药学学报

Method	Biological sample	Reagent	Testing method	Testing substance	Advantage	Insufficient	Ref.
Protein precipitation (PP)	Plasma from rats	Acetonitrile	LC-MS/MS	Strychnine	The operation is simple, and the cost is low.	The impurity is relatively high, and the content determination is not accurate.	[18]
Plasma from rats, brain tissue	Acetonitrile	LC-MS/MS	Dexamethasone	[19]
Plasma from rats	Methanol	HPLC-FL	Scopolamine	[20]
Human blood, urine	Methanol	HPLC-Orbitrap MS	Plant toxins	[21]
Plasma from rats	Acetonitrile	UHPLC-HESI-LTQ-MS	Doxorubicin and lapatinib	[22]
Human blood	Methanol	UHPLC-MS/MS	Digoxin	[23]
Liquid-liquid extraction (LLE)	Human blood	Methyl tert-butyl ether	LC-MS/MS	Digoxin	The extraction range is wide, the operation is simple, and the cost is low.	The usage dosage of organic reagents is comparatively high, making automation difficult.	[24]
Human blood, urine	Methyl tert-butyl ether	GC-MS/MS	SCFAs	[25]
Plasma from rats	Methanol	GC-MS	Ganoderic acid H	[26]
Dispersive liquid-liquid microextraction (DLLME)	Human blood	Tetrachloroethylene-methanol	DLLME-IMS	Gabapentin	Low solvent consumption, short extraction time, and high enrichment factor.	The selection range of the extractant is relatively narrow.	[27]
Human serum	Formic acid-ethyl acetate-acetonitrile	GC-MS	HPAHs	[28]
Solid phase extraction (SPE)	Human serum	-	LC-MS/MS	Methotrexate and its metabolites	Time-saving and efficient, it can reduce reagent and sample loss.	Longer extraction time and lower selectivity.	[29]
brain tissue	-	SPME-UPLC-MS/MS	Nicotine and its metabolites	[30]
Solid-phase microextraction (SPME)	Human blood	-	SPME-PESI-MS/MS	Fentanyl	Simple operation, high throughput, low use of organic solvents, easy automation, green.	The equipment used is expensive and fragile, its specificity needs to be improved, and it cannot be used for macromolecular substances and large-scale extraction.	[31]
Human blood	-	LC-APCI-MS/MS	Isoflurane	[32]
Bone marrow	-	LC-TOF-MS/MS	Benzodiazepine drugs	[33]
Blood	-	HPTLC	Zomepirac	[34]
Tissue	-	DART-MS	Animal medicine	[35]
Hair	Acetonitrile	HPLC	Codeine and morphine	[36]
Microdialysis (MD)	Brain tissue	-	HPLC	Andrographolide	Real-time, online, and dynamic monitoring of the same organism can be achieved.	Not applicable to drugs with a short half-life and those with high lipid solubility; membranes are prone to blockage.	[37]
Aqueous humor	-	HPLC-MS/MS	Tartaric acid bromo-monie	[38]
Molecular imprinting technology (MIT)	Brain tissue	-	LC-MS/MS	Aminopyridinoic acid	The specificity is relatively high.	The functionality of the monomer is singular, and the recognition limitations are considerable.	[39]
Supercritical fluid extraction (SFE)	Plasma from rats	-	PTT-SFEC-MS/MS	Lipids	The extraction efficiency is high, the extraction efficiency and selectivity are high, it saves time, and there is less environmental pollution.	The cost is high.	[40]
Chemical derivatization technology	Plasma from rats, urine, brain tissue	5-DMISC	LC-MS/MS	Phenol	There are many choices for derivatization reagents.	The derivation operations are cumbersome and subject to strict conditions.	[41]
Purge and trap	Human urine	201-Dimethyl silicone oil	GC-MS	Acetone	High sensitivity, low detection limit.	It takes a long time and can easily damage the instruments.	[42]

Method

Biological sample

Reagent

Testing method

Testing substance

Advantage

Insufficient

Ref.

Protein precipitation (PP)

Plasma from rats

Acetonitrile

LC-MS/MS

Strychnine

The operation is simple, and the cost is low.

The impurity is relatively high, and the content determination is not accurate.

[18]

Plasma from rats, brain tissue

Acetonitrile

LC-MS/MS

Dexamethasone

[19]

Plasma from rats

Methanol

HPLC-FL

Scopolamine

[20]

Human blood, urine

Methanol

HPLC-Orbitrap MS

Plant toxins

[21]

Plasma from rats

Acetonitrile

UHPLC-HESI-LTQ-MS

Doxorubicin and lapatinib

[22]

Human blood

Methanol

UHPLC-MS/MS

Digoxin

[23]

Liquid-liquid extraction (LLE)

Human blood

Methyl tert-butyl ether

LC-MS/MS

Digoxin

The extraction range is wide, the operation is simple, and the cost is low.

The usage dosage of organic reagents is comparatively high, making automation difficult.

[24]

Human blood, urine

Methyl tert-butyl ether

GC-MS/MS

SCFAs

[25]

Plasma from rats

Methanol

GC-MS

Ganoderic acid H

[26]

Dispersive liquid-liquid microextraction (DLLME)

Human blood

Tetrachloroethylene-methanol

DLLME-IMS

Gabapentin

Low solvent consumption, short extraction time, and high enrichment factor.

The selection range of the extractant is relatively narrow.

[27]

Human serum

Formic acid-ethyl acetate-acetonitrile

GC-MS

HPAHs

[28]

Solid phase extraction (SPE)

Human serum

LC-MS/MS

Methotrexate and its metabolites

Time-saving and efficient, it can reduce reagent and sample loss.

Longer extraction time and lower selectivity.

[29]

brain tissue

SPME-UPLC-MS/MS

Nicotine and its metabolites

[30]

Solid-phase microextraction (SPME)

Human blood

SPME-PESI-MS/MS

Fentanyl

Simple operation, high throughput, low use of organic solvents, easy automation, green.

The equipment used is expensive and fragile, its specificity needs to be improved, and it cannot be used for macromolecular substances and large-scale extraction.

[31]

Human blood

LC-APCI-MS/MS

Isoflurane

[32]

Bone marrow

LC-TOF-MS/MS

Benzodiazepine drugs

[33]

Blood

HPTLC

Zomepirac

[34]

Tissue

DART-MS

Animal medicine

[35]

Hair

Acetonitrile

HPLC

Codeine and morphine

[36]

Microdialysis (MD)

Brain tissue

HPLC

Andrographolide

Real-time, online, and dynamic monitoring of the same organism can be achieved.

Not applicable to drugs with a short half-life and those with high lipid solubility; membranes are prone to blockage.

[37]

Aqueous humor

HPLC-MS/MS

Tartaric acid bromo-monie

[38]

Molecular imprinting technology (MIT)

Brain tissue

LC-MS/MS

Aminopyridinoic acid

The specificity is relatively high.

The functionality of the monomer is singular, and the recognition limitations are considerable.

[39]

Supercritical fluid extraction (SFE)

Plasma from rats

PTT-SFEC-MS/MS

Lipids

The extraction efficiency is high, the extraction efficiency and selectivity are high, it saves time, and there is less environmental pollution.

The cost is high.

[40]

Chemical derivatization technology

Plasma from rats, urine, brain tissue

5-DMISC

LC-MS/MS

Phenol

There are many choices for derivatization reagents.

The derivation operations are cumbersome and subject to strict conditions.

[41]

Purge and trap

Human urine

201-Dimethyl silicone oil

GC-MS

Acetone

High sensitivity, low detection limit.

It takes a long time and can easily damage the instruments.

