Nina V Kulakova

Maria V Sakirko

Renat V Adelshin

Igor V Khanaev

Ivan A Nebesnykh

Thierry Pérez

Brown Rot Syndrome and Changes in the Bacterial Сommunity of the Baikal Sponge Lubomirskia baicalensis

Keywords: Disease outbreak, Mass mortality, Porifera, Brown Rot Syndrome, Opportunistic pathogens, Freshwater

Mass mortality events have led to a collapse of the sponge fauna of Lake Baikal. We describe a new Brown Rot Syndrome affecting the endemic species Lubomirskia baicalensis. The main symptoms are the appearance of brown patches at the sponge surface, necrosis, and cyanobacterial fouling. 16S rRNA gene sequencing was used to characterize the bacterial community of healthy versus diseased sponges, in order to identify putative pathogens. The relative abundance of 89 eubacterial OTUs out of 340 detected has significantly changed between healthy and diseased groups. This can be explained by the depletion of host-specific prokaryotes and by the appearance and proliferation of disease-specific OTUs. In diseased sponges, the most represented OTUs belong to the families Oscillatoriaceae, Cytophagaceae, Flavobacteriaceae, Chitinophagaceae, Sphingobacteriaceae, Burkholderiaceae, Rhodobacteraceae, Comamonadaceae, Oxalobacteraceae, and Xanthomonadaceae. Although these families may contain pathogenic agents, the primary causes of changes in the sponge bacterial community and their relationship with Brown Rot Syndrome remain unclear. A better understanding of this ecological crisis will thus require a more integrative approach.

Introduction

Sponges (Porifera) are ancient Metazoa inhabiting marine and freshwater environments. They have a wide array of functional roles which make them keystone components of benthic-pelagic couplings, filtering ambient water, feeding on picoplanktonic and nanoplanktonic preys together with suspended detritus, and thus recycling organic matter into mineral material. They may also contribute to primary production and excrete secondary metabolites, thus acting on complex and poorly known networks of biotic interactions [START_REF] Wilkinson | Interocean differences in size and nutrition of coral reef sponge populations[END_REF][START_REF] Diaz | Sponges: an essential component of Caribbean coral reefs[END_REF][START_REF] Hentschel | Marine sponges as microbial fermenters[END_REF][START_REF] Webster | Sponge disease: a global threat?[END_REF]. Sponges can host a huge diversity of symbiotic microorganisms, including viruses, archaea, eubacteria, fungi, and protista [START_REF] Webster | The sponge hologenome[END_REF]. In high microbial abundance (HMA) species, microorganisms can represent up to 40% of the sponge biomass [START_REF] Vacelet | Electron microscope study of the association between some sponges and bacteria[END_REF] and show great taxonomic diversity, with up to 47 bacterial or candidate phyla recorded so far [START_REF] Schmitt | Assessing the com-plex sponge microbiota: core, variable and species-specific bacteri-al communities in marine sponges[END_REF][START_REF] Reveillaud | Hostspecificity among abundant and rare taxa in the sponge microbiome[END_REF][START_REF] Rodríguez-Marconi | Characterization of bacterial, archaeal and eukaryote symbionts from Antarctic sponges reveals a high diver-sity at a three-domain level and a particular signature for this eco-system[END_REF]. Acidobacteria, Actinobacteria, Bacteroidetes, Chloroflexi, Cyanobacteria, Proteobacteria (Alphaproteobacteria, Betaproteobacteria, Gammaproteobacteria, Deltaproteobacteria), Verrucomicrobia, and Nitrospira phyla are the most common both in marine [START_REF] Webster | Sponge disease: a global threat?[END_REF][START_REF] Webster | Same, same but different: symbiotic bacterial associations in GBR sponges[END_REF] and freshwater sponges [START_REF] Gernert | Microbial diversity of the freshwater sponge Spongilla lacustris[END_REF][START_REF] Costa | Evidence for selective bacterial community structuring in the freshwater sponge Ephydatia fluviatilis[END_REF][START_REF] Gladkikh | Analysis of bacterial communities of two Lake Baikal endemic sponge species[END_REF][START_REF] Seo | Comparison of bacterial diversity and species composition in three endemic Baikalian sponges[END_REF]. Sponge disease outbreaks or mass mortality events have been reported for more than a century, with more than 20 events studied, sometimes affecting several species and large areas [START_REF] Webster | Sponge disease: a global threat?[END_REF][START_REF] Gaino | Mortality of commercial sponges: incidence in two Mediterranean areas[END_REF][START_REF] Vacelet | Bacterial attack of spongin skeleton during the 1986-1990 Mediterranean sponge disease[END_REF][START_REF] Perez | Mortalité massive d'invertébrés marins : un événement sans précédent en Méditerranée nord-occidentale[END_REF][START_REF] Olson | Aplysina red band syndrome: a new threat to Caribbean sponges[END_REF][START_REF] Webster | Shifts in microbial and chemical patterns within the marine sponge Aplysina aerophoba during a disease outbreak[END_REF][START_REF] Garrabou | Mass mortality in Northwestern Mediterranean rocky benthic communities: effects of the 2003 heat wave[END_REF][START_REF] Luter | Exploring the role of microorganisms in the disease-like syndrome affecting the sponge Ianthella basta[END_REF][START_REF] Maldonado | Recurrent disease outbreaks in corneous demosponges of the genus Ircinia: epidemic incidence and defense mechanisms[END_REF][START_REF] Angermeier | The pathology of sponge orange band disease affecting the Caribbean barrel sponge Xestospongia muta[END_REF][START_REF] Angermeier | Sponge white patch disease affecting the Caribbean sponge Amphimedon compressa[END_REF][START_REF] Gao | Pyrosequencing revealed shifts of prokaryotic communities between healthy and disease-like tissues of the Red Sea sponge Crella cyathophora[END_REF][START_REF] Sweet | A novel sponge disease caused by a consortium of microorganisms[END_REF][START_REF] Blanquer | Snapshot of a bacterial microbiome shift during the early symptoms of a massive sponge die-off in the Western Mediterranean[END_REF][START_REF] Pérez | Effect of climatic and anthropogenic disturbances on sponge fisheries[END_REF]. However, reports and investigations on the conditions of freshwater sponge disease outbreaks are rare. The most commonly observed symptoms are bleaching, necrosis, and the development of filamentous cyanobacteria overgrowing the sponge surface. Such diseases are widely distributed in the Caribbean region, the Great Barrier Reef, the Indo-Pacific, and the Mediterranean [START_REF] Webster | Sponge disease: a global threat?[END_REF][START_REF] Harvell | Emerging marine diseases-climate links and an-thropogenic factors[END_REF], and in some cases, they have severely affected population densities [START_REF] Wulff | Sponge systematics by starfish: predators distin guish cryptic sympatric species of Caribbean fire sponges, Tedania ignis and Tedania klausi n. sp. (Demospongiae, Poecilosclerida)[END_REF][START_REF] Cerrano | Massive mortalities and extinctions[END_REF][START_REF] Lejeusne | Climate change effects on a miniature ocean: the highly diverse, highly impacted Mediterranean Sea[END_REF][START_REF] Cebrian | Sponge mass mortalities in a warming Mediterranean Sea: are cyanobacteria-harboring species worse off?[END_REF][START_REF] Stabili | Epidemic mortality of the sponge Ircinia variabilis (Schmidt, 1862) associated to proliferation of a Vibrio bacterium[END_REF][START_REF] Carballo | Boring sponges, an increasing threat for coral reefs affected by bleaching events[END_REF][START_REF] Sokolow | Effects of a changing climate on the dynamics of coral infectious disease: a review of the evidence[END_REF][START_REF] Fan | Marine microbial symbiosis heats up: the phylogenetic and functional re-sponse of a sponge holobiont to thermal stress[END_REF][START_REF] Webster | A spongin-boring α-proteobacterium is the etiological agent of disease in the Great Barrier Reef sponge Rhopaloeides odorabile[END_REF]. The causal relationships are poorly known. Global warming and extreme thermal events are considered to be the most important environmental contexts favoring the emergence of pathogens or the expression of their virulence [START_REF] Cebrian | Sponge mass mortalities in a warming Mediterranean Sea: are cyanobacteria-harboring species worse off?[END_REF][START_REF] Sokolow | Effects of a changing climate on the dynamics of coral infectious disease: a review of the evidence[END_REF][START_REF] Fan | Marine microbial symbiosis heats up: the phylogenetic and functional re-sponse of a sponge holobiont to thermal stress[END_REF]. Infectious agents have often been considered to be the main factors triggering mass mortalities [START_REF] Gaino | Mortality of commercial sponges: incidence in two Mediterranean areas[END_REF][START_REF] Vacelet | Bacterial attack of spongin skeleton during the 1986-1990 Mediterranean sponge disease[END_REF][START_REF] Olson | Aplysina red band syndrome: a new threat to Caribbean sponges[END_REF][START_REF] Webster | A spongin-boring α-proteobacterium is the etiological agent of disease in the Great Barrier Reef sponge Rhopaloeides odorabile[END_REF][START_REF] Cervino | Identification of bacteria associated with a disease af-fecting the marine sponge Ianthella basta in New Britain, Papua New Guinea[END_REF], although the pathogens responsible have rarely been identified. Several studies have hypothesized on the putative role of viruses, fungi, cyanobacteria, Alphaproteobacteria, Gammaproteobacteria, Epsilonproteobacteria, Firmicutes, and Bacteroidetes [START_REF] Vacelet | Bacterial attack of spongin skeleton during the 1986-1990 Mediterranean sponge disease[END_REF][START_REF] Webster | Shifts in microbial and chemical patterns within the marine sponge Aplysina aerophoba during a disease outbreak[END_REF][START_REF] Stabili | Epidemic mortality of the sponge Ircinia variabilis (Schmidt, 1862) associated to proliferation of a Vibrio bacterium[END_REF][START_REF] Galstoff | Sponge mortality in the Bahamas[END_REF][START_REF] Galstoff | Wasting disease causing mortality of sponges in the West Indies and Gulf of Mexico[END_REF][START_REF] Vacelet | Virus-like particles in cells of the sponge Verongia cavernicola (Demospongiae, Dictyoceratida) and accompanying tissue changes[END_REF][START_REF] Smith | Sponge mortality at British Honduras[END_REF][START_REF] Sparks | Synopsis of invertebrate pathology: exclusive of insects[END_REF][START_REF] Rützler | Mangrove sponge disease induced by cyanobacterial symbionts: failure of a primitive immune system?[END_REF][START_REF] Camillo | Sponge disease in the Adriatic Sea[END_REF][START_REF] Sweet | Characterisation of the bacterial and fungal communities associated with different lesion sizes of dark spot syndrome occurring in the coral Stephanocoenia intersepta[END_REF]. However, there is only one case in which the fulfillment of Koch's Postulate has enabled the identification of a new Alphaproteobacteria, Pseudoalteromonas agarivorans, as the pathogen behind the disease of Rhopaloeides odorabile [START_REF] Webster | A spongin-boring α-proteobacterium is the etiological agent of disease in the Great Barrier Reef sponge Rhopaloeides odorabile[END_REF][START_REF] Choudhury | The pathogen of the Great Barrier Reef sponge Rhopaloeides odorabile is a new s tr ain of Pseudoalteromonas agarivorans containing abundant and diverse virulence-related genes[END_REF].

