Exploring AI-2-mediated interspecies communications within rumen microbial communities

Abstract

Background The rumen is an ecosystem with a complex microbial microflora in which microbes initiate biofilm formation by attaching to plant surfaces for plant degradation and are capable of converting feed to nutrients and energy via microbial processes. Quorum sensing (QS) is a cell-to-cell communication mechanism that allows microbes to synchronize the expression of multiple genes in the group to perform social behaviors such as chemotaxis and biofilm formation using self-synthesized QS signaling molecules. Whereas QS has been extensively studied in model microorganisms under pure culture conditions, QS mechanisms are poorly understood in complex bacterial communities, such as the rumen microflora, in which cell-to-cell communication may be common. Results Here, we analyzed 981 rumens bacterial and archaeal genomes from the Joint Genome Institute (JGI) and GenBank databases and identified 15 types of known QS signaling molecule-related genes. The analysis of the prevalence and abundance of genes involved in QS showed that 767 microbial genomes appeared to possess QS-related genes, including 680 bacterial genomes containing autoinducer-2 (AI-2) synthase- or receptor-encoding genes. Prevotella, Butyivibrio, Ruminococcus, Oribacterium, Selenomonas, and Treponema, known abundant bacterial genera in the rumen, possessed the greatest numbers of AI-2-related genes; these genes were highly expressed within the metatranscriptome dataset, suggesting that intra- and interspecies communication mediated by AI-2 among rumen microbes was universal in the rumen. The QS processes mediated by the dCache_1-containing AI-2 receptors (CahRs) with various functional modules may be essential for degrading plants, digesting food, and providing energy and nutrients to the host. Additionally, a universal natural network based on QS revealed how rumen microbes coordinate social behaviors via the AI-2-mediated QS system, most of which may potentially function via AI-2 binding to the extracellular sensor dCache_1 domain to activate corresponding receptors involved in different signal transduction pathways, such as methyl-accepting chemotaxis proteins, histidine kinases, serine phosphatases, c-di-GMP synthases and phosphodiesterases, and serine/threonine kinases in the rumen. Conclusions The exploration of AI-2-related genes, especially CahR-type AI-2 receptors, greatly increased our insight into AI-2 as a potentially “universal” signal mediating social behaviors and will help us better understand microbial communication networks and the function of QS in plant-microbe interactions in complex microecosystems.

Deciphering and Constructing the Quorum Sensing Language “Interpreter” Ecosystem for Microbial Community

“…Generally, microbes communicate with each other via diverse QS signals that act as microbial languages [48,49], such as acyl-homoserine lactones (AHLs), indole, autoinducing peptides (AIPs), 4hydroxy-2-alkylquinolines (HAQs), and autoinducer-2 (AI-2), to realize similar functions like bio lm development and virulence [32,50]. In a previous study, we had constructed a comprehensive database (QSHGM) and the corresponding undirected QS communication network (QSCN) for human gut microbes for the rst time [51].…”

— Invited Review — Chemical signalling within the rumen microbiome

“…The variability of results in the above-mentioned experi ments highlights the need to employ both culture-dependent and culture-independent methods for investigating QS in the rumen. Indeed, numerous studies have now utilised genomic, metagenomic, or metatranscriptomic analysis, revealing a large diversity of potential QS mechanisms within the rumen [ 6 , 23 , 24 ]. For example, the advent of the Hungate collection, which sequenced 410 rumen bacteria and 21 archaea isolate cultures, allowed the mining of these genomes against known QS genes [ 23 , 32 ].…”

“…Interestingly, this Citrobacter species genome also contained luxS and luxR genes representing the potential to engage in multiple QS systems, i.e., both AHL and AI-2 [ 23 ]. Liu et al [ 24 ] expanded this mining of rumen genomes to include 948 bacterial genomes and 33 archaeal genomes, sourced from Shi et al [ 33 ], Gharechahi et al [ 34 ], and GenBank [ 35 ]. In this study they found more extensive evidence of AHL QS, with 5 archaeal genomes (all from the genus Methanobrevibacter ) and 58 bacterial genomes containing AHL genes, mainly harboured by the following orders; Eubacteriales, Bacteroidia, Clostridiales, and Selenomonadales [ 24 ].…”

“…In the same study, metatranscriptomic datasets were prospected and showed that LuxS proteins were the most widespread followed by LuxR, while the LuxS synthase was highly expressed by Prevotella species [ 23 ]. Similarly, AI-2 genes were identified as highly expressed using metatranscriptomic based methods by Liu et al [ 24 ]. This study also detected that AI-2 genes are widespread across rumen bacterial genomes, with 680 out of the 948 ruminal bacteria genomes mined containing AI-2 genes, including the following genera of bacteria; Prevotella , Butyrivibrio , Ruminococcus , Oribacterium , Selenomonas , and Treponema genera [ 24 ].…”

Exploring the Microbial Diversity and Characterization of Cellulase and Hemicellulase Genes in Goat Rumen: A Metagenomic Approach

“…Ruminant's rumen houses dense and complex community of symbiotic microbes that work together to break down lignocellulose [6]. These rumen microbial communities are perceived as the most potential biochemical reservoir of inordinately diverse and multi-functional cellulolytic enzymes with peculiar functional adaptation to enhance green biotechnological processes [7]. Bacterial community dominates the ruminal environment and hence considered as the most efficient biomass degrading enzymes in the herbivore gut microbiome.…”