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. 2021 Oct 19;10:e65512. doi: 10.7554/eLife.65512

Human Erbb2-induced Erk activity robustly stimulates cycling and functional remodeling of rat and human cardiomyocytes

Nicholas Strash 1, Sophia DeLuca 1, Geovanni L Janer Carattini 2, Soon Chul Heo 2, Ryne Gorsuch 2, Nenad Bursac 1,2,✉
Editors: Noriaki Emoto3, Matthias Barton4
PMCID: PMC8589446  PMID: 34665129

Abstract

Multiple mitogenic pathways capable of promoting mammalian cardiomyocyte (CM) proliferation have been identified as potential candidates for functional heart repair following myocardial infarction. However, it is unclear whether the effects of these mitogens are species-specific and how they directly compare in the same cardiac setting. Here, we examined how CM-specific lentiviral expression of various candidate mitogens affects human induced pluripotent stem cell-derived CMs (hiPSC-CMs) and neonatal rat ventricular myocytes (NRVMs) in vitro. In 2D-cultured CMs from both species, and in highly mature 3D-engineered cardiac tissues generated from NRVMs, a constitutively active mutant form of the human gene Erbb2 (cahErbb2) was the most potent tested mitogen. Persistent expression of cahErbb2 induced CM proliferation, sarcomere loss, and remodeling of tissue structure and function, which were attenuated by small molecule inhibitors of Erk signaling. These results suggest transient activation of Erbb2/Erk axis in CMs as a potential strategy for regenerative heart repair.

Research organism: Human, Rat

Introduction

The adult mammalian heart is composed primarily of post-mitotic cardiomyocytes (CMs) (Bergmann et al., 2009; Mollova et al., 2013). Due to an apparent lack of resident stem cells (van Berlo et al., 2014), the heart is unable to replace lost CMs following myocardial infarction (MI), and instead undergoes fibroblast-mediated scarring, resulting in a decline in cardiac function. One potential approach to regenerate the heart following MI is to stimulate the proliferation of endogenous CMs by gene therapy targeting cell cycle regulation (Leach and Martin, 2018; Lin et al., 2014; Mohamed et al., 2018; Tzahor and Poss, 2017). While inducing adult CM proliferation is only the first step toward achieving efficient cardiac repair post-MI, it is arguably the most challenging and important one. A major question in the field, however, is that gene or pathway activation in particular is optimal for inducing human CM proliferation and restoration of function.

Several approaches involving increased expression of cell cycle-related proteins and modulation of the Hippo, neuregulin (Nrg1), or Wnt signaling pathways have been shown to generate robust proliferative responses in zebrafish and rodent CMs. Specifically, overexpression of Cyclin D2 alone or a combination of Cyclin-dependent kinase 1 (CDK1), CDK4, Cyclin B1, and Cyclin D1 promoted cell cycle activation in post-mitotic mouse, rat, and human CMs in vitro and in mouse hearts in vivo (Fan et al., 2019; Mohamed et al., 2018; Zhu et al., 2018). Hippo pathway modulation via overexpression of constitutively active (ca) Yap variants (incapable of being phosphorylated and degraded) led to robust proliferative responses in vitro and in vivo through chromatin alteration surrounding proliferation-inducing genes (Byun et al., 2019; Monroe et al., 2019). The mitogen Nrg1 induced CM proliferation in zebrafish through activation of its co-receptor, Erbb2 (Bersell et al., 2009; Gemberling et al., 2015), and overexpression of caErbb2 promoted CM proliferation in adult mice by inducing CM dedifferentiation (D’Uva et al., 2015), possibly via Yap activation (Aharonov et al., 2020). Wnt stimulation by small-molecule inhibition of GSK3β (Buikema et al., 2020; Fan et al., 2018; Mills et al., 2019) or induction of β-catenin release from the cell membrane (Fan et al., 2018) induced proliferation in human CMs in vitro. Yet, there have been no studies that directly compare the pro-proliferative capacity of these different mitogenic pathways in parallel.

In this report, we directly compared the effects of manipulating different mitogenic pathways on in vitro cell cycle activation in CMs from various species and maturation levels, including 2D monolayer cultures of human-induced pluripotent stem cell-derived CMs (hiPSC-CMs; Shadrin et al., 2016; Zhang et al., 2013) and neonatal rat ventricular myocytes (NRVMs), as well as functional 3D engineered NRVM tissues (cardiobundles) (Helfer and Bursac, 2020; Jackman et al., 2016). We then probed the mechanisms underlying the observed mitogenic responses. We found that the human, but not rat (D’Uva et al., 2015), caErbb2 ortholog (cahErbb2) induced the most robust proliferative effects in hiPSC-CMs and NRVMs, which were associated with significant changes in CM morphology and function and mediated via upregulation of the Erk signaling pathway.

Results

Lentiviral expression of mitogens promotes hiPSC-CM proliferation without inducing apoptosis

Lentiviral vectors (LVs) were designed with the MHCK7 promoter (Salva et al., 2007) driving muscle-specific expression of mitogens together with a mCherry reporter (Figure 1—figure supplement 1) and used to transduce hiPSC-CMs and NRVMs. We applied a flow cytometry strategy (Figure 1—figure supplement 2) validated using an established hiPSC-CM mitogen (GSK3 inhibitor, CHIR99021) (Buikema et al., 2020; Mills et al., 2019) to determine whether an LV-induced mitogen expression resulted in cell cycle activation or apoptosis specifically in mCherry-labeled CMs. Compared to LV-driven expression of mCherry only, hiPSC-CMs transduced with LVs (Figure 1A) encoding caCtnnb1 (ca β-catenin), Ccnd2 (Cyclin D2), carErbb2, or cahErbb2, but not caYap8SA, exhibited significantly higher incorporation of 5-ethynyl-2′-deoxyuridine (EdU), indicating greater DNA synthesis (Figure 1B). Increased numbers of CMs expressing phosphorylated histone H3 (H3P), an indicator of the mitotic (M) phase of the cell cycle, were also found with cahErbb2, caCtnnb1, and Ccnd2 transduction, with cahErbb2 appearing to have the most robust effects (Figure 1C). Since cultured hiPSC-CMs are relatively immature, we also assessed whether cahErbb2 treatment would increase cell cycle activity in hiPSC-CMs cultured in a maturation medium (MM) shown to reduce proliferation and promote contractile function in human CMs (Mills et al., 2017). While the MM reduced EdU incorporation in CMs compared to our standard culture medium, cahErbb2 LV treatment in MM consistently increased EdU incorporation and H3P expression in CMs (Figure 1—figure supplement 3). Furthermore, we observed comparable percentages of diploid and polyploid hiPSC-CMs between control and LV-treated total or EdU+ CMs (Figure 1D and E). Collectively, these results showed that hiPSC-CMs with LV-mediated expression of cahErbb2, caCtnnb1, and Ccnd2 were induced to enter DNA synthesis and mitotic phases of the cell cycle at a higher rate than control hiPSC-CMs, and continued to undergo successful cytokinesis. Additionally, from cleaved caspase-3 (Cc3) analysis, transduced mitogens did not increase CM apoptosis, with caYap8SA having an anti-apoptotic effect (Figure 1F). In contrast, both increased DNA synthesis and mitosis as well as pro-apoptotic effects were found with the application of CHIR99021 (Figure 1—figure supplement 2B; Mills et al., 2017). Taken together, increased EdU incorporation with no change in CM polyploidy or apoptosis upon transduction with caCtnnb1, Ccnd2, carErbb2, or cahErbb2 LVs indicated induced CM proliferation.

Figure 1. LV-delivered mitogens drive hiPSC-CM proliferation in monolayers.

(A) Schematic of experimental design in hiPSC-CM monolayers. (B–F) Flow cytometry analysis of mCherry+ hiPSC-CMs showing (B) fold-change (FC) in EdU incorporation relative to control LV-transduced hiPSC-CMs, (C) percentage of H3P+ CMs, (D, E) percentage of 2N and >2N cells in all CMs (D) and EdU+ CMs (E), and (F) percentage of apoptotic Cc3+ CMs. (G, H) Analysis of relative (G) gene expression of Yap and its targets Ctgf and Cyr61, and (H) total and active Yap protein abundance in caYap8SA-transduced vs. control hiPSC-CMs. (I,J) Representative immunostaining images (I) and quantified nuclear mean fluorescence intensity (MFI; J) of YAP in caYap8SA-transduced versus control hiPSC-CMs. (K, L) Analysis of relative (K) expression of Ctnnb1 and Wnt-signaling genes Lef1 and Axin2 and (L) Ctnnb1 protein abundance in caCtnnb1-transduced versus control hiPSC-CMs. (M, N) Analysis of relative Ccnd2 (M) gene and (N) protein expression and (O, P) representative immunostaining images (O) and quantified nuclear MFI (P) of Ccnd2 in Ccnd2-transduced versus control hiPSC-CMs. Data: box and whiskers showing distribution and min to max. Column graphs showing mean+ SD (*p<0.05, **p<0.01, ***p<0.001 vs. Ctrl LV). See Supplementary file 1 for sample numbers and complete statistical information for all figures. Cc3, cleaved caspase-3; hiPSC-CM, human-induced pluripotent stem cell-derived cardiomyocyte; LV, lentiviral vector.

Figure 1.

Figure 1—figure supplement 1. Lentiviral design and transduction efficiency in CM monolayers.

Figure 1—figure supplement 1.

(A) Schematic depicting compositions of lentiviral constructs used to perturb specified pathways. (B–E) Flow cytometry analysis of mCherry signal was used to quantify lentiviral transduction efficiency in (B) hiPSC-CM and (C) NRVM monolayers. Data: box and whiskers showing distribution and min to max (*p<0.05, **p< 0.01, ***p<0.001 vs. Ctrl LV). hiPSC-CM, human-induced pluripotent stem cell-derived cardiomyocyte; LV, lentiviral vector; NRVM, neonatal rat ventricular myocyte.
Figure 1—figure supplement 2. Flow cytometry method for analysis of CM proliferation and apoptosis.

Figure 1—figure supplement 2.

