Background: Little is known about the association between gut microbiota and intestinal injury under a state of chronic cerebral hypoperfusion (CCH). Here, the effects of gut microbiota and short-chain fatty acids (SCFAs), as important metabolic products, on intestinal function and potential mechanisms after CCH were investigated. Methods: Rats were subjected to bilateral common carotid artery occlusion (BCCAo) to induce CCH. The gut microbiota and metabolites of SCFAs were assessed by 16S rRNA sequencing and targeted metabolomics, respectively. Transcriptomic analysis of colon tissues was also conducted. Subsequently, potential molecular pathways and differentially expressed genes were verified by western blot, immunoprecipitation, and immunofluorescence analyses. Furthermore, the integrity of the colonic barrier was evaluated by hematoxylin and eosin and mucin 2 staining and expression levels of tight junction proteins. Besides, colonic inflammation was further assessed by flow cytometry and expression levels of inflammatory cytokines. In addition, colonic mitochondrial dysfunction was analyzed via membrane potential, reactive oxygen species, electron transport chain (ETC) activities, adenosine triphosphate content, and mitochondrial ultrastructure. Results: CCH modified gut microbial composition and microbial metabolism of SCFAs, which may be associated with inhibition of mitochondrial ETC activities and oxidative phosphorylation, leading to dysregulation of mitochondrial energy metabolism. Furthermore, CCH induced differentiation of pathogenic Th17 cells, promoted the formation of complexes of interferon regulatory factor 4 and signal transducer and activator of transcription 3 (STAT3), and increased the phosphorylation of STAT3. This was associated with an impairment of colonic barrier function and chronic colonic inflammation. In contrast, FMT and SCFA replenishment ameliorated CCH-induced gut microbial dysbiosis by increasing the intestinal content of RuminococcusN15_MGS_57 and modulating microbial metabolism of SCFAs by increasing acetic acid contents associated with an improvment of the balance between Tregs and Th17 cells, mitochondrial ETC activities, and oxidative phosphorylation to prevent colonic inflammation and dysregulation of mitochondrial energy metabolism. Conclusion: These findings indicate that FMT and SCFA replenishment present a promising therapeutic strategy against colonic dysfunction under a state of chronic cerebral ischemia.
Keywords: Chronic cerebral hypoperfusion; Gut microbiota; short-chain fatty acids; Mitochondrial energy metabolism; Treg/Th17 balance
Shao-Hua Su and Yi-Fang Wu contributed equally to this work
Chronic cerebral hypoperfusion (CCH), which refers to a chronic state of reduced cerebral blood flow, is associated with the pathology of various cerebrovascular diseases and cognitive impairment via cerebral ischemia-induced apoptosis, inflammation, and excessive autophagy [[
The gut microbiota consists of a diverse community of bacterial species, existing symbiotically with the human host. The health and stability of the gut microbiota is vital to maintain homeostatic balance. Increasing evidence supports the functional effects of the microbiota on bidirectional communication along the microbiota-gut-brain axis [[
Short-chain fatty acids (SCFAs) are important products of gut metabolism, mainly consisting of acetate, propionate, and butyrate [[
Therefore, the aim of the present study was to investigate the effects of the gut microbiota and SCFAs on intestinal function and to explore potential mechanisms after CCH in order to provide new insights into the treatment of CCI-induced gut dysfunction.
Male Sprague–Dawley rats (age, 5 weeks; body weight, 180 ± 10 g) were purchased from the Shanghai Laboratory Animal Resource Center (Shanghai, China) and Shanghai SIPPR-Bk Lab Animal Co., Ltd. (Shanghai, China). Prior to experimentation, the rats were housed in a climate-controlled facility at a constant temperature of 23 ± 1 °C and 60% humidity under a 12-h day/night cycle (lights on 08:30 am–08:30 pm) with ad libitum access to water and standard rat chow. After 1 week of acclimatization, the rats were randomly assigned to one of four groups [5 rats per group for targeted metabolomics of SCFAs; 3 rats per group for RNA sequencing; 5 rats per group for histopathological analysis or immunofluorescence staining (3 rats per group for dihydroethidium (DHE) staining); 4 rats per group for western blots or immunoprecipitation (IP) (3 rats per group for IP); 5 rats per group for enzyme-linked immunosorbent assay (ELISA) or biochemical tests; 3 rats per group for flow cytometry]: (
Rats in all four groups were sacrificed after 12 weeks. Fresh feces and colon tissues were immediately collected for experiments or stored at − 80 °C for later use (Fig. 1). All experiments involving animals were approved by the Committee for Animal Experimentation of Tongji Hospital (Shanghai, China) and conducted in compliance with the Guide for the Care and Use of Laboratory Animals.
Graph: Fig. 1 Timeline for the experimental procedure. Rats were randomly divided into four groups including sham, BCCAo, BCCAo + FMT and BCCAo + SCFAs. Rats received different interventions in these four groups for 12 weeks, then were sacrificed for subsequent experiments. ABX antibiotic treatment
BCCAo at 8–12 weeks is sufficient to sustain CCH in rats and most closely resembles reduced CBF in humans [[
As described in a previous study [[
As previously described [[
For gastric perfusion, a tube was carefully inserted into the stomach from the mouth (distance, 5–7 cm), while maintaining the head and neck in a straight line, and either drugs or liquified fecal samples were slowly injected through a syringe. After removing the tube, the posture of the rat was maintained for 30 s. If the rat struggled or experienced troubled breathing, the procedure was discontinued and the tube was immediately extracted. When the rat recovered to calm and breathed evenly, the procedure of gastric gavage was conducted again.
