Development of a reverse transcriptase digital droplet polymerase chain reaction-based approach for SARS-CoV-2 variant surveillance in wastewater.

An urgent need for effective surveillance strategies arose due to the global emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although vaccines and antivirals are available, concerns persist about the evolution of new variants with potentially increased infectivity, transmissibility, and immune evasion. Therefore, variant monitoring is crucial for public health decision-making. Wastewater-based surveillance has proven to be an effective tool to monitor SARS-CoV-2 variants within populations. Specific SARS-CoV-2 variants are detected and quantified in wastewater in this study using a reverse transcriptase digital droplet polymerase chain reaction (RT-ddPCR) approach. The 11 designed assays were first validated in silico using a substantial dataset of high-quality SARS-CoV-2 genomes to ensure comprehensive variant coverage. The assessment of the sensitivity and specificity with reference material showed the capability of the developed assays to reliably identify target mutations while minimizing false positives and false negatives. The applicability of the assays was evaluated using wastewater samples from a wastewater treatment plant in Ghent, Belgium. The quantification of the specific mutations linked to the variants of concern present in these samples was calculated using these assays based on the detection of single mutations, which confirms their use for real-world variant surveillance. In conclusion, this study provides an adaptable protocol to monitor SARS-CoV-2 variants in wastewater with high sensitivity and specificity. Its potential for broader application in other viral surveillance contexts highlights its added value for rapid response to emerging infectious diseases. PRACTITIONER POINTS: Robust RT-ddPCR methodology for specific SARS-CoV-2 variants of concern detection in wastewater. Rigorous validation that demonstrates high sensitivity and specificity. Demonstration of real-world applicability using wastewater samples. Valuable tool for rapid response to emerging infectious diseases.

Noninvasive integrative approach applied to children in the context of recent air pollution exposure demonstrates association between fractional exhaled nitric oxide (FeNO) and urinary CC16.

Exposure to the air pollutant particulate matter (PM) is associated with increased risks of respiratory diseases and enhancement of airway inflammation in children. In the context of large scale air pollution studies, it can be challenging to measure fractional exhaled nitric oxide (FeNO) as indicator of lung inflammation. Urinary CC16 (U-CC16) is a potential biomarker of increased lung permeability and toxicity, increasing following short-term PM2.5 exposure. The single nucleotide polymorphism (SNP) CC16 G38A (rs3741240) affects CC16 levels and respiratory health. Our study aimed at assessing the use of U-CC16 (incl. CC16 G38A from saliva) as potential alternative for FeNO by investigating their mutual correlation in children exposed to PM. Samples from a small-scale study conducted in 42 children from urban (n = 19) and rural (n = 23) schools examined at two time points, were analysed. When considering recent (lag1) low level exposure to PM2.5 as air pollution measurement, we found that U-CC16 was positively associated with FeNO (ß = 0.23; 95% CI [-0.01; 0.47]; p = 0.06) in an adjusted analysis using a linear mixed effects model. Further, we observed a positive association between PM2.5 and FeNO (ß = 0.56; 95% CI [0.02; 1.09]; p = 0.04) and higher FeNO in urban school children as compared to rural school children (ß = 0.72; 95% CI [0.12; 1.31]; p = 0.02). Although more investigations are needed, our results suggest that inflammatory responses evidenced by increased FeNO are accompanied by potential increased lung epithelium permeability and injury, evidenced by increased U-CC16. In future large scale studies, where FeNO measurement is less feasible, the integrated analysis of U-CC16 and CC16 G38A, using noninvasive samples, might be a suitable alternative to assess the impact of air pollution exposure on the respiratory health of children, which is critical for policy development at population level.

Assessment of the Feasibility of a Future Integrated Larger-Scale Epidemiological Study to Evaluate Health Risks of Air Pollution Episodes in Children.

