1
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Hiruthyaswamy SP, Bose A, Upadhyay A, Raha T, Bhattacharjee S, Singha I, Ray S, Nicky Macarius NM, Viswanathan P, Deepankumar K. Molecular signaling pathways in osteoarthritis and biomaterials for cartilage regeneration: a review. Bioengineered 2025; 16:2501880. [PMID: 40336219 PMCID: PMC12064066 DOI: 10.1080/21655979.2025.2501880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2024] [Revised: 03/07/2025] [Accepted: 04/04/2025] [Indexed: 05/09/2025] Open
Abstract
Osteoarthritis is a prevalent degenerative joint disease characterized by cartilage degradation, synovial inflammation, and subchondral bone alterations, leading to chronic pain and joint dysfunction. Conventional treatments provide symptomatic relief but fail to halt disease progression. Recent advancements in biomaterials, molecular signaling modulation, and gene-editing technologies offer promising therapeutic strategies. This review explores key molecular pathways implicated in osteoarthritis, including fibroblast growth factor, phosphoinositide 3-kinase/Akt, and bone morphogenetic protein signaling, highlighting their roles in chondrocyte survival, extracellular matrix remodeling, and inflammation. Biomaterial-based interventions such as hydrogels, nanoparticles, and chitosan-based scaffolds have demonstrated potential in enhancing cartilage regeneration and targeted drug delivery. Furthermore, CRISPR/Cas9 gene editing holds promise in modifying osteoarthritis-related genes to restore cartilage integrity. The integration of regenerative biomaterials with precision medicine and molecular therapies represents a novel approach for mitigating osteoarthritis progression. Future research should focus on optimizing biomaterial properties, refining gene-editing efficiency, and developing personalized therapeutic strategies. The convergence of bioengineering and molecular science offers new hope for improving joint function and patient quality of life in osteoarthritis management.
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Affiliation(s)
- Samson Prince Hiruthyaswamy
- Department of Biotechnology, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, India
| | - Arohi Bose
- Department of Biotechnology, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, India
| | - Ayushi Upadhyay
- Department of Biotechnology, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, India
| | - Tiasa Raha
- Department of Biotechnology, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, India
| | - Shangomitra Bhattacharjee
- Department of Biotechnology, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, India
| | - Isheeta Singha
- Department of Biotechnology, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, India
| | - Swati Ray
- Department of Biotechnology, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, India
| | | | - Pragasam Viswanathan
- Department of Biotechnology, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, India
| | - Kanagavel Deepankumar
- Department of Biotechnology, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, India
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2
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Chapdelaine-Trépanier V, Shenoy S, Masud W, Minju-Op A, Bérubé MA, Schönherr S, Forer L, Fradet-Turcotte A, Taliun D, Cuella-Martin R. CRISPR-BEasy: a free web-based service for designing sgRNA tiling libraries for CRISPR-dependent base editing screens. Nucleic Acids Res 2025:gkaf382. [PMID: 40377102 DOI: 10.1093/nar/gkaf382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2025] [Revised: 04/15/2025] [Accepted: 04/24/2025] [Indexed: 05/18/2025] Open
Abstract
CRISPR-dependent base editing (BE) enables the modeling and correction of genetic mutations at single-base resolution. Base editing screens, where point mutations are queried en masse, are powerful tools to systematically draw genotype-phenotype associations and characterise the function of genes and other genomic elements. However, the lack of user-friendly web-based tools for designing base editing screens can hinder broad technology adoption. Here, we introduce CRISPR-BEasy (https://crispr-beasy.cerc-genomic-medicine.ca), a free, automated web-based server that streamlines the creation of single guide (sg)RNA tiling libraries for base editing screens. Researchers can provide their genes or genomic features of interest, their base editors of choice, and target sequences to act as positive and negative controls. The server designs and annotates sgRNA libraries by integrating custom code with publicly available tools such as crisprVerse and Ensembl's Variant Effect Predictor. CRISPR-BEasy provides downloadable results, including sgRNA on/off-target scores, predicted mutational outcomes per base editor, and intuitive interactive visualizations for data quality assessment. CRISPR-BEasy also provides a separate tool that assembles sgRNA libraries into oligonucleotides for cloning following the detailed protocol documented in the searchable web server manual. Together, CRISPR-BEasy ensures the seamless design of cloning-ready sgRNA libraries, seeking to democratise access to base editing screening technologies.
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Affiliation(s)
- Vincent Chapdelaine-Trépanier
- Department of Human Genetics, McGill University, Montreal, QC,H3A 0G1, Canada
- Victor Phillip Dahdaleh Institute of Genomic Medicine, McGill University, Montreal, QC,H3A 0G1, Canada
| | - Shamika Shenoy
- Department of Human Genetics, McGill University, Montreal, QC,H3A 0G1, Canada
- Victor Phillip Dahdaleh Institute of Genomic Medicine, McGill University, Montreal, QC,H3A 0G1, Canada
| | - Wardah Masud
- Department of Human Genetics, McGill University, Montreal, QC,H3A 0G1, Canada
- Victor Phillip Dahdaleh Institute of Genomic Medicine, McGill University, Montreal, QC,H3A 0G1, Canada
| | - Amisha Minju-Op
- Department of Human Genetics, McGill University, Montreal, QC,H3A 0G1, Canada
- Victor Phillip Dahdaleh Institute of Genomic Medicine, McGill University, Montreal, QC,H3A 0G1, Canada
| | - Marie-Anne Bérubé
- Department of Molecular Biology, Medical Biochemistry and Pathology, Faculty of Medicine, Université Laval, Québec City, QC,G1V 0A6, Canada
- Oncology Division, Centre Hospitalier Universitaire (CHU) de Québec-Université Laval Research Centre, Québec City, QC,G1R 2J6, Canada
- Université Laval Cancer Research Center, Université Laval, Québec City, QC,G1R 3S3, Canada
| | - Sebastian Schönherr
- Institute of Genetic Epidemiology, Department of Genetics, Medical University of Innsbruck, Innsbruck,6020, Austria
| | - Lukas Forer
- Institute of Genetic Epidemiology, Department of Genetics, Medical University of Innsbruck, Innsbruck,6020, Austria
| | - Amélie Fradet-Turcotte
- Department of Molecular Biology, Medical Biochemistry and Pathology, Faculty of Medicine, Université Laval, Québec City, QC,G1V 0A6, Canada
- Oncology Division, Centre Hospitalier Universitaire (CHU) de Québec-Université Laval Research Centre, Québec City, QC,G1R 2J6, Canada
- Université Laval Cancer Research Center, Université Laval, Québec City, QC,G1R 3S3, Canada
| | - Daniel Taliun
- Department of Human Genetics, McGill University, Montreal, QC,H3A 0G1, Canada
- Victor Phillip Dahdaleh Institute of Genomic Medicine, McGill University, Montreal, QC,H3A 0G1, Canada
| | - Raquel Cuella-Martin
- Department of Human Genetics, McGill University, Montreal, QC,H3A 0G1, Canada
- Victor Phillip Dahdaleh Institute of Genomic Medicine, McGill University, Montreal, QC,H3A 0G1, Canada
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3
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Yeo MJR, Zhang O, Xie X, Nam E, Payne NC, Gosavi PM, Kwok HS, Iram I, Lee C, Li J, Chen NJ, Nguyen K, Jiang H, Wang ZA, Lee K, Mao H, Harry SA, Barakat IA, Takahashi M, Waterbury AL, Barone M, Mattevi A, Carr SA, Udeshi ND, Bar-Peled L, Cole PA, Mazitschek R, Liau BB, Zheng N. UM171 glues asymmetric CRL3-HDAC1/2 assembly to degrade CoREST corepressors. Nature 2025; 639:232-240. [PMID: 39939761 PMCID: PMC11882444 DOI: 10.1038/s41586-024-08532-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Accepted: 12/17/2024] [Indexed: 02/14/2025]
Abstract
UM171 is a potent agonist of ex vivo human haematopoietic stem cell self-renewal1. By co-opting KBTBD4, a substrate receptor of the CUL3-RING E3 ubiquitin ligase (CRL3) complex, UM171 promotes the degradation of the LSD1-CoREST corepressor complex, thereby limiting haematopoietic stem cell attrition2,3. However, the direct target and mechanism of action of UM171 remain unclear. Here we show that UM171 acts as a molecular glue to induce high-affinity interactions between KBTBD4 and HDAC1/2 to promote corepressor degradation. Through proteomics and chemical inhibitor studies, we identify the principal target of UM171 as HDAC1/2. Cryo-electron microscopy analysis of dimeric KBTBD4 bound to UM171 and the LSD1-HDAC1-CoREST complex identifies an asymmetric assembly in which a single UM171 molecule enables a pair of KELCH-repeat propeller domains to recruit the HDAC1 catalytic domain. One KBTBD4 propeller partially masks the rim of the HDAC1 active site, which is exploited by UM171 to extend the E3-neosubstrate interface. The other propeller cooperatively strengthens HDAC1 binding through a distinct interface. The overall CoREST-HDAC1/2-KBTBD4 interaction is further buttressed by the endogenous cofactor inositol hexakisphosphate, which acts as a second molecular glue. The functional relevance of the quaternary complex interaction surfaces is demonstrated by base editor scanning of KBTBD4 and HDAC1. By delineating the direct target of UM171 and its mechanism of action, we reveal how the cooperativity offered by a dimeric CRL3 E3 can be leveraged by a small molecule degrader.
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Affiliation(s)
- Megan J R Yeo
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Olivia Zhang
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Xiaowen Xie
- Department of Pharmacology, University of Washington, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - Eunju Nam
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, USA
| | - N Connor Payne
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Center for Systems Biology, Massachusetts General Hospital, Boston, MA, USA
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Pallavi M Gosavi
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Hui Si Kwok
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Irtiza Iram
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Ceejay Lee
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jiaming Li
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Nicholas J Chen
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA
| | - Khanh Nguyen
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Hanjie Jiang
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, USA
| | - Zhipeng A Wang
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, USA
- Desai Sethi Urology Institute & Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Kwangwoon Lee
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, USA
| | - Haibin Mao
- Department of Pharmacology, University of Washington, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - Stefan A Harry
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA
| | - Idris A Barakat
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Mariko Takahashi
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA
| | - Amanda L Waterbury
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Marco Barone
- Department of Biology and Biotechnology Lazzaro Spallanzani, University of Pavia, Pavia, Italy
| | - Andrea Mattevi
- Department of Biology and Biotechnology Lazzaro Spallanzani, University of Pavia, Pavia, Italy
| | - Steven A Carr
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Liron Bar-Peled
- Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Philip A Cole
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, USA
| | - Ralph Mazitschek
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Systems Biology, Massachusetts General Hospital, Boston, MA, USA
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Brian B Liau
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Ning Zheng
- Department of Pharmacology, University of Washington, Seattle, WA, USA.
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA.
