scholarly journals Genome-Scale Metabolic Model of Caldicellulosiruptor bescii Reveals Optimal Metabolic Engineering Strategies for Bio-based Chemical Production

mSystems ◽  
2021 ◽  
Author(s):  
Ke Zhang ◽  
Weishu Zhao ◽  
Dmitry A. Rodionov ◽  
Gabriel M. Rubinstein ◽  
Diep N. Nguyen ◽  
...  

The extremely thermophilic cellulolytic bacterium, Caldicellulosiruptor bescii , degrades plant biomass at high temperatures without any pretreatments and can serve as a strategic platform for industrial applications. The metabolic engineering of C. bescii , however, faces potential bottlenecks in bio-based chemical productions.

2020 ◽  
Author(s):  
Sergio Garcia ◽  
R. Adam Thompson ◽  
Richard J. Giannone ◽  
Satyakam Dash ◽  
Costas D. Maranas ◽  
...  

AbstractSolving environmental and social challenges such as climate change requires a shift from our current non-renewable manufacturing model to a sustainable bioeconomy. To lower carbon emissions in the production of fuels and chemicals, plant biomass feedstocks can replace petroleum using microorganisms as catalysts. The anaerobic thermophile Clostridium thermocellum is a promising bacterium for bioconversion due to its capability to efficiently degrade untreated lignocellulosic biomass. However, the complex metabolism of C. thermocellum is not fully understood, hindering metabolic engineering to achieve high titers, rates, and yields of targeted molecules. In this study, we developed an updated genome-scale metabolic model of C. thermocellum that accounts for recent metabolic findings, has improved prediction accuracy, and is standard-conformant to ensure easy reproducibility. We illustrated two applications of the developed model. We first formulated a multi-omics integration protocol and used it to understand redox metabolism and potential bottlenecks in biofuel (e.g., ethanol) production in C. thermocellum. Second, we used the metabolic model to design modular cells for efficient production of alcohols and esters with broad applications as flavors, fragrances, solvents, and fuels. The proposed designs not only feature intuitive push-and-pull metabolic engineering strategies, but also novel manipulations around important central metabolic branch-points. We anticipate the developed genome-scale metabolic model will provide a useful tool for system analysis of C. thermocellum metabolism to fundamentally understand its physiology and guide metabolic engineering strategies to rapidly generate modular production strains for effective biosynthesis of biofuels and biochemicals from lignocellulosic biomass.


2017 ◽  
Vol 83 (14) ◽  
Author(s):  
Amanda M. Williams-Rhaesa ◽  
Farris L. Poole ◽  
Jessica T. Dinsmore ◽  
Gina L. Lipscomb ◽  
Gabriel M. Rubinstein ◽  
...  

ABSTRACT Caldicellulosiruptor bescii is the most thermophilic cellulose degrader known and is of great interest because of its ability to degrade nonpretreated plant biomass. For biotechnological applications, an efficient genetic system is required to engineer it to convert plant biomass into desired products. To date, two different genetically tractable lineages of C. bescii strains have been generated. The first (JWCB005) is based on a random deletion within the pyrimidine biosynthesis genes pyrFA, and the second (MACB1018) is based on the targeted deletion of pyrE, making use of a kanamycin resistance marker. Importantly, an active insertion element, ISCbe4, was discovered in C. bescii when it disrupted the gene for lactate dehydrogenase (ldh) in strain JWCB018, constructed in the JWCB005 background. Additional instances of ISCbe4 movement in other strains of this lineage are presented herein. These observations raise concerns about the genetic stability of such strains and their use as metabolic engineering platforms. In order to investigate genome stability in engineered strains of C. bescii from the two lineages, genome sequencing and Southern blot analyses were performed. The evidence presented shows a dramatic increase in the number of single nucleotide polymorphisms, insertions/deletions, and ISCbe4 elements within the genome of JWCB005, leading to massive genome rearrangements in its daughter strain, JWCB018. Such dramatic effects were not evident in the newer MACB1018 lineage, indicating that JWCB005 and its daughter strains are not suitable for metabolic engineering purposes in C. bescii. Furthermore, a facile approach for assessing genomic stability in C. bescii has been established. IMPORTANCE Caldicellulosiruptor bescii is a cellulolytic extremely thermophilic bacterium of great interest for metabolic engineering efforts geared toward lignocellulosic biofuel and bio-based chemical production. Genetic technology in C. bescii has led to the development of two uracil auxotrophic genetic background strains for metabolic engineering. We show that strains derived from the genetic background containing a random deletion in uracil biosynthesis genes (pyrFA) have a dramatic increase in the number of single nucleotide polymorphisms, insertions/deletions, and ISCbe4 insertion elements in their genomes compared to the wild type. At least one daughter strain of this lineage also contains large-scale genome rearrangements that are flanked by these ISCbe4 elements. In contrast, strains developed from the second background strain developed using a targeted deletion strategy of the uracil biosynthetic gene pyrE have a stable genome structure, making them preferable for future metabolic engineering studies.


