Nature Methods最新文献

Genetically encoded biosensor for fluorescence lifetime imaging of PTEN dynamics in the intact brain.

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-02-20 DOI: 10.1038/s41592-025-02610-9

Tomer Kagan, Matan Gabay, Aasha Meenakshisundaram, Yossi Levi, Sharbel Eid, Nikol Malchenko, Maya Maman, Anat Nitzan, Luca Ravotto, Ronen Zaidel-Bar, Britta Johanna Eickholt, Maayan Gal, Tal Laviv

{"title":"Genetically encoded biosensor for fluorescence lifetime imaging of PTEN dynamics in the intact brain.","authors":"Tomer Kagan, Matan Gabay, Aasha Meenakshisundaram, Yossi Levi, Sharbel Eid, Nikol Malchenko, Maya Maman, Anat Nitzan, Luca Ravotto, Ronen Zaidel-Bar, Britta Johanna Eickholt, Maayan Gal, Tal Laviv","doi":"10.1038/s41592-025-02610-9","DOIUrl":"https://doi.org/10.1038/s41592-025-02610-9","url":null,"abstract":"The phosphatase and tensin homolog (PTEN) is a vital protein that maintains an inhibitory brake for cellular proliferation and growth. Accordingly, PTEN loss-of-function mutations are associated with a broad spectrum of human pathologies. Despite its importance, there is currently no method to directly monitor PTEN activity with cellular specificity within intact biological systems. Here we describe the development of a FRET-based biosensor using PTEN conformation as a proxy for the PTEN activity state, for two-photon fluorescence lifetime imaging microscopy. We identify a point mutation that allows the monitoring of PTEN activity with minimal interference to endogenous PTEN signaling. We demonstrate imaging of PTEN activity in cell lines, intact Caenorhabditis elegans and in the mouse brain. Finally, we develop a red-shifted sensor variant that allows us to identify cell-type-specific PTEN activity in excitatory and inhibitory cortical cells. In summary, our approach enables dynamic imaging of PTEN activity in vivo with unprecedented spatial and temporal resolution.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":" ","pages":""},"PeriodicalIF":36.1,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143468633","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

Oblique line scan illumination enables expansive, accurate and sensitive single-protein measurements in solution and in living cells.

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-02-18 DOI: 10.1038/s41592-025-02594-6

Amine Driouchi, Mason Bretan, Brynmor J Davis, Alec Heckert, Markus Seeger, Maité Bradley Silva, William S R Forrest, Jessica Hsiung, Jiongyi Tan, Hongli Yang, David T McSwiggen, Linda Song, Askhay Sule, Behnam Abaie, Hanzhe Chen, Bryant Chhun, Brianna Conroy, Liam A Elliott, Eric Gonzalez, Fedor Ilkov, Joshua Isaacs, George Labaria, Michelle Lagana, DeLaine D Larsen, Brian Margolin, Mai K Nguyen, Eugene Park, Jeremy Rine, Yangzhong Tang, Martin Vana, Andrew Wilkey, Zhengjian Zhang, Stephen Basham, Jaclyn J Ho, Stephanie Johnson, Aaron A Klammer, Kevin Lin, Xavier Darzacq, Eric Betzig, Russell T Berman, Daniel J Anderson

{"title":"Oblique line scan illumination enables expansive, accurate and sensitive single-protein measurements in solution and in living cells.","authors":"Amine Driouchi, Mason Bretan, Brynmor J Davis, Alec Heckert, Markus Seeger, Maité Bradley Silva, William S R Forrest, Jessica Hsiung, Jiongyi Tan, Hongli Yang, David T McSwiggen, Linda Song, Askhay Sule, Behnam Abaie, Hanzhe Chen, Bryant Chhun, Brianna Conroy, Liam A Elliott, Eric Gonzalez, Fedor Ilkov, Joshua Isaacs, George Labaria, Michelle Lagana, DeLaine D Larsen, Brian Margolin, Mai K Nguyen, Eugene Park, Jeremy Rine, Yangzhong Tang, Martin Vana, Andrew Wilkey, Zhengjian Zhang, Stephen Basham, Jaclyn J Ho, Stephanie Johnson, Aaron A Klammer, Kevin Lin, Xavier Darzacq, Eric Betzig, Russell T Berman, Daniel J Anderson","doi":"10.1038/s41592-025-02594-6","DOIUrl":"https://doi.org/10.1038/s41592-025-02594-6","url":null,"abstract":"An ideal tool for the study of cellular biology would enable the measure of molecular activity nondestructively within living cells. Single-molecule localization microscopy (SMLM) techniques, such as single-molecule tracking (SMT), enable in situ measurements in cells but have historically been limited by a necessary tradeoff between spatiotemporal resolution and throughput. Here we address these limitations using oblique line scan (OLS), a robust single-objective light-sheet-based illumination and detection modality that achieves nanoscale spatial resolution and sub-millisecond temporal resolution across a large field of view. We show that OLS can be used to capture protein motion up to 14 μm2 s-1 in living cells. We further extend the utility of OLS with in-solution SMT for single-molecule measurement of ligand-protein interactions and disruption of protein-protein interactions using purified proteins. We illustrate the versatility of OLS by showcasing two-color SMT, STORM and single-molecule fluorescence recovery after photobleaching. OLS paves the way for robust, high-throughput, single-molecule investigations of protein function required for basic research, drug screening and systems biology studies.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":" ","pages":""},"PeriodicalIF":36.1,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143449582","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

