Advancing Drug Resistance Detection: Comparative Analysis Using Short-Read and Long-Read Next-Generation Sequencing Technologies

In recent years, antiviral therapy has proved crucial in the treatment of infectious diseases, particularly infections by highly variable viruses such as human immunodeficiency virus, hepatitis B, hepatitis C, SARS-CoV-2 or bacteria such as Mycobacterium tuberculosis. Under the effect of selection pressure, this variability induces mutations that lead to resistance to antiviral and antibacterial drugs, and thus to escape from treatment. The use of Advanced Biological Laboratories (ABL) assays technology combined with next-generation sequencing (NGS) and automatized software to detect majority and minority variants involved in treatment resistance has become a mainstay for establishing therapeutic strategies. The present study demonstrated high concordance between majority and minority subtypes and mutations identified in 15 samples across four NGS platforms: ISeq100 (Illumina (San Diego, CA, USA)), MiSeq (Illumina), DNBSEQ-G400 (MGI (Santa Clara, CA, USA)) and Mk1C MinION (Oxford Nanopore (Oxford Science Park, UK)). However, nanopore technology showed a higher number of minority mutations (<20%). The analysis also validated the pooling of microbiological samples as a method for detecting mutations and genotypes in viral and bacterial organisms, using the easy-to-use DeepChek® bioinformatics software, compatible with all four sequencing platforms. This study underlines the constant evolution of microbiological diagnostic research and the need to adapt rapidly to improve patient care.

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Publication Details

Journal
LabMed
Published
2025-08-20
DOI
https://doi.org/10.3390/labmed2030014
Primary Topic
Cancer Genomics and Diagnostics
Type
article
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article

Advancing Drug Resistance Detection: Comparative Analysis Using Short-Read and Long-Read Next-Generation Sequencing Technologies

Matthieu Barralon, Ronan Boulmé, Chalom Sayada, José Luis Martínez et al.
LabMed
Cancer Genomics and Diagnostics
article

Advancing Drug Resistance Detection: Comparative Analysis Using Short-Read and Long-Read Next-Generation Sequencing Technologies

Matthieu Barralon, Ronan Boulmé, Chalom Sayada, José Luis Martínez, Sofiane Mohamed, Amira Doudou, J.C. Leonard, Dimitri Gonzalez, Jonathan Porzio, Arnaud Reffay, Mohamed Errafyqy, Jonathan Kolsch, Giuseppina Zuco, Aitor Modol, Rezak Drali, Laurent Deblir, Jérome Wautrin
article en

Abstract

In recent years, antiviral therapy has proved crucial in the treatment of infectious diseases, particularly infections by highly variable viruses such as human immunodeficiency virus, hepatitis B, hepatitis C, SARS-CoV-2 or bacteria such as Mycobacterium tuberculosis. Under the effect of selection pressure, this variability induces mutations that lead to resistance to antiviral and antibacterial drugs, and thus to escape from treatment. The use of Advanced Biological Laboratories (ABL) assays technology combined with next-generation sequencing (NGS) and automatized software to detect majority and minority variants involved in treatment resistance has become a mainstay for establishing therapeutic strategies. The present study demonstrated high concordance between majority and minority subtypes and mutations identified in 15 samples across four NGS platforms: ISeq100 (Illumina (San Diego, CA, USA)), MiSeq (Illumina), DNBSEQ-G400 (MGI (Santa Clara, CA, USA)) and Mk1C MinION (Oxford Nanopore (Oxford Science Park, UK)). However, nanopore technology showed a higher number of minority mutations (<20%). The analysis also validated the pooling of microbiological samples as a method for detecting mutations and genotypes in viral and bacterial organisms, using the easy-to-use DeepChek® bioinformatics software, compatible with all four sequencing platforms. This study underlines the constant evolution of microbiological diagnostic research and the need to adapt rapidly to improve patient care.

LabMedVol. 2(3)
Advanced Biological Laboratories (Luxembourg) (LU), CS Diagnostics (DE), La Salle University (US)
Openalex Percentile: Top 73%
Cancer Genomics and Diagnostics
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