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Höper R, Komkova D, Zavřel T, Steuer R. A quantitative description of light-limited cyanobacterial growth using flux balance analysis. PLoS Comput Biol 2024; 20:e1012280. [PMID: 39102434 PMCID: PMC11326710 DOI: 10.1371/journal.pcbi.1012280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 08/15/2024] [Accepted: 06/26/2024] [Indexed: 08/07/2024] Open
Abstract
The metabolism of phototrophic cyanobacteria is an integral part of global biogeochemical cycles, and the capability of cyanobacteria to assimilate atmospheric CO2 into organic carbon has manifold potential applications for a sustainable biotechnology. To elucidate the properties of cyanobacterial metabolism and growth, computational reconstructions of genome-scale metabolic networks play an increasingly important role. Here, we present an updated reconstruction of the metabolic network of the cyanobacterium Synechocystis sp. PCC 6803 and its quantitative evaluation using flux balance analysis (FBA). To overcome limitations of conventional FBA, and to allow for the integration of experimental analyses, we develop a novel approach to describe light absorption and light utilization within the framework of FBA. Our approach incorporates photoinhibition and a variable quantum yield into the constraint-based description of light-limited phototrophic growth. We show that the resulting model is capable of predicting quantitative properties of cyanobacterial growth, including photosynthetic oxygen evolution and the ATP/NADPH ratio required for growth and cellular maintenance. Our approach retains the computational and conceptual simplicity of FBA and is readily applicable to other phototrophic microorganisms.
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Affiliation(s)
- Rune Höper
- Institute for Biology, Theoretical Biology (ITB), Humboldt-University of Berlin, Berlin, Germany
| | - Daria Komkova
- Institute for Biology, Theoretical Biology (ITB), Humboldt-University of Berlin, Berlin, Germany
| | - Tomáš Zavřel
- Department of Adaptive Biotechnologies, Global Change Research Institute of the Czech Academy of Sciences, Brno, Czechia
| | - Ralf Steuer
- Institute for Biology, Theoretical Biology (ITB), Humboldt-University of Berlin, Berlin, Germany
- Peter Debye Institute for Soft Matter Physics, Universität Leipzig, Leipzig, Germany
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Babele PK, Srivastava A, Young JD. Metabolic flux phenotyping of secondary metabolism in cyanobacteria. Trends Microbiol 2023; 31:1118-1130. [PMID: 37331829 DOI: 10.1016/j.tim.2023.05.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 05/10/2023] [Accepted: 05/15/2023] [Indexed: 06/20/2023]
Abstract
Cyanobacteria generate energy from photosynthesis and produce various secondary metabolites with diverse commercial and pharmaceutical applications. Unique metabolic and regulatory pathways in cyanobacteria present new challenges for researchers to enhance their product yields, titers, and rates. Therefore, further advancements are critically needed to establish cyanobacteria as a preferred bioproduction platform. Metabolic flux analysis (MFA) quantitatively determines the intracellular flows of carbon within complex biochemical networks, which elucidate the control of metabolic pathways by transcriptional, translational, and allosteric regulatory mechanisms. The emerging field of systems metabolic engineering (SME) involves the use of MFA and other omics technologies to guide the rational development of microbial production strains. This review highlights the potential of MFA and SME to optimize the production of cyanobacterial secondary metabolites and discusses the technical challenges that lie ahead.
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Affiliation(s)
- Piyoosh K Babele
- College of Agriculture, Rani Lakshmi Bai Central Agricultural University Jhansi, 284003, Uttar Pradesh, India.
| | - Amit Srivastava
- University of Jyväskylä, Nanoscience Centre, Department of Biological and Environmental Science, 40014 Jyväskylä, Finland
| | - Jamey D Young
- Department of Chemical and Biomolecular Engineering, Vanderbilt University, PMB 351604, Nashville, TN 37235-1604, USA; Department of Molecular Physiology and Biophysics, Vanderbilt University, PMB 351604, Nashville, TN 37235-1604, USA.
