Human disease-related pathways increasing with opportunistic pathogens bloom in intestinal microbiome after vancomycin exposure and restoration with fecal transplantation by simulator of the human intestinal microbial ecosystem (SHIME)

Background: Antibiotics are growing reported to cause human intestinal microbial disorders with increasing abundances of opportunistic pathogens, and fecal microbiota transplantation (FMT) has been confirmed to restore the dysbiosis of gut flora in many kinds of intestinal disease. However, to date, few studies have focused on the bloomed opportunistic pathogens associated human disease-related pathways as well as antibiotic resistance genes (ARGs) after vancomycin exposure, and there is limited information on using FMT for restoration of intestinal microbiome affected by antibiotics. Methods: This study investigated effects of vancomycin on the opportunistic pathogens, human disease-related pathways as well as ARGs in human gut, and the restoration of intestinal microbiome by FMT. Using the simulator of the human intestinal microbial ecosystem (SHIME), two reactors (representing the ascending and descending colon, respectively) were inoculated with human intestinal microbiota from a healthy adult volunteer who did not suffer from gastrointestinal diseases or take any antibiotic in the previous six months. Samples were collected from the reactors at six-time points (before treatment, after seven days of individual 10 mg/L, 100 mg/L, 1000 mg/L vancomycin treatment, 14 days following the termination of vancomycin and 14 days following FMT). The intestinal microbiome composition and function were analyzed using 16S rRNA gene sequencing and High-throughput Quantitative PCR (HT-qPCR). Results: Vancomycin treatment substantially increased human disease-related pathways and decreased abundances of ARGs. Besides, the bloomed opportunistic pathogens including Achromobacter , Klebsiella , and Pseudomonas , caused by vancomycin exposure, were positively correlated with human disease-related pathways. The microbiota abundance and genes of human disease-related pathways and antibiotic resistance showed a remarkable return towards baseline after FMT, but not for natural recovery. Conclusions: These findings suggest that impacts of vancomycin on human gut are profound and FMT will be a promising strategy in clinical application that can restore the dysbiosis of gut microbiota, which may be valuable for directing future work.

clarifying direct effects of antibiotics on human intestinal microbiota without the disturbances from neurohumoral regulation, the individual differences, dietary habits, and physiological status. The simulator of the human intestinal microbial ecosystem (SHIME) model is known to be a useful tool for in vitro studies as (i) interactions between the microbiota; and (ii) the effects of prebiotics and other compounds on the microbial communities and metabolic activities [16]. However, to the best of our knowledge, there are very few researches that added the antibiotics into this in vitro model [17][18][19][20].
Researches mainly focused on the benefit of the mucosal environment, high-fiber diets, probiotic, and propionate-producing consortium in human intestinal microbiota. The effects of antibiotics, including AMX and other antibiotics mixture, vancomycin, and clindamycin, were limited to microbiota composition and metabolite.
Fecal microbiota transplantation (FMT) is the introduction of feces from a healthy donor into the intestinal tract of someone with disrupted microbiota, which has been confirmed superior to oral vancomycin for the treatment of Clostridium difficile infection [21,22]. And combination of FMT with vancomycin could be a better choice to treat this kind of infection [23,24]. However, there is limited information on using fecal microbiota transplantation (FMT) for restoration of intestinal microbiome affected by antibiotics. Therefore, it is exciting for us to investigate whether FMT would restore the human intestinal dysbiosis caused by vancomycin exposure.
Since the reasonable dosage of vancomycin for adult human study is about 500 to 1500 mg day − 1 and only half volume of adult gut can be simulated in the used SHIME model, here the direct effects of 600 mg day − 1 (1000 mg L − 1 ) of vancomycin on the composition and human disease-related pathways as well as ARGs of the human gut microbiota were studied [15,24]. And 10 mg L − 1 and 100 mg L − 1 were chosen as lower doses of vancomycin to verify whether these doses of vancomycin would affect human gut microbiota, because the vancomycin agar plate concentration for vancomycin resistant bacteria isolation is between this range according to the CLSI M07-A8 2011 guidelines. In this study, the composition of human intestinal microbiota composition and human disease-related pathways were analyzed by 16S rRNA gene high-throughput sequencing, and the ARGs were quantified by high-throughput quantitative PCR (HT-qPCR). This study achieved a systematical investigation and precisely understanding of the direct effects of vancomycin modulation on the intestinal microbiota and the restoration of FMT using a SHIME model system, which may be valuable for directing future work.