The 16S rRNA genes of snap-frozen fecal samples were sequenced by BioNovoGene Co., Ltd. (Suzhou, China). Briefly, total DNA was extracted from fecal samples (250 mg, wet weight) using the QIAamp DNA Stool Mini Kit (Qiagen GmbH, Hilden, Germany) in accordance with the manufacturer's instructions. DNA integrity and size were verified by 1% agarose gel electrophoresis and DNA concentrations were determined using a NanoDrop spectrophotometer (NanoDrop Technologies, LLC, Wilmington, DE, USA). For each DNA sample, 16S rRNA was amplified with the primers 341F (5'-CCT AYG GGR BGC ASC AG-3')/806R (5'-GGA CTA CNN GGG TAT CTA AT-3'), which directionally target the V3 and V4 hypervariable regions. Each 20 μL PCR reaction volume contained 4 μL of 5 × FastPfu Buffer, 2 μL of 2.5 mM dNTPs, 0.8 μL of each primer (5 μM), 0.4 μL of FastPfu DNA Polymerase, and 10 ng of template DNA. The PCR reaction included an initial denaturation step at 95 °C for 3 min, followed by 27 cycles of denaturation at 95 °C for 30 s, annealing at 55 °C for 30 s, and elongation at 72 °C for 45 s, and a final extension step at 72 °C for 10 min. The reactions were performed on a GeneAmp™ PCR System 9700 (Applied Biosystems, Carlsbad, CA, USA). All PCR products were purified using an AxyPrep™ DNA Gel Extraction Kit (Axygen Scientific, Inc., Union City, CA, USA) and quantified using a QuantiFluor™-ST fluorometer (Promega Corporation, Madison, WI, USA). Normalized equimolar concentrations of the purified amplicons were pooled and sequenced with a NovaSeq PE250 sequencing instrument (Illumina, Inc., San Diego, CA, USA) in accordance with the manufacturer's specifications.
High-throughput sequencing analysis of the bacterial 16S rRNA genes was processed using Quantitative Insights into Microbial Ecology software (version 1.9.1) [[
16S rRNA gene sequencing data were deposited into the BioProject database (https://
Targeted metabolomics analysis of SCFAs of snap-frozen fecal samples and colon tissues was performed by BioNovoGene Co., Ltd. Briefly, 100 mg of feces and 300 mg of colon tissues were dispersed in acidified water spiked with stable isotope-labeled SCFA standards and extracted with diethyl ether. The ether layer was immediately analyzed by gas chromatography-mass spectrometry (GC-MS) with a TRACE 1300 gas chromatograph (Thermo Fisher Scientific, Waltham, MA, USA). The SCFA standards used in this study were mixtures of acetate, propionate, butyrate, isobutyrate, valerate, isovalerate, and caproate. Quantitation was performed by calibration to internal standards. The protein contents of homogenized tissues were normalized. Then, samples (1 μL) were injected at a split ratio of 10:1. Helium was used as the carrier gas at a constant flow rate of 1.0 mL/min. The injection, transfer line, and ion source temperatures were set at 250 °C, 250 °C, and 230 °C, respectively. The initial temperature program was set at 2 min of isothermal heating at 90 °C and then increased to 120 °C at a rate of 10 °C/min, then to 150 °C at 5 °C/min and finally to 250 °C at 25 °C/min, which was maintained for 2 min. Data were acquired in full-scan mode (electron impact ionization, 70 eV) with an m/z range of 35–780.
The GC-MS data obtained in the.raw format from the platform were converted to the.mzXML format using the msConvert tool ((ProteoWizard). Then, the data sets were normalized, transformed, imputed, and scaled after outlier removal using the R package (v3.3.2). The levels of seven SCFA metabolites were quantified and compared with the non-parametric Mann–Whitney U test. Orthogonal partial least squares discriminant analysis (OPLS-DA) was applied to identify differences among groups.
RNA extracted from snap-frozen colon tissues were sequenced by BioNovoGene Co., Ltd. Briefly, samples with an RNA integrity number > 8 were submitted for library prep and next-generation sequencing. cDNA libraries were prepared using a NEBNext® Ultra™ II RNA Library Prep Kit for Illumina® (New England Biolabs, Ipswich, MA, USA). Purified cDNA libraries were sequenced using a NovaSeq PE250 sequencing instrument with > 6G raw reads (150 bp, pair-ended) per sample. Differentially expressed genes (DEGs) were identified by RNA sequencing (RNA-seq) based on the criteria p < 0.05 and |log
RNA-Seq data were deposited into the BioProject database (https://
The mitochondrial fraction was isolated using the Qproteome® Mitochondria Isolation Kit (Qiagen GmbH). Briefly, colon tissues (~ 20 mg) were cut into pieces and homogenized in 2 mL of lysis buffer with protease inhibitor solution. The supernatant was centrifuged at 1000 × g and 4 °C for 10 min. Then, the resulting pellet was resuspended and disrupted in 1.5 mL of ice-cold disruption buffer. Following centrifugation at 1000 × g and 4 °C for 10 min, the supernatant was collected and centrifuged at 6000 × g for 10 min. The pellet (containing mitochondria) was resuspended in 750 μL of mitochondrial purification buffer and added on the top of a mitochondrial purification buffer layer. After centrifugation at 14,000 × g for 15 min, the pellet or band containing mitochondria that formed in the lower part of the tube was transferred to a new tube. The suspension was washed three times with 1.5 mL of mitochondrial storage buffer by centrifugation at 8000 × g for 10 min. The high-purified mitochondria were resuspended in mitochondrial storage buffer and used to determine the membrane potential. The remaining mitochondrial and cytosolic fractions were stored at − 80 °C for later use.
