Nd designed the experiments: PS SS TPS. Performed the experiments: PS DD MS. Analyzed the data: PS SS TPS. Contributed reagents/materials/analysis tools: PK SY. Wrote the paper: SS TPS.
Second generation of biofuels derived from FGF-401 chemical information lignocellulosic plant biomass represent an important renewable alternative for fossil fuels [1]. Lack of cost-effective technology to overcome the recalcitrant nature of the lignocellulosic substrate impediments its industrial-scale production. Enzymatic deconstruction of plant biomass which could greatly improve lignocellulose hydrolysis with no side-effect of generating fermentation inhibitors was applied as a promising strategy in the popular lignocellulosic biofuel production processes like Simultaneous Saccharification and Fermentation (SSF) or Separate Saccharification and Fermentation (SHF) [2]; nevertheless the relatively low activity of currently available hydrolytic enzymes stands in the way. Thereby retrieving novel effective cellulolytic enzymes from biomass-degrading microbial community is of great potential to boost lignocellulosic biofuel production and the thermo-stable cellulase was especially attractive 25331948 in this concept for its suitability for industrial application. Metagenomics, direct analysis of DNA fragments from environmental sample, offers a powerful tool to understand microbial consortium and to discover diverse genes/enzymes in the system. Metagenome-derived cellulase has been successfully identified and isolated from cellulolytic consortia in several studies [3?]. However before the widely introduction of next generationsequencing (NGS) technologies in recent 10 years, metagenomic library construction by cloning was a heavy labor job which EW-7197 biological activity suffered from the difficulty in discovery of whole genes. Nowadays with the help of the dramatically increased sequencing depth of NGS, metagenomic had stepped into a new chapter that vast gene mining become literally possible. However, among the various metagenomic studies, a good many of them merely focused on community structure characterization, for example the metagenomic characterization of natural ecosystems like the ocean [8], soil [9], permafrost [10], etc. Although several work had demonstrated great practice in metagenomic gene discovery, for example metagenomic biomass-degrading gene discovery from cow rumen and termite gut[11?3], the field of NGS metagenomic gene mining still at its infancy with many potential sources untapped. In addition, metagenomic projects with NGS technologies are now severely challenging the current computational resources. While not mutually exclusive, there are few alternative methods to ensure coverage completeness of a complicated communities other than enlarging sequencing depth which, due to the giant data set required, may bring up the processing and computational cost to more than a million dollars for a metagenomic project, for instance, it was estimated that a minimum of 6 billion base pairs would be required to obtain the genome sequence of the mostMetagenomic Mining of Cellulolytic Genesdominant population in soil sample, and many times more to obtain genomes from less dominant populations [14]. By contrast, metagenomics of reactors with certain intentionally enhanced functions, for example, enhanced biological phosphorus removal reactor (EBPR), cellulose-degrading reactor, phenol decomposing reactor, sludge digester etc., makes more practical sense for most research institutions lack of such admirable.Nd designed the experiments: PS SS TPS. Performed the experiments: PS DD MS. Analyzed the data: PS SS TPS. Contributed reagents/materials/analysis tools: PK SY. Wrote the paper: SS TPS.
Second generation of biofuels derived from lignocellulosic plant biomass represent an important renewable alternative for fossil fuels [1]. Lack of cost-effective technology to overcome the recalcitrant nature of the lignocellulosic substrate impediments its industrial-scale production. Enzymatic deconstruction of plant biomass which could greatly improve lignocellulose hydrolysis with no side-effect of generating fermentation inhibitors was applied as a promising strategy in the popular lignocellulosic biofuel production processes like Simultaneous Saccharification and Fermentation (SSF) or Separate Saccharification and Fermentation (SHF) [2]; nevertheless the relatively low activity of currently available hydrolytic enzymes stands in the way. Thereby retrieving novel effective cellulolytic enzymes from biomass-degrading microbial community is of great potential to boost lignocellulosic biofuel production and the thermo-stable cellulase was especially attractive 25331948 in this concept for its suitability for industrial application. Metagenomics, direct analysis of DNA fragments from environmental sample, offers a powerful tool to understand microbial consortium and to discover diverse genes/enzymes in the system. Metagenome-derived cellulase has been successfully identified and isolated from cellulolytic consortia in several studies [3?]. However before the widely introduction of next generationsequencing (NGS) technologies in recent 10 years, metagenomic library construction by cloning was a heavy labor job which suffered from the difficulty in discovery of whole genes. Nowadays with the help of the dramatically increased sequencing depth of NGS, metagenomic had stepped into a new chapter that vast gene mining become literally possible. However, among the various metagenomic studies, a good many of them merely focused on community structure characterization, for example the metagenomic characterization of natural ecosystems like the ocean [8], soil [9], permafrost [10], etc. Although several work had demonstrated great practice in metagenomic gene discovery, for example metagenomic biomass-degrading gene discovery from cow rumen and termite gut[11?3], the field of NGS metagenomic gene mining still at its infancy with many potential sources untapped. In addition, metagenomic projects with NGS technologies are now severely challenging the current computational resources. While not mutually exclusive, there are few alternative methods to ensure coverage completeness of a complicated communities other than enlarging sequencing depth which, due to the giant data set required, may bring up the processing and computational cost to more than a million dollars for a metagenomic project, for instance, it was estimated that a minimum of 6 billion base pairs would be required to obtain the genome sequence of the mostMetagenomic Mining of Cellulolytic Genesdominant population in soil sample, and many times more to obtain genomes from less dominant populations [14]. By contrast, metagenomics of reactors with certain intentionally enhanced functions, for example, enhanced biological phosphorus removal reactor (EBPR), cellulose-degrading reactor, phenol decomposing reactor, sludge digester etc., makes more practical sense for most research institutions lack of such admirable.