Epigallocatechin gallate (EGCG) inhibits lipopolysaccharide‐induced inflammation in RAW 264.7 macrophage cells via modulating nuclear factor kappa‐light‐chain enhancer of activated B cells (NF‐κB) signaling pathway

Abstract Epigallocatechin‐3‐gallate (EGCG) is a major bioactive compound in tea polyphenol extract. After ingestion, EGCG reaches the intestine and may commence anti‐inflammation in the intestinal organ. Thus, in this paper, the anti‐inflammatory effect of EGCG was studied using lipopolysaccharide (LPS)‐induced inflammation in RAW 264.7 cells. LPS induction instigated morphological deformation extensively which was normalized by EGCG. In LPS‐induced macrophage cells, EGCG was found to lower cellular nitric oxide (32% of LPS group) and intercellular ROS level (45.4% of LPS group). It also suppressed the expression of IL‐1β (LPS 132.6 ± 14.6, EGCG 10.67 ± 3.65), IL‐6 (LPS 2994.44 ± 178.5, EGCG 408.33 ± 52.34), TNF‐α (LPS 27.11 ± 2.84, EGCG 1.22 ± 0.03), and iNOS (LPS 40.45 ± 11.17, EGCG 10.24 ± 0.89). The GO function analysis identified that these differential genes involved 24 biological processes, 18 molecular functions, and 19 cellular component‐related processes. KEGG pathway enrichment analysis revealed that LPS significantly affects NF‐κB, TNF, and TLR signaling pathways. Western blotting revealed that EGCG diminished P‐IκB/IκB ratio by 75% and p‐p65/p65 by 50% compared to the LPS group. Finally, Arg‐1 and CD‐206 mRNA expression were determined by RT‐PCR, which was consistent with the RNA‐Seq result. These findings indicate that EGCG exerts an anti‐inflammatory effect by reducing NO and ROS production, suppressing TLR4 protein expression, and inhibiting IκB and p65 phosphorylation.


| INTRODUC TI ON
Inflammation, which is the first line of defense of our body against pathogens, irritation, and injury, is a sophisticated response regulated by cytokines and chemokines. Various immune cells including monocytes, neutrophils, and macrophages are acquired by our innate immune system to address the inflammation (Novilla et al., 2017;Oyungerel et al., 2013). Macrophage cells play a vital role in inflammation modulation, as they are the first responders to inflammation.
Exposure to cytokines, chemokines, or bacterial lipopolysaccharide (LPS) leads to macrophage cell activation. Phagocytic activity of macrophage cells increases many folds during inflammation and activated macrophage cells fight pathogens directly. Macrophage cells indirectly maneuver inflammation by secreting proinflammatory cytokines (IL-1β, TNFα, IL-6) and inflammatory mediators (NO, iNOS) (Arango Duque & Descoteaux, 2014). Unregulated secretion of cytokines and inflammatory mediators results in damage on both cellular and tissue levels. Cellular damage ends up in apoptosis and necrosis while tissue damage includes the development of many chronic diseases, viz., rheumatoid arthritis, chronic hepatitis, diabetes, pulmonary fibrosis, and cancer (Kim et al., 2016;Laveti et al., 2013;Liu et al., 2017;Tsai et al., 2018).
Nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) is one of the most important transcription factors that regulate inflammatory response along with other physiological processes (Hossen et al., , 2021Schulert & Grom, 2015). As long as an inhibitor of κBs (IκBs) is not phosphorylated, NF-κB remains inactive in the cytoplasm. Phosphorylation of IκB leads to NF-κB nuclear translocation and ends up in transactivation of downstream genes (Baker et al., 2011;Siebenlist et al., 2005). Activated downstream target genes direct the cells to produce inflammatory cytokines and mediators including NO, TNFα, and IL-6. They also direct the recruitment of innate immune cells to combat inflammation (Lawrence, 2009;Schneider et al., 2014). These make NF-κB an ideal candidate to study anti-inflammatory chemicals and substances.
Green tea is very popular in East Asia mainly in China, Japan and gaining popularity around the world (Chacko et al., 2010).
Previous studies have shown that the consumption of green tea may reduce risks associated with cardiovascular disease and exert numerous health benefits (Wang et al., 2011). Around 30% dry weight of green tea are polyphenols and among them, flavonoids are most important; 80%-90% of the flavonoids are catechins and epigallocatechin-3-gallate (EGCG), which cover 59% of the total catechins present (Jigisha et al., 2012;Reygaert, 2017;Roowi et al., 2010). EGCG has low bioavailability (0.1%) but its content in the intestine is very high. The bioavailability of EGCG is proportional to immune system upregulation and improvement of health.
The more EGCG reaches the target site, the better it is for the body (Xu et al., 2015). Lambert et al. (2003) intragastrically fed male CF-1 mice 163.8 μmol/kg EGCG and the levels in the small intestine and colon were 45.2 ± 13.5 and 7.86 ± 2.4 nmol/g, re- spectively. Accumulating studies have demonstrated that EGCG possesses numerous health benefits, including anti-inflammatory, antioxidant, anticancer, and antitumor properties. EGCG lowers the pro-inflammatory cytokine and chemokine expression; also suppresses MAPK, STAT, TLR4, and NF-κB signaling pathway (Almatroodi et al., 2020;Cao et al., 2019;Chu et al., 2017;Yahfoufi et al., 2018). Therefore, this study intends to check the effect of EGCG on suppressing body inflammation and the possible mechanisms involved. This is for the first time the effects of EGCG from morphological impact to the biochemical changes, gene expression level, and protein expression changes are combined in one single manuscript. We attempted to compare the effects of EGCG and dexamethasone (DEX) on inflammation in terms of cell phagocytic capacity and the inhibitory effects on IL-1β, IL-6, TNFα, and iNOS pro-inflammatory factors effect. We also observed the cell morphology using an inverted microscope, measured physiological indicators such as NO and ROS, and used reverse transcription PCR (RT-PCR) to determine the level of inflammatory factors to evaluate the anti-inflammatory effect of EGCG. Additionally, transcriptome sequencing was used to determine the mRNA levels of related factors, and western blotting was used to determine related protein expression related to the possible anti-inflammatory mechanism.
Our findings will provide a more theoretical basis for the role of EGCG in maintaining intestinal permeability, and its later use in the development of healthy foods.

| Cytotoxic and MTT assay
To prepare the EGCG stock solution, 1 mg of EGCG was dissolved in 1-mL PBS and then stored at −20°C till use. Cell viability was measured by MTT assay following the method followed by Hossen et al. (2021). RAW 264.7 cells (1 × 10 5 cells/mL) inoculated at 100 μL in 96-well plates for 24 h. Later, the culture solution is replaced with a serum-free medium mixed with different doses of EGCG and LPS (1 μg/mL) and Dex (25.48 μmol/L). After 24 h of incubation, the culture solution was discarded, and then MTT stock solution was added at 37°C and left for incubation for 4 h. The formazan crystals formed in this step were dissolved by adding 150-μL DMSO and optical density (OD) is measured at 570 nm using a spectrophotometer (Tecan, Männedorf, Switzerland). The following formula is used to measure cell viability.

| Cell morphology analysis
For morphology analysis, 6.3 × 10 5 RAW264.7 cells were seeded in a six-well plate and incubated in a humidified incubator for 24 h at 37°C with 5% CO 2 in it. Then, 43.6 μmol/L EGCG +1 μg/mL LPS, 25.48 μmol/L DEX + 1 μg/mL LPS, and 1 μg/mL LPS were added and incubated for 24 h. Later, an inverted microscope is used to randomly select three locations in the dish for morphological recording, and calculate the pseudo-foot ratio (Hong et al., 2012).
After LPS treatment, the cells were added with EGCG (21.8 μmol/L, 43.6 μmol/L, and 87.2 μmol/L) and DEX (25.48 μmol/L), and incubated for 24 h. In the following, the cells were added with 100 μL of 0.1% neutral red solution and incubated for another 4 h. Later, the culture solution is discarded and washed thrice with PBS to remove neutral red that has not been engulfed by the cells. Then, 100 μL of acetic acid and ethanol solution (1:1, v/v) was added to each well, and the plates were placed at 4°C for 4 h to allow full lysis of the cells. Then, the absorbance of the cell lysate was measured using a spectrophotometer (Tecan) at 540 nm, and relative phagocytic activity was calculated by following the method of Chen et al. (2016).

| Determination of NO content in cells
Griess method was applied to measure the NO content by following the method of Joo et al. (2014). Raw 264.7 cells (6.3 × 10 5 ) grew to confluency in a 6-cm cell culture dish containing a 3-mL culture medium. After confluency, various concentrations of EGCG (10.9 μmol/L, 21.8 μmol/L, 43.6 μmol /L, and 87.2 μmol/L) and DEX (25.48 μmol/L) were added to cells pretreated with LPS (1 μg/mL).
After 24 h of incubation, cell supernatants were separated by centrifugation at 1500x g, then 100 μL of supernatants from each type was added to 100-μL Griess reagent. Absorbance was measured at 540 nm using a spectrophotometer (Tecan, Männedorf, Switzerland) in a 96-well microplate reader, and NO concentration was calculated using the standard curve.

| ROS level determination
DCFH-DA fluorescent probe method was used to detect the ROS level (Hossen et al., 2021). RAW264.7 cells (1 × 10 5 cells) were cultured in a 96-well dark plate until confluency. Then, the culture medium was discarded and cells were washed gently with PBS buffer.

| .Transcriptome analysis
RAW264.7 cells (6.3 × 10 5 cells/mL) were cultured till adherence in a 6-cm-diameter cell culture dish. After the cells adhered to the wall, the serum-free medium was used to replace the culture medium and then inoculated with LPS and EGCG + LPS for 24 h. After that, cells were washed twice with PBS buffer and 1-mL Transzol (TransGen Biotech, Beijing) lysate was added to lyse the cells. After lysis, lysates were transferred to a 1.5 mL of RNase-free centrifuge tube and stored at −80°C. Subsequent RNA extraction, detection, library construction, sequencing (Illumina HiSeq platform), and preliminary analysis were performed in Biomarker Technologies Corporation, Beijing. Sequenced data were filtered to get clean data after primary analysis, and compared the sequence with the mouse reference genome to get mapped data. Subsequent evaluation of library quality included insert length test, randomness test, and data saturation test as well as the analysis of sequence-structure levels such as variable splicing analysis, new gene discovery and gene structure optimization, and finally differential expression quantification of sample genes and difference analysis (Yu et al., 2018).
The expression level of the sample genes was calculated, and the FPKM algorithm was used to normalize the expression level: cDNA fragments indicate the number of fragments aligned to the transcript; mapped fragments (millions) indicate the total number of fragments aligned to the transcript, in millions; Transcript length (kb) is the length of the transcript.
DEseq software was used for differential gene screening, and the screening criteria were fold change ≥2.0 (Log2 fold change ≥l) and FDR ≤0.01. Among them, fold change represents the ratio of expression between two groups of samples, q-value is the significance of the differential expression, and the p-value is corrected to obtain the FDR value of the false discovery rate. Controlling FDR below a certain threshold can reduce the false-positive rate differential expression of genes.

| Determination of IL-1β, IL-6, TNFα , and iNOS using RT-PCR analysis
RT-PCR analysis was conducted using a Bio-Rad CFX96 touch system following the method described by Gao et al. (2020)

| Data processing
Screening and mapping of differential genes of transcriptome sequencing data were completed using various data processing tools provided by the Bimaike cloud platform. Excel 2010 was used to process the data, and then SPSS 17.0 was used for one-way analysis of variance. Finally, GraphPad 7 was used for plotting. Fisher's LSD test was used to corroborate the differences that occur among groups.

| Cytotoxicity and MTT assay
Before experimenting with EGCG, we attempted to evaluate the cytotoxic effects of EGCG with different doses. RAW264.7 cell The number of pseudopods in the LPS group was about four times higher than that of the control group (p < .01). EGCG significantly inhibited the generation of pseudopods caused by LPS, the number of pseudopods in the EGCG group was about 110% (p < .01).
The number of pseudopods in the DEX group was about 220%, which was significantly lower than that in the LPS group, but it was still about twice that of EGCG (p < .05) (Figure 3).

| Effects of EGCG on LPS-induced phagocytosis
Although the LPS group could promote the phagocytic capacity of cells, there was no significant difference from the control group ( Figure 4). Compared with the LPS group, DEX stimulated the phagocytic capacity of the cells, which were approximately 120% and EGCG significantly inhibited the phagocytic capacity of the cells at 21.8 μmol/L, 43.6 μmol/L, and 87.2 μmol/L. The phagocytic capacity was 95%, 89%, and 85% (p < .05), respectively, and the inhibitory effect of EGCG was significantly higher than the DEX group ( Figure 4). production. EGCG at 10.9 μmol/L and 21.8 μmol/L failed to inhibit the production of NO, and there was no significant difference from the LPS group. 43.6 μmol/L and 87.2 μmol/L EGCG inhibited the production of NO induced by LPS, the content was almost reduced to the control group, which was significantly lower than that of the LPS group, and there was no significant difference from the control group. At the same time, the positive control (DEX) also decrease the NO content by about 21 μM, which is 25% lower than the LPS group ( Figure 5).

| EGCG inhibits ROS production in RAW264.7 macrophages
As can be seen from Figure

| Transcriptome analysis
A total of 23,939 genes were detected in this experiment, includ-  (Figure 7).
At the same time, the correlation analysis revealed that the correlation between the control group and the LPS group was only about 0.7, the correlation between the LPS group and the LPS + EGCG group was about 0.78, and the correlation between the control group and the LPS + EGCG group was as high as about 0.91.
This indicates that after EGCG treatment, the overall gene expression trend of cells tends to be that of normal cells (Figure 8).
In the differential gene expression volcano diagram, there are 3677 differential genes between the control group and the LPS group, including 1703 upregulated genes (red dots) and 1974 downregulated genes (green dots); there are 4094 differential genes in the LPS group and the EGCG + LPS group. Among them, there are 1860 upregulated genes and 2234 downregulated genes. The control group and the LPS + EGCG group have a total of 5686 differential genes, 2556 upregulated genes, and 3130 downregulated genes ( Figure 9).
To study the effect of EGCG on the biological process (BP), cellular component (CC), and molecular function (MF) of RAW264.7 cells, the GO secondary function was obtained using the GO database Gene enrichment. Figure 9 shows that 24 BP, 18 MF, and 19 CC-related processes are involved. In BP, we found that differential genes differ from all genes in terms of metabolic processes, multicellular biological processes, signals, immune system processes, biological stages, detoxification, and cell killing.  Figure 10).

Analysis of differentially expressed genes (DEGs) revealed that
the control group and LPS group had 452 differential genes, the control group and LPS + EGCG group had 1073 differential genes, and the LPS group and LPS + EGCG group had 568 differential genes. The three groups involved 858 common differential genes, indicating that LPS induces changes in these genes, and EGCG will also regulate gene expression changes caused by LPS. After that, we further analyzed the differential genes shared by the three groups, which laid the foundation for studying the possible ways of EGCG ( Figure 11).
GO enrichment analysis showed that the three groups of differential genes were enriched in the GO function annotations for the 20 most significant related functions. Among them, 115 differential genes are involved in the Adenosine triphosphate (ATP) binding process. Secondly, the innate immune response involves 20 differential genes, the cell response to LPS involves 17 differential genes, the cell response to interferonβ involves 11 differential genes, and the cell response to interferonα involves five differential genes, the regulation of phagocytosis involves four differential genes. These processes are closely associated with the inflammatory immune response of macrophage cells (Figure 12).
We conducted KEGG enrichment analysis on the three groups of differential genes, and then evaluated the enrichment degree of KEGG by enrichment factor (rich factor), q-value, and gene quantity and displayed the top 20 most enriched signal pathways. The greater the enrichment factor, the more significant the enrichment level of differential genes in this pathway. Among them, the classic inflammation pathway NF-κB is the most significant among the inflammation-related pathways, and its enrichment degree is about 3.1. Secondly, there are the TNF-alpha signaling pathway, Toll-like receptor signaling pathway, etc. (Figure 13).  Figure 14).

| Effect of EGCG on LPS-induced NFκ B signaling pathway
The expression of IκB in the LPS group was significantly lower than that in the EGCG+LPS group, while the expression of activated P-IκB was significantly higher than that in the EGCG+LPS group (P < .05).
At the same time, the ratio of P-IκB/IκB in the EGCG+LPS group was 75% lower than that of the LPS group, indicating that EGCG could significantly inhibit LPS-induced activation of IκB, thereby inhibiting the activation of NF-κB (p < .05) (Figure 17).
Similarly, the expression level of P65 in the EGCG+LPS group was about twice that of the LPS group, while the expression level of P-P65 was only about 2/3 of that in the LPS group. The expression of P-P65/P65 in the EGCG+LPS group was significantly lower than that in the LPS group, about 1/2 times that of the LPS group, indicating that EGCG can significantly inhibit the activation of P65 induced by LPS, thereby exerting an inflammatory protective effect (p < .05) (Figure 18). However, EGCG could not significantly increase the expression of PPARγ (Figure 19).
Compared with the control group, LPS did not significantly affect the protein expression of 67LR. Similarly, there was no significant difference between the LPS group and the LPS + EGCG group as well (Figure 20a). LPS treatment elevated TLR4 expression, but it was also not statistically significant. Compared with the LPS group, EGCG downregulated the expression of TLR4 significantly (p < .05), and the expression level is about 70% of the LPS group, indicating that EGCG can exert an inflammatory protective effect by inhibiting the expression of TLR4 (Figure 20b).

| D ISCUSS I ON AND CON CLUS I ON
EGCG is the major part of green tea polyphenol that suppresses inflammation, oxidation, tumor, and apoptosis. In the present study, we demonstrated that EGCG, a bioactive polyphenol in green tea, suppressed the expression of LPS-induced inflammatory cytokines in Raw 264.7 macrophage cells by mediating TLR4 and NF-κB signaling pathways.
F I G U R E 11 Venn diagram of differential genes. Venn diagram representing total number of genes identified among the groups.
F I G U R E 1 2 Analysis of GO pathway enrichment of differential genes. Gene ontology (GO) analysis of significant genes. Bar plots displaying enriched biological processes, cellular components, and molecular function. The plots show significantly enriched GO terms.
Neutrophils are the key player in the body's defense to combat inflammation. These neutrophils extrude pseudopods while performing their innate task. Pseudopods have many forms and their size and shape depend on the degree of polymerization of actin filaments (Rocheleau et al., 2016). EGCG significantly inhibited the formation of cell pseudopods, and the effect was better than DEX. Cui et al. (2019) also observed similar morphological changes in macrophages. The cells in the control group aggregated and showed a round shape. After LPS treatment, the cell adhesion increased and the body shape increased, forming a long and slender pseudopod protrusion.
Macrophages participate actively in the immune response to fight foreign stimuli, pathogens, and damaged cells by engulfing them. In this experiment, EGCG can significantly reduce the phago- We performed transcriptome sequencing analysis on three sets of cell samples (control, LPS, and LPS + EGCG), and 7346 differential genes were obtained. The three groups of differential genes were screened and analyzed based on GO function enrichment terms. The results show that the ATP binding pathway is significantly affected.
In mitochondria, adenosine diphosphate (ADP) is consumed to produce ATP and oxygen consumption is blocked to produce O 2− , and superoxide anions play a central role in ROS production (Piechota-Polanczyk & Fichna, 2014). About 90% of ROS in cells are produced by mitochondrial oxidative phosphorylation and imbalance of these leads to the release of inflammatory factors such as TNFα and IL-1β, triggering innate immunity, eventually causing immune responses (Gao et al., 2008;Yamauchi et al., 2008). The activation of the TLR-mediated signaling pathway is also closely related to ROS generation. In LPS/TLR4-mediated inflammation, inhibition of ROS production helps reduce LPS-induced NF-κB activation (Ryan et al., 2004). Therefore, a reasonable adjustment of the relationship between ROS and ATP, and the balance of ROS production can help suppress inflammation and maintain the health of the body.
KEGG enrichment analysis revealed that the NF-κB pathway was significantly affected in the common differential genes. KEGG enrichment analysis found that NF-κB, a classic inflammation-related pathway, is significantly higher (involved total of 15 differential genes), and the TNF signaling pathway and TLR signaling pathway involved 15 and 14 differential genes, respectively. He et al. (2017) and Wang et al. (2014)  In this experiment, there was no significant difference between the 67LR protein expression of the LPS group and the LPS + EGCG F I G U R E 17 EGCG significantly inhibits LPS-induced activation of IκB. Data are represented as the mean ± SD (n = 3). *p < .05 versus LPS group. The beta Actin band in this figure is the same band in Figure 20a because we have separated them in the same membrane.
F I G U R E 1 8 EGCG significantly inhibits the activation of P65 induced by LPS. Data are represented as the mean ± SD (n = 3). *p < .05 versus LPS group. The beta Actin band in this figure is the same band in Figure 19b because we have separated them in the same membrane.
This indicates that EGCG can significantly inhibit the activation of NF-κB and thus suppress cell inflammation. PPARγ is closely associated with inflammation, and it can exert anti-inflammatory effects by inhibiting inflammatory signaling pathways such as NF-κB, activator protein-1 (AP-1), JAK-STAT, etc. (Bright et al., 2008;Dana et al., 2019). PPARγ can interact with P65 to prevent protein activation by inhibiting the activation of NF-κB (Yin et al., 2014). In this experiment, the EGCG+LPS group could not significantly increase

F I G U R E 19
Effects of EGCG on PPARγ. Data are represented as the mean ± SD (n = 3).
F I G U R E 2 0 Effects of EGCG on 67LR (a) and TLR4 (b). Data are represented as the mean ± SD (n = 3). *p < .05 versus LPS group. The beta Actin band in this figure is the same band in Figure 18. The beta Actin band in this figure is the same band in Figure 19 because we have separated them in the same membrane.
the expression of PPARγ. The difference is that Jin et al. (2020) found that fucoxanthinol can significantly upregulate the downregulated PPARγ expression in LPS-induced macrophage cells, thereby, directly and indirectly, downregulating NF-κB to suppress inflammation (Jin et al., 2020). This shows that there may be differences in the action pathways of EGCG and fucoxanthinol on macrophages. In macrophages, EGCG may not indirectly inhibit NF-κB activation by upregulating PPARγ and regulating the conversion of macrophages between M1 and M2 types.
In conclusion, the present study demonstrated that EGCG ad-

ACK N OWLED G EM ENTS
We express our gratitude towards Gao Zhipeng, Song Jingyi, Lv Wenwen and Ding Zhiqian for their assistance in the experimental processes including western blotting and transcriptome analysis.

CO N FLI C T O F I NTER E S T S TATEM ENT
The authors declare no conflict of interest.

DATA AVA I L A B I L I T Y S TAT E M E N T
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.