Population dynamics of chemo- and hapto-taxing model cells that have an intrinsic directional persistence in crawling
- 주제(키워드) Cell dynamics
- 발행기관 고려대학교 대학원
- 지도교수 이경진
- 발행년도 2016
- 학위수여년월 2016. 2
- 학위구분 석사
- 학과 대학원 물리학과
- 세부전공 비선형동력학 및 생물물리학전공
- 원문페이지 34 p
- 실제URI http://www.dcollection.net/handler/korea/000000065665
- 본문언어 영어
- 제출원본 000045866716
초록/요약
The crawling of a biological cell is a rather complex phenomenon involving various bio-chemical and bio-mechanical processes, many of which are still not well understood. Some of them are intrinsic to individual cells, while many others are either related to the cell population dynamics or attributed to some extrinsically imposed chemical gradients and/or cell-to-substrate interactions. Here, we discuss the population dynamics of mathematical model cells that have a built-in directional persistence during their crawling for three different cases: 1) when there is a haptotaxis-mediated social interaction, 2) when there is a chemotaxis following an externally imposed global chemical gradient, and 3) when both are present. For the case of 1), we show that cells can form intriguing patterns of trails along which they crawl. The trail morphology very much depends on the degree of the directional persistence. For the case of 2) (i.e., chemotaxis only), the model cell density is measured as a function of time and space. Surprisingly, we find the steady-state cell density profile fits rather well to that of a well-known Keller-Segel population model, in which a chemotatic flux, F_chemo= ρ∇C competes with a diffusive flux, F_diff=-D∇ρ, where C, and Dstand for the strength of chemotaxis, the concentration of chemo-attractant, and the effective diffusion coefficient of the cell population, respectively. In other words, our model cells can be considered as a normal Brownian particle; the time which is relevant for their directional persistence is too small (~100) to be meaningful when it is compared with the much longer time interval (~10000) that we have used for the estimation of the diffusive flux. Finally, for the case of 3) (i.e., both chemotaxis and haptotaxis), we find two interesting consequences. First of all, the time it takes for the system to reach its steady-state gets significantly shortened. Second of all, the cell density at the peak chemo-attractant density becomes much higher. We believe that the mixed case of 3) can be a very realistic picture in many different immune responses, such as microglia or neutrophils moving toward and around a site of wound or pathogens.
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Contents
1 Introduction
2 Backgrounds
2.1 Microglia .................................................................................................... 3.
2.2 Single cell model ........................................................................................ 3.
2.3 Single cell motility ..................................................................................... 5.
2.4 The thesis on trail networks formed by populations of immune cells .. 5.
2.5 Change of movement as a result of external stimulation: taxis.............. 6.
2.6 The Keller-Segal model ............................................................................. 7.
3 Results
3.1 The time scale of model cells identified by persistence length................. 8.
3.2 Trail formation by haptotaxis: Change of network structure as a result
of directional persistence (K_decay) change ................................................ 12.
3.3 Model cells in chemotaxis .......................................................................... 16.
3.4 The chemotaxis-haptotaxis model........................................................... 21.
4 Discussion .......................................................................................... 24.
Reference ................................................................................................... 25.
