Single-cell copy number variation detection

Detection of chromosomal aberrations from a single cell by array comparative genomic hybridization (single-cell array CGH), instead of from a population of cells, is an emerging technique. However, such detection is challenging because of the genome artifacts and the DNA amplification process inherent to the single cell approach. Current normalization algorithms result in inaccurate aberration detection for single-cell data. We propose a normalization method based on channel, genome composition and recurrent genome artifact corrections. We demonstrate that the proposed channel clone normalization significantly improves the copy number variation detection in both simulated and real single-cell array CGH data

Micromachining of Single Cell Array for Oxygen Consumption Rate Analysis

The Oxygen Consumption Rate of biological cells is an important parameter of cellular metabolism. In order to study the behaviour of cell populations, it becomes necessary to capture and store them in one location for analysis. Individual cell analysis within a cell group can provide useful information about the average response of the cell group, as well as identify outliers. Such analysis can be used to identify different groups of cells based on their oxygen levels. However, characterizing the individual cell response within a cell group is challenging since cell dimensions are on the order of a few micrometers. Conventional techniques, such as microtiter plates and flow cytometry, are unable to offer both the high temporal and the high spatial resolution that is required to characterize individual cells. Modern micromachining and microfabrication techniques, on the other hand, allow for the creation of devices that have dimensions that are on the order of a few micrometers. Through a series of thin film deposition, photolithography and thin film etching techniques, it is possible to create single cell trapping structures whose dimensions are only slightly larger than that of individual cells. The aim of this thesis is to create a process flow in order to fabricate such structures on a single crystalline silicon substrate using available micromachining techniques

Micromachining of Single Cell Array for Oxygen Consumption Rate Analysis

The Oxygen Consumption Rate of biological cells is an important parameter of cellular metabolism. In order to study the behaviour of cell populations, it becomes necessary to capture and store them in one location for analysis. Individual cell analysis within a cell group can provide useful information about the average response of the cell group, as well as identify outliers. Such analysis can be used to identify different groups of cells based on their oxygen levels. However, characterizing the individual cell response within a cell group is challenging since cell dimensions are on the order of a few micrometers. Conventional techniques, such as microtiter plates and flow cytometry, are unable to offer both the high temporal and the high spatial resolution that is required to characterize individual cells. Modern micromachining and microfabrication techniques, on the other hand, allow for the creation of devices that have dimensions that are on the order of a few micrometers. Through a series of thin film deposition, photolithography and thin film etching techniques, it is possible to create single cell trapping structures whose dimensions are only slightly larger than that of individual cells. The aim of this thesis is to create a process flow in order to fabricate such structures on a single crystalline silicon substrate using available micromachining techniques

Rapid and label-free identification of single leukemia cells from blood in a high-density microfluidic trapping array by fluorescence lifetime imaging microscopy.

The rapid screening and isolation of single leukemia cells from blood has become critical for early leukemia detection and tumor heterogeneity interrogation. However, due to the size overlap between leukemia cells and the more abundant white blood cells (WBCs), the isolation and identification of leukemia cells individually from peripheral blood is extremely challenging and often requires immunolabeling or cytogenetic assays. Here we present a rapid and label-free single leukemia cell identification platform that combines: (1) high-throughput size-based separation of hemocytes via a single-cell trapping array, and (2) leukemia cell identification through phasor approach and fluorescence lifetime imaging microscopy (phasor-FLIM), to quantify changes between free/bound nicotinamide adenine dinucleotide (NADH) as an indirect measurement of metabolic alteration in living cells. The microfluidic trapping array designed with 1600 highly-packed addressable single-cell traps can simultaneously filter out red blood cells (RBCs) and trap WBCs/leukemia cells, and is compatible with low-magnification imaging and fast-speed fluorescence screening. The trapped single leukemia cells, e.g., THP-1, Jurkat and K562 cells, are distinguished from WBCs in the phasor-FLIM lifetime map, as they exhibit significant shift towards shorter fluorescence lifetime and a higher ratio of free/bound NADH compared to WBCs, because of their glycolysis-dominant metabolism for rapid proliferation. Based on a multiparametric scheme comparing the eight parameter-spectra of the phasor-FLIM signatures, spiked leukemia cells are quantitatively distinguished from normal WBCs with an area-under-the-curve (AUC) value of 1.00. Different leukemia cell lines are also quantitatively distinguished from each other with AUC values higher than 0.95, demonstrating high sensitivity and specificity for single cell analysis. The presented platform is the first to enable high-density size-based single-cell trapping simultaneously with RBC filtering and rapid label-free individual-leukemia-cell screening through non-invasive metabolic imaging. Compared to conventional biomolecular diagnostics techniques, phasor-FLIM based single-cell screening is label-free, cell-friendly, robust, and has the potential to screen blood in clinical volumes through parallelization

New Array Approaches to Explore Single Cells Genomes

Microarray analysis enables the genome-wide detection of copy number variations and the investigation of chromosomal instability. Whereas array techniques have been well established for the analysis of unamplified DNA derived from many cells, it has been more challenging to enable the accurate analysis of single cell genomes. In this review, we provide an overview of single cell DNA amplification techniques, the different array approaches, and discuss their potential applications to study human embryos

High resolution array-CGH analysis of single cells

Heterogeneity in the genome copy number of tissues is of particular importance in solid tumor biology. Furthermore, many clinical applications such as pre-implantation and non-invasive prenatal diagnosis would benefit from the ability to characterize individual single cells. As the amount of DNA from single cells is so small, several PCR protocols have been developed in an attempt to achieve unbiased amplification. Many of these approaches are suitable for subsequent cytogenetic analyses using conventional methodologies such as comparative genomic hybridization (CGH) to metaphase spreads. However, attempts to harness array-CGH for single-cell analysis to provide improved resolution have been disappointing. Here we describe a strategy that combines single-cell amplification using GenomePlex library technology (GenomePlex(®) Single Cell Whole Genome Amplification Kit, Sigma-Aldrich, UK) and detailed analysis of genomic copy number changes by high-resolution array-CGH. We show that single copy changes as small as 8.3 Mb in single cells are detected reliably with single cells derived from various tumor cell lines as well as patients presenting with trisomy 21 and Prader–Willi syndrome. Our results demonstrate the potential of this technology for studies of tumor biology and for clinical diagnostics