George R Young

Urszula Eksmond

Rosalba Salcedo

Lena Alexopoulou

Jonathan P Stoye

George Kassiotis

Resurrection of endogenous retroviruses in antibody-deficient mice

The mammalian host has developed a long-standing symbiotic relationship with a considerable number of microbial species. These include the microbiota on environmental surfaces, such as the respiratory and gastrointestinal tracks 1 , and also endogenous retroviruses (ERVs), comprising a substantial fraction of the mammalian genome 2,3 . The long-term consequences for the host of interaction with these microbial species can range from mutualism to parasitism and are not always completely understood. The potential impact of one microbial symbiont on another is even less clear. We have studied the control of ERVs in the commonly-used C57BL/6 (B6) mouse strain, which lacks endogenous murine leukaemia viruses (MLVs) able to replicate in murine cells. We demonstrate the spontaneous emergence of fully infectious ecotropic 4 MLV (eMLV) in B6 mice with a range of distinct immune deficiencies affecting antibody production. These recombinant retroviruses establish infection of immunodeficient mouse colonies, and ultimately result in retrovirus-induced lymphomas. Notably, ERV activation in immune-deficient mice is prevented in husbandry conditions associated with reduced or absent intestinal microbiota. Our results shed light onto a previously unappreciated role for immunity in the control of ERVs and provide a potential mechanistic link between immune activation by microbial triggers and a range of pathologies associated with ERVs, including cancer.

Retroviruses can establish germline infection and become part of the host genome 2,3 . Most, if not all ERVs have become inactive due to mutations or transcriptionally silenced through the action of diverse mechanisms 2,3 . However, RNA and protein expression of replicationdefective ERVs is frequently elevated in infection, autoimmunity and cancer 2,3 . Whether or not the immune system defends against potential threats posed by ERVs is currently unclear. To address the role of adaptive immunity in this process, we assessed ERV expression in B6 mice. We initially compared the transcriptional profiles of purified macrophages from B6 wild-type (WT) and T and B lymphocyte-deficient Rag1 -/-mice.

highest increase in expression levels in macrophages from Rag1 -/-mice (Fig. 1a) correspond to the env and gag genes, respectively (Supplementary Table 1), of an endogenous eMLV locus, Emv2, a replication-defective single-copy ERV present in B6 mice 5 . Differential expression of eMLV was confirmed by qRT-PCR for spliced env mRNA in macrophages (Fig. 1b), and in multiple tissues (Fig. 1c).

Other ERV families were also differentially expressed in macrophages, albeit less strongly (1.7 -2.1-fold) (Supplementary Table 1). Not distinguishing between members of multicopy families, expression of polytropic MLVs (pMLVs), xenotropic MLVs (xMLVs) and of the MusD family of retrotransposons was also elevated in the lungs of Rag1 -/-mice (Supplementary Fig. 1). In line with increased MLV mRNA expression, 60-80% of total splenocytes and all hematopoietic lineages analysed from Rag1 -/-but not from WT mice, expressed MLV surface glycoprotein (SU) (Fig. 1d,e).

Tcra -/-or Tcrd -/-mice, lacking TCRαβ and TCRγδ T cells, respectively, showed low eMLV expression (Fig. 1f). eMLV expression was similarly low in H2-A,E -/-mice, deficient in MHC II, MHC II-restricted T cells and T cell-dependent antibodies (Fig. 1f). In contrast, mice lacking B cells (Ighm -/-mice) or only the ability to produce polyclonal antibodies (Ighm -/-MD4 mice) expressed substantially higher eMLV levels than WT mice (Fig. 1f), demonstrating that high eMLV expression characterised mice lacking antigenspecific antibodies. In addition to splenocytes from Rag1 -/-mice (Fig. 1e), T and B cells from Ighm -/-MD4, but not from WT control mice, expressed MLV SU (Fig. 1g), indicating that eMLV can be highly expressed also in lymphocytes.

Toll-like receptors (TLRs) have been implicated in the control of B cell responses, and both Myd88 -/-and Tlr7 -/-mice have significantly reduced serum levels of natural antibodies and a defective antibody response to immunisation or infection, including with retroviruses 6-9 . Notably, expression of eMLV was dramatically elevated in Myd88 -/-and Tlr7 -/-mice in comparison with WT mice (Fig. 1h). Similarly elevated eMLV expression was observed in Tlr7 -/-, but not Tlr9 -/-mice housed in a different facility (Supplementary Fig. 2).

To investigate the mechanistic link between antibody deficiencies and elevated MLV expression, we examined the origin of eMLV transcription. The B6 genome does not contain replication-competent eMLV proviruses and, although the Emv2 locus can produce mRNA, it is unable to produce infectious virus due to an inactivating G to C mutation at position 3576 of the pol region [START_REF] King | Mechanism of interaction between endogenous ecotropic murine leukemia viruses in (BALB/c X C57BL/6) hybrid cells[END_REF][START_REF] Li | Sequence and Insertion Sites of Murine Melanoma-Associated Retrovirus[END_REF] . In addition, Emv2 gag encodes an N-tropic capsid, which would be restricted by the Fv1 b restriction factor in B6 mice [START_REF] Li | Sequence and Insertion Sites of Murine Melanoma-Associated Retrovirus[END_REF] . However, it was theoretically possible that recombination between replication-defective Emv2 and non-ecotropic MLVs resulted in an MLV with full infectivity [START_REF] Pothlichet | Mobility and integration sites of a murine C57BL/6 melanoma endogenous retrovirus involved in tumor progression in vivo[END_REF] that could spread in Rag1 -/-mice. Remarkably, plasmas of young and old Rag1 -/-mice, but not of WT control mice, contained retroviruses that were capable of replicating in murine cells in vitro (Fig. 2a), which we refer to as Rag1 -/-mouse-associated retroviruses (RARVs). Sequencing of the pol region demonstrated repair of the Emv2-inactivating mutation in all RARV isolates (Supplementary Fig. 3). Functional in vitro assays (Fig. 2b) and sequencing of the gag region (Fig. 2c) showed that RARVs also exhibited B-tropism. Genome sequence comparisons between RARVs revealed that young Rag1 -/-mice harboured highly similar viruses, which diverged substantially in old Rag1 -/-mice (Fig. 2d). All RARVs were recombinants between Emv2 and endogenous non-ecotropic MLVs (Supplementary Fig. 4). The pol defect of Emv2 was likely restored in RARVs by recombination with Xmv43 (Supplementary Fig. 4), an ERV that contains a functional pol region but is unable to infect mouse cells due to polymorphisms in the murine cellular receptor 2 . Recombination events involving Xmv43 have also been found responsible for the emergence of leukaemogenic MLVs in AKR mice [START_REF] Stoye | Virological events leading to spontaneous AKR thymomas[END_REF] . However, the switch in capsid tropism resulted from recombination with other endogenous xMLVs (Supplementary Fig. 4). Notably, the divergence of RARVs isolated from old Rag1 -/-mice was due to further recombination replacing the ecotropic env with polytropic env either from Pmv1/5 or Pmv16 (Supplementary Fig. 4). Together, these findings indicated the emergence of infectious eMLVs that could have infected Rag1 -/- mice and gave further rise to infectious pMLVs. Supporting this notion, the majority of gag/ pol eMLV mRNA detected in Rag1 -/-mice seemed to be transcribed from integrated RARVs, rather than the germline copy of Emv2 (Supplementary Fig. 5).

