Activation of IRF3 in cardiomyocytes impairs mitochondrial oxidative function through PGC-1α inhibition and drives heart failure

Domain: chemistry
Published: 2026-02-27
Editorial outcome: major_revision

Abstract
Heightened sterile inflammation and mitochondrial metabolic dysfunction drive the pathophysiology of heart failure in ischemic cardiomyopathy. Yet, the transcriptional regulators within cardiomyocytes driving crosstalk between inflammation and energy metabolism remain ill-defined. Here we identify elevated Ser396/Ser398 phosphorylation of the type I interferon (IFN) response regulating transcription factor IRF3 in the myocardium of patients and male mice with ischemic cardiomyopathy. Cardiomyocyte-specific IRF3 deficiency attenuates ischemia induced contractile dysfunction. Conversely, IRF3 activation in cardiomyocytes through a phosphomimetic IRF3 mutant represses Ppargc1α expression leading to dysfunctional mitochondrial oxidative phosphorylation, altered metabolic flux in the pentose phosphate pathway/TCA cycle, impaired NAD metabolism and an excessive type I IFN activation, collectively detrimental for cardiac function. Restoring cardiomyocyte-specific Ppargc1α expression in IRF3-overexpressor male mice attenuates contractile dysfunction by augmenting a metabolic shift towards fatty acid oxidation and decreasing inflammatory fibrotic responses. These findings identify IRF3 activation in cardiomyocytes as a transcriptional nexus between cardiac inflammation and metabolic fuel switch contributing to heart failure progression.

Introduction
Elevated inflammation in cardiac disease is often accompanied by maladaptive cellular metabolism with a concomitant risk for morbidity and mortality. Averting heart failure (HF) in patients surviving acute and chronic ischemic cardiomyopathy remains a challenge despite recent therapeutic advances1. Myocardial infarction (MI) is associated with a heightened sterile inflammatory state and impaired mitochondrial oxidative phosphorylation machinery in the affected myocardium2,3. At the onset of myocardial ischemia, cardiomyocytes are deprived of oxygen and nutrient supply with adverse impact on mitochondrial function4. To combat cardiac injury, the activated innate immune response provides a short term adaptive response5. On the other hand, an exuberant state of inflammation in cardiac tissue injury is created by a sustained or excessive innate inflammatory response along with altered energy metabolism leading to a deleterious process and resulting in HF6. Traditionally, transcriptional activation of myeloid cells has been studied as a major driver of innate immune signaling; however, results from targeting the immune response in these cells as a strategy to revert cardiac dysfunction are ambivalent. On the other hand, the potential of cardiomyocyte to regulate inflammation has only recently been recognized7–9. Yet, our understanding of transcription factors that regulate innate signaling within cardiomyocytes along with the potential to alter mitochondrial oxidative capacity and cardiac metabolic communication remains elusive.

Over the past decades, nuclear factor-κB (NFκB) has been identified as a major transcription factor that regulates ischemic cardiomyopathy and possesses diverse and dichotomous actions in the heart10,11. The role of NFκB has been highly debated and described as both adaptive and maladaptive in cardiac remodeling. During acute hypoxia and reperfusion injury, cardiac-specific expression of IκBα (NFκB inhibitor) increases infarct size with increased apoptosis, indicating a cardioprotective role of NFκB12. To the contrary, prolonged activation of NFκB in ischemia is detrimental and promotes HF by executing elevated TNFα, IL-1β and IL6 mediated ER stress and cell death13. These studies showed that differential effects of cardioprotective vs cardiotoxic roles of NFκB are dependent on the timing and cellular context of NFκB activation. Furthermore, the outcome of randomized controlled trials targeting chronic inflammation in HF patients yielded mixed results14,15. These seemingly conflicting data reflect our limited understanding of the inherent complexity of the transcriptional landscape of innate immunity to modulate inflammation upon cardiac injury.

It is evident from experimental studies that pro-inflammatory signaling in the heart plays an important role in mitochondrial dysfunction while mitochondrial physiology can also serve as the arbiter of cardiomyocyte fate and alter pro-inflammatory response to ischemic injury16–19. Within the heart, cardiomyocyte metabolism is intensively active with mitochondria primarily involved in energy production. Major alterations in mitochondrial energy metabolism contribute to the severity of cardiac injury. In mammals, the principal energy source changes from glycolysis in the fetal heart to mitochondrial oxidative phosphorylation in the adult postnatal heart20. Peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α) is involved in the postnatal induction of nuclear genes encoding fatty acid (FA) oxidation enzymes. PGC-1α functions as a master regulator of mitochondrial biogenesis, OXPHOS gene expression and energy production by interacting with NRF1/2 and TFAM in the adult heart21,22. Deregulation of cardiac PGC-1α expression has been associated with adverse effect on heart function in mice and humans23–25. However, the transcriptional partners of PGC-1α upon activation of innate immune signaling in cardiomyocytes remain undefined.

Recently, three interferon (IFN) stimulated genes (IFIT2, IFIT3 and IFI44L), have been identified as biomarkers of ischemic cardiomyopathy in humans26. In this regard, interferon-regulatory factors (IRFs), a family of transcription factors (IRF1-IRF9) are major inducers of IFN signaling, regulating several aspects of innate and adaptive immune responses, including, but not limited to, driving pro-inflammatory signaling in response to toll-like receptors (TLR) 3/4 activation by exogenous virus or pathogens or by endogenous signals (e.g. dsRNA, mtDNA, matricellular proteins, S100A8)27,28. Among IRFs, IRF3 is a major pro-inflammatory type I IFN signaling transducer29. IRF3 is activated by phosphorylation, which promotes its dimerization, nuclear translocation, and subsequent association with the co-activator CREB-binding protein (CBP) and binding to canonical IFN response element sequence (IRES) to act as a transcriptional regulator of IFN-α and -β30,31. We and others have earlier shown that activation of IFN signaling by IRF3 is associated with metabolic dysfunction in obese and diabetic humans and diet-induced obese mouse models32,33. Recently, global IRF3-deficient mice have been shown to exhibit reduced levels of chemokines and inflammatory cell infiltration associated with improved survival after MI34. While myeloid cells are well known effectors of immune response, here we unravel the potential of cardiomyocytes in regulating IRF3-driven innate immune signaling and how this alters cardiac immunometabolism towards the pathogenesis of HF. In this study, we identify elevated phospho-IRF3 in the left ventricle of HF patients along with impaired mitochondrial OXPHOS machinery. Our findings in cardiomyocyte-specific IRF3 deficient (CMI3KO) mice show that selective inhibition of IRF3-driven immune response in cardiomyocytes attenuates contractile dysfunction in ischemic cardiomyopathy. We further show that cardiomyocyte-specific activation of IRF3 using IRF3-2D phosphomimetic mutant transgene (CMI3OE) emulates an in vivo model of type I IFN stimulated sterile inflammation that reveals a bidirectional relationship between innate inflammation and mitochondria function. Mechanistically, we identify that pathological activation of IRF3 in cardiomyocytes downregulates PGC-1α, enforces glycolysis imbalance and impairs mitochondrial oxidative phosphorylation. Finally, we show that AAV-mediated moderate expression of Ppargc1α sets a break on the deleterious pro-inflammatory signaling driven by IRF3 activation in the myocardium and elevates FA oxidation attenuating cardiac dysfunction.

Results
Activation of IRF3 and downregulation of mitochondrial oxidative phosphorylation in ischemic cardiomyopathy
An excessive innate immune response and mitochondrial abnormality is a characteristic of failing hearts. Yet, the transcriptional control of these processes remains poorly understood. IRF3 is a major transcription factor regulating type I IFN-signaling mediated innate immune response. Phosphorylation of IRF3 (Ser396 and Ser398) is essential for IRF3 transcriptional activity and activation of IRF3-dependent pro-inflammatory IFN-signaling. To assess the role of IRF3 in ischemic heart failure, we determined the expression and phosphorylation level of IRF3 in cardiomyopathy due to ischemic injury. First, we found increased phosphorylated IRF3 (Ser396, Ser398) levels in the left ventricle tissue of humans with ischemic cardiomyopathy (Fig. 1a, b). IRF3-dependent induced IFN stimulated genes (IFIT2 and IFIT3) were recently identified as biomarkers of ischemic cardiomyopathy26. We found increased IRF3 mRNA levels along with significantly increased IFIT2 and a trend to increased IFIT3 levels in left ventricle tissue of humans with ischemic cardiomyopathy (Fig. 1c, and Fig. S1a). Furthermore, in order to determine the expression of IRF3 in heart failure patients, we obtained and analyzed single-cell RNA-seq dataset of heart failure and control patients from publicly available Gene Expression Omnibus (GEO) accession no GSE109816 and GSE121893. We applied t-distributed stochastic neighbor embedding (t-SNE) to visualize the different cell type populations in 9,248 single cells isolated from both healthy and heart failure ventricle samples as annotated in the original publication35 namely, cardiomyocytes (CMs), endothelial cells (ECs), fibroblasts (FBs), macrophages (MPs), and smooth muscle cells (SMCs) (Fig. 1d). We found IRF3 expression to be upregulated in CMs of heart failure patients compared to the controls (Fig. 1e). In addition, IRF3 expression was also increased in ECs, FBs and SMCs but was reduced in MPs in these patients (Fig. S1b). Second, we performed ligation of the left anterior descending coronary artery (LAD) in mice to generate a model of myocardial infarction associated with damage induced pro-inflammatory signaling. This resulted in robust induction of phosphorylated IRF3 (Ser 388, Ser 390) levels upon occlusion in mice with LAD compared to sham controls (Fig. 1f). Furthermore, immunoblot analysis showed higher levels of phosphorylated IRF3 in the nuclear fraction of cardiomyocytes isolated from mice with myocardial infarction suggesting physiological activation of endogenous IRF3 (Fig. S1c). Consistent with these findings, expression of several Irf3-dependent target genes (e.g., Ifit1, Ifit2, Ifit3, etc.) was upregulated in left ventricle of mice with myocardial infarction (Fig. 1g). Of note, we found a marked increase in IRF3 phosphorylation compared to the effect on mRNA expression in mice with ischemic cardiomyopathy. Cardiomyocytes isolated from lipopolysaccharide (LPS) stimulated adult mouse and neonatal rat cardiomyocytes stimulated in presence of polyinosinic:polycytidylic acid (polyI:C) also showed increased expression of Irf3 and IFN stimulated genes indicating a cell-autonomous key role for type I IFN activation in cardiomyocyte inflammatory signaling (Fig. S1d, S1e). Incongruous to the activated inflammatory state, a maladaptive response with mitochondrial dysfunction often occurs in patients with HF. The primary function of mitochondria in cardiac cells is to generate energy in the form of ATP through oxidative phosphorylation (OXPHOS) machinery17. Impaired OXPHOS can lead to a decline in the bioenergetics capacity of the myocardium. In this regard, the five multimeric protein complexes of the OXPHOS system, namely, NADH:ubiquinone oxidoreductase (NDUFB8), Succinate dehydrogenase (SDHB), Cytochrome c oxidase (CoI), Ubiquinol Cytochrome c oxidoreductase (UQCRC2) and ATP synthase (ATP5A) were found to be reduced in the left ventricle of humans with ischemic cardiomyopathy (Fig. 1h, i). Mitochondrial DNA encodes 13 core genes of the OXPHOS using 22 transfer RNAs and 2 ribosomal RNAs. We found severely impaired expression of marker genes of the OXPHOS system (Cytb, Nd1, Nd2, Nd3, Nd4, Nd4L, Nd5, Nd6, Cox1, Cox2, Cox3, Atp5, Atp6, 12sRNA, 16sRNA) indicating inefficiency in electron transport chain (ETC) in mice with ischemic cardiomyopathy (Fig. 1j). mtDNA is a widely studied damage-associated molecular pattern (DAMP) that is also known to trigger the inflammatory response during myocardial damage by ischemia36–38. We treated primary cardiomyocytes with freshly isolated mtDNA from rat ventricle tissue to determine the impact on IRF3 activation within cardiomyocytes. The purity of mtDNA was validated by Nd1 and 16sRNA expression compared to nuclear DNA encoded Sdhb (Fig. 1k). We found a robust increase in pIRF3 levels along with elevated type I IFN signaling markers in the presence of mtDNA (Fig. 1l, and Fig. S1f). Together, these results indicate that elevated phosphorylation of IRF3 in ischemic cardiomyopathy is associated with detrimental cardiac mitochondrial function.

Cardiomyocyte-specific IRF3 deficiency attenuates ischemic cardiomyopathy
To investigate the cardiomyocyte-specific role of IRF3 deficiency in vivo, we utilized mice with an allele in which Irf3 exon three to six were flanked by loxP sites (Fig. 2a). Irf3 floxed mice were crossed with αMHC-Cre mice (Jax: 011038)39, to create cardiomyocyte-specific IRF3-knockouts, hereafter designated as CMI3KO mice. To compare the effects of CMI3KO mice on cardiac physiology, αMHC-Cre littermate mice were used as controls in all experiments. Cardiomyocytes were isolated from 12 wk old CMI3KO mice using Langendorff technique and IRF3 deficiency was confirmed at mRNA and protein level (Fig. 2b, c; and Fig. S2a, S2b). To study the effect of IRF3 deficiency on cardiac function upon injury, MI was induced by left anterior descending coronary artery ligation in 10 wk old CMI3KO and αMHC-Cre control mice (Fig. 2d). Contractile function as determined by echocardiography measurement of ejection fraction and fractional shortening was severely impaired in αMHC-Cre mice post MI compared to sham control (Fig. 2e–g, and Fig. S2d). In contrast, CMI3KO mice subjected to MI showed partial yet significantly attenuated cardiac dysfunction despite intact IRF3 levels in other cardiac cell types (Fig. 2e–g, and Fig. S2b). Cardiomyocyte-specific IRF3 deficiency had no significant effect on body weight, heart weight/body weight or lung weight/body weight ratio (Fig. 2h, i; and Fig. S2c) following MI. Furthermore, IRF3 deficiency in cardiomyocytes led to reduced fibrosis in CMI3KO mice compared to the αMHC-Cre control mice as quantified with Masson-Trichrome immunostaining (Fig. 2j, k). To further investigate the cell-autonomous effect of IRF3 deficiency in cardiomyocytes, we performed IRF3 knockdown in cardiomyocytes isolated from neonatal rats (Fig. S2e, S2f). IRF3 knockdown did not alter the expression of other IRFs with the exception of IRF7 which is a known transcriptional target of IRF340 (Fig. S2g). IRF3 deficiency in cardiomyocytes treated in the absence or presence of LPS attenuated the cellular inflammatory state by reducing the expression of Irf3 target genes (Ifit3, Rsad2, Ccl2, Isg15 etc.) in a cell-autonomous manner (Fig. S2h). These results show that cardiomyocyte-specific IRF3 deficiency attenuates excessive inflammatory signaling and thereby reduces detrimental effects on cardiac function in response to myocardial injury.

