Cell systems最新文献_第4页

Large-scale control over collective cell migration using light-activated epidermal growth factor receptors. 利用光激活表皮生长因子受体对集体细胞迁移的大规模控制。

Cell systems Pub Date : 2025-03-19 Epub Date: 2025-03-03 DOI: 10.1016/j.cels.2025.101203

Kevin Suh, Richard H Thornton, Long Nguyen, Payam E Farahani, Daniel J Cohen, Jared E Toettcher

{"title":"Large-scale control over collective cell migration using light-activated epidermal growth factor receptors.","authors":"Kevin Suh, Richard H Thornton, Long Nguyen, Payam E Farahani, Daniel J Cohen, Jared E Toettcher","doi":"10.1016/j.cels.2025.101203","DOIUrl":"10.1016/j.cels.2025.101203","url":null,"abstract":"Receptor tyrosine kinases (RTKs) play key roles in coordinating cell movement at both single-cell and tissue scales. The recent development of optogenetic tools for controlling RTKs and their downstream signaling pathways suggests that these responses may be amenable to engineering-based control for sculpting tissue shape and function. Here, we report that a light-controlled epidermal growth factor (EGF) receptor (OptoEGFR) can be deployed in epithelial cells for precise, programmable control of long-range tissue movements. We show that in OptoEGFR-expressing tissues, light can drive millimeter-scale cell rearrangements to densify interior regions or produce rapid outgrowth at tissue edges. Light-controlled tissue movements are driven primarily by phosphoinositide 3-kinase (PI3K) signaling, rather than diffusible ligands, tissue contractility, or ERK kinase signaling as seen in other RTK-driven migration contexts. Our study suggests that synthetic, light-controlled RTKs could serve as a powerful platform for controlling cell positions and densities for diverse applications, including wound healing and tissue morphogenesis.","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101203"},"PeriodicalIF":0.0,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143560400","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

SPARROW reveals microenvironment-zone-specific cell states in healthy and diseased tissues. SPARROW揭示了健康和病变组织中微环境区特异性细胞状态。

Cell systems Pub Date : 2025-03-19 DOI: 10.1016/j.cels.2025.101235

Peiyao A Zhao, Ruoxin Li, Temi Adewunmi, Jessica Garber, Claire Gustafson, June Kim, Jocelin Malone, Adam Savage, Peter Skene, Xiao-Jun Li

{"title":"SPARROW reveals microenvironment-zone-specific cell states in healthy and diseased tissues.","authors":"Peiyao A Zhao, Ruoxin Li, Temi Adewunmi, Jessica Garber, Claire Gustafson, June Kim, Jocelin Malone, Adam Savage, Peter Skene, Xiao-Jun Li","doi":"10.1016/j.cels.2025.101235","DOIUrl":"10.1016/j.cels.2025.101235","url":null,"abstract":"Spatially resolved transcriptomics technologies have advanced our understanding of cellular characteristics within tissue contexts. However, current analytical tools often treat cell-type inference and cellular neighborhood identification as separate and hard clustering processes, limiting comparability across scales and samples. SPARROW addresses these challenges by jointly learning latent embeddings and soft clusterings of cell types and cellular organization. It outperformed state-of-the-art methods in cell-type inference and microenvironment zone delineation and uncovered zone-specific cell states in human and mouse tissues that competing methods missed. By integrating spatially resolved transcriptomics and single-cell RNA sequencing (scRNA-seq) data in a shared latent space, SPARROW achieves single-cell spatial resolution and whole-transcriptome coverage, enabling the discovery of both established and unknown microenvironment zone-specific ligand-receptor interactions in the human tonsil. Overall, SPARROW is a computational framework that provides a comprehensive characterization of tissue features across scales, samples, and conditions.","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":"16 3","pages":"101235"},"PeriodicalIF":0.0,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143672011","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

Cold and hot fibrosis define clinically distinct cardiac pathologies. 冷纤维化和热纤维化定义了临床上不同的心脏病理。

