Early lire imprints the hierarchy of T cell clone sizes

The adaptive immune system responds to pathogens by selecting clones of cells with specific receptors. While clonal selection in response to particular antigens has been studied in detail, it is unknown how a lifetime of exposures to many antigens collectively shape the immune repertoire. Here, using mathematical modeling and statistical analyses of T cell receptor sequencing data, we develop a quantitative theory of human T cell dynamics compatible with the statistical laws of repertoire organization. We find that clonal expansions during a perinatal time window leave a long-lasting imprint on the human T cell repertoire, which is only slowly reshaped by fluctuating clonal selection during adult life. Our work provides a mechanism for how early clonal dynamics imprint the hierarchy of T cell clone sizes with implications for pathogen defense and autoimmunity

Early life imprints the hierarchy of T cell clone sizes

The adaptive immune system responds to pathogens by selecting clones of cells with specific receptors. While clonal selection in response to particular antigens has been studied in detail, it is unknown how a lifetime of exposures to many antigens collectively shape the immune repertoire. Here, through mathematical modeling and statistical analyses of T cell receptor sequencing data we demonstrate that clonal expansions during a perinatal time window leave a long-lasting imprint on the human T cell repertoire. We demonstrate how the empirical scaling law relating the rank of the largest clones to their size can emerge from clonal growth during repertoire formation. We statistically identify early founded clones and find that they are indeed highly enriched among the largest clones. This enrichment persists even after decades of human aging, in a way that is quantitatively predicted by a model of fluctuating clonal selection. Our work presents a quantitative theory of human T cell dynamics compatible with the statistical laws of repertoire organization and provides a mechanism for how early clonal dynamics imprint the hierarchy of T cell clone sizes with implications for pathogen defense and autoimmunity.Comment: 8 pages, 4 figures + 27 pages supplement with 20 figure

Receptor crosstalk improves concentration sensing of multiple ligands

Cells need to reliably sense external ligand concentrations to achieve various biological functions such as chemotaxis or signaling. The molecular recognition of ligands by surface receptors is degenerate in many systems leading to crosstalk between different receptors. Crosstalk is often thought of as a deviation from optimal specific recognition, as the binding of non-cognate ligands can interfere with the detection of the receptor's cognate ligand, possibly leading to a false triggering of a downstream signaling pathway. Here we quantify the optimal precision of sensing the concentrations of multiple ligands by a collection of promiscuous receptors. We demonstrate that crosstalk can improve precision in concentration sensing and discrimination tasks. To achieve superior precision, the additional information about ligand concentrations contained in short binding events of the non-cognate ligand should be exploited. We present a proofreading scheme to realize an approximate estimation of multiple ligand concentrations that reaches a precision close to the derived optimal bounds. Our results help rationalize the observed ubiquity of receptor crosstalk in molecular sensing

Precision of readout at the hunchback gene: analyzing short transcription time traces in living fly embryos

The simultaneous expression of the hunchback gene in the numerous nuclei of the developing fly embryo gives us a unique opportunity to study how transcription is regulated in living organisms. A recently developed MS2-MCP technique for imaging nascent messenger RNA in living Drosophila embryos allows us to quantify the dynamics of the developmental transcription process. The initial measurement of the morphogens by the hunchback promoter takes place during very short cell cycles, not only giving each nucleus little time for a precise readout, but also resulting in short time traces of transcription. Additionally, the relationship between the measured signal and the promoter state depends on the molecular design of the reporting probe. We develop an analysis approach based on tailor made autocorrelation functions that overcomes the short trace problems and quantifies the dynamics of transcription initiation. Based on live imaging data, we identify signatures of bursty transcription initiation from the hunchback promoter. We show that the precision of the expression of the hunchback gene to measure its position along the anterior-posterior axis is low both at the boundary and in the anterior even at cycle 13, suggesting additional post-transcriptional averaging mechanisms to provide the precision observed in fixed embryos

Stochatic interacting systems in biophysics : immunology and development

Nous présentons deux problèmes de biologie faisant appel à un traitement de données et des modèles issus de la physique statistique : la dynamique des populations en immunologie et la régulation génétique dans le développement embryonnaire. En immunologie, nous étudions le problème de la sélection somatique dans le système immunitaire adaptatif: la sélection cellulaire et la compétition qui s’y opèrent, constituant un système quasi Darwinien au sein de l’organisme. Dans un premier temps, nous considérons différentes hypothèses surla dynamique sélective : signaux déclenchant la division ou la mort cellulaire par liaison antigénique ou par cytokines, paramètres dynamiques de division, mort et fluctuations environnementales. Nous explorons leur influence sur la taille des clones dont la distribution à queue lourde a été observée à travers les espèces et les types de cellules. Deux familles de modèles émergent : un premier dans lequel le bruit est cohérent à l’échelle du clone et un second dans lequel le bruit varie de cellule à cellule. Nous montrons dans quelle mesure la distribution de taille de clones permet de déterminer le meilleur modèle et relions la forme de la distribution ainsi que l’exposant apparent de la loi de puissance aux paramètres biologiques. Dans un second temps, nous explorons les caractéristiques du réseau complexe et aléatoire formé par les clones et les antigènes : dimension, adjacence, dynamique. Nous nous intéressons à l’effet de la sélection dans le temps et à la vitesse d’évolution des clones.La deuxième partie de cette thèse est consacrée au développement embryonnaire. Dans l’embryon, il est essentiel pour le noyau de déterminer sa position avec une grande précision pour orienter la différentiation et construire un organisme structuré viable. Cette information positionnelle est acquise, transmise et conservée par la diffusion de protéines et l’activa- tion de circuits génétiques.Plus précisément, la formation de l’axe antéropostérieur chez la Drosophile est déterminée entre autres par l’activation du gène hunchback par la protéine Bicoid. Nous analysons des données issues d’expériences d’imagerie fluorescente dynamique dans les premiers cycles cellulaires de l’embryon. Nous construisons un modèle spécifique permettant d’analyser la fonction d’autocorrélation des traces temporelles de fluorescence qui prend en compte toutes les difficultés biologiques et expérimentales (bruit, calibration traces courtes, structure du gène artificiel) pour extraire les paramètre dynamiques d’activation de hunchback. Nous examinons différentes dynamiques potentielles (poisonnienne, markovienne ou non markovienne) et leur implication pour l’information dont la cellule dispose sur sa position ainsi que la précision de la lecture du gradient de Bicoid.This work presents two problems of biology requiring data analysis and models from statistical mechanics: population dynamics in immunology and gene regulation in embryo development. In immunology I study the problem of somatic evolution in the adaptive immune system: selection of and competition among cells that form a close-to-Darwinian system within one individual. First, I consider different potential hypotheses for selective dynamics: division and death signals through antigen binding or cytokines, dynamical parameters for division, death and fluctuations of the environment. I explore their impact on clone sizes. Experimentally, these clone sizes show heavy tail distributions for different species and differentpools of cells. Two families of models emerge: models where noise is consistent at the level of the clone and models where it varies from cell to cell. I show how clone size distributions help discriminate between these models and relate the shape of the distribution and the exponent of the power law to biological parameters. Second, I explore the specifics of the complex stochastic network of clones and antigens: its dimensionality, connectivity and dynamics. I study the effect of selection at different time scales and the speed of evolution of the clones. The second part of this dissertation concerns embryo development. In the fly embryo, it is crucial that nuclei can evaluate their position within the organism accurately to determine cell fate and build a healthy organism. This positional information is obtained, transferred, and maintained through diffusion of proteins and activation of genetic networks. More specifically, the patterning of the antero-posterior axis in drosophila requires the hunchback gene, activated by the Bicoid protein. I analyze data from fluorescent live imaging in the early cell cycles of the embryo. I build a tailor-made model to analyze autocorrelation functions of fluorescence time traces overcoming all biological and experimental challenges (noise, calibration, short traces, transgene construct) to extract the parameters of hunchback activation. I examine several potential types of dynamics for gene switiching (Poisson, Markovian or non-Markovian) and predict their impact on positional information and the accuracy of bicoid gradient readout

Systèmes stochastiques en interaction en biophysique : immunologie et développement

