Fibroblasts play an essential role in tissue repair and regeneration as they migrate to wounded areas to secrete and remodel the extracellular matrix. Fibroblasts recognize chemical substances such as growth factors, which enhance their motility towards the wounded tissues through chemotaxis. Although several studies have characterized single-cell fibroblast motility before, the migration patterns of fibroblasts in response to external factors have not been fully explored in 3D environments. We present a study that combines experimental and computational efforts to characterize the effect of chemical stimuli on the invasion of 3D collagen matrices by fibroblasts. Experimentally, we used microfluidic devices to create chemical gradients using collagen matrices of distinct densities. We evaluated how cell migration patterns were affected by the presence of growth factors and the mechanical properties of the matrix. Based on these results, we present a discrete-based computational model to simulate cell motility, which we calibrated through the quantitative comparison of experimental and computational data via Bayesian optimization. By combining these approaches, we predict that fibroblasts respond to both the presence of chemical factors and their spatial location. Furthermore, our results show that the presence of these chemical gradients could be reproduced by our computational model through increases in the magnitude of cell-generated forces and enhanced cell directionality. Although these model predictions require further experimental validation, we propose that our framework can be applied as a tool that takes advantage of experimental data to guide the calibration of models and predict which mechanisms at the cellular level may justify the experimental findings. Consequently, these new insights may also guide the design of new experiments, tailored to validate the variables of interest identified by the model.

中文翻译：

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一种新的综合实验和计算方法，用于揭示成纤维细胞运动对 3D 胶原基质中化学梯度的反应。

成纤维细胞在组织修复和再生中发挥重要作用，因为它们迁移到受伤区域以分泌和重塑细胞外基质。成纤维细胞识别生长因子等化学物质，这些物质通过趋化作用增强它们对受伤组织的运动能力。尽管之前有几项研究已经对单细胞成纤维细胞运动进行了表征，但尚未在 3D 环境中充分探索成纤维细胞响应外部因素的迁移模式。我们提出了一项结合实验和计算工作的研究，以描述化学刺激对成纤维细胞侵入 3D 胶原基质的影响。在实验上，我们使用微流体装置使用不同密度的胶原蛋白基质创建化学梯度。我们评估了细胞迁移模式如何受生长因子的存在和基质的机械特性的影响。基于这些结果，我们提出了一个基于离散的计算模型来模拟细胞运动，我们通过贝叶斯优化对实验数据和计算数据进行定量比较对其进行了校准。通过结合这些方法，我们预测成纤维细胞对化学因素的存在及其空间位置都有反应。此外，我们的结果表明，这些化学梯度的存在可以通过我们的计算模型通过增加细胞产生的力的大小和增强的细胞方向性来再现。尽管这些模型预测需要进一步的实验验证，我们建议我们的框架可以用作一种工具，利用实验数据来指导模型的校准，并预测细胞水平上的哪些机制可以证明实验结果的合理性。因此，这些新见解也可能会指导新实验的设计，专门用于验证模型确定的感兴趣变量。