Global gene expression profile progression in Gaucher disease mouse models
© Xu et al; licensee BioMed Central Ltd. 2011
Received: 24 August 2010
Accepted: 11 January 2011
Published: 11 January 2011
Gaucher disease is caused by defective glucocerebrosidase activity and the consequent accumulation of glucosylceramide. The pathogenic pathways resulting from lipid laden macrophages (Gaucher cells) in visceral organs and their abnormal functions are obscure.
To elucidate this pathogenic pathway, developmental global gene expression analyses were conducted in distinct Gba1 point-mutated mice (V394L/V394L and D409 V/null). About 0.9 to 3% of genes had altered expression patterns (≥ ± 1.8 fold change), representing several categories, but particularly macrophage activation and immune response genes. Time course analyses (12 to 28 wk) of INFγ-regulated pro-inflammatory (13) and IL-4-regulated anti-inflammatory (11) cytokine/mediator networks showed tissue differential profiles in the lung and liver of the Gba1 mutant mice, implying that the lipid-storage macrophages were not functionally inert. The time course alterations of the INFγ and IL-4 pathways were similar, but varied in degree in these tissues and with the Gba1 mutation.
Biochemical and pathological analyses demonstrated direct relationships between the degree of tissue glucosylceramides and the gene expression profile alterations. These analyses implicate IFNγ-regulated pro-inflammatory and IL-4-regulated anti-inflammatory networks in differential disease progression with implications for understanding the Gaucher disease course and pathophysiology.
Gaucher disease, an autosomal recessive disorder, is a common lysosomal storage disease. Insufficient activity of acid β-glucosidase (glucocerebrosidase, GCase, E.C.126.96.36.199) in all cells leads to the substrate accumulation including glucosylceramide and glucosylsphingosine, and the various clinical phenotypes. The pathologic hallmark of Gaucher disease is the presence of lipid laden macrophages, a.k.a., Gaucher cells, in visceral organs . The macrophages are thought to be the primary visceral cells involved in all variants, and these cells become progressively numerous and engorged with glucosylceramide by phagocytic processes. By yet undefined mechanisms, this process leads to tissue dysfunction that can result in fibrosis and scarring during the later stages of the disease.
Some of these tissue changes have been attributed to "activation" of the engorged macrophages with subsequent release of inflammatory agents. Indeed, some Gaucher disease patients had increased levels of pro-inflammatory (i.e., TNFα, IL-6, IL-8, and IL-1β) and anti-inflammatory cytokines (i.e., CD14) in serum and/or tissues [2–4]. TNFα production has been suggested as a response to glucosylceramide accumulation in Gaucher disease patients . Serum levels of M-CSF, sCD14 (a macrophage activation marker), and IL-8 can also be increased and correlations have been made with the severity of Gaucher disease . An in situ study of spleen from a Gaucher disease patient showed increased expression of anti-inflammatory mediators in macrophages, including CCL18, CD163, chitotriosidase, IL-1Ra, and CD14 . Such anti-inflammatory mediators are considered markers of alternatively activated macrophages (aamφ) [6–10] and implicate secreted cytokines as pathophysiological agents in Gaucher disease. Such studies also suggest a central role of glucosylceramide in altered macrophage function as an initiator of the disease pathogenesis.
How the insufficiency of GCase activity and the subsequent metabolic disturbances related to glucosylceramide and other sphingolipids (GSLs) could lead to such inflammatory imbalances remains obscure. However, the consequent imbalances of ceramide, sphingosine, and sphingosine 1-phosphate in Gaucher disease could affect immunologic responses, inflammation and cell proliferation [11–13]. These and other studies implicate profound systematic pathophysiological changes rather than simple lipid accumulation as the basis of the disease . The pathologic manifestations of various organs suggest that the defective glucosylceramide hydrolysis and substrate accumulation in multiple organs affects numerous metabolic networks. Consequently, systematic transcriptome analyses could provide useful insights into the resultant molecular events underlying GCase deficiency and glucosylceramide storage as well as related tissue pathogenesis in Gaucher disease. In addition to visceral processes, some correlations of neuropathologic involvement with gene expression profiles in brains from neuronopathic Gaucher disease patients or Gba1 variant mice [14, 15] provide isolated cross-sectional views of the disease processes. However, they have not provided insight into the dynamic or sequential nature of such pathophysiological progression.
Here, viable Gba1 point-mutated mice, V394L/V394L (4L) and D409 V/null (9 V/null), were used to explore the temporal and spatial profiles of tissue and Gba1 mutation-related gene expression by genome-wide mRNA microarrays and immunohistochemical analyses. Particular focus was on macrophage activation (classic and alternative) responses and IFNγ regulated pro-inflammatory or IL-4 regulated anti-inflammatory networks. These studies established a starting point for understanding the basis of the progressive pathophysiology in Gaucher disease at a molecular/tissue level.
Phenotype of Gba1 V394L homozygotes (4L) and D409 V/null (9 V/null) mice
Differential gene expression in tissues from Gaucher mice
Classification of significantly expressed genes in tissues of 9 V/null and 4L mice
intracellular signaling cascade
lipid metabolic process
response to stress
Expression profile of macrophage activation genes
Expression of pro- and anti-inflammatory macrophage activation genes in lungs of 9 V/null and 4L mice
chemokine (C-C motif) ligand 19
chemokine (C-C motif) ligand 2
chemokine (C-C motif) ligand 3
chemokine (C-C motif) ligand 6
chemokine (C-C motif) ligand 9
chemokine (C-X-C motif) ligand 1
chemokine (C-X-C motif) ligand 12
macrophage scavenger receptor 1
nitric oxide synthase 2, inducible, macrophage
tumor necrosis factor
arginase type II
chemokine (C-C motif) ligand 17
chemokine (C-C motif) ligand 22
Immunoglobulin heavy chain 6
interleukin 1 receptor antagonist
matrix metallopeptidase 12
matrix metallopeptidase 19
matrix metallopeptidase 9
resistin like alpha
In the IL-4 regulated pathway, 9 anti-inflammatory genes were up regulated in 9 V/null lung (Table 2). Two genes (Igh-6 and Rentlα) were up regulated by 4 wk and then continuously up regulated at 12 to 28 wk. The other seven anti-inflammatory genes were unchanged at 4 wk. These less significant changes in the anti-inflammatory genes at the age of 4-wk reflect the underdevelopment of alternatively activated macrophage features. With age (12-, 18- or 28-wk), all anti-inflammatory genes were consistently up regulated including the NOS2 counteracting enzyme arginase type II (Arg2), cytokine/chemokine CCL17/CCL22, immunoglobulin heavy chain 6 (Igh-6), IL-1 receptor antagonist (IL-1rn), and matrix metallopeptidase MMP9/12/19 (Table 2). Among these genes, MMP12 expression was exceptionally high (37- to 56-fold increased). MMP-12, macrophage elastase, functions to degrade extracellular matrix components, e.g., elastin, and is involved in acute and chronic pulmonary inflammatory diseases associated with an intense airway remodeling [17, 18]. The anti-inflammatory genes, e.g., IL-4, and the macrophage scavenger receptor CD163 did not meet statistical significance, but were positive by immunohistochemistry. With 9 V/null liver mRNA, only three anti-inflammatory genes (Igh-6, IL-1rn and MMP12) were consistently up regulated (Additional file 5) indicating differential effects on the IL-4-regulated anti-inflammatory pathway genes in lung and liver. In 9 V/null lung, these data show that the IL-4 regulated anti-inflammatory cytokines/mediators were also temporally and spatially altered and they were expressed in parallel with coordinate pro-inflammatory genes with disease progression.
