Respiratory Syncytial Virus Matrix Protein-Chromatin Association Is Key to Transcriptional Inhibition in Infected Cells

The morbidity and mortality caused by the globally prevalent human respiratory pathogen respiratory syncytial virus (RSV) approaches that world-wide of influenza. We previously demonstrated that the RSV matrix (M) protein shuttles, in signal-dependent fashion, between host cell nucleus and cytoplasm, and that this trafficking is central to RSV replication and assembly. Here we analyze in detail the nuclear role of M for the first time using a range of novel approaches, including quantitative analysis of de novo cell transcription in situ in the presence or absence of RSV infection or M ectopic expression, as well as in situ DNA binding. We show that M, dependent on amino acids 110–183, inhibits host cell transcription in RSV-infected cells as well as cells transfected to express M, with a clear correlation between nuclear levels of M and the degree of transcriptional inhibition. Analysis of bacterially expressed M protein and derivatives thereof mutated in key residues within M’s RNA binding domain indicates that M can bind to DNA as well as RNA in a cell-free system. Parallel results for point-mutated M derivatives implicate arginine 170 and lysine 172, in contrast to other basic residues such as lysine 121 and 130, as critically important residues for inhibition of transcription and DNA binding both in situ and in vitro. Importantly, recombinant RSV carrying arginine 170/lysine 172 mutations shows attenuated infectivity in cultured cells and in an animal model, concomitant with altered inflammatory responses. These findings define an RSV M-chromatin interface critical for host transcriptional inhibition in infection, with important implications for anti-RSV therapeutic development

KCC1 Activation protects Mice from the Development of Experimental Cerebral Malaria

Plasmodium falciparum malaria causes half a million deaths per year, with up to 9% of this mortality caused by cerebral malaria (CM). One of the major processes contributing to the development of CM is an excess of host inflammatory cytokines. Recently K+ signaling has emerged as an important mediator of the inflammatory response to infection; we therefore investigated whether mice carrying an ENU induced activation of the electroneutral K+ channel KCC1 had an altered response to Plasmodium berghei. Here we show that KCC1(M935K/M935K )mice are protected from the development of experimental cerebral malaria, and that this protection is associated with an increased CD4+ and TNFa response. This is the first description of a K+ channel affecting the development of experimental cerebral malaria.We would like to acknowledge Shelley Lampkin and Australian Phenomics Facility (APF) for the maintenance of the mouse colonies. Tis study was funded by the National Health and Medical Research Council of Australia (Program Grant 490037, and Project Grants 605524 and APP1047090), the National Collaborative Research Infrastructure Strategy (NCRIS), the Education Investment Fund from the Department of Education and Training, the Australian Phenomics Network, Howard Hughes Medical Institute and the Bill and Melinda Gates Foundation

Reproducibility of CRISPR-Cas9 methods for generation of conditional mouse alleles: A multi-center evaluation

