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Physiol. Genomics 25: 179-193, 2006. First published January 17, 2006; doi:10.1152/physiolgenomics.00206.2005
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Received 12 August 2005; accepted in final form 9 January 2006.
Physiological Genomics 25:179-193 (2006)
1094-8341/06 $8.00 © 2006 American Physiological Society

Distinct pattern of lung gene expression in the Cftr-KO mice developing spontaneous lung disease compared with their littermate controls

Claudine Guilbault1, Jaroslav P. Novak2, Patricia Martin1, Marie-Linda Boghdady1, Zienab Saeed1, Marie-Christine Guiot3, Thomas J. Hudson2 and Danuta Radzioch1

1 McGill University Health Center Research Institute, Montreal
2 McGill University and Genome Quebec Innovation Centre, Montreal
3 Montreal Neurological Institute and Hospital, Montreal, Quebec, Canada


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 EXPERIMENTAL PROCEDURES
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
Cystic fibrosis (CF) is caused by a defect in the CF transmembrane conductance regulator (CFTR) protein that functions as a chloride channel. Dysfunction of the CFTR protein results in salty sweat, pancreatic insufficiency, intestinal obstruction, male infertility, and severe pulmonary disease. Most of the morbidity and mortality of CF patients results from pulmonary complications. Differences in susceptibility to bacterial infection and variable degree of CF lung disease among CF patients remain unexplained. Many phenotypic expressions of the disease do not directly correlate with the type of mutation in the Cftr gene. Using a unique CF mouse model that mimics aspects of human CF lung disease, we analyzed the differential gene expression pattern between the normal lungs of wild-type mice (WT) and the affected lungs of CFTR knockout mice (KO). Using microarray analysis followed by quantitation of candidate gene mRNA and protein expression, we identified many interesting genes involved in the development of CF lung disease in mice. These findings point to distinct mechanisms of gene expression regulation between mice with CF and control mice.

microarray; cystic fibrosis; Cftr knockout; mouse model


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
EXPERIMENTAL PROCEDURES
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
THE CYSTIC FIBROSIS (CF) DISEASE is caused by a defect in the CF transmembrane conductance regulator (CFTR) protein that functions as a chloride channel regulated by cyclic AMP. Dysfunction of the CFTR protein results in salty sweat, pancreatic insufficiency, intestinal obstruction, male infertility, and severe pulmonary disease. Most of the morbidity and mortality in CF patients result from pulmonary complications. Chronic infection of the lungs with mucoid strains of Pseudomonas aeruginosa (PA), which tends to persist in most patients, results in an exaggerated neutrophilic inflammatory response and in a dysregulated production of cytokines such as high levels of proinflammatory cytokines [interleukin (IL)-1, IL-6, IL-8, and tumor necrosis factor (TNF)] and low levels of anti-inflammatory IL-10 in bronchoalveolar lavage (BAL) fluids (24, 30, 36, 58).

The differences observed in the lung pathology and cytokine profile of young CF patients before any bacterial infection remain unexplained. Moreover, many phenotypic features of the disease exit that do not directly correlate with the type of mutation of the CFTR gene (67). This would imply the involvement of other factors contributing to the Cftr gene genotypes, which may influence the disease phenotypes. Interestingly, the existence of modifier genes influencing the severity of the CF disease was first documented by studies performed by Höpken et al. (26). These and other studies have clearly shown that modifier genes and potential susceptibility loci are important in modulating CF disease severity associated with the lungs, the intestine, and the weight phenotypes in CF (21–23, 26).

Since the discovery of the Cftr gene, no natural animal model has been found; however, a number of animal models have been developed (for a review, see Nelson et al., Ref. 38). Animal models represent a surrogate for understanding the complexities of the human system, provided that the results from experimental animal studies are extrapolated wisely. Most CF models developed are murine models, in view of the fact that the mouse genome is similar to that of human; also, because its entire genome sequence recently has been established, mouse models are now extensively used for the genome-wide examination of gene expression. A number of investigators have generated Cftr gene knockout (KO) mice by targeted gene disruption (6, 8, 9, 16, 41, 55, 60, 66). Although the generated mice have most of the symptoms of CF, only a few of them display the CF lung phenotype (38).

C57BL/6H/M-Cftr.ko mice, described by Kent et al. (33), represent a unique model of spontaneously occurring lung disease which mimics aspects of human CF lung disease. Our laboratory participated in developing and characterizing various backcrosses of Cftr-KO mice, including the C57BL/6H/M-Cftr.ko mice (18, 33). Histological evaluation of the lungs was performed on this CF mouse model to identify the pathological state of the animals from 3 to 20 wk of age. We observed that the uninfected KO mice showed increased hyperplasia of epithelial cells and basement membrane thickening as well as enhanced inflammatory cell infiltration into the lung tissue compared with the wild-type (WT) uninfected controls. We used this animal model for studies on gene expression regulation in uninfected and PA lung-infected CF mice and their littermate controls (18, 19).

To our knowledge, all previous studies on genetic expression differences between normal and Cftr-deficient animals used CF mutants that do not spontaneously acquire lung disease (31, 39, 45, 61, 63, 64). We therefore used the mouse model of CF that develops spontaneous lung disease to analyze the differential gene expression pattern in the normal lungs of WT mice and the affected lungs of KO mice. The aim of this paper is to identify candidate genes associated with the lung disease phenotype observed in these mice. The comprehensive analysis of the data presented in this manuscript clearly shows differences in the lung environments of WT and KO mice involving gene expression regulation and identifies several novel candidate genes that seem to be associated with lung disease.


   EXPERIMENTAL PROCEDURES
TOP
 ABSTRACT
 INTRODUCTION
 EXPERIMENTAL PROCEDURES
RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 
Mice.
Age- (16–20 wk old) and gender-matched C57BL/6 (B6) WT mice (n = 9 females, n = 13 males) and C57BL/6-Cftr–/– (KO) inbred mice (n = 10 females, n = 12 males) were housed (1–4 animals/cage), bred, and maintained in a barrier facility unit under specific pathogen-free conditions. WT mice were fed from birth with the NIH-31 modified mouse irradiated diet (Harlan Teklad, Indianapolis, IN), whereas KO mice were fed the Peptamen liquid diet (Nestle, Brampton, ON, Canada), starting at 14 days of age. The liquid diet, freshly made every morning, was provided in 50-ml centrifuge tubes (Sarstedt, Montreal, QC, Canada). Mice had ad libitum access to sterile acidified water. Three weeks before an experiment, the WT mice were given Peptamen liquid diet. Experimental procedures with the mice were conducted in accordance with the Canadian Council on Animal Care and with the approval of the Animal Care Committee of the McGill University Health Center, Montreal, Quebec, Canada.

Lung histopathology.
Lungs were removed from the mouse, inflated with 10% buffered formalin acetate (Fisher Scientific, Nepean, ON, Canada), and immersed in that buffer for a minimum of 36 h. The lungs were then trimmed and embedded in paraffin. Paraffin sections were sliced 3 µm thick using a Reichert-Jung microtome. Lung sections were cut at regular intervals to get sections at different depths of the lung. Six sections per mouse (3 from the right lobes and 3 from the left lobes of the lungs) were used for each of the following standard staining methods: hematoxylin and eosin, periodic acid-Schiff, and Masson's Trichrome. Each parameter of lung morphology was observed under these specific stains and scored using scales specific to each parameter, as previously described (18).

RNA extraction.
Total RNA was isolated from the lung tissue using TRIzol (Invitrogen, Burlington, ON, Canada). The quality of the RNA was assessed first using electrophoresis in a 2.2 M formaldehyde-2% agarose gel and then using a 2100 Bioanalyzer with the RNA 6000 Nano LabChip kit (Agilent Technologies). The RNA samples were used for microarray only when they were of a highest quality and integrity.

