Gut microbiota from mice with cerebral ischemia-reperfusion injury affects the brain in healthy mice

Results

Differences in microbiota composition between mice^control and mice^BCCAO

First, we assessed the microbiota composition of feces from mice^control and mice^BCCAO. We performed a metagenomic analysis to reveal the gut microbiota compositions at the phylum and genus levels in both groups. 15 days after fecal microbiota transplantation, the gut microbial composition in mice^control and mice^BCCAO was 47.52% vs. 53.85% Bacteroidetes, 42.29% vs. 42.05% Firmicutes, 2.49% vs. 2.24% Proteobacteria, 6.21% vs. 0.03% Verrucomicrobia, 0.50% vs. 0.35% Actinobacteria, 0.08% vs. 0.43% Tenericutes, 0.10% vs. 0.25% Deferribacteres, and 0.80% vs. 0.81% other phyla. After 29 days, there were 48.43% vs. 70.07% Bacteroidetes, 47.49% vs. 23.19% Firmicutes, 2.56% vs. 2.70% Proteobacteria, 0.01% vs. 1.11% Verrucomicrobia, 0.49% vs. 0.22% Actinobacteria, 0.67% vs. 1.38% Tenericutes, 0.03% vs. 0.23% Deferribacteres, and 0.33% vs. 1.09% other phyla in the gut of mice^control and mice^BCCAO (Figure 1A). The relative abundance of Firmicutes significantly decreased, while the percentage of Bacteroidetes significantly increased in mice^BCCAO compared to mice^control 29 days after transplantation (Figure 1B). Moreover, mice^BCCAO showed a remarkably decreased ratio of Firmicutes to Bacteroidetes on the 29th day (Figure 1C). We performed a principal component analysis (PCA) to determine the influence of baicalin treatment on the gut microbial populations at the phylum level. The plot of principal component 1 (PC1) against PC2 showed that each group formed a distinct cluster; mice^BCCAO clustered separately from mice^control (Figure 1D). Linear discriminant analysis effect size (LEfSe) test was used to assess the microbiota alterations after BCCAO microbiota treatment. The structure and predominant microbiota in both groups were represented as a cladogram (Figure 2A). The LEfSe analysis showed that 20 genera differed in relative abundance between the two experimental groups with linear discriminant analysis (LDA) score > 3.0 and P_unadjusted < 0.05 (Figure 2B). These genera belonged to the phyla Bacteroidetes (7/20), Firmicutes (9/20), Proteobacteria (3/20), and Cyanobacteria (1/20). In total, 10 genera were enriched in mice^BCCAO, while 10 other genera were more abundant in mice^control. From the genera enriched in mice^BCCAO, 3 belonged to the family of Prevotellaceae within the phylum Bacteroidetes (including Prevotellaceae_UCG_001, Prevotellaceae_NK3B31_group, Pasteurella), 2 belonged to the order of Lactobacillales (including Enterococcus and Streptococcus), and 2 belonged to the order of Clostridiales (including Peptococcus and Caproiciproducens) within the phylum Firmicutes. These results indicated that the BCCAO microbiota colonization negatively impacted the mice's gut microbiota.

Figure 1. Microbial analyses on the phyla level. (A) Sankey graph showing changes in gut microbial composition on the 15th and 29th day after fecal microbiota transplantation. (B) Percent of community abundance on the phyla level. Firm. means Firmicutes, Bact. means Bacteroidetes, Prot. means Proteobacteria, Verr. means Verrucomicrobia, Acti. means Actinobacteria, Tene. means Tenericutes, Defe. means Deferribacteres. (C) Ratio of Firmicutes and Bacteroidetes on the 15th and 29th days. (D) Principal component analysis (PCA) plot of weighted UniFrac distances showing a clear separation in microbial composition between mice^control and mice^BCCAO. *** denotes P < 0.001 compared with control mice using a two-way repeated-measures ANOVA with post-hoc Tukey multiple comparisons test. All values are expressed as means ± S.D; n=15.

