Microbial invasions in sludge anaerobic digesters

Microbial community assembly in engineered bioreactors

Microbial community assembly (MCA) processes that shape microbial communities in environments are being used to analyze engineered bioreactors such as activated sludge systems and anaerobic digesters. The goal of studying MCA is to be able to understand and predict the effect of design and operation procedures on bioreactor microbial composition and function. Ultimately, this can lead to bioreactors that are more efficient, resilient, or resistant to perturbations. This review summarizes the ecological theories underpinning MCA, evaluates MCA analysis methods, analyzes how these MCA-based methods are applied to engineered bioreactors, and extracts lessons from case studies. Furthermore, we suggest future directions in MCA research in engineered bioreactor systems. The review aims to provide insights and guidance to the growing number of environmental engineers who wish to design and understand bioreactors through the lens of MCA.

Mechanisms Driving Microbial Community Composition in Anaerobic Co-Digestion of Waste-Activated Sewage Sludge

Anaerobic co-digestion (Co-AD) is used to increase the effectiveness of anaerobic digestion (AD) using local “wastes”, adding economic and environmental benefits. Since system stability is of existential importance for the operation of wastewater treatment plants, thorough testing of potential co-substrates and their effects on the respective community and system performance is crucial for understanding and utilizing Co-AD to its best capacity. Food waste (FW) and canola lecithin (CL) were tested in mesophilic, lab-scale, semi-continuous reactors over a duration of 120 days with stepwise increased substrate addition. Key performance indicators (biogas, total/volatile solids, fatty acids) were monitored and combined with 16S-rRNA amplicon sequencing to assess the impact of co-substrate addition on reactor performance and microbial community composition (MCC). Additionally, the latter was then compared with natural shifts occurring in the wastewater treatment plant (WWTP, source) at the same time. An almost linear increase in biogas production with both co-substrates at an approximate 1:1 ratio with the organic loading rate (OLR) was observed. The MCCs in both experiments were mostly stable, but also prone to drift over time. The FW experiment MCC more closely resembled the original WWTP community and the observed shifts indicated high levels of functional redundancy. Exclusive to the CL co-substrate, a clear selection for a few operational taxonomic units (OTUs) was observed. There was little evidence for a persistent invasion and establishment of microorganisms from typical primary substrates into the stable resident community of the reactors, which is in line with earlier findings that suggested that the inoculum and history mostly define the MCC. However, external factors may still tip the scales in favor of a few r-strategists (e.g., Prolixibacter) in an environment that otherwise favors K-strategists, which may in fact also be recruited from the primary substrate (Trichococcus). In our study, specialization and diversity loss were also observed in response to the addition of the highly specialized CL, which in turn, may have adverse effects on the system’s stability and reduced resilience and recovery.

Microbiome signature and diversity regulates the level of energy production under anaerobic condition

The microbiome of the anaerobic digester (AD) regulates the level of energy production. To assess the microbiome diversity and composition in different stages of anaerobic digestion, we collected 16 samples from the AD of cow dung (CD) origin. The samples were categorized into four groups (Group-I, Group-II, Group-III and Group-IV) based on the level of energy production (CH₄%), and sequenced through whole metagenome sequencing (WMS). Group-I (n = 2) belonged to initial time of energy production whereas Group-II (n = 5), Group-III (n = 5), and Group-IV (n = 4) had 21-34%, 47-58% and 71-74% of CH₄, respectively. The physicochemical analysis revealed that level of energy production (CH₄%) had significant positive correlation with digester pH (r = 0.92, p < 0.001), O₂ level (%) (r = 0.54, p < 0.05), and environmental temperature (°C) (r = 0.57, p < 0.05). The WMS data mapped to 2800 distinct bacterial, archaeal and viral genomes through PathoScope (PS) and MG-RAST (MR) analyses. We detected 768, 1421, 1819 and 1774 bacterial strains in Group-I, Group-II, Group-III and Group-IV, respectively through PS analysis which were represented by Firmicutes, Bacteroidetes, Proteobacteria, Actinobacteria, Spirochaetes and Fibrobacteres phyla (> 93.0% of the total abundances). Simultaneously, 343 archaeal strains were detected, of which 95.90% strains shared across four metagenomes. We identified 43 dominant species including 31 bacterial and 12 archaeal species in AD microbiomes, of which only archaea showed positive correlation with digester pH, CH₄ concentration, pressure and temperature (Spearman correlation; r > 0.6, p < 0.01). The indicator species analysis showed that the species Methanosarcina vacuolate, Dehalococcoides mccartyi, Methanosarcina sp. Kolksee and Methanosarcina barkeri were highly specific for energy production. The correlation network analysis showed that different strains of Euryarcheota and Firmicutes phyla exhibited significant correlation (p = 0.021, Kruskal-Wallis test; with a cutoff of 1.0) with the highest level (74.1%) of energy production (Group-IV). In addition, top CH₄ producing microbiomes showed increased genomic functional activities related to one carbon and biotin metabolism, oxidative stress, proteolytic pathways, membrane-type-1-matrix-metalloproteinase (MT1-MMP) pericellular network, acetyl-CoA production, motility and chemotaxis. Importantly, the physicochemical properties of the AD including pH, CH₄ concentration (%), pressure, temperature and environmental temperature were found to be positively correlated with these genomic functional potentials and distribution of ARGs and metal resistance pathways (Spearman correlation; r > 0.5, p < 0.01). This study reveals distinct changes in composition and diversity of the AD microbiomes including different indicator species, and their genomic features that are highly specific for energy production.

Relationships between community composition, productivity and invasion resistance in semi-natural bacterial microcosms

Common garden experiments that inoculate a standardised growth medium with synthetic microbial communities (i.e. constructed from individual isolates or using dilution cultures) suggest that the ability of the community to resist invasions by additional microbial taxa can be predicted by the overall community productivity (broadly defined as cumulative cell density and/or growth rate). However, to the best of our knowledge, no common garden study has yet investigated the relationship between microbial community composition and invasion resistance in microcosms whose compositional differences reflect natural, rather than laboratory-designed, variation. We conducted experimental invasions of two bacterial strains (Pseudomonas fluorescens and Pseudomonas putida) into laboratory microcosms inoculated with 680 different mixtures of bacteria derived from naturally occurring microbial communities collected in the field. Using 16S rRNA gene amplicon sequencing to characterise microcosm starting composition, and high-throughput assays of community phenotypes including productivity and invader survival, we determined that productivity is a key predictor of invasion resistance in natural microbial communities, substantially mediating the effect of composition on invasion resistance. The results suggest that similar general principles govern invasion in artificial and natural communities, and that factors affecting resident community productivity should be a focal point for future microbial invasion experiments.