Nature Methods最新文献

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Precision control of cellular functions with a temperature-sensitive protein

IF 36.1 1区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

Nature Methods

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

Temperature-sensitive proteins would enable the remote control of cellular functions deep within tissues, although few such proteins have been characterized. Melt is a protein that reversibly clusters and translocates to the membrane in response to small temperature changes, enabling flexible regulation of cellular processes in vitro and in vivo.

引用次数: 0

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

IF 36.1 1区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

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

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.

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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 Q1 BIOCHEMICAL RESEARCH METHODS

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 Q1 BIOCHEMICAL RESEARCH METHODS

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

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.

利用液滴微流体进行单细胞组合索引测序是一种平衡成本、可扩展性、鲁棒性和可及性的有吸引力的方法。然而，现有的方法往往需要为个体模式量身定制方案，限制了它们的自动化潜力和临床适用性。为了解决这个问题，我们引入了UDA-seq，这是一个通用的工作流程，集成了索引后步骤，以提高吞吐量，并系统地适应现有的基于液滴的单细胞多模态方法。UDA-seq在各种组织和细胞类型中进行基准测试，实现几种常见的多模态分析，包括RNA和VDJ， RNA和染色质以及RNA和CRISPR扰动的单细胞联合分析。值得注意的是，在单通道液滴微流体实验中，UDA-seq促进了从36个冷冻临床活检标本中高效生成超过100,000个高质量单细胞数据集。下游分析证明了该方法在识别与临床表型相关的罕见细胞亚群和探索癌细胞易感性方面的稳健性。

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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 Q1 BIOCHEMICAL RESEARCH METHODS

Nature Methods

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

This work presents optimized experimental protocols for the extraction of >2,000 unique membrane proteins directly from their native membranes into native nanodiscs. Combined with orthogonal structural, biochemical or biophysical approaches, these native nanodiscs enable membrane proteins to be studied directly in their native membrane context.

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 Q1 BIOCHEMICAL RESEARCH METHODS

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 Q1 BIOCHEMICAL RESEARCH METHODS

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

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.

尽管在样品制备、仪器和数据分析方面取得了重大进展，但单细胞蛋白质组学目前受到蛋白质组学深度和定量性能的限制。在这里，我们展示了高度改进的蛋白质组覆盖深度以及超低输入量量化的准确性和精度。使用定制的文库，我们以每天50个样品的吞吐量从250 pg的HeLa细胞肽中鉴定多达7400个蛋白质组。使用两个蛋白质组组合，我们检查了量化的最佳参数，并表明2的折叠变化差异仍然可以在单细胞水平输入中成功确定。最终，我们将我们的工作流程应用于A549细胞，根据细胞大小和使用的搜索策略，从单个细胞中获得从1801到最多bbb5300个蛋白质组的蛋白质组覆盖范围，这允许研究细胞大小和细胞周期阶段之间的依赖性。此外，我们的工作流程使我们能够区分两种人类胚泡谱系的体外类似物：幼稚的人类多能干细胞（外胚层）和滋养外胚层样细胞。我们的数据与转录组学数据一致，表明单细胞蛋白质组学具有识别囊胚内生物学相关差异的能力。

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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 Q1 BIOCHEMICAL RESEARCH METHODS

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

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.

单细胞蛋白质组学（SCP）有望通过提供单个细胞中蛋白质组的无与伦比的视图来彻底改变生物医学。在这里，我们提出了一种名为Chip-Tip的高灵敏度SCP工作流程，可在单个HeLa细胞中鉴定bb5000个蛋白质。它还有助于在单个细胞中直接检测翻译后修饰，从而不必进行特定的翻译后修饰富集。我们的研究证明了每天处理多达120个无标签SCP样品的可行性。优化的组织解离缓冲液使药物治疗的癌细胞球体有效的单细胞分解，改善整体SCP分析。为了分析非定向人诱导多能干细胞分化，我们对人诱导多能干细胞中的干细胞标记物OCT4和SOX2以及不同胚状体细胞中的GATA4（内胚层）、HAND1（中胚层）和MAP2（外胚层）等谱系标记物进行了定量分析。我们的工作流程为SCP的灵敏度和吞吐量设定了基准，在基础生物学和生物医学中广泛应用于细胞类型特异性标记物和治疗靶点的鉴定。

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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 Q1 BIOCHEMICAL RESEARCH METHODS

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

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.

体内谱系追踪在揭示组织发育和体内平衡的基本原理方面具有巨大的潜力。然而，目前的人类谱系追踪依赖于极其罕见的体细胞突变，这限制了时间分辨率和谱系准确性。在这里，我们开发了一个基于DNA甲基化频繁变异的通用谱系追踪工具，通过我们的计算方法MethylTree实现。利用已知谱系和表型标签的单细胞全基因组DNA甲基化数据集，MethylTree以接近100%的准确率重建了不同细胞类型、发育阶段和物种的谱系历史。我们在小鼠和人类血液中展示了基于上皮突变的单细胞多组谱系追踪，其中甲基树概括了造血中的分化层次。将MethylTree应用于人类胚胎，我们揭示了四细胞阶段的早期命运承诺。在原生小鼠血液中，我们鉴定出了约250个造血干细胞克隆。MethylTree为人类及其他人群的高分辨率、非侵入性和多组谱系追踪打开了大门。

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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 Q1 BIOCHEMICAL RESEARCH METHODS

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

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.

小代谢产物与荧光染料的不相容性和成像质谱的有限分辨率阻碍了细胞代谢的超分辨率成像。我们提出了超灵敏的重加权可见受激拉曼散射（uv - srs），这是一种无标记的振动成像技术，用于细胞内代谢物的多路纳米观察。我们开发了一种具有广泛脉冲啁啾的可见SRS显微镜，将检测限提高到~4,000个分子，并引入了自监督多智能体去噪器，将SRS中的非独立噪声抑制了7.2 dB以上，从而使灵敏度比近红外SRS提高了50倍。利用增强的灵敏度，我们采用傅立叶重加权来放大以前被噪声淹没的100纳米以下的空间频率。通过傅里叶环相关验证，我们在细胞成像中实现了86 nm的横向分辨率。我们可视化了与宿主细胞中病毒复制和工程细菌中亚细胞脂肪酸合成相关的代谢纳米结构的重编程，证明了其在纳米尺度空间代谢组学方面的能力。

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