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基于质谱的磷酸化蛋白质组学:富集、检测、鉴定和定量
石文昊1,2 , 童梦莎1,2 , 李恺1 , 王钰珅1,2 , 丁琛1,3     
1. 国家蛋白质科学中心(北京),北京蛋白质组研究中心,蛋白质组学国家重点实验室,北京 102206;
2. 清华大学生命科学学院,北京 100084;
3. 复旦大学生命科学学院,上海 200438
摘要: 磷酸化是一种调控生命活动的重要翻译后修饰,调控生物的生长发育、信号转导、以及疾病的发生发展.从上世纪80年代开始,质谱应用于蛋白质磷酸化的检测中,极大地推动了磷酸化蛋白质组学的发展.质谱检测拥有高灵敏度、高通量的特点,更重要的是具有位点分辨率,因此基于质谱的磷酸化蛋白质组检测方法得到不断的发展和推广.常见的磷酸化蛋白质组研究,首先对磷酸化肽段进行富集,然后进行串联质谱分析,最后通过搜索引擎对修饰位点进行鉴定和定量.本文从这个三个基本方面,对磷酸化蛋白质组研究进行综述,并对未来研究发展方向进行讨论.
关键词: 磷酸化蛋白质组学     方法     串联质谱     修饰位点解析    
Phosphoproteomics Based on Mass Spectrometry(MS): Enrichment, Detection, Assignment and Quantification
SHI Wen-Hao1,2 , TONG Meng-Sha1,2 , LI Kai1 , WANG Yu-Shen1,2 , DING Chen1,3     
1. State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (The PHOENIX Center, Beijing), Beijing 102206, China;
2. School of Life Sciences, Fudan University, Shanghai 200438, China;
3. School of Life Sciences, Tsinghua University, Beijing 100084, China
*This work was supported by grants from National Key R & D Program of China (2017YFA0505102) and The National Natural Science Foundation of China (31770886, 31770892, 31700682)
** Corresponding author: DING Chen, Tel: 021-31240741, E-mail: chend@fudan.edu.cn
Received: November 11, 2018 Accepted: December 11, 2018
Abstract: Protein phosphorylation is one of post-translational modifications (PTM), which plays a role in regulation of development, signal transduction, and processes of diseases. Because of high sensitivity, considerable throughput, and residue resolution, mass spectrometry (MS) has been the most popular tool for phosphorylation modification analysis. Common MS-centric phosphoproteomics workflow includes phosphorylation modified peptides sampling, LC-MS/MS detection, phosphorylation sites assignment and quantification. We summarized and discussed these workflow parts in this review.
Key words: phosphoproteomics     methodology     LC-MS/MS     confident phosphosite assignment    

蛋白质翻译后修饰(post-translational modification,PTM)可以改变蛋白质结构和活性、介导细胞信号转导,细胞对外界环境刺激的响应往往通过PTM实现.PTM类型众多,包括磷酸化[1]、乙酰化[2]、泛素化和糖基化[3]等.在众多类型的PTM中,磷酸化是最受关注的[4].磷酸化修饰是一种可逆的蛋白质修饰,通过磷酸化修饰的变化,可以调控蛋白质活性、影响信号传递过程.磷酸化修饰是细胞健康和疾病的核心调控机制之一,依靠众多种类激酶和磷酸酶,细胞可以迅速地增加或减少蛋白质的磷酸化修饰,实现复杂而精确地调控[5-7].真核生物中,约有1/3的蛋白质具有磷酸化修饰,这也体现了磷酸化修饰的普遍性和重要性.

