Biofilm-mediated antibiotic tolerance in Staphylococcus aureus from spinal cord stimulation device-related infections

Abstract

Staphylococcus aureus is a predominant cause of infections in individuals with spinal cord stimulation (SCS) devices. Biofilm formation complicates these infections, commonly requiring both surgical and antibiotic treatments. This study explored the biofilm matrix composition and antimicrobial susceptibility of planktonic and biofilm-growing S. aureus isolates from individuals with SCS-related infections. Whole-genome sequencing (WGS) examined genotypes, virulome, resistome, and the pan-genome structure. The study also analyzed biofilm matrix composition, early surface adhesion, hemolytic activity, and antibiotic-susceptibility testing. WGS revealed genetic diversity among isolates. One isolate, though oxacillin susceptible, contained the mecA gene. The median number of virulence factor genes per isolate was 58. All isolates harbored the biofilm-related icaA/D genes. When assessing phenotypic characteristics, all strains demonstrated the ability to form biofilms in vitro. The antimicrobial susceptibility profile indicated that oxacillin, rifampin, and teicoplanin showed the highest efficacy against S. aureus biofilm. Conversely, high biofilm tolerance was observed for vancomycin, trimethoprim/sulfamethoxazole, and levofloxacin. These findings suggest that S. aureus isolates are highly virulent and produce robust biofilms. In cases of suspected biofilm infections caused by S. aureus, vancomycin should not be the primary choice due to its low activity against biofilm. Instead, oxacillin, rifampin, and teicoplanin appear to be more effective options to manage SCS infections.IMPORTANCESCS devices are increasingly used to manage chronic pain, but infections associated with these devices, particularly those caused by Staphylococcus aureus, present significant clinical challenges. These infections are often complicated by biofilm formation, which protects bacteria from immune responses and antibiotic treatments, making them difficult to eradicate. Understanding the genetic diversity, virulence, and biofilm characteristics of S. aureus isolates from SCS infections is critical to improving treatment strategies. Our study highlights the need to reconsider commonly used antibiotics like vancomycin, which shows reduced activity against biofilm-growing cells. Identifying more effective alternatives, such as oxacillin, rifampin, and teicoplanin, provides valuable insight for clinicians when managing biofilm-related S. aureus infections in patients with SCS implants. This research contributes to the growing evidence that biofilm formation is crucial in treating device-related infections, emphasizing the importance of tailoring antimicrobial strategies to the biofilm phenotype.

Keywords: Staphylococcus aureus; biofilm; oxacillin; spinal cord stimulation; vancomycin.

Fig 1

(A) Representative radiographic images of different implantable neuromodulators, and (B) associated tissue infections for five patients (Pt).

Fig 2

(A) S. aureus pan-genome statistics are divided into three categories: the core genome, the accessory genome, and the unique genome. (B) Phylogenetic tree of the five S. aureus isolates. The S. aureus American Type Culture Collection 6538 strain was also included in the analysis. Branch lengths (−log10 scale) expressed on the tree are proportional to the phylogenetic distances. Different colors were used to highlight clusters. (C) Shared and unique genes in five S. aureus strains. (D) The stacked bar chart of Clusters of Orthologous Groups (COG) functional category proportions is based on the unique genes in all groups. Gene distribution according to COG categories: A, amino acid transport and metabolism; B, carbohydrate transport and metabolism; C, cell cycle and division; D, cell motility; E, cell wall/membrane/envelope biogenesis; F, coenzyme transport and metabolism; G, defense mechanisms; H, energy production and conversion; I, inorganic ion transport and metabolism; J, intracellular trafficking, secretion, and vesicular transport; K, lipid transport and metabolism; L, nucleotide transport and metabolism; M, post-translational modification; N, replication, recombination, and repair; O, secondary metabolites biosynthesis, transport, and catabolism; P, signal transduction mechanism; Q, transcription; R, translation, ribosomal structure, and biogenesis. (E) The bar graph reports the number (N°) of virulence genes and (F) the antimicrobial-resistance genes (ARGs). (G) Non-linear regression to analyze the relationship between VF and ARG. (H) Similarity matrix categories represent the presence (red, +) or the absence (blue, −) of S. aureus genes involved in surface attachment, biofilm formation, exotoxins, endotoxins, and antimicrobial resistance. (I) The antimicrobial susceptibility test was performed for the five S. aureus isolates across 13 antibiotics.

Fig 3

Phenotypic analysis of S. aureus isolates. (A) Biomass production as assessed by crystal violet. Bars above the straight line represent strong biofilm producers, while bars above the dotted line represent moderate biofilm producers. The bar graphs report the values of (B) the early surface adhesion, (C) the metabolic activity of the cells within the biofilm, (D) the number of viable cells in the biofilm matrix, (E) the proportion of eDNA, (F) exopolysaccharides, (G) proteins, and (H) the hemolytic activity in the different isolates and comparison with the reference strain S. aureus ATCC 6538 (mean ± SD). (I) Principal component analysis of five phenotypic traits for the S. aureus isolates and the reference strain S. aureus ATCC 6538. (J) Biplots of S. aureus isolates in terms of their phenotypic profiles. Pearson correlation significance indicated by *P < 0.05, **P < 0.01, ***P < 0.001, **** P < 0.0001.

Fig 4

Antibiotic susceptibility of planktonic and biofilm-growing S. aureus isolates. (A) Balloon plot describing the antimicrobial susceptibility testing against five S. aureus strains in planktonic and biofilm growth measured as minimum inhibitory concentration (MIC₉₀) and minimal biofilm eradication concentration (MBEC₉₀) for the indicated antibiotics. (B) Heat map showing the biofilm tolerance (BT), calculated as the ratio MBEC₉₀/MIC₉₀ for all the antibiotics tested. Red indicates high BT values, and green represents low BT for the indicated antibiotics. TMP/SMX, trimethoprim/sulfamethoxazole.