Cell systems最新文献

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Integrative, high-resolution analysis of single-cell gene expression across experimental conditions with PARAFAC2-RISE. 利用PARAFAC2-RISE对不同实验条件下单细胞基因表达进行综合、高分辨率分析。
Cell systems Pub Date : 2025-05-12 DOI: 10.1016/j.cels.2025.101294
Andrew Ramirez, Brian T Orcutt-Jahns, Sean Pascoe, Armaan Abraham, Breanna Remigio, Nathaniel Thomas, Aaron S Meyer
{"title":"Integrative, high-resolution analysis of single-cell gene expression across experimental conditions with PARAFAC2-RISE.","authors":"Andrew Ramirez, Brian T Orcutt-Jahns, Sean Pascoe, Armaan Abraham, Breanna Remigio, Nathaniel Thomas, Aaron S Meyer","doi":"10.1016/j.cels.2025.101294","DOIUrl":"https://doi.org/10.1016/j.cels.2025.101294","url":null,"abstract":"<p><p>Effective exploration and analysis tools are vital for the extraction of insights from single-cell data. However, current techniques for modeling single-cell studies performed across experimental conditions (e.g., samples) require restrictive assumptions or do not adequately deconvolute condition-to-condition variation from cell-to-cell variation. Here, we report that reduction and insight in single-cell exploration (RISE), an adaptation of the tensor decomposition method PARAFAC2, enables the dimensionality reduction and analysis of single-cell data across conditions. We demonstrate the benefits of RISE across distinct examples of single-cell RNA-sequencing experiments of peripheral immune cells: pharmacologic drug perturbations and systemic lupus erythematosus patient samples. RISE enables associations of gene variation patterns with patients or perturbations while connecting each coordinated change to single cells without requiring cell-type annotations. The theoretical grounding of RISE suggests a unified framework for many single-cell data modeling tasks while providing an intuitive dimensionality reduction approach for multi-sample single-cell studies across biological contexts. A record of this paper's transparent peer review process is included in the supplemental information.</p>","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101294"},"PeriodicalIF":0.0,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144087033","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
Image2Reg: Linking chromatin images to gene regulation using genetic and chemical perturbation screens. Image2Reg:利用遗传和化学干扰屏幕将染色质图像与基因调控联系起来。
Cell systems Pub Date : 2025-05-09 DOI: 10.1016/j.cels.2025.101293
Daniel Paysan, Adityanarayanan Radhakrishnan, Xinyi Zhang, G V Shivashankar, Caroline Uhler
{"title":"Image2Reg: Linking chromatin images to gene regulation using genetic and chemical perturbation screens.","authors":"Daniel Paysan, Adityanarayanan Radhakrishnan, Xinyi Zhang, G V Shivashankar, Caroline Uhler","doi":"10.1016/j.cels.2025.101293","DOIUrl":"https://doi.org/10.1016/j.cels.2025.101293","url":null,"abstract":"<p><p>Representation learning provides an opportunity to uncover the link between 3D genome organization and gene regulatory networks, thereby connecting the physical and the biochemical space of a cell. Our method, Image2Reg, uses chromatin images obtained in large-scale genetic and chemical perturbation screens. Through convolutional neural networks, Image2Reg generates gene embedding that represents the effect of gene perturbation on chromatin organization. In addition, combining protein-protein interaction data with cell-type-specific transcriptomic data through a graph convolutional network, we obtain a gene embedding that represents the regulatory effect of genes. Finally, Image2Reg learns a map between the resulting physical and biochemical representation of cells, allowing us to predict the perturbed gene modules based on chromatin images. Our results confirm the deep link between chromatin organization and gene regulation and demonstrate that it can be harnessed to identify drug targets and genes upstream of perturbed phenotypes from a simple and inexpensive chromatin staining.</p>","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101293"},"PeriodicalIF":0.0,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144055145","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
