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. 2026 Feb 18;110:67. doi: 10.1007/s00253-026-13751-y

Establishment and validation of a rat sepsis model aligned with sepsis-3 via Staphylococcus aureus tail vein infection

Simiao Chen 1,#, Xuanwen Ru 1,#, Qingyi Shao 1, Danlei Chen 1, Fangmei Zhou 2, Zhishan Ding 2, Wenxia Shao 3,✉, Qing Ye 1,4,✉
PMCID: PMC12920337  PMID: 41706154

Abstract

Abstract

Sepsis, a life-threatening organ dysfunction stemming from uncontrolled host responses to infection, continues to be a leading global health threat. Despite the establishment of diverse preclinical animal models for sepsis research, their inherent deficiencies have significantly hindered their clinical translation. In this study, we developed a rat model of sepsis through continuous tail vein injection of a single, defined Staphylococcus aureus strain. Bacteriological identification confirmed the exclusive presence of the inoculated pathogen. The model recapitulated key clinical features of human sepsis, including altered mental status, respiration, and fever. Biochemical tests of peripheral blood revealed that the model rats and clinical sepsis patients presented similar alterations in indicators related to coagulation function and the cardiac, hepatic, and renal systems. Compared with the control group, model rats exhibited increased platelet counts (P < 0.05), total bilirubin, urea, and cystatin levels (P < 0.001, P < 0.01, P < 0.05, respectively). Histopathological and ultrastructural examinations confirmed multi-organ damage. Additionally, tandem mass tag proteomics analysis identified a total of 707 significantly differentially expressed proteins (P < 0.05, fold change > 1.2), with 279 upregulated and 428 downregulated in the model group compared to the control group. These proteins were enriched in inflammatory and immune responses, signal transduction, and oxidative stress pathways, systematically revealing molecular-level dysregulation. Collectively, our model meets Sepsis-3 and provides a standardized, stable, and reproducible platform for mechanistic research and therapeutic development.

Key points

  • A standardized rat sepsis model via sustained Staphylococcus aureus tail vein injection was established.

  • The model meets Sepsis-3 through multilevel clinical and pathological validation.

  • It provides a stable, reproducible tool for mechanistic research and therapeutic development.

Graphical Abstract

graphic file with name 253_2026_13751_Figa_HTML.webp

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Supplementary Information

The online version contains supplementary material available at 10.1007/s00253-026-13751-y.

Keywords: Sepsis, Staphylococcus aureus, Animal model, Pathogen

Introduction

Sepsis, a heterogeneous syndrome arising from dysregulated host responses to infection, is a leading cause of global mortality, with case fatality rates ranging from 15 to 30% in industrialized nations to over 50% in low-resource settings (Dugani and Kissoon 2017). The 2017 Global Burden of Disease report underscored its enduring impact, attributing nearly 20% of all-cause mortality worldwide to sepsis-related complications (Gavelli et al. 2021; Rudd et al. 2020; Seymour et al. 2019). The evolution of diagnostic frameworks reflects deepening pathophysiological insights: the 1991 consensus defined sepsis as infection-induced systemic inflammatory response syndrome (SIRS) (Bone et al. 1991), whereas the 2016 Sepsis-3 pivoted to a clinical mandate, emphasizing life-threatening organ dysfunction secondary to infection (Rhodes et al. 2017). This paradigm shift necessitates comparable advancements in preclinical modeling to align with contemporary clinical standards, particularly the Sequential Organ Failure Assessment (SOFA) score for diagnosis (Raith et al. 2017).

Preclinical animal models remain indispensable for dissecting sepsis pathogenesis, evaluating therapeutic interventions, and mitigating translational gaps. However, existing models—notably, cecal ligation and puncture (CLP), lipopolysaccharide (LPS) administration, and peritoneal contamination and infection (PCI)—exhibit critical limitations. CLP, despite its prevalence, recapitulates complex abdominal polymicrobial infections but suffers from technical variability, high surgical trauma, and mortality rates that correlate with ligation severity, impairing reproducibility (Dejager et al. 2011; Rittirsch et al. 2008; Seemann et al. 2017). While reproducible and technically straightforward, LPS models simulate only exotoxin-driven immune hyperactivation, failing to mirror authentic infection dynamics or multisystem organ failure (Deitch 1998). PCI requires meticulous donor-derived fecal preparation, introducing experimental complexity that hinders scalability (Angus and van der Poll 2013). Moreover, while certain live-bacteria intravenous infection models allow for the visual monitoring of pathogen dissemination and inflammatory responses, they still lack a systematic validation of infection dynamics, multi-organ injury, and dysregulated host responses (Liu et al. 2025b; Pass et al. 1984; Sato et al. 1982). Collectively, these approaches struggle to balance clinical fidelity, technical feasibility, and translational relevance.

An optimal sepsis model should replicate clinical trajectories, incorporate standardized infection sources, and enable quantifiable organ dysfunction assessment (Cohen 2018). Given that bacterial pathogens—particularly Staphylococcus aureus—emerge as predominant sepsis culprits in pediatric and immunocompromised populations (Schlapbach and MacLaren 2017; Schlapbach et al. 2015; van der Poll and Opal 2008), we sought to address existing limitations by developing an S. aureus tail vein injection (STVI) model. This approach streamlines technical execution, standardizes inoculum exposure, and recapitulates sepsis progression from initial bacteremia to end-organ dysfunction, adhering to the Sepsis-3 (Osuchowski et al. 2018). By prioritizing construct validity and clinical translatability, the STVI model aims to advance mechanistic investigations and therapeutic discovery in sepsis research.

Materials and methods

Preparation of bacterial solution

After recovering from ultra-low temperature storage at −80 °C, the standard S. aureus strain (ATCC25923) was inoculated on Columbia blood agar plates (CBAPs) via the four-zone delineation method (Joneberg et al. 2003), cultured at 37 °C in a 5% CO2 incubator for 12 h, and continuously inoculated for two passages. Bacteria in the logarithmic phase of growth were selected, and a 3.9 McFarland units (1.17 × 109 colony-forming units (CFU)/mL) bacterial mixture with saline as the solvent was prepared with a maxwell turbidimeter (BioMérieux, Marcy-l'Étoile, France).

Modeling process

Twenty adult male SD rats (Slack Laboratory Animal Co., Ltd., Shanghai, China), weighing 250–280 g, were randomly divided into model and control groups using a random number table to ensure comparable baseline body weight. Subsequent experimentation and analysis were carried out under double-blind conditions. Based on dose references from relevant modeling literature (Kernbauer et al. 2015; Sawai et al. 1997; Selle et al. 2016) and pre-experimental optimization (Ru et al. 2024), the final modeling protocol was established as follows: in the model group, a single bacterial mixture prepared with 200 μL (2.34 × 108 CFU) of normal saline was directly injected into the animals through the tail vein. In the control group, an equal volume of normal saline was injected in the same way. The injection continued for 2 days. During the modeling process, the rectal temperature of all the rats was measured every 2 h, symptoms were observed, and the respiratory rate and weight were measured appropriately. On the third day, whole blood was collected from the abdominal aorta of the rats after anesthesia. The abdominal cavity was quickly cut, the heart, liver, spleen, lung, kidney, and testis were removed within 2 min, and the tissues were washed with PBS for future use.

Bloodstream infection detection

Peripheral blood from the rats was collected for blood culture via an automatic blood culture system (BD BACTEC™ FX; BD, Sparks, MD, USA) to determine the status of bloodstream infection in the rat model. The blood was then inoculated on CBAPs via the four-zone delineation method. Gram staining, a plasma coagulation enzyme test, and a microbial analyzer (VITEK 2 COMPACT; Mérieux, Marcy-l'Étoile, France) were used to identify the strains.

Blood routine and biochemical tests

Rat blood samples were subjected to routine blood tests and biochemical tests, with a focus on the number of white blood cells, the number of platelets suggesting the status of coagulation, the content of creatine kinase-myocardial band (CKMB) suggesting myocardial injury, and the contents of bilirubin, aspartate aminotransferase (AST), adenosine deaminase (ADA), lactate dehydrogenase (LDH), and acetylcholinesterase (AChE) suggesting liver damage. Additionally, levels of urea and cystatin, which indicate kidney damage, were measured. Concurrently, relevant indicators for patients with sepsis were retrospectively collected and organized.

