Bacteriocin distribution patterns in Enterococcus faecium and Enterococcus lactis: bioinformatic analysis using a tailored genomics framework

Abstract

Multidrug-resistant Enterococcus faecium strains represent a major concern due to their ability to thrive in diverse environments and cause life-threatening infections. While antimicrobial resistance and virulence mechanisms have been extensively studied, the contribution of bacteriocins to E. faecium's adaptability remains poorly explored. E. faecium, within the Bacillota phylum, is a prominent bacteriocin producer. Here, we developed a tailored database of 76 Bacillota bacteriocins (217 sequences, including 40 novel bacteriocins) and applied it to uncover bacteriocin distribution patterns in 997 quality-filtered E. faecium and Enterococcus lactis (former E. faecium clade B) genomes. Curated using computational pipelines and literature mining, our database demonstrates superior precision versus leading public tools in identifying diverse bacteriocins. Distinct bacteriocin profiles emerged between E. faecium and E. lactis, highlighting species-specific adaptations. E. faecium strains from hospitalized patients were significantly enriched in bacteriocins as enterocin A and bacteriocins 43 (or T8), AS5, and AS11. These bacteriocin genes were strongly associated with antibiotic resistance, particularly vancomycin and ampicillin, and Inc18 rep2_pRE25-derivative plasmids, classically associated with vancomycin resistance transposons. Such bacteriocin arsenal likely enhances the adaptability and competitive fitness of E. faecium in the nosocomial environment. By combining a novel tailored database, whole-genome sequencing, and epidemiological data, our work elucidates meaningful connections between bacteriocin determinants, antimicrobial resistance, mobile genetic elements, and ecological origins in E. faecium and provides a framework for elucidating bacteriocin landscapes in other organisms. Characterizing species- and strain-level differences in bacteriocin profiles may reveal determinants of ecological adaptation, and translating these discoveries could further inform strategies to exploit bacteriocins against high-risk clones.

Importance: This work significantly expands the knowledge on the understudied bacteriocin diversity in opportunistic enterococci, revealing their contribution in the adaptation to different environments. It underscores the importance of placing increased emphasis on genetic platforms carrying bacteriocins as well as on cryptic plasmids that often exclusively harbor bacteriocins since bacteriocin production can significantly contribute to plasmid maintenance, potentially facilitating their stable transmission across generations. Further characterization of strain-level bacteriocin landscapes could inform strategies to combat high-risk clones. Overall, these insights provide a framework for unraveling the therapeutic and biotechnological potential of bacteriocins.

Keywords: Enterococcus faecium; Enterococcus lactis; antimicrobial peptides; antimicrobial resistance; bacteriocin database; bacteriocins; plasmids.

Fig 1

The database development and genomic analysis workflow. (A) Bacterial genome collection, (B) bacteriocin database creation, (C) bacteriocin analysis in enterococci genomes, and (D) comparison of our in-house database with other available bacteriocin databases. Abbreviations: CGE, Center for Genomic Epidemiology; cgMLST, core genome multilocus sequence typing; CT, cluster type; MLST, multilocus sequence typing; CT - cluster types; CGE – Center for Genomic Epidemiology.

Fig 2

SNP tree of all Enterococcus genomes (n = 997) analyzed. The 10 isolates with genomes containing a hybrid gluP gene are highlighted in red, along with the corresponding root. Core alignment was performed with Panaroo (v.1.3.4) and identification and removal of recombinogenic regions were performed with Gubbins (v.3.3.1). Phylogenetic tree construction was done using IQtree (v.2.2.6), and visualization was performed with iTOL (v.6.9.1). Final tree was midpoint rooted and ladderized to improve the visualization.

Fig 3

Comparative distribution of bacteriocins across (A) all genomes, (B) E. faecium genomes, and (C) E. lactis genomes.

Fig 4

Comparative distribution of bacteriocins between E. faecium and E. lactis throughout the decades. Years before 1980 are grouped together due to low isolate numbers.

Fig 5

Number of isolates and their amount of bacteriocins (between 0 and 11 in E. faecium and between 0 and 7 in E. lactis) according to source and species.

Fig 6

Sankey diagram illustrating the distribution of bacteriocins (present at least in 5% of the isolates) among Enterococcus faecium and Enterococcus lactis and associations with the presence/absence of antibiotic resistance genes as ampicillin (AmpR and AmpS) and vancomycin (VRE and VSE) and their respective sources. The diagram was constructed in R using the package networkD3 (v.0.4) (23). Abbreviations: AmpR, ampicillin resistant; AmpS, ampicillin susceptible; VRE, vancomycin-resistant Enterococcus; VSE, vancomycin-susceptible Enterococcus.