FK506-binding protein-5 in high-fat diet-induced metabolic dysfunction-associated steatotic liver disease

Across both chow and HFD conditions, FKKO mice consistently weighed less than WT mice throughout the 16-week period. Images of the mice visually confirmed the lower body weight and smaller size of FKKO mice compared to WT, particularly noticeable in the HFD group (Fig. 1a, b). The Serum and hepatic triglyceride levels in both WT and FKKO mice were lower that the NCD and HFD groups (Fig. 1c). FKKO mice exhibited improved glucose tolerance compared to WT mice on HFD, indicating better glucose metabolism (Fig. 1d). Area under the curve analysis confirmed significantly better glucose handling in FKKO mice on HFD compared to their WT counterparts (Fig. 1e). The alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels in both WT and FKBP5 knockout (FKKO) mice under NCD and HFD (Fig. 1f). Hematoxylin and eosin and Oil Red O staining indicated less fat deposition and liver damage in FKKO mice, especially on HFD (Fig. 1g). Quantitative analysis of liver sections (MASLD activity score, based on steatosis, inflammation, and ballooning) shows reduced lipid accumulation and healthier liver morphology in FKKO mice (Fig. 1h). FKKO mice exhibited reduced HFD-induced hepatic steatosis, as shown by histological and molecular markers. FKKO mice show decreased expression of genes associated with fatty acid uptake and synthesis, especially on HFD (Fig. 1i). FKKO mice display lower expression of fibrosis markers such as α-sma, COL1A1, and TGF-β on HFD, indicating reduced liver fibrosis (Fig. 1j). Expression of inflammatory cytokines (TNFα, IL-1β, and IL-6) is significantly lower in FKKO mice, suggesting less inflammation (Fig. 1k). These finding confirmed that FKBP5 deficiency reduces fatty acid uptake and de novo lipogenesis, thus protecting against diet-induced steatosis, inflammation, and fibrosis (Fig. 1l).

FKBP5 deficiency reverses significant changes induced by a high-fat diet on the metabolic signature of macrophage responses in the liver.

Therefore, we investigated the potential role of FKBP5 in macrophage infiltration during HFD-induced MASLD. After 16 weeks of feeding, flow cytometry was performed to characterize the myeloid and lymphoid components of the liver. MASLD was associated with a reduction in the number of CD11bhighF4/80 + macrophages as determined by myeloid population analysis (Fig. 2a). Additionally, the number of CD11bhighLy6C+ monocytes was increased in HFD-fed WT mice (Fig. 2b), which was reversed in FKKO mice. ViSNE was used to visualize immunological marker intensity to investigate myeloid cell differentiation. This method visualizes t-distributed stochastic neighbor embedding to detect myeloid cell subgroups. The viSNE algorithm investigated 10,000 events per sample using CytoBank (cytobank.org), one cell per dot in multidimensional space. Using viSNE, we evaluated myeloid cells for their unique combination of F4/80, Ly6C, and Ly6G expressions (Fig. 2c). Most of the 100 nodes in Fig. 2d indicate unsupervised myeloid cell population clustering and similarity. Spanning-tree Progression Analysis of Density-normalized Events (SPADE) was used to determine the most distinct cell populations across NCD, HFD, WT, and FKKO mice for an unsupervised, unbiased study of their phenotypes. SPADE automatically clusters multidimensional flow cytometry data files into nodes and projects them onto trees¹¹. Each node included cells with the same phenotype across all parameters, and its size represented the population’s cell count, making animal comparisons easy. To compare myeloid cell populations in WT and FKKO mice fed NCD or HFD, we manually gated flow cytometry data in the Cytobank on CD45 ⁺ and created new data files with these gated events. We created SPADE to derive a hierarchy from unsupervised high-dimensional cytometry data. SPADE visualizes several cell types in a branching tree structure without needing cellular ordering, complementing existing cytometric data analysis approaches. SPADE uses a two-dimensional display to show how protein markers behave across cell kinds, allowing scientists to find known and unknown cell types. We recently reported using SPADE for immunophenotyping without explaining the procedure or analysis. SPADE automatically analyzed pre-gated data files from Cytobank. F4/80, CD11b, Ly6C, and Ly6G clustering channels formed SPADE trees. SPADE analysis compared NCD and HFD in WT and FKKO mice utilizing fold-change groups, and baseline WT-NCD set data files. To show group differences, SPADE trees were colored by “percent total ratio log” or log10 (percent of total sample/average percent of total baseline). The first and second clusters on the right side of the SPADE tree-like image increased the number of CD45 ⁺ CD11b⁺F4/80⁺ (133, 25, 152, 42, 103, 80, and 89) and CD45 + CD11b⁺Ly6G^–Ly6C^– (2, 12, 29, 10, 31, 33, 50, 79, 84, 86, 88) cells. The three higher clusters in HFD-fed WT mice increased CD45 ⁺ CD11b⁺Ly6G^–Ly6C⁺ cells (1, 37, 59, 136, 147, 166) (Fig. 2e). These findings demonstrate that liver KCs cause inflammation and attract blood-derived monocytes. Both cell types became pro-inflammatory macrophages and advanced HFD-induced MASLD. HFD significantly impacted lymphoid cell composition by decreasing CD4 ⁺ T cells and increasing CD8 ⁺ T cells. (Fig. 2f). Furthermore, we investigated the lymphoid cells using viSNE. We assessed lymphoid cells based on their unique combination of CD45, CD4, and CD8 expression (Fig. 2g). Additionally, we examined lymphoid cells. We clustered lineage markers (CD45, CD3, CD19, CD4, and CD8) and projected the findings into SPADE trees using the default 100-node aim. As clustering factors increased, the SPADE tree structure changed most on the red node. In FKKO-HFD mice, more nodes were statistically significant than in WT-HFD mice. (Fig. 2h). These findings demonstrate the necessity for quantitative and visual research to comprehend SPADE analysis. They further suggest that FKBP5 depletion causes hepatic steatosis by disrupting macrophage-hepatocyte metabolic coordination in fatty acid-rich conditions.

