Pressure Overload Greatly Promotes Neonatal Right Ventricular Cardiomyocyte Proliferation: A New Model for the Study of Heart Regeneration

Animal Experiments

Pregnant Sprague–Dawley rats were purchased from Xipu'er‐bikai Experimental Animal Co., Ltd (Shanghai, China). After birth, the rat neonates (both males and females) were randomized into 2 groups: an experimental group (PAB group), and a control group (sham group) that underwent the same procedure except for the banding step. Pulmonary artery banding (PAB) surgery was performed according to our previous publication.21 Briefly, after neonatal rats were anesthetized by ice cooling, they were transferred to an ice bed and fixed in the supine position. Horizontal thoracotomy was performed to reveal the pulmonary artery (PA). An 11‐0 nylon thread was positioned under the PA, and a 30‐gauge needle (0.31‐mm diameter) was placed on the PA. The PA and needle were then tied together by the thread. We then removed the needle to form a fixed, constricted opening in the PA lumen. We closed the thoracic wall and then warmed the neonatal rats with a heat plate until natural movements and a red/pink complexion were achieved. We have provided a surgical video of our right ventricular overload model on a website 21 to enable others to learn the technique. All of the procedures conformed to the principles outlined in the Declaration of Helsinki and were approved by the Animal Welfare and Human Studies Committee at Shanghai Children's Medical Center.

Transthoracic Echocardiography

Rats were anesthetized with isoflurane and allowed to breathe spontaneously through a nasal cone (isoflurane/oxygen: 1.5%–2.0% maintenance). Echocardiograms were analyzed with a Vevo 2100 imaging system (Visual Sonics, Toronto, Ontario, Canada), and a long‐axis view of the PA was used to measure the peak pressure gradient across the PA constriction by continuous‐wave Doppler.

Histology

Postnatal day 7 (P7) rat hearts were fixed in 4% paraformaldehyde overnight at 4°C, then dehydrated in an ethanol series, embedded in paraffin, and sectioned into 6‐μm slices. Hematoxylin and eosin staining was performed.

Cardiomyocyte Isolation and Purification

At P7, the young rats were decapitated. The hearts were carefully taken from the chest, and cardiomyocytes were dissociated by Langendorff reverse coronary perfusion with 200 μg/mL Liberase DH (Roche), as described elsewhere.9 Cardiomyocytes were enriched by differential adherence and low‐speed centrifugation.24 The purity of cardiomyocytes was confirmed by flow cytometry. The purified cardiomyocytes were used for total RNA preparation and RNA‐seq.

Total RNA Preparation and Real‐Time Quantitative PCR Analysis

For mRNA quantification, mRNA was extracted and purified using a PureLink RNA Micro Scale Kit (Catalog No. 12183016; Life Technologies, Carlsbad, CA). RT‐PCR was performed using the PrimeScript^™ reagent kit (Takara Bio, Kusatsu, Japan). Quantitative real‐time polymerase chain reaction (qRT‐PCR) were carried out using SYBR Green Power Premix Kits (Applied Biosystems, Foster City, CA) according to the manufacturer's instructions. qRT‐PCR was performed with a 7900 Fast Real‐Time PCR System (Applied Biosystems), and the following conditions were used: 1 cycle at 95°C for 10 s, followed by 40 cycles of 95°C for 15 s and 60°C for 60 s. The primers were obtained from Generay Biotech Co., Ltd (Shanghai, China). The relative fold change was then calculated using the ΔΔCT method.

