In a recently published ‘Letter to the Editor’ in the journal Microbiology Spectrum, scientists have described the procedure of polymerase chain reaction (PCR)-based genotyping in identifying delta-omicron coinfection in clinical samples.
Study: Identification of Omicron-Delta Coinfections Using PCR-Based Genotyping. Image Credit: NIAID
Background
The most recently emerged omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a sharp rise in coronavirus disease 2019 (COVID-19) cases worldwide. A heavily mutated spike protein is responsible for significantly increased transmissibility and immune evasion ability. The omicron variant was first detected in South Africa on November 24, 2021, and soon became predominant worldwide. However, despite high transmissibility and infectivity, the variant mostly causes mild-to-moderate infections.
Before the emergence of the omicron variant, the delta variant of SARS-CoV-2 was predominantly circulating in the US and was responsible for more than 99% of all detected COVID-19 cases. During the delta wave, the US experienced over 100,000 cases per day. Unlike omicron infections, delta infections are associated with high morbidity and mortality.
In many countries across the world, including the US, COVID-19 cases with delta–omicron coinfections have been detected. The whole-genome sequencing analysis has confirmed the presence of both delta and omicron infection. However, evidence suggests that any one of the variants may outcompete the other variant during the course of dual infection.
In the current study, the scientists have described the procedure of detecting delta–omicron confection in clinical samples using a PCR-based genotyping panel.
They have detected the coinfection in four samples. In two samples, they have applied reverse transcription-droplet digital PCR and two distinct amplicon-based sequencing methods to identify delta-omicron coinfections. They have performed two separate rounds of hybrid-capture sequencing in the other two samples to identify coinfections.
Procedures to identify delta-omicron coinfection
The scientists extracted RNAs from a total of 10,000 randomly selected clinical samples with RT-PCR-confirmed SARS-CoV-2 infections. To differentiate between the delta and omicron variants, they selected four specific genomic targets (G8393A, T13195C, C21618G, C23202A) and performed allele-specific PCR to detect the targets. In four out of 10,000 tested samples, they observed intermediate levels of amplification for both alleles on all four targets. This indicates the possibility of delta-omicron coinfection.
In two out of four samples with possible coinfections, they performed another PCR assay to detect spike-gene target failure, and a RT-droplet digital PCR assay targeting four different spike gene loci (417K, 452L, 484E, and 501N). In addition, they utilized the Swift Normalase Amplicon Panel (SNAP) to perform whole-genome sequencing analysis in these two samples. The SNAP provides a robust sequencing platform for complete viral genome coverage and subgenomic RNA detection.
The whole-genome sequencing identified viral genomes specific to delta lineages. In addition, no spike-gene target failure was detected in the samples. However, the minor alleles (the second most common allele at a genetic locus) corresponding to omicron-specific mutations were detected at 5% - 40% frequencies. Furthermore, the results obtained from RT-droplet digital PCR also showed allele-specific droplets in all four target loci at 18% - 34% frequencies. These findings further indicate the presence of coinfection.
The main benefit of droplet digital PCR is extensive partitioning of the sample. The method is based on water-oil emulsion droplet technology. The sample of interest is divided into multiple droplets, and PCR-mediated amplification of the target sequences occurs in each droplet.
In the other two samples, delta-omicron coinfection was identified using the same allele-specific PCR. These samples were subjected to two rounds of hybrid-capture sequencing to confirm the allele frequencies. Collectively, the findings strongly indicate the presence of coinfection.
Study significance
The study highlights the significance of PCR-based genotyping in rapidly identifying delta-omicron coinfections in clinical samples. From canonical genomic sequences, it is challenging to identify coinfections.
Because of high levels of community transmission of different viral variants, the prevalence of coinfections is likely to increase with time. The identification of coinfection is particularly vital as persistent dual infection by two distinct variants can lead to a combination of genetic materials and the subsequent emergence of recombinant variants.
Journal reference:
- Identification of Omicron-Delta Coinfections Using PCR-Based Genotyping Pavitra Roychoudhury,, Shishi Luo, Kathleen Hayashibara, Pooneh Hajian, Margaret G. Mills, Jean Lozach, Tyler Cassens, Seffir T. Wendm, Isabel Arnould, David Becker, Tim Wesselman, Jeremy Davis-Turak, Richard Creager, Eric Lai, Keith R. Jerome, Tracy Basler, Andrew Dei Rossi, William Lee, Alexander L. Greninger, https://journals.asm.org/doi/epub/10.1128/spectrum.00605-22