Profiling of SARS-CoV-2 Subgenomic RNAs in Clinical Specimens

ABSTRACT SARS-CoV-2 transcribes a set of subgenomic RNAs (sgRNAs) essential for the translation of structural and accessory proteins to sustain its life cycle. We applied RNA-seq on 375 respiratory samples from individual COVID-19 patients and revealed that the majority of the sgRNAs were canonical...

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Main Authors: Zigui Chen, Rita Way Yin Ng, Grace Lui, Lowell Ling, Chit Chow, Apple Chung Man Yeung, Siaw Shi Boon, Maggie Haitian Wang, Kate Ching Ching Chan, Renee Wan Yi Chan, David Shu Cheong Hui, Paul Kay Sheung Chan
Format: Article
Language:English
Published: American Society for Microbiology 2022-04-01
Series:Microbiology Spectrum
Subjects:
Online Access:https://journals.asm.org/doi/10.1128/spectrum.00182-22
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author Zigui Chen
Rita Way Yin Ng
Grace Lui
Lowell Ling
Chit Chow
Apple Chung Man Yeung
Siaw Shi Boon
Maggie Haitian Wang
Kate Ching Ching Chan
Renee Wan Yi Chan
David Shu Cheong Hui
Paul Kay Sheung Chan
author_facet Zigui Chen
Rita Way Yin Ng
Grace Lui
Lowell Ling
Chit Chow
Apple Chung Man Yeung
Siaw Shi Boon
Maggie Haitian Wang
Kate Ching Ching Chan
Renee Wan Yi Chan
David Shu Cheong Hui
Paul Kay Sheung Chan
author_sort Zigui Chen
collection DOAJ
description ABSTRACT SARS-CoV-2 transcribes a set of subgenomic RNAs (sgRNAs) essential for the translation of structural and accessory proteins to sustain its life cycle. We applied RNA-seq on 375 respiratory samples from individual COVID-19 patients and revealed that the majority of the sgRNAs were canonical transcripts with N being the most abundant (36.2%), followed by S (11.6%), open reading frame 7a (ORF7a; 10.3%), M (8.4%), ORF3a (7.9%), ORF8 (6.0%), E (4.6%), ORF6 (2.5%), and ORF7b (0.3%); but ORF10 was not detected. The profile of most sgRNAs, except N, showed an independent association with viral load, time of specimen collection after onset, age of the patient, and S-614D/G variant with ORF7b and then ORF6 being the most sensitive to changes in these characteristics. Monitoring of 124 serial samples from 10 patients using sgRNA-specific real-time RT-PCR revealed a potential of adopting sgRNA as a marker of viral activity. Respiratory samples harboring a full set of canonical sgRNAs were mainly collected early within 1 to 2 weeks from onset, and most of the stool samples (90%) were negative for sgRNAs despite testing positive by diagnostic PCR targeting genomic RNA. ORF7b was the first to become undetectable and again being the most sensitive surrogate marker for a full set of canonical sgRNAs in clinical samples. The potential of using sgRNA to monitor viral activity and progression of SARS-CoV-2 infection, and hence as one of the objective indicators to triage patients for isolation and treatment should be considered. IMPORTANCE Attempts to use subgenomic RNAs (sgRNAs) of SARS-CoV-2 to identify active infection of COVID-19 have produced diverse results. In this work, we applied next-generation sequencing and RT-PCR to profile the full spectrum of SARS-CoV-2 sgRNAs in a large cohort of respiratory and stool samples collected throughout infection. Numerous known and novel discontinuous transcription events potentially encoding full-length, deleted and frameshift proteins were observed. In particular, the expression profile of canonical sgRNAs was associated with genomic RNA level and clinical characteristics. Our study found sgRNAs as potential biomarkers for monitoring infectivity and progression of SARS-CoV-2 infection, which provides an alternative target for the management and treatment of COVID-19 patients.
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spelling doaj.art-161448ee7352453e982fc32fda139d642022-12-22T01:09:40ZengAmerican Society for MicrobiologyMicrobiology Spectrum2165-04972022-04-0110210.1128/spectrum.00182-22Profiling of SARS-CoV-2 Subgenomic RNAs in Clinical SpecimensZigui Chen0Rita Way Yin Ng1Grace Lui2Lowell Ling3Chit Chow4Apple Chung Man Yeung5Siaw Shi Boon6Maggie Haitian Wang7Kate Ching Ching Chan8Renee Wan Yi Chan9David Shu Cheong Hui10Paul Kay Sheung Chan11Department of Microbiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, ChinaDepartment of Microbiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, ChinaDepartment of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, ChinaDepartment of Anaesthesia and Intensive Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, ChinaDepartment of Anatomical and Cellular Pathology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, ChinaDepartment of Microbiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, ChinaDepartment of Microbiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, ChinaJockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, ChinaDepartment of Paediatrics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, ChinaDepartment of Paediatrics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, ChinaDepartment of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, ChinaDepartment of Microbiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, ChinaABSTRACT SARS-CoV-2 transcribes a set of subgenomic RNAs (sgRNAs) essential for the translation of structural and accessory proteins to sustain its life cycle. We applied RNA-seq on 375 respiratory samples from individual COVID-19 patients and revealed that the majority of the sgRNAs were canonical transcripts with N being the most abundant (36.2%), followed by S (11.6%), open reading frame 7a (ORF7a; 10.3%), M (8.4%), ORF3a (7.9%), ORF8 (6.0%), E (4.6%), ORF6 (2.5%), and ORF7b (0.3%); but ORF10 was not detected. The profile of most sgRNAs, except N, showed an independent association with viral load, time of specimen collection after onset, age of the patient, and S-614D/G variant with ORF7b and then ORF6 being the most sensitive to changes in these characteristics. Monitoring of 124 serial samples from 10 patients using sgRNA-specific real-time RT-PCR revealed a potential of adopting sgRNA as a marker of viral activity. Respiratory samples harboring a full set of canonical sgRNAs were mainly collected early within 1 to 2 weeks from onset, and most of the stool samples (90%) were negative for sgRNAs despite testing positive by diagnostic PCR targeting genomic RNA. ORF7b was the first to become undetectable and again being the most sensitive surrogate marker for a full set of canonical sgRNAs in clinical samples. The potential of using sgRNA to monitor viral activity and progression of SARS-CoV-2 infection, and hence as one of the objective indicators to triage patients for isolation and treatment should be considered. IMPORTANCE Attempts to use subgenomic RNAs (sgRNAs) of SARS-CoV-2 to identify active infection of COVID-19 have produced diverse results. In this work, we applied next-generation sequencing and RT-PCR to profile the full spectrum of SARS-CoV-2 sgRNAs in a large cohort of respiratory and stool samples collected throughout infection. Numerous known and novel discontinuous transcription events potentially encoding full-length, deleted and frameshift proteins were observed. In particular, the expression profile of canonical sgRNAs was associated with genomic RNA level and clinical characteristics. Our study found sgRNAs as potential biomarkers for monitoring infectivity and progression of SARS-CoV-2 infection, which provides an alternative target for the management and treatment of COVID-19 patients.https://journals.asm.org/doi/10.1128/spectrum.00182-22RT-PCRCOVID-19RNA-seqSARS-CoV-2subgenomic
spellingShingle Zigui Chen
Rita Way Yin Ng
Grace Lui
Lowell Ling
Chit Chow
Apple Chung Man Yeung
Siaw Shi Boon
Maggie Haitian Wang
Kate Ching Ching Chan
Renee Wan Yi Chan
David Shu Cheong Hui
Paul Kay Sheung Chan
Profiling of SARS-CoV-2 Subgenomic RNAs in Clinical Specimens
Microbiology Spectrum
RT-PCR
COVID-19
RNA-seq
SARS-CoV-2
subgenomic
title Profiling of SARS-CoV-2 Subgenomic RNAs in Clinical Specimens
title_full Profiling of SARS-CoV-2 Subgenomic RNAs in Clinical Specimens
title_fullStr Profiling of SARS-CoV-2 Subgenomic RNAs in Clinical Specimens
title_full_unstemmed Profiling of SARS-CoV-2 Subgenomic RNAs in Clinical Specimens
title_short Profiling of SARS-CoV-2 Subgenomic RNAs in Clinical Specimens
title_sort profiling of sars cov 2 subgenomic rnas in clinical specimens
topic RT-PCR
COVID-19
RNA-seq
SARS-CoV-2
subgenomic
url https://journals.asm.org/doi/10.1128/spectrum.00182-22
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