1
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Benyamin MS, Perisin MP, Hellman CA, Schwalm ND, Jahnke JP, Sund CJ. Modeling control and transduction of electrochemical gradients in acid-stressed bacteria. iScience 2023; 26:107140. [PMID: 37404371 PMCID: PMC10316662 DOI: 10.1016/j.isci.2023.107140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 03/05/2023] [Accepted: 06/12/2023] [Indexed: 07/06/2023] Open
Abstract
Transmembrane electrochemical gradients drive solute uptake and constitute a substantial fraction of the cellular energy pool in bacteria. These gradients act not only as "homeostatic contributors," but also play a dynamic and keystone role in several bacterial functions, including sensing, stress response, and metabolism. At the system level, multiple gradients interact with ion transporters and bacterial behavior in a complex, rapid, and emergent manner; consequently, experiments alone cannot untangle their interdependencies. Electrochemical gradient modeling provides a general framework to understand these interactions and their underlying mechanisms. We quantify the generation, maintenance, and interactions of electrical, proton, and potassium potential gradients under lactic acid-stress and lactic acid fermentation. Further, we elucidate a gradient-mediated mechanism for intracellular pH sensing and stress response. We demonstrate that this gradient model can yield insights on the energetic limitations of membrane transport, and can predict bacterial behavior across changing environments.
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Affiliation(s)
- Marcus S. Benyamin
- Biological and Biotechnology Sciences Division, DEVCOM Army Research Laboratory, Adelphi, MD, USA
| | - Matthew P. Perisin
- Biological and Biotechnology Sciences Division, DEVCOM Army Research Laboratory, Adelphi, MD, USA
| | - Caleb A. Hellman
- Biological and Biotechnology Sciences Division, DEVCOM Army Research Laboratory, Adelphi, MD, USA
| | - Nathan D. Schwalm
- Biological and Biotechnology Sciences Division, DEVCOM Army Research Laboratory, Adelphi, MD, USA
| | - Justin P. Jahnke
- Biological and Biotechnology Sciences Division, DEVCOM Army Research Laboratory, Adelphi, MD, USA
| | - Christian J. Sund
- Biological and Biotechnology Sciences Division, DEVCOM Army Research Laboratory, Adelphi, MD, USA
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2
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Clavijo-Buriticá DC, Arévalo-Ferro C, González Barrios AF. A Holistic Approach from Systems Biology Reveals the Direct Influence of the Quorum-Sensing Phenomenon on Pseudomonas aeruginosa Metabolism to Pyoverdine Biosynthesis. Metabolites 2023; 13:metabo13050659. [PMID: 37233700 DOI: 10.3390/metabo13050659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 04/26/2023] [Accepted: 05/06/2023] [Indexed: 05/27/2023] Open
Abstract
Computational modeling and simulation of biological systems have become valuable tools for understanding and predicting cellular performance and phenotype generation. This work aimed to construct, model, and dynamically simulate the virulence factor pyoverdine (PVD) biosynthesis in Pseudomonas aeruginosa through a systemic approach, considering that the metabolic pathway of PVD synthesis is regulated by the quorum-sensing (QS) phenomenon. The methodology comprised three main stages: (i) Construction, modeling, and validation of the QS gene regulatory network that controls PVD synthesis in P. aeruginosa strain PAO1; (ii) construction, curating, and modeling of the metabolic network of P. aeruginosa using the flux balance analysis (FBA) approach; (iii) integration and modeling of these two networks into an integrative model using the dynamic flux balance analysis (DFBA) approximation, followed, finally, by an in vitro validation of the integrated model for PVD synthesis in P. aeruginosa as a function of QS signaling. The QS gene network, constructed using the standard System Biology Markup Language, comprised 114 chemical species and 103 reactions and was modeled as a deterministic system following the kinetic based on mass action law. This model showed that the higher the bacterial growth, the higher the extracellular concentration of QS signal molecules, thus emulating the natural behavior of P. aeruginosa PAO1. The P. aeruginosa metabolic network model was constructed based on the iMO1056 model, the P. aeruginosa PAO1 strain genomic annotation, and the metabolic pathway of PVD synthesis. The metabolic network model included the PVD synthesis, transport, exchange reactions, and the QS signal molecules. This metabolic network model was curated and then modeled under the FBA approximation, using biomass maximization as the objective function (optimization problem, a term borrowed from the engineering field). Next, chemical reactions shared by both network models were chosen to combine them into an integrative model. To this end, the fluxes of these reactions, obtained from the QS network model, were fixed in the metabolic network model as constraints of the optimization problem using the DFBA approximation. Finally, simulations of the integrative model (CCBM1146, comprising 1123 reactions and 880 metabolites) were run using the DFBA approximation to get (i) the flux profile for each reaction, (ii) the bacterial growth profile, (iii) the biomass profile, and (iv) the concentration profiles of metabolites of interest such as glucose, PVD, and QS signal molecules. The CCBM1146 model showed that the QS phenomenon directly influences the P. aeruginosa metabolism to PVD biosynthesis as a function of the change in QS signal intensity. The CCBM1146 model made it possible to characterize and explain the complex and emergent behavior generated by the interactions between the two networks, which would have been impossible to do by studying each system's individual components or scales separately. This work is the first in silico report of an integrative model comprising the QS gene regulatory network and the metabolic network of P. aeruginosa.
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Affiliation(s)
- Diana Carolina Clavijo-Buriticá
- Grupo de Comunicación y Comunidades Bacterianas, Departamento de Biología, Universidad Nacional de Colombia, Carrera 45 No. 26-85, Bogotá 111321, Colombia
| | - Catalina Arévalo-Ferro
- Grupo de Comunicación y Comunidades Bacterianas, Departamento de Biología, Universidad Nacional de Colombia, Carrera 45 No. 26-85, Bogotá 111321, Colombia
| | - Andrés Fernando González Barrios
- Grupo de Diseño de Productos y Procesos (GDPP), Departamento de Ingeniería Química y de Alimentos, Universidad de los Andes, Edificio Mario Laserna, Carrera 1 Este No. 19ª-40, Bogotá 111711, Colombia
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3
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Patakova P, Branska B, Vasylkivska M, Jureckova K, Musilova J, Provaznik I, Sedlar K. Transcriptomic studies of solventogenic clostridia, Clostridium acetobutylicum and Clostridium beijerinckii. Biotechnol Adv 2021; 58:107889. [PMID: 34929313 DOI: 10.1016/j.biotechadv.2021.107889] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 12/10/2021] [Accepted: 12/14/2021] [Indexed: 12/13/2022]
Abstract
Solventogenic clostridia are not a strictly defined group within the genus Clostridium but its representatives share some common features, i.e. they are anaerobic, non-pathogenic, non-toxinogenic and endospore forming bacteria. Their main metabolite is typically 1-butanol but depending on species and culture conditions, they can form other metabolites such as acetone, isopropanol, ethanol, butyric, lactic and acetic acids, and hydrogen. Although these organisms were previously used for the industrial production of solvents, they later fell into disuse, being replaced by more efficient chemical production. A return to a more biological production of solvents therefore requires a thorough understanding of clostridial metabolism. Transcriptome analysis, which reflects the involvement of individual genes in all cellular processes within a population, at any given (sampling) moment, is a valuable tool for gaining a deeper insight into clostridial life. In this review, we describe techniques to study transcription, summarize the evolution of these techniques and compare methods for data processing and visualization of solventogenic clostridia, particularly the species Clostridium acetobutylicum and Clostridium beijerinckii. Individual approaches for evaluating transcriptomic data are compared and their contributions to advancements in the field are assessed. Moreover, utilization of transcriptomic data for reconstruction of computational clostridial metabolic models is considered and particular models are described. Transcriptional changes in glucose transport, central carbon metabolism, the sporulation cycle, butanol and butyrate stress responses, the influence of lignocellulose-derived inhibitors on growth and solvent production, and other respective topics, are addressed and common trends are highlighted.
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Affiliation(s)
- Petra Patakova
- University of Chemistry and Technology Prague, Technicka 5, 16628 Prague 6, Czech Republic.
| | - Barbora Branska
- University of Chemistry and Technology Prague, Technicka 5, 16628 Prague 6, Czech Republic
| | - Maryna Vasylkivska
- University of Chemistry and Technology Prague, Technicka 5, 16628 Prague 6, Czech Republic
| | | | - Jana Musilova
- Brno University of Technology, Technicka 10, 61600 Brno, Czech Republic
| | - Ivo Provaznik
- Brno University of Technology, Technicka 10, 61600 Brno, Czech Republic
| | - Karel Sedlar
- Brno University of Technology, Technicka 10, 61600 Brno, Czech Republic
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4
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Jenior ML, Leslie JL, Powers DA, Garrett EM, Walker KA, Dickenson ME, Petri WA, Tamayo R, Papin JA. Novel Drivers of Virulence in Clostridioides difficile Identified via Context-Specific Metabolic Network Analysis. mSystems 2021; 6:e0091921. [PMID: 34609164 PMCID: PMC8547418 DOI: 10.1128/msystems.00919-21] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Accepted: 09/17/2021] [Indexed: 12/20/2022] Open
Abstract
The pathogen Clostridioides difficile causes toxin-mediated diarrhea and is the leading cause of hospital-acquired infection in the United States. Due to growing antibiotic resistance and recurrent infection, targeting C. difficile metabolism presents a new approach to combat this infection. Genome-scale metabolic network reconstructions (GENREs) have been used to identify therapeutic targets and uncover properties that determine cellular behaviors. Thus, we constructed C. difficile GENREs for a hypervirulent isolate (strain [str.] R20291) and a historic strain (str. 630), validating both with in vitro and in vivo data sets. Growth simulations revealed significant correlations with measured carbon source usage (positive predictive value [PPV] ≥ 92.7%), and single-gene deletion analysis showed >89.0% accuracy. Next, we utilized each GENRE to identify metabolic drivers of both sporulation and biofilm formation. Through contextualization of each model using transcriptomes generated from in vitro and infection conditions, we discovered reliance on the pentose phosphate pathway as well as increased usage of cytidine and N-acetylneuraminate when virulence expression is reduced, which was subsequently supported experimentally. Our results highlight the ability of GENREs to identify novel metabolite signals in higher-order phenotypes like bacterial pathogenesis. IMPORTANCE Clostridioides difficile has become the leading single cause of hospital-acquired infections. Numerous studies have demonstrated the importance of specific metabolic pathways in aspects of C. difficile pathophysiology, from initial colonization to regulation of virulence factors. In the past, genome-scale metabolic network reconstruction (GENRE) analysis of bacteria has enabled systematic investigation of the genetic and metabolic properties that contribute to downstream virulence phenotypes. With this in mind, we generated and extensively curated C. difficile GENREs for both a well-studied laboratory strain (str. 630) and a more recently characterized hypervirulent isolate (str. R20291). In silico validation of both GENREs revealed high degrees of agreement with experimental gene essentiality and carbon source utilization data sets. Subsequent exploration of context-specific metabolism during both in vitro growth and infection revealed consistent patterns of metabolism which corresponded with experimentally measured increases in virulence factor expression. Our results support that differential C. difficile virulence is associated with distinct metabolic programs related to use of carbon sources and provide a platform for identification of novel therapeutic targets.