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4
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Gao S, Weng B, Wich D, Power L, Chen M, Guan H, Ye Z, Xu C, Xu Q. Improving adenine base editing precision by enlarging the recognition domain of CRISPR-Cas9. Nat Commun 2025; 16:2081. [PMID: 40021632 PMCID: PMC11871365 DOI: 10.1038/s41467-025-57154-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2024] [Accepted: 02/11/2025] [Indexed: 03/03/2025] Open
Abstract
Domain expansion contributes to diversification of RNA-guided-endonucleases including Cas9. However, it remains unclear how REC domain expansion could benefit Cas9. In this study, we identify an insertion spot that is compatible with large REC insertion and succeeds in enlarging the non-catalytic REC domain of Streptococcus pyogenes Cas9. The natural-evolution-like giant SpCas9 (GS-Cas9) is created and shows substantially improved editing precision. We further discover that enlarging the REC domain could enable regulation of the N-terminal adenine deaminase TadA8e tethered to the Cas9 scaffold, which contributes to substantially reducing unexpected editing and improving the precision of the adenine base editor ABE8e. We provide proof of concept for evolution-inspired expansion of Cas9 and offer an alternative solution for optimizing gene editors. Our study also indicates a vast potential for engineering the topological malleability of RNA-guided endonucleases and base editors.
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Affiliation(s)
- Shuliang Gao
- Department of Biomedical Engineering, Tufts University, Medford, MA, USA
| | - Benson Weng
- Department of Biomedical Engineering, Tufts University, Medford, MA, USA
| | - Douglas Wich
- Department of Biomedical Engineering, Tufts University, Medford, MA, USA
| | - Liam Power
- Department of Biomedical Engineering, Tufts University, Medford, MA, USA
| | - Mengting Chen
- Department of Biomedical Engineering, Tufts University, Medford, MA, USA
| | - Huiwen Guan
- Department of Biomedical Engineering, Tufts University, Medford, MA, USA
| | - Zhongfeng Ye
- Department of Biomedical Engineering, Tufts University, Medford, MA, USA
| | - Chutian Xu
- Department of Biomedical Engineering, Tufts University, Medford, MA, USA
| | - Qiaobing Xu
- Department of Biomedical Engineering, Tufts University, Medford, MA, USA.
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5
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Acosta J, Johnson GA, Gould SI, Dong K, Lendner Y, Detrés D, Atwa O, Bulkens J, Gruber S, Contreras ME, Wuest AN, Narendra VK, Hemann MT, Sánchez-Rivera FJ. Multiplexed in vivo base editing identifies functional gene-variant-context interactions. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.02.23.639770. [PMID: 40060482 PMCID: PMC11888363 DOI: 10.1101/2025.02.23.639770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 03/16/2025]
Abstract
Human genome sequencing efforts in healthy and diseased individuals continue to identify a broad spectrum of genetic variants associated with predisposition, progression, and therapeutic outcomes for diseases like cancer1-6. Insights derived from these studies have significant potential to guide clinical diagnoses and treatment decisions; however, the relative importance and functional impact of most genetic variants remain poorly understood. Precision genome editing technologies like base and prime editing can be used to systematically engineer and interrogate diverse types of endogenous genetic variants in their native context7-9. We and others have recently developed and applied scalable sensor-based screening approaches to engineer and measure the phenotypes produced by thousands of endogenous mutations in vitro 10-12. However, the impact of most genetic variants in the physiological in vivo setting, including contextual differences depending on the tissue or microenvironment, remains unexplored. Here, we integrate new cross-species base editing sensor libraries with syngeneic cancer mouse models to develop a multiplexed in vivo platform for systematic functional analysis of endogenous genetic variants in primary and disseminated malignancies. We used this platform to screen 13,840 guide RNAs designed to engineer 7,783 human cancer-associated mutations mapping to 489 endogenous protein-coding genes, allowing us to construct a rich compendium of putative functional interactions between genes, mutations, and physiological contexts. Our findings suggest that the physiological in vivo environment and cellular organotropism are important contextual determinants of specific gene-variant phenotypes. We also show that many mutations and their in vivo effects fail to be detected with standard CRISPR-Cas9 nuclease approaches and often produce discordant phenotypes, potentially due to site-specific amino acid selection- or separation-of-function mechanisms. This versatile platform could be deployed to investigate how genetic variation impacts diverse in vivo phenotypes associated with cancer and other genetic diseases, as well as identify new potential therapeutic avenues to treat human disease.
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Affiliation(s)
- Jonuelle Acosta
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Grace A. Johnson
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Samuel I. Gould
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Kexin Dong
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Yovel Lendner
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Diego Detrés
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ondine Atwa
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jari Bulkens
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
- Utrecht University, Utrecht, The Netherlands
| | - Samuel Gruber
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Manuel E. Contreras
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Alexandra N. Wuest
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Varun K. Narendra
- Cancer Biology and Genetics Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Michael T. Hemann
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Francisco J. Sánchez-Rivera
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
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6
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Meeusen B, Ambjørn SM, Veis J, Riley RC, Vit G, Brauer BL, Møller MH, Greiner EC, Chan CB, Weisser MB, Garvanska DH, Zhu H, Davey NE, Kettenbach AN, Ogris E, Nilsson J. A functional map of phosphoprotein phosphatase regulation identifies an evolutionary conserved reductase for the catalytic metal ions. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.02.12.637884. [PMID: 39990307 PMCID: PMC11844454 DOI: 10.1101/2025.02.12.637884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 02/25/2025]
Abstract
Serine/Threonine phosphoprotein phosphatases (PPPs, PP1-PP7) are conserved metalloenzymes and central to intracellular signaling in eukaryotes, but the details of their regulation is poorly understood. To address this, we performed genome-wide CRISPR knockout and focused base editor screens in PPP perturbed conditions to establish a high-resolution functional map of PPP regulation that pinpoints novel regulatory mechanisms. Through this, we identify the orphan reductase CYB5R4 as an evolutionarily conserved activator of PP4 and PP6, but not the closely related PP2A. Heme binding is essential for CYB5R4 function and mechanistically involves the reduction of the metal ions in the active site. Importantly, CYB5R4-mediated activation of PP4 is critical for cell viability when cells are treated with DNA damage-inducing agents known to cause oxidative stress. The discovery of a dedicated PPP reductase points to shared regulatory principles with protein tyrosine phosphatases, where specific enzymes dictate activity by regulating the active site redox state. In sum, our work provides a resource for understanding PPP function and the regulation of intracellular signaling.
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Affiliation(s)
- Bob Meeusen
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, DK
| | - Sara M. Ambjørn
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, DK
| | - Jiri Veis
- Max Perutz Labs, Vienna Biocenter Campus (VBC), Dr.-Bohr-Gasse 9 / Vienna Biocenter 5, 1030, Vienna, Austria. Medical University of Vienna, Max Perutz Labs, Dr.-Bohr-Gasse 9 / Vienna Biocenter 5, 1030, Vienna, Austria
| | - Rachel C. Riley
- Department of Biochemistry and Cell Biology, Dartmouth Geisel School of Medicine, Hanover, NH, USA
| | - Gianmatteo Vit
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, DK
| | - Brooke L. Brauer
- Department of Biochemistry and Cell Biology, Dartmouth Geisel School of Medicine, Hanover, NH, USA
| | - Mads H. Møller
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, DK
| | - Elora C. Greiner
- Department of Biochemistry and Cell Biology, Dartmouth Geisel School of Medicine, Hanover, NH, USA
| | - Camilla B. Chan
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, DK
| | - Melanie B. Weisser
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, DK
| | - Dimitriya H. Garvanska
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, DK
| | - Hao Zhu
- University of Kansas Medical Center, Kansas City, KS, USA
| | | | - Arminja N. Kettenbach
- Department of Biochemistry and Cell Biology, Dartmouth Geisel School of Medicine, Hanover, NH, USA
- Dartmouth Cancer Center, Lebanon, NH, USA
| | - Egon Ogris
- Max Perutz Labs, Vienna Biocenter Campus (VBC), Dr.-Bohr-Gasse 9 / Vienna Biocenter 5, 1030, Vienna, Austria. Medical University of Vienna, Max Perutz Labs, Dr.-Bohr-Gasse 9 / Vienna Biocenter 5, 1030, Vienna, Austria
| | - Jakob Nilsson
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, DK
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7
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Sellés-Baiget S, Ambjørn SM, Carli A, Hendriks IA, Gallina I, Davey NE, Benedict B, Zarantonello A, Gadi SA, Meeusen B, Hertz EPT, Slappendel L, Semlow D, Sturla S, Nielsen ML, Nilsson J, Miller TCR, Duxin JP. Catalytic and noncatalytic functions of DNA polymerase κ in translesion DNA synthesis. Nat Struct Mol Biol 2025; 32:300-314. [PMID: 39300172 PMCID: PMC11832425 DOI: 10.1038/s41594-024-01395-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 08/28/2024] [Indexed: 09/22/2024]
Abstract
Translesion DNA synthesis (TLS) is a cellular process that enables the bypass of DNA lesions encountered during DNA replication and is emerging as a primary target of chemotherapy. Among vertebrate DNA polymerases, polymerase κ (Polκ) has the distinctive ability to bypass minor groove DNA adducts in vitro. However, Polκ is also required for cells to overcome major groove DNA adducts but the basis of this requirement is unclear. Here, we combine CRISPR base-editor screening technology in human cells with TLS analysis of defined DNA lesions in Xenopus egg extracts to unravel the functions and regulations of Polκ during lesion bypass. Strikingly, we show that Polκ has two main functions during TLS, which are differentially regulated by Rev1 binding. On the one hand, Polκ is essential to replicate across a minor groove DNA lesion in a process that depends on PCNA ubiquitylation but is independent of Rev1. On the other hand, through its cooperative interaction with Rev1 and ubiquitylated PCNA, Polκ appears to stabilize the Rev1-Polζ extension complex on DNA to allow extension past major groove DNA lesions and abasic sites, in a process that is independent of Polκ's catalytic activity. Together, our work identifies catalytic and noncatalytic functions of Polκ in TLS and reveals important regulatory mechanisms underlying the unique domain architecture present at the C-terminal end of Y-family TLS polymerases.
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Affiliation(s)
- Selene Sellés-Baiget
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Sara M Ambjørn
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Alberto Carli
- Center for Chromosome Stability, Department of Cellular and Molecular Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ivo A Hendriks
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Irene Gallina
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
- Department of Molecular Medicine, University of Padua, Padua, Italy
| | - Norman E Davey
- Division of Cancer Biology, The Institute of Cancer Research, London, UK
| | - Bente Benedict
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
- Biotech Research and Innovation Centre, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Alessandra Zarantonello
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
- Biotech Research and Innovation Centre, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Sampath A Gadi
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
- Biotech Research and Innovation Centre, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Bob Meeusen
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Emil P T Hertz
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Laura Slappendel
- Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Daniel Semlow
- Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Shana Sturla
- Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Michael L Nielsen
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Jakob Nilsson
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Thomas C R Miller
- Center for Chromosome Stability, Department of Cellular and Molecular Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Julien P Duxin
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark.
- Biotech Research and Innovation Centre, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
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8
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Greenwood E, Cao M, Lee CM, Liu A, Moyo B, Bao G, Gibson G. Haplotype rather than single causal variants effects contribute to regulatory gene expression associations in human myeloid cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.01.30.635675. [PMID: 39975189 PMCID: PMC11838257 DOI: 10.1101/2025.01.30.635675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 02/21/2025]
Abstract
Genome-wide association studies typically identify hundreds to thousands of loci, many of which harbor multiple independent peaks, each parsimoniously assumed to be due to the activity of a single causal variant. Fine-mapping of such variants has become a priority and since most associations are located within regulatory regions, it is also assumed that they colocalize with regulatory variants that influence the expression of nearby genes. Here we examine these assumptions by using a moderate throughput expression CROPseq protocol in which Cas9 nuclease is used to induce small insertions and deletions across the credible set of SNPs that may account for expression quantitative trait loci (eQTL) for genes associated with inflammatory bowel disease (IBD). Of the 4,384 SNPs targeted in 88 loci (an average of 50 per locus), 439 were significant and further examined for validation. From these, 98 significantly altered target gene expression in HL-60 myeloid cell line, 74 in induced macrophages from these HL-60 cells, and 78 in induced neutrophils for a total of 201 validated effects (46%), 43 of which were observed in at least two of the cell types. Considering the observed sensitivity and specificity of the controls, we estimate that there are at least 150 true positives per cell type, an average of almost 2.4 for each of the 64 eQTL for which putative causal variants have been fine-mapped. This implies that haplotype effects are likely to explain many of the associations. We also demonstrate that the same approach can be used to investigate the activity of very rare variants in regulatory regions for 89 genes, providing a rapid strategy for establishing clinical relevance of non-coding mutations.
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Affiliation(s)
- Emily Greenwood
- School of Biological Sciences, Georgia Institute of Technology, Atlanta GA 30332, USA
| | - Mingming Cao
- Department of Bioengineering, Rice University, Houston TX 77005, USA
| | - Ciaran M. Lee
- School of Biochemistry and Cell Biology, University College Cork, Cork, Ireland
| | - Aidi Liu
- Department of Bioengineering, Rice University, Houston TX 77005, USA
| | - Buhle Moyo
- Department of Bioengineering, Rice University, Houston TX 77005, USA
| | - Gang Bao
- Department of Bioengineering, Rice University, Houston TX 77005, USA
| | - Greg Gibson
- School of Biological Sciences, Georgia Institute of Technology, Atlanta GA 30332, USA
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9
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Bao Y, Wei W. Protocol for high-throughput screening of functional lysine residues in cell fitness. STAR Protoc 2024; 5:103418. [PMID: 39471176 PMCID: PMC11550167 DOI: 10.1016/j.xpro.2024.103418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2024] [Revised: 09/09/2024] [Accepted: 10/07/2024] [Indexed: 11/01/2024] Open
Abstract
Amino acid residues are crucial to protein structure and function and have links to various human diseases. Here, we present a protocol for screening functional lysine residues across the human genome. We describe steps for designing lysine codon-targeting single-guide RNAs (sgRNAs), constructing an sgRNA library, conducting cell fitness screenings, and acquiring screening results. This approach leverages base editing and high-throughput screening techniques to systematically examine functional amino acid residues. For complete details on the use and execution of this protocol, please refer to Bao et al.1.
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Affiliation(s)
- Ying Bao
- Changping Laboratory, Beijing 102206, China
| | - Wensheng Wei
- Changping Laboratory, Beijing 102206, China; Biomedical Pioneering Innovation Center, Peking-Tsinghua Center for Life Sciences, Peking University Genome Editing Research Center, State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing 100871, China.
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10
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Wang X, Cheng X, Li Z, Ma S, Zhang H, Chen Z, Yao Y, Li Z, Zhong C, Li Y, Zhang Y, Menon V, Chao L, Li W, Fei T. A comprehensive benchmark for multiple highly efficient base editors with broad targeting scope. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.12.17.628899. [PMID: 39763781 PMCID: PMC11702641 DOI: 10.1101/2024.12.17.628899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/18/2025]
Abstract
As the toolbox of base editors (BEs) expands, selecting appropriate BE and guide RNA (gRNA) to achieve optimal editing efficiency and outcome for a given target becomes challenging. Here, we construct a set of 10 adenine and cytosine BEs with high activity and broad targeting scope, and comprehensively evaluate their editing profiles and properties head-to-head with 34,040 BE-gRNA-target combinations using genomically integrated long targets and tiling gRNA strategies. Interestingly, we observe widespread non-canonical protospacer adjacent motifs (PAMs) for these BEs. Using this large-scale benchmark data, we build a deep learning model, named BEEP (Base Editing Efficiency Predictor), for predicting the editing efficiency and outcome of these BEs. Guided by BEEP, we experimentally test and validate the installment of 3,558 disease-associated single nucleotide variants (SNVs) via BEs, including 20.1% of target sites that would be generally considered as "uneditable", due to the lack of canonical PAMs. We further predict candidate BE-gRNA-target combinations for modeling 1,752,651 ClinVar SNVs. We also identify several cancer-associated SNVs that drive the resistance to BRAF inhibitors in melanoma. These efforts benchmark the performance and illuminate the capabilities of multiple highly useful BEs for interrogating functional SNVs. A practical webserver (http://beep.weililab.org/) is freely accessible to guide the selection of optimal BEs and gRNAs for a given target.
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Affiliation(s)
- Xiaofeng Wang
- Key Laboratory of Bioresource Research and Development of Liaoning Province, College of Life and Health Sciences, Northeastern University, Shenyang, 110819, China
- National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Northeastern University, Shenyang, 110819, China
- Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University), Ministry of Education, Shenyang, 110819, China
- Foshan Graduate School of Innovation, Northeastern University, Foshan 528311, China
| | - Xiaolong Cheng
- Center for Genetic Medicine Research, Children’s National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA
- Department of Genomics and Precision Medicine, George Washington University, 111 Michigan Ave NW, Washington, DC, 20010, USA
| | - Zexu Li
- Key Laboratory of Bioresource Research and Development of Liaoning Province, College of Life and Health Sciences, Northeastern University, Shenyang, 110819, China
- National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Northeastern University, Shenyang, 110819, China
- Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University), Ministry of Education, Shenyang, 110819, China
- Foshan Graduate School of Innovation, Northeastern University, Foshan 528311, China
| | - Shixin Ma
- Key Laboratory of Bioresource Research and Development of Liaoning Province, College of Life and Health Sciences, Northeastern University, Shenyang, 110819, China
- National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Northeastern University, Shenyang, 110819, China
- Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University), Ministry of Education, Shenyang, 110819, China
- Foshan Graduate School of Innovation, Northeastern University, Foshan 528311, China
| | - Han Zhang
- Key Laboratory of Bioresource Research and Development of Liaoning Province, College of Life and Health Sciences, Northeastern University, Shenyang, 110819, China
- National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Northeastern University, Shenyang, 110819, China
- Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University), Ministry of Education, Shenyang, 110819, China
- Foshan Graduate School of Innovation, Northeastern University, Foshan 528311, China
| | - Zhisong Chen
- Key Laboratory of Bioresource Research and Development of Liaoning Province, College of Life and Health Sciences, Northeastern University, Shenyang, 110819, China
- National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Northeastern University, Shenyang, 110819, China
- Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University), Ministry of Education, Shenyang, 110819, China
- Foshan Graduate School of Innovation, Northeastern University, Foshan 528311, China
| | - Yingjia Yao
- Key Laboratory of Bioresource Research and Development of Liaoning Province, College of Life and Health Sciences, Northeastern University, Shenyang, 110819, China
- National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Northeastern University, Shenyang, 110819, China
- Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University), Ministry of Education, Shenyang, 110819, China
- Foshan Graduate School of Innovation, Northeastern University, Foshan 528311, China
| | - Zihan Li
- Key Laboratory of Bioresource Research and Development of Liaoning Province, College of Life and Health Sciences, Northeastern University, Shenyang, 110819, China
- National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Northeastern University, Shenyang, 110819, China
- Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University), Ministry of Education, Shenyang, 110819, China
- Foshan Graduate School of Innovation, Northeastern University, Foshan 528311, China
| | - Chunge Zhong
- Key Laboratory of Bioresource Research and Development of Liaoning Province, College of Life and Health Sciences, Northeastern University, Shenyang, 110819, China
- National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Northeastern University, Shenyang, 110819, China
- Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University), Ministry of Education, Shenyang, 110819, China
- Foshan Graduate School of Innovation, Northeastern University, Foshan 528311, China
| | - You Li
- Key Laboratory of Bioresource Research and Development of Liaoning Province, College of Life and Health Sciences, Northeastern University, Shenyang, 110819, China
- National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Northeastern University, Shenyang, 110819, China
- Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University), Ministry of Education, Shenyang, 110819, China
- Foshan Graduate School of Innovation, Northeastern University, Foshan 528311, China
| | - Yunhan Zhang
- Key Laboratory of Bioresource Research and Development of Liaoning Province, College of Life and Health Sciences, Northeastern University, Shenyang, 110819, China
- National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Northeastern University, Shenyang, 110819, China
- Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University), Ministry of Education, Shenyang, 110819, China
- Foshan Graduate School of Innovation, Northeastern University, Foshan 528311, China
| | - Vipin Menon
- Center for Genetic Medicine Research, Children’s National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA
- Department of Genomics and Precision Medicine, George Washington University, 111 Michigan Ave NW, Washington, DC, 20010, USA
| | - Lumen Chao
- Center for Genetic Medicine Research, Children’s National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA
- Department of Genomics and Precision Medicine, George Washington University, 111 Michigan Ave NW, Washington, DC, 20010, USA
| | - Wei Li
- Center for Genetic Medicine Research, Children’s National Hospital, 111 Michigan Ave NW, Washington, DC, 20010, USA
- Department of Genomics and Precision Medicine, George Washington University, 111 Michigan Ave NW, Washington, DC, 20010, USA
| | - Teng Fei
- Key Laboratory of Bioresource Research and Development of Liaoning Province, College of Life and Health Sciences, Northeastern University, Shenyang, 110819, China
- National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Northeastern University, Shenyang, 110819, China
- Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University), Ministry of Education, Shenyang, 110819, China
- Foshan Graduate School of Innovation, Northeastern University, Foshan 528311, China
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11
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Belli O, Karava K, Farouni R, Platt RJ. Multimodal scanning of genetic variants with base and prime editing. Nat Biotechnol 2024:10.1038/s41587-024-02439-1. [PMID: 39533106 DOI: 10.1038/s41587-024-02439-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 09/18/2024] [Indexed: 11/16/2024]
Abstract
Mutational scanning connects genetic variants to phenotype, enabling the interrogation of protein functions, interactions and variant pathogenicity. However, current methodologies cannot efficiently engineer customizable sets of diverse genetic variants in endogenous loci across cellular contexts in high throughput. Here, we combine cytosine and adenine base editors and a prime editor to assess the pathogenicity of a broad spectrum of variants in the epithelial growth factor receptor gene (EGFR). Using pooled base editing and prime editing guide RNA libraries, we install tens of thousands of variants spanning the full coding sequence of EGFR in multiple cell lines and assess the role of these variants in tumorigenesis and resistance to tyrosine kinase inhibitors. Our EGFR variant scan identifies important hits, supporting the robustness of the approach and revealing underappreciated routes to EGFR activation and drug response. We anticipate that multimodal precision mutational scanning can be applied broadly to characterize genetic variation in any genetic element of interest at high and single-nucleotide resolution.
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Affiliation(s)
- Olivier Belli
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Kyriaki Karava
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Rick Farouni
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Randall J Platt
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
- Basel Research Centre for Child Health, Basel, Switzerland.
- Department of Chemistry, University of Basel, Basel, Switzerland.
- NCCR Molecular Systems Engineering, Basel, Switzerland.
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12
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Coelho MA, Strauss ME, Watterson A, Cooper S, Bhosle S, Illuzzi G, Karakoc E, Dinçer C, Vieira SF, Sharma M, Moullet M, Conticelli D, Koeppel J, McCarten K, Cattaneo CM, Veninga V, Picco G, Parts L, Forment JV, Voest EE, Marioni JC, Bassett A, Garnett MJ. Base editing screens define the genetic landscape of cancer drug resistance mechanisms. Nat Genet 2024; 56:2479-2492. [PMID: 39424923 PMCID: PMC11549056 DOI: 10.1038/s41588-024-01948-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Accepted: 09/13/2024] [Indexed: 10/21/2024]
Abstract
Drug resistance is a principal limitation to the long-term efficacy of cancer therapies. Cancer genome sequencing can retrospectively delineate the genetic basis of drug resistance, but this requires large numbers of post-treatment samples to nominate causal variants. Here we prospectively identify genetic mechanisms of resistance to ten oncology drugs from CRISPR base editing mutagenesis screens in four cancer cell lines using a guide RNA library predicted to install 32,476 variants in 11 cancer genes. We identify four functional classes of protein variants modulating drug sensitivity and use single-cell transcriptomics to reveal how these variants operate through distinct mechanisms, including eliciting a drug-addicted cell state. We identify variants that can be targeted with alternative inhibitors to overcome resistance and functionally validate an epidermal growth factor receptor (EGFR) variant that sensitizes lung cancer cells to EGFR inhibitors. Our variant-to-function map has implications for patient stratification, therapy combinations and drug scheduling in cancer treatment.
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Affiliation(s)
- Matthew A Coelho
- Translational Cancer Genomics, Wellcome Sanger Institute, Hinxton, UK.
- Cancer Genome Editing, Wellcome Sanger Institute, Hinxton, UK.
- Open Targets, Cambridge, UK.
| | - Magdalena E Strauss
- EMBL-European Bioinformatics Institute, Cambridge, UK
- Cancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, UK
- Gene Editing and Cellular Research and Development, Wellcome Sanger Institute, Hinxton, UK
- Department of Mathematics and Statistics, University of Exeter, Exeter, UK
| | - Alex Watterson
- Translational Cancer Genomics, Wellcome Sanger Institute, Hinxton, UK
| | - Sarah Cooper
- Gene Editing and Cellular Research and Development, Wellcome Sanger Institute, Hinxton, UK
| | - Shriram Bhosle
- Translational Cancer Genomics, Wellcome Sanger Institute, Hinxton, UK
| | | | - Emre Karakoc
- Translational Cancer Genomics, Wellcome Sanger Institute, Hinxton, UK
- Open Targets, Cambridge, UK
| | - Cansu Dinçer
- Translational Cancer Genomics, Wellcome Sanger Institute, Hinxton, UK
| | - Sara F Vieira
- Translational Cancer Genomics, Wellcome Sanger Institute, Hinxton, UK
- Open Targets, Cambridge, UK
| | - Mamta Sharma
- Translational Cancer Genomics, Wellcome Sanger Institute, Hinxton, UK
| | - Marie Moullet
- Translational Cancer Genomics, Wellcome Sanger Institute, Hinxton, UK
| | - Daniela Conticelli
- Department of Oncology, University of Turin, Turin, Italy
- Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Italy
| | - Jonas Koeppel
- Generative and Synthetic Genomics, Wellcome Sanger Institute, Hinxton, UK
| | - Katrina McCarten
- Translational Cancer Genomics, Wellcome Sanger Institute, Hinxton, UK
| | - Chiara M Cattaneo
- Department of Immunology and Molecular Oncology, Netherlands Cancer Institute, Amsterdam, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
- Experimental Hematology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Vivien Veninga
- Department of Immunology and Molecular Oncology, Netherlands Cancer Institute, Amsterdam, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
- Department of Pathology, Stanford University, Stanford, CA, USA
| | - Gabriele Picco
- Translational Cancer Genomics, Wellcome Sanger Institute, Hinxton, UK
- Open Targets, Cambridge, UK
| | - Leopold Parts
- Generative and Synthetic Genomics, Wellcome Sanger Institute, Hinxton, UK
| | | | - Emile E Voest
- Department of Immunology and Molecular Oncology, Netherlands Cancer Institute, Amsterdam, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
| | - John C Marioni
- EMBL-European Bioinformatics Institute, Cambridge, UK
- Cancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, UK
- Genentech, South San Francisco, CA, USA
| | - Andrew Bassett
- Gene Editing and Cellular Research and Development, Wellcome Sanger Institute, Hinxton, UK
| | - Mathew J Garnett
- Translational Cancer Genomics, Wellcome Sanger Institute, Hinxton, UK.
- Open Targets, Cambridge, UK.
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13
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Yu T, Fife JD, Bhat V, Adzhubey I, Sherwood R, Cassa CA. FUSE: Improving the estimation and imputation of variant impacts in functional screening. CELL GENOMICS 2024; 4:100667. [PMID: 39389016 PMCID: PMC11602636 DOI: 10.1016/j.xgen.2024.100667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 06/28/2024] [Accepted: 09/05/2024] [Indexed: 10/12/2024]
Abstract
Deep mutational scanning enables high-throughput functional assessment of genetic variants. While phenotypic measurements from screening assays generally align with clinical outcomes, experimental noise may affect the accuracy of individual variant estimates. We developed the FUSE (functional substitution estimation) pipeline, which leverages measurements collectively within screening assays to improve the estimation of variant impacts. Drawing data from 115 published functional assays, FUSE assesses the mean functional effect per amino acid position and makes estimates for individual allelic variants. It enhances the correlation of variant functional effects from different assay platforms and increases the classification accuracy of missense variants in ClinVar across 29 genes (area under the receiver operating characteristic [ROC] curve [AUC] from 0.83 to 0.90). In UK Biobank patients with rare missense variants in BRCA1, LDLR, or TP53, FUSE improves the classification accuracy of associated phenotypes. FUSE can also impute variant effects for substitutions not experimentally screened. This approach improves accuracy and broadens the utility of data from functional screening.
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Affiliation(s)
- Tian Yu
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - James D Fife
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Vineel Bhat
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ivan Adzhubey
- Department of Biomedical Informatics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA
| | - Richard Sherwood
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Christopher A Cassa
- Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
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14
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Sokirniy I, Inam H, Tomaszkiewicz M, Reynolds J, McCandlish D, Pritchard J. A side-by-side comparison of variant function measurements using deep mutational scanning and base editing. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.30.601444. [PMID: 39005366 PMCID: PMC11244880 DOI: 10.1101/2024.06.30.601444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Variant annotation is a crucial objective in mammalian functional genomics. Deep Mutational Scanning (DMS) is a well-established method for annotating human gene variants, but CRISPR base editing (BE) is emerging as an alternative. However, questions remain about how well high-throughput base editing measurements can annotate variant function and the extent of downstream experimental validation required. This study presents the first direct comparison of DMS and BE in the same lab and cell line. Results indicate that focusing on the most likely edits and highest efficiency sgRNAs enhances the agreement between a "gold standard" DMS dataset and a BE screen. A simple filter for sgRNAs making single edits in their window could sufficiently annotate a large proportion of variants directly from sgRNA sequencing of large pools. When multi-edit guides are unavoidable, directly measuring the variants created in the pool, rather than sgRNA abundance, can recover high-quality variant annotation measurements in multiplexed pools. Taken together, our data show a surprising degree of correlation between base editor data and gold standard deep mutational scanning.
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Affiliation(s)
- Ivan Sokirniy
- Huck Institute for the Life Sciences, University Park, PA 16802
| | - Haider Inam
- Huck Institute for the Life Sciences, University Park, PA 16802
- Department of Biomedical Engineering, University Park, PA 16802
| | - Marta Tomaszkiewicz
- Huck Institute for the Life Sciences, University Park, PA 16802
- Department of Biomedical Engineering, University Park, PA 16802
| | - Joshua Reynolds
- Huck Institute for the Life Sciences, University Park, PA 16802
- Department of Biomedical Engineering, University Park, PA 16802
| | - David McCandlish
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724
| | - Justin Pritchard
- Huck Institute for the Life Sciences, University Park, PA 16802
- Department of Biomedical Engineering, University Park, PA 16802
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15
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Singh S, Gleason CE, Fang M, Laimon YN, Khivansara V, Xie S, Durmaz YT, Sarkar A, Ngo K, Savla V, Li Y, Abu-Remaileh M, Li X, Tuladhar B, Odeh R, Hamkins-Indik F, He D, Membreno MW, Nosrati M, Gushwa NN, Leung SSF, Fraga-Walton B, Hernandez L, Baldomero MP, Lent BM, Spellmeyer D, Luna JF, Hoang D, Gritsenko Y, Chand M, DeMart MK, Metobo S, Bhatt C, Shapiro JA, Yang K, Dupper NJ, Bockus AT, Doench JG, Aggen JB, Liu LF, Levin B, Wang EW, Vendrell I, Fischer R, Kessler B, Gokhale PC, Signoretti S, Spektor A, Kreatsoulas C, Singh R, Earp DJ, Garcia PD, Nijhawan D, Oser MG. Cyclin A/B RxL Macrocyclic Inhibitors to Treat Cancers with High E2F Activity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.01.605889. [PMID: 39211113 PMCID: PMC11360997 DOI: 10.1101/2024.08.01.605889] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/04/2024]
Abstract
Cancer cell proliferation requires precise control of E2F1 activity; excess activity promotes apoptosis. Here, we developed cell-permeable and bioavailable macrocycles that selectively kill small cell lung cancer (SCLC) cells with inherent high E2F1 activity by blocking RxL-mediated interactions of cyclin A and cyclin B with select substrates. Genome-wide CRISPR/Cas9 knockout and random mutagenesis screens found that cyclin A/B RxL macrocyclic inhibitors (cyclin A/Bi) induced apoptosis paradoxically by cyclin B- and Cdk2-dependent spindle assembly checkpoint activation (SAC). Mechanistically, cyclin A/Bi hyperactivate E2F1 and cyclin B by blocking their RxL-interactions with cyclin A and Myt1, respectively, ultimately leading to SAC activation and mitotic cell death. Base editor screens identified cyclin B variants that confer cyclin A/Bi resistance including several variants that disrupted cyclin B:Cdk interactions. Unexpectedly but consistent with our base editor and knockout screens, cyclin A/Bi induced the formation of neo-morphic Cdk2-cyclin B complexes that promote SAC activation and apoptosis. Finally, orally-bioavailable cyclin A/Bi robustly inhibited tumor growth in chemotherapy-resistant patient-derived xenograft models of SCLC. This work uncovers gain-of-function mechanisms by which cyclin A/Bi induce apoptosis in cancers with high E2F activity, and suggests cyclin A/Bi as a therapeutic strategy for SCLC and other cancers driven by high E2F activity.
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16
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Dorighi KM, Zhu A, Fortin JP, Hung-Hao Lo J, Sudhamsu J, Wendorff TJ, Durinck S, Callow M, Foster SA, Haley B. Accelerated drug-resistant variant discovery with an enhanced, scalable mutagenic base editor platform. Cell Rep 2024; 43:114313. [PMID: 38838224 DOI: 10.1016/j.celrep.2024.114313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 04/19/2024] [Accepted: 05/17/2024] [Indexed: 06/07/2024] Open
Abstract
Personalized cancer therapeutics bring directed treatment options to patients based on their tumor's genetic signature. Unfortunately, tumor genomes are remarkably adaptable, and acquired resistance through gene mutation frequently occurs. Identifying mutations that promote resistance within drug-treated patient populations can be cost, resource, and time intensive. Accordingly, base editing, enabled by Cas9-deaminase domain fusions, has emerged as a promising approach for rapid, large-scale gene variant screening in situ. Here, we adapt and optimize a conditional activation-induced cytidine deaminase (AID)-dead Cas9 (dCas9) system, which demonstrates greater heterogeneity of edits with an expanded footprint compared to the most commonly utilized cytosine base editor, BE4. In combination with a custom single guide RNA (sgRNA) library, we identify individual and compound variants in epidermal growth factor receptor (EGFR) and v-raf murine sarcoma viral oncogene homolog B1 (BRAF) that confer resistance to established EGFR inhibitors. This system and analytical pipeline provide a simple, highly scalable platform for cis or trans drug-modifying variant discovery and for uncovering valuable insights into protein structure-function relationships.
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Affiliation(s)
- Kristel M Dorighi
- Department of Molecular Biology, Genentech, Inc., South San Francisco, CA 94080, USA.
| | - Anqi Zhu
- Department of OMNI Bioinformatics, Genentech, Inc., South San Francisco, CA 94080, USA
| | - Jean-Philippe Fortin
- Department of Data Science and Statistical Computing, Genentech, Inc., South San Francisco, CA 94080, USA
| | - Jerry Hung-Hao Lo
- Department of Oncology Bioinformatics, Genentech, Inc., South San Francisco, CA 94080, USA
| | - Jawahar Sudhamsu
- Department of Structural Biology, Genentech, Inc., South San Francisco, CA 94080, USA
| | - Timothy J Wendorff
- Department of Structural Biology, Genentech, Inc., South San Francisco, CA 94080, USA
| | - Steffen Durinck
- Department of Oncology Bioinformatics, Genentech, Inc., South San Francisco, CA 94080, USA
| | - Marinella Callow
- Department of Discovery Oncology, Genentech, Inc., South San Francisco, CA 94080, USA
| | - Scott A Foster
- Department of Discovery Oncology, Genentech, Inc., South San Francisco, CA 94080, USA
| | - Benjamin Haley
- Department of Molecular Biology, Genentech, Inc., South San Francisco, CA 94080, USA.
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17
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Ryu J, Barkal S, Yu T, Jankowiak M, Zhou Y, Francoeur M, Phan QV, Li Z, Tognon M, Brown L, Love MI, Bhat V, Lettre G, Ascher DB, Cassa CA, Sherwood RI, Pinello L. Joint genotypic and phenotypic outcome modeling improves base editing variant effect quantification. Nat Genet 2024; 56:925-937. [PMID: 38658794 PMCID: PMC11669423 DOI: 10.1038/s41588-024-01726-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 03/21/2024] [Indexed: 04/26/2024]
Abstract
CRISPR base editing screens enable analysis of disease-associated variants at scale; however, variable efficiency and precision confounds the assessment of variant-induced phenotypes. Here, we provide an integrated experimental and computational pipeline that improves estimation of variant effects in base editing screens. We use a reporter construct to measure guide RNA (gRNA) editing outcomes alongside their phenotypic consequences and introduce base editor screen analysis with activity normalization (BEAN), a Bayesian network that uses per-guide editing outcomes provided by the reporter and target site chromatin accessibility to estimate variant impacts. BEAN outperforms existing tools in variant effect quantification. We use BEAN to pinpoint common regulatory variants that alter low-density lipoprotein (LDL) uptake, implicating previously unreported genes. Additionally, through saturation base editing of LDLR, we accurately quantify missense variant pathogenicity that is consistent with measurements in UK Biobank patients and identify underlying structural mechanisms. This work provides a widely applicable approach to improve the power of base editing screens for disease-associated variant characterization.
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Affiliation(s)
- Jayoung Ryu
- Molecular Pathology Unit, Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Gene Regulation Observatory, The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Sam Barkal
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Tian Yu
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Martin Jankowiak
- Gene Regulation Observatory, The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Yunzhuo Zhou
- School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane, Queensland, Australia
- Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Matthew Francoeur
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Quang Vinh Phan
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Zhijian Li
- Molecular Pathology Unit, Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA
- Gene Regulation Observatory, The Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Manuel Tognon
- Molecular Pathology Unit, Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA
- Gene Regulation Observatory, The Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Computer Science Department, University of Verona, Verona, Italy
| | - Lara Brown
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Michael I Love
- Department of Genetics, Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Vineel Bhat
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Guillaume Lettre
- Montreal Heart Institute, Montréal, Quebec, Canada
- Faculté de Médecine, Université de Montréal, Montréal, Quebec, Canada
| | - David B Ascher
- School of Chemistry and Molecular Biosciences, University of Queensland, Brisbane, Queensland, Australia
- Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Christopher A Cassa
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
| | - Richard I Sherwood
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
| | - Luca Pinello
- Molecular Pathology Unit, Krantz Family Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA.
- Gene Regulation Observatory, The Broad Institute of Harvard and MIT, Cambridge, MA, USA.
- Department of Pathology, Harvard Medical School, Boston, MA, USA.
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18
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Lampson BL, Ramίrez AS, Baro M, He L, Hegde M, Koduri V, Pfaff JL, Hanna RE, Kowal J, Shirole NH, He Y, Doench JG, Contessa JN, Locher KP, Kaelin WG. Positive selection CRISPR screens reveal a druggable pocket in an oligosaccharyltransferase required for inflammatory signaling to NF-κB. Cell 2024; 187:2209-2223.e16. [PMID: 38670073 PMCID: PMC11149550 DOI: 10.1016/j.cell.2024.03.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 09/29/2023] [Accepted: 03/18/2024] [Indexed: 04/28/2024]
Abstract
Nuclear factor κB (NF-κB) plays roles in various diseases. Many inflammatory signals, such as circulating lipopolysaccharides (LPSs), activate NF-κB via specific receptors. Using whole-genome CRISPR-Cas9 screens of LPS-treated cells that express an NF-κB-driven suicide gene, we discovered that the LPS receptor Toll-like receptor 4 (TLR4) is specifically dependent on the oligosaccharyltransferase complex OST-A for N-glycosylation and cell-surface localization. The tool compound NGI-1 inhibits OST complexes in vivo, but the underlying molecular mechanism remained unknown. We did a CRISPR base-editor screen for NGI-1-resistant variants of STT3A, the catalytic subunit of OST-A. These variants, in conjunction with cryoelectron microscopy studies, revealed that NGI-1 binds the catalytic site of STT3A, where it traps a molecule of the donor substrate dolichyl-PP-GlcNAc2-Man9-Glc3, suggesting an uncompetitive inhibition mechanism. Our results provide a rationale for and an initial step toward the development of STT3A-specific inhibitors and illustrate the power of contemporaneous base-editor and structural studies to define drug mechanism of action.
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Affiliation(s)
- Benjamin L Lampson
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA 02215, USA
| | - Ana S Ramίrez
- Institute of Molecular Biology and Biophysics, Eidgenössische Technische Hochschule (ETH), Zürich, Switzerland
| | - Marta Baro
- Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Lixia He
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA 02215, USA
| | - Mudra Hegde
- Genetic Perturbation Platform, Broad Institute, Cambridge, MA 02142, USA
| | - Vidyasagar Koduri
- Division of Hematology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02215, USA
| | - Jamie L Pfaff
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA 02215, USA
| | - Ruth E Hanna
- Genetic Perturbation Platform, Broad Institute, Cambridge, MA 02142, USA
| | - Julia Kowal
- Institute of Molecular Biology and Biophysics, Eidgenössische Technische Hochschule (ETH), Zürich, Switzerland
| | - Nitin H Shirole
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA 02215, USA
| | - Yanfeng He
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA 02215, USA
| | - John G Doench
- Genetic Perturbation Platform, Broad Institute, Cambridge, MA 02142, USA
| | - Joseph N Contessa
- Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Kaspar P Locher
- Institute of Molecular Biology and Biophysics, Eidgenössische Technische Hochschule (ETH), Zürich, Switzerland.
| | - William G Kaelin
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA 02215, USA.
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19
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Johnson GA, Gould SI, Sánchez-Rivera FJ. Deconstructing cancer with precision genome editing. Biochem Soc Trans 2024; 52:803-819. [PMID: 38629716 PMCID: PMC11088927 DOI: 10.1042/bst20230984] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 03/25/2024] [Accepted: 04/03/2024] [Indexed: 04/25/2024]
Abstract
Recent advances in genome editing technologies are allowing investigators to engineer and study cancer-associated mutations in their endogenous genetic contexts with high precision and efficiency. Of these, base editing and prime editing are quickly becoming gold-standards in the field due to their versatility and scalability. Here, we review the merits and limitations of these precision genome editing technologies, their application to modern cancer research, and speculate how these could be integrated to address future directions in the field.
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Affiliation(s)
- Grace A. Johnson
- Department of Biology, Massachusetts Institute of Technology, Cambridge 02142, MA, U.S.A
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge 02142, MA, U.S.A
| | - Samuel I. Gould
- Department of Biology, Massachusetts Institute of Technology, Cambridge 02142, MA, U.S.A
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge 02142, MA, U.S.A
| | - Francisco J. Sánchez-Rivera
- Department of Biology, Massachusetts Institute of Technology, Cambridge 02142, MA, U.S.A
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge 02142, MA, U.S.A
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20
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Roy KR, Smith JD, Li S, Vonesch SC, Nguyen M, Burnett WT, Orsley KM, Lee CS, Haber JE, St Onge RP, Steinmetz LM. Dissecting quantitative trait nucleotides by saturation genome editing. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.02.577784. [PMID: 38352467 PMCID: PMC10862795 DOI: 10.1101/2024.02.02.577784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/24/2024]
Abstract
Genome editing technologies have the potential to transform our understanding of how genetic variation gives rise to complex traits through the systematic engineering and phenotypic characterization of genetic variants. However, there has yet to be a system with sufficient efficiency, fidelity, and throughput to comprehensively identify causal variants at the genome scale. Here we explored the ability of templated CRISPR editing systems to install natural variants genome-wide in budding yeast. We optimized several approaches to enhance homology-directed repair (HDR) with donor DNA templates, including donor recruitment to target sites, single-stranded donor production by bacterial retrons, and in vivo plasmid assembly. We uncovered unique advantages of each system that we integrated into a single superior system named MAGESTIC 3.0. We used MAGESTIC 3.0 to dissect causal variants residing in 112 quantitative trait loci across 32 environmental conditions, revealing an enrichment for missense variants and loci with multiple causal variants. MAGESTIC 3.0 will facilitate the functional analysis of the genome at single-nucleotide resolution and provides a roadmap for improving template-based genome editing systems in other organisms.
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Affiliation(s)
- Kevin R Roy
- Stanford Genome Technology Center, Stanford University, Palo Alto, California, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Justin D Smith
- Stanford Genome Technology Center, Stanford University, Palo Alto, California, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Shengdi Li
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
| | - Sibylle C Vonesch
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
- Laboratory for Genome Editing and Systems Genetics, VIB-KU Leuven Center for Microbiology, Leuven, Belgium
- KU Leuven Center for Microbial and Plant Genetics, Department M2S, Leuven, Belgium
| | - Michelle Nguyen
- Stanford Genome Technology Center, Stanford University, Palo Alto, California, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Wallace T Burnett
- Stanford Genome Technology Center, Stanford University, Palo Alto, California, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Kevin M Orsley
- Stanford Genome Technology Center, Stanford University, Palo Alto, California, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Cheng-Sheng Lee
- Brandeis University, Rosenstiel Basic Medical Sciences Research Center and Department of Biology, Waltham, MA
| | - James E Haber
- Brandeis University, Rosenstiel Basic Medical Sciences Research Center and Department of Biology, Waltham, MA
| | - Robert P St Onge
- Stanford Genome Technology Center, Stanford University, Palo Alto, California, USA
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California, USA
| | - Lars M Steinmetz
- Stanford Genome Technology Center, Stanford University, Palo Alto, California, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
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21
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Chen Y, Luo X, Kang R, Cui K, Ou J, Zhang X, Liang P. Current therapies for osteoarthritis and prospects of CRISPR-based genome, epigenome, and RNA editing in osteoarthritis treatment. J Genet Genomics 2024; 51:159-183. [PMID: 37516348 DOI: 10.1016/j.jgg.2023.07.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 07/13/2023] [Accepted: 07/15/2023] [Indexed: 07/31/2023]
Abstract
Osteoarthritis (OA) is one of the most common degenerative joint diseases worldwide, causing pain, disability, and decreased quality of life. The balance between regeneration and inflammation-induced degradation results in multiple etiologies and complex pathogenesis of OA. Currently, there is a lack of effective therapeutic strategies for OA treatment. With the development of CRISPR-based genome, epigenome, and RNA editing tools, OA treatment has been improved by targeting genetic risk factors, activating chondrogenic elements, and modulating inflammatory regulators. Supported by cell therapy and in vivo delivery vectors, genome, epigenome, and RNA editing tools may provide a promising approach for personalized OA therapy. This review summarizes CRISPR-based genome, epigenome, and RNA editing tools that can be applied to the treatment of OA and provides insights into the development of CRISPR-based therapeutics for OA treatment. Moreover, in-depth evaluations of the efficacy and safety of these tools in human OA treatment are needed.
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Affiliation(s)
- Yuxi Chen
- MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong 510275, China
| | - Xiao Luo
- MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong 510275, China
| | - Rui Kang
- MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong 510275, China
| | - Kaixin Cui
- MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong 510275, China
| | - Jianping Ou
- Center for Reproductive Medicine, The Third Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Guangzhou, Guangdong 510630, China
| | - Xiya Zhang
- Center for Reproductive Medicine, The Third Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Guangzhou, Guangdong 510630, China.
| | - Puping Liang
- MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong 510275, China.
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22
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Dziubańska-Kusibab PJ, Nevedomskaya E, Haendler B. Preclinical Anticipation of On- and Off-Target Resistance Mechanisms to Anti-Cancer Drugs: A Systematic Review. Int J Mol Sci 2024; 25:705. [PMID: 38255778 PMCID: PMC10815614 DOI: 10.3390/ijms25020705] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 12/22/2023] [Accepted: 12/28/2023] [Indexed: 01/24/2024] Open
Abstract
The advent of targeted therapies has led to tremendous improvements in treatment options and their outcomes in the field of oncology. Yet, many cancers outsmart precision drugs by developing on-target or off-target resistance mechanisms. Gaining the ability to resist treatment is the rule rather than the exception in tumors, and it remains a major healthcare challenge to achieve long-lasting remission in most cancer patients. Here, we discuss emerging strategies that take advantage of innovative high-throughput screening technologies to anticipate on- and off-target resistance mechanisms before they occur in treated cancer patients. We divide the methods into non-systematic approaches, such as random mutagenesis or long-term drug treatment, and systematic approaches, relying on the clustered regularly interspaced short palindromic repeats (CRISPR) system, saturated mutagenesis, or computational methods. All these new developments, especially genome-wide CRISPR-based screening platforms, have significantly accelerated the processes for identification of the mechanisms responsible for cancer drug resistance and opened up new avenues for future treatments.
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Affiliation(s)
| | | | - Bernard Haendler
- Research and Early Development Oncology, Pharmaceuticals, Bayer AG, Müllerstr. 178, 13353 Berlin, Germany; (P.J.D.-K.); (E.N.)
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23
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Dampier W, Berman R, Nonnemacher MR, Wigdahl B. Computational analysis of cas proteins unlocks new potential in HIV-1 targeted gene therapy. Front Genome Ed 2024; 5:1248982. [PMID: 38239625 PMCID: PMC10794619 DOI: 10.3389/fgeed.2023.1248982] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 12/11/2023] [Indexed: 01/22/2024] Open
Abstract
Introduction: The human immunodeficiency virus type 1 (HIV-1) pandemic has been slowed with the advent of anti-retroviral therapy (ART). However, ART is not a cure and as such has pushed the disease into a chronic infection. One potential cure strategy that has shown promise is the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas gene editing system. It has recently been shown to successfully edit and/or excise the integrated provirus from infected cells and inhibit HIV-1 in vitro, ex vivo, and in vivo. These studies have primarily been conducted with SpCas9 or SaCas9. However, additional Cas proteins are discovered regularly and modifications to these known proteins are being engineered. The alternative Cas molecules have different requirements for protospacer adjacent motifs (PAMs) which impact the possible targetable regions of HIV-1. Other modifications to the Cas protein or gRNA handle impact the tolerance for mismatches between gRNA and the target. While reducing off-target risk, this impacts the ability to fully account for HIV-1 genetic variability. Methods: This manuscript strives to examine these parameter choices using a computational approach for surveying the suitability of a Cas editor for HIV-1 gene editing. The Nominate, Diversify, Narrow, Filter (NDNF) pipeline measures the safety, broadness, and effectiveness of a pool of potential gRNAs for any PAM. This technique was used to evaluate 46 different potential Cas editors for their HIV therapeutic potential. Results: Our examination revealed that broader PAMs that improve the targeting potential of editors like SaCas9 and LbCas12a have larger pools of useful gRNAs, while broader PAMs reduced the pool of useful SpCas9 gRNAs yet increased the breadth of targetable locations. Investigation of the mismatch tolerance of Cas editors indicates a 2-missmatch tolerance is an ideal balance between on-target sensitivity and off-target specificity. Of all of the Cas editors examined, SpCas-NG and SPRY-Cas9 had the highest number of overall safe, broad, and effective gRNAs against HIV. Discussion: Currently, larger proteins and wider PAMs lead to better targeting capacity. This implies that research should either be targeted towards delivering longer payloads or towards increasing the breadth of currently available small Cas editors. With the discovery and adoption of additional Cas editors, it is important for researchers in the HIV-1 gene editing field to explore the wider world of Cas editors.
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Affiliation(s)
- Will Dampier
- Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA, United States
- Center for Molecular Virology and Gene Therapy, Institute for Molecular Medicine and Infectious Disease, Drexel University College of Medicine, Philadelphia, PA, United States
| | - Rachel Berman
- Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA, United States
- Center for Molecular Virology and Gene Therapy, Institute for Molecular Medicine and Infectious Disease, Drexel University College of Medicine, Philadelphia, PA, United States
| | - Michael R. Nonnemacher
- Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA, United States
- Center for Molecular Virology and Gene Therapy, Institute for Molecular Medicine and Infectious Disease, Drexel University College of Medicine, Philadelphia, PA, United States
- Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, United States
| | - Brian Wigdahl
- Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA, United States
- Center for Molecular Virology and Gene Therapy, Institute for Molecular Medicine and Infectious Disease, Drexel University College of Medicine, Philadelphia, PA, United States
- Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, United States
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24
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Schmidt R, Ward CC, Dajani R, Armour-Garb Z, Ota M, Allain V, Hernandez R, Layeghi M, Xing G, Goudy L, Dorovskyi D, Wang C, Chen YY, Ye CJ, Shy BR, Gilbert LA, Eyquem J, Pritchard JK, Dodgson SE, Marson A. Base-editing mutagenesis maps alleles to tune human T cell functions. Nature 2024; 625:805-812. [PMID: 38093011 PMCID: PMC11065414 DOI: 10.1038/s41586-023-06835-6] [Citation(s) in RCA: 32] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 11/03/2023] [Indexed: 12/18/2023]
Abstract
CRISPR-enabled screening is a powerful tool for the discovery of genes that control T cell function and has nominated candidate targets for immunotherapies1-6. However, new approaches are required to probe specific nucleotide sequences within key genes. Systematic mutagenesis in primary human T cells could reveal alleles that tune specific phenotypes. DNA base editors are powerful tools for introducing targeted mutations with high efficiency7,8. Here we develop a large-scale base-editing mutagenesis platform with the goal of pinpointing nucleotides that encode amino acid residues that tune primary human T cell activation responses. We generated a library of around 117,000 single guide RNA molecules targeting base editors to protein-coding sites across 385 genes implicated in T cell function and systematically identified protein domains and specific amino acid residues that regulate T cell activation and cytokine production. We found a broad spectrum of alleles with variants encoding critical residues in proteins including PIK3CD, VAV1, LCP2, PLCG1 and DGKZ, including both gain-of-function and loss-of-function mutations. We validated the functional effects of many alleles and further demonstrated that base-editing hits could positively and negatively tune T cell cytotoxic function. Finally, higher-resolution screening using a base editor with relaxed protospacer-adjacent motif requirements9 (NG versus NGG) revealed specific structural domains and protein-protein interaction sites that can be targeted to tune T cell functions. Base-editing screens in primary immune cells thus provide biochemical insights with the potential to accelerate immunotherapy design.
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Affiliation(s)
- Ralf Schmidt
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA.
- Department of Laboratory Medicine, Medical University of Vienna, Vienna, Austria.
| | - Carl C Ward
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA.
| | - Rama Dajani
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
| | - Zev Armour-Garb
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
| | - Mineto Ota
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Vincent Allain
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Université Paris Cité, INSERM UMR976, Hôpital Saint-Louis, Paris, France
| | - Rosmely Hernandez
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Madeline Layeghi
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
| | - Galen Xing
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
- Center for Computational Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Laine Goudy
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
| | - Dmytro Dorovskyi
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
- UCSF Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Charlotte Wang
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, CA, USA
| | - Yan Yi Chen
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
| | - Chun Jimmie Ye
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Institute for Human Genetics (IHG), University of California, San Francisco, San Francisco, CA, USA
- Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Brian R Shy
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
- UCSF Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Luke A Gilbert
- UCSF Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
- Department of Urology, University of California, San Francisco, San Francisco, USA
- Arc Institute, Palo Alto, CA, USA
| | - Justin Eyquem
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- UCSF Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
- Institute for Human Genetics (IHG), University of California, San Francisco, San Francisco, CA, USA
- Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA
- Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA, USA
| | - Jonathan K Pritchard
- Department of Genetics, Stanford University, Stanford, CA, USA
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Stacie E Dodgson
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
| | - Alexander Marson
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA.
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.
- UCSF Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA.
- Institute for Human Genetics (IHG), University of California, San Francisco, San Francisco, CA, USA.
- Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA.
- Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA, USA.
- Diabetes Center, University of California, San Francisco, San Francisco, CA, USA.
- Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA.
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25
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Koonin EV, Gootenberg JS, Abudayyeh OO. Discovery of Diverse CRISPR-Cas Systems and Expansion of the Genome Engineering Toolbox. Biochemistry 2023; 62:3465-3487. [PMID: 37192099 PMCID: PMC10734277 DOI: 10.1021/acs.biochem.3c00159] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 04/23/2023] [Indexed: 05/18/2023]
Abstract
CRISPR systems mediate adaptive immunity in bacteria and archaea through diverse effector mechanisms and have been repurposed for versatile applications in therapeutics and diagnostics thanks to their facile reprogramming with RNA guides. RNA-guided CRISPR-Cas targeting and interference are mediated by effectors that are either components of multisubunit complexes in class 1 systems or multidomain single-effector proteins in class 2. The compact class 2 CRISPR systems have been broadly adopted for multiple applications, especially genome editing, leading to a transformation of the molecular biology and biotechnology toolkit. The diversity of class 2 effector enzymes, initially limited to the Cas9 nuclease, was substantially expanded via computational genome and metagenome mining to include numerous variants of Cas12 and Cas13, providing substrates for the development of versatile, orthogonal molecular tools. Characterization of these diverse CRISPR effectors uncovered many new features, including distinct protospacer adjacent motifs (PAMs) that expand the targeting space, improved editing specificity, RNA rather than DNA targeting, smaller crRNAs, staggered and blunt end cuts, miniature enzymes, promiscuous RNA and DNA cleavage, etc. These unique properties enabled multiple applications, such as harnessing the promiscuous RNase activity of the type VI effector, Cas13, for supersensitive nucleic acid detection. class 1 CRISPR systems have been adopted for genome editing, as well, despite the challenge of expressing and delivering the multiprotein class 1 effectors. The rich diversity of CRISPR enzymes led to rapid maturation of the genome editing toolbox, with capabilities such as gene knockout, base editing, prime editing, gene insertion, DNA imaging, epigenetic modulation, transcriptional modulation, and RNA editing. Combined with rational design and engineering of the effector proteins and associated RNAs, the natural diversity of CRISPR and related bacterial RNA-guided systems provides a vast resource for expanding the repertoire of tools for molecular biology and biotechnology.
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Affiliation(s)
- Eugene V. Koonin
- National
Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, United States
| | - Jonathan S. Gootenberg
- McGovern
Institute for Brain Research at MIT, Massachusetts
Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Omar O. Abudayyeh
- McGovern
Institute for Brain Research at MIT, Massachusetts
Institute of Technology, Cambridge, Massachusetts 02139, United States
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26
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Maurer AC, Benyamini B, Fan VB, Whitney ON, Dailey GM, Darzacq X, Weitzman MD, Tjian R. Double-Strand Break Repair Pathways Differentially Affect Processing and Transduction by Dual AAV Vectors. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.19.558438. [PMID: 37790316 PMCID: PMC10542147 DOI: 10.1101/2023.09.19.558438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Recombinant adeno-associated viral vectors (rAAV) are a powerful tool for gene delivery but have a limited DNA carrying capacity. Efforts to expand this genetic payload have focused on engineering the vector components, such as dual trans-splicing vectors which double the delivery size by exploiting the natural concatenation of rAAV genomes in host nuclei. We hypothesized that inefficient dual vector transduction could be improved by modulating host factors which affect concatenation. Since factors mediating concatenation are not well defined, we performed a genome-wide screen to identify host cell regulators. We discovered that Homologous Recombination (HR) is inhibitory to dual vector transduction. We demonstrate that depletion or inhibition of HR factors BRCA1 and Rad51 significantly increase reconstitution of a large split transgene by increasing both concatenation and expression from rAAVs. Our results define new roles for DNA damage repair in rAAV transduction and highlight the potential for pharmacological intervention to increase genetic payload of rAAV vectors.
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Affiliation(s)
- Anna C. Maurer
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA
- CIRM Center of Excellence, University of California, Berkeley, CA
| | - Brian Benyamini
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA
| | - Vinson B. Fan
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA
| | - Oscar N. Whitney
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA
| | - Gina M. Dailey
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA
- Li Ka Shing Center for Biomedical & Health Sciences, University of California, Berkeley, CA, USA
| | - Xavier Darzacq
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA
- Li Ka Shing Center for Biomedical & Health Sciences, University of California, Berkeley, CA, USA
| | - Matthew D. Weitzman
- University of Pennsylvania Perelman School of Medicine and the Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Robert Tjian
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA
- Li Ka Shing Center for Biomedical & Health Sciences, University of California, Berkeley, CA, USA
- Howard Hughes Medical Institute, University of California, Berkeley, CA, USA
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27
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Garcia EM, Lue NZ, Liang JK, Lieberman WK, Hwang DD, Woods J, Liau BB. Base Editor Scanning Reveals Activating Mutations of DNMT3A. ACS Chem Biol 2023; 18:2030-2038. [PMID: 37603861 PMCID: PMC10560492 DOI: 10.1021/acschembio.3c00257] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/23/2023]
Abstract
DNA methyltransferase 3A (DNMT3A) is a de novo cytosine methyltransferase responsible for establishing proper DNA methylation during mammalian development. Loss-of-function (LOF) mutations to DNMT3A, including the hotspot mutation R882H, frequently occur in developmental growth disorders and hematological diseases, including clonal hematopoiesis and acute myeloid leukemia. Accordingly, identifying mechanisms that activate DNMT3A is of both fundamental and therapeutic interest. Here, we applied a base editor mutational scanning strategy with an improved DNA methylation reporter to systematically identify DNMT3A activating mutations in cells. By integrating an optimized cellular recruitment strategy with paired isogenic cell lines with or without the LOF hotspot R882H mutation, we identify and validate three distinct hyperactivating mutations within or interacting with the regulatory ADD domain of DNMT3A, nominating these regions as potential functional target sites for pharmacological intervention. Notably, these mutations are still activating in the context of a heterozygous R882H mutation. Altogether, we showcase the utility of base editor scanning for discovering functional regions of target proteins.
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Affiliation(s)
- Emma M. Garcia
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA 02138
- Broad Institute of Harvard and MIT, Cambridge, MA, USA 02142
| | - Nicholas Z. Lue
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA 02138
- Broad Institute of Harvard and MIT, Cambridge, MA, USA 02142
| | - Jessica K. Liang
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA 02138
| | - Whitney K. Lieberman
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA 02138
| | - Derek D. Hwang
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA 02138
| | - James Woods
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA 02138
- Broad Institute of Harvard and MIT, Cambridge, MA, USA 02142
| | - Brian B. Liau
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA 02138
- Broad Institute of Harvard and MIT, Cambridge, MA, USA 02142
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28
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Ryu J, Barkal S, Yu T, Jankowiak M, Zhou Y, Francoeur M, Phan QV, Li Z, Tognon M, Brown L, Love MI, Lettre G, Ascher DB, Cassa CA, Sherwood RI, Pinello L. Joint genotypic and phenotypic outcome modeling improves base editing variant effect quantification. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.09.08.23295253. [PMID: 37732177 PMCID: PMC10508837 DOI: 10.1101/2023.09.08.23295253] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
CRISPR base editing screens are powerful tools for studying disease-associated variants at scale. However, the efficiency and precision of base editing perturbations vary, confounding the assessment of variant-induced phenotypic effects. Here, we provide an integrated pipeline that improves the estimation of variant impact in base editing screens. We perform high-throughput ABE8e-SpRY base editing screens with an integrated reporter construct to measure the editing efficiency and outcomes of each gRNA alongside their phenotypic consequences. We introduce BEAN, a Bayesian network that accounts for per-guide editing outcomes and target site chromatin accessibility to estimate variant impacts. We show this pipeline attains superior performance compared to existing tools in variant classification and effect size quantification. We use BEAN to pinpoint common variants that alter LDL uptake, implicating novel genes. Additionally, through saturation base editing of LDLR, we enable accurate quantitative prediction of the effects of missense variants on LDL-C levels, which aligns with measurements in UK Biobank individuals, and identify structural mechanisms underlying variant pathogenicity. This work provides a widely applicable approach to improve the power of base editor screens for disease-associated variant characterization.
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Affiliation(s)
- Jayoung Ryu
- Molecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Sam Barkal
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Tian Yu
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Yunzhuo Zhou
- School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Australia
- Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Matthew Francoeur
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Quang Vinh Phan
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Zhijian Li
- Molecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Manuel Tognon
- Molecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Computer Science Department, University of Verona, Verona, Italy
| | - Lara Brown
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Michael I. Love
- Department of Genetics, Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Guillaume Lettre
- Montreal Heart Institute, Montréal, QC H1T 1C8, Canada
- Faculté de Médecine, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - David B. Ascher
- School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Australia
- Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Christopher A. Cassa
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Richard I. Sherwood
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Luca Pinello
- Molecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Pathology, Harvard Medical School, Boston, MA, USA
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29
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Lue NZ, Liau BB. Base editor screens for in situ mutational scanning at scale. Mol Cell 2023; 83:2167-2187. [PMID: 37390819 PMCID: PMC10330937 DOI: 10.1016/j.molcel.2023.06.009] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 05/30/2023] [Accepted: 06/06/2023] [Indexed: 07/02/2023]
Abstract
A fundamental challenge in biology is understanding the molecular details of protein function. How mutations alter protein activity, regulation, and response to drugs is of critical importance to human health. Recent years have seen the emergence of pooled base editor screens for in situ mutational scanning: the interrogation of protein sequence-function relationships by directly perturbing endogenous proteins in live cells. These studies have revealed the effects of disease-associated mutations, discovered novel drug resistance mechanisms, and generated biochemical insights into protein function. Here, we discuss how this "base editor scanning" approach has been applied to diverse biological questions, compare it with alternative techniques, and describe the emerging challenges that must be addressed to maximize its utility. Given its broad applicability toward profiling mutations across the proteome, base editor scanning promises to revolutionize the investigation of proteins in their native contexts.
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Affiliation(s)
- Nicholas Z Lue
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA; Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Brian B Liau
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA; Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
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30
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Awwad SW, Serrano-Benitez A, Thomas JC, Gupta V, Jackson SP. Revolutionizing DNA repair research and cancer therapy with CRISPR-Cas screens. Nat Rev Mol Cell Biol 2023; 24:477-494. [PMID: 36781955 DOI: 10.1038/s41580-022-00571-x] [Citation(s) in RCA: 37] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/08/2022] [Indexed: 02/15/2023]
Abstract
All organisms possess molecular mechanisms that govern DNA repair and associated DNA damage response (DDR) processes. Owing to their relevance to human disease, most notably cancer, these mechanisms have been studied extensively, yet new DNA repair and/or DDR factors and functional interactions between them are still being uncovered. The emergence of CRISPR technologies and CRISPR-based genetic screens has enabled genome-scale analyses of gene-gene and gene-drug interactions, thereby providing new insights into cellular processes in distinct DDR-deficiency genetic backgrounds and conditions. In this Review, we discuss the mechanistic basis of CRISPR-Cas genetic screening approaches and describe how they have contributed to our understanding of DNA repair and DDR pathways. We discuss how DNA repair pathways are regulated, and identify and characterize crosstalk between them. We also highlight the impacts of CRISPR-based studies in identifying novel strategies for cancer therapy, and in understanding, overcoming and even exploiting cancer-drug resistance, for example in the contexts of PARP inhibition, homologous recombination deficiencies and/or replication stress. Lastly, we present the DDR CRISPR screen (DDRcs) portal , in which we have collected and reanalysed data from CRISPR screen studies and provide a tool for systematically exploring them.
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Affiliation(s)
- Samah W Awwad
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
- The Gurdon Institute and Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Almudena Serrano-Benitez
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK.
- The Gurdon Institute and Department of Biochemistry, University of Cambridge, Cambridge, UK.
| | - John C Thomas
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK.
- The Gurdon Institute and Department of Biochemistry, University of Cambridge, Cambridge, UK.
| | - Vipul Gupta
- The Gurdon Institute and Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Stephen P Jackson
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK.
- The Gurdon Institute and Department of Biochemistry, University of Cambridge, Cambridge, UK.
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31
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Pablo JLB, Cornett SL, Wang LA, Jo S, Brünger T, Budnik N, Hegde M, DeKeyser JM, Thompson CH, Doench JG, Lal D, George AL, Pan JQ. Scanning mutagenesis of the voltage-gated sodium channel Na V1.2 using base editing. Cell Rep 2023; 42:112563. [PMID: 37267104 PMCID: PMC10592450 DOI: 10.1016/j.celrep.2023.112563] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 03/24/2023] [Accepted: 05/08/2023] [Indexed: 06/04/2023] Open
Abstract
It is challenging to apply traditional mutational scanning to voltage-gated sodium channels (NaVs) and functionally annotate the large number of coding variants in these genes. Using a cytosine base editor and a pooled viability assay, we screen a library of 368 guide RNAs (gRNAs) tiling NaV1.2 to identify more than 100 gRNAs that change NaV1.2 function. We sequence base edits made by a subset of these gRNAs to confirm specific variants that drive changes in channel function. Electrophysiological characterization of these channel variants validates the screen results and provides functional mechanisms of channel perturbation. Most of the changes caused by these gRNAs are classifiable as loss of function along with two missense mutations that lead to gain of function in NaV1.2 channels. This two-tiered strategy to functionally characterize ion channel protein variants at scale identifies a large set of loss-of-function mutations in NaV1.2.
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Affiliation(s)
- Juan Lorenzo B Pablo
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
| | - Savannah L Cornett
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Lei A Wang
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Sooyeon Jo
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Tobias Brünger
- Cologne Center for Genomics, University of Cologne, 51149 Cologne, Germany; Genomic Medicine Institute, Lerner Research Institute, Neurological Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Nikita Budnik
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Mudra Hegde
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Jean-Marc DeKeyser
- Department of Pharmacology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Christopher H Thompson
- Department of Pharmacology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - John G Doench
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Dennis Lal
- Cologne Center for Genomics, University of Cologne, 51149 Cologne, Germany; Genomic Medicine Institute, Lerner Research Institute, Neurological Institute, Cleveland Clinic, Cleveland, OH 44195, USA; Department of Neurology, McGovern Medical School, UTHealth, Houston, TX 77030, USA
| | - Alfred L George
- Department of Pharmacology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Jen Q Pan
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
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32
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Gundry M, Sankaran VG. Hacking hematopoiesis - emerging tools for examining variant effects. Dis Model Mech 2023; 16:dmm049857. [PMID: 36826849 PMCID: PMC9983777 DOI: 10.1242/dmm.049857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/25/2023] Open
Abstract
Hematopoiesis is a continuous process of blood and immune cell production. It is orchestrated by thousands of gene products that respond to extracellular signals by guiding cell fate decisions to meet the needs of the organism. Although much of our knowledge of this process comes from work in model systems, we have learned a great deal from studies on human genetic variation. Considerable insight has emerged from studies on presumed monogenic blood disorders, which continue to provide key insights into the mechanisms critical for hematopoiesis. Furthermore, the emergence of large-scale biobanks and cohorts has uncovered thousands of genomic loci associated with blood cell traits and diseases. Some of these blood cell trait-associated loci act as modifiers of what were once thought to be monogenic blood diseases. However, most of these loci await functional validation. Here, we discuss the validation bottleneck and emerging methods to more effectively connect variant to function. In particular, we highlight recent innovations in genome editing, which have paved the path forward for high-throughput functional assessment of loci. Finally, we discuss existing barriers to progress, including challenges in manipulating the genomes of primary hematopoietic cells.
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Affiliation(s)
- Michael Gundry
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Vijay G. Sankaran
- Division of Hematology/Oncology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
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33
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Lue NZ, Garcia EM, Ngan KC, Lee C, Doench JG, Liau BB. Base editor scanning charts the DNMT3A activity landscape. Nat Chem Biol 2023; 19:176-186. [PMID: 36266353 PMCID: PMC10518564 DOI: 10.1038/s41589-022-01167-4] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 09/08/2022] [Indexed: 02/04/2023]
Abstract
DNA methylation is critical for regulating gene expression, necessitating its accurate placement by enzymes such as the DNA methyltransferase DNMT3A. Dysregulation of this process is known to cause aberrant development and oncogenesis, yet how DNMT3A is regulated holistically by its three domains remains challenging to study. Here, we integrate base editing with a DNA methylation reporter to perform in situ mutational scanning of DNMT3A in cells. We identify mutations throughout the protein that perturb function, including ones at an interdomain interface that block allosteric activation. Unexpectedly, we also find mutations in the PWWP domain, a histone reader, that modulate enzyme activity despite preserving histone recognition and protein stability. These effects arise from altered PWWP domain DNA affinity, which we show is a noncanonical function required for full activity in cells. Our findings highlight mechanisms of interdomain crosstalk and demonstrate a generalizable strategy to probe sequence-activity relationships of nonessential chromatin regulators.
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Affiliation(s)
- Nicholas Z Lue
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Emma M Garcia
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Kevin C Ngan
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Ceejay Lee
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - John G Doench
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Brian B Liau
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA.
- Broad Institute of Harvard and MIT, Cambridge, MA, USA.
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34
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Yu T, Fife JD, Adzhubey I, Sherwood R, Cassa CA. Joint estimation and imputation of variant functional effects using high throughput assay data. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.01.06.23284280. [PMID: 36711907 PMCID: PMC9882428 DOI: 10.1101/2023.01.06.23284280] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Deep mutational scanning assays enable the functional assessment of variants in high throughput. Phenotypic measurements from these assays are broadly concordant with clinical outcomes but are prone to noise at the individual variant level. We develop a framework to exploit related measurements within and across experimental assays to jointly estimate variant impact. Drawing from a large corpus of deep mutational scanning data, we collectively estimate the mean functional effect per AA residue position within each gene, normalize observed functional effects by substitution type, and make estimates for individual allelic variants with a pipeline called FUSE (Functional Substitution Estimation). FUSE improves the correlation of functional screening datasets covering the same variants, better separates estimated functional impacts for known pathogenic and benign variants (ClinVar BRCA1, p=2.24×10-51), and increases the number of variants for which predictions can be made (2,741 to 10,347) by inferring additional variant effects for substitutions not experimentally screened. For UK Biobank patients who carry a rare variant in TP53, FUSE significantly improves the separation of patients who develop cancer syndromes from those without cancer (p=1.77×10-6). These approaches promise to improve estimates of variant impact and broaden the utility of screening data generated from functional assays.
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Affiliation(s)
- Tian Yu
- Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - James D. Fife
- Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Ivan Adzhubey
- Department of Biomedical Informatics, Blavatnik Institute, Harvard Medical School, Boston, Massachusetts
| | - Richard Sherwood
- Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Christopher A. Cassa
- Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
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35
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Accounting for small variations in the tracrRNA sequence improves sgRNA activity predictions for CRISPR screening. Nat Commun 2022; 13:5255. [PMID: 36068235 PMCID: PMC9448816 DOI: 10.1038/s41467-022-33024-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2022] [Accepted: 08/30/2022] [Indexed: 12/17/2022] Open
Abstract
CRISPR technology is a powerful tool for studying genome function. To aid in picking sgRNAs that have maximal efficacy against a target of interest from many possible options, several groups have developed models that predict sgRNA on-target activity. Although multiple tracrRNA variants are commonly used for screening, no existing models account for this feature when nominating sgRNAs. Here we develop an on-target model, Rule Set 3, that makes optimal predictions for multiple tracrRNA variants. We validate Rule Set 3 on a new dataset of sgRNAs tiling essential and non-essential genes, demonstrating substantial improvement over prior prediction models. By analyzing the differences in sgRNA activity between tracrRNA variants, we show that Pol III transcription termination is a strong determinant of sgRNA activity. We expect these results to improve the performance of CRISPR screening and inform future research on tracrRNA engineering and sgRNA modeling.
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