Single cell analysis devices have become important tools to obtain unique information on cells to improve current medical techniques, such as tissue engineering, or diagnosis of cancer at an early stage. This thesis documents the development of a "cell cross flow system" (CFS), which aims to capture magnetically tagged (MT) cells from a heterogeneous population of cells, and array these cells in pre-determined locations using magnetic force. The CFS integrates a “magnetic single cell micro array” (MSCMA), and a gasket assembly to achieve this. Current single cell technology, relevant fluid and magnetic theory, CFS design process, finite element method (FEM) simulation, and cross flow experiments are detailed in this thesis. The CFS was successful in capturing MT Jurkat cells, and the experimental results were consistent with the FEM simulation analysis. It was found that the CFS was capable of capturing MT Jurkat cells up to a ratio of 1 to 103 (MT to non-magnetically tagged cells) using a cell concentration of 105 cells/mL. Although these results are promising, non-magnetically tagged Jurkat cells were found to adhere to the chip and could not be easily removed. Several recommendations were suggested for future iterations, including changing the gasket assembly design, optimizing the flow rate and cell concentration, and using smaller trap sizes for the MSCMA design.

INTRODUCTION: One important characteristic of solid tumors is heterogeneity at multiple levels of genetic and non-genetic organization. This can include gene mutations, epigenetic alterations, copy number changes, and chromosomal aberrations. Collectively, these alterations contribute as parts of a genome-defined system. Thus, when genetic information is passed from mother to daughter cell in the context of cancer evolution, in contrast to normal cellular processes, an altered system inheritance is often transmitted. When the genome of a somatic cell is highly unstable, such as during certain phases of cancer initiation and progression, many novel alterations to the genome can be introduced in a short timeframe, effectively resulting in the macro-evolution of the somatic cell population (i.e., through the transition stages of cancer, including transformation, metastasis, and drug resistance). Unfortunately, these continually introduced, non-clonal alterations to the cell’s genetic information have often been described as background “noise” that does not function significantly in cancer. Rather, the driving force of cancer has largely been attributed to the accumulation of gene mutations in several key, driver genes. Despite the presumed significance of these driver genes by the gene mutation and clonal evolutionary theories of cancer, recent sequencing efforts have failed to identify common driver genes in the majority of cancer types. Based on this fact, and on the overwhelming presence of non-clonal alterations at multiple levels of organization in the cells comprising tumors, the paradigm of cancer research requires re-examination. A better understanding of genome-level heterogeneity is necessary, as the genome, rather than individual genes, defines system boundaries and unifies the diverse individual molecular mechanisms of cancer through their contribution to major evolutionary transitions. Because inheritance is traditionally defined as a precise process of relaying bio-information with extreme low frequencies of errors, it is challenging to explain how genetics work in cancer evolution. It is thus timely to consider that potentially novel processes of inheritance occur in many types of cancer. The maintenance of a massive extent of multi-level heterogeneity in the cells of solid tumors over generations suggests that a less precise process is taking place. We have described this with a new term, “fuzzy inheritance,” wherein a range of variants, rather than specific variants (such as specific gene mutations or chromosomal aberrations), is recapitulated in the cell division process. This study aimed to elucidate the mechanism of fuzzy inheritance by examining the relationship between genome instability-linked karyotypic heterogeneity and growth heterogeneity, based on single-cell analysis of an in vitro cell culture model. By demonstrating that increased genome-level heterogeneity is reflected by increased and more variable levels of growth heterogeneity, it was hoped to establish that fuzzy inheritance correctly explains the maintenance of high levels of heterogeneity in these somatic cell populations. An example of this phenomenon was also studied in giant cancer cells, as they undergo division processes which appear to contribute to and facilitate genome instability. METHODS: To examine these concepts, various cellular profiling methods were used, including in-situ cell growth, cellular morphological comparison, and karyotype analysis. We first quantified the extent of variation in the growth rates of single cells; by selecting the fastest- and slowest-growing colonies from the parent population, and examining the extent to which growth heterogeneity was passed in subsequent generations of cells, the correlation between genome-level heterogeneity (as reflected by the karyotype) and growth heterogeneity was determined. We then examined an extreme example of fuzzy inheritance, wherein giant cancer cells containing massive amounts of DNA undergo extremely abnormal cell division events, yielding many normal-sized daughter cells with genomes significantly different from those of both the parent cell and other daughter cells. By studying the frequency and other aspects of these cells in two unequally stable cell lines, we sought to gain insight on one specific mechanism of fuzzy inheritance. RESULTS: The data suggested that fuzzy inheritance can be demonstrated in multiple cell culture models. The extent and variability of karyotypic heterogeneity was reflected by those of growth heterogeneity, indicating the karyotype’s importance in facilitating cancer evolutionary processes. Moreover, the cells with giant nuclei can generate diverse genome-level heterogeneity. DISCUSSION: Because fuzzy inheritance allows for the less precise passage of bio-information over generations in cancer cell populations, and for the effective introduction of numerous alterations to the genome in often brief spans of time, the cell population can constantly increase its evolutionary potential, which is essential for the major transition steps of cancer evolution. The mechanism of fuzzy inheritance should be explored further, due to its clear importance in the processes underlying cancer initiation, progression, and drug resistance.