Vancomycin treatment and sample collection
The SHIME model in this study was formed by four double-jacketed reactors designated as the stomach, small intestine, ascending colon, and descending colon, respectively (Fig. S1a). The last two reactors inoculated with a mixture of fecal microbiota collected from a healthy adult volunteer, who did not suffer from gastrointestinal diseases or take any antibiotics in the previous six months, and the differences between individuals may be alleviated by same culture condition [25]. The details of the SHIME system and the startup process are summarized in the Supplementary material.
After two weeks' stabilization and another week's nutritional medium adding, the SHIME sequentially exposed to a gradient of vancomycin (from low to high concentrations) and experienced two weeks' natural recovery and two weeks' FMT. All the samples were collected and analyzed at six-time points: prior to the treatment (C_A, C_D), and after 7 days of each administration of 10 mg L − 1 (V10_A, V10_D), 100 mg L − 1 (V100_A, V100_D), and 1000 mg L − 1 vancomycin (V1000_A, V1000_D), after 14 days of vancomycin discontinuation (NR_A, NR_D), and after 14 days of FMT (FR_A, FR_D), and each sample is a mixture of three samples collected from 7 a.m. to 11 p.m. (Fig. S1b). The samples were stored at − 80 °C for further analyses. on alpha diversity, the taxon richness (Chao1 index), evenness (Simpson index), and diversity (Shannon index) were calculated for all samples. In addition, beta diversity of the microbiota communities at baseline and after antibiotics were portrayed by nonmetric multidimensional scaling (NMDS) and principal coordinate analysis (PCoA) of weighted and unweighted UniFrac distances [28].
Linear discriminant analysis effect size (LEfSe) analysis was performed to determine bacterial taxa that significantly differed between the control and antibiotic group using the Galaxy application tool [29]. Functional predictions of microbial community were performed to visualize the distribution of human disease related pathways in the two parts of colon with different treatment using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) [30]. The accuracy of PICRUST for the detection of these more challenging functional groups was good (min. accuracy = 0.82), suggesting that their inference of gene abundance across various types of functions was reliable, and PICRUSt predictions had high agreement with metagenome sample abundances across all body sites (Spearman r = 0.82, P < 0.001). The details of taxonomical classification, LEfSe analysis, and functional predictions were described in the Supplementary material.
High-throughput quantitative PCR (HT-qPCR) and analysis HT-qPCR reactions were performed to visualize the variation of ARGs during the treatment using Wafergen SmartChip Real-time PCR system, which was conducted by Anhui MicroAnaly Gene Technologies Co., Ltd (Anhui, China). A total of 120 primer sets were used (Excel S1), including 114 primer sets to target almost all major classes of antibiotic resistance genes (ARGs) found in Chinese human gut microbiota [31], five mobile genetic elements (MGEs) and one 16S rRNA gene. The results were analyzed with SmartChip qPCR Software excluding the wells with multiple melting peaks or amplification efficiency beyond the range (90-110%) and then screened with conditions that a threshold cycle (CT) must be < 31 and positive samples should have three replicates simultaneously.
The details of HT-qPCR analysis were described in the Supplementary material. Antibiotic susceptibility test and serum killing resistance assays of pathogens The Pathogenic bacterial strains were isolated from the V1000_A sample using Luria-Bertani (LB) agar plates supplemented with 100 mg L − 1 of vancomycin. Genomic DNA of these strains was extracted using a Promega Wizard Genomic DNA Purification Kit (Promega, Madison, USA) according to the manufacturer's protocols. The isolated strains were identified by 16S ribosomal DNA sequencing conducted by BGI Tech Solutions (Beijing Liuhe) Co., Ltd (Beijing, China). Nine antibiotic resistance genes from the isolated strains were confirmed using Qualitative PCR with the primers listed in Table   S1. MICs of these pathogens were determined according to the CLSI M07-A8 2011 guidelines. The serum-killing assay was performed based on the method described by David and associates [32].
Details of the antibiotic susceptibility test, and the serum killing resistance assays procedures are described in the Supplementary material.

