S Mieszkin
email: sophie.mieszkin@univ-brest.fr

P Richet

C Bach

C Lambrot

L Augusto

M Buée

S Uroz

Oak decaying wood harbors taxonomically and functionally different bacterial communities in sapwood and heartwood

Keywords: Oak decaying wood, bacteria, sapwood, heartwood, functional and metabolic potential, taxonomic diversity

Wood decay is an important process in forest ecosystems, which relies on wood chemical properties and the action of a complex community of decomposers. While the important role of fungi in this process is recognized, our knowledge concerning the colonization of decaying wood by bacteria, their relative distribution as well as their potential functional roles remain under-investigated. In this context, our aim was to characterize how the bacterial communities are structured at both taxonomic and functional levels along the soil-wood continuum, using oak discs positioned on the forest floor for nine months. Using a combination of culture-dependent andindependent methods associated to a physical measure of wood decay, we evidenced that at the middle stage of decay investigated, the heartwood-and sapwood-inhabiting bacterial communities significantly differed from one another in term of richness and taxonomic composition, but also from those of the bulk soil. The functional screening revealed low metabolic potentials and a higher frequency of cellulose decomposing bacteria in wood than in the bulk soil, suggesting an adaptation of these communities to this habitat and to the physical-chemical conditions occurring in decaying wood. Together, our data evidence that the colonization of decaying wood by bacteria is based on a deterministic process linking extrinsic and intrinsic factors.

Introduction

Forest ecosystems, due to the large area they cover on earth (up to 31% of land area in 2015), provide major ecosystem services. One of the most important is their capacity to stock carbon (C) and to act as a C sink [START_REF] Pan | A large and persistent carbon sink in the world's forests[END_REF][START_REF] Seidl | Increasing forest disturbances in Europe and their impact on carbon storage[END_REF]. In addition, trees accumulate inorganic nutrients taken from the soil in their biomass. Even if a significant C fraction is directly transferred to the surrounding environment through belowground allocation and root exudation [START_REF] Litton | Effects of tree density and stand age on carbon allocation patterns in postfire lodgepole pine[END_REF][START_REF] Hobbie | Carbon allocation to ectomycorrhizal fungi correlates with belowground allocation in culture studies[END_REF], a major transfer comes from the seasonal litter deposition and after the death of trees or harvesting, during the wood decay. Consequently, decaying wood strongly impacts nutrient cycling and plays an important role in term of organic and inorganic nutrients recycling [START_REF] Augusto | Influences of evergreen gymnosperm and deciduous angiosperm tree species on the functioning of temperate and boreal forests[END_REF][START_REF] Ricker | Rapid wood decay and nutrient mineralization in an old-growth bottomland hardwood forest[END_REF]. In temperate regions, woody debris can be represented by logs, stumps or fine branches and can reach 2-65 m 3 ha -1 in managed forests where wood is harvested, while it can reach up to 1200 m 3 ha -1 in non-managed forests [START_REF] Hahn | Monitoring and Indicators of Forest Biodiversity in Europe -From Ideas to Operationality[END_REF][START_REF] Stokland | Biodiversity in Dead Wood[END_REF]. This material is a specific habitat for various organisms, such as insects and fungi, providing them an important source of cellulose, lignin and hemicellulose [START_REF] Stokland | Biodiversity in Dead Wood[END_REF][START_REF] Seibold | Experimental studies of dead-wood biodiversity-a review identifying global gaps in knowledge[END_REF][START_REF] Baldrian | Forest microbiome: diversity, complexity and dynamics[END_REF]. However, the nutrients entrapped in the wood structure are not directly accessible to the wood biota, due to the recalcitrance of wood to decomposition. Indeed, the high content of lignin and the low nutrient content (mainly nitrogen (N) and phosphorus (P)) are not favorable to microbial development [START_REF] Meerts | Mineral nutrient concentrations in sapwood and heartwood: a literature review[END_REF]. In addition, presence of toxic wood extractives and low pH conditions prevent wood microbial decomposition. All these parameters vary according to the wood species and the stage of decay, with some wood easily degradable (e.g. Acer sp. or Tilia sp.) and other more recalcitrant (i.e., Quercus sp. or Acacia sp.) [START_REF] Weedon | Global meta-analysis of wood decomposition rates: a role for trait variation among tree species?[END_REF][START_REF] Rajala | Fungal community dynamics in relation to substrate quality of decaying Norway spruce (Picea abies L. Karst.) logs in boreal forests[END_REF][START_REF] Augusto | Influences of evergreen gymnosperm and deciduous angiosperm tree species on the functioning of temperate and boreal forests[END_REF].

A large body of literature suggests that fungi but also insects are the main decomposers of decaying wood. Insects, due to their capability of altering wood structure by tunneling and fragmentation and of decomposing wood through enzymatic digestion, are important engineers of early stage decay [START_REF] Baldrian | Fungi associated with decomposing deadwood in a natural beech-dominated forest[END_REF][START_REF] Ulyshen | Wood decomposition as influenced by invertebrates[END_REF]. Fungi are well known for their ability to produce a large panel of extracellular lignocellulolityc enzymes to decompose the lignin and then the cellulose [START_REF] Schneider | Who is who in litter decomposition? Metaproteomics reveals major microbial players and their biogeochemical functions[END_REF][START_REF] Mathieu | Selection and validation of enzymatic activities as functional markers in wood biotechnology and fungal ecology[END_REF][START_REF] Baldrian | Fungi associated with decomposing deadwood in a natural beech-dominated forest[END_REF][START_REF] Noll | Fungal biomass and extracellular enzyme activities in coarse woody debris of 13 tree species in the early phase of decomposition[END_REF]. In comparison, less attention has been paid to wood-inhabiting bacteria, while they are known to colonize wood since the early steps of decomposition [START_REF] Clausen | Bacterial associations with decaying wood: a review[END_REF][START_REF] Blanchette | A review of microbial deterioration found in archaeological wood from different environments[END_REF][START_REF] Kielak | Bacterial community succession in pine-wood decomposition[END_REF]. Based on the analysis of the bacterial communities occurring at different stages of decomposition of pine-wood, [START_REF] Kielak | Bacterial community succession in pine-wood decomposition[END_REF] proposed that bacterial community assembly may be the result of a stochastic process at the initial stages of dead wood decomposition, and on the contrary determined by the wood properties at advanced stages. It was also reported that decaying bacteria communities could be diverse, potentially active at decomposing dead wood and capable of interacting with fungi [START_REF] Valášková | Phylogenetic composition and properties of bacteria coexisting with the fungus Hypholoma fasciculare in decaying wood[END_REF][START_REF] Hervé | Impact of Phanerochaete chrysosporium on the functional diversity of bacterial communities associated with decaying wood[END_REF][START_REF] Johnston | Bacteria in decomposing wood and their interactions with wood-decay fungi[END_REF][START_REF] Baldrian | Forest microbiome: diversity, complexity and dynamics[END_REF]. Among the different studies performed on these communities, a dominance of Proteobacteria, Actinobacteria, Bacteroidetes and Acidobacteria was reported, suggesting an adaptation to the wood environment [START_REF] Valášková | Phylogenetic composition and properties of bacteria coexisting with the fungus Hypholoma fasciculare in decaying wood[END_REF][START_REF] Hervé | Diversity and structure of bacterial communities associated with Phanerochaete chrysosporium during wood decay[END_REF][START_REF] Sun | Diversity and community structure of primary wood-inhabiting bacteria in boreal forest[END_REF][START_REF] Kielak | Bacterial community succession in pine-wood decomposition[END_REF][START_REF] Rinta-Kanto | Natural decay process affects the abundance and community structure of Bacteria and Archaea in Picea abies logs[END_REF]. Noticeably, some bacterial classes or even genera were shown to differ according to the tree species [START_REF] Prewitt | Fungal and bacterial community succession differs for three wood types during decay in a forest soil[END_REF][START_REF] Moll | Bacteria inhabiting deadwood of 13 tree species are heterogeneously distributed between sapwood and heartwood[END_REF] and/or the stage of decay [START_REF] Hoppe | A pyrosequencing insight into sprawling bacterial diversity and community dynamics in decaying deadwood logs of Fagus sylvatica and Picea abies[END_REF]. The potential structuring effect of the wood compartments (heartwood (HW), the dead inner part of wood; sapwood (SW), the living outermost part of wood) on the bacterial communities was also investigated, but such studies remain scarce [START_REF] Zhang | Unexpectedly high bacterial diversity in decaying wood of a conifer as revealed by a molecular method[END_REF][START_REF] Moll | Bacteria inhabiting deadwood of 13 tree species are heterogeneously distributed between sapwood and heartwood[END_REF]. However, most of these studies described the community composition, while the relative role of the bacterial communities in the decomposition of wood is still largely underexplored.

