47 research outputs found

    Classification and function of small open reading frames

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    Small open reading frames (smORFs) of 100 codons or fewer are usually - if arbitrarily - excluded from proteome annotations. Despite this, the genomes of many metazoans, including humans, contain millions of smORFs, some of which fulfil key physiological functions. Recently, the transcriptome of Drosophila melanogaster was shown to contain thousands of smORFs of different classes that actively undergo translation, which produces peptides of mostly unknown function. Here, we present a comprehensive analysis of smORFs in flies, mice and humans. We propose the existence of several functional classes of smORFs, ranging from inert DNA sequences to transcribed and translated cis-regulators of translation and peptides with a propensity to function as regulators of membrane-associated proteins, or as components of ancient protein complexes in the cytoplasm. We suggest that the different smORF classes could represent steps in gene, peptide and protein evolution. Our analysis introduces a distinction between different peptide-coding classes of smORFs in animal genomes, and highlights the role of model organisms for the study of small peptide biology in the context of development, physiology and human disease

    Methodology of calculation of construction and hydrodynamic parameters of a foam layer apparatus for mass-transfer processes

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    ĐŸŃ€ĐŸĐŒĐžŃĐ»ĐŸĐČĐ° Ń€Đ”Đ°Đ»Ń–Đ·Đ°Ń†Ń–Ń ĐŒĐ”Ń‚ĐŸĐŽŃƒ стабілізації ĐłĐ°Đ·ĐŸŃ€Ń–ĐŽĐžĐœĐœĐŸĐłĐŸ шару ĐŽĐŸĐ·ĐČĐŸĐ»ŃŃ” Đ·ĐœĐ°Ń‡ĐœĐŸ Ń€ĐŸĐ·ŃˆĐžŃ€ĐžŃ‚Đž ĐłĐ°Đ»ŃƒĐ·ŃŒ Đ·Đ°ŃŃ‚ĐŸŃŃƒĐČĐ°ĐœĐœŃ ĐżŃ–ĐœĐœĐžŃ… апаратіĐČ Ń– ĐČіЮĐșроĐČає ĐœĐŸĐČі ĐŒĐŸĐ¶Đ»ĐžĐČĐŸŃŃ‚Ń– Ń–ĐœŃ‚Đ”ĐœŃĐžŃ„Ń–Đșації Ń‚Đ”Ń…ĐœĐŸĐ»ĐŸĐłŃ–Ń‡ĐœĐžŃ… ĐżŃ€ĐŸŃ†Đ”ŃŃ–ĐČ Đ· ĐŸĐŽĐœĐŸŃ‡Đ°ŃĐœĐžĐŒ стĐČĐŸŃ€Đ”ĐœĐœŃĐŒ ĐŒĐ°Đ»ĐŸĐČŃ–ĐŽŃ…ĐŸĐŽĐœĐžŃ… Ń‚Đ”Ń…ĐœĐŸĐ»ĐŸĐłŃ–Đč. ĐŁ статті ĐČŃŃ‚Đ°ĐœĐŸĐČĐ»Đ”ĐœŃ– ĐŸŃĐœĐŸĐČĐœŃ– ĐżĐ°Ń€Đ°ĐŒĐ”Ń‚Ń€Đž, Ń‰ĐŸ ĐČплОĐČають ĐœĐ° ĐłŃ–ĐŽŃ€ĐŸĐŽĐžĐœĐ°ĐŒŃ–Đșу ĐżŃ–ĐœĐœĐžŃ… апаратіĐČ, Ń€ĐŸĐ·ĐłĐ»ŃĐœŃƒŃ‚Ń– ĐŸŃĐœĐŸĐČĐœŃ– ĐșĐŸĐœŃŃ‚Ń€ŃƒĐșції та Ń€Đ”Đ¶ĐžĐŒĐž Ń€ĐŸĐ±ĐŸŃ‚Đž ĐżŃ–ĐœĐœĐžŃ… апаратіĐČ. ВояĐČĐ»Đ”ĐœĐŸ Đ·ĐČ'ŃĐ·ĐŸĐș ĐłŃ–ĐŽŃ€ĐŸĐŽĐžĐœĐ°ĐŒŃ–Ń‡ĐœĐžŃ… ĐżĐ°Ń€Đ°ĐŒĐ”Ń‚Ń€Ń–ĐČ. Đ ĐŸĐ·ĐłĐ»ŃĐœŃƒŃ‚ĐŸ ĐłŃ–ĐŽŃ€ĐŸĐŽĐžĐœĐ°ĐŒŃ–Ń‡ĐœŃ– Đ·Đ°ĐșĐŸĐœĐŸĐŒŃ–Ń€ĐœĐŸŃŃ‚Ń– ĐżŃ–ĐœĐœĐŸĐłĐŸ шару. ВĐșĐ°Đ·Đ°ĐœŃ– фаĐșŃ‚ĐŸŃ€Đž, Ń‰ĐŸ ĐČплОĐČають ĐœĐ° ĐżŃ€ĐŸŃ†Đ”Ń ĐŒĐ°ŃĐŸĐŸĐ±ĐŒŃ–ĐœŃƒ, яĐș ĐČ ĐłĐ°Đ·ĐŸĐČіĐč, таĐș і ĐČ Ń€Ń–ĐŽĐșіĐč Ń„Đ°Đ·Đ°Ń…. ĐŸŃ€ĐŸĐČĐ”ĐŽĐ”ĐœĐžĐč Đ°ĐœĐ°Đ»Ń–Đ· ряЮу ĐŽĐŸŃĐ»Ń–ĐŽĐ¶Đ”ĐœŃŒ ĐżĐŸĐșĐ°Đ·Đ°ĐČ, Ń‰ĐŸ пДрспДĐșтоĐČĐœĐžĐŒ ĐœĐ°ĐżŃ€ŃĐŒĐșĐŸĐŒ Ń–ĐœŃ‚Đ”ĐœŃĐžŃ„Ń–Đșації ĐżŃ€ĐŸŃ†Đ”ŃŃƒ ĐŒĐ°ŃĐŸĐŸĐ±ĐŒŃ–ĐœŃƒ є Ń€ĐŸĐ·Ń€ĐŸĐ±ĐșĐ° апаратіĐČ Đ· Ń‚Ń€ĐžŃ„Đ°Đ·ĐœĐžĐŒ псДĐČĐŽĐŸĐ·Ń€Ń–ĐŽĐ¶Đ”ĐœĐžĐŒ ŃˆĐ°Ń€ĐŸĐŒ Đ·Ń€ĐŸŃˆŃƒĐČĐ°ĐœĐŸŃ— ĐœĐ°ŃĐ°ĐŽĐșĐž сĐșĐ»Đ°ĐŽĐœĐžŃ… Ń„ĐŸŃ€ĐŒ Ń–Đ· сітчастох ĐŒĐ°Ń‚Đ”Ń€Ń–Đ°Đ»Ń–ĐČ. ОтжД, ĐœĐ”ĐŸĐ±Ń…Ń–ĐŽĐœĐ” ĐżŃ€ĐŸĐČĐ”ĐŽĐ”ĐœĐœŃ ŃĐżĐ”Ń†Ń–Đ°Đ»ŃŒĐœĐžŃ… ĐŽĐŸŃĐ»Ń–ĐŽĐ¶Đ”ĐœŃŒ ĐłŃ–ĐŽŃ€ĐŸĐŽĐžĐœĐ°ĐŒŃ–Ń‡ĐœĐžŃ… Ń€Đ”Đ¶ĐžĐŒŃ–ĐČ Ń€ĐŸĐ±ĐŸŃ‚Đž апарату Đ· ŃŃ–Ń‚Ń‡Đ°ŃŃ‚ĐŸŃŽ ĐœĐ°ŃĐ°ĐŽĐșĐŸŃŽ і ĐČĐžĐ·ĐœĐ°Ń‡Đ”ĐœĐœŃĐŒ ĐżĐ°Ń€Đ°ĐŒĐ”Ń‚Ń€Ń–ĐČ, Ń‰ĐŸ ĐČплОĐČають ĐœĐ° шĐČОЎĐșість ĐżĐ”Ń€Đ”Ń…ĐŸĐŽŃƒ ĐœĐ°ŃĐ°ĐŽĐșĐž Đ· ĐŸĐŽĐœĐŸĐłĐŸ Ń€Đ”Đ¶ĐžĐŒŃƒ ĐČ Ń–ĐœŃˆĐžĐč.Industrial implementation of the stabilization method of the gas-liquid layer can significantly expand the field of use of foaming apparatus and opens up new opportunities for intensifying technological processes with the simultaneous creation of low-waste technologies. The article establishes the basic parameters influencing the hydrodynamics of foam apparatus, considers the basic constructions and operating modes of foam apparatus. The connection of hydrodynamic parameters is revealed. The hydrodynamic laws of the foam layer are considered. The indicated factors affecting the process of mass transfer, both in the gas and in the liquid phases. The conducted analysis of a number of studies showed that the perspective direction of intensification of the mass transfer process is the development of apparatuses with a three-phase fluidized bed of an irrigated nozzle of complex forms with mesh materials