Hematoxylin and eosin (H&E) staining

Fresh tissues from the rats were fixed in 4% paraformaldehyde solution, placed in paraffin, and cut into 3-µm-thick sections. The sections were dewaxed in xylene twice for 10 min and hydrated in 100% ethanol for 3 min, 95% ethanol for 2 min, 80% ethanol for 2 min, and 75% ethanol for 2 h. Then, the sections were subjected to H&E staining (Fischer et al. 2008). Images of histopathological changes were acquired with a Leica fluorescence microscope (Leica Microsystems, Wetzlar, Germany).

Electron microscopy

Fresh rat tissues were infiltrated with 2.5% glutaraldehyde at 4 °C, quickly cut into 1-mm3 pieces, placed in a 2.5% glutaraldehyde solution, and fixed at 4 °C for 2 h. The samples were then fixed in a 1% osmic acid solution for 2 h. The samples were then dehydrated in increasing grades of ethanol, embedded in epoxy resin, and polymerized at 60 °C for 48 h. Ultrathin sections (60 nm) were cut with a diamond knife and placed on a 200-mesh copper grid. These sections were then stained with 50% uranyl acetate, saturated ethanol solution, and lead citrate for 15 min. The images were observed, photographed, and analyzed via transmission electron microscopy (TEM) (H-7650; Hitachi High-Tech, Tokyo, Japan).

Tandem mass tag (TMT) proteomics

Neutrophils were extracted from the fresh peripheral blood of the rats according to the manufacturer’s instructions for the Human Peripheral Blood Neutrophil Extraction Kit (TBD, Tianjin, China). The cells were preconditioned and analyzed via liquid chromatography‒mass spectrometry. Data-dependent acquisition (DDA) was performed by an UltiMate 3000 RSLC nano system liquid chromatographer (Thermo Scientific™, Sunnyvale, CA, USA) and a Q Exactive HF-Orbitrap mass spectrometer (Thermo Scientific™, San Jose, CA, USA). Mobile phase A consisted of 2% acetonitrile, 98% water, and 0.1% formic acid, and mobile phase B consisted of 2% water, 98% acetonitrile, and 0.1% formic acid. Analysis was performed via a 90-min electrospray liquid chromatography gradient. The scan parameters for the mass spectrometer were as follows: the primary scan range was 350–1800 m/z, the resolution was 60,000 (at 200 m/z), the automatic gain control target was 3e6, the maximum ion injection time (max IT) was 50 ms, and the signal intensity was less than 8e4. The ions were not collected. The secondary resolution was 60,000 pixels, the automatic gain control target was set to 2e5, the maximum ion injection time was 100 ms, the 20 most abundant precursor ions were selected, and the isolation window was set to 0.7 m/z when precursor ions were selected. The mass was set to 105 m/z. The differentially expressed proteins were compared to all the proteins in swissprot_rat_8615_2022.12.01.fasta. The false discovery rate (FDR) was < 1%, and the differences were considered statistically significant when the P value was <0.05 and the fold change was > 1.2. The proteomic data are available at the PRIDE repository accession number PXD056145 (https://www.iprox.cn//page/SCV017.html?query=PXD056145). The protein list with detailed quality data and fold changes has also been included in the Supplementary Material as the Supplementary Table S1.

Statistical analysis

In this study, deceased animals and data points showing significant outliers were not included in the analysis. The data were analyzed using SPSS Statistics 25.0 (IBM, Armonk, NY, USA) and GraphPad Prism 8 software (GraphPad Software, San Diego, CA, USA), and are presented as the means ± SDs.

When comparing two groups, continuous variables were first examined for normality and homogeneity of variance. If the data met both the normality and homogeneity of variance criteria, an independent samples t-test was used for inter-group comparisons. If the data did not satisfy the normality or homogeneity of variance conditions, the non-parametric Mann–Whitney U-test was applied. Differences with a P value of less than 0.05 were regarded as statistically significant.

