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Busa VF, Ando Y, Aigner S, Yee BA, Yeo GW, Leung AK. Transcriptome regulation by PARP13 in basal and antiviral states in human cells. iScience 2024; 27:109251. [PMID: 38495826 PMCID: PMC10943485 DOI: 10.1016/j.isci.2024.109251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 01/09/2024] [Accepted: 02/13/2024] [Indexed: 03/19/2024] Open
Abstract
The RNA-binding protein PARP13 is a primary factor in the innate antiviral response, which suppresses translation and drives decay of bound viral and host RNA. PARP13 interacts with many proteins encoded by interferon-stimulated genes (ISG) to activate antiviral pathways including co-translational addition of ISG15, or ISGylation. We performed enhanced crosslinking immunoprecipitation (eCLIP) and RNA-seq in human cells to investigate PARP13's role in transcriptome regulation for both basal and antiviral states. We find that the antiviral response shifts PARP13 target localization, but not its binding preferences, and that PARP13 supports the expression of ISGylation-related genes, including PARP13's cofactor, TRIM25. PARP13 associates with TRIM25 via RNA-protein interactions, and we elucidate a transcriptome-wide periodicity of PARP13 binding around TRIM25. Taken together, our study implicates PARP13 in creating and maintaining a cellular environment poised for an antiviral response through limiting PARP13 translation, regulating access to distinct mRNA pools, and elevating ISGylation machinery expression.
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Affiliation(s)
- Veronica F. Busa
- Department of Biochemistry and Molecular Biology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
- McKusick-Nathans Institute of the Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Yoshinari Ando
- Department of Biochemistry and Molecular Biology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Stefan Aigner
- Department of Cellular and Molecular Medicine, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
- Stem Cell Program, University of California San Diego, Sanford Consortium for Regenerative Medicine, 2880 Torrey Pines Scenic Drive, La Jolla, CA 92037, USA
- Institute for Genomic Medicine, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | - Brian A. Yee
- Department of Cellular and Molecular Medicine, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
- Stem Cell Program, University of California San Diego, Sanford Consortium for Regenerative Medicine, 2880 Torrey Pines Scenic Drive, La Jolla, CA 92037, USA
- Institute for Genomic Medicine, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | - Gene W. Yeo
- Department of Cellular and Molecular Medicine, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
- Stem Cell Program, University of California San Diego, Sanford Consortium for Regenerative Medicine, 2880 Torrey Pines Scenic Drive, La Jolla, CA 92037, USA
- Institute for Genomic Medicine, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
| | - Anthony K.L. Leung
- Department of Biochemistry and Molecular Biology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
- McKusick-Nathans Institute of the Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Molecular Biology and Genetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
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Dasovich M, Zhuo J, Goodman JA, Thomas A, McPherson RL, Jayabalan AK, Busa VF, Cheng SJ, Murphy BA, Redinger KR, Alhammad YMO, Fehr AR, Tsukamoto T, Slusher BS, Bosch J, Wei H, Leung AKL. High-Throughput Activity Assay for Screening Inhibitors of the SARS-CoV-2 Mac1 Macrodomain. ACS Chem Biol 2022; 17:17-23. [PMID: 34904435 PMCID: PMC8691451 DOI: 10.1021/acschembio.1c00721] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 11/16/2021] [Indexed: 12/11/2022]
Abstract
Macrodomains are a class of conserved ADP-ribosylhydrolases expressed by viruses of pandemic concern, including coronaviruses and alphaviruses. Viral macrodomains are critical for replication and virus-induced pathogenesis; therefore, these enzymes are a promising target for antiviral therapy. However, no potent or selective viral macrodomain inhibitors currently exist, in part due to the lack of a high-throughput assay for this class of enzymes. Here we developed a high-throughput ADP-ribosylhydrolase assay using the SARS-CoV-2 macrodomain Mac1. We performed a pilot screen that identified dasatinib and dihydralazine as ADP-ribosylhydrolase inhibitors. Importantly, dasatinib inhibits SARS-CoV-2 and MERS-CoV Mac1 but not the closest human homologue, MacroD2. Our study demonstrates the feasibility of identifying selective inhibitors based on ADP-ribosylhydrolase activity, paving the way for the screening of large compound libraries to identify improved macrodomain inhibitors and to explore their potential as antiviral therapies for SARS-CoV-2 and future viral threats.