Decoding the role of the arginine dihydrolase pathway in shaping human gut community assembly and health-relevant metabolites. 解码精氨酸二水解酶途径在塑造人类肠道群落组装和健康相关代谢物中的作用。
Cell systems Pub Date : 2025-05-05 DOI: 10.1016/j.cels.2025.101292
Yiyi Liu, Yu-Yu Cheng, Jaron Thompson, Zhichao Zhou, Eugenio I Vivas, Matthew F Warren, Julie M DuClos, Karthik Anantharaman, Federico E Rey, Ophelia S Venturelli
{"title":"Decoding the role of the arginine dihydrolase pathway in shaping human gut community assembly and health-relevant metabolites.","authors":"Yiyi Liu, Yu-Yu Cheng, Jaron Thompson, Zhichao Zhou, Eugenio I Vivas, Matthew F Warren, Julie M DuClos, Karthik Anantharaman, Federico E Rey, Ophelia S Venturelli","doi":"10.1016/j.cels.2025.101292","DOIUrl":"https://doi.org/10.1016/j.cels.2025.101292","url":null,"abstract":"<p><p>The arginine dihydrolase pathway (arc operon) provides a metabolic niche by transforming arginine into metabolic byproducts. We investigate the role of the arc operon in probiotic Escherichia coli Nissle 1917 on human gut community assembly and health-relevant metabolite profiles. By stabilizing environmental pH, the arc operon reduces variability in community composition in response to pH perturbations and frequently enhances butyrate production in synthetic communities. We use a tailored machine learning model for microbiomes to predict community assembly in response to variation in initial media pH and arc operon activity. This model uncovers the pH- and arc operon-dependent interactions shaping community assembly. Human gut species display altered colonization dynamics in response to the arc operon in the murine gut. In sum, our framework to quantify the contribution of a specific pathway to microbial community assembly and metabolite production can reveal new engineering strategies. A record of this paper's transparent peer review process is included in the supplemental information.</p>","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101292"},"PeriodicalIF":0.0,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144065398","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
All-at-once spatial proteome profiling of complex tissue context with single-cell-type resolution by proximity proteomics. 所有的空间蛋白质组分析复杂的组织背景与单细胞型分辨率接近蛋白质组学。
Cell systems Pub Date : 2025-05-05 DOI: 10.1016/j.cels.2025.101291
Yiheng Mao, Yuan Li, Zhendong Zheng, Yanfen Xu, Mi Ke, An He, Fuchao Liang, Keren Zhang, Xi Wang, Weina Gao, Ruijun Tian
{"title":"All-at-once spatial proteome profiling of complex tissue context with single-cell-type resolution by proximity proteomics.","authors":"Yiheng Mao, Yuan Li, Zhendong Zheng, Yanfen Xu, Mi Ke, An He, Fuchao Liang, Keren Zhang, Xi Wang, Weina Gao, Ruijun Tian","doi":"10.1016/j.cels.2025.101291","DOIUrl":"https://doi.org/10.1016/j.cels.2025.101291","url":null,"abstract":"<p><p>Spatial proteomics enables in-depth mapping of tissue architectures, mostly achieved by laser microdissection-mass spectrometry (LMD-MS) and antibody-based imaging. However, trade-offs among sampling precision, throughput, and proteome coverage still limit the applicability of these strategies. Here, we propose proximity labeling for spatial proteomics (PSPro) by combining precise antibody-targeted biotinylation and efficient affinity purification for all-at-once cell-type proteome capture with sub-micrometer resolution from single tissue slice. With fine-tuned labeling parameters, PSPro shows reliable performance in benchmarking against flow cytometry- and LMD-based proteomic workflows. We apply PSPro to tumor and spleen slices, enriching thousands of proteins containing known markers from ten cell types. We further incorporate LMD into PSPro to facilitate comparison of cell subpopulations from the same tissue slice, revealing spatial proteome heterogeneity of cancer cells and immune cells in pancreatic tumor. Collectively, PSPro converts the traditional \"antibody-epitope\" paradigm to an \"antibody-cell-type proteome\" for spatial biology in a user-friendly manner. A record of this paper's transparent peer review process is included in the supplemental information.</p>","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101291"},"PeriodicalIF":0.0,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144047235","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