Air pollution exposure can lead to exacerbation of respiratory disorders in children. Using sensitive biomarkers helps to assess the impact of air pollution on children's respiratory health and combining protein, genetic and epigenetic biomarkers gives insights on their interrelatedness. Most studies do not contain such an integrated approach and investigate these biomarkers individually in blood, although its collection in children is challenging. Our study aimed at assessing the feasibility of conducting future integrated larger-scale studies evaluating respiratory health risks of air pollution episodes in children, based on a qualitative analysis of the technical and logistic aspects of a small-scale field study involving 42 children. This included the preparation, collection and storage of non-invasive samples (urine, saliva), the measurement of general and respiratory health parameters and the measurement of specific biomarkers (genetic, protein, epigenetic) of respiratory health and air pollution exposure. Bottlenecks were identified and modifications were proposed to expand this integrated study to a higher number of children, time points and locations. This would allow for non-invasive assessment of the impact of air pollution exposure on the respiratory health of children in future larger-scale studies, which is critical for the development of policies or measures at the population level.

Urinary CC16, a potential indicator of lung integrity and inflammation, increases in children after short-term exposure to PM2.5/PM10 and is driven by the CC16 38GG genotype.

Particular matter (PM) exposure is a big hazard for public health, especially for children. Serum CC16 is a well-known biomarker of respiratory health. Urinary CC16 (U-CC16) can be a noninvasive alternative, albeit requiring adequate adjustment for renal handling. Moreover, the SNP CC16 G38A influences CC16 levels. This study aimed to monitor the effect of short-term PM exposure on CC16 levels, measured noninvasively in schoolchildren, using an integrative approach. We used a selection of urine and buccal DNA samples from 86 children stored in an existing biobank. Using a multiple reaction monitoring method, we measured U-CC16, as well as RBP4 (retinol binding protein 4) and ß2M (beta-2-microglobulin), required for adjustment. Buccal DNA samples were used for CC16 G38A genotyping. Linear mixed-effects models were used to find relevant associations between U-CC16 and previously obtained data from recent daily PM ≤ 2.5 or 10 µm exposure (PM2.5, PM10) modeled at the child's residence. Our study showed that exposure to low PM at the child's residence (median levels 18.9 µg/m³ (PM2.5) and 23.6 µg/m³ (PM10)) one day before sampling had an effect on the covariates-adjusted U-CC16 levels. This effect was dependent on the CC16 G38A genotype, due to its strong interaction with the association between PM levels and covariates-adjusted U-CC16 (P = 0.024 (PM2.5); P = 0.061 (PM10)). Only children carrying the 38GG genotype showed an increase of covariates-adjusted U-CC16, measured 24h after exposure, with increasing PM2.5 and PM10 (ß = 0.332; 95% CI: 0.110 to 0.554 and ß = 0.372; 95% CI: 0.101 to 0.643, respectively). To the best of our knowledge, this is the first study using an integrative approach to investigate short-term PM exposure of children, using urine to detect early signs of pulmonary damage, and taking into account important determinants such as the genetic background and adequate adjustment of the measured biomarker in urine.

Development of a multiplex mass spectrometry method for simultaneous quantification of urinary proteins related to respiratory health.

