Distribution of pathogens and antibiotic resistance genes in the vadose zone of soil-aquifer treatment (SAT) system.

Abstract

<p>The main objective of this study was to quantify the distribution of pathogens and antibiotic resistance genes in the vadose zone of the soil aquifer treatment (SAT) system. Soil samples were collected from a treated wastewater infiltration basin to a depth of 25 m in two sampling events: (i) at the end of flooding and infiltration and (ii) following three days of drying before the subsequent flooding event. Viable count parallelly of bacteria compared with microscopic live/dead count and enzymatic activity FDA hydrolysis. The abundance of the total bacteria, coliform, antibiotic resistance bacteria (ARB), were examined.  In addition, total genomic DNA was extracted from soil samples (n-28 for both flooding and drying cycle), and quantitative PCR (qPCR) was used to determine the relative abundance of antimicrobial resistance genes (ARGs), including 1 integron-integrase intI1, blaTEM, blaCTX-M-32, sul1, qnrS.</p><p>In both sampling events, the results demonstrate that the distribution of antibiotic resistance genes in the vadose zone exhibits a similar pattern to the one obtained for the examined pathogen. We observed a high concentration of pathogens in topsoil layers and a gradual decline with depth. In this presentation, the profile obtained will be described and discussed with pathogens and ARGs transport and retention in the SAT system. </p><p> </p><p> </p>

Estimating bacterial breakthrough behaviors based on bacterial retention profiles in porous media

“…Research indicates that bacterial concentrations in natural soils, permeable sand aquifers, and organic fertilizers typically range from 10 6 to 10 9 cells per gram (Bressan et al, 2015;F. Chen et al, 2023;DeFlaun et al, 1997;Yadav et al, 2022). This range underscores the significant diversity in microbial densities across these environments.…”

“…In contrast, collecting multiple RPs can illustrate the dynamic distribution of bacteria, thereby enabling more robust transport modeling. Such profiles can be acquired through soil sampling at specific time points or before and after particular field events like rainfall, irrigation, and flooding (Stocker et al., 2015; Stoddard et al., 1998; Yadav et al., 2022). Following collection, bacterial concentrations in the soil can be determined using various counting methods, including plate count, microscopy count, quantitative polymerase chain reaction (qPCR), bioluminescent count, flow cytometry method, and geometric viability assay (Foght & Aislabie, 2005; Gyawali et al., 2016; Lee et al., 2021; Meyer et al., 2023; Vignola et al., 2018; Yang et al., 2021; Zhang et al., 2022).…”

“…Following collection, bacterial concentrations in the soil can be determined using various counting methods, including plate count, microscopy count, quantitative polymerase chain reaction (qPCR), bioluminescent count, flow cytometry method, and geometric viability assay (Foght & Aislabie, 2005; Gyawali et al., 2016; Lee et al., 2021; Meyer et al., 2023; Vignola et al., 2018; Yang et al., 2021; Zhang et al., 2022). Research indicates that bacterial concentrations in natural soils, permeable sand aquifers, and organic fertilizers typically range from 10 6 to 10 9 cells per gram (Bressan et al., 2015; F. Chen et al., 2023; DeFlaun et al., 1997; Yadav et al., 2022). This range underscores the significant diversity in microbial densities across these environments.…”