Cell systems最新文献_第8页

Integrated multi-omic characterizations of the synapse reveal RNA processing factors and ubiquitin ligases associated with neurodevelopmental disorders. 突触的综合多组学特征揭示了与神经发育障碍相关的RNA加工因子和泛素连接酶。

Cell systems Pub Date : 2025-04-16 Epub Date: 2025-03-06 DOI: 10.1016/j.cels.2025.101204

Yuan Mei, Maya L Gosztyla, Xinzhu Tan, Lara E Dozier, Brent Wilkinson, Justin McKetney, John Lee, Michael Chen, Dorothy Tsai, Hema Kopalle, Marina A Gritsenko, Nicolas Hartel, Nicholas A Graham, Ilse Flores, Stephen K Gilmore-Hall, Shuhao Xu, Charlotte A Marquez, Sophie N Liu, Dylan Fong, Jing Chen, Kate Licon, Derek Hong, Sarah N Wright, Jason F Kreisberg, Alexi Nott, Richard D Smith, Wei-Jun Qian, Danielle L Swaney, Lilia M Iakoucheva, Nevan J Krogan, Gentry N Patrick, Yang Zhou, Guoping Feng, Marcelo P Coba, Gene W Yeo, Trey Ideker

{"title":"Integrated multi-omic characterizations of the synapse reveal RNA processing factors and ubiquitin ligases associated with neurodevelopmental disorders.","authors":"Yuan Mei, Maya L Gosztyla, Xinzhu Tan, Lara E Dozier, Brent Wilkinson, Justin McKetney, John Lee, Michael Chen, Dorothy Tsai, Hema Kopalle, Marina A Gritsenko, Nicolas Hartel, Nicholas A Graham, Ilse Flores, Stephen K Gilmore-Hall, Shuhao Xu, Charlotte A Marquez, Sophie N Liu, Dylan Fong, Jing Chen, Kate Licon, Derek Hong, Sarah N Wright, Jason F Kreisberg, Alexi Nott, Richard D Smith, Wei-Jun Qian, Danielle L Swaney, Lilia M Iakoucheva, Nevan J Krogan, Gentry N Patrick, Yang Zhou, Guoping Feng, Marcelo P Coba, Gene W Yeo, Trey Ideker","doi":"10.1016/j.cels.2025.101204","DOIUrl":"10.1016/j.cels.2025.101204","url":null,"abstract":"The molecular composition of the excitatory synapse is incompletely defined due to its dynamic nature across developmental stages and neuronal populations. To address this gap, we apply proteomic mass spectrometry to characterize the synapse in multiple biological models, including the fetal human brain and human induced pluripotent stem cell (hiPSC)-derived neurons. To prioritize the identified proteins, we develop an orthogonal multi-omic screen of genomic, transcriptomic, interactomic, and structural data. This data-driven framework identifies proteins with key molecular features intrinsic to the synapse, including characteristic patterns of biophysical interactions and cross-tissue expression. The multi-omic analysis captures synaptic proteins across developmental stages and experimental systems, including 493 synaptic candidates supported by proteomics. We further investigate three such proteins that are associated with neurodevelopmental disorders-Cullin 3 (CUL3), DEAD-box helicase 3 X-linked (DDX3X), and Y-box binding protein-1 (YBX1)-by mapping their networks of physically interacting synapse proteins or transcripts. Our study demonstrates the potential of an integrated multi-omic approach to more comprehensively resolve the synaptic architecture.","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101204"},"PeriodicalIF":0.0,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12283108/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143588843","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

Minding the synapse: A multi-omic approach reveals hidden regulators of neurodevelopment. 注意突触：一种多组学方法揭示了隐藏的神经发育调节因子。

Cell systems Pub Date : 2025-04-16 DOI: 10.1016/j.cels.2025.101263

Alicia Ljungdahl, Ryan S Dhindsa

引用次数: 0

SpaGRN: Investigating spatially informed regulatory paths for spatially resolved transcriptomics data. SpaGRN：研究空间解析转录组学数据的空间知情调控路径。

Cell systems Pub Date : 2025-04-16 Epub Date: 2025-04-02 DOI: 10.1016/j.cels.2025.101243

Yao Li, Xiaobin Liu, Lidong Guo, Kai Han, Shuangsang Fang, Xinjiang Wan, Dantong Wang, Xun Xu, Ling Jiang, Guangyi Fan, Mengyang Xu