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Affiliation(s)
- Matthew L. Jenior
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Jhansi L. Leslie
- Department of Medicine, Division of Infectious Diseases & International Health, University of Virginia, Charlottesville, Virginia, USA
| | - Deborah A. Powers
- Department of Biochemistry & Molecular Genetics, University of Virginia, Charlottesville, Virginia, USA
| | - Elizabeth M. Garrett
- Department of Microbiology & Immunology, University of North Carolina Chapel Hill School of Medicine, Chapel Hill, North Carolina, USA
| | - Kimberly A. Walker
- Department of Microbiology & Immunology, University of North Carolina Chapel Hill School of Medicine, Chapel Hill, North Carolina, USA
| | - Mary E. Dickenson
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - William A. Petri
- Department of Medicine, Division of Infectious Diseases & International Health, University of Virginia, Charlottesville, Virginia, USA
- Department of Microbiology, Immunology and Cancer Biology, University of Virginia Health System, Charlottesville, Virginia, USA
- Department of Pathology, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Rita Tamayo
- Department of Microbiology & Immunology, University of North Carolina Chapel Hill School of Medicine, Chapel Hill, North Carolina, USA
| | - Jason A. Papin
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
- Department of Medicine, Division of Infectious Diseases & International Health, University of Virginia, Charlottesville, Virginia, USA
- Department of Biochemistry & Molecular Genetics, University of Virginia, Charlottesville, Virginia, USA
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5
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Montaño López J, Duran L, Avalos JL. Physiological limitations and opportunities in microbial metabolic engineering. Nat Rev Microbiol 2021; 20:35-48. [PMID: 34341566 DOI: 10.1038/s41579-021-00600-0] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/22/2021] [Indexed: 11/10/2022]
Abstract
Metabolic engineering can have a pivotal role in increasing the environmental sustainability of the transportation and chemical manufacturing sectors. The field has already developed engineered microorganisms that are currently being used in industrial-scale processes. However, it is often challenging to achieve the titres, yields and productivities required for commercial viability. The efficiency of microbial chemical production is usually dependent on the physiological traits of the host organism, which may either impose limitations on engineered biosynthetic pathways or, conversely, boost their performance. In this Review, we discuss different aspects of microbial physiology that often create obstacles for metabolic engineering, and present solutions to overcome them. We also describe various instances in which natural or engineered physiological traits in host organisms have been harnessed to benefit engineered metabolic pathways for chemical production.
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Affiliation(s)
- José Montaño López
- Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ, USA
| | - Lisset Duran
- Department of Molecular Biology, Princeton University, Princeton, NJ, USA
| | - José L Avalos
- Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ, USA. .,Department of Molecular Biology, Princeton University, Princeton, NJ, USA. .,Andlinger Center for Energy and the Environment, Princeton University, Princeton, NJ, USA. .,Princeton Environmental Institute, Princeton University, Princeton, NJ, USA.
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6
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Modeling Growth Kinetics, Interspecies Cell Fusion, and Metabolism of a Clostridium acetobutylicum/Clostridium ljungdahlii Syntrophic Coculture. mSystems 2021; 6:6/1/e01325-20. [PMID: 33622858 PMCID: PMC8573953 DOI: 10.1128/msystems.01325-20] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Clostridium acetobutylicum and Clostridium ljungdahlii grown in a syntrophic culture were recently shown to fuse membranes and exchange cytosolic contents, yielding hybrid cells with significant shifts in gene expression and growth phenotypes. Here, we introduce a dynamic genome-scale metabolic modeling framework to explore how cell fusion alters the growth phenotype and panel of metabolites produced by this binary community. Computational results indicate C. ljungdahlii persists in the coculture through proteome exchange during fusing events, which endow C. ljungdahlii cells with expanded substrate utilization, and access to additional reducing equivalents from C. acetobutylicum-evolved H2 and through acquisition of C. acetobutylicum-native cofactor-reducing enzymes. Simulations predict maximum theoretical ethanol and isopropanol yields that are increased by 0.64 mmol and 0.39 mmol per mmol hexose sugar consumed, respectively, during exponential growth when cell fusion is active. This modeling effort provides a mechanistic explanation for the metabolic outcome of cellular fusion and altered homeostasis achieved in this syntrophic clostridial community.IMPORTANCE Widespread cell fusion and protein exchange between microbial organisms as observed in synthetic C. acetobutylicum/C. ljungdahlii culture is a novel observation that has not been explored in silico The mechanisms responsible for the observed cell fusion events in this culture are still unknown. In this work, we develop a modeling framework that captures the observed culture composition and metabolic phenotype, use it to offer a mechanistic explanation for how the culture achieves homeostasis, and identify C. ljungdahlii as primary beneficiary of fusion events. The implications for the events described in this study are far reaching, with potential to reshape our understanding of microbial community behavior synthetically and in nature.
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7
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Hermann M, Teleki A, Weitz S, Niess A, Freund A, Bengelsdorf FR, Takors R. Electron availability in CO 2 , CO and H 2 mixtures constrains flux distribution, energy management and product formation in Clostridium ljungdahlii. Microb Biotechnol 2020; 13:1831-1846. [PMID: 32691533 PMCID: PMC7533319 DOI: 10.1111/1751-7915.13625] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Revised: 06/14/2020] [Accepted: 06/24/2020] [Indexed: 01/25/2023] Open
Abstract
Acetogens such as Clostridium ljungdahlii can play a crucial role reducing the human CO2 footprint by converting industrial emissions containing CO2 , CO and H2 into valuable products such as organic acids or alcohols. The quantitative understanding of cellular metabolism is a prerequisite to exploit the bacterial endowments and to fine-tune the cells by applying metabolic engineering tools. Studying the three gas mixtures CO2 + H2 , CO and CO + CO2 + H2 (syngas) by continuously gassed batch cultivation experiments and applying flux balance analysis, we identified CO as the preferred carbon and electron source for growth and producing alcohols. However, the total yield of moles of carbon (mol-C) per electrons consumed was almost identical in all setups which underlines electron availability as the main factor influencing product formation. The Wood-Ljungdahl pathway (WLP) showed high flexibility by serving as the key NAD+ provider for CO2 + H2, whereas this function was strongly compensated by the transhydrogenase-like Nfn complex when CO was metabolized. Availability of reduced ferredoxin (Fdred ) can be considered as a key determinant of metabolic control. Oxidation of CO via carbon monoxide dehydrogenase (CODH) is the main route of Fdred formation when CO is used as substrate, whereas Fdred is mainly regenerated via the methyl branch of WLP and the Nfn complex utilizing CO2 + H2 . Consequently, doubled growth rates, highest ATP formation rates and highest amounts of reduced products (ethanol, 2,3-butanediol) were observed when CO was the sole carbon and electron source.
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Affiliation(s)
- Maria Hermann
- Institute of Biochemical EngineeringUniversity of StuttgartAllmandring 31Stuttgart70569Germany
| | - Attila Teleki
- Institute of Biochemical EngineeringUniversity of StuttgartAllmandring 31Stuttgart70569Germany
| | - Sandra Weitz
- Institute of Microbiology and BiotechnologyUlm UniversityAlbert‐Einstein‐Allee 11Ulm89069Germany
| | - Alexander Niess
- Institute of Biochemical EngineeringUniversity of StuttgartAllmandring 31Stuttgart70569Germany
| | - Andreas Freund
- Institute of Biochemical EngineeringUniversity of StuttgartAllmandring 31Stuttgart70569Germany
| | - Frank R. Bengelsdorf
- Institute of Microbiology and BiotechnologyUlm UniversityAlbert‐Einstein‐Allee 11Ulm89069Germany
| | - Ralf Takors
- Institute of Biochemical EngineeringUniversity of StuttgartAllmandring 31Stuttgart70569Germany
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8
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Vees CA, Neuendorf CS, Pflügl S. Towards continuous industrial bioprocessing with solventogenic and acetogenic clostridia: challenges, progress and perspectives. J Ind Microbiol Biotechnol 2020; 47:753-787. [PMID: 32894379 PMCID: PMC7658081 DOI: 10.1007/s10295-020-02296-2] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2020] [Accepted: 07/20/2020] [Indexed: 12/11/2022]
Abstract
The sustainable production of solvents from above ground carbon is highly desired. Several clostridia naturally produce solvents and use a variety of renewable and waste-derived substrates such as lignocellulosic biomass and gas mixtures containing H2/CO2 or CO. To enable economically viable production of solvents and biofuels such as ethanol and butanol, the high productivity of continuous bioprocesses is needed. While the first industrial-scale gas fermentation facility operates continuously, the acetone-butanol-ethanol (ABE) fermentation is traditionally operated in batch mode. This review highlights the benefits of continuous bioprocessing for solvent production and underlines the progress made towards its establishment. Based on metabolic capabilities of solvent producing clostridia, we discuss recent advances in systems-level understanding and genome engineering. On the process side, we focus on innovative fermentation methods and integrated product recovery to overcome the limitations of the classical one-stage chemostat and give an overview of the current industrial bioproduction of solvents.
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Affiliation(s)
- Charlotte Anne Vees
- Institute of Chemical, Environmental and Bioscience Engineering, Research Area Biochemical Engineering, Technische Universität Wien, Gumpendorfer Straße 1a, 1060 Vienna, Austria
| | - Christian Simon Neuendorf
- Institute of Chemical, Environmental and Bioscience Engineering, Research Area Biochemical Engineering, Technische Universität Wien, Gumpendorfer Straße 1a, 1060 Vienna, Austria
| | - Stefan Pflügl
- Institute of Chemical, Environmental and Bioscience Engineering, Research Area Biochemical Engineering, Technische Universität Wien, Gumpendorfer Straße 1a, 1060 Vienna, Austria
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9
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Garcia S, Thompson RA, Giannone RJ, Dash S, Maranas CD, Trinh CT. Development of a Genome-Scale Metabolic Model of Clostridium thermocellum and Its Applications for Integration of Multi-Omics Datasets and Computational Strain Design. Front Bioeng Biotechnol 2020; 8:772. [PMID: 32974289 PMCID: PMC7471609 DOI: 10.3389/fbioe.2020.00772] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Accepted: 06/18/2020] [Indexed: 01/29/2023] Open
Abstract
Solving 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 biocatalysts. The anaerobic thermophile Clostridium thermocellum is a promising bacterium for bioconversion due to its capability to efficiently degrade 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 present 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.
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Affiliation(s)
- Sergio Garcia
- Department of Chemical and Biomolecular Engineering, The University of Tennessee, Knoxville, TN, United States.,Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, United States
| | - R Adam Thompson
- Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, United States.,Bredesen Center for Interdisciplinary Research and Graduate Education, The University of Tennessee, Knoxville, TN, United States.,Oak Ridge National Laboratory, Oak Ridge, TN, United States
| | - Richard J Giannone
- Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, United States.,Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States
| | - Satyakam Dash
- Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, United States.,Department of Chemical Engineering, The Pennsylvania State University, University Park, PA, United States
| | - Costas D Maranas
- Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, United States.,Department of Chemical Engineering, The Pennsylvania State University, University Park, PA, United States
| | - Cong T Trinh
- Department of Chemical and Biomolecular Engineering, The University of Tennessee, Knoxville, TN, United States.,Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, United States.,Bredesen Center for Interdisciplinary Research and Graduate Education, The University of Tennessee, Knoxville, TN, United States.,Oak Ridge National Laboratory, Oak Ridge, TN, United States
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10
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Li S, Huang L, Ke C, Pang Z, Liu L. Pathway dissection, regulation, engineering and application: lessons learned from biobutanol production by solventogenic clostridia. BIOTECHNOLOGY FOR BIOFUELS 2020; 13:39. [PMID: 32165923 PMCID: PMC7060580 DOI: 10.1186/s13068-020-01674-3] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Accepted: 02/04/2020] [Indexed: 06/01/2023]
Abstract
The global energy crisis and limited supply of petroleum fuels have rekindled the interest in utilizing a sustainable biomass to produce biofuel. Butanol, an advanced biofuel, is a superior renewable resource as it has a high energy content and is less hygroscopic than other candidates. At present, the biobutanol route, employing acetone-butanol-ethanol (ABE) fermentation in Clostridium species, is not economically competitive due to the high cost of feedstocks, low butanol titer, and product inhibition. Based on an analysis of the physiological characteristics of solventogenic clostridia, current advances that enhance ABE fermentation from strain improvement to product separation were systematically reviewed, focusing on: (1) elucidating the metabolic pathway and regulation mechanism of butanol synthesis; (2) enhancing cellular performance and robustness through metabolic engineering, and (3) optimizing the process of ABE fermentation. Finally, perspectives on engineering and exploiting clostridia as cell factories to efficiently produce various chemicals and materials are also discussed.
