Extremotolerant Fungi in Resinous Soils: A Unique Diversity of Generalist and Specialized Hydrocarbon Degraders

Extremotolerant Fungi in Resinous Soils: A Unique Diversity of Generalist and Specialized Hydrocarbon Degraders | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Extremotolerant Fungi in Resinous Soils: A Unique Diversity of Generalist and Specialized Hydrocarbon Degraders Ângela Pinheiro, Tiago M. Martins, Adélia Varela, Patrícia Domingos, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8530099/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background : Filamentous fungi are ubiquitous and constitute more than 75% of the soil biomass. Fungal diversity increasingly emerges as a key factor in soil ecosystem resilience against climate change and pollution, yet much of this diversity remains hidden and potentially in decline. While investigations have primarily focused on fungal tolerance to extreme physical conditions, such as temperature and salinity, chemically stressed environments remain underexplored reservoirs of novel fungal diversity. These habitats may harbour strains with significant biotechnological potential. This study tested the hypothesis that long-term contamination of soil with Pinus resin alters fungal diversity and promotes the emergence of specialized fungal lineages enriched in hydrocarbon-degrading capabilities. Results : We analysed a resinous soil sample collected from an inactive resin processing site undisturbed for nearly 50 years. Initial physicochemical and microscopy analyses confirmed the presence of viable fungi despite extreme environmental constraints. High-throughput sequencing of fungal ITS2 regions revealed a fungal community composition highly distinct from adjacent forest soil, characterized by unusual taxonomic profiles and a high proportion of poorly classified or novel lineages. Functional inference and taxonomic analyses identified hydrocarbon-associated taxa including Sorocybe resinae (one of the most abundant OTUs) and Amorphotheca resinae (detected at low abundance). Conclusions : The identified fungi are known resinicolous and extremophilic species, illustrating the unique ecological adaptation of fungi within resin-rich, chemically stressful soils. Fungal metacommunity High-throughput sequencing Resin microbial ecology Extremophilic fungi Hydrocarbon-associated taxa Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background Fungi are ubiquitous in topsoil, displaying cosmopolitan distributions but also patterns of habitat filtering that reflect their exceptional adaptability [ 1 , 2 ]. Global fungal species richness is estimated between 2.2 to 3.8 million [ 3 ], yet to date only c.a. 160 000 fungal species have been formally described [ 4 ], including hundreds that can influence human health, both as pathogens or drivers of environmental change [ 5 ]. High-throughput DNA-based surveys have revolutionized our understanding of fungal biogeography and ecological roles, establishing soils as among the most diverse biological habitats on Earth, though their spatial and temporal distributions remain insufficiently understood [ 1 , 6 , 7 ]. Fungi adaptability allows colonization across extremes, from the stratosphere, Antarctic glaciers to the human gut [ 8 ]. This ecological success is driven by unique physiological strategies, and both metabolic and morphologic plasticity [ 9 , 10 ]. Within soil ecosystems, fungi span from specialists constrained to narrow, extreme niches (e.g. Amorphotheca spp. found in polluted habitats) [ 11 , 12 ] to broadly tolerant generalists (e.g. Aspergillus fumigatus that thrive across a wide array of habitats, from compost to croplands) [ 9 , 13 , 14 ]. Adaptation strategies are most apparent in soils with extreme conditions such as temperature, water availability, or nutrient stress: thermophiles like Thermomyces lanuginosus inhabit compost [ 13 , 15 ], psychrophiles such as Thelebolus microsporus persist in frozen soils [ 15 – 17 ] and xerophiles, including Wallemia sebi occur in arid habitats [ 18 , 19 ]. In these settings, selective pressures exclude all but a restricted set of stress-adapted colonizers [ 10 , 18 ]. Anthropogenic environments often impose additional selective pressures, featuring extremes of pH, temperature, radiation, and chemical pollutants; conditions unfriendly to most microorganisms [ 18 ]. Resin-contaminated soils are particularly challenging for microbial colonization due to low nutrient availability, acidic pH, and high resin acids concentration [ 20 – 22 ]. Resin acids, including abietic (AA) acid and dehydroabietic (DHA) acid, are potent allelochemicals for many soil microbes and aquatic organisms (with LC50 values in the sub-mg/L range) [ 20 , 23 ]. As a result, resin acts as a chemical filter in conifer bark and in contaminated soils, shaping microbial succession and community structure during resin acid breakdown events [ 20 , 24 ]. Resin degradation mechanisms are better characterized in bacteria, usually involving dit gene clusters (e.g. Pseudomonas and Paraburkholderia ), compare to fungi, which presumably involve cytochrome P450s activity [ 24 , 25 ]. Examples of fungal species capable of degrading resin acids include Phlebiopsis gigantea and Trametes versicolor [ 26 ]. Fungi inhabiting resin-rich environments plausibly possess traits conferring tolerance and/or degradative capabilities toward these compounds, positioning them as models for studying extremophilic adaptation. However, little is known about how long-term, high-dose resin exposure in industrial environments alters soil mycobiome composition and function, or how these chemically extreme soils compare to other soils. Filling this gap is essential for advancing soil eco-health, biogeochemical management, and strategies for ecosystem recovery or bioremediation. In this study, we use high-throughput, culture-independent (metabarcoding) community profiling to characterize the mycobiome of resin-impacted soil from an inactive industrial site. We compare its taxonomic and predicted functional composition to that of nearby soils (also under anthropogenic pressure) and integrate these findings with global databases of fungal diversity. Our aim is to better classify the ecological distinctiveness of resinous soils within a broader fungal biodiversity framework. Material and Methods Study design. We investigated whether long-term exposure to Pinus resin fosters specialization within the colonizing fungal communities, leading to enrichment of hydrocarbon-degrading fungi. Resinous soil (RS) was collected inside a resin refinery in Portugal, inactive since the 1970s. A nearby forest soil (FS) sample was collected for comparison. Scanning electronic microscopy (SEM) confirmed the presence of numerous fungal structures within RS, which when placed onto culture media showed growing hyphae. The soil mycobiota was analysed via high-throughput sequencing of environmental DNA. For mycobiome profiling, Operational Taxonomic Units (OTUs) were computed and identified with public sequence databases. Bioinformatic and statistical analyses enable resolution of sub-communities, including resinicolous fungi, extremophiles, and generalists, supporting inferences about ecological specialization. Complementary physiochemical characterizations of the RS included analysis of resin acid content by nuclear magnetic resonance (NMR), alongside assessment of their abiotic and biotic degradation. Chemicals. Malt Extract Agar (MEA) and mycological peptone were obtained from Oxoid (Hants, UK). Other culture media components were acquired from Fischer Chemical (Waltham, MA, USA) or Sigma-Aldrich (Darmstadt, Germany). All solvents used were analytical grade or higher: methanol (p.a., > 99.9%, Fisher Chemical), acetone (p.a., > 99.8%, Fisher Chemical), phosphoric acid (p.a., 85%, José M. Gomes Santos), benzene (p.a., > 99.7%, Sigma-Aldrich), and deuterated dimethyl sulfoxide (DMSO- d 6 ; p.a., > 99.99%, Merck). Resin acid standards: abietic acid (AA, p.a., ≥ 85%), dehydroabietic acid (DHA, p.a., > 95%), and isopimaric acid (IPA, p.a., ≥ 98%) purchased from Acros Organics (Verona, Italy), Fluorochem (Hadfield, UK), and Sigma-Aldrich, respectively. Water was obtained from a Milli-Q system (Millipore). Soil sampling and processing. Soil samples were collected in August 2018 at the inactive resin refinery in Oleiros, Portugal (39° 56'34.6 "N, 7° 55'44.3" W). Resinous soil was retrieved as a compact block (1m 2 x 0.005m) weighting 4.90 ± 0.42 kg, from the resin processing pavilion. Control forest soil samples were collected near the outdoor resin receiving area using a transect sampling method: four subsamples spaced approximately 15 meters apart, collected at ≤ 10 cm depth after litter removal, totalling 0.72 ± 0.03 kg. Samples were transported in sterile plastic bags, stored at -20°C in dark. The frozen resinous soil block was subdivided into four segments, each cut into ~ 2 cm 2 pieces using an electric wood saw. From each segment, 25–35 pieces were homogenized by cryomilling at − 196°C (RESTCH cryomill with a 5 mL jar, two 5-mm aluminium balls) employing a 3-min precool, 1-min milling at 30 Hz, and 0.5-min of cooling at 5 Hz. A composite RS sample was prepared by pooling 25 g of homogenized material from each segment. FS subsamples were sieved to particles ≤ 2 mm (ISO 11464:2006), and a composite sample was obtained by pooling 25 g of each subsample. All processed samples were stored sealed at 4 ºC, dark until analysis. Characterization of soil samples. Physicochemical analyses of either soil were performed: pH (ISO 10390:2005, in distilled H 2 O), gravimetric water content (θg; ISO 11465:1993), total nitrogen content (TKN; ISO 11261:1995, modified Kjeldhal Method), water activity (a w ) (HygroPalm HP23-AW-A probe (Rotronic AG, Bassersdorf, Switzerland)) [ 27 ], and organic carbon (OC; Walkley-Black wet oxidation method); organic matter (OM) was estimated as OC x 1.724 [ 28 , 29 ], except that the OM for RS was determined by the European Norm 12879:2000, dry method. Resin acids were extracted from the composite soil samples using a fast solvent-sonication [ 30 ]: soils were mixed with methanol (1:2 w/v), sonicated thrice (45 Hz, 30°C, 30 min), centrifuged (4500 g , 15 min), and the pooled methanolic fractions (two extractions) dried under nitrogen flow, and stored at -20°C until NMR analysis (n = 3). NMR analysis on a Bruker Avance III 800 CRYO (Germany) at 25°C, employed 1D and 2D experiments ( 1 H, 1 H- 1 H COSY, 1 H- 13 C HSQC and 1 H- 13 C HMBC). The methanolic soil extracts (5-mm-diameter NMR tubes) were dissolved in DMSO- d 6 (500 µL) with benzene as internal standard (10 µL of benzene solution, 125 g·L − 1 ) (n = 3). Signals for DHA (H-14 at 6.84 ppm), IPA (H-11 at 5.79 ppm) and Pimaric acid (PA, H-13 at 5.12 ppm) were integrated for quantification as previously defined [ 31 ]. MestReNova, Version 11.04–18998 (Mestrelab Research) was used to process the raw data acquired. RS pieces (2 cm 2 ) and RS cryomilled were imaged via SEM at Instituto Técnico de Lisboa Electron Microscopy Lab (MicroLab). Samples were mounted on aluminium stubs with carbon tape, sputter coated with Au/Pd using a Quorum Technologies coater (model Q150T ES), and observed with a ThermoScientific Phenom ProXG6 SEM (model with a CsB6 filament) equipped with an energy dispersive spectroscopy (EDS) light element detector. Decay of abietic acid (AA) in synthetic soil. The decay of AA (0.3 mgꞏml − 1 , pH = 7) was accessed in synthetic soil (sand, kaolinite, bentonite, CaCO 3 , and humic acid) inoculated with a 6h-old peptone water extract of the RS (10:1, 30°C with shaking, 100 rpm) [ 30 , 32 ]. Abiotic controls were also performed. Samples were incubated for 7, 14 and 29 days (20 ºC, dark), with time-zero controls included. At each endpoint, AA was recovered (fast solvent-sonication, n = 3), and the extracts stored at -20°C until chromatographic analysis. AA content in the synthetic soil extracts was determined by HPLC using an Alliance 2695 system (Waters Corporation, Milford, MA, USA) with a PDA detector (Bromma, Sweden) and Symmetry C18 column (4.6 mm × 250 mm, 5 µm), isocratic elution with 2 mM MeOH:H 3 PO 4 (86:14), flow 1 mLꞏmin − 1 , at 30°C [ 33 ]. AA (240 nm) was quantified using an external standard method with a commercial pure compound; detection and quantification limits were 0.0001 mgꞏmL − 1 and 0.4 mgꞏmL − 1 , respectively. Data acquisition was accomplished with Empower 2 software (Waters). Soil mycobiome profiling. DNA was extracted from 0.5 g composite soil samples (n = 3) using an optimized phenol/chloroform/CTAB methodology [ 34 ]. The ITS2 fungal rDNA region was amplified in two steps: initial PCR with standard primers, followed by a second PCR using the same primers carrying a barcode: gITS7 (5'-GTGARTCATCGARTCTTTG-3') and ITS4 (5'-TCCTCCGCTTATTGATATGC-3'). In the second amplification conditions were modified: denaturation at 95°C, 25 cycles, annealing at 55°C. PCR products were purified (Zymo DNA Clean & Concentrator-5) and quality-checked by gel electrophoresis and NanoDrop™ spectrometry (One Microvolume UV-Vis Spectrophotometer, Thermo Fisher Scientific Inc., USA). Amplicons were sequenced in two independent Illumina MiSeq runs for RS (RS1 and RS2) and in a single one for FS. Sequence data processing and taxonomic assignment. Raw data was pre-processed using fastp v0.23.2, including adapter trimming and read-pair merging [ 35 ]. Sequence clustering and OTU inference followed SEED v2.1 pipeline, as applied before [ 34 , 36 ] (UPARSE v8.1.1861 [ 37 ], ITSx v1.0.11 [ 38 ]). The most abundant sequences were retrieved as representative for each out and used for downstream analyses. Taxonomic assignments targeted the “Full UNITE + INSD dataset for Fungi” (v04.04.2024) [ 39 , 40 ], and alternatively the NCBI fungal subset [ 41 ], with a default e-value threshold of 1e − 5 using either the megablast algorithm or blastn. Bioinformatics and statistical analyses. Statistical analyses were conducted in R v4.4.1. Alpha diversity metrics: observed richness, Shannon, Simpson, inverse Simpson, evenness and Chao1, were computed using Vegan v2.6.10 [ 42 ] and otuSummary v0.1.2 [ 43 ]; rare OTUs were defined as ≤ 1% relative abundance. Statistical comparisons included Wilcoxon rank-sum test or t-tests depending on assumptions verified by Shapiro–Wilk and Levene’s tests. To assess effect sizes, Cliff’s delta was calculated when necessary. Beta diversity was assessed using Bray–Curtis dissimilarity, visualized via Principal Coordinates Analysis (PCoA), and tested using PERMANOVA; homogeneity of dispersion was verified by PERMDISP (ANOVA) [ 42 ]. Taxa visualisation employed Metacoder v0.3.8 (heat trees) [ 44 ], ggVennDiagram [ 45 ], and ComplexHeatmap v2.25.0 [ 46 ]. RS and FS mycobiota (depleted from singletons) were compared with the Global Soil Mycobiome Consortium (GSMc) dataset [ 47 ] using phyloseq v1.48.0 [ 48 ] and the retrieved taxonomic composition was visualized using fantaxtic v0.2.1 [ 49 ]. Boxplots and additional statistical graphics were generated with ggplot2 v3.5.1 and associated tidyverse (v2.0.0) tools [ 50 – 52 ]. Final figures were prepared for publication in Inkscape v1.2.1 [ 53 ]. Functional characterization of the mycobiomes. The ecological traits of the combined RS and FS genus-level dataset (composed of 1079 OTUs, including singletons) was assigned using the FungalTraits v1.2 database [ 54 ]. Trait annotation focused the following trait categories: lifestyle (guild), growth form, substrate preference, decay type, and plant association. Genera lacking trait information (e.g. incertae sedis or unclassified taxa) were excluded from functional summaries and trait coverage estimates. Relative abundance (%) per trait level was calculated independently for each soil, based on aggregated genus-level abundances. Dominant genera were reported only when the RS–FS difference > 1.0% (Δ_pp) and their relative abundance reached ≥ 0.5% in at least one soil. Predictive functional analysis was performed using FunFun v0.1.15 [ 55 , 56 ] to infer metabolic potential from sequence data. Default parameters were applied, with the exception that the epsilon distance for the nearest neighbour was fixed at 0.6. The resulting functional predictions were weighted by OTU abundance, and subsequently normalized. Enrichment analysis for functional categories was then performed using R v4.4.1, DESeq2 v1.48.2, and dplyr v1.1.4 packages [ 57 – 59 ]. Enriched functional categories display log 2 fold change > 1, and adjusted p -value < 0.05. Results and Discussion Resinous soils conceal viable fungi despite selective physicochemical conditions Fungi adapted to resinous environments are often proficient in degrading complex hydrocarbons [20,60], but their diversity and functional potential remains largely underexplored. Our study system, a resin industry facility inactive for over fifty years ( Fig.1A-B ), offers distinct resin-impacted niches: a resin receiving area (open field) and a resin processing pavilion (mostly enclosed, reduced erosion and disturbance) ( Fig. S1A-B ). Resinous soil (RS), sampled within the pavilion, was obtained as a compact block with the bottom surface in contact with cement flooring and high humidity ( Fig. 1C ). Forest soil (FS) was collected in the resin receiving area within a Pinus stand ( Fig. S1C ). Physicochemical analysis ( Fig. S2 ) revealed that RS (cryomilled) is moderately acidic (pH 5.9), extremely rich in OM (84%), and N-poor (0.05%), reflecting resin chemical imprint. FS values (7.41% OM, 0.15% N) were within the expected range reported for Portuguese P. pinaster forest soils (7-12%, >5 cm deep) [61,62], yet RS far exceeded typical OM values. Gravimetric water content was higher in RS (95.38 gꞏKg ‑1 ) compared to FS (13.75 gꞏKg -1 ), due to moisture preserved in the resin-block’s cement interface. However, a w , a critical determinant for microbial life, was 0.78 in RS, favouring xerotolerant taxa, and 0.9 in FS, generally permissive for most microorganisms. NMR analyses of the methanolic extracts of RS confirmed the dominance of DHA, PA, and IP ( Fig. 1D-E ). AA was not detected, despite its prevalence in local Pinus resins [31]. Extraction controls of a synthetic matrix (containing 0.6 mg AA per g of soil) indicated ≥80% recovery efficiency. No resin acids were detected in FS. SEM of untreated resinous blocks revealed abundant mycelial structures: hyphae, conidia, asci, ascospores and conidiophores, distributed throughout the matrix ( Fig. 2 ) and sometimes embedded within resin ( Fig. 2F-G ) or on Pinus sp. pollen grains ( Fig. 2C ). Calcofluor white-stained fungal mycelial expanded outward from RS particles ( Fig. S3A-B ), further confirmed by light microscopy ( Fig. S3C-D ). Moreover, synthetic soil spiked with AA (0.12 mg/g) and inoculated with the RS microbial extract exhibited clear biotic degradation of AA at 14 and 30 days (>50% AA loss by day 30; Fig. S4 ). In the sterilized controls (abiotic controls), AA decay reached a plateau after 14 days. Thus, viable fungi are not only present in RS but are metabolically responsive. These results are consistent with previous reports of resin acids degradation by e.g. Trametes versicolor , Phlebiopsis gigantea , and Aspergillus niger [20,26,63]. Collectively, these results confirm that RS retains colonizing fungi, regardless of high resin acid diversity and concentration (≥0.15 g per g of RS), and C-rich, N-poor and low a w conditions. These conditions resemble those of hydrocarbon-polluted soils, which are often inhabited by hydrocarbon-degrading fungi and bacteria [64,65]. Resinous soil mycobiome: richness and classification uncertainty Aiming to validate unusual diversity and dominance by specialists in the RS mycobiome two independent high-throughput ITS2 sequencing runs (RS1 and RS2) were conducted. Raw reads were 51 million and 69 million ( Table S1 ), yielding post-filtering 53,779 and 65,188 high-quality reads, which were subsequently clustered (97% similarity) into 341 ( Table S2 ) and 476 OTUs ( Table S3 ), for RS1 and RS2, respectively. Alpha diversity metrics: observed richness (number of detected OTUs), Chao1 (total richness including undetected rare taxa), Shannon diversity (accounting for both richness and evenness with sensitivity to rare and abundant taxa), Simpson diversity indices (1–D and 1/D, emphasizing evenness and dominance structure), and evenness (the balance between relative abundances across taxa), confirmed normality and homogeneity (Shapiro–Wilk and Levene’s tests, p > 0.05) ( Table S4 ). Most metrics showed no differences between RS1 and RS2 ( Table 1 , Fig. 3A , Table S5 ), except higher Shannon diversity ( p ≈ 0.02) and Inverse Simpson ( p ≈ 0.05) for RS2 (t-test). Analyses of abundant and rare fungal taxa ( Table S6 ) likewise indicated stable dominant species across runs. RS2 appears marginally more even than RS1, but differences were minor (likely technical). β-diversity (Bray–Curtis, PERMANOVA) showed no significant compositional differences between runs (F = 0.83, R² = 0.17, p = 0.7, Fig. 3B ) and similar within-group variance (F = 0.25, p = 0.65; Fig. 3C ), with only 17% of explained variance attributable to dataset ( Fig. S5 A,B) . Moreover, 63% of the 156 identified genera were shared between runs ( Fig. 3D), with nearly all abundant taxa (>0.5%) present in both, and few unique genera exceptionally rare: 16 in RS1 and 38 in RS2 ( Table S7 ). Consequently, the RS mycobiome (integrating both runs) comprises 620 fungal OTUs ( Table S8 ). Alpha-diversity metrics showed high fungal richness and relatively stable community structure, but also remarkable taxonomic uncertainty ( Table S5 and S6 ). The mean observed richness was 322 OTUs (IQR: 36), with the Chao1 estimator indicating a potentially higher richness (mean: 476, IQR: 93), suggestive of presence of undetected taxa. Shannon diversity (mean: 3.1, IQR: 0.07), Simpson index (mean: 0.9, IQR: 0.007), and evenness (mean: 104, IQR: 10) all displayed narrow interquartile ranges, underscoring low dominance effects and balance composition structure across replicates ( Table S5 ). The RS mycobiome spans 6 phyla, 26 classes, 64 orders, 107 families, and 154 unique genera ( Table S8 ), dominated by Ascomycota (65.5%) and Basidiomycota (26.2%). Minor phyla (Mortierellomycota, Chytridiomycota, and Mucoromycota) were present at negligible abundances (<0.01%; Table S8, Fig.4A ). About 9.4% of OTUs could not be classified beyond Kingdom (“no hit” reads). Taxonomic uncertainty was also substantial at lower ranks: 3.9% of OTUs at phylum level, and up to 30.8% and 56.6% were assigned to incertae sedis at genus and species, respectively. This indicates that the resin’s selective environment may be shaping an uncharted “microbial dark matter” (Fig. 4B), consistent with UNITE classification of ‘dark taxa’ in ITS-based species hypotheses [39,66]. Moreover, the structure of the community ( Fig. S6 ) was highly uneven with a small group of dominant taxa: 19 classified genera plus unclassified reads, Eurotiomycetes, Fungi, Basidiomycota, and Dothideomycetes incertae sedis , accounted for 95.1% of abundance, with 131 genera contributing to the remaining 4.9%, each ≤1%. Key dominants included Eurotiomycetes gen. incertae sedis (26.2%), Sporobolomyces (12.3%), Sorocybe (7.1%), Penicillium (5.6%), along several other genera at intermediate abundances (0.5–5%; Table S9). Many of the genera detected in RS mycobiome represent ecological specialists (Table S9), including resinicolous taxa, both as dominants ( Sorocybe (best-hit S. resinae ) Sarea , Lophium and Mytilinidion [67]) and at low-abundance ( Chaenothecopsis [67]), and taxa associated with conifer hosts ( Colacogloea , Symbiotaphrina , Infundichalara , Phialocephala , Pragmopora [68-71]). Penicillium and Aspergillus spp. build the dominant group of generalists, consistent with their frequent isolation from hydrocarbon-rich environments (e.g. A. tubingensis and A. niger, Penicillium chrysogenum [14,72]) and ability to transform plant terpenes (e.g. P. digitatum [73] and A. niger [74]). In addition, RS is rich in multiple specialist taxa repeatedly reported from extreme and/or petroleum-rich environments: Candida keroseneae (originally described from aviation fuel) [75], Debaryomyces hansenii , Exophiala spp. (black yeasts), Rhodotorula (including R. mucilaginosa ) [18,76] and Scedosporium [14,77]. Within low-abundant taxa it is noted the presence of Amorphotheca resinae (= Hormoconis resinae ), known to utilize fuel components [11,78], Rhinocladiella , Cladosporium , Aureobasidium and Alternaria , frequently documented as hydrocarbon-tolerant/degraders [14], and Neodevriesia s.l., Devriesia , and related Neodevriesiaceae lineages, usually found to colonize nutrient-poor, xeric and chemically stressful surfaces [79]. Collectively, the RS mycobiome display both high taxonomic diversity and uncertainty, ecological uniqueness, and potential novelty, highlighting strong selection for specialized, stress-adapted, and potentially metabolically versatile fungal lineages. High taxonomic turnover and distinctiveness between resinous and nearby forest soils We compared the RS mycobiome to an adjacent FS mycobiome, testing if resin selectivity extends to broader local patterns ( Table S10 ). FS showed slightly higher richness (352 OTUs vs 281 OTUs in RS) but nearly identical Shannon diversity values (3.03 in RS, 3.02 in FS), and marginally lower Simpson’s indices, indicating more pronounced dominance structure in FS ( Table S11 ). Despite these observable differences, Wilcoxon rank-sum tests yield no statistical p -values (>0.05), likely constrained by small sample sizes. Nonetheless, non-parametric effect size (estimated via Cliff’s delta) indicated large biological relevant effect for richness (δ = 1.00) and Simpson’s evenness (1–D; δ = –0.67), whereas Shannon diversity effect size was negligible (δ = 0.00). βeta-diversity analyses (Whittaker’s β, β W ; Bray-Curtis dissimilarity, D BC ) quantified this contrast: richness-based turnover was higher among RS (1.95) than FS (1.41) replicates, reflecting greater internal heterogeneity in RS, while abundance-weighted dissimilarity between environments was extreme (D BC = 0.968; Table S12 ). Consistently, genus-level composition mirrored this separation. FS was dominated by Penicillium (54.2%), Sordariales gen. incertae sedis (6.4%), and Phialocephala (5.6%) (all common soil genera), while RS had Eurotiomycetes gen. incertae sedis (26.4%), Sporobolomyces (12.1%), and Sorocybe (7.7%) as dominant (the last two exclusives to RS), sustaining habitat-specific selection ( Fig.5A-B ). Together, dominant genera comprised 94.4% and 91.9% of the RS and FS communities, respectively. Taxonomic overlap of classified genera was limited: of 359 genera, only 60 (17%) were shared between soils, whereas 204 (57%) were unique to FS, and 95 (26%) to RS, with several clades strongly enriched or depleted in either soil ( Fig. 5B-C) . Each community is composed by a few dominant taxa plus a large pool of low-abundance taxa, supporting both richness/ high turnover and distinct ecological structuring. The RS mycobiome compositions retrieved from either the clustering of RS reads alone, or RS and FS reads combined, are virtually identical, except that in the last five new OTUs could be assigned in RS and the number of unclassified OTUs slightly decreased ( Table S10 ). This reflects how UPARSE defines centroids when clustering pooled data and do not represent biological differences [37]. When running the taxonomic assignment against NCBI nt database (BLASTn; e-value 0.05) instead of UNITE, the number of unclassified OTUs also reduced slightly ( Table S13 ) [39-41]. Systematically unclassified OTUs (e.g. OTU20) likely index true novelty. Overall, RS and FS, though similar in gross α-diversity, diverge strongly in community structure and in the prevalence of poorly classified or novel fungal lineages. Similar patterns have been reported in other chronically polluted substrates, indicating that richness can coexist with relatively even abundance structures due to the replacement of sensitive dominants by stress-tolerant specialists [77,80]. Minimal genus-level overlap, divergent taxonomic profiles and higher proportions of unclassified and incertae sedis OTUs in RS, support the notion of habitat-driven differentiation shaped by selective pressures in resin-rich soils. Functional characterization of the resinous soil mycobiome Trait profiling at the genus level using FungalTraits ( Table S14-S16 ) and FunFun ( Table S17 ) databases [54-56] revealed major functional differences between RS and FS mycobiomes. Substrate preference ( Table S16 ) showed the highest Bray–Curtis dissimilarity between mycobiomes (≈55), followed by growth form (≈53), lifestyle composition (≈51), and plant association (≈31), while decay type showed lower divergence (≈26). Annotation completeness varied across traits, with RS harbouring a substantially higher proportion of poorly characterized genera compared to FS. The RS mycobiome exhibited minimal plant-association coverage (17.4%) with sharp reduction of host-linked interactions, mostly putative foliar endophytes (8.3%; Penicillium , Rhodotorula , Aspergillus ) and others lacking endophytic capacity (5.4%, dominated by Colacogloea ). RS lifestyle composition was enriched in saprotrophic guilds (mostly Sporobolomyces, 12.3%, Colacogloea , 4.6%, and Sorocybe , 7.1%) and antagonistic guilds (mostly mycoparasites, 14.7%), along with substrate preferences for fungal-derived substrates (17.2%), sugar-rich resources (8.6%) and resin-associated substrates (7.1%, exclusively detected in RS). In contrast, FS was strongly dominated by soil-associated substrates (59.0% vs 6.4% in RS) and plant-associated guilds, with foliar endophytes comprising nearly 28% of total abundance (mostly Penicillium ), besides ectomycorrhizal taxa (4.3%), soil saprotrophs (9.0%), and root endophytes (3.8%). These patterns indicate that RS mycobiome exhibits saprotrophic independence and specialization on resin-derived substrates and fungal resources over plant-linked symbiotic roles. Predictive functional pathway analyses revealed substantial divergence between the two mycobiomes ( Table S17 ). The RS mycobiome showed significant enrichment in surface adherence and biofilm formation pathways, including extracellular matrix (ECM) interaction and synthesis: cell adhesion molecules (ko04514), ECM-receptor interaction (ko04512), glycosphingolipids biosynthesis (ko00601), and glycosaminoglycans metabolism (ko00532, ko00534, ko00535) ( Fig. 6A ). These traits are consistent with RS conditions, promoting biofilm-like growth and spatial stability on hydrophobic, low-moisture substrates [11]. By contrast, FS communities exhibited enrichment in niche competition categories: secondary metabolites production (ko00902, ko00997, ko01059), peptidoglycan degradation proteins (ko01011), and metabolism of amino acid precursors (ko00471, ko00473), involving L/D-alanine and D-glutamic acid ( Fig. 6A ). These traits are advantageous in nutrient-variable forest soils with intense microbial competition [81]. FS also retained brown-rot, chitinolytic, and keratinolytic decay profiles (all absent in RS), reflecting broader degradative versatility for forest litter processing. Global context: Biogeography of the resinous soil mycobiome To contextualize the ecological uniqueness of RS, its mycobiome (alongside that of the neighbouring FS) was compared to reference datasets from the Global Soil Mycobiome consortium (GSMc) [47]. RS and FS were placed within the spectrum of terrestrial biomes across European and Mediterranean regions, classified as anthropogenic and forest biomes, respectively. Comparison of Shannon diversity values across GSMc biome categories revealed similar medians, ranging from 5.48 in woodland to 5.26 in forest/shrubland ( Fig. 6B; Table S18 ). Considering only RS and FS classified OTUs (which greatly reduces their dissimilarity), both exhibited much lower Shannon values (3.06 and 3.11, respectively), placing them at the lower boundary of their biome categories and among the least diverse soils in the analysed regions with values ranging from 5.26 (subtropical broadleaf forest in Madeira, Portugal) to 6.19 (forest in Sicily, Italy). This result underscores the local divergence of RS and FS from regional diversity patterns, highlighting how chronic chemical stress and anthropogenic history can produce island-like fungal assemblages even within similar climatic zones [82,83]. Principal Coordinates Analysis (PCoA, based on Bray–Curtis dissimilarity) clustered RS and FS closely together, near the periphery of the Southern European cloud, suggesting partial compositional similarity to these soils, with no strong affiliation to a single regional or biome cluster ( Fig. S7A-B ). Analysis of the 25 most abundant fungal orders across European samples further illustrated their distinctiveness ( Fig. 6C ). RS and FS displayed reduced overall fungal abundance compared to other Portuguese and Spanish soils, and were compositionally divergent. Most reference Portuguese soils were dominated by Basidiomycota, especially Agaricales [12,84]. Contrarily, both RS and FS are dominated by Ascomycota (RS: Chaetothyriales, Saccharomycetales, Eurotiales; FS: Eurotiales, Helotiales, Sordariales), besides that fungal orders usually common in regional soils (Mortierellomycota, Zoopagomycota, and Mucoromycota) are either at low abundance or absent. Collectively, despite that the analysis is narrowed to classified OTUs, data suggest that the RS mycobiome (and to a lesser extent also that of FS) is compositionally and functionally distinct compared to geographically or climatically similar soils. Ecological context of RS mycobiome composition Although bacteria are well-established agents of diterpenoid metabolism [24], our findings underscore the significant, yet underappreciated, role of fungi in resin degradation under extreme conditions. Whereas fungi typically do not dominate in transient, resin-amended environments [24], the RS mycobiome supports their persistence and potential functional relevance. Microcosm experiments suggested that the RS mycobiota is actively involved in resin-acid turnover: under antibiotic suppression of bacteria, >50% of AA was lost in 30 days, confirming viable fungal terpenoid degradation capacity ( Fig. S4 ). Comparative analysis with mycobiomes from resin-rich conifer tissues (pollen, needles, bark, galls) [24,85-87] reveals that typical core classes in those environments: Dothideomycetes, Tremellomycetes, Mortierellomycota, and Mucoromycota, are only detected in RS at vestigial levels (e.g. Dothideomycetes 3.9%, Tremellomycetes 0.3%). In sharp contrast, Eurotiomycetes are strongly enriched ( Fig. 4B-C, Table S8 ), consistent with previous reports on spruce-derived resin enrichments, and resinicolous surveys [24,87]. Experimental enrichment studies confirmed that resin compounds act as long-term selective agents, rapidly filtering fungal and bacterial populations [24]. Early-stage Ascomycota (e.g. A. terreus , A. flavus , P. decumbens ) are only transient community members and are found in RS solely as rare traces (≤0.03%). With the persistence of resin, only extremotolerant Eurotiomycetes and Microbotryomycetes (red yeasts) [12], remain abundant, forming stable, stress-adapted consortia distinct from opportunistic colonizers. Dominant genera from pollen and needles: Epicoccum , Vishniacozyma , Alternaria , Aureobasidium , and Cladosporium , occur in RS at very low abundance, suggesting limited recruitment from above-ground conifer sources, and further supporting the uniqueness of chemical filtering in RS [85,86]. Satellite taxa reported in association with P. pinaster needles, such as Mortierella clonocystis , Cryptococcus podzolicus , Aspergillus piperis , and Metschnikowia sp. [85], are largely absent in RS (<0.01%, except Aspergillus at 0.65–1.06%). This pattern suggest that the RS assemblage arises through soil-chemical selection, consistent with soils under pine plantations favouring Ascomycota (especially Trichocomaceae: Aspergillus , Talaromyces , Penicillium ) over Basidiomycota prevalent in undisturbed forest soils [84]. Conclusions The described resinous soil mycobiome is radically distinct from forest soil and microbial communities associated with natural conifer tissues, indicating that chronic resin saturation from long-term anthropogenic activity acts as an intense ecological filter. RS is dominated by resin acids (≤15% of soil mass), recalcitrant markers of conifer resin [31], representing an anthropogenically amplified natural chemical stress. Combined with low water activity, extreme C:N imbalance (C/N>1600), and persistent toxicity, RS creates an extreme microhabitat filtering for functionally specialized fungal taxa. It parallels chronic heavily oil-polluted soils where hydrocarbon-degrading and/or stress-tolerant fungi dominate [14,72]. These convergent selective pressures underscore the broader relevance of RS as a model for fungal adaptation to persistent chemical stress . Our findings elevate the significant yet frequently overlooked functional contribution of fungi under persistent resin pressure. Microcosm experiments confirmed fungal viability and active resin acid turnover, though the specific taxa driving these modifications remain unidentified. The RS mycobiome is defined by extremotolerant Eurotiomycetes (42.7%) and resilient yeasts from Microbotryomycetes, distinguishing it from conifer needle, pollen, and bark mycobiomes [85,86]. Moreover, early-stage colonizers of resin-rich substrates [24,87], appear only at trace levels, highlighting a succession toward stress-adapted, substrate-specialized lineages. Classical resinicolous genera (e.g. Sorocybe , Sarea , and Chaenothecopsis ( Mycocaliciales ) [67]) and hydrocarbon-tolerant genera (e.g. Exophiala , and Debaryomyces [18,76]), comprise the most dominant, functionally important groups. Conversely, canonically dominant aerial or foliar associates are rare, reflecting limited persistence of above-ground propagules [85,86,88]. The ecological uniqueness of RS relies on many low abundant taxa, yet some culturable strains (e.g. Amorphotheca spp., 0.33%; T. versicolor , 0.001%) remain viable under standard conditions (unpublished data). Beyond known resinicolous and hydrocarbon-associated fungi, RS harbours a considerable fraction of unclassified or incertae sedis OTUs (>30% at genus level, >56% at species level) [39,66], far exceeding ambiguity in forest soil or global soil datasets. This suggests resin-saturated habitats function as refugia for fungal “dark matter,” hosting novel lineages and metabolic functions, deserving deep analysis. The persistence of ancient resinicolous fungi like Sarea and Chaenothecopsis in Paleogene fossil records underscores the deep evolutionary continuity of resin-associated niches [67,89,90], while modern resinicolous fungi (e.g. Ganoderma adspersum ) colonizing diverse polymeric matrices [91,92] extend the ecological significance of resin adaptation to anthropogenic substrates. This evolutionary breadth reflects the fundamental selective power of resin chemistry across natural and industrial timescales. RS resin acid persistence mirrors chemical legacies encountered in pulp-mill effluents and industrial sites [20]. Thus, selecting for fungal consortia capable of modifying such stressors offers significant bioremediation potential. However, RS dominant taxa also included opportunists’ pathogens (e.g. Exophiala , Aspergillus ), highlighting a link between environmental extremotolerance and opportunistic pathogenicity [93,94] with implications relevant to One Health and Eco Health frameworks [95,96]. Far from being marginal, resinous soils highlight fungal potential to colonize, persist, and drive transformations in extreme ecosystems. These findings expand our view of natural product-shaped environments, proposing resin-rich habitats as “laboratories” for adaptive innovation with applications from pollutant attenuation to biocatalysts discovery. Future work integrating targeted cultivation with deep molecular analyses will further unravel, both the known and unknown, fungal diversity revealed here. Declarations Ethics approval and consent to participate Not applicable. Note that all samples – fungal isolates - were provided anonymized. Consent for publication Not applicable Ethics declaration Not applicable Data availability statement Raw sequencing data generated in this study have been deposited in the NCBI Sequence Read Archive (SRA) under BioProject accession PRJNA1392999. All processed data supporting the findings of this study, including taxonomic tables, diversity metrics, and functional analyses, are provided in the Supplementary Information. Competing interests The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest Authors’ contributions All authors have made important contributions to the acquisition, analysis and interpretation of data and contributed to the drafting of the manuscript: CAMA (sampling); AP, AV (fungal experiments, analytics); PD, IM (technical support); AP, TM (bioinformatics); RE, AB (NMR analyses); AP (manuscript draft); CSP (conceptualization resources, supervision and final manuscript). All authors read and approved the final version of the manuscript. Funding We acknowledge funding from the Fundação para a Ciência e Tecnologia (FCT) through the projects ‘FATE’ (PTDC/CTA-AMB/6587/2020), FATE4FUTURE (nº 2023.16924.ICDT), MOSTMICRO-ITQB Unit (UIDB/04612/2020 and UIDP/04612/2020) and LS4FUTURE Associated Laboratory (LA/P/0087/2020), and by Fundo Europeu de Desenvolvimento Regional (FEDER) under the project “BIOPINUS” (CENTRO-01-0247-FEDER-072630). ÂP and RE are grateful to FCT for the fellowships references SFRH/BD/144593/2019 (https://doi.org/10.54499/SFRH/BD/144593/2019), and 2021.06435.B (https://doi.org/10.54499/2021.06435.BD), respectively. TM is grateful for the working contract (2023.11076.TENURE.076) financed by national funds under the FCT-TENURE Programme. Acknowledgments We extend our gratitude to all members of the Silva Pereira lab for their valuable discussions, with special thanks to alumni researchers Celso Martins, Daryna Piontkivska and Stefano Nones for their assistance in the initial data analyses. The authors are also grateful to the technical support provided by Maria Cristina Leitão (chromatography, ITQB NOVA), Carolina Feliciano (microscopy, BIC ITQB NOVA), Francisco Martins (Electric saw operator, INIAV), and Isabel Nogueira (SEM imaging, IST Microlab). The NMR data were acquired at CERMAX, ITQB NOVA, Oeiras, Portugal, with equipment funded by Fundação para a Ciência e Tecnologia (FCT) and the microscopy imaging was performed in the BIC cluster at ITQB NOVA, which is supported by PPBI (Portuguese Platform of BioImaging), co-funded by national funds from OE (Orçamento de Estado) and by European funds from FEDER (Fundo Europeu de Desenvolvimento Regional, PPBI-POCI-01-0145-FEDER-022122). References Tedersoo L, Bahram M, Põlme S , et al . Global diversity and geography of soil fungi. Science . 2014;346(6213):1256688. doi:doi:10.1126/science.1256688 Niskanen T, Lücking R, Dahlberg A , et al . 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Mechanisms and implications of bacterial-fungal competition for soil resources. Isme j . Jan 8 2024;18(1)doi:10.1093/ismejo/wrae073 Zheng Q, Hu Y, Zhang S , et al . Soil multifunctionality is affected by the soil environment and by microbial community composition and diversity. Soil Biol Biochem . Sep 2019;136:107521. doi:10.1016/j.soilbio.2019.107521 Tedersoo L, Mikryukov V, Zizka A , et al . Global patterns in endemicity and vulnerability of soil fungi. Glob Chang Biol . Nov 2022;28(22):6696-6710. doi:10.1111/gcb.16398 Byers AK, Condron L, Donavan T , et al . Soil microbial diversity in adjacent forest systems - contrasting native, old growth kauri (Agathis australis) forest with exotic pine (Pinus radiata) plantation forest. FEMS Microbiol Ecol . May 1 2020;96(5)doi:10.1093/femsec/fiaa047 Romeralo C, Martín-García J, Martínez-Álvarez P , et al . Pine species determine fungal microbiome composition in a common garden experiment. Fungal Ecology . 2022;56doi:10.1016/j.funeco.2021.101137 Armstrong C, Ganasamurthy S, Wigley K, Mercier C, Wakelin S. The microorganisms and metabolome of Pinus radiata Pollen. Environ Microbiome . Dec 18 2024;19(1):103. doi:10.1186/s40793-024-00656-4 Vilanova C, Marin M, Baixeras J, Latorre A, Porcar M. Selecting microbial strains from pine tree resin: biotechnological applications from a terpene world. PLoS One . 2014;9(6):e100740. doi:10.1371/journal.pone.0100740 Abrego N, Furneaux B, Hardwick B , et al . Airborne DNA reveals predictable spatial and seasonal dynamics of fungi. Nature . Jul 2024;631(8022):835-842. doi:10.1038/s41586-024-07658-9 Tuovila H, Schmidt AR, Beimforde C, Dörfelt H, Grabenhorst H, Rikkinen J. Stuck in time – a new Chaenothecopsis species with proliferating ascomata from Cunninghamia resin and its fossil ancestors in European amber. Fungal Diversity . 2012;58(1):199-213. doi:10.1007/s13225-012-0210-9 Rikkinen J, Poinar G. A new species of resinicolous Chaenothecopsis (Mycocaliciaceae, Ascomycota) from 20 million year old Bitterfeld amber, with remarks on the biology of resinicolous fungi. Mycological Research . 2000;104(1):7-15. doi:10.1017/s0953756299001884 Pardi-Comensoli L, Tonolla M, Colpo A , et al . Microbial Depolymerization of Epoxy Resins: A Novel Approach to a Complex Challenge. Applied Sciences . 2022;12(1)doi:10.3390/app12010466 Najam M, Javaid S, Iram S , et al . Microbial Biodegradation of Synthetic Polyethylene and Polyurethane Polymers by Pedospheric Microbes: Towards Sustainable Environmental Management. Polymers (Basel) . Jan 11 2025;17(2)doi:10.3390/polym17020169 Siscar-Lewin S, Hube B, Brunke S. Emergence and evolution of virulence in human pathogenic fungi. Trends Microbiol . Jul 2022;30(7):693-704. doi:10.1016/j.tim.2021.12.013 Casadevall A, Pirofski LA. Accidental virulence, cryptic pathogenesis, martians, lost hosts, and the pathogenicity of environmental microbes. Eukaryot Cell . Dec 2007;6(12):2169-2174. doi:10.1128/ec.00308-07 One Health High-Level Expert P, Adisasmito WB, Almuhairi S , et al . One Health: A new definition for a sustainable and healthy future. PLOS Pathogens . 2022;18(6):e1010537. doi:10.1371/journal.ppat.1010537 Harrison S, Kivuti-Bitok L, Macmillan A, Priest P. EcoHealth and One Health: A theory-focused review in response to calls for convergence. Environment International . 2019/11/01/ 2019;132:105058. doi:https://doi.org/10.1016/j.envint.2019.105058 Table Table 1. Parametric t -test results for alpha diversity metrics in resinous soil datasets RS1 and RS2. Metrics tested include richness, Shannon and Simpson diversity, Chao1 richness estimator, and evenness. Mean Metric RS1 RS2 t -statistic p -value 95% Confidence Interval Richness 201.67 260.33 -2.24 0.09 -131.36, 14.03 Shannon* 2.99 3.19 -3.77 0.02 -0.35, -0.05 Simpson 0.90 0.91 -2.64 0.06 -0.03, 0.0007 Inverse Simpson* 9.74 11.20 -2.79 0.05 -2.92, -0.006 Chao1 313.37 375.75 -1.14 0.32 -213.88, 89.11 Evenness 67.52 81.70 -1.70 0.17 -37.41, 9.04 (*) Values marked with an asterisk denote significant differences ( p < 0.05). Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterial.pdf TableS2FileS1RS1.xlsx TableS3FileS2RS2.xlsx TableS8FileS3RS.xlsx TableS10FileS4RSFS.xlsx TableS14FileS5RSFSFungalTraits.xlsx TableS17FileS6functionalenrichment.xlsx TableS18FileS7alphadiversity.xlsx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8530099","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":576011306,"identity":"0d9fe455-8044-4f18-9ac7-30f022ec5b20","order_by":0,"name":"Ângela Pinheiro","email":"","orcid":"","institution":"Universidade Nova de Lisboa","correspondingAuthor":false,"prefix":"","firstName":"Ângela","middleName":"","lastName":"Pinheiro","suffix":""},{"id":576011308,"identity":"33b13321-c500-4661-b173-62828a019cd0","order_by":1,"name":"Tiago M. Martins","email":"","orcid":"","institution":"Universidade Nova de Lisboa","correspondingAuthor":false,"prefix":"","firstName":"Tiago","middleName":"M.","lastName":"Martins","suffix":""},{"id":576011309,"identity":"e81fd768-d34d-4918-8ce6-9f2cd9217a67","order_by":2,"name":"Adélia Varela","email":"","orcid":"","institution":"Instituto Nacional de Investigação Agrária e Veterinária","correspondingAuthor":false,"prefix":"","firstName":"Adélia","middleName":"","lastName":"Varela","suffix":""},{"id":576011313,"identity":"ba3fbdff-d000-423a-a357-80608f9b16b5","order_by":3,"name":"Patrícia Domingos","email":"","orcid":"","institution":"Universidade Nova de Lisboa","correspondingAuthor":false,"prefix":"","firstName":"Patrícia","middleName":"","lastName":"Domingos","suffix":""},{"id":576011314,"identity":"1f01eb03-7dc8-4ec4-9953-e73526021aff","order_by":4,"name":"Rita Escórcio","email":"","orcid":"","institution":"Universidade Nova de Lisboa","correspondingAuthor":false,"prefix":"","firstName":"Rita","middleName":"","lastName":"Escórcio","suffix":""},{"id":576011315,"identity":"d4c125fa-9b29-4a75-9fd8-43aa18e6fee3","order_by":5,"name":"Artur Bento","email":"","orcid":"","institution":"Universidade Nova de Lisboa","correspondingAuthor":false,"prefix":"","firstName":"Artur","middleName":"","lastName":"Bento","suffix":""},{"id":576011316,"identity":"757287ec-8a76-49e9-9b1a-f5ed69d2e862","order_by":6,"name":"Isabel Martins","email":"","orcid":"","institution":"Universidade Nova de Lisboa","correspondingAuthor":false,"prefix":"","firstName":"Isabel","middleName":"","lastName":"Martins","suffix":""},{"id":576011317,"identity":"c79a5ccf-6e5e-4f96-8130-47fcea0f77b9","order_by":7,"name":"Carlos A. M. Afonso","email":"","orcid":"","institution":"University of Lisbon","correspondingAuthor":false,"prefix":"","firstName":"Carlos","middleName":"A. M.","lastName":"Afonso","suffix":""},{"id":576011318,"identity":"707a07d3-e3a8-44c1-8630-561157d9d61f","order_by":8,"name":"Cristina Silva Pereira","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIiWNgGAWjYNACAwYGfmYGBmYQm49oLZLNzBAtbAwMjA3E6TpArBb52c3HPnwouCdvfJz/4O0ChsN5bAy8xx/gNfzOseSZMwyKDbcdZma2nsFwuJiNgS8Rry0GEjnGzDwGCYxALWzSPAyHE9sYeAzxO2xG/mfmPwYJ9pubidXCcCOHmZnBICFxAzOxWoB+MWbsMUhInnGY2dh6hkF6YhszX+IMvA6b3fyY4cefBNv+/oMPbxdUWCf2s/ce+IDXYRIobGCcMjDz4NWArgUMCGkZBaNgFIyCkQYAWLM/wIL4OLIAAAAASUVORK5CYII=","orcid":"","institution":"Universidade Nova de Lisboa","correspondingAuthor":true,"prefix":"","firstName":"Cristina","middleName":"Silva","lastName":"Pereira","suffix":""}],"badges":[],"createdAt":"2026-01-06 10:38:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8530099/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8530099/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102313573,"identity":"acd0c3b9-c056-4fc4-9b46-b6577a8f6103","added_by":"auto","created_at":"2026-02-10 12:12:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":516813,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOrigin, composition, and chemical characterisation of resinous soil samples. \u003c/strong\u003eResinous soil samples were collected in Oleiros, Portugal (A), specifically within an inactive resin refinery at the resin processing pavilion (B). These samples, obtained in the form of thick blocks (C), preserve a diverse array of typical resin acids, as demonstrated by a representative NMR spectrum of the soil organic extract; average concentrations (mg·g\u003csup\u003e-1\u003c/sup\u003e) of each resin acid detected in the organic extracts of the resinous soil (n=3) are shown as an insert (D). Additionally, the chemical structures of resin acids commonly found in \u003cem\u003ePinus pinaster\u003c/em\u003e resin are illustrated for reference (E). A schematic of the resin receiving area and the resin processing pavilion is shown in the Supplementary information Fig.\u0026nbsp;S1. Maps and satellite images (A and B) were prepared using QGIS v3.34.7 (QGIS Development Team, 2024).\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8530099/v1/fa71386a1b584b74e7b1309f.png"},{"id":102397524,"identity":"05dfcee4-588b-46d5-b4fe-cd46ade967eb","added_by":"auto","created_at":"2026-02-11 10:17:42","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":729294,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMorphological characterisation of resinous soil.\u003c/strong\u003eScanning electron microscopy (SEM) micrographs of the resinous soil matrix and associated fungal structures. \u003cstrong\u003e(A)\u003c/strong\u003eThe surface morphology of the resinous soil sample under analysis, providing a general overview of the sample. At this scale, no clearly identifiable fungal structures are observed. Scale bar: 200 µm. \u003cstrong\u003e(B)\u003c/strong\u003e Filamentous structures resembling fungal hyphae. Scale bar: 100 µm. \u003cstrong\u003e(C)\u003c/strong\u003e A \u003cem\u003ePinus\u003c/em\u003e pollen grain (~10–15 µm in diameter) undergoing fungal parasitism. The pollen exine remains largely intact, but fungal hyphae are observed penetrating and surrounding the grain. Scale bar: 30 µm. \u003cstrong\u003e(D)\u003c/strong\u003e A dense, filamentous fungal network interspersed with small spherical structures (~1–3 µm) developing at the tips of the hyphae, suggestive of conidia, ascospores or sporocarps. Scale bar: 20 µm. \u003cstrong\u003e(E)\u003c/strong\u003e A smooth, porous matrix containing embedded unidentifiable material along with a free-floating fungal spore (~5–10 µm in diameter). The surrounding matrix may represent an area of fungal colonisation or preservation. Scale bar: 20 µm. \u003cstrong\u003e(F)\u003c/strong\u003e A fragmented matrix entrapping elongated, oval structures (~3–5 µm long), which are morphologically consistent with ascospores or conidia from filamentous fungi. Scale bar: 20 µm. \u003cstrong\u003e(G)\u003c/strong\u003eA cavity-like structure (~7 µm in diameter) with multiple rounded elements (~3 µm in diameter) enclosed within the resin matrix, either a sporangium or a degraded fungal fruiting body containing spores. The spores appear loosely aggregated, suggesting a prior release event. Scale bar: 15 µm. \u003cstrong\u003e(H)\u003c/strong\u003e A filamentous fungal structure resembling a conidiophore. Scale bar: 15 µm. Yellow arrows indicate fungal hyphae, cyan arrows indicate conidia, ascospores, or sporocarps, and green arrows indicate fungal spores. See also supplementary Fig. S4 for confocal and light microscopy on the viability of fungal material from resinous soil particles.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8530099/v1/53e58dcdacf398d1530aa956.png"},{"id":102313524,"identity":"068aa31c-b374-4b5b-8120-22d1167a26d2","added_by":"auto","created_at":"2026-02-10 12:12:35","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":279317,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparative analysis of fungal community diversity and composition in resinous soil datasets, RS1 and RS2. (A) \u003c/strong\u003eAlpha diversity indices (Observed Richness, Chao1, Shannon, Simpson) shown as boxplots, based on biological replicates (S3I–S3III). Interquartile ranges, medians, and replicate values are indicated. Alpha diversity metrics presented in Table 1. Detailed summary statistics are provided in supplementary Table S5. \u003cstrong\u003e(B)\u003c/strong\u003e Principal Coordinates Analysis (PCoA) based on Bray–Curtis dissimilarity, showing ordination of fungal communities by dataset. Colours indicate dataset origin; variance is represented along the first two axes. PERMANOVA (F = 0.83, R² = 0.172, p = 0.7) indicated no significant differences between datasets.\u003cstrong\u003e (C)\u003c/strong\u003e Beta dispersion distances shown as boxplots, representing within-group variability. PERMDISP (F = 0.25, p = 0.6) indicated no significant differences in dispersion, supporting the PERMANOVA results. See also Supplementary Fig. S5A–B. \u003cstrong\u003e(D)\u003c/strong\u003eGenus-level composition similarity between datasets shown as a Venn diagram. Of the 156 detected genera, 99 (63%) were shared, while 18 (12%) and 39 (25%) were unique to RS1 and RS2, respectively. Only taxa classified to the genus level are shown; unclassified OTUs were excluded. Details on shared and unique genera in Table S7).\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8530099/v1/a9f02d73c5f862bc23e581c5.png"},{"id":102313560,"identity":"b81a6fbf-34f8-4968-b363-3a11855c97b6","added_by":"auto","created_at":"2026-02-10 12:12:42","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":378735,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTaxonomic composition and structure of the resinous soil (RS) mycobiome. (A) \u003c/strong\u003eRelative abundance of fungal phyla detected in the RS mycobiome, shown as mean relative abundance (%) across RS replicates. Ascomycota and Basidiomycota dominate the community, whereas other phyla (Mortierellomycota, Chytridiomycota, and Mucoromycota) are present only at trace levels. A noticeable fraction of reads could not be confidently assigned beyond higher taxonomic ranks, including taxa classified as \u003cem\u003eincertae sedis\u003c/em\u003e and unclassified (“no hit”) sequences.\u003cstrong\u003e (B) \u003c/strong\u003eHeat tree visualisation of the RS fungal community generated using the metacoder framework, illustrating taxonomic relationships from phylum to genus. Node colour reflects mean relative abundance (%) across RS replicates, with darker colours indicating higher abundance, while node size corresponds to the number of OTUs assigned to each taxon. The presence of numerous poorly resolved branches and \u003cem\u003eincertae sedis\u003c/em\u003eassignments highlights the uneven structure of the community and the prevalence of taxonomically unresolved fungal lineages in resinous soil.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8530099/v1/b9736030a18c6824bca09bcb.png"},{"id":102313476,"identity":"78ad6ec8-1f53-4426-96b4-1f1d7bc445cf","added_by":"auto","created_at":"2026-02-10 12:12:31","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1015458,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLocal comparison of fungal communities in resinous soil (RS) and adjacent forest soil (FS). (A) \u003c/strong\u003eGenus-level composition of the RS and FS mycobiomes, shown as mean relative abundance (%) across replicates. In both soils, community structure is highly uneven and dominated by a small number of taxa, and the identity of dominant genera differs strongly between habitats.\u003cstrong\u003e (B) \u003c/strong\u003eHeat tree representation highlighting taxonomic differences between RS and FS at the genus level. Node colour indicates the log₂ fold change in relative abundance between soils, with enrichment toward RS or FS shown by negative or positive values, respectively, while node size reflects the number of OTUs associated with each taxon. The distribution of coloured branches illustrates clades that are consistently favoured or suppressed in each soil type.\u003cstrong\u003e (C) \u003c/strong\u003eOverlap of classified fungal genera between RS and FS. Only a small subset of genera is shared between the two soils, whereas most taxa are unique to one environment, underscoring strong habitat-specific filtering and limited taxonomic overlap despite close spatial proximity.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8530099/v1/3eb623464b9e4327d03f664c.png"},{"id":102313574,"identity":"6bdd6f1c-6e1d-4189-979c-b267e1f467eb","added_by":"auto","created_at":"2026-02-10 12:12:45","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":438679,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFunctional differentiation of resinous soil (RS) and forest soil (FS) mycobiomes and their placement within European fungal diversity. (A) \u003c/strong\u003ePredictive functional pathway analysis inferred using FunFun, showing differentially enriched KEGG pathways between RS and FS mycobiomes (log₂ fold change \u0026gt; 1 or \u0026lt; −1; adjusted P \u0026lt; 0.05). Pathways related to surface adherence, extracellular matrix interaction, and biofilm-associated processes are enriched in RS, whereas FS is enriched in pathways associated with secondary metabolite biosynthesis, microbial competition, and amino acid metabolism. Point colour indicates the direction and magnitude of enrichment (log₂ fold change), and point size reflects statistical significance (−log₁₀ Pₐdⱼ). \u003cstrong\u003e(B) \u003c/strong\u003eShannon diversity indices of fungal communities across biome categories defined in the Global Soil Mycobiome consortium (GSMc), including anthropogenic, forest, grassland, shrubland, tundra, woodland, and unknown biomes. Boxplots show the distribution of diversity values within each biome. RS and FS (yellow dots) fall at the lower boundary of their respective biome categories, indicating reduced diversity relative to regional reference soils. \u003cstrong\u003e(C) \u003c/strong\u003eRelative abundances of the 25 most abundant fungal orders across selected European sampling sites, including RS and FS. Bars are grouped by country and coloured by phylum and order. RS and FS are dominated by Ascomycota and show reduced representation or absence of fungal orders commonly abundant in regional soils, including Mortierellomycota, Zoopagomycota, and Mucoromycota, highlighting their compositional divergence from geographically and climatically similar European soils.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-8530099/v1/7350705c2da5a208ae66abf4.png"},{"id":104834865,"identity":"fcc74d85-0511-4a54-ad75-9656c99251e0","added_by":"auto","created_at":"2026-03-17 17:33:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4860788,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8530099/v1/c52af066-a79c-4224-82d2-49e2e2e079e8.pdf"},{"id":102313475,"identity":"a36ac205-7baf-427f-a63c-8bc5d71a657e","added_by":"auto","created_at":"2026-02-10 12:12:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":3005312,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8530099/v1/62df11e5c806fa9eb27d8345.pdf"},{"id":102397241,"identity":"0e216650-8eff-4e85-9808-e96fb26dd89a","added_by":"auto","created_at":"2026-02-11 10:12:08","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":64307,"visible":true,"origin":"","legend":"","description":"","filename":"TableS2FileS1RS1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8530099/v1/4ea22d90684b352a3c1a2ed8.xlsx"},{"id":102313572,"identity":"f9ed6381-c1bc-4593-a9ed-65c5520e480a","added_by":"auto","created_at":"2026-02-10 12:12:44","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":84608,"visible":true,"origin":"","legend":"","description":"","filename":"TableS3FileS2RS2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8530099/v1/63a4d3f4154dc6b02a676f2d.xlsx"},{"id":102313483,"identity":"17c9b0a8-4611-45e5-9d34-2d2f83ab16c9","added_by":"auto","created_at":"2026-02-10 12:12:32","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":96325,"visible":true,"origin":"","legend":"","description":"","filename":"TableS8FileS3RS.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8530099/v1/a76f471a91ca502d508fdc8e.xlsx"},{"id":102313479,"identity":"012ea529-adce-4e52-aa93-df913caf2edf","added_by":"auto","created_at":"2026-02-10 12:12:32","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":183464,"visible":true,"origin":"","legend":"","description":"","filename":"TableS10FileS4RSFS.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8530099/v1/010f5249db36bedc14fce476.xlsx"},{"id":102313557,"identity":"bfdc7a30-46df-4be1-b31a-db062765b022","added_by":"auto","created_at":"2026-02-10 12:12:38","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":1499437,"visible":true,"origin":"","legend":"","description":"","filename":"TableS14FileS5RSFSFungalTraits.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8530099/v1/8cd8aae98a8a55754735b5b5.xlsx"},{"id":102313577,"identity":"aa9a04f6-6c35-4242-bddf-50b51c768e0b","added_by":"auto","created_at":"2026-02-10 12:12:47","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":119664,"visible":true,"origin":"","legend":"","description":"","filename":"TableS17FileS6functionalenrichment.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8530099/v1/69a8bb289f534e49ead072e9.xlsx"},{"id":102397275,"identity":"70a7f59a-d395-49ef-a4dc-5d8e53e4c41f","added_by":"auto","created_at":"2026-02-11 10:14:29","extension":"xlsx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":131577,"visible":true,"origin":"","legend":"","description":"","filename":"TableS18FileS7alphadiversity.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8530099/v1/5396253257c7d2283453afad.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Extremotolerant Fungi in Resinous Soils: A Unique Diversity of Generalist and Specialized Hydrocarbon Degraders","fulltext":[{"header":"Background","content":"\u003cp\u003eFungi are ubiquitous in topsoil, displaying cosmopolitan distributions but also patterns of habitat filtering that reflect their exceptional adaptability [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Global fungal species richness is estimated between 2.2 to 3.8\u0026nbsp;million [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], yet to date only c.a. 160 000 fungal species have been formally described [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], including hundreds that can influence human health, both as pathogens or drivers of environmental change [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. High-throughput DNA-based surveys have revolutionized our understanding of fungal biogeography and ecological roles, establishing soils as among the most diverse biological habitats on Earth, though their spatial and temporal distributions remain insufficiently understood [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFungi adaptability allows colonization across extremes, from the stratosphere, Antarctic glaciers to the human gut [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. This ecological success is driven by unique physiological strategies, and both metabolic and morphologic plasticity [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Within soil ecosystems, fungi span from specialists constrained to narrow, extreme niches (e.g. \u003cem\u003eAmorphotheca\u003c/em\u003e spp. found in polluted habitats) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] to broadly tolerant generalists (e.g. \u003cem\u003eAspergillus fumigatus\u003c/em\u003e that thrive across a wide array of habitats, from compost to croplands) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Adaptation strategies are most apparent in soils with extreme conditions such as temperature, water availability, or nutrient stress: thermophiles like \u003cem\u003eThermomyces lanuginosus\u003c/em\u003e inhabit compost [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], psychrophiles such as \u003cem\u003eThelebolus microsporus\u003c/em\u003e persist in frozen soils [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] and xerophiles, including \u003cem\u003eWallemia sebi\u003c/em\u003e occur in arid habitats [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In these settings, selective pressures exclude all but a restricted set of stress-adapted colonizers [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Anthropogenic environments often impose additional selective pressures, featuring extremes of pH, temperature, radiation, and chemical pollutants; conditions unfriendly to most microorganisms [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eResin-contaminated soils are particularly challenging for microbial colonization due to low nutrient availability, acidic pH, and high resin acids concentration [\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Resin acids, including abietic (AA) acid and dehydroabietic (DHA) acid, are potent allelochemicals for many soil microbes and aquatic organisms (with LC50 values in the sub-mg/L range) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. As a result, resin acts as a chemical filter in conifer bark and in contaminated soils, shaping microbial succession and community structure during resin acid breakdown events [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Resin degradation mechanisms are better characterized in bacteria, usually involving \u003cem\u003edit\u003c/em\u003e gene clusters (e.g. \u003cem\u003ePseudomonas\u003c/em\u003e and \u003cem\u003eParaburkholderia\u003c/em\u003e), compare to fungi, which presumably involve cytochrome P450s activity [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Examples of fungal species capable of degrading resin acids include \u003cem\u003ePhlebiopsis gigantea\u003c/em\u003e and \u003cem\u003eTrametes versicolor\u003c/em\u003e [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Fungi inhabiting resin-rich environments plausibly possess traits conferring tolerance and/or degradative capabilities toward these compounds, positioning them as models for studying extremophilic adaptation. However, little is known about how long-term, high-dose resin exposure in industrial environments alters soil mycobiome composition and function, or how these chemically extreme soils compare to other soils. Filling this gap is essential for advancing soil eco-health, biogeochemical management, and strategies for ecosystem recovery or bioremediation.\u003c/p\u003e \u003cp\u003eIn this study, we use high-throughput, culture-independent (metabarcoding) community profiling to characterize the mycobiome of resin-impacted soil from an inactive industrial site. We compare its taxonomic and predicted functional composition to that of nearby soils (also under anthropogenic pressure) and integrate these findings with global databases of fungal diversity. Our aim is to better classify the ecological distinctiveness of resinous soils within a broader fungal biodiversity framework.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cp\u003e \u003cb\u003eStudy design.\u003c/b\u003e We investigated whether long-term exposure to \u003cem\u003ePinus\u003c/em\u003e resin fosters specialization within the colonizing fungal communities, leading to enrichment of hydrocarbon-degrading fungi. Resinous soil (RS) was collected inside a resin refinery in Portugal, inactive since the 1970s. A nearby forest soil (FS) sample was collected for comparison. Scanning electronic microscopy (SEM) confirmed the presence of numerous fungal structures within RS, which when placed onto culture media showed growing hyphae. The soil mycobiota was analysed \u003cem\u003evia\u003c/em\u003e high-throughput sequencing of environmental DNA. For mycobiome profiling, Operational Taxonomic Units (OTUs) were computed and identified with public sequence databases. Bioinformatic and statistical analyses enable resolution of sub-communities, including resinicolous fungi, extremophiles, and generalists, supporting inferences about ecological specialization. Complementary physiochemical characterizations of the RS included analysis of resin acid content by nuclear magnetic resonance (NMR), alongside assessment of their abiotic and biotic degradation.\u003c/p\u003e \u003cp\u003e \u003cb\u003eChemicals.\u003c/b\u003e Malt Extract Agar (MEA) and mycological peptone were obtained from Oxoid (Hants, UK). Other culture media components were acquired from Fischer Chemical (Waltham, MA, USA) or Sigma-Aldrich (Darmstadt, Germany). All solvents used were analytical grade or higher: methanol (p.a., \u0026gt; 99.9%, Fisher Chemical), acetone (p.a., \u0026gt; 99.8%, Fisher Chemical), phosphoric acid (p.a., 85%, Jos\u0026eacute; M. Gomes Santos), benzene (p.a., \u0026gt;\u0026thinsp;99.7%, Sigma-Aldrich), and deuterated dimethyl sulfoxide (DMSO-\u003cem\u003ed\u003c/em\u003e\u003csub\u003e\u003cem\u003e6\u003c/em\u003e\u003c/sub\u003e; p.a., \u0026gt;\u0026thinsp;99.99%, Merck). Resin acid standards: abietic acid (AA, p.a., \u0026ge;\u0026thinsp;85%), dehydroabietic acid (DHA, p.a., \u0026gt;\u0026thinsp;95%), and isopimaric acid (IPA, p.a., \u0026ge;\u0026thinsp;98%) purchased from Acros Organics (Verona, Italy), Fluorochem (Hadfield, UK), and Sigma-Aldrich, respectively. Water was obtained from a Milli-Q system (Millipore).\u003c/p\u003e \u003cp\u003e \u003cb\u003eSoil sampling and processing.\u003c/b\u003e Soil samples were collected in August 2018 at the inactive resin refinery in Oleiros, Portugal (39\u0026deg; 56'34.6 \"N, 7\u0026deg; 55'44.3\" W). Resinous soil was retrieved as a compact block (1m\u003csup\u003e2\u003c/sup\u003e x 0.005m) weighting 4.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42 kg, from the resin processing pavilion. Control forest soil samples were collected near the outdoor resin receiving area using a transect sampling method: four subsamples spaced approximately 15 meters apart, collected at \u0026le;\u0026thinsp;10 cm depth after litter removal, totalling 0.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03 kg. Samples were transported in sterile plastic bags, stored at -20\u0026deg;C in dark. The frozen resinous soil block was subdivided into four segments, each cut into ~\u0026thinsp;2 cm\u003csup\u003e2\u003c/sup\u003e pieces using an electric wood saw. From each segment, 25\u0026ndash;35 pieces were homogenized by cryomilling at \u0026minus;\u0026thinsp;196\u0026deg;C (RESTCH cryomill with a 5 mL jar, two 5-mm aluminium balls) employing a 3-min precool, 1-min milling at 30 Hz, and 0.5-min of cooling at 5 Hz. A composite RS sample was prepared by pooling 25 g of homogenized material from each segment. FS subsamples were sieved to particles\u0026thinsp;\u0026le;\u0026thinsp;2 mm (ISO 11464:2006), and a composite sample was obtained by pooling 25 g of each subsample. All processed samples were stored sealed at 4 \u0026ordm;C, dark until analysis.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCharacterization of soil samples.\u003c/b\u003e Physicochemical analyses of either soil were performed: pH (ISO 10390:2005, in distilled H\u003csub\u003e2\u003c/sub\u003eO), gravimetric water content (θg; ISO 11465:1993), total nitrogen content (TKN; ISO 11261:1995, modified Kjeldhal Method), water activity (a\u003csub\u003ew\u003c/sub\u003e) (HygroPalm HP23-AW-A probe (Rotronic AG, Bassersdorf, Switzerland)) [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], and organic carbon (OC; Walkley-Black wet oxidation method); organic matter (OM) was estimated as OC x 1.724 [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], except that the OM for RS was determined by the European Norm 12879:2000, dry method.\u003c/p\u003e \u003cp\u003eResin acids were extracted from the composite soil samples using a fast solvent-sonication [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]: soils were mixed with methanol (1:2 w/v), sonicated thrice (45 Hz, 30\u0026deg;C, 30 min), centrifuged (4500 \u003cem\u003eg\u003c/em\u003e, 15 min), and the pooled methanolic fractions (two extractions) dried under nitrogen flow, and stored at -20\u0026deg;C until NMR analysis (n\u0026thinsp;=\u0026thinsp;3). NMR analysis on a Bruker Avance III 800 CRYO (Germany) at 25\u0026deg;C, employed 1D and 2D experiments (\u003csup\u003e1\u003c/sup\u003eH, \u003csup\u003e1\u003c/sup\u003eH-\u003csup\u003e1\u003c/sup\u003eH COSY, \u003csup\u003e1\u003c/sup\u003eH-\u003csup\u003e13\u003c/sup\u003eC HSQC and \u003csup\u003e1\u003c/sup\u003eH-\u003csup\u003e13\u003c/sup\u003eC HMBC). The methanolic soil extracts (5-mm-diameter NMR tubes) were dissolved in DMSO-\u003cem\u003ed\u003c/em\u003e\u003csub\u003e\u003cem\u003e6\u003c/em\u003e\u003c/sub\u003e (500 \u0026micro;L) with benzene as internal standard (10 \u0026micro;L of benzene solution, 125 g\u0026middot;L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) (n\u0026thinsp;=\u0026thinsp;3). Signals for DHA (H-14 at 6.84 ppm), IPA (H-11 at 5.79 ppm) and Pimaric acid (PA, H-13 at 5.12 ppm) were integrated for quantification as previously defined [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. MestReNova, Version 11.04\u0026ndash;18998 (Mestrelab Research) was used to process the raw data acquired.\u003c/p\u003e \u003cp\u003eRS pieces (2 cm\u003csup\u003e2\u003c/sup\u003e) and RS cryomilled were imaged via SEM at Instituto T\u0026eacute;cnico de Lisboa Electron Microscopy Lab (MicroLab). Samples were mounted on aluminium stubs with carbon tape, sputter coated with Au/Pd using a Quorum Technologies coater (model Q150T ES), and observed with a ThermoScientific Phenom ProXG6 SEM (model with a CsB6 filament) equipped with an energy dispersive spectroscopy (EDS) light element detector.\u003c/p\u003e \u003cp\u003e \u003cb\u003eDecay of abietic acid (AA) in synthetic soil.\u003c/b\u003e The decay of AA (0.3 mgꞏml\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, pH\u0026thinsp;=\u0026thinsp;7) was accessed in synthetic soil (sand, kaolinite, bentonite, CaCO\u003csub\u003e3\u003c/sub\u003e, and humic acid) inoculated with a 6h-old peptone water extract of the RS (10:1, 30\u0026deg;C with shaking, 100 rpm) [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Abiotic controls were also performed. Samples were incubated for 7, 14 and 29 days (20 \u0026ordm;C, dark), with time-zero controls included. At each endpoint, AA was recovered (fast solvent-sonication, n\u0026thinsp;=\u0026thinsp;3), and the extracts stored at -20\u0026deg;C until chromatographic analysis. AA content in the synthetic soil extracts was determined by HPLC using an Alliance 2695 system (Waters Corporation, Milford, MA, USA) with a PDA detector (Bromma, Sweden) and Symmetry C18 column (4.6 mm \u0026times; 250 mm, 5 \u0026micro;m), isocratic elution with 2 mM MeOH:H\u003csub\u003e3\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e (86:14), flow 1 mLꞏmin\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, at 30\u0026deg;C [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. AA (240 nm) was quantified using an external standard method with a commercial pure compound; detection and quantification limits were 0.0001 mgꞏmL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 0.4 mgꞏmL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, respectively. Data acquisition was accomplished with Empower 2 software (Waters).\u003c/p\u003e \u003cp\u003e \u003cb\u003eSoil mycobiome profiling.\u003c/b\u003e DNA was extracted from 0.5 g composite soil samples (n\u0026thinsp;=\u0026thinsp;3) using an optimized phenol/chloroform/CTAB methodology [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The ITS2 fungal rDNA region was amplified in two steps: initial PCR with standard primers, followed by a second PCR using the same primers carrying a barcode: gITS7 (5'-GTGARTCATCGARTCTTTG-3') and ITS4 (5'-TCCTCCGCTTATTGATATGC-3'). In the second amplification conditions were modified: denaturation at 95\u0026deg;C, 25 cycles, annealing at 55\u0026deg;C. PCR products were purified (Zymo DNA Clean \u0026amp; Concentrator-5) and quality-checked by gel electrophoresis and NanoDrop\u0026trade; spectrometry (One Microvolume UV-Vis Spectrophotometer, Thermo Fisher Scientific Inc., USA). Amplicons were sequenced in two independent Illumina MiSeq runs for RS (RS1 and RS2) and in a single one for FS.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSequence data processing and taxonomic assignment.\u003c/b\u003e Raw data was pre-processed using fastp v0.23.2, including adapter trimming and read-pair merging [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Sequence clustering and OTU inference followed SEED v2.1 pipeline, as applied before [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] (UPARSE v8.1.1861 [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], ITSx v1.0.11 [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]). The most abundant sequences were retrieved as representative for each out and used for downstream analyses. Taxonomic assignments targeted the \u0026ldquo;Full UNITE\u0026thinsp;+\u0026thinsp;INSD dataset for Fungi\u0026rdquo; (v04.04.2024) [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], and alternatively the NCBI fungal subset [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], with a default e-value threshold of 1e\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e using either the megablast algorithm or blastn.\u003c/p\u003e \u003cp\u003e \u003cb\u003eBioinformatics and statistical analyses.\u003c/b\u003e Statistical analyses were conducted in R v4.4.1. Alpha diversity metrics: observed richness, Shannon, Simpson, inverse Simpson, evenness and Chao1, were computed using Vegan v2.6.10 [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] and otuSummary v0.1.2 [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]; rare OTUs were defined as \u0026le;\u0026thinsp;1% relative abundance. Statistical comparisons included Wilcoxon rank-sum test or t-tests depending on assumptions verified by Shapiro\u0026ndash;Wilk and Levene\u0026rsquo;s tests. To assess effect sizes, Cliff\u0026rsquo;s delta was calculated when necessary. Beta diversity was assessed using Bray\u0026ndash;Curtis dissimilarity, visualized via Principal Coordinates Analysis (PCoA), and tested using PERMANOVA; homogeneity of dispersion was verified by PERMDISP (ANOVA) [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Taxa visualisation employed Metacoder v0.3.8 (heat trees) [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], ggVennDiagram [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e], and ComplexHeatmap v2.25.0 [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. RS and FS mycobiota (depleted from singletons) were compared with the Global Soil Mycobiome Consortium (GSMc) dataset [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] using phyloseq v1.48.0 [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e] and the retrieved taxonomic composition was visualized using fantaxtic v0.2.1 [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Boxplots and additional statistical graphics were generated with ggplot2 v3.5.1 and associated tidyverse (v2.0.0) tools [\u003cspan additionalcitationids=\"CR51\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Final figures were prepared for publication in Inkscape v1.2.1 [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cb\u003eFunctional characterization of the mycobiomes.\u003c/b\u003e The ecological traits of the combined RS and FS genus-level dataset (composed of 1079 OTUs, including singletons) was assigned using the FungalTraits v1.2 database [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Trait annotation focused the following trait categories: lifestyle (guild), growth form, substrate preference, decay type, and plant association. Genera lacking trait information (e.g. \u003cem\u003eincertae sedis\u003c/em\u003e or unclassified taxa) were excluded from functional summaries and trait coverage estimates. Relative abundance (%) \u003cem\u003eper\u003c/em\u003e trait level was calculated independently for each soil, based on aggregated genus-level abundances. Dominant genera were reported only when the RS\u0026ndash;FS difference\u0026thinsp;\u0026gt;\u0026thinsp;1.0% (Δ_pp) and their relative abundance reached\u0026thinsp;\u0026ge;\u0026thinsp;0.5% in at least one soil.\u003c/p\u003e \u003cp\u003ePredictive functional analysis was performed using FunFun v0.1.15 [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] to infer metabolic potential from sequence data. Default parameters were applied, with the exception that the epsilon distance for the nearest neighbour was fixed at 0.6. The resulting functional predictions were weighted by OTU abundance, and subsequently normalized. Enrichment analysis for functional categories was then performed using R v4.4.1, DESeq2 v1.48.2, and dplyr v1.1.4 packages [\u003cspan additionalcitationids=\"CR58\" citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. Enriched functional categories display log\u003csub\u003e2\u003c/sub\u003efold change\u0026thinsp;\u0026gt;\u0026thinsp;1, and adjusted \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e"},{"header":"Results and Discussion","content":"\u003cp\u003e\u003cstrong\u003eResinous soils conceal viable fungi despite selective physicochemical conditions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFungi adapted to resinous environments are often proficient in degrading complex hydrocarbons [20,60], but their diversity and functional potential remains largely underexplored. Our study system, a resin industry facility inactive for over fifty years (\u003cstrong\u003eFig.1A-B\u003c/strong\u003e), offers distinct resin-impacted niches: a resin receiving area (open field) and a resin processing pavilion (mostly enclosed, reduced erosion and disturbance) (\u003cstrong\u003eFig. S1A-B\u003c/strong\u003e). Resinous soil (RS), sampled within the pavilion, was obtained as a compact block with the bottom surface in contact with cement flooring and high humidity (\u003cstrong\u003eFig. 1C\u003c/strong\u003e). Forest soil (FS) was collected in the resin receiving area within a \u003cem\u003ePinus\u003c/em\u003e stand (\u003cstrong\u003eFig. S1C\u003c/strong\u003e). Physicochemical analysis (\u003cstrong\u003eFig. S2\u003c/strong\u003e) revealed that RS (cryomilled) is moderately acidic (pH 5.9), extremely rich in OM (84%), and N-poor (0.05%), reflecting resin chemical imprint. FS values (7.41% OM, 0.15% N) were within the expected range reported for Portuguese \u003cem\u003eP. pinaster\u003c/em\u003e forest soils (7-12%, \u0026gt;5 cm deep) [61,62], yet RS far exceeded typical OM values. Gravimetric water content was higher in RS (95.38 gꞏKg\u003csup\u003e‑1\u003c/sup\u003e) compared to FS (13.75 gꞏKg\u003csup\u003e-1\u003c/sup\u003e), due to moisture preserved in the resin-block\u0026rsquo;s cement interface. However, a\u003csub\u003ew\u003c/sub\u003e, a critical determinant for microbial life, was 0.78 in RS, favouring xerotolerant taxa, and 0.9 in FS, generally permissive for most microorganisms. NMR analyses of the methanolic extracts of RS confirmed the dominance of DHA, PA, and IP (\u003cstrong\u003eFig. 1D-E\u003c/strong\u003e). AA was not detected, despite its prevalence in local \u003cem\u003ePinus\u0026nbsp;\u003c/em\u003eresins [31]. Extraction controls of a synthetic matrix (containing 0.6 mg AA \u003cem\u003eper\u003c/em\u003e g of soil) indicated \u0026ge;80% recovery efficiency. No resin acids were detected in FS.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSEM of untreated resinous blocks revealed abundant mycelial structures: hyphae, conidia, asci, ascospores and conidiophores, distributed throughout the matrix (\u003cstrong\u003eFig.\u0026nbsp;2\u003c/strong\u003e) and sometimes embedded within resin (\u003cstrong\u003eFig.\u0026nbsp;2F-G\u003c/strong\u003e) or on \u003cem\u003ePinus\u003c/em\u003e sp. pollen grains (\u003cstrong\u003eFig.\u0026nbsp;2C\u003c/strong\u003e). Calcofluor white-stained fungal mycelial expanded outward from RS particles (\u003cstrong\u003eFig.\u0026nbsp;S3A-B\u003c/strong\u003e), further confirmed by light microscopy (\u003cstrong\u003eFig.\u0026nbsp;S3C-D\u003c/strong\u003e). Moreover, synthetic soil spiked with AA (0.12 mg/g) and inoculated with the RS microbial extract exhibited clear biotic degradation of AA at 14 and 30 days (\u0026gt;50% AA loss by day 30; \u003cstrong\u003eFig. S4\u003c/strong\u003e). In the sterilized controls (abiotic controls), AA decay reached a plateau after 14 days. Thus, viable fungi are not only present in RS but are metabolically responsive. These results are consistent with previous reports of resin acids degradation by e.g. \u003cem\u003eTrametes versicolor\u003c/em\u003e, \u003cem\u003ePhlebiopsis gigantea\u003c/em\u003e, and \u003cem\u003eAspergillus niger\u003c/em\u003e [20,26,63]. \u0026nbsp;Collectively, these results confirm that RS retains colonizing fungi, regardless of high resin acid diversity and concentration (\u0026ge;0.15 g \u003cem\u003eper\u003c/em\u003e g of RS), and C-rich, N-poor and low a\u003csub\u003ew\u003c/sub\u003e conditions. These conditions resemble those of hydrocarbon-polluted soils, which are often inhabited by hydrocarbon-degrading fungi and bacteria [64,65].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResinous soil mycobiome: richness and classification uncertainty\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAiming to validate unusual diversity and dominance by specialists in the RS mycobiome two independent high-throughput ITS2 sequencing runs (RS1 and RS2) were conducted. Raw reads were 51 million and 69 million (\u003cstrong\u003eTable\u0026nbsp;S1\u003c/strong\u003e), yielding post-filtering 53,779 and 65,188 high-quality reads, which were subsequently clustered (97% similarity) into 341 (\u003cstrong\u003eTable\u0026nbsp;S2\u003c/strong\u003e) and 476 OTUs (\u003cstrong\u003eTable\u0026nbsp;S3\u003c/strong\u003e), for RS1 and RS2, respectively. Alpha diversity metrics: observed richness (number of detected OTUs), Chao1 (total richness including undetected rare taxa), Shannon diversity (accounting for both richness and evenness with sensitivity to rare and abundant taxa), Simpson diversity indices (1\u0026ndash;D and 1/D, emphasizing evenness and dominance structure), and evenness (the balance between relative abundances across taxa), confirmed normality and homogeneity (Shapiro\u0026ndash;Wilk and Levene\u0026rsquo;s tests, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026gt;\u0026nbsp;0.05) (\u003cstrong\u003eTable\u0026nbsp;S4\u003c/strong\u003e). Most metrics showed no differences between RS1 and RS2 (\u003cstrong\u003eTable\u0026nbsp;1\u003c/strong\u003e, \u003cstrong\u003eFig.\u0026nbsp;3A\u003c/strong\u003e, \u003cstrong\u003eTable\u0026nbsp;S5\u003c/strong\u003e), except higher Shannon diversity (\u003cem\u003ep\u003c/em\u003e \u0026asymp; 0.02) and Inverse Simpson (\u003cem\u003ep\u003c/em\u003e \u0026asymp; 0.05) for RS2 (t-test). Analyses of abundant and rare fungal taxa (\u003cstrong\u003eTable\u0026nbsp;S6\u003c/strong\u003e) likewise indicated stable dominant species across runs. RS2 appears marginally more even than RS1, but differences were minor (likely technical). \u0026beta;-diversity (Bray\u0026ndash;Curtis, PERMANOVA) showed no significant compositional differences between runs (F = 0.83, R\u0026sup2; = 0.17, \u003cem\u003ep\u003c/em\u003e = 0.7, \u003cstrong\u003eFig.\u0026nbsp;3B\u003c/strong\u003e) and similar within-group variance (F = 0.25, \u003cem\u003ep\u003c/em\u003e = 0.65; \u003cstrong\u003eFig.\u0026nbsp;3C\u003c/strong\u003e), with only 17% of explained variance attributable to dataset (\u003cstrong\u003eFig.\u0026nbsp;S5\u0026nbsp;A,B)\u003c/strong\u003e. Moreover, 63% of the 156 identified genera were shared between runs (\u003cstrong\u003eFig. 3D),\u0026nbsp;\u003c/strong\u003ewith nearly all abundant taxa (\u0026gt;0.5%) present in both, and few unique genera exceptionally rare: 16 in RS1 and 38 in RS2 (\u003cstrong\u003eTable S7\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsequently, the RS mycobiome (integrating both runs) comprises 620 fungal OTUs (\u003cstrong\u003eTable\u0026nbsp;S8\u003c/strong\u003e). Alpha-diversity metrics showed high fungal richness and relatively stable community structure, but also remarkable taxonomic uncertainty (\u003cstrong\u003eTable\u0026nbsp;S5 and S6\u003c/strong\u003e). The mean observed richness was 322\u0026nbsp;OTUs (IQR:\u0026nbsp;36), with the Chao1 estimator indicating a potentially higher richness (mean: 476, IQR:\u0026nbsp;93), suggestive of presence of undetected taxa. Shannon diversity (mean:\u0026nbsp;3.1, IQR:\u0026nbsp;0.07), Simpson index (mean:\u0026nbsp;0.9, IQR:\u0026nbsp;0.007), and evenness (mean:\u0026nbsp;104, IQR:\u0026nbsp;10) all displayed narrow interquartile ranges, underscoring low dominance effects and balance composition structure across replicates (\u003cstrong\u003eTable\u0026nbsp;S5\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe RS mycobiome spans 6 phyla, 26 classes, 64 orders, 107 families, and 154 unique genera (\u003cstrong\u003eTable\u0026nbsp;S8\u003c/strong\u003e), dominated by Ascomycota (65.5%) and Basidiomycota (26.2%). Minor phyla (Mortierellomycota, Chytridiomycota, and Mucoromycota) were present at negligible abundances (\u0026lt;0.01%; \u003cstrong\u003eTable\u0026nbsp;S8, Fig.4A\u003c/strong\u003e). About 9.4% of OTUs could not be classified beyond Kingdom (\u0026ldquo;no hit\u0026rdquo; reads). Taxonomic uncertainty was also substantial at lower ranks: 3.9% of OTUs at phylum level, and up to 30.8% and 56.6% were assigned to \u003cem\u003eincertae sedis\u003c/em\u003e at genus and species, respectively. This indicates that the resin\u0026rsquo;s selective environment may be shaping an uncharted \u0026ldquo;microbial dark matter\u0026rdquo; (Fig. 4B), consistent with UNITE classification of \u0026lsquo;dark taxa\u0026rsquo; in ITS-based species hypotheses [39,66]. Moreover, the structure of the community (\u003cstrong\u003eFig. S6\u003c/strong\u003e) was highly uneven with a small group of dominant taxa: 19 classified genera plus unclassified reads, Eurotiomycetes, Fungi, Basidiomycota, and Dothideomycetes \u003cem\u003eincertae sedis\u003c/em\u003e, accounted for 95.1% of abundance, with 131 genera contributing to the remaining 4.9%, each \u0026le;1%.\u0026nbsp;Key dominants included Eurotiomycetes gen.\u003cem\u003e\u0026nbsp;incertae sedis\u003c/em\u003e (26.2%), \u003cem\u003eSporobolomyces\u003c/em\u003e (12.3%), \u003cem\u003eSorocybe\u003c/em\u003e (7.1%), \u003cem\u003ePenicillium\u003c/em\u003e (5.6%), along several other genera at intermediate abundances (0.5\u0026ndash;5%; Table S9).\u003c/p\u003e\n\u003cp\u003eMany of the genera detected in RS mycobiome represent ecological specialists (Table\u0026nbsp;S9), including resinicolous taxa, both as dominants (\u003cem\u003eSorocybe\u003c/em\u003e (best-hit \u003cem\u003eS.\u0026nbsp;resinae\u003c/em\u003e)\u003cem\u003e\u0026nbsp;Sarea\u003c/em\u003e, \u003cem\u003eLophium\u003c/em\u003e and \u003cem\u003eMytilinidion\u0026nbsp;\u003c/em\u003e[67]) and at low-abundance (\u003cem\u003eChaenothecopsis\u003c/em\u003e [67]), and taxa associated with conifer hosts (\u003cem\u003eColacogloea\u003c/em\u003e, \u003cem\u003eSymbiotaphrina\u003c/em\u003e, \u003cem\u003eInfundichalara\u003c/em\u003e, \u003cem\u003ePhialocephala\u003c/em\u003e, \u003cem\u003ePragmopora\u003c/em\u003e [68-71]). \u003cem\u003ePenicillium\u003c/em\u003e and \u003cem\u003eAspergillus\u003c/em\u003e spp. build the dominant group of generalists, consistent with their frequent isolation from hydrocarbon-rich environments (e.g. \u003cem\u003eA. tubingensis and A. niger, Penicillium chrysogenum\u003c/em\u003e [14,72]) and ability to transform plant terpenes (e.g. \u003cem\u003eP.\u0026nbsp;digitatum\u003c/em\u003e [73] and \u003cem\u003eA. niger\u0026nbsp;\u003c/em\u003e [74]). In addition, RS is rich in multiple specialist taxa repeatedly reported from extreme and/or petroleum-rich environments: \u003cem\u003eCandida\u0026nbsp;keroseneae\u003c/em\u003e (originally described from aviation fuel) [75], \u003cem\u003eDebaryomyces\u0026nbsp;hansenii\u003c/em\u003e, \u003cem\u003eExophiala\u003c/em\u003e spp. (black yeasts), \u003cem\u003eRhodotorula\u003c/em\u003e (including \u003cem\u003eR.\u0026nbsp;mucilaginosa\u003c/em\u003e) [18,76] and \u003cem\u003eScedosporium\u0026nbsp;\u003c/em\u003e[14,77]. Within low-abundant taxa it is noted the presence of \u003cem\u003eAmorphotheca\u0026nbsp;resinae\u003c/em\u003e (= \u003cem\u003eHormoconis\u0026nbsp;resinae\u003c/em\u003e), known to utilize fuel components [11,78], \u003cem\u003eRhinocladiella\u003c/em\u003e, \u003cem\u003eCladosporium\u003c/em\u003e, \u003cem\u003eAureobasidium\u003c/em\u003e and \u003cem\u003eAlternaria\u003c/em\u003e, frequently documented as hydrocarbon-tolerant/degraders [14], and \u003cem\u003eNeodevriesia\u003c/em\u003e s.l., \u003cem\u003eDevriesia\u003c/em\u003e, and related Neodevriesiaceae lineages, usually found to colonize nutrient-poor, xeric and chemically stressful surfaces [79]. Collectively, the RS mycobiome display both high taxonomic diversity and uncertainty, ecological uniqueness, and potential novelty, highlighting strong selection for specialized, stress-adapted, and potentially metabolically versatile fungal lineages.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHigh taxonomic turnover and distinctiveness between resinous and nearby forest soils\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe compared the RS mycobiome to an adjacent FS mycobiome, testing if resin selectivity extends to broader local patterns (\u003cstrong\u003eTable\u0026nbsp;S10\u003c/strong\u003e). FS showed slightly higher richness (352\u0026nbsp;OTUs vs 281 OTUs in RS) but nearly identical Shannon diversity values (3.03 in RS, 3.02 in FS), and marginally lower Simpson\u0026rsquo;s indices, indicating more pronounced dominance structure in FS (\u003cstrong\u003eTable S11\u003c/strong\u003e). Despite these observable differences, Wilcoxon rank-sum tests yield no statistical \u003cem\u003ep\u003c/em\u003e-values (\u0026gt;0.05), likely constrained by small sample sizes. Nonetheless, non-parametric effect size (estimated via Cliff\u0026rsquo;s delta) indicated large biological relevant effect for richness (\u0026delta; = 1.00) and Simpson\u0026rsquo;s evenness (1\u0026ndash;D; \u0026delta; = \u0026ndash;0.67), whereas Shannon diversity effect size was negligible (\u0026delta; = 0.00).\u003c/p\u003e\n\u003cp\u003e\u0026beta;eta-diversity analyses (Whittaker\u0026rsquo;s \u0026beta;, \u0026beta;\u003csub\u003eW\u003c/sub\u003e; Bray-Curtis dissimilarity, D\u003csub\u003eBC\u003c/sub\u003e) quantified this contrast: richness-based turnover was higher among RS (1.95) than FS (1.41) replicates, reflecting greater internal heterogeneity in RS, while abundance-weighted dissimilarity between environments was extreme (D\u003csub\u003eBC\u003c/sub\u003e = 0.968; \u003cstrong\u003eTable\u0026nbsp;S12\u003c/strong\u003e). Consistently, genus-level composition mirrored this separation. FS was dominated by \u003cem\u003ePenicillium\u0026nbsp;\u003c/em\u003e(54.2%), Sordariales gen. \u003cem\u003eincertae sedis\u0026nbsp;\u003c/em\u003e(6.4%), and \u003cem\u003ePhialocephala\u0026nbsp;\u003c/em\u003e(5.6%) (all common soil genera), while RS had Eurotiomycetes gen. \u003cem\u003eincertae sedis\u003c/em\u003e (26.4%), \u003cem\u003eSporobolomyces\u003c/em\u003e (12.1%), and \u003cem\u003eSorocybe\u003c/em\u003e (7.7%) as dominant (the last two exclusives to RS), sustaining habitat-specific selection (\u003cstrong\u003eFig.5A-B\u003c/strong\u003e). Together, dominant genera comprised 94.4% and 91.9% of the RS and FS communities, respectively. Taxonomic overlap of classified genera was limited: of 359 genera, only 60 (17%) were shared between soils, whereas 204 (57%) were unique to FS, and 95 (26%) to RS, with several clades strongly enriched or depleted in either soil (\u003cstrong\u003eFig. 5B-C)\u003c/strong\u003e. Each community is composed by a few dominant taxa plus a large pool of low-abundance taxa, supporting both richness/ high turnover and distinct ecological structuring.\u003c/p\u003e\n\u003cp\u003eThe RS mycobiome compositions retrieved from either the clustering of RS reads alone, or RS and FS reads combined, are virtually identical, except that in the last five new OTUs could be assigned in RS and the number of unclassified OTUs slightly decreased (\u003cstrong\u003eTable\u0026nbsp;S10\u003c/strong\u003e). This reflects how UPARSE defines centroids when clustering pooled data and do not represent biological differences [37]. When running the taxonomic assignment against NCBI nt database (BLASTn; e-value 0.05) instead of UNITE, the number of unclassified OTUs also reduced slightly (\u003cstrong\u003eTable S13\u003c/strong\u003e) [39-41]. Systematically unclassified OTUs (e.g. OTU20) likely index true novelty.\u003c/p\u003e\n\u003cp\u003eOverall, RS and FS, though similar in gross \u0026alpha;-diversity, diverge strongly in community structure and in the prevalence of poorly classified or novel fungal lineages. Similar patterns have been reported in other chronically polluted substrates, indicating that richness can coexist with relatively even abundance structures due to the replacement of sensitive dominants by stress-tolerant specialists [77,80]. Minimal genus-level overlap, divergent taxonomic profiles and higher proportions of unclassified and \u003cem\u003eincertae sedis\u003c/em\u003e OTUs in RS, support the notion of habitat-driven differentiation shaped by selective pressures in resin-rich soils.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunctional characterization of the resinous soil mycobiome\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTrait profiling at the genus level using FungalTraits (\u003cstrong\u003eTable\u0026nbsp;S14-S16\u003c/strong\u003e) and FunFun (\u003cstrong\u003eTable\u0026nbsp;S17\u003c/strong\u003e) databases [54-56] revealed major functional differences between RS and FS mycobiomes. Substrate preference (\u003cstrong\u003eTable S16\u003c/strong\u003e) showed the highest Bray\u0026ndash;Curtis dissimilarity between mycobiomes (\u0026asymp;55), followed by growth form (\u0026asymp;53), lifestyle composition (\u0026asymp;51), and plant association (\u0026asymp;31), while decay type showed lower divergence (\u0026asymp;26). Annotation completeness varied across traits, with RS harbouring a substantially higher proportion of poorly characterized genera compared to FS. The RS mycobiome exhibited minimal plant-association coverage (17.4%) with sharp reduction of host-linked interactions, mostly putative foliar endophytes (8.3%; \u003cem\u003ePenicillium\u003c/em\u003e, \u003cem\u003eRhodotorula\u003c/em\u003e, \u003cem\u003eAspergillus\u003c/em\u003e) and others lacking endophytic capacity (5.4%, dominated by \u003cem\u003eColacogloea\u003c/em\u003e). RS lifestyle composition was enriched in saprotrophic guilds (mostly Sporobolomyces, 12.3%, \u003cem\u003eColacogloea\u003c/em\u003e, 4.6%, and \u003cem\u003eSorocybe\u003c/em\u003e, 7.1%) and antagonistic guilds (mostly mycoparasites, 14.7%), along with substrate preferences for fungal-derived substrates (17.2%), sugar-rich resources (8.6%) and resin-associated substrates (7.1%, exclusively detected in RS). In contrast, FS was strongly dominated by soil-associated substrates (59.0% vs 6.4% in RS) and plant-associated guilds, with foliar endophytes comprising nearly 28% of total abundance (mostly \u003cem\u003ePenicillium\u003c/em\u003e), besides ectomycorrhizal taxa (4.3%), soil saprotrophs (9.0%), and root endophytes (3.8%). These patterns indicate that RS mycobiome exhibits saprotrophic independence and specialization on resin-derived substrates and fungal resources over plant-linked symbiotic roles.\u003c/p\u003e\n\u003cp\u003ePredictive functional pathway analyses revealed substantial divergence between the two mycobiomes (\u003cstrong\u003eTable\u0026nbsp;S17\u003c/strong\u003e). The RS mycobiome showed significant enrichment in surface adherence and biofilm formation pathways, including extracellular matrix (ECM) interaction and synthesis: cell adhesion molecules (ko04514), ECM-receptor interaction (ko04512), glycosphingolipids biosynthesis (ko00601), and glycosaminoglycans metabolism (ko00532, ko00534, ko00535) (\u003cstrong\u003eFig. 6A\u003c/strong\u003e). These traits are consistent with RS conditions, promoting biofilm-like growth and spatial stability on hydrophobic, low-moisture substrates [11]. By contrast, FS communities exhibited enrichment in niche competition categories: secondary metabolites production (ko00902, ko00997, ko01059), peptidoglycan degradation proteins (ko01011), and metabolism of amino acid precursors (ko00471, ko00473), involving L/D-alanine and D-glutamic acid (\u003cstrong\u003eFig. 6A\u003c/strong\u003e). These traits are advantageous in nutrient-variable forest soils with intense microbial competition [81]. FS also retained brown-rot, chitinolytic, and keratinolytic decay profiles (all absent in RS), reflecting broader degradative versatility for forest litter processing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGlobal context: Biogeography of the resinous soil mycobiome\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo contextualize the ecological uniqueness of RS, its mycobiome (alongside that of the neighbouring FS) was compared to reference datasets from the Global Soil Mycobiome consortium (GSMc) [47]. RS and FS were placed within the spectrum of terrestrial biomes across European and Mediterranean regions, classified as anthropogenic and forest biomes, respectively. Comparison of Shannon diversity values across GSMc biome categories revealed similar medians, ranging from 5.48 in woodland to 5.26 in forest/shrubland (\u003cstrong\u003eFig. 6B; Table S18\u003c/strong\u003e). Considering only RS and FS classified OTUs (which greatly reduces their dissimilarity), both exhibited much lower Shannon values (3.06 and 3.11, respectively), placing them at the lower boundary of their biome categories and among the least diverse soils in the analysed regions with values ranging from 5.26 (subtropical broadleaf forest in Madeira, Portugal) to 6.19 (forest in Sicily, Italy). This result underscores the local divergence of RS and FS from regional diversity patterns, highlighting how chronic chemical stress and anthropogenic history can produce island-like fungal assemblages even within similar climatic zones [82,83]. Principal Coordinates Analysis (PCoA, based on Bray\u0026ndash;Curtis dissimilarity) clustered RS and FS closely together, near the periphery of the Southern European cloud, suggesting partial compositional similarity to these soils, with no strong affiliation to a single regional or biome cluster (\u003cstrong\u003eFig. S7A-B\u003c/strong\u003e). Analysis of the 25 most abundant fungal orders across European samples further illustrated their distinctiveness (\u003cstrong\u003eFig. 6C\u003c/strong\u003e). RS and FS displayed reduced overall fungal abundance compared to other Portuguese and Spanish soils, and were compositionally divergent. Most reference Portuguese soils were dominated by Basidiomycota, especially Agaricales [12,84]. Contrarily, both RS and FS are dominated by Ascomycota (RS: Chaetothyriales, Saccharomycetales, Eurotiales;\u0026nbsp;FS: Eurotiales, Helotiales, Sordariales), besides that fungal orders usually common in regional soils (Mortierellomycota, Zoopagomycota, and Mucoromycota) are either at low abundance or absent. Collectively, despite that the analysis is narrowed to classified OTUs, data suggest that the RS mycobiome (and to a lesser extent also that of FS) is compositionally and functionally distinct compared to geographically or climatically similar soils.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEcological context of RS mycobiome composition\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAlthough bacteria are well-established agents of diterpenoid metabolism [24], our findings underscore the significant, yet underappreciated, role of fungi in resin degradation under extreme conditions. Whereas fungi typically do not dominate in transient, resin-amended environments [24], the RS mycobiome supports their persistence and potential functional relevance. Microcosm experiments suggested that the RS mycobiota is actively involved in resin-acid turnover: under antibiotic suppression of bacteria, \u0026gt;50% of AA was lost in 30 days, confirming viable fungal terpenoid degradation capacity (\u003cstrong\u003eFig. S4\u003c/strong\u003e). Comparative analysis with mycobiomes from resin-rich conifer tissues (pollen, needles, bark, galls) [24,85-87] reveals that typical core classes in those environments: Dothideomycetes, Tremellomycetes, Mortierellomycota, and Mucoromycota, are only detected in RS at vestigial levels (e.g. Dothideomycetes 3.9%, Tremellomycetes 0.3%). In sharp contrast, Eurotiomycetes are strongly enriched (\u003cstrong\u003eFig.\u0026nbsp;4B-C, Table\u0026nbsp;S8\u003c/strong\u003e), consistent with previous reports on spruce-derived resin enrichments, and resinicolous surveys [24,87]. Experimental enrichment studies confirmed that resin compounds act as long-term selective agents, rapidly filtering fungal and bacterial populations [24]. Early-stage Ascomycota (e.g. \u003cem\u003eA. terreus\u003c/em\u003e, \u003cem\u003eA. flavus\u003c/em\u003e, \u003cem\u003eP. \u0026nbsp;decumbens\u003c/em\u003e) are only transient community members and are found in RS solely as rare traces (\u0026le;0.03%). With the persistence of resin, only extremotolerant Eurotiomycetes and Microbotryomycetes (red yeasts) [12], remain abundant, forming stable, stress-adapted consortia distinct from opportunistic colonizers.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDominant genera from pollen and needles: \u003cem\u003eEpicoccum\u003c/em\u003e, \u003cem\u003eVishniacozyma\u003c/em\u003e, \u003cem\u003eAlternaria\u003c/em\u003e, \u003cem\u003eAureobasidium\u003c/em\u003e, and \u003cem\u003eCladosporium\u003c/em\u003e, occur in RS at very low abundance, suggesting limited recruitment from above-ground conifer sources, and further supporting the uniqueness of chemical filtering in RS [85,86]. Satellite taxa reported in association with \u003cem\u003eP. pinaster\u003c/em\u003e needles, such as \u003cem\u003eMortierella clonocystis\u003c/em\u003e, \u003cem\u003eCryptococcus podzolicus\u003c/em\u003e, \u003cem\u003eAspergillus piperis\u003c/em\u003e, and \u003cem\u003eMetschnikowia\u0026nbsp;\u003c/em\u003esp. [85], are largely absent in RS (\u0026lt;0.01%, except \u003cem\u003eAspergillus\u003c/em\u003e at 0.65\u0026ndash;1.06%). This pattern suggest that the RS assemblage arises through soil-chemical selection, consistent with soils under pine plantations favouring Ascomycota (especially Trichocomaceae: \u003cem\u003eAspergillus\u003c/em\u003e, \u003cem\u003eTalaromyces\u003c/em\u003e, \u003cem\u003ePenicillium\u003c/em\u003e) over Basidiomycota prevalent in undisturbed forest soils [84].\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe described resinous soil mycobiome is radically distinct from forest soil and microbial communities associated with natural conifer tissues, indicating that chronic resin saturation from long-term anthropogenic activity acts as an intense ecological filter. RS is dominated by resin acids (\u0026le;15% of soil mass), recalcitrant markers of conifer resin [31], representing an anthropogenically amplified natural chemical stress. Combined with low water activity, extreme C:N imbalance (C/N\u0026gt;1600), and persistent toxicity, RS creates an extreme microhabitat filtering for functionally specialized fungal taxa. It parallels chronic heavily oil-polluted soils where hydrocarbon-degrading and/or stress-tolerant fungi dominate\u0026nbsp;[14,72]. These convergent selective pressures underscore the broader relevance of RS as a model for fungal adaptation to persistent chemical stress\u003cem\u003e.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOur findings elevate the significant yet frequently overlooked functional contribution of fungi under persistent resin pressure. Microcosm experiments confirmed fungal viability and active resin acid turnover, though the specific taxa driving these modifications remain unidentified. The RS mycobiome is defined by extremotolerant Eurotiomycetes (42.7%) and resilient yeasts from Microbotryomycetes, distinguishing it from conifer needle, pollen, and bark mycobiomes [85,86]. Moreover, early-stage colonizers of resin-rich substrates [24,87], \u0026nbsp;appear only at trace levels, highlighting a succession toward stress-adapted, substrate-specialized lineages. Classical resinicolous genera (e.g. \u003cem\u003eSorocybe\u003c/em\u003e, \u003cem\u003eSarea\u003c/em\u003e, and \u003cem\u003eChaenothecopsis\u003c/em\u003e (\u003cem\u003eMycocaliciales\u003c/em\u003e) [67]) and hydrocarbon-tolerant genera (e.g. \u003cem\u003eExophiala\u003c/em\u003e, and \u003cem\u003eDebaryomyces\u003c/em\u003e [18,76]), comprise the most dominant, functionally important groups. Conversely, canonically dominant aerial or foliar associates are rare, reflecting limited persistence of above-ground propagules [85,86,88]. The ecological uniqueness of RS relies on many low abundant taxa, yet some culturable strains (e.g. \u003cem\u003eAmorphotheca\u0026nbsp;\u003c/em\u003espp., 0.33%; \u003cem\u003eT. versicolor\u003c/em\u003e, 0.001%) remain viable under standard conditions (unpublished data).\u003c/p\u003e\n\u003cp\u003eBeyond known resinicolous and hydrocarbon-associated fungi, RS harbours a considerable fraction of unclassified or \u003cem\u003eincertae sedis\u003c/em\u003e OTUs (\u0026gt;30% at genus level, \u0026gt;56% at species level) [39,66], far exceeding ambiguity in forest soil or global soil datasets. This suggests resin-saturated habitats function as refugia for fungal \u0026ldquo;dark matter,\u0026rdquo; hosting novel lineages and metabolic functions, deserving deep analysis. The persistence of ancient resinicolous fungi like \u003cem\u003eSarea\u003c/em\u003e and \u003cem\u003eChaenothecopsis\u003c/em\u003e in Paleogene fossil records underscores the deep evolutionary continuity of resin-associated niches [67,89,90], while modern resinicolous fungi (e.g. \u003cem\u003eGanoderma adspersum\u003c/em\u003e) colonizing diverse polymeric matrices [91,92] extend the ecological significance of resin adaptation to anthropogenic substrates. This evolutionary breadth reflects the fundamental selective power of resin chemistry across natural and industrial timescales.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRS resin acid persistence mirrors chemical legacies encountered in pulp-mill effluents and industrial sites [20]. Thus, selecting for fungal consortia capable of modifying such stressors offers significant bioremediation potential. However, RS dominant taxa also included opportunists\u0026rsquo; pathogens (e.g. \u003cem\u003eExophiala\u003c/em\u003e, \u003cem\u003eAspergillus\u003c/em\u003e), highlighting a link between environmental extremotolerance and opportunistic pathogenicity [93,94] with implications relevant to One Health and Eco Health frameworks [95,96].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFar from being marginal, resinous soils highlight fungal potential to colonize, persist, and drive transformations in extreme ecosystems. These findings expand our view of natural product-shaped environments, proposing resin-rich habitats as \u0026ldquo;laboratories\u0026rdquo; for adaptive innovation with applications from pollutant attenuation to biocatalysts discovery. Future work integrating targeted cultivation with deep molecular analyses will further unravel, both the known and unknown, fungal diversity revealed here.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. Note that all samples \u0026ndash; fungal isolates - were provided anonymized. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRaw sequencing data generated in this study have been deposited in the NCBI Sequence Read Archive (SRA) under BioProject accession PRJNA1392999. All processed data supporting the findings of this study, including taxonomic tables, diversity metrics, and functional analyses, are provided in the Supplementary Information.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have made important contributions to the acquisition, analysis and interpretation of data and contributed to the drafting of the manuscript: CAMA (sampling); AP, AV (fungal experiments, analytics); PD, IM (technical support); AP, TM (bioinformatics); RE, AB (NMR analyses); AP (manuscript draft); CSP (conceptualization resources, supervision and final manuscript). All authors read and approved the final version of the manuscript. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge funding from the Funda\u0026ccedil;\u0026atilde;o para a Ci\u0026ecirc;ncia e Tecnologia (FCT) through the projects \u0026lsquo;FATE\u0026rsquo; (PTDC/CTA-AMB/6587/2020), FATE4FUTURE (n\u0026ordm; 2023.16924.ICDT), MOSTMICRO-ITQB Unit (UIDB/04612/2020 and UIDP/04612/2020) and LS4FUTURE Associated Laboratory (LA/P/0087/2020), and by Fundo Europeu de Desenvolvimento Regional (FEDER) under the project \u0026ldquo;BIOPINUS\u0026rdquo; (CENTRO-01-0247-FEDER-072630). \u0026Acirc;P and RE are grateful to FCT for the fellowships references SFRH/BD/144593/2019 (https://doi.org/10.54499/SFRH/BD/144593/2019), and 2021.06435.B (https://doi.org/10.54499/2021.06435.BD), respectively. TM is grateful for the working contract (2023.11076.TENURE.076) financed by national funds under the FCT-TENURE Programme.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe extend our gratitude to all members of the Silva Pereira lab for their valuable discussions, with special thanks to alumni researchers Celso Martins, Daryna Piontkivska and Stefano Nones\u003csup\u003e\u0026nbsp;\u003c/sup\u003efor their assistance in the initial data analyses. The authors are also grateful to the technical support provided by Maria Cristina Leit\u0026atilde;o (chromatography, ITQB NOVA), Carolina Feliciano (microscopy, BIC ITQB NOVA), Francisco Martins (Electric saw operator, INIAV), and Isabel Nogueira (SEM imaging, IST Microlab).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe NMR data were acquired at CERMAX, ITQB NOVA, Oeiras, Portugal, with equipment funded by Funda\u0026ccedil;\u0026atilde;o para a Ci\u0026ecirc;ncia e Tecnologia (FCT) and the microscopy imaging was performed in the BIC cluster at ITQB NOVA, which is supported by PPBI (Portuguese Platform of BioImaging), co-funded by national funds from OE (Or\u0026ccedil;amento de Estado) and by European funds from FEDER (Fundo Europeu de Desenvolvimento Regional, PPBI-POCI-01-0145-FEDER-022122).\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eTedersoo L, Bahram M, P\u0026otilde;lme S\u003cem\u003e, et al\u003c/em\u003e. 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Jul 2024;631(8022):835-842. doi:10.1038/s41586-024-07658-9\u003c/li\u003e\n\u003cli\u003eTuovila H, Schmidt AR, Beimforde C, D\u0026ouml;rfelt H, Grabenhorst H, Rikkinen J. Stuck in time \u0026ndash; a new Chaenothecopsis species with proliferating ascomata from Cunninghamia resin and its fossil ancestors in European amber. \u003cem\u003eFungal Diversity\u003c/em\u003e. 2012;58(1):199-213. doi:10.1007/s13225-012-0210-9\u003c/li\u003e\n\u003cli\u003eRikkinen J, Poinar G. A new species of resinicolous Chaenothecopsis (Mycocaliciaceae, Ascomycota) from 20 million year old Bitterfeld amber, with remarks on the biology of resinicolous fungi. \u003cem\u003eMycological Research\u003c/em\u003e. 2000;104(1):7-15. doi:10.1017/s0953756299001884\u003c/li\u003e\n\u003cli\u003ePardi-Comensoli L, Tonolla M, Colpo A\u003cem\u003e, et al\u003c/em\u003e. Microbial Depolymerization of Epoxy Resins: A Novel Approach to a Complex Challenge. \u003cem\u003eApplied Sciences\u003c/em\u003e. 2022;12(1)doi:10.3390/app12010466\u003c/li\u003e\n\u003cli\u003eNajam M, Javaid S, Iram S\u003cem\u003e, et al\u003c/em\u003e. Microbial Biodegradation of Synthetic Polyethylene and Polyurethane Polymers by Pedospheric Microbes: Towards Sustainable Environmental Management. \u003cem\u003ePolymers (Basel)\u003c/em\u003e. Jan 11 2025;17(2)doi:10.3390/polym17020169\u003c/li\u003e\n\u003cli\u003eSiscar-Lewin S, Hube B, Brunke S. Emergence and evolution of virulence in human pathogenic fungi. \u003cem\u003eTrends Microbiol\u003c/em\u003e. Jul 2022;30(7):693-704. doi:10.1016/j.tim.2021.12.013\u003c/li\u003e\n\u003cli\u003eCasadevall A, Pirofski LA. Accidental virulence, cryptic pathogenesis, martians, lost hosts, and the pathogenicity of environmental microbes. \u003cem\u003eEukaryot Cell\u003c/em\u003e. Dec 2007;6(12):2169-2174. doi:10.1128/ec.00308-07\u003c/li\u003e\n\u003cli\u003eOne Health High-Level Expert P, Adisasmito WB, Almuhairi S\u003cem\u003e, et al\u003c/em\u003e. One Health: A new definition for a sustainable and healthy future. \u003cem\u003ePLOS Pathogens\u003c/em\u003e. 2022;18(6):e1010537. doi:10.1371/journal.ppat.1010537\u003c/li\u003e\n\u003cli\u003eHarrison S, Kivuti-Bitok L, Macmillan A, Priest P. EcoHealth and One Health: A theory-focused review in response to calls for convergence. \u003cem\u003eEnvironment International\u003c/em\u003e. 2019/11/01/ 2019;132:105058. doi:https://doi.org/10.1016/j.envint.2019.105058\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Parametric \u003cem\u003et\u003c/em\u003e-test results for alpha diversity metrics in resinous soil datasets RS1 and RS2.\u0026nbsp;\u003c/strong\u003eMetrics tested include richness, Shannon and Simpson diversity, Chao1 richness estimator, and evenness.\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"576\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 133px;\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003eMetric\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eRS1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eRS2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e-statistic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 139px;\"\u003e\n \u003cp\u003e95% Confidence Interval\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003eRichness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e201.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e260.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e-2.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e-131.36,\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e14.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003eShannon*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e2.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e3.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e-3.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e-0.35,\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003eSimpson\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e-2.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e-0.03,\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.0007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003eInverse Simpson*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e9.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e11.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e-2.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e-2.92,\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e-0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003eChao1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e313.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e375.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e-1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e-213.88,\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e89.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003eEvenness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e67.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e81.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 82px;\"\u003e\n \u003cp\u003e-1.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e-37.41,\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e9.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e(*) Values marked with an asterisk denote significant differences (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05).\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Fungal metacommunity, High-throughput sequencing, Resin microbial ecology, Extremophilic fungi, Hydrocarbon-associated taxa","lastPublishedDoi":"10.21203/rs.3.rs-8530099/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8530099/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e:\u003c/em\u003e\u003cstrong\u003e \u003c/strong\u003eFilamentous fungi are ubiquitous and constitute more than 75% of the soil biomass. Fungal diversity increasingly emerges as a key factor in soil ecosystem resilience against climate change and pollution, yet much of this diversity remains hidden and potentially in decline. While investigations have primarily focused on fungal tolerance to extreme physical conditions, such as temperature and salinity, chemically stressed environments remain underexplored reservoirs of novel fungal diversity. These habitats may harbour strains with significant biotechnological potential. This study tested the hypothesis that long-term contamination of soil with \u003cem\u003ePinus\u003c/em\u003e resin alters fungal diversity and promotes the emergence of specialized fungal lineages enriched in hydrocarbon-degrading capabilities.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e:\u003c/em\u003e We analysed a resinous soil sample collected from an inactive resin processing site undisturbed for nearly 50 years. Initial physicochemical and microscopy analyses confirmed the presence of viable fungi despite extreme environmental constraints. High-throughput sequencing of fungal ITS2 regions revealed a fungal community composition highly distinct from adjacent forest soil, characterized by unusual taxonomic profiles and a high proportion of poorly classified or novel lineages. Functional inference and taxonomic analyses identified hydrocarbon-associated taxa including \u003cem\u003eSorocybe resinae\u003c/em\u003e (one of the most abundant OTUs) and \u003cem\u003eAmorphotheca resinae\u003c/em\u003e (detected at low abundance).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e:\u003c/em\u003e The identified fungi are known resinicolous and extremophilic species, illustrating the unique ecological adaptation of fungi within resin-rich, chemically stressful soils.\u003c/p\u003e","manuscriptTitle":"Extremotolerant Fungi in Resinous Soils: A Unique Diversity of Generalist and Specialized Hydrocarbon Degraders","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-10 12:11:39","doi":"10.21203/rs.3.rs-8530099/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2e5c54e7-dba2-4064-adac-015178023e5c","owner":[],"postedDate":"February 10th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-05T02:53:14+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-10 12:11:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8530099","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8530099","identity":"rs-8530099","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}