慢性阻塞性肺疾病比较蛋白质组学初步研究
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摘要
目的:通过对非COPD不吸烟者(对照组)、非COPD吸烟者(吸烟组)、吸烟COPD患者(COPD组)肺组织表达的蛋白质组进行比较。寻找差异表达蛋白,以期为揭示COPD的发生、发展机制提供新的线索。
方法:收集因肺癌行肺叶切除的对照组、吸烟组、COPD组的肺组织标本各24例(其中吸烟组与COPD组的吸烟指数无显著性差异),提取组织总蛋白,各组内按照随机每6例构建一个蛋白池。对每一个蛋白池进行双向凝胶电泳(2-DE),通过对凝胶进行图像扫描获取2-DE图像,利用PDQUEST软件对3组研究对象的2-DE图像进行比较分析,识别出差异表达的蛋白质斑点。从凝胶中切取差异表达的蛋白质斑点,TPCK-Trypsin酶解后进行MOLDI-TOF-MS分析,获取肽质量指纹图谱,借助于Mascot Distiller/Mascot Wizard软件进行蛋白质鉴定。对鉴定的部分代表性的蛋白质进行免疫组织化学染色和Western blot检测,一方面验证蛋白质组学实验结果,另一方面对蛋白质的表达进行定位和半定量分析。
结果:
1.对照组、吸烟组、COPD组的肺组织蛋白质组进行2-DE分别分离出775±38、641±33、729±21个蛋白质斑点。通过对3组研究对象的2-DE图像进行比较分析,共找到表达差异大于1.5倍的蛋白质斑点47个。通过对47个差异表达蛋白质斑点进行质谱分析和数据库鉴定,共鉴定出24种蛋白质,功能主要涉及基本代谢酶类、氧化应激蛋白、凝血/纤溶相关蛋白、蛋白降解相关酶及细胞生长分化相关蛋白等,其中21种蛋白在COPD肺组织蛋白质组学研究中未见报道。与对照组相比,22种蛋白质在吸烟组表达上调,在COPD组表达水平进一步增高。
2.免疫组织化学染色结果显示:HSP27蛋白表达于肺内各种类型细胞,Cathepsin D主要表达于肺泡结构区域,PPIA及D4-GDI表达于除支气管上皮细胞以外的各种肺组织细胞,3组间的表达强度变化趋势与蛋白质组学研究结果一致。
3.Western blot检测结果显示:与不吸烟者相比较,HSP27、Cathepsin D、PPIA、D4-GDI在吸烟者肺组织表达上调,COPD患者较非COPD吸烟者表达水平进一步增高。3组间的表达强度变化趋势与蛋白质组学研究结果一致。
结论:
1.通过对对照组、吸烟组及COPD组进行蛋白质组学比较分析,成功鉴定了24种差异表达的蛋白质,主要为基本代谢酶类、凝血/纤溶相关蛋白质、氧化应激相关酶类、蛋白降解相关酶以及细胞生长分化相关蛋白质。
2.本研究结果首次说明:吸烟能够导致肺组织HSP27、PPIA及D4-GDI等蛋白质表达水平升高,吸烟者肺组织的HSP27、Cathepsin D、PPIA及D4-GDI等蛋白质表达水平与COPD的发病机制和COPD易感性相关。
Objective: Proteome expression in lung tissue of non-COPD never smokers (control group), non-COPD smokers (smoking group), smokers with COPD (COPD group) were compared to discover differentially expressed proteins, in order to acquire new clues for exploration the mechanisms of the occurrence and the development of COPD.
