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PubMed2005

Influence of ESAT-6 secretion system 1 (RD1) of Mycobacterium tuberculosis on the interaction between mycobacteria and the host immune system.

The chromosomal locus encoding the early secreted antigenic target, 6 kDa (ESAT-6) secretion system 1 of Mycobacterium tuberculosis, also referred to as "region of difference 1 (RD1)," is absent from Mycobacterium bovis bacillus Calmette-Guerin (BCG). In this study, using low-dose aerosol infection in mice, we demonstrate that BCG complemented with RD1 (BCG::RD1) displays markedly increased virulence which albeit does not attain that of M. tuberculosis H37Rv. Nevertheless, phenotypic and functional analyses of immune cells at the site of infection show that the capacity of BCG::RD1 to initiate recruitment/activation of immune cells is comparable to that of fully virulent H37Rv. Indeed, in contrast to the parental BCG, BCG::RD1 mimics H37Rv and induces substantial influx of activated (CD44highCD45RB(-)CD62L(-)) or effector (CD45RB(-)CD27(-)) T cells and of activated CD11c(+)CD11bhigh cells to the lungs of aerosol-infected mice. For the first time, using in vivo analysis of transcriptome of inflammatory cytokines and chemokines of lung interstitial CD11c+ cells, we show that in a low-dose aerosol infection model, BCG::RD1 triggered an activation/inflammation program comparable to that induced by H37Rv while parental BCG, due to its overattenuation, did not initiate the activation program in lung interstitial CD11c+ cells. Thus, products encoded by the ESAT-6 secretion system 1 of M. tuberculosis profoundly modify the interaction between mycobacteria and the host innate and adaptive immune system. These modifications can explain the previously described improved protective capacity of BCG::RD1 vaccine candidate against M. tuberculosis challenge.

Animals↗

PubMed2003

The antigen processing machinery of class I human leukocyte antigens: linked patterns of gene expression in neoplastic cells.

The ultimate outcome of an immune response (escape or surveillance) depends on a delicate balance of opposing signals delivered by activating and inhibitory immune receptors expressed by cytotoxic T lymphocytes and natural killer cells. In this light, loss and down-regulation of human leukocyte antigens (HLA) class I molecules, while important for keeping tumors below the T-cell detection levels, may incite recognition of missing self. Conversely, the maintenance of normal levels of expression (or even up-regulation) may be favorable to tumors, at least in certain cases. In this study, we took advantage of a previously characterized panel of 15 early passage tumor cell lines (mainly from melanoma and lung carcinoma lesions) enriched with class I-low phenotypes. These cells were systematically characterized by Northern and/or Western blotting (e.g., mini-transcriptome/mini-proteome analysis) for the expression of HLA-A, -B, -C, beta(2)-microglobulin, and the members of the "antigen processing machinery" of class I molecules (LMP2, LMP7, TAP1, TAP2, tapasin, calreticulin, calnexin, and ERp57). In addition, we established four pairs of cultures, each comprising melanoma cells and normal melanocytes from the same patient. We found that approximately 97% of the 185 tested gene products are expressed (although often weakly), and in many cases coordinately regulated in 18 of 19 tumor cell lines. Linked expression patterns could be hierarchically arranged by statistical methods and graphically described as a class I HLA "coordinome." Deviations (both down- and up-regulation) from the coordinome expression pattern inherited from the normal, paired melanocyte counterpart, were allowed but limited in magnitude, as if melanoma cells were trying to keep a "low profile" HLA phenotype. We conclude that irreversible HLA loss is a rare event, and class I expression in tumor cells almost invariably results from reversible gene regulatory (rather than gene disruption) events.

Antigens, Neoplasm↗

PubMed2004

[Expression profile of immune associated genes in nasal polyps].

