Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 5 de 5
Filtrar
Más filtros










Intervalo de año de publicación
1.
Preprint en Inglés | bioRxiv | ID: ppbiorxiv-433156

RESUMEN

SARS-CoV-2 lineage B.1.1.7 viruses are more transmissible, may lead to greater clinical severity, and result in modest reductions in antibody neutralization. subgenomic RNA (sgRNA) is produced by discontinuous transcription of the SARS-CoV-2 genome and is a crucial step in the SARS-CoV-2 life cycle. Applying our tool (periscope) to ARTIC Network Oxford Nanopore genomic sequencing data from 4400 SARS-CoV-2 positive clinical samples, we show that normalised sgRNA expression profiles are significantly increased in B.1.1.7 infections (n=879). This increase is seen over the previous dominant circulating lineage in the UK, B.1.177 (n=943), which is independent of genomic reads, E gene cycle threshold and days since symptom onset at sampling. A noncanonical sgRNA which could represent ORF9b is found in 98.4% of B.1.1.7 SARS-CoV-2 infections compared with only 13.8% of other lineages, with a 16-fold increase in median expression. We hypothesise that this is a direct consequence of a triple nucleotide mutation in nucleocapsid (28280:GAT>CAT, D3L) creating a transcription regulatory-like sequence complementary to a region 3 of the genomic leader. These findings provide a unique insight into the biology of B.1.1.7 and support monitoring of sgRNA profiles in sequence data to evaluate emerging potential variants of concern. One Sentence SummaryThe recently emerged and more transmissible SARS-CoV-2 lineage B.1.1.7 shows greater subgenomic RNA expression in clinical infections and enhanced expression of a noncanonical subgenomic RNA near ORF9b.

2.
Preprint en Inglés | bioRxiv | ID: ppbiorxiv-181867

RESUMEN

We have developed periscope, a tool for the detection and quantification of sub-genomic RNA (sgRNA) in SARS-CoV-2 genomic sequence data. The translation of the SARS-CoV-2 RNA genome for most open reading frames (ORFs) occurs via RNA intermediates termed "sub-genomic RNAs". sgRNAs are produced through discontinuous transcription which relies on homology between transcription regulatory sequences (TRS-B) upstream of the ORF start codons and that of the TRS-L which is located in the 5 UTR. TRS-L is immediately preceded by a leader sequence. This leader sequence is therefore found at the 5 end of all sgRNA. We applied periscope to 1,155 SARS-CoV-2 genomes from Sheffield, UK and validated our findings using orthogonal datasets and in vitro cell systems. Using a simple local alignment to detect reads which contain the leader sequence we were able to identify and quantify reads arising from canonical and non-canonical sgRNA. We were able to detect all canonical sgRNAs at expected abundances, with the exception of ORF10. A number of recurrent non-canonical sgRNAs are detected. We show that the results are reproducible using technical replicates and determine the optimum number of reads for sgRNA analysis. In VeroE6 ACE2+/- cell lines, periscope can detect the changes in the kinetics of sgRNA in orthogonal sequencing datasets. Finally, variants found in genomic RNA are transmitted to sgRNAs with high fidelity in most cases. This tool can be applied to all sequenced COVID-19 samples worldwide to provide comprehensive analysis of SARS-CoV-2 sgRNA.

3.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-20141739

RESUMEN

Ascertaining the state of coronavirus outbreaks is crucial for public health decision-making. Absent repeated representative viral test samples in the population, public health officials and researchers alike have relied on lagging indicators of infection to make inferences about the direction of the outbreak and attendant policy decisions. Recently researchers have shown that SARS-CoV-2 RNA can be detected in municipal sewage sludge with measured RNA concentrations rising and falling suggestively in the shape of an epidemic curve while providing an earlier signal of infection than hospital admissions data. The present paper presents a SARS-CoV-2 epidemic model to serve as a basis for estimating the incidence of infection, and shows mathematically how modeled transmission dynamics translate into infection indicators by incorporating probability distributions for indicator-specific time lags from infection. Hospital admissions and SARS-CoV-2 RNA in municipal sewage sludge are simultaneously modeled via maximum likelihood scaling to the underlying transmission model. The results demonstrate that both data series plausibly follow from the transmission model specified, provide a direct estimate of the reproductive number R0 = 2.38, and suggest that the detection of viral RNA in sewage sludge leads hospital admissions by 4.6 days on average.

4.
Preprint en Inglés | medRxiv | ID: ppmedrxiv-20105999

RESUMEN

We report a time course of SARS-CoV-2 RNA concentrations in primary sewage sludge during the Spring COVID-19 outbreak in a northeastern U.S. metropolitan area. SARS-CoV-2 RNA was detected in all environmental samples, and when adjusted for the time lag, the virus RNA concentrations tracked the COVID-19 epidemiological curve. SARS-CoV-2 RNA concentrations were a leading indicator of community infection ahead of compiled COVID-19 testing data and local hospital admissions. Decisions to implement or relax public health measures and restrictions require timely information on outbreak dynamics in a community.

5.
Artículo en Inglés | WPRIM (Pacífico Occidental) | ID: wpr-264576

RESUMEN

<p><b>OBJECTIVE</b>To describe the baseline data of cancers in the Jinchang Cohort, this paper examined trends in cancer mortality among adults investigated in Jinchang, Gansu province from 2001 to 2010.</p><p><b>METHODS</b>Mortality data were collected from company departments through administrative documents, death certificates, etc. Trend analyses of cancer mortality were performed on the basis of 925 cancer deaths between 2001 and 2010.</p><p><b>RESULTS</b>The crude mortality rate of cancer continuously increased from 161.86 per 100,000 in 2001 to 315.32 per 100,000 in 2010, with an average increase of 7.69% per year in the Jinchang Cohort (16.41% in females compared to 6.04% in males), but the age-standardized mortality rate increased only in females. Thirteen leading cancers accounted for 92.10% of all cancer deaths. The five leading causes of cancer mortality in males were lung, gastric, liver, esophageal, and colorectal cancer, whereas those in females were lung, liver, gastric, breast, and esophageal cancer.</p><p><b>CONCLUSION</b>The overall cancer mortality rate increased from 2001 to 2010 in the Jinchang Cohort, with greater rate of increase in females than in males. Lung, breast, and gastric cancer, in that order, were the leading causes of increased cancer mortality in females.</p>


Asunto(s)
Adulto , Femenino , Humanos , Masculino , China , Epidemiología , Estudios de Cohortes , Neoplasias , Epidemiología , Mortalidad , Estudios Retrospectivos , Factores de Tiempo
SELECCIÓN DE REFERENCIAS
DETALLE DE LA BÚSQUEDA
...