Project description:The present study applied both metagenomic and metatranscriptomic approaches to characterize microbial structure and gene expression of an activated sludge community from a municipal wastewater treatment plant in Hong Kong. DNA and cDNA were sequenced by Illumina Hi-seq2000 at a depth of 2.4 Gbp. Taxonomic analysis by MG-RAST showed bacteria were dominant in both DNA and cDNA datasets. The taxonomic profile obtained by BLAST against SILVA SSUref database and annotation by MEGAN showed that activated sludge was dominated by Proteobacteria, Actinobacteria, Bacteroidetes, Firmicutes and Verrucomicrobia phyla in both DNA and cDNA datasets. Global gene expression annotation based on KEGG metabolism pathway displayed slight disagreement between the DNA and cDNA datasets. Further gene expression annotation focusing on nitrogen removal revealed that denitrification-related genes sequences dominated in both DNA and cDNA datasets, while nitrifying genes were also expressed in relative high levels. Specially, ammonia monooxygenase and hydroxylamine oxidase demonstrated the high cDNA/DNA ratios in the present study, indicating strong nitrification activity. Enzyme subunits gene sequences annotation discovered that subunits of ammonia monooxygenase (amoA, amoB, amoC) and hydroxylamine oxygenase had higher expression levels compared with subunits of the other enzymes genes. Taxonomic profiles of selected enzymes (ammonia monooxygenase and hydroxylamine oxygenase) showed that ammonia-oxidizing bacteria present mainly belonged to Nitrosomonas and Nitrosospira species and no ammonia-oxidizing Archaea sequences were detected in both DNA and cDNA datasets.
Project description:ImportanceWastewater treatment plays an essential role in minimizing negative impacts on downstream aquatic environments. Microbial communities are known to play a vital role in the wastewater treatment process, particularly in the removal of nitrogen and phosphorus, which can be especially damaging to aquatic ecosystems. There is limited understanding of how these microbial communities may change in response to fluctuating temperatures or how seasonality may impact their ability to participate in the treatment process. The findings of this study indicate that the microbial communities of wastewater are relatively stable both compositionally and functionally across fluctuating temperatures.
Project description:Peri-implantitis and periodontitis are both polymicrobial diseases induced by subgingival plaque accumulation, with some differing clinical features. Studies on the microbial and gene transcription activity of peri-implantitis microbiota are limited. This study aimed to verify the hypothesis that disease-specific microbial and gene transcription activity lead to disease-specific clinical features, using an integrated metagenomic, metatranscriptomic, and network analysis. Metagenomic data in peri-implantitis and periodontitis were obtained from the same 21 subjects and metatranscriptomic data from 12 subjects were obtained from a database. The microbial co-occurrence network based on metagenomic analysis had more diverse species taxa and correlations than the network based on the metatranscriptomic analysis. Solobacterium moorei and Prevotella denticola had high activity and were core species taxa specific to peri-implantitis in the co-occurrence network. Moreover, the activity of plasmin receptor/glyceraldehyde-3-phosphate dehydrogenase genes was higher in peri-implantitis. These activity differences may increase complexity in the peri-implantitis microbiome and distinguish clinical symptoms of the two diseases. These findings should help in exploring a novel biomarker that assist in the diagnosis and preventive treatment design of peri-implantitis.
Project description:Activated sludge (AS) plays a crucial role in the treatment of domestic and industrial wastewater. AS is a biocenosis of microorganisms capable of degrading various pollutants, including organic compounds, toxicants, and xenobiotics. We performed 16S rRNA gene sequencing of AS and incoming sewage in three wastewater treatment plants (WWTPs) responsible for processing sewage with different origins: municipal wastewater, slaughterhouse wastewater, and refinery sewage. In contrast to incoming wastewater, the taxonomic structure of AS biocenosis was found to become stable in time, and each WWTP demonstrated a unique taxonomic pattern. Most pathogenic microorganisms (Streptococcus, Trichococcus, etc.), which are abundantly represented in incoming sewage, were significantly decreased in AS of all WWTPs, except for the slaughterhouse wastewater. Additional load of bioreactors with influent rich in petroleum products and organic matter was associated with the increase of bacteria responsible for AS bulking and foaming. Here, we present a novel approach enabling the prediction of the metabolic potential of bacterial communities based on their taxonomic structures and MetaCyc database data. We developed a software application, XeDetect, to implement this approach. Using XeDetect, we found that the metabolic potential of the three bacterial communities clearly reflected the substrate composition. We revealed that the microorganisms responsible for AS bulking and foaming (most abundant in AS of slaughterhouse wastewater) played a leading role in the degradation of substrates such as fatty acids, amino acids, and other bioorganic compounds. Moreover, we discovered that the chemical, rather than the bacterial composition of the incoming wastewater was the main factor in AS structure formation. XeDetect (freely available: https://sourceforge.net/projects/xedetect) represents a novel powerful tool for the analysis of the metabolic capacity of bacterial communities. The tool will help to optimize bioreactor performance and avoid some most common technical problems.