Emv2 and non-ecotropic MLV recombination events resulting in infectious eMLV generation might occur de novo in individual Rag1 -/-mice. Alternatively, these RARVs might have been vertically transmitted through successive generations. To directly test the latter possibility and assess the capacity of RARVs to spread in immunodeficient mice, we established a colony of Rag1 -/-Emv2 -/-mice by firstly crossing an Emv2 -/-male mouse [START_REF] Young | Negative selection by an endogenous retrovirus promotes a higher-avidity CD4 + T cell response to retroviral infection[END_REF] with a Rag1 -/-female mouse, and then intercrossing selected progeny to homozygosity. These mice lack the germline copy of Emv2, meaning any infectious eMLV present would have been vertically transmitted. Both eMLV spliced env mRNA (Fig. 2e) and MLV SU expression (Fig. 2f) was readily detected in the spleens of Rag1 -/-Emv2 -/-mice in this colony. Furthermore, analysis of eMLV env and pol DNA copies indicated extensive replication of vertically transmitted RARVs in Rag1 -/-Emv2 -/-mice (Fig. 2g). In contrast, sexual or in utero infection was not observed in separate crosses of either male or female virus-positive Rag1 -/-Emv2 -/-mice with virus-free Emv2 -/-mice (Supplementary Fig. 6).

To further examine the potential of RARVs to replicate in Rag1 -/-mice, we assessed the frequency of tumours characteristic of retroviral infection [START_REF] Stocking | Murine endogenous retroviruses[END_REF][START_REF] Stoye | Studies of endogenous retroviruses reveal a continuing evolutionary saga[END_REF] in cohorts of Rag1 -/-mice. Notably, starting from 180 days and affecting 67% of the animals by 380 days, Rag1 -/- mice, but not WT control mice, showed signs of morbidity (Fig. 2h). Upon examination, large tumours, often associated with anaemia, were observed in all morbid Rag1 -/-mice (Fig. 2h and Supplementary Fig. 7). The pathogenic potential of infection with RARVs was established in aged cohorts of vertically-infected Rag1 -/-Emv2 -/-mice, which developed tumours at a comparable incidence rate (Fig. 2h).

Thymic or splenic tumours in Rag1 -/-mice consisted mainly of a single MLV SUexpressing cell type, which differed between animals, and had the histological appearance of lymphoblastic lymphosarcomas (Supplementary Fig. 8). Discrete chromosomal aberrations were found in the majority of tumours analysed (Supplementary Fig. 8), suggestive of clonal origin. Consistent with MLV production by tumour cells, we observed an abundance of MLV-type particles in the extracellular space of tumour samples, but not in a spleen sample from a healthy Rag1 -/-mouse (Supplementary Fig. 9). Furthermore, a significant increase in both eMLV env and pol DNA copy numbers was detected in all tumour samples, with one exception where only pol DNA copies were increased (Supplementary Fig. 9), indicating that RARVs had extensively infected the cells that gave rise to lymphomas. Together these results support a model where multiple recombination events restore Emv2 infectivity, leading to spontaneous retroviremia and vertical transmission to progeny, and eventually drive an oncogenic process similar to that extensively described in mouse strains carrying fully infectious ERVs 2,3 .

Our results associated lack of antibodies with establishment of infectious eMLVs in mouse colonies. Next, we investigated the potential mode of antibody action. Antiretroviral antibodies have a long-established role in limiting the spread of infectious endogenous retroviruses [START_REF] Melamedoff | Suppression of endogenous murine leukemia virus by maternal resistance factor[END_REF] , both within and between animals. However, it was also possible that antibodies were preventing a step prior to the emergence of infectious eMLV recombinants. Rescue of Emv2 infectivity by recombination with a non-ecotropic MLV necessitates co-expression of both proviruses in the same cell at sufficient levels for co-packaging into the same virion. Low expression of these proviruses in WT mice could be a rate-limiting factor in the emergence of infectious eMLVs. However, expression of certain endogenous MLVs in mouse cells is known to be inducible, notably, by microbial products [START_REF] Stocking | Murine endogenous retroviruses[END_REF][START_REF] Stoye | Studies of endogenous retroviruses reveal a continuing evolutionary saga[END_REF][START_REF] Stoye | Endogenous retrovirus expression in stimulated murine lymphocytes. Identification of a new locus controlling mitogen induction of a defective virus[END_REF] . For example, bacterial lipopolysaccharide (LPS) stimulation activates non-ecotropic MLVs, and Xmv43 in particular [START_REF] Stoye | Endogenous retrovirus expression in stimulated murine lymphocytes. Identification of a new locus controlling mitogen induction of a defective virus[END_REF][START_REF] Kozak | Genetic mapping of xenotropic murine leukemia virus-inducing loci in five mouse strains[END_REF][START_REF] Mccubrey | Genetic interactions in induction of endogenous murine leukemia virus from low leukemic mice[END_REF][START_REF] Moroni | Lipopolysaccharide induces C-type virus in short term cultures of BALB/ c spleen cells[END_REF][START_REF] Greenberger | Induction of mouse type-C RNA virus by lipopolysaccharide[END_REF] . To examine the responsiveness of ERVs and other retroelements (REs) to microbial stimulation, we took advantage of probes or probesets in standard microarray platforms that report ERV or RE expression. Analysis of a publicly-available dataset [START_REF] Amit | Unbiased Reconstruction of a Mammalian Transcriptional Network Mediating Pathogen Responses[END_REF] uncovered specific induction of non-ecotropic MLV transcripts by LPS and poly(I:C), and suppression by Pam 3 CSK 4 (Fig. 3a,b). Early Transposon (ETn) transcripts were also induced by poly(I:C) (Fig. 3a). These findings were confirmed by LPS stimulation, which induced high MLV SU expression in WT and Emv2 -/-mouse splenocytes, also in a MyD88-independent manner (Fig. 3c and Supplementary Fig. 10). These in vitro conditions did not significantly induce eMLV expression (Fig. 3a). However, ex vivo analysis revealed higher expression of eMLV (Fig. 1c), as well as of other ERVs/REs (Supplementary Fig. 1), specifically in the colon, suggestive of microbial involvement.

