
==== Front
Heliyon
Heliyon
Heliyon
2405-8440
Elsevier

S2405-8440(24)10416-1
10.1016/j.heliyon.2024.e34385
e34385
Research Article
CircRNA-Phf21a_0002 promotes pyroptosis to aggravate hepatic ischemia/ reperfusion injury by sponging let-7b-5p
Jiang Peng bc1
Li Xinqiang bc1
Shen Yuntai bc
Luo Lijian a
Wu Bin a
Teng Dahong a
Wang Jinshan a
Muhammad Imran bc
Xu Qingguo c
Li Shipeng shipengli2010@163.com
d⁎⁎⁎
Zhang Bin 18661808021@126.com
c⁎⁎
Cai Jinzhen caijinzhen@qdu.edu.cn
abc⁎
a Organ Transplant Center, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
b The Institute of Transplantation Science, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China
c Organ Transplantation Center, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China
d Department of Hepatopancreaticobiliary Surgery, Henan Provincial People's Hospital, Zhengzhou University, Zhengzhou, China
⁎ Corresponding author. Organ Transplant Center, Fujian Medical University Union Hospital, Fuzhou, Fujian, China. caijinzhen@qdu.edu.cn
⁎⁎ Corresponding author. 18661808021@126.com
⁎⁎⁎ Corresponding author. shipengli2010@163.com
1 These authors contributed equally to this work and should be considered co-first authors.

15 7 2024
30 8 2024
15 7 2024
10 16 e3438525 5 2023
24 6 2024
9 7 2024
© 2024 Published by Elsevier Ltd.
2024

https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Hepatic ischemia‒reperfusion injury is a common injury in liver surgery and liver transplantation that can lead to liver function damage, including oxidative stress, apoptosis, autophagy and inflammatory reactions. Pyroptosis is a type of inflammatory programmed cell death that has been implicated in ischemia‒reperfusion injury-associated inflammatory reactions. Although circular RNAs can regulate cell death in hepatic ischemia‒reperfusion injury, their relationship with pyroptosis remains unclear. Therefore, this study aimed to investigate the effect of circular RNA on pyroptosis in hepatic ischemia‒reperfusion injury. We constructed a mouse hepatic ischemia‒reperfusion injury model for circular RNA sequencing and obtained 40 circular RNAs with significant differential expression, of which 39 were upregulated and 1 was downregulated. Subsequently, the endogenous competitive RNA network was constructed using TarBase, miRTarBase, TargetScan, RNAhybrid, and miRanda. Gene Set Enrichment Analysis, Kyoto Encyclopedia of Genes and Genomes and Gene Ontology functional analyses of downstream target genes revealed that circRNA-Phf21a_0002 might affect pyroptosis by regulating the mTOR signaling pathway and Bach1 by sponging let-7b-5p. The overexpression plasmid upregulated the expression of circRNA-Phf21a_0002 in a hypoxia/reoxygenation model, which aggravated pyroptosis in AML12 cells and apoptosis and necrosis of hepatocytes. Next, we investigated the underlying mechanism and found that circRNA-Phf21a_0002 enabled the expression of Bach1 through sponging of let-7b-5p. The aggravation of pyroptosis via overexpression of circRNA-Phf21a_0002 was reversed by let-7b-5p mimics in hypoxia/reoxygenation-subjected AML12 cells. Collectively, our study clarifies that circRNA-Phf21a_0002 aggravates the pyroptosis of hepatocytes related to ischemia-reperfusion by sponging let-7b-5p. These findings provide new molecular mechanisms and novel biomarkers for follow-up treatment.

Highlights

• By utilizing bioinformatics and sequencing technologies, the expression profile and biological functions of circular RNAs have been elucidated, particularly their role in the competitive endogenous RNA network.

• Experimental validation has shown that upregulation of circRNA-Phf21a_0002 exacerbates hepatocellular pyroptosis in an in vitro model of hepatic ischemia-reperfusion injury.

• CircRNA-Phf21a_0002 has been shown to modulate pyroptosis by functioning as a ceRNA to sponge let-7b-5p molecules in an in vitro model of hepatic ischemia-reperfusion injury.

• Further validation suggests the potential of circRNA-Phf21a_0002 in regulating hepatic ischemia-reperfusion injury through the let-7b-5p/Bach1 network.

Keywords

Pyroptosis
Hepatic ischemia‒reperfusion injury
Circular RNA
Endogenous competitive RNA
Oxidative stress
==== Body
pmcAbbreviations

IRI ischemia-reperfusion injury

GSDMD gasdermin D

circRNA circular RNA

ceRNA competing endogenous RNA

GSEA Gene set enrichment analysis

KEGG Kyoto Encyclopedia of Genes and Genome

GO Gene Ontology

PCA principal component analysis

ALT alanine aminotransferase

AST aspartate aminotransferase

IHC immunohistochemistry

OE overexpression

VEC negative control

FISH fluorescence in situ hybridization

MREs miRNA response elements

BP biological process

CC cellular component

MF molecular function

H/R hypoxia/reoxygenation

1 Introduction

Hepatic ischemia-reperfusion injury (IRI) is a common and challenging issue in liver surgery and transplantation that can lead to graft dysfunction and primary dysfunction [1,2]. The mechanisms underlying hepatic IRI are complex and involve adaptive immune responses, inflammatory responses, oxidative stress, and cell death [3]. There is a critical need to attenuate hepatic IRI by targeting these mechanisms.

