Pub Date : 2024-06-21DOI: 10.1038/s41596-024-01001-2
Gustavo Monasterio, Rodrigo A. Morales, David A. Bejarano, Xesús M. Abalo, Jennifer Fransson, Ludvig Larsson, Andreas Schlitzer, Joakim Lundeberg, Srustidhar Das, Eduardo J. Villablanca
Tissues are dynamic and complex biological systems composed of specialized cell types that interact with each other for proper biological function. To comprehensively characterize and understand the cell circuitry underlying biological processes within tissues, it is crucial to preserve their spatial information. Here we report a simple mounting technique to maximize the area of the tissue to be analyzed, encompassing the whole length of the murine gastrointestinal (GI) tract, from mouth to rectum. Using this method, analysis of the whole murine GI tract can be performed in a single slide not only by means of histological staining, immunohistochemistry and in situ hybridization but also by multiplexed antibody staining and spatial transcriptomic approaches. We demonstrate the utility of our method in generating a comprehensive gene and protein expression profile of the whole GI tract by combining the versatile tissue-rolling technique with a cutting-edge transcriptomics method (Visium) and two cutting-edge proteomics methods (ChipCytometry and CODEX-PhenoCycler) in a systematic and easy-to-follow step-by-step procedure. The entire process, including tissue rolling, processing and sectioning, can be achieved within 2–3 d for all three methods. For Visium spatial transcriptomics, an additional 2 d are needed, whereas for spatial proteomics assays (ChipCytometry and CODEX-PhenoCycler), another 3–4 d might be considered. The whole process can be accomplished by researchers with skills in performing murine surgery, and standard histological and molecular biology methods. This protocol presents a versatile tissue-rolling technique for spatially profiling the transcriptome and proteome of the whole murine gastrointestinal tract with high spatial resolution.
{"title":"A versatile tissue-rolling technique for spatial-omics analyses of the entire murine gastrointestinal tract","authors":"Gustavo Monasterio, Rodrigo A. Morales, David A. Bejarano, Xesús M. Abalo, Jennifer Fransson, Ludvig Larsson, Andreas Schlitzer, Joakim Lundeberg, Srustidhar Das, Eduardo J. Villablanca","doi":"10.1038/s41596-024-01001-2","DOIUrl":"10.1038/s41596-024-01001-2","url":null,"abstract":"Tissues are dynamic and complex biological systems composed of specialized cell types that interact with each other for proper biological function. To comprehensively characterize and understand the cell circuitry underlying biological processes within tissues, it is crucial to preserve their spatial information. Here we report a simple mounting technique to maximize the area of the tissue to be analyzed, encompassing the whole length of the murine gastrointestinal (GI) tract, from mouth to rectum. Using this method, analysis of the whole murine GI tract can be performed in a single slide not only by means of histological staining, immunohistochemistry and in situ hybridization but also by multiplexed antibody staining and spatial transcriptomic approaches. We demonstrate the utility of our method in generating a comprehensive gene and protein expression profile of the whole GI tract by combining the versatile tissue-rolling technique with a cutting-edge transcriptomics method (Visium) and two cutting-edge proteomics methods (ChipCytometry and CODEX-PhenoCycler) in a systematic and easy-to-follow step-by-step procedure. The entire process, including tissue rolling, processing and sectioning, can be achieved within 2–3 d for all three methods. For Visium spatial transcriptomics, an additional 2 d are needed, whereas for spatial proteomics assays (ChipCytometry and CODEX-PhenoCycler), another 3–4 d might be considered. The whole process can be accomplished by researchers with skills in performing murine surgery, and standard histological and molecular biology methods. This protocol presents a versatile tissue-rolling technique for spatially profiling the transcriptome and proteome of the whole murine gastrointestinal tract with high spatial resolution.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":"19 10","pages":"3085-3137"},"PeriodicalIF":13.1,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141437254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-18DOI: 10.1038/s41596-024-01004-z
Pedro Weickert, Sophie Dürauer, Maximilian J. Götz, Hao-Yi Li, Julian Stingele
Covalent DNA–protein cross-links (DPCs) are pervasive DNA lesions that challenge genome stability and can be induced by metabolic or chemotherapeutic cross-linking agents including reactive aldehydes, topoisomerase poisons and DNMT1 inhibitors. The purification of x-linked proteins (PxP), where DNA–cross-linked proteins are separated from soluble proteins via electro-elution, can be used to identify DPCs. Here we describe a versatile and sensitive strategy for PxP. Mammalian cells are collected following exposure to a DPC-inducing agent, embedded in low-melt agarose plugs and lysed under denaturing conditions. Following lysis, the soluble proteins are extracted from the agarose plug by electro-elution, while genomic DNA and cross-linked proteins are retained in the plug. The cross-linked proteins can then be analyzed by standard analytical techniques such as sodium dodecyl-sulfate–polyacrylamide gel electrophoresis followed by western blotting or fluorescent staining. Alternatively, quantitative mass spectrometry-based proteomics can be used for the unbiased identification of DPCs. The isolation and analysis of DPCs by PxP overcomes the limitations of alternative methods to analyze DPCs that rely on precipitation as the separating principle and can be performed by users trained in molecular or cell biology within 2–3 d. The protocol has been optimized to study DPC induction and repair in mammalian cells but may also be adapted to other sample types including bacteria, yeast and tissue samples. An assay based on the electrophoresis of whole-cell lysates embedded in agarose plugs separates soluble from immobilized proteins, enabling the purification and the subsequent identification of DNA–protein cross-links.
