Biology subjects

Starruss, J.

Publications and source records attributed to Starruss, J..

6 recordsLinked to original sources

bioRxiv2026

Decoupling T Cell Cytotoxicity: A CCL21+ICAM1-Based Synthetic Immune Niche Enhances Tumor Elimination by Accelerating Lytic Hit Delivery

Preserving T cell cytotoxic function during ex vivo expansion remains a major challenge for adoptive cancer immunotherapy. A synthetic immune niche (SIN) composed of immobilized CCL21 and ICAM1 was shown to improve T cell expansion while preserving cytotoxicity; however, it remains unclear which specific step of the T cell killing process is enhanced by the SIN stimulation. Here, we combined advanced imaging based on time-lapse microscopy with a mean-field model to analyze the distinct stages in killing of B16 melanoma cells by CD8+ T cells. This framework enabled us to resolve the tumor cell killing process into discrete steps throughout target cell engagement with SIN-treated T cells and lytic hit delivery. We found that tumor cell death is best explained by a multi-hit process, requiring approximately four discrete hits to trigger cell death. Model-based analysis identified an increase in the lytic hit delivery as the parameter that best accounts for the enhanced cytotoxicity of SIN-treated T cells, a difference not explained by changes in target encounter frequency or conjugate stability. Global sensitivity analysis further showed that tumor control is more strongly improved by enhancing lytic hit delivery than by increasing target encounter rates. These findings fundamentally reorient our understanding of optimized T cell manufacturing, suggesting that the lytic execution step may be the primary rate-limiting bottleneck in this in-vitro system, and that engineering strategies targeting granule polarization or discharge warrant prioritization alongside affinity-enhancement approaches.

immunology↗

bioRxiv2023

Collective cell migration due to guidance-by-followers is robust to multiple stimuli

Collective cell migration is an important process during biological development and tissue repair, but may turn malignant during tumor invasion. Mathematical and computational models are essential to unravel the mechanisms of self-organization that underlie the emergence of collective migration from the interactions among individual cells. Recently, guidance-by-followers was identified as one such underlying mechanism of collective cell migration in the zebrafish embryo. This poses the question how guidance stimuli are integrated when multiple cells interact simultaneously. Here, we extend a recent individual-based model by an integration step of the vectorial guidance stimuli and compare model predictions obtained for various variants of the mechanism (arithmetic mean of stimuli, dominance of stimulus with largest transmission interface, dominance of most head-on stimulus). Simulations are carried out and quantified within the modeling and simulation framework Morpheus. Collective cell migration is sfound to be robust and qualitatively identical for all considered variants of stimulus integration. Moreover, this study highlights the role of individual-based modeling approaches for understanding collective phenomena at the population scale that emerge from cell-cell interactions.

developmental biology↗

bioRxiv2023

FitMultiCell: Simulating and parameterizing computational models of multi-scale and multi-cellular processes

MotivationBiological tissues are dynamic and highly organized. Multi-scale models are helpful tools to analyze and understand the processes determining tissue dynamics. These models usually depend on parameters that need to be inferred from experimental data to achieve a quantitative understanding, to predict the response to perturbations, and to evaluate competing hypotheses. However, even advanced inference approaches such as Approximate Bayesian Computation (ABC) are difficult to apply due to the computational complexity of the simulation of multi-scale models. Thus, there is a need for a scalable pipeline for modeling, simulating, and parameterizing multi-scale models of multi-cellular processes. ResultsHere, we present FitMultiCell, a computationally efficient and user-friendly open-source pipeline that can handle the full workflow of modeling, simulating, and parameterizing for multi-scale models of multi-cellular processes. The pipeline is modular and integrates the modeling and simulation tool Morpheus and the statistical inference tool pyABC. The easy integration of high-performance infrastructure allows to scale to computationally expensive problems. The introduction of a novel standard for the formulation of parameter inference problems for multi-scale models additionally ensures reproducibility and reusability. By applying the pipeline to multiple biological problems, we demonstrate its broad applicability, which will benefit in particular image-based systems biology. AvailabilityFitMultiCell is available open-source at https://gitlab.com/fitmulticell/fit. Contactjan.hasenauer@uni-bonn.de Supplementary informationSupplementary data are available at https://doi.org/10.5281/zenodo.7646287 online.

systems biology↗

bioRxiv2022

Inferring cell motility in complex environments with incomplete tracking data

Cell motility has important influence on cell interactions and functionality for various biological aspects. Deciphering these dynamics often relies on live-cell microscopy measurements, which partly have to deal with limitations that could impair a reliable quantification of their motility. Especially given complex environments and tissue structures, limited observation periods, cells moving in and out of focus and impaired calibration of observation axes often lead to loss of cell tracks and insufficient tracking of motility within several dimensions. However, a reliable quantification of cell motility dynamics is essential when aiming at extrapolating the observed dynamics in order to understand cell population dynamics at larger temporal and spatial scales using appropriate simulation environments. To analyze how incomplete observations affect interpretation and parameterization of cell motility, we combined experimental observations with computational models. Studying individual cell dynamics within 3D collagen environments, we found that the gradual loss of cell tracks leads to an underestimation of several motility parameters with the effect dependent on the collagen density. By extending the automated fitting strategy FitMultiCell to account for cell track loss, we show that we are able to retrieve the actual cell dynamics and, thus, to reliably parameterize cell motility from such incomplete data. Applying our approach to the analysis of CD4+ T cells within 3D collagen environments that were infected with HIV-1, we could show that despite a considerable loss of cell tracks, the data still contained sufficient information to compare individual cell motilities by inferring and simulating their dynamics. Thereby, the analysis allowed us to disentangle the effect of HIV-1 infection and collagen density on individual cell motility. Our extended FitMultiCell-approach presented here provides a solution for the elimination of artifacts from cell track data analysis to robustly infer cell motility dynamics.

systems biology↗

bioRxiv2021

Guidance by followers ensures long-range coordination of cell migration through α-Catenin mechanoperception

Morphogenesis, wound healing and some cancer metastases depend upon migration of cell collectives that need to be guided to their destination as well as coordinated with other cell movements. During zebrafish gastrulation, extension of the embryonic axis is led by the mesendodermal polster that migrates towards the animal pole, followed by axial mesoderm that undergoes convergence and extension. We here investigate how polster cells are guided towards the animal pole. Using a combination of precise laser ablations, advanced transplants and functional as well as in silico approaches, we establish that each polster cell is oriented by its immediate follower cells. Each cell perceives the migration of followers, through E-Cadherin/-Catenin mechanotransduction, and aligns with them. Directional information therefore propagates from cell to cell over the whole tissue. Such guidance of migrating cells by followers ensures long-range coordination of movements and developmental robustness.

developmental biology↗

bioRxiv2021

Locally confined IFNγ production by CD4+ T cells provides niches for murine cytomegalovirus replication in the salivary gland

Cytomegalovirus (CMV) has evolved a unique virus-host relationship in the salivary glands (SGs) to sustain prolonged viral replication and hence chances for horizontal transmission. Previous reports have established a decisive role for IFN{gamma} producing CD4+ T cells to control murine CMV (MCMV) infection in the SGs; however, micro-anatomical information regarding their mode of action is largely missing. Here, we provide a spatiotemporal analysis of defined antiviral immune actions that eventually culminate in control of lytic MCMV replication in this preferred mucosal niche. CXCR3-mediated guidance of CD4+ T cells towards CXCL9 and CXCL10 expressing cells resulted in discrete clusters close to infection foci where they reported TCR engagement and produced IFN{gamma}. Of note, these clusters occasionally contained CD11c+ antigen-presenting cells with engulfed virus-associated remnants, most likely apoptotic bodies derived from previously infected cells, enabling antigen presentation to CD4+ T cells. The induced IFN{gamma} production within these CD4+ T cell accumulations triggered IFN{gamma}R signaling in a confined perimeter, thereby inducing local, but not organ-wide protection, and allowing MCMV replication to continue at not yet protected sites. Combining experimental data with a mathematical model of the spatiotemporal dynamics of infection and CD4+ T cell dynamics revealed a scenario, in which ultimate MCMV control is achieved through accumulating sites of regionally-confined tissue protection.

immunology↗