超高效液相色谱-四极杆/静电场轨道阱质谱快速测定保健食品中13种β-受体阻滞剂

doi:10.3724/SP.J.1123.2023.06006

摘要/Abstract

摘要：

建立了基于超高效液相色谱-四极杆/静电场轨道阱质谱快速测定保健食品中13种β-受体阻滞剂的分析方法,并对其质谱裂解规律进行了分析研究。实验对质谱条件、色谱条件、提取溶剂及基质效应等进行了详细探究,使用甲醇对样品进行稀释提取,高速离心、超声处理,用Acquity UPLC BEH C18柱(100 mm×2.1 mm, 1.7 μm)分离,以乙腈和0.1%(v/v)甲酸水溶液作为流动相进行梯度洗脱,采用正离子模式检测,数据采集使用一级母离子全扫描和数据依赖的二级离子扫描(Full MS/dd-MS²)模式,在10 min内实现了保健食品中13种β-受体阻滞剂的分离和高精度一级、二级扫描,得到准确的质量数和准确碎片离子信息。通过方法学验证,13种β-受体阻滞剂在0.5~100 μg/L内线性关系良好,相关系数(r)均≥0.9912,检出限为1~10 μg/kg。空白加标样品中13种β-受体阻滞剂的平均回收率为75.3%~108.4%,相对标准偏差为0.9%~10.0%(n=6)。用本方法对市售的30批次保健食品进行筛查,均未检出13种β-受体阻滞剂。该方法检测速度快,准确性强,灵敏度高,可用于保健食品中β-受体阻滞剂的快速测定。

关键词: 超高效液相色谱-四极杆/静电场轨道阱质谱法, β-受体阻滞剂, 保健食品

Abstract:

A method based on ultra performance liquid chromatography-quadrupole/electrostatic field orbitrap mass spectrometry was developed for the rapid determination of 13 β-blockers in health foods. The MS fragmentation pathways of the analytes were subsequently investigated. The optimal MS conditions, extraction solvents, mobile phases, and matrix effects were evaluated in detail. The samples were extracted with methanol, filtered by high-speed centrifugation and ultrasonic treatment, and then separated on an Acquity UPLC BEH C18 column (100 mm×2.1 mm, 1.7 μm) with gradient elution using acetonitrile and 0.1% (v/v) formic acid aqueous solution as mobile phases. MS analysis was conducted in positive-ion mode, and the data were collected using full mass and data-dependent MS² scans (Full MS/dd-MS²). The efficient separation and high-precision primary and secondary scanning of the 13 β-blockers in health foods were realized within 10 min, and accurate mass numbers and fragment-ion information were obtained. The methodological validation showed good linear relationships in the range of 0.5-100 μg/L, with correlation coefficients (r)≥0.9912. The limits of detection ranged from 1 to 10 μg/kg. When the standard substances were added to the blank sample in the amount of 10-200 μg/kg, the recoveries were in the range of 75.3%-108.4%, and the relative standard deviations ranged from 0.9% to 10.0% (n=6). The method was used to screen 30 batches of commercially available health foods, and none of the 13 β-blockers was detected. The proposed method is fast, accurate, and sensitive, and can be used for the rapid determination of β-blockers in health foods.

Key words: ultra performance liquid chromatography-quadrupole/electrostatic field orbitrap mass spectrometry, β-blockers, health foods

中图分类号:

O658

李彤辉, 冯峰, 申一鸣, 张峰. 超高效液相色谱-四极杆/静电场轨道阱质谱快速测定保健食品中13种β-受体阻滞剂[J]. 色谱, 2023, 41(11): 1030-1037.

LI Tonghui, FENG Feng, SHEN Yiming, ZHANG Feng. Rapid determination of 13 β-blockers in health foods by ultra performance liquid chromatography-quadrupole/electrostatic field orbitrap mass spectrometry[J]. Chinese Journal of Chromatography, 2023, 41(11): 1030-1037.

