dc.creatorCastro, Lilian dos Santos
dc.creatorPedersoli, Wellington Ramos
dc.creatorAntoniêto, Amanda Cristina Campos
dc.creatorSteindorff, Andrei S
dc.creatorSilva-Rocha, Rafael
dc.creatorMartinez-Rossi, Nilce M
dc.creatorRossi, Antonio
dc.creatorBrown, Neil A
dc.creatorGoldman, Gustavo H
dc.creatorFaça, Vitor M
dc.creatorPersinoti, Gabriela F
dc.creatorSilva, Roberto Nascimento
dc.date.accessioned2015-01-09T17:03:48Z
dc.date.accessioned2018-07-04T16:59:00Z
dc.date.available2015-01-09T17:03:48Z
dc.date.available2018-07-04T16:59:00Z
dc.date.created2015-01-09T17:03:48Z
dc.date.issued2014-03-21
dc.identifierBiotechnology for Biofuels. 2014 Mar 21;7(1):41
dc.identifierhttp://dx.doi.org/10.1186/1754-6834-7-41
dc.identifierhttp://www.producao.usp.br/handle/BDPI/47384
dc.identifier10.1186/1754-6834-7-41
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1643049
dc.description.abstractAbstract Background The filamentous fungus Trichoderma reesei is a major producer of lignocellulolytic enzymes utilized by bioethanol industries. However, to achieve low cost second generation bioethanol production on an industrial scale an efficient mix of hydrolytic enzymes is required for the deconstruction of plant biomass. In this study, we investigated the molecular basis for lignocellulose-degrading enzyme production T. reesei during growth in cellulose, sophorose, and glucose. Results We examined and compared the transcriptome and differential secretome (2D-DIGE) of T. reesei grown in cellulose, sophorose, or glucose as the sole carbon sources. By applying a stringent cut-off threshold 2,060 genes were identified as being differentially expressed in at least one of the respective carbon source comparisons. Hierarchical clustering of the differentially expressed genes identified three possible regulons, representing 123 genes controlled by cellulose, 154 genes controlled by sophorose and 402 genes controlled by glucose. Gene regulatory network analyses of the 692 genes differentially expressed between cellulose and sophorose, identified only 75 and 107 genes as being specific to growth in sophorose and cellulose, respectively. 2D-DIGE analyses identified 30 proteins exclusive to sophorose and 37 exclusive to cellulose. A correlation of 70.17% was obtained between transcription and secreted protein profiles. Conclusions Our data revealed new players in cellulose degradation such as accessory proteins with non-catalytic functions secreted in different carbon sources, transporters, transcription factors, and CAZymes, that specifically respond in response to either cellulose or sophorose.
dc.languageen
dc.publisherBioMed Central
dc.relationBiotechnology for Biofuels
dc.rightsdos Santos Castro et al.; licensee BioMed Central Ltd.
dc.rightsopenAccess
dc.subjectTrichoderma reesei
dc.subjectRNA-seq
dc.subjectDIGE
dc.subjectCellulases
dc.subjectBioethanol
dc.titleComparative metabolism of cellulose, sophorose and glucose in Trichoderma reesei using high-throughput genomic and proteomic analyses
dc.typeArtículos de revistas


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