Microarray experiment.
Twenty micrograms of total RNA from each sample were reverse transcribed using oligo-dT primer containing a T7 RNA polymerase-binding site. An in vitro transcription was performed on this cDNA, and the resulting cRNA was biotinylated via incorporation of biotinylated dUTP and dCTP. The cRNA samples were then fragmented in 40 mM Tris-acetate, 100 mM potassium acetate, and 30 mM MgCl2 (pH 8.1) at 95°C. cRNA was hybridized to Affymetrix GeneChips MG-U74Av2 for 16 h at 45°C, washed, stained, and scanned with a Hewlett Packard Gene Array scanner. The hybridization assays and data collection were performed at the McGill University and Genome Quebec Innovation Centre (Montreal, QC, Canada). Microarray data are deposited in the Gene Expression Omnibus (GEO). Affymetrix Analysis Microarray Suite (MAS)5 software was used to estimate the expression level for each probe set from the recorded laser intensity of 11 probe pairs. Before the analysis, all arrays were globally prenormalized to 100% of the array mean. The dispersion patterns were examined for all pairwise combinations of the same type (WT-WT, KO-KO) as well as WT-KO arrays for both female and male samples. In the case of several samples, we observed small deviations from linearity and introduced appropriate corrections. Generally, the plots exhibited low-dispersion characteristics with few strongly over- and/or underexpressed genes.

Microarray data processing.
For microarray analysis, we used lung mRNA from three pairs of male and five pairs of female mice. In the first step of analysis, we characterized the dispersion properties of the samples in pairwise comparisons, using the consecutive sampling program (40). Briefly, the program's main subroutine ranks the genes according to the mean expression, takes as statistical "consecutive" samples 12 consecutive genes, and calculates the characteristic function that approximates standard deviation of the dispersion plot as a linear function of the mean expression. Complementary subroutines determine boundaries of the probability intervals as well as calculate the percentage of the consecutive samples that violate the Kolmogorov-Smirnov normality test and other parameters. To determine which genes have significantly different expression levels between the WT and KO samples, we analyzed the data using both the consecutive sampling and coincidence test (40) and robust multiarray analysis (RMA) (4, 28). The RMA model is based on simultaneous analysis of the adjusted signals. The theoretical limit for the fitting is two arrays. On the basis of our experience, RMA is not very reliable for three or fewer samples. The RMA model provides an independent estimate of the gene expression. We limited the comparison range to ~7,450 genes that have mean expressions >10. First, for the males, using the consecutive sampling method, we identified all genes for which the level of expression in WT and KO was different at 0.8 probability (80%). Such genes were located above and below the 0.8 probability interval. Furthermore, there were nine possible pairwise comparisons between WT and KO samples. We selected as candidates the genes with expression levels above the 0.8 probability interval in at least seven of nine possible cases. Because every statistical method involves an element of uncertainty and each has its particular advantages and disadvantages, we also employed the complementary Wilcoxon-Mann-Whitney and t-tests. Generally, the parametric tests are more sensitive but less robust. Employing the t-test will result in a smaller percentage of false negatives but in a higher percentage of false positives. However, when using the t-test, verification by an alternative technique is crucial. The risk of missing the relevant genes is smaller compared with the nonparametric methods such as coincidence testing and Mann-Whitney. For the females, we did a similar analysis, selecting the genes with expressions above the 0.8 probability interval in at least 15 of 25 possible cases.

Subsequent gene expression analyses.
The gene expression patterns of arrays were compared by hierarchical clustering (10 arrays for females, 6 arrays for males). Cluster analysis was performed for 81 genes from females and 116 genes from males that met the necessary criteria. This clustering analysis was done using CLUSFAVOR (http://condor.bcm.tmc.edu/genepi/clusfavor.html) with the centroid method (42). The distance between the arrays was measured as Euclidean distance. The array data of the experimental sets (WT and KO) common to both sexes were also compared according to gene ontology. Gene ontologies were analyzed with the use of GENMAPP~MAPPFinder (http://www.genmapp.org/) (10) in all selected candidate genes.

Real-time PCR.
The mRNA expression levels were also quantified using the quantitative real-time RT-PCR method. Genes of interest whose expression levels were changed depending on the Cftr genotype in the microarray experiments were selected. Primers were designed for these selected genes. Total RNA was treated with DNase I and reverse transcribed into cDNA, using the DNA-free kit (Ambion, Austin, TX). The cDNA was amplified in the MX4000 system (Stratagene), using the Brilliant SYBR Green QPCR kit (Stratagene, Cedar Creek, TX) according to the manufacturer's instruction. The amount of cDNA was calculated based on the threshold cycle (CT) value and standardized by the amount of the housekeeping gene, using the 2Formula method (34)

Formula
where the "Target" represents the gene of interest tested. Each gene expression was standardized by the expression of a housekeeping gene, GAPDH. The melting curve as well as agarose gel electrophoresis analyses were also performed to confirm that a single product of expected length was amplified. Following is a list of primer sequences, both sense and anti-sense, used for the validation of selected candidate genes: Arg-2 (5'-AAGGTATGGGTTTAAGTGCGCTGC-3', 5'-CGACTTGGGATCCAGAAAGTGAAGGA-3'), MMP-9 (5'-TTCTTCTCTGGACGTCAAAT-3', 5'-CCTAGACCCAACTTATCCAG-3'), Ccl5 (5'-CCAGAGAAGAAGTGGGTTCAAG-3', 5'-GGAAGCGTATACAGGGTCAGAATC-3'), S100a8 (5'-CCATGCCCTCTACAAGAATGAC-3', 5'-CTACTCCTTGTGGCTGTCTTTG-3'), IL-1ß (5'-GTCTTCCTAAAGTATGGGCTGGAC-3', 5'-GAGTCTCCTAGAGATTGAGCTGTC-3'), IL-7R (5'-TCTCTCTCTCTCTCTCTCTCTCTC-3', 5'-GTCTGCATCTTCTAGGTCTCCATC-3'), and Tcra-J (5'-GAACCGATTCTGCTCTGAGATG-3', 5'-CTCCCATTCTCCTTTGTTCCTG-3').

Method of mouse lung infection with PA instilled in agarose beads.
To establish a model of prolonged lung infection, PA strain 508 (18) was impregnated in agar beads. The beads' suspension was freshly prepared the day before each experiment, as previously described, and stored at 4°C overnight. The number of bacteria was determined after homogenizing the bacteria-impregnated bead suspension. Inoculum was prepared by diluting the bead suspension to 2 x 107 colony-forming units (CFU) per milliliter. Mice were anesthetized with a combination of ketamine (7.5 mg/ml) and xylazine (0.5 mg/ml) administered intraperitoneally at a dose of 20 ml/kg body wt. Once the mouse was successfully anesthetized, the animal was installed under binoculars (Microscope M650; Wild Leitz, Willowdale, ON, Canada) in the vertical position and was held on a restraining board by holding the animal by its upper incisor teeth, as previously described (18). The tongue was then gently pulled to the side of the mouth, and a 26-gauge gavage needle was inserted into the mouth and guided through the pharynx to gently touch the vocal cords to see the lumen of the trachea; the needle was then introduced into the trachea to reach the lung for the bilateral injection of 50 µl of inoculum. After inoculation, the animal regained its righting reflex within an hour. A final dose of 1 x 106 PA was used for infection in B6 WT and B6 KO mice. Mice were monitored three times daily; the maximum weight loss allowed was 15%. Mice were killed by CO2 overdose.

Immunostaining (immunohistochemistry).
The formalin-inflated lung sections were deparaffinized and hydrated to distilled water in the following sequence: xylene wash (5 min), xylene wash (x2), 100% ethanol wash (x2), 95% ethanol wash (x2), 70% ethanol wash, distilled water, 2 min each. Slides were then placed in the DAKO Autostainer Universal Staining System machine (DAKO, Cartinteria, CA) for the following treatment steps: 3% H2O2 (in distilled water) for 10 min, Tris buffer for 5 min, proteinase K (DAKO) for 5 min, protein block (DAKO) for 10 min, rabbit polyclonal anti-matrix metalloproteinase (MMP)-9 antibody (Ab) (Chemicon International, Temecula, CA) or secretory leukoproteinase inhibitor (SLPI) Ab (kindly provided by Dr. Aihao Ding, Cornell University, Ithaca, NY) for 60 min, Tris buffer for 5 min (x2), biotinylated goat anti-rabbit immunoglobulin IgG (DAKO) for 30 min, Tris buffer for 5 min (x2), streptavidin-horseradish peroxidase complex for 30 min, Tris buffer for 5 min (x2), 3-amino-9-ethyl-carbazole (AEC) substrate-chromogen solution for 10 min, distilled water for 5 min. Slides were then removed from the DAKO Autostainer and counterstained in Harris hematoxylin for 1 min. Slides were then mounted using AquaMount Mounting Media. They were left to dry for at least 24 h before analysis. The expression of the proteins analyzed in the lung was assessed by scoring the intensity of the immunostain. The stain intensity was scored according to the following arbitrary scale ranging from 0 to 5, where 0 refers to no stain, and 5 indicates that all structures in the lung were stained. A score of 1 represented sporadic staining; a score of 2 was given when the lung displayed some staining, mostly in the alveoli. Moderate staining, expressed mostly in capillaries and larger blood vessels throughout the lung surface, was given a score of 3; and when alveoli and blood vessels were relatively all stained, but not the airways, a score of 4 was given. The averaged score was then calculated to a relative percentage of protein expression to illustrate the comparison between the different groups studied.