    The impact of viral mutations on recognition by SARS-CoV-2 specific T cells.

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    We identify amino acid variants within dominant SARS-CoV-2 T cell epitopes by interrogating global sequence data. Several variants within nucleocapsid and ORF3a epitopes have arisen independently in multiple lineages and result in loss of recognition by epitope-specific T cells assessed by IFN-γ and cytotoxic killing assays. Complete loss of T cell responsiveness was seen due to Q213K in the A∗01:01-restricted CD8+ ORF3a epitope FTSDYYQLY207-215; due to P13L, P13S, and P13T in the B∗27:05-restricted CD8+ nucleocapsid epitope QRNAPRITF9-17; and due to T362I and P365S in the A∗03:01/A∗11:01-restricted CD8+ nucleocapsid epitope KTFPPTEPK361-369. CD8+ T cell lines unable to recognize variant epitopes have diverse T cell receptor repertoires. These data demonstrate the potential for T cell evasion and highlight the need for ongoing surveillance for variants capable of escaping T cell as well as humoral immunity.This work is supported by the UK Medical Research Council (MRC); Chinese Academy of Medical Sciences(CAMS) Innovation Fund for Medical Sciences (CIFMS), China; National Institute for Health Research (NIHR)Oxford Biomedical Research Centre, and UK Researchand Innovation (UKRI)/NIHR through the UK Coro-navirus Immunology Consortium (UK-CIC). Sequencing of SARS-CoV-2 samples and collation of data wasundertaken by the COG-UK CONSORTIUM. COG-UK is supported by funding from the Medical ResearchCouncil (MRC) part of UK Research & Innovation (UKRI),the National Institute of Health Research (NIHR),and Genome Research Limited, operating as the Wellcome Sanger Institute. T.I.d.S. is supported by a Well-come Trust Intermediate Clinical Fellowship (110058/Z/15/Z). L.T. is supported by the Wellcome Trust(grant number 205228/Z/16/Z) and by theUniversity of Liverpool Centre for Excellence in Infectious DiseaseResearch (CEIDR). S.D. is funded by an NIHR GlobalResearch Professorship (NIHR300791). L.T. and S.C.M.are also supported by the U.S. Food and Drug Administration Medical Countermeasures Initiative contract75F40120C00085 and the National Institute for Health Research Health Protection Research Unit (HPRU) inEmerging and Zoonotic Infections (NIHR200907) at University of Liverpool inpartnership with Public HealthEngland (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford.L.T. is based at the University of Liverpool. M.D.P. is funded by the NIHR Sheffield Biomedical ResearchCentre (BRC – IS-BRC-1215-20017). ISARIC4C is supported by the MRC (grant no MC_PC_19059). J.C.K.is a Wellcome Investigator (WT204969/Z/16/Z) and supported by NIHR Oxford Biomedical Research Centreand CIFMS. The views expressed are those of the authors and not necessarily those of the NIHR or MRC

