Comparative bioinformatics analysis of transcriptomes between β-aminopropionitrile-induced aortic dissection murine model and human aortic dissection

Introduction

Aortic dissection (AD) is a fatal vascular disease characterized by the separation of the intima from the media caused by an intimal tear and resulting in aortic bleeding or blood flow into the aortic wall forming a false lumen which rapidly expands within the aorta (1,2). AD usually causes sudden persistent intense pain. The mortality rate associated with aortic rupture secondary to acute AD is as high as 90% (3). End organ malperfusion caused by AD is also life-threatening (4,5). The exact mechanism of AD formation is not fully understood. Therefore, a better understanding of the molecular mechanisms and pathophysiology of AD will aid the development of new diagnostic and therapeutic strategies and improve clinical outcomes.

One factor that greatly restricts research into the mechanism of action of AD is that clinical samples are difficult to obtain. Multiple AD experimental animal models have been generated to mimic the spontaneous development of AD, investigate its pathogenesis, and identify novel therapeutic targets and measurements, including drug- or chemical-induced experimental models, genetically modified experimental models, and surgically or invasively induced experimental models (6-8). In recent years, β-aminopropionitrile (BAPN)-induced AD in rodents has been widely used in basic research (9-11). This model is simple, is inexpensive, and can be implemented without genetic engineering, which provides a good platform for exploring the pathogenesis of AD and drug modification.

This study aimed to reveal transcriptional changes in BAPN-induced AD murine model in detail for the first time. It also aimed to compare the similarities and differences between the murine AD model and human AD models in the transcriptome. We present this article in accordance with the ARRIVE reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-23-981/rc).

Methods

Murine AD model and sample collection

Male C57BL/6J mice (3 weeks old; mean 10±2 g each) were purchased from Vital River Laboratory Animal Technology Co., Ltd. (Beijing, China). The mice were housed under controlled conditions of 55%±5% humidity and 22±2 ℃ under a 12 hours light/dark cycle with ad libitum access to food and water. All animals underwent adaptive feeding for 3 days before further treatment. All experiments involving animal treatment were performed in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals, and the protocol was approved by the Ethics Committee of Union Hospital affiliated with Huazhong University of Science and Technology (No. 2636).

All mice were randomly divided into two groups (n=5) by drawing lots: control group and AD group. The mice were fed a normal diet and freshly prepared BAPN solution (Sigma-Aldrich, St. Louis, MO, USA) dissolved in drinking water (1 g/kg/day) for 4 weeks to induce AD as described previously (12). The control group was not treated with BAPN. Mice surviving at the end of the experiment were sacrificed with an overdose of sodium pentobarbital, and tissue samples were collected for further analysis. Five AD tissues and five control tissues were subjected to RNA extraction. One control sample was discarded because its RNA concentration did not meet the standards. We then constructed the library and subsequently sequenced these nine samples (four controls, five ADs).

Ultrasound observation

The ultrasound observation was carried out on the 28^th day for survival mice through a high-resolution Vevo 2100 microimaging system with an MX400 linear array transducer at 30 MHz (VisualSonics, Toronto, Canada). A thoracic aortic diameter increase of ≥50% was considered as aneurysm secondary to the dissection.

RNA extraction, library preparation, and sequencing

Total RNA was extracted using TRIzol reagent (cat. No. AG21101; Accurate Biotechnology Co., Guangzhou, China) as described by Chomczynski et al. (13).

Two micrograms of total RNA were used for stranded RNA sequencing library preparation using a KCTM Stranded mRNA Library Prep Kit for Illumina^® (Catalog No. DR08402; Wuhan SeqHealth Co., Ltd., Wuhan, China) according to the manufacturer’s instructions. Polymerase chain reaction products corresponding to 200–500 base pairs were enriched, quantified, and sequenced on a NovaSeq 6000 sequencer (PE150 model; Illumina, Wuhan, China). Raw sequencing data were first filtered using Trimmomatic tool (version 0.36), low-quality reads were discarded and the reads contaminated with adaptor sequences were trimmed, and clean data were mapped to the reference genome of Mus musculus using STRA software (version 2.5.3a) with default parameters. Reads mapped to the exon regions of each gene were counted using featureCounts (Subread-1.5.1; Bioconductor, Massachusetts, USA), and reads per kilobase of exon per million reads mapped were calculated. Raw RNA-seq data of the murine AD model were analyzed.

Murine and human AD data sources

The murine RNA-seq data in this study can be found in National Center for Biotechnology Information (NCBI)’s Sequence Read Archive (accession no. PRJNA903222; http://www.ncbi.nlm.nih.gov/bioproject/903222). The dataset contained nine samples (four controls, five ADs).

The human AD dataset (GSE147026) was extracted from the NCBI Gene Expression Omnibus database (https://www.ncbi.nlm.nih.gov/geo/). Raw bioinformatics RNA-seq gene counts were obtained from GSE147026 using the GPL24676 platform (Illumina NovaSeq 6000; Homo sapiens). The dataset contains 10 samples (five controls, five ADs).

Differential expression analysis

We analyzed the differentially expressed genes (DEGs) using the DESeq package of R software (version 4.0.1; https://www.rproject.org/) (14). The significant criteria for identifying DEGs with a low false discovery rate were set as adjusted P values <0.001 and |log2(fold change)| ≥1.

Functional and pathway enrichment analysis

Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to analyze the functional enrichment of the DEGs associated with the biology underlying AD. GO terms with corrected P values <0.05 and KEGG pathways with P values <0.05 were defined as significant enrichments. The R packages ggplot2, enrichplot, and GOplot were used to create the bubble plot and circle plot of the GO and KEGG pathway annotation.

Construction of protein-protein interaction (PPI) network and identification of hub genes

A PPI network based on the DEGs was constructed using STRING (https://string-db.org/), with the cut-off standard as a combined score >0.95. Subsequently, PPI networks were exported from STRING and imported into Cytoscape. To identify the hub genes, we ranked all listed genes according to their degrees calculated in the PPI and co-expression networks. The hub genes in the PPI network were defined as those with the highest degree of connectivity. The Molecular Complex Detection (MCODE) app was used to identify significant modules in the PPI network.

Morphometric and immunohistochemical analysis

The tissues were fixed in 4% paraformaldehyde for 48 hours, transferred to 70% ethanol, processed in a graded series of ethanol solutions, embedded in paraffin, and cut into 3-µm-thick sections. The slices were dewaxed, dehydrated, and repaired using standard methods. The slices were blocked and treated with the target primary antibody and goat anti-rabbit/mouse immunoglobulin G. The slices were then dripped with Streptomyces ovalbumin protein labeled with horseradish peroxidase, and the slices were developed using diaminobenzidine. Hematoxylin was used as the counterstain. Gene expression was calculated as the integrated optical density of the yellow-brown-stained area using Image Pro Plus. The integrated optical density value was divided by the area of the target distribution region to obtain the average optical density.

Identification of potential drugs

Enrichr is a comprehensive web-based tool used for gene set enrichment analysis (15). It currently contains a large genome library available for analysis and download, containing 180–184 annotated gene sets from 102 gene set libraries. Drug Gene Interaction Database version 3.0.2 (https://www.dgidb.org) is a resource of drug-targeted and -sensitive genomes along with drug-gene interactions (16). To explore potential drugs, DSigDB in the Enrichr online database was used to analyze the potential drug targets of the overlapping DEGs.

Statistical analysis

Data were presented as mean ± standard deviation (SD). All data were analyzed using GraphPad Prism 8 software (GraphPad Software, La Jolla, CA, USA). Analysis of variance with repeated measures followed by a post hoc Bonferroni correction or Student’s two-sided t-test was used. For all comparisons, P values of <0.05 were considered statistically significant.