Project description:Wastewater treatment plants (WWTPs) are host to diverse microbial communities and receive a constant influx of microbes from influent wastewater. However, the impact of immigrants on the structure and activities of the activated sludge (AS) microbial community remains unclear. To gain insight on this phenomenon known as perpetual community coalescence, the current study utilized controlled manipulative experiments that decoupled the influent wastewater composition from the microbial populations to reveal the fundamental mechanisms involved in immigration between sewers and AS-WWTP. The immigration dynamics of heterotrophs were analyzed by harvesting wastewater biomass solids from three different sewer systems and adding to synthetic wastewater. Immigrating influent populations were observed to contribute up to 14% of the sequencing reads in the AS. By modeling the net growth rate of taxa, it was revealed that immigrants primarily exhibited low or negative net growth rates. By developing a protocol to reproducibly grow AS-WWTP communities in the lab, we have laid down the foundational principles for the testing of operational factors creating community variations with low noise and appropriate replication. Understanding the processes that drive microbial community diversity and assembly is a key question in microbial ecology. In the future, this knowledge can be used to manipulate the structure of microbial communities and improve system performance in WWTPs.IMPORTANCEIn biological wastewater treatment processes, the microbial community composition is essential in the performance and stability of the system. This study developed a reproducible protocol to investigate the impact of influent immigration (or perpetual coalescence of the sewer and activated sludge communities) with appropriate reproducibility and controls, allowing intrinsic definitions of core and immigrant populations to be established. The method developed herein will allow sequential manipulative experiments to be performed to test specific hypothesis and optimize wastewater treatment processes to meet new treatment goals.
Project description:BackgroundAnaerobic digestion has been widely applied to treat the waste activated sludge from biological wastewater treatment and produce methane for biofuel, which has been one of the most efficient solutions to both energy crisis and environmental pollution challenges. Anaerobic digestion sludge contains highly complex microbial communities, which play crucial roles in sludge treatment. However, traditional approaches based on 16S rRNA amplification or fluorescent in situ hybridization cannot completely reveal the whole microbial community structure due to the extremely high complexity of the involved communities. In this sense, the next-generation high-throughput sequencing provides a powerful tool for dissecting microbial community structure and methane-producing pathways in anaerobic digestion.ResultsIn this work, the metagenomic sequencing was used to characterize microbial community structure of the anaerobic digestion sludge from a full-scale municipal wastewater treatment plant. Over 3.0 gigabases of metagenomic sequence data were generated with the Illumina HiSeq 2000 platform. Taxonomic analysis by MG-RAST server indicated that overall bacteria were dominant (~93%) whereas a considerable abundance of archaea (~6%) were also detected in the anaerobic digestion sludge. The most abundant bacterial populations were found to be Proteobacteria, Firmicutes, Bacteroidetes, and Actinobacteria. Key microorganisms and related pathways involved in methanogenesis were further revealed. The dominant proliferation of Methanosaeta and Methanosarcina, together with the functional affiliation of enzymes-encoding genes (acetate kinase (AckA), phosphate acetyltransferase (PTA), and acetyl-CoA synthetase (ACSS)), suggested that the acetoclastic methanogenesis is the dominant methanogenesis pathway in the full-scale anaerobic digester.ConclusionsIn short, the metagenomic sequencing study of this work successfully dissected the detail microbial community structure and the dominated methane-producing pathways of a full-scale anaerobic digester. The knowledge garnered would facilitate to develop more efficient full-scale anaerobic digestion systems to achieve high-rate waste sludge treatment and methane production.
Project description:Reports regarding the composition and functions of microorganisms in activated sludge from wastewater treatment plants for treating tuna processing wastewater remains scarce, with prevailing studies focusing on municipal and industrial wastewater. This study delves into the efficiency and biological dynamics of activated sludge from tuna processing wastewater, particularly under conditions of high lipid content, for pollutant removal. Through metagenomic analysis, we dissected the structure of microbial community, and its relevant biological functions as well as pathways of nitrogen and lipid metabolism in activated sludge. The findings revealed the presence of 19 phyla, 1,880 genera, and 7,974 species, with Proteobacteria emerging as the predominant phylum. The study assessed the relative abundance of the core microorganisms involved in nitrogen removal, including Thauera sp. MZ1T and Alicycliphilus denitrificans K601, among others. Moreover, the results also suggested that a diverse array of fatty acid-degrading microbes, such as Thauera aminoaromatica and Cupriavidus necator H16, could thrive under lipid-rich conditions. This research can provide some referable information for insights into optimizing the operations of wastewater treatment and identify some potential microbial agents for nitrogen and fatty acid degradation.