Commonality of significantly expressed genes involved in macrophage activation
Effects of genetic background on mRNA profiles
The genetic backgrounds of 9 V/null (FVB and C57BL/6J-129SvEvBrd) and 4L (C57BL/6J-129SvEvBrd) were slightly different, since the 9 V/null was generated by crosses of 9 V/9 V (C57BL/6J-129SvEvBrd) with null/WT (FVB) mice. To validate the macrophage gene expression profile and evaluate effects of the FVB strain on gene expression, FVB WT data sets (2 chips at 4 different time points each tissue) were run using the same methods and standards. A total of 48 chip sets (each 8 chip data from 9 V/null lung and liver, 4L lung and liver, and FVB WT lung and liver) were loaded into Partek Genomics Suite 6.4, and the data were normalized and analyzed (see Methods). FDR was set at 0.01 and fold change was set at ±1.8 for significance.
The numbers of significantly expressed genes in 9 V/null lung based upon the WT controls from these two different genetic backgrounds are as follows. With the FVB WT as control data set, 910 genes with significantly altered expression were selected. Among them, 10% (90/910 genes) were macrophage activation genes and 1.6% (15/910) were pro-/anti-inflammatory genes (Additional file 6 and Additional file 7 Table S1). The commonality of macrophage genes selected based upon different genetic background was also analyzed. Among 90 macrophage genes (FVB8chip), 52% (47 genes) were the same as with genetic matched controls (FVB/C57BL/6J-129Svchip). Also, 83% of INFγ/IL-4 regulated pathway genes were shown to have similar gene expression profiles using either of the two genetic backgrounds. Although some variation exists in the selected genes and their expression significance, the macrophage activation genes, including INFγ and IL-4 pathway genes, were identified as a major functional group using either strains.
Validation of selected mRNA expression
Immunohistochemical studies of the macrophage activation related genes
Histological and immunohistochemical studies were conducted with lung and liver sections from 9 V/null and 4L mice to correlate gene expression patterns with protein levels. As shown, numerous large storage cells were observed in 9 V/null lung with positivity for the surface antigens, CD68 and F4/80 (Figure 2). CD68 RNA also was elevated in lungs (3.3-7.2 fold) and livers (2.0-4.8 fold) of 9 V/null mice at 12 to 28 wk, but they had no significant alteration in 4L lung and liver (Additional files 1 and 4). This result would be expected because of the large number of storage cells in the lungs of 9 V/null mice. Immunohistochemical staining with CD68 antibody showed high intensity CD68-positive storage cells in the lung (Figure 2, middle) and liver (not shown). CD68-positive cells were quantified and showed 205 and 241 per 20 representative fields (40×) in the lung from two 9 V/null mice. A few small sized CD68-positive cells were observed in WT lung at 28 wk (Figure 2, middle). In 4L lungs, multiple (268 ± 38, 40× field, n = 10) small CD68-positive macrophages were present at 28 wk (Figure 2, middle). F4/80 (Emr1) RNA signals were within ±1.8-fold range in all 9 V/null and 4L tissues. By immunohistochemistry, F4/80 positive macrophages were 190 and 174 per 20 fields (40×) in the lung of two 9 V/null mice. The qualitative staining intensity of F4/80-positive storage cells was weak to medium compared to that of CD68 positive cells in lung of 9 V/null mice (Figure 2, bottom).
IFNγ and IL-4 regulated pathways and gene expression networks
The genome-wide transcriptome data presented here demonstrate genotype and tissue-type related gene expression patterns in 9 V/null and 4L mice that are analogues of human Gaucher disease. Interestingly, the percentage of functional categories containing dysregulated RNAs was similar across all 9 V/null or 4L tissues, except for the macrophage activation genes that showed ~2-fold enrichment in 9 V/null lung, the most extensively involved organ (Table 1). Another identified group was that for immune response genes, which were altered only in 9 V/null lung. Among the 54 immune response genes, 47 overlapped with the macrophage group. Since histological analyses did not find obvious T-cell and B-cell infiltration in 9 V/null lung, these immune responses likely emanated from macrophages. Macrophage activation in 9 V/null lung was also supported by hierarchical clustering analysis in which the 117 genes in cluster 3 (Figure 3) were exclusively expressed in 9 V/null, rather than in 4L lung; a third of these were macrophage activation genes (Figure 3, highlighted region). These results indicate significant involvement of macrophage activation genes in 9 V/null lung, which was concordant with the extensive macrophage infiltration in the lungs. Moreover, the complementary histopathological studies showed that the nature of macrophage activation was not uniform between tissues or within macrophages in a specific tissue. These data support the concept of a variety of dysregulated macrophages that are tissue and disease state dependent as a dynamic component of the Gaucher disease/glucosylceramide storage pathophysiology.
Engorged macrophages are a hallmark of Gaucher disease, and these cells were differentially activated in tissues of 9 V/null and 4L mice at the mRNA, cellular, and immunohistochemical levels. The progressively increasing sizes and numbers of macrophages in visceral organs of Gba1 variant mice, because of the lipid storage, was particularly evident in lungs of 9 V/null mice from 12 to 28 wk (Figure 1). Immunohistochemistry with the antibodies to selected IFNγ-regulated pro-inflammatory and IL-4-regulated anti-inflammatory cytokines showed that these cytokines were expressed in lung macrophages, but not in lung epithelial cells, i.e., there were pro- and anti-inflammatory responses (or activation) of the lipid-laden macrophage. Also, such analyses showed significant expression of the IFNγ protein in lung macrophages of 9 V/null mice at 12 and 28 wk (Figure 9), but lesser expression in liver. These expression patterns were concordant with the differential activation of macrophages in these tissues as was evident by both microarray and morphologic data. In addition, IFNγ and its regulated pathway genes were less aberrant in tissues of the 4L mice, a more attenuated model, as ascertained by RNA or protein analyses. These results implicate pro-inflammation as a primary pathophysiological mechanism in Gaucher disease, as well as the degree of alterations in this pathway in the severity of Gaucher disease involvement. The production and secretion of cytokines from storage macrophages can be the important factors for the extracellular matrix components and function as they influence the interaction of surrounding macrophages with phagocytotic or endocytotic ligands and propagate the pathophysiology .
