National-scale surveillance of emerging SARS-CoV-2 variants in wastewater

SARS-CoV-2 surveillance is crucial to identify variants with altered epidemiological properties. Wastewater-based epidemiology (WBE) provides an unbiased and complementary approach to sequencing individual cases. Yet, national WBE surveillance programs have not been widely implemented and data analyses remain challenging. We deep-sequenced 2,093 wastewater samples representing 95 municipal catchments, covering >57% of Austria's population, from December 2020 to September 2021. Our Variant Quantification in Sewage pipeline designed for Robustness (VaQuERo) enabled us to deduce variant abundance from complex wastewater samples and delineate the spatiotemporal dynamics of the dominant Alpha and Delta variants as well as regional clusters of other variants of concern. These results were cross validated by epidemiological records of >130,000 individual cases. Finally, we provide a framework to predict emerging variants de novo and infer variant-specific reproduction numbers from wastewater. This study demonstrates the power of national-scale WBE to support public health and promises particular value for countries without dense individual monitoring.

Detection of Enterovirus D68 in Wastewater Samples from the UK between July and November 2021

Infection with enterovirus D68 (EV-D68) has been linked with severe neurological disease such as acute flaccid myelitis (AFM) in recent years. However, active surveillance for EV-D68 is lacking, which makes full assessment of this association difficult. Although a high number of EV-D68 infections were expected in 2020 based on the EV-D68′s known biannual circulation patterns, no apparent increase in EV-D68 detections or AFM cases was observed during 2020. We describe an upsurge of EV-D68 detections in wastewater samples from the United Kingdom between July and November 2021 mirroring the recently reported rise in EV-D68 detections in clinical samples from various European countries. We provide the first publicly available 2021 EV-D68 sequences showing co-circulation of EV-D68 strains from genetic clade D and sub-clade B3 as in previous years. Our results show the value of environmental surveillance (ES) for the early detection of circulating and clinically relevant human viruses. The use of a next-generation sequencing (NGS) approach helped us to estimate the prevalence of EV-D68 viruses among EV strains from other EV serotypes and to detect EV-D68 minor variants. The utility of ES at reducing gaps in virus surveillance for EV-D68 and the possible impact of nonpharmaceutical interventions introduced to control the COVID-19 pandemic on EV-D68 transmission dynamics are discussed.

Estimating the relative proportions of SARS-CoV-2 strains from wastewater samples

Wastewater surveillance has become essential for monitoring the spread of SARS-CoV-2. The quantification of SARS-CoV-2 RNA in wastewater correlates with the Covid-19 caseload in a community. However, estimating the proportions of different SARS-CoV-2 strains has remained technically difficult. We present a method for estimating the relative proportions of SARS-CoV-2 strains from wastewater samples. The method uses an initial step to remove unlikely strains, imputation of missing nucleotides using the global SARS-CoV-2 phylogeny, and an Expectation-Maximization (EM) algorithm for obtaining maximum likelihood estimates of the proportions of different strains in a sample. Using simulations with a reference database of >3 million SARS-CoV-2 genomes, we show that the estimated proportions accurately reflect the true proportions given sufficiently high sequencing depth and that the phylogenetic imputation is highly accurate and substantially improves the reference database.

High Frequency of the EMRSA-15 Clone (ST22-MRSA-IV) in Hospital Wastewater

Hospital wastewaters often carry multidrug-resistant bacteria and priority pathogens, such as methicillin-resistant Staphylococcus aureus (MRSA). Pathogens and antibiotic resistance genes present in wastewaters may reach the natural environment facilitating their spread. Thus, we aimed to isolate MRSA from wastewater of 3 hospitals located in the north of Portugal and to characterize the isolates regarding the antimicrobial resistance and genetic lineages. A total of 96 wastewater samples were collected over six months. The water was filtered, and the filtration membrane was immersed in BHI broth supplemented with 6.5% of NaCl and incubated. The inoculum was streaked in ORSAB agar plates for MRSA isolation. The isolates susceptibility testing was performed against 14 antimicrobial agents. The presence of resistance and virulence genes was accessed by PCR. Molecular typing was performed in all isolates. From the 96 samples, 28 (29.2%) were MRSA-positive. Most isolates had a multidrug-resistant profile and carried the mecA, blaZ, aac(6′)-Ie-aph(2″)-Ia, aph(3′)-IIIa, ermA, ermB, ermC, tetL, tetM, dfrA dfrG and catpC221 genes. Most of the isolates were ascribed to the immune evasion cluster (IEC) type B. The isolates belonged to ST22-IV, ST8-IV and ST105-II and spa-types t747, t1302, t19963, t6966, t020, t008 and tOur study shows that MRSA can be found over time in hospital wastewater. The wastewater treatment processes can reduce the MRSA load. The great majority of the isolates belonged to ST22 and spa-type t747 which suggests the fitness of these genetic lineages in hospital effluents.