Figure 2. Microbial analyses. (A) The central point represents the root of the tree (bacteria), and each ring represents the next lower taxonomic level (phylum to genus). The diameter of each circle represents the relative abundance of the taxon. (B) The different bacterial genera between mice^control and mice^BCCAO using linear discriminant analysis effect size (LEfSe) analysis, linear discriminant analysis (LDA) score > 3.0, P < 0.05 unadjusted; n=15.

Decreased functional connectivity in mice^BCCAO

Next, we compared the brain ROIs based on rs-fMRI to evaluate the effect of BCCAO microbiota colonization on the brain FC patterns. The ROIs were chosen based on the results of rs-fMRI and included auditory cortex (AC), cingulate cortex (CC), hippocampus (HC), motor cortex (MC), orbitofrontal cortex (OC), somatosensory cortex (SC), thalamus (T), and visual cortex (VC). The functional connections between these ROIs are shown in the virtual graphs (Figure 3A). The results show decreased FC in the cingulate cortex, hippocampus, and thalamus of mice^BCCAO compared to control mice (Figure 3B). We found no changes in FC correlation analysis between each ROIs in the correlation matrices (Figure 3C, 3D). These data indicated that BCCAO microbiota colonization decreased the brain FC in mice^BCCAO.

Figure 3. Effect of BCCAO microbiota on brain structure and function. (A) Virtual graphics show brain functional connectivity (FC) in mice^control and mice^BCCAO. (B) The mean functional connectivity strength per brain network. * denotes P < 0.05 compared with control mice using a two-way repeated-measures ANOVA with post-hoc Tukey multiple comparisons test. All values are expressed as means ± S.D; n=15. (C) The mean FC matrices show the strength of functional connectivity between pairs of brain regions in control and BCCAO-treated groups. The color scale represents the strength of functional connectivity. (D) Correlation analyses of 8 regions of interest (ROIs) in the mouse brain. The brain regions analyzed include orbitofrontal cortex (OC), cingulate cortex (CC), somatosensory cortex (SC), thalamus (T), hippocampus (HC), motor cortex (MC), auditory cortex (AC), and visual cortex (VC).

Increased anxiety and memory deficits in mice colonized with BCCAO microbiota

Next, we explored the effect of mouse BCCAO microbiota on the behavior of healthy mice. In the open field test (OFT), we assessed the spontaneous locomotor activity. Compared to control mice, mice^BCCAO spent more time in the corners, and less time in the center (Figure 4A). There was no difference in the time spent in the periphery arena. The increased time spent in the corners in mice^BCCAO indicated increased anxiety. The crunching of harmless objects, such as cotton or soft papers to build a nest, has been associated with compulsive or natural behavior. However, the nest building test did not show any differences in nest building scores between mice^control and mice^BCCAO (Figure 4B).

Figure 4. Effect of BCCAO microbiota on mice behavior. (A) Time spent in the center (left), corner (middle), and periphery (right) of the open field test. (B) The nest-building scores of mice^control and mice^BCCAO. (C) The latency in the training and testing phases for mice^control and mice^BCCAO in the Morris water maze test. (D) The preferential index (%) after 1 hour (left) and 24 hours (right) of training in the testing phase of the novel object recognition test. * denotes P < 0.05, ** denotes P < 0.01 and *** denotes P < 0.001 compared with control mice using unpaired Student`s t-tests or a two-way repeated-measures ANOVA with post-hoc Tukey multiple comparisons test. All values are expressed as means ± S.D, n=15.

To examine spatial learning and memory, and object recognition memory, we performed the Morris water maze (MWM) test and the novel object recognition (NOR) test. During the training and testing phases of the MWM test, mice^BCCAO showed significantly longer escape latencies compared to control mice (Figure 4C). Besides, mice^BCCAO demonstrated a significantly lower preferential index compared to mice^control in the NOR test using the 1-hour interval between training and testing phases; however, there was no difference when the interval between training and testing phases was 24 hours (Figure 4D). These findings showed that oral treatment with BCCAO microbiota declined spatial learning and memory, and decreased short-term object recognition memory in mice.

