Polymorphism, genetic exchange and intragenic recombination of the aureolysin gene among Staphylococcus aureus strains

<p>Abstract</p> <p>Background</p> <p><it>Staphylococcus aureus </it>expresses several proteases, which are thought to contribute to the virulence of this bacterium. Here we focus on aureolysin, the major thermolysin-like metalloprotease. Despite the importance of aureolysin in the physiology and pathogenesis of <it>S. aureus</it>, relatively little information was so far available concerning the <it>aur </it>gene diversity and mobility within and between the major subdivisions of the <it>S. aureus </it>population. Therefore, an epidemiologically and genetically diverse collection of <it>S. aureus </it>strains was used to determine the range of aureolysin (<it>aur</it>) gene polymorphism.</p> <p>Results</p> <p>Sequence analyses support the conclusion that the <it>aur </it>gene occurs in two distinct types of related sequences. The <it>aur </it>gene was much more polymorphic but, at the same time, showed higher purifying selection than genes utilized for multilocus sequence typing (MLST). Gene trees constructed from <it>aur </it>and concatenated MLST genes revealed several putative assortative recombination events (<it>i.e</it>. entire <it>aur </it>gene exchanges) between divergent lineages of <it>S. aureus</it>. Evidence for intragenic recombination events (<it>i.e</it>. exchanges of internal <it>aur </it>segments) across <it>aur </it>genes was also found. The biochemical properties and substrate specificity of the two types of aureolysin purified to homogeneity were studied, revealing minor differences in their affinity to low molecular weight synthetic substrates.</p> <p>Conclusion</p> <p>Although numerous nucleotide differences were identified between the <it>aur </it>alleles studied, our findings showed that a strong purifying selection is acting on the <it>aur </it>gene. Moreover, our study distinguishes between homologous exchanges of the entire <it>aur </it>gene (assortative recombination) between divergent <it>S. aureus </it>lineages and recombination events within <it>aur </it>genes.</p

Treatment change as a predictor of outcome among patients with classic chronic graft-versus-host disease

We analyzed outcomes for 668 patients who had systemic treatment for chronic graft-versus-host disease (GVHD) to assess the utility of early treatment change for exacerbation of chronic GVHD as a surrogate for survival endpoints in clinical trials. Fifty-six percent of patients had treatment change within 2 years after diagnosis of chronic GVHD. The median onset of treatment change was 4.4 months (range, 0.3 – 50 months). The cumulative incidence of non-relapse mortality (NRM) at 2 years was 16%, and overall survival at 2 years was 74%. In time-dependent Cox models, treatment change was associated with an increase in risk of NRM (hazard ratio, 2.53; 95% CI, 1.7-3.7; p < .0001). The hazard ratio was attenuated by 6% per month of delay in treatment change. Our results confirm that exacerbation of chronic GVHD is associated with an increased risk of NRM and with decreased survival, but the strength of this association is not large enough to allow the use of early exacerbation as a surrogate for survival endpoints in clinical trials. Other measures of clinical benefit, such as response, will need to be developed as endpoints in phase II trials for patients with chronic GVHD

Getting Genetic Ancestry Right for Science and Society

There is a scientific and ethical imperative to embrace a multidimensional, continuous view of ancestry and move away from continental ancestry categorie

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Electron spin coherence exceeding seconds in high purity silicon

Silicon is undoubtedly one of the most promising semiconductor materials for spin-based information processing devices. Its highly advanced fabrication technology facilitates the transition from individual devices to large-scale processors, and the availability of an isotopically-purified $^{28}$Si form with no magnetic nuclei overcomes what is a main source of spin decoherence in many other materials. Nevertheless, the coherence lifetimes of electron spins in the solid state have typically remained several orders of magnitude lower than what can be achieved in isolated high-vacuum systems such as trapped ions. Here we examine electron spin coherence of donors in very pure $^{28}$Si material, with a residual $^{29}$Si concentration of less than 50 ppm and donor densities of $10^{14-15}$ per cm$^3$. We elucidate three separate mechanisms for spin decoherence, active at different temperatures, and extract a coherence lifetime $T_2$ up to 2 seconds. In this regime, we find the electron spin is sensitive to interactions with other donor electron spins separated by ~200 nm. We apply a magnetic field gradient in order to suppress such interactions and obtain an extrapolated electron spin $T_2$ of 10 seconds at 1.8 K. These coherence lifetimes are without peer in the solid state by several orders of magnitude and comparable with high-vacuum qubits, making electron spins of donors in silicon ideal components of a quantum computer, or quantum memories for systems such as superconducting qubits.Comment: 18 pages, 4 figures, supplementary informatio

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment