Application of lncRNA TTN-AS1 in sepsis-induced liver injury

Abstract

The application relates to the field of biological medicine, in particular to application of lncRNA TTN-AS1 in sepsis liver injury. The application comprises application of lncRNA TTN-AS1 in diagnosis or prevention or treatment of sepsis liver injury, the proinflammatory effect of TTN-AS1 in SALI is disclosed for the first time, it is suggested that TTN-AS1 can be used as a potential early diagnosis marker and treatment target of SALI, the lncRNA TTN-AS1 is an important molecule for mediating liver injury in sepsis, and the lncRNA TTN-AS1 has important application prospects in early detection, early diagnosis and targeted treatment of sepsis liver injury.

Description

Technical Field

[0001] This invention relates to the field of biomedical technology, and in particular to the application of lncRNA TTN-AS1 in sepsis-induced liver injury. Background Technology

[0002] Sepsis is a systemic inflammatory response caused by a dysregulation of the host's response to infection, often accompanied by life-threatening organ dysfunction or failure. [SINGERM,DEUTSCHMAN C S,SEYMOUR C W,et al.The Third International Consensus Definitions for Sepsis and Septic Sho ck(Sepsis-3)[J].Jama,2016,315(8):801-10.] Globally, approximately 48.9 million new cases of sepsis are diagnosed each year, with over 11 million deaths, making it the leading cause of death among ICU patients. [RUDD K E,JOHNSON S C,AGESA K M,et al.Global,regional,and national sepsis incidence and mortality,1990-2017:analy sis for the Global Burden of Disease Study[J].Lancet,2020,395(10219):200-11] Sepsis activates the host's systemic innate immune system, leading to the excessive release of cytokines, a phenomenon known as a "cytokine storm." [DELANO M J,WARD P A.The immune system's role in sepsis progression,resolution,and long-term outcome[J].Immunol Rev,2016,274(1):330-53] Cytokine storms can transform normally beneficial responses to fight infection into excessive and harmful inflammation, further inducing cell dysfunction and apoptosis, leading to organ dysfunction and death. The liver, as a core organ regulating immune defense mechanisms during systemic infection, plays a crucial role in regulating the systemic immune inflammatory response. In sepsis, the liver is not only an important barrier against pathogens but also a critical target organ that is easily damaged. Liver injury is one of the most common complications of sepsis. Studies have shown that early liver dysfunction is an independent risk factor for poor prognosis in sepsis; the mortality rate can reach 68% when patients have liver injury, and it also severely affects the long-term survival rate of sepsis patients. [CUI L,BAO J,YU C,et al.Development of a nomogram for predicting 90-day mortality in patients with sepsis-associa ted liver injury[J].Sci Rep,2023,13(1):3662] Therefore, early identification and intervention of sepsis-related liver injury are of great significance for improving the prognosis of sepsis patients.

[0003] In light of this, we combined cutting-edge technologies such as whole-transcriptome sequencing and proteomics to perform comparative whole-transcriptome and OLINK proteomics analyses on blood samples from SALI patients. This allowed us to explore and analyze specific biomarkers of sepsis-induced liver injury, leading to the innovative discovery of lncRNA TTN-AS1. Through experiments using a CLP sepsis mouse model, we verified its significant role in inducing liver injury. Therefore, by combining clinical case samples and animal experiments, we are the first to propose that lncRNA TTN-AS1 is a crucial molecule mediating sepsis-induced liver injury, and it holds significant promise for early detection, early diagnosis, and targeted therapy of sepsis-induced liver injury. We hereby apply for the application of this invention's lncRNA in sepsis-induced liver injury. Summary of the Invention

[0004] The purpose of this invention is to provide the application of LncRNA in sepsis-induced liver injury, to reveal the pro-inflammatory role of TTN-AS1 in SALI, suggesting its potential as an early diagnostic biomarker and therapeutic target.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] This invention provides the application of lncRNA TTN-AS1 in the diagnosis, prevention or treatment of sepsis-induced liver injury, the nucleotide sequence of which is shown in SEQ ID NO:1.

