Inositol Metabolism Modulates Inflammatory Injury in Acute Pancreatitis via the ISYNA1-NETs Axis

Abstract

Background

Neutrophil extracellular traps (NETs) were key factors mediating inflammatory injury in acute pancreatitis (AP). To this end, there was an urgent need to identify precise and effective therapeutic targets that modulate NETs formation, providing new ideas for the prevention and treatment of AP pancreatitis injury.

Gap

To address this gap, we investigated the potential involvement of the myo-inositol metabolism in modulating NETs and inflammatory damage during AP.

Methods

Multi-omics analysis identified myo-inositol metabolism as critical. We then established the in vitro NETs model using phorbol-12-myristate-13-acetate (PMA) to investigate the role and regulatory mechanism of inositol-3-phosphate synthase 1 (ISYNA1) on NETs formation. Finally, the findings were validated in the classic AP mouse model to verify the correlation between myo-inositol metabolism and AP pathogenesis.

Results

Multiple omics analyses showed that the myo-inositol metabolic pathway is the most significant, and the key enzyme ISYNA1 involved in myo-inositol synthesis was significantly reduced. ISYNA1 was significantly downregulated in both the in vitro NETs model and in neutrophils infiltrating the pancreatic tissue of AP mice. Meanwhile, exogenous supplementation of ISYNA1 or myo-inositol significantly inhibited the NETs formation in vitro and inflammatory injury in AP mice. Mechanistically, downregulation of ISYNA1 led to reduced myo-inositol synthesis, thereby promoting NETs formation via modulation of the PI3K/AKT pathway.

Conclusion

ISYNA1 and myo-inositol metabolism were among the key links that regulated NETs formation and inflammatory injury in AP. Therefore, enhancing ISYNA1 and myo-inositol metabolism might serve as a potential intervention target for treating acute organ injury in AP.

Graphical Abstract

Introduction

Acute pancreatitis (AP) is an acute inflammatory disorder of the digestive system, whose incidence has been rising; consequently, AP inpatients now account for 12.7% of digestive emergency admissions.¹ Although approximately 80% of AP cases are mild and self-limiting, the remaining 20% progress to severe acute pancreatitis (SAP). Repeated or excessive acinar cell damage leads to pancreatic necrosis, which releases large quantities of pro-inflammatory mediators and chemokines. This cascade can quickly progress to a systemic inflammatory response, the critical state associated with mortality rates of up to 40%.^2,3 The pathogenesis of SAP involves profound dysregulation of the immune system, involving both an overactivated innate immune response and a dysfunctional adaptive immune response that orchestrate disease progression.⁴ The immediate immune response to acinar injury is the critical determinant of severe disease progression in AP.⁵ Therefore, identifying novel therapeutic targets to intervene in the progression to severe AP is of paramount importance.

Neutrophils constitute the first line of host defense, exerting crucial functions in anti‑infective immunity and inflammation regulation through phagocytosis and the release of inflammatory mediators.^6,7 In the progression of AP disease, neutrophils are the earliest immune cells recruited to pancreatic tissue, directly participating in acinar cell damage and the formation of a local inflammatory microenvironment by releasing a large amount of inflammatory mediators, including cytokines and reactive oxygen species (ROS).^8,9 Neutrophils participate in inflammatory diseases progression by releasing neutrophil extracellular traps (NETs).¹⁰ ROS activates the PI3K/AKT cascade reaction, which in turn regulates downstream effector molecules to promote the release of NETs in the pathological process of AP.¹¹ NETs mediate neutrophil activity to clear pathogens; nevertheless, their overproduction or faulty resolution has a detrimental effect, driving multi-organ injury during acute inflammation.^12,13 Our previous research has demonstrated that the expressions of Src kinase,¹⁴ CD53,¹¹ CD177,¹⁵ and pore-forming protein gasdermin D (GSDMD)¹⁶ are closely related to NETs formation and the clinical prognosis of AP. Blocking the formation and downstream pathways of NETs, inhibiting ROS, disrupting the structure of NETs, and inhibiting their activity are effective intervention methods for preventing AP-associated organ damage.

ISYNA1 (Inositol-3-phosphate Synthase 1) is the rate limiting enzyme that catalyzes the conversion of glucose to myo-inositol during de novo synthesis of myo-inositol, and it is the only key enzyme responsible for endogenous myo-inositol synthesis.^17,18 Previous studies have shown that myo-inositol plays a key role in reducing the process of renal inflammation, improving podocyte function and preventing diabetes‑related renal injury.^19–21 Notably, myo-inositol and its derivatives exhibit tumor‑suppressive effects through inhibition of the PI3K/AKT pathway.^19–21 As is well known, the ISYNA1-myo-inositol axis plays a crucial role in cancer and metabolic research. However, its role in the formation of AP and NETs is currently unclear. Hence, the aim of this study is to elucidate the function and molecular mechanism of ISYNA1–myo-inositol axis as a novel regulatory target for the formation of NETs, and to provide theoretical support for the search for new targets for the clinical diagnosis and treatment of AP inflammatory injury.

