Nature Protocols最新文献

{"title":"Observing isolated synaptic vesicle association and fusion ex vivo.","authors":"Jeremy Leitz, Chuchu Wang, Luis Esquivies, John J Peters, Nisha Gopal, Richard A Pfuetzner, Austin L Wang, Axel T Brunger","doi":"10.1038/s41596-024-01014-x","DOIUrl":"https://doi.org/10.1038/s41596-024-01014-x","url":null,"abstract":"<p><p>Here, we present a protocol for isolating functionally intact glutamatergic synaptic vesicles from whole-mouse brain tissue and using them in a single-vesicle assay to examine their association and fusion with plasma membrane mimic vesicles. This is a Protocol Extension, building on our previous protocol, which used a purely synthetic system comprised of reconstituted proteins in liposomes. We also describe the generation of a peptide based on the vesicular glutamate transporter, which is essential in the isolation process of glutamatergic synaptic vesicles. This method uses easily accessible reagents to generate fusion-competent glutamatergic synaptic vesicles through immunoisolation. The generation of the vGlut peptide can be accomplished in 6 d, while the isolation of the synaptic vesicles by using the peptide can be accomplished in 2 d, with an additional day to fluorescently label the synaptic vesicles for use in a single-vesicle hybrid fusion assay. The single-vesicle fusion assay can be accomplished in 1 d and can unambiguously delineate synaptic vesicle association, dissociation, Ca²⁺-independent and Ca²⁺-dependent fusion modalities. This assay grants control of the synaptic vesicle environment while retaining the complexity of the synaptic vesicles themselves. This protocol can be adapted to studies of other types of synaptic vesicles or, more generally, different secretory or transport vesicles. The workflow described here requires expertise in biochemistry techniques, in particular, protein purification and fluorescence imaging. We assume that the laboratory has protein-purification equipment, including chromatography systems.</p>","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":null,"pages":null},"PeriodicalIF":13.1,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141492702","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}

{"title":"Spatially resolved epigenome sequencing via Tn5 transposition and deterministic DNA barcoding in tissue.","authors":"Negin Farzad, Archibald Enninful, Shuozhen Bao, Di Zhang, Yanxiang Deng, Rong Fan","doi":"10.1038/s41596-024-01013-y","DOIUrl":"https://doi.org/10.1038/s41596-024-01013-y","url":null,"abstract":"<p><p>Spatial epigenetic mapping of tissues enables the study of gene regulation programs and cellular functions with the dependency on their local tissue environment. Here we outline a complete procedure for two spatial epigenomic profiling methods: spatially resolved genome-wide profiling of histone modifications using in situ cleavage under targets and tagmentation (CUT&Tag) chemistry (spatial-CUT&Tag) and transposase-accessible chromatin sequencing (spatial-ATAC-sequencing) for chromatin accessibility. Both assays utilize in-tissue Tn5 transposition to recognize genomic DNA loci followed by microfluidic deterministic barcoding to incorporate spatial address codes. Furthermore, these two methods do not necessitate prior knowledge of the transcription or epigenetic markers for a given tissue or cell type but permit genome-wide unbiased profiling pixel-by-pixel at the 10 μm pixel size level and single-base resolution. To support the widespread adaptation of these methods, details are provided in five general steps: (1) sample preparation; (2) Tn5 transposition in spatial-ATAC-sequencing or antibody-controlled pA-Tn5 tagmentation in CUT&Tag; (3) library preparation; (4) next-generation sequencing; and (5) data analysis using our customed pipelines available at: https://github.com/dyxmvp/Spatial_ATAC-seq and https://github.com/dyxmvp/spatial-CUT-Tag . The whole procedure can be completed on four samples in 2-3 days. Familiarity with basic molecular biology and bioinformatics skills with access to a high-performance computing environment are required. A rudimentary understanding of pathology and specimen sectioning, as well as deterministic barcoding in tissue-specific skills (e.g., design of a multiparameter barcode panel and creation of microfluidic devices), are also advantageous. In this protocol, we mainly focus on spatial profiling of tissue region-specific epigenetic landscapes in mouse embryos and mouse brains using spatial-ATAC-sequencing and spatial-CUT&Tag, but these methods can be used for other species with no need for species-specific probe design.</p>","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":null,"pages":null},"PeriodicalIF":13.1,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141469524","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}

{"title":"Characterizing the structure of mouse behavior using Motion Sequencing.","authors":"Sherry Lin, Winthrop F Gillis, Caleb Weinreb, Ayman Zeine, Samuel C Jones, Emma M Robinson, Jeffrey Markowitz, Sandeep Robert Datta","doi":"10.1038/s41596-024-01015-w","DOIUrl":"https://doi.org/10.1038/s41596-024-01015-w","url":null,"abstract":"<p><p>Spontaneous mouse behavior is composed from repeatedly used modules of movement (e.g., rearing, running or grooming) that are flexibly placed into sequences whose content evolves over time. By identifying behavioral modules and the order in which they are expressed, researchers can gain insight into the effect of drugs, genes, context, sensory stimuli and neural activity on natural behavior. Here we present a protocol for performing Motion Sequencing (MoSeq), an ethologically inspired method that uses three-dimensional machine vision and unsupervised machine learning to decompose spontaneous mouse behavior into a series of elemental modules called 'syllables'. This protocol is based upon a MoSeq pipeline that includes modules for depth video acquisition, data preprocessing and modeling, as well as a standardized set of visualization tools. Users are provided with instructions and code for building a MoSeq imaging rig and acquiring three-dimensional video of spontaneous mouse behavior for submission to the modeling framework; the outputs of this protocol include syllable labels for each frame of the video data as well as summary plots describing how often each syllable was used and how syllables transitioned from one to the other. In addition, we provide instructions for analyzing and visualizing the outputs of keypoint-MoSeq, a recently developed variant of MoSeq that can identify behavioral motifs from keypoints identified from standard (rather than depth) video. This protocol and the accompanying pipeline significantly lower the bar for users without extensive computational ethology experience to adopt this unsupervised, data-driven approach to characterize mouse behavior.</p>","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":null,"pages":null},"PeriodicalIF":13.1,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141458192","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}

{"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":"https://doi.org/10.1038/s41596-024-01001-2","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":null,"pages":null},"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}

{"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":"https://doi.org/10.1038/s41596-024-01004-z","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":null,"pages":null},"PeriodicalIF":14.8,"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}

{"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":"https://doi.org/10.1038/s41596-024-01007-w","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":null,"pages":null},"PeriodicalIF":14.8,"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}

{"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":"https://doi.org/10.1038/s41596-024-01011-0","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":null,"pages":null},"PeriodicalIF":14.8,"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}

{"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":"https://doi.org/10.1038/s41596-024-01006-x","url":null,"abstract":"<p><p>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 (UL36^USP) 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.</p>","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":null,"pages":null},"PeriodicalIF":14.8,"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}

{"title":"Molecular recording using DNA Typewriter.","authors":"Hanna Liao, Junhong Choi, Jay Shendure","doi":"10.1038/s41596-024-01003-0","DOIUrl":"https://doi.org/10.1038/s41596-024-01003-0","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":null,"pages":null},"PeriodicalIF":14.8,"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}

{"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":"https://doi.org/10.1038/s41596-024-00991-3","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":null,"pages":null},"PeriodicalIF":14.8,"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}