Next Article in Journal
A Practical and Analytical Comparative Study of Gel-Based Top-Down and Gel-Free Bottom-Up Proteomics Including Unbiased Proteoform Detection
Next Article in Special Issue
Proteomic Analysis in Valvular Cardiomyopathy: Aortic Regurgitation vs. Aortic Stenosis
Previous Article in Journal
Depletion of Paraoxonase 1 (Pon1) Dysregulates mTOR, Autophagy, and Accelerates Amyloid Beta Accumulation in Mice
Previous Article in Special Issue
Human Health during Space Travel: State-of-the-Art Review
 
 
Comment published on 31 August 2023, see Cells 2023, 12(17), 2186.
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Spectrin-Based Regulation of Cardiac Fibroblast Cell-Cell Communication

1
The Frick Center for Heart Failure and Arrhythmia, Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University Medical Center, Columbus, OH 43210, USA
2
Department of Biomedical Engineering, The Ohio State University, Columbus, OH 43210, USA
3
Department of Internal Medicine, Division of Pulmonary, Critical Care & Sleep Medicine, The Ohio State University, Columbus, OH 43210, USA
4
Department of Internal Medicine, Division of Cardiovascular Medicine, The Ohio State University, Columbus, OH 43210, USA
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Cells 2023, 12(5), 748; https://doi.org/10.3390/cells12050748
Submission received: 4 November 2022 / Revised: 14 February 2023 / Accepted: 24 February 2023 / Published: 26 February 2023
(This article belongs to the Special Issue Research Advances Related to Cardiovascular System)

Abstract

:
Cardiac fibroblasts (CFs) maintain the fibrous extracellular matrix (ECM) that supports proper cardiac function. Cardiac injury induces a transition in the activity of CFs to promote cardiac fibrosis. CFs play a critical role in sensing local injury signals and coordinating the organ level response through paracrine communication to distal cells. However, the mechanisms by which CFs engage cell-cell communication networks in response to stress remain unknown. We tested a role for the action-associated cytoskeletal protein βIV-spectrin in regulating CF paracrine signaling. Conditioned culture media (CCM) was collected from WT and βIV-spectrin deficient (qv4J) CFs. WT CFs treated with qv4J CCM showed increased proliferation and collagen gel compaction compared to control. Consistent with the functional measurements, qv4J CCM contained higher levels of pro-inflammatory and pro-fibrotic cytokines and increased concentration of small extracellular vesicles (30–150 nm diameter, exosomes). Treatment of WT CFs with exosomes isolated from qv4J CCM induced a similar phenotypic change as that observed with complete CCM. Treatment of qv4J CFs with an inhibitor of the βIV-spectrin-associated transcription factor, STAT3, decreased the levels of both cytokines and exosomes in conditioned media. This study expands the role of the βIV-spectrin/STAT3 complex in stress-induced regulation of CF paracrine signaling.

1. Introduction

Cardiac mechanical function depends on the coordinated activity of cardiac myocytes organized in interconnected muscle fibers and supported by a fibrous extracellular matrix (ECM) maintained by resident cardiac fibroblasts (CFs) [1,2,3]. Under physiological conditions, CFs typically reside in a quiescent (non-activated) state; however, cardiac stress or injury induces a dramatic transition in CF phenotype, characterized by increased proliferation, contractility and excessive ECM production leading to cardiac fibrosis [4,5,6,7]. While cardiac fibrosis is critical for repairing damaged myocardial tissue, dysregulation of the process in disease contributes to cardiac mechanical and electrical dysfunction [3,8,9].
CFs have the remarkable ability to sense local injury signals and communicate distress in a paracrine manner to distal cells, including other CFs, myocytes, immune cells, and endothelial cells [10,11]. Mounting data indicate that CFs engage in a cell-cell communication network following cardiac injury that depends, at least in part, on small (30–150 nm) extracellular vesicles (exosomes) capable of delivering proteins, lipids, mRNA and other bioactive cargo within the heart or even to other organs [12,13,14,15,16,17]. However, the mechanisms responsible for tuning CF exosome-dependent communication networks in response to chronic stress remain unclear. Mechanistic insight into the biogenesis of exosomes and their evolution with disease presents great promise for not only improving existing treatments but expanding therapeutic approaches.
Spectrin family members are actin-associated cytoskeletal proteins that support cellular architecture and membrane stability in metazoan cells [18,19,20]. Beyond mechanical support for the membrane, spectrins facilitate intracellular signaling through the formation of macromolecular complexes involving ion channels, regulatory, adapter molecules, and transcription factors. The βIV-spectrin isoform, in particular, has been shown to act as a dynamic scaffold that organizes local signaling domains for regulation of signal transduction events in a variety of cell types, including CFs. Recently, we discovered a novel role for βIV-spectrin in regulating the subcellular localization and activity of the pleiotropic transcription factor signal transducer and activator of transcription 3 (STAT3) [21]. Further, we found that disruption of βIV-spectrin (in response to chronic stress) promotes STAT3 subcellular redistribution and aberrant activity to alter CF gene expression, proliferation, and contractility [22,23]. At the organ level, βIV-spectrin deficiency results in enhance maladaptive remodeling, fibrosis, and cardiac dysfunction, consistent with the CF phenotype [21,22].
Here, we demonstrate that beyond controlling the local activity of individual CFs, βIV-spectrin supports a long-range communication network between CFs and other cardiac cells. Using a genetic mouse model of βIV-spectrin deficiency (qv4J mouse), we demonstrate that loss of βIV-spectrin triggers the release of paracrine stress signals from CFs in a STAT3-dependent manner with the capacity to alter the behavior of recipient quiescent CFs. Interestingly, we show that βIV-spectrin-deficient CFs secrete higher concentrations of both inflammatory paracrine protein factors as well as bioactive exosomes, when compared to quiescent WT CFs. Our work identifies a novel role of the spectrin-based pathway in facilitating long-range communication responsible for impacting healthy cardiac function.

2. Materials and Methods

2.1. Experimental Animals

Adult (2–4 mos, 18–22 g) male and female C57BL/6J wildtype (WT, control) and βIV-spectrin truncated (qv4J) littermate mice were used (see Table 1 for complete list of abbreviations). qv4J animals genetically express a Spnb4 allele with a spontaneous insertion point mutation at C4234T (Q1358 > Stop) resulting in a premature stop codon in βIV-spectrin repeat 10 leading to the lack of repeats 11 through the C-terminus including the putative STAT3 binding region [22,24,25]. qv4J animals were acquired from Jackson Laboratory. All procedures were conducted in accordance with the Guide for the Care and Use of Laboratory Animals published by the National Institutes of Health following protocols approved by the IACUC at The Ohio State University. Animals were euthanized using isoflurane and cervical dislocation followed by collection of tissue or cell isolation.

2.2. Isolation of Primary Mouse Cardiac Fibroblasts

Primary mouse CFs were isolated from left and right ventricles under sterile conditions, as described [22,26]. Briefly, ventricular tissue was minced in 2 mg/mL collagenase (Worthington Biochemical, Lakewood, NJ, USA) dissolved in 1× Ham’s F-10 buffer (Corning) at 37 °C. After digestion, the cell extract was filtered and centrifuged. After discarding the supernatant, cells were resuspended in normal feeding media containing 1× DMEM supplemented with 10% FBS, 1% l-glutamine, and 1% Pen/Strep. Cells were plated onto tissue culture treated plates for 4–5 h to allow for adhering. Culture media containing nonadherent cells (e.g., myocytes, endothelial cells) was then removed from culture and discarded. Fresh feeding media was replenished for adhered to CFs. Cells were grown in culture to the desired confluency. All experiments were performed at passage one (P1) conditions [22].

2.3. Conditioned Culture Media Collection

After CFs reached ~50–60% confluency, cells were washed with PBS and cultured with exosome depleted FBS (ThermoFisher Scientific, Waltham, MA, USA, Catalog #: A2720803) in DMEM medium with 1% l-glutamine and 1% Pen/Strep for 24 h. CF conditioned culture media (CCM) was collected and centrifuged to remove dead cells/debris. For experiments testing the differences in molecular weight fractions, conditioned media underwent a differential ultracentrifugation process to separate large (includes exosomes) and small (includes proteins and peptides) MW fractions, as described with slight modifications [27,28]. Briefly, CCM was filtered through a 100,000 MW Amicon ultra centrifugal filter unit (Millipore Sigma, Burlington, MA, USA) and centrifuged at 10,000× g for 30 min at 4 °C. The flow through was collected as the small MW fraction, while the captured material was resuspended in equal volumes of fresh CCM as the large MW fraction.

2.4. CF Proliferation Assay

Separate isolations of WT CFs were seeded into 12-well culture-treated plates, as described [23]. Briefly, cells were adhered for 24 h with serum starvation. The next day medium was replaced with either the complete CCM, small MW media, or large MW media. Cells were trypsinized at 24, 48, and 72 h postplating. Cell pellets were resuspended in a fixed volume and manually counted using a hemacytometer to calculate total cell numbers. Manual counting was performed blindly by the same person throughout the study to maintain accuracy and reproducibility.

2.5. Collagen Gel Formation and Macroscopic Gel Contraction Measurements

Type I rat- collagen gels (2 mg/mL) were prepared by mixing 10× PBS, sterile H2O, acidic rat tail collagen, and 1 M NaOH. Cells were added (200,000 cells/mL) and mixed before gelation. Cell-collagen mixtures were cast into 24 well culture plates and incubated at 37 °C in 5% CO2 for 1 h. After casting, gels were covered with 1 mL of culture feeding media and released from bottom of wells. Photographs of gels following 24 h of incubation were analyzed using NIH ImageJ software (v. 1.53), as described [22]. Experiments were conducted in technical triplicates.

2.6. Cytokine/Chemokine Analysis

CCM supernatant from WT and qv4J CFs was used to examine levels of cytokines/chemokines using Proteome Profiler Mouse XL array kit (R&D Systems, Minneapolis, MN, USA, Catalog #: ARY028) according to manufacturer’s protocol. Briefly, CFs were cultured in normal feeding media until 70–80% confluency was reached. Cells were then serum starved for 24 h. CCM was collected and centrifuged at 2000 rpm for 5 min to remove dead cells/debris. Supernatant was stored at −80 °C until samples were processed and analyzed. Manual cell counts were performed on a subset of experiments at the time of CCM collection. Cytokine/chemokine levels were normalized to a control CC motif chemokine ligand 3 (CCL3).

2.7. Characterization and Isolation of Extracellular Vesicles

Isolated CFs from WT and qv4J mice were grown in culture to ~50–60% confluency (4–5 d after plating). For experiments testing the effects of STAT3 inhibition, a subset of qv4J CFs were treated for 48 h with S3I-201 (100 µM) [21,22]. Cells were subsequently washed with PBS and cultured with exosome depleted FBS in DMEM medium for 24 h. CCM was collected and centrifuged at 2000× g for 30 min to remove any cells or debris. Manual cell counts were performed on a subset of experiments at the time of CCM collection. The supernatant was treated with Total Exosome Isolation reagent, according to the manufacturer’s protocol (0.5× volume of the media, Fisher: 4478359) and incubated overnight at 4 °C. After incubation, the media was centrifuged at 10,000× g for 1 h at 4 °C. The supernatant was discarded and the pellet containing the EVs was resuspended in PBS and stored at −80 °C until analysis. EV suspensions were then analyzed for size and count using an NS300 nanoparticle tracking analysis system.

2.8. Statistics

Statistical analyses were performed with SigmaPlot 14.5. Data distribution for all comparisons was first tested for normality and equal variance using the Shapiro-Wilk test and Brown-Forsythe test, respectively. For single comparisons, an unpaired two-tailed t-test (data presented as mean ± SEM) or Mann-Whitney U rank-sum test (data presented as the median with 25th and 75th percentiles [box] and 10th and 90th percentiles [whiskers]) was performed to determine p values. For multiple comparisons, a two-way ANOVA with Holm-Sidak post hoc test was used. p < 0.05 was determined significant.

3. Results

3.1. βIV-Spectrin Deficiency Alters Cell-Cell Communication in Cardiac Fibroblasts

To test the hypothesis that βIV-spectrin regulates a cell-cell communication network, CFs isolated from adult WT hearts were treated with conditioned culture media (CCM) from CFs isolated from WT (control) or spectrin-deficient hearts (qv4J mice expressing truncated βIV-spectrin). A significant increase in proliferation was observed in WT CFs treated with qv4J CCM at 48 and 72 h compared to those treated with WT CCM (Figure 1), indicating that spectrin-deficient cells generate paracrine signals capable of altering the phenotype of distal cells.
As a first step in identifying βIV-spectrin-dependent paracrine signals, WT and qv4J CF CCM was separated into small and large molecular weight (MW) fractions, with the large MW fraction consisting of exosomes and other extracellular vesicles and the small MW component containing soluble proteins and signaling molecules. Interestingly, both fractions from qv4J CCM significantly increased proliferation of WT CFs at 48 and 72 h of treatment relative to WT controls, suggesting that βIV-spectrin modulates multiple targets relevant for cell-cell communication (Figure 2).

3.2. βIV-Spectrin Deficiency Alters Secretion of Pro-Inflammatory and Pro-Fibrotic Cytokines/Chemokines from Cardiac Fibroblasts

To identify specific paracrine factors secreted by βIV-spectrin-deficient CFs to alter the behavior of distal cells, a proteome profiler array assay was used to screen 111 cytokines/chemokines in CCM from WT and qv4J CFs. Increased expression of a host of pro-fibrotic and pro-inflammatory factors was observed in qv4J CCM compared to WT, including MMP3, periostin, CCL17, osteoprotegerin, and CX3CL1 (Figure 3), consistent with previous RNA-sequencing analysis showing significant upregulation of these factors at the gene level within qv4J derived CFs [22]. Although qv4J CFs show enhanced proliferation, which on its own could increase generation of paracrine factors due to larger cell numbers, the levels of cytokines/chemokines and exosomes were assessed in CCM collected only 24 h after the cells reached target confluency, which is not enough time for differences in proliferation rate to confound the results (compare cell numbers in WT and qv4J at 24 h timepoint in Figure 1). These data indicate that loss of βIV-spectrin triggers the release of a host of cytokines and chemokines with the capacity to modulate phenotype of neighboring cells.

3.3. Exosomes Contribute to βIV-Spectrin Dependent Cell-Cell Communication

To further explore the role of βIV-spectrin in exosome biogenesis/secretion, exosomes from WT and qv4J CFs were isolated and characterized. The size distribution and number of isolated exosomes were quantified using a NanoSight Particle Tracking system (Nanosight300). This approach confirmed that WT and qv4J CCM was enriched in extracellular vesicles within the size range that is characteristic for exosomes (Figure 4, 30–150 nm). Consistent with the increased cell-cell communication from spectrin deficient CFs, the concentration of exosomes was significantly greater in qv4J CCM compared to WT CCM (Figure 4), despite similar CF numbers at time of collection (compare cell numbers in WT and qv4J at 24 h timepoint in Figure 1).

3.4. Role of STAT3 in βIV-Spectrin Dependent Cell-Cell Communication

βIV-spectrin alters CF gene transcription (including for several targets identified here, Figure 2) in a STAT3-dependent manner [22]. To determine whether altered STAT3 activity contributes to release of proinflammatory and profibrotic cytokines/chemokines from βIV-spectrin-deficient CFs, qv4J CFs were pre-treated with the STAT3 inhibitor S3I-201 (100 µM) or vehicle (3% DMSO in PBS) for 72 h before collection and analysis of CCM. Interestingly, STAT3 inhibition largely normalized the profile of secreted chemokines/cytokines in qv4J to that observed in WT CCM (Figure 5).
STAT3 inhibition also reduced the concentration of exosomes secreted by qv4J CFs (Figure 6). These data suggest that βIV-spectrin regulates CF paracrine signaling in a STAT3-dependent manner.

