基于超高效液相色谱质谱联用的艰难梭菌腹泻患者粪便代谢组学研究
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摘要
目的 探索艰难梭菌腹泻患者粪便代谢谱特点,为揭示其发病机制、建立新的诊断方法提供参考。方法 收集2013年7月-2014年2月入住医院重症监护室患者的腹泻粪便41份,其中艰难梭菌组21份,艰难梭菌阴性组20份,另收集健康对照者粪便23份,使用超高效液相色谱质谱联用检测其代谢谱,采用多元统计分析进行数据分析。结果 三组在无监督的主成分分析得分图上有分离的趋势,而在有监督的正交偏最小二乘法判别分析得分图上清晰有序排列,三组两两比较时,在各得分图中区分度更好。正交偏最小二乘法判别分析对于艰难梭菌组和腹泻组样本判断的准确率、灵敏度和特异性均为100%,受试者工作曲线下面积为1.000。艰难梭菌组患者粪便中的甘氨熊脱氧胆酸(Glycoursodeoxycholic acid,GUDCA)、甘氨鹅脱氧胆酸(Glycochenodeoxycholic acid,GCDCA)、溶血卵磷脂18∶0、溶血卵磷脂18∶1、亚油酸、油酸的相对丰度较高,卵磷脂18∶0/18∶1的相对丰度较低。结论 艰难梭菌感染者有着独特的粪便代谢谱,可用代谢组学模型来诊断。
OBJECTIVE The aim of the study was to characterize the fecal metabolome of Clostridium difficile diarrhea patients, so as to provide useful information for revealing its pathogenesis and establishing new diagnostic methods. METHODS We collected 41 fecal samples between Jul. 2013 and Feb. 2014, among them 21 samples were C difficile positive(C group), and 20 samples were C difficile negative(F group). Another 23 fecal samples from healthy controls were selected as N group. Ultra-performance liquid chromatography-mass spectrometry was used to detect the fecal metabolome. Multivariate statistical analysis was used for data analysis. RESULTS The three groups tended to be separated from each other on the unsupervised principal component analysis score plot, while they were arranged in a clear and orderly manner in the supervised orthogonal partial least squares discriminant analysis score plot. When the three groups were compared in pairs, the discriminations in each score plot were better. The accuracy, sensitivity and specificity of orthogonal partial least squares discriminant analysis for discriminating C difficile diarrhea and other diarrhea were all 100%, and the area under ROC curve was 1.000. The relative abundance of glycoursodeoxycholic acid, glycochenodeoxycholic acid, lysophosphatidylcholin(18∶0, 18∶1), linoleic acid and oleic acid in feces of C group was higher, whereas the relative abundance of phosphatidylcholin 18∶0/18∶1 was lower than that in other groups. CONCLUSION C difficile infection has unique fecal metabolome, and it could be diagnosed by metabolomic models.
OBJECTIVE The aim of the study was to characterize the fecal metabolome of Clostridium difficile diarrhea patients, so as to provide useful information for revealing its pathogenesis and establishing new diagnostic methods. METHODS We collected 41 fecal samples between Jul. 2013 and Feb. 2014, among them 21 samples were C difficile positive(C group), and 20 samples were C difficile negative(F group). Another 23 fecal samples from healthy controls were selected as N group. Ultra-performance liquid chromatography-mass spectrometry was used to detect the fecal metabolome. Multivariate statistical analysis was used for data analysis. RESULTS The three groups tended to be separated from each other on the unsupervised principal component analysis score plot, while they were arranged in a clear and orderly manner in the supervised orthogonal partial least squares discriminant analysis score plot. When the three groups were compared in pairs, the discriminations in each score plot were better. The accuracy, sensitivity and specificity of orthogonal partial least squares discriminant analysis for discriminating C difficile diarrhea and other diarrhea were all 100%, and the area under ROC curve was 1.000. The relative abundance of glycoursodeoxycholic acid, glycochenodeoxycholic acid, lysophosphatidylcholin(18∶0, 18∶1), linoleic acid and oleic acid in feces of C group was higher, whereas the relative abundance of phosphatidylcholin 18∶0/18∶1 was lower than that in other groups. CONCLUSION C difficile infection has unique fecal metabolome, and it could be diagnosed by metabolomic models.