IgG measurements.
The levels of IgG were assessed in plasma samples prepared from uninfected animals with the Mouse IgG1 ELISA set (Bethyl Laboratories, Montgomery, TX) and with the Mouse IgG2a ELISA set (BD Biosciences, San Diego, CA), according to the manufacturers' instructions. Briefly, 96-well polyvinyl chloride microtiter Immulon II plates (Dynatech, Chantilly, VA) were coated at 4°C overnight with anti-mouse IgG1 or anti-mouse IgG2a capture Abs. Plates were then washed, incubated with blocking buffer (IgG1: 50 mM Tris, 0.14 M NaCl, 1% bovine serum albumin, pH 8.0; IgG2: PBS, 10% FBS, pH 7.0), and sequentially incubated at room temperature with various dilutions of plasma samples, biotinylated anti-mouse IgG1 Ab or biotinylated anti-mouse IgG2a Ab, avidin-horseradish peroxidase-conjugated Ab, and peroxidase substrate. The intensity of the colorimetric reaction was determined by spectrophotometry at 405 nm. The levels of IgG1 were calculated with reference to a four-parameter logistic (4PL) standard curve established with recombinant mouse IgG1 supplied with the ELISA kit. The levels of IgG2a were calculated with reference to a linear standard curve established with recombinant mouse IgG2a supplied with the ELISA kit.

Statistical analyses.
Analyses were performed for each gender separately because of the known gender differences in the immune response (). Data were analyzed using SigmaStat V.3.01 software (SPSS, Chicago, IL). Statistically significant differences between means and medians of studied groups were evaluated using Student's t-test and the nonparametric Mann-Whitney U-test, respectively. One-way ANOVA and Kruskal-Wallis ANOVA on ranks, combined with pairwise appropriate multiple comparison procedures, were used to evaluate differences between multiple groups. Significance was set at a two-tailed P value of ≤0.05. Specific statistical methods used for the intensity of the microarray probe analyses were described above (see Microarray data processing).


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 EXPERIMENTAL PROCEDURES
 RESULTS
DISCUSSION
 GRANTS
 REFERENCES
 
Mouse model of CF.
Histological evaluation of the lungs of B6 CF mouse model was performed as reported in Guilbault et al. (18, 20). As represented in Fig. 1, the uninfected KO mice showed enhanced inflammatory cell infiltration (Fig. 1A) and fibrosis (Fig. 1B) as well as increased hyperplasia of epithelial cells (Fig. 1C) in the lung tissue compared with the WT uninfected controls.


Figure 1
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  		Fig. 1. Histopathological status of the lungs of uninfected wild-type (WT) and knockout (KO) mice. Representative hematoxylin and eosin-stained (A, C) and Masson's Trichrome-stained (B) lung sections were prepared from uninfected WT and KO mice. Sections from KO mice show cell infiltration in the bronchi and alveoli (A), fibrosis (B), and hyperplasia of the epithelium (C) compared with sections from WT mice that show a normal lung structure.

 
Genes differentially expressed between WT and KO mice: microarray analyses.
First, using the consecutive sampling method, we identified all genes whose level of expression in the female WT and KO groups of mice was different at 0.8 probabilities (80%). Such genes are located above and below the 0.8 probability interval. Furthermore, for the selection of candidate genes, we required that a given gene be above (upregulation of gene expression in KO vs. WT) or below (downregulation) the probability interval 0.8 in 15 of 25 possible comparisons (KO1 vs. WT1, KO2 vs. WT1, KO3 vs. WT1, KO1 vs. WT2, etc.). The red squares and green triangles in Fig. 2A show the upregulated and downregulated averaged values of the candidate genes, respectively. Table 1 summarizes the set of the candidate genes for females specifically. We selected a total of 81 probes; 62 probes showed higher expression in KO compared with WT (55 probe sets passed the Wilcoxon test), and 19 probes had lower expression (11 probe sets passed the Wilcoxon test) (see also Supplemental Appendix S1; available at the Physiological Genomics web site).1


Figure 2
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  		Fig. 2. Dispersion plots of the average values from microarray analysis. Experimental points and boundary of the 0.8 probability interval for females (A) and males (B): KO over WT mRNA samples. Candidate genes are shown as red squares (upregulated) and green triangles (downregulated; coincidence test).

 

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  		Table 1. Genes differentially expressed between KO and WT females

 
Next, we performed a similar analysis using the mRNA samples purified from the lungs of the male KO and WT mice. In the males, there are nine possible pairwise comparisons between WT and KO samples. For the selection of candidate genes, we required that a given gene probe be above or below the probability interval of 0.8 in seven comparisons. The red squares and green triangles in Fig. 2B show the upregulated and downregulated averaged values of the candidate genes, respectively. Table 2 summarizes the set of candidate genes for males specifically. We selected a total of 116 probes; 102 probes showed higher expression in the KO compared with the WT (83 probe sets passed the Wilcoxon test), and 14 probes had lower expression (11 probe sets passed the Wilcoxon test, and 12 passed the t-test) (see also Supplemental Appendix S1). Table 3 shows the candidate genes common to both females and males.


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  		Table 2. Genes differentially expressed between KO and WT males

 

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  		Table 3. Genes differentially expressed between KO and WT mice common to females and males

 
For comparison, Fig. 3 shows the results of two-way hierarchical clustering for the female (Fig. 3A) and male (Fig. 3B) samples individually and for both genders combined (Fig. 3C), respectively. In both cases, the algorithm appropriately arranges the WT and KO samples in the same clusters. In summary, we identified a total of 116 genes in males and 81 genes in females that are differentially expressed between KO and their WT control mice.


Figure 3
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  		Fig. 3. Cluster analysis of microarray experiment in WT and KO mice. Differentially expressed genes were selected and subjected to cluster analysis; 81 genes are represented for the female (A) mice (n = 5/group), 116 genes are represented for the male (B) mice (n = 3/group), and 25 genes are represented for both genders combined (C). Each column represents the gene expression of 1 mouse. Data in the same row represent those of same gene. All the WT and KO mice are grouped together.

 
Other potential candidate genes.
This list of genes was generated based on microarray data from lung mRNA of male mice that were analyzed by Affymetrix MAS5 software (Supplemental Appendix S2). Briefly, the mean expression level for each probe was scaled to 1,000, statistical (unpaired) analysis on mean scale-normalized data was performed, and the genes that qualified had a P value <0.05 and had at least two of three Present or Marginal Calls. The candidate genes that were detected from less restrictive analysis were also very interesting. However, when using this type of analysis, there is an increased possibility of obtaining false positive results when the studied groups are 20–30% different from each other, even if they are demonstrated to be statistically significant. Nonetheless, because the differences arising in the KO compared with their WT control mice, in terms of lung histopathology, happen over time, the gene expression associated with this lung disease condition might be small compared with the WT controls. By using very restrictive methods of gene selection, it is possible to fail to identify important candidate genes. This analysis highlighted 445 statistically significant genes that were differently expressed in KO compared with WT (Supplemental Appendix S2). Of these 445 genes of interest, we evaluated each gene individually with respect to the specific lung disease phenotype. The results of this extensive analysis are presented in Table 4, which lists the genes that are in close distance to loci associated with lung phenotypes, as described in Haston et al. (22), corresponding to interstitial thickening, alveoli count, and fibrosis phenotypes. Supplemental Appendix S2 also lists the genes, or the ones that are in the same family of genes, identified as candidate genes associated with the CF phenotype following whole genome scan. Supplemental Appendix S2 also contains other genes previously shown to be of relevance to the CF lung disease phenotype, and that were found to be differentially expressed between WT and KO in this study.


