A quantitative description of light-limited cyanobacterial growth using flux balance analysis

. 2024 Aug ; 20 (8) : e1012280. [epub] 20240805

Jazyk angličtina Země Spojené státy americké Médium electronic-ecollection

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/pmid39102434

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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Zavřel T, Faizi M, Loureiro C, Poschmann G, Stühler K, Sinetova M, et al.. Quantitative insights into the cyanobacterial cell economy. eLife. 2019;8:e42508. doi: 10.7554/eLife.42508 PubMed DOI PMC

Mills LA, McCormick AJ, Lea-Smith DJ. Current knowledge and recent advances in understanding metabolism of the model cyanobacterium Synechocystis sp. PCC 6803. Biosci Rep. 2020;40(4). doi: 10.1042/BSR20193325 PubMed DOI PMC

Nogales J, Gudmundsson S, Knight EM, Palsson BO, Thiele I. Detailing the optimality of photosynthesis in cyanobacteria through systems biology analysis. Proceedings of the National Academy of Sciences. 2012;109(7):2678–2683. doi: 10.1073/pnas.1117907109 PubMed DOI PMC

Knoop H, Zilliges Y, Lockau W, Steuer R. The metabolic network of Synechocystis sp. PCC 6803: systemic properties of autotrophic growth. Plant Physiol. 2010;154(1):410–422. doi: 10.1104/pp.110.157198 PubMed DOI PMC

Knoop H, Gründel M, Zilliges Y, Lehmann R, Hoffmann S, Lockau W, et al.. Flux balance analysis of cyanobacterial metabolism: the metabolic network of Synechocystis sp. PCC 6803. PLoS Comput Biol. 2013;9(6):e1003081. doi: 10.1371/journal.pcbi.1003081 PubMed DOI PMC

Maarleveld TR, Boele J, Bruggeman FJ, Teusink B. A data integration and visualization resource for the metabolic network of Synechocystis sp. PCC 6803. Plant Physiol. 2014;164(3):1111–1121. doi: 10.1104/pp.113.224394 PubMed DOI PMC

Joshi CJ, Peebles CAM, Prasad A. Modeling and analysis of flux distribution and bioproduct formation in Synechocystis sp. PCC 6803 using a new genome-scale metabolic reconstruction. Algal Research. 2017;27:295–310. doi: 10.1016/j.algal.2017.09.013 DOI

Sarkar D, Mueller TJ, Liu D, Pakrasi HB, Maranas CD. A diurnal flux balance model of Synechocystis sp. PCC 6803 metabolism. PLoS Comput Biol. 2019;15(1):e1006692. doi: 10.1371/journal.pcbi.1006692 PubMed DOI PMC

Toyoshima M, Toya Y, Shimizu H. Flux balance analysis of cyanobacteria reveals selective use of photosynthetic electron transport components under different spectral light conditions. Photosynth Res. 2020;143(1):31–43. doi: 10.1007/s11120-019-00678-x PubMed DOI

Kugler A, Stensjö K. Optimal energy and redox metabolism in the cyanobacterium Synechocystis sp. PCC 6803. NPJ Syst Biol Appl. 2023;9(1):47. doi: 10.1038/s41540-023-00307-3 PubMed DOI PMC

Saha R, Verseput AT, Berla BM, Mueller TJ, Pakrasi HB, Maranas CD. Reconstruction and comparison of the metabolic potential of cyanobacteria Cyanothece sp. ATCC 51142 and Synechocystis sp. PCC 6803. PLoS One. 2012;7(10):e48285. doi: 10.1371/journal.pone.0048285 PubMed DOI PMC

Hendry JI, Prasannan CB, Joshi A, Dasgupta S, Wangikar PP. Metabolic model of Synechococcus sp. PCC 7002: Prediction of flux distribution and network modification for enhanced biofuel production. Bioresour Technol. 2016;213:190–197. doi: 10.1016/j.biortech.2016.02.128 PubMed DOI

Reimers AM, Knoop H, Bockmayr A, Steuer R. Cellular trade-offs and optimal resource allocation during cyanobacterial diurnal growth. Proc Natl Acad Sci U S A. 2017;114(31):E6457–E6465. doi: 10.1073/pnas.1617508114 PubMed DOI PMC

