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3 Publications visible to you, out of a total of 3
covRNA: discovering covariate associations in large-scale gene expression data.

Abstract (Expand)

OBJECTIVE: The biological interpretation of gene expression measurements is a challenging task. While ordination methods are routinely used to identify clusters of samples or co-expressed genes, these … methods do not take sample or gene annotations into account. We aim to provide a tool that allows users of all backgrounds to assess and visualize the intrinsic correlation structure of complex annotated gene expression data and discover the covariates that jointly affect expression patterns. RESULTS: The Bioconductor package covRNA provides a convenient and fast interface for testing and visualizing complex relationships between sample and gene covariates mediated by gene expression data in an entirely unsupervised setting. The relationships between sample and gene covariates are tested by statistical permutation tests and visualized by ordination. The methods are inspired by the fourthcorner and RLQ analyses used in ecological research for the analysis of species abundance data, that we modified to make them suitable for the distributional characteristics of both, RNA-Seq read counts and microarray intensities, and to provide a high-performance parallelized implementation for the analysis of large-scale gene expression data on multi-core computational systems. CovRNA provides additional modules for unsupervised gene filtering and plotting functions to ensure a smooth and coherent analysis workflow.

Authors: L. Urban, C. W. Remmele, M. Dittrich, R. F. Schwarz, T. Muller

Date Published: 24th Feb 2020

Publication Type: Not specified

Moraxella catarrhalis induces CEACAM3-Syk-Card9-dependent activation of human granulocytes

Abstract (Expand)

The human restricted pathogen Moraxella catarrhalis is an important causal agent for exacerbations in chronic obstructive lung disease (COPD) in adults. In such patients, increased numbers of granulocytes … are present in the airways, which correlate with bacteria-induced exacerbations and severity of the disease. Our study investigated whether the interaction of M. catarrhalis with the human granulocyte-specific carcinoembryonic antigen-related cell adhesion molecule (CEACAM)-3 is linked to NF-kappaB activation, resulting in chemokine production. Granulocytes from healthy donors and NB4 cells were infected with M. catarrhalis in the presence of different inhibitors, blocking antibodies and siRNA. The supernatants were analysed by ELISA for chemokines. NF-kappaB activation was determined using a luciferase reporter gene assay and chromatin-immunoprecipitation. We found evidence that the specific engagement of CEACAM3 by Moraxella catarrhalis ubiquitous surface protein A1 (UspA1) results in the activation of pro-inflammatory events, such as degranulation of neutrophils, ROS production and chemokine secretion. The interaction of UspA1 with CEACAM3 induced the activation of the NF-kappaB pathway via Syk and the Card9 pathway and was dependent on the phosphorylation of the CEACAM3 ITAM -like motif. These findings suggest that the CEACAM3 signalling in neutrophils is able to specifically modulate airway inflammation caused by infection with M. catarrhalis.

Authors: A. Heinrich, K. A. Heyl, E. Klaile, , , A. Wiessner, K. Fischer, R. R. Schumann, U. Seifert, K. Riesbeck, A. Moter, B. B. Singer, S. Bachmann,

Date Published: 3rd Apr 2016

Publication Type: Not specified

Integrated inference and evaluation of host-fungi interaction networks

Abstract (Expand)

Fungal microorganisms frequently lead to life-threatening infections. Within this group of pathogens, the commensal Candida albicans and the filamentous fungus Aspergillus fumigatus are by far the most … important causes of invasive mycoses in Europe. A key capability for host invasion and immune response evasion are specific molecular interactions between the fungal pathogen and its human host. Experimentally validated knowledge about these crucial interactions is rare in literature and even specialized host-pathogen databases mainly focus on bacterial and viral interactions whereas information on fungi is still sparse. To establish large-scale host-fungi interaction networks on a systems biology scale, we develop an extended inference approach based on protein orthology and data on gene functions. Using human and yeast intraspecies networks as template, we derive a large network of pathogen-host interactions (PHI). Rigorous filtering and refinement steps based on cellular localization and pathogenicity information of predicted interactors yield a primary scaffold of fungi-human and fungi-mouse interaction networks. Specific enrichment of known pathogenicity-relevant genes indicates the biological relevance of the predicted PHI. A detailed inspection of functionally relevant subnetworks reveals novel host-fungal interaction candidates such as the Candida virulence factor PLB1 and the anti-fungal host protein APP. Our results demonstrate the applicability of interolog-based prediction methods for host-fungi interactions and underline the importance of filtering and refinement steps to attain biologically more relevant interactions. This integrated network framework can serve as a basis for future analyses of high-throughput host-fungi transcriptome and proteome data.

Authors: , C. H. Luther, J. Balkenhol, , ,

Date Published: 4th Aug 2015

Publication Type: Not specified

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