Insight into dynamics and bioavailability of antibiotics in paddy soils by in situ soil moisture sampler

Uddin, Misbah; Chen, Jingwen; Qiao, Xianliang; Tian, Run Xia; Zhu, Minghua

doi:10.1016/j.scitotenv.2019.135562

Cited by 23 publications

(16 citation statements)

References 64 publications

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“…Manure, as compared to fertilizers, is a major source of antibiotics and antimicrobial resistance genes due to the undefined use of antibiotics in animal farming ( Lin et al, 2016 ; Rahman et al, 2018 ). Different antibiotics and antibiotic resistance genes have been identified in the rice rhizosphere ( Uddin et al, 2020 ). The abundance of ARGs in paddy is positively correlated with antibiotics, soil properties including pH and soil organic matter (SOM), and heavy metals such as As, Cd, Cu, and Zn ( Tang et al, 2015 ; Lin et al, 2016 ; Cao et al, 2020 ; Zhao et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Biochar and Manure Applications Differentially Altered the Class 1 Integrons, Antimicrobial Resistance, and Gene Cassettes Diversity in Paddy Soils

et al. 2022

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Integrons are genetic components that are critically involved in bacterial evolution and antimicrobial resistance by assisting in the propagation and expression of gene cassettes. In recent decades, biochar has been introduced as a fertilizer to enhance physiochemical properties and crop yield of soil, while manure has been used as a fertilizer for centuries. The current study aimed to investigate the impact of biochar, manure, and a combination of biochar and manure on integrons, their gene cassettes, and relative antimicrobial resistance in paddy soil. Field experiments revealed class 1 (CL1) integrons were prevalent in all samples, with higher concentration and abundance in manure-treated plots than in biochar-treated ones. The gene cassette arrays in the paddy featured a broad pool of cassettes with a total of 35% novel gene cassettes. A majority of gene cassettes encoded resistance to aminoglycosides, heat shock protein, heavy metals, pilus secretory proteins, and twin-arginine translocases (Tat), TatA, TatB, and TatC. Both in combination and solo treatments, the diversity of gene cassettes was increased in the manure-enriched soil, however, biochar reduced the gene cassettes’ diversity and their cassettes array. Manure considerably enhanced CL1 integrons abundance and antimicrobial resistance, whereas biochar amendments significantly reduced integrons and antimicrobial resistance. The results highlighted the differential effects of biochar and manure on integrons and its gene cassette arrays, showing increased abundance of integrons and antibiotic resistance upon manure application and decrease of the same with biochar. The use of biochar alone or in combination with manure could be a beneficial alternative to mitigate the spread of antimicrobial resistance and bacterial evolution in the environment, specifically in paddy soils.

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Section: Introductionmentioning

confidence: 99%

Biochar and Manure Applications Differentially Altered the Class 1 Integrons, Antimicrobial Resistance, and Gene Cassettes Diversity in Paddy Soils

et al. 2022

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“…No significant correlation was observed between the dominant occurrence of quinolone and tetracycline antibiotics and microbial community composition in this study. The adsorption of these antibiotic groups onto the mineral phase of soil is a key factor influencing their mobility, stabilization, bioavailability, and bioaccessibility to microorganisms [ 64 , 65 ]. A bacterial community may develop antibiotic tolerance, which could also account for the lack of observed effects [ 66 , 67 ].…”

Section: Discussionmentioning

confidence: 99%

Adaptation of Rhizosphere Microbial Communities to Continuous Exposure to Multiple Residual Antibiotics in Vegetable Farms

Qiu

Chen

Feng

et al. 2023

IJERPH

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The constant application of manure-based fertilizers in vegetable farms leads to antibiotic residue accumulation in soils, which has become a major stressor affecting agroecosystem stability. The present study investigated the adaptation profiles of rhizosphere microbial communities in different vegetable farms to multiple residual antibiotics. Multiple antibiotics, including trimethoprim, sulfonamides, quinolones, tetracyclines, macrolides, lincomycins, and chloramphenicols, were detected in the vegetable farms; the dominant antibiotic (trimethoprim) had a maximum concentration of 36.7 ng/g. Quinolones and tetracyclines were the most prevalent antibiotics in the vegetable farms. The five most abundant phyla in soil samples were Proteobacteria, Actinobacteria, Acidobacteria, Chloroflexi and Firmicutes, while the five most abundant phyla in root samples were Proteobacteria, Actinobacteria, Bacteroidetes, Firmicutes and Myxococcota. Macrolides were significantly correlated with microbial community composition changes in soil samples, while sulfonamides were significantly correlated with microbial community composition changes in root samples. Soil properties (total carbon and nitrogen contents and pH) influenced the shifts in microbial communities in rhizosphere soils and roots. This study provides evidence that low residual antibiotic levels in vegetable farms can shift microbial community structures, potentially affecting agroecosystem stability. However, the degree to which the shift occurs could be regulated by environmental factors, such as soil nutrient conditions.

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“…Yes grown carrot, sweet potato and wheat (Malachi et al, 2014), individually grown spinach, arugula and radish (Kodesova et al, 2019) or comparing between rice and no plants (Kodesova et al, 2019)). There are also variations in terms of different irrigation regimes (e.g., daily (Uddin et al, 2020), approximately every two days (Kodesova et al, 2019); for 35 min at a time (Koroša et al, 2020) or until column saturation (Yu et al, 2020)). Column experimental setups also contact the water with the soil via different methods, like drip irrigation (Paz et al, 2016), sprinkle irrigation (Koroša et al, 2020), or saturation of the soil column (Uddin et al, 2020;Yu et al, 2020).…”

Section: Tablementioning

confidence: 99%

“…There are also variations in terms of different irrigation regimes (e.g., daily (Uddin et al, 2020), approximately every two days (Kodesova et al, 2019); for 35 min at a time (Koroša et al, 2020) or until column saturation (Yu et al, 2020)). Column experimental setups also contact the water with the soil via different methods, like drip irrigation (Paz et al, 2016), sprinkle irrigation (Koroša et al, 2020), or saturation of the soil column (Uddin et al, 2020;Yu et al, 2020). It is possible to enter qualitative variables as quantitative variables in a model but only as binary ('yes or no') variables (Agudelo-Jaramillo et al, 2016).…”

Section: Tablementioning

confidence: 99%

“…Cation exchange capacity (CEC) of soil was not always reported in the same units and so all CEC data was converted to cmol kg −1 . All except one study reported organic carbon content of the soil and one study reported organic matter (Uddin et al, 2020) (Table 3), a factor of 1.72 was used to convert total organic carbon to organic matter (Fenton et al, 2008). The soil pH, pollutant's pK a and LogK ow were entered as LogD (Schaffer et al, 2012), based on Eqs.…”

Section: Tablementioning

confidence: 99%

See 1 more Smart Citation

Meta-analysis and machine learning to explore soil-water partitioning of common pharmaceuticals

Garduño-Jiménez

Durán–Álvarez

Gomes

2022

Science of The Total Environment

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Insight into dynamics and bioavailability of antibiotics in paddy soils by in situ soil moisture sampler

Cited by 23 publications

References 64 publications

Biochar and Manure Applications Differentially Altered the Class 1 Integrons, Antimicrobial Resistance, and Gene Cassettes Diversity in Paddy Soils

Biochar and Manure Applications Differentially Altered the Class 1 Integrons, Antimicrobial Resistance, and Gene Cassettes Diversity in Paddy Soils

Adaptation of Rhizosphere Microbial Communities to Continuous Exposure to Multiple Residual Antibiotics in Vegetable Farms

Meta-analysis and machine learning to explore soil-water partitioning of common pharmaceuticals

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