不同真空采血管对血浆/血清多肽质谱分析的影响
|
摘要
目的观察不同添加剂处理的真空采血管留取标本对患者血浆/血清多肽检测的影响,确立临床适用的血浆/血清多肽质谱分析采血管。方法招募6名志愿者,男性2例,年龄(28±2)岁;女性4例,年龄(30±3)岁。采集志愿者的静脉血液样本放入6种临床上日常使用的真空采血管,并按采血管的种类分为6组。采用弱阳离子磁珠提取多肽,Clin-TOF平台进行检测,通过BioExplorer软件和SPSS22.0进行多肽峰的比较。结果 6组采血管共出峰117个,108个多肽峰具有差异(P <0.05),其中95个具有显著差异(P <0.01),血浆管之间差异峰的数量显著高于血清管之间;分离胶促凝管正态分布的血清多肽峰最多(110个),且峰强度大于300的强势峰出峰数均值最高,标准差最小(27.7±1.97);根据正态分布多肽峰数、强势峰出峰均值、全峰强度、强势峰强度这四个指标进行因子分析,分离胶促凝管得分最高。结论含有分离胶的促凝管是基质辅助激光解析/电离飞行时间质谱分析的最佳采血管。
Objective To investigate the influence of blood collection tubes with different additives on serum or plasma polypeptide detection and confirm the optimal vacuum tube for the test of serum polypeptides. Methods Vein blood samples were taken from 6 volunteers, including 2 males with age of(28±2) years and 4 females with age of(30±3) years. And the samples from each case were divided and transferred to 6 types of blood collection tubes. The polypeptides were extracted with weak cationic magnetic beads and detected with clin-tof platform. The polypeptide peaks were analyzed and compared by BioExplorer and SPSS 22.0. Results In total, 108 out of 117 peptide peaks showed differences among the six type of tubes(P <0.05), and 95 showed significant differences(P <0.01). The number of different peptide peaks among plasma tubes was significantly higher than that among serum tubes. The highest proportion of normality peptide peaks(110) appeared in the sixth group(coagulation promoting tube containing separation glue), where the mean of intensive peaks number(peak intensity>300) was the largest and the standard deviation was the smallest(27.7±1.97). Four factors(the whole peak intensity, the peak numbers with normal distribution, the average of intensive peak numbers, and intensive peaks' intensity) were investigated with factor analysis to rank tube types, and the sixth group got the highest score. Conclusion The coagulation promoting tube containing separation glue is determined as the most optimal blood collection tube for MALDI-TOF MS.
Objective To investigate the influence of blood collection tubes with different additives on serum or plasma polypeptide detection and confirm the optimal vacuum tube for the test of serum polypeptides. Methods Vein blood samples were taken from 6 volunteers, including 2 males with age of(28±2) years and 4 females with age of(30±3) years. And the samples from each case were divided and transferred to 6 types of blood collection tubes. The polypeptides were extracted with weak cationic magnetic beads and detected with clin-tof platform. The polypeptide peaks were analyzed and compared by BioExplorer and SPSS 22.0. Results In total, 108 out of 117 peptide peaks showed differences among the six type of tubes(P <0.05), and 95 showed significant differences(P <0.01). The number of different peptide peaks among plasma tubes was significantly higher than that among serum tubes. The highest proportion of normality peptide peaks(110) appeared in the sixth group(coagulation promoting tube containing separation glue), where the mean of intensive peaks number(peak intensity>300) was the largest and the standard deviation was the smallest(27.7±1.97). Four factors(the whole peak intensity, the peak numbers with normal distribution, the average of intensive peak numbers, and intensive peaks' intensity) were investigated with factor analysis to rank tube types, and the sixth group got the highest score. Conclusion The coagulation promoting tube containing separation glue is determined as the most optimal blood collection tube for MALDI-TOF MS.
引文
1张宁,陆学东,吴正林.飞行时间质谱技术在糖尿病肾病患者尿蛋白成分分析中的研究进展[J].现代检验医学杂志,2016,31(5):160-164.
2 Bao R,Gao X,Hu B,et al.Matrix-assisted laser desorption ionization time-of-flight mass spectrometry:a powerful tool for identification of Corynebacterium species[J].J Thorac Dis,2017,9(9):3239-3245.
3 Calderaro A,Buttrini M,Montecchini S,et al.MALDI-TOF MS as a new tool for the identification of Dientamoeba fragilis[J].Parasit Vectors,2018,11(1):11.
4 Liu DX,He JN.Effects of additives in blood collection tubes on testing the alcohol concentration in blood samples[J].Fa Yi Xue Za Zhi,2014,30(6):452-455.
5 Ridefelt P,?kerfeldt T,Helmersson-Karlqvist J.Increased plasma glucose levels after change of recommendation from NaF to citrate blood collection tubes[J].Clin Biochem,2014,47(7-8):625-628.
6李慧,白利芬,惠玉芬,等.不同采血管在不同存放条件下对循环酶法同型半胱氨酸测定结果的影响[J].检验医学与临床,2015,12(22):3294-3296.
7毛远丽,秦建成,李波.基质辅助激光解吸电离飞行时间质谱技术在感染性疾病病原及耐药检测中的应用[J].传染病信息,2014,27(5):270-273.
8 Liu X,Hoene M,Wang X,et al.Serum or plasma,what is the difference?Investigations to facilitate the sample material selection decision making process for metabolomics studies and beyond[J].Analytica Chimica Acta,2018,1037:293-300.
