Biology subjects

Altan-Bonnet, G.

Publications and source records attributed to Altan-Bonnet, G..

11 recordsLinked to original sources

bioRxiv2026

A capture assay to analyse immunoglobulin secretion at the single-cell level

Several secretion capture assays have been developed to measure a secreted protein of interest, using paired monoclonal antibodies of different specificities that bind simultaneously to a cell surface antigen and to the secreted protein of interest. Here we have developed a novel method to measure antibody secretion on B cells, which, by capitalising on the bivalent nature of an antibody molecule, utilises an anti-immunoglobulin (Ig) antibody to bind on one side to the membrane-bound Ig (in the B cell receptor), and then capture any secreted Ig with the second binding site. Binding of the secreted cargo is then detected through a second application of anti-Ig, this time fluorophore-labelled. We demonstrate that this can effectively measure single cell Ig secretion in a population of B cells undergoing differentiation to plasma cells. This offers a reliable and accessible tool for quantifying antibody secretion dynamics at the single-cell level with potential applications in immunological studies, antibody discovery and functional profiling of B cell responses.

immunology↗

bioRxiv2025

Design principles of the cytotoxic CD8+ T-cell response

Cytotoxic T lymphocytes eliminate infected or malignant cells, safeguarding surrounding tissues. Although experimental and systems-immunology studies have cataloged many molecular and cellular actors involved in an immune response, the design principles governing how the speed and magnitude of T-cell responses emerge from cellular decision-making remain elusive. Here, we recast the T-cell response as a feedback-controlled program, wherein the rates of activation, proliferation, differentiation and death are regulated through antigenic, pro- and anti-inflammatory cues. By exploring a broad class of feedback-controller designs as potential immune programs, we demonstrate how the speed and magnitude of T-cell responses emerge from optimizing signal-feedback to protect against diverse infection settings. We recover an inherent trade-off: infection clearance at the cost of immunopathology. We show how this trade-off is encoded into the logic of T-cell responses by hierarchical sensitivity to different immune signals. Notably, we find that designs that balance harm from acute infections and autoimmunity produce immune responses consistent with experimentally observed patterns of T-cell effector expansion in mice. Extending our model to immune-based T-cell therapies for cancer tumors, we identify a trade-off between the affinity for tumor antigens ("quality") and the abundance ("quantity") of infused T-cells necessary for effective treatment. Finally, we show how therapeutic efficacy can be improved by targeted genetic perturbations to T-cells. Our findings offer a unified control-logic for cytotoxic T-cell responses and point to specific regulatory programs that can be engineered for more robust T-cell therapies.

immunology↗

bioRxiv2025

Dynamical model and geometric insights in the discontinuity theory of immunity

The immune systems most basic task is to decide what is "self" and "non-self", but a precise definition of self versus non-self remains challenging. According to the discontinuity theory of immunity, effector responses depend on how quickly an antigenic stimulus changes: rapid change triggers an immune response, whereas gradual change fosters tolerance. We present a model of adaptive immune dynamics including T cells, Tregs and cytokines that reproduces the hallmarks of the discontinuity theory. The model allows for sharp discrimination between acute and chronic infections based on the growth rate of the immune challenge, and vaccination-like acute dynamics upon presentation of a bolus of immune challenge. We further show that the model behavior only depends on a handful of testable assumptions that we map to geometric constraints in phase space. This suggests that the model properties are generic and robust across alternative mechanistic details. We also examine the impact of multiple concurrent immune challenges in this model, and demonstrate the occurrence of dynamical antagonism, wherein, in some parameter regimes, slow-growing challenges hinder acute responses to fast-growing ones, with further counter-intuitive behaviors for sequential co-infections. Together, these results place the discontinuity theory on firm mathematical footing and encourage further investigation of interferences of multi-agent immune challenges, from chronic viral co-infections to cancer immunoediting.

