A genome-wide CRISPR/Cas9 screen reveals the requirement of host sphingomyelin synthase 1 for infection with Pseudorabies virus mutant gD–Pass

Herpesviruses are large DNA viruses, which encode up to 300 different proteins including enzymes enabling efficient replication. Nevertheless, they depend on a multitude of host cell proteins for successful propagation. To uncover cellular host factors important for replication of pseudorabies virus (PrV), an alphaherpesvirus of swine, we performed an unbiased genome-wide CRISPR/Cas9 forward screen. To this end, a porcine CRISPR-knockout sgRNA library (SsCRISPRko.v1) targeting 20,598 genes was generated and used to transduce porcine kidney cells. Cells were then infected with either wildtype PrV (PrV-Ka) or a PrV mutant (PrV-gD–Pass) lacking the receptor-binding protein gD, which regained infectivity after serial passaging in cell culture. While no cells survived infection with PrV-Ka, resistant cell colonies were observed after infection with PrV-gD–Pass. In these cells, sphingomyelin synthase 1 (SMS1) was identified as the top hit candidate. Infection efficiency was reduced by up to 90% for PrV-gD–Pass in rabbit RK13-sgms1KO cells compared to wildtype cells accompanied by lower viral progeny titers. Exogenous expression of SMS1 partly reverted the entry defect of PrV-gD–Pass. In contrast, infectivity of PrV-Ka was reduced by 50% on the knockout cells, which could not be restored by exogenous expression of SMS1. These data suggest that SMS1 plays a pivotal role for PrV infection, when the gD-mediated entry pathway is blocked

Reframing Kurtz’s Painting: Colonial Legacies and Minority Rights in Ethnically Divided Societies

Minority rights constitute some of the most normatively and economically important human rights. Although the political science and legal literatures have proffered a number of constitutional and institutional design solutions to address the protection of minority rights, these solutions are characterized by a noticeable neglect of, and lack of sensitivity to, historical processes. This Article addresses that gap in the literature by developing a causal argument that explains diverging practices of minority rights protections as functions of colonial governments’ variegated institutional practices with respect to particular ethnic groups. Specifically, this Article argues that in instances where colonial governments politicize and institutionalize ethnic hegemony in the pre-independence period, an institutional legacy is created that leads to lower levels of minority rights protections. Conversely, a uniform treatment and depoliticization of ethnicity prior to independence ultimately minimizes ethnic cleavages post-independence and consequently causes higher levels of minority rights protections. Through a highly structured comparative historical analysis of Botswana and Ghana, this Article builds on a new and exciting research agenda that focuses on the role of long-term historio-structural and institutional influences on human rights performance and makes important empirical contributions by eschewing traditional methodologies that focus on single case studies that are largely descriptive in their analyses. Ultimately, this Article highlights both the strength of a historical approach to understanding current variations in minority rights protections and the varied institutional responses within a specific colonial government

Toward interoperable bioscience data

© The Author(s), 2012. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Nature Genetics 44 (2012): 121-126, doi:10.1038/ng.1054.To make full use of research data, the bioscience community needs to adopt technologies and reward mechanisms that support interoperability and promote the growth of an open 'data commoning' culture. Here we describe the prerequisites for data commoning and present an established and growing ecosystem of solutions using the shared 'Investigation-Study-Assay' framework to support that vision.The authors also acknowledge the following funding sources in particular: UK Biotechnology and Biological Sciences Research Council (BBSRC) BB/I000771/1 to S.-A.S. and A.T.; UK BBSRC BB/I025840/1 to S.-A.S.; UK BBSRC BB/I000917/1 to D.F.; EU CarcinoGENOMICS (PL037712) to J.K.; US National Institutes of Health (NIH) 1RC2CA148222-01 to W.H. and the HSCI; US MIRADA LTERS DEB-0717390 and Alfred P. Sloan Foundation (ICoMM) to L.A.-Z.; Swiss Federal Government through the Federal Office of Education and Science (FOES) to L.B. and I.X.; EU Innovative Medicines Initiative (IMI) Open PHACTS 115191 to C.T.E.; US Department of Energy (DOE) DE-AC02- 06CH11357 and Arthur P. Sloan Foundation (2011- 6-05) to J.G.; UK BBSRC SysMO-DB2 BB/I004637/1 and BBG0102181 to C.G.; UK BBSRC BB/I000933/1 to C.S. and J.L.G.; UK MRC UD99999906 to J.L.G.; US NIH R21 MH087336 (National Institute of Mental Health) and R00 GM079953 (National Institute of General Medical Science) to A.L.; NIH U54 HG006097 to J.C. and C.E.S.; Australian government through the National Collaborative Research Infrastructure Strategy (NCRIS); BIRN U24-RR025736 and BioScholar RO1-GM083871 to G.B. and the 2009 Super Science initiative to C.A.S

