Negative regulation of NKG2D expression by IL-4 in memory CD8 T cells.

IL-4 is one of the main cytokines produced during Th2-inducing pathologies. This cytokine has been shown to affect a number of immune processes such as Th differentiation and innate immune responses. However, the impact of IL-4 on CD8 T cell responses remains unclear. In this study, we analyzed the effects of IL-4 on global gene expression profiles of Ag-induced memory CD8 T cells in the mouse. Gene ontology analysis of this signature revealed that IL-4 regulated most importantly genes associated with immune responses. Moreover, this IL-4 signature overlapped with the set of genes preferentially expressed by memory CD8 T cells over naive CD8 T cells. In particular, IL-4 downregulated in vitro and in vivo in a STAT6-dependent manner the memory-specific expression of NKG2D, thereby increasing the activation threshold of memory CD8 T cells. Furthermore, IL-4 impaired activation of memory cells as well as their differentiation into effector cells. This phenomenon could have an important clinical relevance as patients affected by Th2 pathologies such as parasitic infections or atopic dermatitis often suffer from viral-induced complications possibly linked to inefficient CD8 T cell responses.

SQUAT: A web tool to mine human, murine and avian SAGE data.

BACKGROUND: There is an increasing need in transcriptome research for gene expression data and pattern warehouses. It is of importance to integrate in these warehouses both raw transcriptomic data, as well as some properties encoded in these data, like local patterns. DESCRIPTION: We have developed an application called SQUAT (SAGE Querying and Analysis Tools) which is available at: http://bsmc.insa-lyon.fr/squat/. This database gives access to both raw SAGE data and patterns mined from these data, for three species (human, mouse and chicken). This database allows to make simple queries like "In which biological situations is my favorite gene expressed?" as well as much more complex queries like: <>. Connections with external web databases enrich biological interpretations, and enable sophisticated queries. To illustrate the power of SQUAT, we show and analyze the results of three different queries, one of which led to a biological hypothesis that was experimentally validated. CONCLUSION: SQUAT is a user-friendly information retrieval platform, which aims at bringing some of the state-of-the-art mining tools to biologists.

Phenotypic and Genomic Characterization of AmpC-Producing Klebsiella pneumoniae From Korea.

The prevalence of multidrug-resistant gram-negative bacteria has continuously increased over the past few years; bacterial strains producing AmpC ß-lactamases and/or extended-spectrum ß-lactamases (ESBLs) are of particular concern. We combined high-resolution whole genome sequencing and phenotypic data to elucidate the mechanisms of resistance to cephamycin and ß-lactamase in Korean Klebsiella pneumoniae strains, in which no AmpC-encoding genes were detected by PCR. We identified several genes that alone or in combination can potentially explain the resistance phenotype. We showed that different mechanisms could explain the resistance phenotype, emphasizing the limitations of the PCR and the importance of distinguishing closely-related gene variants.

Routine Whole-Genome Sequencing for Outbreak Investigations of Staphylococcus aureus in a National Reference Center.

The French National Reference Center for Staphylococci currently uses DNA arrays and spa typing for the initial epidemiological characterization of Staphylococcus aureus strains. We here describe the use of whole-genome sequencing (WGS) to investigate retrospectively four distinct and virulent S. aureus lineages [clonal complexes (CCs): CC1, CC5, CC8, CC30] involved in hospital and community outbreaks or sporadic infections in France. We used a WGS bioinformatics pipeline based on de novo assembly (reference-free approach), single nucleotide polymorphism analysis, and on the inclusion of epidemiological markers. We examined the phylogeographic diversity of the French dominant hospital-acquired CC8-MRSA (methicillin-resistant S. aureus) Lyon clone through WGS analysis which did not demonstrate evidence of large-scale geographic clustering. We analyzed sporadic cases along with two outbreaks of a CC1-MSSA (methicillin-susceptible S. aureus) clone containing the Panton-Valentine leukocidin (PVL) and results showed that two sporadic cases were closely related. We investigated an outbreak of PVL-positive CC30-MSSA in a school environment and were able to reconstruct the transmission history between eight families. We explored different outbreaks among newborns due to the CC5-MRSA Geraldine clone and we found evidence of an unsuspected link between two otherwise distinct outbreaks. Here, WGS provides the resolving power to disprove transmission events indicated by conventional methods (same sequence type, spa type, toxin profile, and antibiotic resistance profile) and, most importantly, WGS can reveal unsuspected transmission events. Therefore, WGS allows to better describe and understand outbreaks and (inter-)national dissemination of S. aureus lineages. Our findings underscore the importance of adding WGS for (inter-)national surveillance of infections caused by virulent clones of S. aureus but also substantiate the fact that technological optimization at the bioinformatics level is still urgently needed for routine use. However, the greatest limitation of WGS analysis is the completeness and the correctness of the reference database being used and the conversion of floods of data into actionable results. The WGS bioinformatics pipeline (EpiSeqTM) we used here can easily generate a uniform database and associated metadata for epidemiological applications.