Most of the current knowledge on the ability of bacteria to decompose wood comes from the analysis of soil bacteria and on their capacities to hydrolyse cellulose [START_REF] Nicolitch | Tree roots select specific bacterial communities in the subsurface critical zone[END_REF], hemicelluloses [START_REF] Lee | Lysinibacillus xylanilyticus sp. nov., a xylan-degrading bacterium isolated from forest humus[END_REF]), lignin (Větrovsky ́ et al., 2014) or even pectin [START_REF] Clausen | Bacterial associations with decaying wood: a review[END_REF]. For instance, these functional abilities were found in culturable representatives of Acidobacteria (Silvibacterium bohemicum) [START_REF] Lladó | Functional screening of abundant bacteria from acidic forest soil indicates the metabolic potential of Acidobacteria subdivision 1 for polysaccharide decomposition[END_REF], of Actinobacteria (e.g. Streptomyces) [START_REF] Nicolitch | Soil type determines the distribution of nutrient mobilizing bacterial communities in the rhizosphere of beech trees[END_REF] or of Proteobacteria (e.g., Burkholderia) [START_REF] Hervé | Impact of Phanerochaete chrysosporium on the functional diversity of bacterial communities associated with decaying wood[END_REF]. Together, these results suggest that the soil may act as a reservoir of bacteria capable of adapting to woody debris and of participating to wood decomposition. Comparatively, few functional analyses have been done on bacteria directly collected in situ from decaying wood [START_REF] Murray | Temporal changes in functional diversity of culturable populations in Sitka spruce stumps[END_REF][START_REF] Valášková | Phylogenetic composition and properties of bacteria coexisting with the fungus Hypholoma fasciculare in decaying wood[END_REF][START_REF] Vorob'ev | Methylovirgula ligni gen. nov., sp. nov., an obligately acidophilic, facultatively methylotrophic bacterium with a highly divergent mxaF gene[END_REF].

Consequently, determining whether bacteria are functionally structured according to the stage of wood decay, the wood compartment or according to the tree species are questions of importance in microbial ecology. As bacteria are not considered as the main actors of wood decay in the early stages of decomposition, we investigated the taxonomic and functional distribution of the bacterial communities at middle stage of wood decay and across a soil-wood continuum. At this stage of decay, we hypothesized that i) the direct role and the structure of the bacterial communities vary according to the compartments (i.e., bulk soil (BS) versus HW versus SW), and ii) the two main wood compartments (HW and SW) select different bacterial communities according to their own properties (i.e., nutritive content, wood biopolymers). To test these hypotheses, we combined metabolic and functional bioassays, with a cultureindependent approach on oak wood samples incubated nine months on a forest floor.

Materials and Methods

Experimental site and sampling description

The present study was performed in the forest experimental site of Champenoux (north-eastern of France; Lat: 48.718°; Long: 6.347°; Alt: 248 m; 0.5 ha of surface).

The site is characterized as an oak forest aged of 110 years old where Quercus petraea (Q. petraea) and Carpinus betulus represent the dominant tree species, followed by some Fagus sylvatica and Quercus robur trees. The soil is classified as an acidic luvic cambisol (pH-H2O = 4.6 in the A1 horizon, 0-5 cm) and is characterized by a mull-type humus and a loamy texture. The site is flat with understory vegetation (i.e. oak and hornbeam seedlings, Convallaria majalis L.,

Deschampsia cespitosa L.).

At this site, four living oak trees of similar age (ca. 110 years old; 42 cm diameter), spatially distant from 5 to 20 m, were selected. Oak was selected, as it represents a major tree species in Europe and its coverage is expected to increase with changes in temperatures and precipitations due to climate change [START_REF] Hanewinkel | Climate change may cause severe loss in the economic value of European forest land[END_REF]. An area of 25 m 2 (∼5 m x ∼5 m) was delimited around each oak tree, and the litter was removed. Then, twenty oak discs were placed around each oak tree directly on the surface of the soil and spatially separated from one another by a distance of approximately 50 cm, giving a total of 80 wood discs. The wood discs came from a sessile oak tree (Q. petraea) aged of approximately 48 years and cut off in January 2015 from a neighboring forest plot and then stored and air-dried in the laboratory protected from light and moisture for six months. Their average diameter without the bark was 14.5 cm and their average thickness 2 cm. They were placed directly in contact with the soil and incubated nine months in natural conditions to enable wood decomposition (Fig. SI-1).

After a nine months incubation period, sampling was performed (April 2016) to focus on the middle stage of wood decay and on the associated bacterial communities. For each tree area and each oak disc, SW and HW as well as the soil (BS) in contact with the wood discs were sampled. SW and HW samples were recovered by drilling using a sterilized 10-mm drill bit. For each tree area, the sawdust of the twenty oak discs was recovered from the two wood compartments (HW and SW). The samples were then pooled to obtain four composite HW sawdust samples (n=20 per composite samples) and four composite SW sawdust samples (n=20 per composite samples). To compare the wood-inhabiting bacterial community structures and functions, with those of the adjacent soil, 5 g of BS samples underlying each wood-decaying disc (5 cm depth corresponding to the A1 horizon) were sampled. The BS samples were then pooled for each tree area, leading to four composite BS samples (n=20 per composite samples). Each sample was stored in sterile containers and once at the laboratory directly analyzed.

Soil chemical analyses

For each replicate tree area, the chemical properties of the four BS samples have been determined. Total N and C contents, both obtained after combustion at 1000°C, and P content, were determined according to methods published by [START_REF] Olsen | Estimation of available phosphorus. In soils by extraction with sodium bicarbonate[END_REF], Duchaufour and Bonneau, (1959) [START_REF] Duval | Etude des conditions de validité du dosage céruléomolybdique de l'acide phosphorique[END_REF]. The cation exchange capacity (CEC) was determined according to the cobalti-hexamine method, which is based on the titration of the cobalti-hexamine chloride soil extract. Exchangeable cations (Ca, Mg, Na, K, Fe, Mn and Al) and protons were extracted using cobaltihexamine and determined by inductively coupled plasma spectrometry-atomic emission spectrometry (ICP-AES) for cations and by potentiometric measurement using 0.05 M KOH for protons. The pH was determined by the water method using a soil/water ratio of 1:5 (w/v).

Wood decaying stage and chemical analyses

The variation of density of the SW and HW was assessed during the wood decay directly on specific oak discs incubated on the experimental site. For each replicate tree area, one oak disk at T0 and five oak disks at T3, T6 and T9 months were considered. A Pilodyn penetrometer with a 3 mm pin was used to measure penetration depth (i.e., the density) (Mäkipää and Linkosalo, 2011;[START_REF] Fundova | Non-destructive wood density assessment of Scots pine (Pinus sylvestris L.) using Resistograph and Pilodyn[END_REF]. For each sampling time and oak disc, three measures were performed for both the SW and HW samples. Results were expressed as a mean percentage of penetration depth for each wood compartment at each time point.

For each tree area and each wood compartment, the chemical properties of the samples have been determined (four SW and four HW sawdust samples). All the samples were dried at 65°C during 72h, homogenized and then sub-sampled for the different analyses described in the supplementary section. Briefly, C and N were analyzed through total combustion. Nutrients (i.e., P, K, Ca, and Mg) were analyzed after wet mineralisation. Quantification of the cellulose was obtained by successive separations with different solvents using a Soxhlet extractor. Quantification of the lignin content in the wood samples was performed with the Klason method. Finally, the pH was determined for each sample.

Collection of bacterial strains

For each sample (four BS, four SW and four HW), 1 g of sawdust (SW or HW) or BS was added to 20 mL of sterile distilled water and vortexed three times during 90 s. After a serial dilution in sterile distilled water, a volume of 0.1 mL from the dilutions 10 -2 to 10 -5 , was then spread in triplicate onto 1/10 diluted Tryptic Soy Agar (TSA) medium (Triptic Soy Broth (TSB) from Difco, 3 g.L -1 and agar 15 g.L -1 ) containing cycloheximide (100 µg.L -1 , final concentration). The pH of the medium was adjusted at 5 to fit with the pH found in oak sawdust and soil. All plates were then incubated at 25°C for 5 days. After incubation, the number of colony-forming units (CFU).g -1 from sawdust or soil samples was determined using the appropriate dilutions (10 -3 and 10 - 4 according to the sample considered) permitting to quantify the densities of culturable bacteria in each compartment. For each compartment (BS, HW and SW) and replicate, and considering the dilution giving a total of 30 colonies per Petri dish, all the bacterial colonies were recovered. Bacterial isolates were then purified by three successive platings on 1/10 diluted TSA at pH 5 to obtain pure cultures. All the bacterial isolates were cryopreserved at -80°C in 35% glycerol. The bacterial collection was composed of 308 bacterial isolates that were distributed as follow: 117 BS isolates, 107 SW isolates and 84 HW isolates.

Metabolic and functional bioassays performed on bacterial isolates

The metabolic potential of each bacterial isolate was determined using Biolog microplates, which contain ninety-five different C sources. The GN2 microplates were selected in our study because they contain relevant substrates related to wood derivatives (ie, cellulose) or fungal metabolites (trehalose). The screening was performed according to the manufacturer's instruction. After 48 h incubation at 25°C, the absorbance was measured at 595 nm using an iMark microplate reader (Bio-Rad, USA) (see supplementary section for detailed information).

The capacity of each bacterial isolate to degrade organic matter and specific compounds found in wood (cellulose, lignin, xylan and chitin) as well as their ability to recover iron through the production of siderophores was evaluated. Five different bioassays allowing to measure: i) their cellulolytic ability (carboxy-methyl-cellulose (CMC) assay), ii) their lignolytic ability (Remazol brillant blue R (RBBR) assay), iii) their xylanolytic ability (xylan assay); iv) their chitinolytic ability (chitin assay) and v) their ability to mobilise iron (the CAS (chromoazurol-S assay), were used. Each bioassay is based on a gelosed medium allowing the measure of a discoloration halo. When compatible with the bioassay, the pH of the medium was adjusted to 5 to stay close to the pH of the wood and the soil. Composition of each medium and the experimental procedure are fully described in the supplementary section.

Molecular identification of bacterial strains and phylogenetic analyses

A fragment of the 16S rRNA gene was amplified using the universal set of primers pA and 907r [START_REF] Edwards | Isolation and direct complete nucleotide determination of entire genes. Characterization of a gene coding for 16S ribosomal RNA[END_REF][START_REF] Lane | Nucleic acid techniques in bacterial systematics[END_REF]. The polymerase chain reaction (PCR) was performed in a total reaction volume of 50 μL containing 20 μL of master mix (PCR Taq PCR Master Mix, Qiagen), 2 μL of each primer (10 μM) and 2 μL of bacterial cells inoculum. PCR conditions were the following: 94°C for 4 min, then 30 cycles of 30 s denaturation at 94°C, 60 s annealing at 53°C, 90 s extension at 72°C, and a final extension step of 10 min at 72°C. PCR products were then purified using the QIAquick PCR purification kit (Qiagen) and concentration determined using a Nanodrop-1000 spectrometer (NanoDrop Technologies, Wilmington, DE, USA). The Sanger sequencing reactions were performed by MWG Eurofin Operon (Ebersberg, Germany) using the primer 907r. All the sequences were identified using the nucleotide BLAST program [START_REF] Altschul | Evaluating the statistical significance of multiple distinct local alignments[END_REF]. Sequence alignment and distance tree were constructed using SeaView (version 4.7) [START_REF] Gouy | SeaView version 4: a multiplatform graphical user interface for sequence alignment and phylogenetic tree building[END_REF] and by using neighbor-joining algorithms with the Kimura two-parameter correction. Distance trees were constructed and bootstrap values were obtained using 1,000 replicates. Trees were generated using the Dendroscope 3 software (version 3.6.3) [START_REF] Huson | Dendroscope 3: an interactive tool for rooted phylogenetic trees and networks[END_REF].

The 16S rRNA Sanger sequences generated for this study were submitted to the Genbank database of NCBI under the accession numbers MN193104 -MN193411.

Illumina 16S high-throughput sequencing and data processing

Total DNA was extracted from 0.2 g of soil or oak sawdust (SW and HW) using the Fast DNA SPIN kit for soil extraction kit (MPbiomedical, Illkirch, France) following manufacturer's instructions with slight modifications including a step to grind the samples using a Retsch MM301 mixer (Retsch GbmH, Haan, Germany) and three additional washings with guanidine thiocyanate (5.5 M, pH 7) before to add the binding matrix. This step allows to efficiently denature endogenous nucleases and would facilitate the separation of proteins from the related sugars or polyols [START_REF] Cox | The use of guanidinium chloride in the isolation of nucleic acids[END_REF][START_REF] Mason | The hydration structure of guanidinium and thiocyanate ions: implications for protein stability in aqueous solution[END_REF]. To prepare the amplicon libraries for the paired-end Illumina sequencing, the primers 515f and 806r targeting the V4 region have been used [START_REF] Caporaso | Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample[END_REF]. The sample multiplexing, the paired-end Illumina sequencing using 2x250 bp Miseq v3 and the de-multiplexing of the sequences were performed at GeT-PlaGe (Genotoul, Toulouse, France) according to the manufacturer's instructions.

Raw sequences processing was performed using FROGS (Find Rapidly OTU with Galaxy Solution) pipeline [START_REF] Escudié | FROGS: find, rapidly, OTUs with galaxy solution[END_REF]. Paired sequences were merged into contigs with flash [START_REF] Magoc | FLASH: fast length adjustment of short reads to improve genome assemblies[END_REF], cleaned with cutadapt [START_REF] Martin | Cutadapt removes adapter sequences from high-throughput sequencing reads[END_REF] and chimeras were removed with VSEARCH [START_REF] Rognes | VSEARCH: a versatile open source tool for metagenomics[END_REF]. The clustering to generate Operational Taxonomic Units (OTU) was then performed with SWARM algorithm [START_REF] Mahé | Swarm: robust and fast clustering method for amplicon-based studies[END_REF] using a local clustering threshold (97% similarity) and the taxonomic affiliation of each OTU was based on the reference databases NCBI Blast+ on SILVA123 16S [START_REF] Camacho | BLAST+: architecture and applications[END_REF], Quast et al., 2013). Finally, a table presenting the number of 16S rRNA sequences assigned to each OTU as well as their taxonomic affiliation was generated. OTUs belonging to Eukaryota or Archaea, chloroplasts or mitochondria were discarded as well as contaminant OTUs generated by the extraction and amplification steps. All the singletons were removed for the OTUs analyses. Finally, the number of sequences per sample ranged from 17,806 to 39,132 giving a total of 334,380 sequences and 3,079 OTUs. OTU analyses were then performed using packages in R with a random subsampling to normalize each sample with the smallest number of sequences. The bacterial richness and alphadiversity (Chao1, ACE, Shannon and inverse Simpson indexes) were calculated based on OTU relative abundance. The Illumina 16S rRNA sequences generated for this study were submitted to the Sequence Read Archive (SRA) of NCBI under the accession number PRJNA55031.

