S.Yadry.A Kapley Science of the Tota r622019)1155-1164 Table 1 nic datasets obtained sludge onle using A2_$27_assembly AKR012_contigs resistance genes are represented as points of larger size and dark color 3.Result and discussion 11502 ldvcyegardigthebateri e m). a5 embly）comprise of bacteri alyze the amplified library ir mprising676%and 8 respectively ir n the two metagenomes.A b (up to s rel drug eema ir resistance(G 20wa20 ples and Enter tive clea a,201 2.4.Metagenomic analysis using MG RAST derived)infection. The two r for such patients.Recently it h hee 0s78554 with D embly)respe uitceresi e against Carbapenem "the last resort antibiotics SAMN03074223(SRA ID:SRR1702227)(A2_S27_ass cstistantbacteri mycin (D and Graham.2017). boicdiversity of the two metagenomes was compared using STAMP done using the Storey q-value (Parks et al.2014).The asse an 32.The occurrence of ARGs and metal resistant genes in activated sludge 60%(Clausen et) 25.Comprehensive analysis of metagenome using BusyBee web-based server for the metag omic analysis(Laczny c2leddistrtbuionofmicrobiomras ciated with two activated sludee sample ched against the genes)using hmmsearch from HMMER(v3.1b2:http://hmmer.janelia.using SP beads supplied in the kit, followed by PCR amplification of size￾selected product as described in the manual (Yadav et al., 2014). High Sensitivity (HS) DNA chip was used to analyze the amplified library in Bioanalyzer 2100 (Agilent Technologies). 2.3. Cluster generation and sequencing After analyzing the library using Bioanalyzer, the positive libraries were loaded onto NextSeq for cluster generation and sequencing. Both the forward and reverse directions NextSeq were performed by imply￾ing paired-end sequencing of the template fragments. Binding of sam￾ples to complementary adapter oligos was performed by using the kit reagents on the paired-end flow cell. After resynthesis of the reverse strand, the adapters were allowed to bind the selective cleavage of the forward strands, followed by the sequencing from the opposite end of the fragment which was carried out by the copied reverse strand. 2.4. Metagenomic analysis using MG RAST The two metagenome sequences obtained from activated sludge samples were submitted to NCBI with accession number SAMN03074221 (SRA ID: SRS785543) (AKR012_contigs) and SAMN03074223 (SRA ID: SRR1702227) (A2_S27_assembly) respec￾tively. For the analysis of microbial taxonomic abundance and preva￾lence of antibiotic and metal resistance genes, sequences were analyzed using “MG-RAST” server with default parameter (Keegan et al., 2016). Annotation of metagenomic sequences was given in Table 1. Taxonomic and catabolic diversity was further statically ana￾lyzed using Statistical Analysis of Metagenomic Profiles (STAMP) soft￾ware. A two-sided G test (w/Yates') + Fisher's exact test was implemented for hypothesis testing, whereas the difference in propor￾tions (DPs) and confidence intervals (CIs) for P ¼ 0.95 were calculated using the Newcombe-Wilson method. Multiple test corrections were done using the Storey q-value (Parks et al., 2014). The assembled contigs of both metagenomes were also used for finding acquired anti￾microbial resistance genes using ResFinder 3.1 tool of center for geno￾mics epidemiology (CGEwebface@cbs.dtu.dk). The parameter for contigs annotation was threshold id of 90% and a minimum length of 60% (Clausen et al., 2016). 2.5. Comprehensive analysis of metagenome using BusyBee BusyBee is a web-based server for the metagenomic analysis (Laczny et al., 2017). Both taxonomic and functional annotation of metagenome can be performed using BusyBee. It utilizes a bootstrapped approach for the annotation of metagenomic sequences. It requires input files in the fasta format. It utilizes Prokka as a tool for the rapid annotation of micro￾bial genomes (Seemann, 2014). The translated coding sequences are then searched against the ResFams (collection of antibiotic resistance genes) using hmmsearch from HMMER (v3.1b2; http://hmmer.janelia. org/) using hidden Markov models (profile HMMs) (Liu et al., 2016). In BusyBee input sequences are represented as individual points in the 2D scatter plot. Convex hull delineates the predicted cluster. Antibiotic resistance genes are represented as points of larger size and dark color. 