Methods: Lung tissue specimens of the control group, smoking group, COPD group were collected from patients accepted lobectomy because of lung cancer for 24 specimens in each group (the smoking index of smoking group was no significant difference compared with COPD group). Total protein were extracted from lung tisseue, then 4 protein pools were built in every group by each 6 cases assemblage randomly. Protein component of protein pools were separated by two-dimensional gel electrophoresis (2-DE), images were acquired by scanning the 2-DE gels and followed by PDQUEST software analysis to identify differentially expressed protein spots between groups. Differentially expressed protein spots were cut from the gels and digested by TPCK-Trypsin for MOLDI-TOF-MS analysis to generate peptide mass fingerprinting(PMF). Proteins were identified according to the PMF by means of Mascot Distiller/Mascot Wizard online software. Several representative identified proteins were detected by means of immunohistochemical staining and Western-blot to inspection tissue localization and quantitative as well as validate of proteomics results.
Results:
1.For 2-DE, 775±38, 641±33, 729±21 protein spots were separated from the lung tissue proteomes of control group, smoking group and COPD group respectively, and 47 protein spots were found differentially expression between groups more than 1.5 times. Through mass spectrometry analysis and database enquiry, 24 proteins were identified from the 47 differentially expressed protein spots, categorized as basic metabolism enzymes, oxidative stress proteins, coagulation/fibrinolysis protein, protein degradation-related enzymes and cell growth and differentiation related proteins. To the 24 identified proteins,21 have not been reported in smoking/COPD lung proteomics studies hitherto. Compared with the control group, 22 proteins expression up-regulated in the smoking group and further increased in COPD group.
2. Immunohistochemical staining showed that: HSP27 protein expressed in all types of cells in the lungs, Cathepsin D was mainly expressed in alveolar structure region of the lung, PPIA and D4-GDI expressed in variety of lung tissue cells except for bronchial epithelial cells. Expression level change trend between groups was accorded with the proteomics results.
3. Western-blot results showed that: compared to the non-smokers, the expression levels of HSP27, Cathepsin D, PPIA, D4-GDI were up-regulated in smokers. The expression levels of HSP27, Cathepsin D, PPIA, D4-GDI were higher in lung tissue of COPD patients than non-COPD smokers. Expression level change trend between groups was accorded with the proteomics results.
Conclusions:
1. Through the control group, smoking group and COPD group comparative analysis of proteomics , successfully identified 24 differentially expressed proteins, mainly including essential metabolic enzymes, coagulation / fibrinolysis proteins, oxidative stress related enzymes, protein degradation enzymes, and cell growth and differentiation related proteins.
2. The results for the study first time to description: Smoking up-regulate the expression levels of PPIA, D4-GDI, etc. in lung tissue. The expression levels of HSP27, Cathepsin D, PPIA, and D4-GDI,etc. in lung tissue of smokers were involved in COPD development and COPD susceptibility.
方法:收集因肺癌行肺叶切除的对照组、吸烟组、COPD组的肺组织标本各24例(其中吸烟组与COPD组的吸烟指数无显著性差异),提取组织总蛋白,各组内按照随机每6例构建一个蛋白池。对每一个蛋白池进行双向凝胶电泳(2-DE),通过对凝胶进行图像扫描获取2-DE图像,利用PDQUEST软件对3组研究对象的2-DE图像进行比较分析,识别出差异表达的蛋白质斑点。从凝胶中切取差异表达的蛋白质斑点,TPCK-Trypsin酶解后进行MOLDI-TOF-MS分析,获取肽质量指纹图谱,借助于Mascot Distiller/Mascot Wizard软件进行蛋白质鉴定。对鉴定的部分代表性的蛋白质进行免疫组织化学染色和Western blot检测,一方面验证蛋白质组学实验结果,另一方面对蛋白质的表达进行定位和半定量分析。
结果:
1.对照组、吸烟组、COPD组的肺组织蛋白质组进行2-DE分别分离出775±38、641±33、729±21个蛋白质斑点。通过对3组研究对象的2-DE图像进行比较分析,共找到表达差异大于1.5倍的蛋白质斑点47个。通过对47个差异表达蛋白质斑点进行质谱分析和数据库鉴定,共鉴定出24种蛋白质,功能主要涉及基本代谢酶类、氧化应激蛋白、凝血/纤溶相关蛋白、蛋白降解相关酶及细胞生长分化相关蛋白等,其中21种蛋白在COPD肺组织蛋白质组学研究中未见报道。与对照组相比,22种蛋白质在吸烟组表达上调,在COPD组表达水平进一步增高。
2.免疫组织化学染色结果显示:HSP27蛋白表达于肺内各种类型细胞,Cathepsin D主要表达于肺泡结构区域,PPIA及D4-GDI表达于除支气管上皮细胞以外的各种肺组织细胞,3组间的表达强度变化趋势与蛋白质组学研究结果一致。
3.Western blot检测结果显示:与不吸烟者相比较,HSP27、Cathepsin D、PPIA、D4-GDI在吸烟者肺组织表达上调,COPD患者较非COPD吸烟者表达水平进一步增高。3组间的表达强度变化趋势与蛋白质组学研究结果一致。
结论:
1.通过对对照组、吸烟组及COPD组进行蛋白质组学比较分析,成功鉴定了24种差异表达的蛋白质,主要为基本代谢酶类、凝血/纤溶相关蛋白质、氧化应激相关酶类、蛋白降解相关酶以及细胞生长分化相关蛋白质。
2.本研究结果首次说明:吸烟能够导致肺组织HSP27、PPIA及D4-GDI等蛋白质表达水平升高,吸烟者肺组织的HSP27、Cathepsin D、PPIA及D4-GDI等蛋白质表达水平与COPD的发病机制和COPD易感性相关。
Objective: Proteome expression in lung tissue of non-COPD never smokers (control group), non-COPD smokers (smoking group), smokers with COPD (COPD group) were compared to discover differentially expressed proteins, in order to acquire new clues for exploration the mechanisms of the occurrence and the development of COPD.
Methods: Lung tissue specimens of the control group, smoking group, COPD group were collected from patients accepted lobectomy because of lung cancer for 24 specimens in each group (the smoking index of smoking group was no significant difference compared with COPD group). Total protein were extracted from lung tisseue, then 4 protein pools were built in every group by each 6 cases assemblage randomly. Protein component of protein pools were separated by two-dimensional gel electrophoresis (2-DE), images were acquired by scanning the 2-DE gels and followed by PDQUEST software analysis to identify differentially expressed protein spots between groups. Differentially expressed protein spots were cut from the gels and digested by TPCK-Trypsin for MOLDI-TOF-MS analysis to generate peptide mass fingerprinting(PMF). Proteins were identified according to the PMF by means of Mascot Distiller/Mascot Wizard online software. Several representative identified proteins were detected by means of immunohistochemical staining and Western-blot to inspection tissue localization and quantitative as well as validate of proteomics results.
Results:
1.For 2-DE, 775±38, 641±33, 729±21 protein spots were separated from the lung tissue proteomes of control group, smoking group and COPD group respectively, and 47 protein spots were found differentially expression between groups more than 1.5 times. Through mass spectrometry analysis and database enquiry, 24 proteins were identified from the 47 differentially expressed protein spots, categorized as basic metabolism enzymes, oxidative stress proteins, coagulation/fibrinolysis protein, protein degradation-related enzymes and cell growth and differentiation related proteins. To the 24 identified proteins,21 have not been reported in smoking/COPD lung proteomics studies hitherto. Compared with the control group, 22 proteins expression up-regulated in the smoking group and further increased in COPD group.
2. Immunohistochemical staining showed that: HSP27 protein expressed in all types of cells in the lungs, Cathepsin D was mainly expressed in alveolar structure region of the lung, PPIA and D4-GDI expressed in variety of lung tissue cells except for bronchial epithelial cells. Expression level change trend between groups was accorded with the proteomics results.
3. Western-blot results showed that: compared to the non-smokers, the expression levels of HSP27, Cathepsin D, PPIA, D4-GDI were up-regulated in smokers. The expression levels of HSP27, Cathepsin D, PPIA, D4-GDI were higher in lung tissue of COPD patients than non-COPD smokers. Expression level change trend between groups was accorded with the proteomics results.
