Super donor assessment tool for oral microbiome transplantation
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Date
2026
Authors
Nath, S.
Mittinty, M.
Zilm, P.
Santiago, P.H.R.
Ketagoda, D.K.H.
Jamieson, L.
Weyrich, L.
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BMC Microbiology, 2026; 26(1):56-1-56-12
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Sonia Nath, Murthy Mittinty, Peter Zilm, Pedro Henrique Ribeiro Santiago, Don Kevin Hashan Ketagoda, Lisa Jamieson and Laura Weyrich
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Aims Oral microbiome transplantation (OMT) involves transferring microbiota from donor to recipient. However, selecting suitable donors remains challenging due to a lack of standardised guidelines. This study developed a novel super donor assessment tool (SDAT) combining a multi-criteria decision-making (MCDM) process and an analytical hierarchical process (AHP) to identify OMT “super donors” for dental caries prevention. Methods This cross-sectional study used four sequential screening phases with data from 93 healthy participants, capturing socio-demographics, lifestyle, dietary and oral health behaviours. The SDAT employed MCDM, AHP, combining criteria with normalised and weighted ranks to establish the top 10 donors for three models: “Optimal donor” (Model 1), “Ideal donor” (Model 2), and “Sub-optimal donor” (Model 3). Donor plaque samples underwent 16S ribosomal RNA amplicon sequencing for microbial profiling, examining alpha and betadiversity, differential abundance, and network analysis. Results Alpha diversity analysis showed significant differences among groups (Kruskal-Wallis p < 0.001), with Model 1 showing the lowest diversity and Model 3 the highest. Beta diversity analysis using Permutational Multivariate Analysis of Variance revealed significant differences in microbial community composition (R² = 0.19, p = 0.001). Differential abundance analysis (False Discovery Rate < 0.05, controlling for age and sex) identified health-associated genera (Neisseria, Lautropia, Streptococcus, Veillonella) in Model 1, whereas Model 3 showed higher levels of disease-associated taxa (Treponema, Capnocytophaga). Network analysis revealed that Model 1 was organised around Actinomyces and Prevotella, Model 2 around Rothia and Haemophilus, and Model 3 was dominated by pathogenic taxa. Conclusion SDAT provides a systematic, transparent framework for super-donor selection, ensuring precision and reproducibility in donor rankings. The scoring system standardises the donor selection process, the effectiveness of donor screening, and reduces the risk of adverse events for OMT.
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© The Author(s) 2025. 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 h t t p : / / c r e a t i v e c o m m o n s . o r g / l i c e n s e s / b y / 4 . 0 /.