[0007] SEQ ID NO:1

[0008] >ENST00000419746.5TTN-AS1-203 dna:lncRNA

[0009] GAATGGAGAAGTTGGGTAACCTGCCCCAGGTGAAGCCCAAATTGGATCTCAGCGCCTGGGAGCTCCAACTTTAGCAAGTGCGAAATCCTGTCTTCGGTTTTGGAATTTTCATCCGCACAGACTATATCAGCCACGGATAGGATATGTGAGAATACCAGCATGTCAAGGCTGGGAATCATCCTTAGGCATCACCTAGCCAGTCCTGCCTCTCATTTTAAGGTGATCACAGGATCTGGTTTGCCACTGAAAGGAATCTTGATGCTGACCACTTCACCTCGGAGAGCATGAACTGCTCCCATGCCTTCAAGAGTTTTAGGATGGCATCAACTGTTCCAAAAACATTGCTGAGCTGGACTTTGTATTTCCCAGCATGAGTCTTACGTTGGACATTCTTCATGACAAGATGAGTATAGTGCTCAGTGTTTTCAATAGTAATGTTTTCTGAGTTTTGCAAAAGTTTCTGACCATGGAACCAAGTCATGGCAGGTACTGGACGACCAATGTACATAACATGAAGCCGAAGTGTGGAACCCACAGCTCCATAATATTTCTCTTTCAGTGGGTAACCAGGATGGAACTGCGGTGTTGCTTGCAGGAGAAGCTTACTACTGGTTTCTACTTCTCCAACCTCATTGGTGGCTATGCAGGCACTGTCTCCAGACTGTCTATATTCAACCCAGTATCCAAGAATTTCTTTACCACCATCACATTCAGGTTTCTCCCACTGTAGAGTGACACTATCTTTGGATATTGAAAGAATCTCAAGTTCTCCTGGTTGGCTTGGTTTATCTGAAATATTTTAAAATAATGAAAAGGGAGTCAGCTTTACTGGTGAAATAAAAGGACCAAACATGGCTTGCTTCTTTAATTTAACCCCTTCTTCTGAATTCCTTACCAAATGGATCTTTGCAAACAACTGGTTCAGAAGCAGGGCTGGTCTCACTCAGGCCAACATCATTCTGTGCGATGATGCGGAACTGATACTCAGCATCGGGAACAAGCCCTGTGACAGTGTACATTGTGGTGGTGATCTGAGTCTTGTTGTGTCTGACCCACTTGTCAGTGGATGTCTCTTTGCGTTCGATGTAGTAGCCTGTGACTCTAGAACCACCATCATCTTTGGGCCGGGACCAGGACAAGCTAACAGAACTCTTGGTTACATCGAGTACTTCTGGAGGATTGCTTGGAGGTTCTGGAGGATCTGTAAATATAAGTGGAAAGCACACATGTATTAGAATACAGTCCCAAGTATTATAAGCCAATGACTTTCATTTAAAAACAGAAAAGTGCTGAAATAATGTTTATAATTTTGTGGTTGAAAGGGCACTTACTCAATGGTGTTTTTGGTGTGACTGGTTCCTCAGATTTCAAGGGTTTGCTTATGCCAAACTGGTTTTCTGCTGAAACACGGAAATGGTATTCTACATTCTCTTTGAGGCCTTTTACCACCAGAGATGTACCTCGGACTCTGGAATCAATGGTATACCAGGCGGCTTTAGGCACTTCTCGTCTCTCGAGGATGTAGCCTAAGATGTCAGCACCACCATCATCAGCAGGAGGTCTCCAGCTGACCCTCACAGAGCGGACTTGGATGTCATCATATTCCAGTGGCCCTTCTGGACTGTTGGGACTTCCTATCACCCTGACCTTGATGTAGACAGCCTTCTTGCCACATTTATTTTCCAGAACCAGGTCATAAGTGCCAGAATCACCCCTGTCTGCTTCTTTGATCACAAGCTCAGTGTGTGTTTCAGATGTTGCAATCATGGCACGCTTACTAATATCCTGGCCTTCCTTGGTCCATTTACATATTGGGAATGGTTTTCCTTTGATTGGTATGCAGGCTCACCAGGTCCACCAGCATTACAAGCTAGGACGCGGAACCTGTATTCTGCACCCTGAGAATCAGAGGTGGGGAGAGTGGTGGAAGGGCCTGTGGA The present invention provides a kit for detecting sepsis-related acute liver injury, comprising:

[0010] Primers or probes for the specific detection of TTN-AS1, and / or antibodies or reagents for the detection of TNFSF14.

[0011] This invention provides any of the following applications of lncRNA TTN-AS1:

[0012] (1) Regulate serum transaminase ALT and AST levels;

[0013] (2) Regulates the levels of IL-6, TNF-α, IL-10, TGF-β1 and IFN-γ;

[0014] (3) Regulates the degree of disordered arrangement of hepatocytes, regulates the degree of liver tissue edema, and regulates hepatocyte necrosis;

[0015] (4) Application of targeted intervention of lncRNA TTN-AS1 to reduce or treat liver damage.

[0016] Specifically, the application method is as follows: overexpression of lncRNA TTN-AS1 leads to elevated serum transaminase ALT and AST levels;

[0017] Overexpression of lncRNA TTN-AS1 increases the levels of IL-6, TNF-α, IL-10, TGF-β1, and IFN-γ.

[0018] Overexpression of lncRNA TTN-AS1 increases the degree of disordered hepatocyte arrangement, aggravates liver tissue edema, increases hepatocyte necrosis and hepatocyte apoptosis.

