Mostrar el registro sencillo del ítem
dc.contributor.author | Triana, Julian | es_ES |
dc.contributor.author | Montagud, Arnau | es_ES |
dc.contributor.author | Siurana, Maria | es_ES |
dc.contributor.author | Fuente, David | es_ES |
dc.contributor.author | Urchueguia, Arantxa | es_ES |
dc.contributor.author | Gamermann, Daniel | es_ES |
dc.contributor.author | Torres, Javier | es_ES |
dc.contributor.author | TENA, JOSÉ | es_ES |
dc.contributor.author | Fernández de Córdoba, Pedro | es_ES |
dc.contributor.author | Urchueguía Schölzel, Javier Fermín | es_ES |
dc.date.accessioned | 2020-10-04T03:31:59Z | |
dc.date.available | 2020-10-04T03:31:59Z | |
dc.date.issued | 2014-08-20 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/151045 | |
dc.description.abstract | [EN] The reconstruction of genome-scale metabolic models and their applications represent a great advantage of systems biology. Through their use as metabolic flux simulation models, production of industrially-interesting metabolites can be predicted. Due to the growing number of studies of metabolic models driven by the increasing genomic sequencing projects, it is important to conceptualize steps of reconstruction and analysis. We have focused our work in the cyanobacterium Synechococcus elongatus PCC7942, for which several analyses and insights are unveiled. A comprehensive approach has been used, which can be of interest to lead the process of manual curation and genome-scale metabolic analysis. The final model, iSyf715 includes 851 reactions and 838 metabolites. A biomass equation, which encompasses elementary building blocks to allow cell growth, is also included. The applicability of the model is finally demonstrated by simulating autotrophic growth conditions of Synechococcus elongatus PCC7942. | es_ES |
dc.description.sponsorship | The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement number 308518 (CyanoFactory), from the Spanish Ministerio de Educación Cultura y Deporte grant FPU12/05873 through the program FPU and from the UniversitatPolitècnia de València grant Contratos Predoctorales FPI 2013 | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | MDPI AG | es_ES |
dc.relation.ispartof | Metabolites | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject | Genome-scale metabolic network reconstruction | es_ES |
dc.subject | Systems biology | es_ES |
dc.subject | Metabolic pathways | es_ES |
dc.subject | Flux balance analysis | es_ES |
dc.subject | Biological databases | es_ES |
dc.subject.classification | FISICA APLICADA | es_ES |
dc.subject.classification | TECNOLOGIA DEL MEDIO AMBIENTE | es_ES |
dc.subject.classification | MATEMATICA APLICADA | es_ES |
dc.title | Generation and Evaluation of a Genome-Scale Metabolic Network Model of Synechococcus elongatus PCC7942 | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.3390/metabo4030680 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/FP7/308518/EU/Design, construction and demonstration of solar biofuel production using novel (photo)synthetic cell factories/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MECD//FPU12%2F05873/ES/FPU12%2F05873/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Ingeniería Hidráulica y Medio Ambiente - Departament d'Enginyeria Hidràulica i Medi Ambient | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Instituto Universitario de Matemática Pura y Aplicada - Institut Universitari de Matemàtica Pura i Aplicada | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Física Aplicada - Departament de Física Aplicada | es_ES |