Results

Pathological changes and validation of murine AD model

AD and expansion were clearly observed in the murine model. Macroscopic pictures and ultrasound images showed the dissection aneurysm in BAPN-induced murine model (Figure 1A,1B). Hematoxylin and eosin staining showed tearing of the aortic wall and thrombi in the false lumen (Figure 1C). Elastica van Gieson (EVG) staining confirmed extensive elastic fiber fragmentation and depletion as well as loss of smooth muscle cells (Figure 1D). All of these pathological changes were similar to those observed in humans.

Figure 1 BAPN induced animal model reproduced the pathological changes of aortic dissection. (A) Representative images showing macroscopic features of isolated mouse aorta after vehicle or BAPN treatment; black arrow indicates location of AD; (B) representative images showing dissection aneurysm examined with ultrasound; white arrow indicates enlarged lumen of AD; (C) representative HE staining showing aortic wall tears and thrombosis after BAPN administration; (D) representative image of EVG staining confirmed extensive elastic fiber fragmentation. AD, aortic dissection; BAPN, β-aminopropionitrile; HE, haematoxylin and eosin; EVG, elastica van gieson.

Gene expression levels in murine AD model

Principal component analysis (PCA) and principal coordinate analysis (PCoA) cluster analysis indicated significant differences between the AD and control groups (Figure 2A,2B). A total of 2,060 DEGs were identified, of which 1,467 were significantly upregulated and 593 were significantly downregulated (Figure 2C). We conducted GO enrichment analysis of the functions of the DEGs, including biological processes, cellular components, and molecular functions, to reveal the AD-related functional annotated terms. The top 10 are listed in Figure 2D.

Figure 2 Difference in gene expression between AD mice and control mice. (A) PCA analysis was performed on the relative gene expression of AD and control mice. The dashed circles delineate samples from AD and control mice, green represents AD mice and orange represents control mice. Each point represents a sample; (B) PCoA analysis of the relative gene expression of AD and control mice shows that the two can be distinguished significantly. The dashed circles delineate samples from AD and control mice, green represents AD mice and orange represents control mice. Each point represents a sample; (C) the volcano graph shows the relative gene expression levels of mice. The red dots indicate genes whose expression levels increased (n=1,467) in the AD group, and the blue dots indicate genes whose expression levels decreased (n=593) in the AD group; (D) GO enrichment analysis of differentially expressed genes in mice. We divide the pathways into three categories according to the annotation of GO database: BP, CC and MF. The size of the dots indicates the amount of gene enrichment in the pathway. Gene Ratio represents the ratio of the genes included in the pathway divided by the number of all genes. AD, aortic dissection; PCA, principal component analysis; PCoA, principal coordinate analysis; GO, gene ontology; BP, biological process; CC, cellular components; MF, molecular function.

GO enrichment analysis revealed that DEGs were significantly enriched in biological processes, which involved positive regulation of cytokine production, positive regulation of cell adhesion, leukocyte migration, regulation of cell-cell adhesion, leukocyte cell-cell adhesion, and positive regulation of response to external stimuli. The DEGs also had a certain degree of enrichment in cellular components, including collagen-containing extracellular matrix, membrane raft, membrane microdomain, and receptor complex. The DEGs were enriched in molecular functions such as receptor ligand activity and cell adhesion molecule binding (Figure 2D).

Transcriptomes in murine AD model versus human AD

A total of 463 overlapping DEGs were identified (Figure 3A), of which 436 were significantly upregulated and 27 were significantly downregulated. Top 10 are listed in Table 1. The top 10 DEGs that were up- and down-specific for the murine and human samples are shown in Table 2. Wilcoxon’s rank-sum test of the relative expression data was performed for these 463 genes, which exhibited similar fold differential gene expression (Figure 3B). The heat map of the relative abundance of the 463 genes indicated that the murine AD model and human samples could be clustered accurately and had a similar clustering trend (Figure 3C).

Figure 3 Aorta genes similar in the BAPN-induced AD mice and humans with AD at the transcriptome level. (A) There are 463 differentially expressed genes in human AD aorta and BAPN-induced mouse aorta. Here, the dotted ellipses colored in red stands for 1,677 homologous genes can be seen in mice, and the dotted ellipses colored in blue stands for 1,790 differentially expressed genes in the human tissues; (B) the differentially expressed genes of humans and mice are very close in terms of relative expression levels. The size of the dots indicates the amount of gene enrichment in the pathway. Gene ratio represents the ratio of the genes included in the pathway divided by the number of all genes; (C) tendency of clustering between healthy and AD samples between human and animal model. FC, fold change; NS, no significant; BAPN, β-aminopropionitrile; AD, aortic dissection.

