Accurate detection and quantification of SARS-CoV-2 genomic and subgenomic mRNAs by ddPCR and meta-transcriptomics analysis
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ABSTRACT:
SUBMITTER: Oranger A
PROVIDER: S-EPMC8536764 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiologic agent responsible for the ongoing pandemic of coronavirus disease 2019 (COVID-19). Single cell RNA sequencing (scRNAseq) studies have been valuable for studying SARS-CoV-2 pathogenesis, but the performance of these methods to detect and quantify viral RNAs has not been evaluated. Here we develop an analysis pipeline, single cell coronavirus sequencing (scCoVseq), to quantify unambiguous reads derived from coronavirus genomic (gRNA) and subgenomic mRNAs (sgmRNAs). We use this method to compare the ability of scRNAseq methods developed by 10X Genomics to detect and quantify SARS-CoV-2 RNAs, with particular focus on sgmRNAs. We find that while sequencing libraries from 10X Genomics Chromium Next Gem Single Cell V(D)J (10X 5') contain more unambiguous reads derived from sgmRNAs due to the presence of reads spanning junctions between the viral 5' leader and sgmRNA open reading frames. We demonstrate that by extending read 1 (R1) of 10X 5' leaders we can further increase the number of unambiguous reads from SARS-CoV-2 sgmRNA resulting in more UMIs per sgmRNA per cell. Using this method, which we call 10X 5' Extended R1, we are able quantify viral sgmRNA production per cell, which we believe will improve understanding regarding the dynamics of coronavirus RNA biogenesis over time and across cell types and viruses. We believe this will improve our understanding of coronavirus pathogenesis.
2023-07-30 | GSE189900 | GEO
Project description:The replication of SARS-CoV-2 and other coronaviruses depends on transcription of negative-sense RNA intermediates that serve as the templates for the synthesis of positive-sense genomic RNA (gRNA) and multiple different subgenomic mRNAs (sgRNAs) encompassing fragments arising from discontinuous transcription. Recent studies have aimed to characterize the expression of subgenomic SARS-CoV-2 transcripts in order to investigate their clinical significance. Here, we describe a novel panel of reverse transcription droplet digital PCR (RT-ddPCR) assays designed to specifically quantify multiple different subgenomic SARS-CoV-2 transcripts and distinguish them from transcripts that do not arise from discontinuous transcription at each locus. These assays can be applied to samples from SARS-CoV-2 infected patients to better understand the regulation of SARS-CoV-2 transcription and how different sgRNAs may contribute to viral pathogenesis and clinical disease severity.
| S-EPMC8105137 | biostudies-literature
Project description:Single cell RNA sequencing (scRNAseq) studies have provided critical insight into the pathogenesis of Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2), the causative agent of COronaVIrus Disease 2019 (COVID-19). scRNAseq workflows are generally designed for the detection and quantification of eukaryotic host mRNAs and not viral RNAs. The performance of different scRNAseq methods to study SARS-CoV-2 RNAs has not been thoroughly evaluated. Here, we compare different scRNAseq methods for their ability to quantify and detect SARS-CoV-2 RNAs with a focus on subgenomic mRNAs (sgmRNAs), which are produced only during active viral replication and not present in viral particles. We present a data processing strategy, single cell CoronaVirus sequencing (scCoVseq), which quantifies reads unambiguously assigned to sgmRNAs or genomic RNA (gRNA). Compared to standard 10X Genomics Chromium Next GEM Single Cell 3' (10X 3') and Chromium Next GEM Single Cell V(D)J (10X 5') sequencing, we find that 10X 5' with an extended R1 sequencing strategy maximizes the unambiguous detection of sgmRNAs by increasing the number of reads spanning leader-sgmRNA junction sites. Differential gene expression testing and KEGG enrichment analysis of infected cells compared with bystander or mock cells showed an enrichment for COVID19-associated genes, supporting the ability of our method to accurately identify infected cells. Our method allows for quantification of coronavirus sgmRNA expression at single-cell resolution, and thereby supports high resolution studies of the dynamics of coronavirus RNA synthesis.ImportanceSingle cell RNA sequencing (scRNAseq) has emerged as a valuable tool to study host-viral interactions particularly in the context of COronaVIrus Disease-2019 (COVID-19). scRNAseq has been developed and optimized for analyzing eukaryotic mRNAs, and the ability of scRNAseq to measure RNAs produced by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has not been fully characterized. Here we compare the performance of different scRNAseq methods to detect and quantify SARS-CoV-2 RNAs and develop an analysis workflow to specifically quantify unambiguous reads derived from SARS-CoV-2 genomic RNA and subgenomic mRNAs. Our work demonstrates the strengths and limitations of scRNAseq to measure SARS-CoV-2 RNA and identifies experimental and analytical approaches that allow for SARS-CoV-2 RNA detection and quantification. These developments will allow for studies of coronavirus RNA biogenesis at single-cell resolution to improve our understanding of viral pathogenesis.