Data analysis
Correlation between the microbiota and human disease-related pathways or ARGs were analyzed using the Spearman test in R with the vegan package. Correlations between pairs of variables were considered to be significant at r > 0.6, and P values were < 0.05. The Gephi (V 0.9.1) software was used to visualize the bipartite network graphs using the Force Atlas algorithm.

Human disease-related pathways and ARGs
The human disease-related pathways and ARGs in samples from the SHIME model were assessed at different time points, which included samples prior to antibiotic treatment (C), sequential doses (10, 100, and 1000 mg L − 1 ) of antibiotic treatments at seven days interval designated as V10, V100, and V1000, followed by 14 days after termination of vancomycin (NR) and 14 days after FMT (FR). The hierarchy cluster heatmap showed that gene numbers of human disease-related pathways, including drug resistance, cancer, cardiovascular diseases, immune system diseases, infectious diseases, metabolic diseases, and neurosurgery diseases were more abundant in antibiotic exposure groups than that in control group, which was especially apparent in ascending colon (Fig. 1). For instance, gene numbers of bladder cancer, renal cell carcinoma, primary immunodeficiency, type II diabetes mellitus, and prion diseases were nearly 1.3-1.5 times more enriched in the V1000 group than in control. Moreover, gene numbers of these human disease-related pathways still maintained at a higher level (about 1.2-1.3 times enriched than control) after natural recovery and FMT treatment could restore them to baseline level.
The relative abundance of ARGs such as aminoglycoside, beta-lactam, multidrug, and tetracycline resistance genes were lower in vancomycin exposure groups than that in control samples, which was also especially obvious in ascending colon (Fig. 2). For instance, log relative abundance reduction of aac6ie (aminoglycoside) was about 2.9 log units after 1000 mg L − 1 vancomycin treatment than in control, and bl2b_tem1 (beta_lactam), ermb (MLSB), and qacedelta1 (multidrug) were about 2.0, 2.3, and 1.5 log units, respectively. Besides, the ARGs such as ant3ia (aminoglycoside), bl1_ec (beta_lactam), ermf (MLSB), mexf (multidrug), tetq (tetracycline), and sul1 (sulfonamide) were not detected after vancomycin treatment. Similarly, these ARGs were unable to return to the baseline level following the natural recovery with about 2.2 to 3.8 log units lower of relative abundance. FMT would restore most of them to some extent (about 1.7 log units lower to 0.6 log units higher).
Meanwhile, fecal microbiota alpha diversity was assessed. The taxon richness (Chao1 index), evenness (Simpson index), and diversity (Shannon index) are shown in Fig. S3a to c. Compared with control sample C_A, a drop in microbiota richness (Chao1), evenness (Simpson), and diversity (Shannon) was observed in sample collected from ascending colon after 1000 mg L − 1 of vancomycin treatment; however opposite change was observed in sample V10_A. As shown in Fig. S3, the decreasing of microbiota richness, evenness, and diversity caused by vancomycin treatment restored after two weeks of vancomycin discontinued (NR). Besides, the beta diversity of the microbiota communities and weighted UniFrac distance was affected by antibiotic treatment. As shown in Fig. 3, the samples that collected after vancomycin treatments were differed from the control group in both UniFrac NMDS and PCoA analyses. The beta diversity results also showed that gut microbial composition remained comparable after two weeks of vancomycin discontinued (NR) because these two samples were clustered together with vancomycin treatment groups. Meanwile, after two weeks of FMT treatment, the samples clustered to control group for both UniFrac NMDS and PCoA analyses.
Moreover, weighted UniFrac distance between 1000 mg L − 1 vancomycin treatment group and control group (V1000 vs. C) were higher than that within the control group (C vs. C), and that between the recovery groups and the control group (NR vs. C, FR vs. C) were slightly higher (Fig. S4).