The membrane potential of isolated mitochondria was measured using a JC-1 staining kit (Beyotime Institute of Biotechnology, Haimen, China). Briefly, 10 μL of fresh mitochondria were incubated in 100 μL of JC-1 staining reagent for 10 min. Images were captured using an inverted microscope (IX71; Olympus Corporation, Tokyo, Japan) at wavelengths of 488 and 594 nm. The ratio of red/green intensity was observed to assess the membrane potential of isolated mitochondria. Healthy mitochondria showed a high intensity of red fluorescence at 594 nm and a low intensity of green fluorescence at 488 nm, while impaired mitochondria demonstrated opposite results.
Colon tissues were homogenized in ice-cold HEPES buffer (3 mM, pH 7.2) containing sucrose (0.25 M), egtazic acid (0.5 mM), and protease inhibitor cocktail (1:40; Roche Life Science, Penzberg, Germany). The protein concentration of the tissue homogenate was measured with a Pierce™ BCA Protein Assay Kit (Pierce Biotechnology, Waltham, MA, USA). Then, the fractions were quantified using ATP and ETC Complex I–V assay kits (Beijing Solarbio Science & Technology Co., Ltd., Beijing, China) in accordance with the manufacturer's instructions. Briefly, equal amounts of fresh proteins were loaded into all wells and absorbance was measured using a spectrophotometer as follows: ε340 nm for nicotinamide adenine dinucleotide (NADH) dehydrogenase (complex I) and ATP content, ε550 nm for mitochondrial complex III (cytochrome c reductase) or complex IV (cytochrome c oxidase), ε605 nm for complex II (succinate-coenzyme Q reductase), and ε660 nm for complex V (F0F1-ATPase/ATP synthase). For convenience, the ATP content is expressed as µmol/mL, while the other results are expressed as µmol/mg of protein.
Paraffin-embedded sections were deparaffinized and washed three times with PBS for 5 min for histopathological analysis and immunofluorescence staining. For histopathological analysis, the slices were stained with a hematoxylin and eosin (HE) staining kit (Baso Diagnostics, Inc., Wuhan, China) in accordance with the manufacturer's instructions and viewed under an inverted microscope (Olympus IX71) to identify morphological changes to the intestinal mucosa. For immunofluorescence staining, the sections were immersed in ethylenediaminetetraacetic acid (EDTA)-Tris solution (pH 9.0) for 30 min at 98 °C for antigen retrieval, rinsed three times with PBS for 5 min, and then incubated with 10% non-immune goat serum for 30 min at room temperature to block non-specific labeling before overnight incubation with an antibody against mucin 2 (MUC2) (1:50; Santa Cruz Biotechnology, Inc., Dallas, TX, USA) in a humidified chamber at 4 °C [[
Reactive oxygen species (ROS) were detected by staining with DHE. Briefly, the sections were incubated in 10 mM DHE (Beyotime Institute of Biotechnology) at room temperature for 30 min in the dark and then viewed under an inverted microscope (Olympus IX71).
The amount of acetyl coenzyme A (Ac-CoA) in colon tissues was quantified with a commercial ELISA kit (Nanjing Jiancheng Bioengineering Institute, Nanjing, China) in accordance with the manufacturer's instructions. Briefly, 50 mg tissues were homogenized and centrifuged at 4000 × g for 10 min and the supernatant was separated. The total protein concentration in each group was determined by the BCA method, and the optical densities (450 nm) of equal amounts of proteins (50 μL) were determined with a microplate reader and the concentrations were determined by reference to a standard curve. The concentration of Ac-CoA is expressed as ng/mL of protein.
Colonic samples (20 µg proteins) were separated on an 8%, 10%, or 12% sodium dodecyl sulfate polyacrylamide gel and transferred to a polyvinylidene difluoride (PVDF) membrane, which was blocked with 5% non-fat milk and 0.1% Tween-20 in Tris-buffered saline for 1 h and then incubated overnight at 4 °C with primary antibodies against G protein-coupled receptor (GPR) 41 (1:500; Signalway Antibody LLC, College Park, MD, USA), GPR 43 (1:500; Sigma-Aldrich Corporation), histone deacetylation 1/2 (HDAC1/2; 1:1500; Abcam, Cambridge, MA, USA), occludin (1:2000; Abcam), claudin 1 (1:500; Santa Cruz Biotechnology, Inc.), interferon regulatory factor 4 (IRF4; 1:1000; Cell Signaling Technology, Inc., Danvers, MA, USA), NLR family, pyrin domain containing 3 (NLRP3; 1:1000; Abcam), vascular cell adhesion molecule 1 (VCAM1; 1:500; Santa Cruz Biotechnology, Inc.), retinoid acid receptor-related orphan receptor gamma t (RORγt, 1:500; Santa Cruz Biotechnology, Inc.), transforming growth factor β1 (1:1000, Abcam), signal transducer and activator of transcription 3 (STAT3; 1:1000; Cell Signaling Technology), phospho-STAT3 (p-STAT3, Tyr705; 1:1000; Cell Signaling Technology), NADH dehydrogenase subunit 4 (ND4; 1:1000; Signalway Antibody LLC), cytochrome c oxidase subunit 1 (COX1; 1:1000; Abcam), interleukin (IL)-1β (1:500; Invitrogen Corporation, Carlsbad, CA, USA), IL-6 (1:300; Santa Cruz Biotechnology, Inc.), IL-10 (1:300; Santa Cruz Biotechnology, Inc.), IL-17 (1:300; Santa Cruz Biotechnology, Inc.), IL-23 (1:300; Santa Cruz Biotechnology, Inc.), voltage-dependent anion-selective channel 1 (VDAC-1; 1:1000; Santa Cruz Biotechnology, Inc.), glyceraldehyde 3-phosphate dehydrogenase (GAPDH; 1:5000; Abcam), and β-actin (1:5000, Abcam), followed by incubation with a horseradish peroxidase-conjugated goat anti-rabbit or mouse secondary antibody against immunoglobulin G for 1 h at room temperature. The antibody-protein complexes were detected using an enhanced chemiluminescent substrate solution (EMD Millipore Corporation, Billerica, MA, USA) and quantified based on optical density against GAPDH as a control. For mitochondria, VDAC1 was employed as the loading control. The extent of phosphorylation of each protein was evaluated with respect to the abundance of the native form (p-STAT3/STAT3).