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Affiliation(s)
- Shubo Li
- College of Light Industry and Food Engineering, Guangxi University, Nanning, 530004 China
| | - Li Huang
- College of Light Industry and Food Engineering, Guangxi University, Nanning, 530004 China
| | - Chengzhu Ke
- College of Light Industry and Food Engineering, Guangxi University, Nanning, 530004 China
| | - Zongwen Pang
- College of Life Science and Technology, Guangxi University, Nanning, 530005 China
| | - Liming Liu
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi, 214122 China
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11
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Yoo M, Nguyen NPT, Soucaille P. Trends in Systems Biology for the Analysis and Engineering of Clostridium acetobutylicum Metabolism. Trends Microbiol 2020; 28:118-140. [DOI: 10.1016/j.tim.2019.09.003] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2018] [Revised: 09/04/2019] [Accepted: 09/06/2019] [Indexed: 11/25/2022]
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12
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Huang X, Lin Y. Reconstruction and analysis of a three‐compartment genome‐scale metabolic model for
Pseudomonas fluorescens. Biotechnol Appl Biochem 2020; 67:133-139. [DOI: 10.1002/bab.1852] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Accepted: 11/05/2019] [Indexed: 01/25/2023]
Affiliation(s)
- Xiaoyan Huang
- Department of Chemical and Biological EngineeringUniversity of Saskatchewan Saskatoon Saskatchewan Canada
| | - Yen‐Han Lin
- Department of Chemical and Biological EngineeringUniversity of Saskatchewan Saskatoon Saskatchewan Canada
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13
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Gilbert J, Pearcy N, Norman R, Millat T, Winzer K, King J, Hodgman C, Minton N, Twycross J. Gsmodutils: a python based framework for test-driven genome scale metabolic model development. Bioinformatics 2019; 35:3397-3403. [PMID: 30759197 PMCID: PMC6748746 DOI: 10.1093/bioinformatics/btz088] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2018] [Revised: 01/29/2019] [Accepted: 02/12/2019] [Indexed: 12/13/2022] Open
Abstract
MOTIVATION Genome scale metabolic models (GSMMs) are increasingly important for systems biology and metabolic engineering research as they are capable of simulating complex steady-state behaviour. Constraints based models of this form can include thousands of reactions and metabolites, with many crucial pathways that only become activated in specific simulation settings. However, despite their widespread use, power and the availability of tools to aid with the construction and analysis of large scale models, little methodology is suggested for their continued management. For example, when genome annotations are updated or new understanding regarding behaviour is discovered, models often need to be altered to reflect this. This is quickly becoming an issue for industrial systems and synthetic biotechnology applications, which require good quality reusable models integral to the design, build, test and learn cycle. RESULTS As part of an ongoing effort to improve genome scale metabolic analysis, we have developed a test-driven development methodology for the continuous integration of validation data from different sources. Contributing to the open source technology based around COBRApy, we have developed the gsmodutils modelling framework placing an emphasis on test-driven design of models through defined test cases. Crucially, different conditions are configurable allowing users to examine how different designs or curation impact a wide range of system behaviours, minimizing error between model versions. AVAILABILITY AND IMPLEMENTATION The software framework described within this paper is open source and freely available from http://github.com/SBRCNottingham/gsmodutils. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- James Gilbert
- Synthetic Biology Research Centre, University of Nottingham, Nottingham, UK
| | - Nicole Pearcy
- Synthetic Biology Research Centre, University of Nottingham, Nottingham, UK
| | - Rupert Norman
- Synthetic Biology Research Centre, University of Nottingham, Nottingham, UK
- School of Biosciences, University of Nottingham, Sutton Bonington, Loughborough, UK
| | - Thomas Millat
- Synthetic Biology Research Centre, University of Nottingham, Nottingham, UK
| | - Klaus Winzer
- Synthetic Biology Research Centre, University of Nottingham, Nottingham, UK
| | - John King
- School of Mathematical Sciences, University of Nottingham, Nottingham, UK
| | - Charlie Hodgman
- Synthetic Biology Research Centre, University of Nottingham, Nottingham, UK
- School of Biosciences, University of Nottingham, Sutton Bonington, Loughborough, UK
| | - Nigel Minton
- Synthetic Biology Research Centre, University of Nottingham, Nottingham, UK
| | - Jamie Twycross
- School of Computer Science, University of Nottingham, Nottingham, UK
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Norman RO, Millat T, Schatschneider S, Henstra AM, Breitkopf R, Pander B, Annan FJ, Piatek P, Hartman HB, Poolman MG, Fell DA, Winzer K, Minton NP, Hodgman C. Genome‐scale model of
C. autoethanogenum
reveals optimal bioprocess conditions for high‐value chemical production from carbon monoxide. ENGINEERING BIOLOGY 2019. [DOI: 10.1049/enb.2018.5003] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Affiliation(s)
- Rupert O.J. Norman
- Synthetic Biology Research CentreUniversity of Nottingham, University ParkNottinghamNG7 2RDUK
- School of BiosciencesUniversity of NottinghamSutton Bonington Campus, Sutton BoningtonLeicestershireLE12 5RDUK
| | - Thomas Millat
- Synthetic Biology Research CentreUniversity of Nottingham, University ParkNottinghamNG7 2RDUK
| | - Sarah Schatschneider
- Synthetic Biology Research CentreUniversity of Nottingham, University ParkNottinghamNG7 2RDUK
- Evonik Nutrition and Care GmbHKantstr. 233798Halle‐KinsbeckGermany
| | - Anne M. Henstra
- Synthetic Biology Research CentreUniversity of Nottingham, University ParkNottinghamNG7 2RDUK
| | - Ronja Breitkopf
- Synthetic Biology Research CentreUniversity of Nottingham, University ParkNottinghamNG7 2RDUK
| | - Bart Pander
- Synthetic Biology Research CentreUniversity of Nottingham, University ParkNottinghamNG7 2RDUK
| | - Florence J. Annan
- Synthetic Biology Research CentreUniversity of Nottingham, University ParkNottinghamNG7 2RDUK
| | - Pawel Piatek
- Synthetic Biology Research CentreUniversity of Nottingham, University ParkNottinghamNG7 2RDUK
| | - Hassan B. Hartman
- Department of Biology and Medical SciencesOxford Brookes UniversityOxfordOX3 0BPUK
- Public Health England61 Colindale AvenueLondonNW9 5EQUK
| | - Mark G. Poolman
- Department of Biology and Medical SciencesOxford Brookes UniversityOxfordOX3 0BPUK
| | - David A. Fell
- Department of Biology and Medical SciencesOxford Brookes UniversityOxfordOX3 0BPUK
| | - Klaus Winzer
- Synthetic Biology Research CentreUniversity of Nottingham, University ParkNottinghamNG7 2RDUK
| | - Nigel P. Minton
- Synthetic Biology Research CentreUniversity of Nottingham, University ParkNottinghamNG7 2RDUK
| | - Charlie Hodgman
- Synthetic Biology Research CentreUniversity of Nottingham, University ParkNottinghamNG7 2RDUK
- School of BiosciencesUniversity of NottinghamSutton Bonington Campus, Sutton BoningtonLeicestershireLE12 5RDUK
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15
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Sangavai C, Bharathi M, Ganesh SP, Chellapandi P. Kinetic modeling of Stickland reactions-coupled methanogenesis for a methanogenic culture. AMB Express 2019; 9:82. [PMID: 31183623 PMCID: PMC6557928 DOI: 10.1186/s13568-019-0803-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2019] [Accepted: 05/22/2019] [Indexed: 12/03/2022] Open
Abstract
Studying amino acid catabolism-coupled methanogenesis is the important standpoints to decipher the metabolic behavior of a methanogenic culture. l-Glycine and l-alanine are acted as sole carbon and nitrogen sources for acidogenic bacteria. One amino acid is oxidized and another one is reduced for acetate production via pyruvate by oxidative deamination process in the Stickland reactions. Herein, we have developed a kinetic model for the Stickland reactions-coupled methanogenesis (SRCM) and simulated objectively to maximize the rate of methane production. We collected the metabolic information from enzyme kinetic parameters for amino acid catabolism of Clostridium acetobutylicum ATCC 824 and methanogenesis of Methanosarcina acetivorans C2A. The SRCM model of this study consisted of 18 reactions and 61 metabolites with enzyme kinetic parameters derived experimental data. The internal or external metabolic flux rate of this system found to control the acidogenesis and methanogenesis in a methanogenic culture. Using the SRCM model, flux distributions were calculated for each reaction and metabolite in order to maximize the methane production rate from the glycine–alanine pair. Results of this study, we demonstrated the metabolic behavior, metabolite pairing while mutually interact, and advantages of syntrophic metabolism of amino acid-directed methane production in a methanogenic starter culture.
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16
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Neumann-Schaal M, Jahn D, Schmidt-Hohagen K. Metabolism the Difficile Way: The Key to the Success of the Pathogen Clostridioides difficile. Front Microbiol 2019; 10:219. [PMID: 30828322 PMCID: PMC6384274 DOI: 10.3389/fmicb.2019.00219] [Citation(s) in RCA: 80] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2018] [Accepted: 01/28/2019] [Indexed: 12/11/2022] Open
Abstract
Strains of Clostridioides difficile cause detrimental diarrheas with thousands of deaths worldwide. The infection process by the Gram-positive, strictly anaerobic gut bacterium is directly related to its unique metabolism, using multiple Stickland-type amino acid fermentation reactions coupled to Rnf complex-mediated sodium/proton gradient formation for ATP generation. Major pathways utilize phenylalanine, leucine, glycine and proline with the formation of 3-phenylproprionate, isocaproate, butyrate, 5-methylcaproate, valerate and 5-aminovalerate. In parallel a versatile sugar catabolism including pyruvate formate-lyase as a central enzyme and an incomplete tricarboxylic acid cycle to prevent unnecessary NADH formation completes the picture. However, a complex gene regulatory network that carefully mediates the continuous adaptation of this metabolism to changing environmental conditions is only partially elucidated. It involves the pleiotropic regulators CodY and SigH, the known carbon metabolism regulator CcpA, the proline regulator PrdR, the iron regulator Fur, the small regulatory RNA CsrA and potentially the NADH-responsive regulator Rex. Here, we describe the current knowledge of the metabolic principles of energy generation by C. difficile and the underlying gene regulatory scenarios.
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Affiliation(s)
- Meina Neumann-Schaal
- Leibniz Institute DSMZ, German Collection of Microorganisms and Cell Cultures, Braunschweig, Germany.,Integrated Centre of Systems Biology (BRICS), Braunschweig University of Technology, Braunschweig, Germany
| | - Dieter Jahn
- Integrated Centre of Systems Biology (BRICS), Braunschweig University of Technology, Braunschweig, Germany.,Institute of Microbiology, Braunschweig University of Technology, Braunschweig, Germany
| | - Kerstin Schmidt-Hohagen
- Integrated Centre of Systems Biology (BRICS), Braunschweig University of Technology, Braunschweig, Germany.,Department of Bioinformatics and Biochemistry, Braunschweig University of Technology, Braunschweig, Germany
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17
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Alkhaldi AN, Al-Sa’di A. Gender Differences in User Satisfaction of Mobile Touch Screen Interfaces: University Students’ Service Sites. INTERNATIONAL JOURNAL OF INNOVATION AND TECHNOLOGY MANAGEMENT 2018. [DOI: 10.1142/s0219877019500032] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The rapid development of mobile user interfaces for students’ websites and the constant utilization of such interfaces by students have witnessed a significant upsurge in growth. However, mobile service providers may lack valuable feedback on user satisfaction, particularly for Arabic users, because the sites are designed and implemented without students’ participation. This paper empirically investigates the user satisfaction of a mobile banner system for the University of Ha’il in Saudi Arabia. Users’ satisfaction was evaluated across six scales: overall reactions, screens, terminology and system information, learning, system capabilities, and technical manuals and online help. A quantitative research method was utilized, involving a questionnaire survey of 235 students. We found that female students have significant concerns about user satisfaction. The paper proposes theoretical and practical implications for future work.
