Abstract
Background
An increasing body of evidence now shows that the long-term mortality of patients with sepsis are associated with various sepsis-related immune cell defects. Alternative splicing (AS), as a sepsis-related immune cell defect, is considered as a potential immunomodulatory therapy target to improve patient outcomes. However, our understanding of the role AS plays in sepsis is currently insufficient.
Aim
This study investigated possible associations between AS and the gene regulatory networks affecting immune cells. We also investigated apoptosis and AS functionality in sepsis pathophysiology.
Methods
In this study, we assessed publicly available mRNA-seq data that was obtained from the NCBI GEO dataset (GSE154918), which included a healthy group (HLTY), a mild infection group (INF1), asepsis group (Seps), and a septic shock group (Shock). A total of 79 samples (excluding significant outliers) were identified by a poly-A capture method to generate RNA-seq data. The variable splicing events and highly correlated RNA binding protein (RBP) genes in each group were then systematically analyzed.
Results
For the first time, we used systematic RNA-seq analysis of sepsis-related AS and identified 1505 variable AS events that differed significantly (p <= 0.01) across the four groups. In the sepsis group, the genes related to significant AS events, such as, SHISA5 and IFI27, were mostly enriched in the cell apoptosis pathway. Furthermore, we identified differential splicing patterns within each of the four groups. Significant differences in the expression of RNA Binding Protein(RBP) genes were observed between the control group and the sepsis group. RBP gene expression was highly correlated with variant splicing events in sepsis, as determined by co-expression analysis; The expression of DDX24, CBFA2T2, NOP, ILF3, DNMT1, FTO, PPRC1, NOLC1 RBPs were significant reduced in sepsis compared to the healthy group. Finally, we constructed an RBP-AS functional network.
Conclusion
Analysis indicated that the RBP-AS functional network serves as a critical post-transcriptional mechanism that regulates the development of sepsis. AS dysregulation is associated with alterations in the regulatory gene expression network that is involved in sepsis. Therefore, the RBP-AS expression network could be useful in refining biomarker predictions in the development of new therapeutic targets for the pathogenesis of sepsis.
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Introduction
Pre-messenger RNA splicing has been reported to be a critical step in RNA maturation, which includes joining exons together as well as removing introns. The process of splicing is accomplished in the cell nucleus by means of one of two different macromolecular ribonucleoprotein complexes, which are called the major and minor spliceosomes [1]. It has been determined that greater than 90% of the genes that are expressed in humans undergo alternative splicing [2], allowing individual genes to give rise to several different mRNAs that encode unique proteins, which can significantly expand the proteome complexity.
Published reports have described numerous types of AS events, although cassette exons appear to be the dominant form. Regulation of AS events is known to occur in a spatiotemporal-dependent manner [1] through combined actions of cis-elements as well as trans-factors [3]. Furthermore, aberrant splicing events have been associated with numerous diseases [4, 5].
Dysregulation of the host’s response to infections appears to be the primary cause of sepsis and represents a leading cause of morbidity, mortality, and healthcare utilization for intensive care unit (ICU) patients [6]. The pathogenesis of sepsis is relatively complex. However, while there are many related studies on the pathogenesis of sepsis, the precise mechanisms involved have yet to be elucidated. In particular, the lack of special treatment methods for sepsis is closely associated with high levels of mortality. Studies that have been carried out recently have demonstrated that the transcriptome signatures of the host are able to distinguish between causes of sepsis that are viral and those that are bacterial. RNA-seq analysis of responses mounted in whole blood by the immune system of the host could reveal the “true” prevalence and epidemiology underlying the occurrence of sepsis [7]. Several studies have indicated that AS dysregulation is associated with several clinical entities, including cancer, by influencing cell proliferation, apoptosis, invasion, migration, and metabolism [8]. The diversity and flexible characteristics of proteins are critical in regulating AS and are a prerequisite for the maintenance of functional immune responses. Numerous genes that are involved in signaling in the innate or adaptive immune pathways are known to undergo varying degrees of AS [9]. Based on the functions of the genes that are spliced, AS can influence the physiological functions that the immune system carries out in a range of ways. In addition, alterations in the mechanisms by which splicing occurs and even participation by non-coding RNAs may result in alterations in the patterns of splicing that occur in sepsis-related genes [10]. However, there is a lack of research on the role of AS with regard to the immune regulation of sepsis and the progression of this condition. Therefore, the identification of potential targets for AS could provide information that might prove beneficial in develo** novel methods that could be used in diagnosing and treating sepsis.
In this investigation, we profiled mRNAs that were differentially expressed (DE) in sepsis, which was accomplished through the assessment of a publicly available RNA-seq dataset and the construction of a new co-expression network for DE mRNAs. The variable splicing events and highly correlated RNA binding protein (RBP) genes in differentially expressed (DE) mRNAs were then comprehensively analyzed. Differentially expressed analysis was then utilized in the identification of differentially expressed alternative splicing (DEAS) events among sepsis, septic shock, and healthy individuals. In addition, correlations that occurred between the DEAS events and immune features or functional analyses were assessed. Cluster analysis, which was based on DEAS, was used to accurately represent any differences that were observed among the included study groups with respect to the immune microenvironment. We also predicted the target genes and related RNA binding proteins (RBP) and determined their functionality. Various genes with different alternative splicing types were chosen to confirm the alternative splicing events that were identified using bioinformatic analysis. This step was followed by experimentally verifying the splice variants that were predicted by using reverse transcription-polymerase chain reaction (RT-PCR). The results of this study will contribute to a deeper and more inclusive understanding of how AS is involved in the process of sepsis. Our findings also might be useful in identifying novel therapeutic targets that could help decrease patient morbidity and mortality resulting from septic syndromes.
Material and methods
Accessing and processing publicly available data
The publicly available sequence data files from GSE154918 [11] were accessed from the Sequence Read Archive (SRA). Then the SRA Run files were changed to the fastq format by the NCBI SRA Tool fastq-dump (v.2.8.0). The FASTX-Toolkit (v.0.0.13; http://hannonlab.cshl.edu/fastx_toolkit/) was utilized to trim the data by removing low-quality bases(Remove the base with terminal mass less than 20; Remove 30% of the reads whose base mass is less than 20) in raw reads.
The alignment of the reads and differentially expressed gene (DEG) analysis
The processed reads underwent alignment to the human GRch38 genome via HISAT2(v.2.2.1) [12]. Uniquely mapped reads were screened for further analysis. We then calculated the reads number located on each gene. The gene expression levels were evaluated with FPKM (fragments per kilobase of exon per million fragments mapped). DEseq2 (v. 1.30.1) software was used to perform differential gene expression analysis using the reads count file [13]. DEseq2 was then utilized to assess the differential expression that occurred among two or more samples to decide if a specific gene was differentially expressed through the calculation of fold changes (FC) as well as determination of the false discovery rate (FDR).
**Two critical parameters were determined**
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1)
FC: fold change, which indicated the absolute ratio of the change in expression.
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2)
FDR: the false discovery rate.
**The criteria used to assess the significant difference in expression included the following:**
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FC ≥ 2 or ≤ 0.5, FDR ≤ 0.05;
Analysis of alternative splicing
The alternative splicing events (AS) and regulated alternative splicing events (RAS) that were observed among the different groups in this study were defined and measured with the SUVA (v2.0)(Splicing site Usage Variation Analysis) pipeline, as described previously [14]. The proportion of reads with a SUVA AS event (pSAR) was determined for each AS event.
Co-expression analysis
A co-disturbed network was constructed utilizing 79 samples obtained from the GSE154918 dataset. The network was constructed between the RBP expression and the splicing ratio of the RAS events (pSAR >= 50. Next, the Pearson’s correlation coefficients (PCCs) were determined between these parameters, which allowed the classification of their relationship into one of three classes: positive correlation, negative correlation, or no correlation, as determined by the PCC value. Factors with a Pearson’s correlation of 0.7 or greater and with a P-value equal to or less than 0.01 were retained.
Analysis of functional enrichment
To comprehensively identify the different DEG functional categories, we performed Gene Ontology (GO) and KEGG pathway analysis of the splicing data utilizing a KOBAS 2.0 server [39]. On the other hand, when this exon is included, a membrane receptor is produced, which triggers signaling pathways associated with cell death [40]. These findings indicate that the distinct AS patterns involved in sepsis pathophysiology might display essential functions in immune cell apoptosis in sepsis.
RNA-binding proteins (RBPs) are known to be crucial effectors in the expression of many genes [41] and are involved in the regulation of nearly every aspect of RNA functionality, including transcription, splicing, modification, intracellular trafficking, translation, and decay [42, 43]. Importantly, gene expression differences between sepsis survivors and non-survivors have been detected previously; furthermore, multiple genes related to immune function were poorly expressed in non-survivors [44]. This study has demonstrated that RBP expression was substantially different among the different study groups and clearly separated the sepsis group from the infection and healthy groups. Interestingly, the number of RBPs decreased with increasing severity of sepsis. The differential expression of RBPs during the process of sepsis may lead to differences in AS, thus affecting various aspects of cell function. GO analysis of the DE RBPs in sepsis identified terms that were mostly enriched in the immune/inflammatory response; we identified significant differences in 8 down-regulated RBPs in sepsis, including DDX24, CBFA2T2, NOP, ILF3, DNMT1, FTO, PPRC1, NOLC1. These changes indicate that the distinct expression levels of RBPs related to immune/inflammatory genes play important roles in the molecular mechanisms underlying the pathophysiology of sepsis.
