Discovery of a potent nanoparticle P‐selectin antagonist with anti‐inflammatory effects in allergic airway disease

The severity of allergic asthma is dependent, in part, on the intensity of peribronchial inflammation. P‐selectin is known to play a role in the development of allergen‐induced peribronchial inflammation and airway hyperreactivity. Selective inhibitors of P‐selectin‐ mediated leukocyte endothelial‐cell interactions may therefore attenuate the inflammatory processes associated with allergic airway disease. Novel P‐selectin inhibitors were created using a polyvalent polymer nanoparticle capable of displaying multiple synthetic, low molecular weight ligands. By assembling a particle that presents an array of groups, which as monomers interact with only low affinity, we created a construct that binds extremely efficiently to P‐ selectin. The ligands acted as mimetics of the key binding elements responsible for the high‐ avidity adhesion of P‐selectin to the physiologic ligand, PSGL‐1. The inhibitors were initially evaluated using an in vitro shear assay system in which interactions between circulating cells and P‐selectin‐coated capillary tubes were measured. The nanoparticles were shown to preferentially bind to selectins expressed on activated endothelial cells. We subsequently demonstrated that nanoparticles displaying P‐selectin blocking arrays were functionally active in vivo, significantly reducing allergen‐induced airway hyperreactivity and peribronchial eosinophilic inflammation in a murine model of asthma.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154265/1/fsb2fj030166fje-sup-0001.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154265/2/fsb2fj030166fje.pd

The Naked Mole Rat Genome Resource: facilitating analyses of cancer and longevity-related adaptations

Motivation: The naked mole rat (Heterocephalus glaber) is an exceptionally long-lived and cancer-resistant rodent native to East Africa. Although its genome was previously sequenced, here we report a new assembly sequenced by us with substantially higher N50 values for scaffolds and contigs. Results: We analyzed the annotation of this new improved assembly and identified candidate genomic adaptations which may have contributed to the evolution of the naked mole rat’s extraordinary traits, including in regions of p53, and the hyaluronan receptors CD44 and HMMR (RHAMM). Furthermore, we developed a freely available web portal, the Naked Mole Rat Genome Resource (http://www.naked-mole-rat.org), featuring the data and results of our analysis, to assist researchers interested in the genome and genes of the naked mole rat, and also to facilitate further studies on this fascinating species. Availability and implementation: The Naked Mole Rat Genome Resource is freely available online at http://www.naked-mole-rat.org. This resource is open source and the source code is available at https://github.com/maglab/naked-mole-rat-portal. Contact: [email protected]

Comprehensive comparative analysis of RNA sequencing methods for degraded or low input samples

RNA-Seq is an effective method to study the transcriptome, but can be difficult to apply to scarce or degraded RNA from fixed clinical samples, rare cell populations, or cadavers. Recent studies have proposed several methods for RNA-Seq of low quality and/or low quantity samples, but their relative merits have not been systematically analyzed. Here, we compare five such methods using metrics relevant to transcriptome annotation, transcript discovery, and gene expression. Using a single human RNA sample, we constructed and sequenced ten libraries with these methods and two control libraries. We find that the RNase H method performed best for low quality RNA, and confirmed this with actual degraded samples. RNase H can even effectively replace oligo (dT) based methods for standard RNA-Seq. SMART and NuGEN had distinct strengths for low quantity RNA. Our analysis allows biologists to select the most suitable methods and provides a benchmark for future method development

A scalable, fully automated process for construction of sequence-ready human exome targeted capture libraries

Genome targeting methods enable cost-effective capture of specific subsets of the genome for sequencing. We present here an automated, highly scalable method for carrying out the Solution Hybrid Selection capture approach that provides a dramatic increase in scale and throughput of sequence-ready libraries produced. Significant process improvements and a series of in-process quality control checkpoints are also added. These process improvements can also be used in a manual version of the protocol

Enhanced methods for unbiased deep sequencing of Lassa and Ebola RNA viruses from clinical and biological samples

We have developed a robust RNA sequencing method for generating complete de novo assemblies with intra-host variant calls of Lassa and Ebola virus genomes in clinical and biological samples. Our method uses targeted RNase H-based digestion to remove contaminating poly(rA) carrier and ribosomal RNA. This depletion step improves both the quality of data and quantity of informative reads in unbiased total RNA sequencing libraries. We have also developed a hybrid-selection protocol to further enrich the viral content of sequencing libraries. These protocols have enabled rapid deep sequencing of both Lassa and Ebola virus and are broadly applicable to other viral genomics studies. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0519-7) contains supplementary material, which is available to authorized users

Comparative analysis of RNA sequencing methods for degraded or low-input samples

available in PMC 2014 January 01RNA-seq is an effective method for studying the transcriptome, but it can be difficult to apply to scarce or degraded RNA from fixed clinical samples, rare cell populations or cadavers. Recent studies have proposed several methods for RNA-seq of low-quality and/or low-quantity samples, but the relative merits of these methods have not been systematically analyzed. Here we compare five such methods using metrics relevant to transcriptome annotation, transcript discovery and gene expression. Using a single human RNA sample, we constructed and sequenced ten libraries with these methods and compared them against two control libraries. We found that the RNase H method performed best for chemically fragmented, low-quality RNA, and we confirmed this through analysis of actual degraded samples. RNase H can even effectively replace oligo(dT)-based methods for standard RNA-seq. SMART and NuGEN had distinct strengths for measuring low-quantity RNA. Our analysis allows biologists to select the most suitable methods and provides a benchmark for future method development.National Institutes of Health (U.S.) (Pioneer Award DP1-OD003958-01)National Human Genome Research Institute (U.S.) (NHGRI) 1P01HG005062-01)National Human Genome Research Institute (U.S.) (NHGRI Center of Excellence in Genome Science Award 1P50HG006193-01)Howard Hughes Medical Institute (Investigator)Merkin Family Foundation for Stem Cell ResearchBroad Institute of MIT and Harvard (Klarman Cell Observatory)National Human Genome Research Institute (U.S.) (NHGRI grant HG03067)Fonds voor Wetenschappelijk Onderzoek--Vlaandere

US Cosmic Visions: New Ideas in Dark Matter 2017: Community Report

This white paper summarizes the workshop "U.S. Cosmic Visions: New Ideas in Dark Matter" held at University of Maryland on March 23-25, 2017.Comment: 102 pages + reference