Nature Methods最新文献_第5页

Mild and ultrafast GLORI enables absolute quantification of m⁶A methylome from low-input samples. 温和和超快GLORI能够从低输入样品中绝对定量m6A甲基组。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-06-01 Epub Date: 2025-05-05 DOI: 10.1038/s41592-025-02680-9

Hanxiao Sun, Bo Lu, Zeyu Zhang, Ye Xiao, Zhe Zhou, Lin Xi, Zhichao Li, Zhe Jiang, Jiayi Zhang, Meng Wang, Cong Liu, Yichen Ma, Jinying Peng, Xiu-Jie Wang, Chengqi Yi

{"title":"Mild and ultrafast GLORI enables absolute quantification of m6A methylome from low-input samples.","authors":"Hanxiao Sun, Bo Lu, Zeyu Zhang, Ye Xiao, Zhe Zhou, Lin Xi, Zhichao Li, Zhe Jiang, Jiayi Zhang, Meng Wang, Cong Liu, Yichen Ma, Jinying Peng, Xiu-Jie Wang, Chengqi Yi","doi":"10.1038/s41592-025-02680-9","DOIUrl":"10.1038/s41592-025-02680-9","url":null,"abstract":"Methods for absolute quantification of N6-methyladenosine (m6A) have emerged as powerful tools in epitranscriptomics. We previously reported GLORI, a chemical-assisted approach to achieve unbiased and precise m6A measurement. However, its lengthy reaction time and severe RNA degradation have limited its applicability, particularly for low-input samples. Here, we present two updated GLORI approaches that are ultrafast, mild and enable absolute m6A quantification from one to two orders of magnitude less than the RNA starting material: GLORI 2.0 is compatible with RNA from ~10,000 cells and enhances sensitivity for both transcriptome-wide and locus-specific m6A detection; GLORI 3.0 further utilizes a reverse transcription-silent carrier RNA to achieve m6A quantification from as low as 500-1,000 cells. Using limited RNA from mouse dorsal hippocampus, we reveal a high modification level in synapse-related gene sets. We envision that the updated GLORI methods will greatly expand the applicability of absolute quantification of m6A in biology.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":" ","pages":"1226-1236"},"PeriodicalIF":36.1,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143982104","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

Cell simulation as cell segmentation. 细胞模拟作为细胞分割。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-06-01 Epub Date: 2025-05-22 DOI: 10.1038/s41592-025-02697-0

Daniel C Jones, Anna E Elz, Azadeh Hadadianpour, Heeju Ryu, David R Glass, Evan W Newell

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 : 2025-06-01 Epub 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":"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":"1199-1212"},"PeriodicalIF":36.1,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12165859/pdf/","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":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Imaging neuronal voltage beyond the scattering limit. 成像超过散射极限的神经元电压。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-06-01 Epub Date: 2025-05-19 DOI: 10.1038/s41592-025-02692-5

Tsai-Wen Chen, Xian-Bin Huang, Sarah E Plutkis, Katie L Holland, Luke D Lavis, Bei-Jung Lin

{"title":"Imaging neuronal voltage beyond the scattering limit.","authors":"Tsai-Wen Chen, Xian-Bin Huang, Sarah E Plutkis, Katie L Holland, Luke D Lavis, Bei-Jung Lin","doi":"10.1038/s41592-025-02692-5","DOIUrl":"10.1038/s41592-025-02692-5","url":null,"abstract":"Voltage imaging is a promising technique for high-speed recording of neuronal population activity. However, tissue scattering severely limits its application in dense neuronal populations. Here we adopt the principle of localization microscopy, a technique that enables super-resolution imaging of single molecules, to resolve dense neuronal activities in vivo. Leveraging the sparse activation of neurons during action potentials (APs), we precisely localize the fluorescence changes associated with each AP, creating a super-resolution image of neuronal activity. This approach, termed activity localization imaging (ALI), identifies overlapping neurons and separates their activities with over tenfold greater precision than what tissue scattering permits. We applied ALI to widefield, targeted illumination and light sheet microscopy data, resolving neurons that cannot be distinguished by existing signal extraction pipelines. In the mouse hippocampus, ALI generates a cellular resolution map of theta oscillations, revealing the diversity of neuronal phase locking within a dense local network.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":" ","pages":"1366-1375"},"PeriodicalIF":36.1,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12165860/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144102265","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

