转基因定量检测结果测量不确定度的自上而下评定方法研究及应用

doi:10.3864/j.issn.0578-1752.2023.22.002

Abstract

Abstract:

【Objective】The enforcement of labeling regulations on genetically modified organisms (GMOs) requires establishing a standard system for accurate quantification of GMOs that includes the standard or guide for estimating measurement uncertainty (MU). It is urgent to establish a standardized top-down approach for estimating MU of quantitative results, which is conveniently adopted by the general testing laboratories. 【Method】There are two approaches for estimating the MU introduced by precision of quantitative method, one is to establish the equation of MU estimation using data obtained on 15 routine samples based on the "uncertainty function", the other is to evaluate the MU by repeatedly measuring a certified reference material (CRM) and calculating the intermediate precision. The uncertainty introduced by bias is evaluated using a CRM or a sample prepared by laboratory as bias control. The uncertainty of the nominal value of the sample prepared by laboratory is evaluated by using a simplified program based on the preparation process. The MU contributed by method precision and bias are combined into the standard uncertainty of the quantitative results, and then multiplied by the coverage factor k to obtain the expanded uncertainty. 【Result】The event-specific PCR method of genetically modified maize DBN9936 was took as an example. The MU of method precision was evaluated to be 0.76% using simulated DBN9936 routine samples, and to be 0.33% using a CRM (GBW (E) 100901). Compared with routine samples, the MU of method precision evaluated using a CRM is significantly underestimated. The uncertainty introduced by bias was evaluated to be 0.26% using a CRM (GBW (E) 100901) as a bias control. Using a laboratory prepared powder sample and a genomic DNA sample (nominal values of 3.0%) as bias control, the bias uncertainty was evaluated to be 0.20% and 0.19%, respectively. Since the simplified program ignored some uncertainty components, the uncertainty of the nominal value of laboratory prepared samples was estimated to be smaller. By combining the MU of method precision and bias, the expanded uncertainty using routine samples was obtained to be 1.26%, 1.20%, and 1.20%, respectively, the expanded uncertainty using a CRM was 0.84%, 0.78%, and 0.76%, respectively. 【Conclusion】This study established the top-down approaches for MU estimation of quantitative results, testing laboratories should prioritize routine samples to estimate the MU contributed by the method precision, and select CRMs as bias control in principle to evaluate bias uncertainty during GMO quantification.

Key words: quantitative results of GMO content, measurement uncertainty, top-down approach, certified reference materials, bias control

LI Jun, ZHAO Xin, CHEN Hong, LI FeiWu, LIANG JinGang, LI YunJing, WANG HaoQian, GAO HongFei, ZHANG Hua, CHEN ZiYan, WU Gang, SHEN Ping, XU LiQun, WU YuHua. Development and Application of Top-Down Approaches for Estimating Measurement Uncertainty of GMO Quantitative Results[J].Scientia Agricultura Sinica, 2023, 56(22): 4371-4385.

