Tiago Paixão

When three is not a crowd : a Crossregulation Model of the dynamics and repertoire selection of regulatory CD4+ T cells

Summary:  Regulatory CD4+ T cells, enriched in the CD25 pool of healthy individuals, mediate natural tolerance and prevent autoimmune diseases. Despite their fundamental and potential clinical significance, regulatory T (TR) cells have not yet been incorporated in a coherent theory of the immune system. This article reviews experimental evidence and theoretical arguments supporting a model of TR cell dynamics, uncovering some of its most relevant biological implications. According to this model, the persistence and expansion of TR cell populations depend strictly on specific interactions they make with antigen‐presenting cells (APCs) and conventional effector T (TE) cells. This three‐partner crossregulation imposes that TR cells feed on the specific autoimmune activities they suppress, with implications ranging from their interactions with other cells to their repertoire selection in the periphery and in the thymus, and to the relationship between these cells and the innate immune system. These implications stem from the basic prediction that the peripheral dynamics sort the CD4+ T‐cell repertoire into two subsets: a less diverse set of small clones of autoreactive effector and regulatory cells that regulate each other’s growth, and a more diverse set of barely autoreactive TE cell clones, whose expansion is limited only by APC availability. It is argued that such partitioning of the repertoire sets the ground for self–non‐self discrimination.

Stochastic Monoallelic Expression of IL-10 in T Cells

IL-10 is a potent anti-inflammatory and immunomodulatory cytokine, exerting major effects in the degree and quality of the immune response. Using a newly generated IL-10 reporter mouse model, which easily allows the study of IL-10 expression from each allele in a single cell, we report here for the first time that IL-10 is predominantly monoallelic expressed in CD4+ T cells. Furthermore, we have compelling evidence that this expression pattern is not due to parental imprinting, allelic exclusion, or strong allelic bias. Instead, our results support a stochastic regulation mechanism, in which the probability to initiate allelic transcription depends on the strength of TCR signaling and subsequent capacity to overcome restrictions imposed by chromatin hypoacetylation. In vivo Ag-experienced T cells show a higher basal probability to transcribe IL-10 when compared with naive cells, yet still show mostly monoallelic IL-10 expression. Finally, statistical analysis on allelic expression data shows transcriptional independence between both alleles. We conclude that CD4+ T cells have a low probability for IL-10 allelic activation resulting in a predominantly monoallelic expression pattern, and that IL-10 expression appears to be stochastically regulated by controlling the frequency of expressing cells, rather than absolute protein levels per cell.

Within-host competition selects for plasmid-encoded toxin–antitoxin systems

Toxin–antitoxin (TA) systems are commonly found on bacterial plasmids. The antitoxin inhibits toxin activity unless the system is lost from the cell. Then the shorter lived antitoxin degrades and the cell becomes susceptible to the toxin. Selection for plasmid-encoded TA systems was initially thought to result from their reducing the number of plasmid-free cells arising during growth in monoculture. However, modelling and experiments have shown that this mechanism can only explain the success of plasmid TA systems under a restricted set of conditions. Previously, we have proposed and tested an alternative model explaining the success of plasmid TA systems as a consequence of competition occurring between plasmids during co-infection of bacterial hosts. Here, we test a further prediction of this model, that competition between plasmids will lead to the biased accumulation of TA systems on plasmids relative to chromosomes. Transposon-encoded TA systems were added to populations of plasmid-containing cells, such that TA systems could insert into either plasmids or chromosomes. These populations were enriched for transposon-containing cells and then incubated in environments that did, or did not, allow effective within-host plasmid competition to occur. Changes in the ratio of plasmid- to chromosome-encoded TA systems were monitored. In agreement with our model, we found that plasmid-encoded TA systems had a competitive advantage, but only when host cells were sensitive to the effect of TA systems. This result demonstrates that within-host competition between plasmids can select for TA systems.

