Preliminary safety assessment of a membrane-bound delta 9 desaturase candidate protein for transgenic oilseed crops

AbstractA gene encoding delta 9 desaturase (D9DS), an integral membrane protein, is being considered for incorporation into oilseed crops to reduce saturated fatty acids and thus improve human nutritional value. Typically, a safety assessment for transgenic crops involves purifying heterologously produced transgenic proteins in an active form for use in safety studies. Membrane-bound proteins have been very difficult to isolate in an active form due to their inherent physicochemical properties. Described here are methods used to derive enriched preparations of the active D9DS protein for use in early stage safety studies. Results of these studies, in combination with bioinformatic results and knowledge of the mode of action of the protein, along with a history of safe consumption of related proteins, provides a weight of evidence supporting the safety of the D9DS protein in food and feed

Fast Computing Betweenness Centrality with Virtual Nodes on Large Sparse Networks

Betweenness centrality is an essential index for analysis of complex networks. However, the calculation of betweenness centrality is quite time-consuming and the fastest known algorithm uses time and space for weighted networks, where and are the number of nodes and edges in the network, respectively. By inserting virtual nodes into the weighted edges and transforming the shortest path problem into a breadth-first search (BFS) problem, we propose an algorithm that can compute the betweenness centrality in time for integer-weighted networks, where is the average weight of edges and is the average degree in the network. Considerable time can be saved with the proposed algorithm when , indicating that it is suitable for lightly weighted large sparse networks. A similar concept of virtual node transformation can be used to calculate other shortest path based indices such as closeness centrality, graph centrality, stress centrality, and so on. Numerical simulations on various randomly generated networks reveal that it is feasible to use the proposed algorithm in large network analysis

Experiences Building Globus Genomics: A Next-Generation Sequencing Analysis Service using Galaxy, Globus, and Amazon Web Services

ABSTRACT We describe Globus Genomics, a system that we have developed for rapid analysis of large quantities of next-generation sequencing (NGS) genomic data. This system achieves a high degree of end-to-end automation that encompasses every stage of data analysis including initial data retrieval from remote sequencing centers or storage (via the Globus file transfer system); specification, configuration, and reuse of multi-step processing pipelines (via the Galaxy workflow system); creation of custom Amazon Machine Images and on-demand resource acquisition via a specialized elastic provisioner (on Amazon EC2); and efficient scheduling of these pipelines over many processors (via the HTCondor scheduler). The system allows biomedical researchers to perform rapid analysis of large NGS datasets in a fully automated manner, without software installation or a need for any local computing infrastructure. We report performance and cost results for some representative workloads

Fast network centrality analysis using GPUs

<p>Abstract</p> <p>Background</p> <p>With the exploding volume of data generated by continuously evolving high-throughput technologies, biological network analysis problems are growing larger in scale and craving for more computational power. General Purpose computation on Graphics Processing Units (GPGPU) provides a cost-effective technology for the study of large-scale biological networks. Designing algorithms that maximize data parallelism is the key in leveraging the power of GPUs.</p> <p>Results</p> <p>We proposed an efficient data parallel formulation of the All-Pairs Shortest Path problem, which is the key component for shortest path-based centrality computation. A betweenness centrality algorithm built upon this formulation was developed and benchmarked against the most recent GPU-based algorithm. Speedup between 11 to 19% was observed in various simulated scale-free networks. We further designed three algorithms based on this core component to compute closeness centrality, eccentricity centrality and stress centrality. To make all these algorithms available to the research community, we developed a software package <it>gpu</it>-<it>fan </it>(GPU-based Fast Analysis of Networks) for CUDA enabled GPUs. Speedup of 10-50× compared with CPU implementations was observed for simulated scale-free networks and real world biological networks.</p> <p>Conclusions</p> <p><it>gpu</it>-<it>fan </it>provides a significant performance improvement for centrality computation in large-scale networks. Source code is available under the GNU Public License (GPL) at <url>http://bioinfo.vanderbilt.edu/gpu-fan/</url>.</p

Spider Silk Constructs Enhance Axonal Regeneration and Remyelination in Long Nerve Defects in Sheep

BACKGROUND: Surgical reapposition of peripheral nerve results in some axonal regeneration and functional recovery, but the clinical outcome in long distance nerve defects is disappointing and research continues to utilize further interventional approaches to optimize functional recovery. We describe the use of nerve constructs consisting of decellularized vein grafts filled with spider silk fibers as a guiding material to bridge a 6.0 cm tibial nerve defect in adult sheep. METHODOLOGY/PRINCIPAL FINDINGS: The nerve constructs were compared to autologous nerve grafts. Regeneration was evaluated for clinical, electrophysiological and histological outcome. Electrophysiological recordings were obtained at 6 months and 10 months post surgery in each group. Ten months later, the nerves were removed and prepared for immunostaining, electrophysiological and electron microscopy. Immunostaining for sodium channel (NaV 1.6) was used to define nodes of Ranvier on regenerated axons in combination with anti-S100 and neurofilament. Anti-S100 was used to identify Schwann cells. Axons regenerated through the constructs and were myelinated indicating migration of Schwann cells into the constructs. Nodes of Ranvier between myelin segments were observed and identified by intense sodium channel (NaV 1.6) staining on the regenerated axons. There was no significant difference in electrophysiological results between control autologous experimental and construct implantation indicating that our construct are an effective alternative to autologous nerve transplantation. CONCLUSIONS/SIGNIFICANCE: This study demonstrates that spider silk enhances Schwann cell migration, axonal regrowth and remyelination including electrophysiological recovery in a long-distance peripheral nerve gap model resulting in functional recovery. This improvement in nerve regeneration could have significant clinical implications for reconstructive nerve surgery

Primary Postnatal Dorsal Root Ganglion Culture from Conventionally Slaughtered Calves

Neurological disorders in ruminants have an important impact on veterinary health, but very few host-specific in vitro models have been established to study diseases affecting the nervous system. Here we describe a primary neuronal dorsal root ganglia (DRG) culture derived from calves after being conventionally slaughtered for food consumption. The study focuses on the in vitro characterization of bovine DRG cell populations by immunofluorescence analysis. The effects of various growth factors on neuron viability, neurite outgrowth and arborisation were evaluated by morphological analysis. Bovine DRG neurons are able to survive for more than 4 weeks in culture. GF supplementation is not required for neuronal survival and neurite outgrowth. However, exogenously added growth factors promote neurite outgrowth. DRG cultures from regularly slaughtered calves represent a promising and sustainable host specific model for the investigation of pain and neurological diseases in bovines