Exosomal hsa_circRNA_104484 and hsa_circRNA_104670 may serve as potential novel biomarkers and therapeutic targets for sepsis

In order to explore the role of exosomal circRNAs in the occurrence and development of sepsis, we looked for potential diagnostic markers to accurately identify sepsis and to lay a molecular basis for precise treatment. Ultracentrifugation was used to extract exosomes from the serum of patients with sepsis and healthy individuals. Then, changes in circRNA expression in exosomes were studied by circRNA microarray analysis. Gene ontology (GO) analysis and Kyoto City Encyclopaedia of Genes and Genomes (KEGG) pathway analysis were used to annotate the biological functions and pathways of genes, and a circRNA-miRNA-mRNA regulatory network was constructed. In the microarray analysis, 132 circRNAs were significantly differentially expressed, including 80 and 52 that were upregulated and downregulated, respectively. RT-qPCR verified the results of microarray analysis: hsa_circRNA_104484 and hsa_circRNA_104670 were upregulated in sepsis serum exosomes. ROC analysis showed that hsa_circRNA_104484 and hsa_circRNA_104670 in serum exosomes have the potential to be used as diagnostic markers for sepsis. The circRNA-miRNA-mRNA network predicted the potential regulatory pathways of differentially expressed circRNAs. There are differences in the expression of circRNA in serum exosomes between patients with sepsis and healthy individuals, which may be involved in the occurrence and development of the disease. Among them, elevations in hsa_circRNA_104484 and hsa_circRNA_104670 could be used as novel diagnostic biomarkers and molecular therapeutic targets.

RNA extraction and quality control. Total RNA was extracted from the exosome suspension using the TRI Reagent BD (Molecular Research Center, Inc., USA) according to the manufacturer's protocol. The total RNA from each exosome sample was quantified and its purity was evaluated using a NanoDrop 2000 ultra-micro spectrophotometer (Thermo Fisher Scientific, USA). circRNA microarray analysis. CircRNA microarray analysis was performed on serum exosomes from three people with sepsis and three healthy persons. According to the manufacturer's protocol (Arraystar Inc., USA), sample labelling and microarray hybridization were performed. First, RNA was fluorescently labelled. Rnase R reagent (Epicenter, Inc., USA) was used to digest total RNA to remove linear RNA and enrich circRNAs. The enriched circRNAs were then transcribed into fluorescently labelled cRNA using a random priming method (Arraystar Super RNA Labelling Kit; Arraystar, USA). The labelled cRNAs were purified using the RNeasy Mini Kit (Qiagen, Germany). Microarray hybridisation was then performed in an Agilent Hybridisation oven. The fluorescently labelled cRNAs were cleaved into fragments and were then hybridised on the circRNA expression microarray slide. After hybridisation was completed, the hybridised microarrays were washed, fixed, and scanned using the Agilent Scanner G2505C. Agilent Feature Extraction software was used to extract raw data from the scanned images. Quantile normalisation of raw data was performed using the limma package (version 3.48.0) 20 in R, and the circRNAs labelled by the software were retained for subsequent difference analysis. A t-test was used to estimate the statistical significance of the difference. Fold changes and p-values were used to screen for significant differences in the expression of circRNAs between the two groups of samples. Volcano plots and heat maps were used to display differentially expressed circRNAs.
real-time quantitative PCR (RT-qPCR) analysis. Total RNA was extracted from serum exosomes of 25 sepsis patients and 22 controls. Real-time quantitative polymerase chain reaction (RT-qPCR) was used to verify the experiment. The sequences of the primers used in the experiment are shown in Table 2. Total RNA was reverse transcribed into complementary DNA (cDNA) using a PrimeScript RT reagent kit (Takara, Japan) according to the manufacturer's protocol. Real-time quantitative PCR reactions were then carried out with a real-time PCR system (LightCycler480, Roche, Switzerland) using TB Green Premix Ex Taq II (Takara, Japan). The PCR conditions were 95 °C for 30 s, followed by 40 cycles at 95 °C for 10 s, and 60 °C for 60 s. β-actin was Table 1. Demographic characteristics of septic patients. Data are expressed as number (%), mean ± SD, or median (25th-75th percentile).

