Matching Items (21)
Description
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.
ContributorsShi, Xu (Author) / Meldrum, Deirdre R. (Thesis advisor) / Zhang, Weiwen (Committee member) / Chao, Shih-hui (Committee member) / Westerhoff, Paul (Committee member) / Arizona State University (Publisher)
Created2013
Description
Cell-cell interactions in a microenvironment under stress conditions play a critical role in pathogenesis and pre-malignant progression. Hypoxia is a central factor in carcinogenesis, which induces selective pressure in this process. Understanding the role of intercellular communications and cellular adaptation to hypoxia can help discover new cancer biosignatures and more effective diagnostic and therapeutic strategies. This dissertation presents a study on transcriptomic and metabolic profiling of pre-malignant progression of Barrett's esophagus. It encompasses two methodology developments and experimental findings of two related studies. To integrate phenotype and genotype measurements, a minimally invasive method was developed for selectively retrieving single adherent cells from cell cultures. Selected single cells can be harvested by a combination of mechanical force and biochemical treatment after phenotype measurements and used for end-point assays. Furthermore, a method was developed for analyzing expression levels of ten genes in individual mammalian cells with high sensitivity and reproducibility without the need of pre-amplifying cDNA. It is inexpensive and compatible with most of commercially available RT-qPCR systems, which warrants a wide applicability of the method to gene expression analysis in single cells. In the first study, the effect of intercellular interactions was investigated between normal esophageal epithelial and dysplastic Barrett's esophagus cells on gene expression levels and cellular functions. As a result, gene expression levels in dysplastic cells were found to be affected to a significantly larger extent than in the normal esophageal epithelial cells. These differentially expressed genes are enriched in cellular movement, TGFβ and EGF signaling networks. Heterotypic interactions between normal and dysplastic cells can change cellular motility and inhibit proliferation in both normal and dysplastic cells. In the second study, alterations in gene transcription levels and metabolic phenotypes between hypoxia-adapted cells and age-matched normoxic controls representing four different stages of pre-malignant progression in Barrett's esophagus were investigated. Through differential gene expression analysis and mitochondrial membrane potential measurements, evidence of clonal evolution induced by hypoxia selection pressure in metaplastic and high-grade dysplastic cells was found. These discoveries on cell-cell interactions and hypoxia adaptations provide a deeper insight into the dynamic evolutionary process in pre-malignant progression of Barrett's esophagus.
ContributorsZeng, Jia (Author) / Meldrum, Deirdre R (Thesis advisor) / Kelbauskas, Laimonas (Committee member) / Barrett, Michael T (Committee member) / Bussey, Kimberly J (Committee member) / Zhang, Weiwen (Committee member) / Arizona State University (Publisher)
Created2014
Description
The production of monomer compounds for synthesizing plastics has to date been largely restricted to the petroleum-based chemical industry and sugar-based microbial fermentation, limiting its sustainability and economic feasibility. Cyanobacteria have, however, become attractive microbial factories to produce renewable fuels and chemicals directly from sunlight and CO2. To explore the feasibility of photosynthetic production of (S)- and (R)-3-hydroxybutyrate (3HB), building-block monomers for synthesizing the biodegradable plastics polyhydroxyalkanoates and precursors to fine chemicals, synthetic metabolic pathways have been constructed, characterized and optimized in the cyanobacterium Synechocystis sp. PCC 6803 (hereafter Synechocystis 6803). Both types of 3HB molecules were produced and readily secreted from Synechocystis cells without over-expression of transporters. Additional inactivation of the competing PHB biosynthesis pathway further promoted the 3HB production. Analysis of the intracellular acetyl-CoA and anion concentrations in the culture media indicated that the phosphate consumption during the photoautotrophic growth and the concomitant elevated acetyl-CoA pool acted as a key driving force for 3HB biosynthesis in Synechocystis. Fine-tuning of the gene expression levels via strategies, including tuning gene copy numbers, promoter engineering and ribosome binding site optimization, proved critical to mitigating metabolic bottlenecks and thus improving the 3HB production. One of the engineered Synechocystis strains, namely R168, was able to produce (R)-3HB to a cumulative titer of ~1600 mg/L, with a peak daily productivity of ~200 mg/L, using light and CO2 as the sole energy and carbon sources, respectively. Additionally, in order to establish a high-efficiency transformation protocol in cyanobacterium Synechocystis 6803, methyltransferase-encoding genes were cloned and expressed to pre-methylate the exogenous DNA before Synechocystis transformation. Eventually, the transformation efficiency was increased by two orders of magnitude in Synechocystis. This research has demonstrated the use of cyanobacteria as cell factories to produce 3HB directly from light and CO2, and developed new synthetic biology tools for cyanobacteria.
ContributorsWang, Bo (Author) / Meldrum, Deirdre R (Thesis advisor) / Zhang, Weiwen (Committee member) / Sandrin, Todd R. (Committee member) / Nielsen, David R (Committee member) / Arizona State University (Publisher)
Created2014
Description
Cellular heterogeneity is a key factor in various cellular processes as well as in disease development, especially associated with immune response and cancer progression. Cell-to-cell variability is considered to be one of the major obstacles in early detection and successful treatment of cancer. Most present technologies are based on bulk cell analysis, which results in averaging out the results acquired from a group of cells and hence missing important information about individual cells and their behavior. Understanding the cellular behavior at the single-cell level can help in obtaining a complete profile of the cell and to get a more in-depth knowledge of cellular processes. For example, measuring transmembrane fluxes oxygen can provide a direct readout of the cell metabolism.
The goal of this thesis is to design, optimize and implement a device that can measure the oxygen consumption rate (OCR) of live single cells. A microfluidic device has been designed with the ability to rapidly seal and unseal microchambers containing individual cells and an extracellular optical oxygen sensor for measuring the OCR of live single cells. The device consists of two parts, one with the sensor in microwells (top half) and the other with channels and cells trapped in Pachinko-type micro-traps (bottom half). When the two parts of the device are placed together the wells enclose each cell. Oil is flown in through the channels of the device to produce isolated and sealed microchamber around each cell. Different fluids can be flowed in and out of the device, alternating with oil, to rapidly switch between sealed and unsealed microenvironment around each cell. A fluorescent ratiometric dual pH and oxygen sensor is placed in each well. The thesis focuses on measuring changes in the oxygen consumption rate of each cell within a well. Live and dead cells are identified using a fluorescent live/dead cell assay. Finally, the technology is designed to be scalable for high-throughput applications by controlling the flow rate of the system and increasing the cell array density.
The goal of this thesis is to design, optimize and implement a device that can measure the oxygen consumption rate (OCR) of live single cells. A microfluidic device has been designed with the ability to rapidly seal and unseal microchambers containing individual cells and an extracellular optical oxygen sensor for measuring the OCR of live single cells. The device consists of two parts, one with the sensor in microwells (top half) and the other with channels and cells trapped in Pachinko-type micro-traps (bottom half). When the two parts of the device are placed together the wells enclose each cell. Oil is flown in through the channels of the device to produce isolated and sealed microchamber around each cell. Different fluids can be flowed in and out of the device, alternating with oil, to rapidly switch between sealed and unsealed microenvironment around each cell. A fluorescent ratiometric dual pH and oxygen sensor is placed in each well. The thesis focuses on measuring changes in the oxygen consumption rate of each cell within a well. Live and dead cells are identified using a fluorescent live/dead cell assay. Finally, the technology is designed to be scalable for high-throughput applications by controlling the flow rate of the system and increasing the cell array density.
ContributorsRodrigues, Meryl (Author) / Meldrum, Deirdre (Thesis advisor) / Kelbauskas, Laimonas (Committee member) / LaBelle, Jeffrey (Committee member) / Arizona State University (Publisher)
Created2014
Description
The technology expansion seen in the last decade for genomics research has permitted the generation of large-scale data sources pertaining to molecular biological assays, genomics, proteomics, transcriptomics and other modern omics catalogs. New methods to analyze, integrate and visualize these data types are essential to unveil relevant disease mechanisms. Towards these objectives, this research focuses on data integration within two scenarios: (1) transcriptomic, proteomic and functional information and (2) real-time sensor-based measurements motivated by single-cell technology. To assess relationships between protein abundance, transcriptomic and functional data, a nonlinear model was explored at static and temporal levels. The successful integration of these heterogeneous data sources through the stochastic gradient boosted tree approach and its improved predictability are some highlights of this work. Through the development of an innovative validation subroutine based on a permutation approach and the use of external information (i.e., operons), lack of a priori knowledge for undetected proteins was overcome. The integrative methodologies allowed for the identification of undetected proteins for Desulfovibrio vulgaris and Shewanella oneidensis for further biological exploration in laboratories towards finding functional relationships. In an effort to better understand diseases such as cancer at different developmental stages, the Microscale Life Science Center headquartered at the Arizona State University is pursuing single-cell studies by developing novel technologies. This research arranged and applied a statistical framework that tackled the following challenges: random noise, heterogeneous dynamic systems with multiple states, and understanding cell behavior within and across different Barrett's esophageal epithelial cell lines using oxygen consumption curves. These curves were characterized with good empirical fit using nonlinear models with simple structures which allowed extraction of a large number of features. Application of a supervised classification model to these features and the integration of experimental factors allowed for identification of subtle patterns among different cell types visualized through multidimensional scaling. Motivated by the challenges of analyzing real-time measurements, we further explored a unique two-dimensional representation of multiple time series using a wavelet approach which showcased promising results towards less complex approximations. Also, the benefits of external information were explored to improve the image representation.
ContributorsTorres Garcia, Wandaliz (Author) / Meldrum, Deirdre R. (Thesis advisor) / Runger, George C. (Thesis advisor) / Gel, Esma S. (Committee member) / Li, Jing (Committee member) / Zhang, Weiwen (Committee member) / Arizona State University (Publisher)
Created2011
Description
Esophageal adenocarcinoma (EAC) is one of the most lethal and fastest growing cancers in the United States. Its onset is commonly triggered by metaplastic transformation of normal squamous esophageal epithelial cells to Barrett's esophagus (BE) cells in response to acid reflux. BE patients are believed to progress through non-dysplastic metaplasia and increasing grades of dysplasia prior to EAC. Conventional cancer diagnostic tools rely on bulk-cell analyses that are incapable of identifying intratumoral heterogeneity or rare driver cells that play important roles in cancer progression. An improved single-cell method of cancer diagnosis would overcome this challenge by detecting cancer initiating cells before they progress into untreatable stages. In this study, using EAC as a model, we attempted to identify a more effective method of cancer diagnosis. We quantified the single- and bulk-cell mRNA expression of genes that have been proposed to be instrumental in the progression of EAC through BE. Quantitative Reverse Transcription Polymerase Chain Reaction (qRT-PCR) analysis was performed on human primary cells to measure the mRNA expression levels of BE- and EAC-associated genes. Our results showed high levels of heterogeneity of CDX2 and TFF3 at the single-cell resolution in human BE and EAC samples. Additionally, while expression of VEGF is generally low at the bulk-cell level, our results showed that a few, rare cells had significantly higher VEGF expression levels than the majority of cells in the EAC sample. In conclusion, we have affirmed that EAC cancer cells, as well as BE cells, show high levels of heterogeneity. Based on the VEGF gene expression pattern, single-cell analysis could potentially be more effective for identifying rare, but essential cells for cancer progression, which could then be targeted for treatment. Future studies will focus on analyzing human samples from thousands of normal and cancer subjects to validate the use of single-cell profiling in cancer.
ContributorsHaeuser, Kelsey Lynn (Author) / Tran, Thai (Thesis director) / Kelbauskas, Laimonas (Committee member) / Gao, Weimin (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2013-12
Description
In vitro measurements of cellular respiration have proven to be key biomarkers for the early onset of tumor formation in certain pathological mechanisms.1 The examination of isolated single cells has shown promise in predicting the onset of cancerous growth much earlier than current methods allow.2 Specifically, measurements of the oxygen consumption rates of precancerous cells have elucidated outliers which predict the early onset of esophageal cancer.2 Single cell profiling can fit in to current pathology studies and can serve as a step along the way, much like PCR or gel assays, in detecting biomarkers earlier than current clinical methods.3 Measurement of these single cell metabolic rates is currently limited to 25 cells per experiment. It is the aim of this project to increase throughput from 25 cells to 225 cells per experiment via the implementation of new hardware and software which fit with current methods to allow the same experimental structure. Successful implementation of such methods will allow for more rapid and efficient data collection, facilitating quantitative results and nine times the yield from the same experimental manpower and funding. This document focuses on the implementation ultra high density (UHD) hardware consisting of a pneumatic molar design, angular adjustment features and a mechanical Z-stage. These components have produced the most encouraging results thus far and are the key changes in transitioning to higher throughput experiments.
ContributorsUeberroth, Benjamin Edward (Author) / Kelbauskas, Laimonas (Thesis director) / Ashili, Shashanka (Committee member) / Myers, Jakrey (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor) / School of Life Sciences (Contributor)
Created2013-05
Description
In the past decades, single-cell metabolic analysis has been playing a key role in understanding cellular heterogeneity, disease initiation, progression, and drug resistance. Therefore, it is critical to develop technologies for individual cellular metabolic analysis using various configurations of microfluidic devices. Compared to bulk-cell analysis which is widely used by reporting an averaged measurement, single-cell analysis is able to present the individual cellular responses to the external stimuli. Particularly, oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) are two key parameters to monitor heterogeneous metabolic profiles of cancer cells. To achieve multi-parameter metabolic measurements on single cells, several technical challenges need to be overcome: (1) low adhesion of soft materials micro-fabricated on glass surface for multiple-sensor deposition and single-cell immobilization, e.g. SU-8, KMPR, etc.; (2) high risk of using external mechanical forces to create hermetic seals between two rigid fused silica parts, even with compliance layers; (3) how to accomplish high-throughput for single-cell trapping, metabolic profiling and drug screening; (4) high process cost of micromachining on glass substrate and incapability of mass production.
In this dissertation, the development of microfabrication technologies is demonstrated to design reliable configurations for analyzing multiple metabolic parameters from single cells, including (1) improved KMPR/SU-8 microfabrication protocols for fabricating microwell arrays that can be integrated and sealed to 3 × 3 tri-color sensor arrays for OCR and ECAR measurements; (2) design and characterization of a microfluidic device enabling rapid single-cell trapping and hermetic sealing single cells and tri-color sensors within 10 × 10 hermetically sealed microchamber arrays; (3) exhibition of a low-cost microfluidic device based on plastics for single-cell metabolic multi-parameter profiling. Implementation of these improved microfabrication methods should address the aforementioned challenges and provide a high throughput and multi-parameter single cell metabolic analysis platform.
In this dissertation, the development of microfabrication technologies is demonstrated to design reliable configurations for analyzing multiple metabolic parameters from single cells, including (1) improved KMPR/SU-8 microfabrication protocols for fabricating microwell arrays that can be integrated and sealed to 3 × 3 tri-color sensor arrays for OCR and ECAR measurements; (2) design and characterization of a microfluidic device enabling rapid single-cell trapping and hermetic sealing single cells and tri-color sensors within 10 × 10 hermetically sealed microchamber arrays; (3) exhibition of a low-cost microfluidic device based on plastics for single-cell metabolic multi-parameter profiling. Implementation of these improved microfabrication methods should address the aforementioned challenges and provide a high throughput and multi-parameter single cell metabolic analysis platform.
