Discovery of genes coding for carbohydrate-active enzyme by metagenomic analysis of lignocellulosic biomasses.
Identifieur interne : 001444 ( Main/Curation ); précédent : 001443; suivant : 001445Discovery of genes coding for carbohydrate-active enzyme by metagenomic analysis of lignocellulosic biomasses.
Auteurs : Salvatore Montella [Italie] ; Valeria Ventorino [Italie] ; Vincent Lombard [France] ; Bernard Henrissat [France, Arabie saoudite] ; Olimpia Pepe [Italie] ; Vincenza Faraco [Italie]Source :
- Scientific reports [ 2045-2322 ] ; 2017.
Descripteurs français
- KwdFr :
- Analyse de profil d'expression de gènes (MeSH), Biologie informatique (méthodes), Biomasse (MeSH), Biotransformation (MeSH), Cadres ouverts de lecture (MeSH), Cellulases (génétique), Cellulases (métabolisme), Dépollution biologique de l'environnement (MeSH), Glycosidases (génétique), Glycosidases (métabolisme), Hydrolyse (MeSH), Lignine (métabolisme), Microbiote (MeSH), Métabolisme glucidique (génétique), Métagénome (MeSH), Métagénomique (méthodes), Polyosides (métabolisme), Produits agricoles (MeSH), Séquençage nucléotidique à haut débit (MeSH).
- MESH :
- génétique : Cellulases, Glycosidases, Métabolisme glucidique.
- métabolisme : Cellulases, Glycosidases, Lignine, Polyosides.
- méthodes : Biologie informatique, Métagénomique.
- Analyse de profil d'expression de gènes, Biomasse, Biotransformation, Cadres ouverts de lecture, Dépollution biologique de l'environnement, Hydrolyse, Microbiote, Métagénome, Produits agricoles, Séquençage nucléotidique à haut débit.
English descriptors
- KwdEn :
- Biodegradation, Environmental (MeSH), Biomass (MeSH), Biotransformation (MeSH), Carbohydrate Metabolism (genetics), Cellulases (genetics), Cellulases (metabolism), Computational Biology (methods), Crops, Agricultural (MeSH), Gene Expression Profiling (MeSH), Glycoside Hydrolases (genetics), Glycoside Hydrolases (metabolism), High-Throughput Nucleotide Sequencing (MeSH), Hydrolysis (MeSH), Lignin (metabolism), Metagenome (MeSH), Metagenomics (methods), Microbiota (MeSH), Open Reading Frames (MeSH), Polysaccharides (metabolism).
- MESH :
- chemical , genetics : Cellulases, Glycoside Hydrolases.
- genetics : Carbohydrate Metabolism.
- chemical , metabolism : Cellulases, Glycoside Hydrolases, Lignin, Polysaccharides.
- methods : Computational Biology, Metagenomics.
- Biodegradation, Environmental, Biomass, Biotransformation, Crops, Agricultural, Gene Expression Profiling, High-Throughput Nucleotide Sequencing, Hydrolysis, Metagenome, Microbiota, Open Reading Frames.
Abstract
In this study, a high-throughput sequencing approach was applied to discover novel biocatalysts for lignocellulose hydrolysis from three dedicated energy crops, Arundo donax, Eucalyptus camaldulensis and Populus nigra, after natural biodegradation. The microbiomes of the three lignocellulosic biomasses were dominated by bacterial species (approximately 90%) with the highest representation by the Streptomyces genus both in the total microbial community composition and in the microbial diversity related to GH families of predicted ORFs. Moreover, the functional clustering of the predicted ORFs showed a prevalence of poorly characterized genes, suggesting these lignocellulosic biomasses are potential sources of as yet unknown genes. 1.2%, 0.6% and 3.4% of the total ORFs detected in A. donax, E. camaldulensis and P. nigra, respectively, were putative Carbohydrate-Active Enzymes (CAZymes). Interestingly, the glycoside hydrolases abundance in P. nigra (1.8%) was higher than that detected in the other biomasses investigated in this study. Moreover, a high percentage of (hemi)cellulases with different activities and accessory enzymes (mannanases, polygalacturonases and feruloyl esterases) was detected, confirming that the three analyzed samples were a reservoir of diversified biocatalysts required for an effective lignocellulose saccharification.
DOI: 10.1038/srep42623
PubMed: 28198423
PubMed Central: PMC5309792
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pubmed:28198423Le document en format XML
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<front><div type="abstract" xml:lang="en">In this study, a high-throughput sequencing approach was applied to discover novel biocatalysts for lignocellulose hydrolysis from three dedicated energy crops, Arundo donax, Eucalyptus camaldulensis and Populus nigra, after natural biodegradation. The microbiomes of the three lignocellulosic biomasses were dominated by bacterial species (approximately 90%) with the highest representation by the Streptomyces genus both in the total microbial community composition and in the microbial diversity related to GH families of predicted ORFs. Moreover, the functional clustering of the predicted ORFs showed a prevalence of poorly characterized genes, suggesting these lignocellulosic biomasses are potential sources of as yet unknown genes. 1.2%, 0.6% and 3.4% of the total ORFs detected in A. donax, E. camaldulensis and P. nigra, respectively, were putative Carbohydrate-Active Enzymes (CAZymes). Interestingly, the glycoside hydrolases abundance in P. nigra (1.8%) was higher than that detected in the other biomasses investigated in this study. Moreover, a high percentage of (hemi)cellulases with different activities and accessory enzymes (mannanases, polygalacturonases and feruloyl esterases) was detected, confirming that the three analyzed samples were a reservoir of diversified biocatalysts required for an effective lignocellulose saccharification.</div>
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<Abstract><AbstractText>In this study, a high-throughput sequencing approach was applied to discover novel biocatalysts for lignocellulose hydrolysis from three dedicated energy crops, Arundo donax, Eucalyptus camaldulensis and Populus nigra, after natural biodegradation. The microbiomes of the three lignocellulosic biomasses were dominated by bacterial species (approximately 90%) with the highest representation by the Streptomyces genus both in the total microbial community composition and in the microbial diversity related to GH families of predicted ORFs. Moreover, the functional clustering of the predicted ORFs showed a prevalence of poorly characterized genes, suggesting these lignocellulosic biomasses are potential sources of as yet unknown genes. 1.2%, 0.6% and 3.4% of the total ORFs detected in A. donax, E. camaldulensis and P. nigra, respectively, were putative Carbohydrate-Active Enzymes (CAZymes). Interestingly, the glycoside hydrolases abundance in P. nigra (1.8%) was higher than that detected in the other biomasses investigated in this study. Moreover, a high percentage of (hemi)cellulases with different activities and accessory enzymes (mannanases, polygalacturonases and feruloyl esterases) was detected, confirming that the three analyzed samples were a reservoir of diversified biocatalysts required for an effective lignocellulose saccharification.</AbstractText>
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