Article https://doi.org/10.1038/s41467-025-62567-3 Wood decay under anoxia by the brown-rot fungus Fomitopsis pinicola Robert Röllig 1, Annie Lebreton 1,2, Lucia Grenga 3, Rosalie Cresswell 4, Signe Lett5,6, Theodora Tryfona 7, David Navarro 1,8, Julien Lambert1, Sacha Grisel 1,9, Isabelle Gimbert1, Helle Jakobe Martens5, Guylaine Miotello3, Xiaolan Yu7, Elodie Drula 1,2, Marie-Noelle Rosso 1, Lionel Tarrago 1, BernardHenrissat 10, Katja Johansen 7, RayDupree 4,11, JeanArmengaud 3, Paul Dupree 7 & Jean-Guy Berrin 1 Basidiomycete fungi are the main decomposers of dead wood with an impact on the global carbon cycle. Their degradative mechanisms have been well- studied under aerobic conditions. Here, we study their activity in oxygen- depleted environments. We use metaproteomics in a field study to identify active wood-decomposing fungi and their enzymes at different depths from the wood surface, including in oxygen-depleted conditions. In vitro, we observe that the brown-rot fungus Fomitopsis pinicola can grow on wood in complete anoxia. Using 13C solid-state NMR, we demonstrate the degradation of plant cell-wall polysaccharides and fungal growth in the absence of oxygen. Proteomic analyses reveal that F. pinicola switches from a Fenton chemistry- based process under aerobic conditions to the secretion of plant cell wall- active enzymes in anoxia. Our finding that wood decay fungi can thrive in complete anoxia provides a deeper understanding of lignocellulose degrada- tion mechanisms in nature and raises opportunities for the development of bio-inspired anaerobic processes. Forests are a large and persistent carbon sink that stores 45% of the total carbon (C) of terrestrial ecosystems1,2. An equilibrated forest microbiome is required to enable a continuous C cycle and ensure the forest’s resilience towards global changes3. While plants are respon- sible for the large ecosystem uptake of C through photosynthesis, fungal saprotrophs are the main decomposers of lignocellulose4. The most efficient fungal wood decayers have been empirically classified into soft-, white-, and brown-rots based on the appearanceof the degraded wood following colonisation. Their decaying strategies rely on complex mechanisms combining abiotic chemistry with enzymatic activities5. Differences in the mode of wood decay between brown-rots and white-rots have been supported in recent years by comparing the number of genes encoding plant cell wall-degrading enzymes (PCWDEs) in fungal genomes and machine-learning techniques4,6–8. White-rot fungi secrete a complete arsenal of PCWDEs, including oxidative and hydrolytic enzymes, to degrade the different plant cell wall polymers6,9. However, brown-rot fungi, which are predominant decayers of softwood in boreal forests, degrade holocellulose in a staggeredmechanism10,11, initiated by the controlled biochemical and enzymatic formation of highly reactive and short- Received: 9 April 2024 Accepted: 21 July 2025 Check for updates 1INRAE, Aix Marseille Univ., BBF, Biodiversité et Biotechnologie Fongiques, Marseille, France. 2Architecture et Fonction desMacromolécules Biologiques, Aix- Marseille Univ., CNRS, INRAE, Marseille, France. 3Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), SPI, Bagnols-sur-Cèze, France. 4Department of Physics, University of Warwick, Coventry, UK. 5Department of Geosciences and Natural Resource Management, University of Copenhagen, Frederiksberg C, Denmark. 6Department of Biology, University of Copenhagen, Copenhagen, Denmark. 7Department of Bio- chemistry, University of Cambridge, University of Cambridge, Cambridge, UK. 8INRAE, Aix Marseille Univ., CIRM-CF, Marseille, France. 9INRAE, Aix Marseille Univ., 3PE,Marseille, France. 10Department of Biotechnology and Biomedicine (DTUBioengineering), Technical University of Denmark, Kgs. Lyngby, Denmark. 11Deceased: Ray Dupree. e-mail: jean-guy.berrin@inrae.fr Nature Communications | (2025) 16:7352 1 12 34 56 78 9 0 () :,; 12 34 56 78 9 0 () :,; http://orcid.org/0000-0001-9940-6788 http://orcid.org/0000-0001-9940-6788 http://orcid.org/0000-0001-9940-6788 http://orcid.org/0000-0001-9940-6788 http://orcid.org/0000-0001-9940-6788 http://orcid.org/0000-0002-8301-9983 http://orcid.org/0000-0002-8301-9983 http://orcid.org/0000-0002-8301-9983 http://orcid.org/0000-0002-8301-9983 http://orcid.org/0000-0002-8301-9983 http://orcid.org/0000-0001-5560-1717 http://orcid.org/0000-0001-5560-1717 http://orcid.org/0000-0001-5560-1717 http://orcid.org/0000-0001-5560-1717 http://orcid.org/0000-0001-5560-1717 http://orcid.org/0000-0001-8061-2530 http://orcid.org/0000-0001-8061-2530 http://orcid.org/0000-0001-8061-2530 http://orcid.org/0000-0001-8061-2530 http://orcid.org/0000-0001-8061-2530 http://orcid.org/0000-0002-1618-3521 http://orcid.org/0000-0002-1618-3521 http://orcid.org/0000-0002-1618-3521 http://orcid.org/0000-0002-1618-3521 http://orcid.org/0000-0002-1618-3521 http://orcid.org/0000-0002-3266-8270 http://orcid.org/0000-0002-3266-8270 http://orcid.org/0000-0002-3266-8270 http://orcid.org/0000-0002-3266-8270 http://orcid.org/0000-0002-3266-8270 http://orcid.org/0000-0001-6983-0107 http://orcid.org/0000-0001-6983-0107 http://orcid.org/0000-0001-6983-0107 http://orcid.org/0000-0001-6983-0107 http://orcid.org/0000-0001-6983-0107 http://orcid.org/0000-0002-9168-5214 http://orcid.org/0000-0002-9168-5214 http://orcid.org/0000-0002-9168-5214 http://orcid.org/0000-0002-9168-5214 http://orcid.org/0000-0002-9168-5214 http://orcid.org/0000-0001-8317-7220 http://orcid.org/0000-0001-8317-7220 http://orcid.org/0000-0001-8317-7220 http://orcid.org/0000-0001-8317-7220 http://orcid.org/0000-0001-8317-7220 http://orcid.org/0000-0001-7115-8137 http://orcid.org/0000-0001-7115-8137 http://orcid.org/0000-0001-7115-8137 http://orcid.org/0000-0001-7115-8137 http://orcid.org/0000-0001-7115-8137 http://orcid.org/0000-0002-3434-8588 http://orcid.org/0000-0002-3434-8588 http://orcid.org/0000-0002-3434-8588 http://orcid.org/0000-0002-3434-8588 http://orcid.org/0000-0002-3434-8588 http://orcid.org/0000-0002-7587-5990 http://orcid.org/0000-0002-7587-5990 http://orcid.org/0000-0002-7587-5990 http://orcid.org/0000-0002-7587-5990 http://orcid.org/0000-0002-7587-5990 http://orcid.org/0000-0002-3334-0429 http://orcid.org/0000-0002-3334-0429 http://orcid.org/0000-0002-3334-0429 http://orcid.org/0000-0002-3334-0429 http://orcid.org/0000-0002-3334-0429 http://orcid.org/0000-0003-1589-445X http://orcid.org/0000-0003-1589-445X http://orcid.org/0000-0003-1589-445X http://orcid.org/0000-0003-1589-445X http://orcid.org/0000-0003-1589-445X http://orcid.org/0000-0001-9270-6286 http://orcid.org/0000-0001-9270-6286 http://orcid.org/0000-0001-9270-6286 http://orcid.org/0000-0001-9270-6286 http://orcid.org/0000-0001-9270-6286 http://orcid.org/0000-0001-7570-3745 http://orcid.org/0000-0001-7570-3745 http://orcid.org/0000-0001-7570-3745 http://orcid.org/0000-0001-7570-3745 http://orcid.org/0000-0001-7570-3745 http://crossmark.crossref.org/dialog/?doi=10.1038/s41467-025-62567-3&domain=pdf http://crossmark.crossref.org/dialog/?doi=10.1038/s41467-025-62567-3&domain=pdf http://crossmark.crossref.org/dialog/?doi=10.1038/s41467-025-62567-3&domain=pdf http://crossmark.crossref.org/dialog/?doi=10.1038/s41467-025-62567-3&domain=pdf mailto:jean-guy.berrin@inrae.fr www.nature.com/naturecommunications lived hydroxyl radicals through Fenton chemistry, which is believed to be the primary causeof the decay5,12–14. For the second stage, brown-rot fungi employ PCWDEs, yet these are a smaller set enzymes compared to white-rot fungi5,8. Lignin and crystalline cellulose remain because they lack of key hydrolytic and oxidative enzymes (e.g. cellobiohy- drolases, lytic polysaccharide monooxygenases, multicopper oxi- dases, and peroxidases)4,15,16. Despite these recent advances in the genomics and biochemistry of fungal saprotrophs, improved under- standing of wood decay is needed. The mechanisms used by white-rot and brown-rot fungi to decay wood were deciphered mostly using cultures made at an ambient O2 concentration of 20.9%, which facilitates the experimental set-up17. While such concentration is relevant to the decay in the surface of wood or in biotechnological set-ups with air supply, it does not cor- respond to the conditions naturally encountered by fungi inside the wood. Here, the O2 concentration can decrease to a very low percen- tage as a function of depth in the wood18,19. Despite the physiological relevance of evaluating the influence of O2 concentrations on the ability of white-rot and brown-rot wood-decayers to grow, relatively few studies have addressed this aspect. Cultures under limited O2 concentrations (hypoxia) have shown that some white-rot and brown- rot fungi can grow at low levels of O2 20 thanks to a metabolic reorga- nisation allowing them to withstand the hypoxic constraint21,22. How- ever, it remains unclear whether fungal wood decay can take place in the absence of O2 (anoxia). Here, we explored in situ wood decaywith particular emphasis on the constraints imposed by restricted O2 availability towards the cen- tral part of the wood. Using metaproteomics on wood stumps and trunks collected in nature, we identified the basidiomycetes fungi at play and their secreted PCWDEs. A targeted in vitro approach undertaken on the brown-rot fungus Fomitopsis pinicola (F. pinicola) uncovered that fungal wood decay can occur in anoxic conditions and provide insights into fungal strategies for lignocellulosedegradation in O2-deprived environments. Results A restricted microbial community decomposes wood under O2 constraints in nature To investigate the impact of O2 depletion on microbial wood decay in nature, we collected decaying spruce wood (Picea abies) in a boreal forest at different stages of decay, i.e. trees that were cut down 3, 10, and 15 years before sampling (Fig. 1a, Supplementary Fig. 1a). Using a needle O2 sensor, we