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.
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http://dx.doi.org/10.1016/j.cels.2025.101204 | DOI Listing |
Gastroenterology
March 2025
APC Microbiome Ireland, College of Medicine and Health, University College Cork, Cork, Ireland.
Inflammatory bowel disease (IBD) is marked by significant clinical heterogeneity, posing challenges for accurate diagnosis and personalized treatment strategies. Conventional approaches, such as endoscopy and histology, often fail to adequately and accurately predict medium and long-term outcomes, leading to suboptimal patient management. Artificial intelligence (AI) is emerging as a transformative force enabling standardized, accurate, and timely disease assessment and outcome prediction, including therapeutic response.
View Article and Find Full Text PDFRedox Biol
March 2025
Laboratory for Disease Glycoproteomics, College of Life Sciences, Northwest University, Xi'an, 710069, PR China. Electronic address:
Ovarian aging typically precedes the decline of other organ systems, yet its molecular mechanisms remain poorly understood. Glycosylation as one of the most important protein modifications has been especially unexplored in this context. Here, we present the first high-resolution glycoproteomic landscape of aging mouse ovaries, uncovering site-specific N-glycan signatures across subcellular components such as high proportions of complex glycans, core fucosylation, and LacdiNAc branches at the zone pellucida.
View Article and Find Full Text PDFBrief Bioinform
March 2025
School of Artificial Intelligence, Jilin University, 3003 Qianjin Street, Changchun 130012, Jilin Province, China.
Identifying genes causally linked to cancer from a multi-omics perspective is essential for understanding the mechanisms of cancer and improving therapeutic strategies. Traditional statistical and machine-learning methods that rely on generalized correlation approaches to identify cancer genes often produce redundant, biased predictions with limited interpretability, largely due to overlooking confounding factors, selection biases, and the nonlinear activation function in neural networks. In this study, we introduce a novel framework for identifying cancer genes across multiple omics domains, named ICGI (Integrative Causal Gene Identification), which leverages a large language model (LLM) prompted with causality contextual cues and prompts, in conjunction with data-driven causal feature selection.
View Article and Find Full Text PDFDiscov Oncol
March 2025
Department of Hematology, Anqing Municipal Hospital, Anqing Hospital Affiliated to Anhui Medical University, Anqing, China.
Clinical management of acute myeloid leukemia (AML) poses significant challenges due to its poor prognosis and heterogeneous nature. Discovering new biomarkers is crucial for improving risk assessment and customizing treatment approaches. While leukocyte-specific transcript 1 (LST1) is implicated in inflammation and immune regulation, its function in AML remains ambiguous.
View Article and Find Full Text PDFBiophys Rep
February 2025
Department of Analytical Chemistry, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China.
Advancements in molecular characterization technologies have accelerated targeted cancer therapy research at unprecedented resolution and dimensionality. Integrating comprehensive multi-omic molecular profiling of a tumor, proteogenomics, marks a transformative milestone for preclinical cancer research. In this paper, we initially provided an overview of proteogenomics in cancer research, spanning genomics, transcriptomics, and proteomics.
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