Cell migration, which is regulated by intracellular signaling pathways (ICSP) and extracellular matrix (ECM), plays an indispensable role in many physiological and pathological process such as normal tissue development and cancer metastasis. However, there is a lack of rigorous and quantitative tools for analyzing the time-varying characteristics of cell migration in heterogeneous microenvironment, resulted from, e.g. the time-dependent local stiffness due to microstructural remodeling by migrating cells. Here, we develop a wavelet-analysis approach to derive the time-dependent motility parameters from cell migration trajectories, based on the time-varying persistent random walk model. In particular, the wavelet denoising and wavelet transform are employed to analyze migration velocities and obtain the wavelet power spectrum. Subsequently, the time-dependent motility parameters are derived via Lorentzian power spectrum. Our results based on synthetic data indicate the superiority of the method for estimating the intrinsic transient motility parameters, robust against a variety of stochastic noises. We also carry out a systematic parameter study and elaborate the effects of parameter selection on the performance of the method. Moreover, we demonstrate the utility of our approach via analyzing experimental data of in vitro cell migration in distinct microenvironments, including the migration of MDA-MB-231 cells in confined micro-channel arrays and correlated migration of MCF-10A cells due to ECM-mediated mechanical coupling. Our analysis shows that our approach can be as a powerful tool to accurately derive the time-dependent motility parameters, and further analyze the time-dependent characteristics of cell migration regulated by complex microenvironment.

细胞迁移受细胞内信号通路（ICSP）和细胞外基质（ECM）调控，在正常组织发育和癌症转移等许多生理和病理过程中起着不可或缺的作用。然而，缺乏严格和定量的工具来分析异质微环境中细胞迁移的时变特征，例如由于迁移细胞的微观结构重塑导致的时间依赖性局部刚度。在这里，我们开发了一种小波分析方法，基于时变持续随机游走模型，从细胞迁移轨迹中推导出与时间相关的运动参数。特别是利用小波去噪和小波变换来分析迁移速度并获得小波功率谱。随后，通过洛伦兹功率谱推导出与时间相关的运动参数。我们基于合成数据的结果表明估计固有瞬态运动参数的方法的优越性，对各种随机噪声具有鲁棒性。我们还进行了系统的参数研究，并详细阐述了参数选择对方法性能的影响。此外，我们通过分析实验数据证明了我们的方法的实用性 我们还进行了系统的参数研究，并详细阐述了参数选择对方法性能的影响。此外，我们通过分析实验数据证明了我们的方法的实用性 我们还进行了系统的参数研究，并详细阐述了参数选择对方法性能的影响。此外，我们通过分析实验数据证明了我们的方法的实用性不同微环境中的体外细胞迁移，包括 MDA-MB-231 细胞在受限微通道阵列中的迁移和由于 ECM 介导的机械耦合引起的 MCF-10A 细胞的相关迁移。我们的分析表明，我们的方法可以作为一种强大的工具来准确推导时间依赖性运动参数，并进一步分析复杂微环境调节的细胞迁移的时间依赖性特征。