Cell Reports Methods最新文献

TransTag enables simple and efficient transgene mapping in zebrafish via tagmentation. TransTag可以通过标记在斑马鱼中进行简单有效的转基因定位。

IF 4.3

Cell Reports Methods Pub Date : 2025-06-28 DOI: 10.1016/j.crmeth.2025.101090

Fanju W Meng, Paige Schneider, Xiaolu Wei, Krishan Ariyasiri, Marnie E Halpern, Patrick J Murphy

{"title":"TransTag enables simple and efficient transgene mapping in zebrafish via tagmentation.","authors":"Fanju W Meng, Paige Schneider, Xiaolu Wei, Krishan Ariyasiri, Marnie E Halpern, Patrick J Murphy","doi":"10.1016/j.crmeth.2025.101090","DOIUrl":"https://doi.org/10.1016/j.crmeth.2025.101090","url":null,"abstract":"Zebrafish has become a preeminent model for developmental biology research, largely due to the ease of transgenesis. Despite widespread usage of transgenic lines, mapping of transgene insertion sites is rare, which raises complications involving potential local chromatin influences on transgene expression, off-target effects, and issues with allelic variation. To address these shortcomings, we introduce TransTag, a simple and efficient method utilizing Tn5 transposase-mediated tagmentation, for the streamlined identification of Tol2-based transgene insertion sites in zebrafish. TransTag is straightforward to perform and can identify insertion sites without the need for the alignment of raw sequencing data. We also provide a detailed protocol for TransTag, a step-by-step guide for data analysis, and a user-friendly Shiny app, making transgene mapping achievable at a low cost for researchers without programming expertise. Altogether, TransTag emerges as a valuable tool to enhance the precision and utility of transgenesis studies by providing essential chromosome-specific information on transgene locations.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"101090"},"PeriodicalIF":4.3,"publicationDate":"2025-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144601757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Self-supervised learning for generalizable particle picking in cryo-EM micrographs. 低温电镜显微图中可泛化粒子拾取的自监督学习。

IF 4.3

Cell Reports Methods Pub Date : 2025-06-28 DOI: 10.1016/j.crmeth.2025.101089

Andreas Zamanos, Panagiotis Koromilas, Giorgos Bouritsas, Panagiotis L Kastritis, Yannis Panagakis

{"title":"Self-supervised learning for generalizable particle picking in cryo-EM micrographs.","authors":"Andreas Zamanos, Panagiotis Koromilas, Giorgos Bouritsas, Panagiotis L Kastritis, Yannis Panagakis","doi":"10.1016/j.crmeth.2025.101089","DOIUrl":"https://doi.org/10.1016/j.crmeth.2025.101089","url":null,"abstract":"We present cryoelectron microscopy masked autoencoder (cryo-EMMAE), a self-supervised method designed to overcome the need for manually annotated cryo-EM data. cryo-EMMAE leverages the representation space of a masked autoencoder to pick particle pixels through clustering of the MAE latent representation. Evaluation across different EMPIAR datasets demonstrates that cryo-EMMAE outperforms state-of-the-art supervised methods in terms of generalization capabilities. Importantly, our method showcases consistent performance, independent of the dataset used for training. Additionally, cryo-EMMAE is data efficient, as we experimentally observe that it converges with as few as five micrographs. Further, 3D reconstruction results indicate that our method has superior performance in reconstructing the volumes in both single-particle datasets and multi-particle micrographs derived from cell extracts. Our results underscore the potential of self-supervised learning in advancing cryo-EM image analysis, offering an alternative for more efficient and cost-effective structural biology research. Code is available at https://github.com/azamanos/Cryo-EMMAE.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"101089"},"PeriodicalIF":4.3,"publicationDate":"2025-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144592461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Automated denoising of CITE-seq data with ThresholdR. 基于ThresholdR的CITE-seq数据自动去噪。

IF 4.3

Cell Reports Methods Pub Date : 2025-06-27 DOI: 10.1016/j.crmeth.2025.101088

Mohammad Oliaeimotlagh, Sunil Kumar, Aleksandr Taraskin, Sujit Silas Armstrong Suthahar, Vasantika Suryawanshi, Austin W T Chiang, Klaus Ley

{"title":"Automated denoising of CITE-seq data with ThresholdR.","authors":"Mohammad Oliaeimotlagh, Sunil Kumar, Aleksandr Taraskin, Sujit Silas Armstrong Suthahar, Vasantika Suryawanshi, Austin W T Chiang, Klaus Ley","doi":"10.1016/j.crmeth.2025.101088","DOIUrl":"https://doi.org/10.1016/j.crmeth.2025.101088","url":null,"abstract":"Cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) is a potent addition to single-cell RNA sequencing (scRNA-seq). This method enriches transcriptomic insights by incorporating information about the cell surface phenotype through the application of oligonucleotide-tagged monoclonal antibodies. Similar to observations in flow cytometry, the CITE-seq signal (antibody-derived tag [ADT]) contains technical noise originating from ambient antibodies within the reaction compartment, non-specific binding, and/or imperfect titration. To denoise ADT data provided through CITE-seq experiments, we present ThresholdR, an R-based automated tool, to reliably and systematically find the threshold that separates the signal from the noise for each antibody. We assess the performance of ThresholdR across different datasets and platforms and benchmark it against two alternative methods, DSB (denoised and scaled by background) and CellBender. We show that ThresholdR remedies the high false negative rates of DSB and CellBender. We propose that denoising with ThresholdR can improve cell-type annotation and improve downstream analyses.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"101088"},"PeriodicalIF":4.3,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144601756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

TAS-seq enables subcellular single-stranded adenosine profiling by signal peptide-assisted adenosine deamination. TAS-seq通过信号肽辅助的腺苷脱胺，实现亚细胞单链腺苷谱分析。

IF 4.3

Cell Reports Methods Pub Date : 2025-06-19 DOI: 10.1016/j.crmeth.2025.101087

Lixia Wang, Yangfan Zhou, Zhenxing Yu, Panfeng Wu, Zhike Lu, Lijia Ma

引用次数: 0

A single-cell transposable element atlas of human cell identity. 人类细胞身份的单细胞转座因子图谱。

IF 4.3

Cell Reports Methods Pub Date : 2025-06-18 DOI: 10.1016/j.crmeth.2025.101086

Helena Reyes-Gopar, Jez L Marston, Bhavya Singh, Matthew Greenig, Jonah Lin, Mario A Ostrowski, Kipchoge N Randall, Santiago Sandoval-Motta, Nicholas Dopkins, Elsa Lawrence, Morgan M O'Mara, Tongyi Fei, Rodrigo R R Duarte, Timothy R Powell, Enrique Hernández-Lemus, Luis P Iñiguez, Douglas F Nixon, Matthew L Bendall

{"title":"A single-cell transposable element atlas of human cell identity.","authors":"Helena Reyes-Gopar, Jez L Marston, Bhavya Singh, Matthew Greenig, Jonah Lin, Mario A Ostrowski, Kipchoge N Randall, Santiago Sandoval-Motta, Nicholas Dopkins, Elsa Lawrence, Morgan M O'Mara, Tongyi Fei, Rodrigo R R Duarte, Timothy R Powell, Enrique Hernández-Lemus, Luis P Iñiguez, Douglas F Nixon, Matthew L Bendall","doi":"10.1016/j.crmeth.2025.101086","DOIUrl":"10.1016/j.crmeth.2025.101086","url":null,"abstract":"Single-cell RNA sequencing (scRNA-seq) is revolutionizing the study of complex biological systems. However, most sequencing studies overlook the contribution of transposable element (TE) expression to the transcriptome. The quantification of locus-specific TE expression in scRNA-seq experiments is challenging due to their repetitive sequence content and poorly characterized annotations. Here, we developed a computational tool for single-cell transposable element locus-level analysis of scRNA sequencing (Stellarscope) that reassigns multimapped reads to specific genomic loci using an expectation maximization algorithm. Using Stellarscope, we built an atlas of TE expression in human PBMCs. We found that locus-specific TEs delineate cell types and define cell subsets not identified by standard mRNA expression profiles. Altogether, this study provides comprehensive insights into the influence of TEs in human biology at the single-cell level.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"101086"},"PeriodicalIF":4.3,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144340482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Highly quantitative measurement of differential protein-genome binding with PerCell chromatin sequencing. 利用PerCell染色质测序对差异蛋白-基因组结合进行高度定量测量。

IF 4.3

Cell Reports Methods Pub Date : 2025-06-16 Epub Date: 2025-05-19 DOI: 10.1016/j.crmeth.2025.101052

Alexi Tallan, Jack Kucinski, Benjamin Sunkel, Cenny Taslim, Stephanie LaHaye, Qi Liu, Jun Qi, Meng Wang, Genevieve C Kendall, Benjamin Z Stanton

引用次数: 0

Engineering high-efficiency matriptase substrates using E. coli display for applications in prodrug activation. 利用大肠杆菌显示器设计高效基质酶底物用于前药活化。

IF 4.3

Cell Reports Methods Pub Date : 2025-06-16 Epub Date: 2025-06-10 DOI: 10.1016/j.crmeth.2025.101077

