Nature MethodsPub Date : 2026-08-31DOI: 10.1038/s41592-026-03196-6
Wei Guo (, ), Lely Feletti, Aleksandra Radenovic
{"title":"SPIFFI enables single-shot super-resolution and multidimensional imaging","authors":"Wei Guo \u0000 (, ), Lely Feletti, 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}
Nature MethodsPub Date : 2026-08-31DOI: 10.1038/s41592-026-03195-7
{"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}
Nature MethodsPub Date : 2026-08-31DOI: 10.1038/s41592-026-03226-3
Juan José Montero, Riccardo Trozzo, Roland Rad
{"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}
Nature MethodsPub Date : 2026-08-28DOI: 10.1038/s41592-026-03214-7
Jean-Luc Pellequer, Sebastian Aguayo, Andrea Alessandrini, David Alsteens, Toshio Ando, Audrey Beaussart, Michael Betton, Timo Betz, Kerstin G. Blank, Simone Bovio, Clément Campillo, Claudio Canale, Alexander X. Cartagena-Rivera, Filomena A. Carvalho, Ignacio Casuso, Guillaume Charras, Marti Checa, Liam Collins, Adai Colom, Luca Costa, Etienne Dague, Tanya E. S. Dahms, Pedro Jose de Pablo, Alexandra Delvallée, Simone Dinarelli, Lorna Dougan, Yves F. Dufrêne, Andra C. Dumitru, Yuri M. Efremov, Sofiane El-Kirat-Chatel, Paolo Facci, Georg E. Fantner, Amir Farokh Payam, Cécile Feuillie, Cristina Flors, Nancy Forde, Cécile Formosa-Dague, Gregory Francius, Clemens M. Franz, Kristian Franze, Ricardo Garcia, Sergi Garcia-Manyes, Núria Gavara, Marina I. Giannotti, Marco Girasole, Martin Guthold, George R. Heath, Céline Heu, Peter Hinterdorfer, Jamie K. Hobbs, Bart W. Hoogenboom, Sébastien Janel, Miklós Kellermayer, Petr Klapetek, Noriyuki Kodera, Melanie Koehler, Frank Lafont, Guillaume Lamour, Jessem Landoulsi, Valérie M. Laurent, Philippe Leclère, Malgorzata Lekka, Hongbin Li, Giovanni Longo, Arin Marchesi, Marion Mathelié-Guinlet, Gerald A. Meininger, Ioanna Mela, Pierre-Emmanuel Milhiet, Ruben Millan-Solsona, Tea Mišić Radić, Michaël Molinari, Fernando Moreno-Herrero, Michael A. Nash, Olivier Noël, Yoo Jin Oh, Laia Pasquina-Lemonche, Shivprasad Patil, Patricia Pedraz, Ana Paula Pêgo, Thomas T. Perkins, Martin Pesl, Tri Thanh Pham, Laura Picas, Alessandro Podestà, Johannes Preiner, Jan Přibyl, Roger Proksch, Pierre-Henri Puech, Alice L. B. Pyne, Manfred Radmacher, Lorena Redondo-Morata, Felix Rico, Wouter H. Roos, Robert Ros, Nuno C. Santos, Ugis Sarkans, Tilman E. Schäffer, Hermann Schillers, Zhifeng Shao, Delphine Sicard, Adam Cohen Simonsen, Igor Sokolov, Susana R. Sousa, Bjørn T. Stokke, Andreas Stylianou, Marek Szymonski, Florence Tama, Neil H. Thomson, Takayuki Uchihashi, Massimo Vassalli, Claude Verdier, Anthony Vial, Véronique Vié, Tomaso Zambelli, Renato Zenobi, Peng Zheng, Claire Valotteau
{"title":"A FAIR road to a bioAFM databank","authors":"Jean-Luc Pellequer, Sebastian Aguayo, Andrea Alessandrini, David Alsteens, Toshio Ando, Audrey Beaussart, Michael Betton, Timo Betz, Kerstin G. Blank, Simone Bovio, Clément Campillo, Claudio Canale, Alexander X. Cartagena-Rivera, Filomena A. Carvalho, Ignacio Casuso, Guillaume Charras, Marti Checa, Liam Collins, Adai Colom, Luca Costa, Etienne Dague, Tanya E. S. Dahms, Pedro Jose de Pablo, Alexandra Delvallée, Simone