197 research outputs found
Vaginal microbiota and cytokine levels predict preterm delivery in Asian women
Preterm birth (PTB) is the most common cause of neonatal morbidity and mortality worldwide. Approximately half of PTBs is linked with microbial etiologies, including pathologic changes to the vaginal microbiota, which vary according to ethnicity. Globally more than 50% of PTBs occur in Asia, but studies of the vaginal microbiome and its association with pregnancy outcomes in Asian women are lacking. This study aimed to longitudinally analyzed the vaginal microbiome and cytokine environment of 18 Karen and Burman pregnant women who delivered preterm and 36 matched controls delivering at full term. Using 16S ribosomal RNA gene sequencing we identified a predictive vaginal microbiota signature for PTB that was detectable as early as the first trimester of pregnancy, characterized by higher levels of Prevotella buccalis, and lower levels of Lactobacillus crispatus and Finegoldia, accompanied by decreased levels of cytokines including IFNgamma, IL-4, and TNFalpha. Differences in the vaginal microbial diversity and local vaginal immune environment were associated with greater risk of preterm birth. Our findings highlight new opportunities to predict PTB in Asian women in low-resource settings who are at highest risk of adverse outcomes from unexpected PTB, as well as in Burman/Karen ethnic minority groups in high-resource regions
HIV-tuberculosis-associated immune reconstitution inflammatory syndrome is characterized by Toll-like receptor and inflammasome signalling
Patients with HIV-associated tuberculosis (TB) initiating antiretroviral therapy (ART) may develop immune reconstitution inflammatory syndrome (TB-IRIS). No biomarkers for TB-IRIS have been identified and the underlying mechanisms are unclear. Here we perform transcriptomic profiling of the blood samples of patients with HIV-associated TB. We identify differentially abundant transcripts as early as week 0.5 post ART initiation that predict downstream activation of proinflammatory cytokines in patients who progress to TB-IRIS. At the characteristic time of TB-IRIS onset (week 2), the signature is characterized by over-representation of innate immune mediators including TLR signalling and TREM-1 activation of the inflammasome. In keeping with the transcriptional data, concentrations of plasma cytokines and caspase-1/5 are elevated in TB-IRIS. Inhibition of MyD88 adaptor and group 1 caspases reduces secretion of cytokines including IL-1 in TB-IRIS patients. These data provide insight on the pathogenesis of TB-IRIS and may assist the development of specific therapies
An interferon-inducible neutrophil-driven blood transcriptional signature in human tuberculosis
Tuberculosis (TB), caused by infection with Mycobacterium tuberculosis (M. tuberculosis), is a major cause of morbidity and mortality worldwide and efforts to control TB are hampered by difficulties with diagnosis, prevention and treatment 1,2. Most people infected with M. tuberculosis remain asymptomatic, termed latent TB, with a 10% lifetime risk of developing active TB disease, but current tests cannot identify which individuals will develop disease 3. The immune response to M. tuberculosis is complex and incompletely characterized, hindering development of new diagnostics, therapies and vaccines 4,5. We identified a whole blood 393 transcript signature for active TB in intermediate and high burden settings, correlating with radiological extent of disease and reverting to that of healthy controls following treatment. A subset of latent TB patients had signatures similar to those in active TB patients. We also identified a specific 86-transcript signature that discriminated active TB from other inflammatory and infectious diseases. Modular and pathway analysis revealed that the TB signature was dominated by a neutrophil-driven interferon (IFN)-inducible gene profile, consisting of both IFN-γ and Type I IFNαβ signalling. Comparison with transcriptional signatures in purified cells and flow cytometric analysis, suggest that this TB signature reflects both changes in cellular composition and altered gene expression. Although an IFN signature was also observed in whole blood of patients with Systemic Lupus Erythematosus (SLE), their complete modular signature differed from TB with increased abundance of plasma cell transcripts. Our studies demonstrate a hitherto under-appreciated role of Type I IFNαβ signalling in TB pathogenesis, which has implications for vaccine and therapeutic development. Our study also provides a broad range of transcriptional biomarkers with potential as diagnostic and prognostic tools to combat the TB epidemic
Probing host pathogen cross-talk by transcriptional profiling of both Mycobacterium tuberculosis and infected human dendritic cells and macrophages
This study provides the proof of principle that probing the host and the microbe transcriptomes simultaneously is a valuable means to accessing unique information on host pathogen interactions. Our results also underline the extraordinary plasticity of host cell and pathogen responses to infection, and provide a solid framework to further understand the complex mechanisms involved in immunity to M. tuberculosis and in mycobacterial adaptation to different intracellular environments