This work presents two problems of biology requiring data analysis and models from statistical mechanics: population dynamics in immunology and gene regulation in embryo development. In immunology I study the problem of somatic evolution in the adaptive immune system: selection of and competition among cells that form a close-to-Darwinian system within one individual. First, I consider different potential hypotheses for selective dynamics: division and death signals through antigen binding or cytokines, dynamical parameters for division, death and fluctuations of the environment. I explore their impact on clone sizes. Experimentally, these clone sizes show heavy tail distributions for different species and differentpools of cells. Two families of models emerge: models where noise is consistent at the level of the clone and models where it varies from cell to cell. I show how clone size distributions help discriminate between these models and relate the shape of the distribution and the exponent of the power law to biological parameters. Second, I explore the specifics of the complex stochastic network of clones and antigens: its dimensionality, connectivity and dynamics. I study the effect of selection at different time scales and the speed of evolution of the clones. The second part of this dissertation concerns embryo development. In the fly embryo, it is crucial that nuclei can evaluate their position within the organism accurately to determine cell fate and build a healthy organism. This positional information is obtained, transferred, and maintained through diffusion of proteins and activation of genetic networks. More specifically, the patterning of the antero-posterior axis in drosophila requires the hunchback gene, activated by the Bicoid protein. I analyze data from fluorescent live imaging in the early cell cycles of the embryo. I build a tailor-made model to analyze autocorrelation functions of fluorescence time traces overcoming all biological and experimental challenges (noise, calibration, short traces, transgene construct) to extract the parameters of hunchback activation. I examine several potential types of dynamics for gene switiching (Poisson, Markovian or non-Markovian) and predict their impact on positional information and the accuracy of bicoid gradient readout.Nous présentons deux problèmes de biologie faisant appel à un traitement de données et des modèles issus de la physique statistique : la dynamique des populations en immunologie et la régulation génétique dans le développement embryonnaire. En immunologie, nous étudions le problème de la sélection somatique dans le système immunitaire adaptatif: la sélection cellulaire et la compétition qui s’y opèrent, constituant un système quasi Darwinien au sein de l’organisme. Dans un premier temps, nous considérons différentes hypothèses surla dynamique sélective : signaux déclenchant la division ou la mort cellulaire par liaison antigénique ou par cytokines, paramètres dynamiques de division, mort et fluctuations environnementales. Nous explorons leur influence sur la taille des clones dont la distribution à queue lourde a été observée à travers les espèces et les types de cellules. Deux familles de modèles émergent : un premier dans lequel le bruit est cohérent à l’échelle du clone et un second dans lequel le bruit varie de cellule à cellule. Nous montrons dans quelle mesure la distribution de taille de clones permet de déterminer le meilleur modèle et relions la forme de la distribution ainsi que l’exposant apparent de la loi de puissance aux paramètres biologiques. Dans un second temps, nous explorons les caractéristiques du réseau complexe et aléatoire formé par les clones et les antigènes : dimension, adjacence, dynamique. Nous nous intéressons à l’effet de la sélection dans le temps et à la vitesse d’évolution des clones.La deuxième partie de cette thèse est consacrée au développement embryonnaire. Dans l’embryon, il est essentiel pour le noyau de déterminer sa position avec une grande précision pour orienter la différentiation et construire un organisme structuré viable. Cette information positionnelle est acquise, transmise et conservée par la diffusion de protéines et l’activa- tion de circuits génétiques.Plus précisément, la formation de l’axe antéropostérieur chez la Drosophile est déterminée entre autres par l’activation du gène hunchback par la protéine Bicoid. Nous analysons des données issues d’expériences d’imagerie fluorescente dynamique dans les premiers cycles cellulaires de l’embryon. Nous construisons un modèle spécifique permettant d’analyser la fonction d’autocorrélation des traces temporelles de fluorescence qui prend en compte toutes les difficultés biologiques et expérimentales (bruit, calibration traces courtes, structure du gène artificiel) pour extraire les paramètre dynamiques d’activation de hunchback. Nous examinons différentes dynamiques potentielles (poisonnienne, markovienne ou non markovienne) et leur implication pour l’information dont la cellule dispose sur sa position ainsi que la précision de la lecture du gradient de Bicoid

A mechanism for hunchback promoters to readout morphogenetic positional information in less than a minute

International audienceCell fate decisions in the fly embryo are rapid: hunchback genes decide in minutes whether nuclei follow the anterior/posterior developmental blueprint by reading out positional information in the Bicoid morphogen. This developmental system is a prototype of regulatory decision processes that combine speed and accuracy. Traditional arguments based on fixed-time sampling of Bicoid concentration indicate that an accurate readout is impossible within the experimental times. This raises the general issue of how speed-accuracy tradeoffs are achieved. Here, we compare fixed-time to on-the-fly decisions, based on comparing the likelihoods of anterior/posterior locations. We found that these more efficient schemes complete reliable cell fate decisions within the short embryological timescales. We discuss the influence of promoter architectures on decision times and error rates, present concrete examples that rapidly readout the morphogen, and predictions for new experiments. Lastly, we suggest a simple mechanism for RNA production and degradation that approximates the log-likelihood function

hunchback Promoters Can Readout Morphogenetic Positional Information in Less Than a Minute

The first cell fate decisions in the developing fly embryo are made very rapidly: hunchback genes decide in a few minutes whether a given nucleus follows the anterior or the posterior developmental blueprint by reading out the positional information encoded in the Bicoid morphogen. This developmental system constitutes a prototypical instance of the broad spectrum of regulatory decision processes that combine speed and accuracy. Traditional arguments based on fixed-time sampling of Bicoid concentration indicate that an accurate readout is not possible within the short times observed experimentally. This raises the general issue of how speed-accuracy tradeoffs are achieved. Here, we compare fixed-time sampling strategies to decisions made on-the-fly, which are based on updating and comparing the likelihoods of being at an anterior or a posterior location. We found that these more efficient schemes can complete reliable cell fate decisions even within the very short embryological timescales. We discuss the influence of promoter architectures on the mean decision time and decision error rate and present concrete promoter architectures that allow for the fast readout of the morphogen. Lastly, we formulate explicit predictions for new experiments involving Bicoid mutants