Results

Blood cultures confirmed that the pathogen in the STVI model was a single S. aureus

In this study, a sepsis model was established by injecting S. aureus into the tail vein for two consecutive days (Fig. 1(A)). Blood cultures from the control group remained negative after 5 days, confirming that there was no bloodstream infection. In the model group, blood cultures were positive after 13 h. Gram staining identified the pathogen as a Gram-positive coccobacillus. The positive sample was cultured on CBAPs via the four-zone method. Further testing with Gram staining and a plasma coagulase test confirmed that the pathogen was a pathogenic Gram-positive Staphylococcus. Microbial analysis and identification revealed that the pathogenic strain in the model group was consistent with the injected S. aureus ATCC25923 strain (Fig. 1(B)). No other bacteria were detected. These results validated the model as a sepsis model.

Fig. 1.

Fig. 1

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The STVI model was consistent with the clinical characteristics of sepsis patients. A Modeling process of the STVI model. B Blood cultures and bacterial identification were performed to verify bloodstream infection in rats. C Changes in body surface symptoms in rats during the modeling process. D Changes in body temperature in the model and control groups (n = 4). E Changes in the respiratory rate in the model and control groups (n = 3). F Changes in body weight in the model and control groups (n = 4). The data are shown as the means ± SDs. The significance was calculated by t-tests or Mann–Whitney U-tests and marked as *P < 0.05; **P < 0.01

The STVI model has similar phenotypic changes, such as temperature fluctuations, abnormal respiratory rates, and weight loss, to those of patients with clinical sepsis

Patients with clinical sepsis present symptoms of hyperthermia or hypothermia, tachycardia, and shortness of breath. Accordingly, the model rats presented messy fur, swollen testicles, red eyes, and bloody eye secretions (Fig. 1(C)). In addition, after injecting S. aureus via the tail vein, the model rats developed chiropractic fever within 2 days, and the temperature was still higher than normal at the lowest point, which was in line with the fever type of clinical sepsis. Compared with that of the control group, the temperature of the model group significantly increased after 2 h of S. aureus directly entering the blood, with significant differences across multiple time periods (Fig. 1(D)). Moreover, the respiratory rate of the rats in the model group was significantly and persistently disordered, with occasional increases, whereas their body weight decreased continuously (Fig. 1 (E, F)). In general, these features mirrored clinical sepsis symptoms.

The STVI model has similar organ function damage to that of clinical sepsis patients

As a key clinical tool for diagnosing sepsis, the SOFA score quantifies the degree of organ dysfunction by sequentially assessing respiratory, coagulation, hepatic, cardiovascular, neurological, and renal function (Raith et al. 2017). However, its application in animal models is limited. This study used rat blood tests to infer organ abnormalities and compared the findings with clinical sepsis data (Fig. 2). H&E staining (Fig. 3) and TEM (Fig. 4) revealed pathological changes and ultramicroscopic structural changes in model organs, confirming the validity of the model in reflecting clinical manifestations of sepsis. The results revealed that the organs of the control group rats were essentially normal. In the model group, while the spleen and testis structures were normal, significant hematological and biochemical changes were observed. Compared with the control group, the model group presented abnormal white blood cell counts (Fig. 2(A)) and reduced platelet counts, indicating impaired coagulation function (Fig. 2(B)). Elevated CKMB levels suggested myocardial injury (Fig. 2(C)), with heart tissue showing structural abnormalities such as cell breakage and inflammatory infiltration. Ultrastructural analysis revealed swollen mitochondria with disorganized cristae.

Fig. 2.

Fig. 2

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STVI model trends with indicators of clinical sepsis patients.A and B Changes in white blood cell and platelet counts (n(Normal) = 13, n(Sepsis) = 49, n(Control) = 5, n(Model) = 7). C Changes in CKMB levels. D–J Changes in total bilirubin, direct bilirubin, indirect bilirubin, LDH, AST, AChE, and ADA levels. (K‒M) Changes in uric acid, urea, and cystatin levels. (C–M, n(Normal) = 6, n(Sepsis) = 36, n(Control) = 7, n(Model) = 7) The data are shown as the means ± SDs. The significance was calculated via t-tests or Mann–Whitney U-tests and marked as *P < 0.05; **P < 0.01; and ***P < 0.001

Fig. 3.

