Unknown,Transcriptomics,Genomics,Proteomics

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Host lung gene expression patterns predict the etiology of infectious pneumonias

ABSTRACT: Rationale: Lower respiratory tract infections continue to exact unacceptable worldwide mortality, often because the infecting pathogen cannot be identified. The respiratory epithelia provide protection from pneumonias through organism-specific generation of antimicrobial products, offering potential insight into the identity of infecting pathogens. Objective: This study assesses the capacity of the host gene expression response to infection to predict lower respiratory pathogens without reliance on culture data. Methods: Mice were inhalationally challenged with S. pneumoniae, P. aeruginosa, A. fumigatus or PBS prior to whole genome gene expression microarray analysis of their pulmonary parenchyma. Characteristic gene expression patterns for each condition were identified, allowing the derivation of prediction rules for each pathogen. After confirming the predictive capacity of gene expression data in blinded challenges, a computerized algorithm was devised to predict the infectious conditions of subsequent subjects. Measurements and Main Results: We observed robust, pathogen-specific gene expression patterns as early as 2 h after infection. We were able to develop a predictive model that used a limited number of specifically regulated transcripts to discriminate perfectly among infecting pathogens in the training data. Validation trials using an algorithmic decision tree revealed 94.4% diagnostic accuracy when discerning the presence of bacterial infection. The model subsequently differentiated between bacterial pathogens with 71.4% accuracy and between non-bacterial conditions with 70.0% accuracy, both far exceeding the expected diagnostic yield of standard culture-based bronchoscopy with bronchoalveolar lavage. Conclusions: These data substantiate the specificity of the pulmonary innate immune response and support the feasibility of a gene expression-based clinical tool for pneumonia diagnosis. Keywords: pathogen- and time-dependent host lung gene expression changes in pneumonia Mouse lungs were removed 6 h after challenge with P. aeruginosa, S. pneumoniae, A. fumigatus or sham (PBS), RNA was collected from leukoreduced lung homogenates, then cRNA was amplified and hybridized to Illumina Sentrix mouse-6 gene expression arrays v1.1. Gene expression data was analyzed to determine if there were distinct patterns of host trasnscription that corresponded with a specific infection.

ORGANISM(S): Mus musculus

SUBMITTER: Scott Evans

PROVIDER: E-GEOD-15869 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Rationale: Lower respiratory tract infections continue to exact unacceptable worldwide mortality, often because the infecting pathogen cannot be identified. The respiratory epithelia provide protection from pneumonias through organism-specific generation of antimicrobial products, offering potential insight into the identity of infecting pathogens. Objective: This study assesses the capacity of the host gene expression response to infection to predict lower respiratory pathogens without reliance on culture data. Methods: Mice were inhalationally challenged with S. pneumoniae, P. aeruginosa, A. fumigatus or PBS prior to whole genome gene expression microarray analysis of their pulmonary parenchyma. Characteristic gene expression patterns for each condition were identified, allowing the derivation of prediction rules for each pathogen. After confirming the predictive capacity of gene expression data in blinded challenges, a computerized algorithm was devised to predict the infectious conditions of subsequent subjects. Measurements and Main Results: We observed robust, pathogen-specific gene expression patterns as early as 2 h after infection. We were able to develop a predictive model that used a limited number of specifically regulated transcripts to discriminate perfectly among infecting pathogens in the training data. Validation trials using an algorithmic decision tree revealed 94.4% diagnostic accuracy when discerning the presence of bacterial infection. The model subsequently differentiated between bacterial pathogens with 71.4% accuracy and between non-bacterial conditions with 70.0% accuracy, both far exceeding the expected diagnostic yield of standard culture-based bronchoscopy with bronchoalveolar lavage. Conclusions: These data substantiate the specificity of the pulmonary innate immune response and support the feasibility of a gene expression-based clinical tool for pneumonia diagnosis. Keywords: pathogen- and time-dependent host lung gene expression changes in pneumonia