图/表 7

参考文献

[1]	Chen D Y, Zhang H, Feng J L, et al. Chinese Journal of Chromatography, 2020, 38(8): 880
[1]	陈东洋, 张昊, 冯家力, 等. 色谱, 2020, 38(8): 880
[2]	Zhou Y L, Xi Z, Kang J, et al. Journal of Food Safety and Quality, 2022, 13(9): 2908
[2]	周亚兰, 席彰, 康靖, 等. 食品安全质量检测学报, 2022, 13(9): 2908
[3]	Sung I K, Park S J, Karig K, et al. Korean J Food Sci Anim Resour, 2015, 135(1): 121
[4]	Regal P, Monica D B, Rocio B, et al. Food Addit Contam, 2017, 34(4): 10
[5]	Cao Y C, Feng Y X. Journal of Huaihai Medicine, 2019, 39(6): 659
[5]	曹永春, 冯燕娴. 淮海医药, 2019, 39(6): 659
[6]	Fan W S, Zhang L, Zhu J K, et al. Occupation and Health, 2023, 39(7): 904
[6]	范雯谡, 张蕾, 朱吉凯, 等. 职业与健康, 2023, 39(7): 904
[7]	Yue H X, Lei W, Du X N, et al. Journal of Chinese Mass Spectrometry Society, 2018, 39(1): 61
[7]	岳韩笑, 雷雯, 杜晓宁, 等. 质谱学报, 2018, 39(1): 61
[8]	Liu X J, Zhang Y Y, Liu T T, et al. Chemical Analysis and Meterage, 2023, 32(4): 63
[8]	刘晓晶, 张媛媛, 刘彤彤, 等. 化学分析计量, 2023, 32(4): 63
[9]	Peng J W, Xu L, Li X C, et al. Chemical Industry Times, 2016, 30(8): 1
[9]	彭佳伟, 徐蕾, 李小晨, 等. 化工时刊, 2016, 30(8): 1
[10]	Wang J J, Zheng G J, Wang J L, et al. Chinese Journal of Analytical Chemistry, 2001, 29(6): 671
[10]	王建军, 郑国钧, 王佳亮, 等. 分析化学, 2001, 29(6): 671
[11]	Tan X P. [MS Dissertation]. Chongqing: Southwest University, 2016
[11]	谭选平. [硕士学位论文]. 重庆: 西南大学, 2016
[12]	Cai W J, Ying Y F, Lu C B, et al. Chinese Journal of Veterinary Drug, 2017, 51(8): 26
[12]	蔡文金, 应永飞, 陆春波, 等. 中国兽药杂志, 2017, 51(8): 26
[13]	Hu S J, Li Y, Zhou Y, et al. Chinese Journal of Chromatography, 2019, 37(7): 701
[13]	胡胜杰, 李优, 周莹, 等. 色谱, 2019, 37(7), 701
[14]	Zhao K X, Chai M J, Song X, et al. Journal of Food Safety and Quality, 2019, 10(11): 3481
[14]	赵孔祥, 柴铭骏, 宋旭, 等. 食品安全质量检测学报, 2019, 10(11): 3481
[15]	Liu X H, Shi Y H, Ding W H, et al. Quality and Safety of Agro-products, 2020(5): 68
[15]	刘新辉, 史永晖, 丁文慧, 等. 农产品质量与安全, 2020(5): 68
[16]	Yuan L J, Zong W. Journal of Food Safety and Quality, 2022, 13(20): 6518
[16]	袁利杰, 纵伟. 食品安全质量检测学报, 2022, 13(20): 6518
[17]	Zeng X, Zhao T T, Liu C S, et al. Journal of Food Science and Technology, 2023, 23(2): 288
[17]	曾曦, 赵甜甜, 刘春生, 等. 中国食品学报, 2023, 23(2): 288
[18]	Nie X M, Dong X Y, Xu X L, et al. Chinese Journal of Chromatography, 2019, 37(9): 1011
[18]	聂雪梅, 董旭阳, 许秀丽, 等. 色谱, 2019, 37(9): 1011
[19]	Ni Z, Zhang C S, Xie X C. Chinese Journal of Pharmaceutical Analysis, 2019, 39(5): 895
[19]	倪赞, 张崇生, 谢循策. 药物分析杂志, 2019, 39(5): 895
[20]	Zhang Q, Zhao P Z, Qu L, et al. Food Science, 2014, 35(20): 202
[20]	张旖, 赵普贞, 曲栗, 等. 食品科学, 2014, 35(20): 202
[21]	Wang H, Zhao Y, Liao P, et al. Chemical Journal of Chinese Universities, 2013, 34(3): 556
[21]	王华, 赵勇, 廖鹏, 等. 高等学校化学学报, 2013, 34(3): 556
[22]	Liu B, Bao Y, Lang L, et al. Journal of Food Safety and Quality, 2019, 10(6): 1511
[22]	刘斌, 包懿, 郎乐, 等. 食品安全质量检测学报, 2019, 10(6): 1511
[23]	Xu H B, Zhang S P, Du R Y, et al. Chinese Journal of Chromatography, 2022, 40(6): 531
[23]	徐红斌, 张申平, 杜茹云, 等. 色谱, 2022, 40(6): 531
[24]	Tan H J, Guo C C, Xing S, et al. Chinese Journal of Chromatography, 2019, 37(9): 969
[24]	谭会洁, 郭常川, 邢晟, 等. 色谱, 2019, 37(9): 969

