Cell Reports Methods最新文献_第3页

A thermoplastic chip for 2D and 3D correlative assays combining screening and high-resolution imaging of immune cell responses. 一种用于二维和三维相关分析的热塑性芯片，结合免疫细胞反应的筛选和高分辨率成像。

IF 4.3

Cell Reports Methods Pub Date : 2025-01-27 Epub Date: 2025-01-17 DOI: 10.1016/j.crmeth.2025.100965

Hanna van Ooijen, Quentin Verron, Hanqing Zhang, Patrick A Sandoz, Thomas W Frisk, Valentina Carannante, Karl Olofsson, Arnika K Wagner, Niklas Sandström, Björn Önfelt

{"title":"A thermoplastic chip for 2D and 3D correlative assays combining screening and high-resolution imaging of immune cell responses.","authors":"Hanna van Ooijen, Quentin Verron, Hanqing Zhang, Patrick A Sandoz, Thomas W Frisk, Valentina Carannante, Karl Olofsson, Arnika K Wagner, Niklas Sandström, Björn Önfelt","doi":"10.1016/j.crmeth.2025.100965","DOIUrl":"10.1016/j.crmeth.2025.100965","url":null,"abstract":"We present an easy-to-use, disposable, thermoplastic microwell chip designed to support screening and high-resolution imaging of single-cell behavior in two- and three-dimensional (2D and 3D) cell cultures. We show that the chip has excellent optical properties and provide simple protocols for efficient long-term cell culture of suspension and adherent cells, the latter grown either as monolayers or as hundreds of single, uniformly sized spheroids. We then demonstrate the applicability of the system for single-cell analysis by correlating the dynamic cytotoxic response of single immune cells grown under different metabolic conditions to their intracellular cytolytic load at the end of the assay. Additionally, we illustrate highly multiplex cytotoxicity screening of tumor spheroids in the chip, comparing the effect of environment cues characteristic of the tumor microenvironment on natural killer (NK)-cell-induced killing. Following the functional screening, we perform high-resolution 3D immunofluorescent imaging of infiltrating NK cells within the spheroid volumes.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"100965"},"PeriodicalIF":4.3,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11841093/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143013077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Detecting copy-number alterations from single-cell chromatin sequencing data by AtaCNA. 通过AtaCNA检测单细胞染色质测序数据的拷贝数改变。

IF 4.3

Cell Reports Methods Pub Date : 2025-01-27 Epub Date: 2025-01-14 DOI: 10.1016/j.crmeth.2024.100939

Xiaochen Wang, Zijie Jin, Yang Shi, Ruibin Xi

{"title":"Detecting copy-number alterations from single-cell chromatin sequencing data by AtaCNA.","authors":"Xiaochen Wang, Zijie Jin, Yang Shi, Ruibin Xi","doi":"10.1016/j.crmeth.2024.100939","DOIUrl":"10.1016/j.crmeth.2024.100939","url":null,"abstract":"Single-cell assay of transposase-accessible chromatin sequencing (scATAC-seq) unbiasedly profiles genome-wide chromatin accessibility in single cells. In single-cell tumor studies, identification of normal cells or tumor clonal structures often relies on copy-number alterations (CNAs). However, CNA detection from scATAC-seq is difficult due to the high noise, sparsity, and confounding factors. Here, we describe AtaCNA, a computational algorithm that accurately detects high-resolution CNAs from scATAC-seq data. We benchmark AtaCNA using simulation and real data and find AtaCNA's superior performance. Analyses of 10 scATAC-seq datasets show that AtaCNA could effectively distinguish malignant from non-malignant cells. In glioblastoma, endometrial, and ovarian cancer samples, AtaCNA identifies subclones at distinct cellular states, suggesting an important interplay between genetic and epigenetic plasticity. Some tumor subclones only differ in small-scale (10-20 Mb) CNAs, demonstrating the importance of high-resolution CNA detection. These data show that AtaCNA can aid in integrative analysis to understand the complex heterogeneity in cancer.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"100939"},"PeriodicalIF":4.3,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11840951/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143013080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Selective activation of mesoscale functional circuits via multichannel infrared stimulation of cortical columns in ultra-high-field 7T MRI.

