Article(id=1308455370507187136, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1308455335962894804, articleNumber=null, orderNo=null, doi=10.16438/j.0513-4870.2024-1299, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1735315200000, receivedDateStr=2024-12-28, revisedDate=1746633600000, revisedDateStr=2025-05-08, acceptedDate=null, acceptedDateStr=null, onlineDate=1789889670254, onlineDateStr=2026-09-20, pubDate=1749657600000, pubDateStr=2025-06-12, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1789889670254, onlineIssueDateStr=2026-09-20, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1789889670254, creator=13701087609, updateTime=1789889670254, updator=13701087609, issue=Issue{id=1308455335962894804, tenantId=1146029695717560320, journalId=1189982191388893191, year='2025', volume='60', issue='6', pageStart='1573', pageEnd='1964', issueExtLink='null', onlineDate='null', pubDate='1749657600000', pubDateStr='2025-06-12', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1789889662017, creator='13701087609', updateTime=1789893590327, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1308471812564734358, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1308455335962894804, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1308471812564734359, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1308455335962894804, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1641, endPage=1653, ext={EN=ArticleExt(id=1308455370704319425, articleId=1308455370507187136, tenantId=1146029695717560320, journalId=1189982191388893191, language=EN, title=Recent advances for spatial distribution on endogenous small molecule metabolites and drug spatial dynamics in central nervous system diseases using mass spectrometry imaging, columnId=1190335348648547107, journalTitle=Acta Pharmaceutica Sinica, columnName=Reviews, runingTitle=null, highlight=null, articleAbstract=

The endogenous small molecule metabolites (such as neurotransmitters, fatty acids, carbohydrates, nucleotides, and amino acids) in the body played an important role in the development and progression of central nervous system diseases. With the emergence of precision medicine, an increasing demand for the precise localization and precise analysis of those metabolites, as well as a clearer understanding of their biological functions was presented. Mass spectrometry imaging (MSI) technology, a non-invasive in vivo imaging technique, could provide an accurate spatial distribution, and the concentrations of endogenous metabolites or pharmaceutical components in different organs. There were many advantages including no specific labeling, short duration, and wide detection range. Matrix-assisted laser desorption/ionization mass spectrometry imaging played a leading role in the study of the precise distribution of endogenous metabolites in the brain microregions of disease animal model such as Parkinson's disease, Alzheimer's disease, stroke, and insomnia. In addition, it was widely applied to study the distribution of central nervous system drugs in the brain microregions. This review systematically examines the fundamental principles underlying MSI and its groundbreaking technological innovations over the past decade.

, authors=Yu TAO1, Chen-hui DU2, Jia-ying LIU1, Xue-mei QIN1, Rui-ping ZHANG3, *, Yan YAN1, *, authorsList=Yu TAO, Chen-hui DU, Jia-ying LIU, Xue-mei QIN, Rui-ping ZHANG, Yan YAN, authorCompany=null, correspAuthors=Rui-ping ZHANG, Yan YAN, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright ©2025 Acta Pharmaceutica Sinica. All rights reserved., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1308455371631260616, articleId=1308455370507187136, tenantId=1146029695717560320, journalId=1189982191388893191, language=CN, title=基于质谱成像的中枢神经系统疾病内源性小分子代谢物与药物空间动力学研究进展, columnId=1190335349655180086, journalTitle=药学学报, columnName=综述, runingTitle=null, highlight=null, articleAbstract=

内源性小分子代谢物(如神经递质类、脂肪酸、糖类、核苷酸和氨基酸类) 在中枢神经系统疾病的发生和发展过程中发挥着重要作用。随着精准医学的提出, 越来越要求对内源性小分子代谢物精准定位与精准分析, 且明确其生物学功能。质谱成像技术是一种可直观反映药物作用部位内源性代谢物、药源性成分的精准空间分布及其器官浓度显著差异的原位成像技术, 具有无需特异性标记、时间短、检测范围广等特点。基质辅助激光解吸电离质谱成像作为主流质谱成像, 已经开始在神经退行性疾病(帕金森病、阿尔茨海默病、脑卒中和失眠等) 内源性小分子代谢物的脑微区精准分布进行研究, 并在中枢神经系统药物脑微区分布的研究中发挥引领性作用。本文简要介绍了质谱成像技术的基本原理和重要技术进展, 并着重讨论了近10年中枢神经系统疾病涉及的内源性小分子代谢物, 以及治疗药物脑微区的空间分布研究进展。

, authors=陶宇1, 杜晨晖2, 刘嘉颖1, 秦雪梅1, 张瑞平3, *, 闫艳1, *, authorsList=陶宇, 杜晨晖, 刘嘉颖, 秦雪梅, 张瑞平, 闫艳, authorCompany=null, correspAuthors=张瑞平, 闫艳, authorNote=

作者贡献:

陶宇负责文献总结和文章初稿撰写; 杜晨晖负责文章的审阅; 刘嘉颖负责文献收集与整理; 秦雪梅、张瑞平负责文章写作思路设计; 闫艳负责文章的写作与修正。

, correspAuthorsNote=
闫艳, E-mail:
张瑞平, E-mail:
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COMT: Catechol-O-methyltransferase; ADH1_7: Alcohol dehydrogenase 1/7; CTX: Cerebral cortex; Str: Striatum; BF: Basal forebrain; Cg: Cingulate cortex; Spr: Septal region; VMA: Vanillylmandelic acid; DOMA: 3, 4-Dihydroxymandellic acid; MOPEG: 3-Methoxy-4-hydroxyphenylethyleneglycol; NMN: Normetanephrine; E: Epinephrine; DOPEG: Dihydroxyphenylethyleneglycol; MOPEGAL: 3-Methoxy-4-hydroxyphenylglycolaldehyde; DOPEGAL: 3, 4-Dihydroxyphenylglycolaldehyde; DOPAL: 3, 4-Dihydroxyphenylacetaldehyde; DOPAC: 3, 4-Dihydroxyphenylacetic acid; MOPAL: 3-Methoxy-4-hydroxyphenylacetaldehyde, reprinted with permission from reference[15]. 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No.Derivatization reagentAnalyte
12-Fluoro-1-methylpyridine (FMP)5-HT, GABA, L-DOPA, DA, 5-HIAA and HVA[15]
22, 4, 6-Trimethylpyrylium tetrafluoroborate (TMP-TFB)GABA, DA, L-DOPA, glycine[18, 19]
31, 4-Phenylene-4, 4'-bis (2, 6-diphenyl-4-pyrylium) (PBDPP)
42-(4-Bromophenyl)-4, 6-diphenylpyranylium (Br-TPP)DA, GABA, taurine[20]
52, 4, 6-Triphenylpyrylium tetrafluoroborate (TPP-TFB)
62, 3-Diphenylpyranotetrafluoroboric acid (DPP-TFB)5-HT, GABA, 3-MT, DA, aspartate, alanine, valine, tyrosine, lysine, proline[21, 22]
72, 4-Diphenylpyran (DPP)5-HT, DA, NE[23]
84-Hydroxy-3-methoxycinnamaldehyde (CA)GABA, DA, L-DOPA, glycine, alanine, valine, tyrosine[24]
9p-(N, N, N-Trimethylammonio) benzamidyl N'-hydroxysuccinimidyl formate iodide (TAHS)GABA, DA, Glu, glycine, alanine, aspartate, tryptophan, tyrosine[21, 25]
), ArticleFig(id=1308497490912052203, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1308455370507187136, language=CN, label=Tab.1, caption=