Materials and Methods

Animals

Male wild-type C57BL/6J mice (weight 20–25g) were used in this study. All experimental animals were purchased from GemPharmatech Co., Ltd., Nanjing, China. C57BL/6J mice were maintained under specific pathogen-free (SPF) conditions with a 12-hour light/dark cycle and a controlled room temperature of 20–25°C. The animals had free access to a standard laboratory diet and water. All experimental procedures were conducted in strict accordance with the “National Institutes of Health Guide for the Care and Use of Laboratory Animals (NIH Publication No. 85–50, revised 1996)” and the animal protection guidelines “Guidelines for Ethical Review of Laboratory Animals - Animal Welfare (GB/T 35892–2018, China), and were approved by the Animal Ethics Committee of Yangzhou University (Approval No. 202208012). The authors have followed the ARRIVE guidelines.

Cells Culture

Neutrophils Derived from Mouse Bone Marrow

According to the strict experimental procedures of our research group, we selected male wild-type C57BL/6J mice weighing 20–25g, and obtained complete femur and tibia bones using anatomical techniques. Subsequently, the bones were immediately transferred to RPMI 1640 medium (BC-M-017, BIO Channel) to maintain cell viability. We used a sterile syringe to aspirate RPMI 1640 medium and repeatedly washed the bone marrow cavity from both ends of the femur and tibia until they turned transparent. The obtained bone marrow suspension was transferred to a centrifuge tube with a 70 µm cell sieve (CLS431751, MERCK) at room temperature, 450 (×g), and centrifuged for 10 minutes. We separated cells using the mouse peripheral blood neutrophil isolation kit (P9201, Solarbio) and aspirated the neutrophil layer fluid. Subsequently, we resuspended and diluted the cells with RPMI 1640 medium, centrifuged at 4 °C, 350 (×g), for 5 minutes. After discarding the supernatant, neutrophils were resuspended in complete culture medium (RPMI 1640 medium+10% FBS) for subsequent experiments.

HL60 Cells

The promyelocytic leukemia cell line HL-60 was obtained from the Shanghai Institute of Biochemistry and Cell Biology (Shanghai, China). HL60 cells were cultured in IMEM medium with 20% FBS. Pre-treat with 1.5% dimethyl sulfoxide for 4 days to induce differentiation into dHL60 cells for subsequent experiments.

Reagents and Antibodies

All reagents and antibodies involved in this study were listed in Supplementary Tables 1 and 2.

In vitro NETs Construction

Inoculated bone marrow neutrophils at a concentration of 1 × 10⁷/mL into a 12‑well plate and incubated in a 37 ° C, 5% CO₂ incubator for 30 minutes. Subsequently, an equal amount of 100 nM PMA or 1X PBS was added to the well plate and placed in a 37 ° C, 5% CO₂ incubator for further cultivation for 4 hours.

Preparation of in vivo AP Mouse Model and Drugs Intervention

Male 6–8 week old C57BL/6J mice were selected and subjected to myo-inositol (I5125, Sigma) intervention experiments. The mice were divided into three groups: a caerulein induced AP group (Cae), myo-inositol treatment groups with different doses (Cae/myo-inositol, 100mg/kg, 300mg/kg, 600mg/kg), and control group (Control). The AP group and the myo-inositol treatment groups with different doses were both intraperitoneally injected with 100 μg/kg of caerulein, with an interval of 1 hour, for 10 consecutive times, to establish the AP mouse model. The control group received an intraperitoneal injection of the same dose of phosphate‑buffered saline (PBS) as the other groups.

Samples Collection

Male wild-type C57BL/6J mice weighing 20–25 g were used to establish the AP mouse model. After 12 hours of modeling, the mice were anesthetized with Zoletil™50 (Virbac) (55mg/kg intraperitoneal injection), and the depth of anesthesia was confirmed by the absence of a response to a toe pinch. Under deep anesthesia, blood was collected from the mouse orbital vein. After blood collection, the mice were euthanized by cervical dislocation. The samples were left to stand at 4 ° C for 30 minutes, then centrifuged at 1200 ×g for 10 minutes, and the upper layer of serum was retained. The serum was stored at −80 ° C for subsequent enzymatic testing. Most of the pancreatic tissue was placed in a 4% paraformaldehyde solution, and the remaining pancreatic tissue was stored at −80 °C for future experiments.

Samples Preparation and Histological Analysis

Mouse pancreatic tissue was fixed in a 4% paraformaldehyde solution for about 48 hours and then placed in a tissue embedding box. Gradient dehydration and fresh xylene transparency treatment were performed on the embedding boxes containing pancreatic tissue. The pancreatic tissue block was placed in paraffin and embedded after the paraffin completely penetrated the tissue, followed by cooling. After paraffin fixation, the tissue was cut into sections with a thickness of 5 µm and adhered to glass slides. The pancreatic tissue adhered to the glass slide was placed in a drying oven at 60 °C for 1 hour, dried, and set aside.

Pancreatic tissue sections were first dewaxed with xylene, then dehydrated with gradient ethanol, stained with hematoxylin and eosin (H&E), sealed with neutral gel, and observed under an optical microscope. The histological scoring of pancreatic tissue was performed by two independent pathologists using the method we previously described.²²

Immunofluorescence Staining Method

After dewaxing and hydration, the glass slide containing pancreatic tissue was placed in sodium citrate antigen retrieval solution, microwave‑heated for 15 minutes, and naturally cooled. Subsequently, the tissue surface was covered with a solution containing 0.25% Triton X-100 to break the membrane, and left it at room temperature for 10 minutes. A solution containing 5% normal goat serum was prepared to cover the tissue surface and sealed it at room temperature for 1 hour. Then the tissue surface was covered with Anti‑MPO (1:100), Anti-Cith3 (1:300), and Anti-ISYNA1 (1:100) antibodies and incubated at 4 °C for 12 hours. Afterwards, the slide was washed with 1X PBS for 2 minutes and this step was repeated 5 times. The biotinylated secondary antibody (1:1000) solution was taken and applied to the surface of the tissue at room temperature for 2 hours. Then a drop of DAPI solution was taken and applied to the surface of the tissue at room temperature in the dark for 10 minutes. Finally, a quencher was added and the slide was sealed. The slide was then observed using a laser confocal microscope (Leica TCS SP8 STED, Germany), and the corresponding LAS X imaging software was used to capture images and analyze them.

Measurement of NETs Related Indicators in vitro

Inoculated the extracted and purified bone marrow-derived neutrophils into a 12 well plate containing slides, and cultured them in RPMI 1640 medium containing 10% FBS in a 37 °C, 5% CO₂ incubator for 30 minutes. Constructed the in vitro NETs model by treating with 100 nM PMA or PBS for 4 hours. Observed the NETs formation in vitro using immunofluorescence method. The main method was as follows: first fixed the slide with 4% paraformaldehyde, then covered the tissue surface with a 0.25% Triton X-100 solution to break the membrane, followed by blocking with goat serum, and then covered the entire slide with Anti-MPO (1:100) and Anti‑CitH3 (1:300) antibodies. Incubated overnight at 4 °C in the dark. The next day, gently aspirated the liquid from the slide, and washed the slide with PBS, then incubated with a secondary antibody at 37 °C for 2 hours, and finally added DAPI. Observed the sample using a confocal microscope and collected images using the corresponding LAS X imaging software for analysis. All images were collected and analyzed with consistent exposure parameters and threshold settings between groups. Used ImageJ software to analyze MPO or CitH3 positive area. The results were expressed as the percentage (%) of positive area to total cell area; then compared with the control group as a benchmark.

Enzyme-Linked Immunosorbent Assay

According to the instructions of the reagent kits, we measured the levels of myo-inositol, TNF-α (88–7324-77, Affymetrix eBioscience), MCP-1 (88–7391-77, Affymetrix eBioscience) and IL-6 (88–7064-77, Affymetrix eBioscience). We adjusted the ELISA reader to measure the OD values of each well at a wavelength of 450 nm. We drew a four-parameter logistic regression (4-PL) model according to industry standards, with standard curve correlation coefficients all greater than 0.99. Standard and quality control samples (QCs) are set at both ends of each board. To ensure the reliability of the data, each group consists of 6 samples. Finally, we calculated the concentration values of each sample based on the standard curve. The concentration range of the standard curve and the measurement of the standards and samples were repeated twice.

Flow Cytometry Analysis

Measurement of MPO

The mouse bone marrow neutrophils were stained with surface antibodies (Anti-CD45.2, Anti-CD11b, and Anti-Ly6G) at 4°C for 30 minutes, then washed with PBS and fixed with fixative at 4°C for 20 minutes, and then washed with PBS and stained with Anti-MPO antibody at 4°C for 20 minutes. The cells were washed with PBS and resuspended in PBS. Finally, we collected the cells on a Beckman DxFlex B5-R3-V3 (Indianapolis, IN, United States) and analyzed them using CytExpert for DxFlex. The flow cytometry steps for dHL60 cells are the same as above.

Determination of ROS

Used DHE fluorescent probe (Sigma, D70N8) to detect the content of intracellular ROS.²³ Incubated the mouse bone marrow neutrophils with DHE solution at 37 °C in the dark for 30 minutes. Washed the cells with PBS and stained with surface antibodies (Anti-CD45.2, Anti-CD11b, and Anti-Ly6G) at 4 °C for 30 minutes. Washed the cells with PBS and resuspended them in PBS. Finally, collected cells for analysis as described above. The flow cytometry steps for dHL60 cells are the same as above.

RNA Sequencing (RNA-Seq)

RNA-Seq was used to analyze the mRNA expression before and after PMA‑induced NETs formation. The total RNAs of the control group and the PMA group were isolated using TRNzol universal reagent (TIANGEN, China). The mRNA from both groups was extracted and subjected to RNA-Seq by Novogene Corporation (Tianjin, China). Subsequently, the differentially expressed genes (DEGs) between the two groups were analyzed using R software.

Full Spectrum Metabolism Dual Platform Metabolomics

Full spectrum metabolism dual platform metabolomics was used to analyze the metabolites in neutrophils before and after PMA‑induced NETs formation. Neutrophils from the control group and the PMA group were collected and placed in liquid nitrogen. The cell pellet was quenched for 1 minute and then frozen at −80 degrees Celsius. Subsequently, the two groups of cells were subjected to metabolomics analysis by Lumingbio (Shanghai, China).

Protein Extraction and Western Blot Analysis (WB)

Cells were disrupted by ultrasonic homogenization, followed by centrifugation (13800 ×g, 30 min) to collect the supernatant. Protein concentration was measured using the BCA protein assay kit (P0012, Beyotime). The remaining supernatant was mixed with protein loading buffer (P0015, Beyotime), denatured at 100°C for 10 min, and stored at −80°C.

The protein samples were subjected to 10% SDS-polyacrylamide gel electrophoresis (PAGE), followed by transfer of proteins onto the PVDF membrane. The membrane was blocked with BSA at room temperature for 2 hours, then incubated overnight at 4°C with primary antibodies including Anti-ISYNA1 (1:1000, Proteintech), PI3 Kinase p85 (19H8) Rabbit mAb (1:1000, CST), Phospho-PI3 Kinase p85 (Tyr458)/p55 (Tyr199) (E3U1H) Rabbit mAb (1:1000, CST), Akt (C67E7) Rabbit mAb (1:1000, CST), Phospho-Akt (Ser473) (D9E) Rabbit mAb (1:1000, CST), and Anti-β-actin (1:1000, CST). The membrane was then incubated with horseradish peroxidase-conjugated secondary antibodies at 37°C for 2 hours. After washing, we used the Tanon 5200 Multi fully automated chemiluminescence imaging analysis system and the ECL Plus chemiluminescence system to detect protein bands. The original image is saved in TIFF format. We used ImageJ software to perform grayscale analysis on the bands. The expression level of the target protein was first standardized using the reference protein (β - actin, and then compared with the control group as a benchmark.

Scanning Electron Microscope (SEM)

Firstly, the cells were fixed with 2.5% glutaraldehyde for 24 hours. Next, gradient ethanol was used to perform gradient dehydration on the sample. The cell slide was inserted vertically into the CPD-300 critical point dryer and dried for 2 hours. The dried slide was then stuck onto the sample stage. After the sample was sprayed with a gold film using an SCD‑500 ion sputtering instrument, it was observed and photographed under a scanning electron microscope (GeminiSEM 300, UK).

Small Interfering RNA (siRNA) Transfection in dHL60 Cells

According to the manufacturer’s instructions, transfection of dHL60 cells was performed using Lipofectamine 3000 transfection reagent (Thermo Fisher Scientific, USA). The cells were seeded and grew to 40% fusion during transfection. The transfection complex was prepared using lipo3000 and siRNA (50 nM) in a 2:1 ratio.

ISYNA1 siRNAs were used to target the Human ISYNA1 mRNA sequences: 5′-GCAGCUGCAUCGAGAACAUTT-3′ and 5′-AUGUUCUCGAUGCAGCUGCTT-3′. The negative control sequences: 5′-UUCUCCGAACGUGUCACGUTT-3′ and 5′-ACGUGACACGUUCGGAGAATT-3′. All siRNAs were synthesized by Shanghai Gene Pharma (Shanghai Gene Pharma).

Statistical Analysis

All statistical analyses were conducted using GraphPad Prism 9.0 and R language.

Apply the Shapiro Wilk test to evaluate the normality of the data distribution. Data that conform to the normality assumption will be analyzed using parameter testing; perform a logarithmic transformation on non‑compliant data or use non‑parametric tests (Kruskal–Wallis test) for analysis when appropriate. Then use the Bonferroni correction for multiple pairwise comparisons. Student’s t-test was used to analyze the mean between two groups, and one-way analysis of variance (ANOVA) was used for multiple group comparisons. For comparisons between two or more groups, perform one-way ANOVA, followed by Tukey’s multiple-comparisons test. The results were presented as mean ± standard error (SE), and the histogram data were presented as mean ± standard error of the mean (SEM). P<0.05 indicated a bilateral difference. To ensure robustness, three biological replicates were conducted for each experiment. Statistical indicators: *p<0.05, * *p<0.01, * * *p<0.001, NS not significant.

Results

ISYNA1 Exhibits Markedly Reduced Expression in PMA-Induced NETs Formation

To explore the metabolic changes of neutrophils before and after PMA induction, we performed untargeted metabolomics and RNA-Seq transcriptomics analysis on neutrophils in the PMA‑induced NETs group and the control group (Figure 1A). KEGG enrichment analysis was performed on all differential metabolites, and it was found that the myo-inositol metabolic pathway was more significant. In the PMA‑induced NETs group, myo-inositol was a differentially downregulated metabolite in neutrophils (Figure 1B and C). We conducted heatmap analysis on all genes involved in the myo-inositol metabolism pathway in RNA-Seq transcriptomics and found a significant decrease in the key enzyme ISYNA1 involved in myo-inositol upstream synthesis (Figure 1D). Given that ISYNA1 was the rate‑limiting enzyme in the de novo synthesis pathway of myo-inositol, we further identified it as a research focus. To further clarify the expression of ISYNA1 during NETs formation, we employed immunofluorescence staining and observed a significant reduction in ISYNA1 expression (co-localization of ISYNA1/MPO) after NETs formation compared to the control group (Figure 1E and F). Additionally, WB analysis revealed the marked decrease in ISYNA1 protein levels following PMA stimulation, which was consistent with the aforementioned findings (Figure 1G and H).

Figure 1.

ISYNA1 exhibits markedly reduced expression in PMA-induced NETs formation. (A) Joint analysis of untargeted metabolomics and RNA-Seq transcriptomics. The red arrow indicates that the combined analysis of untargeted metabolomics and RNA-Seq transcriptomics revealed that Inositol phosphate metabolism is one of the metabolic pathways with significant changes. (B) KEGG enrichment analysis combining untargeted metabolomics and RNA-Seq transcriptomics. The red box represents KEGG enrichment analysis of all differential metabolites, and it was found that the myo-inositol phosphate metabolism was more significant (ranked second). (C) Volcanic diagram analysis of differential metabolites. The red arrow represents that in the PMA‑induced NETs group, myo-inositol was a differentially downregulated metabolite in neutrophils. (D) Thermal map analysis of genes related to myo-inositol metabolism pathway. The red box indicates that all genes involved in the myo-inositol metabolism pathway in RNA-Seq transcriptomics were subjected to heatmap analysis, and it was found that the key enzyme ISYNA1 involved in myo-inositol upstream synthesis was significantly reduced. (E) Representative immunofluorescence image of ISYNA1 and MPO at 400× (Scale Bar = 50μm) and 1000× (Scale Bar = 10μm) magnification. (F) Densitometric analysis of ISYNA1 and MPO fluorescence (N = 6). (G) ISYNA1 protein abundance in neutrophils determined via WB (N = 3). (H) Relative protein expression of ISYNA1 (N = 3); β-actin is used as a control for protein loading. Each experiment underwent three biological replicates. Statistical significance was denoted as: **P < 0.01, ***P < 0.001.

ISYNA1 and Myo-Inositol Significantly Attenuate PMA-Induced NETs Formation

The role of ISYNA1 in the formation of NETs was currently unclear. After exogenous supplementation of different doses of Recombinant Human ISYNA1 (rhISYNA1) (1, 10, and 100 ng/mL), flow cytometry analysis revealed that, compared with the PMA group, the exogenous supplementation of 100ng/mL rhISYNA1 treatment group significantly reduced MPO⁺ neutrophil and ROS production, and the protective effect was more pronounced than the other doses (Figure 2A). Subsequently, we detected, through immunofluorescence and SEM, that ISYNA1 significantly reduced CitH3 release and NETs formation after intervention (Figure 2B and C). In addition, rhISYNA1 also inhibited the levels of pro-inflammatory cytokines in the cell supernatant during PMA‑induced NETs formation (Figure 2D).

Figure 2.

ISYNA1 significantly alleviates PMA‑induced NETs formation. (A) Bone marrow neutrophils isolated from C57BL/6J mice were cultured and stimulated with PMA (100 nM), and incubated with different doses of rhISYNA1 (1, 10, and 100 ng/mL) before flow cytometry analysis. Representative flow cytometry gating of bone marrow neutrophils (CD45.2⁺ CD11b⁺ Ly6G⁺). Representative flow cytometry plots and bar graphs depicting the proportion of neutrophils and the expression levels of MPO and ROS. Data is presented as mean ± SEM (N = 4). (B) Representative immunofluorescence image of Cith3 and MPO at 400× (Scale Bar = 50μm) and 1000× (Scale Bar = 10μm) magnification. Representative SEM of neutrophils. White arrows: neutrophils, yellow arrows: NETs (N = 6). (C) Densitometric analysis of Cith3 and MPO fluorescence (N = 6). (D) Supernatant levels of IL6, TNF-α, and MCP-1 detected using ELISA (N = 6). Each experiment underwent three biological replicates. Statistical significance was denoted as: *P < 0.05, **P < 0.01, ***P < 0.001.

ISYNA1 was the essential and unique enzyme required for endogenous synthesis of myo-inositol, and its effect on myo-inositol in the NETs formation was not yet clear. As shown in Supplementary Figure 1, exogenous administration of ISYNA1 promoted intracellular myo-inositol metabolism during NETs formation. To evaluate the role of the ISYNA1 downstream metabolite myo-inositol in NETs, we used flow cytometry to assess MPO⁺ neutrophil activity and ROS production in mouse bone marrow neutrophils stimulated with PMA at different concentrations of myo-inositol (100, 200, 400 μM). Compared with the other doses, MPO⁺ neutrophil and ROS production in the myo-inositol 400 μM group were significantly reduced (Figure 3A). As shown in Figure 3B and C, we detected by immunofluorescence and SEM that myo-inositol effectively reduced the release of NETs. In addition, myo-inositol significantly alleviated the levels of pro-inflammatory cytokines in the cell supernatant during PMA‑induced NETs formation (Figure 3D).

Figure 3.

Myo-inositol significantly reduces PMA‑induced NETs formation. (A) Bone marrow neutrophils isolated from C57BL/6J mice were cultured and stimulated with PMA (100 nM), and incubated with different doses of myo-inositol (100, 200, and 400 μM) before flow cytometry analysis. Representative flow cytometry gating of bone marrow neutrophils (CD45.2⁺ CD11b⁺ Ly6G⁺). Representative flow cytometry plots and bar graphs depicting the proportion of neutrophils and the expression levels of MPO and ROS. Data is presented as mean ± SEM (N = 4). (B) Representative immunofluorescence image of Cith3 and MPO at 400× (Scale Bar = 50μm) and 1000× (Scale Bar = 10μm) magnification. Representative SEM of neutrophils. White arrows: neutrophils, yellow arrows: NETs (N = 6). (C) Densitometric analysis of Cith3 and MPO fluorescence (N = 6). (D) Supernatant levels of IL6, TNF-α, and MCP-1 detected using ELISA (N = 6). Each experiment underwent three biological replicates. Statistical significance was denoted as: **P < 0.01, ***P < 0.001.

Downregulation of ISYNA1 Leads to Reduced Myo-Inositol Synthesis, Thereby Promoting NETs Formation Through Modulation of the PI3K/AKT Pathway

Previous studies had shown that ISYNA1 was the rate‑limiting enzyme that catalyzes the conversion of glucose-6-phosphate to inositol-3-phosphate, with its core function being to promote endogenous myo-inositol production.^17,18 Therefore, when ISYNA1 was knocked down, the direct consequence was a decrease in myo-inositol synthesis. To further clarify the mechanism, we constructed ISYNA1 siRNA and its control group, and validated the knockdown efficiency through Western blot analysis experiments (Supplementary Figure 2A and B). Subsequently, we transfected silenced human dHL60 cells ISYNA1 with small interfering RNA. Through flow cytometry analysis, it was found that compared with the PMA stimulation group, the ISYNA1‑specific siRNA knockdown group significantly increased MPO⁺neutrophil and ROS production (Supplementary Figure 3A and B).

The PI3K/AKT signaling pathway activated NADPH oxidase, mediating ROS generation and thereby promoting the formation of NETs, making it one of the key pathways in NETs formation.²⁴ Our research group had previously confirmed that CD53 promoted NETs formation by regulating the PI3K/AKT pathway.¹¹ To clarify the specific roles of ISYNA1 and myo-inositol in PI3K/AKT signaling pathway during NETs formation, we found that the protein expression of P-PI3K and P-AKT significantly increased after PMA stimulation, while the protein expression of P-PI3K and P-AKT significantly decreased after administration of rhISYNA1 (Figure 4A and C) and myo-inositol (Figure 4B and D), respectively.

Figure 4.

Downregulation of ISYNA1 leads to reduced myo-inositol synthesis, thereby promoting NETs formation through modulation of PI3K/AKT pathway. (A) The protein levels of p-PI3K and p-AKT in neutrophils of four groups (Control, Control + rhISYNA1, PMA, PMA + rhISYNA1) were assessed using Western blotting (N = 3). (B) The protein levels of p-PI3K and p-AKT in neutrophils of four groups (Control, Control + myo-inositol, PMA, PMA + myo-inositol) were assessed using Western blotting (N = 3). (C) Relative protein expression of p-PI3K and p-AKT in neutrophils of four groups (Control, Control + rhISYNA1, PMA, PMA + rhISYNA1) (n = 3); PI3K and AKT are used as controls for protein loading (N = 3). (D) Relative protein expression of p-PI3K and p-AKT in neutrophils of four groups (Control, Control + myo-inositol, PMA, PMA + myo-inositol) (N = 3); PI3K and AKT were used as controls for protein loading (N = 3). (E) Representative bar charts of ROS and MPO expression levels in five groups: Control, PMA, PMA+ rhISYNA1, PMA+LY294002, and PMA+rhISYNA1+LY294002. Data is presented as mean ± SEM (N = 4). (F) Representative bar charts of ROS and MPO expression levels in five groups: Control, PMA, PMA+ myo-inositol, PMA+LY294002, and PMA+myo-inositol+LY294002. Data is presented as mean ± SEM (N = 4). Each experiment underwent three biological replicates. Statistical significance was denoted as: *P < 0.05, **P < 0.01, ***P < 0.001.

LY294002 was the classic inhibitor of the PI3K/AKT pathway. We found through flow cytometry analysis that the combination therapy of recombinant proteins ISYNA1 and LY294002 did not further inhibit MPO⁺ neutrophil and ROS production on the basis of LY294002 intervention (Figure 4E). Similarly, on the basis of LY294002 intervention, the combination therapy of myo-inositol and LY294002 also did not further inhibit MPO⁺ neutrophil and ROS production (Figure 4F). These results further supported the conclusion that downregulation of ISYNA1 led to reduced myo-inositol synthesis, thereby promoting NETs formation through modulation of PI3K/AKT pathway.

Myo-Inositol Significantly Reduces Pancreatic Injury in AP Mice

We established a cerulein-induced AP model and observed the effect of myo-inositol on AP. Based on the previous dose‑gradient experiment (Supplementary Figure 4), we chose 600mg/kg myo-inositol for subsequent experimental validation. Our research resulted show that after administration of myo-inositol, the pathological damage to pancreatic tissue in mice was remarkably reduced, and the levels of serum amylase, lipase, and inflammatory factors were also significantly decreased (Figure 5A, B, D and E). In addition, we found through immunofluorescence detection that the formation of NETs (Cith3/MPO co-localization) in the pancreatic tissue of AP mice after administration of myo-inositol was prominently reduced compared to the control group (Figure 5A and C). In brief, these in vivo experimental results indicated that myo-inositol could inhibit the formation of NETs in pancreatic tissue and protect pancreatic injury in AP mice, and reduce inflammatory response.

Figure 5.