引文
[1] 中华预防医学会医院感染控制分会.中国艰难梭菌医院感染预防与控制指南[J].中华医院感染学杂志,2018,28(23):3674-3680.
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[13] Weingarden AR,Chen C,Bobr A,et al.Microbiota transplantation restores normal fecal bile acid composition in recurrent Clostridium difficile infection[J].Am J Physiol Gastrointest Liver Physiol,2014,306(4):G310-G319.
[14] Chen Y,Qin N,Guo J,et al.Functional gene arrays-based analysis of fecal microbiomes in patients with liver cirrhosis[J].BMC Genomics,2014,15:753.
[15] 赵杏珍,杨靖,赵建宏.肠道微生物群和免疫反应在艰难梭菌感染中的作用研究进展[J].中国感染控制杂志,2018,17(12):1117-1121.
[16] Theriot CM,Koenigsknecht MJ,Carlson PE Jr,et al.Antibiotic-induced shifts in the mouse gut microbiome and metabolome increase susceptibility to Clostridium difficile infection[J].Nat Commun,2014,5:3114.
[17] Kellingray L,Gall GL,Defernez M,et al.Microbial taxonomic and metabolic alterations during faecal microbiota transplantation to treat Clostridium difficile infection[J].J Infect,2018,77(2):107-118.
[18] Theriot CM,Young VB.Microbial and metabolic interactions between the gastrointestinal tract and Clostridium difficile infection[J].Gut Microbes,2014,5(1):86-95.
[19] Zhou P,Zhou N,Shao L,et al.Diagnosis of Clostridium difficile infection using an UPLC-MS based metabolomics method[J].Metabolomics,2018,14(8):102.
[20] Zhou P,Shao L,Zhao L,et al.Efficacy of fluidized bed bioartificial liver in treating fulminant hepatic failure in pigs:a metabolomics study[J].Sci Rep,2016,6:26070.
[21] Zhou P,Li J,Shao L,et al.Dynamic patterns of serum metabolites in fulminant hepatic failure pigs[J].Metabolomics,2012,8(5):869-879.
[22] Greathouse KL,Harris CC,Bultman SJ.Dysfunctional families:Clostridium scindens and secondary bile acids inhibit the growth of Clostridium difficile[J].Cell Metab,2015,21(1):9-10.
[23] Huang HJ,Zhang AY,Cao HC,et al.Metabolomic analyses of faeces reveals malabsorption in cirrhotic patients[J].Dig Liver Dis,2013,45(8):677-682.
[24] Dekker N.Outer-membrane phospholipase A:known structure,unknown biological function[J].Mol Microbiol,2000,35(4):711-717.
[25] Sitkiewicz I,Stockbauer KE,Musser JM.Secreted bacterial phospholipase A2 enzymes:better living through phospholipolysis[J].Trends Microbiol,2007,15(2):63-69.
[26] Wang Y,de Valliere C,Imenez Silva PH,et al.The proton-activated receptor GPR4 modulates intestinal inflammation[J].J Crohns Colitis,2018,12(3):355-368.
[2] Li C,Teng P,Peng Z,et al.Bis-cyclic guanidines as a novel class of compounds potent against Clostridium difficile[J].ChemMedChem,2018,13(14):1414-1420.
[3] Freeman J,Bauer MP,Baines SD,et al.The changing epidemiology of Clostridium difficile infections[J].Clin Microbiol Rev,2010,23(3):529-549.
[4] 孔懿,叶家欣.艰难梭菌流行病学国内外研究进展[J].中国感染控制杂志,2017,16(3):280-286.
[5] Banaei N,Anikst V,Schroeder LF.Burden of Clostridium difficile infection in the United States[J].N Engl J Med,2015,372(24):2368-2369.
[6] Li C,Li Y,Huai Y,et al.Incidence and outbreak of healthcare-onset healthcare-associated Clostridioides difficile infections among intensive care patients in a large teaching hospital in China[J].Front Microbiol,2018,9:566.