dc.description.bibliographicCitation | Triana, J.; Montagud, A.; Siurana, M.; Fuente, D.; Urchueguia, A.; Gamermann, D.; Torres, J.... (2014). Generation and Evaluation of a Genome-Scale Metabolic Network Model of Synechococcus elongatus PCC7942. Metabolites. 4(3):680-698. https://doi.org/10.3390/metabo4030680 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.3390/metabo4030680 | es_ES |
dc.description.upvformatpinicio | 680 | es_ES |
dc.description.upvformatpfin | 698 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 4 | es_ES |
dc.description.issue | 3 | es_ES |
dc.identifier.eissn | 2218-1989 | es_ES |
dc.identifier.pmid | 25141288 | es_ES |
dc.identifier.pmcid | PMC4192687 | es_ES |
dc.relation.pasarela | S\278781 | es_ES |
dc.contributor.funder | Universitat Politècnica de València | es_ES |
dc.contributor.funder | Ministerio de Educación, Cultura y Deporte | es_ES |
dc.description.references | Shestakov, S. V., & Khyen, N. T. (1970). Evidence for genetic transformation in blue-green alga Anacystis nidulans. Molecular and General Genetics MGG, 107(4), 372-375. doi:10.1007/bf00441199 | es_ES |
dc.description.references | Andersson, C. R., Tsinoremas, N. F., Shelton, J., Lebedeva, N. V., Yarrow, J., Min, H., & Golden, S. S. (2000). Application of bioluminescence to the study of circadian rhythms in cyanobacteria. Methods in Enzymology, 527-542. doi:10.1016/s0076-6879(00)05511-7 | es_ES |
dc.description.references | Rippka, R., Stanier, R. Y., Deruelles, J., Herdman, M., & Waterbury, J. B. (1979). Generic Assignments, Strain Histories and Properties of Pure Cultures of Cyanobacteria. Microbiology, 111(1), 1-61. doi:10.1099/00221287-111-1-1 | es_ES |
dc.description.references | Scanlan, D. J., & West, N. J. (2002). Molecular ecology of the marine cyanobacterial genera Prochlorococcus and Synechococcus. FEMS Microbiology Ecology, 40(1), 1-12. doi:10.1111/j.1574-6941.2002.tb00930.x | es_ES |
dc.description.references | Ducat, D. C., Way, J. C., & Silver, P. A. (2011). Engineering cyanobacteria to generate high-value products. Trends in Biotechnology, 29(2), 95-103. doi:10.1016/j.tibtech.2010.12.003 | es_ES |
dc.description.references | Snoep, J. L., Bruggeman, F., Olivier, B. G., & Westerhoff, H. V. (2006). Towards building the silicon cell: A modular approach. Biosystems, 83(2-3), 207-216. doi:10.1016/j.biosystems.2005.07.006 | es_ES |
dc.description.references | Papin, J. A., Price, N. D., Wiback, S. J., Fell, D. A., & Palsson, B. O. (2003). Metabolic pathways in the post-genome era. Trends in Biochemical Sciences, 28(5), 250-258. doi:10.1016/s0968-0004(03)00064-1 | es_ES |
dc.description.references | Montagud, A., Navarro, E., Fernández de Córdoba, P., Urchueguía, J. F., & Patil, K. R. (2010). Reconstruction and analysis of genome-scale metabolic model of a photosynthetic bacterium. BMC Systems Biology, 4(1). doi:10.1186/1752-0509-4-156 | es_ES |
dc.description.references | Montagud, A., Zelezniak, A., Navarro, E., de Córdoba, P. F., Urchueguía, J. F., & Patil, K. R. (2011). Flux coupling and transcriptional regulation within the metabolic network of the photosynthetic bacterium Synechocystis sp. PCC6803. Biotechnology Journal, 6(3), 330-342. doi:10.1002/biot.201000109 | es_ES |
dc.description.references | Park, J., Kim, T., & Lee, S. (2011). Genome-scale reconstruction and in silico analysis of the Ralstonia eutropha H16 for polyhydroxyalkanoate synthesis, lithoautotrophic growth, and 2-methyl citric acid production. BMC Systems Biology, 5(1), 101. doi:10.1186/1752-0509-5-101 | es_ES |
dc.description.references | Milne, C. B., Eddy, J. A., Raju, R., Ardekani, S., Kim, P.-J., Senger, R. S., … Price, N. D. (2011). Metabolic network reconstruction and genome-scale model of butanol-producing strain Clostridium beijerinckii NCIMB 8052. BMC Systems Biology, 5(1), 130. doi:10.1186/1752-0509-5-130 | es_ES |
