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Challenges in the Application of Synthetic Biology Toward Synthesis of Commodity Products by Cyanobacteria via “Direct Conversion”

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Synthetic Biology of Cyanobacteria

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 1080))

Abstract

Cyanobacterial direct conversion of CO2 to several commodity chemicals has been recognized as a potential contributor to support the much-needed sustainable development of human societies. However, the feasibility of this “green conversion” hinders on our ability to overcome the hurdles presented by the natural evolvability of microbes. The latter may result in the genetic instability of engineered cyanobacterial strains leading to impaired productivity. This challenge is general to any “cell factory” approach in which the cells grow for multiple generations, and based on several studies carried out in different microbial hosts, we could identify that three distinct strategies have been proposed to tackle it. These are (1) to reduce microbial evolvability by decreasing the native mutation rate, (2) to align product formation with cell growth/fitness, and, paradoxically, (3) to efficiently reallocate cellular resources to product formation by uncoupling it from growth. The implementation of either of these strategies requires an advanced synthetic biology toolkit. Here, we review the existing methods available for cyanobacteria and identify areas of focus in which specific developments are still needed. Furthermore, we discuss how potentially stabilizing strategies may be used in combination leading to further increases of productivity while ensuring the stability of the cyanobacterial-based direct conversion process.

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References

  1. Ragauskas AJ et al (2006) The path forward for biofuels and biomaterials. Science 311:484–489

    Article  PubMed  CAS  Google Scholar 

  2. Miyamoto K (1997) Renewable biological systems for alternative sustainable energy production. Food & Agriculture Organisation, Rome

    Google Scholar 

  3. Naik SN, Goud VV, Rout PK, Dalai AK (2010) Production of first and second generation biofuels: a comprehensive review. Renew Sustain Energ Rev 14:578–597

    Article  CAS  Google Scholar 

  4. Savakis P, Hellingwerf KJ (2015) Engineering cyanobacteria for direct biofuel production from CO2. Curr Opin Biotechnol 33:8–14

    Article  PubMed  CAS  Google Scholar 

  5. Heidorn T et al (2011) Synthetic biology in cyanobacteria: engineering and analyzing novel functions. Methods Enzymol 497:539–579

    Article  PubMed  CAS  Google Scholar 

  6. Chen Q, Montesarchio D, Hellingwerf KJ (2016) Adv Bot Res 79:43–62

    Article  Google Scholar 

  7. Hellingwerf KJ, Teixeira de Mattos MJ (2009) Alternative routes to biofuels: light-driven biofuel formation from CO2 and water based on the ‘photanol’ approach. J Biotechnol 142:87–90

    Article  PubMed  CAS  Google Scholar 

  8. Angermayr SA, Gorchs Rovira A, Hellingwerf KJ (2015) Metabolic engineering of cyanobacteria for the synthesis of commodity products. Trends Biotechnol 33:352–361

    Article  PubMed  CAS  Google Scholar 

  9. Wijffels RH, Kruse O, Hellingwerf KJ (2013) Potential of industrial biotechnology with cyanobacteria and eukaryotic microalgae. Curr Opin Biotechnol 24:405–413

    Article  PubMed  CAS  Google Scholar 

  10. Nielsen J, Keasling JD (2016) Engineering cellular metabolism. Cell 164:1185–1197

    Article  PubMed  CAS  Google Scholar 

  11. Cooney CL (1983) In: Foundations of biochemical engineering, vol 207. American Chemical Society, pp 179–198–8

    Google Scholar 

  12. Jones PR (2014) Genetic instability in cyanobacteria – an elephant in the room? Synth Biol 2:12

    Google Scholar 

  13. Cassier-Chauvat C, Veaudor T, Chauvat F (2016) Comparative genomics of DNA recombination and repair in cyanobacteria: biotechnological implications. Front Microbiol 7:1–13

    Article  Google Scholar 

  14. Kusakabe T et al (2013) Engineering a synthetic pathway in cyanobacteria for isopropanol production directly from carbon dioxide and light. Metab Eng 20:101–108

    Article  PubMed  CAS  Google Scholar 

  15. Jacobsen JH, Frigaard NU (2014) Engineering of photosynthetic mannitol biosynthesis from CO2 in a cyanobacterium. Metab Eng 21:60–70

    Article  PubMed  CAS  Google Scholar 

  16. Ungerer J et al (2012) Sustained photosynthetic conversion of CO2 to ethylene in recombinant cyanobacterium Synechocystis 6803. Energy Environ Sci 5:8998

    Article  CAS  Google Scholar 

  17. Du W et al (2017) Nonhierarchical flux regulation exposes the fitness burden associated with lactate production in Synechocystis sp. PCC6803. ACS Synth Biol 6:395–401

    Article  PubMed  CAS  Google Scholar 

  18. Wiser MJ, Lenski RE (2015) A comparison of methods to measure fitness in Escherichia coli. PLoS One 10:e0126210

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  19. de Jong H, Geiselmann J, Ropers D (2017) Resource reallocation in bacteria by reengineering the gene expression machinery. Trends Microbiol 25:480–493

    Article  PubMed  CAS  Google Scholar 

  20. Zhuang K, Vemuri GN, Mahadevan R (2014) Economics of membrane occupancy and respiro-fermentation. Mol Syst Biol 7:500–500

    Article  Google Scholar 

  21. Vickers CE, Bongers M, Liu Q, Delatte T, Bouwmeester H (2014) Metabolic engineering of volatile isoprenoids in plants and microbes. Plant Cell Environ 37:1753–1775

    Article  PubMed  CAS  Google Scholar 

  22. Nicolaou SA, Gaida SM, Papoutsakis ET (2010) A comparative view of metabolite and substrate stress and tolerance in microbial bioprocessing: from biofuels and chemicals, to biocatalysis and bioremediation. Metab Eng 12:307–331

    Article  PubMed  CAS  Google Scholar 

  23. Angermayr SA, Hellingwerf KJ (2013) On the use of metabolic control analysis in the optimization of cyanobacterial biosolar cell factories. J Phys Chem B. https://doi.org/10.1021/jp4013152

  24. Renda BA, Hammerling MJ, Barrick JE (2014) Engineering reduced evolutionary potential for synthetic biology. Mol BioSyst 10:1668–1678

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  25. Beneyton T, Coldren F, Baret J-C, Griffiths AD, Taly V (2014) CotA laccase: high-throughput manipulation and analysis of recombinant enzyme libraries expressed in E. coli using droplet-based microfluidics. Analyst 139:3314–3323

    Article  PubMed  CAS  Google Scholar 

  26. Guo HH, Choe J, Loeb LA (2004) Protein tolerance to random amino acid change. Proc Natl Acad Sci U S A 101:9205–9210

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  27. Watt VM, Ingles CJ, Urdea MS, Rutter WJ (1985) Homology requirements for recombination in Escherichia coli. Proc Natl Acad Sci U S A 82:4768–4772

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. Moxon R, Bayliss C, Hood D (2006) Bacterial contingency loci: the role of simple sequence DNA repeats in bacterial adaptation. Annu Rev Genet 40:307–333

    Article  PubMed  CAS  Google Scholar 

  29. Mirkin EV, Mirkin SM (2007) Replication fork stalling at natural impediments. Microbiol Mol Biol Rev 71:13–35

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  30. Kazazian HH (2004) Mobile elements: drivers of genome evolution. Science 303:1626–1632

    Article  PubMed  CAS  Google Scholar 

  31. Blattner FR et al (1997) The complete genome sequence of Escherichia coli K-12. Science (80-) 277:719–720

    Article  Google Scholar 

  32. Grabherr R, Nilsson E, Striedner G, Bayer K (2002) Stabilizing plasmid copy number to improve recombinant protein production. Biotechnol Bioeng 77:142–147

    Article  PubMed  CAS  Google Scholar 

  33. Galhardo RS, Hastings PJ, Rosenberg SM (2007) Mutation as a stress response and the regulation of evolvability. Crit Rev Biochem Mol Biol 42:399–435

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  34. Holliday R, Grigg GW (1993) DNA methylation and mutation. Mutat Res Fundam Mol Mech Mutagen 285:61–67

    Article  CAS  Google Scholar 

  35. Lee H, Popodi E, Tang H, Foster PL (2012) Rate and molecular spectrum of spontaneous mutations in the bacterium Escherichia coli as determined by whole-genome sequencing. Proc Natl Acad Sci U S A 109:E2774–E2783

    Article  PubMed  PubMed Central  Google Scholar 

  36. Darmon E, Leach DRF (2014) Bacterial genome instability. Microbiol Mol Biol Rev 78:1–39

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  37. Bryson V, Szybalski W (1952) Microbial selection. Science (80-)116:45 LP–51

    Google Scholar 

  38. Du W et al (2016) Photonfluxostat: a method for light-limited batch cultivation of cyanobacteria at different, yet constant, growth rates. Algal Res 20:118–125

    Article  Google Scholar 

  39. Tsoularis A, Wallace J (2002) Analysis of logistic growth models. Math Biosci 179:21–55

    Article  PubMed  CAS  Google Scholar 

  40. Vapnek D, Alton NK, Bassett CL, Kushner SR (1976) Amplification in Escherichia coli of enzymes involved in genetic recombination: construction of hybrid ColE1 plasmids carrying the structural gene for exonuclease I. Proc Natl Acad Sci U S A 73:3492–3496

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  41. Pósfai G et al (2006) Emergent properties of reduced-genome Escherichia coli. Science 312:1044–1046

    Article  PubMed  CAS  Google Scholar 

  42. Umenhoffer K et al (2010) Reduced evolvability of Escherichia coli MDS42, an IS-less cellular chassis for molecular and synthetic biology applications. Microb Cell Factories 9:38

    Article  CAS  Google Scholar 

  43. Csorgo B, Feher T, Timar E, Blattner FR, Posfai G (2012) Low-mutation-rate, reduced-genome Escherichia coli: an improved host for faithful maintenance of engineered genetic constructs. Microb Cell Factories 11:11

    Article  CAS  Google Scholar 

  44. Jack BR et al (2015) Predicting the genetic stability of engineered DNA sequences with the EFM calculator. ACS Synth Biol 4:939–943

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  45. Marinus MG, Løbner-Olesen A (2014) DNA methylation. EcoSal Plus 6. https://doi.org/10.1128/ecosalplus.ESP-0003-2013

  46. Du W et al (2018) Alignment of microbial fitness with engineered product formation: obligatory coupling between acetate production and photoautotrophic growth. Biotechnol Biofuels 11:38

    Google Scholar 

  47. Westerhoff HV, Lolkema JS, Otto R, Hellingwerf KJ (1982) Thermodynamics of growth non-equilibrium thermodynamics of bacterial growth the phenomenological and the mosaic approach. BBA Rev Bioenerg 683:181–220

    CAS  Google Scholar 

  48. Martin VJJ, Pitera DJ, Withers ST, Newman JD, Keasling JD (2003) Engineering a mevalonate pathway in Escherichia coli for production of terpenoids. Nat Biotechnol 21:796–802

    Article  PubMed  CAS  Google Scholar 

  49. Yim H et al (2011) Metabolic engineering of Escherichia coli for direct production of 1,4-butanediol. Nat Chem Biol 7:445–452

    Article  PubMed  CAS  Google Scholar 

  50. Theodosiou, E. (2017), et al. An artificial TCA cycle selects for efficient α-ketoglutarate dependent hydroxylase catalysis in engineered Escherichia coli. Biotechnol Bioeng. n/a–n/a. https://doi.org/10.1002/bit.26281

