Biology subjects

Dupre, L.

Publications and source records attributed to Dupre, L..

4 recordsLinked to original sources

bioRxiv2024

Deconstructing CTL-mediated autoimmunity through weak TCR-cross-reactivity towards highly abundant self-antigen

T-cell antigen receptors (TCRs) exhibit inherent cross-reactivity which broadens the spectrum of epitopes that are recognizable by a finite TCR-repertoire but also carries the risk of autoimmunity. However, TCRs support also a high level of antigen specificity as they allow T-cells to discriminate single antigenic peptide/MHC complexes (pMHCs) against millions of structurally related self-pMHCs, in some cases based on the absence or presence of a single methyl-group. How TCRs manage to convey such seemingly contrary properties and why some T-cells become over time autoreactive despite negative thymic selection, has remained elusive. Here, we devised a non-invasive molecular live cell imaging platform to investigate the biophysical parameters governing stimulatory TCR:pMHC interactions in settings of autoreactivity and anti-viral responses - two extremes in T-cell antigen recognition. We show that CMV-specific CD8+ RA14-T-cells respond effectively to even a single HLA-A2/CMV (A2/CMV) antigen, with synaptic TCR:pMHC lifetimes lasting seconds. In contrast, cross-reactivity of type 1 diabetes (T1D)-associated CD8+ 1E6 T-cells towards HLA-A2/preproinsulin (A2/PPI) self-epitopes involved ten-fold less stable synaptic TCR interactions resulting in severely attenuated ZAP70 recruitment and downstream signaling. Compared to A2/CMV-engaged RA14 T-cells, 1E6-T-cells required for activation 4000 or more A2/PPI and at least 100-times as many simultaneously pMHC-engaged TCRs. In support of antigen discrimination, CD8 co-engagement of MHC class I (MHCI) strengthened both settings of TCR:pMHC interactions equally but was essential only for sensitized virus detection but not autorecognition (1000-versus 5-fold enhancement). We conclude that the binding dynamics of TCRs and CD8 with pMHC shape the boundaries of central tolerance in the physiological context of the phenomenal yet also differential T-cell antigen detection capacity, TCR-cross-reactivity and self-antigen abundance. Gained insights are integral to a molecular and quantitative understanding of CD8+ T-cell mediated autoimmunity and protective immunity against infections and cancer. ONE SENTENCE SUMMARYWith the use of newly devised molecular live-cell imaging modalities we measured with unprecedented precision T-cell antigen recognition dynamics in human T-cells in settings of anti-viral immunity and autoimmunity-causing cross-reactivity. These two extremes within the spectrum of T-cell antigen detection differed substantially with regard to synaptic TCR: antigen-engagement, the level of sensitization through the CD8-coreceptor and the overall efficiency of ensuing downstream signaling. Our results demarcate limits of central tolerance and protective immunity and set quantitative boundaries on the occurrence of autoimmunity with direct implications for T-cell-based designs of immunotherapies.

immunology↗

bioRxiv2021

BioProfiling.jl: Profiling biological perturbations with high-content imaging in single cells and heterogeneous populations

MotivationHigh-content imaging screens provide a cost-effective and scalable way to assess cell states across diverse experimental conditions. The analysis of the acquired microscopy images involves assembling and curating morphological measurements of individual cells into morphological profiles suitable for testing biological hypotheses. Despite being a critical step, there is currently no standard approach to morphological profiling and no solution is available for the high-performance Julia programming language. ResultsHere, we introduce BioProfiling.jl, an efficient end-to-end solution for compiling and filtering informative morphological profiles in Julia. The package contains all the necessary data structures to curate morphological measurements and helper functions to transform, normalize and visualize profiles. Robust statistical distances and permutation tests enable quantification of the significance of the observed changes despite the high fraction of outliers inherent to high-content screens. This package also simplifies visual artifact diagnostics, thus streamlining a bottleneck of morphological analyses. We showcase the features of the package by analyzing a chemical imaging screen, in which the morphological profiles prove to be informative about the compounds mechanisms of action and can be conveniently integrated with the network localization of molecular targets. AvailabilityThe Julia package is available on GitHub: https://github.com/menchelab/BioProfiling.jl We also provide Jupyter notebooks reproducing our analyses: https://github.com/menchelab/BioProfilingNotebooks Contactjoerg.menche@univie.ac.at

bioinformatics↗

bioRxiv2021

Computational modelling of cell motility modes emerging from cell-matrix adhesion dynamics

Lymphocytes have been described to perform different motility patterns such as Brownian random walks, persistent random walks, and Levy walks. Depending on the conditions, such as confinement or the distribution of target cells, either Brownian or Levy walks lead to more efficient interaction with the targets. The diversity of these motility patterns may be explained by an adaptive response to the surrounding extracellular matrix (ECM). Indeed, depending on the ECM composition, lymphocytes either display a floating motion without attaching to the ECM, or sliding and stepping motion with respectively continuous or discontinuous attachment to the ECM, or pivoting behaviour with sustained attachment to the ECM. Moreover, on the long term, lymphocytes either perform a persistent random walk or a Brownian-like movement depending on the ECM composition. How the ECM affects cell motility is still incompletely understood. Here, we integrate essential mechanistic details of the lymphocyte-matrix adhesions and lymphocyte intrinsic cytoskeletal induced cell propulsion into a Cellular Potts model (CPM). We show that the combination of de novo cell-matrix adhesion formation, adhesion growth and shrinkage, adhesion rupture, and feedback of adhesions onto cell propulsion recapitulates multiple lymphocyte behaviours, for different lymphocyte subsets and various substrates. With an increasing attachment area and increased adhesion strength, the cells speed and persistence decreases. Additionally, the model can predict short-term persistent with long-term subdiffusive motility, showing a pivoting motion. For small adhesion areas, we observe that the spatial distribution of adhesions influences cell motility. Small adhesions at the front allow for more persistent motion than larger clusters at the back, despite a similar total adhesion area. In conclusion, we present an integrated framework to simulate the effects of ECM proteins on cell-matrix adhesion dynamics. The model reveals a sufficient set of principles explaining the plasticity of lymphocyte motility. Author summaryDuring immunosurveillance, lymphocytes patrol through tissues to interact with cancer cells, other immune cells, and pathogens. The efficiency of this process depends on the kinds of trajectories taken, ranging from simple Brownian walks to Levy walks. The composition of the extracellular matrix (ECM), a network of macromolecules, affects the formation of cell-matrix adhesions, thus strongly influencing the way lymphocytes move. Here, we present a model of lymphocyte motility driven by adhesions that grow, shrink and rupture in response to the ECM and cellular forces. Compared to other models, our model is computationally light making it suitable for generating long term cell track data, while still capturing actin dynamics and adhesion turnover. Our model suggests that cell motility is affected by the force required to break adhesions and the rate at which new adhesions form. Adhesions can promote cell protrusion by inhibiting retrograde actin flow. After introducing this effect into the model, we found that it reduces the cellular diffusivity and that it promotes stick-slip behaviour. Furthermore, location and size of adhesion clusters determined cell persistence. Overall, our model explains the plasticity of lymphocyte behaviour in response to the ECM.

cell biology↗

bioRxiv2020

Morphological profiling of human T and NK lymphocytes identifies actin-mediated control of the immunological synapse

The detection and neutralization of infected cells and tumors by cytotoxic lymphocytes is a vital immune defense mechanism. The immunological synapse orchestrates the target recognition process and the subsequent cytotoxic activity. Here, we present an integrated experimental and computational strategy to systematically characterize the morphological properties of the immunological synapse of human cytotoxic lymphocytes. Our approach combines high-content imaging with an unbiased, data-driven identification of high-resolution morphological profiles. Such profiling discriminates with high accuracy immunological synapse perturbations induced by an array of actin drugs in both model cell lines and primary lymphocytes. It reveals inter-individual heterogeneity in lymphocyte morphological traits. Furthermore, it uncovers immunological synapse alterations in functionally defective CD8+ T cells from immunodeficient patients carrying ARPC1B mutations. Our study thus provides a foundation for the application of morphological profiling as a powerful and scalable approach to monitor lymphocyte activation status in experimental and disease settings.

immunology↗