From SARS-CoV-2 to Global Preparedness: A Graphical Interface for Standardised High-Throughput Bioinformatics Analysis in Pandemic Scenarios and Surveillance of Drug Resistance.


Journal

International journal of molecular sciences
ISSN: 1422-0067
Titre abrégé: Int J Mol Sci
Pays: Switzerland
ID NLM: 101092791

Informations de publication

Date de publication:
17 Jun 2024
Historique:
received: 06 05 2024
revised: 04 06 2024
accepted: 15 06 2024
medline: 27 6 2024
pubmed: 27 6 2024
entrez: 27 6 2024
Statut: epublish

Résumé

The COVID-19 pandemic highlighted the need for a rapid, convenient, and scalable diagnostic method for detecting a novel pathogen amidst a global pandemic. While command-line interface tools offer automation for SARS-CoV-2 Oxford Nanopore Technology sequencing data analysis, they are inapplicable to users with limited programming skills. A solution is to establish such automated workflows within a graphical user interface software. We developed two workflows in the software Geneious Prime 2022.1.1, adapted for data obtained from the Midnight and Artic's nCoV-2019 sequencing protocols. Both workflows perform trimming, read mapping, consensus generation, and annotation on SARS-CoV-2 Nanopore sequencing data. Additionally, one workflow includes phylogenetic assignment using the bioinformatic tools pangolin and Nextclade as plugins. The basic workflow was validated in 2020, adhering to the requirements of the European Centre for Disease Prevention and Control for SARS-CoV-2 sequencing and analysis. The enhanced workflow, providing phylogenetic assignment, underwent validation at Uppsala University Hospital by analysing 96 clinical samples. It provided accurate diagnoses matching the original results of the basic workflow while also reducing manual clicks and analysis time. These bioinformatic workflows streamline SARS-CoV-2 Nanopore data analysis in Geneious Prime, saving time and manual work for operators lacking programming knowledge.

Identifiants

pubmed: 38928350
pii: ijms25126645
doi: 10.3390/ijms25126645
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Knut and Alice Wallenberg Foundation
ID : KAW 2020.0241
Organisme : Gullstrand Foundation
ID : ALF-938076

Auteurs

Tomas Cumlin (T)

Department of Medical Sciences, Section for Clinical Microbiology, Uppsala University, Akademiska Sjukhuset Entrance 40, 751 85 Uppsala, Sweden.

Ida Karlsson (I)

Clinical Genomics Uppsala, Science for Life Laboratory, Uppsala University, 751 85 Uppsala, Sweden.

Jonathan Haars (J)

Department of Medical Sciences, Section for Clinical Microbiology, Uppsala University, Akademiska Sjukhuset Entrance 40, 751 85 Uppsala, Sweden.

Maria Rosengren (M)

Department of Medical Sciences, Section for Clinical Microbiology, Uppsala University, Akademiska Sjukhuset Entrance 40, 751 85 Uppsala, Sweden.

Johan Lennerstrand (J)

Department of Medical Sciences, Section for Clinical Microbiology, Uppsala University, Akademiska Sjukhuset Entrance 40, 751 85 Uppsala, Sweden.

Maryna Pimushyna (M)

Department of Medical Sciences, Section for Clinical Microbiology, Uppsala University, Akademiska Sjukhuset Entrance 40, 751 85 Uppsala, Sweden.

Lars Feuk (L)

National Genomics Infrastructure Uppsala, Uppsala University, 751 08 Uppsala, Sweden.
Department of Immunology, Genetics and Pathology, Uppsala University, 751 08 Uppsala, Sweden.

Claes Ladenvall (C)

Clinical Genomics Uppsala, Science for Life Laboratory, Uppsala University, 751 85 Uppsala, Sweden.
Department of Immunology, Genetics and Pathology, Uppsala University, 751 08 Uppsala, Sweden.

Rene Kaden (R)

Department of Medical Sciences, Section for Clinical Microbiology, Uppsala University, Akademiska Sjukhuset Entrance 40, 751 85 Uppsala, Sweden.
Clinical Genomics Uppsala, Science for Life Laboratory, Uppsala University, 751 85 Uppsala, Sweden.

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Classifications MeSH