Pyroptosis has recently been found to play a crucial role in IRI. Unlike other cell death types, pyroptosis involves cell swelling and rupture, indicating the formation of many small bubbles (pyroptosomes) [4]. Caspase-1 activation is essential throughout this process. In the canonical pathway, when Caspase-1 is activated, it causes gasdermin D-N (GSDMD-N) formation and perforation at the cell membrane, yielding cleaved IL-18 and cleaved IL-1β [5]. Pyroptosis regulates many diseases. For example, GSDMD can promote pyroptosis and aggravate myocardial IRI [6]. Hepatic stellate cells become activated after hepatocyte pyroptosis, leading to liver fibrosis [7]. Pyroptosis can also be activated by the AMPK/mTOR/TFEB signaling pathway and PI3K/AKT/Foxo1 signaling pathway [8,9]. Noncoding RNAs have also been implicated in the regulation of pyroptosis. For example, miR-30 d-5p in exosomes released by neutrophils can induce pyroptosis of macrophages in acute lung injury [10]. In addition, research has reported that circRNA-Calm4 regulates pyroptosis through the miR-124–3p/PDCD6 axis [11]. Therefore, it is of great significance to study the mechanism and regulatory pathway of pyroptosis in order to find new therapeutic strategies.

Circular RNAs (circRNA) are molecules with multiple biological functions that can play roles in regulating gene expression, RNA stability, miRNA activity and protein interactions in cells [12]. CircRNA can reduce the expression of miRNA through its endogenous competitive binding with miRNA, thus leading to an increase in the expression of target genes. CircRNAs are regulated predominantly through competing endogenous RNA (ceRNA) networks in multiple diseases, including hepatocellular carcinoma, nonalcoholic steatohepatitis, and liver injury [13,14]. However, there have been few studies of circRNAs in hepatic IRI.

Based on the above information, we hypothesized that circRNAs may regulate IRI by mediating pyroptosis in hepatocytes. Using comprehensive RNA sequencing, bioinformatics, and online databases, we found that circRNA-Phf21a_0002 (mmu-Phf21a_0002) was significantly downregulated in both the mouse hepatic IRI model and the HR of the AML12 cell model (Fig. 1). We found that circRNA-Phf21a_0002 can aggravate pyroptosis to promote hepatic IRI by sponging let-7b-5p. In addition, we identified Bach1 as a potential target gene that participates in the ceRNA network of circRNA-Phf21a_0002. Thus, the current study sheds light on the mechanism of circRNA-Phf21a_0002 in the regulation of pyroptosis in hepatic IRI and provides targets for future treatment and prevention.Fig. 1 Flow chart of circRNA analysis and validation in this study.

Fig. 1

2 Material and methods

2.1 Animals

Seven-week-old C57BL/6 J male mice were used for experiments obtained from SiPeiFu (Beijing, China). Each mouse weighed 20–25 g and was fed at the animal experimental center of Qingdao University (Qingdao, China) under a suitable temperature and circadian light/dark rhythm.

2.2 Animal hepatic IRI model

Male mice were selected as experimental animals and the modeling method was referenced from existing reports [[15], [16], [17]]. Mice were fasted from eating beginning 12 h before modeling. First, anesthesia was performed with 1 % pentobarbital (50 mg/kg). Then, an open laparotomy was performed, and the blood vessels separated. The liver was clamped using a vascular clip, allowing 70 % of the volume of the liver to develop ischemia. At the same time, a color change in the ischemic liver was observed. The vascular clip was released after 1 h of ischemia, and the abdomen was subsequently closed. The reperfusion times were 2 h, 6 h, 12 h, and 24 h, and a sham group was set up (n = 6) in which the abdomen was only opened and closed. At the end of the experiment, all the mice were sacrificed, and liver and blood samples were obtained. The hepatic IRI model used for RNA sequencing include the sham group (n = 3) and the 12 h reperfusion group (n = 3). All animal protocols were approved by the Institutional Ethics Committee.

2.3 Hematoxylin and eosin staining

For liver pathological evaluation, hematoxylin and eosin were used to stain the liver sections (4 μm). The level of liver IRI was estimated using Suzuki's score [18]. The criteria were as follows: vacuolization (none-0, minimal-1, mild-2, moderate-3, severe-4), congestion (none-0, minimal-1, mild-2, moderate-3, severe-4), and necrosis (none-0, single-cell necrosis-1, -30%-2, −60%-3, >60%-4).

2.4 RNA sequencing

Magzol Reagent (Magen, China) was used to extract and isolate total RNA from liver tissue. According to the instructions, Agilent 2200 TapeStation (Agilent Technologies, USA) and K5500 (Beijing Kaiao, China) were used to evaluate the quantity and integrity of the produced RNA, respectively. Ribosomal RNAs (rRNAs) and linear RNAs were removed from total RNA by using RNase R (Epicenter, USA) and a RiboCop rRNA Depletion Trial kit (LEXOGEN, Australia). Library preparation was performed using an Illumina RNA library preparation kit (NEB, USA). The quality of library products was evaluated using Qubit and Agilent 2200 TapeStation (Thermo Fisher Scientific, USA). Finally, the products were sequenced using Illumina (RiboBio, China). After sequencing was completed, the adapters in the raw data were removed by using Trimmomatic tools (version: 0.36). Before outputting the statistical results, FastQC software was used to check the read quality. The CIRI2 and CIRCexplorer2 algorithms were used to identify circRNAs. If both methods detected circRNAs, the circRNAs were considered identified. CircRNAs with expression differences, analyzed using the R package limma (version: 3.54.0) and edgeR (version: 3.40.1), were required for P values less than 0.05. Table S3 is the sequencing result of circRNA.

