Nature Methods最新文献_第7页

EvoAI enables extreme compression and reconstruction of the protein sequence space. EvoAI 实现了蛋白质序列空间的极度压缩和重建。

IF 36.1 1区生物学

Nature Methods Pub Date : 2024-11-11 DOI: 10.1038/s41592-024-02504-2

Ziyuan Ma, Wenjie Li, Yunhao Shen, Yunxin Xu, Gengjiang Liu, Jiamin Chang, Zeju Li, Hong Qin, Boxue Tian, Haipeng Gong, David R Liu, B W Thuronyi, Christopher A Voigt, Shuyi Zhang

{"title":"EvoAI enables extreme compression and reconstruction of the protein sequence space.","authors":"Ziyuan Ma, Wenjie Li, Yunhao Shen, Yunxin Xu, Gengjiang Liu, Jiamin Chang, Zeju Li, Hong Qin, Boxue Tian, Haipeng Gong, David R Liu, B W Thuronyi, Christopher A Voigt, Shuyi Zhang","doi":"10.1038/s41592-024-02504-2","DOIUrl":"10.1038/s41592-024-02504-2","url":null,"abstract":"Designing proteins with improved functions requires a deep understanding of how sequence and function are related, a vast space that is hard to explore. The ability to efficiently compress this space by identifying functionally important features is extremely valuable. Here we establish a method called EvoScan to comprehensively segment and scan the high-fitness sequence space to obtain anchor points that capture its essential features, especially in high dimensions. Our approach is compatible with any biomolecular function that can be coupled to a transcriptional output. We then develop deep learning and large language models to accurately reconstruct the space from these anchors, allowing computational prediction of novel, highly fit sequences without prior homology-derived or structural information. We apply this hybrid experimental-computational method, which we call EvoAI, to a repressor protein and find that only 82 anchors are sufficient to compress the high-fitness sequence space with a compression ratio of 1048. The extreme compressibility of the space informs both applied biomolecular design and understanding of natural evolution.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":" ","pages":""},"PeriodicalIF":36.1,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142624356","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

ONIX: a unified open-source platform for multimodal neural recording and perturbation during naturalistic behavior. ONIX：在自然行为过程中进行多模态神经记录和扰动的统一开源平台。

IF 36.1 1区生物学

Nature Methods Pub Date : 2024-11-11 DOI: 10.1038/s41592-024-02521-1

Jonathan P Newman, Jie Zhang, Aarón Cuevas-López, Nicholas J Miller, Takato Honda, Marie-Sophie H van der Goes, Alexandra H Leighton, Filipe Carvalho, Gonçalo Lopes, Anna Lakunina, Joshua H Siegle, Mark T Harnett, Matthew A Wilson, Jakob Voigts

{"title":"ONIX: a unified open-source platform for multimodal neural recording and perturbation during naturalistic behavior.","authors":"Jonathan P Newman, Jie Zhang, Aarón Cuevas-López, Nicholas J Miller, Takato Honda, Marie-Sophie H van der Goes, Alexandra H Leighton, Filipe Carvalho, Gonçalo Lopes, Anna Lakunina, Joshua H Siegle, Mark T Harnett, Matthew A Wilson, Jakob Voigts","doi":"10.1038/s41592-024-02521-1","DOIUrl":"10.1038/s41592-024-02521-1","url":null,"abstract":"Behavioral neuroscience faces two conflicting demands: long-duration recordings from large neural populations and unimpeded animal behavior. To meet this challenge we developed ONIX, an open-source data acquisition system with high data throughput (2 GB s-1) and low closed-loop latencies (<1 ms) that uses a 0.3-mm thin tether to minimize behavioral impact. Head position and rotation are tracked in three dimensions and used to drive active commutation without torque measurements. ONIX can acquire data from combinations of passive electrodes, Neuropixels probes, head-mounted microscopes, cameras, three-dimensional trackers and other data sources. We performed uninterrupted, long (~7 h) neural recordings in mice as they traversed complex three-dimensional terrain, and multiday sleep-tracking recordings (~55 h). ONIX enabled exploration with similar mobility as nonimplanted animals, in contrast to conventional tethered systems, which have restricted movement. By combining long recordings with full mobility, our technology will enable progress on questions that require high-quality neural recordings during ethologically grounded behaviors.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":" ","pages":""},"PeriodicalIF":36.1,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142624365","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

Single-molecule dynamic structural biology with vertically arranged DNA on a fluorescence microscope. 荧光显微镜上垂直排列 DNA 的单分子动态结构生物学。

IF 36.1 1区生物学

Nature Methods Pub Date : 2024-11-08 DOI: 10.1038/s41592-024-02498-x

Alan M Szalai, Giovanni Ferrari, Lars Richter, Jakob Hartmann, Merve-Zeynep Kesici, Bosong Ji, Kush Coshic, Martin R J Dagleish, Annika Jaeger, Aleksei Aksimentiev, Ingrid Tessmer, Izabela Kamińska, Andrés M Vera, Philip Tinnefeld