Briefly, 200 µg of colonic homogenate were incubated with 3 µg of IRF4 antibody at 4 °C overnight. Protein G-Sepharose beads (Sigma-Aldrich Corporation) were prewashed three times in IP buffer (10 mMTris-Cl, pH 7.5, 150 mM sodium chloride, 2 mM EDTA, 0.5% Triton-100) for 15 min and incubated with a protein/antibody mixture under constant rotation at 4 °C for 2 h. The precipitant was centrifuged at 10,000 × g for 1 min and washed three times with IP buffer to remove nonspecifically bound proteins. Afterward, the immune-complexed beads were resuspended in sodium dodecyl sulfate–polyacrylamide gel electrophoresis loading buffer, heated at 95 °C for 5 min, and then removed by centrifugation at 10,000 × g. The supernatants were collected for immunoblot detection of IRF4 and STAT3 with homogenates and without IP buffer as input controls.
Single-lymphocyte suspensions were harvested from the lamina propria colon tissues of rats for flow cytometry, which was conducted with the following gating strategy: lymphocytes → single cells → live cells → CD4 + cells. Briefly, after washing with sterile PBS, the tissues were cut into pieces, which were then subjected to enzymatic treatment using 0.125 mg/mL of Liberase™ Thermolysin Medium (Sigma-Aldrich Corporation) and 0.5 mg/mL of DNase I for 20 min. Cells were filtered through a sieve with 100-μm pores. Filtration of digestive juices was terminated by the addition of 500 μL of fetal bovine serum. The remaining tissue fragments were processed as described above. Cells were collected by filtering through a sieve with 40-μm pores. After centrifugation at 500 × g for 5 min at room temperature, the supernatant was discarded and the cells were resuspended in PBS containing 2% fetal bovine serum. Prior to intracellular cytokine staining, 10
For observation of mitochondria, fresh slices of colon tissue, approximately 1 mm thick, were fixed in 2.5% glutaraldehyde overnight at 4 °C, then washed three times with 0.1 M PBS and postfixed in 1% osmium tetroxide at 4 °C for 2 h. Afterward, the blocks were dehydrated in graded ethanol and embedded in epoxy resin. Randomly selected ultrathin sections were poststained with uranyl acetate and lead citrate and examined under an electron microscope (Koninklijke Philips N.V., Amsterdam, Netherlands).
The microbiome population, targeted metabolomics, and RNA sequencing statistics are described in detail above. Excluding these, the data are presented as the mean ± standard deviation (SD). Statistically significant differences between the means of two or more independent (unrelated) groups were identified by one-way analysis of variance, followed by post-hoc analysis with Dunnett's test. A probability (p) value of less than 0.05 was considered statistically significant (Fig. 1).
Sequencing of the 16S rRNA gene was conducted at 12 weeks after BCCAo. In this study, the observed_species and Shannon diversity indices were used to evaluate the diversity of the gut microbiota. CCH significantly decreased the number of observed species and Shannon diversity (observed species: p < 0.001; Shannon: p = 0.004). However, FMT partially reversed the decreased number of observed species (p = 0.02, Fig. 2A). NMDS analysis was conducted to visualize differences in the taxa of the gut microbiota among the four groups. The results revealed that BCCAo induced a marked difference in gut microbiota composition as compared with the healthy control group, whereas CCH induced significant changes in the gut microbiota of the BCCAo + FMT and BCCAo + SCFAs groups (Fig. 2B). Analysis of similarity using the Bray–Curtis dissimilarity matrix revealed clear compositional differences in gut microbiota between the sham-operated and BCCAo groups, BCCAo and BCCAo + FMT groups, and BCCAo and BCCAo + SCFAs groups. Of the top 10 gut microbiota at the genus level, as compared with the sham-operated group, BCCAo significantly increased the relative abundance of Prevotellaceae_NK3B31_group and [Eubacterium]_siraeum_group, and lowered that of
Graph: Fig. 2 FMT and SCFAs treatment ameliorate CCH-induced gut microbial dysbiosis. A Analysis of alpha diversity by shannon index and observed_species. B Analysis of beta diversity by non-metric multi-dimensional scaling (NMDS). C Relative abundance of top 10 gut microbiota at the genus level. D Heatmap based on nonparametric Wilcoxon test by MetaStat showing relative abundance of gut microbiota at the genus level. E Analysis of significant difference in abundance of gut bacteria by Linear discriminant analysis (LDA) coupled with effect size (LEfSe). Data are expressed as mean ± SD (n = 8 per group). *P < 0.05 vs. sham group. #P < 0.05 vs. BCCAo group
According to these data, CCH rats developed gut microbial dysbiosis with prolonged CCI by decreasing the richness, diversity, and composition of the gut microbiota, while FMT and SCFA replenishment modulated CCH-induced gut microbial disruption by increasing the abundance of some species, including Ruminococcaceae and Clostridia_UCG_014.
To determine whether changes to the bacterial communities impacted the concentrations of SCFAs in fecal samples and colon tissues, the concentrations of SCFAs were measured with a targeted metabolomics assay. Consistent with the changes to the microbial community structure and composition, CCH, FMT, and SCFAs induced different profiles in SCFAs, especially between the sham-operated and BCCAo, BCCAo and BCCAo + FMT, and BCCAo and BCCAo + SCFAs groups, as determined by OPLS-DA (Fig. 3C, D). Specifically, the concentrations of acetic acid and propionic acid in fecal samples were significantly higher in the BCCAo + FMT and BCCAo + SCFAs groups than the BCCAo group (p
Graph: Fig.3 FMT and SCFAs treatment increase CCH-induced metabolite SCFAs. A Analysis of fecal SCFAs concentration by gas chromatography-mass spectrometry (GC-MS) (n = 8 in sham, BCCAo and BCCAo + FMT group; n = 6 in BCCAo + SCFAs group). B Analysis of colonic SCFAs concentration by GC-MS (n = 5 per group). C, D Segregation trends of fecal and colonic SCFAs evaluated by orthogonal partial least squares discriminant analysis (OPLS-DA) respectively. E, F Spearman correlation analysis between gut microbiota and metabolite SCFAs using fecal samples. Data are expressed as mean ± SD. *P < 0.05 vs. sham group. #P < 0.05 vs. BCCAo group. In E, F, *P < 0.05, **P < 0.01
To clarify whether the increased metabolism of SCFAs was caused by alterations to the gut microbiota following FMT and SCFA administration, Spearman correlation analysis was conducted using data from the fecal samples. The results showed that acetic acid was positively associated with Ruminococcus_sp_N15_MGS_57 and Prevotella, and negatively related to Lachnospiraceae and Lachnospirales. Moreover, propionic acid was positively correlated with Ruminococcus and Ruminococcus_sp_N15_MGS_57. However, interestingly, Lachnospiraceae and Lachnospirales were positively correlated with butyric acid production, while Prevotella was negatively correlated (Fig. 3E, F).
Taken together, these results revealed that the levels of acetic acid and propionic acid were significantly elevated in fecal samples after FMT and SCFA administration. Notably, acetic acid was the only markedly increased metabolite identified in the colon tissues after FMT and SCFA treatment, suggesting that this SCFA might drive the effects of FMT and SCFA treatment against CCH-induced colon dysfunction. Ruminococcus_sp_N15_MGS_57, an established gut microbial biomarker after FMT, was positively associated with acetic acid after FMT and SCFA treatment, indicating that Ruminococcus_sp_N15_MGS_57 may be partially responsible for the increased production of acetic acid after FMT and SCFA treatment in response to CCI.
To determine the effects of FMT and SCFA treatment on colonic barrier function, morphological changes and the expression levels of tight junction proteins and MUC2, as the major component of the colonic mucus layer, were assessed. Furthermore, SCFAs may influence microbe-gut-brain interactions by signaling to the host via G protein-coupled receptors and inhibition of HDAC. Therefore, the protein levels of GPR41, GPR43, and HDAC1/2 were measured in colon tissues. The average weight of male rats at 18 weeks notably decreased from 609 ± 14 to 496 ± 8 g (p < 0.01) after BCCAo and then returned to 564 ± 10 g (p < 0.01) following FMT treatment and 534 ± 8 g (p < 0.01) after SCFA administration (Fig. 4A). Colon tissues stained with HE showed excessive mucosal damage in BCCAo group, which were seldom found in BCCAo + FMT and BCCAo + SCFAs groups (Fig. 4B). Moreover, CCH significantly decreased the number of MUC2-positive cells and the expression levels of tight junction proteins, such as claudin 1 and occludin. Nevertheless, FMT and SCFA replenishment eliminated these changes (Fig. 4C–F). These results indicate that CCH impaired colonic barrier function, markedly reduced the protein levels of GPR41 and GPR43, and aggravated overexpression of HDAC1/2, which were ameliorated by FMT and SCFA treatment (Fig. 4E, F), suggesting alleviation of colonic barrier dysfunction via activation of GPR41 and GPR43 and inhibition of HDAC.
Graph: Fig. 4 FMT and SCFAs treatment alleviate CCH-induced impaired colonic barrier. A Evaluation of body weight. B Representative HE staining in colon (scale bars = 50 µm). C Representative immunofluorescence staining for MUC2 in colon (scale bars = 50 µm). red: MUC2; blue: DAPI. D Relative level of MUC2-positive cells (ratio of sham group, n = 5 per group). The average area of MUC2-positive puncta in sham group is set to 1. E Representative western blot for GPR41, GPR43, HDAC1/2, occludin, claudin1, and GAPDH in colon. F Relative optical density analysis for GPR41, GPR43, HDAC1/2, occludin, claudin1, and GAPDH in colon (n = 4 per group). Data are expressed as mean ± SD. *P < 0.05 vs. sham group. #P < 0.05 vs. BCCAo group
Transcriptome analysis was performed to explore the potential molecular mechanisms by which FMT and SCFA treatment promote functional recovery of colonic tissues after CCH. Compared with BCCAo group, GO analysis between the BCCAo + FMT and BCCAo groups showed that FMT was associated with a down-regulation of the pathways related with the production of the cytokines IL-1β, IL-6, and IL-17, the immune response of Th17 cells, and regulation of HDAC, while ATP synthesis coupled electron transport, mitochondrial ATP synthesis coupled electron transport, respiratory ETC, and oxidative phosphorylation were markedly enhanced (Fig. 5A). Furthermore, KEGG analysis illustrated that FMT strikingly inhibited Th17 cell differentiation, cell adhesion molecules, and the T cell receptor and NF-kappa B (NF-κB) pathways (Fig. 5A). Similar to FMT, SCFA replenishment significantly weakened regulation of cell–cell adhesion, IL-1 and IL-17 production, differentiation and immune response of Th17 cells, and regulation of HDAC pathways, but notably strengthened ATP synthesis coupled electron transport, mitochondrial ATP synthesis coupled electron transport, respiratory electron transport chain, mitochondrial respiratory chain complex I/III/IV, oxidative phosphorylation, oxidoreductase activity, NADH dehydrogenase activity, and cytochrome-c oxidase activity (Fig. 5C). Moreover, SCFA treatment significantly attenuated Th17 cell differentiation, cell adhesion molecules, and the T cell receptor and NF-κB pathways, but promoted oxidative phosphorylation (Fig. 5C). In addition, GSEA found that SCFA treatment significantly modified pathways associated with the Ac-CoA metabolic process, oxidative phosphorylation, and respiratory chain complex IV (Fig. 5E). These results indicate that both SCFA treatment and FMT were associated with signaling of IL-1β, IL-6, and IL-17, Th17 cell differentiation, regulation of HDAC, cell adhesion molecules, NF-κB pathway, ATP synthesis coupled electron transport, respiratory ETC, and oxidative phosphorylation.
Graph: Fig. 5 The potential molecular mechanisms involved in the FMT and SCFAs treatment in colon. A, C Histogram of the significantly enriched GO or KEGG terms in BCCAo group vs. BCCAo + FMT group and BCCAo group vs. BCCAo + SCFAs group respectively according to RNA sequencing datasets. The horizontal coordinate represents − log10 (p-value), the vertical coordinate represents GO or KEGG names. B, D Volcano plots showing partial differentially expressed genes (DEGs) in the above pathways we are interested in in BCCAo group vs. BCCAo + FMT group and BCCAo group vs. BCCAo + SCFAs group respectively according to RNA sequencing datasets. The horizontal axis indicates log2 (fold change), the vertical axis indicates −log10 (p-value). Some DEGs passed the verification of western blot are marked with names. E Gene set enrichment analysis (GSEA) performed in BCCAo group vs. BCCAo + SCFAs group based on RNA sequencing datasets. The total height of the curve reflects the extent of enrichment, the normalized enrichment score (NES) and norminal p value are indicated
Overall, 850 differentially expressed genes (DEGs) were upregulated and 330 were downregulated between the BCCAo + FMT and BCCAo groups, while 876 DEGs were upregulated and 1395 were downregulated between the BCCAo + SCFAs and BCCAo groups. Of note, the DEGs ND4, COX1, IRF4, NLRP3, and VCAM1 verified by western blot analysis were associated with cytokine-mediated signaling, including production of IL-1β and IL-17, Th17 cell differentiation, cell adhesion molecules, respiratory ETC, and oxidative phosphorylation (Figs. 8A and 9F).
The significant modification of cytokine-mediated signaling, including IL-1β, IL-6, and IL-17 production and Th17 cell differentiation pathways after FMT and SCFA treatment demonstrated that Treg/Th17 balance plays a fundamental role in stabilizing immune homeostasis in colon tissues. To reveal the impact of FMT and SCFA treatment on the balance of Tregs and Th17 cells, colon tissues were harvested from all four groups for flow cytometry. The relative abundance of each cell type was reported as a percent of CD4
Graph: Fig. 6 FMT and SCFAs treatment improve colonic Treg/Th17 balance. A Representative plot of Th17 cells analyzed by flow cytometry and scatter diagram of the percentage of Th17 cells in colon. B Representative plot of CD4+IL-10+ cells analyzed by flow cytometry and scatter diagram of the percentage of CD4+IL-10+ cells in colon. C Representative plot of Treg cells analyzed by flow cytometry and scatter diagram of the percentage of Treg cells in colon. D Representative plot of FOXP3+IL-10+ cells analyzed by flow cytometry and scatter diagram of the percentage of FOXP3+IL-10+ cells in colon. Data are expressed as mean ± SD (n = 3 per group). *P < 0.05 vs. sham group. #P < 0.05 vs. BCCAo group
Recent evidence indicates that cytokines regulate the differentiation of pathogenic and non-pathogenic Th17 cells [[
Graph: Fig. 7 FMT and SCFAs treatment decrease pathogenic- Th17 cells differentiation. A Representative western blot for IL-1β, IL-6, IL-10, IL17A, IL-23 and GAPDH in colon. B Relative optical density analysis for IL-1β, IL-6, IL-10, IL17A, IL-23 and GAPDH in colon. Data are expressed as mean ± SD (n = 4 per group). *P < 0.05 vs. sham group. #P < 0.05 vs. BCCAo group
Graph: Fig. 8 FMT and SCFAs treatment inhibit CCH-induced inflammatory IL-17 pathways in colon. A Representative western blot for TGFβ1, IRF4, RORγT, NLRP3, VCAM1, p-STAT3, STAT3 and GAPDH in colon. B Relative optical density analysis for TGFβ1, IRF4, RORγT, NLRP3, VCAM1, p-STAT3, STAT3 and GAPDH in colon (n = 4 per group). C The protein–protein interaction network downloaded from the STRING database indicated the interactions among the candidate genes. D Representative immunoprecipitation (IP) for IRF4, STAT3 and GAPDH in colon. (E) Relative ratio of STAT3 in IP complex and STAT3 in whole cell lysates in colon (n = 3 per group). The relative abundance of STAT3 in IP complex is determined by western blotting, and compared to the level of STAT3 in whole cell lysates. Data are expressed as mean ± SD. *P < 0.05 vs. sham group. #P < 0.05 vs. BCCAo group
Transcription factor IRF4 is essential for differentiation of Th17 cells [[
To explore the potential interactions among candidate proteins, functional enrichment analysis of protein–protein interaction networks was conducted using the STRING database. The results demonstrated that the transcription factor STAT3 might play an important role in these interactions (Fig. 8C). Co-IP and MS analyses were performed to further determine whether these molecular mechanisms of FMT and SCFA treatment were involved in the differentiation of pathogenic Th17 cells and inflammatory signaling of IL-17, which showed that STAT3 interacted with IRF4 following CCH. This result was confirmed by the IP with an antibody against IRF4 (Fig. 8D, E). The relative abundance of STAT3 in the IRF4/STAT3 complex was compared to that in whole-cell lysate. As compared with the sham-operated group, CCH significantly increased the level of STAT3 in IP complex/STAT3 in whole-cell lysate. Notably, there was no significant difference in the total abundance of STAT3 between the sham-operated and CCH groups, while the level of p-STAT3 was markedly increased after CCH treatment. These results showed that CCH promoted formation of the IRF4/STAT3 complex and phosphorylation of STAT3 (Fig. 8A, B, D, E), leading to chronic inflammation of colon tissues. However, FMT and SCFA treatment induced the dissociation of IRF4 and STAT3 and decreased the phosphorylation of STAT3, resulting in inhibition of chronic inflammation of colon tissues.
Considering that modules upregulated in the RNA-seq dataset were mainly enriched in mitochondrial respiratory ETC and oxidative phosphorylation after FMT and SCFA treatment, mitochondrial membrane potential, ultrastructural changes, and ROS production were evaluated in colon tissues. As compared with the sham-operated group, CCH significantly increased ROS accumulation, but decreased the ratio of red/green fluorescence intensity induced by staining for JC-1 (Fig. 9D, H). Analysis of the mitochondrial ultrastructure showed that CCH induced abnormal mitochondrial swelling and vague cristae (Fig. 9E), thereby confirming mitochondrial dysfunction. Then, to determine whether and how FMT and SCFA treatment regulate mitochondrial ETC function, the activities of ETC complexes I–V and ATP content were assessed in colon tissues. As compared to the sham-operated group, CCH administration markedly reduced the activities of NADH dehydrogenase (complex I), succinate-coenzyme Q reductase, cytochrome c reductase, cytochrome c oxidase, and ATPase and the subsequent decrease in ATP content (Fig. 9A, B). Acetate was the prominent metabolite of SCFAs following FMT and SCFA treatment in this study. As administration of CCH can result in a state of hypoxia or glucose deprivation, acetate could serve as an important source of Ac-CoA [[
Graph: Fig. 9 FMT and SCFAs treatment relieve CCH-induced colonic mitochondrial dysfunction. A The activities of electron transport chain complex I-V in colon (n = 5 per group). B The content of ATP in colon (n = 5 per group). C The content of acetyl coenzyme A in colon (n = 5 per group). D Representative DHE fluorescence staining for ROS and relative level of ROS in colon (ratio of sham group, n = 3 per group, scale bars = 20 μm). The average area of ROS-positive puncta in sham group is set to 1. E Representative electron micrographs of mitochondria in colon (scale bars = 0.5 µm). F Representative western blot for ND4,COX1 and VDAC1 in colon. G Relative optical density analysis for ND4,COX1 and VDAC1 in colon (n = 4 per group). H Representative JC-1 fluorescence staining for mitochondrial membrane potential (scale bars = 50 µm). Impaired mitochondria: low intensity of red fluorescence but high intensity of green fluorescence. Healthy mitochondria: high intensity of red fluorescence but low intensity of green fluorescence. Data are expressed as mean ± SD. *P < 0.05 vs. sham group. #P < 0.05 vs. BCCAo group
To the best of our knowledge, the present study is the first to report that FMT and SCFA replenishment ameliorated CCH-induced gut microbial dysbiosis by increasing the proportion of Ruminococcus_sp_N15_MGS_57, which may promote microbial metabolism of SCFAs, resulting in increased production of acetic acid and subsequent alterations to mitochondrial energy metabolism in colon tissues by promoting mitochondrial ETC and oxidative phosphorylation. Furthermore, FMT and SCFA administration reversed the CCH-induced imbalance in Tregs and Th17 cells by inhibiting differentiation of pathogenic Th17 cells and the IL-17 pathway, resulting in alleviation of impaired barrier function and chronic inflammation in colon tissues. In aggregate, these results indicate that FMT and SCFA replenishment constitute a promising therapeutic strategy for the treatment of colonic dysfunction due to CCI.