Analysis of the 463 co-expressed genes in the KEGG pathway revealed that the cytokine-cytokine receptor interaction, tuberculosis, and phagosome pathways were significantly enriched and may interact with other pathways (Figure 4A,4B).

Figure 4 Analysis of the co-expressed genes in the KEGG pathway. (A) Enrichment analysis of the KEGG pathway shows that many of these differentially expressed genes are involved in important physiological processes related to the AD process; (B) the ten pathways with the highest degree of enrichment in the KEGG pathway. The size of the dots indicates the amount of gene enrichment in the pathway. Gene ratio represents the ratio of the genes included in the pathway divided by the number of all genes. KEGG, Kyoto Encyclopedia of Genes and Genomes; AD, aortic dissection.

We performed GO enrichment analysis of the murine- and human-specific DEGs. Human-specific DEGs showed the highest enrichment in T cell activation, muscle system processes, and cell-cell adhesion regulation. Meanwhile, in the murine-specific DEGs, positive regulation of cell adhesion, leukocyte migration, and regulation of response to external stimuli had the highest enrichment degree (Figure 5A,5B).

Figure 5 GO enrichment analysis of the murine- and human-specific DEGs. (A) GO enrichment analysis was performed on DEGs found only in human, and the results showed the top 10 (if the number of differential pathways was greater than or equal to 10) pathways in each physiological process. The size of the dots indicates the amount of gene enrichment in the pathway. Gene ratio represents the ratio of the genes included in the pathway divided by the number of all genes; (B) GO enrichment analysis of DEGs found only in mouse shows the top 10 (if the number of differential pathways is greater than or equal to 10) pathways in each physiological process. The size of the dots indicates the amount of gene enrichment in the pathway. Gene ratio represents the ratio of the genes included in the pathway divided by the number of all genes. GO, gene ontology; DEGs, differentially expressed genes; BP, biological process; CC, cellular components; MF, molecular function.

To further demonstrate the differences in physiological processes involved in murine- and human-specific DEGs, we performed a network analysis of all enriched GO pathways (Figure S1).

PPI network and module construction and hub gene analyses

To explore the interplay among DEGs in the different groups, PPI networks were built using the STRING tool with confidence >0.95 as the cut-off criterion (Figure 6A). Furthermore, according to the topological property analysis of the PPI network, we found that CDC20, CCNB2, and CCNB1 were the top three nodes with the greatest number of connections with other nodes (Figure 6B). Using the MCODE app, we found three clusters in the network. The first cluster, which had the highest score, contained nine nodes and 31 edges (Figure 6C). The second cluster, which contained four nodes and six edges, also exhibited a strong connection (Figure 6D). The third cluster contained three nodes and three edges (Figure 6E). These findings strongly suggest that these hub genes play vital roles in the pathogenesis of AD.

Figure 6 PPI network and hub genes in co-expressed DEG. (A) PPI network in co-expressed DEG. Orange indicates core gene, red indicates up-regulated genes, and blue indicates down-regulated genes; (B) hub genes in co-expressed DEG; (C-E) the three clusters which had the highest score. PPI, protein-protein interaction; DEG, differentially expressed gene.

Hub gene validation

Owing to the complexity of obtaining clinical samples of human AD, we examined the protein levels of hub genes in the murine AD model tissues. Immunohistochemistry was used to assess the expression of the top three hub genes: CDC20, CCNB2, and CCNB1 (Figure 7). The protein expression levels of these genes were significantly increased in the AD group.

