Application of biomarker BIG1 in preparation of reagent for diagnosing or monitoring sepsis immunosuppression

Abstract

The invention belongs to the technical field of biology, and particularly relates to application of a biomarker BIG1 to preparation of a reagent for diagnosing or monitoring sepsis immunosuppression. According to the invention, BIG1 expression in peripheral blood mononuclear cells is used as a biomarker to prepare a reagent for predicting sepsis immunosuppression, and by detecting the transcription or translation level of BIG1 in peripheral blood mononuclear cells or tissue macrophages, expression reduction indicates immune activation of sepsis patients, and expression increase indicates immunosuppression of sepsis patients. Therefore, individualized precise intervention treatment can be properly given, the treatment rate of sepsis is increased, reference information is provided for reasonable selection of treatment means and allocation of medical resources, and the method has important clinical application value in improvement of prognosis of sepsis patients.

Description

Technical Field

[0001] The present invention belongs to the field of biotechnology, and in particular relates to the application of a biomarker BIG1 in the preparation of a reagent for diagnosing or monitoring sepsis immunosuppression. Background Art

[0002] Sepsis is a life-threatening multi-organ dysfunction disease caused by host immune dysregulation against infection. It has long been one of the leading causes of death in intensive care unit patients. Since the World Health Organization listed it as a "global health priority" in 2017, the diagnosis and treatment of sepsis has become a major challenge that the medical community needs to overcome. Studies have shown that the initial acute inflammation of sepsis patients will quickly turn into a low immune response (immunosuppression), which will have a lasting impact on the functions of multiple organs in the body, leading to organ damage and systemic multiple organ dysfunction syndrome (MODS) and other serious diseases. At present, in addition to traditional methods such as fluid resuscitation, anti-infection treatment and symptomatic supportive therapy, there is still a lack of effective targeted treatment methods. At present, the difficulty in treating sepsis lies in the difficulty in timely determining the immune status of sepsis patients. Some patients are admitted to the hospital at the time of the first infection. At this time, the patients are basically in the acute inflammatory stage and should be given anti-inflammatory treatment; while most patients are admitted to the hospital after experiencing secondary or even multiple infections. At this time, the patient's body is often in a severe immunosuppression stage, and the patient's immune function should be enhanced. However, it is difficult to quickly determine the patient's immune status, which often leads to inappropriate treatment options, which not only fails to improve the condition, but may worsen the condition or even lead to the patient's death. Therefore, making a rapid and accurate judgment of the patient's immune status in the early stage of hospitalization is the key to treating sepsis and reducing mortality, and is also a hot topic in current research.

[0003] Existing technologies can detect monocyte HLA-DR and serum cytokine expression levels to reflect the antigen presentation ability of monocytes, and can diagnose the state of immunosuppression in patients with sepsis; however, the entire detection process requires the participation of equipment such as flow cytometers, the operation is relatively complicated, and the interpretation of results requires professional knowledge. Others, such as genomic and transcriptomic testing or flow cytometry, can provide more comprehensive immune response information and are suitable for complex immune status analysis. However, there are also defects such as expensive equipment, complex operation, high technical requirements, and complex data interpretation, which requires the participation of professionals.

[0004] Although lymphocyte counts or biomarker tests are low-cost, fast, and convenient, they generally have limited specificity and sensitivity, and may be inaccurate when used alone for diagnosis. Therefore, finding new markers to identify or diagnose the immune status of sepsis patients is an urgent problem to be solved.

[0005] The existing markers related to the immune status of sepsis mainly include interleukin 10 (IL-10), soluble leukocyte differentiation antigen 14 subtype (sCD14-ST), IL-3, costimulatory molecules HLA-DR on the surface of monocytes, tumor necrosis factor (TNF-α), etc. Among them, IL-10 is an anti-inflammatory cytokine that can inhibit the proliferation of T lymphocytes. Its elevated level is related to the level of inhibition of monocyte HLA-DR molecules and can predict the mortality rate of sepsis. However, due to limited clinical research, there is no consensus on whether the biological markers used in the evaluation of CARS can be used clinically. sCD14-ST is greatly affected by the patient's age, renal function, and G+ or G- bacteria infection. The specificity and sensitivity of IL-3 in the detection of immune status in sepsis are both low, and its positive predictive value is not ideal. HLA-DR can be used as an overall biomarker of injury-related immunosuppression, but in the early stage of sepsis, its relationship with the overactivation of the immune system is not very clear, and the correlation between its dynamic changes and the occurrence and prognosis of sepsis still needs further evidence support. TNF-α may be elevated in a variety of clinical situations, such as advanced age, acute coronary syndrome, and renal insufficiency. It has poor specificity and is greatly affected by other inflammatory factors, making it insufficient to fully reflect the complex immune status of sepsis.

[0006] Therefore, the purpose of the present invention is to find a biomarker that can stably, universally, accurately and highly sensitively reflect the immune status of patients at all stages of sepsis. Summary of the invention

[0007] ADP-ribosylation factor guanine nucleotide exchange factor 1 (BIG1) is a protein that plays an important role in intracellular vesicle trafficking. It participates in the activation of ADP-ribosylation factors (ARFs) by accelerating the process of replacing bound GDP with GTP. Arfgef1 contains a Sec7 domain, which may be responsible for guanine nucleotide exchange activity and inhibition of BrefeldinA, and plays an important role in the integrity of the Golgi apparatus, mature integrin β1 glycosylation, and the development of neurites. BIG1 is widely expressed in immune cells such as monocytes / macrophages and plays a vital role in the regulation of immune responses. However, there have been no reports on the correlation between BIG1 and sepsis or septic immunosuppression.

[0008] The present study showed that the BIG1 mRNA level of monocytes in patients with sepsis was negatively correlated with the expression of HLA-DR, TNF-α and IL-6, which can reflect the immune status of sepsis. This shows that monocyte BIG1 may be a marker reflecting the immune status of patients with sepsis. During acute inflammatory stimulation, the expression of BIG1 in bone marrow macrophages and human monocytes (THP-1) was significantly reduced; on the contrary, during endotoxin tolerance, the expression of BIG1 was significantly increased. This suggests that changes in macrophage BIG1 expression may reflect changes in the state of macrophage immune ability, and may be a new marker for monitoring the occurrence of immunosuppression in sepsis.

[0009] To address the deficiencies of the prior art, the present invention provides the use of the biomarker BIG1 in the preparation of a reagent for diagnosing or monitoring sepsis immunosuppression.

[0010] The first aspect of the present invention discloses the use of a substance for detecting a marker in a sample to be tested in the preparation of a product for diagnosing or monitoring the immune status of sepsis, wherein the marker comprises a BIG1 marker;

[0011] The sample includes a blood sample, a urine sample, a puncture fluid sample, a respiratory sample, a cerebrospinal fluid or a tissue sample.

[0012] Preferably, the blood sample includes blood, plasma, and serum;

[0013] The puncture fluid samples include pleural effusion and ascites;

[0014] The respiratory samples include sputum and bronchoalveolar lavage fluid.

[0015] The second aspect of the present invention discloses a product, which includes a substance for detecting a BIG1 marker;

[0016] The products include products for diagnosing or assisting in diagnosing the immune status of sepsis in a sample to be tested, and products for diagnosing or assisting in diagnosing the immune status of sepsis in a subject to be tested;

[0017] The products include products for monitoring or assisting in monitoring the sepsis immune status of a sample to be tested, and products for monitoring or assisting in monitoring the sepsis immune status of a subject to be tested.

[0018] Preferably, in the above product, the substance for detecting the BIG1 marker includes a substance for detecting gene expression level or a substance for detecting protein level;

[0019] The products include reagents, test kits, test strips, nucleic acid membrane strips, chips, primers, and probes;

[0020] The test subject includes a human or a non-human mammal;

[0021] Among them, the reagents include detecting the presence of BIG1 genes, fragments and proteins in the sample through PCR reaction, RT-PCR derivatization reaction, 3SR amplification, LCR, SDA, NASBA, TMA, SYBR Green, TaqMan probe, molecular beacon, double hybridization probe, composite probe, ISH, microarray, Southern blot, Northern blot, multi-analyte spectrum test, enzyme-linked immunosorbent assay (ELISA), radioimmunoassay, immunofluorescence assay, enzyme immunoassay, immunoprecipitation assay, chemiluminescence assay, immunohistochemistry assay, dot blot assay or slot blot assay.

