Views
3 years ago

Gene expression profiling of human alveolar macrophages of ...

Gene expression profiling of human alveolar macrophages of ...

nonsmokers. Most

nonsmokers. Most of these genes belong to the functionalcategories of immune/inflammatory response, cell adhesionand extracellular matrix, proteolysis and antiproteolysis,lysosomal function, antioxidant-related function, signaltransduction, and regulation of transcription. Of these 75genes, 69 have not been previously recognized to be up- ordown-regulated in AM in association with smoking orCOPD, including genes coding for proteins belonging to allof the above categories, and others belonging to variousfunctional categories or of unknown function. These observationssuggest that gene expression responses of AMassociated with the stress of cigarette smoking are morecomplex than previously thought, and offer a variety of newinsights into the complex pathogenesis of smoking-inducedlung diseases.Keywords Chronic obstructive pulmonary disease .Molecular pathogenesis . Immune responseand inflammationIntroductionCigarette smoking is the leading risk factor for the developmentof chronic obstructive pulmonary disease(COPD), including chronic bronchitis and emphysema [1,2]. For most individuals with COPD, the disease is causedby the chronic burden of oxidants, particles, and xenobioticsimposed by chronic cigarette smoking on the componentsof the lung [3, 4]. COPD is a slow, progressivedisease that does not manifest until at least >20 pack-yearsof smoking [1, 2, 5–7]. Although the molecular mechanismsinvolved in the pathogenesis of COPD are verycomplex, there is considerable data suggesting that alveolarmacrophages (AM) play a significant role in the pathogenesisof COPD associated with cigarette smoking [8, 9].In this regard, individuals who smoke but are otherwisephenotypically normal have approximately three timesmore AM on their airways and alveolar surface [8–10].Compatible with this observation, the earliest pathologicchange in response to moderate smoking is a respiratorybronchiolitis associated with clusters of intraluminal AM[11, 12]. Exposure of the AM of smokers to tobacco smokeresults in AM activation [8–10]. Consistent with these data,the AM of healthy smokers express elevated levels of avariety of mediators, including neutrophil chemoattractantsand other immune response and inflammatory mediators,proteases, and cell adhesion molecules, among others [8,13, 14]. The current concepts of the pathogenesis of COPDhold that the burden of these AM-derived mediators plays amajor role in the lung damage that characterizes thisdisorder [2, 8, 9].The focus of the present study is to further identify theAM-derived processes with potential relevance to thepathogenesis of COPD, based on the hypothesis that anunbiased assessment of early gene expression changes,taking place before the establishment of COPD, will help toidentify processes not previously associated with tobaccosmoking or COPD. The strategy is to employ microarrayanalysis to survey the differences in gene expression profilesof the AM of phenotypically normal, 20 pack-yearsmokers compared to normal nonsmokers. The assessmentof ten individuals (five nonsmokers, five current smokers)revealed up-regulation or down-regulation among smokersof a specific subset of 75 genes (40 up-regulated and 35down-regulated), in the functional categories of immune/inflammatory response, cell adhesion and extracellularmatrix, proteolysis and antiproteolysis, lysosomal function,antioxidant-related function, signal transduction and regulationof transcription, and others. Of these 75 genes, 69have not been previously linked with AM in associationwith smoking or COPD.Materials and methodsStudy subjectsThis study was approved by the Weill Cornell MedicalCollege Institutional Review Board. Written informed consentwas obtained from each individual prior to enrollmentin the study. Individuals underwent an initial screeningevaluation including history (detailed smoking habits),complete physical exam, blood studies, urine analysis,chest roentgenogram, lung function tests, and electrocardiogram(EKG). Special screening evaluation relevant tosmoking habits included the urinary levels of nicotine andits derivative cotinine, and serum levels of carboxyhemoglobin.Upon completion of the baseline evaluation, thoseindividuals who met the inclusion criteria (five nonsmokersand five smokers) underwent fiber-optic bronchoscopy andbronchoalveolar lavage (BAL) to obtain AM.Collection of alveolar macrophagesFiber-optic bronchoscopy was performed to obtain cellspresent in the BAL fluid using methods developed in ourlaboratory to ensure high quality RNA for gene expressionanalysis [15]. The total volume used per site was typically100 ml. A maximum of three sites were evaluated, with atotal volume not exceeding 300 ml. Recovery of the infusedvolume was typically 45–65%. The right middlelobe, right lower lobe, and lingula were the usual sites forlavage. BAL fluid was filtered with gauze and centrifugedat 1,200 rpm for 5 min, 4°C. Cells were washed twice inRPMI 1640 containing 10% fetal bovine serum, 50 U/mlpenicillin, 50 U/ml streptomycin and 2 mM glutamine(Invitrogen, Carlsbad, CA), suspended in 10 ml medium,and an aliquot of 0.5 ml was used for a differential cellcount. Cell viability was estimated by Trypan blue exclusionand expressed as a percentage of the total cellsrecovered. Total cell number was determined by countingon a hemocytometer. Differential cell count was assessedon sedimented cells prepared by cytocentrifugation (Cytospin3; Shandon Instruments, Pittsburgh, PA) stainedwith DiffQuik (Baxter Healthcare, Miami, FL). The remainderwas processed for RNA extraction, by seeding the

