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Multiomics-based Exploration Of The Role Of Gut Microbiota And Its Metabolites In Transplant Rejection

Posted on:2024-06-29Degree:DoctorType:Dissertation
Country:ChinaCandidate:J P WangFull Text:PDF
GTID:1524307202985489Subject:Surgery
Abstract/Summary:PDF Full Text Request
BackgroundOrgan transplantation is the first treatment of choice for patients with end-stage organ dysfunction.However,the survival of the allograft is usually limited.Transplant rejection is a maj or cause of impaired graft function.Increasing evidences have demonstrated the link between gut microbiota alterations and allograft outcome.However,there has been no comprehensive analysis to explore the role and the mechanism of gut microbiota and metabolites in transplant rejection.ObjectivesCharacterize the changes of structural and functional the gut microbiota in patients with antibody-mediated rejection(AMR)after kidney transplantation,and provide the basis for revealing the potential role of gut microbiota in AMR.Explore the effects of anti-graft rejection drug tacrolimus on the gut microbiota and interstinal metabolites in mice,and study the effects of tacrolimus-induced mice gut microbiota alternation on transplantation rejection and the potential mechanism.MethodsFecal specimens from patients with AMR and patients with stable renal function after kidney transplantation were subjected to 16S rRNA gene sequencing and metagenomics,and untargeted metabolomics based on liquid chromatograph-mass spectrometry(LC-MS),and the gut microbiota structure,function and intestinal metabolites between the two groups were analyzed and compared using statistical methods.Establish the mouse skin transplantation model,detect the effect of tacrolimus on the gut microbiota and interstinal metabolites of mice using 16S rRNA gene sequencing and untargeted metabolomics,and further study the effect and potential mechanism of tacrolimus-induced alternations in the gut microbiota of mice on transplant rejection using fecal microbiota transplantation.Results1.There were significant differences in the diversity and composition of gut microbiota between the AMR and control groups.A total of 123 AMR-related differential gut microbial species were identified based on macrogenetics data and LEfSe analysis.Specific microbial taxa were correlated with clinical indicators and could be used as potential biomarkers to distinguish patients in the AMR and control groups.In addition,there were 437 differential functional genes between the two groups,which were enriched on 22 pathways.2.There were 32 different intestinal metabolites between patients in the AMR and control groups.Among them,the changes of 3b-hydroxy-5-cholenoic acid,L-piperidinic acid,taurocholate and 6k-PGF1alpha-d4 were correlated with changes in gut microbial species and functions.Specific differential metabolites are correlated with clinical indicators such as Cr and BUN,and can be used as potential biomarkers to distinguish AMR and control patients.3.Tacrolimus can induce changes in the gut microbiota and interstinal metabolites in mice.The fecal microbiota transplantation for mice with allogeneic skin grafts using feces from the tacrolimus-treated mice could significantly improve the survival time of skin allograft,increase the levels of indole-3-acetic acid and the expression of aromatic hydrocarbon receptor(AHR)in the intestine,thereby increasing the proportion of Treg cells and reducing the proportion of Th 17 in lymph nodes.Conclusion1.Compared with patients with stable kidney function,patients with AMR after kidney transplantation exhibited changes in gut microbiota structure and function.2.Compared with patients with stable kidney function,patients with AMR after kidney transplantation exhibited changes in interstinal metabolic profiles,which are related to changes in gut microbiota.3.Tacrolimus could significantly improve the survival time of skin allograft by regulating the gut microbiota,upregulating the level of indole-3-acetic acid and the expression of aromatic hydrocarbon receptor,and thereby affecting the balance of Treg cells and Th17 cells.
Keywords/Search Tags:16S rRNA gene sequencing, Metagenomics, Metabolomics, Transplantation rejection, Gut microbiota
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