早期白假丝酵母血流感染大鼠模型的血浆代谢组学分析
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摘要
为探寻白假丝酵母(又称白念珠菌)早期感染的血浆代谢标记,采用尾静脉注射白念珠菌方法建立大鼠白念珠菌感染模型。将20只大鼠按随机数字法分为对照组和白念珠菌组,每组10只。应用超高效液相色谱-四级杆飞行时间串联质谱(ultra-high performance liquid chromatography/quadrupole-time-of-flight tandem mass spectrometry,UHPLC-Q-TOF-MS)技术结合数据依赖性采集方式检测大鼠血浆中的代谢物,采用SIMCA-P软件对所测数据分别进行偏最小二乘法判别分析(partial least squares discrimination analysis,PLS-DA)、正交偏最小二乘法判别分析(orthogonal PLS-DA,OPLS-DA)及主成分分析(principal component analysis,PCA),以进行模式识别,区分白念珠菌组与正常对照组血浆代谢物的差异。根据OPLS-DA模型的变量投影重要度(variable importance in the projection,VIP)筛选可能的代谢标记。结果显示,白念珠菌组与对照组的血浆代谢物存在明显差异,OPLS-DA、PLS-DA及PCA模型均可区分两组,初步确认了18个正离子模式鉴定的差异物,对应化合物可能是大鼠念珠菌感染的潜在标记。受试者工作特征曲线(receiver operating characteristic curve,ROC)分析发现,LysoPC(14∶0)、LysoPC(18∶1(9Z))、LysoPC(18∶0)、LTryptophan、L-Gulonic acidγ-lactone这5个代谢物ROC的曲线下面积均>0.90。本研究初步筛选出早期白念珠菌感染的可能代谢生物标记,可为白念珠菌感染早期诊断和治疗提供理论基础。
The present paper aimed to find the metabolic biomarkers of Candida albicans(C.albicans)infection in early stage.The model of C.albicans-infected Wistar rats was established by tail vein injection of C.albicans liquid.Twenty rats were divided into control group and C.albicans group according to the random number table,10 in each group.The samples were analyzed by ultra-high performance liquid chromatography/quadrupole-time-of-flight tandem mass spectrometry(UHPLC-Q-TOF-MS)combined with data-dependent acquisition.The measured data were analyzed using SIMCA-P software.Partial least squares discrimination analysis(PLS-DA),orthogonal PLS-DA(OPLS-DA)and principal component analysis(PCA)were used for pattern recognition analysis,respectively,to distinguish the differences in plasma metabolites between the C.albicans group and the control group.The possible metabolic markers were screened according to the variable importance in the projection(VIP)values of OPLS-DA model.The results showed that plasma metabolites in the two groups differed significantly.The OPLS-DA,PLS-DA and PCA models were effective methods to distinguish the two groups.The differences in 18 metabolites were preliminary confirmed.Receiver operating characteristic curve(ROC)analysis demonstrated that the areas under ROC(AUCs)of LysoPC(14∶0),LysoPC(18∶1(9 Z)),LysoPC(18∶0),L-tryptophan,Lgulonic acidγ-lactone were all higher than 0.90.The study indicates that the corresponding compounds might be potential markers of Candida infection in Wistar rats,which may help the early diagnosis and treatment of C.albicans infection.
The present paper aimed to find the metabolic biomarkers of Candida albicans(C.albicans)infection in early stage.The model of C.albicans-infected Wistar rats was established by tail vein injection of C.albicans liquid.Twenty rats were divided into control group and C.albicans group according to the random number table,10 in each group.The samples were analyzed by ultra-high performance liquid chromatography/quadrupole-time-of-flight tandem mass spectrometry(UHPLC-Q-TOF-MS)combined with data-dependent acquisition.The measured data were analyzed using SIMCA-P software.Partial least squares discrimination analysis(PLS-DA),orthogonal PLS-DA(OPLS-DA)and principal component analysis(PCA)were used for pattern recognition analysis,respectively,to distinguish the differences in plasma metabolites between the C.albicans group and the control group.The possible metabolic markers were screened according to the variable importance in the projection(VIP)values of OPLS-DA model.The results showed that plasma metabolites in the two groups differed significantly.The OPLS-DA,PLS-DA and PCA models were effective methods to distinguish the two groups.The differences in 18 metabolites were preliminary confirmed.Receiver operating characteristic curve(ROC)analysis demonstrated that the areas under ROC(AUCs)of LysoPC(14∶0),LysoPC(18∶1(9 Z)),LysoPC(18∶0),L-tryptophan,Lgulonic acidγ-lactone were all higher than 0.90.The study indicates that the corresponding compounds might be potential markers of Candida infection in Wistar rats,which may help the early diagnosis and treatment of C.albicans infection.
