Dataset Information

Comparative genomics of the white-rot fungi, Phanerochaete carnosa and P. chrysosporium, to elucidate the genetic basis of the distinct wood types they colonize.

ABSTRACT: BACKGROUND: Softwood is the predominant form of land plant biomass in the Northern hemisphere, and is among the most recalcitrant biomass resources to bioprocess technologies. The white rot fungus, Phanerochaete carnosa, has been isolated almost exclusively from softwoods, while most other known white-rot species, including Phanerochaete chrysosporium, were mainly isolated from hardwoods. Accordingly, it is anticipated that P. carnosa encodes a distinct set of enzymes and proteins that promote softwood decomposition. To elucidate the genetic basis of softwood bioconversion by a white-rot fungus, the present study reports the P. carnosa genome sequence and its comparative analysis with the previously reported P. chrysosporium genome. RESULTS: P. carnosa encodes a complete set of lignocellulose-active enzymes. Comparative genomic analysis revealed that P. carnosa is enriched with genes encoding manganese peroxidase, and that the most divergent glycoside hydrolase families were predicted to encode hemicellulases and glycoprotein degrading enzymes. Most remarkably, P. carnosa possesses one of the largest P450 contingents (266 P450s) among the sequenced and annotated wood-rotting basidiomycetes, nearly double that of P. chrysosporium. Along with metabolic pathway modeling, comparative growth studies on model compounds and chemical analyses of decomposed wood components showed greater tolerance of P. carnosa to various substrates including coniferous heartwood. CONCLUSIONS: The P. carnosa genome is enriched with genes that encode P450 monooxygenases that can participate in extractives degradation, and manganese peroxidases involved in lignin degradation. The significant expansion of P450s in P. carnosa, along with differences in carbohydrate- and lignin-degrading enzymes, could be correlated to the utilization of heartwood and sapwood preparations from both coniferous and hardwood species.

SUBMITTER: Suzuki H

PROVIDER: S-EPMC3463431 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Comparative genomics of the white-rot fungi, Phanerochaete carnosa and P. chrysosporium, to elucidate the genetic basis of the distinct wood types they colonize.

Suzuki Hitoshi H MacDonald Jacqueline J Syed Khajamohiddin K Salamov Asaf A Hori Chiaki C Aerts Andrea A Henrissat Bernard B Wiebenga Ad A VanKuyk Patricia A PA Barry Kerrie K Lindquist Erika E LaButti Kurt K Lapidus Alla A Lucas Susan S Coutinho Pedro P Gong Yunchen Y Samejima Masahiro M Mahadevan Radhakrishnan R Abou-Zaid Mamdouh M de Vries Ronald P RP Igarashi Kiyohiko K Yadav Jagjit S JS Grigoriev Igor V IV Master Emma R ER

BMC genomics 20120902

<h4>Background</h4>Softwood is the predominant form of land plant biomass in the Northern hemisphere, and is among the most recalcitrant biomass resources to bioprocess technologies. The white rot fungus, Phanerochaete carnosa, has been isolated almost exclusively from softwoods, while most other known white-rot species, including Phanerochaete chrysosporium, were mainly isolated from hardwoods. Accordingly, it is anticipated that P. carnosa encodes a distinct set of enzymes and proteins that pr ...[more]

PMID: 22937793

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Project description:UnlabelledIdentification of the specific genes and enzymes involved in the fungal degradation of lignocellulosic biomass derived from feedstocks with various compositions is essential to the development of improved bioenergy processes. In order to elucidate the effect of substrate composition on gene expression in wood-rotting fungi, we employed microarrays based on the annotated genomes of the brown- and white-rot fungi, Rhodonia placenta (formerly Postia placenta) and Phanerochaete chrysosporium, respectively. We monitored the expression of genes involved in the enzymatic deconstruction of the cell walls of three 4-year-old Populus trichocarpa (poplar) trees of genotypes with distinct cell wall chemistries, selected from a population of several hundred trees grown in a common garden. The woody substrates were incubated with wood decay fungi for 10, 20, and 30 days. An analysis of transcript abundance in all pairwise comparisons highlighted 64 and 84 differentially expressed genes (>2-fold, P < 0.05) in P. chrysosporium and P. placenta, respectively. Cross-fungal comparisons also revealed an array of highly differentially expressed genes (>4-fold, P < 0.01) across different substrates and time points. These results clearly demonstrate that gene expression profiles of P. chrysosporium and P. placenta are influenced by wood substrate composition and the duration of incubation. Many of the significantly expressed genes encode "proteins of unknown function," and determining their role in lignocellulose degradation presents opportunities and challenges for future research.ImportanceThis study describes the variation in expression patterns of two wood-degrading fungi (brown- and white-rot fungi) during colonization and incubation on three different naturally occurring poplar substrates of differing chemical compositions, over time. The results clearly show that the two fungi respond differentially to their substrates and that several known and, more interestingly, currently unknown genes are highly misregulated in response to various substrate compositions. These findings highlight the need to characterize several unknown proteins for catalytic function but also as potential candidate proteins to improve the efficiency of enzymatic cocktails to degrade lignocellulosic substrates in industrial applications, such as in a biochemically based bioenergy platform.

Dataset Information

Comparative genomics of the white-rot fungi, Phanerochaete carnosa and P. chrysosporium, to elucidate the genetic basis of the distinct wood types they colonize.

Publications

Comparative genomics of the white-rot fungi, Phanerochaete carnosa and P. chrysosporium, to elucidate the genetic basis of the distinct wood types they colonize.

Similar Datasets

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