Distinct relaxation timescales of neurites revealed by rate-dependent indentation, relaxation and micro-rheology tests. Issue 2 (13th November 2018)

• Record Type: Journal Article
• Authors: Gong, Ze; Fang, Chao; You, Ran; Shao, Xueying; Wei, Xi; Chang, Raymond Chuen-Chung; Lin, Yuan
• Is Part Of: Soft matter. Volume 15:Issue 2(2018)
• Page Start: 166
• Page End: 174
• Publication Date: 2018-11-13
• Subjects: Soft condensed matter -- Periodicals; 530.413
• DOI: 10.1039/c8sm01747f
• Languages: English
• ISSNs: 1744-683X

Abstract

Abstract : Although the dynamic response of neurites is believed to play crucial roles in processes like axon outgrowth and formation of the neural network, the dynamic mechanical properties of such protrusions remain poorly understood. Abstract : Although the dynamic response of neurites is believed to play crucial roles in processes like axon outgrowth and formation of the neural network, the dynamic mechanical properties of such protrusions remain poorly understood. In this study, by using AFM (atomic force microscopy) indentation, we systematically examined the dynamic behavior of well-developed neurites on primary neurons under different loading modes (step loading, oscillating loading and ramp loading). Interestingly, the response was found to be strongly rate-dependent, with an apparent initial and long-term elastic modulus around 800 and 80 Pa, respectively. To better analyze the measurement data and extract information of key interest, the finite element simulation method (FEM) was also conducted where the neurite was treated as a viscoelastic solid consisting of multiple characteristic relaxation times. It was found that a minimum of three relaxation timescales, i.e. ∼0.01, 0.1 and 1 seconds, are needed to explain the observed relaxation curve as well as fit simulation results to the indentation and rheology data under different loading rates and driving frequencies. We further demonstrated that these three characteristic relaxation times likely originate from the thermal fluctuations of the microtubule, membrane relaxation and cytosol viscosity, respectively. By identifying key parameters describing the time-dependent behavior of neurites, as well as revealing possible physical mechanisms behind, this study could greatly help us understand how neural cells perform their biological duties over a wide spectrum of timescales.