| S-EPMC8629185 | biostudies-literature
Project description:Single-cell RNA sequencing (scRNA-Seq) studies have provided critical insight into the pathogenesis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19). scRNA-Seq library preparation methods and data processing workflows are generally designed for the detection and quantification of eukaryotic host mRNAs and not viral RNAs. Here, we compare different scRNA-Seq library preparation methods for their ability to quantify and detect SARS-CoV-2 RNAs with a focus on subgenomic mRNAs (sgmRNAs). We show that compared to 10X Genomics Chromium Next GEM Single Cell 3' (10X 3') libraries or 10X Genomics Chromium Next GEM Single Cell V(D)J (10X 5') libraries sequenced with standard read configurations, 10X 5' libraries sequenced with an extended length read 1 (R1) that covers both cell barcode and transcript sequence (termed "10X 5' with extended R1") increase the number of unambiguous reads spanning leader-sgmRNA junction sites. We further present a data processing workflow, single-cell coronavirus sequencing (scCoVseq), which quantifies reads unambiguously assigned to viral sgmRNAs or viral genomic RNA (gRNA). We find that combining 10X 5' with extended R1 library preparation/sequencing and scCoVseq data processing maximizes the number of viral UMIs per cell quantified by scRNA-Seq. Corresponding sgmRNA expression levels are highly correlated with expression in matched bulk RNA-Seq data sets quantified with established tools for SARS-CoV-2 analysis. Using this scRNA-Seq approach, we find that SARS-CoV-2 gene expression is highly correlated across individual infected cells, which suggests that the proportion of viral sgmRNAs remains generally consistent throughout infection. Taken together, these results and corresponding data processing workflow enable robust quantification of coronavirus sgmRNA expression at single-cell resolution, thereby supporting high-resolution studies of viral RNA processes in individual cells. IMPORTANCE Single-cell RNA sequencing (scRNA-Seq) has emerged as a valuable tool to study host-virus interactions, especially for coronavirus disease 2019 (COVID-19). Here we compare the performance of different scRNA-Seq library preparation methods and sequencing strategies to detect SARS-CoV-2 RNAs and develop a data processing workflow to quantify unambiguous sequence reads derived from SARS-CoV-2 genomic RNA and subgenomic mRNAs. After establishing a workflow that maximizes the detection of SARS-CoV-2 subgenomic mRNAs, we explore patterns of SARS-CoV-2 gene expression across cells with variable levels of total viral RNA, assess host gene expression differences between infected and bystander cells, and identify non-canonical and lowly abundant SARS-CoV-2 RNAs. The sequencing and data processing strategies developed here can enhance studies of coronavirus RNA biology at single-cell resolution and thereby contribute to our understanding of viral pathogenesis.
| S-EPMC10580996 | biostudies-literature
Project description:Quantitative real time PCR (RT-PCR) is widely used as the gold standard for clinical detection of SARS-CoV-2. However, due to the low viral load specimens and the limitations of RT-PCR, significant numbers of false negative reports are inevitable, which results in failure to timely diagnose, cut off transmission, and assess discharge criteria. To improve this situation, an optimized droplet digital PCR (ddPCR) was used for detection of SARS-CoV-2, which showed that the limit of detection of ddPCR is significantly lower than that of RT-PCR. We further explored the feasibility of ddPCR to detect SARS-CoV-2 RNA from 77 patients, and compared with RT-PCR in terms of the diagnostic accuracy based on the results of follow-up survey. 26 patients of COVID-19 with negative RT-PCR reports were reported as positive by ddPCR. The sensitivity, specificity, PPV, NPV, negative likelihood ratio (NLR) and accuracy were improved from 40% (95% CI: 27-55%), 100% (95% CI: 54-100%), 100%, 16% (95% CI: 13-19%), 0.6 (95% CI: 0.48-0.75) and 47% (95% CI: 33-60%) for RT-PCR to 94% (95% CI: 83-99%), 100% (95% CI: 48-100%), 100%, 63% (95% CI: 36-83%), 0.06 (95% CI: 0.02-0.18), and 95% (95% CI: 84-99%) for ddPCR, respectively. Moreover, 6/14 (42.9%) convalescents were detected as positive by ddPCR at 5-12 days post discharge. Overall, ddPCR shows superiority for clinical diagnosis of SARS-CoV-2 to reduce the false negative reports, which could be a powerful complement to the RT-PCR.
