Metabolic model guided strain design of cyanobacteria

Current Opinion in Biotechnology - Tập 64 - Trang 17-23 - 2020
John I Hendry1, Anindita Bandyopadhyay2, Shyam Srinivasan1, Himadri B Pakrasi2, Costas D Maranas1
1Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802, United States
2Department of Biology, Washington University, St. Louis, MO 63130, United States

Tài liệu tham khảo

Dismukes, 2008, Aquatic phototrophs: efficient alternatives to land-based crops for biofuels, Curr Opin Biotechnol, 19, 235, 10.1016/j.copbio.2008.05.007 Knoot, 2018, Cyanobacteria: promising biocatalysts for sustainable chemical production, J Biol Chem, 293, 5044, 10.1074/jbc.R117.815886 Yu, 2015, Synechococcus elongatus UTEX 2973, a fast growing cyanobacterial chassis for biosynthesis using light and CO2, Sci Rep, 5 Jaiswal, 2018, Genome features and biochemical characteristics of a robust, fast growing and naturally transformable cyanobacterium Synechococcus elongatus PCC 11801 isolated from India, Sci Rep, 8, 10.1038/s41598-018-34872-z Kim, 2018, A review of dynamic modeling approaches and their application in computational strain optimization for metabolic engineering, Front Microbiol, 9, 10.3389/fmicb.2018.01690 Simeonidis, 2015, Genome-scale modeling for metabolic engineering, J Ind Microbiol Biotechnol, 42, 327, 10.1007/s10295-014-1576-3 O’Brien Edward, 2015, Using genome-scale models to predict biological capabilities, Cell, 161, 971, 10.1016/j.cell.2015.05.019 Lewis, 2012, Constraining the metabolic genotype–phenotype relationship using a phylogeny of in silico methods, Nat Rev Microbiol, 10, 291, 10.1038/nrmicro2737 Orth, 2010, What is flux balance analysis?, Nat Biotechnol, 28, 245, 10.1038/nbt.1614 Maia, 2016, Constraint-based strain optimization methods: the quest for optimal cell factories, Microbiol Mol Biol Rev, 80, 45, 10.1128/MMBR.00014-15 Zomorrodi, 2012, Mathematical optimization applications in metabolic networks, Metab Eng, 14, 672, 10.1016/j.ymben.2012.09.005 Knoop, 2013, Flux balance analysis of cyanobacterial metabolism: the metabolic network of Synechocystis sp. PCC 6803, PLoS Comput Biol, 9, 10.1371/journal.pcbi.1003081 Saha, 2012, Reconstruction and comparison of the metabolic potential of cyanobacteria Cyanothece sp. ATCC 51142 and Synechocystis sp. PCC 6803, PLoS One, 7, 10.1371/journal.pone.0048285 Hendry, 2016, Metabolic model of Synechococcus sp. PCC 7002: prediction of flux distribution and network modification for enhanced biofuel production, Bioresour Technol, 213, 190, 10.1016/j.biortech.2016.02.128 Qian, 2017, Flux balance analysis of photoautotrophic metabolism: uncovering new biological details of subsystems involved in cyanobacterial photosynthesis, Biochim Biophys Acta Bioenerg, 1858, 276, 10.1016/j.bbabio.2016.12.007 Broddrick, 2016, Unique attributes of cyanobacterial metabolism revealed by improved genome-scale metabolic modeling and essential gene analysis, Proc Natl Acad Sci U S A, 113, E8344, 10.1073/pnas.1613446113 Mueller, 2017, Identifying the metabolic differences of a fast-growth phenotype in Synechococcus UTEX 2973, Sci Rep, 7, 10.1038/srep41569 Vu, 2012, Genome-scale modeling of light-driven reductant partitioning and carbon fluxes in diazotrophic unicellular cyanobacterium Cyanothece sp. ATCC 51142, PLoS Comput Biol, 8, 10.1371/journal.pcbi.1002460 Anfelt, 2015, Genetic and nutrient modulation of acetyl-CoA levels in Synechocystis for n-butanol production, Microb Cell Fact, 14, 167, 10.1186/s12934-015-0355-9 Yoshikawa, 2017, Metabolic engineering of Synechocystis sp. PCC 6803 for enhanced ethanol production based on flux balance analysis, Bioprocess Biosyst Eng, 40, 791, 10.1007/s00449-017-1744-8 Hirokawa, 2017, Metabolic engineering of Synechococcus elongatus