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高分辨率熔解分析在布基纳法索和肯尼亚监测严重急性呼吸综合征冠状病毒2(SARS-CoV-2)变体中的应用。

Application of a high-resolution melt assay for monitoring SARS-CoV-2 variants in Burkina Faso and Kenya.

作者信息

Greenland-Bews Caitlin, Shah Sonal, Achieng Morine, Badoum Emilie S, Bah Yaya, Barsosio Hellen C, Brazal-Monzó Helena, Canizales Jennifer, Drabko Anna, Fraser Alice J, Hannan Luke, Jarju Sheikh, Kaboré Jean-Moise, Kujabi Mariama A, Leggio Cristina, Lesosky Maia, Manneh Jarra, Marlais Tegwen, Matthewman Julian, Nebié Issa, Onyango Eric, Ouedraogo Alphonse, Otieno Kephas, Serme Samuel S, Sirima Sodiomon, Soulama Ben, Tangara Brian, Tiono Alfred, Wu William, Adams Emily R, Sesay Abdul Karim, Drakeley Chris, Ter Kuile Feiko O, Soulama Issiaka, Kariuki Simon, Allen David J, Edwards Thomas

机构信息

The Department of Tropical Disease Biology, Liverpool School of Tropical Medicine, Liverpool, United Kingdom.

Department of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom.

出版信息

mSphere. 2025 Jun 25;10(6):e0002725. doi: 10.1128/msphere.00027-25. Epub 2025 May 29.

Abstract

The rapid emergence and global dissemination of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) highlighted a need for robust, adaptable surveillance systems. However, financial and infrastructure requirements for whole-genome sequencing mean most surveillance data have come from higher-resource geographies, despite unprecedented investment in sequencing in low- and middle-income countries (LMICs). Consequently, the molecular epidemiology of SARS-CoV-2 in some LMICs is limited, and there is a need for more cost-accessible technologies to help close data gaps for surveillance of SARS-CoV-2 variants. To address this, we have developed two high-resolution melt (HRM) curve assays that target variant-defining mutations in the SARS-CoV-2 genome, which give unique signature profiles that define different SARS-CoV-2 variants of concern (VOCs). Extracted RNA from SARS-CoV-2-positive samples collected from 205 participants (112 in Burkina Faso, 93 in Kenya) enrolled in the MALCOV study (Malaria as a Risk Factor for COVID-19) between February 2021 and February 2022 were analyzed using our optimized HRM assays. With next-generation sequencing on Oxford Nanopore MinION as a reference, two HRM assays, HRM-VOC-1 and HRM-VOC-2, demonstrated sensitivity/specificity of 100%/99.29% and 92.86%/99.39%, respectively, for detecting Alpha, 90.08%/100% and 92.31%/100% for Delta, and 93.75%/100% and 100%/99.38% for Omicron BA.1. The assays described here provide a lower-cost approach to conducting molecular epidemiology, capable of high-throughput testing. We successfully scaled up the HRM-VOC-2 assay to screen a total of 506 samples from which we were able to show the replacement of Alpha with the introduction of Delta and the replacement of Delta by the Omicron variant in this community in Kisumu, Kenya.IMPORTANCEThe rapid evolution of the severe acute respiratory syndrome coronavirus 2 variants of concern (VOCs) demonstrated the need for accessible surveillance tools so all communities can conduct viral surveillance. Sequencing, the gold standard, is still a largely inaccessible methodology in low-resource settings. Here, we present a quick, low-cost tool to screen for the common VOCs, designed to support surveillance efforts in low-resource settings. This tool was used to screen samples from Burkina Faso and Western Kenya throughout the pandemic. We show through comparison to sequencing that our assay can generate highly similar data on the different variants circulating in a population, therefore showing the effectiveness of our tool. While not a replacement for sequencing, we present a method of screening and prioritizing samples for further investigation and reduce overburdening sequencing capacity. Our findings provide insight into one potential tool that could be further applied to pathogen screening in the absence of robust sequencing infrastructure.

摘要

严重急性呼吸综合征冠状病毒2(SARS-CoV-2)的迅速出现和全球传播凸显了对强大、适应性强的监测系统的需求。然而,全基因组测序所需的资金和基础设施意味着,尽管低收入和中等收入国家(LMICs)在测序方面获得了前所未有的投资,但大多数监测数据仍来自资源更丰富的地区。因此,一些LMICs中SARS-CoV-2的分子流行病学情况有限,需要更具成本效益的技术来帮助填补SARS-CoV-2变异株监测的数据空白。为了解决这一问题,我们开发了两种高分辨率熔解(HRM)曲线分析方法,针对SARS-CoV-2基因组中定义变异的突变,这些方法给出了独特的特征图谱,可定义不同的关注SARS-CoV-2变异株(VOCs)。使用我们优化的HRM分析方法,对2021年2月至2022年2月期间参与MALCOV研究(疟疾作为COVID-19的危险因素)的205名参与者(布基纳法索112名,肯尼亚93名)采集的SARS-CoV-2阳性样本中提取的RNA进行了分析。以牛津纳米孔MinION上的下一代测序为参考,两种HRM分析方法,即HRM-VOC-1和HRM-VOC-2,检测Alpha变异株的灵敏度/特异性分别为100%/99.29%和92.86%/99.39%,检测Delta变异株的灵敏度/特异性分别为90.08%/100%和92.31%/100%,检测奥密克戎BA.1变异株的灵敏度/特异性分别为93.75%/100%和100%/99.38%。本文所述的分析方法提供了一种成本更低的分子流行病学研究方法,能够进行高通量检测。我们成功扩大了HRM-VOC-2分析方法的规模,共筛查了506个样本,从而能够显示在肯尼亚基苏木的这个社区中,随着Delta变异株的引入,Alpha变异株被取代,以及奥密克戎变异株取代了Delta变异株。

重要性

严重急性呼吸综合征冠状病毒2关注变异株(VOCs)的快速进化表明需要可获取的监测工具,以便所有社区都能进行病毒监测。测序作为金标准,在资源匮乏地区仍然基本上无法使用。在此,我们展示了一种快速、低成本的工具,用于筛查常见的VOCs,旨在支持资源匮乏地区的监测工作。在整个疫情期间,该工具被用于筛查来自布基纳法索和肯尼亚西部的样本。通过与测序结果进行比较,我们表明我们的分析方法能够生成关于人群中传播的不同变异株的高度相似的数据,从而证明了我们工具的有效性。虽然不能替代测序,但我们提出了一种筛选和优先排序样本以进行进一步调查的方法,并减少测序能力的负担过重问题。我们的研究结果为一种潜在工具提供了见解,该工具可在缺乏强大测序基础设施的情况下进一步应用于病原体筛查。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55a9/12188703/353b85b7fb93/msphere.00027-25.f001.jpg

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