Inferring Multiple Graphical Structures

Gaussian Graphical Models provide a convenient framework for representing dependencies between variables. Recently, this tool has received a high interest for the discovery of biological networks. The literature focuses on the case where a single network is inferred from a set of measurements, but, as wetlab data is typically scarce, several assays, where the experimental conditions affect interactions, are usually merged to infer a single network. In this paper, we propose two approaches for estimating multiple related graphs, by rendering the closeness assumption into an empirical prior or group penalties. We provide quantitative results demonstrating the benefits of the proposed approaches. The methods presented in this paper are embeded in the R package 'simone' from version 1.0-0 and later

The LIM-only protein FHL2 attenuates lung inflammation during bleomycin-induces fibrosis

Fibrogenesis is usually initiated when regenerative processes have failed and/or chronic inflammation occurs. It is characterised by the activation of tissue fibroblasts and dysregulated synthesis of extracellular matrix proteins. FHL2 (four-and-a-half LIM domain protein 2) is a scaffolding protein that interacts with numerous cellular proteins, regulating signalling cascades and gene transcription. It is involved in tissue remodelling and tumour progression. Recent data suggest that FHL2 might support fibrogenesis by maintaining the transcriptional expression of alpha smooth muscle actin and the excessive synthesis and assembly of matrix proteins in activated fibroblasts. Here, we present evidence that FHL2 does not promote bleomycin-induced lung fibrosis, but rather suppresses this process by attenuating lung inflammation. Loss of FHL2 results in increased expression of the pro-inflammatory matrix protein tenascin C and downregulation of the macrophage activating C-type lectin receptor DC-SIGN. Consequently, FHL2 knockout mice developed a severe and long-lasting lung pathology following bleomycin administration due to enhanced expression of tenascin C and impaired activation of inflammation-resolving macrophages

Temporal patterns in Ixodes ricinus microbial communities: an insight into tick-borne microbe interactions

Background: Ticks transmit pathogens of medical and veterinary importance and are an increasing threat to human and animal health. Assessing disease risk and developing new control strategies requires identifying members of the tick-borne microbiota as well as their temporal dynamics and interactions. Methods: Using high-throughput sequencing, we studied the Ixodes ricinus microbiota and its temporal dynamics. 371 nymphs were monthly collected during three consecutive years in a peri-urban forest. After a Poisson lognormal model was adjusted to our data set, a principal component analysis, sparse network reconstruction, and differential analysis allowed us to assess seasonal and monthly variability of I. ricinus microbiota and interactions within this community. Results: Around 75% of the detected sequences belonged to five genera known to be maternally inherited bacteria in arthropods and to potentially circulate in ticks: Candidatus Midichloria, Rickettsia, Spiroplasma, Arsenophonus and Wolbachia. The structure of the I. ricinus microbiota varied over time with interannual recurrence and seemed to be mainly driven by OTUs commonly found in the environment. Total network analysis revealed a majority of positive partial correlations. We identified strong relationships between OTUs belonging to Wolbachia and Arsenophonus, evidence for the presence of the parasitoid wasp Ixodiphagus hookeri in ticks. Other associations were observed between the tick symbiont Candidatus Midichloria and pathogens belonging to Rickettsia. Finally, more specific network analyses were performed on TBP-infected samples and suggested that the presence of pathogens belonging to the genera Borrelia, Anaplasma and Rickettsia may disrupt microbial interactions in I. ricinus. Conclusions: We identified the I. ricinus microbiota and documented marked shifts in tick microbiota dynamics over time. Statistically, we showed strong relationships between the presence of specific pathogens and the structure of the I. ricinus microbiota. We detected close links between some tick symbionts and the potential presence of either pathogenic Rickettsia or a parasitoid in ticks. These new findings pave the way for the development of new strategies for the control of ticks and tick-borne diseases. [MediaObject not available: see fulltext.] © 2021, The Author(s)

