MathJax.Hub.Config({tex2jax: {inlineMath: [['$','$'], ['\\(','\\)']]}}); 高分辨质谱数据MDF技术的进展
  天津中医药  2016, Vol. 33 Issue (12): 765-768

文章信息

侯艳婷, 王晓明, 张家伟, 潘桂湘
HOU Yan-ting, WANG Xiao-ming, ZHANG Jia-wei, PAN Gui-xiang
高分辨质谱数据MDF技术的进展
Advance of mass defect filter technique by high-resolution mass spectrometry
天津中医药, 2016, 33(12): 765-768
Tianjin Journal of Traditional Chinese Medicine, 2016, 33(12): 765-768
http://dx.doi.org/10.11656/j.issn.1672-1519.2016.12.16

文章历史

收稿日期: 2016-05-01
高分辨质谱数据MDF技术的进展
侯艳婷1,2, 王晓明1, 张家伟1,2, 潘桂湘1     
1. 天津中医药大学, 天津市现代中药重点实验室(培育), 天津 300193;
2. 天津国际生物医药联合研究院, 天津 300457
摘要: 近年来,质谱在药物鉴定中的应用日益广泛,许多质谱采集及数据挖掘技术,如全信息串联质谱(MSE)扫描、提取离子流技术、中性丢失过滤技术、产物离子过滤技术等,也相应得到较大程度的开发和发展。其中一种基于高分辨质谱数据的过滤技术--质量亏损过滤技术(MDF),根据代谢物与原形药物具有相近的质量亏损这一规律,对采集的高分辨质谱数据进行处理和识别,通过一次或有限几次进样可从复杂背景中发现和鉴定药物及其代谢产物,显现出独特的优势。
关键词: 质量亏损过滤     代谢物鉴定     中药成分鉴定    

三重四极杆(QQQ)、线性离子阱(LTQ),四极杆-线性离子阱(Q-trap)、四极杆-飞行时间(Q-TOF)等液质联用仪,在代谢物鉴定中有较多的应用[1-3]。对于可预测或已知生物转化反应的代谢产物,可采用中性丢失、前体离子和多反应监测(MRM)等扫描方式,或利用提取离子流(EIC)方法等,靶向分析代谢产物;但对于非常规或多步生物转化反应形成的代谢产物,尤其当存在大量内源性化合物干扰时,上述鉴定策略存在较大的局限[4-5]

质量亏损是指某一元素(或化合物)的精确质量数与它最接近的整数值之间的差异[6]。2003年Zhang等[7]发现代谢物与原型药物小数部分的精确质量数变化范围不大,质量亏损通常在几十个毫道尔顿之内,例如羟基化的质量亏损是-5 mu,脱氢是-16 mu,脱甲基化是-23 mu,葡萄糖醛酸结合是+ 32 mu,硫酸化是-43 mu,谷胱甘肽结合(GSH)是68 mu,代谢产物质量亏损均在可预测范围内[8],据此提出了基于高分辨质谱数据的质量亏损过滤技术(MDF)。与代谢物类似,中药具有母核结构相同而取代基稍有不同的类似物,它们经羟基化、甲基化、甲氧基化、糖基取代或结合反应而成,与母体化合物的质量亏损差异不大。因此,在代谢物和中药结构类似物鉴定过程中,可以通过设定质量亏损范围,利用MDF技术对采集的高分辨质谱数据进行处理和识别,从复杂背景中筛选已知或未知的代谢产物/中药结构类似物,发挥其独特的技术优势。

1 常规MDF技术

常规MDF技术,根据母体药物与核心亚结构的质量亏损,估计代谢产物的质量亏损落在什么区间,预先设定过滤标准,在全扫描质谱数据集中提取代谢产物离子,排除所有落在期望范围之外的离子,从而在复杂生物基质中快速挖掘出可能的代谢产物[9]。它无需考虑代谢产物不同的裂解类型,而主要考虑代谢产物与过滤模板之间质量亏损的相似性。

MDF的筛选模板主要分为4类[10]:1)适用于质量、结构与母体相似的代谢物,例如发生氧化、还原、脱烷基(<50 mu)等反应,使母体化合物加上或减去一个或几个C/H/O/N等。2)适用于母体裂分产生的小分子化合物,如水解反应。3)适用于母体化合物加合产生的大分子化合物,如结合型代谢物;4)适用于脱卤代谢物,即母体化合物脱去一个或多个卤素。其中模板1)、2)、4)涉及母体产生的氧化、还原、水解反应,3)主要为母体的结合反应。

MDF技术早期应用于体内血液、尿液、胆汁、粪便[11-14]中代谢物的检测。为了印证MDF技术在代谢物检测方面的有效应性,有学者开展了代谢轮廓谱分析,结果显示MDF技术确实能够在复杂基质中筛选出目标化合物,但其在尿液中的检测结果较血液、胆汁、粪便稍差[12]。随着时间的推移,该技术拓展应用到组织样品如肝微粒体、肠菌和中药结构类似物的鉴定[15-19]。Morales-Gutierrez[20]利用MDF技术,检测沙氟沙星、恩诺沙星、环丙沙星、双福沙星在pH改变、反复冻融等处理条件下的物质转化,及其在鸡肉肌肉组织中代谢物。最终鉴定了恩诺沙星21个转化物,环丙沙星6个转化物,双福沙星14个转化物,沙氟沙星12个转化物,以及它们在肌肉组织的14个代谢产物。王广基等[21]利用MDF技术,选取麦冬皂苷和麦冬高异黄酮为模板,对麦冬提取物进行数据挖掘,鉴定了50个麦冬皂苷类和27个麦冬高异黄酮类化合物。

但常规MDF技术由于只选择单一的母体化合物为模板,其质量亏损范围设置较宽,常导致筛选结果偏差大,干扰性化合物多。随着数据挖掘技术的发展,学者们在常规MDF技术基础上开发了一些新型的MDF技术。

2 多重MDF技术(MMDF)

MMDF技术,选取多个化合物为模板,分别对各类型的化合物进行筛选。相较于常规MDF,它可以在有限的进样次数中,筛选出更多的代谢物或同系物。屠鹏飞等[22]利用MMDF技术,选取去氧五味子素的原型及其4个代谢物为模板,对大鼠尿液和粪便中的代谢物进行检测,共鉴定了51个代谢产物,其中49个为Ⅰ相代谢产物,2个为Ⅱ相代谢产物。Qian Ruan等[23]采用MMDF技术,选取噻氯匹定-谷胱甘肽加合物、脱氯噻氯匹定-谷胱甘肽加合物、氯苯甲醛-谷胱甘肽加合物、四氢化噻吩并吡啶-谷胱甘肽加合物为模板,对噻氯匹定经大鼠肝微粒体孵育后与谷胱甘肽结合的产物进行检测,共筛选出17个与谷胱甘肽结合的代谢产物,确定了噻氯匹定体外的代谢途径。

3 逐级MDF技术(stepwise MDF)

逐级MDF技术,通过确定不同取代基化合物的母体结构,以及取代基的数量,选取多个质量亏损过滤窗口或多个质量范围,可以筛选出更多的化合物。张加余[24]总结了黄酮类化合物结构规律,确定黄酮分子量范围为282~436 Da,取代基最高为5个甲基,最低为5个羟基,从而设置质量亏损范围为70 mu至166 mu,利用逐级MDF技术,分五段对柑橘中的多甲氧基黄酮进行筛选,共鉴定出81个成分,较常规MDF技术(鉴定30多个成分)检出了更多的化合物。德国学者Macherius[25],利用逐级MDF技术对辣根酱中三氯生代谢物进行检测,成功筛选出了33个化合物。

4 线性梯度MDF技术(linear gradient MDF)

线性梯度MDF技术,以多个化合物为模板,用曲线连接各模板化合物的质量数,形成一个动态质量过滤曲线,将曲线两端平行延长50 Da,质量亏损值设为一定的区间范围,则认为分子量落在这一区域内的化合物可能是代谢物或结构类似物(见图 1)。该技术利用Waters公司UPLC/Q-TOF-MS的MSE扫描模式进行数据采集,然后采用Metabolynx XS软件中的MDF工具对数据进行处理。王喜军等[26]利用线性梯度MDF技术,对茵陈四逆汤中的乌头类生物碱进行检测,以Songorine、Senbusine A、Hypaconitine 3个化合物为模板,将质量亏损范围设定在-38mu到23 mu之间,共筛选识别145个化合物,通过假阳性筛选剔除55个化合物,通过元素分析和质谱裂解规律剔除27个化合物,最终鉴定了62个乌头类生物碱;而采用传统的气质或液质方法,只能鉴定出15个乌头类生物碱。

图 1 线性梯度MDF概图 Fig. 1 Schematic of linear gradient MDF
5 五点筛查MDF技术(five-point screening MDF)

五点筛查MDF技术,将MDF与数学中的边界理论[27]相结合,以5个化合物(a、b、c、d、e)为模板,连接五个点,确定筛选范围(见图 2),它使筛选结果不再是一个开放的空间,理论上能够将其他干扰类型的化合物排除在外。五点的选择原则如下:a点为分子量最低的化合物;b、c点为小的取代基连接小的糖配基的化合物,b、c两点相连确定质量亏损的下界限;d、e点为大的取代基连接大的糖配基的化合物,d、e两点相连确定质量亏损的上界限;上下界限斜率与取代基的数量和种类相关。李萍等[28]采用五点筛查MDF技术,选取最小质量数的B7型人参皂苷为a点,3个氧(负贡献最小)取代的齐墩果酸型皂苷为b点,5个木糖(正贡献第二大)3个二甲酰基(正贡献最小)取代的齐墩果酸型皂苷为c点,7个鼠李糖取代(正贡献最大)的去氢A1型人参皂苷为d点,1个鼠李糖取代的去氢A1型人参皂苷为e点,五点顺次连接确定皂苷类化合物的筛选范围及边界斜率,结合诊断离子分析和视觉同位素技术,共鉴定了三七中234个皂苷类成分,其中67个为潜在的新化合物。

图 2 五点筛查MDF概图 Fig. 2 Schematic of five-point screening MDF
6 MDF技术与其他数据挖掘技术的整合

将MDF技术与提取离子流(EIC)、子离子过滤(PIF)、中性丢失过滤(NLF)、同位素过滤(IPF)、诊断碎片离子(DFI)等数据挖掘技术整合,串联或并联使用,可增加复杂生物基质样品中微量代谢物检测的灵敏度和选择性。姚新生等[29]将MDF技术与EIC相结合,鉴定大鼠口服参松养心后的入血成分,成功检测出92个外源性成分,其中45个为原型药物,47个为代谢产物。RuanQ[8]将MDF技术和EIC/ NLF/PIF相结合,对大鼠肝S9孵育液中茚地那韦的代谢物进行鉴定,共检测出15个代谢产物,其中2个为新发现的代谢产物。Tian[30]将MDF技术和DFI相结合,对马钱子中二氢吲哚类生物碱进行鉴定,先采用MDF技术减少背景噪音,然后利用DFI确定化合物的结构,对于无法确证的同分异构体5和11,辅以量子化学计算法,确定其分别为2-羟基-3-甲氧基士的宁和4-羟基-3-甲氧基士的宁。

7 展望

MDF技术可以通过设定质量亏损范围,从复杂背景中筛选出代谢物或中药结构类似物,操作简便。随着多种优化技术[31]的出现,以及与其他数据挖掘技术的结合,相信MDF的鉴定结果可靠性将不断提高,得到更加广泛的应用。

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Advance of mass defect filter technique by high-resolution mass spectrometry
HOU Yan-ting1,2, WANG Xiao-ming1, ZHANG Jia-wei1,2, PAN Gui-xiang1     
1. Tianjin State Key Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China;
2. Tianjin International Joint Academy of Biotechnology and Medicine, Tianjin 300457, China
Abstract: In recent years, with the development of the high resolution mass spectrometry, its application in medical field has expanded, followed by the development and exploitation of the related data mining techniques of mass spectrometry, such as extract ion chromatography technology, neutral lost filtering technology, and product ion filtering technology.In all of those methods, a novel date filtering technology, the mass defect filter (MDF) which is produced by processing and identifying the collected dates according to the similarity mass defect between prototype drugs and its metabolites can select and identify drug and its metabolites from complex matrix via once or limited injection.And it had shown greatest advantage in this field.
Key words: mass defect filter     metabolites identification     traditional Chinese medicine ingredient identification