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  		Table 4. Candidate genes located within previously identified region associated with lung phenotypes* corresponding to "interstitial thickening," "alveoli count," and "fibrosis"

 
Validation of gene expression differences found by microarray data.
To validate microarray data, the expression of seven candidate genes was analyzed using quantitative real-time RT-PCR as described in EXPERIMENTAL PROCEDURES. IL-1ß and calgranulin A (S100a8) genes were selected because of their known involvement in CF lung disease. IL-7R gene was chosen because we previously observed an IL-7R protein increase in the lung of KO mice infected with PA (18). MMP-9, arginase (Arg)-2, Ccl5, and T cell receptor-a-J (Tcra-J) genes were selected because of their previously reported involvement in inflammation and their potential role in the CF lung priming. Figure 4 illustrates the relative differences in the expression of these genes in the lungs of WT and KO mice (9–17 mice/group). Using quantitative real-time RT-PCR, we were able to confirm the differences in the gene expression between WT and KO originally found using Affymetrix chips for all seven selected genes. Moreover, we were able to confirm for the genes which expression differences were as small as 1.5- to 2.0-fold.


Figure 4
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  		Fig. 4. Validation of the difference in mRNA expression between WT and KO mice for selected genes. Lung mRNA abundance from WT (solid bars) and KO (open bars) mice was determined by quantitative real-time RT-PCR. Values were calculated using the 2Formula method (34) as described in EXPERIMENTAL PROCEDURES, where mRNA expression of KO over WT samples was normalized to GAPDH. Data are presented as mean mRNA relative expression levels calculated as 2Formula± SE; the no. of mice per group varied from 8 to 15. *Significant difference.

 
Gene ontology classification.
Next, we processed all generated microarray results for both genders using GENMAPP and MAPPFinder softwares (http://www.genmapp.org/) to sort the genes into categories depending on their known functions (gene ontology; GO) to enable us to define specific biological processes involved in the lung disease phenotype. GO-based analysis separates the selected candidate genes into three major categories: biological process, molecular function, and cellular component. These three categories subdivide further into gene functions. Figure 5 illustrates some of these subclasses in which several genes had their expression affected by the lack of the Cftr gene in uninfected mice. It is noteworthy that a given gene product may exhibit one or more functions. This section focuses on the functional categories of the genes differentially expressed in the KO compared with their WT control lungs.


Figure 5
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  		Fig. 5. Gene ontology (GO)-based analysis: effect of Cftr deletion on gene expression in the lungs of mice. Genes differentially expressed between WT and KO mouse lungs are represented by their functional categories: biological process categorization (A), molecular function categorization (B), and cellular component categorization (C). CFTR, cystic fibrosis transmembrane conductance regulator.

 
The biological process category (Fig. 5A) includes genes whose products relate to biological phenomenon, mediated by one or more gene products. This category can be subdivided into three main classes, including cell communication, physiological process, and cellular process; it also contains the majority of candidate genes we found. The molecular function category (Fig. 5B) includes genes whose products' elemental activities, such as catalysis or binding, describe the actions at the molecular level. The cellular component category (Fig. 5C) includes genes whose products are part of cells; these include extracellular environments, products that may be a component of one or more parts of a cell structure, and products that are parts of macromolecular complexes.

Overall, GO-based analysis gives us a global picture of the functional systems implicated in the differential gene expression between the lungs of uninfected KO and WT mice (Figs. 5 and 6).


Figure 6
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  		Fig. 6. Representation of candidate genes potentially involved in the manifestation of the lung disease phenotype observed in KO mice developing spontaneous lung disease. Genes are classified by functional categories. {uparrow}, Upregulated genes in KO compared with WT mice; {downarrow}, downregulated genes in KO compared with WT mice.

 
Protein expression in the lungs.
To further confirm the results obtained from quantitative real-time RT-PCR, we looked at the MMP-9 protein levels using lung sections from WT and KO mice fixed in formalin (WT, n = 7; KO, n = 8). We observed an increase in MMP-9 protein expression in the uninfected KO compared with the WT uninfected control mice (Fig. 7A) \. (see EXPERIMENTAL PROCEDURES for details on scoring analysis). The uninfected KO mice showed 36.4% higher MMP-9 protein expression compared with the WT uninfected mice, where there was only a small or no expression detected in their lungs (mean ± SE expression scores for WT mice of 1.3 ± 0.5 compared with a mean score of 1.9 ± 0.4 for KO mice; P = 0.05). Next, we evaluated the MMP-9 protein expression levels of PA lung-infected WT and KO mice 3 days postinfection. As expected, we observed an increase in MMP-9 when the mice were infected with PA in the lungs; WT infected mice had a 69.4% increase in MMP-9 protein expression compared with a small or no expression in the WT uninfected animals (WT uninfected, 1.3 ± 0.5; WT-PA, 2.3 ± 0.6; P = 0.013), and, similarly, KO infected mice had a 73.3% higher expression of MMP-9 protein compared with KO uninfected animals (KO uninfected, 1.9 ± 0.4; KO-PA, 3.3 ± 0.5; P = 0.010) (Fig. 7B). Interestingly, we observed a very similar mean difference of ~40% between the levels of MMP-9 expression in KO mice and their WT controls, independent of their infectious status (infected with PA, 39.5%; uninfected, 36.4%). The comparative analysis of the MMP-9 protein in the lungs of WT and KO mice clearly demonstrates that the lungs of uninfected KO mice already show an elevated expression of MMP-9.


Figure 7
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  		Fig. 7. Immunostaining on the lungs of WT and KO mice. Representative matrix metalloproteinase (MMP)-9 immunostaining (40x to 400x) from uninfected and Pseudomonas aeruginosa (PA)-infected mice at 3 days postinfection from lung sections prepared from WT and KO mice. Sections from uninfected KO mice show 36.4% more MMP-9 protein expression than WT mice, which show a small or no expression (Uninfected). An increase in MMP-9 was observed when the mice were infected with PA in the lungs; WT infected mice had a 69.4% increase in MMP-9 protein expression compared with WT uninfected animals. Similarly, KO infected mice had 73.3% higher expression of MMP-9 protein compared with KO uninfected animals.

 
Because many probes of variable chains were shown to be overexpressed in the lungs of KO mice compared with their controls, we assessed the levels of IgG1 and IgG2a in the plasma of uninfected KO and WT mice. We observed a statistically significant 1.7-fold increase in the mean concentration of IgG1 in the uninfected KO mice (7,593 ± 1,021 ng/ml, n = 6) compared with their WT uninfected controls (4,514 ± 587 ng/ml, n = 8) (P = 0.017). Although a trend toward higher levels of IgG2a was observed in the plasma of uninfected KO mice (53 ± 8 ng/ml) compared with their uninfected WT controls (38 ± 3 ng/ml), this difference did not reach statistical significance (P = 0.137).

Because we found a significant difference at the level of Slpi mRNA expression between WT and KO uninfected mice (P = 0.006), we analyzed the level of SLPI protein expression in the lungs of uninfected WT and KO mice by immunohistochemistry staining. Interestingly, we found a striking difference at the level of SLPI protein expression in the lungs of uninfected KO mice compared with their uninfected WT controls (P = 0.015). The WT mice had low to no protein expression detected [median score of 0.5; 0.0 (25%)–0.5 (75%); n = 10], and the KO mice showed low to moderate SLPI protein expression in the lungs [median score of 1.0; 0.8 (25%)–1.3 (75%); n = 12].

Overall, these increases in MMP-9, IgG1, and SLPI protein levels seem to be consistent with the hypothesis that the lungs of KO mice are in a heightened activation state even before experimental infection with PA.


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 EXPERIMENTAL PROCEDURES
 RESULTS
 DISCUSSION
GRANTS
 REFERENCES
 
CF patients display several disease symptoms, including intestinal obstruction, infertility, pancreatic insufficiency, and chronic lung infections. Although it is well documented that this wide spectrum of symptoms results from dysfunctions of the CFTR protein, the exact mechanism of disease development has not yet been elucidated.