could penetrate the two stumps with the highest grade of decay (chopped down 10 and 15 years before sampling), and measured a strong depletion of O2 beneath the surface of dead wood (Fig. 1b, Supplementary Fig. 1b). Macroscopically, we observed fungal mycelium in areas with very restricted O2 concentrations, indicative of the growth of some wood-decaying fungi under minimal O2 con- centrations. To get access to the active microbial species and their enzymatic portfolio, we collected samples at different depths in the dead wood, i.e. from the external layer to the centre of wood stumps and trunks (Fig. 1a) and we used a metaproteomic approach because recent breakthroughs in high-resolution tandem mass spectrometry allow to investigate microbiome functionality by identifying and quantifying active proteins. We identified 11,551 proteins of which 93% pertained to fungal genera (see Supplementary Data 1). Only a restricted number of microbial genera, mostly tree-specific, were detected in trunk and stump samples (Fig. 1c, Supplementary Fig. 2). The brown-rot F. pinicola dominated the microbial community of the decaying trunk cut down 3 years before sampling (Supplementary Fig. 1 | Metaproteomic identification of fungi and their enzymes at different wood depths. a Summary of the experimental design. All protein extractions were carried out in parallel with three independent replicates per sample. Pictures were drawn with Inkscape. b O2 profiles measured in P. abies wood of different decay ages. Individual lines are separate profiles in the same piece of wood, and each line represents an individual profile measured at a distinct spot from the wood surface (see Supplementary Fig. 1b). Measurements stopped before 40mm depth and could not penetrate further into the wood. Wood of 3 years decay was not soft enough to allow the dioxygen probe to penetrate. c Taxonomic assignation of the fungal proteins extracted from the samples. Genus prevalence, estimated as the cumulative NSAF (normalized spectral abundance factor) percentage of proteins assigned to each genus, is displayed for each sample analysed. d Secreted carbo- hydrate active enzymes (CAZymes) prevalence in the samples. The abundance of CAZymes acting on key wood substrates is estimated by the cumulative NSAF percentage of the corresponding CAZymes. 3ydT: 3 years decayed trunk, 3ydS: 3 years decayed stump, 10ydS: 10 years decayed stump, 15ydS: 15 years decayed stump, cen. centre, int. intermediate, ext. external part of the wood, near the surface. Article https://doi.org/10.1038/s41467-025-62567-3 Nature Communications | (2025) 16:7352 2 www.nature.com/naturecommunications Figs. 2 and 3). The species identity—F. pinicola (Sw.) P. Karst.—was confirmed using molecular tools (Genbank sequence ID PP277039). Heterobasidion sp., a saprotrophic white-rot species, was detected in the centre of the same trunk, and dominated the corresponding stump. In this stump, other species, such as the white-rot Cristinia sp. appeared confined to the centre and intermediary part of the wood. In the 10 years decayed stump, the white-rot Resinicium sp. was the only microorganism detected. Finally, the 15 years decayed stump was colonised by a broader variety of fungal saprotrophs (Meripilus, Trametes) together with mycorrhizal fungi (Russula, Laccaria) and diverse bacteria within Acidipila, Acidisphaera, Acid- obacteria, Dyella and Methylovirgula genera (Supplementary Fig. 2). Overall, this in vivo proteotyping approach unveiled distinct colonisation patterns of deadwood samples by a specific subset of fungal species, some being present across the different depths from normoxia (20.9% O2) towards anoxia. To identify the enzymes at play during in vivowood decay, we assigned putative function to 85%of the proteins (accounting for 91% of the captured signal) (Supplementary Fig. 4). The methodology developed allowed the identification of secreted enzymes, including carbohydrate-active enzymes (CAZymes) involved in the degradation of holocellulose, and lignin, indicating that the detected fungi were actively decaying the wood (Fig. 1d, Supple- mentary Fig. 4). Fomitopsis pinicola can grow and decay wood in anoxia The presence of the brown-rot fungus F. pinicola at the centre of the trunk (Fig. 1c, Supplementary Figs. 2 and 3) attracted our attention since brown-rot fungi are known to rely on Fenton chemistry to decay softwood and these reactions require hydrogen peroxide, and thusO2, which is depleted in the centre of dead wood. We thus hypothesised the existence of an undescribed alternative pathway allowing wood decomposition in a limitedO2 environment. To test this hypothesis,we assessed the impact ofO2 depletionon the growthof F. pinicola and on wooddegradationbydesigning in vitro set-ups tomeasure and control this parameter. Of note, we have used milled pine wood (<1.5mm particle size) in all experimental set-ups. The first system developed was a solid-state culture set-up in a column that mimicked the entire radial profile in the wood and allowed to non-intrusively measure the O2 gradient between the top and the bottom, i.e. from normoxia (proxy of the surface of the tree) to anoxia (proxy of the heart of the tree) (Fig. 2a). Initially, we strived to determine the minimum O2 level required for the saprotroph to colonise the substrate, but surprisingly, we observed the migration of the fungus throughout the entire O2 gradient and into the anoxic zone at the bottom of the col- umn (Fig. 2a). To confirm this unexpected observation, we developed a second solid-state culture system in Roux flaskswith either air or N2 to provide 4 8 126 10 142 time (days) 10 O 2 c on ce nt ra tio n (% ) 15 20.9 0 5 a diffusing air O2 sensing patches (in the cylinder) gas permeable sterile membrane fungal mycelium 100 m m b humidified gas air N2 c normoxia 20.9% O2 anoxia 0.0% O2 20.0 15.0 10.0 5.0 gr ow th (x -ti m es ) normoxia anoxia d Fig. 2 | Solid-state cultures of Fomitopsis pinicola in normoxia and anoxia. a Experimental set-upmimicking the O2-gradient during saprotrophic colonisation with non-intrusive measurements of O2 concentrations at the top (blue patch) and the bottom (white patch). The picturewasdrawnwith Inkscape.bO2 concentration measured during the growth of F. pinicola in the set-up at the air-wood interphase (blue) and at the bottom of the column (white). c In vitro saprotrophic solid-state cultures of F. pinicola on softwood in normoxia and anoxia. The experimental set- up ensured constant normoxia (air) and anoxia (N2 with O2 < 2 ppm) (Supple- mentary Fig. 5). Scanning electron microscopy confirmed the presence of fungal mycelium (framed in dotted lines) in both normoxia and anoxia conditions. Scale bar represents 50 µm. d Box plots depict fungal growth (after 14 days) assessed using quantitative PCR in four biological replicates (n [normoxia] = 34, and n [anoxia] = 33). In each box plot, the lower and upper boundaries of the box represent the first quartile (Q1) and the third quartile (Q3), respectively. The whiskers extend from the quartiles to theminimumandmaximum values within 1.5 times the interquartile range. Of note, the water content remained stable between 71.6–75.0% (mass) (73.8% at the start of the cultivation) in both conditions. Article https://doi.org/10.1038/s41467-025-62567-3 Nature Communications | (2025) 16:7352 3 www.nature.com/naturecommunications a stable normoxic or anoxic environment, respectively (Supplemen- tary Fig. 5, Fig. 2c). This experimental set-up demonstrated the ability of F. pinicola to grow under anoxia in twoweeks. Indeed, the growth of the mycelium, as assessed qualitatively by microscopy and quantita- tively by qPCR, was similar in normoxia and anoxia (Fig. 2d). Of note, we confirmed the growth of F. pinicola on wood in anoxia using alternative culture configurations in an anaerobic jar and an O2- depleted bioreactor (Supplementary Fig. 6). In the solid-state culture conditions (Fig. 2c), F. pinicola decayed wood to the same extentwith 7.4–13.2%mass loss (wooddryweight) in normoxia and 8.0–8.9% in anoxia. Furthermore, we confirmed holo- cellulose and pectin degradation by the fungus through the identifi- cation of glucose and the respective sugar monomers of glucuronoarabinoxylan, galactoglucomannan, andpectin components (Supplementary Fig. 7, Supplementary Fig. 8). Interestingly, holo- cellulose monomers (i.e. glucose, xylose, mannose) and the main component of pectin (galacturonic acid), were primarily detected in anoxia (Supplementary Figs. 7a, b and 8a). A deeper saccharide ana- lysis of the colonised wood using carbohydrate gel electrophoresis (PACE)23 revealed improved accessibility for the structural poly- saccharide backbones independent of the O2 concentration during cultivation compared to the untreated sample (Supplementary Fig. 7c–e). We attribute this improved accessibility to (i) substantial Fenton chemistry-mediated cleavage of glycosidic bonds under nor- moxic condition, and (ii) Fenton-independent modifications under anoxia. To further investigate this hypothesis, we measured the key reagent in Fenton reactions (i.e. H2O2) as well as oxalate (Supple- mentary Fig. 8b), its potential precursor24, which we observed micro- scopically in both culture conditions (Supplementary Fig. 9).While the amount of soluble oxalate was not significantly increased in normoxia, we detected considerably higher concentrations of H2O2 and a lower pH (Fenton-promoting acidic environment) in normoxia compared to the O2-depleted cultures. Therefore, the normoxic condition provided the core prerequisites for promoting the formation of short-lived hydroxyl radicals, which are claimed to be essential to brown-rot wood decay. In contrast, in the O2-depleted conditions, these requirements were not fulfilled. In anoxia, Fomitopsis pinicola decays wood polysaccharides to build its cell wall To identify changes in the molecular architecture of pine cell walls induced by F. pinicola growth, we analyzed with solid-state NMR (ssNMR) 13C enriched pine wood25 before and after 28 days of fungal wood decay (solid-state cultures). The quantitative Direct Polarization (q-DP) 1DNMR spectra, normalized to the celluloseC41 peak (89 ppm), showed significant differences in the relative abundance of cell wall components (Supplementary Fig. 10), with the mannan carbon 1 peak at ~101 ppm (M1) being significantly smaller in the decayed wood. Furthermore, thedecayedwood showedadecrease in the acetate peak (AcetateCH3, ~21 ppm). In softwoods such as pine, mannan is the only acetylated hemicellulose26. Therefore, the observed decrease in acet- ylation in the q-DP spectrum can be attributed to the reduction of acetylated mannan. Additionally, two new peaks were observed in the decayed sample at 93 ppm and 97 ppm, corresponding to newly formed unknown oligo/polysaccharide reducing ends27, indicating that F. pinicola degraded cell wall polysaccharides. There was also a significant increase in aliphatics (~30 ppm) and many changes in the aromatic region (110–155 ppm). Further information was revealed from the 2D 30ms CP-PDSD 13C NMR spectra (Supplementary Fig. 11). Clear differences were observed in the mannan C4-C6 cross-peak (M4-M6, 80.3, 61.6) ppm confirming the reduction of mannan in the rotting pine wood (Fig. 3A). It was also evident that the xylan threefold (Xn3f) C4-C5 cross-peak (77.8, 63.7) ppmwas significantly decreased in rotting pinewoodwhilst the bound twofold (Xn2f)28 C4-C5 cross-peak (82.0, 64.0) ppm also showed a significant but less marked reduction (Fig. 3A). These changes in mannan and xylan were also clearly visible in the C1-C6 region of the spectrum (Supplementary Fig. 11 and Supplementary Fig. 12). Inter- estingly, we found evidence that F. pinicola incorporated 13C-labeled pine wood polysaccharides into its own cell wall. Indeed, we identified exclusively in the rotting pine sample C3-C4 cross-peaks at (87.0, 68.3) ppm (Fig. 3B) and C1–C4 (103.9, 68.3) ppm (Supplementary Fig. 11), corresponding to β-1,3-glucan29 and also the C2–C1 peak cross peak at (55.4, 103.9) ppm (Fig. 3B) corresponding to chitin30. It is not possible to know from the NMR spectra whether or not cellulose is degraded because we needed to use cellulose C4(1) as a cell wall internal refer- ence for spectral normalisation. In conclusion, ssNMR revealed that under anoxia F. pinicola can metabolize xylan and mannan from pine cell walls, and uses these hemicellulose polysaccharides as a carbon source to synthesize fungal cell wall polysaccharides, including β-1,3- glucan and chitin. Secretion of a complete set of PCWDEs in anoxia To understand how the degradation could occur without Fenton chemistry, the enzymatic machinery of F. pinicola was explored using mass spectrometry under anoxia and normoxia conditions (experi- mental set-up from Fig. 2c). Cumulatively, approx. 1200 proteins were identified in the normoxic and anoxic conditions (see Supplementary Data 1 and Supplementary Fig. 13 for the assessment of reproducibility in biological replicates). Most of the proteins were detected in com- parable quantities in these two conditions, including key enzymes of energy processing and regulation (Supplementary Fig. 14). Note- worthy, hydrolases (EC 3) accounted for themain differencewith >25% increased abundance in anoxia (vide infra). To highlight the main dif- ferences between the two conditions, we focused on the most differentially-produced proteins in each condition. Strikingly, a puta- tive oxalate oxidase stood out on the top under normoxia, while being absent in anoxia (Fig. 4a). This enzyme (EC 1.2.3.4) catalyses the for- mation of H2O2 from oxalic acid in an acidic environment31,32, and hence confirms Fenton-mediated wood decay in the presence of O2. Under anoxia, the top 25 most differentially-produced proteins dis- closed a different trend with the striking presence of most of the PCWDEs encoded by the genome of F. pinicola, in particular, glycoside hydrolases (GHs, EC 3.2.1) targeting cellulose, hemicelluloses and pectin (Fig. 4). TwoGH10 xylanases, three GH43 arabinofuranosidases, and a single GH115 glucuronidase, which cleave glucuronoarabinox- ylan ranked high in abundance in anoxia, but were not detected in normoxia. Consistently, galactoglucomannan-degrading enzymes (one GH5_7 mannanase and three GH27 galactosidases) and a CE15 methyl-glucuronoyl esterase, targeting lignin-xylan ester bonds, were exclusively detected in anoxia. Additional PCWDEs targeting the hemicellulose side chains (GH51 and CE16), cellulose (e.g. GH5_5) and pectin (e.g. GH28) were significantly increased in anoxia (Fig. 4). The endo-xylanase and endo-glucanase activity were confirmed from the secretomes only in the anoxia condition using cyclophellitol-derived activity-based probes (Supplementary Fig. 15). Some proteins of unknown function were also preferentially secreted under anoxia conditions (Fig. 4a). Noteworthy, the protein corresponding to DUF1793 was already identified in Pycnoporus coccineus secretomes induced on wood33, suggesting a potential role related to wood decay. In conclusion, an extensive set of PCWDEs targeting the linkages of glucuronoarabinoxylan, galactoglucomannan, cellulose, and pectin are secreted preferentially or exclusively in anoxic conditions (Fig. 4b). Discussion The global approach we initiated on decaying softwood from a boreal forest has uncovered that fungal wood decay can occur in nature under O2-depleted conditions. In vitro cultures of F. pinicola corro- borated these initial observations, demonstrating the ability of this brown-rot fungus to grow in anoxic conditions. Using proteomics, we Article https://doi.org/10.1038/s41467-025-62567-3 Nature Communications | (2025) 16:7352 4 www.nature.com/naturecommunications revealed that under anoxia, F. pinicola secretes a full set of glycoside hydrolases and carbohydrate esterases, enabling the degradation of softwood xylan and mannan. A significant decrease of both hemi- celluloses during the anoxic culture of wood was confirmed by solid- state NMR spectroscopy, which also demonstrated the fungus syn- thesized its own cell wall polysaccharides such as β-1,3-glucan and chitin. Thus, our findings provide a functional explanation for the retention of PCWDEs in the genomes of brown-rot fungi8,15,16. Although these fungi have lost most of their oxidative enzymes, such as lytic polysaccharide monooxygenases (LPMOs) and class II peroxidases, critical for crystalline cellulose and lignin degradation, they have preserved a strategically-relevant set of hydrolytic PCWDEs, pre- dominantly targeting hemicelluloses, including recalcitrant xylan. Our results enable us to propose a mechanism to explain how the fungus penetrates and colonizes regions of wood where O2 is limited or absent (Fig. 5). During the initial phase of decay, in the presence of O2, plant polysaccharide breakdown occurs through a combination of Fenton chemistry and a limited set of PCWDEs5,12–14. As decay pro- gresses, fungal growth continues into the substrate until a “critical”O2 concentration is reached, which slows down and eventually stops Fenton chemistry-mediated decay. Deeper within the wood, PCWDEs become the main contributors of plant polysaccharide breakdown, consistent with the second step of the staggered decay mechanism Fig. 3 | Solid-state NMR of 13C-enriched pine decayed by Fomitopsis pinicola under anoxia. A An overlay of the 76–91, 58–68 ppm region of the 30ms CP-PDSD 13C NMR spectra showing the xylan Xn4–Xn5 and mannan M4–M6 cross peaks. There is a significant decrease in the mannan M4–M6 and in both threefold (Xn3f) and twofold (Xn2f) xylan conformations in thedecayingpinewood.B LeftHandSide the 82–92, 58–70 ppm region of the 30msCP-PDSD 13CNMR spectrum, RightHand Side the 52–70, 98–110 ppm region. The C3–C4 and C1–C2 cross-peak areas for β −1,3-glucan and chitin respectively are highlightedwithdotted yellow circles. These signals are absent in the control pine wood and indicate the emergence of 13C-labeled fungal cell wall polysaccharides in the decaying wood sample. All spectra have been normalized to 89 ppm (C41). A full 30ms CP PDSD spectrum is shown in Supplementary Fig. 12. Article https://doi.org/10.1038/s41467-025-62567-3 Nature Communications | (2025) 16:7352 5 www.nature.com/naturecommunications described for brown-rot fungi10,11. In nature, this mechanism allows the fungus to continue its colonization even in the absence of O2. F. pinicola is among themost damaging wood-decaying species in old-growth forests of the Northern hemisphere. Infected dead trees are prone to windthrow and top-breakage, making them high- risk hazard trees34 and compromising timber quality35. Interestingly, empirical observations describe F. pinicola and other wood decay- ers as heart rot decayers36–38. Our findings of fungal growth and decay under anoxia may have implications for heart rot decay, which is not exclusively associated with brown-rot species, or the genus Fomitopsis. For instance, Heterobasidion spp., identified in the center of our deadwood samples, are also described as heart rot decayers39,40. Furthermore, other species like the white-rot fungi Phlebia radiata and Phanerochaete sordida, have been reported to grow on wood under O2-limited conditions21 and resist to hypoxic conditions22. Growth and wood degradation under O2-restricted conditions, including anoxia, may be more widespread among wood-decaying fungi than previously recognized. This raises intri- guing questions about the mechanisms of wood decay in white-rot fungi under anoxic conditions, particularly given their extensive repertoire of oxidative enzymes involved in lignocellulose degra- dation. We believe that a deeper understanding of the biochemical processes of wood