Nature Methods最新文献

{"title":"Spatial chromatin architecture and accessibility co-profiling of mammalian tissues","authors":"Ping Wang, Juan Wang, Qixuan Wang, Mark W. Youngblood, Yang Cheng, Bo Tao, Josiah Hiu-Yuen Wong, Yu Luan, Shaojun Yu, Alok Swaroop, Khizar R. Nandoliya, Hinda Najem, Yihao Fu, Kathleen McCortney, Di Zhang, Yarui Diao, Amy B. Heimberger, Adam M. Sonabend, Craig M. Horbinski, Rong Fan, Feng Yue","doi":"10.1038/s41592-026-03217-4","DOIUrl":"10.1038/s41592-026-03217-4","url":null,"abstract":"Cellular function depends on the spatial organization of cells and biomolecules within the tissue microenvironment. Advances in spatial omics have enabled profiling of molecular features such as transcriptome, proteome and epigenome, and there has been rapid progress of imaging-based approaches to study spatial three-dimensional (3D) genome organization. Here we present Spatial-ATAC-Hi-C, a microfluidic‑based platform for genome-wide, spatially resolved joint-profiling of 3D genome organization and chromatin accessibility on tissue slides. Applied to mouse and human brains, Spatial-ATAC-Hi-C revealed distinct chromatin architecture and gene regulatory programs in neuronal and non-neuronal populations in their native tissue context. In glioblastoma and astrocytoma samples, we detected spatially resolved 3D genome alterations, copy number variations and structural variations across tumor regions, revealing clinically relevant oncogenic events and clonal heterogeneity. By co-profiling of genome architecture and chromatin accessibility while preserving tissue architecture, Spatial-ATAC-Hi-C provides a powerful tool for studying spatial gene regulation in human biology and disease. Spatial-ATAC-Hi-C enables the profiling of both chromatin accessibility and organization in a spatially resolved manner, as demonstrated on mouse brain and human glioblastoma and astrocytoma samples.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":"23 10","pages":"2015-2028"},"PeriodicalIF":28.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41592-026-03217-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148875311","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}

{"title":"Go figure: transparency in neuroscience images preserves context and clarifies interpretation.","authors":"Paul A Taylor, Himanshu Aggarwal, Peter A Bandettini, Marco Barilari, Molly G Bright, César Caballero-Gaudes, Vince D Calhoun, Mallar Chakravarty, Gabriel A Devenyi, Jennifer W Evans, Eduardo A Garza-Villarreal, Rémi Gau, Daniel R Glen, Rainer Goebel, Javier Gonzalez-Castillo, Omer Faruk Gulban, Yaroslav Halchenko, Daniel A Handwerker, Taylor Hanayik, Peter D Lauren, David A Leopold, Jason P Lerch, Christian Mathys, Paul McCarthy, Anke McLeod, Amanda F Mejia, Stefano Moia, Thomas E Nichols, Cyril Pernet, Luiz Pessoa, Bettina Pfleiderer, Justin K Rajendra, Jalil Rasgado-Toledo, Laura D Reyes, Richard C Reynolds, Vinai Roopchansingh, Chris Rorden, Brian E Russ, Benedikt Sundermann, Bertrand Thirion, Salvatore Torrisi, Gang Chen","doi":"10.1038/s41592-026-03206-7","DOIUrl":"10.1038/s41592-026-03206-7","url":null,"abstract":"<p><p>Visualizations are vital for communicating scientific results. Historically, brain images in neuroscience figures have only depicted regions that surpass a given statistical threshold. This practice substantially biases interpretation of the results and subsequent meta-analyses, particularly toward non-reproducibility. We advocate for 'transparent thresholding' that not only highlights statistically significant regions but also includes subthreshold locations, retaining key experimental context. This balances the dual needs of distilling modeling results and enabling informed interpretations of neuroimaging results. Transparent thresholding removes ambiguity, decreases hypersensitivity to nonphysiological features, helps catch potential artifacts, improves cross-study comparisons, reduces non-reproducibility biases and clarifies interpretations. We address considerations raised by researchers in the field and highlight the many software packages implementing transparent thresholding, several of which were added or streamlined as part of this work. We hope that by showing how transparent thresholding can meaningfully improve the interpretation (and reproducibility) of neuroimaging findings, we will encourage more researchers to adopt this method.</p>","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":" ","pages":""},"PeriodicalIF":28.3,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13537210/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148865912","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}

