Using metagenomics and metatranscriptomics to study specific bacterial species involved in biological phosphorus removal from wastewater

Examining the complete gene expression of unculturable bacteria in complex communities has been the dream of microbial ecologists for years. However, a major obstacle is the recovery of a reliable template, the relevant genomes from the communities. While metagenomics has been proposed to solve the problem, it is extremely rare to be able to recover high quality genomes from complex samples. This is not due to lack of sequencing depth, but the presence of multiple closely related species, which prevents decent genome assemblies.
In this work we show that a successful approach is to make an enrichment of the target organisms in laboratory scale reactors under controlled conditions. We demonstrate that it is now easy and affordable to extract genomes of all the dominant organisms from reactors due to reduced micro-diversity and further use these to examine their individual gene expression profiles by metatranscriptomics. To demonstrate this we revisited the bacteria involved in enhanced biological phosphorus removal (EBPR) from wastewater treatment plants. The EBPR process is used all over the world, has a large body of information regarding the underlying microbiology, and is often studied using laboratory scale reactors. However, conflicting evidence is often obtained for laboratory scale studies, likely due to difference in the microbial community composition, which is often not defined.
We investigated three laboratory scale reactors seeded with full-scale activated sludge and operated to enrich for bacteria contributing to phosphorus removal and their normal competitors. To extract complete genomes we generated two metagenomes from each reactor, taken approximately 1 month apart, using the Illumina HiSeq2000 platform. Due to low micro-diversity in the reactors (2-15 dominating species), most species assembled into few scaffolds that were subsequently binned to separate genomes using the two time-points through the multi-metagenome strategy. To investigate the individual gene expression of the dominant species in each reactor we designed a cycle study that mimicked the normal phosphorus removal process in the treatment plant, sampling every 20 min during the 9 hour experiment. Metratranscriptome data was generated from selected samples using the stranded RNAseq Illumina protocol.
We were able to extract genomes from the model polyphosphate accumulating organism (PAO) Ca. Accumilibacter, the putative PAO Tetrasphaera and the model competitors Defluviicoccus and Ca. Competibacter. The metatranscriptomes were subsequently used to annotate the genomes and finally shed light on many of the previous literature-based hypotheses regarding their physiologies. Interestingly, we also recovered a genome of an abundant bacteria closely related to Ca. Accumulibacter, which did not accumulate phosphate, i.e. a potential new competitor. Surprisingly, the bacteria was also hit by the Accumulibacter group-defining FISH probe (PAOmix) and would thereby mistakenly lead to an overestimation of the abundance of PAOs in treatment plants. In full-scale metagenomes, the Accumulibacter-related putative competitor was often found in higher abundance than Ca. Accumulibacter.
In conclusion, it is now feasible to generate genomes and subsequent individual transcriptomes from laboratory scale reactors, which provides an opportunity for unprecedented levels of insight into the competition and cooperation between unculturable species.