Identification of Selected Antibiotic Resistance Genes in Two Different Wastewater Treatment Plant Systems in Poland: A Preliminary Study.
Magdalena PazdaMagda RybickaStefan StolteKrzysztof Piotr BielawskiPiotr StepnowskiJolanta KumirskaDaniel WoleckiEwa MulkiewiczPublished in: Molecules (Basel, Switzerland) (2020)
Antibiotic resistance is a growing problem worldwide. The emergence and rapid spread of antibiotic resistance determinants have led to an increasing concern about the potential environmental and public health endangering. Wastewater treatment plants (WWTPs) play an important role in this phenomenon since antibacterial drugs introduced into wastewater can exert a selection pressure on antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs). Therefore, WWTPs are perceived as the main sources of antibiotics, ARB and ARG spread in various environmental components. Furthermore, technological processes used in WWTPs and its exploitation conditions may influence the effectiveness of antibiotic resistance determinants' elimination. The main aim of the present study was to compare the occurrence of selected tetracycline and sulfonamide resistance genes in raw influent and final effluent samples from two WWTPs different in terms of size and applied biological wastewater treatment processes (conventional activated sludge (AS)-based and combining a conventional AS-based method with constructed wetlands (CWs)). All 13 selected ARGs were detected in raw influent and final effluent samples from both WWTPs. Significant ARG enrichment, especially for tet(B, K, L, O) and sulIII genes, was observed in conventional WWTP. The obtained data did not show a clear trend in seasonal fluctuations in the abundance of selected resistance genes in wastewaters.
Keyphrases
- wastewater treatment
- antibiotic resistance genes
- bioinformatics analysis
- public health
- genome wide
- human health
- risk assessment
- genome wide identification
- randomized controlled trial
- systematic review
- depressive symptoms
- physical activity
- mental health
- dna methylation
- machine learning
- drinking water
- gene expression
- visible light