Cell systems Pub Date : 2025-03-19 Epub Date: 2025-02-18 DOI: 10.1016/j.cels.2025.101198

Shoval Miyara, Miri Adler, Kfir B Umansky, Daniel Häußler, Elad Bassat, Yalin Divinsky, Jacob Elkahal, David Kain, Daria Lendengolts, Ricardo O Ramirez Flores, Hanna Bueno-Levy, Ofra Golani, Tali Shalit, Michael Gershovits, Eviatar Weizman, Alexander Genzelinakh, Danielle M Kimchi, Avraham Shakked, Lingling Zhang, Jingkui Wang, Andrea Baehr, Zachary Petrover, Rachel Sarig, Tatjana Dorn, Alessandra Moretti, Julio Saez-Rodriguez, Christian Kupatt, Elly M Tanaka, Ruslan Medzhitov, Achim Krüger, Avi Mayo, Uri Alon, Eldad Tzahor

{"title":"Cold and hot fibrosis define clinically distinct cardiac pathologies.","authors":"Shoval Miyara, Miri Adler, Kfir B Umansky, Daniel Häußler, Elad Bassat, Yalin Divinsky, Jacob Elkahal, David Kain, Daria Lendengolts, Ricardo O Ramirez Flores, Hanna Bueno-Levy, Ofra Golani, Tali Shalit, Michael Gershovits, Eviatar Weizman, Alexander Genzelinakh, Danielle M Kimchi, Avraham Shakked, Lingling Zhang, Jingkui Wang, Andrea Baehr, Zachary Petrover, Rachel Sarig, Tatjana Dorn, Alessandra Moretti, Julio Saez-Rodriguez, Christian Kupatt, Elly M Tanaka, Ruslan Medzhitov, Achim Krüger, Avi Mayo, Uri Alon, Eldad Tzahor","doi":"10.1016/j.cels.2025.101198","DOIUrl":"10.1016/j.cels.2025.101198","url":null,"abstract":"Fibrosis remains a major unmet medical need. Simplifying principles are needed to better understand fibrosis and to yield new therapeutic approaches. Fibrosis is driven by myofibroblasts that interact with macrophages. A mathematical cell-circuit model predicts two types of fibrosis: hot fibrosis driven by macrophages and myofibroblasts and cold fibrosis driven by myofibroblasts alone. Testing these concepts in cardiac fibrosis resulting from myocardial infarction (MI) and heart failure (HF), we revealed that acute MI leads to cold fibrosis whereas chronic injury (HF) leads to hot fibrosis. MI-driven cold fibrosis is conserved in pigs and humans. We computationally identified a vulnerability of cold fibrosis: the myofibroblast autocrine growth factor loop. Inhibiting this loop by targeting TIMP1 with neutralizing antibodies reduced myofibroblast proliferation and fibrosis post-MI in mice. Our study demonstrates the utility of the concepts of hot and cold fibrosis and the feasibility of a circuit-to-target approach to pinpoint a treatment strategy that reduces fibrosis. A record of this paper's transparent peer review process is included in the supplemental information.","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101198"},"PeriodicalIF":0.0,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11922821/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143461028","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

How well do contextual protein encodings learn structure, function, and evolutionary context? 背景蛋白编码如何学习结构、功能和进化背景？

Cell systems Pub Date : 2025-03-19 Epub Date: 2025-03-04 DOI: 10.1016/j.cels.2025.101201

