Rapid identification and tracking of emerging SARS-CoV-2 variants are critical for understanding the transmission dynamics and developing strategies for interrupting the transmission chain. Next-Generation Sequencing (NGS) is an exceptional tool for whole-genome analysis and deciphering new mutations. The technique has been instrumental in identifying the variants of concern (VOC) and tracking this pandemic. However, NGS is complex and expensive for large-scale adoption, and epidemiological monitoring with NGS alone could be unattainable in limited-resource settings. In this study, we explored the application of RT-qPCR-based detection of the variant identified by NGS. We analyzed a total of 78 deidentified samples that screened positive for SARS-CoV-2 from two timeframes, August 2020 and July 2021. All 78 samples were classified into WHO lineages by whole-genome sequencing and then compared with two commercially available RT-qPCR assays for spike protein mutation(s). The data showed good concordance between RT-qPCR and NGS analysis for specific SARS-CoV-2 lineages and characteristic mutations. RT-qPCR assays are quick and cost-effective and thus can be implemented in synergy with NGS for screening NGS-identified mutations of SARS-CoV-2 for clinical and epidemiological interest. Strategic use of NGS and RT-qPCR can offer several COVID-19 epidemiological advantages.

BackgroundUrinary tract infections (UTIs) remain a diagnostic challenge and often promote antibiotic overuse. Despite urine culture being the gold standard for UTI diagnosis, some uropathogens may lead to false-negative or inconclusive results. Although PCR testing is fast and highly sensitive, its diagnostic yield is limited to targeted microorganisms. Metagenomic next-generation sequencing (mNGS) is a hypothesis-free approach with potential of deciphering the urobiome. However, clinically relevant information is often buried in the enormous amount of sequencing data.MethodsPrecision metagenomics (PM) is a hybridization capture-based method with potential of enhanced discovery power and better diagnostic yield without diluting clinically relevant information. We collected 47 urine samples of clinically suspected UTI and in parallel tested each sample by microbial culture, PCR, and PM; then, we comparatively analyzed the results. Next, we phenotypically classified the cumulative microbial population using the Explify® data analysis platform for potential pathogenicity.ResultsResults revealed 100% positive predictive agreement (PPA) with culture results, which identified only 13 different microorganisms, compared to 19 and 62 organisms identified by PCR and PM, respectively. All identified organisms were classified into phenotypic groups (0–3) with increasing pathogenic potential and clinical relevance. This PM can simultaneously quantify and phenotypically classify the organisms readily through bioinformatic platforms like Explify®, essentially providing dissected and quantitative results for timely and accurate empiric UTI treatment.ConclusionPM offers potential for building effective diagnostic models beyond usual care testing in complex UTI diseases. Future studies should assess the impact of PM-guided UTI management on clinical outcomes.

Although it is clinically important for acute respiratory tract (co)infections to have a rapid and accurate diagnosis, it is critical that respiratory medicine understands the advantages of current laboratory methods. In this study, we tested nasopharyngeal samples (n = 29) with a commercially available PCR assay and compared the results with those of a hybridization-capture-based mNGS workflow. Detection criteria for positive PCR samples was Ct < 35 and for mNGS samples it was >40% target coverage, median depth of 1X and RPKM > 10. A high degree of concordance (98.33% PPA and 100% NPA) was recorded. However, mNGS yielded positively 29 additional microorganisms (23 bacteria, 4 viruses, and 2 fungi) beyond PCR. We then characterized the microorganisms of each method into three phenotypic categories using the IDbyDNA Explify® Platform (Illumina® Inc, San Diego, CA, USA) for consideration of infectivity and trafficking potential to the lower respiratory region. The findings are significant for providing a comprehensive yet clinically relevant microbiology profile of acute upper respiratory infection, especially important in immunocompromised or immunocompetent with comorbidity respiratory cases or where traditional syndromic approaches fail to identify pathogenicity. Accordingly, this technology can be used to supplement current syndrome-based tests, and data can quickly and effectively be phenotypically characterized for trafficking potential, clinical (co)infection, and comorbid consideration—with promise to reduce morbidity and mortality.

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