Computational approaches to discovering differentiation genes in the peripheral nervous system of drosophila melanogaster

In the common fruit fly, Drosophila melanogaster, neural cell fate specification is triggered by a group of conserved transcriptional regulators known as proneural factors. Proneural factors induce neural fate in uncommitted neuroectodermal progenitor cells, in a process that culminates in sensory neuron differentiation. While the role of proneural factors in early fate specification has been described, less is known about the transition between neural specification and neural differentiation. The aim of this thesis is to use computational methods to improve the understanding of terminal neural differentiation in the Peripheral Nervous System (PNS) of Drosophila. To provide an insight into how proneural factors coordinate the developmental programme leading to neural differentiation, expression profiling covering the first 3 hours of PNS development in Drosophila embryos had been previously carried out by Cachero et al. [2011]. The study revealed a time-course of gene expression changes from specification to differentiation and suggested a cascade model, whereby proneural factors regulate a group of intermediate transcriptional regulators which are in turn responsible for the activation of specific differentiation target genes. In this thesis, I propose to select potentially important differentiation genes from the transcriptional data in Cachero et al. [2011] using a novel approach centred on protein interaction network-driven prioritisation. This is based on the insight that biological hypotheses supported by diverse data sources can represent stronger candidates for follow-up studies. Specifically, I propose the usage of protein interaction network data because of documented transcriptome-interactome correlations, which suggest that differentially expressed genes encode products that tend to belong to functionally related protein interaction clusters. Experimental protein interaction data is, however, remarkably sparse. To increase the informative power of protein-level analyses, I develop a novel approach to augment publicly available protein interaction datasets using functional conservation between orthologous proteins across different genomes, to predict interologs (interacting orthologs). I implement this interolog retrieval methodology in a collection of open-source software modules called Bio:: Homology::InterologWalk, the first generalised framework using web-services for “on-the- fly” interolog projection. Bio::Homology::InterologWalk works with homology data for any of the hundreds of genomes in Ensembl and Ensembgenomes Metazoa, and with experimental protein interaction data curated by EBI Intact. It generates putative protein interactions and optionally collates meta-data into a prioritisation index that can be used to help select interologs with high experimental support. The methodology proposed represents a significant advance over existing interolog data sources, which are restricted to specific biological domains with fixed underlying data sources often only accessible through basic web-interfaces. Using Bio::Homology::InterologWalk, I build interolog models in Drosophila sensory neurons and, guided by the transcriptome data, find evidence implicating a small set of genes in a conserved sensory neuronal specialisation dynamic, the assembly of the ciliary dendrite in mechanosensory neurons. Using network community-finding algorithms I obtain functionally enriched communities, which I analyse using an array of novel computational techniques. The ensuing datasets lead to the elucidation of a cluster of interacting proteins encoded by the target genes of one of the intermediate transcriptional regulators of neurogenesis and ciliogenesis, fd3F. These targets are validated in vivo and result in improved knowledge of the important target genes activated by the transcriptional cascade, suggesting a scenario for the mechanisms orchestrating the ordered assembly of the cilium during differentiation

Functionalized carbon nanotubes as a filler for dielectric elastomer composites with improved actuation performance

Among the broad class of electro-active polymers, dielectric elastomer actuators represent a rapidly growing technology for electromechanical transduction. In order to further develop this applied science, the high driving voltages currently needed must be reduced. For this purpose, one of the most widely considered approaches is based on making elastomeric composites with highly polarizable fillers in order to increase the dielectric constant while maintaining both low dielectric losses and high-mechanical compliance. In this work, multi-wall carbon nanotubes were first functionalized by grafting either acrylonitrile or diurethane monoacrylate oligomers, and then dispersed into a polyurethane matrix to make dielectric elastomer composites. The procedures for the chemical functionalization of carbon nanotubes and proper characterizations of the obtained products are provided in detail. The consequences of the use of chemically modified carbon nanotubes as a filler, in comparison to using unmodified ones, were studied in terms of dielectric, mechanical and electromechanical response. In particular, an increment of the dielectric constant was observed for all composites throughout the investigated frequency spectrum, but only in the cases of modified carbon nanotubes did the loss factor remain almost unchanged with respect to the simple matrix, indicating that conductive percolation paths did not arise in such systems. An effective improvement in the actuation strain was observed for samples loaded with functionalized carbon nanotubes

Crack growth behavior of SBR, NR and BR rubber compounds: comparison of Pure-Shear versus Strip Tensile test