Cardiomyocyte-specific IRF3 activation impairs cardiac function and leads to HF
As we found increased phosphorylated IRF3 in ischemic cardiomyopathy in humans and mice, we hypothesized that aberrant IRF3 activation in cardiomyocytes is sufficient to create local and systemic pro-inflammatory milieu and is detrimental to cardiac function in vivo. To note, in human IRF3, mutations of Ser396 and Ser398 to Asp results in a phosphomimetic constitutively active allele that enables modeling IRF3 activation without a need for external stimuli such as lipopolysaccharide or polyI:C30,32,41. Our previous studies have shown that an analogous double mutant murine IRF3 allele in which Ser388 and Ser390 are mutated to Asp, hereafter designated as IRF3-2D, is constitutively active in vitro32. To study the role of IRF3 activation on cardiac function, we developed a knock-in mouse line, in which IRF3-2D allele was flag-tagged and placed within the Rosa26 locus behind a loxP-stop-loxP cassette, allowing Cre-dependent expression of IRF3-2D (Fig. 3a). Floxed IRF3-2D mice were bred with αMHC-MerCreMer mice (αMHCMCM, JAX: 005657)42 to generate cardiomyocyte-specific IRF3-2D expressor mice, hereafter designated as CMI3OE. To minimize Cre expression-induced cardiotoxicity, we used oral gavage of low dose Tamoxifen (30 mg/kg) for 3 days in CMI3OE (Fig. 3b). Littermate αMHCMCM mice were used for comparison. Oral administration of tamoxifen has been earlier reported to be better tolerated in mice and lower doses have been associated with minimal adverse effects on heart function43. IRF3 activation in cardiomyocytes led to unexpected mortality following 5th day of IRF3-2D expression in CMI3OE mice (Fig. 3c, d). We found ~3 fold upregulation of IRF3 protein levels in CMI3OE mice (Fig. 3e, f) compared to tamoxifen-gavaged αMHCMCM controls which is similar to the amount of phosphorylated IRF3 induction seen in the left ventricle of patients with ischemic cardiomyopathy (Fig. 1b). Irf3 mRNA and interferon target genes Ifnβ, Ifit1, Ifit2, Ifit3, Rsad2, and Ccl2 were significantly upregulated (Fig. 3g). Similarly, circulating cytokines levels of CCL2, IL-6, and TNFα was also significantly increased (Fig. 3h–j). CMI3OE mice did not show a significant change in body weight (Fig. 3k). Echocardiography showed impaired contractile function with reduction in left ventricular ejection fraction and fractional shortening (Fig. 3l-n) in CMI3OE mice compared to αMHCMCM control mice. CMI3OE mice also showed left ventricle dysfunction with increased left ventricle thickness and posterior wall thickness measured during diastole (Fig. 3o-q). The ratio of heart weight but not lung weight to tibial length was increased in CMI3OE mice (Fig. 3r, s).

Furthermore, in an additional study we determined the effect of IRF3 activation on cardiac function using Mck-Cre mouse (JAX: 006475), wherein Cre is expressed in skeletal muscle with a moderate expression in the cardiac tissue44. Floxed IRF3-2D mice were crossed with Mck-Cre mice to generate muscle-specific IRF3-2D transgenic mice, hereafter designated as MI3OE (Fig. S3a). To our surprise, body weight was significantly reduced in MI3OE mice compared to Mck-Cre control mice and the animals displayed early mortality from 4 weeks postnatal (Fig. S3b–S3d). Muscle-specific IRF3 activation resulted in ~2.5 fold and ~5 fold increased expression of Irf3 in cardiac tissue and gastrocnemius muscle, respectively (Fig. S3e–S3g). This led to increased expression of IRF3 target genes in skeletal muscle as well as in the cardiac tissue of MI3OE mice (Fig. S3e, S3f). It is worth noting that plasma glucose and insulin levels were reduced whereas circulating CCL2 levels were robustly increased (Fig. S3h–S3j). Cardiac function determined by echocardiography in 4 wk old MI3OE displayed severely impaired contractility with reduced ejection fraction and fractional shortening along with increased heart weight to body weight ratios (Fig. S3k–S3p). Taken together, these results show that aberrant activation of IRF3 in cardiomyocytes is a robust in vivo model recapitulating the potential of type I IFN signaling mediated sterile inflammation in promoting cardiac contractile dysfunction.

Impaired PGC-1α activity and oxidative phosphorylation upon cardiomyocyte-specific IRF3 activation
We have earlier shown a role for the transcription factor IRF3 in regulating glucose and energy homeostasis in fat and liver tissues32,33,41. Little is known about how inflammatory signaling by activated IRF3 controls the transcriptional network in the heart regulating contractile and metabolic functions. Intrigued by the severe contractile dysfunction observed in CMI3OE mice, we performed bulk RNA-seq analysis to understand the impact of IRF3 activation on the cardiac transcriptome. We identified four major cluster of genes dysregulated in CMI3OE cardiac tissue upon IRF3 activation compared to αMHCMCM controls (Fig. 4a). Interestingly, we found the gene expression of oxidation-reduction processes severely downregulated with increased expression of pro-inflammatory and fibrotic markers (Fig. 4b, and Fig. S4a–S4d). Notably, expression of genes regulating chemokine signaling and extracellular matrix organization (Ccl2, Ccl5, Col12a1, Col1a1, Col3a1, Itgax, Tgfb2 etc.) were increased suggesting metabolic and structural remodeling along with elevated inflammatory state in CMI3OE mice (Fig. 4a, b). Despite significantly elevated expression of fibrotic markers, structural changes indicative of fibrosis were not observed suggesting an early phase of cellular adaptation in CMI3OE mice (Fig. S4e, S4f). Next, we determined the effect on OXPHOS proteins in the heart that generates oxidative energy and empowers the cellular energy signaling. We found that protein levels of NDUFB8, SDHB, CoI, and UQCRC2 were significantly reduced indicating severely impaired electron transport chain via reduced OXPHOS proteins in CMI3OE mice (Fig. 4c, d). Additionally, in the heart, the creatine kinase phosphotransfer circuit functions as an energy shuttle between mitochondria and cytosol45. Creatine kinase regulates cardiac muscle contractility which in turn is coupled to mitochondrial ETC (Fig. 4e). CMI3OE mice displayed increased myocardial cellular injury with increased creatine kinase (CK-MB) levels (Fig. 4f).

A profound decrease in mitochondrial aerobic respiration processes in CMI3OE mice was identified in Gene Ontology pathway analysis (Fig. S4d). The preponderance of genes regulating mitochondrial function in the transcriptomics analysis prompted us to assess the effect on mitochondrial DNA content and mitochondrial biogenesis markers upon IRF3 activation in CMI3OE mice. To assess an effect on mitochondrial DNA content, mitochondrial DNA copy number was quantified by determining the mitochondrial DNA/nuclear DNA ratio. Similar ratio suggests that mitochondrial function and not the quantity is altered in the left ventricle of CMI3OE mice (Fig. 4g). We identified robust downregulation of Ppargc1α at mRNA and protein level in the cardiac tissue of CMI3OE mice (Fig. 4h, and Fig. 5i). PGC-1α is a transcriptional coactivator and master regulator of mitochondrial bioenergetics46. However, the transcriptional partners of PGC-1α modulating cardiac function are not completely known. In this regard, we utilized multiple approaches to understand the interaction between IRF3 and PGC-1α and transcriptional activity in cardiomyocytes. First, we performed co-immunoprecipitation assays in isolated cardiomyocytes and found that IRF3-2D and pIRF3 interacts with PGC-1α (Figs. 4i, j and Fig. S5a). Also, cell fractionation analysis in cardiomyocytes isolated from CMI3OE showed nuclear abundance of IRF3-2D in CMI3OE mice compared to Cre controls (Fig. S5b, S5c). Second, expression of IRF3-2D in isolated cardiomyocytes showed enhanced nuclear abundance (Fig. S5d–S5f) and led to reduced expression of Ppargc1α (Fig. 5a, and Fig. S5g). Concordant with these findings, expression of type I IFN stimulated genes (Ifit3, Isg15, OasII, and Rsad2) was increased whereas mitochondrial marker genes expression was impaired in cardiomyocytes upon activation of IRF3 (Fig. S5h, S5i). Similarly, upregulation of Ppargc1α in cardiomyocytes downregulated Irf3 mRNA levels (Fig. 5b). Contrary to the effect of IRF3 activation, Ppargc1α expression attenuated type I IFN stimulated genes expression and increased the mitochondrial marker genes expression in cardiomyocytes under basal as well as inflamed (LPS) or stressed (hypoxia) conditions (Fig. 5c, d; and Fig. S6a–S6d). Third, our results show that siRNA mediated knockdown of Irf3 in cardiomyocytes increased Ppargc1α mRNA levels (Fig. 5e). Fourth, we utilized reporter based assays to identify the impact of modulating IRF3 levels on PGC-1α transcriptional activity. To examine the effect of IRF3 activation on PGC-1α activity, we utilized a target reporter plasmid containing a PPARα response element (PPRE) derived from the peroxisomal acyl-CoA oxidase gene promoter multimerized upstream of the thymidine kinase minimal promoter [(PPRE)3TKLuc)]. Ppargc1α and Irf3-2D were ectopically overexpressed alone or in combination in neonatal rat cardiomyocytes (NRCMs). While Ppargc1α expression increased PPARα mediated activation of the reporter by 2-fold, expression of Irf3-2D inhibited this transcriptional activity of Ppargc1α in cardiomyocytes (Fig. 5f). On the other hand, siRNA mediated knockdown of IRF3 enhanced PGC-1α activity (Fig. 5g). In line with these findings, PPARα target genes (Cd36, Acox1, Acadm, Acadvl, and Cpt1b) were downregulated in CMI3OE mice (Fig. S6e). Fifth, to get a deeper insight into the IRF3-PGC-1α axis, we analyzed the effect of IRF3 activation on transcriptional targets and post-translational regulators of PGC-1α in CMI3OE. In this regard, mRNA level of Foxo1, Mef2a and Esrra that are known PGC-1α transcriptional targets was reduced in the left ventricle of CMI3OE (Fig. 5h). Because PGC-1α expression can also be regulated by a panoply of post translational modifications such as phosphorylation and O-GlcNAcylation, we determined the effect on pAMPKα, p-p38MAPK and pAKT that are among the key kinases known to regulate PGC-1α activity47. We found reduced p-p38MAPK along with reduced expression of Mapk14 (encoding p38MAPK) (Fig. 5i, k) in CMI3OE mice. There was no effect on pAMPKα levels, whereas both total AKT as well as pAKT was reduced in the myocardium of CMI3OE mice. O-GlcNAc transferase (OGT) is the sole enzyme that catalyzes O-GlcNAcylation by transfer of N-acetylglucosamine from UDP-N-acetylglucosamine to serine/threonine residues of proteins. Interestingly, we found reduced levels of OGT and an overall reduced O-GlcNAcylation in CMI3OE mice (Fig. 5i–k) indicating reduced activity of OGT. While increased OGT levels are detrimental for heart function, reduced OGT levels have also been identified to exacerbate heart failure48,49. Taken together, these results identify an important cardiomyocyte-specific IRF3/PGC-1α axis acting as a transcriptional control of sterile inflammation wherein activated IRF3 reduces mitochondrial oxidative capacity by downregulating Ppargc1α activity.

Metabolic fuel alteration and impaired NAD metabolism upon cardiomyocyte-specific IRF3 activation
Cardiac function and metabolism are inextricably linked. By virtue of metabolic flexibility, the heart has the ability to adapt to an altered physiological environment. We sought to understand the alteration in the cardiac metabolic state upon IRF3 activation in cardiomyocytes. In the first approach, we performed metabolomics study and identified metabolic adaptations in fatty acid and glucose metabolism and impaired/alternate substrate utilization in the left ventricular tissue of CMI3OE mice (Fig. 6a–j, and Fig. S7a, S7b). Carnitine is essential for normal fatty acid oxidation and carnitine deficiency results in enhanced myocardial injury after ischemia50–52. Our results show reduced L-Carnitine, acetyl-Carnitine, and propionyl-Carnitine in the myocardium of CMI3OE mice (Fig. 6a–c). On the other hand, cardiac UDP-Glucose and UDP-Glucosamine levels (Fig. 6d, e) were increased in CMI3OE mice compared to αMHCMCM mice. Similarly, activation of IRF3 led to ~1.5 fold increase in glucose uptake in adult cardiomyocytes isolated from CMI3OE mice (Fig. S7c). Importantly, we found an increase in cardiac 3-hydoxybutyric acid (3OHB) (Fig. 6f) along with increased dimethylglycine levels (Fig. 6g), indicating increased ketogenesis and choline metabolism upon IRF3 activation in CMI3OE mice. Oxidation of 3OHB to acetoacetate by mitochondrial enzyme 3-hydoxybutyrate dehydrogenase 1 (BDH1) is essential for utilization in the oxidative pathway of the TCA cycle53–55. However, reduced expression of Bdh1 in CMI3OE mice suggests a failure in 3OHB oxidation to improve the energy-starved state in the myocardium (Fig. S8a). Isocitrate dehydrogenase 1 (IDH1) and succinate dehydrogenase (SDHA) play a key role in regulating the citrate and fumarate pool in the TCA cycle56. We found differential regulation of the TCA cycle metabolites with increased citric acid and reduced fumaric acid levels in CMI3OE mice (Fig. 6h, i). Similarly, Idh1 and Sdha expression was reduced in the myocardium of CMI3OE mice (Fig. 6o, and Fig. S8b). Notably, fumarate-succinate ratio is a crucial indicator of SDH activity and succinate oxidation in the TCA cycle was found to be reduced in the ventricle of CMI3OE mice (Fig. 6k). Interestingly, our transcriptomics analysis showed a reduced expression of genes involved in the TCA cycle whereas the marker genes for upper glycolysis metabolism were increased (Fig. 6l, m). However, the marker genes for lower glycolytic pathway were downregulated in CMI3OE mice, indicating an imbalanced but not increased glycolysis. Inflammation driven increased ceramide accumulation functions as an immunological signal regulating cell survival along with glucose and lipid utilization57,58. In this regard, we found increased levels of ceramide 18:1/22:1 and ceramide 18:1/24:1 upon IRF3 activation in the myocardium of CMI3OE mice (Fig. 6n; and Fig. S7d, S7e). While plasma triglycerides and cholesterol was not altered, we found reduced free fatty acids in CMI3OE mice (Table S1).

In a second approach, we identified further alterations in the circulating lipid profile in CMI3OE mice by plasma lipidomic analysis using the Lipidyzer platform. Here, we found an increase in circulating sphingolipids such as hexosylceramide (HCER) and lactosylceramide (LCER) levels in the CMI3OE mice (Fig. S7f). Sphingolipids have been shown to regulate cellular structural integrity and act as effectors of cell stress response in myocardial pathology59,60. These results indicate that IRF3 activation in cardiomyocytes generates immunomodulatory impact with dysregulated ceramide/sphingolipid metabolism in CMI3OE mice.

Interestingly, in addition to the effect on fatty acid and glucose oxidation pathways, transcriptomic analysis of RNA-seq datasets revealed impaired NAD metabolism marker genes upon heightened inflammatory state (Fig. 6o; and Fig. S8c). Thus, in a third approach, we applied NAD metabolomics and assessed the effect on cardiac NAD homeostasis. IRF3 activation in cardiomyocytes of CMI3OE mice resulted in a significantly reduced cardiac NAD+ pool, increased NADH level and reduced NAD+/NADH ratio in comparison to αMHCMCM controls (Fig. 6p–r). Overall, these data suggest that IRF3 activation leads to impaired fatty acid and NAD metabolism in CMI3OE mice.

IRF3 activation in cardiomyocytes rewires fuel metabolism
Cardiac dysfunction is accompanied by swift metabolic adaptations creating a complex interplay between cellular glycolysis, TCA cycle, and PPP, wherein the flow of each pathway can be context dependent. To obtain a deeper insight into the effect of IRF3 activation on cardiomyocyte metabolism we performed stable-isotope labeling in cardiomyocytes isolated from CMI3OE and Cre control mice. Isolated cardiomyocytes were treated with 5.5 mM U-13C6-Glucose and incubated for 10 min and 120 min to determine the flux in glycolysis, PPP, and TCA cycle (Fig. 7a). While increased glucose uptake, UDP-N-acetylglucosamine and expression of Hk1 and Gpi1 primarily indicated a transient increase in upper glycolysis pathway, there was a modest reduction in isotopologue distribution in glycolytic pathway, especially M+6 isotopologue of Fructose-1-6-bisphosphate, overall indicating a rather reduced glycolytic flux at 10 min (Fig. 7b-e, Fig. S9a–S9e) in the cardiomyocytes of CMI3OE mice. Strikingly, our results from the isotopologue analysis showed increased flux from glucose to Sedoheptulose-7-phosphate, a product of the non-oxidative PPP (Fig. 7f). Additionally, our data from this analysis also demonstrated a substantially reduced flux in TCA cycle metabolites in CMI3OE cardiomyocytes (Fig. 7g–j, and Fig. S9f–S9h). These metabolic changes were also captured by the transcriptomic analysis that revealed an altered expression of genes regulating upper and lower glycolysis, TCA cycle, and PPP pathway with similar pattern in the left ventricle CMI3OE mice (Fig. 6l, m; and Fig. S9i). Overall, these data along with the results from the lipidomic analysis acclaim the unique flexibility of cardiomyocytes and suggest that IRF3 activation drives cardiac fuel adaptation towards increased PPP, impaired ketone body metabolism along with reduced oxidative phosphorylation and disrupted NAD metabolism in CMI3OE mice. Thus, our studies highlight a key role of IRF3 activation in reshaping myocardial metabolism during progression to heart failure in mice via switching cardiac fuel preferences (Fig. 7k).