Colony context and size-dependent compensation mechanisms give rise to variations in nuclear growth trajectories. 群体环境和大小依赖的补偿机制引起了核生长轨迹的变化。
Cell systems Pub Date : 2025-05-01 DOI: 10.1016/j.cels.2025.101265
Julie C Dixon, Christopher L Frick, Chantelle L Leveille, Philip Garrison, Peyton A Lee, Saurabh S Mogre, Benjamin Morris, Nivedita Nivedita, Ritvik Vasan, Jianxu Chen, Cameron L Fraser, Clare R Gamlin, Leigh K Harris, Melissa C Hendershott, Graham T Johnson, Kyle N Klein, Sandra A Oluoch, Derek J Thirstrup, M Filip Sluzewski, Lyndsay Wilhelm, Ruian Yang, Daniel M Toloudis, Matheus P Viana, Julie A Theriot, Susanne M Rafelski
{"title":"Colony context and size-dependent compensation mechanisms give rise to variations in nuclear growth trajectories.","authors":"Julie C Dixon, Christopher L Frick, Chantelle L Leveille, Philip Garrison, Peyton A Lee, Saurabh S Mogre, Benjamin Morris, Nivedita Nivedita, Ritvik Vasan, Jianxu Chen, Cameron L Fraser, Clare R Gamlin, Leigh K Harris, Melissa C Hendershott, Graham T Johnson, Kyle N Klein, Sandra A Oluoch, Derek J Thirstrup, M Filip Sluzewski, Lyndsay Wilhelm, Ruian Yang, Daniel M Toloudis, Matheus P Viana, Julie A Theriot, Susanne M Rafelski","doi":"10.1016/j.cels.2025.101265","DOIUrl":"https://doi.org/10.1016/j.cels.2025.101265","url":null,"abstract":"<p><p>To investigate how cellular variations arise across spatiotemporal scales in a population of identical healthy cells, we performed a data-driven analysis of nuclear growth variations in hiPS cell colonies as a model system. We generated a 3D timelapse dataset of thousands of nuclei over multiple days and developed open-source tools for image and data analysis and feature-based timelapse data exploration. Together, these data, tools, and workflows comprise a framework for systematic quantitative analysis of dynamics at individual and population levels, and the analysis further highlights important aspects to consider when interpreting timelapse data. We found that individual nuclear volume growth trajectories arise from short-timescale variations attributable to their spatiotemporal context within the colony. We identified a time-invariant volume compensation relationship between nuclear growth duration and starting volume across the population. Notably, we discovered that inheritance plays a crucial role in determining these two key nuclear growth features while other growth features are determined by their spatiotemporal context and are not inherited.</p>","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101265"},"PeriodicalIF":0.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144053835","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
FlowDesign: Improved design of antibody CDRs through flow matching and better prior distributions. FlowDesign:通过流程匹配和更好的先验分布,改进抗体cdr的设计。
Cell systems Pub Date : 2025-04-24 DOI: 10.1016/j.cels.2025.101270
Jun Wu, Xiangzhe Kong, Ningguan Sun, Jing Wei, Sisi Shan, Fuli Feng, Feng Wu, Jian Peng, Linqi Zhang, Yang Liu, Jianzhu Ma
{"title":"FlowDesign: Improved design of antibody CDRs through flow matching and better prior distributions.","authors":"Jun Wu, Xiangzhe Kong, Ningguan Sun, Jing Wei, Sisi Shan, Fuli Feng, Feng Wu, Jian Peng, Linqi Zhang, Yang Liu, Jianzhu Ma","doi":"10.1016/j.cels.2025.101270","DOIUrl":"https://doi.org/10.1016/j.cels.2025.101270","url":null,"abstract":"<p><p>Designing antibodies with desired binding specificity and affinity is essential for pharmaceutical research. While diffusion-based models have advanced the co-design of the complementarity-determining region (CDR) sequences and structures, challenges remain, including non-informative priors, incompatibility with discrete amino acid types, and impractical computational costs in large-scale sampling. To address these, we propose FlowDesign, a sequence-structure co-design approach via flow matching, offering (1) flexible prior selection, (2) direct matching of discrete distributions, and (3) enhanced efficiency for large-scale sampling. By leveraging various priors, data-driven structural models proved the most informative. FlowDesign outperformed baselines in amino acid recovery (AAR), root-mean-square deviation (RMSD), and Rosetta energy. We also applied FlowDesign to design antibodies targeting the HIV-1 receptor CD4. FlowDesign yielded antibodies with improved binding affinity and neutralizing potency compared with the antibody ibalizumab across multiple HIV mutants, validated by biolayer interferometry (BLI) and pseudovirus neutralization. This highlights FlowDesign's potential in antibody and protein design. A record of this paper's transparent peer review process is included in the supplemental information.</p>","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101270"},"PeriodicalIF":0.0,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144060427","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
