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AutophagyNet:用于分析自噬及其调控的高分辨率数据源。

AutophagyNet: high-resolution data source for the analysis of autophagy and its regulation.

机构信息

Earlham Institute, Norwich, UK.

Department of Genetics, ELTE Eötvös Loránd University, Budapest, Hungary.

出版信息

Autophagy. 2024 Jan;20(1):188-201. doi: 10.1080/15548627.2023.2247737. Epub 2023 Aug 17.

Abstract

Macroautophagy/autophagy is a highly-conserved catabolic procss eliminating dysfunctional cellular components and invading pathogens. Autophagy malfunction contributes to disorders such as cancer, neurodegenerative and inflammatory diseases. Understanding autophagy regulation in health and disease has been the focus of the last decades. We previously provided an integrated database for autophagy research, the Autophagy Regulatory Network (ARN). For the last eight years, this resource has been used by thousands of users. Here, we present a new and upgraded resource, AutophagyNet. It builds on the previous database but contains major improvements to address user feedback and novel needs due to the advancement in omics data availability. AutophagyNet contains updated interaction curation and integration of over 280,000 experimentally verified interactions between core autophagy proteins and their protein, transcriptional and post-transcriptional regulators as well as their potential upstream pathway connections. AutophagyNet provides annotations for each core protein about their role: 1) in different types of autophagy (mitophagy, xenophagy, etc.); 2) in distinct stages of autophagy (initiation, expansion, termination, etc.); 3) with subcellular and tissue-specific localization. These annotations can be used to filter the dataset, providing customizable download options tailored to the user's needs. The resource is available in various file formats (e.g. CSV, BioPAX and PSI-MI), and data can be analyzed and visualized directly in Cytoscape. The multi-layered regulation of autophagy can be analyzed by combining AutophagyNet with tissue- or cell type-specific (multi-)omics datasets (e.g. transcriptomic or proteomic data). The resource is publicly accessible at http://autophagynet.org.: ARN: Autophagy Regulatory Network; ATG: autophagy related; BCR: B cell receptor pathway; BECN1: beclin 1; GABARAP: GABA type A receptor-associated protein; IIP: innate immune pathway; LIR: LC3-interacting region; lncRNA: long non-coding RNA; MAP1LC3B: microtubule associated protein 1 light chain 3 beta; miRNA: microRNA; NHR: nuclear hormone receptor; PTM: post-translational modification; RTK: receptor tyrosine kinase; TCR: T cell receptor; TLR: toll like receptor.

摘要

自噬是一种高度保守的分解代谢过程,可消除功能失调的细胞成分和入侵的病原体。自噬功能障碍与癌症、神经退行性和炎症性疾病等疾病有关。了解健康和疾病中的自噬调控一直是过去几十年的研究重点。我们之前提供了一个用于自噬研究的综合数据库,即自噬调控网络(ARN)。在过去的八年中,成千上万的用户使用了这个资源。在这里,我们呈现了一个新的和升级的资源,AutophagyNet。它建立在前一个数据库的基础上,但包含了重大改进,以解决用户反馈和由于组学数据可用性的进步而产生的新需求。AutophagyNet 包含了经过更新的相互作用注释,并整合了超过 280,000 个核心自噬蛋白与其蛋白、转录和转录后调节因子及其潜在上游途径连接的实验验证相互作用。AutophagyNet 为每个核心蛋白提供了关于它们在不同类型的自噬(线粒体自噬、异噬等)、不同自噬阶段(起始、扩展、终止等)以及亚细胞和组织特异性定位中的作用的注释。这些注释可用于过滤数据集,提供可定制的下载选项,以满足用户的需求。该资源有多种文件格式(如 CSV、BioPAX 和 PSI-MI),并且可以直接在 Cytoscape 中分析和可视化数据。通过将 AutophagyNet 与组织或细胞类型特异性(多)组学数据集(如转录组或蛋白质组数据)结合使用,可以分析自噬的多层次调控。该资源可在 http://autophagynet.org 上公开访问。ARN:自噬调控网络;ATG:自噬相关;BCR:B 细胞受体途径;BECN1:beclin 1;GABARAP:GABA 型 A 受体相关蛋白;IIP:先天免疫途径;LIR:LC3 相互作用区域;lncRNA:长非编码 RNA;MAP1LC3B:微管相关蛋白 1 轻链 3β;miRNA:microRNA;NHR:核激素受体;PTM:翻译后修饰;RTK:受体酪氨酸激酶;TCR:T 细胞受体;TLR: toll 样受体。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f0f0/10761021/ba08af8b1321/KAUP_A_2247737_F0001_OC.jpg

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