Bloomed opportunistic pathogens
The linear discriminant analysis effect size (LEfSe) comparison analysis between the control and antibiotic groups was shown in Moreover, five opportunistic pathogens were isolated from V1000_A sample (Table S2), which included Klebsiella aerogenes (NKU-Kae), Klebsiella pneumoniae (NKU-Kpn7), Klebsiella oxytoca (NKU-Kox6), Achromobacter xylosoxidans (NKU-Axy), and Pseudomonas aeruginosa (NKU-Pae). Table S3 represents the minimal inhibitory concentration (MIC) of these opportunistic pathogens. Data  Table S4 showed a total of nine ARGs detecting in these opportunistic pathogens. The results showed that all the opportunistic pathogens carried qnrs and bl2be_shv2, and except NKU-Kae, all others contained aac3iia, vang, arna, rosb, and ant2ia ARGs. Therefore, their intrinsic ARGs such as vang, aac3iia, sul1, and bl2be_shv2 might be attributed to high values of MICs to vancomycin, gentamicin, sulfamethoxazole, ampicillin, and amoxicillin. As shown in Table S5, a considerable variability in serum resistance for the opportunistic pathogens was observed, which constituted an important virulence trait that allowed these opportunistic pathogens to persist in vivo. And the survival of Pseudomonas aeruginosa (NKU-Pae) strain was significantly higher (12-54 times) than other strains with a virulence level of Grade 5.
Correlation between microbial taxa and human disease-related pathways or ARGs Figure 5 showed the results of co-occurrence patterns between microbial taxa and human diseaserelated pathways. It can be seen that significantly increased bacteria after vancomycin exposure such as Achromobacter and Klebsiella were positively associated with almost all of those human diseaserelated pathways, and the decreased bacteria were negatively associated with these pathways.
Specifically, the correlation coefficients of Achromobacter with colorectal cancer, viral myocarditis and toxoplasmosis were about 0.8 (P < 0.01) and the correlation coefficient of Klebsiella oxytoca with Staphylococcus aureus infection was 0.7 (P < 0.01).
The network analysis of co-occurrence patterns between microbial taxa and ARG subtypes was shown in Fig. 6. Interestingly, a very similar pattern of results was observed that a significantly decreased the bacteria was positively associated with the most ARGs. For example, the correlation coefficients of Bacteroides fragilis with bl2e_cepa aac6ie and tet32 were about 1.0 (P < 0.001), and the correlation coefficient of Parabacteroides with ermb was about 0.8 (P < 0.01). Only two significantly increased bacterial genera were positively associated with several ARGs. For example, the strong correlations were found in Klebsiella oxytoca with yidy/mdtl and tetc (about 0.9, P < 0.01), and in Pseudomonas with ermf and tetq (about 0.8, P < 0.05).