OBJECTIVE: To investigate the expression profile of immune associated genes in nasal polyps by gene chip technology and to probe into the role of correlative genes in the immune pathogenesis of nasal polyps. METHODS: Microarray analysis was used to find the expressing profile of 491 immune associated genes in nasal polyps. The total RNAs were respectively extracted from four samples of nasal polyps and inferior turbinates, and then were reversely transcribed to cDNAs with incorporation of fluorescent dUTP as the hybridization probes. The mixed probes were then hybridized with two pieces of immune associated gene chip. It was scanned by laser scanner and the acquired image was analyzed by software. RESULTS: Eighty-seven genes were differently expressed in immune associated gene profile of nasal polyps, among which 45 genes were upregulated and 42 genes were down regulated. Fifteen genes were shown differential expression in both chips with 5 upregulated genes and 10 downregulated genes. The differentially expressed genes mostly involved in cytokines and their receptors, chemokines and their receptors, adhesion molecules, leukocytes differential antigens, immune signal transduction molecules, and still included some genes about complements and their receptors, immune transcription regulatory molecules, innate immune molecules and neural immune molecules. CONCLUSIONS: The differently expressed genes in immune associated gene chips will provide clues and theoretical foundation for the pathogenesis of nasal polyps. Furthermore IL-17 may have an important role in the occurrence of nasal polyps, and the role of innate immunity and immune signal transduction molecules in the pathogenesis of nasal polyps need further researches.

Adult↗

PubMed2006

Challenges in the stratification of breast tumors for tailored therapies.

Studying the molecular stratification of breast carcinoma is a real challenge considering the extreme heterogeneity of these tumors. Many patients are now treated following recommendation established at several NIH and St Gallen consensus conferences. However a significant fraction of these breast cancer patients do not need adjuvant chemotherapies while other patients receive inefficacious therapies. High density gene expression arrays have been designed to attempt to establish expression profiles that could be used as prognostic indicators or as predictive markers for response to treatment. This review is intended to discuss the potential value of these new indicators, but also the current weaknesses of these new genomic and bioinformatic approaches. The combined analysis of transcriptomic and genomic alteration data from relatively large numbers of well annotated tumor specimens may offer an opportunity to overcome the current difficulties in validating recently published non overlapping gene lists as prognostic or therapeutic indicators. There is also hope for identifying and deciphering signal transduction pathways driving tumor progression with newly developed algorithms and semi quantitative parameters obtained in simplified in vitro or in vivo models for specific transduction pathways.

Animals↗

PubMed2007

A meta-analysis of human embryonic stem cells transcriptome integrated into a web-based expression atlas.

Microarray technology provides a unique opportunity to examine gene expression patterns in human embryonic stem cells (hESCs). We performed a meta-analysis of 38 original studies reporting on the transcriptome of hESCs. We determined that 1,076 genes were found to be overexpressed in hESCs by at least three studies when compared to differentiated cell types, thus composing a "consensus hESC gene list." Only one gene was reported by all studies: the homeodomain transcription factor POU5F1/OCT3/4. The list comprised other genes critical for pluripotency such as the transcription factors NANOG and SOX2, and the growth factors TDGF1/CRIPTO and Galanin. We show that CD24 and SEMA6A, two cell surface protein-coding genes from the top of the consensus hESC gene list, display a strong and specific membrane protein expression on hESCs. Moreover, CD24 labeling permits the purification by flow cytometry of hESCs cocultured on human fibroblasts. The consensus hESC gene list also included the FZD7 WNT receptor, the G protein-coupled receptor GPR19, and the HELLS helicase, which could play an important role in hESCs biology. Conversely, we identified 783 genes downregulated in hESCs and reported in at least three studies. This "consensus differentiation gene list" included the IL6ST/GP130 LIF receptor. We created an online hESC expression atlas, http://amazonia.montp.inserm.fr, to provide an easy access to this public transcriptome dataset. Expression histograms comparing hESCs to a broad collection of fetal and adult tissues can be retrieved with this web tool for more than 15,000 genes.

Cell Differentiation↗

PubMed2003

Granular gland transcriptomes in stimulated amphibian skin secretions.

Amphibian defensive skin secretions are complex, species-specific cocktails of biologically active molecules, including many uncharacterized peptides. The study of such secretions for novel peptide discovery is time-limited, as amphibians are in rapid global decline. While secretion proteome analysis is non-lethal, transcriptome analysis has until now required killing of specimens prior to skin dissection for cDNA library construction. Here we present the discovery that polyadenylated mRNAs encoding dermal granular gland peptides are present in defensive skin secretions, stabilized by endogenous nucleic acid-binding amphipathic peptides. Thus parallel secretory proteome and transcriptome analyses can be performed without killing the specimen in this model amphibian system--a finding that has important implications in conservation of biodiversity within this threatened vertebrate taxon and whose mechanistics may have broader implications in biomolecular science.

