Predictive microfluidic control of regulatory ligand trajectories in individual pluripotent cells

Abstract

Local (cell-level) signaling environments, regulated by autocrine and paracrine signaling, and modulated by cell organization, are hypothesized to be fundamental stem cell fate control mechanisms used during development. It has, however, been challenging to demonstrate the impact of cell-level organization on stem cell fate control and to relate stem cell fate outcomes to autocrine and paracrine signaling. We address this fundamental problem using a combined in silico and experimental approach in which we directly manipulate, using laminar fluid flow, the local impact of endogenously secreted gp130-activating ligands and their activation of signal transducer and activator of transcription3 (STAT3) signaling in mouse embryonic stem cells (mESC). Our model analysis predicted that flow-dependent changes in autocrine and paracrine ligand binding would impact heterogeneity in cell- and colony-level STAT3 signaling activation and cause a gradient of cell fate determination along the direction of flow. Interestingly, analysis also predicted that local cell density would be inversely proportional to the degree to which endogenous secretion contributed to cell fate determination. Experimental validation using functional activation of STAT3 by secreted factors under microfluidic perfusion culture demonstrated that STAT3 activation and consequently mESC fate were manipulable by flow rate, position in the flow field, and local cell organization. As a unique demonstration of how quantitative control of autocrine and paracrine signaling can be integrated with spatial organization to elicit higher order cell fate effects, this work provides a general template to investigate organizing principles due to secreted factors.

Fig. 1.

Overview of experimental and computational strategies for investigating autocrine and paracrine signaling in static and perfused mESC culture. (A) LIF signals by forming a LIFR-gp130 heterodimeric receptor complex, leading to the recruitment and phosphorylation (p) of STAT3, which can be directly measured and related to ligand binding (4). Nuclear translocation of pSTAT3 induces the transcription of members of the Jak-STAT pathway (13), as well as genes needed for self-renewal (1). (B) Schematic representation of the simulated cell culture system. Cells are treated as flat disks of radius r_cell with total and free receptors R_t and R, respectively, complex number C_n, and binding rate constant κ. Ligand capture boundary layer is at position z = δ. For additional simulation details, please see SI Appendix, Section S.3. Inset: Schematic depicting the different predictions made by deterministic vs. stochastic models of diffusion. In a deterministic model, a source S of diffusible ligands produces a Gaussian concentration gradient [L] such that all cells at position x experience an identical concentration [L_x] of the ligand (left). In contrast, a stochstic model will result only in a certain probability P[L_x] < 1 that the ligand concentration will be equal to L[_x].

Fig. 2.

Cell density and secreted factor trajectory simulations. Representative 2D projections of ligand trajectories in the xy plane as a function of Pe and σ (flow is from left to right). Inset i and ii: Magnified view of selected ligand trajectories.

Fig. 3.

Simulations predict a flow-rate-dependent gradient of gp130 complex numbers and pSTAT3 concentrations. (A) Absolute levels of receptor-ligand complexes increase with cell density and decreasing flow rate. (B) Increasing the density of a uniformly distributed cell population produces a concomitant increase in the heterogeneity of complex number across the population, whereas increasing flow rate results in less variation across the cells. (C) Whereas the mean theoretical pSTAT3 levels were uniforn along the channel under passive diffusion, the STAT3 activation per cell increased significantly with respect to axial distance under all flow conditions (*), indicating the formation of a gradient of cell fate responses. (D) When normalized to the number of neighboring cells, the impact of flow on the predicted mean pSTAT3 levels is significantly diminished. That the normalized levels of pSTAT3 are lower when cell density is higher suggests that each neighboring cell contributes less to the maintenance of colony pluripotency than cells located within a less cell-dense local environment.

Fig. 4.

Experimentally determined cell responses closely match theoretical predictions. (A) Mean and (B) local cell density normalized pSTAT3 levels in microchannel under test (-LIF) and control (+JakI) conditions closely follow the simulated results. Blue line represents mean normalized simulated data. Data represent mean ± s.d. (C) pSTAT3 levels in static controls. (D) Representative choropleth map of simulated STAT3 activation under Pe = 1 flow using an empirically determined cell map. A gradient of cell response is apparent. Correponding plots for other flow rates can be found in SI Appendix, Section 3.2. (E) Mean STAT3 activation along the axial distance reveals a graded response of cell fate under all perfusion regimes that is similar to those predicted by the model simulation. Data points with solid lines show experimentally determined values, while dashed lines depict the simulation predictions. All data are normalized to +LIF condition under static conditions.

Fig. 5.

Molecular consequences of fluidic-controlled pSTAT3 gradients. (A) Levels Oct4 expression along the length of the microchannel indicate that downstream cells maintain their pluripotent state in the absence of LIF. The red line denotes the threshold set for determining Oct4+ expression levels in undifferentiated cells (13). (B) Mean STAT3 activation under moderate perfusion indicates the overall level of pluripotent cells decreases in the absence of LIF. (C) Under static conditions, Jak inhibition results in pSTAT3 and Oct4 levels comparable to those of the -LIF condition, suggesting complete inhibition of signaling occurs due to LIF deprivation. (D and E) Representative fluorescent images of cells stained with Hoechst 33342 and anti-Oct4 after 24 h perfusion in -LIF conditions demonstrates different cell after distributions in upstream (D) and downstream (E) regions of the channel.