[0022] Preferably, the kit includes a gene detection kit and a protein detection kit.

[0023] The third aspect of the present invention discloses the use of the marker BIG1 as a target in constructing a sepsis immunosuppression model, wherein the model includes an animal model and a cell model.

[0024] The fourth aspect of the present invention discloses the use of the marker BIG1 in the preparation of a drug for regulating the immune status of sepsis patients.

[0025] Preferably, the medicament comprises an agent that knocks out or knocks down BIG1, an agent that inhibits the activity of BIG1, or a substance that increases the level or activity of a BIG1 inhibitor.

[0026] The fifth aspect of the present invention discloses a risk prediction model for the immune status of sepsis, wherein the prediction model includes a risk prediction model constructed by model training using a machine learning method, and the machine learning method includes a process of machine training using a BIG1 marker; using the risk prediction model, the immune status of sepsis can be predicted based on the detected BIG1 marker content.

[0027] The machine learning methods include decision tree models, random forest models, K-nearest neighbor algorithm models, naive Bayes models, support vector machine models, and neural network models.

[0028] A sixth aspect of the present invention discloses a sepsis immune status monitoring system.

[0029] The monitoring system includes a result determination module for comparing a processed value of a marker obtained by detecting the gene or protein expression level of a BIG1 marker with a set value;

[0030] The monitoring system includes a processing module, which is used to detect and process the expression level of genes or proteins related to markers in the sample to obtain a processing value; and to determine the immune state of sepsis.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] (1) New biomarkers: The present invention proposes the use of BIG1 as a biomarker of the immune status of sepsis, which is an important supplement to existing markers (such as IL-10, sCD14-ST, IL-3, HLA-DR, TNF-α, etc.). These existing markers have certain limitations, such as poor specificity, being greatly affected by other factors, and having an unstable relationship with the immune status of sepsis.

[0033] (2) Higher diagnostic accuracy: Studies have shown that the BIG1 mRNA level in monocytes of patients with sepsis is negatively correlated with the mRNA levels of HLA-DR, TNF-α, and IL-6, suggesting that BIG1 may be a more accurate marker for diagnosing the immune status of patients with sepsis.

[0034] (3) Stronger ability to monitor immune response: The present invention also provides an application of using BIG1 as a marker to monitor the immune response ability of sepsis patients, which helps to more comprehensively evaluate the immune status of patients.

[0035] (4) Multi-level detection: The detection of BIG1 levels in the present invention includes mRNA transcription level and protein expression level, which provides flexible detection options for clinical use. The present invention provides a variety of methods for detecting BIG1 levels, including PCR, qPCR, RT-qPCR, digital PCR, constant temperature amplification method, ELISA, western blot, immunochromatography, immunoturbidimetry, etc., providing a more comprehensive detection method.

[0036] (5) Comprehensiveness of the reagent: The BIG1 level detection reagent provided by the present invention includes multiple components such as detection primers, detection probes, aptamers and antibodies, providing comprehensive technical support for the accurate detection of BIG1 levels.

[0037] (6) Targeted therapeutic strategies: Reagents that knock out or knock down BIG1, reagents that inhibit BIG1 activity, and substances that increase the level or activity of BIG1 inhibitors may be used to regulate the immune status of patients with sepsis, as well as to construct sepsis immunosuppressive animal or cell models, providing new strategies for the treatment of sepsis.

[0038] (7) Application of model construction: The present invention also provides the application of BIG1 as a target in constructing a sepsis immunosuppression model, including an animal model and a cell model, which is helpful for studying the pathogenesis of sepsis and evaluating the treatment effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1The expression of HLA-DR on the surface of monocytes, the ratio of TNF-α / IL-10, and the levels of IL-6 and IL-1β were used to evaluate the immune level of patients with sepsis.

