High turnover in the haematopoietic system is sustained by stem and progenitor cells, which divide and mature to produce the range of cell types present in the blood. This complex system has long served as a model of differentiation in adult stem cell systems and its study has important clinical relevance. Maintaining a healthy blood system requires regulation of haematopoietic cell fate decisions, with severe dysregulation of these fate choices observed in diseases such as leukaemia. As transcriptional regulation is known to play a role in this regulation, the gene expression of many haematopoietic progenitors has been measured. However, many of the classic populations are actually extremely heterogeneous in both expression and function, highlighting the need for characterising the haematopoietic progenitor compartment at the level of individual cells. The first aim of this work was to chart the single-cell transcriptional landscape of the haematopoietic stem and progenitor cell (HSPC) compartment. To build a comprehensive map of this landscape, 1,654 HSPCs from mouse bone marrow were profiled using single-cell RNA-sequencing. Analysis of these data generated a useful resource, and reconstructed changes in gene expression, cell cycle and RNA content along differentiation trajectories to three blood lineages. To investigate how single-cell gene expression can be used to learn about regulatory relationships, data measuring the expression of 41 genes (including 31 transcription factors) in 2,167 stem and progenitor cells were used to construct Boolean gene regulatory network models describing the regulation of differentiation from stem cells to two different progenitor populations. The inferred relationships revealed positive regulation of Nfe2 and Cbfa2t3h by Gata2 that was unique to differentiation towards megakaryocyte-erythroid progenitors, which was subsequently experimentally validated. The next study focused on investigating the link between transcriptional and functional heterogeneity within blood progenitor populations. Single-cell profiles of human cord blood progenitors revealed a continuum of lympho-myeloid gene expression. Culture assays performed to assess the functional output of single cells found both unilineage and bilineage output and, by investigating the link between surface marker expression and function, a new sorting strategy was devised that was able to enrich for function within conventional lympho-myeloid progenitor sorting gates. The final project aimed to study changes to the HSPC compartment in a perturbed state. A droplet-based single-cell RNA-sequencing dataset of 44,802 cells was analysed to identify entry points to eight blood lineages and to characterise gene expression changes in this transcriptional landscape. Mapping single-cell data from W41/W41 Kit mutant mice highlighted quantitative shifts in progenitor populations such as a reduction in mast cell progenitors and an increase towards more mature progenitors along the erythroid trajectory. Differential gene expression identified upregulation of stress response and a reduction of apoptosis during erythropoiesis as potential compensatory mechanisms in the Kit mutant progenitors. Together this body of work characterises the HSPC compartment at single-cell level and provides methods for how single-cell data can be used to discover regulatory relationships, link expression heterogeneity to function, and investigate changes in the transcriptional landscape in a perturbed environment.

A microfluidic device was created for single-cell capture and analysis using polydimethylsiloxane (PDMS) channels and a glass substrate to develop a microfluidic single-cell impedance sensor for cell diagnostics. The device was fabricated using photolithography to create a master mold which in turn will use soft lithography to create the PDMS components for constant device production. The commercial software, COMSOLTM Multiphysics, was used to quantify the fluid dynamics in shallow micro-channels. The device will be able to capture a cell and sequester it long enough to enable measurement of the impedance spectra that can characterize cell. The proposed device will be designed to capture a single cell and permit back-flow to flush out excess cells in the chamber. The device will be designed to use syringe pumps and the syringe-controlled channel will also be used to capture and release the cell to ensure cell control and device reusability. We hypothesize that these characteristics along with other proposed design factors will result in a unique microfluidic cell-capture device that will enable single-cell impedance sensing and characterization.

The goal of this project was to develop a series of nano platforms for single cell analysis and drug delivery. Nanoparticles are a promising option to improve our medical therapies by controlling biodistribution and pharmacokinetics of therapeutics. Nanosystems also offer significant opportunity to improve current imaging modalities. The systems developed during this thesis work can be foundations for developing advanced therapies for obesity and improving our fundamental understandings of single cell behavior. The first of the two systems we attempt to create was a drug delivery system that could selectively target adipose tissue to deliver uncoupling agents and drive browning of adipose tissue and associated weight loss. Protonophores have a history of significant toxic side effects in cardiac and neuronal tissues a recently discovered protonophore, but BAM-15, has been shown to have reduced cytotoxicity. We hypothesized that the altered biodistribution of BAM-15 encapsulated in a nanoparticle could provide systemic weight loss with minimized side effects. The second system developed utilized quantum dots to create a fluorescent barcode that could be repeatedly identified using quantitative fluorescent emission readings. This platform would allow for the tracking of individual cells, allowing repeat interrogation across time and space in complex multicellular environments. Ultimately this work demonstrates the process and complexity involved in developing nanoparticulate systems meant to interact with incredibly complex intracellular environments.

Denna projektrapport är avsedd att vara ett hjälpmedel för SiCell, en del av SciLifeLab Uppsala som ska bli Europas första plattform för enkelcellgenomik till hösten 2013. SiCell har bett projektgruppen om undersökningar gällande ett Laboratory Information Management System, LIMS. På svenska ett datahanteringsystem för laboratorier. Ett sådant system skulle kunna effektivisera SiCells verksamhet. Undersökningarna har resulterat i en kravspecifikation som ett LIMS för SiCell ska uppfylla och en sammanställning av tillgängliga mjukvaror som bäst uppfyller dessa krav. Screensaver, MISO och Gnomex är de tre gratisprogram med öppen källkod som hamnade högst upp i listan. Inget av dem uppfyller alla krav men med modifieringar av programmerare tros detta vara möjligt. SiCell bad också om lägre prioriterade undersökningar av några av de metoder som används inom plattformen. Cellysering, Alternativa amplifieringsmetoder och transkriptomik har undersökts av projektgruppen. Detta resulterade i en sammanställning av vilka alternativ som finns och vad som är under utveckling inom respektive område.

A micro-electrophysiological analysis system (-EPAS) using various microfabrication techniques for single cell study was developed. Conventional microfabrication techniques combined with plastic and polymer microfabrication techniques have been used to realize the system. The system is capable of performing patch clamp recording and whole cell electrical impedance spectroscopy (EIS) on a single cell. Methodologies for single cell manipulation were developed. The ion channel activities of primary cultured bovine chromaffin cells were measured in both the patch clamping mode and the whole cell EIS mode. Membrane capacitance of the chromaffin cell was calculated from these measurements. Increases in the capacitances were observed when certain ion channels were blocked using toxins. The dielectric properties of human breast cancer cell lines from different pathological stages were measured and compared to a normal human breast cell line in the whole cell EIS mode. The measured properties were correlated to the pathological stages of the breast cancer cell lines. Decreases in the membrane capacitances were observed for the more pathologically progressed cancer cell lines.

Most human organs consist of solid tissues. Most human disorders occur in solid tissues. No two cells are equivalent in native solid tissues as single cells widely vary in their biochemistry, specialization, and location. Yet, the fundamental limitations of solid-tissue processing and analysis have made it challenging to access the richness of molecular information in single cells of animal and human solid tissues. We have eliminated a set of limitations of solid-tissue processing and analysis. In this thesis, I first describe a new method for sampling single cells in live solid tissues. This method preserves the molecules of all molecular classes and thus fulfills the precondition for multiplexing within and across molecular classes. I then describe new analytical methods and strategies for massively multiplex analysis within and across molecular classes in each sampled single cell. Standard curves, the basis of analytical methods, can be constructed in all measurements and signals can be mapped to the corresponding quantities. Proof of principle experiments are presented. These methods will enable the quantification of the molecular mechanism of each sampled single cell in solid tissues by analytically measuring tens of proteins, transcripts and/or metabolites at once. By performing these measurements in human solid-tissue biopsies, we will be able to define a new category of diagnostic tests, to personalize single-cell pharmacology and to rapidly identify mechanistic biomarkers and drug targets.

A major unanswered question in neuroscience is whether there exists genomic variability between individual neurons of the brain, contributing to functional diversity or to an unexplained burden of neurologic disease. To address this question, we developed methods to amplify genomes of single neurons from human brains, achieving >80% genome coverage of single-cells and allowing study of a wide-range of somatic mutation types.

No description available.

Thesis (Ph. D.)--University of Washington, 2005. / Vita. Includes bibliographical references (leaves 136-140).

A fundamental challenge in biology is to understand the complex gene regulatory networks which control tissue development in the mammalian embryo, and maintain homoeostasis in the adult. The cell fate decisions underlying these processes are ultimately made at the level of individual cells. Recent experimental advances in biology allow researchers to obtain gene expression profiles at single-cell resolution over thousands of cells at once. These single-cell measurements provide snapshots of the states of the cells that make up a tissue, instead of the population-level averages provided by conventional high-throughput experiments. The aim of this PhD was to investigate the possibility of using this new high resolution data to reconstruct mechanistic computational models of gene regulatory networks. In this thesis I introduce the idea of viewing single-cell gene expression profiles as states of an asynchronous Boolean network, and frame model inference as the problem of reconstructing a Boolean network from its state space. I then give a scalable algorithm to solve this synthesis problem. In order to achieve scalability, this algorithm works in a modular way, treating different aspects of a graph data structure separately before encoding the search for logical rules as Boolean satisfiability problems to be dispatched to a SAT solver. Together with experimental collaborators, I applied this method to understanding the process of early blood development in the embryo, which is poorly understood due to the small number of cells present at this stage. The emergence of blood from Flk1+ mesoderm was studied by single cell expression analysis of 3934 cells at four sequential developmental time points. A mechanistic model recapitulating blood development was reconstructed from this data set, which was consistent with known biology and the bifurcation of blood and endothelium. Several model predictions were validated experimentally, demonstrating that HoxB4 and Sox17 directly regulate the haematopoietic factor Erg, and that Sox7 blocks primitive erythroid development. A general-purpose graphical tool was then developed based on this algorithm, which can be used by biological researchers as new single-cell data sets become available. This tool can deploy computations to the cloud in order to scale up larger high-throughput data sets. The results in this thesis demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the gene regulatory networks that underpin organogenesis. Rapid technological advances in our ability to perform single-cell profiling suggest that my tool will be applicable to other organ systems and may inform the development of improved cellular programming strategies.