Project description:Chloroxylenol (CHL) is an antimicrobial ingredient that is frequently used in antiseptics/disinfectants for skin (e.g. hand soap) and non-living surfaces. CHL is an alternative to triclosan and triclocarban, the use of which has recently been banned in some countries. Accordingly, the more widespread use of CHL may significantly increase its occurrence and level in aquatic environments in the near future, eventually resulting in potential ecological risks. Wastewater treatment plants (WWTPs) may be a point source of CHL in natural environments due to extensive discharge through urban waste stream disposal. While the satisfactory removal of CHL in WWTPs is critical for maintaining healthy aquatic ecosystems, the extent of CHL removal and whether CHL causes system upset/failure in WWTPs currently remain unknown. In the present study, we conducted bioreactor operation and batch experiments to investigate the fate and effects of CHL and elucidate the mechanisms underlying degradation at various levels from environmentally relevant to high levels (0.5-5 mg L-1). Bioreactors partially removed CHL (44-87%) via a largely biological route. Microbial association networks constructed using 16S rRNA gene sequencing data revealed selective enrichment and a correlation between Sphingobium and CHL, implying its involvement in the biological breakdown of CHL through dehalogenation and ring hydroxylation pathways. The present results provide insights into the behavior and effects of CHL in activated sludge communities and important information for the sustainable management of CHL that may be an emerging issue in the urban water cycle.
Project description:In wastewater treatment systems, the interactions among various microbes based on chemical signals, namely quorum sensing (QS), play critical roles in influencing microbial structure and function. However, it is challenging to understand the QS-controlled behaviors and the underlying mechanisms in complex microbial communities. In this study, we constructed a QS signaling network, providing insights into the intra- and interspecies interactions of activated sludge microbial communities based on diverse QS signal molecules. Our research underscores the role of diffusible signal factors in both intra- and interspecies communication among activated sludge microorganisms, and signal molecules commonly considered to mediate intraspecies communication may also participate in interspecies communication. QS signaling molecules play an important role as communal resources among the entire microbial group. The communication network within the microbial community is highly redundant, significantly contributing to the stability of natural microbial systems. This work contributes to the establishment of QS signaling network for activated sludge microbial communities, which may complement metabolic exchanges in explaining activated sludge microbial community structure and may help with a variety of future applications, such as making the dynamics and resilience of highly complex ecosystems more predictable.
Project description:Synthetic estrogen analogues are among the most potent estrogenic contaminants in effluents from wastewater treatment plants. Although its effects have been well elucidated in the feminization of male fish and interference with the endocrine systems in humans, it has not been fully explored in the activated sludge (AS) microbiome, particularly EE2 (17α-ethynylestradiol). Therefore, in this study, the bacterial community shift in a 6-day laboratory-scale reactor in environmental (0, 5, 10, and 100 ng/L) and predictive elevated concentrations (5, 10, and 100 mg/L) of EE2 was investigated using culture-based and metagenomics approaches. Results showed significant changes (t-test, all p < 0.05) between initial and final physicochemical parameters (pH, DO, and EC). Although environmental concentrations showed a slight decrease in microbial counts (5.6 × 106 to 4.6 × 106 CFU/ml) after a 24-h incubation for the culturable approach, the predictive elevated concentrations (5 to 100 mg/L) revealed a drastic microbial counts reduction (5.6 × 106 to 8 × 102 CFU/ml). The metagenomic data analysis uncovered that bacterial communities in the control sample were dominated by Proteobacteria, followed by Bacteroidetes and Firmicutes. The taxonomic classification after exposure of microbial communities in various concentrations revealed significant differences in community composition between environmental concentration (Shannon indices between 2.58 to 3.68) and predictive elevated concentrations (Shannon indices between 2.24 and 2.84; t-test, all p < 0.05). The EE2 enriched seven OTUs were Novosphingobium, Cloacibacterium, Stenotrophomonas, Enterobacteriaceae_unclassified, Stenotrophomonas, Enterobacteriaceae_unclassified and Rhodobacteraceae_unclassified. These results were supported by a dehydrogenase activity (DHA) test, which demonstrated less (about 40%) DHA in predictive elevated concentrations than in environmental concentrations. Notwithstanding, these findings suggest that EE2 may possess potent hormetic effect as evidenced by promotion of microbiome richness and dehydrogenase activity of AS in lower EE2 doses.