1
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Noel EA, Sahu SU, Wyman SK, Krishnappa N, Jeans C, Wilson RC. Hairpin Internal Nuclear Localization Signals in CRISPR-Cas9 Enhance Editing in Primary Human Lymphocytes. CRISPR J 2025; 8:105-119. [PMID: 40163415 DOI: 10.1089/crispr.2024.0080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/02/2025] Open
Abstract
The incorporation of nuclear localization signal (NLS) sequences at one or both termini of CRISPR enzymes is a widely adopted strategy to facilitate genome editing. Engineered variants of CRISPR enzymes with diverse NLS sequences have demonstrated superior performance, promoting nuclear localization and efficient DNA editing. However, limiting NLS fusion to the CRISPR protein's termini can negatively impact protein yield via recombinant expression. Here we present a distinct strategy involving the installation of hairpin internal NLS sequences (hiNLS) at rationally selected sites within the backbone of CRISPR-Cas9. We evaluated the performance of these hiNLS Cas9 variants by editing genes in human primary T cells following the delivery of ribonucleoprotein enzymes via either electroporation or co-incubation with amphiphilic peptides. We show that hiNLS Cas9 variants can improve editing efficiency in T cells compared with constructs with terminally fused NLS sequences. Furthermore, many hiNLS Cas9 constructs can be produced with high purity and yield, even when these constructs contain as many as nine NLS. These hiNLS Cas9 constructs represent a key advance in optimizing CRISPR effector design and may contribute to improved editing outcomes in research and therapeutic applications.
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Affiliation(s)
- Eric A Noel
- Innovative Genomics Institute, University of California Berkeley, Berkeley, California, USA
- Department of Molecular and Cell Biology, University of California Berkeley, Berkeley, California, USA
- California Institute for Quantitative Biosciences at University of California Berkeley, Berkeley, California, USA
| | - Srishti U Sahu
- Innovative Genomics Institute, University of California Berkeley, Berkeley, California, USA
- Department of Molecular and Cell Biology, University of California Berkeley, Berkeley, California, USA
- California Institute for Quantitative Biosciences at University of California Berkeley, Berkeley, California, USA
| | - Stacia K Wyman
- Innovative Genomics Institute, University of California Berkeley, Berkeley, California, USA
| | - Netravathi Krishnappa
- Innovative Genomics Institute, University of California Berkeley, Berkeley, California, USA
| | - Chris Jeans
- California Institute for Quantitative Biosciences at University of California Berkeley, Berkeley, California, USA
| | - Ross C Wilson
- Innovative Genomics Institute, University of California Berkeley, Berkeley, California, USA
- Department of Molecular and Cell Biology, University of California Berkeley, Berkeley, California, USA
- California Institute for Quantitative Biosciences at University of California Berkeley, Berkeley, California, USA
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2
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Major RM, Mills CA, Xing L, Krantz JL, Wolter JM, Zylka MJ. Exploring the Cytoplasmic Retention of CRISPR-Cas9 in Eukaryotic Cells: The Role of Nuclear Localization Signals and Ribosomal Interactions. CRISPR J 2025; 8:120-136. [PMID: 40019800 DOI: 10.1089/crispr.2024.0074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/19/2025] Open
Abstract
Cas9 must be localized to the nucleus to access the genome of mammalian cells. For most proteins, adding a single nuclear localization signal (NLS) is sufficient to promote nuclear entry. However, Cas9 nuclear entry appears to be inefficient as multiple NLSs are typically added to Cas9. Here, we found that three different Cas9 variants interact with the ribosome in HEK293T cells, and that this interaction is RNA mediated. Following immunoprecipitation-mass spectrometry of cytoplasmic-localized Cas9-0NLS and nuclear-localized Cas9-4NLS constructs, we identified novel Cas9 interactors in postmitotic neurons, including KEAP1 and additional ribosomal subunits, the latter were enriched in Cas9-0NLS samples. Collectively, our results suggest that Cas9 is sequestered in the cytoplasm of mammalian cells, in part, via interaction with the ribosome. Increasing the number of NLSs on Cas9 and/or increasing the amount of cytoplasmic guide RNA has the potential to outcompete ribosomal RNA binding and promote efficient nuclear localization of CRISPR-Cas9 variants.
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Affiliation(s)
- Rami M Major
- Curriculum in Genetics and Molecular Biology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- UNC Neuroscience Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Christine A Mills
- Proteomics Core Facility, Department of Pharmacology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Pharmacology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Lei Xing
- UNC Neuroscience Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - James L Krantz
- UNC Neuroscience Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Justin M Wolter
- UNC Neuroscience Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Cell Biology and Physiology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Mark J Zylka
- UNC Neuroscience Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- Department of Cell Biology and Physiology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
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3
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Tang K, Zhou L, Tian X, Fang SY, Vandenbulcke E, Du A, Shen J, Cao H, Zhou J, Chen K, Kim HR, Luo Z, Xin S, Lin SH, Park D, Yang L, Zhang Y, Suzuki K, Majety M, Ling X, Lam SZ, Chow RD, Ren P, Tao B, Li K, Codina A, Dai X, Shang X, Bai S, Nottoli T, Levchenko A, Booth CJ, Liu C, Fan R, Dong MB, Zhou X, Chen S. Cas12a-knock-in mice for multiplexed genome editing, disease modelling and immune-cell engineering. Nat Biomed Eng 2025:10.1038/s41551-025-01371-2. [PMID: 40114032 DOI: 10.1038/s41551-025-01371-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2024] [Accepted: 02/13/2025] [Indexed: 03/22/2025]
Abstract
The pleiotropic effects of human disease and the complex nature of gene-interaction networks require knock-in mice allowing for multiplexed gene perturbations. Here we describe a series of knock-in mice with a C57BL/6 background and with the conditional or constitutive expression of LbCas12a or of high-fidelity enhanced AsCas12a, which were inserted at the Rosa26 locus. The constitutive expression of Cas12a in the mice did not lead to discernible pathology and enabled efficient multiplexed genome engineering. We used the mice for the retrovirus-based immune-cell engineering of CD4+ and CD8+ T cells, B cells and bone-marrow-derived dendritic cells, for autochthonous cancer modelling through the delivery of multiple CRISPR RNAs as a single array using adeno-associated viruses, and for the targeted genome editing of liver tissue using lipid nanoparticles. We also describe a system for simultaneous dual-gene activation and knockout (DAKO). The Cas12a-knock-in mice and the viral and non-viral delivery vehicles provide a versatile toolkit for ex vivo and in vivo applications in genome editing, disease modelling and immune-cell engineering, and for the deconvolution of complex gene interactions.
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Affiliation(s)
- Kaiyuan Tang
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
- Combined Program in the Biological and Biomedical Sciences, Yale University, New Haven, CT, USA
- Molecular Cell Biology, Genetics, and Development Program, Yale University, New Haven, CT, USA
| | - Liqun Zhou
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
- Combined Program in the Biological and Biomedical Sciences, Yale University, New Haven, CT, USA
- Immunobiology Program, Yale University, New Haven, CT, USA
| | - Xiaolong Tian
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Shao-Yu Fang
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
| | - Erica Vandenbulcke
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
- Yale College, Yale University, New Haven, CT, USA
| | - Andrew Du
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
- Yale College, Yale University, New Haven, CT, USA
| | - Johanna Shen
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
- Yale College, Yale University, New Haven, CT, USA
| | - Hanbing Cao
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
| | - Jerry Zhou
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
- Yale College, Yale University, New Haven, CT, USA
| | - Krista Chen
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
- Yale College, Yale University, New Haven, CT, USA
| | - Hyunu R Kim
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
| | - Zhicheng Luo
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
- Combined Program in the Biological and Biomedical Sciences, Yale University, New Haven, CT, USA
| | - Shan Xin
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
| | - Shawn H Lin
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
- Combined Program in the Biological and Biomedical Sciences, Yale University, New Haven, CT, USA
- Immunobiology Program, Yale University, New Haven, CT, USA
| | - Daniel Park
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
- Yale College, Yale University, New Haven, CT, USA
| | - Luojia Yang
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
- Combined Program in the Biological and Biomedical Sciences, Yale University, New Haven, CT, USA
- Molecular Cell Biology, Genetics, and Development Program, Yale University, New Haven, CT, USA
| | - Yueqi Zhang
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
| | - Kazushi Suzuki
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
| | - Medha Majety
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
- Yale College, Yale University, New Haven, CT, USA
| | - Xinyu Ling
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
| | - Stanley Z Lam
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
- Yale College, Yale University, New Haven, CT, USA
| | - Ryan D Chow
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
- M.D.-Ph.D. Program, Yale University, West Haven, CT, USA
| | - Ping Ren
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
| | - Bo Tao
- System Biology Institute, Yale University, West Haven, CT, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Keyi Li
- Combined Program in the Biological and Biomedical Sciences, Yale University, New Haven, CT, USA
| | - Adan Codina
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
- Combined Program in the Biological and Biomedical Sciences, Yale University, New Haven, CT, USA
- Molecular Cell Biology, Genetics, and Development Program, Yale University, New Haven, CT, USA
| | - Xiaoyun Dai
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- System Biology Institute, Yale University, West Haven, CT, USA
- Center for Genome Editing, Westlake Laboratory of Life Sciences and Biomedicine, School of Medicine, Westlake University, Hangzhou, China
| | - Xingbo Shang
- System Biology Institute, Yale University, West Haven, CT, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Suxia Bai
- Department of Comparative Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Timothy Nottoli
- Department of Comparative Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Andre Levchenko
- System Biology Institute, Yale University, West Haven, CT, USA
- Immunobiology Program, Yale University, New Haven, CT, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
- Department of Neurosurgery, Yale University School of Medicine, New Haven, CT, USA
| | - Carmen J Booth
- Department of Comparative Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Chen Liu
- Department of Pathology, Yale University School of Medicine, New Haven, CT, USA
| | - Rong Fan
- System Biology Institute, Yale University, West Haven, CT, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
- Department of Pathology, Yale University School of Medicine, New Haven, CT, USA
- Yale Comprehensive Cancer Center, Yale University School of Medicine, New Haven, CT, USA
- Yale Stem Cell Center, Yale University School of Medicine, New Haven, CT, USA
- Yale Center for RNA Science and Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Matthew B Dong
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA.
- System Biology Institute, Yale University, West Haven, CT, USA.
- M.D.-Ph.D. Program, Yale University, West Haven, CT, USA.
- Department of Medicine, Johns Hopkins Hospital, Baltimore, MD, USA.
| | - Xiaoyu Zhou
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA.
- System Biology Institute, Yale University, West Haven, CT, USA.
| | - Sidi Chen
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA.
- System Biology Institute, Yale University, West Haven, CT, USA.
- Combined Program in the Biological and Biomedical Sciences, Yale University, New Haven, CT, USA.
- Molecular Cell Biology, Genetics, and Development Program, Yale University, New Haven, CT, USA.
- Immunobiology Program, Yale University, New Haven, CT, USA.
- Yale College, Yale University, New Haven, CT, USA.
- M.D.-Ph.D. Program, Yale University, West Haven, CT, USA.
- Department of Neurosurgery, Yale University School of Medicine, New Haven, CT, USA.
- Yale Comprehensive Cancer Center, Yale University School of Medicine, New Haven, CT, USA.
- Yale Stem Cell Center, Yale University School of Medicine, New Haven, CT, USA.
- Yale Center for RNA Science and Medicine, Yale University School of Medicine, New Haven, CT, USA.
- Yale Liver Center, Yale University School of Medicine, New Haven, CT, USA.
- Yale Center for Biomedical Data Science, Yale University School of Medicine, New Haven, CT, USA.
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4
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Sahu SU, Castro M, Muldoon JJ, Asija K, Wyman SK, Krishnappa N, de Oñate L, Eyquem J, Nguyen DN, Wilson RC. Peptide-enabled ribonucleoprotein delivery for CRISPR engineering (PERC) in primary human immune cells and hematopoietic stem cells. Nat Protoc 2025:10.1038/s41596-025-01154-8. [PMID: 40032999 DOI: 10.1038/s41596-025-01154-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2024] [Accepted: 10/10/2024] [Indexed: 03/05/2025]
Abstract
Peptide-enabled ribonucleoprotein delivery for CRISPR engineering (PERC) is a new approach for ex vivo genome editing of primary human cells. PERC uses a single amphiphilic peptide reagent to mediate intracellular delivery of the same pre-formed CRISPR ribonucleoprotein enzymes that are broadly used in research and therapeutics, resulting in high-efficiency editing of stimulated immune cells and cultured hematopoietic stem and progenitor cells (HSPCs). PERC facilitates nuclease-mediated gene knockout, precise transgene knock-in and base editing. The protocol involves mixing the CRISPR ribonucleoprotein enzyme with peptide and then incubating with cultured cells. For efficient transgene knock-in, adeno-associated virus (AAV) homology-directed repair template (HDRT) DNA may be included. In contrast to electroporation, PERC is appealing because it needs no dedicated hardware and has less impact on cell phenotype and viability. Because of the gentle nature of PERC, delivery can be performed multiple times without substantial impact to cell health or phenotype. Editing efficiencies can surpass 90% when using either Cas9 or Cas12a in primary T cells or HSPCs. After 3 h dedicated to reagent preparation, the PERC delivery step can be completed in 1 h, with the associated cell culture steps taking 3-7 d total. Because the protocol calls for only three readily available reagents (protein, RNA and peptide) and does not require dedicated hardware for any step, PERC demands no special expertise and is exceptionally straightforward to adopt. The inherent compatibility of PERC with established cell engineering pipelines makes the protocol appealing for rapid deployment in research and clinical settings.
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Affiliation(s)
- Srishti U Sahu
- Innovative Genomics Institute, University of California Berkeley, Berkeley, CA, USA
- Department of Molecular and Cell Biology, University of California Berkeley, Berkeley, CA, USA
- California Institute for Quantitative Biosciences at University of California Berkeley, Berkeley, CA, USA
| | - Madalena Castro
- Innovative Genomics Institute, University of California Berkeley, Berkeley, CA, USA
- Department of Molecular and Cell Biology, University of California Berkeley, Berkeley, CA, USA
- California Institute for Quantitative Biosciences at University of California Berkeley, Berkeley, CA, USA
| | - Joseph J Muldoon
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Kunica Asija
- Innovative Genomics Institute, University of California Berkeley, Berkeley, CA, USA
- Department of Molecular and Cell Biology, University of California Berkeley, Berkeley, CA, USA
- California Institute for Quantitative Biosciences at University of California Berkeley, Berkeley, CA, USA
| | - Stacia K Wyman
- Innovative Genomics Institute, University of California Berkeley, Berkeley, CA, USA
| | | | - Lorena de Oñate
- Innovative Genomics Institute, University of California Berkeley, Berkeley, CA, USA
- Department of Molecular and Cell Biology, University of California Berkeley, Berkeley, 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
- Parker Institute for Cancer Immunotherapy, University of California San Francisco, San Francisco, CA, USA
- Department of Microbiology and Immunology, 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, University of California San Francisco, San Francisco, CA, USA
| | - David N Nguyen
- Innovative Genomics Institute, University of California Berkeley, Berkeley, CA, USA
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Ross C Wilson
- Innovative Genomics Institute, University of California Berkeley, Berkeley, CA, USA.
- Department of Molecular and Cell Biology, University of California Berkeley, Berkeley, CA, USA.
- California Institute for Quantitative Biosciences at University of California Berkeley, Berkeley, CA, USA.
