Transdifferentiation of pancreatic cells by loss of contact-mediated signaling

Abstract

Background: Replacement of dysfunctional β-cells in the islets of Langerhans by transdifferentiation of pancreatic acinar cells has been proposed as a regenerative therapy for diabetes. Adult acinar cells spontaneously revert to a multipotent state upon tissue dissociation in vitro and can be stimulated to redifferentiate into β-cells. Despite accumulating evidence that contact-mediated signals are involved, the mechanisms regulating acinar-to-islet cell transdifferentiation remain poorly understood.

Results: In this study, we propose that the crosstalk between two contact-mediated signaling mechanisms, lateral inhibition and lateral stabilization, controls cell fate stability and transdifferentiation of pancreatic cells. Analysis of a mathematical model combining gene regulation with contact-mediated signaling reveals the multistability of acinar and islet cell fates. Inhibition of one or both modes of signaling results in transdifferentiation from the acinar to the islet cell fate, either by dedifferentiation to a multipotent state or by direct lineage switching.

Conclusions: This study provides a theoretical framework to understand the role of contact-mediated signaling in pancreatic cell fate control that may help to improve acinar-to-islet cell transdifferentiation strategies for β-cell neogenesis.

Figure 1

Gene regulation and lateral signaling network. In cell i, the common names of the transcription factors are used. In cell j, these are replaced by the respective model variables. Cells i and j are coupled by lateral inhibition of factors X, and by lateral stabilization between factors Y. For each cell, the upstream factor A induces expression of X and Y, while X also induces Z expression, which activates itself. Both endocrine factors X and Z antagonize exocrine factor Y. Once differentiated, the markers Y and Z down-regulate A. Parameters in small lower case represent strengths of the interactions.

Figure 2

Bifurcation analysis. Stability of cell fates change as a function of strength of lateral stabilization. Bifurcation diagram showing stable attractors (solid) and unstable states (dashed) for a minimal tissue consisting of three-cells (hexagons). Arrows indicate trajectories after loss of stabilization. (A) In presence of lateral inhibition, a>a_c, loss of stabilization, b<b_c, causes dedifferentiation towards a progenitor-like multipotent state. If lateral stabilization is recovered at this early stage, the developmental process is recapitulated and a mixed pattern of both cell fates arises. In contrast, if stabilization remains inhibited, cells redifferentiate into islet cells. (B) In absence of lateral inhibition, a<a_c, loss of stabilization results in direct lineage conversion, due to the absence of a progenitor-like multipotent state. This unstable multipotent state vanishes at a_c in a saddle-node bifurcation with another solution branch of similar Y-values but higher Z activity which is additionally unstable against perturbations in Z and therefore omitted in (A). Note that ΣY is a projection of a high (12)-dimensional space, such that intersections do not imply bifurcations or changes in stability as these need not intersect in the actual state space. In the legend, the stability of X or Y means (un)stable with respect to perturbations in variable X or Y, respectively. With parameters as in Table 1, a_c≈0.0017 and b_c≈0.012.

Figure 3

Dynamics of cell fate control. Dynamics of cell fate decisions during development (left column) and lineage conversion (middle and right columns). (A) Sketch of cell-cell signaling condition. (B) Expression of transcription factors over time. A: Hnf6, X: Ngn3, Y: Ptf1a, Z: Isl1. Black lines in B’ depict population averages. (C) Emergent spatial patterns, representing cell fates by colors. Color coding: Y⁺ acinar cells are red, Z⁺ islet cells are blue, and Y⁻Z⁻ cells are white. Initial condition for development is A=1,X=Y=Z=0 and for conversion is Y=1,A=X=Y=0. Parameters as in Table 1. Movies of the spatiotemporal dynamics are available as Additional files (2, 3 and 4).

Figure 4

Cell density affects conversion efficiency.(A) The fraction of acinar cells that convert to islet cells increases with decreasing cell density, as shown for three values of lateral stabilization strength, b=1 (dotted), b=0.1 (solid), b=0.01 (dashed). (B) Examples of the steady-state situation (acinar cells in red and islet cells in blue) for three different cell densities as indicated on the dashed curve (b=0.01, densities 0.25, 0.50 and 0.75). Note the presence of compact clusters of stable acinar cells in the middle panel. (C) Shape of cellular aggregates determines the efficiency of conversion. A decrease in compactness, measured as average neighbors per cell, increases the islet cell yield. Parameters as in Table 1, b as indicated.