The Co-Culture of Staphylococcal Biofilm and Fibroblast Cell Line: The Correlation of Biological Phenomena with Metabolic NMR1 Footprint.
Joanna CzajkowskaAdam F JunkaJakub HoppeMonika ToporkiewiczAndrzej PawlakPaweł MigdałMonika Oleksy-WawrzyniakKarol FijałkowskiMarcin SmiglakAgata Markowska-SzczupakPublished in: International journal of molecular sciences (2021)
Staphylococcus aureus is one of the most prevalent pathogens associated with several types of biofilm-based infections, including infections of chronic wounds. Mature staphylococcal biofilm is extremely hard to eradicate from a wound and displays a high tendency to induce recurring infections. Therefore, in the present study, we aimed to investigate in vitro the interaction between S. aureus biofilm and fibroblast cells searching for metabolites that could be considered as potential biomarkers of critical colonization and infection. Utilizing advanced microscopy and microbiological methods to examine biofilm formation and the staphylococcal infection process, we were able to distinguish 4 phases of biofilm development. The analysis of staphylococcal biofilm influence on the viability of fibroblasts allowed us to pinpoint the moment of critical colonization-12 h post contamination. Based on the obtained model we performed a metabolomics analysis by 1H NMR spectroscopy to provide new insights into the pathophysiology of infection. We identified a set of metabolites related to the switch to anaerobic metabolism that was characteristic for staphylococcal biofilm co-cultured with fibroblast cells. The data presented in this study may be thus considered a noteworthy but preliminary step in the direction of developing a new, NMR-based tool for rapid diagnosing of infection in a chronic wound.
Keyphrases
- staphylococcus aureus
- biofilm formation
- pseudomonas aeruginosa
- methicillin resistant staphylococcus aureus
- induced apoptosis
- candida albicans
- high resolution
- cell cycle arrest
- microbial community
- wound healing
- endothelial cells
- wastewater treatment
- big data
- signaling pathway
- multidrug resistant
- solid state
- sensitive detection
- quantum dots
- deep learning
- health risk
- gram negative
- surgical site infection
- drug induced