Impact of the Post-Transplant Period and Lifestyle Diseases on Human Gut Microbiota in Kidney Graft Recipients

Abstract

Gaining long-term graft function and patient life quality remain critical challenges following kidney transplantation. Advances in immunology, gnotobiotics, and culture-independent molecular techniques have provided growing insights into the complex relationship of the microbiome and the host. However, little is known about the over time-shift of the gut microbiota in the context of kidney transplantation and its impact on both graft and health stability. Here we aimed to characterize the structure of gut microbiota within stable kidney graft recipients. We enrolled forty kidney transplant patients after at least three months of transplantation and compared them to eighteen healthy controls. The overall microbial community structure of the kidney transplanted group was clearly different from control subjects. We found lower relative abundances of Actinobacteria, Bacteroidetes, and Verrucomicrobia within the patient group and a higher abundance of Proteobacteria compared to the control group. Both richness and Shannon diversity indexes were significantly lower in the kidney graft recipients than in healthy controls. Post-graft period was positively correlated with the relative abundance of the Proteobacteria phylum, especially Escherichia.Shigella genus. Interestingly, only Parabacteroides was found to significantly differentiate patients that were not suffering from lifestyle diseases and those who suffer from post-graft complications. Furthermore, network analysis showed that the occurrence of lifestyle diseases was significantly linked with a higher number of negative interactions of Sutterella and Succinivibrio genera within patients. This study characterizes gut microbiome fluctuation in stable kidney transplant patients after a long post-allograft period. Analysis of fecal microbiota could be useful for nephrologists as a new clinical tool that can improve kidney allograft monitoring and outcomes.

Keywords

• 16S rRNA gene
• amplicon sequencing
• dysbiosis
• bioinformatics
• kidney transplantation