首页> 美国卫生研究院文献>PLoS Computational Biology >Understanding the Sub-Cellular Dynamics of Silicon Transportation and Synthesis in Diatoms Using Population-Level Data and Computational Optimization
【2h】

Understanding the Sub-Cellular Dynamics of Silicon Transportation and Synthesis in Diatoms Using Population-Level Data and Computational Optimization

机译:使用种群水平数据和计算优化了解硅藻中硅运输和合成的亚细胞动力学

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Controlled synthesis of silicon is a major challenge in nanotechnology and material science. Diatoms, the unicellular algae, are an inspiring example of silica biosynthesis, producing complex and delicate nano-structures. This happens in several cell compartments, including cytoplasm and silica deposition vesicle (SDV). Considering the low concentration of silicic acid in oceans, cells have developed silicon transporter proteins (SIT). Moreover, cells change the level of active SITs during one cell cycle, likely as a response to the level of external nutrients and internal deposition rates. Despite this topic being of fundamental interest, the intracellular dynamics of nutrients and cell regulation strategies remain poorly understood. One reason is the difficulties in measurements and manipulation of these mechanisms at such small scales, and even when possible, data often contain large errors. Therefore, using computational techniques seems inevitable. We have constructed a mathematical model for silicon dynamics in the diatom Thalassiosira pseudonana in four compartments: external environment, cytoplasm, SDV and deposited silica. The model builds on mass conservation and Michaelis-Menten kinetics as mass transport equations. In order to find the free parameters of the model from sparse, noisy experimental data, an optimization technique (global and local search), together with enzyme related penalty terms, has been applied. We have connected population-level data to individual-cell-level quantities including the effect of early division of non-synchronized cells. Our model is robust, proven by sensitivity and perturbation analysis, and predicts dynamics of intracellular nutrients and enzymes in different compartments. The model produces different uptake regimes, previously recognized as surge, externally-controlled and internally-controlled uptakes. Finally, we imposed a flux of SITs to the model and compared it with previous classical kinetics. The model introduced can be generalized in order to analyze different biomineralizing organisms and to test different chemical pathways only by switching the system of mass transport equations.
机译:硅的受控合成是纳米技术和材料科学中的主要挑战。硅藻是单细胞藻类,是二氧化硅生物合成的一个令人鼓舞的例子,它产生复杂而细腻的纳米结构。这发生在几个细胞室中,包括细胞质和二氧化硅沉积囊泡(SDV)。考虑到海洋中硅酸的浓度低,细胞已开发出硅转运蛋白(SIT)。此外,细胞可能在一个细胞周期内改变活性SIT的水平,这可能是对外部营养物水平和内部沉积速率的反应。尽管这个话题引起了人们的极大兴趣,但对营养的细胞内动力学和细胞调节策略仍然知之甚少。原因之一是难以在如此小的规模上测量和操纵这些机制,并且即使在可能的情况下,数据也经常包含较大的错误。因此,使用计算技术似乎是不可避免的。我们已经建立了硅藻Thalassiosira pseudonana中硅动力学的数学模型,该数学模型分为四个部分:外部环境,细胞质,SDV和沉积的二氧化硅。该模型基于质量守恒和Michaelis-Menten动力学作为质量传输方程。为了从稀疏,嘈杂的实验数据中找到模型的自由参数,已应用了一种优化技术(全局和局部搜索)以及与酶有关的惩罚项。我们已将种群级别的数据与单个细胞级别的数量相关联,包括非同步细胞的早期分裂的影响。我们的模型是鲁棒的,通过敏感性和扰动分析得到证明,并且可以预测不同隔室中细胞内营养物质和酶的动力学。该模型产生了不同的吸收方式,这些吸收方式先前被认为是喘振,外部控制和内部控制的吸收。最后,我们对模型施加了SIT的通量,并将其与以前的经典动力学进行了比较。为了分析不同的矿化生物和测试不同的化学途径,仅通过切换传质方程组就可以推广引入的模型。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号