主题:【第十一届原创】超高效液相色谱-串联质谱法测定牛奶中糠氨酸的含量

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7月二等奖 年度三等奖
本文建立了超高效液相色谱-串联质谱法(UPLC-MS/MS)测定牛奶中糠氨酸含量的分析方法。该方法灵敏度高,糠氨酸定量限(LOQ)达到0.5 mg/100g蛋白,能满足生牛乳、巴氏杀菌乳及UHT高温灭菌乳等不同样品中糠氨酸含量的检测。同时该方法具有较高的准确度和精密度,前处理步骤简单,分析速度快,可有效避免由于色谱柱柱效下降对最终检测结果的影响,特别适合大批量样品的检测。
                                      超高效液相色谱-串联质谱法测定牛奶中糠氨酸的含量

户江涛

(农业农村部食品质量监督检验测试中心(佳木斯),黑龙江省农垦科学院测试化验中心,黑龙江 佳木斯 154007 )



摘要:采用超高效液相色谱-串联质谱法建立了检测牛奶中糠氨酸含量的分析方法。试样经10.6 mol/L 盐酸水解,纯水稀释后,糠氨酸在C18色谱柱上以0.1%甲酸水溶液和乙腈为流动相,进行液相色谱分离;质谱检测采用电喷雾正离子化模式和多反应监测模式(MRM)。结果表明,糠氨酸在0.01~0.5mg/L范围内线性关系良好,相关系数(R)为0.9996,定量限(LOQ)为0.5 mg/100g蛋白。在生牛乳空白样品添加浓度为10、100、300 mg/100g蛋白时,糠氨酸的平均回收率为93.1%~95.7%,相对标准偏差(RSD)为1.16%~1.71%(n=6)。本方法简便、灵敏、抗干扰,适用于牛奶中糠氨酸含量检测。
关键词:超高效液相色谱-串联质谱;牛奶;糠氨酸

Determination of Furosinein milkby ultra performance liquid chromatography-tandem mass spectrometry

HU Jiangtao

(Food QualitySupervision and Testing Center(Jiamusi), Ministry of Agriculture and RuralAffairs, Testing and Analysis Center of Heilongjiang Academy of LandReclamation Sciences, Jiamusi 154007,China)