Building consensus around the assessment and interpretation of Symbiodiniaceae diversity

Within microeukaryotes, genetic variation and functional variation sometimes accumulate more quickly than morphological differences. To understand the evolutionary history and ecology of such lineages, it is key to examine diversity at multiple levels of organization. In the dinoflagellate family Symbiodiniaceae, which can form endosymbioses with cnidarians (e.g., corals, octocorals, sea anemones, jellyfish), other marine invertebrates (e.g., sponges, molluscs, flatworms), and protists (e.g., foraminifera), molecular data have been used extensively over the past three decades to describe phenotypes and to make evolutionary and ecological inferences. Despite advances in Symbiodiniaceae genomics, a lack of consensus among researchers with respect to interpreting genetic data has slowed progress in the field and acted as a barrier to reconciling observations. Here, we identify key challenges regarding the assessment and interpretation of Symbiodiniaceae genetic diversity across three levels: species, populations, and communities. We summarize areas of agreement and highlight techniques and approaches that are broadly accepted. In areas where debate remains, we identify unresolved issues and discuss technologies and approaches that can help to fill knowledge gaps related to genetic and phenotypic diversity. We also discuss ways to stimulate progress, in particular by fostering a more inclusive and collaborative research community. We hope that this perspective will inspire and accelerate coral reef science by serving as a resource to those designing experiments, publishing research, and applying for funding related to Symbiodiniaceae and their symbiotic partnerships.journal articl

COordination of Standards in MetabOlomicS (COSMOS): facilitating integrated metabolomics data access

Metabolomics has become a crucial phenotyping technique in a range of research fields including medicine, the life sciences, biotechnology and the environmental sciences. This necessitates the transfer of experimental information between research groups, as well as potentially to publishers and funders. After the initial efforts of the metabolomics standards initiative, minimum reporting standards were proposed which included the concepts for metabolomics databases. Built by the community, standards and infrastructure for metabolomics are still needed to allow storage, exchange, comparison and re-utilization of metabolomics data. The Framework Programme 7 EU Initiative ‘coordination of standards in metabolomics’ (COSMOS) is developing a robust data infrastructure and exchange standards for metabolomics data and metadata. This is to support workflows for a broad range of metabolomics applications within the European metabolomics community and the wider metabolomics and biomedical communities’ participation. Here we announce our concepts and efforts asking for re-engagement of the metabolomics community, academics and industry, journal publishers, software and hardware vendors, as well as those interested in standardisation worldwide (addressing missing metabolomics ontologies, complex-metadata capturing and XML based open source data exchange format), to join and work towards updating and implementing metabolomics standards

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care(1) or hospitalization(2-4) after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes-including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)-in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease. © 2022, The Author(s)

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical Covid-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalisation2-4 following SARS-CoV-2 infection. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from critically-ill cases with population controls in order to find underlying disease mechanisms. Here, we use whole genome sequencing in 7,491 critically-ill cases compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical Covid-19. We identify 16 new independent associations, including variants within genes involved in interferon signalling (IL10RB, PLSCR1), leucocyte differentiation (BCL11A), and blood type antigen secretor status (FUT2). Using transcriptome-wide association and colocalisation to infer the effect of gene expression on disease severity, we find evidence implicating multiple genes, including reduced expression of a membrane flippase (ATP11A), and increased mucin expression (MUC1), in critical disease. Mendelian randomisation provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5, CD209) and coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of Covid-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication, or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between critically-ill cases and population controls is highly efficient for detection of therapeutically-relevant mechanisms of disease