Cardiomyocyte-specific moderate expression of PGC-1α attenuates contractile dysfunction upon IRF3 activation
Compromised and damaged mitochondria can provoke inflammatory responses16,61. However, it remains unclear whether improved mitochondrial function can attenuate the deleterious effects of a type I IFN signaling driven inflammatory assault. Because IRF3 activation in cardiomyocytes diminished expression of PGC-1α and mitochondrial electron transport marker genes, we sought to test the potential of PGC-1α in regulating IRF3 driven type I IFN inflammatory response and mitochondrial oxidative dysfunction. Taking advantage of the recent finding that moderate expression of cardiac-specific Ppargc1α in young mice (3 month old) improves cardiac function62, we evaluated the role of restoring cardiac Ppargc1α levels in preserving mitochondrial function, impact on inflammatory signaling and attenuating heart failure in CMI3OE mice. We utilized AAV9-mediated moderate expression of Ppargc1α in cardiomyocytes prior to induction of IRF3 expression (Fig. 8a). We injected AAV-PGC-1α (AAV9-TnT-PGC-1α) to achieve cardiomyocyte-specific expression of murine Ppargc1α, and AAV-EGFP (AAV9-TnT-EGFP) was used as control. CMI3OE mice with moderate expression of Ppargc1α in cardiac tissue were followed by IRF3 activation using low dose tamoxifen oral gavage (Fig. 8a, b; and Fig. S10a). To note, we found that cardiomyocyte-specific expression of PGC-1α in CMI3OE mice improved cardiac systolic function with increased ejection fraction and fractional shortening compared to CMI3OE mice expressing EGFP (Fig. 8c-e). Furthermore, there was no significant effect of PGC-1α expression on heart weight/body weight ratio in CMI3OE or control mice (Fig. 8f, and Fig. S10b). While the end diastole left ventricle posterior wall thickness was unaltered, the end systole left ventricle posterior wall thickness showed a non-significant trend towards increase in CMI3OE mice as well as control mice expressing PGC-1α (Fig. S10c, S10d). These results unravel a previously undescribed vital role of cardiomyocyte-specific PGC-1α expression in attenuating cardiac dysfunction caused by IRF3 activation driven sterile inflammation.

Improved oxidative phosphorylation and metabolic state in CMI3OE mice upon cardiomyocyte-specific PGC-1α expression
We next sought to identify the role of PGC-1α expression in CMI3OE mice and investigated the effects on transcriptional profile of cellular processes and metabolic pathways in the left ventricle using RNA-sequencing datasets. We identified total 11,248 genes significantly differentially regulated, among these, PGC-1α expressing CMI3OE mice modulated 811 genes compared to CMI3OE mice expressing EGFP (Fig. S11a, S11b). Heat map analysis showed four major clusters of biological processes differentially altered (Fig. 9a). Importantly, among these, two clusters were related to downregulated pathways, namely, immune response and response to external stimuli. CMI3OE mice expressing PGC-1α showed significantly reduced pro-inflammatory and fibrotic marker genes compared to EGFP expressing CMI3OE (Fig. 9b, and Fig. S11c). Among the downregulated inflammatory genes were Irf3 and several type I IFN stimulating genes such as Ifnb1, Ifit2, Rsad2, etc. indicating downregulation of pro-inflammatory signaling upon Ppargc1α expression. The two other clusters identified pathways upregulated corresponding to regulation of heart contraction and ion transmembrane transport. Importantly, PGC-1α expression increased mitochondrial marker gene expression in CMI3OE mice (Fig. 9c; and Fig. S11d). Similarly, mitochondrial OXPHOS protein levels (NDUFB8, SDHB, CoI, UQCRC2, ATP5A) were increased in CMI3OE mice expressing PGC-1α (Fig. 9d, e). We also found augmented expression of NAD metabolism marker genes in CMI3OE mice with PGC-1α expression (Fig. 9f; Fig. S11e). To corroborate our findings, we measured NAD+ and NADH levels upon expression of IRF3-2D and PGC-1α in isolated cardiomyocytes. Our data showed that IRF3-2D and PGC-1α expression regulated NAD+ and NADH levels oppositely, wherein IRF3-2D expression resulted in reduced NAD+ and increased NADH levels (Fig. 9g–i). On the other hand, PGC-1α expression increased NAD+ levels and reduced NADH levels. Interestingly, cardiomyocytes co-expressing PGC-1α and IRF3-2D showed an increased NAD+/NADH ratio. Taken together, these data highlight that upregulating mitochondrial electron transport function via cardiomyocyte-specific PGC-1α expression downregulates IRF3-dependent pro-inflammatory pathways and restores NAD+/NADH homeostasis.

Reactome analysis provided further insight into the metabolic state of the myocardium upon cardiomyocyte-specific PGC-1α expression in CMI3OE mice, where pathways regulating cardiac contractile function were upregulated (Fig. 10a). Additionally, we also found pathways regulating fatty acid and lipid metabolism upregulated in PGC-1α expressing CMI3OE mice. Pathway enrichment analysis identified increased expression of genes regulating fatty acid oxidation (Cpt1b, Cpt2, Acad10, Acad11, etc.), fatty acid metabolism (Scd4, Acot, Gpam, lipin, Dgat2, etc.) and TCA cycle (Idh3a, Idh3b, Mdh1, Sdhb, etc.) in the Reactome (Fig. 10b, c). These findings are consistent with the proposed role of PGC-1α in transcriptional control of genes inducing mitochondrial fatty acid oxidation63,64. Concordantly, flex assays in isolated cardiomyocytes identified increased fatty acid dependency compared to glucose in the cells expressing PGC-1α and IRF3-2D (Fig. 10d, e). Thus, our studies establish CMI3OE mice as an effective model to study cardiomyocyte-specific sterile inflammation via downregulation of PGC-1α and mitochondrial OXPHOS function ultimately leading to cardiac dysfunction (Fig. 10f). Moreover, our data indicate that elevated PGC-1α levels in cardiomyocytes may attenuate IRF3 driven contractile dysfunction by preserving the cardiac fuel fuel utilization from FA metabolism.

Methods
Animal Experiments
Animal experiments were approved by the Animal Welfare Officers at University Medical Center Hamburg-Eppendorf, Behörde für Gesundheit und Verbraucherschutz (BGV) Hamburg and Ministerium für Landwirtschaft, ländliche Räume, Europa und Verbraucherschutz (MLLEV) of the state of Schleswig-Holstein, and were carried out in accordance with institutional ethical guidelines. Mice had ad libitum access to standard chow diet (Altromin, 1329P) and water. Mice were housed under a regular 12h light/12h dark cycle at constant temperature (23°C). Strains purchased include: C57BL/6J (JAX: 000664), αMHCMCM (JAX: 005657), Mck-Cre (JAX: 006475), αMHC-Cre (JAX: 011038).

Generation of IRF3 deficient mice
The IRF3 floxed mice were generated by using a gene targeting vector designed to place LoxP sites flanking exons 3-6 in collaboration with Texas A&M Institute of Genomic Medicine (TIGM). Murine C57BL/6 embryonic stem cells were transfected, and integration of the genomic construct at the predicted site within the Irf3 locus was confirmed by long distance PCR using primers external to the targeted region (3′ homologous arm and 5′ homologous arm). Following ES cell expansion and karyotyping, selected clones were microinjected into C57BL/6 blastocysts and implanted into pseudo-pregnant female mice. Male germ line chimeras carrying an Irf3 floxed allele were backcrossed with wild-type C57BL/6N females. Heterozygous F1 progeny were crossed to Flpe line (B6.Cg-Tg(ACTFLPe)9205Dym/J) to remove the selection cassette and obtain the floxed allele only. Use of mice was in accordance with protocols approved by the TAMU Institutional Animal Care and Use Committee and following the National Institutes of Health guidelines for laboratory animal use. This mouse line is available from the Jackson Laboratory: Irf3 flox (JAX: 036260).

Generation of IRF3 transgenic mice
To generate IRF3-2D mice, the 3XFlag-IRF3-2D transgene was introduced into the ROSA26 locus downstream of a “STOP” cassette consisting of multiple polyadenylation signals flanked by loxP sites. The IRF3-2D coding sequence was amplified using murine 3XFlag-IRF3-2D-pCDH-CMV-MCS-EF1-puro construct32 with the addition of MluI and NsiI restriction sites and ligated into the BirA-RanGap-TRAP vector97. Primers used for cloning are: forward 5’-GACACGCGTACCATGGATTACAAGGATGACGACGATAA-GATGGAAACCCCGAAACCG-3’ and reverse 5’-GACATGCATTCAGATATTTCCAGTGGCCTG-3’. The vector was linearized by KpnI digestion and the purified product was introduced into C57BL/6N ES cells. Correctly targeted ES cell clones were identified by long-range PCR screen98. The following primers were used to screen the 5’ insertion site: 5’-GCCAAGTGGGCAGTTTACCG-3’ (outside of the 5’-arm) and 5’-TAGGTAGGGGATCGGGACTCT-3’ (in the CAG). For the 3’ insertion site, the primers used were: 5’-GCCAGCTCATTCCTCCCACTC-3’ and 5’-GGCATGGCAATGTTCAAGCAG-3’ (outside of 3’-arm). Chimeric mice were generated by microinjection of ES cells into blastocysts, and germ-line transmission was confirmed by testing the presence of ROSA26 transgene DNA into genomic DNA by PCR using two pairs of the following primers: forward 5’-GCAGCCCAAGCTAGATCGAAT-3’, and reverse 5’-TTGACACGTCCGGCTTATCC-3’ for the transgene and forward 5’-CCTAGCTGTCACCAACCCTTT-3’, reverse 5’-GACGAAGAGCATCACAAGGAG-3’ for the wild-type. This mouse line is available from the Jackson Laboratory: IRF3-2D (JAX: 036261).

Echocardiography
Echocardiography was performed either in anesthetized ~12 week old (αMHCMCM, CMI3OE, αMHC-Cre, CMI3KO) with 1.5-2.0% Isofluorane or in awake ~4 week old (Mck-Cre and MI3OE) mice using the Vevo 3100 System (VisualSonics) equipped with a 30 MHz-transducer (MX400 Transducer). Left ventricular structural measurements were obtained in the short-axis view using 2D B-mode and M-mode images including left ventricular posterior wall diameter during diastole and systole (LVPWd, LWPWs). Left ventricular structural measurements were used to obtain systolic indices, ejection fraction (EF) and fractional shortening (FS).

AAV9-mediated cardiomyocyte-specific PGC-1α overexpression in mice
To attain cardiomyocyte-specific expression of murine PGC-1α in adult mice we obtained ultra-purified AAV9-TnT-mPGC-1α (1.36×1014 GC/ml) and AAV9-TnT-EGFP (5.2×1013 GC/ml) from Vector Builder Inc, USA. Male C57BL/6J, 8 week old mice were injected with various doses of AAV9-TnT-mPGC-1α to identify the optimum dose for PGC-1α expression. After screening, 1×1012 was selected as the appropriate dose to obtain moderate gene expression (~3 fold) of PGC-1α in the left ventricle tissue of CMI3OE mice compared to EGFP controls.

Analysis of human cardiac tissue
The human studies were approved by Ethics Committee of the Medical Association Hamburg, File No. 523/116/9.7.1991. Non-failing specimens were obtained between 1991 and 1999, where, in rare cases, incompatibilities prevented transplantation. Patients provided written informed consent. Human left ventricle tissue samples from non-failing and ischemic patients were processed for RNA isolation using RNeasy Universal Minikit (Cat. No. 73404, Qiagen) combined with genomic DNA elimination following the manufacturer instructions. To obtain protein lysates Kranias buffer (30mM Tris pH 8.8, 5mM EDTA, 30mM NaF, 3% SDS, 10% Glycerol, 1mM DTT) was used. Protease inhibitor cocktail (Roche), phosphatase inhibitor cocktail (Thermo Fisher), 1mM Na3VO4 and 1mM PMSF was added fresh, right before tissue homogenization. For immunoblotting, tissue samples were homogenized in Qiagen Tissue Lyser II and immunoblotted as mentioned below.

Reagents
Tamoxifen, lipopolysaccharide (LPS), polyinosinic-polycytidylic acid (polyI:C), Insulin, cytochalasin B, glucose, and 2-deoxyglucose were purchased from Sigma-Aldrich. 2-Deoxy-D-glucose, [1,2-3H(N)]- (1mCi/ml, Cat. MT911) was purchased from Hartmann Analytic.

Tamoxifen gavage
Body weight was measured before and on third day of Tamoxifen gavage. For inducing gene expression, 12-week old CMI3OE mice were treated with tamoxifen by oral gavage of 30mg/kg tamoxifen dissolved in corn oil on 3 consecutive days.

Isolation of adult cardiomyocytes
Adult mouse ventricle cardiomyocytes were isolated by enzymatic digestion via the Langendorff perfusion as previously described99. In brief, 12 week old mice were euthanized, hearts were quickly excised and transferred into a chamber filled with ice-cold PBS, aorta was connected to a 21G cannula. The heart was perfused with the perfusion buffer (NaCl 113mM, KCl 4.7mM, KH2PO4 0.6mM, Na2HPO4.2H2O 0.6mM, MgSO4.7H2O 1.2mM, NaHCO3 12mM, KHCO3 10mM, HEPES 10mM, Taurine 30mM, 2,3-butanedione-monoxime 10mM, glucose 5.5mM, pH 7.4) for 3 min at 37°C. The heart was digested with 30 ml digestion buffer containing perfusion buffer with liberase DH (0.04 mg/ml, Roche), trypsin (0.025%, Gibco) and CaCl2 (12.5 μM, Sigma) at 37°C. The atria were excised and discarded, and the ventricle tissue digestion was stopped using 2.5 ml stop buffer I (perfusion buffer containing 1% BSA (Sigma, Germany) and 50 μM CaCl2). The digested heart was cut into small pieces, minced with 1 ml syringe for 3 min and filtered through a 200 µm nylon mesh. Cardiomyocytes were allowed to sediment for 10 min and transferred to stop buffer II (perfusion buffer containing 0.5% BSA and 37.5 μM CaCl2) settled by subjecting to increasing recalcification up to 1 µM Ca2+ concentration. The supernatant was aspirated and the isolated cardiomyocyte pellet was resuspended in 20 ml myocyte culture medium. Isolated adult cardiomyocytes were plated in laminin coated 24 well plates. After 2h the culture media was changed and cells were used for glucose uptake assay or harvested for protein or RNA isolation.

Glucose uptake in isolated adult cardiomyocytes
Glucose uptake assay was performed in isolated cardiomyocytes from CMI3OE and αMHCMCM mice as described earlier32. Briefly, adult cardiomyocytes were isolated as described above and incubated in serum-free DMEM (11-965-118, Gibco) for 15 min. Cells were treated with 0.5 µCi/ml of 2-Deoxy-D-glucose, [1,2-3H(N)]- (1mCi/ml, Cat. MT911, Hartmann Analytic) for 15 min. Glucose uptake was stopped quickly with media containing 10 µM cytochalasin B (Sigma) on ice. Cardiomyocytes were solubilized in 0.1N NaOH for 20 min, and radioactivity was measured by scintillation counting. Total protein was measured by BCA protein assay kit (Pierce) and the glucose uptake was normalized to the protein content.

Isolation of mouse fibroblasts
Fibroblasts from CMI3KO and Cre control were isolated following the protocol from Sahadevan P and Allen BG100 with slight modifications. Briefly, the heart was perfused with ice-cold perfusion buffer (PBS containing 2% FBS) by inserting a 27G needle into the left ventricle apex at a rate of ~3 ml/min for 3 min. The heart was excised and rinsed twice with ice-cold perfusion buffer. The atria were removed and the ventricle was minced into small pieces using scissors in 50 µl digestion buffer (DMEM/F12 (1:1) containing 2 mg/ml Collagenase II, 1% FBS, 1% penicillin/streptomycin). The minced heart was transferred into a 15 ml falcon tube containing digestion buffer (2 ml per heart) and incubated at 37°C for 20 min with gentle rotation and cardiac fibroblasts were isolated as described in the protocol. Isolated cardiac fibroblasts were cultured on collagen pre-coated plates in DMEM/F12 (1:1) containing 10% FCS and 1% penicillin/streptomycin. After 2h, cells were washed twice with PBS and fresh media was added. Cardiac fibroblasts at ~70% confluency were harvested for RNA isolation.

Isolation of mouse endothelial cells
Endothelial cells from CMI3KO and Cre control was isolated following the protocol from Sokoi et al.101 with slight modifications. Briefly, transcardial perfusion via the left ventricle was performed with ice-cold PBS at a perfusion rate of ~3 ml/min for 3 min. Heart was harvested, atria were removed and cut into tiny pieces with scissor, pooled (from two mice) and transferred in a 50 ml falcon tube with 5 ml digestion buffer (KnockOut DMEM (Thermo Fisher) containing Pencillin/Streptomycin, Antibiotic-Antimycotic, sodium pyruvate, MEM non-essential amino acids, endothelial cell growth supplement, Collagenase II, and DNAse I). Samples were digested in 37°C water bath for 25 min. Tubes were shaken vigorously by hand ever 5-10 min for faster tissue dissociation. The mix was transferred onto a Gentle MACS tube (Miltenyi Biotech #130-093-237), placed on a gentle MACS TM Octo Dissociator and Protocol C was run. Collected samples were washed and pelleted by sequential steps as described in the protocol. The pellet was resuspended in 90 µl wash buffer (PBS containing 0.5% BSA and 2mM EDTA) and 10 µl of CD31 Microbeads (Miltenyi Biotech #130-097-418) for 1×107 cells was added and incubated for 15 min at 4C. Cells were washed with 3 ml wash buffer and centrifuged at 300g for 5 min at 4°C. The pellet was resuspended in 0.5 ml wash buffer, the cell suspension was loaded onto the LD column (Miltenyi Biotech #130-042-901) and CD31 positive cells were collected as described in the protocol. The isolated endothelial cells were seeded in 12 well plates in culturing media (KnockOut DMEM (Thermo Fisher) containing Penicillin/Streptomycin, Antibiotic-Antimycotic, sodium pyruvate, MEM non-essential amino acids, and endothelial cell growth supplement) and the media was changed after 3h. Endothelial cells were harvested after 24h for RNA isolation.

Cloning of IRF3, IRF3-2D mutant or PGC-1α
For expression in primary cardiomyocytes, the PCR product encoding murine PGC-1α, WT murine IRF3 or IRF3-2D mutant (described earlier32) or was recombined into the pDonR221 plasmid (Invitrogen) using the Gateway technology and was subsequently shuttled into the p-DEST (Invitrogen) vector to generate HA-tagged WT murine IRF3 or IRF3-2D mutant, Flag-tagged murine PGC-1α following manufacturer’s instructions. For adenoviral expression, vector pAd/CMV/V5-DEST (Invitrogen) encoding cDNA for murine PGC-1α, WT murine IRF3 or IRF3-2D mutant was generated as described earlier32. Briefly, the PCR product encoding murine PGC-1α, WT murine IRF3 or IRF3-2D was recombined into the pDonR221 plasmid using the Gateway technology and was subsequently shuttled into the pAd/CMV/V5-DEST vector to generate adenoviruses as described below. A β-galactosidase-V5–encoding adenovirus (Ad-LacZ, Life Technologies) served as a control.

Adenovirus production and titer for cell culture
HEK293A cells were transfected with PacI restriction-digested adenovirus vector pAd/CMV/V5-DEST encoding cDNA for WT murine IRF3 or IRF3-2D or PGC-1α using Lipofectamine 2000 (Life Technologies). Adenovirus titer was determined by staining transduced HEK293A cells with fluorescent anti-Hexon antibody. A β-galactosidase-V5-encoding adenovirus (pAd-LacZ, Life Technologies) served as a control.

Isolation and treatment of neonatal rat cardiomyocytes
NRCMs were isolated as previously described102. In brief, left ventricles from 1–2-days old Wistar rats (Charles River, Germany) were harvested and chopped in ADS buffer containing 120mM NaCl, 20mM HEPES, 8mM NaHPO4, 6mM glucose, 5mM KCl, and 0.8mM MgSO4, pH 7.4. About five to six enzymatic digestion steps were performed at 37°C with 0.6 mg/ml pancreatin (Sigma-Aldrich) and 0.5 mg/ml collagenase type II (Worthington Biochemical Corporation) in sterile ADS buffer. The homogeneous cell suspension was passed through a cell strainer followed by the addition of newborn calf serum to stop the enzymatic digestion. A Percoll (GE Healthcare) gradient centrifugation was used to separate cardiomyocytes from fibroblasts and cultured in DMEM containing 10% FCS, penicillin/streptomycin (Life Technologies), and L-glutamine (Life Technologies). About 80% confluent NRCMS were treated with 0.5 µg/ml polyI:C for 6h and harvested for RNA isolation. Overexpression and knockdown studies for gene expression and immunoblotting was achieved using adenovirus-mediated transduction for 48h. For hypoxia treatments, 70-80% confluent NRCMs were transduced with adenovirus for 24h and the media was changed to DMEM supplemented with 1% penicillin/streptomycin and placed into the hypoxic incubator (1% O2, 5% CO2, 94% N2). The media was equilibrated overnight to respective oxygen levels before use. After 24h, cells were briefly washed with DBPS and terminated with TRIzolTM (Invitrogen #15596018) for RNA isolation.

Reporter gene assays
The reporter gene assays were performed in 70% confluent NRCMs cultured in 24 well plates. For overexpression, NRCMs were transfected with HA-IRF3-2D, Flag-PGC-1α or empty vector (pcDNA3.1); for knock-down experiments, NRCMs were transfected with siRNA against IRF3 or SilencerTM negative control siRNA (siCtrl) from Silencer® Select (siIRF3: Cat AM16704, ID 217531, Ambion; Silencer negative control: Cat AM4635, Ambion) along with plasmid constructs encoding Renilla luciferase, PPRE-luciferase reporter (PPRE X3-TK-Luc), PPARα, RXRα using Lipofectamine 3000. After 48h of transfection, chemiluminescence was measured using a Dual-luciferase® Reporter Assay kit (E1960 Promega) on TECAN Spark multimode reader with injector module following manufacturer’s instructions. Luciferase activity was normalized for transfection efficiency against Renilla activity that was used as an internal control.

RNA isolation and gene expression analysis by quantitative PCR
Total RNA was isolated from mice cardiac ventricle tissue using the RNeasy Universal Mini kit (Cat. No. 73404, Qiagen) combined with genomic DNA elimination following the manufacturer instructions. From cultured cells, total RNA was isolated using TRIzol reagent (Invitrogen). RNA was reverse transcribed using MMLV reverse transcriptase. Gene expression was assessed by quantitative PCR (qPCR) using synthesized cDNA with SYBR Green qPCR Master Mix (Thermo Fisher) and specific primers using a 7900HT Fast Real Time PCR System (Applied Biosystems). Primer sequences used in this manuscript are listed in Source data file_ Supplemental Table 2. The relative abundance of mRNA was normalized to 36B4 mRNA as the invariant control using the ΔΔCt method (where Ct is the threshold cycle)103.

RNA-seq
mRNA was purified from total RNA using poly-T oligo-attached magnetic beads. After fragmentation, the first strand cDNA was synthesized using random hexamer primers, followed by the second strand cDNA synthesis. Libraries prepared using Novogene NGS RNA Library Prep Set (PT042) were sequenced on Illumina NovaSeq 6000 platform S4 flow cell. RNA-seq data are aligned using Hisat2 v2.0.5. Reads are assigned to transcripts using featureCounts104. Differential expression analysis of the data was performed using edgeR105. The P values were adjusted using the Benjamini & Hochberg method. Local version of the gene set enrichment analysis tool (http://www.broadinstitute.org/gsea/index.jsp) was used, GO, KEGG (Kyoto Encyclopedia of genes and Genomens) and Reactome were used for GSEA independently106,107.

Single-cell RNA-Seq data analysis
The analysis and visualization of the data obtained from GEO accession number GSE109816 and GSE12189335 was performed using Python v3.12.4 with the following modules: pandas (v2.2.2), matplotlib (v3.8.4), scanpy (v1.10.3) and anndata (v0.10.0).

Mitochondrial DNA isolation from the left ventricle of rats
Mitochondrial DNA of high purity for transfection was isolated from the left ventricle tissue of 16 wk old Wistar rats using mtDNA Extractor CT kit from WAKO (#291-55301) following the manual instructions. Isolated mtDNA was dissolved in TE buffer and treated with 10 µg/ml RNase A (Thermo Fisher) for 30 min at RT. About 80% confluent NRCMs were transfected with freshly isolated mtDNA (1 µg/ml) using Lipofectamine 3000 (Life Technologies) for RNA and protein analysis.

Mitochondrial DNA content measurement by mtDNA/nDNA ratio
To access the mitochondrial DNA content, mitochondrial DNA to nuclear DNA ratio was estimated from mitochondrial DNA isolated from the left ventricle of CMI3OE and Cre controls using a method established in our lab following the detailed protocol published by Quiros et al.108. The primer sequences used to quantify mtDNA/nDNA ratio by accessing Nd1, 16sRNA and HK2 expression are provided in the referred article.

Cell-Fractionation
For cell fractionation, adult cardiomyocytes were isolated from CMI3OE and Cre control mice following the Langendorff-free method from Roger Foo lab109. Cells were fractionated into cytoplasm, membrane bound and nuclear fractions following the protocol published by Baghirova et al.110. Protein in each fraction was quantified by BCA method and immunoblotting was performed with GAPDH, VDAC and Histone H3 antibody as a marker for cytoplasmic, membrane bound and nuclear protein fraction.

Co-Immunoprecipitation assay
About 70% confluent primary cardiomyocytes were transfected with HA-IRF3-2D and Flag-PGC-1α in DMEM containing 10% FCS. Cells transfected with empty vector were used as negative control. After 6h, media was changed and cells were culture for another 48h in DMEM containing Pen/Strep and 10% FCS. Cells were harvested after 48h and lysed in Cell lysis buffer (Cell signaling #9803). Protein was determined by BCA protein assay kit and 1mg protein was used for co-immunoprecipitation using anti-Flag Dynabeads (Sigma) following manufacturer’s instructions. Eluted sample (20 µl) was loaded on 4%–12% SDS-PAGE gel, transferred to nitrocellulose membrane and immunoblotted with anti-Flag and anti-HA antibody.

Similarly, co-immunoprecipitation assay in the cardiomyocytes isolated from the left ventricle tissue of CMI3OE and Cre control mice was performed using 1mg of the protein lysate with anti-PGC-1α antibody pulldown followed by incubation with Dynabeads Protein G (Invitrogen #10004D). In another assay, primary cardiomyocytes seeded in 10 cm dishes were treated with PolyI:C (2 µg/ml) for 6h, cells were lysed in Cell lysis buffer and co-immunoprecipitation was performed using 1mg total protein lysate as mentioned above. Immunoblots were blocked using Easy blocker (GTX425858) and incubated with primary antibody overnight. Monoclonal mouse anti-rabbit IgG HRP (Cell signaling #5127) was used as secondary antibody.

Immunostaining and confocal imaging
For immunostaining, NRCMs seeded in 4 well µ-slides (Ibidi, Cat. #80426) were transduced with adenovirus for 48h. Cells were washed with PBS and fixed in 4% paraformaldehyde (PFA) for 30 min at room temperature (RT). Following three PBS washes, cells were incubated in blocking solution (1x PBS containing 2.5% bovine serum albumin and 0.3% Triton X-100) for 1h at RT. Primary antibodies, diluted 1:200 in blocking solution, were applied overnight at 4°C. After three PBS washes, cells were incubated with secondary antibodies diluted 1:400 in blocking solution for 90 min at RT. Cells were washed in PBS and incubated with DAPI (MilliporeSigma, Cat. #10236276001), diluted 1:1000 in blocking solution, for 6 min at RT. Primary antibodies used were anti-IRF3 (Cell Signaling Technology, Cat. #4302) and anti-α-actinin (Sigma-Aldrich, Cat. #A7732). Secondary antibodies were Alexa Fluor 488-conjugated anti-mouse IgG and Alexa Fluor 647-conjugated anti-rabbit (Thermo Fisher Scientific). Confocal imaging was performed using a Leica Mica confocal microscope with a 63x HC PL APO objective.

Immunoblotting
Tissue lysates (20-40 µg protein), cell lysates (10 µg protein) prepared in RIPA buffer (9806 Cell signaling) with appropriate protease and phosphatase inhibitors were separated by 4%-12% gradient SDS-PAGE and transferred to nitrocellulose membrane (Millipore). Blots were incubated with primary and HRP-conjugated secondary antibodies. Detection was performed with enhanced chemiluminescence (GE healthcare) and imaged on Amersham Imager 600 (GE healthcare). All bots were quantified using ImageJ software (NIH, Bethesda, MD). To view unedited blots please refer to the Source data_unedited blots.

Antibodies
Antibodies were purchased from Cell Signaling (IRF3, 4302; pIRF3 [S396], 29047; Vinculin, 4650; HA-Tag, 3724; VDAC [D73D12], 4661; Histone H3 [D1H2], 4499; OGT [D1D8Q], 24083; p-p38MAPK [Thr180/Tyr182] 9211; p38MAPK, 9212; pAMPKα [Thr172], 2535; AMPKα, 2532; pAKT [S473], 4051; AKT, 9272; O-GlcNAc [CTD110.6], 9875), Abcam (OXPHOS, ab110413), Merck Millipore (PGC-1α, ST1202), and Sigma (Flag M2 [F1804], GAPDH [G8795]). Secondary antibodies used were: HRP goat anti-rabbit (Cat. 111-035-144, Jackson ImmunoResearch Labs) and HRP goat anti-mouse (Cat. 115-035-003, Jackson ImmunoResearch Labs).

Analysis of plasma parameters
Blood glucose levels were measured using a portable glucometer (Accu-Chek). Blood samples were collected from fed (ad libitum) animals in EDTA-coated blood collection tubes. Plasma insulin levels were quantified using an ELISA kit (Crystal Chem) following the manufacturer’s instructions.

Measurement of plasma free fatty acids, triglyceride and cholesterol
Plasma free fatty acids were determined using the NEFA HR (2) Assay (FUJIFILM). Plasma cholesterol and triglycerides were measured using commercial colorimetric kits (Roche, Mannheim, Germany) that were adapted to 96-well microtiter plates with Precipath as standard.

Measurement of plasma cytokines
The concentration of TNF-α (#DY410), CCL2 (#DY479), IL-1β (#DY401), and IL-6 (#DY406) was measured in the mouse plasma samples using the equivalent DuoSet ELISA kits (R&D Systems, Minneapolis, MN, USA) following the manufacturer’s protocols. Coating of Nunc-immuno modules (#469949, Thermo Scientific, Waltham, MA, USA) with the respective capture antibodies was performed overnight and 1% Bovine Serum Albumin, Fraktion V (#9048-46-8, Carl Roth, Karlsruhe, Germany) in PBS, pH 7.4 was used as a reagent diluent. To detect HRP-conjugated antibodies KPL TMB Microwell Peroxidase Substrate System (#5120-0047, Seracare, Milford, MA, USA) was used as a substrate and 1N Sulfuric acid (#339741, Merck, Darmstadt, Germany) was used as a stop solution. Finally, absorbance was measured at 450 nm using a Multiskan GO Microplate Spectrophotometer (Thermo Scientific, Waltham, MA, USA).

Measurement of CK-MB
Quantitative determination of CK-MB levels was performed in plasma samples using colorimetric ELISA kit (#NBP2-75312, Novus Biologicals) following manufacturer’s instructions.

Metabolome and lipidome sample processing and data analysis
Sample collection and processing for metabolome and lipidome. To perform metabolome and lipidome profiling, mice were perfused with PBS, cardiac ventricle tissue samples were harvested, snap frozen in liquid nitrogen and stored at -80°C before extraction.

Metabolites extraction (water-soluble metabolites and lipids). The samples were homogenized with Mixer Mill (Retsch) and steel beads at maximum frequency for 3 min in pre-cooled racks after adding ice-cold methanol/H2O (4:1, v/v, 500 µL per 10 mg tissue) with internal standards (D4-glutaric acid, and D8-phenylalanine, 4 µl Splash Lipidomix per 10 mg tissue). A total of 500 µL of homogenate was then collected and extracted by applying 120 µL 0.2 M HCl, 800 µL chloroform, and 400 µL H2O consecutively with vortex. The extracts were spun down at 16000g for 10 min, and the upper phase (water-soluble metabolites) was transferred to a 1.5 ml vial and evaporated for 15 min at 35°C under nitrogen and dried in SpeedVac (Eppendorf) at 15°C overnight. The lower phase (lipids) was evaporated to dryness at 45°C under nitrogen. The interphase was used to determine the protein concentration with the BCA assay. Samples were stored at −80°C until processed.

LC-MS analysis of water-soluble metabolites. Water-soluble metabolites extract was dissolved in 100 µl 5 mM ammonium acetate (in 75% acetonitrile (v/v)) before loading to LC/MS. LC-MS analysis was performed on an Ultimate 3000 HPLC system (Thermo Fisher Scientific) coupled with a Q Exactive Plus MS (Thermo Fisher Scientific) in both ESI positive and negative mode. The analytical gradients were carried out using an Accucore 150-Amide-HILIC column (2.6 µm, 2.1 mm × 100 mm, Thermo Fisher Scientific) with solvent A (5 mM ammonium acetate in 5% acetonitrile) and solvent B (5 mM ammonium acetate in 95% acetonitrile). A total of 3 µl sample was applied to the Amide-HILIC column at 30°C, and the analytical gradient lasted 20 min. During this time, 98% of solvent B was applied for 1 min, followed by a linear decrease to 40% within 5 min and maintained for 13 min before returning to 98% in 1 min and appended with a 5-min equilibration step. The flow rate was maintained at 350 µL/min. The eluents were analyzed with MS in ESI positive/negative mode with ddMS2. The full scan at 70k resolution (69-1000 m/z scan range, 1e6 AGC-Target, 50ms maximum Injection Time (maxIT)) was followed by add MS2 at 17.5k resolution (1e5 AGC target, 50ms maxIT, 1 loop count, 0.1s to 10s apex trigger, 2e3 minimum AGC target, 20s dynamic exclusion). The HESI source parameters were set as 30 sheath gas flow rate, 10 auxiliary gas flow rate, 0 sweep gas flow rate, spray voltage: 3.6 kV in positive mode, 2.5 kV in negative mode, 320°C capillary temperature, and the heater temperature of auxiliary gas was 120°C. The annotation of the metabolites was performed using the EI-Maven software (Elucidata, https://www.elucidata.io/el-maven) with an offset of ±15 ppm.

LC-MS/MS analysis of lipids. The lipids extract was dissolved in 100 µl of isopropyl alcohol (iPrOH) before loading. The analytical gradients were carried out using an Accucore C8 column (2.6 µm, 2.1 mm × 50 mm, Thermo Fisher Scientific) with solvent A (acetonitrile/H2O/formic acid (10/89.9/0.1, v/v/v)) and solvent B (acetonitrile/iPrOH/H2O/formic acid (45/45/9.9/0.1, v/v/v/v)). 3 µl sample was applied to the C8 column at 40°C, and the analytical gradient lasted for 35 min. During this time, 20% of solvent B was applied for 2 min, followed by a linear increase to 99.5% within 5 min and maintained for 27 min before returning to 20% in 1 min and appended with a 5-min equilibration step. The flow rate was maintained at 350 µl/min. The full scan and ddMS2 parameters were the same as the analysis of the water-soluble metabolites, except the scan range were adjusted to 200–1600 m/z. The HESI source parameters were also adapted with a 3-sweep gas flow rate and a 3.2 kV spray voltage in positive and 3.0 kV in negative mode. Peaks corresponding to the calculated lipid masses (±5 ppm) were integrated using El-Maven software.

Stable-isotope tracing for metabolic flux measurement
Sample isolation, treatment and collection. Cardiomyocytes were isolated from 12-14 wk old CMI3OE and Cre controls following the Langendorff-free method from Roger Foo lab109. About 1×106 cells were plated on laminin (5 µg/ml) pre-coated 6cm dishes for 3h in plating media [M199 (Sigma 4530) containing 5% FBS, 10 mM BDM and 1X Pen/Strep]. Cardiomyocytes were washed twice with PBS and treated with 5.5 mM U-13C6-Glucose (Merck #389374) in DMEM media (GibcoTM 11966025) for 10 min and 120 min to measure metabolic flux into glycolysis, PPP and TCA cycle. Cells were washed quickly with PBS, flash frozen in liq. N2 and stored at -80°C until analysis.

Polar Metabolites extraction and LC-MS analysis. Cells were scraped off in 1 ml ice-cold methanol: H2O: acetonitrile (50:20:30 v/v) containing internal standards (MSK-CAA-1, DLM-7654, DLM-9476, DLM-9045, DLM-9071, DLM-6068, DLM-831 and DLM-3487, Cambridge Isotope Laboratories). Polar metabolites were extracted using a C18 8B-S001-DAK solid phase column, as previously described111. Dried metabolite extracts were dissolved in 100 μl acetonitrile/water (25:75, v/v) before analysis. Water-soluble metabolites were analyzed by LC-MS/MS using a Q-Exactive Plus quadrupole-Orbitrap mass spectrometer (Thermo) interfaced with an ultra high-performance liquid chromatography (Ultimate 3000, Thermo). The analytical gradient was carried out as previously described112 using a SeQuant ZIC-pHILIC column (5 µm, 2.1 mm × 150 mm, Millipore Sigma) with solvent A (20 mM ammonium carbonate + 0.1% ammonium hydroxide in water) and solvent B (acetonitrile). The samples (3 µL) were injected into the column at 25°C, and the analytical gradient lasted 30 min, as follows: linear gradient from 80% to 20% within 20 min before returning to 80% in 0.5 min. and appended with a 7.5-min equilibration step. The flow rate was maintained at 150 µL/min. The eluents were analyzed with MS in ESI positive/negative mode with ddMS2. The full scan at 70k resolution (69-1000 m/z scan range, x106 AGC-Target, 50ms maximum injection time (maxIT)) was followed by add MS2 at 17.5k resolution (1×105 AGC target, 20ms maxIT, 1 loop count, 2s to 10s apex trigger, 2×103 minimum AGC target, 20s dynamic exclusion). The HESI source parameters were set as 40 sheath gas flow rate, 15 auxiliary gas flow rate, 1 sweep gas flow rate, spray voltage: 3.0 kV in positive mode, 3.1 kV in negative mode, 320°C capillary temperature, and the heater temperature of auxiliary gas was 120°C. Peaks were integrated using the El-MAVEN software and the R package IsoCorrectoR113 was used to correct for natural 13C abundance. The peak area of each target was normalized to the peak area of internal standards (positive/negative standards for metabolites) and protein concentration.

NAD metabolomics
Preparation of murine heart tissue for NAD metabolomics. The heart of an anaesthetized mouse was perfused with ice-cold phosphate-buffered saline (PBS), quickly excised, and placed in a dish containing ice-cold PBS. Subsequently, the atria were removed, and the ventricle was excised by cross-section cut. ~20–25 mg of the apex was weighed and promptly transferred into a pre-chilled tube. The collected tissue sample was snap-frozen in liquid nitrogen and stored at -80°C until further processing.

Determination of energy carrier metabolites. Frozen murine heart tissues (15-25 mg) were processed following an adjusted protocol targeting energy carriers such as NAD/NADH and NADP/NADPH114. Briefly, on ice to the frozen murine heart tissues were added ice-cooled steel balls with 250 µl cooled extraction buffer (Acetonitrile: Methanol: 15mM ammonium acetate in H2O (3:1:1), pH 10). Subsequently, frozen material was grinded in a Retsch© Mill MM400 (1×30 sec.; frequency 25/sec.). Afterwards, samples were centrifuged for 15 min at 4°C and 13,000g, and the resulting supernatant was transferred to a new LC-MS grade autosampler vial for measuring.

For metabolite separation and detection, an ACQUITY I-class PLUS UPLC system (Waters) coupled to a QTRAP 6500+ (ABSCIEX) mass spectrometer with electrospray ionization (ESI) source was used. In detail, metabolites were separated on an ACQUITY Premier BEH Amide Vanguard Fit column (100 mm × 2.1 mm, 1.7 µm, Waters) with constant column temperature of 35°C. Separation of NAD/NADH and NADP/NADPH was achieved by the following LC gradient scheme (Table S2) using mobile phase A (50/50; Acetonitrile/Water with 5mM ammonium acetate + 0.05% (v/v) ammonium hydroxide, pH 10) and mobile phase B (90/10; Acetonitrile: Water with 5mM ammonium acetate + 0.05% (v/v) ammonium hydroxide, pH 10). Data acquisition was performed using Analyst 1.7.2 (ABSCIEX) and processed using the OS software suite 2.0.0 (ABSCIEX).

Intracellular NAD+/NADH measurement in neonatal rat cardiomyocytes. Cardiomyocytes isolated from neonatal rat ventricles were transduced with adenovirus expressing IRF3-2D or PGC-1α alone or in combination. LacZ transduced cardiomyocytes were used as a control. Intracellular nucleotides NADH, NAD and their ratio measured using NAD+/NADH Quantification Kit, (Cat. #K337-100, BioVision) following the manufacturer’s instructions.

Plasma Lipidomic analysis. Plasma lipidomic analysis was performed using the LipidyzerTM Platform from SCIEX. In brief, plasma samples were spiked with LipidyzerTM Internal Standards and lipid extraction was done using an adjusted MTBE/methanol extraction protocol115. Briefly, plasma samples were mixed with the MTBE/methanol/water in the ratio 10:3:2.5 (v/v/v). Samples were homogenized and centrifuged at 10,000g, 4°C for 10 min. The upper phase containing lipids was separated, concentrated and reconstituted in a mixture of dichloromethane (50): methanol (50) containing 10 mM ammonium acetate. Separation and targeted profiling of lipid species was performed combining differential mobility spectrometry and a QTRAP® system (QTRAP® 5500; SCIEX). Lipids were quantified by the LipidyzerTM software (Lipidomics Workflow Manager software version 1.0.5.0; SCIEX) employing specific multiple reaction monitoring transitions.

Measurement of fuel dependency with Fuel-Flex assay using Agilent Seahorse XF. Cardiomyocytes were isolated from neonatal rats and seeded in 96-well plate at the density of 5000 cells per well for Seahorse assays (Agilent Seahorse XFE96 Analyzer). Cardiomyocytes were transduced with adenovirus expressing LacZ (25 ifu), IRF3-2D (10 ifu) and PGC-1α (25 ifu) for 48h. Fuel dependency was determined using Agilent Seahorse XF Mito Fuel Flex Test kit (Cat. #103270) following manufacturer guidelines. Glucose oxidation, glutamine oxidation, and fatty acid oxidation was measured using UK5099 (2 µM), BPTES (3 µM), and Etomoxir (4 µM) final concentration to the cells. Fuel dependency percentage was calculated using formula [(Baseline OCR-Target inhibitor OCR)/ (Baseline OCR-All inhibitor OCR)]*100.

Tissue histology and Masson’s-Trichrome staining. Heart tissues were frozen in Tissue-Tek O.C.T and were cryosectioned using Cryotom Leica CM3050 S to generate heart cross-sections of 6 µM thickness. Cryosections were stained for fibrosis using Masson’s-Trichrome staining method. Imaging was done with the Leica Microsystems CMS Microscope (Cat no: DFC310FX). The fraction of fibrotic area stained in blue was quantified using ImageJ software.

Statistics. All Biochemical and physiological data are presented as mean ± SEM. Statistical significance between two groups was measured using an unpaired two-tailed Student’s t test. A one-way ANOVA followed by Šídák’s multiple comparisons test was performed for more than two groups containing one factor. No exclusion or inclusion criteria were used to analyze the data. RNA-seq studies were analyzed as described above. GraphPad Prism 9.0 was used for statistical calculations. P value less than 0.05 was considered statistically significant and the statistical parameters can be found in each Figure legends.

Reporting summary
Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability
All data supporting the findings are available in the manuscript, supplemental file containing Lipidomics checklist, and Source data file. The raw RNA-seq dataset generated in this paper is submitted to NCBI Gene Expression Omnibus (GEO) and can be accessed through accession number GSE283352, GSE283353). The Metabolomics and Lipidomics data have been deposited to MetaboLights repository with the study identifier MTBLS13783. Source data file contains the raw numbers for graphs and box plots, raw immunoblot images, metabolite levels (shown in Fig. 6, Fig. 7, Figure S7 and Figure S9) associated with this manuscript. Primer sequences utilized for qPCR in this manuscript are included as a Supplemental file. Source data are provided with this paper.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "There is currently a plethora of published data implicating IRF3 in cardiac fibrosis and myocardial infarction. The manuscript by Kumari and colleagues extends our understanding of how IRF3 may contribute mechanistically to these conditions within cardiomyocytes. The authors used a variety of strategies including knockout, knockdown, cell-specific knockout, inducible overexpression, etc, that provides for an overall rigorous analysis of IRF3 function. Noteworthy findings are the 1) identification of PGC1a as a transcriptional target of IRF3 within cardiomyocytes, 2) regulation of metabolic mediators by IRF3 that contribute to heart failure, and 3) reversal of IRF3-driven disease by AAV overexpression of PGC1a. Although the two factors appear to be linked by negative regulation and/or interaction, there are some discrepancies in the function of unphosphorylated versus phosphorylated IRF3 that could be addressed with additional experimentation, as well as clarification of cell-specific function. Below are the major comments related to IRF3 studies.\n1. While the authors show elevated IRF3 transcript levels and pIRF3 levels in both human and mouse models of ischemic cardiomyopathy, it is never addressed what is causing this upregulation. Mechanistically, this seems important to understand disease pathogenesis and to understand 1, what is driving IRF3 expression and 2, what is inducing IRF3 activation in models of heart failure. Further, data in SF1c-d suggests a differential mechanism of IRF3 induction by LPS and poly IC in cardiomyocytes than that seen in the models (TLR ligands appear more robust). This may shed light on the requirements for IRF3-mediated PGC1a expression in cardiomyocytes.\n2. Alterations in transcript expression shown throughout the manuscript of a variety of genes are somewhat correlative with IRF3 expression rather than mechanistically proven. This is particularly relevant for mitochondrial and metabolic genes.\n3. Specificity of CMI3KO mice was only shown in cardiomyocytes (Fig. 2b) versus organs not relevant to the heart (SF2a). Given findings of IRF3 expression within other cell types in the heart (SF1b), it would be more beneficial to examine IRF3 expression within ECs, FBs, MPs and SMCs of CMI3KO mice to exclude functional contributions.\n4. Relevant to comment #3, as shown in Fig. 2, CMI3KO mice are only partially protected.\n5. Data shown in SF2f is a bit confusing as it seems to represent IRF3-mediated transcriptional regulation by non-activated (non-pIRF3) IRF3 since no stimuli appears to be included. These data then suggest that pIRF3 may not be the driver and/or not necessary for transcriptional regulation. Is this instead an issue of siRNA specificity? In addition, did the authors ever examine cellular localization of IRF3 to confirm activity>\n6. Fig. 4i co-immunoprecipitation experiment was done by overexpression. Why not look at interaction of endogenous proteins within the model, which would be more physiologic?\n7. The mechanism(s) by which IRF3 and PGC1a regulate each other is not entirely clear. Moreover, the relevance of the interaction is not clear nor is the data shown in Fig. 4k suggesting that PGC1a somehow regulates IRF3 transcription by overexpression.", "reviewer_2": "In this study, Manju Kumari et al. demonstrated that phosphorylation levels of Ser396/Ser398 in the transcription factor IRF3 are significantly elevated in the left ventricles of both patients with ischemic cardiomyopathy and mouse models. The phosphorylation of IRF3 suppresses the expression of Ppargc1α, resulting in impaired mitochondrial oxidative phosphorylation, dysregulated NAD metabolism, and an excessive type I IFN-driven inflammatory response, collectively contributing to the development of heart failure. Notably, in IRF3-2D-overexpressing mice, restoration of Ppargc1α expression alleviated contractile dysfunction by promoting a metabolic shift toward fatty acid oxidation and attenuating inflammatory fibrotic responses. These findings provide novel insights into the molecular mechanisms underlying heart failure, yet several critical questions remain to be addressed.\n1. The authors' explanation of how IRF3 inhibits PGC-1α function through their interaction is not completely clear. In Fig.4i, the authors described the interaction between IRF3 and PGC-1α. Actually, the author used IRF3-2D (phosphomimic mutant) to investigate its interaction with PGC-1ɑ. What are the differences in the interaction strength between PGC-1α and phosphorylated/non-phosphorylated IRF3? Was the localization of p-IRF3 and PGC-1α examined in cardiomyocytes of Cre and CMI3OE mice using immunofluorescence? Additionally, does p-IRF3 compete with PPAR(or other PGC-1α related transcript factors) for binding to PGC-1α ?\n2. The authors should provide the extent of cardiac fibrosis in CMI3OE mice following tamoxifen treatment. If severe fibrosis has already developed in the heart, its cellular composition would significantly differ from that of a normal heart. Therefore, it is important to determine whether the observed metabolic differences may be caused by changes in cellular composition.\n3. PGC1-ɑ plays a role in promoting mitochondrial biogenesis. Therefore, it is necessary to compare mitochondrial mass and quantity between the Cre group and the CMI3OE group to determine whether the observed metabolic changes are caused by alterations in mitochondrial function or changes in mitochondrial quantity.\n4. An increase in 3OHB alone cannot definitively indicate increased ketogenesis metabolism, as it could also be explained by reduced BOH1 and NAD+ levels leading to its accumulation. Additionally, it is necessary to analyze the fumarate-to-succinate ratio to assess the status of succinate oxidation, rather than relying solely on a decrease in fumarate.\n5. Although the authors observed increased glucose uptake using Deoxy-D-glucose, it can be seen from Fig.S5c that both fructose-1,6-bisphosphate and phosphoenolpyruvate significantly decrease in glycolysis. This suggests that glycolysis may not actually be increased in CMI3OE group. The increased glucose may also be utilized through the pentose phosphate pathway to generate reducing power to counteract ROS. It may not necessarily be that energy metabolism shifted from FA oxidation to glycolysis in CMI3OE group (Fig.5o). Therefore, further analysis of metabolites in the PPP pathway is needed, as well as an examination of whether the transcriptomics of the glycolytic pathway reveals changes in the expression of glycolytic enzymes. It is especially important to use U-13C-glucose in vivo isotope labeling to analyze changes in the glycolysis-TCA cycle metabolic flux.", "reviewer_3": "This is an interesting manuscript that presents new evidence for an axis between IRF3/PGC-1a in promoting ischemic cardiomyopathy. The work uses state of the art approaches and rigorous data analysis. These efforts make a strong case that IRF-3 activation contributes to cardiomyopathy and that PGC-1a overexpression is protective. However, several major questions remain unresolved and should be addressed to understand the mechanisms underlying the proposed axis and maximize the value of these findings to the field.\nSpecific points\n1. Could repair of energetics in cardiomyocytes, independent of IFN response signaling, be sufficient to protect against cardiomyopathy? Is PGC-1a over expression protection due to metabolic repair exclusively (i.e. where inflammatory signals are not important) or a combination of metabolic and inflammatory repair? These studies make a convincing case for a connection between excessive IRF-3 activation, type I IFN response and fuel switch/defective energetics in cardiomyocytes. However, it is not clear how much of the cardiomyopathy phenotype is caused by defective energetics versus the type I IFN response. The role of inflammation in contributing to cardiomyopathy in the context of myocytes is not proven in these studies; the current studies do show augmentation of IFN response in response to injury in cardiomyocytes but stop short of proving the IFN response drives cardiomyopathy. The current studies do not measure or distinguish the individual contributions nor make a convincing case that the IFN response alone is important in these models, despite the schematic that suggests both arms are essential.\n2. Separating the IFN from metabolic responses to injury/IRF3 activation is important, particularly given the introductory narrative making the point that inflammation plays context and time dependent beneficial and detrimental roles. Perhaps this critical confusion can be resolved by a focus on energetics alone: can preservation of Ox-phos sustain injury resistance despite an augmented IFN response? It seems like this may be the case because Ppargc1a overexpression is protective against genetically augmented IRF-3 activity.\n3. Is Ppargc1a over expression sufficient to protect NRCMs from inflammatory (LPS) or ischemic injury responses?\n4. Does IRF-3 binding to PGC-1a sequester PGC-1a and IRF-3 from their transcriptional tasks or are there other mechanisms at play for the apparently reciprocal transcriptional responses? How does the IRF-3/PCG-1a axis in cardiomyocytes work?\n5. Do the current findings exclude a role of myeloid cells in the INF-3-PGC-1-metabolism pathway? Why or why not?\n6. What kinases/phosphatases are necessary for setting the balance of IRF3 phosphorylation?"}, "author_response": "We express our sincere gratitude to all the reviewers and are thankful for their thoughtful and\nconstructive comments. We have performed several additional experiments and also added\nrelevant text in the discussion section to address the concerns raised. We believe that the\nmanuscript research findings have overall gained more strength. The reviewer comments are\nmarked below in bold and our response in plain text.\nReviewer #1 (Remarks to the Author):\nThere is currently a plethora of published data implicating IRF3 in cardiac fibrosis and\nmyocardial infarction. The manuscript by Kumari and colleagues extends our\nunderstanding of how IRF3 may contribute mechanistically to these conditions within\ncardiomyocytes. The authors used a variety of strategies including knockout,\nknockdown, cell-specific knockout, inducible overexpression, etc, that provides for an\noverall rigorous analysis of IRF3 function. Noteworthy findings are the 1) identification of\nPGC1a as a transcriptional target of IRF3 within cardiomyocytes, 2) regulation of\nmetabolic mediators by IRF3 that contribute to heart failure, and 3) reversal of IRF3-\ndriven disease by AAV overexpression of PGC1a. Although the two factors appear to be\nlinked by negative regulation and/or interaction, there are some discrepancies in the\nfunction of unphosphorylated versus phosphorylated IRF3 that could be addressed with\nadditional experimentation, as well as clarification of cell-specific function. Below are the\nmajor comments related to IRF3 studies.\nWe appreciate that the reviewer finds our study noteworthy for the research field.\n1. While the authors show elevated IRF3 transcript levels and pIRF3 levels in both human\nand mouse models of ischemic cardiomyopathy, it is never addressed what is causing\nthis upregulation. Mechanistically, this seems important to understand disease\npathogenesis and to understand 1, what is driving IRF3 expression and 2, what is\ninducing IRF3 activation in models of heart failure. Further, data in SF1c-d suggests a\ndifferential mechanism of IRF3 induction by LPS and poly IC in cardiomyocytes than that\nseen in the models (TLR ligands appear more robust). This may shed light on the\nrequirements for IRF3-mediated PGC1a expression in cardiomyocytes.\nWe agree that this is an important issue and have thus addressed the role of damage-\nassociated molecular patters (DAMPs) generated by sterile inflammation within the myocardium\nin aggravating innate immune response in the discussion section of the revised manuscript\n(page 22) and in the manuscript text of Fig. 1k,l. IRF3 is a transcriptional regulator of innate\nimmune response via type I interferon signaling, expressed in various tissues and mostly\nlocalized to the cytosol under resting state indicating a role in maintaining basal cellular function.\nData in Fig. S1c-d indeed show a robust innate response to TLR ligands in neonatal\ncardiomyocytes and this likely is not only because of the TLR ligands being robust but also due\nto mammalian immune response differences between the neonate and adults resulting\n1\nheightened yet uncontrolled (immature) innate immune response of neonatal cardiomyocytes\ncompared to adult cardiomyocytes (PMID 18490660 and studies from our lab).\nSeveral DAMPs such as mitochondrial DNA (mtDNA), dsRNA, ssRNA, heat shock proteins,\nS100 proteins etc. have been reported to provoke innate immune signaling in the injured\nmyocardium (PMID 27340270). Relevant to the focus of the current study, mtDNA is a widely\nstudied DAMP, also known to trigger the inflammatory response during cardiac injury. In the\nrevised manuscript we show that mtDNA introduction in primary cardiomyocytes elicits an\nincrease in type I IFN signaling along with a robust increase in phospho-IRF3 (Fig. 1k). Recent\nstudies have identified a role for cellular mtDNA content and circulating mtDNA in disease\npathology of heart failure patients (PMID 20339121, PMID 30632383, PMID 28049543). Thus, it\nis plausible that mtDNA released from damaged cells in myocardial infarction provoke type I IFN\nresponse in the surviving cells including cardiomyocytes resulting in IRF3 activation by\nphosphorylation and translocation to the nucleus. PGC-1α is also localized in the nucleus and\nunder stress conditions its transcriptional activity is regulated by multiple post-translational\nalterations (PMID 31406949, PMID 29388552). Although it is not known whether PGC-1α is a\ndirect transcriptional target of IRF3 in cardiomyocytes, in the revised manuscript we investigated\nthe effect of IRF3 activation on potential factors that are known to regulate PGC-1α\nposttranslational state. This is also further described in our response to the next comment\nbelow.\n2. Alterations in transcript expression shown throughout the manuscript of a variety of\ngenes are somewhat correlative with IRF3 expression rather than mechanistically\nproven. This is particularly relevant for mitochondrial and metabolic genes.\nWe agree to the reviewer that the effects on inflammatory and mitochondrial oxidative\nphosphorylation marker genes are correlated to IRF3 expression. Our findings in the\ncardiomyocyte-specific IRF3 deficient and IRF3 activation model together with effect on primary\ncardiomyocytes indeed suggest a mechanistic link and are in accordance of IRF3 as a\ntranscriptional nexus between inflammation and oxidative function within cardiomyocytes via\nregulation of PGC-1α. We have shown in Fig. 4g and Fig. 5i that PGC-1α is downregulated\nupon IRF3 activation. Furthermore, we have shown that cardiomyocyte specific expression of\nAAV9-TnT-PGC-1α could partially rescue the systolic dysfunction in CMI3OE mice (Fig. 7d-e).\nOur data demonstrates effect on PGC-1α target genes in CMI3OE and also in AAV9-TnT-PGC-\n1α expressing CMI3OE mice that confirms the relevance of IRF3-PGC-1α nexus for\ncardiomyocyte function but certainly doesnot claim as the only mechanism affecting\nmitochondrial and metabolic genes. In the revised manuscript we show the potential of PGC-1α\nin protecting cardiomyocytes from type I IFN (LPS) and hypoxia driven side effects by\ndownregulating inflammation and mitochondrial damage in cardiomyocytes (Fig S6a-d). Overall,\nthese studies provide mechanistic insight into the bidirectional role of IRF3-PGC-1α axis\nregulating cardiac sterile inflammation and metabolism.\n3. Specificity of CMI3KO mice was only shown in cardiomyocytes (Fig. 2b) versus organs\n2\nnot relevant to the heart (SF2a). Given findings of IRF3 expression within other cell types\nin the heart (SF1b), it would be more beneficial to examine IRF3 expression within ECs,\nFBs, MPs and SMCs of CMI3KO mice to exclude functional contributions.\nWe have utilized αMHC-Cre mouse to generate cardiomyocyte-specific Irf3KO (CMI3KO) that\nresulted in a target allele deletion when crossed to a mouse with a floxed Irf3 transgene. αMHC-\nCre has been previously shown to be cardiac specific with no expression in other tissues (lung,\nliver, skeletal muscle, spleen) (PMID 9202069). To rule out any functional contribution from\nother cell types, in addition to cardiomyocytes we isolated other cell types of the heart (cardiac\nfibroblasts, cardiac endothelial cells and other pooled cardiac cells [after separating\ncardiomyocytes and fibroblasts]) to examine IRF3 expression in adult CMI3KO mice (Fig. S2b).\nWe found no effect on Irf3 levels in these cell types by αMHC-mediated IRF3 deletion.\n4. Relevant to comment #3, as shown in Fig. 2, CMI3KO mice are only partially protected.\nWe agree with the reviewer that despite IRF3 deficiency in cardiomyocytes, basal IRF3 levels in\nother cell types is likely the cause of the partial protection of CMI3KO mice from myocardial\ninfarction induced systolic dysfunction. In the revised manuscript, we have included this info in\nthe text of Fig. 2e-g.\n5. Data shown in SF2f is a bit confusing as it seems to represent IRF3-mediated\ntranscriptional regulation by non-activated (non-pIRF3) IRF3 since no stimuli appears to\nbe included. These data then suggest that pIRF3 may not be the driver and/or\nnot necessary for transcriptional regulation. Is this instead an issue of siRNA specificity? In\naddition, did the authors ever examine cellular localization of IRF3 to confirm activity?