Sai Pooja Mahajan, Fátima A Dávila-Hernández, Jeffrey A Ruffolo, Jeffrey J Gray

{"title":"How well do contextual protein encodings learn structure, function, and evolutionary context?","authors":"Sai Pooja Mahajan, Fátima A Dávila-Hernández, Jeffrey A Ruffolo, Jeffrey J Gray","doi":"10.1016/j.cels.2025.101201","DOIUrl":"10.1016/j.cels.2025.101201","url":null,"abstract":"In proteins, the optimal residue at any position is determined by its structural, evolutionary, and functional contexts-much like how a word may be inferred from its context in language. We trained masked label prediction models to learn representations of amino acid residues in different contexts. We focus questions on evolution and structural flexibility and whether and how contextual encodings derived through pretraining and fine-tuning may improve representations for specialized contexts. Sequences sampled from our learned representations fold into template structure and reflect sequence variations seen in related proteins. For flexible proteins, sampled sequences traverse the full conformational space of the native sequence, suggesting that plasticity is encoded in the template structure. For protein-protein interfaces, generated sequences replicate wild-type binding energies across diverse interfaces and binding strengths in silico. For the antibody-antigen interface, fine-tuning recapitulate conserved sequence patterns, while pretraining on general contexts improves sequence recovery for the hypervariable H3 loop. A record of this paper's transparent peer review process is included in the supplemental information.","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101201"},"PeriodicalIF":0.0,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12026297/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143569193","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

DeST-OT: Alignment of spatiotemporal transcriptomics data. est - ot：时空转录组学数据比对。

Cell systems Pub Date : 2025-02-19 Epub Date: 2025-01-27 DOI: 10.1016/j.cels.2024.12.001

Peter Halmos, Xinhao Liu, Julian Gold, Feng Chen, Li Ding, Benjamin J Raphael

引用次数: 0

Should biology put complexity first? 生物学应该把复杂性放在第一位吗？

Cell systems Pub Date : 2025-02-19 Epub Date: 2025-02-10 DOI: 10.1016/j.cels.2025.101197

Philip Ball

引用次数: 0

A genetic toolbox for engineering C. acnes. 一个基因工具箱的工程痤疮。

Cell systems Pub Date : 2025-02-19 DOI: 10.1016/j.cels.2025.101199

Y Erin Chen

引用次数: 0

Spatial transcriptomics-aided localization for single-cell transcriptomics with STALocator. 空间转录组辅助定位单细胞转录组与STALocator。

Cell systems Pub Date : 2025-02-19 Epub Date: 2025-02-03 DOI: 10.1016/j.cels.2025.101195

Shang Li, Qunlun Shen, Shihua Zhang

{"title":"Spatial transcriptomics-aided localization for single-cell transcriptomics with STALocator.","authors":"Shang Li, Qunlun Shen, Shihua Zhang","doi":"10.1016/j.cels.2025.101195","DOIUrl":"10.1016/j.cels.2025.101195","url":null,"abstract":"Single-cell RNA-sequencing (scRNA-seq) techniques can measure gene expression at single-cell resolution but lack spatial information. Spatial transcriptomics (ST) techniques simultaneously provide gene expression data and spatial information. However, the data quality of the spatial resolution or gene coverage is still much lower than the quality of the single-cell transcriptomics data. To this end, we develop a ST-Aided Locator for single-cell transcriptomics (STALocator) to localize single cells to corresponding ST data. Applications on simulated data showed that STALocator performed better than other localization methods. When applied to the human brain and squamous cell carcinoma data, STALocator could robustly reconstruct the relative spatial organization of critical cell populations. Moreover, STALocator could enhance gene expression patterns for Slide-seqV2 data and predict genome-wide gene expression data for fluorescence in situ hybridization (FISH) and Xenium data, leading to the identification of more spatially variable genes and more biologically relevant Gene Ontology (GO) terms compared with the raw data. A record of this paper's transparent peer review process is included in the supplemental information.","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101195"},"PeriodicalIF":0.0,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143191539","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

Macrophage memory emerges from coordinated transcription factor and chromatin dynamics. 巨噬细胞记忆源于转录因子和染色质动力学的协调。

Cell systems Pub Date : 2025-02-19 Epub Date: 2025-02-11 DOI: 10.1016/j.cels.2025.101171

Andrew G Wang, Minjun Son, Aleksandr Gorin, Emma Kenna, Abinash Padhi, Bijentimala Keisham, Adam Schauer, Alexander Hoffmann, Savaş Tay