4. Discussion

Here, we describe a novel role for βIV-spectrin in tuning a cell-cell communication network in heart. Specifically, we report that βIV-spectrin-deficient (qv4J) CFs secrete a host of pro-fibrotic and pro-inflammatory paracrine signals into CCM with the capacity to alter the proliferative activity of WT CFs. Furthermore, we demonstrate an increase in release of bioactive exosomes from qv4J CFs. Finally, we report that STAT3 inhibition normalized the secretory profile of qv4J CFs. Based on our findings, we propose that the βIV-spectrin/STAT3 axis serves as a new avenue for modulating cell-cell communication and cardiac function in the setting of chronic disease.
Degradation of βIV-spectrin induces changes in STAT3 signaling and gene expression in both cardiomyocytes and CFs that drive altered cardiac function and fibrosis. At the cellular level, βIV-spectrin/STAT3 dysfunction promotes highly eccentric cardiomyocyte growth and increased collagen deposition, proliferation, and contractility in CFs. A similar phenotype is observed in qv4J mice. Further, the distinctive remodeling profile of hypertrophy and fibrosis was observed together even in cardiomyocyte- or fibroblast-specific βIV-spectrin knock out models, despite confirmation of βIV-spectrin expression in Cre negative cells [21,22]. Interestingly, global CF activation has been observed following ischemic injury, even in remote areas from the infarct region, although the mechanism for propagating the pro-fibrotic stimuli is unknown [29,30]. Our new findings reveal a potential mechanism for how those pathological changes are communicated throughout the myocardium. Together, these studies implicate a role for the βIV-spectrin/STAT3 complex in cell-cell communication. It will be important for future studies to test the role for this complex in cell-cell communication in vivo. In this context, we have the ability to home in on specific cell populations (e.g., CFs, myocytes, immune cells) using our cell-specific βIV-spectrin knockout model [21,22].
Over the last decade, there has been growing interest in the characteristics and functional effects of cardiac cell-derived exosomes in the setting of pathologic stress. Many studies have described specific miRNA expression changes in secreted exosomes following pathological stress. For example, increased circulating exosomes enriched with miR-22 have been reported following ischemic injury and proposed to aide in repair and remodeling following myocardial infarction [31]. However, the mechanisms underlying these pathologic changes in exosome secretion are not well defined. Here, we report that βIV-spectrin-deficiency increases the secretion of exosomes from CFs. Exosomes have an endosomal origin and are thought to be trafficked using the same pathways as exocytosis and endocytosis. The secretion of extracellular vesicles relies on the highly dynamic membrane-cytoskeletal interface [32,33]. In response to internal and external stimuli, cytoskeletal proteins undergo localized remodeling that results in detachment from the membrane, exposing locations for fusion and vesicle secretion [34,35,36]. Interestingly, it is thought that the actin-spectrin network can regulate not only the location of vesicle secretion, but the dynamics as well [34,37]. For example, in neurons, F-actin regulates the pore opening and speed of vesicle secretion [38,39]. Further, other studies have speculated that spectrin proteins can modulate actin assembly dynamics [20,40]. While it is known that βIV-spectrin associates with F-actin at the cell membrane, it is still unclear whether the dissociation of the βIV-spectrin-complex from F-actin directly alters the secretion of exosomes. Although we did not directly test this relationship, it will be interesting in the future to determine whether spectrin-dependent regulation of exosome secretion depends on βIV-spectrin/F-actin interaction.
STAT3 has a multifaceted role in regulating cell-cell communication, cardiac inflammation, and fibrosis. In CFs, STAT3 and miR-21 form a positive feedback loop to increase proliferation and expression of fibrotic genes, while STAT3 inhibition leads to the downregulation of miR-21 and abrogated myofibroblast activation fibrosis [41]. Interestingly, miR-21 was also found to be abundant in cardiac fibroblast-derived exosomes [14]. This may explain the observed decrease in exosome production following STAT3 inhibition. Our findings add to the growing literature that STAT3 is a critical regulator of cell communication during disease. Importantly, our results demonstrate that the βIV-spectrin/STAT3 complex plays a role in exosome biogenesis.
Cardiac wound healing (e.g., following myocardial infarction) relies on paracrine signaling between different cell types to carefully orchestrate the transition from inflammation to repair. Mounting data support the idea that CFs have a role in initiating the inflammasome. Here, we found that loss of βIV-spectrin lead to increased expression of pro-reparative and pro-inflammatory stimuli. For example, we observed increased expression of CCL17 and CXC3CL1, chemokine ligands that play a vital role in immune cell infiltration [42,43]. Further, we found increased expression of ECM-degrading matrix metalloproteinases (MMP2 and MMP3) and OPG, which are secreted from CFs to aide in repair of the myocardium [44,45]. The generation of these paracrine signals was abrogated with STAT3 inhibition and reintroduction of the full βIV-spectrin construct. These findings support our previous work that loss of βIV-spectrin and STAT3 dysregulation is a critical step for CF activation and communication.
While our findings demonstrate regulatory capacity for the βIV-spectrin/STAT3 complex in exosome production, our study focuses on the communication between CFs. Going forward, it will be interesting to determine whether a similar pathway supports communication between CFs and other cardiac cells, like cardiomyocytes and immune cells and to assess its role in vivo using cell-specific βIV-spectrin knockout models. It will also be interesting to determine how βIV-spectrin links specific stress stimuli to changes in exosome production and/or cargo. We propose that stress-induced loss of βIV-spectrin not only triggers activation of CFs, but also initiates pathological signal generation that is required for remodeling.

5. Conclusions

Overall, this study expands the role of the βIV-spectrin/STAT3 complex in mediating cell-cell communication. We found that βIV-spectrin deficiency in CFs resulted in increased secretion of cytokines and exosomes that induced phenotypic changes (increased proliferation and contractility) in quiescent CFs. The secretory profile of βIV-spectrin deficient CFs could be attenuated by inhibiting STAT3. Our findings implicate potential mechanisms as to how CFs modulate exosome secretion following chronic stress. Future work will dissect the interplay of these interactions in exosome biogenesis and secretion. It will be exciting to validate the contribution of the βIV-spectrin/STAT3 complex in cell communication in future in vivo studies.

Author Contributions

Conceptualization, D.M.N., R.S., N.J.P., N.L.P. and T.J.H.; methodology, D.M.N., R.S., N.J.P., J.Y., N.L., D.B., N.L.P. and T.J.H.; analysis, D.M.N., R.S., N.J.P., J.Y., N.L., N.L.P. and T.J.H.; investigation, D.M.N., R.S., N.J.P., J.Y., N.L. and D.B.; resources, N.L.P. and T.J.H.; writing—original draft preparation, D.M.N., R.S. and N.J.P.; writing—review and editing, D.M.N., R.S., N.J.P., N.L.P. and T.J.H.; supervision, project administration, and funding acquisition, N.L.P. and T.J.H. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Institutes of Health, grant numbers R01HL135096, and R01HL156652 (T.J.H.), K99/R00 HL157684 (D.M.N.), T32 HL124616 (support for R.S.); the Foundation Leducq FANTASY 19CV03; and the Bob and Corinne Frick Center for Heart Failure and Arrhythmia and Davis Heart and Lung Research Institute at the Ohio State University Wexner Medical Center.

Institutional Review Board Statement

Animal studies were conducted in accordance with the Guide for the Care and Use of Laboratory Animals published by the National Institutes of Health following protocols approved by the IACUC at The Ohio State University (protocol # 2011A00000068-R3, approved 10 August 21).

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Banerjee, I.; Fuseler, J.W.; Price, R.L.; Borg, T.K.; Baudino, T.A. Determination of cell types and numbers during cardiac development in the neonatal and adult rat and mouse. Am. J. Physiol. Heart Circ. Physiol. 2007, 293, H1883–H1891. [Google Scholar] [CrossRef] [Green Version]
  2. Tallquist, M.D.; Molkentin, J.D. Redefining the identity of cardiac fibroblasts. Nat. Rev. Cardiol. 2017, 14, 484–491. [Google Scholar] [CrossRef]
  3. Travers, J.G.; Kamal, F.A.; Robbins, J.; Yutzey, K.E.; Blaxall, B.C. Cardiac Fibrosis: The Fibroblast Awakens. Circ Res. 2016, 118, 1021–1040. [Google Scholar] [CrossRef] [Green Version]
  4. Humeres, C.; Frangogiannis, N.G. Fibroblasts in the Infarcted, Remodeling, and Failing Heart. JACC Basic Transl. Sci. 2019, 4, 449–467. [Google Scholar] [CrossRef]
  5. Fu, X.; Khalil, H.; Kanisicak, O.; Boyer, J.G.; Vagnozzi, R.J.; Maliken, B.D.; Sargent, M.A.; Prasad, V.; Valiente-Alandi, I.; Blaxall, B.C.; et al. Specialized fibroblast differentiated states underlie scar formation in the infarcted mouse heart. J. Clin. Investig. 2018, 128, 2127–2143. [Google Scholar] [CrossRef] [Green Version]
  6. Kanisicak, O.; Khalil, H.; Ivey, M.J.; Karch, J.; Maliken, B.D.; Correll, R.N.; Brody, M.J.; SC, J.L.; Aronow, B.J.; Tallquist, M.D.; et al. Genetic lineage tracing defines myofibroblast origin and function in the injured heart. Nat. Commun. 2016, 7, 12260. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  7. Davis, J.; Molkentin, J.D. Myofibroblasts: Trust your heart and let fate decide. J. Mol. Cell Cardiol. 2014, 70, 9–18. [Google Scholar] [CrossRef] [Green Version]
  8. Gourdie, R.G.; Dimmeler, S.; Kohl, P. Novel therapeutic strategies targeting fibroblasts and fibrosis in heart disease. Nat. Rev. Drug Discov. 2016, 15, 620–638. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  9. Frangogiannis, N.G. Cardiac fibrosis: Cell biological mechanisms, molecular pathways and therapeutic opportunities. Mol. Aspects Med. 2019, 65, 70–99. [Google Scholar] [CrossRef] [PubMed]
  10. Broughton, K.M.; Wang, B.J.; Firouzi, F.; Khalafalla, F.; Dimmeler, S.; Fernandez-Aviles, F.; Sussman, M.A. Mechanisms of Cardiac Repair and Regeneration. Circ. Res. 2018, 122, 1151–1163. [Google Scholar] [CrossRef]
  11. LaFramboise, W.A.; Scalise, D.; Stoodley, P.; Graner, S.R.; Guthrie, R.D.; Magovern, J.A.; Becich, M.J. Cardiac fibroblasts influence cardiomyocyte phenotype in vitro. Am. J. Physiol. Cell Physiol. 2007, 292, C1799–C1808. [Google Scholar] [CrossRef]
  12. Lyu, L.; Wang, H.; Li, B.; Qin, Q.; Qi, L.; Nagarkatti, M.; Nagarkatti, P.; Janicki, J.S.; Wang, X.L.; Cui, T. A critical role of cardiac fibroblast-derived exosomes in activating renin angiotensin system in cardiomyocytes. J. Mol. Cell Cardiol. 2015, 89, 268–279. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Liu, N.; Xie, L.; Xiao, P.; Chen, X.; Kong, W.; Lou, Q.; Chen, F.; Lu, X. Cardiac fibroblasts secrete exosome microRNA to suppress cardiomyocyte pyroptosis in myocardial ischemia/reperfusion injury. Mol. Cell Biochem. 2022, 477, 1249–1260. [Google Scholar] [CrossRef] [PubMed]
  14. Bang, C.; Batkai, S.; Dangwal, S.; Gupta, S.K.; Foinquinos, A.; Holzmann, A.; Just, A.; Remke, J.; Zimmer, K.; Zeug, A.; et al. Cardiac fibroblast-derived microRNA passenger strand-enriched exosomes mediate cardiomyocyte hypertrophy. J. Clin. Investig. 2014, 124, 2136–2146. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Ibrahim, A.G.; Cheng, K.; Marban, E. Exosomes as critical agents of cardiac regeneration triggered by cell therapy. Stem Cell Reports. 2014, 2, 606–619. [Google Scholar] [CrossRef] [Green Version]
  16. Borosch, S.; Dahmen, E.; Beckers, C.; Stoppe, C.; Buhl, E.M.; Denecke, B.; Goetzenich, A.; Kraemer, S. Characterization of extracellular vesicles derived from cardiac cells in an in vitro model of preconditioning. J. Extracell Vesicles 2017, 6, 1390391. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  17. Hohn, J.; Tan, W.; Carver, A.; Barrett, H.; Carver, W. Roles of Exosomes in Cardiac Fibroblast Activation and Fibrosis. Cells 2021, 10, 2933. [Google Scholar] [CrossRef]
  18. Bennett, V.; Baines, A.J. Spectrin and ankyrin-based pathways: Metazoan inventions for integrating cells into tissues. Physiol. Rev. 2001, 81, 1353–1392. [Google Scholar] [CrossRef] [Green Version]
  19. Machnicka, B.; Grochowalska, R.; Boguslawska, D.M.; Sikorski, A.F.; Lecomte, M.C. Spectrin-based skeleton as an actor in cell signaling. Cell Mol. Life Sci. 2012, 69, 191–201. [Google Scholar] [CrossRef] [Green Version]
  20. Unudurthi, S.D.; Greer-Short, A.; Patel, N.; Nassal, D.; Hund, T.J. Spectrin-based pathways underlying electrical and mechanical dysfunction in cardiac disease. Expert Rev. Cardiovasc. Ther. 2018, 16, 59–65. [Google Scholar] [CrossRef]
