The Overlap of Soil and Vegetable Microbes Driving the Transfer of Antibiotic Resistance Genes from Manure-Amended Soil to Vegetables

2022 ◽  
Author(s):  
Fenghua Wang ◽  
Ruibo Sun ◽  
Hang-Wei Hu ◽  
Guilan Duan ◽  
Liang Meng ◽  
...  
Author(s):  
Harmanpreet Sidhu ◽  
Hee-Sung Bae ◽  
Andrew Ogram ◽  
George O’Connor ◽  
Fahong Yu

Spread of biosolids-borne antibiotic resistance is a growing public and environmental health concern. Herein we conducted incubation experiments involving biosolids, derived from sewage treatment plants, and biosolids-amended soil. Quantitative reverse transcription PCR (RT-qPCR) was employed to assess responses of select antibiotic resistance genes (ARGs) and mobile elements to environmentally relevant concentrations of two biosolids-borne antibiotics, azithromycin (AZ) and ciprofloxacin (CIP). Additionally, we examined sequence distribution of gyrA (encoding DNA gyrase; site of action of CIP) to assess potential shifts in genotype. Increasing antibiotic concentrations generally increased the transcriptional activities of qnrS (encoding CIP resistance) and ermB and mefE (encoding AZ resistance). The transcriptional activity of intl1 , a marker of Class 1 integrons, was unaffected by CIP or AZ concentrations, but biosolids amendment increased intl1 activity in the soil by 4 to 5 times which persisted throughout incubation. While the dominant gyrA sequences found herein were unrelated to known CIP-resistant genotypes, the increasing CIP concentrations significantly decreased the diversity of genes encoding gyrA , suggesting changes in microbial community structures. This study suggests that biosolids harbor transcriptionally active ARGs and mobile elements that could survive and spread in biosolids-amended soils. However, more research is warranted to investigate these trends under field conditions. IMPORTANCE Although previous studies have indicated that biosolids may be important spreaders of antibiotics and antibiotic resistance genes (ARGs) in environments, the potential activities of ARGs or their responses to environmental parameters have been understudied. This study highlights that certain biosolids-borne antibiotics can induce transcriptional activities of ARGs and mobile genetic elements in biosolids and biosolids-amended soil, even when present at environmentally relevant concentrations. Furthermore, these antibiotics can alter the structure of microbial population expressing ARGs. Our findings indicate the bioavailability of the antibiotics in biosolids and provide evidence that biosolids can promote the activities and dissemination of ARGs and mobile genes in biosolids and soils that receive contaminated biosolids; thus, underscoring the importance of investigating anthropogenically-induced antibiotic resistance in the environment under real-world scenarios.


2015 ◽  
Vol 299 ◽  
pp. 215-221 ◽  
Author(s):  
Feng-Hua Wang ◽  
Min Qiao ◽  
Zheng Chen ◽  
Jian-Qiang Su ◽  
Yong-Guan Zhu

2020 ◽  
Author(s):  
Sankalp Arya ◽  
Alexander Williams ◽  
Saul Vazquez Reina ◽  
Charles W. Knapp ◽  
Jan-Ulrich Kreft ◽  
...  

Abstract Many antibiotic resistance genes co-occur with resistance genes for transition metals, such as copper, zinc, or mercury. In some environments, a positive correlation between high metal concentration and high abundance of antibiotic resistance genes has been observed, suggesting co-selection due to metal presence. Of particular concern is the use of copper and zinc in animal husbandry, leading to potential co-selection for antibiotic resistance in animal gut microbiomes, slurry, manure, or amended soils. For antibiotics, predicted no effect concentrations have been derived from laboratory measured minimum inhibitory concentrations and some minimal selective concentrations have been investigated in environmental settings. However, minimal co-selection concentrations for metals are difficult to identify. Here, we use mathematical modelling to provide a general mechanistic framework to predict minimal co-selective concentrations for metals, given knowledge of their toxicity at different concentrations. We apply the method to copper (Cu), Zinc (Zn), mercury (Hg), lead (Pb) and silver (Ag), predicting their minimum co-selective concentrations in mg/L (Cu: 5.5, Zn: 1.6, Hg: 0.0156, Pb: 21.5, Ag: 0.152). To exemplify use of these thresholds, we consider metal concentrations from slurry and slurry-amended soil from a UK dairy farm that uses copper and zinc as additives for feed and antimicrobial footbath: the slurry is predicted to be co-selective, but not the slurry-amended soil. This modelling framework could be used as the basis for defining standards to mitigate risks of antimicrobial resistance applicable to a wide range of environments, including manure, slurry and other waste streams.


2016 ◽  
Vol 1 (2) ◽  
pp. 22 ◽  
Author(s):  
Navindra Kumari Palanisamy ◽  
Parasakthi Navaratnam ◽  
Shamala Devi Sekaran

Introduction: Streptococcus pneumoniae is an important bacterial pathogen, causing respiratory infection. Penicillin resistance in S. pneumoniae is associated with alterations in the penicillin binding proteins, while resistance to macrolides is conferred either by the modification of the ribosomal target site or efflux mechanism. This study aimed to characterize S. pneumoniae and its antibiotic resistance genes using 2 sets of multiplex PCRs. Methods: A quintuplex and triplex PCR was used to characterize the pbp1A, ermB, gyrA, ply, and the mefE genes. Fifty-eight penicillin sensitive strains (PSSP), 36 penicillin intermediate strains (PISP) and 26 penicillin resistance strains (PRSP) were used. Results: Alteration in pbp1A was only observed in PISP and PRSP strains, while PCR amplification of the ermB or mefE was observed only in strains with reduced susceptibility to erythromycin. The assay was found to be sensitive as simulated blood cultures showed the lowest level of detection to be 10cfu. Conclusions: As predicted, the assay was able to differentiate penicillin susceptible from the non-susceptible strains based on the detection of the pbp1A gene, which correlated with the MIC value of the strains.


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