Wastewater dataset on the SARS-CoV-2 sublineages circulating in Central Arkansas, USA, post-COVID-19 pandemic.

IF 5.8 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Volodymyr P Tryndyak, Tetyana Kudlyk, Patricia Shores, Michelle M Vanlandingham, Lisa Mullis, Luísa Camacho, Marli Azevedo, Camila S Silva
{"title":"Wastewater dataset on the SARS-CoV-2 sublineages circulating in Central Arkansas, USA, post-COVID-19 pandemic.","authors":"Volodymyr P Tryndyak, Tetyana Kudlyk, Patricia Shores, Michelle M Vanlandingham, Lisa Mullis, Luísa Camacho, Marli Azevedo, Camila S Silva","doi":"10.1038/s41597-025-05100-x","DOIUrl":null,"url":null,"abstract":"<p><p>The ability of coronaviruses to adapt to new hosts and cause widespread disease outbreaks poses a significant threat to global public health systems and economies. The severity of the COVID-19 pandemic has emphasized the importance of studying coronaviruses and monitoring them in communities. We investigated SARS-CoV-2 and its genomic changes in wastewater influent sampled from two metropolitan areas in Arkansas, USA, between April 2020 and March 2024. The data presented here are a follow up report to our previous publication on the findings from the period of April 2020 to January 2022 and show the SARS-CoV-2 variants circulating between February 2022 and March 2024. The levels of viral RNA were measured by reverse-transcription quantitative polymerase chain reaction and targeted three SARS-CoV-2 genes (encoding ORF1ab polyprotein, ORF1ab; surface glycoprotein, S-protein; and nucleocapsid phosphoprotein, N-protein). The identity and genetic diversity of the virus were investigated using amplicon-based RNA sequencing. These data provide important information on SARS-CoV-2 evolution and help to understand the occurrence of COVID-19 outbreaks in the community.</p>","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":"12 1","pages":"934"},"PeriodicalIF":5.8000,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Data","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41597-025-05100-x","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

The ability of coronaviruses to adapt to new hosts and cause widespread disease outbreaks poses a significant threat to global public health systems and economies. The severity of the COVID-19 pandemic has emphasized the importance of studying coronaviruses and monitoring them in communities. We investigated SARS-CoV-2 and its genomic changes in wastewater influent sampled from two metropolitan areas in Arkansas, USA, between April 2020 and March 2024. The data presented here are a follow up report to our previous publication on the findings from the period of April 2020 to January 2022 and show the SARS-CoV-2 variants circulating between February 2022 and March 2024. The levels of viral RNA were measured by reverse-transcription quantitative polymerase chain reaction and targeted three SARS-CoV-2 genes (encoding ORF1ab polyprotein, ORF1ab; surface glycoprotein, S-protein; and nucleocapsid phosphoprotein, N-protein). The identity and genetic diversity of the virus were investigated using amplicon-based RNA sequencing. These data provide important information on SARS-CoV-2 evolution and help to understand the occurrence of COVID-19 outbreaks in the community.

covid -19大流行后美国阿肯色州中部流行的SARS-CoV-2亚谱系的废水数据集
冠状病毒适应新宿主并引起广泛疾病暴发的能力对全球公共卫生系统和经济构成重大威胁。COVID-19大流行的严重性强调了研究冠状病毒并在社区监测它们的重要性。我们调查了2020年4月至2024年3月期间从美国阿肯色州两个大都市采集的废水中SARS-CoV-2及其基因组变化。这里提供的数据是我们之前发表的关于2020年4月至2022年1月期间调查结果的后续报告,并显示SARS-CoV-2变体在2022年2月至2024年3月之间传播。采用逆转录定量聚合酶链反应检测病毒RNA水平,并针对3个SARS-CoV-2基因(编码ORF1ab多蛋白,ORF1ab;表面糖蛋白,s蛋白;和核衣壳磷蛋白(n蛋白)。利用基于扩增子的RNA测序技术研究了该病毒的特性和遗传多样性。这些数据提供了关于SARS-CoV-2演变的重要信息,有助于了解社区中COVID-19疫情的发生情况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信