SarcTrack

Abstract

Rationale: Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) in combination with CRISPR/Cas9 genome editing provide unparalleled opportunities to study cardiac biology and disease. However, sarcomeres, the fundamental units of myocyte contraction, are immature and nonlinear in hiPSC-CMs, which technically challenge accurate functional interrogation of contractile parameters in beating cells. Furthermore, existing analysis methods are relatively low-throughput, indirectly assess contractility, or only assess well-aligned sarcomeres found in mature cardiac tissues.

Objective: We aimed to develop an analysis platform that directly, rapidly, and automatically tracks sarcomeres in beating cardiomyocytes. The platform should assess sarcomere content, contraction and relaxation parameters, and beat rate.

Methods and results: We developed SarcTrack, a MatLab software that monitors fluorescently tagged sarcomeres in hiPSC-CMs. The algorithm determines sarcomere content, sarcomere length, and returns rates of sarcomere contraction and relaxation. By rapid measurement of hundreds of sarcomeres in each hiPSC-CM, SarcTrack provides large data sets for robust statistical analyses of multiple contractile parameters. We validated SarcTrack by analyzing drug-treated hiPSC-CMs, confirming the contractility effects of compounds that directly activate (CK-1827452) or inhibit (MYK-461) myosin molecules or indirectly alter contractility (verapamil and propranolol). SarcTrack analysis of hiPSC-CMs carrying a heterozygous truncation variant in the myosin-binding protein C ( MYBPC3) gene, which causes hypertrophic cardiomyopathy, recapitulated seminal disease phenotypes including cardiac hypercontractility and diminished relaxation, abnormalities that normalized with MYK-461 treatment.

Conclusions: SarcTrack provides a direct and efficient method to quantitatively assess sarcomere function. By improving existing contractility analysis methods and overcoming technical challenges associated with functional evaluation of hiPSC-CMs, SarcTrack enhances translational prospects for sarcomere-regulating therapeutics and accelerates interrogation of human cardiac genetic variants.

Keywords: MYK-461; cardiomyocyte contractility; cell imaging; hypertrophic cardiomyopathy; induced pluripotent stem cells; myosin binding protein-C; sarcomeres.

Figure 1.

Using SarcTrack to identify fluorescent sarcomeres. A, Initial parameters are defined on a single frame of an acquired image stack to test fitting of Z-discs by SarcTrack wavelets. Wavelet parameters include the wavelet dimensions (d, e, f), the df for fitting the wavelet in certain orientations (α, the angles around c), and the definition of the grid points when performing the convolution for fitting the wavelets to fluorescent Z-disc pairs (hopsize and halfwindowsize). Once parameters are defined (see Online Methods), dwProcessFrame can be run to visualize the goodness of wavelet fitting to a specific frame. This process is repeated to find the best parameters for labeling Z-discs. In this example, we show a highly disordered cell with significant out of focus fluorescence to demonstrate the ability of these parameters to be adapted to robustly define true Z-disc pairs. B, Once parameters have been defined and tested on a single frame a stack can be analyzed using dwProcessFolder. This process allows the user to deposit one stack into a folder for analysis and this provides 4 outputs. A folder containing each individual frame fit with marked wavelets to check fidelity of wavelet fitting, DWPrdFrq providing the period and frequency of beating defined by sinusoidal fitting of the contractile functions, DWDists providing the distance (d, in pixels) of each wavelet pair for each frame of the stack. DWStats provides the precalibrated raw values derived from the sawtooth fitting of contractile cycles of each sarcomere tracked including contraction time (frames), relaxation time (frames), the minimum distance between wavelets, and the maximum distance between wavelets (pixels). dwCheckResults will output graphs of these parameters and show the fitting of the sinusoid and sawtooth for the combined sarcomere contractility of the entire field of view (FOV). C, Once parameters have been set and quality control of data has been approved using dwCheckResults one can run a folder of multiple movies. A computing cluster can be used to run many movies in parallel, and by using 4 cores, users can analyze 5-second movies every 40 min with parallel batches of up to 100 movies at a time. Once movies are batch analyzed, a script is applied to convert the outputs from DWStats to microns and seconds from pixels and frames. A mean and SEM is obtained from each DWStats file and data is output into a single .txt file. This script also adds the number of sarcomeres tracked in each movie as a separate column to all other parametric means and errors. This workflow ensures that the user can efficiently troubleshoot wavelet fitting and batch analyze hundreds of movies and tens of thousands of sarcomeres in a few hours.

Figure 2.

Comparison of SarcTrack with existing methods of sarcomere tracking and computational benchmarking of SarcTrack with simulated z-disc pairs. A, Simulated sarcomeres produced using a custom MatLab code define adjustable synthetic sarcomeres that can be altered for distances between Z-discs and contraction rates. B, Fitting of simulated sarcomeres by SarcTrack showing the goodness of initial fitting using the algorithm, where the colored bar indicates the relative stretch of the wavelet fit with pink being longer sarcomeres and blue shorter. C and D, This shows ground truth and computed curves of distances for 8 synthetic movies. gt is the ground truth distance curve. The numbers after gt are the proportions of contraction vs relaxation times. For example, gt (1, 2) means relaxation takes twice as long as contraction, and in gt (2, 2) both contraction and relaxation are twice the values in gt (1, 1). The number in parenthesis after avg fit is the number of sarcomeres tracked. The avg fit curves are the average of the curves of distances measured for individual sarcomeres (registered to handle lack of synchronicity). E, A frame showing an unpatterned human induced pluripotent stem cell–derived cardiomyocyte (hiPSC-CM) at 100X magnification, where red lines indicate sarcomeres selected for fast Fourier transform (FFT) analysis. FFT analysis tracks the periodicity of many linearly arranged sarcomeres, which is problematic in unpatterned hiPSC-CMs, because of cellular irregularities and nonlinearly arranged sarcomeres. For FFT analyses, the user must manually define regions of interest in each movie, which is inefficient, labor intensive, and can introduce selection bias. FFT provides reliable measures of maximum and minimum sarcomere length, as the signal becomes noisy when aligned sarcomeres number <10–20. F, In comparison SarcTrack wavelet labeling of sarcomeres is automated and selects all sarcomeres in a field of view by parametric thresholding as described in Figure 1. SarcTrack labels individual sarcomeres irrespective of orientation and is fully automated once parameters are predefined for a batch of movies. SarcTrack can provide sarcomere length as well as contraction and relaxation durations and beat rate. G, Graph showing data analysis of sarcomere shortening from 3 movies that were analyzed by both FFT analysis and SarcTrack analysis. Plotted dots represent a single FFT measure in FFT analysis (derived from red lines shown in A) or a single-tracked sarcomere in SarcTrack analysis. SarcTrack provided on average across 3 samples 100-fold more data points, in an automated analysis. H, Graph showing the data analysis of sarcomere shortening when cells are treated with 1 μmol/L MYK-461 reducing cellular contractility. No significant differences were observed when the 2 techniques were statistically compared against one another using a Student t test where a significance cutoff of P<0.05 was used.

Figure 3.

SarcTrack assessment of sarcomere function in human induced pluripotent stem cell–derived cardiomyocytes (hiPSC-CMs) with different fluorescent tags and throughout differentiation. A, Sarcomere shortening as a percentage of initial sarcomere length, studied at day 30 of differentiation in hiPSC-CM lines with 3 different fluorescent tags labeling the sarcomere Z-disc or M-line. B, Relaxation duration (time to peak relaxation after peak contraction) of hiPSC-CM lines. In A and B, circles denote microscopic field of view, each containing ≈200 sarcomeres. Composite data includes ≈10 000 sarcomeres. There were no statistical differences (denoted as NS) in sarcomere shortening or relaxation durations between hiPSC-CMs with distinct fluorescent tags. C, Sarcomere shortening measured in hiPSC-CMs at differentiation days 12 to 40. D, The mean SEM of sarcomere contractility as a function of differentiation day. Sarcomere contractility had less variability postdifferentiation day 20 (reduced SEM). E, Relaxation duration as a function of differentiation days. Relaxation duration decreased with differentiation day and was stabilized by day 20. F, The mean and SEM of relaxation duration decreased with differentiation days and plateaued by day 20. These data infer that hiPSC-CM analyses at day 30 of differentiation should minimize variability. In C-F, time points are the average of ≥30 fields of views (each containing 50–300 sarcomeres) from 3 separate differentiations.

Figure 4.

Effects of electrical pacing on TTN-GFP human induced pluripotent stem cell–derived cardiomyocytes (hiPSC-CMs) contractile parameters assessed by SarcTrack. A, Histogram showing the number of observations as a function of contraction time in paced (gray, 1 Hz stimulation) and unpaced (green) hiPSC-CMs. B, Relaxation time as a function of pacing status. C, Contracted sarcomere length (SL) as a function of pacing. D, Relaxed SL as a function of pacing. E, Sarcomere shortening as a function of pacing. F, Beat rate as a function of pacing. TTN-GFP hiPSC-CMs were studied at day 30 of differentiation. Observation denotes the mean data from one field of view (≈200 sarcomeres). Histograms were generated from 122 unpaced and 116-paced fields of views. Each histogram was fitted with a single Gaussian distribution and the mean and SEM is indicated.

Figure 5.

SarcTrack assessment of contractile effects of pharmacological agents. A–D, Plots of contractile parameters assessed by SarcTrack in day 30 TTN-GFP human induced pluripotent stem cell–derived cardiomyocytes (hiPSC-CMs) varied with dose-dependent increases of CK-1827452 (myosin activator) or MYK-461 (myosin inhibitor). Dotted lines denote the mean of untreated samples, which served as controls. E–H, Plots of hiPSC-CMs contractile parameters derived from SarcTrack demonstrate dose-dependent effects of verapamil and propranolol. For each panel, ≈10 fields of view were assessed per drug concentration for each of 3 independent differentiations of hiPSC-CMs. Significances are denoted as *P<0.05, **P<0.01, and ***P<0.001. All values are stated as mean±SEM.

Figure 6.

MyBPC (myosin-binding protein C) haploinsufficiency modeled in TTN-GFP human induced pluripotent stem cell–derived cardiomyocytes (hiPSC-CMs) and studied by SarcTrack. A, Guide RNA used to target exon-2 of MYBPC3 in TTN-GFP hiPSC-CMs for CRISPR/Cas9 mutagenesis. B, Schematic representation of the excision of 8 nucleotides resulting in a premature stop codon (*) in exon-2. C, Western blot of MyBPC protein and β-actin obtained from 3 independent differentiations of wild-type (WT) and MyBPC mutant TTN-GFP hiPSC-CMs at differentiation day 30. D, MyBPC protein normalized to β-actin expression in WT and MyBPC mutant hiPSCs demonstrates 50% reduction of MyBPC protein content. E and F, SarcTrack analyses of heterozygous MyBPC^t/+ TTN-GFP hiPSC-CMs and isogenic controls (nucleofected with CRISPR-Cas9 but without MYBCP3 guides) showed indistinguishable beat rates of 36±1.4 ms, but MyBPC^t/+ TTN-GFP hiPSC-CMs had increased sarcomere contractility and prolonged relaxation. G and H, The allosteric myosin inhibitor MYK-461 caused dose-dependent reduction in contractility and improved relaxation in MyBPC^t/+ TTN-GFP hiPSC-CMs, highlighting SarcTrack as an effective platform for assessing the parametric effects of compounds on cardiomyocyte contractility.