The role of tenascin-C in tissue injury and tumorigenesis

The extracellular matrix molecule tenascin-C is highly expressed during embryonic development, tissue repair and in pathological situations such as chronic inflammation and cancer. Tenascin-C interacts with several other extracellular matrix molecules and cell-surface receptors, thus affecting tissue architecture, tissue resilience and cell responses. Tenascin-C modulates cell migration, proliferation and cellular signaling through induction of pro-inflammatory cytokines and oncogenic signaling molecules amongst other mechanisms. Given the causal role of inflammation in cancer progression, common mechanisms might be controlled by tenascin-C during both events. Drugs targeting the expression or function of tenascin-C or the tenascin-C protein itself are currently being developed and some drugs have already reached advanced clinical trials. This generates hope that increased knowledge about tenascin-C will further improve management of diseases with high tenascin-C expression such as chronic inflammation, heart failure, artheriosclerosis and cancer

Inferring gene regression networks with model trees

<p>Abstract</p> <p>Background</p> <p>Novel strategies are required in order to handle the huge amount of data produced by microarray technologies. To infer gene regulatory networks, the first step is to find direct regulatory relationships between genes building the so-called gene co-expression networks. They are typically generated using correlation statistics as pairwise similarity measures. Correlation-based methods are very useful in order to determine whether two genes have a strong global similarity but do not detect local similarities.</p> <p>Results</p> <p>We propose model trees as a method to identify gene interaction networks. While correlation-based methods analyze each pair of genes, in our approach we generate a single regression tree for each gene from the remaining genes. Finally, a graph from all the relationships among output and input genes is built taking into account whether the pair of genes is statistically significant. For this reason we apply a statistical procedure to control the false discovery rate. The performance of our approach, named R<smcaps>EG</smcaps>N<smcaps>ET</smcaps>, is experimentally tested on two well-known data sets: <it>Saccharomyces Cerevisiae </it>and E.coli data set. First, the biological coherence of the results are tested. Second the E.coli transcriptional network (in the Regulon database) is used as control to compare the results to that of a correlation-based method. This experiment shows that R<smcaps>EG</smcaps>N<smcaps>ET</smcaps> performs more accurately at detecting true gene associations than the Pearson and Spearman zeroth and first-order correlation-based methods.</p> <p>Conclusions</p> <p>R<smcaps>EG</smcaps>N<smcaps>ET</smcaps> generates gene association networks from gene expression data, and differs from correlation-based methods in that the relationship between one gene and others is calculated simultaneously. Model trees are very useful techniques to estimate the numerical values for the target genes by linear regression functions. They are very often more precise than linear regression models because they can add just different linear regressions to separate areas of the search space favoring to infer localized similarities over a more global similarity. Furthermore, experimental results show the good performance of R<smcaps>EG</smcaps>N<smcaps>ET</smcaps>.</p

Fulminant Staphylococcus lugdunensis septicaemia following a pelvic varicella-zoster virus infection in an immune-deficient patient: a case report

<p>Abstract</p> <p>Introduction</p> <p>The deadly threat of systemic infections with coagulase negative <it>Staphylococcus lugdunensis </it>despite an appropriate antibiotic therapy has only recently been recognized. The predominant infectious focus observed so far is left-sided native heart valve endocarditis, but bone and soft tissue infections, septicaemia and vascular catheter-related bloodstream infections have also been reported. We present a patient with a fatal <it>Staphylococcus lugdunensis </it>septicaemia following zoster bacterial superinfection of the pelvic region.</p> <p>Case presentation</p> <p>A 71-year old male diagnosed with IgG kappa plasmocytoma presented with a conspicuous weight loss, a hypercalcaemic crisis and acute renal failure. After initiation of haemodialysis treatment his condition improved rapidly. However, he developed a varicella-zoster virus infection of the twelfth thoracic dermatome requiring intravenous acyclovir treatment. Four days later the patient presented with a fulminant septicaemia. Despite an early intravenous antibiotic therapy with ciprofloxacin, piperacillin/combactam and vancomycin the patient died within 48 hours, shortly before the infective isolate was identified as <it>Staphylococcus lugdunensis </it>by polymerase chain reaction.</p> <p>Conclusion</p> <p>Despite <it>S. lugdunensis </it>belonging to the family of coagulase-negative staphylococci with an usually low virulence, infections with <it>S. lugdunensis </it>may be associated with an aggressive course and high mortality. This is the first report on a <it>Staphylococcus lugdunensis </it>septicaemia following a zoster bacterial superinfection of the pelvic region.</p