Background CRISPR-Cas9 gene-editing technology has facilitated the generation of knockout mice, providing an alternative to cumbersome and time-consuming traditional embryonic stem cell-based methods. An earlier study reported up to 16% efficiency in generating conditional knockout (cKO or floxed) alleles by microinjection of 2 single guide RNAs (sgRNA) and 2 single-stranded oligonucleotides as donors (referred herein as “two-donor floxing” method). Results We re-evaluate the two-donor method from a consortium of 20 laboratories across the world. The dataset constitutes 56 genetic loci, 17,887 zygotes, and 1718 live-born mice, of which only 15 (0.87%) mice contain cKO alleles. We subject the dataset to statistical analyses and a machine learning algorithm, which reveals that none of the factors analyzed was predictive for the success of this method. We test some of the newer methods that use one-donor DNA on 18 loci for which the two-donor approach failed to produce cKO alleles. We find that the one-donor methods are 10- to 20-fold more efficient than the two-donor approach. Conclusion We propose that the two-donor method lacks efficiency because it relies on two simultaneous recombination events in cis, an outcome that is dwarfed by pervasive accompanying undesired editing events. The methods that use one-donor DNA are fairly efficient as they rely on only one recombination event, and the probability of correct insertion of the donor cassette without unanticipated mutational events is much higher. Therefore, one-donor methods offer higher efficiencies for the routine generation of cKO animal models.This work was supported by the National Collaborative Research Infrastructure (NCRIS) via the Australian Phenomics Network (APN) (to Gaetan Burgio and Paul Thomas), by an Institutional Development Award (PI: Shelley Smith) P20GM103471 (to CBG, RMQ, DWH, JDE, and RR), by NIGMS 1P30GM110768-01 and P30CA036727 (as part of support to University of Nebraska Mouse Genome Engineering and DNA Sequencing Cores), the British Heart Foundation FS12-57, FS12/57/29717, and CH/13/2/30154 and the program grant RG/15/12/31616 (to Kathryn Hentges and Bernard Keavney), the Wellcome Trust grants 107849/Z/ 15/Z, 097820/Z11/B, and 105610/Z/14/Z, the Medical Research Council MR/ N029992/1 (to DB and CBL), the National BioResource Project of Ministry of Education, Culture, Sports, Science and Technology/Japan Agency for Medical Research and Development (MEXT/AMED), Japan, the Canadian Institutes of Health Research MOP#142452 (MCB and LJM). LJM is a member of the Research Centre of the McGill University Health Centre which is supported in part by FQRS. Dr. William Thompson was supported by the Indiana Clinical and Translational Sciences Institute, funded in part by grant #UL1 TR001108 from the National Institute of Health (NIH), National Center for Advancing Translational Sciences, Clinical and Translational Sciences Award. KC Kent Lloyd is supported by the NIH (UM1OD023221), and work contributed by staff from the UC Davis Mouse Biology Program (MBP) is supported by a grant from the American College of Laboratory Animal Medicine. The work contributed from Xiande Liu, Chad Smith, Eric Jonasch, Xuesong Zhang, and Jan ParkerThornburg is supported by the NIH under the award number P30CA16672 (XL, CS, EJ, XZ, JPT) and R50CA211121 (JPT). Joseph Miano is supported by the NIH under the award number HL138987. R Sedlacek was supported by LM2015040 (Czech Centre for Phenogenomics), CZ.1.05/1.1.00/02.0109 (BIOCEV), and CZ.1.05/2.1.00/19.0395 by the Ministry of Education, Youth and Sports (MEYS) and by Academy of Sciences of the Czech Republic (RVO 68378050). David Ray was supported by a Wellcome Trust Investigator (107849/Z/15/Z) and the Medical Research Council (MR/P011853/1 and MR/P023576/) grants. Andrew Loudon was supported by a Wellcome Trust Investigator (107849/Z/15/Z), Biotechnology and Biological Sciences Research Council (BB/N015584/1), Medical Research Council (MR/P023576/1). The work contributed from Gloria Lopez-Castejon is supported by the Wellcome Trust (104192/Z/14/Z) and the Royal Society. Pilar Alcaide was supported by the NIH (HL 123658). The work contributed from Surinder K. Batra is supported by the NIH under the award number P01 CA217798

KCC1 Activation protects Mice from the Development of Experimental Cerebral Malaria

Abstract Plasmodium falciparum malaria causes half a million deaths per year, with up to 9% of this mortality caused by cerebral malaria (CM). One of the major processes contributing to the development of CM is an excess of host inflammatory cytokines. Recently K+ signaling has emerged as an important mediator of the inflammatory response to infection; we therefore investigated whether mice carrying an ENU induced activation of the electroneutral K+ channel KCC1 had an altered response to Plasmodium berghei. Here we show that Kcc1M935K/M935K mice are protected from the development of experimental cerebral malaria, and that this protection is associated with an increased CD4+ and TNFa response. This is the first description of a K+ channel affecting the development of experimental cerebral malaria

Simultaneous identification of m6A and m5C reveals coordinated RNA modification at single-molecule resolution

The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions, using signals from nanopore direct RNA sequencing. CHEUI processes observed and expected signals with convolutional neural networks to achieve high single-molecule accuracy and outperform other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions

Simultaneous identification of m6A and m5C reveals coordinated RNA modification at single-molecule resolution