{"title":"SPIFFI enables single-shot super-resolution and multidimensional imaging","authors":"Wei Guo \u0000 (,&nbsp;),&nbsp;Lely Feletti,&nbsp;Aleksandra Radenovic","doi":"10.1038/s41592-026-03196-6","DOIUrl":"10.1038/s41592-026-03196-6","url":null,"abstract":"Fluorescence super-resolution microscopy has advanced optical imaging into the nanoscale regime, transforming biological and interdisciplinary research. However, wide-field super-resolution techniques often compromise temporal resolution, thereby limiting the capture of rapid and transient biological events in living systems. Here we introduce spatial polarization-induced fluorescence fluctuation imaging (SPIFFI), a multichannel polarimetric method for single-shot super-resolution imaging and six-dimensional information extraction. By leveraging the inherently smaller point spread function under polarized detection and capturing polarization-dependent spatial fluctuations across multiplexed channels, SPIFFI achieves instant resolution enhancement from a single exposure. This capability substantially enhances the feasibility of volumetric live-cell super-resolution imaging. Moreover, SPIFFI images can integrate seamlessly with existing fluctuation-based methods for further postprocessing and resolution improvement. We demonstrate the versatility of SPIFFI through experiments on both fixed and live cells, capturing rapid subcellular dynamics and enabling high-throughput, multidimensional imaging beyond the diffraction limit. SPIFFI thus offers a practical and robust platform for real-time super-resolution imaging in biological research. Using a polarimetric approach, SPIFFI enables real-time super-resolution imaging of live-cell samples.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":"23 10","pages":"2077-2086"},"PeriodicalIF":28.3,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41592-026-03196-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148865891","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}

{"title":"Polarized detection sharpens optical live-cell fluorescence imaging","authors":"","doi":"10.1038/s41592-026-03195-7","DOIUrl":"10.1038/s41592-026-03195-7","url":null,"abstract":"A multichannel microscopy method that exploits the polarization of fluorescent molecules reconstructs super-resolved images from a single camera frame. The approach not only captures fast cellular dynamics that are missed by methods that require hundreds of frames, but also reads the orientation of fluorescent molecules within cells.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":"23 10","pages":"1946-1947"},"PeriodicalIF":28.3,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148865905","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}

{"title":"Confounders of lncRNA screens: sources, consequences and possible solutions.","authors":"Juan José Montero, Riccardo Trozzo, Roland Rad","doi":"10.1038/s41592-026-03226-3","DOIUrl":"https://doi.org/10.1038/s41592-026-03226-3","url":null,"abstract":"","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":" ","pages":""},"PeriodicalIF":28.3,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148865958","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}