Alternative Splicing↗

PubMed2026

High-throughput single-cell proteomics and transcriptomics from same cells with a nanoliter-scale, spin-transfer approach.

Single-cell multiomic platforms provide a comprehensive snapshot of cellular states and cell types by offering critical insights into the spatiotemporal regulation of biomolecular networks at a systems level, thereby defining the basis of multicellularity. Here, we introduce nanoSPINS, an advanced platform that enables high-throughput profiling and integrative analysis of the transcriptome and proteome from the same single cells using RNA sequencing and isobaric labeling LC-MS-based proteomics, respectively. NanoSPINS can efficiently transfer mRNA-containing droplets across two microarrays via a centrifugation-based approach, while proteins are retained on the initial platform. Benchmarking of nanoSPINS on two cell lines demonstrates its ability to generate global proteomic and transcriptomic profiles that align well with previously established methodologies/platforms. The incorporation of isobaric TMTpro labeling into this single-cell multiomics platform significantly enhances the throughput of single-cell proteomic analyses. Through the high-throughput quantification of the proteome and transcriptome, nanoSPINS not only facilitates the identification of molecular features at both mRNA and protein level but also provides larger sample sizes for improved statistical power in clustering and differential abundance. Given the broad applicability of single-cell multiomics in biological research and clinical settings, we believe nanoSPINS represents a powerful platform for the characterization of heterogeneous cell populations.

Single-Cell Analysis↗

PubMed2025

A genome-wide association study identifies a novel East Asian-specific locus for dementia with Lewy bodies in Japanese subjects.

BACKGROUND: Dementia with Lewy bodies (DLB) is the second most common type of degenerative dementia in older patients. As with other multifactorial diseases, the pathogenesis results from interactions of environmental and genetic factors. The genetic basis of DLB is not yet fully understood. Recent genomic analyses of DLB in Caucasian cohorts identified genetic susceptibility loci for DLB, but the comprehensive genomic analysis in Asians was still not performed. METHODS: We conducted a genome-wide association study (GWAS) in Japanese subjects (211 DLB cases and 6113 controls) to clarify the genetic architecture of DLB pathogenesis. RESULTS: We identified the East Asian-specific DHTKD1 locus (rs138587229) on chromosome 10 with genome-wide significance (GWS; P = 3.2710-8) and the ICOS/PARD3B locus on chromosome 2 with suggestive significance (P = 3.9510-7) as novel DLB genetic risk loci. We also confirmed the APOE locus (rs429358, P < 5.0 × 10-8), a known risk locus for DLB and Alzheimer's disease in Caucasians. The DHTKD1 locus was associated with the gene expression of SEC61A2 and showed a causal relationship with cholinesterase levels. In a trans-ethnic meta-analysis that included Japanese, UK Biobank, and other Caucasian GWAS, we confirmed the risk for DLB at APOE and SNCA loci with GWS. Transcriptome-wide association analysis identified ZNF155 and ZNF284 in the brain cortex and GPRIN3 in the substantia nigra as putative causal genes for DLB. CONCLUSIONS: This is the first GWAS for DLB in East Asians, and our findings provide new biological and clinical insights into the pathogenesis of DLB.

Aged↗

PubMed2002

Genomics and plant cells: application of genomics strategies to Arabidopsis cell biology.

In this review I seek to describe how the complete catalogue of plant genes and proteins, revealed by genome sequencing, can provide novel insights into cell biology. Many new analytical methods have been developed to digest the flood of genome sequence data, including analysis of the transcriptome, proteome and metabolites. High-throughput analysis of protein targeting and other methods will ascribe new information to proteins and create important links with other large datasets. To fulfil the potential revealed by this genomic information, many challenges have to be met. Among these are organizational changes needed to create common datasets accessible to all scientists, and bioinformatics solutions to capture and integrate diverse datasets. Once harnessed, these new strategies will irrevocably change the way we conduct plant science.

