Measuring Single-Cell Calcium Dynamics Using a Myofilament-Localized Optical Biosensor in hiPSC-CMs Derived from DCM Patients

Figures

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  Figure 1. The contraction cycle of cardiomyocytes. Calcium enters the cell to induce a large-scale release of intracellular calcium from the sarcoplasmic reticulum. Calcium then binds to the troponin complex on the myofilament to initiate the contraction. The contraction ceases when calcium returns to intracellular stores or exits the cell.

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  Figure 2. Methods to assess calcium handling in cardiomyocytes. Commonly used methods to study calcium signaling in cardiomyocytes include (1) calcium-sensitive dyes and (2) genetically encoded calcium indicators (GECIs). (1) Calcium-sensitive dyes such as Fluo-4 and Fura-2 enter cells and their acetomethoxy (AM) ester moiety is cleaved, allowing the compounds to fluoresce in response to calcium. (2) GECIs are expressed by cells. (2a) GCaMP is composed of circularly permutated enhanced GFP (cpEGFP), calcium-binding domain calmodulin, and calmodulin target sequence M13. Calcium binding to calmodulin increases fluorescence intensity. (2b) RGECO-TnT is composed of the calcium indicator RGECO and troponin T to localize the GECI to the myofilament in order to assess calcium signalling at the site of contraction.

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  Figure 3. Workflow for imaging and analysis of Ca2+ transient in hiPSC-CMs. (A) Once hiPSC-CMs are beating in culture, they can be transduced with AAV to deliver the RGECO-TnT biosensor. (B) With sufficient biosensor expression, hiPSC-CMs can be imaged. The fluorescence intensity of single cells can then be extracted using ImageJ software. These data can be imported into OriginPro software which can compute 11 features of calcium transients along with graphing and statistical analysis features.

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  Figure 4. Features of a calcium transient. (A) The custom calcium transient analysis application described in the text is capable of computing 11 features of a calcium transient, as depicted. Features of calcium transients include (A) time between peaks, (B) time taken to reach peak maximum, (C) transient amplitude, (D) transient duration, (E) area under the curve, (F) time taken to reach 50% baseline, (G) time taken to reach 90% baseline, and (H) decay tau. Features computed but not shown are upstroke velocity, inter-event interval, and transient frequency. (B) Descriptions of each feature that can be extracted from OriginPro.

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  Figure 5. Calcium transients of hiPSC-CMs derived from control HID041004. (A–D) Single-cell calcium transients from iPSC-CMs derived from a female healthy control (HID041004) visualized using graphs generated in the Calcium Transient Analysis application in OriginPro 2022. (E) Microscopy image illustrating the expression of RGECO-TnT in HID041004.

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  Figure 6. Calcium transients of hiPSC-CMs derived from DCM patients HID041020 and HID041021. (A–D) Single-cell calcium transients from hiPSC-CMs derived from a male DCM patient (HID041020) visualized using the Calcium Transient Analysis application in OriginPro 2022. (E–H) Single-cell calcium transients from iPSC-CMs derived from a female DCM patient (HID041021) visualized using the Calcium Transient Analysis application in OriginPro 2022. (I) Microscopy image illustrating the expression of RGECO-TnT in HID041020.

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  Figure 7. Comparisons of averaged calcium transients in DCM patients vs. control hiPSC-CMs. Features of calcium transients computed using the Calcium Transient Analysis application in OriginPro 2022. Comparisons were made between hiPSC-CMs derived from a female healthy control (HID041004), male DCM patient (HID041020), and female DCM patient (HID041021). Features investigated were (A) area under the curve, (B) transient duration, (C) time between peaks, (D) time to 50% baseline, (E) time to 90% baseline, (F) time to peak, (G) decay tau, (H) upstroke velocity, (I) transient amplitude, and (J) transient frequency. Multiple comparisons were made using Bonferroni correction. n = 29–33 cells from four independent replicates. * p < 0.05, ** p < 0.01, *** p < 0.001.