Linking mixed microbial community phenotype to individual genotypes

Biological wastewater treatment is arguably the most widely used biotechnological process on Earth. Wastewater also represents a valuable energy commodity that is currently not being harnessed comprehensively. Mixed microbial communities that naturally occur at the air-water interface of certain biological wastewater treatment systems accumulate excess long chain fatty acids intracellularly. This phenotypic trait may potentially be exploited for the transformation of lipid-rich wastewater into biodiesel (fatty acid methyl esters). Using a molecular Eco-Systems Biology approach, we are studying which genes contribute to the lipid accumulation phenotype and, thus, overall community function. We first compared the lipid accumulation phenotype to the structure of lipid accumulating communities from a local wastewater treatment plant by coupled deep sequencing of the 16S rRNA locus, metagenome sequencing and metabolomic analysis of 4 biological replicates sampled at 4 different time points. Based on the results of these analyses and in order to obtain a detailed view of the structure and function of the respective microbial communities, metagenomic, metatranscriptomic, metaproteomic and (meta-)metabolomic analyses were completed for a single representative biological sample of highest interest. In order to facilitate meaningful data integration of this highly heterogeneous consortium, biomolecular fractions used for the omic analyses were extracted from a unique single sample using a recently developed biomolecular isolation protocol. The coupled survey and the comparative metagenomic analysis demonstrate that the communities change significantly from dates with warm water temperatures to cold water temperatures while alpha diversity remains stable. In the winter period, this switch results in a strong enrichment of a bacterial genus well known to accumulate intracellular lipids, namely Microthrix spp., a representative genome of which has recently been sequenced by us. Correlation networks based on microorganism and concomitant intra- and extra-cellular metabolite abundances provides an overview of organisms potentially involved in the community-wide lipid accumulating phenotype. A sample with the highest abundance of Microthrix spp. was subsequently chosen for the construction of a community-wide metabolic model using metagenomic, metatranscriptomic, metaproteomic and (meta-)metabolomics data. Based on these omic datasets, expressed enzyme variants linked to the lipid accumulation phenotype have been identified and are currently undergoing in vitro characterization. Meta-omic analyses offer exciting prospects for elucidating the genetic blueprints and the functional relevance of specific populations within microbial communities. Consequently, connecting the overall community phenotype to specific genotypes will allow much needed fundamental ecological understanding of microbial community and population dynamics, particularly in relation to environment-driven demography changes leading to tipping points and catastrophic bifurcations