2.5 Data set acquisition and data processing

A mouse hepatic IRI data set GSE93034 [19] was obtained from the GEO database (https://www.ncbi.nlm.nih.gov/geo/). The R package limma (version: 3.54.0) [20] and edgeR (version: 3.40.1) [21] were used to process the data. Since the data used in this study are sourced entirely from online databases, there is no need for ethical approval from an ethics committee. The R package ggfortify (version: 0.4.15) was used to perform principal component analysis (PCA). We used the R package limma (version: 3.54.0) to determine differentially expressed mRNAs.

2.6 Construction of the circRNA–miRNA-mRNA network

The most significantly differentially expressed circRNAs (logFC >1.5, P value < 0.05) were used to construct a ceRNA network. For prediction of the relationships between circRNAs and miRNAs, the results from three databases, TargetScan, RNAhybrid, and miRanda, were intersected to obtain circRNA that might adsorb miRNA. The R package multiMiR (version: 1.20.0) [22] was used to predict downstream mRNAs, and a Venn diagram was used to show the intersection of three databases, TargetScan, miRTarBase, and TarBase. The circRNA-miRNA-mRNA network was then formed and visualized using Cytoscape (version: 3.8.2).

2.7 Pathway enrichment analysis

Gene set enrichment analysis (GSEA), Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway enrichment analysis were performed by the clusterProfiler (version: 4.6.0) [23] package in Bioconductor. For the host gene of each circRNA, the threshold of KEGG enrichment analysis was P value < 0.05. The threshold used for mRNA analysis in the ceRNA network was an adj.P value < 0.05. The R package ggplot2 (version 3.4.0) was used to visualize the enrichment analysis results.

2.8 Analyses of hepatic injury and cytokine levels

We detected the expression levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) in the serum of mice by using an automatic biochemical analyzer. In addition, to detect pyroptosis factors, the serum levels of IL-1 and IL-18 were measured using ELISA kits from Elabscience (Wuhan, China) following the kit instructions.

2.9 Real-time PCR

An AFTSpin Tissue/Cell Fast RNA Extraction Kit for Animal (Abclonal, China) was used to remove gDNA and extract total RNA. The total RNA was reverse transcribed to cDNA by ABScript III RT Master Mix (Abclonal, China). Real-time fluorescence quantification was performed using a QuantStudio Dx real-time fluorescence quantitative PCR instrument (Thermo Fisher Scientific, USA). The reaction solution (20 μL) contained the following: 10 μL of Genious 2X SYBR Green Fast qPCR Mix (Abclonal, China), 0.4 μL of forward primer (10 μm), 0.4 μL of reverse primer (10 μm), cDNA and ddH2O. The reaction procedure was 95 °C (3 min), 95 °C (5 s) and 60 °C (30 s) for 40 cycles. The circRNA, miRNA, and mRNA relative expression levels were determined using the standard 2-△△Ct method. The following primers were used for sequencing: circRNA-Phf21a_0002, circRNA-Smad4_0007, circRNA-Dennd1b_0009, let-7b-5p, Bach1, and Actb (β-actin). All primers used were provided by Sangon Biotech (Shanghai, China) (Table S1).

2.10 Western blotting

RIPA buffer (Solarbio, China) with phenylmethylsulfonyl fluoride (PMSF) (Solarbio, China) was used to lyse tissues and cells. Protein quantification was performed using a BCA Protein Assay Kit (Solarbio, China). The protein supernatant solution was mixed with SDS‒PAGE loading buffer (Solarbio, China) and boiled at 100 °C for 3–5 min. For protein samples (30 μg–50 μg), 8 %–15 % SDS‒PAGE gels were used for electrophoresis, and the proteins were transferred to PVDF membranes (Millipore, USA). Each membrane was blocked using 5 % nonfat powdered milk (Solarbio, China) and 1x TBST configured blocking solution. The antibodies used were Caspase-1 (Cell Signaling Technology, USA), Cleaved Caspase-1(Cell Signaling Technology, USA), IL-18 (Cell Signaling Technology, USA), IL-1β (Cell Signaling Technology, USA), Bax (Abclonal, China), and Bcl-2 (Abclonal, China). ECL Western Blotting Substrate (Glpbio, USA) was applied to measure the protein bands using a Tanon 5200 automated chemiluminescence image analysis system (Tanon, China), and the bands were analyzed in grayscale with ImageJ software.

2.11 TUNEL

Apoptosis detection in tissues and cells was performed using a One-step TUNEL In Situ Apoptosis Kit (Elabscience, China). The whole experimental process followed the instructions of the kit. After staining, samples were observed by using epifluorescence microscopy (Leica, Germany). Apoptotic rates were calculated using ImageJ.

2.11.1 Immunohistochemistry (IHC)

Mouse liver tissue paraffin samples were cut into 4 m thick sections. Sections were incubated with F4/80(Cell Signaling Technology, USA), Caspase-1/Cleaved Caspase-1 (Wanleibio, China) and IL-1β· (Wanleibio, China) at 4 °C overnight. The sections were then incubated with HRP-polymer-conjugated secondary antibodies and immunostained with a DAB commercial kit (Solarbio, China).

2.11.2 Cell culture and transfection

The mouse hepatocyte line AML12 was obtained from and cultured in DMEM/F12 (BI, USA) with 10 fetal bovine serum (BI, USA), penicillin streptomycin (Solarbio, China), dexamethasone (Solarbio, China), and insulin-transferrin-sodium selenite (Solarbio, China). Cell transfection was performed with the circRNA-Phf21a_0002 overexpression (OE) plasmid, negative control (VEC) plasmid (GeneChem, China), let-7b-5p mimic, negative control (GenePharma, China), and Lipofectamine 3000 (Life Technologies, Carlsbad, CA, USA).