The gut microbial populations of WT and FKKO littermates were compared using 16S ribosomal RNA (16S rRNA) gene sequencing. HFD-fed mice had more Firmicutes: Bacteroides, endotoxin-producing Proteobacteria, and less immune-homeostatic bacteria in their GM. We used pyrosequencing of the 16S rRNA (V3-V4 region) of colon feces bacteria to determine how FKBP5 affects GM composition. Metagenomic study utilizing NGS Ion Torrent Technology. QIIME analysis utilized 25,535,562 of 49,106,850 quality-filtered reads from sequencing runs. From these reads, we used 17,220 operational taxonomic units (OTUs) for sections V3 and V4 of the 16 S rRNA gene sequence to assess GM abundance and diversity at different taxonomic levels. We avoided samples with fewer than 3000 compelling reads. This investigation compared GM composition in WT and FKKO mice given HFD or NCD. In mice, HFD affects the GM¹² and we observed a comparable effect in WT and FKKO mice. Taken together, our findings indicate that most of the prevalent genera vary considerably between the WT-HFD and FKKO-HFD groups. The most abundant bacteria belong to the phyla Bacteroidetes, Proteobacteria, and Firmicutes. We observed an increased number of Firmicutes in FKKO-HFD mice, whereas FKBP5 mice showed a reduction in the Firmicutes/Bacteroidetes ratio (Fig. 3a). FKKO mice demonstrated a reduction in Bacteroidaceae after HFD treatment (p = 0.0011) compared with WT mice (p = 0.0043) (Fig. 3a). Further analysis of the Firmicutes/Bacteroidetes composition at the family level revealed that FKKO mice had decreased Ruminococcaceae (p = 0.0205) and increased Lachnospiraceae (p = 0.0091) prior to HFD treatment (Fig. 3b). FKKO animals fed an HFD showed a significantly greater abundance of Lachnospiraceae (p = 0.003) and a significantly lower abundance of Muribaculaceae (p = 0.013) (Fig. 3b) than WT mice fed an HFD. Compared to FKKO-NCD mice, FKKO mice had lower levels of Muribaculaceae (p = 0.0205) and higher levels of Bacteroidaceae (p = 0.0091) (Fig. 3c). Venn diagrams indicated that the digesta compartments had 198 OTUs as the compartmental core microbiota, whereas the HFD and NCD control groups had 85 and 93, respectively. Interestingly, FKBP5 animals were resistant to HFD-induced Firmicutes and Bacteroidetes alterations (Fig. 3d, e). Further GM data analysis using linear discriminant analysis (LDA) effect size (LEfSe) identified 17 differently abundant clades (p = 0.05) in NCD-fed WT and FKKO mice and 15 in HFD-fed animals. LEfSe analysis also revealed bacterial differences between WT and FKKO groups following NCD and HFD (Fig. 3f). A bubble graphic showed the relative abundance of bacterial phyla and species in each category. Compared to the HFD group, the FKKO group had more Firmicutes (59.75% vs. 71.68%, p < 0.05) and Actinobacteria (1.25% vs. 4.13%, p = 0.06) but lower Bacteroidetes (35.35% vs. 21.46%, p < 0.05). FKKO exhibited a large rise in Faecalibaculum abundance at the genus level, which greatly contributed to the overall difference (Fig. 3g). The abundance of many additional taxa, such as Odoribacter, Parabacteroides, Blaudia, and Coriobacteriaceae UCG-002, differed between the WT-HFD and FKBP5 KO-HFD groups (Fig. 3f). Our results indicate that FKKO-deficient mice exhibit a distinct GM response to HFD, and that lean-associated microbiota may contribute to obesity resistance. Spearman’s correlation analysis showed that the numbers of the bacterial genera Alistipes, f_Muribaculaceae, Odoribacter, Lactobacillus, Bacteroides, Helicobacter, Dubosiella, Tyzzerella, and Blautia increased in the HFD model mice and were linked to pathophysiological characteristics. GM was also altered significantly with liver disease progression, and the connection between GM ecology and liver pathology may represent a potential target for the prevention and treatment of chronic liver disease (Fig. 3h). Taken together, our findings indicate that FKBP5 deficiency affects not only the composition of the GM, but also the responsiveness of the GM to HFD.

