Identification of Naturally Occurring Polyamines as Root-Knot Nematode Attractants

无名地 尸体 南方根结线虫 生物 腐胺 植物 根结线虫 线虫 生物化学 生态学
作者
Morihiro Oota,Allen Yi‐Lun Tsai,Dan Aoki,Yasuyuki Matsushita,Syuuto Toyoda,Kazuhiko Fukushima,Kentaro Saeki,Kei Toda,Laetitia Perfus‐Barbeoch,Bruno Favery,Mariko Kitajima,Shinichiro Sawa
出处
期刊:Molecular Plant [Elsevier BV]
卷期号:13 (4): 658-665 被引量:38
标识
DOI:10.1016/j.molp.2019.12.010
摘要

Abstract

Root-knot nematodes (RKNs; genus Meloidogyne) are a class of plant parasites that infect the roots of many plant species. It is believed that RKNs target certain signaling molecules derived from plants to locate their hosts; however, currently, no plant compound has been unambiguously identified as a universal RKN attractant. To address this question, we screened a chemical library of synthetic compounds for Meloidogyne incognita attractants. The breakdown product of aminopropylamino-anthraquinone, 1,3-diaminopropane, as well as its related compounds, putrescine and cadaverine, were found to attract M. incognita. After examining various polyamines, M. incognita were found to be attracted specifically by natural compounds that possess three to five methylene groups between two terminal amino groups. Using cryo-TOF-SIMS/SEM, cadaverine was indeed detected in soybean root cortex cells and the surrounding rhizosphere, establishing a chemical gradient. In addition to cadaverine, putrescine and 1,3-diaminopropane were also detected in root exudate by HPLC-MS/MS. Furthermore, exogenously applied cadaverine is sufficient to enhance M. incognita infection of Arabidopsis seedlings. These results suggest that M. incognita is likely attracted by polyamines to locate the appropriate host plants, and the naturally occurring polyamines have potential applications in agriculture in developing protection strategies for crops from RKN infection.
最长约 10秒,即可获得该文献文件

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
俞孤风完成签到,获得积分10
1秒前
偷看星星完成签到 ,获得积分10
1秒前
香蕉觅云应助liuniuniu采纳,获得10
2秒前
邓博完成签到,获得积分10
4秒前
耍酷的小海豚完成签到 ,获得积分10
6秒前
萝卜特二完成签到,获得积分10
6秒前
上善若水完成签到 ,获得积分10
7秒前
hj123完成签到,获得积分10
8秒前
sunyz应助田甜采纳,获得50
8秒前
好的昂完成签到,获得积分10
8秒前
小二郎应助Migrol采纳,获得10
10秒前
flymove完成签到,获得积分10
10秒前
Jimmybythebay完成签到,获得积分10
10秒前
弹指一挥间完成签到 ,获得积分10
12秒前
hulin_zjxu完成签到,获得积分10
13秒前
甜蜜鹭洋完成签到 ,获得积分10
14秒前
研友_nVNBVn完成签到,获得积分10
14秒前
17秒前
CodeCraft应助晓亮采纳,获得10
17秒前
紫陌完成签到,获得积分10
18秒前
世佳何完成签到,获得积分10
19秒前
蓝天碧海小西服完成签到,获得积分0
20秒前
李义天1212发布了新的文献求助30
20秒前
星海种花完成签到 ,获得积分10
20秒前
木樨完成签到,获得积分10
21秒前
朴实寻琴完成签到 ,获得积分10
21秒前
昏睡的妙梦完成签到 ,获得积分10
21秒前
23秒前
23秒前
城南烤地瓜完成签到 ,获得积分10
24秒前
26秒前
wuyuyu5413完成签到,获得积分10
26秒前
27秒前
篮孩子完成签到,获得积分10
27秒前
zzh完成签到 ,获得积分10
27秒前
28秒前
晓亮完成签到,获得积分10
28秒前
zhoushuai1a发布了新的文献求助10
28秒前
马小翠完成签到,获得积分10
28秒前
往返完成签到,获得积分10
28秒前
高分求助中
Thinking Small and Large 500
Algorithmic Mathematics in Machine Learning 500
Mapping the Stars: Celebrity, Metonymy, and the Networked Politics of Identity 400
Friction Capacity of Piles Driven into Clay 300
Getting Published in SSCI Journals: 200+ Questions and Answers for Absolute Beginners 300
Engineering the boosting of the magnetic Purcell factor with a composite structure based on nanodisk and ring resonators 240
Study of enhancing employee engagement at workplace by adopting internet of things 200
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 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3837587
求助须知:如何正确求助?哪些是违规求助? 3379721
关于积分的说明 10510250
捐赠科研通 3099320
什么是DOI,文献DOI怎么找? 1707062
邀请新用户注册赠送积分活动 821413
科研通“疑难数据库(出版商)”最低求助积分说明 772615