Conclusions:
1. Through the control group, smoking group and COPD group comparative analysis of proteomics , successfully identified 24 differentially expressed proteins, mainly including essential metabolic enzymes, coagulation / fibrinolysis proteins, oxidative stress related enzymes, protein degradation enzymes, and cell growth and differentiation related proteins.
2. The results for the study first time to description: Smoking up-regulate the expression levels of PPIA, D4-GDI, etc. in lung tissue. The expression levels of HSP27, Cathepsin D, PPIA, and D4-GDI,etc. in lung tissue of smokers were involved in COPD development and COPD susceptibility.
引文
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9 Shuan-ying Yang, Xue-yuan Xiao, Wang-gang Zhang, et al. Application of serum SELDI proteomic patterns in diagnosis of lung cancer[J]. BMC Cancer ,2005, 5:83.
10 Au JS, Cho WC, Yip TT, et al. Deep proteome profiling of sera from never-smoked lung cancer patients[J]. Biomed Pharmacother, 2007, 61(9): 570-577.
11 Hanash S, Brichory F, Beer D, et al. A proteomic approach to the identification of lung cancer markers[J]. Dis Markers, 2001, 17(4): 295-300.
12 Mayrl M, Mayrl U, Chung Y L, et al. Vascular proteomics: Linking proteomic and metabolomic changes[J]. Proteomics, 2004, 4(12): 3751-3761.
13 Butterfield D A. Proteomics: a new approach to investigate oxidative stress in Alzheimer’s disease brain[J]. Brain Res, 2004, 1000(1-2): 1-7.
14 Canard B, Joseph JS, Kuhn P . International research networks in viral structural proteomics: Again, lessons from SARS[J]. Antiviral Research, 2008, 78(1): 47–50.
15 Yoshida T, Tuder RM, et al. Pathobiology of cigarette smoke-induced chronic obstructive pulmonary disease[J]. Physiol Rev, 2007, 87(3): 1047-1082.
16 Schroder M, Kaufman RJ. ER stress and the unfolded protein response[J]. Mutat Res, 2005, 569(1-2): 29–63.
17 G?rlach A, Klappa P, Kietzmann T. The endoplasmic reticulum: folding, calcium homeostasis, signaling, and redox control[J]. Antioxid Redox Signal, 2006, 8(9-10): 1391–1418.
18 Gargalovic PS, Gharavi NM, Clark MJ, et al. The unfolded protein response is an important regulator of inflammatory genes in endothelial cells[J]. Arterioscler Thromb Vasc Biol, 2006, 26(11): 2490–2496.
19 Kelsen SG, Duan X, Ji R, et al. Cigarette Smoke Induces an Unfolded Protein Response in the Human Lung: A Proteomic Approach[J]. Am J Respir Cell Mol Biol, 2008, 38(5): 541-550.
20 Lee EJ, In KH, Kim JH, et al. Proteomic Analysis in Lung Tissue of Smokers and COPD Patients[J]. Chest, 2009, 135(2): 344-352.
21 Bowler RP, Canham ME, Ellison MC. Surface enhanced laser desorption/ionization (SELDI) time-of-flight mass spectrometry to identify patients with chronic obstructive pulmonary disease[J].COPD, 2006, 3(1): 41-50.
22 Gao WM, Kuick R, Orchekowski RR, et al. Distinctive serum protein profiles involving abundant proteins in lung cancer patients based upon antibody microarray analysis[J]. BMC Cancer, 2005, 5:110.
23 Stolk J, Veldhuisen B, Annovazzi L, et al. Short-term variability of biomarkers of proteinase activity in patients with emphysema associated with type Z alpha-1-antitrypsin deficiency[J]. Respir Res, 2005; 6: 47.
24 Ma S, Lin YY, Turino GM. Measurements of Desmosine and Isodesmosine by Mass Spectrometry in COPD[J].Chest, 2007, 131(5): 1363-1371.