Abstract:A method wasdeveloped for the determination of Furosinein milkby ultra performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS).The samples were hydrolysed by 10.6 mol/LHCL and then decided by water, Furosine was separated on a Waters BEH C18column with gradient elution with the mobile phase of 0.1% formic acid andacetonitrile, and finally detected by positive eletrospray ionization-mass spectrometry(ESI+-MS/MS)in multiple reaction monitoring(MRM) mode. The results showed the linearity of Furosine was good in the concentration range of 0.01~0.5mg/L , and the correlation coefficient was 0.9996. The limit ofquantification(LOQ) of Furosine was 0.5 mg/100g protein. At the spiked levels of 10、100、300 mg/100gprotein in the blank raw milk samples, the mean recovery of Furosine was 93.1%~95.7%, and the relative standard deviation(RSD) of Furosinewas 1.16%~1.71%(n=6).This method is simple,sensitive, anti-jamming and suitable for simultaneous determination of Furosine in milk.
Key words: ultra performance liquid chromatography-tandem massspectrometry (UPLC-
MS/MS); Furosine;milk
    糠氨酸(Furosine,ε-N-2-呋喃甲基-L-赖氨酸)又名呋喃素,分子式为C12H18N2O4,是结构与氨基酸类似的赖氨酸衍生物,是蛋白质与乳糖在热处理过程中经美拉德反应的特征产物之一。加热温度和时间是影响牛奶中糠氨酸含量的两个重要因素,在储存过程中也会导致糠氨酸含量增加,因此国际上常用糠氨酸作为热处理和储存对乳制品质量影响的重要评估指标。同时,研究发现牛奶中糠氨酸含量和乳果糖指标相结合,可用于鉴别液态奶制品中是否含有复原乳
  目前,糠氨酸的检测方法主要有高效液相色谱法(HPLC)、质谱法(HPLC-MS/MS、CE-MS/MS)、表面荧光光谱法 等。毛细管电泳串联质谱法(CE-MS/MS)虽然能有效分离水解液中的糠氨酸和杂质,但其仪器使用和维护成本较高,专用性强(主要针对生物大分子),且前处理复杂,检测速度较慢,故不适用于大批量样品检测;表面荧光光谱法是一种操作简便的快速检测方法,但其灵敏度不高,只能进行半定量分析,应用范围有限;目前,糠氨酸检测现有的国际标准ISO18329、国内农业行业标准NY/T 939-2016采用的都是高效液相色谱法(HPLC),该方法前处理相对简单、快速,灵敏度高。在实际检测过程中发现,由于牛奶水解后的溶液还含有糖、无机酸、盐等杂质,随着进样次数的增加,会发现色谱柱柱效明显下降,以至于不能满足分离度要求,严重干扰糠氨酸峰面积积分定量,特别对巴氏杀菌乳这类糠氨酸含量较低(一般小于12 mg/100g蛋白)的样品影响巨大。而LC-MS/MS法通过选定糠氨酸的特征离子,能有效去除上述杂质干扰,定量更加准确可靠。
    目前,国外采用LC-MS/MS法检测牛奶中糠氨酸含量的文献很少,国内还未见该方面报道。本文对牛奶中糠氨酸检测的前处理方法借鉴NY/T939-2016,水解液经纯水稀释后UPLC-MS/MS测定。该方法前处理过程简便、灵敏度高、分析时间短、抗干扰能力强,适用于大批量牛奶样品中糠氨酸含量的检测。
1 实验部分
1.1 材料与试剂
糠氨酸(纯度99%Polypeptide公司);盐酸(色谱纯,J.T.Baker公司);乙腈、甲酸(色谱纯,Fisher公司);实验用水为Millipore纯水仪制备。
1.2 仪器与设备
Acquity UPLC型超高效液相色谱仪(Waters公司);XEVO TQ-MS三重四级杆质谱仪(Waters公司);20mL带螺盖耐热水解试管(KIMBLE公司);DHG-9146 A型干燥箱(上海精宏实验设备有限公司);涡旋混合器(IKA公司)。
1.3 糠氨酸标准储备液的配置
称取一定量的糠氨酸标准品,用3 mol/L盐酸配置成质量浓度为200 ug/mL标准储备液,于-20℃冰箱保存(可贮存24个月),待用;使用时用0.1mol/L盐酸逐级稀释成所需浓度的标准工作液。
1.4 样品前处理
1.4.1试样的水解
用移液管准确吸取2.00 mL牛奶试样,放置于20mL耐热水解试管中,加入6.00 mL 10.6 mol/L盐酸溶液,涡旋混匀。用螺帽拧紧密闭试管,置于干燥箱中,在110℃下加热水解12-23小时。加热约1h后,轻轻摇动试管。加热结束后,将试管从干燥箱中取出,冷却至室温后用滤纸过滤,滤液待进一步处理。
1.4.2试样水解液中糠氨酸含量的测定
a)对于巴氏杀菌乳:准确吸取1.00 mL试样水解液(1.4.1),加入5.00 mL纯水,混匀,过0.22 um水系微孔滤膜后得到上机液,供UPLC-MS/MS分析测定;
b)对于UHT高温灭菌乳:由于其糠氨酸含量较高,需将1.4.2 a)中的上机液稀释10倍后再供UPLC-MS/MS分析测定。
1.4.3试样水解液中蛋白质含量的测定
准确吸取1.00 mL试样水解液(1.4.1),按GB 5009.5的规定测定试样水解液中蛋白质含量。
1.5 液相色谱及质谱条件
液相色谱:色谱柱:Waters BEH C18(1.7 µm,50mm×2.1mm);柱温:40℃;流速:0.4 mL/min;进样量:1 µL;流动相A:乙腈;流动相B:0.1%的甲酸水溶液。梯度洗脱程序:0~0.8min,3% A;0.8~1. 0 min,3%~100% A;1. 0 ~2. 0 min,100%A,2 ~2.1min,100% A~3% A,2.1 ~3.0min 3% A。
质谱:离子源:电喷雾离子源( ESI + ) ;扫描方式:正离子扫描;检测方式:多反应监测( MRM);毛细管电压:3.2 kv;离子源温度:150℃;去溶剂气温度:500℃;去溶剂气流量:1000 L /h;定性、定量离子对及碰撞能量见表1。

表1糠氨酸的质谱参数

Table 1 MRM parameters of Furosine


                       

Analyte

Cone/V

Parent ion/(m/z)

Daughter ion/(m/z)

Collision energy/V

Furosine

 

30

255.1

 

84.1﹡

 

192.1

27

 