\nThis is an important point raised by the reviewer. We show that the siRNA mediated knock\ndown of IRF3 reduces the overall inflammatory gene expression in NRCMs in the absence of a\nstimulus (Fig. S2e,f, h). There are two potential reasons for this effect on inflammatory markers.\nFirst, we and others have noted an elevated and rapid inflammatory response in NRVCM\ncompared to adult cardiomyocytes (PMID 18490660). Second, both siCtrl and siIRF3 is\nintroduced into cardiomyocytes by transfection using Lipofectamine reagent. Our results and\nprevious reports (PMID 9858316) have shown that liposome based reagents and control siRNA\nper se may result in significant but generalized induction of interferons and ISG (interferon\nstimulated genes) compared to un-transfected cells possibly due to cationic lipid composition of\nthe Lipofectamine reagent and the mere presence of a non-specific siRNA (short dsRNA) as a\nDAMP. Thus, the effect seen at basal level due to siIRF3 is against transfection stress of siCtrl\nRNA. Additionally, we have also done siIRF3 KD in presence of LPS and in the revised\nmanuscript we now show that LPS mediated inflammatory response was severely impaired with\nIRF3 KD in primary cardiomyocytes (Fig. S2h). Furthermore, we have tested siIRF3 specificity\nand with the exception of IRF7 no other IRF is modulated by siIRF3 knock-down in primary\ncardiomyocytes in this study (Fig. S2g). It has been known that IRF7 is a transcriptional target of\nIRF3 and IRF3-IRF7 can dimerize under stress conditions where the primary effect is driven by\nIRF3 (PMID 33205822). Thus, siIRF3 effect on IRF7 mRNA level is not surprising. We have\n3\nadded this info in the revised manuscript text on page 9. Cellular localization of IRF3 has been\nasked for by reviewer 2 (point 1) as well. In the revised manuscript we thus performed cell\nfractionation from the isolated cardiomyocytes of CMI3OE mice and show enriched nuclear\nexpression of IRF3-2D in CMI3OE mice compared to Cre controls (Fig. S5b).\n6. Fig. 4i co-immunoprecipitation experiment was done by overexpression. Why not look\nat interaction of endogenous proteins within the model, which would be more\nphysiologic?\nAs per the reviewer’s suggestion to assess the physiological interaction within the model, we\nhave now included an endogenous Co-IP in CMI3OE mouse model (Figure 4j). These results\nindeed confirm that IRF3-2D interacts with PGC-1α.\n7. The mechanism(s) by which IRF3 and PGC1a regulate each other is not entirely clear.\nMoreover, the relevance of the interaction is not clear nor is the data shown in Fig. 4k\nsuggesting that PGC1a somehow regulates IRF3 transcription by overexpression.\nWe thank the reviewer for this comment and agree that how IRF3 regulates PGC-1α gene\nexpression is not completely clear. We had also noted this in the manuscript under “Limitations\nof the study”. Yet, it is worth noting that PGC-1α expression is low in pre- and -neonatal heart\nwhere innate inflammatory response can be paradoxically high. In the revised manuscript, we\nhave shown that PGC-1α expression is sufficient to suppress inflammatory effects alone and\nthis characteristic is maintained even in the presence of extravagant IFN response induced by\nLPS or under hypoxia condition in NRCMs (Fig. 5c, d and Fig. S6a-d). Thus, effect of IRF3 and\nPGC-1α on each other’s levels is highly relevant.\nWe have not been successful with IRF3 ChIP in cardiomyocytes per se and this makes\ndifferentiating direct and indirect effect of IRF3-PGC-1a interaction exceedingly difficult. We\nunderstand that interaction studies using Co-IP apparently speaks of the close proximity of two\nfactors but doesnot provide insight into their function. Due to multiple interacting partners of\nPGC-1α the relationship between IRF3 and PGC-1α is perhaps not a linear pathway but rather\na complex network. However, the below mentioned new findings in the revised manuscript\nprovide further insight into indirect regulation of PGC-1α levels by IRF3 activation and enhances\nour understanding of how IRF3 and PGC-1α may influence each other’s function:\n1) PGC-1α is known to interact with its cognate transcription factors and thereby influence\na broad range of metabolic pathways (FAO and glucose metabolism). Foxo1, Mef2, and\nEsrra, are well-known and important transcriptional targets of Ppargc1a regulating\nmitochondrial function, metabolism and βoxidation (PMID 16511594). We now show that\nIRF3 activation downregulates Esrra, Foxo1 and Mef2 gene expression in the\nmyocardium of CMI3OE mice (Fig. 5h).\n2) Using Luciferase assay we have shown that IRF3 activation impairs PGC-1α activity on\nPPARα reporter. We also found reduced expression of PPARα target genes (Cd36,\nCpt1b, Acox1, Acadm, Acadvl) involved in FA transport and mitochondrial βoxidation\n4\nupon IRF3 activation in CMI3OE (Fig. S6e). Similarly, PGC-1α expression reduced IRF3\ndirect target gene expression in cardiomyocytes as shown in the new Fig. 5c.\n3) Apart from direct transcriptional control, PGC-1α expression can also be regulated by\npanoply of posttranslational modifications such as phosphorylation and O-GlcNAc\nmodification (PMID 31406949, PMID 27646831, PMID 19103600). AMPK, p38MAPK\nand AKT are among the key kinases that are known to regulate PGC-1α levels. We\nfound reduced p-p38MAPK levels in CMI3OE mice along with reduced expression of\nMapk14 (encoding p38MAPK) (Fig. 5i,k). There was no effect on pAMPK levels,\nwhereas both total AKT as well as pAKT was reduced in the myocardium of CMI3OE\nmice. O-GlcNAcylation is another novel pathway to regulate PGC-1α stability. O-GlcNAc\ntransferase (OGT) is the sole enzyme that catalyzes O-GlcNAcylation by transfer of N-\nacetylglucosamine from UDP-N-acetylglucosamine to serine/threonine residues of\ncytosolic and nuclear proteins. Interestingly, we found increased levels of UDP-N-\nacetylglucosamine in CMI3OE mice (Fig. 6e) indicating reduced activity of OGT. While\nincreased OGT levels are detrimental for heart function, reduced OGT levels have also been\nshown to exacerbate heart failure (PMID 20876116). These data together suggest\nmetabolic and transcriptional adaptation upon IRF3 activation in the myocardium.\nOverall, our above mentioned findings suggest that the IRF3 and PGC-1α interaction may divert\nthem from their transcriptional task by direct or indirect interactive pathways.\nOf note, IRF3 has been traditionally studied with inflammatory perspective, on the other hand\nmost of the studies highlight PGC-1α role in mitochondrial function. Here we show bidirectional\neffect of IRF3-PGC-1α expression wherein IRF3 activation downregulates PGC-1α expression\n(now Fig. 5a, earlier Fig. 4j) along with downregulation of mitochondrial oxidative\nphosphorylation marker genes (Fig. S5g, in the revised manuscript) whereas PGC-1α\noverexpression downregulates inflammatory marker gene expression (Fig. 5b, c in the revised\nmanuscript) including IRF3 (Fig. 5b, earlier Fig. 4k). We believe that these studies contributes to\nan improved understanding by extending IRF3 and PGC-1α function beyond their classical\nboundaries and highlight a broader role in cardiac immuno-metabolism.\nReviewer #2 (Remarks to the Author):\nIn this study, Manju Kumari et al. demonstrated that phosphorylation levels of\nSer396/Ser398 in the transcription factor IRF3 are significantly elevated in the left\nventricles of both patients with ischemic cardiomyopathy and mouse models. The\nphosphorylation of IRF3 suppresses the expression of Ppargc1α, resulting in impaired\nmitochondrial oxidative phosphorylation, dysregulated NAD metabolism, and an\nexcessive type I IFN-driven inflammatory response, collectively contributing to the\ndevelopment of heart failure. Notably, in IRF3-2D-overexpressing mice, restoration of\nPpargc1α expression alleviated contractile dysfunction by promoting a metabolic shift\ntoward fatty acid oxidation and attenuating inflammatory fibrotic responses. These\nfindings provide novel insights into the molecular mechanisms underlying heart failure,\nyet several critical questions remain to be addressed.\npositive comments.\n1. The authors' explanation of how IRF3 inhibits PGC-1α function through their\ninteraction is not completely clear. In Fig.4i, the authors described the interaction\nbetween IRF3 and PGC-1α. Actually, the author used IRF3-2D (phosphomimic mutant) to\ninvestigate its interaction with PGC-1ɑ. What are the differences in the interaction\nstrength between PGC-1α and phosphorylated/non-phosphorylated IRF3? Was the\nlocalization of p-IRF3 and PGC-1α examined in cardiomyocytes of Cre and CMI3OE mice\nusing immunofluorescence? Additionally, does p-IRF3 compete with PPAR(or other PGC-\n1α related transcript factors) for binding to PGC-1α ?\nDue to lower endogenous expression level and antibody specificity concerns related to one or\nboth of the interacting factors/proteins, co-immunoprecipitation (Co-IP) assays are often\nperformed with tagged proteins or overexpression system. For these reasons, we had used\nNRCMs overexpressing Flag-tagged PGC-1α and IRF3-2D to show interaction by Co-IP. In the\nrevised manuscript, to investigate the physiological interaction between PGC-1α and IRF3-2D in\nthe model we have used to study cardiac function, we now performed endogenous Co-IP and\nconfirmed the interaction between PGC-1α and IRF3-2D in the ventricular tissue of CMI3OE\nmice compared to healthy Cre controls (Fig. 4j). This also addresses a similar concern of\nreviewer 1 (point 6). Furthermore, we also performed Co-IP assays in NRCMs treated with Poly\nI:C to induce IRF3 phosphorylation and show that PGC-1α interacts with phosphorylated IRF3\nand not wild type IRF3 most likely due to nuclear localization of p-IRF3 (Fig. S5a).\nDue to lack of optimal antibodies for the immunofluorescence (IF) studies in mouse\ncardiomyocytes, we instead performed cell fractionation of isolated adult cardiomyocytes.\nNuclear localization of IRF3-2D and PGC-1α in the cardiomyocytes of CMI3OE mice can clearly\nbe seen with appropriate controls (Fig. S5b). Although IF in mouse samples for IRF3 are not\noptimized yet in our lab (likely due to epitope conformation/accessibility differences), we have\nsuccessfully seen nuclear localization of human IRF3-2D in hiPSC-cardiomyocytes transduced\nwith adenovirus expressing human IRF3-2D compared to LacZ as shown here in Fig. 1Revision.\nDAPI IRF3 αActinin Merge\nZ\nc\na\nL\nD\n2\n3-\nF\nR\nIh\nFig. 1Revision: Immunofluorescence in hiPSC-cardiomyocytes\ntransduced with LacZcontrol or human IRF3-2D adenovirus at\n10 ifufor 48 h showing nuclear localization of human IRF3-2D.\nWe have not been successful with IRF3 ChIP in cardiomyocytes per se and this makes\nidentifying direct effects of IRF3-PGC-1α interaction exceedingly difficult. Nevertheless, using\nPPRE Luc (Fig. 5f, g). In the revised manuscript we furthermore show that IRF3 activation\nresulted in reduced expression of Ppara target genes (Cd36, Acox1, Acadm, Acadvl, Cpt1b)\n(Fig. S5g) and Ppargc1a transcriptional targets (Esrra, Mef2a, and Foxo1) (Fig. 5h).\nFurthermore, apart from direct transcriptional control, PGC-1α expression can also be regulated\nby posttranslational modifications such as phosphorylation and O-GlcNAcylation. In the revised\nmanuscript we show reduced p-p38MAPK and OGT levels in the myocardium of CMI3OE mice\nproviding additional insight into the effect of IRF3-PGC-1α axis within cardiomyocytes (Fig. 5i,j).\n2. The authors should provide the extent of cardiac fibrosis in CMI3OE mice following\ntamoxifen treatment. If severe fibrosis has already developed in the heart, its cellular\ncomposition would significantly differ from that of a normal heart. Therefore, it is\nimportant to determine whether the observed metabolic differences may be caused by\nchanges in cellular composition.\nWe thank the reviewer for raising this important point. We have now included Masson’s\nTrichrome stained ventricular IHC images of CMI3OE mice in the revised manuscript (Fig. S4e).\nWe could not detect increased fibrosis by IHC indicating obvious structural changes with severe\nfibrosis have not developed. However, at mRNA level, the expression of fibrotic markers are\nsignificantly elevated upon IRF3 activation in CMI3OE mice (Fig. 4b) and can also be seen with\nαSMA protein levels included in the new Fig. S4f. CMI3OE were treated with low dose\nTamoxifen by gavage and the cardiac tissue was analyzed on 5th day after the start of the\ntreatment. While severe fibrosis is not set in during this period, we believe that IRF3 activation\ndoes provoke pro-fibrotic signaling with potential to change cellular metabolism and cellular\ncomposition. Our laboratory is actively investigating the crucial role of IRF3 in modulating\ncardiomyocyte microenvironment which is part of a follow up manuscript-in-preparation. We\nhave addressed this in the revised manuscript Results section (para 1, page 12) where we\nwrote “Despite significantly elevated expression of fibrotic markers, structural changes indicative\nof fibrosis were not observed suggesting an early phase of cellular adaptation in CMI3OE mice\n(Fig. S4e, S4f)”.\n3. PGC1-ɑ plays a role in promoting mitochondrial biogenesis. Therefore, it is necessary\nto compare mitochondrial mass and quantity between the Cre group and the CMI3OE\ngroup to determine whether the observed metabolic changes are caused by alterations in\nmitochondrial function or changes in mitochondrial quantity.\nIn the revised manuscript we have quantified mitochondrial DNA copy number by determining\nthe mitochondrial DNA/nuclear DNA ratio in ventricular tissue of CMI3OE mice compared to Cre\ncontrols to assess an effect on mitochondrial DNA content/mass (Fig. 4g). These results show\nthat indeed mitochondrial function and not the quantity is altered in the heart of CMI3OE mice.\n4. An increase in 3OHB alone cannot definitively indicate increased ketogenesis\nmetabolism, as it could also be explained by reduced BOH1 and NAD+ levels leading to\n7\nits accumulation. Additionally, it is necessary to analyze the fumarate-to-succinate ratio\nto assess the status of succinate oxidation, rather than relying solely on a decrease in\nfumarate.\nWe agree and thank the reviewer for highlighting the importance of fumarate to succinate ratio\nthat is an indicator of SDH activity and succinate oxidation in TCA cycle. We have analyzed and\nincluded the fumarate-succinate ratio to the access succinate oxidation in the revised\nmanuscript (Fig. 6k). The analysis showed reduced succinate oxidation in the myocardium of\nCMI3OE mice.\n5. Although the authors observed increased glucose uptake using Deoxy-D-glucose, it\ncan be seen from Fig.S5c that both fructose-1,6-bisphosphate and phosphoenolpyruvate\nsignificantly decrease in glycolysis. This suggests that glycolysis may not actually be\nincreased in CMI3OE group. The increased glucose may also be utilized through the\npentose phosphate pathway to generate reducing power to counteract ROS. It may not\nnecessarily be that energy metabolism shifted from FA oxidation to glycolysis in CMI3OE\ngroup (Fig.5o). Therefore, further analysis of metabolites in the PPP pathway is needed,\nas well as an examination of whether the transcriptomics of the glycolytic pathway\nreveals changes in the expression of glycolytic enzymes. It is especially important to use\nU-13C-glucose in vivo isotope labeling to analyze changes in the glycolysis-TCA cycle\nmetabolic flux.\nWe sincerely thank the reviewer for this detailed observation and thoughtful comment. This\nprompted us to perform stable isotope labeling assays and we could identify a unique capacity\nof cardiomyocyte to adapt towards PPP for fuel utilization upon IRF3 activation. Cardiac injury is\nfollowed by swift metabolic adaptations creating a complex interplay between cellular glycolysis,\nTCA cycle, and PPP wherein the flow of each pathway is indeed context dependent. In our\nlipidomic study, the metabolic changes in the ventricular tissue reflect the static metabolic state\nbut may not represent the cardiomyocyte intrinsic effects driven by IRF3 activation. Stable\nisotope labelling represents the true metabolic flux status, thus, we investigated metabolic flux in\nglycolysis, TCA cycle and PPP in adult cardiomyocytes isolated from Cre controls and CMI3OE\nmice utilizing U-13C -Glucose. Our studies in CMI3OE mice highlight the previously unknown\n6\npotential of the cardiomyocyte’s response towards sterile inflammation. Strikingly, we found an\nincrease in Sedoheptulose-7-phosphate (at 120 min) which represents increased flux in PPP in\ncardiomyocytes with IRF3 activation (Fig. 7f). Additionally, we found decreased flux in TCA\ncycle in cardiomyocytes (Fig. 7g-j, Fig. S9f) at 120 min. These metabolic changes were also\ncaptured in the transcriptomics analysis and we show that expression of genes regulating upper\nglycolysis, TCA cycle and PPP pathway were altered in the same pattern in CMI3OE mice (Fig.\n6l,m; Fig.7k). While increase in glucose uptake, increased UDP-Glucosamine and increased\nexpression of Hk1 and Gpi1 primarily indicated a transient increase in upper glycolysis pathway,\nthere was no major effect on glycolysis flux at 10 min (Fig. 7b-e, Fig. S9a-e).\nWe have also modified the Fig. 5o (now Fig. 7k) and updated the text in the manuscript Results\nsection to accommodate these new findings. Taken together, alterations in the metabolic flux in\nautonomous effect of IRF3 activation more precisely in maintaining metabolic homeostasis.\nReviewer #3 (Remarks to the Author):\nThis is an interesting manuscript that presents new evidence for an axis between\nIRF3/PGC-1α in promoting ischemic cardiomyopathy. The work uses state of the art\napproaches and rigorous data analysis. These efforts make a strong case that IRF-3\nactivation contributes to cardiomyopathy and that PGC-1α overexpression is protective.\nHowever, several major questions remain unresolved and should be addressed to\nunderstand the mechanisms underlying the proposed axis and maximize the value of\nthese findings to the field.\nWe thank the reviewer for appreciating our work and providing thoughtful comments.