cells in six-well plastic culture dishes (2×10 6 per 2 ml/well)and purifying the AM by 2 h adherence at 37°C in a 5%CO 2 humidified incubator, removing the nonadherent cellsby washing with RPMI 1640.RNA extraction and preparation for AffymetrixmicroarraysTotal RNA was extracted using the TRIzol (Life Technologies,Gaithersburg, MD) method followed by RNeasyclean-up (Qiagen, Valencia, CA) to remove residual DNA,a procedure giving a yield of 2 to 4 μg from 10 6 cells.Complementary DNA (cDNA) and complementary RNA(cRNA) synthesis was prepared, and hybridized to theAffymetrix GeneChip HuGeneFL microarray, which enablesthe relative monitoring of messenger RNA (mRNA)transcripts of approximately 5,600 full-length human genes(∼6,800 probes), initially released by Affymetrix in Novemberof 1998. All procedures were carried out asspecified by Affymetrix (Santa Clara, CA).Microarray data analysisThe data on each individual microarray chip was scaled toan arbitrary target intensity, as recommended by Affymetrix,using the Microarray Suite version 5.0 software. Normalizationwas carried out using the GeneSpring software(Agilent Biotechnologies, Palo Alto, CA) as follows: (1)per microarray sample, dividing the raw data by the 50thpercentile of all measurements; and (2) per gene, bydividing the raw data by the median of the expression levelfor the gene in all samples. To eliminate those genes notexpressed in the AM, only the genes with detectable expressionin at least one out of the ten samples (AffymetrixDetection Call of Present in at least one of the ten samples)were chosen for further analysis. The statistical analysiswas carried out for these 4,199 genes. Fold-changes werecalculated as the ratio of the average expression level in thesmokers to the average expression level in the nonsmokers.Clustering and tree building programs were used tocompare the overall gene expression patterns amongsamples from smokers and nonsmokers for both globalcomparisons of all 4,199 genes flagged as Present in at leastone sample, as well as evaluations of the genes that werefound to be differentially expressed in the smokers comparedto the nonsmokers (see Statistics). Normalized, logtransformedgene expression levels were evaluated usingthe Cluster program [16] and subjected to hierarchicalcomplete linkage clustering by both individual and gene.The resulting cluster was visualized with the TreeViewprogram [16].TaqMan mRNA analysisTo confirm the results of the microarray analysis, TaqManreal-time reverse transcriptase (RT) polymerase chain reaction(PCR) analysis was used as an independent methodof measuring gene expression levels. Samples from all fivenonsmokers and four of the five smokers were assessedfor three genes representative of novel observations[osteopontin, a disintegrin and metalloprotease domain 10(ADAM10), and chemokine (C-X-C motif) ligand 6]. Firststrand cDNA was synthesized from 2 μg of RNA in a100 μl reaction volume, using the TaqMan ReverseTranscriptase Reaction Kit (Applied Biosystems, FosterCity, CA), with random hexamers as primers, and dilutedwith Universal Master Mix (Applied Biosystems) to 1:100or 1:10. The probe and primers specific for mRNA weredesigned for each gene using the PrimerExpress software(Applied Biosystems). Each dilution was assayed intriplicate wells. Relative expression levels were calculatedusing the ΔΔ Ct method (Applied Biosystems), with ribosomalRNA (rRNA) as the internal control (HumanRibosomal RNA Kit, Applied Biosystems), and a cocktailconsisting of equal parts of mRNA samples from the AMof the nonsmokers in this study, as the calibrator. TherRNA probe was labeled with VIC, and the probe for eachof the three specific genes was labeled with FAM. The PCRreactions were run in an Applied Biosystems SequenceDetection System 7700. The relative quantity was calculatedusing the algorithm provided by Applied Biosystems.StatisticsComparison of the age of the subjects, cell yield andviability, and % cells types in the smokers and nonsmokerswas performed by a two-tailed Student’s t test. Thesignificance of gene expression differences between thetwo groups was determined by calculating the p value forexpression levels between the nonsmoker group and thesmoker group using the Student’s t test, assuming a twotaileddistribution and equal variances, with the log of thesignal to background ratio as the starting value, using theGeneSpring software. To compare the results obtainedusing microarrays to those obtained using TaqMan realtimeRT-PCR, a two-way analysis of variance (ANOVA)was performed, using method (microarray vs TaqMan) andsmoking status (smokers vs nonsmokers) as independentfactors. For the ANOVA, expression levels were normalizedseparately for the microarray and TaqMan analysis bydividing individual values by the average expression levelof all nonsmokers and smokers for that method, to allowdirect comparisons of values between the two methods.ResultsStudy population and alveolar macrophage samplesThe study population included ten individuals (all men;five healthy nonsmokers and five phenotypically normalcurrent smokers, Supplemental Table 1). The smokers hadan average smoking history of 19±3 pack-years. The twogroups were similar in regard to age (p>0.7, smokers’

