Polycomb-dependent regulatory contacts between distant Hox loci in Drosophila.

In Drosophila melanogaster, Hox genes are organized in an anterior and a posterior cluster, called Antennapedia complex and bithorax complex, located on the same chromosome arm and separated by 10 Mb of DNA. Both clusters are repressed by Polycomb group (PcG) proteins. Here, we show that genes of the two Hox complexes can interact within nuclear PcG bodies in tissues where they are corepressed. This colocalization increases during development and depends on PcG proteins. Hox gene contacts are conserved in the distantly related Drosophila virilis species and they are part of a large gene interaction network that includes other PcG target genes. Importantly, mutations on one of the loci weaken silencing of genes in the other locus, resulting in the exacerbation of homeotic phenotypes in sensitized genetic backgrounds. Thus, the three-dimensional organization of Polycomb target genes in the cell nucleus stabilizes the maintenance of epigenetic gene silencing.

Next-Gen GWAS: full 2D epistatic interaction maps retrieve part of missing heritability and improve phenotypic prediction.

The problem of missing heritability requires the consideration of genetic interactions among different loci, called epistasis. Current GWAS statistical models require years to assess the entire combinatorial epistatic space for a single phenotype. We propose Next-Gen GWAS (NGG) that evaluates over 60 billion single nucleotide polymorphism combinatorial first-order interactions within hours. We apply NGG to Arabidopsis thaliana providing two-dimensional epistatic maps at gene resolution. We demonstrate on several phenotypes that a large proportion of the missing heritability can be retrieved, that it indeed lies in epistatic interactions, and that it can be used to improve phenotype prediction.

Reverse engineering highlights potential principles of large gene regulatory network design and learning.

Inferring transcriptional gene regulatory networks from transcriptomic datasets is a key challenge of systems biology, with potential impacts ranging from medicine to agronomy. There are several techniques used presently to experimentally assay transcription factors to target relationships, defining important information about real gene regulatory networks connections. These techniques include classical ChIP-seq, yeast one-hybrid, or more recently, DAP-seq or target technologies. These techniques are usually used to validate algorithm predictions. Here, we developed a reverse engineering approach based on mathematical and computer simulation to evaluate the impact that this prior knowledge on gene regulatory networks may have on training machine learning algorithms. First, we developed a gene regulatory networks-simulating engine called FRANK (Fast Randomizing Algorithm for Network Knowledge) that is able to simulate large gene regulatory networks (containing 104 genes) with characteristics of gene regulatory networks observed in vivo. FRANK also generates stable or oscillatory gene expression directly produced by the simulated gene regulatory networks. The development of FRANK leads to important general conclusions concerning the design of large and stable gene regulatory networks harboring scale free properties (built ex nihilo). In combination with supervised (accepting prior knowledge) support vector machine algorithm we (i) address biologically oriented questions concerning our capacity to accurately reconstruct gene regulatory networks and in particular we demonstrate that prior-knowledge structure is crucial for accurate learning, and (ii) draw conclusions to inform experimental design to performed learning able to solve gene regulatory networks in the future. By demonstrating that our predictions concerning the influence of the prior-knowledge structure on support vector machine learning capacity holds true on real data (Escherichia coli K14 network reconstruction using network and transcriptomic data), we show that the formalism used to build FRANK can to some extent be a reasonable model for gene regulatory networks in real cells.

Improvement of the interfacial compatibility between cellulose and poly(L-lactide) films by plasma-induced grafting of L-lactide: the evaluation of the adhesive properties using a peel test.

HYPOTHESIS: The interfacial compatibility between hydrophilic cellulose and hydrophobic poly(L-lactide) film surfaces is dependent on the interactions and interlocking of the macromolecular chains of the uppermost layers of both polymers. Grafting or coating the cellulose surface with molecular structures similar to the lactide monomer or oligomer is expected to improve the compatibility. Therefore, it should be possible to enhance the adhesive properties. EXPERIMENTS: Cellulose films were oxygen plasma treated and immersed in a L-lactide solution. The grafting was performed under various conditions (power, pressure, time). The treated cellulose and poly(L-lactide) films were hot-pressed, and the resulting bi-layer laminates were subjected to a peel test. Comparative experiments were performed with the bi-layer laminates prepared from the cellulose films coated with poly(L-lactide-graft-vinyl alcohol) copolymers. FINDINGS: X-ray photoelectron spectroscopy, infra-red analyses and wettability measurements revealed that chains bearing ester groups similar to that of lactide were covalently grafted onto the cellulose. The possible grafting mechanism that was initiated by the ionic species from the surface is discussed. As a result, the peel strength to separate the cellulose and the poly(L-lactide) films increased significantly. A comparison with data in the literature highlights the formation of entanglements inside the interfacial zone showing the efficiency of the plasma treatment.

Synthesis of antibacterial surfaces by plasma grafting of zinc oxide based nanocomposites onto polypropylene.

Antibacterial polymer surfaces were designed using ZnO nanoparticles as a bactericide. Mineral encapsulated nanoparticles were grafted onto activated polymer surfaces through their shells. Polypropylene (PP) surfaces were treated using an innovative process coupling core-shell technology and plasma grafting, well-known techniques commonly used to obtain active surfaces for biomedical applications. First, ZnO nanoparticles were encapsulated by (co)polymers: poly(acrylic acid) (PAA) or a poly(methyl methacrylate-co-methacrylic acid) copolymer [P(MMA-MA)]. Second, PP substrates were activated using plasma treatment. Finally, plasma-treated surfaces were immersed in solutions containing the encapsulated nanoparticles dispersed in an organic solvent and allowed to graft onto it. The presence of nanoparticles on the substrates was demonstrated using Fourier-Transform Infrared Spectroscopy (FTIR) analysis, Scanning Electron Microspcopy (SEM)/Energy-Dispersive X-ray (EDX), and Atomic Force Microscopy (AFM) studies. Indeed, the ZnO-functionalized substrates exhibited an antibacterial response in Escherichia coli adhesion tests. Moreover, this study revealed that, surprisingly, native ZnO nanoparticles without any previous functionalization could be directly grafted onto polymeric surfaces through plasma activation. The antibacterial activity of the resulting sample was shown to be comparable to that of the other samples.

Grafting of poly-L-lysine dendrigrafts onto polypropylene surface using plasma activation for ATP immobilization - Nanomaterial for potential applications in biotechnology.

The present work describes a new environmental friendly strategy for the development of surfaces with high amine density via the grafting of native or modified poly-L-lysine dendrigraft (DGL G3) onto plasma activated polypropylene (PP), polystyrene (PS), polyimide, and polytetrafluoroethylene (PTFE) surface. Modified DGL G3 was prepared by replacement of few peripheral amines by various functionalities. Grafting efficiency was determined by wettability measurements, IRTF, XPS, AFM, and by colorimetry using optimized Coomassie Brilliant Blue method tailored for surface analysis. It was shown that a 4-7nm DGL G3 monolayer with 4×10(14)aminecm(-)(2) was covalently grafted onto various surfaces. Immobilization of adenosine triphosphate on the DGL-g-PP material from dilute solution was studied by bioluminescence and proved the ability of the material to interact with polyanionic biological compounds: 1 ATP complex with 5 amine groups. So, this material has a potential use in diagnostic and more widely for biotechnology due to its high capacity for biomolecule immobilization.