Interactions between Helcococcus kunzii and Staphylococcus aureus: How a commensal bacterium modulates the virulence and metabolism of a pathogen in a chronic wound in vitro model

Abstract

Background: Staphylococcus aureus is the predominant pathogen isolated in diabetic foot infections. Recently, the skin commensal bacterium, Helcococcus kunzii, was found to modulate the virulence of this pathogen in an in vivo model. This study aims to elucidate the molecular mechanisms underlying the interaction between these two bacterial species, using a proteomic approach.

Results: Our results reveal that H. kunzii can coexist and proliferate alongside S. aureus in a Chronic Wound Media (CWM), thereby mimicking an in vitro chronic wound environment. We noted that the secreted proteome of H. kunzii induced a transcriptional effect on S. aureus virulence, resulting in a decrease in the expression level of agrA, a gene involved in quorum sensing. The observed effect could be ascribed to specific proteins secreted by H. kunzii including polysaccharide deacetylase, peptidoglycan DD-metalloendopeptidase, glyceraldehyde-3-phosphate dehydrogenase, trypsin-like peptidase, and an extracellular solute-binding protein. These proteins potentially interact with the agr system, influencing S. aureus virulence. Additionally, the virulence of S. aureus was notably affected by modifications in iron-related pathways and components of cell wall architecture in the presence of H. kunzii. Furthermore, the overall metabolism of S. aureus was reduced when cocultured with H. kunzii.

Conclusion: Future research will focus on elucidating the role of these excreted factors in modulating virulence.

Keywords: Helcococcus kunzii; Staphylococcus aureus; Bacterial interactions; Chronic wound; In vitro model; Proteomic analysis.

Fig. 1

Growth kinetics of coculture experiment. This figure presents the endpoint CFU counts at 0 and 24 h for S. aureus and H. kunzii, with the initial OD₆₀₀ set at A. 1 and B. 0.1. C. Growth curves in coculture (with an initial inoculum OD600 of 0.1) of S. aureus and H. kunzii over a 24 h period. The initial ratio was set at 1:3 in favour of H. kunzii to achieve an equal quantity of bacteria at 21 h. The curves were smoothed using a linear model, with each point representing CFU counts according to time in hours. Colonies grown on TSS were differentiated based on their morphology: H. kunzii colonies appeared as pinhead translucent grey, while S. aureus formed hemolytic, yellowish, and larger ones. In addition, the CFU counts of S. aureus were compared between LB and TSS agar medium

Fig. 2

Level of agrA gene expression in Staphylococcus aureus after a 24 h exposure to either Helcococcus kunzii cells (in coculture) or MEHkE (a protein extract from the supernatant of H. kunzii culture media). The Initial inoculum of S. aureus was set at an OD₆₀₀ of 1 (for the stationary phase), and an OD₆₀₀ of 0.1 (for both the exponential and stationary phases). MEHkE refers to a medium enriched with the exoproteome of H. kunzii. A p-value < 0.05 is indicated by *

Fig. 3

Regulatory network of S. aureus virulence within the proteome fraction of the stationary growth phase (OD1). Triangle shape arrows in green indicate activating interactions, while blunt head arrows in red indicate inhibiting activity. Blue double-headed arrows represent the dynamics of protein complexation. Proteins are depicted in boxes with solid black borders (to denote statistical significance), or dashed borders (to indicate trends). Red-filled boxes indicate proteins less produced in coculture, whereas green-filled boxes denote proteins with increased production. The associated log₂ fold change (FC) values are presented above each box

Fig. 4

Distribution of proteins in proteome (A) and exoproteome (B) of Staphylococcus aureus and their associated pathways. It compares the proteome and exoproteome of S. aureus identified at the exponential (OD600 = 0.1) and stationary (OD600 = 1) phases of growth in both mono-culture (NSA) and coculture conditions. The data are visualized using an UpSet matrix layout and plotted horizontally. Each column in the layout represents a set of proteins, indicated by the dark circles, and illustrates the associated pathways