Discussion
Vancomycin exposure significantly increased the opportunistic pathogens Achromobacter, Pseudomonas, and Klebsiella genera were all confirmed to increase after vancomycin exposure, although these bacteria are all considered commensal in the human gut, fecal carriage of these opportunistic pathogens was confirmed to be a severe risk factor for the infection [11,12].
Achromobacter and Klebsiella intrinsically carry ARGs such as vang, aac3iia, sul1, and bl2be_shv2, which make them inherently resistant to vancomycin, aminoglycosides, sulfonamides, and beta-lactam antibiotics, consequently pose a significant therapeutic challenge [37]. Additionally, the multidrug resistant Pseudomonas aeruginosa with high virulence obtained from this research has also been well recorded in many previous research papers, indicating its immense threat to human health [38]. Some commensal microbiota in the human gut that decreased after vancomycin exposure such as Bacteroides fragilis and Parabacteroides are novel probiotics [39,40], and the decrease of these probiotics may cause dysbiosis of gut microbiota, which would lead human health problem [41,42].
Therefore, the results of our research demonstrated a serious impact and a negative side-effect of vancomycin that enriched pathogens related to health problems, which should be considered as a fundamental aspect of the cost-benefit equation for an antibiotic prescription.
Opportunistic pathogens associated human disease-related pathways increased by vancomycin exposure The significant increase in opportunistic pathogens associated human disease-related pathways and decrease in ARGs of human intestinal microbiota following vancomycin treatment exhibited in this study have not been reported in details yet. However, ampicillin had been found to enhance glucose tolerance, and promote the selection of antimicrobial resistance genes in intestinal microbiota using animal models [43]. Importantly, this study displayed a positive correlation between opportunistic pathogens (Klebsiella and Achromobacter) and human disease-related pathways, which suggested the bloom of these opportunistic pathogens caused by vancomycin treatment that might contribute to human diseases. For instance, some studies have indicated that Klebsiella was enriched in cancer and diabetes patients [44], and be related to various infectious diseases [45] and neurosurgery disease [14]. Furthermore, Achromobacter was also reported to be related to human diseases such as pneumonia [46], colitis [47], cancer [48], and cardiovascular diseases [13]. All of the findings, as mentioned above, were also linked with positive correlations between the abundances of these opportunistic pathogens and human disease-related pathways in our study. Some previous studies have also reported multiple ARGs resided in these types of pathogenic bacteria [49,50], that maybe one of the critical reason for ARGs were more abundantly present in control samples.
Vancomycin effects were "SHIME-compartment" different and persistent The phenomenon observed in the SHIME model that a larger shift of microbiota found in the ascending colon was also revealed by previous reporters. They demonstrated that changes of intestinal microbiota by vancomycin or mixed antibiotics exposure were "SHIME-compartment" different [17,18]. Meanwhile, more extensive shifts in bloomed opportunistic pathogens associated human disease-related pathways as well as ARGs found in this study were in line with other research that had clarified the primary effect observed at the level of the microbiota could also be found at genomic and metabolic levels [51,52]. The intestinal microbiota is a key "organ" for the individual's health and their different shifting in the ascending colon and descending colon suggested that more studies should focus on the proximal colon for the uniform data sheets of colon microbiota. However, in vivo experiments usually analyses the feces that standing for the distal intestinal microbiota.
Furthermore, the vancomycin effects were still evident for at least two weeks after the vancomycin discontinued, although the resilient reduction of opportunistic pathogens and human disease-related pathways was observed. Reijnders and colleagues revealed that a markedly decreased of microbial diversity, decreased relative abundance of most Gram-positive bacteria of the Firmicutes, and

FMT restored microbiome composition and genes
Finally, this study revealed that the FMT would restore human intestinal microbiome composition, human disease-related pathways, and ARGs that profoundly affected by vancomycin. The restoration of microbiome composition find in our study may refer to the findings by Lee and associates that germ-free mice mono-associated with a single Bacteroides species are resistant to colonization by the same, but not different, species [53]. FMT may also colonize missing flora after vancomycin exposure with priority to restore the dysbiosis. For recurrent of Clostridium difficile infection, several researchers have suggested that FMT is a superior method to oral vancomycin for the treatment [21,22], and combinations of them would be a better choice attributed to restore the intestinal microbiota [23,24]. The clinical application of FMT also includes inflammatory bowel disease, diabetes mellitus, liver cirrhosis, gut-brain disease, and others [54]. Moreover, the FMT has become a completely novel way to eradicate drug-resistant bacteria from the intestinal reservoir, which would include decolonization of extended-spectrum beta-lactamase (ESBL)-producing and carbapenemaseproducing Enterobacteriaceae, vancomycin-resistant Enterococci, or methicillin-resistant Staphylococcus aureus [55]. However, the clinical utility of FMT to displace the multidrug-resistant bacteria or treat patients with ulcerative colitis (UC) is still controversial because of little benefit shown in other papers, and the use of probiotics maybe better with potentially lower risks of adverse events [56-59]. Thus, there would be much work to reveal whether FMT will be promising in clinical application that limit opportunistic pathogens overgrowth and restore human intestinal microbiota composition and genes that profound affected by antibiotic exposure.

