Project description:In this study, we exposed Caenorhabditis elegans wild types N2 to water collected from six sources in the Dutch village Sneek. The sources were: wastewater from a hospital, a community (80 households), a nursing home, influent into the local municipal wastewater treatment plant, effluent of the wastewater treatment plant, and surface water samples. The goal of the experiment was to determine if C. elegans can be used to identify pollutants in the water by transcriptional profiling. Age synchronized worms at developmental L4 larval stage were exposed to treatment for 24 hours. After flash freezing the samples, RNA was isolated, labeled and hybridized on oligo microarray (Agilent) slides.
Project description:Wastewater treatment plants (WWTPs) and Drinking water treatment plants (DWTPs) are critical points for public health for persistently remaining microorganisms after treatment may pose a risk. This study aimed to conduct microbial metagenomic analyses on waters from both DWTPs and WWTPs under the Istanbul Water and Sewerage Administration (ISKI). In this study a total of 52 samples were included, comprising 18 samples from DWTPs and 34 from WWTPs. All water samples underwent pre-isolation filtration. DNA isolation was conducted using filter material, followed by library preparation and sequencing on a NovaSeq 6000 instrument following the manufacturer's guidelines.
Project description:Evaluation of short-read-only, long-read-only, and hybrid assembly approaches on metagenomic samples demonstrating how they affect gene and protein prediction which is relevant for downstream functional analyses. For a human gut microbiome sample, we use complementary metatranscriptomic, and metaproteomic data to evaluate the metagenomic-based protein predictions.
Project description:Wastewater treatment plants use a variety of bioreactor types and configurations to remove organic matter and nutrients. Little is known regarding the effects of different configurations and within-plant immigration on microbial community dynamics. Previously, we found that the structure of ammonia-oxidizing bacterial (AOB) communities in a full-scale dispersed growth activated sludge bioreactor correlated strongly with levels of NO2- entering the reactor from an upstream trickling filter (Wells et al 2009). Here, to further examine this puzzling association, we profile within-plant microbial biogeography (spatial variation) and test the hypothesis that substantial microbial immigration occurs along a transect (raw influent, trickling filter biofilm, trickling filter effluent, and activated sludge) at the same full-scale wastewater treatment plant. AOB amoA gene abundance increased >30-fold between influent and trickling filter effluent concomitant with NO2- production, indicating unexpected growth and activity of AOB within the trickling filter. Nitrosomonas europaea was the dominant AOB phylotype in trickling filter biofilm and effluent, while a distinct ‘Nitrosomonas-like’ lineage dominated in activated sludge. Prior time series indicated that this ‘Nitrosomonas-like’ lineage was dominant when NO2- levels in the trickling filter effluent (i.e., activated sludge influent) were low, while N. europaea became dominant in the activated sludge when NO2- levels were high. This is consistent with the hypothesis that NO2- production may co-occur with biofilm sloughing, releasing N. europaea from the trickling filter into the activated sludge bioreactor. Phylogenetic microarray (PhyloChip) analyses revealed significant spatial variation in taxonomic diversity, including a large excess of methanogens in the trickling filter relative to activated sludge and attenuation of Enterobacteriaceae across the transect, and demonstrated transport of a highly diverse microbial community via the trickling filter effluent to the activated sludge bioreactor. Our results provide compelling evidence that substantial immigration between coupled process units occurs and may exert significant influence over microbial community dynamics within staged bioreactors.
Project description:Wastewater-based surveillance (WBS) is a proven tool for monitoring population-level infection events. Wastewater contains high concentrations of inhibitors, which contaminate total nucleic acids (TNA) extracted from these samples. We found that TNA extracts from raw influent of Berlin wastewater treatment plants contained highly variable amounts of inhibitors that impaired molecular analyses like dPCR and next-generation sequencing (NGS). By using dilutions, we were able to detect inhibitory effects. To enhance WBS sensitivity and stability, we applied a combination of PCR inhibitor removal and TNA dilution (PIR+D). This approach led to a 26-fold increase in measured SARS-CoV-2 concentrations, practically reducing the detection limit. Additionally, we observed a substantial increase in stability of the time series. We define suitable stability as a mean absolute error (MAE) below 0.1 log10 copies/l and a geometric mean relative absolute error (GMRAE) below 26%. Using PIR+D, the MAE could be reduced from 0.219 to 0.097 and the GMRAE from 65.5% to 26.0% and even further in real-world WBS. Furthermore, PIR+D improved SARS-CoV-2 genome alignment and coverage in amplicon-based NGS for low to medium concentrations. In conclusion, we strongly recommend both the monitoring and removal of inhibitors from samples for WBS.
Project description:Understanding microbial community diversity is thought to be crucial for improving process functioning and stabilities of wastewater treatment systems. However, current studies largely focus on taxonomic groups based on 16S rRNA, which are not necessarily linked to functioning, or a few selected functional genes. Here we launched a study to profile the overall functional genes of microbial communities in three full-scale wastewater treatment systems. Triplicate activated sludge samples from each system were analyzed using a high-throughput metagenomics tool named GeoChip 4.2, resulting in the detection of 38,507 to 40,647 functional genes. A high similarity of 75.5% to 79.7% shared genes was noted among the nine samples. Moreover, correlation analyses showed that the abundances of a wide array of functional genes were associated with system performances. For example, the abundances of overall nitrogen cycling genes had a strong correlation to total nitrogen (TN) removal rates (r = 0.7647, P < 0.01). The abundances of overall carbon cycling genes were moderately correlated with COD removal rates (r = 0.6515, P < 0.01). Lastly, we found that influent chemical oxygen demand (COD inf) and total phosphorus concentrations (TP inf), and dissolved oxygen (DO) concentrations were key environmental factors shaping the overall functional genes. Together, the results revealed vast functional gene diversity and some links between the functional gene compositions and microbe-mediated processes.
Project description:Next-Generation-Sequencing (NGS) technologies have led to important improvement in the detection of new or unrecognized infective agents, related to infectious diseases. In this context, NGS high-throughput technology can be used to achieve a comprehensive and unbiased sequencing of the nucleic acids present in a clinical sample (i.e. tissues). Metagenomic shotgun sequencing has emerged as powerful high-throughput approaches to analyze and survey microbial composition in the field of infectious diseases. By directly sequencing millions of nucleic acid molecules in a sample and matching the sequences to those available in databases, pathogens of an infectious disease can be inferred. Despite the large amount of metagenomic shotgun data produced, there is a lack of a comprehensive and easy-use pipeline for data analysis that avoid annoying and complicated bioinformatics steps. Here we present HOME-BIO, a modular and exhaustive pipeline for analysis of biological entity estimation, specific designed for shotgun sequenced clinical samples. HOME-BIO analysis provides comprehensive taxonomy classification by querying different source database and carry out main steps in metagenomic investigation. HOME-BIO is a powerful tool in the hand of biologist without computational experience, which are focused on metagenomic analysis. Its easy-to-use intrinsic characteristic allows users to simply import raw sequenced reads file and obtain taxonomy profile of their samples.