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.
In this dissertation project, an inexpensive, portable, low-energy consuming, and highly quantitative microbiological genomic sensor has been developed for in situ ocean-observing systems. A novel real-time colorimetric loop-mediated isothermal amplification (LAMP) technology has been developed for quantitative detection of microbial nucleic acids. This technology was implemented on a chip-level device with an embedded inexpensive imaging device and temperature controller to achieve quantitative detection within one hour. A bubble-free liquid handling approach was introduced to avoid bubble trapping during liquid loading, a common problem in microfluidic devices. An algorithm was developed to reject the effect of bubbles generated during the reaction process, to enable more accurate nucleic acid analysis. This genomic sensor has been validated at gene and gene expression levels using Synechocystis sp. PCC 6803 genomic DNA and total RNA. Results suggest that the detection limits reached 10 copies/μL and 100 fg/μL, respectively. This approach was highly quantitative, with linear standard curves down to 103 copies/μL and 1 pg/μL, respectively. In addition to environmental microbe characterization, this genomic sensor has been employed for viral RNA quantification during an infectious disease outbreak. As the Zika fever was spreading in America, a quantitative detection of Zika virus has been performed. The results show that the genomic sensor is highly quantitative from 10 copies/μL to 105 copies/μL. This suggests that the novel nucleic acid quantification technology is sensitive, quantitative, and robust. It is a promising candidate for rapid microbe detection and quantification in routine laboratories.
In the future, this genomic sensor will be implemented in in situ platforms as a core analytical module with minor modifications, and could be easily accessible by oceanographers. Deployment of this microbial genomic sensor in the field will enable new scientific advances in oceanography and provide a possible solution for infectious disease detection.
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.
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.
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.