3. Result and discussion 3.1. Taxonomic distribution of microbes in activated sludge metagenome Activated sludge samples harbor huge prokaryotic diversity which carries out bioremediation of toxic compounds present in wastewater. Among the microbes, bacterial community plays a major role in the en￾tire process. The two-metagenome obtained from both sludge samples showed remarkably similar microbial diversity regarding the bacterial community. Sample from CETP (AKR012_contigs) and ETP (A2_S27_assembly) comprise of 97.8 and 98.6% of bacteria. Proteobacteria was the predominant among the bacterial community comprising 67.6% and 88.3% respectively in the two metagenomes. Ar￾chaea communities were least abundant in both metagenome samples comprising of 0.64 and 0.26%, respectively (Table 2). Taxonomic distri￾bution of microbial diversity has been shown in Fig. 1a and b (up to genus level) and supplementary material (up to phylum level). Recently WHO has released a list of twelve drug-resistant patho￾genic bacteria that pose the greatest threat to human health due to their resistance (Göttig et al., 2014; Willyard, 2017). These MRBs, i.e., “Enterococcus spp., Staphylococcus aureus, Klebsiella spp., Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp.” are referred as “ESKAPE” pathogens, and they have raised the ep￾idemic of antibiotic resistance by several folds (Lewis et al., 2015). Pres￾ence of these bacteria have been recently reported in the Indian subcontinent by various studies and was detected in the activated sludge samples used in the present study (Das et al., 2011; Laxminarayan and Chaudhury, 2016; Walsh et al., 2011). Acinetobacter baumanii is responsible for nosocomial (hospital derived) infection. It causes severe infection to the already critically ill/chronic patients, and no clinical treatment exists for such patients. Recently it has been found that the most strain of Acinetobacter baumanii bacterium has ac￾quired resistance against Carbapenem “the last resort antibiotics” (McKenna, 2013). WHO has categorized Helicobacter pylori as the high-priority drug￾resistant bacteria, which accounts for more than 95% cases of gastric cancer. Earlier triple therapy was used for the treatment of Helicobacter pylori derived infection, but its efficacy has declined more than 80% from 2000 to 2017 due to the acquisition of resistance against antibiotic Clarithromycin (Dang and Graham, 2017). Enterobacter cloacae were also detected in the sludge metagenome with much abundance, which has been found resistant to colistin antibiotics (Band et al., 2016). Cata￾bolic diversity of the two metagenomes was compared using STAMP software and has been shown in Fig. 2. 3.2. The occurrence of ARGs and metal resistant genes in activated sludge Twenty-four genes conferring resistance to antibiotics and metals were detected in the sludge metagenome using MG-RAST (Fig. 3 a and Table 1 Annotation of metagenomic datasets obtained from two activated sludge sample using MGRAST. Feature A2_S27_assembly AKR012_contigs Total sequences 87,058,937 137,225,975 Total reads 101,935 143,628 Average read length (bases) 854 955 Average GC content 58 ± 13% 62 ± 10% QC passed reads 94,537 123,297 Average read length after QC (bases) 646 ± 705 bp 548 ± 695 bp Predicted protein feature 115,002 144,151 Predicted rRNA features 452 577 Identified protein features 68,545 98,720 Identified functional categories 57,492 85,462 Table 2 Domain level distribution of microbiome associated with two activated sludge sample. Domain A2_S27_assembly (% abundance) AKR012_contigs (% abundance) Bacteria 97.88 98.68 Archaea 0.64 0.25 Eukaryotes 1.02 0.46 Viruses 0.33 0.31 Other 0.14 0.12 S. Yadav, A. Kapley / Science of the Total Environment 692 (2019) 1155–1164 1157