Integrase enables synthetic intercellular logic via bacterial conjugation. 整合酶使合成细胞间逻辑通过细菌偶联。
Cell systems Pub Date : 2025-04-22 DOI: 10.1016/j.cels.2025.101268
Fang Ba, Yufei Zhang, Luyao Wang, Xiangyang Ji, Wan-Qiu Liu, Shengjie Ling, Jian Li
{"title":"Integrase enables synthetic intercellular logic via bacterial conjugation.","authors":"Fang Ba, Yufei Zhang, Luyao Wang, Xiangyang Ji, Wan-Qiu Liu, Shengjie Ling, Jian Li","doi":"10.1016/j.cels.2025.101268","DOIUrl":"https://doi.org/10.1016/j.cels.2025.101268","url":null,"abstract":"<p><p>Integrases have been widely used in synthetic biology for genome engineering and genetic circuit design. They mediate DNA recombination to alter the genotypes of single cell lines in vivo, with these changes being permanently recorded and inherited via vertical gene transfer. However, integrase-based intercellular DNA messaging and its regulation via horizontal gene transfer remain underexplored. Here, we introduce a versatile strategy to design, build, and test integrase-based intercellular DNA messaging through bacterial conjugation. First, we screened conjugative plasmids and recipient cells for efficient conjugation. Then, we established a layered framework to describe the interactions among hierarchical E. coli strains and implemented dual-layer Boolean logic gates to demonstrate intercellular DNA messaging and management. Finally, we expanded the design to include four-layer single-processing pathways and dual-layer multi-processing systems. This strategy advances intercellular DNA messaging, hierarchical signal processing, and the application of integrase in systems and synthetic biology.</p>","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101268"},"PeriodicalIF":0.0,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144000528","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
Model-guided design of microRNA-based gene circuits supports precise dosage of transgenic cargoes into diverse primary cells. 基于microrna的基因电路的模型引导设计支持转基因货物进入不同原代细胞的精确剂量。
Cell systems Pub Date : 2025-04-22 DOI: 10.1016/j.cels.2025.101269
Kasey S Love, Christopher P Johnstone, Emma L Peterman, Stephanie Gaglione, Michael E Birnbaum, Kate E Galloway
{"title":"Model-guided design of microRNA-based gene circuits supports precise dosage of transgenic cargoes into diverse primary cells.","authors":"Kasey S Love, Christopher P Johnstone, Emma L Peterman, Stephanie Gaglione, Michael E Birnbaum, Kate E Galloway","doi":"10.1016/j.cels.2025.101269","DOIUrl":"https://doi.org/10.1016/j.cels.2025.101269","url":null,"abstract":"<p><p>In a therapeutic context, supraphysiological expression of transgenes can compromise engineered phenotypes and lead to toxicity. To ensure a narrow range of transgene expression, we developed a single-transcript, microRNA-based incoherent feedforward loop called compact microRNA-mediated attenuator of noise and dosage (ComMAND). We experimentally tuned the ComMAND output profile, and we modeled the system to explore additional tuning strategies. By comparing ComMAND to two-gene implementations, we demonstrate the precise control afforded by the single-transcript architecture, particularly at low copy numbers. We show that ComMAND tightly regulates transgene expression from lentiviruses and precisely controls expression in primary human T cells, primary rat neurons, primary mouse embryonic fibroblasts, and human induced pluripotent stem cells. Finally, ComMAND effectively sets levels of the clinically relevant transgenes frataxin (FXN) and fragile X messenger ribonucleoprotein 1 (Fmr1) within a narrow window. Overall, ComMAND is a compact tool well suited to precisely specify the expression of therapeutic cargoes. A record of this paper's transparent peer review process is included in the supplemental information.</p>","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101269"},"PeriodicalIF":0.0,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144063516","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
