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关于肠道上皮干细胞增殖与分化的房室群体动力学模型的效用

On the utility of a compartmental population kinetics model of intestinal epithelial stem cell proliferation and differentiation.

作者信息

Barthel Erik R

机构信息

Department of Surgery, Section of Pediatric Surgery, University of Chicago Biological Sciences Division, 5841 S Maryland Ave MC 4062, Chicago, IL, 60637, USA.

出版信息

Theor Biol Med Model. 2017 Dec 19;14(1):25. doi: 10.1186/s12976-017-0071-8.

DOI:10.1186/s12976-017-0071-8
PMID:29254493
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5735948/
Abstract

BACKGROUND

The small intestinal epithelium is a dynamic system with specialized cell types. The various cell populations of this tissue are continually renewed and replenished from stem cells that reside in the small intestinal crypt. The cell types and their locations in the crypt and villus are well known, but the details of the kinetics of stem cell division, and precursor cell proliferation and differentiation into mature enterocytes and secretory cells are still being studied. These proliferation and differentiation events have been extensively modeled with a variety of computational approaches in the past.

METHODS

A compartmental population kinetics model, incorporating experimentally measured proliferation rates for various intestinal epithelial cell types, is implemented for a previously reported scheme for the intestinal cell dynamics. A sensitivity analysis is performed to determine the effect that varying the model parameters has upon the model outputs, the steady-state cell populations.

RESULTS

The model is unable to reproduce the experimentally known timescale of renewal of the intestinal epithelium if literature values for the proliferation rates of stem cells and transit amplifying cells are employed. Unphysically large rates of proliferation result when these parameters are allowed to vary to reproduce this timescale and the steady-state populations of terminally differentiated intestinal epithelial cells. Sensitivity analysis reveals that the strongest contributor to the steady-state populations is the transit amplifying cell proliferation rate when literature values are used, but that the differentiation rate of transit amplifying cells to secretory progenitor cells dominates when all parameters are allowed to vary.

CONCLUSIONS

A compartmental population kinetics model of proliferation and differentiation of cells of the intestinal epithelium can provide a simplifying means of understanding a complicated multistep process. However, when literature values for proliferation rates of the crypt based columnar and transit amplifying cell populations are employed in the model, it cannot reproduce the experimentally known timescale of intestinal epithelial renewal. Nevertheless, it remains a valuable conceptual tool, and its sensitivity analysis provides important clues for which events in the process are the most important in controlling the steady-state populations of specialized intestinal epithelial cells.

摘要

背景

小肠上皮是一个具有特殊细胞类型的动态系统。该组织中的各种细胞群体不断更新,并由位于小肠隐窝的干细胞补充。细胞类型及其在隐窝和绒毛中的位置是众所周知的,但干细胞分裂动力学以及前体细胞增殖和分化为成熟肠上皮细胞和分泌细胞的细节仍在研究中。过去,这些增殖和分化事件已通过多种计算方法进行了广泛建模。

方法

针对先前报道的肠道细胞动力学方案,实施了一个包含各种肠道上皮细胞类型实验测量增殖率的房室群体动力学模型。进行敏感性分析以确定改变模型参数对模型输出(稳态细胞群体)的影响。

结果

如果采用干细胞和过渡增殖细胞增殖率的文献值,该模型无法再现实验已知的小肠上皮更新时间尺度。当允许这些参数变化以再现该时间尺度和终末分化小肠上皮细胞的稳态群体时,会产生不符合生理的高增殖率。敏感性分析表明,当使用文献值时,对稳态群体贡献最大的是过渡增殖细胞增殖率,但当允许所有参数变化时,过渡增殖细胞向分泌祖细胞的分化率起主导作用。

结论

小肠上皮细胞增殖和分化的房室群体动力学模型可以提供一种简化手段来理解复杂的多步骤过程。然而,当模型中采用基于隐窝的柱状细胞和过渡增殖细胞群体增殖率的文献值时,它无法再现实验已知的小肠上皮更新时间尺度。尽管如此,它仍然是一个有价值的概念工具,其敏感性分析为该过程中哪些事件对控制特殊小肠上皮细胞的稳态群体最为重要提供了重要线索。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d21/5735948/adbd24f28032/12976_2017_71_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d21/5735948/cb8d4279f45e/12976_2017_71_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d21/5735948/cc6b67809d54/12976_2017_71_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d21/5735948/adbd24f28032/12976_2017_71_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d21/5735948/cb8d4279f45e/12976_2017_71_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d21/5735948/cc6b67809d54/12976_2017_71_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d21/5735948/adbd24f28032/12976_2017_71_Fig3_HTML.jpg

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