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5
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Karp H, Zoltek M, Wasko K, Vazquez A, Brim J, Ngo W, Schepartz A, Doudna J. Packaged delivery of CRISPR-Cas9 ribonucleoproteins accelerates genome editing. Nucleic Acids Res 2025; 53:gkaf105. [PMID: 40036508 PMCID: PMC11878570 DOI: 10.1093/nar/gkaf105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2024] [Revised: 01/05/2025] [Accepted: 02/06/2025] [Indexed: 03/06/2025] Open
Abstract
Effective genome editing requires a sufficient dose of CRISPR-Cas9 ribonucleoproteins (RNPs) to enter the target cell while minimizing immune responses, off-target editing, and cytotoxicity. Clinical use of Cas9 RNPs currently entails electroporation into cells ex vivo, but no systematic comparison of this method to packaged RNP delivery has been made. Here we compared two delivery strategies, electroporation and enveloped delivery vehicles (EDVs), to investigate the Cas9 dosage requirements for genome editing. Using fluorescence correlation spectroscopy, we determined that >1300 Cas9 RNPs per nucleus are typically required for productive genome editing. EDV-mediated editing was >30-fold more efficient than electroporation, and editing occurs at least 2-fold faster for EDV delivery at comparable total Cas9 RNP doses. We hypothesize that differences in efficacy between these methods result in part from the increased duration of RNP nuclear residence resulting from EDV delivery. Our results directly compare RNP delivery strategies, showing that packaged delivery could dramatically reduce the amount of CRISPR-Cas9 RNPs required for experimental or clinical genome editing.
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Affiliation(s)
- Hannah Karp
- Department of Chemistry, University of California, Berkeley, CA 94720, United States
- Innovative Genomics Institute, University of California, Berkeley, CA 94720, United States
| | - Madeline Zoltek
- Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, United States
| | - Kevin Wasko
- Innovative Genomics Institute, University of California, Berkeley, CA 94720, United States
- Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, United States
| | - Angel Luis Vazquez
- Department of Chemistry, University of California, Berkeley, CA 94720, United States
| | - Jinna Brim
- Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, United States
| | - Wayne Ngo
- Innovative Genomics Institute, University of California, Berkeley, CA 94720, United States
- California Institute for Quantitative Biosciences, University of California, Berkeley, CA 94720, United States
- Gladstone Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA 94158, United States
| | - Alanna Schepartz
- Department of Chemistry, University of California, Berkeley, CA 94720, United States
- Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, United States
- California Institute for Quantitative Biosciences, University of California, Berkeley, CA 94720, United States
- ARC Institute, Palo Alto, CA 94304, United States
- Chan Zuckerberg Biohub, San Francisco, CA 94158, United States
| | - Jennifer A Doudna
- Department of Chemistry, University of California, Berkeley, CA 94720, United States
- Innovative Genomics Institute, University of California, Berkeley, CA 94720, United States
- Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, United States
- California Institute for Quantitative Biosciences, University of California, Berkeley, CA 94720, United States
- Gladstone Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA 94158, United States
- Howard Hughes Medical Institute, University of California, Berkeley, CA 94720, United States
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6
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Jin W, Deng Y, La Marca JE, Lelliott EJ, Diepstraten ST, König C, Tai L, Snetkova V, Dorighi KM, Hoberecht L, Hedditch MG, Whelan L, Healey G, Fayle D, Lau K, Potts MA, Chen MZ, Johnston APR, Liao Y, Shi W, Kueh AJ, Haley B, Fortin JP, Herold MJ. Advancing the genetic engineering toolbox by combining AsCas12a knock-in mice with ultra-compact screening. Nat Commun 2025; 16:974. [PMID: 39885149 PMCID: PMC11782673 DOI: 10.1038/s41467-025-56282-2] [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: 12/12/2024] [Accepted: 01/09/2025] [Indexed: 02/01/2025] Open
Abstract
Cas12a is a next-generation gene editing tool that enables multiplexed gene targeting. Here, we present a mouse model that constitutively expresses enhanced Acidaminococcus sp. Cas12a (enAsCas12a) linked to an mCherry fluorescent reporter. We demonstrate efficient single and multiplexed gene editing in vitro, using primary and transformed cells from enAsCas12a mice. We further demonstrate successful in vivo gene editing, using normal and cancer-prone enAsCas12a stem cells to reconstitute the haematopoietic system of wild-type mice. We also present compact, genome-wide Cas12a knockout libraries, with four crRNAs per gene encoded across one (Scherzo) or two (Menuetto) vectors, and demonstrate the utility of these libraries across methodologies: in vitro enrichment and drop-out screening in lymphoma cells and immortalised fibroblasts, respectively, and in vivo screens to identify lymphoma-driving events. Finally, we demonstrate CRISPR multiplexing via simultaneous gene knockout (via Cas12a) and activation (via dCas9-SAM) using primary T cells and fibroblasts. Our enAsCas12a mouse and accompanying crRNA libraries enhance genome engineering capabilities and complement current CRISPR technologies.
