Application of digital PCR for public health-related water quality monitoring.

Digital polymerase chain reaction (dPCR) is emerging as a reliable platform for quantifying microorganisms in the field of water microbiology. This paper reviews the fundamental principles of dPCR and its application for health-related water microbiology. The relevant literature indicates increasing adoption of dPCR for measuring fecal indicator bacteria, microbial source tracking marker genes, and pathogens in various aquatic environments. The adoption of dPCR has accelerated recently due to increasing use for wastewater surveillance of Severe Acute Respiratory Coronavirus 2 (SARS-CoV-2) - the virus that causes Coronavirus Disease 2019 (COVID-19). The collective experience in the scientific literature indicates that well-optimized dPCR assays can quantify genetic material from microorganisms without the need for a calibration curve and often with superior analytical performance (i.e., greater sensitivity, precision, and reproducibility) than quantitative polymerase chain reaction (qPCR). Nonetheless, dPCR should not be viewed as a panacea for the fundamental uncertainties and limitations associated with measuring microorganisms in water microbiology. With dPCR platforms, the sample analysis cost and processing time are typically greater than qPCR. However, if improved analytical performance (i.e., sensitivity and accuracy) is critical, dPCR can be an alternative option for quantifying microorganisms, including pathogens, in aquatic environments.

Global subtype diversity, spatial distribution patterns, and phylogenetic analysis of avian influenza virus in water.

The current COVID-19 pandemic highlights the need for zoonotic infectious disease surveillance. Avian influenza virus (AIV) poses a significant threat to animal and public health due to its pandemic potential. Virus-contaminated water has been suggested as an important AIV spread mechanism among multiple species. Nevertheless, few studies have characterized the global AIV subtype diversity and distribution in environmental water. Therefore, this study aims to provide an updated descriptive and phylogenetic analysis of AIVs isolated in water samples from high risk-sites for influenza outbreaks (i.e. live bird markets, poultry farms, and wild bird habitats) on a global scale. The descriptive analysis evidenced that 21 subtypes were reported from nine countries between 2003 and 2020. Fourteen AIV subtypes were solely reported from Asian countries. Most of the viral sequences were obtained in China and Bangladesh with 47.44% and 23.93%, respectively. Likewise, the greatest global AIV subtype diversity was observed in China with 12 subtypes. Live bird markets represented the main sampling site for AIV detection in water samples (64.1%), mostly from poultry cage water. Nevertheless, the highest subtype diversity was observed in water samples from wild bird habitats, especially from the Izumi plain and the Dongting Lake located in Japan and China, respectively. Water from drinking poultry troughs evidenced the greatest subtype diversity in live bird markets; meanwhile, environmental water used by ducks had the highest number of different subtypes in poultry farms. Maximum-likelihood phylogenetic trees of hemagglutinin (HA) and neuraminidase (NA) genes showed that some sequences were closely related among different poultry/wild bird-related environments from different geographic origins. Therefore, the results suggest that even though the availability of gene sequences in public-access databases varies greatly among countries, environmental AIV surveillance represents a useful tool to elucidate potential viral diversity in wild and domestic bird populations.