scholarly journals Genome-scale metabolic reconstruction and metabolic versatility of an obligate methanotrophMethylococcus capsulatusstr. Bath

2018 ◽  
Author(s):  
Ankit Gupta ◽  
Ahmad Ahmad ◽  
Dipesh Chothwe ◽  
Midhun K. Madhu ◽  
Shireesh Srivastava ◽  
...  
Keyword(s):  
Amino Acids ◽  
Metabolic Model ◽  
Metabolic Reconstruction ◽  
Methylococcus Capsulatus ◽  
Double Knockout ◽  
Metabolic Potential ◽  
Methane Mitigation ◽  
Metabolic Versatility ◽  
A Genome ◽  
Genome Scale

AbstractThe increase in greenhouse gases with high global warming potential such as methane is a matter of concern and requires multifaceted efforts to reduce its emission and increase its mitigation from the environment. Microbes such as methanotrophs can assist in methane mitigation. To understand the metabolic capabilities of methanotrophs, a complete genome-scale metabolic model of an obligate methanotroph,Methylococcus capsulatusstr. Bath was reconstructed. The model contains 535 genes, 898 reactions and 784 unique metabolites and is namediMC535. The predictive potential of the model was validated using previously-reported experimental data. The model predicted the Entner-Duodoroff (ED) pathway to be essential for the growth of this bacterium, whereas the Embden-Meyerhof-Parnas (EMP) pathway was found non-essential. The performance of the model was simulated on various carbon and nitrogen sources and found thatM. capsulatuscan grow on amino acids. The analysis of network topology of the model identified that six amino acids were in the top-ranked metabolic hubs. Using flux balance analysis (FBA), 29% of the metabolic genes were predicted to be essential, and 76 double knockout combinations involving 92 unique genes were predicted to be lethal. In conclusion, we have reconstructed a genome-scale metabolic model of a unique methanotrophMethylococcus capsulatusstr. Bath. The model will serve as a knowledge-base for deeper understanding, as a platform for exploring the metabolic potential, and as a tool to engineer this bacterium for methane mitigation and industrial applications.

scholarly journals Genome-scale metabolic reconstruction and metabolic versatility of an obligate methanotrophMethylococcus capsulatusstr. Bath

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6685 ◽  
Author(s):  
Ankit Gupta ◽  
Ahmad Ahmad ◽  
Dipesh Chothwe ◽  
Midhun K. Madhu ◽  
Shireesh Srivastava ◽  
...  
Keyword(s):  
Amino Acids ◽  
Nitrogen Sources ◽  
Metabolic Model ◽  
Metabolic Reconstruction ◽  
Methylococcus Capsulatus ◽  
Double Knockout ◽  
Metabolic Genes ◽  
Metabolic Versatility ◽  
Balance Analysis ◽  
Genome Scale

The increase in greenhouse gases with high global warming potential such as methane is a matter of concern and requires multifaceted efforts to reduce its emission and increase its mitigation from the environment. Microbes such as methanotrophs can assist in methane mitigation. To understand the metabolic capabilities of methanotrophs, a complete genome-scale metabolic model (GSMM) of an obligate methanotroph,Methylococcus capsulatusstr. Bath was reconstructed. The model contains 535 genes, 899 reactions and 865 metabolites and is namediMC535. The predictive potential of the model was validated using previously-reported experimental data. The model predicted the Entner–Duodoroff pathway to be essential for the growth of this bacterium, whereas the Embden–Meyerhof–Parnas pathway was found non-essential. The performance of the model was simulated on various carbon and nitrogen sources and found thatM. capsulatuscan grow on amino acids. The analysis of network topology of the model identified that six amino acids were in the top-ranked metabolic hubs. Using flux balance analysis, 29% of the metabolic genes were predicted to be essential, and 76 double knockout combinations involving 92 unique genes were predicted to be lethal. In conclusion, we have reconstructed a GSMM of a methanotrophMethylococcus capsulatusstr. Bath. This is the first high quality GSMM of a Methylococcus strain which can serve as an important resource for further strain-specific models of the Methylococcus genus, as well as identifying the biotechnological potential ofM. capsulatusBath.

scholarly journals A metabolic reconstruction of Lactobacillus reuteri JCM 1112 and analysis of its potential as a cell factory

2019 ◽  
Vol 18 (1) ◽  
Author(s):  
Thordis Kristjansdottir ◽  
Elleke F. Bosma ◽  
Filipe Branco dos Santos ◽  
Emre Özdemir ◽  
Markus J. Herrgård ◽  
...  
Keyword(s):  
Experimental Data ◽  
Metabolic Engineering ◽  
Growth Rates ◽  
Lactobacillus Reuteri ◽  
Metabolic Model ◽  
Metabolic Reconstruction ◽  
Cell Factory ◽  
A Genome ◽  
A Cell ◽  
Genome Scale