Correlation between phenotypic antibiotic susceptibility and the resistome in Pseudomonas aeruginosa.

Genetic determinants of antibiotic resistance (AR) have been extensively investigated. High-throughput sequencing allows for the assessment of the relationship between genotype and phenotype. A panel of 672 Pseudomonas aeruginosa strains was analysed, including representatives of globally disseminated multidrug-resistant and extensively drug-resistant clones; genomes and multiple antibiograms were available. This panel was annotated for AR gene presence and polymorphism, defining a resistome in which integrons were included. Integrons were present in >70 distinct cassettes, with In5 being the most prevalent. Some cassettes closely associated with clonal complexes, whereas others spread across the phylogenetic diversity, highlighting the importance of horizontal transfer. A resistome-wide association study (RWAS) was performed for clinically relevant antibiotics by correlating the variability in minimum inhibitory concentration (MIC) values with resistome data. Resistome annotation identified 147 loci associated with AR. These loci consisted mainly of acquired genomic elements and intrinsic genes. The RWAS allowed for correct identification of resistance mechanisms for meropenem, amikacin, levofloxacin and cefepime, and added 46 novel mutations. Among these, 29 were variants of the oprD gene associated with variation in meropenem MIC. Using genomic and MIC data, phenotypic AR was successfully correlated with molecular determinants at the whole-genome sequence level.

Clinical metagenomics for the management of hospital- and healthcare-acquired pneumonia.

The increasing burden of multidrug-resistant bacteria affects the management of several infections. In order to prescribe adequate antibiotics, clinicians facing severe infections such as hospital-acquired pneumonia (HAP) need to promptly identify the pathogens and know their antibiotic susceptibility profiles (AST), which with conventional microbiology currently requires 24 and 48 h, respectively. Clinical metagenomics, based on whole genome sequencing of clinical samples, could improve the diagnosis of HAP, however, many obstacles remain to be overcome, namely the turn-around time, the quantification of pathogens, the choice of antibiotic resistance determinants (ARDs), the inference of the AST from metagenomic data and the linkage between ARDs and their host. Here, we propose to tackle those issues in a bottom-up, clinically driven approach.

Immune signatures of protective spleen memory CD8 T cells.

Memory CD8 T lymphocyte populations are remarkably heterogeneous and differ in their ability to protect the host. In order to identify the whole range of qualities uniquely associated with protective memory cells we compared the gene expression signatures of two qualities of memory CD8 T cells sharing the same antigenic-specificity: protective (Influenza-induced, Flu-TM) and non-protective (peptide-induced, TIM) spleen memory CD8 T cells. Although Flu-TM and TIM express classical phenotypic memory markers and are polyfunctional, only Flu-TM protects against a lethal viral challenge. Protective memory CD8 T cells express a unique set of genes involved in migration and survival that correlate with their unique capacity to rapidly migrate within the infected lung parenchyma in response to influenza infection. We also enlighten a new set of poised genes expressed by protective cells that is strongly enriched in cytokines and chemokines such as Ccl1, Ccl9 and Gm-csf. CCL1 and GM-CSF genes are also poised in human memory CD8 T cells. These immune signatures are also induced by two other pathogens (vaccinia virus and Listeria monocytogenes). The immune signatures associated with immune protection were identified on circulating cells, i.e. those that are easily accessible for immuno-monitoring and could help predict vaccines efficacy.

Overexpression of the transcription factor Sp1 activates the OAS-RNAse L-RIG-I pathway.

Deregulated expression of oncogenes or transcription factors such as specificity protein 1 (Sp1) is observed in many human cancers and plays a role in tumor maintenance. Paradoxically in untransformed cells, Sp1 overexpression induces late apoptosis but the early intrinsic response is poorly characterized. In the present work, we studied increased Sp1 level consequences in untransformed cells and showed that it turns on an early innate immune transcriptome. Sp1 overexpression does not activate known cellular stress pathways such as DNA damage response or endoplasmic reticulum stress, but induces the activation of the OAS-RNase L pathway and the generation of small self-RNAs, leading to the upregulation of genes of the antiviral RIG-I pathway at the transcriptional and translational levels. Finally, Sp1-induced intrinsic innate immune response leads to the production of the chemokine CXCL4 and to the recruitment of inflammatory cells in vitro and in vivo. Altogether our results showed that increased Sp1 level in untransformed cells constitutes a novel danger signal sensed by the OAS-RNase L axis leading to the activation of the RIG-I pathway. These results suggested that the OAS-RNase L-RIG-I pathway may be activated in sterile condition in absence of pathogen.

