scholarly journals Fine-tuning mitochondrial activity in Yarrowia lipolytica for citrate overproduction

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jorgelindo da Veiga Moreira ◽  
Mario Jolicoeur ◽  
Laurent Schwartz ◽  
Sabine Peres

AbstractYarrowia lipolytica is a non-conventional yeast with promising industrial potentials for lipids and citrate production. It is also widely used for studying mitochondrial respiration due to a respiratory chain like those of mammalian cells. In this study we used a genome-scale model (GEM) of Y. lipolytica metabolism and performed a dynamic Flux Balance Analysis (dFBA) algorithm to analyze and identify metabolic levers associated with citrate optimization. Analysis of fluxes at stationary growth phase showed that carbon flux derived from glucose is rewired to citric acid production and lipid accumulation, whereas the oxidative phosphorylation (OxPhos) shifted to the alternative respiration mode through alternative oxidase (AOX) protein. Simulations of optimized citrate secretion flux resulted in a pronounced lipid oxidation along with reactive oxygen species (ROS) generation and AOX flux inhibition. Then, we experimentally challenged AOX inhibition by adding n-Propyl Gallate (nPG), a specific AOX inhibitor, on Y. lipolytica batch cultures at stationary phase. Our results showed a twofold overproduction of citrate (20.5 g/L) when nPG is added compared to 10.9 g/L under control condition (no nPG addition). These results suggest that ROS management, especially through AOX activity, has a pivotal role on citrate/lipid flux balance in Y. lipolytica. All taken together, we thus provide for the first time, a key for the understanding of a predominant metabolic mechanism favoring citrate overproduction in Y. lipolytica at the expense of lipids accumulation.

2015 ◽  
Vol 9 (1) ◽  
Author(s):  
Martin Kavšček ◽  
Govindprasad Bhutada ◽  
Tobias Madl ◽  
Klaus Natter

2018 ◽  
Author(s):  
Masood Khaksar ◽  
Will Cluett ◽  
Radhakrishnan Mahadevan

Constraint-based multi-scale metabolic models are powerful tools to study complex biological systems like the human body, and to develop new treatment strategies for human diseases. They capture different scales of the system under study and provide the opportunity of understanding the interaction between multiple scales. In this paper, we have used our previously developed multi-scale whole body metabolism framework to establish a new approach to include multiple objectives of the human cells in computational analysis. The model has 3555 ordinary differential equations (ODEs) integrated with a genome-scale model of the hepatocyte, including 1826 biochemical reactions. The model has been solved for 74 objective functions simultaneously. Simulation results show that the integration algorithm has promise with respect to convergence, computational efficiency and response to perturbation. The results suggest that this method holds significant potential for the simulation of the range of metabolic phenotypes for mammalian cells where there are multiple objectives.


2020 ◽  
Vol 117 (10) ◽  
pp. 3006-3017 ◽  
Author(s):  
Carolina Shene ◽  
Paris Paredes ◽  
Liset Flores ◽  
Allison Leyton ◽  
Juan A. Asenjo ◽  
...  

2008 ◽  
Vol 190 (8) ◽  
pp. 2790-2803 ◽  
Author(s):  
Matthew A. Oberhardt ◽  
Jacek Puchałka ◽  
Kimberly E. Fryer ◽  
Vítor A. P. Martins dos Santos ◽  
Jason A. Papin

ABSTRACT Pseudomonas aeruginosa is a major life-threatening opportunistic pathogen that commonly infects immunocompromised patients. This bacterium owes its success as a pathogen largely to its metabolic versatility and flexibility. A thorough understanding of P. aeruginosa's metabolism is thus pivotal for the design of effective intervention strategies. Here we aim to provide, through systems analysis, a basis for the characterization of the genome-scale properties of this pathogen's versatile metabolic network. To this end, we reconstructed a genome-scale metabolic network of Pseudomonas aeruginosa PAO1. This reconstruction accounts for 1,056 genes (19% of the genome), 1,030 proteins, and 883 reactions. Flux balance analysis was used to identify key features of P. aeruginosa metabolism, such as growth yield, under defined conditions and with defined knowledge gaps within the network. BIOLOG substrate oxidation data were used in model expansion, and a genome-scale transposon knockout set was compared against in silico knockout predictions to validate the model. Ultimately, this genome-scale model provides a basic modeling framework with which to explore the metabolism of P. aeruginosa in the context of its environmental and genetic constraints, thereby contributing to a more thorough understanding of the genotype-phenotype relationships in this resourceful and dangerous pathogen.


Cancers ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 2956
Author(s):  
Paweł Jóźwiak ◽  
Piotr Ciesielski ◽  
Piotr K. Zakrzewski ◽  
Karolina Kozal ◽  
Joanna Oracz ◽  
...  

O-GlcNAcylation is a cell glucose sensor. The addition of O-GlcNAc moieties to target protein is catalyzed by the O-Linked N-acetylglucosamine transferase (OGT). OGT is encoded by a single gene that yields differentially spliced OGT isoforms. One of them is targeted to mitochondria (mOGT). Although the impact of O-GlcNAcylation on cancer cells biology is well documented, mOGT’s role remains poorly investigated. We performed studies using breast cancer cells with up-regulated mOGT or its catalytic inactive mutant to identify proteins specifically modified by mOGT. Proteomic approaches included isolation of mOGT protein partners and O-GlcNAcylated proteins from mitochondria-enriched fraction followed by their analysis by mass spectrometry. Moreover, we analyzed the impact of mOGT dysregulation on mitochondrial activity and cellular metabolism using a variety of biochemical assays. We found that mitochondrial OGT expression is glucose-dependent. Elevated mOGT expression affected the mitochondrial transmembrane potential and increased intramitochondrial ROS generation. Moreover, mOGT up-regulation caused a decrease in cellular ATP level. We identified many mitochondrial proteins as mOGT substrates. Most of these proteins are localized in the mitochondrial matrix and the inner mitochondrial membrane and participate in mitochondrial respiration, fatty acid metabolism, transport, translation, apoptosis, and mtDNA processes. Our findings suggest that mOGT interacts with and modifies many mitochondrial proteins, and its dysregulation affects cellular bioenergetics and mitochondria function.


2006 ◽  
Vol 394 (3) ◽  
pp. 575-579 ◽  
Author(s):  
Sergey V. Novoselov ◽  
Deame Hua ◽  
Alexey V. Lobanov ◽  
Vadim N. Gladyshev

Sec (selenocysteine) is a rare amino acid in proteins. It is co-translationally inserted into proteins at UGA codons with the help of SECIS (Sec insertion sequence) elements. A full set of selenoproteins within a genome, known as the selenoproteome, is highly variable in different organisms. However, most of the known eukaryotic selenoproteins are represented in the mammalian selenoproteome. In addition, many of these selenoproteins have cysteine orthologues. Here, we describe a new selenoprotein, designated Fep15, which is distantly related to members of the 15 kDa selenoprotein (Sep15) family. Fep15 is absent in mammals, can be detected only in fish and is present in these organisms only in the selenoprotein form. In contrast with other members of the Sep15 family, which contain a putative active site composed of Sec and cysteine, Fep15 has only Sec. When transiently expressed in mammalian cells, Fep15 incorporated Sec in an SECIS- and SBP2 (SECIS-binding protein 2)-dependent manner and was targeted to the endoplasmic reticulum by its N-terminal signal peptide. Phylogenetic analyses of Sep15 family members suggest that Fep15 evolved by gene duplication.


Microbiology ◽  
2014 ◽  
Vol 160 (6) ◽  
pp. 1252-1266 ◽  
Author(s):  
Hassan B. Hartman ◽  
David A. Fell ◽  
Sergio Rossell ◽  
Peter Ruhdal Jensen ◽  
Martin J. Woodward ◽  
...  

