Pim1 induces M1 polarization of peritoneal macrophage and aggravates sepsis by upregulating glycolysis

doi:10.21203/rs.3.rs-4935468/v1

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Pim1 induces M1 polarization of peritoneal macrophage and aggravates sepsis by upregulating glycolysis

https://doi.org/10.21203/rs.3.rs-4935468/v1

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Peritoneal macrophages play a crucial role in sepsis and the resulting organ damage. However, the precise mechanism through which peritoneal macrophages contribute to sepsis remains incompletely understood. The scRNA-seq and RNA-seq have revealed that the septic environment can enhance glycolysis and promote M1 polarization in peritoneal macrophages. Pim1 is a key player in this process. Inhibiting Pim1 expression effectively mitigates glycolysis in macrophages and reduces M1 polarization. As a transcription factor, C-Myc interacts with Pim1, regulating its protein expression and phosphorylation levels. Chromatin immunoprecipitation (ChIP) experiments have confirmed that C-Myc binds to the promoter region of crucial glycolytic genes, enhancing gene transcription and glycolysis. Administration of a Pim1 inhibitor in CLP mice can alleviate glycolysis and M1 polarization in peritoneal macrophages, thereby effectively reducing lung injury. We identified that sepsis-induced Pim1 promotes the transcription of glycolytic genes and M1 polarization in macrophages by modulating c-Myc phosphorylation levels, exacerbating sepsis-related lung injury. This study provided novel insights into M1 polarization of peritoneal macrophage during the infection and revealed potential molecular and metabolic targets for the regulation of sepsis.

Sepsis

Peritoneal Macrophage

Glycolysis

Pim1

c-Myc

Sepsis is a severe systemic inflammatory syndrome with a mortality rate of up to 40%[1]. Intestinal injury serves as the trigger for multiple organ dysfunction syndrome, which can lead to damage in vital organs like the liver and lungs, consequently increasing the morbidity and mortality associated with sepsis [2, 3]. Macrophages are believed to play a crucial role in the advancement of sepsis by releasing proteases and pro-inflammatory cytokines to drive the inflammatory response [4]. Among these, peritoneal macrophages are particularly significant in the progression of sepsis. In patients with sepsis, peritoneal macrophages are often polarized towards the M1 phenotype, releasing high levels of pro-inflammatory cytokines that worsen the disease process [5, 6]. Therefore, investigating the specific mechanism of M1 polarization in peritoneal macrophages in sepsis patients could be a key target for clinical treatment and prevention of sepsis.

Emerging evidence suggests that alterations in cellular metabolism are vital for supporting M1 polarization in macrophages [7]. In M1 macrophages, there is a significant increase in the glycolytic pathway to aid in combating infections and producing inflammatory mediators[8]. Blocking the glycolytic pathway with 2-DG treatment has been shown to significantly hinder the differentiation of proinflammatory macrophages following LPS and IFN-γ stimulation [9]. These findings highlight the importance of cellular metabolism in macrophage M1 polarization, indicating that targeting these metabolic pathways could be an effective strategy for modulating macrophage polarization and the inflammatory response.

Pim1 is a well-known serine/threonine kinase involved in various cellular processes such as proliferation, differentiation, and apoptosis[10]. While initially identified as a proto-oncogene in hematological tumors, Pim1 kinase has also been implicated in inflammation-related signal transduction pathways[11]. Inhibiting Pim1 can regulate p65 phosphorylation levels and reduce the release of macrophage inflammatory cytokines, thereby alleviating LPS-induced sepsis-related lung injury[12]. The interaction between Pim1 and different proteins and signaling pathways positions it as a potential anti-inflammatory target. Studies have indicated that Pim1 influences cancer cell invasion and migration by modulating the glycolytic process in colorectal cancer cells[13], and the Pim1 inhibitor can effectively suppress glycolysis and protect cellular function[14]. These findings suggest that Pim1 may play a crucial role in cellular metabolic reprogramming. Further investigation is warranted to determine if Pim1 is involved in regulating peritoneal macrophage metabolic reprogramming and subsequently influencing macrophage polarization towards the M1 phenotype.

c-Myc functions as a transcription factor that regulates numerous cellular physiological and metabolic processes[15], with a primary role in promoting glycolysis[16]. E-box is a DNA sequence typically found upstream of a gene's promoter region, where c-Myc binds to regulate gene transcription[17, 18]. By binding to the E-box region, c-Myc stimulates the transcription of glycolytic genes like Glut1, Hk2, Pkm2, Eno1, and Ldha[19]. Previous studies have shown that Pim1 can impact the glycolytic process in tumor cells by regulating c-Myc transcription[20]. Therefore, this study aims to confirm that Pim1 influences peritoneal macrophage glycolysis and facilitates M1 polarization by regulating c-Myc transcription and phosphorylation activation, thereby contributing to the progression of sepsis.