systems biology↗

bioRxiv2024

Chaotic dynamics for homeostatic hematopoiesis

Homeostatic hematopoiesis is a dynamical process, characterized by large variations (e.g., with coefficients of variation larger than 1) of cell quantities, cell proliferation rates, and extensive correlations/anticorrelations between cell types within the myeloid/lymphoid lineage, and between lineages. All cell types exhibit rare but synchronized bursts of proliferation in the bone marrow, blood and spleen. Through longitudinal study of the blood contents of healthy mice, we found that leukocyte fluctuations are ergodic yet subject to chaotic behaviors characterized by a broad spectrum of characteristic timescales. We then built a minimal mathematical model to capture these dynamical features of hematopoiesis (fluctuations, correlations, and chaos) and explain how the accumulation of B cells (e.g. during lymphoma development) would transition the blood cell dynamics from chaos to oscillations as observed clinically. Finally, we demonstrated the ubiquity of the correlated blood cell fluctuations by comparing mouse cohorts of different genetic backgrounds and ages.

immunology↗

bioRxiv2022

Apoptotic contraction drives target cell release by cytotoxic T cells

Cytotoxic T lymphocytes (CTLs) use immune synapses to destroy infected or transformed target cells. Although the mechanisms governing synapse assembly have been studied extensively, little is known about how this interface dissociates, which is a critical step that both frees the CTL to search for additional prey and enables the phagocytosis of target corpses. Here, we applied time-lapse imaging to explore the basis for synapse dissolution and found that it occurred concomitantly with the cytoskeletal contraction of apoptotic targets. Genetic and pharmacological disruption of apoptotic contraction indicated that it was necessary for CTL dissociation. Furthermore, acute stimulation of contractile forces triggered the release of live targets, demonstrating that contraction is sufficient to drive the response. Finally, mechanically amplifying apoptotic contractility promoted faster CTL detachment and serial killing. Collectively, these results establish a biophysical basis for synapse dissolution and highlight the importance of mechanosensory feedback in the regulation of cell-cell interactions.

immunology↗

bioRxiv2022

Tuning of cytokine signaling through imbalanced abundances of receptors and kinases

Cells use surface receptors to detect extra-cellular ligands (e.g., growth factors or cytokines) and engender signaling cascades. We explore the effect of cell-to-cell variability in receptor subunit copy number for cells responding to{gamma} c cytokines (e.g., IL-2, IL-7 and IL-15). We find that primary T cells expressing higher levels of the common{gamma} c receptor chain have weaker responses to IL-7, both in terms of lowered STAT5 phosphorylation amplitude and higher EC50. A mathematical model that accounts for abundance imbalance (e.g., insufficient expression of JAK kinases compared to the number of receptors, or{gamma} c competition for other receptor subunit chains) predicts the formation of non-signalling complexes, consistent with the observed cellular behaviour. This type of built-in limit on signaling responses illustrates how phenotypic heterogeneity generates biological functional diversity. Significance StatementCells rely on cytokines to coordinate their activation, differentiation, proliferation and survival. In particular,{gamma} c cytokines (interleukins IL-2, 4, 7, 9, 15, and 21) regulate the fate of leukocytes. The signaling cascade induced by these cytokines is relatively simple, and involves the phosphorylation of receptor-associated Janus-like kinases (JAK). Here, we explore the cell-to-cell variability of cytokine responses in primary mouse T cells, and find a paradoxical and quantitative imprint of receptor expression levels and other signaling components. For instance, high abundance of the common{gamma} c chain reduces cytokine responses (both in terms of signaling amplitudes and characteristic cytokine concentrations triggering 50% of the response). We develop mathematical models to quantify how limited abundances of signaling components (e.g., JAK or other cytokine receptor subunit chains) may explain our experimental observations. We conclude by generalizing this observation of cell-to-cell signaling variability to other ligand-receptor-kinase systems.

systems biology↗

bioRxiv2021

T cell receptor and IL-2 signaling strength control memory CD8+ T cell functional fitness via chromatin remodeling

Cognate antigen signal controls CD8+ T cell priming, expansion size and effector versus memory cell fates, but it is not known if and how it modulates the functional features of memory CD8+ T cells. Here we show that the strength of T cell receptor (TCR) signaling determines the requirement for interleukin-2 (IL-2) signals to form a pool of memory CD8+ T cells that competitively re-expand upon secondary antigen encounter. Combining strong TCR and intact IL-2 signaling synergistically induces genome-wide chromatin accessibility in regions targeting a wide breadth of biological processes, consistent with their greater functional fitness. Chromatin accessibility in promoters of genes encoding for stem cell, cell cycle and calcium-related proteins correlated with faster intracellular calcium accumulation, initiation of cell cycle and more robust expansion. High-dimensional flow-cytometry analysis also highlights higher subset diversity and phenotypes. These results formally establish that epitope selection in vaccine design strongly impacts memory CD8+ T cell epigenetic programming and functions. One Sentence SummaryThe strength of antigenic and interleukin 2 signals received by CD8+ T cells during vaccination epigenetically programs their ability to form functional memory.