25 Pinto-Plata V, Toso J, Lee K, et al. Profiling serum biomarkers in patients with COPD: associations with clinical parameters[J]. Thorax, 2007, 62(7): 595-601.
26 Bozinovski S, Hutchinson A, Thompson M, et al. Serum Amyloid A Is a Biomarker of Acute Exacerbations of Chronic Obstructive Pulmonary Disease[J]. Am J Respir Crit Care Med, 2008,177(3): 269–278.
27 Papi A, Bellettato CM, Braccioni F, et al. Infections and airway inflammation in chronic obstructive pulmonary disease severe exacerbations[J]. Am J Respir Crit Care Med, 2006, 173(10): 1114–1121.
28 Rohde G, Wiethege A, Borg I, et al. Respiratory viruses in exacerbations of chronic obstructive pulmonary disease requiring hospitalisation: a case-control study[J]. Thorax, 2003, 58(1): 37–42.
29 Dahl M,Vestbo J, Lange P, et al. C-reactive protein as a predictor of prognosis in chronic obstructive pulmonary disease[J]. Am J Respir Crit Care Med, 2006,175(3): 250–255.
30 Pinto-Plata VM, Müllerova H, Toso JF, et al. C-reactive protein in patients with COPD, control smokers and non-smokers[J]. Thorax , 2006, 61(1): 23–28.
31 Bai Y, Galetskiy D, Damoc E, et al. Lung alveolar proteomics of bronchoalveolar lavage from a pulmonary alveolar proteinosis patient using high-resolution FTICR mass spectrometry[J]. Anal Bioanal Chem, 2007, 389(4): 1075–1085.
32 Guo Y, Ma SF, Grigoryev D, et al.1-DE MS and 2-D LC-MS analysis of the mouse bronchoalveolar lavage proteome[J]. Proteomics, 2005, 5(17): 4608-4624.
33 Signor L, Tigani B, Beckmann N, et al. Two-dimensional electrophoresis protein profiling and identification in rat bronchoalveolar lavage fluid following allergen and endotoxin challenge[J]. Proteomics, 2004, 4(7): 2101-2110.
34 Lewis JA, Rao KM, Castranova V, et al. Proteomic Analysis of Bronchoalveolar Lavage Fluid: Effect of Acute Exposure to Diesel Exhaust Particles in Rats[J]. Environ Health Perspect, 2007,115(5): 756–763.
35 Merkel D, Rist W, Seither P, et al. Proteomic study of human bronchoalveolar lavage fluids from smokers with chronic obstructive pulmonary disease by combining surface-enhanced laser desorption/ionization-mass spectrometry profiling with mass spectrometric protein identification[J]. Proteomics, 2005, 5(11): 2972–2980.
36 Plymoth A, Yang Z, L?fdahl CG, et al. Rapid Proteome Analysis of Bronchoalveolar Lavage Samples of Lifelong Smokers and Never-Smokers by Micro-Scale Liquid Chromatography and Mass Spectrometry[J]. Clin Chem, 2006, 52(4): 671–679.
37 Rahman SM. J, Shyr Y,.Yildiz PB, et al. Proteomic patterns of preinvasive bronchial lesions[J]. Am J Respir Crit Care Med, 2005,172(12): 1556–1562.
38 Yang SR, Chida AS, Bauter MR, Cigarette smoke induces proinflammatory cytokine release by activation of NF-kappaB and posttranslational modifications of histone deacetylase in macrophages[J]. Am J Physiol Lung Cell Mol Physiol, 2006, 291(1): L46–L57.
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1 Demedts IK, Demoor T, Bracke KR, et al. Role of apoptosis in the pathogenesis of COPD and pulmonary emphysema[J]. Respir Res, 2006, 7: 53.
2 Ugenskiene R, Sanak M, Sakalauskas R, et al. Genetic polymorphisms in chronic obstructive pulmonary disease[J]. Medicina (Kaunas), 2005, 41(1):17-22.
3陈主初,肖志强.疾病蛋白质组学[M].北京:化学工业出版社,2005:1-2.
