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

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

    Research output: Contribution to journalArticlepeer-review

    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.

    Original languageEnglish
    Article numbere00027-25
    JournalmSphere
    Volume10
    Issue number6
    DOIs
    Publication statusPublished - Jun 2025

    Bibliographical note

    Publisher Copyright:
    Copyright © 2025 Greenland-Bews et al.

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

    Keywords

    • Africa
    • Burkina Faso
    • COVID-19
    • HRM
    • Kenya
    • SARS-CoV-2
    • diagnostics
    • surveillance
    • variants of concern

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