IFNγ is a potent activator of macrophages and induces the expression of >300 genes, including those in the inflammatory mediator/chemokine pathway . Also, activated macrophages can be a significant source of IFNγ [23–25]. Importantly, IFNγ inhibits macrophage proliferation and protects them from apoptosis , thereby prolonging their survival within inflammatory loci . Here, the RNA expression levels of IFNγ, IL-6, NOS2, and TNFα were not significantly increased (FDR = 0.01), but their protein levels were specifically and highly expressed in the large lung macrophages. This observation indicates that the expression of these proteins and RNAs could be missed in whole tissue homogenates in which there may be large dilutional effects, if expression is restricted to specific cell types that make up a small percentage of total cells, e.g., macrophages. Importantly, 12 other cytokines are in the IFNγ pathway and could be downstream modulated by this cytokine. For example, IFNγ can induce TNFα and NOS2, and has differential effects on several individual chemokine genes  that provide for selective stimulus sensitivity in mediating restricted pattern of chemokine gene expression. Transcripts for CXCL1/12 and the CCL chemokines (CCL2, 3, 6, 9 or 19) can be enhanced by Th1-related inflammatory mediators including IFNγ, IL-6, TNFα, or LPS [28, 29] as well as modulating the effects of each other (Figure 15). The outcomes of such interactions lead to a cascading cytokine pro-inflammatory dysregulation that propagates Gaucher disease. Indeed, TNFα is a major regulator of chemokine gene expression, e.g., CXCL2, CCL3 and IL-6 [30–37]. The finding here that TNFα protein was up regulated (Figure 11) implicates its downstream cytokine network during Gaucher disease progression. Also, cytokines, e.g., CCL3, act synergistically with other macrophage chemokines  to maintain the pro-inflammatory reactions.
Pro-inflammatory cytokines play a critical role in macrophage/leukocyte recruitment and adhesion [39–42] and they recruit new macrophages to involved tissues via this cytokine network. Under the stimulus of accumulating glucosylceramide and other glucolipids, such a positive feedback macrophage-cytokine-macrophage cycle can be envisioned to expand and promote progression and the recruitment of additional pro-inflammatory cytokines/mediators networks (Figure 15). The progressive cascade is schematically shown in Figure 15 in which numerous interacting cytokines and chemokines are progressively up-regulated during disease progression from 4 to 28 wk. IFNγ central to this cascading network with initial mRNA up-regulation of β- and α-chemokines, as well as Mrs1 (macrophage scavenger receptor 1), TNFα, and NOS2. Among these interacting factors is the pleiotropic cytokine IL-6, which is a systemic alarm for tissue damage [43–45]. The β-chemokines, CCL2, CCL3, CCL6, CCL9, CCL19, and the α-chemokines, CXCL1, CXCL12, mediate pro-inflammatory effects in the various types of cells and also have synergetic effects on their targets [30, 33, 46]. The macrophage scavenger receptor 1 (Msr1) has been implicated in many macrophage-associated physiological and pathological processes through endocytosis . NOS2 and arginase were up-regulated at the RNA and protein levels in the 9 V/null mice, and as has been observed in ex vivo studies . NOS2 produces nitric oxide from arginine and stimulates pro-inflammation [49–51]. NOS2 production in macrophages up-regulates vascular endothelial growth factor (e.g. VEGF) production and activates angiogenic activity [52, 53]. In comparison, arginase2 is a negative angiogenic regulator that inhibits NOS2 activity . Thus, arginase2 and NOS2 alternative pathways in activated macrophages  and their up-regulation in 9 V/null mice simultaneous pro- and anti-inflammatory networks are being activated in the Gaucher disease process.
Interrogation of the IL-4 mediated anti-inflammatory network highlights significantly differential expression of 11 anti-inflammatory genes, indicating that participation of the aamφ IL-4 pathway that counteract expression of macrophage pro-inflammatory cytokines and induce molecules that facilitate tolerance, healing and expression of innate immunity receptors, e.g. the scavenger receptor, CD163 [7, 55, 56]. The IL-4 pathway (Figure 15B) displays the IL-4 time course and interactions over the 4 to 28 wk period. After an initial lag period from 4 to 12 wk, a network of such Th2 response genes [57, 58] is up-regulated at the RNA and/or protein levels. This network includes the structurally and functionally related matrix metalloproteinases MMP9/12/19 that are endopeptidases important to remodeling processes [9, 17, 59, 60]. These MMPs are among the most highly-expressed genes in most 9 V/null tissues. The high level expression of MMPs correlated with chronic fibrotic processes in 9 V/null lung and liver (unpublished observation). MMP12 expression occurs in human alveolar macrophages [18, 61] and airway smooth muscle cells , and in murine alveolar type II epithelial cells  or primary lung fibroblasts . The immunohistochemistry showed very strong signals in the lipid-laden macrophages, and much weaker signals in other lung cells (Figure 12). The extremely high level of MMP12 expression (37 to 56-fold in 9 V/null lung and 16 to 22-fold in 9 V/null liver) implicates the aamφ in Gaucher disease progression.
The aamφs are also implicated in the disease progression in 9 V/null mice as evidenced by CD163 expression [10, 65] and, particularly, expression of the IL-1 receptor antagonist (IL-1rn). IL-1rn inhibits the activities of IL-1A and IL-1B, and modulates IL-1 related immune and inflammatory responses. IL-1rn is typically produced by aamφ and regulated by IL-4 [66, 67]. The interactions of these anti-inflammatory cytokines are schematically shown in Figure 15 and indicate an overall description of pro-/anti-inflammatory networks in Gba1 mutant mice.
The global gene expression networks integrate the gene expression patterns observed in 9 V/null or 4L mice. In these networks, more than 1/3 of significantly expressed genes were connected through the cascade interactions of pro- and anti-inflammatory genes. Although the macrophage involvement is major histopathological finding, about 3% of the genome was significantly altered at a molecular level during the development of the disease process. The propagation of the disease clearly depends on a generalized pro- and anti-inflammatory disruption.
Macrophages display marked phenotype heterogeneity in vitro and in vivo, including the responsiveness to endogenous and exogenous stimuli . Such heterogeneity results in differential phagocytosis or endocytosis, intracellular signaling and gene activation or repression [21, 68]. Macrophage heterogeneity was observed in the 9 V/null and 4L models by their differential activation and tissue distribution. Large lipid-laden macrophages (CD68 and F4/80 positive) were mostly observed in the lung of 9 V/null mice. Quantitative immunohistochemistry showed only some cytokines/effectors (i.e., IL-6, NOS2, CCL2, CCL3, CCL9, IL-4, and MMP12) were present in ~50% of lung macrophages (Figure 14). However, IFNγ and Arg2 were present in nearly all of such macrophages. The corresponding RNAs of the cytokine/effectors were also up regulated. The basis for this heterogeneous expression of cytokine proteins in macrophages is unknown, but may be due to the different origins, differentiation sates, or maturation of the macrophage populations.