Dinarelli, Lorna Dougan, Yves F. Dufrêne, Andra C. Dumitru, Yuri M. Efremov, Sofiane El-Kirat-Chatel, Paolo Facci, Georg E. Fantner, Amir Farokh Payam, Cécile Feuillie, Cristina Flors, Nancy Forde, Cécile Formosa-Dague, Gregory Francius, Clemens M. Franz, Kristian Franze, Ricardo Garcia, Sergi Garcia-Manyes, Núria Gavara, Marina I. Giannotti, Marco Girasole, Martin Guthold, George R. Heath, Céline Heu, Peter Hinterdorfer, Jamie K. Hobbs, Bart W. Hoogenboom, Sébastien Janel, Miklós Kellermayer, Petr Klapetek, Noriyuki Kodera, Melanie Koehler, Frank Lafont, Guillaume Lamour, Jessem Landoulsi, Valérie M. Laurent, Philippe Leclère, Malgorzata Lekka, Hongbin Li, Giovanni Longo, Arin Marchesi, Marion Mathelié-Guinlet, Gerald A. Meininger, Ioanna Mela, Pierre-Emmanuel Milhiet, Ruben Millan-Solsona, Tea Mišić Radić, Michaël Molinari, Fernando Moreno-Herrero, Michael A. Nash, Olivier Noël, Yoo Jin Oh, Laia Pasquina-Lemonche, Shivprasad Patil, Patricia Pedraz, Ana Paula Pêgo, Thomas T. Perkins, Martin Pesl, Tri Thanh Pham, Laura Picas, Alessandro Podestà, Johannes Preiner, Jan Přibyl, Roger Proksch, Pierre-Henri Puech, Alice L. B. Pyne, Manfred Radmacher, Lorena Redondo-Morata, Felix Rico, Wouter H. Roos, Robert Ros, Nuno C. Santos, Ugis Sarkans, Tilman E. Schäffer, Hermann Schillers, Zhifeng Shao, Delphine Sicard, Adam Cohen Simonsen, Igor Sokolov, Susana R. Sousa, Bjørn T. Stokke, Andreas Stylianou, Marek Szymonski, Florence Tama, Neil H. Thomson, Takayuki Uchihashi, Massimo Vassalli, Claude Verdier, Anthony Vial, Véronique Vié, Tomaso Zambelli, Renato Zenobi, Peng Zheng, 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}
Nature MethodsPub Date : 2026-08-27DOI: 10.1038/s41592-026-03180-0
Yajuan Li, Zhaojun Zhang, Archibald Enninful, Negin Farzad, Presha Rajbhandari, Hua Tian, Jungmin Nam, Xiaoyu Qin, Jorge Villazon, Anthony A. Fung, Hongje Jang, Zhiliang Bai, Nancy R. Zhang, Brent R. Stockwell, Rong Fan, Mina L. Xu, Zongming Ma, Lingyan Shi
{"title":"All-optical multimodal mapping of single-cell-type-specific metabolic activities via REDCAT","authors":"Yajuan Li, Zhaojun Zhang, Archibald Enninful, Negin Farzad, Presha Rajbhandari, Hua Tian, Jungmin Nam, Xiaoyu Qin, Jorge Villazon, Anthony A. Fung, Hongje Jang, Zhiliang Bai, Nancy R. Zhang, Brent R. Stockwell, Rong Fan, Mina L. Xu, Zongming Ma, 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}
Nature MethodsPub Date : 2026-08-27DOI: 10.1038/s41592-026-03181-z
{"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}
Nature MethodsPub Date : 2026-08-24DOI: 10.1038/s41592-026-03194-8
Jieran Sun, Kirti Biharie, Peiying Cai, Niklas Müller-Bötticher, Paul Kiessling, Meghan A. Turner, Søren Helweg Dam, Florian Heyl, Sarusan Kathirchelvan, Martin Emons, Samuel Gunz, Sven Twardziok, Amin El-Heliebi, Martin Zacharias, SpaceHack 2.0 participants, Roland Eils, Marcel Reinders, Raphael Gottardo, Christoph Kuppe, Brian Long, Ahmed Mahfouz, Mark D. Robinson, Naveed Ishaque