1. The glycolysis of peritoneal macrophages in septic mice is enhanced.

We utilized the GSE249975 dataset to perform clustering analysis on the scRNA-seq results of peritoneal lavage fluid (Fig. 1A, left). Five major immune cell populations were identified (Fig. 1A, right). Deeply, the cells were primarily categorized into neutrophils (Cxcl2, Ccl3, Cstdc4), macrophages (Pt4, Alox15, Lyz2), B cells (Igkc, Ighm, Cd79a), lymphocytes (Ms4a4b, Ccl5, Cma1), and dendritic cells (Ccr7, Satb1, Ncl) (Fig. 1B). Given the significant role of peritoneal macrophages in sepsis, we extracted the macrophage subpopulation for further analysis. By comparing the CLP group with the control group, we identified 2706 differentially expressed genes (Fig. 1C). Subsequent GSEA analysis revealed the activation of the innate immune system, glycolysis, and glucose metabolism pathways in peritoneal macrophages of the CLP mice (Fig. 1D).

2. Pim1 was upregulated in the peritoneal macrophage with the LPS treatment

Next, using the GSE234930 dataset, we analyzed the RNA-seq results of peritoneal macrophages treated with LPS. Setting the criteria at logFC ≥ 2 and p < 0.05, we identified 1765 differentially expressed genes (Fig. 2A). By intersecting these genes with the top 100 differentially expressed genes from the scRNA-seq data, we narrowed down to 32 representative genes (Fig. 2B). The KEGG analysis of these genes revealed enrichment in signaling pathways such as cytokine-cytokine receptor interaction, Jak-STAT, MAPK, NF-κB, TNF, NOD-like receptor, and Toll-like receptor signaling pathways (Fig. 2C). Moreover, There was an upregulation of M1 polarization markers (Il1b, Nos2, Il6, Trl2, Cd86), and an increase in the expression of essential genes involved in glycolysis (Hk2, Pfkp, Dld, Minpp1) in LPS-treated peritoneal macrophages (Fig. 2D, E). Notably, Pim1 is one of the 32 representative genes, and its expression was elevated following LPS treatment (Fig. 2F). Furthermore, immune infiltration analysis indicated a close association between high expression of Pim1 in peritoneal macrophages and T cell follicular helper and mast cell activation (Fig. 2G), all of these results suggested that Pim1 could play a crucial role in driving the M1 polarization of peritoneal macrophages and inducing glycolysis in sepsis.

3. Knockout of Pim1 alleviated inflammation and inhibited glycolysis

To further investigate the role of Pim1 in macrophage, we analyzed the dataset GSE195582 of bone marrow-derived macrophage (BMDM) with Pim1 knockout. Under the LPS-treated condition, setting the criteria at logFC\(\:\ge\:\)1.5 and p-value<0.01, the knockout of Pim1 resulted in changes in the expression of 318 genes (Fig. 3A). GO enrichment analysis was conducted on the differential expressed genes. In terms of Biological Processes (BP), the results showed that the knockout of Pim1 upregulated positive regulation of the mitotic cell cycle and positive regulation of chromosome separation while inhibiting the ERK1 and ERK2 cascade, leukocyte chemotaxis, and monocyte chemotaxis. For Cellular Components (CC), the knockout of Pim1 upregulated microtubule-associated complex and protein-DNA complex, while inhibiting the expression of plasma lipoprotein particle, lipoprotein particle, and protein-lipid complex. In Molecular Function (MF), the knockout of Pim1 upregulated single-stranded DNA binding and microtubule binding, while inhibiting the expression of cytokine activity and chemokine activity (Fig. 3B). Furthermore, the KEGG enrichment analysis results indicated that the knockout of Pim1 affected the signaling transduction of numerous pathways, such as the TNF, PPAR, p53, HIF-1, and FoxO signaling pathways. It also directly regulated the metabolism of steroid, pyrimidine, amino acid, glutathione, and cholesterol (Fig. 3C). Most importantly, we observed that the knockout of Pim1 led to the inhibition of LPS-induced glycolysis in macrophages, with a significant downregulation in the expression of glycolysis-related genes Pfkl, Pgm2, Hk2, Acss2, and Aldh2 (Fig. 3D). Consequently, this resulted in a decrease in the M1 polarization of macrophages, accompanied by reduced expression of Il1a, Il1b, Nos2, Cd86, and Cxcl9 (Fig. 3E).