[42]

Method	Biological sample	Reagent	Testing method	Testing substance	Advantage	Insufficient	Ref.
Protein precipitation (PP)	Plasma from rats	Acetonitrile	LC-MS/MS	Strychnine	The operation is simple, and the cost is low.	The impurity is relatively high, and the content determination is not accurate.	[18]
Plasma from rats, brain tissue	Acetonitrile	LC-MS/MS	Dexamethasone	[19]
Plasma from rats	Methanol	HPLC-FL	Scopolamine	[20]
Human blood, urine	Methanol	HPLC-Orbitrap MS	Plant toxins	[21]
Plasma from rats	Acetonitrile	UHPLC-HESI-LTQ-MS	Doxorubicin and lapatinib	[22]
Human blood	Methanol	UHPLC-MS/MS	Digoxin	[23]
Liquid-liquid extraction (LLE)	Human blood	Methyl tert-butyl ether	LC-MS/MS	Digoxin	The extraction range is wide, the operation is simple, and the cost is low.	The usage dosage of organic reagents is comparatively high, making automation difficult.	[24]
Human blood, urine	Methyl tert-butyl ether	GC-MS/MS	SCFAs	[25]
Plasma from rats	Methanol	GC-MS	Ganoderic acid H	[26]
Dispersive liquid-liquid microextraction (DLLME)	Human blood	Tetrachloroethylene-methanol	DLLME-IMS	Gabapentin	Low solvent consumption, short extraction time, and high enrichment factor.	The selection range of the extractant is relatively narrow.	[27]
Human serum	Formic acid-ethyl acetate-acetonitrile	GC-MS	HPAHs	[28]
Solid phase extraction (SPE)	Human serum	-	LC-MS/MS	Methotrexate and its metabolites	Time-saving and efficient, it can reduce reagent and sample loss.	Longer extraction time and lower selectivity.	[29]
brain tissue	-	SPME-UPLC-MS/MS	Nicotine and its metabolites	[30]
Solid-phase microextraction (SPME)	Human blood	-	SPME-PESI-MS/MS	Fentanyl	Simple operation, high throughput, low use of organic solvents, easy automation, green.	The equipment used is expensive and fragile, its specificity needs to be improved, and it cannot be used for macromolecular substances and large-scale extraction.	[31]
Human blood	-	LC-APCI-MS/MS	Isoflurane	[32]
Bone marrow	-	LC-TOF-MS/MS	Benzodiazepine drugs	[33]
Blood	-	HPTLC	Zomepirac	[34]
Tissue	-	DART-MS	Animal medicine	[35]
Hair	Acetonitrile	HPLC	Codeine and morphine	[36]
Microdialysis (MD)	Brain tissue	-	HPLC	Andrographolide	Real-time, online, and dynamic monitoring of the same organism can be achieved.	Not applicable to drugs with a short half-life and those with high lipid solubility; membranes are prone to blockage.	[37]
Aqueous humor	-	HPLC-MS/MS	Tartaric acid bromo-monie	[38]
Molecular imprinting technology (MIT)	Brain tissue	-	LC-MS/MS	Aminopyridinoic acid	The specificity is relatively high.	The functionality of the monomer is singular, and the recognition limitations are considerable.	[39]
Supercritical fluid extraction (SFE)	Plasma from rats	-	PTT-SFEC-MS/MS	Lipids	The extraction efficiency is high, the extraction efficiency and selectivity are high, it saves time, and there is less environmental pollution.	The cost is high.	[40]
Chemical derivatization technology	Plasma from rats, urine, brain tissue	5-DMISC	LC-MS/MS	Phenol	There are many choices for derivatization reagents.	The derivation operations are cumbersome and subject to strict conditions.	[41]
Purge and trap	Human urine	201-Dimethyl silicone oil	GC-MS	Acetone	High sensitivity, low detection limit.	It takes a long time and can easily damage the instruments.	[42]

Method

Biological sample

Reagent

Testing method

Testing substance

Advantage

Insufficient

Ref.

Protein precipitation (PP)

Plasma from rats

Acetonitrile

LC-MS/MS

Strychnine

The operation is simple, and the cost is low.

The impurity is relatively high, and the content determination is not accurate.

[18]

Plasma from rats, brain tissue

Acetonitrile

LC-MS/MS

Dexamethasone

[19]

Plasma from rats

Methanol

HPLC-FL

Scopolamine

[20]

Human blood, urine

Methanol

HPLC-Orbitrap MS

Plant toxins

[21]

Plasma from rats

Acetonitrile

UHPLC-HESI-LTQ-MS

Doxorubicin and lapatinib

[22]

Human blood

Methanol

UHPLC-MS/MS

Digoxin

[23]

Liquid-liquid extraction (LLE)

Human blood

Methyl tert-butyl ether

LC-MS/MS

Digoxin

The extraction range is wide, the operation is simple, and the cost is low.

The usage dosage of organic reagents is comparatively high, making automation difficult.

[24]

Human blood, urine

Methyl tert-butyl ether

GC-MS/MS

SCFAs

[25]

Plasma from rats

Methanol

GC-MS

Ganoderic acid H

[26]

Dispersive liquid-liquid microextraction (DLLME)

Human blood

Tetrachloroethylene-methanol

DLLME-IMS

Gabapentin

Low solvent consumption, short extraction time, and high enrichment factor.

The selection range of the extractant is relatively narrow.

[27]

Human serum

Formic acid-ethyl acetate-acetonitrile

GC-MS

HPAHs

[28]

Solid phase extraction (SPE)

Human serum

LC-MS/MS

Methotrexate and its metabolites

Time-saving and efficient, it can reduce reagent and sample loss.

Longer extraction time and lower selectivity.

[29]

brain tissue

SPME-UPLC-MS/MS

Nicotine and its metabolites

[30]

Solid-phase microextraction (SPME)

Human blood

SPME-PESI-MS/MS

Fentanyl

Simple operation, high throughput, low use of organic solvents, easy automation, green.

The equipment used is expensive and fragile, its specificity needs to be improved, and it cannot be used for macromolecular substances and large-scale extraction.

[31]

Human blood

LC-APCI-MS/MS

Isoflurane

[32]

Bone marrow

LC-TOF-MS/MS

Benzodiazepine drugs

[33]

Blood

HPTLC

Zomepirac

[34]

Tissue

DART-MS

Animal medicine

[35]

Hair

Acetonitrile

HPLC

Codeine and morphine

[36]

Microdialysis (MD)

Brain tissue

HPLC

Andrographolide

Real-time, online, and dynamic monitoring of the same organism can be achieved.

Not applicable to drugs with a short half-life and those with high lipid solubility; membranes are prone to blockage.

[37]

Aqueous humor

HPLC-MS/MS

Tartaric acid bromo-monie

[38]

Molecular imprinting technology (MIT)

Brain tissue

LC-MS/MS

Aminopyridinoic acid

The specificity is relatively high.

The functionality of the monomer is singular, and the recognition limitations are considerable.

[39]

Supercritical fluid extraction (SFE)

Plasma from rats

PTT-SFEC-MS/MS

Lipids

The extraction efficiency is high, the extraction efficiency and selectivity are high, it saves time, and there is less environmental pollution.

The cost is high.

[40]

Chemical derivatization technology

Plasma from rats, urine, brain tissue

5-DMISC

LC-MS/MS

Phenol

There are many choices for derivatization reagents.

The derivation operations are cumbersome and subject to strict conditions.

[41]

Purge and trap

Human urine

201-Dimethyl silicone oil

GC-MS

Acetone

High sensitivity, low detection limit.

It takes a long time and can easily damage the instruments.

[42]

Instrument	Principle	Advantage	Data analysis	Detection range	Application	Ref.
GC-MS/MS	The sample is separated by chromatographic columns, and under ionization in the ion source, it produces ion fragments with a certain charge.	Use of no or minimal solvent, easy to automate, simple operation, high sensitivity, and a well-established database.	Qualitative and quantitative analysis	Volatile substances	Environmental monitoring field; metabolomics; traditional Chinese medicine industry; et al.	[58, 69]
HS-SPME-GC-MS	The adsorption of volatile compounds into the chromatographic column is carried out in a vacuum using adsorptive molten quartz fibers.	Solvent-free, easy to operate, high sensitivity, no sample pre-treatment required, low cost, and a well-established database.	Qualitative and quantitative analysis	Volatile substances	Food quality evaluation; environmental monitoring	[70]
GC-IMS	Based on the separation of volatile organic compounds in the gas chromatography column and the ionization and movement of those compounds in the ion mobility spectrometry.	The reaction speed is fast, the operation is simple, no sample pre-treatment is required, it can be performed under normal pressure, and the treatment efficiency is high.	Qualitative and quantitative analysis	Volatile substances	Food varieties; origin tracing; food quality evaluation	[71, 72]

Instrument

Principle

Advantage

Data analysis

Detection range

Application

Ref.

GC-MS/MS

The sample is separated by chromatographic columns, and under ionization in the ion source, it produces ion fragments with a certain charge.

Use of no or minimal solvent, easy to automate, simple operation, high sensitivity, and a well-established database.

Qualitative and quantitative analysis

Volatile substances

Environmental monitoring field; metabolomics; traditional Chinese medicine industry; et al.

[58, 69]

HS-SPME-GC-MS

The adsorption of volatile compounds into the chromatographic column is carried out in a vacuum using adsorptive molten quartz fibers.

Solvent-free, easy to operate, high sensitivity, no sample pre-treatment required, low cost, and a well-established database.

Qualitative and quantitative analysis

Volatile substances

Food quality evaluation; environmental monitoring

[70]

GC-IMS

Based on the separation of volatile organic compounds in the gas chromatography column and the ionization and movement of those compounds in the ion mobility spectrometry.

