# Recovery Dynamics of Intestinal Bacterial Communities of CCl4-Treated Mice with or without Mesenchymal Stem Cell Transplantation over Different Time Points

Authors: Yanping Xu; Hua Zha; Wenyi Chen; Hongcui Cao; Lanjuan Li
Journal: BioMed Research International
 (2020)

---

## Abstract

Liver injury has caused significant illness in humans worldwide. The dynamics of intestinal bacterial communities associated with natural recovery and therapy for CCl4-treated liver injury remain poorly understood. This study was designed to determine the recovery dynamics of intestinal bacterial communities in CCl4-treated mice with or without mesenchymal stem cell transplantation (i.e., MSC and CCl4 groups) at 48 h, 1 week (w), and 2 w. MSCs significantly improved the histopathology, survival rate, and intestinal structural integrity in the treated mice. The gut bacterial communities were determined with significant changes in both the MSC and CCl4 groups over time, with the greatest difference between the MSC and CCl4 groups at 48 h. The liver injury dysbiosis ratio experienced a decrease in the MSC groups and a rise in the CCl4 groups over time, suggesting the mice in the MSC group at 48 h and the CCl4 group at two weeks were at the least gut microbial dysbiosis status among the corresponding cohorts. Multiple OTUs and functional categories were associated with each of the bacterial communities in the MSC and CCl4 groups over time. Among these gut phylotypes, OTU1352_S24-7 was determined as the vital member in MSC-treated mice at 48 h, while OTU453_S24-7, OTU1213_Ruminococcaceae, and OTU841_Ruminococcus were determined as the vital phylotypes in CCl4-treated mice at two weeks. The relevant findings could assist the diagnosis of the microbial dysbiosis status of intestinal bacterial communities in the CCl4-treated cohorts with or without MSC transplantation.


---

## Body

## 1. Introduction

Liver injury is a severe liver condition and has caused significant illness in human worldwide [1, 2]. This condition has been associated with the changes of intestinal microbiota [3, 4]. The intestinal microbiota is involved in the maintenance of the intestinal barrier by several mechanisms such as preventing colonization by pathogenic bacteria and by cooperating with the intestinal epithelium to produce mucin 2 [5]. Recent findings suggest that the disruption of the intestinal barrier is a prerequisite for liver injury [6]. Some probiotics were effective for the prevention of this condition [7, 8]; however, the effective therapies and the corresponding mechanisms remain poorly understood.The application of mesenchymal stem cells (MSCs) on liver injury repair has attracted increasing attention in recent years. The transplantation of MSCs has been found to alleviate injuries in multiple organs [8–14], including liver injury [15, 16]. Among the MSCs, bone marrow MSCs (BM-MSCs) could improve the clinical indices of liver function in the patients with liver injury caused by hepatitis B [17] and attenuate hepatic ischemia-reperfusion injury in mice [16, 18].Our previous study has provided important insights on the changes of survival rate, liver biochemistry parameters, histology, and intestinal microbiota between the CCl4-treated mice with or without MSC therapy [19]. In the current study, we aimed to (1) determine the recovery dynamics of intestinal bacterial communities of CCl4-treated mice with or without MSC transplantation over different time points and (2) investigate the vital phylotypes in the least dysbiotic intestinal bacterial community in CCl4-treated mice with or without MSC transplantation over the three time points.


## 2. Materials and Methods

### 2.1. Animal Information

Enhanced green fluorescent protein (GFP) transgenic C57BL/6 mice were purchased from Nanjing Biomedical Research Institute of Nanjing University. Then, female mice were backcrossed to C57BL/6 male mice to produce younger male C57BL/6 mice for isolation and culture of MSCs.The 6-8-week-old male C67BL/6 mice were purchased from Shanghai SLAC Laboratory Animal Co., Ltd. For the induction of acute liver injury (ALI) with CCl4. Animals were allowed access to food and water and housed under specific pathogen-free conditions. All animal experimental procedures were conducted according to a protocol approved by the Ethics Committee of the First Affiliated Hospital of Zhejiang University.


### 2.2. Isolation and Culture of Mouse MSCs

MSCs were isolated and cultured as previously described [20]. Briefly, two- to three-week-old wild-type C57BL/6 male mice were sacrificed for obtaining the humeri, tibiae, and femurs, the marrow of which was flushed out thoroughly with 3 ml α-minimal essential medium until the bones became pale. The compact bones were chopped into pieces and transferred to collagenase II digestion solution in 15 ml tubes, before being incubated at 37°C for 1.5 h with continuous rotation. The enzyme-treated bone chips were suspended in 7.5 ml C57BL/6-MSC special complete MEM and incubated at 37°C in a 5% CO2 incubator. Afterwards, nonadherent cells were removed and the complete MEM was replaced, before harvesting the adherent MSCs using 0.25% trypsin-EDTA and resuspending in fresh complete MEM. Purified MSCs were characterized by inducing osteogenic and adipogenic differentiation and analyzing surface marker expression by flow cytometry (Supplementary Figure S1) [19].


### 2.3. Inducing Acute Liver Injury in Mice with CCl4

Sixty 6-8-week-old male C67BL/6J mice were intraperitoneally administered with 3 ml/kg CCl4 dissolved in olive oil (v/v, 50%) to induce ALI, while six mice in the negative control (NC) group received olive oil. Six hours after the CCl4 administration, mice with ALI were randomly divided into the MSC group (n=30) and the CCl4 group (n=30). A 0.1 ml aliquot of PBS containing 5×105 MSCs was injected into the tail vein of each mouse in the MSC group, while each mouse in the CCl4 group received an injection of 0.1 ml PBS. Mice in the NC group were injected with PBS (n=6). Eighteen mice were randomly selected from the MSC group and anesthetized at 48 h (M48, n=6), 1 w (M1W, n=6), and 2 w (M2W, n=6). Likewise, 18 mice were randomly selected from the CCl4 group and anesthetized at 48 h (C48, n=6), 1 w (C1W, n=6), and 2 w (C2W, n=6). The NC group was anesthetized at 48 h.


### 2.4. Tissue Collection and Histopathology

The anesthetized mice were sacrificed for collecting the liver, small intestinal segments, and cecum and colon contents. The liver and small intestinal segments were processed in standard histological methods, while the ileum samples were processed and observed under transmission electron microscopy by a previous study [19].


### 2.5. Molecular Experiments for Illumina Sequencing

DNA was extracted from the cecum and colon contents by using QIAamp DNA stoolMini Kit (Qiagen Inc., USA), before being amplified by fusion dual barcoded primers 319F/806R targeting the V3-V4 regions of bacterial 16SrRNA gene by Dong et al. [19]. The PCR products were purified, quality checked, and subjected for sequencing on an Illumina Miseq sequencer (Illumina Inc. USA) using 2×300bp chemistry.


### 2.6. Intestinal Flora Analyses and Statistical Analyses

#### 2.6.1. Processing of Sequencing Data

Quality filtering, dereplication, chimera filtering, and taxonomy assignment procedures were performed in QIIME software version 1.9.0 as described by Dong et al. [19]. Operational taxonomic units (OTUs) were clustered based on sequence identity threshold≥97%.