To determine both sequence homology and the relative environmental representativeness of the bacterial isolates recovered in our study, the Sanger 16S rRNA gene sequences were compared to the Illumina 16S rRNA gene sequences using the Basic Local Alignment Search Tool (BLAST) algorithm [START_REF] Altschul | Basic local alignment search tool[END_REF]. The Illumina 16S rRNA gene sequences of each compartment were used as database and an alignment of the Sanger 16S rRNA gene sequences was performed with NCBI-Blast+ using an e-value cutoff of 1 e-5. This analysis was done on the 253 bp overlapping between the Sanger and Illumina 16S rRNA gene sequences.

Statistical analyses

All statistical analyses were performed using R 3.2.3 software (R Core Team, 2015). The effect of the compartment (i.e., BS vs HW vs SW) was tested on the chemistry data and the bioassay data using an analysis of variance (one-way ANOVA, P<0.05), followed by a Tukey test. Wood density differences between the two oak wood compartments (SW and HW) was determined by a t-test. For the culture-dependent approaches, a Chi 2 test (P<0.05) analysis was performed to determine whether the frequency of distribution of the bacterial isolates according to their efficacy depended on their ecological origin.

For the Illumina 16S rRNA gene sequences and the related OTUs, the analyses were performed using R packages: phyloseq (McMurdie and Holmes, 2013), ape [START_REF] Paradis | APE: analyses of phylogenetics and evolution in R language[END_REF] and vegan [START_REF] Oksanen | The vegan package[END_REF]. The data were visualized using ggplot 2 [START_REF] Wickham | ggplot2: elegant graphics for data analysis[END_REF]. The distribution of the bacterial communities according to their compartments was analyzed by performing multidimensional scaling (MDS) ordination using Bray Curtis matrix distance. Permutational multivariate analysis of variance (PERMANOVA) based on Bray-Curtis distances with 999 permutations were performed on the OTU table using the vegan package and the Adonis command. Analysis of variance and subsequent post-hoc Tukey's tests to compare taxonomic and functional differences between the compartments were also performed. Relative abundance values at all taxonomic levels (phylum, class, order, family, genus, OTU) were compared for taxa or OTUs presenting a minimum of 100 sequences. These values were transformed using the arcsine square root to achieve a normal distribution. When required, a p adjustment was done using the false-Discovery-Procedure (FDR) of [START_REF] Benjamini | Controlling the false discovery rate: a practical and powerful approach to multiple testing[END_REF] to determine the pvalue threshold. Correlations between the major wood phyla and wood chemistry was assessed using Pearson correlations (P<0.05).

Results

Chemical analyses and wood decay stage assessment

The chemical analyses were done after nine months of incubation on the BS and wood samples (SW and HW sawdust) (Table SI-1A, B). The analysis of the pH revealed that BS harbored similar pH to the SW. The C/N ratio was 10 to 26 times lower in BS than in the wood compartments (Tab. SI-1A, B). The comparison of the wood compartments revealed that SW was characterized by significantly higher pH (pH-SW=4.63 vs pH-HW=3.75), higher amounts of N, P and Mg (ANOVA, P<0.05) and lower (approximately two times) C/N ratio (ANOVA, P<0.05). The content of cellulose and lignin (expressed on percentage relative to the global composition) appeared similar in HW and SW (ANOVA, P>0.05) (Tab. SI-1A).

After nine months of in situ decay, the visual inspection showed a strong fungal colonization of the SW compartment, while the HW compartment appeared poorly colonized (Fig. 1A,B). Significant variations of the wood density were observed based on the pilodyn measurements. Indeed, the penetration increased from T0 (25.8% ± 7.4 depth penetration in SW vs 16.4% ± 3.2 in HW) to T9 months (55.8% ± 12.6 in SW vs 30.4% ± 4.5 in HW). A significantly higher decay stage was measured for SW from T3 to T9 months compared to HW (t-Test; P<0.05) (Fig. 1C). According to these data, the decay stage of the oak discs after nine months of decay was considered as a middle stage.

OTUs distribution and diversity indices in soil and decaying wood

From the 213,672 16SrRNA sequences retained after bioinformatics treatments (Tab. SI-2), a total of 2,901 OTUs were generated. Comparison between the compartments revealed that the BS harbors significantly more OTUs (1,141 ± 189) than the wood compartments (SW: 548 ± 127 and HW: 351 ± 123) (ANOVA, P<0.05). No difference was observed between the SW and HW (ANOVA, P>0.05) (Tab. SI-3). Among the total number of OTUs obtained, 9.8% were shared between the three compartments, while some were compartment specific (BS: 50.2%; SW: 14.3% and HW: 7.7% OTUs). Furthermore, 7.4% of the OTUs were shared between the two wood compartments and ca 5% of the OTUs were shared between BS and the wood compartments (Fig. SI-2). The observed (i.e., number of OTU observed) and the estimated richness (i.e., chao1, ACE) as well as the alpha-diversity (i.e., Shannon, Inv. Simpson) were significantly higher in BS compared to the wood compartments (ANOVA, P<0.05). These indices tended to be higher in the SW than in the HW, but only significantly for the Shannon values (Tab. SI-3). Most of the OTUs obtained were assigned at the phylum (99.8%-23 different phyla) to family (88.1%) level, but only 66.4% of these sequences were assigned at the genus level.

A global description of the taxonomic affiliation of these OTUs is presented in the table SI-4.

Structure and taxonomic composition of the bacterial communities in soil and decaying wood.

The properties of the different compartments considered (BS, SW and HW) strongly determined the bacterial community structure (i.e., BS vs HW vs SW; F=10.6; R 2 =0.70; P=0.01; PERMANOVA and Fig. 2A). Noticeably, the bacterial community structure significantly differed between SW and HW (i.e., F=3.17; R 2 = 0.35; P=0.03; PERMANOVA). A MDS analysis done on the OTUs confirmed this compartment effect (Fig. 2A,B). A detailed analysis of the taxonomic composition revealed that the wood-inhabiting bacterial community was significantly dominated by the Proteobacteria (59 to 73.4% of the 16S rRNA sequences in SW and HW, respectively) compared to the BS compartment (ANOVA, P<0.05) (Fig. 2A, Tab. SI-5). Alphaproteobacteria was the most abundant class in wood with 28.8% in SW and 41.7% in HW. A similar trend was observed for Betaproteobacteria (wood > BS; ANOVA, P<0.05). Notably, our analyses revealed that the SW was significantly enriched in Bacteroidetes (ANOVA, P<0.05). In contrast, the BS bacterial community was mainly represented by Acidobacteria, followed by Proteobacteria (with Alphaproteobacteria being the most represented class) and Verrucomicrobia (12.8%). The relative abundance of Acidobacteria and Verrucomicrobia was significantly higher in BS than in HW and SW (ANOVA, P<0.05). Noticeably, the relative abundance of the Bacteroidetes (mainly present in SW) was positively correlated with wood pH (P=0.01) and P concentration (P=0.02), while it was negatively correlated with the C/N ratio (P=0.02). At the opposite, the relative abundance of the Alphaproteobacteria (dominant in HW) was positively correlated with the C/N ratio (P=0.001) but negatively correlated with P concentrations (P=0.02) and the total amount of N (P=0.02) (Fig. SI-3).