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Affiliation(s)
- Wei Jin
- Olivia Newton-John Cancer Research Institute, Heidelberg, Melbourne, Australia
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Melbourne, Australia
- Department of Medical Biology, University of Melbourne, Parkville, Melbourne, Australia
| | - Yexuan Deng
- Olivia Newton-John Cancer Research Institute, Heidelberg, Melbourne, Australia
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Melbourne, Australia
- Department of Medical Biology, University of Melbourne, Parkville, Melbourne, Australia
- The State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, China
| | - John E La Marca
- Olivia Newton-John Cancer Research Institute, Heidelberg, Melbourne, Australia
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Melbourne, Australia
- Department of Medical Biology, University of Melbourne, Parkville, Melbourne, Australia
| | - Emily J Lelliott
- Olivia Newton-John Cancer Research Institute, Heidelberg, Melbourne, Australia
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Melbourne, Australia
- Department of Medical Biology, University of Melbourne, Parkville, Melbourne, Australia
- School of Cancer Medicine, La Trobe University, Bundoora, Melbourne, Australia
| | - Sarah T Diepstraten
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Melbourne, Australia
- Department of Medical Biology, University of Melbourne, Parkville, Melbourne, Australia
| | - Christina König
- Olivia Newton-John Cancer Research Institute, Heidelberg, Melbourne, Australia
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Melbourne, Australia
- School of Cancer Medicine, La Trobe University, Bundoora, Melbourne, Australia
| | - Lin Tai
- Olivia Newton-John Cancer Research Institute, Heidelberg, Melbourne, Australia
| | - Valentina Snetkova
- Department of Molecular Biology, Genentech, Inc., South San Francisco, California, USA
| | - Kristel M Dorighi
- Department of Molecular Biology, Genentech, Inc., South San Francisco, California, USA
| | - Luke Hoberecht
- Computational Sciences, Genentech, Inc., South San Francisco, California, USA
| | - Millicent G Hedditch
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Melbourne, Australia
| | - Lauren Whelan
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Melbourne, Australia
| | - Geraldine Healey
- Olivia Newton-John Cancer Research Institute, Heidelberg, Melbourne, Australia
| | - Dan Fayle
- Olivia Newton-John Cancer Research Institute, Heidelberg, Melbourne, Australia
| | - Kieran Lau
- Olivia Newton-John Cancer Research Institute, Heidelberg, Melbourne, Australia
- School of Cancer Medicine, La Trobe University, Bundoora, Melbourne, Australia
| | - Margaret A Potts
- Olivia Newton-John Cancer Research Institute, Heidelberg, Melbourne, Australia
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Melbourne, Australia
- Department of Medical Biology, University of Melbourne, Parkville, Melbourne, Australia
- School of Cancer Medicine, La Trobe University, Bundoora, Melbourne, Australia
| | - Moore Z Chen
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Melbourne, Australia
| | - Angus P R Johnston
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Melbourne, Australia
| | - Yang Liao
- Olivia Newton-John Cancer Research Institute, Heidelberg, Melbourne, Australia
- School of Cancer Medicine, La Trobe University, Bundoora, Melbourne, Australia
| | - Wei Shi
- Olivia Newton-John Cancer Research Institute, Heidelberg, Melbourne, Australia
- School of Cancer Medicine, La Trobe University, Bundoora, Melbourne, Australia
| | - Andrew J Kueh
- Olivia Newton-John Cancer Research Institute, Heidelberg, Melbourne, Australia
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Melbourne, Australia
- Department of Medical Biology, University of Melbourne, Parkville, Melbourne, Australia
- School of Cancer Medicine, La Trobe University, Bundoora, Melbourne, Australia
| | - Benjamin Haley
- Department of Molecular Biology, Genentech, Inc., South San Francisco, California, USA
- Université de Montréal, Centre de recherche de l'Hôpital Maisonneuve-Rosemont, Rosemont, Canada
| | | | - Marco J Herold
- Olivia Newton-John Cancer Research Institute, Heidelberg, Melbourne, Australia.
- The Walter and Eliza Hall Institute of Medical Research, Parkville, Melbourne, Australia.
- Department of Medical Biology, University of Melbourne, Parkville, Melbourne, Australia.
- School of Cancer Medicine, La Trobe University, Bundoora, Melbourne, Australia.
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7
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Wang L, Han H. Strategies for improving the genome-editing efficiency of class 2 CRISPR/Cas system. Heliyon 2024; 10:e38588. [PMID: 39397905 PMCID: PMC11471210 DOI: 10.1016/j.heliyon.2024.e38588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2024] [Revised: 09/26/2024] [Accepted: 09/26/2024] [Indexed: 10/15/2024] Open
Abstract
Since its advent, gene-editing technology has been widely used in microorganisms, animals, plants, and other species. This technology shows remarkable application prospects, giving rise to a new biotechnological industry. In particular, third-generation gene editing technology, represented by the CRISPR/Cas9 system, has become the mainstream gene editing technology owing to its advantages of high efficiency, simple operation, and low cost. These systems can be widely used because they have been modified and optimized, leading to notable improvements in the efficiency of gene editing. This review introduces the characteristics of popular CRISPR/Cas systems and optimization methods aimed at improving the editing efficiency of class 2 CRISPR/Cas systems, providing a reference for the development of superior gene editing systems. Additionally, the review discusses the development and optimization of base editors, primer editors, gene activation and repression tools, as well as the advancement and refinement of compact systems such as IscB, TnpB, Fanzor, and Cas12f.
