Cutibacterium granulosum , a commensal bacterium found on human skin, formerly known as Propionibacterium granulosum , rarely causes infections and is generally considered non-pathogenic. Recent research has revealed the transferability of the multidrug-resistant plasmid pTZC1 between C. granulosum and Cutibacterium acnes , the latter being an opportunistic pathogen in surgical site infections. However, there is a noticeable lack of research on the genome of C. granulosum , and the genetic landscape of this species remains largely uncharted. We investigated the genomic features and evolutionary structure of C. granulosum by analyzing a total of 30 Metagenome-Assembled Genomes (MAGs) and isolate genomes retrieved from public databases, as well as those generated in this study. A pan-genome of 6,077 genes was identified for C. granulosum . Remarkably, the 'cloud genes' constituted 62.38% of the pan-genome. Genes associated with mobilome: prophages, transposons [X], defense mechanisms [V] and replication, recombination and repair [L] were enriched in the cloud genome. Phylogenomic analysis revealed two distinct mono-clades, highlighting the genomic diversity of C. granulosum . The genomic diversity was further confirmed by the distribution of Average Nucleotide Identity (ANI) values. The functional profiles analysis of C. granulosum unveiled a wide range of potential Antibiotic Resistance Genes (ARGs) and virulence factors, suggesting its potential tolerance to various environmental challenges. Subtype I-E of the CRISPR-Cas system was the most abundant in these genomes, a feature also detected in C. acnes genomes. Given the widespread distribution of C. granulosum strains within skin microbiome, our findings make a substantial contribution to our broader understanding of the genetic diversity, which may open new avenues for investigating the mechanisms and treatment of conditions such as acne vulgaris.
Keyphrases
- genome wide
- copy number
- crispr cas
- antibiotic resistance genes
- escherichia coli
- genetic diversity
- multidrug resistant
- dna methylation
- single cell
- healthcare
- genome editing
- gene expression
- pseudomonas aeruginosa
- mental health
- microbial community
- staphylococcus aureus
- minimally invasive
- dna repair
- soft tissue
- deep learning
- climate change
- klebsiella pneumoniae
- human health