The genetic background of mice can influence gene expression profiles. Interstrain variations (1-3%) of gene expression profiles have been shown in different brain regions of mouse inbred strains [69–72]. For example, such variation can be observed in the differential susceptibility to a wide range of pathogens [73–76]. Here, 9 V/null and 4L mice had mixed strain backgrounds from three in-bred mouse strains FVB and/or C57BL/6J-129Sv. To evaluate the potential effects of mouse strain background on the expression profiles of macrophage activation genes, the WT data sets from FVB and three inbred mixed strains were used in the analyses. The result showed >50% of significantly expressed macrophage activation genes were shared when either of the two background controls were used. There was 83% concordance in the INFγ- and IL-4- regulated pathway genes. In addition, comparative analyses were conducted with duplicate lung RNA chip data from WT adult mice of three different genetic backgrounds (FVB, C57BL/6J, or 129Sv). The combined WT data generated 790 significantly expressed genes in 9 V/null lung (data not shown). About 60% of significantly expressed macrophage genes were concordant between FVB only or strain-matched WT controls, including >90% of INFγ-/IL4-regulated pathway genes (data not shown). The results showed general agreement of the gene expression profiles from individual WT backgrounds with those from WT controls either pure FVB or strain-matched backgrounds. The results show that macrophage activation genes are a significant functional group in the propagation of Gaucher disease in several genetic backgrounds.
We demonstrated direct relationships between the degree of tissue glucosylceramides and the gene expression profile alterations. These analyses implicate IFNγ-regulated pro-inflammatory and IL-4-regulated anti-inflammatory networks in differential disease progression with implications for understanding the Gaucher disease course and pathophysiology.
The following were from commercial sources: RNA Later and TOTALLY RNA kit (Ambion, Austin, TX). Antibody sources are as the follows: Anti-INFγ, CCL2, CCL3, CCL9, CD68, F4/80, IL-4, CD68, and Goat anti-rat-HRP (Serotec, Raleigh, NC). Anti-TNFα (Biosource, Camarillo, CA). Anti-Arg1, Arg2 and CD163 (Santa Cruz, CA). Anti-NOS2 (Chemicon, Temecula, CA), Anti-IL6 (R & D, Minneapolis, MN). Anti-MMP12 (Biomol, Plymouth Meeting, PA). Horse anti-goat-HRP, ABC Vectastain and DAB Substrate Kit (Vector laboratory, Burlingame, CA). Sheep anti-mouse-HRP, Streptavidin-Alexa Fluor 488, Goat anti-rabbit Alexa Flour610, Goat anti-rabbit-HRP (Molecular Probes, Irvine, CA). High Capacity cDNA Archive Kit and SYBR Green PCR Master Mix (Applied Biosystems, Foster City, CA).
Gba1 mutated mice
V394L/V394L homozygote (4L) and D409V/null mice (9 V/null) were generated with mixed genetic backgrounds. 4L mice were 50% of C57BL/6J and129SvEvBrd and 9 V/null mice were 50% of FVB, 25% of C57BL/6J and129SvEvBrd . The wild-type (WT) controls were strain genetic background matched adult mice (50% of FVB, 25% of C57BL/6J and129SvEvBrd,). All mice were housed under pathogen-free conditions in the barrier animal facility and according to IACUC standard procedures at Cincinnati Children's Hospital Research Foundation.
Glycosphingolipids in liver and lung from Gba1 mutant and WT mice (5 mg tissues) were extracted with chloroform and methanol as described . Glucosylceramide analysis was carried out by ESI-LC-MS/MS using a Waters Quattro Micro API triple quadrupole mass spectrometer (Milford, MA) interfaced with Acquity UPLC system. The ESI-MS/MS was operated in the multiple reaction monitoring mode for monitoring transition pair of the individual protonated parent ions and their common daughter ion m/z 264. Calibration curves were built for C16, C18 and C24:1 β-glucosylceramides using C12 β-glucosylceramide as an internal standard (Matreya, LLC and Avanti Polar lipids, Inc.). The extracted glycosphingolipid samples were suspended in methanol containing internal standard and injected (10 μL) into the LC/MS. The level of total glucosylceramide in the liver and lung were normalized to mg tissue weight.
RNA preparation and microarray hybridization
Lungs and livers were collected from 9 V/null and 4L mice at the age of 4, 12, 18 and 28 wk, and from genetic background matched adult WT mice (28 wk) and age-matched FVB WT mice (4 - 28 wk) for total RNA preparation. Collected tissues were immediately immersed in RNA Later and tissue RNAs were extracted using the TOTALLY RNA kit. Each tissue RNA set for microarray analysis was pooled from 3 age and genotype matched mice and at least duplicate sample sets for each genotype, tissue, and age were used. This represents 39 labeled RNA sample sets (4 WT, 8 9 V/null and 8 4L lung RNAs; 3 WT, 8 9 V/null and 8 4L liver RNAs) were submitted to the CCHRF Affymetrix Microarray Core for hybridization to Affymetrix GeneChip Mouse Genome 430 2.0 Arrays using standardized protocols. Labeled cRNA synthesis, GeneChip hybridization, washing and staining followed standard Affymetrix protocols. The probed arrays were scanned with the Affymetrix GeneChip® Scanner 3000 and the intensities of array signals were captured with GeneChip Operating Software (GCOS) v1.1.0, according to standard Affymetrix procedures. The entire microarray data set is available at the Gene Expression Omnibus (GEO) accessible through GEO series accession number GSE23408.
GeneChip quality assessment
Array data were evaluated for quality assessment using the procedures in the Affymetrix based on scaling factor (10-50), percent present (>30%), and housekeeping gene yielding 3'/5' signal ratios <3. Global normalization for outliers or "bad chips" was conducted with each sample/chip. The normalized intensity values were subjected to hierarchical clustering to determine the relative signal intensity of tissue RNA samples derived from different developmental stages and to identify the outlier(s) or bad chips. GeneChips that passed these screenings were used for subsequent analyses to identify significantly affected genes in tissues of 4L and 9 V/null mice at various time points. To evaluate the affects of strain or genetic background, additional control chip data were from age-matched WT FVB mice (4 to 28 wk, 2 chips for each age group).
Microarray data normalization and analysis
Here yijkm is the expression of the gene for ith genotype, jth tissue, and kth age, and mth subject. The symbols G, T, A, GTA and S represent effects due to genotype (G), tissue (T), age (A), genotype-by-tissue-by-age interaction (GTA), and subject (S). The error for each gene for sample ijk is designated εijkm. Genotype, tissue, and age are fixed effects, and subject is a random effect in the mixed model. For each comparison, a linear contrast was set up to obtain the relative fold changes between each mutant and WT control for each tissue at all time points. Four contrasts were added in the computation: 9 V/null vs. control and 4L vs. control in lung and liver. False Discovery Rate (FDR) was used to further guard against false positives because of multiple testing . FDR was set at ≤0.01 and fold change was set at ±1.8.
Significantly affected or differentially expressed genes were subjected to an intensive search to identify biological functions. Functional classifications were performed using the Gene Ontology classification obtained through the DAVID Bioinformatics Database (available at http://david.abcc.ncifcrf.gov/home.jsp), and public information and/or literature references. The enriched functional categories were determined by Fisher Exact Test using the corresponding murine genome as a reference dataset. The significance was set at p-value < 0.05. The differentially expressed genes were grouped into the following categories (Table 1): catalytic activity, cell death, cytoskeleton, immune response, intracellular signaling cascade, kinase activity, lipid metabolic process, lysosome, macrophage activation, response to stress, transcription and transport.
Clustering of gene expression profiles
Hierarchical cluster analysis of the significantly expressed genes was performed using GeneSpring GX 7.3 (Agilent Technologies, Inc., Santa Clara, CA), which showed the correlated groups of genes and their expression patterns across all time points.