dc.description.references | Van den Hondel, C. A., Verbeek, S., van der Ende, A., Weisbeek, P. J., Borrias, W. E., & van Arkel, G. A. (1980). Introduction of transposon Tn901 into a plasmid of Anacystis nidulans: preparation for cloning in cyanobacteria. Proceedings of the National Academy of Sciences, 77(3), 1570-1574. doi:10.1073/pnas.77.3.1570 | es_ES |
dc.description.references | Plas, J., Oosterhoff-Teertstra, R., Borrias, M., & Weisbeek, P. (1992). Identification of replication and stability functions in the complete nucleotide sequence of plasmid pUH24 from the cyanobacterium Synechococcus sp. PCC 7942. Molecular Microbiology, 6(5), 653-664. doi:10.1111/j.1365-2958.1992.tb01513.x | es_ES |
dc.description.references | Chen, Y., Kay Holtman, C., Magnuson, R. D., Youderian, P. A., & Golden, S. S. (2008). The complete sequence and functional analysis of pANL, the large plasmid of the unicellular freshwater cyanobacterium Synechococcus elongatus PCC 7942. Plasmid, 59(3), 176-192. doi:10.1016/j.plasmid.2008.01.005 | es_ES |
dc.description.references | Weise, S., Grosse, I., Klukas, C., Koschützki, D., Scholz, U., Schreiber, F., & Junker, B. H. (2006). Meta-All: a system for managing metabolic pathway information. BMC Bioinformatics, 7(1). doi:10.1186/1471-2105-7-465 | es_ES |
dc.description.references | Forster, J. (2003). Genome-Scale Reconstruction of the Saccharomyces cerevisiae Metabolic Network. Genome Research, 13(2), 244-253. doi:10.1101/gr.234503 | es_ES |
dc.description.references | Price, N. D., Papin, J. A., Schilling, C. H., & Palsson, B. O. (2003). Genome-scale microbial in silico models: the constraints-based approach. Trends in Biotechnology, 21(4), 162-169. doi:10.1016/s0167-7799(03)00030-1 | es_ES |
dc.description.references | Durot, M., Bourguignon, P.-Y., & Schachter, V. (2009). Genome-scale models of bacterial metabolism: reconstruction and applications. FEMS Microbiology Reviews, 33(1), 164-190. doi:10.1111/j.1574-6976.2008.00146.x | es_ES |
dc.description.references | Price, N. D., Reed, J. L., & Palsson, B. Ø. (2004). Genome-scale models of microbial cells: evaluating the consequences of constraints. Nature Reviews Microbiology, 2(11), 886-897. doi:10.1038/nrmicro1023 | es_ES |
dc.description.references | Orth, J. D., Thiele, I., & Palsson, B. Ø. (2010). What is flux balance analysis? Nature Biotechnology, 28(3), 245-248. doi:10.1038/nbt.1614 | es_ES |
dc.description.references | Thiele, I., & Palsson, B. Ø. (2010). A protocol for generating a high-quality genome-scale metabolic reconstruction. Nature Protocols, 5(1), 93-121. doi:10.1038/nprot.2009.203 | es_ES |
dc.description.references | Feist, A. M., Herrgård, M. J., Thiele, I., Reed, J. L., & Palsson, B. Ø. (2008). Reconstruction of biochemical networks in microorganisms. Nature Reviews Microbiology, 7(2), 129-143. doi:10.1038/nrmicro1949 | es_ES |
dc.description.references | Notebaart, R. A., van Enckevort, F. H., Francke, C., Siezen, R. J., & Teusink, B. (2006). BMC Bioinformatics, 7(1), 296. doi:10.1186/1471-2105-7-296 | es_ES |
dc.description.references | Karp, P. D., Paley, S., & Romero, P. (2002). The Pathway Tools software. Bioinformatics, 18(Suppl 1), S225-S232. doi:10.1093/bioinformatics/18.suppl_1.s225 | es_ES |
dc.description.references | Reyes, R., Gamermann, D., Montagud, A., Fuente, D., Triana, J., Urchueguía, J. F., & de Córdoba, P. F. (2012). Automation on the Generation of Genome-Scale Metabolic Models. Journal of Computational Biology, 19(12), 1295-1306. doi:10.1089/cmb.2012.0183 | es_ES |
dc.description.references | Kanehisa, M., Goto, S., Furumichi, M., Tanabe, M., & Hirakawa, M. (2009). KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Research, 38(suppl_1), D355-D360. doi:10.1093/nar/gkp896 | es_ES |