Chronic lung infections resulting in a gradual loss of function and high mortality are particularly difficult to handle, since no universal treatment that is able to prevent or reverse lung damage has been developed yet. Because we developed a CF mouse model that displays most of the CF lung phenotype without infection (e.g., infiltration of inflammatory cells, fibrosis, lipid imbalance), we used this model to perform genome-wide transcriptional analysis of gene expression in the lungs of these KO mice compared with their WT littermate controls. The spontaneous lung disease observed in uninfected KO mice is characterized by the increased hyperplasia of epithelial cells, basal membrane thickening, and inflammatory cell infiltration in the lung tissue compared with control littermates. We have previously reported that lung disease starts to develop between 12 and 16 wk (18, 33) of age and gradually progresses. In this study, we have used 20-wk-old KO mice that display very striking changes in their lungs compared with their littermate controls. We have performed a very meticulous comparison of gene expression patterns between the total lung homogenates of KO mice and their controls using multiple animals of both genders. Although the use of the whole lung homogenate may lead to underestimation of the differences, it is an objective measure of the observed differences at the level of whole lung and not only a selected part of the lung (e.g., trachea, epithelial cells). Gene chip expression analysis has been subsequently corroborated using real-time RT-PCR quantification and protein expression analysis for selected genes.

Tables 1, 2, and 3 show lists of the over- and underexpressed candidate genes, obtained for the probability interval 0.8; they contain a total of 116 candidate genes in males and 81 candidate genes in females that are differentially expressed between KO and their WT control mice. Due to the fundamental differences in female and male inflammatory regulations and PA infection susceptibilities, both genders were analyzed together and separately.

When comparing the gene expression patterns between KO mice (both males and females) and their control littermates, it was evident that there were many more upregulated than downregulated genes in the lungs of KO mice than in WT controls. Several of the identified genes belong to the immunoglobulin family, more specifically in heavy chains (Igh-VJ558, Igh-4), joining chain (Igj), and {kappa}-chain (Igk-V8) genes (common for females and males). Several other genes (or chip probes of the same gene) of immunoglobulin chains were also identified to be differentially expressed in the KO males or KO females compared with their WT controls (Igh-VJ558, Igh-4, Igk-V8, Igh-6, IgI-V1, and Igk-V28). Anomalies in the production of immunoglobulins (hypo- and hypergammaglobulinemia) in CF patients and animal models have been reported in the literature (5, 25, 35, 37, 43, 46). Raman et al. (46) found decreased levels of IgG in children with CFTR mutations with chronic rhinosinusitis but free of the CF symptoms. Matthews et al. (35) and Hodson et al. (25) reported lower levels of the IgG in CF patients with less severe disease and elevated levels in cases of more advanced stages. Generally, IgG is overexpressed in the lungs compared with other tissues (17). Moreover, most of the murine model studies have not reported any significant changes in the immunoglobulin family of genes (7, 14, 27, 32, 44, 56, 57, 59, 64, 65). Recently, Norkina et al. (39) reported a significant increase in the expression of the immunoglobulin-{kappa} variable chains V-5, V-8, and V-28 in the intestine of the CF mouse (39). Our data clearly show an increase in the mRNA expression in the lungs of KO mice compared with their WT controls for several immunoglobulin genes, which correlates with higher IgG1 protein expression in the plasma of KO mice compared with WT.

The upregulation of several genes that belong to the immunoglobulin family was also accompanied by the upregulation of expression of several genes, which suggests an overall enhancement of B cell functions, antigen presentation, and antigen binding. Genes such as major histocompatibility complex (MHC) class II (H2-Eb1, H2-DMa, H2-Q10, H2-DMb1), cytokines (IL-1ß, IL-7R), complement components (C1qa, C1qb, C1qg, C3, C4), antigens (CD37, CD79a, CD79b, CD52, CD19, CD48, CD53), and other B cell-related genes such as B cell translocation gene 3 (Btg3), B-lymphoid kinase (Blk), and paired Ig-like receptor B (Pirb) were differentially expressed in KO mice.

Other genes that were upregulated in the KO mice include calgranulins that function as inflammatory cytokines, expressed abundantly in infiltrating monocytes and granulocytes under conditions of chronic inflammation. Elevated amounts of calgranulins (A and B) were found in the serum of patients with CF and clinically normal heterozygous carriers (12, 13). Interestingly, calgranulin A (S100a8) and calgranulin B (S100a9) genes were upregulated in our mouse model that develops lung disease and also in the lungs of gut-corrected CF mice, which lack the lung disease phenotype (64). Other members of the S100 calcium-binding protein family of genes were downregulated in KO mice, notably S100a6 (calcyclin) and S100a13, one of the most recently identified members of the S100 family, as illustrated in Supplemental Appendix S2.

T cell-related genes were found to be upregulated in the lungs of KO mice compared with their WT counterparts. More specifically, members of the recently identified Schlafen (Slfn) gene family, such as Slfn1 (Table 1), Slfn 2 (Table 2), Slfn 3, and Slfn 4 (Supplemental Appendix S2), have been implicated in an as yet unidentified regulatory mechanism involved in T cell development and growth control. The Schlafen gene family (49) has also been observed in the CF mouse small intestine by Norkina et al. (39). We observed the upregulation of the following gene expressions: thymus cell antigen 1-{theta} (Thy1), lymphocyte protein tyrosine kinase (Lck), T cell-specific GTPase (Tgtp), T cell receptors (Tcrb-V13, Tcra-J), lymphocyte cytosolic protein 1 (Lcp), granzyme A (Gzma; T cell- and natural killer cell-specific serine protease), and fibrinogen-like protein 2 (Fgl2), which exerts immunosuppressive effects on T cell proliferation and dendritic cell maturation.

Chemokines regulate the cell trafficking of various types of leukocytes through interactions with a subset of transmembrane G protein-coupled receptors. These are involved in macrophage recruitment during inflammation and also play a role in the development, homeostasis, and function of the immune system. The mRNA expression of three chemokine genes of the C-C motif subfamily of chemokines and one chemokine receptor gene was found to be elevated in KO lungs compared with their WT counterparts: Ccl6, previously known as "macrophage inflammatory protein-related protein (MRP)-1;" Ccl9, also known as "macrophage inflammatory protein (MIP)-1{gamma}" or MRP-2; and Ccl5, known as RANTES, and its receptor Ccr5 (Supplemental Appendix S2), which also binds the chemokines MIP-1{alpha} and MIP-1ß with high affinity.

We also found that several other proteins known to be involved in the general inflammatory response had their gene expression affected by the deleted Cftr gene ablation. Serum amyloid A3 (Saa3), which is expressed particularly in macrophages and known as an acute-phase reactant [also observed recently by Norkina et al. (39)]; Arg2, which is closely involved in the cellular production of NO; integrin (Itgb7); and lipocalin 2 (Lcn2) were all upregulated in the KO lungs.

A few genes found in the present study are related to the structure of the cell and might explain some of the differences we observed in the KO lungs, such as tubulin (Tubb2), actinin (Actn1), and epithelial membrane protein (Emp2) (Table 3). We also found genes involved in the proteolytic degradation of the extracellular matrix, such as MMPs (Mmp-9, Mmp-11, Adam-8; Supplemental Appendix S2) and cathepsin H, which is involved in the conversion of pro-MMPs into active MMPs. Interestingly, an increase in the expression of cathepsin H was shown to be associated with lung disease in lung cancer patients (50).

Furthermore, in our analyses, constitutive expressions of protease inhibitors, especially serine protease inhibitors, were demonstrated to be differentially expressed in the lungs when comparing KO mice with lung disease with their WT healthy littermate controls. The production of these inhibitors in the lung tissue should not be ignored, since they may play a very important regulation function in the lungs. It is possible that their overexpression might activate the mechanisms that contribute to a progressive fibrosis development. Proteinases such as SLPI, synthesized and secreted by pulmonary epithelium and macrophages, are further augmented after lung exposure to endotoxin, expressed by PA and inflammatory cytokines such as TNF and IL-1 (47), IL-10, and IL-6 (29). SLPI protein has been implicated in wound healing processes (2), pulmonary inflammation (3), and gram-negative and gram-positive bacterial infections (29) as an anti-inflammatory mediator. SLPI is considered undoubtedly as a major elastase inhibitor in the respiratory tract, more importantly associated with neutrophil elastase inhibition (1, 48) but also improving anti-oxidant protection by raising glutathione levels in the lungs (62). In CF, it was hypothesized that an increase in SLPI could be beneficial to the control of lung functions, since it can control the abnormally high levels of elastase found in the lung and characteristic of CF disease (48), associated with the exacerbation of the immune response. Our mRNA data from the microarray experiment have shown a significant difference between WT and KO in SLPI mRNA expression in male mice. These data are consistent with a clinical observation in male CF patients (61). We observe a clearly increased expression of this important mediator in the lungs of the KO male mice with spontaneous lung disease compared with their WT littermate controls (Table 2). Overall, these results support the hypothesis that the CF lung milieu is dysregulated, not only in terms of inflammatory responses to bacterial pathogens but even before the mice are infected, at the gene expression levels, either directly by CFTR deficiency itself or secondary to the Cftr gene defect, by modifier genes.

The gene Col6a2, procollagen type VI-{alpha} 2, encodes one of the three {alpha}-chains of type VI collagen, a beaded filament collagen found in most connective tissues. The product of this gene contains several domains that have been shown to bind extracellular matrix proteins, an interaction that explains the importance of this collagen in organizing matrix components. Also, the gene Col1a1, procollagen type I-{alpha} 1, encodes the major component of type I collagen, the fibrillar collagen found in most connective tissues, and the only component of the collagen found in cartilage. Furthermore, we observed a third gene involved in the composition of collagen, Col14a1, procollagen type XIV-{alpha} 1. Interestingly, we found that the expression of these three genes was higher in the KO lungs than in the normal lungs, which might be an important factor in the lung disease phenotype we observe in these mice.

Prnp gene was also found to be underexpressed in KO males (1.5-fold) and females (1.8-fold) compared with WT control mice. The protein encoded by this gene is involved in lipid raft formation. These lipids rafts are specialized membrane domains composed mainly of cholesterol and sphingolipids and are relatively poor in polyunsaturated lipids such as glycerophospholipids (54). The formation of these membrane domains is promoted by the presence of cholesterol in the lipid bilayer. Because the hexagonal rings of cholesterol can pack tightly against the saturated hydrocarbon chains of membrane lipids, it allows these lipids to assemble into cohesive units floating in the mass of loosely packed polyunsaturated plasma membrane components (51). Interestingly, it has been shown recently that the internalization of PA bacteria in nasal and tracheal epithelium involves the formation of lipid rafts (52, 53). These large lipid raft platforms may concentrate as yet unknown intracellular signaling molecules and binding receptors involved in the cellular response to Pseudomonas infection in addition to CFTR.

Interestingly, in an attempt to correlate our findings with current knowledge, we correlated the loci of the genes we found with the loci associated with the CF lung disease phenotype, namely interstitial thickening, fibrosis, and alveoli count, as previously described by Haston et al. (22). The immunoglobulin gene Igh-4 and Igh-VJ558 heavy chains, as well as Ena vasodilator-stimulated phosphoprotein (Evl), lipocalin 2 (Lcn2), and Arg2, were found to be localized in the genetic region associated with the "interstitial thickening" phenotype. Arg2 was also observed to be differentially expressed in the pancreas and duodenum of CF mouse KO (31).

Moreover, seven other genes were associated with the "fibrosis" phenotype, specifically, IL-1ß, complement component 4 (C4), histocompatibility 2 class II (H2-DMb1), C-type lectin superfamily member 8 (Clecsf8), glycoprotein 49 A (Gp49a), killer cell lectin-like receptor subfamily G member 1 (Klrg1), and subfamily D member 1 (Klrd1). Finally, B lymphoid kinase (Blk) was found to be in the region associated with the "alveoli count" phenotype. We were very excited to find a total of 17 genes that were associated with lung disease phenotype.

Human studies of CF have performed gene expression analyses on blood samples or on human epithelial cell lines. Moreover, Zielenski's laboratory (11, 15) presented results identifying secondary genes, other than Cftr, influencing the clinical severity of CF disease. A number of genes found by Zielinski and colleagues were also associated with CF lung disease in humans (Supplemental Appendix S2). Among the genes identified in our study that were differentially expressed between WT and KO mice and that could play an important role in CF lung disease were genes such as IL-1ß, IL-8R, CLCA1, GSTM1, heat shock protein (HSP)40, and HSP70. We also observed other genes differentially expressed between KO and WT, including slc22a and slc, aquaporin, and the clca family of genes, which belong to the same family as some of the identified genes in the human CF study.

This wide-genome screening led us to reveal several candidate genes involved in cellular physiological processes as well as in the immune response, signal transducer and antigen-binding activities, and matrix remodeling. These genes might contribute to the development of lung disease before PA lung infection in our CF mouse model. Some of these genes have already been identified in human CF patients, and other genes of interest found in our CF mouse model will be assessed in CF humans. Overall, our results strongly suggest that the control of the immune system is crucial to prevent the development of the disease.


   GRANTS
TOP
 ABSTRACT
 INTRODUCTION
 EXPERIMENTAL PROCEDURES
 RESULTS
 DISCUSSION
 GRANTS
REFERENCES
 
This work was supported by Canadian Cystic Fibrosis Foundation Grant No. CCFF2167.


   ACKNOWLEDGMENTS
 
We thank Pierre Camateros for technical assistance and Dominique Marion for critical review of the manuscript.


   FOOTNOTES
 
Article published online before print. See web site for date of publication (http://physiolgenomics.physiology.org).

Address for reprint requests and other correspondence: D. Radzioch, McGill Univ. Health Center, Montreal General Hospital Research Institute, 1650 Cedar Ave., Rm. L11-218, Montreal, Quebec H3G 1A4, Canada (e-mail: danuta.radzioch{at}muhc.mcgill.ca).

1 The Supplemental Material for this article (Supplemental Appendixes S1 and S2) is available online at http://physiolgenomics.physiology.org/cgi/content/full/00206.2005/DC1. Back


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 EXPERIMENTAL PROCEDURES
 RESULTS
 DISCUSSION
 GRANTS
 REFERENCES
 

  1. Abbinante-Nissen JM, Simpson LG, and Leikauf GD. Neutrophil elastase increases secretory leukocyte protease inhibitor transcript levels in airway epithelial cells. Am J Physiol Lung Cell Mol Physiol 265: L286–L292, 1993.[Abstract/Free Full Text]
  2. Ashcroft GS, Lei K, Jin W, Longenecker G, Kulkarni AB, Greenwell-Wild T, Hale-Donze H, McGrady G, Song XY, and Wahl SM. Secretory leukocyte protease inhibitor mediates non-redundant functions necessary for normal wound healing. Nat Med 6: 1147–1153, 2000.[CrossRef][Web of Science][Medline]
  3. Bingle L and Tetley TD. Secretory leukoprotease inhibitor: partnering alpha 1-proteinase inhibitor to combat pulmonary inflammation. Thorax 51: 1273–1274, 1996.[Abstract/Free Full Text]
  4. Bolstad BM, Irizarry RA, Astrand M, and Speed TP. A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 19: 185–193, 2003.[Abstract/Free Full Text]
  5. Bubien JK. CFTR may play a role in regulated secretion by lymphocytes: a new hypothesis for the pathophysiology of cystic fibrosis. Pflügers Arch 443, Suppl 1: S36–S39, 2001.[CrossRef]
  6. Colledge WH, Abella BS, Southern KW, Ratcliff R, Jiang C, Cheng SH, MacVinish LJ, Anderson JR, Cuthbert AW, and Evans MJ. Generation and characterization of a delta F508 cystic fibrosis mouse model. Nat Genet 10: 445–452, 1995.[CrossRef][Web of Science][Medline]
  7. Cressman VL, Hicks EM, Funkhouser WK, Backlund DC, and Koller BH. The relationship of chronic mucin secretion to airway disease in normal and CFTR-deficient mice. Am J Respir Cell Mol Biol 19: 853–866, 1998.[Abstract/Free Full Text]
  8. Davidson DJ, Dorin JR, McLachlan G, Ranaldi V, Lamb D, Doherty C, Govan J, and Porteous DJ. Lung disease in the cystic fibrosis mouse exposed to bacterial pathogens. Nat Genet 9: 351–357, 1995.[CrossRef][Web of Science][Medline]
  9. Delaney SJ, Alton EW, Smith SN, Lunn DP, Farley R, Lovelock PK, Thomson SA, Hume DA, Lamb D, Porteous DJ, Dorin JR, and Wainwright BJ. Cystic fibrosis mice carrying the missense mutation G551D replicate human genotype-phenotype correlations. EMBO J 15: 955–963, 1996.[Web of Science][Medline]
  10. Doniger SW, Salomonis N, Dahlquist KD, Vranizan K, Lawlor SC, and Conklin BR. MAPPFinder: using Gene Ontology and GenMAPP to create a global gene-expression profile from microarray data. Genome Biol 4: R7, 2003.[CrossRef][Medline]
  11. Dorfman R, Sandford A, Markiewicz D, Master A, Deng G, Patel M, Corey M, Yuan X, Tan M, Li F, Frangolias DD, Sun L, Pare P, Durie P, Tsui LC, and Zielenski J. Analysis of candidate genes as modifiers of cystic fibrosis (Abstract). Pediatr Pulmonol Suppl 27: 220–221, 2004.
  12. Dorin JR, Emslie E, and van Heyningen V. Related calcium-binding proteins map to the same subregion of chromosome 1q and to an extended region of synteny on mouse chromosome 3. Genomics 8: 420–426, 1990.[CrossRef][Web of Science][Medline]
  13. Dorin JR, Novak M, Hill RE, Brock DJ, Secher DS, and van Heyningen V. A clue to the basic defect in cystic fibrosis from cloning the CF antigen gene. Nature 326: 614–617, 1987.[CrossRef][Medline]
  14. Eidelman O, Srivastava M, Zhang J, Leighton X, Murtie J, Jozwik C, Jacobson K, Weinstein DL, Metcalf EL, and Pollard HB. Control of the proinflammatory state in cystic fibrosis lung epithelial cells by genes from the TNF-alphaR/NFkappaB pathway. Mol Med 7: 523–534, 2001.[Web of Science][Medline]
  15. Evtoushenko I, Markiewicz D, Deng G, Patel M, Dorfman R, Corey M, Tan M, Li F, Sun L, Sandford A, Pare P, Durie P, Tsui LC, and Zielenski J. Analysis of human chromosome 6q27 region as a potential modifier locus for pulmonary disease in cystic fibrosis (Abstract). Pediatr Pulmonol Suppl 27: 221, 2004.
  16. French PJ, van Doorninck JH, Peters RH, Verbeek E, Ameen NA, Marino CR, de Jonge HR, Bijman J, and Scholte BJ. A delta F508 mutation in mouse cystic fibrosis transmembrane conductance regulator results in a temperature-sensitive processing defect in vivo. J Clin Invest 98: 1304–1312, 1996.[Web of Science][Medline]
  17. Genter MB, Van Veldhoven PP, Jegga AG, Sakthivel B, Kong S, Stanley K, Witte DP, Ebert CL, and Aronow BJ. Microarray-based discovery of highly expressed olfactory mucosal genes: potential roles in the various functions of the olfactory system. Physiol Genomics 16: 67–81, 2003.[Abstract/Free Full Text]
  18. Guilbault C, Martin P, Houle D, Boghdady ML, Guiot MC, Marion D, and Radzioch D. Cystic fibrosis lung disease following infection with Pseudomonas aeruginosa in the Cftr knockout mice using novel non-invasive direct pulmonary infection technique. Lab Anim 39: 336–352, 2005.[Abstract/Free Full Text]
  19. Guilbault C, Nelson A, Martin P, Stotland PK, Boghdady ML, Guiot MC, De Sanctis JB, and Radzioch D. Protective effect of DHA treatment in non-infected CFTR knockout mice with CF lung disease. Int Proc Immunol: 79–88, 2004.
  20. Guilbault C, Stotland P, Lachance C, Tam M, Keller A, Thompson-Snipes L, Cowley E, Hamilton TA, Eidelman DH, Stevenson MM, and Radzioch D. Influence of gender and interleukin-10 deficiency on the inflammatory response during lung infection with Pseudomonas aeruginosa in mice. Immunology 107: 297–305, 2002.[CrossRef][Web of Science][Medline]
  21. Haston CK, Corey M, and Tsui LC. Mapping of genetic factors influencing the weight of cystic fibrosis knockout mice. Mamm Genome 13: 614–618, 2002.[CrossRef][Web of Science][Medline]
  22. Haston CK, McKerlie C, Newbigging S, Corey M, Rozmahel R, and Tsui LC. Detection of modifier loci influencing the lung phenotype of cystic fibrosis knockout mice. Mamm Genome 13: 605–613, 2002.[CrossRef][Web of Science][Medline]
  23. Haston CK and Tsui LC. Loci of intestinal distress in cystic fibrosis knockout mice. Physiol Genomics 12: 79–84, 2003.[Abstract/Free Full Text]
  24. Heeckeren A, Walenga R, Konstan MW, Bonfield T, Davis PB, and Ferkol T. Excessive inflammatory response of cystic fibrosis mice to bronchopulmonary infection with Pseudomonas aeruginosa. J Clin Invest 100: 2810–2815, 1997.[Web of Science][Medline]
  25. Hodson ME, Morris L, and Batten JC. Serum immunoglobulins and immunoglobulin G subclasses in cystic fibrosis related to the clinical state of the patient. Eur Respir J 1: 701–705, 1988.[Abstract]
  26. Hopken UE, Lu B, Gerard NP, and Gerard C. The C5a chemoattractant receptor mediates mucosal defence to infection. Nature 383: 86–89, 1996.[CrossRef][Medline]
  27. Hybiske K, Ichikawa JK, Huang V, Lory SJ, and Machen TE. Cystic fibrosis airway epithelial cell polarity and bacterial flagellin determine host response to Pseudomonas aeruginosa. Cell Microbiol 6: 49–63, 2004.[CrossRef][Web of Science][Medline]
  28. Irizarry RA, Bolstad BM, Collin F, Cope LM, Hobbs B, and Speed TP. Summaries of Affymetrix GeneChip probe level data. Nucleic Acids Res 31: e15, 2003.[Abstract/Free Full Text]
  29. Jin F, Nathan CF, Radzioch D, and Ding A. Lipopolysaccharide-related stimuli induce expression of the secretory leukocyte protease inhibitor, a macrophage-derived lipopolysaccharide inhibitor. Infect Immun 66: 2447–2452, 1998.[Abstract/Free Full Text]
  30. Johnson LG, Boyles SE, Wilson J, and Boucher RC. Normalization of raised sodium absorption and raised calcium-mediated chloride secretion by adenovirus-mediated expression of cystic fibrosis transmembrane conductance regulator in primary human cystic fibrosis airway epithelial cells. J Clin Invest 95: 1377–1382, 1995.[Web of Science][Medline]
  31. Kaur S, Norkina O, Ziemer D, Samuelson LC, and De Lisle RC. Acidic duodenal pH alters gene expression in the cystic fibrosis mouse pancreas. Am J Physiol Gastrointest Liver Physiol 287: G480–G490, 2004.[Abstract/Free Full Text]