| S-EPMC7448897 | biostudies-literature
Project description:The widespread Coronavirus Disease 2019 (COVID-19) is caused by infection with the novel coronavirus SARS-CoV-2. Currently, we have a limited toolset available for visualizing SARS-CoV-2 in cells and tissues, particularly in tissues from patients who died from COVID-19. Generally, single-molecule RNA FISH techniques have shown mixed results in formalin fixed paraffin embedded tissues such as those preserved from human autopsies. Here, we present a platform for preparing autopsy tissue for visualizing SARS-CoV-2 RNA using RNA FISH with amplification by hybridization chain reaction (HCR). We developed probe sets that target different regions of SARS-CoV-2 (including ORF1a and N) as well as probe sets that specifically target SARS-CoV-2 subgenomic mRNAs. We validated these probe sets in cell culture and tissues (lung, lymph node, and placenta) from infected patients. Using this technology, we observe distinct subcellular localization patterns of the ORF1a and N regions, with the ORF1a concentrated around the nucleus and the N showing a diffuse distribution across the cytoplasm. In human lung tissue, we performed multiplexed RNA FISH HCR for SARS-CoV-2 and cell-type specific marker genes. We found viral RNA in cells containing the alveolar type 2 (AT2) cell marker gene ( SFTPC ) and the alveolar macrophage marker gene ( MARCO ), but did not identify viral RNA in cells containing the alveolar type 1 (AT1) cell marker gene ( AGER ). Moreover, we observed distinct subcellular localization patterns of viral RNA in AT2 cells and alveolar macrophages, consistent with phagocytosis of infected cells. In sum, we demonstrate the use of RNA FISH HCR for visualizing different RNA species from SARS-CoV-2 in cell lines and FFPE autopsy specimens. Furthermore, we multiplex this assay with probes for cellular genes to determine what cell-types are infected within the lung. We anticipate that this platform could be broadly useful for studying SARS-CoV-2 pathology in tissues as well as extended for other applications including investigating the viral life cycle, viral diagnostics, and drug screening.
| S-EPMC8366794 | biostudies-literature
Project description:We have developed periscope, a tool for the detection and quantification of subgenomic RNA (sgRNA) in SARS-CoV-2 genomic sequence data. The translation of the SARS-CoV-2 RNA genome for most open reading frames (ORFs) occurs via RNA intermediates termed "subgenomic RNAs." sgRNAs are produced through discontinuous transcription, which relies on homology between transcription regulatory sequences (TRS-B) upstream of the ORF start codons and that of the TRS-L, which is located in the 5' UTR. TRS-L is immediately preceded by a leader sequence. This leader sequence is therefore found at the 5' end of all sgRNA. We applied periscope to 1155 SARS-CoV-2 genomes from Sheffield, United Kingdom, and validated our findings using orthogonal data sets and in vitro cell systems. By using a simple local alignment to detect reads that contain the leader sequence, we were able to identify and quantify reads arising from canonical and noncanonical sgRNA. We were able to detect all canonical sgRNAs at the expected abundances, with the exception of ORF10. A number of recurrent noncanonical sgRNAs are detected. We show that the results are reproducible using technical replicates and determine the optimum number of reads for sgRNA analysis. In VeroE6 ACE2+/- cell lines, periscope can detect the changes in the kinetics of sgRNA in orthogonal sequencing data sets. Finally, variants found in genomic RNA are transmitted to sgRNAs with high fidelity in most cases. This tool can be applied to all sequenced COVID-19 samples worldwide to provide comprehensive analysis of SARS-CoV-2 sgRNA.
| S-EPMC8015849 | biostudies-literature
Project description:The invasive American bullfrog (Lithobates catesbeianus) imperils freshwater biodiversity worldwide. Effective management hinges on early detection of incipient invasions and subsequent rapid response, as established populations are extremely difficult to eradicate. Although environmental DNA (eDNA) detection methods provide a highly sensitive alternative to conventional surveillance techniques, extensive testing is imperative to generate reliable output. Here, we tested and compared the performance of two primer/probe assays to detect and quantify the abundance of bullfrogs in Western Europe in silico and in situ using digital droplet PCR (ddPCR). Although both assays proved to be equally target-specific and sensitive, one outperformed the other in ddPCR detection resolution (i.e., distinguishing groups of target-positive and target-negative droplets), and hence was selected for further analyses. Mesocosm experiments revealed that tadpole abundance and biomass explained 99% of the variation in eDNA concentration. Because per individual eDNA emission rates did not differ significantly among tadpoles and juveniles, and adults mostly reside out of the water, eDNA concentration can be used as an approximation of local bullfrog abundance in natural populations. Seasonal eDNA patterns in three colonized ponds showed parallel fluctuations in bullfrog eDNA concentration. An increase in eDNA concentration was detected in spring, followed by a strong peak coinciding with the breeding season (August, September or October), and continuously low eDNA concentrations during winter. With this study, we report the validation process required for appropriately implementing eDNA barcoding analyses in lentic systems. We demonstrate that this technique can serve as a solid and reliable tool to detect the early stages of bullfrog invasions and to quantify temporal changes in abundance that will be useful in coordinating large-scale bullfrog eradication programs and evaluating their efficiency.
| S-EPMC8163797 | biostudies-literature
Project description:A hallmark of severe acute respiratory syndrome virus (SARS-CoV-2) replication is the discontinuous transcription of open reading frames (ORFs) encoding structural virus proteins. Real-time reverse transcription PCR (RT-qPCR) assays in previous publications used either single or multiplex assays for SARS-CoV-2 genomic RNA detection and a singleplex approach for subgenomic RNA detection. Although multiplex approaches often target multiple genomic RNA segments, an assay that concurrently detects genomic and subgenomic targets has been lacking. To bridge this gap, we developed two duplex one-step RT-qPCR assays that detect SARS-CoV-2 genomic ORF1a and either subgenomic spike or subgenomic ORF3a RNAs. All primers and probes for our assays were designed to bind to variants of SARS-CoV-2. In this study, our assays successfully detected SARS-CoV-2 Washington strain and delta variant isolates at various time points during the course of live virus infection in vitro. The ability to quantify subgenomic SARS-CoV-2 RNA is important, as it may indicate the presence of active replication, particularly in samples collected longitudinally. Furthermore, specific detection of genomic and subgenomic RNAs simultaneously in a single reaction increases assay efficiency, potentially leading to expedited lucidity about viral replication and pathogenesis of any variant of SARS-CoV-2.
| S-EPMC9143037 | biostudies-literature
Project description:BackgroundSome mutations in the receptor binding domain of the SARS-CoV-2 Spike protein are associated with increased transmission or substantial reductions in vaccine efficacy, including in recently described Omicron subvariants. The changing frequencies of these mutations combined with their differing susceptibility to available therapies have posed significant problems for clinicians and public health professionals.ObjectiveTo develop an assay capable of rapidly and accurately identifying variants including Omicron in clinical specimens to enable case tracking and/or selection of appropriate clinical treatment.Study designUsing three duplex RT-ddPCR reactions targeting four amino acids, we tested 419 positive clinical specimens from February to December 2021 during a period of rapidly shifting variant prevalences and compared genotyping results to genome sequences for each sample, determining the sensitivity and specificity of the assay for each variant.ResultsMutation determinations for 99.7% of detected samples agree with NGS data for those samples, and are accurate despite wide variation in RNA concentration and potential confounding factors like transport medium, presence of additional respiratory viruses, and additional mutations in primer and probe sequences. The assay accurately identified the first 15 Omicron variants in our laboratory including the first Omicron in Washington State and discriminated against S-gene dropout Delta specimen.ConclusionWe describe an accurate, precise, and specific RT-ddPCR assay for variant detection that remains robust despite being designed prior the emergence of Delta and Omicron variants. The assay can quickly identify mutations in current and past SARS-CoV-2 variants, and can be adapted to future mutations.
| S-EPMC9212762 | biostudies-literature