The reaction speed is fast, the operation is simple, no sample pre-treatment is required, it can be performed under normal pressure, and the treatment efficiency is high.

Qualitative and quantitative analysis

Volatile substances

Food varieties; origin tracing; food quality evaluation

[71, 72]

Instrument	Principle	Advantage	Data analysis	Detection range	Application	Ref.
GC-MS/MS	The sample is separated by chromatographic columns, and under ionization in the ion source, it produces ion fragments with a certain charge.	Use of no or minimal solvent, easy to automate, simple operation, high sensitivity, and a well-established database.	Qualitative and quantitative analysis	Volatile substances	Environmental monitoring field; metabolomics; traditional Chinese medicine industry; et al.	[58, 69]
HS-SPME-GC-MS	The adsorption of volatile compounds into the chromatographic column is carried out in a vacuum using adsorptive molten quartz fibers.	Solvent-free, easy to operate, high sensitivity, no sample pre-treatment required, low cost, and a well-established database.	Qualitative and quantitative analysis	Volatile substances	Food quality evaluation; environmental monitoring	[70]
GC-IMS	Based on the separation of volatile organic compounds in the gas chromatography column and the ionization and movement of those compounds in the ion mobility spectrometry.	The reaction speed is fast, the operation is simple, no sample pre-treatment is required, it can be performed under normal pressure, and the treatment efficiency is high.	Qualitative and quantitative analysis	Volatile substances	Food varieties; origin tracing; food quality evaluation	[71, 72]

Instrument

Principle

Advantage

Data analysis

Detection range

Application

Ref.

GC-MS/MS

The sample is separated by chromatographic columns, and under ionization in the ion source, it produces ion fragments with a certain charge.

Use of no or minimal solvent, easy to automate, simple operation, high sensitivity, and a well-established database.

Qualitative and quantitative analysis

Volatile substances

Environmental monitoring field; metabolomics; traditional Chinese medicine industry; et al.

[58, 69]

HS-SPME-GC-MS

The adsorption of volatile compounds into the chromatographic column is carried out in a vacuum using adsorptive molten quartz fibers.

Solvent-free, easy to operate, high sensitivity, no sample pre-treatment required, low cost, and a well-established database.

Qualitative and quantitative analysis

Volatile substances

Food quality evaluation; environmental monitoring

[70]

GC-IMS

Based on the separation of volatile organic compounds in the gas chromatography column and the ionization and movement of those compounds in the ion mobility spectrometry.

The reaction speed is fast, the operation is simple, no sample pre-treatment is required, it can be performed under normal pressure, and the treatment efficiency is high.

Qualitative and quantitative analysis

Volatile substances

Food varieties; origin tracing; food quality evaluation

[71, 72]

指纹图谱技术在生物样品内效应组分分析中的研究与应用进展

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杨泽荣 , 刘淑琼 , 钟月彤 , 张国琼 , 李林哲 , 胡慧玲 , 张美 ^* , 俞捷 ^*

药学学报 | 综述 2025,60(9): 2710-2723

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药学学报 |综述 2025 , 60 (9) : 2710 -2723

指纹图谱技术在生物样品内效应组分分析中的研究与应用进展

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杨泽荣, 刘淑琼, 钟月彤, 张国琼, 李林哲, 胡慧玲, 张美^*, 俞捷^*

作者信息

云南中医药大学, 中药学院暨云南省南药可持续利用研究重点实验室, 云南昆明 650500

通讯作者:

张美, E-mail: meizhang213@163.com

俞捷, E-mail: yujie@ynucm.edu.cn

作者简介:

作者贡献:

杨泽荣负责撰写并修改综述; 刘淑琼负责提供修改意见; 钟月彤、张国琼、李林哲、胡慧玲负责文献分析; 张美、俞捷负责综述选题、构思及全程指导。

Research and application progress of fingerprint technology in the analysis of effect components in biological samples

Ze-rong YANG, Shu-qiong LIU, Yue-tong ZHONG, Guo-qiong ZHANG, Lin-zhe LI, Hui-ling HU, Mei ZHANG^*, Jie YU^*

Affiliations

School of Chinese Materia Medica and Yunnan Key Laboratory of Southern Medicine Utilization, Yunnan University of Chinese Medicine, Kunming 650500, China

出版时间: 2025-09-12 doi: 10.16438/j.0513-4870.2025-0242

文章导航

摘要

收起

指纹图谱是指某些成分复杂的物质或组分, 在经过适当的处理和分析后, 得到的能标识其本质特征的色谱图、光谱图或其他可视化的数据。生物样品内效应组分分析具有生物介质组分复杂、理化性质差异大、效应成分代谢反应复杂种类多、原型与代谢产物微量痕量为主等特点, 因此准确快速测定其中效应组分有重要意义。本文综述了近年来各指纹图谱技术在生物样品分析中的应用研究进展, 并分析各种方法的优劣, 展望了今后指纹图谱技术在生物样品中效应组分分析的发展趋势, 为指纹图谱技术在生物样品检测领域的发展和应用提供参考。

关键词

指纹图谱技术 / 效应组分 / 生物样品分析

Abstract

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Fingerprint refers to the chromatography, spectrum or other visual data that can identify the essential characteristics of certain substances or components with complex ingredients after proper processing and analysis. The analysis of effect components in biological samples is characterized by complex biological medium components, large differences in physical and chemical properties, complex and diverse metabolic reactions of effect components, and mainly trace amounts of prototypes and metabolites. Therefore, accurate and rapid determination of the effect components is of great significance. The advantages and disadvantages of each method in recent years are analyzed. The development trend of fingerprint technology in the analysis of effect components in biological samples is prospected in the future, so as to provide reference for the development and application of fingerprint technology in the field of biological sample detection.

Key words

fingerprint technology / component of effect / biological sample analysis

引用本文

杨泽荣, 刘淑琼, 钟月彤, 张国琼, 李林哲, 胡慧玲, 张美, 俞捷. 指纹图谱技术在生物样品内效应组分分析中的研究与应用进展. 药学学报, 2025 , 60 (9) : 2710 -2723 . DOI: 10.16438/j.0513-4870.2025-0242

Ze-rong YANG, Shu-qiong LIU, Yue-tong ZHONG, Guo-qiong ZHANG, Lin-zhe LI, Hui-ling HU, Mei ZHANG, Jie YU. Research and application progress of fingerprint technology in the analysis of effect components in biological samples[J]. Acta Pharmaceutica Sinica, 2025 , 60 (9) : 2710 -2723 . DOI: 10.16438/j.0513-4870.2025-0242

正文

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指纹图谱技术是依据样本的某种特性, 采用现代分析手段得到能够代表该样本特征的色谱、光谱以及其他图谱数据资料, 从而进行成分鉴定及质量控制的一种综合的、可量化的手段, 具有分析速度快、分离效能高等优点, 具备整体性、系统性、特征性、稳定性和重现性好的特点, 主要应用于生物样品分析、中药分析、食品分析、石油化工、环境监测等领域^{[1, 2]}。目前建立指纹图谱的方法有多种, 根据其特点主要分为五大类: 色谱、质谱(MS)、振动光谱法、核磁共振波谱(NMR) 和DNA条形码^[3-5]。指纹图谱评价与数据分析的方法主要有直观分析比较法、非线性映照法、主成分分析法、聚类分析法^[6]、相似度评价法、多元统计分析方法和人工神经网络^[7]等。

生物样品中效应组分是指在生物样品中能够产生影响或引起变化的化学物质或生物分子。由于生物样品具有生物介质组分复杂、理化性质差异大、效应成分代谢反应复杂种类多、原型与代谢产物微量痕量为主等特点, 因此准确快速测定其中效应组分有重要意义^{[8, 9]}。本文将对指纹图谱技术在生物样品中的应用进行阐述。

生物样品主要包括体液(血清、血浆、全血、唾液、乳汁、脑脊液、关节腔液等)、组织(胃、肝、肺、肾等)、排泄物(尿液、粪便、汗液等) 和细胞亚细胞(胞浆、线粒体) 等, 其中最常用的是血清、血浆及尿液^[10]。生物样品分析主要包括样品采集、样品前处理(预处理)、样品检测、数据分析及结果分析等几个过程, 生物样品中效应组分指纹图谱构建过程与其相似(图1)。由于生物样品组分十分复杂, 要准确测定其中所含组分, 不仅需要预处理制备好样品, 也需要一种较为准确快速的测定方法, 而指纹图谱技术包括了对已知成分和未知成分的分析, 可反映出待测组分的特有信息, 且具有高度特异性和选择性, 可充分地反映出生物样品体系中各种化学成分及分布的整体状况, 能特征性地鉴定所需要的测定组分。因此将指纹图谱技术应用到生物样品分析中具有一定的优越性^[11]。

