134 research outputs found

    Gene expression profiling of bronchial brushes is associated with the level of emphysema measured by computed tomography-based parametric response mapping

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    Parametric response mapping (PRM) is a computed tomography (CT)-based method to phenotype patients with chronic obstructive pulmonary disease (COPD). It is capable of differentiating emphysema-related air trapping with nonemphysematous air trapping (small airway disease), which helps to identify the extent and localization of the disease. Most studies evaluating the gene expression in smokers and COPD patients related this to spirometric measurements, but none have investigated the relationship with CT-based measurements of lung structure. The current study aimed to examine gene expression profiles of brushed bronchial epithelial cells in association with the PRM-defined CT-based measurements of emphysema (PRM(Emph)) and small airway disease (PRM(fSAD)). Using the Top Institute Pharma (TIP) study cohort (COPD = 12 and asymptomatic smokers = 32), we identified a gene expression signature of bronchial brushings, which was associated with PRM(Emph) in the lungs. One hundred thirty-three genes were identified to be associated with PRM(Emph). Among the most significantly associated genes, CXCL11 is a potent chemokine involved with CD8(+) T cell activation during inflammation in COPD, indicating that it may play an essential role in the development of emphysema. The PRM(Emph) signature was then replicated in two independent data sets. Pathway analysis showed that the PRM(Emph) signature is associated with proinflammatory and notch signaling pathways. Together these findings indicate that airway epithelium may play a role in the development of emphysema and/or may act as a biomarker for the presence of emphysema. In contrast, its role in relation to functional small airways disease is less clear

    Complete Genome Sequence of the Aerobic Facultative Methanotroph Methylocella tundrae Strain T4

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    Methylocella tundrae T4T is a facultative aerobic methanotroph which was isolated from an acidic tundra wetland and possesses only a soluble methane monooxygenase. The complete genome, which includes two megaplasmids, was sequenced using a combination of Illumina and Nanopore technologies. One of the megaplasmids carries a propane monooxygenase gene cluster

    Draft genome of a novel methanotrophic Methylobacter sp. from the volcanic soils of Pantelleria Island

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    The genus Methylobacter is considered an important and often dominant group of aerobic methane-oxidizing bacteria in many oxic ecosystems, where members of this genus contribute to the reduction of CH4 emissions. Metagenomic studies of the upper oxic layers of geothermal soils of the Favara Grande, Pantelleria, Italy, revealed the presence of various methane-oxidizing bacteria, and resulted in a near complete metagenome assembled genome (MAG) of an aerobic methanotroph, which was classified as a Methylobacter species. In this study, the Methylobacter sp. B2 MAG was used to investigate its metabolic potential and phylogenetic affiliation. The MAG has a size of 4,086,539 bp, consists of 134 contigs and 3955 genes were found, of which 3902 were protein coding genes. All genes for CH4 oxidation to CO2 were detected, including pmoCAB encoding particulate methane monooxygenase (pMMO) and xoxF encoding a methanol dehydrogenase. No gene encoding a formaldehyde dehydrogenase was present and the formaldehyde to formate conversion follows the tetrahydromethanopterin (H4MPT) pathway. β€œCa. Methylobacter favarea” B2 uses the Ribulose-Mono-Phosphate (RuMP) pathway for carbon fixation. Analysis of the MAG indicates that Na+/H+ antiporters and the urease system might be important in the maintenance of pH homeostasis of this strain to cope with acidic conditions. So far, thermoacidophilic Methylobacter species have not been isolated, however this study indicates that members of the genus Methylobacter can be found in distinct ecosystems and their presence is not restricted to freshwater or marine sediments

    Gene signatures from scRNA-seq accurately quantify mast cells in biopsies in asthma

