Linking microbial communities, environmental factors and performance of biological treatment reactors using metagenomics

Abstract

The thesis was conducted to reveal the associations among microbial communities, environmental factors (i.e., operational and physicochemical conditions) and performance of biological treatment reactors of activated sludge (AS) and anaerobic digestion (AD) using metagenomics. Moreover, environmental and biological factors that govern microbiome assembly and population dynamics were examined with emphasis on core, functional and uncultured microorganisms. Additionally, occurrence of antibiotic resistance genes (ARGs) and human bacterial pathogens (HBPs) in digested sludge and their removal and dissemination during AD were evaluated.

Full-scale AS reactors in wastewater treatment plants (WWTPs) were extensively investigated both spatially (50 grab samples, 27 reactors, 17 cities) and temporally (58 monthly samples, 1 reactor, Hong Kong). Metagenomics and network analysis of spatio-temporal data show that AS bacterial communities are nonrandomly assembled by taxonomic relatedness, which is induced by multiple deterministic processes, including habitat filtering and competition. Moreover, bacterial communities in full-scale municipal AS reactor follow no apparent seasonal succession over five years and biological interactions dominate over environmental conditions (mainly sludge retention time (SRT) and inorganic nitrogen) in determining bacterial assembly and population dynamics. Additionally, a core set of cosmopolitan functional microorganisms (e.g., nitrogen-cycling-related bacteria) widely occur in globally distributed AS reactors.

Besides AS systems in WWTPs, performance of downstream AD reactors that receive primary and/or secondary sludge is also related with biological and environmental factors. First, multivariate, correlation and network analyses of three-year data of two full-scale municipal AD reactors show that methane production and percentage are significantly correlated (P-values ≤ 0.05) with environmental variables (i.e., pH, alkalinity and SRT) and species richness and/or evenness. It is proposed that deterministic (environmental and biological) and stochastic (i.e. random) processes may co-drive microbial community assembly. Moreover, AD is demonstrated as an efficient process for methanogenesis from chemically enhanced primary treatment (CEPT) sludge. Its efficiency is significantly affected (P-values ≤ 0.05) by SRT, organic loading rate (OLR) and FeCl3 dosing. However, nature and seeding effect of feed sludge and interspecific competition dominate over tested differences of SRT (7 to 16 days) and OLR in shaping microbial dynamics and assembly. Additionally, most ARGs and a few HBPs (e.g., C. aerofaciens, S. Salivarius and G. bronchialis) are not effectively removed by AD, revealing a potential biological risk of digested sludge in disseminating antibiotic resistance and pathogenicity.

Last, comparative genomics of 23 prokaryotic genomes reconstructed from phenol-degrading methanogenic reactors reveals that temperature difference induced colonization of sulfate/sulfite/sulfur (20oC) or nitrate/nitrite-respiring (37℃) sub-communities as competitors of methanogens, which differentiates methanogenesis from phenol. The discovery of interspecific competition justifies attempts towards biological manipulation for maximizing methanogenesis in anaerobic reactors.

Combined, this thesis presents a large-scale metagenomic exploration of spatio-temporal “microbiome-environment-performance” association. Metagenomics and network analysis are demonstrated as effective approaches to disclose the intricate microbial mechanisms that deteriorate, maintain and advance biological treatment performance and stability. These two “open-ended” approaches have also put forward a number of novel hypotheses (e.g., those on microbial interactions and metabolic clues for isolation of uncultured microbes) which require validation via design of hypothesis-driven studies using high-throughput multi-omics approaches.