A sense of proximity: Cell packing modulates oxygen consumption.

IF 6.6 3区 医学 Q1 ENGINEERING, BIOMEDICAL APL Bioengineering Pub Date : 2023-09-01 DOI:10.1063/5.0160422
Ermes Botte, Piera Mancini, Chiara Magliaro, Arti Ahluwalia
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Abstract

Accurately modeling oxygen transport and consumption is crucial to predict metabolic dynamics in cell cultures and optimize the design of tissue and organ models. We present a methodology to characterize the Michaelis-Menten oxygen consumption parameters in vitro, integrating novel experimental techniques and computational tools. The parameters were derived for hepatic cell cultures with different dimensionality (i.e., 2D and 3D) and with different surface and volumetric densities. To quantify cell packing regardless of the dimensionality of cultures, we devised an image-based metric, referred to as the proximity index. The Michaelis-Menten parameters were related to the proximity index through an uptake coefficient, analogous to a diffusion constant, enabling the quantitative analysis of oxygen dynamics across dimensions. Our results show that Michaelis-Menten parameters are not constant for a given cell type but change with dimensionality and cell density. The maximum consumption rate per cell decreases significantly with cell surface and volumetric density, while the Michaelis-Menten constant tends to increase. In addition, the dependency of the uptake coefficient on the proximity index suggests that the oxygen consumption rate of hepatic cells is superadaptive, as they modulate their oxygen utilization according to its local availability and to the proximity of other cells. We describe, for the first time, how cells consume oxygen as a function of cell proximity, through a quantitative index, which combines cell density and dimensionality. This study enhances our understanding of how cell-cell interaction affects oxygen dynamics and enables better prediction of aerobic metabolism in tissue models, improving their translational value.

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接近感:细胞包装调节氧气消耗。
准确建模氧气运输和消耗是至关重要的预测代谢动力学在细胞培养和优化组织和器官模型的设计。我们提出了一种方法来表征体外Michaelis-Menten耗氧量参数,整合了新的实验技术和计算工具。这些参数是针对不同维度(即二维和三维)、不同表面和体积密度的肝细胞培养而得出的。无论培养物的维度如何,为了量化细胞包装,我们设计了一种基于图像的度量,称为接近指数。Michaelis-Menten参数通过吸收系数(类似于扩散常数)与接近指数相关联,从而可以跨维度定量分析氧动力学。我们的研究结果表明Michaelis-Menten参数对于给定的细胞类型不是恒定的,而是随着细胞密度和维数的变化而变化。每个细胞的最大消耗率随细胞表面积和体积密度的增加而显著降低,Michaelis-Menten常数呈增加趋势。此外,摄取系数对接近指数的依赖性表明,肝细胞的耗氧率是超适应性的,因为它们根据其局部可用性和与其他细胞的接近程度来调节其氧利用。我们首次通过结合细胞密度和维度的定量指数,描述了细胞如何消耗氧气作为细胞接近度的函数。这项研究增强了我们对细胞-细胞相互作用如何影响氧动力学的理解,使我们能够更好地预测组织模型中的有氧代谢,提高它们的翻译价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
APL Bioengineering
APL Bioengineering ENGINEERING, BIOMEDICAL-
CiteScore
9.30
自引率
6.70%
发文量
39
审稿时长
19 weeks
期刊介绍: APL Bioengineering is devoted to research at the intersection of biology, physics, and engineering. The journal publishes high-impact manuscripts specific to the understanding and advancement of physics and engineering of biological systems. APL Bioengineering is the new home for the bioengineering and biomedical research communities. APL Bioengineering publishes original research articles, reviews, and perspectives. Topical coverage includes: -Biofabrication and Bioprinting -Biomedical Materials, Sensors, and Imaging -Engineered Living Systems -Cell and Tissue Engineering -Regenerative Medicine -Molecular, Cell, and Tissue Biomechanics -Systems Biology and Computational Biology
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