Metabolic and Transcriptional Stress Memory in Sorbus pohuashanensis Suspension Cells Induced by Yeast Extract.
Yuan LiZhi-Qiang LuoJie YuanSheng WangJuan LiuPing SuJun-Hui ZhouXiang LiJian YangLan-Ping GuoPublished in: Cells (2022)
Plant stress memory can provide the benefits of enhanced protection against additional stress exposure. Here, we aimed to explore the responses of recurrent and non-recurrent yeast extract (YE) stresses in Sorbus pohuashanensis suspension cells (SPSCs) at metabolomics and transcriptional levels. Biochemical analyses showed that the cell wall integrity and antioxidation capacity of SPSCs in the pretreated group were evidently improved. Metabolic analysis showed that there were 39 significantly altered metabolites in the pretreated group compared to the non-pretreated group. Based on the transcriptome analysis, 219 differentially expressed genes were obtained, which were highly enriched in plant-pathogen interaction, circadian rhythm-plant, oxidative phosphorylation, and phenylpropanoid biosynthesis. Furthermore, the correlation analysis of the transcriptome and metabolome data revealed that phenylpropanoid biosynthesis involved in the production of biphenyl phytoalexins may play a critical role in the memory response of SPSC to YE, and the key memory genes were also identified, including PAL1 , BIS1 , and BIS3 . Collectively, the above results demonstrated that the memory responses of SPSC to YE were significant in almost all levels, which would be helpful for better understanding the adaptation mechanisms of medicinal plants in response to biotic stress, and laid a biotechnological foundation to accumulate favorable antimicrobial drug candidates from plant suspension cells.
Keyphrases
- cell wall
- induced apoptosis
- working memory
- cell cycle arrest
- gene expression
- oxidative stress
- genome wide
- transcription factor
- stress induced
- endoplasmic reticulum stress
- ionic liquid
- signaling pathway
- single cell
- cell death
- dna methylation
- blood pressure
- atrial fibrillation
- machine learning
- rna seq
- pi k akt
- genome wide identification
- cell proliferation
- heat shock
- protein kinase
- candida albicans