Gene-expression Profiles as Gene-expression Profiles as
Gene Expression Profiles of Multiple Independent Cadmium- and ...
Gene expression profiling in DNA repair- deficient Xpa ... - Cefic LRI
HIV-1 Infection Does Not Impair Human Alveolar Macrophage ...
Comprehensive gene expression profiles reveal pathways related to ...
Human Alveolar Macrophage Phagocytic Function is ... - Precaution
bacterial products in human alveolar macrophages ... - Progetto LIBRA
in Activated Alveolar Macrophages - Medicina Biomolecular
Gene expression profiling of human oocytes following in ... - Sismer
Gene Expression Profiling of Human Lung to Elucidate the Genetic ...
3'tag digital gene expression profiling of human brain and universal ...
Characterization and Gene Expression Profiling of Human ...
Gene expression profiling for adult human olfactory neuroepithelial ...
Gene expression profiling in the human hypothalamus-pituitary ...
Gene expression profiling in human insulinoma tissue - Endocrine ...
Methodological considerations for gene expression profiling of ...
A quality-controlled microarray method for gene expression profiling
Gene expression profiling and qRT-PCR expression of RRP1B ...
Mycobacterium tuberculosis gene expression profiling ... - UCLA-DOE
Gene expression profiles in liver of zebrafish treated with microcystin ...
TNF- Release from Alveolar Macrophages and Serum Level of sIL ...
Gene expression profiling in the stem of young maritime pine trees ...
Gene Expression Profiling of Xeroderma ... - BioMed Central
Focused microarray analysis of glyco-gene expression in human ...
Gene Expression Profiles of Uterine Normal Myometrium and ...
Clinical Application of Gene Expression Profiling in Breast Cancer
Microarray analysis of gene expression profiles of cardiac myocytes ...
Gene Expression Profiling in Postmortem Rett Syndrome Brain ...
Expression profiling of hypothetical genes in Desulfovibrio vulgaris ...