引文
[1]李光辉,朱德妹,汪复,倪语星,孙景勇,徐英春,张小江,胡云建,艾效曼,俞云松,杨青,孙自镛,陈中举,贾蓓,黄文祥,卓超,苏丹虹,魏莲花,吴玲,张朝霞,季萍,王传清,王爱敏,张泓,孔菁,徐元宏,沈继录,单斌,杜艳.2010年中国CHINET血流感染的病原菌分布及耐药性[J].中国感染与化疗杂志,2012,12(4):251-258.
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[3]刘蓉,乔莉,张劲松.念珠菌血流感染病原学及影响预后的危险因素分析[J].临床急诊杂志,2015,16(1):5-8.
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[6]Plumb RS,Granger JH,Stumpf CL,Johnson KA,Smith BW,Gaulitz S,Wilson ID,Castro-Perez J.A rapid screening approach to metabonomics using UPLC and oaTOF mass spectrometry:application to age,gender and diurnal variation in normal/Zucker obese rats and black,white and nude mice[J].Analyst,2005,130(6):844-849.
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[8]汪甜,叶燕青,潘庭静.真菌血流感染临床特点及危险因素分析[J].临床内科杂志,2016,33(7):475-478.
[9]阿基业.代谢组学数据处理方法---主成分分析[J].中国临床药理学与治疗学,2010,15(5):481-489.
[10]Surmacki J,Brozek-Pluska B,Kordek R,Abramczyk H.The lipid-reactive oxygen species phenotype of breast cancer.Raman spectroscopy and mapping,PCA and PLSDA for invasive ductal carcinoma and invasive lobular carcinoma.Molecular tumorigenic mechanisms beyond Warburg effect[J].Analyst,2015,140(7):2121-2133.
[11]柯朝甫,武晓岩,侯艳,李康.偏最小二乘判别分析交叉验证在代谢组学数据分析中的应用[J].中国卫生统计,2014,31(1):85-87.
[12]Westerhuis JA,van Velzen EJ,Hoefsloot HC,Smilde AK.Multivariate paired data analysis:multilevel PLSDA versus OPLSDA[J].Metabolomics,2010,6(1):119-128.
[13]Zelante T,Iannitti RG,Cunha C,De Luca A,Giovannini G,Pieraccini G,Zecchi R,D’Angelo C,Massi-Benedetti C,Fallarino F,Carvalho A,Puccetti P,Romani L.Tryptophan catabolites from microbiota engage aryl hydrocarbon receptor and balance mucosal reactivity via interleukin-22[J].Immunity,2013,39(2):372-385.
[14]Cervantes-Barragan L,Chai JN,Tianero MD,Di Luccia B,Ahern PP,Merriman J,Cortez VS,Caparon MG,Donia MS,Gilfillan S,Cella M,Gordon JI,Hsieh CS,Colonna M.Lactobacillus reuteri induces gut intraepithelial CD4+CD8αα+T cells[J].Science,2017,357(6353):806-810.
[15]Cheng SC,Joosten LA,Kullberg BJ,Netea MG.Interplay between Candida albicans and the mammalian innate host defense[J].Infect Immun,2012,80(4):1304-1313.
[16]Brown AJ,Brown GD,Netea MG,Gow NA.Metabolism impacts upon Candida immunogenicity and pathogenicity at multiple levels[J].Trends Microbiol,2014,22(11):614-622.
[17]Hung ND,Kim MR,Sok DE.Mechanisms for antiinflammatory effects of 1-[15(S)-hydroxyeicosapentaenoyl]lysophosphatidylcholine,administered intraperitoneally,in zymosan A-induced peritonitis[J].Br J Pharmacol,2011,162(5):1119-1135.
[18]Shi Y,Zhang P,Zhang L,Osman H,Mohler ER 3rd,Macphee C,Zalewski A,Postle A,Wilensky RL.Role of lipoprotein-associated phospholipase A2 in leukocyte activation and inflammatory responses[J].Atherosclerosis,2007,191(1):54-62.
[19]冉宝才,胡仁静,胡锡池.血浆1,3-β-D葡聚糖的检测在深部真菌感染诊断中的应用价值[J].国际检验医学杂志,2017,38(13):1770-1772,1775.
[20]黄云昆,史玉芹,朱雯梅,王佳,姚瑶.血浆(1,3)-β-D葡聚糖检测对深部真菌感染诊断的临床评价[J].检验医学与临床,2013,10(5):520-521,523.
[2]吴昌德,郭凤梅,邱海波.中国ICU患者侵袭性念珠菌感染现状[J].中国医刊,2018,53(6):585-587.