Compound	Molecular formula	t_R/ min	Theoretical [M+H]⁺	Measured [M+H]⁺	Fragment ions (m/z)
Atenolol	C₁₄H₂₂N₂O₃	6.23	267.1703	267.1694	225.1227, 208.0975, 116.1077, 98.0973
Nadolol	C₁₇H₂₇NO₄	6.77	310.2013	310.2017	205.0868, 149.0240, 119.7833
Acebutolol	C₁₈H₂₈N₂O₄	7.25	337.2122	337.2108	319.2004, 260.1272, 116.1070, 98.0967
Arotinolol	C₁₅H₂₁N₃O₂S₃	7.26	372.0869	372.0856	316.0232, 298.9968, 74.0607
Metoprolol	C₁₅H₂₅NO₃	7.39	268.1907	268.1898	191.1060, 159.0799, 116.1069, 98.0967
Celiprolol	C₂₀H₃₃N₃O₄	7.55	380.2544	380.2527	307.1648, 251.1021, 119.7495
Esmolol	C₁₆H₂₅NO₄	7.57	296.1856	296.1846	219.1008, 145.0644, 116.1070, 98.0967
Labetalol	C₁₉H₂₄N₂O₃	7.77	329.1860	329.1848	311.1743, 294.1479, 162.0544, 91.0546
Bisoprolol	C₁₈H₃₁NO₄	7.86	326.2326	326.2314	116.1070, 98.0967, 74.0607
Propranolol	C₁₆H₂₁NO₂	8.01	260.1645	260.1637	183.0799, 157.0644, 116.1070, 98.0967
Bevantolol	C₂₀H₂₇NO₄	8.13	346.2013	346.2000	165.0906, 150.0671
Carvedilol	C₂₄H₂₆N₂O₄	8.35	407.1965	407.1953	283.1430, 224.1273, 100.0759
Nebivolol	C₂₂H₂₅F₂NO₄	8.55	406.1824	406.1814	388.1701, 151.0550, 123.0603

Compound	Molecular formula	t_R/ min	Theoretical [M+H]⁺	Measured [M+H]⁺	Fragment ions (m/z)
Atenolol	C₁₄H₂₂N₂O₃	6.23	267.1703	267.1694	225.1227, 208.0975, 116.1077, 98.0973
Nadolol	C₁₇H₂₇NO₄	6.77	310.2013	310.2017	205.0868, 149.0240, 119.7833
Acebutolol	C₁₈H₂₈N₂O₄	7.25	337.2122	337.2108	319.2004, 260.1272, 116.1070, 98.0967
Arotinolol	C₁₅H₂₁N₃O₂S₃	7.26	372.0869	372.0856	316.0232, 298.9968, 74.0607
Metoprolol	C₁₅H₂₅NO₃	7.39	268.1907	268.1898	191.1060, 159.0799, 116.1069, 98.0967
Celiprolol	C₂₀H₃₃N₃O₄	7.55	380.2544	380.2527	307.1648, 251.1021, 119.7495
Esmolol	C₁₆H₂₅NO₄	7.57	296.1856	296.1846	219.1008, 145.0644, 116.1070, 98.0967
Labetalol	C₁₉H₂₄N₂O₃	7.77	329.1860	329.1848	311.1743, 294.1479, 162.0544, 91.0546
Bisoprolol	C₁₈H₃₁NO₄	7.86	326.2326	326.2314	116.1070, 98.0967, 74.0607
Propranolol	C₁₆H₂₁NO₂	8.01	260.1645	260.1637	183.0799, 157.0644, 116.1070, 98.0967
Bevantolol	C₂₀H₂₇NO₄	8.13	346.2013	346.2000	165.0906, 150.0671
Carvedilol	C₂₄H₂₆N₂O₄	8.35	407.1965	407.1953	283.1430, 224.1273, 100.0759
Nebivolol	C₂₂H₂₅F₂NO₄	8.55	406.1824	406.1814	388.1701, 151.0550, 123.0603