Scalable image-based visualization and alignment of spatial transcriptomics datasets. 可扩展的基于图像的可视化和空间转录组学数据集的对齐。
Cell systems Pub Date : 2025-04-17 DOI: 10.1016/j.cels.2025.101264
Stephan Preibisch, Michael Innerberger, Daniel León-Periñán, Nikos Karaiskos, Nikolaus Rajewsky
{"title":"Scalable image-based visualization and alignment of spatial transcriptomics datasets.","authors":"Stephan Preibisch, Michael Innerberger, Daniel León-Periñán, Nikos Karaiskos, Nikolaus Rajewsky","doi":"10.1016/j.cels.2025.101264","DOIUrl":"https://doi.org/10.1016/j.cels.2025.101264","url":null,"abstract":"<p><p>We present the \"spatial transcriptomics imaging framework\" (STIM), an imaging-based computational framework focused on visualizing and aligning high-throughput spatial sequencing datasets. STIM is built on the powerful, scalable ImgLib2 and BigDataViewer (BDV) image data frameworks and thus enables novel development or transfer of existing computer vision techniques to the sequencing domain characterized by datasets with irregular measurement-spacing and arbitrary spatial resolution, such as spatial transcriptomics data generated by multiplexed targeted hybridization or spatial sequencing technologies. We illustrate STIM's capabilities by representing, interactively visualizing, 3D rendering, automatically registering, and segmenting publicly available spatial sequencing data from 13 serial sections of mouse brain tissue and from 19 sections of a human metastatic lymph node. We demonstrate that the simplest alignment mode of STIM achieves human-level accuracy.</p>","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101264"},"PeriodicalIF":0.0,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144055553","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
Signaling and transcriptional dynamics underlying early adaptation to oncogenic BRAF inhibition. 早期适应致癌BRAF抑制的信号和转录动力学。
Cell systems Pub Date : 2025-04-16 Epub Date: 2025-03-20 DOI: 10.1016/j.cels.2025.101239
Cameron T Flower, Chunmei Liu, Hui-Yu Chuang, Xiaoyang Ye, Hanjun Cheng, James R Heath, Wei Wei, Forest M White
{"title":"Signaling and transcriptional dynamics underlying early adaptation to oncogenic BRAF inhibition.","authors":"Cameron T Flower, Chunmei Liu, Hui-Yu Chuang, Xiaoyang Ye, Hanjun Cheng, James R Heath, Wei Wei, Forest M White","doi":"10.1016/j.cels.2025.101239","DOIUrl":"10.1016/j.cels.2025.101239","url":null,"abstract":"<p><p>A major contributor to poor sensitivity to anti-cancer kinase inhibitor therapy is drug-induced cellular adaptation, whereby remodeling of signaling and gene regulatory networks permits a drug-tolerant phenotype. Here, we resolve the scale and kinetics of critical subcellular events following oncogenic kinase inhibition and preceding cell cycle re-entry, using mass spectrometry-based phosphoproteomics and RNA sequencing (RNA-seq) to monitor the dynamics of thousands of growth- and survival-related signals over the first minutes, hours, and days of oncogenic BRAF inhibition in human melanoma cells. We observed sustained inhibition of the BRAF-ERK axis, gradual downregulation of cell cycle signaling, and three distinct, reversible phase transitions toward quiescence. Statistical inference of kinetically defined regulatory modules revealed a dominant compensatory induction of SRC family kinase (SFK) signaling, promoted in part by excess reactive oxygen species, rendering cells sensitive to co-treatment with an SFK inhibitor in vitro and in vivo, underscoring the translational potential for assessing early drug-induced adaptive signaling. A record of this paper's transparent peer review process is included in the supplemental information.</p>","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101239"},"PeriodicalIF":0.0,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12045616/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143674913","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
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