[3]刘蓉,乔莉,张劲松.念珠菌血流感染病原学及影响预后的危险因素分析[J].临床急诊杂志,2015,16(1):5-8.
[4]许国旺,路鑫,杨胜利.代谢组学研究进展[J].中国医学科学院学报,2007,29(6):701-711.
[5]Nicholson JK,Lindon JC,Holmes E.‘Metabonomics’:understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data[J].Xenobiotica,1999,29(11):1181-1189.
[6]Plumb RS,Granger JH,Stumpf CL,Johnson KA,Smith BW,Gaulitz S,Wilson ID,Castro-Perez J.A rapid screening approach to metabonomics using UPLC and oaTOF mass spectrometry:application to age,gender and diurnal variation in normal/Zucker obese rats and black,white and nude mice[J].Analyst,2005,130(6):844-849.
[7]Ivanisevic J,Zhu ZJ,Plate L,Tautenhahn R,Chen S,O’ Brien PJ,Johnson CH,Marletta MA,Patti GJ,Siuzdak G.Toward‘omic’scale metabolite profiling:a dual separation-mass spectrometry approach for coverage of lipids and central carbon metabolism[J].Anal Chem,2013,85(14):6876-6884.
[8]汪甜,叶燕青,潘庭静.真菌血流感染临床特点及危险因素分析[J].临床内科杂志,2016,33(7):475-478.
[9]阿基业.代谢组学数据处理方法---主成分分析[J].中国临床药理学与治疗学,2010,15(5):481-489.
[10]Surmacki J,Brozek-Pluska B,Kordek R,Abramczyk H.The lipid-reactive oxygen species phenotype of breast cancer.Raman spectroscopy and mapping,PCA and PLSDA for invasive ductal carcinoma and invasive lobular carcinoma.Molecular tumorigenic mechanisms beyond Warburg effect[J].Analyst,2015,140(7):2121-2133.
[11]柯朝甫,武晓岩,侯艳,李康.偏最小二乘判别分析交叉验证在代谢组学数据分析中的应用[J].中国卫生统计,2014,31(1):85-87.
[12]Westerhuis JA,van Velzen EJ,Hoefsloot HC,Smilde AK.Multivariate paired data analysis:multilevel PLSDA versus OPLSDA[J].Metabolomics,2010,6(1):119-128.
[13]Zelante T,Iannitti RG,Cunha C,De Luca A,Giovannini G,Pieraccini G,Zecchi R,D’Angelo C,Massi-Benedetti C,Fallarino F,Carvalho A,Puccetti P,Romani L.Tryptophan catabolites from microbiota engage aryl hydrocarbon receptor and balance mucosal reactivity via interleukin-22[J].Immunity,2013,39(2):372-385.
[14]Cervantes-Barragan L,Chai JN,Tianero MD,Di Luccia B,Ahern PP,Merriman J,Cortez VS,Caparon MG,Donia MS,Gilfillan S,Cella M,Gordon JI,Hsieh CS,Colonna M.Lactobacillus reuteri induces gut intraepithelial CD4+CD8αα+T cells[J].Science,2017,357(6353):806-810.
[15]Cheng SC,Joosten LA,Kullberg BJ,Netea MG.Interplay between Candida albicans and the mammalian innate host defense[J].Infect Immun,2012,80(4):1304-1313.
[16]Brown AJ,Brown GD,Netea MG,Gow NA.Metabolism impacts upon Candida immunogenicity and pathogenicity at multiple levels[J].Trends Microbiol,2014,22(11):614-622.
[17]Hung ND,Kim MR,Sok DE.Mechanisms for antiinflammatory effects of 1-[15(S)-hydroxyeicosapentaenoyl]lysophosphatidylcholine,administered intraperitoneally,in zymosan A-induced peritonitis[J].Br J Pharmacol,2011,162(5):1119-1135.
[18]Shi Y,Zhang P,Zhang L,Osman H,Mohler ER 3rd,Macphee C,Zalewski A,Postle A,Wilensky RL.Role of lipoprotein-associated phospholipase A2 in leukocyte activation and inflammatory responses[J].Atherosclerosis,2007,191(1):54-62.
[19]冉宝才,胡仁静,胡锡池.血浆1,3-β-D葡聚糖的检测在深部真菌感染诊断中的应用价值[J].国际检验医学杂志,2017,38(13):1770-1772,1775.
[20]黄云昆,史玉芹,朱雯梅,王佳,姚瑶.血浆(1,3)-β-D葡聚糖检测对深部真菌感染诊断的临床评价[J].检验医学与临床,2013,10(5):520-521,523.