Nature Protocols最新文献

{"title":"Statistical analysis of feature-based molecular networking results from non-targeted metabolomics data","authors":"Abzer K. Pakkir Shah, Axel Walter, Filip Ottosson, Francesco Russo, Marcelo Navarro-Diaz, Judith Boldt, Jarmo-Charles J. Kalinski, Eftychia Eva Kontou, James Elofson, Alexandros Polyzois, Carolina González-Marín, Shane Farrell, Marie R. Aggerbeck, Thapanee Pruksatrakul, Nathan Chan, Yunshu Wang, Magdalena Pöchhacker, Corinna Brungs, Beatriz Cámara, Andrés Mauricio Caraballo-Rodríguez, Andres Cumsille, Fernanda de Oliveira, Kai Dührkop, Yasin El Abiead, Christian Geibel, Lana G. Graves, Martin Hansen, Steffen Heuckeroth, Simon Knoblauch, Anastasiia Kostenko, Mirte C. M. Kuijpers, Kevin Mildau, Stilianos Papadopoulos Lambidis, Paulo Wender Portal Gomes, Tilman Schramm, Karoline Steuer-Lodd, Paolo Stincone, Sibgha Tayyab, Giovanni Andrea Vitale, Berenike C. Wagner, Shipei Xing, Marquis T. Yazzie, Simone Zuffa, Martinus de Kruijff, Christine Beemelmanns, Hannes Link, Christoph Mayer, Justin J. J. van der Hooft, Tito Damiani, Tomáš Pluskal, Pieter Dorrestein, Jan Stanstrup, Robin Schmid, Mingxun Wang, Allegra Aron, Madeleine Ernst, Daniel Petras","doi":"10.1038/s41596-024-01046-3","DOIUrl":"10.1038/s41596-024-01046-3","url":null,"abstract":"Feature-based molecular networking (FBMN) is a popular analysis approach for liquid chromatography–tandem mass spectrometry-based non-targeted metabolomics data. While processing liquid chromatography–tandem mass spectrometry data through FBMN is fairly streamlined, downstream data handling and statistical interrogation are often a key bottleneck. Especially users new to statistical analysis struggle to effectively handle and analyze complex data matrices. Here we provide a comprehensive guide for the statistical analysis of FBMN results, focusing on the downstream analysis of the FBMN output table. We explain the data structure and principles of data cleanup and normalization, as well as uni- and multivariate statistical analysis of FBMN results. We provide explanations and code in two scripting languages (R and Python) as well as the QIIME2 framework for all protocol steps, from data clean-up to statistical analysis. All code is shared in the form of Jupyter Notebooks ( https://github.com/Functional-Metabolomics-Lab/FBMN-STATS ). Additionally, the protocol is accompanied by a web application with a graphical user interface ( https://fbmn-statsguide.gnps2.org/ ) to lower the barrier of entry for new users and for educational purposes. Finally, we also show users how to integrate their statistical results into the molecular network using the Cytoscape visualization tool. Throughout the protocol, we use a previously published environmental metabolomics dataset for demonstration purposes. Together, the protocol, code and web application provide a complete guide and toolbox for FBMN data integration, cleanup and advanced statistical analysis, enabling new users to uncover molecular insights from their non-targeted metabolomics data. Our protocol is tailored for the seamless analysis of FBMN results from Global Natural Products Social Molecular Networking and can be easily adapted to other mass spectrometry feature detection, annotation and networking tools. Feature-based molecular networking is used to analyze non-targeted liquid chromatography–tandem mass spectrometry metabolomics data. This protocol includes instructions, ready-made code and a web app ( https://fbmn-statsguide.gnps2.org/ ) for statistical analysis of feature-based molecular networking results.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":"20 1","pages":"92-162"},"PeriodicalIF":13.1,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142291583","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":"Publisher Correction: In vivo pulse labeling of isochronic cohorts of cells in the central nervous system using FlashTag.","authors":"Subashika Govindan, Polina Oberst, Denis Jabaudon","doi":"10.1038/s41596-024-01069-w","DOIUrl":"https://doi.org/10.1038/s41596-024-01069-w","url":null,"abstract":"","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":" ","pages":""},"PeriodicalIF":13.1,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142291581","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":"Interfacial property determination from dynamic pendant-drop characterizations","authors":"Ziqing Pan, J. P. Martin Trusler, Zhijun Jin, Kaiqiang Zhang","doi":"10.1038/s41596-024-01049-0","DOIUrl":"https://doi.org/10.1038/s41596-024-01049-0","url":null,"abstract":"<p>The