IF 4.3

Cell Reports Methods Pub Date : 2025-01-27 DOI: 10.1016/j.crmeth.2024.100961

Feiyan Tian, Yipeng Liu, Meixuan Chen, Kenneth Edward Schriver, Anna Wang Roe

{"title":"Selective activation of mesoscale functional circuits via multichannel infrared stimulation of cortical columns in ultra-high-field 7T MRI.","authors":"Feiyan Tian, Yipeng Liu, Meixuan Chen, Kenneth Edward Schriver, Anna Wang Roe","doi":"10.1016/j.crmeth.2024.100961","DOIUrl":"10.1016/j.crmeth.2024.100961","url":null,"abstract":"To restore vision in the blind, advances in visual cortical prosthetics (VCPs) have offered high-channel-count electrical interfaces. Here, we design a 100-fiber optical bundle interface apposed to known feature-specific (color, shape, motion, and depth) functional columns that populate the visual cortex in humans, primates, and cats. Based on a non-viral optical stimulation method (INS, infrared neural stimulation; 1,875 nm), it can deliver dynamic patterns of stimulation, is non-penetrating and non-damaging to tissue, and is movable and removable. In addition, its magnetic resonance (MR) compatibility (INS-fMRI) permits systematic mapping of brain-wide circuits. In the MRI, we illustrate (1) the single-point activation of functionally specific networks, (2) shifting cortical networks activated via shifting points of stimulation, and (3) \"moving dot\" stimulation-evoked activation of higher-order motion-selective areas. We suggest that, by mimicking patterns of columnar activation normally activated by visual stimuli, a columnar VCP opens doors for the planned activation of feature-specific circuits and their associated visual percepts.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":"5 1","pages":"100961"},"PeriodicalIF":4.3,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11840946/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143059417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A network-enabled pipeline for gene discovery and validation in non-model plant species.

IF 4.3

Cell Reports Methods Pub Date : 2025-01-27 DOI: 10.1016/j.crmeth.2024.100963

Dae Kwan Ko, Federica Brandizzi

引用次数: 0

Generation of super-resolution images from barcode-based spatial transcriptomics by deep image prior. 基于条形码的空间转录组学的深度图像先验生成超分辨率图像。

IF 4.3

Cell Reports Methods Pub Date : 2025-01-27 Epub Date: 2024-12-26 DOI: 10.1016/j.crmeth.2024.100937

Jeongbin Park, Seungho Cook, Dongjoo Lee, Jinyeong Choi, Seongjin Yoo, Sungwoo Bae, Hyung-Jun Im, Daeseung Lee, Hongyoon Choi

{"title":"Generation of super-resolution images from barcode-based spatial transcriptomics by deep image prior.","authors":"Jeongbin Park, Seungho Cook, Dongjoo Lee, Jinyeong Choi, Seongjin Yoo, Sungwoo Bae, Hyung-Jun Im, Daeseung Lee, Hongyoon Choi","doi":"10.1016/j.crmeth.2024.100937","DOIUrl":"10.1016/j.crmeth.2024.100937","url":null,"abstract":"Spatially resolved transcriptomics (ST) has revolutionized the field of biology by providing a powerful tool for analyzing gene expression in situ. However, current ST methods, particularly barcode-based methods, have limitations in reconstructing high-resolution images from barcodes sparsely distributed in slides. Here, we present SuperST, an algorithm that enables the reconstruction of dense matrices (higher-resolution and non-zero-inflated matrices) from low-resolution ST libraries. SuperST is based on deep image prior, which reconstructs spatial gene expression patterns as image matrices. Compared with previous methods, SuperST generated output images that more closely resembled immunofluorescence images for given gene expression maps. Furthermore, we demonstrated how one can combine images created by SuperST with computer vision algorithms. In this context, we proposed a method for extracting features from the images, which can aid in spatial clustering of genes. By providing a dense matrix for each gene in situ, SuperST can successfully address the resolution and zero-inflation issue.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"100937"},"PeriodicalIF":4.3,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11840945/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142898681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analysis of TEM micrographs with deep learning reveals APOE genotype-specific associations between HDL particle diameter and Alzheimer's dementia.

IF 4.3

Cell Reports Methods Pub Date : 2025-01-27 DOI: 10.1016/j.crmeth.2024.100962

Jack Jingyuan Zheng, Brian Vannak Hong, Joanne K Agus, Xinyu Tang, Fei Guo, Carlito B Lebrilla, Izumi Maezawa, Lee-Way Jin, Wyatt N Vreeland, Dean C Ripple, Angela M Zivkovic

{"title":"Analysis of TEM micrographs with deep learning reveals APOE genotype-specific associations between HDL particle diameter and Alzheimer's dementia.","authors":"Jack Jingyuan Zheng, Brian Vannak Hong, Joanne K Agus, Xinyu Tang, Fei Guo, Carlito B Lebrilla, Izumi Maezawa, Lee-Way Jin, Wyatt N Vreeland, Dean C Ripple, Angela M Zivkovic","doi":"10.1016/j.crmeth.2024.100962","DOIUrl":"10.1016/j.crmeth.2024.100962","url":null,"abstract":"High-density lipoprotein (HDL) particle diameter distribution is informative in the diagnosis of many conditions, including Alzheimer's disease (AD). However, obtaining an accurate HDL size measurement is challenging. We demonstrated the utility of measuring the diameter of more than 1,800,000 HDL particles with the deep learning model YOLOv7 (you only look once) from micrographs of 183 HDL samples, including patients with dementia or normal cognition (controls). This method was shown to be more efficient and accurate than conventional image analysis software. Using this method, we found a higher abundance of small HDLs in participants with dementia compared to controls in patients with the apolipoprotein E (APOE) ε3ε4 genotype, whereas patients with the APOE ε3ε3 genotype had higher variability in the abundance of different HDL subclasses. Our results show an example of accurate individual HDL particle diameter measurement for large-scale clinical samples, which can be expanded to characterize the relationship between disease risk and other nanoparticles in the sub-20-nm diameter size range.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":"5 1","pages":"100962"},"PeriodicalIF":4.3,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11840948/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143059114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multimodal hierarchical classification of CITE-seq data delineates immune cell states across lineages and tissues. CITE-seq数据的多模式分层分类描绘了跨谱系和组织的免疫细胞状态。

IF 4.3

Cell Reports Methods Pub Date : 2025-01-27 Epub Date: 2025-01-14 DOI: 10.1016/j.crmeth.2024.100938

Daniel P Caron, William L Specht, David Chen, Steven B Wells, Peter A Szabo, Isaac J Jensen, Donna L Farber, Peter A Sims

{"title":"Multimodal hierarchical classification of CITE-seq data delineates immune cell states across lineages and tissues.","authors":"Daniel P Caron, William L Specht, David Chen, Steven B Wells, Peter A Szabo, Isaac J Jensen, Donna L Farber, Peter A Sims","doi":"10.1016/j.crmeth.2024.100938","DOIUrl":"10.1016/j.crmeth.2024.100938","url":null,"abstract":"Single-cell RNA sequencing (scRNA-seq) is invaluable for profiling cellular heterogeneity and transcriptional states, but transcriptomic profiles do not always delineate subsets defined by surface proteins. Cellular indexing of transcriptomes and epitopes (CITE-seq) enables simultaneous profiling of single-cell transcriptomes and surface proteomes; however, accurate cell-type annotation requires a classifier that integrates multimodal data. Here, we describe multimodal classifier hierarchy (MMoCHi), a marker-based approach for accurate cell-type classification across multiple single-cell modalities that does not rely on reference atlases. We benchmark MMoCHi using sorted T lymphocyte subsets and annotate a cross-tissue human immune cell dataset. MMoCHi outperforms leading transcriptome-based classifiers and multimodal unsupervised clustering in its ability to identify immune cell subsets that are not readily resolved and to reveal subset markers. MMoCHi is designed for adaptability and can integrate annotation of cell types and developmental states across diverse lineages, samples, or modalities.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"100938"},"PeriodicalIF":4.3,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11840950/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143013083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A core genome MLST scheme for Borrelia burgdorferi sensu lato improves insights into the evolutionary history of the species complex. 针对普通包柔氏包虫病的核心基因组多基因组测序技术（MLST）方案有助于深入了解该物种复合体的进化历史。

IF 4.3

Cell Reports Methods Pub Date : 2025-01-27 Epub Date: 2024-12-18 DOI: 10.1016/j.crmeth.2024.100935

Sabrina Hepner, Keith A Jolley, Santiago Castillo-Ramirez, Evangelos Mourkas, Alexandra Dangel, Andreas Wieser, Johannes Hübner, Andreas Sing, Volker Fingerle, Gabriele Margos

{"title":"A core genome MLST scheme for Borrelia burgdorferi sensu lato improves insights into the evolutionary history of the species complex.","authors":"Sabrina Hepner, Keith A Jolley, Santiago Castillo-Ramirez, Evangelos Mourkas, Alexandra Dangel, Andreas Wieser, Johannes Hübner, Andreas Sing, Volker Fingerle, Gabriele Margos","doi":"10.1016/j.crmeth.2024.100935","DOIUrl":"10.1016/j.crmeth.2024.100935","url":null,"abstract":"Multi-locus sequence typing (MLST) based on eight genes has become the method of choice for Borrelia typing and is extensively used for population studies. Whole-genome sequencing enables studies to scale up to genomic levels but necessitates extended schemes. We have developed a 639-loci core genome MLST (cgMLST) scheme for Borrelia burgdorferi sensu lato (s.l.) that enables unambiguous genotyping and improves the robustness of phylogenies and lineage resolution within species. Notably, all inner nodes of the cgMLST phylogenies had consistently high statistical support. Analyses of the genetically homogeneous European B. bavariensis population support the notion that cgMLST provides high discriminatory power even for closely related isolates. While isolates differed maximally in one MLST locus, there were up to 179 cgMLST loci differences. Thus, the developed cgMLST scheme for B. burgdorferi s.l. resolves lineages at a finer resolution than MLST and improves insights into the evolutionary history of the species complex.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"100935"},"PeriodicalIF":4.3,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11840949/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142865597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Unifying community whole-brain imaging datasets enables robust neuron identification and reveals determinants of neuron position in C. elegans. 统一的社区全脑成像数据集可以实现稳健的神经元识别，并揭示秀丽隐杆线虫神经元位置的决定因素。

IF 4.3

Cell Reports Methods Pub Date : 2025-01-27 Epub Date: 2025-01-17 DOI: 10.1016/j.crmeth.2024.100964

Daniel Y Sprague, Kevin Rusch, Raymond L Dunn, Jackson M Borchardt, Steven Ban, Greg Bubnis, Grace C Chiu, Chentao Wen, Ryoga Suzuki, Shivesh Chaudhary, Hyun Jee Lee, Zikai Yu, Benjamin Dichter, Ryan Ly, Shuichi Onami, Hang Lu, Koutarou D Kimura, Eviatar Yemini, Saul Kato

{"title":"Unifying community whole-brain imaging datasets enables robust neuron identification and reveals determinants of neuron position in C. elegans.","authors":"Daniel Y Sprague, Kevin Rusch, Raymond L Dunn, Jackson M Borchardt, Steven Ban, Greg Bubnis, Grace C Chiu, Chentao Wen, Ryoga Suzuki, Shivesh Chaudhary, Hyun Jee Lee, Zikai Yu, Benjamin Dichter, Ryan Ly, Shuichi Onami, Hang Lu, Koutarou D Kimura, Eviatar Yemini, Saul Kato","doi":"10.1016/j.crmeth.2024.100964","DOIUrl":"10.1016/j.crmeth.2024.100964","url":null,"abstract":"We develop a data harmonization approach for C. elegans volumetric microscopy data, consisting of a standardized format, pre-processing techniques, and human-in-the-loop machine-learning-based analysis tools. Using this approach, we unify a diverse collection of 118 whole-brain neural activity imaging datasets from five labs, storing these and accompanying tools in an online repository WormID (wormid.org). With this repository, we train three existing automated cell-identification algorithms, CPD, StatAtlas, and CRF_ID, to enable accuracy that generalizes across labs, recovering all human-labeled neurons in some cases. We mine this repository to identify factors that influence the developmental positioning of neurons. This growing resource of data, code, apps, and tutorials enables users to (1) study neuroanatomical organization and neural activity across diverse experimental paradigms, (2) develop and benchmark algorithms for automated neuron detection, segmentation, cell identification, tracking, and activity extraction, and (3) share data with the community and comply with data-sharing policies.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"100964"},"PeriodicalIF":4.3,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11840940/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143013087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The FIRE biosensor illuminates iron regulatory protein activity and cellular iron homeostasis. FIRE生物传感器照亮铁调节蛋白活性和细胞铁稳态。

IF 4.3

Cell Reports Methods Pub Date : 2025-01-27 Epub Date: 2025-01-16 DOI: 10.1016/j.crmeth.2024.100960

Carolyn Sangokoya

引用次数: 0