CalmBelt: Rapid SARS-CoV-2 Genome Characterization for Outbreak Tracking.

Area of Science:

• Genomic epidemiology
• Infectious disease surveillance
• Bioinformatics tools

Background:

• The COVID-19 pandemic necessitates rapid identification of SARS-CoV-2 transmission, especially in healthcare settings.
• Clinical diagnostic laboratories can now sequence SARS-CoV-2 but often lack bioinformatics expertise.
• There is a need for accessible, on-site tools for rapid genome analysis in clinical settings.

Purpose of the Study:

• To develop and present CalmBelt, an integrated framework for on-site whole genome characterization and outbreak tracking of SARS-CoV-2.
• To provide clinical laboratories with an intuitive tool for analyzing multiple SARS-CoV-2 genomes and deriving actionable insights.

Main Methods:

• Utilized Nanopore sequencing technology for on-site, rapid (within 12h) whole genome sequencing of multiple SARS-CoV-2 samples.
• Developed CalmBelt, an interactive web application with a user-friendly interface for genome analysis.
• Integrated SARS-CoV-2 nomenclature (GISAID clades, PANGO lineages) for visualizing sample relatedness.

Main Results:

• CalmBelt enables on-site whole genome characterization and outbreak tracking of SARS-CoV-2.
• The framework facilitates analysis of multiple genomes, collection dates, and epidemiological data to identify potential clusters.
• Demonstrated use cases include hospital transmission investigation, outbreak pattern mining, and monitoring diagnostic escape variants.

Conclusions:

• CalmBelt provides a rapid, on-site framework for SARS-CoV-2 whole genome characterization suitable for clinical laboratories.
• Non-technical users can identify SARS-CoV-2 variants of concern and investigate transmission clusters using CalmBelt.
• The tool generates crucial information for immediate infection control, enhancing safety in healthcare settings.