Highly Pathogenic Avian Influenza Viruses and Generation of Novel Reassortants, United States, 2014–2015

Asian highly pathogenic avian influenza A(H5N8) viruses spread into North America in 2014 during autumn bird migration. Complete genome sequencing and phylogenetic analysis of 32 H5 viruses identified novel H5N1, H5N2, and H5N8 viruses that emerged in late 2014 through reassortment with North American low-pathogenicity avian influenza viruses

Highly Pathogenic Avian Influenza Viruses and Generation of Novel Reassortants, United States, 2014–2015

Asian highly pathogenic avian influenza A(H5N8) viruses spread into North America in 2014 during autumn bird migration. Complete genome sequencing and phylogenetic analysis of 32 H5 viruses identified novel H5N1, H5N2, and H5N8 viruses that emerged in late 2014 through reassortment with North American low-pathogenicity avian influenza viruses

2022 taxonomic update of phylum Negarnaviricota (Riboviria: Orthornavirae), including the large orders Bunyavirales and Mononegavirales

In March 2022, following the annual International Committee on Taxonomy of Viruses (ICTV) ratification vote on newly proposed taxa, the phylum Negarnaviricota was amended and emended. The phylum was expanded by two new families (bunyaviral Discoviridae and Tulasviridae), 41 new genera, and 98 new species. Three hundred forty-nine species were renamed and/or moved. The accidentally misspelled names of seven species were corrected. This article presents the updated taxonomy of Negarnaviricota as now accepted by the ICTV.Instituto de Patología VegetalFil: Kuhn, Jens H. National Institute of Allergy and Infectious Diseases. National Institutes of Health. Integrated Research Facility at Fort Detrick; Estados UnidosFil: Adkins, Scott. US Horticultural Research Laboratory. United States Department of Agriculture. Agricultural Research Service; Estados UnidosFil: Alkhovsky, Sergey V. Ministry of Health of Russian Federation. National Center on Epidemiology and Microbiology .D.I. Ivanovsky Institute of Virology of N.F. Gamaleya; RusiaFil: Avšič-Županc, Tatjana. University of Ljubljana. Faculty of Medicine. Institute of Microbiology and Immunology; EsloveniaFil: Ayllón, María A. Universidad Politécnica de Madrid. Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria.Centro de Biotecnología y Genómica de Plantas; EspañaFil: Ayllón, María A. Universidad Politécnica de Madrid. Escuela Técnica Superior de Ingeniería Agronómica, Alimentaria y de Biosistemas. Departamento de Biotecnología-Biología Vegetal; EspañaFil: Bahl, Justin. University of Georgia. Center for Ecology of Infectious Diseases. Insitute of Bioinformatics. Department of Infectious Diseases. Department of Epidemiology and Biostatistics; Estados UnidosFil: Balkema-Buschmann, Anne. Friedrich-Loeffler-Institut. Institute of Novel and Emerging Infectious Diseases; AlemaniaFil: Ballinger, Matthew J. Mississippi State University. Department of Biological Sciences; Estados UnidosFil: Bandte, Martina. Humboldt-Universität zu Berlin. Faculty of Life Sciences. Division Phytomedicine; AlemaniaFil: Beer, Martin. Friedrich-Loeffler-Institut. Institute of Diagnostic Virology; AlemaniaFil: Bejerman, Nicolas Esteban. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Patología Vegetal; ArgentinaFil: Bejerman, Nicolas Esteban. Consejo Nacional de Investigaciones Científicas y Técnicas. Unidad de Fitopatología y Modelización Agrícola (UFyMA); ArgentinaFil: Lodden Økland, Arnfnn. Pharmaq Analytiq; Norueg

Ecosystem Interactions Underlie the Spread of Avian Influenza A Viruses with Pandemic Potential

Despite evidence for avian influenza A virus (AIV) transmission between wild and domestic ecosystems, the roles of bird migration and poultry trade in the spread of viruses remain enigmatic. In this study, we integrate ecosystem interactions into a phylogeographic model to assess the contribution of wild and domestic hosts to AIV distribution and persistence. Analysis of globally sampled AIV datasets shows frequent two-way transmission between wild and domestic ecosystems. In general, viral flow from domestic to wild bird populations was restricted to within a geographic region. In contrast, spillover from wild to domestic populations occurred both within and between regions. Wild birds mediated long-distance dispersal at intercontinental scales whereas viral spread among poultry populations was a major driver of regional spread. Viral spread between poultry flocks frequently originated from persistent lineages circulating in regions of intensive poultry production. Our analysis of long-term surveillance data demonstrates that meaningful insights can be inferred from integrating ecosystem into phylogeographic reconstructions that may be consequential for pandemic preparedness and livestock protection.National Institutes of Health (U.S.) (NIH Centers for Excellence in Influenza Research and Surveillance (CEIRS, contract # HHSN266200700010C))National Institutes of Health (U.S.) (NIH Centers for Excellence in Influenza Research and Surveillance (CEIRS, contract # HHSN272201400008C))National Institutes of Health (U.S.) (NIH Centers for Excellence in Influenza Research and Surveillance (CEIRS, contract # HHSN272201400006C)

