Optimizing bioreactor performance for organic matter removal can achieve sustainable and energy-efficient micropollutant removal in subsequent tertiary treatment. Bioreactor performance heavily depends on its resident microbial community; hence, a deeper understanding of community dynamics is essential. The microbial communities of three different bioreactors (biological activated carbon, moving bed biofilm reactor, sand filter), used for organic matter removal from wastewater treatment effluent, were characterized by 16S rRNA gene amplicon sequence analysis. An interdependency between bioreactor performance and microbial community profile was observed. Overall, Proteobacteria was the most predominant phylum, and Comamonadaceae was the most predominant family in all bioreactors. The relative abundance of the genus Roseococcus was positively correlated with organic matter removal. A generalized Lotka-Volterra (gLV) model was established to understand the interactions in the microbial community. By identifying microbial dynamics and their role in bioreactors, a strategy can be developed to improve bioreactor performance.

Natural microbial communities are composed of a large diversity of interacting microorganisms, each with a specific role in the functional properties of the ecosystem. The objectives in microbial ecology research are related to identifying, understanding and exploring the role of these different microorganisms. Because of the rapidly increasing power of DNA sequencing and the rapid increase of genomic data, main attention of microbial ecology research shifted from cultivation-oriented studies towards metagenomic studies. Despite these efforts, the direct link between the molecular properties and the measurable changes in the functional performance of the ecosystem is often poorly documented. A quantitative understanding of functional properties in relation to the molecular changes requires effective integration, standardization, and parallelization of experiments. High-resolution functional characterization is a prerequisite for interpretation of changes in metagenomic properties, and will improve our understanding of microbial communities and facilitate their exploration for health and circular economy related objectives.

Anaerobic oxidation of methane (AOM) is catalyzed by anaerobic methane-oxidizing archaea (ANME) via a reverse and modified methanogenesis pathway. Methanogens can also reverse the methanogenesis pathway to oxidize methane, but only during net methane production (i.e., "trace methane oxidation"). In turn, ANME can produce methane, but only during net methane oxidation (i.e., enzymatic back flux). Net AOM is exergonic when coupled to an external electron acceptor such as sulfate (ANME-1, ANME-2abc, and ANME-3), nitrate (ANME-2d), or metal (oxides). In this review, the reversibility of the methanogenesis pathway and essential differences between ANME and methanogens are described by combining published information with domain based (meta)genome comparison of archaeal methanotrophs and selected archaea. These differences include abundances and special structure of methyl coenzyme M reductase and of multiheme cytochromes and the presence of menaquinones or methanophenazines. ANME-2a and ANME-2d can use electron acceptors other than sulfate or nitrate for AOM, respectively. Environmental studies suggest that ANME-2d are also involved in sulfate-dependent AOM. ANME-1 seem to use a different mechanism for disposal of electrons and possibly are less versatile in electron acceptors use than ANME-2. Future research will shed light on the molecular basis of reversal of the methanogenic pathway and electron transfer in different ANME types.