{"title":"A FAIR road to a bioAFM databank","authors":"Jean-Luc Pellequer,&nbsp;Sebastian Aguayo,&nbsp;Andrea Alessandrini,&nbsp;David Alsteens,&nbsp;Toshio Ando,&nbsp;Audrey Beaussart,&nbsp;Michael Betton,&nbsp;Timo Betz,&nbsp;Kerstin G. Blank,&nbsp;Simone Bovio,&nbsp;Clément Campillo,&nbsp;Claudio Canale,&nbsp;Alexander X. Cartagena-Rivera,&nbsp;Filomena A. Carvalho,&nbsp;Ignacio Casuso,&nbsp;Guillaume Charras,&nbsp;Marti Checa,&nbsp;Liam Collins,&nbsp;Adai Colom,&nbsp;Luca Costa,&nbsp;Etienne Dague,&nbsp;Tanya E. S. Dahms,&nbsp;Pedro Jose de Pablo,&nbsp;Alexandra Delvallée,&nbsp;Simone Dinarelli,&nbsp;Lorna Dougan,&nbsp;Yves F. Dufrêne,&nbsp;Andra C. Dumitru,&nbsp;Yuri M. Efremov,&nbsp;Sofiane El-Kirat-Chatel,&nbsp;Paolo Facci,&nbsp;Georg E. Fantner,&nbsp;Amir Farokh Payam,&nbsp;Cécile Feuillie,&nbsp;Cristina Flors,&nbsp;Nancy Forde,&nbsp;Cécile Formosa-Dague,&nbsp;Gregory Francius,&nbsp;Clemens M. Franz,&nbsp;Kristian Franze,&nbsp;Ricardo Garcia,&nbsp;Sergi Garcia-Manyes,&nbsp;Núria Gavara,&nbsp;Marina I. Giannotti,&nbsp;Marco Girasole,&nbsp;Martin Guthold,&nbsp;George R. Heath,&nbsp;Céline Heu,&nbsp;Peter Hinterdorfer,&nbsp;Jamie K. Hobbs,&nbsp;Bart W. Hoogenboom,&nbsp;Sébastien Janel,&nbsp;Miklós Kellermayer,&nbsp;Petr Klapetek,&nbsp;Noriyuki Kodera,&nbsp;Melanie Koehler,&nbsp;Frank Lafont,&nbsp;Guillaume Lamour,&nbsp;Jessem Landoulsi,&nbsp;Valérie M. Laurent,&nbsp;Philippe Leclère,&nbsp;Malgorzata Lekka,&nbsp;Hongbin Li,&nbsp;Giovanni Longo,&nbsp;Arin Marchesi,&nbsp;Marion Mathelié-Guinlet,&nbsp;Gerald A. Meininger,&nbsp;Ioanna Mela,&nbsp;Pierre-Emmanuel Milhiet,&nbsp;Ruben Millan-Solsona,&nbsp;Tea Mišić Radić,&nbsp;Michaël Molinari,&nbsp;Fernando Moreno-Herrero,&nbsp;Michael A. Nash,&nbsp;Olivier Noël,&nbsp;Yoo Jin Oh,&nbsp;Laia Pasquina-Lemonche,&nbsp;Shivprasad Patil,&nbsp;Patricia Pedraz,&nbsp;Ana Paula Pêgo,&nbsp;Thomas T. Perkins,&nbsp;Martin Pesl,&nbsp;Tri Thanh Pham,&nbsp;Laura Picas,&nbsp;Alessandro Podestà,&nbsp;Johannes Preiner,&nbsp;Jan Přibyl,&nbsp;Roger Proksch,&nbsp;Pierre-Henri Puech,&nbsp;Alice L. B. Pyne,&nbsp;Manfred Radmacher,&nbsp;Lorena Redondo-Morata,&nbsp;Felix Rico,&nbsp;Wouter H. Roos,&nbsp;Robert Ros,&nbsp;Nuno C. Santos,&nbsp;Ugis Sarkans,&nbsp;Tilman E. Schäffer,&nbsp;Hermann Schillers,&nbsp;Zhifeng Shao,&nbsp;Delphine Sicard,&nbsp;Adam Cohen Simonsen,&nbsp;Igor Sokolov,&nbsp;Susana R. Sousa,&nbsp;Bjørn T. Stokke,&nbsp;Andreas Stylianou,&nbsp;Marek Szymonski,&nbsp;Florence Tama,&nbsp;Neil H. Thomson,&nbsp;Takayuki Uchihashi,&nbsp;Massimo Vassalli,&nbsp;Claude Verdier,&nbsp;Anthony Vial,&nbsp;Véronique Vié,&nbsp;Tomaso Zambelli,&nbsp;Renato Zenobi,&nbsp;Peng Zheng,&nbsp;Claire Valotteau","doi":"10.1038/s41592-026-03214-7","DOIUrl":"10.1038/s41592-026-03214-7","url":null,"abstract":"In this Comment, we direct attention to initial efforts to establish a high-quality databank of atomic force microscopy (AFM) data: bioAFM-DB. We outline the state of this endeavor, its challenges, and potential courses of action.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":"23 10","pages":"1927-1931"},"PeriodicalIF":28.3,"publicationDate":"2026-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148851052","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}

{"title":"All-optical multimodal mapping of single-cell-type-specific metabolic activities via REDCAT","authors":"Yajuan Li,&nbsp;Zhaojun Zhang,&nbsp;Archibald Enninful,&nbsp;Negin Farzad,&nbsp;Presha Rajbhandari,&nbsp;Hua Tian,&nbsp;Jungmin Nam,&nbsp;Xiaoyu Qin,&nbsp;Jorge Villazon,&nbsp;Anthony A. Fung,&nbsp;Hongje Jang,&nbsp;Zhiliang Bai,&nbsp;Nancy R. Zhang,&nbsp;Brent R. Stockwell,&nbsp;Rong Fan,&nbsp;Mina L. Xu,&nbsp;Zongming Ma,&nbsp;Lingyan Shi","doi":"10.1038/s41592-026-03180-0","DOIUrl":"10.1038/s41592-026-03180-0","url":null,"abstract":"Metabolism is fundamental to cell function, yet its activities vary across tissue environments. Resolving these processes in situ at single-cell resolution is crucial for understanding physiology in health and disease. However, existing methods lack biochemical specificity or direct linkage to cell identity. Here we report a method, Raman Enhanced Delineation of Cell Atlases in Tissues (REDCAT), an all-optical platform integrating Raman scattering microscopy and high-plex immunofluorescence to co-map metabolism and cell types. REDCAT achieves subcellular profiling of protein, lipid, nuclear metabolites and redox metabolism in human tissues. In lymph nodes, it revealed cell-type-specific metabolic specialization. In lymphoma, REDCAT uncovered profound reprogramming and transitional states during tumor transformation. In the liver, it resolved zonation-dependent metabolic gradients. By linking cell identity to spatial metabolic states, REDCAT provides a framework for studying immunity and cancer, offering a path to deciphering the metabolic basis of disease. Raman Enhanced Delineation of Cell Atlases in Tissues (REDCAT) integrates stimulated Raman scattering microscopy and high-plex immunofluorescence to profile single-cell proteins, lipids, nuclear metabolites and redox metabolism in tissue.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":"23 9","pages":"1840-1853"},"PeriodicalIF":28.3,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13541623/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148840870","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}