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Affiliation(s)
- Ayman N. Alkhaldi
- Community College, Management Information Systems Department, University of Ha’il, Ha’il, Kingdom of Saudi Arabia
| | - Ahmed Al-Sa’di
- Software Development Department, Northtec, Auckland, New Zealand
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18
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Mora Salguero DA, Fernández-Niño M, Serrano-Bermúdez LM, Páez Melo DO, Winck FV, Caldana C, González Barrios AF. Development of a Chlamydomonas reinhardtii metabolic network dynamic model to describe distinct phenotypes occurring at different CO 2 levels. PeerJ 2018; 6:e5528. [PMID: 30202653 PMCID: PMC6126472 DOI: 10.7717/peerj.5528] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2018] [Accepted: 08/06/2018] [Indexed: 12/13/2022] Open
Abstract
The increase in atmospheric CO2 due to anthropogenic activities is generating climate change, which has resulted in a subsequent rise in global temperatures with severe environmental impacts. Biological mitigation has been considered as an alternative for environmental remediation and reduction of greenhouse gases in the atmosphere. In fact, the use of easily adapted photosynthetic organisms able to fix CO2 with low-cost operation is revealing its high potential for industry. Among those organism, the algae Chlamydomonas reinhardtii have gain special attention as a model organism for studying CO2 fixation, biomass accumulation and bioenergy production upon exposure to several environmental conditions. In the present study, we studied the Chlamydomonas response to different CO2 levels by comparing metabolomics and transcriptomics data with the predicted results from our new-improved genomic-scale metabolic model. For this, we used in silico methods at steady dynamic state varying the levels of CO2. Our main goal was to improve our capacity for predicting metabolic routes involved in biomass accumulation. The improved genomic-scale metabolic model presented in this study was shown to be phenotypically accurate, predictive, and a significant improvement over previously reported models. Our model consists of 3726 reactions and 2436 metabolites, and lacks any thermodynamically infeasible cycles. It was shown to be highly sensitive to environmental changes under both steady-state and dynamic conditions. As additional constraints, our dynamic model involved kinetic parameters associated with substrate consumption at different growth conditions (i.e., low CO2-heterotrophic and high CO2-mixotrophic). Our results suggest that cells growing at high CO2 (i.e., photoautotrophic and mixotrophic conditions) have an increased capability for biomass production. In addition, we have observed that ATP production also seems to be an important limiting factor for growth under the conditions tested. Our experimental data (metabolomics and transcriptomics) and the results predicted by our model clearly suggest a differential behavior between low CO2-heterotrophic and high CO2-mixotrophic growth conditions. The data presented in the current study contributes to better dissect the biological response of C. reinhardtii, as a dynamic entity, to environmental and genetic changes. These findings are of great interest given the biotechnological potential of this microalga for CO2 fixation, biomass accumulation, and bioenergy production.
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Affiliation(s)
- Daniela Alejandra Mora Salguero
- Grupo de Diseño de Productos y Procesos (GDPP), Department of Chemical Engineering, Universidad de Los Andes, Bogotá, Colombia
| | - Miguel Fernández-Niño
- Grupo de Diseño de Productos y Procesos (GDPP), Department of Chemical Engineering, Universidad de Los Andes, Bogotá, Colombia
| | | | - David O. Páez Melo
- Grupo de Diseño de Productos y Procesos (GDPP), Department of Chemical Engineering, Universidad de Los Andes, Bogotá, Colombia
| | - Flavia V. Winck
- Laboratory of Regulatory Systems Biology, Department of Biochemistry, Institute of Chemistry, Universidade de São Paulo, São Paulo, Brazil
| | - Camila Caldana
- Brazilian Bioethanol Science and Technology Laboratory, Brazilian Center for Research in Energy and Materials, Campinas, Brazil
- Max Planck Partner Group, Brazilian Bioethanol Science and Technology Laboratory, Brazilian Center for Research in Energy and Materials, Campinas, Brazil
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19
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Patakova P, Kolek J, Sedlar K, Koscova P, Branska B, Kupkova K, Paulova L, Provaznik I. Comparative analysis of high butanol tolerance and production in clostridia. Biotechnol Adv 2018; 36:721-738. [DOI: 10.1016/j.biotechadv.2017.12.004] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2017] [Revised: 12/05/2017] [Accepted: 12/12/2017] [Indexed: 12/24/2022]
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20
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Kaushal M, Chary KVN, Ahlawat S, Palabhanvi B, Goswami G, Das D. Understanding regulation in substrate dependent modulation of growth and production of alcohols in Clostridium sporogenes NCIM 2918 through metabolic network reconstruction and flux balance analysis. BIORESOURCE TECHNOLOGY 2018; 249:767-776. [PMID: 29136931 DOI: 10.1016/j.biortech.2017.10.080] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/25/2017] [Revised: 10/18/2017] [Accepted: 10/20/2017] [Indexed: 06/07/2023]
Abstract
Flux Balance Analysis was performed for Clostridium sporogenes NCIM 2918 grown on sole glucose and glycerol or glucose-glycerol combinations at varied concentrations. During acidogenesis, glucose and glucose-glycerol combinations favored improved growth and butyric acid production. Glycerol fermentation was however marked by reduced growth and predominant ethanol synthesis. Further, with increase of glycerol fraction in glucose-glycerol blend, flux towards ethanol synthesis linearly increased with simultaneous decrease in butanol flux. Elevated ATP demand due to improved growth was satisfied by upregulated carbon flux towards butyric acid synthesis during both glucose and dual substrate fermentations. Possible repression of pyruvate carboxylase by glycerol resulting in downturn of carbon uptake flux towards TCA cycle through anaplerotic reaction may be responsible for reduced growth in glycerol fermentation. Ammonium acetate mediated induction of acetic acid utilization, during acidogenesis, led to excess acetyl-CoA generation and its subsequent metabolism to lesser reduced products, butyric acid or ethanol.
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Affiliation(s)
- Mehak Kaushal
- Department of Biosciences & Bioengineering, Indian Institute of Technology, Guwahati, Assam 781039, India; DBT-PAN IIT Centre for Bioenergy, Indian Institute of Technology, Guwahati, Assam 781039, India
| | - K Venkata Narayana Chary
- Department of Biosciences & Bioengineering, Indian Institute of Technology, Guwahati, Assam 781039, India; DBT-PAN IIT Centre for Bioenergy, Indian Institute of Technology, Guwahati, Assam 781039, India
| | - Saumya Ahlawat
- Department of Biosciences & Bioengineering, Indian Institute of Technology, Guwahati, Assam 781039, India; DBT-PAN IIT Centre for Bioenergy, Indian Institute of Technology, Guwahati, Assam 781039, India
| | - Basavaraj Palabhanvi
- Department of Biosciences & Bioengineering, Indian Institute of Technology, Guwahati, Assam 781039, India; DBT-PAN IIT Centre for Bioenergy, Indian Institute of Technology, Guwahati, Assam 781039, India
| | - Gargi Goswami
- Department of Biosciences & Bioengineering, Indian Institute of Technology, Guwahati, Assam 781039, India; DBT-PAN IIT Centre for Bioenergy, Indian Institute of Technology, Guwahati, Assam 781039, India
| | - Debasish Das
- Department of Biosciences & Bioengineering, Indian Institute of Technology, Guwahati, Assam 781039, India; DBT-PAN IIT Centre for Bioenergy, Indian Institute of Technology, Guwahati, Assam 781039, India.
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21
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Palomo-Briones R, Trably E, López-Lozano NE, Celis LB, Méndez-Acosta HO, Bernet N, Razo-Flores E. Hydrogen metabolic patterns driven by Clostridium-Streptococcus community shifts in a continuous stirred tank reactor. Appl Microbiol Biotechnol 2018; 102:2465-2475. [DOI: 10.1007/s00253-018-8737-7] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2017] [Revised: 12/20/2017] [Accepted: 12/22/2017] [Indexed: 01/08/2023]
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22
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Wilson J, Gering S, Pinard J, Lucas R, Briggs BR. Bio-production of gaseous alkenes: ethylene, isoprene, isobutene. BIOTECHNOLOGY FOR BIOFUELS 2018; 11:234. [PMID: 30181774 PMCID: PMC6114056 DOI: 10.1186/s13068-018-1230-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2018] [Accepted: 08/17/2018] [Indexed: 05/05/2023]
Abstract
To reduce emissions from petrochemical refinement, bio-production has been heralded as a way to create economically valuable compounds with fewer harmful effects. For example, gaseous alkenes are precursor molecules that can be polymerized into a variety of industrially significant compounds and have biological production pathways. Production levels, however, remain low, thus enhancing bio-production of gaseous petrochemicals for chemical precursors is critical. This review covers the metabolic pathways and production levels of the gaseous alkenes ethylene, isoprene, and isobutene. Techniques needed to drive production to higher levels are also discussed.
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Affiliation(s)
- James Wilson
- Department of Biological Sciences, University of Alaska Anchorage, Anchorage, AK 99508 USA
| | - Sarah Gering
- Department of Biological Sciences, University of Alaska Anchorage, Anchorage, AK 99508 USA
| | - Jessica Pinard
- Department of Biological Sciences, University of Alaska Anchorage, Anchorage, AK 99508 USA
| | - Ryan Lucas
- Department of Biological Sciences, University of Alaska Anchorage, Anchorage, AK 99508 USA
| | - Brandon R. Briggs
- Department of Biological Sciences, University of Alaska Anchorage, Anchorage, AK 99508 USA
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23
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Sangavai C, Chellapandi P. Amino acid catabolism-directed biofuel production in Clostridium sticklandii: An insight into model-driven systems engineering. ACTA ACUST UNITED AC 2017; 16:32-43. [PMID: 29167757 PMCID: PMC5686429 DOI: 10.1016/j.btre.2017.11.002] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2017] [Revised: 10/17/2017] [Accepted: 11/03/2017] [Indexed: 01/01/2023]
Abstract
Model-driven systems engineering has been more fascinating process for microbial biofuel production. Clostridium sticklandii is a potential strain for the solventogenesis and acidogenesis. The present review provides an insight for the protein catabolism-directed biofuel production.
Model-driven systems engineering has been more fascinating process for the microbial production of biofuel and bio-refineries in chemical and pharmaceutical industries. Genome-scale modeling and simulations have been guided for metabolic engineering of Clostridium species for the production of organic solvents and organic acids. Among them, Clostridium sticklandii is one of the potential organisms to be exploited as a microbial cell factory for biofuel production. It is a hyper-ammonia producing bacterium and is able to catabolize amino acids as important carbon and energy sources via Stickland reactions and the development of the specific pathways. Current genomic and metabolic aspects of this bacterium are comprehensively reviewed herein, which provided information for learning about protein catabolism-directed biofuel production. It has a metabolic potential to drive energy and direct solventogenesis as well as acidogenesis from protein catabolism. It produces by-products such as ethanol, acetate, n-butanol, n-butyrate and hydrogen from amino acid catabolism. Model-driven systems engineering of this organism would improve the performance of the industrial sectors and enhance the industrial economy by using protein-based waste in environment-friendly ways.
