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10.1080/21505594.2024.2395835
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Research Article
Research Article
Simulating the clinical manifestations and disease progression of human sepsis: A monobacterial injection approach for animal modeling
X. RU ET AL.
VIRULENCE
https://orcid.org/0009-0002-7870-2515
Ru Xuanwen a *
Chen Simiao a *
Chen Danlei b
Shao Qingyi b
Shao Wenxia c
https://orcid.org/0000-0002-6756-0630
Ye Qing a
a Department of Clinical Laboratory, Children’s Hospital, Zhejiang University School of Medicine , Hangzhou, China
b School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University , Hangzhou, China
c Hangzhou First People’s Hospital, Zhejiang University School of Medicine , Hangzhou, China
CONTACT Wenxia Shao wx5366@163.com
Qing Ye qingye@zju.edu.cn
* These first authors contributed equally to this article.

1 9 2024
2024
1 9 2024
15 1 2395835Integra29 8 2024
Integra29 8 2024
15 1 2024
08 8 2024
19 8 2024
© 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
2024
The Author(s)
https://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

ABSTRACT

Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection, with great clinical heterogeneity, high morbidity, and high mortality. At the same time, there are many kinds of infection sources, the pathophysiology is very complex, and the pathogenesis has not been fully elucidated. An ideal animal model of sepsis can accurately simulate clinical sepsis and promote the development of sepsis-related pathogenesis, treatment methods, and prognosis. The existing sepsis model still uses the previous Sepsis 2.0 modelling standard, which has some problems, such as many kinds of infection sources, poor repeatability, inability to take into account single-factor studies, and large differences from clinical sepsis patients. To solve these problems, this study established a new animal model of sepsis. The model uses intravenous tail injection of a single bacterial strain, simplifying the complexity of multibacterial infection, and effectively solving the above problems.

GRAPHICAL ABSTRACT

KEYWORDS

Sepsis
monobacterial infection
animal model of sepsis
pathophysiology
clinical translation
The author (s) reported there is no funding associated with the work featured in this article.
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pmcBackground

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection and remains the leading cause of death in critically ill patients [1]. Despite significant advances in sepsis research and a deeper understanding of its pathophysiology, the incidence and mortality rates of sepsis are still increasing globally. The estimated number of sepsis patients worldwide is approximately 50 million annually, with 11 million deaths, resulting in a mortality rate of almost 20%, representing a significant public health burden [2]. In the United States, for example, sepsis is the most common cause of hospital death, resulting in annual losses of over $24 billion [3,4]. Epidemiological studies have shown that the number of deaths caused by sepsis and septic shock has surpassed the number of deaths caused by acute myocardial infarction and continues to increase, imposing considerable medical and economic burdens on people worldwide [5]. The incomplete understanding of its pathogenesis is the primary reason for this situation.

Animal models are essential for studying human disease pathogenesis, but current animal models related to sepsis still rely on the previous Sepsis 2.0 criteria (infection+SIRS) [6]. This model standard differs from the latest Sepsis 3.0 standard, in which “life-threatening organ dysfunction” is a crucial consideration [7]; consequently, the use of this model to study the pathophysiology of sepsis and related drug development will be greatly limited [1]. Studies have shown that 40% of studies use the endotoxin injection model, and 44% of studies use the caecal ligation and puncture (CLP) model in terms of infection mode [8]. However, sepsis can be caused by a variety of pathogenic bacteria, parasites, fungi, or viruses [9], suggesting that LPS is the main inducer of this disease. Furthermore, the current evidence clearly indicates significant differences between sepsis phenotypes and those induced by LPS [10]. In addition, mice are insensitive to bacterial products such as LPS, and the lethal LPS dose for mice is approximately 1000 times greater than the estimated lethal dose for humans [11,12]. These factors inevitably limit the transfer of research conclusions obtained through LPS-induced sepsis to clinical practice.

The widely used CLP model can induce similar sepsis dynamics in animals, including the activation of proinflammatory and anti-inflammatory immune responses, persistent inflammatory responses, multiple organ dysfunction, and cytokine responses. However, there are many confounding factors in the CLP model, and the severity of sepsis in this model is related to the length of caecum ligation, the size of the perforation needle, and supportive treatment after CLP [13]. Additionally, CLP cannot replicate infections in the most common site (lung) of patients. The complex interaction between host cells and pathological factors in different tissues and organs cannot be truly reproduced in vitro.

To provide a reference for clinical sepsis treatment, a reliable sepsis animal model is still necessary to simulate the clinical manifestations and disease progression of human sepsis. Therefore, this research utilized a single bacterial strain injection modelling method for the first time, simplifying the mixed infection into a single bacterial strain and eliminating the severe surgical damage caused by caecal ligation. Using tail vein injections, live bacteria were directly injected into the animal’s body to simulate a systemic infection. Additionally, we utilized a low-dose multiple injection method to simulate the continuous release of bacteria and endotoxins from the infection site. We ultimately established a sepsis model in rats caused by a single bacterial strain. This model has significant potential for standardizing sepsis model systems.

Methods

Induction of septicemia in rats

Rat

Male adult SD rats (Shanghai Slaik Experimental Animal Co., Ltd.) greater than 250 g in weight were housed in a standard specific pathogen-free (SPF)-grade animal facility with 12 hours of light/12 hours of dark conditions, optimal temperature and humidity, filtered water, and appropriate nutritious feed.

