T cell recognition. Statistics & Dynamics of Functional Sensitivity

Transcription

1 T cell recognition Statistics & Dynamics of Functional Sensitivity C Molina-París LEEDS APPLIED MATHEMATICS G Lythe LEEDS APPLIED MATHEMATICS A K Sewell CARDIFF MEDICAL BIOCHEMISTRY & IMMUNOLOGY L Wooldridge CARDIFF MEDICAL BIOCHEMISTRY & IMMUNOLOGY B Laugel OXFORD IMMUNOLOGY D A Rand WARWICK SYSTEMS BIOLOGY N J Burroughs WARWICK SYSTEMS BIOLOGY H A van den Berg WARWICK SYSTEMS BIOLOGY

2 The problem in immunology pathogen challenge P(response to pathogen) 1 P(response to own tissue) 0

3 T cells kill diseased cells peptide antigen T cell infected cell or cancer cell Productive recognition conjugated cells: leads to death of diseased cell, T cell antigen receptor recognizes peptide antigen stemming further spread of disease in the body

4 The immune system T cell T Cell Receptor/peptide/MHC interaction

5 TCR peptide/mhc interaction

6 Mathematical modelling of T cell responses

7 Hepatitis B dynamics fast slow Burroughs, Rand, Pillay, Elias & Mutimer

8 Hepatitis B: viral quasi species liver virions in plasma infection infected hepatocytes infected by mutant virion secretion mu tati on wild-type mutant mutant proliferation Burroughs & Rand

9 Quasi species dynamics immune response against strain m destroys infected cells mutation from wild-type rate of change of. induces strain m Cm = αm s vm - km cdecay number of hepatocytes of virions m efficacy infected strain of m of immune response rate ofby change. fast rate vm =- δ m µm b cwt + βm cm - δm vm number of plasma virions of strain m infection of susceptible hepatocytes δm km scritical = K Σ cm by virions of strain m slow rate which is negative iff: s < secretion αm βm by susceptibility infected hepatocytes > s efficacy of viral spread minimum immune efficacy needed to protect s cells an effective immune response satisfies δm km > K αm βm Burroughs & Rand

10 The susceptibility spectrum s 0 s s K number of hepatocytes Characteristics of a persistent viral quasi-species: One or more critical susceptibilities below carrying capacity K The dominant strain (wild-type) has the lowest critical susceptibility The level of chronic infection is determined by the efficacy of the immune response to the strain with the lowest critical susceptibility Burroughs & Rand

11 Calculate the escape probability from molecular/cellular parameters

12 Viral escape and T cell poly clonality escape gap = expected number of mutations before uncontrolled mutant arises escape gap = 1 1-p n ( ) Σ j =1 n j (-1) -1 j Σ j -1 k=0 pk Key parameters: n p number of CTL clonotypes prominent in immune response probability that a clonotype retains recognition

13 Altered peptide cross reactivity Mean duration of interaction between TCR of clonotype i and pmhc ligand species j T ij = τ exp{σ Uij } Total energy of interaction TCR i with pmhc j U ij ~N(0,1) Mutate j k where a fraction η is altered Tik = τ exp{σ Uik } where U ik ~N((1-η)ln{T /ijτ },η(2-η)) conditional on the value of Tij

14 Relate Tij to the efficacy of the T cell response

15 TCR/CD3 triggering pmhci T cell antigen receptor/cd3 complex coreceptor CD8 cleft between T cell and APC T cell membrane cytosol

16 TCR triggering threshold and functional avidity time TCR triggering threshold triggering probability = exp{-tr /Tij } receptor mean time to triggering triggering rate = ligand density kinetic pre-factor dissociation triggering probability threshold TCR i with pmhc j high ligand density can compensate for low triggering probability: avidity principle functional sensitivity

17 Quantifying the avidity effect: functional sensitivity functional sensitivity L. Wooldridge, HAB, A. K. Sewell

18 Avidity and mean dissociation time optimum type curve under MHC-limited TCR/pMHC kinetics quasi-monotone type curve under TCR-limited TCR/pMHC kinetics

19 TCR triggering kinetics theory TCR/pMHC half life determines functional sensitivity TCR and pmhc levels modulate functional sensitivity dependent on affinity

20 T cell receptors work together with coreceptors CD8 TCR A. K. Sewell

21 Possible coreceptor effects: stabilizing TCR/pMHCI contact

22 Possible coreceptor effects: assist in TCR/pMHCI association

23 Possible coreceptor effects: promoting TCR/CD3 triggering lowering the triggering threshold

24 CD8 modulatory effects acting together triggering effect improves functional sensitivity of optimal ligand stabilization effect reduces avidity of optimal ligand both effects together triggering effect stabilization effect