(A) Representative flow cytometry analysis plots showing gating strategies for various stains. All samples used the same indicated FSC-A by SSC-A and FSC-H by FSC-A gating to gate all single cells while excluding doublets. For cTnT staining to verify differentiation purity, the isotype is in red and the stained sample is in blue. For EdU staining, the unstained sample is in red and the stained sample is in blue. For mCherry detection, the non-transduced sample is in red and the transduced sample is in blue. Plots shown for hiPSC-CMs; NRVM analysis was conducted in the same manner. (B) Validation of the flow cytometry analysis method in hiPSC-CMs exposed for 48 hr to a known mitogen, the GSK-3 inhibitor CHIR99021 (2 µM), and simultaneously incubated with EdU. Data: box and whiskers showing distribution and min to max (*p<0.05, **p<0.01, ***p<0.001 vs. Ctrl LV). hiPSC-CM, human-induced pluripotent stem cell-derived cardiomyocyte; LV, lentiviral vector; NRVM, neonatal rat ventricular myocyte.
Figure 1—figure supplement 3. cahErbb2 induces cycling in low-glucose, palmitate-containing maturation culture media.

Figure 1—figure supplement 3.

(A) Schematic of experimental design in hiPSC-CM monolayers. (B) Flow cytometry analysis of control mCherry+ hiPSC-CMs, showing the fold-change (FC) in CM EdU incorporation in a maturation media (MM) and control media (Mills Ctrl) from Mills et al. relative to our standard media used in Figure 1 (Stand). (C, D) Flow cytometry analysis of hiPSC-CMs transduced with cahErbb2 or control lentivirus (LV) and cultured in MM, showing (C) relative FC in CM EdU incorporation or (D) H3P expression. Data: box and whiskers showing distribution and min to max (*p<0.05, **p<0.01, ***p<0.001 vs. Ctrl LV). hiPSC-CM, human-induced pluripotent stem cell-derived cardiomyocyte.
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Lentiviral expression of mitogens in hiPSC-CMs may activate negative feedback loops

We then assessed molecular effects of LV transduction and found that caYap8SA-transduced hiPSC-CMs exhibited significantly increased gene expression of Yap and its downstream targets Ctgf and Cyr61 (Figure 1G). However, the expression of the total and active, non-phosphorylated Yap protein was significantly decreased (Figure 1H). Immunostaining of transduced hiPSC-CMs further revealed that the nuclear abundance of active Yap was unchanged by caYap8SA expression (Figure 1I and J). Because caYap8SA cannot be phosphorylated and degraded, these findings may be explained by the activation of a negative feedback loop that degraded endogenous Yap protein to compensate for caYap8SA overexpression, which in turn attenuated the mitogenic effects in caYap8SA-transduced hiPSC-CMs. We further assessed caCtnnb1-transduced hiPSC-CMs and found that the gene expression of Ctnnb1 was increased, but also noted an increased expression of Lef1 and Axin2 (Figure 1K), potentially signifying the presence of a Wnt pathway-mediated negative feedback inhibitory to Ctnnb1 expression (Bernkopf et al., 2014; Lustig et al., 2002). Supporting this hypothesis, we also observed no difference in Ctnnb1 protein expression between control and transduced cells (Figure 1L). Similar to caYap8SA and caCtnnb1, we further found increased Ccnd2 gene but not protein expression in Ccnd2-transduced hiPSC-CMs (Figure 1M and N). Still, immunostaining analysis revealed that Ccnd2-transduced hiPSC-CMs exhibited higher nuclear abundance of the protein (Figure 1O and P), which likely contributed to the observed increase in CM cycling (Figure 1B and C; Zhu et al., 2018). Overall, while these results suggest that LV-mediated expressions of various mitogens in hiPSC-CMs can induce post-transcriptional negative feedback responses to limit protein overexpression, mechanistic underpinnings of these processes remain to be additionally studied.

cahErbb2 induces increased cell cycle activity in NRVM monolayers associated with sarcomere disassembly

To further compare the effects of studied mitogens in CMs from different species and maturity levels, we utilized cultured NRVMs. Specifically, NRVMs were transduced with the LVs the day of seeding and analyzed by flow cytometry at 14 days of monolayer culture, 2 days after EdU application (Figure 2A). We found that expression of cahErbb2 but not other mitogens resulted in increased EdU incorporation in NRVMs, while both Ccnd2 and cahErbb2 yielded increased H3P expression (Figure 2B and C). However, NRVMs transduced with some of the mitogens showed a significantly decreased fraction of diploid and increased fraction of polyploid CMs (Figure 2D), indicating that post-12 days of NRVM culture LV-induced cycling events led to CM polyploidization rather than cytokinesis, in contrast to the results in hiPSC-CMs (Figure 1D). This inference was supported by the finding that compared to control LV, the diploid fraction of EdU+ NRVMs was significantly decreased and polyploid fraction significantly increased in all LV-treated groups (Figure 2E). Taken together, these results revealed that by 14 days of 2D NRVM culture, cahErbb2 was still able to promote cell cycle entry and mitosis, while all tested mitogens led to increased NRVM polyploidy. Interestingly, in both NRVMs and hiPSC-CMs, LV expression of cahErbb2, but not other mitogens, also induced sarcomere disassembly (Figure 2F) without altering expression of sarcomeric genes (Figure 2G) or non-myocyte abundance (Figure 2—figure supplement 1). This result suggested that regulatory changes at a protein level were responsible for the loss of sarcomeric organization with cahErbb2 expression. Furthermore, increased expression of Runx1 (Figure 2G) implied that cell cycle activity and sarcomere loss in cahErbb2-expressing NRVMs were associated with cell dedifferentiation (D’Uva et al., 2015; Kubin et al., 2011).

Figure 2. cahErbb2 induces NRVM cycle entry in monolayers and promotes sarcomere disassembly in NRVMs and hiPSC-CMs.

(A) Schematic of experimental design in NRVM monolayers. (B–E) Flow cytometry analysis of mCherry+ NRVMs showing (B) fold-change (FC) in EdU incorporation relative to control LV-treated NRVMs, (C) percentage of H3P+ CMs, and (D, E) percentage of 2N and >2N cells in all CMs (D) and EdU+ CMs (E). (F) Representative immunostaining images of sarcomeric α-actinin showing sarcomeric structure in LV transduced NRVMs and hiPSC-CMs. (G) Relative expression of Erbb2, sarcomeric genes (Myh6, Myh7, and Tnnt2), and dedifferentiation marker Runx1 in cahErbb2-transduced versus control hiPSC-CMs. Data: box and whiskers showing distribution and min to max. Column graphs showing mean+ SD (*p<0.05, **p<0.01, ***p<0.001 vs. Ctrl LV). hiPSC-CM, human-induced pluripotent stem cell-derived cardiomyocyte; LV, lentiviral vector; NRVM, neonatal rat ventricular myocyte.

Figure 2.

Figure 2—figure supplement 1. cahErbb2 expression does not affect non-CM abundance or CM size in hiPSC-CM and NRVM monolayers.

Figure 2—figure supplement 1.

(A) Quantification of non-CM abundance based on cTnT staining and flow cytometry analysis of hiPSC-CMs (left) and Mef2c expression in immunostained NRVMs (right). (B) Relative CM size in hiPSC-CMs (left) and NRVMs (right) quantified from flow cytometry forward scatters. Data: box and whiskers showing distribution and min to max (*p<0.05, **p<0.01, ***p<0.001 vs. Ctrl LV). hiPSC-CM, human-induced pluripotent stem cell-derived cardiomyocyte; LV, lentiviral vector; NRVM, neonatal rat ventricular myocyte.
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cahErbb2 induces cell cycle activation, growth, and contractile deficit in NRVM cardiobundles

We further tested whether LV delivery of mitogens affected CM proliferation and function in three-dimensional NRVM cardiobundles, currently representing the most mature in vitro model of the postnatal myocardium (; Jackman et al., 2016). NRVMs were transduced at the time of cardiobundle formation, pulsed with EdU at culture day 12, and assessed after 2 weeks of culture (Figure 3A), first ensuring that no studied structural or functional properties differed between control LV-transduced and non-transduced tissues (Figure 3—figure supplement 1). From cardiobundle cross-sectional stainings, EdU+ nuclei were observed in both vimentin+ cardiac fibroblasts (; Jackman et al., 2016) predominantly residing at the tissue periphery and in F-actin+/vimentin− CMs (Figure 3B, top, middle). Similar to hiPSC-CM and NRVM monolayers, all studied mitogens except caYap8SA increased EdU incorporation in NRVM cardiobundles, with cahErbb2 showing the strongest effect (Figure 3C). We then assessed morphological and functional characteristics of cardiobundles and found that cahErbb2 expression uniquely increased both the total cross-sectional area (CSA; Figure 3D) and F-actin+ (CM) area of cardiobundles, leading to the formation of a necrotic core (devoid of Hoechst-positive nuclei; Figure 3B and E), likely caused by limited diffusion of oxygen and nutrients into the center of these avascular tissues (Laschke and Menger, 2016). We also observed increased vimentin+ CSA, indicating increased fibroblast abundance (Figure 3F) and by dividing F-actin+/vimentin− CSA with number of nuclei within that area inferred that CM size was not significantly altered by mitogen expression (Figure 3G). In CM monolayers, we also compared relative cell size using flow cytometry and found that cahErbb2 does not affect CM size (Figure 2—figure supplement 1D, E). Coupled with our measurements in cardiobundles, this confirmed that cahErbb2 expression does not increase CM size in either culture setting or cell type. Finally, similar to the findings in CM monolayers (Figure 2G), only the cahErbb2-transduced cardiobundles showed a near-complete loss of sarcomere structure, despite maintained NRVM alignment (Figure 3B, bottom).

Figure 3. cahErbb2 induces NRVM cycle entry in cardiobundles and promotes sarcomere disassembly and contractile dysfunction.

(A) Schematic of experimental design in NRVM cardiobundles. (B) Representative immunostaining images of cardiobundle cross-sections showing morphology (top), EdU incorporation (middle), and whole-mount tissue showing sarcomere structure (bottom). (C–G) Quantification of immunostained cardiobundle cross-sections for (C) NRVM EdU incorporation and (D) total, (E) F- actin+, (F) vimentin+ cross-sectional area (CSA), and (G) Quantified F-actin+ CSA per nuclei number within this area, shown as a measure of CM size. (H, I) Force analysis in LV-transduced cardiobundles showing (H) representative twitch traces and quantified maximum twitch amplitude and (I) passive force-length and force amplitude at 12% stretch (0% stretch is culture length of 7 mm). Data: box and whiskers showing distribution and min to max. Line plot showing mean+ SEM (*p<0.05, **p<0.01, ***p<0.001 vs. Ctrl LV). LV, lentiviral vector; NRVM, neonatal rat ventricular myocyte.

Figure 3.

Figure 3—figure supplement 1. LV transduction does not affect NRVM cardiobundles.

Figure 3—figure supplement 1.