decay, particularly the role of O₂, could improve the classification of rot types. In conclusion, our findings advance the understanding of natural lignocellulose degradation mechanisms, highlighting the critical role of O2 in fungal wood decay. By demonstrating saprotrophic wood decay in an anoxic environment, we reveal a previously unexplored dimension of fungal adaptability. The extent of anaerobic wood depolymerisation by basidiomycetes must be further investigated for the understanding and quantification of carbon dynamics in forest ecosystems, especially in the boreal forest dominated by conifers. This discovery also opens avenues for developing innovative dec- arbonization strategies through bio-inspired anaerobic processes leveraging the unique capabilities of fungal wood decayers. Methods Wood sampling In May 2022, we sampled wood from Picea abies (L.) Karst (P. abies) stumps in the experimental forest of Stensholt Vang in Denmark (709370, 620263 UTM), one site (site ID 1011) in a larger national tree planting experiment41. At this site, 5-year-old seedlings of native pro- venance Rye Nørskov F. 300 were planted in 1965 on ploughed crop- land. Trees were thinned every 4-6 years leaving behind wood stumps a classification / function oxalate oxidase phospholipase D ester bond modification dimethylaniline monooxygenase guanine deaminase NAD(+) or NADP(+) as acceptor sulfate adenylyltransferase short-chain DHase/reductase aryl-alcohol DHase (NADP+) unspecific monooxygenase benzaldehyde DHase (NAD+) WD40 repeat estradiol 17 beta-Dhase carboxylic ester hydrolase carboxylesterase GH37 unspecific monooxygenase unknown function unknown function L-lactate DHase (cytochrome) oxidoreductase arginase aspartate aminotransferase L-arabinose isomerase phosphotransferase 20 453525155 403010 fold change classification / function GH92 GH115 GH2 CE15 carboxylesterase, type B GH3 GH55 GH92 GH3 CE16 GH10 DUF1793 GH31 GH3 GH51 L-lactate DHase (cytochrome) unknown function carboxylesterase GH43 GH43 GH43-CBM35 GH95 CH27 GH5_5 GH10 0 2. 15 × 10 -3 1. 05 × 10 -3 % N AS F – no rm ox ia 0 1.05 × 10 -2 5.00 × 10 -3 % N ASF – anoxia % NSAF Top 25 normoxia Top 25 anoxia GH43* GH115* CE15* GH10* GH51 3/7 1/1 1/1 2/3 1/3 β 4 4-O-Me β 4β 4 β 4 ββ 4 4 α 2 GH10 GH43/51 GH115lignin CE15 Glucuronoarabinoxylan 0 0 0 1 4 59 57 39 52 72 # enzymes# SC normoxia anoxia # ma 2/3 1/2 9/11 GH5_5 GH1 GH3 β 4 β 4β 4 β 4β 4 GH1/3 GH5_5 Cellulose 18 2 99 208 22 381 GH27* GH5_7* GH1 CE16 GH3 3/4 1/2 1/2 2/7 9/11 β 4 β 4β 4 β 4β 4 β 4 2/3 6 α Ac CE16 GH1/3 GH27 GH5_7 0 0 2 9 99 46 11 22 57 381 Galactoglucomannan fold change 10 20 GH35 GH28 CE8 GH2 GH78 2/2 3/12 2/2 3/4 1/4 4 α 4 α 2α 4 α 2α 4 α 4 4 β Me α 4 β 4 β 4 β β 6 6 β β 4 α 3 α 2 β 3 GH2/35 GH95 GH28 GH78 CE8 15 5 5 89 17 127 21 12 169 27 Pectin / / / / / 4 1 b Glc GalMan GlcA GalA Ara XylFuc Rha 20 453525155 403010 fold change 0 2. 15 × 10 -3 1. 05 × 10 -3 % N AS F – no rm ox ia 0 1.05 × 10 -2 5.00 × 10 -3 % N ASF – anoxia % NSAF fold change 10 20 # enzymes# SC normoxia anoxia , Fig. 4 | Proteomic profile of Fomitopsis pinicola in normoxia and anoxia. a Differentially produced fungal proteins in normoxia (left, in blue) and anoxia (right, in black) ranked by fold change and their relative abundance (%NSAF) in the respective conditions. bDifferentially secreted CAZyme families under anoxia with their respective target bonds in holocellulose and pectin. “#SC” indicates the total spectral counts for the CAZyme member(s) within a CAZy family. On the right, “#enzymes” indicates the CAZyme(s)member(s) identified/gene(s) encoded by the genome. * indicates that the CAZyme was exclusively found under anoxia. NSAF: normalized spectral abundance factor, GH: glycoside hydrolase, DHase: dehy- drogenase, DUF: domain of unknown function. The fold change calculation is defined in the method section. Article https://doi.org/10.1038/s41467-025-62567-3 Nature Communications | (2025) 16:7352 6 www.nature.com/naturecommunications of different, known ages. Wood stumps remaining from thinning events in 2007, 2012 and 2019 were selected for our purpose to represent a gradient of wood degradation. The selected sample trees were located in the same area, just a fewmetres apart.With a chainsaw, we removed the top of the stump that was exposed to air (approx. 10 cm). From there, we cut off approx. 20 × 20 × 20 cm irregular- shapedpieces fromeachof the threewood stumps. In addition, a piece of the trunk from the 2019-felled tree with visible carpophores of Fomitopsis sp. was collected (Supplementary Fig. 1a). Pieces of trunk and stumps were wrapped and transported in individual bags. Strain isolation and authentication Basidiomes of F. pinicola were collected from the fallen trunk of decayed spruce tree (cut in 2019), at Stensholt Vang forest (Denmark). The isolation process involved transferring tissues from the basi- diomes to agar plates containing malt extract supplemented with 0.025% chloramphenicol and 0.04% gentamicin. Successive sub- cultures without antibiotics were performed to verify the absence of contaminants. To confirm the identity of the isolated strains, the rDNA barcoding region ITS1-5,8S-ITS2 was PCR-amplified and sequenced42. Followingmolecular authentication (Genbank sequence IDPP277039), the strain corresponding to the species F. pinicola (Swartz: Fr.) Karst. was deposited in the Biological Resource Center CIRM-CF (Interna- tional Center of Microbial Resources, Marseille, France; https://doi. org/10.15454/KJQW-SJ57) under the accession number CIRM- BRFM 3531. Dioxygen (O2) profiles in wood O2 concentrations in the wood from Stenholt Vang were measured from outside going into the wood. Wood O2 profiles were determined from the exterior part (sapwood under the bark) into the inner sap- wood with a minimum distance of 50mm to the air-exposed cutting sections of the stump. Therefore, a needle sensor (OX-NP, Unisense, Århus, Denmark) mounted on a motorised stage (MMS, Unisense, Århus, Denmark, Supplementary Fig. 1b), which moved n steps of 1.0mm towards the wood centre until a depth of 4-6 cm. The optical sensors were mounted inside a surgical needle for strength. The measured O2 concentrations were calibrated with a two-point proce- dure: at an atmospheric O2 level through water bubbled with an aquarium pump, and at 0% O2 in a sodium ascorbate solution (pH 9.9, zero oxygen calibration kit, Unisense, Århus, Denmark) and corrected for temperature in the programme SensorTrace Suite (version 3.4.100.15377, Unisense, Århus, Denmark). Microscopy Specimens of approx. 2 × 3 × 5mm were prepared from 3-year-old Norway spruce (P. abies) wood collected in Stensholt Vang forest and from pine (Pinus halepensis) used as substrate in the fungal solid-state cultures. The material was carefully recovered from the wood and immediatelyfixed in 2%glutaraldehyde in0.05MNaPO4buffer, pH 7.5, and stored at 4 °C. Samples were washed in the buffer, dehydrated in an ascending ethanol series, critical point dried in an EMS850CP-drier, mountedontometal stubswith double-sided tape, sputter-coatedwith gold in an EMACE200 automated sputter coater and viewed inQuanta 200 SEM (FEI CompanyTM) at 10 kV. Protein extraction from wood samples All protein extractions were carried out in parallel with three inde- pendent replicates per sample. The wood samples were sliced into smaller pieces (mm size) using a wood driller and thenmilled into fine powder, using a cryo-grinder Freezer/Mill 6770 (SPEX SamplePrep, Metuchen, USA) in liquid nitrogen with 15 Hz in 3 cycles of 30 s and an interval cooling time of 1min. The freeze ground wood was stored at −20 °C. Proteins were extracted using a modified TCA/Acetone method, adapted fromNui et al.43. Briefly, 200mgofwoodpowderwas suspended with 1mL of sodium dodecyl sulphate (SDS)-PE buffer (1% SDS (w/v), 0.1M Tris-HCl at pH 8.0, 2mM dithiothreitol (DTT), 2mM phenylmethylsulfonylfluorid (PMSF)) and incubated at 600 rpm at sa pw oo d Fenton chemistry-mediated oxidative biomass decay20.9 O2 concentration (%) Secreted oxidative enzymes Extensive PCWDE set for hydrolytic biomass decay Reactive Oxygen Species (ROS) / Fenton chemistry O2 H2O2 HO oxalic acid e.g. Oxalate Oxidase decay he ar tw oo d 43 GHs / 5 CEs 0.0 fungal migration toward an O2-restricted centre limited PCWDE set No ROS No Fenton chemistry ≈ 0.0% O2 no accessibility of stochiometric oxygen (species) Fig. 5 | Schematicmodel illustrating the penetrationofFomitopsis pinicola into the wood towards anoxic conditions. The data presented in this study suggest a shift from Fenton-mediated wood decay under normoxia towards exclusive PCWDE-driven hydrolytic decomposition in anoxia. In a staggered mechanism, the first stage of decay, in the presence of O2, is characterized by non-specific Fenton chemistry and a small set of PCWDEs. At the later stage of decay, deeper in wood, and hence under O2-restricted conditions, secreted glycoside hydrolases and car- bohydrate esterases depolymerize the holocellulose and pectin fraction in the immediate vicinity of the fungal hyphae, which enables the fungus to penetrate the substrate further. F. pinicola is represented by grey filaments, oxidative enzymes by light blue triangles, and hydrolytic CAZymes by black circles. The picture was drawn with Inkscape. Article https://doi.org/10.1038/s41467-025-62567-3 Nature Communications | (2025) 16:7352 7 https://doi.org/10.15454/KJQW-SJ57 https://doi.org/10.15454/KJQW-SJ57 www.nature.com/naturecommunications room temperature for 1 h. The insoluble part was discarded after centrifugation at 15,000 × g for 5min at 4 °C and the supernatant was transferred into Eppendorf tubes (2mL). Twenty percent (v/v) cold TCA/acetonewas added at a 1-to-1 (v/v) ratio to a final concentration of 10% TCA and 40% acetone mixed with the supernatant, and incubated for 5min on ice for precipitation. The protein pellet was centrifuged at 15,000× g for 3min at 4 °C, washed three times with 80% ice-cold acetone followed by centrifugation at 15,000 × g for 3min at 4 °C. The protein precipitatewas air-dried for amaximumof 3min, resuspended in 25 µL of loading SDS buffer (Laemmli buffer, 10% (w/v) SDS, 40% (w/v) Glycerol, 1% (w/v) DTT, 0.1M Tris-HCl pH 6.8), heated for 10min at 95 °C, and stored at 4 °C. Metaproteomics Extracted proteins (pooled triplicates from the samples collected in nature) were incubated at 99 °C for 5min before 25 μL was loaded onto a NuPAGE 4–12% Bis-Tris gel (Thermo Fisher Scientific, Mas- sachusetts, USA), and subjected to 5min SDS-PAGE migration. Pro- teins were stained for 5min with Coomassie SimplyBlue SafeStain (Thermo Fisher Scientific) prior to in-gel trypsin proteolysis with Trypsin Gold (Promega, Wisconsin, USA) using 0.011% ProteaseMAX surfactant (Promega, Wisconsin, USA), as described in Hartmann et al.44. Peptides were quantified using the Pierce Quantitative Fluorometric Peptide Assay (Thermo Fisher Scientific), and 350 ng were injected on an Exploris 480mass spectrometer (Thermo Fisher Scientific) connectedwith a Vanquish Neo LC system (Thermo Fisher Scientific) operating in data-dependent mode. The peptides were desalted on an Acclaim PepMap100 C18 precolumn (5 μm, 100 Å, 300 μm id × 5mm), and resolved on a nanoscale EasySpray PepMap Neo C18 column (2 μm, 100 Å, 75 μm id × 50 cm) with a 95min gra- dient at a flow rate of 0.25 μLmin−1. The gradient was applied from 5 to 25% of solvent B (100% CH3CN, 0.1% formic acid) over 90min, and then from 25 to 40% over 5min, with solvent A being 0.1% formic acid. Peptides were analysed initiated by a full scan of peptide ions in the ultra-high-field Orbitrap analyzer, followed by high-energy col- lisional dissociation and MS/MS scans on the 20 most abundant precursor ions. Full-scan mass spectra were acquired from m/z 350 to 1500 at a resolution of 120,000with internal calibration activated on the m/z 445.12002 signal. During ion selection for MS/MS frag- mentation and measurement, a 10 s dynamic-exclusion window was appliedwith an intensity threshold of 5 × 104. Only ions with positive charges 2+ and 3+ were considered. Precursor ions were isolated using a 2.0m/z isolation window and activated with 30% normalized collision energy. The Mascot Daemon 2.6.1 search engine (Matrix Science) was employed to match MS/MS spectra to peptides (Peptide-spectrum matches - PSM) and identify taxonomies (Taxon-Spectrum Matches —TSM) in amulti-round search process. An initial Mascot search was performed on a reduced NCBInr‐based database (National Center for Biotechnology Information)45. Genera validated in the first‐ round search, along with all their descendants, were extracted from the complete NCBInr database (downloaded in January 2021), sup- plemented with genome sequences of Agaromycetes from the MycoCosm portal (downloaded in March 2023)7, forming the database for the second Mascot search. Genera validated following this search were used to construct a refined sample-specific data- base for the final MS/MS spectrum searches. Protein accession numbers were mapped to taxids46. PSMs validated with a Mascot p- value of 0.05 were filtered using a false discovery rate (FDR) <1% and subsequently used to infer peptide and protein identifications. Proteins were grouped if they shared at least one peptide. Label-free quantification was performed based on PSM counts for each pro- tein, applying the principle of parsimony. The count values from taxonomic data (number of TSMs) were scaled relative to their total in the sample. Protein annotations The proteins identified though proteomics were annotated as follows: functional annotations of Clusters of Orthologous Groups of proteins (COG), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and Enzyme Commission number (EC) were performed using the eggNOG mapper (eggNOG Database v5.0.2, minimum query and sub- ject coverage 80%,minimum identity 50%)47. Functional domains were detected using InterProScan (Database v5.59-91.0 galaxy3)48. Carbohydrate-active enzymes (CAZymes) were identified using the CAZy database (www.cazy.org, last access June 2023) and subsequent manual curation6. Proteases were identified based on the MEROPS database49 (v.12.4) and Lipases based on the Lipase Engineering Data- base (v.4.1). Secretomes were predicted using SignalP v650 and dee- ploc v.251. Non-intrusive O2 concentration measurements The O2 concentration was measured during the cultivation non- invasively using flexible, self-adhesive dioxygen sensing patches (FOSPOR RedEye, Ocean Insight, US patent 7,862,770 B2) attached to the inside of i) one-side open glass cylinder at 25mm, 75mm, and 125mm from the opening, or ii) Roux flasks. The O2 sensing patch applied the fluorescence quenching of tris-(4,7-diphenyl-1,10-phenan- throline) ruthenium(II) chloride embedded in a sol-gel. An optical probe sends excitation light (blue LED) to the complex resulting in a quenching of the fluorescence signal in the presence of O2. This signal correlates to O2 partial pressure in the gel matrix as a dynamic equi- librium with O2 in the narrow environment of the patch. The optical signal was detected through a bifurcated optical fibre (RE-BIFBORO-2, Ocean Insight) and a benchtop NeoFox phase fluorometer (NeoFox- GT, Ocean Insight), and the phase shift between the excitation and the emission (excited state lifetime) was determined and transformed into the partial O2 pressure at the patch through the Stern-Volmer equation after calibrating the system in a two-point calibration with air and with N2 according to the manufacturer’s manual. Fungal solid-state cultures on pine The fungi were transferred fromMA2 agar plates (20 g L−1 malt extract, 20 g L−1 agar) to a liquid medium (10 g L−1 glucose, 2 g L−1 Bacto Pep- tone, 1 g L−1 yeast extract) and cultivated statically for 14 days at 30 °C passively supplied by air. The mycelium was separated from the liquid medium and resuspended in H2O at 8000 rpm for 1min (Ultra-Turrax T25, Janke & Kunkel IKA®-Labortechnik). Dried Pinus halepensis (<1.5mm particle size, untreated mix of heartwood and sapwood without the bark) was rehydrated (1 to 1.778, w(dry pine) w(water) −1) and autoclaved at 110 °C for 30min, or sterilised by γ-irradiation (10MeV, 25 kGy) and rehydrated. The resuspendedmyceliumwas inoculated in a ratio of 2.222mg(fungal dry weight) g(autoclaved pine) −1. In initial experi- ments, 25mgg(autoclaved pine) −1 glucose and 2.5mgg(autoclaved pine) −1 ammonium tartrate were added and mixed carefully to homogenize the mycelium in the substrate. After the method was established, cultures were cultivated without glucose or ammonium tartrate, and similar growth and morphology were observed, which proved the growth of the mycelium purely on wood in the absence of O2. Solid-state cultures in an O2 gradient A sterile one-side open glass cylinder (150mmheight, 140mL volume) with O2 sensing patches was filled at a height of 120mm with the 96 g fungal-inoculated pine and closed with a gas-permeable membrane. In a similar setup, the column was filled with sterile pine and the fungus was inoculated from the top. Both types of cultureswere kept statically at 30 °C for at least 14 days. The dioxygen concentration was deter- mined non-invasively in biological duplicates, which were cultivated from two independent inoculates. After 14 days the pine-mycelium conglomerate was recovered from the cylinder, divided into three parts, and stored at −20 °C for protein extraction. Article https://doi.org/10.1038/s41467-025-62567-3 Nature Communications | (2025) 16:7352 8 http://www.cazy.org www.nature.com/naturecommunications Solid-state cultures in controlled O2 concentration Roux flasks (1.1 L) were filled with 30–45 g of the pine-mycelium mix- ture to form a thin layer (<5mm) to minimise the gas gradient during the solid-state cultures, which were cultivated statically for 14 days at 30 °C with an active supply of air or N2 (Alphagaz 1 Azote, O2 < 2 ppm, Air Liquide, Paris, France). In one experimental setup, each condition – anoxia and normoxia – was tested as a biological duplicate. Three experimental set-ups were executed in this study. The gas flow was regulated to 9mLmin−1 by digital thermal mass flow controllers (EL- FLOW Select, F-200CV/F-210CV, Bronkhorst, Montigny-Les-Cor- meilles, France), passed a sterile filter, and was humidified through a water bottle (300mL sterile H2O in 500mL vessel) to maintain the water content of the solid-state cultures. The O2 partial pressure was measured non-intrusively via dioxygen sensing patches at the inside of the Roux flasks during the cultivation. The experimental setup is dis- played in Supplementary Fig. 5a. At the end of the solid-state cultures (14 days), the fungus-pine mixtures were harvested from the Roux flasks and stored at −20 °C until cryo-grinding, or used for in vitro assessments of the fungus and sample characteristics (biochemical assays). Mass loss and water content Mass loss and water content were determined from two biological replicates, that is twoRoux flasks cultivated in normoxia and two Roux flasks cultivated in anoxia. Mass loss was calculated from the weight at the beginning minus the weight at the end of the cultivation. The weight was determined (Sartorius Entris 4202-1S) as the entire weight of the Roux flask and the solid-state cultures therein. The water con- tent [%]wasdetermined at the beginning and the endof the cultivation by measuring wet weight and dry weight using the formula: 1 - (dry weight / wet weight) × 100. The water contents were applied to cal- culate the dry mass loss from the wet masses of the cultures with the following formula: dry weight mass loss (pine and fungi) = wet mass loss (at the endof the cultivation) × (1−water content [%]/100). Thedry mass loss of the wood (= converted substrate) was calculated taking into account the mass gain of the fungal mycelium calculated from qPCR (see below) The mass loss in the manuscript refers to the dry mass loss of the cultures. Determination of fungal growth by quantitative PCR (qPCR) Fungal growth was determined in four biological replicates for each culture condition. From each culture, triplicates were randomly taken. Thereof, fungal genomic DNA was extracted three times from 200mg cryo-grinded material (mycelium, or mycelium-pine mix- ture) by the commercial DNA extraction kit NucleoSpin Plant II Kit (Macherey-Nagel, Düren, Germany) according to themanufacturer’s instructions, but with an extended extraction step of 60min and an elution of the gDNA in two steps with a total volume of 50 µL Milli-Q water at 65 °C. The concentration and the purity were analysed via NanoDrop ND-2000 spectrophotometer (Thermo Fisher Scientific) and confirmed by Qubit™ dsDNA Quantification Assay Kit (Thermo Fisher Scientific) as fluorescence endpoint measurement (excita- tion: 485 nm, emission: 525 nm) in a Greiner 96 Black Flat Bottom Fluotrac well plate. The qPCR was performed in a final reaction volume of 10 µL including 2 µL sample using the qPCRMasterMix for SYBR Plus (Bio-Rad, California, USA) and 5.8S conserved primer sequences (300 nM in reaction, 5′-TTT CAG CAA CGG ATC TCT TGG C-3′, and 5′-CAA ACA GGC ATG CTC CTC GG-3′) in a modified PCR protocol50: 2min at 95 °C, 39 cycles of: 15 s at 95 °C and 10 s at 58 °C, and amelting step: 30 s at 65 °C and gradually increase (0.5 °C steps) to 95 °C in a C1000 Touch Thermal Cycler CFX96 real-time system (Bio-Rad), or the AriaMx system (Agilent, California, USA), and quantification cycles (Cq) were determined in regression mode of the Bio-Rad CFXManager™ software (v 3.0), or Agilent Aria Software v2.0, respectively. For each condition, 36 qPCRs were performed, and thereof 34 or 33 were considered for normoxia, or anoxia, respectively. The deter- mined gDNA amount correlates linearly with the mycelial fresh weight of the fungus52. The dry weight at the beginning and the end of the cultivation was calculated from the fresh weights taking the water content of the culture into account, and mycelium growth was calcu- lated based on the dry weights. Anaerobic jar cultures Standard petri dishes (15mm× 100mm)were filled with 25mL of 2.0% (w/v) agar. When hardening was completed, 2.5 g of rehydrated (1 to 1.778, w(dry pine) w(water) −1), autoclaved (110 °C for 30min) pine chips (<1.5mm particle size) were distributed on the agar surface and cov- ered by 20mL 2.0% (w/v) agar. F. pinicola was transferred from MA2 agar plates (20 g L−1 malt extract, 20 g L−1 agar) to the centre of the plate. The plates were cultivated in an anaerobic jar (Anaerocult™, 2.5 L, Merck, Darmstadt, Germany) with a chemically introduced (Anaerocult™ A, Merck) and controlled (Bandelettes Anaerotest™, Merck) O2-depleted environment, or in normoxia, at 30 °C for 22 days. Bioreactor F. pinicola was cultivated from 1.36 g(dry weight) resuspended mycelium (see fungal solid-state cultures on pine) in a stirred tank reactor (3.0 L, 120 rpm) in 1.5 L liquidmedium of 15 g L−1 autoclaved pine chips, 3 g L−1 glucose, and 1.8 g L−1 diammonium tartrate at 30 °C for 11 days. Air (normoxic phase) supplied the culture at a flow rate of 0.75 Lmin−1 (0.5 VVM) for the first 66 h, followed by the removal of O2 by N2 for 6.5 h (identical flow rate). When anoxia was reached, the N2 flow rate was reduced to0.15 Lmin−1 (0.1 VVM)until the endof the fermentation. In an identical setup, another bioreactor (identical model) was sup- plied with air at the same flow rates to cultivate the fungus without O2 restriction. Dissolved oxygen (DO), pH, temperature, and stirring rate were controlled and recorded online during the cultivation. Proteomics Extracted proteins from 14-day solid-state cultures in Roux flasks (biological replicates) were dissolved in Laemmli buffer, subjected to SDS-PAGE, and in-gel trypsin proteolyzed with Trypsin Gold (Pro- mega). The resulting peptides (100 ng) were injected in an Exploris 480 mass spectrometer (Thermo Fisher Scientific) connected with a Vanquish Neo LC system (Thermo Fisher Scientific) and operated in data-dependent mode53. MS/MS spectra were assigned with Mascot Daemon 2.6.1 taking into consideration Carbamidomethyl (C) as fixed modification, Deamidated (NQ) andOxydation (M) as variable options. Peptides with p value below 0.05 were selected. Proteins were vali- dated with at least 2 peptides at FDR 1%. The fold change (see Fig. 4 of themainmanuscript) was calculated the following (1): f old change= X SCconditionA + 2= X SCconditionB +2 with SCcondition A,B: spectral counts of a protein from the cultures in normoxia or anoxia. Quantification of hydrogen peroxide H2O2wasextracted from14-day solid-state cultures inRouxflasks from biological duplicates of each condition – anoxia and normoxia – with cold water (1-to-1 ratio) shaking at 450 rpm for 30min at 4 °C. The supernatant was filtered (0.22 µm) and directly applied (1-to-10 ratio, 10 µL) in a 96-well-plate assay (Invitrogen™ A22188) with 100 µL total volume in 50mM, pH 7.0 sodium phosphate buffer with 200 µM Amplex Red (10-acetyl-3,7-dihydroxyphenoxazine in DMSO), and 0.1 mU mL−1 Horseradish Peroxidase (HRP) at 23 °C. Resorufin fluor- escence (excitation: 563 nm, emission: 587 nm), and absorbance at 575 nm, was monitored over 15min. H2O2 concentration was Article https://doi.org/10.1038/s41467-025-62567-3 Nature Communications | (2025) 16:7352 9 www.nature.com/naturecommunications determined at the beginning of the assay based on a H2O2 standard curve (0–8.34 µM, H2O2 concentration determined at 240nm) at the same conditions. Experiments (assay) and controls (no HRP, or 0.834 µM H2O2 added) were performed in triplicates. pH measurements and glycoside hydrolase activity assay Secreted proteins were extracted from 2.5 g mycelium-pine mix from 14-days solid-state cultures in Roux flasks frombiological duplicates of each condition in 10mLwater shaking at 200 rpm for 6 h at 20 °C. The supernatant was filtered (0.45 µm) and pH was measured with a pH meter (Fisherbrand Accumet AE150, Thermo Fisher Scientific) before storing the sample at −20 °C without cryoprotectants addition. The glycoside activity was determined with cyclophellitol-derived activity- based probes54 added in a 1-to-6 ratio directly in the secretomes, or in NH4OAc-buffered (1M, 0.1 volume, pH 5.5) supernatants. Samples were incubated at 30 °C for 1 h, mixed with SDS-PAGE loading dye, heated to 96 °C for 5min, and loaded on a 10% SDS-PAGE gel (Bio-Rad, California, USA). Cy3 and Cy5 filter/laser sets were applied to image enzyme-bound endo-β-glucanase probe (CB664), or endo-β-xylanase probe (SY-F230) directly in the SDS-PAGE gel, respectively. Monosaccharide detection and quantification Soluble compounds (released soluble residual monomers of the pine substrate) were extracted from 0.45 g mycelium-wood mix from 14- day solid-state cultures in Roux flasks in 45mL H2O for 6 h at 80 °C. Solid particles were removed from the supernatant through a 0.22 µm filter, and the liquid phase was analysed by high-performance anion- exchange chromatography (HPAEC) with a CarboPac-PA1 guard col- umn (2 × 50mm) and a CarboPac-PA1 column (2 × 250mm), and coupled to a pulsed amperometric detector (PAD) (Dionex ICS6000 system, Thermo Fisher Scientific) at 30 °C. 100mM NaOH (eluent A) and H2O (eluent C) were used as the solvents at with 25 µL sample volume. Monosaccharides were detected and quantified at 0.25mLmin−1 flow rate starting from 10% eluent A with the following gradient: 0–20min, 10%A; 20–44min, 10–100%A; 44–49min, 100%A; 49–59min, 10%A.D-galacturonic acidwasdetected andquantified at a flow rate of 0.25mLmin−1 and 25 µL of the sample was injected. 100mMNaOH (eluent A) and NaOAc (1M) in 100mMNaOH (eluent B) were used as solvents. The initial conditions were set to 100% eluent A, and the following gradientwas applied: 0–10min, 0–10%B; 10–35min, 10–30% B; 35–40min, 30–100% B; 40–41min, 100–0% B; 41–50min, 100% A. Chromeleon 7.2.10 chromatography data software was used for the integration of the chromatograms. D-glucose was confirmed and quantified by using the glucose oxidase-peroxidase (GOD-POD) method (Glucose Assay Kit, Libios, Vindry-sur-Turdine, France) according to the supplier’s protocol in a 200 µL assay with 10 µL sample at 30 °C. Liquid chromatography mass spectrometry (LC-MS) analysis The samples of extracted and filtered soluble compounds (described in the previous section) were mixed with cold ethanol (1-to-9 v/v) and centrifuged at 13,000 × g for 15min at 4 °C to remove the remaining polysaccharides, and concentrated (Savant SpeedVac SPD1030 Inte- grated Vacuum Concentrator System, Thermo Fisher Scientific) under reduced pressure at 45 °C for 4 h before Liquid ChromatographyMass Spectrometry (LC-MS) analysis. Samples were filtered (0.2 µm, Chromafil®, Macherey-Nagel). D-galacturonic acid and oxalic acid were confirmed by Ultra High Performance Liquid Chromatography (UHPLC, UltiMate™ 3000 Rapid Separation (RS) HPLC Systems, ThermoFisher Scientific) coupled to a charged aerosol detector (CAD), and an ISQ-EM mass spectrometer (Thermo Fisher Scientific). Separation was performed on a Kinetex F5 column (Phenomenex, 1.7 µm, 150×2.1mm)at aflow rate of0.32mLmin−1 at 25 °C. Themobile phases used were solvent A: Ammonium formate 12mM at pH 2.1, and solvent B: Acetonitrile 100%. The gradientwas programmed as follows: solvent A started at 100% for 5min, then solvent B increased to 80% in 2min, until the end of running (10min). Negative-ion ESI–MS spectra (15–800m/z) were acquired by setting the vaporizer temperature at 145 °C, ion transfer tube temperature at 300 °C, sheath gas pressure at 33 psig, auxiliary gas pressure at 3.4 psig, and sweep gas pressure at 0.5 psig. UHPLC-CAD-ESI-MS data were acquired and analysed with Chromeleon v7.2.10 (Thermo Fisher Scientific), and the quantification was performed by external standard calibrations. The calibration and controls (samples spiked with oxalic acid) were performed with pure oxalic acid (Sigma Aldrich). Preparation of alcohol Insoluble residue and hemicellulose extraction Samples were submerged in 96% (v/v) ethanol and boiled at 70 °C for 30min before homogenization using a ball mixer mill (Glen Creston, now Retsch). The pellet was collected by centrifugation (4000 × g for 15min) and was washed with 100% (v/v) ethanol, twice with chlor- oform:methanol (2:1), followed by successive washes with 65% (v/v), 80% (v/v) and 100% (v/v) ethanol. The remaining pellet of AIR was air dried and hemicelluloses were extracted with 4M NaOH55. Enzymatic hydrolysis and polysaccharide analysis by carbohy- drate gel electrophoresis (PACE) Enzymes used in this study were GH11 endo-β-1,4-xylanase from Neo- callimastix patriciarum56 NpGH11; endo-glucuronoxylanase EcGH30 from Erwinia chrysanthemi57; endo-mannanaseAnGH5 fromAspergillus nidulans58; xyloglucanaseAaGH12 fromAspergillus aculeatus59.NpGH11 and EcGH30 hydrolyses were carried out at 30 °C, while AnGH5 and AaGH12 were carried out at 37 °C. All hydrolyses were carried out under constant shaking for 24 h. Five hundred micrograms of extrac- ted hemicellulose were used for hydrolysis in 50mM ammonium acetate buffer pH 6.0. Following hydrolysis, enzymes were heat- deactivated for 10min and were then taken to dryness under vacuo. Derivatisation of oligosaccharides was performed as described in ref. 55. For carbohydrate electrophoresis, samples were loaded on polyacrylamide gels andelectrophoresed at 10 °C at 1000V for 1 hwith 0.1M TRIS-borate (pH 8.2) solution used as the running buffer. PACE gel scanning was performed using a GBox CCD camera with a tran- silluminator with long-wave tubes emitting at 365 nm. Images were captured using GeneSnap software. Solid-state NMR Pine (Douglas pine, Pseudotsuga menziesii) was labeled with 13C by the labeling facility of IsoLife (Wageningen, The Netherlands), sliced in wood chips of approx. 2 to 5mm and sterilized by γ-irradiation (10MeV, 25 kGy). After rehydration of the 13C-enriched pine, fungal mycelium was inoculated (1:30) without adding any additional source of nutrition. The solid-state culture remained for 28days at 25 °Cunder anoxic conditions (pureN2) as described above. After freezing in liquid nitrogen, the culture was stored at -80 °C until use. Solid-state NMR experiments of 13C-enriched pine and of the F. pinicola inoculatedpinewereacquiredon aBruker 1 GHzAVANCENEO solid-state NMR spectrometer operating at 1H and 13C Larmor fre- quencies of 1000.4 and 251.6MHz, respectively, using a 3.2mm EFree triple resonance MAS probe. All experiments were conducted at an indicated temperature of 10 °C and an MAS frequency of 14.25 kHz with a recycle delay of 2 s. The 13C chemical shifts were determined using the carbonyl peak at 177.8 ppm of L-alanine as an external reference with respect to tetramethylsilane. The 1H 90° pulse length was 3.25 µs and the 13C 90° was 3.9 µs for pine and 4.3 µs for the pine inoculated by F. pinicola. Cross polarization from 1H to 13C was achieved using ramped (70–100%) 1H radiofrequency amplitude and a contact time of 1ms60. SPINAL-64 decoupling was applied at a 1H nutation frequency of 70–80 kHz during acquisition60. Sign dis- crimination in the indirect dimension of the 2D experiments was Article https://doi.org/10.1038/s41467-025-62567-3 Nature Communications | (2025) 16:7352 10 www.nature.com/naturecommunications achieved using the States-TPPImethod. Assignments were determined using 2D 13C-13C proton-driven spin diffusion (PDSD) experiment with a mixing time of 30ms61. The acquisition time in the indirect dimension (t1) of the CP PDSD experiments was 6.4ms. The spectral width in the indirect dimension was 42.75 kHz with 64 acquisitions per t1 FID. The 2D spectra were processed with Fourier transformation into 8 K (F2) × 2 K (F1) points with exponential line broadening of 20-50Hz in F2 and cubed sine bell processing in F1 using Bruker Topspin v.3.6. Contour levels are x 1.1 unless otherwise stated. The minimum contour is cho- sen to show the desired features. Reporting summary Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article. Data availability The data generated in this study are provided in the Supplementary Information, Supplementary Dataset and Source Data file. Unpro- cessed NMR data files are available from https://wrap.warwick.ac.uk/ id/eprint/191899/. Metaproteomics and proteomics data are available on PRIDE under PXD048319 and PXD048362 accessions, respectively. The accession code for the F. pinicola rDNA sequence is Genbank ID PP277039. Source data are provided with this paper. References 1. Bonan, G. B. Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320, 1444–1449 (2008). 2. Harris, N. L. et al. Global maps of twenty-first century forest carbon fluxes. Nat. Clim. Chang. 11, 234–240 (2021). 3. Baldrian, P., López-Mondéjar, R. & Kohout, P. Forest microbiome and global change. Nat. Rev. Microbiol. 21, 487–501 (2023). 4. Floudas, D. et al. The paleozoic origin of enzymatic lignin decom- position reconstructed from 31 fungal genomes. Science 336, 1715–1719 (2012). 5. Riley, R. et al. Extensive sampling of basidiomycete genomes demonstrates inadequacy of the white-rot/brown-rot paradigm for wood decay fungi. Proc. Natl Acad. Sci. USA 111, 9923–9928 (2014). 6. Drula, E. et al. The carbohydrate-active enzyme database: functions and literature. Nucleic Acids Res. 50, D571–D577 (2022). 7. Grigoriev, I. V. et al. MycoCosm portal: gearing up for 1000 fungal genomes. Nucleic Acids Res. 42, D699–D704 (2014). 8. Hasegawa, N., Sugiyama, M. & Igarashi, K. Random forest machine- learning algorithm classifies white- and brown-rot fungi according to the number of the genes encodingCarbohydrate-Active enZyme families. Appl. Environ. Microbiol. 90, e00482–24 (2024). 9. Hage, H. & Rosso, M.-N. Evolution of fungal carbohydrate-active enzyme portfolios and adaptation to plant cell-wall polymers. J. Fungi 7, 185 (2021). 10. Zhang, J. et al. Localizing gene regulation reveals a staggeredwood decay mechanism for the brown rot fungus Postia placenta. Proc. Natl. Acad. Sci. USA 113, 10968–10973 (2016). 11. Anderson, C. E. et al. Capturing an early gene induction event during wood decay by the brown rot fungus Rhodonia placenta. Appl. Environ. Microbiol. 88, e00188–22 (2022). 12. Eastwood, D. C. et al. The plant cell wall-decomposing machinery underlies the functional diversity of forest fungi. Science 333, 762–765 (2011). 13. Vanden Wymelenberg, A. et al. Comparative transcriptome and secretome analysis of wood decay Fungi Postia placenta and Pha- nerochaete chrysosporium.Appl. Environ.Microbiol. 76, 3599–3610 (2010). 14. Mattila, H. K., Österman-Udd, J., Mali, T. & Lundell, T. Basidiomycota Fungi and ROS: genomic perspective on key enzymes involved in generation andmitigation of reactive oxygen species. Front. Fungal Biol. 3, 837605 (2022). 15. Martinez, D. et al. Genome, transcriptome, and secretome analysis of wood decay fungus Postia placenta supports unique mechan- isms of lignocellulose conversion. Proc. Natl Acad. Sci. USA 106, 1954–1959 (2009). 16. Kohler, A. et al. Convergent losses of decay mechanisms and rapid turnover of symbiosis genes in mycorrhizal mutualists. Nat Genet 47, 410–415 (2015). 17. Fukasawa, Y. & Matsukura, K. Decay stages of wood and associated fungal communities characterise diversity–decomposition rela- tionships. Sci. Rep. 11, 8972 (2021). 18. Thacker, D. G. &Good,H.M. The composition of air in trunk of sugar maple in relation to decay. Can. J. Bot. 30, 475–485 (1952). 19. Jensen, K. F. Oxygen and carbon dioxide concentrations in sound and decaying red oak trees. Forest Sci 15, 246–251 (1960). 20. Scheffer, T. C. O2 requirements for growth and survival of wood- decaying and sapwood-staining fungi. Can. J. Bot. 64, 1957–1963 (1986). 21. Mattila, H. K., Mäkinen, M. & Lundell, T. Hypoxia is regulating enzymatic wood decomposition and intracellular carbohydrate metabolism infilamentouswhite rot fungus.Biotechnol. Biofuels 13, 26 (2020). 22. Mori, T., Masuda, A., Kawagishi, H. & Hirai, H. Ethanol fermentation by saprotrophic white-rot fungus Phanerochaete sordida YK-624 duringwooddecay as a system for short-term resistance tohypoxic conditions. J. Biosci. Bioeng. 133, 64–69 (2022). 23. Goubet, F., Dupree, P. & Johansen, K. S. Carbohydrate Gel Elec- trophoresis. (ed Popper, Z.) The Plant Cell Wall. Methods Mol. 715, 81–92, (Humana Press, 2011). 24. Presley,G.N., Zhang, J. &Schilling, J. S. Agenomics-informedstudy of oxalate and cellulase regulation by brown rot wood-degrading fungi. Fungal Genet. Biol. 112, 64–70 (2018). 25. Terrett, O. M. et al. Molecular architecture of softwood revealed by solid-state NMR. Nat. Commun. 10, 4978 (2019). 26. Busse-Wicher, M. et al. Evolution of xylan substitution patterns in gymnosperms and angiosperms: implications for xylan interaction with cellulose. Plant Physiol 171, 4418–2431 (2016). 27. Klukowski, P. & Schubert, M. Chemical shift-based identification of monosaccharide spin-systems with NMR spectroscopy to comple- ment untargeted glycomics. Bioinformatics 35, 293–300 (2019). 28. Simmons, T. et al. Folding of xylan onto cellulose fibrils in plant cell walls revealed by solid-state NMR. Nat. Commun. 7, 13902 (2016). 29. Bourdon, M. et al. Ectopic callose deposition into woody biomass modulates the nano-architecture of macrofibrils. Nat. Plants 9, 1530–1546 (2023). 30. Jang, M.-K. et al. Physicochemical characterization of α-chitin, β- chitin, and γ-chitin separated from natural resources. J. Polym. Sci. A Polym. Chem. 42, 3423–3432 (2004). 31. Urzúa, U., Kersten, P. J. & Vicuña, R. Manganese Peroxidase- Dependent Oxidation of Glyoxylic and Oxalic Acids Synthesized by Ceriporiopsis subvermispora Produces Extracellular Hydrogen Peroxide. Appl. Environ. Microbiol. 64, 68–73 (1998). 32. Berna, A. & Bernier, F. Regulation by biotic and abiotic stress of a wheat germin gene encoding oxalate oxidase, a H2O2-producing enzyme. Plant Mol. Biol. 39, 539–549 (1999). 33. Couturier, M. et al. Enhanced degradation of softwood versus hardwood by the white-rot fungus Pycnoporus coccineus. Bio- technol. Biofuels 8, 216 (2015). 34. Runnel, K. & Lõhmus, A. Deadwood-rich managed forests provide insights into the old-forest association of wood-inhabiting fungi. Fungal Ecol 27, 155–167 (2017). 35. Temnuhin, V. B. Preliminary quantitative estimation of wood decomposition by fungi in a Russian temperate pine forest. For. Ecol. Manag. 81, 249–257 (1996). 36. Wagener,W.W. & Davidson, R.W. Heart rots in living trees. Bot. Rev 20, 61–134 (1954). Article https://doi.org/10.1038/s41467-025-62567-3 Nature Communications | (2025) 16:7352 11 https://wrap.warwick.ac.uk/id/eprint/191899/ https://wrap.warwick.ac.uk/id/eprint/191899/ https://www.ebi.ac.uk/pride/ www.nature.com/naturecommunications 37. Hennon, P. E. Areheart rot fungimajor factors of disturbance ingap- dynamic forests? Northwest Sci 69, 284–293 (1995). 38. Glaeser, J. A. & Smith, K. T. Wood decay fungi of subalpine conifer forests. In Proc Presented at the 8th Western Hazard Tree Workshop https://www.fs.usda.gov/nrs/pubs/jrnl/2016/nrs_2016_glaeser_ 001.pdf (2016). 39. Yuan, Y., Chen, J.-J., Korhonen, K., Martin, F. & Dai, Y.-C. An updated global species diversity and phylogeny in the forest pathogenic genus Heterobasidion (Basidiomycota, Russulales). Front. Micro- biol. 11, 596393 (2021). 40. Garbelotto, M. & Gonthier, P. Biology, epidemiology, and control of heterobasidion species worldwide. Annu. Rev. Phytopathol. 51, 39–59 (2013). 41. Nord-Larsen, T. & Pretzsch, H. Biomass production dynamics for common forest tree species in Denmark – Evaluation of a common garden experiment after 50 yrs ofmeasurements. For. Ecol. Manag. 400, 645–654 (2017). 42. Navarro, D. et al. A. large-scale phenotyping of 1,000 fungal strains for the degradation of non-natural, industrial compounds. Com- mun. Biol. 4, 871 (2021). 43. Niu, L. et al. Modified TCA/acetone precipitation of plant proteins for proteomic analysis. PLoS ONE 13, e0202238 (2018). 44. Hartmann, E. M., Allain, F., Gaillard, J.-C., Pible, O. & Armengaud, J. Taking the shortcut for high-throughput shotgun proteomic analy- sis of bacteria. (eds. Vergunst, A. & O’Callaghan, D.) Host-Bacteria Interactions. Methods Mol. Vol. 1197, 275–285, (Humana Press, 2014). 45. Ramos-Nascimento, A. et al. Human gut microbiome and metabo- lite dynamics under simulated microgravity. Gut Microbes 15, 2259033 (2023). 46. Pible, O. et al. Estimating relative biomasses of organisms in microbiota using “phylopeptidomics. Microbiome 8, 30 (2020). 47. Huerta-Cepas, J. et al. Fast genome-wide functional annotation through orthology assignment by eggNOG-mapper.Mol. Biol. Evol. 34, 2115–2122 (2017). 48. Jones, P. et al. InterProScan 5: genome-scale protein function classification. Bioinformatics 30, 1236–1240 (2014). 49. Rawlings, N. D. et al. TheMEROPSdatabase of proteolytic enzymes, their substrates and inhibitors in 2017 and a comparison with pep- tidases in the PANTHER database. Nucleic Acids Res. 46, D624–D632 (2018). 50. Teufel, F. et al. SignalP 6.0 predicts all five types of signal peptides using protein language models. Nat. Biotechnol. 40, 1023–1025 (2022). 51. Thumuluri, V., Almagro Armenteros, J. J., Johansen, A. R., Nielsen, H. & Winther, O. DeepLoc 2.0: multi-label subcellular localization prediction using protein language models. Nucleic Acids Res. 50, W228–W234 (2022). 52. Zhou, S., Grisel, S., Herpoël-Gimbert, I. & Rosso, M.-N. A PCR-based method to quantify fungal growth during pretreatment of lig- nocellulosic biomass. J. Microbiol. Methods 115, 67–70 (2015). 53. Klein, G. et al. RNA-binding proteins are a major target of silica nanoparticles in cell extracts.Nanotoxicology 10, 1555–1564 (2016). 54. McGregor, N. G. S. et al. Activity-based protein profiling reveals dynamic substrate-specific cellulase secretion by saprotrophic basidiomycetes. Biotechnol. Biofuels 15, 6 (2022). 55. Tryfona, T. et al. Grass xylan structural variation suggests functional specialization and distinctive interaction with cellulose and lignin. The Plant Journal 113, 1004–1020 (2023). 56. Gilbert, H. J., Hazlewood, G. P., Laurie, J. I., Orpin, C. G. & Xue, G. P. Homologous catalytic domains in a rumen fungal xylanase: evi- dence for gene duplication and prokaryotic origin. Mol. Microbiol. 6, 2065–2072 (1992). 57. Urbániková, Ľ., Vršanská, M., Krogh, K. B. R., Hoff, T. & Biely, P. Structural basis for substrate recognition by Erwinia chrysanthemi GH30 glucuronoxylanase. FEBS J. 278, 2105–2116 (2011). 58. von Freiesleben, P. et al. An Aspergillus nidulans GH26 endo-β- mannanase with a novel degradation pattern on highly substituted galactomannans. Enzyme Microb Technol. 83, 68–77 (2016). 59. Pauly, M. et al. A xyloglucan-specific endo-β-1,4-glucanase from Aspergillus aculeatus: expression cloning in yeast, purification and characterization of the recombinant enzyme. Glycobiology 9, 93–100 (1999). 60. Fung, B. M., Khitrin, A. K. & Ermolaev, K. An improved broadband decoupling sequence for liquid crystals and solids. J. Magn. Reson. 142, 97–101 (2000). 61. Takegoshi, K., Nakamura, S. & Terao, T. 13C–1H dipolar-assisted rotational resonance in magic-angle spinning NMR. Chem. Phys. Lett. 344, 631–637 (2001). Acknowledgements The authors would like to thank the French Institute of Bioinformatics (IFB) for providing computational facilities through their Galaxy interface and the CAZy team for updating the CAZy database. Mireille Haon and Jonas Thomsen are acknowledged for their participation to the collec- tion of samples, Gideon Davies, Hermen Overkleft and Zirui Li for pro- viding chemical probes, and Bastien Bissaro for his help with H2O2 quantification. K.J., P.D. and J.G.B. received funding from the Novo Nordisk Foundation grant NNF20OC0059697 -OxyMiST project. The UK High-Field Solid-State NMR Facility used in this research was funded by EPSRC and BBSRC (EP/T015063/1), as well as, for the 1GHz instrument, EP/R029946/1. J.G.B. received funding from the European Union’s Hor- izon 2020 research and innovation programme under Grant Agreement No 101008500. Author contributions R.R., M.N.R., L.T., P.D., B.H., K.J., J.A. and J.G.B. conceived the work. J.G.B coordinated the study. R.R., L.G., R.C., S.L., I.G., T.T., L.T., K.J., R.D. and J.G.B. designed the experiments. R.R., A.L., L.G., R.C., S.L., D.N., J.L., S.G., I.G., H.J.M., G.M., T.T., X.Y. and E.D. performed the experiments. R.R., A.L., L.G., R.C., S.L., I.G., H.J.M., T.T., M.N.R., L.T., P.D., B.H., K.J., R.D., J.A. and J.G.B. analysed the data. R.R., A.L. and J.G.B. wrote the original draft. All authors have approved the final version of the paper. Competing interests The authors declare no competing interests. Additional information Supplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41467-025-62567-3. Correspondence and requests for materials should be addressed to Jean-Guy Berrin. Peer review information Nature Communications thanks Gry Alfredsen and the other, anonymous, reviewers for their contribution to the peer review of this work. A peer review file is available. Reprints and permissions information is available at http://www.nature.com/reprints Publisher’s note Springer Nature remains neutral with regard to jur- isdictional claims in published maps and institutional affiliations. Article https://doi.org/10.1038/s41467-025-62567-3 Nature Communications | (2025) 16:7352 12 https://www.fs.usda.gov/nrs/pubs/jrnl/2016/nrs_2016_glaeser_001.pdf https://www.fs.usda.gov/nrs/pubs/jrnl/2016/nrs_2016_glaeser_001.pdf https://doi.org/10.1038/s41467-025-62567-3 http://www.nature.com/reprints www.nature.com/naturecommunications Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, 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 you modified the licensed material. Youdonot havepermissionunder this licence toshare adapted material derived from this article or parts of it. 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-nc-nd/4.0/. © The Author(s) 2025 Article https://doi.org/10.1038/s41467-025-62567-3 Nature Communications | (2025) 16:7352 13 http://creativecommons.org/licenses/by-nc-nd/4.0/ http://creativecommons.org/licenses/by-nc-nd/4.0/ www.nature.com/naturecommunications Wood decay under anoxia by the brown-rot fungus Fomitopsis pinicola Results A restricted microbial community decomposes wood under O2 constraints in nature Fomitopsis pinicola can grow and decay wood in anoxia In anoxia, Fomitopsis pinicola decays wood polysaccharides to build its cell wall Secretion of a complete set of PCWDEs in anoxia Discussion Methods Wood sampling Strain isolation and authentication Dioxygen (O2) profiles in wood Microscopy Protein extraction from wood samples Metaproteomics Protein annotations Non-intrusive O2 concentration measurements Fungal solid-state cultures on pine Solid-state cultures in an O2 gradient Solid-state cultures in controlled O2 concentration Mass loss and water content Determination of fungal growth by quantitative PCR (qPCR) Anaerobic jar cultures Bioreactor Proteomics Quantification of hydrogen peroxide pH measurements and glycoside hydrolase activity assay Monosaccharide detection and quantification Liquid chromatography mass spectrometry (LC-MS) analysis Preparation of alcohol Insoluble residue and hemicellulose extraction Enzymatic hydrolysis and polysaccharide analysis by carbohydrate gel electrophoresis (PACE) Solid-state NMR Reporting summary Data availability References Acknowledgements Author contributions Competing interests Additional information