Differences, at the OTUs level, between wood compartments and between wood and BS were also observed. Dominant and specific OTUs of each compartment are presented in Fig. 3, Table SI-6 and7.

Taxonomic affiliation of the bacterial isolates and relationship with their ecological origin

The quantification of the culturable bacteria by dilution-plating revealed that BS harbored significantly higher densities (9.03 ± 0.14 Log10 CFU g -1 of soil) than the SW (8.09 ± 0.08; ANOVA, P<0.05), but was not different from HW (8.80 ± 0.30; ANOVA, P>0.05). HW harbored slightly higher densities than the SW (ANOVA,

P<0.05).

The taxonomic affiliation of the bacterial isolates revealed that most of them were affiliated to Proteobacteria (77.7%), Actinobacteria (15.5%), Acidobacteria (4.5%) and Bacteroidetes (2.3%). The relative distribution of the 30 genera detected is presented in Figure 4 and Table SI-8. Notably, ca. 10% of the bacterial isolates had less than 97% similarity with the 16S rRNA gene sequence of a known culturable bacterial strain deposited in NCBI. Most of these particular isolates came from SW.

When the taxonomic affiliation of the bacterial isolates was linked to their ecological niche (BS vs HW vs SW), our analysis showed that isolates belonging to the Beta-and Gammaproteobacteria were common to the three compartments (Fig. 4; Tab. SI-8). However, we noticed that the SW compartment was significantly enriched in Gammaproteobacteria isolates (SW, 57.8% of the isolates; BS, 24.4% and HW, 17.8%; Chi 2 , P<0.002), whereas, the BS compartment was significantly enriched in Betaproteobacteria isolates (BS, 49.6% of the isolates; SW, 30.6% and HW, 19.8%; Chi 2 , P<0.003). Interestingly, all the isolates belonging to Acidobacteria and Bacteroidetes (Alphaproteobacteria) were exclusively found in wood (SW and/or HW). Several genera were strongly represented and only detected in wood. This is the case of Sphingomonas, Mucilaginibacter and Luteibacter in SW, and Acidocella, Acidipila and Novosphingobium in HW. At the opposite, Actinobacteria strains assigned to Streptomyces, Kitasatospora, Arthrobacter and Streptacidiphilus were dominant in BS. Strains assigned to the Paraburkholderia and Dyella genus were recovered in the three compartments considered, with Paraburkholderia representing 34.7% of the total of the isolates.

Metabolic and functional potentials of the culturable bacterial communities

The metabolic bioassays based on Biolog plates revealed that the BS bacterial isolates harbored significantly higher metabolic potentials than those of the decayingwood compartments (BS>SW=HW) (ANOVA; P<0.05) (Fig. SI-4). Such difference was observed at both substrate and substrate category levels (Fig. .

Comparisons between wood bacterial isolates showed that HW isolates had a higher metabolic potentials for substrates belonging to (i) the carboxylic acid group (ca. 2 fold higher than SW for quinic acid, sebacic acid, succinamic acid, D-glucosaminic acid, glycyl-L-glutamic acid) (ii) the amino acid group (ca. 2 fold higher than SW for L-histidine); (iii) the miscellaneous group (15 fold higher than SW for thymidine); and finally, (iv) the amine-amide group (aminoethanol, 3 fold higher). Beta-methyl-D-glucoside was almost the unique substrate more effectively metabolized by the SW bacterial isolates (4 fold higher than HW isolates) (Fig. 5).

Among the functional bioassays performed, the cellulose decomposition assay gave the highest number of positive bacterial isolates. Indeed, ca. 12.6% of the bacterial isolates tested appeared capable of degrading cellulose (Fig. SI-5).

Significantly more bacteria isolated from HW (ca. 28.6%) were capable of degrading cellulose, than those coming from SW (13.4%) and BS (10.3%) (Chi2; P<0.0001). In term of effectiveness, the BS and HW bacterial isolates tended to be more effective at degrading cellulose (halo diameters: 0.21cm±0.04 for BS isolates and 0.20cm±0.02 for HW isolates) than the SW isolates (0.12cm±0.02; ANOVA 443 P=0.07). In the wood compartments, the ability to degrade cellulose was mainly encountered for bacterial isolates assigned to the genus Mucilaginibacter (relative efficacy to degrade cellulose (halo diameter): 0.81cm±0.51), Novosphingobium (0.50cm±0.51) and Acidisoma (0.48cm±0.41). Noticeably, 71.4% of the Mucilaginibacter isolates were capable of hydrolyzing cellulose, while only 54.5% for Acidisoma and 38.5% for Novosphingobium (Fig. 6). In contrast, in the BS compartment this function was mainly encountered for bacterial isolates assigned to the genus Kitasatospora (2.05cm±1.61) and Streptomyces (0.73cm±1.21) (Fig. 6).

Concerning the ability to degrade chitin, only 8.5% of the bacterial isolates were capable of degrading this compound and were mainly isolated from BS (45.5% of the isolates capable to hydrolyze chitin were originated from BS) (Fig. SI-5). The BS and HW bacterial isolates tended to be more effective at degrading chitin. The bacterial genera presenting the highest potential were assigned to the genus Collimonas (halo diameter: 1.83cm±0.49; only recovered from the BS compartment), Luteibacter (0.91±0.74; only recovered from the HW compartment) and Streptomyces (0.62cm±0.72; only recovered from the BS compartment). While all of the Collimonas isolates were effective at hydrolyzing chitin, only 57.1% and 25% of the Luteibacter and Streptomyces isolates did it (Fig. 6).

For the other functions related to organic matter decomposition, the ability to degrade xylan was only detected for seven bacterial isolates (2.8% of the bacterial collection) (Fig. 6) and none of the bacterial isolates was capable of degrading lignin.

Concerning the ability to mobilize iron, ca. 24% of the bacterial isolates tested were positives (Fig. SI-5). Significantly higher proportions were observed in BS (72.9% of the isolates mobilizing iron) than in HW (18.6%) or SW (8.5%) (Chi 2 ; P<0.001). The bacterial genera presenting the highest potentials to mobilize iron were assigned to the genus Pseudomonas (relative efficacy to mobilize iron (halo diameter): 2.08cm±0.98) and in a lesser extend to Collimonas isolates (1.48cm±0.69) with respectively 85.7% and 100% of the isolates of these genera being effective for iron mobilization. The two other genera: Paraburkholderia (0.7cm±0.93) and Streptomyces (0.2cm±0.49) were significantly less efficient than Pseudomonas isolates (ANOVA, P<0.05) (Fig. 6).

Comparison of the Sanger and Illumina 16S RNA gene sequences

This analysis highlighted that all the 308 bacterial isolates of our collection had a minimum of 97% of sequence homology with at least one OTU of the Illumina sequence dataset. When the highest homology was considered, this analysis revealed that the bacterial isolates corresponded to 65 OTUs identified in the Illumina dataset. These OTUs represented 55.4% of the total number of Illumina 16S rRNA sequences. Interestingly, the most represented bacterial isolates in our collection (at the genus level) were also among the dominant in the OTUs (Rank in the collection / rank in the OTU table; Paraburkholderia (1/1), Acidisoma (2/5), Dyella (3/12), Acidocella (6/4) and more distantly Pseudomonas (7/114) (data not shown).

Discussion

To date, a few studies have investigated the taxonomic diversity and especially the metabolic and functional role of decaying wood-inhabiting bacteria [START_REF] Murray | Temporal changes in functional diversity of culturable populations in Sitka spruce stumps[END_REF][START_REF] Folman | Impact of whiterot fungi on numbers and community composition of bacteria colonizing beech wood from forest soil[END_REF][START_REF] Hervé | Impact of Phanerochaete chrysosporium on the functional diversity of bacterial communities associated with decaying wood[END_REF]. However, this aspect is of importance to better understand the decaying wood process and how bacteria contribute to the recycling of the nutritive elements accumulated in the tree biomass.

Therefore, to investigate the structure and the potential role of the bacterial communities, we used oak discs installed on the floor of an oak forest site, mimicking partially in this way the conditions when trees fall on the soil and initiate a decomposition process. A combination of culture-dependent and -independent approaches combined with chemical analyses were used and comparisons with bulk soil bacteria was made to highlight the soil-decaying wood continuum.

Edaphic origin of decaying oak wood-inhabiting bacteria.

How decaying-wood is colonized by microorganisms is rather difficult to determine. Indeed, part of the microorganisms found in decaying wood may originate from the tree tissues (i.e., endophytes), atmospheric deposits or from the surrounding BS [START_REF] Baldrian | Fungi associated with decomposing deadwood in a natural beech-dominated forest[END_REF]. Previous analyses provided clear evidences that whether or not an initial microbiota exists inside trees during their life, its biomass and diversity changed importantly and quickly between the early and later stages of wood decay [START_REF] Tláskal | Bacteria associated with decomposing dead wood in a natural temperate forest[END_REF]. The Venn diagram analyses done in our study suggest that a part of the wood-inhabiting bacterial communities is also part of the BS bacterial communities (10.6%). The other OTUs only detected in wood may represent minor groups occurring in BS but not detected by sequencing or may be coming from other locations (i.e., atmosphere, endophytes of the oak discs, woody debris fallen on the oak discs). Interestingly, [START_REF] Probst | Bacterial communities of decaying Norway spruce follow distinct slope exposure and time-dependent trajectories[END_REF] also observed that a significant part of the OTUs identified in decaying wood were shared with the surrounding BS, supporting an edaphic origin of wood-inhabiting bacteria. The detailed analysis of the culture-dependent approach also indicated that several bacterial genera were detected in both the BS and wood compartments including bacterial isolates assigned to Paraburkholderia, Dyella and Pseudomonas. These bacterial genera have frequently been described in forest soils, underlying their ability to adapt to various habitats such as decaying wood [START_REF] Folman | Impact of whiterot fungi on numbers and community composition of bacteria colonizing beech wood from forest soil[END_REF][START_REF] Lladó | Functional screening of abundant bacteria from acidic forest soil indicates the metabolic potential of Acidobacteria subdivision 1 for polysaccharide decomposition[END_REF][START_REF] Nicolitch | Tree roots select specific bacterial communities in the subsurface critical zone[END_REF]. Supporting this hypothesis, [START_REF] Hervé | Diversity and structure of bacterial communities associated with Phanerochaete chrysosporium during wood decay[END_REF] demonstrated that Burkholderia and Dyella strains isolated from BS and inoculated in wood sawdust microcosms became dominant after a succession of enrichment steps. Those results support the idea that the BS in forest ecosystem represents a seedbank with a high diversity of functional groups capable of decomposing wood. This is not surprising as the topsoil is continuously in contact with litter and wood debris. Consequently, the abundance of wood-inhabiting bacteria depends on the turnover of tree biomass (wood, litter) with bacteria returning to the surrounding soil at the end of the wood decomposition process [START_REF] Probst | Bacterial communities of decaying Norway spruce follow distinct slope exposure and time-dependent trajectories[END_REF].

Metabolic and functional potential of decaying oak wood-inhabiting bacterial communities differ from soil bacterial communities.

Decaying oak wood-inhabiting bacterial communities may directly or indirectly contribute to wood decomposition. In this study, we tested the hypothesis of a direct role of bacteria in wood decay. To do it, a functional screening targeting the main wood constituents (cellulose, xylan and lignin) was performed. We also focused on chitin because it is an essential constituent of fungal cell walls, and the decomposition of the wood is characterized also by a dynamic succession of different fungi during the whole process [START_REF] Rajala | Habitat models of woodinhabiting fungi along a decay gradient of Norway spruce logs[END_REF], generating an important fungal necromass potentially recyclable by bacteria. Mobilization of iron was also studied because iron plays a role in the oxidative process of wood decomposition [START_REF] Goodell | Low molecular weight chelators and phenolic compounds isolated from wood decay fungi and their role in the fungal biodegradation of wood[END_REF]. Our results showed that cellulose degrading bacteria were more frequent in wood, especially in HW, than in the surrounding BS. However, BS was characterized by bacterial isolates presenting a higher effectiveness at degrading cellulose, xylan or chitin or at mobilizing iron than HW and SW. These results differ from those obtained by [START_REF] Hervé | Impact of Phanerochaete chrysosporium on the functional diversity of bacterial communities associated with decaying wood[END_REF] where there was no functional difference observed between bacteria isolated from BS and those adapted to beech decaying wood. However, our experiment was done in situ and over a longer period, which may explain the differences we observed. Looking at the taxonomic identity of the strains, we found that representatives of the Kitasatospora genus, isolated from BS, were among the most effective at degrading cellulose. Nonetheless, representatives of the Mucilaginibacter, Acidisoma and Novosphingobium genera, all isolated from wood (SW and HW), were also effective. Except for Novosphingobium, these genera were previously identified as important cellulose decomposers [START_REF] Štursová | Cellulose utilization in forest litter and soil: identification of bacterial and fungal decomposers[END_REF][START_REF] Lladó | Functional screening of abundant bacteria from acidic forest soil indicates the metabolic potential of Acidobacteria subdivision 1 for polysaccharide decomposition[END_REF][START_REF] Lopez-Mondejar | Cellulose and hemicellulose decomposition by forest soil bacteria proceeds by the action of structurally variable enzymatic systems[END_REF][START_REF] Nicolitch | Soil type determines the distribution of nutrient mobilizing bacterial communities in the rhizosphere of beech trees[END_REF]. The absence of bacterial strains able to degrade lignin confirms the results obtained by [START_REF] Murray | Temporal changes in functional diversity of culturable populations in Sitka spruce stumps[END_REF] and [START_REF] Hervé | Impact of Phanerochaete chrysosporium on the functional diversity of bacterial communities associated with decaying wood[END_REF]. Those results suggest that the ligninolytic activity is probably mainly attributable to fungi [START_REF] Janusz | Lignin degradation: microorganisms, enzymes involved, genomes analysis and evolution[END_REF]). However, bacterial strains affiliated to the Actinomycetes, Alphaproteobacteria and Gammaproteobacteria have been reported for their ability to break down lignin [START_REF] Bugg | The emerging role for bacteria in lignin degradation and bio-product formation[END_REF][START_REF] Janusz | Lignin degradation: microorganisms, enzymes involved, genomes analysis and evolution[END_REF]. The metabolic assays (strain by strain) revealed significant differences between wood and soil bacteria. The decaying wood-inhabiting bacteria presented weaker metabolic potentials than the BS isolates, but a conserved ability to consume cellulose and hemicellulose derived monomers such as alpha Dglucose, D-mannitol, D-mannose, L-arabinose, N-acetyl-D-glucosamine, L-fucose, Dsorbitol, D-fructose, L-rhamnose and beta-methyl-D-glucoside. The preferential use of these wood monomers by bacterial strains isolated from a wood environment was also demonstrated by [START_REF] Hervé | Impact of Phanerochaete chrysosporium on the functional diversity of bacterial communities associated with decaying wood[END_REF]. Another hypothesis explaining the enrichment of particular bacteria in decaying wood is their indirect role in the wood decay process [START_REF] Clausen | Bacterial associations with decaying wood: a review[END_REF][START_REF] Johnston | Bacteria in decomposing wood and their interactions with wood-decay fungi[END_REF]. Indeed, it was proposed that wood-colonizing fungi enrich their habitat with bacteria capable of fixing nitrogen or providing them other services, promoting fungal development and wood decomposition. Although this hypothesis was not tested in our study, the chitin degradation assay performed evidenced that some HW bacteria may have a negative impact on fungi. Altogether, the results obtained through the functional bioassays suggest that the decaying wood-inhabiting bacteria are adapted to their environment where substrates are less diverse than in the soil and potentially more recalcitrant to decomposition.