(A) Representative immunostaining images of cardiobundle cross-sections showing morphology (left), EdU incorporation (middle), and whole-mount tissue showing sarcomere structure (right). (B, C) Quantification of immunostained cardiobundle cross-sections for (B) CM and total EdU incorporation, and (C) total and F- actin+ CSA. (D, E) Force analysis in cardiobundles showing (D) representative twitch traces and quantified maximum twitch amplitude and (E) passive force-length and force amplitude at 12% stretch (0% stretch is culture length of 7 mm). Data: box and whiskers showing distribution and min to max. Line plot showing mean+ SEM (*p<0.05, **p<0.01, ***p<0.001 vs. Ctrl LV). CM, cardiomyocyte; CSA, cross-sectional area; LV, lentiviral vector.
Figure 3—figure supplement 2. Twitch kinetics and unloaded contractile force in cardiobundles.

Figure 3—figure supplement 2.

(A–C) Twitch kinetics in cardiobundles characterized by (A) total twitch duration, (B) time to peak, and (C) relaxation time. (D, E) Passive force-length relationship shown from the slack length where tissues were fully unloaded (passive force=0)—16% stretch (D, 0% stretch is culture length of 7 mm) and corresponding twitch forces measured at a slack length (E). Data: box and whiskers showing distribution and min to max. Line plot showing mean+ SEM (*p<0.05, **p<0.01, ***p<0.001 vs. Ctrl LV). LV, lentiviral vector.
Figure 3—figure supplement 3. Underlying mechanisms of increased passive tension in cahErbb2-expressing cardiobundles.

Figure 3—figure supplement 3.

(A) Representative cross-sectional immunostaining images of cardiobundles made using standard (Ctrl) or 1.4× larger (1.4×) cell/hydrogel volume and corresponding quantifications of nuclei per cross-section (CS), and total and acellular CS area (CSA) shown relative to Ctrl group, as well as total and acellular CSA shown relative to CahErbb2 group. (B) Passive force in 1.4× cardiobundles quantified at 12% stretch shown relative to Ctrl group. (C) Representative cross-sectional immunostaining images and corresponding quantification of collagen I (Coll1) abundance. (D) Vimentin abundance quantified from cardiobundle cross-section images in Figure 3B. (E) Longitudinal tissue sections and corresponding quantification of nestin abundance. Data: box and whiskers showing distribution and min to max (*p<0.05, **p<0.01, ***p<0.001 vs. Ctrl LV or Ctrl). LV, lentiviral vector.
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We then measured contractile force generation in cardiobundles and found a reduced maximum twitch amplitude in tissues transduced with cahErbb2 but not other mitogens (Figure 3H). This loss of maximum active force in cahErbb2 cardiobundles was accompanied by slower twitch kinetics (Figure 3—figure supplement 2A-C), as well as a significant increase in passive tension that indicated increased tissue stiffness (Figure 3I). We then confirmed that reduced contractile force generation due to cahErbb2 expression was also characteristic of mechanically unloaded tissues (Figure 3—figure supplement 2D, E). To examine the potential causes of cahErbb2-induced increase in stiffness, we first generated tissues with 1.4× NRVM/hydrogel volume which exhibited an increased size and necrotic core similar to those of cahErbb2 cardiobundles, however, this did not lead to larger passive tension (Figure 3—figure supplement 3A). We compared the 1.4× tissues to cahErbb2 tissues and found that both the tissue size and acellular area within the tissues were similar, which suggests that a larger tissue alone does not cause greatly increased passive tension as seen with cahErbb2 cardiobundles (Figure 3—figure supplement 3B). We further examined collagen I in cross-sections of cahErbb2 cardiobundles and found similar abundance to that of control tissues, indicating that increased tissue stiffness was not contributed by significant ECM accumulation (Figure 3—figure supplement 3C; Li et al., 2017). However, we found significant upregulation of intermediate filaments nestin and vimentin (Figure 3F, Figure 3—figure supplement 3D, E), suggesting that cahErbb2-induced cell stiffening, at least partly, was responsible for the observed increase in tissue stiffness (Calderone, 2018; Ward and Iskratsch, 2020). Taken together, among the studied mitogens, cahErbb2 induced the most potent pro-proliferative effects in both rat and human CMs, which also involved the sarcomere loss characteristic of CM dedifferentiation observed in carErbb2-expressing mice (D’Uva et al., 2015). Furthermore, in engineered NRVM cardiobundles, cahErbb2 mitogenic effects were uniquely associated with the increase in tissue size, loss of contractile force, increased intermediate filament expression, and tissue stiffening.

Human but not rat caErbb2 activates Erk signaling in hiPSC-CMs

We were intrigued by the finding that human but not rat caErbb2 exerted significant mitogenic effects in hiPSC-CMs and NRVMs, and decided to further probe the mechanisms of cahErbb2 action. Previously, the expression of rat caErbb2 in mouse CMs led to sarcomere disassembly in vitro and in vivo, while downstream Erk and Akt signaling were found to be the primary drivers of carErbb2-induced CM cell cycle activation (D’Uva et al., 2015). In hiPSC-CMs in our study, cahErbb2 but not carErbb2 expression resulted in increased pErk and Erk abundance (Figure 4A). Moreover, previously reported pAkt increase was not observed for either rat or human caErbb2 expression, with carErbb2 expression reducing total Akt (Figure 4A). We then measured the relative gene expression of Erk downstream targets indicative of increased Erk activity (Wagle et al., 2018). Whereas cahErbb2 expression robustly increased transcription of multiple Erk targets, carErbb2 expression caused no such increase (Figure 4B). Consistent with the cahErbb2-induced Erk activation, we also observed an increase in nuclear localization of Erk protein (Figure 4C), and further confirmed Erk activation by analyzing the expression of additional gene targets (Figure 4D). In contrast to Erk, Akt localization was unaffected by cahErbb2 expression (Figure 4E). Interestingly, cahErbb2 but not carErbb2 also increased the abundance of phosphorylated ribosomal protein S6 (pS6) in Western blots (Figure 4F), which was further confirmed by immunostaining (Figure 4G). pS6 is usually considered as a downstream target of mTOR, which can be activated by stimulation of Akt or Erk pathway (Roux et al., 2007; Warfel et al., 2011). Curiously, pmTOR expression was unaffected by cahErbb2 (Figure 4F) and the Akt pathway was not upregulated (Figure 4A and B); thus, the human caErbb2-induced pS6 increase likely resulted from an mTOR-independent, Erk-dependent mechanism previously associated with Ser235/236 phosphorylation of pS6 (Roux et al., 2007).

Figure 4. cahErbb2 but not carErbb2 activates Erk signaling to drive proliferation in CMs.

Figure 4.

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(A–B) Representative Western blots and quantified relative protein (A) and Erk target gene expression (B) in carErbb2- or cahErbb2-transduced versus control hiPSC-CM monolayers. (C) Representative immunostaining images and quantified nuclear MFI of Erk in cahErbb2-transduced versus control hiPSC-CMs. (D) Quantified relative Erk target gene expression in cahErbb2-transduced versus control hiPSC-CM monolayers. (E) Representative immunostaining images and quantified nuclear MFI of Akt in cahErbb2-transduced versus control hiPSC-CMs. (F) Representative Western blots and quantified relative phosphorylated mTOR (pmTOR) and ribosomal protein S6 (pS6) expression in carErbb2- or cahErbb2-transduced versus control hiPSC-CMs. (G) Representative immunostaining images and quantified nuclear MFI of pS6 in cahErbb2-transduced versus control hiPSC-CMs. Data: box and whiskers showing distribution and min to max. Column graphs showing mean+ SD (*p<0.05, **p<0.01, ***p<0.001 vs. Ctrl LV). hiPSC-CM, human-induced pluripotent stem cell-derived cardiomyocyte; LV, lentiviral vector MFI, mean fluorescence intensity.

Erk or Mek inhibition attenuates cahErbb2-induced effects in hiPSC-CMs and NRVMs

To determine whether upregulated Erk signaling was required for the observed effects of cahErbb2 expression on hiPSC-CMs, we performed flow cytometry analysis in cells treated with the Mek inhibitor (Meki) PD0325901 (Mirdametinib) or the Erk inhibitor (Erki) SCH772984 applied for 48 hr before sample collection; EdU was applied during the final 24 hr to capture DNA synthesis that only occurred after adding the inhibitors (Hashimoto et al., 2014). We simultaneously measured Cc3 abundance because excessive Erk inhibition was expected to interfere with homeostatic Erk activity required to promote cell survival (Lu and Xu, 2006). As expected, in both control and cahErbb2-treated hiPSC-CMs, Meki or Erki treatment resulted in a dose-dependent decrease in EdU incorporation and a dose-dependent increase or an increasing trend in apoptotic events (Figure 5—figure supplement 1). The increased Erk activity in cahErbb2-transduced CMs appeared to both protect against the Erki/Meki-induced apoptosis and necessitate higher inhibitor doses to maximally block EdU incorporation (Figure 5—figure supplement 1). We then tested whether the inhibition of Erk signaling pathway can prevent cahErbb2-induced effects in NRVM cardiobundles by applying 100 nM Erki or 100 nM Meki between days 8 and 14 of culture (Figure 5A). We found that both inhibitors reduced CM EdU incorporation in control and cahErbb2-transduced cardiobundles, while the Erki-treated cahErbb2 tissues still showed higher rates of cycling compared to the control (Figure 5B, middle, Figure 5C). Strikingly, the Erk and Mek inhibition also attenuated cahErbb2-induced deficits in tissue morphology, evident from the findings that inhibitor-treated, cahErbb2 cardiobundles had total, F-actin+, and vimentin+ CSA comparable to those of control cardiobundles (Figure 5B and D–F) and showed improved sarcomere structure, especially with the Erki treatment (Figure 5B). Furthermore, while the inhibitors did not affect force responses in the control cardiobundles, inhibitor-treated cahErbb2 tissues exhibited higher active force (Figure 5G) and lower passive tension (Figure 5H), as well as improved twitch kinetics (Figure 5—figure supplement 2) compared to vehicle treatment. Collectively, these results suggested that the baseline CM cycling in NRVM cardiobundles is Erk-dependent and that cahErbb2-induced morphological and functional deficits can be prevented or reverted by Erk/Mek inhibition, further providing evidence that Erk pathway is a major effector of cahErbb2 expression in CMs.

Figure 5. Erk or Mek inhibition attenuates cahErbb2-induced effects in NRVM cardiobundles.

(A) Schematic of experimental design in cahErbb2 and Ctrl LV NRVM cardiobundles. (B) Representative immunostaining images of cardiobundle cross-sections showing morphology (top), EdU incorporation (middle), and whole-mount tissue showing sarcomere structure (bottom). (C–F) Quantification of immunostained cardiobundle cross-sections for (C) NRVM EdU incorporation and (D) total, (E) F- actin+, and (F) vimentin+ cross-sectional area (CSA). (G, H) Force analysis in cardiobundles showing (G) representative twitch traces and quantified maximum twitch amplitude and (H) passive force-length and force amplitude at 12% stretch (0% stretch is culture length of 7 mm). Data: box and whiskers showing distribution and min to max. Line plot showing mean+ SEM (*p<0.05, **p<0.01, ***p<0.001 vs. Ctrl LV; #p<0.05, ##p<0.01, ###p<0.001 vs. cahErbb2). LV, lentiviral vector; NRVM, neonatal rat ventricular myocyte.

Figure 5.

Figure 5—figure supplement 1. Erk or Mek inhibition attenuates cahErbb2-induced proliferation in hiPSC-CMs.

Figure 5—figure supplement 1.

(A) Schematic of experimental design in hiPSC-CM monolayers. (B, C) Flow cytometry analysis of cahErbb2-transduced and control mCherry+ hiPSC-CMs treated for 48 hr with vehicle control or increasing doses (10 nM, 100 nM, and 1 µM) of Erk (SCH772984) or Mek (PD0325901) inhibitors showing (B) the fold-change in CM EdU incorporation relative to corresponding vehicle-treated CMs and (C) Cc3 expression. Data: box and whiskers showing distribution and min to max (*p<0.05, **p<0.01, ***p<0.001 vs. Ctrl LV). Cc3, cleaved caspase-3; hiPSC-CM, human-induced pluripotent stem cell-derived cardiomyocyte; LV, lentiviral vector.
Figure 5—figure supplement 2. Twitch kinetics of NRVM cardiobundles treated with Erki or Meki.

Figure 5—figure supplement 2.

(A–C) Twitch kinetics in cardiobundles characterized by (A) total twitch duration, (B) time to peak, and (C) relaxation time. Data: box and whiskers showing distribution and min to max (*p<0.05, **p<0.01, ***p<0.001 vs. Ctrl LV; #p<0.05, ##p<0.01, ###p<0.001 vs. cahErbb2). NRVM, neonatal rat ventricular myocyte.
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Discussion

Development of methods to induce transient proliferation of endogenous or transplanted CMs could lead to therapeutic strategies to restore lost muscle mass and function of the injured heart (Karra and Poss, 2017). In this in vitro study, we directly compared a panel of lentivirally delivered mitogens to identify those capable of inducing the most potent and conserved pro-proliferative effects in CMs from different species, maturation stages, and culture environments. We found that constitutively active human Erbb2 induced the most robust and consistent proliferative response in hiPSC-CMs and NRVMs among rat caErbb2, human caCtnnb1, human Ccnd2, and human caYap8SA. Interestingly, we found evidence for the existence of negative post-transcriptional feedbacks on expression of mitogen proteins following transduction with caYap8SA, caCtnnb1, or Ccnd2 LVs, which appeared strongest in caYap8SA-transduced rat and human CMs where we did not find increased EdU incorporation. A negative feedback mechanism in the Hippo pathway mediated by Lats1/2 upregulation was previously reported when constitutively active Yap was expressed or Sav1 was deleted in mice and cultured cells (Kim et al., 2020; Moroishi et al., 2015; Park et al., 2016). Regardless, our findings appear to contradict the potent proliferative effects of constitutively active Yap mutants observed in previous studies (Mills et al., 2017; Monroe et al., 2019; von Gise et al., 2012), which may be attributable to differences in species and mechanical environment of studied CMs (Aragona et al., 2013; Benham-Pyle et al., 2015; Meng et al., 2018; Panciera et al., 2020; Zhao et al., 2007), and will require further investigations.

Although cahErbb2 caused strong mitogenic effects in CMs, we suspect that this did not translate to improved contractile function in our cardiobundle system for two reasons. First, cell survival in the avascular cardiobundles relies on the ability of oxygen and nutrients to diffuse from the surface to the center of the tissue (Bursac et al., 1999; Laschke and Menger, 2016). This limits the growth of metabolically active, functional myocardium and causes the development of central necrotic core, as observed in both cahErbb2-transduced and control, larger-volume tissues. Second, the LV-induced, continuous cahErbb2 expression in cardiobundles not only produces persistent proliferative effects, but also chronically over-activates Erk pathway leading to sarcomere disorganization and increased tissue stiffness. The partial functional rescue with Erki/Meki treatment suggests that in the vascularized myocardium in vivo, temporally controlled rather than the continuous expression of cahErbb2 could be a strategy to induce both transient CM hyperplasia and, ultimately, following cahErbb2 inactivation, enhanced myocardial function.

We were surprised to find that only the human but not rat ortholog of caErbb2 was able to activate Erk signaling in hCMs and NRVMs, especially considering the rat Erbb2-V663E and human Erbb2-V659E activating mutations are both located in the transmembrane domain and known to promote homo- and hetero-dimerizations of the receptor (Ou et al., 2017). Previously, rat caErbb2 has been shown to drive CM dedifferentiation, proliferation, and hypertrophy when inducibly expressed in transgenic mice (Aharonov et al., 2020; D’Uva et al., 2015). In our study, persistent cahErbb2 expression and downstream Erk activation induced not only CM cycling but also structural (sarcomere disassembly and fibroblast accumulation) and functional (reduced contractile force and increased stiffness) deficits, which in several aspects resembled in vivo pathologic cardiac remodeling mediated by hyperactive Erk signaling (Gallo et al., 2019). While we noticed increased Runx1 expression in cahErbb2-transduced hiPSC-CMs, we did not observe a gene expression pattern characteristic of sustained CM de-differentiation as Myh6, Myh7, and Tnnt2 levels remained unchanged. Although our in vitro systems lack the complexity of an in vivo cardiac milieu (e.g., cellular diversity and related signaling cross-talk), it is possible that the effects of caErbb2 expression in CMs may be species or maturation level-dependent. Further work will be needed to explore if human caErbb2 or its downstream effectors can generate comparable or more potent therapeutic effects than those of rat caErbb2 in both small and large animal studies.

Materials availability

Plasmids generated in this study are available from the corresponding author upon reasonable request, maps of generated plasmids are provided in Source data 4.

Materials and methods

Key resources table.

Reagent type (species) or resource Designation Source or reference Identifiers Additional information
Antibody Anti-Cardiac Troponin T (Rabbit polyclonal) Abcam ab45932 FC (1:200)
Antibody Anti-Sarcomeric Alpha Actinin (Mouse monoclonal) Sigma-Aldrich A7811 IF (1:200)
Antibody Cleaved Caspase-3 (Asp175) (Rabbit polyclonal) Cell Signaling Technology 9661 FC (1:800)
Antibody GAPDH (Mouse monoclonal) Santa Cruz Biotechnology sc-47724 WB (1:1000)
Antibody Mouse IgG1, kappa monoclonal [15-6E10A7] - Isotype Control Abcam ab170190 FC (1:2000)
Antibody Phospho-p44/42 MAPK (Erk1/2) (Thr202/Tyr204) (Rabbit polyclonal) Cell Signaling Technology 9101 WB (1:1000)
Antibody p44/42 MAPK (Erk1/2) (Total Erk) (Rabbit polyclonal) Cell Signaling Technology 9102 WB (1:1000)
Antibody Phospho-Histone H3 (Ser10) (6G3) (Mouse monoclonal) Cell Signaling Technology 9706 FC (1:1000)
Antibody Phospho-mTOR (Ser2448) (Rabbit polyclonal) Cell Signaling Technology 2971 WB (1:1000)
Antibody Phospho-S6 Ribosomal Protein (Ser235/236) (Rabbit polyclonal) Cell Signaling Technology 2211 WB (1:1000)IF (1:100)
Antibody Rabbit IgG, polyclonal - Isotype Control Abcam ab37415 FC (1:2000)
Antibody Recombinant Anti-active YAP1 [EPR19812] (Rabbit polyclonal) Abcam ab205270 WB (1:1000)IF (1:500)
Antibody Recombinant Anti-AKT1 (phospho S473) [EP2109Y] (Rabbit monoclonal) Abcam ab81283 WB (1:5000)
Antibody Recombinant Anti-AKT1+ AKT2+ AKT3 [EPR16798] (Rabbit monoclonal) Abcam ab179463 WB (1:10,000)IF (1:100)
Antibody Recombinant Anti-Cyclin D2 (Rabbit monoclonal) Abcam ab207604 WB (1:1000)IF (1:100)
Antibody Recombinant Anti-Vimentin [EPR3776] (Rabbit monoclonal) Abcam ab92547 IF (1:500)
Antibody YAP (D8H1X) (Total Yap) (Rabbit monoclonal) Cell Signaling Technology 14074 WB (1:1000)IF (1:200)
Antibody β-Catenin (Carboxy-terminal Antigen) (Rabbit polyclonal) Cell Signaling Technology 9587 WB (1:1000)
Chemical compound, drug SCH772984 Cayman Chemical 19166  
Chemical compound, drug PD0325901 Sigma-Aldrich PZ0162-5MG  
Commercial assay, kit Click-iT EdU Alexa Fluor 647 Flow Cytometry Assay Kit Thermo Fisher Scientific C10419  
Commercial assay, kit Click-iT EdU Alexa Fluor 488 Imaging Kit Thermo Fisher Scientific C10337  
Cell line (Homo sapiens, male) DU11 iPSC Line Duke University Stem Cell Core  
Cell line (H. sapiens) Hek293T ATCC CRL-3216  
Strain, strain background (Rattus Norvegicus) P2 Sprague-Dawley Rat Pups Charles River  
Recombinant DNA reagent pLV-beta-catenin deltaN90 pLV-beta-catenin deltaN90 was a gift from Bob Weinberg Addgene plasmid # 36985 Used to generate new plasmids
Recombinant DNA reagent HER2 CA (V659E) HER2 CA (V659E) was a gift from Mien-Chie Hung Addgene plasmid # 16259 Used to generate new plasmids
Recombinant DNA reagent R777-E020 Hs.CCND2-nostop R777-E020 Hs.CCND2-nostop was a gift from Dominic Esposito Addgene plasmid # 70304 Used to generate new plasmids
Recombinant DNA reagent pSV2 neuNT pSV2 neuNT was a gift from Bob Weinberg Addgene plasmid # 10,918 Used to generate new plasmids
Recombinant DNA reagent pCMV-flag YAP2 5SA pCMV-flag YAP2 5SA was a gift from Kunliang Guan Addgene plasmid # 27371 Used to generate new plasmids
Recombinant DNA reagent Pax2 psPAX2 was a gift from Didier Trono Addgene plasmid # 12260 Used to generate lentivirus in HEK293Ts
Recombinant DNA reagent VSVG pMD2.G was a gift from Didier Trono Addgene plasmid # 12259 Used to generate lentivirus in HEK293Ts
Recombinant DNA reagent Control Lentivirus (MHCK7-mCherry) This manuscript See Materials and methods section
Recombinant DNA reagent Cyclin Lentivirus (MHCK7-Ccnd2-P2A-mCherry-NLS) This manuscript See Materials and methods section
Recombinant DNA reagent B-catenin Lentivirus (MHCK7- Ctnnb1(∆90)-P2A-mCherry-NLS) This manuscript See Materials and methods section
Recombinant DNA reagent Human Erbb2 Lentivirus (MHCK7-Erbb2(V659E-P2A-mCherry)) This manuscript See Materials and methods section
Recombinant DNA reagent Rat Erbb2 Lentivirus (MHCK7-Erbb2(V663E-P2A-mCherry-NLS)) This manuscript See Materials and methods section
Recombinant DNA reagent Yap Lentivirus (MHCK7-Yap8SA-P2A-mCherry-NLS) This manuscript See Materials and methods section
Software, algorithm CellProfiler McQuin et al., 2018 https://cellprofiler.org/  
Software, algorithm ImageJ Schneider et al., 2012 https://imagej.nih.gov/ij/  
Software, algorithm FlowJo Software The FlowJo team, 2021  
Software, algorithm GraphPad Prism   https://www.graphpad.com/  
Software, algorithm Matlab    
Sequence-based reagent Yap1   PrimerBank ID: 303523510c1 F:TAGCCCTGCGTAGCCAGTTAR:TCATGCTTAGTCCACTGTCTGT
Sequence-based reagent Myh6   NCBI PrimerBlast F:GCCCTTTGACATTCGCACTGR:GGTTTCAGCAATGACCTTGCC
Sequence-based reagent Myh7   PrimerBank ID: 115496168c1 F:ACTGCCGAGACCGAGTATGR:GCGATCCTTGAGGTTGTAGAGC
Sequence-based reagent Ctgf   PrimerBank ID: 98986335c1 F:CAGCATGGACGTTCGTCTGR:AACCACGGTTTGGTCCTTGG
Sequence-based reagent Cyr61   PrimerBank ID: 197313774c3 F:CAGCATGGACGTTCGTCTGR:AACCACGGTTTGGTCCTTGG
Sequence-based reagent Ctnnb1   PrimerBank ID: 148233337c2 F:CATCTACACAGTTTGATGCTGCTR:GCAGTTTTGTCAGTTCAGGGA
Sequence-based reagent Lef1   PrimerBank ID: 260656055c1 F:AGAACACCCCGATGACGGAR:GGCATCATTATGTACCCGGAAT
Sequence-based reagent Axin2   PrimerBank ID: 195927058c1 F:CAACACCAGGCGGAACGAAR:GCCCAATAAGGAGTGTAAGGACT
Sequence-based reagent Ccnd2   PrimerBank ID: 209969683c3 F:TTTGCCATGTACCCACCGTCR:AGGGCATCACAAGTGAGCG
Sequence-based reagent Erbb2   PrimerBank ID: 54792097c2 F:TGTGACTGCCTGTCCCTACAAR:CCAGACCATAGCACACTCGG
Sequence-based reagent Epha2   PrimerBank ID: 296010835c2 F:AGAGGCTGAGCGTATCTTCATR:GGTCCGACTCGGCATAGTAGA
Sequence-based reagent Epha4   PrimerBank ID: 45439363c3 F:GCAAGGAGACGTTTAACCTGTR:CTTGGGTGAAGCTCTCATCAG
Sequence-based reagent Fn1   PrimerBank ID: 47132556c2 F:AGGAAGCCGAGGTTTTAACTGR:AGGACGCTCATAAGTGTCACC
Sequence-based reagent Dusp5   PrimerBank ID: 62865889c2 F:GCCAGCTTATGACCAGGGTGR:GTCCGTCGGGAGACATTCAG
Sequence-based reagent Dusp6   PrimerBank ID: 42764682c1 F:GAAATGGCGATCAGCAAGACGR:CGACGACTCGTATAGCTCCTG
Sequence-based reagent Spry4   PrimerBank ID: 188595696c1 F:TCTGACCAACGGCTCTTAGACR:GTGCCATAGTTGACCAGAGTC
Sequence-based reagent Etv5   PrimerBank ID: 194018465c1 F:TCAGCAAGTCCCTTTTATGGTCR:GCTCTTCAGAATCGTGAGCCA
Sequence-based reagent Phlda1   PrimerBank ID: 83977458c1 F:GAAGATGGCCCATTCAAAAGCGR:GAGGAGGCTAACACGCAGG
Sequence-based reagent Spry2   PrimerBank ID: 22209007c1 F:CCTACTGTCGTCCCAAGACCTR:GGGGCTCGTGCAGAAGAAT
Sequence-based reagent Dusp4   PrimerBank ID: 325651887c1 F:GGCGGCTATGAGAGGTTTTCCR:TGGTCGTGTAGTGGGGTCC
Sequence-based reagent Etv4   PrimerBank ID: 118918427c2 F:CAGTGCCTTTACTCCAGTGCCR:CTCAGGAAATTCCGTTGCTCT
Sequence-based reagent Fos   PrimerBank ID: 254750707c2 F:GGGGCAAGGTGGAACAGTTATR:CCGCTTGGAGTGTATCAGTCA
Sequence-based reagent Dab2   PrimerBank ID: 349585059c1 F:GTAGAAACAAGTGCAACCAATGGR:GCCTTTGAACCTTGCTAAGAGA
Sequence-based reagent Pdgfa   PrimerBank ID: 197333758c1 F:GCAAGACCAGGACGGTCATTTR:GGCACTTGACACTGCTCGT
Sequence-based reagent Runx1   PrimerBank ID: 169790826c1 F:CTGCCCATCGCTTTCAAGGTR:GCCGAGTAGTTTTCATCATTGCC
Sequence-based reagent Hprt1   PrimerBank ID: 164518913c1 F:CCTGGCGTCGTGATTAGTGR:AGACGTTCAGTCCTGTCCATAA
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NRVM isolation and 2D culture

All animal procedures were performed in compliance with the Institutional Animal Care and Use Committee at Duke University and the NIH Guide for the Care and Use of Laboratory Animals. NRVMs were isolated as previously described (Jackman et al., 2018; Jackman et al., 2016; Li et al., 2017). Briefly, ventricles were harvested from P2 male and female Sprague-Dawley rat pups, minced finely, and pooled before overnight trypsin incubation at 4°C. The following day, the minced ventricular tissue was subjected to several collagenase digestions and filtering steps to yield single-cell suspension. Cells were pre-plated for 1 hr to remove non-myocytes and enrich the NRVM population. The non-adherent cells were resuspended in 2D cardiac medium (DMEM, 10% fetal bovine serum [FBS], penicillin (5 U/ml), and vitamin B12 (2 µg/ml)) and plated onto fibronectin-coated Aclar coverslips at a density of 5× 105 cells per well of a 12-well plate. Twenty-four hours following plating, the medium was changed to only include 5% FBS and full media changes were performed every other day.

Cardiobundle fabrication and 3D culture

NRVM cardiobundles were prepared as previously described (Helfer and Bursac, 2020; Jackman et al., 2018; Jackman et al., 2016). Briefly, 6.5×105 freshly isolated NRVMs were mixed with a fibrin-based hydrogel (2.5 mg/ml fibrinogen, 1 U/ml thrombin, and 10% v/v/Matrigel) and cast in PDMS tissue molds with two 2 mm×7 mm troughs and a porous nylon frame. In experiments testing, the effects of increased cell/hydrogel volume, our standard cell number and gel volume were scaled up by 1.4-fold. The molds containing the hydrogel-cell mixture were incubated at 4°C for 45 min to allow the hydrogel to fully polymerize and attach to the nylon frame. Tissues were then immersed in 3D cardiac medium (Low Glucose DMEM, 10% horse serum, 1% chick embryo extract, aminocaproic acid [1 mg/ml], L-ascorbic acid 2-phosphate sesquimagnesium salt hydrate [50 µg/ml], penicillin [5 U/ml], and vitamin B12 [2 µg/ml]). The following day, the cardiobundles on frames were carefully removed from the molds and cultured in free-floating dynamic conditions on a rocker. Full media changes of 2 ml per well were performed every other day for 14 days.

For experiments utilizing small molecule inhibitors of Erk or Mek, we used SCH772984 (Erki) or PD0325901 (Meki). Both inhibitors were applied from days 8 to 14 after tissue generation at 100 nM, and were compared to a DMSO vehicle control. See Materials table for drug information.

hiPSC maintenance and CM differentiation

BJ fibroblasts from a healthy male newborn (ATCC cell line, CRL-2522) were reprogrammed episomally into hiPSCs at the Duke University iPSC Core Facility and named DU11 (Duke University clone #11) following verification of pluripotency as described previously (Shadrin et al., 2017). hiPSCs were maintained as feeder-free cultures on ESC-Matrigel in mTeSR Plus medium and colony-passaged as small (10–20 cells) clusters every 3 days using 0.5 mM EDTA (1:10 split ratio). All hiPSC-CM experiments were performed using DU11 hiPSCs between passages 24 and 45. Mycoplasma testing was done routinely with commercially available testing kits (MycoAlert, Lonza).

hiPSCs were differentiated into CMs via small-molecule-based modulation of Wnt signaling, as previously described (Lian et al., 2012). Briefly, DU11 hiPSCs were dissociated into single cells using Accutase and plated into ESC-Matrigel coated dishes at 4×105/cm2 with 5 µM Y27632 (ROCK inhibitor). Maintenance media was changed daily prior to differentiation. To induce cardiac differentiation (day 0), cells were incubated in 6 μM CHIR99021 in RPMI-1640 with B27(−) insulin. Exactly 48 h later, CHIR was removed and replaced with basal RPMI/B27(−) medium. On day 3, the cells were incubated in RB- containing 5 uM IWR-1, which was switched to basal RPMI/B27(−) medium on day 5. From days 7 to 10, the cells were cultured in RPMI/B27(+)-insulin with media changed every 2–3 days. Spontaneous contractions of hiPSC-CMs started on days 7–10 of differentiation. Differentiating CM cultures were purified via metabolic selection between days 10 and 14 (Tohyama et al., 2013), by incubation in ‘no glucose’ medium (glucose-free RPMI supplemented with 4 mM lactate, 0.5 mg/ml recombinant human albumin, and 213 μg/ml L-ascorbic acid 2-phosphate) for 48 h. At the end of the selection period, cultures were dissociated into single cells using 0.05% trypsin/EDTA followed by quenching with stop buffer (DMEM, 20% FBS, 20 μg/ml DNAse I [Millipore 260913]) and replated onto fresh Matrigel-coated dishes to remove dead cells and debris. Cells were then maintained in our ‘standard’ media consisting of RPMI/B27(+)-insulin with 2 mg/ml aminocaproic acid, 50 μg/ml L-ascorbic acid 2-phosphate, 0.45 μM 1-thioglycerol, 1% pen/strep, 1% non-essential amino acids, and 1% sodium pyruvate. hiPSC-CM cultures with greater than 90% cTnT positive cells as measured by flow cytometry were used for all experiments. For select experiments, we used maturation media (Mills MM) by Mills et al., 2017 consisting of DMEM with no glucose and no glutamine, with 4% B27 without insulin, 1% GlutaMAX, 200 μM L-ascorbic acid 2-phosphate sesquimagnesium salt hydrate, 1 % penicillin/streptomycin, 1 mM glucose, and 100 μM BSA-palmitate saturated fatty acid complex or control media from the same group (Mills Ctrl) consisting of α-MEM with GlutaMAX, 10% FBS, 200 μM L-ascorbic acid 2-phosphate sesquimagnesium salt hydrate, and 1% Penicillin/Streptomycin.

