From Capillary Electrophoresis to Deep Sequencing: An Improved HIV-1 Drug Resistance Assessment Solution Using In Vitro Diagnostic (IVD) Assays and Software

Abstract

Background: Drug-resistance mutations were mostly detected using capillary electrophoresis sequencing, which does not detect minor variants with a frequency below 20%. Next-Generation Sequencing (NGS) can now detect additional mutations which can be useful for HIV-1 drug resistance interpretation. The objective of this study was to evaluate the performances of CE-IVD assays for HIV-1 drug-resistance assessment both for target-specific and whole-genome sequencing, using standardized end-to-end solution platforms. Methods: A total of 301 clinical samples were prepared, extracted, and amplified for the three HIV-1 genomic targets, Protease (PR), Reverse Transcriptase (RT), and Integrase (INT), using the CE-IVD DeepChek® Assays; and then 19 clinical samples, using the CE-IVD DeepChek® HIV Whole Genome Assay, were sequenced on the NGS iSeq100 and MiSeq (Illumina). Sequences were compared to those obtained by capillary electrophoresis. Quality control for Molecular Diagnostics (QCMD) samples was added to validate the clinical accuracy of these in vitro diagnostics (IVDs). Nineteen clinical samples were then tested with the same sample collection, handling, and measurement procedure for evaluating the use of NGS for whole-genome HIV-1. Sequencing analyzer outputs were submitted to a downstream CE-IVD standalone software tailored for HIV-1 analysis and interpretation. Results: The limits of range detection were 1000 to 106 cp/mL for the HIV-1 target-specific sequencing. The median coverage per sample for the three amplicons (PR/RT and INT) was 13,237 reads. High analytical reproducibility and repeatability were evidenced by a positive percent agreement of 100%. Duplicated samples in two distinct NGS runs were 100% homologous. NGS detected all the mutations found by capillary electrophoresis and identified additional resistance variants. A perfect accuracy score with the QCMD panel detection of drug-resistance mutations was obtained. Conclusions: This study is the first evaluation of the DeepChek® Assays for targets specific (PR/RT and INT) and whole genome. A cutoff of 3% allowed for a better characterization of the viral population by identifying additional resistance mutations and improving the HIV-1 drug-resistance interpretation. The use of whole-genome sequencing is an additional and complementary tool to detect mutations in newly infected untreated patients and heavily experienced patients, both with higher HIV-1 viral-load profiles, to offer new insight and treatment strategies, especially using the new HIV-1 capsid/maturation inhibitors and to assess the potential clinical impact of mutations in the HIV-1 genome outside of the usual HIV-1 targets (RT/PR and INT).

Current Uses and Future Perspectives of Genomic Technologies in Clinical Microbiology

“…For instance, in HIV research, tNGS can identify minor variants carrying drug resistance mutations that might elude detection with traditional Sanger sequencing [24]. Similarly, tNGS has played a pivotal role in characterising variants of the SARS-CoV-2 virus during the COVID-19 pandemic, aiding in the tracking of specific strain spread and the assessment of the potential implications for diagnostics, vaccines, and therapeutics [51,52]. In microbial identification, tNGS is particularly valuable for distinguishing bacterial species using the 16S ribosomal RNA (rRNA) gene or fungal species through the internal transcribed spacer 1/2 (ITS-1/2) regions.…”

Usefulness of Capillary Gel Electrophoresis-Based PCR for Detection of Clostridioides difficile Strains with Hypervirulent Ribotypes

“…It has also been proven that applying appropriate sequences (e.g., 16S-23S, ITS) in capillary gel electrophoresis is useful for bacteria and yeast identification [2,3]. Therefore, capillary gel electrophoresis has already been applied to a number of research studies dedicated to particular microbial investigation and differentiation, including viruses [4,5], bacteria [6][7][8][9][10] and fungi [11]. Other application aspects are especially dedicated to foodborne pathogen detection [8,[12][13][14][15] and their typing [16][17][18][19][20].…”