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A diverse and distinct microbiome inside living trees

Nature volume 644, pages 1039–1048 (2025)Cite this article

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Abstract

Despite significant advances in microbiome research across various environments1, the microbiome of Earth’s largest biomass reservoir—the wood of living trees2—remains largely unexplored. Here, we illuminate the microbiome inhabiting and adapted to wood and further specialized to individual host tree species, revealing that wood is a harbour of biodiversity and potential key players in tree health and forest ecosystem functions. We demonstrate that a single tree hosts approximately one trillion bacteria in its woody tissues, with microbial communities distinctly partitioned between heartwood and sapwood, each maintaining unique microbiomes with minimal similarity to other plant tissues or ecosystem components. The heartwood microbiome emerges as a particularly unique ecological niche, distinguished by specialized archaea and anaerobic bacteria driving consequential biogeochemical processes. Our findings support the concept of plants as ‘holobionts’3,4—integrated ecological units of host and associated microorganisms—with implications for tree health, disease and functionality. By characterizing the composition, structure and functions of tree internal microbiomes, our work opens up pathways for understanding tree physiology and forest ecology and establishes a new frontier in environmental microbiology.

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Fig. 1: Bacterial and archaeal community structure and metabolism in wood microbiome.
Fig. 2: Fungal community structure and metabolism in wood microbiome.
Fig. 3: Microbial abundance, metabolism and gas production in heartwood and sapwood.
Fig. 4: Black oak prokaryotic microbiome composition and source tracking across plant tissues.
Fig. 5: Black oak fungal microbiome composition and source tracking across plant tissues.

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Data availability

The data that support the findings of this study are publicly accessible from the NCBI database under accession number PRJNA1124946.

Code availability

All code used in this analysis, along with all necessary files, are available on GitHub at https://github.com/jgewirtzman/tree-microbiome.git.

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Acknowledgements

We thank M. Spicer, J. Orefice, M. Valido, T. Harris, M. Ashton, B. Girgenti, L. Logozzo, T. Maavara, J. Rosentreter, L. Welker, A. Polussa, M. Birkey, M. Hlavka, E. Jose, C. Ledezma, A. Gewirtzman and C. Thibodeau for their help in the field. We also thank C. Butler, A. Rubenstein, M. Furze, D. Angel, J. Karosas, T. Kolodkin and E. Ward for assistance in the laboratory. We acknowledge the University of Minnesota Genomics Center for its technical assistance. Thank you to members of the Bradford Lab for feedback on earlier drafts of this manuscript, and to the Yale Forests faculty, staff and facilities for enabling the research. Illustrations in Figs. 4a and 5a were created using BioRender (https://biorender.com). Funding for this research was provided by the National Science Foundation Graduate Research Fellowship Program (NSF-GRFP), the Yale Institute for Biospheric Studies (YIBS) and the Kohlberg-Donohoe Research Fellowship to J.G.; the National Defense Science and Engineering Graduate (NDSEG) Fellowship to W.A.; and additional support from the Yale Center for Natural Carbon Capture and the Yale Planetary Solutions Project to J.P., M.A.B., P.A.R., C.R.B., M.C.D., J.G. and W.A.

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Author notes

  1. These authors contributed equally: Wyatt Arnold, Jonathan Gewirtzman

Authors and Affiliations

  1. Department of Chemical and Environmental Engineering, School of Engineering and Applied Science, Yale University, New Haven, CT, USA

    Wyatt Arnold, Cade Brown & Jordan Peccia

  2. Yale School of the Environment, Yale University, New Haven, CT, USA

    Jonathan Gewirtzman, Peter A. Raymond, Marlyse C. Duguid, Craig R. Brodersen & Mark A. Bradford

  3. The Forest School, Yale School of the Environment, Yale University, New Haven, CT, USA

    Marlyse C. Duguid, Craig R. Brodersen & Mark A. Bradford

  4. Department of Earth and Planetary Science, Yale University, New Haven, CT, USA

    Naomi Norbraten

  5. Universidad Nacional de San Antonio Abad del Cusco, Cusco, Peru

    Qespi T’ika Vizcarra Wood

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Contributions

J.G. and W.A. contributed equally to this work. J.G. and W.A. conceived the study, performed data curation and conducted formal analysis. Funding was acquired by J.P., M.A.B., P.A.R., M.C.D., C.R.B., J.G. and W.A. The investigation was carried out by J.G., W.A., C.B., N.N. and Q.T.V.W. Methodology was developed by W.A., J.G., C.R.B., M.A.B. and J.P. Project administration was handled by J.G., W.A. and J.P., with resources provided by J.P., P.A.R. and M.A.B. W.A. and J.G. were responsible for software. Supervision was overseen by J.P., M.A.B., P.A.R., C.R.B., M.C.D., J.G. and W.A. Validation of the results was conducted by W.A., J.G. and J.P. Visualization was created by W.A. and J.G. Original drafts were written by W.A., J.G., J.P. and M.A.B., and all authors reviewed and edited the final manuscript, including W.A., J.G., P.A.R., M.C.D., C.R.B., C.B., N.N., Q.T.V.W., M.A.B. and J.P.

Corresponding authors

Correspondence to Jonathan Gewirtzman or Jordan Peccia.

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Nature thanks Jack Gilbert and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data figures and tables

Extended Data Fig. 1 Global distribution of studied tree genera.

The species included in this survey represent 16 species from 11 genera which have a global distribution, with the map colorized by the number of species within this set of genera native to each country (data from GlobalTreeSeacrch).

Extended Data Fig. 2 Prokaryotic abundance variation across tree species in wood tissues.

Prokaryotic abundances within the wood of living trees, as determined by 16S qPCR (per dry gram wood). Abundance distributions are split by species, with the mean heartwood and sapwood abundance identified by points per species. Estimates of the average 16S copies (assuming 4 copies per cell49) in three different biological media (per gram of human stomach fluid39, seawater50, and soil51) are identified in vertical red dashed lines. The number of cores sampled per species ranged from n = 2 to n = 38 (see Materials and Methods); a distribution is not shown for species with n < 3.

Extended Data Fig. 3 Alpha diversity patterns in wood and soil microbial communities.

Alpha diversity measures for (left) 16S rRNA and (right) ITS communities. Panels A-B: Chao1 diversity by sample type. Panels C-D: Chao1 diversity split by tree species and sample type. Panels E-F: Shannon diversity by sample type. Panels G-H: Shannon diversity split by tree species and sample type. Mean (±SD) represented by the larger outlined points and error bars. Individual points are unique samples. All analyses performed on rarefied data.

Extended Data Fig. 4 Phylogenetic congruence between tree species and their wood microbiomes.

The A.) phylogenetic relatedness of the 16 tree species included in this study, based on the PhytoPhylo megaphylogeny. Both Latin binomial names and species codes are included at the tips. Using both B, C.) 16S sequencing data and D, E.) ITS sequencing data, phylogenies showing the relatedness of living wood microbiomes between tree species were produced based on beta diversity (weighted UniFrac distance) similarity. Species codes in red represent tip pairings between microbial communities that match the phylogenetic relatedness between host tree species.

Extended Data Fig. 5 Microbial source tracking between wood tissues and surrounding environments.

Source-tracking results produced using FEAST, treating both A, C.) heartwood and B, D.) sapwood as “sinks.” For heartwood analyses, the contribution of sapwood, organic soil, and mineral soil communities was assessed, with “unknown” corresponding to taxa with indeterminate origins. For sapwood, the contribution of heartwood, organic soil, and mineral soil communities was assessed. Results are split by tree species, with the central number representing the average contribution out of all samples (out of 1). Analyses were performed in a paired manner, meaning that contribution estimates were assessed on a per tree basis (e.g., wood and soil samples specific to each tree, rather than bulk groups).

Extended Data Fig. 6 Community similarity patterns within and between wood tissue types.

Left panels: Barplots of estimated marginal means (EMMeans) of weighted UniFrac distances for intra- and inter-species tissue comparisons, grouped into within-species and between-species categories. EMMeans calculated using linear mixed-effects models with random effects for repeated sample involvement. Error bars show standard errors; pairwise comparisons adjusted using Sidak correction with significant differences denoted by distinct letters. Sample types: Sapwood-Heartwood, Sapwood-Sapwood, and Heartwood-Heartwood comparisons. Right panels: Heatmaps of mean weighted UniFrac distances between communities grouped by species and tissue type. Only groups with n > 5 wood samples are included in heatmaps. Distance values were averaged and hierarchically clustered. Tissue annotations show sapwood (blue) and heartwood (brown). Color gradient represents distance with red indicating greater dissimilarity and blue indicating greater similarity.

Extended Data Fig. 7 Unique and shared microbial taxa across forest compartments.

Venn diagrams showing the counts of unique and shared ASVs in each forest compartment for 16S (top) and ITS (bottom). ASV tables were filtered to remove chloroplast and mitochondrial DNA, as well as ultra-low abundance ASVs (≤10 reads). Percentages indicate the proportion of total ASVs in each compartment.

Extended Data Fig. 8 Alpha diversity across black oak tissue and environmental samples.

Alpha diversity estimates, using Chao1 and Shannon indices, for varying tissue and environmental samples from the black oak study, split by (top) prokaryotic and (bottom) fungal communities. Bar heights represent mean diversity, with the error bars representing ± SE.

Extended Data Fig. 9 Taxonomic composition across black oak compartments.

Top: Heatmaps showing relative abundance of the top 25 most abundant prokaryotic (top) and fungal (bottom) classes across different compartments of Black Oak (Quercus velutina). Samples were rarefied to 3,500 reads (prokaryotic) and 4,000 reads (fungal) prior to analysis. Relative abundance is displayed on a log scale with color intensity indicating abundance percentage (darker red = higher abundance). Classes are ordered by total abundance across all compartments.

Extended Data Fig. 10 Heartwood microbiome variation with tree height in black oak.

Variation in the A. fungal and prokaryotic heartwood microbiomes with tree height in the black oak (central numbers represent distance from ground in cm). The relatedness between those tissues, based on weighted UniFrac distances, is represented in B. and D., with ordination (PCoA, weighted UniFrac) of those same tissues in C. and E.

Supplementary information

Supplementary Information

Supplementary Table 1 and Figs. 1–12. The supplementary table provides species identification codes for all 16 tree species studied. The supplementary figures collectively demonstrate distinct microbial communities between heartwood and sapwood across multiple tree species, with detailed taxonomic compositions, functional predictions, gas concentration measurements and comprehensive analysis of a single black oak tree sectioned into multiple compartments. Includes quality control data (rarefaction curves) and statistical analyses (UniFrac distances, differential abundance testing).

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Arnold, W., Gewirtzman, J., Raymond, P.A. et al. A diverse and distinct microbiome inside living trees. Nature 644, 1039–1048 (2025). https://doi.org/10.1038/s41586-025-09316-0

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