Wastewater
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1146140 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR31392082_1.fastq.gz | Fastqsanger.gz | |||
| SRR31392083_1.fastq.gz | Fastqsanger.gz | |||
| SRR31392084_1.fastq.gz | Fastqsanger.gz | |||
| SRR31392085_1.fastq.gz | Fastqsanger.gz | |||
| SRR31392086_1.fastq.gz | Fastqsanger.gz |
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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.
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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.
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