[0040] Figure 2 Results of correlation analysis between BIG1 mRNA expression in monocytes of patients with sepsis and indicators for monitoring the immune status of sepsis (HLA-DR, TNF-α / IL-10, IL-6, IL-1β).

[0041] Figure 3 A and B in the middle are Western blots to detect the protein level of BIG1; Figure 3 Middle C is the result of BIG1 mRNA after LPS stimulation.

[0042] Figure 4 Transcription levels of TNF-α, IL-6, IL-1β, IL-12p40, IL-10, and BIG1 genes at different time points after secondary LPS stimulation.

[0043] Figure 5 Figure 2. Results of the different factors affected during endotoxin tolerance.

[0044] Figure 6 Figure 3. Results of secondary infection model established by intravenous injection of Escherichia coli in immunosuppressed CLP mice.

[0045] Figure 7 A graph showing the effects of pro-inflammatory factors in mouse peritoneal macrophages after deletion of the myeloid BIG1 gene.

[0046] Figure 8 The expression results of different factors in peripheral blood were detected by enzyme-linked immunosorbent assay (ELISA) under different models. DETAILED DESCRIPTION

[0047] Sepsis: Sepsis is a life-threatening multi-organ dysfunction disease caused by host immune dysregulation to infection.

[0048] BIG1: ADP ribosylation factor guanine nucleotide exchange factor 1 (BIG1), plays an important role in intracellular vesicle transport, immune regulation and other processes.

[0049] Monocytes: The largest white blood cells in the blood, a type of immune cell. They originate from precursor cells in the bone marrow and mature in the blood circulation. Monocytes live in the blood for about 24 hours, after which they migrate to tissues and differentiate into macrophages or dendritic cells. Monocytes play an important role in the immune system, engulfing and digesting pathogens, dead cells and other foreign matter, participating in inflammatory responses, and playing a role in antigen presentation in adaptive immune responses.

[0050] Macrophages: Macrophages are large phagocytes in the immune system and are widely distributed in various tissues of the body. They originate from precursor cells in the bone marrow, then migrate to various tissues and mature. The main function of macrophages is to engulf and digest foreign particles, microorganisms, dead cells and tissue debris. In addition to direct phagocytosis, macrophages can also participate in inflammatory responses and immune regulation by secreting cytokines and chemokines, and also play a role in tissue repair and tumor immunity.

[0051] Endotoxin tolerance: The phenomenon that after the body is exposed to a small dose of endotoxin (usually refers to the cell wall components of Gram-negative bacteria, such as lipopolysaccharide LPS), it develops tolerance to the inflammatory response caused by a large dose of endotoxin. In the tolerant state, the cell's response to endotoxin is weakened, resulting in a decrease in the production of inflammatory factors. This tolerance is a protective mechanism of the body that prevents excessive inflammatory responses from causing damage to its own tissues. However, endotoxin tolerance may also lead to a weakened response to infection in the body and affect immune defense capabilities.

[0052] Marker: refers to a gene or gene product that is a target for modulating one or more target phenotypes (e.g., a target phenotype in myeloid cells). In this context, the term "marker" is synonymous with "target." The term also encompasses compositions that modulate genes or gene products.

[0053] Sample to be tested: can be any biological sample separated from a subject. The term "sample" includes any biological sample that can be extracted from a subject, untreated, treated, diluted or concentrated. Samples may include, but are not limited to, biological fluids, such as whole blood, serum, red blood cells, white blood cells, plasma, saliva, urine, feces (i.e., feces), tears, sweat, sebum, nipple aspirate, duct lavage fluid, tumor exudate, synovial fluid, ascites, peritoneal fluid, amniotic fluid, cerebrospinal fluid, lymph fluid, fine needle aspiration fluid, amniotic fluid, any other body fluid, cell lysate, cell secretion, inflammatory fluid, semen and vaginal secretion. Samples may include tissue samples and biopsy samples, tissue homogenates, etc. Samples refer to those containing any one or more biomarkers described herein and whose content is sufficient to be detected. Appropriately, the sample can be easily obtained by minimally invasive methods, thereby allowing the sample to be removed or separated from the subject. In certain embodiments, the sample comprises blood, especially peripheral blood, or a portion or extract thereof. Typically, the sample comprises blood cells, such as mature, immature or developing leukocytes, including lymphocytes, polymorphonuclear leukocytes, neutrophils, monocytes, reticulocytes, basophils, coelomocytes, hemocytes, eosinophils, megakaryocytes, macrophages, dendritic cells or natural killer cells, or a portion (e.g., a nucleic acid or protein portion) of such cells.

[0054] Substances for detecting markers in the sample to be tested include reagents used in western blotting, ELISA, radioimmunoassay, radioimmunodiffusion, octoclotonic immunodiffusion, rocket electrophoresis, tissue immunostaining, immunoprecipitation assay, complement fixation assay, FACS, and protein chip detection.

[0055] Agent: includes compounds that induce the desired pharmacological and / or physiological effects. The term also covers pharmaceutically acceptable and pharmacologically active components of those compounds specifically mentioned herein, including but not limited to salts, esters, amides, prodrugs, active metabolites, analogs, etc. When the above terms are used, it should be understood that this includes the active agent itself as well as pharmaceutically acceptable, pharmacologically active salts, esters, amides, prodrugs, metabolites, analogs, etc. The term "agent" should not be interpreted narrowly, but should be extended to small molecules, protein molecules, such as peptides, polypeptides and proteins, and compositions containing them, as well as genetic molecules, such as RNA, DNA and their mimetics and chemical analogs and cellular agents.

[0056] Diagnosis: refers to the identification or classification of a molecular or pathological state, disease or condition.

[0057] Auxiliary diagnosis: refers to methods that assist clinical determination of the presence or nature of a particular type of symptom or condition of a disease or disorder. For example, an auxiliary diagnosis method for a disease or disorder may include measuring certain biomarkers in a biological sample from an individual.

[0058] Patient, subject: refers to any subject in need of treatment or prevention, especially a vertebrate subject, and even more especially a mammalian subject.

[0059] The present invention is further described below by way of examples, but the present invention is not limited to the scope of the examples. The experimental methods in the following examples, unless otherwise specified, are conventional methods, and are performed according to the techniques or conditions described in the literature in the art or according to the product instructions. The materials, reagents, etc. used in the following examples, unless otherwise specified, can all be obtained from commercial sources.

[0060] The present invention provides the use of ADP ribosylation factor guanine nucleotide exchange factor 1 (BIG1) as a marker in the preparation of a reagent for diagnosing or monitoring sepsis immunosuppression. Those skilled in the art can refer to the content of the present invention and appropriately improve the process parameters to achieve it. It is particularly important to point out that all similar substitutions and modifications are obvious to those skilled in the art, and they are all considered to be included in the present invention. The methods and applications of the present invention have been described through preferred embodiments, and relevant personnel can obviously modify or appropriately change and combine the methods and applications herein without departing from the content, spirit and scope of the present invention to implement and apply the technology of the present invention.

[0061] The present invention will be further described below in conjunction with embodiments:

[0062] Example 1 BIG1 is down-regulated in peripheral blood monocytes of patients in the acute inflammatory phase of sepsis, and is up-regulated in peripheral blood monocytes of patients with immunosuppression.

[0063] Study population: Sepsis was diagnosed according to the Sepsis 3.0 diagnostic criteria. Patients with sepsis admitted to the comprehensive ICU of Minhang Hospital Affiliated to Fudan University were selected. Inclusion criteria: ① met the diagnostic criteria for sepsis in Sepsis 3.0; ② age ≥ 18 years old; Exclusion criteria: ① age < 18 years old; ② incomplete clinical data. Peripheral blood samples were collected within 24 hours of admission to the ICU. Twenty patients with sepsis and 20 healthy controls were included in this study and set up as the control group; the research plan was approved by the Medical Ethics Committee of this unit. Peripheral blood mononuclear cells (PBMCs) were separated by density gradient centrifugation, and then prepared into a cell suspension in DMEM medium containing 10% fetal bovine serum and inoculated in a culture dish. The monocytes were separated by adsorption separation (adherence method) at 37°C in a CO2 incubator for 60 minutes. The expression of HLA-DR on the surface of monocytes, the ratio of TNF-α / IL-10, and the levels of IL-6 and IL-1β were used to judge the immune level of patients with sepsis ( Figure 1 Middle A, Figure 1 Medium B and Figure 1 C). Twenty patients with sepsis were included in this study, and 20 patients without sepsis were set up as the control group. The levels of BIG1, HLA-DR, TNF-α, IL-10, IL-6, and IL-1β mRNA in monocytes of each group were detected by RT-qPCR. RNAtrizol reagent (R401) from Novozymes was used to extract total RNA, and 1 μg RNA was used to synthesize cDNA using RT-PCR kit (AG11728) from AG Acori. The synthesized cDNA, primers, and SYBR real-time PCR detection kit from Yeasen were used as follows:

[0064] Primers for qPCR detection of BIG1:

[0065] F(5'-3'):AAGTGTACACTGCCCTGATAT;

[0066] R(5'-3'):GATGGTGGATTCGTGAGA.

[0067] Table 1 PCR reaction system

[0068] Element volume 2×SYSBMasterMix 10μL PCR upstream primer 1μL PCR downstream primers 1μL DEPC water 6μL cDNA 2μL

[0069] PCR reaction cycle system:

[0070] Stage 1: 95℃, 300s

[0071] Stage 2: 95℃, 5s

[0072] Stage 3: 95℃, 5s

[0073] Stage4: 60℃, 30s, for 35cycles

[0074] Stage 5: 70℃, 60s

[0075] Stage 6: 4℃.

[0076] like Figure 1 Compared with normal controls, patients with sepsis who had low BIG1 expression in peripheral blood monocytes had significantly higher expression of HLA-DR, TNF-α / IL-10, IL-6, and IL-1β; on the contrary, patients with sepsis who had high BIG1 expression in peripheral blood monocytes had significantly lower expression of HLA-DR, TNF-α / IL-10, IL-6, and IL-1β. This result suggests that monocyte BIG1 may be a marker of the immune status of patients with sepsis.

[0077] Example 2 Analysis of the correlation between the expression of BIG1 in monocytes of patients with sepsis and the immune status of patients

[0078] The results of the correlation analysis between the BIG1 mRNA expression in monocytes of patients with sepsis in Example 1 and the indicators for monitoring the immune status of sepsis (HLA-DR, TNF-α / IL-10, IL-6, IL-1β) are shown in Figure 2 As shown in the results, BIG1 was downregulated in peripheral blood monocytes of patients in the acute inflammatory phase of sepsis, and upregulated in peripheral blood monocytes of patients with immunosuppression, and BIG1 was negatively correlated with these immune indicators. Immune activation in patients with sepsis was associated with low expression of BIG1, while immunosuppression in patients with sepsis was associated with increased BIG1 expression in monocytes, suggesting that BIG1 can be used as an evaluation indicator for immune activation or inhibition in sepsis.

[0079] Example 3 Immune activated macrophages have low BIG1 expression and endotoxin tolerant macrophages have high BIG1 expression

[0080] Mouse bone marrow primary macrophages were stimulated with LPS at a concentration of 100 ng / mL, and total cell protein was extracted at 0 h, 6 h, 12 h, 24 h, and 36 h, and the protein level of BIG1 was detected by Western blot. Figure 3 As shown in A, with the extension of LPS stimulation time, the protein level of BIG1 has a significant downward trend. In addition, cells were stimulated with LPS at concentrations of 1 ng / mL, 10 ng / mL, 100 ng / mL, and 1000 ng / mL, and total cell protein was extracted 12 hours later. Western blot was used to detect the expression of BIG1 protein ( Figure 3B). With the increase of LPS concentration, the protein level of BIG1 showed a significant downward trend. The cells were stimulated with LPS at a concentration of 100 ng / mL, and total RNA was extracted at 0h, 12h, and 24h, and the expression of BIG1 mRNA was detected by RT-qPCR. Figure 3 As shown in C, BIG1 mRNA was significantly downregulated after LPS stimulation. These results indicate that BIG1 is lowly expressed in immune-activated macrophages.