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Faizi M, Steuer R. Optimal proteome allocation strategies for phototrophic growth in a light-limited chemostat. Microb Cell Fact 2019; 18:165. [PMID: 31601201 PMCID: PMC6785936 DOI: 10.1186/s12934-019-1209-7] [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: 07/01/2019] [Accepted: 09/06/2019] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Cyanobacteria and other phototrophic microorganisms allow to couple the light-driven assimilation of atmospheric [Formula: see text] directly to the synthesis of carbon-based products, and are therefore attractive platforms for microbial cell factories. While most current engineering efforts are performed using small-scale laboratory cultivation, the economic viability of phototrophic cultivation also crucially depends on photobioreactor design and culture parameters, such as the maximal areal and volumetric productivities. Based on recent insights into the cyanobacterial cell physiology and the resulting computational models of cyanobacterial growth, the aim of this study is to investigate the limits of cyanobacterial productivity in continuous culture with light as the limiting nutrient. RESULTS We integrate a coarse-grained model of cyanobacterial growth into a light-limited chemostat and its heterogeneous light gradient induced by self-shading of cells. We show that phototrophic growth in the light-limited chemostat can be described using the concept of an average light intensity. Different from previous models based on phenomenological growth equations, our model provides a mechanistic link between intracellular protein allocation, population growth and the resulting reactor productivity. Our computational framework thereby provides a novel approach to investigate and predict the maximal productivity of phototrophic cultivation, and identifies optimal proteome allocation strategies for developing maximally productive strains. CONCLUSIONS Our results have implications for efficient phototrophic cultivation and the design of maximally productive phototrophic cell factories. The model predicts that the use of dense cultures in well-mixed photobioreactors with short light-paths acts as an effective light dilution mechanism and alleviates the detrimental effects of photoinhibition even under very high light intensities. We recover the well-known trade-offs between a reduced light-harvesting apparatus and increased population density. Our results are discussed in the context of recent experimental efforts to increase the yield of phototrophic cultivation.
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Affiliation(s)
- Marjan Faizi
- Institut für Biologie, Fachinstitut für Theoretische Biologie, Humboldt-Universität zu Berlin, Invalidenstr. 110, 10115, Berlin, Germany
| | - Ralf Steuer
- Institut für Biologie, Fachinstitut für Theoretische Biologie, Humboldt-Universität zu Berlin, Invalidenstr. 110, 10115, Berlin, Germany.
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Sun T, Li S, Song X, Diao J, Chen L, Zhang W. Toolboxes for cyanobacteria: Recent advances and future direction. Biotechnol Adv 2018; 36:1293-1307. [DOI: 10.1016/j.biotechadv.2018.04.007] [Citation(s) in RCA: 78] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2018] [Revised: 04/09/2018] [Accepted: 04/26/2018] [Indexed: 12/20/2022]
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Abernathy MH, Yu J, Ma F, Liberton M, Ungerer J, Hollinshead WD, Gopalakrishnan S, He L, Maranas CD, Pakrasi HB, Allen DK, Tang YJ. Deciphering cyanobacterial phenotypes for fast photoautotrophic growth via isotopically nonstationary metabolic flux analysis. BIOTECHNOLOGY FOR BIOFUELS 2017; 10:273. [PMID: 29177008 PMCID: PMC5691832 DOI: 10.1186/s13068-017-0958-y] [Citation(s) in RCA: 74] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2017] [Accepted: 11/06/2017] [Indexed: 05/09/2023]
Abstract
BACKGROUND Synechococcus elongatus UTEX 2973 is the fastest growing cyanobacterium characterized to date. Its genome was found to be 99.8% identical to S. elongatus 7942 yet it grows twice as fast. Current genome-to-phenome mapping is still poorly performed for non-model organisms. Even for species with identical genomes, cell phenotypes can be strikingly different. To understand Synechococcus 2973's fast-growth phenotype and its metabolic features advantageous to photo-biorefineries, 13C isotopically nonstationary metabolic flux analysis (INST-MFA), biomass compositional analysis, gene knockouts, and metabolite profiling were performed on both strains under various growth conditions. RESULTS The Synechococcus 2973 flux maps show substantial carbon flow through the Calvin cycle, glycolysis, photorespiration and pyruvate kinase, but minimal flux through the malic enzyme and oxidative pentose phosphate pathways under high light/CO2 conditions. During fast growth, its pool sizes of key metabolites in central pathways were lower than suboptimal growth. Synechococcus 2973 demonstrated similar flux ratios to Synechococcus 7942 (under fast growth conditions), but exhibited greater carbon assimilation, higher NADPH concentrations, higher energy charge (relative ATP ratio over ADP and AMP), less accumulation of glycogen, and potentially metabolite channeling. Furthermore, Synechococcus 2973 has very limited flux through the TCA pathway with small pool sizes of acetyl-CoA/TCA intermediates under all growth conditions. CONCLUSIONS This study employed flux analysis to investigate phenotypic heterogeneity among two cyanobacterial strains with near-identical genome background. The flux/metabolite profiling, biomass composition analysis, and genetic modification results elucidate a highly effective metabolic topology for CO2 assimilatory and biosynthesis in Synechococcus 2973. Comparisons across multiple Synechococcus strains indicate faster metabolism is also driven by proportional increases in both photosynthesis and key central pathway fluxes. Moreover, the flux distribution in Synechococcus 2973 supports the use of its strong sugar phosphate pathways for optimal bio-productions. The integrated methodologies in this study can be applied for characterizing non-model microbial metabolism.
