Comprehending the existence of Antimicrobial Resistant Genes (ARGs) in poultry litter and bacteria harbouring them may provide insights into the potentiality of gene transmission into microbial communities of humans and opportunistic pathogens, highlighting the significance of a One-Health approach that considers the intricate relationships between humans, animals, and environmental health. The outcomes provide insights into the interaction of genes, phenotypes, and environmental variables in forming AMR profiles in poultry contexts, which has implications for agricultural settings and public health.

WGS Analysis workflow includes sequence quality checking, quality control, taxonomy assignment, genome assembly, assembly quality assessment, assembled contig annotation, antimicrobial resistance, and taxonomy predictions.

• Raw sequence quality assessment using FASTQC Toolkit (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/)
• Adapter trimming and low quality filtering using PrinSeq-Lite v0.20.4 (Parameters: -min_qual_mean 30 --min_len 50 -ns_max_n 0) and reports using MultiQC version 1.20
• Illumina Paired-end trimmed and filtered reads were assembled using Unicycler with the command line options at local server (unicycler -1 filt_reads_R1.fastq.gz -2 filt_reads_R2.fastq.gz -o output_dir). Unicycler is an assembly pipeline for bacterial genomes.
• Genome quality check and statistics using CheckM v2 and QUality ASsessment Tool (QUAST) v5.0.2
• Genome based taxonomy assignment using (GTDB-Tk) and multi-locus sequence typing (MLST) using PubMLST server (https://pubmlst.org/)
• Gene prediction using Prokka and annotation of genes among different subsystems utilizing the SEED Servers (http://www.theseed.org/servers) and Rapid Annotation using Subsystem Technology (RAST) Server (https://rast.nmpdr.org/) and eggNOG-mapper v2 assisted with precomputed eggNOG v5.0 clusters.
• Idenitfication of the Antimicrobial Resistant Genes (ARGs) using Comprehensive Antibiotic Resistance Database (CARD) (https://card.mcmaster.ca/)
• Prediction of phage sequences using PHASTER (PHAge Search Tool Enhanced Release) server (https://phaster.ca/)
• Analysis of virulence factors using VFDB server version 2022 (http://www.mgc.ac.cn/cgi-bin/VFs/v5/main.cgi)
• Analysis of Integrative and conjugative elements (ICEs), integrative and mobilizable elements (IMEs), and cis-mobilizable elements (CIMEs) using ICEfinder (https://bioinfo-mml.sjtu.edu.cn/ICEfinder/ICEfinder.html) for the detection of ICEs/IMEs of bacterial genomes.
• The heavy metal resistant genes (HMRGs) were analysed using the Hidden Markov models (HMMs) profile protein family (PF13801: Heavy-metal resistance) https://www.ebi.ac.uk/interpro/entry/pfam/PF13801/
• Genomic feature visulisation using Proksee server (https://proksee.ca/). Proksee is a suite of command line tools for performing assembly and evaluation of microbial genomes.

MEGA 11 (Version 11.0.13) was employed for multiple sequence alignment, while the phylogenetic investigation was done using a maximum likelihood approach with 1000 bootstrap replicates. Using the iTOL server, aligned sequences were subsequently utilized to generate a circular phylogenetic tree (https://itol.embl.de/). All 16S rRNA gene sequences have been submitted to the NCBI public repository (GenBank Accession numbers PP053433-PP053445)

Proksee (https://proksee.ca) provides users with a powerful, easy-to-use, and feature-rich system for assembling, annotating, analysing, and visualizing bacterial genomes. Proksee accepts Illumina sequence reads as compressed FASTQ files or pre-assembled contigs in raw, FASTA, or GenBank format.

Accession numbers (PP053433-PP053445) of 16S rRNA nucleotide sequences of selected poultry litter bacterial isolates used in this study are available in National Centre for Biotechnology Information (NCBI) database and the raw reads generated through WGS has been submitted to the NCBI under Sequence Read Archive (SRA) submission with Bio-project accession number PRJNA1058239.

This research work was supported by Gujarat Biotechnology Research Centre (GBRC), Department of Science and Technology (DST), Government of Gujarat, Gandhinagar, India. Authors would like to gratefully acknowledge the UKRI-GCRF One Health Poultry Hub (OHPH), UK for supporting research activity. Department of Biotechnology (DBT), Government of India, New Delhi gratefully acknowledged for financial assistance to Animesh Tripathi in the form of Junior Research Fellow (DBTHRDPMU/JRF/BET-20/2020/AL/293).

Tripathi, Animesh, Anjali Jaiswal, Dinesh Kumar, Ramesh Pandit, Damer Blake, Fiona Tomley, Madhvi Joshi, Chaitanya G. Joshi, and Suresh Kumar Dubey. "High occurrence of antimicrobial resistance genes in bacteria isolated from poultry manure assessed using bacterial genome sequencing.