Mouse models of rhinovirus-induced disease and exacerbation of allergic airway inflammation

Rhinoviruses cause serious morbidity and mortality as the major etiological agents of asthma exacerbations and the common cold. A major obstacle to understanding disease pathogenesis and to the development of effective therapies has been the lack of a small-animal model for rhinovirus infection. Of the 100 known rhinovirus serotypes, 90% (the major group) use human intercellular adhesion molecule-1 (ICAM-1) as their cellular receptor and do not bind mouse ICAM-1; the remaining 10% (the minor group) use a member of the low-density lipoprotein receptor family and can bind the mouse counterpart. Here we describe three novel mouse models of rhinovirus infection: minor-group rhinovirus infection of BALB/c mice, major-group rhinovirus infection of transgenic BALB/c mice expressing a mouse-human ICAM-1 chimera and rhinovirus-induced exacerbation of allergic airway inflammation. These models have features similar to those observed in rhinovirus infection in humans, including augmentation of allergic airway inflammation, and will be useful in the development of future therapies for colds and asthma exacerbations

SnugDock: Paratope Structural Optimization during Antibody-Antigen Docking Compensates for Errors in Antibody Homology Models

High resolution structures of antibody-antigen complexes are useful for analyzing the binding interface and to make rational choices for antibody engineering. When a crystallographic structure of a complex is unavailable, the structure must be predicted using computational tools. In this work, we illustrate a novel approach, named SnugDock, to predict high-resolution antibody-antigen complex structures by simultaneously structurally optimizing the antibody-antigen rigid-body positions, the relative orientation of the antibody light and heavy chains, and the conformations of the six complementarity determining region loops. This approach is especially useful when the crystal structure of the antibody is not available, requiring allowances for inaccuracies in an antibody homology model which would otherwise frustrate rigid-backbone docking predictions. Local docking using SnugDock with the lowest-energy RosettaAntibody homology model produced more accurate predictions than standard rigid-body docking. SnugDock can be combined with ensemble docking to mimic conformer selection and induced fit resulting in increased sampling of diverse antibody conformations. The combined algorithm produced four medium (Critical Assessment of PRediction of Interactions-CAPRI rating) and seven acceptable lowest-interface-energy predictions in a test set of fifteen complexes. Structural analysis shows that diverse paratope conformations are sampled, but docked paratope backbones are not necessarily closer to the crystal structure conformations than the starting homology models. The accuracy of SnugDock predictions suggests a new genre of general docking algorithms with flexible binding interfaces targeted towards making homology models useful for further high-resolution predictions

Synthetic Biology Open Language Visual (SBOL Visual) Version 2.1

People who are engineering biological organisms often find it useful to communicate in diagrams, both about the structure of the nucleic acid sequences that they are engineering and about the functional relationships between sequence features and other molecular species . Some typical practices and conventions have begun to emerge for such diagrams. The Synthetic Biology Open Language Visual (SBOL Visual) has been developed as a standard for organizing and systematizing such conventions in order to produce a coherent language for expressing the structure and function of genetic designs. This document details version 2.1 of SBOL Visual, which builds on the prior SBOL Visual 2.0 standard by expanding diagram syntax to include methods for showing modular structure and mappings between elements of a system, interactions arrows that can split or join (with the glyph at the split or join indicating either superposition or a chemical process), and adding new glyphs for indicating genomic context (e.g., integration into a plasmid or genome) and for stop codons

Enrollment bias: frequency and impact on patient selection in endovascular stroke trials.

BackgroundSelection bias may have affected enrollment in first generation endovascular stroke trials. We investigate, evaluate, and quantify such bias for these trials at our institution.MethodsDemographic, clinical, imaging, and angiographic data were prospectively collected on a consecutive cohort of patients with acute ischemic stroke who were enrolled in formal trials of endovascular stroke therapy (EST) or received EST in clinical practice outside of a randomized trial for acute cerebral ischemia at a single tertiary referral center from September 2004 to December 2012.ResultsAmong patients considered appropriate for EST in practice, 47% were eligible for trials, with rates for individual trials ranging from 17% to 70%. Compared with trial ineligible patients treated with EST, trial eligible patients were younger (67 vs. 74 years; p<0.05), more often treated with intravenous tissue plasminogen activator (53% vs. 34%; p<0.01), and had shorter last known well to puncture times (328 vs. 367 min; p<0.05). Focusing on the largest trial with a non-interventional control arm, compared with trial eligible patients treated with EST outside the trial, enrolled patients presented later (274 vs. 163 min; p<0.001), had higher National Institutes of Health Stroke Scale scores (20 vs. 17; p<0.05), and larger strokes (diffusion weighted imaging volumes 49 vs. 18; p<0.001).ConclusionsThe majority of patients felt suitable for EST at our institution were excluded from recent trials. Formal entry criteria succeeded in selecting patients with better prognostic features, although many of these patients were treated outside of trials. Acknowledging and mitigating these biases will be crucial to ongoing investigations

Craniotomy: True Sham for Traumatic Brain Injury, or a Sham of a Sham?

Neurological dysfunction after traumatic brain injury (TBI) is caused by both the primary injury and a secondary cascade of biochemical and metabolic events. Since TBI can be caused by a variety of mechanisms, numerous models have been developed to facilitate its study. The most prevalent models are controlled cortical impact and fluid percussion injury. Both typically use “sham” (craniotomy alone) animals as controls. However, the sham operation is objectively damaging, and we hypothesized that the craniotomy itself may cause a unique brain injury distinct from the impact injury. To test this hypothesis, 38 adult female rats were assigned to one of three groups: control (anesthesia only); craniotomy performed by manual trephine; or craniotomy performed by electric dental drill. The rats were then subjected to behavioral testing, imaging analysis, and quantification of cortical concentrations of cytokines. Both craniotomy methods generate visible MRI lesions that persist for 14 days. The initial lesion generated by the drill technique is significantly larger than that generated by the trephine. Behavioral data mirrored lesion volume. For example, drill rats have significantly impaired sensory and motor responses compared to trephine or naïve rats. Finally, of the seven tested cytokines, KC-GRO and IFN-γ showed significant increases in both craniotomy models compared to naïve rats. We conclude that the traditional sham operation as a control confers profound proinflammatory, morphological, and behavioral damage, which confounds interpretation of conventional experimental brain injury models. Any experimental design incorporating “sham” procedures should distinguish among sham, experimentally injured, and healthy/naïve animals, to help reduce confounding factors

Synthetic Biology Open Language Visual (SBOL Visual) Version 2.1

People who are engineering biological organisms often find it useful to communicate in diagrams, both about the structure of the nucleic acid sequences that they are engineering and about the functional relationships between sequence features and other molecular species . Some typical practices and conventions have begun to emerge for such diagrams. The Synthetic Biology Open Language Visual (SBOL Visual) has been developed as a standard for organizing and systematizing such conventions in order to produce a coherent language for expressing the structure and function of genetic designs. This document details version 2.1 of SBOL Visual, which builds on the prior SBOL Visual 2.0 standard by expanding diagram syntax to include methods for showing modular structure and mappings between elements of a system, interactions arrows that can split or join (with the glyph at the split or join indicating either superposition or a chemical process), and adding new glyphs for indicating genomic context (e.g., integration into a plasmid or genome) and for stop codons