  32. Kelley TJ and Drumm ML. Inducible nitric oxide synthase expression is reduced in cystic fibrosis murine and human airway epithelial cells. J Clin Invest 102: 1200–1207, 1998.[Web of Science][Medline]
  33. Kent G, Iles R, Bear CE, Huan LJ, Griesenbach U, McKerlie C, Frndova H, Ackerley C, Gosselin D, Radzioch D, O'Brodovich H, Tsui LC, Buchwald M, and Tanswell AK. Lung disease in mice with cystic fibrosis. J Clin Invest 100: 3060–3069, 1997.[Web of Science][Medline]
  34. Livak KJ and Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(–Delta Delta C(T)) Method. Methods 25: 402–408, 2001.[CrossRef][Web of Science][Medline]
  35. Matthews WJ Jr, Williams M, Oliphint B, Geha R and Colten HR. Hypogammaglobulinemia in patients with cystic fibrosis. N Engl J Med 302: 245–249, 1980.[Abstract]
  36. Morissette C, Francoeur C, Darmond-Zwaig C, and Gervais F. Lung phagocyte bactericidal function in strains of mice resistant and susceptible to Pseudomonas aeruginosa. Infect Immun 64: 4984–4992, 1996.[Abstract]
  37. Moss RB. Hypergammaglobulinemia in cystic fibrosis. Role of Pseudomonas endobronchial infection. Chest 91: 522–526, 1987.[Medline]
  38. Nelson A, Guilbault C, and Radzioch D. Animal models used for the study of cystic fibrosis. Recent Res Dev Cell Res 1: 91–130, 2003.
  39. Norkina O, Kaur S, Ziemer D, and De Lisle RC. Inflammation of the cystic fibrosis mouse small intestine. Am J Physiol Gastrointest Liver Physiol 286: G1032–G1041, 2004.[Abstract/Free Full Text]
  40. Novak JP, Sladek R, and Hudson TJ. Characterization of variability in large-scale gene expression data: implications for study design. Genomics 79: 104–113, 2002.[CrossRef][Web of Science][Medline]
  41. O'Neal WK, Hasty P, McCray PB Jr, Casey B, Rivera-Perez J, Welsh MJ, Beaudet AL and Bradley A. A severe phenotype in mice with a duplication of exon 3 in the cystic fibrosis locus. Hum Mol Genet 2: 1561–1569, 1993.[Abstract/Free Full Text]
  42. Peterson LE. CLUSFAVOR 5.0: hierarchical cluster and principal-component analysis of microarray-based transcriptional profiles. Genome Biol 3: SOFTWARE0002, 2002.[Medline]
  43. Pier GB and Elcock ME. Nonspecific immunoglobulin synthesis and elevated IgG levels in rabbits immunized with mucoid exopolysaccharide from cystic fibrosis isolates of Pseudomonas aeruginosa. J Immunol 133: 734–739, 1984.[Abstract]
  44. Pier GB, Grout M, and Zaidi TS. Cystic fibrosis transmembrane conductance regulator is an epithelial cell receptor for clearance of Pseudomonas aeruginosa from the lung. Proc Natl Acad Sci USA 94: 12088–12093, 1997.[Abstract/Free Full Text]
  45. Prince LS, Karp PH, Moninger TO, and Welsh MJ. KGF alters gene expression in human airway epithelia: potential regulation of the inflammatory response. Physiol Genomics 6: 81–89, 2001.[Abstract/Free Full Text]
  46. Raman V, Clary R, Siegrist KL, Zehnbauer B, and Chatila TA. Increased prevalence of mutations in the cystic fibrosis transmembrane conductance regulator in children with chronic rhinosinusitis. Pediatrics 109: E13, 2002.[Medline]
  47. Sallenave JM. The role of secretory leukocyte proteinase inhibitor and elafin (elastase-specific inhibitor/skin-derived antileukoprotease) as alarm antiproteinases in inflammatory lung disease. Respir Res 1: 87–92, 2000.[CrossRef][Medline]
  48. Schuster A, Hansen G, Zubrod-Eichert C, and Wahn V. Effects of native and oxidation-resistant secretory leukoprotease inhibitor on cystic fibrosis sputum: inhibition of neutrophil elastase activity and of sputum-induced secretion from porcine tracheal submucosal glands. Pediatr Res 40: 732–737, 1996.[Web of Science][Medline]
  49. Schwarz DA, Katayama CD, and Hedrick SM. Schlafen, a new family of growth regulatory genes that affect thymocyte development. Immunity 9: 657–668, 1998.[CrossRef][Web of Science][Medline]
  50. Schweiger A, Staib A, Werle B, Krasovec M, Lah TT, Ebert W, Turk V, and Kos J. Cysteine proteinase cathepsin H in tumours and sera of lung cancer patients: relation to prognosis and cigarette smoking. Br J Cancer 82: 782–788, 2000.[CrossRef][Web of Science][Medline]
  51. Shaked Y, Engelstein R, and Gabizon R. The binding of prion proteins to serum components is affected by detergent extraction conditions. J Neurochem 82: 1–5, 2002.[CrossRef][Web of Science][Medline]
  52. Shin JS and Abraham SN. Caveolae as portals of entry for microbes. Microbes Infect 3: 755–761, 2001.[CrossRef][Web of Science][Medline]
  53. Shin JS and Abraham SN. Co-option of endocytic functions of cellular caveolae by pathogens. Immunology 102: 2–7, 2001.[CrossRef][Web of Science][Medline]
  54. Simons K and Ikonen E. Functional rafts in cell membranes. Nature 387: 569–572, 1997.[CrossRef][Medline]
  55. Snouwaert JN, Brigman KK, Latour AM, Malouf NN, Boucher RC, Smithies O, and Koller BH. An animal model for cystic fibrosis made by gene targeting. Science 257: 1083–1088, 1992.[Abstract/Free Full Text]
  56. Srivastava M, Eidelman O, and Pollard HB. Pharmacogenomics of the cystic fibrosis transmembrane conductance regulator (CFTR) and the cystic fibrosis drug CPX using genome microarray analysis. Mol Med 5: 753–767, 1999.[Web of Science][Medline]
  57. Steagall WK, Elmer HL, Brady KG, and Kelley TJ. Cystic fibrosis transmembrane conductance regulator-dependent regulation of epithelial inducible nitric oxide synthase expression. Am J Respir Cell Mol Biol 22: 45–50, 2000.[Abstract/Free Full Text]
  58. Stotland PK, Radzioch D, and Stevenson MM. Mouse models of chronic lung infection with Pseudomonas aeruginosa: models for the study of cystic fibrosis. Pediatr Pulmonol 30: 413–424, 2000.[CrossRef][Medline]
  59. Thomas GR, Costelloe EA, Lunn DP, Stacey KJ, Delaney SJ, Passey R, McGlinn EC, McMorran BJ, Ahadizadeh A, Geczy CL, Wainwright BJ, and Hume DA. G551D cystic fibrosis mice exhibit abnormal regulation of inflammation in lungs and macrophages. J Immunol 164: 3870–3877, 2000.[Abstract/Free Full Text]
  60. van Doorninck JH, French PJ, Verbeek E, Peters RH, Morreau H, Bijman J, and Scholte BJ. A mouse model for the cystic fibrosis delta F508 mutation. EMBO J 14: 4403–4411, 1995.[Web of Science][Medline]
  61. Virella-Lowell I, Herlihy JD, Liu B, Lopez C, Cruz P, Muller C, Baker HV, and Flotte TR. Effects of CFTR, interleukin-10, and Pseudomonas aeruginosa on gene expression profiles in a CF bronchial epithelial cell Line. Mol Ther 10: 562–573, 2004.[CrossRef][Web of Science][Medline]
  62. Vogelmeier C, Gillissen A, and Buhl R. Use of secretory leukoprotease inhibitor to augment lung antineutrophil elastase activity. Chest 110: 261S–266S, 1996.[Medline]
  63. Wright JM, Zeitlin PL, Cebotaru L, Guggino SE, and Guggino WB. Gene expression profile analysis of 4-phenylbutyrate treatment of IB3–1 bronchial epithelial cell line demonstrates a major influence on heat-shock proteins. Physiol Genomics 16: 204–211, 2004.[Abstract/Free Full Text]
  64. Xu Y, Clark JC, Aronow BJ, Dey CR, Liu C, Wooldridge JL, and Whitsett JA. Transcriptional adaptation to cystic fibrosis transmembrane conductance regulator deficiency. J Biol Chem 278: 7674–7682, 2003.[Abstract/Free Full Text]
  65. Zahm JM, Gaillard D, Dupuit F, Hinnrasky J, Porteous D, Dorin JR, and Puchelle E. Early alterations in airway mucociliary clearance and inflammation of the lamina propria in CF mice. Am J Physiol Cell Physiol 272: C853–C859, 1997.[Abstract/Free Full Text]
  66. Zeiher BG, Eichwald E, Zabner J, Smith JJ, Puga AP, McCray PB Jr, Capecchi MR, Welsh MJ, and Thomas KR. A mouse model for the delta F508 allele of cystic fibrosis. J Clin Invest 96: 2051–2064, 1995.[Web of Science][Medline]
  67. Zielenski J. Genotype and phenotype in cystic fibrosis. Respiration 67: 117–133, 2000.[CrossRef][Web of Science][Medline]



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