[0019] This invention has at least the following beneficial effects:

[0020] This invention reveals for the first time the pro-inflammatory role of TTN-AS1 in SALI, suggesting that it may serve as a potential early diagnostic biomarker and therapeutic target for SALI. It also proposes that lncRNA TTN-AS1 is an important molecule mediating liver damage in sepsis, and it has significant application prospects in the early detection, early diagnosis, and targeted therapy of sepsis-related liver injury. Attached Figure Description

[0021] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1For the identification of DEGs. A is a volcano plot of DEPs; and heatmaps of DEPs (B), DEmRNAs (C), DEcircRNAs (D), DElncRNAs (E), and DEmiRNAs (F).

[0023] Figure 2 Functional enrichment of DEPs. Enrichment analysis of GO(A,B) and KEGG(C,D) of DEPs.

[0024] Figure 3 For the construction of a weighted gene co-expression network: A. Selecting the optimal soft threshold power. B. Gene clustering diagrams based on topological overlap and different similarity of specified module colors. C. WGCNA reveals a total of 7 modules.

[0025] Figure 4 Acquisition and functional enrichment analysis of R-DE mRNAs. A. Genes overlapping with differentially expressed genes within the red module. BD. GO enrichment analysis of R-DE mRNAs. E. KEGG enrichment analysis of R-DE mRNAs.

[0026] Figure 5 Functional enrichment analysis of R-DEmiRNAs and R-DElncRNAs target genes. AC represents GO enrichment analysis of DElncRNAs target genes. D represents KEGG enrichment analysis of DElncRNAs target genes. EG represents GO enrichment analysis of DEmiRNAs target genes. H represents KEGG enrichment analysis of DEmiRNAs target genes.

[0027] Figure 6 This section describes the construction of an mRNA-lncRNA co-expression network. Elliptical nodes represent R-DE mRNAs, and triangular nodes represent R-DE lncRNAs. Blue lines represent mRNA-lncRNA interactions, and gray lines represent mRNA-mRNA interactions.

[0028] Figure 7 For external dataset validation and key gene screening. Volcano plots of DEmRNAs (A), DElncRNAs (B), and DEmiRNAs (C) in GSE142255. Heatmaps of DEmRNAs (D), DElncRNAs (E), and DEmiRNAs (F). Genes overlapping with G-demrna, R-DEmRNA, and DEP. Genes overlapping with G-DElncRNA and R-DElncRNA.

[0029] Figure 8TTN-AS1 is highly expressed in SALI. A is a violin plot of TTN-AS1 in GSE142255. B is a volcano plot of TTN-AS1 in whole transcriptome resequencing. C shows the expression of TTN-AS1 in different normal tissues.

[0030] Figure 9 The expression of lncRNA TTN-AS1 was upregulated in the liver tissue of septic mice. Overexpression of lncRNA TTN-AS1 upregulated hepatocyte apoptosis and aggravated the levels of inflammatory factors in septic mice. A shows the expression of TTN-AS1 in the liver tissue of different groups of mice detected by qRT-PCR. BC shows the expression of ALT and AST in the serum of each group of mice detected by ELISA. DH shows the expression of IL-6, TNF-α, IL-10, TGF-β1, and IFN-γ in the serum of each group of mice detected by ELISA. I shows the HE staining and VDBP immunohistochemical analysis of the liver tissue of each group of mice 24 h after surgery. Black arrow: hemorrhage; blue arrow: edema and abnormal hepatic sinusoidal structure; red arrow: inflammatory cell infiltration; green arrow: hepatocyte necrosis. J shows the TUNEL staining analysis of the liver tissue of each group 24 h after surgery. Detailed Implementation

[0031] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0032] The main objective of this invention is to provide the application of lncRNA in sepsis-induced liver injury. Specific embodiments are as follows:

[0033] 1. Research and approval

[0034] All animal experiments were conducted in accordance with the "Guidelines for the Management and Use of Laboratory Animals" approved by the Laboratory Animal Welfare and Ethics Committee of Chongqing University and the Guidelines for the Management and Use of Laboratory Animals of the National Institutes of Health (IACUC No.: CQU-IACUC-RE-202504-022). Human studies were approved by the Ethics Committee of Chongqing University Central Hospital (Clinical Research Ethics No.: 202555), and the ethical principles complied with the relevant requirements of the October 2024 update of the Declaration of Helsinki. All participants signed written informed consent forms before inclusion in the study.

[0035] 2.1 Data Download and Data Preprocessing

[0036] We downloaded the dataset GSE142255 (GPL17586) from the Gene Expression Omnibus (GEO) database (https: / / www.ncbi.nlm.nih.gov / geo / ). This dataset contains 8 SALI patients and 7...

[0037] Whole blood samples from healthy volunteers were used for whole transcriptome sequencing.