Antibodies have established roles in controlling intestinal bacteria and neutralising their products, such as LPS, in the gut lumen or the systemic circulation, and antibody-deficient mice are known to display increased microbial trasnslocation [START_REF] Honda | The Microbiome in Infectious Disease and Inflammation[END_REF][START_REF] Kirkland | B cell-intrinsic MyD88 signaling prevents the lethal dissemination of commensal bacteria during colonic damage[END_REF][START_REF] Lim | Antibody and B-cell responses may control circulating lipopolysaccharide in patients with HIV infection[END_REF][START_REF] Reid | Endotoxin shock in antibody-deficient mice: unraveling the role of natural antibody and complement in the clearance of lipopolysaccharide[END_REF][START_REF] Shulzhenko | Crosstalk between B lymphocytes, microbiota and the intestinal epithelium governs immunity versus metabolism in the gut[END_REF] . It was, therefore, possible that antibody deficiency allowed microbial products to induce expression of MLV proviruses in Rag1 -/-mice, including the parents of recombinant RARVs (Supplementary Fig 1). In support of this notion, and in agreement with the established role of natural IgM in systemic clearance of bacterial LPS and protection from endotoxemia [START_REF] Kirkland | B cell-intrinsic MyD88 signaling prevents the lethal dissemination of commensal bacteria during colonic damage[END_REF][START_REF] Lim | Antibody and B-cell responses may control circulating lipopolysaccharide in patients with HIV infection[END_REF][START_REF] Reid | Endotoxin shock in antibody-deficient mice: unraveling the role of natural antibody and complement in the clearance of lipopolysaccharide[END_REF] , production of non-hypermutated IgM alone was sufficient for eMLV control (Supplementary Fig. 11). If antibodies required for preventing MLV expression were, indeed, against multiple microbial products, then antibody deficiency should not result in elevated MLV expression in the absence of microbial triggers (Supplementary Fig 12).

To begin to examine the contribution of microbial triggers, we measured eMLV expression in specific pathogen-free (SPF) Rag1 -/-mice from colonies that differed in intestinal microbiota. Importantly, the use of embryo transfer for the rederivation of these independent colonies removes adventitious organisms, including vertically-transmitted eMLVs. Therefore, any RARVs found in these rederived Rag1 -/-mouse colonies must be generated de novo in the life-history of each colony. In stark contrast to Rag1 -/-mice that were maintained on neutral pH water at NIMR, colonies of Rag1 -/-mice that were maintained on acidified water expressed minimal eMLV levels (Fig. 4a). Water acidification reduced overall bacterial diversity in the colons of Rag1 -/-mice (Supplementary Fig. 13 and Supplementary Table 2) and is a common precautionary measure used in many animal facilities that reduces bacterial colonisation within the intestinal tract and translocation into the circulation [START_REF] Wu | Chronic acid water feeding protects mice against lethal gut-derived sepsis due to Pseudomonas aeruginosa[END_REF] . Lack of eMLV expression was noted in Rag1 -/-mice obtained from The Jackson Laboratory (JAX), also maintained on acidified water (Fig. 4a). Furthermore, minimal levels of eMLV were detected in Rag1 -/-mice on neutral pH water at the Rodent Center CHCI, ETH Zurich (RCHCI) (Fig. 4a), which harboured distinct bacterial genera in comparison with Rag1 -/-mice at NIMR (Supplementary Fig. 13 and Supplementary Table 2). Lastly, negligible levels of eMLV were expressed in Rag1 -/-mice in germ-free facilities at the University of Michigan (UMICH) and offered neutral pH water (Fig. 4a). The latter two conditions also distinguished between effects of acidified water on intestinal flora and effects on other physiological processes. Thus, high eMLV expression in independentlyrederived colonies of Rag1 -/-mice correlated with the presence of the normal SPF microbiota.

Husbandry conditions contributed to high eMLV expression also in independently-rederived strains with distinct immunodeficiencies. Colonies of Ighm -/-and Tlr7 -/-mice maintained on acidified water at JAX expressed minimal levels of eMLV (Fig. 4b). Variable eMLV expression levels were detected in Myd88 -/-mice at JAX (Fig. 4b), likely because, once generated, vertical transmission of infectious eMLVs was unaffected by water acidification. Although defining the precise role of the microbiota on eMLV induction will require further investigation, collectively our results demonstrate that the high eMLV expression phenotype, in genotypes causing immunodeficiency, requires environmental interaction.

High eMLV expression in independently-rederived immunodeficient colonies reveals de novo eMLV induction in each colony. It does not, however, indicate when or how often in a colony's life-history infectious eMLV may emerge. Adult RARV-free Rag1 -/-mice, previously on acidified water, maintained low eMLV expression following switch to neutral pH water, indicating low probability of RARV emergence and spread in an individual mouse. To examine if this probability is low in general or could be higher during early mouse development, we monitored successive generations of Ighm -/-mouse colonies from two independent rederivations, one of which was recent, into the NIMR SPF facility. This analysis suggested that eMLV induction occurred during the first few filial generations (F) (Supplementary Fig. 14). Moreover, eMLV-expressing Myd88 -/-mice at JAX (Fig. 4b), were at F5 of homozygous breeding. Thus, although low in individual mice, there is high cumulative probability of infectious eMLV emergence, involving a sequence of recombination events similar to those seen in Rag1 -/-mice (Supplementary Fig. 12), and subsequent establishment in an antibody-deficient colony over a few generations.

The B6 strain historically dominated many research fields partly due to their resistance to retrovirally-induced tumours. Our results demonstrate that this important attribute of B6 mice is conditional on their immune competence, with significant implications both for the design and interpretation of mouse studies. Furthermore, our results also show that ERV activation is determined by husbandry conditions, thus accentuating potential differences in ERV expression between animal facilities.

Although well-established in the mouse [START_REF] Stocking | Murine endogenous retroviruses[END_REF][START_REF] Stoye | Studies of endogenous retroviruses reveal a continuing evolutionary saga[END_REF] , an oncogenic potential of ERVs in humans has not been observed [START_REF] Belancio | All y'all need to know 'bout retroelements in cancer[END_REF][START_REF] Romanish | Potential mechanisms of endogenous retroviral-mediated genomic instability in human cancer[END_REF] . However, non-LTR RE families have been documented to have caused human cancers by insertional mutagenesis at the somatic level [START_REF] Belancio | All y'all need to know 'bout retroelements in cancer[END_REF][START_REF] Romanish | Potential mechanisms of endogenous retroviral-mediated genomic instability in human cancer[END_REF] . Interestingly, we found that TLR stimulation of human cells induced expression of distinct ERVs and REs, including the mammalian apparent long terminal repeat (LTR) retrotransposon (MaLR) family (Supplementary Fig. 15), previously implicated in the pathogenesis of human lymphomas [START_REF] Lamprecht | Derepression of an endogenous long terminal repeat activates the CSF1R proto-oncogene in human lymphoma[END_REF] . Transcription of human ERVs and REs can also be induced by physiological activation of both adaptive and innate immune cells [START_REF] Bannert | Retroelements and the human genome: New perspectives on an old relation[END_REF] . Moreover, increased risk of lymphomas in humans is linked to infection or inflammation [START_REF] Trinchieri | Cancer and Inflammation: An Old Intuition with Rapidly Evolving New Concepts[END_REF] and also to antibody deficiencies [START_REF] Park | Common variable immunodeficiency: a new look at an old disease[END_REF] . Thus, interplay between microbial symbionts, leading to ERV/RE activation, may provide a mechanistic link between cancer and stimulation of the immune system by microbiota or pathogenic infections.

Methods

Mice

Inbred C57BL/6J (B6) and B6-backcrossed Rag1-deficient B6.129S7-Rag1 tm1Mom (Rag1 -/-) mice [START_REF] Mombaerts | RAG-1-deficient mice have no mature B and T lymphocytes[END_REF] , T cell receptor (TCR) α-deficient B6.129P2-Tcra tm1Mjo (Tcra -/-) mice [START_REF] Philpott | Lymphoid development in mice congenitally lacking T cell receptor alpha betaexpressing cells[END_REF] , TCR δ-deficient B6.129S7-Tcrd tm1Mom (Tcrd -/-) mice [START_REF] Itohara | T cell receptor delta gene mutant mice: independent generation of alpha beta T cells and programmed rearrangements of gamma delta TCR genes[END_REF] , MHC class II-deficient mice B6.129S2-H2 dlAb1-Ea (H2-A,E -/-) mice [START_REF] Cosgrove | Mice lacking MHC class II molecules[END_REF] , B cell-deficient, Ig heavy constant chain μtargeted B6.129S2-Ighm tm1Cgn (Ighm -/-) mice [START_REF] Kitamura | A B cell-deficient mouse by targeted disruption of the membrane exon of the immunoglobulin mu chain gene[END_REF] , hen-egg lysozyme (HEL)-specific B cell receptor-transgenic (Ighm -/-MD4) mice [START_REF] Goodnow | Altered immunoglobulin expression and functional silencing of self-reactive B lymphocytes in transgenic mice[END_REF] , MyD88-deficient B6.129P2-Myd88 tm1Aki (Myd88 -/-) mice [START_REF] Adachi | Targeted disruption of the MyD88 gene results in loss of IL-1-and IL-18-mediated function[END_REF] , toll-interleukin 1 receptor (TIR) domain-containing adaptor protein (TIRAP)-deficient B6.129P2-Tirap tm1Aki (Tirap -/-) mice [START_REF] Yamamoto | Essential role for TIRAP in activation of the signalling cascade shared by TLR2 and TLR4[END_REF] , and toll-like receptor adaptor molecule 1 (TICAM-1)-deficient B6.129P2-Ticam1 tm1Aki (Ticam1 -/-) mice [START_REF] Yamamoto | Role of adaptor TRIF in the MyD88-independent toll-like receptor signaling pathway[END_REF] have been described. B6-congenic mice lacking Emv2 (Emv2 -/-) were generated by 12 nuclear generations onto the B6 genetic background of the respective site on chromosome 8 from the A/J strain, which lacks the Emv2 integration, and have been previously described [START_REF] Young | Negative selection by an endogenous retrovirus promotes a higher-avidity CD4 + T cell response to retroviral infection[END_REF] . Emv2 -/-mice were subsequently crossed with B6-backcrossed Rag1 -/-mice to create Rag1 -/-Emv2 -/-mice. These strains were maintained in individually ventilated cages (IVCs) in specific pathogen-free (SPF) facilities at NIMR, and kept on UV-irradiated and filtered neutral pH water. In addition, separate colonies of Rag1 -/-mice, Ighm -/-mice, Myd88 -/-mice, Tirap -/-mice and Tcam1 -/-mice were maintained in the same facilities and constantly kept on a diet of acidified water (pH 2.5).

B6 and B6-backcrossed B6.129S7-Rag1 tm1Mom /J (Rag1 -/-) mice, B6.129S2-Ighm tm1Cgn /J (Ighm -/-) mice, B6.129S1-Tlr7 tm1Flv /J (Tlr7 -/-) mice [START_REF] Lund | Recognition of single-stranded RNA viruses by Toll-like receptor 7[END_REF] , and B6.129P2-Myd88 tm1.1Defr /J (Myd88 -/-) mice [START_REF] Hou | Toll-like receptors activate innate and adaptive immunity by using dendritic cell-intrinsic and -extrinsic mechanisms[END_REF] were also maintained in SPF facilities at The Jackson Laboratory, MA, USA (JAX), and were kept on acidified water (pH 2.8-3.2).

B6 and B6-backcrossed B6.129S7-Rag1 tm1Mom (Rag1 -/-) were also maintained in germfree (GF) facilities at the Unit for Laboratory Animal Medicine, University of Michigan, MI, USA (UMICH) and kept on autoclaved distilled water.

B6 and B6-backcrossed B6.129S1-Tlr7 tm1Flv (Tlr7 -/-) mice, and B6.129P2-Tlr9 tm1Aki (Tlr9 -/-) mice [START_REF] Hemmi | A Toll-like receptor recognizes bacterial DNA[END_REF] were also maintained in SPF facilities at the Centre d'Immunologie de Marseille-Luminy, Marseille, France (CIML) and kept on autoclaved water. B6-backcrossed TLR7-deficient B6.129P2-Tlr7 tm1Aki (Tlr7 -/-) mice [START_REF] Hemmi | Small anti-viral compounds activate immune cells via the TLR7 MyD88dependent signaling pathway[END_REF] were also maintained in SPF facilities at the London Research Institute (LRI), Cancer Research UK and kept on autoclaved water. These mice were received into the NIMR quarantine facility and bred before testing.