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Affiliation(s)
- Linli Wang
- Frontiers Science Center for Molecular Design Breeding (MOE), China Agricultural University, Beijing, 100193, China
- Beijing Key Laboratory of Animal Genetic Improvement, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
- Key Laboratory of Animal Genetics, Breeding and Reproduction of the Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Hongbing Han
- Frontiers Science Center for Molecular Design Breeding (MOE), China Agricultural University, Beijing, 100193, China
- Beijing Key Laboratory of Animal Genetic Improvement, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
- Key Laboratory of Animal Genetics, Breeding and Reproduction of the Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
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8
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Sahu S, Castro M, Muldoon JJ, Asija K, Wyman SK, Krishnappa N, de Onate L, Eyquem J, Nguyen DN, Wilson RC. Peptide-enabled ribonucleoprotein delivery for CRISPR engineering (PERC) in primary human immune cells and hematopoietic stem cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.14.603391. [PMID: 39071446 PMCID: PMC11275745 DOI: 10.1101/2024.07.14.603391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
Peptide-enabled ribonucleoprotein delivery for CRISPR engineering (PERC) is a new approach for ex vivo genome editing of primary human cells. PERC uses a single amphiphilic peptide reagent to mediate intracellular delivery of the same pre-formed CRISPR ribonucleoprotein enzymes that are broadly used in research and therapeutics, resulting in high-efficiency editing of stimulated immune cells and cultured hematopoietic stem and progenitor cells (HSPCs). PERC facilitates nuclease-mediated gene knockout, precise transgene knock-in, and base editing. PERC involves mixing the CRISPR ribonucleoprotein enzyme with peptide and then incubating the formulation with cultured cells. For efficient transgene knock-in, adeno-associated virus (AAV) bearing homology-directed repair template DNA may be included. In contrast to electroporation, PERC is appealing as it requires no dedicated hardware and has less impact on cell phenotype and viability. Due to the gentle nature of PERC, delivery can be performed multiple times without substantial impact to cell health or phenotype. Here we report methods for improved PERC-mediated editing of T cells as well as novel methods for PERC-mediated editing of HSPCs, including knockout and precise knock-in. Editing efficiencies can surpass 90% using either Cas9 or Cas12a in primary T cells or HSPCs. Because PERC calls for only three readily available reagents - protein, RNA, and peptide - and does not require dedicated hardware for any step, PERC demands no special expertise and is exceptionally straightforward to adopt. The inherent compatibility of PERC with established cell engineering pipelines makes this approach appealing for rapid deployment in research and clinical settings.
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9
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Roth GV, Gengaro IR, Qi LS. Precision epigenetic editing: Technological advances, enduring challenges, and therapeutic applications. Cell Chem Biol 2024; 31:S2451-9456(24)00309-X. [PMID: 39137782 PMCID: PMC11799355 DOI: 10.1016/j.chembiol.2024.07.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Revised: 05/31/2024] [Accepted: 07/15/2024] [Indexed: 08/15/2024]
Abstract
The epigenome is a complex framework through which gene expression is precisely and flexibly modulated to incorporate heritable memory and responses to environmental stimuli. It governs diverse cellular processes, including cell fate, disease, and aging. The need to understand this system and precisely control gene expression outputs for therapeutic purposes has precipitated the development of a diverse set of epigenetic editing tools. Here, we review the existing toolbox for targeted epigenetic editing, technical considerations of the current technologies, and opportunities for future development. We describe applications of therapeutic epigenetic editing and their potential for treating disease, with a discussion of ongoing delivery challenges that impede certain clinical interventions, particularly in the brain. With simultaneous advancements in available engineering tools and appropriate delivery technologies, we predict that epigenetic editing will increasingly cement itself as a powerful approach for safely treating a wide range of disorders in all tissues of the body.
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Affiliation(s)
- Goldie V Roth
- Department of Chemical Engineering, Stanford University, Stanford, CA, USA
| | - Isabella R Gengaro
- Department of Chemical Engineering, Stanford University, Stanford, CA, USA; Sarafan ChEM-H, Stanford University, Stanford, CA, USA
| | - Lei S Qi
- Sarafan ChEM-H, Stanford University, Stanford, CA, USA; Department of Bioengineering, Stanford University, Stanford, CA, USA; Chan Zuckerberg Biohub - San Francisco, San Francisco, CA, USA.
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10
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Szelenyi ER, Navarrete JS, Murry AD, Zhang Y, Girven KS, Kuo L, Cline MM, Bernstein MX, Burdyniuk M, Bowler B, Goodwin NL, Juarez B, Zweifel LS, Golden SA. An arginine-rich nuclear localization signal (ArgiNLS) strategy for streamlined image segmentation of single cells. Proc Natl Acad Sci U S A 2024; 121:e2320250121. [PMID: 39074275 PMCID: PMC11317604 DOI: 10.1073/pnas.2320250121] [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: 11/29/2023] [Accepted: 06/25/2024] [Indexed: 07/31/2024] Open
Abstract
High-throughput volumetric fluorescent microscopy pipelines can spatially integrate whole-brain structure and function at the foundational level of single cells. However, conventional fluorescent protein (FP) modifications used to discriminate single cells possess limited efficacy or are detrimental to cellular health. Here, we introduce a synthetic and nondeleterious nuclear localization signal (NLS) tag strategy, called "Arginine-rich NLS" (ArgiNLS), that optimizes genetic labeling and downstream image segmentation of single cells by restricting FP localization near-exclusively in the nucleus through a poly-arginine mechanism. A single N-terminal ArgiNLS tag provides modular nuclear restriction consistently across spectrally separate FP variants. ArgiNLS performance in vivo displays functional conservation across major cortical cell classes and in response to both local and systemic brain-wide AAV administration. Crucially, the high signal-to-noise ratio afforded by ArgiNLS enhances machine learning-automated segmentation of single cells due to rapid classifier training and enrichment of labeled cell detection within 2D brain sections or 3D volumetric whole-brain image datasets, derived from both staining-amplified and native signal. This genetic strategy provides a simple and flexible basis for precise image segmentation of genetically labeled single cells at scale and paired with behavioral procedures.
