Broadly reactive human CD4+ T cells against Enterobacteriaceae are found in the naïve repertoire and are clonally expanded in the memory repertoire.
Antonino CassottaJérémie D GoldsteinGreta DuriniDavid JarrossayFranca Baggi MenozziMario VendittiAlessandro RussoMarco FalconeAntonio LanzavecchiaMaria Cristina GagliardiDaniela LatorreFederica SallustoPublished in: European journal of immunology (2020)
Enterobacteriaceae are a large family of Gram-negative bacteria that includes both commensals and opportunistic pathogens. The latter can cause severe nosocomial infections, with outbreaks of multi-antibiotics resistant strains, thus being a major public health threat. In this study, we report that Enterobacteriaceae-reactive memory Th cells were highly enriched in a CCR6+ CXCR3+ Th1*/17 cell subset and produced IFN-γ, IL-17A, and IL-22. This T cell subset was severely reduced in septic patients with K. pneumoniae bloodstream infection who also selectively lacked circulating K. pneumonie-reactive T cells. By combining heterologous antigenic stimulation, single cell cloning and TCR Vβ sequencing, we demonstrate that a large fraction of memory Th cell clones was broadly cross-reactive to several Enterobacteriaceae species. These cross-reactive Th cell clones were expanded in vivo and a large fraction of them recognized the conserved outer membrane protein A antigen. Interestingly, Enterobacteriaceae broadly cross-reactive T cells were also prominent among in vitro primed naïve T cells. Collectively, these data point to the existence of immunodominant T cell epitopes shared among different Enterobacteriaceae species and targeted by cross-reactive T cells that are readily found in the pre-immune repertoire and are clonally expanded in the memory repertoire.
Keyphrases
- single cell
- multidrug resistant
- klebsiella pneumoniae
- pseudomonas aeruginosa
- gram negative
- public health
- rna seq
- urinary tract infection
- working memory
- cell therapy
- acinetobacter baumannii
- drug resistant
- escherichia coli
- dendritic cells
- endothelial cells
- acute kidney injury
- machine learning
- stem cells
- transcription factor
- artificial intelligence
- immune response
- cell death
- deep learning
- saccharomyces cerevisiae