2.11.3 Cell hypoxia/reoxygenation (H/R) model

Cell modeling was performed according to previous literature [24]. The previous medium was discarded first, and Hank's balanced salt solution (Solarbio, China) was added to the cell culture dish. Finally, we used mineral oil to cover the entire liquid surface, creating a deprived oxygen environment. After an hour of hypoxia, the cell models were replaced with complete medium and continued to be cultured at 37 °C under 95 % air and 5 % CO2.

2.11.4 Hoechst/PI staining assay

The Hoechst/PI staining assay was used to detect the effects of circRNA-Phf21a_0002 on pyroptosis and apoptosis. AML12 cells were seeded into 12-well plates, transfected with OE plasmid and negative control plasmid, and stained with Hoechst/PI (Solarbio, China).

2.11.5 Fluorescence in situ hybridization (FISH)

An Alexa Fluor 555-labeled probe was used to detect the localization of circRNA-Phf21a_0002 in cells. In brief, the AML12 cells were subjected to prehybridization buffer and hybridization buffer. The probe signals were examined using a FISH kit (Servicebio, China). The sequence of circRNA-Phf21a_0002 was 5′- CTCTCCAGTCCCCTGTTTCTCACTCAAA -3’.

2.11.6 Ribonuclease R assay

The total RNA, RNase R, reaction buffer, and RNase-free water were fixed into the reaction solution system for 15 min at 37 °C. Real-time qPCR was used to examine the relative expression levels of circRNA-Phf21a_0002, Phf21a and β-actin.

2.11.7 Actinomycin D assay

The stability of RNA was assessed by Actinomycin D (Glpbio, China). AML12 cells were treated with 1 μg/ml actinomycin D. Total RNA was extracted, and the relative expression levels of circRNA-Phf21a_0002 and mRNA Phf21a were measured.

2.11.8 Dual-luciferase reporter assay

We seeded HEK293T cells at a density of 1 × 10^4 cells per well in a 96-well plate. Subsequently, a co-transfection was performed using mimics of let-7b-5p and a dual-luciferase reporter plasmid, and Lipofectamine 3000 was utilized for transfection. After a 48-h incubation period, the culture medium was aspirated, and the cells were washed with PBS. Cell lysis was carried out using the Dual Luciferase Reporter Assay Kit (Vazyme, China). Firefly luciferase reporter gene activity was measured by adding the Luciferase Substrate. Subsequently, Renilla luciferase reporter gene activity was assessed by adding the Renilla substrate working solution. Finally, the relative luciferase activity was calculated.

2.11.9 Flow cytometry

H/R model was constructed using a 12-well plate, and the cell supernatant was collected after the reoxygenation phase. Cells were washed three times with 4 °C PBS, followed by digestion with trypsin without EDTA at 37 °C for 3 min. Subsequently, the digestion was terminated using the collected cell supernatant. After centrifugation at 1000g for 5 min, discard the supernatant. Use the Annexin V-FITC Apoptosis Detection Kit (Beyotime, China) and add 5 μl of Annexin V-FITC and 10 μl of PI to the suspension. Incubate at room temperature (20-25 °C) in the dark for 10–20 min, followed by placing the samples on ice. The samples were loaded onto the Navios flow cytometer (Beckman Coulter, USA) for analysis, and the results were analyzed using FlowJo 10 (Version 10.8.1). Prepared samples need to be used within 1 h.

2.11.10 Statistical analysis

Data analysis for this study was performed using GraphPad Prism 9.0 and R software (version 4.2.2). Differences between groups were analyzed by Student's t-test or one-way ANOVA. All data are indicated as the mean ± standard deviation. A two-tailed P value of <0.05 was considered to indicate statistical significance.

3 Results

3.1 Pyroptosis and liver injury in a mouse IRI model at different reperfusion time points

To study pyroptosis, we established a mouse hepatic IRI model at different reperfusion time points. The pathological examinations suggested that Suzuki's score gradually increased and peaked at 12 h after reperfusion (Fig. 2A and B). Similarly, the TUNEL assay showed the highest apoptotic ratio at 12 h after reperfusion (Fig. 2C and D). In addition, we measured the levels of the apoptosis-related genes Bcl-2 and Bax. Western blotting demonstrated that apoptotic levels after 12 h of reperfusion are higher than in the other groups (Fig. 2E). Pathological changes and serum AST and ALT levels were used to evaluate the degree of liver tissue damage (Fig. 2F and G). Consistent with the above results, the serum levels of AST and ALT were higher after a 12-h reperfusion compared to the other groups. Pyroptosis is associated with macrophages; therefore, we assessed the expression of F4/80 at different reperfusion time points (Fig. 2H). The results indicate a significant increase in F4/80 expression at 6 h and 12 h after reperfusion. To examine the levels of pyroptosis, we used Western blotting (Fig. 2I) and ELISA (Fig. 2J and K) and found that hepatic IR significantly increased pyroptosis at after 12 h of reperfusion. In the IHC results, the lower expression of mature IL-1b in the sham group may be associated with nonspecific staining and antibody concentration, while in the IR group, the expression of mature IL-1b is significantly elevated compared to the sham group (Fig. 2L–N).Fig. 2 Pyroptosis, liver injury, serological and pathological studies in a mouse hepatic IRI model. (A–B) Liver damage by HE staining and Suzuki's score (magnification × 100 and × 400). (C–D) TUNEL assay and apoptotic cell percentage counting in liver sections. (E) Western blot experiments and relative gray values were determined to analyze the expression of the apoptotic proteins Bax and Bcl-2 in liver tissues. (F–G) Serum levels of ALT and AST. (H) IHC of F4/80 at different reperfusion time points (magnification × 400). (I) Analysis of pyroptosis at different reperfusion time points in liver tissue using western blotting. (J–K) Serum levels of IL-1β and IL-18. (L–N) IHC of Caspase-1/Cleaved Caspase-1 (top) and IL-1β (bottom) to show hepatic pyroptotic alteration (magnification × 400). Between-group comparisons were conducted using Student's t-test, while comparisons among multiple groups were performed using one-way analysis of variance, all data represent the mean ± SD, n = 6/group. *p < 0.05, **p < 0.01, ***p < 0.001.

