How do cells optimize luminal environments of endosomes/lysosomes for efficient inflammatory responses?

作者
Toshihiko Kobayashi,Tsubasa Tanaka,Noriko Toyama‐Sorimachi
出处
期刊:Journal of Biochemistry [Oxford University Press]
卷期号:154 (6): 491-499 被引量:21
标识
DOI:10.1093/jb/mvt099
摘要

The endosome/lysosome compartments play pivotal roles in immune cell functions as signalling platforms. These intracellular compartments can efficiently restrict the localization of signalling complexes and temporally regulate signalling events to produce qualitatively different outcomes. Immune cells also exploit the endosome/lysosome system for signal transduction and intercellular communication to elicit immune responses. Antigen-presenting cells such as dendritic cells and macrophages take up pathogens by endocytosis and prepare antigens via the endosome/lysosome system. At the same time, pathogen-derived DNA and RNA are recognized by immune sensors at the endosome/lysosome compartments, which transmit signals to induce immune responses. Recent studies revealed the importance of controlling the endosomal/lysosomal environment for eliciting efficient signalling events at the endosomes/lysosomes. Many factors including pH, membrane potential, amino acid concentrations and lipid composition are finely tuned at the endosome/lysosome compartments, and dysregulation of these factors greatly affect immune cell functions. Redox-related molecules and various types of transporters are involved in the control of endosomal/lysosomal environment and could be good therapeutic targets for treating autoimmune diseases.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
1秒前
2秒前
可可发布了新的文献求助10
3秒前
莫听南发布了新的文献求助10
4秒前
夏虫发布了新的文献求助10
5秒前
英姑应助elle采纳,获得10
5秒前
wddhy发布了新的文献求助10
5秒前
愤怒的豆腐人完成签到,获得积分10
6秒前
7秒前
大模型应助SnownS采纳,获得80
7秒前
咧咧咧完成签到,获得积分10
7秒前
渡人舟应助GSR采纳,获得10
10秒前
斯文败类应助莫听南采纳,获得10
10秒前
认真觅荷完成签到 ,获得积分10
10秒前
Orange应助莫听南采纳,获得10
10秒前
科研通AI6.2应助莫听南采纳,获得10
10秒前
斯文败类应助莫听南采纳,获得10
11秒前
黄油小熊完成签到 ,获得积分10
11秒前
11秒前
12秒前
科研通AI6.3应助听闻墨笙采纳,获得10
14秒前
15秒前
16秒前
白石人家应助阳光采纳,获得10
16秒前
夏虫完成签到,获得积分10
16秒前
wddhy完成签到,获得积分10
16秒前
紧张的枫叶完成签到,获得积分10
16秒前
朝闻道完成签到 ,获得积分10
17秒前
壮观又亦发布了新的文献求助10
18秒前
19秒前
大个应助无私的画笔采纳,获得10
20秒前
21秒前
你好发布了新的文献求助10
22秒前
23秒前
毛毛哦啊完成签到,获得积分10
23秒前
大模型应助雪白秋灵采纳,获得30
25秒前
Apricity发布了新的文献求助10
26秒前
光光光光头完成签到 ,获得积分10
26秒前
阿聪发布了新的文献求助10
27秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Handbuch Trainingswissenschaft – Trainingslehre 500
Additive Manufacturing Design and Applications (ASM Handbook, Volume 24A) 500
Variations: A More Diverse Picture of Contemporary Art 400
A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) Fourth Edition 400
Induction Heating and Heat Treatment (ASM Handbook, Volume 4C) 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7587101
求助须知:如何正确求助?哪些是违规求助? 9165510
关于积分的说明 19615773
捐赠科研通 7167587
什么是DOI,文献DOI怎么找? 3266810
关于科研通互助平台的介绍 2431763
邀请新用户注册赠送积分活动 2258648