Statistical physics of T cell receptor selection and function Thesis committee meeting, 04/15/2009 Andrej Košmrlj Physics Department Massachusetts Institute of Technology

Andrej Košmrlj, 04/15/ Immune system Flexible system to combat diverse pathogens Mis-regulation leads to autoimmune diseases Multiple Sclerosis Diabetes

Andrej Košmrlj, 04/15/ Antigen presentation and recognition APCs internally process self and foreign proteins, cut them to short peptides (8-15 aa) and present them on the surface antigen recognition: strong binding of TCR to antigenic pMHC self pMHC bind TCR more weakly Antigen presenting cell T cell

Andrej Košmrlj, 04/15/ T cell receptors most T cell express distinct TCR - stochastic gene rearrangement process TCR antigen recognition: degeneracy - each TCR can recognize many antigenic peptides specificity - TCR recognition of antigen is specific for single point amino acid mutations

Andrej Košmrlj, 04/15/ Development in thymus strong binding weak binding Negative selection deletes strongly binding autoimmune TCR Positive selection results in weak binding of TCR to endogenous pMHC – implicated in survival, MHC restriction. Palmer et al, Nature (2006)

Andrej Košmrlj, 04/15/ Specificity of antigen recognition Specificity to antigenic peptide: Many peptides: mutations destroy activation – specific T-cells Single peptide: mutations don’t matter – cross-reactive T-cells Huesby et al, Cell (2005) P-1 P2 P3 P5 P-1 P2 P3 P5 Many self-peptidesOne self-peptide

Andrej Košmrlj, 04/15/ Model Surviving T cells: E int > E N for all peptides; E int < E P for at least one peptide TCR-peptide contacts: self peptides in thymus: PNAS (2008) PRL (submitted)

Andrej Košmrlj, 04/15/ Extreme value distribution increasing M (self-peptides) TCRs with weaker amino acids Selection condition: Probability of TCR selection: Properties of

Andrej Košmrlj, 04/15/ Amino acid composition of selected TCRs WEAK STRONG

Andrej Košmrlj, 04/15/ Selected TCRs are enriched with weak amino acids WEAK STRONG Abhishek Jha

Andrej Košmrlj, 04/15/ Frustration leads to specific TCR repertoire One peptide E N < E < E P selected E < E N negatively selected Many peptides Solution: special class of sequences enriched with weak amino acids that distribute moderate interactions through the entire sequence Optimizing interactions with one peptide leads to “bad” interactions with another More hotspots – specific T cell repertoire TCR peptide

Andrej Košmrlj, 04/15/ Recall specificity of antigen recognition Specificity to antigenic peptide: Many peptides: mutations destroy activation – specific T-cells Single peptide: mutations don’t matter – cross-reactive T-cells Huesby et al, Cell (2005) P-1 P2 P3 P5 P-1 P2 P3 P5 Many self-peptidesOne self-peptide

Andrej Košmrlj, 04/15/ Specificity mirrors experiments Hot spot: more than half the mutations of a peptide amino acid destroy reactivity

Andrej Košmrlj, 04/15/ Increased number of moderately interacting contacts B3K 506 TCR C57BL/6 derived MHC + peptide specific YAe62.8 TCR IA b -SP derived MHC + peptide degenerate Increased number of moderate interactions Decreased number of strong interactions Huesby et al, Nat. Immunol (2006)

Andrej Košmrlj, 04/15/ TCR RECOGNITION ~ STATISTICAL SCAN OF A BAR CODE

Andrej Košmrlj, 04/15/ Large N limit (1/2) Selection condition: Scaling in the large peptide (N) limit: Statistical mechanics:

Andrej Košmrlj, 04/15/ Large N limit (2/2) Selection condition: Hamiltonian minimization: Amino acid composition of selected TCRs: STRONG AA WEAK AA

Andrej Košmrlj, 04/15/ Phase diagram

Andrej Košmrlj, 04/15/ Selected TCRs are enriched withweak amino acids WEAK STRONG

Andrej Košmrlj, 04/15/ Future project HIV elite controllers (long term non-progressors) are associated with special MHC alleles (e.g. HLA B57). TCRs restricted by B57 allele are more cross-reactive - helps recognizing HIV mutants. HLA B57 allele bind fewer peptide than most other alleles. Our model: thymic selection with fewer self- peptides leads to more cross-reactive TCRs. Connect thymic selection to viral dynamics model (Elizabeth Read) to explain differences in the acute phase of viral infection HIV

Acknowledgements Arup K. Chakraborty Mehran Kardar Abhishek K. Jha Elizabeth L. Read Thesis committee meeting, 04/15/2009

Andrej Košmrlj, 04/15/ T cell Innate Immunity Adaptive Immunity Antigen presentation and recognition dendritic cell How does our immune system work ?

Andrej Košmrlj, 04/15/ UNDERSTANDING ADAPTIVE IMMUNITY Flexible system to combat diverse pathogens Mis-regulation leads to autoimmune diseases Multiple Sclerosis principles design rules The challenge: develop principles that govern the emergence of an immune response or autoimmunity and design rules for therapies Diabetes Theory/computationExperiments statistical mechanics genetics biochemistry imaging chemical kinetics

Andrej Košmrlj, 04/15/ Model Surviving T cells: E>E N for all peptides; E < E P for at least one peptide TCR-peptide contacts: self peptides in thymus:

Andrej Košmrlj, 04/15/ Amino acid frequencies of recognized antigens

Andrej Košmrlj, 04/15/ Distribution of single site contact energies between reactive T cells and antigen B3K 506 TCR C57BL/6 derived MHC + peptide specific YAe62.8 TCR IA b -SP derived MHC + peptide degenerate

Andrej Košmrlj, 04/15/ Distribution of single site contact energies between reactive T cells and antigen Increased number of moderate interactions Decreased number of strong interactions Selection with many peptides increases the number of moderate contacts between TCR and peptide amino acids

Andrej Košmrlj, 04/15/ Recall hotspots in experiments Hot spot: more than half the mutations of a peptide amino acid destroy reactivity

Andrej Košmrlj, 04/15/ How long is peptide? Human proteome P ≈10 7

Andrej Košmrlj, 04/15/ TCR RECOGNITION IS LIKE SCANNING A BAR CODE

Andrej Košmrlj, 04/15/ Model TCR pMHC MHC peptide conserved variable Miyazawa-Jernigan Surviving T cells: E E P for at least one peptide Pairwise interactions

Andrej Košmrlj, 04/15/ Fraction of selected T cells Negative selection dominates Positive selection dominates

Andrej Košmrlj, 04/15/ Fraction of selected T cells Negative selection dominates Positive selection dominates