Structure-Activity Relationship for the Oxadiazole Class of Antibacterials

A structure-activity relationship (SAR) for the oxadiazole class of antibacterials was evaluated by syntheses of 72 analogs and determination of the minimal-inhibitory concentrations (MICs) against the ESKAPE panel of bacteria. Selected compounds were further evaluated for in vitro toxicity, plasma protein binding, pharmacokinetics (PK), and a mouse model of methicillin-resistant Staphylococcus aureus (MRSA) infection. Oxadiazole 72c shows potent in vitro antibacterial activity, exhibits low clearance, a high volume of distribution, and 41% oral bioavailability, and shows efficacy in mouse models of MRSA infection.Fil: Boudreau, Marc A.. University of Notre Dame; Estados UnidosFil: Ding, Derong. University of Notre Dame; Estados UnidosFil: Meisel, Jayda E.. University of Notre Dame; Estados UnidosFil: Janardhanan, Jeshina. University of Notre Dame; Estados UnidosFil: Spink, Edward. University of Notre Dame; Estados UnidosFil: Peng, Zhihong. University of Notre Dame; Estados UnidosFil: Qian, Yuanyuan. University of Notre Dame; Estados UnidosFil: Yamaguchi, Takao. University of Notre Dame; Estados UnidosFil: Testero, Sebastian Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina. University of Notre Dame; Estados UnidosFil: O'Daniel, Peter I.. University of Notre Dame; Estados UnidosFil: Leemans, Erika. University of Notre Dame; Estados UnidosFil: Lastochkin, Elena. University of Notre Dame; Estados UnidosFil: Song, Wei. University of Notre Dame; Estados UnidosFil: Schroeder, Valerie A.. University of Notre Dame; Estados UnidosFil: Wolter, William R.. University of Notre Dame; Estados UnidosFil: Suckow, Mark A.. University of Notre Dame; Estados UnidosFil: Mobashery, Shahriar. University of Notre Dame; Estados UnidosFil: Chang, Mayland. University of Notre Dame; Estados Unido

Structure-Activity Relationship for the Oxadiazole Class of Antibiotics

The structure-activity relationship (SAR) for the newly discovered oxadiazole class of antibiotics is described with evaluation of 120 derivatives of the lead structure. This class of antibiotics was discovered by in silico docking and scoring against the crystal structure of a penicillin-binding protein. They impair cell-wall biosynthesis and exhibit activities against the Gram-positive bacterium Staphylococcus aureus, including methicillin-resistant S. aureus (MRSA) and vancomycin-resistant and linezolid-resistant S. aureus. 5-(1H-Indol-5-yl)-3-(4-(4-(trifluoromethyl)phenoxy)phenyl)-1,2,4-oxadiazole (antibiotic 75b) was efficacious in a mouse model of MRSA infection, exhibiting a long half-life, a high volume of distribution, and low clearance. This antibiotic is bactericidal and is orally bioavailable in mice. This class of antibiotics holds great promise in recourse against infections by MRSA.Fil: Spink, Edward. University of Notre Dame-Indiana; Estados UnidosFil: Ding, Derong. University of Notre Dame-Indiana; Estados UnidosFil: Peng, Zhihong. University of Notre Dame-Indiana; Estados UnidosFil: Boudreau, Marc A.. University of Notre Dame-Indiana; Estados UnidosFil: Leemans, Erika. University of Notre Dame-Indiana; Estados UnidosFil: Lastochkin, Elena. University of Notre Dame-Indiana; Estados UnidosFil: Song, Wei. University of Notre Dame-Indiana; Estados UnidosFil: Lichtenwalter, Katerina. University of Notre Dame-Indiana; Estados UnidosFil: O’Daniel, Peter I.. University of Notre Dame-Indiana; Estados UnidosFil: Testero, Sebastian Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina. University of Notre Dame-Indiana; Estados UnidosFil: Pi, Hualiang. University of Notre Dame-Indiana; Estados UnidosFil: Schroeder, Valerie A.. University of Notre Dame-Indiana; Estados UnidosFil: Wolter, William R.. University of Notre Dame-Indiana; Estados UnidosFil: Antunes, Nuno T.. University of Notre Dame-Indiana; Estados UnidosFil: Suckow, Mark A.. University of Notre Dame-Indiana; Estados UnidosFil: Vakulenko, Sergei. University of Notre Dame-Indiana; Estados UnidosFil: Chang, Mayland. University of Notre Dame-Indiana; Estados UnidosFil: Mobashery, Shahriar. University of Notre Dame-Indiana; Estados Unido

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

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

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

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

Global wetland contribution to 2000-2012 atmospheric methane growth rate dynamics

Increasing atmospheric methane (CH4) concentrations have contributed to approximately 20% of anthropogenic climate change. Despite the importance of CH4 as a greenhouse gas, its atmospheric growth rate and dynamics over the past two decades, which include a stabilization period (1999–2006), followed by renewed growth starting in 2007, remain poorly understood. We provide an updated estimate of CH4 emissions from wetlands, the largest natural global CH4 source, for 2000–2012 using an ensemble of biogeochemical models constrained with remote sensing surface inundation and inventory-based wetland area data. Between 2000–2012, boreal wetland CH4 emissions increased by 1.2 Tg yr−1 (−0.2–3.5 Tg yr−1), tropical emissions decreased by 0.9 Tg yr−1 (−3.2−1.1 Tg yr−1), yet globally, emissions remained unchanged at 184 ± 22 Tg yr−1. Changing air temperature was responsible for increasing high-latitude emissions whereas declines in low-latitude wetland area decreased tropical emissions; both dynamics are consistent with features of predicted centennial-scale climate change impacts on wetland CH4 emissions. Despite uncertainties in wetland area mapping, our study shows that global wetland CH4 emissions have not contributed significantly to the period of renewed atmospheric CH4 growth, and is consistent with findings from studies that indicate some combination of increasing fossil fuel and agriculture-related CH4 emissions, and a decrease in the atmospheric oxidative sink

Measurement of the inclusive isolated-photon cross section in pp collisions at √s = 13 TeV using 36 fb−1 of ATLAS data

The differential cross section for isolated-photon production in pp collisions is measured at a centre-of-mass energy of 13 TeV with the ATLAS detector at the LHC using an integrated luminosity of 36.1 fb. The differential cross section is presented as a function of the photon transverse energy in different regions of photon pseudorapidity. The differential cross section as a function of the absolute value of the photon pseudorapidity is also presented in different regions of photon transverse energy. Next-to-leading-order QCD calculations from Jetphox and Sherpa as well as next-to-next-to-leading-order QCD calculations from Nnlojet are compared with the measurement, using several parameterisations of the proton parton distribution functions. The predictions provide a good description of the data within the experimental and theoretical uncertainties. [Figure not available: see fulltext.

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies