins in the amyloid coronae have revealed an unexpectedly large and functionally diverse collection of proteins. Notably, after refining the purification strategy, the number of co-purifying proteins was reduced by more than 10-fold, indicating the high purity of the isolated SDS insoluble material. Negative staining and immuno-gold electron microscopy allowed confirmation of the purity of these preparations. Further studies are required to understand the spatial and biological attributes that contribute to the deposition of these proteins into amyloid inclusions. Taken together, this analytical strategy is well-positioned to increase the understanding of amyloid biology.

This biochemical purification method with mass spectrometry-based proteomic analysis facilitates the robust characterization of amyloid fibril cores, which may accelerate the identification of targets for preventing Alzheimer's disease.

来自大脑的淀粉样原纤维核心的生化纯化和蛋白质组学表征

Proteinaceous fibrillar inclusions are key pathological hallmarks of multiple neurodegenerative diseases. In the early stages of Alzheimer&#39;s disease ...

<meta charset="utf8"></head><body>从最小组织中高效分离脑 sEVs 以发现生物标志物

Harnessing the Power of MicroRNA Cargoes in Small Extracellular Vesicles Released from Fresh-Frozen Human Brain Sections

Small extracellular vesicles (sEVs) are crucial mediators of cell-cell communication, transporting diverse cargoes like proteins, lipids, and nucleic acids (microRNA, mRNA, DNA). The microRNA sEV cargo has potential utility as a powerful non-invasive disease biomarker due to sEV&#39;s ability to traverse biological barriers (e.g., blood-brain barrier) and become accessible through various body fluids. Despite numerous studies on sEV biomarkers in body fluids, identifying tissue or cell-specific sEV subpopulations remains challenging, particularly from the brain. Our study addresses this challenge by adapting existing methods to isolate sEVs from minimal amounts of frozen human brain sections using size exclusion chromatography (SEC).
After ethical approval, approximately 250 &#181;g of fresh-frozen human brain tissue (obtained from Manchester Brain Bank [UK]) was sliced from the 3 donor tissues and incubated in collagenase type 3/Hibernate-E solution, with intermediate agitation, followed by serial centrifugation and filtration steps. Then, sEVs were isolated using the SEC method and characterized by following MISEV guidelines. Before isolating RNA from within these sEVs, the solution was treated with Proteinase-K and RNase-A to remove any non-sEV extracellular RNA. The RNA quantity and quality were checked and processed further for qPCR and small RNA sequencing experiments.
The presence of sEVs was confirmed through fluorescence nanoparticle tracking analysis (fNTA) and western blot for surface markers (CD9, CD63, CD81). Size distribution (50-200 nm) was confirmed by NTA and electron microscopy. The total RNA concentration within lysed sEVs ranged from 3-9 ng/&#181;L and was used for successful quantification by qPCR for selected candidate microRNAs. Small RNA sequencing on MiSeq provided high-quality data (Q &#62;32) with 1.4-5 million reads per sample.
This method enables efficient isolation and characterization of sEVs from minimal brain tissue volumes, facilitating non-invasive biomarker research and holds promise for equitable disease biomarker studies, offering insights into neurodegenerative diseases and potentially other disorders.

<meta charset="utf8"></head><body>利用 MicroRNA 货物在新鲜冷冻人脑切片释放的小细胞外囊泡中的力量

Here, we establish a protocol using minimal amounts of fresh-frozen brain tissue sections and an accessible high-speed centrifugation method coupled with size exclusion chromatography to obtain small extracellular vesicles as sources for microRNA (miRNA) biomarkers for neurological disorders.

利用 MicroRNA 货物在新鲜冷冻人脑切片释放的小细胞外囊泡中的力量 

Small extracellular vesicles (sEVs) are crucial mediators of cell-cell communication, transporting diverse cargoes like proteins, lipids, and nucleic ...

人脑脊液 Endopeptidomic 分析的样品制备

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MALDI成像帕金森病的神经肽质谱

通过 FASP 消化和数据独立分析，EPS-尿液的蛋白质配置文件

共识脑源性蛋白，人类和小鼠脑蛋白质组使用两个2D-DIGE和Mini双向电泳免疫印迹法研究提取协议

卡利内克特氏菌中神经肽的多方面质谱研究

鼠脑区的高分辨率定量突触蛋白质双向听觉辨别学习后

高通量，复用和有针对性的蛋白质组学分析脑脊液量化神经退行性生物标志物和载脂蛋白E亚型状态

修正了福尔马林蛋白质组学样品的制备和石蜡包埋组织

来自大脑的淀粉样原纤维核心的生化纯化和蛋白质组学表征

利用 MicroRNA 货物在新鲜冷冻人脑切片释放的小细胞外囊泡中的力量

利用 MicroRNA 货物在新鲜冷冻人脑切片释放的小细胞外囊泡中的力量