Bioavailability of potentially toxic elements influences antibiotic resistance gene and mobile genetic element abundances in urban and rural soils

Effects of Organic Soil Amendments on Antimicrobial-Resistant Bacteria in Urban Agriculture Environments

Biological soil amendments of animal origin (BSAAOs) are widely used in urban agriculture to improve soil quality. Although BSAAO use is regulated due to risks for introducing foodborne pathogens, effects on antimicrobial-resistant (AMR) bacteria are not well established. Here, we aimed to explore the impacts of BSAAOs on levels of resident AMR bacteria in leafy vegetable production environments (i.e., kale, lettuce, chard, cabbage) across urban farms and community gardens in the greater Washington D.C. area (n = 7 sites). Leaf tissue (LT), root zone soil (RZS; amended soil in crop beds), and bulk soil (BS; site perimeter) were collected and analyzed for concentrations of total heterotrophic bacteria (THB), ampicillin (Amp) or tetracycline (Tet) resistant THB, and coliforms. As expected, amended plots harbored significantly higher concentrations of THB than bulk soil (P < 0.001). The increases in total bacteria associated with reduced fractions of Tet-resistant bacteria (P = 0.008), as well as case-specific trends for reduced fractions of Amp-resistant bacteria and coliforms. Site-to-site variation in concentrations of AMR bacteria in soil and vegetable samples reflected differences in land history and crop management, while within-site variation was associated with specific amendment sources, as well as vegetable type and cultivar. Representative isolates of the AMR bacteria and coliforms were further screened for multidrug resistance (MDR) phenotypes, and a high frequency was observed for the former. In amended soils, as the soil pH (range 6.56-7.80) positively correlated with the fraction of Tet-resistant bacteria (rho = 0.529; P < 0.001), crop management strategies targeting pH may have applications to control related risks. Overall, our findings demonstrate that soil amendments promote soil bacteria concentrations and have important implications for limiting the spread of AMR bacteria, at least in the urban landscape.

Antimicrobial resistance in rural rivers: Comparative study of the Coquet (Northumberland) and Eden (Cumbria) River catchments

Many studies have characterised resistomes in river microbial communities. However, few have compared resistomes in parallel rural catchments that have few point-source inputs of antimicrobial genes (ARGs) and organisms (i.e., AMR) - catchments where one can contrast more nebulous drivers of AMR in rural rivers. Here, we used quantitative microbial profiling (QMP) to compare resistomes and microbiomes in two rural river catchments in Northern England, the Coquet and Eden in Northumberland and Cumbria, respectively, with different hydrological and geographical conditions. The Eden has higher flow rates, higher annual surface runoff, and longer periods of soil saturation, whereas the Coquet is drier and has lower flowrates. QMP analysis showed the Eden contained significantly more abundant microbes associated with soil sources, animal faeces, and wastewater than the Coquet, which had microbiomes like less polluted rivers (Wilcoxon test, p < 0.01). The Eden also had greater ARG abundances and resistome diversity (Kruskal Wallis, p < 0.05), and higher levels of potentially clinically relevant ARGs. The Eden catchment had greater and flashier runoff and more extensive agricultural land use in its middle reach, which explains higher levels of AMR in the river. Hydrological and geographic factors drive AMR in rural rivers, which must be considered in environmental monitoring programmes.

Antibiotic resistance genes and heavy metals in landfill: A review

Landfill is reservoir containing antibiotic resistance genes (ARGs) that pose a threat to human life and health. Heavy metals impose lasting effects on ARGs. This review investigated and analyzed the distribution, composition, and abundance of heavy metals and ARGs in landfill. The abundance ranges of ARGs detected in refuse and leachate were similar. The composition of ARG varied with sampling depth in refuse. ARG in leachate varies with the distribution of ARG in the refuse. The ARG of sulI was associated with 11 metals (Co, Pb, Mn, Zn, Cu, Cr, Ni, Sb, As, Cd, and Al). The effects of the total metal concentration on ARG abundance were masked by many factors. Low heavy metal concentrations showed positive effects on ARG diffusion; conversely, high heavy metal concentrations showed negative effects. Organic matter had a selective pressure effect on microorganisms and could provide energy for the diffusion of ARGs. Complexes of heavy metals and organic matter were common in landfill. Therefore, the hypothesis was proposed that organic matter and heavy metals have combined effects on the horizontal gene transfer (HGT) of ARGs during landfill stabilization. This work provides a new basis to better understand the HGT of ARGs in landfill.

The need for One Health systems-thinking approaches to understand multiscale dissemination of antimicrobial resistance

Although the effects of antimicrobial resistance (AMR) are most obvious at clinical treatment failure, AMR evolution, transmission, and dispersal happen largely in environmental settings, for example within farms, waterways, livestock, and wildlife. We argue that systems-thinking, One Health approaches are crucial for tackling AMR, by understanding and predicting how anthropogenic activities interact within environmental subsystems, to drive AMR emergence and transmission. Innovative computational methods integrating big data streams (eg, from clinical, agricultural, and environmental monitoring) will accelerate our understanding of AMR, supporting decision making. There are challenges to accessing, integrating, synthesising, and interpreting such complex, multidimensional, heterogeneous datasets, including the lack of specific metrics to quantify anthropogenic AMR. Moreover, data confidentiality, geopolitical and cultural variation, surveillance gaps, and science funding cause biases, uncertainty, and gaps in AMR data and metadata. Combining systems-thinking with modelling will allow exploration, scaling-up, and extrapolation of existing data. This combination will provide vital understanding of the dynamic movement and transmission of AMR within and among environmental subsystems, and its effects across the greater system. Consequently, strategies for slowing down AMR dissemination can be modelled and compared for efficacy and cost-effectiveness.