Decreased hippocampal neuronal plasticity in BCCAO microbiota-colonized mice

To investigate the effect of BCCAO microbiota colonization on hippocampal neuronal plasticity, we assessed dendritic spine density with the Golgi staining. Golgi staining displayed neuropathological modifications in the hippocampal region in mice^BCCAO (Figure 5A), and indicated a significant decrease in the dendritic spine density in the hippocampus of BCCAO microbiota-colonized mice (Figure 5B). Moreover, the levels of synaptophysin (SYP) and PSD95 were significantly decreased in the hippocampal region in mice^BCCAO (Figure 5C).

Figure 5. Effect of BCCAO microbiota on hippocampal neuronal plasticity. (A) Representative confocal microscopic images of the Golgi-stained hippocampal regions in mice^control and mice^BCCAO. (B) Mean dendritic spine densities of the hippocampal neurons based on the analysis of Golgi-stained brain tissue sections of mice^control and mice^BCCAO. (C) Protein levels of synaptophysin (SYP) and PSD95 in the hippocampal region. *denotes P < 0.05 and ** denotes P < 0.01 compared to control mice using unpaired Student`s t-tests. All values are expressed as means ± S.D; n=15.

BCCAO microbiota colonization increases hippocampal neuroinflammation

Because of the observed differences in hippocampal neuronal plasticity, we next assessed the levels of pro-inflammatory cytokines G-CSF, GM-CSF, IL-1β, IL-2, IL-4, IL-5, IL-6, IL-17, IFNγ, IP-10, TNF-α, RANTES, MCP-1, eotaxin, and MIP-1β in the hippocampus by multiplex bead analysis. Mice^BCCAO had significantly increased levels of pro-inflammatory cytokines, including GM-CSF, IFNγ, IL-1β, IL-2, and TNF-α (Figure 6A). Principal component analysis (PCA) revealed that PC1 and PC2 grouped mice formed two distinct clusters (Figure 6B). To further investigate the effect of BCCAO microbiota colonization on neuroinflammation, average PCA scores were graphically illustrated (Figure 6C). This illustration revealed that the average neuroinflammation score was significantly different between mice^control and mice^BCCAO, indicating increased neuroinflammation in mice^BCCAO.

Figure 6. Effect of BCCAO microbiota on hippocampal neuroinflammation. (A) Levels of G-CSF, GM-CSF, IL-1β, IL-2, IL-4, IL-5, IL-6, IL-17, IFNγ, IP-10, TNF-α, RANTES, MCP-1, eotaxin, and MIP-1β in the hippocampus of mice^control and mice^BCCAO. (B) PCA of the data from multiplex bead analysis; each dot represents one mouse. (C) Mean PCA scores of mice with and without BCCAO microbiota. *, P < 0.05; **, P < 0.01; and ***, P < 0.001 compared with control mice using unpaired Student`s t-tests or a two-way repeated-measures ANOVA with post-hoc Tukey multiple comparisons test. All values are expressed as means ± S.D; n=15.

Changes in microbiota are associated with behavioral and neurobiological alterations

We investigated whether the microbiota changes described above (Figure 2) correlated with changes in behavioral and neurobiological characteristics, such as anxiety, cognition, fMRI measured FC, hippocampal neuronal plasticity, and neuroinflammation. The results are illustrated in Figure 7 (P < 0.01). FC strength of the cingulate cortex showed a positive correlation with the relative abundance of Odoribacter. Thalamus showed a negative correlation with the relative abundance of Proteus. Hippocampus showed a positive correlation with the relative abundance of Bartonella, Coprococcus_3, and a negative correlation with Erysipelatoclostridium, Pasteurella, and Proteus. The motor cortex showed a negative correlation with Ruminiclostridium_5 and norank_c_Cyanobacteria. In anxiety-like behavior, the time spent in the center of the open field showed a positive correlation with Coprococcus_3, Enterococcus, and a negative correlation with Pasteurella and Proteus. In cognitive behavior, nest building ability showed a positive correlation with Bartonella, and a negative correlation with Caproiciproducens and Proteus. Latency in the testing phase of the MWM test showed a positive correlation with Pasteurella and Proteus. Preferential index with 1-hour interval between training and testing phase showed a positive correlation with Coprococcus_3, and a negative correlation with Pasteurella. The preferential index (24 h) showed a positive correlation with Erysipelatoclostridium. In hippocampal neuronal plasticity, the levels of PSD95 protein showed a positive correlation with Coprococcus_3. The SYP protein showed a positive correlation with Bartonella and Coprococcus_3. The neuroinflammation status in the hippocampus showed a negative correlation with Bartonella, norank_c_Cyanobacteria, Coprococcus_3, and Odoribacter, and a positive correlation with Erysipelatoclostridium and Pasteurella.