Tail vein injection model of Escherichia coli

A frozen stock of Escherichia coli (ATCC25922) was inoculated onto a sterile culture loop and streaked onto four quadrants of a sterile agar plate before being incubated overnight at 37°C. This process was repeated to obtain activated bacterial colonies. The activated colonies were added to physiological saline to make a bacterial suspension with a McFarland concentration of 0.39, which was then stored for later use. Using the conversion formula 1 MCF = 3 × 108 CFU/mL, the bacterial suspension was adjusted with sterile physiological saline to a concentration of 1.17 × 108 CFU/mL. Rats were randomly divided into a control group and an experimental group. The control group was injected with 200 μL of sterile physiological saline via the tail vein, and the experimental group was injected with the same volume of E. coli bacterial suspension. The rats were injected once a day for two consecutive days.

LPS model

An SD rat model was used to assess the lipopolysaccharide (LPS)-induced inflammatory response. Rats in the experimental group were given 10 mg/kg LPS via intraperitoneal injection to induce a systemic inflammatory response.

CLP model

In all rats, anaesthesia was induced by 5% isoflurane (Baxter, Unterschleißheim, Germany) and maintained throughout by delivery of 2.5% isoflurane gas through a face mask. Preoperative sterilization was performed using betaxolide polysporin. For analgesia, all mice were injected subcutaneously with 0.1 mg/kg body weight buprenorphine (Lidgett, Mannheim, Germany) 30 min before surgery. After performing median laparotomy, the caecum was identified and alloyed with 5 × 0 Vicryl in the midportion. Then, two punctures of the distal portion were performed with a 21 G cannula, and the abdomen was closed with simple interrupted sutures.

Monitoring the physiological indicators of septicemic rats

Starting from day 1 after the injection, the rats were monitored for signs of discomfort or disease every 2 hours. The following indicators were recorded: body temperature, respiratory rate, mental status, behaviour, food and water intake, and hair condition. The weight of the rats was measured daily to monitor their health.

Blood culture and bacterial identification in septicemic rats

Twenty-four hours after the second injection (preceded by a 12-hour fast with no access to food or water), 2 mL of blood was extracted from the abdominal aorta of each rat and added to blood culture bottles. The remaining blood was stored in a heparinized tube for future use. Positive culture bottle fluids were subjected to Gram staining and single colony culture. Individual bacterial colonies were then automatically identified using MALDI-TOF mass spectrometry after separation.

Routine blood tests, inflammatory cytokines and biochemical indices

To assess the physiological status of the rats, routine blood tests and biochemical index analyses were performed. First, blood samples were collected from the rats via abdominal aortic blood sampling, and the blood samples were partially placed in EDTA anticoagulation tubes for routine blood tests. Blood parameters such as red blood cells, white blood cells and platelets were determined using a fully automated haematology analyser (Mindray, BC-7500 series) and its accompanying kits. The other part of the blood sample was centrifuged to separate the serum for inflammatory cytokine detection and biochemical analysis. A Rat IL-1 beta ELISA Kit (Youke Life Sciences Technology Co., Hangzhou) was used. LTD, ER00010004), Rat IL-6 ELISA Kit (Youke Life Sciences Technology (IL-6), and TNF-α levels were measured. Serum indicators of liver and kidney function, including alanine aminotransferase (ALT), aliquot transaminase (AST), creatinine (Cr), and urea nitrogen (BUN), were measured using a fully automated biochemistry analyser (e.g. Beckman Coulter AU5800).

Histopathology of septicemic rat tissues

After blood was drawn from the abdominal aorta, the heart, liver, spleen, lung, and kidney were collected, washed with saline, and fixed in 4% paraformaldehyde for 48 hours. Kidney tissues fixed in 4% formalin and embedded in paraffin were sliced into 4 μm sections and stained with haematoxylin and eosin stain for observation under a microscope.

Transcriptomics

In this study, we analysed the gene expression profiles of the samples using transcriptomic techniques. First, total RNA was extracted from rat blood cell samples from the treatment and control groups, and RNA from the total samples was isolated and purified using TRIzol reagent (Thermo Fisher 15,596,018) according to the manufacturer’s instructions. Subsequently, RNA sequencing (RNA-seq) technology was used for library construction and high-throughput sequencing of the extracted RNA. Finally, we used Illumina NovaSeqTM 6000 (LC Bio Technology Co., Ltd., Hangzhou, China) for double-end sequencing according to standard procedures with the PE150 sequencing mode and a standard bioinformatics analysis pipeline for quality control, read-length comparison and expression quantification. Differentially expressed genes were identified by the DESeq2 software package and analysed for GO and KEGG pathway enrichment. Differentially expressed genes were obtained and enriched for analysis in set comparison groups using fold change (fold change) ≥2 (i.e. absolute value of log2FC ≥ 1) and q-value <0.05 (q-value is the corrected value of p value) as threshold criteria for screening differentially expressed genes (|log2FC|≥1 & q < 0.05).

Proteomic analysis of WBCs from septicemic rats

Rat blood was extracted using a TBD scientific cell extraction kit (LZA11131). After the WBCs were isolated, the protein concentration was measured following the instructions of the BCA kit. TMT labelling and HPLC fractionation were carried out according to standard procedures. LC‒MS analysis was performed on a Vanquish Neo UHPLC ultrahigh-performance liquid chromatography system. Mass spectrometry analysis was conducted after peptide separation. If p < 0.05 and the fold change > 1.2, the protein was considered to be significantly different between the Model and Control groups and was classified as a differentially expressed protein (DEP). Fisher’s exact two-tailed test was used for GO analysis and KEGG pathway enrichment analysis of DEPs, with p < 0.05 considered to indicate significant enrichment.

Statistical analysis

SPSS 25.0 software was used for statistical analysis. The independent samples t test was used for data that passed the normality and homogeneity of variance tests, while the Mann‒Whitney test was used for data that did not meet the assumptions. One-way ANOVA was used for comparisons of data at different time points within a group. The data are expressed as the mean ± standard deviation (±s), with p < 0.05 considered to indicate statistical significance.

Results

General characteristics and temperature changes in three different sepsis models reflecting their pathophysiological conditions

The inflammatory physiological state of the rats was assessed by measuring body temperature. In the control group, no significant changes in body temperature were observed, and the body temperature was maintained at approximately 37°C. In contrast, both the LPS and CLP groups exhibited similar temperature patterns. Initially, during the early phase of model establishment (6 hours), their body temperatures dropped below those of the control group. Subsequently, the temperatures of the model groups increased and remained elevated above those of the control group, indicating a sustained hyperthermic state (Figure 1a). Figure 1. Pathophysiological conditions of animal models of sepsis. (a) shows the changes in body temperature and respiratory rate of the three rat models of sepsis at different time points (the labelling of the first injection and the second injection is only for the Model group); (b) shows the comparison of testes, hair, and secretion from the eyes of the eyes of the rats of the control group and the Model group; (c) shows the graph of the positive results of the blood cultures in the blood culture flasks, the graph of the staining of the smear, the graph of the culture results via the four-zone line the positive results of blood culture in blood culture bottles, smear staining, and identification by four-zone delineation and colony mass spectrometer; (d) is the blood levels of IL-1β, IL-6, and tnf-α inflammatory factors in three sepsis model rats; e is the routine blood tests in the rats of three sepsis models after 48 h of modelling.

The pathological state of the rats was evaluated by monitoring respiratory rates. Compared to those in the control group, the respiratory rates in both the LPS and model groups showed similar trends, fluctuating above the control levels. In the CLP group, the respiratory rates were lower than those in the control group during the first 4 hours postsurgery but then tended to increase, ultimately exceeding the rates observed in the LPS and model groups (Figure 1a).

After saline injection, the control rats recovered well, exhibiting normal activity and healthy fur. In contrast, the model rats displayed signs of lethargy, piloerection, rapid breathing, and reduced activity. Noticeable redness and swelling in the testicular area were observed in the experimental group 4 hours after the first injection. Additionally, blood-tinged secretions were observed at the corners of the eyes in the model rats before the second injection (Figure 1b).Videos of the different time states of the three models will be presented in the supplementary file.

Blood culture identification results of E. coli infected rats to clarify their infections

Positive blood culture is the “gold standard” for identification of infection; therefore, after two consecutive days of E. coli injection, blood was taken 24 h after the second injection for blood culture, and the control group did not report positive results at 120 h, while the model group reported positive results (Figure 1c). Gram staining of liquid smears from positive blood culture bottles in the model group and microscopic examination of single colonies in culture medium followed by smears revealed E. coli (Figure 1c). A single colony on Columbia medium selected for this study was identified as E. coli. by mass spectrometry (Figure 1c).

Abnormal inflammatory cytokine levels and blood routine tests showed abnormal coagulation function

Inflammatory cytokines and routine blood parameters play important roles in the progression of sepsis; therefore, we analysed cytokine levels and blood indices at different time points in the three models and compared them. At 24 h, the levels of interleukin-1β (IL-1β), interleukin-6 (IL-6), and tumour necrosis factor-α (TNF-α) were higher in the LPS and CLP groups than in the model group. At 48 h, the levels of IL-1β, IL-6, and TNF-α inflammatory factors were higher in the model group than in the control group. The levels of IL-1β in the model group were comparable to those in the CLP group, and the levels of IL-6 and TNF-α in the model group were significantly greater than those in the LPS and CLP groups (p < 0.05), as shown in Figure 1d. At 48 h routine blood tests, platelet count (PLT) and platelet corpuscle pressure (PCT) were significantly lower (p < 0.05) in all three models of sepsis compared with the control group (Figure 1e). The results of 24 h routine blood tests in septic rats are demonstrated in Supplement Figure S1.

Pathologic histomorphometric comparison of organ lesions in different rat models of sepsis

H&E staining revealed that histopathology can clearly reflect the lesions of organ tissues, and in this study, the lesions of organs such as the heart, liver, spleen, lungs, and kidneys were comparatively analysed in the three models (Figure 2a). The structure of each organ in the control group was normal, with no pathological changes. In the model group, the myocardial tissue was mildly abnormal, with inflammatory cell infiltration (black arrows); a small number of cardiomyocytes were deeply stained, and the nuclei of individual cardiomyocytes were internally shifted and denatured (blue arrows), with a small number of fat vacuoles infiltrating the interstitial space of the cardiac muscle and interstitial vasodilatation and congestion of cardiac blood vessels (red arrowheads). The myocardial tissues of the rats in the LPS and CLP groups did not have any obvious abnormal pathological structures. Figure 2. Comparison of organ damage in three rat models of sepsis (after 48 h of modelling) (a) is the graph of HE staining pathological results of heart, liver, spleen, lungs and kidneys in the rat model of sepsis; (b) is the situation of biochemical indexes representing heart damage; (c) is the situation of biochemical indexes representing kidney damage; (d) is the situation of biochemical indexes representing liver damage.

Fatty vacuole infiltration was present in the liver tissues of both the model and LPS groups (black arrows) and was more severe in the model group. The nuclei of individual cells in the model group were deeply stained, and a small number of hepatocytes exhibited nuclear degeneration (blue arrows). A small amount of inflammatory cell infiltration was observed in the tissue (red arrowheads). Focal infiltration of inflammatory cells was observed locally in the portal duct area of the liver tissue of the rats in the LPS group (red arrowheads). A small amount of hepatocellular oedema was observed in the liver tissue of the rats in the CLP group, with cellular swelling and sparsely pale stained cytoplasm (black arrowheads).

In the model group, mild disorganization of lymphoid nodules was observed, with identifiable cell necrosis in the splenic nodules (blue arrowheads) and a few darkly stained lymphocytes in the red medulla (black arrowheads). In the LPS group, lymphocytes were tightly arranged in the splenic tissue, and a slight increase in neutrophils was observed in the red medulla (red arrowheads). The splenic structure of the CLP group showed occasional focal lymphocytic necrosis in the white medulla, with punctiform infiltration of neutrophils (black arrowheads).

The lung tissue structure of rats in the model group was mildly abnormal, with some alveoli atrophied and collapsed, the alveolar wall was obviously thickened, and the surrounding alveoli were fused to each other and dilated (blue arrows). Slight shedding of bronchial epithelial cells was observed in the lumen of blood vessels (red arrows), and a small amount of inflammatory cell infiltration was detected in the interstitium of the lungs (black arrows). There was no obvious abnormal pathological structure in the lung tissue of the rats in the LPS and CLP groups.

The renal tissue of rats in the model group was mildly abnormal in structure, with a small amount of glomerular atrophy and degeneration (blue arrowheads) and the presence of ischemically necrotic tubules with epithelial detachment (black arrowheads). Some erythrocytes were present in the renal interstitium (red arrowheads). There were no obvious abnormal pathological structures in the renal tissues of the rats in the LPS and CLP groups.

Clinical biochemical indices comparing organ lesions in different rat models of sepsis

Biochemical index tests can specifically assess the liver, kidney and heart functions of an organism and reflect the pathology of these organs. The results of biochemical indices of septic rats at 48 h were as follows: creatine kinase (CK) and creatine kinase-MB activity (CK-MB) are markers of myocardial injury, and CK-MB was elevated to varying degrees in all three models of sepsis, with LPS being the most significant (p < 0.05) (Figure 2b). Creatinine (CREA), urea (UREA), cystatin C (Cys C), and uric acid (URIC) are markers suggestive of renal injury, and CREA, UREA, and Cys C were significantly elevated in the LPS group compared with those in the control group (p < 0.05); however, the levels in the model group remained the same as those in the CLP group (Figure 2c). As shown in Figure 2d, all of which are biochemical indicators suggestive of liver injury, some of the indicators in the three sepsis models were significantly different from those in the control group and maintained a consistent trend, with total protein (TP), globulin (GLB), alanine aminotransferase/aspartate aminotransferase (AST/ALT), gamma-glutamyltransferase (GGT), and prealbumin (PALB) levels significantly increasing (p < 0.05), while the white globe ratio (A/G) and cholinesterase (CHE) content decreased significantly (p < 0.05). Figure 2d shows that the trends of the ALB, LDH, and ALP levels in the model group were different from those in the LPS and CLP groups, with an increase in the ALB concentration (p > 0.05) and a decrease in the ALP concentration (p < 0.05). These results indicate that the tail vein injection E. coli model is consistent with the CLP model in terms of cardiac and renal injury markers as well as hepatic bilirubin-related markers and has a certain degree of specificity. Results of routine blood tests in 24-h septic rats are shown in Supplement Figure S2. It is undeniable that tail vein injection of E. coli causes damage to various organs in rats.

Transcriptomic comparison of intrinsic organismal responses in E. coli infection models and CLP models

To clarify the ability of tail vein injection of the E. coli model to simulate the organismal response to sepsis, we analysed the transcriptomic data of peripheral blood leukocytes from the E. coli model rats in comparison with those from the peripheral blood cells of rats from the recognized sepsis model – the CLP model. At 48 h in the CLP model, 1591 genes were significantly upregulated; the top five genes were Ahnak, Ly6a, Ace, Rps18, and Rpsa; the remaining 1950 genes were significantly downregulated; and the top five genes were Il1b, Cxcr4, H2-Q10, Nfkbiz, and Csrnp1. At 48 h in the E. coli infection model, 858 genes were significantly upregulated, with the top five genes being Serpinb1a, Cd14, Vcan, Top2a, and Slpi, and 204 genes were significantly downregulated, with the top five being Slc2a4, Mfsd4a, Hemgn, Gnaz, and Ciart (Figure 3a). Figure 3. Comparative transcriptomics data situation. (a) differential gene volcano plot, the upper part is the CLP sepsis rat model differential gene volcano plot, the black labelled genes are the top five genes that are significantly up-regulated and significantly down-regulated in the CLP model, and the green labelled genes are the top five genes that are significantly up-regulated and significantly down-regulated in the E. coli infection model in the CLP differential genes; the lower part is the E. coli infection sepsis rat model differential gene volcano plot, black labelled genes are the top five genes significantly up-regulated and significantly down-regulated in the E. coli infection model, green labelled genes are the top five genes significantly up-regulated and significantly down-regulated in the CLP model expressed in the E. coli infection model differential genes; (b) is the differential gene clustering heatmap, on the left side is the heatmap of the top fifty significant differential genes in the CLP model, on the right side is the heatmap of the heatmap of the top fifty significant differential genes of the E. coli infection model; (c) is the differential gene VENN plot, the top is the venn plot of the significant differential genes up-regulated by the CLP model versus the E. coli infection model, and the bottom is the venn plot of the significant differential genes down-regulated by the CLP model versus the E. coli infection model; (d) is the GO function analysis, from the top to the bottom of the plot, the genes that are jointly significantly up-regulated by the two models enriched by the E. coli infection model, the GO function analysis enriched by the E. coli infection model alone significantly up-regulated genes, and the GO function analysis enriched by the CLP model alone significantly up-regulated genes; (e) is the KEGG function analysis, from top to bottom for the KEGG function analysis enriched by the E. coli infection model alone significantly up-regulated genes, and from bottom to bottom for the KEGG function analysis enriched by the CLP model alone significantly up-regulated genes functional analysis; (f) is the MCODE analysis of genes significantly up-regulated by the CLP model and E. coli infection model together; on the left is the PPI network constructed based on STRING for genes significantly up-regulated by the CLP model and E. coli infection model together, and on the right is the MCODE analysis of genes significantly up-regulated by the CLP model together, and the hub subclasses of the network were filtered by using MCODE in Cytoscape.Cytoscape.The significance was calculated by t-test marked as *p < 0.5; **p < 0.01. The cut-off of dysregulated proteins has been set at -log10 (p value) < 0.05 and log2(FC) >log2(2).

A heatmap was used to visualize the relative quantification of the top fifty genes in the two models, and the differentially expressed proteins were able to distinguish the model group from the control group well (Figure 3b). Subsequently, we jointly analysed the DEGs between the CLP model and the E. coli infection model and identified 82 genes whose expression was upregulated by both models and 12 genes whose expression was downregulated by both models (Sptb, Reep6, Plp1, Wnk4, Aqp1, Hemgn, Spta1, Sytl4, Ank1, Ciart, Ccnd1, and Slc2a4) (Figure 3c). To further understand the functions of the genes differentially regulated by these two models, we enriched the genes upregulated by the two models together, the genes upregulated by the E. coli infection model alone, and the genes upregulated by the CLP model alone. GO and KEGG analyses were performed (see Supplementary material for the enrichment of significantly downregulated genes). GO analysis revealed that the cooccurring biological processes in both models were involved in inflammation, positive regulation of the inflammatory response, phagocytosis, cell killing, cell chemotaxis, etc (Figure 3d). GO analysis of genes significantly enriched in genes related to sister chromatid segregation, mitotic nuclear division, and myeloid leukocyte migration in the E. coli infection model alone, which was clearly different from that in the CLP model in terms of GO function (Figure 3d). The analysis of significantly upregulated genes enriched for GO in the CLP and E. coli infection models alone is shown in Figure 3d. The common KEGG pathway was not enriched because of the small number of differentially expressed proteins upregulated in the two models together. KEGG pathway analysis revealed that genes significantly upregulated in the E. coli infection model alone were mainly involved in cytokine‒cytokine receptor interactions, lipid and atherosclerosis, the MAPK signalling pathway, the TNF signalling pathway, fluid shear stress and atherosclerosis, Kaposi sarcoma-associated herpesvirus infection, human cytomegalovirus infection, osteoclast differentiation, the cell cycle, and the chemokine signalling pathway. In the CLP model alone, the significantly upregulated genes were involved mainly in natural killer cell-mediated cytotoxicity, primary immunodeficiency, Th17 cell differentiation, biosynthesis of amino acids, apoptosis, biosynthesis of cofactors, Th1 and Th2 cell differentiation, and herpes simplex virus 1 infection. To further investigate the role of the two models in sepsis. We constructed a PPI network based on STRING of genes whose expression was jointly upregulated by the two models and screened the hub subclasses of the network using MCODE in Cytoscape (Figure 3f). Cfb, Fcnb, C3, Cfh, and C1qb were the highest-scoring hub subclasses screened and could serve as key targets for sepsis research.

Proteomic analysis of Escherichia coli-infected septic rats confirms dysregulation of their organic immune homeostasis

Differential protein screening and expression analysis

Through TMT peptide labelling and hierarchical LC‒MS/MS analysis, a total of 3547 proteins were identified. Using t tests and differential multiples, 341 differentially expressed proteins were identified between the model and control groups, of which 177 were upregulated, and 164 were downregulated. A volcano plot showing the number and expression of differentially expressed proteins between the two groups (Figure 4a). Figure 4. Proteomics of E. coli infection model. (a) is the volcano plot of differential analysis of control and Model groups; (b) is the heatmap of clustering of the top 50 differential proteins in control and Model groups; (c) is the GO functional analysis; (d) is the KEGG analysis; (e) is the network map analysis of the top 40 differential protein-enriched pathways in the top 15 enriched pathways associated with the development of sepsis and inflammation; (f) is the PPI network of kegg-enriched pathway-associated proteins.Proteins.The significance was calculated by t-test marked as *p < 0.5; **p < 0.01. The cut-off of dysregulated proteins has been set at -log10 (p value) <0.05 and log2(FC) >log2(1.2).

GO analysis of differentially expressed proteins

GO annotations of differentially expressed proteins were performed separately for the model and control groups. Biological processes (BP), cellular components (CC), and molecular functions (MF) are represented in different colours (Figure 4c). A total of 6896 GO functions were enriched between the model and control groups, and 1455 GO functions were significantly enriched. Among the significantly upregulated and downregulated GO functions, the top 10 enriched BP, CC, and MF terms were as follows: response to endoplasmic reticulum stress, protein stabilization, regulation of dendrite development, platelet activation, regulation of dendrite morphogenesis, organelle localization by membrane tethering, establishment of organelle localization, regulation of protein stability, cellular response to heat, and positive regulation of platelet activation. The main MFs included unfolded protein binding, protein C-terminus binding, nonmembrane spanning protein tyrosine kinase activity, SH domain binding, ATP hydrolysis activity, protease binding, transmembrane transporter binding, phospholipase binding, scaffold protein binding, and BH domain binding. The main cellular components included membrane raft, membrane microdomain, sarcoplasmic reticulum, ruffle, sarcoplasm, melanosome, pigment granule, ruffle membrane, lamellipodium, and dendrite terminus.

KEGG pathway enrichment analysis results

A total of 379 DEP enrichment pathways were determined through differential protein enrichment pathway analysis, 102 of which exhibited significant differences. Among the top 40 differentially expressed protein enrichment pathways, platelet activation, mismatch repair, the NOD-like receptor signalling pathway, apoptosis, dilated cardiomyopathy, the chemokine signalling pathway, lipid and atherosclerosis, platinum resistance, bacterial invasion of epithelial cells, proteoglycans in cancer, inflammatory mediator regulation of TRP channels, apoptosis-multiple species, the MAPK signalling pathway, the C-type lectin receptor signalling pathway, and leukocyte transendothelial migration were the 15 pathways related to sepsis development and inflammation (Figure 4d). A KEGG enrichment network map of these 15 pathways was constructed, and the platelet activation and MAPK signalling pathways had the strongest interactions (Figure 4e). In addition, PPI protein interaction network analysis of the proteins enriched in these pathways using the STRING database revealed that protein molecules with high scores, such as Src, Ptk2, Lyn, Casp3, and Itgb1, play important roles (Figure 4f).

Discussion

Sepsis is a global medical problem that can easily lead to multiple organ dysfunction and is one of the main causes of death in critically ill patients [14]. The pathogenesis and disease progression of sepsis are complex, and its diagnosis and treatment are still being actively explored because its pathophysiological mechanisms have not been fully elucidated. The current consensus on the pathogenesis of sepsis is that the inflammatory reaction is the starting point of sepsis, which can stimulate the complement and specific cell surface receptors of immune cells and endothelial cells in the body and then activate a large number of cytokines through multiple signalling pathways to participate in the inflammatory cascade. Furthermore, more inflammatory mediators are produced to participate in the systemic inflammatory response process and eventually cause organ function damage [1,15–17].

The effectiveness of animal models can be assessed from two perspectives: clinical phenotype and disease progression. The clinical phenotype is the foundation, and the symptoms exhibited by animal models should be similar to those of human disease. SPF rats that had no obvious infection or inflammation before the experiment were used in this model. Therefore, the relatively small within-group variance of the rats used to establish the model can directly reflect the fact that the infection of this model was not affected by other diseases or inflammation. The most common symptoms of clinical sepsis are fever, chills, dyspnoea, diarrhoea, and changes in mental status [18]. Similarly, the rat model established in this study showed symptoms such as lethargy, reduced food intake, poor mental state, slow movement, curling up, and piloerection, which could be used as similar symptoms to those of clinical sepsis. Therefore, the model rats established in this study had a high degree of similarity to the clinical symptoms of sepsis in terms of clinical manifestations.

Disease progression mainly focuses on the diagnosis and mechanistic investigation of clinical sepsis. At present, the main diagnostic criteria for sepsis include two indicators: a clear infection and severe organ dysfunction.

Blood culture is a reliable diagnostic method for detecting bacterial pathogens in sepsis [19]. By culturing blood samples in a culture dish and accelerating the growth rate of bacteria, it is possible to better determine the existence of bacteria and determine the species of bacteria in the blood, which is currently the “gold standard” for disease diagnosis at present [20]. In the model established in this study, researchers injected an Escherichia coli suspension into the bloodstream of rats via the tail vein. The injections were administered twice over two consecutive days. On the third day, blood samples were collected from the rats for culture. The culture results were positive, and the bacteria were identified as Escherichia coli, indicating the presence of bacteraemia. These findings provide direct evidence of the infection characteristics of the model.

Second, abnormalities in routine blood tests may also reflect the body’s immune response to infection. According to the results of this study, routine blood tests revealed that, compared with those of the control group, the PLT and PCT of all three models were significantly lower, and the MPV was increased. A significant reduction in both the PLT and PCT may reflect the body’s immune response to infection or inflammation. It is now well documented that during sepsis, platelets are activated and depleted in the circulatory system, leading to endothelial cell injury, promoting neutrophil extracellular traps and microthrombosis, and exacerbating septic coagulation and inflammatory responses [21]. This is a key factor contributing to the high mortality rate of sepsis patients [22]. In addition, the elevation of the mean platelet volume may be a compensatory response to the decrease in platelet count. Our model of sepsis resulting from single-strain injections maintains a high degree of consistency with the CLP model in terms of platelet abnormalities, suggesting the validity of the sepsis model developed in this study, which is also essential for assessing the extent of infection and inflammatory state of the model.