Sir Alec Jeffreys was the first to describe human identification with deoxyribonucleic acid (DNA) in his seminal work in 1985 (1); the result was the birth of forensic DNA analysis. Since then, DNA has become the primary substance used to conduct human identification testing. Forensic DNA analysis has evolved since the work of Jeffreys and now incorporates the analysis of 15 to 24 STR (short tandem repeat) locations, or loci (2-4). The simultaneous amplification and subsequent electrophoresis of tens of STR polymorphisms results in analysis that are highly discriminating. DNA target masses of 0.5 to 2 nanograms (ng) are sufficient to obtain a full STR profile (4); however, pertinent information can still be obtained if low copy numbers of DNA are collected from the crime scene or evidentiary material (4-9). Despite the sensitivity of polymerase chain reaction (PCR) - capillary electrophoresis (CE) based technology, low copy DNA signal can be difficult to interpret due to the preponderance of low signal-to-noise ratios. Due to the complicated nature of low template signal, optimization of the DNA laboratory process such that high-fidelity signal is regularly produced is necessary; studies designed to effectively hone in on optimized laboratory conditions are presented herein. The STR regions of a set of samples containing 0.0078 ng of DNA were amplified for 29 cycles; the amplified fragments were separated using two types of CE platforms: an ABI 3130 Genetic Analyzer and an ABI 3500 Genetic Analyzer. The result is a genetic trace, or electropherogram (EPG), comprised of three signal components that include noise, artifact, and allele. The EPGs were analyzed using two peak detection software programs. In addition, a tool, termed Simulating Evidentiary Electropherograms (SEEIt) (10, 11), was utilized to simulate EPG signal obtained when one copy of DNA is processed through the forensic pipeline. SEEIt was parameterized to simulate data corresponding to two laboratory scenarios: the amplification of a single copy of DNA injected on an ABI 3130 Genetic Analyzer and on an ABI 3500 Genetic Analyzer. In total, 20,000 allele peaks and 20,000 noise peaks were generated for each CE platform. Comparison of simulated and experimental data was used to elucidate features that are difficult to ascertain by experimental work alone. The data demonstrate that experimental signal obtained with the ABI 3500 platform results in signal that is, on average, a factor of four larger than signal obtained from the ABI 3130 platform. When a histogram of the signal is plotted, a multi modal distribution is observed. The first mode is hypothesized to be the result of noise, while the second, third, etc. modes are the signal obtained when one, two, etc. target DNA molecules are amplified. By evaluating the data in this way, full signal resolution between noise and allelic signal is visualized. Therefore, this methodology may be used to: 1) optimize post-PCR laboratory conditions to obtain excellent resolution between noise and allelic signal; and 2) determine an analytical threshold (AT) that results in few false detections and few cases of allelic dropout. A χ2 test for independence of the experimental signal in noise positions and the experimental signal within allele positions < 12 relative fluorescence units (RFU), i.e. signal in the noise regime, indicate the populations are not independent when sufficient signal-to-noise resolution is obtained. Once sufficient resolution is achieved, optimized ATs may be acquired by evaluating and minimizing the false negative and false positive detection rates. Here, a false negative is defined as the non-detection of an allele and a false positive is defined as the detection of noise. An AT of 15 RFU was found to be the optimal AT for samples injected on the ABI 3130 for at least 10 seconds (sec) as 99.42% of noise peaks did not exceed this critical value while allelic dropout was kept to a minimum, 36.97%, at this AT. Similarily, in examining signal obtained from the ABI 3500, 99.41% and 99.0% of noise fell under an AT of 50 RFU for data analyzed with GeneMapper ID-X (GM) and OSIRIS (OS), respectively. Allelic dropout was 36.34% and 36.55% for GM and OS, respectively, at this AT.

abstract: 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. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2017

La microscopie par résonance de plasmon de surface (SPR) à couplage par prisme a vu le jour à la fin des années 60. Le principal avantage de cette technique d'imagerie optique réside dans sa très grande sensibilité à de faibles variations d'indice optique ou d'épaisseurs à la surface d'un métal. De ce fait, le suivi d'interactions biologiques peut se faire en temps réel sans avoir recours à l'utilisation de marqueurs fluorescents ou enzymatiques. Depuis plus de 30 ans, la microscopie SPR s'est imposée comme la technique de référence de biodétection sans marquage. Ses champs d'application vont de la détermination de constantes d'affinité à la détection de bactéries pathogènes, en passant par la biologie cellulaire. Jusqu'à présent, on pensait la résolution spatiale limitée par la longueur de propagation des plasmons de surface. Or, de nombreux exemples ne corroborent pas cette hypothèse. Dans cette thèse, nous montrons qu'à ce phénomène de propagation se rajoute des aberrations optiques induites par l'utilisation d'un prisme pour coupler la lumière et les plasmons de surface. Nous expliquons ainsi pourquoi les résolutions expérimentales étaient souvent bien moins bonnes que celles attendues. Par l'analyse de la formation des images et la quantification des aberrations, nous aboutissons à deux nouvelles configurations optiques optimisées pour la résolution. Nous analysons ensuite quel métal offre le meilleur compromis entre longueur de propagation et sensibilité. Expérimentalement, nous obtenons une résolution comprise entre 1,5 et 4 μm suivant la direction, sur des champs de vision de plusieurs mm2, et ce, avec une sensibilité standard en biodétection. Nous sommes ainsi en mesure d'observer simultanément plusieurs milliers de cellules individuelles, eucaryotes et procaryotes. Finalement, nous développons un prototype dédié au suivi en temps réel de sécrétions de protéines par des cellules immunitaires. Les limites de la microscopie SPR et les solutions qui permettraient de faire aboutir ce type d'étude sont examinées. Des études préliminaires sont aussi menées sur l'amélioration de la détection de bactéries. / Prism-based surface plasmon resonance (SPR) microscopy is an optical imaging technique invented in the late 60s'. Its main advantage lies in its high sensitivity to optical index or thickness variations at a metal surface. Therefore, the monitoring of biological reactions can be performed in real-time without labeling agent such as fluorescence or enzymes. Over the last 30 years, SPR microscopy has become the major technique in label-free biodetection. The field of application range from the determination of affinity constant in biochemistry to the detection of pathogenic bacteria via cellular biology. Until now, the propagation length of the surface plasmons has been considered as the spatial resolution limit. However, many examples do not support this statement. In this PhD thesis, we demonstrate that the resolution is also limited by optical aberrations induced by the prism used to couple light and surface plasmons. Thus, we are able to explain why the experimental resolution was usually worse than the predicted one. The analysis of the image formation and the quantification of aberrations lead us to suggest two new optical configurations optimized for resolution. We also analyze which metal exhibits the better trade-off between propagation length and sensitivity. Experimentally, we obtain a resolution between 1.5 and 4 μm depending on the direction, on field-of-view up to several mm2, and with a standard sensitivity for biodetection (monolayer of DNA). We are then able to observe simultaneously several thousands of individual eukaryote and prokaryote cells. Finally, we develop a prototype dedicated to the real-time monitoring of protein secretion by immune cells. The limits of SPR microscopy and the solutions which could allow this kind of study are discussed. Preliminary results on the improvement of bacterial detection are also presented.

In this dissertation, advances in the fields of Photonics, and Plasmonics, and specifically, single cell analysis and waveguide sensing will be addressed. The first part of the dissertation is on Finite Difference Time Domain (FDTD) optimization and experimental demonstration of a nano-scale instrument that allows sensing at the cellular and subcellular levels. A new design of plasmonic coupler into a nanoscale waveguide is proposed and optimized using FDTD simulations. Following this, a subcellular nanoendoscope that can locally excite fluorescence in labelled cell organelles and collect the emitted fluorescent light for detailed spectrum analysis is fabricated and tested. The nanoendoscope has a sharp tapered tip of diameter ~ 50 nm that permits safe insertion into the cell that was confirmed by a number of viability experiments. FDTD analysis demonstrated that, with an optimized nanoendoscope taper profile, light emission and collection was very local. Thus, signal detection could be used for nano-photonic sensing of proximity of fluorophores. In further experiments, fluorescent signals were collected from individual organelles of living cells including: the nucleus of Acridine orange labelled human fibroblast cells, the nucleus of Hoechst stained live liver cells and the mitochondria of MitoTracker Red labelled MDA-MB-231 cells. In addition, this endoscope was inserted into a live organism, the nematode Caenorhabditis elegans, and in- vivo fluorescence signal was collected. Second, an innovative single step fabrication method of low loss polysilicon waveguides was developed as a potential platform for a number of photonic sensors. Optimization of a capacitively coupled plasma etching for the fabrication of a polysilicon waveguide with smooth sidewalls and low optical loss was demonstrated. A detailed experimental study on the influences of RF plasma power and chamber pressure on the roughness of the sidewalls of waveguides was conducted and waveguides were characterized using a scanning electron microscope. It was demonstrated that optimal combination of pressure (30 mTorr) and power (150 W) resulted in the smoothest sidewalls. The optical losses of the optimized waveguide were 4.1± 0.6 dB/ cm. Finally, an on-chip nanophotonic sensor for continuous blood coagulation analysis was proposed. The system was simulated using three-dimensional FDTD software. At first, the noise due to the presence of cells was calculated. Next, the design of a waveguide cladding-based filtering structure for elimination of the noise from cells was proposed and significantly decreased noise level was theoretically demonstrated.

No description available.

京都大学 / 新制・課程博士 / 博士(医学) / 甲第24499号 / 医博第4941号 / 新制||医||1064(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 伊藤 貴浩, 教授 中島 貴子, 教授 藤田 恭之 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

This Master’s Thesis project consists of the research, design, and fabrication of a system that could perform broadband impedance measurements (1kHz-20Mhz) of single cells using National Instruments Labview data acquisition and programming in coordination with a single cell capture device. Presented first is the background information on cells and their electrical properties, along with background in micro-total-analysis systems as well as impedance spectroscopy. Experimental Methods are then discussed for the electrode design, cellular modeling in COMSOL, fabrication methods, and Labview 8.0 Set-up and programming. Measurements were performed using the single-cell capture device on saline, yeast cells, and a polysterene bead. Analysis of the impedance data showed a clear visual and statistically significant difference between live yeast, the bead, and saline. A comparison of live yeast cells to nutrient-starved yeast cells was also performed and a distinct difference in spectra was observed.

With the rapid progress of next-generation sequencing (NGS) technologies, new tools and methods have emerged to investigate the transcriptomics of various organisms. RNA sequencing (RNA-seq) employs NGS to evaluate the presence and abundance of RNA transcripts in biological samples. This technique offers a comprehensive snapshot of the RNA dynamics within cells. With the ability to profile the entire transcriptome of organisms rapidly and accurately, RNA-seq has become the state-of-the-art method for transcriptome profiling, surpassing the traditional microarray approach. Single-cell RNA sequencing (scRNA-seq) was introduced in 2009 to profile the single-cell gene expression in highly heterogeneous samples such as brain tissue and tumors. The advancement of scRNA-seq technologies enables the in-depth transcriptomic study in each cell subtype. When selecting an scRNA-seq method, researchers must weigh the trade-off between profiling more single cells versus obtaining more comprehensive transcripts per cell, while considering the overall costs. The throughput of full-length scRNA-seq methods is usually lower, as each single cell needs to be processed separately to produce scRNA-seq libraries. However, full-length methods enable the researchers to investigate the splicing variants and allele-specific expression. Non-full-length methods only capture the 3' or 5' ends of transcripts, which limits their application in isoform detection, but as cells are pooled after barcoding for cDNA synthesis, the throughput is 2–3 orders of magnitude higher than full-length methods. We developed a droplet-based platform for full-length single-cell RNA-seq, which enabled the efficient recovery of full-length mRNA from individual cells in a high-throughput manner. The developed platform can process ~8,000 single cells within 2 days and detect ~20% more genes compared to Drop-seq. Besides scRNA-seq technology development, we also applied a low-input RNA-seq method to study the transcriptomics in different biological samples. When handling precious biological samples, a low-input method is necessary to profile the transcriptome of homogeneous cell populations. We first studied the epigenomic and transcriptomic regulations in colorectal cancer (CRC) using MOWChIP-seq, a low-input high-throughput method, in conjunction with our low-input RNA-seq approach. Fusobacterium nucleatum (Fnn) is closely related to the progression of cancers like CRC and pancreatic cancer. However, the molecular mechanisms of how Fnn adjusts the tumor microenvironment (TME) and leads to poor clinical outcomes are still unclear. In this in-vitro study, we characterized how hypoxia, an important TME ignored by previous research, facilitates Fnn infection of CRC and corresponding alterations of global epigenome and transcriptome. We infer that hypoxia has similar effects as Fnn infection alone on the CRC cells. The Fnn infection under hypoxia further boosts the proliferation and progression of CRC. We then applied our low-input RNA-seq method to study brain neuroscience and immunology. Psychedelics like DOI show promising clinical efficacy in patients with psychiatric conditions. Although psychedelics exhibit rapid antidepression action and long-lasting effectiveness compared to conventional treatment, their acute psychotic symptoms and potential for drug abuse discourage their application in clinical practice. In this case, it is important to comprehend the molecular mechanisms responsible for psychedelics' clinical efficacy. This understanding can pave the way for the development of improved treatments that do not rely on psychedelics. After profiling the transcriptome of mouse brain samples exposed to psychedelics with different post-exposure times, we concluded that the psychedelic-induced transcriptomic variations are more transient than epigenomic changes. In the second brain neuroscience project, we first applied 3-color FACS sorting to differentiate four neuron and non-neuron subtypes in human postmortem prefrontal cortex tissues. Then we profiled the gene expression of the four subtypes and validated the FACS sorting by examining the expression of marker genes. Differentially expressed genes between each subtype and the others were extracted and proceeded to gene ontology analysis. We identified unique altered biological pathways related to each subtype. The immunology research focuses on revealing the difference between low-grade inflammation and monocyte exhaustion, as well as the unique biological pathways they regulate. Therefore, we profiled the transcriptome of bone marrow-derived monocytes stimulated by PBS control, a low- or high-dose LPS. In addition to wild-type mice, we also included TRAM-deficient and IRAK-M-deficient mice. We concluded that low-dose LPS specifically regulates the TRAM-dependent pathway of TLR4 signaling, and high-dose LPS exclusively upregulates exhaustion markers by impacting metabolic and proliferative pathways. / Doctor of Philosophy / Transcriptomics is the comprehensive study of RNA transcripts derived from an organism's genome. RNA plays a vital role in maintaining the fundamental functions of cells and organisms. In eukaryotes, the genetic information stored in the DNA of cells is transferred to messenger RNA (mRNA) molecules through a process called transcription. These mRNA molecules serve as a bridge between DNA and proteins, as they carry the instructions encoded in genes to ribosomes for protein synthesis. Studying mRNA transcripts reveals various cellular mechanisms and their impact on overall organism function, gene regulation, and disease pathways. With the aid of next-generation sequencing, various RNA-seq approaches have been developed to study mRNA transcripts quantitatively in the past decades. To better understand the gene expression regulations in biological samples, we first applied bulk RNA-seq to profile the transcriptome of various samples under different conditions. Our in-house bulk RNA-seq protocol has been proven to be both high-performance and cost-effective compared to commercial kits. To better understand cellular diversity and uncover rare cell types in heterogeneous biological samples, we developed a droplet-based scRNA-seq platform that can recover full-length mRNA transcripts in a high throughput manner. It can profile the transcriptome of thousands of single cells within two days. It combines the advantages of the droplet-based scRNA-seq method (high throughput) and the well plate-based scRNA-seq method (full-length mRNA recovery).