The human nucleolar protein 14 (NOP14) gene has been reported previously to be located on chromosome 4p16.317 and is a key gene in the process of sepsis. This gene might be associated with pre‑18S rRNA processing that occurs during sepsis, or it might be involved in the inflammation that takes place during sepsis, acting through the regulation of miRNA‑2909 expression [45]. EMG1 and NOP14 are known to be members of a family of repressed environmental stress response (ESR) genes, which also includes genes that encode ribosomal proteins (RPs) as well as additional proteins known to be associated with RNA metabolism and the synthesis of proteins [46]. Furthermore, the enhancer binding factor 3 (ILF3) functions as a stable heterodimeric complex to stabilize mRNAs and regulate gene expression [47]. As reported previously, miR-215-5p expression is protective in inflammation injury that occurs in sepsis caused by H9c2 by targeting ILF3 and LRRFIP1 [48]. DDX24 is a DEAD-box helicase whose role in cells is largely unknown. However, DDX24 is capable of binding ssRNA and dsRNA. Interestingly, it has been shown to negatively affect RLR-dependent innate immune activation through several mechanisms [49]. DDX24 has been shown to compete with RIG-I for VSV RNA binding through its ability to bind RNA, exerting a direct inhibitory effect on viral perception [50]. At the same time, the qRT-PCR results of this study showed that the expression of DDX24 in the sepsis group was significantly lower than that in the healthy group, so we speculated that it plays a protective role in the innate immune response in sepsis through negative regulation.DNA methyltransferases1(DNMT1) -mediated DNA methylation is involved in many human diseases by affecting many types of cellular processes, including cell growth, cell cycle progression, metastasis, apoptosis, development, and tumorigenesis [51]. Fubing Ma et al. report that DNMT1-mediated increased DNA methylation plays a key role in LPS-induced sepsis by regulating the SMAD2/DNMT1/miR-145 negative regulatory loop [52]. The first discovered RNA demethylase obesity-associated protein (FTO) [53], involved in cell proliferation, apoptosis, cell cycle, migration, invasion, drug resistance and other processes [54]. As an oncogene, FTO promotes IDH mutations through the FTO/MYC/CEBPA signaling pathway, which in turn leads to tumorigenesis [55]. The human fragile histidine triad (FHIT) gene is a tumor suppressor gene, and heterozygous deletion (LOH), homozygous deletion, and abnormal expression of the FHIT gene have been implicated in several types of human malignancy [56]. In addition, FHIT has been reported to increase mitochondrial calcium release and promote apoptosis [57].The mechanism of action of FTO, NUDT2 and FHIT in sepsis is not clear, and we speculate that FTO, NUDT2 and FHIT may promote the development of sepsis by participating in apoptosis, and the mechanism needs further study. Collectively, these results suggested that genes encoding RBPs, such as DDX24, NOP, ILF3, DNMT1, FTO, PPRC1, NOLC1,represent novel targets for the molecular mechanisms that regulate sepsis and may be involved in the immune response by regulating AS events in key genes that are associated with cellular apoptosis.
Our study has some limitations that should be considered, even though we detected significant differences in AS in sepsis compared with a healthy group. However, we are still unclear whether changes in AS are related to certain bacterial categories. The factors that exert impact on AS in sepsis needs further research. Similarly, we need to investigate the mechanisms and clinical outcomes of ILF3 regulation on crucial genes in sepsis.
Conclusion
In this study, we describe the characteristic of AS and characterize the function of genes related to AS in sepsis. Furthermore, we identified the significant role of RBPs in the progression of sepsis. In addition, the functional pathways of RASG were related to the apoptosis pathway, the regulation of catalytic activity, and the positive regulation of apoptosis. We also generated a functional path diagram for the RBP-RAS-RASG network, representing a novel RBP-based post-transcriptional network that links sepsis progression and immunomodulation within the sepsis microenvironment. These transcripts, in particular, encode secretory factors that not only limit the metastasis of sepsis, but also remodel the sepsis immune microenvironment towards immune function suppression. Alterations in splicing factors, including transcriptional alteration, and their functional impactions in sepsis development, have been extensively studied.
Availability of data and materials
All data generated or analyzed during this study have been included in this published article. The datasets supporting the results of this article are available in the NCBI Gene Expression Omnibus and are accessible through the GEO series accession number (GSE154918).
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Acknowledgements
The authors are thankful for the beneficial discussions provided by Mr. Chao Cheng and Mr. Li Ning (ABLife BioBing Data Institute). We also thank EditSprings (https://www.editsprings.cn/) for the expert linguistic services provided.
Funding
This research was supported by the Natural Science Foundation of **njiang (#2016D01C255). The State Key Laboratory of Causes and Prevention of High Incidence in Central Asia was jointly established by the province and the ministry [grant number SKL-HIDCA-2022-18].
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Dilixiati Tuerdimaimaiti and Buzukela Abuduaini designed the project. Baihetinisha Tuerdi supervised the experiments. Sicheng Xu, Kang **aotao, Jiao **liang, Li Mengchen,and Wolazihan Madeniyati performed the experiments. Baihetinisha Tuerdi performed the data analysis and wrote the paper. All authors analyzed the results and approved the final version of the manuscript.
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Tuerdimaimaiti, D., Abuduaini, B., Kang, S. et al. Genome-wide identification and functional analysis of dysregulated alternative splicing profiles in sepsis. J Inflamm 20, 31 (2023). https://doi.org/10.1186/s12950-023-00355-w
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DOI: https://doi.org/10.1186/s12950-023-00355-w