Project description:We performed a deep, comparative metaproteomics study on three aerobic granular sludge wastewater treatment communities to determine the core microbiome and the occurrence and relative abundance of the central nutrient-removing organisms. Our systematic study underscores the importance of metaproteomics when characterizing complex microbiomes, and the necessity of accurate reference sequence databases to improve the comparison between studies and omics approaches.
Project description:The transcriptome analysis by the human DNA microarray was applied to evaluate the impacts of whole wastewater effluents from the membrane bioreactors (MBRs) and the activated sludge process (AS), on the biological processes of human hepatoma HepG2 cells. The three conventional bioassays (i.e., cytotoxicity tests and bioluminescence inhibition test) and chemical analysis of the domestic effluent standards were conducted in parallel since they are well-established methods with previous applications to wastewater. A significant variation of effluent quality was sdemonstrated among the tested effluents despite that all effluents met the 40 national effluent standards. The three conventional bioassays supported the result of the transcriptome analysis, indicating the comparable or even higher sensitivity of the new assay. The most superior effluent quality was found in the MBR operated at a relatively long sludge retention time (i.e., 40 days) and small membrane pore size (i.e., 0.03 M-NM-<m). In addition, functional analysis of the differentially expressed genes revealed that the effluents made various impacts on the cellular functions, suggesting the transcriptome analysis by DNA microarray as more comprehensive, rapid and sensitive tool to detect multiple impacts of the whole effluents. Moreover, the potential genetic markers were proposed to quantitatively evaluate the treatability of the wastewater effluents. In this study, we examined the gene expression alteration in human hepatoma cell line, HepG2 exposed to the raw wastewater, effluents from three types of membrane bioreactors (MBRs), and the activated sludge process. Wastewater DNA microarray with 8795 human genes. MQ water was used as control. For duplicate, two dishes were prepared for each sample and individually treated in parallel.
Project description:The transcriptome analysis by the human DNA microarray was applied to evaluate the impacts of whole wastewater effluents from the membrane bioreactors (MBRs) and the activated sludge process (AS), on the biological processes of human hepatoma HepG2 cells. The three conventional bioassays (i.e., cytotoxicity tests and bioluminescence inhibition test) and chemical analysis of the domestic effluent standards were conducted in parallel since they are well-established methods with previous applications to wastewater. A significant variation of effluent quality was sdemonstrated among the tested effluents despite that all effluents met the 40 national effluent standards. The three conventional bioassays supported the result of the transcriptome analysis, indicating the comparable or even higher sensitivity of the new assay. The most superior effluent quality was found in the MBR operated at a relatively long sludge retention time (i.e., 40 days) and small membrane pore size (i.e., 0.03 μm). In addition, functional analysis of the differentially expressed genes revealed that the effluents made various impacts on the cellular functions, suggesting the transcriptome analysis by DNA microarray as more comprehensive, rapid and sensitive tool to detect multiple impacts of the whole effluents. Moreover, the potential genetic markers were proposed to quantitatively evaluate the treatability of the wastewater effluents.
Project description:Wastewater has been extensively studied along the years. However, these studies have been focused on the analysis of small molecules. There are no studies about the proteins present in wastewater and let alone an established method to study them. We propose a method for the study of the proteins in wastewater overcoming their low concentration and the interference of other molecules. Moreover, we differentiate between the proteins that are soluble and the ones in the particulate. This method is based on concentration, lysis and clean-up steps. The samples were analyzed afterward using liquid chromatography coupled to high-resolution mass spectrometry (HR-LC/MS) and the data searched with Proteome Discoverer. Thus, this complete method has allowed us to characterize the proteomic composition of different wastewater samples with a low volume.
Project description:Nucleic acids in wastewater provide a rich source of data for detection and surveillance of microbes. We have longitudinally collected 116 RNA samples from a wastewater treatment plant in Berlin/Germany, from March 2021 to July 2022, and 24 DNA samples from May to July 2022. We tracked human astroviruses, enteroviruses, noroviruses and adenoviruses over time to the level of strains or even individual nucleotide variations, showing how detailed human pathogens can be observed using wastewater. For respiratory pathogens, a broad enrichment panel enabled us to detect waves of RSV, influenza, or common cold coronaviruses in high agreement with clinical data. By applying a profile Hidden Markov Model-based search for novel viruses, we identified more than 100 thousand novel transcript assemblies likely not belonging to known virus species, thus substantially expanding our knowledge of virus diversity. Phylogenetic analysis is shown for bunyaviruses and parvoviruses. Finally, we identify Hundreds of novel protein sequences for CRISPR-associated proteins such as Transposase B, a class of small RNA-guided DNA editing enzymes. Taken together, we present a longitudinal and deep investigation into wastewater-derived genomic sequencing data that underlines the value of sewage surveillance for public health, planetary virome research, and biotechnological potential.
Project description:Bio-augmentation could be a promising strategy to improve processes for treatment and resource recovery from wastewater. In this study, the Gram-positive bacterium Bacillus subtilis was co-cultured with the microbial communities present in wastewater samples with high concentrations of nitrate or ammonium. Glucose supplementation (1%) was used to boost biomass growth in all wastewater samples. In anaerobic conditions, the indigenous microbial community bio-augmented with B. subtilis was able to rapidly remove nitrate from wastewater. In these conditions, B. subtilis overexpressed nitrogen assimilatory and respiratory genes including NasD, NasE, NarG, NarH, and NarI, which arguably accounted for the observed boost in denitrification. Next, we attempted to use the the ammonium- and nitrate-enriched wastewater samples bio-augmented with B. subtilis in the cathodic compartment of bioelectrochemical systems (BES) operated in anaerobic condition. B. subtilis only had low relative abundance in the microbial community, but bio-augmentation promoted the growth of Clostridium butyricum and C. beijerinckii, which became the dominant species. Both bio-augmentation with B. subtilis and electrical current from the cathode in the BES promoted butyrate production during fermentation of glucose. A concentration of 3.4 g/L butyrate was reached with a combination of cathodic current and bio-augmentation in ammonium-enriched wastewater. With nitrate-enriched wastewater, the BES effectively removed nitrate reaching 3.2 mg/L after 48 h. In addition, 3.9 g/L butyrate was produced. We propose that bio-augmentation of wastewater with B. subtilis in combination with bioelectrochemical processes could both boost denitrification in nitrate-containing wastewater and enable commercial production of butyrate from carbohydrate- containing wastewater, e.g. dairy industry discharges. These results suggest that B. subtilis bio-augmentation in our BES promotes simultaneous wastewater treatment and butyrate production.
Project description:We developed a laboratory-scale model to improve our understanding and capacity to assess the biological risks of genetically engineered bacteria and their genetic elements in the natural environment. Our hypothetical scenario concerns an industrial bioreactor failure resulting in the introduction of genetically engineered bacteria to a downstream municipal wastewater treatment plant (MWWTP). As the first step towards developing a model for this scenario, we sampled microbial communities from the aeration basin of a MWWTP at three seasonal time points. Having established a baseline for community composition, we investigated how the community changed when propagated in the laboratory, including cell culture media conditions that could provide selective pressure in future studies. Specifically, using PhyloChip 16S rRNA gene-targeting microarrays, we compared the compositions of sampled communities to those of inoculates propagated in the laboratory in simulated wastewater conditionally amended with various carbon sources (glucose, chloroacetate, D-threonine) or the ionic liquid 1-ethyl-3-methylimidazolium chloride ([C2mim]Cl). Proteobacteria, Bacteroidetes, and Actinobacteria were predominant in aeration basin and laboratory-cultured populations. Laboratory-cultured populations were enriched in Gammaproteobacteria. Enterobacteriaceae and Aeromonadaceae were enriched by glucose, Pseudomonadaceae by chloroacetate and D-threonine, and Burkholderiaceae by high (50 mM) concentrations of chloroacetate. Microbial populations cultured with chloroacetate and D-threonine were more similar to sampled populations than thoes cultured with glucose or [C2mim]Cl. Although observed relative richness in operational taxonomic units was lower for laboratory cultures than for sampled populations, both flask and reactor systems cultured phylogenetically diverse communities. These results importantly provide a foundation for laboratory models of industrial bioreactor failure scenarios.
Project description:Time course extraction of the Yeast Metabolic cycle, followed by ATAC seq processing. These files are used in a multi-omics study to complement a series of datasets that cover other moluecular layers of the Yeast Metabolic Cycle, including metabolomics, gene expression and histone modificaiton datasets. Our goal in this project is to create statistical integratory tools to comprehend YMC regulatory mechanism.