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Affiliation(s)
- C Sangavai
- Molecular Systems Engineering Lab, Department of Bioinformatics, School of Life Sciences, Bharathidasan University, Tiruchirappalli, 620 024, Tamil Nadu, India
| | - P Chellapandi
- Molecular Systems Engineering Lab, Department of Bioinformatics, School of Life Sciences, Bharathidasan University, Tiruchirappalli, 620 024, Tamil Nadu, India
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24
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Serrano-Bermúdez LM, González Barrios AF, Maranas CD, Montoya D. Clostridium butyricum maximizes growth while minimizing enzyme usage and ATP production: metabolic flux distribution of a strain cultured in glycerol. BMC SYSTEMS BIOLOGY 2017; 11:58. [PMID: 28571567 PMCID: PMC5455137 DOI: 10.1186/s12918-017-0434-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/26/2016] [Accepted: 05/16/2017] [Indexed: 01/15/2023]
Abstract
BACKGROUND The increase in glycerol obtained as a byproduct of biodiesel has encouraged the production of new industrial products, such as 1,3-propanediol (PDO), using biotechnological transformation via bacteria like Clostridium butyricum. However, despite the increasing role of Clostridium butyricum as a bio-production platform, its metabolism remains poorly modeled. RESULTS We reconstructed iCbu641, the first genome-scale metabolic (GSM) model of a PDO producer Clostridium strain, which included 641 genes, 365 enzymes, 891 reactions, and 701 metabolites. We found an enzyme expression prediction of nearly 84% after comparison of proteomic data with flux distribution estimation using flux balance analysis (FBA). The remaining 16% corresponded to enzymes directionally coupled to growth, according to flux coupling findings (FCF). The fermentation data validation also revealed different phenotype states that depended on culture media conditions; for example, Clostridium maximizes its biomass yield per enzyme usage under glycerol limitation. By contrast, under glycerol excess conditions, Clostridium grows sub-optimally, maximizing biomass yield while minimizing both enzyme usage and ATP production. We further evaluated perturbations in the GSM model through enzyme deletions and variations in biomass composition. The GSM predictions showed no significant increase in PDO production, suggesting a robustness to perturbations in the GSM model. We used the experimental results to predict that co-fermentation was a better alternative than iCbu641 perturbations for improving PDO yields. CONCLUSIONS The agreement between the predicted and experimental values allows the use of the GSM model constructed for the PDO-producing Clostridium strain to propose new scenarios for PDO production, such as dynamic simulations, thereby reducing the time and costs associated with experimentation.
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Affiliation(s)
- Luis Miguel Serrano-Bermúdez
- Bioprocesses and Bioprospecting Group, Universidad Nacional de Colombia. Ciudad Universitaria, Carrera 30 No. 45-03, Bogotá, D.C Colombia
| | - Andrés Fernando González Barrios
- Grupo de Diseño de Productos y Procesos (GDPP), Departamento de Ingeniería Química, Universidad de los Andes, Carrera 1 N.° 18A – 12, Bogotá, Colombia
| | - Costas D. Maranas
- Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802 USA
| | - Dolly Montoya
- Bioprocesses and Bioprospecting Group, Universidad Nacional de Colombia. Ciudad Universitaria, Carrera 30 No. 45-03, Bogotá, D.C Colombia
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Model-based quantification of metabolic interactions from dynamic microbial-community data. PLoS One 2017; 12:e0173183. [PMID: 28278266 PMCID: PMC5344373 DOI: 10.1371/journal.pone.0173183] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2016] [Accepted: 02/16/2017] [Indexed: 02/01/2023] Open
Abstract
An important challenge in microbial ecology is to infer metabolic-exchange fluxes between growing microbial species from community-level data, concerning species abundances and metabolite concentrations. Here we apply a model-based approach to integrate such experimental data and thereby infer metabolic-exchange fluxes. We designed a synthetic anaerobic co-culture of Clostridium acetobutylicum and Wolinella succinogenes that interact via interspecies hydrogen transfer and applied different environmental conditions for which we expected the metabolic-exchange rates to change. We used stoichiometric models of the metabolism of the two microorganisms that represents our current physiological understanding and found that this understanding - the model - is sufficient to infer the identity and magnitude of the metabolic-exchange fluxes and it suggested unexpected interactions. Where the model could not fit all experimental data, it indicates specific requirement for further physiological studies. We show that the nitrogen source influences the rate of interspecies hydrogen transfer in the co-culture. Additionally, the model can predict the intracellular fluxes and optimal metabolic exchange rates, which can point to engineering strategies. This study therefore offers a realistic illustration of the strengths and weaknesses of model-based integration of heterogenous data that makes inference of metabolic-exchange fluxes possible from community-level experimental data.
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26
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Mathematical modelling of clostridial acetone-butanol-ethanol fermentation. Appl Microbiol Biotechnol 2017; 101:2251-2271. [PMID: 28210797 PMCID: PMC5320022 DOI: 10.1007/s00253-017-8137-4] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2016] [Revised: 01/14/2017] [Accepted: 01/16/2017] [Indexed: 12/24/2022]
Abstract
Clostridial acetone-butanol-ethanol (ABE) fermentation features a remarkable shift in the cellular metabolic activity from acid formation, acidogenesis, to the production of industrial-relevant solvents, solventogensis. In recent decades, mathematical models have been employed to elucidate the complex interlinked regulation and conditions that determine these two distinct metabolic states and govern the transition between them. In this review, we discuss these models with a focus on the mechanisms controlling intra- and extracellular changes between acidogenesis and solventogenesis. In particular, we critically evaluate underlying model assumptions and predictions in the light of current experimental knowledge. Towards this end, we briefly introduce key ideas and assumptions applied in the discussed modelling approaches, but waive a comprehensive mathematical presentation. We distinguish between structural and dynamical models, which will be discussed in their chronological order to illustrate how new biological information facilitates the ‘evolution’ of mathematical models. Mathematical models and their analysis have significantly contributed to our knowledge of ABE fermentation and the underlying regulatory network which spans all levels of biological organization. However, the ties between the different levels of cellular regulation are not well understood. Furthermore, contradictory experimental and theoretical results challenge our current notion of ABE metabolic network structure. Thus, clostridial ABE fermentation still poses theoretical as well as experimental challenges which are best approached in close collaboration between modellers and experimentalists.
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Bengelsdorf FR, Poehlein A, Flitsch SK, Linder S, Schiel-Bengelsdorf B, Stegmann BA, Krabben P, Green E, Zhang Y, Minton N, Dürre P. Host Organisms: Clostridium acetobutylicum/ Clostridium beijerinckiiand Related Organisms. Ind Biotechnol (New Rochelle N Y) 2016. [DOI: 10.1002/9783527807796.ch9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Affiliation(s)
- Frank R. Bengelsdorf
- Universität Ulm; Institut für Mikrobiologie und Biotechnologie; Albert-Einstein-Allee 11 89081 Ulm Germany
| | - Anja Poehlein
- Georg-August University; Genomic and Applied Microbiology and Göttingen Genomics Laboratory; Göttingen, Grisebachstr. 8 37077 Göttingen Germany
| | - Stefanie K. Flitsch
- Universität Ulm; Institut für Mikrobiologie und Biotechnologie; Albert-Einstein-Allee 11 89081 Ulm Germany
| | - Sonja Linder
- Universität Ulm; Institut für Mikrobiologie und Biotechnologie; Albert-Einstein-Allee 11 89081 Ulm Germany
| | - Bettina Schiel-Bengelsdorf
- Universität Ulm; Institut für Mikrobiologie und Biotechnologie; Albert-Einstein-Allee 11 89081 Ulm Germany
| | - Benjamin A. Stegmann
- Universität Ulm; Institut für Mikrobiologie und Biotechnologie; Albert-Einstein-Allee 11 89081 Ulm Germany
| | - Preben Krabben
- Green Biologics Limited; 45A Western Avenue, Milton Park Abingdon Oxfordshire OX14 4RU UK
| | - Edward Green
- CHAIN Biotechnology Limited; Imperial College Incubator, Imperial College London; Level 1 Bessemer Building London SW7 2AZ UK
| | - Ying Zhang
- University of Nottingham; BBSRC/EPSRC Synthetic Biology Research Centre (SBRC), School of Life Sciences; University Park Nottingham NG7 2RD UK
| | - Nigel Minton
- University of Nottingham; BBSRC/EPSRC Synthetic Biology Research Centre (SBRC), School of Life Sciences; University Park Nottingham NG7 2RD UK
| | - Peter Dürre
- Universität Ulm; Institut für Mikrobiologie und Biotechnologie; Albert-Einstein-Allee 11 89081 Ulm Germany
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Lee SH, Kim S, Kim JY, Cheong NY, Kim KH. Enhanced butanol fermentation using metabolically engineered Clostridium acetobutylicum with ex situ recovery of butanol. BIORESOURCE TECHNOLOGY 2016; 218:909-917. [PMID: 27441828 DOI: 10.1016/j.biortech.2016.07.060] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2016] [Revised: 07/12/2016] [Accepted: 07/13/2016] [Indexed: 06/06/2023]
Abstract
In this study, metabolic target reactions for strain engineering were searched via intracellular coenzyme A (CoA) metabolite analysis. The metabolic reactions catalyzed by thiolase (AtoB) and aldehyde-alcohol dehydrogenase (AdhE1) were considered potential rate-limiting steps. In addition, CoA transferase (CtfAB) was highlighted as being important for the assimilation of organic acids, in order to achieve high butanol production. Based on this quantitative analysis, the BEKW_E1AB-atoB strain was constructed by overexpressing the thl (atoB), adhE1, and ctfAB genes in Clostridium acetobutylicum strain BEKW, which has the phosphotransacetylase (pta) and butyrate kinase (buk) genes knocked out. After 100h of continuous fermentation coupled with adsorptive ex situ butanol recovery, the concentrations found after considering desorption, yield, and productivity for the BEKW_E1AB-atoB strain were 55.7g/L, 0.38g/g, and 2.64g/L/h, respectively. The level of butanol production achieved (2.64g/L/h) represents the highest reported value obtained after adsorptive, long-term fermentation.
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Affiliation(s)
- Sang-Hyun Lee
- Department of Biotechnology, Graduate School, Korea University, Seoul 02841, South Korea
| | - Sooah Kim
- Department of Biotechnology, Graduate School, Korea University, Seoul 02841, South Korea
| | - Jung Yeon Kim
- Department of Biotechnology, Graduate School, Korea University, Seoul 02841, South Korea
| | - Nam Yong Cheong
- Environmental Analysis Division, Korea Apparel Testing & Research Institute, Anyang 14088, South Korea
| | - Kyoung Heon Kim
- Department of Biotechnology, Graduate School, Korea University, Seoul 02841, South Korea.
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Wang YF, Tian J, Ji ZH, Song MY, Li H. Intracellular metabolic changes of Clostridium acetobutylicum and promotion to butanol tolerance during biobutanol fermentation. Int J Biochem Cell Biol 2016; 78:297-306. [DOI: 10.1016/j.biocel.2016.07.031] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2016] [Revised: 07/22/2016] [Accepted: 07/27/2016] [Indexed: 12/16/2022]
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Lee SH, Yun EJ, Kim J, Lee SJ, Um Y, Kim KH. Biomass, strain engineering, and fermentation processes for butanol production by solventogenic clostridia. Appl Microbiol Biotechnol 2016; 100:8255-71. [PMID: 27531513 DOI: 10.1007/s00253-016-7760-9] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2016] [Revised: 07/26/2016] [Accepted: 07/28/2016] [Indexed: 12/14/2022]
Abstract
Butanol is considered an attractive biofuel and a commercially important bulk chemical. However, economical production of butanol by solventogenic clostridia, e.g., via fermentative production of acetone-butanol-ethanol (ABE), is hampered by low fermentation performance, mainly as a result of toxicity of butanol to microorganisms and high substrate costs. Recently, sugars from marine macroalgae and syngas were recognized as potent carbon sources in biomass feedstocks that are abundant and do not compete for arable land with edible crops. With the aid of systems metabolic engineering, many researchers have developed clostridial strains with improved performance on fermentation of these substrates. Alternatively, fermentation strategies integrated with butanol recovery processes such as adsorption, gas stripping, liquid-liquid extraction, and pervaporation have been designed to increase the overall titer of butanol and volumetric productivity. Nevertheless, for economically feasible production of butanol, innovative strategies based on recent research should be implemented. This review describes and discusses recent advances in the development of biomass feedstocks, microbial strains, and fermentation processes for butanol production.
