Innocuous IFNγ induced by adjuvant-free antigen restores normoglycemia in NOD mice through inhibition of IL-17 production

The role of Th17 cells in type I diabetes (TID) remains largely unknown. Glutamic acid decarboxylase (GAD) sequence 206–220 (designated GAD2) represents a late-stage epitope, but GAD2-specific T cell receptor transgenic T cells producing interferon γ (IFNγ) protect against passive TID. Because IFNγ is known to inhibit Th17 cells, effective presentation of GAD2 peptide under noninflammatory conditions may protect against TID at advanced disease stages. To test this premise, GAD2 was genetically incorporated into an immunoglobulin (Ig) molecule to magnify tolerance, and the resulting Ig-GAD2 was tested against TID at different stages of the disease. The findings indicated that Ig-GAD2 could not prevent TID at the preinsulitis phase, but delayed TID at the insulitis stage. More importantly, Ig-GAD2 sustained both clearance of pancreatic cell infiltration and β-cell division and restored normoglycemia when given to hyperglycemic mice at the prediabetic stage. This was dependent on the induction of splenic IFNγ that inhibited interleukin (IL)-17 production. In fact, neutralization of IFNγ led to a significant increase in the frequency of Th17 cells, and the treatment became nonprotective. Thus, IFNγ induced by an adjuvant free antigen, contrary to its usual inflammatory function, restores normoglycemia, most likely by localized bystander suppression of pathogenic IL-17–producing cells

The Systems Biology Research Tool: evolvable open-source software

BACKGROUND: Research in the field of systems biology requires software for a variety of purposes. Software must be used to store, retrieve, analyze, and sometimes even to collect the data obtained from system-level (often high-throughput) experiments. Software must also be used to implement mathematical models and algorithms required for simulation and theoretical predictions on the system-level. RESULTS: We introduce a free, easy-to-use, open-source, integrated software platform called the Systems Biology Research Tool (SBRT) to facilitate the computational aspects of systems biology. The SBRT currently performs 35 methods for analyzing stoichiometric networks and 16 methods from fields such as graph theory, geometry, algebra, and combinatorics. New computational techniques can be added to the SBRT via process plug-ins, providing a high degree of evolvability and a unifying framework for software development in systems biology. CONCLUSION: The Systems Biology Research Tool represents a technological advance for systems biology. This software can be used to make sophisticated computational techniques accessible to everyone (including those with no programming ability), to facilitate cooperation among researchers, and to expedite progress in the field of systems biology

Exhaustive identification of steady state cycles in large stoichiometric networks

BACKGROUND: Identifying cyclic pathways in chemical reaction networks is important, because such cycles may indicate in silico violation of energy conservation, or the existence of feedback in vivo. Unfortunately, our ability to identify cycles in stoichiometric networks, such as signal transduction and genome-scale metabolic networks, has been hampered by the computational complexity of the methods currently used. RESULTS: We describe a new algorithm for the identification of cycles in stoichiometric networks, and we compare its performance to two others by exhaustively identifying the cycles contained in the genome-scale metabolic networks of H. pylori, M. barkeri, E. coli, and S. cerevisiae. Our algorithm can substantially decrease both the execution time and maximum memory usage in comparison to the two previous algorithms. CONCLUSION: The algorithm we describe improves our ability to study large, real-world, biochemical reaction networks, although additional methodological improvements are desirable

The Seventh Data Release of the Sloan Digital Sky Survey

This paper describes the Seventh Data Release of the Sloan Digital Sky Survey (SDSS), marking the completion of the original goals of the SDSS and the end of the phase known as SDSS-II. It includes 11663 deg^2 of imaging data, with most of the roughly 2000 deg^2 increment over the previous data release lying in regions of low Galactic latitude. The catalog contains five-band photometry for 357 million distinct objects. The survey also includes repeat photometry over 250 deg^2 along the Celestial Equator in the Southern Galactic Cap. A coaddition of these data goes roughly two magnitudes fainter than the main survey. The spectroscopy is now complete over a contiguous area of 7500 deg^2 in the Northern Galactic Cap, closing the gap that was present in previous data releases. There are over 1.6 million spectra in total, including 930,000 galaxies, 120,000 quasars, and 460,000 stars. The data release includes improved stellar photometry at low Galactic latitude. The astrometry has all been recalibrated with the second version of the USNO CCD Astrograph Catalog (UCAC-2), reducing the rms statistical errors at the bright end to 45 milli-arcseconds per coordinate. A systematic error in bright galaxy photometr is less severe than previously reported for the majority of galaxies. Finally, we describe a series of improvements to the spectroscopic reductions, including better flat-fielding and improved wavelength calibration at the blue end, better processing of objects with extremely strong narrow emission lines, and an improved determination of stellar metallicities. (Abridged)Comment: 20 pages, 10 embedded figures. Accepted to ApJS after minor correction

Analysis of protein-coding genetic variation in 60,706 humans

Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. We describe the aggregation and analysis of high-quality exome (protein-coding region) sequence data for 60,706 individuals of diverse ethnicities generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of truncating variants with 72% having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human “knockout” variants in protein-coding genes

Analysis of protein-coding genetic variation in 60,706 humans

Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human 'knockout' variants in protein-coding genes.Peer reviewe

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Severity and properties of cardiac damage caused by Streptococcus pneumoniae are strain dependent.

Streptococcus pneumoniae is an opportunistic Gram-positive pathogen that can cause invasive disease. Recent studies have shown that S. pneumoniae is able to invade the myocardium and kill cardiomyocytes, with one-in-five adults hospitalized for pneumococcal pneumonia having a pneumonia-associated adverse cardiac event. Furthermore, clinical reports have shown up to a 10-year increased risk of adverse cardiac events in patients formerly hospitalized for pneumococcal bacteremia. In this study, we investigated the ability of nine S. pneumoniae clinical isolates, representing eight unique serotypes, to cause cardiac damage in a mouse model of invasive disease. Following intraperitoneal challenge of C57BL/6 mice, four of these strains (D39, WU2, TIGR4, and 6A-10) caused high-grade bacteremia, while CDC7F:2617-97 and AMQ16 caused mid- and low-grade bacteremia, respectively. Three strains did not cause any discernible disease. Of note, only the strains capable of high-grade bacteremia caused cardiac damage, as inferred by serum levels of cardiac troponin-I. This link between bacteremia and heart damage was further corroborated by Hematoxylin & Eosin and Trichrome staining which showed cardiac cytotoxicity only in D39, WU2, TIGR4, and 6A-10 infected mice. Finally, hearts infected with these strains showed varying histopathological characteristics, such as differential lesion formation and myocytolysis, suggesting that the mechanism of heart damage varied between strains