Disclosing ambiguous gene aliases by automatic literature profiling
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Previous issue date: 2010Fundação Oswaldo Cruz. Centro de Pesquisa René Rachou. Centro de Excelência em Bioinformática. Belo Horizonte, MG, Brasil/Fundação Oswaldo Cruz. Centro de Pesquisa René Rachou. Grupo de Genômica e Biologia Computacional. Belo Horizonte, MG, BrasilGlaxoSmithKline Moore Dr. Molecular Discovery Research. Research Triangle Park, NC, USAFundação Oswaldo Cruz. Centro de Pesquisa René Rachou. Centro de Excelência em Bioinformática. Belo Horizonte, MG, Brasil/Fundação Oswaldo Cruz. Centro de Pesquisa René Rachou. Grupo de Genômica e Biologia Computacional. Belo Horizonte, MG, BrasilBackground
Retrieving pertinent information from biological scientific literature requires cutting-edge text mining methods which may be able to recognize the meaning of the very ambiguous names of biological entities. Aliases of a gene share a common vocabulary in their respective collections of PubMed abstracts. This may be true even when these aliases are not associated with the same subset of documents. This gene-specific vocabulary defines a unique fingerprint that can be used to disclose ambiguous aliases. The present work describes an original method for automatically assessing the ambiguity levels of gene aliases in large gene terminologies based exclusively in the content of their associated literature. The method can deal with the two major problems restricting the usage of current text mining tools: 1) different names associated with the same gene; and 2) one name associated with multiple genes, or even with non-gene entities. Important, this method does not require training examples.
Results
Aliases were considered “ambiguous” when their Jaccard distance to the respective official gene symbol was equal or greater than the smallest distance between the official gene symbol and one of the three internal controls (randomly picked unrelated official gene symbols). Otherwise, they were assigned the status of “synonyms”. We evaluated the coherence of the results by comparing the frequencies of the official gene symbols in the text corpora retrieved with their respective “synonyms” or “ambiguous” aliases. Official gene symbols were mentioned in the abstract collections of 42 % (70/165) of their respective synonyms. No official gene symbol occurred in the abstract collections of any of their respective ambiguous aliases. In overall, querying PubMed with official gene symbols and “synonym” aliases allowed a 3.6-fold increase in the number of unique documents retrieved.
Conclusions
These results confirm that this method is able to distinguish between synonyms and ambiguous gene aliases based exclusively on their vocabulary fingerprint. The approach we describe could be used to enhance the retrieval of relevant literature related to a gen
Enhanced Monocyte Response and Decreased Central Memory T Cells in Children with Invasive Staphylococcus aureus Infections
Staphylococcus aureus has emerged as a significant pathogen causing severe invasive disease in otherwise healthy people. Despite considerable advances in understanding the epidemiology, resistance mechanisms, and virulence factors produced by the bacteria, there is limited knowledge of the in vivo host immune response to acute, invasive S. aureus infections. Herein, we report that peripheral blood mononuclear cells from patients with severe S. aureus infections demonstrate a distinctive and robust gene expression profile which is validated in a distinct group of patients and on a different microarray platform. Application of a systems-wide modular analysis framework reveals significant over-expression of innate immunity genes and under-expression of genes related to adaptive immunity. Simultaneous flow cytometry analyses demonstrated marked alterations in immune cell numbers, with decreased central memory CD4 and CD8 T cells and increased numbers of monocytes. CD14+ monocyte numbers significantly correlated with the gene expression levels of genes related to the innate immune response. These results demonstrate the value of applying a systems biology approach that reveals the significant alterations in the components of circulating blood lymphocytes and monocytes in invasive S. aureus infections
GenCLiP: a software program for clustering gene lists by literature profiling and constructing gene co-occurrence networks related to custom keywords
