Exploring microbial structure and carbohydrate metabolism of thermophilic anaerobic cellulose-degrading consortia by metagenomics based on next generation sequencing

Abstract

The pressing need for clean renewable energy sources has aroused worldwide research interest on the exploration of biofuels produced from lignocellulosic feedstock (e.g. forestry or agricultural residues and municipal wastes). The general absence of cost-effective method to overcome the recalcitrant nature of cellulosic biomass is the major challenge for the industrialization of this so-called second-generation biofuel. With the purpose to enhance our understanding of the fundamental mechanism of thermophilic microbial cellulose conversion process, we used culture-independent metagenomic analysis based on Next Generation Sequencing to explore the physiological ecology of thermophilic cellulolytic microbial community and more importantly to discover metabolic potentials.

During the enrichment of thermophilic cellulolytic consortium, noticeable effects of co-substrate and pH was observed and subsequently investigated. Based on the community structure revealed by 16S rRNA gene sequencing at various pH values, we concluded that keeping pH higher than 6.0 was crucial to maintain effective cellulose conversion because the growth of Thermoanaerobacterium over other more efficient cellulolytic populations could be practically avoided.

Given in mind that uncharacterized microbial populations may possess critical enzymatic components that are essential for the breakdown of cellulosic feedstock, gene-centric metagenomic pipeline was developed to discover genes that are functionally beneficial for thermophilic cellulose hydrolysis. Aside from that, metagenomic gene mining based on functional prediction using HMM (Hidden Markov Model) showed higher positive ratio in identifying novel carbohydrate-active genes than that of functional screening. Without cultivation, near complete genomes of the major thermophilic cellulose degraders were recovered from the metagenome by a gene binning pipeline combining tetranucleotide frequency based primary k-means clustering and subsequent scaffolding with paired-end relationship between two reads (sequences).

Furthermore, by quantifying the transcriptional activities of various carbohydrate-active genes in the metatranscriptome of the enriched thermophilic cellulose-degrading consortium, we disclosed significance of enzymes of GH09 and GH48 which had been underestimated by previous metagenomic studies. Eventually, metagenomic survey of various sludge samples collected at specific operational conditions helped to confirm the metabolism potential of thermophilic sludge in cellulose up taking by possessing more enzymes of GH05 and GH04 families.