脑代谢组、脂质组和血糖的空间映射

IF 15.7 1区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Harrison A. Clarke, Xin Ma, Cameron J. Shedlock, Terrymar Medina, Tara R. Hawkinson, Lei Wu, Roberto A. Ribas, Shannon Keohane, Sakthivel Ravi, Jennifer L. Bizon, Sara N. Burke, Jose Francisco Abisambra, Matthew E. Merritt, Boone M. Prentice, Craig W. Vander Kooi, Matthew S. Gentry, Li Chen, Ramon C. Sun
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引用次数: 0

摘要

代谢物、脂质和聚糖是基本的但相互联系的生物分子,它们构成了代谢网络的基础。这些分子通过控制细胞生理和病理的多种途径动态地传递。在这里,我们提出了一个框架,同时空间分析代谢组,脂质组和糖从一个组织切片使用质谱成像。该工作流集成了一个计算平台,即空间增强多组学接口(Sami),它可以实现多组学集成、高维聚类、匹配分子特征的空间解剖映射和代谢途径富集。为了证明这种方法的实用性,我们应用Sami来评估不同脑区域的代谢多样性,并比较野生型和Ps19型阿尔茨海默病(AD)小鼠模型。我们的研究结果揭示了正常大脑中特定区域的代谢需求,并强调了Ps19模型中的代谢失调,为神经变性相关的生化改变提供了见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Spatial mapping of the brain metabolome lipidome and glycome

Spatial mapping of the brain metabolome lipidome and glycome

Metabolites, lipids, and glycans are fundamental but interconnected classes of biomolecules that form the basis of the metabolic network. These molecules are dynamically channeled through multiple pathways that govern cellular physiology and pathology. Here, we present a framework for the simultaneous spatial analysis of the metabolome, lipidome, and glycome from a single tissue section using mass spectrometry imaging. This workflow integrates a computational platform, the Spatial Augmented Multiomics Interface (Sami), which enables multiomics integration, high-dimensional clustering, spatial anatomical mapping of matched molecular features, and metabolic pathway enrichment. To demonstrate the utility of this approach, we applied Sami to evaluate metabolic diversity across distinct brain regions and to compare wild-type and Ps19 Alzheimer’s disease (AD) mouse models. Our findings reveal region-specific metabolic demands in the normal brain and highlight metabolic dysregulation in the Ps19 model, providing insights into the biochemical alterations associated with neurodegeneration.

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来源期刊
Nature Communications
Nature Communications Biological Science Disciplines-
CiteScore
24.90
自引率
2.40%
发文量
6928
审稿时长
3.7 months
期刊介绍: Nature Communications, an open-access journal, publishes high-quality research spanning all areas of the natural sciences. Papers featured in the journal showcase significant advances relevant to specialists in each respective field. With a 2-year impact factor of 16.6 (2022) and a median time of 8 days from submission to the first editorial decision, Nature Communications is committed to rapid dissemination of research findings. As a multidisciplinary journal, it welcomes contributions from biological, health, physical, chemical, Earth, social, mathematical, applied, and engineering sciences, aiming to highlight important breakthroughs within each domain.
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