QC conferred a protective effect on renal damage in lupus-like mice

At 12 weeks, MRL/lpr mice were randomly assigned to the control group and QC group. Throughout the treatment regimen, all MRL/lpr mice underwent regular monitoring for survival rates, body weight variations, and fluctuations in urine protein levels (Fig. 1A). The results of the investigation showed that no discernible change in body weight was observed for either group of MRL/lpr mice over the course of the treatment (Fig. 1B). However, the QC group exhibited substantially lower urine protein levels compared to the control group after 12 and 15 weeks of treatment (Fig. 1C).

After 15 weeks of treatment, the control group had significantly greater glomerular volume, mesangial cell proliferation, and inflammatory cell infiltration than the QC group (Fig. 1D). Three kidney sections were taken from each mouse, and the mean glomerular diameter of these sections was calculated to represent the glomerular diameter of that particular mouse. After QC administration, a significant reduction in glomerular diameter was observed in mice as compared with controls (Figure S1A). Subsequently, we used multispectral immunohistochemical staining to examine IgG and C3 deposition within the glomerulus (Fig. 1E). We counted the mean fluorescence intensity (MFI) of C3 and IgG in glomeruli and found that the MFI of C3 and IgG decreased significantly in the quercetin group (Fig. 1F). Furthermore, we assessed the immune cell infiltration within the kidneys and discovered that the infiltration of both T cells and B cells was substantially diminished following treatment with quercetin (Figure S1B and S1C).

MRL/lpr mice were consistently administered QC or a control treatment, and serum samples were regularly collected. Subsequently, we observed that following QC treatment, the control mice exhibited a marked reduction in total IgG levels at 22 and 25 weeks, dsDNA levels at 15 weeks, and ANA levels at 22 weeks. (Fig. 1G).

Fig. 1

QC alleviated renal damage in lupus-like mice. (A) Schematics for the experimental workflow with MRL/lpr lupus mice. (B) MRL/lpr lupus mice weight in the QC and control groups. (C) Urine protein changes in the MRL/lpr lupus mice treated for 15 weeks, both in the QC group and the control group. (D) Renal pathological changes from MRL/lpr lupus mice (200-fold field of view; H&E staining). (E) Immune complex deposition in the kidney of lupus-like mice, IgG shown in green, C3 shown in red, nuclei shown in blue (200-fold field of view). (F) Statistical analysis of mean fluorescence intensity of IgG and C3 in glomeruli. (G) Serum total IgG levels, Serum ANA levels and serum dsDNA levels in lupus-like mice. (Quercetin: n = 5, Control: n = 5),(*P < 0.05, **P < 0.01, ****P < 0.0001)

QC significantly diminished the prevalence of Tfh cells and senescent T cells within the mLNs of lupus-like mice

At the treatment endpoint, there was no differences in the weights of mLNs or spleen between the two groups were observed (Fig. 2A). Nevertheless, a notable reduction in lymphocyte count was observed in the mLNs of the QC-treated group compared to the control (Fig. 2B).

In both the mLNs and spleen of MRL/lpr mice, we conducted an investigation into the effects of QC on Tfh cells, plasma cells and senescent CD4+ T cells by FCM, according to previously reported biomarkers [23,24,25]. We analyzed the frequencies of CD4+PD−1+CXCR5+ Tfh cells, CD4+CD44hiCD62L−PD-1+CD153+ senescent CD4+ T cells, and B220−CD138+ plasma cells in both the mLNs and spleens of MRL/lpr mice. The results showed that there was no significant difference in the frequency of Tfh cells (Fig. 2C and Figure S2C), senescent CD4+T cells (Fig. 2D and Figure S2D) and plasma cells (Figures S2A and S2E) between the two groups. Furthermore, we determined the absolute counts of these cellular subsets and observed that quercetin treatment significantly diminished the numbers of Tfh cells (Fig. 2E), senescent CD4+ T cells (Fig. 2F), and plasma cells (Figure S2B) in the mLNs.

Fig. 2

QC alleviated the swelling of the mLNs s in lupus-like mice. After 15 weeks of treatment, (A) Spleen size and statistical analysis of spleen of weight and cell counts from MRL/lpr mice in QC group and control group. (B) The weight and lymphocyte cell counts of mLNs from MRL/lpr mice in the QC group and control group were statistically analysed. (C, D) Representative flow diagrams of the frequency of Tfh cells and senescent CD4+ T cells from the spleen and mLNs of MRL/lpr mice with QC or vehicle. (E, F) Statistical analysis of cell counts of Tfh (CD4+PD−1+CXCR5+) and senescent CD4+ T cells (CD4+CD44hiCD62L−PD-1+CD153+) from the mLNs and spleen of MRL/lpr mice. (Quercetin: n = 5, Control: n = 5, *P < 0.05)

QC exerted a statistically significant reduction in the percentage of tfh cells in vitro

To assess the impact of QC on human Tfh cells, we cultured CD4+ T cells obtained from healthy individuals in the presence of QC at final concentrations of 0, 5, and 7µM for a duration of 72 h in vitro. Subsequently, the cells were harvested and subjected to FCM to quantify the percentage of Tfh and CD4+CD25+CD127− regulatory T (Treg) cells within the CD4+ T population(Figure S3A), according to previously reported biomarkers [23, 26].

The data revealed that the presence of QC at concentrations of 5µM and 7µM led to a significant decrease in the proportion of Tfh cells within the CD4+ T cell population (Fig. 3A). Furthermore, the 5µM QC treatment group displayed a statistically significant increase in the proportion of Treg cells when compared to the control group (0µM). However, no significant difference was observed in the percentage of Treg cells between the 7µM QC treatment group and the control group (Fig. 3B).

To explore the potential of QC therapy in inhibiting the progression of Tfh cell development, we conducted an experiment in which naïve CD4+ T cells from healthy individuals were cultured in the presence of QC at final concentrations of 0, 5, and 7µM, along with the cytokines IL12, IL21, TGF-β, and IL6, for 3 and 7 days. The cells were subsequently harvested and the proportions of Tfh and senescent Tfh cells were measured by FCM. The results indicated that after 3 days of treatment with 7µM QC, there was a substantial reduction in the number of Tfh cells compared to the control group. Moreover, a dose-dependent decrease in the proportion of Tfh cells was observed over the course of 3 and 7 days of QC treatment (Fig. 3C).

CD57 has been identified as a specific surface marker that is expressed on senescent CD4+ T cells in humans [27]. Our findings revealed a significant decrease in the percentage of senescent Tfh cells in the 7µM QC group on Day 7 compared to the control group. Besides, the 7µM QC group exhibited a greater reduction in the proportion of senescent Tfh cells after 7 days of treatment, in comparison to the 5µM QC treatment group (Fig. 3D).

Fig. 3

QC exerted a suppressive effect on the differentiation of Tfh cells in vitro. (A) Quantification of the impact of various concentrations of QC on the proportion of Tfh cells by FCM. (B) Quantification of the impact of various concentrations of QC on the proportion of Treg cells by FCM. (C) Quantification of the impact of various concentrations of QC on Tfh cell differentiation on day 3 and day 7 by FCM (n = 5). (D) Quantification of the impact of various concentrations of QC on the proportion of senescent Tfh cells on day 7 by FCM (n = 5). (*P < 0.05, **P < 0.01)

QC induced apoptosis in Tfh cells in vitro

To assess the effects of QC on apoptosis, cellular samples were harvested and subjected to FCM to quantify the apoptotic index. The results indicated that exposure of CD4+ T cells to 5 and 7µM QC for 3 days did not result in any alteration in the percentage of apoptotic cells when compared to the control group. However, the proportion of viable Tfh cells was notably reduced in the 7µM QC group after 3 days, as compared to the control group. Moreover, the 7µM QC group exhibited a significant decrease in viable Tfh cells compared to the 5µM QC group (Fig. 4A). Furthermore, we cultured PBMC from healthy donor with QC at a final concentration of 0, 5, and 7µM for 3 days, and then collected these cells to test the cell cytotoxicity by a CCK8 kit. The findings suggested that QC at doses of 5µM and 7µM did not exert cytotoxic effects on cell viability in comparison to the control group (Fig. 4B).

To elucidate the impact of QC within its therapeutic range on the cell cycle progression, CD4+ T cells were obtained from healthy donors cultured with QC at final concentrations of 0, 5, and 7 µM for 3 days in vitro. Subsequently, the FCM was employed to analyze the distribution of cells across each phase of the cell cycle and to investigate the influence of QC on CD4+ T cell cycle dynamics (Fig. 4C). The data indicated that no significant disparities in the cell cycle were observed between the 5 µM and 7 µM QC groups and the control group (Fig. 4D).

Fig. 4

QC induced apoptosis in Tfh cells in vitro.(A) Quantification of the effect of different levels of QC on apoptosis in CD4+ T cells and Tfh cells over a 3-day period by FCM (n = 4). (B) The cytotoxic effects of various concentrations of QC on PBMCs (n = 4). (C, D) The impact of QC at varying concentrations on the cell cycle progression of CD4+ T cells (n = 4). (*P < 0.05)

QC induced upregulation of apoptosis-related gene expression while downregulating genes associated with Tfh cells differentiation

We conducted an RNA sequencing (RNA-seq) analysis to compare the global transcriptional profiles of CD4+ T cells between the control group and the 7µM QC group on Day 3. Utilizing DESeq2 analysis in R with a significance threshold of p < 0.05, we identified a total of 2,266 differentially expressed genes (DEGs) in the qc treatment group. This dataset comprised 973 genes that were upregulated and 1,293 genes that were downregulated in comparison to the control group(Figure 5A). Additionally, we found that apoptosis related genes (including BCL2L11(BIM), PIK3CB, BCL2A1, CASP3, CAPN2, TNFSF11, ACTBP2, TNFRSF10A, TNFRSF11A and ATM) were up-regulated after QC intervention. The increased expression levels of these genes could be dominant factor to promote cell apoptosis. While the expression levels of apoptosis-resistant genes were also decreased, such as IKBKB, IL3RA, LMNA, SPTBN1, TRAF2, RARP3, TP53INP2, AKT2, AKT1S1, BBC3, DDIT4, BAK1, BCL3, ATF4, GZMB, BCL2L2, ATP4P3 and SIRT3(Fig. 5B). This maybe indicate that QC could attenuate cell senescence by promoting cell apoptosis.

KEGG pathway analysis identified the predominant enrichment pathways as “Systemic lupus erythematosus”, “the Longevity regulating pathway”, and other immune-related pathways, which indicated that QC ameliorates lupus symptoms probably by regulating immune and inflammatory homeostasis.

Subsequently, we identified a downregulation of key gene including IL6, IL21-AS1, IL27, and BCL6, and an upregulation of FOXP1 and CD80, as revealed by RNA-seq analysis. These cytokines and transcription factors are pivotal in the differentiation of Tfh cells, suggesting that QC may interfere with Tfh cell differentiation by modulating cytokine and transcription factors expression. To corroborate these findings, we employed RT-qPCR to validate the mRNA expression levels of Tfh cell-associated molecule. The RT-qPCR results revealed an increase in IL2 mRNA expression in the QC group compared to the control group, while BCL6 and IL6 expression levels were observed to decrease, aligning with the RNA-seq data. Moreover, we detected a significant upregulation of genes associated with “the longevity regulating pathway”, such as PPARG, SESN3, CAMK4, and SOD2, in the QC group (Fig. 5D). These observations collectively indicate that QC may inhibit Tfh cell differentiation by promoting the apoptosis of senescent cells.

Fig. 5

QC increased apoptosis genes while suppressing Tfh cell genes. (A) Volcano diagram of DEGs (differentially expressed genes) of CD4+ T cells between control group and QC group (n = 5). (B) Heatmap of DEGs related to apoptosis, senescence and differentiation in control group and QC group (n = 5). (C) KEGG enrichment analysis of CD4+ T cells in control group and QC group (n = 5), these pathways were significant differences in the diagram. (D) RT-PCR verified relative expression of mRNA in control group and QC group, Values are shown as mean ± SEM (n = 5, *P < 0.05, ** P < 0.01)

Identification of BCL-2 as a direct QC-Binding protein

To reveal the underlying mechanisms by which QC regulates cellular senescence gene expression, we screened for potential QC-binding proteins. We assessed the binding of QC to recombinant proteins synthesized on a HuProt human protein microarray. After incubation with QC or D-biotin, binding was detected using Cy5-SA (Cy5-streptavidin). (Fig. 6A). Additionally, we screened 193 target proteins for QC-specific binding using D-biotin as a control, further these specific positive proteins were used to construct protein-protein interactions (Fig. 6B). BCL-2, CASP8, MAPK8 were the main targets of the PPI network.

Using the KEGG database, we conducted pathway enrichment analysis on the 193 sample-specific binding target proteins (Supplementary Material 1). We identified BCL-2-related pathways that had a p-value less than 0.05 and used them to create the bar map. The KEGG pathways analysis revealed that the main enrichment pathway included the “Apoptosis”, “Endocrine resistance” and “Necroptosis” (Fig. 6C).

A bar chart was plotted to show the BCL-2 related terms with a p-value < 0.05 for each of the three functional modules in the enrichment analysis of 193 samples that specifically bind to target proteins based on the Gene Ontology database. The GO enrichment analysis indicate that QC exerts its biological effects through “cellular response to oxidative stress”, “focal adhesion assembly”, “neural nucleus development” and other biological processes and molecular functions (Fig. 6D). The Protein-Protein Interaction Networks analysis revealed that QC interacts with BCL-2 family protein.

Fig. 6

Identification of QC-binding proteins. (A) The protein microarray representation depicts red arrows as positive points, blue arrows as negative control points, and yellow arrows as specific positive protein points. (B) Visualization results of the protein–protein interaction network of specific positive protein. (C) The KEGG pathway analysis is performed on specific positive proteins to elucidate the pathways associated with BCL-2. The bar length corresponds to the number of target genes, while the bar colors correspond to the different values of p-value. (D) GO functional enrichment analysis associated with BCL-2 in specific positive proteins, including biological processes (BP), molecular functions (MF), and cellular components (CC)