Fig. 2

3.2 Characterization of circRNA profiles in hepatic IRI

To investigate circRNAs in hepatic IRI, we performed RNA sequencing in a mouse hepatic IRI model. The results showed high correlation between samples (all above 0.85). This indicated that our sample quality and sequencing results were reliable (Fig. 3A). PCA showed that the sham group and IR group had a large difference, which indicated that circRNAs in IR had a significant difference (Fig. 3B). After differential expression analysis, we obtained 375 differential circRNAs (P value < 0.05), 40 of which were more significant (including 39 downregulated and 1 upregulated, logFC >1.5, P value < 0.05) (Fig. 3C and D). The host genes of circRNAs may play some functional roles. KEGG analysis was performed on host genes of differential circRNAs, which showed major enrichment in the FoxO signaling pathway and AMPK signaling pathway (Fig. 3E).Fig. 3 Analysis of circRNA sequencing. (A) Correlation analysis between each data point. R2 > 0.8 was regarded as a high correlation. (B) PCA of the sham and IR groups revealed differences. (C) The heatmap shows all the circRNAs with expression differences (P value < 0.05). (D) Volcano plot presenting differential expression distribution and significant differential circRNAs (LogFC >1.5, P value < 0.05). (E) KEGG analysis of host genes for differential circRNAs. IR: ischemia-reperfusion.

Fig. 3

3.3 Prediction of the circRNA–miRNA‒mRNA network

The functions and roles of ceRNAs have been well established. One important function of circRNAs is to act as ceRNAs to regulate miRNAs by interacting with miRNA response elements (MREs). To investigate the potential target miRNAs of significantly differentially expressed circRNAs, we used three databases: TargetScan, RNAhybrid and miRanda. A total of 1145 miRNAs were predicted (Table S2). Then, to predict the miRNA‒mRNA network, 2992 mRNAs were acquired from TargetScan, miRTarBase and TarBase by the R package multiMiR (Fig. 4A). In addition, we obtained 6811 differentially expressed mRNAs between the sham and IRI groups from GSE93034 (Fig. 4B). Finally, 1275 target mRNAs were obtained from the intersection of the online database and GSE93034 (Fig. 4C).Fig. 4 Prediction of the circRNA–miRNA‒mRNA network and target mRNA functional analysis. (A) The Venn diagram shows miRs that are the intersection of three databases (miRTarBase, TarBase, TargetScan). (B) Heatmap showing differentially expressed mRNAs in GSE93034 (IR vs. WT sham). (C) The Venn diagram shows mRNAs with an opposite direction of alterations between the comparison groups (predicted mRNAs vs. differentially expressed mRNAs in GSE93034). (D–F) GSEA, KEGG, and GO analysis of target mRNAs. KEGG: Kyoto Encyclopedia of Genes and Genome, GO: Gene Ontology, GSEA: Gene set enrichment analysis, IR: ischemia-reperfusion.

Fig. 4

3.4 Functional enrichment analyses for target mRNAs

For the functional exploration of target mRNAs, the R package clusterProfiler was used to analyze the functions of the mRNAs enriched in GSEA and KEGG/GO analyses. GSEA indicated that target mRNAs were mainly activated in hallmark IL6-JAK-STAT3 signaling, hallmark unfolded protein response, hallmark TNFα-NFκB signaling and hallmark hypoxia (Fig. 4D). In addition, the results of KEGG pathway analysis showed that mRNAs were mainly enriched in the PI3k-Akt signaling pathway, Wnt signaling pathway, mTOR signaling pathway, MAPK signaling pathway, Ras signaling pathway, FoxO signaling pathway and autophagy (Fig. 4E). For GO analysis, we focused on the top ten results in the biological process (BP), cellular component (CC) and molecular function (MF) categories. Binding of small molecules such as Ras-GTPases and small GTPases, actin and enzyme activator activity were enriched in the BP category. The CC category showed enrichment of the compositions of multiple organelles. In addition, in the MF category, we found that target mRNAs were closely related to the cellular response to oxidative stress and the response to oxidative stress (Fig. 4F). In conclusion, the results demonstrate the association of the target mRNAs with the mechanisms involved in hepatic IRI, which may be involved in oxidative stress, the inflammatory response, and pyroptosis.

3.5 The expression of circRNA-Phf21a_0002 is downregulated in hepatic IRI

To gain more insight into the function of circRNAs in hepatic IRI, we filtered the top ten significant circRNAs and found that four of them were retrievable in the circBase database (http://www.circbase.org/). Among them, circRNA-Phf21a_0002 (mm9_circ_006097), circRNA-Smad4_0007 (mm9_circ_006973), and circRNA-Dennd1b_0009 (mm9_circ_002352) were found to have a potential ceRNA network (Fig. 5A). Based on the results of RNA sequencing, three downregulated circRNAs that might be associated with hepatic IRI were selected for further validation. The expression levels of circRNA-Phf21a_0002, circRNA-Smad4-0007, and circRNA-Dennd1b_0009 were consistent with the RNA sequencing results (Fig. 5B). According to the ceRNA network results, the target genes of circRNA-Phf21a_0002 were associated with mTOR signaling, which was speculated to be involved in pyroptosis (Fig. S1). Considering the significantly downregulated expression of circRNA-Phf21a_0002 (Fig. 3D), the AML12H/R model was used to further detect the change in the expression levels of circRNA-Phf21a_0002. As expected, the downregulated expression levels of circRNA-Phf21a_0002 in the H/R model showed the same trend as that of downregulated expression levels in the mouse model (Fig. 5C). Finally, circRNA-Phf21a_0002 was selected for subsequent experiments. After the total RNA of AML12 cells were treated with RNase R, the expression levels of Phf21a mRNA were much lower than those of circRNA-Phf21a_0002, suggesting the resistance of circRNA-Phf21a_0002 to RNase R (Fig. 5D). We next measured the stability of circRNA-Phf21a_0002 and its linear counterpart mRNA Phf21a using actinomycin D treatment. The results revealed that circRNA-Phf21a_0002 had higher stability than mRNA Phf21a (Fig. 5F). In addition, we examined the localization of circRNA-Phf21a_0002. RNA-FISH results showed that circRNA-Phf21a_0002 was mainly expressed in the nucleus (Fig. 5E and Fig. S2). The results of Sanger sequencing identified the back-spliced site, providing conclusive evidence for the existence of circRNA-Phf21a_0002 (Fig. 5G). Given all these findings, we conclude that circRNA-Phf21a_0002 has the potential function of regulating pyroptosis in hepatic IRI.Fig. 5 CeRNA network and qRT‒PCR validation of expression. (A) CeRNA network. (B) qRT‒PCR expression of circRNA-Phf21a_0002, circRNA-Smad4_0007, and circRNA-Dennd1b_0009 in the IR and sham groups. (C) qRT‒PCR analysis of circRNA-Phf21a_0002 expression at different reperfusion time points (2 h, 6 h, 12 h, 24 h) in the H/R AML12 cell model. (D and F) RNase R and actinomycin D experiments to validate cyclic RNA ring-forming stability. (E) RNA-FISH showing the cellular localization of circRNA-Phf21a_0002 (magnification × 600 and 1200, scale bar = 25 and 50 μm). (G) Sanger sequencing identified the back-spliced site of circRNA-Phf21a_0002. Between-group comparisons were conducted using Student's t-test, while comparisons among multiple groups were performed using one-way analysis of variance, all data represent the mean ± SD, n = 3 *p < 0.05, **p < 0.01, ***p < 0.001.

Fig. 5

3.6 CircRNA-Phf21a_0002 aggravates pyroptosis in an H/R model

To further explore the role of circRNA-Phf21a_0002 in mediating pyroptosis in the H/R model, AML12 cells were transfected with the circRNA-Phf21a_0002 OE plasmid. The effects of upregulated expression of circRNA-Phf21a_0002 on pyroptotic hepatocytes were measured using western blotting. As shown in Fig. 6A, the upregulation of circRNA-Phf21a_0002 markedly enhanced pyroptosis-related protein expression levels of Cleaved Gsdmd, mature-IL-1, IL-18, and Cleaved Caspase-1 compared to the control group (Fig. 6 B-F). qRT-PCR results also corroborated the aforementioned trend, with significantly elevated mRNA expression of IL-1β, IL-6, and TNF-α in the OE group compared to the VEC group (Fig. 6G–I). In addition, we also evaluated the effects of circRNA-Phf21a_0002 OE on hepatocyte pyroptosis. The results of Hoechst/PI staining suggested that the percentages of pyroptotic cells in the circRNA-Phf21a_0002 OE group were higher than those in the control group (Fig. 6J). Cell electron microscopy results similarly revealed pronounced mitochondrial swelling and vacuolization in the OE group (Fig. 6K). Additionally, the apoptosis flow cytometry results indicate that after H/R treatment, the proportion of apoptosis in the OE group is significantly higher than that in the VEC group (Fig. 6L). Taken together, these results indicate that circRNA-Phf21a_0002 aggravates pyroptosis in hepatic IRI.Fig. 6 CircRNA-Phf21a_0002 aggravates pyroptosis in an H/R model. (A–F) Western blot experiments and relative gray values were determined to analyze the expression of the pyroptosis proteins Gsdmd, Cleaved caspase-1, IL-18, IL-1β, and Cleaved Gsdmd in different groups (control, H/R, VEC-H/R, OE-H/R). (G–I) qRT-PCR was conducted to examine the mRNA expression changes of inflammatory factors, including IL-1β, IL-6, and TNF-α. (J) Hoechst/PI staining shows pyroptosis and apoptosis in different groups (control, H/R, VEC-H/R, OE-H/R) (magnification × 200). (K) Mitochondrial alterations were observed using cellular electron microscopy (magnification × 40000). (L) After the H/R modeling, the proportion of apoptosis is detected using apoptosis flow cytometry. Between-group comparisons were conducted using Student's t-test, while comparisons among multiple groups were performed using one-way analysis of variance, all data represent the mean ± SD, n = 3/group. *p < 0.05, **p < 0.01, ***p < 0.001. H/R: hypoxia/reoxygenation, VEC: negative control, OE: overexpression.

Fig. 6

CircRNA-Phf21a_0002 can regulate pyroptosis and cell injury through endogenous competitive binding with let-7b-5p.

The binding sites of circRNA-Phf21a_0002 (mmu-circ_0001047) and let-7b-5p were predicted by circMir (version 1.0) (Fig. 7A and B). The dual-luciferase reporter gene assay was employed to elucidate the interaction between circRNA-Phf21a_0002 and let-7b-5p. Co-transfection of circRNA-Phf21a_0002-WT and let-7b-5p mimics into 293 T cells resulted in the inhibition of luciferase activity, whereas no impact was observed on the MUT group (Fig. 7C). qRT‒PCR showed that let-7b-5p was obviously downregulated in the OE group upon H/R induction relative to the VEC group (Fig. 7D). The let-7b-5p mimics were subsequently constructed, and qRT‒PCR showed an obvious upregulation effect (Fig. 7E). The expression of circRNA-Phf21a_0002 and Bach1 was downregulated in response to let-7b-5p mimics treatment (Fig. 7F and G). Western blot analysis showed that let-7b-5p alleviated the pyroptosis induced by upregulation of circRNA-Phf21a_0002 and decreased the expression of Cleaved Caspase-1 and mature IL-1β in H/R AML12 cells (Fig. 7H and I).Fig. 7 CircRNA-Phf21a_0002 serves as a sponge for let-7b-5p in vitro. (A–B) Prediction of circRNA and miRNA binding sites. (C) circRNA-Phf2a_0002-WT/MUT, along with NC or let-7b-5p mimics, were co-transfected into 293 T cells to assess luciferase intensity. (D) OE of circRNA-Phf21a_0002 leads to downregulation of let-7b-5p expression by qRT‒PCR. (E) Transfection effects of let-7b-5p mimics in AML12 cells by qRT‒PCR. (F–G) Relative expression levels of circRNA-Phf21a_0002 and Bach1, comparison between OE-H/R and OE-mimics-H/R. (H–I) Western blot analyses of Caspase-1, Cleaved Caspase-1, IL-1β, mature IL-1β in AML12 cells treated with OE-circRNA-Phf21a_0002 or let-7b-5p mimics. Between-group comparisons were conducted using Student's t-test, while comparisons among multiple groups were performed using one-way analysis of variance, all data represent the mean ± SD, n = 3/group. *p < 0.05, **p < 0.01, ***p < 0.001. H/R: hypoxia/reoxygenation, VEC: negative control, OE: overexpression.

Fig. 7

4 Discussion

Hepatic IRI is a common liver disease that mainly occurs during clinical operations such as liver surgery, trauma, and liver transplantation. The mechanism of IRI is complex and involves multiple factors, including apoptosis, oxidative stress, pyroptosis, and inflammation. In this study, we identified differentially expressed circRNAs in mouse hepatic IRI and found that the circRNA-Phf21a_0002/let-7b-5p axis regulates hepatic ischemia/reperfusion-related pyroptosis, which may inhibit hepatocyte pyroptosis by targeting Bach1.

Pyroptosis is important because it is related to innate immunity and diseases [5]. Pyroptosis can lead to the release of numerous cytokines, thereby promoting immune cell activation, inducing immune responses, and triggering phagocytosis [25]. Specific danger-associated molecular patterns of various liver diseases, such as nonalcoholic steatohepatitis, hepatocellular carcinoma, and alcoholic liver disease, have been proven to trigger sterile inflammation and pyroptosis through different signaling pathways [26]. In the current study, a mouse hepatic IRI model was constructed, and pyroptosis and injury were observed after hepatic IR. In the serum, the levels of ALT and AST were significantly increased, and the levels of the pyroptosis factors IL-1β and IL-18 were increased, indicating that the hepatocytes were in a severe pyroptosis state. In addition, the expression of pyroptosis proteins, including Cleaved caspase-1, IL-18, and mature IL-1β, was also changed in the livers of the IR group compared with those of the sham group.

With the development of sequencing technology and bioinformatics technology, circRNAs have been proven to play important roles in different biological processes [27]. CircRNAs can serve as biomarkers for myocardial infarction. Additionally, circFOXN2 and circNECTIN3 have been identified as markers for predicting early graft dysfunction [28].Thus far, research on hepatic IRI has mainly focused on mRNAs and miRNAs, while few studies on circRNAs have been performed [29,30]. According to reports, certain circRNAs have been implicated in the exacerbation of fatty hepatic IRI [31]. There has not been an in-depth molecular mechanism study on circRNAs. Using bioinformatics, we analyzed the sequencing data and identified a total of 375 differentially expressed circRNAs, of which 40 circRNAs had significant differences (39 downregulated and 1 upregulated) after hepatic IRI. CircRNAs are produced during the processing of mRNA precursors and share the same parental genes with mRNA [32]. As some circRNAs have been found to function by regulating their parental linear transcripts, there may be a relationship between the functions of circRNAs and their host genes. After performing KEGG pathway enrichment analysis on the host genes, we found a high correlation with the FoxO signaling pathway and the AMPK signaling pathway. The AMPK signaling pathway has been extensively studied in IRI and can affect autophagy through the AMPK/mTOR pathway to alleviate IRI [33]. The FoxO signaling pathway is also involved, and it can alleviate inflammation through the PI3k/Akt pathway [34]. This suggests that these circRNAs may play a role in IRI, and the significant parental genes of circRNAs are mostly associated with the severity of injury.

