Project description:We described the integration of the general reversibility of glycosyltransferase-catalyzed reactions, artificial glycosyl donors, and a high throughput colorimetric screen to enable the engineering of glycosyltransferases for combinatorial sugar nucleotide synthesis. The best engineered catalyst from this study, the OleD Loki variant, contained the mutations P67T/I112P/T113M/S132F/A242I compared with the OleD wild-type sequence. Evaluated against the parental sequence OleD TDP16 variant used for screening, the OleD Loki variant displayed maximum improvements in k(cat)/K(m) of >400-fold and >15-fold for formation of NDP-glucoses and UDP-sugars, respectively. This OleD Loki variant also demonstrated efficient turnover with five variant NDP acceptors and six variant 2-chloro-4-nitrophenyl glycoside donors to produce 30 distinct NDP-sugars. This study highlights a convenient strategy to rapidly optimize glycosyltransferase catalysts for the synthesis of complex sugar nucleotides and the practical synthesis of a unique set of sugar nucleotides.
Project description:We present a new heteroditopic ligand (3pyCCMoid) that contains the typical skeleton of a curcuminoid (CCMoid) decorated with two 3-pyridyl groups. The coordination of 3pyCCMoid with ZnII centres results in a set of novel coordination polymers (CPs) that display different architectures and dimensionalities (from 1D to 3D). Our work analyses how synthetic methods and slight changes in the reaction conditions affect the formation of the final materials. Great efforts have been devoted toward understanding the coordination entities that provide high dimensional systems, with emphasis on the characterization of 2D materials, including analyses of different types of substrates, stability and exfoliation in water. Here, we foresee the great use of CCMoids in the field of CPs and emphasize 3pyCCMoid as a new-born linker.
Project description:Purpose of reviewDiamond Blackfan anemia (DBA) is an inherited bone marrow failure syndrome characterized by erythroid failure, congenital anomalies and predisposition to cancer. Recently, the notion of DBA as a disorder of ribosome biogenesis has been clarified. Correlations between molecular underpinnings and disease pathophysiology, while elusive, are beginning to emerge. Advances in these areas will be explored in this review.Recent findingsAll known genes mutated in DBA encode ribosomal proteins associated with either the small (RPS) or large (RPL) subunit and in these cases ribosomal protein haploinsufficiency gives rise to the disease. The number of genes affected, their potential interactions with the environment and modifier genes, and the myriad of potential signaling pathways linking abortive ribosome synthesis to cell-cycle regulators may all contribute to disease heterogeneity. Genotype/phenotype relationships emerging over the past year promise to shed light on these complex interrelationships and their role in DBA pathophysiology.SummaryThe nosology of DBA has recently expanded to include two distinct disease categories: a classical inherited bone marrow failure syndrome and a 'ribosomopathy'. The description of DBA as a ribosomopathy has provided a context for scientific inquiry analogous to the description of Fanconi anemia as a disorder of DNA repair.
Project description:Background:Group A Streptococcus (GAS) skin infections are particularly prevalent in developing nations. The GAS M protein, by which strains are differentiated into >220 different emm types, is immunogenic and elicits protective antibodies. A major obstacle for vaccine development has been the traditional understanding that immunity following infection is restricted to a single emm type. However, recent evidence has led to the hypothesis of immune cross-reactivity between emm types. Methods:We investigated the human serological response to GAS impetigo in Fijian schoolchildren, focusing on 3 major emm clusters (E4, E6, and D4). Pre- and postinfection sera were assayed by enzyme-linked immunosorbent assay with N-terminal M peptides and bactericidal assays using the infecting-type strain, emm cluster-related strains, and nonrelated strains. Results:Twenty of the 53 paired sera demonstrated a ?4-fold increase in antibody titer against the infecting type. When tested against all cluster-related M peptides, we found that 9 of 17 (53%) paired sera had a ?4-fold increase in antibody titer to cluster-related strains as well. When grouped by cluster, the mean change to cluster-related emm types in E4 and E6 was >4-fold (5.9-fold and 19.5-fold, respectively) but for D4 was 3.8-fold. The 17 paired sera were tested in bactericidal assays against selected cluster-related and nonrelated strains. While the responses were highly variable, numerous instances of cross-reactive killing were observed. Conclusions:These data demonstrate that M type-specific and cross-reactive immune responses occur following skin infection. The cross-reactive immune responses frequently align with emm clusters, raising new opportunities to design multivalent vaccines with broad coverage.