Figure 7 Validation of hub genes in AD animal model. (A) Immunohistochemical staining for CDC20; (B) immunohistochemical staining of CCNB1; (C) immunohistochemical staining of CCNB2; (D-F) the quantitative analysis of hub genes. Cells staining brown are positive for hub genes. Two-sample t-test was performed (N=3). Each bar represents mean ± SD. *, P<0.05, significant differences. Scale bar is 100 µm. AD, aortic dissection; IOD, integrated optical density; SD, standard deviation.

Identification of potential drugs

Assessment of protein-drug interactions is essential for the identification of important therapeutic targets for diseases (17,18). Targeting the overlapping DEGs in the murine and human AD models, we identified 10 possible drug molecules using Enrichr based on transcriptome signatures from the DSigDB database. The top 10 chemical compounds were extracted based on their P values (Table 3).

Discussion

AD is a cardiovascular emergency with a high mortality rate. The most common causes of AD are arterial hypertension, connective tissue disease, vascular injury, and atherosclerosis (19-21). The incidence of AD is as high as 5 per 100,000 people, a rate that has increased dramatically over the past decade (22-25). Seasonal variation has an important effect on the incidence of AD, which increases significantly during winter (26). In addition, heavy physical labor and emotional excitement can increase blood pressure and induce AD (27). The pathogenesis of AD includes phenotypic switching and death of vascular smooth muscle cells, abnormal degradation of the extracellular matrix, endothelial dysfunction, and immune abnormalities (28). Although research on the etiology and mechanism of AD has made some progress, the exact mechanism of AD formation is not fully understood. Therefore, a better understanding of the molecular mechanisms of AD will aid our understanding of its pathophysiology, develop new diagnostic and therapeutic strategies, and improve clinical outcomes.

At present, a variety of experimental animal models of AD have been used to simulate the spontaneous development of AD, study its pathogenesis, and identify new therapeutic targets and methods for it; these mainly include surgical-induced experimental models and experimental models targeting pathogenic genes (compound induction or gene editing technology) (8). The existing microsurgery-induced AD animal models are established by surgical or intradural approaches to achieve the same appearance as of dissection. However, this model is similar to traumatic or iatrogenic AD in pathophysiological aspects but quite different from the occurrence and development of spontaneous AD. In addition, the establishment of this type of model depends on the operator’s surgical skills, which has the disadvantages of complex operation, difficulty in establishing modeling standards, and poor repeatability. Here we constructed a murine model of BAPN-induced AD. BAPN, a lysyl oxidase inhibitor, is the most widely used chemical compound for inducing AD in growth period mice and rats as it inhibits the cross-linking of collagen fibers (29). This model is simple, inexpensive, and can be implemented without genetic engineering of animals, which provides a good platform for exploring the pathogenesis and drug modification of AD.

This study constructed a murine model of BAPN-induced AD. On the one hand, anatomical dissection showed that, after a 4-week BAPN intervention, the mice showed obvious thrombolysis of the false lumen and dilation of the inner blood vessel walls. In contrast, hematoxylin and eosin staining showed blood clots in the tearing aortic wall after BAPN administration. EVG staining showed elastic fiber layer rupture and smooth muscle cell loss in the BAPN-treated group. These results again show that the pathological aspects of BAPN-induced AD are similar to those of spontaneous dissection. In the subsequent sequencing analysis, we observed an obvious clustering effect between the disease and normal groups of this model through PCA, which proved considerable model stability.

A total of 2,060 DEGs were identified and GO enrichment analysis showed that DEGs were significantly enriched in the immune and inflammatory pathways, including positive regulation of cytokine production, positive regulation of cell adhesion, leukocyte migration, regulation of cell-cell adhesion, leukocyte cell-cell adhesion, and other pathways.