Myo-inositol significantly reduces pancreatic injury in AP mice. (A) Representative H&E staining of pancreatic tissues at 100× (Scale Bar = 100 μm) and 400 × (Scale Bar = 50 μm) magnification. Representative immunofluorescence image of CitH3 and MPO at 400× (Scale Bar = 50μm) and 1000× (Scale Bar = 10μm) magnification (N = 6). The orange arrow points to the co‑localization of CitH3 and MPO, indicating NET formation. (B) Serum levels of amylase and lipase (N = 6). (C) Densitometric analysis of CitH3 and MPO fluorescence (N = 6). (D) Pathological scores of pancreatic tissues (N = 6). (E) Serum levels of IL‑6, TNF-α, and MCP-1 detected by ELISA (N = 6). Each experiment underwent three biological replicates. Statistical significance was denoted as: *P < 0.05, **P < 0.01, ***P < 0.001.

Discussion

Our study suggested that the crucial role of ISYNA1 in intracellular ROS generation and NETs formation in AP. Specifically, we elucidated the roles of ISYNA1 and myo-inositol in NETs formation, and demonstrated that myo-inositol could inhibit the release of NETs and reduce acute inflammatory organ damage in AP mice, and improve disease prognosis. Importantly, we also showed that ISYNA1 and the downstream metabolite myo-inositol are key points in the formation of targeted NETs in AP.

Neutrophils had unique antibacterial effects by releasing NETs to capture and kill various microbial pathogens.²⁵ NETs exhibited a typical fibrous network morphology, with their main structural component being the depolymerized chromatin DNA backbone. While NETs release contributed to capturing invading pathogens, their excessive release could trigger uncontrollable inflammatory responses. We first conducted a combined analysis of untargeted metabolomics and transcriptomics, and found a significant decrease in myo-inositol and its key enzyme ISYNA1 synthesis in neutrophils induced by PMA in NETs.

ISYNA1 was the rate‑limiting enzyme that catalyzes the conversion of glucose to inositol during de novo synthesis of myo-inositol, and it was the only enzyme responsible for endogenous myo-inositol synthesis. Hu et al¹⁹ showed that myo-inositol played the key role in reducing the process of renal inflammation, improving podocyte function, and preventing diabetes related renal injury. Myo-inositol and its derivatives exhibited tumor‑suppressive effects through inhibition of the PI3K/AKT pathway.^20,21 Although ISYNA1-myo-inositol axis had been extensively demonstrated in cancer and metabolic diseases; its role in AP, especially in regulating the NETs formation, was not yet clear. Given that PI3K/AKT signaling was the classic pathway in the NETs formation. Therefore, our study mainly explored the ISYNA1-myo-inositol axis driving PI3K/AKT activation to promote the formation of NETs in AP. Our study also indicated that ISYNA1 expression was significantly reduced in PMA‑induced NETs. Meanwhile, ISYNA1 and myo-inositol both inhibited NETs formation in vitro and reduced the levels of inflammatory factors during the formation of NETs. Through flow cytometry analysis, compared with the PMA stimulation group, the ISYNA1‑specific siRNA knockdown group significantly also increased the MPO⁺neutrophil and ROS production. Furthermore, myo-inositol significantly alleviated pancreatic tissue damage in AP mice and suppressed inflammatory response, concomitant with a reduction in NETs formation within the pancreatic tissue. Collectively, these results demonstrated that ISYNA1 knockdown led to a decrease in myo-inositol synthesis, resulting in an increase in NETs production; exogenous supplementation of myo-inositol could lead to the decrease in the NETs formation. Therefore, ISYNA1 and myo-inositol were possible regulators in the formation of NETs, and enhancing ISYNA1-myo-inositol axis was a potential intervention strategy for inhibiting the formation of NETs.

Research demonstrated that activation of the PI3K/AKT signaling pathway in immune cells could promote the secretion of anti-inflammatory factors while inhibiting the production of pro-inflammatory factors, laying the foundation for treating various inflammatory diseases.²⁶ Zhang et al showed that apigenin promoted apoptosis in 4T1 cells and improved the tumor immune microenvironment in vivo via the PI3K/AKT/Nrf2 pathway.²⁷ Another study indicated that cathepsin B regulates microglial migration and phagocytosis of amyloid-β in Alzheimer’s disease via PI3K-AKT signaling.²⁸ NETs contributed to the pathogenesis of AP by inducing trypsin activation, causing tissue damage, and accelerating systemic inflammatory responses.^29–31 Currently, no effective clinical interventions were available to specifically inhibit NETs release. In our study, we also confirmed that ISYNA1 and myo-inositol both inhibited the NETs formation via the PI3K/AKT pathway. These results supported that downregulation of ISYNA1 led to reduced myo-inositol synthesis, thereby promoting NETs formation through modulation of the PI3K/AKT pathway. However, the possibility that ISYNA1 might interact with other signaling pathways requires further investigation.