Qian X, Kim MK, Kumaraswamy GK, Agarwal A, Lun DS, Dismukes GC. Flux balance analysis of photoautotrophic metabolism: Uncovering new biological details of subsystems involved in cyanobacterial photosynthesis. Biochim Biophys Acta Bioenerg. 2017;1858(4):276–287. doi: 10.1016/j.bbabio.2016.12.007 PubMed DOI

Malatinszky D, Steuer R, Jones PR. A Comprehensively Curated Genome-Scale Two-Cell Model for the Heterocystous Cyanobacterium Anabaena sp. PCC 7120. Plant Physiol. 2017;173(1):509–523. doi: 10.1104/pp.16.01487 PubMed DOI PMC

Kanehisa M, Goto S. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000;28(1):27–30. doi: 10.1093/nar/28.1.27 PubMed DOI PMC

Kanehisa M, Furumichi M, Sato Y, Kawashima M, Ishiguro-Watanabe M. KEGG for taxonomy-based analysis of pathways and genomes. Nucleic Acids Res. 2023;51(D1):D587–D592. doi: 10.1093/nar/gkac963 PubMed DOI PMC

Caspi R, Altman T, Billington R, Dreher K, Foerster H, Fulcher CA, et al.. The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of Pathway/Genome Databases. Nucleic Acids Research. 2013;42(D1):D459–D471. doi: 10.1093/nar/gkt1103 PubMed DOI PMC

Moore LR, Caspi R, Campbell DA, Casey JR, Crevecoeur S, Lea-Smith DJ, et al.. CyanoCyc cyanobacterial web portal. Front Microbiol. 2024;15:1340413. doi: 10.3389/fmicb.2024.1340413 PubMed DOI PMC

Steuer R, Junker BH. Computational Models of Metabolism: Stability and Regulation in Metabolic Networks. In: Advances in Chemical Physics, Rice S.A. (Ed.). John Wiley & Sons, Ltd; 2009. p. 105–251.

Orth JD, Thiele I, Palsson BØ. What is flux balance analysis? Nature Biotechnology. 2010;28(3):245–248. doi: 10.1038/nbt.1614 PubMed DOI PMC

Westermark S, Steuer R. Toward Multiscale Models of Cyanobacterial Growth: A Modular Approach. Front Bioeng Biotechnol. 2016;4:95. doi: 10.3389/fbioe.2016.00095 PubMed DOI PMC

Bruggeman FJ, Teusink B, Steuer R. Trade-offs between the instantaneous growth rate and long-term fitness: Consequences for microbial physiology and predictive computational models. Bioessays. 2023;45(10):e2300015. doi: 10.1002/bies.202300015 PubMed DOI

Harcombe WR, Delaney NF, Leiby N, Klitgord N, Marx CJ. The Ability of Flux Balance Analysis to Predict Evolution of Central Metabolism Scales with the Initial Distance to the Optimum. PLOS Computational Biology. 2013;9(6):1–11. doi: 10.1371/journal.pcbi.1003091 PubMed DOI PMC

Maarleveld TR, Wortel MT, Olivier BG, Teusink B, Bruggeman FJ. Interplay between constraints, objectives, and optimality for genome-scale stoichiometric models. PLoS Comput Biol. 2015;11(4):e1004166. doi: 10.1371/journal.pcbi.1004166 PubMed DOI PMC

Broddrick JT, Ware MA, Jallet D, Palsson BO, Peers G. Integration of physiologically relevant photosynthetic energy flows into whole genome models of light-driven metabolism. Plant J. 2022;112(3):603–621. doi: 10.1111/tpj.15965 PubMed DOI PMC

Knoop H, Steuer R. A Computational Analysis of Stoichiometric Constraints and Trade-Offs in Cyanobacterial Biofuel Production. Frontiers in Bioengineering and Biotechnology. 2015;3. doi: 10.3389/fbioe.2015.00047 PubMed DOI PMC

Chen X, Schreiber K, Appel J, Makowka A, Fähnrich B, Roettger M, et al.. The Entner–Doudoroff pathway is an overlooked glycolytic route in cyanobacteria and plants. Proceedings of the National Academy of Sciences. 2016;113(19):5441–5446. doi: 10.1073/pnas.1521916113 PubMed DOI PMC

Kaneko T, Sato S, Kotani H, Tanaka A, Asamizu E, Nakamura Y, et al.. Sequence analysis of the genome of the unicellular cyanobacterium Synechocystis sp. strain PCC6803. II. Sequence determination of the entire genome and assignment of potential protein-coding regions. DNA Res. 1996;3(3):109–136. doi: 10.1093/dnares/3.3.185 PubMed DOI

