A weight-of-evidence approach for identifying potential sources of untreated sewage inputs into a complex urbanized catchment.

The Hawkesbury-Nepean River (HNR) is the largest catchment in the Sydney region and is undergoing unprecedented population growth. The HNR system receives a mix of anthropogenic inputs such as treated sewage, stormwater and agricultural runoff. Combined, these can diminish the ecological system health and pose potential concerns to human health. Of particular concern are inputs of untreated sewage, that can occur due to a range of different reasons including illegal point source discharges, failure of the sewerage network, and overloading of wastewater treatment plants during storm events. Here, we present findings of an intensive assessment across the HNR catchment where we used a weight-of-evidence (WOE) approach to identify untreated sewage contamination in surface waters against the background of treated effluent and diffuse inputs during post high flow conditions. Total nitrogen and phosphorus concentrations were used to assess treated effluent and diffuse inputs, and microbial analysis, including both culture-based traditional methods for E. coli and enterococci and qPCR analysis of Bacteroides and Lachnospiraceae, were used to assess raw sewage contamination. Despite a background of diffuse inputs from recent high flow events and the influence of treated wastewater, we found no gradient of faecal contamination along the HNR system or its tributaries. We observed two sites with evidence of untreated sewage contamination, where the human markers Bacteroides and Lachnospiraceae qPCR copy numbers were high. The biological and chemical approaches suggested these latter two hotspots originate from an industrial runoff source and possibly from a dry weather sewage leak. Our findings demonstrate the potential of a WOE approach in the assessment of human faecal signal in an urban river that can also pinpoint small sources of contamination as a strategy that can reshape the way monitoring is performed and the chemical end-points chosen to provide pertinent information on the potential risks to aquatic system health.

Increased genetic diversity and prevalence of co-infection with Trypanosoma spp. in koalas (Phascolarctos cinereus) and their ticks identified using next-generation sequencing (NGS).

Infections with Trypanosoma spp. have been associated with poor health and decreased survival of koalas (Phascolarctos cinereus), particularly in the presence of concurrent pathogens such as Chlamydia and koala retrovirus. The present study describes the application of a next-generation sequencing (NGS)-based assay to characterise the prevalence and genetic diversity of trypanosome communities in koalas and two native species of ticks (Ixodes holocyclus and I. tasmani) removed from koala hosts. Among 168 koalas tested, 32.2% (95% CI: 25.2-39.8%) were positive for at least one Trypanosoma sp. Previously described Trypanosoma spp. from koalas were identified, including T. irwini (32.1%, 95% CI: 25.2-39.8%), T. gilletti (25%, 95% CI: 18.7-32.3%), T. copemani (27.4%, 95% CI: 20.8-34.8%) and T. vegrandis (10.1%, 95% CI: 6.0-15.7%). Trypanosoma noyesi was detected for the first time in koalas, although at a low prevalence (0.6% 95% CI: 0-3.3%), and a novel species (Trypanosoma sp. AB-2017) was identified at a prevalence of 4.8% (95% CI: 2.1-9.2%). Mixed infections with up to five species were present in 27.4% (95% CI: 21-35%) of the koalas, which was significantly higher than the prevalence of single infections 4.8% (95% CI: 2-9%). Overall, a considerably higher proportion (79.7%) of the Trypanosoma sequences isolated from koala blood samples were identified as T. irwini, suggesting this is the dominant species. Co-infections involving T. gilletti, T. irwini, T. copemani, T. vegrandis and Trypanosoma sp. AB-2017 were also detected in ticks, with T. gilletti and T. copemani being the dominant species within the invertebrate hosts. Direct Sanger sequencing of Trypanosoma 18S rRNA gene amplicons was also performed and results revealed that this method was only able to identify the genotypes with greater amount of reads (according to NGS) within koala samples, which highlights the advantages of NGS in detecting mixed infections. The present study provides new insights on the natural genetic diversity of Trypanosoma communities infecting koalas and constitutes a benchmark for future clinical and epidemiological studies required to quantify the contribution of trypanosome infections on koala survival rates.