.Yadav.Kapley/Scence of the Total 692(01)1155-1164 as p CeOfanDiotictsgai tro et al 20 dos Santos).The me ic ar nds in the divers tance (Berund.5:Chet 201 201 abun and Antibiotic Res tance Bacteria(ARBs)are ortant factors which pha gonresisto ome profiling of a ctivated sludge from India Mos 2014-Eu e.2017).U5g ted sludge san WWTPs.A ndia ing nex the treat aeC品8a9 mpr ing the a ce of the s,and MGEs in a qured infections(WHO.01).Such first time the study rep orts the al f ARGs and MGE rd to ug re ering antibiotics as a poten 2 Materials methods e (o tl,2017: es et 2.1.Sampling and ype 22013L a it be vska and Pilla.2017 54 ent Plants(STPs ies.Sim PlantE )in higher con tracted fromeach samplng bote in duplicate(1for each samp ance.Also,thes are rich in nutrient concentration,whicl samples w 20181. to like tracted DNA was he WWTPs (A DNA ST pooled togethe wastewat Act tivated sude harbor ore. 22.Preparation of2x150 NextSeq libraries ged as an a ve matter o Metagenomic se 0 DNA HT ing was Truse plat ch Uel 016 L A o ng ource f then c d to bl nds u ng En ng to by 5'to 3'polymerase.Single'A in the past decade and con the a e the 2016 munities (Forbes et al.2017).Metagenomics has the potential to flow cell.The purification of the ligated product was carried out by Therefore, they are being considered as chemicals of emerging concern or as pollutants. The total amount of resistance gene associated with an ecosystem is known as “resistome” (Finley et al., 2013; Stalder et al., 2019). Generally, antimicrobial resistance develops by natural selection or by adaptation of bacteria in the presence of antibiotics. It is gained ei￾ther by acquiring resistance genes or by chromosomal mutation. Hori￾zontal Gene Transfer (HGT) plays an essential role in the dissemination of antimicrobial resistance (Berglund, 2015; Che et al., 2019). It accounts for about 75% resistance genes exchange between en￾vironments, farm animals, and gut microbiota (Soucy et al., 2015) (von Wintersdorff et al., 2016). Mobile Genetic Elements (MGEs) also acts as a vector for the dissemination of ARGs (Stevenson et al., 2017; Tao et al., 2016). The higher concentration of antibiotics residues, heavy metals and Antibiotic Resistance Bacteria (ARBs) are important factors which contribute in the selection of new ARGs and Multidrug-resistant Bacte￾ria (MRBs) (Andersson and Hughes, 2014; Fluegge, 2017). Usage of an￾tibiotics at the subinhibitory concentration also promotes the wider dissemination of antimicrobial resistance (Andersson and Hughes, 2014). World Health Organization (WHO) has expressed its concern over increasing incidences of resistance, which is compromising the treat￾ment of infectious diseases and causing widespread of community￾acquired infections (Hofer, 2019; Willyard, 2017). Mostly, MRBs like Escherichia coli, Klebsiella pneumoniae, and Staphylococcus aureus are re￾sponsible for community-acquired infections (WHO, 2014). Such infec￾tious diseases are hard to treat because of the higher drug resistance, which results in a more extended hospital stay and an increase in the treatment cost. Due to the poor sanitary conditions and unregulated use of antibiotics, the problem has become more severe in developing countries (Founou et al., 2017; Holmes et al., 2016). The burden of anti￾biotic resistance is rising consistently, and India has emerged as the largest consumer of antibiotics (Laxminarayan and Chaudhury, 2016). A significant portion of the Indian population has acquired resistance to antibiotics of one or another type (McKenna, 2013). Thus, it becomes evident that the epidemic of antimicrobial resistance (AMR) is rising globally, with a much higher pace than what has been imagined earlier (Lobanovska and Pilla, 2017). Further, engineered systems like Sewage Treatment Plants (STPs) and Wastewater Treatment Plants (WWTPs) are acting as a reservoir of ARGs (Almakki et al., 2019; Karkman et al., 2017). Because of the prevalence of antibiotic residues, ARBs, and heavy metals at higher con￾centration, such system acts as a hotspot for the dissemination of resis￾tance. Also, these systems are rich in nutrient concentration, which facilitates cell-cell interaction, thus increasing chances of HGT (Manaia et al., 2018). Antibiotics belonging to classes like β-lactams, fluoroquinolones, tetracyclines, macrolides, etc. have been found in the WWTPs (Almakki et al., 2019; Brunton et al., 2019; Guo et al., 2017; Nnadozie et al., 2017). Activated sludge process is commonly used for biological remedia￾tion of pollutants present in wastewater. Activated sludge harbors huge prokaryotic diversity. Bacteria play a key role in the degradation of toxic pollutants (Cai et al., 2016; Kapley et al., 2015). Therefore, the presence of antibiotics and to what extent such compounds can be elim￾inated by activated sludge process has emerged as an active matter of research (Jelic et al., 2011; Shchegolkova et al., 2016). Microorganisms inhabiting such a complex environment produce secondary metabo￾lites, which may act as a bioresource for the development of novel anti￾microbial compounds (Culligan et al., 2014; Lewis et al., 2010). They belong to various chemical classes having antitumor, antiviral, or antibi￾otic activities (Vaishnav and Demain, 2011). Since no new antibiotic was discovered in the past decade and conventional techniques have failed to yield new antimicrobials, analysis of activated sludge metagenome may increase the chances of discovering novel secondary metabolite with antimicrobial potential (Brown and Wright, 2016; Teitzel, 2019). Metagenomics is the genomic analysis of microbial com￾munities (Forbes et al., 2017). Metagenomics has the potential to discover enormous microbial diversity associated with activated sludge biomass (Jadeja et al., 2014; Lv et al., 2015). Thus, functional screening of metagenomic libraries generated from activated sludge may yield novel biocatalysts having pharmaceutical and commercial importance (Castro et al., 2014; dos Santos et al., 2017). The metagenomic approach is currently used for monitoring the abundance of antibiotic-resistant genes and for the discovery of novel bioactive compounds in the diverse niche (Gatica et al., 2019; He et al., 2019; Lewis, 2017; Nowrotek et al., 2019; Zhang et al., 2019). Reddy & Dubey et al. (2019) used metagenomic approach for the mining of antibiotic and metal ion resis￾tance genes in the water of river Ganga. They found that beta-lactam was most abundant ARGs in the water of Ganga (Reddy and Dubey, 2019). While going through the literature, no articles were found em￾phasizing on resistome profiling of activated sludge from India. Most of the study available aims on catabolic and taxonomic profiling, targeting the bioremediation potential of microbial consortia (Jadeja et al., 2019; Raina et al., 2019; Sen and Mukhopadhyay, 2019). There￾fore, in the present study, two activated sludge samples obtained from WWTPs, Ankleshwar, Gujarat, India were sequenced using next￾generation Illumina sequencing. The study emphasized on the monitor￾ing the abundance of the ARBs, ARGs, and MGEs in activated sludge metagenome because of their role in the dissemination of AMRs. The present study also investigated the prevalence of biosynthetic gene cluster encoding for secondary metabolites in the activated sludge. For the first time, the study reports the abundance of ARGs and MGEs from an activated sludge sample considering antibiotics as a potent chemical pollutant of WWTPs from India. 2. Materials & methods 2.1. Sampling and qualitative and quantitative analysis of gDNA Samples were collected from both effluent treatment plants situated in Ankleshwar, Gujarat, India. Sample AKR012_contigs was collected from the Common Effluent Treatment Plant (CETP) in five 500 ml sam￾pling bottle treating wastewater generated from dyes and other chem￾ical industries. Similarly, sample A2_S27_assembly was collected from Effluent Treatment Plant (ETP) in five 500 ml sampling bottle treating wastewater from different small-scale industries. The collected samples were immediately preserved using dry ice. Metagenomic DNA was ex￾tracted from each sampling bottle in duplicate (10 for each sample) using Fast DNA Spin Kit for Soil, MP Biomedicals. After extraction metagenomic DNA obtained from both activated sludge samples were checked by agarose gel (1%) electrophoresis. Five microliters (μl) of ex￾tracted DNA was loaded and checked for the intact band. The agarose gel was run at 85 V for 50 min. The obtained DNA was also checked for purity (A260/280 ratio) using Nanodrop 8000. Positive DNA samples were pooled together and were then sent for sequencing. The concen￾tration of extracted DNA from each sample was determined using Qubit® 2.0 Fluorometer. 2.2. Preparation of 2 ×150 NextSeq libraries Metagenomic sequencing was performed on Illumina Truseq plat￾form using “Nano DNA HT Library Preparation Kit.” Around 200 ng of the obtained DNA was sheared by Covaris. The resulting fragments were then converted to blunt ends using End Repair Mix. 3′ overhangs were removed by the 3′ to 5′ exonuclease, and the subsequent gaps of 5′ overhangs were filled by 5′ to 3′ polymerase. Single ‘A’ nucleotide was added to the 3′ end of blunt fragments to prevent self-ligation dur￾ing the adapter ligation reaction (Kapley et al., 2015). Single ‘T’ nucleo￾tide was added on the 3′ end of the adapter during its ligation to the fragment to ensure lower chimera or concatenated templates forma￾tion. For hybridization, indexing adapters were ligated to the ends of the template DNA fragments and subsequently introduced onto the flow cell. The purification of the ligated product was carried out by 1156 S. Yadav, A. Kapley / Science of the Total Environment 692 (2019) 1155–1164