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Affiliation(s)
- Mary H. Abernathy
- Department of Energy, Environmental and Chemical Engineering, Washington University, St. Louis, MO 63130 USA
| | - Jingjie Yu
- Department of Biology, Temple University, Philadelphia, PA 19122 USA
| | - Fangfang Ma
- Donald Danforth Plant Science Center, St. Louis, MO 63132 USA
| | - Michelle Liberton
- Department of Biology, Washington University, St. Louis, MO 63130 USA
| | - Justin Ungerer
- Department of Biology, Washington University, St. Louis, MO 63130 USA
| | - Whitney D. Hollinshead
- Department of Energy, Environmental and Chemical Engineering, Washington University, St. Louis, MO 63130 USA
| | - Saratram Gopalakrishnan
- Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802 USA
| | - Lian He
- Department of Energy, Environmental and Chemical Engineering, Washington University, St. Louis, MO 63130 USA
| | - Costas D. Maranas
- Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802 USA
| | - Himadri B. Pakrasi
- Department of Energy, Environmental and Chemical Engineering, Washington University, St. Louis, MO 63130 USA
- Department of Biology, Washington University, St. Louis, MO 63130 USA
| | - Doug K. Allen
- Donald Danforth Plant Science Center, St. Louis, MO 63132 USA
- United States Department of Agriculture, Agricultural Research Service, St. Louis, MO 63132 USA
| | - Yinjie J. Tang
- Department of Energy, Environmental and Chemical Engineering, Washington University, St. Louis, MO 63130 USA
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Unique attributes of cyanobacterial metabolism revealed by improved genome-scale metabolic modeling and essential gene analysis. Proc Natl Acad Sci U S A 2016; 113:E8344-E8353. [PMID: 27911809 DOI: 10.1073/pnas.1613446113] [Citation(s) in RCA: 77] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
The model cyanobacterium, Synechococcus elongatus PCC 7942, is a genetically tractable obligate phototroph that is being developed for the bioproduction of high-value chemicals. Genome-scale models (GEMs) have been successfully used to assess and engineer cellular metabolism; however, GEMs of phototrophic metabolism have been limited by the lack of experimental datasets for model validation and the challenges of incorporating photon uptake. Here, we develop a GEM of metabolism in S. elongatus using random barcode transposon site sequencing (RB-TnSeq) essential gene and physiological data specific to photoautotrophic metabolism. The model explicitly describes photon absorption and accounts for shading, resulting in the characteristic linear growth curve of photoautotrophs. GEM predictions of gene essentiality were compared with data obtained from recent dense-transposon mutagenesis experiments. This dataset allowed major improvements to the accuracy of the model. Furthermore, discrepancies between GEM predictions and the in vivo dataset revealed biological characteristics, such as the importance of a truncated, linear TCA pathway, low flux toward amino acid synthesis from photorespiration, and knowledge gaps within nucleotide metabolism. Coupling of strong experimental support and photoautotrophic modeling methods thus resulted in a highly accurate model of S. elongatus metabolism that highlights previously unknown areas of S. elongatus biology.
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