Figure 7. Correlation between bacterial genera and key behavioral/neurobiological findings. Pearson correlation between relative taxa abundance and cognitive behavior test, fMRI measured FC, hippocampal neuronal plasticity, and neuroinflammation. All observed correlations were statistically significant (P < 0.01); strong correlations are indicated by large circles, and weaker correlations by small circles. The colors signify whether the correlation was negative (red) or positive (blue).

Materials and Methods

Mouse model of repeated cerebral ischemia-reperfusion

Forty-five male C57BL/6J mice (2-3 months of age) were received from the experimental animal center of Shandong University. Before BCCAO, the three or four mice per cage were group-housed in enriched, ventilated cages. The mice were randomly assigned to two groups, with the sham surgery group (n=20), BCCAO group (n=20). The model of repeated global cerebral ischemia was followed by reperfusion as previously described [60]. In short, mice were initially anesthetized with 4% isoflurane followed by intraperitoneal injections of 4 mg/kg xylazine and subsequently maintained with 1.5% isoflurane. The physique temperature was maintained at 37° C by a heating lamp. Bilateral carotid arteries were exposed by a midline incision on the anterior neck. Then, the common carotid arteries were isolated with 3-0 silk ligatures, and the arteries were occluded via microaneurysm clips for 30 min. The carotid artery was occluded two times, with a 10-minute interval between the two occlusions. The sham-operated mice acquired identical surgical procedures without ischemia.

Germ-free mice

Thirty male, C57BL/6J mice wild-type mice received from Cyeagen Biosciences Inc (Jiangsu, China) and made germ-free via hysterectomy rederivation. The animals were housed in aseptic cages, under normal laboratory conditions, with one-way airflow, sterile food, and sterile water. The behavioral and electrophysiological experiments were performed in the gnotobiotic isolators. The mice were randomly divided into two therapy groups. Littermates were assigned to intervention before the experiment. The therapy groups were concealed from everyone involved. Three or four animals were kept in cages. The mice were tested in three separate series (Batch 1: mice^control n=6, mice^BCCAO n=4; Batch 2: mice^control n=5, mice^BCCAO n=5; Batch 3: mice^control n=4, mice^BCCAO n=6; total mice^control: n=15, total mice^BCCAO n=15).

Preparation of BCCAO mice fecal samples for colonization

The fecal implantation was carried out as described somewhere else with slight modifications [61]. Briefly, BCCAO mice fecal samples were placed on ice after collection and stored at -80° C until processing. The fecal samples of BCCAO mice were organized for colonization by way of pooling equal quantities of fecal material. A total of 100 mg samples was returned to 1 ml of 0.1M sterile PBS. Before centrifugation at 700g for 5 min, the solution was mixed steadily for 10 s by a vortex. The supernatant was accumulated as transplantation material and kept at -80° C.

Experimental design

In total, forty male normal C57BL/6J mice (2-3 months of age) and 30 male germ-free C57BL/6J mice (1 month of age) were used in the study, blinded control. The study schedule is shown in Figure 8. The mouse model of repeated cerebral I/R injury was caused by BCCAO on day -8 of the test. The bacterial transplant material was organized from day -3 to 0. Germ-free mice were colonized with microbiota from BCCAO mice (mice^BCCAO) or sham-operated mice (mice^control) microbiota on day 1 via oral gavage for 30 days. The germ-free control group was colonized with gut microbiota from the mice^control group. On day 15 and 29, fresh fecal pellets were amassed between 9 a.m.to10 a.m., snap-frozen, and stored at -80° C till use. On day 26-28, MRI continuously scanned the animals in random order. On day 30, after the behavioral and MRI tests, mice were positioned in a closed chamber and euthanized by isoflurane inhalation and cervical dislocation to collect hemisphere, hippocampus, and plasma. All samples were saved in a 4% paraformaldehyde solution or at -80° C until use.