Fig. 3

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H&E staining results of the rat organs. A small amount of inflammatory cell infiltration (black arrow) was observed in the liver tissue of the model group, a small amount of myocardial cells was crushed and dissolved (yellow arrow), a small amount of myocardial cell nuclei moved inward (green arrow), and some inflammatory cell infiltration was observed in the myocardial gap (black arrow), a small amount of secreted proteins in the alveolar tissues (black arrow), a small amount of glomerular atrophy and degeneration of kidney tissues (black arrow), and a large amount of ischemic necrotic renal tubular epithelial cells sloughing off (yellow arrow). The scale bar is 100 μm

Fig. 4.

Fig. 4

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Ultramicroscopic structural changes in rat organs under an electron microscope. Electron microscopy revealed marked ultrastructural injuries in multiple organs of the sepsis model rats. Compared with the normal morphology in controls, the model group exhibited disorganized cardiomyocytes with swollen mitochondria and loss of cristae; hepatocytes showed reduced rough endoplasmic reticulum and glycogen, along with collagen deposition; type II alveolar cells and renal tissues displayed mitochondrial vacuolization, cristae loss, and increased membrane density (original magnification, ×10,000)

In addition, the levels of liver function markers (bilirubin, AST, LDH, and ADA) were elevated (Fig. 2 (D–H, J)), and AChE levels were decreased (Fig. 2 (I)), indicating liver injury. Liver tissue displayed mild structural abnormalities, including degenerated hepatocytes and inflammatory infiltration. The endoplasmic reticulum and glycogen content were markedly reduced on the rough surface of the hepatocytes, and collagen fiber production was representative of damage.

Moreover, the levels of urea and cystatin, which are indicators of kidney damage, were increased in the model group (Fig. 2(L, M)), and the content of uric acid, a secondary indicator of renal function, was decreased (Fig. 2(K)). Renal tissue showed moderate abnormalities, such as glomerular atrophy, tubular necrosis, epithelial shedding, and interstitial inflammation. Mitochondrial damage was evident, with swelling, disorganized cristae, and vacuolization. In addition, the lung tissue in the model group was moderately abnormal, with some alveolar atrophy, wall thickening, vascular bleeding, and protein secretion. Type II alveolar cells presented with mitochondrial membrane rupture and vacuoles, with reduced or absent cristae and increased membrane density. The above biochemical indicators matched the patients’ clinical trends. H&E staining and electron microscopy confirmed organic changes and organ dysfunction in the STVI model, validating its clinical simulation.

The STVI model confirmed that sepsis is associated with molecular-level intrinsic response dysregulation

This study focused on neutrophils, the body’s first line of defense against pathogens, to explore the pathogenesis of sepsis via proteomics. Neutrophils were isolated from rat peripheral blood post-STVI modeling, and proteomics revealed 3407 proteins, 707 of which were significantly altered (279 upregulated, 428 downregulated) (Fig. 5(A)). For the proteins with statistically significant differences in the above analyses, the heatmaps highlighted differential expression between the control and model groups (Fig. 5(B)). To better understand the functions of these differential proteins, GO (http://geneontology.org), KEGG (https://www.kegg.jp), and GSEA (https://www.gsea-msigdb.org/gsea/index.jsp) analyses were performed. According to the GO results, these proteins were partially located in organelles such as lysosomes, autophagosomes, protease complexes, and peroxisomes (Fig. 5(C)). KEGG pathway analysis also revealed that the pathways in which the multiple differentially expressed proteins were enriched involved the immune response (antigen processing and presentation, neutrophil extracellular trap formation, etc.), coagulation function (complement and coagulation cascades, the C-type lectin receptor signaling pathway, etc.), and oxidative stress (mTOR signaling pathway, NF-kappa B signaling pathway, etc.) as well as signaling processes such as cell proliferation, apoptosis, and inflammation (Fig. 5(D)). Moreover, GSEA was used to quantify potential functional pathways. The enrichment results revealed that the enrichment results were focused mainly on the activation of immune cells, the transcription of cytokines, and the phagocytosis of neutrophils (Fig. 5(E)). Next, to study sepsis-related pathways in a more targeted manner, the above-described KEGG-enriched pathways and their associated proteins (identified in this study) were presented in a network diagram form (Fig. 5(F)), and Pearson analysis was performed. Correlation cluster analysis (Fig. 5(G)) revealed that related proteins presented significant positive and negative correlations. For example, high mobility histone B1 (Hmgb1) was highly positively correlated with cathepsin E and highly negatively correlated with protein-tyrosine kinase 2-β but relatively less correlated with matrix metalloproteinase 2 (MMP2). The high correlation between proteins further illustrated the reliability of the enriched sepsis-related pathways. In addition, a protein–protein interaction (PPI) network analysis was performed on these proteins via the STRING database (https://string-db.org) (Fig. 5(H)). Proteins with many interactions and high scores, such as signal transducer and activator 3 (Stat3), mitogen-activated protein kinase 9 (MAPK9), CD4 (Cd4), and protein tyrosine kinase 2B (Ptk2b), play important roles in cell signal transduction and immune recognition and response. Currently available studies have identified the pathogenesis of clinical sepsis as a complex process involving various aspects, such as the activation of inflammatory signaling pathways, the activation and regulation of immune cells, the expression and function of immunomodulatory factors, intra- and extracellular signaling, apoptosis, oxidative stress, and cytoskeletal remodeling. Therefore, the above proteomics results further validated the dysregulated nature of the STVI model and its similarity to clinical sepsis, supporting its use in clinical translation.

Fig. 5.

Fig. 5

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Proteomic profiling of neutrophils in the STVI model.(A) Volcano map of differentially expressed proteins. Each point represents a protein. Red and blue points denote significantly upregulated and downregulated proteins, gray points indicate non-significant proteins. (B) Heatmap of differentially expressed proteins. Expression patterns of significant proteins across samples are shown (rows, proteins; columns, samples; color, Z-score normalized expression). (C) Histogram of some important items in the biological process (BP), cellular component (CC), and molecular function (MF) based on GO analysis. Bar height represents enrichment significance (−log₁₀(P-value)). (D) Bubble plot of several important pathways identified by KEGG enrichment analysis. Bubble size corresponds to the number of enriched proteins, and color indicates the enrichment significance. (E) GSEA results were enriched in the neutrophil response to phagocytosis data (GSE2405). The “phagosome” related gene set (referenced dataset GSE2405) was significantly activated in neutrophils in response to model induction. (F) Network diagram of several important pathways identified by KEGG enrichment analysis. This visualization illustrates the membership relationships between key pathways and their enriched differential proteins. (G) Heatmap of the results of the correlation cluster analysis of KEGG-enriched pathway-related proteins. This reveals co-expression patterns of these proteins across samples. (H) PPI network of KEGG-enriched pathway-related proteins. Node size is proportional to connectivity, and core hub proteins are highlighted. The significance was calculated via t tests (n = 3); *P < 0.05; **P < 0.01. The cutoff for dysregulated proteins was set at −log10(P-value) < 0.05 and log2(FC) > log2(1.2), protein FDR < 1%

Discussion

Sepsis, a systemic infection-induced syndrome with high mortality, poses significant public health challenges (Liu et al. 2025a). This study established an STVI model using S. aureus as the sole pathogen, which was in strict accordance with Sepsis-3. The model’s clinical validity was verified through blood culture, comparisons with clinical sepsis characteristics, organ damage assessment, and molecular mechanism analysis.

First, using blood culture as the gold standard for sepsis diagnosis, a positive bloodstream infection in the model was confirmed, the pathogenic strain in the body was consistent with the injection strain, and there was no other miscellaneous bacterial infection, thus preliminarily confirming that the STVI model was a sepsis model. In addition, patients with clinical sepsis usually present with chills, mental status malaise, tachycardia, shortness of breath, and leukocytosis or reduction (Hotchkiss et al. 2016), with a typical relaxation heat-up type (Bhavani et al. 2019, 2022). In the STVI model, there was a significant increase in temperature after 2 h of S. aureus infection, with a fluctuation range of more than 2 °C within 24 h. An increase or decrease in white blood cells was detected. These findings confirmed that the STVI model established in this study exhibited characteristics similar to those of clinical sepsis patients.