Fatigue crack growth experiments on different carbon black–filled rubber compounds have been carried out to evaluate the influence of pure-shear and strip tensile testing mode by using sine and pulse as waveforms. In a previous set of experimental investigations regarding the influence of both waveform and tested material, it was found that the mode I of crack opening sometimes propagates too quickly to be properly monitored in tests involving strip-tensile specimens. An alternative test methodology based on pure-shear test mode has been investigated, optimizing both the shape of the specimen and the test equipment. Data obtained from the different compound formulations were consistent with the theoretical background and resulted in similar ranking of compound crack growth resistance for the two testing modes; in addition, pure-shear mode showed a higher sensitivity to formula variations

Most brain disease-associated and eQTL haplotypes are not located within transcription factor DNase-seq footprints in brain

Dense genotyping approaches have revealed much about the genetic architecture both of gene expression and disease susceptibility. However, assigning causality to genetic variants associated with a transcriptomic or phenotypic trait presents a far greater challenge. The development of epigenomic resources by ENCODE, the Epigenomic Roadmap and others has led to strategies that seek to infer the likely functional variants underlying these genome-wide association signals. It is known, for example, that such variants tend to be located within areas of open chromatin, as detected by techniques such as DNase-seq and FAIRE-seq. We aimed to assess what proportion of variants associated with phenotypic or transcriptomic traits in human brain are located within transcription factor binding sites. The bioinformatic tools, Wellington and HINT, were used to infer transcription factor footprints from existing DNase-seq data derived from central nervous system tissues with high spatial resolution. This dataset was then employed to assess the likely contribution of altered transcription factor binding to both expression quantitative trait loci (eQTL) and genome-wide association study (GWAS) signals. Surprisingly, we show that most haplotypes associated with GWAS or eQTL phenotypes are located outside of DNase-seq footprints. This could imply that DNase-seq footprinting is too insensitive an approach to identify a large proportion of true transcription factor binding sites. Importantly, this suggests that prioritising variants for genome engineering studies to establish causality will continue to be frustrated by an inability of footprinting to identify the causative variant within a haplotype

Renal progenitor cells revert LPS-induced endothelial-to-mesenchymal transition by secreting CXCL6, SAA4, and BPIFA2 antiseptic peptides

Endothelial dysfunction is a hallmark of LPS-induced acute kidney injury (AKI). Endothelial cells (ECs) acquired a fibroblast-like phenotype and contributed to myofibroblast generation through the endothelial-to-mesenchymal transition (EndMT) process. Of note, human adult renal stem/progenitor cells (ARPCs) enhance the tubular regenerative mechanism during AKI but little is known about their effects on ECs. Following LPS exposure, ECs proliferated, decreased EC markers CD31 and vascular endothelial cadherin, and up-regulated myofibroblast markers, collagen I, and vimentin. The coculture with ARPCs normalized the EC proliferation rate and abrogated the LPS-induced EndMT. The gene expression analysis showed that most of the genes modulated in LPS-stimulated ARPCs belong to cell activation and defense response pathways. We showed that the ARPC-specific antifibrotic effect is exerted by the secretion of CXCL6, SAA4, and BPIFA2 produced after the anaphylatoxin stimulation. Next, we investigated the molecular signaling that underlies the ARPC protective mechanism and found that renal progenitors diverge from differentiated tubular cells and ECs in myeloid differentiation primary response 88-independent pathway activation. Finally, in a swine model of LPS-induced AKI, we observed that activated ARPCs secreted CXCL6, SAA4, and BPIFA2 as a defense response. These data open new perspectives on the treatment of both sepsis- and endotoxemia-induced AKI, suggesting an underestimated role of ARPCs in preventing endothelial dysfunction and novel strategies to protect the endothelial compartment and promote kidney repair.-Sallustio, F., Stasi, A., Curci, C., Divella, C., Picerno, A., Franzin, R., De Palma, G., Rutigliano, M., Lucarelli, G., Battaglia, M., Staffieri, F., Crovace, A., Pertosa, G. B., Castellano, G., Gallone, A., Gesualdo, L. Renal progenitor cells revert LPS-induced endothelial-to-mesenchymal transition by secreting CXCL6, SAA4, and BPIFA2 antiseptic peptides

Nanomaterials-based strategies for piezoelectric cochlear implants

Nanomaterials-based strategies for piezoelectric cochlear implant

Design, fabrication and characterization of composite piezoelectric ultrafine fibers for cochlear stimulation

