Nature Protocols最新文献_第8页

Quantitative molecular imaging using deep magnetic resonance fingerprinting. 定量分子成像使用深层磁共振指纹。

IF 13.1 1区生物学

Nature Protocols Pub Date : 2025-04-01 DOI: 10.1038/s41596-025-01152-w

Nikita Vladimirov, Ouri Cohen, Hye-Young Heo, Moritz Zaiss, Christian T Farrar, Or Perlman

{"title":"Quantitative molecular imaging using deep magnetic resonance fingerprinting.","authors":"Nikita Vladimirov, Ouri Cohen, Hye-Young Heo, Moritz Zaiss, Christian T Farrar, Or Perlman","doi":"10.1038/s41596-025-01152-w","DOIUrl":"https://doi.org/10.1038/s41596-025-01152-w","url":null,"abstract":"Deep learning-based saturation transfer magnetic resonance fingerprinting (MRF) is an emerging approach for noninvasive in vivo imaging of proteins, metabolites and pH. It involves a series of steps, including sample/participant preparation, image acquisition schedule design, biophysical model formulation and artificial intelligence and computational model training, followed by image acquisition, deep reconstruction and analysis. Saturation transfer-based molecular MRI has been slow to reach clinical maturity and adoption for clinical practice due to its technical complexity, semi-quantitative contrast-weighted nature and long scan times needed for the extraction of quantitative molecular biomarkers. Deep MRF provides solutions to these challenges by providing a quantitative and rapid framework for extracting biologically and clinically meaningful molecular information. Here we define a complete protocol for quantitative molecular MRI using deep MRF. We describe in vitro sample preparation and animal and human scan considerations, and provide intuition behind the acquisition protocol design and optimization of chemical exchange saturation transfer (CEST) and semi-solid magnetization transfer (MT) quantitative imaging. We then extensively describe the building blocks for several artificial intelligence models and demonstrate their performance for different applications, including cancer monitoring, brain myelin imaging and pH quantification. Finally, we provide guidelines to further modify and expand the pipeline for imaging a variety of other pathologies (such as neurodegeneration, stroke and cardiac disease), accompanied by the related open-source code and sample data. The procedure takes between 48 min (for two proton pools or in vitro imaging) and 57 h (for complex multi-proton pool in vivo imaging) to complete and is suitable for graduate student-level users.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":" ","pages":""},"PeriodicalIF":13.1,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143764458","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}

引用次数: 0

Author Correction: Life-long functional regeneration of in vivo airway epithelium by the engraftment of airway basal stem cells. 作者更正：通过植入气道基底干细胞实现气道上皮的终身功能性再生。

IF 13.1 1区生物学

Nature Protocols Pub Date : 2025-03-31 DOI: 10.1038/s41596-025-01180-6

Liang Ma, Bibek R Thapa, Jake A Le Suer, Andrew Tilston-Lünel, Michael J Herriges, Feiya Wang, Pushpinder S Bawa, Xaralabos Varelas, Finn J Hawkins, Darrell N Kotton

引用次数: 0

Correlative light and electron microscopy for human brain and other biological models. 相关光学和电子显微镜用于人脑和其他生物模型。

IF 13.1 1区生物学

Nature Protocols Pub Date : 2025-03-31 DOI: 10.1038/s41596-025-01153-9

Notash Shafiei, Daniel Stӓhli, Domenic Burger, Marta Di Fabrizio, Lukas van den Heuvel, Jean Daraspe, Carolin Böing, Sarah H Shahmoradian, Wilma D J van de Berg, Christel Genoud, Henning Stahlberg, Amanda J Lewis

{"title":"Correlative light and electron microscopy for human brain and other biological models.","authors":"Notash Shafiei, Daniel Stӓhli, Domenic Burger, Marta Di Fabrizio, Lukas van den Heuvel, Jean Daraspe, Carolin Böing, Sarah H Shahmoradian, Wilma D J van de Berg, Christel Genoud, Henning Stahlberg, Amanda J Lewis","doi":"10.1038/s41596-025-01153-9","DOIUrl":"https://doi.org/10.1038/s41596-025-01153-9","url":null,"abstract":"Correlative light and electron microscopy (CLEM) combines light microscopy, for identifying a target via genetic labels, dyes, antibodies and morphological features, with electron microscopy, for analyzing high-resolution subcellular ultrastructures. Here, we describe step-by-step instructions to perform a CLEM experiment, optimized for the investigation of ultrastructural features in human brain tissue. The procedure is carried out at room temperature and can be adapted to other human and animal tissue samples. The procedure requires 8 d to complete and includes the stages of sample fixation for optimal ultrastructural preservation, immunofluorescence staining, image acquisition and multimodal image correlation and is executable within standard electron microscopy laboratories. Serving as a critical tool for characterizing human tissue and disease models, room-temperature CLEM facilitates the identification and quantification of subcellular morphological features across brain regions.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":" ","pages":""},"PeriodicalIF":13.1,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143753622","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}

引用次数: 0

Tutorial: guidelines for quality filtering of whole-exome and whole-genome sequencing data for population-scale association analyses. 教程：用于群体规模关联分析的全外显子组和全基因组测序数据的质量过滤指南。

IF 13.1 1区生物学

Nature Protocols Pub Date : 2025-03-28 DOI: 10.1038/s41596-025-01169-1

Julia M Sealock, Franjo Ivankovic, Calwing Liao, Siwei Chen, Claire Churchhouse, Konrad J Karczewski, Daniel P Howrigan, Benjamin M Neale

{"title":"Tutorial: guidelines for quality filtering of whole-exome and whole-genome sequencing data for population-scale association analyses.","authors":"Julia M Sealock, Franjo Ivankovic, Calwing Liao, Siwei Chen, Claire Churchhouse, Konrad J Karczewski, Daniel P Howrigan, Benjamin M Neale","doi":"10.1038/s41596-025-01169-1","DOIUrl":"https://doi.org/10.1038/s41596-025-01169-1","url":null,"abstract":"Genetic sequencing technologies are powerful tools for identifying rare variants and genes associated with Mendelian and complex traits; indeed, whole-exome and whole-genome sequencing are increasingly popular methods for population-scale genetic studies. However, careful quality control steps should be taken to ensure study accuracy and reproducibility, and sequencing data require extensive quality filtering to delineate true variants from technical artifacts. Although processing standards are harmonized across pipelines to call variants from sequencing reads, there currently exists no standardized pipeline for conducting quality filtering on variant-level datasets for the purpose of population-scale association analysis. In this Tutorial, we discuss key quality control parameters, provide guidelines for conducting quality filtering of samples and variants, and compare commonly used software programs for quality control of samples, variants and genotypes from sequencing data. As sequencing data continue to gain popularity in genetic research, establishing standardized quality control practices is crucial to ensure consistent, reliable and reproducible results across studies.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":" ","pages":""},"PeriodicalIF":13.1,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143742928","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}

引用次数: 0

Cyborg organoids integrated with stretchable nanoelectronics can be functionally mapped during development. 集成了可拉伸纳米电子学的半机械人类器官可以在开发过程中进行功能映射。

IF 13.1 1区生物学

Nature Protocols Pub Date : 2025-03-26 DOI: 10.1038/s41596-025-01147-7

Zuwan Lin, Wenbo Wang, Ren Liu, Qiang Li, Jaeyong Lee, Charles Hirschler, Jia Liu

{"title":"Cyborg organoids integrated with stretchable nanoelectronics can be functionally mapped during development.","authors":"Zuwan Lin, Wenbo Wang, Ren Liu, Qiang Li, Jaeyong Lee, Charles Hirschler, Jia Liu","doi":"10.1038/s41596-025-01147-7","DOIUrl":"10.1038/s41596-025-01147-7","url":null,"abstract":"Organoids are in vitro miniaturized cellular models of organs that offer opportunities for studying organ development, disease mechanisms and drug screening. Understanding the complex processes governing organoid development and function requires methods suitable for the continuous, long-term monitoring of cell activities (for example, electrophysiological and mechanical activity) at single-cell resolution throughout the entire three-dimensional (3D) structure. Cyborg organoid technology addresses this need by seamlessly integrating stretchable mesh nanoelectronics with tissue-like properties, such as tissue-level flexibility, subcellular feature size and mesh-like networks, into 3D organoids through a 2D-to-3D tissue reconfiguration process during organogenesis. This approach enables longitudinal, tissue-wide, single-cell functional mapping, thereby overcoming the limitations of existing techniques including recording duration, spatial coverage, and the ability to maintain stable contact with the tissue during organoid development. This protocol describes the fabrication and characterization of stretchable mesh nanoelectronics, their electrical performance, their integration with organoids and the acquisition of long-term functional organoid activity requiring multimodal data analysis techniques. Cyborg organoid technology represents a transformative tool for investigating organoid development and function, with potential for improving in vitro disease models, drug screening and personalized medicine. The procedure is suitable for users within a multidisciplinary team with expertise in stem cell biology, tissue engineering, nanoelectronics fabrication, electrophysiology and data science.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":" ","pages":""},"PeriodicalIF":13.1,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143720178","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}

引用次数: 0

A detailed guide to assessing genome assembly based on long-read sequencing data using Inspector. 一个详细的指南评估基因组组装基于长读测序数据使用检查员。

IF 13.1 1区生物学

Nature Protocols Pub Date : 2025-03-26 DOI: 10.1038/s41596-025-01149-5

Yan Guo, Yuwei Song, Limin Jiang, Yu Chen, Michele Ceccarelli, Min Gao, Zechen Chong

{"title":"A detailed guide to assessing genome assembly based on long-read sequencing data using Inspector.","authors":"Yan Guo, Yuwei Song, Limin Jiang, Yu Chen, Michele Ceccarelli, Min Gao, Zechen Chong","doi":"10.1038/s41596-025-01149-5","DOIUrl":"10.1038/s41596-025-01149-5","url":null,"abstract":"Long-read sequencing technologies yield extended DNA sequences capable of spanning intricate, repetitive genome regions, thereby facilitating the generation of more precise and comprehensive genome assemblies. However, assembly errors are inevitable owing to inherent genomic complexity and limitations of sequencing technology and assembly algorithms, making assembly evaluation crucial. The genome assembly evaluation tool Inspector presents several advantages over existing long-read de novo assembly evaluation tools, including (1) both reference-free and reference-guided assembly evaluation; (2) the ability to detect both small- and large-scale structural errors; (3) the option of assembly error correction, which can improve the quality value of the original assembly; and (4) the ability to perform haplotype-resolved assembly evaluation. Inspector can provide not only basic contig and alignment statistics, but also the precise locations and types of the different structural errors. These advantages provide a robust framework for long-read assembly evaluation. In this Protocol, we showcase four procedures to demonstrate the different applications of Inspector for long-read assembly evaluation. Inspector software and additional guides can be found at https://github.com/ChongLab/Inspector_protocol .","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":" ","pages":""},"PeriodicalIF":13.1,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143720173","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}

引用次数: 0

CellPhoneDB v5: inferring cell-cell communication from single-cell multiomics data. CellPhoneDB v5：从单细胞多组学数据推断细胞-细胞通信。

IF 13.1 1区生物学

Nature Protocols Pub Date : 2025-03-25 DOI: 10.1038/s41596-024-01137-1

Kevin Troulé, Robert Petryszak, Batuhan Cakir, James Cranley, Alicia Harasty, Martin Prete, Zewen Kelvin Tuong, Sarah A Teichmann, Luz Garcia-Alonso, Roser Vento-Tormo

{"title":"CellPhoneDB v5: inferring cell-cell communication from single-cell multiomics data.","authors":"Kevin Troulé, Robert Petryszak, Batuhan Cakir, James Cranley, Alicia Harasty, Martin Prete, Zewen Kelvin Tuong, Sarah A Teichmann, Luz Garcia-Alonso, Roser Vento-Tormo","doi":"10.1038/s41596-024-01137-1","DOIUrl":"10.1038/s41596-024-01137-1","url":null,"abstract":"Cell-cell communication is essential for tissue development, function and regeneration. The revolution of single-cell genomics technologies offers an unprecedented opportunity to uncover how cells communicate in vivo within their tissue niches and how disruption of these niches can lead to diseases and developmental abnormalities. CellPhoneDB is a bioinformatics toolkit designed to infer cell-cell communication by combining a curated repository of bona fide ligand-receptor interactions with methods to integrate these interactions with single-cell genomics data. Here we present a protocol for the latest version of CellPhoneDB (v5), offering several new features. First, the repository has been expanded by one-third with the addition of new interactions, including ~1,000 interactions mediated by nonpeptidic ligands such as steroidogenic hormones, neurotransmitters and small G-protein-coupled receptor (GPCR)-binding ligands. Second, we outline a new way of using the database that allows users to tailor queries to their experimental designs. Third, the update incorporates novel strategies to prioritize specific cell-cell interactions, leveraging information from other modalities such as tissue microenvironments derived from spatial transcriptomics technologies or transcription factor activities derived from a single-cell assay for transposase accessible chromatin assays. Finally, we describe the new CellPhoneDBViz module to interactively visualize and share results. Altogether, CellPhoneDB v5 enhances the precision of cell-cell communication inference, offering new insights into tissue biology in physiological microenvironments. This protocol typically takes ~15 min and requires basic knowledge of python.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":" ","pages":""},"PeriodicalIF":13.1,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143710776","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}

引用次数: 0

Advancing cell-cell communication analysis from single-cell genomics data. 从单细胞基因组学数据推进细胞-细胞通讯分析。

IF 13.1 1区生物学

Nature Protocols Pub Date : 2025-03-25 DOI: 10.1038/s41596-025-01140-0

Iguaracy Pinheiro-de-Sousa, Evangelia Petsalaki

引用次数: 0

Gene expression and chromatin state mapped in space. 基因表达和染色质状态在空间上的映射。

IF 13.1 1区生物学

Nature Protocols Pub Date : 2025-03-21 DOI: 10.1038/s41596-025-01151-x

Enric Llorens-Bobadilla

引用次数: 0

Spatially resolved genome-wide joint profiling of epigenome and transcriptome with spatial-ATAC-RNA-seq and spatial-CUT&Tag-RNA-seq. 利用空间- atac - rna -seq和空间- cut - tag - rna -seq进行空间分辨的全基因组表观基因组和转录组联合分析。

IF 13.1 1区生物学

Nature Protocols Pub Date : 2025-03-21 DOI: 10.1038/s41596-025-01145-9

Haikuo Li, Shuozhen Bao, Negin Farzad, Xiaoyu Qin, Anthony A Fung, Di Zhang, Zhiliang Bai, Bo Tao, Rong Fan

{"title":"Spatially resolved genome-wide joint profiling of epigenome and transcriptome with spatial-ATAC-RNA-seq and spatial-CUT&Tag-RNA-seq.","authors":"Haikuo Li, Shuozhen Bao, Negin Farzad, Xiaoyu Qin, Anthony A Fung, Di Zhang, Zhiliang Bai, Bo Tao, Rong Fan","doi":"10.1038/s41596-025-01145-9","DOIUrl":"10.1038/s41596-025-01145-9","url":null,"abstract":"The epigenome of a cell is tightly correlated with gene transcription, which controls cell identity and diverse biological activities. Recent advances in spatial technologies have improved our understanding of tissue heterogeneity by analyzing transcriptomics or epigenomics with spatial information preserved, but have been mainly restricted to one molecular layer at a time. Here we present procedures for two spatially resolved sequencing methods, spatial-ATAC-RNA-seq and spatial-CUT&Tag-RNA-seq, that co-profile transcriptome and epigenome genome wide. In both methods, transcriptomic readouts are generated through tissue fixation, permeabilization and in situ reverse transcription. In spatial-ATAC-RNA-seq, Tn5 transposase is used to probe accessible chromatin, and in spatial-CUT&Tag-RNA-seq, the tissue is incubated with primary antibodies that target histone modifications, followed by Protein A-fused Tn5-induced tagmentation. Both methods leverage a microfluidic device that delivers two sets of oligonucleotide barcodes to generate a two-dimensional mosaic of tissue pixels at near single-cell resolution. A spatial-ATAC-RNA-seq or spatial-CUT&Tag-RNA-seq library can be generated in 3-5 d, allowing researchers to simultaneously investigate the transcriptomic landscape and epigenomic landscape of an intact tissue section. This protocol is an extension of our previous spatially resolved epigenome sequencing protocol and provides opportunities in multimodal profiling.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":" ","pages":""},"PeriodicalIF":13.1,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143677154","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}

引用次数: 0