A novel integrated experimental and computational approach to unravel fibroblast motility in response to chemical gradients in 3D collagen matrices.

IF 1.5 4区 生物学 Q4 CELL BIOLOGY Integrative Biology Pub Date : 2022-12-30 DOI:10.1093/intbio/zyad002
Nieves Movilla, Inês G Gonçalves, Carlos Borau, Jose Manuel García-Aznar
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引用次数: 2

Abstract

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.

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一种新的综合实验和计算方法来解开成纤维细胞对三维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起着至关重要的作用,因为它们迁移到损伤区域分泌和重塑细胞外基质。成纤维细胞能识别生长因子等化学物质,通过趋化性增强其向损伤组织的运动性。虽然之前有一些研究描述了单细胞成纤维细胞的运动,但成纤维细胞响应外部因素的迁移模式尚未在3D环境中得到充分探索。我们提出了一项结合实验和计算的研究,以表征化学刺激对成纤维细胞侵入3D胶原基质的影响。实验中,我们使用微流控装置利用不同密度的胶原蛋白基质产生化学梯度。我们评估了细胞迁移模式如何受到生长因子和基质机械性能的影响。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和计算数据的定量比较来校准该模型。通过结合这些方法,我们预测成纤维细胞对化学因素及其空间位置的存在都有反应。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。虽然这些模型预测需要进一步的实验验证,但我们认为我们的框架可以作为一种工具,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。因此,这些新的见解也可以指导新实验的设计,以验证模型确定的感兴趣的变量。
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来源期刊
Integrative Biology
Integrative Biology 生物-细胞生物学
CiteScore
4.90
自引率
0.00%
发文量
15
审稿时长
1 months
期刊介绍: Integrative Biology publishes original biological research based on innovative experimental and theoretical methodologies that answer biological questions. The journal is multi- and inter-disciplinary, calling upon expertise and technologies from the physical sciences, engineering, computation, imaging, and mathematics to address critical questions in biological systems. Research using experimental or computational quantitative technologies to characterise biological systems at the molecular, cellular, tissue and population levels is welcomed. Of particular interest are submissions contributing to quantitative understanding of how component properties at one level in the dimensional scale (nano to micro) determine system behaviour at a higher level of complexity. Studies of synthetic systems, whether used to elucidate fundamental principles of biological function or as the basis for novel applications are also of interest.
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