The epitranscriptome embodies many new and largely unexplored functions of RNA. A major roadblock in the epitranscriptomics field is the lack of transcriptome-wide methods to detect more than a single RNA modification type at a time, identify RNA modifications in individual molecules, and estimate modification stoichiometry accurately. We address these issues with CHEUI (CH3 (methylation) Estimation Using Ionic current), a new method that concurrently detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual RNA molecules from the same sample, as well as differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals with convolutional neural networks to achieve high single-molecule accuracy and outperforms other methods in detecting m6A and m5C sites and quantifying their stoichiometry. CHEUI’s unique capability to identify two modification types in the same sample reveals a non-random co-occurrence of m6A and m5C in mRNA transcripts in cell lines and tissues. CHEUI unlocks an unprecedented potential to study RNA modification configurations and discover new epitranscriptome functions

Loss of intra-islet heparan sulfate is a highly sensitive marker of type 1 diabetes progression in humans

<div><p>Type 1 diabetes (T1D) is an autoimmune disease in which insulin-producing beta cells in pancreatic islets are progressively destroyed. Clinical trials of immunotherapies in recently diagnosed T1D patients have only transiently and partially impacted the disease course, suggesting that other approaches are required. Our previous studies have demonstrated that heparan sulfate (HS), a glycosaminoglycan conventionally expressed in extracellular matrix, is present at high levels inside normal mouse beta cells. Intracellular HS was shown to be critical for beta cell survival and protection from oxidative damage. T1D development in Non-Obese Diabetic (NOD) mice correlated with loss of islet HS and was prevented by inhibiting HS degradation by the endoglycosidase, heparanase. In this study we investigated the distribution of HS and heparan sulfate proteoglycan (HSPG) core proteins in normal human islets, a role for HS in human beta cell viability and the clinical relevance of intra-islet HS and HSPG levels, compared to insulin, in human T1D. In normal human islets, HS (identified by 10E4 mAb) co-localized with insulin but not glucagon and correlated with the HSPG core proteins for collagen type XVIII (Col18) and syndecan-1 (Sdc1). Insulin-positive islets of T1D pancreases showed significant loss of HS, Col18 and Sdc1 and heparanase was strongly expressed by islet-infiltrating leukocytes. Human beta cells cultured with HS mimetics showed significantly improved survival and protection against hydrogen peroxide-induced death, suggesting that loss of HS could contribute to beta cell death in T1D. We conclude that HS depletion in beta cells, possibly due to heparanase produced by insulitis leukocytes, may function as an important mechanism in the pathogenesis of human T1D. Our findings raise the possibility that intervention therapy with dual activity HS replacers/heparanase inhibitors could help to protect the residual beta cell mass in patients recently diagnosed with T1D.</p></div

HS optimizes human beta cell survival <i>in vitro</i>.

<p>Flow cytometry analyses of the viability of freshly isolated human islet cells (Con) on day 0 and after culture for 2 days with or without heparin, PI-88 or BT548 at 50 μg/ml. (<b>A-C</b>) Islet cells were stained with Newport Green (NG) to identify beta cells and with 7AAD (<b>B</b> and <b>C</b>) to label non-viable cells; NG+ve, 7AAD-ve staining identified viable beta cells (<b>C</b>). Con, control; Hep, Heparin; BT548, chemically modified LMWH. Data (% islet cells) shows mean ± SEM; n = 8–10 independent experiments and significance was measured by non-parametric ANOVA (Kruskal-Wallis test) with Dunn’s Multiple Comparisons test. * P<0.001, **P<0.01, ***P<0.05.</p

Intra-islet HS and HSPG core proteins in human pancreases correlate with insulin-positive beta cells.

<p>Immunohistochemical analyses of (<b>A-E</b>) a normal human pancreas (nPOD #6134) and (<b>F-J</b>) a pancreas with insulin-containing (Ins+) islets from a donor with T1D (nPOD #6084, 4 years post-T1D onset) show the distribution of (<b>B,G</b>) insulin-positive beta cells, intra-islet (<b>C,H</b>) HS, (<b>D,I</b>) Col18 core protein and (<b>E,J</b>) Sdc1 core protein. (<b>A,F</b>), H&E. Scale bar = 100 μm.</p