bioRxivBioinformaticsPreprint
BGX: A Comprehensive Pipeline for Genomic Insight into Bioactivity Prediction, Genomic Surveillance, and Novel Biosynthetic Gene Cluster Assessment
Ardhendu ChakraborttyiD, Lovepreet SinghiD, Babanpreet KauriD, Sunaina PaliyaliD, Shrikant Subhash MantriiD
Abstract
The increasing availability of genomic and metagenomic data has created significant opportunities to explore microbial diversity, biosynthetic potential and functional traits. However, comprehensive and comparative genome analysis often requires integrating multiple independent tools, making large-scale studies challenging to implement and manage. Here, we present Bacterial Genome eXplorer (BGX), an integrated and scalable pipeline that streamlines large-scale genome analysis and exploration of biosynthetic potential. BGX integrates different analytical tools into six major stages: (i) genome retrieval and assembly, (ii) genome quality assessment, (iii) antimicrobial resistance (AMR) gene profiling, (iv) annotating Biosynthetic gene clusters (BGCs) and novelty assessment, (v) bioactivity predictions, and (vi) clustering and networking analysis. In addition, BGX provides a user-friendly interactive interface to facilitate data exploration and interpretation. We demonstrated the versatility and scalability of BGX through large-scale analysis of two independent datasets: 248 genomes from the One Day One Genome (ODOG) initiative and 153 publicly available genomes from NCBI. This analysis enabled the comprehensive characterisation of genome quality, AMR determinants, biosynthetic potential and candidate bioactive metabolites across two datasets. BGX is distributed as a Docker container that simplifies installation, enables reproducible data processing, and supports pipeline execution across different computational environments. The modular and reproducible architecture of the BGX pipeline provides an effective framework for large-scale genome mining, genomic surveillance, and accelerates the discovery and prioritisation of novel secondary metabolites. BGX is now accessible at https://bgx.nabi.res.in
- assay: metagenomics
- assay: whole-genome sequencing
- research focus: variant calling
- research focus: gene regulatory network inference
- research focus: database / resource
- approach: statistical model
- approach: experimental assay
- Citations
- 0
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- A computational framework for systematic exploration of biosynthetic diversity from large-scale genomic data
Jorge Carlos Navarro-Muñoz, Nelly Selem Mojica, … Marnix H. Medema·Nature Chemical BiologyPeer-reviewed·Nov 25, 2019
- BGCFlow: Systematic pangenome workflow for the analysis of biosynthetic gene clusters across large genomic datasets
Matin Nuhamunada, Omkar S. Mohite, … Tilmann Weber·Nucleic Acids ResearchPeer-reviewed·Apr 11, 2024
- PanBGC: A Pangenome-inspired framework for comparative analysis of biosynthetic gene clusters
Davide Paccagnella, Caner Bağcı, … Nadine Ziemert·ISME CommunicationsPeer-reviewed·Jan 1, 2025
- BiG-SLiCE: A Highly Scalable Tool Maps the Diversity of 1.2 Million Biosynthetic Gene Clusters
Satria Ardhe Kautsar, Justin J. J. van der Hooft, … Marnix H. Medema·GigaSciencePeer-reviewed·Jan 1, 2021
- BGC Atlas v2: biosynthetic gene clusters with taxonomic and environmental context at scale
Caner Bağcı, Alec Talamas-Tanner, Nadine Ziemert·bioRxiv·Sep 18, 2026
- Mining metagenomes for natural product biosynthetic gene clusters: unlocking new potential with ultrafast techniques
Emiliano Pereira-Flores, Marnix H. Medema, … Antonio Fernández-Guerra·bioRxiv·Jan 20, 2021