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[1]	焦悦, 王智, 张振民, 彭萱子, 付海滨, 朱鹏宇, 黄春蒙, 张永江, 付伟. 基于转基因产品成分低水平混杂问题探究我国转基因阈值制度. 中国农业科技导报, 2022, 24(3): 20-27. doi: 10.13304/j.nykjdb.2020.0984
	JIAO Y, WANG Z, ZHANG Z M, PENG X Z, FU H B, ZHU P Y, HUANG C M, ZHANG Y J, FU W. Research on the transgenic threshold system in China based on low-level presence of genetically modified products. Journal of Agricultural Science and Technology, 2022, 24(3): 20-27. (in Chinese) doi: 10.13304/j.nykjdb.2020.0984
[2]	TRANBERG J. Developing a policy for low-level presence (LLP): A Canadian case study. AgBioForum, 2013, 16: 37-45.
[3]	徐丽丽, 李宁, 田志宏. 转基因产品低水平混杂问题研究. 中国农业大学学报(社会科学版), 2012, 29(2): 125-132.
	XU L L, LI N, TIAN Z H. Analysis on the low level presence of genetically modified product. Journal of China Agricultural University (Social Sciences), 2012, 29(2): 125-132. (in Chinese)
[4]	International Organization for Standardization ISO, International Electrotechnical Commission (IEC). International vocabulary of metrology—Basic and general concepts and associated terms (VIM), ISO/IEC Guide 99:2007, https://www.iso.org/standard/45324.html2022-04-07].
[5]	INFUSINO I, PANTEGHINI M. Measurement uncertainty: Friend or foe? Clinical Biochemistry, 2018, 57: 3-6. doi: S0009-9120(18)30002-X pmid: 29410277
[6]	International Organization for Standardization ISO, International Electrotechnical Commission (IEC). Uncertainty of measurement— Part 4:Role of measurement uncertainty in conformity assessment. ISO/IEC Guide 98-4:2012. https://www.iso.org/standard/50465.html
[7]	International Organization for Standardization ISO, International Electrotechnical Commission (IEC). Uncertainty of measurement— Part 3: Guide to the expression of uncertainty in measurement (GUM:1995), ISO/IEC Guide 98-3:2008. https://www.iso.org/standard/50461.html2022-04-07].
[8]	GB/T 27418—2017. 测量不确定度评定和表示. 北京: 中国标准出版社, 2017: 1-77.
	GB/T 27418—2017. Guide to the evaluation and expression of uncertainty in measurement. Beijing: China Standards Press, 2017: 1-77. (in Chinese)
[9]	叶培德, 赵峰, 施昌彦, 原遵东, 沙定国, 周桃庚, 陈红. 测量不确定度评定与表示, JJF1059.1-2012. 北京: 中国质检出版社, 2012: 1-56.
	YE P D, ZHAO F, SHI C Y, YUAN Z D, SHA D G, ZHOU T G, CHEN H. Evaluation and expression of uncertainty in measurement, JJF1059.1-2012. Beijing: China Quality Inspection Press, 2012: 1-56. (in Chinese)
[10]	FARRANCE I, BADRICK T, FRENKEL R. Uncertainty in measurement and total error: Different roads to the same quality destination? Clinical Chemistry and Laboratory Medicine, 2018, 56(12): 2010-2014. doi: 10.1515/cclm-2018-0421 pmid: 29949508
[11]	DABALUS ISLAM M, SCHWEIKERT TURCU M, CANNAVAN A. Comparison of methods for the estimation of measurement uncertainty for an analytical method for sulphonamides. Food Additives & Contaminants Part A, Chemistry, Analysis, Control, Exposure & Risk Assessment, 2008, 25(12): 1439-1450.
[12]	RIGO-BONNIN R, BLANCO-FONT A, CANALIAS F. Different top-down approaches to estimate measurement uncertainty of whole blood tacrolimus mass concentration values. Clinical Biochemistry, 2018, 57: 56-61. doi: 10.1016/j.clinbiochem.2018.05.005
[13]	MORGADO V, PALMA C, BETTENCOURT DA SILVA R J N. Bottom-up evaluation of the uncertainty of the quantification of microplastics contamination in sediment samples. Environmental Science & Technology, 2022, 56(15): 11080-11090. doi: 10.1021/acs.est.2c01828
[14]	FARRANCE I, FRENKEL R. Uncertainty of measurement: A review of the rules for calculating uncertainty components through functional relationships. The Clinical Biochemist Reviews, 2012, 33(2): 49-75.
[15]	WHITE G H, FARRANCE I, AACB Uncertainty of Measurement Working Group. Uncertainty of measurement in quantitative medical testing: A laboratory implementation guide. The Clinical Biochemist Reviews, 2004, 25(4): S1-S24.
[16]	FRENKEL R B, FARRANCE I. Uncertainty in measurement: Procedures for determining uncertainty with application to clinical laboratory calculations. Advances in Clinical Chemistry, 2018, 85: 149-211. doi: S0065-2423(18)30003-9 pmid: 29655460
[17]	SOUSA J A, BATISTA E, DEMEYER S, FISCHER N, PELLEGRINO O, RIBEIRO A S, MARTINS L L. Uncertainty calculation methodologies in microflow measurements: Comparison of GUM, GUM-S1 and Bayesian approach. Measurement, 2021, 181: 109589. doi: 10.1016/j.measurement.2021.109589
[18]	GIECHASKIEL B, LÄHDE T, MELAS A D, VALVERDE V, CLAIROTTE M. Uncertainty of laboratory and portable solid particle number systems for regulatory measurements of vehicle emissions. Environmental Research, 2021, 197: 111068. doi: 10.1016/j.envres.2021.111068
[19]	FARRANCE I, BADRICK T, FRENKEL R. Uncertainty in measurement: A review of the procedures for determining uncertainty in measurement and its use in deriving the biological variation of the estimated glomerular filtration rate. Practical Laboratory Medicine, 2018, 12: e00097. doi: 10.1016/j.PLABM.2018.e00097
[20]	International Organization for Standardization ISO. Guidance for the use of repeatability, reproducibility and trueness estimates in measurement uncertainty estimation. ISO/TS 21748:2004. https://www.iso.org/standard/34686.html2022-04-07]
[21]	王斗文, 陈玉忠, 于振凡, 张帆, 杨军, 王海鹰, 丁文兴, 宋桂兰, 曾泽. 利用重复性、再现性和正确度的估计值评估测量不确定度的指南. GB/Z 22553-2010. 北京: 中国标准出版社, 2010: 1-20.
	WANG D W, CHEN Y Z, YU Z F, ZHAGN F, YANG J, WANG H Y, DING W X, SONG G L, ZENG Z. Guidance for the use of repeatability, reproducibility and trueness estimates in measurement uncertainty estimation. GB/Z 22553-2010. Beijing: Standards Press of China, 2010:1-20. (in Chinese)
[22]	TRAPMANN S, BURNS M, CORBISIER P, GATTO F, ROBOUCH P, SOWA S, EMONS H. Guidance document on Measurement Uncertainty for GMO Testing Laboratories 3rd Edition, EUR 30248 EN, Publications Office of the European Union, Luxembourg, 2020, ISBN 978-92-76-19432-3, doi:10.2760/738565, JRC120898.
[23]	MARTINELLO F, SNOJ N, SKITEK M, JERIN A. The top-down approach to measurement uncertainty: Which formula should we use in laboratory medicine? Biochemia Medica, 2020, 30(2): 020101.
[24]	LEE J H, CHOI J H, YOUN J S, CHA Y J, SONG W, PARK A J. Comparison between bottom-up and top-down approaches in the estimation of measurement uncertainty. Clinical Chemistry and Laboratory Medicine, 2015, 53(7): 1025-1032. doi: 10.1515/cclm-2014-0801 pmid: 25539513
[25]	国家市场监督管理总局认可与检验检测监督管理局. 检验检测机构资质评审准则. https://www.samr.gov.cn/rkjcs/tzgg/202201/t20220128_339457.html2023-01-11].
	State Administration for Market Regulation, Administration for Accreditation, Inspection and Testing Supervision. Qualification evaluation criteria for inspection and testing institutions. https://www.samr.gov.cn/rkjcs/tzgg/202201/t20220128_339457.html2023-01-11]. (in Chinese)
[26]	INTERNATIONAL ORGANIZATION FOR STANDARDIZATION ISO. General requirements for the competence of testing and calibration laboratories, ISO17025-2017. https://www.iso.org/standard/66912.html2022-04-07].
[27]	梁新苗, 蔡颖, 郭铮蕾, 李宏, 饶红, 骆卫峰, 周广彪, 韩玥, 马丹, 徐姗, 刘若思. 转基因检测实验室测量不确定度评估指南, SN/T 4562-2016. 北京: 中国标准出版社, 2016: 1-22.
	LIANG X M, CAI Y, GUO Z L, LI H, RAO H, LUO W F, ZHOU G B, HAN Y, MA D, XU S, LIU R S. Guidance on measurement uncertainty for GMO testing laboratories, SN/T 4562-2016. Beijing: Standards Press of China, 2016:1-22. (in Chinese)
[28]	高运华, 张秀杰, 李亮, 李夏莹, 金芜军, 刘卫晓, 王迪, 梅英婷. 转基因植物及其产品成分检测转基因成分定量检测结果不确定度评定与表示, 农业农村部公告第423号—10—2021. 北京: 中国农业出版社, 2021: 1-9.
	GAO Y H, ZHANG X J, LI L, LI X Y, JIN W J, LIU W X, WANG D, MEI Y T. Detection of genetically modified plants and derived products— Guidance on measurement uncertainty for GMO testing results, Announcement of Ministry of Agriculture and Rural Affairs 423-10-2021. Beijing: Agriculture press of China, 2021: 1-9. (in Chinese)
[29]	LI J, GAO H F, LI Y J, XIAO F, ZHAI S S, WU G, WU Y H. Event-specific PCR methods to quantify the genetically modified DBN9936 maize. Journal of Food Composition and Analysis, 2022, 105: 104236. doi: 10.1016/j.jfca.2021.104236
[30]	THOMPSON M, MATHIESON K, DAMANT A P, WOOD R. A general model for interlaboratory precision accounts for statistics from proficiency testing in food analysis. Accreditation and Quality Assurance, 2008, 13(4/5): 223-230. doi: 10.1007/s00769-008-0356-z
[31]	BURNS M, VALDIVIA H. A procedural approach for the identification of sources of uncertainty associated with GM quantification and real-time quantitative PCR measurements. European Food Research and Technology, 2007, 226(1/2): 7-18. doi: 10.1007/s00217-006-0502-y

