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Achouri E, Felt SA, Hackbart M, Rivera-Espinal NS, López CB. VODKA2: a fast and accurate method to detect non-standard viral genomes from large RNA-seq data sets. RNA (NEW YORK, N.Y.) 2023; 30:16-25. [PMID: 37891004 PMCID: PMC10726161 DOI: 10.1261/rna.079747.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 10/12/2023] [Indexed: 10/29/2023]
Abstract
During viral replication, viruses carrying an RNA genome produce non-standard viral genomes (nsVGs), including copy-back viral genomes (cbVGs) and deletion viral genomes (delVGs), that play a crucial role in regulating viral replication and pathogenesis. Because of their critical roles in determining the outcome of RNA virus infections, the study of nsVGs has flourished in recent years, exposing a need for bioinformatic tools that can accurately identify them within next-generation sequencing data obtained from infected samples. Here, we present our data analysis pipeline, Viral Opensource DVG Key Algorithm 2 (VODKA2), that is optimized to run on a parallel computing environment for fast and accurate detection of nsVGs from large data sets.
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Affiliation(s)
- Emna Achouri
- Department of Molecular Microbiology and Center for Women's Infectious Disease Research, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| | - Sébastien A Felt
- Department of Molecular Microbiology and Center for Women's Infectious Disease Research, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| | - Matthew Hackbart
- Department of Molecular Microbiology and Center for Women's Infectious Disease Research, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| | - Nicole S Rivera-Espinal
- Department of Molecular Microbiology and Center for Women's Infectious Disease Research, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| | - Carolina B López
- Department of Molecular Microbiology and Center for Women's Infectious Disease Research, Washington University School of Medicine, St. Louis, Missouri 63110, USA
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Aguilar Rangel M, Dolan PT, Taguwa S, Xiao Y, Andino R, Frydman J. High-resolution mapping reveals the mechanism and contribution of genome insertions and deletions to RNA virus evolution. Proc Natl Acad Sci U S A 2023; 120:e2304667120. [PMID: 37487061 PMCID: PMC10400975 DOI: 10.1073/pnas.2304667120] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 06/07/2023] [Indexed: 07/26/2023] Open
Abstract
RNA viruses rapidly adapt to selective conditions due to the high intrinsic mutation rates of their RNA-dependent RNA polymerases (RdRps). Insertions and deletions (indels) in viral genomes are major contributors to both deleterious mutational load and evolutionary novelty, but remain understudied. To characterize the mechanistic details of their formation and evolutionary dynamics during infection, we developed a hybrid experimental-bioinformatic approach. This approach, called MultiMatch, extracts insertions and deletions from ultradeep sequencing experiments, including those occurring at extremely low frequencies, allowing us to map their genomic distribution and quantify the rates at which they occur. Mapping indel mutations in adapting poliovirus and dengue virus populations, we determine the rates of indel generation and identify mechanistic and functional constraints shaping indel diversity. Using poliovirus RdRp variants of distinct fidelity and genome recombination rates, we demonstrate tradeoffs between fidelity and Indel generation. Additionally, we show that maintaining translation frame and viral RNA structures constrain the Indel landscape and that, due to these significant fitness effects, Indels exert a significant deleterious load on adapting viral populations. Conversely, we uncover positively selected Indels that modulate RNA structure, generate protein variants, and produce defective interfering genomes in viral populations. Together, our analyses establish the kinetic and mechanistic tradeoffs between misincorporation, recombination, and Indel rates and reveal functional principles defining the central role of Indels in virus evolution, emergence, and the regulation of viral infection.