B6 and B6-backcrossed B6.129S7-Rag1 tm1Mom (Rag1 -/-) mice, B cell-deficient, Ig heavy chain joining region-targeted B6.129S7-Igh-J tm1Dhu (Igh-j -/-) mice [START_REF] Chen | Immunoglobulin gene rearrangement in B cell deficient mice generated by targeted deletion of the JH locus[END_REF] , IgA-deficient, Ig heavy constant α chain-targeted B6.129S7-Igha tm1Grh (Igha -/-) mice [START_REF] Harriman | Targeted deletion of the IgA constant region in mice leads to IgA deficiency with alterations in expression of other Ig isotypes[END_REF] , and polymeric Ig receptor-deficient B6.129P2-Pigr tm1Rast (Pigr -/-) mice [START_REF] Uren | Role of the polymeric Ig receptor in mucosal B cell homeostasis[END_REF] were maintained in IVC cages in SPF facilities at Rodent Center HCI, ETH Zürich, Zürich, Switzerland (RCHCI) and kept on autoclaved water. C57BL/6NCrl-backcrossed B6.129S2-Ighm tm1Cgn (Ighm -/-) and activation-induced cytidine deaminase-deficient B6.CBA-Aicda tm1Hon (Aicda -/-) mice [START_REF] Muramatsu | Class switch recombination and hypermutation require activation-induced cytidine deaminase (AID), a potential RNA editing enzyme[END_REF] , were also maintained in SPF facilities at the Center for Cancer Research, National Cancer Institute, Frederick, MD, USA (NCI) and kept on autoclaved water.

All colonies of Rag1 -/-mice tested in this study (NIMR, JAX, UMICH and RCHCI) were established by rederivation of a common JAX stock into each of these facilities. This process ensures the removal of adventitious agents, including infectious eMLVs, and leads to colonisation of the newly-rederived mice with the specific microbiota of each facility (or the lack of colonisation in the case of the germ-free facility). These independent colonies were maintained by homozygous breeding for at least 12 and up to 45 filial generations (F12-F45) prior to testing.

Colonies of Ighm -/-mice at NIMR and JAX were also established by rederivation. The Ighm -/-mouse colony at JAX was at least the F15 of homozygous breeding prior to testing. Two colonies of Ighm -/-mice, established at NIMR by two independent rederivations (as part of the unit reorganisation), were tested at different points following rederivation. The first was maintained for 16 months (F4) on a diet of neutral pH water (before switching to acidified water for F12), and the second, more recent colony was maintained on a diet of neutral pH water for only 7 months (F1-F2) prior to testing.

Colonies of Myd88 -/-mice at NIMR and JAX were also established by rederivation and maintained for approximately F16 and F5 of homozygous breeding, respectively, prior to testing. Colonies of Tlr7 -/-mice at LRI/NIMR, JAX and CIML were also established by rederivation and maintained for approximately F11, F5 and F9 of homozygous breeding, respectively, prior to testing.

Unless otherwise indicated (e.g. aged mice) all mice were used between 4 and 8 weeks after birth. All animal experiments were approved by ethical committees of respective Institutes, and conducted according to local guidelines and regulations.

Expression analyses

For transcriptional analysis, peritoneal exudate cells were isolated from B6 or Rag1 -/-mice and were subsequently purified by cell sorting, performed on MoFlo cell sorters (Dako, Fort Collins, CO, USA), as CD11b + MHC-II hi B220 -Gr1 -macrophages. RNA was isolated from the cells using TRI reagent (Sigma-Aldrich, St. Louis, US), according to manufacturer's instructions. Purified RNA samples were checked for quality using the Agilent bioanalyzer (Agilent, Santa Clara, CA, USA). Synthesis of cDNA, probe labelling and hybridisation were performed using Affymetrix MouseGene 1.0 ST oligonucleotide arrays (Affymetrix, Santa Clara, CA, USA). Primary microarray data from triplicate arrays were analysed with GeneSpring GX (Agilent Technologies, Inc., Santa Clara, CA, USA) and deposited at http:// www.ebi.ac.uk/arrayexpress (E-MEXP-3623).

ERV/RE transcription was quantified in various tissues by real-time quantitative reverse transcription-based PCR (qRT-PCR). Briefly, organs were removed from mice and placed in TRI reagent or RNAlater reagent (Invitrogen, Carlsbad, CA, USA) at each animal facility. For mice bred outside NIMR, tissues were then shipped to NIMR for further processing. Total RNA was isolated with TRI reagent, precipitated with isopropanol and washed in 75% ethanol before being dissolved in water. DNase digestion and clean-up was performed with the RNeasy Mini Kit (Qiagen, Hilden, Germany) and cDNA produced with the High Capacity Reverse Transcription kit (Applied Biosystems, Carlsbad, US) with an added RNase-inhibitor (Promega Biosciences, Madison, US). A final clean-up was performed with the QIAquick PCR purification kit (Qiagen). RNase-free water (Qiagen) and later nucleasefree water (Qiagen) was used throughout the protocol. Purified cDNA was then used as template for the amplification of target gene transcripts with SYBR Green PCR Master Mix (Applied Biosystems), run on the ABI Prism SDS 7000 and 7900HT (Applied Biosystems) cyclers, with the following primers, produced by Eurofins MWG Operon (Ebersberg, Germany): eMLV spliced env cDNA -116 bp product. Primers previously described [START_REF] Young | Negative selection by an endogenous retrovirus promotes a higher-avidity CD4 + T cell response to retroviral infection[END_REF] . that use tRNA Gln (GLN), murine endogenous retrovirus-like (MuERV-L) and intracisternal A-type particle elements (IAP) have been previously described [START_REF] Yoshinobu | Selective Up-Regulation of Intact, but Not Defective env RNAs of Endogenous Modified Polytropic Retrovirus by the Sgp3 Locus of Lupus-Prone Mice[END_REF][START_REF] Karimi | DNA Methylation and SETDB1/H3K9me3 Regulate Predominantly Distinct Sets of Genes, Retroelements, and Chimeric Transcripts in mESCs[END_REF][START_REF] Macfarlan | Endogenous retroviruses and neighboring genes are coordinately repressed by LSD1/KDM1A[END_REF] . Data are plotted as expression of the target transcript, relative to expression of Hprt in the same sample, derived using the algorithm:

A theoretical detection limit of 2 arbitrary units is also displayed as dashed horizontal lines. For eMLV expression in particular, values above 10 3 were considered as high and are indicated with red-filled symbols.

eMLV mRNA transcripts originating from the Emv2 locus or from potentially integrated RARV proviruses were distinguished by RT-PCR on cDNA reverse-transcribed using a reverse primer specific to the ecotropic env gene (5′-TTCTGGACCACCACACGAC-3′) and amplified using unique transcript-specific forward primers in the pol region together with a common reverse primer in the same region. The 3′ nucleotides of the transcriptspecific forward primers correspond to position 3576 of the pol gene, which is a C in Emv2, but a required G in all sequenced RARVs. These primers (Eurofins MWG Operon) were:

