Exploring the regulation of human neural precursor cell differentiation using arrays of signaling microenvironments

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Yoav Soen¹, Akiko Mori², Theo D Palmer² & Patrick O Brown^1,3

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Synopsis

The development of the nervous system depends on spatially and temporally programmed differentiation of precursors into specific neurons and glial cells. Understanding the regulation of precursor cell differentiation in complex microenvironments is a major challenge of developmental biology. However, despite remarkable progress that has been made in elucidating individual pathways and cell-intrinsic factors, we are still a long way from an integrative understanding of how multiple pathways interact with one another and with cell-intrinsic mechanisms to specify cellular fate and function.

To systematically investigate mechanisms and logic by which extracellular signals specify the fate of human neural precursor cells, we developed and applied a signaling microenvironment microarray paradigm. This approach is based on parallel exposure of multi-potent neural progenitor cells to a diverse array of defined signaling molecules (e.g. extracellular matrix components, morphogens, and other signaling proteins) presented individually and in combinations. Cells were cultured in the arrayed signaling microenvironments for varying periods, then analyzed by a scanning microscope to provide a high-throughput quantitative analysis of multiple phenotypic outcomes at single cell resolution. Ensemble average responses to each microenvironment were determined by averaging over all the cells exposed to the same signaling combination, and higher level analyses were performed using novel computational tools for interpreting data with the scale and complexity produced by this experimental paradigm. The entire approach is very general. It can be applied to a wide range of cell types (different types of stem cells, tumor cells, immune cells, etc.) and can be used to study a broad spectrum of responses to diverse variations in a cell's signaling microenvironment.

In this experiment, human neural precursors, capable of differentiating into neurons or glial cells, were captured on these printed signaling microarrays and cultured for several days under defined, differentiation conditions. Quantitative cell by cell analysis revealed consistent and striking effects of some of these signals on the differentiation of primary human neural stem cells (Figure 2A). We found that co-stimulation with two factors, Wnt and Notch, could maintain the cells in an undifferentiated-like, proliferative state, whereas a third factor, bone morphogenetic protein 4, induced an 'indeterminate' differentiation phenotype characterized by simultaneous expression of glial and neuronal markers. Multi-parameter analysis of responses segregated all the various signaling combinations into four main groups based on their characteristic effects (Figure 5): (1) combinations that promoted neurogenesis, (2) combinations that promoted gliogenesis, (3) combinations that prevented both, and (4) combinations that elevated both neural and glial markers in the same cell (an indeterminate differentiation phenotype).

Figure 2

Microenvironment-dependent differentiation and morphology. Human neural precursors were captured and cultured on a printed Ln/ligand array for 70 h under differentiation-promoting conditions. Following the differentiation period, the cells were fixed and counterstained with GFAP (red), BrdU (blue), TUJ1 (green), and DAPI (not shown). (A) A small portion of the array with 16 different microenvironments each containing a few hundred cells. The balance between TUJ1 and GFAP staining on the reference Ln spot (top left) was skewed toward preferential expression of the neuronal marker TUJ1. This balance was shifted in a spot-dependent manner by some of the signal-containing spots. In particular, spots containing CNTF (bottom right) and Notch ligands (right panels on the 2nd and 3rd rows) led to a dramatic shift toward increased GFAP proportions, suggesting a gliogenic response to Notch stimulation. Dilution series of Jagged-1 (2nd row panels) revealed dose-dependent response to Notch stimulation. Combination of some gliogenic signals (e.g. Jagged-1 and CNTF) led to further increase in the gliogenic response. A smaller shift toward increased neuronal proportions was observed on Wnt-3A spots. (B) Color inverted images demonstrating spot-dependent morphological differences. Cells that were exposed to a combination of Wnt-3A and a Notch ligand (second spot from the top) exhibited longer and more elaborated processes compared to Ln alone (top). Typical spot diameter was 400 m. Fields of view in all panels are identical in size. Wnt-3A-containing spots consistently larger.

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Figure 5

A color-coded map connecting external stimulation (in rows) to differentiation-related phenotypes (columns). Columns display relative fractions of cells measured in each of nine regions of the TUJ1-GFAP 'differentiation plane' representing low, medium, and high staining intensity for each marker. Each row corresponds to a particular signaling microenvironment. Ensemble average fractions of cells were measured in two array experiments, averaged across experiments, and normalized by the corresponding values on spots containing Ln alone. Normalized values were log-transformed and each column was scaled to a unit standard deviation. Red and green colors represent higher and lower than Ln values, respectively. Rows and columns were clustered using Pearson correlation as a similarity metric. Signaling combinations that induced a similar TUJ1-GFAP distribution profile were clustered together, resulting in four main groups of influence: (i) gliogenic-like (red-labeled), (ii) neurogenic-like (green), (iii), undifferentiated-like (light blue), and (iv) indeterminate differentiation (orange).

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To examine differentiation responses following simultaneous exposure to potentially conflicting signals (e.g. neurogenic and gliogenic signals), we compared the responses to individual signals with responses to the combined signals. We found that combinations of signals often promoted responses different from the effects of the individual signals. In some, however, the response to one of the signals appeared to dominate over the response to the others. Interestingly, some of the observed dominance relationships were complex—with the responses to different signals dominating with respect to different response parameters. Such dominance relations may reflect a cell-intrinsic system for robust specification of responses in complex microenvironments.

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