{"title":"SpaGRN: Investigating spatially informed regulatory paths for spatially resolved transcriptomics data.","authors":"Yao Li, Xiaobin Liu, Lidong Guo, Kai Han, Shuangsang Fang, Xinjiang Wan, Dantong Wang, Xun Xu, Ling Jiang, Guangyi Fan, Mengyang Xu","doi":"10.1016/j.cels.2025.101243","DOIUrl":"10.1016/j.cels.2025.101243","url":null,"abstract":"Cells spatially organize into distinct cell types or functional domains through localized gene regulatory networks. However, current spatially resolved transcriptomics analyses fail to integrate spatial constraints and proximal cell influences, limiting the mechanistic understanding of tissue organization. Here, we introduce SpaGRN, a statistical framework that reconstructs cell-type- or functional-domain-specific, dynamic, and spatial regulons by coupling intracellular spatial regulatory causality with extracellular signaling path information. Benchmarking across synthetic and real datasets demonstrates SpaGRN's superior precision over state-of-the-art tools in identifying context-dependent regulons. Applied to diverse spatially resolved transcriptomics platforms (Stereo-seq, STARmap, MERFISH, CosMx, Slide-seq, and 10x Visium), complex cancerous samples, and 3D datasets of developing Drosophila embryos and larvae, SpaGRN not only provides a versatile toolkit for decoding receptor-mediated spatial regulons but also reveals spatiotemporal regulatory mechanisms underlying organogenesis and inflammation.","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101243"},"PeriodicalIF":0.0,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143782281","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

Compact transcription factor cassettes generate functional, engraftable motor neurons by direct conversion. 紧凑的转录因子盒式磁带通过直接转化产生功能性的、可移植的运动神经元。

Cell systems Pub Date : 2025-04-16 Epub Date: 2025-03-13 DOI: 10.1016/j.cels.2025.101206

Nathan B Wang, Honour O Adewumi, Brittany A Lende-Dorn, Adam M Beitz, Timothy M O'Shea, Kate E Galloway

{"title":"Compact transcription factor cassettes generate functional, engraftable motor neurons by direct conversion.","authors":"Nathan B Wang, Honour O Adewumi, Brittany A Lende-Dorn, Adam M Beitz, Timothy M O'Shea, Kate E Galloway","doi":"10.1016/j.cels.2025.101206","DOIUrl":"10.1016/j.cels.2025.101206","url":null,"abstract":"Direct conversion generates patient-specific, disease-relevant cell types, such as neurons, that are rare, limited, or difficult to isolate from common and easily accessible cells, such as skin cells. However, low rates of direct conversion and complex protocols limit scalability and, thus, the potential of cell-fate conversion for biomedical applications. Here, we optimize the conversion protocol by examining process parameters, including transcript design; delivery via adeno-associated virus (AAV), retrovirus, and lentivirus; cell seeding density; and the impact of media conditions. Thus, we report a compact, portable conversion process that boosts proliferation and increases direct conversion of mouse fibroblasts to induced motor neurons (iMNs) to achieve high conversion rates of above 1,000%, corresponding to more than ten motor neurons yielded per cell seeded, which we achieve through expansion. Our optimized, direct conversion process generates functional motor neurons at scales relevant for cell therapies (>107 cells) that graft with the mouse central nervous system. High-efficiency, compact, direct conversion systems will support scaling to patient-specific, neural cell therapies.","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101206"},"PeriodicalIF":0.0,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12207523/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143630724","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

Assembly of stool-derived bacterial communities follows "early-bird" resource utilization dynamics. 粪便衍生细菌群落的组装遵循“早起鸟”的资源利用动态。

Cell systems Pub Date : 2025-04-16 Epub Date: 2025-03-28 DOI: 10.1016/j.cels.2025.101240

Andrés Aranda-Díaz, Lisa Willis, Taylor H Nguyen, Po-Yi Ho, Jean Vila, Tani Thomsen, Taylor Chavez, Rose Yan, Feiqiao Brian Yu, Norma Neff, Brian C DeFelice, Alvaro Sanchez, Sylvie Estrela, Kerwyn Casey Huang

