Matching Items (13)
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
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
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
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
Description
Background
Grading schemes for breast cancer diagnosis are predominantly based on pathologists' qualitative assessment of altered nuclear structure from 2D brightfield microscopy images. However, cells are three-dimensional (3D) objects with features that are inherently 3D and thus poorly characterized in 2D. Our goal is to quantitatively characterize nuclear structure in 3D, assess its variation with malignancy, and investigate whether such variation correlates with standard nuclear grading criteria.
Methodology
We applied micro-optical computed tomographic imaging and automated 3D nuclear morphometry to quantify and compare morphological variations between human cell lines derived from normal, benign fibrocystic or malignant breast epithelium. To reproduce the appearance and contrast in clinical cytopathology images, we stained cells with hematoxylin and eosin and obtained 3D images of 150 individual stained cells of each cell type at sub-micron, isotropic resolution. Applying volumetric image analyses, we computed 42 3D morphological and textural descriptors of cellular and nuclear structure.
Principal Findings
We observed four distinct nuclear shape categories, the predominant being a mushroom cap shape. Cell and nuclear volumes increased from normal to fibrocystic to metastatic type, but there was little difference in the volume ratio of nucleus to cytoplasm (N/C ratio) between the lines. Abnormal cell nuclei had more nucleoli, markedly higher density and clumpier chromatin organization compared to normal. Nuclei of non-tumorigenic, fibrocystic cells exhibited larger textural variations than metastatic cell nuclei. At p<0.0025 by ANOVA and Kruskal-Wallis tests, 90% of our computed descriptors statistically differentiated control from abnormal cell populations, but only 69% of these features statistically differentiated the fibrocystic from the metastatic cell populations.
Conclusions
Our results provide a new perspective on nuclear structure variations associated with malignancy and point to the value of automated quantitative 3D nuclear morphometry as an objective tool to enable development of sensitive and specific nuclear grade classification in breast cancer diagnosis.
Grading schemes for breast cancer diagnosis are predominantly based on pathologists' qualitative assessment of altered nuclear structure from 2D brightfield microscopy images. However, cells are three-dimensional (3D) objects with features that are inherently 3D and thus poorly characterized in 2D. Our goal is to quantitatively characterize nuclear structure in 3D, assess its variation with malignancy, and investigate whether such variation correlates with standard nuclear grading criteria.
Methodology
We applied micro-optical computed tomographic imaging and automated 3D nuclear morphometry to quantify and compare morphological variations between human cell lines derived from normal, benign fibrocystic or malignant breast epithelium. To reproduce the appearance and contrast in clinical cytopathology images, we stained cells with hematoxylin and eosin and obtained 3D images of 150 individual stained cells of each cell type at sub-micron, isotropic resolution. Applying volumetric image analyses, we computed 42 3D morphological and textural descriptors of cellular and nuclear structure.
Principal Findings
We observed four distinct nuclear shape categories, the predominant being a mushroom cap shape. Cell and nuclear volumes increased from normal to fibrocystic to metastatic type, but there was little difference in the volume ratio of nucleus to cytoplasm (N/C ratio) between the lines. Abnormal cell nuclei had more nucleoli, markedly higher density and clumpier chromatin organization compared to normal. Nuclei of non-tumorigenic, fibrocystic cells exhibited larger textural variations than metastatic cell nuclei. At p<0.0025 by ANOVA and Kruskal-Wallis tests, 90% of our computed descriptors statistically differentiated control from abnormal cell populations, but only 69% of these features statistically differentiated the fibrocystic from the metastatic cell populations.
Conclusions
Our results provide a new perspective on nuclear structure variations associated with malignancy and point to the value of automated quantitative 3D nuclear morphometry as an objective tool to enable development of sensitive and specific nuclear grade classification in breast cancer diagnosis.