#### 2.6.2. Comparisons of Gut Bacterial Communities between the MSC and CCl4 Groups at Three Time Points

Permutation analysis of variance (PERMANOVA) was applied to compare the gut bacterial communities in the MSC group and CCl4 group at 48 h (M48 versus C48), 1 w (M1W versus C1W), and 2 w (C2W versus M2W) in R software version 3.6.1.Similarity percentage (SIMPER) analysis was used to compare the dissimilarities of gut bacterial communities between the MSC group and CCl4 group at three time points after overall transformation of the dataset in square-root.Partition Around Medoid (PAM) clustering analysis was performed to cluster all the gut bacterial communities in the CCl4 and MSC groups at three time points, after determining the optimal numbers of clusters by using an average silhouette method [21].


#### 2.6.3. Dysbiosis Ratio in the Intestinal Bacterial Communities in the MSC or CCl4 Groups

Microbial dysbiosis ratio has been investigated in multiple disease studies to evaluate the microbial dysbiosis status of bacterial community [22–25]. In the present study, the dysbiosis ratio in the gut bacterial communities, i.e., liver injury dysbiosis ratio (LIDR), was defined as the abundance ratio of OTUs associated with the CCl4 group and OTUs associated with the NC group at 48 h. A LEfSe analysis was performed to determine the OTUs associated with the CCl4 group or NC group. LIDRs of C48 and M48 were compared with a t-test, after appropriate data transformation.


#### 2.6.4. Changes of Gut Bacterial Communities of the MSC Groups or CCl4 Groups over Time

The LIDRs in M48, M1W, and M2W were compared with one-way ANOVA after appropriate data transformation.t-tests were performed for the pairwise comparisons, with Bonferroni’s correction for adjusting the P values. The LIDRs in C48, C1W, and C2W were compared with the same approaches.PERMANOVA was used to compare the intestinal bacterial composition between M48, M1W, and M2W, as well as those between M48 and M1W and between M1W and M2W. The same technique was applied for the comparisons of CCl4 groups over time.One-way analysis of variance (ANOVA) was used to compare the alpha diversity, i.e., richness (observed species), diversity (Shannon index), and evenness (Pielou index), in the MSC groups at 48 h, 1 w, and 2 w.t-tests were used for the pairwise comparisons, with Bonferroni’s correction for the correcting the P values. The same approaches were applied for comparisons of alpha diversity of gut bacterial communities of CCl4 groups at three time points.LEfSe analysis was applied to determine the OTUs associated with each of the gut bacterial communities of MSC groups at three time points. The same analysis was carried out for determining the OTUs associated with each of the gut bacterial communities in CCl4 groups at three time points.


#### 2.6.5. Changes of Bacterial Networks and Gatekeepers in the MSC or CCl4 Groups over Time

Co-occurrence network (CoNet) analysis was carried out to investigate the co-occurrence and coexclusion of OTUs in the MSC groups at 48 h, 1 w, and 2 w. The top 10 OTUs with most correlations at each time point in MSC group were determined. The detailed procedures were performed as described by Wagner Mackenzie et al. [26]. Briefly, Spearman, Pearson, Bray Curtis, Mutual Information, and Kullback-Leibler dissimilarities were chosen to calculate the ensemble inference, with the top 1000 positive and negative correlations recorded. The method-specific P values were computed by permutation procedure, followed by a bootstrap step to merge the P values into one final P value. The same technique was performed for CCl4 groups over time.Gatekeepers were regarded as the OTUs interacting with different parts of the bacterial network that holds together the bacterial community [27]. In the current study, fragmentation was carried out to determine the gatekeeper(s) of the bacterial networks in each of the MSC groups and CCl4 groups at different time points. The detailed manipulations were performed as described by Wagner Mackenzie et al. [26]. A total of 10, 000 randomly constructed networks with identical node and edge distributions to the original network was used to create a null distribution of fragmentation scores. Statistical significance was defined as the number of times a fragmentation score greater than that resulting from the removal of the phylotype observed within the null distribution.


#### 2.6.6. Changes of Functional Categories in Gut Microbiota of the MSC or CCl4 Groups at Three Time Points

Functional profiles of bacterial communities of MSC groups at three time points were predicted by Tax4fun based in R software [28]. LEfSe analysis was used to determine the functional categories associated with each of the MSC groups at three time points. The same approaches were applied to determine the functional categories associated with each of the CCl4 groups at three time points.


## 2.1. Animal Information

Enhanced green fluorescent protein (GFP) transgenic C57BL/6 mice were purchased from Nanjing Biomedical Research Institute of Nanjing University. Then, female mice were backcrossed to C57BL/6 male mice to produce younger male C57BL/6 mice for isolation and culture of MSCs.The 6-8-week-old male C67BL/6 mice were purchased from Shanghai SLAC Laboratory Animal Co., Ltd. For the induction of acute liver injury (ALI) with CCl4. Animals were allowed access to food and water and housed under specific pathogen-free conditions. All animal experimental procedures were conducted according to a protocol approved by the Ethics Committee of the First Affiliated Hospital of Zhejiang University.


## 2.2. Isolation and Culture of Mouse MSCs

MSCs were isolated and cultured as previously described [20]. Briefly, two- to three-week-old wild-type C57BL/6 male mice were sacrificed for obtaining the humeri, tibiae, and femurs, the marrow of which was flushed out thoroughly with 3 ml α-minimal essential medium until the bones became pale. The compact bones were chopped into pieces and transferred to collagenase II digestion solution in 15 ml tubes, before being incubated at 37°C for 1.5 h with continuous rotation. The enzyme-treated bone chips were suspended in 7.5 ml C57BL/6-MSC special complete MEM and incubated at 37°C in a 5% CO2 incubator. Afterwards, nonadherent cells were removed and the complete MEM was replaced, before harvesting the adherent MSCs using 0.25% trypsin-EDTA and resuspending in fresh complete MEM. Purified MSCs were characterized by inducing osteogenic and adipogenic differentiation and analyzing surface marker expression by flow cytometry (Supplementary Figure S1) [19].


## 2.3. Inducing Acute Liver Injury in Mice with CCl4

Sixty 6-8-week-old male C67BL/6J mice were intraperitoneally administered with 3 ml/kg CCl4 dissolved in olive oil (v/v, 50%) to induce ALI, while six mice in the negative control (NC) group received olive oil. Six hours after the CCl4 administration, mice with ALI were randomly divided into the MSC group (n=30) and the CCl4 group (n=30). A 0.1 ml aliquot of PBS containing 5×105 MSCs was injected into the tail vein of each mouse in the MSC group, while each mouse in the CCl4 group received an injection of 0.1 ml PBS. Mice in the NC group were injected with PBS (n=6). Eighteen mice were randomly selected from the MSC group and anesthetized at 48 h (M48, n=6), 1 w (M1W, n=6), and 2 w (M2W, n=6). Likewise, 18 mice were randomly selected from the CCl4 group and anesthetized at 48 h (C48, n=6), 1 w (C1W, n=6), and 2 w (C2W, n=6). The NC group was anesthetized at 48 h.


