Zhipu Xuebao (Jul 2023)
Exploring the Effect of Chlorophyll Content on Plant Growth by Proteomic Technology
Abstract
Rice is not only an important staple food source for half of the world′s population, but also an excellent plant model for plant research. As an important part of the rice life cycle, rice seedling development stage is a process that combines multiple genetic, physiological, metabolic and signaling pathways. Since the rice seedling stage is susceptible to internal and external stimuli, the mechanism of various stimuli in the rice seedling growth stage has received extensive attentions. The photosynthesis of rice is affected by internal physiological and biochemical pathways, and external environmental factors. The content of chlorophyll can be used as an indicator of plant photosynthesis ability and developmental stage, which is one of the important indicators for monitoring plant growth and health. This study measured the chlorophyll content of different stages of rice seedlings and made a proteomics analysis. Taking rice seedlings of three stages as the research objects, the leaves of rice seedlings at three stages were collected in turn, and the content of their chlorophyll was determined. The first stage of the rice seedlings was normally growing up until 14 days, the second stage was continue growing up until suffered 7 days cold treatment (15 ℃), and the third stage was growing up 7 days at normal temperature after cold treatment. In this study, combined with statistical analysis methods such as principal component analysis and partial least squares discriminant analysis, and the differential proteomic analysis combined with statistical analysis methods were used to study the correlation between the differential expressed proteins and the changes of chlorophyll content. The results showed that seven metabolic pathways of starch and sucrose metabolism, glycolysis pathway, pentose phosphate pathway, photosynthesis and its carbon fixation, tricarboxylic acid cycle were enriched. Nearly 30 types of enzymes with strongly related to chlorophyll content were screened out, such as P42862, A0A0D3GZA9, Q8S5M6, A0A0E0HGC6 and so on. This study explored the metabolic pathways related with the changes of chlorophyll content, and proved that chlorophyll content can be used as an important indicator of plant growth and health from the perspective of proteomics. The relationship between chlorophyll content and the metabolic pathways, as well as the relationship between chlorophyll content and plant growth and health were explored, and an empirical model of certain reliability and universality was obtained.
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