Literature DB >> 26915092

Genome-scale metabolic modeling and in silico analysis of lipid accumulating yeast Candida tropicalis for dicarboxylic acid production.

Pranjul Mishra1, Gyu-Yeon Park2,3, Meiyappan Lakshmanan4, Hee-Seok Lee2,3, Hongweon Lee2,3, Matthew Wook Chang5,6, Chi Bun Ching1, Jungoh Ahn7,8, Dong-Yup Lee9,10,11.   

Abstract

Recently, the bio-production of α,ω-dicarboxylic acids (DCAs) has gained significant attention, which potentially leads to the replacement of the conventional petroleum-based products. In this regard, the lipid accumulating yeast Candida tropicalis, has been recognized as a promising microbial host for DCA biosynthesis: it possess the unique ω-oxidation pathway where the terminal carbon of α-fatty acids is oxidized to form DCAs with varying chain lengths. However, despite such industrial importance, its cellular physiology and lipid accumulation capability remain largely uncharacterized. Thus, it is imperative to better understand the metabolic behavior of this lipogenic yeast, which could be achieved by a systems biological approach. To this end, herein, we reconstructed the genome-scale metabolic model of C. tropicalis, iCT646, accounting for 646 unique genes, 945 metabolic reactions, and 712 metabolites. Initially, the comparative network analysis of iCT646 with other yeasts revealed several distinctive metabolic reactions, mainly within the amino acid and lipid metabolism including the ω-oxidation pathway. Constraints-based flux analysis was, then, employed to predict the in silico growth rates of C. tropicalis which are highly consistent with the cellular phenotype observed in glucose and xylose minimal media chemostat cultures. Subsequently, the lipid accumulation capability of C. tropicalis was explored in comparison with Saccharomyces cerevisiae, indicating that the formation of "citrate pyruvate cycle" is essential to the lipid accumulation in oleaginous yeasts. The in silico flux analysis also highlighted the enhanced ability of pentose phosphate pathway as NADPH source rather than malic enzyme during lipogenesis. Finally, iCT646 was successfully utilized to highlight the key directions of C. tropicalis strain design for the whole cell biotransformation application to produce long-chain DCAs from alkanes. Biotechnol. Bioeng. 2016;113: 1993-2004.
© 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Entities:  

Keywords:  Candida tropicalis; dicarboxylic acid; genome-scale metabolic model; lipid accumulating yeasts; systems biology

Mesh:

Substances:

Year:  2016        PMID: 26915092     DOI: 10.1002/bit.25955

Source DB:  PubMed          Journal:  Biotechnol Bioeng        ISSN: 0006-3592            Impact factor:   4.530


  15 in total

1.  Increasing Long-Chain Dicarboxylic Acid Production in Candida tropicalis by Engineering Fatty Transporters.

Authors:  Lihua Zhang; Xiang Xiu; Zirui Wang; Yanjun Jiang; Han Fan; Jing Su; Songsen Sui; Songjiang Wang; Ruiming Wang; Junlin Li; Junqing Wang; Nan Li; Jianbin Wang
Journal:  Mol Biotechnol       Date:  2021-03-30       Impact factor: 2.695

2.  Production of dodecanedioic acid via biotransformation of low cost plant-oil derivatives using Candida tropicalis.

Authors:  Irina Funk; Nina Rimmel; Christoph Schorsch; Volker Sieber; Jochen Schmid
Journal:  J Ind Microbiol Biotechnol       Date:  2017-07-29       Impact factor: 3.346

Review 3.  Biotechnological production of bio-based long-chain dicarboxylic acids with oleogenious yeasts.

Authors:  Nicole Werner; Susanne Zibek
Journal:  World J Microbiol Biotechnol       Date:  2017-10-05       Impact factor: 3.312

4.  Adipic acid tolerance screening for potential adipic acid production hosts.

Authors:  Emma Karlsson; Valeria Mapelli; Lisbeth Olsson
Journal:  Microb Cell Fact       Date:  2017-02-01       Impact factor: 5.328

5.  Effects of glucose concentration on 1,18-cis-octadec-9-enedioic acid biotransformation efficiency and lipid body formation in Candida tropicalis.

Authors:  Irina Funk; Volker Sieber; Jochen Schmid
Journal:  Sci Rep       Date:  2017-10-23       Impact factor: 4.379

6.  Reconstruction of a Genome-scale Metabolic Network of Komagataeibacter nataicola RZS01 for Cellulose Production.

Authors:  Heng Zhang; Chao Ye; Nan Xu; Chuntao Chen; Xiao Chen; Fanshu Yuan; Yunhua Xu; Jiazhi Yang; Dongping Sun
Journal:  Sci Rep       Date:  2017-08-11       Impact factor: 4.379

7.  Effect of decanoic acid and 10-hydroxydecanoic acid on the biotransformation of methyl decanoate to sebacic acid.

Authors:  Yohanes Eko Chandra Sugiharto; Heeseok Lee; Annur Dyah Fitriana; Hyeokwon Lee; Wooyoung Jeon; Kyungmoon Park; Jungoh Ahn; Hongweon Lee
Journal:  AMB Express       Date:  2018-05-05       Impact factor: 3.298

8.  Metabolic pathway analysis of walnut endophytic bacterium Bacillus subtilis HB1310 related to lipid production from fermentation of cotton stalk hydrolysate based on genome sequencing.

Authors:  Qin Zhang; Panpan Liu; Yanbin Li; Hui Jiang
Journal:  Biotechnol Lett       Date:  2021-07-06       Impact factor: 2.461

Review 9.  Genome-scale modeling of yeast: chronology, applications and critical perspectives.

Authors:  Helder Lopes; Isabel Rocha
Journal:  FEMS Yeast Res       Date:  2017-08-01       Impact factor: 2.796

10.  Metabolic network model guided engineering ethylmalonyl-CoA pathway to improve ascomycin production in Streptomyces hygroscopicus var. ascomyceticus.

Authors:  Junhua Wang; Cheng Wang; Kejing Song; Jianping Wen
Journal:  Microb Cell Fact       Date:  2017-10-03       Impact factor: 5.328

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