properties of the interface between materials have practical implications in various fields, encompassing capillary action, foam and emulsion stability, adhesion properties of materials and mass and heat transfer processes. Studying the dynamics of interfaces is also fundamental for understanding intermolecular interactions, change of molecular conformations and molecular aggregations. Pendant-drop tensiometry and its extension, the oscillating drop method, are simple, versatile methods used to measure surface tension, interfacial tension and interfacial rheological properties. These methods can, however, generate unreliable results because of inadequate material preparation, an incorrect calibration method, inappropriate selection of data for analysis, neglect of optical influences or operating the system outside the linear viscoelastic regime. In addition, many studies fail to report accurate uncertainties. This protocol addresses all these critical points and provides detailed descriptions of some operation tips relating to purifying methods for different kinds of material, the time frame for analyzing measurement data, the correction method for optical effects, implementation of the oscillating method with a common programmable pump and remedies for some common problems encountered during the measurement. Examples of interfacial tension measurements for two- and three-phase systems, as well as interfacial dilational modulus measurements for N₂ and surfactant solutions, are provided to illustrate procedural details and results. A single measurement takes minutes to hours to complete, while the entire protocol, including the leak test, cleaning, repeated measurements and data analysis, may take several days.</p>","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":"41 1","pages":""},"PeriodicalIF":14.8,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142269497","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":"From whole-slide image to biomarker prediction: end-to-end weakly supervised deep learning in computational pathology","authors":"Omar S. M. El Nahhas,&nbsp;Marko van Treeck,&nbsp;Georg Wölflein,&nbsp;Michaela Unger,&nbsp;Marta Ligero,&nbsp;Tim Lenz,&nbsp;Sophia J. Wagner,&nbsp;Katherine J. Hewitt,&nbsp;Firas Khader,&nbsp;Sebastian Foersch,&nbsp;Daniel Truhn,&nbsp;Jakob Nikolas Kather","doi":"10.1038/s41596-024-01047-2","DOIUrl":"10.1038/s41596-024-01047-2","url":null,"abstract":"Hematoxylin- and eosin-stained whole-slide images (WSIs) are the foundation of diagnosis of cancer. In recent years, development of deep learning-based methods in computational pathology has enabled the prediction of biomarkers directly from WSIs. However, accurately linking tissue phenotype to biomarkers at scale remains a crucial challenge for democratizing complex biomarkers in precision oncology. This protocol describes a practical workflow for solid tumor associative modeling in pathology (STAMP), enabling prediction of biomarkers directly from WSIs by using deep learning. The STAMP workflow is biomarker agnostic and allows for genetic and clinicopathologic tabular data to be included as an additional input, together with histopathology images. The protocol consists of five main stages that have been successfully applied to various research problems: formal problem definition, data preprocessing, modeling, evaluation and clinical translation. The STAMP workflow differentiates itself through its focus on serving as a collaborative framework that can be used by clinicians and engineers alike for setting up research projects in the field of computational pathology. As an example task, we applied STAMP to the prediction of microsatellite instability (MSI) status in colorectal cancer, showing accurate performance for the identification of tumors high in MSI. Moreover, we provide an open-source code base, which has been deployed at several hospitals across the globe to set up computational pathology workflows. The STAMP workflow requires one workday of hands-on computational execution and basic command line knowledge. We present a practical workflow for end-to-end weakly supervised deep learning to predict biomarkers directly from whole-slide images, enabling clinical researchers to work with engineers to set up a complete computational pathology project.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":"20 1","pages":"293-316"},"PeriodicalIF":13.1,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142263727","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":"CellChat for systematic analysis of cell–cell communication from single-cell transcriptomics","authors":"Suoqin Jin,&nbsp;Maksim V. Plikus,&nbsp;Qing Nie","doi":"10.1038/s41596-024-01045-4","DOIUrl":"10.1038/s41596-024-01045-4","url":null,"abstract":"Recent advances in single-cell sequencing technologies offer an opportunity to explore cell–cell communication in tissues systematically and with reduced bias. A key challenge is integrating known molecular interactions and measurements into a framework to identify and analyze complex cell–cell communication networks. Previously, we developed a computational tool, named CellChat, that infers and analyzes cell–cell communication networks from single-cell transcriptomic data within an easily interpretable framework. CellChat quantifies the signaling communication probability between two cell groups using a simplified mass-action-based model, which incorporates the core interaction between ligands and receptors with multisubunit structure along with modulation by cofactors. Importantly, CellChat performs a systematic and comparative analysis of cell–cell communication using a variety of quantitative metrics and machine-learning approaches. CellChat v2 is an updated version that includes additional comparison functionalities, an expanded database of ligand–receptor pairs along with rich functional annotations, and an Interactive CellChat Explorer. Here we provide a step-by-step protocol for using CellChat v2 on single-cell transcriptomic data, including inference and analysis of cell–cell communication from one dataset and identification of altered intercellular communication, signals and cell populations from different datasets across biological conditions. The R implementation of CellChat v2 toolkit and its tutorials together with the graphic outputs are available at https://github.com/jinworks/CellChat . This protocol typically takes ~5 min depending on dataset size and requires a basic understanding of R and single-cell data analysis but no specialized bioinformatics training for its implementation. CellChat enables systematic inference, quantitative analysis and intuitive visualization of cell–cell communication from single-cell transcriptomic data, as well as comparative analysis of intercellular communication across biological conditions.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":"20 1","pages":"180-219"},"PeriodicalIF":13.1,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142269498","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":"Facile photopatterning of perfusable microchannels in hydrogels for microphysiological systems","authors":"Ana Mora-Boza,&nbsp;Adriana Mulero-Russe,&nbsp;Nikolas Di Caprio,&nbsp;Jason A. Burdick,&nbsp;Eric O’Neill,&nbsp;Ankur Singh,&nbsp;Andrés J. García","doi":"10.1038/s41596-024-01041-8","DOIUrl":"10.1038/s41596-024-01041-8","url":null,"abstract":"Perfusable hydrogels have garnered substantial attention in recent years for the fabrication of microphysiological systems. However, current methodologies to fabricate microchannels in hydrogel platforms involve sophisticated equipment and techniques, which hinder progress of the field. In this protocol, we present a cost-effective, simple, versatile and ultrafast method to create perfusable microchannels of complex shapes in photopolymerizable hydrogels. Our method uses one-step UV photocross-linking and a photomask printed on inexpensive transparent films, to photopattern both synthetic (PEG-norbornene) and natural (hyaluronic acid-norbornene) hydrogels in just 0.8 s. Moreover, these perfusable hydrogels are fully integrated into a custom-made microfluidic device that allows continuous fluid perfusion when connected to an external pump system. This methodology can be easily reproduced by professionals with basic laboratory skills and a fundamental knowledge of polymers and materials science. In this protocol, we demonstrate the functionality of our photopatterned hydrogels by seeding human endothelial cells into the microchannels, culturing them under dynamic conditions for 7 d, and exposing them to inflammatory stimuli to elicit cellular responses. This highlights the versatility of our platform in fabricating microphysiological systems and different microenvironments. The fabrication of perfusable channels within the hydrogels, including the fabrication of the microfluidic devices, requires ~3 d. The development of the cell-seeded microphysiological system, including the stimulation of cells, takes ~7 d. In conclusion, our approach provides a straightforward and widely applicable solution to simplify and reduce the cost of biofabrication techniques for developing functional in vitro models using perfusable three-dimensional hydrogels. A cost-effective, facile, versatile and ultrafast methodology to fabricate perfusable microchannels of complex shapes in photopolymerizable hydrogels without the need for specialized equipment or sophisticated protocols.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":"20 1","pages":"272-292"},"PeriodicalIF":13.1,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142176229","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":"Assembly of a stem cell-derived human postimplantation embryo model","authors":"Carlos W. Gantner,&nbsp;Bailey A. T. Weatherbee,&nbsp;Yuntao Wang,&nbsp;Magdalena Zernicka-Goetz","doi":"10.1038/s41596-024-01042-7","DOIUrl":"10.1038/s41596-024-01042-7","url":null,"abstract":"The embryonic and extraembryonic tissue interactions underlying human embryogenesis at implantation stages are not currently understood. We have generated a pluripotent stem cell-derived model that mimics aspects of peri-implantation development, allowing tractable experimentation otherwise impossible in the human embryo. Activation of the extraembryonic lineage-specific transcription factors GATA6 and SOX17 (hypoblast factors) or GATA3 and TFAP2C (encoding AP2γ; trophoblast factors) in human embryonic stem (ES) cells drive conversion to extraembryonic-like cells. When combined with wild-type ES cells, self-organized embryo-like structures form in the absence of exogenous factors, termed human inducible embryoids (hiEmbryoids). The epiblast-like domain of hiEmbryoids polarizes and differentiates in response to extraembryonic-secreted extracellular matrix and morphogen cues. Extraembryonic mesenchyme, amnion and primordial germ cells are specified in hiEmbryoids in a stepwise fashion. After establishing stable inducible ES lines and converting ES cells to RSeT culture media, the protocol takes 7–10 d to generate hiEmbryoids. Generation of hiEmbryoids can be performed by researchers with basic expertise in stem cell culture. Protocol for the generation of a stem cell-derived human postimplantation embryo model by the combination of embryonic and transgene-induced extraembryonic-like cells.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":"20 1","pages":"67-91"},"PeriodicalIF":13.1,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142176228","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":"Precise tracking of nanoparticles in plant roots","authors":"Xiao-Dong Sun,&nbsp;Jing-Ya Ma,&nbsp;Li-Juan Feng,&nbsp;Jian-Lu Duan,&nbsp;Xian-Zheng Yuan","doi":"10.1038/s41596-024-01044-5","DOIUrl":"10.1038/s41596-024-01044-5","url":null,"abstract":"One of the foremost challenges in nanobiotechnology is obtaining direct evidence of nanoparticles’ absorption and internalization in plants. Although confocal laser scanning microscopy (CLSM) or transmission electron microscopy (TEM) are currently the most commonly used tools to characterize nanoparticles in plants, subjectivity of researchers, incorrect sample handling, inevitable fluorescence leakage and limitations of imaging instruments lead to false positives and non-reproducibility of experimental results. This protocol provides an easy-to-operate dual-step method, combining CLSM for macroscopic tissue examination and TEM for cellular-level analysis, to effectively trace single particles in plant roots with accuracy and precision. In addition, we also provide detailed methods for processing plant materials before imaging, including cleaning, and staining, to maximize the accuracy and reliability of imaging. This protocol involves currently commonly used nanomaterial types, such as metal-based and doped carbon-based materials, and enables accurate localization of nanoparticles with different sizes at the cell level in Arabidopsis thaliana root samples either through contrast or element mapping analysis. It serves as a valuable reference and benchmark for scholars in plant science, chemistry and environmental studies to understand the interaction between plant roots and nanomaterials and to detect the distribution of nanomaterials in plants. Excluding plant culture time, the protocol can be completed in 4–5 d. This protocol for the precise tracking of nanoparticles in plant roots uses CLSM for macroscopic tissue examination and TEM for cellular-level analysis and provides methodologies for preparing plant materials before imaging.