Salmonella enterica sv. Typhimurium is an established model organism for Gram-negative, intracellular pathogens. Owing to the rapid spread of resistance to antibiotics among this group of pathogens, new approaches to identify suitable target proteins are required. Based on the genome sequence of S. Typhimurium and associated databases, a genome-scale metabolic model was constructed. Output was based on an experimental determination of the biomass of Salmonella when growing in glucose minimal medium. Linear programming was used to simulate variations in the energy demand while growing in glucose minimal medium. By grouping reactions with similar flux responses, a subnetwork of 34 reactions responding to this variation was identified (the catabolic core). This network was used to identify sets of one and two reactions that when removed from the genome-scale model interfered with energy and biomass generation. Eleven such sets were found to be essential for the production of biomass precursors. Experimental investigation of seven of these showed that knockouts of the associated genes resulted in attenuated growth for four pairs of reactions, whilst three single reactions were shown to be essential for growth.


mSystems ◽  
2017 ◽  
Vol 2 (2) ◽  
Author(s):  
Keith Dufault-Thompson ◽  
Huahua Jian ◽  
Ruixue Cheng ◽  
Jiefu Li ◽  
Fengping Wang ◽  
...  

ABSTRACT The well-studied nature of the metabolic diversity of Shewanella bacteria makes species from this genus a promising platform for investigating the evolution of carbon metabolism and energy conservation. The Shewanella phylogeny is diverged into two major branches, referred to as group 1 and group 2. While the genotype-phenotype connections of group 2 species have been extensively studied with metabolic modeling, a genome-scale model has been missing for the group 1 species. The metabolic reconstruction of Shewanella piezotolerans strain WP3 represented the first model for Shewanella group 1 and the first model among piezotolerant and psychrotolerant deep-sea bacteria. The model brought insights into the mechanisms of energy conservation in WP3 under anaerobic conditions and highlighted its metabolic flexibility in using diverse carbon sources. Overall, the model opens up new opportunities for investigating energy conservation and metabolic adaptation, and it provides a prototype for systems-level modeling of other deep-sea microorganisms. Shewanella piezotolerans strain WP3 belongs to the group 1 branch of the Shewanella genus and is a piezotolerant and psychrotolerant species isolated from the deep sea. In this study, a genome-scale model was constructed for WP3 using a combination of genome annotation, ortholog mapping, and physiological verification. The metabolic reconstruction contained 806 genes, 653 metabolites, and 922 reactions, including central metabolic functions that represented nonhomologous replacements between the group 1 and group 2 Shewanella species. Metabolic simulations with the WP3 model demonstrated consistency with existing knowledge about the physiology of the organism. A comparison of model simulations with experimental measurements verified the predicted growth profiles under increasing concentrations of carbon sources. The WP3 model was applied to study mechanisms of anaerobic respiration through investigating energy conservation, redox balancing, and the generation of proton motive force. Despite being an obligate respiratory organism, WP3 was predicted to use substrate-level phosphorylation as the primary source of energy conservation under anaerobic conditions, a trait previously identified in other Shewanella species. Further investigation of the ATP synthase activity revealed a positive correlation between the availability of reducing equivalents in the cell and the directionality of the ATP synthase reaction flux. Comparison of the WP3 model with an existing model of a group 2 species, Shewanella oneidensis MR-1, revealed that the WP3 model demonstrated greater flexibility in ATP production under the anaerobic conditions. Such flexibility could be advantageous to WP3 for its adaptation to fluctuating availability of organic carbon sources in the deep sea. IMPORTANCE The well-studied nature of the metabolic diversity of Shewanella bacteria makes species from this genus a promising platform for investigating the evolution of carbon metabolism and energy conservation. The Shewanella phylogeny is diverged into two major branches, referred to as group 1 and group 2. While the genotype-phenotype connections of group 2 species have been extensively studied with metabolic modeling, a genome-scale model has been missing for the group 1 species. The metabolic reconstruction of Shewanella piezotolerans strain WP3 represented the first model for Shewanella group 1 and the first model among piezotolerant and psychrotolerant deep-sea bacteria. The model brought insights into the mechanisms of energy conservation in WP3 under anaerobic conditions and highlighted its metabolic flexibility in using diverse carbon sources. Overall, the model opens up new opportunities for investigating energy conservation and metabolic adaptation, and it provides a prototype for systems-level modeling of other deep-sea microorganisms.


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