Abstract Background Lactobacillus reuteri is a heterofermentative Lactic Acid Bacterium (LAB) that is commonly used for food fermentations and probiotic purposes. Due to its robust properties, it is also increasingly considered for use as a cell factory. It produces several industrially important compounds such as 1,3-propanediol and reuterin natively, but for cell factory purposes, developing improved strategies for engineering and fermentation optimization is crucial. Genome-scale metabolic models can be highly beneficial in guiding rational metabolic engineering. Reconstructing a reliable and a quantitatively accurate metabolic model requires extensive manual curation and incorporation of experimental data. Results A genome-scale metabolic model of L. reuteri JCM 1112T was reconstructed and the resulting model, Lreuteri_530, was validated and tested with experimental data. Several knowledge gaps in the metabolism were identified and resolved during this process, including presence/absence of glycolytic genes. Flux distribution between the two glycolytic pathways, the phosphoketolase and Embden–Meyerhof–Parnas pathways, varies considerably between LAB species and strains. As these pathways result in different energy yields, it is important to include strain-specific utilization of these pathways in the model. We determined experimentally that the Embden–Meyerhof–Parnas pathway carried at most 7% of the total glycolytic flux. Predicted growth rates from Lreuteri_530 were in good agreement with experimentally determined values. To further validate the prediction accuracy of Lreuteri_530, the predicted effects of glycerol addition and adhE gene knock-out, which results in impaired ethanol production, were compared to in vivo data. Examination of both growth rates and uptake- and secretion rates of the main metabolites in central metabolism demonstrated that the model was able to accurately predict the experimentally observed effects. Lastly, the potential of L. reuteri as a cell factory was investigated, resulting in a number of general metabolic engineering strategies. Conclusion We have constructed a manually curated genome-scale metabolic model of L. reuteri JCM 1112T that has been experimentally parameterized and validated and can accurately predict metabolic behavior of this important platform cell factory.

scholarly journals A metabolic reconstruction of Lactobacillus reuteri JCM 1112 and analysis of its potential as a cell factory

2019 ◽  
Author(s):  
Thordis Kristjansdottir ◽  
Elleke F. Bosma ◽  
Filipe Branco dos Santos ◽  
Emre Özdemir ◽  
Markus J. Herrgård ◽  
...  
Keyword(s):  
Experimental Data ◽  
Metabolic Engineering ◽  
Growth Rates ◽  
Lactobacillus Reuteri ◽  
Metabolic Model ◽  
Metabolic Reconstruction ◽  
Cell Factory ◽  
A Genome ◽  
A Cell ◽  
Genome Scale

AbstractBackgroundLactobacillus reuteri is a heterofermentative Lactic Acid Bacterium (LAB) that is commonly used for food fermentations and probiotic purposes. Due to its robust properties, it is also increasingly considered for use as a cell factory. It produces several industrially important compounds such as 1,3-propanediol and reuterin natively, but for cell factory purposes, developing improved strategies for engineering and fermentation optimization is crucial. Genome-scale metabolic models can be highly beneficial in guiding rational metabolic engineering. Reconstructing a reliable and a quantitatively accurate metabolic model requires extensive manual curation and incorporation of experimental data.ResultsA genome-scale metabolic model of L. reuteri JCM 1112T was reconstructed and the resulting model, Lreuteri_530, was validated and tested with experimental data. Several knowledge gaps in the metabolism were identified and resolved during this process, including presence/absence of glycolytic genes. Flux distribution between the two glycolytic pathways, the phosphoketolase and Embden-Meyerhof-Parnas pathways, varies considerably between LAB species and strains. As these pathways result in different energy yields, it is important to include strain-specific utilization of these pathways in the model. We determined experimentally that the Embden-Meyerhof-Parnas pathway carried at most 7% of the total glycolytic flux. Predicted growth rates from Lreuteri_530 were in good agreement with experimentally determined values. To further validate the prediction accuracy of Lreuteri_530, the predicted effects of glycerol addition and adhE gene knock-out, which results in impaired ethanol production, were compared to in vivo data. Examination of both growth rates and uptake- and secretion rates of the main metabolites in central metabolism demonstrated that the model was able to accurately predict the experimentally observed effects. Lastly, the potential of L. reuteri as a cell factory was investigated, resulting in a number of general metabolic engineering strategies.ConclusionWe have constructed a manually curated genome-scale metabolic model of L. reuteri JCM 1112T that has been experimentally parameterized and validated and can accurately predict metabolic behavior of this important platform cell factory.

scholarly journals A genome-scale metabolic model forMethylococcus capsulatuspredicts reduced efficiency uphill electron transfer to pMMO

2018 ◽  
Author(s):  
Christian Lieven ◽  
Leander A. H. Petersen ◽  
Sten Bay Jørgensen ◽  
Krist V. Gernaey ◽  
Markus J. Herrgard ◽  
...  
Keyword(s):  
Electron Transfer ◽  
Metabolic Model ◽  
Single Cell Protein ◽  
Cell Protein ◽  
Methylococcus Capsulatus ◽  
Design Strategies ◽  
C1 Metabolism ◽  
Oxidation Of Methane ◽  
A Genome ◽  
Genome Scale

AbstractBackgroundGenome-scale metabolic models allow researchers to calculate yields, to predict consumption and production rates, and to study the effect of genetic modificationsin silico, without running resource-intensive experiments. While these models have become an invaluable tool for optimizing industrial production hosts likeE. coliandS. cerevisiae, few such models exist for one-carbon (C1) metabolizers.ResultsHere we present a genome-scale metabolic model forMethylococcus capsulatus, a well-studied obligate methanotroph, which has been used as a production strain of single cell protein (SCP). The model was manually curated, and spans a total of 877 metabolites connected via 898 reactions. The inclusion of 730 genes and comprehensive annotations, make this model not only a useful tool for modeling metabolic physiology, but also a centralized knowledge base forM. capsulatus. With it, we determined that oxidation of methane by the particulate methane monooxygenase is most likely driven through uphill electron transfer operating at reduced efficiency as this scenario matches best with experimental data from literature.ConclusionsThe metabolic model will serve the ongoing fundamental research of C1 metabolism, and pave the way for rational strain design strategies towards improved SCP production processes inM. capsulatus.

scholarly journals Genome-scale metabolic reconstruction of the stress-tolerant hybrid yeast Zygosaccharomyces parabailii

2018 ◽  
Author(s):  
Marzia Di Filippo ◽  
Raúl A. Ortiz-Merino ◽  
Chiara Damiani ◽  
Gianni Frascotti ◽  
Danilo Porro ◽  
...  
Keyword(s):  
Laboratory Data ◽  
Metabolic Model ◽  
Cellular Systems ◽  
Metabolic Reconstruction ◽  
Genome Sequences ◽  
Metabolic Potential ◽  
Cell Factories ◽  
Metabolic Models ◽  
Constraint Based Modeling ◽  
Genome Scale

Genome-scale metabolic models are powerful tools to understand and engineer cellular systems facilitating their use as cell factories. This is especially true for microorganisms with known genome sequences from which nearly complete sets of enzymes and metabolic pathways are determined, or can be inferred. Yeasts are highly diverse eukaryotes whose metabolic traits have long been exploited in industry, and although many of their genome sequences are available, few genome-scale metabolic models have so far been produced. For the first time, we reconstructed the genome-scale metabolic model of the hybrid yeast Zygosaccharomyces parabailii, which is a member of the Z. bailii sensu lato clade notorious for stress-tolerance and therefore relevant to industry. The model comprises 3096 reactions, 2091 metabolites, and 2413 genes. Our own laboratory data were then used to establish a biomass synthesis reaction, and constrain the extracellular environment. Through constraint-based modeling, our model reproduces the co-consumption and catabolism of acetate and glucose posing it as a promising platform for understanding and exploiting the metabolic potential of Z. parabailii.

scholarly journals A Genome-Scale Metabolic Model of 2,3-Butanediol Production by Thermophilic Bacteria Geobacillus icigianus

2020 ◽  
Vol 8 (7) ◽  
pp. 1002
Author(s):  
Mikhail Kulyashov ◽  
Sergey E. Peltek ◽  
Ilya R. Akberdin
Keyword(s):  
Citrate Synthase ◽  
Thermophilic Bacteria ◽  
Carbon Sources ◽  
Metabolic Model ◽  
Biofuel Production ◽  
Biotechnological Applications ◽  
Metabolic Potential ◽  
A Genome ◽  
Wide Range ◽  
Genome Scale

The thermophilic strain of the genus Geobacillus, Geobacillus icigianus is a promising bacterial chassis for a wide range of biotechnological applications. In this study, we explored the metabolic potential of Geobacillus icigianus for the production of 2,3-butanediol (2,3-BTD), one of the cost-effective commodity chemicals. Here we present a genome-scale metabolic model iMK1321 for Geobacillus icigianus constructed using an auto-generating pipeline with consequent thorough manual curation. The model contains 1321 genes and includes 1676 reactions and 1589 metabolites, representing the most-complete and publicly available model of the genus Geobacillus. The developed model provides new insights into thermophilic bacterial metabolism and highlights new strategies for biotechnological applications of the strain. Our analysis suggests that Geobacillus icigianus has a potential for 2,3-butanediol production from a variety of utilized carbon sources, including glycerine, a common byproduct of biofuel production. We identified a set of solutions for enhancing 2,3-BTD production, including cultivation under anaerobic or microaerophilic conditions and decreasing the TCA flux to succinate via reducing citrate synthase activity. Both in silico predicted metabolic alternatives have been previously experimentally verified for closely related strains including the genus Bacillus.

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