## 2.4. Tissue Collection and Histopathology

The anesthetized mice were sacrificed for collecting the liver, small intestinal segments, and cecum and colon contents. The liver and small intestinal segments were processed in standard histological methods, while the ileum samples were processed and observed under transmission electron microscopy by a previous study [19].


## 2.5. Molecular Experiments for Illumina Sequencing

DNA was extracted from the cecum and colon contents by using QIAamp DNA stoolMini Kit (Qiagen Inc., USA), before being amplified by fusion dual barcoded primers 319F/806R targeting the V3-V4 regions of bacterial 16SrRNA gene by Dong et al. [19]. The PCR products were purified, quality checked, and subjected for sequencing on an Illumina Miseq sequencer (Illumina Inc. USA) using 2×300bp chemistry.


## 2.6. Intestinal Flora Analyses and Statistical Analyses

### 2.6.1. Processing of Sequencing Data

Quality filtering, dereplication, chimera filtering, and taxonomy assignment procedures were performed in QIIME software version 1.9.0 as described by Dong et al. [19]. Operational taxonomic units (OTUs) were clustered based on sequence identity threshold≥97%.


### 2.6.2. Comparisons of Gut Bacterial Communities between the MSC and CCl4 Groups at Three Time Points

Permutation analysis of variance (PERMANOVA) was applied to compare the gut bacterial communities in the MSC group and CCl4 group at 48 h (M48 versus C48), 1 w (M1W versus C1W), and 2 w (C2W versus M2W) in R software version 3.6.1.Similarity percentage (SIMPER) analysis was used to compare the dissimilarities of gut bacterial communities between the MSC group and CCl4 group at three time points after overall transformation of the dataset in square-root.Partition Around Medoid (PAM) clustering analysis was performed to cluster all the gut bacterial communities in the CCl4 and MSC groups at three time points, after determining the optimal numbers of clusters by using an average silhouette method [21].


### 2.6.3. Dysbiosis Ratio in the Intestinal Bacterial Communities in the MSC or CCl4 Groups

Microbial dysbiosis ratio has been investigated in multiple disease studies to evaluate the microbial dysbiosis status of bacterial community [22–25]. In the present study, the dysbiosis ratio in the gut bacterial communities, i.e., liver injury dysbiosis ratio (LIDR), was defined as the abundance ratio of OTUs associated with the CCl4 group and OTUs associated with the NC group at 48 h. A LEfSe analysis was performed to determine the OTUs associated with the CCl4 group or NC group. LIDRs of C48 and M48 were compared with a t-test, after appropriate data transformation.


### 2.6.4. Changes of Gut Bacterial Communities of the MSC Groups or CCl4 Groups over Time

The LIDRs in M48, M1W, and M2W were compared with one-way ANOVA after appropriate data transformation.t-tests were performed for the pairwise comparisons, with Bonferroni’s correction for adjusting the P values. The LIDRs in C48, C1W, and C2W were compared with the same approaches.PERMANOVA was used to compare the intestinal bacterial composition between M48, M1W, and M2W, as well as those between M48 and M1W and between M1W and M2W. The same technique was applied for the comparisons of CCl4 groups over time.One-way analysis of variance (ANOVA) was used to compare the alpha diversity, i.e., richness (observed species), diversity (Shannon index), and evenness (Pielou index), in the MSC groups at 48 h, 1 w, and 2 w.t-tests were used for the pairwise comparisons, with Bonferroni’s correction for the correcting the P values. The same approaches were applied for comparisons of alpha diversity of gut bacterial communities of CCl4 groups at three time points.LEfSe analysis was applied to determine the OTUs associated with each of the gut bacterial communities of MSC groups at three time points. The same analysis was carried out for determining the OTUs associated with each of the gut bacterial communities in CCl4 groups at three time points.


### 2.6.5. Changes of Bacterial Networks and Gatekeepers in the MSC or CCl4 Groups over Time

Co-occurrence network (CoNet) analysis was carried out to investigate the co-occurrence and coexclusion of OTUs in the MSC groups at 48 h, 1 w, and 2 w. The top 10 OTUs with most correlations at each time point in MSC group were determined. The detailed procedures were performed as described by Wagner Mackenzie et al. [26]. Briefly, Spearman, Pearson, Bray Curtis, Mutual Information, and Kullback-Leibler dissimilarities were chosen to calculate the ensemble inference, with the top 1000 positive and negative correlations recorded. The method-specific P values were computed by permutation procedure, followed by a bootstrap step to merge the P values into one final P value. The same technique was performed for CCl4 groups over time.Gatekeepers were regarded as the OTUs interacting with different parts of the bacterial network that holds together the bacterial community [27]. In the current study, fragmentation was carried out to determine the gatekeeper(s) of the bacterial networks in each of the MSC groups and CCl4 groups at different time points. The detailed manipulations were performed as described by Wagner Mackenzie et al. [26]. A total of 10, 000 randomly constructed networks with identical node and edge distributions to the original network was used to create a null distribution of fragmentation scores. Statistical significance was defined as the number of times a fragmentation score greater than that resulting from the removal of the phylotype observed within the null distribution.


### 2.6.6. Changes of Functional Categories in Gut Microbiota of the MSC or CCl4 Groups at Three Time Points

Functional profiles of bacterial communities of MSC groups at three time points were predicted by Tax4fun based in R software [28]. LEfSe analysis was used to determine the functional categories associated with each of the MSC groups at three time points. The same approaches were applied to determine the functional categories associated with each of the CCl4 groups at three time points.


## 2.6.1. Processing of Sequencing Data

Quality filtering, dereplication, chimera filtering, and taxonomy assignment procedures were performed in QIIME software version 1.9.0 as described by Dong et al. [19]. Operational taxonomic units (OTUs) were clustered based on sequence identity threshold≥97%.


## 2.6.2. Comparisons of Gut Bacterial Communities between the MSC and CCl4 Groups at Three Time Points

Permutation analysis of variance (PERMANOVA) was applied to compare the gut bacterial communities in the MSC group and CCl4 group at 48 h (M48 versus C48), 1 w (M1W versus C1W), and 2 w (C2W versus M2W) in R software version 3.6.1.Similarity percentage (SIMPER) analysis was used to compare the dissimilarities of gut bacterial communities between the MSC group and CCl4 group at three time points after overall transformation of the dataset in square-root.Partition Around Medoid (PAM) clustering analysis was performed to cluster all the gut bacterial communities in the CCl4 and MSC groups at three time points, after determining the optimal numbers of clusters by using an average silhouette method [21].