Library Preparation for Transcriptome Sequencing

A total amount of 1 μg RNA per sample was used as input material for the RNA sample preparations. Sequencing libraries were generated using the NEBNext^® Ultra^™ RNA Library Prep Kit for Illumina^® (NEB, USA) following the manufacturer's recommendations. Index codes were added to attribute sequences to each sample. Briefly, mRNA was purified from total RNA using poly‐T oligo‐attached magnetic beads. Fragmentation was carried out using divalent cations under elevated temperature in NEB Next First Strand Synthesis Reaction Buffer (5×). First strand cDNA was synthesized using random hexamer primers and M‐MuLV Reverse Transcriptase (RNase H –). Second strand cDNA synthesis was subsequently performed using DNA polymerase I and RNase H. Remaining overhangs were converted into blunt ends via exonuclease/polymerase activities. After adenylation of the 3′ ends of the DNA fragments, NEBNext Adaptors with hairpin loop structures were ligated to prepare for hybridization. In order to select cDNA fragments of preferentially 250–300 bp in length, the library fragments were purified with the AMPure XP system (Beckman Coulter, Beverly, MA). Then 3 μL USER Enzyme (NEB, USA) was used with size‐selected, adaptor‐ligated cDNA at 37°C for 15 minutes followed by 5 minutes at 95°C. Then, PCR was performed with Phusion High‐Fidelity DNA polymerase, Universal PCR primers, and Index (X) Primer. At last, PCR products were purified (AMPure XP system), and library quality was assessed on an Agilent Bioanalyzer 2100 system.

Clustering and Sequencing

The clustering of the index‐coded samples was performed on a cBot Cluster Generation System using a TruSeq PE Cluster Kit v3‐cBot‐HS (Illumina) according to the manufacturer's instructions. After cluster generation, the library preparations were sequenced on an Illumina Novaseq platform, and 150 bp paired‐end reads were generated.

Quality Control, Read Mapping, and Quantification of Gene Expression Levels

Raw data (raw reads) in fastq format were first processed through in‐house Perl scripts. In this step, clean data (clean reads) were obtained by removing reads containing adapters, reads containing poly‐N, and low‐quality reads from raw data. At the same time, Q20, Q30, and GC content of the clean data were calculated. All of the downstream analyses were based on the clean data with high quality.

Reference genome and gene model annotation files were downloaded from the genome website directly. The index of the reference genome was built using Hisat2 v2.0.5, and paired‐end clean reads were also aligned to the reference genome using Hisat2 v2.0.5. We selected Hisat2 as the mapping tool since it can generate a database of splice junctions based on the gene model annotation file and thus a better mapping result than other nonsplice mapping tools.

The expected number of fragments per kilobase of transcript sequence per million base pairs sequenced considers the effect of sequencing depth and gene length for the reads counted at the same time. Fragments per kilobase of transcript sequence per million is currently the most commonly used method for estimating gene expression levels. For this, featureCounts v1.5.0‐p3 was used to count the number of reads mapped to each gene. Then, fragments per kilobase of transcript sequence per million of each gene was calculated based on the length of the gene and read counts mapped to each gene.

Differential Expression Analysis and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes Enrichment Analysis of Differentially Expressed Genes

Differential expression analysis was performed using the DESeq2 R package (1.16.1). DESeq2 provides statistical routines for determining differential expression in digital gene expression data using a model based on the negative binomial distribution. The resulting P values were adjusted using Benjamini and Hochberg's approach for controlling the false discovery rate. Genes with an adjusted P value of <0.05 found by DESeq2 were assigned as differentially expressed.

Gene Ontology (GO) enrichment analysis of differentially expressed genes was implemented by the clusterProfiler R package, in which gene length bias was corrected. GO terms with corrected P values <0.05 considered to be significantly enriched by differentially expressed genes.

Kyoto Encyclopedia of Genes and Genomes (KEGG) is a database resource for understanding high‐level functions and utilities of biological systems, such as the cell, the organism, and the ecosystem, from molecular‐level information, especially large‐scale molecular data sets generated by genome sequencing and other high‐throughput experimental technologies (http://www.genome.jp/kegg/). We used the clusterProfiler R package to test the statistical enrichment of differentially expressed genes in KEGG pathways.

Tetralogy of Fallot Patients

We collected 20 right‐ventricular‐outflow myocardial tissue specimens from resections required to relieve obstructions in tetralogy of Fallot (TOF) patients at the Shanghai Children's Medical Center, Shanghai, China, between February 2015 and July 2018. Each specimen was preserved in liquid nitrogen and later divided into 3 portions, which were used for DNA extraction, qRT‐PCR, and immunofluorescence. All of the procedures conformed to the principles outlined in the Declaration of Helsinki and were approved by the Animal Welfare and Human Studies Committee at the Shanghai Children's Medical Center. Parental written informed consent was obtained before study initiation.