It is known that miRNAs can silence genes by binding to mRNAs, while ceRNAs can regulate gene expression by competitively binding to miRNAs. CircRNAs can bind to MREs to impair the functions of miRNAs, thus regulating biological functions [12]. For instance, CircTTC3 modulates cerebral ischemia-reperfusion injury by interacting with miR-372–3p to affect TLR4 expression [35]. The ceRNA network constructed by circRNA-Phf21a_0002 showed a high correlation with the mTOR signaling pathway, and the target gene Bach1 has also been reported to be involved in IRI regulation. Silencing the Bach1 gene can effectively enhance the ability of liver cells to resist oxidative stress [36]. In addition, knockout of Bach1 can improve the ability of liver cells to resist ischemia‒reperfusion injury through HO-1 and affect mitochondrial biological functions [37]. In addition, the mTOR signaling pathway can regulate GSDMD to affect pyroptosis [38]. Therefore, we conclude that circRNA-Phf21a_0002 may be related to pyroptosis in IRI.

Subsequently, the circular stability of circRNA-Phf21a_0002 was verified, and this molecule was confirmed to be a circRNA. OE of circRNA-Phf21a_0002 significantly exacerbated H/R-induced pyroptosis and cell death in AML12 cells, indicating that upregulation of circRNA-Phf21a_0002 worsened IRI through pyroptosis. Bioinformatics analysis showed that circRNA-Phf21a_0002 may act as a ceRNA of let-7b-5p to regulate downstream regulation. Research has shown that let-7b-5p acts as a sponge for circRNA-KDM4C, induces ferroptosis in acute myeloid leukemia and upregulates p53 [39]. In addition, let-7b-5p functionally converges on the mTOR/AKT signaling axes [40]. Based on the above findings, we hypothesized that let-7b-5p plays a certain role in hepatic IRI. Our experiments showed that let-7b-5p alleviated pyroptosis when cells were simultaneously induced to overexpress circRNA-Phf21a_0002 and transfected with mimics of let-7b-5p. qRT‒PCR also showed that OE of circRNA-Phf21a_0002 upregulated Bach1 but that let-7b-5p could reverse this upregulation effect. These results demonstrate that a targeted regulatory relationship exists between let-7b-5p and Bach1 in IR.

Notably, there were some limitations in the current study. We constructed a mouse hepatic IRI model, which may not have fully simulated the entire process of hepatic IRI in humans. However, there is a high degree of similarity between mouse circRNAs and human circRNAs, and most of the circRNAs identified in this study have homologous circRNAs in humans, which provides some implications for human research.

Moreover, our current research showed that hepatic IRI is related to pyroptosis. Upregulation of circRNA-Phf21a_0002 can promote the pyroptosis and injury of AML12 cells in response to IR. This mechanism can be regulated via sponging of let-7b-5p. Based on these findings, we have discovered the significant role of circRNA-Phf21a_0002 in regulating hepatocyte pyroptosis through let-7b-5p in hepatic IRI. These findings provide an important foundation for further research into the mechanisms of hepatic IRI.

5 Conclusion

Our study not only comprehensively investigated and predicted a mechanism by which circRNAs regulate injury through a ceRNA network in hepatic IRI but also provided experimental evidence of the functional role of circRNAs in severe liver IRI. Specifically, we found that circRNA-Phf21a_0002 exacerbates injury by mediating hepatocyte pyroptosis via the circRNA-Phf21a_0002/let-7b-5p axis. These findings provide new ideas and directions for the development of new therapeutic strategies and diagnostic methods.

Data availability statement

The data used in this article are available in the online database (GSA, ID: CRA016567, https://ngdc.cncb.ac.cn/gsa/) or in the supplementary material. All data used in the generation of the results presented in this manuscript will be made available upon reasonable request from the first author Peng Jiang (email: jiangpeng97@163.com)

Ethics statement

The animal study was reviewed and approved by the ethics committee of the Affiliated Hospital of Qingdao University (QYFY WZLL 27854).

Funding

This work was supported by the Science Foundation of Fujian Province, China (No. 2021J02041 ), and the 10.13039/501100001809 National Natural Science Foundation of China (No. 82370666 ).

CRediT authorship contribution statement

Peng Jiang: Writing – review & editing, Writing – original draft, Validation. Xinqiang Li: Visualization, Validation. Yuntai Shen: Writing – review & editing, Writing – original draft. Lijian Luo: Validation. Bin Wu: Formal analysis, Data curation. Dahong Teng: Supervision, Project administration. Jinshan Wang: Visualization, Data curation. Imran Muhammad: Writing – review & editing. Qingguo Xu: Writing – review & editing. Shipeng Li: Validation, Project administration, Conceptualization. Bin Zhang: Project administration. Jinzhen Cai: Funding acquisition, Data curation, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A Supplementary data

The following are the Supplementary data to this article:Figure S1 KEGG analysis of circRNA-Phf21a_0002 target mRNAs. (A) The KEGG results indicate that the ceRNA network target genes regulated by circRNA-Phf21a_0002 are mainly enriched in the mTOR signaling pathway. KEGG: Kyoto Encyclopedia of Genes and Genome, ceRNA: competing endogenous RNA.

Figure S1

Figure S2 CircRNA-Phf21a_0002 RNA-FISH localization results. (A) The cellular localization results of circRNA-Phf21a_0002 in different perspectives using RNA-FISH. (magnification ×600 and 1200, scale bar = 25 and 50 μm).

Figure S2

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Acknowledgments

I am grateful to SYD and XQG for support on my way to learn biological information. I also thank the WeChat official account Guo Zi Xue Sheng Xin.

Appendix A Supplementary data to this article can be found online at https://doi.org/10.1016/j.heliyon.2024.e34385.
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