中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Deep Learning-Based Morphological Classification of Endoplasmic Reticulum Under Stress

文献类型:期刊论文

作者Guo, Yuanhao3,4; Shen, Di2; Zhou, Yanfeng3,4; Yang, Yutong4; Liang, Jinzhao4; Zhou, Yating3,4; Li, Ningning1; Liu, Yu2; Yang, Ge3,4; Li, Wenjing3,4
刊名FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY
出版日期2022-01-21
卷号9页码:13
ISSN号2296-634X
关键词ER stress morphological classification image biomarker deep learning homeostasis
DOI10.3389/fcell.2021.767866
通讯作者Yang, Ge(ge.yang@ia.ac.cn) ; Li, Wenjing(wenjing.li@ia.ac.cn)
英文摘要Endoplasmic reticulum stress (ER stress) is a condition that is defined by abnormal accumulation of unfolded proteins. It plays an important role in maintaining cellular protein, lipid, and ion homeostasis. By triggering the unfolded protein response (UPR) under ER stress, cells restore homeostasis or undergo apoptosis. Chronic ER stress is implicated in many human diseases. Despite extensive studies on related signaling mechanisms, reliable image biomarkers for ER stress remain lacking. To address this deficiency, we have validated a morphological image biomarker for ER stress and have developed a deep learning-based assay to enable automated detection and analysis of this marker for screening studies. Specifically, ER under stress exhibits abnormal morphological patterns that feature ring-shaped structures called whorls (WHs). Using a highly specific chemical probe for unfolded and aggregated proteins, we find that formation of ER whorls is specifically associated with the accumulation of the unfolded and aggregated proteins. This confirms that ER whorls can be used as an image biomarker for ER stress. To this end, we have developed ER-WHs-Analyzer, a deep learning-based image analysis assay that automatically recognizes and localizes ER whorls similarly as human experts. It does not require laborious manual annotation of ER whorls for training of deep learning models. Importantly, it reliably classifies different patterns of ER whorls induced by different ER stress drugs. Overall, our study provides mechanistic insights into morphological patterns of ER under stress as well as an image biomarker assay for screening studies to dissect related disease mechanisms and to accelerate related drug discoveries. It demonstrates the effectiveness of deep learning in recognizing and understanding complex morphological phenotypes of ER.
WOS关键词UNFOLDED PROTEIN RESPONSE ; MODULATES ER STRESS ; MICROSCOPY IMAGES ; IRE1-ALPHA ; AUTOPHAGY ; TRANSLATION ; COMBINATION ; EXPRESSION ; DISCOVERY ; APOPTOSIS
资助项目Natural Science Foundation of China[91954201] ; Natural Science Foundation of China[31971289] ; Natural Science Foundation of China[32101216] ; Chinese Academy of Sciences[292019000056] ; University of Chinese Academy of Sciences[115200M001] ; Beijing Municipal Science & Technology Commission[5202022]
WOS研究方向Cell Biology ; Developmental Biology
语种英语
出版者FRONTIERS MEDIA SA
WOS记录号WOS:000751283800001
资助机构Natural Science Foundation of China ; Chinese Academy of Sciences ; University of Chinese Academy of Sciences ; Beijing Municipal Science & Technology Commission
源URL[http://ir.ia.ac.cn/handle/173211/47370]  
专题模式识别国家重点实验室_计算生物学与机器智能
通讯作者Yang, Ge; Li, Wenjing
作者单位1.Sun Yat Sen Univ, Affiliated Hosp 7, Tomas Lindahl Lab, Shenzhen, Peoples R China
2.Chinese Acad Sci, Dalian Inst Chem Phys, CAS Key Lab Separat Sci Analyt Chem, Dalian, Peoples R China
3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China
4.Chinese Acad Sci, Inst Automat, Lab Computat Biol & Machine Intelligence, Natl Lab Pattern Recognit, Beijing, Peoples R China
推荐引用方式
GB/T 7714
Guo, Yuanhao,Shen, Di,Zhou, Yanfeng,et al. Deep Learning-Based Morphological Classification of Endoplasmic Reticulum Under Stress[J]. FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY,2022,9:13.
APA Guo, Yuanhao.,Shen, Di.,Zhou, Yanfeng.,Yang, Yutong.,Liang, Jinzhao.,...&Li, Wenjing.(2022).Deep Learning-Based Morphological Classification of Endoplasmic Reticulum Under Stress.FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY,9,13.
MLA Guo, Yuanhao,et al."Deep Learning-Based Morphological Classification of Endoplasmic Reticulum Under Stress".FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY 9(2022):13.

入库方式: OAI收割

来源:自动化研究所

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