Jonathan van Eyll

Nrf2 defense pathway: Experimental evidence for its protective role in epilepsy

Epigenetic mechanisms involved in transcriptional regulation of multiple molecular pathways are potentially attractive therapeutic interventions for epilepsy, because single target therapies are unlikely to provide both anticonvulsant and disease‐modifying effects.

Shh-dependent differentiation of intestinal tissue from embryonic pancreas by activin A

The pancreas develops from the endoderm to give rise to ducts, acini and islets of Langerhans. This process involves extracellular signals of the Transforming Growth Factor β (TGFβ) family. The aim of this work was to study the effects of activin A, a member of this family, whose potential role in pancreas differentiation is controversial. To this end, we used pancreatic explants from E12.5 mouse embryos. In culture these explants exhibited spontaneous growth, epithelial morphogenesis and endocrine and exocrine differentiation. Exposure to activin A did not affect exocrine or endocrine differentiation. Surprisingly, activin A induced in the explants the appearance of a large contractile structure surrounded by a cylindrical epithelium, a thick basal lamina and a smooth muscle layer. This structure, the formation of which was prevented by follistatin, was typical of an intestinal wall. Consistent with this interpretation, activin A rapidly induced in the explants the mRNAs for fatty acid binding proteins (FABPs), which are markers of the intestine, but not of the pancreas. We also found that induction of the FABPs was preceded by induction of Sonic hedgehog (Shh), a known inducer of intestinal differentiation in the endoderm. Activin B induced neither Shh nor intestinal differentiation. The activin A-mediated intestinal differentiation was blocked by cyclopamine, an inhibitor of Hedgehog signaling, and it was mimicked by Shh. We conclude that activin A does not appear to affect the exocrine or endocrine components of the pancreas, but that it can promote differentiation of pancreatic tissue into intestine via a Shh-dependent mechanism. These findings illustrate the plasticity of differentiation programs in response to extracellular signals in the pancreas and they shed new light on the regulation of pancreas and intestinal development.

Mechanism of primitive duct formation in the pancreas and submandibular glands: a role for SDF-1

BackgroundThe exocrine pancreas is composed of a branched network of ducts connected to acini. They are lined by a monolayered epithelium that derives from the endoderm and is surrounded by mesoderm-derived mesenchyme. The morphogenic mechanisms by which the ductal network is established as well as the signaling pathways involved in this process are poorly understood.ResultsBy morphological analyzis of wild-type and mutant mouse embryos and using cultured embryonic explants we investigated how epithelial morphogenesis takes place and is regulated by chemokine signaling. Pancreas ontogenesis displayed a sequence of two opposite epithelial transitions. During the first transition, the monolayered and polarized endodermal cells give rise to tissue buds composed of a mass of non polarized epithelial cells. During the second transition the buds reorganize into branched and polarized epithelial monolayers that further differentiate into tubulo-acinar glands. We found that the second epithelial transition is controlled by the chemokine Stromal cell-Derived Factor (SDF)-1. The latter is expressed by the mesenchyme, whereas its receptor CXCR4 is expressed by the epithelium. Reorganization of cultured pancreatic buds into monolayered epithelia was blocked in the presence of AMD3100, a SDF-1 antagonist. Analyzis of sdf1 and cxcr4 knockout embryos at the stage of the second epithelial transition revealed transient defective morphogenesis of the ventral and dorsal pancreas. Reorganization of a globular mass of epithelial cells in polarized monolayers is also observed during submandibular glands development. We found that SDF-1 and CXCR4 are expressed in this organ and that AMD3100 treatment of submandibular gland explants blocks its branching morphogenesis.ConclusionIn conclusion, our data show that the primitive pancreatic ductal network, which is lined by a monolayered and polarized epithelium, forms by remodeling of a globular mass of non polarized epithelial cells. Our data also suggest that SDF-1 controls the branching morphogenesis of several exocrine tissues.

Cloning and embryonic expression pattern of the mouse Onecut transcription factor OC-2.

Onecut (OC) transcription factors are evolutionarily conserved proteins with important developmental functions. They contain a bipartite DNA-binding domain composed of a single cut domain associated with a divergent homeodomain. The human genome contains three Onecut paralogues, Hnf6 (also called Oc1), Oc2 and Oc3. We describe here the cloning of mouse (m) OC-2 and its expression pattern in the mouse embryo. The mOc2 gene was localized on chromosome 18. Analysis of the mOC-2 amino acid sequence revealed overall identities of 67% with mHNF-6 and of 56% with mOC-3, and the presence of functional domains delineated earlier in HNF-6. The sequence of the 153 residue-long cut-homeodomain was very conserved, as it was 92% identical to that of mHNF-6 and 89% identical to that of mOC-3. In situ hybridization showed expression of mOc2 in the developing nervous system and gut endoderm. Like Hnf6, Oc2 was expressed in developing liver and pancreas. As many genes that are targeted by Onecut factors are recognized by both OC-2 and HNF-6, this overlap of expression patterns may have functional implications.

Pathway analysis from lists of microRNAs: common pitfalls and alternative strategy

MicroRNAs (miRNAs) are involved in the regulation of gene expression at a post-transcriptional level. As such, monitoring miRNA expression has been increasingly used to assess their role in regulatory mechanisms of biological processes. In large scale studies, once miRNAs of interest have been identified, the target genes they regulate are often inferred using algorithms or databases. A pathway analysis is then often performed in order to generate hypotheses about the relevant biological functions controlled by the miRNA signature. Here we show that the method widely used in scientific literature to identify these pathways is biased and leads to inaccurate results. In addition to describing the bias and its origin we present an alternative strategy to identify potential biological functions specifically impacted by a miRNA signature. More generally, our study exemplifies the crucial need of relevant negative controls when developing, and using, bioinformatics methods.

BED: a Biological Entity Dictionary based on a graph data model

The understanding of molecular processes involved in a specific biological system can be significantly improved by combining and comparing different data sets and knowledge resources. However, these information sources often use different identification systems and an identifier conversion step is required before any integration effort. Mapping between identifiers is often provided by the reference information resources and several tools have been implemented to simplify their use. However, most of these tools do not combine the information provided by individual resources to increase the completeness of the mapping process. Also, deprecated identifiers from former versions of databases are not taken into account. Finally, finding automatically the most relevant path to map identifiers from one scope to the other is often not trivial. The Biological Entity Dictionary (BED) addresses these three challenges by relying on a graph data model describing possible relationships between entities and their identifiers. This model has been implemented using Neo4j and an R package provides functions to query the graph but also to create and feed a custom instance of the database. This design combined with a local installation of the graph database and a cache system make BED very efficient to convert large lists of identifiers.

A computational framework for complex disease stratification from multiple large-scale datasets

BackgroundMultilevel data integration is becoming a major area of research in systems biology. Within this area, multi-‘omics datasets on complex diseases are becoming more readily available and there is a need to set standards and good practices for integrated analysis of biological, clinical and environmental data. We present a framework to plan and generate single and multi-‘omics signatures of disease states.MethodsThe framework is divided into four major steps: dataset subsetting, feature filtering, ‘omics-based clustering and biomarker identification.ResultsWe illustrate the usefulness of this framework by identifying potential patient clusters based on integrated multi-‘omics signatures in a publicly available ovarian cystadenocarcinoma dataset. The analysis generated a higher number of stable and clinically relevant clusters than previously reported, and enabled the generation of predictive models of patient outcomes.ConclusionsThis framework will help health researchers plan and perform multi-‘omics big data analyses to generate hypotheses and make sense of their rich, diverse and ever growing datasets, to enable implementation of translational P4 medicine.