\nSpecific points\n1. Could repair of energetics in cardiomyocytes, independent of IFN response signaling,\nbe sufficient to protect against cardiomyopathy? Is PGC-1α over expression protection\ndue to metabolic repair exclusively (i.e. where inflammatory signals are not important) or\na combination of metabolic and inflammatory repair? These studies make a convincing\ncase for a connection between excessive IRF-3 activation, type I IFN response and fuel\nswitch/defective energetics in cardiomyocytes. However, it is not clear how much of the\ncardiomyopathy phenotype is caused by defective energetics versus the type I IFN\nresponse. The role of inflammation in contributing to cardiomyopathy in the context of\nmyocytes is not proven in these studies; the current studies do show augmentation of\nIFN response in response to injury in cardiomyocytes but stop short of proving the IFN\nresponse drives cardiomyopathy. The current studies do not measure or distinguish the\nindividual contributions nor make a convincing case that the IFN response alone is\nimportant in these models, despite the schematic that suggests both arms are essential.\nWe agree with the reviewer’s comment that the individual contribution of IFN response vs\nmaladaptive cardiac metabolism is not segregated in CMI3OE model. Earlier studies from King\net al (PMID 29106401) and Ninh et al (PMID 39198639) have proven the role of IRF3 driven\ninflammation in myocardial infarction. Findings from these studies support the conclusion that\nIRF3 driven IFN signaling has the potential to drive cardiomyopathy. However, these studies\nfocused on the role of IRF3 upregulation in myeloid cells towards cardiac inflammation or\nidentification of IFN induced cells in myocardial infarction model and did not address a role for\nIRF3 on cardiac metabolism or cardiomyocytes in those inflamed hearts. Our data in CMI3OE,\nCMI3KO and cell-autonomous studies in primary cardiomyocytes indeed suggests a\nbidirectional role of IRF3 and PGC-1α in regulating inflammation and cardiac metabolism which\nin our view is novel and fascinating. However, this bidirectional effect apparently comes with a\nchallenge to deconvolute the contribution of their respective functions. Our stable isotope\n9\nlabeling studies highlights that swift metabolic adaptations occur in the presence of IRF3\nmediated sterile inflammation and are essential to track earlier changes leading to an energy\ndeficit. PGC-1α expression partially rescued cardiac dysfunction by reducing cardiac\ninflammation and increasing FA oxidation pathways. IRF3-PGC-1α axis is indeed one of the\nmechanisms but certainly doesnot claim as the only mechanism affecting mitochondrial and\nmetabolic genes. Overall “limited studies including ours highlight the importance of inflammation\nand cardiac energy deficit working in parallel. However, the kinetics of inflammation and\nmetabolic changes may not be parallel in each context (PMID 37086246) and with lack of this\nknowledge an attempt to prioritize one or the other pathway may lead to a causality dilemma”.\nTo emphasize this fundamental aspect we have included this text in the last paragraph of the\nrevised manuscript (page 25).\n2. Separating the IFN from metabolic responses to injury/IRF3 activation is important,\nparticularly given the introductory narrative making the point that inflammation plays\ncontext and time dependent beneficial and detrimental roles. Perhaps this critical\nconfusion can be resolved by a focus on energetics alone: can preservation of Ox-phos\nsustain injury resistance despite an augmented IFN response? It seems like this may be\nthe case because Ppargc1a overexpression is protective against genetically augmented\nIRF-3 activity.\nBecause the beneficial or detrimental outcome of inflammation is both context and time\ndependent, our data showing that PGC-1α expression rescues cardiac systolic dysfunction in\nCMI3OE mice indeed emphasizes that the prompt control of oxidative metabolic homeostasis at\nthe onset of inflammation occurring during the early phase of cardiac injury appears beneficial.\nBoth extreme upregulation and downregulation of PGC-1α has been associated with heart\nfailure (PMID 31412728). To note, we have shown that apart from improved OXPHOS levels,\nmoderate PGC-1α expression also reduced overall cardiac inflammation in CMI3OE (Fig. 9b).\nWe believe that reduced inflammation due to PGC-1α (Fig. 9b, Fig. 5c) plays a critical role in\nimproving cardiac function apart from the effect on energetics alone. Taken together, our results\nsuggest that both restored OXPHOS and attenuated but not diminished cardiac inflammation\nare required to maintain cardiac function. Furthermore, in response to this comment as well as\nthe next (see below), our findings from cardiomyocytes expressing PGC-1α highlight that the\nanti-inflammatory properties of PGC-1α are indeed maintained in the presence of type I IFN\n(LPS) stimuli in vitro (Fig. S6a, b). However, despite amelioration of acute cardiac dysfunction,\nthe long term effect of persistent inflammation and the role of improving oxidative function in\ncardiac muscle remains unknown. This is being actively pursued in our lab using other HF\nmodels due to limited survival of CMI3OE model.\n3. Is Ppargc1a over expression sufficient to protect NRCMs from inflammatory (LPS) or\nischemic injury responses?\nWe sincerely thank the reviewer for prompting us to perform this interesting experiment. Indeed\nPpargc1α expression in NRVCM protects the cells from LPS induced inflammatory response\n10\n(Fig. S6a-d). PGC-1α expression also led to increased expression of mitochondrial marker\ngenes in a hypoxia model. These results also suggest that Ppargc1α exerts stronger effect in an\ninflammation inducing model. Overall, this again confirmed the bidirectional role of PGC-1α in\nimproving mitochondrial function as well as reducing IFN signaling in cardiomyocytes.\n4. Does IRF-3 binding to PGC-1α sequester PGC-1α and IRF-3 from their transcriptional\ntasks or are there other mechanisms at play for the apparently reciprocal transcriptional\nresponses? How does the IRF-3/PCG-1a axis in cardiomyocytes work?\nIn the revised manuscript we provide further mechanistic insight into the reciprocal regulation of\nIRF3-PGC-1α levels in cardiomyocytes as a similar comment has been raised by another\nreviewer. We show activated IRF3 (IRF3-2D/pIRF3) and PGC-1α interaction by native co-\nimmunoprecipitation assay (Fig. 4j). PGC-1α doesnot directly bind to DNA but influence other\ntranscription factor’s activity. In neonatal heart, innate inflammatory response is paradoxically\nhigh whereas PGC-1α expression is low. On the other hand, PGC-1a expression increases in\nadult heart along with the establishment of adaptive immune response and oxidative\nmetabolism. Thus, the effect of IRF3 and PGC-1α on each other inflammatory and metabolic\nroles in cardiomyocytes is highly relevant.\nPGC-1α has multiple transcriptional targets in different tissues. We found reduced expression of\nEsrra, Mef2 and Foxo1 in the myocardium of CMI3OE indicating reduced PGC-1α\ntranscriptional activity (Fig. 5h). Similarly, Ifits (Ifit1, Ifit2 and Ifit3) and Rsad2 are recognized as\nIRF3 targets and PGC-1α expression reduced their expression in cardiomyocytes (Fig. 5c).\nPGC-1α levels and activity can also controlled by various post-translational regulations such as\nphosphorylation and O-GlcNAcylation. We now show that p-P38MAPK and OGT (O-linked N-\nacetylglucosamine transferase) levels that are known to regulate PGC-1α levels by\nphosphorylation and O-GlcNAcylation were downregulated at mRNA and protein level in the\nmyocardium of CMI3OE mice (Fig. 5i,k). pAMPK and pAKT also plays an important role in PGC-\n1α regulation. However, there was no effect on pAMPKα levels, whereas both total AKT as well\nas pAKT was reduced in the myocardium of CMI3OE mice indicating a tissue specific effect of\nIRF3 activation. OGT is the sole enzyme that catalyzes O-GlcNAcylation by transfer of N-\nacetylglucosamine from UDP-N-acetylglucosamine to serine/threonine residues of cytosolic and\nnuclear proteins. This O-GlcNAcylation is strictly dependent on the UDP-N-acetylglucosamine\nlevel which is a substrate for OGT activity. Interestingly, we found increased levels of UDP-N-\nacetylglucosamine in CMI3OE mice (Fig. 6e) indicating reduced activity of OGT. While\nincreased OGT levels are detrimental for heart function, reduced OGT levels have also been\nshown to exacerbate heart failure (PMID 20876116). Taken together, these results identify a\ncontext specific role of IRF3 activation in the myocardium.\n5. Do the current findings exclude a role of myeloid cells in the INF-3-PGC-1-metabolism\npathway? Why or why not?\nBecause IRF3 upregulation has been noted in the myeloid cells upon ischemic injury (PMID\n29106401) and PGC-1α has been shown to influence macrophage polarization towards M2\n11\nstate (PMID 32215168), our findings do not exclude a role of myeloid cells per se in IRF3-PGC-\n1α metabolic regulation. In addition, IRF3 activation in cardiomyocytes altered circulating\nchemokine levels (Fig. 3h), thus, we are aware that paracrine effects likely can also alter the\nfunction of other cell-types including myeloid cells and overall modulate cardiac metabolism. In\nthis regard, we had included a text in the Limitations of this study stating “Importantly, increased\nchemokine signaling suggests further research required to unveil the potential of IRF3 to\nmodulate autocrine or paracrine processes regulating cardiac function”.\nOf note, in the revised manuscript, our data from the metabolic flux assay using U-13C -Glucose\n6\nin isolated cardiomyocytes from CMI3OE and Cre control mice shows that IRF3 activation\nincreased flux into PPP along with a reduced flux in TCA cycle. These findings from metabolic\nflux assays in adult cardiomyocytes and cardiomyocyte-specific IRF3 activation model highlights\nthat cardiomyocytes possess the potential to initiate type I IFN inflammatory response and\ninfluence cardiac metabolism to a greater extent than previously anticipated. However, these\nstudies do not exclude contribution of other cell types within myocardium towards immuno-\nmetabolism.\n6. What kinases/phosphatases are necessary for setting the balance of IRF3\nphosphorylation?\nThe kinases and phosphatases necessary for maintaining pIRF3/IRF3 balance have been\nmostly studied in immune cells. We have included this info in the discussion of the revised\nmanuscript (page 21) stating that “IKKε and TANK-binding-kinase 1 (TBK1) are the two major\nphosphorylation kinases of IRF3 (PMID 39384770), whereas IRF3 can be deactivated by\ndephosphorylation mediated by serine threonine phosphatase PP2A and its adaptor protein\nRACK1 (PMID 24726876).\n12"}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have done a nice job of addressing the majority of this Reviewers' comments. However, there remains concern (that was brought up by two of the Reviewers) over whether pIRF3 corresponds to nuclear/functional IRF3 in the physiologic model. The authors included a Figure 1Revision image within the Response Letter that is not compelling as the majority of hIRF3-2D is cytoplasmic and the comparative control should be overexpressed wild-type unphosphorylated IRF3 rather than just showing minimal IRF3 expression. This image is not shown in the revised manuscript. In efforts to further address the concern, the authors performed cellular fractionation and provided a new Fig. S5b showing cytoplasmic, membrane and nuclear expression of (p)IRF3 in CMI3OE cardiomyocytes. Indeed, they show 'more' constitutive pIRF3 in both the cytoplasm and nucleus of these cells as compared to Cre mice; however, this may simply be due to overexpression of pIRF3 than a response of IRF3 to ischemic cardiomyopathy. It seems more relevant to examine IRF3 cellular localization in LAD mice (Fig. 1f). It is also concerning in this blot (new Fig. S5b) that there appears to be no 'strong' affect on PGC-1a expression. This is different than what is shown in Fig. 5i, whereby elevated IRF3 in CMI3OE mice corresponds to decreased PGC-1a expression. These apparent differences in the same cells need to be explained. Densitometry analysis could help.\nLast, it would be helpful to include molecular weight markers on all uncut blots as locations for individual proteins on the blots change quite dramatically between blots, particularly for IRF3/pIRF3.", "reviewer_2": "The authors have addressed all my concerns and made the corresponding revisions. There are only the following minor issues remaining:\n1. Figure 7a: The labeling pattern for Sedoheptulose-7-phosphate (S7P) requires correction.\n2. Figure S9g: The acetyl-CoA labeling should be verified, as species above M+2 should not be present."}, "author_response": "RESPONSE TO REVIEWERS\nWe are again thankful to all the reviewers for their thoughtful comments. We believe that in the\nrevised manuscript we have now addressed all the remaining concerns from the reviewers by\nperforming required experiments or additional analyses. The reviewer comments are marked\nbelow in bold and our response in plain text.\nReviewer #1 (Remarks to the Author):\nThe authors have done a nice job of addressing the majority of this Reviewers'\ncomments. However, there remains concern (that was brought up by two of the\nReviewers) over whether pIRF3 corresponds to nuclear/functional IRF3 in the physiologic\nmodel. The authors included a Figure 1Revision image within the Response Letter that is\nnot compelling as the majority of hIRF3-2D is cytoplasmic and the comparative control\nshould be overexpressed wild-type unphosphorylated IRF3 rather than just showing\nminimal IRF3 expression. This image is not shown in the revised manuscript. In efforts to\nfurther address the concern, the authors performed cellular fractionation and provided a\nnew Fig. S5b showing cytoplasmic, membrane and nuclear expression of (p)IRF3 in\nCMI3OE cardiomyocytes. Indeed, they show 'more' constitutive pIRF3 in both the\ncytoplasm and nucleus of these cells as compared to Cre mice; however, this may\nsimply be due to overexpression of pIRF3 than a response of IRF3 to ischemic\ncardiomyopathy. It seems more relevant to examine IRF3 cellular localization in LAD\nmice (Fig. 1f). It is also concerning in this blot (new Fig. S5b) that there appears to be no\n'strong' affect on PGC-1a expression. This is different than what is shown in Fig. 5i,\nwhereby elevated IRF3 in CMI3OE mice corresponds to decreased PGC-1a expression.\nThese apparent differences in the same cells need to be explained. Densitometry\nanalysis could help.\nLast, it would be helpful to include molecular weight markers on all uncut blots as\nlocations for individual proteins on the blots change quite dramatically between blots,\nparticularly for IRF3/pIRF3.\nWe thank the reviewer for appreciating our work done to address the concerns raised. We\nagree with the reviewer that indeed the nuclear expression of IRF3 might be influenced by high\nexpression in the transgenic CMI3OE model. In order to determine IRF3 activation by\nphosphorylation in a physiological model, we isolated adult cardiomyocytes from mice subjected\nto LAD-induced myocardial infarction and sham controls. Cell fractionation of these\ncardiomyocytes showed robust increase in nuclear pIRF3 levels in ischemic mice compared to\nsham controls (Fig. S1c). We have now added the following text on page 7 of the revised\nmanuscript to include this finding, “Furthermore, immunoblot analysis showed higher levels of\nphosphorylated IRF3 in the nuclear fraction of cardiomyocytes isolated from mice with\nmyocardial infarction suggesting physiological activation of endogenous IRF3 (Fig. S1c)”.\nOf note, in vitro experiments in this manuscript are carried out in cardiomyocytes isolated from\nneonatal rats or adult mouse heart. Thus, immunofluorescence images from hiPS-\ncardiomyocytes were not included in the manuscript but shown as a response to the reviewer in\nthe previous revision. Meanwhile, we have taken multiple efforts to optimize the\nimmunofluorescence (IF) in neonatal rat cardiomyocytes since the last revision. In the revised\nmanuscript, we show that wild type IRF3 resides predominantly in the cytoplasm whereas IRF3-\n2D showed higher nuclear abundance compared to LacZ and wild-type IRF3 (Fig. S5f). We also\nadded the following text on page 13, “Second, expression of IRF3-2D in isolated\ncardiomyocytes showed enhanced nuclear abundance (Fig. S5d-S5f)”. We appreciate the\nreviewer’s feedback and do acknowledge observing IRF3-2D expression as a halo around\nnucleus in cultured cardiomyocytes, in both neonatal rat cardiomyocytes as well as hiPS-\ncardiomyocytes. We believe that there can be multiple reasons for this observation in IF images\nsuch as: a) technical limitations of the antibody permeability to nucleus, or b) interplay between\nphosphatases vs kinases in regulating IRF3 levels in the cytosol in response to IRF3 activation\nto maintain cellular homeostasis (PMID 24726876, PMID 39384770), or c) binding to unknown\nnuclear envelop proteins/associated organelles upon IRF3-2D expression, or d) requirement of\nfurther optimization of blocking, permeability and antibody dilution conditions.\nTo address the next concern, we performed densitometry analysis and quantified PGC-1α\nexpression in the cell fractions of adult cardiomyocytes isolated from CMI3OE mice and\nnormalized to the respective loading controls of cell fractions. In the revised manuscript, Figure\nS5c shows significant downregulation of ~30% for PGC-1α level in cardiomyocytes of CMI3OE\nmice. We agree that this downregulation is lower than the Figure 5i (probably due to cell-\nfractionation processing), nevertheless PGC-1α downregulation remains significant in multiple\ncohorts we have studied.\nFinally, we ofcourse agree with the reviewer’s suggestion and have added molecular weight to\nall the original uncut blots.\nReviewer #2 (Remarks to the Author):\nThe authors have addressed all my concerns and made the corresponding revisions.\nThere are only the following minor issues remaining:\n1. Figure 7a: The labeling pattern for Sedoheptulose-7-phosphate (S7P) requires\ncorrection.\n2. Figure S9g: The acetyl-CoA labeling should be verified, as species above M+2 should\nnot be present.\nWe thank the reviewer for these careful observations. We have corrected the isotope labeling of\nSedoheptulose7P in Fig 7a.\nFor the acetyl-CoA labeling in Fig. S9g, the isotopologues starting from M+3 to M+23 were\nexcluded, as they do not get any label from glucose.\nReviewer #3 (Remarks to the Author):\ncongratulations\nThank you!"}, {"round": 3, "reviewer_comments": {"reviewer_1": "The authors have provided additional data in support of their conclusions."}, "author_response": ""}]

Decision letter