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Affiliation(s)
- Eric R. Szelenyi
- Center of Excellence in Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA98195
- Department of Biological Structure, University of Washington, Seattle, WA98195
| | - Jovana S. Navarrete
- Center of Excellence in Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA98195
- Department of Biological Structure, University of Washington, Seattle, WA98195
- Graduate Program in Neuroscience, University of Washington, Seattle, WA98195
| | - Alexandria D. Murry
- Center of Excellence in Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA98195
- Department of Biological Structure, University of Washington, Seattle, WA98195
| | - Yizhe Zhang
- Center of Excellence in Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA98195
- Department of Biological Structure, University of Washington, Seattle, WA98195
| | - Kasey S. Girven
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA 98195
| | - Lauren Kuo
- Center of Excellence in Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA98195
- Undergraduate Program in Biochemistry, University of Washington, Seattle, WA98195
| | - Marcella M. Cline
- Center of Excellence in Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA98195
- Department of Pharmacology, University of Washington, Seattle, WA98195
| | - Mollie X. Bernstein
- Center of Excellence in Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA98195
- Department of Pharmacology, University of Washington, Seattle, WA98195
| | | | - Bryce Bowler
- Department of Biological Structure, University of Washington, Seattle, WA98195
| | - Nastacia L. Goodwin
- Center of Excellence in Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA98195
- Department of Biological Structure, University of Washington, Seattle, WA98195
- Graduate Program in Neuroscience, University of Washington, Seattle, WA98195
| | - Barbara Juarez
- Center of Excellence in Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA98195
- Department of Pharmacology, University of Washington, Seattle, WA98195
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA98195
| | - Larry S. Zweifel
- Center of Excellence in Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA98195
- Department of Pharmacology, University of Washington, Seattle, WA98195
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA98195
| | - Sam A. Golden
- Center of Excellence in Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA98195
- Department of Biological Structure, University of Washington, Seattle, WA98195
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11
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Sharrar A, Arake de Tacca L, Meacham Z, Staples-Ager J, Collingwood T, Rabuka D, Schelle M. Discovery and engineering of AiEvo2, a novel Cas12a nuclease for human gene editing applications. J Biol Chem 2024; 300:105685. [PMID: 38272227 PMCID: PMC10877636 DOI: 10.1016/j.jbc.2024.105685] [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: 11/06/2023] [Revised: 01/12/2024] [Accepted: 01/16/2024] [Indexed: 01/27/2024] Open
Abstract
The precision of gene editing technology is critical to creating safe and effective therapies for treating human disease. While the programmability of CRISPR-Cas systems has allowed for rapid innovation of new gene editing techniques, the off-target activity of these enzymes has hampered clinical development for novel therapeutics. Here, we report the identification and characterization of a novel CRISPR-Cas12a enzyme from Acinetobacter indicus (AiCas12a). We engineer the nuclease (termed AiEvo2) for increased specificity, protospacer adjacent motif recognition, and efficacy on a variety of human clinical targets. AiEvo2 is highly precise and able to efficiently discriminate between normal and disease-causing alleles in Huntington's patient-derived cells by taking advantage of a single nucleotide polymorphism on the disease-associated allele. AiEvo2 efficiently edits several liver-associated target genes including PCSK9 and TTR when delivered to primary hepatocytes as mRNA encapsulated in a lipid nanoparticle. The enzyme also engineers an effective CD19 chimeric antigen receptor-T-cell therapy from primary human T cells using multiplexed simultaneous editing and chimeric antigen receptor insertion. To further ensure precise editing, we engineered an anti-CRISPR protein to selectively inhibit off-target gene editing while retaining therapeutic on-target editing. The engineered AiEvo2 nuclease coupled with a novel engineered anti-CRISPR protein represents a new way to control the fidelity of editing and improve the safety and efficacy of gene editing therapies.
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Affiliation(s)
| | | | | | | | | | - David Rabuka
- Acrigen Biosciences, Inc, Berkeley, California, USA
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12
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Kruglova N, Shepelev M. Increasing Gene Editing Efficiency via CRISPR/Cas9- or Cas12a-Mediated Knock-In in Primary Human T Cells. Biomedicines 2024; 12:119. [PMID: 38255224 PMCID: PMC10813735 DOI: 10.3390/biomedicines12010119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 12/22/2023] [Accepted: 01/03/2024] [Indexed: 01/24/2024] Open
Abstract
T lymphocytes represent a promising target for genome editing. They are primarily modified to recognize and kill tumor cells or to withstand HIV infection. In most studies, T cell genome editing is performed using the CRISPR/Cas technology. Although this technology is easily programmable and widely accessible, its efficiency of T cell genome editing was initially low. Several crucial improvements were made in the components of the CRISPR/Cas technology and their delivery methods, as well as in the culturing conditions of T cells, before a reasonable editing level suitable for clinical applications was achieved. In this review, we summarize and describe the aforementioned parameters that affect human T cell editing efficiency using the CRISPR/Cas technology, with a special focus on gene knock-in.
