Figure 1.
Overview of the multi-scale Imaging and Informatics pipeline.
(A) Our system enables researchers to analyze intercellular dynamics in hES cells by structuring relationships between cells within a colony; between cells and the colony they belong to; and from one colony to another. (B) The window of the main GUI controlling the automated image acquisition software. (C) A daughter window of the GUI facilitating pre-scanning of the slide and selection of regions. (D) A workflow to obtain image-derived features from single cells, while placing them in the context of the colony they belong to. Thus, the pipeline involves a multi-scale segmentation of the colonies within the sample, and the cells within the colonies. Each cell not only has a physical address within the colony, but is linked with colony-wide properties, such as the size and shape of the colony it is derived from.
Figure 2.
Spatial enrichment of G1 and G2 phase cells in colonies.
(A) Illustration of the distance transform applied to cells in all colonies. Outside of the boundaries of the colony, the distance from edge is “0”, and within the border of the colony, the distance ranges between 0 and the maximum radius of the colony. (B) Frequencies of cells as a function of distance from edge for the G1 (red), S (magenta), and G2 (blue) and M (green) subpopulations. Error bars indicate the 95% confidence interval based on 1000 bootstrap samples. Abscissa tick marks indicate the distance intervals from which the population and bootstrap frequencies were calculated. Each distance interval contains approximately 1500 cells. The data points are located halfway in between each interval. The frequencies at each point add up to 1. Of note is the statistically significant peak in the G2/M subpopulation at 25 microns. (C) A cellular map illustrating the periphery (blue), Cell Layer 1 (green), Cell Layer 2 (red), and Cell Layer 3 (blue) subpopulations. (D) Distributions of cell cycle phases for each cell layer across many colonies. There is a significant enrichment of G2 cells in Cell Layer 1 relative to Cell Layers 2 and 3.
Figure 3.
Cells in different regions of colonies respond differently to DNA damage.
(A–C) In order to investigate regional heterogeneity, colonies of differentiated and NCS-treated cells were computationally divided into windows, which were then classified according to the density of cells contained. 25 colonies were divided into 164 windows, containing a total of 13,133 cells. As demonstrated, high cell density regions (purple) tend to have low Oct4 (B), and reduced induction of cPARP (C) upon DNA damage, than low (blue) and mixed (red) density regions. (D) Oct4 distribution of the cells in the above classified subregions. Black line shows the distribution of all cells. (E) Proportion of Oct4 positive cells in each subpopulation. (F) proportion of cPARP positive cells.
Figure 4.
Large-scale mapping of single-cell heterogeneity in Oct4 mRNA expression.
(A) Quantification of Oct4 mRNA level with smFISH in a hES cell. Top: raw image; Bottom: segmented FISH spots. (B) Segmentation of Oct4 spots in hES cells with nuclear boundaries in red, cell boundaries in yellow, and colonies boundaries in green. (C) Method for setting smFISH spot detection thresholds to ensure spot detection consistency across adjacent fields in a large region. (D) Reconstruction of Oct4 mRNA levels across 6 contiguous fields of view using the spot matching procedure detailed in the main text. Each circle represents an individual cell and circle color denotes the expression level of Oct4. Overall, Oct4 levels diminish through differentiation, although small clusters of cells with elevated Oct4 levels can be observed after 2 days of differentiation.