De Vrieze, L. | Search bioRxiv

bioRxiv2025

CAGEcleaner: reducing genomic redundancy in gene cluster mining

SummaryMining homologous biosynthetic gene clusters (BGCs) typically involves searching colocalised genes against large genomic databases. However, the high degree of genomic redundancy in these databases often propagates into the resulting hit sets, complicating downstream analyses and visualisation. To address this challenge, we present CAGEcleaner, a Python-based tool with auxiliary bash scripts designed to reduce redundancy in gene cluster hit sets by dereplicating the genomes that host these hits. CAGEcleaner integrates seamlessly with widely used gene cluster mining tools, such as cblaster and CAGECAT, enabling efficient filtering and streamlining BGC discovery workflows. Availability and implementationSource code and documentation is available at GitHub (https://github.com/LucoDevro/CAGEcleaner) and at Zenodo (https://doi.org/10.5281/zenodo.14726119) under an MIT license. CAGEcleaner comes with its own Conda environment but can also be installed from the Python Package Index (https://pypi.org/project/cagecleaner/). Contactlucas.devrieze@kuleuven.be or joleen.masschelein@kuleuven.be Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2025

Comparative pangenome and mobilome analysis of clostridial species clusters reveals different levels of host adaptation and novel conserved biosynthetic potential

To thrive in diverse ecological niches, bacteria adopt various lifestyles, that range from living freely in the soil to forming close associations with human and animal hosts. However, the impact of these adaptation processes on their genomes and metabolisms remains largely unexplored beyond the genus level. Investigating these evolutionary dynamics at higher taxonomic levels can enhance our understanding of the relationship between host adaptation and their functional capabilities. Here, we examine the evolutionary trajectories and metabolic capabilities of the Clostridia class, which displays a variety of lifestyles and is of high importance for industry, medicine and microbiome research. First, we uncover that the clostridial orders have significantly different adaptation rates. Second, we show that the Oscillospirales order has undergone extensive genomic and functional specialisation toward a host-associated lifestyle, while the Lachnospirales order tends to be at a lower level of host association, retaining a remarkably high number of free-living trait genes and a high degree of metabolic versatility. Third, we reveal substantial differences in genomic architecture and metabolic versatility between the clostridial orders and link these to the progressing stages of host adaptation. Additionally, we identify widely conserved biosynthetic gene clusters, highlighting untapped biosynthetic potential of evolutionary significance. Hence, the beyond-genus level analyses in this study provide valuable new insights into bacterial adaptation with broad implications for evolutionary biology, microbiome research and biotechnology.

bioinformatics↗