Keloid disorder is delineated by the presence of keloidal scars, a consequence triggered by skin injuries, infections, and inflammatory processes. Manifesting symptoms such as pain and pruritus, this condition can exert a profound impact on both the physical and mental well-being of individuals. Dermatologists and plastic surgeons confront a substantial challenge in addressing keloids, primarily attributable to the dearth of efficacious pharmaceutical interventions and the elevated recurrence rate subsequent to surgical procedures. Unveiling the intricacies of the keloid microenvironment harbors the potential to engender innovative treatment modalities and preventative strategies.
Shan and her colleagues employed a diverse array of multi-omics technologies to elucidate the intricacies of the bacterial-keloid disease relationship. This comprehensive investigation involved 132 patients diagnosed with keloid and 115 patients who underwent cosmetic surgery. The researchers leveraged methodologies such as microbiome analysis, metaproteomics, metabolomics, single-cell transcriptomics, and cell-derived xenograft (CDX) mice models.
Amplicon sequencing was executed on both keloid tissue and normal skin tissue, revealing a differential abundance of microbial species. Notably, at the species level; Clostridia, Roseburia, Brucellaceae, and Burkholderiales were found to be prolific in keloid samples, whereas Desulfovibrionaceae, Methylophilaceae, Comamonadaceae, Lysinibacillus, and others exhibited abundance in the control group. Furthermore, bacterial species in keloid tissues tested negative in catalase assays, whereas those in normal skin tissues demonstrated positive catalase activity. Additionally, the microbial diversity in normal tissues surpassed that of keloid tissues. This study posits a noteworthy association between bacteria and catalase (CAT) expression in the context of keloid disease, shedding light on potential contributory factors to the pathogenesis of keloids.
Researchers observed distinctive histological features differentiating keloid and normal skin tissues. Specifically, the epidermis of keloids exhibited significant thickening compared to normal skin, and the dermal fiber bundles in keloids were abnormally thick, dense, and vascularized, contrasting with the smaller and sparser fiber bundles in normal skin dermal tissue. Significant variations in CAT, superoxide dismutase 1 (SOD1), and nitric oxide synthase (iNOS) levels, key components in the body’s response to oxidative stress, were noted between normal skin and keloid tissue. CAT and SOD1 levels were higher in normal skin, while iNOS showed a significant elevation in keloid tissue, where CAT expression was notably reduced. Fibroblasts were classified into subgroups, revealing an increased proportion of MF (comprising oxidative stress-related and collagen-related genes) in keloids, while SPF and SRF were elevated in the control. Keloid tissues exhibited a higher fibroblast death score, and the Gene Ontology (GO) pathway related to oxidative stress significantly differed between keloid and normal tissue.
Employing lentiviruses, researchers established stable cell lines with primary keloid fibroblasts, inducing CAT knockdown or overexpression to investigate CAT’s role. Fibroblasts with suppressed CAT produced more keloid-associated collagen types. Antibiotics hindered keloid fibroblast proliferation by decreasing H2O2 and ROS production. Invasive capacity increased with CAT knockdown but decreased with overexpression. In a nude mice CDX model, CAT overexpression restrained keloid development. Results also showed Clostridium butyricum significantly promoted keloid fibroblast mass growth. CAT-negative bacteria, like Clostridium butyricum, may contribute to in vivo keloid growth.
In summation, the study conducted by Shan and her colleagues not only elucidates significant correlations between bacterial presence and the formation of keloids but also yields findings that hold the potential to provide promising insights into prospective and efficacious treatments.
Author: Hüseyin Çavuş
Editor: Elif Duymaz
Reference: Shan, M., Xiao, M., Xu, J., Sun, W., Wang, Z., Du, W. (2023). Multi-omics analyses reveal bacteria and catalase associated with keloid disease. Lancet eBioMedicine, 99, 104904. https://doi.org/10.1016/j.ebiom.2023.104904
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