{"title":"Assembly of stool-derived bacterial communities follows \"early-bird\" resource utilization dynamics.","authors":"Andrés Aranda-Díaz, Lisa Willis, Taylor H Nguyen, Po-Yi Ho, Jean Vila, Tani Thomsen, Taylor Chavez, Rose Yan, Feiqiao Brian Yu, Norma Neff, Brian C DeFelice, Alvaro Sanchez, Sylvie Estrela, Kerwyn Casey Huang","doi":"10.1016/j.cels.2025.101240","DOIUrl":"10.1016/j.cels.2025.101240","url":null,"abstract":"Diet can impact host health through changes to the gut microbiota, yet we lack mechanistic understanding linking nutrient availability and microbiota composition. Here, we use thousands of microbial communities cultured in vitro from human stool to develop a predictive model of community composition upon addition of single nutrients from central carbon metabolism to a complex medium. Among these communities, membership was largely determined by the donor stool, whereas relative abundances were determined by the supplemental carbon source. The absolute abundance of most taxa was independent of the supplementing nutrient due to the ability of a few organisms to quickly exhaust their niche in the complex medium and then exploit and monopolize the supplemental carbon source. Relative abundances of dominant taxa could be predicted from the nutritional preferences and growth dynamics of species in isolation, and exceptions were consistent with strain-level variation in growth capabilities. Our study reveals that assembly of this community of gut commensals can be explained by nutrient utilization dynamics that provide a predictive framework for manipulating community composition through nutritional perturbations.","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101240"},"PeriodicalIF":0.0,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143744676","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

Probing enzyme-dependent pseudouridylation using direct RNA sequencing to assess epitranscriptome plasticity in a neuronal cell line. 利用直接RNA测序探测酶依赖性假尿嘧啶化以评估神经细胞系的表转录组可塑性。

Cell systems Pub Date : 2025-04-16 Epub Date: 2025-03-20 DOI: 10.1016/j.cels.2025.101238

Oleksandra Fanari, Sepideh Tavakoli, Yuchen Qiu, Amr Makhamreh, Keqing Nian, Stuart Akeson, Michele Meseonznik, Caroline A McCormick, Dylan Bloch, Howard Gamper, Miten Jain, Ya-Ming Hou, Meni Wanunu, Sara H Rouhanifard

{"title":"Probing enzyme-dependent pseudouridylation using direct RNA sequencing to assess epitranscriptome plasticity in a neuronal cell line.","authors":"Oleksandra Fanari, Sepideh Tavakoli, Yuchen Qiu, Amr Makhamreh, Keqing Nian, Stuart Akeson, Michele Meseonznik, Caroline A McCormick, Dylan Bloch, Howard Gamper, Miten Jain, Ya-Ming Hou, Meni Wanunu, Sara H Rouhanifard","doi":"10.1016/j.cels.2025.101238","DOIUrl":"10.1016/j.cels.2025.101238","url":null,"abstract":"Chemical modifications in mRNAs, such as pseudouridine (psi), can control gene expression. Yet, we know little about how they are regulated, especially in neurons. We applied nanopore direct RNA sequencing to investigate psi dynamics in SH-SY5Y cells in response to two perturbations that model a natural and unnatural cellular state: retinoic-acid-mediated differentiation (healthy) and exposure to the neurotoxicant lead (unhealthy). We discovered that the expression of some psi writers changes significantly in response to physiological conditions. We also found that globally, lead-treated cells have more psi sites but lower relative occupancy than untreated cells and differentiated cells. Examples of highly plastic sites were accompanied by constant expression for psi writers, suggesting trans-regulation. Many positions were static throughout all three cellular states, suggestive of a \"housekeeping\" function. This study enables investigations into mechanisms that control psi modifications in neurons and their possible protective effects in response to cellular stress.","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101238"},"PeriodicalIF":0.0,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12006983/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143674910","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

Explainable modeling of single-cell perturbation data using attention and sparse dictionary learning. 利用注意力和稀疏字典学习对单细胞扰动数据进行可解释建模

Cell systems Pub Date : 2025-04-16 Epub Date: 2025-04-04 DOI: 10.1016/j.cels.2025.101245

Yang Xu, Stephen Fleming, Matthew Tegtmeyer, Steven A McCarroll, Mehrtash Babadi

{"title":"Explainable modeling of single-cell perturbation data using attention and sparse dictionary learning.","authors":"Yang Xu, Stephen Fleming, Matthew Tegtmeyer, Steven A McCarroll, Mehrtash Babadi","doi":"10.1016/j.cels.2025.101245","DOIUrl":"10.1016/j.cels.2025.101245","url":null,"abstract":"Single-cell transcriptomics, in conjunction with genetic and compound perturbations, offers a robust approach for exploring cellular behaviors in diverse contexts. Such experiments allow uncovering cell-state-specific responses to perturbations and unraveling the intricate molecular mechanisms governing cellular behavior. However, prevailing computational methods predominantly focus on predicting average cellular responses, disregarding inherent response heterogeneity associated with cell state diversity and model explainability. In this study, we present CellCap, a deep generative model designed for the end-to-end analysis of single-cell perturbation experiments. CellCap employs sparse dictionary learning in a latent space to deconstruct cell-state-specific perturbation responses into a set of transcriptional response programs and utilizes an attention mechanism to capture correspondence between cell state and perturbation response. We thoroughly evaluate CellCap's interpretability using multiple simulated scenarios as well as two real single-cell perturbation datasets. Our results demonstrate that CellCap successfully uncovers the relationship between cell state and perturbation response, unveiling insights overlooked in previous analyses.","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101245"},"PeriodicalIF":0.0,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143789413","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