The derivatization reactions reagents of neurotransmitters and amino acid metabolites. GABA: Gamma-aminobutyric acid; DA: Dopamine; 5-HT: 5-Hydroxytryptamine; Glu: Glutamate; 3-MT: 3-Methoxytyramine; NE: Norepinephrine; 5-HIAA: 5-Hydroxyindole acetic acid; HVA: Homovanillic acid; L-DOPA: 3, 4-Dihydroxyphenyl L-alanine

, figureFileSmall=null, figureFileBig=null, tableContent=
No.Derivatization reagentAnalyte
12-Fluoro-1-methylpyridine (FMP)5-HT, GABA, L-DOPA, DA, 5-HIAA and HVA[15]
22, 4, 6-Trimethylpyrylium tetrafluoroborate (TMP-TFB)GABA, DA, L-DOPA, glycine[18, 19]
31, 4-Phenylene-4, 4'-bis (2, 6-diphenyl-4-pyrylium) (PBDPP)
42-(4-Bromophenyl)-4, 6-diphenylpyranylium (Br-TPP)DA, GABA, taurine[20]
52, 4, 6-Triphenylpyrylium tetrafluoroborate (TPP-TFB)
62, 3-Diphenylpyranotetrafluoroboric acid (DPP-TFB)5-HT, GABA, 3-MT, DA, aspartate, alanine, valine, tyrosine, lysine, proline[21, 22]
72, 4-Diphenylpyran (DPP)5-HT, DA, NE[23]
84-Hydroxy-3-methoxycinnamaldehyde (CA)GABA, DA, L-DOPA, glycine, alanine, valine, tyrosine[24]
9p-(N, N, N-Trimethylammonio) benzamidyl N'-hydroxysuccinimidyl formate iodide (TAHS)GABA, DA, Glu, glycine, alanine, aspartate, tryptophan, tyrosine[21, 25]
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基于质谱成像的中枢神经系统疾病内源性小分子代谢物与药物空间动力学研究进展
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陶宇 1 , 杜晨晖 2 , 刘嘉颖 1 , 秦雪梅 1 , 张瑞平 3, * , 闫艳 1, *
药学学报 | 综述 2025,60(6): 1641-1653
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药学学报 |综述 2025 , 60 (6) : 1641 -1653
基于质谱成像的中枢神经系统疾病内源性小分子代谢物与药物空间动力学研究进展
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陶宇1, 杜晨晖2, 刘嘉颖1, 秦雪梅1, 张瑞平3, * , 闫艳1, *
作者信息
  • 1山西大学中医药现代研究中心, 山西 太原 030006
  • 2山西中医药大学中药与食品工程学院, 山西 太原 030619
  • 3山西医科大学附属山西省人民医院放射科, 山西 太原 030001
通讯作者:
闫艳, E-mail:
张瑞平, E-mail:
作者简介:

作者贡献:

陶宇负责文献总结和文章初稿撰写; 杜晨晖负责文章的审阅; 刘嘉颖负责文献收集与整理; 秦雪梅、张瑞平负责文章写作思路设计; 闫艳负责文章的写作与修正。

Recent advances for spatial distribution on endogenous small molecule metabolites and drug spatial dynamics in central nervous system diseases using mass spectrometry imaging
Yu TAO1, Chen-hui DU2, Jia-ying LIU1, Xue-mei QIN1, Rui-ping ZHANG3, * , Yan YAN1, *
Affiliations
  • 1Modern Research Center of Traditional Chinese Medicine, Shanxi University, Taiyuan 030006, China
  • 2Institute of Pharmaceutical & Food Engineering, Shanxi University of Traditional Chinese Medicine, Taiyuan 030619, China
  • 3The Radiology Department of Shanxi Provincial People's Hospital Affiliated to Shanxi Medical University, Taiyuan 030001, China
出版时间: 2025-06-12 doi: 10.16438/j.0513-4870.2024-1299
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内源性小分子代谢物(如神经递质类、脂肪酸、糖类、核苷酸和氨基酸类) 在中枢神经系统疾病的发生和发展过程中发挥着重要作用。随着精准医学的提出, 越来越要求对内源性小分子代谢物精准定位与精准分析, 且明确其生物学功能。质谱成像技术是一种可直观反映药物作用部位内源性代谢物、药源性成分的精准空间分布及其器官浓度显著差异的原位成像技术, 具有无需特异性标记、时间短、检测范围广等特点。基质辅助激光解吸电离质谱成像作为主流质谱成像, 已经开始在神经退行性疾病(帕金森病、阿尔茨海默病、脑卒中和失眠等) 内源性小分子代谢物的脑微区精准分布进行研究, 并在中枢神经系统药物脑微区分布的研究中发挥引领性作用。本文简要介绍了质谱成像技术的基本原理和重要技术进展, 并着重讨论了近10年中枢神经系统疾病涉及的内源性小分子代谢物, 以及治疗药物脑微区的空间分布研究进展。

质谱成像  /  中枢神经系统疾病  /  脑微区  /  内源性小分子代谢物  /  空间分布

The endogenous small molecule metabolites (such as neurotransmitters, fatty acids, carbohydrates, nucleotides, and amino acids) in the body played an important role in the development and progression of central nervous system diseases. With the emergence of precision medicine, an increasing demand for the precise localization and precise analysis of those metabolites, as well as a clearer understanding of their biological functions was presented. Mass spectrometry imaging (MSI) technology, a non-invasive in vivo imaging technique, could provide an accurate spatial distribution, and the concentrations of endogenous metabolites or pharmaceutical components in different organs. There were many advantages including no specific labeling, short duration, and wide detection range. Matrix-assisted laser desorption/ionization mass spectrometry imaging played a leading role in the study of the precise distribution of endogenous metabolites in the brain microregions of disease animal model such as Parkinson's disease, Alzheimer's disease, stroke, and insomnia. In addition, it was widely applied to study the distribution of central nervous system drugs in the brain microregions. This review systematically examines the fundamental principles underlying MSI and its groundbreaking technological innovations over the past decade.