Experiments utilizing Erk or Mek inhibition were performed using the same small molecules described for NRVM cardiobundles, but we also performed dose-response testing from 10 nM to 1 μM of both compounds and compared to a DMSO vehicle control. Erki or Meki was applied for 24 hr, media was then changed to include new inhibitor and 10 μM EdU for another 24 hr prior to collection for flow cytometry analysis.

Cloning of mitogen constructs

For generation of mitogen constructs caYap8SA, caCtnnb1, Ccnd2 OE, carErbb2, and cahErbb2, plasmid containing the gene sequence was used as PCR template for amplification of inserts prior to cloning (see Key Resources Table for plasmids). PCR primers were designed to add complementary restriction site overhangs to the gene inserts which were also present in the MHCK7-MCS-P2A-mCherry backbone used for cloning the constructs. Standard restriction cloning was used to insert the gene fragments. Sanger sequencing was performed to ensure maintenance of reading frame and correct sequence. See Source data 4 for maps of generated plasmids.

Preparation of lentivirus vectors

LVs were prepared as previously described (Rao et al., 2018). Briefly, Hek293T cells were cultured in high glucose DMEM containing 10% FBS and 1% Penicillin/Streptomycin. Plasmids (Construct plasmid, Pax2, and VSVG) were purified using midiprep before transfection into Hek293T cells at 65–75% confluence using Jetprime transfection reagent. Medium was changed 16 hr following transfection, and medium containing virus was harvested 3–4 days following initial transfection. Virus was purified by precipitation using 3 volumes medium to 1 volume LentiX-Concentrator at 4°C overnight, then pelleted by centrifugation at 1500×g for 45 min at 4°C. Precipitated virus was aliquoted and stored at –80°C before use.

For experiments investigating the effects of the LVs on hiPSC-CM monolayers, cells were transduced with the LVs 17–20 days following the initiation of differentiation and were maintained for 1 week to allow the LVs to reach maximal expression before terminal analysis. For NRVM monolayer experiments, viral suspension was added at the time of cell plating. For NRVM cardiobundle experiments, LVs were added to the hydrogel-cell mixture at the time of cardiobundle fabrication to yield transduction efficiency between 45% and 80%.

Flow cytometry

NRVM or hiPSC-CM monolayers were rinsed with phosphate-buffered saline (PBS) then dissociated using 0.05% Trypsin-EDTA at 37°C for 3 min, upon which monolayers were triturated several times to yield a single-cell suspension. Trypsin was quenched with DMEM/F12 containing 20% FBS and 20 µg/ml DNase I. The cell suspension was centrifuged at 300×g for 5 min, then resuspended in % paraformaldehyde (PFA) diluted in PBS. Cells were incubated in PFA for 10 min at room temperature (RT), centrifuged again, then resuspended in PBS containing 5% FBS for storage at 4°C.

Cells were stained for flow cytometry after centrifugation at 300×g for 5 min to remove storage medium. If EdU staining was performed, cells were incubated with the EdU flow cytometry staining cocktail as per the manufacturer’s protocol (Thermo Fisher Scientific) and incubated in the dark for 30 min, then washed 2× by addition of PBS followed by centrifugation. Antibody staining was performed after EdU staining. For antibody staining, cells were resuspended in FACS buffer (PBS with 0.5% BSA, 0.1% Triton-X 100, and 0.02% Azide). Primary antibodies including an isotype control were diluted in FACS buffer and incubated for 1 hr on ice. Cells were washed 2× with FACS buffer before addition of secondary antibodies and Hoechst diluted in FACS buffer. Secondary antibodies were incubated for 30 min at RT. Samples were run on a BD Fortessa X-20.

Immunostaining and imaging

Cell monolayers were fixed with 4% v/v PFA at RT for 15 min, then blocked in antibody buffer (5 w/v donkey serum, 0.1% v/v Triton X-100, in PBS) for 2 hr at RT and incubated with primary antibodies for 2 hr in antibody buffer. Primary antibody sources and dilutions are indicated in the Key Resources Table. The monolayers were washed with PBS before incubation with Alexa Fluor-conjugated secondary antibodies at 1:1000 and Hoechst at 1:200 in antibody buffer for 1 hr. Monolayer samples were mounted using Fluoromount-G Mounting Medium and imaged using an Andor Dragonfly spinning disk confocal microscope.

Engineered cardiobundles were fixed with 2% v/v PFA on a rocking platform at 4°C overnight. For cross-sectional analysis, the fixed tissues were suspended in OCT and flash-frozen in liquid nitrogen until solidified. The frozen tissue blocks were sectioned using a cryostat (Leica) into 10 µm sections. Cardiobundle cross-sections were blocked in antibody buffer for two hours at RT. Whole bundles for longitudinal images were blocked overnight at 4°C. All samples were incubated with primary antibodies at 4°C overnight in antibody buffer. Primary antibodies were used at the indicated dilutions in the Key Resources Table. Samples were incubated with Alexa Fluor-conjugated secondary antibodies at 1:1000 and Hoechst 1:200 in antibody buffer for 2.5 hr at RT for cross-sections and overnight at 4°C for whole bundles. Cross-sections and un-sectioned whole bundles were mounted with hard-set mounting medium (Antifade Glass) and imaged using an Andor Dragonfly spinning disk confocal microscope.

qPCR

RNA was extracted using RNeasy Plus Mini Kit according to the manufacturer’s instructions (Qiagen). Total RNA was converted to cDNA using iScript cDNA Synthesis Kit (Bio-Rad). Standard qPCR reactions with 5 ng cDNA per reaction were performed with iTaq Universal SYBR Green Supermix (Bio-Rad) in the CFX Connect Real-Time PCR Detection System. All primers used are listed in qPCR Primer Table in Key Resources Table.

Force measurements

After 14 days of culture, cardiobundle force generation was measured using custom-made force measurement setup consisting of an optical force transducer and linear actuator as previously described (Jackman et al., 2016). In 37°C Tyrode’s solution, the cardiobundle was pinned to chamber at one end and a PDMS float connected to a linear actuator controlled by Labview software at the other end. Using platinum electrodes, a 90 V biphasic electrical pulse was applied for 5 ms at a 2 Hz rate to induce contractions. The force measurements were performed at the ends of 4% stretch steps lasting 45 s (0% stretch being the culture length of 7 mm), until 16% stretch was reached. Maximum twitch amplitude (occurring anywhere between 4% and 12% stretch), passive force-length curves, and parameters of twitch kinetics were derived as previously described using custom Matlab software (Madden et al., 2015). For contractile force measurements under mechanically unloaded conditions, tissues were relaxed between 0% and –8% stretch to length where passive force became 0, upon which electrically induced contractions were recorded at 2 Hz rate.

Western blot

To isolate total protein from hiPSC-CM samples, cells were rinsed twice with ice-cold PBS before lysis with RIPA buffer containing protease inhibitor cocktail (Sigma-Aldrich P8340) and phosphatase inhibitor cocktail 3 (Sigma-Aldrich P0044). Cells were incubated on ice for 10 min, then lysates were collected and spun down at 10,000×g to pellet debris. Supernatants were measured using BCA assay to determine total protein concentration. About 30 µg of samples were run on 4–12% gradient gels with Tris-Glycine-SDS running buffer at 100 V for 1–1.5 hr depending on the size of proteins being separated. Proteins were transferred to 0.45 µm PVDF membranes for Western blot at 4°C at 60 V for 2 hr. Membranes were blocked overnight in 3% BSA in Tris-buffered saline (TBS). Membranes were cut such that multiple size proteins could be blotted from the same membranes. Primary antibodies were diluted in 3% BSA and incubated with membranes overnight at 4°C. Membranes were washed 3× with TBS containing 0.1% Tween-20 (TBS-T) before incubation with HRP-conjugated secondary antibodies. Membranes were washed 3× with TBS-T before incubation in SuperSignal West Pico PLUS Chemiluminescent Substrate for 5 min. Membranes were imaged with a Biorad ChemiDoc using signal accumulation mode for up to 2 min. If the protein of interest was similar in size to the housekeeping gene (GAPDH), membranes were stripped following exposure for 10 min using Restore PLUS Western Blot Stripping Buffer. Membranes were then reblocked and re-probed as indicated above. Antibodies and their dilutions can be found in the Materials and methods section.

Quantification and statistical analysis

Statistical analysis was performed with GraphPad Prism software. Statistical details can be found in Supplementary file 1. Outliers were identified and removed using GraphPad Prism 8.3.0 ROUT method (Q=1%). Normality testing was done using the Shapiro-Wilk test and testing for equal variances was done using the Brown-Forsythe test. If data was not normally distributed, we performed logarithmic transformations and re-tested for normality and equal variances prior to performing the appropriate statistical test. All experiments were carried out in multiple cell batches. To analyze experiments in which not all mitogen groups were studied simultaneously, we first expressed results relative to Ctrl LV group within each experiment and then compared normalized results among different groups by applying logarithmic transformation followed by the appropriate statistical test.

Image analysis

Image analysis was performed using custom CellProfiler (Carpenter et al., 2006) and FIJI (Schindelin et al., 2012) macros. Briefly, CellProfiler was used to determine nuclear number as well as vimentin+ and EdU+ cells. To quantify nuclear number and EdU+ nuclei, the identify primary objects function was used with global minimum cross entropy thresholding. To quantify vimentin+ cells, vimentin signal was smoothed using Gaussian filter, thresholded using the minimum cross-entropy function, holes were removed using the remove holes function, and the watershed function was applied for segmentation. Colocalization analysis using the related objects function between vimentin signal and nuclei as well as EdU signal and nuclei was performed to exclude proliferative fibroblasts from cardiomyocyte EdU quantification. A custom FIJI macro using auto-thresholding methods was used to determine cardiobundle F-actin+ area and total CSA.

Acknowledgements

The authors thank A Helfer for numerous discussions regarding the experiments performed in this manuscript, and L Baugh for providing feedback on the initial draft of the manuscript. This study was supported by the National Institutes of Health (NIH) grants U01HL134764, R01HL132389, 5T32HD040372, an 1F31HL156453, the Foundation Leducq grant 15CVD03, and a grant from Duke Translating Duke Health Initiative. The content of the manuscript is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Funding Statement

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Contributor Information

Nenad Bursac, Email: nenad.bursac@duke.edu.

Noriaki Emoto, Kobe Pharmaceutical University, Japan.

Matthias Barton, University of Zurich, Switzerland.

Funding Information

This paper was supported by the following grants:

  • National Institutes of Health Research Project Cooperative Agreement to Nenad Bursac.

  • National Institutes of Health Research Project Grant to Nenad Bursac.

  • National Institutes of Health Training Grant to Nicholas Strash, Sophia DeLuca.

  • Foundation Leducq Transatlantic Networks of Excellence Program to Nenad Bursac.

  • Duke University Translating Duke Health: Cardiovascular Health Initiative to Nenad Bursac.

  • National Institutes of Health U01HL134764 to Nenad Bursac.

  • National Institutes of Health R01HL132389 to Nenad Bursac.

  • National Institutes of Health 5T32HD040372 to Nicholas Strash, Sophia DeLuca.

  • Foundation Leducq 15CVD03 to Nenad Bursac.

  • National Institutes of Health 1F31HL156453 to Nicholas Strash.

Additional information

Competing interests

No competing interests declared.

Author contributions

Conceptualization, Data curation, Investigation, Methodology, Supervision, Validation, Visualization, Writing - original draft, Writing - review and editing.

Data curation, Investigation, Validation, Writing - original draft, Writing - review and editing.

Investigation.

Conceptualization, Methodology.

Conceptualization, Methodology.

Conceptualization, Funding acquisition, Methodology, Project administration, Supervision, Visualization, Writing - original draft, Writing - review and editing.

Ethics

This study was performed in accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to approved institutional animal care and use committee (IACUC) protocol (#A100-18-04) at Duke University.

Additional files

Supplementary file 1. Statistical information for all figures.
elife-65512-supp1.docx (23.2KB, docx)
Transparent reporting form
Source data 1. Source data used to generate figures.
elife-65512-supp2.xlsx (91.4KB, xlsx)
Source data 2. Unedited, labeled western blots for all figures.
elife-65512-supp3.docx (9.5MB, docx)
Source data 3. Unedited, uncropped western blots for all figures.
elife-65512-supp4.zip (3.1MB, zip)
Source data 4. Plasmid maps for constructs generated in this study.
elife-65512-supp5.zip (172.1KB, zip)

Data availability

All data generated or analyzed during this study are included in the manuscript and supplemental source data file for all figures.

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Decision letter

Editor: Noriaki Emoto1
Reviewed by: Gilles De Keulenaer

Our editorial process produces two outputs: (i) public reviews designed to be posted alongside the preprint for the benefit of readers; (ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.

Acceptance summary:

Using in vitro 2-D and engineered cardiac tissue 3-D models the authors analyzed several mitogenic signaling routes in rodent and human cardiomyocytes. Specifically, the authors identified a constitutively active mutant form of human Erbb2 as the most potent mitogen, and that its expression determines cardiomyocyte sarcomere loss, cell proliferation, as well as cardiac tissue structure and function in an ERK-dependent manner. The findings presented may facilitate development of regenerative heart repair strategies following myocardial infarction and will be of interest to scientists and clinician-scientists working in the field of myocardial regeneration.

Decision letter after peer review:

Thank you for submitting your article "Human Erbb2-induced Erk Activity Robustly Stimulates Cycling and Functional Remodeling of Rat and Human Cardiomyocytes" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by a Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Gilles De Keulenaer (Reviewer #3).

Essential revisions

1) Use of post-mitotic human CMs, such as metabolically "matured" CMs or EHTs from hiPSC-CMs would add value to the work. These can be obtained using metabolic stimuli as shown by Mills et al. 2017 (PNAS, https://doi.org/10.1073/pnas.1707316114).

2) Although cell cycle activity was clearly induced, no proof of increased cytokinesis has been presented. Is the increase in size of cardiac bundles due to increased number of CMs or increased size of CMs? Both can lead to the development of a necrotic centre as seen in the cahErbb2 overexpressing cardio bundle. The ERK pathway is key mediator of most hypertrophic stimuli and its activation induces CM hypertrophy (see for example the review by Bueno and Molkentin 2002, Circ Res, https://doi.org/10.1161/01.RES.0000038488.38975.1A). Also the Erbb2 ligand Neuregulin-1 has been shown to induce CM hypertrophy (Zurek et al. 2020, Circulation, https://doi.org/10.1161/CIRCULATIONAHA.119.044313).

Analysis of hypertrophy on either phenotypic or gene expression level in cardiac bundles is needed to exclude hypertrophy as a mechanism behind the increased CSA. For example cross-sectional area of individual cardiomyocytes by using a cell membrane stain combined with a CM marker – or gene expression of hypertrophic markers.

3) All figures: STDEV should be used instead of SEM. Moreover, violin plots or dot plots should be considered to better visualize the distribution of the data.

4) Some concerns about statistics, which require clarification:

i) The N numbers are huge and according to the Table 1 it is unclear if they all indeed represent independent samples. Were several samples from the same differentiations or cell isolations used? One field in a monolayer (Table 1, definition of n in Figures 1J, 1P, 4C, 4E, 4G) should not be considered to represent n=1, if several images were analysed from the same sample and/or if several technical replicates (samples prepared from the same cell isolation or differentiation and treated similarly) were analysed. Similarly, RNA or 10^4 cells from one monolayer do not correspond to n=1, if several technical replicates were used. Only samples from separate differentiations or cell isolations should be considered as representatives of n and the results from technical replicates should be averaged to form the n=1 data.

ii) Were the data analysed for equal variances before selecting the test (parametric vs. non-parametric)? If not, this should be done and an appropriate test chosen.

iii) Why did the authors carry out multiple t tests instead of using ANOVA, which is more suitable for multiple comparisons? For example, randomized block ANOVA is a very useful test for example for analysing data for which baseline values may vary between cell preparations (e.g. the percentage of Edu+ cells). In particular, the statistics for data in Figure 5 – Supplemental figure 1, panel B should be corrected. Why have the authors not included the control sample in the statistical analysis? Analysis of the percentage of Edu+ cells (not normalised data) using randomized block ANOVA solves the issue of experiment/cell-preparation-dependent variability in basal levels and the zero variance in normalised data. The data can be presented as is (normalised to control), but statistics should be corrected.

5) The authors have to be complimented for the high technical quality of their studies. This reviewer does not ask for new experiments, but suggests to underscore the limitations of this study, especially with regards to the observed effects of Erbb2 overexpression.

i) First, authors indicate that a necrotic core develops in the 3D model (because of extensive proliferation and development of hypoxia in the core); the extent to which the necrotic core contributes to an increased stiffness is undetermined, and should be addressed. Also, authors should discuss whether development of a necrotic core is related to the avascular structure of the 3D model?

ii) Second, the lentiviral overexpression of ERBB2 is not transient, because it cannot be turned off. Ideally, an on-off system is used so that after the proliferation phase, cardiomyocytes are allowed to redifferentiate and restructure their sarcomeres. No one is going to advocate continuous overexpression of ERBB2 in any tissue. An on-off system would allow the cardiomyocytes to redifferentiate resulting in a level playing field for all vectors. This issue should be better discussed.

iii) Third, it is not surprising that cardio bundles with the most actively proliferating cardiomyocytes and the most disorganized sarcomeres are less contractile. Are these unloaded cardiomyocytes operating at slack length which would, beside the proliferating phenotype, be an explanation for their hypo-contractility due to increased restoring forces? This question is important, since then hypocontractility may be, at least to some extent, an in vitro artefact.

6) The authors have provided some functional measurements of the cardiomyocyte bundles, however, additional parameters of cardiomyocyte function warrants investigation to properly establish that the induced proliferation translates into improved function.

eLife. 2021 Oct 19;10:e65512. doi: 10.7554/eLife.65512.sa2

Author response

Essential revisions

1) Use of post-mitotic human CMs, such as metabolically "matured" CMs or EHTs from hiPSC-CMs would add value to the work. These can be obtained using metabolic stimuli as shown by Mills et al. 2017 (PNAS, https://doi.org/10.1073/pnas.1707316114).

To address this comment, we examined whether lentiviral cahErbb2 expression could induce pro-proliferative effects in hiPSC-CMs cultured in maturation medium by Mills et al. 2017. As shown in Figure 1 —figure supplement 3, we found that maturation media reduced the baseline EdU incorporation rate in CMs by half compared to our standard media as well as control media used by Mills et al. Transduction of cahErbb2 in CMs cultured in maturation media significantly increased EdU incorporation and H3P expression compared to transduction of mCherry (control). These results confirmed that mitogenic effects of cahErbb2 are also robust in metabolically matured hiPSC-CMs. In the main text, revisions made in response to reviewers’ comments are highlighted in red. Additional stylistic edits throughout the text were made to improve readability of the manuscript.

2) Although cell cycle activity was clearly induced, no proof of increased cytokinesis has been presented. Is the increase in size of cardiac bundles due to increased number of CMs or increased size of CMs? Both can lead to the development of a necrotic centre as seen in the cahErbb2 overexpressing cardio bundle. The ERK pathway is key mediator of most hypertrophic stimuli and its activation induces CM hypertrophy (see for example the review by Bueno and Molkentin 2002, Circ Res, https://doi.org/10.1161/01.RES.0000038488.38975.1A). Also the Erbb2 ligand Neuregulin-1 has been shown to induce CM hypertrophy (Zurek et al. 2020, Circulation, https://doi.org/10.1161/CIRCULATIONAHA.119.044313).

Analysis of hypertrophy on either phenotypic or gene expression level in cardiac bundles is needed to exclude hypertrophy as a mechanism behind the increased CSA. For example cross-sectional area of individual cardiomyocytes by using a cell membrane stain combined with a CM marker – or gene expression of hypertrophic markers.

We thank reviewers for this insightful comment. While we did not definitively show CM cytokinesis, the polyploid fraction within the hiPSC-CM population was not increased with application of most mitogens (Figure 1D,E), suggesting the cells which incorporated EdU ended up dividing (and re-attaining 2N DNA content) instead of becoming polyploid (having 4N or greater DNA content). In NRVMs the situation is less clear, but we measured the F-actin+/vimentin- area divided by number of nuclei within this area in cardio bundle cross-sections as a proxy for CM size that we have used in previous publications (e.g., Jackman et al., 2016, Biomaterials; Jackman et al. 2018, Acta Biomaterialia). This analysis revealed no change in CM size with mitogen expression (new Figure 3F), suggesting that the increase in cardio bundle size for cahErbb2 group was likely caused by an increase in CM numbers rather than the CM size. We also included measurements of relative cell size based on forward scatter data collected in our flow cytometry experiments in hiPSC-CMs and NRVMs (new Figure 1 —figure supplement 1D-E) which suggested that cahErbb2 does not affect cell size in the monolayer setting.

3) All figures: STDEV should be used instead of SEM. Moreover, violin plots or dot plots should be considered to better visualize the distribution of the data.

We converted any remaining bar/line plots to display STDEV rather than SEM, and most bar graphs were converted to box-and-whisker plots to visualize distribution of the data points.

4) Some concerns about statistics, which require clarification:

i) The N numbers are huge and according to the Table 1 it is unclear if they all indeed represent independent samples. Were several samples from the same differentiations or cell isolations used? One field in a monolayer (Table 1, definition of n in Figures 1J, 1P, 4C, 4E, 4G) should not be considered to represent n=1, if several images were analysed from the same sample and/or if several technical replicates (samples prepared from the same cell isolation or differentiation and treated similarly) were analysed. Similarly, RNA or 10^4 cells from one monolayer do not correspond to n=1, if several technical replicates were used. Only samples from separate differentiations or cell isolations should be considered as representatives of n and the results from technical replicates should be averaged to form the n=1 data.

We very much appreciate this comment. We have corrected our mistakes regarding using n=1 to represent images from the same sample and instead have averaged images to generate n=1 per biological replicate; the corrected n values are updated in the supplemental statistics table.

We also wanted to clarify that for the rest of our studies in both monolayer and cardio bundle experiments, we did not use technical replicates as individual n’s. Experiments were performed in multiple cell batches/differentiations to ensure reproducibility. Within a cell batch/differentiation, we used n=3 monolayer culture wells or tissues that were independently treated with LVs or small molecules and independently assessed thereafter, not n=1 well or tissue that was treated, collected, and assessed multiple times to generate n=3.

ii) Were the data analysed for equal variances before selecting the test (parametric vs. non-parametric)? If not, this should be done and an appropriate test chosen.

We have corrected our analyses to test for equal variances before selecting the style of ANOVA and, where appropriate, we have used Welch’s ANOVA or Welch’s t test for statistical analysis to account for unequal variances. This information is updated in our new statistics table.

iii) Why did the authors carry out multiple t tests instead of using ANOVA, which is more suitable for multiple comparisons? For example, randomized block ANOVA is a very useful test for example for analysing data for which baseline values may vary between cell preparations (e.g. the percentage of Edu+ cells). In particular, the statistics for data in Figure 5 – Supplemental figure 1, panel B should be corrected. Why have the authors not included the control sample in the statistical analysis? Analysis of the percentage of Edu+ cells (not normalised data) using randomized block ANOVA solves the issue of experiment/cell-preparation-dependent variability in basal levels and the zero variance in normalised data. The data can be presented as is (normalised to control), but statistics should be corrected.

We appreciate this comment and have now applied ANOVA instead of multiple t-tests for our qPCR and western blot data analyses. We omitted to include that our multiple t-tests had included p value correction for multiple comparison, so revising the statistical tests did not affect our conclusions. The corrected statistical test information can be now found in our updated statistics table; we ran ANOVAs to ensure proper correction for multiple comparisons as suggested. We also corrected our figure to include the control sample in the graph for Figure 5 – supplemental figure 1 as suggested.

Through our analysis of the normalized data, we found they achieved a normal distribution following logarithmic transformation and therefore we determined that analysis of the normalized data was appropriate for our statistical analysis. We then applied Brown-Forsythe tests and if variance was found to be significantly different between groups, we used Welch’s ANOVA with Dunnett T3 correction for multiple comparisons rather than the standard ANOVA method. This information is included in our updated statistics table and statistical analysis section in the methods.

5) The authors have to be complimented for the high technical quality of their studies. This reviewer does not ask for new experiments, but suggests to underscore the limitations of this study, especially with regards to the observed effects of Erbb2 overexpression.

i) First, authors indicate that a necrotic core develops in the 3D model (because of extensive proliferation and development of hypoxia in the core); the extent to which the necrotic core contributes to an increased stiffness is undetermined, and should be addressed.

To address this comment, we generated cardio bundles using increased hydrogel volume and cell number, which resulted in a larger tissue size and formation of acellular core (new Figure 3 —figure supplement 3A-F) like those observed in cahErbb2-expressing cardio bundles. However, this increase in tissue size and core formation did not significantly alter passive force of the cardio bundles, in contrast to cahErbb2 expression that yielded 8-fold higher passive forces (Figure 3H). This suggested to us that cahErbb2-expressing cardio bundles have increased stiffness not due to the presence of acellular core, but due to an increase in ECM stiffness (e.g., accumulated collagen I), cell stiffness (e.g., more abundant intermediate filaments), or both. We thus performed additional quantitative immunostaining analyses in cahErbb2-expressing cardio bundles and found that collagen I abundance was not changed (new Figure 3 —figure supplement 3G), while abundances of intermediate filament proteins nestin and vimentin were significantly increased (new Figure 3 —figure supplement 3I-K). Collectively, these results suggested that increased cell stiffness may be the main contributor to increased tissue stiffness induced by cahErbb2 expression.

Also, authors should discuss whether development of a necrotic core is related to the avascular structure of the 3D model?

Owing to the lack of functional vasculature, cell survival in cardio bundles depends on the adequate diffusion of oxygen and nutrients from surrounding culture media into the center of the tissue. Thus, the mitogen-induced increase in cardio bundle size, along with a potentially higher metabolism of proliferating CMs, likely caused reduced levels of oxygen/nutrients in the cardio bundle center leading to the formation of the necrotic core. In the revised manuscript, we now discuss roles of the avascular nature of cardio bundles in development of necrotic core.

ii) Second, the lentiviral overexpression of ERBB2 is not transient, because it cannot be turned off. Ideally, an on-off system is used so that after the proliferation phase, cardiomyocytes are allowed to redifferentiate and restructure their sarcomeres. No one is going to advocate continuous overexpression of ERBB2 in any tissue. An on-off system would allow the cardiomyocytes to redifferentiate resulting in a level playing field for all vectors. This issue should be better discussed.

We agree with reviewers that constitutive expression of caErbb2 or any other mitogens would not be a safe approach to cardiac therapy. In our studies, we constitutively expressed mitogens to facilitate direct comparison of how they affect CM structure and function. Some potential effects of the cahErbb2 turn-off after 7-day expression could be inferred from our Meki and Erki experiments. Per reviewers’ suggestion, in the revised manuscript, we additionally discuss effects of continuous vs. transient mitogen expression in CMs.

iii) Third, it is not surprising that cardio bundles with the most actively proliferating cardiomyocytes and the most disorganized sarcomeres are less contractile. Are these unloaded cardiomyocytes operating at slack length which would, beside the proliferating phenotype, be an explanation for their hypo-contractility due to increased restoring forces? This question is important, since then hypocontractility may be, at least to some extent, an in vitro artefact.

We thank the reviewer for this insightful comment. We measure active (contractile) and passive forces in cardio bundles at multiple tissue lengths, i.e., starting from the culture length of 7mm, then increasing the length in 4% steps and measuring active and passive force at each step after the tissue equilibrates. This allows us to both find the maximum active force that tissue generates and construct passive force-length curves. Generally, with this protocol, our control cardio bundles produced maximum active forces at 8-12% stretch, while cahErbb2expressing cardio bundles produced maximum active force at ~4% stretch. These maximum active forces were presented and compared among groups. To address the reviewers’ comment, we performed additional experiments shown in new Figure 3 – supplemental figure 2 (panels D, E), where we decreased tissue length (negative %stretch) to a point when passive tension became 0 (~slack length). At these equally unloaded conditions, we compared generated active forces and confirmed that cahErbb2-expressing tissues still produced significantly lower forces compared to control tissues.

6) The authors have provided some functional measurements of the cardiomyocyte bundles, however, additional parameters of cardiomyocyte function warrants investigation to properly establish that the induced proliferation translates into improved function.

We note that sustained cahErbb2 expression in cardio bundles induced deterioration rather than improvement of contractile function. To address reviewers’ request for measurement of additional functional parameters, we included analyses of the twitch kinetics in our tissues (new Figure 3 —figure supplement 2A-C and Figure 5 —figure supplement 2). These measurements serve as additional readouts of CM function and together indicate that the increased Erk activity because of cahErbb2 activation slows kinetics of force generation in cardio bundles. As noted in our answer to Reviewers’ comment 5 (ii), transient rather than continuous upregulation of mitogen expression would offer a possibility to induce short-lasting proliferation of CMs, followed by their redifferentiation and improvement of cardiac function, as shown previously by D’Uva et al., (Nat Cell Biol., 2015).

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    Supplementary file 1. Statistical information for all figures.
    elife-65512-supp1.docx (23.2KB, docx)
    Transparent reporting form
    elife-65512-transrepform1.pdf (236.1KB, pdf)
    Source data 1. Source data used to generate figures.
    elife-65512-supp2.xlsx (91.4KB, xlsx)
    Source data 2. Unedited, labeled western blots for all figures.
    elife-65512-supp3.docx (9.5MB, docx)
    Source data 3. Unedited, uncropped western blots for all figures.
    elife-65512-supp4.zip (3.1MB, zip)
    Source data 4. Plasmid maps for constructs generated in this study.
    elife-65512-supp5.zip (172.1KB, zip)

    Data Availability Statement

    All data generated or analyzed during this study are included in the manuscript and supplemental source data file for all figures.

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