Effects of biochar addition on the fate of ciprofloxacin and its associated antibiotic tolerance in an activated sludge microbiome. (1st August 2022)

• Record Type: Journal Article
• Authors: Oh, Seungdae; Kim, Youngjun; Choi, Donggeon; Park, Ji Won; Noh, Jin Hyung; Chung, Sang-Yeop; Maeng, Sung Kyu; Cha, Chang-Jun
• Is Part Of: Environmental pollution. Volume 306(2022)
• Publication Date: 2022-08-01
• Subjects: Pollution -- Periodicals; Pollution -- Environmental aspects -- Periodicals; Environmental Pollution -- Periodicals; Pollution -- Périodiques; Pollution -- Aspect de l'environnement -- Périodiques; Pollution -- Effets physiologiques -- Périodiques; Pollution; Pollution -- Environmental aspects; Periodicals; Electronic journals; 363.73
• DOI: 10.1016/j.envpol.2022.119407
• Languages: English
• ISSNs: 0269-7491

Abstract

Abstract: This study investigated the effects of adding biochar (BC) on the fate of ciprofloxacin (CIP) and its related antibiotic tolerance (AT) in activated sludge. Three activated sludge reactors were established with different types of BC, derived from apple, pear, and mulberry tree, respectively, and one reactor with no BC. All reactors were exposed to an environmentally relevant level of CIP that acted as a definitive selective pressure significantly promoting AT to four representative antibiotics (CIP, ampicillin, tetracycline, and polymyxin B) by up to two orders of magnitude. While CIP removal was negligible in the reactor without BC, the BC-dosed reactors effectively removed CIP (70–95% removals) through primarily adsorption by BC and biodegradation/biosorption by biomass. The AT in the BC-added reactors was suppressed by 10–99%, compared to that without BC. The BC addition played a key role in sequestering CIP, thereby decreasing the selective pressure that enabled the proactive prevention of AT increase. 16S rRNA gene sequencing analysis showed that the BC addition alleviated the CIP-mediated toxicity to community diversity and organisms related to phosphorous removal. Machine learning modeling with random forest and support vector models using AS microbiome data collectively pinpointed Achromobacter selected by CIP and strongly associated with the AT increase in activated sludge. The identification of Achromobacter as an important AT bacteria revealed by the machine learning modeling with multiple models was also validated with a linear Pearson's correlation analysis. Overall, our study highlighted Achromobacter as a potential useful sentinel for monitoring AT occurring in the environment and suggested BC as a promising additive in wastewater treatment to improve micropollutant removal, mitigate potential AT propagation, and maintain community diversity against toxic antibiotic loadings. Graphical abstract: Image 1 Highlights: Ciprofloxacin acted as the selective pressure inducing antibiotic tolerance to four antibiotics. Machine learning identified Achromobacter as major potential antibiotic tolerant bacteria. Biochar-added reactors significantly enhanced ciprofloxacin removals. Biochar-added reactors suppressed propagation of antibiotic tolerance. Biochar addition reduced ciprofloxacin toxicity to biodiversity and potential ecosystem functions.