Metagenomic and bioanalytical insights into quorum sensing of methanogens in anaerobic digestion systems with or without the addition of conductive filter

Understanding microbial interactions in the methanogenesis system through quorum sensing (QS) is very important for system optimization. Known QS genes were collected and classified into seven groups based on the signal molecules, which were used for constructing a hierarchical quorum sensing database (QSDB). QSDB containing 39,981 QS genes of seven QS groups was constructed and QS genes were analyzed with QSDB. Melhanogen genomes were aligned with QSDB and acyl-homoserine lactones (AHLs) system was predicted as the most probable QS system. This database was further applied to analyze QS in methanogens from two upflow anaerobic sludge blanke-anaerobic filter hybrid reactors with conductive filter (CUB) and nonconductive filter (SEP), and a control without filter (CON). The maximum COD degradation rates in CFB (722.2 +/- 10.1 mg/L.h) was elevated by 42.9% compared to CON (505.4 +/- 5.98 mg/L. h). Metagenomic sequencing revealed Methanosaeta, Methanobacterium, and Methanosarcina were dominant, and the abundances was 4.3 times higher in the sludge of CFB compared to CON. The overall abundance of QS genes was CFB > SEP > CON, and AHLs were the most abundant group of QS genes. The fill/filR system, a luxI/luxR homolog, was firstly detected in methanogens, showing a high abundance in the CFB (0.085%) compared to in the CON (0.058%). The concentration of AHL molecules in CFB biofilms (0.04%) was about four times that in the CON (0.01%). Syntrophobacter and Smithella were the two major syntrophic bacteria of methanogens, and their abundances were positively correlated with methanogens. In addition, Syntrophobacter and Smithella harbored QS RpfB (component of the diffusible signal factor system) and PDE (component of cyclic di-GMP system). This study provides useful guidance for deeply understanding of QS in anaerobic digestion systems. (C) 2020 Elsevier B.V. All rights reserved.

Automated summary

Understanding microbial interactions in the methanogenesis system through quorum sensing (QS) is crucial for system optimization. In this study, a hierarchical quorum sensing database (QSDB) was constructed and analyzed to predict the AHLs system as the most probable QS system in methanogens. Additionally, the fill/filR system, a luxI/luxR homolog, was detected in methanogens for the first time, showing a higher abundance in certain reactors.