alexa The Phanerochaete chrysosporium secretome: database predictions and initial mass spectrometry peptide identifications in cellulose-grown medium.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Proteomics & Bioinformatics

Author(s): Wymelenberg AV, Sabat G, Martinez D, Rajangam AS, Teeri TT,

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Abstract The white rot basidiomycete, Phanerochaete chrysosporium, employs an array of extracellular enzymes to completely degrade the major polymers of wood: cellulose, hemicellulose and lignin. Towards the identification of participating enzymes, 268 likely secreted proteins were predicted using SignalP and TargetP algorithms. To assess the reliability of secretome predictions and to evaluate the usefulness of the current database, we performed shotgun LC-MS/MS on cultures grown on standard cellulose-containing medium. A total of 182 unique peptide sequences were matched to 50 specific genes, of which 24 were among the secretome subset. Underscoring the rich genetic diversity of P. chrysosporium, identifications included 32 glycosyl hydrolases. Functionally interconnected enzyme groups were recognized. For example, the multiple endoglucanases and processive exocellobiohydrolases observed quite probably attack cellulose in a synergistic manner. In addition, a hemicellulolytic system included endoxylanases, alpha-galactosidase, acetyl xylan esterase, and alpha-l-arabinofuranosidase. Glucose and cellobiose metabolism likely involves cellobiose dehydrogenase, glucose oxidase, and various inverting glycoside hydrolases, all perhaps enhanced by an epimerase. To evaluate the completeness of the current database, mass spectroscopy analysis was performed on a larger and more inclusive dataset containing all possible ORFs. This allowed identification of a previously undetected hypothetical protein and a putative acid phosphatase. The expression of several genes was supported by RT-PCR amplification of their cDNAs. This article was published in J Biotechnol and referenced in Journal of Proteomics & Bioinformatics

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