MARBLE: interpretable representations of neural population dynamics using geometric deep learning.

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-02-17 DOI: 10.1038/s41592-024-02582-2

Adam Gosztolai, Robert L Peach, Alexis Arnaudon, Mauricio Barahona, Pierre Vandergheynst

{"title":"MARBLE: interpretable representations of neural population dynamics using geometric deep learning.","authors":"Adam Gosztolai, Robert L Peach, Alexis Arnaudon, Mauricio Barahona, Pierre Vandergheynst","doi":"10.1038/s41592-024-02582-2","DOIUrl":"https://doi.org/10.1038/s41592-024-02582-2","url":null,"abstract":"The dynamics of neuron populations commonly evolve on low-dimensional manifolds. Thus, we need methods that learn the dynamical processes over neural manifolds to infer interpretable and consistent latent representations. We introduce a representation learning method, MARBLE, which decomposes on-manifold dynamics into local flow fields and maps them into a common latent space using unsupervised geometric deep learning. In simulated nonlinear dynamical systems, recurrent neural networks and experimental single-neuron recordings from primates and rodents, we discover emergent low-dimensional latent representations that parametrize high-dimensional neural dynamics during gain modulation, decision-making and changes in the internal state. These representations are consistent across neural networks and animals, enabling the robust comparison of cognitive computations. Extensive benchmarking demonstrates state-of-the-art within- and across-animal decoding accuracy of MARBLE compared to current representation learning approaches, with minimal user input. Our results suggest that a manifold structure provides a powerful inductive bias to develop decoding algorithms and assimilate data across experiments.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":" ","pages":""},"PeriodicalIF":36.1,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143441476","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

The value of lab values.

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-02-17 DOI: 10.1038/s41592-025-02602-9

Vivien Marx

引用次数: 0

Interpreting and comparing neural activity across systems by geometric deep learning.

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-02-17 DOI: 10.1038/s41592-024-02581-3

引用次数: 0

Vector choices, vector surprises.

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-02-17 DOI: 10.1038/s41592-025-02609-2

Vivien Marx

引用次数: 0

Segment Anything for Microscopy.

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-02-12 DOI: 10.1038/s41592-024-02580-4

Anwai Archit, Luca Freckmann, Sushmita Nair, Nabeel Khalid, Paul Hilt, Vikas Rajashekar, Marei Freitag, Carolin Teuber, Genevieve Buckley, Sebastian von Haaren, Sagnik Gupta, Andreas Dengel, Sheraz Ahmed, Constantin Pape

引用次数: 0

Imaging of cellular dynamics from a whole organism to subcellular scale with self-driving, multiscale microscopy.

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-02-12 DOI: 10.1038/s41592-025-02598-2

Stephan Daetwyler, Hanieh Mazloom-Farsibaf, Felix Y Zhou, Dagan Segal, Etai Sapoznik, Bingying Chen, Jill M Westcott, Rolf A Brekken, Gaudenz Danuser, Reto Fiolka

引用次数: 0

Cellpose3: one-click image restoration for improved cellular segmentation.

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-02-12 DOI: 10.1038/s41592-025-02595-5

Carsen Stringer, Marius Pachitariu

引用次数: 0

Scalable co-sequencing of RNA and DNA from individual nuclei.

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-02-12 DOI: 10.1038/s41592-024-02579-x

Timothy R Olsen, Pranay Talla, Romella K Sagatelian, Julia Furnari, Jeffrey N Bruce, Peter Canoll, Shan Zha, Peter A Sims

引用次数: 0