Quorum sensing (QS) signalling has been extensively studied in single species populations. However, the ecological role of QS in complex, multi-species communities, particularly in the context of community assembly, has neither been experimentally explored nor theoretically addressed. Here, we performed a long-term bioreactor ecology study to address the links between QS, organization and composition of complex microbial communities. The conversion of floccular biomass to highly structured granules was found to be non-random, but strongly and positively correlated with N-acyl-homoserine-lactone (AHL)-mediated QS. Specific AHLs were elevated up to 100-fold and were strongly associated with the initiation of granulation. Similarly, the levels of particular AHLs decreased markedly during the granular disintegration phase. Metadata analysis indicated that granulation was accompanied by changes in extracellular polymeric substance (EPS) production and AHL add-back studies also resulted in increased EPS synthesis. In contrast to the commonly reported nanomolar to micromolar signal concentrations in pure culture laboratory systems, QS signalling in the granulation ecosystem occurred at picomolar to nanomolar concentrations of AHLs. Given that low concentrations of AHLs quantified in this study were sufficient to activate AHL bioreporters in situ in complex granular communities, AHL mediated QS may be a common feature in many natural and engineered ecosystems, where it coordinates community behaviour.

BackgroundThere are numerous computational tools for taxonomic or functional analysis of microbiome samples, optimized to run on hundreds of millions of short, high quality sequencing reads. Programs such as MEGAN allow the user to interactively navigate these large datasets. Long read sequencing technologies continue to improve and produce increasing numbers of longer reads (of varying lengths in the range of 10k-1M bps, say), but of low quality. There is an increasing interest in using long reads in microbiome sequencing, and there is a need to adapt short read tools to long read datasets.MethodsWe describe a new LCA-based algorithm for taxonomic binning, and an interval-tree based algorithm for functional binning, that are explicitly designed for long reads and assembled contigs. We provide a new interactive tool for investigating the alignment of long reads against reference sequences. For taxonomic and functional binning, we propose to use LAST to compare long reads against the NCBI-nr protein reference database so as to obtain frame-shift aware alignments, and then to process the results using our new methods.ResultsAll presented methods are implemented in the open source edition of MEGAN, and we refer to this new extension as MEGAN-LR (MEGAN long read). We evaluate the LAST+MEGAN-LR approach in a simulation study, and on a number of mock community datasets consisting of Nanopore reads, PacBio reads and assembled PacBio reads. We also illustrate the practical application on a Nanopore dataset that we sequenced from an anammox bio-rector community.ReviewersThis article was reviewed by Nicola Segata together with Moreno Zolfo, Pete James Lockhart and Serghei Mangul.ConclusionThis work extends the applicability of the widely-used metagenomic analysis software MEGAN to long reads. Our study suggests that the presented LAST+MEGAN-LR pipeline is sufficiently fast and accurate.

Background Short-read sequencing technologies have long been the work-horse of microbiome analysis. Continuing technological advances are making the application of long-read sequencing to metagenomic samples increasingly feasible. Results We demonstrate that whole bacterial chromosomes can be obtained from an enriched community, by application of MinION sequencing to a sample from an EBPR bioreactor, producing 6 Gb of sequence that assembles into multiple closed bacterial chromosomes. We provide a simple pipeline for processing such data, which includes a new approach to correcting erroneous frame-shifts. Conclusions Advances in long-read sequencing technology and corresponding algorithms will allow the routine extraction of whole chromosomes from environmental samples, providing a more detailed picture of individual members of a microbiome. Electronic supplementary material The online version of this article (10.1186/s40168-019-0665-y) contains supplementary material, which is available to authorized users.