[7] Wang X,Cai L,Yu R,et al.ICU-onset Clostridium difficile infection in a university hospital in China:a prospective cohort study[J].PLOS ONE,2014,9(11):e111735.
[8] Li C,Duan J,Liu S,et al.Assessing the risk and disease burden of Clostridium difficile infection among patients with hospital-acquired pneumonia at a University Hospital in Central China[J].Infection,2017,45(5):621-628.
[9] Berry N,Sewell B,Jafri S,et al.Real-time polymerase chain reaction correlates well with clinical diagnosis of Clostridium difficile infection[J].J Hosp Infect,2014,87(2):109-114.
[10] 刘昊,徐修礼,张瑞雪.艰难梭菌感染实验室检测方法进展[J].中国感染控制杂志,2017,16(1):89-93.
[11] Bomers MK,Menke FP,Savage RS,et al.Rapid,accurate,and on-site detection of C.difficile in stool samples[J].Am J Gastroenterol,2015,110(4):588-594.
[12] Peng Z,Ling L,Stratton CW,et al.Advances in the diagnosis and treatment of Clostridium difficile infections[J].Emerg Microbes Infect,2018,7(1):15.
[13] Weingarden AR,Chen C,Bobr A,et al.Microbiota transplantation restores normal fecal bile acid composition in recurrent Clostridium difficile infection[J].Am J Physiol Gastrointest Liver Physiol,2014,306(4):G310-G319.
[14] Chen Y,Qin N,Guo J,et al.Functional gene arrays-based analysis of fecal microbiomes in patients with liver cirrhosis[J].BMC Genomics,2014,15:753.
[15] 赵杏珍,杨靖,赵建宏.肠道微生物群和免疫反应在艰难梭菌感染中的作用研究进展[J].中国感染控制杂志,2018,17(12):1117-1121.
[16] Theriot CM,Koenigsknecht MJ,Carlson PE Jr,et al.Antibiotic-induced shifts in the mouse gut microbiome and metabolome increase susceptibility to Clostridium difficile infection[J].Nat Commun,2014,5:3114.
[17] Kellingray L,Gall GL,Defernez M,et al.Microbial taxonomic and metabolic alterations during faecal microbiota transplantation to treat Clostridium difficile infection[J].J Infect,2018,77(2):107-118.
[18] Theriot CM,Young VB.Microbial and metabolic interactions between the gastrointestinal tract and Clostridium difficile infection[J].Gut Microbes,2014,5(1):86-95.
[19] Zhou P,Zhou N,Shao L,et al.Diagnosis of Clostridium difficile infection using an UPLC-MS based metabolomics method[J].Metabolomics,2018,14(8):102.
[20] Zhou P,Shao L,Zhao L,et al.Efficacy of fluidized bed bioartificial liver in treating fulminant hepatic failure in pigs:a metabolomics study[J].Sci Rep,2016,6:26070.
[21] Zhou P,Li J,Shao L,et al.Dynamic patterns of serum metabolites in fulminant hepatic failure pigs[J].Metabolomics,2012,8(5):869-879.
[22] Greathouse KL,Harris CC,Bultman SJ.Dysfunctional families:Clostridium scindens and secondary bile acids inhibit the growth of Clostridium difficile[J].Cell Metab,2015,21(1):9-10.
[23] Huang HJ,Zhang AY,Cao HC,et al.Metabolomic analyses of faeces reveals malabsorption in cirrhotic patients[J].Dig Liver Dis,2013,45(8):677-682.
[24] Dekker N.Outer-membrane phospholipase A:known structure,unknown biological function[J].Mol Microbiol,2000,35(4):711-717.
[25] Sitkiewicz I,Stockbauer KE,Musser JM.Secreted bacterial phospholipase A2 enzymes:better living through phospholipolysis[J].Trends Microbiol,2007,15(2):63-69.
[26] Wang Y,de Valliere C,Imenez Silva PH,et al.The proton-activated receptor GPR4 modulates intestinal inflammation[J].J Crohns Colitis,2018,12(3):355-368.
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