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The prevalence of antibiotic resistance genes (ARGs) in waste sludge, especially for the pharmaceutical waste sludge, presents great potential risks to human health. Although ARGs and factors affecting their spreading are of major importance for human health, the factors influencing the fate of ARGs during sludge treatment, especially for pharmaceutical sludge treatment are not yet well understood. In order to be able to minimize ARGs spreading, it is important to find what is influencing their spreading. Therefore, certain factors, such as the sludge characteristics, bacterial diversity and community composition, and mobile genetic elements (MGEs) during the advanced AD of pharmaceutical sludge with different pretreatments were studied, and their affinity with ARGs was elucidated by Spearman correlation analysis. Furthermore, multiple linear regression was introduced to evaluate the importance of the various factors. Results showed that 59.7%–88.3% of the variations in individual ARGs and total ARGs can be explained by the corresponding factors. Bacterial diversity rather than specific bacterial community composition affected the fate of ARGs, whereas alkalinity was the most important factor on ARGs among all sludge characteristics investigated in this study. Besides, 66.4% of variation of total ARGs was driven by the changes of MGEs. Multiple linear regression models also reveal the collective effect of these factors on ARGs, and the contributions of each factor impact on ARGs. This study provides more comprehension about the factors impact on the fate of ARGs during pharmaceutical sludge treatment, and offers an approach to evaluate the importance of each factor, which method could be introduced for evaluation of factors influencing ARGs during other types of sludge or wastewater treatment.
Original languageEnglish
JournalEnvironmental Pollution
ISSN0269-7491
DOIs
StateAccepted/In press - 2018
CitationsWeb of Science® Times Cited: No match on DOI

    Research areas

  • Antibiotic resistance genes (ARGs), Mobile genetic elements (MGEs), Bacterial community, Sludge characteristics, Multiple linear regression
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