4 Alaiya AA, Franzén B, Auer G, et al. Cancer proteomics : from identification of novel markers to creation of artificial learning models for tumor classification[J]. Electrophoresis, 2000, 21(6):1210-1217.
5 Jones M B, Krutzsch H, Shu H, et al. Proteomic analysis and identification of new biomarkers and therapeutic targets for invasive ovarian cancer[J].Proteomics, 2002, 2(1):76-84.
6 Cui Li, Zhiqiang Xiao, Zhuchu Chen. et al. Proteome analysis of human lung squamous carcinoma[J]. Proteomics, 2006, 6(2): 547–558.
7 Patz EF Jr, Campa MJ, Gottlin EB, et al. Panel of serum biomarkers for the diagnosis of lung cancer[J]. J Clin Oncol, 2007, 25(35): 5578-5583.
8李香兰,尤庆山,杨艳梅.表面增强激光解吸电离飞行时间质谱技术筛查肺癌血清特异性蛋白质及临床床意义[J].现代生物医学进展,2007,7: 234-236.
9 Shuan-ying Yang, Xue-yuan Xiao, Wang-gang Zhang, et al. Application of serum SELDI proteomic patterns in diagnosis of lung cancer[J]. BMC Cancer ,2005, 5:83.
10 Au JS, Cho WC, Yip TT, et al. Deep proteome profiling of sera from never-smoked lung cancer patients[J]. Biomed Pharmacother, 2007, 61(9): 570-577.
11 Hanash S, Brichory F, Beer D, et al. A proteomic approach to the identification of lung cancer markers[J]. Dis Markers, 2001, 17(4): 295-300.
12 Mayrl M, Mayrl U, Chung Y L, et al. Vascular proteomics: Linking proteomic and metabolomic changes[J]. Proteomics, 2004, 4(12): 3751-3761.
13 Butterfield D A. Proteomics: a new approach to investigate oxidative stress in Alzheimer’s disease brain[J]. Brain Res, 2004, 1000(1-2): 1-7.
14 Canard B, Joseph JS, Kuhn P . International research networks in viral structural proteomics: Again, lessons from SARS[J]. Antiviral Research, 2008, 78(1): 47–50.
15 Yoshida T, Tuder RM, et al. Pathobiology of cigarette smoke-induced chronic obstructive pulmonary disease[J]. Physiol Rev, 2007, 87(3): 1047-1082.
16 Schroder M, Kaufman RJ. ER stress and the unfolded protein response[J]. Mutat Res, 2005, 569(1-2): 29–63.
17 G?rlach A, Klappa P, Kietzmann T. The endoplasmic reticulum: folding, calcium homeostasis, signaling, and redox control[J]. Antioxid Redox Signal, 2006, 8(9-10): 1391–1418.
18 Gargalovic PS, Gharavi NM, Clark MJ, et al. The unfolded protein response is an important regulator of inflammatory genes in endothelial cells[J]. Arterioscler Thromb Vasc Biol, 2006, 26(11): 2490–2496.
19 Kelsen SG, Duan X, Ji R, et al. Cigarette Smoke Induces an Unfolded Protein Response in the Human Lung: A Proteomic Approach[J]. Am J Respir Cell Mol Biol, 2008, 38(5): 541-550.
20 Lee EJ, In KH, Kim JH, et al. Proteomic Analysis in Lung Tissue of Smokers and COPD Patients[J]. Chest, 2009, 135(2): 344-352.
21 Bowler RP, Canham ME, Ellison MC. Surface enhanced laser desorption/ionization (SELDI) time-of-flight mass spectrometry to identify patients with chronic obstructive pulmonary disease[J].COPD, 2006, 3(1): 41-50.
22 Gao WM, Kuick R, Orchekowski RR, et al. Distinctive serum protein profiles involving abundant proteins in lung cancer patients based upon antibody microarray analysis[J]. BMC Cancer, 2005, 5:110.
