Endosomal membrane budding patterns in plants

ESCRT公司 内体 萌芽 细胞生物学 生物 小泡 内膜 膜曲率 生物物理学 生物化学 线粒体 细胞内
作者
Ethan R. Weiner,Elizabeth Berryman,Felix J. Frey,Ariadna González‐Solís,André Leier,Tatiana T. Marquez‐Lago,Anđela Šarić,Marisa S. Otegui
出处
期刊:Proceedings of the National Academy of Sciences of the United States of America [Proceedings of the National Academy of Sciences]
卷期号:121 (44)
标识
DOI:10.1073/pnas.2409407121
摘要

Multivesicular endosomes (MVEs) sequester membrane proteins destined for degradation within intralumenal vesicles (ILVs), a process mediated by the membrane-remodeling action of Endosomal Sorting Complex Required for Transport (ESCRT) proteins. In Arabidopsis , endosomal membrane constriction and scission are uncoupled, resulting in the formation of extensive concatenated ILV networks and enhancing cargo sequestration efficiency. Here, we used a combination of electron tomography, computer simulations, and mathematical modeling to address the questions of when concatenated ILV networks evolved in plants and what drives their formation. Through morphometric analyses of tomographic reconstructions of endosomes across yeast, algae, and various land plants, we have found that ILV concatenation is widespread within plant species, but only prevalent in seed plants, especially in flowering plants. Multiple budding sites that require the formation of pores in the limiting membrane were only identified in hornworts and seed plants, suggesting that this mechanism has evolved independently in both plant lineages. To identify the conditions under which these multiple budding sites can arise, we used particle-based molecular dynamics simulations and found that changes in ESCRT filament properties, such as filament curvature and membrane binding energy, can generate the membrane shapes observed in multiple budding sites. To understand the relationship between membrane budding activity and ILV network topology, we performed computational simulations and identified a set of membrane remodeling parameters that can recapitulate our tomographic datasets.

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
坦率友儿完成签到,获得积分10
刚刚
nimo发布了新的文献求助10
1秒前
科研通AI6.2应助立冬采纳,获得10
1秒前
2秒前
战五渣发布了新的文献求助10
2秒前
热心的尔蓝完成签到,获得积分10
3秒前
求助人员发布了新的文献求助10
3秒前
3秒前
3秒前
英姑应助聪明怀寒采纳,获得10
4秒前
grmqgq完成签到,获得积分10
4秒前
4秒前
ADJ完成签到,获得积分10
4秒前
4秒前
认真的灵竹完成签到 ,获得积分10
4秒前
思源应助派123采纳,获得10
4秒前
HAI关注了科研通微信公众号
4秒前
4秒前
王俊完成签到,获得积分10
4秒前
Lily完成签到,获得积分10
5秒前
yohan发布了新的文献求助10
5秒前
sjll完成签到,获得积分10
5秒前
biudungdung完成签到,获得积分10
5秒前
5秒前
屈屈完成签到,获得积分10
5秒前
养乐多发布了新的文献求助30
5秒前
专注若蕊完成签到,获得积分10
6秒前
夫茶饮完成签到,获得积分10
6秒前
7秒前
7秒前
哈ha完成签到,获得积分10
7秒前
Extreme_jiang完成签到 ,获得积分10
7秒前
YY完成签到,获得积分10
7秒前
ding应助大王叫我来巡山采纳,获得10
8秒前
9秒前
9秒前
陈莹发布了新的文献求助10
9秒前
9秒前
9秒前
交个朋友完成签到 ,获得积分10
10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
Modern Epidemiology, Fourth Edition 5000
Kinesiophobia : a new view of chronic pain behavior 5000
Molecular Biology of Cancer: Mechanisms, Targets, and Therapeutics 3000
Digital Twins of Advanced Materials Processing 2000
Propeller Design 2000
Weaponeering, Fourth Edition – Two Volume SET 2000
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 纳米技术 化学工程 生物化学 物理 计算机科学 内科学 复合材料 催化作用 物理化学 光电子学 电极 冶金 细胞生物学 基因
热门帖子
关注 科研通微信公众号,转发送积分 6013945
求助须知:如何正确求助?哪些是违规求助? 7586030
关于积分的说明 16143775
捐赠科研通 5161447
什么是DOI,文献DOI怎么找? 2763635
邀请新用户注册赠送积分活动 1743835
关于科研通互助平台的介绍 1634492