Network and Pathway analysis
The significantly differentially expressed genes in the lung of 9 V/null or 4L were loaded into PathwayArchitect 2.0.1 (Stratagene, La Jolla, CA) and built into IFNγ- or IL-4- regulated pathways and global networks. The pathways and networks were constructed based upon the published literature, Ingenuity Pathways Analysis (Ingenuity Systems, Inc), and PathwayArchitect 2.0.1 (Stratagene, La Jolla, CA).
Common genes selection
The common differentially expressed genes and consistently expressed macrophage activation genes in the lung or liver between 9 V/null and 4L mice were displayed as Venn diagrams.
To verify selected targets from the RNA chip data, real-time RT-PCR assays were developed. RNAs (10 μg) from the same pooled samples as used for microarray chip analyses were used for real-time RT-PCR assays. Each RNA sample was reverse-transcribed (RT) using High Capacity cDNA Archive Kit to synthesize total RNA-cDNA templates with random hexamers. Real-time RT-PCR was conducted using SYBR Green PCR Master Mix with sequence specific primers for CCL9, Msr1, CCL17, MMP12, and β-actin cDNA (Additional file 7 Table S2). The reaction mixtures were incubated in ABI/Prism7000 Sequence Detection System for 40 cycles (95°C, 15 sec and 60°C, 20 sec). The primers were designed with Primer Expression 2.0 (Applied Biosystems) and spanned exon/exon conjunctions (Additional file Table S2). The real-time RT-PCR signals from each RNA primer set were normalized by β-actin signals.
Mouse tissues (liver and lung) were collected and fixed in 10% buffered formalin for hematoxylin and eosin (H&E) staining and light microscopic studies. For immunohistochemistry and immunofluorescence staining, tissues were fixed in 4% paraformaldehyde/phosphate buffered saline (PBS), pH 7.4, and processed for frozen sections. Tissue sections were blocked with 5% nonfat milk containing 0.4% Triton X-100 in PBS. Tissue sections were incubated with primary anti-mouse cytokine antibodies at 4°C overnight, and then with the compatible secondary antibodies at room temperature (1 h). The secondary antibodies were conjugated with fluorescene or horseradish peroxidase (HRP), or a biotinylated secondary antibody/streptavidin-dye system was used. CD68 (FITC) was used as a macrophage marker, and cytokines were detected using specific antibodies and biotin/streptavidin-conjugated dye Alexa Fluor-610. Positively stained macrophages were quantified using a series of 20 frames (magnification 400×) and counted using MetaMorph 6.1 (Universal Imaging Corp, Downingtown, PA).
The authors thank Venette Inskeep for her excellent technical assistance; Lisa McMillin and Meredith Farmer for skilled tissue preparation; Drs. Daniel Prows and Yan Xu for providing their mouse WT lung microarray data. This work was supported by a NIH grant (R01DK 36729) to GAG.
- Beutler E, Grabowski GA: Gaucher Disease. The Metabolic and Molecular Basis of Inherited Disease. Edited by: Scriver CR, Beaudet AL, Sly WS, Valle D. 2001, New York: McGraw-Hill, III: 3635-3668. eighthGoogle Scholar
- Barak V, Acker M, Nisman B, Kalickman I, Abrahamov A, Zimran A, Yatziv S: Cytokines in Gaucher's disease. Eur Cytokine Netw. 1999, 10 (2): 205-210.PubMedGoogle Scholar
- Hollak CE, Evers L, Aerts JM, van Oers MH: Elevated levels of M-CSF, sCD14 and IL8 in type 1 Gaucher disease. Blood Cells Mol Dis. 1997, 23 (2): 201-212. 10.1006/bcmd.1997.0137.PubMedView ArticleGoogle Scholar
- Michelakakis H, Spanou C, Kondyli A, Dimitriou E, Van Weely S, Hollak CE, Van Oers MH, Aerts JM: Plasma tumor necrosis factor-a (TNF-a) levels in Gaucher disease. Biochim Biophys Acta. 1996, 1317 (3): 219-222.PubMedView ArticleGoogle Scholar
- Boven LA, van Meurs M, Boot RG, Mehta A, Boon L, Aerts JM, Laman JD: Gaucher cells demonstrate a distinct macrophage phenotype and resemble alternatively activated macrophages. Am J Clin Pathol. 2004, 122 (3): 359-369. 10.1309/BG5VA8JRDQH1M7HN.PubMedView ArticleGoogle Scholar
- Frings W, Dreier J, Sorg C: Only the soluble form of the scavenger receptor CD163 acts inhibitory on phorbol ester-activated T-lymphocytes, whereas membrane-bound protein has no effect. FEBS Lett. 2002, 526 (1-3): 93-96. 10.1016/S0014-5793(02)03142-3.PubMedView ArticleGoogle Scholar
- Goerdt S, Politz O, Schledzewski K, Birk R, Gratchev A, Guillot P, Hakiy N, Klemke CD, Dippel E, Kodelja V, et al: Alternative versus classical activation of macrophages. Pathobiology. 1999, 67 (5-6): 222-226. 10.1159/000028096.PubMedView ArticleGoogle Scholar
- Gordon S: Alternative activation of macrophages. Nat Rev Immunol. 2003, 3 (1): 23-35. 10.1038/nri978.PubMedView ArticleGoogle Scholar
- Gratchev A, Guillot P, Hakiy N, Politz O, Orfanos CE, Schledzewski K, Goerdt S: Alternatively activated macrophages differentially express fibronectin and its splice variants and the extracellular matrix protein betaIG-H3. Scand J Immunol. 2001, 53 (4): 386-392. 10.1046/j.1365-3083.2001.00885.x.PubMedView ArticleGoogle Scholar
- Mantovani A, Sozzani S, Locati M, Allavena P, Sica A: Macrophage polarization: tumor-associated macrophages as a paradigm for polarized M2 mononuclear phagocytes. Trends Immunol. 2002, 23 (11): 549-555. 10.1016/S1471-4906(02)02302-5.PubMedView ArticleGoogle Scholar
- Cuvillier O: Sphingosine in apoptosis signaling. Biochim Biophys Acta. 2002, 1585 (2-3): 153-162.PubMedView ArticleGoogle Scholar
- Obeid LM, Linardic CM, Karolak LA, Hannun YA: Programmed cell death induced by ceramide. Science. 1993, 259 (5102): 1769-1771. 10.1126/science.8456305.PubMedView ArticleGoogle Scholar
- Pettus BJ, Chalfant CE, Hannun YA: Sphingolipids in inflammation: roles and implications. Curr Mol Med. 2004, 4 (4): 405-418. 10.2174/1566524043360573.PubMedView ArticleGoogle Scholar