dc.description.references | Caspi, R. (2006). MetaCyc: a multiorganism database of metabolic pathways and enzymes. Nucleic Acids Research, 34(90001), D511-D516. doi:10.1093/nar/gkj128 | es_ES |
dc.description.references | Overton, I. M., van Niekerk, C. A. J., Carter, L. G., Dawson, A., Martin, D. M. A., Cameron, S., … Barton, G. J. (2008). TarO: a target optimisation system for structural biology. Nucleic Acids Research, 36(Web Server), W190-W196. doi:10.1093/nar/gkn141 | es_ES |
dc.description.references | SCHILLING, C. H., LETSCHER, D., & PALSSON, B. Ø. (2000). Theory for the Systemic Definition of Metabolic Pathways and their use in Interpreting Metabolic Function from a Pathway-Oriented Perspective. Journal of Theoretical Biology, 203(3), 229-248. doi:10.1006/jtbi.2000.1073 | es_ES |
dc.description.references | Pearce, J., & Carr, N. G. (1967). The Metabolism of Acetate by the Blue-green Algae, Anabaena variabilis and Anacystis nidulans. Journal of General Microbiology, 49(2), 301-313. doi:10.1099/00221287-49-2-301 | es_ES |
dc.description.references | Li, C., Donizelli, M., Rodriguez, N., Dharuri, H., Endler, L., Chelliah, V., … Laibe, C. (2010). BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Systems Biology, 4(1), 92. doi:10.1186/1752-0509-4-92 | es_ES |
dc.description.references | Barabási, A.-L., & Albert, R. (1999). Emergence of Scaling in Random Networks. Science, 286(5439), 509-512. doi:10.1126/science.286.5439.509 | es_ES |
dc.description.references | Albert, R., Jeong, H., & Barabási, A.-L. (2000). Error and attack tolerance of complex networks. Nature, 406(6794), 378-382. doi:10.1038/35019019 | es_ES |
dc.description.references | Barabási, A.-L., & Bonabeau, E. (2003). Scale-Free Networks. Scientific American, 288(5), 60-69. doi:10.1038/scientificamerican0503-60 | es_ES |
dc.description.references | Barabási, A.-L., & Oltvai, Z. N. (2004). Network biology: understanding the cell’s functional organization. Nature Reviews Genetics, 5(2), 101-113. doi:10.1038/nrg1272 | es_ES |
dc.description.references | Feist, A. M., Henry, C. S., Reed, J. L., Krummenacker, M., Joyce, A. R., Karp, P. D., … Palsson, B. Ø. (2007). A genome‐scale metabolic reconstruction forEscherichia coliK‐12 MG1655 that accounts for 1260 ORFs and thermodynamic information. Molecular Systems Biology, 3(1), 121. doi:10.1038/msb4100155 | es_ES |
dc.description.references | Csete, M., & Doyle, J. (2004). Bow ties, metabolism and disease. Trends in Biotechnology, 22(9), 446-450. doi:10.1016/j.tibtech.2004.07.007 | es_ES |
dc.description.references | Hardy, M. (2010). Pareto’s Law. The Mathematical Intelligencer, 32(3), 38-43. doi:10.1007/s00283-010-9159-2 | es_ES |
dc.description.references | Newman, M. (2005). Power laws, Pareto distributions and Zipf’s law. Contemporary Physics, 46(5), 323-351. doi:10.1080/00107510500052444 | es_ES |
dc.description.references | Wagner, A., & Fell, D. A. (2001). The small world inside large metabolic networks. Proceedings of the Royal Society of London. Series B: Biological Sciences, 268(1478), 1803-1810. doi:10.1098/rspb.2001.1711 | es_ES |
dc.description.references | Kajiwara, S., Yamada, H., Ohkuni, N., & Ohtaguchi, K. (1997). Design of the bioreactor for carbon dioxide fixation by Synechococcus PCC7942. Energy Conversion and Management, 38, S529-S532. doi:10.1016/s0196-8904(96)00322-6 | es_ES |
dc.description.references | Shastri, A. A., & Morgan, J. A. (2005). Flux Balance Analysis of Photoautotrophic Metabolism. Biotechnology Progress, 21(6), 1617-1626. doi:10.1021/bp050246d | es_ES |