Arabidopsis↗

PubMed2026

Machine learning-integrated multi-omics risk prediction for pulmonary fungal infection in COPD and lung cancer: a transcriptomic and immune profiling study.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) and lung cancer are major risk factors for invasive pulmonary fungal infection (IPFI), carrying an attributable mortality of 30%-80%. Their coexistence further amplifies immunosuppression, while current diagnostic criteria remain inadequate for early risk identification. METHODS: Transcriptomic data from the GEO dataset GSE296912 (scRNA-seq; 12,078 cells from normal and COPD lung tissue) and The Cancer Genome Atlas (TCGA)-lung adenocarcinoma (LUAD) bulk RNA-seq cohort (539 tumor and 59 normal samples) underwent differential expression and cross-omics integration analysis. Five machine learning models were constructed: logistic regression, SVM, random forest, XGBoost, and LASSO. Candidate genes were validated by qRT-PCR in A549 cells and THP-1-derived macrophages stimulated with heat-inactivated Aspergillus fumigatus conidia, a protocol selected to ensure BSL-2 biosafety compliance and isolate PAMP-mediated innate immune signaling. Model performance was evaluated using 5-fold stratified cross-validation with AUC, calibration curves, and decision curve analysis. RESULTS: Single-cell transcriptomic analysis of 12,078 cells identified 14 distinct cell populations, with marked myeloid expansion and immune dysregulation in COPD lung tissue. Cross-omics integration with TCGA-LUAD data identified 1,145 shared genes (79 immune-related), converging on NF-κB, TLR4, and cytokine receptor signaling. The random forest model achieved excellent discriminative performance (5-fold CV AUC = 0.988), with Treg infiltration, TLR4, and MMP9 as the top predictors. qRT-PCR confirmed significant upregulation of all five candidate genes (DEFB4A, S100A8, IL-8, MMP9, and TLR4) in both A549 and THP-1 cells following fungal stimulation. CONCLUSION: This multi-omics machine learning model integrating scRNA-seq and TCGA transcriptomic data demonstrates excellent discriminative performance (AUC = 0.988), with mechanistic convergence of NF-κB, TLR4, and oncogenic signaling pathways identified across shared immune gene signatures. In vitro qRT-PCR validation confirms the biological relevance of five key antifungal immune genes, providing a transcriptomic foundation for future prospective IPFI risk stratification in patients with COPD and lung cancer.

TLR4↗

PubMed2004

Metabolic pathway analysis of yeast strengthens the bridge between transcriptomics and metabolic networks.

Central carbon metabolism of the yeast Saccharomyces cerevisiae was analyzed using metabolic pathway analysis tools. Elementary flux modes for three substrates (glucose, galactose, and ethanol) were determined using the catabolic reactions occurring in yeast. Resultant elementary modes were used for gene deletion phenotype analysis and for the analysis of robustness of the central metabolism and network functionality. Control-effective fluxes, determined by calculating the efficiency of each mode, were used for the prediction of transcript ratios of metabolic genes in different growth media (glucose-ethanol and galactose-ethanol). A high correlation was obtained between the theoretical and experimental expression levels of 38 genes when ethanol and glucose media were considered. Such analysis was shown to be a bridge between transcriptomics and fluxomics. Control-effective flux distribution was found to be promising in in silico predictions by incorporating functionality and regulation into the metabolic network structure.

Biomass↗

PubMed2025

Longitudinal Multi-Organ Transcriptomic Atlas of Salt-Induced Hypertension.

BACKGROUND: Salt-sensitive hypertension is a prevalent and clinically significant subtype of hypertension, where increased dietary salt intake elevates blood pressure and causes injury to multiple organ systems. Despite extensive research, dynamic molecular changes and conserved versus organ-specific transcriptional programs in hypertensive multi-organ damage remain poorly understood. Defining complex molecular pathways both in a temporal sequence and in an organ-specific manner is essential for developing targeted, precision therapies to mitigate hypertensive disease burden. METHODS: We generated a longitudinal multi-organ transcriptomic atlas of salt-sensitive hypertension using RNA sequencing of kidney cortex, kidney medulla, heart, and liver from Dahl salt-sensitive rats across four disease stages. A comprehensive bioinformatic analysis mapped dynamic transcriptional programs, evaluated 50 biological pathways, and defined upstream regulators. Histological and biochemical assays complemented transcriptomic analysis, while integration with human genome-wide association studies (GWAS) and compound-transcriptome analysis provided translational insights and identified candidate therapeutics. RESULTS: Salt-induced hypertension elicited both shared and tissue-specific transcriptional programs that evolved with disease progression. The kidney medulla showed robust early immune activation with metabolic suppression, while the cortex exhibited transient metabolic activation before declining and initiating immune activation. The liver and heart showed time-dependent metabolic and inflammatory remodeling. Cross-organ comparisons revealed a shared early proliferative response that converged on proinflammatory and fibrotic signatures. Upstream regulator analysis identified 79 time- and tissue-specific transcription factors associated with gene expression dynamics. GWAS integration analysis revealed endocrine signaling, ion transport, lipid metabolism, and detoxification as conserved pathways across species, underscoring the translational relevance of the model and study. Predictive compound-transcriptome analyses identified kinase inhibitors targeting phosphoinositide 3-kinase, mechanistic target of rapamycin and cyclin-dependent kinases as top candidates to counteract maladaptive transcriptional programs. CONCLUSIONS: This study defines temporal and tissue-specific transcriptomic remodeling in salt-sensitive hypertension and highlights the need for precision interventions to prevent progressive organ damage.