  21. Unudurthi, S.D.; Nassal, D.; Greer-Short, A.; Patel, N.; Howard, T.; Xu, X.; Onal, B.; Satroplus, T.; Hong, D.; Lane, C.; et al. betaIV-Spectrin regulates STAT3 targeting to tune cardiac response to pressure overload. J. Clin. Investig. 2018, 128, 5561–5572. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Patel, N.J.; Nassal, D.M.; Greer-Short, A.D.; Unudurthi, S.D.; Scandling, B.W.; Gratz, D.; Xu, X.; Kalyanasundaram, A.; Fedorov, V.V.; Accornero, F.; et al. betaIV-Spectrin/STAT3 complex regulates fibroblast phenotype, fibrosis, and cardiac function. JCI Insight 2019, 4, e131046. [Google Scholar] [CrossRef] [PubMed]
  23. Nassal, D.M.; Patel, N.J.; Unudurthi, S.D.; Shaheen, R.; Yu, J.; Mohler, P.J.; Hund, T.J. Ca2+/calmodulin kinase II-dependent regulation of betaIV-spectrin modulates cardiac fibroblast gene expression, proliferation, and contractility. J. Biol. Chem. 2021, 297, 100893. [Google Scholar] [CrossRef]
  24. Parkinson, N.J.; Olsson, C.L.; Hallows, J.L.; McKee-Johnson, J.; Keogh, B.P.; Noben-Trauth, K.; Kujawa, S.G.; Tempel, B.L. Mutant beta-spectrin 4 causes auditory and motor neuropathies in quivering mice. Nat. Genet. 2001, 29, 61–65. [Google Scholar] [CrossRef]
  25. Hund, T.J.; Snyder, J.S.; Wu, X.; Glynn, P.; Koval, O.M.; Onal, B.; Leymaster, N.D.; Unudurthi, S.D.; Curran, J.; Camardo, C.; et al. betaIV-Spectrin regulates TREK-1 membrane targeting in the heart. Cardiovasc. Res. 2014, 102, 166–175. [Google Scholar] [CrossRef] [Green Version]
  26. Martin, T.P.; Lawan, A.; Robinson, E.; Grieve, D.J.; Plevin, R.; Paul, A.; Currie, S. Adult cardiac fibroblast proliferation is modulated by calcium/calmodulin-dependent protein kinase II in normal and hypertrophied hearts. Pflugers Arch. 2014, 466, 319–330. [Google Scholar] [CrossRef]
  27. Cosme, J.; Guo, H.; Hadipour-Lakmehsari, S.; Emili, A.; Gramolini, A.O. Hypoxia-Induced Changes in the Fibroblast Secretome, Exosome, and Whole-Cell Proteome Using Cultured, Cardiac-Derived Cells Isolated from Neonatal Mice. J. Proteome Res. 2017, 16, 2836–2847. [Google Scholar] [CrossRef]
  28. Bansal, S.; Sharma, M.; Ranjithkumar, R.; Mohanakumar, T. The role of exosomes in allograft immunity. Cell Immunol. 2018, 331, 85–92. [Google Scholar] [CrossRef]
  29. Shah, H.; Hacker, A.; Langburt, D.; Dewar, M.; McFadden, M.J.; Zhang, H.; Kuzmanov, U.; Zhou, Y.Q.; Hussain, B.; Ehsan, F.; et al. Myocardial Infarction Induces Cardiac Fibroblast Transformation within Injured and Noninjured Regions of the Mouse Heart. J. Proteome Res. 2021, 20, 2867–2881. [Google Scholar] [CrossRef] [PubMed]
  30. Nagaraju, C.K.; Dries, E.; Popovic, N.; Singh, A.A.; Haemers, P.; Roderick, H.L.; Claus, P.; Sipido, K.R.; Driesen, R.B. Global fibroblast activation throughout the left ventricle but localized fibrosis after myocardial infarction. Sci. Rep. 2017, 7, 10801. [Google Scholar] [CrossRef] [Green Version]
  31. Emanueli, C.; Shearn, A.I.; Angelini, G.D.; Sahoo, S. Exosomes and exosomal miRNAs in cardiovascular protection and repair. Vasc. Pharmacol. 2015, 71, 24–30. [Google Scholar] [CrossRef] [Green Version]
  32. Sorkin, R.; Huisjes, R.; Boskovic, F.; Vorselen, D.; Pignatelli, S.; Ofir-Birin, Y.; Freitas Leal, J.K.; Schiller, J.; Mullick, D.; Roos, W.H.; et al. Nanomechanics of Extracellular Vesicles Reveals Vesiculation Pathways. Small 2018, 14, e1801650. [Google Scholar] [CrossRef]
  33. Unsain, N.; Stefani, F.D.; Caceres, A. The Actin/Spectrin Membrane-Associated Periodic Skeleton in Neurons. Front. Synaptic Neurosci. 2018, 10, 10. [Google Scholar] [CrossRef] [Green Version]
  34. Gundelfinger, E.D.; Kessels, M.M.; Qualmann, B. Temporal and spatial coordination of exocytosis and endocytosis. Nat. Rev. Mol. Cell Biol. 2003, 4, 127–139. [Google Scholar] [CrossRef] [PubMed]
  35. Trifaro, J.; Rose, S.D.; Lejen, T.; Elzagallaai, A. Two pathways control chromaffin cell cortical F-actin dynamics during exocytosis. Biochimie 2000, 82, 339–352. [Google Scholar] [CrossRef] [PubMed]
  36. Yang, L.; Dun, A.R.; Martin, K.J.; Qiu, Z.; Dunn, A.; Lord, G.J.; Lu, W.; Duncan, R.R.; Rickman, C. Secretory vesicles are preferentially targeted to areas of low molecular SNARE density. PLoS ONE. 2012, 7, e49514. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  37. Taylor, J.; Patio, K.; De Rubis, G.; Morris, M.B.; Evenhuis, C.; Johnson, M.; Bebawy, M. Membrane to cytosol redistribution of alphaII-spectrin drives extracellular vesicle biogenesis in malignant breast cells. Proteomics 2021, 21, e2000091. [Google Scholar] [CrossRef]
  38. Piriya Ananda Babu, L.; Wang, H.Y.; Eguchi, K.; Guillaud, L.; Takahashi, T. Microtubule and Actin Differentially Regulate Synaptic Vesicle Cycling to Maintain High-Frequency Neurotransmission. J. Neurosci. 2020, 40, 131–142. [Google Scholar] [CrossRef] [Green Version]
  39. Wu, L.G.; Chan, C.Y. Multiple Roles of Actin in Exo- and Endocytosis. Front. Synaptic Neurosci. 2022, 14, 841704. [Google Scholar] [CrossRef]
  40. Benz, P.M.; Merkel, C.J.; Offner, K.; Abesser, M.; Ullrich, M.; Fischer, T.; Bayer, B.; Wagner, H.; Gambaryan, S.; Ursitti, J.A.; et al. Mena/VASP and alphaII-Spectrin complexes regulate cytoplasmic actin networks in cardiomyocytes and protect from conduction abnormalities and dilated cardiomyopathy. Cell Commun. Signal. 2013, 11, 56. [Google Scholar] [CrossRef] [Green Version]