  51. Orth JD, Thiele I, Palsson BØ (2010) What is flux balance analysis? Nat Biotechnol 28:245–248

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  52. Mahadevan R, Schilling CH (2003) The effects of alternate optimal solutions in constraint-based genome-scale metabolic models. Metab Eng 5:264–276

    Article  PubMed  CAS  Google Scholar 

  53. Klamt S, Mahadevan R (2015) On the feasibility of growth-coupled product synthesis in microbial strains. Metab Eng 30:166–178

    Article  PubMed  CAS  Google Scholar 

  54. King ZA, O’Brien EJ, Feist AM, Palsson BO (2017) Literature mining supports a next-generation modeling approach to predict cellular byproduct secretion. Metab Eng 39:220–227

    Article  PubMed  CAS  Google Scholar 

  55. Burgard AP, Pharkya P, Maranas CD (2003) OptKnock: a bilevel programming framework for identifying gene knockout strategies for microbial strain optimization. Biotechnol Bioeng 84:647–657

    Article  PubMed  CAS  Google Scholar 

  56. Patil KR, Rocha I, Forster J, Nielsen J (2005) Evolutionary programming as a platform for in silico metabolic engineering. BMC Bioinforma 6:308

    Article  CAS  Google Scholar 

  57. Rocha I et al (2010) OptFlux: an open-source software platform for in silico metabolic engineering. BMC Syst Biol 4:45

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  58. Ohno S, Shimizu H, Furusawa C (2014) FastPros: screening of reaction knockout strategies for metabolic engineering. Bioinformatics 30:981–987

    Article  PubMed  CAS  Google Scholar 

  59. Nogales J, Gudmundsson S, Knight EM, Palsson BO, Thiele I (2012) Detailing the optimality of photosynthesis in cyanobacteria through systems biology analysis. Proc Natl Acad Sci 109:2678–2683

    Article  PubMed  PubMed Central  Google Scholar 

  60. Maarleveld TR, Boele J, Bruggeman FJ, Teusink B (2014) A data integration and visualization resource for the metabolic network of Synechocystis sp. PCC 6803. Plant Physiol 164:1111–1121

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  61. Branco dos Santos F, 2017 iGEM team Amsterdam (2017) Wiki page of 2017. iGEM team Amsterdam

    Google Scholar 

  62. Neijssel OM, Tempest DW (1975) The regulation of carbohydrate metabolism in Klebsiella aerogenes NCTC 418 organisms, growing in chemostat culture. Arch Microbiol 106:251–258

    Article  PubMed  CAS  Google Scholar 

  63. Purnick PEM, Weiss R (2009) The second wave of synthetic biology: from modules to systems. Nat Rev Mol Cell Biol 10:410–422

    Article  PubMed  CAS  Google Scholar 

  64. Shen-Orr SS, Milo R, Mangan S, Alon U (2002) Network motifs in the transcriptional regulation network of Escherichia coli. Nat Genet 31:64–68

    Article  PubMed  CAS  Google Scholar 

  65. Wendt KE, Ungerer J, Cobb RE, Zhao H, Pakrasi HB (2016) CRISPR/Cas9 mediated targeted mutagenesis of the fast growing cyanobacterium Synechococcus elongatus UTEX 2973. Microb Cell Factories 15:115

    Article  CAS  Google Scholar 

  66. Abe K et al (2014) Engineering of a green-light inducible gene expression system in Synechocystis sp. PCC6803. Microb Biotechnol 7:177–183

    Article  PubMed  CAS  Google Scholar 

  67. Miyake K et al (2014) A green-light inducible lytic system for cyanobacterial cells. Biotechnol Biofuels 7:56

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  68. Albers SC, Peebles CAM (2017) Evaluating light-induced promoters for the control of heterologous gene expression in Synechocystis sp. PCC 6803. Biotechnol Prog 33:45–53

