1
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Carlson CK, Loveless TB, Milisavljevic M, Kelly PI, Mills JH, Tyo KEJ, Liu CC. A Massively Parallel In Vivo Assay of TdT Mutants Yields Variants with Altered Nucleotide Insertion Biases. ACS Synth Biol 2024; 13:3326-3343. [PMID: 39302688 DOI: 10.1021/acssynbio.4c00414] [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] [Indexed: 09/22/2024]
Abstract
Terminal deoxynucleotidyl transferase (TdT) is a unique DNA polymerase capable of template-independent extension of DNA. TdT's de novo DNA synthesis ability has found utility in DNA recording, DNA data storage, oligonucleotide synthesis, and nucleic acid labeling, but TdT's intrinsic nucleotide biases limit its versatility in such applications. Here, we describe a multiplexed assay for profiling and engineering the bias and overall activity of TdT variants with high throughput. In our assay, a library of TdTs is encoded next to a CRISPR-Cas9 target site in HEK293T cells. Upon transfection of Cas9 and sgRNA, the target site is cut, allowing TdT to intercept the double-strand break and add nucleotides. Each resulting insertion is sequenced alongside the identity of the TdT variant that generated it. Using this assay, 25,623 unique TdT variants, constructed by site-saturation mutagenesis at strategic positions, were profiled. This resulted in the isolation of several altered-bias TdTs that expanded the capabilities of our TdT-based DNA recording system, Cell HistorY Recording by Ordered InsertioN (CHYRON), by increasing the information density of recording through an unbiased TdT and achieving dual-channel recording of two distinct inducers (hypoxia and Wnt) through two differently biased TdTs. Select TdT variants were also tested in vitro, revealing concordance between each variant's in vitro bias and the in vivo bias determined from the multiplexed high throughput assay. Overall, our work and the multiplex assay it features should support the continued development of TdT-based DNA recorders, in vitro applications of TdT, and further study of the biology of TdT.
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Affiliation(s)
- Courtney K Carlson
- Department of Biomedical Engineering, University of California, Irvine, California 92697, United States
- Center for Synthetic Biology, University of California, Irvine, California 92697, United States
| | - Theresa B Loveless
- Department of Biomedical Engineering, University of California, Irvine, California 92697, United States
- Center for Synthetic Biology, University of California, Irvine, California 92697, United States
- Department of BioSciences, Rice University, Houston, Texas 77005, United States
| | - Marija Milisavljevic
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois 60208, United States
| | - Patrick I Kelly
- Center for Molecular Design and Biomimetics, The Biodesign Institute, Arizona State University, Tempe, Arizona 82587, United States
- School of Molecular Sciences, Arizona State University, Tempe, Arizona 82587, United States
| | - Jeremy H Mills
- Center for Molecular Design and Biomimetics, The Biodesign Institute, Arizona State University, Tempe, Arizona 82587, United States
- School of Molecular Sciences, Arizona State University, Tempe, Arizona 82587, United States
| | - Keith E J Tyo
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois 60208, United States
| | - Chang C Liu
- Department of Biomedical Engineering, University of California, Irvine, California 92697, United States
- Center for Synthetic Biology, University of California, Irvine, California 92697, United States
- Department of Molecular Biology & Biochemistry, University of California, Irvine, California 92697, United States
- Department of Chemistry, University of California, Irvine, California 92697, United States
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2
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Braunger JM, Velten B. Guide assignment in single-cell CRISPR screens using crispat. BIOINFORMATICS (OXFORD, ENGLAND) 2024; 40:btae535. [PMID: 39240651 PMCID: PMC11399228 DOI: 10.1093/bioinformatics/btae535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Revised: 08/26/2024] [Accepted: 09/05/2024] [Indexed: 09/07/2024]
Abstract
MOTIVATION Pooled single-cell CRISPR screens have emerged as a powerful tool in functional genomics to probe the effect of genetic interventions at scale. A crucial step in the analysis of the resulting data is the assignment of cells to gRNAs corresponding to a specific genetic intervention. However, this step is challenging due to a lack of systematic benchmarks and accessible software to apply and compare different guide assignment strategies. To address this, we here propose crispat (CRISPR guide assignment tool), a Python package to facilitate the choice of a suitable guide assignment strategy for single-cell CRISPR screens. RESULTS We demonstrate the package on four single-cell CRISPR interference screens at low multiplicity of infection from two studies, where crispat identifies strong differences in the number of assigned cells, downregulation of the target genes and number of discoveries across different guide assignment strategies, highlighting the need for a suitable guide assignment strategy to obtain optimal power in single-cell CRISPR screens. AVAILABILITY AND IMPLEMENTATION crispat is implemented in python, the source code, installation instructions and tutorials can be found at https://github.com/velten-group/crispat and it can be installed from PyPI (https://pypi.org/project/crispat/). Code to reproduce all findings in this paper is available at https://github.com/velten-group/crispat_analysis, as well as at https://zenodo.org/records/13373265.
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Affiliation(s)
- Jana M Braunger
- Centre for Organismal Studies, Heidelberg University, Heidelberg, 69120, Germany
| | - Britta Velten
- Centre for Organismal Studies, Heidelberg University, Heidelberg, 69120, Germany
- Interdisciplinary Center for Scientific Computing, Heidelberg University, Heidelberg, 69120, Germany
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3
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Zheng X, Wu B, Liu Y, Simmons SK, Kim K, Clarke GS, Ashiq A, Park J, Li J, Wang Z, Tong L, Wang Q, Rajamani KT, Muñoz-Castañeda R, Mu S, Qi T, Zhang Y, Ngiam ZC, Ohte N, Hanashima C, Wu Z, Xu X, Levin JZ, Jin X. Massively parallel in vivo Perturb-seq reveals cell-type-specific transcriptional networks in cortical development. Cell 2024; 187:3236-3248.e21. [PMID: 38772369 PMCID: PMC11193654 DOI: 10.1016/j.cell.2024.04.050] [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: 09/08/2023] [Revised: 11/30/2023] [Accepted: 04/30/2024] [Indexed: 05/23/2024]
Abstract
Leveraging AAVs' versatile tropism and labeling capacity, we expanded the scale of in vivo CRISPR screening with single-cell transcriptomic phenotyping across embryonic to adult brains and peripheral nervous systems. Through extensive tests of 86 vectors across AAV serotypes combined with a transposon system, we substantially amplified labeling efficacy and accelerated in vivo gene delivery from weeks to days. Our proof-of-principle in utero screen identified the pleiotropic effects of Foxg1, highlighting its tight regulation of distinct networks essential for cell fate specification of Layer 6 corticothalamic neurons. Notably, our platform can label >6% of cerebral cells, surpassing the current state-of-the-art efficacy at <0.1% by lentivirus, to achieve analysis of over 30,000 cells in one experiment and enable massively parallel in vivo Perturb-seq. Compatible with various phenotypic measurements (single-cell or spatial multi-omics), it presents a flexible approach to interrogate gene function across cell types in vivo, translating gene variants to their causal function.
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Affiliation(s)
- Xinhe Zheng
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Boli Wu
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Yuejia Liu
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Sean K Simmons
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Kwanho Kim
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Grace S Clarke
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Abdullah Ashiq
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Joshua Park
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Jiwen Li
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Zhilin Wang
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Liqi Tong
- Center for Neural Circuit Mapping, Department of Anatomy and Neurobiology, University of California, Irvine, Irvine, CA 92617, USA
| | - Qizhao Wang
- Center for Neural Circuit Mapping, Department of Anatomy and Neurobiology, University of California, Irvine, Irvine, CA 92617, USA
| | - Keerthi T Rajamani
- Appel Alzheimer's Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
| | - Rodrigo Muñoz-Castañeda
- Appel Alzheimer's Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
| | - Shang Mu
- Appel Alzheimer's Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
| | - Tianbo Qi
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Yunxiao Zhang
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA
| | - Zi Chao Ngiam
- Center for Advanced Biomedical Sciences, Waseda University, Tokyo 162-8480, Japan
| | - Naoto Ohte
- Center for Advanced Biomedical Sciences, Waseda University, Tokyo 162-8480, Japan
| | - Carina Hanashima
- Center for Advanced Biomedical Sciences, Waseda University, Tokyo 162-8480, Japan
| | - Zhuhao Wu
- Appel Alzheimer's Disease Research Institute, Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
| | - Xiangmin Xu
- Center for Neural Circuit Mapping, Department of Anatomy and Neurobiology, University of California, Irvine, Irvine, CA 92617, USA
| | - Joshua Z Levin
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Xin Jin
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA 92037, USA.
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Carlson CK, Loveless TB, Milisavljevic M, Kelly PI, Mills JH, Tyo KEJ, Liu CC. A massively parallel in vivo assay of TdT mutants yields variants with altered nucleotide insertion biases. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.11.598561. [PMID: 38915690 PMCID: PMC11195295 DOI: 10.1101/2024.06.11.598561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
Terminal deoxynucleotidyl transferase (TdT) is a unique DNA polymerase capable of template-independent extension of DNA with random nucleotides. TdT's de novo DNA synthesis ability has found utility in DNA recording, DNA data storage, oligonucleotide synthesis, and nucleic acid labeling, but TdT's intrinsic nucleotide biases limit its versatility in such applications. Here, we describe a multiplexed assay for profiling and engineering the bias and overall activity of TdT variants in high throughput. In our assay, a library of TdTs is encoded next to a CRISPR-Cas9 target site in HEK293T cells. Upon transfection of Cas9 and sgRNA, the target site is cut, allowing TdT to intercept the double strand break and add nucleotides. Each resulting insertion is sequenced alongside the identity of the TdT variant that generated it. Using this assay, 25,623 unique TdT variants, constructed by site-saturation mutagenesis at strategic positions, were profiled. This resulted in the isolation of several altered-bias TdTs that expanded the capabilities of our TdT-based DNA recording system, Cell History Recording by Ordered Insertion (CHYRON), by increasing the information density of recording through an unbiased TdT and achieving dual-channel recording of two distinct inducers (hypoxia and Wnt) through two differently biased TdTs. Select TdT variants were also tested in vitro , revealing concordance between each variant's in vitro bias and the in vivo bias determined from the multiplexed high throughput assay. Overall, our work, and the multiplex assay it features, should support the continued development of TdT-based DNA recorders, in vitro applications of TdT, and further study of the biology of TdT.