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Affiliation(s)
- Sang-Hyun Lee
- Department of Biotechnology, Graduate School, Korea University, Seoul, 02841, South Korea
| | - Eun Ju Yun
- Department of Biotechnology, Graduate School, Korea University, Seoul, 02841, South Korea
| | - Jungyeon Kim
- Department of Biotechnology, Graduate School, Korea University, Seoul, 02841, South Korea
| | - Sang Jun Lee
- Biosystems and Bioengineering Program, University of Science and Technology and Microbiomics and Immunity Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon, 34141, South Korea
| | - Youngsoon Um
- Clean Energy Research Center, Korea Institute of Science and Technology, Seoul, 02792, South Korea
| | - Kyoung Heon Kim
- Department of Biotechnology, Graduate School, Korea University, Seoul, 02841, South Korea.
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Islam MA, Zengler K, Edwards EA, Mahadevan R, Stephanopoulos G. Investigating Moorella thermoacetica metabolism with a genome-scale constraint-based metabolic model. Integr Biol (Camb) 2016; 7:869-82. [PMID: 25994252 DOI: 10.1039/c5ib00095e] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Moorella thermoacetica is a strictly anaerobic, endospore-forming, and metabolically versatile acetogenic bacterium capable of conserving energy by both autotrophic (acetogenesis) and heterotrophic (homoacetogenesis) modes of metabolism. Its metabolic diversity and the ability to efficiently convert a wide range of compounds, including syngas (CO + H2) into acetyl-CoA have made this thermophilic bacterium a promising host for industrial biotechnology applications. However, lack of detailed information on M. thermoacetica's metabolism is a major impediment to its use as a microbial cell factory. In order to overcome this issue, a genome-scale constraint-based metabolic model of Moorella thermoacetica, iAI558, has been developed using its genome sequence and physiological data from published literature. The reconstructed metabolic network of M. thermoacetica comprises 558 metabolic genes, 705 biochemical reactions, and 698 metabolites. Of the total 705 model reactions, 680 are gene-associated while the rest are non-gene associated reactions. The model, in addition to simulating both autotrophic and heterotrophic growth of M. thermoacetica, revealed degeneracy in its TCA-cycle, a common characteristic of anaerobic metabolism. Furthermore, the model helped elucidate the poorly understood energy conservation mechanism of M. thermoacetica during autotrophy. Thus, in addition to generating experimentally testable hypotheses regarding its physiology, such a detailed model will facilitate rapid strain designing and metabolic engineering of M. thermoacetica for industrial applications.
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Affiliation(s)
- M Ahsanul Islam
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
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32
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Liao C, Seo SO, Lu T. System-level modeling of acetone-butanol-ethanol fermentation. FEMS Microbiol Lett 2016; 363:fnw074. [PMID: 27020410 DOI: 10.1093/femsle/fnw074] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/22/2016] [Indexed: 11/12/2022] Open
Abstract
Acetone-butanol-ethanol (ABE) fermentation is a metabolic process of clostridia that produces bio-based solvents including butanol. It is enabled by an underlying metabolic reaction network and modulated by cellular gene regulation and environmental cues. Mathematical modeling has served as a valuable strategy to facilitate the understanding, characterization and optimization of this process. In this review, we highlight recent advances in system-level, quantitative modeling of ABE fermentation. We begin with an overview of integrative processes underlying the fermentation. Next we survey modeling efforts including early simple models, models with a systematic metabolic description, and those incorporating metabolism through simple gene regulation. Particular focus is given to a recent system-level model that integrates the metabolic reactions, gene regulation and environmental cues. We conclude by discussing the remaining challenges and future directions towards predictive understanding of ABE fermentation.
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Affiliation(s)
- Chen Liao
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Seung-Oh Seo
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA Department of Food Science and Human Nutrition, University of Illinois at Urbana-Champaign, IL 61801, USA
| | - Ting Lu
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
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Characterizing the Phenotypic Responses of Escherichia coli to Multiple 4-Carbon Alcohols with Raman Spectroscopy. FERMENTATION-BASEL 2016. [DOI: 10.3390/fermentation2010003] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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Dash S, Ng CY, Maranas CD. Metabolic modeling of clostridia: current developments and applications. FEMS Microbiol Lett 2016; 363:fnw004. [PMID: 26755502 DOI: 10.1093/femsle/fnw004] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/06/2016] [Indexed: 12/12/2022] Open
Abstract
Anaerobic Clostridium spp. is an important bioproduction microbial genus that can produce solvents and utilize a broad spectrum of substrates including cellulose and syngas. Genome-scale metabolic (GSM) models are increasingly being put forth for various clostridial strains to explore their respective metabolic capabilities and suitability for various bioconversions. In this study, we have selected representative GSM models for six different clostridia (Clostridium acetobutylicum, C. beijerinckii, C. butyricum, C. cellulolyticum, C. ljungdahlii and C. thermocellum) and performed a detailed model comparison contrasting their metabolic repertoire. We also discuss various applications of these GSM models to guide metabolic engineering interventions as well as assessing cellular physiology.
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Affiliation(s)
- Satyakam Dash
- Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802-1503, USA
| | - Chiam Yu Ng
- Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802-1503, USA
| | - Costas D Maranas
- Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802-1503, USA
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Gallardo R, Acevedo A, Quintero J, Paredes I, Conejeros R, Aroca G. In silico analysis of Clostridium acetobutylicum ATCC 824 metabolic response to an external electron supply. Bioprocess Biosyst Eng 2015; 39:295-305. [PMID: 26650720 DOI: 10.1007/s00449-015-1513-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2015] [Accepted: 11/21/2015] [Indexed: 11/26/2022]
Abstract
The biological production of butanol has become an important research field and thanks to genome sequencing and annotation; genome-scale metabolic reconstructions have been developed for several Clostridium species. This work makes use of the iCAC490 model of Clostridium acetobutylicum ATCC 824 to analyze its metabolic capabilities and response to an external electron supply through a constraint-based approach using the Constraint-Based Reconstruction Analysis Toolbox. Several analyses were conducted, which included sensitivity, production envelope, and phenotypic phase planes. The model showed that the use of an external electron supply, which acts as co-reducing agent along with glucose-derived reducing power (electrofermentation), results in an increase in the butanol-specific productivity. However, a proportional increase in the butyrate uptake flux is required. Besides, the uptake of external butyrate leads to the coupling of butanol production and growth, which coincides with results reported in literature. Phenotypic phase planes showed that the reducing capacity becomes more limiting for growth at high butyrate uptake fluxes. An electron uptake flux allows the metabolism to reach the growth optimality line. Although the maximum butanol flux does not coincide with the growth optimality line, a butyrate uptake combined with an electron uptake flux would result in an increased butanol volumetric productivity, being a potential strategy to optimize the production of butanol by C. acetobutylicum ATCC 824.
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Affiliation(s)
- Roberto Gallardo
- Escuela de Ingeniería Bioquímica, Pontificia Universidad Católica de Valparaíso, Av. Brasil, 2085, Valparaíso, Chile
| | - Alejandro Acevedo
- Escuela de Ingeniería Bioquímica, Pontificia Universidad Católica de Valparaíso, Av. Brasil, 2085, Valparaíso, Chile
| | - Julián Quintero
- Escuela de Ingeniería Bioquímica, Pontificia Universidad Católica de Valparaíso, Av. Brasil, 2085, Valparaíso, Chile
| | - Ivan Paredes
- Escuela de Ingeniería Bioquímica, Pontificia Universidad Católica de Valparaíso, Av. Brasil, 2085, Valparaíso, Chile
| | - Raúl Conejeros
- Escuela de Ingeniería Bioquímica, Pontificia Universidad Católica de Valparaíso, Av. Brasil, 2085, Valparaíso, Chile
| | - Germán Aroca
- Escuela de Ingeniería Bioquímica, Pontificia Universidad Católica de Valparaíso, Av. Brasil, 2085, Valparaíso, Chile.
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Abstract
Most natural microbial systems have evolved to function in environments with temporal and spatial variations. A major limitation to understanding such complex systems is the lack of mathematical modelling frameworks that connect the genomes of individual species and temporal and spatial variations in the environment to system behaviour. The goal of this review is to introduce the emerging field of spatiotemporal metabolic modelling based on genome-scale reconstructions of microbial metabolism. The extension of flux balance analysis (FBA) to account for both temporal and spatial variations in the environment is termed spatiotemporal FBA (SFBA). Following a brief overview of FBA and its established dynamic extension, the SFBA problem is introduced and recent progress is described. Three case studies are reviewed to illustrate the current state-of-the-art and possible future research directions are outlined. The author posits that SFBA is the next frontier for microbial metabolic modelling and a rapid increase in methods development and system applications is anticipated.
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Affiliation(s)
- Michael A Henson
- Department of Chemical Engineering, University of Massachusetts, Amherst, MA 01003, U.S.A.
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37
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Abstract
Engineering industrial microorganisms for ambitious applications, for example, the production of second-generation biofuels such as butanol, is impeded by a lack of knowledge of primary metabolism and its regulation. A quantitative system-scale analysis was applied to the biofuel-producing bacterium Clostridium acetobutylicum, a microorganism used for the industrial production of solvent. An improved genome-scale model, iCac967, was first developed based on thorough biochemical characterizations of 15 key metabolic enzymes and on extensive literature analysis to acquire accurate fluxomic data. In parallel, quantitative transcriptomic and proteomic analyses were performed to assess the number of mRNA molecules per cell for all genes under acidogenic, solventogenic, and alcohologenic steady-state conditions as well as the number of cytosolic protein molecules per cell for approximately 700 genes under at least one of the three steady-state conditions. A complete fluxomic, transcriptomic, and proteomic analysis applied to different metabolic states allowed us to better understand the regulation of primary metabolism. Moreover, this analysis enabled the functional characterization of numerous enzymes involved in primary metabolism, including (i) the enzymes involved in the two different butanol pathways and their cofactor specificities, (ii) the primary hydrogenase and its redox partner, (iii) the major butyryl coenzyme A (butyryl-CoA) dehydrogenase, and (iv) the major glyceraldehyde-3-phosphate dehydrogenase. This study provides important information for further metabolic engineering of C. acetobutylicum to develop a commercial process for the production of n-butanol. Currently, there is a resurgence of interest in Clostridium acetobutylicum, the biocatalyst of the historical Weizmann process, to produce n-butanol for use both as a bulk chemical and as a renewable alternative transportation fuel. To develop a commercial process for the production of n-butanol via a metabolic engineering approach, it is necessary to better characterize both the primary metabolism of C. acetobutylicum and its regulation. Here, we apply a quantitative system-scale analysis to acidogenic, solventogenic, and alcohologenic steady-state C. acetobutylicum cells and report for the first time quantitative transcriptomic, proteomic, and fluxomic data. This approach allows for a better understanding of the regulation of primary metabolism and for the functional characterization of numerous enzymes involved in primary metabolism.
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Antoniewicz MR. Parallel labeling experiments for pathway elucidation and (13)C metabolic flux analysis. Curr Opin Biotechnol 2015; 36:91-7. [PMID: 26322734 DOI: 10.1016/j.copbio.2015.08.014] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2015] [Revised: 08/07/2015] [Accepted: 08/09/2015] [Indexed: 12/21/2022]
Abstract
Metabolic pathway models provide the foundation for quantitative studies of cellular physiology through the measurement of intracellular metabolic fluxes. For model organisms metabolic models are well established, with many manually curated genome-scale model reconstructions, gene knockout studies and stable-isotope tracing studies. However, for non-model organisms a similar level of knowledge is often lacking. Compartmentation of cellular metabolism in eukaryotic systems also presents significant challenges for quantitative (13)C-metabolic flux analysis ((13)C-MFA). Recently, innovative (13)C-MFA approaches have been developed based on parallel labeling experiments, the use of multiple isotopic tracers and integrated data analysis, that allow more rigorous validation of pathway models and improved quantification of metabolic fluxes. Applications of these approaches open new research directions in metabolic engineering, biotechnology and medicine.
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Affiliation(s)
- Maciek R Antoniewicz
- Department of Chemical and Biomolecular Engineering, Metabolic Engineering and Systems Biology Laboratory, University of Delaware, Newark, DE 19716, USA.