[0081] Endotoxin tolerance was induced by sequential administration of 10 ng / mL LPS and 1000 ng / mL LPS. We then extracted total cellular RNA and detected the transcriptional levels of TNF-α, IL-6, IL-1β, IL-12p40, IL-10, and BIG1 genes at different time points after the second LPS stimulation. The results showed that Figure 4 As shown in the results, when endotoxin tolerance was established, the mRNA expression of pro-inflammatory factors TNF-α, IL-6, IL-1β, and IL-12p40 in BMDM was significantly inhibited, while the mRNA expression of anti-inflammatory factor IL-10 was significantly upregulated. At the same time, the mRNA expression of BIG1 was significantly increased when endotoxin tolerance was established. In addition, after inducing endotoxin tolerance, total cell protein was extracted to detect the protein levels of NF-κB signaling pathway and BIG1. The results showed that Figure 5 As shown in the results, when endotoxin tolerance was established, the activation of the NF-κB signaling pathway in BMDM was significantly inhibited, P-p65 and P-IKK were significantly downregulated, and the level of IκB was significantly increased. At the same time, the protein of BIG1 was significantly increased after the second LPS stimulation of endotoxin tolerance. These results indicate that BIG1 is highly expressed in endotoxin-tolerant macrophages.

[0082] Example 4 Relationship between the expression pattern of BIG1 in peritoneal macrophages of septic mice and the immune status of sepsis

[0083] Cecal ligation and puncture (CLP) was used to induce a mouse sepsis model. That is, after the mice were anesthetized, the cecum was ligated 1.0 cm from the end, and bilateral punctures were performed using an 18-gauge needle. A small amount of feces was gently squeezed out, and then sutured. The mice in the sham group only had an abdominal incision but no ligation was performed. Subsequently, normal saline was infused subcutaneously. In the early stages of CLP-induced sepsis in mice, an inflammatory response occurred rapidly, and the levels of BIG1 mRNA and protein were significantly downregulated. On the sixth day after CLP, mice showed a typical immunosuppressive phenotype. On the sixth day after CLP, a secondary infection model was established in immunosuppressed CLP mice by intravenous injection of Escherichia coli, and 24 hours later, mouse peritoneal macrophages were collected and total RNA was extracted. Figure 6A, RT-qPCR showed that the mRNA level of BIG1 in mouse peritoneal macrophages was significantly upregulated. In CLP-induced sepsis secondary infection model mice, the protein level of BIG1 in mouse peritoneal macrophages was detected by Western Blot. Figure 6 B, The protein level of BIG1 was significantly upregulated in mouse peritoneal macrophages.

[0084] Example 5 Effect of knocking out BIG1 on the immune response of macrophages in mice during the acute phase of sepsis

[0085] To further observe the relationship between BIG1 and the immune status in the acute phase of sepsis in vivo, the present invention used myeloid cell-specific BIG1 gene conditional knockout (Cre + BIG1 fl / fl , i.e., BIG1 cKO) mice, using Cre - BIG1 fl / fl (WT) mice were used as controls. Referring to the method in Example 4, a cecal ligation and puncture (CLP) sepsis model and a sham operation (sham) model were constructed. Peritoneal macrophages were collected 2h and 4h after surgery, and the expression levels of cytokines TNF-α, IL-6, IL-1β, IL-12p40, IL-10, and IFN-β mRNA were detected by fluorescence quantitative PCR. Figure 7 The results showed that compared with the WT group, after the myeloid BIG1 gene was deleted, the gene transcription of pro-inflammatory factors TNF-α, IL-6, IL-1β, and IL-12p40 in the peritoneal macrophages of mice decreased, and the gene transcription of anti-inflammatory factors IL-10 and IFN-β increased.