Source of sepsis
Abdominal, n (%) 3 (14) Lung, n (%) 19  If the data of continuous variables were distributed normally, the data were analysed using t-tests; results are expressed as the mean ± standard deviation. If data were non-normal, the Mann-Whitney U test was used, and the data are expressed in percentile form. Data of categorical variables between groups were tested using the Chi-square test. A p value of < 0.05 means that the difference is statistically significant. The receiver operating characteristic (ROC) curve was constructed to evaluate the diagnostic ability of exosomal circRNAs for sepsis. The area under the ROC curve (AUC) was used to evaluate the diagnostic efficacy of circRNA. The Youden Index was used to determine the optimal cut-off value, sensitivity and specificity (Youden Index = Sensitivity + Specificity-1). The highest Youden index corresponds to the optimal cut-off value, sensitivity and specificity.
Ethics approval and consent to participate. This study was approved by the Ethics Committee of the second hospital of Jilin University. All participants were informed and willing to sign informed consent.

Consent for publication.
All the authors read and consented to the publication of the manuscript.

Results
Characterization of circulating serum exosomes. The serum exosome was confirmed by transmission electron microscopy (TEM) and WB for CD63 or TSG101 (Fig. 1a). The exosomes are round or oval 'cupshaped' , with a diameter in the range of 40-160 nm. CD63 and TSG101 showed positive expression in WB (Fig. 1b).
Identification of differentially expressed circRNAs. We used circRNA microarray technology to detect changes in the circRNA expression profile of serum exosomes in sepsis. After scanning the fluorescent signal of circRNA microarray hybridisation, a total of six scanning pictures of the sepsis and control groups were obtained (Fig. 2a). The box plot shows the results of the quality control analysis of the microarray data (Fig. 2b). Volcano plots and scatter plots were used to visually show the differences in circRNA expression between the two groups. In the volcano map (Fig. 2c), the vertical lines represent 1.5 times up and down, and the horizontal lines represent p ≤ 0.05. Red dots indicate circRNAs that are significantly differently expressed, and grey dots indicate circRNAs that are not significantly differently expressed. In the scatter plot (Fig. 2d), the X-axis and Y-axis represent the normalised signal values of the two groups of samples, respectively, and the green line is the fold line. Plots distributed above the upper green line and below the lower green line represent significantly differently expressed circRNAs.  Tables 3 and 4. Then, cluster analysis was performed on the significantly differentially expressed circRNAs to visually display the differentially expressed circRNAs and to test their rationality and accuracy. As shown in the heat map ( Fig. 2e), red represents highly expressed circRNAs and green represents low-expressed circRNAs. The results showed distinguishable circRNA expression profiles between the two groups of samples.
We further verified the expression levels of hsa_circRNA_104484 and hsa_circRNA_104670 in the serum exosomes of 22 patients with sepsis and 19 controls collected subsequently. As shown in Fig. 4, the expression of hsa_circRNA_104484 (1.829 ± 0.718 to 1.124 ± 0.506; p = 0.005) and hsa_circRNA_104670 (2.045 [1.319-3.049] to 0.948 [0.684-1.639]; p = 0.003) in serum exosomes of patients with sepsis increased, and the expression differences were statistically significant, which was consistent with the results of microarray analysis.

ROC analysis of serum exosomal hsa_circRNA_104484 and hsa_circRNA_104670 in sepsis.
The results of qPCR were used to construct the ROC curve to evaluate the diagnostic value of exosomal hsa_circRNA_104484 and hsa_circRNA_104670 in sepsis (Fig. 5). Compared with healthy subjects, the AUC of hsa_circRNA_104484 in sepsis exosomes was 0.782 (95% confidence interval [CI]: 0.643-0.921; p < 0.05), the sensitivity and specificity were 0.545 and 0.947, respectively. The highest Youden index was 0.492 and the corresponding optimal cut-off value was 31.901. The AUC of hsa_circRNA_104670 was 0.775 (95% CI: 0.632-0.919; p < 0.05), and the sensitivity and specificity were 0.591 and 0.895, respectively. The highest Youden index was 0.486 and the corresponding optimal cut-off value was 1.357. The results indicate that hsa_circRNA_104484 and hsa_circRNA_104670 have a medium diagnostic value and have the potential to be used as diagnostic markers in sepsis.
Prediction of the potential functions of target genes. GO analysis results showed that the biological process and molecular functions of target genes were concentrated in several aspects, such as 'negative regulation of transcription from the RNA polymerase II promoter' , 'transcription' , 'positive regulation of transcription' , 'negative regulation of transcription' , 'positive regulation of transcription from the RNA polymerase II promoter' , 'protein binding' , 'DNA binding' , 'transcriptional activator activity' , 'RNA polymerase II transcription factor  www.nature.com/scientificreports/ activity' , 'transcription factor activity' , and 'transcriptional repressor activity' (Fig. 7a). Most of them were related to the transcriptional regulation of gene expression. Therefore, hsa_circRNA_104484 and hsa_circRNA_104670 might participate in the process of sepsis by regulating transcription. KEGG pathway analysis results show that the target gene-related signalling pathways are the PI3K-Akt signalling pathway, signalling pathways regulating the pluripotency of stem cells, the MAPK signalling pathway, hepatitis B, viral carcinogenesis, osteoclast differentiation, hepatitis C, HTLV-I infection, TNF signalling pathway, and the insulin signalling pathway, among others (Fig. 7b). Among them, the PI3K-Akt signalling pathway 22 , MAPK signalling pathway 23 , and the TNF signalling pathway have been confirmed by several studies to be related to sepsis.

