Figures and data
Sarcomere tracking in genetically engineered Z-line labeled iPSC-derived cardiomyocytes on micropatterned soft gels.
(A) Sketch of a human cardiomyocyte (CM) on soft gel (top) and sarcomere structure in relaxed and contracted state (bottom). (B) ACTN2-Citrine cardiomyocytes (culture day 20) on a polyacrylamide gel substrate (Young’s modulus: 15 kPa), patterned with rectangular stripes of Synthemax (70 × 10 µm). More than 50% of the stripes were typically occupied by single cardiomyocytes. Inset: zoomed-in view of CMs on pattern. (C) Workflow for measurement of sarcomere motion: (1) individual CM adherent to a 15 kPa substrate, first frame of a 1,500-frame confocal time-lapse recording. (2) Deep-learning (Siam-U-Net)-based segmentation of sarcomere Z-bands in the CMs depicted above. (3) Kymograph from the region of interest (ROI) labeled with yellow lines in B and C, demonstrating sarcomere z-band motion. Inset shows Z-band intensity profiles of one time frame with and without Siam-U-Net. (D-E) Confocal images (top row) of representative ACTN2-Citrine-labeled CMs with corresponding deep-learning Z-band segmentation (bottom row) and kymographs (dashed lines mark the start of contraction cycles) recorded from the automatically selected ROI (red lines). (Bottom panels) Overlay plot of single sarcomere length change ΔSL(t) for all tracked sarcomeres in the marked ROIs (first 4 seconds). Thin colored lines are individual sarcomere length changes, the thick black lines display the average of the sarcomere length changes. Contraction intervals are highlighted in gray. Sarcomere popping events are marked with asterisks. Conditions (substrate stiffness): 5 kPa (D); 15 kPa (physiological); E); 85 kPa (F).
Analysis of sarcomere dynamics in length change vs. velocity phase-space.
(A-C) Phase-space plots of sarcomere length change ΔSL vs. velocity V for three representative ROIs from CMs on substrates of increasing stiffness (same ROIs as in Fig. 1). Thin black lines show individual sarcomere dynamics, red lines average dynamics. Annotations highlight selected maximal and minimal values of single and average ΔSL and V. (D) Box plot of maximal average contractions 
Static versus stochastic heterogeneity of sarcomere motion.
(A) Concatenated contraction periods from a representative ROI in one beating cell on a 15 kPa substrate showing sarcomere length changes during activation, labeled as ΔSLi,k with sarcomere number i and contraction cycle number k. Each box is 0.6 s in width and −0.5 to 0.5 µm in height. Insets show correlation scatter plots from the ΔSLi,k-pairs marked in red (serial correlation) and blue (mutual correlation) respectively in A. The respective Pearson correlation coefficient r(i,j),(k,l) (see Eq. 1) is noted in the graphs. (B) (left column) Average serial correlation rsbetween ΔSL and V (i = j) of individual sarcomere from different contraction cycles (k ≠ l), quantifying the variability of motion patterns of individual sarcomere across contraction cycles. (Middle column) Average mutual correlation rmof ΔSL and V between all sarcomeres in a myofibril (i ≠ j) in each contraction cycle (k = l), quantifying the variability between motions of neighboring sarcomeres in each contraction cycle. (Right column) Ratio R between average mutual and serial correlation of sarcomere ΔSL and V respectively. R is a measure for the degree of stochasticity in the motions, purely stochastic when R = 1, or largely static when R ≪ 1. (C) Average Pearson correlation coefficients of ΔSL/Vi,k and ΔSL/Vj,l. The x-axis shows the mutual correlation of the motion of different sarcomeres (i ≠ j), the y-axis the serial correlation of the different cycles of one sarcomere (i = j), while (k ≠ l). The set of dashed lines mark regions of stochastic heterogeneity (right) and static heterogeneity (left). The yellow star marks data of the ROI in A. B,C show data of 2,062 ROIs (5 kPa: N = 134, 9 kPa: 442, 15 kPa: 339, 29 kPa: 393, 49 kPa: 449, 85 kPa: 305). Boxes show quartiles, red lines the median, green triangles the mean and whiskers the 5th and 95th percentile of the distribution per condition. Statistical analysis was performed using the Kruskal-Wallis and Dunn’s posthoc tests, with significance set at p < 0.01. All differences were significant. (D,E) Illustrative sketches of sarcomere length changes ΔSL in different contraction cycles, assuming purely static heterogeneity (D) and purely stochastic heterogeneity (E). Color maps denotes sarcomere contractile strength.
Analysis of sarcomere popping.
(A) Representative ΔSL time-series of one section of a myofibril containing 16 sarcomeres in one representative CM on a 29 kPa substrate. Popping events, the elongation of a sarcomere within one contraction cycle beyond 0.25 µm, are marked in red. (B) Zoomed plot of 4 consecutive contraction cycles showing two popping events (shaded red). (C) Spatio-temporal map of popping events (black), from data shown in A. Upper and right bar graphs show marginal popping frequencies per contraction cycle nc(P) or per sarcomere ns(P). (D) Overall popping frequencies for different substrate conditions. Boxes show quartiles, red lines the median, green triangles the mean and whiskers the 5th and 95th percentile of the distribution per condition. Statistical analysis was performed using the Kruskal-Wallis and Dunn’s posthoc tests, with significance set at p < 0.01. All differences were significant. (E) Popping frequency as a function of sarcomere equilibrium length SL0. Lines show average of all ROIs for the respective substrate stiffness. (F) Randomly generated events with probability p = 0.3, demonstrating that apparent clustering of popping events shows up even in purely random event sequences. (G,H) Distributions of distance d and time τ between popping events for single ROI in comparison with corresponding geometric distribution (red line). D and E show data of 2,062 ROIs.
Representative CM selection with automatically and individually detected ROIs.
CMs are randomly selected from the data sets for three substrate stiffnesses (9, 15 and 85 kPa); automatically determined ROIs depicted as red lines.
Effects of substrate elasticity on spontaneous beating of cardiomyocytes.
(A) Spontaneous beating frequencies. (B) Beating irregularity: relative standard deviation of beating periods. (C) Average length of contraction cycles Tc (identified as systole). A-C include data from 3,985 ROIs. Boxes show quartiles, red lines the median, green triangles the mean and whiskers the 5th and 95th percentile of the distributions.
Composition of polyacrylamide soft gels used in the study.
All gels used here were made from the same respective stock solution (10 ml). The Young’s modulus was measured for a gel sample from each prepared stock solution using a rheometer (Physica MCR 501 Rheometer, Anton Paar, Germany) using a 25 mm, 2° cone plate with a sample volume of 140 μl. A time sweep (1 h, spacing 30 s, 1% strain, 1 Hz), a frequency sweep (3 measurements per decade, 1% strain, 0.01 – 100 Hz), and an amplitude sweep (3 measurements per decade, 0.01 – 100% strain, 1 Hz) were performed consecutively.