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Affiliation(s)
- Natalia Kruglova
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Institute of Gene Biology RAS, 119334 Moscow, Russia;
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13
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Szelenyi ER, Navarrete JS, Murry AD, Zhang Y, Girven KS, Kuo L, Cline MM, Bernstein MX, Burdyniuk M, Bowler B, Goodwin NL, Juarez B, Zweifel LS, Golden SA. An arginine-rich nuclear localization signal (ArgiNLS) strategy for streamlined image segmentation of single-cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.22.568319. [PMID: 38045271 PMCID: PMC10690249 DOI: 10.1101/2023.11.22.568319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
High-throughput volumetric fluorescent microscopy pipelines can spatially integrate whole-brain structure and function at the foundational level of single-cells. However, conventional fluorescent protein (FP) modifications used to discriminate single-cells possess limited efficacy or are detrimental to cellular health. Here, we introduce a synthetic and non-deleterious nuclear localization signal (NLS) tag strategy, called 'Arginine-rich NLS' (ArgiNLS), that optimizes genetic labeling and downstream image segmentation of single-cells by restricting FP localization near-exclusively in the nucleus through a poly-arginine mechanism. A single N-terminal ArgiNLS tag provides modular nuclear restriction consistently across spectrally separate FP variants. ArgiNLS performance in vivo displays functional conservation across major cortical cell classes, and in response to both local and systemic brain wide AAV administration. Crucially, the high signal-to-noise ratio afforded by ArgiNLS enhances ML-automated segmentation of single-cells due to rapid classifier training and enrichment of labeled cell detection within 2D brain sections or 3D volumetric whole-brain image datasets, derived from both staining-amplified and native signal. This genetic strategy provides a simple and flexible basis for precise image segmentation of genetically labeled single-cells at scale and paired with behavioral procedures.
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Affiliation(s)
- Eric R. Szelenyi
- University of Washington Center of Excellence in Neurobiology of Addiction, Pain, and Emotion (NAPE), Seattle, WA, USA
- University of Washington, Department of Biological Structure, Seattle, WA, USA
| | - Jovana S. Navarrete
- University of Washington Center of Excellence in Neurobiology of Addiction, Pain, and Emotion (NAPE), Seattle, WA, USA
- University of Washington, Department of Biological Structure, Seattle, WA, USA
- University of Washington, Graduate Program in Neuroscience, Seattle, WA, USA
| | - Alexandria D. Murry
- University of Washington Center of Excellence in Neurobiology of Addiction, Pain, and Emotion (NAPE), Seattle, WA, USA
- University of Washington, Department of Biological Structure, Seattle, WA, USA
| | - Yizhe Zhang
- University of Washington Center of Excellence in Neurobiology of Addiction, Pain, and Emotion (NAPE), Seattle, WA, USA
- University of Washington, Department of Biological Structure, Seattle, WA, USA
| | - Kasey S. Girven
- University of Washington, Department of Anesthesiology and Pain Medicine
| | - Lauren Kuo
- University of Washington Center of Excellence in Neurobiology of Addiction, Pain, and Emotion (NAPE), Seattle, WA, USA
- University of Washington Undergraduate Program in Biochemistry
- Allen Institute for Cell Science, Seattle, WA, USA
| | - Marcella M. Cline
- University of Washington Center of Excellence in Neurobiology of Addiction, Pain, and Emotion (NAPE), Seattle, WA, USA
- University of Washington, Department of Pharmacology, Seattle, WA, USA
- Cajal Neuroscience, Seattle, WA, USA
| | - Mollie X. Bernstein
- University of Washington Center of Excellence in Neurobiology of Addiction, Pain, and Emotion (NAPE), Seattle, WA, USA
- University of Washington, Department of Pharmacology, Seattle, WA, USA
| | | | - Bryce Bowler
- University of Washington, Department of Biological Structure, Seattle, WA, USA
| | - Nastacia L. Goodwin
- University of Washington Center of Excellence in Neurobiology of Addiction, Pain, and Emotion (NAPE), Seattle, WA, USA
- University of Washington, Department of Biological Structure, Seattle, WA, USA
- University of Washington, Graduate Program in Neuroscience, Seattle, WA, USA
| | - Barbara Juarez
- University of Washington Center of Excellence in Neurobiology of Addiction, Pain, and Emotion (NAPE), Seattle, WA, USA
- University of Washington, Department of Psychiatry and Behavioral Sciences, Seattle, WA, USA
- University of Washington, Department of Pharmacology, Seattle, WA, USA
- University of Maryland School of Medicine, Department of Neurobiology, Baltimore, MD, USA
| | - Larry S. Zweifel
- University of Washington Center of Excellence in Neurobiology of Addiction, Pain, and Emotion (NAPE), Seattle, WA, USA
- University of Washington, Department of Psychiatry and Behavioral Sciences, Seattle, WA, USA
- University of Washington, Department of Pharmacology, Seattle, WA, USA
| | - Sam A. Golden
- University of Washington Center of Excellence in Neurobiology of Addiction, Pain, and Emotion (NAPE), Seattle, WA, USA
- University of Washington, Department of Biological Structure, Seattle, WA, USA
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