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Author Loira, N.; Mendoza, S.; Cortes, M.P.; Rojas, N.; Travisany, D.; Di Genova, A.; Gajardo, N.; Ehrenfeld, N.; Maass, A. pdf  doi
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  Title (down) Reconstruction of the microalga Nannochloropsis salina genome-scale metabolic model with applications to lipid production Type
  Year 2017 Publication Bmc Systems Biology Abbreviated Journal BMC Syst. Biol.  
  Volume 11 Issue Pages 17 pp  
  Keywords Genome-scale Metabolic model; Nannochloropsis salina; TAG; Microalg ae  
  Abstract Background: Nannochloropsis salina (= Eustigmatophyceae) is a marine microalga which has become a biotechnological target because of its high capacity to produce polyunsaturated fatty acids and triacylglycerols. It has been used as a source of biofuel, pigments and food supplements, like Omega 3. Only some Nannochloropsis species have been sequenced, but none of them benefit from a genome-scale metabolic model (GSMM), able to predict its metabolic capabilities. Results: We present iNS934, the first GSMM for N. salina, including 2345 reactions, 934 genes and an exhaustive description of lipid and nitrogen metabolism. iNS934 has a 90% of accuracy when making simple growth/no-growth predictions and has a 15% error rate in predicting growth rates in different experimental conditions. Moreover, iNS934 allowed us to propose 82 different knockout strategies for strain optimization of triacylglycerols. Conclusions: iNS934 provides a powerful tool for metabolic improvement, allowing predictions and simulations of N. salina metabolism under different media and genetic conditions. It also provides a systemic view of N. salina metabolism, potentially guiding research and providing context to -omics data.  
  Address [Loira, Nicolas; Mendoza, Sebastian; Paz Cortes, Maria; Travisany, Dante; Di Genova, Alex; Maass, Alejandro] Univ Chile, Ctr Math Modeling, Math, Beauchef 851,7th Floor, Santiago, Chile, Email: nloira@dim.uchile.cl  
  Corporate Author Thesis  
  Publisher Biomed Central Ltd Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1752-0509 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000404918700001 Approved  
  Call Number UAI @ eduardo.moreno @ Serial 744  
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Author Cortes, M.P.; Mendoza, S.N.; Travisany, D.; Gaete, A.; Siegel, A.; Cambiazo, V.; Maass, A. pdf  doi
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  Title (down) Analysis of Piscirickettsia salmonis Metabolism Using Genome-Scale Reconstruction, Modeling, and Testing Type
  Year 2017 Publication Frontiers In Microbiology Abbreviated Journal Front. Microbiol.  
  Volume 8 Issue Pages 15 pp  
  Keywords pathogen; genome-scale; metabolism; constraint-based; Piscirickettsia; salmonis  
  Abstract Piscirickettsia salmonis is an intracellular bacterial fish pathogen that causes piscirickettsiosis, a disease with highly adverse impact in the Chilean salmon farming industry. The development of effective treatment and control methods for piscireckttsiosis is still a challenge. To meet it the number of studies on P. salmonis has grown in the last couple of years but many aspects of the pathogen's biology are still poorly understood. Studies on its metabolism are scarce and only recently a metabolic model for reference strain LF-89 was developed. We present a new genomescale model for P. salmonis LF-89 with more than twice as many genes as in the previous model and incorporating specific elements of the fish pathogen metabolism. Comparative analysis with models of different bacterial pathogens revealed a lower flexibility in P. salmonis metabolic network. Through constraint-based analysis, we determined essential metabolites required for its growth and showed that it can benefit from different carbon sources tested experimentally in new defined media. We also built an additional model for strain A1-15972, and together with an analysis of P. salmonis pangenome, we identified metabolic features that differentiate two main species clades. Both models constitute a knowledge-base for P. salmonis metabolism and can be used to guide the efficient culture of the pathogen and the identification of specific drug targets.  
  Address [Cortes, Maria P.; Mendoza, Sebastian N.; Travisany, Dante; Maass, Alejandro] Univ Chile, Ctr Math Modeling, Math, Santiago, Chile, Email: mpcortes@dim.uchile.cl  
  Corporate Author Thesis  
  Publisher Frontiers Media Sa Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1664-302x ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000417578100001 Approved  
  Call Number UAI @ eduardo.moreno @ Serial 787  
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