Evaluation of De Vries et al.: Quantifying cellular shapes and how they correlate to cellular responses. De Vries等人的评价：量化细胞形状及其与细胞反应的关系。

Cell systems Pub Date : 2025-03-19 DOI: 10.1016/j.cels.2025.101242

Manuel D Leonetti

引用次数: 0

Virus targeting as a dominant driver of interfacial evolution in the structurally resolved human-virus protein-protein interaction network. 在结构上解决的人-病毒蛋白-蛋白相互作用网络中，病毒靶向是界面进化的主要驱动因素。

Cell systems Pub Date : 2025-03-19 Epub Date: 2025-02-28 DOI: 10.1016/j.cels.2025.101202

Wan-Chun Su, Yu Xia

{"title":"Virus targeting as a dominant driver of interfacial evolution in the structurally resolved human-virus protein-protein interaction network.","authors":"Wan-Chun Su, Yu Xia","doi":"10.1016/j.cels.2025.101202","DOIUrl":"10.1016/j.cels.2025.101202","url":null,"abstract":"Regions on a host protein that interact with virus proteins (exogenous interfaces) frequently overlap with those that interact with other host proteins (endogenous interfaces), resulting in competition between hosts and viruses for these shared interfaces (mimic-targeted interfaces). Yet, the evolutionary consequences of this competitive relationship on the host are not well understood. Here, we integrate experimentally determined structures and homology-based templates of protein complexes with protein-protein interaction networks to construct a high-resolution human-virus structural interaction network. We perform site-specific evolutionary rate analyses on this structural interaction network and find that exogenous-specific interfaces evolve faster than endogenous-specific interfaces. Mimic-targeted interfaces evolve as fast as exogenous-specific interfaces, despite being targeted by both human and virus proteins. Our findings suggest that virus targeting plays a dominant role in host interfacial evolution within the context of domain-domain interactions and that mimic-targeted interfaces on human proteins are the key battleground for a mammalian-specific host-virus evolutionary arms race.","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101202"},"PeriodicalIF":0.0,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143538243","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

Geometric deep learning and multiple-instance learning for 3D cell-shape profiling. 三维细胞形状轮廓的几何深度学习和多实例学习。

Cell systems Pub Date : 2025-03-19 DOI: 10.1016/j.cels.2025.101229

Matt De Vries, Lucas G Dent, Nathan Curry, Leo Rowe-Brown, Vicky Bousgouni, Olga Fourkioti, Reed Naidoo, Hugh Sparks, Adam Tyson, Chris Dunsby, Chris Bakal

{"title":"Geometric deep learning and multiple-instance learning for 3D cell-shape profiling.","authors":"Matt De Vries, Lucas G Dent, Nathan Curry, Leo Rowe-Brown, Vicky Bousgouni, Olga Fourkioti, Reed Naidoo, Hugh Sparks, Adam Tyson, Chris Dunsby, Chris Bakal","doi":"10.1016/j.cels.2025.101229","DOIUrl":"10.1016/j.cels.2025.101229","url":null,"abstract":"The three-dimensional (3D) morphology of cells emerges from complex cellular and environmental interactions, serving as an indicator of cell state and function. In this study, we used deep learning to discover morphology representations and understand cell states. This study introduced MorphoMIL, a computational pipeline combining geometric deep learning and attention-based multiple-instance learning to profile 3D cell and nuclear shapes. We used 3D point-cloud input and captured morphological signatures at single-cell and population levels, accounting for phenotypic heterogeneity. We applied these methods to over 95,000 melanoma cells treated with clinically relevant and cytoskeleton-modulating chemical and genetic perturbations. The pipeline accurately predicted drug perturbations and cell states. Our framework revealed subtle morphological changes associated with perturbations, key shapes correlating with signaling activity, and interpretable insights into cell-state heterogeneity. MorphoMIL demonstrated superior performance and generalized across diverse datasets, paving the way for scalable, high-throughput morphological profiling in drug discovery. A record of this paper's transparent peer review process is included in the supplemental information.","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":"16 3","pages":"101229"},"PeriodicalIF":0.0,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143672010","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