    Article  PubMed  CAS  Google Scholar 

  69. Camsund D, Heidorn T, Lindblad P (2014) Design and analysis of LacI-repressed promoters and DNA-looping in a cyanobacterium. J Biol Eng 8:4

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  70. Zess EK, Begemann MB, Pfleger BF (2016) Construction of new synthetic biology tools for the control of gene expression in the cyanobacterium Synechococcus sp. strain PCC 7002. Biotechnol Bioeng 113:424–432

    Article  PubMed  CAS  Google Scholar 

  71. Englund E, Liang F, Lindberg P (2016) Evaluation of promoters and ribosome binding sites for biotechnological applications in the unicellular cyanobacterium Synechocystis sp. PCC 6803. Sci Rep 6:36640

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  72. Dühring U, Baier K, Germer F, Shi T (2017) Genetically enhanced cyanobacteria for the production of a first chemical compound harbouring Zn2+, Co2+ or Ni2+ -inducible promoters. At https://www.google.nl/patents/US9551014

  73. Blasi B, Peca L, Vass I, Kós PB (2012) Characterization of stress responses of heavy metal and metalloid inducible promoters in synechocystis PCC6803. J Microbiol Biotechnol 22:166–169

    Article  PubMed  CAS  Google Scholar 

  74. Cheah YE, Albers SC, Peebles CAM (2013) A novel counter-selection method for markerless genetic modification in Synechocystis sp. PCC 6803. Biotechnol Prog 29:23–30

    Article  PubMed  CAS  Google Scholar 

  75. Liu X, Curtiss R (2009) Nickel-inducible lysis system in Synechocystis sp. PCC 6803. Proc Natl Acad Sci U S A 106:21550–21554

    Article  PubMed  PubMed Central  Google Scholar 

  76. Lin X et al (2004) Development of a tightly regulated U6 promoter for shRNA expression. FEBS Lett 577:376–380

    Article  PubMed  CAS  Google Scholar 

  77. Blazeck J, Alper HS (2013) Promoter engineering: recent advances in controlling transcription at the most fundamental level. Biotechnol J 8:46–58

    Article  PubMed  CAS  Google Scholar 

  78. Nevoigt E et al (2007) Engineering promoter regulation. Biotechnol Bioeng 96:550–558

    Article  PubMed  CAS  Google Scholar 

  79. Bulter T et al (2004) Design of artificial cell-cell communication using gene and metabolic networks. Proc Natl Acad Sci 101:2299–2304

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  80. Brockman IM, Prather KLJ (2015) Dynamic metabolic engineering: new strategies for developing responsive cell factories. Biotechnol J 10:1360–1369

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  81. Dahl RH et al (2013) Engineering dynamic pathway regulation using stress-response promoters. Nat Biotechnol 31:1039–1046

    Article  PubMed  CAS  Google Scholar 

  82. Zhang F, Carothers JM, Keasling JD (2012) Design of a dynamic sensor-regulator system for production of chemicals and fuels derived from fatty acids. Nat Biotechnol 30:354–359

    Article  PubMed  CAS  Google Scholar 

  83. Skjoedt ML et al (2016) Engineering prokaryotic transcriptional activators as metabolite biosensors in yeast. Nat Chem Biol 12:951–958

    Article  PubMed  CAS  Google Scholar 

  84. Bothfeld W, Kapov G, Tyo KEJ (2017) A glucose-sensing toggle switch for autonomous, high productivity genetic control. ACS Synth Biol. https://doi.org/10.1021/acssynbio.6b00257

  85. Peng B, Plan MR, Carpenter A, Nielsen LK, Vickers CE (2017) Coupling gene regulatory patterns to bioprocess conditions to optimize synthetic metabolic modules for improved sesquiterpene production in yeast. Biotechnol Biofuels 10:43

