Metabolic Resistance to Acetolactate Synthase Inhibiting Herbicide Tribenuron-Methyl in Descurainia sophia L. Mediated by Cytochrome P450 Enzymes

乙酰乳酸合酶 生物 基因 马拉硫磷 细胞色素P450 代谢途径 新陈代谢 生物化学 遗传学 植物 杀虫剂 农学
作者
Qian Yang,Jinyao Li,Jing Shen,Yufang Xu,Hongjie Liu,Wei Deng,Xuefeng Li,Mingqi Zheng
出处
期刊:Journal of Agricultural and Food Chemistry [American Chemical Society]
卷期号:66 (17): 4319-4327 被引量:50
标识
DOI:10.1021/acs.jafc.7b05825
摘要

Descurainia sophia is one of the most notorious broadleaf weeds in China and has evolved extremely high resistance to acetolactate synthase (ALS)-inhibiting herbicide tribenuron-methyl. The target-site resistance due to ALS gene mutations was well-known, while the non-target-site resistance is not yet well-characterized. Metabolic resistance, which is conferred by enhanced rates of herbicide metabolism, is the most important NTSR. To explore the mechanism of metabolic resistance underlying resistant (R) D. sophia plants, tribenuron-methyl uptake and metabolism levels, qPCR reference gene stability, and candidate P450 genes expression patterns were investigated. The results of liquid chromatography-mass spectrometry (LC-MS) analysis indicated that the metabolic rates of tribenuron-methyl in R plants was significantly faster than in susceptible (S) plants, and this metabolism differences can be eliminated by P450 inhibitor malathion. The genes for 18S rRNA and TIP41-like were identified as the most suitable reference genes using programs of BestKeeper, NormFinder, and geNorm. The P450 gene CYP96A146 constitutively overexpressed in R plants compared to S plants; this overexpression in R plants can be suppressed by malathion. Taken together, a higher expression level of P450 genes, leading to higher tribenuron-methyl metabolism, appears to be responsible for metabolic resistance to tribenuron-methyl in R D. sophia plants.

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
跨材料发布了新的文献求助10
刚刚
大佬发布了新的文献求助10
1秒前
1秒前
老乡开下门吧完成签到,获得积分10
1秒前
wgqiang完成签到,获得积分10
2秒前
茶多酚完成签到,获得积分10
2秒前
功成完成签到,获得积分10
2秒前
Ww完成签到,获得积分10
2秒前
俏皮凝琴完成签到,获得积分10
3秒前
Song完成签到 ,获得积分0
3秒前
傻自强呀完成签到,获得积分10
4秒前
lidan_2008完成签到,获得积分10
4秒前
4秒前
活泼的飞双完成签到,获得积分10
4秒前
赘婿应助韶雅山采纳,获得10
5秒前
5秒前
5秒前
6秒前
weiwei完成签到,获得积分10
6秒前
6秒前
mwang完成签到,获得积分10
6秒前
火星上誉完成签到,获得积分10
7秒前
7秒前
Sheldson完成签到,获得积分10
7秒前
祖百川完成签到,获得积分10
8秒前
HSTrigger完成签到,获得积分10
8秒前
KathyDu完成签到,获得积分20
9秒前
9秒前
广州城建职业技术学院完成签到,获得积分10
9秒前
linus完成签到,获得积分10
9秒前
sci_fp应助土豆淀粉采纳,获得10
9秒前
自然大米发布了新的文献求助30
10秒前
文静的忆文完成签到,获得积分10
10秒前
yiyiyi瓜子完成签到 ,获得积分10
10秒前
栗早完成签到 ,获得积分10
10秒前
ler发布了新的文献求助10
10秒前
北窗发布了新的文献求助10
10秒前
11秒前
11秒前
11秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(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
48V Low-voltage Power Distribution Network (PDN) Architecture Industry Report, 2024 800
ズームレンズの光学設計に関する研究 800
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
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 7298653
求助须知:如何正确求助?哪些是违规求助? 8917065
关于积分的说明 18881412
捐赠科研通 6963724
什么是DOI,文献DOI怎么找? 3210701
关于科研通互助平台的介绍 2380016
邀请新用户注册赠送积分活动 2187206