NATURE METHODS 是一个发表新方法和显着改进生命科学中久经考验的基础研究技术的论坛。该月刊面向广泛的跨学科受众，包括积极参与实验室实践的学术和行业研究人员。它为他们提供了进行研究的新工具，并强调所提出的工作的直接实际相关性。该杂志发表主要研究论文以及最近技术和方法发展的概述。我们正在积极寻找与生物和生物医学科学相关的主要方法论文，包括以化学为基础的方法，这些方法在生物学问题的研究中具有实际应用。

NATURE METHODS is a journal dedicated to publishing new methods and significant improvements in established research techniques within the life sciences. This monthly publication targets a broad interdisciplinary audience, including academic and industry researchers actively engaged in laboratory practices. It provides researchers with new tools for conducting studies and emphasizes the direct practical relevance of the work presented. The journal publishes primary research articles as well as reviews on recent developments in technologies and methods. We are actively seeking major method papers related to biological and biomedical sciences, particularly those based on chemistry that have practical applications in the study of biological questions.

NATURE METHODS 是一个专注于发表生命科学领域新方法和显著改进的基础研究技术的期刊。该月刊面向广泛的跨学科受众，包括积极参与实验室实践的学术和行业研究人员。它为研究人员提供了新的研究工具，并强调所提出工作的直接实际相关性。该杂志发表主要研究论文以及最近技术和方法发展的综述。我们积极寻找与生物和生物医学科学相关的主要方法论文，特别是那些在生物学研究中具有实际应用的化学基础方法。

Nature Methods

Long-term visualization of the dynamic interactions between intracellular structures throughout the three-dimensional space of whole live cells is essential to better understand their functions, but this task remains challenging due to the limitations of existing three-dimensional fluorescence microscopy techniques, such as an insufficient axial resolution, low volumetric imaging rate and photobleaching. Here, we present the combination of a progressive deep-learning super-resolution strategy with a double-ring-modulated selective plane illumination microscopy design capable of visualizing the dynamics of intracellular structures in live cells for hours at an isotropic spatial resolution of roughly 100 nm in three dimensions at speeds up to roughly 17 Hz. Using this approach, we reveal the complex spatial relationships and interactions between endoplasmic reticulum (ER) and mitochondria throughout live cells, providing new insights into ER-mediated mitochondrial division. We also examined the motion of Drp1 oligomers involved in mitochondrial fission and revealed the dynamic interactions between Drp1 and mitochondria in three dimensions.

Yuxuan Zhao

Meng Zhang

Wenting Zhang

Yao Zhou

Longbiao Chen

Qing Liu

Peng Wang

Rong Chen

Xinxin Duan

Feifan Chen

Huan Deng

Yunfei Wei

Peng Fei

Yu-Hui Zhang

Nature methods

Nat Methods

Isotropic super-resolution light-sheet microscopy of dynamic intracellular structures at subsecond timescales.

Abstract Artificial intelligence-based protein structure prediction methods such as AlphaFold have revolutionized structural biology. The accuracies of these predictions vary, however, and they do not take into account ligands, covalent modifications or other environmental factors. Here, we evaluate how well AlphaFold predictions can be expected to describe the structure of a protein by comparing predictions directly with experimental crystallographic maps. In many cases, AlphaFold predictions matched experimental maps remarkably closely. In other cases, even very high-confidence predictions differed from experimental maps on a global scale through distortion and domain orientation, and on a local scale in backbone and side-chain conformation. We suggest considering AlphaFold predictions as exceptionally useful hypotheses. We further suggest that it is important to consider the confidence in prediction when interpreting AlphaFold predictions and to carry out experimental structure determination to verify structural details, particularly those that involve interactions not included in the prediction.

Thomas C. Terwilliger

Dorothee Liebschner

Tristan I. Croll

Christopher J. Williams

Airlie J. McCoy

Billy K. Poon

Pavel V. Afonine

Robert D. Oeffner

Jane S. Richardson

Randy J. Read

Paul D. Adams

AlphaFold predictions are valuable hypotheses and accelerate but do not replace experimental structure determination

Membrane proteins are a large, diverse group of proteins, serving a multitude of cellular functions. They are difficult to study because of their requirement of a lipid membrane for function. Here we show that two-photon polarization microscopy can take advantage of the cell membrane requirement to yield insights into membrane protein structure and function, in living cells and organisms. The technique allows sensitive imaging of G-protein activation, changes in intracellular calcium concentration and other processes, and is not limited to membrane proteins. Conveniently, many suitable probes for two-photon polarization microscopy already exist.