效应组分与药效的关联主要体现在量效关系与构效关系上。量效关系通过剂量-效应曲线表达, 分为质反应和量反应; 构效关系强调药物化学结构决定其作用靶点的特异性。通常情况下, 效应组分的剂量与药效之间存在一定的量效关系。在一定范围内, 增加剂量可以增强药效, 这是因为药物浓度增加, 与作用靶点的结合机会也增多。然而, 这种关系有一个最佳剂量范围, 超出这个范围可能会导致药效降低或者产生不良反应。但某些情况下, 效应组分的剂量与药效之间可能呈非线性, 这可能是因为个体差异、时间等影响^{[12, 13]}。而谱效关系则通过指纹图谱技术构建成分指纹图谱, 结合统计学模型(回归分析、主成分分析) 建立关键成分与药效的动态关联, 整合多组学数据应对复杂性, 从而解析多组分协同作用机制, 为药物开发、监测管理、质量控制及疾病诊断提供科学依据。

本文简单介绍了生物样品分析中样品前处理技术及指纹图谱数据分析方法, 综合各生物样品分析中各指纹图谱技术的应用, 分析各技术方法的优劣, 展望今后指纹图谱技术在生物样品分析领域的发展趋势, 为指纹图谱发展提供一定参考。

1　样品前处理技术在生物样品分析中的应用

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在生物样品效应组分分析的研究过程中, 生物样品前处理是影响分析速度、分析准确性以及灵敏度的一个重要因素, 占有非常重要的地位, 由于药物在体内的存在形式不同、待测药物浓度高低不同、生物样品的成分复杂, 基质干扰严重、待测药物类型众多、理化性质各异等原因, 除了少数生物样品可经简单处理后直接测定外, 大部分样品需进行适当预处理(分离、净化、浓集或化学衍生化等) 后, 才能进行检测分析, 故测定之前需对样品采取适当的前处理, 以适应检测系统的要求, 以得到最佳的分析性能^{[14, 15]}。

目前已被广泛应用于生物样品分析检测中的样品前处理技术主要有蛋白沉淀(PP)、液液萃取法(LLE)、分散液液微萃取法(DLLME)、固相萃取法(SPE)、固相微萃取法(SPME)、分子印迹技术(MIT) 和化学衍生化技术等^{[16, 17]} (表1^[18-42])。

但也有部分生物样品采样量少、成本高等原因, 经前处理后, 可供检测的样品量所剩无几, 因此通过优化前处理过程或者通过限进材料(无需样品前处理) 直接进样检测的方法, 逐渐成为了一个研究热点。例如Liu^[43]以多巴胺(DA) 作为模板分子印迹聚合物(MIPs) 成功制成聚甲基丙烯酸缩水甘油酯-共-乙基二甲基丙烯酸酯, 实现了对尿液样品中痕量多巴胺的特异识别和灵敏测定。限进介质-分子印迹材料不仅可以特异性吸附样品中的目标成分, 还可以有效去除蛋白质大分子的干扰, 为直接从复杂样品中选择性提取和检测目标分子提供了一种改进的策略。

2　指纹图谱评价与数据分析方法

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指纹图谱评价与数据分析的方法主要有直观分析比较法、非线性映照法、主成分分析法、聚类分析法、相似度评价法、多元统计分析方法和人工神经网络等。以下对三种分析法进行简单介绍。

2.1　直观分析比较法

即将待测生物样品中效应组分的图谱与标准图谱进行直接比较, 可以直观分析所测样品中的效应组分。但这种方法缺乏量化的数据和统一的标准, 不利于生物样品指纹图谱的推广应用及规范化, 近年来已经使用甚少。

2.2　聚类分析法

聚类分析法是将一组数据(如试验数据) 在一定的算法规则下, 按照其相似性和差异性分为几个类别, 使得同一类别中的数据特征相近, 而不同类别间的数据相似性尽可能的低^[44]。将聚类分析法运用于生物样品指纹图谱分析中, 可以通过其实验组数据与模型组和正常组之间进行比较, 对生物样品中效应组分初步判断, 为后续验证提供数据支持。

2.3　多元统计分析方法

多元统计分析(又称多因素统计分析) 是定量地分析事物之间相互复杂关系的一种数理统计方法, 能够分析出多因素对最终结果的联合作用或单独作用。多元统计方法可综合体现不同因素对目标结果的影响, 将其应用于生物样品中效应组分分析, 可增加结果分析的准确性及可信度。主成分分析法是一种应用广泛的多元统计方法, 用于简化数据, 快速实现模式或关系的可视化识别^[45]。在生物指纹图谱研究中, 一般先选定几个已知化学成分的相对峰面积作为特征值, 采用主成分分析求出指标的相关矩阵特征值。

3　生物样品内效应组分分析中的指纹图谱技术

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3.1　色谱指纹图谱技术

3.1.1　高效液相色谱技术指纹图谱在生物样品分析中的应用

高效液相色谱法(HPLC) 是应用最广泛的色谱分析方法, 一般由高压输液系统、进样系统、色谱分离系统、检测系统、数据记录与处理系统组成, 目前广泛应用于生物样品分析、食品安全、环境监管等领域, 具有高精度、高灵敏度、高分离能力、专属性好等特点^{[46, 47]}。生物样品组分十分复杂, HPLC利用生物样品中待测物质组分特征峰、峰面积及其比值等进行评价。随着科技的进步与发展, 为提高其便利性与灵敏度, 现代液相色谱技术常与其他检测器(紫外检测器UV、二极管阵列检测器DAD等) 或检测技术(MS、四极杆飞行时间质谱Q-TOF-MS) 联用^[48]。通过所测效应组分相关信息, 选择合适检测器, 建立合适的方法, 可更快更准确检测出待测物质。

3.1.1.1　高效液相色谱技术指纹图谱在体液分析中的应用

HPLC指纹图谱技术在体液中的分析主要用于血清、血浆的分析, 根据所测化学物质或生物小分子物质特性, 选择恰当的前处理方式、合适的检测器, 可更快更准确检测出待测物质。Fang等^[49]利用HPLC-DAD建立了续断盐制前后HPLC指纹图谱, 得到15个共有峰, 并指认了11个成分, 检测大鼠血清中多种成分的含量变化, 比较续断盐制前后的药效差异, 为后续对盐制续断的药效成分及分子机制研究奠定了基础。Koo等^[50]建立了一种HPLC与荧光检测器(FLD) 联用检测大鼠血浆中普纳替尼的浓度, 所开发的方法在1~1 000 ng·mL^-1内具有出色的线性、灵敏度和重现性, 重要的是需要样品量极少和运行时间较短。Yuan等^[51]设计了基于顺式二醇的共价有机框架(COF), 对血清进行简单预处理, 结合UHPLC-MS/MS分析, 结果表明其中短链脂肪酸(SCFAs) 的检测灵敏度比未用COF处理的方法提高了1.2~2 500倍, 并且检测出四组大鼠血清中26种与骨质疏松症相关的SCFAs, 确定了与三羧酸循环和脂肪酸代谢途径相关的重要生物标志物。Bao等^[52]利用UPLC-Q-TOF-MS技术建立给予瓜蒌薤白(GLXB) 药物后大鼠血清指纹图谱谱效关系, 在大鼠血清中鉴定了GLXB的17种成分; 并探讨了GLXB对动脉粥样硬化的治疗机制及潜在的活性效应物。结果表明GLXB通过抑制P2RY12的活化, 激活脂吞噬作用, 抑制脂质蓄积相关的血管平滑肌细胞源性泡沫细胞形成, 从而发挥抗动脉粥样硬化作用。揭示了GLXB抗P2RY12活性效应物主要成分芍药内酯苷、芹菜素、木犀草素、山柰酚、7, 8-二羟基黄酮和橙皮素。

3.1.1.2　高效液相色谱技术指纹图谱在排泄物分析中的应用

液相色谱指纹图谱技术在尿液和粪便中相关物质的检测方面也有很好的应用。Wang等^[53]利用固相萃取与液相色谱-质谱(LC-MS) 联用的分析方法, 建立了尿液基质中10种芬太尼类物质测定方法, 为芬太尼类物质的非法滥用行为监管提供技术支持。Gao等^[54]利用电膜萃取法(EME) 处理样品, 建立了EME-HPLC联用分析羟基多环芳烃的方法, 该方法线性范围为1~500 ng·mL^-1, 检出限为0.05~0.3 ng·mL^-1。并成功应用于非吸烟者和吸烟者尿样中4种痕量羟基多环芳烃的测定, 最高浓度分别为2.24和3.56 ng·mL^-1, 相对标准偏差均小于9.4%, 该方法在生物样品中痕量羟基多环芳烃的分析中具有很好的应用前景。