Single-cell ultra-high-throughput multiplexed chromatin and RNA profiling reveals gene regulatory dynamics. 单细胞超高通量多重染色质和RNA分析揭示基因调控动力学。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-06-01 Epub Date: 2025-05-26 DOI: 10.1038/s41592-025-02700-8

Sara Lobato-Moreno, Umut Yildiz, Annique Claringbould, Nila H Servaas, Evi P Vlachou, Christian Arnold, Hanke Gwendolyn Bauersachs, Víctor Campos-Fornés, Minyoung Kim, Ivan Berest, Karin D Prummel, Kyung-Min Noh, Mikael Marttinen, Judith B Zaugg

{"title":"Single-cell ultra-high-throughput multiplexed chromatin and RNA profiling reveals gene regulatory dynamics.","authors":"Sara Lobato-Moreno, Umut Yildiz, Annique Claringbould, Nila H Servaas, Evi P Vlachou, Christian Arnold, Hanke Gwendolyn Bauersachs, Víctor Campos-Fornés, Minyoung Kim, Ivan Berest, Karin D Prummel, Kyung-Min Noh, Mikael Marttinen, Judith B Zaugg","doi":"10.1038/s41592-025-02700-8","DOIUrl":"10.1038/s41592-025-02700-8","url":null,"abstract":"Enhancers and transcription factors (TFs) are crucial in regulating cellular processes. Current multiomic technologies to study these elements in gene regulatory mechanisms lack multiplexing capability and scalability. Here we present single-cell ultra-high-throughput multiplexed sequencing (SUM-seq) for co-assaying chromatin accessibility and gene expression in single nuclei. SUM-seq enables profiling hundreds of samples at the million cell scale and outperforms current high-throughput single-cell methods. We demonstrate the capability of SUM-seq to (1) resolve temporal gene regulation of macrophage M1 and M2 polarization to bridge TF regulatory networks and immune disease genetic variants, (2) define the regulatory landscape of primary T helper cell subsets and (3) dissect the effect of perturbing lineage TFs via arrayed CRISPR screens in spontaneously differentiating human induced pluripotent stem cells. SUM-seq offers a cost-effective, scalable solution for ultra-high-throughput single-cell multiomic sequencing, accelerating the unraveling of complex gene regulatory networks in cell differentiation, responses to perturbations and disease studies.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":" ","pages":"1213-1225"},"PeriodicalIF":36.1,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12165849/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144151299","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

Imaging 3D cell cultures with optical microscopy. 用光学显微镜成像三维细胞培养。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-06-01 Epub Date: 2025-04-17 DOI: 10.1038/s41592-025-02647-w

Huai-Ching Hsieh, Qinghua Han, David Brenes, Kevin W Bishop, Rui Wang, Yuli Wang, Chetan Poudel, Adam K Glaser, Benjamin S Freedman, Joshua C Vaughan, Nancy L Allbritton, Jonathan T C Liu

引用次数: 0

Dark-based optical sectioning assists background removal in fluorescence microscopy. 暗基光学切片有助于荧光显微镜去除背景。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-06-01 Epub Date: 2025-05-12 DOI: 10.1038/s41592-025-02667-6

Ruijie Cao, Yaning Li, Yao Zhou, Meiqi Li, Fangrui Lin, Wenyi Wang, Guoxun Zhang, Gang Wang, Boya Jin, Wei Ren, Yu Sun, Zhifeng Zhao, Wei Zhang, Jing Sun, Yiwei Hou, Xinzhu Xu, Jiakui Hu, Wei Shi, Shuang Fu, Qianxi Liang, Yanye Lu, Changhui Li, Yuxuan Zhao, Yiming Li, Dong Kuang, Jiamin Wu, Peng Fei, Junle Qu, Peng Xi

{"title":"Dark-based optical sectioning assists background removal in fluorescence microscopy.","authors":"Ruijie Cao, Yaning Li, Yao Zhou, Meiqi Li, Fangrui Lin, Wenyi Wang, Guoxun Zhang, Gang Wang, Boya Jin, Wei Ren, Yu Sun, Zhifeng Zhao, Wei Zhang, Jing Sun, Yiwei Hou, Xinzhu Xu, Jiakui Hu, Wei Shi, Shuang Fu, Qianxi Liang, Yanye Lu, Changhui Li, Yuxuan Zhao, Yiming Li, Dong Kuang, Jiamin Wu, Peng Fei, Junle Qu, Peng Xi","doi":"10.1038/s41592-025-02667-6","DOIUrl":"10.1038/s41592-025-02667-6","url":null,"abstract":"In fluorescence microscopy, a persistent challenge is the defocused background that obscures cellular details and introduces artifacts. Here, we introduce Dark sectioning, a method inspired by natural image dehazing for removing backgrounds that leverages dark channel prior and dual frequency separation to provide single-frame optical sectioning. Unlike denoising or deconvolution, Dark sectioning specifically targets and removes out-of-focus backgrounds, stably improving the signal-to-background ratio by nearly 10 dB and structural similarity index measure of images by approximately tenfold. Dark sectioning was validated using wide-field, confocal, two/three-dimensional structured illumination and one/two-photon microscopy with high-fidelity reconstruction. We further demonstrate its potential to improve the segmentation accuracy in deep tissues, resulting in better recognition of neurons in the mouse brain and accurate assessment of nuclei in prostate lesions or mouse brain sections. Dark sectioning is compatible with many other microscopy modalities, including light-sheet and light-field microscopy, as well as processing algorithms, including deconvolution and super-resolution optical fluctuation imaging.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":" ","pages":"1299-1310"},"PeriodicalIF":36.1,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144064294","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

Digitalized organoids: integrated pipeline for high-speed 3D analysis of organoid structures using multilevel segmentation and cellular topology. 数字化类器官：集成流水线高速三维分析类器官结构使用多层次分割和细胞拓扑。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-06-01 Epub Date: 2025-05-14 DOI: 10.1038/s41592-025-02685-4

Hui Ting Ong, Esra Karatas, Titouan Poquillon, Gianluca Grenci, Alessandro Furlan, Florian Dilasser, Saburnisha Binte Mohamad Raffi, Damien Blanc, Elise Drimaracci, Dimitri Mikec, Gaetan Galisot, Blake A Johnson, Albert Zou Liu, Cora Thiel, Oliver Ullrich, Victor Racine, Anne Beghin

{"title":"Digitalized organoids: integrated pipeline for high-speed 3D analysis of organoid structures using multilevel segmentation and cellular topology.","authors":"Hui Ting Ong, Esra Karatas, Titouan Poquillon, Gianluca Grenci, Alessandro Furlan, Florian Dilasser, Saburnisha Binte Mohamad Raffi, Damien Blanc, Elise Drimaracci, Dimitri Mikec, Gaetan Galisot, Blake A Johnson, Albert Zou Liu, Cora Thiel, Oliver Ullrich, Victor Racine, Anne Beghin","doi":"10.1038/s41592-025-02685-4","DOIUrl":"10.1038/s41592-025-02685-4","url":null,"abstract":"Organoids replicate tissue architecture and function and offer a unique opportunity to explore the impact of external perturbations in vitro. However, conducting large-scale screening procedures to investigate the effects of various stresses on cellular morphology and topology in these systems poses important challenges, including limitations in high-resolution three-dimensional (3D) imaging and accessible 3D analysis platforms. In this study, we introduce an AI-based multilevel segmentation and cellular topology pipeline for screening morphology and topology modifications in 3D cell culture at both the nuclear and cytoplasmic levels, as well as at the whole-organoid scale. We demonstrate the versatility of our approach through proof-of-concept experiments, encompassing well-characterized conditions and poorly explored mechanical stressors such as microgravity. By offering a user-friendly interface named 3DCellScope and a comprehensive set of tools for discovery-like assays in screening 3D organoid models, our pipeline demonstrates wide-ranging potential for applications in biomedical research.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":" ","pages":"1343-1354"},"PeriodicalIF":36.1,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12165853/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144208932","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

An exceptionally photostable mScarlet3 mutant. 一个非常耐光的mScarlet3突变体。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-06-01 DOI: 10.1038/s41592-025-02675-6

Benjamin C Campbell

引用次数: 0

Prediction of protein subcellular localization in single cells. 单细胞中蛋白质亚细胞定位的预测。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-06-01 Epub Date: 2025-05-13 DOI: 10.1038/s41592-025-02696-1

Xinyi Zhang, Yitong Tseo, Yunhao Bai, Fei Chen, Caroline Uhler

引用次数: 0