    Spatial growth rate of emerging SARS-CoV-2 lineages in England, September 2020-December 2021

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    This paper uses a robust method of spatial epidemiological analysis to assess the spatial growth rate of multiple lineages of SARS-CoV-2 in the local authority areas of England, September 2020–December 2021. Using the genomic surveillance records of the COVID-19 Genomics UK (COG-UK) Consortium, the analysis identifies a substantial (7.6-fold) difference in the average rate of spatial growth of 37 sample lineages, from the slowest (Delta AY.4.3) to the fastest (Omicron BA.1). Spatial growth of the Omicron (B.1.1.529 and BA) variant was found to be 2.81× faster than the Delta (B.1.617.2 and AY) variant and 3.76× faster than the Alpha (B.1.1.7 and Q) variant. In addition to AY.4.2 (a designated variant under investigation, VUI-21OCT-01), three Delta sublineages (AY.43, AY.98 and AY.120) were found to display a statistically faster rate of spatial growth than the parent lineage and would seem to merit further investigation. We suggest that the monitoring of spatial growth rates is a potentially valuable adjunct to outbreak response procedures for emerging SARS-CoV-2 variants in a defined population

    The SARS-CoV-2 Alpha variant was associated with increased clinical severity of COVID-19 in Scotland: A genomics-based retrospective cohort analysis

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    Objectives The SARS-CoV-2 Alpha variant was associated with increased transmission relative to other variants present at the time of its emergence and several studies have shown an association between Alpha variant infection and increased hospitalisation and 28-day mortality. However, none have addressed the impact on maximum severity of illness in the general population classified by the level of respiratory support required, or death. We aimed to do this. Methods In this retrospective multi-centre clinical cohort sub-study of the COG-UK consortium, 1475 samples from Scottish hospitalised and community cases collected between 1st November 2020 and 30th January 2021 were sequenced. We matched sequence data to clinical outcomes as the Alpha variant became dominant in Scotland and modelled the association between Alpha variant infection and severe disease using a 4-point scale of maximum severity by 28 days: 1. no respiratory support, 2. supplemental oxygen, 3. ventilation and 4. death. Results Our cumulative generalised linear mixed model analyses found evidence (cumulative odds ratio: 1.40, 95% CI: 1.02, 1.93) of a positive association between increased clinical severity and lineage (Alpha variant versus pre-Alpha variants). Conclusions The Alpha variant was associated with more severe clinical disease in the Scottish population than co-circulating lineages

    Investigation of hospital discharge cases and SARS-CoV-2 introduction into Lothian care homes

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    Summary Background The first epidemic wave of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in Scotland resulted in high case numbers and mortality in care homes. In Lothian, over one-third of care homes reported an outbreak, while there was limited testing of hospital patients discharged to care homes. Aim To investigate patients discharged from hospitals as a source of SARS-CoV-2 introduction into care homes during the first epidemic wave. Methods A clinical review was performed for all patients discharges from hospitals to care homes from 1st March 2020 to 31st May 2020. Episodes were ruled out based on coronavirus disease 2019 (COVID-19) test history, clinical assessment at discharge, whole-genome sequencing (WGS) data and an infectious period of 14 days. Clinical samples were processed for WGS, and consensus genomes generated were used for analysis using Cluster Investigation and Virus Epidemiological Tool software. Patient timelines were obtained using electronic hospital records. Findings In total, 787 patients discharged from hospitals to care homes were identified. Of these, 776 (99%) were ruled out for subsequent introduction of SARS-CoV-2 into care homes. However, for 10 episodes, the results were inconclusive as there was low genomic diversity in consensus genomes or no sequencing data were available. Only one discharge episode had a genomic, time and location link to positive cases during hospital admission, leading to 10 positive cases in their care home. Conclusion The majority of patients discharged from hospitals were ruled out for introduction of SARS-CoV-2 into care homes, highlighting the importance of screening all new admissions when faced with a novel emerging virus and no available vaccine

