Bioinfo_eXtrema : un enfoque bioinformático para integrar información ambiental, bioquímica y genómica, enfocado en bioprospección y selección de consorcios de microorganismos con aplicaciones en biorremediación

Authors

  • Fabián Capdevielle Unidad de Biotecnología, Instituto Nacional de Investigación Agropecuaria (INIA), Uruguay
  • Carolina Ottati Departamento de Bioprocesos y Biotecnología, Laboratorio Tecnológico del Uruguay (LATU), Uruguay
  • Mary Lopretti Departamento de Bioprocesos y Biotecnología, Laboratorio Tecnológico del Uruguay (LATU), Laboratorio de Bioquímica y Bitecnología (CIN), Facultad de Ciencias, Universidad de la República, Uruguay

DOI:

https://doi.org/10.26461/05.07

Abstract

The ability to identify microbe extremophiles with metabolic capabilities suited for specific bioprocesses opens the doors of extreme environments for development of new industrial products. Identification of key functional components from existing biodiversity supported selection of candidate isolates from three Penicillium fungal species. These candidates were evaluated in vitro to further characterize their potential as components of a microbial consortium for biorremediation of industrial effluents containing lignocellulosic residues. Results from annotation of available genomic sequences for one of these Penicillium species pointed to the existence of putative genes highly similar to those functionally identified in reference fungi for degradation of lignin in natural environments. Proposed functional annotations from available sequences were identified through a specialized database –Fungal Oxidative Lignin Enzymes (FOLy)– and could be contrasted straightforward with experimental results for strains growing in different media containing lignin, representing extreme industry-related environments. We propose the as- sembly of Bioinfo_eXtreme as an industrial-biotechnology-centered bioinformatics approach for consortia selection, combining diverse data mining techniques –components of the Waikato Environment for Knowledge Analysis (WEKA)–, to facilitate inte- gration of available molecular information and relevant phenotypic indicators for biorremediation applications.

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References

NATIONAL CENTRE FOR TEXT MINING; THE UNIVERSITY OF MANCHESTER. SCHOOL OF COMPUTER SCIENCE. FACTA + [En línea]. Versión 0.7. s.l.: National Centre for Text Mining School of Computer Science; The University of Manchester, 2009. [Consulta 27 de junio de 2010]. Disponible en: http://refine1-nactem.mc.man.ac.uk/facta_events/

KEMPER, Brian; MATSUZAKi, Takuya; MATSUOKA, Yukiko; TSURUOKA, Yoshimasa; KITANO, Hiroaki; ANANIADOU, Sophia; TSUJII, Jun’ichi. PathText: a text mining integrator for biological pathway visualizations. En: Bioinformatics. 2010, 26(12):374-381.

KUNIK Vered; MEROZ, Yasmine; SOLAN, Zach; SANDBANK, Ben; WEINGART, Uri; RUPPIN, Eytan; HORN, David. Functional representation of enzymes by specific peptides. En: PLOS Comp Biol.2007, 3(8):1623-1632

INRI; UNIVERSITES DE PROVENCE ET DE LA MEDITERRANEE; UMR. FOLy Fungal Oxidative Lignin enzymes [En línea]. Marseille: INRI; Universites de Provence et de la Mediterranee; UMR, 2010. [Consulta 27 de junio de 2010]. Disponible en: http://foly.esil.univ-mrs.fr/

LEITAO, Ana Lucía. Potential of Penicillium species in the bioremediation field. En: Int. J. Environ. Res. Public Health. 2009, 6(4):1393-1417

LEVASSEUR, Anthony; PIUMI, Francois; COUTIÑO, Pedro M.; RANCUREL, Corinne; ASTHER, Michèlle; DELATTRE, Michel; HENRISSAT, Bernard; PONTAROTTI, Pierre; ASTHER, Marcel; RECORD, Eric. FOLy: An integrated database for the classification and functional annotation of fungal oxidoreductases potentially involved in the degradation of lignin and related aromatic compounds. En: Fungal Genetics and Biology. 2008, 45(5):638–645.

LOPRETTI, Mary; OTTATI, Carolina; CAPDEVIELLE, Fabián; DAMBORIARENA, Agustín; SIBAJA, María. Penicillium ́s consortium: potential modifier of polyphenols for management and industrial use. En: EUROPEAN COMmISSION. 18th European Biomass Conference and Exhibition (Lyon 3-7 de mayo de 2010). Lyon: European Commission, 2010.

MARTINEZ, Diego; LARRONDO, Luis; PUTMAN, Nik; GELPKE, Maarten D.S.; HUANG, Katherine; CHAPMAN, Jarrod; HELFENBEIN, Kevin G.; RAMAIYA, Preethi; DETTER, J. Chris; LARIMER, Frank; COUTINHO, PEDRO M.; HENRISSAT, Bernard; BERKA, Randy; CULLEN, Dan; ROKHSAR, Daniel. Genome sequence of the lignocellulose degrading fungus Phanerochaete chrysosporium strain RP78. En: Nature Biotechnology. 2004, (22):1–6.

NATIONAL CENTER FOR BIOTECHNOLOGY INFORMATION. Genomes & maps [En línea]. Bethesda: NCBI, s.d. [Consulta 27 de junio de 2010]. Disponible en: http://www.ncbi.nlm.nih.gov/guide/genomes-maps/

NOBATA, Chikashi; COTTER, Philip; OKAZAKI, Naoaki; REA, Brian; SASAKI, Yutaka; TSURUOKA, Yoshimasa; ANANIADOU, Sophia. Kleio: a knowledge-enriched information retrieval system for biology. En: MYAENG, S.H. et al. Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. Singapore: ACM, 2008. pp. 787-788.

TSURUOKA,Yoshimasa; TSUJII, Jun’ichi; ANANIADOU, Sophia. FACTA: a text search engine for finding associated biomedical concepts. En: Bioinformatics. 2008, 24(21):2259–2260.

THE NATIONAL CENTRE FOR TEXT MINING. KLEIO [En línea]. Manchester: The National Centre for Text Mining, s.d. [Consulta 27 de junio de 2010]. Disponible en: http://www.nactem.ac.uk/software/kleio/

WEINGART, Uri; LAVI, Yair; HORN, David. Data mining of enzymes using specific peptides. En: BMC Bioinformatics. 2009, (10):446-456.

WEINGART, Uri; LAVI, Yair; HORN, David. Data mining of enzymes. Peptide search [En línea]. s.l.: Uri Weingar, s.d. [Consulta 27 de junio de 2010]. Disponible en: http://adios.tau.ac.il/DME/

UNIVERSITY OF CALIFORNIA. Phanerochaete chrysosporium [En línea]. Versión 2.0. California: University of California, s.d. [Consulta 27 de junio de 2010]. Disponible en: http://genome.jgi-psf.org/Phchr1/Phchr1.home.html

WITTEN, Ian H.; FRANK, Eibe. Data mining: practical machine learning tools and techniques. San Francisco: Morgan-Kaufmann, 2005.

How to Cite

Capdevielle, F., Ottati, C., & Lopretti, M. (2011). Bioinfo_eXtrema : un enfoque bioinformático para integrar información ambiental, bioquímica y genómica, enfocado en bioprospección y selección de consorcios de microorganismos con aplicaciones en biorremediación. INNOTEC, (5 ene-dic), 43–47. https://doi.org/10.26461/05.07

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