Journal Article↗

PubMed2006

Integrative investigation of metabolic and transcriptomic data.

BACKGROUND: New analysis methods are being developed to integrate data from transcriptome, proteome, interactome, metabolome, and other investigative approaches. At the same time, existing methods are being modified to serve the objectives of systems biology and permit the interpretation of the huge datasets currently being generated by high-throughput methods. RESULTS: Transcriptomic and metabolic data from chemostat fermentors were collected with the aim of investigating the relationship between these two data sets. The variation in transcriptome data in response to three physiological or genetic perturbations (medium composition, growth rate, and specific gene deletions) was investigated using linear modelling, and open reading-frames (ORFs) whose expression changed significantly in response to these perturbations were identified. Assuming that the metabolic profile is a function of the transcriptome profile, expression levels of the different ORFs were used to model the metabolic variables via Partial Least Squares (Projection to Latent Structures--PLS) using PLS toolbox in Matlab. CONCLUSION: The experimental design allowed the analyses to discriminate between the effects which the growth medium, dilution rate, and the deletion of specific genes had on the transcriptome and metabolite profiles. Metabolite data were modelled as a function of the transcriptome to determine their congruence. The genes that are involved in central carbon metabolism of yeast cells were found to be the ORFs with the most significant contribution to the model.

Algorithms↗

PubMed2005

Longitudinal analysis of the group A Streptococcus transcriptome in experimental pharyngitis in cynomolgus macaques.

Identification of the genetic events that contribute to host-pathogen interactions is important for understanding the natural history of infectious diseases and developing therapeutics. Transcriptome studies conducted on pathogens have been central to this goal in recent years. However, most of these investigations have focused on specific end points or disease phases, rather than analysis of the entire time course of infection. To gain a more complete understanding of how bacterial gene expression changes over time in a primate host, the transcriptome of group A Streptococcus (GAS) was analyzed during an 86-day infection protocol in 20 cynomolgus macaques with experimental pharyngitis. The study used 260 custom Affymetrix (Santa Clara, CA) chips, and data were confirmed by TaqMan analysis. Colonization, acute, and asymptomatic phases of disease were identified. Successful colonization and severe inflammation were significantly correlated with an early onset of superantigen gene expression. The differential expression of two-component regulators covR and spy0680 (M1_spy0874) was significantly associated with GAS colony-forming units, inflammation, and phases of disease. Prophage virulence gene expression and prophage induction occurred predominantly during high pathogen cell densities and acute inflammation. We discovered that temporal changes in the GAS transcriptome were integrally linked to the phase of clinical disease and host-defense response. Knowledge of the gene expression patterns characterizing each phase of pathogen-host interaction provides avenues for targeted investigation of proven and putative virulence factors and genes of unknown function and will assist vaccine research.

Animals↗

PubMed2001

Human mast cell transcriptome project.

After draft reading of the human genome sequence, systemic analysis of the transcriptome (the whole transcripts present in a cell) is progressing especially in commonly available cell types. Until recently, human mast cells were not commonly available. We have succeeded to generate a substantial number of human mast cells from umbilical cord blood and from adult peripheral blood progenitors. Then, we have examined messenger RNA selectively transcribed in these mast cells using high-density oligonucleotide probe arrays. Many unexpected but important transcripts were selectively expressed in human mast cells. We discuss the results obtained from transcriptome screening by introducing our data regarding mast-cell-specific genes.

Blood Cells↗

PubMed2004

Analysis of mouse germ-cell transcriptome at different stages of spermatogenesis by SAGE: biological significance.

