Linking microbial identity to hydrolytic activity in anaerobic digestion systems processing lignocellulose-rich substrates

Background: Hydrolytic bacteria are a critical part of the anaerobic digester (AD) microbiome, but little is known about the specific organisms performing this conversion. Studying the hydrolytic activity in AD and linking this to microbial identity is therefore essential to obtain a more comprehensive understanding about the microbial ecology in engineered AD systems, and to develop management strategies to secure high VS-degradation.Results: Cellulase and xylanase activities were successfully monitored with a new fluorometric enzymatic assay. Samples from running lab-scale reactors, inoculated with sludge- or manure-base full-scale digesters, were used in the analysis. The reactors were fed with a substrate mixture of slurry and downsized wheat-straw representative of lignocellulose-rich material. The microbial communities showed adaptation to the substrate, observed from the enzymatic activities, but also mirrored in the methane production. The cellulolytic and xylanolytic activities were determined using MUF-labelled compounds and the enzyme expression was affected by the straw-feedings. The cellulolytic activities increased as much as 1700%, whereas minor responses were observed for the xylanolytic activities. The microbial community compositions were determined using 16S rRNA gene amplicon sequencing and Firmicutes, Bacteroidetes, and Cloacimonetes were the dominating phyla. A number of microorganisms correlated positively to the enzymatic activities including Fastidiospila and Ruminiclostridium. The individual reactors harbored functionally redundant communities, securing parallel pathways to catalyze the degradation. Conclusion: This study presents a fluorometric method to monitor enzymatic activities in samples from AD reactors. Microbial communities from different inocula adapted to degrade lignocellulose-rich substrate, which was reflected in the development of the enzymatic activities and the methane production. Correlation of the enzymatic data with amplicon sequencing data allowed identification of potential hydrolytic microorganisms.