mass spectrometry imaging  /  central nervous system disease  /  brain microregion  /  endogenous metabolite  /  spatial distribution
陶宇, 杜晨晖, 刘嘉颖, 秦雪梅, 张瑞平, 闫艳. 基于质谱成像的中枢神经系统疾病内源性小分子代谢物与药物空间动力学研究进展. 药学学报, 2025 , 60 (6) : 1641 -1653 . DOI: 10.16438/j.0513-4870.2024-1299
Yu TAO, Chen-hui DU, Jia-ying LIU, Xue-mei QIN, Rui-ping ZHANG, Yan YAN. Recent advances for spatial distribution on endogenous small molecule metabolites and drug spatial dynamics in central nervous system diseases using mass spectrometry imaging[J]. Acta Pharmaceutica Sinica, 2025 , 60 (6) : 1641 -1653 . DOI: 10.16438/j.0513-4870.2024-1299
大脑是人体内功能最复杂、结构最精细的器官, 其研究始终面临重大技术挑战。生命科学领域长期致力于发展高分辨率、多维度及多模态的生物成像技术, 以精确了解重要生物活性分子或药物分子等在脑组织、细胞中的时空分布特征及动态变化规律。在当前脑科学研究中, 功能成像技术主要依赖于功能性磁共振成像和正电子发射断层成像; 而脑结构成像则采用磁共振成像、单光子发射计算机断层成像和计算机断层成像等技术。尽管这些技术在神经退行性和中枢神经系统疾病研究中发挥了重要作用, 但其仅提供了脑组织结构信息, 缺少分子水平成像信息, 同时存在低空间分辨率和有限的物质检测能力等问题[1]。
在精准医学快速发展的时代背景下[2], 质谱成像(mass spectrometry imaging, MSI) 技术凭借其独特优势成为脑科学研究的关键突破点。该技术是一种可直观反映疾病状态或药物作用条件下, 机体内源性小分子代谢物或药物精准空间分布的原位成像技术, 具有无需特异性标记、时间短和检测范围广等特点[3]。该技术可在分子水平上了解脑组织微区内源性代谢物(如神经递质、脂肪酸、核苷酸和氨基酸类) 的原位分布及含量差异变化, 有助于深入阐明中枢神经功能和疾病形成机制。代谢组学作为系统生物学的重要组成部分之一, 虽在揭示生理病理机制及药物作用靶点方面取得重大进展, 却长期受限于无法获取代谢物的原位空间信息[4]。基于MSI技术与代谢组学技术相结合, 将组学信息拓展到了三维空间水平, 极大地提升了对脑组织样品信息的深度发现和认识。值得关注的是, 中国药科大学李萍教授与李彬教授课题组开展的“空间代谢组学等新技术助力中药复杂体系物质基础解析”研究[5, 6], 成功破解了中药多组分空间代谢的时空动态规律, 被评为“2023年度中医药十大学术进展”。
本文系统综述近十年来MSI技术在中枢神经系统疾病研究中的创新应用及突破性进展。如图1A所示, MSI技术涵盖药物研发、食品科学、环境毒理等多个领域, 其中在中枢神经系统疾病研究中展现出显著优势——占据了总发文量的17%, 而针对神经药物代谢动力学的探索性研究占比达4%。尤为引人注目的是, 该技术在中枢神经系统疾病领域研究年度发文量呈现增长态势(图1B)。
MSI技术采用多种原位离子化技术使样本表面化合物离子化, 传输进入质谱中获得离子的质荷比(m/z) 和离子强度, 并利用质谱成像软件将含有空间位置信息的质谱数据集合转换为离子分布图像, 从而获得样本表面各像素点离子的质荷比和离子强度[7]。根据离子源类型不同, 分为基质辅助激光解吸电离(matrix-assisted laser desorption ionization, MALDI)、解吸电喷雾离子化(desorption electrospray ionization, DESI) 和次级离子质谱(secondary ion mass spectrometry, SIMS) 成像技术[8]。1987年Hillenkamp及Karas首次发明MALDI技术, 该技术是对激光解吸电离技术的重大改进。其利用能够吸收特定波长激光的基质与样本表面的分子形成共结晶。当激光照射晶体时, 实现对待测物的原位解吸和离子化, 具有质量范围宽, 空间分辨率高(5~100 μm) 的特点[9], 适用于从整体动物到器官、组织和细胞水平(图1C)。SIMS-MSI技术利用一束初级离子喷射待测样品表面, 溅射产生正、负二次离子, 只适用于元素成像[10]。该技术具有极高的空间分辨率, 可达亚细胞级(约50 nm)[11]。
依据真空度的不同, 目前主流的敞开式MSI技术主要包括DESI-MSI和空气动力辅助解吸电喷雾质谱成像(air flow assisted-DESI-MSI, AFADESI-MSI)。这些技术突破了传统质谱对真空环境的要求, 直接在常压下完成样品分析。由于无需基质辅助, 有效避免了基质分子对检测信号的干扰。然而, DESI产生的碎裂最小, 适用于低分子量极性化合物的成像, 但空间分辨率较低(30~200 μm)。研究人员还开发了纳米喷雾解吸电喷雾电离(nano-DESI) 技术, 可实现高空间分辨率成像(约10 μm), 适用于药物及其代谢物等检测[12]。AFADESI-MSI可在常压环境中完成大体积动物整体成像(20~100 μm)[13]。德国TransMIT公司开发了环境大气压扫描微探针MALDI成像系统, 采用激光束和离子流同轴设计的创新构架, 解决了高空间分辨率和低采样量之间的矛盾, 实现单细胞水平成像(约5 μm)[14]。
因成像部位及目标成分不同, MSI样本制备和分析方法有所区别, 但其核心分析流程相似。以MALDI-MSI样品处理方法为例, 其准备与分析流程如图1D所示。首先, 获得大鼠或小鼠脑组织, 置于-80 ℃环境, 包埋, 切片, 放于氧化铟锡载玻片; 其次, 根据分析物种类及其结构, 选择合适的洗涤溶剂和方法除去组织中多肽和蛋白质, 以减少离子效应。