Annual (2023) taxonomic update of RNA-directed RNA polymerase-encoding negative-sense RNA viruses (realm Riboviria: kingdom Orthornavirae: phylum Negarnaviricota)

In April 2023, following the annual International Committee on Taxonomy of Viruses (ICTV) ratification vote on newly proposed taxa, the phylum Negarnaviricota was amended and emended. The phylum was expanded by one new family, 14 new genera, and 140 new species. Two genera and 538 species were renamed. One species was moved, and four were abolished. This article presents the updated taxonomy of Negarnaviricota as now accepted by the ICTV

Evolutionary Dynamics and Emergence of Panzootic H5N1 Influenza Viruses

The highly pathogenic avian influenza (HPAI) H5N1 virus lineage has undergone extensive genetic reassortment with viruses from different sources to produce numerous H5N1 genotypes, and also developed into multiple genetically distinct sublineages in China. From there, the virus has spread to over 60 countries. The ecological success of this virus in diverse species of both poultry and wild birds with frequent introduction to humans suggests that it is a likely source of the next human pandemic. Therefore, the evolutionary and ecological characteristics of its emergence from wild birds into poultry are of considerable interest. Here, we apply the latest analytical techniques to infer the early evolutionary dynamics of H5N1 virus in the population from which it emerged (wild birds and domestic poultry). By estimating the time of most recent common ancestors of each gene segment, we show that the H5N1 prototype virus was likely introduced from wild birds into poultry as a non-reassortant low pathogenic avian influenza H5N1 virus and was not generated by reassortment in poultry. In contrast, more recent H5N1 genotypes were generated locally in aquatic poultry after the prototype virus (A/goose/Guangdong/1/96) introduction occurred, i.e., they were not a result of additional emergence from wild birds. We show that the H5N1 virus was introduced into Indonesia and Vietnam 3–6 months prior to detection of the first outbreaks in those countries. Population dynamics analyses revealed a rapid increase in the genetic diversity of A/goose/Guangdong/1/96 lineage viruses from mid-1999 to early 2000. Our results suggest that the transmission of reassortant viruses through the mixed poultry population in farms and markets in China has selected HPAI H5N1 viruses that are well adapted to multiple hosts and reduced the interspecies transmission barrier of those viruses

Setting research priorities to improve global newborn health and prevent stillbirths by 2025.

BACKGROUND: In 2013, an estimated 2.8 million newborns died and 2.7 million were stillborn. A much greater number suffer from long term impairment associated with preterm birth, intrauterine growth restriction, congenital anomalies, and perinatal or infectious causes. With the approaching deadline for the achievement of the Millennium Development Goals (MDGs) in 2015, there was a need to set the new research priorities on newborns and stillbirth with a focus not only on survival but also on health, growth and development. We therefore carried out a systematic exercise to set newborn health research priorities for 2013-2025. METHODS: We used adapted Child Health and Nutrition Research Initiative (CHNRI) methods for this prioritization exercise. We identified and approached the 200 most productive researchers and 400 program experts, and 132 of them submitted research questions online. These were collated into a set of 205 research questions, sent for scoring to the 600 identified experts, and were assessed and scored by 91 experts. RESULTS: Nine out of top ten identified priorities were in the domain of research on improving delivery of known interventions, with simplified neonatal resuscitation program and clinical algorithms and improved skills of community health workers leading the list. The top 10 priorities in the domain of development were led by ideas on improved Kangaroo Mother Care at community level, how to improve the accuracy of diagnosis by community health workers, and perinatal audits. The 10 leading priorities for discovery research focused on stable surfactant with novel modes of administration for preterm babies, ability to diagnose fetal distress and novel tocolytic agents to delay or stop preterm labour. CONCLUSION: These findings will assist both donors and researchers in supporting and conducting research to close the knowledge gaps for reducing neonatal mortality, morbidity and long term impairment. WHO, SNL and other partners will work to generate interest among key national stakeholders, governments, NGOs, and research institutes in these priorities, while encouraging research funders to support them. We will track research funding, relevant requests for proposals and trial registers to monitor if the priorities identified by this exercise are being addressed

