New parameters for the quantitative assessment of the proliferation of antibiotic resistance genes dynamic in the environment and its application: A case of sulfonamides and sulfonamide resistance genes

Dissipation of Sulfonamides in Soil Emphasizing Taxonomy and Function of Microbiomes by Metagenomic Analysis

“…For PLS modeling, DT 50 derived from dissipation in nonsterile soil (reflecting overall dissipation, labeled with D) was set as a dependent variable and the difference in DT 50 between sterile and nonsterile soil (reflecting microbial degradation contribution to overall dissipation, labeled with M) and K F derived from the Freundlich isotherm model (reflecting sorption contribution to overall dissipation, labeled with K) were set as independent variables. As seen from PLS modeling results (Table S3), both determination coefficient ( R 2 = 0.777) and cross-validated determination coefficient ( Q 2 = 0.547) are higher than 0.5 and the difference between R 2 and Q 2 ( R 2 – Q 2 = 0.23) is lower than 0.3, indicating that the relationship developed is excellent due to no irrelevant terms and few outliers. , In addition, the Williams plot based on standardized residuals (δ) and leverage values ( h i ) (Figure S5) shows that δ lies between −3 and 3 and all of the h i values are lower than warning leverage h *, revealing no outliers for the response. , Consequently, the relationship developed is robust and reliable. From Table S3, the relationship between overall dissipation and biodegradation/sorption can be described with important diagnostics as follows where D represents overall dissipation of SAs in soil (i.e., DT 50 derived from dissipation in nonsterile soil), M represents microbial degradation contribution to overall dissipation (i.e., the difference in DT 50 between sterile and nonsterile soils), K represents sorption contribution to overall dissipation (i.e., K F derived from the Freundlich isotherm model), R 2 is the determination coefficient, and Q 2 is the cross-validated determination coefficient.…”

“…However, the relationship between overall dissipation and biodegradation/sorption and the relative importance of biodegradation/sorption to overall dissipation remain ambiguous. In this work, therefore, we try to solve this problem through PLS analysis aided with software SIMCA . For PLS modeling, DT 50 derived from dissipation in nonsterile soil (reflecting overall dissipation, labeled with D) was set as a dependent variable and the difference in DT 50 between sterile and nonsterile soil (reflecting microbial degradation contribution to overall dissipation, labeled with M) and K F derived from the Freundlich isotherm model (reflecting sorption contribution to overall dissipation, labeled with K) were set as independent variables.…”

“…In this study, 10 SAs, which were frequently detected in the environment, were chosen with an analytical grade from Aladdin Reagent Co., Ltd., i.e., sulfathiazole (STZ), sulfadiazine (SDZ), sulfapyridine (SPY), sulfamerazine (SMR), sulfamethazine (SMZ), sulfisoxazole (SSZ), sulfachlorpyridazine (SCP), sulfadoxine (SDX), sulfamethoxazole (SMX), and sulfadimethoxine (SDT). Soil collection and the physicochemical properties are identical to our previous work . Briefly, the soil samples were obtained from the surface horizon (depths of approximately 5–20 cm) at the Qianyanzhou Experimental Station (115°08′E, 26°75′N), Chinese Academy of Sciences, in Jiangxi Province, southern China.…”

“…One-way analysis of variance (ANOVA) at level p 50 and K F among SAs used, which was further verified by hierarchical cluster analysis. The possible relationship between overall dissipation behavior and dissipation factors and the relative importance of individual factors to overall dissipation were explored by PLS analysis aided with software SIMCA. ,, The abundance of taxonomic and functional profiles was visualized by a heatmap, and both principal component analysis (PCA) and nonmetric multidimensional scaling analysis (NMDS) were applied to group the samples. To compare the significant difference of taxonomic and functional profiles between different samples, STAMP software was employed. , Spearman correlation analysis was performed on the basis of abundance of taxonomic and functional profiles that were putatively involved in SA microbial degradation.…”

“…Soil collection and the physicochemical properties are identical to our previous work. 33 Briefly, the soil samples were obtained from the surface horizon (depths of approximately 5−20 cm) at the Qianyanzhou Experimental Station (115°08′E, 26°75′N), Chinese Academy of Sciences, in Jiangxi Province, southern China. This site experiences a subtropical warm and humid monsoon climate, and the soil sample consists of red soil.…”