{"title":"Single-molecule dynamic structural biology with vertically arranged DNA on a fluorescence microscope.","authors":"Alan M Szalai, Giovanni Ferrari, Lars Richter, Jakob Hartmann, Merve-Zeynep Kesici, Bosong Ji, Kush Coshic, Martin R J Dagleish, Annika Jaeger, Aleksei Aksimentiev, Ingrid Tessmer, Izabela Kamińska, Andrés M Vera, Philip Tinnefeld","doi":"10.1038/s41592-024-02498-x","DOIUrl":"10.1038/s41592-024-02498-x","url":null,"abstract":"The intricate interplay between DNA and proteins is key for biological functions such as DNA replication, transcription and repair. Dynamic nanoscale observations of DNA structural features are necessary for understanding these interactions. Here we introduce graphene energy transfer with vertical nucleic acids (GETvNA), a method to investigate DNA-protein interactions that exploits the vertical orientation adopted by double-stranded DNA on graphene. This approach enables the dynamic study of DNA conformational changes via energy transfer from a probe dye to graphene, achieving spatial resolution down to the Ångström scale at subsecond temporal resolution. We measured DNA bending induced by adenine tracts, bulges, abasic sites and the binding of endonuclease IV. In addition, we observed the translocation of the O6-alkylguanine DNA alkyltransferase on DNA, reaching single base-pair resolution and detecting preferential binding to adenine tracts. This method promises widespread use for dynamical studies of nucleic acids and nucleic acid-protein interactions with resolution so far reserved for traditional structural biology techniques.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":" ","pages":""},"PeriodicalIF":36.1,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142624369","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

Induced pluripotent stem cell-derived cardiomyocyte in vitro models: benchmarking progress and ongoing challenges. 诱导多能干细胞衍生心肌细胞体外模型：基准进展与持续挑战。

IF 36.1 1区生物学

Nature Methods Pub Date : 2024-11-08 DOI: 10.1038/s41592-024-02480-7

Jourdan K Ewoldt, Samuel J DePalma, Maggie E Jewett, M Çağatay Karakan, Yih-Mei Lin, Paria Mir Hashemian, Xining Gao, Lihua Lou, Micheal A McLellan, Jonathan Tabares, Marshall Ma, Adriana C Salazar Coariti, Jin He, Kimani C Toussaint, Thomas G Bifano, Sharan Ramaswamy, Alice E White, Arvind Agarwal, Emma Lejeune, Brendon M Baker, Christopher S Chen

{"title":"Induced pluripotent stem cell-derived cardiomyocyte in vitro models: benchmarking progress and ongoing challenges.","authors":"Jourdan K Ewoldt, Samuel J DePalma, Maggie E Jewett, M Çağatay Karakan, Yih-Mei Lin, Paria Mir Hashemian, Xining Gao, Lihua Lou, Micheal A McLellan, Jonathan Tabares, Marshall Ma, Adriana C Salazar Coariti, Jin He, Kimani C Toussaint, Thomas G Bifano, Sharan Ramaswamy, Alice E White, Arvind Agarwal, Emma Lejeune, Brendon M Baker, Christopher S Chen","doi":"10.1038/s41592-024-02480-7","DOIUrl":"https://doi.org/10.1038/s41592-024-02480-7","url":null,"abstract":"Recent innovations in differentiating cardiomyocytes from human induced pluripotent stem cells (hiPSCs) have unlocked a viable path to creating in vitro cardiac models. Currently, hiPSC-derived cardiomyocytes (hiPSC-CMs) remain immature, leading many in the field to explore approaches to enhance cell and tissue maturation. Here, we systematically analyzed 300 studies using hiPSC-CM models to determine common fabrication, maturation and assessment techniques used to evaluate cardiomyocyte functionality and maturity and compiled the data into an open-access database. Based on this analysis, we present the diversity of, and current trends in, in vitro models and highlight the most common and promising practices for functional assessments. We further analyzed outputs spanning structural maturity, contractile function, electrophysiology and gene expression and note field-wide improvements over time. Finally, we discuss opportunities to collectively pursue the shared goal of hiPSC-CM model development, maturation and assessment that we believe are critical for engineering mature cardiac tissue.","PeriodicalId":18981,"journal":{"name":"Nature Methods","volume":" ","pages":""},"PeriodicalIF":36.1,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142624358","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

Pushing the limits of MRI brain imaging 突破磁共振成像脑成像的极限

IF 36.1 1区生物学

Nature Methods Pub Date : 2024-11-07 DOI: 10.1038/s41592-024-02489-y

Michael Eisenstein