SearcharxivSearch

arXiv · 1003.1415

Affinity Discrimination in B cells in Response to Membrane Antigen Requires Kinetic Proofreading

Abstract

B cells signaling in response to antigen is proportional to antigen affinity, a process known as affinity discrimination. Recent research suggests that B cells can acquire antigen in membrane-bound form on the surface of antigen-presenting cells (APCs), with signaling being initiated within a few seconds of B cell/APC contact. During the earliest stages of B cell/APC contact, B cell receptors (BCRs) on protrusions of the B cell surface bind to antigen on the APC surface and form micro-clusters of 10-100 BCR/Antigen complexes. In this study, we use computational modeling to show that B cell affinity discrimination at the level of BCR-antigen micro-clusters requires a threshold antigen binding time, in a manner similar to kinetic proofreading. We find that if BCR molecules become signaling-capable immediately upon binding antigen, there is a loss in serial engagement due to the increase in bond lifetime as koff decreases. This results in decreasing signaling strength as affinity increases. A threshold time for antigen to stay bound to BCR before the latter becomes signaling-capable favors high affinity BCR-antigen bonds, as these long-lived bonds can better fulfill the threshold time requirement than low-affinity bonds. A threshold antigen binding time of ~10 seconds results in monotonically increasing signaling with affinity, replicating the affinity discrimination pattern observed in B cell activation experiments. This time matches well (within order of magnitude) with the experimentally observed time (~ 20 seconds) required for the BCR signaling domains to undergo antigen and lipid raft-mediated conformational changes that lead to association with Syk.

Explore related subjects

Keep this discovery

BibTeXRIS

Philippos K. Tsourkas, Subhadip Raychaudhuri. 2010-03-06. Affinity Discrimination in B cells in Response to Membrane Antigen Requires Kinetic Proofreading. https://arxiv.org/abs/1003.1415

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Modeling Tissue Detachment and Rupture Using an Extended Vertex Model with T2-inverse Transitions

The vertex model is widely used to describe the mechanics of epithelial tissues, but its conventional formulation assumes that all cells remain tightly packed and always share edges with their neighbors, making it difficult to represent local detachment or gap formation. Here, we propose a minimal extension of the vertex model that enables cell detachment by introducing a new topological transformation, T2-inverse, which acts as the inverse of the classical T2 transition. When the imbalance of forces acting on a vertex, quantified by a tension metric $T$, exceeds a threshold, the T2-inverse splits the vertex into multiple vertices and creates a closed polygon that is incorporated as a pseudo-cell. This operation allows the model to represent the emergence and propagation of local detachment events. Using this framework, we simulate the stretching of a cell sheet and show that force-induced local detachments can accumulate to produce macroscopic tissue rupture. These results demonstrate that the proposed model extends the capability of the vertex model to describe tissue-level breakdown processes, including detachment and tearing, and provides a foundation for studying a broader class of epithelial mechanical phenomena.

q-bio.CB

3D hybrid cellular Potts model with a discrete deformable fiber network: modeling cell contraction and extracellular matrix remodeling

The extracellular matrix (ECM) is a fibrous and dynamic network that plays a critical role in development, homeostasis, and disease. Cells both respond to and remodel the ECM, engaging in a mechanical reciprocity that shapes tissues. To study these interactions, computational models have been developed that simulate either ECM mechanics or cell behavior. The Cellular Potts Model (CPM) is a flexible cell-based framework that has been extended to many biological processes, including coupling to a discrete deformable fiber network. So far, however, this extension has only been applied in two dimensions, even though a three-dimensional setting is biologically more relevant. Here, we present a 3D hybrid framework that couples the CPM with a discrete and deformable representation of the ECM. This model enables explicit simulation of cell-induced ECM remodeling, including fiber reorientation and matrix densification. By incorporating contractile forces through static adhesion points, the model captures how ECM elasticity and fiber stiffness influences cell shape. The simulations show that ECM stiffness, controlled by fiber crosslinking, resists contraction and reaches equilibrium, while crosslink density modulates fiber alignment and local matrix accumulation. This framework provides a versatile platform for studying cell-ECM mechanics and supports future studies of multicellular behavior in realistic 3D environments.

q-bio.CB

Coarse-Graining Agent-Based Models of Bacterial Infections

Agent-based models (ABMs) provide a natural framework for representing cell-level rules and spatial heterogeneity in bacterial infections, but their computational cost limits their use for macroscopic tissue-scale simulations and broad parameter exploration. We derive a deterministic coarse-grained description for a class of bacterial-infection ABMs in which immune cells and extracellular bacteria diffuse, immune cells ingest nearby bacteria, and intracellular bacterial loads evolve through prescribed birth and clearance processes. The first coarse-grained model is a semidiscrete reaction--diffusion system that retains a discrete internal state for each immune-cell bacterial load while representing cell and bacterial populations by continuum concentration fields. The key technical step is the derivation of state-dependent effective ingestion rates from the microscopic ABM parameters: these rates are obtained by solving an auxiliary diffusion problem around a single bacterium and computing the flux of immune cells into the interaction region. We then take a continuum limit in the internal state variable, yielding a state-structured reaction--diffusion system in which intracellular dynamics appear as advection and diffusion in state space. Numerical comparisons with ensemble-averaged ABM simulations show close agreement in biologically motivated parameter regimes. The resulting framework preserves the rule-based structure of the ABM while producing PDE models that are substantially more tractable for large-scale simulation and parameter studies.

q-bio.CB