Josef Lazar

Alexey Bondar

Stepan Timr

Stuart J Firestein

Two-photon polarization microscopy reveals protein structure and function.

We demonstrate that a deep neural network can be trained to virtually refocus a two-dimensional fluorescence image onto user-defined three-dimensional (3D) surfaces within the sample. Using this method, termed Deep-Z, we imaged the neuronal activity of a Caenorhabditis elegans worm in 3D using a time sequence of fluorescence images acquired at a single focal plane, digitally increasing the depth-of-field by 20-fold without any axial scanning, additional hardware or a trade-off of imaging resolution and speed. Furthermore, we demonstrate that this approach can correct for sample drift, tilt and other aberrations, all digitally performed after the acquisition of a single fluorescence image. This framework also cross-connects different imaging modalities to each other, enabling 3D refocusing of a single wide-field fluorescence image to match confocal microscopy images acquired at different sample planes. Deep-Z has the potential to improve volumetric imaging speed while reducing challenges relating to sample drift, aberration and defocusing that are associated with standard 3D fluorescence microscopy.

Yichen Wu

Yair Rivenson

Hongda Wang

Yilin Luo

Eyal Ben-David

Laurent A Bentolila

Christian Pritz

Aydogan Ozcan

Three-dimensional virtual refocusing of fluorescence microscopy images using deep learning.

Functional ultrasound imaging and electroencephalography are combined to assess brain activity in mobile rats. The methodology is applied to the analysis of theta rhythms in a maze task and of epileptic seizures. We developed an integrated experimental framework that extends the brain exploration capabilities of functional ultrasound imaging to awake and mobile rats. In addition to acquiring hemodynamic data, this method further allows parallel access to electroencephalography (EEG) recordings of neuronal activity. We illustrate this approach with two proofs of concept: a behavioral study on theta rhythm activation in a maze running task and a disease-related study on spontaneous epileptic seizures.

Lim-Anna Sieu

Antoine Bergel

Elodie Tiran

Thomas Deffieux

Mathieu Pernot

Jean-Luc Gennisson

Mickaël Tanter

Ivan Cohen

EEG and functional ultrasound imaging in mobile rats

移动大鼠的脑电图和功能性超声成像

The rapid adoption of single-cell technologies has created an opportunity to build single-cell 'atlases' integrating diverse datasets across many laboratories. Such atlases can serve as a reference for analyzing and interpreting current and future data. However, it has become apparent that atlasing approaches differ, and the impact of these differences are often unclear. Here we review the current atlasing literature and present considerations for building and using atlases. Importantly, we find that no one-size-fits-all protocol for atlas building exists, but rather we discuss context-specific considerations and workflows, including atlas conceptualization, data collection, curation and integration, atlas evaluation and atlas sharing. We further highlight the benefits of integrated atlases for analyses of new datasets and deriving biological insights beyond what is possible from individual datasets. Our overview of current practices and associated recommendations will improve the quality of atlases to come, facilitating the shift to a unified, reference-based understanding of single-cell biology.

Karin Hrovatin

Lisa Sikkema

Vladimir A. Shitov

Graham Heimberg

Maiia Shulman

Amanda J. Oliver

Michaela F. Mueller

Ignacio L. Ibarra

Hanchen Wang

Ciro Ramírez-Suástegui

Peng He

Anna C. Schaar

Sarah A. Teichmann

Fabian J. Theis

Malte D. Luecken

Considerations for building and using integrated single-cell atlases

构建和使用综合单细胞图谱的考虑因素

To understand gene function, it is necessary to compare cells carrying the mutated target gene with normal cells. In most biomedical studies, the cells being compared are in different mutant and control animals and, therefore, do not experience the same epigenetic changes and tissue microenvironment. The experimental induction of genetic mosaics is essential to determine a gene cell-autonomous function and to model the etiology of diseases caused by somatic mutations. Current technologies used to induce genetic mosaics in mice lack either accuracy, throughput or barcoding diversity. Here we present the iFlpMosaics toolkit comprising a large set of new genetic tools and mouse lines that enable recombinase-dependent ratiometric induction and single-cell clonal tracking of multiple fluorescently labeled wild-type and Cre-mutant cells within the same time window and tissue microenvironment. The labeled cells can be profiled by multispectral imaging or by fluorescence-activated flow cytometry and single-cell RNA sequencing. iFlpMosaics facilitate the induction and analysis of genetic mosaics in any quiescent or progenitor cell, and for any given single or combination of floxed genes, thus enabling a more accurate understanding of how induced genetic mutations affect the biology of single cells during tissue development, homeostasis and disease. iFlpMosaics are a compendium of mouse lines and genetic tools for tissue-agnostic generation and analysis of genetic mosaics.

