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The ability to adhere and adapt to the human respiratory tract mucosa plays a pivotal role in the pathogenic lifestyle of nontypeable Haemophilus influenzae (NTHi). However, the temporal events associated with a successful colonization have not been fully characterized. In this study, by reconstituting the ciliated human bronchial epithelium in vitro, we monitored the global transcriptional changes in NTHi and infected mucosal epithelium simultaneously for up to 72 h by dual RNA sequencing. The initial stage of colonization was characterized by the binding of NTHi to ciliated cells. Temporal profiling of host mRNA signatures revealed significant dysregulation of the target cell cytoskeleton elicited by bacterial infection, with a profound effect on the intermediate filament network and junctional complexes. In response to environmental stimuli of the host epithelium, NTHi downregulated its central metabolism and increased the expression of transporters, indicating a change in the metabolic regime due to the availability of host substrates. Concurrently, the oxidative environment generated by infected cells instigated bacterial expression of stress-induced defense mechanisms, including the transport of exogenous glutathione and activation of the toxin-antitoxin system. The results of this analysis were validated by those of confocal microscopy, Western blotting, Bio-plex, and real-time quantitative reverse transcription-PCR (qRT-PCR). Notably, as part of our screening for novel signatures of infection, we identified a global profile of noncoding transcripts that are candidate small RNAs (sRNAs) regulated during human host infection in Haemophilus species. Our data, by providing a robust and comprehensive representation of the cross talk between the host and invading pathogen, provides important insights into NTHi pathogenesis and the development of efficacious preventive strategies.
Pubmed ID: 26578681 RIS Download
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Portal to interactively visualize genomic data. Provides reference sequences and working draft assemblies for collection of genomes and access to ENCODE and Neanderthal projects. Includes collection of vertebrate and model organism assemblies and annotations, along with suite of tools for viewing, analyzing and downloading data.
View all literature mentionsFunctional genomics data repository supporting MIAME-compliant data submissions. Includes microarray-based experiments measuring the abundance of mRNA, genomic DNA, and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. Array- and sequence-based data are accepted. Collection of curated gene expression DataSets, as well as original Series and Platform records. The database can be searched using keywords, organism, DataSet type and authors. DataSet records contain additional resources including cluster tools and differential expression queries.
View all literature mentionsImaris provides range of capabilities for working with three dimensional images. Uses flexible editing and processing functions, such as interactive surface rendering and object slicing capabilities. And output to standard TIFF, Quicktime and AVI formats. Imaris accepts virtually all image formats that are used in confocal microscopy and many of those used in wide-field image acquisition.
View all literature mentionsA next-generation web-based application that aims to provide an integrated solution for both visualization and analysis of deep-sequencing data, along with simple access to public datasets.
View all literature mentionsThe Rfam database is a collection of RNA families, each represented by multiple sequence alignments, consensus secondary structures and covariance models (CMs). The families in Rfam break down into three broad functional classes: Non-coding RNA genes, structured cis-regulatory elements and self-splicing RNAs. Typically these functional RNAs often have a conserved secondary structure which may be better preserved than the RNA sequence. The CMs used to describe each family are a slightly more complicated relative of the profile hidden Markov models (HMMs) used by Pfam. CMs can simultaneously model RNA sequence and the structure in an elegant and accurate fashion. Rfam is also available via FTP. You can find data in Rfam in various ways... * Analyze your RNA sequence for Rfam matches * View Rfam family annotation and alignments * View Rfam clan details * Query Rfam by keywords * Fetch families or sequences by NCBI taxonomy * Enter any type of accession or ID to jump to the page for a Rfam family, sequence or genome
View all literature mentionsA web-based software application that enables users to analyze, integrate, and understand data derived from gene expression, microRNA, and SNP microarrays, metabolomics, proteomics, and RNA-Seq experiments, and small-scale experiments that generate gene and chemical lists. Users can search for targeted information on genes, proteins, chemicals, and drugs, and build interactive models of experimental systems. IPA allows exploration of molecular, chemical, gene, protein and miRNA interactions, creation of custom molecular pathways, and the ability to view and modify metabolic, signaling, and toxicological canonical pathways. In addition to the networks and pathways that can be created, IPA can provide multiple layering of additional information, such as drugs, disease genes, expression data, cellular functions and processes, or a researchers own genes or chemicals of interest.
View all literature mentionsSoftware package for DNA and protein sequence alignment to find regions of local or global similarity between Protein or DNA sequences, either by searching Protein or DNA databases, or by identifying local duplications within a sequence.
View all literature mentionsScript distributed with the HT-Seq Python framework for processing RNA-seq or DNA-seq data.
View all literature mentionsFunctional genomics data repository supporting MIAME-compliant data submissions. Includes microarray-based experiments measuring the abundance of mRNA, genomic DNA, and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. Array- and sequence-based data are accepted. Collection of curated gene expression DataSets, as well as original Series and Platform records. The database can be searched using keywords, organism, DataSet type and authors. DataSet records contain additional resources including cluster tools and differential expression queries.
View all literature mentionsThe SciCrunch Infrastructure was developed as a cooperative data platform to be used by diverse communities in making data more FAIR.
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