## 2.6.3. Dysbiosis Ratio in the Intestinal Bacterial Communities in the MSC or CCl4 Groups

Microbial dysbiosis ratio has been investigated in multiple disease studies to evaluate the microbial dysbiosis status of bacterial community [22–25]. In the present study, the dysbiosis ratio in the gut bacterial communities, i.e., liver injury dysbiosis ratio (LIDR), was defined as the abundance ratio of OTUs associated with the CCl4 group and OTUs associated with the NC group at 48 h. A LEfSe analysis was performed to determine the OTUs associated with the CCl4 group or NC group. LIDRs of C48 and M48 were compared with a t-test, after appropriate data transformation.


## 2.6.4. Changes of Gut Bacterial Communities of the MSC Groups or CCl4 Groups over Time

The LIDRs in M48, M1W, and M2W were compared with one-way ANOVA after appropriate data transformation.t-tests were performed for the pairwise comparisons, with Bonferroni’s correction for adjusting the P values. The LIDRs in C48, C1W, and C2W were compared with the same approaches.PERMANOVA was used to compare the intestinal bacterial composition between M48, M1W, and M2W, as well as those between M48 and M1W and between M1W and M2W. The same technique was applied for the comparisons of CCl4 groups over time.One-way analysis of variance (ANOVA) was used to compare the alpha diversity, i.e., richness (observed species), diversity (Shannon index), and evenness (Pielou index), in the MSC groups at 48 h, 1 w, and 2 w.t-tests were used for the pairwise comparisons, with Bonferroni’s correction for the correcting the P values. The same approaches were applied for comparisons of alpha diversity of gut bacterial communities of CCl4 groups at three time points.LEfSe analysis was applied to determine the OTUs associated with each of the gut bacterial communities of MSC groups at three time points. The same analysis was carried out for determining the OTUs associated with each of the gut bacterial communities in CCl4 groups at three time points.


## 2.6.5. Changes of Bacterial Networks and Gatekeepers in the MSC or CCl4 Groups over Time

Co-occurrence network (CoNet) analysis was carried out to investigate the co-occurrence and coexclusion of OTUs in the MSC groups at 48 h, 1 w, and 2 w. The top 10 OTUs with most correlations at each time point in MSC group were determined. The detailed procedures were performed as described by Wagner Mackenzie et al. [26]. Briefly, Spearman, Pearson, Bray Curtis, Mutual Information, and Kullback-Leibler dissimilarities were chosen to calculate the ensemble inference, with the top 1000 positive and negative correlations recorded. The method-specific P values were computed by permutation procedure, followed by a bootstrap step to merge the P values into one final P value. The same technique was performed for CCl4 groups over time.Gatekeepers were regarded as the OTUs interacting with different parts of the bacterial network that holds together the bacterial community [27]. In the current study, fragmentation was carried out to determine the gatekeeper(s) of the bacterial networks in each of the MSC groups and CCl4 groups at different time points. The detailed manipulations were performed as described by Wagner Mackenzie et al. [26]. A total of 10, 000 randomly constructed networks with identical node and edge distributions to the original network was used to create a null distribution of fragmentation scores. Statistical significance was defined as the number of times a fragmentation score greater than that resulting from the removal of the phylotype observed within the null distribution.


## 2.6.6. Changes of Functional Categories in Gut Microbiota of the MSC or CCl4 Groups at Three Time Points

Functional profiles of bacterial communities of MSC groups at three time points were predicted by Tax4fun based in R software [28]. LEfSe analysis was used to determine the functional categories associated with each of the MSC groups at three time points. The same approaches were applied to determine the functional categories associated with each of the CCl4 groups at three time points.


## 3. Results

### 3.1. Protective Effects of MSCs against CCl4-Induced Liver Injury

MSC transplantation dramatically increased the survival rate of CCl4-treated mice from 45.5% to 77.3% as described by Dong et al. [19], though there was no significant difference in body weight between the MSC and CCl4 groups. The liver and ileum of the MSC transplanted mice have experienced an overall improvement compared with those of the CCl4-treated mice (Figures 1(a)–1(c)).Figure 1
(a) H & E staining of mouse livers sections. Typical signs of steatosis and necrosis of hepatocytes were observed in the liver of the C48 group, while mice in the M48 group experienced a marked improvement. Magnifications: × 20. (b) Hematoxylin and eosin staining of mouse ileum pathology revealed an increase in the length and number of villi in the interposed ileum segment of the M48 group, compared with the C48 group. (c) Ultrastructure of the ileal mucosa using transmission electron microscopy. 48 h, 1 w, and 2 w represent 48 h, 1 week, and 2 weeks after CCl4 treatment, respectively.
(a)
(b)
(c)


### 3.2. Difference of Intestinal Bacterial Communities between the MSC and CCl4 Groups

PERMANOVA revealed that significant difference was determined in the gut bacterial communities between the MSC and CCl4 groups at 48 h (R2=0.30, P=0.005) and at 1 w (R2=0.18, P=0.007), but not at 2 w (R2=0.14, P>0.10). SIMPER analyses showed dissimilarity between the MSC and CCl4 groups at 48 h (SIMPERdissimilarity=64.8%) was greater than those at 1 w (SIMPERdissimilarity=56.7%) and at 2 w (SIMPERdissimilarity=46.4%).Three and five were determined to be the two optimal numbers for clustering with the highest silhouette scores (Supplementary FigureS2). Three clusters could cluster the bacterial communities of the MSC and CCl4 groups compared with five clusters, so three was chosen for PAM analysis. PAM clustering analysis showed three clusters, Cluster_1 (including most C48 and one C1W), Cluster_3 (including all M48 and one C48), and Cluster_2 (including the remaining ones) (Figure 2). All these results suggest that the largest difference in the gut bacterial communities between the CCl4 and MSC groups was at 48 h, but not at 1 w and 2 w.Figure 2
Three clusters of bacterial communities from the MSC and CCl4 groups determined by Partition Around Medoid (PAM) clustering analysis. C: carbon tetrachloride- (CCl4-) treated group; M: mesenchymal stem cell- (MSC-) transplanted group. 48, 1 w, and 2 w represent 48 h, 1 week, and 2 weeks following CCl4 treatment, respectively.


### 3.3. Changes of LIDRs in the MSC or CCl4 Groups over Time

LIDRs in the intestinal bacterial communities of all groups were calculated after determining the OTUs associated with the CCl4 or NC groups (Supplementary Figure S3). LIDR was significantly lower in C48 (0.15±0.11 SE) than in M48 (12.9±4.37 SE) at baseline (t-test, P<0.001).The LIDRs were significantly different among the M48 (12.9±4.37 SE), M1W (1.83±0.5 SE), and M2W (1.3±0.44 SE) (one-way ANOVA, P=0.002). The LIDR was significantly higher in M48 than in M1W (t-test, P=0.01) and M2W (t-test, P=0.002), while LIDRs were similar between M1W and M2W (t-test, P>0.9). Likewise, the LIDRs were significantly different among the C48 (0.15±0.11 SE), C1W (0.57±0.15 SE), and C2W (1.46±0.13 SE) (one-way ANOVA, P=0.001). The LIDR was significantly higher in C2W than in C48 (t-test, P<0.001) and C1W (t-test, P=0.001), while the ratios were similar between C48 and C1W (t-test, P>0.08).


### 3.4. Changes of Intestinal Bacterial Communities in the MSC or CCl4 Groups over Time

PERMANOVA revealed a significant difference among the bacterial communities of M48, M1W, and M2W (R2=0.38, P<0.001). Significant difference was found between M48 and M1W (R2=0.37, P=0.005), but not in M1W and M2W (R2=0.13, P>0.1). Likewise, PERMANOVA showed a significant difference between the C48, C1W, and C2W (R2=0.28, P<0.001). Significant differences were also determined between C48 and C1W (R2=0.15, P<0.04), and between C1W and C2W (R2=0.24, P=0.003).There was a significant difference in richness among M48, M1W, and M2W (one-way ANVOA,P<0.03). Richness was significantly greater in M48 than in M1W (t-test, P<0.03), but similar between M1W and M2W (t-test, P>0.2). The diversity and evenness were both similar among M48, M1W, and M2W (one-way ANOVA, P>0.05). By contrast, significant differences were found in diversity (one-way ANVOA, P<0.02) and evenness (one-way ANVOA, P<0.03) between C48, C1W, and C2W. The diversity and evenness were both higher in C2W than in C48 (t-test, all P<0.03).A total of 73 OTUs were associated with M48, M1W, or M2W according to LEfSe results. Twenty-five out of the 73 OTUs could distinguish M48 from M1W and M2W, over half of which were assigned to Clostridiales andS24-7 (Figure 3). A group of 25 OTUs could differentiate M1W from M48 and M2W, over half of which were from Oscillospira, Lachnospiraceae, and S24-7. The remaining 23 OTUs were more associated with M2W and dominated by OTUs assigned to S24-7.Figure 3
Linear discriminant analysis (LDA) effect size (LEfSe) determined the OTUs associated with each of the three MSC groups at three time points. M: mesenchymal stem cell- (MSC-) transplanted group. 48, 1 w, and 2 w represent 48 h, 1 week, and 2 weeks following CCl4 treatment.By contrast, 11 OTUs were associated with C48, among which OTUs assigned toBacteroides and Prevotella accounted for over half of the phylotypes (Figure 4). Fourteen OTUs from 11 taxa were associated with C1W, with OTU1383_Bacteroides, OTU446_Enterobacteriaceae, and OTU519_Mucispirillum as the three phylotypes with the largest LDA scores (over 4.0). A total of 34 OTUs were associated with C2W, almost two-thirds of which were from Clostridiales (12 OTUs), Lachnospiraceae (five OTUs), and Oscillospira (five OTUs) (Figure 4).Figure 4
LEfSe analysis determined the OTUs differentiating the gut microbiota from three CCl4 groups at three time points. C: carbon tetrachloride- (CCl4-) treated group. 48, 1 w, and 2 w indicate 48 h, 1 week, and 2 weeks after performing CCl4 administration.


### 3.5. Changes of Networks and Gatekeeper(s) over Time

The bacterial networks belonging to M48, M1W, M2W, C48, C1W, and C2W were determined by CoNet analyses (data not shown). The top 10 OTUs with most correlations in M48, M1W, and M2W were largely distinct (Table1), with OTUs assigned to S24-7 being determined in the top 10 OTUs in each of the three networks. Likewise, the top 10 OTUs with most correlations in C48, C1W, and C2W were largely distinct (Table 2), and OTUs assigned to S24-7 were also determined in the top 10 OTUs in each of the three networks.Table 1
The 10 OTUs with most correlations in the bacterial networks of MSC groups at 48 h, 1 w, and 2 w determined by co-occurrence network analysis.
Rank
M48
M1W
M2W
1
OTU1321_Clostridiaceae
OTU191_S24-7
OTU865_S24-7
2
OTU313_S24-7
OTU651_S24-7
OTU828_Parabacteroides
3
OTU921_Prevotella
OTU1268_Bacteroides
OTU1288_S24-7
4
OTU362_S24-7
OTU384_Rikenellaceae
OTU128_S24-7
5
OTU229_Pseudomonas
OTU143_S24-7
OTU344_Clostridiales
6
OTU1305_Bacteroides
OTU891_Oscillospira
OTU1502_S24-7
7
OTU1170_Bacteroidales
OTU717_Streptophyta
OTU718_Oscillospira
8
OTU915_S24-7
OTU155_Ruminococcaceae
OTU821_Coprococcus
9
OTU215_S24-7
OTU352_Lachnospiraceae
OTU1052_Lachnospiraceae
10
OTU677_Bacteroidales
OTU727_S24-7
OTU952_S24-7
Note: M48, M1W, and M2W represent three cohorts of CCl4-treated mice receiving MSC transplantation after 48 hours, 1 week, and 2 weeks, respectively.Table 2
The top 10 OTUs with most correlations in the bacterial networks of CCl4 groups at 48 h, 1 w, and 2 w (i.e., C48, C1W, and C2W) determined by co-occurrence network analysis.
Rank
C48
C1W
C2W
1
OTU1195_Prevotella
OTU143_S24-7
OTU1099_AF12
2
OTU421_Prevotella
OTU1313_Lachnospiraceae
OTU200_Rikenellaceae
3
OTU191_S24-7
OTU62_Clostridiales
OTU221_Bacteroides
4
OTU651_S24-7
OTU1127_MVS-40
OTU412_Rikenellaceae
5
OTU741_Parabacteroides
OTU453_S24-7
OTU824_Ruminococcaceae
6
OTU264_Flexispira
OTU1359_Koribacteraceae
OTU804_S24-7
7
OTU1453_Clostridiales
OTU521_S24-7
OTU1111_Clostridiales
8
OTU483_Parabacteroides
OTU1083_MVS-40
OTU656_Clostridiales
9
OTU457_S24-7
OTU807_S24-7
OTU807_S24-7
10
OTU601_Ruminococcaceae
OTU246_Sutterella
OTU651_S24-7
Note: C48, C1W, and C2W represent three cohorts of mice treated with CCl4 after 48 hours, 1 week, and 2 weeks, respectively.Multiple OTUs were determined as gatekeepers in the bacterial networks of M48, M1W, M2W, C48, C1W, or C2W (Table3). Among them, OTU1352_S24-7, i.e., a gatekeeper in the M48 network, was also associated with M48 by LEfSe analysis (Supplementary Figure S4A). Likewise, OTU453_S24-7, OTU1213_Ruminococcaceae, and OTU841_Ruminococcus, i.e., gatekeepers in C2W, were also associated with C2W determined by LEfSe analysis (Supplementary Figure S4B).Table 3
Gatekeepers in the bacterial networks in (A) MSC and (B) CCl4 groups at 48 h, 1 w, and 2 w determined by network fragmentation analysis.
(a)
M48
M1W
M2W
OTU1279_Ruminococcaceae
OTU1437_S24-7
OTU1132_Clostridiales
OTU1352_S24-7
OTU124_Ruminococcaceae
OTU467_Clostridiales
OTU1297_Clostridiales
OTU1318_Coprococcus
OTU1368_S24-7
OTU1390_Oscillospira
OTU320_S24-7
OTU446_Enterobacteriaceae
OTU620_Clostridiales
OTU85_Lachnospiraceae
(b)
C48
C1W
C2W
OTU1195_Prevotella
OTU123_Lachnospiraceae
OTU104_Ruminococcaceae
OTU1039_Ruminococcus
OTU1284_Lachnospiraceae
OTU440_Lachnospiraceae
OTU1202_Clostridiales
OTU1340_Lachnospiraceae
OTU1085_Ignavibacteriaceae
OTU1275_S24-7
OTU1213_Ruminococcaceae
OTU1340_Lachnospiraceae
OTU1383_Bacteroides
OTU1383_Bacteroides
OTU1450_Adlercreutzia
OTU1474_Mogibacteriaceae
OTU15_Lachnospiraceae
OTU311_S24-7
OTU279_Rikenellaceae
OTU421_Prevotella
OTU453_S24-7
OTU572_Lachnospiraceae
OTU62_Clostridiales
OTU577_S24-7
OTU841_Ruminococcus
OTU637_Staphylococcus
OTU650_S24-7
OTU703_Holdemania
OTU918_S24-7


