Digital PCR can augment the interpretation of RT-qPCR Cq values for SARS-CoV-2 diagnostics.

Coronavirus disease 2019 (COVID-19) is an infectious, acute respiratory disease caused mainly by person-to-person transmission of the coronavirus SARS-CoV-2. Its emergence has caused a world-wide acute health crisis, intensified by the challenge of reliably identifying individuals likely to transmit the disease. Diagnosis is hampered by the many unknowns surrounding this disease, including those relating to infectious viral burden. This uncertainty is exacerbated by disagreement surrounding the clinical relevance of molecular testing using reverse transcription quantitative PCR (RT-qPCR) for the presence of viral RNA, most often based on the reporting of quantification cycles (Cq), which is also termed the cycle threshold (Ct) or crossing point (Cp). Despite it being common knowledge that Cqs are relative values varying according to a wide range of different parameters, there have been efforts to use them as though they were absolute units, with Cqs below an arbitrarily determined value, deemed to signify a positive result and those above, a negative one. Our results investigated the effects of a range of common variables on Cq values. These data include a detailed analysis of the effect of different carrier molecules on RNA extraction. The impact of sample matrix of buccal swabs and saliva on RNA extraction efficiency was demonstrated in RT-qPCR and the impact of potentially inhibiting compounds in urine along with bile salts were investigated in RT-digital PCR (RT-dPCR). The latter studies were performed such that the impact on the RT step could be separated from the PCR step. In this way, the RT was shown to be more susceptible to inhibitors than the PCR. Together, these studies demonstrate that the consequent variability of test results makes subjective Cq cut-off values unsuitable for the identification of infectious individuals. We also discuss the importance of using reliable control materials for accurate quantification and highlight the substantial role played by dPCR as a method for their development.

Whole-genome amplification of single-cell genomes for next-generation sequencing.

DNA sequence analysis and genotyping of biological samples using next-generation sequencing (NGS), microarrays, or real-time PCR is often limited by the small amount of sample available. A single cell contains only one to four copies of the genomic DNA, depending on the organism (haploid or diploid organism) and the cell-cycle phase. The DNA content of a single cell ranges from a few femtograms in bacteria to picograms in mammalia. In contrast, a deep analysis of the genome currently requires a few hundred nanograms up to micrograms of genomic DNA for library formation necessary for NGS sequencing or labeling protocols (e.g., microarrays). Consequently, accurate whole-genome amplification (WGA) of single-cell DNA is required for reliable genetic analysis (e.g., NGS) and is particularly important when genomic DNA is limited. The use of single-cell WGA has enabled the analysis of genomic heterogeneity of individual cells (e.g., somatic genomic variation in tumor cells). This unit describes how the genome of single cells can be used for WGA for further genomic studies, such as NGS. Recommendations for isolation of single cells are given and common sources of errors are discussed.