  41. Huang, Z.; Chen, X.J.; Qian, C.; Dong, Q.; Ding, D.; Wu, Q.F.; Li, J.; Wang, H.F.; Li, W.H.; Xie, Q.; et al. Signal Transducer and Activator of Transcription 3/MicroRNA-21 Feedback Loop Contributes to Atrial Fibrillation by Promoting Atrial Fibrosis in a Rat Sterile Pericarditis Model. Circ. Arrhythm Electrophysiol. 2016, 9, e003396. [Google Scholar] [CrossRef] [PubMed]
  42. Feng, G.; Bajpai, G.; Ma, P.; Koenig, A.; Bredemeyer, A.; Lokshina, I.; Lai, L.; Forster, I.; Leuschner, F.; Kreisel, D.; et al. CCL17 Aggravates Myocardial Injury by Suppressing Recruitment of Regulatory T Cells. Circulation 2022, 145, 765–782. [Google Scholar] [CrossRef] [PubMed]
  43. Weisheit, C.K.; Kleiner, J.L.; Rodrigo, M.B.; Niepmann, S.T.; Zimmer, S.; Duerr, G.D.; Coburn, M.; Kurts, C.; Frede, S.; Eichhorn, L. CX3CR1 is a prerequisite for the development of cardiac hypertrophy and left ventricular dysfunction in mice upon transverse aortic constriction. PLoS ONE 2021, 16, e0243788. [Google Scholar] [CrossRef] [PubMed]
  44. Lindner, D.; Zietsch, C.; Becher, P.M.; Schulze, K.; Schultheiss, H.P.; Tschope, C.; Westermann, D. Differential expression of matrix metalloproteases in human fibroblasts with different origins. Biochem. Res. Int. 2012, 2012, 875742. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Habibie, H.; Adhyatmika, A.; Schaafsma, D.; Melgert, B.N. The role of osteoprotegerin (OPG) in fibrosis: Its potential as a biomarker and/or biological target for the treatment of fibrotic diseases. Pharmacol. Ther. 2021, 228, 107941. [Google Scholar] [CrossRef] [PubMed]
Figure 1. (A) Summary data for the number of WT cardiac fibroblasts (CFs) at 24, 48 and 72 h following treatment with either WT or qv4J culture conditioned media (CCM). All groups had an initial seeding at a density of 1 × 105 cells/well. N = 3 independent preparations; * p < 0.05 with two-way ANOVA (with timepoint and genotype as factors) and Holm-Sidak post hoc pairwise comparison. (B) Summary data on collagen gel area (left) and representative collagen gel images (right) following 72 h of treatment of WT CFs with WT or qv4J CCM. N = 3 independent preparations; * p < 0.05 with unpaired two-tailed t-test. Scale bars = 2 mm.
Figure 1. (A) Summary data for the number of WT cardiac fibroblasts (CFs) at 24, 48 and 72 h following treatment with either WT or qv4J culture conditioned media (CCM). All groups had an initial seeding at a density of 1 × 105 cells/well. N = 3 independent preparations; * p < 0.05 with two-way ANOVA (with timepoint and genotype as factors) and Holm-Sidak post hoc pairwise comparison. (B) Summary data on collagen gel area (left) and representative collagen gel images (right) following 72 h of treatment of WT CFs with WT or qv4J CCM. N = 3 independent preparations; * p < 0.05 with unpaired two-tailed t-test. Scale bars = 2 mm.
Cells 12 00748 g001
Figure 2. Summary data for the number of WT cardiac fibroblasts at 24, 48 and 72 h following treatment with small MW fraction or large MW fraction of WT or qv4J culture conditioned media (CCM). All groups had an initial seeding at a density of 1 × 105 cells/well. N = 3 independent preparations; * p < 0.05 with two-way ANOVA (with timepoint and CCM group as factors) and Holm-Sidak post hoc pairwise comparison. There was a significant (p < 0.05) difference between the 24 h and 48 h timepoints and 48 h and 72 h timepoints for all groups (not indicated in figure for simplicity).
Figure 2. Summary data for the number of WT cardiac fibroblasts at 24, 48 and 72 h following treatment with small MW fraction or large MW fraction of WT or qv4J culture conditioned media (CCM). All groups had an initial seeding at a density of 1 × 105 cells/well. N = 3 independent preparations; * p < 0.05 with two-way ANOVA (with timepoint and CCM group as factors) and Holm-Sidak post hoc pairwise comparison. There was a significant (p < 0.05) difference between the 24 h and 48 h timepoints and 48 h and 72 h timepoints for all groups (not indicated in figure for simplicity).
Cells 12 00748 g002
Figure 3. Representative dot blots (noncontiguous images from 2 separate assays for WT and qv4J) and quantitative estimation on top candidates from proteome profiler mouse cytokine array performed on conditioned culture media (CCM) from WT and qv4J cardiac fibroblasts following 24 h in serum-free media. Quantitative estimation was performed by normalizing densitometry value for each sample to a control [CC motif chemokine ligand 3 (CCL3)] and then expressing as percent change in qv4J compared to WT CCM. N = 2 independent preparations for each condition; Bars indicate mean value (data points superimposed). Abbreviations are as follows: CCL17 = CC motif chemokine ligand 17; CD142 = coagulation factor III; CX3CL1 = C-X3-C motif chemokine ligand 1 (or fractalkine); CXCL16 = C-X-C motif chemokine ligand 16; MMP3 = matrix metallopeptidase 3; OPG = osteoprotegerin.
