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Single cell RT-qPCR based ocean environmental sensing device development.

机译:基于单细胞RT-qPCR的海洋环境传感设备开发。

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摘要

This thesis research focuses on developing a single-cell gene expression analysis method for marine diatom Thalassiosira pseudonana and constructing a chip level tool to realize the single cell RT-qPCR analysis. This chip will serve as a conceptual foundation for future deployable ocean monitoring systems. T. pseudonana, which is a common surface water microorganism, was detected in the deep ocean as confirmed by phylogenetic and microbial community functional studies. Six-fold copy number differences between 23S rRNA and 23S rDNA were observed by RT-qPCR, demonstrating the moderate functional activity of detected photosynthetic microbes in the deep ocean including T. pseudonana. Because of the ubiquity of T. pseudonana, it is a good candidate for an early warning system for ocean environmental perturbation monitoring. This early warning system will depend on identifying outlier gene expression at the single-cell level. An early warning system based on single-cell analysis is expected to detect environmental perturbations earlier than population level analysis which can only be observed after a whole community has reacted. Preliminary work using tube-based, two-step RT-qPCR revealed for the first time, gene expression heterogeneity of T. pseudonana under different nutrient conditions. Heterogeneity was revealed by different gene expression activity for individual cells under the same conditions. This single cell analysis showed a skewed, lognormal distribution and helped to find outlier cells. The results indicate that the geometric average becomes more important and representative of the whole population than the arithmetic average. This is in contrast with population level analysis which is limited to arithmetic averages only and highlights the value of single cell analysis. In order to develop a deployable sensor in the ocean, a chip level device was constructed. The chip contains surface-adhering droplets, defined by hydrophilic patterning, that serve as real-time PCR reaction chambers when they are immersed in oil. The chip had demonstrated sensitivities at the single cell level for both DNA and RNA. The successful rate of these chip-based reactions was around 85%. The sensitivity of the chip was equivalent to published microfluidic devices with complicated designs and protocols, but the production process of the chip was simple and the materials were all easily accessible in conventional environmental and/or biology laboratories. On-chip tests provided heterogeneity information about the whole population and were validated by comparing with conventional tube based methods and by p-values analysis. The power of chip-based single-cell analyses were mainly between 65-90% which were acceptable and can be further increased by higher throughput devices. With this chip and single-cell analysis approaches, a new paradigm for robust early warning systems of ocean environmental perturbation is possible.
机译:本文的研究重点是为海洋硅藻拟人拟南芥(Thalassiosira pseudonana)开发一种单细胞基因表达分析方法,并构建一种芯片级工具来实现单细胞RT-qPCR分析。该芯片将作为未来可部署海洋监测系统的概念基础。系统发育和微生物群落功能研究证实,在深海中发现了常见的地表水微生物假单胞菌。通过RT-qPCR观察到23S rRNA和23S rDNA之间存在六倍的拷贝数差异,表明在深海(包括拟南芥)中检测到的光合微生物具有中等的功能活性。由于假单胞菌无处不在,因此它是海洋环境扰动监测预警系统的良好候选者。该预警系统将取决于在单细胞水平上鉴定异常基因的表达。基于单细胞分析的预警系统有望比人口水平分析更早地发现环境扰动,只有在整个社区做出反应后才能观察到这种扰动。使用基于管的两步法RT-qPCR进行的初步工作首次揭示了在不同营养条​​件下拟南芥的基因表达异质性。异质性是由相同条件下单个细胞的不同基因表达活性所揭示。这种单细胞分析显示出偏斜,对数正态分布,并有助于发现异常细胞。结果表明,几何平均数比算术平均数更重要,在整个人口中具有代表性。这与人口水平分析相反,人口水平分析仅限于算术平均值,突出了单细胞分析的价值。为了在海洋中开发可部署的传感器,构建了芯片级设备。该芯片包含通过亲水性图案定义的表面粘附液滴,当它们浸入油中时,这些液滴可用作实时PCR反应室。该芯片已证明在单细胞水平上对DNA和RNA均具有敏感性。这些基于芯片的反应的成功率约为85%。该芯片的灵敏度与已发布的具有复杂设计和协议的微流体设备相当,但是该芯片的生产过程很简单,并且在常规的环境和/或生物学实验室中所有材料都易于获得。片上测试提供了有关整个种群的异质性信息,并通过与传统的基于管的方法进行比较并通过p值分析进行了验证。基于芯片的单电池分析的能力主要在65-90%之间,这是可以接受的,并且可以通过更高吞吐量的设备进一步提高。通过这种芯片和单细胞分析方法,可以为海洋环境扰动的强大预警系统提供新的范例。

著录项

  • 作者

    Shi, Xu.;

  • 作者单位

    Arizona State University.;

  • 授予单位 Arizona State University.;
  • 学科 Engineering Environmental.;Biology Microbiology.;Biology Oceanography.
  • 学位 Ph.D.
  • 年度 2013
  • 页码 159 p.
  • 总页数 159
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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