Immunofluorescence

Slides were washed 3 times with PBS, fixed with 4% paraformaldehyde for 10 minutes, permeated with 0.5% Triton X‐100 for 15 minutes, blocked with 10% donkey serum for 30 minutes, and stained with primary antibodies overnight at 4°C. After washing the slides 3 more times, we incubated the sections or cells with secondary antibodies and 4′,6‐diamidino‐2‐phenylindole for 30 minutes. Three researchers who were blinded to sample identity quantified cellular Ki67, phospho‐histone H3 (pH3), and aurora B via either manual counting or digital thresholding. This included image segmentation and creation of a binary image from a grayscale. We analyzed the converted binary images using ImageJ software (NIH, Bethesda, MD; Laboratory for Optical and Computational Instrumentation, University of Wisconsin, Madison, WI).

EdU Labeling

For EdU labeling experiments, rats were injected subcutaneously with 5 μg/g EdU at 24 hours before harvesting and signals were detected with a Click‐iT@ Imaging Kit according to the manufacturer's instructions.

Pressure Overload Greatly Changes Genes Expression in Neonatal Right Ventricular Cardiomyocytes

To investigate how pressure overload changes gene expression in right ventricular cardiomyocytes (RVCMs), we isolated and purified cardiomyocytes from the RVs of the hearts of PAB and sham‐operated mice (Figure S1) and performed RNA‐seq on these cardiomyocytes. We verified the RNA‐seq results by qRT‐PCR (Figures S2 and S3) and have provided the list of top 24 genes and their detailed information (Figure S2 and Table S4). Our results showed that there were 5469 differentially expressed genes, among which 2567 were downregulated and 2902 were upregulated (Figure 2A). These 2 groups of cardiomyocytes shared 13 257 expressed genes in common. In the PAB group, another 624 genes were expressed (operation1week, opt1w), and 695 genes were expressed only in the sham group (control1week, con1w) (Figure 2B). When these genes were clustered, a heatmap showed that the individual rats in the same group were similar to each other but were noticeably different from the rats in the other group (Figure 2C).

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Figure 2

Pressure overload greatly changes gene expression of cardiomyocytes.

A, Volcano map of differentially expressed genes. There were 5469 differentially expressed genes between PAB (Operation‐1 week, Opt1w) and sham (control‐1 week, Con1w) groups, among which, 2902 genes were upregulated, and 2567 genes were downregulated. B, Venn diagram of differentially expressed genes. There were 13 257 genes expressed in both groups, 624 genes expressed only in the PAB group, and 695 genes expressed only in the sham group. C, Cluster analysis of differentially expressed genes. Every group had 6 rats. The clusters of genes in each animal in the same group were similar to each other but quite different from the other group. OWOP is from the PAB group; OWCON is from the sham group. OWCON indicates Operationer Wang‐Control; OWOP, Operationer Wang‐operationl; and PAB, pulmonary artery banding.

Most Enriched GO Terms Are Closely Related to Cell Proliferation

We performed GO analysis to find out whether the differentially expressed genes were associated with cell proliferation. Biological process analysis showed that the top 10 most enriched GO terms were chromosome segregation, sister chromatid segregation, mitotic sister chromatid segregation, nuclear chromosome segregation, DNA replication, DNA repair, DNA‐dependent DNA replication, regulation of cell cycle process, mitotic nuclear division, and organelle fission (Figure 3A through C). Cell component analysis showed the top 10 most enriched GO terms were chromosomal region, kinetochore, condensed chromosome‐centromeric region, condensed chromosome kinetochore, condensed chromosome, spindle, centrosome, condensed chromosome outer kinetochore, and condensed nuclear chromosome kinetochore (Figure 3A through D). Molecular function analysis showed the top 10 most enriched GO terms were DNA‐dependent ATPase activity, catalytic activity acting on DNA, histone binding, ATP‐dependent DNA helicase activity, modification‐dependent protein binding, damaged DNA binding, helicase activity, ATP‐dependent 3′‐5′ DNA helicase activity, and single‐stranded DNA binding (Figure 3A, ​A,3B,3B, and ​and3E).3E). GO analysis suggested that pressure overload significantly promoted cardiomyocyte proliferation.

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Figure 3

GO analysis indicates that the differentially expressed genes mainly mediate mitosis and cell division.

A, From the results of the GO enrichment analysis, the most significant 30 terms are displayed. The abscissa is the GO Term, and the ordinate is the significance level of GO Term enrichment. The higher the value, the more significant, and the different colors represent 3 different GO subclasses: biological process (BP), (CC), and MF. B, From the results of the GO enrichment analysis, we selected the most significant 30 terms to draw scatterplots for display. The abscissa is the ratio of the number of differentially expressed genes on the GO Term to the total number of differentially expressed genes, the ordinate is the GO Term, the size of the dots represents the number of genes annotated to the GO Term, and the color from red to purple represents the significance level of GO Term enrichment. C, A network diagram of the top 5 most significant GO Terms in BP. D, A network diagram of the top 5 most significant GO Terms in BP in MF in CC. E, A network diagram of the top 5 most significant GO Terms in biological processes in molecular functions. BP indicates biological processes; CC, cellular components; GO, gene ontology; and MF, molecular function.

KEGG Pathway Analysis Showed That Most Enriched Terms Were Closely Related to Cell Proliferation

We performed KEGG pathway analysis to find out whether the pathways regulating differentially expressed genes were associated with cell proliferation. The top 10 enriched pathways were cell cycle, DNA replication, nucleotide excision repair, mismatch repair, small cell lung cancer, pyrimidine metabolism, homologous recombination, base excision repair, bladder cancer, and Fanconi anemia pathway (Figure 4A through C). KEGG pathway analysis suggested that pressure overload largely activated pathways associated with cell proliferation.

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Figure 4

KEGG pathway analysis indicates that the differentially expressed genes mainly mediate mitosis and cell division.

A, From the KEGG enrichment results, the most significant 20 KEGG pathways are displayed. The abscissa is the KEGG pathway, and the ordinate is the significance level of pathway enrichment. The higher the value, the more significant. B, From the KEGG enrichment results, the most significant 20 KEGG pathways were selected for the scatterplots. The abscissa is the ratio of the number of differentially expressed genes on the KEGG pathway to the total number of differentially expressed genes, the ordinate is the KEGG pathway, the size of the dots represents the number of genes annotated to the KEGG pathway, and the color from red to purple the represents significance level of KEGG pathway enrichment. C, The Network of the top 5 most significantly enriched KEGG pathways. KEGG indicates Kyoto Encyclopedia of Genes and Genomes.

Verification of RNA‐seq Results by Proliferation Marker Detection

To confirm the RNA‐seq results, we performed immunostaining on both PAB rat model samples at P7 and on human samples of pressure‐overloaded RVs (Table). The number of Ki67‐positive cardiomyocytes per section was 262.9±15.1 in the PAB group and 182.1±14.4 in the sham group (Figure 5A and ​and5B).5B). The number of pH3‐positive cardiomyocytes was 66.4±5.9 in the PAB group and 45.3±4.9 in the sham group (Figure 5C and ​and5D).5D). The percentage of pH3‐positive cardiomyocytes in sham and PAB groups was 0.412%±0.162% and 1.585%±0.223%, respectively (P<0.0001, n=10), and the percentage of Ki67‐positive cardiomyocytes in sham and PAB was 2.563%±0.381% and 7.628%±1.468%, respectively (P<0.0001, n=10) (Figure S4). The number of aurora B‐positive cardiomyocytes was 3.8±0.9 in the PAB group and 0.4±0.5 in the sham group (Figure 5E and ​and5F).5F). In addition to immune staining, we also used synthetic nucleoside uptake to confirm the above results. As shown in Figure S5, at P7 the number of EdU‐positive cardiomyocytes per section was 555.9±64.6 in the PAB group and 286±53.8 in the sham group.

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Figure 5

Immunofluorescence staining confirms that pressure overload greatly promotes RVCM proliferation.