Irene Garcia-Gonzalez

Stefano Gambera

Susana F. Rocha

Alvaro Regano

Lourdes Garcia-Ortega

Mariya Lytvyn

Luis Diago-Domingo

Maria S. Sanchez-Muñoz

Aroa Garcia-Cabero

Ivana Zagorac

Wen Luo

Macarena De Andrés-Laguillo

Macarena Fernández-Chacón

Verónica Casquero-Garcia

Federica Francesca Lunella

Carlos Torroja

Fátima Sánchez-Cabo

Rui Benedito

iFlpMosaics enable the multispectral barcoding and high-throughput comparative analysis of mutant and wild-type cells

iFlpMosaics 实现突变型与野生型细胞的多光谱条形码标记与高通量比较分析

Srijit Seal

Maria-Anna Trapotsi

Ola Spjuth

Shantanu Singh

Jordi Carreras-Puigvert

Nigel Greene

Andreas Bender

Anne E. Carpenter

Author Correction: Cell Painting: a decade of discovery and innovation in cellular imaging

作者勘误：细胞绘画：细胞成像领域十年发现与创新

Abstract Due to technical roadblocks, it is unclear how visual circuits represent multiple features or how behaviorally relevant representations are selected for long-term memory. Here we developed Moculus, a head-mounted virtual reality platform for mice that covers the entire visual field, and allows binocular depth perception and full visual immersion. This controllable environment, with three-dimensional (3D) corridors and 3D objects, in combination with 3D acousto-optical imaging, affords rapid visual learning and the uncovering of circuit substrates in one measurement session. Both the control and reinforcement-associated visual cue coding neuronal assemblies are transiently expanded by reinforcement feedback to near-saturation levels. This increases computational capability and allows competition among assemblies that encode behaviorally relevant information. The coding assemblies form partially orthogonal and overlapping clusters centered around hub cells with higher and earlier ramp-like responses, as well as locally increased functional connectivity.

Linda Judák

Gergely Dobos

Katalin Ócsai

Eszter Báthory

Huba Szebik

Balázs Tarján

Pál Maák

Zoltán Szadai

István Takács

Balázs Chiovini

Tibor Lőrincz

Áron Szepesi

Botond Roska

Gergely Szalay

Balázs Rózsa

Moculus: an immersive virtual reality system for mice incorporating stereo vision

Moculus：一种结合立体视觉的沉浸式虚拟现实系统，用于小鼠

Abstract Small-animal virtual reality (VR) systems have become invaluable tools in neuroscience for studying complex behavior during head-fixed neural recording, but they lag behind commercial human VR systems in terms of miniaturization, immersivity and advanced features such as eye tracking. Here we present MouseGoggles, a miniature VR headset for head-fixed mice that delivers independent, binocular visual stimulation over a wide field of view while enabling eye tracking and pupillometry in VR. Neural recordings in the visual cortex validate the quality of image presentation, while hippocampal recordings, associative reward learning and innate fear responses to virtual looming stimuli demonstrate an immersive VR experience. Our open-source system’s simplicity and compact size will enable the broader adoption of VR methods in neuroscience.

Matthew Isaacson

Hongyu Chang

Laura Berkowitz

Rick Zirkel

Yusol Park

Danyu Hu

Ian Ellwood

Chris B. Schaffer

MouseGoggles: an immersive virtual reality headset for mouse neuroscience and behavior

MouseGoggles：用于小鼠神经科学与行为学的沉浸式虚拟现实头戴设备

短名	Nat Methods
Journal Impact	36.09
国际分区	BIOCHEMICAL RESEARCH METHODS(Q1)
期刊索引	SCI Q1中科院 1 区

ISSN	1548-7091, 1548-7105
h-index	388
国内分区	生物学(1区)生物学生化研究方法(1区)
Top 期刊	是

涉及主题	生物计算生物学化学遗传学生物化学计算机科学基因物理细胞生物学医学
出版信息	出版商: Nature Research，出版周期: Monthly，期刊类型: journal，开源期刊: 否
基本数据	创刊年份: 2004，原创研究文献占比: 97.96%，自引率:2.80%， Gold OA占比: 33.54%
平均审稿周期	网友分享经验：平均1.0个月
平均录用比例	网友分享经验：极难

Nature Methods

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