immunology↗

bioRxiv2021

Scalable Clustering with Supervised Linkage Methods

Data clustering plays a significant role in biomedical sciences, particularly in single-cell data analysis. Researchers use clustering algorithms to group individual cells into populations that can be evaluated across different levels of disease progression, drug response, and other clinical statuses. In many cases, multiple sets of clusters must be generated to assess varying levels of cluster specificity. For example, there are many subtypes of leukocytes (e.g. T cells), whose individual preponderance and phenotype must be assessed for statistical/functional significance. In this report, we introduce a novel hierarchical density clustering algorithm (HAL-x) that uses supervised linkage methods to build a cluster hierarchy on raw single-cell data. With this new approach, HAL-x can quickly predict multiple sets of labels for immense datasets, achieving a considerable improvement in computational efficiency on large datasets compared to existing methods. We also show that cell clusters generated by HAL-x yield near-perfect F1-scores when classifying different clinical statuses based on single-cell profiles. Our hierarchical density clustering algorithm achieves high accuracy in single cell classification in a scalable, tunable and rapid manner. We make HAL-x publicly available at: https://pypi.org/project/hal-x/

bioinformatics↗

bioRxiv2019

Quantitative Immunology for Physicists

The adaptive immune system is a dynamical, self-organized multiscale system that protects vertebrates from both pathogens and internal irregularities, such as tumours. For these reason it fascinates physicists, yet the multitude of different cells, molecules and sub-systems is often also petrifying. Despite this complexity, as experiments on different scales of the adaptive immune system become more quantitative, many physicists have made both theoretical and experimental contributions that help predict the behaviour of ensembles of cells and molecules that participate in an immune response. Here we review some recent contributions with an emphasis on quantitative questions and methodologies. We also provide a more general methods section that presents some of the wide array of theoretical tools used in the field.

immunology↗

bioRxiv2019

Quantifying the dynamics of hematopoiesis by in vivo IdU pulse-chase, mass cytometry and mathematical modeling

We present a new method to directly quantify the dynamics of differentiation of multiple cellular subsets in unperturbed mice. We combine a pulse-chase protocol of IdU injections with subsequent analysis by mass cytometry (CyTOF), and mathematical modeling of the IdU dynamics. Measurements by CyTOF allow for a wide range of cells to be analyzed at once, due to the availability of a large staining panel without the complication of fluorescence spill-over. These are also compatible with direct detection of integrated iodine signal, with minimal impact on immunophenotyping based on surface markers. Mathematical modeling beyond a binary classification of surface marker abundance allows for a continuum of cellular states as the cells transition from one state to another. Thus, we present a complete and robust method for directly quantifying differentiation at the systemic level, allowing for system-wide comparisons between different mouse strains and/or experimental conditions.

immunology↗

bioRxiv2017

Modeling of cytometry data in logarithmic space: when is a bimodal distribution not bimodal?

Recent efforts in systems immunology lead researchers to build quantitative models of cell activation and differentiation. One goal is to account for the distributions of proteins from single-cell measurements by flow cytometry or mass cytometry as a readout of biological regulation. In that context, large cell-to-cell variability is often observed in biological quantities. We show here that these readouts, viewed in logarithmic scale may result in two easily-distinguishable modes, while the underlying distribution (in linear scale) is unimodal. We introduce a simple mathematical test to highlight this mismatch. We then dissect the flow of influence of cell-to-cell variability proposing a graphical model which motivates higher-dimensional analysis of the data. Finally we show how acquiring additional biological information can be used to reduce uncertainty introduced by cell-to-cell variability, helping to clarify whether the data is uni- or bimodal. This communication has cautionary implications for manual and automatic gating strategies, as well as clustering and modeling of single-cell measurements.

immunology↗