Figure 3. Representative dot blots (noncontiguous images from 2 separate assays for WT and qv4J) and quantitative estimation on top candidates from proteome profiler mouse cytokine array performed on conditioned culture media (CCM) from WT and qv4J cardiac fibroblasts following 24 h in serum-free media. Quantitative estimation was performed by normalizing densitometry value for each sample to a control [CC motif chemokine ligand 3 (CCL3)] and then expressing as percent change in qv4J compared to WT CCM. N = 2 independent preparations for each condition; Bars indicate mean value (data points superimposed). Abbreviations are as follows: CCL17 = CC motif chemokine ligand 17; CD142 = coagulation factor III; CX3CL1 = C-X3-C motif chemokine ligand 1 (or fractalkine); CXCL16 = C-X-C motif chemokine ligand 16; MMP3 = matrix metallopeptidase 3; OPG = osteoprotegerin.
Cells 12 00748 g003
Figure 4. Size distribution of extracellular vesicles isolated from WT or qv4J conditioned culture medium (CCM) (left) and summary data (right) on area under the curve (AUC) in the 30–150 nm size range. N = 7 independent preparations for each condition; * p < 0.05 vs. WT with Whitney-Mann rank-sum test.
Figure 4. Size distribution of extracellular vesicles isolated from WT or qv4J conditioned culture medium (CCM) (left) and summary data (right) on area under the curve (AUC) in the 30–150 nm size range. N = 7 independent preparations for each condition; * p < 0.05 vs. WT with Whitney-Mann rank-sum test.
Cells 12 00748 g004
Figure 5. Dot blots (noncontiguous images from 2 separate assays for vehicle and S3I-201) from proteome profiler mouse cytokine array performed on conditioned culture media (CCM) from qv4J cardiac fibroblasts pretreated for 72 h with STAT3 inhibitor S3I-201 (100 μM) or vehicle control (N = 2 independent preparation for each condition). Abbreviations are as follows: CC motif chemokine ligand 3 = CCL3; CCL17 = CC motif chemokine ligand 17; CD142 = coagulation factor III; CX3CL1 = C-X3-C motif chemokine ligand 1 (or fractalkine); CXCL16 = C-X-C motif chemokine ligand 16; MMP3 = matrix metallopeptidase 3; OPG = osteoprotegerin.
Figure 5. Dot blots (noncontiguous images from 2 separate assays for vehicle and S3I-201) from proteome profiler mouse cytokine array performed on conditioned culture media (CCM) from qv4J cardiac fibroblasts pretreated for 72 h with STAT3 inhibitor S3I-201 (100 μM) or vehicle control (N = 2 independent preparation for each condition). Abbreviations are as follows: CC motif chemokine ligand 3 = CCL3; CCL17 = CC motif chemokine ligand 17; CD142 = coagulation factor III; CX3CL1 = C-X3-C motif chemokine ligand 1 (or fractalkine); CXCL16 = C-X-C motif chemokine ligand 16; MMP3 = matrix metallopeptidase 3; OPG = osteoprotegerin.
Cells 12 00748 g005
Figure 6. Size distribution of extracellular vesicles isolated from conditioned culture medium (CCM) collected from qv4J fibroblasts ± STAT3 inhibitor S3I-201 (100 M) (left) and summary data (right) on area under the curve (AUC) in the 30–150 nm size range. N = 4 independent preparations for each condition; * p < 0.05 with Whitney-Mann rank-sum test.
Figure 6. Size distribution of extracellular vesicles isolated from conditioned culture medium (CCM) collected from qv4J fibroblasts ± STAT3 inhibitor S3I-201 (100 M) (left) and summary data (right) on area under the curve (AUC) in the 30–150 nm size range. N = 4 independent preparations for each condition; * p < 0.05 with Whitney-Mann rank-sum test.
Cells 12 00748 g006
Table 1. Table of abbreviations.
Table 1. Table of abbreviations.
AbbreviationDefinition
CCL17CC motif chemokine ligand 17
CCL3CC motif chemokine ligand 3
CCMConditioned culture media
CD142Coagulation factor III
CFCardiac fibroblast
CX3CL1C-X3-C motif chemokine ligand 1
CXCL16C-X-C motif chemokine ligand 16
ECMExtracellular matrix
EVExtracellular vesicle
MMP3Matrix metallopeptidase 3
MWMolecular weight
OPGOsteoprotegerin
STAT3Signal transducer and activation of transcription 3
qv4JMouse with point mutation in Spnb4 gene resulting in truncated βIV-spectrin
WTWildtype
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Nassal, D.M.; Shaheen, R.; Patel, N.J.; Yu, J.; Leahy, N.; Bibidakis, D.; Parinandi, N.L.; Hund, T.J. Spectrin-Based Regulation of Cardiac Fibroblast Cell-Cell Communication. Cells 2023, 12, 748. https://doi.org/10.3390/cells12050748

AMA Style

Nassal DM, Shaheen R, Patel NJ, Yu J, Leahy N, Bibidakis D, Parinandi NL, Hund TJ. Spectrin-Based Regulation of Cardiac Fibroblast Cell-Cell Communication. Cells. 2023; 12(5):748. https://doi.org/10.3390/cells12050748

Chicago/Turabian Style

Nassal, Drew M., Rebecca Shaheen, Nehal J. Patel, Jane Yu, Nick Leahy, Dimitra Bibidakis, Narasimham L. Parinandi, and Thomas J. Hund. 2023. "Spectrin-Based Regulation of Cardiac Fibroblast Cell-Cell Communication" Cells 12, no. 5: 748. https://doi.org/10.3390/cells12050748

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop