Nature Methods最新文献_第8页

Transcriptome-wide and single-base m⁶A quantification with ultra-low RNA input. 转录组范围和单碱基m6A定量与超低RNA输入。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-06-01 DOI: 10.1038/s41592-025-02681-8

引用次数: 0

Light-microscopy-based connectomics. Light-microscopy-based——神经。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-06-01 DOI: 10.1038/s41592-025-02732-0

Nina Vogt

引用次数: 0

Mapping effective connectivity by virtually perturbing a surrogate brain. 通过干扰替代大脑来绘制有效连接图。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-06-01 Epub Date: 2025-04-22 DOI: 10.1038/s41592-025-02654-x

Zixiang Luo, Kaining Peng, Zhichao Liang, Shengyuan Cai, Chenyu Xu, Dan Li, Yu Hu, Changsong Zhou, Quanying Liu

{"title":"Mapping effective connectivity by virtually perturbing a surrogate brain.","authors":"Zixiang Luo, Kaining Peng, Zhichao Liang, Shengyuan Cai, Chenyu Xu, Dan Li, Yu Hu, Changsong Zhou, Quanying Liu","doi":"10.1038/s41592-025-02654-x","DOIUrl":"10.1038/s41592-025-02654-x","url":null,"abstract":"Effective connectivity (EC), which reflects the causal interactions between brain regions, is fundamental to understanding information processing in the brain; however, traditional methods for obtaining EC, which rely on neural responses to stimulation, are often invasive or limited in spatial coverage, making them unsuitable for whole-brain EC mapping in humans. Here, to address this gap, we introduce Neural Perturbational Inference (NPI), a data-driven framework for mapping whole-brain EC. NPI employs an artificial neural network trained to model large-scale neural dynamics, serving as a computational surrogate of the brain. By systematically perturbing all regions in the surrogate brain and analyzing the resulting responses in other regions, NPI maps the directionality, strength and excitatory/inhibitory properties of brain-wide EC. Validation of NPI on generative models with known ground-truth EC demonstrates its superiority over existing methods such as Granger causality and dynamic causal modeling. When applied to resting-state functional magnetic resonance imaging data across diverse datasets, NPI reveals consistent, structurally supported EC patterns. Furthermore, comparisons with cortico-cortical evoked potential data show a strong resemblance between NPI-inferred EC and real stimulation propagation patterns. By transitioning from correlational to causal understandings of brain functionality, NPI marks a stride in decoding the brain's functional architecture and facilitating both neuroscience studies and clinical applications.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":" ","pages":"1376-1385"},"PeriodicalIF":36.1,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143982102","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

Extended culture of 2D gastruloids to model human mesoderm development. 二维类胃细胞扩展培养以模拟人类中胚层发育。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-06-01 Epub Date: 2025-05-07 DOI: 10.1038/s41592-025-02669-4

Bohan Chen, Hina Khan, Zhiyuan Yu, LiAng Yao, Emily Freeburne, Kyoung Jo, Craig Johnson, Idse Heemskerk

{"title":"Extended culture of 2D gastruloids to model human mesoderm development.","authors":"Bohan Chen, Hina Khan, Zhiyuan Yu, LiAng Yao, Emily Freeburne, Kyoung Jo, Craig Johnson, Idse Heemskerk","doi":"10.1038/s41592-025-02669-4","DOIUrl":"10.1038/s41592-025-02669-4","url":null,"abstract":"Micropatterned human pluripotent stem cells treated with BMP4 (two-dimensional (2D) gastruloids) are among the most widely used stem cell models for human gastrulation. Due to its simplicity and reproducibility, this system is ideal for high-throughput quantitative studies of tissue patterning and has led to many insights into the mechanisms of mammalian gastrulation. However, 2D gastruloids have been studied only up to about 2 days owing to a loss of organization beyond this time with earlier protocols. Here we report an extended 2D gastruloid model to up to 10 days. We discovered a phase of highly reproducible morphogenesis between 2 and 4 days during which directed migration from the primitive streak-like region gives rise to a mesodermal layer beneath an epiblast-like layer. Multiple types of mesoderm arise with striking spatial organization including lateral plate mesoderm-like cells on the colony border and paraxial mesoderm-like cells further inside the colony. Single-cell transcriptomics showed strong similarity of these cells to mesoderm in human and nonhuman primate embryos. Our results illustrate that extended culture of 2D gastruloids provides a powerful model for human mesoderm differentiation and morphogenesis.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":" ","pages":"1355-1365"},"PeriodicalIF":36.1,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144037048","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

Methods for multiplexing single-cell multi-omics. 单细胞多组学多路复用方法。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-06-01 DOI: 10.1038/s41592-025-02657-8

Laura C Kida, Caleb A Lareau

引用次数: 0

Challenges of microscopy technology dissemination to resource-constrained communities. 显微镜技术向资源受限社区传播的挑战。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-05-06 DOI: 10.1038/s41592-025-02690-7

Jesse S Aaron, Caron A Jacobs, Leonel Malacrida, Antje Keppler, Paul French, Daniel A Fletcher, Christopher Wood, Claire M Brown, Graham D Wright, Satoshi Ogawa, Mahmoud Maina, Teng-Leong Chew

引用次数: 0

Deep learning-assisted analysis of single-particle tracking for automated correlation between diffusion and function. 深度学习辅助的单粒子跟踪分析，用于扩散和函数之间的自动关联。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-05-01 Epub Date: 2025-05-08 DOI: 10.1038/s41592-025-02665-8

Jacob Kæstel-Hansen, Marilina de Sautu, Anand Saminathan, Gustavo Scanavachi, Ricardo F Bango Da Cunha Correia, Annette Juma Nielsen, Sara Vogt Bleshøy, Konstantinos Tsolakidis, Wouter Boomsma, Tomas Kirchhausen, Nikos S Hatzakis

{"title":"Deep learning-assisted analysis of single-particle tracking for automated correlation between diffusion and function.","authors":"Jacob Kæstel-Hansen, Marilina de Sautu, Anand Saminathan, Gustavo Scanavachi, Ricardo F Bango Da Cunha Correia, Annette Juma Nielsen, Sara Vogt Bleshøy, Konstantinos Tsolakidis, Wouter Boomsma, Tomas Kirchhausen, Nikos S Hatzakis","doi":"10.1038/s41592-025-02665-8","DOIUrl":"https://doi.org/10.1038/s41592-025-02665-8","url":null,"abstract":"Subcellular diffusion in living systems reflects cellular processes and interactions. Recent advances in optical microscopy allow the tracking of this nanoscale diffusion of individual objects with unprecedented precision. However, the agnostic and automated extraction of functional information from the diffusion of molecules and organelles within the subcellular environment is labor intensive and poses a significant challenge. Here we introduce DeepSPT, a deep learning framework integrated in an analysis software, to interpret the diffusional two- or three-dimensional temporal behavior of objects in a rapid and efficient manner, agnostically. Demonstrating its versatility, we have applied DeepSPT to automated mapping of the early events of viral infections, identifying endosomal organelles, clathrin-coated pits and vesicles among others with F1 scores of 81%, 82% and 95%, respectively, and within seconds instead of weeks. The fact that DeepSPT effectively extracts biological information from diffusion alone illustrates that besides structure, motion encodes function at the molecular and subcellular level.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":"22 5","pages":"1091-1100"},"PeriodicalIF":36.1,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144034068","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

Illuminating life processes by vibrational probes. 用振动探测器照亮生命过程。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-05-01 Epub Date: 2025-05-13 DOI: 10.1038/s41592-025-02689-0

Naixin Qian, Zhilun Zhao, Elsy El Khoury, Xin Gao, Carli Canela, Yihui Shen, Lingyan Shi, Lixue Shi, Fanghao Hu, Lu Wei, Wei Min

引用次数: 0

scMultiSim: simulation of single-cell multi-omics and spatial data guided by gene regulatory networks and cell-cell interactions. scMultiSim：由基因调控网络和细胞-细胞相互作用引导的单细胞多组学和空间数据模拟。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-05-01 Epub Date: 2025-04-17 DOI: 10.1038/s41592-025-02651-0

Hechen Li, Ziqi Zhang, Michael Squires, Xi Chen, Xiuwei Zhang

{"title":"scMultiSim: simulation of single-cell multi-omics and spatial data guided by gene regulatory networks and cell-cell interactions.","authors":"Hechen Li, Ziqi Zhang, Michael Squires, Xi Chen, Xiuwei Zhang","doi":"10.1038/s41592-025-02651-0","DOIUrl":"10.1038/s41592-025-02651-0","url":null,"abstract":"Simulated single-cell data are essential for designing and evaluating computational methods in the absence of experimental ground truth. Here we present scMultiSim, a comprehensive simulator that generates multimodal single-cell data encompassing gene expression, chromatin accessibility, RNA velocity and spatial cell locations while accounting for the relationships between modalities. Unlike existing tools that focus on limited biological factors, scMultiSim simultaneously models cell identity, gene regulatory networks, cell-cell interactions and chromatin accessibility while incorporating technical noise. Moreover, it allows users to adjust each factor's effect easily. Here we show that scMultiSim generates data with expected biological effects, and demonstrate its applications by benchmarking a wide range of computational tasks, including multimodal and multi-batch data integration, RNA velocity estimation, gene regulatory network inference and cell-cell interaction inference using spatially resolved gene expression data. Compared to existing simulators, scMultiSim can benchmark a much broader range of existing computational problems and even new potential tasks.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":"22 5","pages":"982-993"},"PeriodicalIF":36.1,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12226025/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144028492","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

Capturing more than meets the eye. 捕捉比表面更多的东西。

IF 36.1 1区生物学

Nature Methods Pub Date : 2025-05-01 DOI: 10.1038/s41592-025-02714-2

引用次数: 0