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Riaz MR, Preston GM, Mithani A. MAPPS: A Web-Based Tool for Metabolic Pathway Prediction and Network Analysis in the Postgenomic Era. ACS Synth Biol 2020; 9:1069-1082. [PMID: 32347714 DOI: 10.1021/acssynbio.9b00397] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Comparative and evolutionary analyses of metabolic networks have a wide range of applications, ranging from research into metabolic evolution through to practical applications in drug development, synthetic biology, and biodegradation. We present MAPPS: Metabolic network Analysis and Pathway Prediction Server (https://mapps.lums.edu.pk), a web-based tool to study functions and evolution of metabolic networks using traditional and 'omics data sets. MAPPS provides diverse functionalities including an interactive interface, graphical visualization of results, pathway prediction and network comparison, identification of potential drug targets, in silico metabolic engineering, host-microbe interactions, and ancestral network building. Importantly, MAPPS also allows users to upload custom data, thus enabling metabolic analyses on draft and custom genomes, and has an 'omics pipeline to filter pathway results, making it relevant in today's postgenomic era.
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Affiliation(s)
- Muhammad Rizwan Riaz
- Department of Biology, Syed Babar Ali School of Science and Engineering, Lahore University of Management Sciences (LUMS), DHA, Lahore 54792, Pakistan
| | - Gail M. Preston
- Department of Plant Sciences, University of Oxford, South Parks Road, Oxford OX1 3RB, U.K
| | - Aziz Mithani
- Department of Biology, Syed Babar Ali School of Science and Engineering, Lahore University of Management Sciences (LUMS), DHA, Lahore 54792, Pakistan
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Heijstra BD, Leang C, Juminaga A. Gas fermentation: cellular engineering possibilities and scale up. Microb Cell Fact 2017; 16:60. [PMID: 28403896 PMCID: PMC5389167 DOI: 10.1186/s12934-017-0676-y] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2016] [Accepted: 04/04/2017] [Indexed: 12/11/2022] Open
Abstract
Low carbon fuels and chemicals can be sourced from renewable materials such as biomass or from industrial and municipal waste streams. Gasification of these materials allows all of the carbon to become available for product generation, a clear advantage over partial biomass conversion into fermentable sugars. Gasification results into a synthesis stream (syngas) containing carbon monoxide (CO), carbon dioxide (CO2), hydrogen (H2) and nitrogen (N2). Autotrophy-the ability to fix carbon such as CO2 is present in all domains of life but photosynthesis alone is not keeping up with anthropogenic CO2 output. One strategy is to curtail the gaseous atmospheric release by developing waste and syngas conversion technologies. Historically microorganisms have contributed to major, albeit slow, atmospheric composition changes. The current status and future potential of anaerobic gas-fermenting bacteria with special focus on acetogens are the focus of this review.
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Affiliation(s)
| | - Ching Leang
- LanzaTech, Inc., 8045 Lamon Ave, Suite 400, Skokie, IL USA
| | - Alex Juminaga
- LanzaTech, Inc., 8045 Lamon Ave, Suite 400, Skokie, IL USA
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Guo W, Sheng J, Feng X. Synergizing 13C Metabolic Flux Analysis and Metabolic Engineering for Biochemical Production. ADVANCES IN BIOCHEMICAL ENGINEERING/BIOTECHNOLOGY 2017; 162:265-299. [PMID: 28424826 DOI: 10.1007/10_2017_2] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Metabolic engineering of industrial microorganisms to produce chemicals, fuels, and drugs has attracted increasing interest as it provides an environment-friendly and renewable route that does not depend on depleting petroleum sources. However, the microbial metabolism is so complex that metabolic engineering efforts often have difficulty in achieving a satisfactory yield, titer, or productivity of the target chemical. To overcome this challenge, 13C Metabolic Flux Analysis (13C-MFA) has been developed to investigate rigorously the cell metabolism and quantify the carbon flux distribution in central metabolic pathways. In the past decade, 13C-MFA has been widely used in academic labs and the biotechnology industry to pinpoint the key issues related to microbial-based chemical production and to guide the development of the appropriate metabolic engineering strategies for improving the biochemical production. In this chapter we introduce the basics of 13C-MFA and illustrate how 13C-MFA has been applied to synergize with metabolic engineering to identify and tackle the rate-limiting steps in biochemical production.