### 3.6. Changes of Functional Categories in Gut Microbiota of the MSC/CCl4 Groups over Time

Three groups of functional categories were associated with M48 (22), M1W (2), and M2W (42). Glycogen phosphorylase, heterodisulfide reductase subunit A, and hexosaminidase were the three functional categories most associated with M48, M1W, and M2W (Figure5(a)), respectively. By contrast, outer membrane usher protein, long-chain acyl-CoA synthetase, and methyl-accepting chemotaxis protein were the three functional categories most associated with C48, C1W, and C2W, respectively (Figure 5(b)).Figure 5
Functional categories associated with (a) MSC groups over time and (b) CCl4 groups over time determined by Tax4fun and LEfSe analysis. C: carbon tetrachloride- (CCl4-) treated group; M: mesenchymal stem cell- (MSC-) transplanted group. 48, 1 w, and 2 w indicate 48 h, 1 week, and 2 weeks following CCl4 treatment, respectively.
(a)
(b)


## 3.1. Protective Effects of MSCs against CCl4-Induced Liver Injury

MSC transplantation dramatically increased the survival rate of CCl4-treated mice from 45.5% to 77.3% as described by Dong et al. [19], though there was no significant difference in body weight between the MSC and CCl4 groups. The liver and ileum of the MSC transplanted mice have experienced an overall improvement compared with those of the CCl4-treated mice (Figures 1(a)–1(c)).Figure 1
(a) H & E staining of mouse livers sections. Typical signs of steatosis and necrosis of hepatocytes were observed in the liver of the C48 group, while mice in the M48 group experienced a marked improvement. Magnifications: × 20. (b) Hematoxylin and eosin staining of mouse ileum pathology revealed an increase in the length and number of villi in the interposed ileum segment of the M48 group, compared with the C48 group. (c) Ultrastructure of the ileal mucosa using transmission electron microscopy. 48 h, 1 w, and 2 w represent 48 h, 1 week, and 2 weeks after CCl4 treatment, respectively.
(a)
(b)
(c)


## 3.2. Difference of Intestinal Bacterial Communities between the MSC and CCl4 Groups

PERMANOVA revealed that significant difference was determined in the gut bacterial communities between the MSC and CCl4 groups at 48 h (R2=0.30, P=0.005) and at 1 w (R2=0.18, P=0.007), but not at 2 w (R2=0.14, P>0.10). SIMPER analyses showed dissimilarity between the MSC and CCl4 groups at 48 h (SIMPERdissimilarity=64.8%) was greater than those at 1 w (SIMPERdissimilarity=56.7%) and at 2 w (SIMPERdissimilarity=46.4%).Three and five were determined to be the two optimal numbers for clustering with the highest silhouette scores (Supplementary FigureS2). Three clusters could cluster the bacterial communities of the MSC and CCl4 groups compared with five clusters, so three was chosen for PAM analysis. PAM clustering analysis showed three clusters, Cluster_1 (including most C48 and one C1W), Cluster_3 (including all M48 and one C48), and Cluster_2 (including the remaining ones) (Figure 2). All these results suggest that the largest difference in the gut bacterial communities between the CCl4 and MSC groups was at 48 h, but not at 1 w and 2 w.Figure 2
Three clusters of bacterial communities from the MSC and CCl4 groups determined by Partition Around Medoid (PAM) clustering analysis. C: carbon tetrachloride- (CCl4-) treated group; M: mesenchymal stem cell- (MSC-) transplanted group. 48, 1 w, and 2 w represent 48 h, 1 week, and 2 weeks following CCl4 treatment, respectively.


## 3.3. Changes of LIDRs in the MSC or CCl4 Groups over Time

LIDRs in the intestinal bacterial communities of all groups were calculated after determining the OTUs associated with the CCl4 or NC groups (Supplementary Figure S3). LIDR was significantly lower in C48 (0.15±0.11 SE) than in M48 (12.9±4.37 SE) at baseline (t-test, P<0.001).The LIDRs were significantly different among the M48 (12.9±4.37 SE), M1W (1.83±0.5 SE), and M2W (1.3±0.44 SE) (one-way ANOVA, P=0.002). The LIDR was significantly higher in M48 than in M1W (t-test, P=0.01) and M2W (t-test, P=0.002), while LIDRs were similar between M1W and M2W (t-test, P>0.9). Likewise, the LIDRs were significantly different among the C48 (0.15±0.11 SE), C1W (0.57±0.15 SE), and C2W (1.46±0.13 SE) (one-way ANOVA, P=0.001). The LIDR was significantly higher in C2W than in C48 (t-test, P<0.001) and C1W (t-test, P=0.001), while the ratios were similar between C48 and C1W (t-test, P>0.08).


