Streptococcal Arginine Deiminase Inhibits T Lymphocyte Differentiation In Vitro.
Eleonora Alexandrovna StarikovaJennet T MammedovaArina OzhiganovaTatiana A LeveshkoAleksandra M LebedevaAlexey V SokolovDmitry V IsakovAlena B KarasevaLarissa A BurovaIgor V KudryavtsevPublished in: Microorganisms (2023)
Pathogenic microbes use arginine-metabolizing enzymes as an immune evasion strategy. In this study, the impact of streptococcal arginine deiminase (ADI) on the human peripheral blood T lymphocytes function in vitro was studied. The comparison of the effects of parental strain ( Streptococcus pyogenes M49-16) with wild type of ArcA gene and its isogenic mutant with inactivated ArcA gene ( Streptococcus pyogenes M49-16del ArcA ) was carried out. It was found that ADI in parental strain SDSC composition resulted in a fivefold decrease in the arginine concentration in human peripheral blood mononuclear cell (PBMC) supernatants. Only parental strain SDSCs suppressed anti-CD2/CD3/CD28-bead-stimulated mitochondrial dehydrogenase activity and caused a twofold decrease in IL-2 production in PBMC. Flow cytometry analysis revealed that ADI decreased the percentage of CM (central memory) and increased the proportion of TEMRA (terminally differentiated effector memory) of CD4+ and CD8+ T cells subsets. Enzyme activity inhibited the proliferation of all CD8+ T cell subsets as well as CM, EM (effector memory), and TEMRA CD4+ T cells. One of the prominent ADI effects was the inhibition of autophagy processes in CD8+ CM and EM as well as CD4+ CM, EM, and TEMRA T cell subsets. The data obtained confirm arginine's crucial role in controlling immune reactions and suggest that streptococcal ADI may downregulate adaptive immunity and immunological memory.
Keyphrases
- peripheral blood
- nitric oxide
- wild type
- working memory
- endothelial cells
- flow cytometry
- amino acid
- nk cells
- single cell
- oxidative stress
- regulatory t cells
- induced pluripotent stem cells
- genome wide
- copy number
- cell death
- biofilm formation
- escherichia coli
- pseudomonas aeruginosa
- endoplasmic reticulum stress
- deep learning
- big data
- artificial intelligence
- machine learning
- stem cells
- staphylococcus aureus
- data analysis
- cell therapy