Fibroblast mechanotransduction network predicts targets for mechano-adaptive infarct therapies
- Department of Bioengineering; Clemson University, United States
Figures
Figure 1 with 1 supplement
Schematic of expanded logic-based ordinary differential equation model of cardiac fibroblast chemo/mechanotransduction.
Extracellular stimuli, intracellular signaling species, transcription factors, and fibroblast-secreted outputs are represented as nodes (boxes, 109 total). Directed edges represent activating and …
Figure 1—figure supplement 1
Schematic of fibroblast chemo-mechanotransduction network modifications for current study.
Added nodes relating to mechanotransduction mechanisms, mechano-chemo-crosstalk mechanisms, and additional secreted outputs are highlighted in blue.
Figure 2 with 1 supplement
Model accurately predicts qualitative changes in output expression and intermediate activity as measured by independent in vitro studies.
(A) Expression of cell-secreted outputs and phenotypic markers (i.e. αSMA) were predicted in response to single biochemical stimuli and mechanical tension and compared to an independent set of …
Figure 2—figure supplement 1
Optimization of reaction parameters for maximizing accuracy of qualitative predictions.
Parameter sweeps of half-maximal effective concentration (EC50) and Hill coefficients (n) were conducted by simulating changes in output node expression (A) and intermediate node activity (B) in …
Figure 3 with 1 supplement
Network-wide responses to biochemical stimuli are dependent on the tensional context.
(A–B) Dose-response curves were simulated under elevated levels of tension with incremental doses of each biochemical input, and changes in area under normalized dose-response curves (ΔAUC) were …
Figure 3—figure supplement 1
Comparison of mechano-chemo interaction trends across individual biochemical stimuli.
(A) Probability density distributions of changes in area under normalized dose-response curves (ΔAUC) with incremental levels of tension. Distributions were estimated from data using a kernel …
Figure 4 with 1 supplement
Network perturbation analysis reveals influential pathways of fibroblast mechanotransduction.
(A–C) Changes in activity levels for top 10 sensitive nodes with simulated knockdown of top 10 influential nodes at low (A), medium (B), and high (C) levels of tension. Nodes were ranked based on …
Figure 4—figure supplement 1
Full network perturbation analysis results.
Changes in activity for all nodes in the network were measured following comprehensive knockdown of individual noes (Ymax = 0.1) under given levels of tension. Values reflect changes in node …
Figure 5 with 1 supplement
Model-predicted effects of current post-myocardial infarction (MI) drug treatments reflect experimental evidence from independent case studies.
(A) Comparison of model-predicted effect of angiotensin receptor blocker (ARB) doses with or without neprilysin inhibitor (NEPi) treatment on procollagen I expression with measurements of collagen …
Figure 5—figure supplement 1
Comparisons of model-predicted and experimentally measured changes in procollagen expression and signaling intermediate activity.
(A) Simulated and experimental measurements of procollagen I synthesis in response to increasing doses of neprilysin inhibitor (NEPi) LBQ657 (LBQ). Simulated concentrations of NEPi represent …
Figure 6 with 1 supplement
Comprehensive drug screen identifies mechano-adaptive candidates for post-myocardial infarction (MI) fibrosis.
(A) Target combinations meeting preliminary threshold for mechano-adaptive behavior (i.e. promoted negative change in matrix content in low tension and positive change in matrix content in high …
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Figure 6—source data 1
In vitro validation experimental results.
- https://cdn.elifesciences.org/articles/62856/elife-62856-fig6-data1-v2.xlsx
Figure 6—figure supplement 1
Screen of individual drug targets for mechano-adaptive matrix expression.
Changes in matrix content as a function of output node expression were measured following comprehensive knockdown and overexpression of individual nodes in low- or high-tension contexts. …
Tables
Table 1
Statistical tests of tension dependencies.
