As the most diverse vertebrate group and a major component of a growing global aquaculture industry, teleosts continue to attract significant scientific attention. The growth in global aquaculture, driven by declines in wild stocks, has provided additional empirical demand, and thus opportunities, to explore teleost diversity. Among key developments is the recent growth in microbiome exploration, facilitated by advances in high-throughput sequencing technologies. Here, we consider studies on teleost gut microbiomes in the context of sustainable aquaculture, which we have discussed in four themes: diet, immunity, artificial selection and closed-loop systems. We demonstrate the influence aquaculture has had on gut microbiome research, while also providing a road map for the main deterministic forces that influence the gut microbiome, with topical applications to aquaculture. Functional significance is considered within an aquaculture context with reference to impacts on nutrition and immunity. Finally, we identify key knowledge gaps, both methodological and conceptual, and propose promising applications of gut microbiome manipulation to aquaculture, and future priorities in microbiome research. These include insect-based feeds, vaccination, mechanism of pro- and prebiotics, artificial selection on the hologenome, in-water bacteriophages in recirculating aquaculture systems (RAS), physiochemical properties of water and dysbiosis as a biomarker.

Wastewater serves as an important reservoir of antimicrobial resistance (AMR), and its surveillance can provide insights into population-level trends in AMR to inform public health policy. This study compared two common high-throughput screening approaches, namely (i) high-throughput quantitative PCR (HT qPCR), targeting 73 antimicrobial resistance genes, and (ii) metagenomic sequencing. Weekly composite samples of wastewater influent were taken from 47 wastewater treatment plants (WWTPs) across Wales, as part of a national AMR surveillance programme, alongside 4 weeks of daily wastewater effluent samples from a large municipal hospital. Metagenomic analysis provided more comprehensive resistome coverage, detecting 545 genes compared to the targeted 73 genes by HT qPCR. It further provided contextual information critical to risk assessment (i.e. potential bacterial hosts). In contrast, HT qPCR exhibited higher sensitivity, quantifying all targeted genes including those of clinical relevance present at low abundance. When limited to the HT qPCR target genes, both methods were able to reflect the spatiotemporal dynamics of the complete metagenomic resistome, distinguishing that of the hospital and the WWTPs. Both approaches revealed correlations between resistome compositional shifts and environmental variables like ammonium wastewater concentration, though differed in their interpretation of some potential influencing factors. Overall, metagenomics provides more comprehensive resistome profiling, while qPCR permits sensitive quantification of genes significant to clinical resistance. We highlight the importance of selecting appropriate methodologies aligned to surveillance aims to guide the development of effective wastewater-based AMR monitoring programmes.

Anthropogenically forced changes in global freshwater biodiversity demand more efficient monitoring approaches. Consequently, environmental DNA (eDNA) analysis is enabling ecosystem-scale biodiversity assessment, yet the appropriate spatio-temporal resolution of robust biodiversity assessment remains ambiguous. Here, using intensive, spatio-temporal eDNA sampling across space (five rivers in Europe and North America, with an upper range of 20–35 km between samples), time (19 timepoints between 2017 and 2018) and environmental conditions (river flow, pH, conductivity, temperature and rainfall), we characterise the resolution at which information on diversity across the animal kingdom can be gathered from rivers using eDNA. In space, beta diversity was mainly dictated by turnover, on a scale of tens of kilometres, highlighting that diversity measures are not confounded by eDNA from upstream. Fish communities showed nested assemblages along some rivers, coinciding with habitat use. Across time, seasonal life history events, including salmon and eel migration, were detected. Finally, effects of environmental conditions were taxon-specific, reflecting habitat filtering of communities rather than effects on DNA molecules. We conclude that riverine eDNA metabarcoding can measure biodiversity at spatio-temporal scales relevant to species and community ecology, demonstrating its utility in delivering insights into river community ecology during a time of environmental change.

Healthcare settings are recognised as potential hotspots for the emergence and spread of antimicrobial resistance (AMR). Metagenomic sequencing was conducted on a national scale using wastewater from hospitals across Wales to screen for antimicrobial resistance genes (ARGs) and opportunistic pathogens. The total abundance and diversity of ARGs varied significantly across the hospitals. Genes conferring resistance to aminoglycosides, beta-lactams, and Macrolide-Lincosamide-Streptogramin-class antibiotics were predominant, with distinct resistome patterns emerging spatially. OXA-type beta-lactamases were the dominant ARG types. Spatial variability was observed in the distribution of the "big five" carbapenemases (KPC, IMP, VIM, NDM, OXA-48-like) and mcr genes, as well as WHO-listed fungal priority pathogens and Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter spp., and Escherichia coli (ESKAPEE) pathogens. Furthermore, antibiotic concentrations in the effluents often exceeded risk quotients, posing a substantial risk for AMR emergence. Overall, the study highlights the effectiveness of combining wastewater-based epidemiology with metagenomics to gain critical insights into the distinct resistome and microbiome profiles in hospital settings. Tailored strategies are essential to mitigate the spread of antibiotics, clinically relevant ARGs and pathogens in these settings. This study underscores the necessity of implementing pre-treatment processes for hospital effluents before release into community sewers and environmental waters to curb the spread of these micro-pollutants.

Most sewer networks collect domestic wastewater and a variable proportion of extraneous water, such as rainwater, through surface runoff and industrial discharges. Accounting for wastewater dilution is essential to properly quantify wastewater particle loads, whether these are molecular fragments of SARS-CoV-2, or other substances of interest such as illicit drugs or microplastics. This paper presents a novel method for obtaining real-time estimates of wastewater dilution and total daily volume through wastewater treatment works, namely when flow data is not available or unreliable. The approach considers the levels of several physico-chemical markers (ammonia, electrical conductivity, and orthophosphate) in the wastewater against their dry-weather levels. Using high-resolution data from the national Wastewater Surveillance Programme of Wales, we illustrate how the method is robust to spikes in markers and can recover peaks in wastewater flow measurements that may have been capped by hydraulic relief valves. We show the method proves effective in normalising SARS-CoV-2 viral loads in wastewater samples and discuss other applications for this method, looking at wastewater surveillance as a vital tool to monitor both human and environmental health.