Why Is the Adaptive Immune System So Diverse and Specific?

Why is the adaptive immune system so diverse and specific? What will you learn today? Self tolerance is more complicated than what the textbook says Repertoires are very diverse because lymphocytes have to be specific Simple mathematical models help us thinking clearly Polymorphism versus diversity of MHC First short refresh on tolerance Death by neglect 0.3 R/R0 0.2 0.1 0 1 2 3 4 MHC diversity (log M ) Figure 2: Positive and negative selection according to the avidity model [13]. The curve in (a) depicts the distribution of thymocyte avidities for self peptide–MHC complexes. In our model, the chance p to be positively selected by a single MHC type is the chance that the avidity between the thymocyte T cell receptor and any of the self peptide– MHC complexes exceeds threshold T1. Thymocytes with avidities for self peptide–MHC complexes exceeding the upper threshold T2 are negatively selected (with chance n per MHC type). Panel (b) depicts the size of the T cell repertoire as a function of MHC diversity. The number of clones in the functional repertoire R is plotted as a fraction of the total initial lymphocyte repertoire R0. Parameters are: p =0.01, and n =0.005. 2 MHC diversity within the individual Since individual MHC diversity increases the presentation of pathogens to the immune system, one may wonder why the number of MHC genes is not much higher than it is. The argument that is mostly invoked is that more MHC diversity within the individual would lead to T cell repertoire depletion during self tolerance induction. This argument is incomplete, however, because more MHC diversity could also increase the number of clones in the T cell repertoire through positive selection. In order to be rescued in the thymus, lymphocytes need to recognize MHC–self peptide complexes with su⇤cient avidity. A high MHC diversity thus increases both the number of lymphocyte clones that are positively selected and the number of clones that are negatively selected. To calculate the net effect of these two opposing processes we develop a simple mathematical model [5]. Consider an individual with M different MHC molecules and an initial T lymphocyte repertoire consisting of R0 different clones. Let p and n denote the (unconditional) chances that a clone is positively selected by a single MHC type, because its avidity is higher than a threshold T1, or negatively selected because its avidity exceeds a higher threshold T2, respectively (see Fig. 2). By this definition, thymocytes can only be negatively selected by MHC molecules by which they are also positively selected, i.e. n<p. Since T cell clones need to be positively selected by at least one of the MHC molecules, and avoid negative selection by all of the MHC molecules, the number of clones in the functional repertoire R can be expressed as R = R (1 n)M (1 p)M , (7) 0 − − − [5]. The functional repertoire R thus contains all T cell clones that⇥ fail to be negatively selected, minus the ones that also fail to be positively selected by any of the M different MHC molecules of the host. Experimental estimates for the parameters of this model have recently become available. In mice, around 3% of the T cells produced in the thymus end up in the mature T cell repertoire, and at least 50% of all positively selected T cells have been shown to undergo negative selection in the thymus [17]. Thus, 94% of all thymic T cells fail to be positively selected by any of the MHC molecules in the host [17]. These estimates can be used to calculate the chances p and n of a T cell clone to be positively or negatively selected by a single type of MHC molecule. Taking into account that inbred mice are homozygous and therefore express 3 types of class I MHC and 3 types of class II MHC molecules, p and n follow from: (1 p)6 =0.94 and n = p/2. This yields p =0.01 and n =0.005. − Using these experimental estimates, the number of clones in the functional T cell repertoire R increases with 3 What is the diversity of the T cell repertoire? Parham cites estimate from Arstila [Science, 1999]: 2.5x107 Nowadays next generation sequencing (NGS): The current study was designed explicitly to improve estima- A CD4 naive T cells CD8 naive T cells tion of the TCR repertoire richness of stringently defined naïve p=0.008 p=0.008 and memory T cells. By sequencing multiple replicate TCRB li- 2x108 braries of cells from each T-cell subset and applying nonparametric 1x108 statistical analysis, we find that human TCR repertoires are an order of magnitude more diverse than previously estimated. 5x107 Despite significant age-related decreases in richness, humans 7 maintain high diversity during healthy aging. Strikingly, we find 2x10 age-associated changes in the distribution of clonal sizes, in 1x107 particular in the naïve compartment, which may reflect un- Distinct TCRB sequences evenness of homeostatic expansion with clonal expansion of 20 - 35 70 - 85 20 - 35 70 - 85 2014 PNAS Qial. et some naïve T cells that equal or exceed clonal sizes of memory T B p=0.008Age p=0.008Age cells. The inequalities in clonal sizes could compromise the im- 4x107 mune response to the majority of antigenic epitopes while Note that this is β-chains only (nucleotides & Chao2)! causing an increased responsiveness to selected few epitopes. 2x107 sequences In mice almost every naive T cell unique TCR β Results 1x107 Gene Segment Use and CDR3 Features in Young and Elderly TCRB Rearrangements. In initially evaluating TCRB repertoires in 5x106 young and elderly subjects we compared the composition of TCRB gene rearrangements at the level of TCRBV and TCRBJ Distinct TCR 20 - 35 70 - 85 20 - 35 70 - 85 gene segment use and the features of the CDR3-encoding Age (years) Age (years) junctional nucleotides. Apheresis lymphocytes were obtained C CD4 memory T cells CD8 memory T cells from four 20- to 35- and five 70- to 85-y-old healthy adults who p=0.06 p=0.11 were regular platelet donors. Naïve CD4 and CD8 T cells were purified by cell sorting. We used a stringent definition of naïve 2x106 cells (CD3+CD4+ or CD8+CCR7+CD45RAhighCD28+) and very restrictive gating to ensure purity. Approximately 1.5–3 million sequence reads were obtained for each T-cell subset of each 1x106 donor (Table S1). TCRBV and TCRBJ gene segments were used at comparable frequencies in the repertoires of naïve CD4 and 0.0 CD8 T cells in young and old individuals (Fig. S1A), whereas the sequences TCRB Distinct 20 - 35 70 - 85 20 - 35 70 - 85 memory repertoires of CD4 and, particularly, CD8 T cells show variable and individual-specific gene segment use frequencies 6 p=0.06 p=0.10 (Fig. S1B). CDR3 sequences in the young and elderly were D 2x10 comparable in length and did not show any definitive age-related features (Fig. S1 C and D). 6 sequences 1x10 High Richness of Naïve CD4 and CD8 TCRB Repertoires in Young and β Elderly Adults. To obtain sequence data to estimate global TCRB repertoire richness we used the experimental design of analyzing 0.0 aseriesofreplicatelibrariesfromindependentcellaliquotsfrom 20 - 35 70 - 85 20 - 35 70 - 85 each T-cell subset in each individual. These replicates allowed us to Distinct TCR Age (years) Age (years) calculate repertoire richness by applying the “Chao2” estimator, anonparametricestimatorofunseenspecies(14).Theapproach Fig. 1. Age is associated with a modest decrease in diversity of the TCRB reper- allows estimation of the extent to which the full repertoire is cov- toire. TCRB sequences were obtained from replicate samples of naïve (A and B)and ered and use of this information to determine a lower bound of the memory (C and D)CD4andCD8Tcells.AlowerboundofTCRBrichnesswasesti- total number of species in the repertoire. Because the Chao2 estimated by applying nonparametric statistics using the Chao2 estimator. Results are mator requires only a binary characterization of presence or ab- shown for nucleotide (A and C)andderivedaminoacidsequences(B and D). – – sence of each clone in each replicate library, it circumvents the Estimates were compared by Wilcoxon Mann Whitney test. Increase in age is associated with a decline in richness of naïve CD4 and CD8 T cells; however, the challenges that arise in experimental designs using only a single repertoire in the elderly remains highly diverse. Richness in CD4 and CD8 memory library and avoids confusing the effects of PCR amplification with Tcellsmarkedlydiffered,whereastheimpactofagewasnegligiblysmall. the presence of expanded T-cell clones. To not count possible sequencing errors as independent sequences, we rejected single sequences as erroneous if a highly similar clone of greater frequency (15). Second, we estimated the confidence intervals using the ap- was identified in the same library (see Materials and Methods for the proach originally developed by Chao (16). The 95% confidence definition of similarity). intervals with both methods were very narrow (Table S2). The lower bounds on TCRB gene richness obtained with this Naïve TCRB repertoire richness declined significantly in the approach yielded higher estimates than previous studies (Fig. 1). 70- to 85-y-old adults to a lower bound richness of 8–57 million Young adults carried an estimated 60–120 million different different nucleotide sequences encoding ∼5–15 million TCR TCRB genes, both in the CD4 and CD8 naïve T-cell repertoires. β-chain amino acid sequences (P = 0.008, Fig. 1 A and B). In- This high diversity in nucleotide sequences was reflected in a terestingly, the estimates in elderly CD4 and CD8 naïve T cells large functional repertoire of TCR β chains with a lower boundary were similar despite the greater decline in CD8 compared with of ∼20 million different amino acid sequences.

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