Results of Kolmogorov-Smirnov (K-S) tests with Benjamini-Hochberg correction comparing changes in area under normalized dose-response curves (ΔAUC) distributions for inputs across levels of tension.
| Input | Tension levels | K-S test p-value | Tension levels | K-S test p-value | Tension levels | K-S test p-value |
|---|---|---|---|---|---|---|
| AngII | 0.2 vs. 0.5 | 2.2e-17 | 0.2 vs. 0.9 | 2.37e-37 | 0.5 vs. 0.9 | 1.00e-32 |
| TGFβ | 0.2 vs. 0.5 | 1.88e-13 | 0.2 vs. 0.9 | 6.10e-32 | 0.5 vs. 0.9 | 5.20e-31 |
| IL6 | 0.2 vs. 0.5 | 1.87e-28 | 0.2 vs. 0.9 | 9.56e-6 | 0.5 vs. 0.9 | 9.90e-23 |
| IL1 | 0.2 vs. 0.5 | 5.38e-21 | 0.2 vs. 0.9 | 5.88e-16 | 0.5 vs. 0.9 | 5.88e-16 |
| TNFα | 0.2 vs. 0.5 | 3.17e-21 | 0.2 vs. 0.9 | 1.55e-39 | 0.5 vs. 0.9 | 1.55e-39 |
| NE | 0.2 vs. 0.5 | 1.07e-22 | 0.2 vs. 0.9 | 1.19e-3 | 0.5 vs. 0.9 | 7.47e-13 |
| PDGF | 0.2 vs. 0.5 | 5.38e-21 | 0.2 vs. 0.9 | 6.10e-32 | 0.5 vs. 0.9 | 6.10e-32 |
| ET1 | 0.2 vs. 0.5 | 1.15e-15 | 0.2 vs. 0.9 | 8.30e-34 | 0.5 vs. 0.9 | 1.70e-32 |
| NP | 0.2 vs. 0.5 | 1.18e-17 | 0.2 vs. 0.9 | 2.02e-12 | 0.5 vs. 0.9 | 6.97e-4 |
Table 2
Model parameters used for drug effect simulations.
Minimum/maximum AT1R inhibitor (AT1Ri) values represent modifiers subtracted from the Ymax parameter of the AT1R node, and minimum/maximum neprilysin inhibitor (NEPi) values represent modifiers …
| Study | TGFβ (w) | AngII (w) | NP (w) | Tension (w) | AT1Ri minimum | AT1Ri maximum | NEPi minimum | NEPi maximum |
|---|---|---|---|---|---|---|---|---|
| von Lueder et al., 2015 | – | 0.4 | – | 0.3 | 0.01 | 0.5 | 0.05 | 4 |
| Burke et al., 2019 | 0.4 | 0.4 | 0.6 | 0.3 | 0.5 | 0.5 | 4 | 4 |
| Ramirez et al., 2014 | Int. | Int. | Int. | 0.1/0.6 | 0.5 | 0.5 | – | – |
Table 3
Experimental group culture media conditions.
| Control | Media (0.5% FBS)+ TGFβ (10 ng/mL)+ TNFα (10 ng/mL)+ L-ascorbic acid (50 ng/mL) |
|---|---|
| PI3K + STAT inhibitors | Control + LY294002 (10 μM)+ Niclosamide (0.5 μM) |
| PI3K + gp130 inhibitors | Control + LY294002 (10 μM)+ SC144 (10 μM) |
| PI3K + IL6 inhibitors | Control + LY294002 (10 μM)+ Rosuvastatin (10 μM) |
| mTOR + STAT inhibitors | Control + Everolimus (0.5 μM)+ Niclosamide (0.5 μM) |
| mTOR + gp130 inhibitors | Control + Everolimus (0.5 μM)+ SC144 (10 μM) |
| mTOR+ IL6 inhibitors | Control + Everolimus (0.5 μM)+ Rosuvastatin (10 μM) |
Additional files
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Supplementary file 1
Fibroblast mechano-chemo signal transduction model.
Database detailing all nodes, reactions, model parameters, and references used for construction of the signaling network.
- https://cdn.elifesciences.org/articles/62856/elife-62856-supp1-v2.xlsx
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Supplementary file 2
Model validation database.
Database detailing all qualitative input-output and input-intermediate relationships and references used for validation of the signaling network with independent experimental studies.
- https://cdn.elifesciences.org/articles/62856/elife-62856-supp2-v2.xlsx
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Transparent reporting form
- https://cdn.elifesciences.org/articles/62856/elife-62856-transrepform1-v2.docx
