Characterization of cellulose-degrading microbiota from the eastern subterranean termite and soil

Abstract

Background: While there have been a lot of studies on the termite gut microbiota, there has been very little research directly on the cellulose-degrading microbiota in termites or their soil environment. This study addresses this problem by profiling cellulose-degrading bacteria and archaea in the selective cellulose cultures of two samples of the eastern subterranean termite (Reticulitermes flavipes) and one soil sample collected at the same location as one of the termite samples. Methods: All the cultures were examined for cell concentration and remaining cellulose after the culture was completed. The 16S rRNA pyrotag sequencing method was used to identify the prokaryotic microbiota for the three cultures and one termite colony without culture. The MOTHUR, SSU-ALIGN, RDPTools, phyloseq, and other R packages were used for sequence and statistical analyses. Results: Biochemical analyses of the cultures suggested high efficiency of cellulose degradation. Comparative analyses between the cultured and uncultured termite gut microbiota revealed a significant difference. Proteobacteria and Firmicutes were found to be the two most abundant phyla of cellulose-degrading bacteria from the three cultures, but different classes within each phylum dominated the different samples. Shared and sample-specific cellulose-degrading taxa, including a core set of taxa across all the cultures, were identified. Conclusions: Our study demonstrates the importance of using selective cellulose culture to study the cellulose-degrading microbial community. It also revealed that the cellulose-degrading microbiota in the eastern subterranean termite is significantly influenced by the microbiota in the surrounding soil environment. Biochemical analyses showed that the microbial communities enriched from all the selective cultures were efficient in degrading cellulose, and a core set of bacteria have been identified as targets for further functional analyses.