[0086] Example 6 Effect of knocking out BIG1 on the immune response ability of macrophages in mice during the immunosuppression period of sepsis

[0087] To further observe the relationship between BIG1 and the immune status of sepsis in vivo, the present invention uses myeloid cell-specific BIG1 gene conditional knockout mice. Referring to the method in Example 4, a cecal ligation and puncture (CLP) sepsis model and a sham operation (sham) model were constructed, and 1×10 9 24 h after CFU E. coli infection, peripheral blood was collected from mice and serum was separated. The levels of TNF-α and IL-6 in peripheral blood were detected by enzyme-linked immunosorbent assay (ELISA). Figure 8 Compared with WT mice, the levels of TNF-α and IL-6 in the peripheral blood of BIG1 cKO mice were significantly improved. This suggests that the increased immune response of macrophages in septic immunosuppressed mice is related to the knockout of BIG1.

[0088] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. Use of a substance for detecting a marker in a sample to be tested in the preparation of a product for diagnosing or monitoring the immune status of sepsis, characterized in that: The markers include BIG1 markers; The sample includes a blood sample, a urine sample, a puncture fluid sample, a respiratory sample, a cerebrospinal fluid or a tissue sample.

2. The use according to claim 1, characterized in that The blood sample includes blood, plasma, and serum; The puncture fluid samples include pleural effusion and ascites; The respiratory samples include sputum and bronchoalveolar lavage fluid.

3. A product, characterized in that: The product includes a substance for detecting the BIG1 marker; The products include products for diagnosing or assisting in diagnosing the immune status of sepsis in a sample to be tested, and products for diagnosing or assisting in diagnosing the immune status of sepsis in a subject to be tested; The products include products for monitoring or assisting in monitoring the sepsis immune status of a sample to be tested, and products for monitoring or assisting in monitoring the sepsis immune status of a subject to be tested.

4. The product according to claim 3, characterized in that The substance for detecting the BIG1 marker includes a substance for detecting gene expression level or a substance for detecting protein level; The products include reagents, test kits, test strips, nucleic acid membrane strips, chips, primers, and probes; The subject includes a human or a non-human mammal.

5. The product according to claim 4, characterized in that The reagents include detecting the presence of BIG1 genes, fragments and proteins in a sample by PCR reaction, RT-PCR derivatization reaction, 3SR amplification, LCR, SDA, NASBA, TMA, SYBR Green, TaqMan probe, molecular beacon, double hybridization probe, composite probe, ISH, microarray, Southern blot, Northern blot, multi-analyte spectrum test, enzyme-linked immunosorbent assay (ELISA), radioimmunoassay, immunofluorescence assay, enzyme immunoassay, immunoprecipitation assay, chemiluminescence assay, immunohistochemistry assay, dot blot assay or slot blot assay.

6. The product according to claim 4, characterized in that The kit includes a gene detection kit and a protein detection kit.

7. Application of the marker BIG1 as a target in constructing a sepsis immunosuppression model, including an animal model and a cell model.

8. Application of the marker BIG1 in the preparation of drugs for regulating the immune status of patients with sepsis.

9. The use according to claim 7, characterized in that The drug includes an agent that knocks out or knocks down BIG1, an agent that inhibits the activity of BIG1, or a substance that increases the level or activity of a BIG1 inhibitor.

10. A sepsis immune status risk prediction model, characterized in that: The prediction model includes a risk prediction model constructed by model training using a machine learning method, wherein the machine learning method includes a process of machine training using a BIG1 marker; The machine learning methods include decision tree models, random forest models, K-nearest neighbor algorithm models, naive Bayes models, support vector machine models, and neural network models.

11. A sepsis immune status monitoring system, characterized in that: The monitoring system includes a result determination module for comparing a processed value of a marker obtained by detecting the gene or protein expression level of a BIG1 marker with a set value; The monitoring system includes a processing module, which is used to detect and process the expression level of genes or proteins related to markers in the sample to obtain a processing value; and to determine the immune state of sepsis.

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