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转化体（基因） Event (gene)	引物/探针名称及序列 Sequences of primer/probe (5′-3′)	扩增片段大小 Amplicon size (bp)
DBN9936	LF51：CAGGGGCAAGAAAACATC	76
	LR126：TCTTGTGTGCCCATGAGCCTA
	LP79：FAM-TCTTGTGTGCCCATGAGCCTA-BHQ1
zSSIIb	F：CGGTGGATGCTAAGGCTGATG	88
	R：AAAGGGCCAGGTTCATTATCCTC
	P：Hex-TAAGGAGCACTCGCCGCCGCATCTG-BHQ1

样品类型 Sample type	样品编号 Sample code	预期浓度 Expected concentration (%)	测量值 Measured value (%)		${{\bar{c}}_{j}}$(%)	SD (%)	RSD (%)
样品类型 Sample type	样品编号 Sample code	预期浓度 Expected concentration (%)	c_1,_j	c_2,_j	${{\bar{c}}_{j}}$(%)	SD (%)	RSD (%)
低浓度样品 Low level sample	R1	0.10	0.119	0.096	0.107	0.021	19.20
	R2	0.12	0.126	0.100	0.113	0.023	20.53
	R3	0.15	0.135	0.142	0.139	0.006	4.13
	R4	0.20	0.215	0.192	0.204	0.020	9.81
	R5	0.25	0.249	0.311	0.280	0.054	19.41
	R6	0.30	0.331	0.385	0.358	0.048	13.48
高浓度样品 High level sample	R7	0.35	0.439	0.330	0.385	0.097	25.28
	R8	0.40	0.561	0.474	0.518	0.077	14.86
	R9	0.50	0.524	0.590	0.557	0.058	10.45
	R10	0.70	0.788	0.609	0.699	0.159	22.70
	R11	1.00	0.978	0.946	0.962	0.028	2.88
	R12	2.00	2.270	2.181	2.226	0.079	3.55
	R13	2.50	2.238	2.854	2.546	0.546	21.43
	R14	3.00	2.974	3.543	3.258	0.505	15.48
	R15	4.00	4.320	4.151	4.236	0.150	3.55

样品分类 Sample type	样品编号 Sample code	测量值 Measured value (%)		分析结果 Analytical result (%)
样品分类 Sample type	样品编号 Sample code	c_1,_j	c_2,_j	$\left\| \text{ }{{d}_{j}} \right\|$	$\left\| \text{ }\bar{d} \right\|$	α
低浓度样品 Low level sample	R1	0.119	0.096	0.023	0.032	0.029
	R2	0.126	0.100	0.026
	R3	0.135	0.142	0.006
	R4	0.215	0.192	0.023
	R5	0.249	0.311	0.061
	R6	0.331	0.385	0.054