Freshwater sponges (order Spongillida) include both cosmopolitan species living in lakes and rivers and endemic species. Compared to other freshwater systems, Lake Baikal harbors a highly diverse and abundant sponge fauna which be-longs to two families, Spongillidae with 5 species and Lubomirskiidae with 13 valid species to date [START_REF] Efremova | Porifera. In: Timoshkin OA (ed) An annotat-ed list of the fauna of Lake Baikal and its catchment area[END_REF]. In the lake, species diversity varies with depth, light, and availability of solid (stone, rock) substrates. Most Baikal sponges host eukaryotic photosymbionts which may favor their high occur-rence in the photic zone [START_REF] Efremova | Porifera. In: Timoshkin OA (ed) An annotat-ed list of the fauna of Lake Baikal and its catchment area[END_REF][START_REF] Kozhov | Essays on Lake Baikal studies[END_REF]. Lubomirskia baicalensis (Pallas, 1771) is the most common and emblematic sponge species of Lake Baikal [START_REF] Efremova | Porifera. In: Timoshkin OA (ed) An annotat-ed list of the fauna of Lake Baikal and its catchment area[END_REF]. This endemic species presents variable growth morphologies, and its branching forms-which measure up to 1.5 m high-shape the underwater scape, in particular between 10-and 20-m depths where their maximal biomass has been recorded [START_REF] Kozhov | Essays on Lake Baikal studies[END_REF][START_REF] Masuda | Studies on the taxonomy and distribution of freshwater sponges in Lake Baikal[END_REF]. The first observations of a disease-like syndrome in L. baicalensis sponges were recorded in Central Baikal in 2010 (Khanaev, personal video records) and in 2011 [START_REF] Bormotov | What has happened with Baikal sponges?[END_REF]. Over the past 6 years, diseased sponges have been found along the nearshore zone from South to North Baikal. The most obvious signs of dis-ease are sponge surfaces covered with reddish colored filamentous cyanobacteria, oscule deformation [START_REF] Timoshkin | Ecological crisis at Lake Baikal: scientists diagnose[END_REF], and bleaching [START_REF] Kaluzhnaya | Bleaching of Baikalian sponge affects the taxonomic composition of symbiotic microor-ganisms[END_REF]. This disease outbreak developed into a sponge mass mortality in 2013. The most visible effects concerned the branching forms of L. baicalensis with, in this case, a disease occurrence affecting between 30 and 100% in the Southern Basin of Lake Baikal [START_REF] Timoshkin | Rapid ecological change in the coast-al zone of Lake Baikal (East Siberia): is the site of the world's greatest freshwater biodiversity in danger?[END_REF].

This study focuses on individuals of L. baicalensis presenting the same syndrome of dark brown necrotic patches. Sponge-associated bacterial communities were studied using deep sequencing of the 16S ribosomal RNA gene in order to identify microbial taxa associated with diseased sponges, and thus provide initial clues about the mechanisms behind the outbreak.

Materials and Methods

Sponge and Water Sampling

Healthy and diseased individuals (Fig. 1) of L. baicalensis were collected by scuba diving during a field trip conducted in May-June 2015.

Sponges were collected at three sites along the littoral zone of Lake Baikal: 51° 51′ 46″ N, 104° 50′ 51″ E(site L); 53° 01′ 03″ N, 106° 55′ 47″ E (site OV); 55° 17′ 16″ N, 109° 45′ 31″ E (site T) (Fig. 2). The population of sponges at these sites was well represented by L. baicalensis. Sponge samples were divided into healthy (n =11) and diseased (n = 11) groups, based on absence or presence of dark brown patches (Table 1). Samples were obtained from individual sponges, with the exception of samples T1H and T5D, which consisted of healthy and diseased parts of the same individual. Pieces of sponges, measuring 4-8 cm long, were collected by divers, placed in 50-mL tubes filled with sterile water, lifted to the ship, and gently washed three times with sterile water. Each sample was photographed, divided into pieces, and frozen at -20 °C before DNA extraction. Extraction of DNA was performed within 2 months following the expedition. Additionally, pieces of samples were stored in 70% ethanol at room temperature for morphology identification. Sponge species were identified based on morphological characteristics of skeletons and spicules, according to the guidelines of Rezvoi [START_REF] Rezvoi | Freshwater sponges of the USSR. In: Rezvoi PD (ed) The fauna of the USSR[END_REF] and Efremova [START_REF] Gaino | Mortality of commercial sponges: incidence in two Mediterranean areas[END_REF]. Ambient water samples (200 mL per site) were collected and filtered through a sterile filter (Minisart NML, Sartorius) with a 0.22-μm pore size. Filters were stored at -20 °C before DNA extraction. Extracts of DNA from each filter from different locations were mixed in one sample in order to optimize our chances of obtaining good amplification. According to Mikhailov et al. [START_REF] Mikhailov | Similarity of structure of taxonomic bacterial communities in the photic layer of Lake Baikal's three basins differing in spring phy-toplankton composition and abundance[END_REF], at this season, the bacterioplankton composition is rather homogenous across the three different basins of Lake Baikal.

Chemical Water Analysis

Water samples (1.5 L) were collected in each site at 5-15-and 15-30-m depths, to measure pH, temperature, nutrients, and dissolved oxygen using standard methods described in Semenov [START_REF] Semenov | Guidance on the chemical analysis of surface waters[END_REF], Stroganov and Buzinova [59], and Wetzel and Likens [START_REF] Wetzel | Limnological analyses[END_REF]. Results were compared to reference values obtained after long-term monitoring in Lake Baikal [START_REF] Shimaraev | Trends in hydrological and hydrochemical processes in Lake Baikal under conditions of modern climate change[END_REF][START_REF] Domysheva | ) Baikal: nature and people[END_REF][START_REF] Sakirko | Concentration of nutrients in the water of Southern Baikal in summer[END_REF][START_REF] Khodzher | Methods for monitoring the chemical composition of Lake Baikal water[END_REF].

Pyrosequencing of Bacterial 16S rRNA Genes

The genomic DNA was extracted from 30 to 50 mg of sponge tissue and water filters using TRIzol LS reagent, following the manufacturer's instructions (Invitrogen, Ambion, USA). In total, 22 sponge samples and one water sample were used for 454 sequencing.

For each sample, the hypervariable region V4-V6 of the 16S rRNA gene was amplified by PCR with bacterial primers 518F and 1064R [START_REF] Newton | A microbial signa-ture approach to identify fecal pollution in the waters off an urbanized coast of Lake Michigan[END_REF], incorporated into the for-ward primer A (Lib-L) with samplespecific MIDs at the 5` end and reverse primer B, respectively, as described in the Guidelines for Amplicon Experimental Design (April 2014) for the GS FLX Titanium 454 Sequencing System. The three replicates of the 15-μL PCR mixture contained 1× Tersus buffer, 1× high-fidelity polymerase Tersus, 2.5 M Mg2+, 0.2 mM of each dNTP (Tersus PCR kit, Evrogen, Russia), 10 pmol of forward and reverse primers, and 50 ng DNA. Negative (no template) controls were used in the PCR with each MID. The PCR conditions included an initial denaturation step at 96 °C for 3 min; 30 cycles of 94 °C for 20 s, 55 °C for 20 s, and 72 °C for 1 min; and a final extension at 72 °C for 5 min, using a DNA Engine Dyad Thermal Cycler (MJ Research, USA). Products from triplicate PCR reactions were combined, and 25 μL of the mix was cleaned to remove products smaller than 300 bp, using a SeqCap Pure Capture Bead Kit (Roche). The DNA pool was diluted in 10 mM Tris-EDTA to a final concentration of 1 × 106 molecules/μL, and one molecule per bead was used in emulsion PCR. Amplicons were unidirectionally sequenced (two runs for all samples) using a Roche Genome Sequencer, the GS Junior System. The GS Run Browser 3.0 (Roche) was used for primary data processing, and the script Extended MIDConfig.parse (Roche) was used for automated sorting of MID-containing reads. The number of reads was normalized to 4500 reads per sample. Sequences were trimmed, quality-controlled, and aligned using Mothur [START_REF] Schloss | Introducing mothur: open-source, platform-independent, communitysupported software for describing and comparing mi-crobial communities[END_REF]. Pipeline and SeqClean software image processing and signal calling were performed using the Roche amplicon-processing pipeline (version 2.53) with a recursive phase correction algorithm to maximize the number of long reads. The ChimeraSlayer algorithm [START_REF] Haas | Chimeric 16S rRNA sequence formation and de-tection in Sanger and 454-pyrosequenced PCR amplicons[END_REF] inside a Mothur package was used to eliminate chimeras, and singletons were discarded. The Silva database [START_REF] Quast | The SILVA ribosomal RNA gene database project: improved data processing and web-based tools[END_REF], with the alignment, taxonomy, and operational taxonomic units (OTUs) assigned according to Greengenes repository [START_REF] Desantis | Greengenes, a chimera-checked 16S rRNA gene database and workbench com-patible with ARB[END_REF], was used as a template for annotation of input sequences. Grouping of input data with ≥ 97% identity threshold was implemented by a greedy complete-linkage clustering following the recommendations of He et al. [START_REF] He | Stability of operational taxonomic units: an important but neglected property for analyzing microbial diversity[END_REF]. Unclassified reads and chloroplast sequences were removed from downstream analysis. The percentage values of sequence reads in groups of healthy and dis-eased sponges were used to analyze differences between sponge-associated bacterial communities. Nucleotide sequences were submitted to the NCBI Sequence Read Archive SRP073411.

Statistical Analysis

The Shannon biodiversity index and species richness estimates Chao1 and ACE were calculated from canonical formulas, as documented in the Mothur manual [START_REF] Schloss | Introducing mothur: open-source, platform-independent, communitysupported software for describing and comparing mi-crobial communities[END_REF]. The principal component analysis and the Mann-Whitney test were per-formed using XLSTAT 2016. Between-group comparisons of bacteria prevalence in healthy and diseased L. baicalensis sponges (at 97% of homology) were calculated using the U-criterion of the two-tailed Mann-Whitney test; values of p < 0.05wereconsideredassignificant.Actualp values can be found in Supplementary S1. Standard deviation of the mean was used for data presentation.

Results

Disease Occurrence

Diseased L. baicalensis were found at all sampling sites between 3 and 30 m. Dark brown patches were the most common external signs that we thereafter defined as Brown Rot Syndrome (BRS). Bleaching sponges were found only occasionally. Patches could cover parts of the sponge surface or entire individuals. They usually led to necrosis, collapse of the tissue, and death. Filamentous cyanobacteria covered the affected branches, giving them a brownish-pink color. The incidence disease on sponge populations was variable between sites, from a few scattered diseased individuals (site T) to extensive areas with dozens of decaying sponges (sites L and OV).

Chemical Water Analysis

The obtained data on temperature, pH, and concentrations of biogenic elements generally corresponded to average back-ground values [START_REF] Domysheva | ) Baikal: nature and people[END_REF][START_REF] Khodzher | Methods for monitoring the chemical composition of Lake Baikal water[END_REF], the exception being a drop in pH and an increase in N and P concentrations in the water layer near the bottom at site L (Table 2).

16S Taxonomic Richness and Bacterial Composition in Healthy and Diseased Sponges

The total number of reads of 16S rRNA gene was 125,560. The average sequence length of filtered reads was 524 ± 14 nucleotides. The Shannon diversity index was 2.5 ± 0.6 for the healthy sponge group and 3.5 ± 0.4 for the diseased sponge group (mean ± SD). Diversity indices for each sample are given in Table 3. A total of 340 OTUs was detected among our sponge samples (Supplementary file S2). Rarefaction curves for each sample indicated that the major part of the sequence diversity was identified (Supplementary file S3). However, deeper sequencing would certainly allow to recover more minor OTUs. The PCA analysis on the relative OTU abundance based on the Pearson correlation matrix clearly separates the two groups: diseased and healthy sponges with samples of healthy tissue taken from diseased individuals grouped with healthy sponges (Fig. 3). In healthy sponges, the bacterial community appeared to be composed by 19 phyla: Crenarchaeota, Acidobacteria, Actinobacteria, Bacteroidetes, Chlamydiae, Chlorobi, Chloroflexi, Cyanobacteria, Deinococcus-Thermus, Elusimicrobia, Firmicutes, Gemmatimonadetes, Lentisphaerae, Nitrospira, Planctomycetes, Fibrobacteres, Proteobacteria (Alphaproteobacteria, Betaproteobacteria, Gammaproteobacteria, Deltaproteobacteria, Epsilonbacteria), Spirochaetes, Verrucomicrobia, and five candidate phyla BD 1-5, OD1, OP10, TM6, and WCHB1-60. Two additional candidate phyla, SM2F11 and SR1, were found in diseased sponges. The most abundant bacterial phyla were Bacteroidetes and Proteobacteria and, to a lesser extent, Actinobacteria, Cyanobacteria, Planctomycetes, and Verrucomicrobia. The microbial community of the water sample differed from that obtained from sponge samples and was dominated by Actinobacteria (Fig. 4).

Significant changes were detected in the composition of the bacterial community of diseased sponges. Some taxa showing more than 5-fold increases in abundance belonged to Cyanobacteria, Bacteroidetes, Alphaproteobacteria, Betaproteobacteria, and Gammaproteobacteria. At the family level, members of Oscillatoriaceae, Cytophagaceae, Flavobacteriaceae, Chitinophagaceae, Sphingobacteriaceae, Burkholderiaceae, Rhodobacteraceae, Comamonadaceae, Oxalo bacteraceae Xanthomonadaceae, and Verrucomicrobiaceae were over-represented in diseased sponges. At the genus level, 19 genera and unclassified taxa were more abundant in diseased sponges (Fig. 5). In addition, other genera such as Cytophaga, Phormidium, Bosea, Pseudorhodobacter, Luteolibacter, and Prosthecobacter were recorded in low quantity (< 0.9%), but only in diseased sponges.

At the lowest taxonomic level (97% similarity), significant quantitative changes between groups of healthy and diseased sponges were highlighted by 89 bacterial OTUs (Supplementary Table S1). Among the changes detected at this level, the relative read abundance increased for 64 OTUs, whereas it decreased for 25 OTUs. In each genus, increased abundance was found in one-to-two closely related OTUs (96-96.9%) dominating bacterial communities of diseased sponges, and was actually absent-or found only in trace amounts-in healthy sponges or water samples.

Oscillatoriales cyanobacteria (Subsection III) are the most increased OTUs in diseased sponges. In particular, the abundance of the genera Chamaesiphon and Limnothrix and of an unclassified group increased by 5% in diseased sponges, whereas they accounted for only 0-0.1% of bacterial communities in healthy samples, and were totally absent in the water sample. Several other cyanobacterial OTUs belonging to gen-era Leptolyngbya and Phormidium also prevailed in the diseased sponge group. (Sediminibacterium, Fabibacter), candidate division OD1, Planctomycetes (CL500-3), Alphaproteobacteria (LD12), Betaproteobacteria (LD28, OM43, Polynucleobacter, Limnohabitans), Deltaproteobacteria (Bacteriovorax), and Verrucomicrobia (vadinH A64, Candidatus Methylacidiphilum).

Discussion

The results of chemical analysis showed that water parameters were in the range of the reference values; however, in site L some changes were detected in terms of pH and nutrient concentrations. In particular, a drop in pH from 7.9 to 7.2, along with increased concentrations of nitrate (1.4-fold), phosphate (1.5-fold), ammonium (from 0.005 to 0.56 mg/L), and nitrite ions (from 0.002 to 0.05 mg/L), was detected in the water sampled near the bottom. At this site, the sponge disease appeared concomitantly with a green algae bloom described by Kravtsova et al. [START_REF] Kravtsova | Disturbances of the vertical zoning of green algae in the coastal part of the Listvennichnyi gulf of Lake Baikal[END_REF][START_REF] Kravtsova | Nearshore benthic blooms of filamentous green algae in Lake Baikal[END_REF] and attributed to a local eutrophication. The relationship between the sponge BRS and this eutrophication event is unclear; however, the green algae proliferation significantly affected the sponge environment, the substrate and light availability, and the water quality, and thus likely disturbed sponge filter-feeding, growth, and reproduction ability.

The analysis of 16S rRNA gene of the bacterial community associated with sponges highlighted a more diverse microbial community in healthy L. baicalensis than in previously studied specimens [START_REF] Gladkikh | Analysis of bacterial communities of two Lake Baikal endemic sponge species[END_REF][START_REF] Seo | Comparison of bacterial diversity and species composition in three endemic Baikalian sponges[END_REF]. This might be explained by differences in sample preparation and amplification strategy. Under reference condition, the L. baicalensis bacterial com-munity includes Crenarchaeota and 23 Eubacteria phyla and candidate phyla. The major bacterial phyla are Bacteroidetes, Proteobacteria, Actinobacteria, Verrucomicrobia, and Planctomycetes, which also dominate bacterial communities of other freshwater sponges such as Ephydatia fluviatilis [START_REF] Costa | Evidence for selective bacterial community structuring in the freshwater sponge Ephydatia fluviatilis[END_REF], Eunapius carteri, and Corvospongilla lapidosa [START_REF] Gaikwad | Microbial community structure of two freshwater sponges using Illumina MiSeq sequenc-ing revealed high microbial diversity[END_REF]. Moreover, Cyanobacteria and OD1 candidate phylum seem to be also very common in L. baicalensis.

Significant changes in composition of the bacterial com-munity were detected in sponges with BRS. Species diversity appeared higher in the diseased sponge group, which seems to be a recurrent observation in marine sponges [START_REF] Maldonado | Recurrent disease outbreaks in corneous demosponges of the genus Ircinia: epidemic incidence and defense mechanisms[END_REF][START_REF] Galstoff | Sponge mortality in the Bahamas[END_REF][START_REF] Vicente | Regional commercial sponge extinction in the West Indies: are recent climatic changes responsible?[END_REF]and corals [START_REF] Roder | Bacterial profiling of White Plague Disease across corals and oceans indicates a conserved and distinct disease microbiome[END_REF]. This higher diversity is likely due to the emergence of new opportunistic species benefiting from sponge loss of health and resulting tissue degradation. However, the change detected in the bacterial community of diseased sponges can also be explained by the depletion of several OTUs which are common in healthy specimens.

Previous studies have shown that uncultured Oscillatoriales are often associated with marine sponge and coral diseases [START_REF] Luter | Exploring the role of microorganisms in the disease-like syndrome affecting the sponge Ianthella basta[END_REF][START_REF] Sweet | A novel sponge disease caused by a consortium of microorganisms[END_REF][START_REF] Galstoff | Sponge mortality in the Bahamas[END_REF][START_REF] Miller | A meta-analysis of 16S rRNA gene clone libraries from the polymicrobial black band disease of corals[END_REF], these cyanobacteria being high-ly represented in diseased L. baicalensis. Some detailed investigations revealed several putative pathogens within this order. Species of the Hormoscilla genus were involved in mangrove sponge disease (MSD) [START_REF] Choudhury | The pathogen of the Great Barrier Reef sponge Rhopaloeides odorabile is a new s tr ain of Pseudoalteromonas agarivorans containing abundant and diverse virulence-related genes[END_REF] and detected in necrosis of Callyspongia (Euplacella) aff. biru [START_REF] Galstoff | Sponge mortality in the Bahamas[END_REF]. The filament-forming Limnothrix, Plectonema, and Leptolyngbya were detected in sponge orange band disease [START_REF] Sweet | A novel sponge disease caused by a consortium of microorganisms[END_REF]. The redpigmented Leptolyngbya spp. appeared on lesions of the Aplysina red band syndrome [START_REF] Olson | Molecular community profiling reveals impacts of time, space, and disease status on the bacterial community associated with the Caribbean sponge Aplysina cauliformis[END_REF], and some unclassified Oscillatoriales were also found forming a white veil on three dictyoceratid sponges [START_REF] Efremova | Porifera. In: Timoshkin OA (ed) An annotat-ed list of the fauna of Lake Baikal and its catchment area[END_REF]. The results obtained in this study show that Oscillatoriales are important components of a complex assemblage of opportunistic bacteria and can be used as a marker for BRS. However, a significant increase of their abundance is not necessarily equivalent to a demonstration of their precise role as a primary pathogenic agent. Further studies are thus required to prove their pathogenic function.

Cyanobacteria predominance has already been observed in bleached and diseased Baikal sponges [START_REF] Kaluzhnaya | Bleaching of Baikalian sponge affects the taxonomic composition of symbiotic microor-ganisms[END_REF][START_REF] Denikina | The first case of disease of the sponge Lubomirskia Baicalensis: inves-tigation of its microbiome[END_REF]. In these recent studies, Synechococcus spp. were shown to be highly abundant (> 80%) in diseased sponges. This contrasts with our findings which reveal that Synechococcus OTU (98-99% similarity with S. rubescens AM709629 and Synechococcus sp. from bleached Baikal sponge JQ272733)-which is also common in lake water-was considerably less represented both in BRS (0.3%) and in healthy sponges (1.7%) (no significant difference was observed between the two sponge categories, p =0.22; U = 79.00). However, the earlier reports listed above were based on the analysis of a single sponge individual, using clone library sequencing [START_REF] Kaluzhnaya | Bleaching of Baikalian sponge affects the taxonomic composition of symbiotic microor-ganisms[END_REF], so it is rather hard to believe that their findings accurately reflect the existing high variability between disease symptoms across Lake Baikal sites, sea-sons, and years.

Analysis of nucleotide similarity in sequences that were substantially detected in diseased sponges revealed a variety of aerobic and anaerobic bacteria belonging to the families Rhodobacteraceae (e.g., 99% EU641680, EU376256), Sphingomonadaceae (98% KC157048), Burkholderiaceae (99% AB826334), Comamonadaceae (99% GU454909, KX771629), Nitrosomonadaceae (98% HQ595214), Xanthomonadaceae (99% EU64 068 2), and Verrucomicrobiaceae (98% AJ401106), which are known to be involved in the biodegradation of a wide range of carbohydrates and biopolymers [START_REF] Kantor | Small genomes and sparse metabolisms of sediment-associated bacteria from four can-didate phyla[END_REF][START_REF] Dennis | Diverse populations of lake water bacteria exhibit chemotaxis towards in-organic nutrients[END_REF][START_REF] Kirchman | The ecology of Cytophaga-Flavobacteria in aquatic environments[END_REF][START_REF] Newton | A unique assemblage of cosmo-politan freshwater bacteria and higher community diversity differ-entiate an urbanized estuary from oligotrophic Lake Michigan[END_REF][START_REF] Liang | Nitrogen removal and water microbiota in grass carp culture following supplementation with Bacillus licheniformis BSK-4[END_REF]. Among them, some Rhodobacteraceae may be associated with sponge and coral diseases [START_REF] Webster | Sponge disease: a global threat?[END_REF][START_REF] Galstoff | Sponge mortality in the Bahamas[END_REF][START_REF] Vacelet | Virus-like particles in cells of the sponge Verongia cavernicola (Demospongiae, Dictyoceratida) and accompanying tissue changes[END_REF][START_REF] Cárdenas | Shifts in bacterial communities of two Caribbean reef-building coral species affected by white plague disease[END_REF]. Moreover, genera such as Flavobacterium (96% NR_112662), Flexibacter (80%KP997194) and Acidovorax (96% KF769125), which are known to be fish or plant pathogens [START_REF] Hansen | Flexibacter ovolyticus sp. nov., a pathogen of eggs and larvae of Atlantic halibut, Hippoglossus hippoglossus L[END_REF][START_REF] Declercq | Columnaris disease in fish: a review with em-phasis on bacterium-host interaction[END_REF][START_REF] Willems | The family Comamonadaceae[END_REF][START_REF] Verner-Jeffreys | Emergence of cold water strawberry disease of rainbow trout Oncorynchus mykiss in England and Wales: outbreak investiga-tions and transmission studies[END_REF], were recorded in abundance in diseased L. baicalensis.

All observed changes in the microbial community of diseased sponges have been attributed to three main observations: proliferation of common OTUs (12%), depletion of species-specific OTUs (7% of the bacterial community), and appearance of new OTUs (7%) that may be acquired from ambient water or present in minimal quantities. Thus, the change in the bacterial community which has been detected in diseased L. baicalensis is undoubtedly much more complex than a simple case of emerging pathogens. Indeed, it appears to include a high number of opportunistic and proliferating bacterial species, some of which likely become pathogenic, leading to disease progression when they proliferate in the sponge body. The results of this study have allowed to detect the consequences of events that lead to changes in the sponge-associated bacterial community and the progression of BRS. The initial cause of BRS and of these changes in the bacterial community remains unclear, and a better understanding of the process will require greater inter-disciplinary as well as an integrative approach to detect the triggers of disease outbreak in Baikal sponges. 4 Composition of major eubacterial taxa in L. baicalensis and lake water assessed using 16S rRNA gene pyrosequencing. Relative abundances of taxa are expressed in percentage of total 16S rRNA gene reads. Bacteroidetes and Proteobacteria prevail in sponge-associated bacterial communities of healthy and BRS sponges whereas Actinobacteria dominate in the water sample. Sampling sites L, OV, and T; Healthy sponges H; Brown Rot Syndrome sponges BRS; Unaffected area of BRS sponge H*. The group "other" includes taxa that account for less than 1% of reads Fig. 5 The most abundant bacterial taxa identified in BRS sponges. The mean values of relative abundance of 16S rRNA gene reads in OTUs were found significantly higher in the group of diseased sponges in comparison with the group of healthy sponges Tables Table 1 Sponge samples Table 2 The water chemical properties in sampling sites Table 3 Richness and diversity indices of the sponge-associated bacterial communities obtained from 16S rRNA gene pyrosequencing

FiguresFig. 1 a

 1 Figures Fig. 1 a Healthy sponge Lubomirskia baicalensis are often inhabited by crustacean Brandtia parasitica. b Sponge with signs of Brown Rot Syndrome

Fig. 2

 2 Fig. 2 Location of sampling sites in Lake Baikal

Fig. 3

 3 Fig.[START_REF] Hentschel | Marine sponges as microbial fermenters[END_REF] Principal component analysis (PCA) based on Pearson correlation matrix of relative OTU abundance shows differences in bacterial communities. Sponge-associated bacterial communities of BRS and healthy sponges are clearly separated Fig.[START_REF] Webster | Sponge disease: a global threat?[END_REF] Composition of major eubacterial taxa in L. baicalensis and lake water assessed using 16S rRNA gene pyrosequencing. Relative abundances of taxa are expressed in percentage of total 16S rRNA gene reads. Bacteroidetes and Proteobacteria prevail in sponge-associated bacterial communities of healthy and BRS sponges whereas Actinobacteria dominate in the water sample. Sampling sites L, OV, and T; Healthy sponges H; Brown Rot Syndrome sponges BRS; Unaffected area of BRS sponge H*. The group "other" includes taxa that account for less than 1% of reads

Fig. 1

 1 Fig. 1

Fig. 2

 2 Fig. 2

Fig. 3

 3 Fig. 3

Fig. 4

 4 Fig. 4

Fig. 5

 5 Fig. 5

  Table 1

Table 2 Table 3

 23

Acknowledgments

We thank Sergey Feranchuk for bioinformatics analysis, Olga Maikova for the morphological identification, the diver Yuriy Yushchik for sampling, Natalya Bel'kova for sharing amplification primers, Maxim Khasnatinov for assistance with statistical analyses, Lubov Kravtsova and Tatyana Butina for the valuable discussion, Rachel Mackie for the English reviewing, and finally Sergey Belikov and Alexander Ereskovsky for their support.

Funding Information Funding came from the Russian State Projects (0345-2016-0002, 0345-2016-0008), the Russian Foundation for Basic Research Project (16-54-150007), and the French Centre National de la Recherche Scientifique (CNRS, PRC 216483).


Q Bui

A Maurel-Pantel

F Mazerolle

C Hochard

Aurelien Maurel
email: maurel@lma.cnrs-mrs.fr

Pantel Maître

The Flexible Initiation Test (FIT): a new experimental test to characterize fracture initiation in mode I at the free edge of bonded assemblies

Keywords: fracture initiation test, mode I, brittle bonding, adhesives, direct bonding

Direct bonding is based on molecular adhesion. This bonding technique consists to join two surfaces into direct contact without the use of any adhesives or additional material. This process requires clean surfaces with a nanometric roughness, sufficiently close together to initiate bonding. Mechanical characterization of this type of assembly with classical mechanical test as for instance wedge test, cleavage test or double shear test present a highly scattering on mechanical results. This paper presents the Flexible Initiation Test (FIT test), an original test designed to characterize fracture initiation in mode I, and to decrease scattering in fracture initiation load measurements, in particular for adhesive with brittle behavior. This new test has to take into account the industrial framework: to be easy to manufacture, easy to execute repeatedly and efficient to provide experimental data for numerical models (stress criteria applications for instance). The paper proceeds first with an explanation of the main initial ideas to introduce the concept of this new test. Next, a numerical analysis is proposed to validate the concept and to determine the optimal geometry of the tests. Then the experimental device is set up and the concept is validated on three different adhesives with the same substrate (a brittle cyanoacrylate adhesive, a ductile and a brittle epoxy adhesives). To conclude, the FIT test is applied on direct bonded samples (an extreme case nanometric interface and very brittle behavior) to determine the fracture initiation load and to compare scattering of measurements.

Introduction:

Adhesive bonding presents many advantages compared to other joining methods such as riveting, welding or mechanical fastening. These advantages include the ability to bond different materials together, lower structural weight, lower fabrication cost, reduction in stress concentration, design flexibility and easy manufacturing. In fact, adhesive bonding is used in a wide range of industrial applications, such as construction, transportation, automotive, marine, electronics, aeronautics and aerospace. Adhesively bonded joints offer many advantages for the design of structures, but a lack of confidence currently limits the use of this technology [START_REF] Adams | Structural adhesives joints in engineering[END_REF][START_REF] Tong | Analysis and design of structural bonded joints[END_REF][START_REF] Adams | Adhesive bonding: science, technology and applications[END_REF].

Mechanical strength characterization of bonding surfaces is essential to improve integration of bonded assemblies in complex systems [START_REF] Adams | Adhesive bonding: science, technology and applications[END_REF]. Within the frameworks of fracture mechanics and structure damage evolution tracking, two main issues are addressed: characterization of fracture initiation and fracture propagation in bonded assemblies. In literature many experiments characterizing fracture propagation have been described as in Ripling et al. [START_REF] Ripling | Measuring fracture toughness of adhesive joints[END_REF]. These tests are really well known and numerous numerical and experimental results have been reported. There are also a number of tests available to characterize fracture initiation: the standard Single Lap Joint test in ASTM standard, the Thick Adhesive Shear test in ASTM standard, the simple tensile test on a two bonded cylinder assembly as in Berry [START_REF] Berry | Determination of Fracture Surface Energies by the Cleavage Technique[END_REF], the three-point bending test as in McDevitt et al. [START_REF] Mcdevitt | The Three-Point Bend Test for Adhesive Joints. Adhesive joints -formation, characteristics and testing[END_REF], as well as more recent tests such as the ARCAN test [START_REF] Arcan | Method to produce uniform plane-stress states with applications to fiber-reinforced materials[END_REF]. However, all these tests exhibit a non-negligible scattering of results due to a strong sensitivity to defects, in particular for bonding with a brittle behavior. In bonded samples or assemblies, edge effects occur which mainly depend on the Young's moduli and Poison's ratio of both the adhesive and the substrates, as well as on the stiffness and geometries of the substrates. These effects can induce high stress concentrations, which affect the mechanical strength and generally lead to early rupture. The slightest defects in the adhesive or in the substrate can cause the breaking of the assembly, and that's why measurements of ultimate load failure exhibit large scatter. In their interesting and important work, Cognard et al. [START_REF] Cognard | A study of the non-linear behaviour of adhesively-bonded composite assemblies[END_REF][START_REF] Cognard | Analysis of the nonlinear behavior of adhesives in bonded assemblies-Comparison of TAST and Arcan tests[END_REF][START_REF] Cognard | Analysis of the Non-linear Behavior of an Adhesive in Bonded ssemblies Under Shear Loadings. Proposal of an Improved TAST[END_REF] and Davies et al. [START_REF] Davies | Influence of adhesive bond line thickness on joint strength[END_REF] have developed a process of sample geometry optimization to overcome this problem. The new modified ARCAN test allows better measurement reliability. To reduce the edge effects, a beak, machined with an angle of 45°, a blending radius of 0.8 mm and a convex shape, is imposed on the edge part of the adhesive. The introduction of a beak raises manufacturing and handling issues. These specific geometries are very difficult to reproduce in complex industrial structure assemblies, in particular on fused silicate substrate for direct bonding. Furthermore, the experimental results obtained for the epoxy resin Araldite ® 420 [START_REF]Epoxy resin Araldite ® 420 Huntsman technical files[END_REF], for example, Cognard et al. [START_REF] Cognard | Development of an improved adhesive test method for composite assembly design[END_REF] in their results still display residual scattering. This paper reports on the research conducted within the framework of cooperation with the French National Center of Spatial Studies (CNES) concerning fused silica or Zerodur® direct bonding technology. Direct bonding consists in joining two surfaces without the use of any adhesive or additional material as described by Kendall [START_REF] Kendall | Molecular adhesion and its applications[END_REF]. Usually, by bringing two flats, well-polished surfaces into contact at room temperature, they locally attracted to each other by Van der Walls or hydrogen bonds and adhere or bond. The main applications are on silicon-on-insulator devices. Silicon based sensor and actuators, electronics substrates are other examples of wafer bond classic applications reported by Ventosa et al. [START_REF] Ventosa | Hydrophilic low-temperature direct wafer bonding[END_REF]. Recently, this process has been used in the manufacturing of high performance optical system for terrestrial application such as Fabry-Perot interferometers, prism assemblies. Nowadays, direct bonding is of particular interest for spatial instrument applications. Indeed, this is a high-precision production process, and direct-bonded assemblies obtained present a dimensional stability (CTE) due to the absence of mechanical parts or glue.

In addition, since no adhesive material is used in the process, the risks of contamination associated with degassing are avoided, which is another advantage in a spatial context. A first prototype has successfully passed the space environment tests (mechanical and thermal constraints) where the constraints involved (thermal fatigue, accelerations, vibrations, etc.) are very different from those encountered on Earth.

However, a better understanding of the assemblies' mechanical strength behaviour is required to validate the system life expectancy and to meet the European Space Agency standards. The mechanical strength of direct bonded interfaces depends on the interface defects and on the nature of the bonds involved as described Cocheteau et al. [START_REF] Cocheteau | Mechanical characterization of direct bonded silica surfaces[END_REF][START_REF] Cocheteau | Influence of roughness on mechanical strength of direct bonded silica and Zerodur® glasses[END_REF]. Indeed, Liao et al. [START_REF] Liao | Effect of surface characteristic on room-temperature silicon direct bonding[END_REF] explained that room temperature bonding needs flatness and roughness perfectly controlled, and no particles contaminations on surfaces. Room temperature bonding is usually relatively weak; consequently, for some applications, the bonded assemblies undergo an annealing treatment causing changes in the nature of bonds responsible for adhesion and thus strengthen the bond across the interface as explained in Kissinger et al. [START_REF] Kissinger | Void-free silicon-wafer-bond strengthening in the 200-400°C range, Sensor and Actuators A[END_REF]. Direct bonding exhibit a brittle behavior and an interface thickness at molecular scale. This paper presents an original test designed to characterize fracture initiation in mode I, and to decrease scattering in experimental results, in particular for direct bonding. This new test have to take into account the industrial framework: have to be easy to manufacture, easy to execute repeatedly, efficient to confront adhesive performance and to provide experimental data for numerical models. The final aim consist to develop a new experimental test to measure critical initiation load for brittle adhesive considering the extreme case of direct bonding interface (i.e. thickness interface at molecular scale), in order to be able to use these experimental results to apply stress criterion (point stress, average stress, or coupled criteria).

The paper proceeds first with an explanation of the main initial ideas to introduce the concept of this new test named FIT for Flexible Initiation Test. A numerical analysis is proposed to validate the concept of the experimental bench and determine the optimal geometry of the experimental device (Section 3). In section 4, the design of the new experimental bench is described and the concept is validated experimentally on three different adhesives with the same substrate: the Permabond 910 a brittle cyanoacrylate adhesive with a thickness of 0.01 mm [START_REF]Cyanoacrylate adhesive Permabond 910 technical files[END_REF]; the Scotch-Weld™ 3M 2216 B/A a ductile epoxy adhesive with a thickness of 0.1 mm [START_REF]Scotch-Weld™ 3M[END_REF]; and the Araldite® AV138M-1/ Hardener HV998 a brittle epoxy adhesive with a thickness of 0.1 mm [START_REF]Hardener HV 998 technical files[END_REF]. In section 5, the direct bonding case is considered, the scattering of direct bonding critical initiation load measurement is compared. Finally, conclusions and prospects are drawn in Section 6.

New fracture initiation test in mode I

In previous investigation, Cocheteau et al. [START_REF] Cocheteau | Mechanical characterization of direct bonded silica surfaces[END_REF] were performed a peel test and a modified cleavage test in order to determine the influence of the reinforced direct bonding process parameters on the bonding mechanical strength. The experiments were run on five fused silica samples for each condition. In the tensile testing machine, the sample was mounted and bonded between two aluminum mechanical parts, as related in Figure 1. For each sample, the critical initiation load was measured to characterize the bonding mechanical strength. Then to determine a stress value for the interface mechanical strength, a failure stress criteria is applied. After the analysis of measurements, the scattering (standard deviation in %) around the critical initiation load average value in these two tests is reported in Figure 2. A lower dispersion is observed for the modified cleavage test than for the peel test. We can see that for this modified cleavage test, the load application point is shifted from the bonding edge. This observation leads to determining the role played by the load application point position. In order to study the influence of the load application point position, the Double Cantilever Beam (DCB) classical test, used for crack propagation, is considered (Figure 3). Using the Euler-Bernoulli beam theory, the critical strain energy release rate can be expressed as follows:

= 12 ℎ (1)
where is the critical strain energy release rate, the crack propagation load, the crack length distance measured between the vertical load line and the tip of crack on the edge of the specimen, the longitudinal modulus, the width and ℎ the thickness of the sample. With equation ( 1), the crack propagation load can be written as a function of the crack length with the following expression: If the critical strain energy release rate is assumed to be constant, the mathematical relation proposed in equation ( 2) describes the evolution of the crack propagation load as a function of the crack length (the curves are shown in Figure 4). Therefore, it should be noticed that the longer is, the smaller the load variation ∆ is with respect to ∆ . Concerning the initiation test, we make an analogy between ∆ and inherent bonding defect close to the edge with different sizes. Based on this observation, we make the assumption that increasing will make it possible to decrease scattering of the test. We can remark that increasing the distance is equivalent to increasing the beam flexibility. In conclusion, the idea is to increase the flexibility of the beam to decrease scattering on fracture initiation load measurement. During the test we need to stay within the elastic range, the geometric condition on the support beam thickness ℎ can be written as:

= 1 ℎ 12 (2)
ℎ ≥ 6 ( -) (4)
with the yield stress of the support beam material and a safety factor on the yield stress (for instance in our case s=2). Then to maintain deformable support beams, we choose to define the following rules (ℎ is practically chosen the smallest as possible):

ℎ < ℎ (5)
After the introduction of this new test, a numerical analysis is proposed to determine the efficiency of this new configuration to measure the fracture initiation critical load # .

Numerical analysis of the flexible initiation test:

In this section, a preliminary 2D numerical simulation of the FIT is performed with the commercial finite element code ABAQUS 6.10 in order to define the optimal geometry to decrease the critical initiation load measurements scattering for a given bonded joint under static loading in mode I.

Material parameters and geometry:

In Figure 5, substrate and deformable support beam materials can be different as in the final application in section 5. In the case of adhesive characterization, the substrate and the beam can be in the same material. We chose to have the same material for the deformable support beam and the substrate: an aluminum-alloy 2014-T4 with an elastic and isotropic behavior.

The mechanical properties used for the simulation are related in Table 1. It is assumed in simulations that the deformable support beam and the samples are machined in a single part as related in Figure 6. In simulations, the bonded joint considered, was the Hysol EA 9321 adhesive on an aluminum substrate. The adhesive material parameters used in FEM analysis were taken in Da Silva et al. paper [START_REF] Silva | Effect of adhesive type and thickness on the lap shear strength[END_REF]. The parameters are reported in Table 2. According to equation introduced in section 2, the thickness of deformable support beam and substrate were respectively set to: ℎ = 1 $$ and ℎ = 4 $$. In these preliminary investigation, the flexible initiation test configurations chosen for numerical simulations are: a sample with a rounded edge, and two different deformable backing beam lengths (110 mm and 300 mm) in order to analyze the influence of the beam flexibility on the scattering of fracture initiation load measurement.

The rounded edge geometry is used to check the decreasing of scattering with the FIT test in this particular case (close to the industrial application). Indeed, in case of a round edge and in neglecting the adhesive thickness, the stress concentration is finite. The sample geometry and the bonded assembly are described in Figure 6.

Adhesive behavior and boundary conditions:

In these simulations, cohesive zone models (CZMs) have been used to model adhesive mechanical behavior. The CZMs approach is one of the most commonly numerical methods used to investigate the failure of adhesive joints. This model is based on the assumption that a cohesive damage zone (or process zone) develops near the initiation zone at the crack tip generally. This zone can model the initiation of a micro crack. The cohesive zone model links tensile stress σ to displacement jump or crack opening %&' at an interface where a crack initiates in the adhesive. Damage initiation occurs when the stress reaches the tensile strength.

During the crack opening process, energy is dissipated, when total energy dissipated corresponds to the critical energy release rate # , the interface element fails and the crack propagates. In literature, many CZMs with damage law have been proposed (trapezoidal law, bilinear law, power law, exponential law, etc.). In these simulations, the bilinear law shown in Figure 7 is applied. The cohesive layer is modeled in Abaqus code with a four-node cohesive element COH2D4, zero thickness is imposed, the solid substrates are modeled with twodimensional plane strain elements (CPE4 and CPE3 in ABAQUS), as shown in Figure 8. The problem is in plane, there is no boundary condition like in the experimental configuration, but there are two symmetrical loads applied at the tip of each flexible support beam in the vertical direction ( ) as related in Figure 6.

Mesh Convergence

First simulations have been performed to investigate mesh convergence. The cohesive element length and the mesh size is estimated from the length of the process zone at the crack tip. Turon et al. [START_REF] Turon | An engineering solution for mesh size effects in the simulation of delamination using cohesive zone models[END_REF] proposed to determine the size of the fracture process zone * +, as a material property given by the following expression:

* +, = - # # ( 6
)
where E is the Young modulus, GC is the critical energy release rate, σc is the interface mechanical strength, and M is a parameter which is dependent on the cohesive zone model; its value ranges from 0.21 to 1.0.

Figure 9. Influence of the mesh size on the macroscopic response (numerical fracture initiation load) using a bilinear CZM law.

The mesh size is calculated with the following expression:

* . = * +, / (7)
where N is the number of cohesive elements needed in the process zone; its value ranges from 3 to 10 as reported in Moës et al. [START_REF] Moës | Extended finite element method for cohesive crack growth[END_REF]. According to Eq. ( 6) and Eq. ( 7), the mesh size ranges from 0.0248mm to 0.23 mm. Thus, the following mesh sizes, 0.2mm, 0.1mm, 0.05mm and 0.025mm, were chosen to test the mesh convergence. Mesh size optimization is performed in order to improve the numerical prediction on the bonding edge and to decrease the calculation time, as related in Figure 8. The numerical load-displacement curves are described in Figure 9. The results indicate that a mesh size of * . ≤0.05mm is necessary to obtain the converged solution. All the simulations are conducted with a mesh size of 0.05mm.

Numerical Results:

In order to investigate the influence of a simulated defects on scattering in bonding joint strength, two flexible initiation test configurations is simulated: the first one in the case of long deformable support beams (L = 300 mm) and the second one in the case of very short deformable support beams (L = 110 mm), as described in Figure 6. The defect is represented by a small pre-crack (∆a) as related in Figure 10. Four different sizes of defect are considered for each length of deformable support beam. The flexible initiation test is simulated and critical fracture initiation loads are measured. The numerical load-displacement curves are reported in Figure 11. The scattering of fracture initiation load measurement is described in Figure 12. The results indicate that when the long deformable beam is used, the influence of the numerical defects introduced on the scattering is reduced. The FIT test seems to be less sensitive and more accurate to measure the fracture initiation load. The FIT test proposed seems to be able to decrease the uncertainty on the fracture initiation load determination. As the concept of the FIT test (Flexible Initiation Test) is validated numerically, the long beam geometry is chosen for the experimental campaign.

Experimental validation of the FIT test 4.1. Design and technology of the experimental setup:

Figure13. Standard DCB test setup.

In the FIT test proposed, to remain in pure mode I, the specimen is positioned vertically, in order to minimize the influence of gravity as developed in Marzi et al. [START_REF] Marzi | On experimental methods to investigate the effect of layer thickness on the fracture behavior of adhesively bonded joints[END_REF]. Because in standard DCB quasi-static tests, one side of the sample is fastened to the tensile test machine by a pivoting link while a vertical force is applied on the other side of the sample. In this configuration, an effect of the weight of the device appeared during the vertical movement of the test on the tensile testing machine, even more in the case of long deformable support beams as in the flexible initiation test, as shown in Figure 13. In this configuration, the mode II of failure can be activated, and the bonding joint is solicited not only in mode I but also in mixed mode (I+II). The vertical positioning of the FIT test is described in Figure . 14. The experimental device is designed and made in our laboratory. A linear displacement device from RK-Rose-Krieger [START_REF]Symmetrical linear displacement system technical files[END_REF] is used to set the sample in vertical position with symmetrical displacement of each deformable support beam. This device (Figure 15) is composed of two linear carriages, a right-hand and a left-hand thread allowing a symmetric displacement, with two guides and a spindle clamping to control the symmetrical displacement of the carriage. During the test, two measurements are essential: the displacement δ and the applied load F at the tip of the deformable support beams. That is why the system described above is equipped with displacement and load sensors. In the flexible initiation test, two load cells and one displacement sensor of LVDT (Linear Variable Differential Transformer) type are used.