Figure 8. Study design. On day -8, the model of repeated global cerebral ischemia was induced by BCCAO. On day -3 to day 0, the BCCAO mice fecal samples for colonization were prepared. Germ-free mice were colonized with BCCAO mice or control mice microbiota on day 1 of the experiment. Fecal pellets were collected on days 15 and 29. The open-field test (OFT) was performed on day 13, the nest building test (NBT) on day 14, the Morris water maze test on days 18-23, and the novel object recognition test (NOR) on days 24 and 25. The mice underwent MRI on days 26, 27, or 28.

Open field test

Animals were placed in the center of the open field (40 × 40 × 25 cm) with white walls and were free to explore the area for 15 min. The trial was videoed through a behavior monitoring program (XinRan Technology, China). The exploration activities in the corners (10 × 10 cm) and center (20 × 20 cm) were mechanically recorded. Between tests, the experimental amenities were cleaned and removed odor by 70% ethanol.

Nest building test

The animals were kept in an individual and sterile testing container with one nestled (4 cm × 4 cm). The nesting scores were analyzed by three assessors the next morning, following a pre-determined scale (least: 1, best: 6).

Morris-water maze test

The Morris water maze test was measured on day 18-23. In the water maze test, the animals were positioned in a white circular pool filled with 30-cm-depth opaque water. A platform of diameter 6 cm was submerged below 1 cm of water’s surface in the target quadrant. The training and testing phases were 60 s. In the training phase, the mice were placed into the water facing the wall of the pool at one of the four quadrants for five consecutive days. Each mouse was allowed 60 s to find the hidden platform. If the mouse did not find the platform, it was gently led onto the hidden platform for 5 s. In the testing phase, the hidden platform was removed and the mice explored for 60 s. The time to find the hidden platform in the training and testing phase was recorded and analyzed.

Novel object recognition test

The test was performed on day 24 and 25. In general, each mouse was placed in the middle of an empty chamber (10 min) to be familiar with the testing condition. One-hour delay, mouse allowed to explore two same objects called A1 and A2 placed distantly from each other. After a 1-hour and 24-hour, a novel object (object B or C) was replaced by one of the objects A1. The preferential index $\text{(Preferential}\text{Index}=\frac{\text{exploration}\text{time}\text{for}\text{object}\text{B}\text{or}\text{C}}{\text{total}\text{amount}\text{of}\text{exploration}\text{of}\text{both}\text{objects}}\times 100)$ was calculated to measure non-spatial memory in 5 min phase.

Magnetic resonance imaging (MRI)

All MRI measurements were conducted on a 7.0 T Biospec small animal MRI system (Bruker BioSpin, Germany) with the Paravision 6.0 software platform (https://www.bruker.com/en.html), using a two-element receive-transmit cryogenic quadrature coil. Isoflurane (1.5~2.0%) was used for anesthesia. T₂-weighted echo-planar imaging sequences were used to acquire MRI data with the following parameters: echo time=35 ms, the field of view=100 mm², acquisition matrix=256 × 256, repetition time=3150 ms, echo train length=8, 28 slices of 0.4 mm. Resting-state functional MRI (rs-fMRI) was performed to assess functional connectivity (FC) between specific regions of interest (ROI) that support numerous cognitive processes: auditory cortex (AC), cingulate cortex (CC), hippocampus (HC), motor cortex (MC), orbitofrontal cortex (OC), somatosensory cortex (SC), thalamus (T), and visual cortex (VC). Rs-fMRI signals were acquired by a T₂-weighted single-shot echo-planar imaging sequence. The rs-fMRI data analysis was performed using a statistical parametric mapping (SPM) mouse toolbox, which extended the functionality of SPM5 [62]. All selected ROIs were imported into the REST toolbox [63]. FC group comparison between ROIs was tailored software for MATLAB2019, which allowed for z-transform by an in-house program and exported of an FC strength correlation matrix. These independently transformed zFC-maps were loaded into SPM12 and average zFC-maps were analyzed.