Lieven C, Beber ME, Olivier BG, Bergmann FT, Ataman M, Babaei P, et al.. MEMOTE for standardized genome-scale metabolic model testing. Nat Biotechnol. 2020;38(3):272–276. doi: 10.1038/s41587-020-0446-y PubMed DOI PMC

Ofaim S, Sulheim S, Almaas E, Sher D, Segrè D. Dynamic Allocation of Carbon Storage and Nutrient-Dependent Exudation in a Revised Genome-Scale Model of Prochlorococcus. Front. Genet. 2021; 12:586293. doi: 10.3389/fgene.2021.586293 PubMed DOI PMC

John Pirt S. The thermodynamic efficiency (quantum demand) and dynamics of photosynthetic growth. New Phytol. 1986;102(1):3–37. doi: 10.1111/j.1469-8137.1986.tb00794.x PubMed DOI

Laws EA. Photosynthetic quotients, new production and net community production in the open ocean. Deep Sea Research Part A Oceanographic Research Papers. 1991;38(1):143–167. doi: 10.1016/0198-0149(91)90059-O DOI

Clark RL, McGinley LL, Purdy HM, Korosh TC, Reed JL, Root TW, et al.. Light-optimized growth of cyanobacterial cultures: Growth phases and productivity of biomass and secreted molecules in light-limited batch growth. Metab Eng. 2018;47:230–242. doi: 10.1016/j.ymben.2018.03.017 PubMed DOI PMC

Steuer R. Fast-growing phototrophic microorganisms and the productivity of phototrophic cultures. Biotechnol Bioeng. 2022;119(8):2261–2267. doi: 10.1002/bit.28123 PubMed DOI

Theune ML, Hildebrandt S, Steffen-Heins A, Bilger W, Gutekunst K, Appel J. In-vivo quantification of electron flow through photosystem I—Cyclic electron transport makes up about 35% in a cyanobacterium. Biochimica et Biophysica Acta (BBA)—Bioenergetics. 2021;1862(3):148353. doi: 10.1016/j.bbabio.2020.148353 PubMed DOI

Eilers PHC, Peeters JCH. A model for the relationship between light intensity and the rate of photosynthesis in phytoplankton. Ecological Modelling. 1988;42(3):199–215. doi: 10.1016/0304-3800(88)90057-9 DOI

Han BP. A Mechanistic Model of Algal Photoinhibition Induced by Photodamage to Photosystem-II. Journal of Theoretical Biology. 2002;214(4):519–527. doi: 10.1006/jtbi.2001.2468 PubMed DOI

Aiba S. Growth kinetics of photosynthetic microorganisms. In: Microbial Reactions. Berlin, Heidelberg: Springer Berlin Heidelberg; 1982. p. 85–156.

Murata N, Nishiyama Y. ATP is a driving force in the repair of photosystem II during photoinhibition. Plant Cell Environ. 2018;41(2):285–299. doi: 10.1111/pce.13108 PubMed DOI

Tyystjärvi E, Mäenpää P, Aro E. Mathematical modelling of photoinhibition and Photosystem II repair cycle. I. Photoinhibition and D1 protein degradation in vitro and in the absence of chloroplast protein synthesis in vivo. Photosynth Res. 1994;41:439–449. doi: 10.1007/BF02183046 PubMed DOI

Tyystjärvi E, Aro EM. The rate constant of photoinhibition, measured in lincomycin-treated leaves, is directly proportional to light intensity. Proc Natl Acad Sci U S A. 1996;93(5):2213–2218. doi: 10.1073/pnas.93.5.2213 PubMed DOI PMC

Melis A. Photosystem-II damage and repair cycle in chloroplasts: what modulates the rate of photodamage in vivo? Trends in Plant Science. 1999;4(4):130–135. doi: 10.1016/S1360-1385(99)01387-4 PubMed DOI

Campbell DA, Tyystjärvi E. Parameterization of photosystem II photoinactivation and repair. Biochimica et Biophysica Acta (BBA)—Bioenergetics. 2012;1817(1):258–265. doi: 10.1016/j.bbabio.2011.04.010 PubMed DOI

Faizi M, Steuer R. Optimal proteome allocation strategies for phototrophic growth in a light-limited chemostat. Microb Cell Fact. 2019;18(1):165. doi: 10.1186/s12934-019-1209-7 PubMed DOI PMC