Sensorineural hearing loss, primed by dysfunction or death of hair cells in the cochlea, is the main cause of severe or profound deafness. Piezoelectric materials work similarly to hair cells, namely, as mechano-electrical transducers. Polyvinylidene fluoride (PVDF) films have demonstrated potential to replace the hair cell function, but the obtained piezoresponse was insufficient to stimulate effectively the auditory neurons. In this study, we reported on piezoelectric nanocomposites based on ultrafine PVDF fibers and barium titanate nanoparticles (BTNPs), as a strategy to improve the PVDF performance for this application. BTNP/PVDF fiber meshes were produced via rotating-disk electrospinning, up to 20/80 weight composition. The BTNP/PVDF fibers showed diameters ranging in 0.160-1.325 μm. Increasing collector velocity to 3000 rpm improved fiber alignment. The piezoelectric β phase of PVDF was well expressed following fabrication and the piezoelectric coefficients increased according to the BTNP weight ratio. The BTNP/PVDF fibers were not cytotoxic towards cochlear epithelial cells. Neural-like cells adhered to the composite fibers and, upon mechanical stimulation, showed enhanced viability. Using BTNP filler for PVDF matrices, in the form of aligned ultrafine fibers, increased the piezoresponse of PVDF transducers and favored neural cell contact. Piezoelectric nanostructured composites might find application in next generation cochlear implants

A transcriptomic study of Hereditary Angioedema attacks

Background: Hereditary angioedema (HAE) caused by C1-inhibitor deficiency is a lifelong illness characterized by recurrent acute attacks of localized skin or mucosal edema. Activation of the kallikrein/bradykinin pathway at the endothelial cell level has a relevant pathogenetic role in acute HAE attacks. Moreover, other pathways are involved given the variable clinical expression of the disease in different patients. Objective: We sought to explore the involvement of other putative genes in edema formation. Methods: We performed a PBMC microarray gene expression analysis on RNA isolated from patients with HAE during an acute attack and compared them with the transcriptomic profile of the same patients in the remission phase. Results: Gene expression analysis identified 23 genes significantly modulated during acute attacks that are involved primarily in the natural killer cell signaling and leukocyte extravasation signaling pathways. Gene set enrichment analysis showed a significant activation of relevant biological processes, such as response to external stimuli and protein processing (q < 0.05), suggesting involvement of PBMCs during acute HAE attacks. Upregulation of 2 genes, those encoding adrenomedullin and cellular receptor for urokinase plasminogen activator (uPAR), which occurs during an acute attack, was confirmed in PBMCs of 20 additional patients with HAE by using real-time PCR. Finally, in vitro studies demonstrated the involvement of uPAR in the generation of bradykinin and endothelial leakage. Conclusions: Our study demonstrates the increase in levels of adrenomedullin and uPAR in PBMCs during an acute HAE attack. Activation of these genes usually involved in regulation of vascular tone and in inflammatory response might have a pathogenic role by amplifying bradykinin production and edema formation in patients with HAE

Detecting cryptic clinically relevant structural variation in exome-sequencing data increases diagnostic yield for developmental disorders.

Structural variation (SV) describes a broad class of genetic variation greater than 50 bp in size. SVs can cause a wide range of genetic diseases and are prevalent in rare developmental disorders (DDs). Individuals presenting with DDs are often referred for diagnostic testing with chromosomal microarrays (CMAs) to identify large copy-number variants (CNVs) and/or with single-gene, gene-panel, or exome sequencing (ES) to identify single-nucleotide variants, small insertions/deletions, and CNVs. However, individuals with pathogenic SVs undetectable by conventional analysis often remain undiagnosed. Consequently, we have developed the tool InDelible, which interrogates short-read sequencing data for split-read clusters characteristic of SV breakpoints. We applied InDelible to 13,438 probands with severe DDs recruited as part of the Deciphering Developmental Disorders (DDD) study and discovered 63 rare, damaging variants in genes previously associated with DDs missed by standard SNV, indel, or CNV discovery approaches. Clinical review of these 63 variants determined that about half (30/63) were plausibly pathogenic. InDelible was particularly effective at ascertaining variants between 21 and 500 bp in size and increased the total number of potentially pathogenic variants identified by DDD in this size range by 42.9%. Of particular interest were seven confirmed de novo variants in MECP2, which represent 35.0% of all de novo protein-truncating variants in MECP2 among DDD study participants. InDelible provides a framework for the discovery of pathogenic SVs that are most likely missed by standard analytical workflows and has the potential to improve the diagnostic yield of ES across a broad range of genetic diseases