Second, blood tests revealed that organ dysfunction in the model was abnormal. H&E staining and TEM revealed histopathological and ultramicroscopic structural changes, confirming that the STVI model has organ dysfunction, which meets the criteria of Sepsis-3. One of the pathological features of sepsis is excessive activation of the immune and coagulation systems by pathogens, especially bacteria, which can lead to multiorgan failure and death of the host (Gando et al. 2016; Zhang et al. 2020). Multiple organ failure in sepsis is the progressive failure of several interdependent organ systems and is related to inflammation, mitochondrial dysfunction, and cell apoptosis. In this study, blood test indicators such as platelets, CKMB, AST, and urea indicated abnormal coagulation and cardiac, liver, and kidney function in the models. After comparison with the corresponding indicators of clinical sepsis patients, the same trend was found, indicating the clinical reliability of the model. In addition, pathological changes, including tissue structure abnormalities and inflammatory infiltration, were observed in the heart, liver, lungs, and kidneys via H&E staining. TEM further revealed ultrastructural changes, such as disordered cell arrangement and mitochondrial damage. Additionally, H&E staining revealed that the histological structures of both the spleen and testicular tissues were largely normal, suggesting that organ damage in this model likely did not involve the spleen. Consequently, no further ultrastructural analysis at the electron microscopic level was performed. However, existing studies have shown that, as the largest peripheral immune organ of the host, the spleen is the main location of immune cells (Lewis et al. 2019). Impaired spleen function is a common phenomenon in sepsis patients. However, Martinez-Orengo et al. (2022) used [18F]N,N-diethyl-2-[4-(2-fluoroethoxy)phenyl]−5,7-dimethylpyrazolo[1,5-a]pyrimidine-3-acetamide (DPA)−714 as a biomarker of inflammation in the brain and peripheral organs and positron emission tomography (PET) imaging to quantify immunoreactivity at the organ level in sepsis patients. The results revealed inflammatory responses in the brain, lung, bone marrow, and liver. However, there was no significant change in the spleen. The combined literature evidence suggests that splenic dysfunction may be more pronounced during the late or most severe stages of sepsis (such as septic shock), potentially occurring later than in other organs. This hypothesis is primarily based on existing studies, and the precise timing and mechanisms remain to be further elucidated in future research. These results indicate damage at the organ level in the STVI model, effectively suggesting organ dysfunction.

Finally, high-throughput proteomic detection revealed that the intrinsic molecular mechanism of the STVI model was dysregulated at the cellular and molecular levels, which was consistent with studies on clinical sepsis. Immune response dysregulation caused by infection and subsequent tissue damage is the pathobiological basis of sepsis (Qi et al. 2021). Neutrophils are an essential part of the innate immune system; they are considered the most sensitive cells in sepsis (Wang et al. 2023) and play a critical role in eliminating invading bacteria (Ley et al. 2018). Therefore, in this study, neutrophils in the STVI model were used for proteomic analysis, and 707 proteins significantly differentially expressed between the model and control groups were identified. GO analysis revealed that these proteins were localized to organelles such as lysosomes and peroxisomes, suggesting effective pathogen clearance by neutrophils. KEGG analysis highlighted pathways related to coagulation, oxidative stress, apoptosis, and inflammation, all of which are critical in sepsis pathogenesis. Extensive basic and clinical studies have shown that neutrophil apoptosis and autophagy are directly related to the development of organ dysfunction during sepsis (Iba et al. 2013), whereas cytokines regulate inflammatory signaling and reactive oxygen species (ROS) generation (Yang et al. 2019). The relevant reactions and proteins were included in the KEGG and GSEA results. NETosis or necrotic neutrophils release damage-associated molecular patterns (DAMPs) such as histones and high mobility group box 1 (Hmgb1) (Iba et al. 2013; Li and Lu 2021), which mediate inflammation, coagulation, organ damage, and death through Toll-like receptors or inflammasome pathways (Iba et al. 2014; Rondina and Garraud 2014). Pearson correlation clustering analysis of the enriched pathway-related proteins confirmed the highly significant correlation between Hmgb1 and other proteins, indicating its important role in sepsis. In addition, neutrophils recognize chemokines and enter the site of infection through mobilization, rolling, adhesion, migration, and chemotaxis. However, in sepsis, neutrophils cannot migrate to appropriate target locations, and chemokine receptor dysregulation is an important cause of impaired migration (Wang et al. 2023). The mTOR/HIF-1α signaling pathway enriched in this study was confirmed to be involved in the chemotaxis of neutrophils during sepsis (Pan et al. 2022), which is expected to elucidate the mechanisms involved in impaired neutrophil migration. These results preliminarily revealed abnormalities in neutrophil immune function in sepsis and confirmed that the STVI model could effectively simulate dysfunction of the intrinsic molecular mechanisms of clinical sepsis. In summary, this study verified that the STVI model met the Sepsis-3 standard through systematic appearance and mechanistic validation, laying the foundation for further studies on the pathogenesis of sepsis and the development of treatment strategies.

In addition to meeting the clinical Sepsis-3, the STVI model established in this study has several advantages. This model uses continuous tail vein injection to confirm that the single pathogenic source is S. aureus. This simplifies modeling, reduces operational variability, and enhances result interpretation. By strictly controlling the bacterial concentration, systemic inflammation without acute death can be induced, maintaining the model in the acute inflammatory stage. Two days of bacterial injection mimics persistent infection, providing a stable and controllable method. These features make the STVI model a reliable tool for studying sepsis progression.

Limitations and future directions

This study focuses on constructing and validating a standardized, reproducible venous infection model. Its core advantage lies in using a single pathogen (S. aureus) and fixed parameters to achieve a stable, controllable, non-lethal phenotype. This deliberate design also defines the model’s current application boundaries: First, it concentrates on S. aureus infection and does not yet cover clinically common mixed infection scenarios; Second, to prioritize study feasibility during the acute phase, the infection protocol may not fully replicate all pathological features of late-stage sepsis (e.g., the shock phase). These limitations are dictated by the foundational validation objectives of this study. Future work can leverage this stable platform to expand its potential for simulating diverse infection types and disease progression by adjusting pathogens, doses, or time windows.

Supplementary Information

Below is the link to the electronic supplementary material.

ESM 1 (354KB, xlsx)

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Acknowledgements

Not applicable.

Author contribution

Conceptualization and project administration: QY Data curation and Writing-original draft: SC, XR Methodology: QS, DC Visualization: FZ, ZD Writing-review & editing: WS. All the authors have read and approved the final manuscript.

Funding

This study was supported by the Joint TCM Science & Technology Projects of National Demonstration Zones for Comprehensive TCM Reform (Grant No. GZY-KJS-ZJ-2025-015), the Joint Fund of Zhejiang Provincial Natural Science Foundation of China (Grant No. LKLY25H200004), and the Zhejiang Provincial Outstanding Youth Science Foundation (Grant No. LR24H200001).

Data availability

The proteomic data are available at the PRIDE repository accession number: PXD056145 (https://www.iprox.cn//page/SCV017.html?query=PXD056145). The protein list with detailed quality data and fold changes has also been included in the supplementary materials in an (excel) table (Table S1).

Declarations

Ethics approval and consent to participate

This study adhered to the Declaration of Helsinki and ARRIVE guidelines. All animal procedures were approved by the Animal Care and Use Committee of Zhejiang Eyong Pharmaceutical Research and Development Center (Approval No: ZJEY20230420-04). And the clinical retrospective data analysis study was approved by the Children’s Hospital, Zhejiang University School of Medicine Ethics Committee (Approval No: 2023-IRB-0107-P-01).

Consent for publication

All authors have read and approved the submission of the manuscript.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Simiao Chen and Xuanwen Ru contributed equally to this work.

Contributor Information

Wenxia Shao, Email: wx5366@163.com.

Qing Ye, Email: qingye@zju.edu.cn.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

ESM 1 (354KB, xlsx)

(XLSX 353 KB)

Data Availability Statement

The proteomic data are available at the PRIDE repository accession number: PXD056145 (https://www.iprox.cn//page/SCV017.html?query=PXD056145). The protein list with detailed quality data and fold changes has also been included in the supplementary materials in an (excel) table (Table S1).

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