Microbial dark matter ecogenomics reveals complex synergistic networks in a methanogenic bioreactor

Abstract

Ecogenomic investigation of a methanogenic bioreactor degrading terephthalate (TA) allowed elucidation of complex synergistic networks of uncultivated microorganisms, including those from candidate phyla with no cultivated representatives. Our previous metagenomic investigation proposed that Pelotomaculum and methanogens may interact with uncultivated organisms to degrade TA; however, many members of the community remained unaddressed because of past technological limitations. In further pursuit, this study employed state-of-the-art omics tools to generate draft genomes and transcriptomes for uncultivated organisms spanning 15 phyla and reports the first genomic insight into candidate phyla Atribacteria, Hydrogenedentes and Marinimicrobia in methanogenic environments. Metabolic reconstruction revealed that these organisms perform fermentative, syntrophic and acetogenic catabolism facilitated by energy conservation revolving around H 2 metabolism. Several of these organisms could degrade TA catabolism by-products (acetate, butyrate and H 2 ) and syntrophically support Pelotomaculum. Other taxa could scavenge anabolic products (protein and lipids) presumably derived from detrital biomass produced by the TA-degrading community. The protein scavengers expressed complementary metabolic pathways indicating syntrophic and fermentative step-wise protein degradation through amino acids, branched-chain fatty acids and propionate. Thus, the uncultivated organisms may interact to form an intricate syntrophy-supported food web with Pelotomaculum and methanogens to metabolize catabolic by-products and detritus, whereby facilitating holistic TA mineralization to CO 2 and CH 4 .

Phylogeny and physiology of candidate phylum ‘Atribacteria’ (OP9/JS1) inferred from cultivation-independent genomics

“…Further supporting a role in propionate catabolism, metatranscriptomics of the TA-degrading community revealed the expression of 'Ca. Atricorium' genes potentially involved in propionate degradation via the methylmalonyl-CoA (Mmc) pathway (Nobu et al, 2015b). Members of both JS1-1 and JS1-2 lineages encode Mmc mutase, epimerase and decarboxylase (alpha subunit) genes with high similarity (470, 70 and 60%, respectively) to those from a representative thermophilic propionatedegrading syntroph, Pelotomaculum thermopropionicum strain SI (Imachi et al, 2002), along with other genes that could enable conversion of propionate to pyruvate (Supplementary Figure S13).…”

“…Moreover, they possess complementary energy conservation genes for facilitating thermodynamically limited disposal of reducing power derived from syntrophic propionate catabolism (Figure 4c). Specifically, an electron-bifurcating formate dehydrogenase (EBFdh, containing Fdh and HylABC, where Fdh and HylA are fused; Supplementary Table S5) and membranebound hydrogenase could serve as potential mechanisms for energy-conserving formate (Wang et al, 2013) and H 2 production (Vignais and Colbeau, 2004) possibly involved in syntrophic metabolism, based on identification of homologues in Pelobacter carbinolicus (Nobu et al, 2015b) and Moorella thermoacetica (Pierce et al, 2008). Succinate dehydrogenase and NADH:Nqo may also be involved in energy conservation, allowing for reduction of NAD + by reduced flavin produced in propionate catabolism by the Mmc pathway (Figure 4c).…”

“…Notably, many of these environments, such as the TA reactor (Nobu et al, 2015b), Etoliko Lagoon sediment (Chamalaki et al, 2014) and Sakinaw Lake monimolimnion (Gies et al, 2014), contain considerable amounts of organic carbon but have relatively low availability of inorganic compounds suitable for use in anaerobic respiration and thus represent the so-called 'low-energy' ecosystems where fermentation and syntrophy are likely important metabolic strategies. These characteristics coincide with the potential catabolisms and lack of respiratory capacity predicted for the 'Atribacteria' lineages represented by the genomic data sets analysed in this study.…”

“…C. saccharofermentans' bin in the 77CS metagenome was refined using Metawatt and manually filtered based on contig coverage profile, retaining contigs with coverage values from 170 to 300. For PhylopythiaS, default settings were used and manual curation was performed based on average contig read depth, BLAST, principle component analysis of tetranucleotide frequency and the presence of single-copy conserved markers (SCMs; Nobu et al, 2015b). For ESOM, metagenome contigs were split into 2500-bp long sequences with a window size of 5000 bp, and tetranucleotide frequencies were calculated for these sequences using tetramer_freqs_esom.pl (https:// github.com/tetramerfreqs/binning).…”

Metagenomic analysis of rapid gravity sand filter microbial communities suggests novel physiology ofNitrospiraspp.

“…In the era of next-generation sequencing techniques, metagenomics-based approaches have enabled the discovery of a suite of novel microbial pathways (Schleper et al, 2005;Bryant et al, 2007;Ettwig et al, 2010;Carrión et al, 2015) and the expansion of the tree of life (Brown et al, 2015). Some of these discoveries have been made in technical systems; for example, novel candidate phyla and expanded metabolic versatility have been identified in aerobic and anaerobic bioreactors (Wexler et al, 2005;Rinke et al, 2013;Nobu et al, 2015).…”