Microarray-based analyses of retroelement expression

Expression levels of ERVs and retroelements (RE) were determined in publicly-available microarray data sets, by assigning ERV-or RE-reporting probes to the correct ERV or RE family they are reporting. Individual probe sequences were obtained for mouse and human microarray platforms from the vendors' websites. Nucleotide sequence data for mouse and human REs (including elements present in ancestral species) were downloaded from RepBase Update 52 (http://www.girinst.org/repbase/) (v25/11/2011) and additional human REs from dbRIP database [START_REF] Wang | dbRIP: a highly integrated database of retrotransposon insertion polymorphisms in humans[END_REF] (http://www.dbrip.org) (v2h). Low-copy mouse ERV sequences were obtained from the literature [START_REF] Jern | Role of APOBEC3 in genetic diversity among endogenous murine leukemia viruses[END_REF][START_REF] Bromham | Discovery of a novel murine type C retrovirus by data mining[END_REF] , database searches and mining of the C57BL/6J RefSeq assembly (v37) sequence. Local BLAST libraries were produced with the NCBI C+ + Toolkit (http://blast.ncbi.nlm.nih.gov/) and a Python 3.2 (http://www.python.org/) script was used to run and query BLASTn ('-task blastn-short' optimised) for the obtained probe sequences. Three separate stringencies were used in the screening: 90% (>90% length, >90% nucleotide homology), 95% (>95% length, >95% nucleotide homology) and 100% (identical matching required). For microarray platforms where single transcripts are represented by multiple probes, an additional screen was imposed to ensure >75% of probes gave appropriate BLASTn hits. Under this threshold, probes were assumed to be divided across a RE-gene boundary and were excluded from further analysis. Probes were compiled from the 90% stringency analysis for human and mouse REs and from the 100% stringency analysis for low-copy C57BL/6J ERVs. These were used to produce a Python tool, REsearch, which will be described in detail elsewhere, and the code of which is available upon request, to mine RE expression from text-based microarray analysis output.

Emv2/eMLV copy number analysis DNA copy numbers of Emv2/eMLV were determined by real-time quantitative PCR (qPCR) on DNA samples isolated from the indicated organs or tumours using the following primers (Eurofins MWG Operon):

Emv2/eMLV env DNA -169 bp product. Primers modified from published sequences [START_REF] Yoshinobu | Selective Up-Regulation of Intact, but Not Defective env RNAs of Endogenous Modified Polytropic Retrovirus by the Sgp3 Locus of Lupus-Prone Mice[END_REF] .

Forward 5′-AGGCTGTTCCAGAGATTGTG-3′

Reverse 5′-TTCTGGACCACCACACGAC-3′ Emv2/eMLV pol DNA -76 bp product. Primers previously described [START_REF] Lotscher | Induced Prion Protein Controls Immune-Activated Retroviruses in the Mouse Spleen[END_REF] .

Forward 5′-CACTTTGAGGGATCAGGAGCC-3′

Reverse 5′-CTTCTAGGTTTAGGGTCAACACCTGT-3′ Signals were normalised for the amount of DNA used in the reactions based on amplification of the single-copy Ifnar1 gene with the following primers:

Ifnar1 DNA -150 bp product Forward 5′-AAGATGTGCTGTTCCCTTCCTCTGCTCTGA-3′ Reverse 5′-ATTATTAAAAGAAAAGACGAGGCGAAGTGG-3′

Copy numbers were calculated with a ΔΔC T method, using splenic DNA from B6 mice as control, which was assigned a value of 1 copy per haploid genome, N.

Sequencing and sequence analyses

Bacterial genera diversity was determined in faecal samples from the large intestines of mice, by high-throughput sequencing of amplicons of bacterial DNA encoding 16S ribosomal RNA, using a the Roche FLX Genome Sequencer. Samples were either collected at NIMR or at RCHCI and were subsequently transported frozen to NIMR, where DNA was isolated, using the QIAamp DNA Stool Mini Kit (Qiagen). DNA amplification, sequencing and metagenomic analysis was performed by DNAVision (Gosselies, Belgium).

The region of the pol gene carrying the inactivating mutation in Emv2 was sequenced in isolated RARVs as described below. A 708bp fragment spanning this region was amplified from genomic DNA isolated from Mus dunni cells infected with the respective RARV using the following primers (Eurofins MWG Operon):

Emv2/eMLV pol DNA -708 bp product.

Forward 5′-ATCGGGCCTCGGCCAAGAAAG-3′

Reverse 5′-CCGGGAGAGGGAGTAAGGTGGC-3′ RARV genomes were amplified from the same DNA template in two halves using the following primers (Eurofins MWG Operon):

RARV first half -4074 bp product.

Forward 5′-GCGCCAGTCCTCCGATAGACT-3′

Reverse 5′-CCGGGAGAGGGAGTAAGGTGGC-3′

RARV second half -4909 bp product.

Forward 5′-ATCGGGCCTCGGCCAAGAAAG-3′

Reverse 5′-TGCAACAGCAAAAGGCTTTATTGG-3′ PCR products were purified with the QIAquick PCR purification kit (Qiagen) and subjected to sequencing at Source BioScience (Cambridge, UK).

Sequence analyses, comparisons and alignments were performed with Vector NTI v11.5 (Invitrogen). RARV contigs were aligned against B6 MLVs as previously defined [START_REF] Jern | Role of APOBEC3 in genetic diversity among endogenous murine leukemia viruses[END_REF] using MAFFT within UGENE software [START_REF] Katoh | MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform[END_REF][START_REF] Martin | RDP3: a flexible and fast computer program for analyzing recombination[END_REF] . Distance plots were calculated with RDP (Recombination Detection Program) v4.16, using a 100 bp window and a 10 bp shift [START_REF] Martin | RDP3: a flexible and fast computer program for analyzing recombination[END_REF] . RARV phylogenetic analyses were performed with PHYLIP (Phylogeny inference package) v3.2 within UGENE software.