共价 DNA 蛋白交联（DPCs）是一种普遍存在的 DNA 病变，对基因组的稳定性构成挑战，可由代谢或化疗交联剂诱发，包括活性醛类、拓扑异构酶毒物和 DNMT1 抑制剂。通过电洗脱将 DNA 交联蛋白从可溶性蛋白中分离出来的 x 链接蛋白（PxP）纯化法可用于鉴定 DPC。在此，我们介绍一种多功能、灵敏的 PxP 方法。在暴露于 DPC 诱导剂后收集哺乳动物细胞，将其嵌入低熔点琼脂糖塞中，并在变性条件下进行裂解。裂解后，用电洗脱法从琼脂糖塞中提取可溶性蛋白质，而基因组 DNA 和交联蛋白质则保留在琼脂糖塞中。交联蛋白质可通过标准分析技术进行分析，如十二烷基硫酸钠-聚丙烯酰胺凝胶电泳，然后进行 Western 印迹或荧光染色。另外，还可以使用基于质谱的定量蛋白质组学方法对 DPC 进行无偏见的鉴定。通过 PxP 分离和分析 DPCs 克服了其他分析 DPCs 方法的局限性，这些方法依赖沉淀作为分离原理，受过分子或细胞生物学培训的用户可在 2-3 天内完成。
{"title":"Electro-elution-based purification of covalent DNA–protein cross-links","authors":"Pedro Weickert, Sophie Dürauer, Maximilian J. Götz, Hao-Yi Li, Julian Stingele","doi":"10.1038/s41596-024-01004-z","DOIUrl":"10.1038/s41596-024-01004-z","url":null,"abstract":"Covalent DNA–protein cross-links (DPCs) are pervasive DNA lesions that challenge genome stability and can be induced by metabolic or chemotherapeutic cross-linking agents including reactive aldehydes, topoisomerase poisons and DNMT1 inhibitors. The purification of x-linked proteins (PxP), where DNA–cross-linked proteins are separated from soluble proteins via electro-elution, can be used to identify DPCs. Here we describe a versatile and sensitive strategy for PxP. Mammalian cells are collected following exposure to a DPC-inducing agent, embedded in low-melt agarose plugs and lysed under denaturing conditions. Following lysis, the soluble proteins are extracted from the agarose plug by electro-elution, while genomic DNA and cross-linked proteins are retained in the plug. The cross-linked proteins can then be analyzed by standard analytical techniques such as sodium dodecyl-sulfate–polyacrylamide gel electrophoresis followed by western blotting or fluorescent staining. Alternatively, quantitative mass spectrometry-based proteomics can be used for the unbiased identification of DPCs. The isolation and analysis of DPCs by PxP overcomes the limitations of alternative methods to analyze DPCs that rely on precipitation as the separating principle and can be performed by users trained in molecular or cell biology within 2–3 d. The protocol has been optimized to study DPC induction and repair in mammalian cells but may also be adapted to other sample types including bacteria, yeast and tissue samples. An assay based on the electrophoresis of whole-cell lysates embedded in agarose plugs separates soluble from immobilized proteins, enabling the purification and the subsequent identification of DNA–protein cross-links.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":"19 10","pages":"2891-2914"},"PeriodicalIF":13.1,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141419846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-17DOI: 10.1038/s41596-024-01007-w
Karl D. Gaisser, Sophie N. Skloss, Leandra M. Brettner, Luana Paleologu, Charles M. Roco, Alexander B. Rosenberg, Matthew Hirano, R. William DePaolo, Georg Seelig, Anna Kuchina
Microbial split-pool ligation transcriptomics (microSPLiT) is a high-throughput single-cell RNA sequencing method for bacteria. With four combinatorial barcoding rounds, microSPLiT can profile transcriptional states in hundreds of thousands of Gram-negative and Gram-positive bacteria in a single experiment without specialized equipment. As bacterial samples are fixed and permeabilized before barcoding, they can be collected and stored ahead of time. During the first barcoding round, the fixed and permeabilized bacteria are distributed into a 96-well plate, where their transcripts are reverse transcribed into cDNA and labeled with the first well-specific barcode inside the cells. The cells are mixed and redistributed two more times into new 96-well plates, where the second and third barcodes are appended to the cDNA via in-cell ligation reactions. Finally, the cells are mixed and divided into aliquot sub-libraries, which can be stored until future use or prepared for sequencing with the addition of a fourth barcode. It takes 4 days to generate sequencing-ready libraries, including 1 day for collection and overnight fixation of samples. The standard plate setup enables single-cell transcriptional profiling of up to 1 million bacterial cells and up to 96 samples in a single barcoding experiment, with the possibility of expansion by adding barcoding rounds. The protocol requires experience in basic molecular biology techniques, handling of bacterial samples and preparation of DNA libraries for next-generation sequencing. It can be performed by experienced undergraduate or graduate students. Data analysis requires access to computing resources, familiarity with Unix command line and basic experience with Python or R. Single-cell transcriptomics of bacteria is challenging. microSPLiT is a high-throughput method for single-cell RNA sequencing of both Gram-positive and Gram-negative bacteria using combinatorial barcoding without the need for specialized equipment.
{"title":"High-throughput single-cell transcriptomics of bacteria using combinatorial barcoding","authors":"Karl D. Gaisser, Sophie N. Skloss, Leandra M. Brettner, Luana Paleologu, Charles M. Roco, Alexander B. Rosenberg, Matthew Hirano, R. William DePaolo, Georg Seelig, Anna Kuchina","doi":"10.1038/s41596-024-01007-w","DOIUrl":"10.1038/s41596-024-01007-w","url":null,"abstract":"Microbial split-pool ligation transcriptomics (microSPLiT) is a high-throughput single-cell RNA sequencing method for bacteria. With four combinatorial barcoding rounds, microSPLiT can profile transcriptional states in hundreds of thousands of Gram-negative and Gram-positive bacteria in a single experiment without specialized equipment. As bacterial samples are fixed and permeabilized before barcoding, they can be collected and stored ahead of time. During the first barcoding round, the fixed and permeabilized bacteria are distributed into a 96-well plate, where their transcripts are reverse transcribed into cDNA and labeled with the first well-specific barcode inside the cells. The cells are mixed and redistributed two more times into new 96-well plates, where the second and third barcodes are appended to the cDNA via in-cell ligation reactions. Finally, the cells are mixed and divided into aliquot sub-libraries, which can be stored until future use or prepared for sequencing with the addition of a fourth barcode. It takes 4 days to generate sequencing-ready libraries, including 1 day for collection and overnight fixation of samples. The standard plate setup enables single-cell transcriptional profiling of up to 1 million bacterial cells and up to 96 samples in a single barcoding experiment, with the possibility of expansion by adding barcoding rounds. The protocol requires experience in basic molecular biology techniques, handling of bacterial samples and preparation of DNA libraries for next-generation sequencing. It can be performed by experienced undergraduate or graduate students. Data analysis requires access to computing resources, familiarity with Unix command line and basic experience with Python or R. Single-cell transcriptomics of bacteria is challenging. microSPLiT is a high-throughput method for single-cell RNA sequencing of both Gram-positive and Gram-negative bacteria using combinatorial barcoding without the need for specialized equipment.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":"19 10","pages":"3048-3084"},"PeriodicalIF":13.1,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141419847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-17DOI: 10.1038/s41596-024-01011-0
Rodrigo V. Honorato, Mikael E. Trellet, Brian Jiménez-García, Jörg J. Schaarschmidt, Marco Giulini, Victor Reys, Panagiotis I. Koukos, João P. G. L. M. Rodrigues, Ezgi Karaca, Gydo C. P. van Zundert, Jorge Roel-Touris, Charlotte W. van Noort, Zuzana Jandová, Adrien S. J. Melquiond, Alexandre M. J. J. Bonvin
Interactions between macromolecules, such as proteins and nucleic acids, are essential for cellular functions. Experimental methods can fail to provide all the information required to fully model biomolecular complexes at atomic resolution, particularly for large and heterogeneous assemblies. Integrative computational approaches have, therefore, gained popularity, complementing traditional experimental methods in structural biology. Here, we introduce HADDOCK2.4, an integrative modeling platform, and its updated web interface ( https://wenmr.science.uu.nl/haddock2.4 ). The platform seamlessly integrates diverse experimental and theoretical data to generate high-quality models of macromolecular complexes. The user-friendly web server offers automated parameter settings, access to distributed computing resources, and pre- and post-processing steps that enhance the user experience. To present the web server’s various interfaces and features, we demonstrate two different applications: (i) we predict the structure of an antibody–antigen complex by using NMR data for the antigen and knowledge of the hypervariable loops for the antibody, and (ii) we perform coarse-grained modeling of PRC1 with a nucleosome particle guided by mutagenesis and functional data. The described protocols require some basic familiarity with molecular modeling and the Linux command shell. This new version of our widely used HADDOCK web server allows structural biologists and non-experts to explore intricate macromolecular assemblies encompassing various molecule types. The HADDOCK2.4 web server is a modeling platform that can integrate experimental and theoretical data for guiding 3D prediction of biomolecular complexes.
{"title":"The HADDOCK2.4 web server for integrative modeling of biomolecular complexes","authors":"Rodrigo V. Honorato, Mikael E. Trellet, Brian Jiménez-García, Jörg J. Schaarschmidt, Marco Giulini, Victor Reys, Panagiotis I. Koukos, João P. G. L. M. Rodrigues, Ezgi Karaca, Gydo C. P. van Zundert, Jorge Roel-Touris, Charlotte W. van Noort, Zuzana Jandová, Adrien S. J. Melquiond, Alexandre M. J. J. Bonvin","doi":"10.1038/s41596-024-01011-0","DOIUrl":"10.1038/s41596-024-01011-0","url":null,"abstract":"Interactions between macromolecules, such as proteins and nucleic acids, are essential for cellular functions. Experimental methods can fail to provide all the information required to fully model biomolecular complexes at atomic resolution, particularly for large and heterogeneous assemblies. Integrative computational approaches have, therefore, gained popularity, complementing traditional experimental methods in structural biology. Here, we introduce HADDOCK2.4, an integrative modeling platform, and its updated web interface ( https://wenmr.science.uu.nl/haddock2.4 ). The platform seamlessly integrates diverse experimental and theoretical data to generate high-quality models of macromolecular complexes. The user-friendly web server offers automated parameter settings, access to distributed computing resources, and pre- and post-processing steps that enhance the user experience. To present the web server’s various interfaces and features, we demonstrate two different applications: (i) we predict the structure of an antibody–antigen complex by using NMR data for the antigen and knowledge of the hypervariable loops for the antibody, and (ii) we perform coarse-grained modeling of PRC1 with a nucleosome particle guided by mutagenesis and functional data. The described protocols require some basic familiarity with molecular modeling and the Linux command shell. This new version of our widely used HADDOCK web server allows structural biologists and non-experts to explore intricate macromolecular assemblies encompassing various molecule types. The HADDOCK2.4 web server is a modeling platform that can integrate experimental and theoretical data for guiding 3D prediction of biomolecular complexes.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":"19 11","pages":"3219-3241"},"PeriodicalIF":13.1,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141419848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-12DOI: 10.1038/s41596-024-01006-x
Juan Luo, Yao Yu, Ke Wang, Sizhe He, Longjie Wang, Fangfang Liang, Jason W. Chin, Shan Tang
Catalytic mechanism-based, light-activated traps have recently been developed to identify the substrates of cysteine or serine hydrolases. These traps are hydrolase mutants whose catalytic cysteine or serine are replaced with genetically encoded 2,3-diaminopropionic acid (DAP). DAP-containing hydrolases specifically capture the transient thioester- or ester-linked acyl–enzyme intermediates resulting from the first step of the proteolytic reaction as their stable amide analogs. The trapped substrate fragments allow the downstream identification of hydrolase substrates by mass spectrometry and immunoblotting. In this protocol, we provide a detailed step-by-step guide for substrate capture and identification of the peptidase domain of the large tegument protein deneddylase (UL36USP) from human herpesvirus 1, both in mammalian cell lysate and live mammalian cells. Four procedures are included: Procedure 1, DAP-mediated substrate trapping in mammalian cell lysate (~8 d); Procedure 2, DAP-mediated substrate trapping in adherent mammalian cells (~6 d); Procedure 3, DAP-mediated substrate trapping in suspension mammalian cells (~5 d); and Procedure 4, substrate identification and validation (~12–13 d). Basic skills to perform protein expression in bacteria or mammalian cells, affinity enrichment and proteomic analysis are required to implement the protocol. This protocol will be a practical guide for identifying substrates of serine or cysteine hydrolases either in a complex mixture, where genetic manipulation is challenging, or in live cells such as bacteria, yeasts and mammalian cells. Light-activated, 2,3-diaminopropionic acid-containing hydrolases trap substrate fragments, facilitating the discovery of new substrates and activities of enzymes in complex mixtures and live cells by mass spectrometry.
{"title":"Capturing acyl–enzyme intermediates with genetically encoded 2,3-diaminopropionic acid for hydrolase substrate identification","authors":"Juan Luo, Yao Yu, Ke Wang, Sizhe He, Longjie Wang, Fangfang Liang, Jason W. Chin, Shan Tang","doi":"10.1038/s41596-024-01006-x","DOIUrl":"10.1038/s41596-024-01006-x","url":null,"abstract":"Catalytic mechanism-based, light-activated traps have recently been developed to identify the substrates of cysteine or serine hydrolases. These traps are hydrolase mutants whose catalytic cysteine or serine are replaced with genetically encoded 2,3-diaminopropionic acid (DAP). DAP-containing hydrolases specifically capture the transient thioester- or ester-linked acyl–enzyme intermediates resulting from the first step of the proteolytic reaction as their stable amide analogs. The trapped substrate fragments allow the downstream identification of hydrolase substrates by mass spectrometry and immunoblotting. In this protocol, we provide a detailed step-by-step guide for substrate capture and identification of the peptidase domain of the large tegument protein deneddylase (UL36USP) from human herpesvirus 1, both in mammalian cell lysate and live mammalian cells. Four procedures are included: Procedure 1, DAP-mediated substrate trapping in mammalian cell lysate (~8 d); Procedure 2, DAP-mediated substrate trapping in adherent mammalian cells (~6 d); Procedure 3, DAP-mediated substrate trapping in suspension mammalian cells (~5 d); and Procedure 4, substrate identification and validation (~12–13 d). Basic skills to perform protein expression in bacteria or mammalian cells, affinity enrichment and proteomic analysis are required to implement the protocol. This protocol will be a practical guide for identifying substrates of serine or cysteine hydrolases either in a complex mixture, where genetic manipulation is challenging, or in live cells such as bacteria, yeasts and mammalian cells. Light-activated, 2,3-diaminopropionic acid-containing hydrolases trap substrate fragments, facilitating the discovery of new substrates and activities of enzymes in complex mixtures and live cells by mass spectrometry.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":"19 10","pages":"2967-2999"},"PeriodicalIF":13.1,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141311211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-06DOI: 10.1038/s41596-024-01003-0
Hanna Liao, Junhong Choi, Jay Shendure
Recording molecular information to genomic DNA is a powerful means of investigating topics ranging from multicellular development to cancer evolution. With molecular recording based on genome editing, events such as cell divisions and signaling pathway activity drive specific alterations in a cell’s DNA, marking the genome with information about a cell’s history that can be read out after the fact. Although genome editing has been used for molecular recording, capturing the temporal relationships among recorded events in mammalian cells remains challenging. The DNA Typewriter system overcomes this limitation by leveraging prime editing to facilitate sequential insertions to an engineered genomic region. DNA Typewriter includes three distinct components: DNA Tape as the ‘substrate’ to which edits accrue in an ordered manner, the prime editor enzyme, and prime editing guide RNAs, which program insertional edits to DNA Tape. In this protocol, we describe general design considerations for DNA Typewriter, step-by-step instructions on how to perform recording experiments by using DNA Typewriter in HEK293T cells, and example scripts for analyzing DNA Typewriter data ( https://doi.org/10.6084/m9.figshare.22728758 ). This protocol covers two main applications of DNA Typewriter: recording sequential transfection events with programmed barcode insertions by using prime editing and recording lineage information during the expansion of a single cell to many. Compared with other methods that are compatible with mammalian cells, DNA Typewriter enables the recording of temporal information with higher recording capacities and can be completed within 4–6 weeks with basic expertise in molecular cloning, mammalian cell culturing and DNA sequencing data analysis. This protocol describes a CRISPR prime editing-based method for the sequential and unidirectional tracing of insertional events in mammalian cells, generating a dynamic recording of such information within living cells.
将分子信息记录到基因组 DNA 是研究从多细胞发育到癌症进化等各种课题的有力手段。通过基于基因组编辑的分子记录，细胞分裂和信号通路活动等事件会驱动细胞 DNA 发生特定改变，从而在基因组上标记出细胞的历史信息，这些信息可以在事后读出。虽然基因组编辑已被用于分子记录，但捕捉哺乳动物细胞中记录事件之间的时间关系仍是一项挑战。DNA 打字机系统克服了这一限制，它利用素体编辑来促进对工程基因组区域的顺序插入。DNA 打字机包括三个不同的组件：作为 "底物 "的 DNA 磁带（其上的编辑以有序的方式累积）、素编辑酶和素编辑向导 RNA（将插入编辑编程到 DNA 磁带上）。在本方案中，我们介绍了 DNA 打字机的一般设计注意事项、如何在 HEK293T 细胞中使用 DNA 打字机进行记录实验的分步说明以及分析 DNA 打字机数据的示例脚本 ( https://doi.org/10.6084/m9.figshare.22728758 )。本实验方案涵盖了 DNA Typewriter 的两大应用：通过素描编辑记录带有编程条形码插入的连续转染事件，以及记录单细胞扩增到多细胞过程中的系谱信息。与其他与哺乳动物细胞兼容的方法相比，DNA Typewriter 能以更高的记录能力记录时间信息，而且只需具备分子克隆、哺乳动物细胞培养和 DNA 测序数据分析方面的基本专业知识，就能在 4-6 周内完成。
{"title":"Molecular recording using DNA Typewriter","authors":"Hanna Liao, Junhong Choi, Jay Shendure","doi":"10.1038/s41596-024-01003-0","DOIUrl":"10.1038/s41596-024-01003-0","url":null,"abstract":"Recording molecular information to genomic DNA is a powerful means of investigating topics ranging from multicellular development to cancer evolution. With molecular recording based on genome editing, events such as cell divisions and signaling pathway activity drive specific alterations in a cell’s DNA, marking the genome with information about a cell’s history that can be read out after the fact. Although genome editing has been used for molecular recording, capturing the temporal relationships among recorded events in mammalian cells remains challenging. The DNA Typewriter system overcomes this limitation by leveraging prime editing to facilitate sequential insertions to an engineered genomic region. DNA Typewriter includes three distinct components: DNA Tape as the ‘substrate’ to which edits accrue in an ordered manner, the prime editor enzyme, and prime editing guide RNAs, which program insertional edits to DNA Tape. In this protocol, we describe general design considerations for DNA Typewriter, step-by-step instructions on how to perform recording experiments by using DNA Typewriter in HEK293T cells, and example scripts for analyzing DNA Typewriter data ( https://doi.org/10.6084/m9.figshare.22728758 ). This protocol covers two main applications of DNA Typewriter: recording sequential transfection events with programmed barcode insertions by using prime editing and recording lineage information during the expansion of a single cell to many. Compared with other methods that are compatible with mammalian cells, DNA Typewriter enables the recording of temporal information with higher recording capacities and can be completed within 4–6 weeks with basic expertise in molecular cloning, mammalian cell culturing and DNA sequencing data analysis. This protocol describes a CRISPR prime editing-based method for the sequential and unidirectional tracing of insertional events in mammalian cells, generating a dynamic recording of such information within living cells.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":"19 10","pages":"2833-2862"},"PeriodicalIF":13.1,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141284272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-06DOI: 10.1038/s41596-024-00991-3
Brian L. Hie, Soochi Kim, Thomas A. Rando, Bryan Bryson, Bonnie Berger
Merging diverse single-cell RNA sequencing (scRNA-seq) data from numerous experiments, laboratories and technologies can uncover important biological insights. Nonetheless, integrating scRNA-seq data encounters special challenges when the datasets are composed of diverse cell type compositions. Scanorama offers a robust solution for improving the quality and interpretation of heterogeneous scRNA-seq data by effectively merging information from diverse sources. Scanorama is designed to address the technical variation introduced by differences in sample preparation, sequencing depth and experimental batches that can confound the analysis of multiple scRNA-seq datasets. Here we provide a detailed protocol for using Scanorama within a Scanpy-based single-cell analysis workflow coupled with Google Colaboratory, a cloud-based free Jupyter notebook environment service. The protocol involves Scanorama integration, a process that typically spans 0.5–3 h. Scanorama integration requires a basic understanding of cellular biology, transcriptomic technologies and bioinformatics. Our protocol and new Scanorama–Colaboratory resource should make scRNA-seq integration more widely accessible to researchers. Scanorama is an effective tool for combining multiple single-cell RNA sequencing datasets, addressing technical variation introduced by differences in sample preparation, sequencing depth and experimental batches that can confound the analysis of diverse datasets.