    SARS-CoV-2 lineage dynamics in England from September to November 2021: high diversity of Delta sub-lineages and increased transmissibility of AY.4.2

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    Background: Since the emergence of SARS-CoV-2, evolutionary pressure has driven large increases in the transmissibility of the virus. However, with increasing levels of immunity through vaccination and natural infection the evolutionary pressure will switch towards immune escape. Genomic surveillance in regions of high immunity is crucial in detecting emerging variants that can more successfully navigate the immune landscape. Methods: We present phylogenetic relationships and lineage dynamics within England (a country with high levels of immunity), as inferred from a random community sample of individuals who provided a self-administered throat and nose swab for rt-PCR testing as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. During round 14 (9 September–27 September 2021) and 15 (19 October–5 November 2021) lineages were determined for 1322 positive individuals, with 27.1% of those which reported their symptom status reporting no symptoms in the previous month. Results: We identified 44 unique lineages, all of which were Delta or Delta sub-lineages, and found a reduction in their mutation rate over the study period. The proportion of the Delta sub-lineage AY.4.2 was increasing, with a reproduction number 15% (95% CI 8–23%) greater than the most prevalent lineage, AY.4. Further, AY.4.2 was less associated with the most predictive COVID-19 symptoms (p = 0.029) and had a reduced mutation rate (p = 0.050). Both AY.4.2 and AY.4 were found to be geographically clustered in September but this was no longer the case by late October/early November, with only the lineage AY.6 exhibiting clustering towards the South of England. Conclusions: As SARS-CoV-2 moves towards endemicity and new variants emerge, genomic data obtained from random community samples can augment routine surveillance data without the potential biases introduced due to higher sampling rates of symptomatic individuals. © 2022, The Author(s)

    Tracking SARS-CoV-2 mutations and variants through the COG-UK-Mutation Explorer

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    COG-UK Mutation Explorer (COG-UK-ME, https://sars2.cvr.gla.ac.uk/cog-uk/—last accessed date 16 March 2022) is a web resource that displays knowledge and analyses on SARS-CoV-2 virus genome mutations and variants circulating in the UK, with a focus on the observed amino acid replacements that have an antigenic role in the context of the human humoral and cellular immune response. This analysis is based on more than 2 million genome sequences (as of March 2022) for UK SARS-CoV-2 data held in the CLIMB-COVID centralised data environment. COG-UK-ME curates these data and displays analyses that are cross-referenced to experimental data collated from the primary literature. The aim is to track mutations of immunological importance that are accumulating in current variants of concern and variants of interest that could alter the neutralising activity of monoclonal antibodies (mAbs), convalescent sera, and vaccines. Changes in epitopes recognised by T cells, including those where reduced T cell binding has been demonstrated, are reported. Mutations that have been shown to confer SARS-CoV-2 resistance to antiviral drugs are also included. Using visualisation tools, COG-UK-ME also allows users to identify the emergence of variants carrying mutations that could decrease the neutralising activity of both mAbs present in therapeutic cocktails, e.g. Ronapreve. COG-UK-ME tracks changes in the frequency of combinations of mutations and brings together the curated literature on the impact of those mutations on various functional aspects of the virus and therapeutics. Given the unpredictable nature of SARS-CoV-2 as exemplified by yet another variant of concern, Omicron, continued surveillance of SARS-CoV-2 remains imperative to monitor virus evolution linked to the efficacy of therapeutics
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