[0038] 2.2 Data Preprocessing

[0039] After standardizing, annotating, and cleaning the clinical information in dataset GSE142255, the R package "limma" was used to identify differentially expressed mRNAs (DEmRNA), miRNAs (DEmiRNA), and lncRNAs (DElncRNA), with |logFC|>0.585 and pvalue<0.05 as cutoff values.

[0040] 2.3 Collection and processing conditions of whole blood samples for whole transcriptome sequencing

[0041] The study protocol was approved by the Ethics Committee of the Fourth People's Hospital of Chongqing. Sixteen whole blood samples were collected from healthy volunteers (n=8) and patients with sepsis-induced liver injury (n=8). Whole blood was collected via venipuncture, injected into PAXGene tubes (BD company), and RNA was extracted using column-mounted DNase digestion (Qiagen). Excess globin transcripts were removed using GLOBINclear (Ambion). RNA concentration was measured using a NanoDrop spectrophotometer, and RNA integrity was assessed using a Bioanalyzer 2100 (Agilent), validated by agarose gel electrophoresis. Concentration >50 ng / μL, RIN value >7.0, OD260 / 280 >1.8, and total RNA >2 μg met the requirements for downstream experiments. All patients provided written informed consent. The definition of sepsis met the Sepsis 3.0 Diagnostic Criteria. Figure 1 According to the Surviving Sepsis Campaign (SSC) guidelines, total bilirubin (TBIL) >2 mg / dL and international normalized ratio (INR) >1.5 are recommended as diagnostic criteria for SALI.

[0042] 2.4 RNA sequencing and bioinformatics analysis

[0043] Illumina Novaseq provided by Hangzhou Lianchuan Biotechnology Co., Ltd. TM RNA sequencing, including mRNA, lncRNA, and circRNA, was performed using Illumina Hiseq. TM miRNA sequencing was performed at 2500. To construct a competitive endogenous RNA (ceRNA) network, potential interactions between circRNA-miRNA or lncRNA-miRNA and miRNA-mRNA were downloaded from the ENCORI online webtool (http: / / starbase.sysu.edu.cn / ). Pearson correlation analysis was used to screen for relevant lncRNA-mRNAs. After cross-expressing differentially expressed mRNAs, miRNAs, lncRNAs, and circRNAs, a lncRNA-mRNA co-expression network based on correlation coefficients and p-values ​​was constructed using Cytoscape 3.8.0 software. The protein-protein interaction (PPI) was analyzed on the STRING website (http: / / string-db.org / ) and visualized using Cytoscape 3.8.0. The R package "DESeq2" was used to identify differentially expressed mRNAs (DEmRNA), miRNAs (DEmiRNA), lncRNAs (DElncRNA), and circRNAs (DEcircRNA), with a cutoff value of |log2FC|>2.0 and p-value<0.05.

[0044] 2.5Weighted Gene Co-Expression Network Analysis

[0045] For WGCNA, outlier samples are removed to ensure the reliability of the network construction results. First, a soft threshold is selected for network construction. The adjacency matrix consists of continuous values ​​between 0 and 1, thus the constructed network conforms to a power-law distribution, more closely resembling the real biological state. Second, a scale-free network is constructed using a block module function, and module partitioning analysis is performed to identify gene co-expression modules. These modules are defined by gene branches using a dynamic tree slicing algorithm and assigned different colors for visualization. All modules are summarized by module feature (ME) genes. Module feature genes are the most important component of each module and are calculated as synthetic genes representing the expression profile of all genes in a given module.

[0046] 2.6 Enrichment Analysis

[0047] Enrichment analysis was performed using the R package “clusterprofiler”, which included Gene Ontology (GO) and KEGG. GO included three items: Biological Processes (BP), Cellular Components (CC), and Molecular Functions (MF). Enrichment results with a false discovery rate (FDR) ≤ 0.05 were selected.

[0048] 2.7 Serum Sample Collection and Inflammation-Related Protein Analysis

[0049] We collected 5 ml of peripheral venous blood from 8 SALI patients, placed it in test tubes, centrifuged at 3,000 rpm for 15 minutes, extracted the serum, and stored it at -80°C until further analysis. Following the manufacturer's instructions, we used the... The target 92 inflammation panel (Olink Proteomics, LC-Bio Technology Co., Ltd., Hangzhou, China) was used to quantify protein levels. Olink inflammation-related protein expression profiles from healthy volunteers were downloaded as a control group from https: / / github.com / SonnenburgLab / fiber-fermented-study / . Normalized Protein Expression (NPX), an arbitrary unit on the Log2 scale, was used to assess current protein abundance. High protein levels imply high NPX values. However, it cannot compare NPX values ​​between different proteins. The R package "OlinkAnalyze" was used to find differentially expressed proteins (DEPs) between groups. Principal component analysis (PCA) was performed using the "princomp" function in R software, which highlights the most important aspects of data variability. Heatmaps and volcano plots were generated using ggplot2.