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":"20 1","pages":"248-271"},"PeriodicalIF":13.1,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142140587","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":"Mapping protein–DNA interactions with DiMeLo-seq","authors":"Annie Maslan,&nbsp;Nicolas Altemose,&nbsp;Jeremy Marcus,&nbsp;Reet Mishra,&nbsp;Lucy D. Brennan,&nbsp;Kousik Sundararajan,&nbsp;Gary Karpen,&nbsp;Aaron F. Straight,&nbsp;Aaron Streets","doi":"10.1038/s41596-024-01032-9","DOIUrl":"10.1038/s41596-024-01032-9","url":null,"abstract":"We recently developed directed methylation with long-read sequencing (DiMeLo-seq) to map protein–DNA interactions genome wide. DiMeLo-seq is capable of mapping multiple interaction sites on single DNA molecules, profiling protein binding in the context of endogenous DNA methylation, identifying haplotype-specific protein–DNA interactions and mapping protein–DNA interactions in repetitive regions of the genome that are difficult to study with short-read methods. With DiMeLo-seq, adenines in the vicinity of a protein of interest are methylated in situ by tethering the Hia5 methyltransferase to an antibody using protein A. Protein–DNA interactions are then detected by direct readout of adenine methylation with long-read, single-molecule DNA sequencing platforms such as Nanopore sequencing. Here we present a detailed protocol and practical guidance for performing DiMeLo-seq. This protocol can be run on nuclei from fresh, lightly fixed or frozen cells. The protocol requires 1–2 d for performing in situ targeted methylation, 1–5 d for library preparation depending on desired fragment length and 1–3 d for Nanopore sequencing depending on desired sequencing depth. The protocol requires basic molecular biology skills and equipment, as well as access to a Nanopore sequencer. We also provide a Python package, dimelo, for analysis of DiMeLo-seq data. DiMeLo-seq uses long-read, single-molecule sequencing to map protein–DNA interactions genome wide. This allows mapping of multiple interaction sites on single DNA molecules and profiling protein binding in the context of endogenous DNA methylation.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":"19 12","pages":"3697-3720"},"PeriodicalIF":13.1,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142140586","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":"Construction and utilization of a new generation of bacteriophage-based particles, or TPA, for guided systemic delivery of nucleic acids to tumors.","authors":"Lauren Gay, Keittisak Suwan, Amin Hajitou","doi":"10.1038/s41596-024-01040-9","DOIUrl":"https://doi.org/10.1038/s41596-024-01040-9","url":null,"abstract":"<p><p>Successful delivery of nucleic acid therapeutics to diseased sites would present a pivotal advancement in cancer treatment. However, progress has been hindered by the lack of efficient tumor-selective vectors via clinical systemic routes, the blood-brain barrier for brain tumors and problems with repeated administrations. We present a new generation of M13 phage-based vectors termed transmorphic phage/adeno-associated virus (AAV) (TPA), wherein the phage genome has been excised to facilitate exclusive packaging of human AAV DNA by phage coat proteins. Here we provide a detailed protocol for the molecular cloning of DNA into the TPA construct, display of disease-specific ligands on the helper phage capsid for cell targeting and entry, and packaging of TPA DNA by helper phage coat proteins in a bacterial host. Furthermore, we provide methods for mammalian cell transduction and assessment of transgene expression in vitro as well as in vivo application of TPA particles in tumor-bearing mice. Unlike other similar methods, our protocol enables high-yield production and control of helper phage quantity in TPA preparations. Moreover, compared with existing M13 phage vectors, TPA particles can accommodate large size transgene inserts, despite being considerably more compact, providing superior gene delivery through enhanced diffusion across the extracellular matrix, improved cellular binding and entry and increased vector DNA accumulation in the nucleus. The protocol encompasses a timeline of 4-5 months, including construction and production of TPA particles with transgene and targeted ligand and in vitro/in vivo testing. This protocol can be conducted by researchers trained in basic molecular biology/bacteriology research techniques.</p>","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":" ","pages":""},"PeriodicalIF":13.1,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142140585","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}