{"title":"Scanorama: integrating large and diverse single-cell transcriptomic datasets","authors":"Brian L. Hie, Soochi Kim, Thomas A. Rando, Bryan Bryson, Bonnie Berger","doi":"10.1038/s41596-024-00991-3","DOIUrl":"10.1038/s41596-024-00991-3","url":null,"abstract":"Merging diverse single-cell RNA sequencing (scRNA-seq) data from numerous experiments, laboratories and technologies can uncover important biological insights. Nonetheless, integrating scRNA-seq data encounters special challenges when the datasets are composed of diverse cell type compositions. Scanorama offers a robust solution for improving the quality and interpretation of heterogeneous scRNA-seq data by effectively merging information from diverse sources. Scanorama is designed to address the technical variation introduced by differences in sample preparation, sequencing depth and experimental batches that can confound the analysis of multiple scRNA-seq datasets. Here we provide a detailed protocol for using Scanorama within a Scanpy-based single-cell analysis workflow coupled with Google Colaboratory, a cloud-based free Jupyter notebook environment service. The protocol involves Scanorama integration, a process that typically spans 0.5–3 h. Scanorama integration requires a basic understanding of cellular biology, transcriptomic technologies and bioinformatics. Our protocol and new Scanorama–Colaboratory resource should make scRNA-seq integration more widely accessible to researchers. Scanorama is an effective tool for combining multiple single-cell RNA sequencing datasets, addressing technical variation introduced by differences in sample preparation, sequencing depth and experimental batches that can confound the analysis of diverse datasets.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":"19 8","pages":"2283-2297"},"PeriodicalIF":13.1,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141284273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-04DOI: 10.1038/s41596-024-01005-y
Veronika Csillag, J. C. Noble, Daniela Calvigioni, Björn Reinius, János Fuzik
Neuronal pathways recruit large postsynaptic populations and maintain connections via distinct postsynaptic response types (PRTs). Until recently, PRTs were accessible as a selection criterion for single-cell RNA sequencing only through probing by low-throughput whole-cell electrophysiology. To overcome these limitations and target neurons on the basis of specific PRTs for soma collection and subsequent single-cell RNA sequencing, we developed Voltage-Seq using the genetically encoded voltage indicator Voltron in acute brain slices from mice. We also created an onsite analysis tool, VoltView, to guide soma collection of specific PRTs using a classifier based on a previously acquired database of connectomes from multiple animals. Here we present our procedure for preparing the optical path, the imaging setup and detailing the imaging and analysis steps, as well as a complete procedure for sequencing library preparation. This enables researchers to conduct our high-throughput all-optical synaptic assay and to obtain single-cell transcriptomic data from selected postsynaptic neurons. This also allows researchers to resolve the connectivity ratio of a specific pathway and explore the diversity of PRTs within that connectome. Furthermore, combining high throughput with quick analysis gives unique access to find specific connections within a large postsynaptic connectome. Voltage-Seq also allows the investigation of correlations between connectivity and gene expression changes in a postsynaptic cell-type-specific manner for both excitatory and inhibitory connections. The Voltage-Seq workflow can be completed in ~6 weeks, including 4–5 weeks for viral expression of the Voltron sensor. The technique requires knowledge of basic laboratory techniques, micromanipulator handling skills and experience in molecular biology and bioinformatics. Voltage-Seq is a method for all-optical voltage imaging-guided postsynaptic single-cell transcriptomics. It combines the use of the Voltron voltage indicator with the analysis tool VoltView to select specific neuronal somas to collect for single-cell RNA sequencing.
{"title":"All-optical voltage imaging-guided postsynaptic single-cell transcriptome profiling with Voltage-Seq","authors":"Veronika Csillag, J. C. Noble, Daniela Calvigioni, Björn Reinius, János Fuzik","doi":"10.1038/s41596-024-01005-y","DOIUrl":"10.1038/s41596-024-01005-y","url":null,"abstract":"Neuronal pathways recruit large postsynaptic populations and maintain connections via distinct postsynaptic response types (PRTs). Until recently, PRTs were accessible as a selection criterion for single-cell RNA sequencing only through probing by low-throughput whole-cell electrophysiology. To overcome these limitations and target neurons on the basis of specific PRTs for soma collection and subsequent single-cell RNA sequencing, we developed Voltage-Seq using the genetically encoded voltage indicator Voltron in acute brain slices from mice. We also created an onsite analysis tool, VoltView, to guide soma collection of specific PRTs using a classifier based on a previously acquired database of connectomes from multiple animals. Here we present our procedure for preparing the optical path, the imaging setup and detailing the imaging and analysis steps, as well as a complete procedure for sequencing library preparation. This enables researchers to conduct our high-throughput all-optical synaptic assay and to obtain single-cell transcriptomic data from selected postsynaptic neurons. This also allows researchers to resolve the connectivity ratio of a specific pathway and explore the diversity of PRTs within that connectome. Furthermore, combining high throughput with quick analysis gives unique access to find specific connections within a large postsynaptic connectome. Voltage-Seq also allows the investigation of correlations between connectivity and gene expression changes in a postsynaptic cell-type-specific manner for both excitatory and inhibitory connections. The Voltage-Seq workflow can be completed in ~6 weeks, including 4–5 weeks for viral expression of the Voltron sensor. The technique requires knowledge of basic laboratory techniques, micromanipulator handling skills and experience in molecular biology and bioinformatics. Voltage-Seq is a method for all-optical voltage imaging-guided postsynaptic single-cell transcriptomics. It combines the use of the Voltron voltage indicator with the analysis tool VoltView to select specific neuronal somas to collect for single-cell RNA sequencing.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":"19 10","pages":"2863-2890"},"PeriodicalIF":13.1,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141248028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-04DOI: 10.1038/s41596-024-01018-7
