Search PubMedSearch

PubMed · 39106263

Diagnosis with Metagenomic Next-Generation Sequencing (mNGS) technology and real-time PCR for SARS-CoV-2 Omicron detection using various nasopharyngeal swabs in SARS-CoV-2 Omicron.

Abstract

BACKGROUND: The SARS-CoV-2 Omicron variant, with the main subtypes BA.5.2 and BF.7 in China, led to off-target effects on the S and N genes from December 1, 2022, to January 31, 2023. The kits used for studying and developing these agents were not adequately and independently evaluated. It is important to verify the performance of commercial Real-Time quantitative PCR (RT-qPCR) tests. OBJECTIVE: We conducted a clinical evaluation of two Real Time SARS-CoV-2 Omicron assays to verify their performance using various detection reagents and clinical specimens. METHODS: We performed clinical evaluations of two existing Chinese SARS-CoV-2 Omicron RT-qPCR kits 2019-nCoV nucleic acid diagnostic kits (Fosun Biotechnology, National instrument registration 20203400299, Shanghai, China) and COVID-19 nucleic acid detection kits (eDiagnosis Biomedicine, National instrument registration 20203400212, Wuhan, China) and using BSD (Bondson) (Guangzhou Bondson Biotechnology Co. Ltd, batch number 2022101), quality controls provided by the inspection center and a large number of clinically confirmed specimens. RESULTS: The concordance rates for the Fosun and eDiagnosis kits were 95% and 100%, respectively. The detection limit for the Fosun and eDiagnosis kits was verified to be 300 copies/mL and 500 copies/mL. The Fosun assay exhibited the largest coefficient of variation (CV) for ORF1ab and N gene at the detection limit concentration (4.80%, 3.49%), whereas eDiagnosis showed a smaller CV (0.93%, 1.10%). In the reference product from the Hangzhou Clinical Laboratory Center test, it was found that Fosun had the lowest sensitivity of 93.47% and a specificity of 100%, while eDiagnosis exhibited 100% for both sensitivity and specificity. The lowest single target gene detection rate of Fosun reagents was 68.7% for the ORF1ab gene and 87.5% for the N gene, while eDiagnosis detection rate was 100%. Among the clinical group S specimens, the missed detection rate of the Fosun reagent was 10.9%, which was higher than the 3.9% of eDiagnosis. However, there was no significant difference in the clinical diagnostic efficiency of the two reagents. CONCLUSIONS: The ORF1ab and N assays of SARS-CoV-2 Omicron on the eDiagnosis platform yielded higher values compared to those on the Fosun platform. Consequently, the eDiagnosis kit has also been used as standard detection reagents. Considering that the Fosun reagent has a relatively low detection limit and targets three single genes, it is more advantageous as a confirmatory reagent for the new museum.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Sujuan Li, Yuanhang Zhang, Pengcheng Tong, Wei Yang. 2024-08-06. Diagnosis with Metagenomic Next-Generation Sequencing (mNGS) technology and real-time PCR for SARS-CoV-2 Omicron detection using various nasopharyngeal swabs in SARS-CoV-2 Omicron.. https://doi.org/10.1371/journal.pone.0305289

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans