TY - JOUR
T1 - Application of a high-resolution melt assay for monitoring SARS-CoV-2 variants in Burkina Faso and Kenya
AU - Greenland-Bews, Caitlin
AU - Shah, Sonal
AU - Achieng, Morine
AU - Badoum, Emilie S.
AU - Bah, Yaya
AU - Barsosio, Hellen C.
AU - Brazal-Monzó, Helena
AU - Canizales, Jennifer
AU - Drabko, Anna
AU - Fraser, Alice J.
AU - Hannan, Luke
AU - Jarju, Sheikh
AU - Kaboré, Jean Moise
AU - Kujabi, Mariama A.
AU - Leggio, Cristina
AU - Lesosky, Maia
AU - Manneh, Jarra
AU - Marlais, Tegwen
AU - Matthewman, Julian
AU - Nebié, Issa
AU - Onyango, Eric
AU - Ouedraogo, Alphonse
AU - Otieno, Kephas
AU - Serme, Samuel S.
AU - Sirima, Sodiomon
AU - Soulama, Ben
AU - Tangara, Brian
AU - Tiono, Alfred
AU - Wu, William
AU - Adams, Emily R.
AU - Sesay, Abdul Karim
AU - Drakeley, Chris
AU - Ter Kuile, Feiko O.
AU - Soulama, Issiaka
AU - Kariuki, Simon
AU - Allen, David J.
AU - Edwards, Thomas
PY - 2025/6/25
Y1 - 2025/6/25
N2 - 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.
AB - 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.
KW - Africa
KW - Burkina Faso
KW - COVID-19
KW - diagnostics
KW - HRM
KW - Kenya
KW - SARS-CoV-2
KW - surveillance
KW - variants of concern
UR - http://www.scopus.com/inward/record.url?scp=105009855520&partnerID=8YFLogxK
U2 - 10.1128/msphere.00027-25
DO - 10.1128/msphere.00027-25
M3 - Article
C2 - 40439429
AN - SCOPUS:105009855520
SN - 2379-5042
VL - 10
SP - e0002725
JO - mSphere
JF - mSphere
IS - 6
ER -