18



﹡quantitativeion
2 结果与讨论
2.1 色谱及质谱条件的优化
流动相的选择:对比了酸性体系(0.1%甲酸水溶液)与非酸性体系(纯水、乙酸铵溶液)分别与甲醇、乙腈的流动相体系组合,结果发现目标物在酸性体系中比非酸性体系峰形更加对称,分离效果更好;由于牛奶水解液中仍含有少量的糖、脂肪等杂质可能会残留在色谱柱上,影响色谱柱的使用寿命,而乙腈比甲醇体系洗脱能力更强,可以有效去这些杂质。综合考虑目标物信号强度、色谱分离效果以及除杂等因素,本研究采用0.1%甲酸水溶液+乙腈流动相体系。
质谱的选择:糠氨酸分子量为254.1。用0.1mol/L盐酸配置1.0 mg/L 糠氨酸标准溶液直接注射到质谱中,在正负离子模式下分别进行母离子全扫描,发现正离子模式下255.1具有很好的响应,然后分别以255.1为母离子进行子离子全扫描,各得到两组丰度高、干扰小的子离子对进行MRM监测,最终确定的质谱条件见表1。
2.2 质谱法(UPLC-MS/MS)与色谱法(HPLC、UPLC)的比较
农业部行业标准《NY/T 939-2016 巴氏杀菌乳和UHT灭菌乳中复原乳的鉴定》中规定的糠氨酸检测方法为HPLC和UPLC法。对从超市采购的品牌样品(包括巴氏杀菌乳和UHT灭菌乳)采用1.4前处理步骤,其上机液分别采用UPLC-MS/MS(MRM色谱图见图1、2)和UPLC法检测,结果表明两种仪器测定的糠氨酸含量值基本一致。
在实际大批量样品检测中发现,色谱法的局限性在于随着进样次数增加,色谱柱柱效下降严重:对于刚使用的新色谱柱,干扰峰与糠氨酸目标峰(箭头所示)能达到基线分离(图3);但由于牛奶水解液中含有糖、无机酸及盐等杂质,随着进样次数的增加,会发现杂质峰与糠氨酸峰越来越近,以至于不能达到分离度要求(图4为进样约200次后的谱图),影响目标物峰面积积分,这会对如巴氏杀菌乳等糠氨酸含量较低样品的测定值造成很大的干扰。而质谱法通过选定的糠氨酸特征离子,可有效去除杂质的干扰,其目标物分离度不受进样次数增加的影响(图2与图4所使用的色谱柱为同一根),定量更加准确可靠。

图1 糠氨酸标准溶液(0.1mg/L)MRM色谱图
    Fig.1 MRM chromatograms of Furosinestandard solution at 0.1 mg/L
[img=,276,200]data:image/png;base64,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[/img]
图2 牛奶样品中糠氨酸MRM色谱图
Fig.2 MRM chromatograms of Furosine in milk


                           
2.3线性范围和定量限
吸取不同体积的糠氨酸标准储备液(1.3),用0.1mol/L盐酸分别配置0.010.050.10.20.5的糠氨酸上机标准溶液,以各自定量离子的峰面积为Y对应质量浓度X(mg/L)做标准曲线,得到的线性方程和相关系数见表2。结果表明,糠氨酸标准溶液在0.01~0.5 mg/L浓度范围内线性良好,相关系数R为0.9996。以10倍信噪比(S/N)计算,糠氨酸上机液最低定量浓度为0.0025 mg/L,通过公式(1)计算得到糠氨酸的质量分数,最终确定本方法糠氨酸的定量限(LOQ)为0.5 mg/100g蛋白。
糠氨酸质量分数计算公式:
………………(1)
  式中:X为试样中每100g蛋白质中糠氨酸含量,以mg/100g计;C为糠氨酸上机浓度(mg/L);D为水解液稀释倍数(D=6);m为试样水解液中蛋白质质量浓度(g/L)。
            表2 糠氨酸标准溶液的线性方程、相关系数和定量限(LOQ)
  Table 2 Linear equation, correlation and LOQ of Furosine inthe 0.1HCL matrix standard solutions
                       

Analyte

Linear range/(mg/L)

Linear equation

R

LOQ/(mg/ 100g protein)

Furosine

0.01~0.5

Y=76338x+85.182

0.9996

0.5




2.4回收率和精密度
生牛乳中糠氨酸含量较低(一般为2-5 mg/100g蛋白),故本方法准确度实验采用
生牛乳作为空白样品进行加标。
移取生牛乳2.00 mL,分别添加一定量的糠氨酸标准储备液(1.3),使得通过公式(1)计算后的糠氨酸理论添加浓度分别为10100300 mg/100g蛋白,每个水平重复6次,同时做该生牛乳的空白本底实验。按照1.4前处理方法处理后上机检测,回收率计算结果(扣除空白后)见表3。结果表明,该方法糠氨酸的平均回收率为93.1%~95.7%,相对标准偏差(RSD,n=6)为1.16%~1.71%。
表3 生牛乳中糠氨酸的加标回收率和相对标准偏差(n=6)
Table 3 Recoveries and relative standard deviations(RSD)of  Furosinein raw milk(n=6)
                   

Analyte

Spiked level(mg/100g protein)

Recovery/%

RSD/%

Furosine

10

 

100

 

300

 

95.7

 

93.6

 

93.1

1.71

 

1.53

 

1.16

 


3 结语
本文建立了超高效液相色谱-串联质谱法(UPLC-MS/MS)测定牛奶中糠氨酸含量的分析方法。该方法灵敏度高,糠氨酸定量限(LOQ)达到0.5 mg/100g蛋白,能满足生牛乳、巴氏杀菌乳及UHT高温灭菌乳等不同样品中糠氨酸含量的检测。同时该方法具有较高的准确度和精密度,前处理步骤简单,分析速度快,可有效避免由于色谱柱柱效下降对最终检测结果的影响,特别适合大批量样品的检测。
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楼主的前处理方法简单快速是大家测定样品时候的追求,感谢分享。
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