Transcriptomic Analysis of the Erythritol High-Yielding Mutant Strain Yarrowia lipolytica Y44
- 1 Shandong University of Technology, China
- 2 Shandong University, China
- 3 China National Research Institute of Food and Fermentation Industry Co., Ltd. Beijing, China
Abstract
RNA-seq technique was used to analyze the transcriptomics of Yarrowia lipolytica control strain Po1g, an erythritol-producing natural isolate Yarrowia lipolytica Y 22 and an erythritol high-yielding mutant strain Y44 derived from Y 22. Functional annotation of genes and classification of metabolic pathways were carried out to identify Differentially Expressed Genes (DEGs). These DEGs were classified into related metabolic pathways to explain the molecular mechanism of high yield of erythritol production. The results showed that the upregulated genes in erythritol-producing natural isolate Y 22 and erythritol-producing mutant strain Y 44 were mainly involved in pentose phosphate pathway, Tricarboxylic Acid Cycle (TCA) and malic acid cycle. The downregulated genes were mainly involved in amino acid synthesis and oxycarboxylic acid metabolism. The synergistic regulation of the above metabolic pathways can increase the input and reduce the output of erythrose-4-P (E-4-P), which is the precursor of erythritol, promoting erythritol production. In addition, compared with the natural isolate Y 22, the genes related to cell wall synthesis were down-regulated and the expression of transmembrane transporter protein was up-regulated in high-yield mutant strain Y 44. In this way, the permeability of yeast cells is enhanced and the synthesized erythritol can be quickly transported to the outside of the cell, which reduces the decomposition of erythritol and further promotes its yield.
DOI: https://doi.org/10.3844/ajbbsp.2021.433.447
Copyright: © 2021 Xiaojie Ren, Heng Ban, Chao Huang, Baoyue Liu, Yuanda Song, Xinhe Zhao and Jiangsen Pei. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Yarrowia lipolytica
- Transcriptomic Analysis
- GO Clustering
- KEGG Clustering