神经递质等小分子代谢物(m/z < 500) 易受到基质峰覆盖及复杂的离子抑制影响, 往往需要对待测物进行衍生化反应处理, 增加其分子质量, 避免与基质信号重合, 提高离子化效率[15, 16]。常见衍生化反应包括酯化反应、酰化反应、加成反应和取代反应等[17]。常见衍生化试剂见表1[15, 18-25]。
Ito等[26]创新性地开发了一种“三重喷雾”样品衍生化处理方法, 并设计了一组mTRAQ衍生化试剂(包含胺反应性非稳定同位素mTRAQΔ0和稳定同位素mTRAQΔ4), 成功实现了易卒中型自发性高血压大鼠与正常大鼠脑组织中多种水溶性氨基酸甘氨酸、丙氨酸、γ-氨基丁酸(gamma-aminobutyric acid, GABA)、丝氨酸、谷氨酰胺(glutamine, Gln) 和谷氨酸(glutamate, Glu) 的空间分布及相对含量的靶向定量分析。Liu等[27]采用吡啶甲基苄基硼酸与吡啶盐组成的衍生化系统, 通过对顺式二醇和伯胺基团进行共价电荷标记, 显著提升了氨基酸类神经递质和核苷调质类化合物的检测灵敏度。Esteve等[21]研究发现, 4-羟基-3-甲氧基肉桂醛(4-hydroxy-3-methoxycinnamaldehyde, CA)、2, 4-二苯基四氟硼酸吡喃和对-N, N, N-三甲基氨酰N'-羟基琥珀酰亚胺氨基甲酸酯碘化物三种衍生化试剂具有互补特性。通过MALDI-MSI技术, 成功绘制了皮层扩散性抑制小鼠模型中23种氨基酸类神经递质的空间分布图谱。
依据MALDI-MSI原理, 高质量图像从根本上依赖于基质与分析物之间形成均匀稳定的共结晶结构。基质在激光波长处具有高吸收系数及分析物的高效解吸和离子化是形成稳定共结晶的前提。主流有机基质有2, 5-二羟基苯甲酸(2, 5-dihydroxy benzoic acid, DHB)、α-氰基-4-羟基肉桂酸(α-cyano-4-hydroxycinnamic acid, CHCA)、芥子酸和9-氨基吖啶(9-aminoacridine, 9-AA) 等小分子有机物。另一方面, 基质沉积技术同样影响成像性能。喷雾法是目前MALDI-MSI技术的主流沉积方法, 分为气动喷雾法和电喷雾法等[28, 29]。
近年来, 新基质的发现和基质沉积技术取得了突破性进展。Fu等[18]研发的2, 5-二羟基对苯二甲酸展现出独特优势, 其在355 nm处强紫外吸收特性使激光能量转化效率提升2.3倍, 在人血清氨基酸类成分检测中灵敏度较传统基质DHB提高一二个数量级。Chen等[30]设计的双极性离子化基质4-氨基噌啉-3-甲酰胺(4-aminocinnoline-3-carboxamide, 4-AC), 与DHB和9-AA相比, 4-AC (355 nm) 离子化效率高, 背景干扰小且真空稳定时间延长至72 h。在APP/PS1转基因阿尔茨海默病(Alzheimer's disease, AD) 小鼠脑中精准定位93种代谢物, 包括三羧酸循环中间体、甘油磷脂(phosphoglyceride, PC) 类、脂肪酸(fatty acids, FA) 类和鞘磷脂(sphingomyelin, SM) 类以及ω-3多不饱和脂肪酸, 同时在小鼠血清中检测到81种差异代谢物。
MSI数据的高维性对数据处理、分析、存储提出了挑战。众多的商用分析软件, 如布鲁克的SCiLSTM Lab和MetaboScape®、赛默飞的ImageQuest、沃特世的High Definition Imaging Software[31]等; 以及开源的MSi-Reader、MassImager、Metabolite Imager分析软件平台[32]等。MSI数据分析包括去噪、峰校正、归一化等预处理, 以提高MSI图像的质量[33]。此外, 多元统计分析方法、机器学习和深度学习模型等人工智能技术的引入, 显著提升了空间代谢组学的数据解析能力和应用价值[34]。
内源性代谢物是指生物体内部合成的代谢物, 这些代谢物通过细胞内的代谢反应产生, 并在维持生命活动、调节生理功能等方面发挥重要作用, 主要分为神经递质类、脂质类和氨基酸类代谢物。
神经递质和神经调质作为神经系统中神经细胞交流的信使, 在神经退行性疾病AD、帕金森病(Parkinson's disease, PD)、抑郁症及失眠症等疾病中扮演着重要的角色。基于MSI技术的神经递质和神经调质空间分布研究多聚焦于多巴胺(dopamine, DA)、去甲肾上腺素(norepinephrine, NE)、肾上腺素(epinephrine, E)、5-羟色胺(5-hydroxytryptamine, 5-HT) 和组胺等胺类; GABA、Glu、天冬氨酸和甘氨酸等氨基酸类; 乙酰胆碱(acetylcholine, ACh) 等胆碱类; 腺苷、三磷酸腺苷(adenosine triphosphate, ATP) 和肽类等嘌呤类。此外, 也有部分对神经肽类(阿片类肽、脑啡肽以及内啡肽等) 神经调质脑微区分布的研究。
瑞典乌普萨拉大学Per E. Andren课题组[15, 35]于2014年起, 基于MALDI-MSI技术, 在大鼠及非人灵长类动物脑矢状面和冠状面开展系统性研究, 成功实现神经递质、小分子代谢物及神经肽的高分辨空间成像。考察了2, 4-二苯基四氟硼酸吡喃和2-氟-1-甲基吡啶的离子化效率, 并将其应用于6-羟基多巴胺(6-hydroxydopamine, 6-OHDA) 中脑定位注射诱导PD模型研究。通过该技术揭示了模型大鼠脑中DA、3-甲氧酪胺(3-methoxytyramine, 3-MT)、酪氨酸和GABA等代谢物微区分布特征。
经过衍生化的DA在富含DA能神经元的纹状体(striatum, ST) 呈现特异性分布。与正常脑半球相比(124 pmol·mg-1), 损伤侧脑区DA响应显著降低至84 pmol·mg-1, 这与6-OHDA诱导的DA能神经元特异性损伤机制相符。此外, 由于DA能神经元末端在ST分布具有异质性, PD模型大鼠尾壳核区域DA显著减少。Shikano等[36]研究同样显示在6-OHDA诱导PD大鼠, 相较于未损脑侧, 受损脑侧尾壳核和伏隔核DA显著降低。如图2所示, 在正常脑侧DA关键代谢产物3-MT和3, 4-二羟基苯甲醛(DOPAL) 平均浓度高于受损脑侧, 与DA分布相同[15]。