Discussion
In recent years, despite significant advances in antimicrobial treatment and organ support technologies, sepsis remains the leading cause of death in patients with severe infections 24 . This may be related to the lack of specificity of clinical manifestations, the complexity of pathophysiological processes, and the heterogeneity of sepsis 5 . Unfortunately, despite the continuous exploration of its mechanism, our understanding of it is still far from being sufficient. In fact, there are currently no laboratory testing methods to accurately identify sepsis and there are no individualised therapies to cure it. Therefore, researchers are committed to developing a precision medicine method that aims to classify patients into different types based on transcriptomic signatures and other biological and clinical data, thus providing a molecular basis for precision targeted therapy. Improving the identification and diagnosis of sepsis, exploring its pathogenesis, classification, and individualised therapy can maximise the efficacy and improve prognosis.
In recent years, exosomes have been extensively studied as a new form of intercellular signal transduction. Studies have shown that circRNAs are specifically enriched and stable in exosomes and can be detected in a variety of bodily fluids 17 . This means that exosomal circRNA has the potential to diagnose diseases as a biomarker 5,19 . They are also involved in the pathogenesis of various diseases, such as tumours 25,26 , cardiovascular diseases [27][28][29] , neurological disorders [30][31][32] , infections, and immune-related diseases 30,33,34 , indicating that they may be used as targets for precise treatment. To date, the expression and function of exosomal circRNAs in sepsis have not been reported. In order to clarify their regulatory role in the pathophysiology of sepsis, it is necessary to explore the changes in circRNA expression levels in serum exosomes and their regulatory pathways.
By comparing and analysing the results of microarrays, molecules with fold changes > 1.5 and p values < 0.05 were considered statistically significant. Then, we selected five circRNA molecules for experimental verification, including hsa_circRNA_101491, hsa_circRNA_103864, hsa_circRNA_104484, hsa_circRNA_104670, and hsa_circRNA_406194. These circRNA molecules were then verified by RT-qPCR among the 3 septic patients and 3 healthy volunteers that had been tested by microarray to determine the reliability of the microarray results. Among these five circRNA molecules, the expression of two circRNA molecules (hsa_circRNA_104484  www.nature.com/scientificreports/ and hsa_circRNA_104670) were significantly upregulated, consistent with the microarray results, but the other three circRNA molecules (hsa_circRNA_101491, hsa_circRNA_103864, and hsa_circRNA_406194) were not significantly different between the two groups. This indicates that microarray results contain false positives, thus, only differential circRNA molecules qualified by RT-qPCR are considered reliable. We continued to verify hsa_circRNA_104484 and hsa_circRNA_104670 in small clinical samples, and the results are consistent with those of previous studies. To the best of our knowledge, this study is the first report the expression of hsa_cir-cRNA_104484 and hsa_circRNA_104670 in sepsis serum exosomes. At present, ceRNA is the most common circRNA regulation mechanism. CircRNA targets miRNAs and indirectly regulates the expression of miRNA target genes and plays an important role in the occurrence and development of diseases 35 . Studies have found that circulating miRNAs are differentially expressed in inflammation-related diseases and can target the tumour necrosis factor pathway (TLR/NF-κB signalling pathway), acting as inflammation regulators 36,37 . Therefore, we speculate that circRNA may indirectly regulate the expression of inflammation-related genes by targeting miRNAs in sepsis. The annotation of the circRNA-miRNA regulatory axis and the construction of the ceRNA network showed that five miRNAs and several targeted mRNAs interacted with hsa_circRNA_104484 and hsa_circRNA_104670, respectively.
Among them, hsa_circRNA_104484 is a sponge molecule of hsa-miR-378a-3p/hsa-miR-378d. In recent experimental studies, miR-378 has been found to act directly or indirectly as a regulator of inflammation and participates in the processes of inflammation and immune regulation. Platelet-derived exosomal miR-378a-3p directly targets PDK1, resulting in the inhibition of the Akt/mTOR pathway and promoting the formation of neutrophil extracellular traps (NET) in sepsis 38 . A study by Caserta et al. 36 showed that miR-378a-3p is differentially expressed in systemic inflammatory response syndrome (SIRS) and correlated with its severity. miR-378a can directly target ZBTB20, which plays a role in cell growth and apoptosis 39 . ZBTB20 is a transcriptional repressor that inhibits the transcription of the IκBα gene and positively regulates the activation of NF-κB, triggering an innate immune response 40,41 . This is consistent with the results of the GO analysis. In addition,    www.nature.com/scientificreports/ miR-378 negatively regulates nuclear respiratory factor-1 (NRF-1), AMP-activated protein kinase γ2 (AMPKγ2), and phosphoinositide 3-kinase (PI3K), inhibits energy metabolism processes, and activates the NF-κB-TNFα pathway, which may be related to SIRS and sepsis [42][43][44] . Similarly, hsa_circRNA_104670 is a sponge molecule of hsa-miR-17-3p. Jiang and Li et al. 45 found that lipopolysaccharide (LPS) and TNF-α can regulate the expression of miR-17-3p. miR-17-3p directly targets intercellular adhesion molecule 1 (ICAM-1) and inhibits its expression in LPS-induced acute lung injury (ALI) 46 . ICAM-1 is an important inflammatory mediator, and its expression is upregulated in sepsis, which enhances inflammatory cell infiltration and organ damage 47,48 . Therefore, we speculate that hsa_circRNA_104484 and hsa_circRNA_104670 may be involved in the pathogenesis of sepsis.

Conclusions
Our study compared the differences in the expression levels of circRNAs in serum exosomes between sepsis and healthy people, and initially evaluated the clinical application value of hsa_circRNA_104484 and hsa_cir-cRNA_104670. The results provide a basis for mechanistic research. However, our research sample is relatively small; in the future, the sample size will be enlarged. We will further explore the biological functions of hsa_cir-cRNA_104484 and hsa_circRNA_104670 through cell and animal experiments. Currently, the pathogenesis of sepsis is still unclear. As such, there is no effective therapeutic intervention; the exploration of the circRNA regulatory mechanism in sepsis will have great clinical translation research value.