- Hong YB, Kim EY, Jung SC: Down-regulation of Bcl-2 in the fetal brain of the Gaucher disease mouse model: a possible role in the neuronal loss. J Hum Genet. 2004, 49 (7): 349-354. 10.1007/s10038-004-0155-2.PubMedView ArticleGoogle Scholar
- Myerowitz R, Mizukami H, Richardson KL, Finn LS, Tifft CJ, Proia RL: Global gene expression in a type 2 Gaucher disease brain. Mol Genet Metab. 2004, 83 (4): 288-296. 10.1016/j.ymgme.2004.06.020.PubMedView ArticleGoogle Scholar
- Xu YH, Quinn B, Witte D, Grabowski GA: Viable mouse models of acid beta-glucosidase deficiency: the defect in Gaucher disease. Am J Pathol. 2003, 163 (5): 2093-2101.PubMedPubMed CentralView ArticleGoogle Scholar
- Nenan S, Boichot E, Lagente V, Bertrand CP: Macrophage elastase (MMP-12): a pro-inflammatory mediator?. Mem Inst Oswaldo Cruz. 2005, 100 (Suppl 1): 167-172.PubMedView ArticleGoogle Scholar
- Shapiro SD, Kobayashi DK, Ley TJ: Cloning and characterization of a unique elastolytic metalloproteinase produced by human alveolar macrophages. J Biol Chem. 1993, 268 (32): 23824-23829.PubMedGoogle Scholar
- Lam-Yuk-Tseung S, Gros P: Genetic control of susceptibility to bacterial infections in mouse models. Cell Microbiol. 2003, 5 (5): 299-313. 10.1046/j.1462-5822.2003.00276.x.PubMedView ArticleGoogle Scholar
- Pradines JR, Farutin V, Rowley S, Dancik V: Analyzing protein lists with large networks: edge-count probabilities in random graphs with given expected degrees. J Comput Biol. 2005, 12 (2): 113-128. 10.1089/cmb.2005.12.113.PubMedView ArticleGoogle Scholar
- de Fougerolles AR, Chi-Rosso G, Bajardi A, Gotwals P, Green CD, Koteliansky VE: Global expression analysis of extracellular matrix-integrin interactions in monocytes. Immunity. 2000, 13 (6): 749-758. 10.1016/S1074-7613(00)00073-X.PubMedView ArticleGoogle Scholar
- Boehm U, Klamp T, Groot M, Howard JC: Cellular responses to interferon-gamma. Annu Rev Immunol. 1997, 15: 749-795. 10.1146/annurev.immunol.15.1.749.PubMedView ArticleGoogle Scholar
- Fenton MJ, Vermeulen MW, Kim S, Burdick M, Strieter RM, Kornfeld H: Induction of gamma interferon production in human alveolar macrophages by Mycobacterium tuberculosis. Infect Immun. 1997, 65 (12): 5149-5156.PubMedPubMed CentralGoogle Scholar
- Munder M, Eichmann K, Moran JM, Centeno F, Soler G, Modolell M: Th1/Th2-regulated expression of arginase isoforms in murine macrophages and dendritic cells. J Immunol. 1999, 163 (7): 3771-3777.PubMedGoogle Scholar
- Xing Z, Zganiacz A, Santosuosso M: Role of IL-12 in macrophage activation during intracellular infection: IL-12 and mycobacteria synergistically release TNF-alpha and nitric oxide from macrophages via IFN-gamma induction. J Leukoc Biol. 2000, 68 (6): 897-902.PubMedGoogle Scholar
- Xaus J, Cardo M, Valledor AF, Soler C, Lloberas J, Celada A: Interferon gamma induces the expression of p21waf-1 and arrests macrophage cell cycle, preventing induction of apoptosis. Immunity. 1999, 11 (1): 103-113. 10.1016/S1074-7613(00)80085-0.PubMedView ArticleGoogle Scholar
- Gudmundsson G, Hunninghake GW: Interferon-gamma is necessary for the expression of hypersensitivity pneumonitis. J Clin Invest. 1997, 99 (10): 2386-2390. 10.1172/JCI119420.PubMedPubMed CentralView ArticleGoogle Scholar
- Chiu BC, Freeman CM, Stolberg VR, Komuniecki E, Lincoln PM, Kunkel SL, Chensue SW: Cytokine-chemokine networks in experimental mycobacterial and schistosomal pulmonary granuloma formation. Am J Respir Cell Mol Biol. 2003, 29 (1): 106-116. 10.1165/rcmb.2002-0241OC.PubMedPubMed CentralView ArticleGoogle Scholar
- Jiang Y, Beller DI, Frendl G, Graves DT: Monocyte chemoattractant protein-1 regulates adhesion molecule expression and cytokine production in human monocytes. J Immunol. 1992, 148 (8): 2423-2428.PubMedGoogle Scholar
- Baggiolini M, Dewald B, Moser B: Interleukin-8 and related chemotactic cytokines--CXC and CC chemokines. Adv Immunol. 1994, 55: 97-179. full_text.PubMedView ArticleGoogle Scholar
- Kopydlowski KM, Salkowski CA, Cody MJ, van Rooijen N, Major J, Hamilton TA, Vogel SN: Regulation of macrophage chemokine expression by lipopolysaccharide in vitro and in vivo. J Immunol. 1999, 163 (3): 1537-1544.PubMedGoogle Scholar
- Ohmori Y, Wyner L, Narumi S, Armstrong D, Stoler M, Hamilton TA: Tumor necrosis factor-alpha induces cell type and tissue-specific expression of chemoattractant cytokines in vivo. Am J Pathol. 1993, 142 (3): 861-870.PubMedPubMed CentralGoogle Scholar
- Oppenheim JJ, Zachariae CO, Mukaida N, Matsushima K: Properties of the novel proinflammatory supergene "intercrine" cytokine family. Annu Rev Immunol. 1991, 9: 617-648.PubMedView ArticleGoogle Scholar
- Schall TJ, Bacon KB: Chemokines, leukocyte trafficking, and inflammation. Curr Opin Immunol. 1994, 6 (6): 865-873. 10.1016/0952-7915(94)90006-X.PubMedView ArticleGoogle Scholar
- Tessier PA, Naccache PH, Clark-Lewis I, Gladue RP, Neote KS, McColl SR: Chemokine networks in vivo: involvement of C-X-C and C-C chemokines in neutrophil extravasation in vivo in response to TNF-alpha. J Immunol. 1997, 159 (7): 3595-3602.PubMedGoogle Scholar
- VanOtteren GM, Standiford TJ, Kunkel SL, Danforth JM, Strieter RM: Alterations of ambient oxygen tension modulate the expression of tumor necrosis factor and macrophage inflammatory protein-1 alpha from murine alveolar macrophages. Am J Respir Cell Mol Biol. 1995, 13 (4): 399-409.PubMedView ArticleGoogle Scholar
- Wu AJ, Kurrasch RH, Katz J, Fox PC, Baum BJ, Atkinson JC: Effect of tumor necrosis factor-alpha and interferon-gamma on the growth of a human salivary gland cell line. J Cell Physiol. 1994, 161 (2): 217-226. 10.1002/jcp.1041610205.PubMedView ArticleGoogle Scholar