Prior reports revealed the impact of acute ischemic stroke on gut dysfunction and intestinal dysbiosis, highlighting the delicate interplay between intestinal injury and the intestinal microbiota [[
Tregs act as dedicated inhibitors of diverse inflammatory responses through Th17 suppression and anti-inflammatory cytokine IL-10 secretion [[
In a state of CCH, the activated NLRP3 inflammasome regulates the production of IL-1β [[
In the mitochondria, NADH generated in the tricarboxylic acid cycle enters the ETC, leading to oxidative phosphorylation and subsequent production of ATP, which is important to the physiological and biochemical activities of all cells [[
Histone acetyltransferase (HAT) and HDAC are enzymes that control the state of histone acetylation. Long-held belief indicates that SCFAs promote histone acetylation by inhibiting HDAC [[
There were several limitations to this study that should be addressed. First, the effects of FMT and SCFA treatment on brain tissues after CCH remain unclear. Second, cerebral blood flow was not measured in this study, which prevented assessment of successful ischemia among the three BCCAo groups. Third, 16S rRNA gene expression analysis after antibiotic treatment is needed to verify that antibiotic treatment depleted the gut microbiota. Furthermore, considering that antibiotic treatment or salt alone could affect gut dysfunction, control groups would be needed to determine whether antibiotic treatment or salt-matched control had amplified the effects of FMT and SCFA treatment, respectively. Fourth, only colon tissues were examined, thus further studies are needed to validate the effects in colonic Th17 cells. Fifth, although there is presently no appropriate cell model of CCI, determination of the oxygen consumption rate using appropriate CCI cells would effectively complement the results of oxidative phosphorylation. Lastly, SCFA treatment not only inhibited the production of pro-inflammatory cytokines, but also prevented migration and recruitment of immune cells to endothelial cells, which is an important step in the development of inflammatory diseases [[
In summary, these findings showed that CCH modified the composition of the gut microbiota and the production of metabolites of SCFAs that might be associated with inhibition of mitochondrial ETC activities and oxidative phosphorylation, leading to dysregulation of mitochondrial energy metabolism. Besides, CCH induced differentiation of pathogenic Th17 cells, formation of IRF4/STAT3 complexes, and phosphorylation of STAT3, in association with an impairment of the colonic barrier and chronic colonic inflammation. In contrast, FMT and SCFA replenishment ameliorated CCH-induced gut microbial dysbiosis by increasing the intestinal abundance of Ruminococcus_sp_N15_MGS_57 and modulating microbial metabolism of SCFAs by increasing the acetic acid content. This was associated by an improvement of the balance between Tregs and Th17 cells, mitochondrial ETC activities, and oxidative phosphorylation to prevent colonic inflammation and dysregulation of mitochondrial energy metabolism in response to CCH. Collectively, these findings highlight the potential therapeutic effects of FMT and SCFA replenishment against colonic dysfunction after CCI.
Not applicable.
SSH, WYF and HJ conceived and designed this work. WYF, LQ, ZL and WDP performed the experiments. WYF and WDP performed the data analysis. SSH and HJ wrote the manuscript. All authors read and approved the final manuscript.
This work was supported by National Natural Science Foundation of China (Grant No: 81974209, 81601146 and 81771410).
The 16S rRNA gene sequencing and RNA-seq data were uploaded in BioProject database (https://
Experimental protocols and procedures were approved by the Committee for Animal Experimentation of Tongji Hospital.
Not applicable.
The authors have declared that they have no competing interests.
• CCH
- Chronic cerebral hypoperfusion
• SCFAs
- Short-chain fatty acids
• FMT
- Fecal microbiota transplantation
• BCCAo
- Bilateral common carotid artery's occlusion
• HDAC
- Histone deacetylation
• GC-MS
- Gas chromatography-mass spectrometry
• DEGs
- Differential genes
• KEGG
- Kyoto encyclopedia of genes and genomes
• GO
- Gene ontology
• GSEA
- Gene set enrichment analysis
• ATP
- Adenosine triphosphate
• NADH-DH
- NADH dehydrogenase
• SQR
- Succinate-coenzyme Q reductase
• CCR
- Cytochrome c reductase
• CCO
- Cytochrome c oxidase
• ATPase
- ATP synthase
• ETC
- Electron transport chain
• HE
- Hematoxylin and eosin
• DHE
- Dihydroethidium
• ELISA
- Enzyme-linked immunosorbent assay
• IRF4
- Interferon regulatory factor 4
• NLRP3
- NLR family, pyrin domain containing 3
• VCAM1
- Vascular cell adhesion molecule 1
- TGFβ1
- Transforming growth factor β1
• COX1
- Cytochrome c oxidase subunit 1
• ND4
- NADH dehydrogenase subunit 4
- RORγt
- Retinoid acid receptor-related orphan receptor gamma t
• STAT3
- Signal transducer and activator of transcription 3
• FOXP3
- Forkhead box P3
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By Shao-Hua Su; Yi-Fang Wu; Qi Lin; Lin Zhang; Da-Peng Wang and Jian Hai
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