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    Respiratory disease, characterized by changes in the cells of the lung, can affect molecular phenotype of cells and the intercellular interactions, resulting in a disbalance in the relative proportions of individual cell types. Understanding these changes is essential to understand the pathophysiology of lung disease. Conventional 'bulk' RNA-sequencing (RNA-seq), analyzing the entire transcriptome of the tissue sample, provides information about average expression levels of each gene in the mixed cell population; whereas it does not consider the cellular heterogeneity in samples composed of more than one cell type 1 . Single-cell RNA-seq (scRNA-seq) assesses the transcriptome of a complex biological sample with single-cell resolution, allowing identification of the relative frequency of discrete cell-types and analysis of their transcriptomes 1 . Nevertheless, analyzing the transcriptomic signature in large numbers of patients by scRNA-Seq is currently limited by its high costs. Mast cells are key regulatory cells driving the inflammatory process in asthma2 . Since they can be quantified by immunohistochemical staining for validation purposes, we used mast cells as an example of a rare cell population to assess the validity of our deconvolution approach. Recently, a number of bulk RNA-seq deconvolution methods have become available 3 , for instance of two deconvolution methods, namely support vector regression (SVR) 4 , the machine-learning method implemented in CYBERSORT, and Non-Negative Least Square (NNLS) 5 , using a matrix of cell-type selective genes identified with AutoGeneSc 6 . Both approaches are designed to estimate relative proportion of the main, common cell types present in the sample. When we used these methods to estimate the number of mast cells, we found a poor correlation with the number of mast cells stained by immunohistochemistry in the biopsies, suggesting the CIBERSORT and NNLS are less reliable in the case of rare cell types. We explored the possibility to use scRNA-Seq data from small numbers of subjects to specifically interrogate the relative cell type frequency of a rare cell population in a bulk RNA-Seq dataset obtained from a large asthma cohort

    Determinants of SARS-CoV-2 receptor gene expression in upper and lower airways

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    The recent outbreak of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), has led to a worldwide pandemic. One week after initial symptoms develop, a subset of patients progresses to severe disease, with high mortality and limited treatment options. To design novel interventions aimed at preventing spread of the virus and reducing progression to severe disease, detailed knowledge of the cell types and regulating factors driving cellular entry is urgently needed. Here we assess the expression patterns in genes required for COVID-19 entry into cells and replication, and their regulation by genetic, epigenetic and environmental factors, throughout the respiratory tract using samples collected from the upper (nasal) and lower airways (bronchi). Matched samples from the upper and lower airways show a clear increased expression of these genes in the nose compared to the bronchi and parenchyma. Cellular deconvolution indicates a clear association of these genes with the proportion of secretory epithelial cells. Smoking status was found to increase the majority of COVID-19 related genes including ACE2 and TMPRSS2 but only in the lower airways, which was associated with a significant increase in the predicted proportion of goblet cells in bronchial samples of current smokers. Both acute and second hand smoke were found to increase ACE2 expression in the bronchus. Inhaled corticosteroids decrease ACE2 expression in the lower airways. No significant effect of genetics on ACE2 expression was observed, but a strong association of DNA- methylation with ACE2 and TMPRSS2- mRNA expression was identified in the bronchus.</p

    An airway epithelial IL-17A response signature identifies a steroid-unresponsive COPD patient subgroup

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    BACKGROUND. Chronic obstructive pulmonary disease (COPD) is a heterogeneous smoking-related disease characterized by airway obstruction and inflammation. This inflammation may persist even after smoking cessation and responds variably to corticosteroids. Personalizing treatment to biologically similar "molecular phenotypes" may improve therapeutic efficacy in a COPD. IL-17A is involved in neutrophilic inflammation and corticosteroid resistance, and thus may be particularly important in a COPD molecular phenotype. METHODS. We generated a gene expression signature of IL-17A response in bronchial airway epithelial brushings from smokers with and without COPD (n = 238) , and validated it using data from 2 randomized trials of IL-17 blockade in psoriasis. This IL-17 signature was related to clinical and pathologic characteristics in 2 additional human studies of COPD: (a) SPIROMICS (n = 47), which included former and current smokers with COPD, and (b) GLUCOLD (n = 79), in which COPD participants were randomized to placebo or corticosteroids. RESULTS. The IL-17 signature was associated with an inflammatory profile characteristic of an IL-17 response, including increased airway neutrophils and macrophages. In SPIROMICS the signature was associated with increased airway obstruction and functional small airways disease on quantitative chest CT. In GLUCOLD the signature was associated with decreased response to corticosteroids, irrespective of airway eosinophilic or type 2 inflammation. CONCLUSION. These data suggest that a gene signature of IL-17 airway epithelial response distinguishes a biologically, radiographically, and clinically distinct COPD subgroup that may benefit from personalized therapy