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Sargo CR, Campani G, Silva GG, Giordano RC, Da Silva AJ, Zangirolami TC, Correia DM, Ferreira EC, Rocha I. Salmonella typhimurium and Escherichia coli dissimilarity: Closely related bacteria with distinct metabolic profiles. Biotechnol Prog 2015; 31:1217-25. [PMID: 26097206 DOI: 10.1002/btpr.2128] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2015] [Revised: 05/20/2015] [Indexed: 01/17/2023]
Abstract
Live attenuated strains of Salmonella typhimurium have been extensively investigated as vaccines for a number of infectious diseases. However, there is still little information available concerning aspects of their metabolism. S. typhimurium and Escherichia coli show a high degree of similarity in terms of their genome contents and metabolic networks. However, this work presents experimental evidence showing that significant differences exist in their abilities to direct carbon fluxes to biomass and energy production. It is important to study the metabolism of Salmonella to elucidate the formation of acetate and other metabolites involved in optimizing the production of biomass, essential for the development of recombinant vaccines. The metabolism of Salmonella under aerobic conditions was assessed using continuous cultures performed at dilution rates ranging from 0.1 to 0.67 h(-1), with glucose as main substrate. Acetate assimilation and glucose metabolism under anaerobic conditions were also investigated using batch cultures. Chemostat cultivations showed deviation of carbon towards acetate formation, starting at dilution rates above 0.1 h(-1). This differed from previous findings for E. coli, where acetate accumulation was only detected at dilution rates exceeding 0.4 h(-1), and was due to the lower rate of acetate assimilation by S. typhimurium under aerobic conditions. Under anaerobic conditions, both microorganisms mainly produced ethanol, acetate, and formate. A genome-scale metabolic model, reconstructed for Salmonella based on an E. coli model, provided a poor description of the mixed fermentation pattern observed during Salmonella cultures, reinforcing the different patterns of carbon utilization exhibited by these closely related bacteria.
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Affiliation(s)
- Cintia R Sargo
- Graduate Program of Chemical Engineering, Federal University of São Carlos, Rodovia Washington Luís, Km 235, São Carlos, SP, 13565-905,, Brazil
| | - Gilson Campani
- Graduate Program of Chemical Engineering, Federal University of São Carlos, Rodovia Washington Luís, Km 235, São Carlos, SP, 13565-905,, Brazil
| | - Gabriel G Silva
- Graduate Program of Chemical Engineering, Federal University of São Carlos, Rodovia Washington Luís, Km 235, São Carlos, SP, 13565-905,, Brazil
| | - Roberto C Giordano
- Graduate Program of Chemical Engineering, Federal University of São Carlos, Rodovia Washington Luís, Km 235, São Carlos, SP, 13565-905,, Brazil
| | - Adilson J Da Silva
- Graduate Program of Chemical Engineering, Federal University of São Carlos, Rodovia Washington Luís, Km 235, São Carlos, SP, 13565-905,, Brazil
| | - Teresa C Zangirolami
- Graduate Program of Chemical Engineering, Federal University of São Carlos, Rodovia Washington Luís, Km 235, São Carlos, SP, 13565-905,, Brazil
| | - Daniela M Correia
- Graduate Program of Chemical Engineering, Federal University of São Carlos, Rodovia Washington Luís, Km 235, São Carlos, SP, 13565-905,, Brazil.,CEB-Centre of Biological Engineering, University of Minho, Campus De Gualtar, Braga, 4710-057,, Portugal
| | - Eugénio C Ferreira
- CEB-Centre of Biological Engineering, University of Minho, Campus De Gualtar, Braga, 4710-057,, Portugal
| | - Isabel Rocha
- CEB-Centre of Biological Engineering, University of Minho, Campus De Gualtar, Braga, 4710-057,, Portugal
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40
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Schultz A, Qutub AA. Predicting internal cell fluxes at sub-optimal growth. BMC SYSTEMS BIOLOGY 2015; 9:18. [PMID: 25890056 PMCID: PMC4397736 DOI: 10.1186/s12918-015-0153-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/29/2014] [Accepted: 02/20/2015] [Indexed: 11/17/2022]
Abstract
Background Flux Balance Analysis (FBA) is a widely used tool to model metabolic behavior and cellular function. Applications of FBA span a breadth of research from synthetic engineering of biofuels to understanding evolutionary adaptations. FBA predicts metabolic reaction fluxes that optimize a given objective. This objective is generally defined for unicellular organisms by a theoretical reaction which simulates biomass production. FBA has been extremely successful at predicting in E. coli growth rates under different media and gene essentiality, amongst other things. In order to improve predictions, additional constraints are coupled with optimization of the biomass function. Studies have suggested, however, that unicellular organisms - like multicellular organisms - do not grow at optimal rates. To further improve FBA predictions, particularly of internal cell fluxes, new techniques to explore the sub-optimal solution space need to be developed. Results We present an innovative FBA method called corsoFBA based on the optimization of protein cost at sub-optimal objective levels. Our method shows good agreement with experimental data of E. coli grown at different dilution rates. Maintaining the objective function close to its maximum value predicts metabolic states that closely resemble low dilution rates; while higher dilution rates can be mirrored by lowering the biomass production value. By using a modified version of Extreme Pathways, we are also able to quantify the energy production and overall protein cost for all possible pathways in the central carbon metabolism. Conclusion Metabolic flux distributions at the optimal objective can be substantially different from the near-optimal distributions. Importantly, the behavior of E. coli central carbon metabolism can be better predicted by exploring the sub-optimal FBA solution space. The corsoFBA method presented here is able to predict the behavior of PEP Carboxylase, the glyoxylate shunt and the Entner-Doudoroff pathway at different glucose levels, a behavior not predicted by the minimization of metabolic steps and FBA alone. This technique can be used to better predict internal cell fluxes under different conditions, and corsoFBA will be of great help for the study of cells from multicellular organisms using Flux Balance Analysis. Electronic supplementary material The online version of this article (doi:10.1186/s12918-015-0153-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- André Schultz
- Department of Bioengineering, Rice University, Main Street, Houston, 6500, USA.
| | - Amina A Qutub
- Department of Bioengineering, Rice University, Main Street, Houston, 6500, USA.
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41
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Sund CJ, Liu S, Germane KL, Servinsky MD, Gerlach ES, Hurley MM. Phosphoketolase flux in Clostridium acetobutylicum during growth on l-arabinose. Microbiology (Reading) 2015; 161:430-440. [DOI: 10.1099/mic.0.000008] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Affiliation(s)
- Christian J. Sund
- US Army Research Laboratory, Sensors and Electron Devices Directorate, 2800 Powder Mill Road, Adelphi, MD 20783, USA
| | - Sanchao Liu
- Federal Staffing Resources, 2200 Somerville Rd, Annapolis, MD 21401, USA
| | - Katherine L. Germane
- Oak Ridge Associated Universities, 4692 Millennium Drive, Suite 101, Belcamp, MD 21017, USA
| | - Matthew D. Servinsky
- US Army Research Laboratory, Sensors and Electron Devices Directorate, 2800 Powder Mill Road, Adelphi, MD 20783, USA
| | - Elliot S. Gerlach
- Federal Staffing Resources, 2200 Somerville Rd, Annapolis, MD 21401, USA
| | - Margaret M. Hurley
- US Army Research Laboratory, RDRL-WML-B, 4600 Deer Creek Loop, Aberdeen Proving Ground, MD 21005, USA
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Köhler KAK, Rühl J, Blank LM, Schmid A. Integration of biocatalyst and process engineering for sustainable and efficientn-butanol production. Eng Life Sci 2015. [DOI: 10.1002/elsc.201400041] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Affiliation(s)
| | - Jana Rühl
- Laboratory of Chemical Biotechnology; TU Dortmund University; Dortmund Germany
| | - Lars M. Blank
- Institute of Applied Microbiology (iAMB); Aachen Biology and Biotechnology (ABBt); RWTH Aachen University; Aachen Germany
| | - Andreas Schmid
- Department Solar Materials; Helmholtz Centre for Environmental Research (UFZ); Leipzig Germany
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Rafieenia R, Chaganti SR. Flux balance analysis of different carbon source fermentation with hydrogen producing Clostridium butyricum using Cell Net Analyzer. BIORESOURCE TECHNOLOGY 2015; 175:613-618. [PMID: 25453441 DOI: 10.1016/j.biortech.2014.10.070] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2014] [Revised: 10/13/2014] [Accepted: 10/14/2014] [Indexed: 06/04/2023]
Abstract
A metabolic network model for Clostridium butyricum was developed using six different carbon sources (sucrose, fructose, galactose, mannose, trehalose and ribose) to study the fermentative H2 production. The model was used for investigation of H2 production and the ability of growth on different substrates to predict the maximum abilities for fermentative H2 production that each substrate can support. NADH fluxes were calculated by the model as an important cofactor affecting on H2 production. Butyrate and acetate production were used as model assumptions and biomass formation was chosen as the objective function for flux analysis calculations. Among the substrates selected, sucrose and trehalose supported the maximum growth and H2 yields. The Cell Net Analyzer metabolic network model developed for H2 estimation revealed good correlation with experimental data and could be further used to study the effect of environmental conditions and substrates concentration on H2 yield.
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Affiliation(s)
- Razieh Rafieenia
- Biotechnology Group, Department of Chemical Engineering, Islamic Azad University of Iran, Science and Research Branch, Tehran, Iran.
| | - Subba Rao Chaganti
- Great Lakes Institute for Environmental Research, University of Windsor, 401 Sunset Ave., Windsor, Ontario N9B 3P4, Canada.
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Daniell J, Nagaraju S, Burton F, Köpke M, Simpson SD. Low-Carbon Fuel and Chemical Production by Anaerobic Gas Fermentation. ADVANCES IN BIOCHEMICAL ENGINEERING/BIOTECHNOLOGY 2015; 156:293-321. [PMID: 26957126 DOI: 10.1007/10_2015_5005] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
World energy demand is expected to increase by up to 40% by 2035. Over this period, the global population is also expected to increase by a billion people. A challenge facing the global community is not only to increase the supply of fuel, but also to minimize fossil carbon emissions to safeguard the environment, at the same time as ensuring that food production and supply is not detrimentally impacted. Gas fermentation is a rapidly maturing technology which allows low carbon fuel and commodity chemical synthesis. Unlike traditional biofuel technologies, gas fermentation avoids the use of sugars, relying instead on gas streams rich in carbon monoxide and/or hydrogen and carbon dioxide as sources of carbon and energy for product synthesis by specialized bacteria collectively known as acetogens. Thus, gas fermentation enables access to a diverse array of novel, large volume, and globally available feedstocks including industrial waste gases and syngas produced, for example, via the gasification of municipal waste and biomass. Through the efforts of academic labs and early stage ventures, process scale-up challenges have been surmounted through the development of specialized bioreactors. Furthermore, tools for the genetic improvement of the acetogenic bacteria have been reported, paving the way for the production of a spectrum of ever-more valuable products via this process. As a result of these developments, interest in gas fermentation among both researchers and legislators has grown significantly in the past 5 years to the point that this approach is now considered amongst the mainstream of emerging technology solutions for near-term low-carbon fuel and chemical synthesis.