Phylogenetic Distribution of CRISPR-Cas Systems in Antibiotic-Resistant Pseudomonas aeruginosa.

UNLABELLED: Pseudomonas aeruginosa is an antibiotic-refractory pathogen with a large genome and extensive genotypic diversity. Historically, P. aeruginosa has been a major model system for understanding the molecular mechanisms underlying type I clustered regularly interspaced short palindromic repeat (CRISPR) and CRISPR-associated protein (CRISPR-Cas)-based bacterial immune system function. However, little information on the phylogenetic distribution and potential role of these CRISPR-Cas systems in molding the P. aeruginosa accessory genome and antibiotic resistance elements is known. Computational approaches were used to identify and characterize CRISPR-Cas systems within 672 genomes, and in the process, we identified a previously unreported and putatively mobile type I-C P. aeruginosa CRISPR-Cas system. Furthermore, genomes harboring noninhibited type I-F and I-E CRISPR-Cas systems were on average ~300 kb smaller than those without a CRISPR-Cas system. In silico analysis demonstrated that the accessory genome (n = 22,036 genes) harbored the majority of identified CRISPR-Cas targets. We also assembled a global spacer library that aided the identification of difficult-to-characterize mobile genetic elements within next-generation sequencing (NGS) data and allowed CRISPR typing of a majority of P. aeruginosa strains. In summary, our analysis demonstrated that CRISPR-Cas systems play an important role in shaping the accessory genomes of globally distributed P. aeruginosa isolates. IMPORTANCE: P. aeruginosa is both an antibiotic-refractory pathogen and an important model system for type I CRISPR-Cas bacterial immune systems. By combining the genome sequences of 672 newly and previously sequenced genomes, we were able to provide a global view of the phylogenetic distribution, conservation, and potential targets of these systems. This analysis identified a new and putatively mobile P. aeruginosa CRISPR-Cas subtype, characterized the diverse distribution of known CRISPR-inhibiting genes, and provided a potential new use for CRISPR spacer libraries in accessory genome analysis. Our data demonstrated the importance of CRISPR-Cas systems in modulating the accessory genomes of globally distributed strains while also providing substantial data for subsequent genomic and experimental studies in multiple fields. Understanding why certain genotypes of P. aeruginosa are clinically prevalent and adept at horizontally acquiring virulence and antibiotic resistance elements is of major clinical and economic importance.

Cellular receptors, differentiation and endocytosis requirements are key factors for type I IFN response by human epithelial, conventional and plasmacytoid dendritic infected cells by measles virus.

While the antiviral response during measles virus (MeV) infection is documented, the contribution of the hosting cell type to the type I interferon (IFN-alpha/beta) response is still not clearly established. Here, we report that a signature heterogeneity of the IFN-alpha/beta response according to the cell type. The MeV tropism dictated by the expression of appropriate cellular receptor appeared to be crucial for epithelial cells. For conventional DCs (cDCs), the maturation state played a prominent role. In response to both wild type MeV isolates and laboratory/vaccine strains, immature cDCs produced higher levels of IFN-alpha than mature cDCs, despite the reduced expression levels of both CD46 and CD150 receptors by the former ones. While in epithelial cells and cDCs the MeV transcription was required to activate the IFN-alpha/beta response, plasmacytoid DCs (pDCs) rapidly produced large amounts of IFN-alpha mostly independently of the viral infection cycle. This argues for a significant contribution of pDCs in response to MeV infection and/or vaccination.

Extracting signature motifs from promoter sets of differentially expressed genes.

There is a critical need for new and efficient computational methods aimed at discovering putative transcription factor binding sites (TFBSs) in promoter sequences. Among the existing methods, two families can be distinguished: statistical or stochastic approaches, and combinatorial approaches. Here we focus on a complete approach incorporating a combinatorial exhaustive motif extraction, together with a statistical Twilight Zone Indicator (TZI), in two datasets: a positive set and a negative one, which represents the result of a classical differential expression experiment. Our approach relies on the existence of prior biological information in the form of two sets of promoters of differentially expressed genes. We describe the complete procedure used for extracting either exact or degenerated motifs, ranking these motifs, and finding their known related TFBSs. We exemplify this approach using two different sets of promoters. The first set consists in promoters of genes either repressed or not by the transforming form of the v-erbA oncogene. The second set consists in genes the expression of which varies between self-renewing and differentiating progenitors. The biological meaning of the found TFBSs is discussed and, for one TF, its biological involvement is demonstrated. This study therefore illustrates the power of using relevant biological information, in the form of a set of differentially expressed genes that is a classical outcome in most of transcriptomics studies. This allows to severely reduce the search space and to design an adapted statistical indicator. Taken together, this allows the biologist to concentrate on a small number of putatively interesting TFs.