[0050] 2.8 Animals

[0051] Eight-week-old specific pathogen-free (SPF) male C57BL / 6J mice were purchased from Hunan Slaike Jingda Laboratory Animal Co., Ltd. Mice were housed in individually ventilated cages (IVCs) at 45%–55% humidity with a 12-hour light-dark cycle and received human care according to the National Institutes of Health's guidelines for animal research. Mice were randomly divided into four groups of five mice each: sham-operated group, model group, model + empty transfection vector group, and model + TTN-AS1 overexpression transfection vector group.

[0052] 2.9 Construction of a CLP sepsis mouse model

[0053] Based on previous research, a mouse sepsis model was established using the cecum ligation and puncture (CLP) method. [RITTIRSCH D,HUBER-LANG M S,FLIERL M A,et al.Immunodesign of experimental sepsis by cecal l igation and puncture[J].Nat Protoc,2009,4(1):31-6.,COLETTA C, K, G,et al.Endothelial dysfunction is a potential c ontributor to multiple organ failure and mortality in aged mice subjected to septic shock :preclinical studies in a murine model of cecal ligation and puncture[J].Crit Care,2014,18(5):511] After weighing and recording the mice's weight, they were anesthetized by intraperitoneal injection of 1% sodium pentobarbital (50 mg / kg) on ​​a heated mat. Once the mice had completely lost their pain reflexes, the abdominal hair was shaved and the area was routinely disinfected with 75% alcohol and povidone-iodine. A 1 cm incision was made along the midline of the abdomen, the subcutaneous tissue was gently dissected, and the peritoneum was opened to carefully expose the cecum. The cecum was gently lifted to the outside of the abdominal wall using blunt forceps. A non-absorbable suture (4-0) was used to ligate the cecum at approximately 50% of its distal end. Subsequently, a single penetrating puncture was performed on the cecum using a 21G needle, and a very small amount of feces was gently expelled to ensure patency. The cecum was repositioned into the abdominal cavity, and the abdominal muscles and skin were sutured in layers using absorbable sutures. Postoperatively, 1 ml of sterile saline was administered subcutaneously for rehydration. In the sham surgery group, only the cecum was exposed without ligation or puncture; the remaining steps were the same. The mice were kept warm on a heated mat and returned to their cages after recovery. Mice were fasted for 12 hours before sampling for animal experiments. Twenty-four hours post-surgery, mice were sacrificed, blood samples were collected and centrifuged. Liver tissue was collected, fixed with 4% paraformaldehyde, and used for histological examination.

[0054] 2.10 In vivo transfection

[0055] Entranster in vivo transfection reagent (Engreen Biosystem Co.) was used to administer 1 mg / kg of the TTN-AS1 overexpression plasmid (pcDNA3.1-TTN-AS1) via tail vein injection 2 hours before CLP-induced sepsis in mice. Transfection was performed according to the manufacturer's instructions. An empty vector (pcDNA3.1-NC) was used as a negative control. Both pcDNA3.1-NC and pcDNA3.1-TTN-AS1 were purchased from GeneCopoeia.

[0056] 2.11 RNA extraction, reverse transcription, and qPCR

[0057] Total RNA was extracted from liver tissue using Trizol (Thermo Fisher Scientific, Waltham, MAUSA) according to the manufacturer's instructions. The required reverse transcription system was prepared using a high-capacity cDNA reverse transcription kit (Thermo Fisher Scientific, Waltham, MAUSA), and then the RNA was transcribed into cDNA using a standard PCR instrument. Quantitative real-time PCR was performed using a ChamQ Universal SYBR qPCRMasterMix (Vazyme, Nanjing, China) on a 7500 real-time PCR instrument (Applied Biosystems, USA) according to the manufacturer's protocol. GAPDH was used as an internal control to normalize mRNA levels. Relative mRNA levels were calculated using the 2-ΔΔCt comparison method. Each experiment was repeated three times. The relevant primer sequences are as follows: GAPDH, forward 5′-GGTTGTCTCCTGCGACTTCA-3′ and reverse 5′-TGGTCCAGGGTTTCTTACTCC-3′; TTN-AS1, forward 5′-TCCTGGTTGGCTTGGTTTATC-3′ and reverse 5′-TATCAGTTCCGCATCATCGC-3′.

[0058] 2.12 HE staining

[0059] The fixed tissue was removed, transferred to a gradient of ethanol, and embedded in paraffin for histopathological analysis. Tissue sections of approximately 4 μm were dewaxed with xylene and hydrated sequentially with a gradient of ethanol. They were then stained with hematoxylin and rinsed with tap water for several minutes to ensure adequate staining. The sections were then differentiated with 1% hydrochloric acid ethanol and blued with tap water, followed by staining with eosin. Finally, they were dehydrated with a gradient of ethanol, cleared with xylene, and mounted with neutral resin.

[0060] 2.13 Immunohistochemistry

[0061] Tissue sections (approximately 4 μm thick) fixed in 4% paraformaldehyde and embedded in paraffin were dewaxed with xylene, then hydrated sequentially with a gradient of ethanol, and incubated at 108°C in citrate buffer (pH 6.0) for 5 minutes for antigen retrieval. Subsequently, they were incubated at room temperature with 3% hydrogen peroxide solution to block endogenous peroxidase activity, and then blocked with 5% goat serum to prevent nonspecific binding. Next, slides were incubated overnight at 4°C with primary antibodies caspase-3 (1:200, HUABIO, ER30804) and BAX (1:200, HUABIO, ER0907). The following day, after washing with PBS, the slides were incubated with secondary antibody (1:500) (horseradishperoxidase-conjugated anti-rabbit IgG) and then developed with diaminobenzidine (DAB) substrate.

[0062] 2.14 TUNEL staining

[0063] We used the TUNEL apoptosis detection kit (Roche) to detect paraffin sections according to the manufacturer's protocol. In short, after dewaxing and hydration, tissue sections were permeabilized with Proteinase K, then incubated with TUNEL reaction solution at 37°C for 1 h, washed with PBS, and then washed with 0.1% Triton X-100. DNase I pretreatment was used as a positive control, and TUNEL reaction mixture lacking terminal transferase (TdT) was used as a negative control. Samples were analyzed by optical microscopy.

[0064] 2.15Enzyme-Linked ImmunosorbentAssay (ELISA) analysis

[0065] According to the manufacturer's protocol (MultiSciences Biotech Co., Ltd., Zhejiang, China), the levels of IL-6, IL-10, TNF-α, TGF-β1 and IFN-γ in serum were measured using an enzyme-linked immunosorbent assay (ELISA) kit.

[0066] 3 Results

[0067] 3.1 Identification of DEGs

[0068] To investigate the potential targets and molecular mechanisms of SALI, we performed whole blood RNASeq and Olink proteomics sequencing. A total of 65 inflammation-related DEPs were identified between the SALI group and the control group, including 43 downregulated proteins and 22 upregulated proteins. Figure 1(A, B). In addition, 2774 DE mRNAs were identified between the SALI group and the control group (804 upregulated, 1970 downregulated). Figure 1 In the middle C), 1304 DEcircRNAs were detected (558 upregulated and 746 downregulated). Figure 1 In the middle D), 3438 DElncRNAs (1284 upregulated, 2154 downregulated), Figure 1 (E) and 114 DEmiRNAs (60 upregulated, 54 downregulated), Figure 1 (F). As shown in the heatmap, the intervention group and the control group were clearly separated.

[0069] 3.2 Functional enrichment of DEPs

[0070] The biological activities of DEPs in the SALI group and the control group were further investigated. In biological processes, a large number of DEPs are involved in leukocyte migration, positive regulation of leukocyte activation, positive regulation of cell activation, positive regulation of cytokine production, and cell chemotaxis. At the molecular level, they are enriched in the external side of the plasma membrane, neuronal cell body, cytoplasmic vesicle lumen, and vesicle lumen. At the cellular level, they are related to cytokine activity, cytokine receptor binding, growth factor activity, and G protein-coupled receptor binding. Figure 2 (A, B). In pathway analysis, DEPs are associated with cytokine-cytokinereceptor interaction, viral protein interaction with cytokine and cytokinereceptor, IL-17 signaling pathway, asthma, rheumatoid arthritis, inflammatory bowel disease, chemokine signaling pathway, malaria, and TNF signaling pathway. Figure 2(C,D). Therefore, these DEPs are associated with the regulation of inflammatory responses, immune cell activation and migration, as well as the activities and structures of various organelles.

[0071] 3.3 Construction of a weighted gene co-expression network

[0072] Whole blood RNASeq data from 16 volunteers were incorporated into WGCNA. To ensure the network was scale-free, a soft threshold of β=9 was chosen. Figure 3 (A). Next, we convert the expression matrix into an adjacency matrix, and then into a topological matrix. We cluster the genes using the average linkage hierarchical clustering method. We also determine the gene modules by setting the minimum number of genes in each gene network module to 300, according to the standard of hybrid dynamic pruning trees, and calculate the feature gene values ​​for each module. The parameters are set as follows: depth split(deepSplit) = 2, minimum module(minModuleSize) size = 300; a total of 7 modules are obtained ( Figure 3 (Medium B). Using clinically relevant indicators from 16 volunteers as phenotypic data, the correlation between modules and clinically relevant indicators was calculated. Results showed that among multiple modules, the red module had the strongest correlation with ALT and AST (cor = 0.55, p < 0.05). Figure 3 The result of the C-cell pattern suggests a close relationship with liver dysfunction, therefore we will focus on this module in the future.

[0073] 3.4 Acquisition and functional enrichment analysis of R-DE mRNAs

[0074] R-DEG refers to DEG genes that overlap with the red module generated by WGCNA. A total of 476 R-DEGs were identified (including 194 mRNAs, 8 circRNAs, 264 lncRNAs, and 10 miRNAs). Figure 4 (A). Our functional enrichment analysis of 194 R-DE mRNAs using GO and KEGG revealed that numerous DEPs are involved in biological processes such as phospholipid metabolic processes, chemotaxis, and glycerolipid metabolic processes. Figure 4 (B); In terms of molecular function, they are enriched in phospholipid binding, transcription corepressor activity, telomeric DNA binding, etc. Figure 4In terms of cellular components, they are related to the vacuolar membrane, chromosomal region, lytic vacuole membrane, etc. Figure 4 In pathway analysis, DEPs were associated with endocytosis, Alzheimer's disease, mTOR signaling pathway, Huntington's disease, etc. Figure 4 (E).

[0075] 3.5 Functional enrichment of target genes of R-DE miRNAs and R-DE lncRNAs

[0076] To comprehensively investigate the functions of differentially expressed non-coding RNAs (DEPs), we performed enrichment analysis on the target genes of R-DEmiRNAs and R-DElncRNAs. Target genes of R-DEmiRNAs: In biological processes, numerous DEPs are involved in macroautophagy, regulation of neuron projection regeneration, and cardiac septum development, etc. Figure 5 (A); In terms of molecular function, they are enriched in protein serine / threonine kinase activity, growth factor binding, and protein serine kinase activity. Figure 5 (B) In terms of cellular components, they are related to transferase complex transferring phosphorus-containing groups, protein kinase complex, cell leading edge, etc. Figure 5 (C); In pathway analysis, they are related to Proteoglycans in cancer, mTOR signaling pathway, and signaling pathways regulating the pluripotency of stem cells, etc. Figure 5(D). R-DE lncRNAs cis-regulated genes: In biological processes, they participate in RNA via transesterification reactions with bulged adenosine asnucleophile, mRNA splicing, RNA splicing, and transesterification reactions, etc. Figure 5 In terms of molecular function, they are enriched in cadherin binding, GTPase binding, transcription corepressor activity, etc. Figure 5 In terms of cellular components, they are related to focal adhesion, cytosolic large ribosomal subunit, nuclear speckle, etc. Figure 5 In pathway analysis, they are related to Ubiquitin-mediated proteolysis, cell cycle, and Focal adhesion. Figure 5 In summary, the target genes of R-DEmiRNA and R-DElncRNA are enriched in key biological processes and signaling pathways such as autophagy regulation, signal transduction, RNA processing, and cell adhesion, suggesting that they may play a synergistic regulatory role in tissue repair, immune regulation, and cellular homeostasis imbalance in SALI.

[0077] 3.6 Construction of mRNA-lncRNA co-expression network

[0078] To investigate the role and mechanism of DElncRNA in the red module, an mRNA-lncRNA co-expression network was constructed. Figure 6 We found that 64 mRNAs and 126 lncRNAs mutually regulate each other, and one lncRNA is co-expressed with multiple mRNAs. Furthermore, multiple lncRNAs are also co-expressed with one mRNA, indicating a complex regulatory relationship between mRNAs and lncRNAs in the differential co-expression network.

[0079] 3.7 External dataset validation and screening of key genes

[0080] We further used GSE142255 from the public database as a validation dataset. Through differential analysis, we identified 788 DE mRNAs from GSE142255 (282 upregulated and 506 downregulated). Figure 7 In the middle (A, D), 17 DElncRNAs (2 upregulated, 15 downregulated), Figure 7 (Tables B, E, and Supplementary Table S9) 16 DEmiRNAs (5 upregulated, 11 downregulated) Figure 7 (C, F). Considering the close correlation between mRNA and protein, we cross-referenced 788 DE mRNAs, 194 R-DE mRNAs, and 65 inflammation-related DEPs in GSE142255 to obtain the upregulated inflammation-related gene TNFSF14 (C, F). Figure 7 In addition, we intercalated the DElncRNA and DEmiRNA in GSE142255 with the DElncRNA and DEmiRNA in R-DEGs, respectively, to obtain lncRNATTN-AS1 ( Figure 7 (H). To investigate DE lncRNAs that may be associated with inflammation-related mRNAs, we selected lncRNA TTN-AS1 for further research.

[0081] 3.8TTN-AS1 is highly expressed in SALI

[0082] In the GSE142255 dataset, the expression levels of TTN-AS1 were extracted from the normal donor group and the SALI group, and the expression difference between the two groups was detected by Wilcox test. The expression of TTN-AS1 in the SALI group was higher than that in the normal group ( Figure 8 (A). In the whole transcriptome sequencing data, the TTN-AS of the SALI group was significantly different from that of the healthy group. Figure 8 (B). Meanwhile, the NCBI website (https: / / www.ncbi.org / ) shows that RNA sequencing data from 99 individuals and 27 normal tissue samples indicate that TTN-AS1 has significant tissue specificity, with the lowest expression level in the liver. Figure 8 (C)

[0083] 3.9 lncRNA TTN-AS1 was upregulated in the liver tissue of septic mice.

[0084] After establishing a CLP mouse model, the expression of lncRNA TTN-AS1 in the liver tissue of septic mice was detected by qRT-PCR. The results showed that lncRNA TTN-AS1 was significantly upregulated in the sepsis group. Figure 9 (A). Serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels were detected by ELISA. The results showed that ALT and AST levels in the sepsis group were significantly higher than those in the sham-operated group. Figure 9(B, C). In addition, ELISA was used to detect the levels of inflammatory factors interleukin (IL)-6, tumor necrosis factor α (TNF-α), IL-10, transforming growth factor β1 (TGF-β1), and interferon-γ (IFN-γ) in peripheral blood. The results showed that serum IL-6, TNF-α, IL-10, TGF-β1, and IFN-γ in the sepsis group were significantly lower than those in the sham-operated group. Figure 9 (H&E staining was then used to assess the degree of liver damage. The results showed that the hepatocytes of septic mice were disorganized, edema was increased, and inflammatory cells were infiltrated, and the Suzuki liver injury score was upregulated.) Figure 9 (I). The above results indicate that the mouse sepsis model was successfully established, and lncRNA TTN-AS1 was highly expressed in the liver tissue of sepsis-affected mice.

[0085] 3.10 Overexpression of lncRNA TTN-AS1 upregulates hepatocyte apoptosis in septic mice and exacerbates inflammatory factor levels.

[0086] To verify the effect of lncRNA TTN-AS1 on SALI in vivo, we overexpressed lncRNA TTN-AS1 in septic mice. First, qRT-PCR confirmed that lncRNA TTN-AS1 was successfully overexpressed in liver tissue. Figure 9 (A). Serum transaminases ALT and AST, as well as inflammatory factors IL-6, TNF-α, IL-10, TGF-β1, and IFN-γ, were measured using ELISA in septic mice. The results showed that overexpression of lncRNA TTN-AS1 increased serum levels of ALT and AST. Figure 9 The levels of B, C), IL-6, TNF-α, IL-10, TGF-β1 and IFN-γ were elevated. Figure 9 H&E staining to detect the degree of liver damage revealed that overexpression of lncRNA TTN-AS1 resulted in disordered hepatocyte arrangement, increased edema, increased cell necrosis, and extensive infiltration of inflammatory cells, significantly upregulating the Suzuki liver injury score (Figure 9I). Immunohistochemistry showed increased expression levels of apoptosis-related proteins Caspase-3 and BAX due to overexpression of lncRNA TTN-AS1, indicating increased hepatocyte apoptosis. Figure 9 (I). TUNEL staining was used to assess liver tissue cell apoptosis, and it was found that the number of apoptotic cells significantly increased after overexpression of lncRNA TTN-AS1. Figure 9 (J). In summary, in sepsis, overexpression of lncRNA TTN-AS1 promotes the release of inflammatory factors, increases hepatocyte necrosis and apoptosis, thereby exacerbating liver damage.

[0087] 4. Conclusion

[0088] This study, for the first time, systematically screened and validated key inflammatory factors and non-coding RNA molecules associated with SALI by integrating whole transcriptome and OLINK proteome data. Based on multi-omics cross-analysis, the pro-inflammatory cytokine TNFSF14 and lncRNA TTN-AS1 were identified as significantly upregulated in SALI patients and animal models, and TTN-AS1 expression was closely related to liver function indicators. Further functional experiments confirmed that TTN-AS1 overexpression can aggravate the inflammatory response and liver tissue damage, suggesting its promoting role in SALI progression.

[0089] As a novel non-coding RNA, TTN-AS1 has not been previously reported in SALI. This study is the first to propose its potential as a regulatory factor and biomarker of inflammation, expanding our understanding of the molecular mechanisms of SALI and demonstrating significant innovation and translational potential. Furthermore, the study combined multi-omics integration, bioinformatics prediction, clinical sample validation, and animal experiments, enhancing the systematicity and reliability of the results. Despite limitations at the mechanistic level that require further exploration, the research direction of TTN-AS1 as a therapeutic target for SALI warrants further attention.

[0090] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.

Claims

1. The application of a reagent for detecting lncRNA TTN-AS1 in the preparation of a kit for detecting sepsis-induced liver injury, characterized in that, The nucleotide sequence of the lncRNA TTN-AS1 is shown in SEQ ID NO:

1.

2. The application of the reagent for detecting lncRNA TTN-AS1 in the preparation of a kit for detecting sepsis-induced liver injury, characterized in that, The kit contains: Primers or probes for the specific detection of lncRNA TTN-AS1; the nucleotide sequence of said lncRNA TTN-AS1 is shown in SEQ ID NO:1.

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