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Affiliation(s)
- James Daniell
- LanzaTech Inc., 8045 Lamon Ave, Suite 400, Skokie, IL, 60077, USA.,School of Biological Sciences, University of Auckland, Auckland, New Zealand
| | - Shilpa Nagaraju
- LanzaTech Inc., 8045 Lamon Ave, Suite 400, Skokie, IL, 60077, USA
| | - Freya Burton
- LanzaTech Inc., 8045 Lamon Ave, Suite 400, Skokie, IL, 60077, USA
| | - Michael Köpke
- LanzaTech Inc., 8045 Lamon Ave, Suite 400, Skokie, IL, 60077, USA
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Goyal N, Widiastuti H, Karimi IA, Zhou Z. A genome-scale metabolic model of Methanococcus maripaludis S2 for CO2 capture and conversion to methane. MOLECULAR BIOSYSTEMS 2014; 10:1043-54. [PMID: 24553424 DOI: 10.1039/c3mb70421a] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Methane is a major energy source for heating and electricity. Its production by methanogenic bacteria is widely known in nature. M. maripaludis S2 is a fully sequenced hydrogenotrophic methanogen and an excellent laboratory strain with robust genetic tools. However, a quantitative systems biology model to complement these tools is absent in the literature. To understand and enhance its methanogenesis from CO2, this work presents the first constraint-based genome-scale metabolic model (iMM518). It comprises 570 reactions, 556 distinct metabolites, and 518 genes along with gene-protein-reaction (GPR) associations, and covers 30% of open reading frames (ORFs). The model was validated using biomass growth data and experimental phenotypic studies from the literature. Its comparison with the in silico models of Methanosarcina barkeri, Methanosarcina acetivorans, and Sulfolobus solfataricus P2 shows M. maripaludis S2 to be a better organism for producing methane. Using the model, genes essential for growth were identified, and the efficacies of alternative carbon, hydrogen and nitrogen sources were studied. The model can predict the effects of reengineering M. maripaludis S2 to guide or expedite experimental efforts.
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Affiliation(s)
- Nishu Goyal
- Department of Chemical and Biomolecular Engineering, National University of Singapore, 4 Engineering Drive 4, Singapore 117576.
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46
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Senger RS, Yen JY, Fong SS. A review of genome-scale metabolic flux modeling of anaerobiosis in biotechnology. Curr Opin Chem Eng 2014. [DOI: 10.1016/j.coche.2014.08.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Larocque M, Chénard T, Najmanovich R. A curated C. difficile strain 630 metabolic network: prediction of essential targets and inhibitors. BMC SYSTEMS BIOLOGY 2014; 8:117. [PMID: 25315994 PMCID: PMC4207893 DOI: 10.1186/s12918-014-0117-z] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/30/2014] [Accepted: 10/08/2014] [Indexed: 12/12/2022]
Abstract
BACKGROUND Clostridium difficile is the leading cause of hospital-borne infections occurring when the natural intestinal flora is depleted following antibiotic treatment. Current treatments for Clostridium difficile infections present high relapse rates and new hyper-virulent and multi-resistant strains are emerging, making the study of this nosocomial pathogen necessary to find novel therapeutic targets. RESULTS We present iMLTC806cdf, an extensively curated reconstructed metabolic network for the C. difficile pathogenic strain 630. iMLTC806cdf contains 806 genes, 703 metabolites and 769 metabolic, 117 exchange and 145 transport reactions. iMLTC806cdf is the most complete and accurate metabolic reconstruction of a gram-positive anaerobic bacteria to date. We validate the model with simulated growth assays in different media and carbon sources and use it to predict essential genes. We obtain 89.2% accuracy in the prediction of gene essentiality when compared to experimental data for B. subtilis homologs (the closest organism for which such data exists). We predict the existence of 76 essential genes and 39 essential gene pairs, a number of which are unique to C. difficile and have non-existing or predicted non-essential human homologs. For 29 of these potential therapeutic targets, we find 125 inhibitors of homologous proteins including approved drugs with the potential for drug repositioning, that when validated experimentally could serve as starting points in the development of new antibiotics. CONCLUSIONS We created a highly curated metabolic network model of C. difficile strain 630 and used it to predict essential genes as potential new therapeutic targets in the fight against Clostridium difficile infections.
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Affiliation(s)
- Mathieu Larocque
- Department of Biochemistry, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, J1H 5N4, Canada.
| | - Thierry Chénard
- Department of Biochemistry, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, J1H 5N4, Canada.
| | - Rafael Najmanovich
- Department of Biochemistry, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, J1H 5N4, Canada.
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Au J, Choi J, Jones SW, Venkataramanan KP, Antoniewicz MR. Parallel labeling experiments validate Clostridium acetobutylicum metabolic network model for (13)C metabolic flux analysis. Metab Eng 2014; 26:23-33. [PMID: 25183671 DOI: 10.1016/j.ymben.2014.08.002] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2014] [Revised: 07/27/2014] [Accepted: 08/15/2014] [Indexed: 12/18/2022]
Abstract
In this work, we provide new insights into the metabolism of Clostridium acetobutylicum ATCC 824 obtained using a systematic approach for quantifying fluxes based on parallel labeling experiments and (13)C-metabolic flux analysis ((13)C-MFA). Here, cells were grown in parallel cultures with [1-(13)C]glucose and [U-(13)C]glucose as tracers and (13)C-MFA was used to quantify intracellular metabolic fluxes. Several metabolic network models were compared: an initial model based on current knowledge, and extended network models that included additional reactions that improved the fits of experimental data. While the initial network model did not produce a statistically acceptable fit of (13)C-labeling data, an extended network model with five additional reactions was able to fit all data with 292 redundant measurements. The model was subsequently trimmed to produce a minimal network model of C. acetobutylicum for (13)C-MFA, which could still reproduce all of the experimental data. The flux results provided valuable new insights into the metabolism of C. acetobutylicum. First, we found that TCA cycle was effectively incomplete, as there was no measurable flux between α-ketoglutarate and succinyl-CoA, succinate and fumarate, and malate and oxaloacetate. Second, an active pathway was identified from pyruvate to fumarate via aspartate. Third, we found that isoleucine was produced exclusively through the citramalate synthase pathway in C. acetobutylicum and that CAC3174 was likely responsible for citramalate synthase activity. These model predictions were confirmed in several follow-up tracer experiments. The validated metabolic network model established in this study can be used in future investigations for unbiased (13)C-flux measurements in C. acetobutylicum.
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Affiliation(s)
- Jennifer Au
- Department of Chemical and Biomolecular Engineering, Metabolic Engineering and Systems Biology Laboratory, University of Delaware, 150 Academy Street, Newark, DE 19716, USA
| | - Jungik Choi
- Department of Chemical and Biomolecular Engineering, Metabolic Engineering and Systems Biology Laboratory, University of Delaware, 150 Academy Street, Newark, DE 19716, USA
| | - Shawn W Jones
- Department of Chemical and Biomolecular Engineering, Metabolic Engineering and Systems Biology Laboratory, University of Delaware, 150 Academy Street, Newark, DE 19716, USA
| | - Keerthi P Venkataramanan
- Department of Chemical and Biomolecular Engineering, Metabolic Engineering and Systems Biology Laboratory, University of Delaware, 150 Academy Street, Newark, DE 19716, USA
| | - Maciek R Antoniewicz
- Department of Chemical and Biomolecular Engineering, Metabolic Engineering and Systems Biology Laboratory, University of Delaware, 150 Academy Street, Newark, DE 19716, USA.
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Benedict MN, Henriksen JR, Metcalf WW, Whitaker RJ, Price ND. ITEP: an integrated toolkit for exploration of microbial pan-genomes. BMC Genomics 2014; 15:8. [PMID: 24387194 PMCID: PMC3890548 DOI: 10.1186/1471-2164-15-8] [Citation(s) in RCA: 78] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2013] [Accepted: 12/18/2013] [Indexed: 01/31/2023] Open
Abstract
Background Comparative genomics is a powerful approach for studying variation in physiological traits as well as the evolution and ecology of microorganisms. Recent technological advances have enabled sequencing large numbers of related genomes in a single project, requiring computational tools for their integrated analysis. In particular, accurate annotations and identification of gene presence and absence are critical for understanding and modeling the cellular physiology of newly sequenced genomes. Although many tools are available to compare the gene contents of related genomes, new tools are necessary to enable close examination and curation of protein families from large numbers of closely related organisms, to integrate curation with the analysis of gain and loss, and to generate metabolic networks linking the annotations to observed phenotypes. Results We have developed ITEP, an Integrated Toolkit for Exploration of microbial Pan-genomes, to curate protein families, compute similarities to externally-defined domains, analyze gene gain and loss, and generate draft metabolic networks from one or more curated reference network reconstructions in groups of related microbial species among which the combination of core and variable genes constitute the their "pan-genomes". The ITEP toolkit consists of: (1) a series of modular command-line scripts for identification, comparison, curation, and analysis of protein families and their distribution across many genomes; (2) a set of Python libraries for programmatic access to the same data; and (3) pre-packaged scripts to perform common analysis workflows on a collection of genomes. ITEP’s capabilities include de novo protein family prediction, ortholog detection, analysis of functional domains, identification of core and variable genes and gene regions, sequence alignments and tree generation, annotation curation, and the integration of cross-genome analysis and metabolic networks for study of metabolic network evolution. Conclusions ITEP is a powerful, flexible toolkit for generation and curation of protein families. ITEP's modular design allows for straightforward extension as analysis methods and tools evolve. By integrating comparative genomics with the development of draft metabolic networks, ITEP harnesses the power of comparative genomics to build confidence in links between genotype and phenotype and helps disambiguate gene annotations when they are evaluated in both evolutionary and metabolic network contexts.
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Affiliation(s)
| | | | | | | | - Nathan D Price
- Institute for Systems Biology, 401 Terry Ave, N,, Seattle, WA 98109, USA.
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Dash S, Mueller TJ, Venkataramanan KP, Papoutsakis ET, Maranas CD. Capturing the response of Clostridium acetobutylicum to chemical stressors using a regulated genome-scale metabolic model. BIOTECHNOLOGY FOR BIOFUELS 2014; 7:144. [PMID: 25379054 PMCID: PMC4207355 DOI: 10.1186/s13068-014-0144-4] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2014] [Accepted: 09/22/2014] [Indexed: 05/20/2023]
Abstract
BACKGROUND Clostridia are anaerobic Gram-positive Firmicutes containing broad and flexible systems for substrate utilization, which have been used successfully to produce a range of industrial compounds. In particular, Clostridium acetobutylicum has been used to produce butanol on an industrial scale through acetone-butanol-ethanol (ABE) fermentation. A genome-scale metabolic (GSM) model is a powerful tool for understanding the metabolic capacities of an organism and developing metabolic engineering strategies for strain development. The integration of stress-related specific transcriptomics information with the GSM model provides opportunities for elucidating the focal points of regulation. RESULTS We describe here the construction and validation of a GSM model for C. acetobutylicum ATCC 824, iCac802. iCac802 spans 802 genes and includes 1,137 metabolites and 1,462 reactions, along with gene-protein-reaction associations. Both (13)C-MFA and gene deletion data in the ABE fermentation pathway were used to test the predicted flux ranges allowed by the model. We also describe the CoreReg method, introduced in this paper, to integrate transcriptomic data and identify core sets of reactions that, when their flux was selectively restricted, reproduced flux and biomass-formation ranges seen under all regulatory constraints. CoreReg was used in response to butanol and butyrate stress to tighten bounds for 50 reactions within the iCac802 model. These bounds affected the flux of tens of reactions in core metabolism. The model, incorporating the regulatory restrictions from CoreReg under chemical stress, exhibited an approximate 70% reduction in biomass yield for most stress conditions. CONCLUSIONS The regulation placed on the model for the two stresses using CoreReg identified differences in the respective responses, including distinct core sets and the restriction of biomass production similar to experimental observations. Given the core sets predicted by the CoreReg method, remedial actions can be taken to counteract the effect of stress on metabolism. For less well-known systems, plausible regulatory loops can be suggested around the affected metabolic reactions, and the hypotheses can be tested experimentally.
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Affiliation(s)
- Satyakam Dash
- />Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania USA
| | - Thomas J Mueller
- />Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania USA
| | - Keerthi P Venkataramanan
- />Delaware Biotechnology Institute, 15 Innovation Way, Newark, 19711 Delaware USA
- />Department of Chemical Engineering, University of Delaware, Newark, Delaware USA
| | - Eleftherios T Papoutsakis
- />Delaware Biotechnology Institute, 15 Innovation Way, Newark, 19711 Delaware USA
- />Department of Chemical Engineering, University of Delaware, Newark, Delaware USA
| | - Costas D Maranas
- />Department of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania USA
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