样品分类 Sample type	样品编号 Sample code	测量值 Measured value (%)		数据分析结果 Analytical result
样品分类 Sample type	样品编号 Sample code	c_1,_j	c_2,_j	$\left\| \text{ }{{d}_{j}} \right\|$(%)	${{\bar{c}}_{j}}$(%)	${{\left\| \text{ }{{d}_{j}} \right\|}_{rel}}$	$\text{ }{{\left\| \text{ }\bar{d} \right\|}_{rel}}$	β
高浓度样品 High level sample	R7	0.439	0.330	0.110	0.385	0.278	0.155	0.137
	R8	0.561	0.474	0.087	0.518	0.181
	R9	0.524	0.590	0.066	0.557	0.128
	R10	0.788	0.609	0.179	0.699	0.240
	R11	0.978	0.946	0.031	0.962	0.032
	R12	2.270	2.181	0.089	2.226	0.042
	R13	2.238	2.854	0.616	2.546	0.260
	R14	2.974	3.543	0.569	3.258	0.191
	R15	4.320	4.151	0.170	4.236	0.041

平行子样 Subsample	检测结果 Measured result (%)					分析结果 Analytical result (%)
平行子样 Subsample	第1天 Day 1	第2天 Day 2	第3天 Day 3	第4天 Day 4	第5天 Day 5	组内均方 MS_w	组间均方 MS_b	重复性方差 $s_{r}^{2}$	组间方差 $s_{b}^{2}$
子样1 Subsample 1	3.95	3.90	3.47	3.30	3.96	0.171	0.412	0.171	0.048
子样2 Subsample 2	3.60	3.14	4.04	3.40	3.93
子样3 Subsample 3	3.06	2.33	3.25	3.02	3.62
子样4 Subsample 4	3.85	2.87	2.87	2.58	3.14
子样5 Subsample 5	3.51	2.94	3.08	3.02	3.60

Development and Application of Top-Down Approaches for Estimating Measurement Uncertainty of GMO Quantitative Results

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质控品 Control	标准值 C_CRM	测量结果 Measured result (%)			分析结果Analytical result (%)
质控品 Control	标准值 C_CRM	C₁	C₂	C₃	$\bar{c}$	\|bias\|	s	$u(\bar{c})$	u_CRM(u_E)	u_bias	RSD
GBW（E）100901	3.49%	3.13	3.05	3.64	3.273	0.217	0.348	0.201	0.165^a	0.260	10.65
实验室配制粉末质控品 Laboratory prepared matrix control	0.03	3.21	3.35	2.81	3.123	0.123	0.319	0.184	0.060^b	0.194	10.21
实验室配制基因组DNA质控品 Laboratory prepared genomic DNA control	0.03	2.90	3.30	3.40	3.200	0.200	0.295	0.171	0.070^b	0.184	9.23

DNA	测量浓度（拷贝(μL)）			平均值 $\bar{c}$	平均值标准差 ${{u}_{{\bar{c}}}}$	平均值相对标准差 ${{u}_{\bar{c}1}}$
DNA	1	2	2	平均值 $\bar{c}$	平均值标准差 ${{u}_{{\bar{c}}}}$	平均值相对标准差 ${{u}_{\bar{c}1}}$
转基因DNA GM DNA	34000	33100	33700	33600	307	0.0091
非转基因DNA Non-GM DNA	33300	33400	34700	33800	477	0.0141

试样检测平均值 Mean of test sample	精密度不确定度评定 Estimation of precision uncertainty		偏倚不确定度评定 Estimation of bias uncertainty		合成不确定度 Combined uncertainty (%)	扩展不确定度 Expanded uncertainty (%)	定量结果 Expression of quantitative result (%)
试样检测平均值 Mean of test sample	评定方法 Method	精密度不确定度 Precision uncertainty (%)	质控品类型 Control type	偏倚不确定度 Bias uncertainty (%)	合成不确定度 Combined uncertainty (%)	扩展不确定度 Expanded uncertainty (%)	定量结果 Expression of quantitative result (%)
4.15%	常规样品 Routine sample	0.57	有证标准物质CRM	0.260	0.63	1.26	4.15±1.26
			实验室配制粉末样品 Laboratory prepared matrix sample	0.194	0.60	1.20	4.15±1.20
			实验室配制基因组DNA样品 Laboratory prepared genomic DNA sample	0.184	0.60	1.20	4.15±1.20
	有证标准物质 CRM	0.33	有证标准物质CRM	0.260	0.42	0.84	4.15±0.84
			实验室配制粉末样品 Laboratory prepared matrix sample	0.194	0.39	0.78	4.15±0.78
			实验室配制基因组DNA样品 Laboratory prepared genomic DNA sample	0.184	0.38	0.76	4.15±0.76