{"title":"A multimodal, all-optical platform for linking cell identity to metabolic function in intact tissues","authors":"","doi":"10.1038/s41592-026-03181-z","DOIUrl":"10.1038/s41592-026-03181-z","url":null,"abstract":"REDCAT is a multimodal, all-optical platform that maps metabolic activity alongside cell identity in intact tissues at single-cell and subcellular resolution. By integrating Raman imaging, autofluorescence and high-plex immunofluorescence, REDCAT has resolved metabolic features in normal lymph nodes, uncovered lipid-redox remodeling in lymphoma, and exposed intratumoral heterogeneity, suggesting a use in functional histopathology.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":"23 9","pages":"1695-1696"},"PeriodicalIF":28.3,"publicationDate":"2026-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148840884","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}

{"title":"Author Correction: OrthoFinder: improved phylogenetic orthology inference with enhanced accuracy and scalability","authors":"David M. Emms,&nbsp;Yi Liu,&nbsp;Laurence Belcher,&nbsp;Jonathan Holmes,&nbsp;Steven Kelly","doi":"10.1038/s41592-026-03238-z","DOIUrl":"10.1038/s41592-026-03238-z","url":null,"abstract":"","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":"23 10","pages":"2110-2110"},"PeriodicalIF":28.3,"publicationDate":"2026-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.comhttps://www.nature.com/articles/s41592-026-03238-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148830726","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}

{"title":"Beyond benchmarking: an expert-guided consensus approach to spatially aware clustering","authors":"Jieran Sun,&nbsp;Kirti Biharie,&nbsp;Peiying Cai,&nbsp;Niklas Müller-Bötticher,&nbsp;Paul Kiessling,&nbsp;Meghan A. Turner,&nbsp;Søren Helweg Dam,&nbsp;Florian Heyl,&nbsp;Sarusan Kathirchelvan,&nbsp;Martin Emons,&nbsp;Samuel Gunz,&nbsp;Sven Twardziok,&nbsp;Amin El-Heliebi,&nbsp;Martin Zacharias,&nbsp;SpaceHack 2.0 participants,&nbsp;Roland Eils,&nbsp;Marcel Reinders,&nbsp;Raphael Gottardo,&nbsp;Christoph Kuppe,&nbsp;Brian Long,&nbsp;Ahmed Mahfouz,&nbsp;Mark D. Robinson,&nbsp;Naveed Ishaque","doi":"10.1038/s41592-026-03194-8","DOIUrl":"10.1038/s41592-026-03194-8","url":null,"abstract":"Spatial omics technologies have revolutionized the study of tissue architecture and cellular heterogeneity by integrating molecular profiles with spatial localization. In spatially resolved transcriptomics, delineating higher-order anatomical structures is critical for understanding how cellular organization affects function. However, the reliability of current benchmarks of spatially aware clustering (SAC) methods is undermined by their narrow focus on Visium and brain tissue datasets and the incorrect interpretation of manual annotation as ground truth. Here we present SACCELERATOR, a community-driven, extensible framework that standardizes data formatting, method integration and metric evaluation, enabling rapid inclusion of new methods and datasets. Our analysis revealed substantial limitations in the generalizability and reproducibility of SAC methods and shows that anatomical labels commonly used as ground truths are often biased, error prone and unsuitable for benchmarking. Rather than ranking methods, we propose a consensus-guided workflow where descriptive spatial metrics highlight high-entropy regions of method disagreement, enabling targeted feedback for tissue experts. Applied to brain and cancer datasets, this approach uncovered biologically meaningful patterns overlooked by individual SAC methods and manual annotations, highlighting the need for iterative, expert-in-the-loop evaluation. Benchmarking spatially aware clustering is challenging. SACCELERATOR is an open-source, extensible framework that formalizes expert-guided spatial clustering analysis.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":"23 9","pages":"1814-1826"},"PeriodicalIF":28.3,"publicationDate":"2026-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13541621/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148813568","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}