{"title":"Macrophage memory emerges from coordinated transcription factor and chromatin dynamics.","authors":"Andrew G Wang, Minjun Son, Aleksandr Gorin, Emma Kenna, Abinash Padhi, Bijentimala Keisham, Adam Schauer, Alexander Hoffmann, Savaş Tay","doi":"10.1016/j.cels.2025.101171","DOIUrl":"10.1016/j.cels.2025.101171","url":null,"abstract":"Cells of the immune system operate in dynamic microenvironments where the timing, concentration, and order of signaling molecules constantly change. Despite this complexity, immune cells manage to communicate accurately and control inflammation and infection. It is unclear how these dynamic signals are encoded and decoded and if individual cells retain the memory of past exposure to inflammatory molecules. Here, we use live-cell analysis, ATAC sequencing, and an in vivo model of sepsis to show that sequential inflammatory signals induce memory in individual macrophages through reprogramming the nuclear factor κB (NF-κB) network and the chromatin accessibility landscape. We use transcriptomic profiling and deep learning to show that transcription factor and chromatin dynamics coordinate fine-tuned macrophage responses to new inflammatory signals. This work demonstrates how macrophages retain the memory of previous signals despite single-cell variability and elucidates the mechanisms of signal-induced memory in dynamic inflammatory conditions like sepsis.","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101171"},"PeriodicalIF":0.0,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143412008","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

A genome-scale metabolic reconstruction resource of 247,092 diverse human microbes spanning multiple continents, age groups, and body sites. 247,092种不同人类微生物的基因组尺度代谢重建资源，跨越多个大陆、年龄组和身体部位。

Cell systems Pub Date : 2025-02-19 Epub Date: 2025-02-12 DOI: 10.1016/j.cels.2025.101196

Almut Heinken, Timothy Otto Hulshof, Bram Nap, Filippo Martinelli, Arianna Basile, Amy O'Brolchain, Neil Francis O'Sullivan, Celine Gallagher, Eimer Magee, Francesca McDonagh, Ian Lalor, Maeve Bergin, Phoebe Evans, Rachel Daly, Ronan Farrell, Rose Mary Delaney, Saoirse Hill, Saoirse Roisin McAuliffe, Trevor Kilgannon, Ronan M T Fleming, Cyrille C Thinnes, Ines Thiele

{"title":"A genome-scale metabolic reconstruction resource of 247,092 diverse human microbes spanning multiple continents, age groups, and body sites.","authors":"Almut Heinken, Timothy Otto Hulshof, Bram Nap, Filippo Martinelli, Arianna Basile, Amy O'Brolchain, Neil Francis O'Sullivan, Celine Gallagher, Eimer Magee, Francesca McDonagh, Ian Lalor, Maeve Bergin, Phoebe Evans, Rachel Daly, Ronan Farrell, Rose Mary Delaney, Saoirse Hill, Saoirse Roisin McAuliffe, Trevor Kilgannon, Ronan M T Fleming, Cyrille C Thinnes, Ines Thiele","doi":"10.1016/j.cels.2025.101196","DOIUrl":"10.1016/j.cels.2025.101196","url":null,"abstract":"Genome-scale modeling of microbiome metabolism enables the simulation of diet-host-microbiome-disease interactions. However, current genome-scale reconstruction resources are limited in scope by computational challenges. We developed an optimized and highly parallelized reconstruction and analysis pipeline to build a resource of 247,092 microbial genome-scale metabolic reconstructions, deemed APOLLO. APOLLO spans 19 phyla, contains >60% of uncharacterized strains, and accounts for strains from 34 countries, all age groups, and multiple body sites. Using machine learning, we predicted with high accuracy the taxonomic assignment of strains based on the computed metabolic features. We then built 14,451 metagenomic sample-specific microbiome community models to systematically interrogate their community-level metabolic capabilities. We show that sample-specific metabolic pathways accurately stratify microbiomes by body site, age, and disease state. APOLLO is freely available, enables the systematic interrogation of the metabolic capabilities of largely still uncultured and unclassified species, and provides unprecedented opportunities for systems-level modeling of personalized host-microbiome co-metabolism.","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101196"},"PeriodicalIF":0.0,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143416386","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