Dynamics of Transcription Factor Binding Site Evolution

Evolution of gene regulation is crucial for our understanding of the phenotypic differences between species, populations and individuals. Sequence-specific binding of transcription factors to the regulatory regions on the DNA is a key regulatory mechanism that determines gene expression and hence heritable phenotypic variation. We use a biophysical model for directional selection on gene expression to estimate the rates of gain and loss of transcription factor binding sites (TFBS) in finite populations under both point and insertion/deletion mutations. Our results show that these rates are typically slow for a single TFBS in an isolated DNA region, unless the selection is extremely strong. These rates decrease drastically with increasing TFBS length or increasingly specific protein-DNA interactions, making the evolution of sites longer than ∼ 10 bp unlikely on typical eukaryotic speciation timescales. Similarly, evolution converges to the stationary distribution of binding sequences very slowly, making the equilibrium assumption questionable. The availability of longer regulatory sequences in which multiple binding sites can evolve simultaneously, the presence of “pre-sites” or partially decayed old sites in the initial sequence, and biophysical cooperativity between transcription factors, can all facilitate gain of TFBS and reconcile theoretical calculations with timescales inferred from comparative genomics.

Redundancy and the Evolution of Cis-Regulatory Element Multiplicity

The promoter regions of many genes contain multiple binding sites for the same transcription factor (TF). One possibility is that this multiplicity evolved through transitional forms showing redundant cis-regulation. To evaluate this hypothesis, we must disentangle the relative contributions of different evolutionary mechanisms to the evolution of binding site multiplicity. Here, we attempt to do this using a model of binding site evolution. Our model considers binding sequences and their interactions with TFs explicitly, and allows us to cast the evolution of gene networks into a neutral network framework. We then test some of the models predictions using data from yeast. Analysis of the model suggested three candidate nonadaptive processes favoring the evolution of cis-regulatory element redundancy and multiplicity: neutral evolution in long promoters, recombination and TF promiscuity. We find that recombination rate is positively associated with binding site multiplicity in yeast. Our model also indicated that weak direct selection for multiplicity (partial redundancy) can play a major role in organisms with large populations. Our data suggest that selection for changes in gene expression level may have contributed to the evolution of multiple binding sites in yeast. We conclude that the evolution of cis-regulatory element redundancy and multiplicity is impacted by many aspects of the biology of an organism: both adaptive and nonadaptive processes, both changes in cis to binding sites and in trans to the TFs that interact with them, both the functional setting of the promoter and the population genetic context of the individuals carrying them.

The effect of gene interactions on the long-term response to selection

Significance The role of gene interactions in the response to selection has long been a controversial subject; whereas some have claimed they are not relevant for adaptation, others have argued that their long-term effects are of high significance. In this manuscript, we derive simple and general predictions for the effect of gene interactions on the long-term response to selection in two extreme regimes. We show that, when the dynamics of allele frequencies are dominated by genetic drift, the long-term response is surprisingly simple, depending only on the initial components of the trait variance, regardless of the detailed genetic architecture. In the opposite regime, when selection dominates the dynamics of allele frequencies, the long-term response depends only on the genotype−phenotype. The role of gene interactions in the evolutionary process has long been controversial. Although some argue that they are not of importance, because most variation is additive, others claim that their effect in the long term can be substantial. Here, we focus on the long-term effects of genetic interactions under directional selection assuming no mutation or dominance, and that epistasis is symmetrical overall. We ask by how much the mean of a complex trait can be increased by selection and analyze two extreme regimes, in which either drift or selection dominate the dynamics of allele frequencies. In both scenarios, epistatic interactions affect the long-term response to selection by modulating the additive genetic variance. When drift dominates, we extend Robertson’s [Robertson A (1960) Proc R Soc Lond B Biol Sci 153(951):234−249] argument to show that, for any form of epistasis, the total response of a haploid population is proportional to the initial total genotypic variance. In contrast, the total response of a diploid population is increased by epistasis, for a given initial genotypic variance. When selection dominates, we show that the total selection response can only be increased by epistasis when some initially deleterious alleles become favored as the genetic background changes. We find a simple approximation for this effect and show that, in this regime, it is the structure of the genotype−phenotype map that matters and not the variance components of the population.

Quantitative insights into stochastic monoallelic expression of cytokine genes

Gene expression from both parental alleles is beneficial by masking the effects of deleterious recessive mutations and by reducing the noise in gene expression in diploid organisms. However, a class of genes are expressed preferentially or strictly from a single allele. The selective advantage of avoiding biallelic expression is clear for allelic‐excluded antigen receptor and odorant receptor genes, genes undergoing X‐chromosome inactivation in females and parental genomic imprinted genes. In contrast, there is no clear biological rationale for the predominant and stochastic monoallelic expression of cytokine genes in the immune system, and the underlying mechanism is elusive and controversial. A clarification of the mechanism of predominant monoallelic expression would be instrumental in better understanding its eventual biological functional. This prompted the development of a quantitative framework that could describe the dynamics of the pattern of allele expression of the IL‐10 gene, from which general quantitative insights could be gained. We report that the experimental observations on these patterns of allelic expression cannot be easily reconciled with a simple model of stochastic transcriptional activation, in which the two alleles are, at any time, equally competent for transcription. Instead, these observations call into action a general model of eukaryotic transcriptional regulation according to which the locus competence for transcription is dynamic, involving multiple, cooperative and stochastic modification steps. In this model, the probability that an allele becomes transcriptionally active is a function of the number of chromatin modifications that it accumulated. On the basis of the properties of this model, we argue that predominant monoallelic expression might have had no adaptive role, and may have evolved under indirect selection for low frequency of expressing cells.

Accumulation of Spontaneous Mutations in the Ciliate Tetrahymena thermophila

Knowledge of the rate and fitness effects of mutations is essential for understanding the process of evolution. Mutations are inherently difficult to study because they are rare and are frequently eliminated by natural selection. In the ciliate Tetrahymena thermophila, mutations can accumulate in the germline genome without being exposed to selection. We have conducted a mutation accumulation (MA) experiment in this species. Assuming that all mutations are deleterious and have the same effect, we estimate that the deleterious mutation rate per haploid germline genome per generation is U = 0.0047 (95% credible interval: 0.0015, 0.0125), and that germline mutations decrease fitness by s = 11% when expressed in a homozygous state (95% CI: 4.4%, 27%). We also estimate that deleterious mutations are partially recessive on average (h = 0.26; 95% CI: –0.022, 0.62) and that the rate of lethal mutations is <10% of the deleterious mutation rate. Comparisons between the observed evolutionary responses in the germline and somatic genomes and the results from individual-based simulations of MA suggest that the two genomes have similar mutational parameters. These are the first estimates of the deleterious mutation rate and fitness effects from the eukaryotic supergroup Chromalveolata and are within the range of those of other eukaryotes.

SEX RATIO EVOLUTION UNDER PROBABILISTIC SEX DETERMINATION

Sex allocation theory has been remarkably successful at explaining the prevalence of even sex ratios in natural populations and at identifying specific conditions that can result in biased sex ratios. Much of this theory focuses on parental sex determination (SD) strategies. Here, we consider instead the evolutionary causes and consequences of mixed offspring SD strategies, in which the genotype of an individual determines not its sex, but the probability of developing one of multiple sexes. We find that alleles specifying mixed offspring SD strategies can generally outcompete alleles that specify pure strategies, but generate constraints that may prevent a population from reaching an even sex ratio. We use our model to analyze sex ratios in natural populations of Tetrahymena thermophila, a ciliate with seven sexes determined by mixed SD alleles. We show that probabilistic SD is sufficient to account for the occurrence of skewed sex ratios in natural populations of T. thermophila, provided that their effective population sizes are small. Our results highlight the importance of genetic drift in sex ratio evolution and suggest that mixed offspring SD strategies should be more common than currently thought.

Toward a unifying framework for evolutionary processes

The theory of population genetics and evolutionary computation have been evolving separately for nearly 30 years. Many results have been independently obtained in both fields and many others are unique to its respective field. We aim to bridge this gap by developing a unifying framework for evolutionary processes that allows both evolutionary algorithms and population genetics models to be cast in the same formal framework. The framework we present here decomposes the evolutionary process into its several components in order to facilitate the identification of similarities between different models. In particular, we propose a classification of evolutionary operators based on the defining properties of the different components. We cast several commonly used operators from both fields into this common framework. Using this, we map different evolutionary and genetic algorithms to different evolutionary regimes and identify candidates with the most potential for the translation of results between the fields. This provides a unified description of evolutionary processes and represents a stepping stone towards new tools and results to both fields.