茉莉酸
生物
斜纹夜蛾
启动(农业)
龙葵
活性氧
罗勒
植物
罗勒
蛋白激酶A
园艺
细胞生物学
激酶
生物化学
水杨酸
发芽
幼虫
作者
Riichiro Yoshida,Shoma Taguchi,Chihiro Wakita,Shinichiro Serikawa,Hiroyuki Miyaji
标识
DOI:10.1007/s00299-024-03285-w
摘要
Abstract Key message Volatile compounds released from basil prime the tomato wound response by promoting jasmonic acid, mitogen-activated protein kinase, and reactive oxygen species signaling. Abstract Within mixed planting systems, companion plants can promote growth or enhance stress responses in target plants. However, the mechanisms underlying these effects remain poorly understood. To gain insight into the molecular nature of the effects of companion plants, we investigated the effects of basil plants ( Ocimum basilicum var. minimum ) on the wound response in tomato plants ( Solanum lycopersicum cv. ‘Micro-Tom’) within a mixed planting system under environmentally controlled chamber. The results showed that the expression of Pin2 , which specifically responds to mechanical wounding, was induced more rapidly and more strongly in the leaves of tomato plants cultivated with companion basil plants. This wound response priming effect was replicated through the exposure of tomato plants to an essential oil (EO) prepared from basil leaves. Tomato leaves pre-exposed to basil EO showed enhanced expression of genes related to jasmonic acid, mitogen-activated protein kinase (MAPK), and reactive oxygen species (ROS) signaling after wounding stress. Basil EO also enhanced ROS accumulation in wounded tomato leaves. The wound response priming effect of basil EO was confirmed in wounded Arabidopsis plants. Loss-of-function analysis of target genes revealed that MAPK genes play pivotal roles in controlling the observed priming effects. Spodoptera litura larvae-fed tomato leaves pre-exposed to basil EO showed reduced growth compared with larvae-fed control leaves. Thus, mixed planting with basil may enhance defense priming in both tomato and Arabidopsis plants through the activation of volatile signaling.
科研通智能强力驱动
Strongly Powered by AbleSci AI