Wood properties determine the structure of the bacterial communities.

Intrinsic (chemistry) and extrinsic (environment) factors may impact the structuration of the wood-inhabiting bacterial communities. Indeed, wood is not a homogenous material and it is established that HW and SW present different properties. In our study, the chemical analyses done on the SW and HW compartments clearly evidenced that SW presented significantly higher content of N, P and Mg, and lower C/N ratio than HW. In addition, HW presented a significantly more acidic pH than SW. Interestingly, C/N ratio and pH have been proposed as driving factors governing the composition of the wood-inhabiting bacterial communities [START_REF] Folman | Impact of whiterot fungi on numbers and community composition of bacteria colonizing beech wood from forest soil[END_REF][START_REF] Hoppe | A pyrosequencing insight into sprawling bacterial diversity and community dynamics in decaying deadwood logs of Fagus sylvatica and Picea abies[END_REF]. In this sense, the correlation analyses done between the Illumina 16S rRNA sequences and the wood properties revealed that the C/N ratio was negatively correlated with the abundance of Bacteroidetes, while it was positively correlated with Alphaproteobacteria. In addition, pH appeared positively correlated with the abundance of Bacteroidetes. These two wood chemical properties were also reported as main drivers of bacterial community structures in decaying wood [START_REF] Tláskal | Bacteria associated with decomposing dead wood in a natural temperate forest[END_REF][START_REF] Moll | Bacteria inhabiting deadwood of 13 tree species are heterogeneously distributed between sapwood and heartwood[END_REF]. The HW compartment is also known to present a higher phenolic extractives content (up to 10%), which may have an antimicrobial activity [START_REF] Kebbi-Benkeder | Quantification and characterization of knotwood extractives of 12 European softwood and hardwood species[END_REF][START_REF] Miranda | Chemical characterization and extractives composition of heartwood and sapwood from Quercus faginea[END_REF][START_REF] Moll | Bacteria inhabiting deadwood of 13 tree species are heterogeneously distributed between sapwood and heartwood[END_REF]. The colonization of the wood compartments by other types of decaying wood organisms (i.e., fungi and insects;Kubartova ́ et al., 2012;[START_REF] Ulyshen | Wood decomposition as influenced by invertebrates[END_REF][START_REF] Leonhardt | Molecular fungal community and its decomposition activity in sapwood and heartwood of 13 temperate European tree species[END_REF] may also be important extrinsic factors driving the structure of the bacterial communities. Indeed, fungi and insects are known to be important wood decomposers [START_REF] Baldrian | Fungi associated with decomposing deadwood in a natural beech-dominated forest[END_REF][START_REF] Ulyshen | Wood decomposition as influenced by invertebrates[END_REF] and their interactions with bacteria are known to have an important ecosystemic role [START_REF] Folman | Impact of whiterot fungi on numbers and community composition of bacteria colonizing beech wood from forest soil[END_REF][START_REF] Frey-Klett | Bacterial-fungal interactions: hyphens between agricultural, clinical, environmental, and food microbiologists[END_REF][START_REF] Hervé | Impact of Phanerochaete chrysosporium on the functional diversity of bacterial communities associated with decaying wood[END_REF][START_REF] Johnston | Bacteria in decomposing wood and their interactions with wood-decay fungi[END_REF]. Notably, bacterial-fungal consortia were shown to degrade wood more effectively than fungi alone [START_REF] Murray | In vitro interactions between bacteria isolated from Sitka spruce stumps and Heterobasidion annosum[END_REF][START_REF] Hervé | Impact of Phanerochaete chrysosporium on the functional diversity of bacterial communities associated with decaying wood[END_REF]. In our study, a visual inspection of the oak discs at the end of the incubation revealed an important fungal development (i.e., hyphae) on the surface of SW, which was not visible on HW. Consequently, it is strongly plausible that differences between HW and SW in term of bacterial community structure are also due to the presence of fungal communities. Whether the density of culturable bacteria was similar between the HW and BS, the taxonomic structuration differed. Although it was only significant for the richness index (i.e., Shannon), all the richness and diversity indices tended to have lower values for the HW compartment compared to SW. A similar trend was obtained by [START_REF] Moll | Bacteria inhabiting deadwood of 13 tree species are heterogeneously distributed between sapwood and heartwood[END_REF] considering 30 tree species, including oak tree. In our study, the decrease of diversity and richness corresponded to higher abundances of Alpha-and Betaproteobacteria and lower abundance of Bacteroidetes in HW than in SW. These results differ from the study of [START_REF] Moll | Bacteria inhabiting deadwood of 13 tree species are heterogeneously distributed between sapwood and heartwood[END_REF] where the major difference between HW and SW of decaying oak wood relied on an increase of Acidobacteria in SW. The culturable approach also permitted to differentiate the SW and HW compartments. Notably, several genera were only isolated in HW (i.e., Acidocella) or only in SW (i.e., Mucilaginibacter, Luteibacter, Yersinia), evidencing a relatively good overlap between the conclusions obtained by the culture-dependent and -independent approaches. Together, these results highlight that specific bacterial communities are enriched in each wood compartment, potentially according to the wood properties as well as due to the interactions with the fungal communities occurring in decaying wood.

Conclusion

Our study highlighted that at middle stage of decay, a significant part of the microbiota enriched in wood is shared with the surrounding bulk soil (BS), evidencing that decaying wood is not disconnected from its environment. At the same time, ca 30% of the OTUs identified in our study were only detected in the wood compartments, highlighting the enrichment of particular taxa and/or functional group in decaying wood. Interestingly, the bacterial communities occurring in the SW and HW compartments significantly differed in their taxonomic and functional compositions. The distribution of some taxa appeared significantly correlated to the wood chemical properties. This differentiation clearly evidences that the colonization of decaying wood by bacteria is based on a deterministic process linking extrinsic and intrinsic factors. Although the bacteria isolated from the wood compartments presented lower metabolic potentials compared to those of the surrounding BS, they were characterized by a conserved ability to decompose cellulose/hemicellulose and derivatives. In contrast, no bacteria capable of decomposing lignin was identified.

Those results suggest that wood-inhabiting bacteria are capable of degrading the easily degradable part of wood, but that the decomposition of the recalcitrant part (i.e., lignin) is probably done by fungi (van der Wal et al., 2015;[START_REF] Hoppe | A pyrosequencing insight into sprawling bacterial diversity and community dynamics in decaying deadwood logs of Fagus sylvatica and Picea abies[END_REF][START_REF] Leonhardt | Molecular fungal community and its decomposition activity in sapwood and heartwood of 13 temperate European tree species[END_REF][START_REF] Tláskal | Bacteria associated with decomposing dead wood in a natural temperate forest[END_REF]. Another hypothesis may be that these bacterial communities indirectly contribute to wood decay through the promotion of fungal growth, highlighting a possible functional complementation between bacteria and fungi [START_REF] Frey-Klett | Bacterial-fungal interactions: hyphens between agricultural, clinical, environmental, and food microbiologists[END_REF]. Future work will need to focus i) on the functional structuration of the bacterial communities at different stage of decay, ii) on bacterialfungal interactions and/or co-occurrence studies during wood decay and iii) on the indirect role of bacteria such as nitrogen fixation during wood decay. Combination of field experiments and controlled microcosms will be necessary to better understand the role of microbial interactions and community successions in wood decay.

Acknowledgments

This work was supported by the Laboratory of Excellence Arbre (ANR-11-LABX-0002-01; DivBacto project) and by the EFABA project (SF 4242; Al-16-3). The UMR1136 is supported by the French Agency through the Laboratory of Excellence Arbre (ANR-11-LABX-0002-01). We would like also to thank A. Deveau for her help concerning the analysis of the Illumina Miseq 16S rRNA sequences. Picture of an oak disc after 9 months of in situ decay (T9 months) showing the side in direct contact with the soil. C. Mean percentage of the penetration depth for the sapwood (SW) and heartwood (HW) compartments assessed using a Pilodyn penetrometer at T0 (n=3) and T3, T6 and T9 months (n=20 per time point). Significant differences between the two wood compartments for each time point are presented using a star (P<0.05 according to a t-test). A bootstrap analysis was performed with 1000 repetitions. Due to the relatively large number of sequences analysed, we have chosen one representative sequence in each genus for the tree representation. Pie chart on the right side of each genus represents the distribution of bacterial isolates assigned to this genus according to their origin (blue: BS, red: SW, green: HW). Number accessions for reference strains from NCBI are indicated in brackets. Figure 5. Heatmap analysis of the metabolic potentials obtained using Biolog GN2 microplates. A total of 304 bacterial isolates was tested. Detailed analysis of the substrates for which metabolic potentials varied significantly among the bacterial isolates depending on the compartment (oak decaying sapwood (SW) and heartwood (HW) and bulk soil (BS)) was done. Statistics on the right of the heatmap were obtained according to a one-way ANOVA followed by a Tukey test (NS: not significant, *P<0.05, **P<0.01, ***P<0.001). Figure 6. Relationship between functional efficacy and taxonomic affiliation. For each bacterial genus represented by a minimum of three effective isolates, their relative efficacy to hydrolyze cellulose, xylan and chitin and to mobilize iron is presented, whatever their compartment (oak decaying sapwood (SW) and heartwood (HW) and bulk soil (BS)) of the bacterial isolates. Lowercase letters (a, b, c, d or e) indicate significant differences between genus efficacies. Statistics were obtained according to a one-way ANOVA followed by a Tukey test (P<0.05). The number of isolates tested per genus as well as their repartition according to their comprtment (BS, SW or HW) is presented under the bars. The error bars indicate the standard error.

Author contributions

  S.M., S.U. and M.B., conceived and designed the study; S.M., C.B., P.R. and C.L., performed field and laboratory work; S.M. and S.U., analyzed the data and wrote the paper. All authors reviewed and edited the manuscript.

  Figure Legends:

Figure 2 .

 2 Figure. 1. Evidence of the oak decay stage. A.Picture of a freshly cut oak disc at the beginning of the experiment (T0 month). B. Picture of an oak disc after 9 months of in situ decay (T9 months) showing the side in direct contact with the soil. C. Mean percentage of the penetration depth for the sapwood (SW) and heartwood (HW) compartments assessed using a Pilodyn penetrometer at T0 (n=3) and T3, T6 and T9 months (n=20 per time point). Significant differences between the two wood compartments for each time point are presented using a star (P<0.05 according to a t-test). Figure 2. A. Relative abundance of the Illumina Miseq 16S rRNA sequences from bacterial taxonomic phyla for each compartment (oak decaying sapwood (SW) and heartwood (HW) and bulk soil (BS)). The ten most abundant phyla were considered. B. Multidimensional scaling (MDS) ordination using Bray Curtis matrix distance representing the distribution of the bacterial communities according to each compartment (oak decaying sapwood (SW) and heartwood (HW) and bulk soil (BS)). Figure 3. Heatmap showing the relative abundance of the 10 most important OTUs per compartment (oak decaying sapwood (SW) or heartwood (HW) or bulk soil (BS)) expressed in percentage. Figure 4. Neighbor-joining tree showing the phylogenetic relationships of bacterial isolates depending on their compartment (oak decaying sapwood (SW) and heartwood (HW), Bulk soil (BS)), based on PCR sequencing of a portion of the 16S rRNA gene.A bootstrap analysis was performed with 1000 repetitions. Due to the relatively large number of sequences analysed, we have chosen one representative sequence in each genus for the tree representation. Pie chart on the right side of each genus represents the distribution of bacterial isolates assigned to this genus according to their origin (blue: BS, red: SW, green: HW). Number accessions for reference strains from NCBI are indicated in brackets. Figure5. Heatmap analysis of the metabolic potentials obtained using Biolog GN2 microplates. A total of 304 bacterial isolates was tested. Detailed analysis of the substrates for which metabolic potentials varied significantly among the bacterial isolates depending on the compartment (oak decaying sapwood (SW) and heartwood (HW) and bulk soil (BS)) was done. Statistics on the right of the heatmap were obtained according to a one-way ANOVA followed by a Tukey test (NS: not significant, *P<0.05, **P<0.01, ***P<0.001). Figure6. Relationship between functional efficacy and taxonomic affiliation. For each bacterial genus represented by a minimum of three effective isolates, their

Figure 4 .

 4 Figure. 1. Evidence of the oak decay stage. A.Picture of a freshly cut oak disc at the beginning of the experiment (T0 month). B. Picture of an oak disc after 9 months of in situ decay (T9 months) showing the side in direct contact with the soil. C. Mean percentage of the penetration depth for the sapwood (SW) and heartwood (HW) compartments assessed using a Pilodyn penetrometer at T0 (n=3) and T3, T6 and T9 months (n=20 per time point). Significant differences between the two wood compartments for each time point are presented using a star (P<0.05 according to a t-test). Figure 2. A. Relative abundance of the Illumina Miseq 16S rRNA sequences from bacterial taxonomic phyla for each compartment (oak decaying sapwood (SW) and heartwood (HW) and bulk soil (BS)). The ten most abundant phyla were considered. B. Multidimensional scaling (MDS) ordination using Bray Curtis matrix distance representing the distribution of the bacterial communities according to each compartment (oak decaying sapwood (SW) and heartwood (HW) and bulk soil (BS)). Figure 3. Heatmap showing the relative abundance of the 10 most important OTUs per compartment (oak decaying sapwood (SW) or heartwood (HW) or bulk soil (BS)) expressed in percentage. Figure 4. Neighbor-joining tree showing the phylogenetic relationships of bacterial isolates depending on their compartment (oak decaying sapwood (SW) and heartwood (HW), Bulk soil (BS)), based on PCR sequencing of a portion of the 16S rRNA gene.A bootstrap analysis was performed with 1000 repetitions. Due to the relatively large number of sequences analysed, we have chosen one representative sequence in each genus for the tree representation. Pie chart on the right side of each genus represents the distribution of bacterial isolates assigned to this genus according to their origin (blue: BS, red: SW, green: HW). Number accessions for reference strains from NCBI are indicated in brackets. Figure5. Heatmap analysis of the metabolic potentials obtained using Biolog GN2 microplates. A total of 304 bacterial isolates was tested. Detailed analysis of the substrates for which metabolic potentials varied significantly among the bacterial isolates depending on the compartment (oak decaying sapwood (SW) and heartwood (HW) and bulk soil (BS)) was done. Statistics on the right of the heatmap were obtained according to a one-way ANOVA followed by a Tukey test (NS: not significant, *P<0.05, **P<0.01, ***P<0.001). Figure6. Relationship between functional efficacy and taxonomic affiliation. For each bacterial genus represented by a minimum of three effective isolates, their