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Description
Continuous underwater observation is a challenging engineering task that could be accomplished by development and deployment of a sensor array that can survive harsh underwater conditions. One approach to this challenge is a swarm of micro underwater robots, known as Sensorbots, that are equipped with biogeochemical sensors that can relay

Continuous underwater observation is a challenging engineering task that could be accomplished by development and deployment of a sensor array that can survive harsh underwater conditions. One approach to this challenge is a swarm of micro underwater robots, known as Sensorbots, that are equipped with biogeochemical sensors that can relay information among themselves in real-time. This innovative method for underwater exploration can contribute to a more comprehensive understanding of the ocean by not limiting sampling to a single point and time. In this thesis, Sensorbot Beta, a low-cost fully enclosed Sensorbot prototype for bench-top characterization and short-term field testing, is presented in a modular format that provides flexibility and the potential for rapid design. Sensorbot Beta is designed around a microcontroller driven platform comprised of commercial off-the-shelf components for all hardware to reduce cost and development time. The primary sensor incorporated into Sensorbot Beta is an in situ fluorescent pH sensor. Design considerations have been made for easy adoption of other fluorescent or phosphorescent sensors, such as dissolved oxygen or temperature. Optical components are designed in a format that enables additional sensors. A real-time data acquisition system, utilizing Bluetooth, allows for characterization of the sensor in bench top experiments. The Sensorbot Beta demonstrates rapid calibration and future work will include deployment for large scale experiments in a lake or ocean.
ContributorsJohansen, John (Civil engineer) (Author) / Meldrum, Deirdre R (Thesis advisor) / Chao, Shih-hui (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Arizona State University (Publisher)
Created2012
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Description
A single cell is the very fundamental element in an organism; however, it contains the most complicated and stochastic information, such as DNA, RNA, and protein expression. Thus, it is a necessity to study stochastic gene expression in order to discover the biosignatures at the single-cell level. The heterogeneous gene

A single cell is the very fundamental element in an organism; however, it contains the most complicated and stochastic information, such as DNA, RNA, and protein expression. Thus, it is a necessity to study stochastic gene expression in order to discover the biosignatures at the single-cell level. The heterogeneous gene expression of single cells from an isogenic cell population has already been studied for years. Yet to date, single-cell studies have been confined in a fashion of analyzing isolated single cells or a dilution of cells from the bulk-cell populations. These techniques or devices are limited by either the mechanism of cell lysis or the difficulties to target specific cells without harming neighboring cells.

This dissertation presents the development of a laser lysis chip combined with a two-photon laser system to perform single-cell lysis of single cells in situ from three-dimensional (3D) cell spheroids followed by analysis of the cell lysate with two-step reverse transcription-quantitative polymerase chain reaction (RT-qPCR). The 3D spheroids were trapped in a well in the custom-designed laser lysis chip. Next, each single cell of interest in the 3D spheroid was identified and lysed one at a time utilizing a two-photon excited laser. After each cell lysis, the contents inside the target cell were released to the surrounding media and carried out to the lysate collector. Finally, the gene expression of each individual cell was measured by two-step RT-qPCR then spatially mapped back to its original location in the spheroids to construct a 3D gene expression map.

This novel technology and approach enables multiple gene expression measurements in single cells of multicellular organisms as well as cell-to-cell heterogeneous responses to the environment with spatial recognition. Furthermore, this method can be applied to study precancerous tissues for a better understanding of cancer progression and for identifying early tumor development.
ContributorsWang, Guozhen (Author) / Meldrum, Deirdre R (Thesis advisor) / Chao, Shih-hui (Committee member) / Wang, Hong (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2016