4. Pim1 regulated RAW264.7 glycolysis under LPS treatment

Given the critical role of Pim1 in regulating glycolysis, we used sh-RNA to knock down Pim1 expression in LPS-treated RAW264.7 cells (Fig. 4A, B). The results showed that the shPim1 could inhibit LPS-induced glycolysis in macrophages, leading to reduced glucose uptake (Fig. 4C), and decreased lactate production within the cells (Fig. 4D). Furthermore, in macrophages with Pim1 knocked out, the mRNA expression levels of glycolysis-related genes were also downregulated (Figure E). Flow cytometry analysis also revealed that the M1 polarization response of LPS-induced macrophages was also suppressed by the knockout of Pim1 (Fig. 4F).

5. c-Myc was regulated by Pim1 and affected M1 macrophage polarization

To uncover the potential regulatory mechanism by which Pim1 modulates macrophage polarization, bioinformatics was employed to predict the proteins that interact with Pim1 in the present study. Many proteins that interacted with pim1 were exhibited in Fig. 5A (https://cn.string-db.org), such as Myc, Il6, Socs1, Edc3 and so on. As an important transcription factor regulating glycolysis, expression of Myc increased in peritoneal macrophages treated with LPS and was regulated by Pim1 (Fig. 5B). The Co-IP experiment indicated that Pim1 had a relationship with c-Myc in the macrophages (Fig. 5C). As the most widely functional subtype[21], we further investigated the role of c-Myc. Western blot results showed that LPS could induce an increase in c-Myc expression and phosphorylation levels, which could be reversed by knocking out Pim1 (Fig. 5D). qPCR results also demonstrated a significant downregulation of c-Myc mRNA level after Pim1 knockout (Fig. 5E). Subsequently, we used si-RNA to inhibit c-Myc expression in RAW264.7 cells (Fig. 5F, G), and the results showed that inhibiting C-Myc expression also led to significant suppression of cellular glycolysis, resulting in reduced glucose uptake and lactate production (Fig. 5H, I). Similarly, the expression of glycolysis-related genes was decreased (Fig. 5J); and the trend of M1 polarization in macrophages was weakened either (Fig. 5K).

6. c-Myc affected the transcriptional efficiency of glycolysis-related genes

Supplement experiments confirmed that overexpression of Pim1 can upregulate c-Myc expression (Fig. 6A, B). The increase in glycolysis caused by overexpression of Pim1 can be reversed by si-c-Myc (Fig. 6C, D), accompanied by changes in glycolysis-related genes and the trend of M1 polarization in macrophages (Fig. 6E, F). We predicted the possible binding site of C-Myc in the promoter region of the target genes (Fig. 6G). Further validation using ChIP assay confirmed that LPS could promote the binding of c-Myc to the promoter region of glycolysis-related genes, while sh-Pim1 inhibited the efficiency of the binding to the gene promoter regions (Fig. 6H).

7. Pharmacological inhibition of Pim1 suppressed the function of peritoneal macrophage in sepsis

Given the regulatory role of Pim1 in peritoneal macrophage in sepsis, we established a mouse model of CLP and used the Pim1 inhibitor SMI-4a. The survival curve of mice showed that inhibition of Pim1 could effectively prolong the survival time of mice (Fig. 7A), and the Tnf-α and Il6 in intraperitoneal lavage fluid were reduced (Figure B, C). The M1 polarization in peritoneal macrophage was decreased either (Fig. 7D). In addition, under the condition of Pim1 inhibitor, the lung injury of CLP mice was improved obviously (Fig. 7E).

Despite significant efforts in the treatment of sepsis, the mortality rate of severe sepsis remains high. Therefore, it is still of paramount importance to investigate the underlying mechanisms of sepsis and discover new therapeutic approaches[22]. Under physiological conditions, the peritoneal cavity with about 50-100mL of buffered serous fluid contains many macrophages, which initiate an immune response in the peritoneal cavity[23]. Once the integrity of the digestive tract is disrupted, the invading pathogenic microorganism is first recognized by macrophages and then initiates an inflammatory immune response[24]. Therefore, effective infection control and prevention of the multiplication and spread of pathogenic bacteria is the key to blocking the progression of abdominal infection to sepsis, and peritoneal macrophage plays an important role in this process.

Studies have shown that macrophage activation during sepsis causes metabolic reprogramming, increased cellular glucose uptake, and metabolic transitions from oxidative phosphorylation to glycolysis, contributing to sepsis-related inflammation and injury [25]. The LPS-induced inflammatory response can increase lactate production by upregulating the expression of glycolysis-related genes such as Glut1, Ldha, and Pdk1 in M1 macrophages, thereby promoting the release of Hmgb1 and IL-1β, and accelerating the process of inflammatory response [26]. We also confirmed that the initial immunity of peritoneal macrophages in sepsis mice was activated by single-cell sequencing results from the analysis of peritoneal lavage fluid, accompanied by increased glucose metabolism and upregulation of glycolysis. We analyzed the RNA-seq results of LPS-stimulated peritoneal macrophages, and the results also showed that LPS-stimulated increased M1 polarization in peritoneal macrophages was accompanied by upregulation of the expression of glycolytic genes.

To further explore the specific mechanism of glycolysis in peritoneal macrophages, we combined the sequencing results and obtained 32 representative differential genes, among which Pim1 was up-regulated in LPS-treated peritoneal macrophages and was closely related to the JAK-STAT signaling pathway [27]. Pim1 is a constitutively active serine-threonine kinase, which can participate in the regulation of cell cycle progression, affect cell proliferation, migration, and apoptosis, and participate in the regulation of the occurrence of cellular glycolysis through phosphorylation modification[13, 28]. The activation of Pim1 kinase is regulated by JAK/STAT and NF-κB pathways [29]. Research has shown that Pim1 can regulate the occurrence of autophagy through the Pim1/P21/mTOR signaling axis [30]. Pim1 is also involved in the regulation of inflammation, and Ratana et al. found that Pim1 can regulate inflammation by phosphorylating the RELA component of nuclear factor NF-κB at the Ser276 site[31]. It has also been confirmed that Pim1 can activate the NLRP3 inflammasome, and Pim1 inhibitor AZD1208 can effectively reduce the activity of NLRP3 and alleviate the inflammatory response [32]. Therefore, we further analyzed the BMDMs with Pim1-specific knockout. After being processed by LPS, the results showed that the knockout of Pim1 upregulated positive regulation of the mitotic cell cycle, positive regulation of chromosome separation, microtubule-associated complex, protein-DNA complex, single-stranded DNA binding, and microtubule binding, while inhibiting the ERK1 and ERK2 cascade, leukocyte chemotaxis, and monocyte chemotaxis, plasma lipoprotein particle, cytokine activity and chemokine activity. Similarly, after Pim1 knockout, macrophage M1 polarization was significantly inhibited, and the expression of M1 polarization markers IL-1α, IL-1β, Nos2, Cd86, and Cxcl9 was reduced, accompanied by the expression of key glycolytic genes Pfkl, Pgm2, Hk2, Acss2, and Aldh2. In RAW264.7 cells, LPS can induce M1 polarization, accompanied by increased glucose uptake, increased lactate and ATP production, and up-regulation of the expression of key glycolysis genes Hk2, Pfkfb3, and Pkm2; while Knocking out Pim1 can reverse the above trends.

It is well known that Pim1 is closely related to the functional role of c-Myc [33]。 Jongchan Kim et al. reported that Pim1 promotes carcinogenesis in part by enhancing c-Myc transcriptional activity in tumor cells[34]. Our results also showed that in LPS-stimulated macrophages, c-Myc could bind to Pim1 interacting, and its expression level was increased and regulated by Pim1 in LPS-stimulated macrophages. Previous studies have confirmed that c-Myc-mediated glycolysis is the key for macrophages to regulate pro-inflammatory responses, and can regulate the expression of many key glycolytic genes, including Ldha, Hk2, and Pfkfb3 [35–38]. Our results also confirmed that c-Myc can directly regulate the expression of key genes of macrophage glycolysis and control the trend of M1 polarization. After using si-RNA to remove the expression of c-Myc, even overexpression of Pim1 could still inhibit the occurrence of RAW264.7 glycolysis and M1 polarization. Subsequent ChIP experiments further confirmed that C-Myc was a transcription factor in LPS-stimulated RAW264.7 and could be enriched in the promoter region of key glycolytic genes Hk2, Pfkfb3, and Pkm2. Knockdown of Pim1 can inhibit the level of phosphorylation modification of c-Myc, and the binding of c-Myc to the promoter of glycolysis-related genes is also reduced, which may be the key mechanism for Pim1 and c-Myc to participate in the regulation of glycolysis in macrophages.

