Potential cross reactions between HIV 1 specific T cells and the microbiome Andrew McMichael Suzanne Campion
Role of the Microbiome? T cell (and B cell) immune responses to HIV and Vaccines are influenced by the pre immune T cell repertoire immunodominance The pre immune naïve T cell repertoire is shaped by the MHC positive and negative selection in the thymus There is also a pre immune memory T cell repertoire that is shaped by exposure to cross reacting immunogens original antigenic sin The microbiome contributes to shaping the pre immune memory T cell repertoire
Pre-Immune CD4 T cell repertoire to HIV-1 Method: Geiger, R., T. Duhen, A. Lanzavecchia, and F. Sallusto. 2009. J Exp Med 206:1525-1534 Campion, S. et a. l 2014; J Exp Med 211: 1273-80. TT POL NEF/ACC ENV GAG UNSTIM Naive Central Memory Effector Memory CD4 T cells sorted and seeded at 1000 cells per well 96 or 192 replicates Non specific expansion with PHA, IL2 and feeders. >12 Cell Divisions Split each well and stimulate with autologous monocytes + peptides. Proliferation or cytokine assays Grow lines specificity
Pre-immune HIV-1 specific CD4 T cells Naïve CD4+T Central Memory CD4+T Effector Memory CD4+T Number Of HIV 1 Specific Cells / Million 200 150 100 50 0 NAIVE 1 2 3 4 5 6 7 8 9 10 200 150 100 50 0 CENTRAL MEMORY 1 2 3 4 5 6 7 8 9 10 Subject ID 200 150 100 50 0 EFFECTOR MEMORY 1 2 3 4 5 6 7 8 9 10 Campion et al. J Ex Med 2014
Mapped T cell responses red: naïve; grey: memory ; solid line: previously known Srin Ranasinghe et al J Exp Med 2013
Validation by Tetramer Enrichment Two VZV epitopes restricted by HLADRB1*1501. - IE63 and GE Data from naïve and memory subsets of 5 anonymous blood donors. Campion et al J Exp Med 2014
NAÏVE (CD45RA+CCR7+) CD8 + T Cell Library CENTRAL MEMORY (CD45RA CCR7+) EFFECTOR MEMORY (CD45RA CCR7 ) N= 1 Total lines screened was 192 lines / subset cells seeded 4000 / well Ex Vivo ELISpot FEC Response Peptide Pool Antigen Specific Cells / 10^6 Naïve Central Memory Effector Memory GAG 0 Detected 1.31 0 Detected ENV 1.31 2.62 0 Detected NEF/ACC 1.31 5.26 0 Detected POL 1.31 6.60 2.62 CTLA* 2.62 2.62 CTLB* 1.31 1.31 0 Detected FEC 0 Detected 425.54 14.75 *Optimal CTL epitopes defined on LANL database arbitrarily split into 2 pools to prevent DMSO concentrations from becoming toxic
Could Microbiota Prime Pre Immune memory T cells? For 34 memory T cell epitopes there were >2000 perfect 8 amino acid matches in HMP database. Higher than expected ~ 1 epitope match in 10 4 bacterial species (Will Fischer and Bette Korber; Campion et al 2014) Su et al (Immunity 2013) showed cross reactivity between pre immune memory CD4 T cell specific for HLA DR*1501 HIV 1 Gag epitope and 8 different microbial peptides (4 5 amino acid matches) Birnbaum et al (Cell 157, 1073 87, 2014) showed cross reactivity of MBP peptide specific TCR and 18 microbial peptides at 100nM 10uM peptide. Selin and Welsh (eg Immunity;20:5 16, 2004. have shown CD8 T cell cross reactivites within the virome
2 slides of unpublished data showing that the T cell library method detects both naïve and memory CD4T cells specific for bacterial lysates. The responses to Staph aureus shows more memory T cells than naïve suggesting priming by infection. The data indicate that there are CD4 T cell responses to microbiome bacteria
Conclusions so far There is a naïve memory repertoire in CD4 and CD8 T cells Many epitopes recognized have near perfect sequence matches in the microbiome Naïve and memory T cells are present that react with bacterial (and candida) lysates, including some that have not caused overt infection How cross reactive is T cell recognition?
Testing single TcRs against random peptides Birnbaum et al, Cell 157, 1073 1087, 2014 This paper describes expression on yeast of single chain MHC class II molecules with random peptides that can be used to examine the specificity of single T cell receptors.
Cross Reactivity of TcRs specific for MBP and HLA DR15 Birnbaum et al, Cell 157, 1073 1087, 2014 examined the specificity of several T cell receptors. Key peptide residues that conferred MHC binding and T cell recognition were identified. Then the selected random peptides were used to find database matches. Several were found in the microbiome data base that were recognized at lowpeptide concentrations.
Unpublished data from collaboration between Gerry Gillespie (Oxford) and Suzanne Fischer and K Chris Garcia (Stanford) showing the nature of random peptides bound to HLA B57 that were seen by the Aga1 T cell receptor specific for the KF11 gag peptide. The key amino acids recognized by this receptor were identified and peptide matches in the microbiome were identified.
Only 1/3 of Single AA Epitope Variants Recognized By two T cell clones Binding to HLA-A2 Recognition by 2 different CD8 + T cell clones 1 2 3 4 5 6 7 8 9 Lee et al., JEM 200, 1455 (2005)
Back of the Envelope Perfect 8mer matches: 25x10 9 possible peptides bacterium: ~ 1.6x10 6 8mers ~ 10 4 bacterial species 4x10 3 proteins per One perfect match per 6/9 matches: 64x10 6 possible peptides bacterium: 1.6x10 6 9mers bacterial species 4x10 3 proteins per One match per 40
Cross Reactivity Microbiome is capable of priming pre immune T cells Perfect matches not needed Restrictions in HLA anchors and key TCR contacts Huge potential for cross reactivity Does the pre immune repertoire, and therefore the microbiome, influence post vaccination T cell responses?
Acknowledgements: Suzanne Campion Elena Brenna Geraldine Gillespie Simon Brackenridge Fiona Powrie (Kennedy Inst. Oxford) Ahmed Hegazy (Kennedy Inst. Oxford) Will Fischer (LANL) Bette Korber (LANL) Chris Garcia (Stanford) Michael Birnbaum (Stanford) Suzanne Fischer (Stanford) Federica Sallusto (Bellinzona)
Acknowledgements Supported by: National Institute of Allergy and Infectious Diseases (NIAID) National Institutes of Health (NIH) Division of AIDS (DAIDS) U.S. Department of Health and Human Services (HHS) Duke Center for HIV/AIDS Vaccine Immunology and Immunogen Discovery (CHAVI ID) #UM1 AI100645