Our research still had some limitations. It mainly includes the following points: Firstly, the study mainly relied on immunofluorescence co‑localization, scanning electron microscopy, and flow cytometry to observe the formation of NETs. We would further quantify the formation of NETs by detecting extracellular DNA, MPO-DNA complexes, or CitH3‑DNA complexes in the future. Secondly, sample size of our study was limited, but we had validated the reliability of the core conclusions through various methods, and the observed effects were large and statistically significant. We would apply a larger sample size for further verification in the future. Thirdly, our research suggested that the myo-inositol metabolism modulated inflammatory injury in AP via the ISYNA1-NETs axis. We would further establish stronger causal relationships and translational applicability through rescue experiments and clinical validation in the future. Fourthly, we used exogenous addition of recombinant ISYNA1 protein for experimental validation. We would further elucidate this mechanism by combining cell uptake assays, intracellular enzyme activity, and subcellular localization analysis. Finally, our research was mainly based on animal models and in vitro cell experiments, and had not yet been validated in clinical samples. We would collect peripheral blood samples from AP patients to detect the correlation between ISYNA1 activity, myo-inositol levels, and NETs markers in serum, and explore the potential value of ISYNA1 or myo-inositol levels as early warning biomarkers for the severity of AP.

Conclusion

To sum up, our findings suggested that downregulation of ISYNA1 led to reduced myo-inositol synthesis, thereby promoting NETs formation through modulation of PI3K/AKT pathway. Targeting myo-inositol metabolism and its upstream ISYNA1 could suppress NETs generation and alleviate inflammatory injury in AP mice. This study provided a new perspective for understanding the regulatory mechanism of NETs formation and laid a theoretical foundation for the development of treatment strategies for AP and related inflammatory diseases. However, these preclinical findings still need further translational research to verify.

Funding Statement

This work was supported by the National Natural Science Foundation (82400763, 82200996, 82500739); Natural Science Foundation of Jiangsu Province (No. BK20240500); 2025 Jiangsu Province Youth Science and Technology Talent Support Project (JSTJ-2025-959); Yangzhou Natural Science Foundation (No. YZ2024186); Surface Project of Basic Science (Natural Science) Research in Higher Education Institutions in Jiangsu Province (No. 24KJD320007); the Policy Guidance Program (International Science and Technology Cooperation) project of Yangzhou (No. YZ2023265); and the Jiangsu Provincial Administration of Traditional Chinese Medicine (MS2022150).

Abbreviations

NETs, Neutrophil extracellular traps; AP, Acute pancreatitis; PMA, Phorbol-12-myristate-13-acetate; KEGG, Kyoto encyclopedia of genes and genomes; RNA-Seq, RNA sequencing; PI3K/AKT, Phosphatidylinositol 3-Kinase /Protein Kinase B; SAP, Severe acute pancreatitis; ROS, Reactive oxygen species; GSDMD, Ggasdermin D; ISYNA1, Inositol-3-phosphate synthase; SPF, Specific pathogen-free; RPMI, Roswell park memorial institute; Cae, Caerulein; PBS, Phosphate buffered saline; H&E, Hematoxylin and eosin; MPO, Myeloperoxidase; Cith3, Citrullinated histone h3; DAPI, 4′,6-Diamidino-2′-phenylindole; FBS, Fetal Bovine Serum; TNF-α, Tumour necrosis factor-alpha; MCP-1, Monocyte chemoattractant protein-1; IL-6, Interleukin-6; DHE, Dihydroethidium; DEGs, Differentially expressed genes; WB, Western blot; BCA, Bicinchoninic acid assay; PAGE, SDS-polyacrylamide gel electrophoresis; PVDF, Polyvinylidene fluoride; PAD4, Peptidylarginine deiminase 4; SEM, Scanning electron microscope; ANOVA, One-way analysis of variance; SE, Standard error; SEM, Standard error of mean; NADPH, Nicotinamide Adenine Dinucleotide Phosphate Hydrogen; Nrf2, Nuclearfactor erythroidderived 2-like 2.

Data Sharing Statement

The data shown in this article are available from the corresponding authors upon a reasonable request.

Author Contributions

Fei Han: Writing-original draft, Methodology, Data curation, Conceptualization, Funding acquisition. Xinyi Liu: Writing-original draft, Validation, Investigation, Conceptualization, Data curation. Yinghong Fan: Formal analysis, Methodology, Software, Resources, Writing-original draft. Xiaolei Shi: Investigation, Funding acquisition, Writing-original draft, Project administration, Supervision. Lin Chen: Investigation, Methodology, Data curation, Validation, Writing-original draft. Weiming Xiao: Conceptualization, Visualization, Writing – review & editing, Supervision, Data curation. Guotao Lu: Writing – review & editing, Data curation, Investigation, Supervision, Validation. Yaning Wang: Investigation, Funding acquisition, Resources, Project administration, Writing – review & editing. Keyan Wu: Investigation, Funding acquisition, Visualization, Validation, Writing – review & editing. Tianqi Xia: Writing – review & editing, Project administration, Investigation, Data curation, Visualization. Jinqiang Zhuang: Writing – review & editing, Supervision, Resources, Visualization, Resources. Runfeng Sun: Writing – review & editing, Supervision, Project administration, Conceptualization, Validation. All authors gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agreed to be accountable for all aspects of the work.

Disclosure

The abstract of this paper was presented at the Digestive Disease Week^® (DDW) 2026 as a poster presentation. The poster’s abstract was published in “Poster Abstracts” in DDW ePoster Library: https://eposters.ddw.org/ddw/2026/ddw-2026/4197144.