Project description:Motivation:Network biology is widely used to elucidate mechanisms of disease and biological processes. The ability to interact with biological networks is important for hypothesis generation and to give researchers an intuitive understanding of the data. We present visJS2jupyter, a tool designed to embed interactive networks in Jupyter notebooks to streamline network analysis and to promote reproducible research. Results:The tool provides functions for performing and visualizing useful network operations in biology, including network overlap, network propagation around a focal set of genes, and co-localization of two sets of seed genes. visJS2jupyter uses the JavaScript library vis.js to create interactive networks displayed within Jupyter notebook cells with features including drag, click, hover, and zoom. We demonstrate the functionality of visJS2jupyter applied to a biological question, by creating a network propagation visualization to prioritize risk-related genes in autism. Availability and implementation:The visJS2jupyter package is distributed under the MIT License. The source code, documentation and installation instructions are freely available on GitHub at https://github.com/ucsd-ccbb/visJS2jupyter. The package can be downloaded at https://pypi.python.org/pypi/visJS2jupyter. Contact:sbrosenthal@ucsd.edu. Supplementary information:Supplementary data are available at Bioinformatics online.
Project description:Neuron classification is an important component in analyzing network structure and quantifying the effect of neuron topology on signal processing. Current quantification and classification approaches rely on morphology projection onto lower-dimensional spaces. In this paper a 3D visualization and quantification tool is presented. The Density Visualization Pipeline (DVP) computes, visualizes and quantifies the density distribution, i.e., the "mass" of interneurons. We use the DVP to characterize and classify a set of GABAergic interneurons. Classification of GABAergic interneurons is of crucial importance to understand on the one hand their various functions and on the other hand their ubiquitous appearance in the neocortex. 3D density map visualization and projection to the one-dimensional x, y, z subspaces show a clear distinction between the studied cells, based on these metrics. The DVP can be coupled to computational studies of the behavior of neurons and networks, in which network topology information is derived from DVP information. The DVP reads common neuromorphological file formats, e.g., Neurolucida XML files, NeuroMorpho.org SWC files and plain ASCII files. Full 3D visualization and projections of the density to 1D and 2D manifolds are supported by the DVP. All routines are embedded within the visual programming IDE VRL-Studio for Java which allows the definition and rapid modification of analysis workflows.
Project description:SummaryOne approach to infer functions of new proteins from their homologs utilizes visualization of an all-against-all pairwise similarity network (A2ApsN) that exploits the speed of BLAST and avoids the complexity of multiple sequence alignment. However, identifying functions of the protein clusters in A2ApsN is never trivial, due to a lack of linking characterized proteins to their relevant information in current software packages. Given the database errors introduced by automatic annotation transfer, functional deduction should be made from proteins with experimental studies, i.e. 'reference proteins'. Here, we present a web server, termed Pclust, which provides a user-friendly interface to visualize the A2ApsN, placing emphasis on such 'reference proteins' and providing access to their full information in source databases, e.g. articles in PubMed. The identification of 'reference proteins' and the ease of cross-database linkage will facilitate understanding the functions of protein clusters in the network, thus promoting interpretation of proteins of interest.AvailabilityThe Pclust server is freely available at http://prodata.swmed.edu/pclust
Project description:SummaryNAViGaTOR is a powerful graphing application for the 2D and 3D visualization of biological networks. NAViGaTOR includes a rich suite of visual mark-up tools for manual and automated annotation, fast and scalable layout algorithms and OpenGL hardware acceleration to facilitate the visualization of large graphs. Publication-quality images can be rendered through SVG graphics export. NAViGaTOR supports community-developed data formats (PSI-XML, BioPax and GML), is platform-independent and is extensible through a plug-in architecture.AvailabilityNAViGaTOR is freely available to the research community from http://ophid.utoronto.ca/navigator/. Installers and documentation are provided for 32- and 64-bit Windows, Mac, Linux and Unix.Contactjuris@ai.utoronto.caSupplementary informationSupplementary data are available at Bioinformatics online.
Project description:Visualization plays a central role in the analysis of biochemical network models to identify patterns that arise from reaction dynamics and perform model exploratory analysis. To facilitate these analyses, we developed PyViPR, a visualization tool that generates static and dynamic representations of biochemical network processes within a Python-based environment. PyViPR embeds network visualizations within Jupyter notebooks, thus enabling integration with modeling, simulation, and analysis workflows. To present the capabilities of PyViPR, we explore execution mechanisms of extrinsic apoptosis in HeLa cells. We show that community-detection algorithms identify groups of molecular species that capture key biological functions and ease exploration of the apoptosis network. We then show how different kinetic parameter sets that fit the experimental data equally well exhibit significantly different signal-execution dynamics as the system progresses toward mitochondrial outer-membrane permeabilization. Therefore, PyViPR aids the conceptual understanding of dynamic network processes and accelerates hypothesis generation for further testing and validation.