作为儿茶酚胺类的合成前体, 酪氨酸与DA和3-MT分布特征相同。尽管3, 4-二羟基苯乙酸(DOPAC) 和其同分异构体3, 4-二羟基苯乙醇醛(DOPEGAL), 以及高香草酸(HVA) 和其同分异构体3-羟基-4-甲氧基苯甲醛(MOPEGAL) 的结构相似, 但仅检测到了DOPAC和HVA, 且其空间分布与DA有相似性。NE与E主要分布于ST和大脑皮层(cerebral cortex, CTX)。PD模型大鼠受损脑侧皮层NE水平较正常脑侧显著降低。DOPEGAL氧化成3, 4-二羟基扁桃酸(DOMA), 进而甲基化生成香草酸(VMA) 的代谢途径在脑中并不占优势, 该代谢实为NE和E在外周肝脏代谢的主要途径。因此, 3, 4-二羟基苯基二醇(DOPEG) 和3-甲氧基-4-羟基扁桃酸(MOPEG) 是NE在脑内的主要代谢产物。而由儿茶酚-O-甲基转移酶(COMT) 介导的甲基化代谢作为次要代谢途径, 导致脑内去甲氧基肾上腺素(NMN) 浓度极低, 同时促使E为该代谢途径的主要代谢产物。
该课题组同时检测了多种神经递质(GABA、5-HT、酪胺、苯乙胺、Glu、ACh和L-α-甘油磷酸胆碱) 的脑区分布特征。结果显示, 5-HT及其代谢物5-羟基吲哚乙酸主要富集于苍白球和ST前部, 这与5-HT能神经元向尾壳核的投射通路一致[15]。口服L-3, 4-二羟基苯丙氨酸(3, 4-dihydroxyphenyl L-alanine, L-DOPA)-d3后, 受损脑半球的DA-d3主要分布于基底前脑和ST, 提示治疗性DA-d3可能主要来源于5-HT能神经元的转化。L-DOPA治疗PD时, 可能诱发运动障碍[35]。研究表明, 在灵长类动物模型研究表明, 运动障碍的发生与脑内L-DOPA及其代谢产物3-O-甲基多巴水平升高有关。此外, 其他脑区的DA及其代谢物含量也显著增加。这种异常蓄积可能是L-DOPA治疗不良反应的关键因素。此外, GABA在CTX、尾壳核、伏隔核、海马(hippocampus, HP) 和下丘脑(hypothalamus, HY) 广泛分布[36]。PD模型中受损侧尾壳核的GABA信号强度显著增加, 提示GABA能中间神经元可能对DA功能缺失起到代偿作用。Wang等[37]应用红外基质辅助激光解吸电喷雾电离技术比较了不同前处理方法对神经递质检测的影响, 发现蔗糖/多聚甲醛/无冰适合DA途径代谢物检测, 而新鲜/冰适合Glu途径代谢物检测。
李彬教授课题组是国内较早从事神经系统疾病脑代谢物MALDI成像研究团队之一。创新性地开发了激光辅助组织转移(laser-assisted tissue transfer, LATT) 技术。该技术通过优化组织厚度、衍生化条件和激光参数, 有效降低了离子抑制效应, 显著提高了检测灵敏度[24]。以CA为衍生化试剂, 在大鼠脑矢状面和冠状面组织中成功检测到67种内源性化合物, 包括神经递质、氨基酸和二肽等代谢物。此外, 该团队还采用吉拉德试剂实现了类固醇类物质的精准测定。在此基础上, Li等[38]进一步采用激光辅助化学转移(laser-assisted chemical transfer, LACT) 技术, 通过引入六氟异丙醇显著提高了大鼠脑组织中二肽类物质的成像效果。在CHCA/CA/三氟乙酸混合体系中添加六氟异丙醇可显著改善分析物响应特性、线性范围宽和重复性。结果显示, 甘氨酰-苯丙氨酸、谷氨酰-谷氨酰胺等主要分布在CTX、ST和HP中, 谷氨酰-谷氨酰胺在齿状回区响应最高; 含组氨酸的二肽呈现特异性分布, 如组氨酰-丙氨酸选择性分布于嗅球, 组氨酰-苏氨酸分布在丘脑(thalamus, TH) 和HY。MALDI-MSI技术也适用于模式动物研究, 通过优化冷冻膜法和防卷板法切片厚度(15 μm), 成功实现了黑腹果蝇头部GABA的空间分布检测[39]。
神经肽作为重要的神经调质类, 在哺乳动物脑中呈低浓度分布。基底神经节含丰富阿片类神经肽(β-内啡肽、脑啡肽和强啡肽)。而黑质和基底神经节则主要分布有激肽类神经肽(P物质、神经激肽A和神经激肽B六个成员)。脑-肠肽神经降压素在ST和黑质中均有表达, 可调控DA能神经系统功能。Hulme等[40]利用MALDI-MSI技术系统研究了6-OHDA诱导的PD大鼠模型脑基底神经节回路中21种神经肽的动态变化。在损伤侧尾壳核中P物质(SP (1-11)) 水平显著降低, L-DOPA治疗可特异性逆转该变化。苍白球和丘脑外侧的SP (1-11) 水平在给药后均明显下降。尾壳核神经肽对6-OHDA损伤更敏感, 而苍白球区域的神经肽则对L-DOPA治疗反应更显著。鉴于SP对DA能神经元耗竭具有神经保护作用, 该研究提示SP可能成为PD治疗的潜在靶点。
综上, 基于MALDI-MSI技术, 研究人员已在AD动物模型(包括大鼠、小鼠及灵长类) 及多种模式生物中成功实现了神经递质及代谢物的空间分布研究。目前该技术主要应用于PD发病机制研究, 重点关注与神经元发生过程密切相关的DA、NE和GABA等关键神经递质的动态变化规律。
脑组织干重的90%由脂质构成, 这类生物分子不仅参与神经信号传导过程, 还在β-淀粉样蛋白(beta-amyloid protein, Aβ) 聚集等病理过程中发挥关键作用。大量研究表明, 神经退行性疾病和精神系统疾病的发生发展与脂质代谢紊乱密切相关。基于疏水性差异, 脂质可分为两大类: 非极性脂质(如FA、甘油三酯和胆固醇酯等) 和极性脂质(包括磷脂、鞘脂、糖脂以及胆固醇等)。借助MALDI-MSI技术, 在10 µm空间分辨率下可实现100余种脂质分子的精准定位分析。脂质MSI分析中常用的基质包括DHB、1, 5-二氨基萘(1, 5-diaminonaphthalene, 1, 5-DAN)、9-AA、N-(1-萘基)乙二胺二盐酸盐和CHCA。值得注意的是, 脂质同分异构体的鉴别仍是当前研究的主要技术瓶颈。离子迁移谱技术的引入为这一难题提供了解决方案, 该技术通过测定碰撞截面等物理参数, 可实现对结构异构体在内的复杂脂质混合物进行高效区分和鉴定。
FA作为中性脂肪、磷脂和糖脂的基本结构单元, 可分为游离脂肪酸(free fatty acid, FFA) 和改性脂肪酸两大类。近年来, 通过优化衍生化喷雾方法及开发新型基质等手段, FFA检测灵敏度得到显著提升。Wu等[41]创新性地采用MALDI-MSI技术, 以2-氨甲基吡啶作为衍生化试剂, 系统比较了传统喷雾与新型电喷雾衍生化方法对大鼠脑组织中二十二碳六烯酸、花生四烯酸、油酸、亚麻酸、二十碳五烯酸、亚油酸等6种不饱和脂肪酸和2种饱和脂肪酸硬脂酸、棕榈酸的检测效果。新型电喷雾衍生化技术有效降低了分析物离域效应, 显著提升检测灵敏度; 在正离子模式下成功实现6类FA成分的可视化; 负离子模式下(空间分辨率20 μm) 清晰观察到二十二碳六烯酸和花生四烯酸在海马齿状回颗粒细胞层及CA1区锥体细胞层的特异性分布。
