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Beyond MHC: The stickleback T-cell repertoire and evolutionary dynamics


Wölfing,  Benno
Department Evolutionary Ecology, Max Planck Institute for Evolutionary Biology, Max Planck Society;

Milinski,  Manfred
Department Evolutionary Ecology, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Wölfing, B. (2012). Beyond MHC: The stickleback T-cell repertoire and evolutionary dynamics. PhD Thesis, Christian-Albrechts-Universität, Kiel.

Parasites and pathogens impose selection pressures on their hosts that are not only strong but also constantly changing as parasites adapt to host defenses or new pathogen strains become abundant because of environmental fluctuations. Parasite mediated selection is believed to be a major selective force responsible for the evolution of sexual reproduction, the maintenance of genetic variation and the evolution of mate choice. It can drive local adaptation and speciation. Since selection exerted by parasites is implicated in so many key topics in evolutionary biology, it is of central interest to understand how defense mechanisms evolve. Major histocompatibility complex (MHC) molecules play a central role in the adaptive immune response of vertebrates. They present pathogenic peptides on the cell surface where they can be recognized by T-cells with their T-cell receptor (TCR). This leads to the initiation of an immune response. Every MHC molecule can present only peptides that match its peptide-binding groove, so that a single MHC molecule confers resistance to some but not all pathogens. Numerous studies have documented associations between resistance and the presence of specific MHC alleles. However, the exact causes and mechanisms of pathogen mediated selection on the MHC are only partly resolved. For example, it is unclear why individuals that express an intermediate number of different MHC molecules are often more immunocompetent than individuals that express many different MHC molecules and why susceptibility MHC alleles are often not recessive but codominant when they occur in combination with resistance alleles. While existing studies on host-pathogen coevolution typically characterize the adaptive immune system only by MHC genotyping host individuals, this thesis is dedicated to extend the focus to T-cells and their TCRs. Our model system is the threespined stickleback (Gasterosteus aculeatus). There are two main incentives to study T-cells and T-cell diversity in this model species for evolutionary ecology. On the one hand research on T-cells may directly help to unravel selection pressures operating on the MHC. On the other hand comparative immunology, that is the study of the similarities and differences between immune systems, can help to enhance our understanding of immune system function and evolution. In the first chapter (my co-authors and) I model the effect of an increase in intra-individual MHC diversity on T-cell repertoire diversity. Since MHC molecules present both self and pathogenic peptides, T-cells have to be screened for self-tolerance during their maturation in order to prevent autoimmune reactions. Self-reactive T-cells are eliminated in this process termed negative selection. As intra-individual MHC-diversity increases, more and more selfpeptides are presented, so that T-cell loss during negative selection increases. Individuals of high MHC-diversity may have reduced immunocompetence because of T-cell repertoire depletion: Their MHC molecules can present many pathogenic peptides, but they may lack Tcells with the appropriate TCR to recognize them. The presented model suggests that this can explain why individuals of intermediate intra-individual MHC diversity are most resistant. The model can be tested by quantifying the loss of TCR specificities during negative selection in individuals of low and high MHC diversity. To this end I characterize the TCRß loci and the thymus of stickleback in chapters two and three and discuss how TCRß diversity can be assessed in chapter four. The loci encoding the ß chain of the TCR do not contain functional genes in the germline state. Instead they consist of arrays of subgenic fragments that are rearranged in an essentially random process during the maturation of each individual T-cell. Based on the published reference genome, BAC-sequencing and linkage analysis I show that sticklebacks – in contrast to all other species studied so far – have two unlinked TCRß loci, which rearrange independently during T-cell maturation and are both expressed in mature T-cells. The extraordinary genomic organization likely influences TCRß repertoire diversity and offers a unique opportunity to gain insights on how allelic exclusion is enforced. I discuss the phylogeny of the subgenic fragments at the two loci that partly arose by block duplication. An interesting allelic variant is a six amino acid repeat motif in the cd loop of the conserved Cß fragment. A complete list of all subgenic fragments allows assessment of the potential TCRß repertoire, defined as the set of all TCRß sequences an individual can produce. This is a robust basis for PCR-based approaches that aim at characterizing realized TCRß repertoires. The thymus provides the microenvironment in which T-cells rearrange their TCR loci and are selected for self-tolerance. In stickleback it is a paired organ in the dorsal region of the gill cavity. Based on the distribution of stromal and parenchymal cell types as well as the expression of recombination activating gene-1 and MHC, two zones can be differentiated that resemble the mammalian cortex and medulla morphologically and functionally. Early developmental stages of T-cells are located in the cortex. Negative selection takes place upon entering the medulla. The anatomical separation of T-cells prior to and post the negative selection phase, opens up the opportunity to study the diversity loss during selection by comparing TCR diversity in the two thymic zones. With a death rate greater than 95% among maturing T-cells, the thymus hosts a developmental process in which the yield of functional cells is less than that of any other organ system. When resources are allocated to this process differs significantly between species. I show that the stickleback thymus develops early in ontogeny. Completely rearranged TCRß genes could already be detected one week post fertilization. Two clearly demarcated zones are present in the thymus from four weeks post hatching. This suggests that sticklebacks may be able to mount an adaptive immune response one or two months post-hatch. In ongoing work I seek to describe the composition and diversity of realized TCRß repertoires in stickleback. Based on the description of TCRß gene segments in chapter two, primers were designed that amplify the most diverse region of rearranged TCRß genes. This region encodes for the complementarity determining region 3 which is in direct contact with the peptide when the TCR interacts with a peptide-MHC complex. Extensive cloning and sequencing of amplicons reveals that the repertoire of naive sticklebacks is diverse but contains a higher proportion of non-functional rearrangements and fewer insertions than the human repertoire. This work provides a basis for exhaustive sequencing and comparison of TCRß repertoires e.g. in pre- and postselection T-cell pools or naive and infected individuals. Based on the knowledge of the selective forces acting on a trait, mathematical models can explore how it will spread in a population. In the fifth chapter I explore models that describe the spreading of traits under frequency-dependent selection. In models of evolutionary game theory frequency dependent selection is implemented by assigning fitness to individuals according to a payoff obtained in an evolutionary game. Traditional evolutionary game theory has derived deterministic differential equations that describe the spreading of traits in infinitely large populations. However, in populations of finite size noise plays a major role in evolutionary dynamics. I analyze two scenarios in a finite population. In the first scenario individuals obtain a payoff based on interactions with a representative sample of the population, so that all individuals of the same phenotype obtain the same payoff. In the second scenario payoff evaluation is based on a single interaction with a randomly drawn individual, so that individuals of the same type can have different payoffs. While the evolutionary dynamics of the two scenarios are identical under weak selection, the evolutionary dynamics become very different under strong selection