dc.description.references | Growth optimization of Synechococcus elongatus PCC7942 in lab flask and 2D photobioreactorhttps://circle.ubc.ca/bitstream/handle/2429/45010/ubc_2013_fall_kuan_david.pdf?sequence=1 | es_ES |
dc.description.references | Lewis, N. E., Hixson, K. K., Conrad, T. M., Lerman, J. A., Charusanti, P., Polpitiya, A. D., … Palsson, B. Ø. (2010). Omic data from evolved E. coli are consistent with computed optimal growth from genome‐scale models. Molecular Systems Biology, 6(1), 390. doi:10.1038/msb.2010.47 | es_ES |
dc.description.references | Imam, S., Yilmaz, S., Sohmen, U., Gorzalski, A. S., Reed, J. L., Noguera, D. R., & Donohue, T. J. (2011). iRsp1095: A genome-scale reconstruction of the Rhodobacter sphaeroides metabolic network. BMC Systems Biology, 5(1), 116. doi:10.1186/1752-0509-5-116 | es_ES |
dc.description.references | Munekage, Y., Hashimoto, M., Miyake, C., Tomizawa, K.-I., Endo, T., Tasaka, M., & Shikanai, T. (2004). Cyclic electron flow around photosystem I is essential for photosynthesis. Nature, 429(6991), 579-582. doi:10.1038/nature02598 | es_ES |
dc.description.references | Chen, Y., Daviet, L., Schalk, M., Siewers, V., & Nielsen, J. (2013). Establishing a platform cell factory through engineering of yeast acetyl-CoA metabolism. Metabolic Engineering, 15, 48-54. doi:10.1016/j.ymben.2012.11.002 | es_ES |
dc.description.references | Shi, S., Chen, Y., Siewers, V., & Nielsen, J. (2014). Improving Production of Malonyl Coenzyme A-Derived Metabolites by Abolishing Snf1-Dependent Regulation of Acc1. mBio, 5(3). doi:10.1128/mbio.01130-14 | es_ES |
dc.description.references | Krivoruchko, A., Serrano-Amatriain, C., Chen, Y., Siewers, V., & Nielsen, J. (2013). Improving biobutanol production in engineered Saccharomyces cerevisiae by manipulation of acetyl-CoA metabolism. Journal of Industrial Microbiology & Biotechnology, 40(9), 1051-1056. doi:10.1007/s10295-013-1296-0 | es_ES |
dc.description.references | Robertson, B. R., Tezuka, N., & Watanabe, M. M. (2001). Phylogenetic analyses of Synechococcus strains (cyanobacteria) using sequences of 16S rDNA and part of the phycocyanin operon reveal multiple evolutionary lines and reflect phycobilin content. International Journal of Systematic and Evolutionary Microbiology, 51(3), 861-871. doi:10.1099/00207713-51-3-861 | es_ES |
dc.description.references | Patil, K., Rocha, I., Förster, J., & Nielsen, J. (2005). BMC Bioinformatics, 6(1), 308. doi:10.1186/1471-2105-6-308 | es_ES |
dc.description.references | Cvijovic, M., Olivares-Hernandez, R., Agren, R., Dahr, N., Vongsangnak, W., Nookaew, I., … Nielsen, J. (2010). BioMet Toolbox: genome-wide analysis of metabolism. Nucleic Acids Research, 38(Web Server), W144-W149. doi:10.1093/nar/gkq404 | es_ES |
dc.description.references | BioOpt softwarehttp://biomet-toolbox.org/index.php?page=downtools-bioOpt | es_ES |
dc.description.references | Gamermann, D., Montagud, A., Conejero, J. A., Urchueguía, J. F., & de Córdoba, P. F. (2014). New Approach for Phylogenetic Tree Recovery Based on Genome-Scale Metabolic Networks. Journal of Computational Biology, 21(7), 508-519. doi:10.1089/cmb.2013.0150 | es_ES |
dc.description.references | Vu, T. T., Stolyar, S. M., Pinchuk, G. E., Hill, E. A., Kucek, L. A., Brown, R. N., … Reed, J. L. (2012). Genome-Scale Modeling of Light-Driven Reductant Partitioning and Carbon Fluxes in Diazotrophic Unicellular Cyanobacterium Cyanothece sp. ATCC 51142. PLoS Computational Biology, 8(4), e1002460. doi:10.1371/journal.pcbi.1002460 | es_ES |
dc.description.references | Hamilton, J. J., & Reed, J. L. (2012). Identification of Functional Differences in Metabolic Networks Using Comparative Genomics and Constraint-Based Models. PLoS ONE, 7(4), e34670. doi:10.1371/journal.pone.0034670 | es_ES |