新型基质开发是提高检测灵敏度的另一关键。研究表明, N1, N4-二苄叉苯-1, 4-二胺(DBDA) 作为新型基质可显著增强FA和硫苷脂的离子化效率[42]。在负离子模式MALDI-MSI分析中(空间分辨率10 µm), 该基质显著提高了Balb/c Npcnih (Npc1) 小鼠脑组织中FA的检测灵敏度。多数FA主要富集于灰质; 棕榈酸和硬脂酸在前额叶皮层呈现高信号响应; 油酸在白质中的分布显著; 二十二碳六烯酸呈现灰质特异性分布。值得注意的是, DBDA基质同样适用于硫苷脂分析, 其中SHexCer (d18∶1/24∶1) 离子丰度最高[42]。此外, N-苯基-2-萘胺在动脉闭塞/再灌注(middle cerebral artery occlusion, MCAO) 模型大鼠脑组织分析中表现出优于传统基质的灵敏度, 研究同时发现缺血区多种脂质水平发生显著变化[43]。
Emre等[44]利用MALDI-MSI技术分析了2、4、8和18月龄淀粉样前体蛋白敲入(App KI) AD模型小鼠脑中改性脂肪酸变化。与野生型(wild-type, WT) 小鼠相比, 花生四烯酸相关代谢物前列腺素E2、D2, 15-羟基二十碳四烯酸和白三烯B4及二十二碳六烯酸相关中间体14-、17-和20-羟基二十二碳六烯酸在18月龄App KI小鼠的CTX中显著增加, 而PGF2α仅在HP增加了。Zhang等[45]建立了一种直接快速分析5×FAD转基因AD模型小鼠脑(15 μm) 和其他脏器中胆固醇的MALDI-MSI空间分布方法。CHCA基质更有利于胆固醇分析。在新鲜脑冠状面切片中, 胆固醇主要分布在HP、小脑(cerebellum, CBC) 和TH, 且AD小鼠小脑白质中胆固醇含量显著高于WT小鼠。
极性脂质(PC、PI、PA及SM等) 是细胞膜的关键成分, 其代谢紊乱可破坏膜结构, 影响突触功能, 并促进AD等神经退行性疾病的发展。利用MALDI-MSI技术, 研究人员在三种经典AD转基因小鼠模型(3×Tg、APP/PS1和tgArcSwe) 中系统揭示了脑脂质空间分布的特征性改变: 对于甘油磷脂类代谢异常, Aβ斑块沉积区PI (38∶4) 和PI (36∶4) 显著升高(3×Tg和APP/PS1模型)[46, 47]; 杏仁核PA、SM及PC (16∶0/16∶0) 升高, 而PI、CPI及含多不饱和脂肪酸的PC (16∶0/20∶4)、(16∶0/22∶6) 降低(3×Tg模型)[48]。对于鞘脂代谢紊乱, 神经节苷脂GM2 (36∶1) 和GM3 (36∶1) 水平普遍升高(APP/PS1和tgArcSwe模型)[49, 50], 神经酰胺Cer (d18∶1/18∶0) 等显著降低, 硫苷脂及糖鞘脂(SHexCer、GroPIn) 在学习记忆相关脑区(CTX、HP和CBC) 明显减少[47, 51]。基于以上分析, AD病理进程中Aβ斑块沉积区域伴随显著的脂质代谢重编程, 特别是甘油磷脂(PC/PA/PI)、鞘脂(SM/神经节苷脂) 及固醇类物质的分布异常最为突出, 这些变化可能通过影响膜流动性、信号转导等机制参与AD的发病过程。
MSI技术在缺血性脑卒中研究中应用也十分广泛[52]。Zhu等[53]利用MALDI-MSI技术发现三七皂苷R1能增加MCAO模型大鼠ST和HP中Glu和N-乙酰天冬氨酸, 及与能量代谢相关的二磷酸腺苷(adenosine diphosphate, ADP)、ATP和单磷酸腺苷(adenosine monophosphate, AMP), 磷脂代谢相关的PI (18∶0)、PA (16∶0/16∶0)、PA (18∶0/18∶1) 和PE (P-18∶0/22∶6) 水平。Mavroudakis等[54]利用Nano-DESI-MSI表征了MCAO模型脑半球LPC和PC的分布。预防性给予胞嘧啶-鸟嘌呤寡脱氧核苷酸, 不仅能减少梗死面积, 同时能降低PC降解和LPC累积。Andrews等[55]利用MALDI-MSI技术研究了N-甲基-D-天冬氨酸的GluN2D-/-在脑缺血中的作用。与WT小鼠相比, GluN2D-/-小鼠脑中PC增加, 甘油二酯减少, 表明脑缺血释放的FFA减少。Liu等[56]利用MALDI-MSI技术发现缺氧缺血性脑病新生大鼠模型脑中脂质代谢的变化, 与对侧正常脑区相比, PA (32∶1)、PS (34∶1)、PI (38∶5)、PI (38∶4) 和9种PE类代谢物在脑缺血侧显著降低, LPC (18∶0)、磷酸鞘氨醇、Cer (d18∶1/18∶1)、Cer (d18∶1/18∶0) 和SM代谢物在缺血脑侧显著升高。
神经退行性疾病的发生与能量代谢失调, 氨基酸代谢紊乱密切相关[57]。Wu等[58]利用MALDI-MSI技术, 以1, 5-DAN为基质, 发现淫羊藿素通过降低1-甲基-4-苯基-1, 2, 3, 6-四氢吡啶诱导的PD小鼠脑黑质中牛磺酸、抗坏血酸、Glu、Gln、肌苷和柠檬酸水平进而抑制氧化应激, 并增加了ATP、ADP和天冬氨酸水平, 表明淫羊藿素通过改善脑能量代谢发挥了神经保护作用。Esteve等[46]的研究表明, 以9-AA为基质, 与WT小鼠相比, 3×Tg小鼠脑组织中嘌呤代谢通路上肌苷、次黄嘌呤、黄嘌呤和尿酸含量升高, 而腺苷和AMP含量降低。海马区N-花生四烯酰牛磺酸显著降低; 其分布不均匀, 在内侧层和齿状回区域的响应强度更高, 而锥体细胞层响应较低。基于MALDI-MSI技术的3×Tg小鼠脑中代谢物的变化趋势与AD中常见的氧化应激和促炎因子增加相吻合。