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Affiliation(s)
- Morgan Dasovich
- Department of Biochemistry and Molecular Biology,
Bloomberg School of Public Health, Johns Hopkins University,
Baltimore, Maryland 21205, United States
- Department of Chemistry, Krieger School of Arts and
Sciences, Johns Hopkins University, Baltimore, Maryland 21218,
United States
| | - Junlin Zhuo
- Department of Biochemistry and Molecular Biology,
Bloomberg School of Public Health, Johns Hopkins University,
Baltimore, Maryland 21205, United States
| | - Jack A. Goodman
- Department of Biochemistry and Molecular Biology,
Bloomberg School of Public Health, Johns Hopkins University,
Baltimore, Maryland 21205, United States
| | - Ajit Thomas
- Johns Hopkins Drug Discovery,
Baltimore, Maryland 21205, United States
- Department of Neurology, School of Medicine,
Johns Hopkins University, Baltimore, Maryland 21205,
United States
| | - Robert Lyle McPherson
- Department of Biochemistry and Molecular Biology,
Bloomberg School of Public Health, Johns Hopkins University,
Baltimore, Maryland 21205, United States
| | - Aravinth Kumar Jayabalan
- Department of Biochemistry and Molecular Biology,
Bloomberg School of Public Health, Johns Hopkins University,
Baltimore, Maryland 21205, United States
| | - Veronica F. Busa
- Department of Biochemistry and Molecular Biology,
Bloomberg School of Public Health, Johns Hopkins University,
Baltimore, Maryland 21205, United States
- McKusick-Nathans Department of Genetics Medicine,
School of Medicine, Johns Hopkins
University, Baltimore, Maryland 21205, United
States
| | - Shang-Jung Cheng
- Department of Biochemistry and Molecular Biology,
Bloomberg School of Public Health, Johns Hopkins University,
Baltimore, Maryland 21205, United States
| | - Brennan A. Murphy
- Johns Hopkins Drug Discovery,
Baltimore, Maryland 21205, United States
| | - Karli R. Redinger
- Center for Global Health and Diseases, Case
Western Reserve University, Cleveland, Ohio 44106, United
States
| | - Yousef M. O. Alhammad
- Department of Molecular Biosciences,
University of Kansas, Lawrence, Kansas 66045, United
States
| | - Anthony R. Fehr
- Department of Molecular Biosciences,
University of Kansas, Lawrence, Kansas 66045, United
States
| | - Takashi Tsukamoto
- Johns Hopkins Drug Discovery,
Baltimore, Maryland 21205, United States
- Department of Neurology, School of Medicine,
Johns Hopkins University, Baltimore, Maryland 21205,
United States
| | - Barbara S. Slusher
- Johns Hopkins Drug Discovery,
Baltimore, Maryland 21205, United States
- Department of Neurology, School of Medicine,
Johns Hopkins University, Baltimore, Maryland 21205,
United States
| | - Jürgen Bosch
- Center for Global Health and Diseases, Case
Western Reserve University, Cleveland, Ohio 44106, United
States
- InterRayBio, LLC,
Cleveland, Ohio 44106, United States
| | - Huijun Wei
- Johns Hopkins Drug Discovery,
Baltimore, Maryland 21205, United States
- Department of Neurology, School of Medicine,
Johns Hopkins University, Baltimore, Maryland 21205,
United States
| | - Anthony K. L. Leung
- Department of Biochemistry and Molecular Biology,
Bloomberg School of Public Health, Johns Hopkins University,
Baltimore, Maryland 21205, United States
- McKusick-Nathans Department of Genetics Medicine,
School of Medicine, Johns Hopkins
University, Baltimore, Maryland 21205, United
States
- Department of Oncology and Department of
Molecular Biology and Genetics, School of Medicine, Johns Hopkins
University, Baltimore, Maryland 21205, United
States
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Busa VF, Favorov AV, Fertig EJ, Leung AK. Spatial correlation statistics enable transcriptome-wide characterization of RNA structure binding. Cell Rep Methods 2021; 1:100088. [PMID: 35474897 PMCID: PMC9017189 DOI: 10.1016/j.crmeth.2021.100088] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 06/23/2021] [Accepted: 08/30/2021] [Indexed: 11/20/2022]
Abstract
Molecular interactions at identical transcriptomic locations or at proximal but non-overlapping sites can mediate RNA modification and regulation, necessitating tools to uncover these spatial relationships. We present nearBynding, a flexible algorithm and software pipeline that models spatial correlation between transcriptome-wide tracks from diverse data types. nearBynding can process and correlate interval as well as continuous data and incorporate experimentally derived or in silico predicted transcriptomic tracks. nearBynding offers visualization functions for its statistics to identify colocalizations and adjacent features. We demonstrate the application of nearBynding to correlate RNA-binding protein (RBP) binding preferences with other RBPs, RNA structure, or RNA modification. By cross-correlating RBP binding and RNA structure data, we demonstrate that nearBynding recapitulates known RBP binding to structural motifs and provides biological insights into RBP binding preference of G-quadruplexes. nearBynding is available as an R/Bioconductor package and can run on a personal computer, making correlation of transcriptomic features broadly accessible.