mSystems ◽  
2021 ◽  
Author(s):  
Dmitry A. Rodionov ◽  
Irina A. Rodionova ◽  
Vladimir A. Rodionov ◽  
Aleksandr A. Arzamasov ◽  
Ke Zhang ◽  
...  

To develop functional metabolic engineering platforms for nonmodel microorganisms, a comprehensive understanding of the physiological and metabolic characteristics is critical. Caldicellulosiruptor bescii and other species in this genus have untapped potential for conversion of unpretreated plant biomass into industrial fuels and chemicals. The highly interactive and complex machinery used by C. bescii to acquire and process complex carbohydrates contained in lignocellulose was elucidated here to complement related efforts to develop a metabolic engineering platform with this bacterium.


2012 ◽  
Vol 78 (24) ◽  
pp. 8735-8742 ◽  
Author(s):  
Yilin Fang ◽  
Michael J. Wilkins ◽  
Steven B. Yabusaki ◽  
Mary S. Lipton ◽  
Philip E. Long

ABSTRACTAccurately predicting the interactions between microbial metabolism and the physical subsurface environment is necessary to enhance subsurface energy development, soil and groundwater cleanup, and carbon management. This study was an initial attempt to confirm the metabolic functional roles within anin silicomodel using environmental proteomic data collected during field experiments. Shotgun global proteomics data collected during a subsurface biostimulation experiment were used to validate a genome-scale metabolic model ofGeobacter metallireducens—specifically, the ability of the metabolic model to predict metal reduction, biomass yield, and growth rate under dynamic field conditions. The constraint-basedin silicomodelof G. metallireducensrelates an annotated genome sequence to the physiological functions with 697 reactions controlled by 747 enzyme-coding genes. Proteomic analysis showed that 180 of the 637G. metallireducensproteins detected during the 2008 experiment were associated with specific metabolic reactions in thein silicomodel. When the field-calibrated Fe(III) terminal electron acceptor process reaction in a reactive transport model for the field experiments was replaced with the genome-scale model, the model predicted that the largest metabolic fluxes through thein silicomodel reactions generally correspond to the highest abundances of proteins that catalyze those reactions. Central metabolism predicted by the model agrees well with protein abundance profiles inferred from proteomic analysis. Model discrepancies with the proteomic data, such as the relatively low abundances of proteins associated with amino acid transport and metabolism, revealed pathways or flux constraints in thein silicomodel that could be updated to more accurately predict metabolic processes that occur in the subsurface environment.


2020 ◽  
Vol 86 (17) ◽  
Author(s):  
Miha Bahun ◽  
Marko Šnajder ◽  
Dušan Turk ◽  
Nataša Poklar Ulrih

