Project description:To understand microbial community functional structures of activated sludge in wastewater treatment plants (WWTPs) and the effects of environmental factors on their structure, 12 activated sludge samples were collected from four WWTPs in Beijing. GeoChip 4.2 was used to determine the microbial functional genes involved in a variety of biogeochemical processes. The results showed that, for each gene category, such as egl, amyA, nir, ppx, dsrA sox and benAB, there were a number of microorganisms shared by all 12 samples, suggestive of the presence of a core microbial community in the activated sludge of four WWTPs. Variance partitioning analyses (VPA) showed that a total of 53% of microbial community variation can be explained by wastewater characteristics (25%) and operational parameters (23%), respectively. This study provided an overall picture of microbial community functional structures of activated sludge in WWTPs and discerned the linkages between microbial communities and environmental variables in WWTPs. Four full-scale wastewater treatment systems located in Beijing were investigated. Triplicate samples were collected in each site.
Project description:To understand microbial community functional structures of activated sludge in wastewater treatment plants (WWTPs) and the effects of environmental factors on their structure, 12 activated sludge samples were collected from four WWTPs in Beijing. GeoChip 4.2 was used to determine the microbial functional genes involved in a variety of biogeochemical processes. The results showed that, for each gene category, such as egl, amyA, nir, ppx, dsrA sox and benAB, there were a number of microorganisms shared by all 12 samples, suggestive of the presence of a core microbial community in the activated sludge of four WWTPs. Variance partitioning analyses (VPA) showed that a total of 53% of microbial community variation can be explained by wastewater characteristics (25%) and operational parameters (23%), respectively. This study provided an overall picture of microbial community functional structures of activated sludge in WWTPs and discerned the linkages between microbial communities and environmental variables in WWTPs.
Project description:On March 12, 2020, the World Health Organization (WHO) declared COVID-19 as a global pandemic. COVID-19 is produced by a novel β-coronavirus known as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) [1]. Several studies have detected SARS-CoV-2 RNA in urine, feces, and other biofluids from both symptomatic and asymptomatic people with COVID-19 [2], suggesting that SARS-CoV-2 RNA could be detected in human wastewater [3]. Thus, wastewater-based epidemiology (WBE) is now used as an approach to monitor COVID-19 prevalence in many different places around the world [4-10] . Reverse transcription quantitative polymerase chain reaction (RT-qPCR) is the most common SARS-CoV-2 detection method in WBE, but there are other methods for viral biomolecule detection that could work as well. The aim of this study was to evaluate the presence of SARS-CoV-2 proteins in untreated wastewater (WW) influents collected from six wastewater treatment plants (WWTPs), from Durham Region, Ontario, Canada, using a LC-MS/MS-based proteomics approach. We identified many SARS-CoV-2 proteins in these wastewater samples, with peptides from pp1ab being the most consistently detected and with consistent abundance.
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: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:Nitric oxide (NO) has several important functions in biology and atmospheric chemistry as a toxin, signaling molecule, ozone depleting agent and the precursor of the greenhouse gas nitrous oxide (N2O). Even though NO is a potent oxidant, and was available on earth earlier than oxygen, its direct use by microorganisms for growth was not demonstrated before. Using physiological experiments, metatranscriptomics and metaproteomics, here we show that anaerobic ammonium-oxidizing (anammox) bacterium Kuenenia stuttgartiensis grow by coupling ammonium oxidation to NO reduction, and produce only N2. Such a metabolism could have existed on early earth, and has implications in controlling N2O and NO emissions both from natural and manmade ecosystems, where anammox bacteria contribute significantly to N2 release to the atmosphere.