PCC 7942 for improvement of 1,3-propanediol and glycerol production based on in silico simulation of metabolic flux distribution, Microb Cell Fact, 16, 212, 10.1186/s12934-017-0824-4 Lin, 2017, Metabolic engineering of the pentose phosphate pathway for enhanced limonene production in the cyanobacterium Synechocystis sp. PCC 6803, Sci Rep, 7, 10.1038/s41598-017-17831-y Englund, 2018, Systematic overexpression study to find target enzymes enhancing production of terpenes in Synechocystis PCC 6803, using isoprene as a model compound, Metab Eng, 49, 164, 10.1016/j.ymben.2018.07.004 Segrè, 2002, Analysis of optimality in natural and perturbed metabolic networks, Proc Natl Acad Sci U S A, 99, 15112, 10.1073/pnas.232349399 Yoshikawa, 2011, Reconstruction and verification of a genome-scale metabolic model for Synechocystis sp. PCC6803, Appl Microbiol Biotechnol, 92, 347, 10.1007/s00253-011-3559-x Burgard, 2003, Optknock: a bilevel programming framework for identifying gene knockout strategies for microbial strain optimization, Biotechnol Bioeng, 84, 647, 10.1002/bit.10803 Tepper, 2009, Predicting metabolic engineering knockout strategies for chemical production: accounting for competing pathways, Bioinformatics, 26, 536, 10.1093/bioinformatics/btp704 Patil, 2005, Evolutionary programming as a platform for in silico metabolic engineering, BMC Bioinformatics, 6, 308, 10.1186/1471-2105-6-308 Kim, 2011, Large-scale bi-level strain design approaches and mixed-integer programming solution techniques, PLoS One, 6 Fowler, 2009, Increased malonyl coenzyme A biosynthesis by tuning the Escherichia coli metabolic network and its application to flavanone production, Appl Environ Microbiol, 75, 5831, 10.1128/AEM.00270-09 Yim, 2011, Metabolic engineering of Escherichia coli for direct production of 1,4-butanediol, Nat Chem Biol, 7, 445, 10.1038/nchembio.580 Ng, 2012, Production of 2,3-butanediol in Saccharomyces cerevisiae by in silico aided metabolic engineering, Microb Cell Fact, 11, 68, 10.1186/1475-2859-11-68 Brochado, 2010, Improved vanillin production in baker’s yeast through in silico design, Microb Cell Fact, 9, 84, 10.1186/1475-2859-9-84 Otero, 2013, Industrial systems biology of Saccharomyces cerevisiae enables novel succinic acid cell factory, PLoS One, 8, 10.1371/journal.pone.0054144 Mahadevan, 2003, The effects of alternate optimal solutions in constraint-based genome-scale metabolic models, Metab Eng, 5, 264, 10.1016/j.ymben.2003.09.002 Shabestary, 2016, Computational metabolic engineering strategies for growth-coupled biofuel production by Synechocystis, Metab Eng Commun, 3, 216, 10.1016/j.meteno.2016.07.003 Ranganathan, 2010, OptForce: an optimization procedure for identifying all genetic manipulations leading to targeted overproductions, PLoS Comput Biol, 6, 10.1371/journal.pcbi.1000744 Xu, 2011, Genome-scale metabolic network modeling results in minimal interventions that cooperatively force carbon flux towards malonyl-CoA, Metab Eng, 13, 578, 10.1016/j.ymben.2011.06.008 Ranganathan, 2012, An integrated computational and experimental study for overproducing fatty acids in Escherichia coli, Metab Eng, 14, 687, 10.1016/j.ymben.2012.08.008 Pharkya, 2006, An optimization framework for identifying reaction activation/inhibition or elimination candidates for overproduction in microbial systems, Metab Eng, 8, 1, 10.1016/j.ymben.2005.08.003 Lun, 2009, Large-scale identification of genetic design strategies using local search, Mol Syst Biol, 5, 296, 10.1038/msb.2009.57 Choi, 2010, In silico identification of gene amplification targets for improvement of lycopene production, Appl Environ Microbiol, 76, 3097, 10.1128/AEM.00115-10 Kim, 2010, OptORF: optimal metabolic and regulatory perturbations for metabolic engineering of microbial strains, BMC Syst Biol, 4, 53, 10.1186/1752-0509-4-53 Yang, 2011, EMILiO: a fast algorithm for genome-scale strain design, Metab Eng, 13, 272, 10.1016/j.ymben.2011.03.002 Saa, 2017, Formulation, construction and analysis of kinetic models of metabolism: a review of modelling frameworks, Biotechnol Adv, 35, 981, 10.1016/j.biotechadv.2017.09.005 Srinivasan, 2015, Constructing kinetic models of metabolism at genome-scales: a review, Biotechnol J, 10, 1345, 10.1002/biot.201400522 Fell, 1992, Metabolic control analysis: a survey of its theoretical and experimental development, Biochem J, 286, 313, 10.1042/bj2860313 Jablonsky, 2016, Different strategies of metabolic regulation in cyanobacteria: from transcriptional to biochemical control, Sci Rep, 6, 10.1038/srep33024 Janasch, 2019, Kinetic modeling of the Calvin cycle identifies flux control and stable metabolomes in Synechocystis carbon fixation, J Exp Bot, 70, 973 Jablonsky, 2013, Phosphoglycerate mutases function as reverse regulated isoenzymes in Synechococcus elongatus PCC 7942, PLoS One, 8, 10.1371/journal.pone.0058281 Wang, 2016, Enhanced limonene production in cyanobacteria reveals photosynthesis limitations, Proc Natl Acad Sci U S A, 113, 14225, 10.1073/pnas.1613340113 Nishiguchi, 2019, Transomics data-driven, ensemble kinetic modeling for system-level understanding and engineering of the cyanobacteria central metabolism, Metab Eng, 52, 273, 10.1016/j.ymben.2019.01.004 Xin, 2015, The benefits of photorespiratory bypasses: how can they work?, Plant Physiol, 167, 574, 10.1104/pp.114.248013 Tran, 2008, Ensemble modeling of metabolic networks, Biophys J, 95, 5606, 10.1529/biophysj.108.135442 Behler, 2018, CRISPR-based technologies for metabolic engineering in cyanobacteria, Trends Biotechnol, 36, 996, 10.1016/j.tibtech.2018.05.011 Sengupta, 2018, Recent advances in synthetic biology of cyanobacteria, Appl Microbiol Biotechnol, 102, 5457, 10.1007/s00253-018-9046-x Gopalakrishnan, 2018, Elucidation of photoautotrophic carbon flux topology in Synechocystis PCC 6803 using genome-scale carbon mapping models, Metab Eng, 47, 190, 10.1016/j.ymben.2018.03.008 Xiong, 2015, The plasticity of cyanobacterial metabolism supports direct CO2 conversion to ethylene, Nat Plants, 1, 15053, 10.1038/nplants.2015.53 Young, 2011, Mapping photoautotrophic metabolism with isotopically nonstationary 13C flux analysis, Metab Eng, 13, 656, 10.1016/j.ymben.2011.08.002 Abernathy, 2017, Deciphering cyanobacterial phenotypes for fast photoautotrophic growth via isotopically nonstationary metabolic flux analysis, Biotechnol Biofuels, 10, 273, 10.1186/s13068-017-0958-y Jazmin, 2017, Isotopically nonstationary 13C flux analysis of cyanobacterial isobutyraldehyde production, Metab Eng, 42, 9, 10.1016/j.ymben.2017.05.001 Hendry, 2017, Rerouting of carbon flux in a glycogen mutant of cyanobacteria assessed via isotopically non-stationary 13C metabolic flux analysis, Biotechnol Bioeng, 114, 2298, 10.1002/bit.26350 Hendry, 2019, Genome-scale fluxome of Synechococcus elongatus UTEX 2973 using transient 13C-labeling data, Plant Physiol, 179, 761, 10.1104/pp.18.01357 Battchikova, 2018, Proteomics of cyanobacteria: current horizons, Curr Opin Biotechnol, 54, 65, 10.1016/j.copbio.2018.02.012 Schwarz, 2013, Recent applications of metabolomics toward cyanobacteria, Metabolites, 3, 72, 10.3390/metabo3010072 Meissner, 2015, Metabolomic analysis indicates a pivotal role of the hepatotoxin microcystin in high light adaptation of Microcystis, Environ Microbiol, 17, 1497, 10.1111/1462-2920.12565 Han, 2015, Comparative metabolomic analysis of the effects of light quality on polysaccharide production of cyanobacterium Nostoc flagelliforme, Algal Res, 9, 143, 10.1016/j.algal.2015.02.019