FKBP5 was not expressed in the colon tissues of FKKO mice fed with NCD or HFD (Fig. 4). Although the number of goblet cells decreased in HFD-fed mice, it increased in FKBP5-deficient HFD-fed animals (Fig. 4b). WT and FKKO mice were given fluorescein isothiocyanate (FITC)-dextran to investigate HFD on intestinal permeability. In HFD-fed WT mice, intestinal permeability increased significantly. In HFD-fed FKKO mice, gut permeability disappeared (Fig. 4c). Although HFD therapy significantly altered ZO-1 expression in WT and FKKO mice, HFD-fed FKKO mice had better junction structure. Importantly, these qualitative findings were supported by FITC-dextran permeability assays, providing quantitative evidence of barrier integrity. (Fig. 4d). After HFD, obese individuals with FKBP5 deficiency may have better intestinal barriers. Transmission electron microscopy assessed ultrastructural changes in tight junctions (TJs) and gap junctions in intercellular apical junctional complexes that may impact paracellular permeability. Ultrastructural changes in HFD-fed FKKO rats included injured TJs and gap junctions, increased intercellular gap, and colon vaporization (Fig. 4e). FKKO mice showed dramatically decreased HFD-induced intestinal epithelial ultrastructure changes. Our results suggest that FKBP5 deficiency is essential for coordinating intestinal ZO-1 TJ formation and preserving the intestinal epithelial barrier from HFD-induced disruption.

Numerous biological processes, including myeloid and lymphocyte control, are associated with the modulation of the immune system in the intestines of FKBP5-deficient animals fed a high-fat diet. Using flow cytometry, we determined the differences in myeloid cells, CD11b⁺Ly6C⁺ monocytes, CD11b⁺Ly6C⁺Ly6G⁺ neutrophils, and CD11b+Ly6C- monocytes between WT and FKKO mice. We observed that HFD increased the number of CD11b⁺Ly6C⁺monocytes in WT mice, but not in FKKO mice (Fig. 4f). Additionally, we examined CD4 ⁺ and CD8 ⁺ T cell expression levels in the mouse colon and discovered that FKKO animals had elevated CD4 ⁺ T cell populations while simultaneously having reduced CD8 ⁺ T cell populations induced by HFD. No discernible differences were observed between spleens (Fig. 4g and h). Data show that low-grade inflammation contributes to HFD-induced obesity, although further study is needed on pro-inflammatory cytokines. Colon protein levels of pro-inflammatory cytokines TNF-α and IL-1β were measured in WT-HFD mice using ELISA. The colon tissues of HFD-fed WT rats showed significantly higher levels of TNF-α and IL-1β. However, HFD-fed FKKO animals had less inflammation (Fig. 4i and j). These findings show that GM changes aid HFD-induced gut ZO-1 TJ breakdown and BT. According to growing evidence, HFD-induced dysbiosis requires FKBP5. Gut-derived endotoxins, lipids, metabolites, hepatocellular injury, and death molecules activate MASLD macrophages.

Our SparCC-derived immune cell-GM co-abundance network analysis indicated that phylotype abundance profiles may represent such interactions via co-occurrence and exclusion patterns. We estimated SparCC correlation coefficients using a robust, newly established approach for analyzing relative abundance data to determine OTU relationships. Of over 400,000 associations, 15,184 had p-values < 0.05, 11,628 were positive (r > 0.6), and 3,556 were negative. Family and genus SparCC networks were established (Fig. 5). The relative species abundance profiles showed substantial co-exclusion and co-occurrence linkages amongst phylotypes, with co-occurrence estimates ranging from − 0.768 to 0.941. After the study, the two groups had distinct weight changes. Spearman’s correlation study indicated GM abundance’s relationship to immune profile metabolites.