We subsequently analyzed the intersecting genes of a BAPN-induced animal model and human AD. The homologous genes in humans and animals are highly conserved. In contrast, the differential genes obtained from disease and animal models helped us verify the important role of this molecule in AD. Among these intersecting genes, we found that many play a preliminary role in basic research on interlayers. For example, the most differentiated gene, spp1, expresses a bone-specific salivary protein in endothelial and smooth muscle cells and is upregulated in fibrosis, autoimmune diseases, and atherosclerosis. A study has shown that serum and local osteopontin expression levels are significantly increased in AD patients. It has also shown that osteopontin affects the progression of the interlayer by enhancing matrix metalloprotein (MMP)-2 gene expression and activity in human vascular smooth muscle cells and affecting extracellular matrix secretion (30). The enrichment analysis revealed the highest degree of enrichment in cytokine-cytokine receptor interactions. Cytokines are secreted proteins produced after immune stimulation. A variety of cytokines, including interleukin (IL), interferon, the tumor necrosis factor superfamily, colony-stimulating factors, chemokines, and growth factors, play an important role in AD directly or indirectly by affecting smooth muscle cell function (17,31). For example, Zhang et al. reported that IL-1β may be involved in AD through the upregulation of MMP-9 and stromal cell apoptosis (32). Data from clinical trials and animal studies indicated that elevated IL-6 mRNA levels in the circulation and aorta of patients with AD (33-35) downregulated IL-6 expression and affected the phenotypic transition of the smooth muscle by inhibiting the vascular smooth muscle cell contraction proteins, α-smooth muscle actin, and SM22α (36).

CXCL1, which was highly expressed in an angiotensin II-induced murine AD model, promotes neutrophil infiltration and activation, upregulates local IL-6 expression, and leads to aortic dilation and rupture (37).

In subsequent construction of the PPI network, the top three genes were CDC20, CCNB2, and CCNB1, all of which are directly or indirectly involved in cell cycle regulation. Apoptosis and proliferation are closely related. Cell cycle regulators can affect cell division and programmed cell death (38). We confirmed the difference in correlation analysis between the disease and normal group through immunohistochemical verification of animal models, but more basic studies are needed to verify the specific mechanism of action.

To predict the potential for the effective treatment of AD, we used the Enrichr to identify therapeutic agents that might reverse the abnormally high expression of AD-related differential genes. Some of these drugs have shown promising results in basic research. For example, calcitriol (1,25-dihydroxyvitamin D3) is the active form of vitamin D3, a fat-soluble vitamin that promotes calcium absorption (39). In apoE^-/- mice, oral calcitriol reduced vascular wall macrophage infiltration and neovascularization; significantly decreased MMP-2, MMP-9, and chemokine expression; and reduced the incidence of interlayer abdominal aortic aneurysm independent of systolic blood pressure or plasma cholesterol concentration (40). Martorell et al. reported that tamibarotene can reduce the damage response pathway and inflammatory pathway activation after inflammatory stimulation in smooth muscle cells by inhibiting the transcription factor KLF5 (40). Trocomatostatin enhances vascular repair in human endothelial progenitor cells and stem cells by increasing TAL1-dependent gene expression (41). However, the role of these drugs or molecular compounds in AD requires further exploration.

Our study had the following limitations. First, the sample size of the animal model was small. In the RNA extraction process, we found that the RNA concentration of a normal sample was low and was thus discarded. To reduce batch effects, we did not add a new control sample. Second, in the hub gene verification process, due to the difficulty acquiring human AD samples, especially normal aortic samples, we chose to use tissue samples from a murine model, which limited the study. Moreover, we do not know the specific mechanism of action of the screened hub genes. We will further explore the specific mechanism of action of these molecules using gene editing technology.

Conclusions

This study revealed transcriptional changes in a murine BAPN-induced AD model versus human AD transcriptome. Furthermore, we identified the important hub genes, related pathways, and potential drugs by analyzing the overlapping DEGs between human AD and the murine AD model. Our results provide a basis for the further identification of potential molecular markers for diagnosing and treating AD.

Acknowledgments

Funding: This work was supported by the National Natural Science Foundation of China (No. 81873529).

Footnote

Reporting Checklist: The authors have completed the ARRIVE reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-23-981/rc

Data Sharing Statement: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-23-981/dss

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-23-981/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-23-981/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All experiments involving animal treatment were performed in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals, and the protocol was approved by the Ethics Committee of Union Hospital affiliated with Huazhong University of Science and Technology (No. 2636).

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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