Spatial patterning of liver progenitor cell differentiation mediated by cellular contractility and Notch signaling

7 figures, 2 tables and 12 additional files

Figures

Figure 1 with 3 supplements
Localized differentiation of liver progenitors in arrayed patterns.

(A) Immunolabeling of BMEL cells for the biliary marker OPN and hepatocyte marker ALB on arrayed collagen I patterns with control IgG or Fc-recombinant Notch ligands DLL1, DLL4, and JAG1. (B) …

https://doi.org/10.7554/eLife.38536.003
Figure 1—figure supplement 1
Immunolabeling and quantification of CK19.

(A) Immunolabeling of BMEL cells presented with IgG for the biliary marker CK19. (B) Quantification of CK19 intensity in BMEL cells presented with IgG as a function of radial distance from the …

https://doi.org/10.7554/eLife.38536.004
Figure 1—figure supplement 2
Immunolabeling of OPN and CK19 at t=24h and cell density with radius at t=72h.

(A) Immunolabeling at t=24h of BMEL cells on 30 kPa substrates presented with IgG and DLL4 for the biliary markers OPN and CK19. Scale bar indicates 75 µm. (B) Measurement of cell density with radius …

https://doi.org/10.7554/eLife.38536.005
Figure 1—figure supplement 3
Immunolabeling for OPN with 300, 600, and 1000 µm diameter patterns.

(A) Immunolabeling for OPN of BMEL cells presented with DLL4 on 30 kPa substrates at t=72h. Both 300 µm and 1000 µm pattern diameters were included in this experiment in addition to the 600 µm pattern …

https://doi.org/10.7554/eLife.38536.006
Figure 2 with 3 supplements
Peripheral biliary differentiation is dependent on both Notch signaling and substrate stiffness.

(A) Immunolabeling for OPN of BMEL cells presented with DLL4 on 30 kPa and 4 kPa substrates. Cells were treated with vehicle control (DMSO) or an inhibitor of Notch signaling (γ-secretase inhibitor …

https://doi.org/10.7554/eLife.38536.009
Figure 2—figure supplement 1
Quantification of OPN+ cell counts in arrayed patterns.

Cells were cultured on 30 kPa and 4 kPa substrates and presented with IgG, DLL1, DLL4, and JAG1. Treatments included vehicle control (DMSO) or an inhibitor of Notch signaling (γ-secretase inhibitor …

https://doi.org/10.7554/eLife.38536.010
Figure 2—figure supplement 2
Regression analysis of OPN+ and ALB+ cell counts.

Data in Figure 2B were separated into peripheral and central subsets for which dimensionless radius was greater than 0.75 (R>0.75) and less than 0.75 (R<0.75). Separate multiple regression models were …

https://doi.org/10.7554/eLife.38536.011
Figure 2—figure supplement 3
Quantification of ALB+ cell counts in arrayed patterns.

Cells were cultured on 30 kPa substrates and presented with IgG, DLL1, DLL4, and JAG1. Treatments included vehicle control (DMSO) or an inhibitor of Notch signaling (γ-secretase inhibitor X, GSI, 5 …

https://doi.org/10.7554/eLife.38536.012
Figure 3 with 2 supplements
TGFβ signaling and cell–cell interaction strength modulate pattern formation.

(A) Immunolabeling for OPN and HNF4A of BMEL cells presented with IgG and DLL4 on 30 kPa substrates. Cultures were treated with vehicle control (DMSO), inhibitor of TGFβ signaling (SB-431542, 10 …

https://doi.org/10.7554/eLife.38536.026
Figure 3—source data 1

Summary table for OPN+ probability density data in Figure 3B.

https://doi.org/10.7554/eLife.38536.029
Figure 3—figure supplement 1
Quantification of OPN+ cell counts and HNF4A intensity with SB-431542 and DECMA treatment.

(A) Quantification of OPN+ cell counts on 30 kPa substrates presented with DLL4 after treatment with vehicle control (DMSO) or inhibitor of TGFβ signaling (SB-431542, 10 µm). (B) Quantification of …

https://doi.org/10.7554/eLife.38536.027
Figure 3—figure supplement 2
TGFβ1 induces Notch ligand and receptor expression uniformly.

BMEL cells were cultured on 30 kPa substrates, presented with IgG or DLL4, and treated with TGFβ1 (1.5 ng/ml). Scale bar is 150 µm.

https://doi.org/10.7554/eLife.38536.028
Figure 4 with 2 supplements
Liver progenitors in arrayed patterns generate gradients of traction stress independent of ligand presentation.

(A) Simulated finite element modeling (FEM) stress profile of arrayed patterns. (B) Stress from FEM as a function of radius. (C) Experimental stress profiles obtained by traction force microscopy …

https://doi.org/10.7554/eLife.38536.015
Figure 4—figure supplement 1
Effect of Notch inhibition on experimental stress profiles.

Experimental stress profiles were obtained by TFM of BMEL cells presented with DLL4 on 30 kPa and 4 kPa substrates and treated with vehicle control (DMSO) or GSI (10 µM). Mean ± 95% CI.

https://doi.org/10.7554/eLife.38536.016
Figure 4—figure supplement 2
Effect of TGFβ and E-cadherin inhibition on experimental stress profiles.

Experimental stress profiles were obtained by TFM of BMEL cells on 30 kPa and 4 kPa substrates presented with ligand (IgG and DLL4) and treated with vehicle control (DMSO), inhibitor of TGFβ …

https://doi.org/10.7554/eLife.38536.017
Peripheral differentiation is dependent on a gradient of actomyosin contractility.

(A) Simulated effect of stress gradients of increasing steepness on Notch signaling activity via trans-activation. Darker shades of blue represent increased Notch signaling activity as measured by …

https://doi.org/10.7554/eLife.38536.018
Mechanotransduction by ERK and ROCK modulate peripheral biliary fate.

(A) BMEL cells on 30 kPa substrates were presented with DLL4 and treated with vehicle control (DMSO) and inhibitors of ERK signaling (FR180204, 10 µM) and ROCK (Y-27632, 10 µM). Samples were …

https://doi.org/10.7554/eLife.38536.019
Figure 7 with 1 supplement
Notch ligands Jag1 and Dll1 are both required for segregation of hepatocytic fate centrally and biliary fate peripherally.

(A) Immunolabeling for OPN and HNF4A of BMEL cells presented with DLL4 on 30 kPa substrates. Control cells were transduced with an shRNA vector coding for a non-mammalian target. shJag1 and shDll1 …

https://doi.org/10.7554/eLife.38536.022
Figure 7—source data 1

Summary table for OPN data in Figure 7C.

https://doi.org/10.7554/eLife.38536.024
Figure 7—source data 2

Summary table for SOX9 and HNF4A data in Figure 7D.

https://doi.org/10.7554/eLife.38536.025
Figure 7—figure supplement 1
Regression analysis of OPN+ cell counts.

Data in Figure 7B were separated into peripheral and central subsets for which dimensionless radius was greater than 0.75 (R>0.75) and less than 0.75 (R<0.75). Separate multiple regression models were …

https://doi.org/10.7554/eLife.38536.023

Tables

Table 1
List of growth factors and drugs.
https://doi.org/10.7554/eLife.38536.030
Factor or drugStockTargetManufacturerCatalog #
(–)-Blebbistatin1 mg/ml25 μMCayman Chemical13013
DECMA1 mg/ml10 μg/mlFisher Scientific50-245-625
FR18020410 mg/ml10 μMSigma-AldrichSML0320
L-685,458 (GSI)1 mM5 μMTocris2627
SB-43154210 mM10 μMSigma-AldrichS4317
TGFβ15 μg/ml1.5 ng/mlR&D Systems240-B-002
Y-276325 mg/ml10 μMEnzo Life Sciences270–333-M005
Table 2
List of primary antibodies.
https://doi.org/10.7554/eLife.38536.031
Antibody targetDilutionManufacturerCatalog #
ALB1/100BethylA90-134A
CK191/200Abcamab52625
Digoxigenin1/500Roche11 093 274 910
HNF4A1/200Abcamab41898
OPN (SPP1)1/50R&D SystemsAF808
SOX91/200EMD MilliporeAB5535
YAP11/50ProteinTech13584–1-AP

Additional files

Source code 1

MATLAB function to process TFM images.

https://doi.org/10.7554/eLife.38536.032
Source code 2

MATLAB function to analyze and plot TFM data.

https://doi.org/10.7554/eLife.38536.033
Source code 3

MATLAB function to retrieve plane data.

https://doi.org/10.7554/eLife.38536.034
Source code 4

MATLAB function to retrieve the reader for an image.

https://doi.org/10.7554/eLife.38536.035
Source code 5

MATLAB function to draw boundaries around cells automatically.

https://doi.org/10.7554/eLife.38536.036
Source code 6

MATLAB function to find the best fit of an ellipse for a given set of points.

https://doi.org/10.7554/eLife.38536.037
Source code 7

MATLAB function to rotate and center cell boundaries for averaging.

https://doi.org/10.7554/eLife.38536.038
Source code 8

COMSOL FEM simulation of cells on 30 kPa and 4 kPa substrates.

https://doi.org/10.7554/eLife.38536.039
Source code 9

MATLAB Notch simulation for no stress (b=0).

https://doi.org/10.7554/eLife.38536.040
Source code 10

MATLAB Notch simulation for intermediate stress (b=0.5).

https://doi.org/10.7554/eLife.38536.041
Source code 11

MATLAB Notch simulation for high stress (b=5).

https://doi.org/10.7554/eLife.38536.042
Transparent reporting form
https://doi.org/10.7554/eLife.38536.043

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