3.1.1.3　高效液相色谱技术指纹图谱在其他生物样品分析中的应用

Jung等^[55]建立了HPLC联合电化学检测(ECD) 法同时测定小鼠脑组织中多种神经递质的含量。该方法灵敏度为0.02~0.1 μg·mL^-1, 线性回归系数为0.993 8~0.999 4, 平均加样回收率为97.43%~103.69%。并在一项比较对照组和东莨菪碱治疗组大脑皮质组织和海马组织的应用中, 五种成分的水平显示出明显的差异, 该指纹图谱技术有望用于各种生物和临床样本中的神经递质筛选。Liu等^[56]利用液相色谱-超高分辨质谱技术的分析方法, 采用亲水色谱和反相色谱相结合的色谱分离系统对代谢物进行分离, 可同时获取肾脏组织中的强极性和弱极性代谢物信息, 为肾脏疾病和药物肾毒性生物标志物的发现提供一种新方法。

3.1.1.4　小结

目前液相色谱技术已经被广泛用于生物样品分析中, 利用HPLC指纹图谱技术可以检测鉴别不同类型生物样品中的待测组分, 有利于对待测组分的进一步探索提供依据, 但它也存在一些不足, 如存在柱外效应、对样品的纯度要求较高, 通常需要经过复杂的前处理过程才能进样等。随着材料化学的发展, 多种新型材料(共价有机框架材料COFs、金属有机骨架化合物MOFs等) 被开发为其固定相, 提高了其专属性和灵敏度等, 此外, 还常与TOF或Q-TOF等质谱检测器、电雾式检测器(CAD)、DAD检测器等联合使用, 能够识别非典型样本, 并结合日益强大的采集数据库进行更准确的分析, 极大地促进了复杂体系中多组分分析的发展。

3.1.2　气相色谱技术指纹图谱在生物样品分析中的应用

气相色谱法(gas chromatography, GC) 是一种适合微量或痕量分析, 与高效液相指纹图谱同为应用最为广泛的色谱指纹图谱技术, 该方法具有分析速度快、分离效率高、选择性好、灵敏度高的特点, 目前气相色谱技术主要应用在生物样品检测、石油化工、环境监测、医药检测及食品安全等领域^{[57, 58]}。

3.1.2.1　气相色谱技术指纹图谱在体液分析中的应用

Guo等^[59]采用顶空进样气相色谱联用质谱法的方法测定血浆中甲酸含量, 用于正常人群甲酸本底水平和甲醇暴露人群血中甲酸浓度的测定。Zhang等^[60]建立了固相萃取-气相色谱同时检测人血浆中草甘膦(GLY) 和氨甲基膦酸(AMPA) 浓度的方法, 能够满足GLY中毒患者血浆中GLY和AMPA浓度检测需求。

3.1.2.2　气相色谱技术指纹图谱在排泄物分析中的应用

气相色谱技术指纹图谱在排泄物分析中主要用于脂肪酸的测定, 本节主要从脂肪酸的测定方法改进方面进行总结。

在过去的十年中, 肠道菌群已成为了解人体体内平衡和疾病发展的重要前沿。人体肠道菌群调节各种代谢功能, 包括酶、氨基酸合成及短链脂肪的产生酸, SCFAs具有多种有益作用, 如改善代谢功能、抑制胰岛素抵抗和改善免疫功能障碍。短链脂肪酸作为肠道菌群的代谢产物已被证实参与宿主的能量代谢, 已成为预测肥胖、糖尿病等代谢性疾病的生物标志物。因此, 如何精准有效测定短链脂肪酸的水平, 对临床疾病的病症进行有效的预判或诊断已成为科学家研究的重点^{[61, 62]}。

Wang等^[63]开发一种用甲酸预处理的快速GC方法, 用于大鼠血浆中的SCFAs定量。在短时间内, 实现了三种SCFA (乙酸、丙酸和丁酸) 基线色谱分离。但所检测出的SCFAs种类较少, 随着气相色谱-质谱联用的普及, 实现了多种脂肪酸的鉴定分离。Fu等^[64]利用衍生化-固相微萃取-气相色谱-质谱联用, 以氯甲酸异丁酯与异丁醇为衍生化试剂, 顶空固相微萃取为提取技术, GC-MS为分析仪器, 同时测定11种SCFAs, 具体流程如图2所示。方法验证表明, 该方法具有良好的线性度、灵敏度、准确度、精密度、稳定性、重复性, 适用于粪便样品中SCFAs的测定。并将所建立的方法成功地应用于小鼠粪便样品中, 在小鼠粪便中发现了10种SCFAs, 其中包括甲酸。

衍生化试剂多数需要在无水条件下进行, 且操作繁琐, 故有研究者建立了无需衍生的方法进行检测, 且该方法可靠快速, Rohde等^[65]利用GC-MS方法, 无需衍生化, 采用琥珀酸酸化, 乙醇提取SCFAs, 碱性真空离心浓缩, 用于定量不同生物基质中的SCFAs监测, 从而研究SCFAs在代谢健康中的生(病) 理作用, 有助于补充SCFAs介导的全身(病理) 生理反应的复杂图景。Zhu等^[66]也利用GC-MS进行检测, 采用50%盐酸酸化和乙醚立即提取, 检测采用多反应监测扫描模式, 能够同时定量测定大鼠粪便中甲酸等10种短链脂肪酸, 无需柱前衍生化。

3.1.2.3　气相色谱技术指纹图谱在其他生物样品分析中的应用

本课题组^[67]通过GC-MS的分析方法首次从组织(肝脏、脾脏、肾脏、肺、胰腺、心脏) 样本中检测出5种SCFAs (乙酸、丙酸、异丁酸、丁酸、戊酸), 在后续进展中, 又建立了高通量固相萃取-气相色谱-质谱分析方法用于生物样品中SCFAs半定量分析, 为SCFAs的测定提供了一种新的方法。Wu等^[68]通过对样本前处理条件和色谱分离条件进行优化, 建立了测定肝脏中39种脂肪酸组成和含量的GC-MS方法, 并将其应用于健康和全氟辛烷磺酸(PFOS) 暴露SD大鼠肝脏中脂肪酸的检测。该方法操作简便, 试剂及样品用量少, 灵敏度高, 能检测出种类更多的脂肪酸, 并能有效分离顺反式同分异构体脂肪酸, 改善了现有的检测方法存在样本消耗量大、检测出的脂肪酸种类少等缺点, 为肝脏中脂肪酸的检测及研究提供了很好的方法, 也为其他组织中脂肪酸的检测提供了参考方法。

3.1.2.4　小结

气相色谱法在生物样品分析中主要用于检测一些挥发性物质, 如乙醇、挥发性有机物(VOCs)、脂肪酸类物质等。目前在生物样品中短链脂肪酸的测定相关研究最为广泛, 中长链脂肪酸及其他挥发性效应组分在人体中也扮演着重要角色, 但相关应用较少, 期望后续研究中能有更多方法或材料同时测定或提取所测效应组分, 通过气相色谱指纹图谱技术进行检测。

气相色谱也存在一定的局限: 在没有标准品条件下, 对试样中未知物的定性和定量较为困难, 往往需要与质谱、红外光谱等结构分析仪联合使用; 对沸点高、热稳定性差、腐蚀性和反应活性较强的物质, 气相色谱分析也比较困难。气相色谱与各种检测器及各种进样技术联用, 在一定程度上弥补了其不足, 各有其特点(表2^{[58, 69-72]})。

3.1.3　其他色谱技术指纹图谱在生物样品分析中的应用

超临界流体萃取(SFC) 技术基本原理是通过将某种超临界状态下的流体溶剂, 与固体混合物或液体混合物进行接触融合, 并通过其特殊性质, 将原有固体或液体混合物进行分离, 最后通过减压或升温等方式对分离物进行萃取^[73]。不饱和脂肪酸(UFAs) 在生物系统中起着重要的作用, 因为它们在某些细胞过程中是必不可少的, 双键的位置对于了解它们的生物功能非常重要。然而, 由于UFAs之间的结构相似性和这些键的稳定性, 确定UFAs中双键的位置是具有挑战性的^[74]。为解决这一问题, Chen等^[75]开发了一种新的在线SFC-PB-Q-TOF-MS快速识别和鉴定UFAs中C=C位置的方法, 以苯甲醛(BA) 为光化学反应试剂, 该方法具有转化率高的优点, 还具有良好的重现性、样品适用性、灵敏度和与质谱的良好兼容性。并将该方法应用于人血浆中游离脂肪酸的特异性识别, 成功地提供了UFAs异构体的定量信息, 有望用于复杂生物样品中不饱和脂肪酸异构体的分析。