Project description:Pulmonary hypertension (PH) and cancer pathophysiology share common signal transduction pathways leading to abnormal endothelial and smooth muscle cell interactions and angioproliferative vasculopathy. Sorafenib (Sor) a drug in clinical trials for cancer treatment, is an inhibitor of multiple kinases important in angiogenesis (Raf-1 kinase, VEGFR-2, VEGFR-3, PDGFR-ï¢)ï©. In this study, we assessed the efficacy of Sor as a potential therapy for PH, and hypothesized that Sor prevents the development of both a conventional and an augmented rodent model of PH. We performed studies in Dahl Salt-Sensitive rats (SS) exposed to hypoxia alone and in combination with the VEGFR-2 inhibitor, SU5416, known to induce a well-characterized augmented PH phenotype. Rats were, thus, divided into 5 groups: normoxia/vehicle (Norm), hypoxia/vehicle (H), hypoxia/ SU5416 (H-SU), hypoxia/Sorafenib (H-Sor) and hypoxia/ SU5416/ Sorafenib (H-SU-Sor). Except for the Norm group, all rats were maintained in a hypoxia chamber with a FiO2 of 10%. Rats received a single injection of SU5416 on Day 1 (20 mg/kg) and Sor solution was administered daily by gavage (2.5mg/kg). After 3.5 weeks, all rats were assessed by open chest catheterizations for pulmonary vascular and right ventricular pressures. Lung and heart tissue were harvested for histological and microarray analyses. Our results showed H-SU rats developed severe PH with changes in hemodynamic and histologic parameters when compared to Norm controls while rats exposed to H alone only displayed mildly elevated pressures compared with Norm. There was no significant change in pressures in the H-Sor or H-SU-Sor compared to Norm. Histopathology demonstrated a dramatic prevention of the PH phenotype in the H-SU-Sor rats with no significant remodeling compared with H-SU rats. Expression profiling data from H (n=4) and H-SU (n=3) rat lungs were compared to Norm (n=4) using normalization in R and SAM (Î´>.639,) (minimum fold change >1.4). With false discovery rates (FDR) of 6.5% in hypoxia and 1.6% in H-SU, 1019 and 465 genes, respectively, were differentially-regulated compared to Norm. In addition, 38 genes were differentially expressed between H-SU and H-SU-Sor (n=4, FDR 6.7%) revealing a molecular signature with potentially novel target genes of Sor. Five differentially expressed genes (Tgfï¢3, C1qg, Nexn, Frzb, and Plaur) were examined by real-time RT-PCR and three were further validated by immunohistochemistry confirming the regulation on protein level. Based on the known pathways of hypoxic-induced PH and Sor, we further utilized immunohistochemistry to show the up-regulation of mediators of the MAPK cascade in the H and H-SU models of PH with subsequent, down-regulation by Sor. We therefore present Sor as a novel treatment for the development of severe PH and theorize that the MAPK cascade is a canonical pathway involved both in the development of PH and in the attenuation by Sor. This SuperSeries is composed of the following subset Series:; GSE8078: A Multi- Kinase Inhibitor Modulates Pulmonary Hypertension in a Rodent Model 1; GSE8132: A Multi- Kinase Inhibitor Modulates Pulmonary Hypertension in a Rodent Model 2 Experiment Overall Design: Refer to individual Series

Project description:Background: Swine influenza is a highly contagious viral infection in pigs affecting the respiratory tract that can have significant economic impacts. Streptococcus suis serotype 2 is one of the most important post-weaning bacterial pathogens in swine causing different infections, including pneumonia. Both pathogens are important contributors to the porcine respiratory disease complex. Outbreaks of swine influenza virus with a significant level of co-infections due to S. suis have lately been reported. In order to analyze a global response to the dual infection, we carried out a comprehensive gene expression profiling using a microarray approach to study the swine tracheal epithelial (NPTr) cell response to a co-infection with H1N1 swine influenza virus (swH1N1) and S. suis serotype 2. Results: Gene clustering showed that the swH1N1 and swH1N1/S. suis infections modified the expression of genes in a similar manner. Additionally, infection of NPTr cells by S. suis alone did not result in many differentially expressed genes compared to mock-infected cells. However, some important genes coding for inflammatory mediators, such as chemokines, interleukins, cell adhesion molecules and eicosanoids, were significantly upregulated in the presence of both pathogens comparing to infection with each pathogen taken individually. This synergy may also be the consequence of an increased adhesion/invasion of epithelial cells previously infected by swH1N1, as recently reported. Conclusion: In a co-infection situation, influenza virus would replicate in the respiratory epithelium inducing an inflammatory infiltrate comprised of mononuclear cells and neutrophils. Despite that these cells are unable to phagocyte and kill S. suis, they are highly activated by this pathogen. S. suis is not considered a primary pulmonary pathogen, but an exacerbated production of pro-inflammatory mediators during a co-infection with influenza virus may be of critical importance in the pathogenesis and outcome of this respiratory disease complex. Total RNA obtained from NPTr cells infected with S. suis, H1N1, or S. suis & H1N1. Four replicates in both groups.

Project description:Sepsis is a clinical syndrome that can be caused by bacteria or fungi. Early knowledge on the nature of the causative agent is a prerequisite for targeted anti-microbial therapy. Besides currently used detection methods like blood culture and PCR-based assays, the analysis of the transcriptional response of the host to infecting organisms holds great promise. In this study, we aim to examine the transcriptional footprint of infections caused by the bacterial pathogens Staphylococcus aureus and Escherichia coli and the fungal pathogens Candida albicans and Aspergillus fumigatus in a human whole-blood model. Moreover, we use the expression information to build a random forest classifier to determine if the pathogen is bacterial, fungal or neither of the two. After normalizing the transcription intensities using stably expressed reference genes, we filtered the gene set for biomarkers of bacterial or fungal blood infections. This selection is based on differential expression and an additional gene relevance measure. In this way, we identified 38 biomarker genes, including IL6, SOCS3, and IRG1 which were already associated to sepsis by other studies. Using these genes, we trained the classifier and assessed its performance. It yielded a 96% accuracy (sensitivities >93%, specificities >97%) for a 10-fold stratified cross-validation and a 92% accuracy (sensitivities and specificities >83%) for an additional dataset comprising Cryptococcus neoformans infections. Furthermore, the noise-robustness of the classifier suggests high rates of correct class predictions on datasets of new species. In conclusion, this genome-wide approach demonstrates an effective feature selection process in combination with the construction of a well-performing classification model. Further analyses of genes with pathogen-dependent expression patterns can provide insights into the systemic host responses, which may lead to new anti-microbial therapeutic advances. Analysis of innate immune activation on the basis of gene expression of whole blood cells during ex vivo whole blood infection with bacterial (Staphylococcus aureus, Escherichia coli) and fungal pathogens (Candida albicans, Aspergillus fumigatus) in comparison to mock-treated blood.

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Host lung gene expression patterns predict the etiology of infectious pneumonias

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