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Aureobasidium pullulans genome scale metabolism network model and application thereof

A pullulan, genome-scale technology, applied in the field of systems biology

Active Publication Date: 2017-05-31
SOUTHWEST UNIVERSITY +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

Although the genome-scale metabolic network has developed rapidly since 2003, and a large number of genome-scale metabolic network models of different species have been published, the genome-scale metabolic network model of Aureobasidium pullulans was constructed using annotation information and literature information, and the genome-scale metabolic Research on network model prediction of metabolic modification nodes and analysis of biochemical metabolic characteristics of Aureobasidium pullulans has not been reported yet

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  • Aureobasidium pullulans genome scale metabolism network model and application thereof
  • Aureobasidium pullulans genome scale metabolism network model and application thereof
  • Aureobasidium pullulans genome scale metabolism network model and application thereof

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Embodiment 1

[0032] Example 1, Construction of Genome-Scale Metabolic Network Model of Aureobasidium pullulans

[0033] The construction of the genome-scale metabolic model of Aureobasidium pullulans includes four steps: the establishment of a network database, the refinement and calibration of the database, the establishment of a mathematical model, and the verification and analysis of the model, as follows: figure 1 Shown:

[0034] (1) Establishment of network database: According to the whole genome sequencing results of A. pullulans (A. pullulans) strain CCTCC M2012223 and GO, KEGG, and Uniprot databases, the gene annotation information of A. pullulans was collected, and then the required buds were extracted by VBA program Gene annotation information of Aureobasidium, and then screen out genes, enzymes and reactions related to polymalic acid metabolism, and correlate with each other through EC enzyme numbers to obtain a network database; determine the reaction direction according to the...

Embodiment 2

[0038] Example 2. Features of the genome-scale metabolic network model of Aureobasidium pullulans:

[0039] Based on the above method, the genome-scale metabolic network model iZX637 of Aureobasidium pullulans was constructed. The model contains 637 genes, 1347 reactions and 1133 metabolites, as shown in Table 1, including glycolysis pathway, pentose phosphate pathway, tricarboxylic acid Circulation, pyruvate metabolism, glyoxylate cycle metabolism, amino acid synthesis and consumption metabolism, nucleotide metabolism, lipid metabolism, peptidoglycan synthesis, coenzyme synthesis and other related reactions. Some reactions are listed in Table 2. Allocated into eight cell compartments, all reactions were divided into 9 subsystems according to the KEGG classification standard, and the 9 subsystems were subdivided into 59 metabolic pathways. The model information list is shown in Table 1. Then, based on the strain characteristics and literature information, the synthesis and se...

Embodiment 3

[0048] Example 3. Application of Aureobasidium pullulans genome-scale metabolic network model and target screening

[0049] Using the constructed genome-scale metabolic network model iZX637 of Aureobasidium pullulans, taking the biomass synthesis reaction (reaction ID: biomass) as the objective function, and gradually increasing the polymalic acid secretion reaction (reaction ID: EXC117e), the simulated metabolic flux Unified storage, multiple sets of flow distribution data are obtained, and the reactions with the same trend and the opposite trend with the polymalic acid secretion response are screened out. Then, the biomass and EXC117e reactions were used as the purpose functions to perform single-reaction deletion simulations, and the disturbance results after deletion were counted. The final results showed that under the condition of high PMA synthesis rate, a large amount of carbon flow was concentrated in the pyruvate (PYR) metabolite, which was catalyzed by pyruvate carb...

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Abstract

The invention discloses an aureobasidium pullulans genome scale metabolism network model and application thereof. Construction of the aureobasidium pullulans genome scale metabolism network model comprises four steps of building of a network database, refining and calibrating of the database, building of a mathematical model and validation and analysis of the model. According to the constructed aureobasidium pullulans genome scale metabolism network model, a gene target for potentially improving polymalic acid can be predicted, a guiding platform is provided for research and comprehensive analysis of aureobasidium pullulans, and the aureobasidium pullulans genome scale metabolism network model has great significance on transformation of the aureobasidium pullulans to obtain high-yield metabolic products of the polymalic acid and pullulan.

Description

technical field [0001] The invention belongs to the field of systems biology, and specifically relates to the genome-scale metabolic network model of Aureobasidium pullulans; it also relates to the application of the Aureobasidium pullulans genome-scale metabolic network model in predicting and improving the target gene of the metabolite yield of Aureobasidium pullulans and the corresponding method. Background technique [0002] With the continuous development of sequencing technology, the cost of sequencing has also been continuously reduced, and a large amount of genomics information has accumulated. How to efficiently process and utilize these data to study the overall life process of organisms as a whole has become a research hotspot. The genome-scale metabolic network model is an important tool for the application of omics information. The genome-scale metabolic network model is based on genome sequence and annotation information, and integrates all biochemical reactio...

Claims

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Application Information

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IPC IPC(8): G06F19/18
CPCG16B20/00
Inventor 邹祥冯骏阳静李正华李云政
Owner SOUTHWEST UNIVERSITY
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