0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Prediction of delayed graft function by early salivary microbiota following kidney transplantation

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Abstract

          Delayed graft function (DGF) is a frequently observed complication following kidney transplantation (KT). Our prior research revealed dynamic shifts in salivary microbiota post-KT with immediate graft function (IGF), yet its behavior during DGF remains unexplored. Five recipients with DGF and 35 recipients with IGF were enrolled. Saliva samples were collected during the perioperative period, and 16S rRNA gene sequencing was performed. The salivary microbiota of IGFs changed significantly and gradually stabilized with the recovery of renal function. The salivary microbiota composition of DGFs was significantly different from that of IGFs, although the trend of variation appeared to be similar to that of IGFs. Salivary microbiota that differed significantly between patients with DGF and IGF at 1 day after transplantation were able to accurately distinguish the two groups in the randomForest algorithm (accuracy = 0.8333, sensitivity = 0.7778, specificity = 1, and area under curve = 0.85), with Selenomonas playing an important role. Bacteroidales (Spearman’s r =  − 0.4872 and p = 0.0293) and Veillonella (Spearmen’s r =  − 0.5474 and p = 0.0125) were significantly associated with the serum creatinine in DGF patients. Moreover, the significant differences in overall salivary microbiota structure between DGF and IGF patients disappeared upon long-term follow-up. This is the first study to investigate the dynamic changes in salivary microbiota in DGFs. Our findings suggested that salivary microbiota was able to predict DGF in the early stages after kidney transplantation, which might help the perioperative clinical management and early-stage intervention of kidney transplant recipients.

          Key points

          • Salivary microbiota on the first day after KT could predict DGF.

          • Alterations in salivary taxa after KT are related to recovery of renal function.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s00253-024-13236-w.

          Related collections

          Most cited references73

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

          SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Building Predictive Models inRUsing thecaretPackage

                Bookmark

                Author and article information

                Contributors
                mingyz_china@csu.edu.cn
                Journal
                Appl Microbiol Biotechnol
                Appl Microbiol Biotechnol
                Applied Microbiology and Biotechnology
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                0175-7598
                1432-0614
                1 July 2024
                1 July 2024
                2024
                : 108
                : 1
                : 402
                Affiliations
                [1 ]GRID grid.216417.7, ISNI 0000 0001 0379 7164, The Transplantation Center of the Third Xiangya Hospital, , Central South University, ; Changsha, 410013 China
                [2 ]Engineering and Technology Research Center for Transplantation Medicine of National Health Commission, Changsha, China
                Author information
                http://orcid.org/0009-0009-8878-3831
                Article
                13236
                10.1007/s00253-024-13236-w
                11217047
                38951204
                857902c7-ecf0-44a1-a039-eb5f157d3eb2
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 7 November 2023
                : 11 June 2024
                : 14 June 2024
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 81771722
                Award Recipient :
                Categories
                Genomics, Transcriptomics, Proteomics
                Custom metadata
                © Springer-Verlag GmbH Germany, part of Springer Nature 2024

                Biotechnology
                salivary microbiota,delayed graft function,early-stage prediction,kidney transplantation,perioperative period

                Comments

                Comment on this article