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[Preprint]. 2024 Apr 9:2024.04.05.588306.
doi: 10.1101/2024.04.05.588306.

Harnessing molecular mechanism for precision medicine in dilated cardiomyopathy caused by a mutation in troponin T

Lina Greenberg  1 , W Tom Stump  1 , Zongtao Lin  1 , Andrea L Bredemeyer  2 , Thomas Blackwell  1 , Xian Han  1 , Akiva E Greenberg  1 , Benjamin A Garcia  1 , Kory J Lavine  2 , Michael J Greenberg  1
Affiliations

Harnessing molecular mechanism for precision medicine in dilated cardiomyopathy caused by a mutation in troponin T

Lina Greenberg et al. bioRxiv. .

Abstract

Familial dilated cardiomyopathy (DCM) is frequently caused by autosomal dominant point mutations in genes involved in diverse cellular processes, including sarcomeric contraction. While patient studies have defined the genetic landscape of DCM, genetics are not currently used in patient care, and patients receive similar treatments regardless of the underlying mutation. It has been suggested that a precision medicine approach based on the molecular mechanism of the underlying mutation could improve outcomes; however, realizing this approach has been challenging due to difficulties linking genotype and phenotype and then leveraging this information to identify therapeutic approaches. Here, we used multiscale experimental and computational approaches to test whether knowledge of molecular mechanism could be harnessed to connect genotype, phenotype, and drug response for a DCM mutation in troponin T, deletion of K210. Previously, we showed that at the molecular scale, the mutation reduces thin filament activation. Here, we used computational modeling of this molecular defect to predict that the mutant will reduce cellular and tissue contractility, and we validated this prediction in human cardiomyocytes and engineered heart tissues. We then used our knowledge of molecular mechanism to computationally model the effects of a small molecule that can activate the thin filament. We demonstrate experimentally that the modeling correctly predicts that the small molecule can partially rescue systolic dysfunction at the expense of diastolic function. Taken together, our results demonstrate how molecular mechanism can be harnessed to connect genotype and phenotype and inspire strategies to optimize mechanism-based therapeutics for DCM.

Keywords: Biological Sciences; Biophysics and Computational Biology; Troponin T; contractility; mechanobiology; myosin; stem cell derived cardiomyocytes.

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Conflict of interest statement

Conflict of interest statement: All experiments were conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest.