Gene expression markers of tendon fibroblasts in normal and diseased tissue compared to monolayer and three dimensional culture systems

<p>Abstract</p> <p>Background</p> <p>There is a paucity of data regarding molecular markers that identify the phenotype of the tendon cell. This study aims to quantify gene expression markers that distinguish between tendon fibroblasts and other mesenchymal cells which may be used to investigate tenogenesis.</p> <p>Methods</p> <p>Expression levels for 12 genes representative of musculoskeletal tissues, including the proposed tendon progenitor marker scleraxis, relative to validated reference genes, were evaluated in matched samples of equine tendon (harvested from the superficial digital flexor tendon), cartilage and bone using quantitative PCR (qPCR). Expression levels of genes associated with tendon phenotype were then evaluated in healthy, including developmental, and diseased equine tendon tissue and in tendon fibroblasts maintained in both monolayer culture and in three dimensional (3D) collagen gels.</p> <p>Results</p> <p>Significantly increased expression of scleraxis was found in tendon compared with bone (P = 0.002) but not compared to cartilage. High levels of COL1A2 and scleraxis and low levels of tenascin-C were found to be most representative of adult tensional tendon phenotype. While, relative expression of scleraxis in developing mid-gestational tendon or in acute or chronically diseased tendon did not differ significantly from normal adult tendon, tenascin-C message was significantly upregulated in acutely injured equine tendon (P = 0.001). Relative scleraxis gene expression levels in tendon cell monolayer and 3D cultures were significantly lower than in normal adult tendon (P = 0.002, P = 0.02 respectively).</p> <p>Conclusion</p> <p>The findings of this study indicate that high expression of both COL1A2 and scleraxis, and low expression of tenascin-C is representative of a tensional tendon phenotype. The <it>in vitro </it>culture methods used in these experiments however, may not recapitulate the phenotype of normal tensional tendon fibroblasts in tissues as evidenced by gene expression.</p

Mechanical Tension Increases CCN2/CTGF Expression and Proliferation in Gingival Fibroblasts via a TGFβ-Dependent Mechanism

Unlike skin, oral gingival do not scar in response to tissue injury. Fibroblasts, the cell type responsible for connective tissue repair and scarring, are exposed to mechanical tension during normal and pathological conditions including wound healing and fibrogenesis. Understanding how human gingival fibroblasts respond to mechanical tension is likely to yield valuable insights not only into gingival function but also into the molecular basis of scarless repair. CCN2/connective tissue growth factor is potently induced in fibroblasts during tissue repair and fibrogenesis. We subjected gingival fibroblasts to cyclical strain (up to 72 hours) using the Flexercell system and showed that CCN2 mRNA and protein was induced by strain. Strain caused the rapid activation of latent TGFβ, in a fashion that was reduced by blebbistatin and FAK/src inhibition, and the induction of endothelin (ET-1) mRNA and protein expression. Strain did not cause induction of α-smooth muscle actin or collagen type I mRNAs (proteins promoting scarring); but induced a cohort of pro-proliferative mRNAs and cell proliferation. Compared to dermal fibroblasts, gingival fibroblasts showed reduced ability to respond to TGFβ by inducing fibrogenic mRNAs; addition of ET-1 rescued this phenotype. Pharmacological inhibition of the TGFβ type I (ALK5) receptor, the endothelin A/B receptors and FAK/src significantly reduced the induction of CCN2 and pro-proliferative mRNAs and cell proliferation. Controlling TGFβ, ET-1 and FAK/src activity may be useful in controlling responses to mechanical strain in the gingiva and may be of value in controlling fibroproliferative conditions such as gingival hyperplasia; controlling ET-1 may be of benefit in controlling scarring in response to injury in the skin