- Dorner BG, Scheffold A, Rolph MS, Huser MB, Kaufmann SH, Radbruch A, Flesch IE, Kroczek RA: MIP-1alpha, MIP-1beta, RANTES, and ATAC/lymphotactin function together with IFN-gamma as type 1 cytokines. Proc Natl Acad Sci USA. 2002, 99 (9): 6181-6186. 10.1073/pnas.092141999.PubMedPubMed CentralView ArticleGoogle Scholar
- Gong JH, Ratkay LG, Waterfield JD, Clark-Lewis I: An antagonist of monocyte chemoattractant protein 1 (MCP-1) inhibits arthritis in the MRL-lpr mouse model. J Exp Med. 1997, 186 (1): 131-137. 10.1084/jem.186.1.131.PubMedPubMed CentralView ArticleGoogle Scholar
- Gunn MD, Nelken NA, Liao X, Williams LT: Monocyte chemoattractant protein-1 is sufficient for the chemotaxis of monocytes and lymphocytes in transgenic mice but requires an additional stimulus for inflammatory activation. J Immunol. 1997, 158 (1): 376-383.PubMedGoogle Scholar
- Rand ML, Warren JS, Mansour MK, Newman W, Ringler DJ: Inhibition of T cell recruitment and cutaneous delayed-type hypersensitivity-induced inflammation with antibodies to monocyte chemoattractant protein-1. Am J Pathol. 1996, 148 (3): 855-864.PubMedPubMed CentralGoogle Scholar
- Zisman DA, Kunkel SL, Strieter RM, Tsai WC, Bucknell K, Wilkowski J, Standiford TJ: MCP-1 protects mice in lethal endotoxemia. J Clin Invest. 1997, 99 (12): 2832-2836. 10.1172/JCI119475.PubMedPubMed CentralView ArticleGoogle Scholar
- Schindler R, Mancilla J, Endres S, Ghorbani R, Clark SC, Dinarello CA: Correlations and interactions in the production of interleukin-6 (IL-6), IL-1, and tumor necrosis factor (TNF) in human blood mononuclear cells: IL-6 suppresses IL-1 and TNF. Blood. 1990, 75 (1): 40-47.PubMedGoogle Scholar
- Tilg H, Trehu E, Atkins MB, Dinarello CA, Mier JW: Interleukin-6 (IL-6) as an anti-inflammatory cytokine: induction of circulating IL-1 receptor antagonist and soluble tumor necrosis factor receptor p55. Blood. 1994, 83 (1): 113-118.PubMedGoogle Scholar
- Xing Z, Gauldie J, Cox G, Baumann H, Jordana M, Lei XF, Achong MK: IL-6 is an antiinflammatory cytokine required for controlling local or systemic acute inflammatory responses. J Clin Invest. 1998, 101 (2): 311-320. 10.1172/JCI1368.PubMedPubMed CentralView ArticleGoogle Scholar
- Miller MD, Krangel MS: Biology and biochemistry of the chemokines: a family of chemotactic and inflammatory cytokines. Crit Rev Immunol. 1992, 12 (1-2): 17-46.PubMedGoogle Scholar
- Emi M, Asaoka H, Matsumoto A, Itakura H, Kurihara Y, Wada Y, Kanamori H, Yazaki Y, Takahashi E, Lepert M, et al: Structure, organization, and chromosomal mapping of the human macrophage scavenger receptor gene. J Biol Chem. 1993, 268 (3): 2120-2125.PubMedGoogle Scholar
- Wang WW, Jenkinson CP, Griscavage JM, Kern RM, Arabolos NS, Byrns RE, Cederbaum SD, Ignarro LJ: Co-induction of arginase and nitric oxide synthase in murine macrophages activated by lipopolysaccharide. Biochem Biophys Res Commun. 1995, 210 (3): 1009-1016. 10.1006/bbrc.1995.1757.PubMedView ArticleGoogle Scholar
- de Vera ME, Shapiro RA, Nussler AK, Mudgett JS, Simmons RL, Morris SM, Billiar TR, Geller DA: Transcriptional regulation of human inducible nitric oxide synthase (NOS2) gene by cytokines: initial analysis of the human NOS2 promoter. Proc Natl Acad Sci USA. 1996, 93 (3): 1054-1059. 10.1073/pnas.93.3.1054.PubMedPubMed CentralView ArticleGoogle Scholar
- Mock BA, Krall MM, Byrd LG, Chin H, Barton CH, Charles I, Liew FY, Blackwell J: The inducible form of nitric oxide synthase (NOS2) isolated from murine macrophages maps near the nude mutation on mouse chromosome 11. Eur J Immunogenet. 1994, 21 (4): 231-238. 10.1111/j.1744-313X.1994.tb00196.x.PubMedView ArticleGoogle Scholar
- Rossi A, Kapahi P, Natoli G, Takahashi T, Chen Y, Karin M, Santoro MG: Anti-inflammatory cyclopentenone prostaglandins are direct inhibitors of IkappaB kinase. Nature. 2000, 403 (6765): 103-108. 10.1038/47520.PubMedView ArticleGoogle Scholar
- Leibovich SJ, Polverini PJ, Fong TW, Harlow LA, Koch AE: Production of angiogenic activity by human monocytes requires an L-arginine/nitric oxide-synthase-dependent effector mechanism. Proc Natl Acad Sci USA. 1994, 91 (10): 4190-4194. 10.1073/pnas.91.10.4190.PubMedPubMed CentralView ArticleGoogle Scholar
- Xiong M, Elson G, Legarda D, Leibovich SJ: Production of vascular endothelial growth factor by murine macrophages: regulation by hypoxia, lactate, and the inducible nitric oxide synthase pathway. Am J Pathol. 1998, 153 (2): 587-598.PubMedPubMed CentralView ArticleGoogle Scholar
- Corraliza IM, Soler G, Eichmann K, Modolell M: Arginase induction by suppressors of nitric oxide synthesis (IL-4, IL-10 and PGE2) in murine bone-marrow-derived macrophages. Biochem Biophys Res Commun. 1995, 206 (2): 667-673. 10.1006/bbrc.1995.1094.PubMedView ArticleGoogle Scholar
- Hogger P, Dreier J, Droste A, Buck F, Sorg C: Identification of the integral membrane protein RM3/1 on human monocytes as a glucocorticoid-inducible member of the scavenger receptor cysteine-rich family (CD163). J Immunol. 1998, 161 (4): 1883-1890.PubMedGoogle Scholar
- Stein M, Keshav S, Harris N, Gordon S: Interleukin 4 potently enhances murine macrophage mannose receptor activity: a marker of alternative immunologic macrophage activation. J Exp Med. 1992, 176 (1): 287-292. 10.1084/jem.176.1.287.PubMedView ArticleGoogle Scholar
- Bonecchi R, Sozzani S, Stine JT, Luini W, D'Amico G, Allavena P, Chantry D, Mantovani A: Divergent effects of interleukin-4 and interferon-gamma on macrophage-derived chemokine production: an amplification circuit of polarized T helper 2 responses. Blood. 1998, 92 (8): 2668-2671.PubMedGoogle Scholar
- Imai T, Nagira M, Takagi S, Kakizaki M, Nishimura M, Wang J, Gray PW, Matsushima K, Yoshie O: Selective recruitment of CCR4-bearing Th2 cells toward antigen-presenting cells by the CC chemokines thymus and activation-regulated chemokine and macrophage-derived chemokine. Int Immunol. 1999, 11 (1): 81-88. 10.1093/intimm/11.1.81.PubMedView ArticleGoogle Scholar