ABSTRACT Pernisine is a subtilisin-like protease that was originally identified in the hyperthermophilic archaeon Aeropyrum pernix, which lives in extreme marine environments. Pernisine shows exceptional stability and activity due to the high-temperature conditions experienced by A. pernix. Pernisine is of interest for industrial purposes, as it is one of the few proteases that has demonstrated prion-degrading activity. Like other extracellular subtilisins, pernisine is synthesized in its inactive pro-form (pro-pernisine), which needs to undergo maturation to become proteolytically active. The maturation processes of mesophilic subtilisins have been investigated in detail; however, less is known about the maturation of their thermophilic homologs, such as pernisine. Here, we show that the structure of pro-pernisine is disordered in the absence of Ca2+ ions. In contrast to the mesophilic subtilisins, pro-pernisine requires Ca2+ ions to adopt the conformation suitable for its subsequent maturation. In addition to several Ca2+-binding sites that have been conserved from the thermostable Tk-subtilisin, pernisine has an additional insertion sequence with a Ca2+-binding motif. We demonstrate the importance of this insertion for efficient folding and stabilization of pernisine during its maturation. Moreover, analysis of the pernisine propeptide explains the high-temperature requirement for pro-pernisine maturation. Of note, the propeptide inhibits the pernisine catalytic domain more potently at high temperatures. After dissociation, the propeptide is destabilized at high temperatures only, which leads to its degradation and finally to pernisine activation. Our data provide new insights into and understanding of the thermostable subtilisin autoactivation mechanism. IMPORTANCE Enzymes from thermophilic organisms are of particular importance for use in industrial applications, due to their exceptional stability and activity. Pernisine, from the hyperthermophilic archaeon Aeropyrum pernix, is a proteolytic enzyme that can degrade infective prion proteins and thus has a potential use for disinfection of prion-contaminated surfaces. Like other subtilisin-like proteases, pernisine needs to mature through an autocatalytic process to become an active protease. In the present study, we address the maturation of pernisine and show that the process is regulated specifically at high temperatures by the propeptide. Furthermore, we demonstrate the importance of a unique Ca2+-binding insertion for stabilization of mature pernisine. Our results provide a novel understanding of thermostable subtilisin autoactivation, which might advance the development of these enzymes for commercial use.


2019 ◽  
Vol 18 (1) ◽  
Author(s):  
Thordis Kristjansdottir ◽  
Elleke F. Bosma ◽  
Filipe Branco dos Santos ◽  
Emre Özdemir ◽  
Markus J. Herrgård ◽  
...  

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.


2019 ◽  
Author(s):  
Thordis Kristjansdottir ◽  
Elleke F. Bosma ◽  
Filipe Branco dos Santos ◽  
Emre Özdemir ◽  
Markus J. Herrgård ◽  
...  

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.


2021 ◽  
Author(s):  
Emil Ljungqvist ◽  
Martin Gustavsson

AbstractThermophilic microorganisms show high potential for use as biorefinery cell factories. Their high growth temperatures provide fast conversion rates, lower risk of contaminations, and facilitated purification of volatile products. To date, only a few thermophilic species have been utilized for microbial production purposes, and the development of production strains is impeded by the lack of metabolic engineering tools. In this study, we constructed a genome-scale metabolic model, iGEL601, of Geobacillus sp. LC300, an important part of the metabolic engineering pipeline. The model contains 601 genes, 1240 reactions and 1305 metabolites, and the reaction reversibility is based on thermodynamics at the optimum growth temperature. Using flux sampling, the model shows high similarity to experimentally determined reaction fluxes with both glucose and xylose as sole carbon sources. Furthermore, the model predicts previously unidentified by-products, closing the gap in the carbon balance for both carbon sources. Finally, iGEL601 was used to suggest metabolic engineering strategies to maximise production of five industrially relevant compounds. The suggested strategies have previously been experimentally verified in other microorganisms, and predicted production rates are on par with or higher than those previously achieved experimentally. The results highlight the biotechnological potential of LC300 and the application of iGEL601 for use as a tool in the metabolic engineering workflow.


2020 ◽  
Vol 8 (12) ◽  
pp. 1849
Author(s):  
Yujin Jeong ◽  
Sang-Hyeok Cho ◽  
Hookeun Lee ◽  
Hyung-Kyoon Choi ◽  
Dong-Myung Kim ◽  
...  

Cyanobacteria, given their ability to produce various secondary metabolites utilizing solar energy and carbon dioxide, are a potential platform for sustainable production of biochemicals. Until now, conventional metabolic engineering approaches have been applied to various cyanobacterial species for enhanced production of industrially valued compounds, including secondary metabolites and non-natural biochemicals. However, the shortage of understanding of cyanobacterial metabolic and regulatory networks for atmospheric carbon fixation to biochemical production and the lack of available engineering tools limit the potential of cyanobacteria for industrial applications. Recently, to overcome the limitations, synthetic biology tools and systems biology approaches such as genome-scale modeling based on diverse omics data have been applied to cyanobacteria. This review covers the synthetic and systems biology approaches for advanced metabolic engineering of cyanobacteria.


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