Perspectives
Typical antibiotics have been detected in the collective gut of the Chinese population in our previous research which provided a reference for this study of the effects of vancomycin on human gut microbiota [4]. However, there were several limitations of this study. First, repeating these experiments at least a number of times more would be better for currently stating that vancomycin causes a significant disruption on gut microbiota and confirming the benefit of FMT on vancomycin induced dysbiosis, which were not taken attributed to the costs associated with system operation and samples detection. On the other hand, the comparation of opportunistic pathogens isolated from control sample with vancomycin treated sample will also be necessary to reveal its effect in bacteria characteristic. It is also of interest to inoculate the microbiota mixture from several healthy humans as well as patient to discover the different effects of vancomycin between individuals. Further in vivo studies are also needed to verify whether the findings in this in vitro study reflect the real recovery in vivo. Moreover, research on the restoration effects of some prebiotics, probiotics, and synbiotics during and after antibiotic therapy will also be promising, which may help discover several clinical strategies to restore side effects caused by antibiotics. As the increasing of opportunistic pathogens and human disease-related genes by antibiotics exposure, which may pose a significant therapeutic challenge and take some efficient measures to reduce or even eliminate the effects after antibiotic treatment should be more critical.

Conclusions
Exposure to vancomycin significantly altered the taxonomic composition and diversity, and it subsequently increased opportunistic pathogens and human disease-related pathways. The changes were "SHIME-compartment" different with a more significant effect on the ascending colon. Moreover, bacteria that increased after vancomycin exposure were positively associated with the human disease-related pathways, while bacterial decreased were positively related to quantified ARGs. The significant shifted human gut microbiota was not recovered after two weeks of vancomycin discontinuance; however, restored thoroughly after FMT. These results may be valuable for directing future work, which may open up new perspectives for assessing the direct effects of antibiotics on the intestinal microbiota and suggested that FMT may be promising in clinical application.

Availability of data and materials
Please contact the author for data requests.

Ethics approval and consent to participate
The study was approved by the Biomedical Ethics Committees of Nankai University. The participant has given written informed consent to understand the study purpose, procedures, risks, benefits, and rights.

Consent for publication
Not applicable.

Competing interests
The authors declare that they have no competing interests.   Heatmap of antibiotic resistance genes (ARGs) in the two parts of colon with different treatment. Heatmap colors reflect relative abundance of ARGs from low (blue) to high (red).

Figure 2
Heatmap of antibiotic resistance genes (ARGs) in the two parts of colon with different treatment. Heatmap colors reflect relative abundance of ARGs from low (blue) to high (red).    LDA score (a) and cladogram of LEfSe (b) comparison analysis between the control and antibiotic groups. The red, green shading depicts bacterial taxa that were significantly higher in either the control or antibiotic groups, as indicated. Selection of discriminative taxa between the control and antibiotic groups were based on an LDA score cutoff of 3.0, and differences in the relative abundances of taxa were statistically determined based on a Mann-Whitney test at a significance level of 0.05.

Figure 5
Network analysis revealing the co-occurrence patterns between microbial taxa and human disease-related pathways. The nodes in Network were colored according to types of human disease-related pathways and microbial genera that increased (red) or decreased (green) after vancomycin exposure. The edges were colored according to positive (red) or negative (blue) correlation. A connection represents strong and significant (P value < 0.05, r > 0.6) correlation. The size of each node is proportional to the number of connections, that is, degree.

Figure 5
Network analysis revealing the co-occurrence patterns between microbial taxa and human disease-related pathways. The nodes in Network were colored according to types of human disease-related pathways and microbial genera that increased (red) or decreased (green) after vancomycin exposure. The edges were colored according to positive (red) or negative (blue) correlation. A connection represents strong and significant (P value < 0.05, r > 0.6) correlation. The size of each node is proportional to the number of connections, that is, degree.

Figure 6
Network analysis revealing the co-occurrence patterns between microbial taxa and ARG subtypes. The nodes in Network were colored according to ARG types and microbial genera that increased (red) or decreased (green) after vancomycin exposure. The edges were colored according to positive (red) or negative (blue) correlation. A connection represents strong and significant (P value < 0.05, r > 0.6) correlation. The size of each node is proportional to the number of connections, that is, degree.

Figure 6
Network analysis revealing the co-occurrence patterns between microbial taxa and ARG subtypes. The nodes in Network were colored according to ARG types and microbial genera that increased (red) or decreased (green) after vancomycin exposure. The edges were colored according to positive (red) or negative (blue) correlation. A connection represents strong and significant (P value < 0.05, r > 0.6) correlation. The size of each node is proportional to the number of connections, that is, degree.

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