## 3.4. Changes of Intestinal Bacterial Communities in the MSC or CCl4 Groups over Time

PERMANOVA revealed a significant difference among the bacterial communities of M48, M1W, and M2W (R2=0.38, P<0.001). Significant difference was found between M48 and M1W (R2=0.37, P=0.005), but not in M1W and M2W (R2=0.13, P>0.1). Likewise, PERMANOVA showed a significant difference between the C48, C1W, and C2W (R2=0.28, P<0.001). Significant differences were also determined between C48 and C1W (R2=0.15, P<0.04), and between C1W and C2W (R2=0.24, P=0.003).There was a significant difference in richness among M48, M1W, and M2W (one-way ANVOA,P<0.03). Richness was significantly greater in M48 than in M1W (t-test, P<0.03), but similar between M1W and M2W (t-test, P>0.2). The diversity and evenness were both similar among M48, M1W, and M2W (one-way ANOVA, P>0.05). By contrast, significant differences were found in diversity (one-way ANVOA, P<0.02) and evenness (one-way ANVOA, P<0.03) between C48, C1W, and C2W. The diversity and evenness were both higher in C2W than in C48 (t-test, all P<0.03).A total of 73 OTUs were associated with M48, M1W, or M2W according to LEfSe results. Twenty-five out of the 73 OTUs could distinguish M48 from M1W and M2W, over half of which were assigned to Clostridiales andS24-7 (Figure 3). A group of 25 OTUs could differentiate M1W from M48 and M2W, over half of which were from Oscillospira, Lachnospiraceae, and S24-7. The remaining 23 OTUs were more associated with M2W and dominated by OTUs assigned to S24-7.Figure 3
Linear discriminant analysis (LDA) effect size (LEfSe) determined the OTUs associated with each of the three MSC groups at three time points. M: mesenchymal stem cell- (MSC-) transplanted group. 48, 1 w, and 2 w represent 48 h, 1 week, and 2 weeks following CCl4 treatment.By contrast, 11 OTUs were associated with C48, among which OTUs assigned toBacteroides and Prevotella accounted for over half of the phylotypes (Figure 4). Fourteen OTUs from 11 taxa were associated with C1W, with OTU1383_Bacteroides, OTU446_Enterobacteriaceae, and OTU519_Mucispirillum as the three phylotypes with the largest LDA scores (over 4.0). A total of 34 OTUs were associated with C2W, almost two-thirds of which were from Clostridiales (12 OTUs), Lachnospiraceae (five OTUs), and Oscillospira (five OTUs) (Figure 4).Figure 4
LEfSe analysis determined the OTUs differentiating the gut microbiota from three CCl4 groups at three time points. C: carbon tetrachloride- (CCl4-) treated group. 48, 1 w, and 2 w indicate 48 h, 1 week, and 2 weeks after performing CCl4 administration.


## 3.5. Changes of Networks and Gatekeeper(s) over Time

The bacterial networks belonging to M48, M1W, M2W, C48, C1W, and C2W were determined by CoNet analyses (data not shown). The top 10 OTUs with most correlations in M48, M1W, and M2W were largely distinct (Table1), with OTUs assigned to S24-7 being determined in the top 10 OTUs in each of the three networks. Likewise, the top 10 OTUs with most correlations in C48, C1W, and C2W were largely distinct (Table 2), and OTUs assigned to S24-7 were also determined in the top 10 OTUs in each of the three networks.Table 1
The 10 OTUs with most correlations in the bacterial networks of MSC groups at 48 h, 1 w, and 2 w determined by co-occurrence network analysis.
Rank
M48
M1W
M2W
1
OTU1321_Clostridiaceae
OTU191_S24-7
OTU865_S24-7
2
OTU313_S24-7
OTU651_S24-7
OTU828_Parabacteroides
3
OTU921_Prevotella
OTU1268_Bacteroides
OTU1288_S24-7
4
OTU362_S24-7
OTU384_Rikenellaceae
OTU128_S24-7
5
OTU229_Pseudomonas
OTU143_S24-7
OTU344_Clostridiales
6
OTU1305_Bacteroides
OTU891_Oscillospira
OTU1502_S24-7
7
OTU1170_Bacteroidales
OTU717_Streptophyta
OTU718_Oscillospira
8
OTU915_S24-7
OTU155_Ruminococcaceae
OTU821_Coprococcus
9
OTU215_S24-7
OTU352_Lachnospiraceae
OTU1052_Lachnospiraceae
10
OTU677_Bacteroidales
OTU727_S24-7
OTU952_S24-7
Note: M48, M1W, and M2W represent three cohorts of CCl4-treated mice receiving MSC transplantation after 48 hours, 1 week, and 2 weeks, respectively.Table 2
The top 10 OTUs with most correlations in the bacterial networks of CCl4 groups at 48 h, 1 w, and 2 w (i.e., C48, C1W, and C2W) determined by co-occurrence network analysis.
Rank
C48
C1W
C2W
1
OTU1195_Prevotella
OTU143_S24-7
OTU1099_AF12
2
OTU421_Prevotella
OTU1313_Lachnospiraceae
OTU200_Rikenellaceae
3
OTU191_S24-7
OTU62_Clostridiales
OTU221_Bacteroides
4
OTU651_S24-7
OTU1127_MVS-40
OTU412_Rikenellaceae
5
OTU741_Parabacteroides
OTU453_S24-7
OTU824_Ruminococcaceae
6
OTU264_Flexispira
OTU1359_Koribacteraceae
OTU804_S24-7
7
OTU1453_Clostridiales
OTU521_S24-7
OTU1111_Clostridiales
8
OTU483_Parabacteroides
OTU1083_MVS-40
OTU656_Clostridiales
9
OTU457_S24-7
OTU807_S24-7
OTU807_S24-7
10
OTU601_Ruminococcaceae
OTU246_Sutterella
OTU651_S24-7
Note: C48, C1W, and C2W represent three cohorts of mice treated with CCl4 after 48 hours, 1 week, and 2 weeks, respectively.Multiple OTUs were determined as gatekeepers in the bacterial networks of M48, M1W, M2W, C48, C1W, or C2W (Table3). Among them, OTU1352_S24-7, i.e., a gatekeeper in the M48 network, was also associated with M48 by LEfSe analysis (Supplementary Figure S4A). Likewise, OTU453_S24-7, OTU1213_Ruminococcaceae, and OTU841_Ruminococcus, i.e., gatekeepers in C2W, were also associated with C2W determined by LEfSe analysis (Supplementary Figure S4B).Table 3
Gatekeepers in the bacterial networks in (A) MSC and (B) CCl4 groups at 48 h, 1 w, and 2 w determined by network fragmentation analysis.
(a)
M48
M1W
M2W
OTU1279_Ruminococcaceae
OTU1437_S24-7
OTU1132_Clostridiales
OTU1352_S24-7
OTU124_Ruminococcaceae
OTU467_Clostridiales
OTU1297_Clostridiales
OTU1318_Coprococcus
OTU1368_S24-7
OTU1390_Oscillospira
OTU320_S24-7
OTU446_Enterobacteriaceae
OTU620_Clostridiales
OTU85_Lachnospiraceae
(b)
C48
C1W
C2W
OTU1195_Prevotella
OTU123_Lachnospiraceae
OTU104_Ruminococcaceae
OTU1039_Ruminococcus
OTU1284_Lachnospiraceae
OTU440_Lachnospiraceae
OTU1202_Clostridiales
OTU1340_Lachnospiraceae
OTU1085_Ignavibacteriaceae
OTU1275_S24-7
OTU1213_Ruminococcaceae
OTU1340_Lachnospiraceae
OTU1383_Bacteroides
OTU1383_Bacteroides
OTU1450_Adlercreutzia
OTU1474_Mogibacteriaceae
OTU15_Lachnospiraceae
OTU311_S24-7
OTU279_Rikenellaceae
OTU421_Prevotella
OTU453_S24-7
OTU572_Lachnospiraceae
OTU62_Clostridiales
OTU577_S24-7
OTU841_Ruminococcus
OTU637_Staphylococcus
OTU650_S24-7
OTU703_Holdemania
OTU918_S24-7


## 3.6. Changes of Functional Categories in Gut Microbiota of the MSC/CCl4 Groups over Time

Three groups of functional categories were associated with M48 (22), M1W (2), and M2W (42). Glycogen phosphorylase, heterodisulfide reductase subunit A, and hexosaminidase were the three functional categories most associated with M48, M1W, and M2W (Figure5(a)), respectively. By contrast, outer membrane usher protein, long-chain acyl-CoA synthetase, and methyl-accepting chemotaxis protein were the three functional categories most associated with C48, C1W, and C2W, respectively (Figure 5(b)).Figure 5
Functional categories associated with (a) MSC groups over time and (b) CCl4 groups over time determined by Tax4fun and LEfSe analysis. C: carbon tetrachloride- (CCl4-) treated group; M: mesenchymal stem cell- (MSC-) transplanted group. 48, 1 w, and 2 w indicate 48 h, 1 week, and 2 weeks following CCl4 treatment, respectively.
(a)
(b)


## 4. Discussion

The gut microbiota in CCl4-treated mice has been reported in different studies [29–31]. Our previous study provided sufficient findings about the differences between the intestinal bacterial communities in the CCl4-treated mice with and without MSC therapy [19]. This study was designed to determine the recovery dynamics of intestinal bacterial communities of CCl4-treated mice with or without mesenchymal stem cell transplantation over different time points, which was rarely reported to our limited knowledge.PERMANOVA, SIMPER, and PAM clustering analyses have been used in a variety of studies [32–34]. In the current study, the differences in bacterial communities between the MSC and CCl4 groups at designated times (i.e., 48 h, 1 w, and 2 w) were determined by the three analyses, and the relevant results showed the largest difference between the MSC and CCl4 groups occurred at 48 h. As the most obvious difference of survival percentages of mice between the MSC and CCl4 groups occurred from 48 h to 1 w, it implied that the change of intestinal bacterial communities was associated with this obvious difference.PERMANOVA results for MSC groups’ comparison suggested the significant change in the gut bacterial communities of MSC groups from 48 h to 1 w, while no such change was found between 1 w and 2 w. By contrast, PERMANOVA results for CCl4 groups’ comparison suggested the significant changes in gut bacterial communities over the two time periods, i.e., 48 h to 1 w and 1 w to 2 w. An overall difference was determined in the richness of the gut bacterial communities of MSC groups over time, while overall differences were determined in diversity and evenness of C48, C1W, and C2W. These results suggest the recovery mechanisms in gut bacterial communities in the MSC and CCl4 groups were different.The dysbiosis ratio has been investigated in multiple disease studies [22–25]. In this study, LIDR was used to evaluate the dysbiosis status of gut bacterial communities in the MSC and CCl4 groups and was significantly lower in C48 than in M48 at baseline. LIDR was decreasing in MSC groups over time, while this ratio experienced an increase in CCl4 groups during the same period, which could partly explain why the difference of gut bacterial communities in the MSC and CCl4 groups were largest at 48 h. These results implied that MSCs-treated mice experienced the mildest intestinal microbial dysbiosis at 48 h, while the CCl4-treated mice had the mildest intestinal microbial dysbiosis at two weeks.LEfSe results showed different phylotypes were associated with each of the MSC and CCl4 groups. Multiple S24-7 phylotypes were associated with all the MCS and CCl4 groups, suggesting different S24-7 phylotypes could play different roles in each of the six groups. This is consistent with the previous findings, which hold different views on the roles of Bacteroidales S24-7 in the gut microbiota [35, 36]. Multiple OTUs assigned to Clostridiales were associated with M48, among which OTU375_ Clostridiales was most associated with M48. Likewise, Clostridiales was determined with varied effects on health [37, 38]. OTU186_Bacteroides was most associated with C2W in this study. Bacteroides species were determined as opportunistic pathogens and probiotics in different studies [39, 40].The top 10 OTUs with most correlations in the networks of M48, M1W, and M2W were largely different, so as for the CCl4 groups, suggesting the gut bacterial networks changed in both the MSC and CCl4 groups at different time points. Multiple distinct gatekeepers were determined in the networks of the MSC and CCl4 groups over time. Among them, OTU1352_S24-7 (i.e., a gatekeeper in M48 network) was also associated with M48 by LEfSe analysis, while OTU453_S24-7, OTU1213_Ruminococcaceae, and OTU841_Ruminococcus (i.e., three gatekeepers in C2W) were also associated with C2W, suggesting these phylotypes could play a key role in maintaining the gut bacterial communities of M48 and C2W (i.e., the cohorts with the highest LIDR in the MSC groups and CCl4 groups, respectively). As mentioned above, S24-7 was determined with varied effects on health. As for the beneficial effect, the enriched S24-7 in the gut microbiota of mice fed with Lactobacillus reuteri ATG-F4 was associated with the improvements of psychological status of a murine model [41]. Ruminococcaceae was believed as a vital member in maintaining the gut health [42], while some Ruminococcus species were determined as normal members in gut microbiota [43].Multiple functional categories were associated with gut microbiota of the MSC and CCl4 groups over time in the current study. Among them, glycogen phosphorylase, heterodisulfide reductase subunit A, and hexosaminidase were most associated with M48, M1W, and M2W, respectively, while outer membrane usher protein, long-chain acyl-CoA synthetase, and methyl-accepting chemotaxis protein were most associated with C48, C1W, and C2W, respectively, suggesting these functional categories could play important roles in the changes of gut bacterial communities of the MSC and CCl4 groups at different stages. Glycogen phosphorylase normally is located in the brain, liver, and skeletal muscle tissue. Heterodisulfide reductase played an important role in the energy-conserving metabolisms of bacteria and archaea [44, 45]. The serum beta-hexosaminidase level was associated with reticuloendothelial function of the patients with viral hepatitis [46]. β-Barrel assembly machine-mediated folding of outer membrane usher protein could be selectively disrupted by nitazoxanide [47]. Long-chain acyl-CoA synthetase in fatty acid metabolism was involved in multiple liver diseases [48]. Methyl-accepting chemotaxis protein was associated with the changes of hepatic inflammation [49].


## 5. Conclusion

In conclusion, the results suggest that the intestinal microbiota, the corresponding networks, and functional categories changed during the recovery dynamics of the MSC or CCl4 group. MSC-treated mice were determined with the mildest intestinal microbial dysbiosis at 48 h, with OTU1352_S24-7 as the vital gut phylotype. CCl4-treated mice experienced the least intestinal microbial dysbiosis status at two weeks, with OTU453_S24-7, OTU1213_Ruminococcaceae, and OTU841_Ruminococcus as the vital gut phylotypes. These findings may assist in monitoring the dysbiosis status of intestinal bacterial communities of CCl4-treated mice with or without MSC transplantation over different time points.



---

*Source: 1673602-2020-10-15.xml*