ContributorsSong, Ganquan (Author) / Meldrum, Deirdre R. (Thesis advisor) / Goryll, Michael (Committee member) / Kelbauskas, Laimonas (Committee member) / Wang, Hong (Committee member) / Arizona State University (Publisher)
Created2017
Description
This thesis research focuses on phylogenetic and functional studies of microbial communities in deep-sea water, an untapped reservoir of high metabolic and genetic diversity of microorganisms. The presence of photosynthetic cyanobacteria and diatoms is an interesting and unexpected discovery during a 16S ribosomal rRNA-based community structure analyses for microbial communities in the deep-sea water of the Pacific Ocean. Both RT-PCR and qRT-PCR approaches were employed to detect expression of the genes involved in photosynthesis of photoautotrophic organisms. Positive results were obtained and further proved the functional activity of these detected photosynthetic microbes in the deep-sea. Metagenomic and metatranscriptomic data was obtained, integrated, and analyzed from deep-sea microbial communities, including both prokaryotes and eukaryotes, from four different deep-sea sites ranging from the mesopelagic to the pelagic ocean. The RNA/DNA ratio was employed as an index to show the strength of metabolic activity of deep-sea microbes. These taxonomic and functional analyses of deep-sea microbial communities revealed a `defensive' life style of microbial communities living in the deep-sea water. Pseudoalteromonas sp.WG07 was subjected to transcriptomic analysis by application of RNA-Seq technology through the transcriptomic annotation using the genomes of closely related surface-water strain Pseudoalteromonas haloplanktis TAC125 and sediment strain Pseudoalteromonas sp. SM9913. The transcriptome survey and related functional analysis of WG07 revealed unique features different from TAC125 and SM9913 and provided clues as to how it adapted to its environmental niche. Also, a comparative transcriptomic analysis of WG07 revealed transcriptome changes between its exponential and stationary growing phases.
ContributorsWu, Jieying (Author) / Meldrum, Deirdre R. (Thesis advisor) / Zhang, Weiwen (Committee member) / Abbaszadegan, Morteza (Committee member) / Neuer, Susanne (Committee member) / Arizona State University (Publisher)
Created2013
Description
In the frenzy of next generation genetic sequencing and proteomics, single-cell level analysis has begun to find its place in the crux of personalized medicine and cancer research. Single live cell 3D imaging technology is one of the most useful ways of providing spatial and morphological details inside living single cells. It provides a window to uncover the mysteries of protein structure and folding, as well as genetic expression over time, which will tremendously improve the state of the fields of biophysics and biomedical research. This thesis project specifically demonstrates a method for live single cell rotation required to image them in the single live cell CT imaging platform. The method of rotation proposed in this thesis uses dynamic optical traps generated by a phase-only spatial light modulator (SLM) to exert torque on a single mammalian cell. Laser patterns carrying the holographic information of the traps are delivered from the SLM through a transformation telescope into the objective lens and onto its focal plane to produce the desired optical trap "image". The phase information in the laser patterns being delivered are continuously altered by the SLM such that the structure of the wavefront produces two foci at opposite edges of the cell of interest that each moves along the circumference of the cell in opposite axial directions. Momentum generated by the motion of the foci exerts a torque on the cell, causing it to rotate. The viability of this method was demonstrated experimentally. Software was written using LabVIEW to control the display panel of the SLM.
ContributorsChan, Samantha W (Author) / Meldrum, Deridre R (Thesis advisor) / Kleim, Jeffrey A (Committee member) / Johnson, Roger H (Committee member) / Kelbauskas, Laimonas (Committee member) / Arizona State University (Publisher)
Created2013