Young JD, Shastri AA, Stephanopoulos G, Morgan JA. Mapping photoautotrophic metabolism with isotopically nonstationary (13)C flux analysis. Metab Eng. 2011;13(6):656–665. doi: 10.1016/j.ymben.2011.08.002 PubMed DOI PMC

Huege J, Goetze J, Schwarz D, Bauwe H, Hagemann M, Kopka J. Modulation of the major paths of carbon in photorespiratory mutants of Synechocystis. PLoS One. 2011;6(1):e16278. doi: 10.1371/journal.pone.0016278 PubMed DOI PMC

Dinh HV, Sarkar D, Maranas CD. Quantifying the propagation of parametric uncertainty on flux balance analysis. Metab Eng. 2022;69:26–39. doi: 10.1016/j.ymben.2021.10.012 PubMed DOI

van Alphen P, Abedini Najafabadi H, Branco Dos Santos F, Hellingwerf KJ. Increasing the Photoautotrophic Growth Rate of Synechocystis sp. PCC 6803 by Identifying the Limitations of Its Cultivation. Biotechnol J. 2018;13(8):e1700764. doi: 10.1002/biot.201700764 PubMed DOI

Luimstra VM, Schuurmans JM, Verschoor AM, Hellingwerf KJ, Huisman J, Matthijs HCP. Blue light reduces photosynthetic efficiency of cyanobacteria through an imbalance between photosystems I and II. Photosynth Res. 2018;138(2):177–189. doi: 10.1007/s11120-018-0561-5 PubMed DOI PMC

Zavřel T, Sinetova MA, Búzová D, Literáková P, Červený J. Characterization of a model cyanobacterium Synechocystis sp. PCC 6803 autotrophic growth in a flat-panel photobioreactor. Engineering in Life Sciences. 2015;15(1):122–132. doi: 10.1002/elsc.201300165 DOI

Zavřel T, Segečová A, Kovács L, Lukeš M, Novák Z, Szabó M, et al.. A Comprehensive Study of Light Quality Acclimation in Synechocystis Sp. PCC 6803. Plant and Cell Physiology, 2024, pcae062 PubMed PMC

Huisman J, Matthijs HC, Visser PM, Balke H, Sigon CA, Passarge J, et al.. Principles of the light-limited chemostat: theory and ecological applications. Antonie Van Leeuwenhoek. 2002;81(1-4):117–133. doi: 10.1023/A:1020537928216 PubMed DOI

Touloupakis E, Cicchi B, Torzillo G. A bioenergetic assessment of photosynthetic growth of Synechocystis sp. PCC 6803 in continuous cultures. Biotechnol Biofuels. 2015;8:133. doi: 10.1186/s13068-015-0319-7 PubMed DOI PMC

Zavřel T, Knoop H, Steuer R, Jones PR, Červený J, Trtílek M. A quantitative evaluation of ethylene production in the recombinant cyanobacterium Synechocystis sp. PCC 6803 harboring the ethylene-forming enzyme by membrane inlet mass spectrometry. Bioresource Technology. 2016;202:142–151. doi: 10.1016/j.biortech.2015.11.062 PubMed DOI

Lomond JS, Tong AZ. Rapid Analysis of Dissolved Methane, Ethylene, Acetylene and Ethane using Partition Coefficients and Headspace-Gas Chromatography. Journal of Chromatographic Science. 2011;49(6):469–475. doi: 10.1093/chrsci/49.6.469 PubMed DOI

Gu JJ, Hu HC, Chai XS, Tian YX, Barnes DG, Huang S. A new method for the determination of biological oxygen demand in domestic wastewater by headspace gas chromatography. Journal of Chromatography A. 2013;1308:32–36. doi: 10.1016/j.chroma.2013.07.098 PubMed DOI

Wang Y, Chen X, Spengler K, Terberger K, Boehm M, Appel J, et al.. Pyruvate:ferredoxin oxidoreductase and low abundant ferredoxins support aerobic photomixotrophic growth in cyanobacteria. Elife. 2022;11. doi: 10.7554/eLife.71339 PubMed DOI PMC

Yu J, Liberton M, Cliften PF, Head RD, Jacobs JM, Smith RD, et al.. Synechococcus elongatus UTEX 2973, a fast growing cyanobacterial chassis for biosynthesis using light and CO2. Sci Rep. 2015;5:8132. doi: 10.1038/srep08132 PubMed DOI PMC