9 Nishiumi S,Suzuki M,Kobayashi T,et al.Differences in metabolite profiles caused by pre-analytical blood processing procedures[J].JBiosci Bioeng,2018,125(5):613-618.
10 Zhou Z,Chen Y,He J,et al.Systematic evaluation of serum and plasma collection on the endogenous metabolome[J].Bioanalysis,2017,9(3):239-250.
11 Ilies M,Iuga C A,Loghin F,et al.Impact of blood sample collection methods on blood protein profiling studies[J].Clinica Chimica Acta,2017,471:128-134.
12 Hebels DG,Georgiadis P,Keun HC,et al.Performance in omics analyses of blood samples in long-term storage:opportunities for the exploitation of existing biobanks in environmental health research[J].Environ Health Perspect,2013,121(4):480-487.
13 Pinto J,Domingues MR,Galhano E,et al.Human plasma stability during handling and storage:impact on NMR metabolomics[J].Analyst,2014,139(5):1168-1177.
14 Suarez-Diez M,Adam J,Adamski J,et al.Plasma and Serum Metabolite Association Networks:Comparability within and between Studies Using NMR and MS Profiling[J].J Proteome Res,2017,16(7):2547-2559.
15 Yin P,Lehmann R,Xu G.Effects of pre-analytical processes on blood samples used in metabolomics studies[J].Anal Bioanal Chem,2015,407(17):4879-4892.
16 Paglia G,Del Greco FM,Sigurdsson BB,et al.Influence of collection tubes during quantitative targeted metabolomics studies in human blood samples[J].Clin Chim Acta,2018,486:320-328.
17 Lin Z,Zhang Z,Lu H,et al.Joint MS-based platforms for comprehensive comparison of rat plasma and serum metabolic profiling[J].Biomed Chromatogr,2014,28(9):1235-1245.
18 Breier M,Wahl S,Prehn C,et al.Targeted metabolomics identifies reliable and stable metabolites in human serum and plasma samples[J].PLoS ONE,2014,9(2):e89728.
2 Bao R,Gao X,Hu B,et al.Matrix-assisted laser desorption ionization time-of-flight mass spectrometry:a powerful tool for identification of Corynebacterium species[J].J Thorac Dis,2017,9(9):3239-3245.
3 Calderaro A,Buttrini M,Montecchini S,et al.MALDI-TOF MS as a new tool for the identification of Dientamoeba fragilis[J].Parasit Vectors,2018,11(1):11.
4 Liu DX,He JN.Effects of additives in blood collection tubes on testing the alcohol concentration in blood samples[J].Fa Yi Xue Za Zhi,2014,30(6):452-455.
5 Ridefelt P,?kerfeldt T,Helmersson-Karlqvist J.Increased plasma glucose levels after change of recommendation from NaF to citrate blood collection tubes[J].Clin Biochem,2014,47(7-8):625-628.
6李慧,白利芬,惠玉芬,等.不同采血管在不同存放条件下对循环酶法同型半胱氨酸测定结果的影响[J].检验医学与临床,2015,12(22):3294-3296.
7毛远丽,秦建成,李波.基质辅助激光解吸电离飞行时间质谱技术在感染性疾病病原及耐药检测中的应用[J].传染病信息,2014,27(5):270-273.
8 Liu X,Hoene M,Wang X,et al.Serum or plasma,what is the difference?Investigations to facilitate the sample material selection decision making process for metabolomics studies and beyond[J].Analytica Chimica Acta,2018,1037:293-300.
9 Nishiumi S,Suzuki M,Kobayashi T,et al.Differences in metabolite profiles caused by pre-analytical blood processing procedures[J].JBiosci Bioeng,2018,125(5):613-618.
10 Zhou Z,Chen Y,He J,et al.Systematic evaluation of serum and plasma collection on the endogenous metabolome[J].Bioanalysis,2017,9(3):239-250.
11 Ilies M,Iuga C A,Loghin F,et al.Impact of blood sample collection methods on blood protein profiling studies[J].Clinica Chimica Acta,2017,471:128-134.
12 Hebels DG,Georgiadis P,Keun HC,et al.Performance in omics analyses of blood samples in long-term storage:opportunities for the exploitation of existing biobanks in environmental health research[J].Environ Health Perspect,2013,121(4):480-487.
13 Pinto J,Domingues MR,Galhano E,et al.Human plasma stability during handling and storage:impact on NMR metabolomics[J].Analyst,2014,139(5):1168-1177.
14 Suarez-Diez M,Adam J,Adamski J,et al.Plasma and Serum Metabolite Association Networks:Comparability within and between Studies Using NMR and MS Profiling[J].J Proteome Res,2017,16(7):2547-2559.
15 Yin P,Lehmann R,Xu G.Effects of pre-analytical processes on blood samples used in metabolomics studies[J].Anal Bioanal Chem,2015,407(17):4879-4892.
16 Paglia G,Del Greco FM,Sigurdsson BB,et al.Influence of collection tubes during quantitative targeted metabolomics studies in human blood samples[J].Clin Chim Acta,2018,486:320-328.
17 Lin Z,Zhang Z,Lu H,et al.Joint MS-based platforms for comprehensive comparison of rat plasma and serum metabolic profiling[J].Biomed Chromatogr,2014,28(9):1235-1245.
18 Breier M,Wahl S,Prehn C,et al.Targeted metabolomics identifies reliable and stable metabolites in human serum and plasma samples[J].PLoS ONE,2014,9(2):e89728.