Compound	Regression equation	r	LOD/ (μg/kg)	LOQ/ (μg/kg)
Atenolol	y=2.31×10⁵x-4.81×10⁵	0.9970	4	10
Nadolol	y=4.91×10⁵x+5.50×10⁵	0.9912	10	20
Acebutolol	y=6.08×10⁵x+1.10×10⁶	0.9937	2	5
Arotinolol	y=4.89×10⁵x-7.25×10⁵	0.9957	1	3
Metoprolol	y=6.97×10⁵x-6.26×10⁵	0.9930	1	3
Celiprolol	y=7.24×10⁵x-7.98×10⁵	0.9962	1	3
Esmolol	y=9.86×10⁵x-6.33×10⁵	0.9958	4	10
Labetalol	y=4.58×10⁵x-8.50×10⁵	0.9942	1	3
Bisoprolol	y=6.96×10⁵x-6.59×10⁵	0.9957	1	3
Propranolol	y=1.01×10⁶x-6.70×10⁵	0.9951	1	3
Bevantolol	y=7.50×10⁵x-7.39×10⁵	0.9960	1	3
Carvedilol	y=6.72×10⁵x-5.65×10⁵	0.9972	1	3
Nebivolol	y=5.24×10⁵x-7.82×10⁵	0.9956	1	3

Compound	Regression equation	r	LOD/ (μg/kg)	LOQ/ (μg/kg)
Atenolol	y=2.31×10⁵x-4.81×10⁵	0.9970	4	10
Nadolol	y=4.91×10⁵x+5.50×10⁵	0.9912	10	20
Acebutolol	y=6.08×10⁵x+1.10×10⁶	0.9937	2	5
Arotinolol	y=4.89×10⁵x-7.25×10⁵	0.9957	1	3
Metoprolol	y=6.97×10⁵x-6.26×10⁵	0.9930	1	3
Celiprolol	y=7.24×10⁵x-7.98×10⁵	0.9962	1	3
Esmolol	y=9.86×10⁵x-6.33×10⁵	0.9958	4	10
Labetalol	y=4.58×10⁵x-8.50×10⁵	0.9942	1	3
Bisoprolol	y=6.96×10⁵x-6.59×10⁵	0.9957	1	3
Propranolol	y=1.01×10⁶x-6.70×10⁵	0.9951	1	3
Bevantolol	y=7.50×10⁵x-7.39×10⁵	0.9960	1	3
Carvedilol	y=6.72×10⁵x-5.65×10⁵	0.9972	1	3
Nebivolol	y=5.24×10⁵x-7.82×10⁵	0.9956	1	3

Compound	Added/(μg/kg)	Recovery/%	RSD/%
Atenolol	10	105.2	0.9
	20	105.8	4.9
	200	93.8	6.5
Nadolol	20	78.4	3.6
	50	77.8	4.1
	200	78.0	3.1
Acebutolol	10	79.4	4.4
	20	82.8	5.7
	200	81.0	7.1
Arotinolol	10	80.6	3.6
	20	77.2	2.9
	200	76.0	5.1
Metoprolol	10	91.9	4.2
	20	89.6	2.5
	200	102.2	5.6
Celiprolol	10	86.5	4.4
	20	75.3	5.7
	200	81.7	4.4
Esmolol	10	80.9	10.0
	20	95.9	8.6
	200	88.9	2.7
Labetalol	10	87.5	1.5
	20	104.8	5.2
	200	79.6	6.1
Bisoprolol	10	91.8	6.5
	20	108.4	5.9
	200	89.0	2.8
Propranolol	10	86.6	8.2
	20	78.3	1.8
	200	82.0	5.1
Bevantolol	10	89.3	3.4
	20	84.0	3.6
	200	84.8	6.3
Carvedilol	10	78.9	9.4
	20	77.3	4.1
	200	77.6	4.8
Nebivolol	10	89.0	2.5
	20	81.3	1.9
	200	90.3	1.2