23 Stolk J, Veldhuisen B, Annovazzi L, et al. Short-term variability of biomarkers of proteinase activity in patients with emphysema associated with type Z alpha-1-antitrypsin deficiency[J]. Respir Res, 2005; 6: 47.
24 Ma S, Lin YY, Turino GM. Measurements of Desmosine and Isodesmosine by Mass Spectrometry in COPD[J].Chest, 2007, 131(5): 1363-1371.
25 Pinto-Plata V, Toso J, Lee K, et al. Profiling serum biomarkers in patients with COPD: associations with clinical parameters[J]. Thorax, 2007, 62(7): 595-601.
26 Bozinovski S, Hutchinson A, Thompson M, et al. Serum Amyloid A Is a Biomarker of Acute Exacerbations of Chronic Obstructive Pulmonary Disease[J]. Am J Respir Crit Care Med, 2008,177(3): 269–278.
27 Papi A, Bellettato CM, Braccioni F, et al. Infections and airway inflammation in chronic obstructive pulmonary disease severe exacerbations[J]. Am J Respir Crit Care Med, 2006, 173(10): 1114–1121.
28 Rohde G, Wiethege A, Borg I, et al. Respiratory viruses in exacerbations of chronic obstructive pulmonary disease requiring hospitalisation: a case-control study[J]. Thorax, 2003, 58(1): 37–42.
29 Dahl M,Vestbo J, Lange P, et al. C-reactive protein as a predictor of prognosis in chronic obstructive pulmonary disease[J]. Am J Respir Crit Care Med, 2006,175(3): 250–255.
30 Pinto-Plata VM, Müllerova H, Toso JF, et al. C-reactive protein in patients with COPD, control smokers and non-smokers[J]. Thorax , 2006, 61(1): 23–28.
31 Bai Y, Galetskiy D, Damoc E, et al. Lung alveolar proteomics of bronchoalveolar lavage from a pulmonary alveolar proteinosis patient using high-resolution FTICR mass spectrometry[J]. Anal Bioanal Chem, 2007, 389(4): 1075–1085.
32 Guo Y, Ma SF, Grigoryev D, et al.1-DE MS and 2-D LC-MS analysis of the mouse bronchoalveolar lavage proteome[J]. Proteomics, 2005, 5(17): 4608-4624.
33 Signor L, Tigani B, Beckmann N, et al. Two-dimensional electrophoresis protein profiling and identification in rat bronchoalveolar lavage fluid following allergen and endotoxin challenge[J]. Proteomics, 2004, 4(7): 2101-2110.
34 Lewis JA, Rao KM, Castranova V, et al. Proteomic Analysis of Bronchoalveolar Lavage Fluid: Effect of Acute Exposure to Diesel Exhaust Particles in Rats[J]. Environ Health Perspect, 2007,115(5): 756–763.
35 Merkel D, Rist W, Seither P, et al. Proteomic study of human bronchoalveolar lavage fluids from smokers with chronic obstructive pulmonary disease by combining surface-enhanced laser desorption/ionization-mass spectrometry profiling with mass spectrometric protein identification[J]. Proteomics, 2005, 5(11): 2972–2980.
36 Plymoth A, Yang Z, L?fdahl CG, et al. Rapid Proteome Analysis of Bronchoalveolar Lavage Samples of Lifelong Smokers and Never-Smokers by Micro-Scale Liquid Chromatography and Mass Spectrometry[J]. Clin Chem, 2006, 52(4): 671–679.
37 Rahman SM. J, Shyr Y,.Yildiz PB, et al. Proteomic patterns of preinvasive bronchial lesions[J]. Am J Respir Crit Care Med, 2005,172(12): 1556–1562.
38 Yang SR, Chida AS, Bauter MR, Cigarette smoke induces proinflammatory cytokine release by activation of NF-kappaB and posttranslational modifications of histone deacetylase in macrophages[J]. Am J Physiol Lung Cell Mol Physiol, 2006, 291(1): L46–L57.
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