Use of a hierarchical oligonucleotide primer extension approach for multiplexed relative abundance analysis of methanogens in anaerobic digestion systems

Comammox Nitrospira Species Dominate in an Efficient Partial Nitrification-Anammox Bioreactor for Treating Ammonium at Low Loadings

Bacteria capable of complete ammonia oxidation (comammox) are widespread and contribute to nitrification in wastewater treatment facilities. However, their roles in partial nitrification-anaerobic ammonium oxidation (anammox) systems remain unclear. In this study, a bench-scale bioreactor with continuous stirring was operated for more than 1000 days with limited oxygen supply to achieve efficient nitrogen removal (70.1 ± 2.7%) at a low ammonium loading of 35.2 mg-N/L/day. High-throughput amplicon sequencing analysis of the comammox ammonia monooxygenase subunit A (amoA) gene revealed seven sequence types from two clusters in clade A of comammox Nitrospira. Quantitative polymerase chain reaction analyses suggested that the comammox species dominated the ammonia-oxidizing community, with an abundance as high as 89.2 ± 7.9% in total prokaryotic amoA copies. Multiple linear regression further revealed the substantial contribution of the comammox Nitrospira to ammonia oxidation in the bioreactor. The investigation with bioreactor and batch experiments consistently showed that activities of comammox Nitrospira were inhibited by free ammonia far more severely than other ammonia-oxidizing microbes. Overall, this study provided new insight into the ecology of comammox Nitrospira under hypoxic conditions and suggested comammox-associated partial nitrification-anammox as a potential method for treating low-strength ammonium-containing wastewater.

Deciphering microbiomes in anaerobic reactors with superior trichloroethylene dechlorination performance at low pH conditions

Different pH conditions have been demonstrated to affect the activities of dechlorinating populations participating in the successive dechlorination of trichloroethylene to ethylene. However, the mechanism of the effect of pH conditions on the assembly of dechlorinating populations and their relations to the structure, function, and dynamics of the microbiome are unclear. In this study, we evaluated the effects of pH on microbiomes assembled in anaerobic trichloroethylene-dechlorinating reactors under neutral (pH 7.2), acidic (pH 6.2), and alkaline (pH 8.2) conditions. The results revealed that among the reactors, the acidic reactor had the highest efficiency for dechlorination without accumulation of dechlorinated metabolites, even at high loading rates. The results of high-throughput sequencing of the 16S rRNA gene indicated that the microbiomes in the 3 reactors underwent varied dynamic succession. The acidic reactor harbored a higher degree of complex microbes, dechlorinator diversity, and abundance of the Victoria subgroup of Dehalococcoides (1.2 ± 0.1 × 10⁶ cell/mL), which were approximately 10-10²-fold higher than those at neutral and alkaline conditions. The pH settings altered species-species connectivity and complexity of microbial interaction networks, with more commensal interactions in the dechlorinators of the acidic reactor. As predicted, abundances of several functional gene categories were in strong linearity with pH values, and the microbiome possessed significantly more abundant functions in the acidic reactor (P < 0.001), such as potentially stimulating hydrogen production, cobalamin synthesis, cobalt transport, transport and metabolism of amino acids and secondary metabolites, cell motility, and transcription. All results of microbiomic analyses consistently revealed the observed superior dechlorination process and suggested an association of the reductive dechlorination process with the pH-dependent microbiome. The results of this study provide a new insight into the trichloroethylene dechlorination with regards to pH, and they will be useful for improving bioremediation and management of trichloroethylene-contaminated sites.

Comparative analysis of deep sequenced methanogenic communities: identification of microorganisms responsible for methane production

BACKGROUND

Although interactions between microorganisms involved in biogas production are largely uncharted, it is commonly accepted that methanogenic Archaea are essential for the process. Methanogens thrive in various environments, but the most extensively studied communities come from biogas plants. In this study, we employed a metagenomic analysis of deeply sequenced methanogenic communities, which allowed for comparison of taxonomic and functional diversity as well as identification of microorganisms directly involved in various stages of methanogenesis pathways.

RESULTS

A comprehensive metagenomic approach was used to compare seven environmental communities, originating from an agricultural biogas plant, cattle-associated samples, a lowland bog, sewage sludge from a wastewater treatment plant and sediments from an ancient gold mine. In addition to the native consortia, two laboratory communities cultivated on maize silage as the sole substrate were also analyzed. Results showed that all anaerobic communities harbored genes of all known methanogenesis pathways, but their abundance varied greatly between environments and that genes were encoded by different methanogens. Identification of microorganisms directly involved in different stages of methane production revealed that hydrogenotrophic methanogens, such as Methanoculleus, Methanobacterium, Methanobrevibacter, Methanocorpusculum or Methanoregula, predominated in most native communities, whereas acetoclastic Methanosaeta seemed to be the key methanogen in the wastewater treatment plant. Furthermore, in many environments, the methylotrophic pathway carried out by representatives of Methanomassiliicoccales, such as Candidatus Methanomethylophilus and Candidatus Methanoplasma, seemed to play an important role in methane production. In contrast, in stable laboratory reactors substrate versatile Methanosarcina predominated.

CONCLUSIONS

The metagenomic approach presented in this study allowed for deep exploration and comparison of nine environments in which methane production occurs. Different abundance of methanogenesis-related functions was observed and the functions were analyzed in the phylogenetic context in order to identify microbes directly involved in methane production. In addition, a comparison of two metagenomic analytical tools, MG-RAST and MetAnnotate, revealed that combination of both allows for a precise characterization of methanogenic communities.

Community and Proteomic Analysis of Anaerobic Consortia Converting Tetramethylammonium to Methane

Tetramethylammonium-degrading methanogenic consortia from a complete-mixing suspended sludge (CMSS) and an upflow anaerobic sludge blanket (UASB) reactors were studied using multiple PCR-based molecular techniques and shotgun proteomic approach. The prokaryotic 16S rRNA genes of the consortia were analyzed by quantitative PCR, high-throughput sequencing, and DGGE-cloning methods. The results showed that methanogenic archaea were highly predominant in both reactors but differed markedly according to community structure. Community and proteomic analysis revealed that Methanomethylovorans and Methanosarcina were the major players for the demethylation of methylated substrates and methane formation through the reduction pathway of methyl-S-CoM and possibly, acetyl-CoA synthase/decarbonylase-related pathways. Unlike high dominance of one Methanomethylovorans population in the CMSS reactor, diverse methylotrophic Methanosarcina species inhabited in syntrophy-like association with hydrogenotrophic Methanobacterium in the granular sludge of UASB reactor. The overall findings indicated the reactor-dependent community structures of quaternary amines degradation and provided microbial insight for the improved understanding of engineering application.

Application of hierarchical oligonucleotide primer extension (HOPE) to assess relative abundances of ammonia- and nitrite-oxidizing bacteria

BACKGROUND

Establishing an optimal proportion of nitrifying microbial populations, including ammonia-oxidizing bacteria (AOB), nitrite-oxidizing bacteria (NOB), complete nitrite oxidizers (comammox) and ammonia-oxidizing archaea (AOA), is important for ensuring the efficiency of nitrification in water treatment systems. Hierarchical oligonucleotide primer extension (HOPE), previously developed to rapidly quantify relative abundances of specific microbial groups of interest, was applied in this study to track the abundances of the important nitrifying bacterial populations.

RESULTS

The method was tested against biomass obtained from a laboratory-scale biofilm-based trickling reactor, and the findings were validated against those obtained by 16S rRNA gene-based amplicon sequencing. Our findings indicated a good correlation between the relative abundance of nitrifying bacterial populations obtained using both HOPE and amplicon sequencing. HOPE showed a significant increase in the relative abundance of AOB, specifically Nitrosomonas, with increasing ammonium content and shock loading (p < 0.001). In contrast, Nitrosospira remained stable in its relative abundance against the total community throughout the operational phases. There was a corresponding significant decrease in the relative abundance of NOB, specifically Nitrospira and those affiliated to comammox, during the shock loading. Based on the relative abundance of AOB and NOB (including commamox) obtained from HOPE, it was determined that the optimal ratio of AOB against NOB ranged from 0.2 to 2.5 during stable reactor performance.

CONCLUSIONS

Overall, the HOPE method was developed and validated against 16S rRNA gene-based amplicon sequencing for the purpose of performing simultaneous monitoring of relative abundance of nitrifying populations. Quantitative measurements of these nitrifying populations obtained via HOPE would be indicative of reactor performance and nitrification functionality.