Intregrated multi-omics of oleaginous microbial consortia in biological wastewater treatment plants

Mixed microbial communities in biological wastewater treatment plants (BWWTPs) represent complex and dynamic systems. A predictive understanding of oleaginous population dynamics is required to guarantee stable process operation and/or to recover lipids from wastewater streams for subsequent biofuel synthesis. We have prioneered an integrative methodological framework comprising wet- and dry-lab methods to enable systematic molecular measurements (comprising metagenomics, metatranscriptomics, metaproteomics and metabolomics) of microbial communities over space and time, and the integration and analysis of the resulting multi-omic data. Two distinct approaches have been developed for the deconvolution of the multi-omic data at the population- or community-level. Through our population-level analysis, we have uncovered patterns, which indicate that the dominance of the microbial generalist and known lipid accumulator, Candidatus Microthrix parvicella, is linked to finely tuned substrate usage. Single-cell analyses demonstrate that the apparent phenotypic heterogeneity within this population is an adaptation to the rapidly changing environmental conditions encountered in BWWTPs. Furthermore, the analysis of reconstructed metabolic networks has resulted in the identification of “keystone genes” which are encoded and expressed by distinct “keystone populations”. By further integrating and analyzing multi-omic data together with operational and environmental information collected longitudinally, we are now able to identify the specific biotic and abiotic factors which drive community dynamics. By integrating information from genome to metabolome, integrated multi-omics allows the deconvoluton of structure-function relationships by identifying key members and functionalities. In the context of BWWTs, identified keystone species and/or genes likely represent driver nodes which may be exploited for future control strategies.