- Lang R, Kocourek A, Braun M, Tschesche H, Huber R, Bode W, Maskos K: Substrate specificity determinants of human macrophage elastase (MMP-12) based on the 1.1 A crystal structure. J Mol Biol. 2001, 312 (4): 731-742. 10.1006/jmbi.2001.4954.PubMedView ArticleGoogle Scholar
- Liu WH, Chen XM, Fu B: Thrombin stimulates MMP-9 mRNA expression through AP-1 pathway in human mesangial cells. Acta Pharmacol Sin. 2000, 21 (7): 641-645.PubMedGoogle Scholar
- Belaaouaj A, Shipley JM, Kobayashi DK, Zimonjic DB, Popescu N, Silverman GA, Shapiro SD: Human macrophage metalloelastase. Genomic organization, chromosomal location, gene linkage, and tissue-specific expression. J Biol Chem. 1995, 270 (24): 14568-14575. 10.1074/jbc.270.24.14568.PubMedView ArticleGoogle Scholar
- Xie S, Issa R, Sukkar MB, Oltmanns U, Bhavsar PK, Papi A, Caramori G, Adcock I, Chung KF: Induction and regulation of matrix metalloproteinase-12 in human airway smooth muscle cells. Respir Res. 2005, 6: 148-10.1186/1465-9921-6-148.PubMedPubMed CentralView ArticleGoogle Scholar
- Qu P, Du H, Wang X, Yan C: Matrix metalloproteinase 12 overexpression in lung epithelial cells plays a key role in emphysema to lung bronchioalveolar adenocarcinoma transition. Cancer Res. 2009, 69 (18): 7252-7261. 10.1158/0008-5472.CAN-09-0577.PubMedPubMed CentralView ArticleGoogle Scholar
- Shukla A, Barrett TF, Nakayama KI, Nakayama K, Mossman BT, Lounsbury KM: Transcriptional up-regulation of MMP12 and MMP13 by asbestos occurs via a PKCdelta-dependent pathway in murine lung. Faseb J. 2006, 20 (7): 997-999. 10.1096/fj.05-4554fje.PubMedView ArticleGoogle Scholar
- Kristiansen M, Graversen JH, Jacobsen C, Sonne O, Hoffman HJ, Law SK, Moestrup SK: Identification of the haemoglobin scavenger receptor. Nature. 2001, 409 (6817): 198-201. 10.1038/35051594.PubMedView ArticleGoogle Scholar
- Gabay C, Porter B, Guenette D, Billir B, Arend WP: Interleukin-4 (IL-4) and IL-13 enhance the effect of IL-1beta on production of IL-1 receptor antagonist by human primary hepatocytes and hepatoma HepG2 cells: differential effect on C-reactive protein production. Blood. 1999, 93 (4): 1299-1307.PubMedGoogle Scholar
- Mantovani A, Locati M, Vecchi A, Sozzani S, Allavena P: Decoy receptors: a strategy to regulate inflammatory cytokines and chemokines. Trends Immunol. 2001, 22 (6): 328-336. 10.1016/S1471-4906(01)01941-X.PubMedView ArticleGoogle Scholar
- Peiser L, Mukhopadhyay S, Gordon S: Scavenger receptors in innate immunity. Curr Opin Immunol. 2002, 14 (1): 123-128. 10.1016/S0952-7915(01)00307-7.PubMedView ArticleGoogle Scholar
- Fernandes C, Paya-Cano JL, Sluyter F, D'Souza U, Plomin R, Schalkwyk LC: Hippocampal gene expression profiling across eight mouse inbred strains: towards understanding the molecular basis for behaviour. Eur J Neurosci. 2004, 19 (9): 2576-2582. 10.1111/j.0953-816X.2004.03358.x.PubMedView ArticleGoogle Scholar
- Korostynski M, Kaminska-Chowaniec D, Piechota M, Przewlocki R: Gene expression profiling in the striatum of inbred mouse strains with distinct opioid-related phenotypes. BMC Genomics. 2006, 7: 146-10.1186/1471-2164-7-146.PubMedPubMed CentralView ArticleGoogle Scholar
- Pavlidis P, Noble WS: Analysis of strain and regional variation in gene expression in mouse brain. Genome Biol. 2001, 2 (10): RESEARCH0042-10.1186/gb-2001-2-10-research0042.PubMedPubMed CentralView ArticleGoogle Scholar
- Sandberg R, Yasuda R, Pankratz DG, Carter TA, Del Rio JA, Wodicka L, Mayford M, Lockhart DJ, Barlow C: Regional and strain-specific gene expression mapping in the adult mouse brain. Proc Natl Acad Sci USA. 2000, 97 (20): 11038-11043. 10.1073/pnas.97.20.11038.PubMedPubMed CentralView ArticleGoogle Scholar
- Bianchi-Frias D, Pritchard C, Mecham BH, Coleman IM, Nelson PS: Genetic background influences murine prostate gene expression: implications for cancer phenotypes. Genome Biol. 2007, 8 (6): R117-10.1186/gb-2007-8-6-r117.PubMedPubMed CentralView ArticleGoogle Scholar
- Burne MJ, Haq M, Matsuse H, Mohapatra S, Rabb H: Genetic susceptibility to renal ischemia reperfusion injury revealed in a murine model. Transplantation. 2000, 69 (5): 1023-1025. 10.1097/00007890-200003150-00065.PubMedView ArticleGoogle Scholar
- Rosas LE, Keiser T, Barbi J, Satoskar AA, Septer A, Kaczmarek J, Lezama-Davila CM, Satoskar AR: Genetic background influences immune responses and disease outcome of cutaneous L. mexicana infection in mice. Int Immunol. 2005, 17 (10): 1347-1357. 10.1093/intimm/dxh313.PubMedView ArticleGoogle Scholar
- Scott MJ, Hoth JJ, Gardner SA, Peyton JC, Cheadle WG: Genetic background influences natural killer cell activation during bacterial peritonitis in mice, and is interleukin 12 and interleukin 18 independent. Cytokine. 2004, 28 (3): 124-136. 10.1016/j.cyto.2004.07.006.PubMedView ArticleGoogle Scholar
- Sun Y, Quinn B, Witte DP, Grabowski GA: Gaucher disease mouse models: point mutations at the acid beta-glucosidase locus combined with low-level prosaposin expression lead to disease variants. J Lipid Res. 2005, 46 (10): 2102-2113. 10.1194/jlr.M500202-JLR200.PubMedView ArticleGoogle Scholar
- Irizarry RA, Bolstad BM, Collin F, Cope LM, Hobbs B, Speed TP: Summaries of Affymetrix GeneChip probe level data. Nucleic Acids Res. 2003, 31 (4): e15-10.1093/nar/gng015.PubMedPubMed CentralView ArticleGoogle Scholar
- Benjamini Y, Drai D, Elmer G, Kafkafi N, Golani I: Controlling the false discovery rate in behavior genetics research. Behav Brain Res. 2001, 125 (1-2): 279-284. 10.1016/S0166-4328(01)00297-2.PubMedView ArticleGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.