ContributorsNandakumar, Vivek (Author) / Kelbauskas, Laimonas (Author) / Hernandez, Kathryn (Author) / Lintecum, Kelly (Author) / Senechal, Patti (Author) / Bussey, Kimberly (Author) / Davies, Paul (Author) / Johnson, Roger (Author) / Meldrum, Deirdre (Author) / Ira A. Fulton Schools of Engineering (Contributor) / School of Electrical, Computer and Energy Engineering (Contributor) / Biodesign Institute (Contributor) / Center for Biosignatures Discovery Automation (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor) / Department of Physics (Contributor)
Created2012-01-05
Description
Quantitative three-dimensional (3D) computed tomography (CT) imaging of living single cells enables orientation-independent morphometric analysis of the intricacies of cellular physiology. Since its invention, x-ray CT has become indispensable in the clinic for diagnostic and prognostic purposes due to its quantitative absorption-based imaging in true 3D that allows objects of interest to be viewed and measured from any orientation. However, x-ray CT has not been useful at the level of single cells because there is insufficient contrast to form an image. Recently, optical CT has been developed successfully for fixed cells, but this technology called Cell-CT is incompatible with live-cell imaging due to the use of stains, such as hematoxylin, that are not compatible with cell viability. We present a novel development of optical CT for quantitative, multispectral functional 4D (three spatial + one spectral dimension) imaging of living single cells. The method applied to immune system cells offers truly isotropic 3D spatial resolution and enables time-resolved imaging studies of cells suspended in aqueous medium. Using live-cell optical CT, we found a heterogeneous response to mitochondrial fission inhibition in mouse macrophages and differential basal remodeling of small (0.1 to 1 fl) and large (1 to 20 fl) nuclear and mitochondrial structures on a 20- to 30-s time scale in human myelogenous leukemia cells. Because of its robust 3D measurement capabilities, live-cell optical CT represents a powerful new tool in the biomedical research field.
ContributorsKelbauskas, Laimonas (Author) / Shetty, Rishabh Manoj (Author) / Cao, Bin (Author) / Wang, Kuo-Chen (Author) / Smith, Dean (Author) / Wang, Hong (Author) / Chao, Shi-Hui (Author) / Gangaraju, Sandhya (Author) / Ashcroft, Brian (Author) / Kritzer, Margaret (Author) / Glenn, Honor (Author) / Johnson, Roger (Author) / Meldrum, Deirdre (Author) / Biodesign Institute (Contributor)
Created2017-12-06
Description
Functional and molecular cell-to-cell variability is pivotal at the cellular, tissue and whole-organism levels. Yet, the ultimate goal of directly correlating the function of the individual cell with its biomolecular profile remains elusive. We present a platform for integrated analysis of functional and transcriptional phenotypes in the same single cells. We investigated changes in the cellular respiration and gene expression diversity resulting from adaptation to repeated episodes of acute hypoxia in a premalignant progression model. We find differential, progression stage-specific alterations in phenotypic heterogeneity and identify cells with aberrant phenotypes. To our knowledge, this study is the first demonstration of an integrated approach to elucidate how heterogeneity at the transcriptional level manifests in the physiologic profile of individual cells in the context of disease progression.
ContributorsKelbauskas, Laimonas (Author) / Ashili, Shashaanka (Author) / Zeng, Jia (Author) / Rezaie, Aida (Author) / Lee, Kristen (Author) / Derkach, Dmitry (Author) / Ueberroth, Benjamin (Author) / Gao, Weimin (Author) / Paulson, T. (Author) / Wang, Hong (Author) / Tian, Yanqing (Author) / Smith, Dean (Author) / Reid, B. (Author) / Meldrum, Deirdre (Author) / Biodesign Institute (Contributor)
Created2017-03-16
Description
Driven by an increasing number of studies demonstrating its relevance to a broad variety of disease states, the bioenergy production phenotype has been widely characterized at the bulk sample level. Its cell-to-cell variability, a key player associated with cancer cell survival and recurrence, however, remains poorly understood due to ensemble averaging of the current approaches. We present a technology platform for performing oxygen consumption and extracellular acidification measurements of several hundreds to 1,000 individual cells per assay, while offering simultaneous analysis of cellular communication effects on the energy production phenotype. The platform comprises two major components: a tandem optical sensor for combined oxygen and pH detection, and a microwell device for isolation and analysis of single and few cells in hermetically sealed sub-nanoliter chambers. Our approach revealed subpopulations of cells with aberrant energy production profiles and enables determination of cellular response variability to electron transfer chain inhibitors and ion uncouplers.
ContributorsKelbauskas, Laimonas (Author) / Glenn, Honor (Author) / Anderson, Clifford (Author) / Messner, Jacob (Author) / Lee, Kristen (Author) / Song, Ganquan (Author) / Houkal, Jeff (Author) / Su, Fengyu (Author) / Zhang, Liqiang (Author) / Tian, Yanqing (Author) / Wang, Hong (Author) / Bussey, Kimberly (Author) / Johnson, Roger (Author) / Meldrum, Deirdre (Author) / Biodesign Institute (Contributor)
Created2017-03-28