25 Experiments to quantify co-receptor effects: Tricks with tetramers

26 Tricks with tetramers Andrew Sewell

27 T cell binding by MHCI tetramers

28 Tetramer kinetics control MHCI/CD8 interaction abrogated B. Laugel, L. Wooldridge, HAB, A. K. Sewell

29 Equilibrium staining by MHCI tetramers B. Laugel, L. Wooldridge, HAB, A. K. Sewell

30 CD8-mediated modulation of functional sensitivity L. Wooldridge, HAB, A. K. Sewell

31 TCR triggering kinetics theory with coreceptor modulation CD8 modulation can increase TCR/pMHCI half life by up to 2 fold CD8 modulation can increase TCR/pMHCI on rate by up to 2 fold CD8 can lower the TCR triggering threshold by up to 4 fold (promoting recruitment to domains with high kinase/low phosphorylase)

32 TCR triggering kinetics theory predicting a continuous, adaptable distribution of functional sensitivities given TCR vis à vis peptide ligands given ligand vis à vis TCR repertoire

33 Statistics of functional sensitivity 1 P(wij> ) functional sensitivity

34 Statistics of functional sensitivity 1 P(wij> ) functional sensitivity

35 Statistics of functional sensitivity 1 P(wij> ) functional sensitivity

36 Statistics of functional sensitivity 1 P(wij> ) this T cell will act as a low avidity clone with respect to many ligands and as a high avidity clone to a very select few which ones? determined by tuning! functional sensitivity

37 Can we determine these statistical distributions by means of experiments?

38 Probing TCR degeneracy: sampling random peptides Q L K I L K R L T Q VE Q HN M L L F L K E L N L KY S L K A L R T YV L L K R L E D QF G L K V L E R SN A L K K L S W YD generate a conditioned subset of peptides

39 Dose-response curves define functional sensitivity functional sensitivity L. Wooldridge, HAB, A. K. Sewell

40 Conditioned sets of random peptides define lower bounds xlgxxxxrl xlxkflxxl ILGKFLyWL / ILGKFLHyL functional sensitivity L. Wooldridge, HAB, A. K. Sewell

41 Probing TCR degeneracy: combinatorial libraries QY K Q V I F K E R G T AQ K GE K V I E R SN F F K L K MG L K E S W YD S L K Y E P N Q HN A T R T YV L H K R E E D QF 20 9 = 180 incubation mixtures, each containing peptides

42 Combinatorial library scan Q N T S G A C P M V I L Y F W H K R E D P1 P2 P3 P4 P5 P6 P7 P8 P9 charged amines alcohols polar, uncharged Q N T S aliphatic small G A C P M aromatic hydrophobic V I L basic (+) Y acidic (-) large F W H K R E L. Wooldridge, A. K. Sewell D

43 How do these findings change how we view the specificity of TCR recognition?

44 Minimal TCR degeneracy: naïve concept of high specificity One TCR, one pmhc ligand species recognized

45 Continuous TCR degeneracy, dynamically tuned a broad array of potential agonists which are actualized one subset at a time by dynamic tuning Perhaps Whatthymic then, selection is the roleisofreally selection negative forselection? tunability

46 Epitope space non-salient ( self ) epitopes indicated by crosses salient ( foreign ) epitopes may occur anywhere epitope space minus self to be covered by TCRs

47 Coverage by a TCR repertoire with clonotypes generated at random receptive field cross-reactivity: size of receptive field polyspecificity: one receptor has multiple receptive fields randomly generated TCRs recognize self epitopes autoimmune disease parts of epitope space remain uncovered, with overcrowding elsewhere

48 Modulation of sensitivity/degeneracy tuning of degeneracy improves coverage

49 Certain areas are crowded, others sparse some dispersion mechanism must operate

50 Statistics of functional sensitivity 1 P(wij> ) this T cell will act as a low avidity clone with respect to many ligands autoantigens and as a high avidity clone to a very select few functional sensitivity

51 Antigen presentation profile T cell Antigen-presenting cell a sea of self at various presentation levels (i.e. MHC copy numbers) & T cell responds to combined signal from many TCRs

52 Combinatorial niche richness

53 Combinatorial niche richness millions of niches with only thousands of autoantigens soft niche concept more overlap, more severe competitive exclusion

54 TCR triggering theory predicts gradated functional sensitivity gradated functional sensitivity explains avidity phenomena high degeneracy of TCR recognition adaptive self/nonself discrimination protection against autoimmunity is active & on going maintenance of an effective TCR repertoire