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5
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Nadal-Ribelles M, Solé C, de Nadal E, Posas F. The rise of single-cell transcriptomics in yeast. Yeast 2024; 41:158-170. [PMID: 38403881 DOI: 10.1002/yea.3934] [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: 09/29/2023] [Revised: 01/24/2024] [Accepted: 02/15/2024] [Indexed: 02/27/2024] Open
Abstract
The field of single-cell omics has transformed our understanding of biological processes and is constantly advancing both experimentally and computationally. One of the most significant developments is the ability to measure the transcriptome of individual cells by single-cell RNA-seq (scRNA-seq), which was pioneered in higher eukaryotes. While yeast has served as a powerful model organism in which to test and develop transcriptomic technologies, the implementation of scRNA-seq has been significantly delayed in this organism, mainly because of technical constraints associated with its intrinsic characteristics, namely the presence of a cell wall, a small cell size and little amounts of RNA. In this review, we examine the current technologies for scRNA-seq in yeast and highlight their strengths and weaknesses. Additionally, we explore opportunities for developing novel technologies and the potential outcomes of implementing single-cell transcriptomics and extension to other modalities. Undoubtedly, scRNA-seq will be invaluable for both basic and applied yeast research, providing unique insights into fundamental biological processes.
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Affiliation(s)
- Mariona Nadal-Ribelles
- Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Carme Solé
- Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Eulalia de Nadal
- Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Francesc Posas
- Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain
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Zheng X, Wu B, Liu Y, Simmons SK, Kim K, Clarke GS, Ashiq A, Park J, Wang Z, Tong L, Wang Q, Xu X, Levin JZ, Jin X. Massively parallel in vivo Perturb-seq reveals cell type-specific transcriptional networks in cortical development. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.18.558077. [PMID: 37790302 PMCID: PMC10542124 DOI: 10.1101/2023.09.18.558077] [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
Systematic analysis of gene function across diverse cell types in vivo is hindered by two challenges: obtaining sufficient cells from live tissues and accurately identifying each cell's perturbation in high-throughput single-cell assays. Leveraging AAV's versatile cell type tropism and high labeling capacity, we expanded the resolution and scale of in vivo CRISPR screens: allowing phenotypic analysis at single-cell resolution across a multitude of cell types in the embryonic brain, adult brain, and peripheral nervous system. We undertook extensive tests of 86 AAV serotypes, combined with a transposon system, to substantially amplify labeling and accelerate in vivo gene delivery from weeks to days. Using this platform, we performed an in utero genetic screen as proof-of-principle and identified pleiotropic regulatory networks of Foxg1 in cortical development, including Layer 6 corticothalamic neurons where it tightly controls distinct networks essential for cell fate specification. Notably, our platform can label >6% of cerebral cells, surpassing the current state-of-the-art efficacy at <0.1% (mediated by lentivirus), and achieve analysis of over 30,000 cells in one experiment, thus enabling massively parallel in vivo Perturb-seq. Compatible with various perturbation techniques (CRISPRa/i) and phenotypic measurements (single-cell or spatial multi-omics), our platform presents a flexible, modular approach to interrogate gene function across diverse cell types in vivo, connecting gene variants to their causal functions.
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Affiliation(s)
- Xinhe Zheng
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA, USA
| | - Boli Wu
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA, USA
| | - Yuejia Liu
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA, USA
| | - Sean K. Simmons
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Kwanho Kim
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Grace S. Clarke
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA, USA
| | - Abdullah Ashiq
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA, USA
| | - Joshua Park
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA, USA
| | - Zhilin Wang
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA, USA
| | - Liqi Tong
- Center for Neural Circuit Mapping, Department of Anatomy and Neurobiology, University of California, Irvine, CA, USA
| | - Qizhao Wang
- Center for Neural Circuit Mapping, Department of Anatomy and Neurobiology, University of California, Irvine, CA, USA
| | - Xiangmin Xu
- Center for Neural Circuit Mapping, Department of Anatomy and Neurobiology, University of California, Irvine, CA, USA
| | - Joshua Z. Levin
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Xin Jin
- Department of Neuroscience, Dorris Neuroscience Center, Scripps Research, La Jolla, CA, USA
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