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Affiliation(s)
- Weihua Guo
- Department of Biological Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA, 24061, USA
| | - Jiayuan Sheng
- Department of Biological Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA, 24061, USA
| | - Xueyang Feng
- Department of Biological Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA, 24061, USA.
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Combined 13C-assisted metabolomics and metabolic flux analysis reveals the impacts of glutamate on the central metabolism of high β-galactosidase-producing Pichia pastoris. BIORESOUR BIOPROCESS 2016; 3:47. [PMID: 27867835 PMCID: PMC5093185 DOI: 10.1186/s40643-016-0124-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2016] [Accepted: 10/26/2016] [Indexed: 01/01/2023] Open
Abstract
Background Pichia pastoris is a popular recombinant protein expression system for its accessibility of efficient gene manipulation and high protein production. Sufficient supply of precursors, energy, and redox cofactors is crucial for high recombinant protein production. In our present work, we found that the addition of glutamate improved the recombinant β-galactosidase (β-gal) production by P. pastoris G1HL. Methods To elucidate the impacts of glutamate on the central metabolism in detail, a combined 13C-assisted metabolomics and 13C metabolic flux analysis was conducted based on LC–MS/MS and GC–MS data. Results The pool sizes of intracellular amino acids were obviously higher on glucose/glutamate (Glc/Glu). The fluxes in EMP entry reaction and in downstream TCA cycle were 50 and 67% higher on Glc/Glu than on Glc, respectively. While the fluxes in upstream TCA cycle kept almost unaltered, the fluxes in PPP oxidative branch decreased. Conclusion The addition of glutamate leads to a remarkable change on the central metabolism of high β-galactosidase-producing P. pastoris G1HL. To meet the increased demands of redox cofactors and energy for higher β-galactosidase production on Glc/Glu, P. pastoris G1HL redistributes the fluxes in central metabolism through the inhibitions and/or activation of the enzymes in key nodes together with the energy and redox status. Electronic supplementary material The online version of this article (doi:10.1186/s40643-016-0124-6) contains supplementary material, which is available to authorized users.
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Guo W, Chen Y, Wei N, Feng X. Investigate the Metabolic Reprogramming of Saccharomyces cerevisiae for Enhanced Resistance to Mixed Fermentation Inhibitors via 13C Metabolic Flux Analysis. PLoS One 2016; 11:e0161448. [PMID: 27532329 PMCID: PMC4988770 DOI: 10.1371/journal.pone.0161448] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2016] [Accepted: 08/07/2016] [Indexed: 11/18/2022] Open
Abstract
The fermentation inhibitors from the pretreatment of lignocellulosic materials, e.g., acetic acid and furfural, are notorious due to their negative effects on the cell growth and chemical production. However, the metabolic reprogramming of the cells under these stress conditions, especially metabolic response for resistance to mixed inhibitors, has not been systematically investigated and remains mysterious. Therefore, in this study, 13C metabolic flux analysis (13C-MFA), a powerful tool to elucidate the intracellular carbon flux distributions, has been applied to two Saccharomyces cerevisiae strains with different tolerances to the inhibitors under acetic acid, furfural, and mixed (i.e., acetic acid and furfural) stress conditions to unravel the key metabolic responses. By analyzing the intracellular carbon fluxes as well as the energy and cofactor utilization under different conditions, we uncovered varied metabolic responses to different inhibitors. Under acetate stress, ATP and NADH production was slightly impaired, while NADPH tended towards overproduction. Under furfural stress, ATP and cofactors (including both NADH and NADPH) tended to be overproduced. However, under dual-stress condition, production of ATP and cofactors was severely impaired due to synergistic stress caused by the simultaneous addition of two fermentation inhibitors. Such phenomenon indicated the pivotal role of the energy and cofactor utilization in resisting the mixed inhibitors of acetic acid and furfural. Based on the discoveries, valuable insights are provided to improve the tolerance of S. cerevisiae strain and further enhance lignocellulosic fermentation.
