Microbial community and antimicrobial resistance niche differentiation in a multistage, surface flow constructed wetland.

Free-living (FL) and particulate-associated (PA) communities are distinct bacterioplankton lifestyles with different mobility and dissemination routes. Understanding spatio-temporal dynamics of PA and FL fractions will allow improvement to wastewater treatment processes including pathogen and AMR bacteria removal. In this study, PA, FL and sediment community composition and antimicrobial resistance gene (ARG; tetW, ermB, sul1, intI1) dynamics were investigated in a full-scale municipal wastewater free-water surface polishing constructed wetland. Taxonomic composition of PA and FL microbial communities shifted towards less diverse communities (Shannon, Chao1) at the CW effluent but retained a distinct fraction-specific composition. Wastewater treatment plant derived PA communities introduced the bulk of AMR load (70 %) into the CW. However, the FL fraction was responsible for exporting over 60 % of the effluent AMR load given its high mobility and the effective immobilization (1-3 log removal) of PA communities. Strong correlations (r2>0.8, p < 0.05) were observed between the FL fraction, tetW and emrB dynamics, and amplicon sequence variants (ASVs) of potentially pathogenic taxa, including Bacteroides, Enterobacteriaceae, Aeromonadaceae, and Lachnospiraceae. This study reveals niche differentiation of microbial communities and associated AMR in CWs and shows that free-living bacteria are a primary escape route of pathogenic and ARG load from CWs under low-flow hydraulic conditions.

PyPop: a mature open-source software pipeline for population genomics.

Python for Population Genomics (PyPop) is a software package that processes genotype and allele data and performs large-scale population genetic analyses on highly polymorphic multi-locus genotype data. In particular, PyPop tests data conformity to Hardy-Weinberg equilibrium expectations, performs Ewens-Watterson tests for selection, estimates haplotype frequencies, measures linkage disequilibrium, and tests significance. Standardized means of performing these tests is key for contemporary studies of evolutionary biology and population genetics, and these tests are central to genetic studies of disease association as well. Here, we present PyPop 1.0.0, a new major release of the package, which implements new features using the more robust infrastructure of GitHub, and is distributed via the industry-standard Python Package Index. New features include implementation of the asymmetric linkage disequilibrium measures and, of particular interest to the immunogenetics research communities, support for modern nomenclature, including colon-delimited allele names, and improvements to meta-analysis features for aggregating outputs for multiple populations. Code available at: https://zenodo.org/records/10080668 and https://github.com/alexlancaster/pypop.

National-scale antimicrobial resistance surveillance in wastewater: A comparative analysis of HT qPCR and metagenomic approaches.

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.