Figures

Figure 1:
Figure 1:. Computational modeling reveals potential therapeutic mechanisms.
(A) Kinetic scheme showing the steps of thin filament activation. ΔK210 reduces thin filament activation. Omecamtiv mecarbil (OM) increases cooperative activation of the thin filament by recruiting additional, non-force generating crossbridges. (B) Computational modeling of the normalized force produced as a function of calcium for WT and ΔK210 based on the kinetic scheme in (A). ΔK210 causes a shift towards supermaximal calcium activation, indicative of reduced thin filament activation. The model predicts that OM can partially rescue this shift by activating the thin filament. (C) Normalized ATPase measurements of myosin interacting with regulated thin filaments over a range of calcium concentrations. ΔK210 causes a shift towards supermaximal calcium activation that can be partially rescued by OM treatment. (D) Computational modeling of the relative force per sarcomere in response to a calcium transient for ΔK210 in the presence and absence of calcium. OM is predicted to cause an increase in force and prolongation of the force transient.
Figure 2:
Figure 2:. Engineered heart tissues with hiPSC-CMΔK210/WT show reduced force production.
(A) Linear engineered heart tissue grown between two deformable PDMS posts. (B) Representative data traces of WT and hiPSC-CMΔK210/WT EHTs under 1 Hz stimulation. See Supplemental Movies 1 and 2. (C) Ensemble averaged beats for WT and hiPSC-CMΔK210/WT EHTs shown above. (D) Data from N=17 WT and N=23 hiPSC-CMΔK210/WT EHTs. Mutant 3D EHTs show reduced force production. Solid bars show median and error bars show interquartile range. See Supplemental Fig. 1 for additional parameters. (E) Ring-shaped EHT mounted between a length mover and a force transducer. (F) Representative trace showing the measured force of an EHT stimulated at 1 Hz undergoing a series of length steps. Inset shows the active force of beating. (G) Active force of beating as a function of stretch. Median values and 95% confidence intervals for N=11 WT and N=34 hiPSC-CMΔK210/WT EHTs. The active force increases with stretch, consistent with the Frank-Starling relationship. A 2-way ANOVA shows significant differences between WT and hiPSC-CMΔK210/WT EHTs with both stretch (P<0.001) and genotype (P<0.001), indicating that the hiPSC-CMΔK210/WT EHTs show reduced force.
Figure 3:
Figure 3:. Measurements of single cell parameters.
(A) Traction force microscopy of single hiPSC-CMs. Cumulative distribution showing the force per area for individual cells. N=159 WT and N=30 hiPSC-CMΔK210/WT cells. The force per area is reduced in the mutant cells, as seen by a Kruskal–Wallis test (P<0.001). (B) Representative immunofluorescence confocal images of WT and hiPSC-CMΔK210/WT cells patterned on to rectangular patterns of extracellular matrix. Sarcomeres are shown by alpha actinin antibody staining (green). (C) Quantification of cell size for N=50 WT and N=58 hiPSC-CMΔK210/WT. Solid bars show median and error bars show interquartile range. Statistical testing was done using a Mann-Whitney test. (D) Cumulative distribution showing the total force per cell in individual cells measured with traction force microscopy. A Kruskal–Wallis test was used to show that the force per area is not significantly different in the mutant cells (P=0.28). (E) Sample traces showing calcium transients for cells paced at 1 Hz. Signal was measured by fluorescence of FluoForte. (F) Quantification of calcium transients showing the amplitude of the transient above baseline (left) and the time to relax by 50% (right). N=91 WT and N=55 hiPSC-CMΔK210/WT cells. Solid bars show median and error bars show interquartile range. Statistical testing was done using a Mann-Whitney test.
Figure 4:
Figure 4:. Whole transcriptome measurements for WT and hiPSC-CMΔK210/WT EHTs.
(A) Volcano plot showing differentially expressed genes between WT and hiPSC-CMΔK210/WT EHTs. Cutoffs for differential expression are log2FC>1 and adjusted p-value < 10−6. (B) Kyoto Encyclopedia of Genes and Genomes (KEGG) terms associated with genes that are differentially expressed between WT and hiPSC-CMΔK210/WT EHTs. Top terms include genes associated with extracellular matrix (ECM) receptor interactions and focal adhesions. (C) Heat maps showing differential expression of genes associated with ECM-receptor interactions and focal adhesions. Data is from N=3 different differentiations with multiple tissues pooled per sample.
Figure 5:
Figure 5:. Whole proteome mass spectrometry measurements for WT and hiPSC-CMΔK210/WT EHTs.
(A) Volcano plot showing differentially expressed proteins between WT and hiPSC-CMΔK210/WT EHTs. (B) Gene ontology (GO) terms associated with proteins that are differentially expressed between WT and hiPSC-CMΔK210/WT EHTs. (C) Heat maps showing differential expression of key genes associated with ECM-receptor interactions and focal adhesions. Data is from N=7 different sample preparations with multiple tissues pooled per sample.
Figure 6:
Figure 6:. Mechanism-based rescue of contraction.
(A) Linear hiPSC-CMΔK210/WT EHTs acutely treated with 250 nM OM for 20 minutes. N=20 tissues. The force increased with treatment, as indicated by a Wilcoxon Matched Pairs Signed Rank Test (P<0.001). (B) Active force produced by tissues. Ring shaped tissues treated with 250 nM for 5 days (N=26 tissues). Shown are the median and 95% confidence intervals. A 2-way ANOVA shows significant differences in active force generation between WT, hiPSC-CMΔK210/WT + DMSO, hiPSC-CMΔK210/WT + 250 nM OM EHTs with both stretch (P<0.001) and genotype (P<0.001). hiPSC-CMΔK210/WT + DMSO tissues generate less force than the WT over the range of all stretches (P<0.001). The force produced by the OM treated hiPSC-CMΔK210/WT EHTs is not significantly different from the WT for stretches > 1.050 L/L0 (P>0.05). (C) Volcano plot showing differentially expressed genes between hiPSC-CMΔK210/WT and hiPSC-CMΔK210/WT + 250 nM OM EHTs. Cutoffs for differential expression are log2FC>1 and adjusted p-value < 10−6. 82 genes were identified. (D) Representative ensemble averaged trace showing the active force produced for hiPSC-CMΔK210/WT tissues treated with DMSO or OM. Treatment with OM increased force and prolonged relaxation. For quantification, see Supplemental Figure 10. (E) Passive force produced by tissues after 5 days of treatment with 250 nM OM. Shown are the median and 95% confidence intervals. A 2-way ANOVA shows significant differences in passive force between WT, hiPSC-CMΔK210/WT + DMSO, hiPSC-CMΔK210/WT + 250 nM OM EHTs with both stretch (P<0.001) and genotype (P<0.001). All 3 conditions are significantly different from each other at stretches > 1.150 L/L0 (P<0.01, corrected for multiple comparisons).
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