Setting research priorities to improve global newborn health and prevent stillbirths by 2025

Background In 2013, an estimated 2.8 million newborns died and 2.7 million were stillborn. A much greater number suffer from long term impairment associated with preterm birth, intrauterine growth restriction, congenital anomalies, and perinatal or infectious causes. With the approaching deadline for the achievement of the Millennium Development Goals (MDGs) in 2015, there was a need to set the new research priorities on newborns and stillbirth with a focus not only on survival but also on health, growth and development. We therefore carried out a systematic exercise to set newborn health research priorities for 2013-2025. Methods We used adapted Child Health and Nutrition Research Initiative (CHNRI) methods for this prioritization exercise. We identified and approached the 200 most productive researchers and 400 program experts, and 132 of them submitted research questions online. These were collated into a set of 205 research questions, sent for scoring to the 600 identified experts, and were assessed and scored by 91 experts. Results Nine out of top ten identified priorities were in the domain of research on improving delivery of known interventions, with simplified neonatal resuscitation program and clinical algorithms and improved skills of community health workers leading the list. The top 10 priorities in the domain of development were led by ideas on improved Kangaroo Mother Care at community level, how to improve the accuracy of diagnosis by community health workers, and perinatal audits. The 10 leading priorities for discovery research focused on stable surfactant with novel modes of administration for preterm babies, ability to diagnose fetal distress and novel tocolytic agents to delay or stop preterm labour. Conclusion These findings will assist both donors and researchers in supporting and conducting research to close the knowledge gaps for reducing neonatal mortality, morbidity and long term impairment. WHO, SNL and other partners will work to generate interest among key national stakeholders, governments, NGOs, and research institutes in these priorities, while encouraging research funders to support them. We will track research funding, relevant requests for proposals and trial registers to monitor if the priorities identified by this exercise are being addressed

2021 Taxonomic update of phylum Negarnaviricota (Riboviria: Orthornavirae), including the large orders Bunyavirales and Mononegavirales.

Correction to: 2021 Taxonomic update of phylum Negarnaviricota (Riboviria: Orthornavirae), including the large orders Bunyavirales and Mononegavirales. Archives of Virology (2021) 166:3567–3579. https://doi.org/10.1007/s00705-021-05266-wIn March 2021, following the annual International Committee on Taxonomy of Viruses (ICTV) ratification vote on newly proposed taxa, the phylum Negarnaviricota was amended and emended. The phylum was expanded by four families (Aliusviridae, Crepuscuviridae, Myriaviridae, and Natareviridae), three subfamilies (Alpharhabdovirinae, Betarhabdovirinae, and Gammarhabdovirinae), 42 genera, and 200 species. Thirty-nine species were renamed and/or moved and seven species were abolished. This article presents the updated taxonomy of Negarnaviricota as now accepted by the ICTV.This work was supported in part through Laulima Government Solutions, LLC prime contract with the US National Institute of Allergy and Infectious Diseases (NIAID) under Contract No. HHSN272201800013C. J.H.K. performed this work as an employee of Tunnell Government Services (TGS), a subcontractor of Laulima Government Solutions, LLC under Contract No. HHSN272201800013C. This work was also supported in part with federal funds from the National Cancer Institute (NCI), National Institutes of Health (NIH), under Contract No. 75N91019D00024, Task Order No. 75N91019F00130 to I.C., who was supported by the Clinical Monitoring Research Program Directorate, Frederick National Lab for Cancer Research. This work was also funded in part by Contract No. HSHQDC-15-C-00064 awarded by DHS S&T for the management and operation of The National Biodefense Analysis and Countermeasures Center, a federally funded research and development center operated by the Battelle National Biodefense Institute (V.W.); and NIH contract HHSN272201000040I/HHSN27200004/D04 and grant R24AI120942 (N.V., R.B.T.). S.S. acknowledges partial support from the Special Research Initiative of Mississippi Agricultural and Forestry Experiment Station (MAFES), Mississippi State University, and the National Institute of Food and Agriculture, US Department of Agriculture, Hatch Project 1021494. Part of this work was supported by the Francis Crick Institute which receives its core funding from Cancer Research UK (FC001030), the UK Medical Research Council (FC001030), and the Wellcome Trust (FC001030).S

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio