Chiarello Marlène
email: marlene.chiarello@gmail.com

Auguet Jean-Christophe

Graham Nicholas

Claverie Thomas

Sucré Elliott

Bouvier Corinne

Rieuvilleneuve Fabien

Claudia Restrepo-Ortiz

Ximena

Bettarel Yvan

Villéger Sébastien

Bouvier Thierry

Marlène Chiarello

Exceptional but vulnerable microbial diversity in coral reef animal surface microbiomes

Keywords: skin microbiota, phylogenetic diversity, conservation, marine biodiversity, Octocorallia, Scleratinia

Coral reefs host hundreds of thousands of animal species that are increasingly threatened by anthropogenic disturbances. These animals host microbial communities at their surface, playing crucial roles for their fitness. However, the diversity of such microbiomes is mostly described in a few coral species and still poorly defined in other invertebrates and vertebrates. Given the diversity of animal microbiomes, and the diversity of host species inhabiting coral reefs, the contribution of such microbiomes to the total microbial diversity of coral reefs could be important, yet potentially vulnerable to the loss of animal species. Analysis of the surface microbiome from 74 taxa, including teleost fishes, hard and soft corals, crustaceans, echinoderms, bivalves and sponges, revealed that more than 90% of their prokaryotic phylogenetic richness was specific and not recovered in surrounding plankton. Estimate of the total richness associated with coral reef animal surface microbiomes reached up to 2.5% of current estimates of Earth prokaryotic diversity. Therefore, coral reef animal surfaces should be recognized as a hotspot of marine microbial diversity. Loss of the most vulnerable reef animals expected under present-day scenarios of reef degradation would induce an erosion of 28% of the prokaryotic richness, with unknown consequences on coral reef ecosystem functioning.

BACKGROUND

Coral reefs provide habitats for at least 500,000 multicellular species [START_REF] Fisher | Species Richness on Coral Reefs and the Pursuit of Convergent Global Estimates[END_REF], including more than 6,000 described fish and 1,000 coral species [START_REF] Knowlton | Coral reefs[END_REF][START_REF] Kulbicki | Global Biogeography of Reef Fishes: A Hierarchical Quantitative Delineation of Regions[END_REF]. These animals are covered by diverse and abundant microbes (Bacteria, Archaea, viruses and micro-eukaryotes) which all together constitute the surface microbiome [START_REF] Bourne | Insights into the Coral Microbiome: Underpinning the Health and Resilience of Reef Ecosystems[END_REF]. Animal surface microbiomes play crucial roles for their hosts, contributing to host resistance to pathogens and environmental perturbations [START_REF] Krediet | Members of native coral microbiota inhibit glycosidases and thwart colonization of coral mucus by an opportunistic pathogen[END_REF][START_REF] Glasl | The microbiome of coral surface mucus has a key role in mediating holobiont health and survival upon disturbance[END_REF], and to assimilation of nutrients [START_REF] Bourne | Insights into the Coral Microbiome: Underpinning the Health and Resilience of Reef Ecosystems[END_REF]. However, animal surface microbiomes have been assessed in less than 50 and 100 coral and fish species, respectively [START_REF] Bourne | Insights into the Coral Microbiome: Underpinning the Health and Resilience of Reef Ecosystems[END_REF][START_REF] Glasl | The microbiome of coral surface mucus has a key role in mediating holobiont health and survival upon disturbance[END_REF][START_REF] Chiarello | Skin microbiome of coral reef fish is highly variable and driven by host phylogeny and diet[END_REF][START_REF] Larsen | Diversity of the skin microbiota of fishes: evidence for host species specificity[END_REF][START_REF] Carlos | Bacterial communities and speciesspecific associations with the mucus of Brazilian coral species[END_REF][START_REF] Chiarello | Environmental conditions and neutral processes shape the skin microbiome of European catfish (Silurus glanis) populations of Southwestern France[END_REF].

Large scale surveys of the marine water column demonstrated the important diversity of planktonic marine microbes [START_REF] Sunagawa | Structure and function of the global ocean microbiome[END_REF][START_REF] Vargas | Eukaryotic plankton diversity in the sunlit ocean[END_REF]. However, these planktonic microbes are compositionally distinct from marine animal surface microbiomes, and many animal-associated microbes remain undetected in planktonic microbial communities [START_REF] Larsen | Diversity of the skin microbiota of fishes: evidence for host species specificity[END_REF][START_REF] Chiarello | Environmental conditions and neutral processes shape the skin microbiome of European catfish (Silurus glanis) populations of Southwestern France[END_REF][START_REF] Troussellier | Sustaining Rare Marine Microorganisms: Macroorganisms As Repositories and Dispersal Agents of Microbial Diversity[END_REF]. In addition, marine animals have diverse biological traits that provide specific habitats at their surface, which ultimately favours the proliferation of microbial lineages that are different among different species [START_REF] Chiarello | Skin microbiome of coral reef fish is highly variable and driven by host phylogeny and diet[END_REF].

Surface microbiomes and planktonic microbes form a microbial 'metacommunity' [START_REF] Cleary | The sponge microbiome within the greater coral reef microbial metacommunity[END_REF],

where local communities within it (individual animal microbiomes, as well as planktonic communities) are connected by dispersal of microbes through direct contacts and through the water column. Given the distinct composition of animal surface microbiomes between species, and the diversity of animal surfaces inhabiting coral reefs, surface microbiomes may constitute an important part of the coral reef microbial metacommunity. However, the contribution of animal surface microbiomes to the coral reef microbial diversity is currently unknown.

Coral reefs are facing increasing human pressures (including ocean warming, acidification and overfishing; [START_REF] Hughes | Global warming and recurrent mass bleaching of corals[END_REF][START_REF] Hughes | Double Jeopardy and Global Extinction Risk in Corals and Reef Fishes[END_REF]) inducing an increased risk of extinction of a significant proportion of animal diversity (up to 8% and 10% of coral and fish species; [START_REF] Hughes | Double Jeopardy and Global Extinction Risk in Corals and Reef Fishes[END_REF][START_REF] Mccauley | Marine defaunation: Animal loss in the global ocean[END_REF]). The documented erosion of animal biodiversity as well as the decrease of animal abundance may result in the loss of their associated microbial species. However, the effect of such erosion on microbial diversity has to date not been assessed.

In this study, we sampled surface microbiomes of abundant coral reef animals (e.g. fishes, corals, crustaceans, echinoderms, mollusks and sponges) from the same restricted area over a short period. In so doing we avoided spatial and/or temporal variation of microbial diversity driven by environmental variability. We sampled the surface prokaryotic microbiome of 265 coral reef animals belonging to 74 different taxa, including 32 and 18 genera of teleost fishes and Anthozoa (hard and soft corals, and anemones), respectively, and 12 taxa of crustaceans, echinoderms, mollusks and sponges, from a single coral reef ecosystem (Mayotte lagoon, Indian Ocean). In order to test the hypothesis that surface microbiomes represent a major component of the coral reef microbial metacommunity, we compared the prokaryotic diversity hosted by animals to that of the surrounding planktonic communities. Ultimately, we compared the amount of microbial diversity to global microbial diversity estimates and estimated the erosion of microbes due to human-induced animal exinction.

METHODS

Sampling procedure

Sampling was conducted in November 2015 in Mayotte lagoon shallow (depth <10 meters) barrier and fringing coral reefs (Western Indian Ocean, Supplementary Material SM1-1 and 2). We sampled the most abundant taxa from each of the main animal groups (teleost fishes, Anthozoa, crustaceans, echinoderms, mollusks and sponges) within a radius of 50 m around each site (SM1-3 and 4). Sampling procedure is provided in SM1-5. Briefly, we sampled skin microbiome by collecting surface mucus or swabbing.

Fishes were identified at species level. Corals were identified at genus level. Classification of other invertebrates was made at species level when possible (for crustaceans, starfish, urchins and anemones), or at higher taxonomic levels for a few clades (one sea cucumber, comatules, hermit crabs, brittle stars and giant clams) (SM1-4). A total of 138 fishes were sampled across two sites, as well as 82 colonies of hard and soft corals, gorgonians and anemones (referred collectively as Anthozoa) belonging to 13 genera of Scleractinia, 3 Octocorallia (soft corals and gorgonians) and one anemone species. We also sampled 43 individuals of crustaceans, echinoderms, mollusks and sponges. For each of 6 days of sampling, water samples were collected and filtrated to collect prokaryotic plankton as explained in SM1-5. Prokaryotic diversity was assessed using high-throughput sequencing of the V4 hypervariable region of the 16S rDNA gene, as detailed in SM1-5.

Sequence processing and phylogenetic analyses

Sequence reads were processed using the 'DADA2' R-package version 1.2 and R software v3.4.3 using script provided in Supplementary Material SM1-6. 7% of the 50,237 constructed ASVs were unclassified at this step. In order to define whether they could potentially correspond to remaining mitochondrial sequences, we mapped them onto the Genbank database (NCBI) using the BLASTn alignment tool. 7% of them showed more than 97% identity with a mitochondrial sequence and were removed before computing further analyses.

Sequence number ranged from 7,074 to 56,927 across samples (SM1-4). 7,000 sequences were randomly sub-sampled within each sample in order to correct the uneven sequencing efficiency among samples using "rrarefy" function from 'vegan' R-package version 2.5-5 [START_REF] Dixon | VEGAN, a package of R functions for community ecology[END_REF]. To assess the effect of rarefaction on our results, all subsequent analyses were computed on both rarefied and un-rarefied data. Analyses based on rarefied data are included in the main document, while the ones based on un-rarefied data are included in Supplementary Material SM2. These two approaches provided similar results. Zhang-Huang's coverage estimator [START_REF] Zhang | Turing's formula revisited*[END_REF] was calculated using the 'entropart' R-package version 1.6-1 [START_REF] Marcon | entropart: An R Package to Measure and Partition Diversity[END_REF], using "coverage" function, and averaged 0.982±0.015 across all samples (0.998±0.001 before rarefaction). A phylogenetic tree was obtained by adding the ASV sequences into the GreenGenes phylogenetic tree version 13.8 [21] using SEPP insertion tool [START_REF] Janssen | Phylogenetic Placement of Exact Amplicon Sequences Improves Associations with Clinical Information[END_REF] with default parameters.

Assessing microbial biodiversity

The average surface microbiome of each fish species, Anthozoa genus, or other invertebrate taxa, was computed as the mean relative abundance of each ASV across individuals from the same taxon (SM1-4). Phylogenetic richness of each community was measured using Faith's PD [START_REF] Faith | Conservation evaluation and phylogenetic diversity[END_REF], using "pd" function from 'picante' R-package version 1.8 [START_REF] Kembel | Picante: R tools for integrating phylogenies and ecology[END_REF]. Phylogenetic diversity, taking into account the relative abundance of ASVs, was measured using Allen's index [START_REF] Allen | A New Phylogenetic Diversity Measure Generalizing the Shannon Index and Its Application to Phyllostomid Bats[END_REF] using our own R-function (https://github.com/marlenec/chao, q=1). The evenness of ASVs abundances was measured for each microbial sample using O [START_REF] Bulla | An Index of Evenness and Its Associated Diversity Measure[END_REF], which is robust against richness variation [START_REF] Mouillot | Can We Tell How a Community Was Constructed? A Comparison of Five Evenness Indices for Their Ability to Identify Theoretical Models of Community Construction[END_REF].

Phylogenetic dissimilarities between animal taxa was assessed using the unweigthed and weighted versions of Unifrac index (U-and W-Unifrac), computed using 'GUniFrac' Rpackage version 1.1 [START_REF] Chen | Package 'GUniFrac[END_REF] and were visualized using Principal Coordinates Analysis (PCoA) computed using 'ape' R-package, and boxplots computed using function "boxplot.stats" from 'grDevices' R-package using default parameters.

Statistical tests

Difference in phylogenetic alpha-diversity between plankton and animal surface microbiomes was tested using Kruskal-Wallis tests (KW, 999 permutations) computed with 'vegan' Rpackage. Correlation between fish vulnerability (see "Vulnerability of microbial diversity" hereafter) and its associated microbiome diversity was assessed using Spearman's correlation tests ("cor.test") performed on phylogenetic independent contrasts (PIC) calculated on diversity indices, using the fish phylogenetic tree used before [START_REF] Chiarello | Skin microbiome of coral reef fish is highly variable and driven by host phylogeny and diet[END_REF]. Due to the lower resolution of taxonomic identification of corals in our dataset (at genus level) and the polyphyly of genera in published coral trees [START_REF] Huang | The future of evolutionary diversity in reef corals[END_REF], it was not possible to compute PIC on scleratinians.

Therefore, correlation between coral vulnerability and its associated microbiome diversity was performed using a simple Spearman's correlation test.

Difference in microbial structure between plankton and animal surface microbiomes was tested using permutational multivariate ANOVAs (PERMANOVAs) performed on dissimilarities, using "adonis" function in 'vegan' R-package and 999 permutations. To test if planktonic communities were more variable than surface-associated communities, a permutation analysis of dispersion (PERMDISP) was performed on both indices among planktonic communities and among animal surface microbiomes using "betadisper" provided in 'vegan', with 999 permutations.

Differences between surface microbiomes associated to the three major animal groups (44 teleostean fish species, 17 anthozoan genera and 12 other invertebrates' taxa) were tested using PERMANOVAs. The effect of animal's taxon to its associated surface microbiome was assessed for each animal group (before averaging the microbiome per animal taxon, SM1-3 and 4) using separated PERMANOVAs.

Lastly, in order to identify prokaryotic clades that are different between plankton and animal surface microbiomes, and consistent enriched in all water samples or animal taxa, we performed a LEfSe analysis [START_REF] Segata | Metagenomic biomarker discovery and explanation[END_REF] using water samples and animal taxa as subclasses, with allagainst-all parameter and p-value threshold for significance of 0.05. Then, to identify biomarkers for each animal group (teleostean fishes, Anthozoa and other vertebrates), a LEfSe analysis was performed using these groups as main classes, and the different animal taxa belonging to these groups (fish species, anthozoan genera and other invertebrates' taxa) as subclasses, using the same parameters.

Contribution of surface microbiomes to total microbial diversity

We used two approaches to assess the importance of planktonic vs. animal-associated prokaryotic diversity to total coral reef microbial diversity. We first computed the phylogenetic richness of ASVs that were unique to plankton or to animal surfaces. We then compared the diversity of planktonic and animal surface microbiomes, by randomly picking from 1 to 74 animal taxa and 1 to 35 planktonic samples and then computing the total ASV and phylogenetic richness for each sampling depth. This procedure was performed 100 times.

To get a conservative estimation of the total sampled + un-sampled prokaryotic species richness in our dataset, we first curated the ASVs in our dataset, removing all unclassified ASVs that could not match any sequence in Genbank database. The remaining ASVs were then grouped into 97%-identity Operational Taxonomic Units (OTUs) using "pick_otus.py" function provided in QIIME version 1.9 [START_REF] Caporaso | QIIME allows analysis of high-throughput community sequencing data[END_REF], with default de novo usearch parameter, and OTUs found in less than 2 animal taxa were removed. We obtained 20,021 OTUs from 37,758 curated ASVs. Then, each animal taxon was considered as an independent sampling unit to count the occurrence of each OTU (i.e. the number of sampling units where the OTU was recovered). Estimates of OTU richness were calculated using the estimators provided in 'SpadeR' R-package [START_REF] Chao | SpadeR (species-richness prediction and diversity estimation in R): an R package in CRAN. Program and user's guide[END_REF] using "ChaoSpecies" function and type 2 incidence frequency data option.

Vulnerability of microbial diversity

To assess the vulnerability of reef microbial diversity to the loss of macro-organisms, we simulated an extinction scenario combining the effects of global warming and overfishing.

Macro-organisms taxa were removed proportionally to their respective vulnerability to heat stress for hard corals, and to habitat loss (due to coral bleaching) plus fishing for fishes.

Vulnerability of scleractinian coral genera to global warming was based on their bleaching response in the Western Indian Ocean [START_REF] Mcclanahan | Western Indian Ocean coral communities: bleaching responses and susceptibility to extinction[END_REF]. The genus Isopora, for which we had no data, was excluded from the extinction scenario. Similarly, no data was available for nonscleratinian Anthozoa and for all other invertebrates. There were therefore excluded from the scenario. Vulnerability to fishing [START_REF] Cheung | A fuzzy logic expert system to estimate intrinsic extinction vulnerabilities of marine fishes to fishing[END_REF] was obtained from Fishbase (http://www.fishbase.org/, 2017). Vulnerability to habitat loss due to global change in coral reefs was computed as in Graham et al. [START_REF] Graham | Extinction vulnerability of coral reef fishes[END_REF] using data from Fishbase.org and expert knowledge for input variables. All vulnerability indices are provided in SM1-7, and the script used to simulate such animal diversity extinction and subsequent losses of microbial taxonomic and phylogenetic diversity is available online (https://github.com/marlenec/MicroErosion).

We assessed the vulnerability of prokaryotic diversity hosted by the 44 fish species and 12 genera of scleractinian corals included in the scenario by simulating loss of the 1 to 100% most vulnerable taxa according to their individual vulnerability. At each level of extinction, the percentage of remaining microbial diversity was compared to the one obtained from a random loss of the same number of scleractinian corals and fishes, computed 100 times.

Deviation from this random loss was assessed by computing a P-value, calculated as the rank of the mean diversity value in the 100 replicates of the extinction scenario, among the increasingly sorted diversity values of all 100 replicates of the random scenario. We considered that the deviation from the random scenario was significant when P<0.05, meaning that the diversity value in the observed community was lower than the 5% lowest diversity values following the random loss of animal taxa.

RESULTS AND DISCUSSION

High diversity of animal microbiomes

In our entire dataset made of 74 animal taxa and 35 samples of plankton, prokaryotic diversity hosted by animal surfaces contributed to 95% of total phylogenetic richness (Faith's PD) on rarefied data (Figure 1a andb; un-rarefied data in SM2-1). Individual fish and Anthozoa samples contained slightly more ASVs than 200-mL planktonic samples (SM2-2). A recent study found on average 5 times more 97%-identity bacterial Operational Taxonomic Units (OTUs) in 1L of seawater than in coral mucus [START_REF] Pollock | Coral-associated bacteria demonstrate phylosymbiosis and cophylogeny[END_REF]. Such different results may be due to the contrasting volume of coral microbiome vs. seawater compared, a coral surface of 15-20 cm 2 (see SM1-5) to 0.2 L water samples in our study vs. ~2cm 2 to 1L of seawater in this former study. Similarly, differences in the protocols used (i.e. biomolecular methods and data analysis pipelines) may explain such discrepancies.

Average surface microbiome recovered from each animal taxon (fish species, coral genus, or other invertebrate taxon) was phylogenetically richer and more diverse than a 200-mL water sample (KW on Faith's PD and Allen's index on rarefied and un-rarefied data, P<0.001), with one animal taxon hosting on average 4.9±2.4% of the total branch length of the phylogenetic tree grouping all ASVs recovered in the rarefied dataset, while one 200-mL water sample contained on average only 1.7±0.2% of the total branch length (Figure 1c andd; un-rarefied data in SM2-1). Additionally, 35 randomly chosen average animal microbiomes reached ca. 8-fold higher phylogenetic richness than our 35 water samples (Figure 1a), indicating that at a similar sampling effort, animal taxa host higher prokaryotic diversity compared to seawater.

When considering un-rarefied data, the gap between both types of communities was narrower (SM2-1). Similar results were obtained based on ASV richness (SM2-3).

ASVs unique to animal surfaces (i.e. not detected in plankton) made more than 85% of total phylogenetic richness (Figure 1b, un-rarefied data in SM2-1), demonstrating that most of the prokaryotic phylogenetic richness was associated to animal microbiomes. [START_REF] Hughes | Double Jeopardy and Global Extinction Risk in Corals and Reef Fishes[END_REF].8% of such ASVs were abundant to moderately abundant on animal surfaces, i.e. belonging to the top 20% most abundant ASVs (Figure 2; un-rarefied data in SM2-4). By contrast, only 0.3% of the ASVs unique to plankton belonged to the 20% most abundant ASVs in planktonic samples. These results suggest that a significant portion of animal microbiome is specialized to host-associated lifestyle and may not thrive in the water column, while the most abundant planktonic prokaryotes were also capable to colonize animal skin. Such transient colonization of animal surface microbiomes may be a result of water contamination [START_REF] Sweet | On the Importance of the Microbiome and Pathobiome in Coral Health and Disease[END_REF], or may permit host adaptation to environmental fluctuations [START_REF] Hester | Stable and sporadic symbiotic communities of coral and algal holobionts[END_REF].

Bacterial composition

Bacteria dominated communities, accounting for 99.1±1.8% of sequences. The 18 dominant bacterial classes in animal microbiome are depicted in Figure 3a. 72% of them were also detected among the dominant classes in the whole microbiome of corals [START_REF] Sharp | Season, but not symbiont state, drives microbiome structure in the temperate coral Astrangia poculata[END_REF][START_REF] Apprill | Distinguishing between Microbial Habitats Unravels Ecological Complexity in Coral Microbiomes[END_REF][START_REF] Quigley | In press. Co-dynamics of Symbiodiniaceae and bacterial populations during the first year of symbiosis with Acropora tenuis juveniles[END_REF], and 61% and 50% were also detected on temperate fish skin and on tropical fish gills, respectively [START_REF] Minniti | The Skin-Mucus Microbial Community of Farmed Atlantic Salmon (Salmo salar)[END_REF][START_REF] Pratte | The gills of reef fish support a distinct microbiome influenced by host-specific factors[END_REF]. Two classes, Gracilibacteria and Campylobacteria, were not reported to be associated to animals in the aforementioned studies. Gracilibacteria belongs to the Candidate Phyla Radiation (CPR), containing ultra-small bacteria that are recovered from diverse environments and have a probable symbiotic lifestyle [START_REF] Méheust | The distinction of CPR bacteria from other bacteria based on protein family content[END_REF]. Campylobacteria contained mostly the genus Arcobacter in our study (up to 8% of abundance). This genus usually inhabits the human or animal gastrointestinal system, though free-living strains have been isolated in various environments [START_REF] Pérez-Cataluña | Revisiting the Taxonomy of the Genus Arcobacter: Getting Order From the Chaos[END_REF]. This genus has been isolated from coral disease lesions [START_REF] Sunagawa | Bacterial diversity and White Plague Disease-associated community changes in the Caribbean coral Montastraea faveolata[END_REF][START_REF] Meyer | Microbial Community Shifts Associated With the Ongoing Stony Coral Tissue Loss Disease Outbreak on the Florida Reef Tract[END_REF]. It has also been recovered from corals exposed to fish farm effluents and in thermally-stressed corals [START_REF] Garren | Resilience of Coral-Associated Bacterial Communities Exposed to Fish Farm Effluent[END_REF][START_REF] Shiu | Dynamics of coral-associated bacterial communities acclimated to temperature stress based on recent thermal history[END_REF]. Here, while the corals were apparently healthy and sampled far from coastal cities (SM1-1), the high temperatures at the time of sampling (SM1-2), together with a potential contamination of the lagoon by human faeces due to the absence of effluent treatment in Mayotte [START_REF] Ph | Coastal environment assessment procedure for sustainable wastewater management in tropical islands: the Mayotte example[END_REF] may explain the presence of this genus.

Structure of prokaryotic communities recovered on animal surfaces was significantly distinct from plankton (PERMANOVA on W-Unifrac on rarefied data, P=0.001, R 2 =0.29, Figure 3a, b andc, un-rarefied data and U-Unifrac in SM2-5 and 6). Plankton was mostly enriched in Alphaproteobacteria (especially SAR11 and SAR86 clades), Cyanobacteria (especially Prochlorochoccus and Synechococcus), and the actinobacterial family Actinomarinaceae (Figures 3a andSM2-6 and7). All these clades are abundant and widely distributed marine photoautotrophs and photoheterotrophs displaying small cell sizes and genomic reduction [START_REF] Burkill | 1993 Synechococcus and its importance to the microbial foodweb of the northwestern Indian Ocean[END_REF][START_REF] Dupont | Genomic insights to SAR86, an abundant and uncultivated marine bacterial lineage[END_REF][START_REF] Ghai | Metagenomics uncovers a new group of low GC and ultra-small marine Actinobacteria[END_REF][START_REF] Grébert | Light color acclimation is a key process in the global ocean distribution of Synechococcus cyanobacteria[END_REF][START_REF] Kent | Global biogeography of Prochlorococcus genome diversity in the surface ocean[END_REF], that may be selected by the very oligotrophic conditions of surface ocean [START_REF] Giovannoni | Implications of streamlining theory for microbial ecology[END_REF]. The presence of such taxa on our sites suggests that the reefs were well preserved from coastal eutrophication at the time of sampling.

By contrast, animal surfaces were mostly enriched in Gammaproteobacteria (especially Endozoicomonas), Firmicutes (especially Clostridia), Betaproteobacteriales (especially Burkholderiaceae), the alpha-proteobacterial Rhizobiales and Sphingomonadaceae, and Verrucomicrobia. Such clades have been previously identified in temperate and tropical marine fish skin, gut and gill microbiomes [START_REF] Minniti | The Skin-Mucus Microbial Community of Farmed Atlantic Salmon (Salmo salar)[END_REF][START_REF] Pratte | The gills of reef fish support a distinct microbiome influenced by host-specific factors[END_REF][START_REF] Chiarello | High diversity of skin-associated bacterial communities of marine fishes is promoted by their high variability among body parts, individuals and species[END_REF][START_REF] Neave | Diversity and function of prevalent symbiotic marine bacteria in the genus Endozoicomonas[END_REF][START_REF] Egerton | The Gut Microbiota of Marine Fish[END_REF][START_REF] Sullam | Environmental and ecological factors that shape the gut bacterial communities of fish: a meta-analysis[END_REF][START_REF] Wang | Intestinal microbiota of healthy and unhealthy Atlantic salmon Salmo salar L. in a recirculating aquaculture system[END_REF], and at the surface or inside marine invertebrates [START_REF] Carlos | Bacterial communities and speciesspecific associations with the mucus of Brazilian coral species[END_REF][START_REF] Neave | Diversity and function of prevalent symbiotic marine bacteria in the genus Endozoicomonas[END_REF][START_REF] Cooney | Characterization of the bacterial consortium associated with black band disease in coral using molecular microbiological techniques[END_REF][START_REF] Maravić | Occurrence and antibiotic susceptibility profiles of Burkholderia cepaciacomplex in coastal marine environment[END_REF]. Endozoicomonas, especially, is associated to a wide range of hosts, from fish to hard and soft corals, sponges and tunicates, and is hypothesized to play a significant role in host's nutrition and health [START_REF] Neave | Diversity and function of prevalent symbiotic marine bacteria in the genus Endozoicomonas[END_REF]. Particularly, Endozoicomonas genomes show enrichment in several functions that may help to cooperate with various types of hosts (e.g. protein secretion and carbohydrate transport), but also potential functional specialization depending on their hosts [START_REF] Neave | Endozoicomonas genomes reveal functional adaptation and plasticity in bacterial strains symbiotically associated with diverse marine hosts[END_REF], that might explain the ubiquity of such genus on the wide diversity of animals studied here. To confirm this hypothesis, such taxonomic assessment of animal-associated microbiomes should be completed by studies assessing the functions that are necessary for bacteria to thrive on marine hosts.

High dissimilarity between animal microbiomes

The high phylogenetic diversity of animal surface microbiomes was paired with a 2.3 times higher variability among those microbiomes than among planktonic samples (PERMDISP on W-Unifrac on rarefied data, P<0.001, Figure 3c andSM2-5). The three major animal groups sampled, i.e. teleostean fishes, Anthozoa and other invertebrates, hosted significantly different prokaryotic communities at their surface, with the distinction between such groups explaining between 5% and 11% of variability (PERMANOVAs, P<0.001, SM2-8). However no significant biomarker was identified using LEfSe analysis for each of these groups, indicating that there is no consistently enriched bacterial clade in all animal taxa of these groups, as highlighted by the high dissimilarity between taxa within each group (Figure 3b andc, SM2-5).

Among each main animal group, there was a significant effect of animal taxon on surfaceassociated microbiome structure and composition (PERMANOVAs, SM2-8). Interestingly, while the larger animal groups explained up to 11% of microbiome dissimilarity, the effect of such smaller taxa explained from 34% (for coral genera) to 49% (for fish species) of surface microbiome variability (PERMANOVAs on rarefied data, P<0.001; SM2-8).

While the species-specificity of marine animal skin microbiome has already been reported [START_REF] Chiarello | Skin microbiome of coral reef fish is highly variable and driven by host phylogeny and diet[END_REF], here we report that this interspecific variability within a clade is as high as between different clades that diverged ~800 Mya (Figures 3c andSM2-5, divergence time estimate between Teleostei and Anthozoa according to http://www.timetree.org/). This finding suggests that the correlation between host phylogenetic relationships and microbiome composition, a pattern called 'phylosymbiosis', that has been evidenced in numerous animal models including microbiomes of tropical fish skin, sponges and coral skeleton [START_REF] Chiarello | Skin microbiome of coral reef fish is highly variable and driven by host phylogeny and diet[END_REF][START_REF] Pollock | Coral-associated bacteria demonstrate phylosymbiosis and cophylogeny[END_REF][START_REF] Easson | Phylogenetic signal in the community structure of host-specific microbiomes of tropical marine sponges[END_REF], may be unobservable at deeper phylogenetic level due to the very large phenotypic differences between the hosts that would saturate this signal.

Exceptional reef microbial diversity

As a consequence of the coupled high diversity and high variability of animal surface microbiomes, the prokaryotic diversity sampled on animal surface microbiomes in this study is far from reaching an asymptote (Figures 1a, SM2-1, SM2-3). We estimated that the total sampled and un-sampled bacterial diversity associated to the subset of reef animals we sampled would range from 8,700 to more than 20,000 97%-identity bacterial OTUs, respectively on rarefied and un-rarefied data (SM2-9).

Recent estimate of world's bacterial diversity predicted that there exists 0.8-1.6 million prokaryotic OTUs worldwide [START_REF] Louca | A census-based estimate of Earth's bacterial and archaeal diversity[END_REF]. Our richness estimates correspond to 0.5% to 2.5% of such global diversity. This is striking, given that coral reefs occupy less than 0.1% of surface worldwide, with southwestern Indian Ocean coral reefs making 1.8% of that surface (0.001% of global surface, www.reefbase.org/). Here, we based our estimates on carefully curated ASVs grouped as 97%-identity OTUs, which prevented any overestimation of prokaryotic richness at a local scale [START_REF] Xue | Impact of DNA Sequencing and Analysis Methods on 16S rRNA Gene Bacterial Community Analysis of Dairy Products[END_REF]. In addition, we only sampled a <7% subset of animal diversity in Mayotte's lagoon, hosting more than 700 fish species [START_REF] Wickel | Composition et structure des peuplements ichtyologiques marins de l'île de Mayotte (sud-ouest de l'océan Indien)[END_REF], 57 soft corals [START_REF] Schleyer | The soft coral fauna (Octocorallia: Alcyonacea) of Mayotte[END_REF], 22 sea cucumbers [START_REF] Eriksson | Sea cucumber (Aspidochirotida) community, distribution and habitat utilization on the reefs of Mayotte, Western Indian Ocean[END_REF], more than 200 scleractinian species and subspecies, 13 Asteroideae, 36 ascidians, 56 bivalves and 23 Ophiuroideae [START_REF]INPN -National Inventory of Natural Heritage[END_REF]. We also did not sample any species from other phylogenetically contrasted clades such as sharks and rays, sea turtle and mammal,, and vegetal species inhabiting Mayotte's lagoon. Likewise, we did not sample the microbes living within the tissue and skeleton of corals nor those living in fish guts. Our claim is that coral reef communities, just as they host a large portion of marine macrobial diversity compared to their surface [START_REF] Fisher | Species Richness on Coral Reefs and the Pursuit of Convergent Global Estimates[END_REF], may also support a significant proportion of global marine prokaryotic diversity. More extensive sampling on the thousands of coral reef animals on different coral reefs will allow refining the estimates provided here.

Vulnerability of reef microbial diversity

The loss of an animal species due to environmental disturbances at a given location induces the loss of its associated unique microbial diversity. We classified fish species and scleratinian genera depending on their respective vulnerability, to the combined overfishing and habitat loss in the case of fish, and ocean warming in the case of corals (see Methods and SM1-7). There was no correlation between animal vulnerability and microbial diversity at its surface (Spearman correlation tests, P>0.05). Microbial diversity erosion following macroscopic extinction scenarios revealed that the loss of the 50% most vulnerable coral and fish species for which we had vulnerability data would induce a loss of ca. 28 to 29% of ASVs (SM2-10) and 23% of phylogenetic richness (Figure 4a and SM2-11). Such lower phylogenetic erosion indicates a moderate phylogenetic redundancy between animal surfaceassociated ASVs. The slope of microbial diversity extinction was only slightly steeper with increasing loss of macroscopic species (Figure 4b and SM2-11). Accordingly, levels of prokaryotic diversity loss were not significantly different from that expected under a random extinction scenario, because the most vulnerable animal species and less vulnerable ones host partially redundant prokaryotic diversity.

To our knowledge, no quantified vulnerability measures exist for invertebrates other than sessile Anthozoa, so we did not include them in our extinction scenario. In our dataset, microbiomes of invertebrates other than Anthozoa showed the highest diversity and variability (Figure 3c, SM2-2, SM2-5), suggesting that the loss of such warming-sensitive taxa [START_REF] Przeslawski | Beyond corals and fish: the effects of climate change on noncoral benthic invertebrates of tropical reefs[END_REF], as well as those targeted by humans [START_REF] Polovina | The Role of Benthic Habitat, Oceanography, and Fishing On the Population Dynamics of the Spiny Lobster, Panulirus Marginatus (Decapoda, Palinuridae), in the Hawaiian Archipelago[END_REF], would induce a more severe erosion of coral reef microbial diversity than the one simulated here. Our results should be further completed by an assessment of the functional erosion that may result from anthropic activities, as such unique phylogenetic diversity in animal microbiomes may also host unique microbial functions in coral reef ecosystems [START_REF] Martiny | Microbiomes in light of traits: A phylogenetic perspective[END_REF]. Finally, our scenario did not account for potential direct effects of anthropic stressors (warming, acidification) that could alter the diversity and functions of microbiomes [START_REF] Zaneveld | Overfishing and nutrient pollution interact with temperature to disrupt coral reefs down to microbial scales[END_REF].

CONCLUSIONS

Reef animals macro-organisms host a high and unique diversity of microbes at their surface.

Hence, the thousands species living in coral reef ecosystems may support a substantial part of marine microbial diversity. For now, roles of animal surface microbiomes for ecosystem functioning are only partially described, but could be essential (e.g. production and degradation of dimethylsulfoniopropionate, a crucial molecule in sulphur cycling; [START_REF] Bourne | Insights into the Coral Microbiome: Underpinning the Health and Resilience of Reef Ecosystems[END_REF]). Future studies should investigate to which extent these unique and vulnerable microbial lineages present on animals contribute to coral reef functioning and possible consequence of their loss in the Anthropocene. (a) Mean (±SD) of remaining prokaryotic phylogenetic richness on the studied coral reef for a given proportion of animal taxa lost according to the simulated erosion scenario (100 replicates). When 100% of coral and fish species included in the scenario are lost, the remaining microbial phylogenetic richness corresponds to the one of prokaryotic communities associated to plankton and animal taxa that were not included in the extinction scenario (i.e. 24% of taxa, corresponding to Isopora, soft corals, gorgonians, anemone and all nonanthozoan invertebrates). Scenario simulating a random loss of fishes and corals (i.e. species removed independently from their vulnerability) is illustrated with the grey area representing the range of remaining phylogenetic richness among 100 replicates.

(b) Mean (solid line) ± SD (shaded area) of slopes of phylogenetic richness loss calculated at each level of extinction on all 100 replicates. The same analyses based on un-rarefied data and on ASV richness are provided in SM2-10 and 11.

FIGURESFigure 1 .

 1 FIGURES

Figure 2 .

 2 Figure 2. Abundance of ASVs in animal surface microbiomes and plankton. (a and b) Average rank-abundance curves obtained from surface microbiomes of (a) animal surface microbiomes and (b) planktonic communities. Vertical dotted lines represent 5, 10, 20 and 50% threshold for most abundant ASVs. The average evenness of ASVs abundances (Bulla's O) in each compartment is indicated on the corresponding plot. (c) Rank of abundances of ASVs unique to animal surface microbiomes or to plankton within respective microbial communities. The same figure based on un-rarefied data is provided in SM2-4.

Figure 3 .

 3 Figure 3. Dissimilarity in taxonomic and phylogenetic structure of microbial communities from plankton or animal surfaces (a) Dominance of 18 prokaryotic classes for animal surface microbiomes (averaged by fish families, Anthozoa genera and other invertebrates' taxa) and for plankton (averaged across all 35 planktonic communities). (b) Microbial communities are plotted on the two first axes of a PCoA computed on W-Unifrac. (c) Intra-and inter-group W-Unifrac. Results based on unrarefied data and on U-Unifrac are provided in SM2-5 and 6.

Figure 4 .

 4 Figure 4. Vulnerability of coral reef microbial phylogenetic richness to loss of fishes and scleratinian corals.

Acknowledgements

We thank Emily Darling and Jérémie Vidal-Dupiol for helping us identify hard corals, and Frederic Ducarme for his help identifying echinoderms.

Funding

This project was funded by the TOTAL Foundation (MICMAC projet BIO-2015-135-49, #138295). The funders had no role in study design, sampling and analysis decision to publish, or preparation of the manuscript.

Data accessibility

Sequence data is available in the NCBI Sequence Read Archive database under the biosample numbers SRS2702344-SRS2702519 and SRS4077375-SRS4077501. Bacterial ASV table and associated metadata and sequences are available on DRYAD repository (https://doi.org/10.5061/dryad.wh70rxwjw).

Competing interests

The authors declare that they have no competing interests.

Authors' contribution

MC, TB and SV contributed to the conceptualization of the study. MC, CB, NAJG, TB, and SV contributed to the methodology. MC, J-CA, CB, TC, CXRO, FR, ES, and SV helped in the investigation. MC conducted the analyses and writing of the original draft. MC, J-CA, YB, CB, TC, NAJG, FR, ES, TB, and SV contributed to writing, reviewing, and editing of the manuscript. TB, MC and SV helped in the acquisition of funding. TB and SV supervised the study. All authors read and approved the final manuscript.


Yitao Wang

Miss Shuen Wei
email: shuen.wei@unsw.edu.au

R Cicconi

Yuta Tsuji

Masahiro Shimizu

Yasuhiko Shimotsuma

Kiyotaka Miura

Gang-Ding Peng

Daniel R Neuville

Bertrand Poumellec

M R Cicconi

G.-D Peng

M Lancry

Femtosecond laser direct writing in SiO 2 -Al 2 O 3 binary glasses and thermal stability of Type II permanent modifications

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Since the discovery of the laser-induced periodic surface structure (LIPSS) by Birnbaum nearly a half-century ago [START_REF] Birnbaum | Semiconductor surface damage produced by ruby lasers[END_REF] , many interesting researches have been carried out from the experimental and theoretical perspectives [START_REF] Buividas | Surface and bulk structuring of materials by ripples with long and short laser pulses: Recent advances[END_REF] . One of the intriguing phenomena induced by the femtosecond (fs) laser pulses is the formation of the polarization-dependent sub-wavelength nanostructures [START_REF] Shimotsuma | Self-organized nanogratings in glass irradiated by ultrashort light pulses[END_REF] . As opposed to the LIPSS written onto the surface of various materials (e.g., metals, semi-conductors, dielectrics), formation of nanogratings within the bulk has been observed mostly in silicate and germanates glasses with a limited alkali content [START_REF] Asai | Systematic control of structural changes in GeO 2 glass induced by femtosecond laser direct writing[END_REF][START_REF] Richter | Laser induced nanogratings beyond fused silica-periodic nanostructures in borosilicate glasses and ULE™[END_REF][START_REF] Fedotov | Direct writing of birefringent elements by ultrafast laser nanostructuring in multicomponent glass[END_REF][START_REF] Lancry | Nanogratings formation in multicomponent silicate glasses[END_REF][START_REF] Bricchi | Form birefringence and negative index change created by femtosecond direct writing in transparent materials[END_REF][START_REF] Lotarev | Light-driven nanoperiodical modulation of alkaline cation distribution inside sodium silicate glass[END_REF] . In the case of SiO 2 or GeO 2 glasses, self-organized nanogratings, which are composed of stripe-like regions with oxygen deficiencies including nanovoids [START_REF] Lancry | Ultrafast nanoporous silica formation driven by femtosecond laser irradiation[END_REF][START_REF] Lancry | Nanoscale femtosecond laser milling and control of nanoporosity in the normal and anomalous regimes of GeO 2 -SiO 2 glasses[END_REF] , are perpendicularly aligned to the laser polarization.

The very high intensity fields achievable using femtosecond laser pulses can lead to highly localized plasma ionization and deoxygenation, resulting in strong sub-diffraction interference effects between the plasma and the optical field, generating complex condensed structures such as nanogratings. These are based on glass decomposition that resolidifies into a nanoporous [START_REF] Lancry | Ultrafast nanoporous silica formation driven by femtosecond laser irradiation[END_REF] , usually silicon-rich, structure, creating a strong and highly stable refractive index contrast [START_REF] Bricchi | Extraordinary stability of anisotropic femtosecond direct-written structures embedded in silica glass[END_REF] .

Based on such photo-induced structures showing localized birefringence in glass, various applications ranging from embedded micro-reflectors, retardation plates, microfluidic channels, to rewritable 5D optical storage, polarization imaging have been investigated as review in Refs. 13, 14 .

Besides these applications mentioned above, nanogratings in SiO 2 due to its remarkable thermal stability up to ~ 1200°C [START_REF] Bricchi | Extraordinary stability of anisotropic femtosecond direct-written structures embedded in silica glass[END_REF][START_REF] Li | Fiber Bragg gratings with enhanced thermal stability by residual stress relaxation[END_REF] , they are now extensively studied for applications like long lifetime optical data storage and for sensing applications in extreme environments. For example, Type II fs-IR modifications which are attributed to the formation of self-organized nanogratings made of oxide decomposition [START_REF] Lancry | Ultrafast nanoporous silica formation driven by femtosecond laser irradiation[END_REF][START_REF] Lancry | Nanoscale femtosecond laser milling and control of nanoporosity in the normal and anomalous regimes of GeO 2 -SiO 2 glasses[END_REF] , demonstrate remarkable thermal stability up to ~ 1000°C for 150 hours after a stabilization for 1 hour at 1000°C [START_REF] Grobnic | Long-term thermal stability tests at 1000°C of silica fibre Bragg gratings made with ultrafast laser radiation[END_REF] , while operating for 100 hours at 1050°C reveals a slight (5%) intensity decay. This is likely associated with thermal relaxation of the bulk glass at these temperatures. It should be noted that, in this work, we categorize the type of modifications from the perspective of the nature of refractive index modifications induced by IR femtosecond laser irradiation. More specifically, Type I IR-fs modification is featured by an isotropic growth of the refractive index with respect to the non-irradiated regime. The Type II IR-fs modification, characterized by a high level of anisotropic index change [START_REF] Bricchi | Form birefringence and negative index change created by femtosecond direct writing in transparent materials[END_REF] and resulting birefringence, is typically induced by the presence of nanogratings. As relates to applications, fs-FBGs have recently been tested as temperature sensors for monitoring fluidized bed combustors [START_REF] Walker | Entrained-flow gasifier and fluidized-bed combustor temperature monitoring using arrays of fs-IR written fiber Bragg gratings[END_REF] , as well as for radiation resistant temperature sensors [START_REF] Morana | Radiation tolerant fiber Bragg gratings for high temperature monitoring at MGy dose levels[END_REF][START_REF] Morana | Dependence of the Voids-Fiber Bragg Grating Radiation Response on Temperature, Dose, and Dose Rate[END_REF] . The refractive change is 3D localized and involves significant stress-induced changes around the irradiated regions. For this reason, the higher temperature regime is limited by the thermal response of both the surrounding regions and the fiber itself, which has not been relaxed prior to application. Recent results indicate the need of >30mol% Al 2 O 3 [START_REF] Grobnic | Type I and II Bragg gratings made with infrared femtosecond radiation in high and low alumina content aluminosilicate optical fibers[END_REF] to improve FBG thermal stability above standard fibers like SMF28 from Corning. To go beyond the thermal stability limit [START_REF] Grobnic | Long-term thermal stability tests at 1000°C of silica fibre Bragg gratings made with ultrafast laser radiation[END_REF] imposed by standard SiO 2 -based optical fibers, FBGs can be inscribed in SiO 2 -Al 2 O 3 optical fibers using femtosecond laser direct writing [START_REF] Grobnic | Type I and II Bragg gratings made with infrared femtosecond radiation in high and low alumina content aluminosilicate optical fibers[END_REF][START_REF] Elsmann | High temperature sensing with fiber Bragg gratings in sapphire-derived all-glass optical fibers[END_REF][START_REF] Cavillon | Overview of high temperature fibre Bragg gratings and potential improvement using highly doped aluminosilicate glass optical fibres[END_REF] . The doping that determines the optical fiber core soften the glass far too much and so are not directly involved in the high temperature processing that allows gratings to operate at higher temperatures. The usual dopants like Germanium (Ge), Fluorine (F) or Boron (B) in the fiber core determine the high temperature processing. Therefore, most commercial fibers will be unlikely to be designed for long-term operation above 1000°C [START_REF] Grobnic | Long-term thermal stability tests at 1000°C of silica fibre Bragg gratings made with ultrafast laser radiation[END_REF] W CO 2 laser via a ZnSe lens (f = 254mm). To ensure homogeneity of the melt, the temperature was kept above the melting point for tens of seconds. Then, the melt was rapidly cooled by turning off the laser power while gas levitating. Colorless and transparent spherical samples with a diameter of approximately 1-2 mm were obtained. Imperfections, such as bubbles, would interrupt laser propagation, thus, hot fully homogeneous sphere were melted again. The glass phases of all prepared samples were verified by Cu K X-ray diffraction (XRD, Rigaku;

RINT-2500HFK/PC) and SEM-EDS chemical analysis. Volumetric mass density (which will be referred to as density for short) of all samples was measured at room temperature by Archimedean method, using toluene as an immersion liquid. The relation between these weights and density and temperature of toluene is well known. For each composition, measurements were performed on five different samples.

Raman spectra of the samples were recorded at room temperature with a T64000

Jobin-Yvon-Horiba® spectrometer equipped with an Olympus® microscope. where B is the linear birefringence (n e -n o ) and L is the length of the birefringent object being measured. The de Sénarmont compensator couples a highly precise quarter wavelength birefringent quartz plate with a 180º rotating analyzer to provide retardation measurements having an accuracy that approaches one thousandth of a wavelength.

Results

Density measurement of SiO 2 -Al 2 O 3 samples

Figure 1 shows the evolution of the density of the SiO 2 -Al 2 O 3 samples for different Al 2 O 3 contents. Data from the literature [START_REF] Okuno | Structure of SiO 2 -Al 2 O 3 glasses: Combined X-ray diffraction, IR and Raman studies[END_REF][START_REF] Ando | Boson peak, heterogeneity and intermediate-range order in binary SiO 2 -Al 2 O 3 glasses[END_REF][START_REF] Rosales-Sosa | Crack-resistant SiO 2 -Al 2 O 3 glasses[END_REF] are reported for the sake of comparison. There is a clear trend where density increases as alumina content increases. From this graph, it is intuitive that the densities of our home-made SiO 2 -Al 2 O 3 samples are consistent with the literature. The standard deviations shown in Figure 1 result from the measurements for five pellets (10 measurements for each pellet) with the same target composition. It can be seen that deviation becomes gradually stronger when the pellet contains more alumina. It might be related to the increasing difficulty to vitrify the glass, which likely results in nanoscale phase separation and voids in the high-alumina-containing samples.

Raman spectra of SiO 2 -Al 2 O 3 samples

Raman spectra of SiO 2 -Al 2 O 3 samples with different concentrations of aluminum oxide (namely 20%, 30%, 40%, and 50% mole of Al 2 O 3 ) are reported in Figure 2, along with the spectrum of Suprasil® CG glass, used as reference. The most intense contribution is located around 430 cm -1 (R band) and is associated to T-O-T symmetric stretching modes (T represents the centered tetrahedron cation) [START_REF] Losq | The role of Al 3+ on rheology and structural changes in sodium silicate and aluminosilicate glasses and melts[END_REF] . By increasing the Al 2 O 3 content, there is a clear intensity decrease of this band, related to both variations of the number of SiO 4 tetrahedra as well as to variations of T-O-T inter-tetrahedral angles and T-O average distances [START_REF] Okuno | Structure of SiO 2 -Al 2 O 3 glasses: Combined X-ray diffraction, IR and Raman studies[END_REF] . The sharp peaks, also called D 1 and D 2 defect lines, at around 490 and 600 cm -1 , are ascribed to the breathing modes of 4-and 3-membered rings, respectively [START_REF] Galeener | Planar rings in glasses[END_REF] . According to Figure 2, both peak intensities relatively decrease with a higher content of alumina, which indicates that the addition of alumina causes modifications of the ring statistic in the silica glass network [START_REF] Okuno | Structure of SiO 2 -Al 2 O 3 glasses: Combined X-ray diffraction, IR and Raman studies[END_REF][START_REF] Ando | Boson peak, heterogeneity and intermediate-range order in binary SiO 2 -Al 2 O 3 glasses[END_REF] . In the mid-frequency area, the asymmetric band near 800 cm -1 results from the motion of Si atoms in their tetrahedral oxygen cage [START_REF] Mcmillan | Structural studies of silicate glasses and melts-applications and limitations of Raman spectroscopy[END_REF] , and slightly decreases in intensity and move toward lower wavenumbers upon addition of Al 2 O 3 . This decrease could be associated to a decrease of Si-BO (Silicon-bridging oxygen).

The high frequency region (HF: 850 -1300 cm -1 ) shows bands related to the Si-O asymmetric stretching vibrations. The HF envelop can be studied by using mathematical function, and in the case of pure SiO 2 glass, three Gaussians can be used to represents the Si centered tetrahedra connected with four bridging oxygens (at ~ 1060 cm -1 , ~1155 cm -1 and ~1200 cm -1 ).

The HF region of the SiO 2 -Al 2 O 3 samples has been studied as well by using mathematical functions, and Figure 2b-e show the Gaussian decomposition of the 850-1300 cm -1 frequency region, and the necessity of four components in order to reproduce the envelope. Indeed, besides the three high frequency bands described for SiO 2 , the addition of alumina in the silica glass leads to the rise of an additional contribution at ~ 975 cm -1 , which increases in intensity by increasing Al 2 O 3 . Furthermore, the band at ~1155 cm -1 shifts toward lower frequencies and increases in intensity upon addition of alumina, and this can be related to the stabilization of 4-fold or 5-fold coordinated Al 3+ units, and the formation of Si-O-Al bonds. Indeed because of the high amount of Al 2 O 3 , besides the presence of AlO 4 tetrahedra, it is expected the presence of higher coordinated species (Al 3+ 5-fold and/or 6-fold coordinated), which would cause the formation of non-bridging oxygens, and strong modifications in the glass connectivity. In particular based on the literature [START_REF] Mcmillan | Vibrational spectroscopy of silicate liquids and glasses[END_REF][START_REF] Neuville | Structure of Mg-and Mg/Ca aluminosilicate glasses: 27Al NMR and Raman spectroscopy investigations[END_REF] , we expect that around 50% of Al are 5-fold coordinated in these glasses. This results in a depolymerization of the silica network (in agreement with the changes of the Boson peak at low frequency) and to the creation of Q n-1 species in agreement with the low frequency shift.

Writing kinetics of Type-II modifications in SiO 2 -Al 2 O 3 samples

Figure 3 shows the measurements of the retardance R for all investigated pellets with different compositions as a function of the laser pulse energy in µJ/pulse. Note we added the results obtained in Suprasil® CG glass (SiO 2 ) as a reference here. Above the Type II threshold, optical properties of the irradiated regions are modified. The average refractive index usually decreases, and the refractive index contrast continues to maintain even after a high temperature processing (typically an annealing for a few hours at 1000°C) in SiO 2 [START_REF] Bricchi | Extraordinary stability of anisotropic femtosecond direct-written structures embedded in silica glass[END_REF] . Moreover, a strong linear birefringence (mostly attributed to a form birefringence) is observed and can be easily detected using any birefringence imaging system.

Analysis of the curves shown in Figure 3 indicates that all samples exhibit a similar trend in their writing kinetics. Note that the threshold T1 [START_REF] Poumellec | Modification thresholds in femtosecond laser processing of pure silica: review of dependencies on laser parameters[END_REF] , related to the formation of permanent index changes without form birefringence, is about 0.3 µJ as we can observe a contrast in natural light but not between crossed polarizers. We did not observe any variation of T1 with the increasing content of Al 2 O 3 in the investigated range. For higher pulse energy, occurrence of form birefringence was revealed using the full order waveplate technique, which allows detecting the slow/fast axis orientation of the photo-induced birefringence. Since we observed a 90° rotation of the slow axis orientation when switching from Xx to Xy writing configuration, we can attest the formation of orientable birefringence that is usually related to the formation of nanogratings [START_REF] Fedotov | Direct writing of birefringent elements by ultrafast laser nanostructuring in multicomponent glass[END_REF][START_REF] Bricchi | Form birefringence and negative index change created by femtosecond direct writing in transparent materials[END_REF] .

Therefore, it was observed that the threshold T2 [START_REF] Poumellec | Modification thresholds in femtosecond laser processing of pure silica: review of dependencies on laser parameters[END_REF]

Thermal stability of Type-II IR-fs modifications in SiO 2 -Al 2 O 3 samples

To investigate the thermal stability of the written Type II modifications, the samples were heat-treated following Δt = 30min step isochronal annealing up to extreme temperatures to observe the evolution in their birefringence. In this context, we have thus monitored retardance R (which is related to the birefringence through the length of the object) at room temperature after each annealing step. The retardance was normalized relative to its initial value at room T i.e. Some typical characteristics of normalized R norm (Δt, T) can be observed from the Figure 4, which typically reveals at least three different erasure mechanisms, which are hypothesized and discussed in the next section. However, they have different trends and contributions for each chemical composition. For both Borofloat® 33 and ULE®, the decay starts after the heat-treatment at 300°C. Typically R norm decreases smoothly until 600°C corresponding to a 20% decay. Then the decline is accelerated for higher temperatures until the laser tracks are not visible under polarizing optical microscope. This corresponds to full erasure after a 30min thermal treatment at 650°C in Borofloat® 33 and 1025°C in ULE® glass. These values are quite close to their respective annealing points T a : 652°C for Borofloat® 33 and 1000°C for ULE®.

R norm (Δt, T)= R(Δt, T) / R(0, 25°C

Note the temperatures mentioned here are dependent on the duration of the isochronal plateau and a longer duration will shift down this "full erasure" temperature, which is somehow at the image of the glass transition temperature range, and revealing in such a way that the erasure mechanisms are in fact distributed [START_REF] Poumellec | Kinetics of thermally activated physical processes in disordered media[END_REF] .

On the contrary, the R norm of both GeO glass melted within a gold image furnace and quenched using twin roller technique [START_REF] Nogami | Hydrogen Gas Reaction with Eu 3+ Doped SiO 2 -Al 2 O 3 Glasses[END_REF] .

Finally, the highest temperature resistance can be found for 50SiO 2 -50Al 2 O 3 pellet and SiO 2 glasses. They show similar trends, and initially the R norm value increases significantly (typ. 30%) above 550°C to reach a maximum around 650°C in SiO 2 and 800°C in 50SiO 2 -50Al 2 O 3 . Then, similarly to the other samples, the R norm value starts to decrease slowly for temperature higher than 800°C. In SiO 2 , this feature is well correlated with the structural relaxation of densified silica formed within the nanograting regime [START_REF] Bellouard | Scanning thermal microscopy and Raman analysis of bulk fused silica exposed to low-energy femtosecond laser pulses[END_REF] that as confirmed by the three and four-folds rings anneal out at the range of 700-900°C [START_REF] Zhang | Wavelength response and thermal stability of embedded nanograting structure light attenuator fabricated by direct femtosecond laser writing[END_REF][START_REF] Witcher | Thermal annealing of femtosecond laser written structures in silica glass[END_REF] . Finally, the further increase in the isochronal annealing temperature above 1100°C leads to a very steep decrease of the birefringence, and the R norm value drops to zero at about 1225°C in both SiO 2 and 50SiO 2 -50Al 2 O 3 samples.

Discussion

Typically, R norm (Δt, T) decreases smoothly until 600°C corresponding to a 20% decay in Borofloat® 33 and ULE® glasses whereas it does not change significant in SiO 2 , GeO 2 -SiO 2 and SiO 2 -Al 2 O 3 samples This indicates that the contribution of point defects centers (E', ODC, NBOHC) to the refractive index contrast of the nanogratings themselves remain quite limited. As another example waveguide formed in silica with an infrared femtosecond laser [START_REF] Saliminia | Waveguide writing in silica glass with femtosecond pulses from an optical parametric amplifier at 1.5 µm[END_REF] showed photo-induced absorption peaks at 213nm and 260nm corresponding to the respective center defects E 'and NBOHC. However, most of these two defects were completely erased after annealing at 400°C, although the waveguide retained its guiding properties up to 900°C. As a result, color centers are unlikely to have played a strong role in the refractive index change [START_REF] Saliminia | Waveguide writing in silica glass with femtosecond pulses from an optical parametric amplifier at 1.5 µm[END_REF] .

Other results lead to the conclusion that the thermal stability of colored centers produced in borosilicate and silica glasses is not compatible with that of the change in refractive index [START_REF] Streltsov | Study of femtosecond-laser-written waveguides in glasses[END_REF] .

Their contribution might explain the slight erasure of the measured retardance that is observed below 600°C especially in Borofloat® 33 and ULE® glasses but point defects cannot account for the observed "abnormal" increase of R norm (Δt, T) within 600-800°C in both SiO 2 and 50SiO 2 -50Al 2 O 3 samples.

The next point is the abnormal behavior that is observed in the intermediate temperature range (600-800°C). Bricchi et al. [START_REF] Bricchi | Extraordinary stability of anisotropic femtosecond direct-written structures embedded in silica glass[END_REF] and Grobnic [START_REF] Grobnic | Long-term thermal stability tests at 1000°C of silica fibre Bragg gratings made with ultrafast laser radiation[END_REF] have already observed such unusual behavior within Type II regime respectively in SiO 2 or in slightly Ge-doped optical fibers. We suggest this could be related to some changes in the strain field resulting in an additional stress-induced birefringence, but this hypothesis needs to be further investigated. More specifically, this hypothesis is based on the imposed sequence of step isochronal annealing associated with quenching to room temperature (after each step), which leads to the occurrence of an additional stress field. This suggestion is supported by a recent publication of Y. Bellouard group [START_REF] Vlugter | Local tuning of fused silica thermal expansion coefficient using femtosecond laser[END_REF] . In this recent work the authors report that while densified zones (so-called Type I regime) display a decrease of thermal expansion coefficient, nanogratings (Type II regime) show the opposite trend, with respect to the pristine material. In addition, the authors highlight that an annealing treatment of 10 hours at 300°C leads to a significant increase in the coefficient of expansion α within Type II affected zone. In the framework of our step isochronal annealing experiments, this should lead to an increase in the residual stresses and thus traditional stress-induced birefringence resulting in the observed increase of the overall retardance in the 600-800°C range.

The last point is the contribution to the birefringence that exhibits a very high thermal stability in SiO 2 and SiO 2 -Al 2 O 3 . This part, typically above 1000°C in Figure 4, is attributed to the nanogratings internal structure itself (e.g. nanoporous silica in SiO 2 ). A first comment about Figure 4 is that the 50SiO 2 -50Al 2 O 3 glass shows similar high temperature stability as the pure silica glass (Suprasil). However, Type II modifications erase at much lower temperature in 70SiO 2 -30Al 2 O 3 . We think that the problem here can mostly be seen in term of glass viscosity and glass structure relaxation. Indeed the limiting factor at high temperature is related the stability of the nanogratings and in particular the "nanopores" within the nanolayers themselves.

In a simple view, the thermal stability of these nanopores can be described by the Rayeigh-Plesset equation as suggested by Rudenko et al. [START_REF] Rudenko | Nanopore-mediated ultrashort laser-induced formation and erasure of volume nanogratings in glass[END_REF] . Assuming a constant surface tension with T, the key term of this equation is thus related to the glass viscosity η at high T. We suggested that the observe difference is mostly related to η(T) that is likely higher for 50% Al 2 O 3 than for 30 mol% Al 2 O 3 in agreement with the reported values of glass melting T m temperatures.

This could be attributed to an increase in Al coordination number (4, 5, and 6 fold-coordination 25, 26, 27, 28 ), increasing glass network cross-linking density and bond strength. Note that additional measurements of the viscosity-tempertaure dependence would be nice to validate this view.

In addition based on nanogratings chemical changes observed in other multicomponent oxide glasses [START_REF] Lotarev | Light-driven nanoperiodical modulation of alkaline cation distribution inside sodium silicate glass[END_REF][START_REF] Mori | Nanogratings Embedded in Al 2 O 3 -Dy 2 O 3 Glass by Femtosecond Laser Irradiation[END_REF][START_REF] Lotarev | Ultrafast laser-induced nanogratings in sodium germanate glasses[END_REF] , we suggest that nanogratings in our aluminosilicate samples are made of Al 2 O 3 -rich phase that separates from the SiO 2 -rich matrix phase. Backscattered electron image and element distribution maps shown in Figure 5 have confirmed this view. In particular the high thermal stability of laser-induced phase separation could be related to immiscibility, which has been reported for example in annealed solgel glasses containing >10 mol% Al 2 O 3 and this immiscibility appears to increase with Al 2 O 3 content as reported in [START_REF] Liu | Clarifying the gel-to-glass transformation in Al 2 O 3 -SiO 2 systems[END_REF][START_REF] Macdowell | Immiscibility and crystallization in Al 2 O 3 -SiO 2 glasses[END_REF] . This immiscibility can be ascribed to the difference in the coordination number between oxygen ions bonded to Si and those bonded to Al. Indeed, when one Al 3+ ions replaces Si 4+ in a tetrahedral coordination site, one oxygen ion must ideally tri-bridge three tetrahedra to maintain the charge balance, leading to a densification of the glass network. This could lead to nanoscale separation between Si and Al-rich glassy phases. Based on literature the Al-rich phase would have a typical composition ranging from 3Al 2 O 3 -2SiO 2 to 2Al 2 O 3 -SiO 2 [START_REF] Gonzalez-Carreno | Formation of mullite and spinel phases from SiO 2 -Al 2 O 3 gels prepared by a spray pyrolysis technique. A 29 Si and 27 Al MAS NMR study[END_REF] , for which the edge-shared AlO 6 octahedral chains are interconnected by AlO 4 or SiO 4 tetrahedra [START_REF] Mcconnell | Incommensurate structure and stability of mullite[END_REF][START_REF] Sadanaga | The structure of mullite, 2Al 2 O 3 . SiO 2 , and relationship with the structures of sillimanite and andalusite[END_REF] . Thus, immiscibility increases the structural connectivity in the "residual" Si-rich matrix. Furthermore, the separation of Al-rich phase likely favors the formation of Mullite nuclei [START_REF] Gonzalez-Carreno | Formation of mullite and spinel phases from SiO 2 -Al 2 O 3 gels prepared by a spray pyrolysis technique. A 29 Si and 27 Al MAS NMR study[END_REF] , and it is not excluding that nanolayers are partly nano-crystallized in the form of Mullite, which would need further investigations.

Conclusion

Here, femtosecond laser direct writing in a set of binary SiO but also ZrO 2 or YAG-derivated [START_REF] Cavillon | Overview of high temperature fibre Bragg gratings and potential improvement using highly doped aluminosilicate glass optical fibres[END_REF] ) suitable for ultra-high temperature operation. (EPMA) equipped with a Schottky field emission (FE) electron gun (JXA-8530F, JEOL). Glass: 50SiO 2 -50Al 2 O 3 . Laser conditions: 1030 nm, 1 ps, 1 µm/s and 2,5 µJ/pulse, Xy writing configuration.

Figure, and Table Caption List

  A confocal system and a 1024 Charge-Coupled Detector cooled by nitrogen were used, allowing a spatial resolution of 1-2 µm² with a x100 objective. The spectral resolution is ~0.7 cm -1 . A Coherent® Argon laser is used with an excitation wavelength of 488,1 nm with 50 mW on the sample. A commercial Suprasil® CG glass from Heraeus (a synthetic Type III pure SiO 2 glass[START_REF] Brueckner | Properties and structure of vitreous silica[END_REF] ) has been chosen to serve as a reference to calibrate the sample spectra. All sample spectra were acquired in the frequency range 17 -1400 cm -1 with the same experimental conditions in order to minimize experimental errors. The intensities of the spectra have been normalized over the total integrated area.Femtosecond laser irradiation (λ = 1030 nm, 250 fs) was performed on the SiO 2 -Al 2 O 3 samples to investigate the writing kinetics of Type II modifications. In order to irradiate with a specific depth, and to make testing easier, samples were glued on a glass slide with a transparent resin, then polished using diamond lapping film (ø = 6 µm, 3 µm, 1 µm, 0.25 µm, 0.1 µm) until reaching optical quality. The polished surface was then placed on a xyz motorized translation stages and irradiated. Laser experiments include writing series of lines along the x-axis with a linear laser polarization oriented either parallel (Xx configuration) or perpendicular (Xy configuration) to the scanning direction. The laser pulse repetition rate was fixed to 100 kHz and the scanning speed to 100 µm/s. The laser beam was focused 300 µm below the surface using a 0.6 NA aspheric lens. The pulse energy was varied by step in different range of energy: ranging from 0.1 to 0.5 µJ with step of 0.1 µJ; ranging from 0.6-1 µJ with step of 0.2 µJ; ranging from 1.5-4 µJ with step of 0.5 µJ. The gap between two consecutive lines was fixed to 25 µm. Then in order to measure the optical retardance R, we use an Olympus BX51 polarizing optical microscope equipped with a de Sénarmont compensator. The retardance R is defined as R=B.L,

  , which is related to the Type II modifications, appears around 0.4 µJ in SiO 2 for our experimental conditions. It depends slightly on the Al 2 O 3 concentration and increases up to 0.6 uJ for 50 mole% Al 2 O 3 . Typically, a strong retardance increase appears above T2 for short pulse energy increment and plateaus around 0.8-1 µJ (1.5 uJ for Suprasil® CG glass). Observing the trends in Figure 3, it is possible to notice two features: as the Al 2 O 3 concentration increases both the slope at the origin and the maximum retardance gradually decrease. With respect to silica, SiO 2 -Al 2 O 3 samples exhibit much lower retardance values by a factor 4 for the 80SiO 2 -20Al 2 O 3 sample and by a factor of 10 for the 50SiO 2 -50Al 2 O 3 one.

Figure 1 :

 1 Figure 1: Density of the SiO 2 -Al 2 O 3 samples compared with the results extracted from the literature30, 31, 32 .

Figure 2 :

 2 Figure 2: a) Raman spectra of SiO 2 -Al 2 O 3 samples + phase SiO 2 for sake of comparison b) Sample 80SiO 2 -20Al 2 O 3 ;

Figure 3 :

 3 Figure 3: Retardance R as a function of pulse energy for SiO 2 -Al 2 O 3 glasses (20%, 30%, 40%, and 50% mole of

Figure 4 :NA=0. 6 ,

 46 Figure 4: Normalized retardance R norm (Δt, T) as a function of temperature for Suprasil® CG (SiO 2 ), 70SiO 2 -30Al 2 O 3.

Figure 5 :

 5 Figure 5: Backscattered electron image and element distribution maps obtained by an electron probe micro analyzer.

  ). Figure4displays the normalized retardance R norm (Δt, T) as a function of temperature. Here we have chosen to perform annealing of samples written at 2.0 µJ/pulse, which corresponds to the stable range of Type II modifications (in term of writing kinetics) and can facilitate the reliable measurements of the retardance. The thermal stability of 70SiO 2 -30Al 2 O 3 and 50SiO 2 -50Al 2 O 3 samples were displayed in Figure4together with some additional samples namely SiO 2 (Suprasil® CG, T a ~ 1150ºC), GeO 2 -SiO 2 (4.6 mole% GeO 2 ; T a ~ 1070ºC), and TiO 2 -SiO 2 (ULE® 7972; 7 mole% TiO 2 ; T a ~ 900ºC) and Alumino-borosilicate (Borofloat® 33; 81 mole% SiO 2 , 13 mole% B 2 O 3 , 4 mole% Na 2 O/K2O, 2 mole% Al 2 O 3 ; T a ~ 652ºC). The glass viscosity at 10 13 dPa.s defines here the annealing point T a values.

  2 -doped SiO 2 and 70SiO 2 -30Al 2 O 3 exhibit a higher thermal stability and quite similar trends. The decay starts slowly at 650°C leading to 10% erasure at 850°C in 70SiO 2 -30Al 2 O 3 . Then it begins to fall within 850-1000°C range and there is a very sharp erasure process above 1000°C. Finally, the Type II modifications disappear completely at 1075°C in 4.6 mole% GeO 2 -doped SiO 2 whereas it survives up to 1175°C in 70SiO 2 -30Al 2 O 3 . Note this value is much higher than the reported glass transition temperature of 865°C (determined from thermal expansion curve) for a 5 wt.% Eu 2 O 3 -doped 70SiO 2 -30Al 2 O 3

  2 -Al 2 O 3 glasses (no alkali) up to 50mol% Al 2 O 3 was investigated. It was shown that Type II (i.e. nanogratings likely made of phase separation) can be photo-induced in these aluminosilicate glasses. Additionally, isochronal thermal annealing of 50SiO 2 -50Al 2 O 3 shows a similar thermal stability of Type II modifications compared to SiO 2 and improved compared to Ge-doped SiO 2 . Indeed, the normalized retardance shows no decrease in magnitude at temperatures lower than 1100°C. In contrast, in the GeO 2 -SiO 2 glass, the retardance has already decreased by ~20% at 1000°C. More generally there is a trend indicating that Type II thermal erasure is strongly related to the glass transition temperature range as suggested by our comparison involving Borofloat® 33, ULE®, GeO 2 -SiO 2 and SiO 2 glasses. These results suggest that inscription of such "Type II fs-IR" modifications in SiO 2 -Al 2 O 3 could be employed to make fiber Bragg gratings with high thermal stability. This opens the door toward the fabrication of a new range of "fiber Bragg gratings host fibres" (Al 2 O 3

Acknowledgements

The DEFI CNRS "Instrumentation aux Limites", UltraBragg project, supported this work. The authors thank Ecole doctorale 2MIB from Paris Saclay University for the financial support provided to Yitao Wang for his doctorate.

Conflict of interest

We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted.