Nature Methods最新文献_第5页

Precision control of cellular functions with a temperature-sensitive protein

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-01-23 DOI: 10.1038/s41592-024-02573-3

引用次数: 0

A temperature-inducible protein module for control of mammalian cell fate

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-01-23 DOI: 10.1038/s41592-024-02572-4

William Benman, Zikang Huang, Pavan Iyengar, Delaney Wilde, Thomas R. Mumford, Lukasz J. Bugaj

{"title":"A temperature-inducible protein module for control of mammalian cell fate","authors":"William Benman, Zikang Huang, Pavan Iyengar, Delaney Wilde, Thomas R. Mumford, Lukasz J. Bugaj","doi":"10.1038/s41592-024-02572-4","DOIUrl":"10.1038/s41592-024-02572-4","url":null,"abstract":"Inducible protein switches are currently limited for use in tissues and organisms because common inducers cannot be controlled with precision in space and time in optically dense settings. Here, we introduce a protein that can be reversibly toggled with a small change in temperature, a stimulus that is both penetrant and dynamic. This protein, called Melt (Membrane localization using temperature) oligomerizes and translocates to the plasma membrane when temperature is lowered. We generated a library of Melt variants with switching temperatures ranging from 30 °C to 40 °C, including two that operate at and above 37 °C. Melt was a highly modular actuator of cell function, permitting thermal control over diverse processes including signaling, proteolysis, nuclear shuttling, cytoskeletal rearrangements and cell death. Finally, Melt permitted thermal control of cell death in a mouse model of human cancer. Melt represents a versatile thermogenetic module for straightforward, non-invasive and spatiotemporally defined control of mammalian cells with broad potential for biotechnology and biomedicine. The Melt (Membrane localization using temperature) protein translocates to the plasma membrane upon temperature shift. Melt variants with a range of switching temperatures enable straightforward thermogenetic control of diverse cellular processes.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":"22 3","pages":"539-549"},"PeriodicalIF":36.1,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143029206","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: Arkitekt: streaming analysis and real-time workflows for microscopy 作者更正：Arkitekt：流式分析和实时工作流程的显微镜。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-01-21 DOI: 10.1038/s41592-025-02597-3

Johannes Roos, Stéphane Bancelin, Tom Delaire, Alexander Wilhelmi, Florian Levet, Maren Engelhardt, Virgile Viasnoff, Rémi Galland, U. Valentin Nägerl, Jean-Baptiste Sibarita

引用次数: 0

UDA-seq: universal droplet microfluidics-based combinatorial indexing for massive-scale multimodal single-cell sequencing. UDA-seq：用于大规模多模态单细胞测序的通用微流控组合索引。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-01-20 DOI: 10.1038/s41592-024-02586-y

Yun Li, Zheng Huang, Lubin Xu, Yanling Fan, Jun Ping, Guochao Li, Yanjie Chen, Chengwei Yu, Qifei Wang, Turun Song, Tao Lin, Mengmeng Liu, Yangqing Xu, Na Ai, Xini Meng, Qin Qiao, Hongbin Ji, Zhen Qin, Shuo Jin, Nan Jiang, Minxian Wang, Shaokun Shu, Feng Zhang, Weiqi Zhang, Guang-Hui Liu, Limeng Chen, Lan Jiang

{"title":"UDA-seq: universal droplet microfluidics-based combinatorial indexing for massive-scale multimodal single-cell sequencing.","authors":"Yun Li, Zheng Huang, Lubin Xu, Yanling Fan, Jun Ping, Guochao Li, Yanjie Chen, Chengwei Yu, Qifei Wang, Turun Song, Tao Lin, Mengmeng Liu, Yangqing Xu, Na Ai, Xini Meng, Qin Qiao, Hongbin Ji, Zhen Qin, Shuo Jin, Nan Jiang, Minxian Wang, Shaokun Shu, Feng Zhang, Weiqi Zhang, Guang-Hui Liu, Limeng Chen, Lan Jiang","doi":"10.1038/s41592-024-02586-y","DOIUrl":"https://doi.org/10.1038/s41592-024-02586-y","url":null,"abstract":"The use of single-cell combinatorial indexing sequencing via droplet microfluidics presents an attractive approach for balancing cost, scalability, robustness and accessibility. However, existing methods often require tailored protocols for individual modalities, limiting their automation potential and clinical applicability. To address this, we introduce UDA-seq, a universal workflow that integrates a post-indexing step to enhance throughput and systematically adapt existing droplet-based single-cell multimodal methods. UDA-seq was benchmarked across various tissue and cell types, enabling several common multimodal analyses, including single-cell co-assay of RNA and VDJ, RNA and chromatin, and RNA and CRISPR perturbation. Notably, UDA-seq facilitated the efficient generation of over 100,000 high-quality single-cell datasets from three dozen frozen clinical biopsy specimens within a single-channel droplet microfluidics experiment. Downstream analysis demonstrated the robustness of this approach in identifying rare cell subpopulations associated with clinical phenotypes and exploring the vulnerability of cancer cells.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":" ","pages":""},"PeriodicalIF":36.1,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143008736","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

Capture of membrane proteins in their native membrane milieu 膜蛋白在其原生膜环境中的捕获。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-01-20 DOI: 10.1038/s41592-024-02518-w

引用次数: 0

Author Correction: Large-scale benchmarking of circRNA detection tools reveals large differences in sensitivity but not in precision 作者更正：circRNA检测工具的大规模基准测试显示灵敏度差异很大，但精度差异不大。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-01-17 DOI: 10.1038/s41592-024-02569-z

Marieke Vromman, Jasper Anckaert, Stefania Bortoluzzi, Alessia Buratin, Chia-Ying Chen, Qinjie Chu, Trees-Juen Chuang, Roozbeh Dehghannasiri, Christoph Dieterich, Xin Dong, Paul Flicek, Enrico Gaffo, Wanjun Gu, Chunjiang He, Steve Hoffmann, Osagie Izuogu, Michael S. Jackson, Tobias Jakobi, Eric C. Lai, Justine Nuytens, Julia Salzman, Mauro Santibanez-Koref, Peter Stadler, Olivier Thas, Eveline Vanden Eynde, Kimberly Verniers, Guoxia Wen, Jakub Westholm, Li Yang, Chu-Yu Ye, Nurten Yigit, Guo-Hua Yuan, Jinyang Zhang, Fangqing Zhao, Jo Vandesompele, Pieter-Jan Volders

引用次数: 0

Challenging the Astral mass analyzer to quantify up to 5,300 proteins per single cell at unseen accuracy to uncover cellular heterogeneity 挑战Astral质谱分析仪，以前所未有的精度量化每个单细胞多达5300个蛋白质，以揭示细胞异质性。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-01-16 DOI: 10.1038/s41592-024-02559-1

Julia A. Bubis, Tabiwang N. Arrey, Eugen Damoc, Bernard Delanghe, Jana Slovakova, Theresa M. Sommer, Harunobu Kagawa, Peter Pichler, Nicolas Rivron, Karl Mechtler, Manuel Matzinger

{"title":"Challenging the Astral mass analyzer to quantify up to 5,300 proteins per single cell at unseen accuracy to uncover cellular heterogeneity","authors":"Julia A. Bubis, Tabiwang N. Arrey, Eugen Damoc, Bernard Delanghe, Jana Slovakova, Theresa M. Sommer, Harunobu Kagawa, Peter Pichler, Nicolas Rivron, Karl Mechtler, Manuel Matzinger","doi":"10.1038/s41592-024-02559-1","DOIUrl":"10.1038/s41592-024-02559-1","url":null,"abstract":"Despite significant advancements in sample preparation, instrumentation and data analysis, single-cell proteomics is currently limited by proteomic depth and quantitative performance. Here we demonstrate highly improved depth of proteome coverage as well as accuracy and precision for quantification of ultra-low input amounts. Using a tailored library, we identify up to 7,400 protein groups from as little as 250 pg of HeLa cell peptides at a throughput of 50 samples per day. Using a two-proteome mix, we check for optimal parameters of quantification and show that fold change differences of 2 can still be successfully determined at single-cell-level inputs. Eventually, we apply our workflow to A549 cells, yielding a proteome coverage ranging from 1,801 to a maximum of >5,300 protein groups from a single cell depending on cell size and search strategy used, which allows for the study of dependencies between cell size and cell cycle phase. Additionally, our workflow enables us to distinguish between in vitro analogs of two human blastocyst lineages: naive human pluripotent stem cells (epiblast) and trophectoderm-like cells. Our data harmoniously align with transcriptomic data, indicating that single-cell proteomics possesses the capability to identify biologically relevant differences within the blastocyst. An ultra-low-input single-cell proteomic workflow is optimized to yield maximum proteome coverage with high accuracy and precision on the Orbitrap Astral mass spectrometer.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":"22 3","pages":"510-519"},"PeriodicalIF":36.1,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41592-024-02559-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143008095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhanced sensitivity and scalability with a Chip-Tip workflow enables deep single-cell proteomics Chip-Tip工作流程增强了灵敏度和可扩展性，可实现深度单细胞蛋白质组学。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-01-16 DOI: 10.1038/s41592-024-02558-2

Zilu Ye, Pierre Sabatier, Leander van der Hoeven, Maico Y. Lechner, Teeradon Phlairaharn, Ulises H. Guzman, Zhen Liu, Haoran Huang, Min Huang, Xiangjun Li, David Hartlmayr, Fabiana Izaguirre, Anjali Seth, Hiren J. Joshi, Sergey Rodin, Karl-Henrik Grinnemo, Ole B. Hørning, Dorte B. Bekker-Jensen, Nicolai Bache, Jesper V. Olsen

{"title":"Enhanced sensitivity and scalability with a Chip-Tip workflow enables deep single-cell proteomics","authors":"Zilu Ye, Pierre Sabatier, Leander van der Hoeven, Maico Y. Lechner, Teeradon Phlairaharn, Ulises H. Guzman, Zhen Liu, Haoran Huang, Min Huang, Xiangjun Li, David Hartlmayr, Fabiana Izaguirre, Anjali Seth, Hiren J. Joshi, Sergey Rodin, Karl-Henrik Grinnemo, Ole B. Hørning, Dorte B. Bekker-Jensen, Nicolai Bache, Jesper V. Olsen","doi":"10.1038/s41592-024-02558-2","DOIUrl":"10.1038/s41592-024-02558-2","url":null,"abstract":"Single-cell proteomics (SCP) promises to revolutionize biomedicine by providing an unparalleled view of the proteome in individual cells. Here, we present a high-sensitivity SCP workflow named Chip-Tip, identifying >5,000 proteins in individual HeLa cells. It also facilitated direct detection of post-translational modifications in single cells, making the need for specific post-translational modification-enrichment unnecessary. Our study demonstrates the feasibility of processing up to 120 label-free SCP samples per day. An optimized tissue dissociation buffer enabled effective single-cell disaggregation of drug-treated cancer cell spheroids, refining overall SCP analysis. Analyzing nondirected human-induced pluripotent stem cell differentiation, we consistently quantified stem cell markers OCT4 and SOX2 in human-induced pluripotent stem cells and lineage markers such as GATA4 (endoderm), HAND1 (mesoderm) and MAP2 (ectoderm) in different embryoid body cells. Our workflow sets a benchmark in SCP for sensitivity and throughput, with broad applications in basic biology and biomedicine for identification of cell type-specific markers and therapeutic targets. Chip-Tip is a label-free quantification-based single-cell proteomics workflow for deep single-cell proteomics, which identifies over 5,000 proteins and 40,000 peptides in single HeLa cells.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":"22 3","pages":"499-509"},"PeriodicalIF":36.1,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41592-024-02558-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143008452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

High-resolution, noninvasive single-cell lineage tracing in mice and humans based on DNA methylation epimutations 基于DNA甲基化模拟的小鼠和人类的高分辨率、无创单细胞谱系追踪。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-01-16 DOI: 10.1038/s41592-024-02567-1

Mengyang Chen, Ruijiang Fu, Yiqian Chen, Li Li, Shou-Wen Wang

{"title":"High-resolution, noninvasive single-cell lineage tracing in mice and humans based on DNA methylation epimutations","authors":"Mengyang Chen, Ruijiang Fu, Yiqian Chen, Li Li, Shou-Wen Wang","doi":"10.1038/s41592-024-02567-1","DOIUrl":"10.1038/s41592-024-02567-1","url":null,"abstract":"In vivo lineage tracing holds great potential to reveal fundamental principles of tissue development and homeostasis. However, current lineage tracing in humans relies on extremely rare somatic mutations, which has limited temporal resolution and lineage accuracy. Here, we developed a generic lineage-tracing tool based on frequent epimutations on DNA methylation, enabled by our computational method MethylTree. Using single-cell genome-wide DNA methylation datasets with known lineage and phenotypic labels, MethylTree reconstructed lineage histories at nearly 100% accuracy across different cell types, developmental stages, and species. We demonstrated the epimutation-based single-cell multi-omic lineage tracing in mouse and human blood, where MethylTree recapitulated the differentiation hierarchy in hematopoiesis. Applying MethylTree to human embryos, we revealed early fate commitment at the four-cell stage. In native mouse blood, we identified ~250 clones of hematopoietic stem cells. MethylTree opens the door for high-resolution, noninvasive and multi-omic lineage tracing in humans and beyond. This work presents a computational tool MethylTree to infer cell lineages based on epimutations on DNA methylation.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":"22 3","pages":"488-498"},"PeriodicalIF":36.1,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143008497","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

Label-free nanoscopy of cell metabolism by ultrasensitive reweighted visible stimulated Raman scattering. 利用超灵敏重加权可见受激拉曼散射技术进行细胞代谢的无标记纳米观察。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-01-16 DOI: 10.1038/s41592-024-02575-1

Haonan Lin, Scott Seitz, Yuying Tan, Jean-Baptiste Lugagne, Le Wang, Guangrui Ding, Hongjian He, Tyler J Rauwolf, Mary J Dunlop, John H Connor, John A Porco, Lei Tian, Ji-Xin Cheng

{"title":"Label-free nanoscopy of cell metabolism by ultrasensitive reweighted visible stimulated Raman scattering.","authors":"Haonan Lin, Scott Seitz, Yuying Tan, Jean-Baptiste Lugagne, Le Wang, Guangrui Ding, Hongjian He, Tyler J Rauwolf, Mary J Dunlop, John H Connor, John A Porco, Lei Tian, Ji-Xin Cheng","doi":"10.1038/s41592-024-02575-1","DOIUrl":"10.1038/s41592-024-02575-1","url":null,"abstract":"Super-resolution imaging of cell metabolism is hindered by the incompatibility of small metabolites with fluorescent dyes and the limited resolution of imaging mass spectrometry. We present ultrasensitive reweighted visible stimulated Raman scattering (URV-SRS), a label-free vibrational imaging technique for multiplexed nanoscopy of intracellular metabolites. We developed a visible SRS microscope with extensive pulse chirping to improve the detection limit to ~4,000 molecules and introduced a self-supervised multi-agent denoiser to suppress non-independent noise in SRS by over 7.2 dB, resulting in a 50-fold sensitivity enhancement over near-infrared SRS. Leveraging the enhanced sensitivity, we employed Fourier reweighting to amplify sub-100-nm spatial frequencies that were previously overwhelmed by noise. Validated by Fourier ring correlation, we achieved a lateral resolution of 86 nm in cell imaging. We visualized the reprogramming of metabolic nanostructures associated with virus replication in host cells and subcellular fatty acid synthesis in engineered bacteria, demonstrating its capability towards nanoscopic spatial metabolomics.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":" ","pages":""},"PeriodicalIF":36.1,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143008708","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