Respiratory health of children is a health priority. Club cell protein (CC16) is an interesting biomarker of lung diseases and adverse effects towards the airway epithelium integrity. Osteopontin (OPN) and nuclear factor-kappa B (NF-κB) also play a role in respiratory health. The use of urine as biomarker source is useful in studies involving children but necessitates proper adjustment for physiological confounders influencing the urinary excretion, potentially characterized with beta-2-microglobulin (ß2M), retinol binding protein 4 (RBP4) or myoglobin (MYO), as well as adjustment for possible renal dysfunction, characterized by human serum albumin (HSA). The simultaneous quantification of all these proteins in urine could facilitate children's health monitoring. A multiple reaction monitoring method (MRM) was developed and validated for the relative quantification of the seven mentioned urinary proteins. A total of nine proteotypic peptides were selected and used for the relative quantification of the seven proteins. The MRM method was completely validated for all proteins and partially for OPN. LOQ's ranged from 0.3 to 42.8 ng/ml, a good reproducibility and a good linearity were obtained across the analytical measurement range (r2 > 0.98). The method yielded varying correlations (r2 of 0.78, 0.71, 0.34 and 0.15 for CC16, ß2M, RBP4 and HSA respectively) with available immunoassay data. It also allowed the identification and successful quantification of ß2M and RBP4 as a protein candidate for adjustment of renal handling and dysfunction. All proteins were detected in the urine samples except for MYO and NF-κB. Our validated MRM-method is able to simultaneously quantify in urine biomarkers of airway epithelium integrity and biomarkers of variation in renal function and urinary dilution. This will allow to investigate further in future studies if urine can be used as a good surrogate source for biomarkers of airway epithelium integrity, and to understand the complex relationship between cause and effect in children's respiratory health monitoring.

Gender-dependent association between exhaled nitric oxide and the CC16 38AA genotype in young school children.

BACKGROUND: Studies that investigated the association between the CC16 A38G polymorphism and the risk of asthma yielded conflicting results. The aim of this study among schoolchildren was to assess the relationships of CC16 A38G polymorphism with aeroallergen sensitization and fractional exhaled nitric oxide (FeNO), two outcomes predicting asthma later in life. METHODS: The study included 139 children (72 boys), median age of 7.7. Information on each child's health, lifestyle, and environment was collected through a questionnaire completed by their parents. CC16 genotypes were determined using urinary DNA. We measured FeNO, the CC16 protein in urine and nasal lavage fluid and aeroallergen-specific immunoglobulin E in nasal mucosa fluid. RESULTS: Children with the homozygous mutant CC16 38AA genotype had higher odds of increased FeNO (>30 ppb) compared with their peers with the wild-type genotype 38GG (OR, 9.85; 95% CI, 2.09-46.4; P = .004). This association was female gender specific (P = .002) not being observed in boys (P = .40). It was also independent of allergic sensitization, which yet emerged as the strongest predictor of FeNO along with the use of bleach for house cleaning. Children with the CC16 38AA genotype had lower covariates-adjusted urinary CC16 levels than those with 38GG (median, µg/L, 1.17 vs 2.08, P = .02). CONCLUSION: Our study suggests that the CC16 38AA allele promotes airway inflammation as measured by FeNO through a gender-dependent association. Deficient levels of CC16 in the deep lung, measured noninvasively in urine, as a possible proxy for serum CC16, might underlie this promoting effect.

Selection of a Noninvasive Source of Human DNA Envisaging Genotyping Assays in Epidemiological Studies: Urine or Saliva?

Genetic epidemiology requires an appropriate approach to measure genetic variation within the population. The aim of this study was to evaluate the characteristics and genotyping results of DNA extracted from 2 human DNA sources, selected for their rapid and noninvasive sampling, and the use of simple and standardized protocols that are essential for large-scale epidemiologic studies. Saliva and urine samples were collected at the same day from 20 subjects aged 9-10 yr. Genomic DNA was extracted using commercial kits. Quantitative and qualitative evaluation was done by assessing the yield, the purity, and integrity of the extracted DNA. As a proof-of-concept, genotyping was performed targeting CC16 A38G and uteroglobin-related protein 1 (UGRP1)-112G/A. Saliva was found to provide the highest yield and concentration of total DNA extracted. Salivary DNA showed higher purity and a significantly less degraded state compared to urinary DNA. Consequently, the salivary DNA gave better genotyping results than urinary DNA. Therefore, if the choice exists, saliva is the preferred noninvasive matrix for genotyping purposes in large-scale genetic epidemiologic studies. Only in particular cases using urine could nevertheless be considered useful, although specific limitations need to be taken into account.