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Affiliation(s)
- Weihua Guo
- Department of Biological Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, United States of America
| | - Yingying Chen
- Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, IN 46556, United States of America
| | - Na Wei
- Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, IN 46556, United States of America
- * E-mail: (NW); (XF)
| | - Xueyang Feng
- Department of Biological Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, United States of America
- * E-mail: (NW); (XF)
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Suástegui M, Guo W, Feng X, Shao Z. Investigating strain dependency in the production of aromatic compounds in
Saccharomyces cerevisiae. Biotechnol Bioeng 2016; 113:2676-2685. [DOI: 10.1002/bit.26037] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2016] [Revised: 05/16/2016] [Accepted: 06/13/2016] [Indexed: 12/13/2022]
Affiliation(s)
- Miguel Suástegui
- Department of Chemical and Biological EngineeringIowa State UniversityAmesIowa
- NSF Engineering Research Center for Biorenewable Chemicals (CBiRC)AmesIowa
| | - Weihua Guo
- Department of Biological Systems EngineeringVirginia Polytechnic Institute and State UniversityBlacksburgVirginia
| | - Xueyang Feng
- Department of Biological Systems EngineeringVirginia Polytechnic Institute and State UniversityBlacksburgVirginia
| | - Zengyi Shao
- Department of Chemical and Biological EngineeringIowa State UniversityAmesIowa
- NSF Engineering Research Center for Biorenewable Chemicals (CBiRC)AmesIowa
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Luo S, Guo W, Nealson KH, Feng X, He Z. ¹³C Pathway Analysis for the Role of Formate in Electricity Generation by Shewanella Oneidensis MR-1 Using Lactate in Microbial Fuel Cells. Sci Rep 2016; 6:20941. [PMID: 26868848 PMCID: PMC4751489 DOI: 10.1038/srep20941] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2015] [Accepted: 01/14/2016] [Indexed: 12/16/2022] Open
Abstract
Microbial fuel cell (MFC) is a promising technology for direct electricity generation from organics by microorganisms. The type of electron donors fed into MFCs affects the electrical performance, and mechanistic understanding of such effects is important to optimize the MFC performance. In this study, we used a model organism in MFCs, Shewanella oneidensis MR-1, and (13)C pathway analysis to investigate the role of formate in electricity generation and the related microbial metabolism. Our results indicated a synergistic effect of formate and lactate on electricity generation, and extra formate addition on the original lactate resulted in more electrical output than using formate or lactate as a sole electron donor. Based on the (13)C tracer analysis, we discovered decoupled cell growth and electricity generation in S. oneidensis MR-1 during co-utilization of lactate and formate (i.e., while the lactate was mainly metabolized to support the cell growth, the formate was oxidized to release electrons for higher electricity generation). To our best knowledge, this is the first time that (13)C tracer analysis was applied to study microbial metabolism in MFCs and it was demonstrated to be a valuable tool to understand the metabolic pathways affected by electron donors in the selected electrochemically-active microorganisms.
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Affiliation(s)
- Shuai Luo
- Department of Civil and Environmental Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA
| | - Weihua Guo
- Department of Biological Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA
| | - Kenneth H Nealson
- Department of Earth Sciences, University of Southern California, Los Angeles, CA 90089, USA
| | - Xueyang Feng
- Department of Biological Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA
| | - Zhen He
- Department of Civil and Environmental Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA
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13C-Metabolic Flux Analysis: An Accurate Approach to Demystify Microbial Metabolism for Biochemical Production. Bioengineering (Basel) 2015; 3:bioengineering3010003. [PMID: 28952565 PMCID: PMC5597161 DOI: 10.3390/bioengineering3010003] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2015] [Revised: 12/10/2015] [Accepted: 12/18/2015] [Indexed: 12/15/2022] Open
Abstract
Metabolic engineering of various industrial microorganisms to produce chemicals, fuels, and drugs has raised interest since it is environmentally friendly, sustainable, and independent of nonrenewable resources. However, microbial metabolism is so complex that only a few metabolic engineering efforts have been able to achieve a satisfactory yield, titer or productivity of the target chemicals for industrial commercialization. In order to overcome this challenge, 13C Metabolic Flux Analysis (13C-MFA) has been continuously developed and widely applied to rigorously investigate cell metabolism and quantify the carbon flux distribution in central metabolic pathways. In the past decade, many 13C-MFA studies have been performed in academic labs and biotechnology industries to pinpoint key issues related to microbe-based chemical production. Insightful information about the metabolic rewiring has been provided to guide the development of the appropriate metabolic engineering strategies for improving the biochemical production. In this review, we will introduce the basics of 13C-MFA and illustrate how 13C-MFA has been applied via integration with metabolic engineering to identify and tackle the rate-limiting steps in biochemical production for various host microorganisms
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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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Impacts of high β-galactosidase expression on central metabolism of recombinant Pichia pastoris GS115 using glucose as sole carbon source via (13)C metabolic flux analysis. J Biotechnol 2014; 187:124-34. [PMID: 25058396 DOI: 10.1016/j.jbiotec.2014.07.011] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2014] [Revised: 06/20/2014] [Accepted: 07/08/2014] [Indexed: 11/22/2022]
Abstract
The yeast Pichia pastoris GS115 is a widely used microbial cell factory for the production of heterologous protein. In order to reveal the impacts of high heterologous protein expression on the central metabolism of Pichia pastoris GS115 using glucose as sole carbon source, we engineered a high β-galactosidase expression strain P. pastoris G1HL and a low expression control strain P. pastoris GHL through controlling the initiation strength of constitutive promoter pGAP. The carbon flux distributions in these two strains were quantified via (13)C metabolic flux analysis. Compared to the control strain, G1HL showed a lower growth rate, a higher flux through glycolysis pathway, a higher flux through pentose phosphate pathway, and a lower flux through by-products secretion pathway. The metabolic flux redistribution in G1HL was thought to compensate the increased redox cofactors and energy demands caused by the high protein expression. Although the fluxes through Krebs cycle in two engineered strains were almost the same, they were significantly lower than those in wild strain. The enhanced expression of β-galactosidase by glutamate supplementation demonstrated the potential of P. pastoris GS115 to catabolize more carbon through the Krebs cycle for even higher protein expression. In conclusion, our work indicates that P. pastoris GS115 can readjusts the central metabolism for higher heterologous protein expression and provides strategies for strain development or process optimization for enhancing production of heterologous protein.
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Fernández-Castané A, Fehér T, Carbonell P, Pauthenier C, Faulon JL. Computer-aided design for metabolic engineering. J Biotechnol 2014; 192 Pt B:302-13. [PMID: 24704607 DOI: 10.1016/j.jbiotec.2014.03.029] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2013] [Revised: 03/18/2014] [Accepted: 03/24/2014] [Indexed: 12/20/2022]
Abstract
The development and application of biotechnology-based strategies has had a great socio-economical impact and is likely to play a crucial role in the foundation of more sustainable and efficient industrial processes. Within biotechnology, metabolic engineering aims at the directed improvement of cellular properties, often with the goal of synthesizing a target chemical compound. The use of computer-aided design (CAD) tools, along with the continuously emerging advanced genetic engineering techniques have allowed metabolic engineering to broaden and streamline the process of heterologous compound-production. In this work, we review the CAD tools available for metabolic engineering with an emphasis, on retrosynthesis methodologies. Recent advances in genetic engineering strategies for pathway implementation and optimization are also reviewed as well as a range of bionalytical tools to validate in silico predictions. A case study applying retrosynthesis is presented as an experimental verification of the output from Retropath, the first complete automated computational pipeline applicable to metabolic engineering. Applying this CAD pipeline, together with genetic reassembly and optimization of culture conditions led to improved production of the plant flavonoid pinocembrin. Coupling CAD tools with advanced genetic engineering strategies and bioprocess optimization is crucial for enhanced product yields and will be of great value for the development of non-natural products through sustainable biotechnological processes.
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Affiliation(s)
- Alfred Fernández-Castané
- Institute of Systems and Synthetic Biology, University of Evry-Val-d'Essonne, CNRS FRE3561, Genopole(®) Campus 1, Genavenir 6, 5 rue Henri Desbruères, F-91030 Evry Cedex, France.
| | - Tamás Fehér
- Institute of Systems and Synthetic Biology, University of Evry-Val-d'Essonne, CNRS FRE3561, Genopole(®) Campus 1, Genavenir 6, 5 rue Henri Desbruères, F-91030 Evry Cedex, France.
| | - Pablo Carbonell
- Institute of Systems and Synthetic Biology, University of Evry-Val-d'Essonne, CNRS FRE3561, Genopole(®) Campus 1, Genavenir 6, 5 rue Henri Desbruères, F-91030 Evry Cedex, France.
| | - Cyrille Pauthenier
- Institute of Systems and Synthetic Biology, University of Evry-Val-d'Essonne, CNRS FRE3561, Genopole(®) Campus 1, Genavenir 6, 5 rue Henri Desbruères, F-91030 Evry Cedex, France.
| | - Jean-Loup Faulon
- Institute of Systems and Synthetic Biology, University of Evry-Val-d'Essonne, CNRS FRE3561, Genopole(®) Campus 1, Genavenir 6, 5 rue Henri Desbruères, F-91030 Evry Cedex, France.
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