Dimensionality Reduction Analysis of the Integrated Solar and Hydraulic Jump Enhanced Waste Stabilization Pond Model Parameters

The study investigated the structure of the integrated solar and hydraulic jump enhanced waste stabilization pond (ISHJEWSP) variables. Also, to determine the cluster of the most important variables that account for the performance of the ISHJEWSP using principal component analysis (PCA). Three sets of experimental ponds were constructed with varying locations of point of initiation of hydraulic jump. Wastewater samples collected from the inlet and outlet for varying inlet velocities were examined for physicochemical and bacteriological characteristics for a period of nine months. The Pearson’s R-matrix and KMO statistic were used in evaluating the structure of the variables. Consequently, the variables of temperature, pH, algae concentration, solar radiation, and locations of the point of initiation of hydraulic jump were subjected to PCA. Two components had eigenvalues above the Jolliffe’s criterion and in combination explained 90.66% of the total variance. The inflexion of the scree plot justified the retained components. The analysis after rotation revealed that the parameters of pH, temperature, solar radiation, and algal concentration loaded highly to component 1. This underscores the precedence of ambient climatic conditions, alongside the state of the wastewater in general, to the inlet velocity and location of point of initiation of hydraulic jump.

VarLOCK - sequencing independent, rapid detection of SARS-CoV-2 variants of concern for point-of-care testing, qPCR pipelines and national wastewater surveillance

The COVID-19 pandemic continues to pose a threat to the general population. The ongoing vaccination programs provide protection to individuals and facilitate the opening of society and a return to normality. However, emergent and existing SARS-CoV-2 variants capable of evading the immune system endanger the efficacy of the vaccination strategy. To preserve the efficacy of SARS-CoV-2 vaccination globally, aggressive and effective surveillance for known and emerging SARS-CoV-2 Variants of Concern (VOC) is required. Rapid and specific molecular diagnostics can provide speed and coverage advantages compared to genomic sequencing alone, benefitting the public health response and facilitating VOC containment. In this work, we expand the recently developed SARS-CoV-2 CRISPR-Cas detection technology (SHERLOCK) to allow rapid and sensitive discrimination of VOCs, that can be used at point of care and/or implemented in the pipelines of small or large testing facilities, and even determine proportion of VOCs in pooled population-level wastewater samples. This technology aims to complement the ongoing sequencing efforts to allow facile and, crucially, rapid identification of individuals infected with VOCs to help break infection chains. Here, we show the optimisation of our VarLOCK assays (Variant-specific SHERLOCK) for multiple specific mutations in the S gene of SARS-CoV-2 and validation with samples from the Cardiff University Testing Service. We also show the applicability of VarLOCK to national wastewater surveillance of SARS-CoV-2 variants. In addition, we show the rapid adaptability of the technique for new and emerging VOCs such as Omicron.

Wastewater QC workflow in GalaxyTrakr (SSQuAWK) v2

PURPOSE: Step-by-step instructions for checking sequence quality for SARS-CoV-2 wastewater samples using SSQuAWK: SARS - CoV - 2 Sequence Quality Assurance Workflow and Kontraption. The SSQuAWK workflow, implemented in a custom Galaxy instance, will produce quality assessments for raw reads (Illumina MiSeq paired-end fastq files). SCOPE: This protocol covers the following tasks: 1. Set up an account in GalaxyTrakr 2. Create a new history 3. Upload data 4. Execute the SSQuAWK workflow 5. Interpret the results Version history: V1: Basic protocol steps with screenshots V2: Addition of a detailed 12 minute video tutorial

Development of a Disposable Pipette Extraction Method Using Coffee Silverskin as an Adsorbent for Chromium Determination in Wastewater Samples by Solid Phase Extraction

A procedure using disposable pipette tips adapted for solid-phase extraction, known as DPX‑SPE, was used as an alternative way for the chromium determination in wastewater samples. DPX-SPE consists of a device which allows a dynamic contact between the sample and the solidphase. A residue obtained from the processing of coffee beans, denominate coffee silverskin, was used as a new adsorbent. Characterization techniques revealed properties of lignocellulosic materials with potential application for chromium adsorption. The parameters including adsorbent mass (25.00 mg), elution solvent (0.1 mol L−1 HCl, 200 μL) and pH (2.0) were optimized. Thus, 1.00 mL of deionized water for conditioning, 4.00 mL of sample, 2 extraction cycles and 1 elution cycle were the employed conditions. Enrichment factor of 12, limit of detection of 6.00 μg L−1 and relative standard deviation (RSD) 1.3% (n = 3) were obtained. The method proved to be fast, cheap, environmentally friendly, and simple, providing good recoveries (104-113%), and it was satisfactorily applied in real samples.