川芎为中医临床治疗偏头痛之要药, 具有显著的“上行头目”功效。研究者基于MALDI-MSI技术进行空间代谢组学研究表明川芎主要成分四甲基吡嗪能显著降低硝酸甘油诱导的大鼠偏头痛模型脑中L-天冬氨醇-4-磷酸、N-乙酰-L-天冬氨酸和N-乙酰葡甘氨酸谷氨酸含量, 并增加ATP代谢物(烟酰胺腺嘌呤二核苷酸、ADP、AMP、鸟苷酸、腺苷和肌苷) 含量, 调整葡萄糖代谢至正常水平, 维持大脑ATP供应, 对抗偏头痛引起的氧化应激发挥治疗作用[59]。Liu等[56]以1, 5-DAN盐酸盐为基质, 采用MALDI-MSI技术发现新生缺氧缺血性脑病模型大鼠缺血脑区共有73种代谢物发生了显著变化, 主要涉及糖酵解、三羧酸循环、核苷代谢、脂质代谢、氧化应激和离子稳态等多种代谢途径。Cheng等[60]利用MALDI-MSI技术发现, MCAO大鼠第7天缺血侧CTX中ATP、葡萄糖和柠檬酸含量升高。另有研究显示了类似的结果, 再灌流24 h后, CTX和ST中天冬氨酸、Glu、尿苷二磷酸和尿苷二磷酸-葡萄糖含量明显下降, 柠檬酸盐的含量增加, 而HP则无明显变化[61]。
药代动力学(吸收、分布、代谢和排泄) 研究在药物研发过程中具有关键作用。针对中枢神经系统药物研发, 药物能否有效穿透血脑屏障并在靶部位达到治疗浓度是亟待解决的重要科学问题。目前常用的药物分布研究方法包括全身放射自显影、正电子发射断层成像和荧光成像等技术, 但这些方法均存在明显局限: 一方面需要依赖放射性标记或荧光探针, 另一方面仅能示踪药物原型分子, 无法同时检测其代谢产物。相比之下, MSI技术作为一种免标记检测方法, 能够同步实现药物及其代谢产物的空间分布可视化, 在药物代谢研究中展现出独特优势。然而, 该技术在灵敏度与空间分辨率的平衡、复杂生物样本的基质效应、定量方法标准化等方面仍面临诸多技术挑战。
李彬教授课题组[7]针对中药成分体内代谢过程复杂的科学难题, 创新性地建立了一套基于MALDI-MSI的中药成分多器官空间代谢分析技术体系。Tang等[62]成功应用该技术揭示了汉防己甲素在心脏、肝脏、脾脏和肺脏的二维空间分布特征, 并首次绘制了其在肾脏的三维时空代谢图谱。在方法学创新方面, Chen等[63]以C57B1/6小鼠为模型, 系统考察了五种中枢神经系统药物(多奈哌齐、他克林、阿立哌唑、氟哌啶醇和氯氮平) 的脑内分布特征。研究采用150 μm空间分辨率的MALDI-MSI技术, 通过优化前处理方法显著提升了检测灵敏度: 首先采用pH 11的醋酸铵溶液洗脱, 有效降低了离子抑制效应; 继而通过正己烷脱脂处理, 使药物信号强度提升4.7~31.5倍, 清晰显示这些药物在CTX、HP、TH和ST的特异性分布。Guo等[64]进一步开发了LACT技术, 通过精确调控激光参数将组织剥离厚度降至最优, 成功消除了64%的脂质和97%的蛋白质干扰, 使组织消光效率提升0.76倍。这一突破性技术实现了16种中枢神经系统药物的高分辨可视化成像。特别值得注意的是, 研究发现利培酮主要富集于前额叶皮层、ST和HP等5-HT和DA能神经元密集区, 而其代谢产物9-OH利培酮则特异性地分布于侧脑室区域, 为理解该药物的作用机制提供了重要的空间分布证据。
L-DOPA作为PD临床治疗的一线药物, 通常需与芳香族氨基酸脱羧酶抑制剂联用以减少外周代谢, 提高中枢递药效率。最新研究采用高分辨MALDI-MSI技术发现, 胡椒碱与L-DOPA联用可显著抑制肠道菌群色氨酸脱羧酶活性, 从而提升L-DOPA的生物利用度及脑内DA水平[65]。这一发现为优化PD治疗方案提供了新思路。Shobo等[66]通过MALDI-MSI技术证实, 治疗AD候选药物D-AIP (100 mg·kg-1) 具有良好的血脑屏障穿透能力, 主要分布于CTX、HP和TH。值得注意的是, 该药物呈现明显的性别差异分布特征: 雌性小鼠TH周围区域药物蓄积量高于CTX和HP, 而雄性小鼠则表现为HP > CTX > TH的分布模式。针对新型乙酰胆碱酯酶抑制剂DC20的代谢研究, Guo等[67]采用DESI-MSI联用技术, 系统揭示了该药物在大鼠脑内的时空分布特征: 给药1 h后, DC20迅速扩散至CTX、HP、ST、TH和CC, 相对于其他区域, DC20在ST中富集。
以上研究不仅展示了现代MSI技术在神经药物研发中的重要作用, 更为理解药物在脑内的靶向分布和代谢动力学提供了关键实验依据。
在药物研发过程中, 采用小鼠、大鼠和犬等整体动物模型进行药动学(pharmacokinetics, PK)-药效学(pharmacodynamics, PD) 研究, 能够同步监测药物及其内源性代谢物的动态变化, 实现宏观层面的精准药理学分析。其中, AFADESI-MSI技术因其独特的整体动物成像能力, 在中药及复方制剂的PK-PD研究中展现出显著的技术优势和广阔的应用前景。再帕尔教授课题组基于AFADESI-MSI技术平台, 开创性地开展了空间代谢组学与药物组织分布研究, 重点针对天麻、远志等具有镇静催眠功效的中药活性成分进行了系统的PK-PD研究[68-70]。
天麻活性成分N6-(4-羟基苄基) 腺嘌呤核苷[N6-(4-hydroxybenzyl) adenine riboside, NHBA] 的代谢特征与药效机制研究表明, 腹腔注射NHBA (40 mg·kg-1) 20 min后主要分布于肠道, 脊椎次之, 脑中分布量最低(70 pg·mg-1)。值得注意的是, 脑内GABA达峰时间与NHBA同步(20 min), 同时观察到肾脏和肠道中PC 20 min达峰; 10~60 min内大脑和肌肉中肌酸持续累积; 10~30 min内脑腺苷水平骤降, 60 min恢复正常。这些发现揭示了NHBA的镇静催眠作用与脑内GABA、胆碱代谢物、腺苷及肌酸的时空动态变化密切相关[68]。进一步研究发现, NHBA衍生物YZG-331和YZG-330口服后主要富集于胃部, 而脑、肺、肝等器官分布极少。其中YZG-330-H能显著提高胃/脑GABA比值(54.05倍), 这种独特的胃-脑GABA代谢调控模式与其增强的镇静效果高度一致[69]。远志乙醇提取物可通过多途径发挥镇静作用, 包括显著增加松果体5-HT含量; 降低ST中DA水平; 抑制脑干(中脑、脑桥及HY) 肾上腺素合成(PNMT酶活性降低); 调节CBC和CTX腺苷及TH组胺水平, 证实了远志通过协同调控单胺类神经递质、腺苷及组胺系统来改善睡眠[70]。人参-五味子配伍后, 人参皂苷RK3、Rg5和F5在AD模型小鼠TH、CBC等区域具有稳定的时空分布特征(2 h与5 h浓度一致)。空间代谢组学分析鉴定出28种与AD病理相关的生物标志物, 人参皂苷和木脂素主要涉及肉碱、花生四烯酸代谢; 多糖调控PE和PC的水平, 人参-五味子提取物共同改善HP和CBC区域的神经炎症、能量代谢等病理过程[71]。
Khalil等[72]采用MALDI-MSI技术对抗抑郁药度洛西汀(duloxetine, DLX) 及其代谢产物在小鼠多个器官中的空间分布进行了系统研究。实验发现, 口服给药后(12和50 mg·kg-1), 脑组织中未能检出DLX原型药物及其Ⅰ相代谢物(M1~M4) 和Ⅱ相代谢物(M14~M17)。代谢产物呈现明显的器官特异性分布特征: Ⅰ相代谢物M1~M4主要富集于脾脏红髓和白髓区域, 而Ⅱ相代谢物M14-M17在脾脏中的分布相对较少。值得注意的是, PC (36∶4) 在脑冠状切片的分布呈现区域异质性, 且在HY、HP、CTX等区域与DLX的分布高度重合。高分辨率成像(40 µm) 进一步揭示给药后亚铁血红素特异性分布于脾脏红髓和白髓的精细结构。在另一项关于精神分裂症治疗药物奥氮平(olanzapine, OLZ) 的研究中[73], 灌胃给药(50 mg·mL-1) 后20 min即可在CTX检测到药物分布, 50 min达到峰值浓度。其代谢产物2-OH-OLZ主要分布于穹隆区域, 给药20 min后显著增加。研究同时监测了多种神经递质的动态变化: HY中GABA水平呈现先降低(20 min)、后升高(20 min~3 h)、再降低(3 h后) 的波动特征。此外, 该研究还对Glu、腺苷和组胺等与认知功能和睡眠调节密切相关的代谢物进行了时空分布分析, 为理解药物作用机制提供了新的视角。
MSI在中枢神经系统疾病病理机制解析和生物标志物发现等领域展现出卓越的应用价值, 有效弥补了传统代谢组学在原位可视化分析方面的技术局限。然而, 该技术的应用前景远未充分发掘, 未来发展空间仍十分广阔。
近年来, 药物研究范式已从传统的“单靶点”策略转向“多靶点、多层次”的系统调控。然而, 常规代谢组学技术依赖均质化样本分析, 仅能反映代谢物的整体水平, 难以解析其在组织中的空间分布异质性, 极大限制了疾病机制的深入探索。MSI技术在AD模型中的应用揭示, Aβ斑块周围特定脂质(如神经节苷脂) 的分布紊乱可能与神经元丢失及Aβ沉积密切相关。类似地, 在PD模型中, MSI技术定位了受损黑质区DA、GABA和5-HT代谢通路的空间异常, 为神经退行性疾病的靶点发现提供了新视角。
目前, MSI技术在失眠症研究中的应用多集中于生理状态下神经递质的脑区分布分析(图3)。未来需进一步探索疾病模型(如睡眠剥夺、昼夜节律紊乱) 中代谢物的空间异质性, 尤其是FA与脂质代谢的动态调控机制。此外, 睡眠-觉醒周期伴随神经元活动与代谢物的显著波动: 清醒状态下兴奋性神经元主导, 而睡眠阶段抑制性神经元活性增强[74]。结合MSI技术与神经环路定位, 从代谢组与细胞水平双维度解析关键脑区的动态变化, 将极大推动失眠症等中枢神经系统疾病的新靶点发现与药物研发。
近年来, MSI在药物组织分布、药效评价及递送系统研究等领域取得了显著进展, 但其在中枢神经系统药物研发中的应用仍面临多重挑战: 首先, 与传统色谱-质谱技术相比, MSI的原位检测受内源性代谢物基质效应干扰, 导致药物离子成像信噪比降低。例如, 在空间分辨率达100 µm时, 12 µm脑组织切片中的药物检测限仅约1 pg per spot, 难以满足低丰度药物分子的可视化需求。其次, 中枢神经系统药物多以口服给药为主, 但肠道代谢、首过效应及血脑屏障穿透率低等问题显著降低其生物利用度。此外, 外排转运蛋白(如P-gp) 的主动外排及药物-蛋白结合进一步限制了靶组织药物蓄积。最后, 由于基质峰在小于m/z 500时干扰, 低分子质量中枢神经系统药物的检测和可视化显得十分困难。
为提升检测灵敏度, 研究者从开发高电离效率的有机基质及低背景噪声的纳米材料(如金纳米颗粒、石墨烯); 通过组织冷冻切片标准化、基质喷涂均一化等方法减少离子抑制效应等角度进行了有益的探索和实践。MSI技术主要集中于已上市抗抑郁/失眠药物的脑区分布研究(如静脉给药后特定核团的药物蓄积分析), 但对中药多成分的时空动态研究仍处于起步阶段。未来, 通过技术创新与多学科交叉, MSI技术将为以中药和天然药物为源头的中枢神经系统药物研发, 从传统经验筛选迈向精准高效发现提供关键技术支持。
MSI与空间多组学技术(如空间转录组学、空间蛋白质组学) 的融合应用, 通过多模态成像的优势互补, 能够在不同尺度上构建组织分子图谱的完整时空特征。这种整合策略不仅实现了从基因调控到代谢调控的全链条解析, 更为中枢神经系统疾病组合生物标志物的发现提供了全新研究范式, 为组织和亚细胞水平内药物和代谢物的无标记空间测绘开辟新航道。
综上所述, MSI技术在中枢神经系统疾病靶点发现、药物研发及生物标志物发现等方面展现出巨大的应用潜力。随着MSI技术的不断进步及不断与其他多模态成像技术的整合, 为中医药实现精准用药、精准创药, 带来更多机遇。

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2025年第60卷第6期
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doi: 10.16438/j.0513-4870.2024-1299
  • 接收时间:2024-12-28
  • 首发时间:2026-09-20
  • 出版时间:2025-06-12
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  • 收稿日期:2024-12-28
  • 修回日期:2025-05-08
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    1山西大学中医药现代研究中心, 山西 太原 030006
    2山西中医药大学中药与食品工程学院, 山西 太原 030619
    3山西医科大学附属山西省人民医院放射科, 山西 太原 030001

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闫艳, E-mail:
张瑞平, E-mail:
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2种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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