FACS

Cell suspensions from spleens, lymph nodes or peritoneal exudates were stained with directly-conjugated antibodies to surface markers, obtained from eBiosciences (San Diego, CA, USA), CALTAG/Invitrogen (Carlsbad, CA, USA), BD Biosciences (San Jose, CA, USA) or BioLegend (San Diego, CA, USA). MLV SU was detected using the 83A25 monoclonal antibody [START_REF] Evans | A neutralizable epitope common to the envelope glycoproteins of ecotropic, polytropic, xenotropic, and amphotropic murine leukemia viruses[END_REF] (rat IgG2a, anti-MLV SU) as the primary reagent, followed by staining with a biotinylated anti-rat IgG2a antibody (clone RG7/1.30, BD Biosciences) as the secondary reagent, and a streptavidin-phycoerythrin (PE) conjugate (BioLegend) or a streptavidin-PE Texas Red conjugate (CALTAG/Invitrogen) as the tertiary reagent. Fourand 8-color cytometry was performed on FACSCalibur (BD Biosciences) and CyAn (Dako, Fort Collins, CO) flow cytometers, respectively, and analysed with FlowJo v8.7 (Tree Star Inc., Ashland, OR, USA) or Summit v4.3 (Dako) analysis software, respectively.

Retroviral isolation and assays

For the isolation of infectious MLVs plasma samples obtained from Rag1 -/-mice were incubated with Mus dunni cells transduced with the XG7 replication-defective retroviral vector, expressing green fluorescent protein (GFP) from a human cytomegalovirus (hCMV) promoter and a neomycin-resistance gene under the control of the LTR [START_REF] Bock | Use of a transient assay for studying the genetic determinants of Fv1 restriction[END_REF] . The presence of infectious MLVs was examined after 10-14 days of culture by testing for the presence of pseudotyped XG7 vector in culture supernatant. For this, culture supernatant of XG7transduced Mus dunni cells that had been incubated with plasma samples was subsequently added onto untransduced Mus dunni cells, which were then assessed for GFP expression by flow cytometry 3 days later. The Fv1 tropism of infectious MLVs was determined by adding serial dilutions of culture supernatant of XG7-transduced Mus dunni cells that had been incubated with plasma samples onto B-3T3 or N-3T3 cells. Infection was quantified by GFP expression in these cells 3 days later. B-tropic and N-tropic stocks of F-MLV, obtained as culture supernatant of Mus dunni cells chronically infected with these viruses, were used as controls. Results were expressed as B:N ratios, which were the percentage of GFP + cells in B-3T3 cultures, divided by the percentage of GFP + cells in N-3T3 cultures.

Histology

For histological analysis, organs were collected in formalin immediately after culling of donor mice. Histological sections were prepared and stained with haematoxylin and eosin and assessed by Dr Mark Stidworthy at IZVG Pathology, Leeds, UK.

Transmission electron microscopy

Samples were immersion fixed in 2% glutaraldehyde/2% paraformaldehyde and post-fixed in 1% osmium tetroxide using 0.1 M sodium cacodylate buffer pH 7.2. Aqueous uranyl acetate was followed by dehydration through a graded ethanol series and propylene oxide. Samples were then embedded in Epon and 50nm sections mounted on pioloform coated grids and stained with ethanolic uranyl acetate followed by Reynold's lead citrate. They were viewed with a JEOL 100EX transmission electron microscope (JEOL, Tokyo, Japan) equipped with an ORIUS 1000 CCD camera (Gatan, Pleasanton, CA, USA).

Statistical analyses

Statistical comparisons were made using SigmaPlot 12.0 (Systat Software Inc., Germany). Parametric comparisons of normally-distributed values that satisfied the variance criteria were made by unpaired Student's t-tests. Pairwise comparisons of data sets that did not pass the variance test were compared with non-parametric two-tailed Mann-Whitney Rank Sum. Bacterial diversity was compared with Analysis of variance (ANOVA) tests with Bonferroni correction for multiple comparisons. Tumour incidence rates were compared by Log-Rank Survival analysis of Kaplan-Meier curves. ANOVA and statistical comparisons of microarray data were made using GeneSpring GX, with Benjamini-Hochberg false discovery rate (FDR) correction for multiple comparisons. /-mice. f, eMLV spliced env mRNA expression in the spleens of the indicated strains (p<0.001 between WT and either Ighm -/-or Ighm -/-MD4 mice; one-way ANOVA). g, MLV SU expression in splenic lymphocytes from WT or Ighm -/-MD4 mice. h, eMLV spliced env mRNA expression in the spleens of the indicated strains (p<0.001 between WT and either Myd88 -/-or Tlr7 -/- mice; one-way ANOVA). In c, f and h, each symbol is an individual mouse. In d, e and g, plots are representative of 4 mice per group. In f and h, values above 10 3 were considered high and are indicated with red-filled symbols. The scale indicates the probability of base substitution per site. e, eMLV spliced env mRNA expression in the spleens of Rag1 -/-mice or vertically-infected Rag1 -/-Emv2 -/-mice. Each dot is an individual mouse (p<0.001; unpaired Student's t-test). Values above 10 3 were considered high and are indicated with red-filled symbols. f, MLV SU expression in splenocytes from Rag1 -/-or vertically- infected Rag1 -/-Emv2 -/-mice (representative of 9 mice per group). g, eMLV DNA copy numbers per haploid genome, determined by qPCR for the pol or ecotropic env gene, in DNA from the spleens of healthy Rag1 -/-(right) or vertically-infected Rag1 -/-Emv2 -/- mice (left). Symbols represent individual mice, grouped according to their age. The sensitivity limit of this PCR method was determined as a median of 0.0003 copies per haploid genome, using Emv2 -/-mice. eMLV DNA copy numbers for Rag1 -/-mice include Emv2 (1/N). h, Tumour (leukaemias/lymphomas) incidence in cohorts of WT (n=37), Rag1 -/-(n=38) or vertically-infected Rag1 -/-Emv2 -/-mice (n=23) at the NIMR SPF facility (p<0.000001 between WT and Rag1 -/-mice; p=0.00025 between WT and Rag1 -/-Emv2 -/-mice; Log-Rank Survival analysis). or acidified water (pH 2.5) at NIMR, on acidified water (pH 2.8) at JAX, on neutral pH at RCHCI or in germ-free (GF) facilities at UMICH (p<0.016 between Rag1 -/-mice at NIMR SPF and all other groups; one-way ANOVA). b, eMLV spliced env mRNA expression in the spleens of Ighm -/-, Myd88 -/-or Tlr7 -/-mice on neutral pH water (SPF) at NIMR or on acidified water (pH 2.8) at JAX (p=0.005 and p=0.029 for Ighm -/-and Tlr7 -/-mice, respectively; unpaired Student's t-test). Each dot is an individual mouse and values above 10 3 were considered high and are indicated with red-filled symbols.