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  86. Tsao C-Y, Hooshangi S, Wu H-C, Valdes JJ, Bentley WE (2010) Autonomous induction of recombinant proteins by minimally rewiring native quorum sensing regulon of E. coli. Metab Eng 12:291–297

    Article  PubMed  CAS  Google Scholar 

  87. Younger AKD, Dalvie NC, Rottinghaus AG, Leonard JN (2016) Engineering modular biosensors to confer metabolite-responsive regulation of transcription. ACS Synth Biol. acssynbio.6b00184. https://doi.org/10.1021/acssynbio.6b00184

  88. Liu D, Evans T, Zhang F (2015) Applications and advances of metabolite biosensors for metabolic engineering. Metab Eng 31:35–43

    Article  PubMed  CAS  Google Scholar 

  89. Xiong D et al (2017) Improving key enzyme activity in phenylpropanoid pathway with a designed biosensor. Metab Eng 40:115–123

    Article  PubMed  CAS  Google Scholar 

  90. Feng J et al (2015) A general strategy to construct small molecule biosensors in eukaryotes. Elife 4:e10606

    Article  PubMed  PubMed Central  Google Scholar 

  91. Immethun CM et al (2016) Oxygen-responsive genetic circuits constructed in Synechocystis sp. PCC 6803. Biotechnol Bioeng 113:433–442

    Article  PubMed  CAS  Google Scholar 

  92. Immethun CM et al (2017) Physical, chemical, and metabolic state sensors expand the synthetic biology toolbox for Synechocystis sp. PCC 6803. Biotechnol Bioeng 114:1561–1569

    Article  PubMed  CAS  Google Scholar 

  93. Izard J et al (2015) A synthetic growth switch based on controlled expression of RNA polymerase. Mol Syst Biol 11:840

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  94. Venturelli OS et al (2017) Programming mRNA decay to modulate synthetic circuit resource allocation. Nat Commun 8:15128

    Article  PubMed  PubMed Central  Google Scholar 

  95. Harder B-J, Bettenbrock K, Klamt S (2017) Temperature-dependent dynamic control of the TCA cycle increases volumetric productivity of itaconic acid production by Escherichia coli. Biotechnol Bioeng 1–9. https://doi.org/10.1002/bit.26446

  96. Berla BM, Pakrasi HB (2012) Upregulation of plasmid genes during stationary phase in Synechocystis sp. strain PCC 6803, a cyanobacterium. Appl Environ Microbiol 78:5448–5451

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  97. Kopf M et al (2014) Comparative analysis of the primary transcriptome of Synechocystis sp. PCC 6803. DNA Res 21:527–539

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  98. Ramey CJ, Barón-Sola Á, Aucoin HR, Boyle NR (2015) Genome engineering in cyanobacteria: where we are and where we need to go. ACS Synth Biol 4:1186–1196

    Article  PubMed  CAS  Google Scholar 

  99. Aikens J, Turner RJ (2013) Transgenic photosynthetic microorganisms and photobioreactor. At https://www.google.ch/patents/US8367379

  100. Zerulla K, Ludt K, Soppa J (2016) The ploidy level of synechocystis sp. PCC 6803 is highly variable and is influenced by growth phase and by chemical and physical external parameters. Microbiol (United Kingdom) 162:730–739

    CAS  Google Scholar 

  101. Li H et al (2016) CRISPR-Cas9 for the genome engineering of cyanobacteria and succinate production. Metab Eng 38:293–302

    Article  PubMed  CAS  Google Scholar 

  102. Ungerer J, Pakrasi HB (2016) Cpf1 is a versatile tool for CRISPR genome editing across diverse species of cyanobacteria. Sci Rep 6:39681

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  103. Zerulla K, Soppa J (2014) Polyploidy in haloarchaea: advantages for growth and survival. Front Microbiol 5:274

