Nature Methods最新文献_第8页

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":"<p><p>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.</p>","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

MethylTree: exploring epimutations for accurate and non-invasive lineage tracing 甲基树：探索精确和非侵入性谱系追踪的epimations。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-01-16 DOI: 10.1038/s41592-024-02568-0

引用次数: 0

Living the life emerita/emeritus 过着退休的生活。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-01-15 DOI: 10.1038/s41592-024-02592-0

Vivien Marx

引用次数: 0

Super-photostable organic dye for long-term live-cell single-protein imaging 用于长期活细胞单蛋白成像的超光稳定有机染料。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-01-15 DOI: 10.1038/s41592-024-02584-0

Do-Hyeon Kim, Hong Minh Triet, Sun Hyeok Lee, Sina Jazani, Seongjae Jang, Syed Ali Abbas Abedi, Xiaogang Liu, Jongcheol Seo, Taekjip Ha, Young-Tae Chang, Sung Ho Ryu

{"title":"Super-photostable organic dye for long-term live-cell single-protein imaging","authors":"Do-Hyeon Kim, Hong Minh Triet, Sun Hyeok Lee, Sina Jazani, Seongjae Jang, Syed Ali Abbas Abedi, Xiaogang Liu, Jongcheol Seo, Taekjip Ha, Young-Tae Chang, Sung Ho Ryu","doi":"10.1038/s41592-024-02584-0","DOIUrl":"10.1038/s41592-024-02584-0","url":null,"abstract":"Organic dyes play a crucial role in live-cell imaging because of their advantageous properties, such as photostability and high brightness. Here we introduce a super-photostable and bright organic dye, Phoenix Fluor 555 (PF555), which exhibits an order-of-magnitude longer photobleaching lifetime than conventional organic dyes without the requirement of any anti-photobleaching additives. PF555 is an asymmetric cyanine structure in which, on one side, the indole in the conventional Cyanine-3 is substituted with 3-oxo-quinoline. PF555 provides a powerful tool for long-term live-cell single-molecule imaging, as demonstrated by the imaging of the dynamic single-molecule interactions of the epidermal growth factor receptor with clathrin-coated structures on the plasma membrane of a live cell under physiological conditions. Phoenix Fluor 555 (PF555) is a bright dye with an exceptional, order-of-magnitude longer photobleaching lifetime than conventional organic dyes that enables extended live-cell single-molecule imaging without anti-photobleaching additives.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":"22 3","pages":"550-558"},"PeriodicalIF":36.1,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143008713","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

Probing the physical hallmarks of cancer. 探查癌症的生理特征。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-01-15 DOI: 10.1038/s41592-024-02564-4

Hadi T Nia, Lance L Munn, Rakesh K Jain

引用次数: 0

Resolving tissue complexity by multimodal spatial omics modeling with MISO 基于MISO的多模态空间组学模型求解组织复杂性。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-01-15 DOI: 10.1038/s41592-024-02574-2

Kyle Coleman, Amelia Schroeder, Melanie Loth, Daiwei Zhang, Jeong Hwan Park, Ji-Youn Sung, Niklas Blank, Alexis J. Cowan, Xuyu Qian, Jianfeng Chen, Jiahui Jiang, Hanying Yan, Laith Z. Samarah, Jean R. Clemenceau, Inyeop Jang, Minji Kim, Isabel Barnfather, Joshua D. Rabinowitz, Yanxiang Deng, Edward B. Lee, Alexander Lazar, Jianjun Gao, Emma E. Furth, Tae Hyun Hwang, Linghua Wang, Christoph A. Thaiss, Jian Hu, Mingyao Li

{"title":"Resolving tissue complexity by multimodal spatial omics modeling with MISO","authors":"Kyle Coleman, Amelia Schroeder, Melanie Loth, Daiwei Zhang, Jeong Hwan Park, Ji-Youn Sung, Niklas Blank, Alexis J. Cowan, Xuyu Qian, Jianfeng Chen, Jiahui Jiang, Hanying Yan, Laith Z. Samarah, Jean R. Clemenceau, Inyeop Jang, Minji Kim, Isabel Barnfather, Joshua D. Rabinowitz, Yanxiang Deng, Edward B. Lee, Alexander Lazar, Jianjun Gao, Emma E. Furth, Tae Hyun Hwang, Linghua Wang, Christoph A. Thaiss, Jian Hu, Mingyao Li","doi":"10.1038/s41592-024-02574-2","DOIUrl":"10.1038/s41592-024-02574-2","url":null,"abstract":"Spatial molecular profiling has provided biomedical researchers valuable opportunities to better understand the relationship between cellular localization and tissue function. Effectively modeling multimodal spatial omics data is crucial for understanding tissue complexity and underlying biology. Furthermore, improvements in spatial resolution have led to the advent of technologies that can generate spatial molecular data with subcellular resolution, requiring the development of computationally efficient methods that can handle the resulting large-scale datasets. MISO (MultI-modal Spatial Omics) is a versatile algorithm for feature extraction and clustering, capable of integrating multiple modalities from diverse spatial omics experiments with high spatial resolution. Its effectiveness is demonstrated across various datasets, encompassing gene expression, protein expression, epigenetics, metabolomics and tissue histology modalities. MISO outperforms existing methods in identifying biologically relevant spatial domains, representing a substantial advancement in multimodal spatial omics analysis. Moreover, MISO’s computational efficiency ensures its scalability to handle large-scale datasets generated by subcellular resolution spatial omics technologies. MISO (MultI-modal Spatial Omics) integrates two or more spatial omics modalities, despite differences in data quality and spatial resolution for improved feature extraction and clustering to reveal biologically meaningful tissue organization.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":"22 3","pages":"530-538"},"PeriodicalIF":36.1,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143008712","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

Year in review 2024 回顾年度

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-01-13 DOI: 10.1038/s41592-024-02591-1

引用次数: 0