磷酸化蛋白质组学在过去20年间发展迅速,多种生命过程都用磷酸化蛋白质组进行了描绘.如对细胞周期的磷酸化解析[8]、不同小鼠组织磷酸化差异谱图[9]、胰岛素分泌机制[10]等.此外,磷酸化蛋白质组研究应用于多种临床问题研究[11-12],推动了人们对疾病发病机制的认知,并提供了一系列临床疾病治疗靶点和治疗方案.比如通过外泌体中蛋白质磷酸化筛选乳腺癌生物标志物[13]、通过小鼠脑不同区域G蛋白偶联受体(G protein-coupled receptor,GPCR)的激活研究药效和药靶[14]等.

基于质谱的自下而上(down-top)的蛋白质组研究方法是常见的解析磷酸化蛋白质组方法[15-17],该方法通过磷酸化肽段富集,液质联用检测和数据解析,构建磷酸化蛋白质组数据集(图 1)[18].以下从这三个方面对磷酸化蛋白质组研究进行综述和讨论.

Fig. 1 Workflow for phosphoproteomics 图 1 磷酸化蛋白质组学研究流程
1 磷酸化肽段的富集

磷酸化修饰肽段的丰度相对整体细胞而言是很低的,直接地全覆盖质谱检测,非磷酸化的肽段会形成很高的背景信号,影响磷酸化肽段的检测[19-20].因此磷酸化肽段的检测,首先需要进行富集.此外,对样品进行预分离、分成多个组分,也是降低复杂程度、提高检测深度的常用方法[19].

1.1 富集方法分类

磷酸化肽段的富集方法,是整个实验流程中最多变的部分[21].磷酸基团与金属亲和的方案是最流行的方案,其中应用最广泛的两种是固相金属离子亲和色谱(immobilized metal affinity chromatograph,IMAC)和金属氧化物亲和色谱(metal oxide affinity chromatography,MOAC)[21-22].IMAC建立时间约有20年,利用过渡态金属阳离子,如Fe3+、Ga3+、Zr4+等,作为亲和试剂,与阴离子结合[23-25].Ti4+离子是该类试剂中新兴的应用[26].这些金属阳离子通过螯合作用,固定在具有磁性的磁珠或硅颗粒上,从而在去除非磷酸化肽段的过程中能够保留磷酸化的肽段. MOAC方法建立约10年,利用氧化金属可以和磷酸根基团中的氧结合的特性进行磷酸化肽段的富集.氧化钛(TiOx)是最常用的MOAC试剂,此外Fe3O4也比较常见[27-28].

IMAC和MOAC方法都可以对磷酸化肽段或者蛋白质进行富集,二者都容易受到酸性肽段影响,比如多羧基集团的肽段会发生非特异性结合[29].IMAC所得样品容易含有金属离子或者金属盐的污染,需要进行脱盐处理.并且IMAC方法对多磷酸化修饰的肽段具有偏好性,容易丢失单磷酸化修饰的肽段.和IMAC相比,MOAC方法灵敏度更高、选择性更好.由于金属氧化物具有很好的稳定性,因此IMAC方法对pH值等环境因素的改变具有更好的耐受.

IMAC和MOAC方法都是针对丝氨酸、苏氨酸和酪氨酸的磷酸化修饰位点(pSer、pThr、pTyr)进行富集的方法.Matheron等[30]2014年比较了两种方法对HeLa细胞中的磷酸化富集,发现只有40%磷酸化肽段是重合的.不过,在肽段长度、位点和模序(motif)等方面,二者并没有明显的不同.最重要的是,生物学的差异,而不是方法上的差异,对结果起到最主要的影响.

免疫共沉淀方法,是专门用于富集酪氨酸磷酸化的主流方法,结合了基于金属的富集方法和基于抗体的富集方法中的优势[31-32],该方法能够高特异性的对酪氨酸磷酸化位点进行富集.目前,针对酪氨酸的特异性抗体正在不断涌现[33-34].