<p>Abstract</p> <p>Background</p> <p>Biomedical researchers often want to explore pathogenesis and pathways regulated by abnormally expressed genes, such as those identified by microarray analyses. Literature mining is an important way to assist in this task. Many literature mining tools are now available. However, few of them allows the user to make manual adjustments to zero in on what he/she wants to know in particular.</p> <p>Results</p> <p>We present our software program, GenCLiP (Gene Cluster with Literature Profiles), which is based on the methods presented by Chaussabel and Sher (<it>Genome Biol </it>2002, 3(10):RESEARCH0055) that search gene lists to identify functional clusters of genes based on up-to-date literature profiling. Four features were added to this previously described method: the ability to 1) manually curate keywords extracted from the literature, 2) search genes and gene co-occurrence networks related to custom keywords, 3) compare analyzed gene results with negative and positive controls generated by GenCLiP, and 4) calculate probabilities that the resulting genes and gene networks are randomly related. In this paper, we show with a set of differentially expressed genes between keloids and normal control, how implementation of functions in GenCLiP successfully identified keywords related to the pathogenesis of keloids and unknown gene pathways involved in the pathogenesis of keloids.</p> <p>Conclusion</p> <p>With regard to the identification of disease-susceptibility genes, GenCLiP allows one to quickly acquire a primary pathogenesis profile and identify pathways involving abnormally expressed genes not previously associated with the disease.</p
Functional Correlations of Pathogenesis-Driven Gene Expression Signatures in Tuberculosis
Tuberculosis remains a major health threat and its control depends on improved measures of prevention, diagnosis and treatment. Biosignatures can play a significant role in the development of novel intervention measures against TB and blood transcriptional profiling is increasingly exploited for their rational design. Such profiles also reveal fundamental biological mechanisms associated with the pathology of the disease. We have compared whole blood gene expression in TB patients, as well as in healthy infected and uninfected individuals in a cohort in The Gambia, West Africa and validated previously identified signatures showing high similarities of expression profiles among different cohorts. In this study, we applied a unique combination of classical gene expression analysis with pathway and functional association analysis integrated with intra-individual expression correlations. These analyses were employed for identification of new disease-associated gene signatures, identifying a network of Fc gamma receptor 1 signaling with correlating transcriptional activity as hallmark of gene expression in TB. Remarkable similarities to characteristic signatures in the autoimmune disease systemic lupus erythematosus (SLE) were observed. Functional gene clusters of immunoregulatory interactions involving the JAK-STAT pathway; sensing of microbial patterns by Toll-like receptors and IFN-signaling provide detailed insights into the dysregulation of critical immune processes in TB, involving active expression of both pro-inflammatory and immunoregulatory systems. We conclude that transcriptomics (i) provides a robust system for identification and validation of biosignatures for TB and (ii) application of integrated analysis tools yields novel insights into functional networks underlying TB pathogenesis
The Genopolis Microarray Database
<p>Abstract</p> <p>Background</p> <p>Gene expression databases are key resources for microarray data management and analysis and the importance of a proper annotation of their content is well understood.</p> <p>Public repositories as well as microarray database systems that can be implemented by single laboratories exist. However, there is not yet a tool that can easily support a collaborative environment where different users with different rights of access to data can interact to define a common highly coherent content. The scope of the Genopolis database is to provide a resource that allows different groups performing microarray experiments related to a common subject to create a common coherent knowledge base and to analyse it. The Genopolis database has been implemented as a dedicated system for the scientific community studying dendritic and macrophage cells functions and host-parasite interactions.</p> <p>Results</p> <p>The Genopolis Database system allows the community to build an object based MIAME compliant annotation of their experiments and to store images, raw and processed data from the Affymetrix GeneChip<sup>® </sup>platform. It supports dynamical definition of controlled vocabularies and provides automated and supervised steps to control the coherence of data and annotations. It allows a precise control of the visibility of the database content to different sub groups in the community and facilitates exports of its content to public repositories. It provides an interactive users interface for data analysis: this allows users to visualize data matrices based on functional lists and sample characterization, and to navigate to other data matrices defined by similarity of expression values as well as functional characterizations of genes involved. A collaborative environment is also provided for the definition and sharing of functional annotation by users.</p> <p>Conclusion</p> <p>The Genopolis Database supports a community in building a common coherent knowledge base and analyse it. This fills a gap between a local database and a public repository, where the development of a common coherent annotation is important. In its current implementation, it provides a uniform coherently annotated dataset on dendritic cells and macrophage differentiation.</p
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