毛细管电泳(CE) 又称高效毛细管电泳(HPCE), 是一类以毛细管为分离通道, 以高压直流电场为驱动力的一种高效快速分离新型液相分离技术^[76]。其以分析速度快、所需样品量低、通用性强等优势, 广泛应用于医药、食品、环境等领域当中, 逐渐成为复杂生物样本中的痕量组分的定性分析和定量分析的强有力工具^[77]。Štícha等^[78]报道了CE-二极管阵列检测器与CE-ESI-MS法测定血浆样品中利奥西呱和代谢物M1。采用局部线性嵌入算法(LLE) 进行样品清理和分析物预浓缩, 在这两种方法下, 分析物都可很好地分离。

目前在生物样品分析中常用的色谱检测技术是液相色谱法和气相色谱法, 其他色谱指纹图谱技术在生物样品分析中也有所应用, 比如薄层色谱技术指纹图谱^[79]、高速逆流色谱技术指纹图谱等。但由于其自身灵敏度低、专属性不强或成本较高等限制, 应用较少, 希望通过仪器优化改变其限制, 利用自身优势, 在生物样品效应组分分析中发挥重要作用。

3.2　质谱指纹图谱技术

质谱技术是一种通过测量样品离子的质量和强度进行定性、定量和结构分析的方法, 具有超高的灵敏度、超快的响应速度和高特异性等优点, 已广泛应用于众多研究领域, 除了上述, 质谱技术常与HPLC、GC等联用外, 也可以在简单的样品前处理或在无需样品预处理的前提下, 实现复杂基质样品的直接质谱分析, 极大地提高了复杂基质样品分析的通量。通过十余年的快速发展, 质谱技术已取得了令人瞩目的进展, 在诸多领域展开了广阔的应用研究^[80]。

Jiang等^[81]建立了一个可靠的方法对高危人群进行肝癌筛查的液体活检, 该方法以多孔硅辅助激光解吸电离质谱(PSALDI-MS) 技术, 以高通量的方式分析隐藏在人血清中的代谢物信息。血清代谢物可以被捕获在氨丙基三乙氧基硅烷(APTES) 修饰的多孔硅颗粒的孔道中, 并在储存或运输过程中得到良好的保存。然后直接在激光解吸离子化质谱(LDI-MS) 上检测, 无需添加有机基质, 从而大大加快了血清样品代谢指纹的获得。该方法具有高通量(每96个样品5 min)、高重现性(变异系数 < 15%)、灵敏度高等特点。在一项多中心队列研究中, 1 433名受试者包括健康对照(HC)、慢性乙型肝炎(CHB)、肝硬化在PSALDI-MS平台上进行非靶向血清代谢物组学分析, 选择特征代谢物后, 通过机器学习算法构建肝病分期分级的逐步诊断模型, 外测HC准确率为91.2%, 化学计量学方法对慢性乙型肝炎、肝硬化和肝癌的诊断率分别为71.4%、70.0%和95.3%, 操作流程及模型建设如图3所示。初步研究表明, 基于血清代谢指纹图谱构建的诊断模型在前瞻性观察中也显示出良好的预测性能, 为PSALDI-MS技术与机器学习的结合成为临床应用的有效工具提供有力支撑。Shi等^[82]采用席夫碱缩合反应在钢针上原位合成了一种共价有机骨架(TAPB-DMTP-COF), 并将其作为固相微萃取纤维, 利用其优异的比表面积和高度规整的孔隙率, 建立了一种检测限低(0.03 μg·L^-1)、线性良好(R² ≥ 0.993 1)、重现性好的基于TAPB-DMTP-COF的固相微萃取和电喷雾质谱方法, 该方法成功地应用于三氯生(TCS) 诱导肝损伤模型组小鼠肝脏和粪便中胆汁酸的分析, 结果表明, TAPB-DMTP-COF-SPME-ESI/MS法用于生物样品中胆汁酸含量的监测和分析具有良好的可靠性和适用性, 同时也证实了TCS可引起生物体的严重肝损伤和胆汁酸代谢紊乱。直接质谱测定避免了耗时的色谱分离过程, 实现了步骤简单、分析周期短的目标, 满足了实验室对样品的快速、原位分析的要求^[83]。

质谱技术应用于生物样品中效应组分的分析中起着至关重要的作用。质谱技术可以用来识别和定量生物样品中的化合物, 特别是那些在生物体内起着重要生物学作用的效应组分, 并且随着高分辨质谱技术的发展及大数据模型的建立, 其灵敏度与分辨率均得到极大的提升, 无论与液相、气相等设备联用, 还是单独使用, 都将有极大提升。

3.3　光谱特性的图谱技术

3.3.1　拉曼光谱技术指纹图谱在生物样品分析中的应用

拉曼光谱法源自对拉曼散射原理的应用, 当激发激光的波长接近分析物的最大吸收带, 拉曼散射强度显著增强, 称为共振拉曼光谱。拉曼光谱指纹图谱技术具有无须样品前处理、非破坏性检测、高可靠性、高灵敏度、高分辨率和适用性广等优点。目前已被广泛用于生物样品分析、中药鉴定、食品安全检测、环境监测及法庭科学等领域^[84-86]。

拉曼光谱法在生物样品效应组分中的应用主要用于一些疾病(肝脏疾病、子宫内膜癌等) 标志物的检测。Zhang等^[87]利用人工智能辅助的表面增强拉曼光谱鉴定了与肝损伤相关的新型分子指纹图谱, 如图4所示。以聚乙二醇修饰的球形金纳米颗粒用作体内计算机断层摄影造影剂, 通过静脉内注射, 使其有效地积累在肝脏中, 特异性地描绘正常和受损肝脏组织的三维结构。金纳米颗粒作为拉曼增强基底, 可以分析富集了金纳米颗粒的肝组织中表面增强拉曼光谱(SERS) 信号, 利用人工智能技术, 对不同程度的肝损伤的分类准确率达到96.45%。分子光谱分析表明, 1 437~1 000 cm^-1信号的比值可以作为与肝损伤相关的SERS指纹, 建立的信息系统为肝脏疾病的精确诊断提供了有价值的工具。Ma等^[88]以碘离子和钙离子修饰的银纳米粒子为拉曼增强基底, 首次在无标记的情况下同时捕获了上皮间质转化(EMT) 相关靶点microRNA-200a-3p和ZEB1的指纹图谱, 具有较高的灵敏度(4.5 pmol·mL^-1、10 ng·mL^-1) 和稳定性, 为阐明子宫内膜癌相关EMT靶点的分子机制、鉴定恶性程度等的生物标志物具有巨大潜力。Gu等^[89]提出了一种多波长SERS方法结合基于机器学习(ML) 的分类, 以提高膀胱癌诊断的人类尿液样本的判别准确性。通过在多个激发波长下捕获SERS指纹, 可以获得复杂样品更全面、独特的化学信息。在ML算法的支持下, 对临床尿液样本的进一步实验检查证明了这种多波长策略的有效性, 并提高了膀胱癌的诊断准确性。拉曼光谱也常用于早期肺癌患者的诊断, Lu等^[90]利用表面增强拉曼光谱技术对DNA甲基化实现常规表征, 用来鉴定早期肺癌患者。研究获取106例患者组织切片(包括65例早期肺癌患者和41例良性疾病患者) 的SERS信息, 提取基因组DNA的甲基化模式, 利用结合偏最小二乘判别分析, 结果显示良性疾病组的甲基化水平高于早期肺癌组。这也表明利用DNA甲基化差异的SERS分析与机器学习方法可能为肺癌患者的早期检测提供一条重要的新途径。

拉曼光谱法技术相对于传统技术的优势, 如最小化样品制备、实时能力和非破坏性, 使其在生物样品效应组分分析检测中展现出广阔的应用前景。随着大型语言模型的发展, SERS与机器学习的集成将增强其诊断潜力, 使生物标志物发现和各疾病的个性化预防治疗策略成为可能, 为实验研究提供了更多可能性, 但也存在一定的局限性: 弱拉曼信号和光谱复杂性、拉曼检测样本的标准和相关操作技术还不够成熟等, 未来还有很大的发展空间。

