Oxidative stress pathogenically remodels the cardiac myocyte cytoskeleton via structural alterations to the microtubule lattice

Abstract

In the failing heart, the cardiac myocyte microtubule network is remodeled, which contributes to cellular contractile failure and patient death. However, the origins of this deleterious cytoskeletal reorganization are unknown. We now find that oxidative stress, a condition characteristic of heart failure, leads to cysteine oxidation of microtubules. Our electron and fluorescence microscopy experiments revealed regions of structural damage within the microtubule lattice that occurred at locations of oxidized tubulin. The incorporation of GTP-tubulin into these damaged, oxidized regions led to stabilized "hot spots" within the microtubule lattice, which suppressed the shortening of dynamic microtubules. Thus, oxidative stress may act inside of cardiac myocytes to facilitate a pathogenic shift from a sparse microtubule network into a dense, aligned network. Our results demonstrate how a disease condition characterized by oxidative stress can trigger a molecular oxidation event, which likely contributes to a toxic cellular-scale transformation of the cardiac myocyte microtubule network.

Keywords: H9c2; cardiomyocytes; cysteine oxidation; microtubule dynamics; microtubule repair; oxidative stress; rescue; tubulin.

Figure 1:. Oxidative stress leads to increased density of the microtubule cytoskeleton in cardiac myocytes.

(A) Left: DHE-loaded live H9c2 cells treated with 0 mM or 0.1 mM H₂O₂. Right: Median nuclear DHE fluorescence intensity normalized to median cytoplasmic background signal for each cell; p<<0.0001, t-test (see methods). Sample sizes in parenthesis indicate number of images analyzed, with multiple cells per image. Dashed indicates baseline value, as all values were normalized to the overall median value of the control data set. (B) Left: Live H9c2 cells that express GFP-tubulin treated with 0 mM or 0.1 mM H₂O₂. Right: Microtubule density as assessed by dividing total microtubule area by total cell area (see methods); p<<0.0001, t-test (see methods). Sample sizes in parenthesis indicate number of cells. (C) Left: Primary cardiac myocytes exposed to 0 mM or 0.1 mM H₂O₂ and immunostained for α-tubulin (green). Right: Microtubule density as assessed by dividing total microtubule area by total cell area (see methods); p<<0.00037, t-test (see methods). Sample sizes in parenthesis indicate number of cells. (D) Tip displacement of representative microtubules from live H9c2 cells that express GFP-tubulin, treated with 0mM or 1mM H₂O₂. (E) Average fraction of time microtubules spent in growth/pausing (left; p<0.00001), or shortening (right; p<0.00001). Sample sizes as shown in parenthesis represent number of microtubules analyzed. P-values determined from calculated Z-statistics for proportions. All box and whisker plots: Crosses: Mean; Bar: Median; Box: first-third quartiles.

Figure 2:. Oxidative stress increases rescue frequency in dynamic microtubules.

(A) Representative time courses during fluorescence imaging of Amplex Red fluorescence intensity as a readout for residual ROS (see methods). All intensity values matched at 6 minutes imaging time to compensate for differing initial conditions. (B) Normalized Amplex Red intensity at 40 min. Amplex Red intensity measurements were normalized to the mean intensity of the control condition (blue). Green dashed line represents the fold increase in ROS for H₂O₂-treated H9c2 cells, shown in Fig. 1A. (C) Top: Schematic of TIRF experiments to measure microtubule length dynamics. Bottom: Representative kymographs of dynamic microtubules in the presence of 0 mM H₂O₂ (left), 0.5 mM H₂O₂ (middle), and 1 mM H₂O₂ (right) (red, GMPCPP-stabilized microtubule seeds; green, Alexa-Fluor-488 dynamic microtubule extensions; yellow arrows: rescue events). (D) Microtubule growth rate as a function of H₂O₂ concentration (n=280, 265, 149, 123 from 0 to 1 mM on graph). (E) Microtubule shortening rate as a function of H₂O₂ concentration (n=41, 39, 41, 39 from 0 to 1 mM on graph). (F) Microtubule catastrophe frequency as a function of H₂O₂ concentration (n=280, 265, 149, 123 from 0 to 1 mM on graph). (G) Microtubule rescue frequency, calculated as the frequency of a rescue event per catastrophe, and normalized to mean microtubule length at catastrophe, n=280, 265, 149, 123 catastrophe events from 0 to 1 mM on graph, absolute number of rescue events observed, from 0 to 1 mM on graph: n=20, 45, 26, 90. All error bars, in all panels, mean ± S.E.M.