    Lung function associated gene Integrator Complex subunit 12 regulates protein synthesis pathways

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    Background: Genetic studies of human lung function and Chronic Obstructive Pulmonary Disease have identified a highly significant and reproducible signal on 4q24. It remains unclear which of the two candidate genes within this locus may regulate lung function: GSTCD, a gene with unknown function, and/or INTS12, a member of the Integrator Complex which is currently thought to mediate 3'end processing of small nuclear RNAs.Results: We found that, in lung tissue, 4q24 polymorphisms associated with lung function correlate with INTS12 but not neighbouring GSTCD expression. In contrast to the previous reports in other species, we only observed a minor alteration of snRNA processing following INTS12 depletion. RNAseq analysis of knockdown cells instead revealed dysregulation of a core subset of genes relevant to airway biology and a robust downregulation of protein synthesis pathways. Consistent with this, protein translation was decreased in INTS12 knockdown cells. In addition, ChIPseq experiments demonstrated INTS12 binding throughout the genome, which was enriched in transcriptionally active regions. Finally, we defined the INTS12 regulome which includes genes belonging to the protein synthesis pathways.Conclusion: INTS12 has functions beyond the canonical snRNA processing. We show that it regulates translation by regulating the expression of genes belonging to protein synthesis pathways. This study provides a detailed analysis of INTS12 activities on a genome-wide scale and contributes to the biology behind the genetic association for lung function at 4q24.</p

    Proteomic Analysis of Neisseria gonorrhoeae Biofilms Shows Shift to Anaerobic Respiration and Changes in Nutrient Transport and Outermembrane Proteins

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    Neisseria gonorrhoeae, the causative agent of gonorrhea, can form biofilms in vitro and in vivo. In biofilms, the organism is more resistant to antibiotic treatment and can serve as a reservoir for chronic infection. We have used stable isotope labeling by amino acids in cell culture (SILAC) to compare protein expression in biofilm and planktonic organisms. Two parallel populations of N. gonorrhoeae strain 1291, which is an arginine auxotroph, were grown for 48 h in continuous-flow chambers over glass, one supplemented with 13C6-arginine for planktonic organisms and the other with unlabeled arginine for biofilm growth. The biofilm and planktonic cells were harvested and lysed separately, and fractionated into three sequential protein extracts. Corresponding heavy (H) planktonic and light (L) biofilm protein extracts were mixed and separated by 1D SDS-PAGE gels, and samples were extensively analyzed by liquid chromatography-mass spectrometry. Overall, 757 proteins were identified, and 152 unique proteins met a 1.5-fold cutoff threshold for differential expression with p-values <0.05. Comparing biofilm to planktonic organisms, this set included 73 upregulated and 54 downregulated proteins. Nearly a third of the upregulated proteins were involved in energy metabolism, with cell envelope proteins making up the next largest group. Of the downregulated proteins, the largest groups were involved in protein synthesis and energy metabolism. These proteomics results were compared with our previously reported results from transcriptional profiling of gonococcal biofilms using microarrays. Nitrite reductase and cytochrome c peroxidase, key enzymes required for anaerobic growth, were detected as highly upregulated in both the proteomic and transcriptomic datasets. These and other protein expression changes observed in the present study were consistent with a shift to anaerobic respiration in gonococcal biofilms, although changes in membrane proteins not explicitly related to this shift may have other functions
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