Introduction Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive interstitial lung disease with a dismal prognosis. While the standard-of-care (SOC) drugs approved for IPF represent a significant advancement in antifibrotic therapies, they primarily slow disease progression and have limited overall efficacy and many side effects. Consequently, IPF remains a condition with high unmet medical and pharmacological needs.
Rationale: Toll-like receptor (TLR) 7/8 ligands are promising candidate drugs for the treatment of allergic asthma and rhinitis. Although their clinical application depends on the development of strategies for topical administration to the lung, this has not been explored in preclinical disease models.Objectives: To examine the therapeutic effectiveness, persistence of effect, and mode of action of intranasal TLR7 ligand administration in allergic airway disease.Methods: Wild-type, IFN-α receptor (IFN-αR)−/−, IFN-γ−/−, CD8−/−, TLR7−/−, and radiation-induced chimeric mice deficient in hematopoietic TLR7 expression were subjected to an established model of allergic airway disease. R-848, a specific TLR7 agonist in mice, was administered prophylactically or therapeutically and effects of treatment on helper T-cell type 2 (Th2) responses, eosinophilia, goblet cell metaplasia, and airway hyperresponsiveness were assessed.Measurements and Main Results: Intranasal R-848 administration induced a transient immune response characterized by type I interferon production and infiltration of innate immune cells into the lung. This conferred long-term suppression of allergic airway disease via two complementary molecular processes, one mediated by type I interferons and providing acute protection by directly inhibiting effector Th2 responses, and one mediated by immunoregulatory CD8+ T cells and inducing long-lasting protection by suppressing Th2 responses in an IFN-γ–dependent manner.Conclusions: Intranasal R-848 administration is an effective treatment for allergic airway disease. It hijacks an otherwise proinflammatory immune process triggered by TLR7 to mediate long-lasting disease suppression. This provides important insight into the efficacy and mode of action of TLR7 ligands in murine models of allergic airway disease and paves the way for their clinical application in humans.
Following the technological advances that have enabled genome-wide analysis in most model organisms over the last decade, there has been unprecedented growth in genomic and post-genomic science with concomitant generation of an exponentially increasing volume of data and material resources. As a result, numerous repositories have been created to store and archive data, organisms and material, which are of substantial value to the whole community. Sustained access, facilitating re-use of these resources, is essential, not only for validation, but for re-analysis, testing of new hypotheses and developing new technologies/platforms. A common challenge for most data resources and biological repositories today is finding financial support for maintenance and development to best serve the scientific community. In this study we examine the problems that currently confront the data and resource infrastructure underlying the biomedical sciences. We discuss the financial sustainability issues and potential business models that could be adopted by biological resources and consider long term preservation issues within the context of mouse functional genomics efforts in Europe.
Microarray technology enables high-throughput parallel gene expression analysis, and use has grown exponentially thanks to the development of a variety of applications for expression, genetics and epigenetic studies. A wealth of data is now available from public repositories, providing unprecedented opportunities for meta-analysis approaches, which could generate new biological information, unrelated to the original scope of individual studies. This study provides a guideline for identification of biological significance of the statistically-selected differentially-expressed genes derived from gene expression arrays as well as to suggest further analysis pathways. The authors review the prerequisites for data-mining and meta-analysis, summarize the conceptual methods to derive biological information from microarray data and suggest software for each category of data mining or meta-analysis.
Autotaxin is a secreted lysophospholipase D which is a member of the ectonucleotide pyrophosphatase/phosphodiesterase family converting extracellular lysophosphatidylcholine and other non-choline lysophospholipids, such as lysophosphatidylethanolamine and lysophosphatidylserine, to the lipid mediator lysophosphatidic acid. Autotaxin is implicated in various fibroproliferative diseases including interstitial lung diseases such as idiopathic pulmonary fibrosis and hepatic fibrosis. In this study, we present an effort of identifying ATX inhibitors that bind to allosteric ATX binding sites using the Enalos Asclepios KNIME Node. All the available PDB crystal structures of ATX were collected, prepared, and aligned. Visual examination of these structures led to the identification of four crystal structures of human ATX co-crystallized with four known inhibitors. These inhibitors bind to five binding sites with five different binding modes. These five binding sites were thereafter used to virtually screen a compound library of 14,000 compounds to identify molecules that bind to allosteric sites. Based on the binding mode and interactions, the docking score, and the frequency that a compound comes up as a top-ranked among the five binding sites, 24 compounds were selected for in vitro testing. Finally, two compounds emerged with inhibitory activity against ATX in the low micromolar range, while their mode of inhibition and binding pattern were also studied. The two derivatives identified herein can serve as “hits” towards developing novel classes of ATX allosteric inhibitors.
Following the technological advances that have enabled genome-wide analysis in most model organisms over the last ten years, there has been unprecedented growth in genome and post-genomic sciences with concomitant generation of an exponentially increasing volume of data. As a result numerous resources have been created to store and archive the data and biological materials produced, which are of substantial value to the whole community. Sustained access facilitating re-use of this primary data is vital, not only for validation, but for re-analysis, testing of new hypotheses and developing new technologies/platforms. A common challenge for most data resources and biological repositories today is finding financial support for maintenance and development so as to best serve the scientific community. In this manuscript we examine the problems that currently confront the data and resource infrastructure underlying the biomedical sciences. We discuss the financial sustainability issues and potential business models that could be adopted by biological resources and consider long term data preservation issues within the context of mouse functional genomics efforts in Europe.