Figure 15. Linear horizontal unit to convert a rotation into a symmetrical displacement [START_REF]Symmetrical linear displacement system technical files[END_REF].

The load cells are mounted on each carriage. This miniaturized sensor (Burster model 8411) is able to measure load ranges from 0 to 200 N with an accuracy deviation below 0.5%. The flexible support beams are linked to an aluminum clevis connected to the load sensors by a ball joint connection, in order to have an isostatic system and to keep the imposed load in a horizontal direction during the test. The displacement sensor is clamped on the frame and measures the displacement of one of the carriages. This sensor is able to measure displacement in the range of 0 to 40 mm with an accuracy deviation below 0.5%. Figure 16 describes the final experimental device of the flexible initiation test.

Material and geometry of the bonded samples:

In these experimental investigations, three types of adhesive are tested: an adhesive with a ductile mechanical behavior (Scotch-Weld™ 3M 2216 B/A Epoxy Adhesive [START_REF]Scotch-Weld™ 3M[END_REF]) and two adhesives with a brittle mechanical behavior (The Permabond 910 cyanoacrylate adhesive

[36] and Araldite® AV138/HV998 epoxy adhesive [START_REF]Hardener HV 998 technical files[END_REF]). The samples are composed of two deformable support beams made in aluminum 2017A with the same geometry. In this case, the adhesive behavior is characterized on an aluminum substrate. Therefore, to simplify samples fabrication, the support beam and the substrate were machined in a single part (Figure 17). Two different geometries are used in the experiments because for the short length of the support beam the measured load exceed the load cell limit. That's why, in this case the width of the support beam is decreased in order to remain in the load cell range.

-The first sample geometries (Figure 17 ), the strain rate is controlled by a belt drive system ensuring a constant rotation speed. The flexible initiation test device with a mounted bonded sample is described in Figure 18.

Experimental results

For each test, five samples are tested, and the experimental force-displacement curves are measured. Figure 19 describe the curves measured for each beam length considered, and we can observe that the scattering decrease with the increase of the beam length and the average value decrease quasi linearly with the increase of the beam length. As explained previously the FIT test stays in linear domain and allows to decrease scattering in measurement. Critical initiation load measurements become more accurate and less sensitive. The fracture initiation load is measured and the average value is calculated. Then, the scattering (standard deviation in %) around the average value is calculated, the values are reported in table 3.

Table 3 Experimental results of the critical initiation load measured for three different adhesives with three different FIT test configuration (three beam lengths). Each scattering of measurement are compared and reported in Figure 20.

Adhesives

FIT test: application on reinforced direct bonding

Then, after the experimental validation of the FIT test, experiments are led on direct-bonded fused silicate samples. The five samples have been designed as two reinforced direct-bonded blades with a chamfered edge at 45°with a final dimension of 50 mm × 20 mm × 1 mm, as related in Figure 21. In these experiments, as in experiments presented in the previous section, the deformable aluminum 2017 support beams were designed with a specific geometry allowing the direct bonded glass samples to be bonded on the optimal length beam, as described in Figure 22.

Direct bonded samples were bonded with the 3M adhesive, the adhesive thickness being controlled, as described in Figure 23. The fracture initiation load is measured for each direct-bonded sample. Experimental results as the average value and the standard deviation of the critical initiation load are reported in Table 4. Figure 24 presents the evolution of the scattering of the fracture initiation load measurements for the three different experimental bench used to characterize reinforced direct-bonded assemblies: the peel test, the cleavage test and the FIT test. In conclusion, the FIT test is efficient to reduce scattering of measurement and to improve reinforced direct bonding characterization.

Conclusions and Prospects:

In this paper, a new test allowing scattering of critical fracture initiation load measurements to be reduced has been described. This new test, named Flexible Initiation Test (FIT), used deformable support beams bonded to samples (the sample is composed of substrate and adhesive). The load is symmetrically imposed and measured at the tip of these support beams, and the displacement is measured. First, a numerical analysis has been performed to validate a first configuration. Then, an experimental campaign was carried out in order to validate the concept in varying the deformable support beam length for three different adhesives (brittle and flexible). Results were showed that a long support beam (200 mm) allows scattering of the fracture initiation load measurements to be reduced, in particular for the adhesives with a brittle mechanical behavior (Araldite, Cyanoacrylate and Direct Bonding). In conclusion, this Flexible Initiation Test is more sensitive and more accurate to characterize fracture initiation in mode I. A forthcoming paper will describe the FIT tests used to analyze some classical stress fracture criteria (point stress, average stress) and a coupled stress and energy failure criterion proposed by Leguillon [START_REF] Leguillon | Strength or toughness? A criterion for crack onset at a notch[END_REF]. In future investigation, the FIT will be extended to different modes of fracture (mode II, mixed-mode (I+II)) and applied to different adhesives.

Figure 1 .

 1 Figure 1. CAD of modified Cleavage test (a) and Peel test (b) experimental devices used to

Figure 2 .

 2 Figure 2. Percent of scattering around the critical initiation load average value for the peel test

Figure 3 .

 3 Figure 3. Picture of the classical DCB test.

Figure 4 .

 4 Figure 4. Evolution of the crack propagation load as a function of crack.

Figure 5 .

 5 Figure 5. The FIT test: the Flexible Initiation Test proposed for the analysis of crack initiation

Figure 6 .

 6 Figure 6. Geometry of the samples. And the two cases considered for the FEM simulation

Figure 7 .

 7 Figure 7. Description of the bilinear law used to model adhesive behavior in finite

Figure 8 .

 8 Figure 8. Mesh Configuration used in the preliminary simulation.

Figure 10 .

 10 Figure 10. Introduction of a defect in simulation of the flexible initiation test as a small pre-

Fig. 11 .

 11 Fig.11. Finite element simulations results: numerical load-displacement curves for the long

Figure 12 .

 12 Figure 12. Scattering of fracture initiation load measurements calculated for different values

Figure 14 .

 14 Figure 14. Flexible initiation test with the sample in vertical position.

Figure. 16 .

 16 Figure. 16. Drawing of the flexible initiation test device.

  (a)) has been used for the Permabond 910 cyanocrylate adhesive. -The second sample geometries (Figure 17(b)) has been used for the Araldite® AV138/HV998 and the Scotch-Weld TM Epoxy Adhesive 2216 B/A.

Figure. 17 .

 17 Figure. 17. Geometry of the bonded specimens. (a) Geometries used for the

Figure 18 .

 18 Figure 18. Experimental device for the flexible initiation test.

Figure 19

 19 Figure 19 Experimental force-displacement curves measured with the FIT test with three

Figure 20 .

 20 Figure 20. Evolution of scattering (defect sensitivity) as a function of the deformable

Figure 21 .

 21 Figure 21. Optical microscope image of the reinforced direct-bonded fused silicate sample.

Figure 22 .

 22 Figure 22. Picture of bonded sample geometries for direct bonding characterization.

Figure 23 .

 23 Figure 23. Device to bond direct-bonded samples on deformable aluminum support

Table 2

 2 Material parameters of the Hysol EA 9321 adhesive modelled in FEM simulations

	Table1 Mechanical properties of deformable support beam and substrate.
	E (GPa)	(MPa)		ν
	70	210		0.33
		[23]
	E (MPa)	ν	# (MPa)	GIC (N/mm)
	3970	0.36	46	0.45

Table 4 .

 4 Experimental results of the critical initiation load measured for direct bonded samples with a 45° chamfered edge.

	Critical

initiation load of the reinforced direct bonding interface Average Load (N) Standard deviation (N) Standard deviation (%)

	4.738	0.423	8.929

Figure 24. Scattering of fracture initiation load measurements for peel test, cleavage test and FIT test.