3.3.2　其他光谱技术指纹图谱在生物样品分析中的应用

红外光谱图(IR) 是利用测量样品在红外区段的吸收光谱来确定其分子结构, 具有无损、快速、特征性强、仪器操作简便、环保等优点, 已被广泛应用于诸多领域^{[91, 92]}。Nadeem等^[93]利用近红外荧光光谱指纹技术与机器学习算法, 通过支持向量机(SVM) 模型对单壁碳纳米管(SWCNT) 荧光数据进行训练, 可以准确识别M1和M2巨噬细胞, 准确率超过95%。这项技术有助于实时监测生命系统中的细胞行为, 为基础研究和临床应用提供参考。Keung等^[94]利用傅里叶变换红外光谱技术分析克罗恩病患者组织样本, 成功识别出预测抗肿瘤坏死因子-α治疗反应的生物标志物, 检测到了纤维化狭窄性克罗恩病组织的生化“指纹”, 这些指纹在预测阿达木单抗治疗临床反应方面表现出极佳的区分能力。Kepesidis等^[95]利用振动光谱分子指纹技术对肺癌进行了探测, 确定了基于血液红外光谱的无创技术可以有效地预测肺癌进展和患者生存率, 节省了成本和时间, 为肺癌的诊断和预后评估提供了新的思路。

等离子体光谱(ICP) 是与上述指纹图谱技术有所不同, 主要用于生物样品中微量元素的检测, 具有检出限低、精密度高、基体效应小等特点, 目前已经广泛应用在生物、药物、食品等领域^[96]。Xiao等^[97]建立了微波消解–电感耦合等离子体发射光谱法同时测定生物样品中12种元素的分析方法, 经方法学验证, 能够满足生物样品分析要求。该方法适合大批量生物样品的多元素同时分析, 对生态地球化学调查研究具有重要的意义。

3.4　核磁共振波谱技术指纹图谱技术

核磁共振波谱技术是一种用于研究分子结构和相互作用的技术。它基于原子核在外加磁场和射频辐射作用下发生共振吸收的原理。通过对核磁共振信号的分析, 可以确定分子的结构、组成和动力学信息。核磁共振波谱技术能在较少样品预处理情况下, 提供定量及可重现的信息, 因此被广泛用于生物样品分析、毒理学、药理学、疾病检测、功能基因组学、食品及营养科学等领域^{[98, 99]}。

Beckonert等^[100]综述了核磁共振用于生物体液、组织样及细胞萃取液中的多组分分析的代谢组学指纹分析和代谢组学研究, 阐述了NMR技术在现代代谢组学中的应用, 并介绍了生物体液(尿样、血清、血浆) 及组织样品制备的详细步骤。Specht等^[101]提出了一种基于标准核磁共振实验对未知样本进行群特异性定性和定量分析的方法。通过机器学习算法分析13C、1H和13C DEPT NMR光谱, 无需专业知识就可以识别和定量混合物中的结构单元。方法通过训练大量纯组分NMR光谱数据, 实现了对混合物中结构单元的准确预测。经测试自动NMR指纹识别的结果与基于样品的重量制备所知的真实情况非常吻合。该方法为过程监控以及过程和质量控制开辟了新的途径。Vignoli等^[102]利用非靶向核磁共振谱的代谢组学方法, 根据临床图像和脑脊液阿尔茨海默病(AD) 核心生物标志, 在痴呆前期和痴呆期以及一组脑脊液(CSF) 生物标志物正常(非AD) 的患者中, 构建AD患者脑脊液代谢组学指纹。该研究表明, 基于核磁共振的指纹图谱可能提供新的见解, 有助于改善目前对出现CSF AD核心生物标志物(Aβ₄₂、t-tau、p-tau) 改变的受试者的认识, 有利于对该疾病发展趋势的控制。

核磁共振波谱学分析方法的主要特点包括: 实验方法的多样性和灵活性、对待测样品的非破坏性和非侵入性。如何充分发挥NMR的这些特性, 利用NMR开发出新方法用于直接分析和研究复杂生物样品的组成、相互作用及其中效应组分的探索, 将为人类健康事业的发展添加一份新保障。

3.5　生物标志特性的指纹图谱技术

与上述指纹图谱不同, 生物标志指纹图谱的构建是基于生物大分子(蛋白质、核糖核酸、脱氧核糖核酸等) 特征序列的不同, 以可见的电泳条带方式呈现生物个体的差异。目前在生物样品分析中主要以DNA指纹图谱技术(DNA条形码) 为主。

DNA指纹图谱技术是将个体的染色体DNA用限制性内切酶消化, 分离得到不同大小的DNA片段, 再以重复序列中的共有序列作为核酸探针进行杂交, 对所得到不同生物个体相似DNA片段的带型图谱(即DNA指纹图谱, 每一个体都是独特的) 进行分析的方法^[103]。Gonçalves等^[104]为了确定早期肝细胞癌(HCC) 的可靠诊断生物标志物, 提出了一个全面的HCC早期生物标志物的测定方法, DNA甲基化指纹图谱和相关的风险评分, 用于从组织和液体活检中检测HCC。

生物标志指纹图谱在生物样品分析中, 目前应用较少, 但随着生物标志物指纹图谱技术的实验技术和统计方法的不断发展和改进, 期待生物指纹图谱技术在生物样品分析中实现广泛应用, 乃至整个生物领域得到更加广泛的应用。

4　结语与展望

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生物样品指纹图谱作为一种综合的定性、定量分析手段, 较为全面地反映了生物样品中效应组分组成及含量分布, 可作生物分析领域的重要技术手段, 在药物质量和生物学研究中发挥着重要作用。对于给药生物样品, 能够提供一种有效的药物质量控制和分析方法, 通过构建指纹图谱, 可以获得药物在生物样品中的特征信息, 从而对其进行准确的定量和定性分析。这对于药物的疗效评估、安全性评价和质量控制等方面都非常重要。同时通过药物在生物样品中化学成分进行分析, 获得生物样品中药物的特征指纹图, 用于药物的鉴别、含量测定、药代动力学研究等方面也有着重要意义。另外生物样品指纹图谱的构建有利于疾病的诊断, 通过生物样品指纹图谱中的分子标记可能具有生物学功能, 可以作为生物标志物用于疾病诊断、疗效监测以及生物活性物质的研究。

基于检测仪器的各类指纹图谱构建技术各有其优缺点, 在具体应用过程中, 各自的适用范围亦不尽相同, 需要结合具体研究目标和应用条件进行选择。目前液相和气相色谱指纹图谱技术在生物样品分析中应用最为广泛, 其他指纹图谱技术受其特点影响应用有所限制, 结合不同检测器, 可更快更准确检测所测效应组分。生物样品指纹图谱在药物质量控制、药代动力学研究及疾病诊断等方面发挥着独特作用。通过联合使用不同检测器(如质谱检测器、CAD检测器等), 可显著提升分析准确性, 弥补单一设备的不足。随着AI技术的发展, 通过机器学习, 构建模型, 推动生物样品分析从传统手段向智能化方向迈进, 为药物监测管理、质量控制及疾病诊断提供科学依据。然而, 联合技术的应用仍面临较高门槛和工艺优化需求, 未来有望进一步拓展其应用范围, 助力人健康可持续发展。

随着高通量技术和新传感器的发展, 指纹图谱构建也将更加高效、准确。这些技术将进一步提升生物样品分析的科学性和实用性, 为药物管理和疾病诊断等提供有力支撑。

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2025年第60卷第9期

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doi: 10.16438/j.0513-4870.2025-0242

接收时间：2025-03-05
首发时间：2026-09-20
出版时间：2025-09-12

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收稿日期：2025-03-05
修回日期：2025-06-26

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云南中医药大学, 中药学院暨云南省南药可持续利用研究重点实验室, 云南昆明 650500

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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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TxT

Method	Biological sample	Reagent	Testing method	Testing substance	Advantage	Insufficient	Ref.
Protein precipitation (PP)	Plasma from rats	Acetonitrile	LC-MS/MS	Strychnine	The operation is simple, and the cost is low.	The impurity is relatively high, and the content determination is not accurate.	[18]
Plasma from rats, brain tissue	Acetonitrile	LC-MS/MS	Dexamethasone	[19]
Plasma from rats	Methanol	HPLC-FL	Scopolamine	[20]
Human blood, urine	Methanol	HPLC-Orbitrap MS	Plant toxins	[21]
Plasma from rats	Acetonitrile	UHPLC-HESI-LTQ-MS	Doxorubicin and lapatinib	[22]
Human blood	Methanol	UHPLC-MS/MS	Digoxin	[23]
Liquid-liquid extraction (LLE)	Human blood	Methyl tert-butyl ether	LC-MS/MS	Digoxin	The extraction range is wide, the operation is simple, and the cost is low.	The usage dosage of organic reagents is comparatively high, making automation difficult.	[24]
Human blood, urine	Methyl tert-butyl ether	GC-MS/MS	SCFAs	[25]
Plasma from rats	Methanol	GC-MS	Ganoderic acid H	[26]
Dispersive liquid-liquid microextraction (DLLME)	Human blood	Tetrachloroethylene-methanol	DLLME-IMS	Gabapentin	Low solvent consumption, short extraction time, and high enrichment factor.	The selection range of the extractant is relatively narrow.	[27]
Human serum	Formic acid-ethyl acetate-acetonitrile	GC-MS	HPAHs	[28]
Solid phase extraction (SPE)	Human serum	-	LC-MS/MS	Methotrexate and its metabolites	Time-saving and efficient, it can reduce reagent and sample loss.	Longer extraction time and lower selectivity.	[29]
brain tissue	-	SPME-UPLC-MS/MS	Nicotine and its metabolites	[30]
Solid-phase microextraction (SPME)	Human blood	-	SPME-PESI-MS/MS	Fentanyl	Simple operation, high throughput, low use of organic solvents, easy automation, green.	The equipment used is expensive and fragile, its specificity needs to be improved, and it cannot be used for macromolecular substances and large-scale extraction.	[31]
Human blood	-	LC-APCI-MS/MS	Isoflurane	[32]
Bone marrow	-	LC-TOF-MS/MS	Benzodiazepine drugs	[33]
Blood	-	HPTLC	Zomepirac	[34]
Tissue	-	DART-MS	Animal medicine	[35]
Hair	Acetonitrile	HPLC	Codeine and morphine	[36]
Microdialysis (MD)	Brain tissue	-	HPLC	Andrographolide	Real-time, online, and dynamic monitoring of the same organism can be achieved.	Not applicable to drugs with a short half-life and those with high lipid solubility; membranes are prone to blockage.	[37]
Aqueous humor	-	HPLC-MS/MS	Tartaric acid bromo-monie	[38]
Molecular imprinting technology (MIT)	Brain tissue	-	LC-MS/MS	Aminopyridinoic acid	The specificity is relatively high.	The functionality of the monomer is singular, and the recognition limitations are considerable.	[39]
Supercritical fluid extraction (SFE)	Plasma from rats	-	PTT-SFEC-MS/MS	Lipids	The extraction efficiency is high, the extraction efficiency and selectivity are high, it saves time, and there is less environmental pollution.	The cost is high.	[40]
Chemical derivatization technology	Plasma from rats, urine, brain tissue	5-DMISC	LC-MS/MS	Phenol	There are many choices for derivatization reagents.	The derivation operations are cumbersome and subject to strict conditions.	[41]
Purge and trap	Human urine	201-Dimethyl silicone oil	GC-MS	Acetone	High sensitivity, low detection limit.	It takes a long time and can easily damage the instruments.	[42]

Method

Biological sample

Reagent

Testing method

Testing substance

Advantage

Insufficient

Ref.

Protein precipitation (PP)

Plasma from rats

Acetonitrile

LC-MS/MS

Strychnine

The operation is simple, and the cost is low.

The impurity is relatively high, and the content determination is not accurate.

[18]

Plasma from rats, brain tissue

Acetonitrile

LC-MS/MS

Dexamethasone

[19]

Plasma from rats

Methanol

HPLC-FL

Scopolamine

[20]

Human blood, urine

Methanol

HPLC-Orbitrap MS

Plant toxins

[21]

Plasma from rats

Acetonitrile

UHPLC-HESI-LTQ-MS

Doxorubicin and lapatinib

[22]

Human blood

Methanol

UHPLC-MS/MS

Digoxin

[23]

Liquid-liquid extraction (LLE)

Human blood

Methyl tert-butyl ether

LC-MS/MS

Digoxin

The extraction range is wide, the operation is simple, and the cost is low.

The usage dosage of organic reagents is comparatively high, making automation difficult.

[24]

Human blood, urine

Methyl tert-butyl ether

GC-MS/MS

SCFAs

[25]

Plasma from rats

Methanol

GC-MS

Ganoderic acid H

[26]

Dispersive liquid-liquid microextraction (DLLME)

Human blood

Tetrachloroethylene-methanol

DLLME-IMS

Gabapentin

Low solvent consumption, short extraction time, and high enrichment factor.

The selection range of the extractant is relatively narrow.

[27]

Human serum

Formic acid-ethyl acetate-acetonitrile

GC-MS

HPAHs

[28]

Solid phase extraction (SPE)

Human serum

LC-MS/MS

Methotrexate and its metabolites

Time-saving and efficient, it can reduce reagent and sample loss.

Longer extraction time and lower selectivity.

[29]

brain tissue

SPME-UPLC-MS/MS

Nicotine and its metabolites

[30]

Solid-phase microextraction (SPME)

Human blood

SPME-PESI-MS/MS

Fentanyl

Simple operation, high throughput, low use of organic solvents, easy automation, green.

The equipment used is expensive and fragile, its specificity needs to be improved, and it cannot be used for macromolecular substances and large-scale extraction.

[31]

Human blood

LC-APCI-MS/MS

Isoflurane

[32]

Bone marrow

LC-TOF-MS/MS

Benzodiazepine drugs

[33]

Blood

HPTLC

Zomepirac

[34]

Tissue

DART-MS

Animal medicine

[35]

Hair

Acetonitrile

HPLC

Codeine and morphine

[36]

Microdialysis (MD)

Brain tissue

HPLC

Andrographolide

Real-time, online, and dynamic monitoring of the same organism can be achieved.

Not applicable to drugs with a short half-life and those with high lipid solubility; membranes are prone to blockage.

[37]

Aqueous humor

HPLC-MS/MS

Tartaric acid bromo-monie

[38]

Molecular imprinting technology (MIT)

Brain tissue

LC-MS/MS

Aminopyridinoic acid

The specificity is relatively high.

The functionality of the monomer is singular, and the recognition limitations are considerable.

[39]

Supercritical fluid extraction (SFE)

Plasma from rats

PTT-SFEC-MS/MS

Lipids

The extraction efficiency is high, the extraction efficiency and selectivity are high, it saves time, and there is less environmental pollution.

The cost is high.

[40]

Chemical derivatization technology

Plasma from rats, urine, brain tissue

5-DMISC

LC-MS/MS

Phenol

There are many choices for derivatization reagents.

The derivation operations are cumbersome and subject to strict conditions.

[41]

Purge and trap

Human urine

201-Dimethyl silicone oil

GC-MS

Acetone

High sensitivity, low detection limit.

It takes a long time and can easily damage the instruments.

[42]

Instrument	Principle	Advantage	Data analysis	Detection range	Application	Ref.
GC-MS/MS	The sample is separated by chromatographic columns, and under ionization in the ion source, it produces ion fragments with a certain charge.	Use of no or minimal solvent, easy to automate, simple operation, high sensitivity, and a well-established database.	Qualitative and quantitative analysis	Volatile substances	Environmental monitoring field; metabolomics; traditional Chinese medicine industry; et al.	[58, 69]
HS-SPME-GC-MS	The adsorption of volatile compounds into the chromatographic column is carried out in a vacuum using adsorptive molten quartz fibers.	Solvent-free, easy to operate, high sensitivity, no sample pre-treatment required, low cost, and a well-established database.	Qualitative and quantitative analysis	Volatile substances	Food quality evaluation; environmental monitoring	[70]
GC-IMS	Based on the separation of volatile organic compounds in the gas chromatography column and the ionization and movement of those compounds in the ion mobility spectrometry.	The reaction speed is fast, the operation is simple, no sample pre-treatment is required, it can be performed under normal pressure, and the treatment efficiency is high.	Qualitative and quantitative analysis	Volatile substances	Food varieties; origin tracing; food quality evaluation	[71, 72]

Instrument

Principle

Advantage

Data analysis

Detection range

Application

Ref.

GC-MS/MS

The sample is separated by chromatographic columns, and under ionization in the ion source, it produces ion fragments with a certain charge.

Use of no or minimal solvent, easy to automate, simple operation, high sensitivity, and a well-established database.

Qualitative and quantitative analysis

Volatile substances

Environmental monitoring field; metabolomics; traditional Chinese medicine industry; et al.

[58, 69]

HS-SPME-GC-MS

The adsorption of volatile compounds into the chromatographic column is carried out in a vacuum using adsorptive molten quartz fibers.

Solvent-free, easy to operate, high sensitivity, no sample pre-treatment required, low cost, and a well-established database.

Qualitative and quantitative analysis

Volatile substances

Food quality evaluation; environmental monitoring

[70]

GC-IMS

Based on the separation of volatile organic compounds in the gas chromatography column and the ionization and movement of those compounds in the ion mobility spectrometry.

The reaction speed is fast, the operation is simple, no sample pre-treatment is required, it can be performed under normal pressure, and the treatment efficiency is high.

Qualitative and quantitative analysis

Volatile substances

Food varieties; origin tracing; food quality evaluation

[71, 72]