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Affiliation(s)
| | - Patrick T. Dolan
- Department of Biology, Stanford University, Stanford, CA94305
- Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA94143
| | - Shuhei Taguwa
- Department of Biology, Stanford University, Stanford, CA94305
- Research Institute for Microbial Diseases, Osaka University, Yamadaoka, Suita, Osaka565-0871, Japan
| | - Yinghong Xiao
- Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA94143
| | - Raul Andino
- Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA94143
| | - Judith Frydman
- Department of Biology, Stanford University, Stanford, CA94305
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Zhou T, Gilliam NJ, Li S, Spandau S, Osborn RM, Connor S, Anderson CS, Mariani TJ, Thakar J, Dewhurst S, Mathews DH, Huang L, Sun Y. Generation and Functional Analysis of Defective Viral Genomes during SARS-CoV-2 Infection. mBio 2023; 14:e0025023. [PMID: 37074178 PMCID: PMC10294654 DOI: 10.1128/mbio.00250-23] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 03/28/2023] [Indexed: 04/20/2023] Open
Abstract
Defective viral genomes (DVGs) have been identified in many RNA viruses as a major factor influencing antiviral immune response and viral pathogenesis. However, the generation and function of DVGs in SARS-CoV-2 infection are less known. In this study, we elucidated DVG generation in SARS-CoV-2 and its relationship with host antiviral immune response. We observed DVGs ubiquitously from transcriptome sequencing (RNA-seq) data sets of in vitro infections and autopsy lung tissues of COVID-19 patients. Four genomic hot spots were identified for DVG recombination, and RNA secondary structures were suggested to mediate DVG formation. Functionally, bulk and single-cell RNA-seq analysis indicated the interferon (IFN) stimulation of SARS-CoV-2 DVGs. We further applied our criteria to the next-generation sequencing (NGS) data set from a published cohort study and observed a significantly higher amount and frequency of DVG in symptomatic patients than those in asymptomatic patients. Finally, we observed exceptionally diverse DVG populations in one immunosuppressive patient up to 140 days after the first positive test of COVID-19, suggesting for the first time an association between DVGs and persistent viral infections in SARS-CoV-2. Together, our findings strongly suggest a critical role of DVGs in modulating host IFN responses and symptom development, calling for further inquiry into the mechanisms of DVG generation and into how DVGs modulate host responses and infection outcome during SARS-CoV-2 infection. IMPORTANCE Defective viral genomes (DVGs) are generated ubiquitously in many RNA viruses, including SARS-CoV-2. Their interference activity to full-length viruses and IFN stimulation provide the potential for them to be used in novel antiviral therapies and vaccine development. SARS-CoV-2 DVGs are generated through the recombination of two discontinuous genomic fragments by viral polymerase complex, and this recombination is also one of the major mechanisms for the emergence of new coronaviruses. Focusing on the generation and function of SARS-CoV-2 DVGs, these studies identify new hot spots for nonhomologous recombination and strongly suggest that the secondary structures within viral genomes mediate the recombination. Furthermore, these studies provide the first evidence for IFN stimulation activity of de novo DVGs during natural SARS-CoV-2 infection. These findings set up the foundation for further mechanism studies of SARS-CoV-2 recombination and provide evidence to harness the immunostimulatory potential of DVGs in the development of a vaccine and antivirals for SARS-CoV-2.
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Affiliation(s)
- Terry Zhou
- Department of Immunology and Microbiology, University of Rochester Medical Center, Rochester, New York, USA
| | - Nora J. Gilliam
- Department of Immunology and Microbiology, University of Rochester Medical Center, Rochester, New York, USA
- Medical Scientist Training Program, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
- Translational Biomedical Sciences PhD Program, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
| | - Sizhen Li
- School of Electrical Engineering & Computer Science, Oregon State University, Corvallis, Oregon, USA
| | - Simone Spandau
- Department of Immunology and Microbiology, University of Rochester Medical Center, Rochester, New York, USA
| | - Raven M. Osborn
- Department of Immunology and Microbiology, University of Rochester Medical Center, Rochester, New York, USA
- Translational Biomedical Sciences PhD Program, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
| | - Sarah Connor
- Department of Pediatrics and Center for Children’s Health Research, University of Rochester, Rochester, New York, USA
| | - Christopher S. Anderson
- Department of Pediatrics and Center for Children’s Health Research, University of Rochester, Rochester, New York, USA
| | - Thomas J. Mariani
- Department of Pediatrics and Center for Children’s Health Research, University of Rochester, Rochester, New York, USA
| | - Juilee Thakar
- Department of Immunology and Microbiology, University of Rochester Medical Center, Rochester, New York, USA
- Department of Biostatistics and Computational Biology, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
- Department of Biomedical Genetics, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
| | - Stephen Dewhurst
- Department of Immunology and Microbiology, University of Rochester Medical Center, Rochester, New York, USA
| | - David H. Mathews
- Department of Biochemistry & Biophysics and Center for RNA Biology, University of Rochester Medical Center, Rochester, New York, USA
| | - Liang Huang
- School of Electrical Engineering & Computer Science, Oregon State University, Corvallis, Oregon, USA
| | - Yan Sun
- Department of Immunology and Microbiology, University of Rochester Medical Center, Rochester, New York, USA
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