Jaiswal D, Sengupta A, Sohoni S, Sengupta S, Phadnavis AG, Pakrasi HB, et al.. Genome Features and Biochemical Characteristics of a Robust, Fast Growing and Naturally Transformable Cyanobacterium Synechococcus elongatus PCC 11801 Isolated from India. Sci Rep. 2018;8(1):16632. doi: 10.1038/s41598-018-34872-z PubMed DOI PMC

Włodarczyk A, Selão TT, Norling B, Nixon PJ. Newly discovered Synechococcus sp. PCC 11901 is a robust cyanobacterial strain for high biomass production. Commun Biol. 2020;3(1):215. doi: 10.1038/s42003-020-0910-8 PubMed DOI PMC

Rodrigues JS, Kovács L, Lukeš M, Höper R, Steuer R, Červený J, Lindberg P, Zavřel T. Characterizing isoprene production in cyanobacteria–Insights into the effects of light, temperature, and isoprene on Synechocystis sp. PCC 6803. Bioresour Technol. 2023;380:129068. doi: 10.1016/j.biortech.2023.129068 PubMed DOI

Zavřel T, Segečová A, Kovács L, Lukeš M, Novák Z, Szabó M, et al.. Photo-physiological Acclimation in Synechocystis sp. PCC 6803 Provides Insight into Growth Limitation in Underwater Spectra. bioRxiv. 2023.

Erdrich P, Knoop H, Steuer R, Klamt S. Cyanobacterial biofuels: new insights and strain design strategies revealed by computational modeling. Microb Cell Fact. 2014;13:128. doi: 10.1186/s12934-014-0128-x PubMed DOI PMC

Shabestary K, Hudson EP. Computational metabolic engineering strategies for growth-coupled biofuel production by Synechocystis. Metab Eng Commun. 2016;3:216–226. doi: 10.1016/j.meteno.2016.07.003 PubMed DOI PMC

Kugler A, Stensjö K. Machine learning predicts system-wide metabolic flux control in cyanobacteria. Metab Eng. 2024;82:171–182. doi: 10.1016/j.ymben.2024.02.013 PubMed DOI

Müller S, Regensburger G, Steuer R. Resource allocation in metabolic networks: kinetic optimization and approximations by FBA. Biochemical Society Transactions. 2015;43(6):1195–1200. doi: 10.1042/BST20150156 PubMed DOI

He L, Wu SG, Wan N, Reding AC, Tang YJ. Simulating cyanobacterial phenotypes by integrating flux balance analysis, kinetics, and a light distribution function. Microb Cell Fact. 2015;14:206. doi: 10.1186/s12934-015-0396-0 PubMed DOI PMC

Mori M, Cheng C, Taylor BR, Okano H, Hwa T. Functional decomposition of metabolism allows a system-level quantification of fluxes and protein allocation towards specific metabolic functions. Nat Commun. 2023;14(1):4161. doi: 10.1038/s41467-023-39724-7 PubMed DOI PMC

Leonidou N, Fritze E, Renz A, Dräger A. SBOannotator: a Python tool for the automated assignment of systems biology ontology terms. Bioinformatics. 2023;39(7):btad437. doi: 10.1093/bioinformatics/btad437 PubMed DOI PMC

Bachhar A, Jablonsky J. Entner-Doudoroff pathway in Synechocystis PCC 6803: Proposed regulatory roles and enzyme multifunctionalities. Frontiers in Microbiology. 2022;13. doi: 10.3389/fmicb.2022.967545 PubMed DOI PMC

Ebrahim A, Lerman JA, Palsson BO, Hyduke DR. COBRApy: COnstraints-Based Reconstruction and Analysis for Python. BMC Systems Biology. 2013;7(1):74. doi: 10.1186/1752-0509-7-74 PubMed DOI PMC

Stanier RY, Kunisawa R, Mandel M, Cohen-Bazire G. Purification and properties of unicellular blue-green algae (order Chroococcales). Bacteriological Reviews. 1971;35(2):171–205. doi: 10.1128/br.35.2.171-205.1971 PubMed DOI PMC

Virtanen P, Gommers R, Oliphant TE, Haberland M, Reddy T, Cournapeau D, et al.. SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python. Nature Methods. 2020;17:261–272. doi: 10.1038/s41592-019-0686-2 PubMed DOI PMC

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