The transcriptomes of mouse type A spermatogonia (Spga), pachytene spermatocytes (Spcy), and round spermatids (Sptd) were determined by sequencing the respective SAGE (Serial Analysis of Gene Expression) libraries. A total of 444,015 tags derived from one Spga, two Spcy, and one Sptd library were analyzed, and 34,619 different species of transcripts were identified, 5279 of which were novel. Results indicated the germ-cell transcriptome comprises of more than 30,000 transcripts. Virtual subtraction showed that cell-specific transcripts constitute 12-19.5% of the transcriptome. Components of the protein biosynthetic machinery are highly expressed in Spga. In Spcy transcription factors are abundantly expressed while transcripts encoding proteins involved in chromosome remodeling and testis-specific transcripts are prominent in Sptd. The databases generated by this work provide very useful resources for cellular localization of genes in silico. They are also extremely useful as sources for identification of splice variants of genes in germ cells.

Animals↗

PubMed2026

Transcriptomics reveals species-specific adaptive strategies to calorie restriction in two Argopecten scallops with distinct lifespans.

Calorie restriction (CR) is a well-established non-genetic intervention for lifespan extension in multiple model organisms. Seasonal food shortage in cold and temperate seas may mimic CR, inducing in bivalves a response similar to that in vertebrates and thereby prolonging life expectancy. However, the relationship and the mechanism underlying the food availability and lifespan in bivalves remain largely unexplored. Two closely related scallop species the short-lived warm-water Argopecten irradians (lifespan <2 years) and the longer-lived cold-water Argopecten purpuratus (7-10 years) provide an ideal comparative system to investigate species-specific adaptive strategies. In this study, we subjected both species to CR for 30 and 56 days and performed comparative transcriptomic profiling, weighted gene co-expression network analysis (WGCNA), and physiological assays to elucidate their distinct molecular responses. Transcriptomic analysis revealed that A. purpuratus exhibited substantially more DEGs than A. irradians at both time points under CR, with both species showing downregulation of metabolic pathways but to different extents. A. irradians mounted an early nutrient-sensing response at 30 days (IGF1R, PIK3R3, INSR suppression), indicating acute sensitivity to limitation; by contrast, A. purpuratus displayed delayed FoxO activation at 56 days, along with its downstream effectors NFKBIA, CREB3L4, and SMAD4, suggesting a gradual adaptive program may link to its extended lifespan. WGCNA identified three negatively correlated modules in each species, with coral2 being the most prominent in A. irradians and darkolivegreen in A. purpuratus. The former was dominated by ciliary motility genes, whereas the latter featured coordinated repression of oxidative phosphorylation. Additionally, both species exhibited conserved suppression of mTOR/S6K growth signaling and activation of cellular maintenance programs. Collectively, these findings expand the understanding of CR-mediated longevity regulation in bivalves and provide candidate gene resources for future functional studies and breeding programs.

Pectinidae↗

PubMed2004

Quantitative analysis of the cardiac fibroblast transcriptome-implications for NO/cGMP signaling.

Cardiac fibroblasts regulate tissue repair and remodeling in the heart. To quantify transcript levels in these cells we performed a comprehensive gene expression study using serial analysis of gene expression (SAGE). Among 110,169 sequenced tags we could identify 30,507 unique transcripts. A comparison of SAGE data from cardiac fibroblasts with data derived from total mouse heart revealed a number of fibroblast-specific genes. Cardiac fibroblasts expressed a specific collection of collagens, matrix proteins and metalloproteinases, growth factors, and components of signaling pathways. The NO/cGMP signaling pathway was represented by the mRNAs for alpha(1) and beta(1) subunits of guanylyl cyclase, cGMP-dependent protein kinase type I (cGK I), and, interestingly, the G-kinase-anchoring protein GKAP42. The expression of cGK I was verified by RT-PCR and Western blot. To establish a functional role for cGK I in cardiac fibroblasts we studied its effect on cell proliferation. Selective activation of cGK I with a cGMP analog inhibited the proliferation of serum-stimulated cardiac fibroblasts, which express cGK I, but not higher passage fibroblasts, which contain no detectable cGK I. Currently, our data suggest that cGK I mediates the inhibitory effects of the NO/cGMP pathway on cardiac fibroblast growth. Furthermore the SAGE library of transcripts expressed in cardiac fibroblasts provides a basis for future investigations into the pathological regulatory mechanisms underlying cardiac fibrosis.

Adaptor Proteins, Signal Transducing↗