Current Biotechnology - Online First

The increasing emergence of zoonotic pathogens and antimicrobial resistance (AMR) highlights the need for rapid and accurate computational tools to assess the zoonotic potential of bacterial strains. In this study, we present Zoonomix, a bioinformatics pipeline designed to detect and rank genes associated with pathogenicity, virulence, and antibiotic resistance, thereby enabling risk assessment for zoonotic transmission.

Zoonomix integrates a curated database of ~25,000 genes related to adherence, biofilm formation, efflux pumps, exotoxins, resistance, integrative and conjugative elements (ICEs), and secretion systems (T3SS, T4SS, and T6SS). It uses BLASTN and a scoring algorithm to assess pathogenicity and HGT risk, classifying bacterial strains into low, moderate, or high risk, with insights into antibiotic resistance migration.

When analyzing 60 whole genome sequences of both zoonotic and non-zoonotic bacterial species using the Zoonomix pipeline, over 90% of the results were accurately classified in accordance with existing literature. Notably, the pipeline predicted a potential future zoonotic and pathogenic capability for bacterial species such as A. pleuropneumoniae and M. haemolytica.

Zoonomix offers a comprehensive framework for assessing zoonotic potential and antibiotic resistance by integrating genomics, bioinformatics, and predictive analytics. Its ability to detect current gene status, identify mutation-prone genes, summarize mutation hotspots, and flag horizontal gene transfer events make it a valuable tool for disease surveillance and outbreak prevention.

Zoonomix is a scalable, open-source bioinformatics pipeline designed to assess the zoonotic potential and antimicrobial resistance (AMR) risk in bacterial whole genome sequences. By detecting key genes associated with zoonosis, identifying markers that predict the future pathogenic or zoonotic potential of bacteria, and flagging integrative conjugative element (ICEs)-mediated resistance gene transfer mechanisms, the tool provides comprehensive insights into bacterial threats. The pipeline's source code and documentation are freely available for the research community at the following GitHub repository: https://github.com/Umeshkumarku1/ZoonomiX.

FimH, a bacterial adhesin on Uropathogenic Escherichia coli (UPEC), facilitates host cell attachment and initiates Urinary Tract Infections (UTIs). With rising antibiotic resistance, alternative therapeutics targeting bacterial adhesion are urgently needed. This study investigates chalcone derivatives as potential anti-adhesive agents against FimH, aiming to inhibit bacterial colonization and reduce virulence through an in silico approach.

A total of 200 chalcone derivatives were subjected to in silico toxicity screening using ProTox-II, followed by molecular docking using MVD 6.0 and AutoDock Vina against FimH (PDB IDs: 5AAP and 4XO8). The most promising compounds underwent structural pharmacophore modeling in LigandScout, pharmacokinetic profiling via SwissADME and PreADMET, and further validation through molecular dynamics simulations and MMPBSA free energy calculations.

Chalcones 103, 122, and 137 showed strong binding affinities, with highly negative MolDock scores surpassing native ligands. Key residues such as Gln133, Asp47, and Phe1 were identified as essential for hydrogen bonding. Pharmacokinetic profiles revealed high gastrointestinal absorption, BBB permeability, and compliance with major drug-likeness filters. RMSF analysis indicated 4XO8’s structural rigidity, while MMPBSA confirmed strong binding energies, particularly for the 4XO8-137 complex.

These findings suggest chalcone derivatives, especially Chalcone 137, demonstrate promising anti-adhesive properties, structural stability, and favourable pharmacokinetics, making them viable candidates for further drug development.

Chalcones 103, 122, and 137, particularly the 4XO8-137 complex, exhibit strong therapeutic potential as non-antibiotic anti-adhesion agents against UTI-causing E. coli, warranting further experimental validation in vitro and in vivo.