Our microbiological investigations revealed a substantial reduction in the relative abundance of Lactobacillaceae and Bifidobacteriaceae within the OTUs representing Lactobacillaceae and Bifidobacteriaceae in HFD-fed WT mice. To determine whether these beneficial bacteria could help mitigate the effects of HFD, mice were gavaged with probiotic VSL#3 (Fig. 6a). We examined whether VSL#3 therapy was beneficial in lowering adiposity and re-establishing glucose homeostasis in obese mice. For 16 weeks, we separated DIO mice into four groups, grouping them as either WT-HFD or FKKO-HFD mice with or without VSL#3 injection. Administering VSL#3 to WT-HFD mice resulted in a decreased body weight (Fig. 6b and c) and a significant decrease in fasting blood glucose levels (Fig. 6d) and subcutaneous fat (Fig. 6e). Next, we used TTGE to determine the variations in GM diversity. Mice administered VSL#3 probiotics exhibited greater GM diversity than mice fed HFD or FKKO (Fig. 6f). Interestingly, we discovered that mice administered VSL#3 probiotics had significantly reduced gut permeability (as measured by 4 kDa FITC-dextran diffusion from the gastrointestinal tract into the blood) compared to their HFD-fed WT counterparts (Fig. 6g). As expected, this was directly related to the increased expression of tight junction proteins, including ZO-1, in the colon tissues of HFD-fed mice receiving VSL#3 probiotics compared to that in HFD-fed WT and FKKO animals (Fig. 6h). Additional complete blood count studies demonstrated that VSL#3 dramatically lowered the number of white blood cells, monocytes, and lymphocytes in the circulation (Fig. 6i–k). VSL#3 also improved hepatic steatosis (Fig. 6l) and ALT and AST levels (Fig. 6m) in the HFD-fed WT and FKKO mice. These biochemical markers provide quantitative support consistent with the histological observations. Therefore, we aimed to gain a better understanding of how VSL#3 probiotics interact with the gut-liver axis through hepatic macrophage regulation. VSL#3 injection dramatically decreased hepatic CD11b⁺Ly6G^–Ly6C⁺ cells in WT-HFD mice (Fig. 6n), suggesting that the positive metabolic benefits of VSL #3 alleviated the inflammatory state often associated with obesity and insulin resistance. Notably, the HFD-induced gut permeability (Fig. 6g) was rescued by probiotic treatment. These findings unequivocally support the use of VSL#3 as an additional therapeutic agent in HFD-induced MASLD.

All experimental procedures were approved by the Institutional Animal Care and Use Committee of National Yang Ming Chiao Tung University (#1100310) and were performed between January 2021 and December 2021 in accordance with the Institutional Guidelines on Animal Experimentation at National Yang Ming Chiao Tung University and ARRIVE (Animal Research: Reporting of In Vivo Experiments) guidelines. FKBP5 KO mice were kindly provided by Dr. Yi-Hsuan Lee (Taiwan) and backcrossed to C57BL/6J background. Taiwan’s National Laboratory Animal Center supplied male C57BL/6J. All mice were treated following College Standards for Experimental Animal Use. The animals were housed at Yang Ming Chiao Tung University College of Medicine’s Laboratory Animal Center.

C57BL/6J FKBP5/ and wild-type (WT) C57BL/6J, 5–8-week-old male mice (20–25 g) were kept in semi-specific pathogen-free conditions. Genealogically similar mice with comparable beginning weight (no blinding) were housed together (4–5 mice per cage), given an autoclaved chow meal, 10% kcal control diet, or 45 kcal high-fat diet on a 12-h light cycle. PCR examination of the eubacterial 16 S rRNA genes and temporal temperature gradient gel electrophoresis (TTGE) confirmed sterility in 12-week-old male germ-free C57BL/6J mice from the National Laboratory Animal Center. Pilot testing showed that DIO experiment sample sizes have at least 80% power at p = 0.05. All mice were anesthetized by isoflurane and sacrificed under high CO₂ environment.

Statistical analyses, except microbiome analyses, were performed using Prism 10.6.1. Animals not meeting requirements were eliminated from the analysis. The biological replicate average was used for statistical analysis. The two-tailed Mann–Whitney U test was used to compare animal studies without a distribution assumption. Two-way analysis of variance with Tukey’s post-hoc test was used to compare > 2 datasets across four groups (WT-NCD, WT-HFD, FKKO-NCD, FKKO-HFD), which accounts for both genotype and diet factors. Statistical significance was set at p < 0.05.