Figure 3:. H₂O₂ exposure leads to tubulin cysteine oxidation

(A) Schematic of mass spectrometry sample preparation for microtubules reconstituted in vitro. (B) Relative abundance of tubulin post-translational modifications measured via mass spectrometry as described in panel A. Parentheses indicate residues associated with each modification. Results for Trypsin digestion shown, results for Chymotrypsin digestion in Fig. S3A. Inset: number of oxidized Cysteine residues (C) Schematic of DCP-Rho1 western blotting sample preparation for microtubules reconstituted in vitro, to detect the concentration of oxidized cysteine residues. (D) Representative western blot for microtubules treated with increasing H₂O₂ concentrations. Anti-Rhodamine antibody was used to detect DCP-Rho1-bound tubulin. (E) Quantification of DCP-Rho1 blot intensities, normalized to total α-tubulin in each case. Circle, square, and asterisks: 3 independent Western blots. (F) Schematic of DCP-Rho1 western blotting sample preparation for H9c2 cells, to detect the concentration of oxidized cysteine residues. (G) Representative western blot for H9c2 cells treated with increasing H₂O₂ concentrations. Anti-Rhodamine antibody was used to detect DCP-Rho1-bound tubulin. The intensity of bands between 45–66 kD were summed for quantification in each lane. (H) Quantification of DCP-Rho1 blot intensities for H9c2 cells, normalized to total α-tubulin in each case. Circle, square, and asterisks: 3 independent Western blots.

Figure 4:. Oxidative stress leads to structural damage in the GDP-tubulin microtubule lattice.

(A) Representative electron microscopy images of GDP-tubulin microtubules treated with 0 mM H₂O₂ (top) and 0.5 mM H₂O₂ (bottom) for 1h. Red arrows, defects and openings in the microtubule lattice. (B) Left: Method of microtubule structural alteration quantification, adapted from Reid et al. 2017. Width deviation (top) and curvature (middle) were calculated for microtubules, and a Structure Metric (S) was quantified (bottom equation). Right: Structure Metric quantified for 0, 0.25, and 0.5mM H₂O₂, all values normalized to the control grand mean. p=0.00145, calculated via single-factor ANOVA. Crosses: Mean; Bar: Median; Box: first-third quartiles; sample sizes represent frames analyzed, many microtubules per frame. Total length of analyzed microtubules from left to right on graph: 75 μm, 44 μm, and 52 μm. Individual comparisons calculated via t-test: 0 and 0.25mM H₂O₂ (p<0.0001), 0 and 0.5mM H₂O₂ (p<0.0001), 0.25 and 0.5mM H₂O₂ (p<0.0001).

Figure 5:. Oxidative-stress induced damage to the microtubule lattice is repaired via the incorporation of GTP-tubulin.

(A) Schematic of microtubule repair assay to measure the incorporation of GTP-tubulin (green) into damaged areas on Taxol-stabilized GDP-tubulin microtubules (red). (B) Left: TIRF microscopy images of GFP-Tubulin (green) and Taxol-stabilized microtubules (red). White arrows: microtubule growth via addition of GTP-tubulin to microtubule ends (excluded from analysis). Yellow arrows: incorporation of GTP-tubulin (green) into damaged areas on the GDP-tubulin lattice (red). Right: Quantification of the coverage area of GTP-tubulin (green) lattice incorporation divided by the total GDP-tubulin microtubule lattice area (red) (p<<0.0001, calculated from single-factor ANOVA). Green tubulin growth from microtubule ends is excluded from the analysis. Individual comparisons calculated via t-test: 0 and 0.25mM H₂O₂ (p<0.005), 0 and 0.5mM H₂O₂ (p<0.0001), 0.25 and 0.5mM H₂O₂ (p<0.0001). Crosses: Mean; Bar: Median; Box: first-third quartiles; sample sizes represent number of images, many microtubules per image. (C) Representative electron microscopy images of Taxol-stabilized microtubules treated with 0 mM H₂O₂ (top) and 0.5 mM H₂O₂ (bottom) followed by repair via GTP-tubulin. Structure Metric quantification shown in Fig. S2C. (D) Left: TIRF microscopy image of 0.5 mM H₂O₂-treated microtubule (blue), GTP-tubulin (green), and DCP-Rho1 (red). White arrows: incorporation of GTP tubulin (green) into microtubule lattice co-localizes with DCP-Rho1 binding (red) within the microtubule. Right: Cross-correlation function of GTP-tubulin repair incorporation and DCP-Rho1 (black), and cross-correlation function of DCP-Rho1 and the microtubule signal (grey). Cross-correlation function plotted as function of absolute value of lags, dashed lines represent 95% confidence intervals, n=83 microtubules. (E) Left: TIRF microscopy image of 0.5 mM H₂O₂-treated microtubule (blue), GTP-tubulin (green), and Mal3-mCherry (red). Yellow arrows: incorporation of GTP tubulin (green) into microtubule lattice co-localizes with Mal3-mCherry binding (red) within the microtubule. Right: Cross-correlation function of GTP-tubulin repair incorporation and Mal3-mCherry (black), and cross-correlation function of Mal3-mCherry and the microtubule signal (grey). Cross-correlation function plotted as function of absolute value of lags, dashed lines represent 95% confidence intervals, n=100 microtubules.

Figure 6:. Oxidative stress leads to GTP-tubulin repair islands in dynamic microtubules.

(A) Schematic of Mal3-GFP binding assay for dynamic microtubules in the presence of oxygen scavenging enzymes. Left: In a dynamic microtubule assay, Mal3-GFP typically binds to growing microtubule ends. Right: Mal3-GFP may bind to damaged areas on the lattice into which GTP-tubulin has incorporated. (B) Left: Representative TIRF images of Mal3-GFP binding assay, in which Mal3-GFP (green) binds the dynamic microtubule extension (red) polymerized from stabilized seeds (white). Mal3-GFP binds to growing microtubule tips, as expected (cyan arrows), but can also be observed within the microtubule lattice (white arrow), especially in the presence of H₂O₂ (bottom). Right: Quantification of Mal3-GFP coverage fraction on microtubules. Crosses: Mean; Bar: Median; Box: first-third quartiles; sample sizes represent number of images, many microtubules per image. p<<0.0001, calculated from single-factor ANOVA. Individual comparisons calculated via t-test: 0 and 0.25mM H₂O₂ (p<0.0001), 0 and 0.5mM H₂O₂ (p<0.0001), 0.25 and 0.5mM H₂O₂ (p<0.001) (C) Incorporation of GTP-tubulin (red) into the GDP-tubulin lattice (grey) may lead to stabilized “hot spot” areas within the GDP-tubulin lattice. (D) Left: kymograph with sequential rescue events, and measurement of Δr, which is the distance between two sequential rescue events along the length of the microtubule. Yellow arrows indicate rescue events. Double magenta arrow indicates photobleaching of stabilized microtubule lattice beyond the rescue “hot spot”. Right: Two sequential rescue locations are nearer to each other than if a random rescue location is selected on the second microtubule (p<0.0001, t-test). Crosses: Mean; Bar: Median; Box: first-third quartiles; sample sizes indicated number of sequential events analyzed. (E) Model for oxidative stress mediated remodeling of the cardiac myocyte microtubule cytoskeleton: the switch from a sparse microtubule network (left) into a dense network (right) suggests that lengthened dynamic microtubules (red) may be stabilized by interaction and binding of the growing microtubule plus-ends with intermediate filaments at the Z-disks (blue) (Robison et al., 2016).