Cell systemsPub Date : 2025-03-19Epub Date: 2025-03-03DOI: 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":"<p><p>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.</p>","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}
Cell systemsPub Date : 2025-03-19Epub Date: 2025-03-12DOI: 10.1016/j.cels.2025.101234
William Benman, Pavan Iyengar, Thomas R Mumford, Zikang Huang, Manya Kapoor, Grace Liu, Lukasz J Bugaj
{"title":"Multiplexed dynamic control of temperature to probe and observe mammalian cells.","authors":"William Benman, Pavan Iyengar, Thomas R Mumford, Zikang Huang, Manya Kapoor, Grace Liu, Lukasz J Bugaj","doi":"10.1016/j.cels.2025.101234","DOIUrl":"10.1016/j.cels.2025.101234","url":null,"abstract":"<p><p>Temperature is an important biological stimulus, yet there is a lack of approaches to modulate the temperature of biological samples in a dynamic and high-throughput manner. The thermoPlate is a device for programmable control of temperature in a 96-well plate, compatible with cell culture and microscopy. The thermoPlate maintains feedback control of temperature independently in each well, with minutes-scale heating and cooling through ΔT = 15-20°C. We first used the thermoPlate to characterize the rapid temperature-dependent phase separation of a synthetic elastin-like polypeptide (ELP<sub>53</sub>). We then examined stress granule (SG) formation in response to dynamic heat stress, revealing adaptation of SGs to persistent heat and formation of a memory of stress that prevented SG formation in response to subsequent heat shocks. The capabilities and open-source nature of the thermoPlate will empower the study and engineering of a wide range of thermoresponsive phenomena. 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":"101234"},"PeriodicalIF":0.0,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143626690","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}
Cell systemsPub Date : 2025-03-19DOI: 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":"https://doi.org/10.1016/j.cels.2025.101235","url":null,"abstract":"<p><p>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.</p>","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}
Cell systemsPub Date : 2025-03-19Epub Date: 2025-02-18DOI: 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":"<p><p>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.</p>","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}
Cell systemsPub Date : 2025-03-19Epub Date: 2025-03-04DOI: 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":"<p><p>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.</p>","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101201"},"PeriodicalIF":0.0,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143569193","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}
Cell systemsPub Date : 2025-03-18DOI: 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":"<p><p>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.</p>","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101238"},"PeriodicalIF":0.0,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143674910","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}
Cell systemsPub Date : 2025-03-17DOI: 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":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143674913","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}
Cell systemsPub Date : 2025-03-11DOI: 10.1016/j.cels.2025.101205
Nathan B Wang, Brittany A Lende-Dorn, Adam M Beitz, Patrick Han, Honour O Adewumi, Timothy M O'Shea, Kate E Galloway
{"title":"Proliferation history and transcription factor levels drive direct conversion to motor neurons.","authors":"Nathan B Wang, Brittany A Lende-Dorn, Adam M Beitz, Patrick Han, Honour O Adewumi, Timothy M O'Shea, Kate E Galloway","doi":"10.1016/j.cels.2025.101205","DOIUrl":"10.1016/j.cels.2025.101205","url":null,"abstract":"<p><p>The sparse and stochastic nature of conversion has obscured our understanding of how transcription factors (TFs) drive cells to new identities. To overcome this limit, we develop a tailored, high-efficiency conversion system that increases the direct conversion of fibroblasts to motor neurons 100-fold. By tailoring the cocktail to a minimal set of transcripts, we reduce extrinsic variation, allowing us to examine how proliferation and TFs synergistically drive conversion. We show that cell state-as set by proliferation history-defines how cells interpret the levels of TFs. Controlling for proliferation history and titrating each TF, we find that conversion correlates with levels of the pioneer TF Ngn2. By isolating cells by both their proliferation history and Ngn2 levels, we demonstrate that levels of Ngn2 expression alone are insufficient to predict conversion rates. Rather, proliferation history and TF levels combine to drive direct conversion. Finally, increasing the proliferation rate of adult human fibroblasts generates morphologically mature induced human motor neurons at high rates.</p>","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101205"},"PeriodicalIF":0.0,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143630934","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}
Cell systemsPub Date : 2025-03-10DOI: 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":"https://doi.org/10.1016/j.cels.2025.101206","url":null,"abstract":"<p><p>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 (>10<sup>7</sup> cells) that graft with the mouse central nervous system. High-efficiency, compact, direct conversion systems will support scaling to patient-specific, neural cell therapies.</p>","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101206"},"PeriodicalIF":0.0,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143630724","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}
Cell systemsPub Date : 2025-03-03DOI: 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":"https://doi.org/10.1016/j.cels.2025.101204","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"101204"},"PeriodicalIF":0.0,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143588843","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}