Prevalence and abundance of traditional and host-associated fecal indicators in urban estuarine sediments: Potential implications for estuarine water quality monitoring.

This study aimed to determine the prevalence and abundance of sewage and animal fecal contamination of sediment at seven estuarine locations in Sydney, NSW, Australia. Sediment samples were tested for the occurrence of microbial targets including molecular marker genes of enterococci (ENT), Bacteroides HF183 (HF183), Methanobrevibacter smithii (nifH), human adenovirus (HAdV) and emerging sewage-associated marker genes crAssphage (CPQ_056) and Lachnospiraceae (Lachno3) and animal feces-associated marker genes, including avian feces-associated Helicobacter spp. (GFD), canine-feces associated Bacteroides (DogBact), cattle-feces associated (cowM2) and horse feces-associated Bacteroides (HoF597).

Marker genes of fecal indicator bacteria and potential pathogens in animal feces in subtropical catchments.

We investigated the abundance of marker genes of two fecal indicator bacteria (FIB) and eight potential pathogens in fecal samples of humans (n = 14) and 10 domestic and native wild animals (n = 134). For each target animal, between 10 and 14 individual fecal samples were collected (n = 148 individual fecal samples in total). The abundance of FIB and potential pathogens within each sample was determined using quantitative PCR (qPCR) assays.

Precipitation influences pathogenic bacteria and antibiotic resistance gene abundance in storm drain outfalls in coastal sub-tropical waters.

Stormwater contamination can threaten the health of aquatic ecosystems and human exposed to runoff via nutrient and pathogen influxes. In this study, the concentrations of 11 bacterial pathogens and 47 antibiotic resistance genes (ARGs) were determined by using high-throughput microfluidic qPCR (MFQPCR) in several storm drain outfalls (SDOs) during dry and wet weather in Tampa Bay, Florida, USA. Data generated in this study were also compared with the levels of fecal indicator bacteria (FIB) and sewage-associated molecular markers (i.

Evaluating water quality investments using cost utility analysis.

This study borrows concepts from healthcare economics and uses cost utility analysis (CUA) to select an optimum portfolio of water quality enhancement projects in Perth, Western Australia. In CUA, costs are handled via standard discounted cash flow analysis, but the benefits, being intangible, are measured with a utility score. Our novel methodology combines CUA with a binary combinatorial optimisation solver, known as a 'knapsack algorithm', to identify the optimum portfolio of projects.