Anna Mestre Borras, Hanna Mehari, Stefan Ståhl, John Löfblom

{"title":"Engineering high-efficiency matriptase substrates using E. coli display for applications in prodrug activation.","authors":"Anna Mestre Borras, Hanna Mehari, Stefan Ståhl, John Löfblom","doi":"10.1016/j.crmeth.2025.101077","DOIUrl":"10.1016/j.crmeth.2025.101077","url":null,"abstract":"Proteases play a crucial role in biological functions such as tumor progression and tissue homeostasis. Recently, protease-activated prodrugs have gained attention for their potential to enhance selectivity in tumor-targeted therapies. In this study, we report the engineering of substrate sequences for matriptase, a protease overexpressed in tumors and previously explored for prodrug activation in vivo. A peptide library containing millions of potential substrates was displayed on Escherichia coli, and flow cytometric sorting was used to isolate improved substrates based on cleavage efficiency. Hits were ranked by flow cytometry, and the top substrates exhibited kcat/KM values over 40-fold higher than previously reported sequences. These substrates were further evaluated in an antibody-prodrug format, demonstrating exceptional activation. The matriptase substrates hold broad potential for applications such as cleavable linkers in next-generation antibody prodrugs. Furthermore, the developed bacterial display platform shows promise for discovering substrates of other proteases.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"101077"},"PeriodicalIF":4.3,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144276074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Expansion microscopy reveals nano-scale insights into the human neuromuscular junction. 扩展显微镜揭示了纳米尺度对人类神经肌肉连接处的洞察。

IF 4.3

Cell Reports Methods Pub Date : 2025-06-16 DOI: 10.1016/j.crmeth.2025.101082

Abdullah Ramadan, Thomas M D Sheard, Abrar Alhindi, Philippa A Rust, Ross A Jones, Izzy Jayasinghe, Thomas H Gillingwater

引用次数: 0

Characterization of human CMV-specific CD8⁺ T cells using multi-layer single-cell omics. 人cmv特异性CD8+ T细胞的多层单细胞组学研究

IF 4.3

Cell Reports Methods Pub Date : 2025-06-16 DOI: 10.1016/j.crmeth.2025.101085

Ioanna Gemünd, Lorenzo Bonaguro, Matthias Becker, Sophie Müller, Clemens Joos, Elena De Domenico, Anna C Aschenbrenner, Joachim L Schultze, Andreas Moosmann, Marc D Beyer

引用次数: 0

Microendoscopy for periodic intravital end-to-end tumor imaging of cancer cells. 显微内镜用于肿瘤细胞的周期性活体端到端肿瘤成像。

IF 4.3

Cell Reports Methods Pub Date : 2025-06-16 Epub Date: 2025-06-04 DOI: 10.1016/j.crmeth.2025.101056

Toshiyuki Goto, Masayuki Nakano, Sally Danno, Chie Ueda, Asako Sakaue-Sawano, Atsushi Miyawaki, Anna Wrabel, Ichiro Nakahara, Takahito Nishikata, Akira Mizoguchi, Yasuhisa Tamura, Kei Mizuno, Yosky Kataoka, Kazuo Funabiki

{"title":"Microendoscopy for periodic intravital end-to-end tumor imaging of cancer cells.","authors":"Toshiyuki Goto, Masayuki Nakano, Sally Danno, Chie Ueda, Asako Sakaue-Sawano, Atsushi Miyawaki, Anna Wrabel, Ichiro Nakahara, Takahito Nishikata, Akira Mizoguchi, Yasuhisa Tamura, Kei Mizuno, Yosky Kataoka, Kazuo Funabiki","doi":"10.1016/j.crmeth.2025.101056","DOIUrl":"10.1016/j.crmeth.2025.101056","url":null,"abstract":"The spatiotemporal heterogeneity in intratumor proliferative behavior of cancer cells deeply affects tumor environment characteristics and the efficacy of anticancer treatments. Thus, intravital imaging with unlimited imaging depth and cellular-level resolution is greatly desired. We developed an optical-fiber-bundle-based microendoscope with a genetically encoded fluorescent ubiquitination-based cell-cycle indicator (Fucci) system to achieve the intravital, periodic, and multicolor end-to-end imaging of the proliferative activity of cancer cells at a cellular-level resolution. This technique enabled the periodic visualization of spatiotemporal cellular responses, including cell-cycle arrest and resumption, and nuclear enlargement following the administration of anticancer drugs in living mice. It was suggested that proliferating cell ratio and nuclear enlargement in cancer cells at the surface region of tumor characterized by abundant vascular invasion contribute to aggressive tumor regrowth after chemotherapy. The application of this technique can accelerate innovation in cancer biology and therapeutics.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"101056"},"PeriodicalIF":4.3,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144235395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0