{"title":"Beyond benchmarking: an expert-guided consensus approach to spatially aware clustering","authors":"Jieran Sun, Kirti Biharie, Peiying Cai, Niklas Müller-Bötticher, Paul Kiessling, Meghan A. Turner, Søren Helweg Dam, Florian Heyl, Sarusan Kathirchelvan, Martin Emons, Samuel Gunz, Sven Twardziok, Amin El-Heliebi, Martin Zacharias, SpaceHack 2.0 participants, Roland Eils, Marcel Reinders, Raphael Gottardo, Christoph Kuppe, Brian Long, Ahmed Mahfouz, Mark D. Robinson, 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}
Nature MethodsPub Date : 2026-08-24DOI: 10.1038/s41592-026-03193-9
{"title":"Benchmark pitfalls expose need for expert-guided spatial clustering","authors":"","doi":"10.1038/s41592-026-03193-9","DOIUrl":"10.1038/s41592-026-03193-9","url":null,"abstract":"Benchmarking computational tools for cutting-edge technologies such as spatially resolved transcriptomics is challenging owing to the lack of reproducibility, of data and of evaluation strategies that are faithful to multiscale spatial biology. However, we found that complementing computational consensus strategies with feedback from histology and cell biology experts circumvents these limitations to accelerate biological discovery.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":"23 9","pages":"1693-1694"},"PeriodicalIF":28.3,"publicationDate":"2026-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148813615","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}
Nature MethodsPub Date : 2026-08-24DOI: 10.1038/s41592-026-03184-w
Matthew C. Jenkins, Daija Bobe, Jake D. Johnston, Jonah Cheung, Akira Karasawa, Christina M. Zimanyi, Ömer Dermanci, Collin T. McManus, M. G. Finn, Alex de Marco, Mykhailo Kopylov
{"title":"Overcoming air–water interface-induced artifacts in cryo-EM with protein nanocrates","authors":"Matthew C. Jenkins, Daija Bobe, Jake D. Johnston, Jonah Cheung, Akira Karasawa, Christina M. Zimanyi, Ömer Dermanci, Collin T. McManus, M. G. Finn, Alex de Marco, Mykhailo Kopylov","doi":"10.1038/s41592-026-03184-w","DOIUrl":"10.1038/s41592-026-03184-w","url":null,"abstract":"Contact with the air–water interface can bias the orientation of macromolecules during cryo-electron microscopy sample preparation, leading to uneven sample distribution, preferred orientation and damage to the molecules of interest. To prevent this, we describe a method to encapsulate target proteins within highly hydrophilic, structurally homogeneous and stable protein shells, which we refer to as ‘nanocrates’ for this purpose. Here we describe the packaging, data acquisition and reconstruction of three proof-of-principle examples, each illuminating a different aspect of the method: apoferritin (demonstrating high-resolution), thyroglobulin (solving a known preferred orientation problem) and 7,8-dihydroneopterin aldolase (a structure previously uncharacterized by cryo-electron microscopy). MS2 bacteriophage-derived protein shells called ‘nanocrates’ help address the air–water interface-induced artifacts in cryo-EM structure determination by encapsulating target proteins and enabling them to randomly orient at the air–water interface.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":"23 9","pages":"1798-1804"},"PeriodicalIF":28.3,"publicationDate":"2026-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148813572","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}