Finally, we tested whether this regulatory mechanism has therapeutic value in sepsis. Studies have confirmed that inhibition of Pim1 can also have a protective effect on LPS-induced acute lung injury by regulating the ELK3-ICAM1 axis [39]. Consistent with expectations, the use of the Pim1-specific inhibitor SMI-4a could reduce mortality of sepsis mice, with reduced levels of inflammatory cytokines Tnf-α and Il-6 in mouse intraperitoneal lavage fluids, and inhibition of mouse peritoneal macrophage M1 polarization. In addition, the results of HE and Masson showed that use of the Pim1-specific inhibitor could improve the histopathological changes in the lungs of septic mice and reduce the severity of pulmonary edema in sepsis mice.

However, this study still leaves many things to be desired. First, RAW264.7 cells were used, and this result needed to be revalidated using different cell lines or primary cells. Second, how Pim1 regulates the phosphorylation modification of c-Myc deserves further study.

Cell culture

RAW264.7 cells were purchased from Procell (Wuhan, China) and cultured in Dulbecco’s Modified Eagle Medium (DMEM) (Cytiva, USA) supplemented with 10% fetal bovine serum (Cytiva, USA), 100 U/ml streptomycin sulfate, and 100 mg/ml penicillin. Cells were grown in a humidified incubator with 5% CO₂ at 37°C. The culture medium was replenished daily.

Mouse model

The animal study was approved by the Medical Ethics Committee of Shanghai Medical College of Fudan University and comply with the ARRIVE guidelines. Male C57BL/6 mice were purchased at seven weeks of age from Shanghai Laboratory Animal Center Co., Ltd. (SLAC) (Shanghai, China). Mice were caged separately under standard lab conditions (12:12 light/dark cycle, 22°C, 60% humidity) with access to food and tap water, and were adapted to these conditions for one week prior to experimentation. The Sepsis mice model was established by the cecal ligation and puncture as described [40]. Mice from the control group underwent the same experimental procedures without ligation or puncture. Mice were given oral gavage of Pim1 inhibitor SMI-4a (50mg/kg, Sigma-Aldrich Corporation, USA). In the end, mice were euthanized using 150 mg/kg pentobarbital sodium intraperitoneal injection.

ScRNA-Seq, Data Pre-Processing and Cell Type Annotation

Microarray datasets were screened and downloaded from gene expression omnibus (GEO). The GSE249975 data was analyzed with the principal components analysis (PCA) and clustered at a proper resolution. Harmony embeddings were used as the input for t-distributed stochastic neighbor embedding (t-SNE), which allows data visualization in a two-dimensional space. Cell-type annotation was conducted with the manually curated cell type markers and 14 clusters were merged into 6 cell types. The differential expression levels of genes were calculated using the FindMarkers, which is based on the Wilcoxon ranking and test with default parameters. Gene set enrichment analysis (GSEA), was conducted to get more essential biological functions or pathways that may be ignored by differential analysis, based on all genes and phenotypes.

RNA-seq analysis

The GSE234930 and GSE195582 series were extracted from GEO for analysis. The differentially expressed genes (DEGs) were screened through R (“limma” package). ClusterProfiler package was applied for DEG to get functional annotations and interpretations, and P < 0.05 was set as the cut-off value. GeneOntology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed on DEGs. The P-value was adjusted with the Benjamini–Hochberg (BH) procedure.

Reverse transcription PCR analysis

RAW264.7 cells were treated with TRIzol reagent (Thermo Fisher, USA) to extract total RNA. Total RNA isolated from cells was subjected to reverse transcription using a PrimeScript RT Master Mix Kit (TaKaRa, Japan). Relative quantification was performed using 2xSYBR Green qPCR Master Mix (Bimake, China). Quantitative real-time PCR was used to determine the levels of mRNA expression using a Bio-Rad iCycler system (Bio-Rad, USA). The qPCR primer sequences used in this study are listed in Supplementary Table 1.

Western blot analysis

Tissues and cell lysates were extracted using RIPA lysis buffer, and the protein concentration was determined following the manufacturer’s instructions. On a 10% SDS-PAGE gel, equivalent quantities of protein were separated and deposited onto PVDF membranes using conventional methods. The membranes were blocked in 5% skim milk in TBST buffer for 1.5 hours at room temperature. Due to the close size of proteins, the membranes were cut and incubated overnight at 4°C with relevant primary antibodies. The following is a list of primary antibodies used for immunoblotting: Actin (ProteinTech, 66009-1-Ig, 1/5000), Pim1 (CST, #3247, 1/2000), c-Myc (CST, #5605, 1/2000), P-c-Myc (CST, #13748, 1/2000). Following two hours of room temperature incubation with a secondary antibody, proteins were identified using the ECL reagent.

Co-IP assay

Lysates of 1x10⁷ cells were immunoprecipitated with IP buffer containing IP antibody-coupled agarose beads, and protein-protein complexes were later subjected to Western blot. Here, IgG was used as a negative control.

Chromatin Immunoprecipitation (ChIP) assay

ChIP was performed using the ChIP assay kit (Millipore, USA) according to the manufacturer’s instructions. DNA and protein crosslinking was achieved by incubating the cells for 20 min at 37°C in the 1% formaldehyde solution. After sonication, chromatin was immunoprecipitated overnight with 6 µg of anti-c-Myc antibody, or 2 µg of a normal IgG antibody (CST, USA). The genomic regions containing the c-Myc binding sites were amplified by RT-PCR in 20 µL volumes for 30–35 cycles to determine the appropriate conditions for the PCR products of each region. Primer sequences were described in Supplementary Table 2.

Glucose uptake, lactate, and ATP production

The RAW 264.7 cells were cultured in a 96-well plate and subjected to analysis using a glucose uptake assay kit and an L-lactate assay kit (Dojindo, Japan) based on the manufacturer’s instructions. The assays were performed using colorimetric methods. To conduct the ATP assay, the cells that were cultivated in 6-well plates underwent lysis in 200 µL/well lysis buffer while being kept on ice and were subsequently centrifuged at 4°C. The quantification of ATP in the supernatant was conducted by utilizing an improved ATP assay kit (Dojindo, Japan) following the prescribed protocol. The cellular content was standardized based on the number of cells.

Flow cytometry

To determine the polarization of macrophage, stimulated RAW264.7 cells were collected, washed, and directly stained with anti-F4/80 and anti-CD86(Biolegend, USA) respectively, for 15 min and analyzed by a flow cytometry analyzer. Data analysis was carried out using CytExpert (Beckman, USA).

Statistical analysis

Continuous variables were presented as mean ± standard deviation (SD) and the sample sizes (n) for each analysis were reported within the figure legends. One-way analysis of variance (ANOVA) was used to examine the statistical differences among multiple groups, while Student’s (two-tailed) t-test was used for comparisons between two groups by Graph-Pad Prism 8.0 software unless otherwise mentioned. P value was considered statistically significant when * P < 0.05;** P < 0.01;*** P < 0.001; **** P < 0.0001.

Acknowledgements

Not applicable.

Author contributions

Xue Shang: Performing experiments, Visualization; Formal analysis; Fan Yang: Writing-original draft; Yi Liu, Huihui Wang: Validation; Yun Zhu: Resources, Supervision; Zhirong Sun: Conceptualization, Funding acquisition, Writing - review & editing; Project administration.

Funding

This study was supported by Clinical research plan of SHDC (No.SHDC2020CR1005A).

Data availability

The data used to support the findings of this study are available from gene expression omnibus (GEO), the GEO data numbers are GSE249975, GSE234930 and GSE195582.

Ethics approval and consent to participate

The animal study was approved by the Medical Ethics Committee of Shanghai Medical College of Fudan University and comply with the ARRIVE guidelines.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

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Pim1 induces M1 polarization of peritoneal macrophage and aggravates sepsis by upregulating glycolysis

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Abstract

Figures

Background

Results

2. Pim1 was upregulated in the peritoneal macrophage with the LPS treatment

3. Knockout of Pim1 alleviated inflammation and inhibited glycolysis

4. Pim1 regulated RAW264.7 glycolysis under LPS treatment

5. c-Myc was regulated by Pim1 and affected M1 macrophage polarization

6. c-Myc affected the transcriptional efficiency of glycolysis-related genes

7. Pharmacological inhibition of Pim1 suppressed the function of peritoneal macrophage in sepsis

Discussion

Materials and methods

Cell culture

Mouse model

ScRNA-Seq, Data Pre-Processing and Cell Type Annotation

RNA-seq analysis

Reverse transcription PCR analysis

Western blot analysis

Co-IP assay

Chromatin Immunoprecipitation (ChIP) assay

Glucose uptake, lactate, and ATP production

Flow cytometry

Statistical analysis

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1