Saima M Sidik, Diego Huet, Sebastian Lourido
{"title":"Author Correction: CRISPR-Cas9-based genome-wide screening of Toxoplasma gondii.","authors":"Saima M Sidik, Diego Huet, Sebastian Lourido","doi":"10.1038/s41596-024-01018-7","DOIUrl":"https://doi.org/10.1038/s41596-024-01018-7","url":null,"abstract":"","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":" ","pages":""},"PeriodicalIF":14.8,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141248029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-03DOI: 10.1038/s41596-024-00997-x
Sidharth Tyagi, Grant P. Higerd-Rusli, Elizabeth J. Akin, Christopher A. Baker, Shujun Liu, Fadia B. Dib-Hajj, Stephen G. Waxman, Sulayman D. Dib-Hajj
The construction of neuronal membranes is a dynamic process involving the biogenesis, vesicular packaging, transport, insertion and recycling of membrane proteins. Optical imaging is well suited for the study of protein spatial organization and transport. However, various shortcomings of existing imaging techniques have prevented the study of specific types of proteins and cellular processes. Here we describe strategies for protein tagging and labeling, cell culture and microscopy that enable the real-time imaging of axonal membrane protein trafficking and subcellular distribution as they progress through some stages of their life cycle. First, we describe a process for engineering membrane proteins with extracellular self-labeling tags (either HaloTag or SNAPTag), which can be labeled with fluorescent ligands of various colors and cell permeability, providing flexibility for investigating the trafficking and spatiotemporal regulation of multiple membrane proteins in neuronal compartments. Next, we detail the dissection, transfection and culture of dorsal root ganglion sensory neurons in microfluidic chambers, which physically compartmentalizes cell bodies and distal axons. Finally, we describe four labeling and imaging procedures that utilize these enzymatically tagged proteins, flexible fluorescent labels and compartmentalized neuronal cultures to study axonal membrane protein anterograde and retrograde transport, the cotransport of multiple proteins, protein subcellular localization, exocytosis and endocytosis. Additionally, we generated open-source software for analyzing the imaging data in a high throughput manner. The experimental and analysis workflows provide an approach for studying the dynamics of neuronal membrane protein homeostasis, addressing longstanding challenges in this area. The protocol requires 5–7 days and expertise in cell culture and microscopy. Conjugation of self-labeling enzymatic tags to axonal membrane proteins enables studying the dynamics of their trafficking, cellular localization and fate.
{"title":"Real-time imaging of axonal membrane protein life cycles","authors":"Sidharth Tyagi, Grant P. Higerd-Rusli, Elizabeth J. Akin, Christopher A. Baker, Shujun Liu, Fadia B. Dib-Hajj, Stephen G. Waxman, Sulayman D. Dib-Hajj","doi":"10.1038/s41596-024-00997-x","DOIUrl":"10.1038/s41596-024-00997-x","url":null,"abstract":"The construction of neuronal membranes is a dynamic process involving the biogenesis, vesicular packaging, transport, insertion and recycling of membrane proteins. Optical imaging is well suited for the study of protein spatial organization and transport. However, various shortcomings of existing imaging techniques have prevented the study of specific types of proteins and cellular processes. Here we describe strategies for protein tagging and labeling, cell culture and microscopy that enable the real-time imaging of axonal membrane protein trafficking and subcellular distribution as they progress through some stages of their life cycle. First, we describe a process for engineering membrane proteins with extracellular self-labeling tags (either HaloTag or SNAPTag), which can be labeled with fluorescent ligands of various colors and cell permeability, providing flexibility for investigating the trafficking and spatiotemporal regulation of multiple membrane proteins in neuronal compartments. Next, we detail the dissection, transfection and culture of dorsal root ganglion sensory neurons in microfluidic chambers, which physically compartmentalizes cell bodies and distal axons. Finally, we describe four labeling and imaging procedures that utilize these enzymatically tagged proteins, flexible fluorescent labels and compartmentalized neuronal cultures to study axonal membrane protein anterograde and retrograde transport, the cotransport of multiple proteins, protein subcellular localization, exocytosis and endocytosis. Additionally, we generated open-source software for analyzing the imaging data in a high throughput manner. The experimental and analysis workflows provide an approach for studying the dynamics of neuronal membrane protein homeostasis, addressing longstanding challenges in this area. The protocol requires 5–7 days and expertise in cell culture and microscopy. Conjugation of self-labeling enzymatic tags to axonal membrane proteins enables studying the dynamics of their trafficking, cellular localization and fate.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":"19 9","pages":"2771-2802"},"PeriodicalIF":13.1,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141238035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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