In addition, IL-1β, IL-6 and TNF-α are also key inflammatory markers that reflect the infection status of an organism. In the present study, the levels of inflammatory cytokines were measured and analysed in three models of sepsis, and comparisons revealed that TNF-α and IL-6 were significantly elevated in the E. coli tail-vein injection model group compared with the control group and the other two models. TNF-α is one of the earliest proinflammatory cytokines to be released [23], and can rapidly stimulate inflammatory responses and lead to vascular and organ damage [24]. The E. coli tail-vein injection model, on the other hand, consistently induces TNF-α release. These results demonstrate that this model can cause a state of persistent infection in the organism, which better fits the clinical sepsis characteristics. In addition, the persistence of IL-6 signifies the persistence and systemic nature of the inflammatory response [25,26]. This implies that a stronger cytokine storm exists in the organism of this model animal, which is more likely to cause multiple organ dysfunction syndrome (MODS). The abnormalities in inflammatory cytokine levels more strongly confirmed the presence of effective microbial infections in this model, further demonstrating the similarity between the inflammatory response of the model and the clinical sepsis state. In summary, the abnormal changes in these indicators help to evaluate the validity of the animal model of sepsis and provide a reliable platform for further research on the pathogenesis of sepsis.

The Sequential (Sepsis-related) Organ Failure Assessment (SOFA) score is a classic tool for assessing the severity of critical illness in patients [27]. In recent years, the SOFA score has been widely adopted to reflect organ dysfunction in patients, particularly in the context of sepsis and septic shock. The third international consensus definition (Sepsis 3.0) of sepsis and septic shock directly incorporates a SOFA score of ≥ 2 as one of the diagnostic criteria for sepsis [28]. The SOFA score involves multiple indicators, such as oxygenation, platelet count, bilirubin, and creatinine, and allows for relatively accurate assessment of organ function in the lungs, liver, heart, kidneys, and other organs [29]. In clinical disease, when an organ or system is dysfunctional, a variety of functional, metabolic, and morphological indicators can be used to study organ dysfunction failure in preclinical models. However, obtaining organ tissues is difficult in clinical practice, and it carries a high risk of injury to the body. Therefore, functional and metabolic indicators are commonly used instead. Nevertheless, histopathological changes remain the most visible signs of organ damage. In this study, HE staining of pathological tissues as well as the detection of biochemical indices were used to determine organ dysfunction. H&E staining revealed that the heart, liver, spleen, lungs and kidneys of the tail vein-injected E. coli model showed abnormal tissue structure and infiltration of inflammatory cells. In contrast, the heart and kidney of the LPS-treated and CLP-treated mice had no obvious abnormal pathological structures. In addition, changes in biochemical parameters provide an important basis for the clinical diagnosis and monitoring of relevant organ pathologies, so the biochemical indices of the model rats were also used in this study for the corroboration of organ dysfunction. According to the biochemical results, the tail vein-injected E. coli model was consistent with the CLP model in terms of markers representing cardiac and renal organ damage as well as hepatic bilirubin-related markers, but it differed from the CLP model in that the opposite trends were observed for ALB, ALP, and LDH. Alkaline phosphatase (ALP) is an endogenous detoxifying enzyme found in many cells and organs (e.g. intestine, placenta, liver, bone, kidney, and granulocytes) and has a detoxifying effect through endotoxin dephosphorylation [30]. In the model established in the present study, the fact that ALP was maintained at extremely low levels suggests that the body’s autoorgan detoxification is severely compromised, which would more than likely exacerbate organ dysfunction.

More importantly, our model also replicated several key features of sepsis pathogenesis. The MAPK pathway plays an important role in the inflammatory process in sepsis-induced heart and lung injury [31,32]. In addition, platelet activation during sepsis leads to endothelial cell damage, neutrophil extracellular trap formation, and microthrombosis, exacerbating the coagulation and inflammatory reactions during sepsis [33] and ultimately causing organ damage [34]. This research performed a proteomic analysis of WBC samples from healthy and septic rats and revealed numerous pathways related to sepsis, inflammation, and immune responses. This confirms the credibility of the symptoms of clinically septic patients simulated by this model. A KEGG enrichment network map of the top 40 enriched protein pathways related to sepsis development and inflammation was constructed, in which platelet activation and MAPK signalling had strong interactions in this model, contributing to microthrombi formation in small blood vessels. This phenomenon may be evidence of the pathological, self-stabilizing imbalance associated with septic shock [35].

From the above analysis, we can see that the tail vein injection of E. coli model has some similarities to CLP, the most commonly used sepsis model, in terms of routine blood parameters, inflammatory cytokines, and biochemical indices. On this basis, we analysed the transcriptomic data of leukocyte components in the peripheral blood of these two model animals. Eighty-two genes were jointly upregulated, and the highest-scoring hub gene subclasses included Cfb, Fcnb, C3, Cfh, and C1qb. Cfb, C3, and C1q, as part of the classical pathway of the complement system, promote the onset of inflammatory responses and accelerate pathogen clearance and immune system activation through activation of the classical pathway. Fcnb, in the presence of pathogens that invade the host immune system, is is able to recognize and bind to specific glycoproteins on the surface of the pathogen, further activating C1q (the first component) of the classical pathway, thereby assisting the host in defending against pathogens [36]. Cfh accelerates the decay of the complement bypass pathway (AP) C3 converting enzyme C3bBb, thereby preventing the local formation of more C3b [37]. In addition, Cfh interacts with CR3/ITGAM receptors, thereby mediating the adhesion of human neutrophils to different pathogens and consequently killing the pathogens [38]. Both models involve the complement activation pathway, and the complement system plays an important role in the pathogenesis and pathological process of sepsis. Both models are better choices for use if we subsequently study the mechanisms related to the complement system in sepsis. In contrast to the CLP model, the tail-vein-injected E. coli model was significantly enriched for genes related to biological processes such as mitosis, nuclear division, and sister chromatid segregation according to the GO analysis, which is an active response of the organism to cope with infections and to repair damage. Sepsis is a systemic inflammatory response, and enhanced cell proliferation and division are adaptive responses by the organism to cope with this extreme stress, demonstrating that severe tissue and organ damage may occur in such models. This finding is consistent with the results of HE staining of pathological tissues, and the model established in this study caused more severe organ damage than did the LPS and CLP models. The novel sepsis model developed in this study may be preferred for future research into the mechanisms of multiorgan failure and the effectiveness of various organ protection and regeneration techniques, including stem cell therapy, tissue engineering techniques and other innovative medical tools.

In summary, using bioinformatics methods for subsequent analysis, multiple signalling pathways related to sepsis were systematically and comprehensively screened, which promoted the understanding of the potential pathogenesis and molecular mechanisms of sepsis and provided potential biomarkers and therapeutic targets for the diagnosis and treatment of sepsis.

This study showed that tail vein injection of live pure E. coli strains simplifies the research background of sepsis and can achieve sustained infection, causing severe organ damage, which is closely related to the pathogenesis of sepsis caused by infection-induced inflammation and is beneficial to the study of sepsis pathology, physiology, and pharmacological evaluation. However, this study did not include a haemodynamic index analysis, which may differ from clinical reality. Nevertheless, we hope that the model established in this study can serve as a reference for the establishment of sepsis animal models and will continue to be improved and improved upon.

Conclusion

In conclusion, in this study, we established a standardized and ideal animal model of sepsis by injecting rats with Escherichia coli through the tail vein. To prove the feasibility of this model, we observed that the clinical symptoms of the model rats established in this study were highly similar to those of clinical sepsis patients. In addition, blood bacterial cultures revealed bacterial infection in the rats. Histological observations revealed that this model could cause multiorgan damage and characteristic manifestations of sepsis in rats. Finally, from the proteomic data, platelet activation and MAPK signalling pathways associated with sepsis development and inflammation were found to be activated and to have the strongest interaction. These findings can improve our understanding of the potential pathogenesis and molecular mechanisms of sepsis and provide potential biomarkers and treatment targets for the diagnosis and treatment of sepsis.

Supplementary Material

Figure S2300.jpg

Author Checklist E10 only.pdf

supplement.docx

Figure S1300.jpg

Disclosure statement

No potential conflict of interest was reported by the authors.

Author contributions statement

Xuanwen Ru:Formal Analysis, Methodology,Visualization,Writing – Original Draft Preparation

Simiao Chen: Investigation, Methodology, Writing – Review & Editing

Danlei Chen: Investigation

Qingyi Shao: Visualization

Wenxia Shao: Writing – Review & Editing, Supervision

Qing Ye: Writing – Review & Editing, Supervision, Project Administration, Resources

All authors have read and approved the final version of the manuscript.

Data availability statement

The authors confirm that data supporting the results of this study are available in the article or via the advisory link: Transcriptomic data for CLP animal models: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE227162

Transcriptomic data for Caudal vein E. coli animal models: https://www.ncbi.nlm.nih.gov/sra/?term=PRJNA1121656

Proteomic data for Caudal vein E. coli animal models:

https://proteomecentral.proteomexchange.org/cgi/GetDataset?ID=PXD053096

Ethics approval

We followed the ARRIVE guidelines. This study has been approved by the Zhejiang Eyong Pharmaceutical Research and Development Center, and is conducted in accordance with relevant laws, regulations and ethical guidelines. The approval number is ZJEY-20230420-04.

Euthanasia guidelines

When the experimental rats lost 20% of their weight before the experiment or lost their ability to move: were unable to eat or drink, were on the verge of death or unable to move, or had no response to gentle stimulation, they were euthanized. The rats were placed in IVC cages, and a CO2 tube was connected to the entrance of the water bottle. The CO2 cylinder valve was opened, and CO2 was injected into the box at a rate of 10%-30% of the euthanasia chamber volume per minute to fill the cage with CO2. After confirming that the rat was motionless, not breathing, and had dilated pupils, the CO2 was turned off and the animal was observed for two more minutes to confirm death.

Video recordings of the state of three sepsis rat models at different time points: https://figshare.com/articles/media/supplement_Animal_state_iMovieMobile/26353159

Blood routine test and clinical biochemical index test results of three kinds of sepsis rat models at 24 h: https://figshare.com/articles/figure/_/26353336

Supplementary Material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/21505594.2024.2395835
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