1.2 富集方法的发展

肽段的检测深度依赖于酶解效率、传统的胰酶(trypsin)酶解,能够在赖氨酸和精氨酸的C末端进行剪切[35].但通过对不同酶的比较,发现两种不同酶的酶切后,检测到的磷酸化位点只有1/3的重合[36],这说明不同酶酶切后检测到的位点不同.利用多种酶共同作用,可以提高酶切效率,提升检测的覆盖深度[37].比如利用LysC和胰蛋白酶(trypsin)共同酶解,可以提高40%的磷酸化检测位点[38].

预分离也是提高鉴定深度的方法.反向液相预分离(reversed phase liquid chromatograph,RPLC)是常用的分组分方法,此外还有强阳离子交换(strong cation exchange,SCX)和强阴离子交换(strong anion exchange,SAX)方法[21].Ruprecht等[39]在比较不同富集方法时发现,通过亲水强阴离子交换预分离,48 h的检测可以获得15 000条磷酸化肽段,要比4 h检测5 500条磷酸化肽段的鉴定深度有所提高.此外,覆盖度的提升,使得数据间的相关性明显提升.强离子交换方法可以和TiOx富集方法结合,但是还没有和抗体富集方法结合的例子[40].

Batth等[41]在2014年比较了SCX和RPLC分组分方法,发现RPLC方法能够鉴定到更多的磷酸化肽段,RPLC方法鉴定到17 566条磷酸化肽段,SCX方法鉴定到6 215条肽段.并且RPLC方法实验流程更加简便,不用额外替换溶液环境.

也有一些亲和方法,用于富集磷酸化的蛋白质而非肽段.因为蛋白质常以复合物形式行使功能,因此该方法能够鉴定细胞中复合物的情况.如Hoehenwarter等[42]利用Al(OH)3富集促细胞分裂剂激活的蛋白激酶.目前,该领域还在持续发展过程.

2 基于串联质谱的磷酸化肽段检测 2.1 质谱仪的发展

磷酸化蛋白质组数据的可重复性和可信度依赖于质谱仪的扫描速度和灵敏度,近年来几乎所有的磷酸化蛋白质组检测都是采用串联质谱(MS/MS),其中包括qTOF、LIT-Orbitrap、quadrupole-Orbitrap和FTICR质谱等[43-46].应用较多的Orbitrap Fusion,扫描频率达22 Hz,快速的扫描能够增加检测深度和检测通量[47].Erickson等[48]利用Orbitrap Fusion和多同位素标记策略,在10种样品中鉴定到11 000个磷酸化位点.扫描速度的提升,使得样品检测机时大幅减少,从一周缩短为两天.另一种仪器类型Q-Exactive HF,能够通过分段4级杆精确选择母离子,提升子离子的谱图质量,对磷酸化修饰的鉴定有所帮助,不过这需要牺牲一定的扫描速度.Olsen研究组[49]报道,利用RPLC和Q-Exactive HF能够从HeLa细胞样品中鉴定到7 600种特异性磷酸化肽段(unique peptide).

2.2 质谱数据获取方法

蛋白质组通常采用的数据获取方式是数据依赖型采集方法(data-dependent acquisition,DDA),该方法能够自动选择母离子并进行碎裂检测.通常该方法选择丰度较高的母离子,忽略了丰度较低的磷酸化肽段.近年来逐渐发展的数据非依赖采集方案(data-independent acquisition,DIA),将检测范围设置成不同的质荷比范围(比如SWATH,sequential windowed acquisition of all theoretical fragment ions),理论上能够检测所有的离子[50].对DDA和DIA进行比较,发现DIA方法能够提高检测的灵敏度5~10倍[50].不过该方法造成数据量增加,数据复杂度提高,谱图解析更加困难.DDA、DIA和靶向检测方法各有优势,灵活使用能够更加高效地检测磷酸化肽段[51-52],如2012年Narumi等[53]在乳腺癌样本中利用DDA进行了全蛋白质检测,同时利用靶向检测方法鉴定生物标志物.

2.3 碎裂方式的选择

利用质谱进行磷酸化修饰等翻译后修饰的检测,原因之一是其具有位点分辨率.但是在实际应用过程中,因为对位点的评估不能满足可信度要求,约有20%~40%的磷酸化肽段数据不可用[21].对磷酸化修饰的质控,往往是以磷酸化肽段的子离子为核心,因此母离子碎裂方式在磷酸化位点检测中至关重要.

常用的碰撞活化解离(collisional activation dissociation,CAD)碎裂模式虽然方法简便,但是容易引起位点重排、N末端附近修饰位点中性丢失增加等问题[54-55].电子转移解离(electron transfer dissociation,ETD)是逐渐成熟起来的应用于磷酸化蛋白质组检测中的碎裂方法[55-56].该方法可以有效保留肽段骨架信息和磷酸化修饰信息,不过当母离子电荷低时,碎裂效率会降低.2012年,Heck实验室[57-58]提出EThcD方法.这种方法与高能碰撞解离(high energy collision dissociation,HCD)相比,鉴定的磷酸化肽段数目会有所降低,但序列覆盖度和位点鉴定比例高于HCD和ETD.

负电模式检测可能是磷酸化蛋白质组的另一个维度.因为磷酸化修饰上带负电,使其更易去质子化,形成阴离子[59-60].因此在碎裂过程中,对形成的阴离子检测,或许更能帮助解析高通量的磷酸化蛋白质组问题.

3 磷酸化修饰的鉴定和定量 3.1 磷酸化修饰定量方法

磷酸化蛋白质组的定量,与普通蛋白质组定量不同.同一个蛋白质不同位点,可能具有不同的磷酸化水平,因此定量是需要直接检测磷酸化肽段、基于位点的定量.对于肽段的定量方法也有很多种,根据是否具有同位素标记,可以分为有标定量和无标定量(表 1).

Table 1 Comparison of different quantitative strategies 表 1 肽段的定量策略

有标定量是已经活跃了近20年的定量方法,包括氨基酸细胞培养基稳定同位素标记(stable isotope labeling with amino acids in cell culture,SILAC)方法[61]、用于相对和绝对定量的胺修饰标记(amine-modifying tags for relative and absolute quantification,TRAQ)方法[62]以及二甲基标记方法[63]等.这些方法可以满足多个样品具有不同标记,因此样品可以混合成单针进行检测,节省机时,降低实验误差.以上都是一级定量所使用的标记方法,与此同时,也有很多成熟的二级定量的标记方法,如串联质谱标签(tandem mass tag,TMT)[64]、相对和绝对定量同位素标记(isobaric tags for relative and absolute quantitation,iTRAQ)[65],能够同时定量6~11个样品.不过这种定量方式覆盖深度会受到影响.有标定量的一个突出的限制是信号压缩效应,分配到一起的母离子,比值差异可能会被压缩到不显著.

近年来也不断涌现了很多新的标记方法.比如Xue等[66]在2014年先将肽段全部去掉磷酸化,然后体外用18O-ATP作为原料,在特定激酶作用下肽段发生磷酸化修饰,修饰位点具有18O修饰.该方法可以研究激酶直接的作用底物.

无标定量没有同位素标记,是一种相对定量方法,该方法以其费用低、灵活性强、易于实验设计等优点受到欢迎[67].虽然该方法不能将样品混合,消耗检测机时会更多,但前期样品准备简单,易于进行预分离,仍成为使用最广泛的方法.无标定量的挑战还是在数据获取后的分析中,Skyline[68]和MaxQuant[69]等已经发展出比较成熟的磷酸化定量方法.此外MaxQuant提出match between runs的思路尝试解决磷酸化检测中常出现的空值问题,虽然这一方法有可能引入更多的不确定性.

3.2 磷酸化位点的质控

在一次质谱鉴定中能够可靠的鉴定数千种被修饰的肽段,但是对PTM位点的定位识别仍然较为武断,对于某些修饰位点的鉴定可信度低.因此在处理PTM质谱数据时,有必要对修饰位点进行错误定位率(false localization rate,FLR)的控制[70].

对于含有两个相同的氨基酸残基的离子碎片,需要通过特定离子类型的鉴定才能明确的分辨出肽段的具体位点.该规则在修饰位点的可靠性鉴定上看起来很简单,但是对于实际谱图来说,需要考虑的因素非常复杂,如质谱中的噪音信号、磷酸化修饰中未修饰片段的中性丢失、与修饰后的氨基酸具有相同质荷比的氨基酸的区别等.

常用的质量可靠性算法包含两类[71]:第一类是基于概率来对鉴定质量进行打分,通常使用统计学模型实现;第二类是基于假阳性率的算法,通常使用Target-Decoy[72]方法实现(表 2).对于PTM来说,错误定位率没有较好的实现方法[73],通常是通过合成肽段来评估[74],对仅包含一个修饰位点的肽段才有较好的效果[75].

Table 2 Quality control strategies of modification sites 表 2 修饰位点定位质量控制的主流工具对比

目前绝大多数位点定位软件或者算法所采用的策略主要分为两种[71]:一种是试图评估某个给定峰匹配到特定位点的概率,采用这种策略的包括A-Score[76]、PTM Score (MaxQuant / Andromeda) [69]、the PLS(phosphorylation localization score) in Inspect[77]、SLoMo[78]、Phosphinator[79]与PhosphoRS[80]等;另一种策略是计算两个修饰位点间搜索引擎给出的打分差值,采用这种策略的包括Mascot Delta Score[74]、the SLIP score in Protein Prospector[71]与the VML(variable modification localization) score in Spectrum Mill [Agilent].

A-Score与PTM Score主要是基于峰值匹配概率的原理.这种算法的核心之处在于先找出定位待评估的两个位点之间的离子,然后分别计算两个修饰位点的离子峰匹配到离子的个数,计算累计二项分布的p值和位点的打分值,最后计算两个修饰位点的打分差值从而判断该肽段的修饰位点.

另一种基于搜索引擎打分差值的策略如Mascot Delta Score,其计算为最高的Mascot ion scores与次高的Mascot ion scores的差值.Bernhard Kuster等[74]的研究工作显示MD-score的敏感性与特异性与A-score类似.他们评估的位点来源于人工合成的180条位点已知的磷酸化肽段.此外,MD-score在酪氨酸位点的定位控制中准确性优于A-score.目前Mascot2.4版本以上的搜库结果可以直接给出位点质量打分,在MD-score计算中不需要另外增加工作流,且计算原理简单实用,而A-score是基于Sequest搜库结果计算的.因此如果搜库软件使用Mascot,可以直接选用MD-score打分.

值得注意的是,A-Score和MD-score都只给出打分最高的位点,而忽略打分次高的位点,而PTM Score (MaxQuant / Andromeda)则对每一个位点都给出了概率打分.The SLIP score in Protein Prospector与the VML score则给出了符合阈值的所有位点的打分.

4 展望与讨论

翻译后修饰调节对生理病理过程影响巨大,不论是正常生理过程,还是癌症中的异常信号转导[81]、神经退行性疾病中的细胞毒性蛋白质聚集等,都与蛋白质的翻译后修饰相关[4-5].磷酸化是研究最广泛的蛋白质翻译后修饰.常见的磷酸化蛋白质组研究,首先对磷酸化肽段进行富集,然后进行串联质谱分析,最后通过搜索引擎对修饰位点进行鉴定和定量[21].基于质谱的蛋白质组学近年来不断发展,已经广泛应用于疾病解析、药物靶点筛选和临床检测等过程[82].应用质谱,可以对磷酸化蛋白质组进行高通量、高效率、深度覆盖的检测.

丝氨酸、苏氨酸和酪氨酸的磷酸化是研究最广泛的磷酸化修饰,这些都是O-磷酸化修饰.本文也是重点关注上述三种磷酸化修饰.此外,还有N-磷酸化修饰(赖氨酸、精氨酸和组氨酸)[83]和S-磷酸化修饰(半胱氨酸)[5].Potel等[84]2018年优化了组氨酸磷酸化修饰方法,利用Fe3+-IMAC柱富集肽段后检测,在大肠杆菌中鉴定到240个具有组氨酸修饰的蛋白质.酪氨酸和组氨酸的磷酸化鉴定数目较少,但是人们发现这些特殊的磷酸化修饰具有重要的生物学功能[34],因此对于酪氨酸和组氨酸的磷酸化修饰方法或在未来具有较大突破.

为了更多地鉴定到磷酸化肽段,人们常常对肽段进行预分离.通过不断的实践,人们逐渐认识到,耗费大量的检测时间对覆盖深度的贡献是有限的.随着技术的进步,单针的检测能够达到很深的覆盖度.在数小时的检测中,单针能够鉴定15 000~20 000个磷酸化位点.同时,单针检测具有更好的重复性,更短的数据分析时间.因此,磷酸化蛋白质组的检测向单针检测方向发展.

质谱检测技术的发展极大地推动了磷酸化蛋白质组研究的进步.人们通过提高质谱扫描速度,优化数据采集模式、母离子碎裂方式,不断提高磷酸化蛋白质组数据的覆盖度和样品检测效率.不论是蛋白质鉴定、翻译后修饰检测,还是蛋白质组数据集的构建,质谱检测技术都是必不可少的.基于质谱的磷酸化蛋白质组学目前面临的主要问题是数据之间的重复性问题.技术重复之间的磷酸化肽段重合约为60%~75%.在追求高效、降低数据复杂度的单针检测时代,怎样获得高可重复度的数据是需要解决的主要问题.

翻译后修饰位点质量打分软件的发展与进步,使得磷酸化蛋白质组数据具有更高的一致性与可信度.基于搜索引擎打分的方法充分考虑了肽段质量的准确性且可以直接在搜库过程中获得,因此更加可靠与便捷.目前最常用的打分软件是MD-score、PTM Score(MaxQuant / Andromeda)与A-score[75].在选择这些软件的过程中,要综合考虑质谱平台检测的类型,搜库算法和软件的便捷性,从而为后续的分析提供较为可靠的磷酸化位点.近年来人们提出一站式蛋白质组大数据分析平台构想,以磷酸化为代表的翻译后修饰数据的定性和定量,都是这些数据分析平台的重点工作之一[85-86].

磷酸化蛋白质组作为逐渐兴起的多组学研究中的重要一环,与蛋白质组、乙酰化、泛素化、甲基化等其他翻译后修饰组学共同整合,从而综合解析生命活动.在一些研究中,蛋白质磷酸化被认为是动植物生命活动核心调控机制,比如节律调控[87]、泛素化的调控[88]和植物的生长发育[89]等.相信基于质谱的磷酸化蛋白质组学,在未来可以解析更多分子机制、致病机理,发现更多临床应用.

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中国科学院生物物理研究所和中国生物物理学会共同主办
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文章信息

石文昊, 童梦莎, 李恺, 王钰珅, 丁琛
SHI Wen-Hao, TONG Meng-Sha, LI Kai, WANG Yu-Shen, DING Chen
基于质谱的磷酸化蛋白质组学:富集、检测、鉴定和定量
Phosphoproteomics Based on Mass Spectrometry(MS): Enrichment, Detection, Assignment and Quantification
生物化学与生物物理进展, 2018, 45(12): 1250-1258
Progress in Biochemistry and Biophysics, 2018, 45(12): 1250-1258
http://dx.doi.org/10.16476/j.pibb.2018.0292

文章历史

收稿日期: 2018-11-11
接受日期: 2018-12-11

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