Abstract
Embryonic stem cells (ESCs) are characterized by two remarkable peculiarities: the capacity to propagate as undifferentiated cells (self-renewal) and the ability to differentiate in ectoderm, endoderm, and mesoderm derivatives (pluripotency). Although the majority of ESCs divide without losing the pluripotency, it has become evident that ESC cultures consists of multiple cell populations highlighted by the expression of early germ lineage markers during spontaneous differentiation. Hence, the identification and characterization of ESCs subpopulations represents an efficient approach to improve the comprehension of correlation between gene expression and cell specification status. To study markers of ESCs heterogeneity, we developed an analysis pipeline which can automatically process images of stem cell colonies in optical microscopy. The question we try to address is to find out the statistically significant preferred locations of the marked cells. We tested our algorithm on a set of images of stem cell colonies to analyze the expression pattern of the Zscan4 gene, which was an elite candidate gene to be studied because it is specifically expressed in subpopulation of ESCs. To validate the proposed method we analyzed the behavior of control genes whose pattern had been associated to biological status such as differentiation (EndoA), pluripotency (Pou5f1), and pluripotency fluctuation (Nanog). We found that Zscan4 is not uniformly expressed inside a stem cell colony, and that it tends to be expressed towards the center of the colony, moreover cells expressing Zscan4 cluster each other. This is of significant importance because it allows us to hypothesize a biological status where the cells expressing Zscan4 are preferably associated to the inner of colonies suggesting pluripotent cell status features, and the clustering between themselves suggests either a colony paracrine effect or an early phase of cell specification through proliferation. Also, the analysis on the control genes showed that they behave as expected.
Highlights
Over the past few years it has become evident that in vitro mouse Embryonic stem cells (ESCs) cultures consist of multiple cell populations [1] with different degrees of pluripotency [2,3]
We implemented the proposed approach in MATLAB and tested it on a set of 57 optical microscopy images obtained from culture of ESCs followed by in situ hybridization
We presented a novel algorithm capable of automatically identifying the location of cells expressing a gene of interest into stem cell colonies and of executing automatic quantitative measurements followed by a statistical analysis
Summary
Over the past few years it has become evident that in vitro mouse ESC cultures consist of multiple cell populations [1] with different degrees of pluripotency [2,3]. The culture heterogeneity is mainly to be addressed to ESC responsiveness to paracrine effects and cell-to-cell interaction. This colony-relative cell position analysis may result very useful to set up biological hypotheses that may lead to the understanding of cell cycle, cell differentiation, and cell meta-stable status, following the location pattern inside the colony itself. To segment the colonies we use a simplified, single contour, two-dimensional version of the Enhanced Interaction Model [17] presented in [14] where an energy functional EI associated to the image is defined as cf (0) cb (0) lf lb rB hB s w rD rm rM s magnif. To segment the colonies we use a simplified, single contour, two-dimensional version of the Enhanced Interaction Model [17] presented in [14] where an energy functional EI associated to the image is defined as cf (0) cb (0) lf lb rB hB s w rD rm rM s magnif. resize
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