    Article  PubMed  PubMed Central  Google Scholar 

  104. Soppa J (2013) Evolutionary advantages of polyploidy in halophilic archaea. Biochem Soc Trans 41:339–343

    Article  PubMed  CAS  Google Scholar 

  105. Zavřel T, Sinetova MA, Búzová D, Literáková P, Červený J (2015) Characterization of a model cyanobacterium Synechocystis sp: PCC 6803 autotrophic growth in a flat-panel photobioreactor. Eng Life Sci 15:122–132

    Article  CAS  Google Scholar 

  106. Bernstein HC et al (2016) Unlocking the constraints of cyanobacterial productivity: acclimations enabling ultrafast growth. MBio 7:e00949–e00916

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  107. Yu J et al (2015) Synechococcus elongatus UTEX 2973, a fast growing cyanobacterial chassis for biosynthesis using light and CO2. Sci Rep 5:8132

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  108. Mueller TJ, Ungerer JL, Pakrasi HB, Maranas CD (2017) Identifying the metabolic differences of a fast-growth phenotype in Synechococcus UTEX 2973. Sci Rep 7:41569

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  109. Richter F et al (2015) Upgrading a microplate reader for photobiology and all-optical experiments. Photochem Photobiol Sci 14:270–279

    Article  PubMed  CAS  Google Scholar 

  110. Tillich UM et al (2014) High-throughput cultivation and screening platform for unicellular phototrophs. BMC Microbiol 14:239

    Article  PubMed  PubMed Central  Google Scholar 

  111. Hammar P et al (2015) Single-cell screening of photosynthetic growth and lactate production by cyanobacteria. Biotechnol Biofuels 8:193

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  112. Abalde-Cela S et al (2015) High-throughput detection of ethanol-producing cyanobacteria in a microdroplet platform. J R Soc Interf 12:20150216

    Article  CAS  Google Scholar 

  113. Angermayr SA, Paszota M, Hellingwerf KJ (2012) Engineering a cyanobacterial cell factory for production of lactic acid. Appl Environ Microbiol 78:7098–7106

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  114. Takahama K, Matsuoka M, Nagahama K, Ogawa T (2003) Construction and analysis of a recombinant cyanobacterium expressing a chromosomally inserted gene for an ethylene-forming enzyme at the psbAI locus. J Biosci Bioeng 95:302–305

    Article  PubMed  CAS  Google Scholar 

  115. Schulze K, Lang I, Enke H, Grohme D, Frohme M (2015) The use of fluorescence microscopy and image analysis for rapid detection of non-producing revertant cells of Synechocystis sp. PCC6803 and Synechococcus sp. PCC7002. BMC Res Notes 8:160

    Article  PubMed  PubMed Central  CAS  Google Scholar 

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Authors and Affiliations

  1. Molecular Microbial Physiology Group, Swammerdam Institute for Life Sciences, Faculty of Sciences, University of Amsterdam, Amsterdam, The Netherlands

    Wei Du, Patricia Caicedo Burbano, Klaas J. Hellingwerf & Filipe Branco dos Santos

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  1. Wei Du
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  2. Patricia Caicedo Burbano
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  3. Klaas J. Hellingwerf
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  4. Filipe Branco dos Santos
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Correspondence to Filipe Branco dos Santos .

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  1. School of Chemical Engineering, Tianjin University, Tianjin, China

    Weiwen Zhang

  2. Center for Biosafety Research and Strategy, Tianjin University, Tianjin, China

    Xinyu Song

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Du, W., Burbano, P.C., Hellingwerf, K.J., Branco dos Santos, F. (2018). Challenges in the Application of Synthetic Biology Toward Synthesis of Commodity Products by Cyanobacteria via “Direct Conversion”. In: Zhang, W., Song, X. (eds) Synthetic Biology of Cyanobacteria. Advances in Experimental Medicine and Biology, vol 1080. Springer, Singapore. https://doi.org/10.1007/978-981-13-0854-3_1

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