A, Immunofluorescence staining for Ki67 (green), cardiac troponin T (red), and DAPI (blue) in rats at P7. B, Quantification of Ki67‐positive cardiomyocytes at P7, n=10 samples. C, Immunofluorescence staining for pHH3 (green), cTnT (red), and DAPI (blue) in rats at P7. Arrows indicate proliferating cardiomyocytes. D, Quantification of pHH3‐positive cardiomyocytes, n=10 samples. E, Immunofluorescence staining for aurora B (green), cTnT (red), and DAPI (blue) in rats at P7. F, Quantification of aurora B‐positive cardiomyocytes at P7. G, Representative Ki67‐positive cardiomyocytes from patients with RV pressure overload. Ki67 (green), cardiac troponin T (red), and DAPI (blue). Arrows indicate proliferating cardiomyocytes. H, Representative pHH3‐positive cardiomyocytes from patients with RV pressure overload. pH3 (red), cTnT (white), and DAPI (blue). Arrows indicate proliferating CMs. I, Quantification of Ki67/pHH3‐positive cardiomyocytes in human samples. J, Representative Ki67‐positive cardiomyocytes from patients with RV pressure overload. Aurora B (green), cTnT (red), and DAPI (blue). K, Quantification of aurora B‐positive cardiomyocytes in human samples. CMs indicates cardiomyocytes; cTnT, cardiac troponin T DAPI, 4′,6‐diamidino‐2‐phenylindole; PAB, pulmonary artery banding; pHH3, phospho‐histone H3; RV, right ventricle; and RVCM, right ventricular cardiomyocyte.

In the human RV samples, the number of Ki67‐positive cardiomyocytes per section in the non‐overload group was 14.6±3.5 and in the overload group it was 30±3.2 (P<0.0001, Figure 5G and ​and5I).5I). The number of pH3‐positive cardiomyocytes per section in the nonoverload group was 4.3±1.4 and in the overload group it was 10.5±2.1 (P<0.0001, Figure 5H and ​and5I).5I). The number of aurora B‐positive cardiomyocytes was 1.5±0.5 in the overloaded group while there were none observed in the nonoverload group (Figure 5J and ​and5K).5K). RNA‐seq data ({"type":"entrez-geo","attrs":{"text":"GSE139561","term_id":"139561"}}GSE139561) showed that the average fragments per kilobase of transcript sequence per million of AURKB in the PAB group was 9.54±1.07 and in the sham group it was 4.21±0.42. qRT‐PCR results showed that the relative mRNA level of AURKB increased ≈10‐fold (Figure S2).

These results suggested that pressure overload indeed profoundly promoted and extended the rate of the proliferation of RVCMs both in humans and rats.

Effect of Pressure Overload on RVCM Proliferation Diminishes With Age

Another important issue is the age‐associated proliferation ability of cardiomyocytes.11, 23 We examined the proliferation status of cardiomyocytes at P3 and P14. We found that the number of Ki67‐positive RVCMs in the sham group at P3, P7, and P14 was 205.6±20.6, 182.1±14.4, and 26.8±2.7, respectively, and the number of pH3‐positive RVCMs in the sham group at P3, P7, and P14 was 54±6.3, 45.3±4.9, and 13.6±1.7, respectively (Figure 6A through C). When these RVCMs were subjected to pressure overload, we found that the Ki67‐fold change (relative to the sham group) at P3, P7, and P14 was 2.4±0.2, 1.5±0.2, and 1.1±0.2, respectively, and the pH3‐fold change at P3, P7, and P14 was 2.3±0.6, 1.5±0.2, and 1.0±0.2, respectively (Figure 6A through C). EdU uptake experiments showed that the number of EdU‐positive RVCMs in the sham group at P3, P7, and P14 was 498.5±63.1, 286±53.8, and 193.7±30.4, respectively, and in the PAB group at P3, P7, and P14 were 826±72.8, 555.9±64.6, and 251.6±30.4, respectively (Figure S5). These data demonstrate that the effects of pressure overload on the promotion of RVCM proliferation diminish with age.

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Figure 6

Pressure overload promotes RVCM proliferation associated with rat age.

Dash LINE indicates scale bar. A, 25 μm; B, 100 μm, above panel. Arrow indicates proliferating CMs. A, Immunofluorescence staining for Ki67 (green), cardiac troponin T (red), and DAPI (blue) in rats at P3. B, Immunofluorescence staining for pH3 (green), cardiac troponin T (red), and DAPI (blue) in rats at P14. C, Quantification of Ki67/pHH3‐positive cardiomyocytes at different ages. DAPI indicates 4′,6‐diamidino‐2‐phenylindole; PAB, pulmonary artery banding; pHH3, phospho‐histone H3; and RVCM, right ventricular cardiomyocyte.