Agile design and development of a high throughput cobas SARS-CoV-2 RT-PCR diagnostic test.

Diagnostic testing is essential for management of the COVID-19 pandemic. An agile assay design methodology, optimized for the cobas® 6800/8800 system, was used to develop a dual-target, qualitative SARS-CoV-2 RT-PCR test using commercially available reagents and existing sample processing and thermocycling profiles. The limit of detection was 30-52 copies/mL for USA-WA1/2020. Assay sensitivity was confirmed for SARS-CoV-2 variants Alpha, Beta, Gamma, Delta and Kappa. The coefficients of variation of the cycle threshold number (Ct) were between 1.1 and 2.2%. There was no difference in Ct using nasopharyngeal compared to oropharyngeal swabs in universal transport medium (UTM). A small increase in Ct was observed with specimens collected in cobas PCR medium compared to UTM. In silico analysis indicated that the dual-target test is capable of detecting all >1,800,000 SARS-CoV-2 sequences in the GISAID database. Our agile assay design approach facilitated rapid development and deployment of this SARS-CoV-2 RT-PCR test.

Clinical evaluation of multiplex RT-PCR assays for the detection of influenza A/B and respiratory syncytial virus using a high throughput system.

BACKGROUND: Lower respiratory tract infections are a major threat to public health systems worldwide, with RSV and influenza being the main agents causing hospitalization. In outbreak situations, high-volume respiratory testing is needed. In this study, we evaluated the analytical and clinical performance of a pre-designed primer/probe set for the simultaneous multiplex detection of both viruses on a high-throughput platform, the cobas® 6800, using the "open channel" of the system for integration of lab-developed assays for the detection of influenza and RSV. RESULTS: Using the influenza/RSV qPCR Assay with swabs, LoD (95%) in TCID50/mL for influenza-A was 0.009, influenza-B 0.003, RSV-A 0.202, and RSV-B 0.009. Inter-run variability (3xLoD) was low (<1 Ct for all targets). Of 371 clinical respiratory specimens analyzed, results were concordant for 358 samples. The calculated sensitivity and specificity of the assay were 98.3% and 98.4% for Flu-A, 100% and 98.5% for Flu-B, and 98.6% and 99.7% for RSV. All quality assessment panel specimens (N = 63, including avian influenza strains) were correctly identified. None of the tested microorganisms showed cross-reactivity. CONCLUSION: Compared with CE-IVD assays, the assay evaluated here showed good analytical and clinical sensitivity and specificity with broad coverage of different virus strains. It offers high-throughput capacity with low hands-on time, facilitating the laboratory management of large respiratory outbreaks.

An efficient and high-throughput approach for experimental validation of novel human gene predictions.

A highly automated RT-PCR-based approach has been established to validate novel human gene predictions with no prior experimental evidence of mRNA splicing (ab initio predictions). Ab initio gene predictions were selected for high-throughput validation using predicted protein classification, sequence similarity to other genomes, colocalization with an MPSS tag, or microarray expression. Initial microarray prioritization followed by RT-PCR validation was the most efficient combination, resulting in approximately 35% of the ab initio predictions being validated by RT-PCR. Of the 7252 novel genes that were prioritized and processed, 796 constituted real transcripts. In addition, high-throughput RACE successfully extended the 5' and/or 3' ends of >60% of RT-PCR-validated genes. Reevaluation of these transcripts produced 574 novel transcripts using RefSeq as a reference. RT-PCR sequencing in combination with RACE on ab initio gene predictions could be used to define the transcriptome across all species.

Assessing gene expression variation in normal human tissues using GeneTag, a novel, global, sensitive profiling method.

GeneTag is a novel expression profiling method that allows the visualization, quantification and identification of expressed genes-whether known or novel-in any species, tissue or cell type, independent of knowledge of the underlying sequence. Here we describe the application of this method to determine variation of gene expression in individual human liver samples and the identification of tissue-specific genes by comparing expression patterns across several human organs. Expression data are stored in a database for future reference and data analysis relies on proprietary software, which allows complex comparisons to be performed. Differentially expressed genes are quickly identified through a link to a sequence database. The results from our study underscore the importance of knowledge of individual variation of gene expression for the design and interpretation of transcript profiling experiments in the context of any biological question.