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Affiliation(s)
- Veronica F. Busa
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Biochemistry and Molecular Biology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Alexander V. Favorov
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Laboratory of Systems Biology and Computational Genetics, Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia
| | - Elana J. Fertig
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Biomedical Engineering, Johns Hopkins University Whiting School of Engineering, Baltimore, MD 21205, USA
- Department of Applied Mathematics and Statistics, Johns Hopkins University Whiting School of Engineering, Baltimore, MD 21205, USA
| | - Anthony K.L. Leung
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Biochemistry and Molecular Biology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
- Department of Molecular Biology and Genetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
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Fischer JW, Busa VF, Shao Y, Leung AKL. Structure-Mediated RNA Decay by UPF1 and G3BP1. Mol Cell 2020; 78:70-84.e6. [PMID: 32017897 DOI: 10.1016/j.molcel.2020.01.021] [Citation(s) in RCA: 134] [Impact Index Per Article: 33.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2019] [Revised: 11/12/2019] [Accepted: 01/16/2020] [Indexed: 12/21/2022]
Abstract
Post-transcriptional mechanisms regulate the stability and, hence, expression of coding and noncoding RNAs. Sequence-specific features within the 3' untranslated region (3' UTR) often direct mRNAs for decay. Here, we characterize a genome-wide RNA decay pathway that reduces the half-lives of mRNAs based on overall 3' UTR structure formed by base pairing. The decay pathway is independent of specific single-stranded sequences, as regulation is maintained in both the original and reverse complement orientation. Regulation can be compromised by reducing the overall structure by fusing the 3' UTR with an unstructured sequence. Mutating base-paired RNA regions can also compromise this structure-mediated regulation, which can be restored by re-introducing base-paired structures of different sequences. The decay pathway requires the RNA-binding protein UPF1 and its associated protein G3BP1. Depletion of either protein increased steady-state levels of mRNAs with highly structured 3' UTRs as well as highly structured circular RNAs. This structure-dependent mechanism therefore enables cells to selectively regulate coding and noncoding RNAs.
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Affiliation(s)
- Joseph W Fischer
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Biochemistry and Molecular Biology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Veronica F Busa
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Biochemistry and Molecular Biology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Yue Shao
- Department of Biochemistry and Molecular Biology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Anthony K L Leung
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Biochemistry and Molecular Biology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA; Department of Molecular Biology and Genetics, School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA; Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA.
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Abstract
DEAD-box proteins are nonprocessive RNA helicases that play diverse roles in cellular processes. The Neurospora crassa DEAD-box protein CYT-19 promotes mitochondrial group I intron splicing and functions as a general RNA chaperone. CYT-19 includes a disordered, arginine-rich "C-tail" that binds RNA, positioning the helicase core to capture and unwind nearby RNA helices. Here we probed the C-tail further by varying the number and positions of arginines within it. We found that removing sets of as few as four of the 11 arginines reduced RNA unwinding activity (kcat/KM) to a degree equivalent to that seen upon removal of the C-tail, suggesting that a minimum or "threshold" number of arginines is required. In addition, a mutant with 16 arginines displayed RNA unwinding activity greater than that of wild-type CYT-19. The C-tail modifications impacted unwinding only of RNA helices within constructs that included an adjacent helix or structured RNA element that would allow C-tail binding, indicating that the helicase core remained active in the mutants. In addition, changes in RNA unwinding efficiency of the mutants were mirrored by changes in functional RNA affinity, as determined from the RNA concentration dependence of ATPase activity, suggesting that the C-tail functions primarily to increase RNA affinity. Interestingly, the salt concentration dependence of RNA unwinding activity is unaffected by C-tail composition, suggesting that the C-tail uses primarily hydrogen bonding, not electrostatic interactions, to bind double-stranded RNA. Our results provide insights into how an unstructured C-tail contributes to DEAD-box protein activity and suggest parallels with other families of RNA- and DNA-binding proteins.
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Affiliation(s)
- Veronica F Busa
- Department of Molecular Biosciences and Institute for Cellular & Molecular Biology, University of Texas at Austin , Austin, Texas 78712, United States
| | - Maxwell J Rector
- Department of Molecular Biosciences and Institute for Cellular & Molecular Biology, University of Texas at Austin , Austin, Texas 78712, United States
| | - Rick Russell
- Department of Molecular Biosciences and Institute for Cellular & Molecular Biology, University of Texas at Austin , Austin, Texas 78712, United States
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