Microbiota methods and measures

Feces of animals were collected after excretion. A total of 190-230 mg of fresh feces were individually collected were frozen in liquid nitrogen immediately. Total bacterial DNA from the feces samples by the EZNA Stool DNA Kit. The concentration, quantity, and purity of the DNA were determined using a TBS-380 mini-fluorometer and NanoDrop 2000 spectrophotometer. The paired-end library and sequencing were constructed by a TruSeq^TM DNA Sample Prep Kit. and the Illumina HiSeq4000 platform (Illumina Inc., USA).

The pool of metagenomics data obtained was assembled using MEGAHIT [64]. Contigs with a length of > 300 bp were selected as the final assembling result. MetaGene was then used to predict open reading frames (ORFs) [65]. All predicted genes (> 95% sequence identity) were clustered and mapped to representative sequences by CD-HIT [66] and a short oligonucleotide analysis package [67]. For taxonomic annotations, the representative sequences of the non-redundant genes were aligned to the NCBI NR database (e-value < 1e^-5) by the BLAST [68].

Golgi staining

To investigate dendritic spine density, the hemispheres were transferred to the Golgi staining solution. Sample preparation and Golgi staining were performed by FD Rapid Golgistain™ Kits (FD NeuroTechnologies, USA). And then the sections were photographed by a transmission electron microscope (Hitachi, Japan).

Enzyme-linked immunosorbent assay

The DLG4 / PSD95 ELISA Kit (LifeSpan BioSciences, USA) and synaptophysin ELISA Kit (Lifeome BioLabs, USA) was used to quantify the concentrations of PSD95 and synaptophysin in the hippocampus, respectively. After incubation, the absorbance value was measured at 450 nm by an Enspire™ multilabel reader 2300 (PerkinElmer, Finland).

Multiplex bead analysis

The hippocampal supernatants were centrifuged, then diluted 1:2 in assay buffer and analyzed by the Luminex 200 (Luminex, USA). Cytokines of the hippocampus including granulocyte colony-stimulating factor (G-CSF), granulocyte-macrophage colony-stimulating factor (GM-CSF), interleukin(IL)-1β, IL-2, IL-4, IL-5, IL-6, IL-17, interferon-γ (IFNγ), interferon-induced protein 10 (IP-10), tumor necrosis factor α (TNF-α), regulated upon activation normal T cell expressed and secreted factor (RANTES), monocyte chemotactic protein-1 (MCP-1), Eotaxin, macrophage inflammatory protein-1β (MIP-1β) were measured by the MILLIPLEX MAP Mouse Cytokine/Chemokine Magnetic Bead Panel (MCYTOMAG-70K, Millipore).

Statistical analyses

The data were expressed as means ± S.D.. GraphPad Prism8 (GraphPad Software, LLC, USA) was used to statistically analyze and visualize the part data. The comparison of two different groups was performed by Student`s t-tests. One-way analysis of variance (ANOVA) followed by Dunnett`s post hoc test or a two-way repeated-measures ANOVA with post-hoc Tukey multiple comparisons test was performed to determine significant differences of data from the multiple groups. The Linear discriminant analysis effect size (LEfSe) statistical analysis was analyzed by the Galaxy Module online, based on P < 0.05 and a logarithmic linear discriminant analysis (LDA) score for discriminant features was 3.0 [69]. The correlations between microbial composition and key neurobiological findings were analyzed and plotted by Spearman correlation coefficients (R, version 3.2.4). A principal component analysis (PCA) plot was also generated in R version 3.2.4. Statistical significance was set at P <0.05.

Ethical approval and consent to participate

Animal experiments were processed in accordance with the references in the Guide for the Care and Use of Laboratory Animals published by the National Institutes of Health and were approved by the Institutional Animal Care and Use Committee of Shandong University.

Author Contributions

LC conceived of the study, and participated in its design and coordination and helped to draft the manuscript. HW and SR carried out behavioral tests, biochemical and histochemical analyses, and wrote and revised the manuscript; HW and HL participated in the design of the study and wrote and revised the manuscript. HW participated in the multiplex bead analysis. HW and SR participated in the histochemical analyses. All authors read and approved the final manuscript.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

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