Forward

  virus (MMTV) spliced env cDNA -116 bp product Forward 5′-AGAGCGGAACGGACTCACCA-3′ Reverse 5′-TCAGTGAAAGGTCGGATGAA-3′ Hprt cDNA -92 bp product Forward 5′-TTGTATACCTAATCATTATGCCGAG-3′ Reverse 5′-CATCTCGAGCAAGTCTTTCA-3′ Primers specific for polytropic MLV (pMLV), modified polytropic MLV (mpMLV), xenotropic MLV (xMLV), Mus musculus type D retrovirus (MusD), murine retroviruses

  Emv2 specific mRNA forward primer Forward 5′-CCTGGGTTTGCGGAAATGGCAC-3′ RARV specific mRNA forward primer Forward 5′-CCTGGGTTTGCGGAAATGGCGG-3′ Common reverse primer Reverse 5′-TTTGGCGTAGCCCTGCTTCTCG-3′ Both PCRs produce a 192 bp product.

Figure 1 .

 1 Figure 1. eMLV activation in antibody-deficient mice a, Significantly upregulated (>4-fold) genes in CD11b + MHC-II hi B220 -Gr1 -macrophages from Rag1 -/-mice compared with macrophages from WT mice. Triplicate microarrays from cells isolated from 40 mice are shown. b, eMLV spliced env mRNA expression in the same cells as in a. Each symbol represents macrophages from 20 mice (p=0.024; paired Student's t-test). c, eMLV spliced env mRNA expression in indicated organs from WT or Rag1 -/- mice (spleen: p=0.020; small intestine: p=0.032; large intestine: p=0.004; lung: p= 0.001; muscle: p=0.016; and kidney: p=0.009; unpaired Student's t-test).d, e, MLV SU expression in splenocytes (d) or in indicated cell types (e) from WT or Rag1 -/-mice. f, eMLV spliced env mRNA expression in the spleens of the indicated strains (p<0.001 between WT and either Ighm -/-or Ighm -/-MD4 mice; one-way ANOVA). g, MLV SU expression in splenic lymphocytes from WT or Ighm -/-MD4 mice. h, eMLV spliced env mRNA expression in the spleens of the indicated strains (p<0.001 between WT and either Myd88 -/-or Tlr7 -/-

Figure 2 .

 2 Figure 2. Retroviremia and leukaemias/lymphomas in antibody-deficient mice a, Detection of infectious MLV (RARV-5/XG7) from the plasma of a representative Rag1 -/-mouse by restoring infectivity of the green fluorescent protein (GFP)-expressing XG7 retroviral vector in the indicated cell type. Numbers within the plots denote the percentage of retrovirally-transduced (GFP + ) cells. b, Fv1 tropism of RARVs isolated from 6-(R2-R4) or 25-(R5-R8) week-old healthy Rag1 -/-mice, shown as the ratio of infectivity in B-3T3 to N-3T3 cells (B:N ratio). B-and N-tropic strains of Friend MLV (F-MLV) are shown for comparison. c, Amino acid residues of capsid positions 105-113 deduced from the nucleotide sequence of Emv2 and the same RARVs as in b. Dots indicate identities. d, Phylogenetic tree of the same RARVs as in b. The scale indicates the probability of base substitution per site. e, eMLV spliced env mRNA expression in the spleens of Rag1 -/-mice or vertically-infected Rag1 -/-Emv2 -/-mice. Each dot is an individual mouse (p<0.001;

Figure 3 .

 3 Figure 3. Murine ERV activation by microbial products a, ERV/RE-reporting probeset (Supplementary Table3) signals in a publicly-available Affymetrix HT Mouse Genome 430A microarray dataset 20 (E-GEOD-17721) of WT B6 bone marrow-derived dendritic cells following stimulation with microbial products. Black arrows indicate the probesets that are significantly regulated (p<0.05) more than 2-fold by at least one stimulus. Mela (Emv2)-specific probesets are also indicated by grey arrows for

3

 3

  ) signals in a publicly-available Affymetrix HT Mouse Genome 430A microarray dataset 20 (E-GEOD-17721) of WT B6 bone marrow-derived dendritic cells following stimulation with microbial products. Black arrows indicate the probesets that are significantly regulated (p<0.05) more than 2-fold by at least one stimulus. Mela (Emv2)-specific probesets are also indicated by grey arrows for comparison. b, Mean log 2 fold-change in MLV-reporting probeset in the same dataset. c, MLV SU expression in WT or Emv2 -/-splenocytes before (open histograms) and after stimulation with 10 μg/ml LPS for 48 hrs (grey-shaded histograms), according to Forward scatter (Fsc) and CD19 expression. Numbers with the plots denote the percentage of cells within each gate and represent 2 donors each analysed in duplicate.

Figure 4 .

 4 Figure 4. eMLV activation in antibody-deficiency depends on husbandry conditions a, eMLV spliced env mRNA expression in the spleens of Rag1 -/-mice on neutral pH (SPF)

Nature. Author manuscript; available in PMC 2013 May 29.

Acknowledgments

We wish to thank Prof. Wolf-Dietrich Hardt for mouse samples and helpful discussion, Ms Lara Sellés Vidal for technical assistance, and colleagues for critical reading of the manuscript. We also wish to thank the staff of the Unit for Laboratory Animal Medicine, University of Michigan for the provision of germ-free mice. We are grateful for assistance from the Division of Biological Services, the Flow Cytometry, Electron Microscopy and Microarray Facilities at NIMR. This work was supported by the UK Medical Research Council (U117581330 and U117512710).

Supplementary Material

Refer to Web version on PubMed Central for supplementary material.


Nicolas Vallee
email: nicolas.vallee5@hotmail.fr

Emmanuel Dugrenot

Anne-Virginie Desruelle

Catherine Tardivel

Jean-Charles Martin

Anthony Guernec

Alain Boussuges

Sarah Rives

Jean-Jacques Risso

François Guerrero

Evidence of a hormonal reshuffle in the cecal metabolome fingerprint of a strain of rats resistant to decompression sickness

On one side, decompression sickness (DCS) with neurological disorders lead to a reshuffle of the fecal metabolome from rat caecum. On the other side, there is high inter-individual variability in terms of occurrence of DCS. One could wonder whether the fecal metabolome could be linked to the DCSsusceptibility. We decided to study male and female rats selected for their resistance to decompression sickness, and we hypothesize a strong impregnation concerning the fecal metabolome. The aim is to verify whether the rats resistant to the accident have a fecal metabolomic signature different from the stem generations sensitive to DCS. 39 DCS-resistant animals (21 females and 18 males), aged 14 weeks, were compared to 18 age-matched standard Wistar rats (10 females and 8 males), i.e., the same as those we used for the founding stock. Conventional and ChemRICH approaches helped the metabolomic interpretation of the 226 chemical compounds analyzed in the cecal content. Statistical analysis shows a panel of 81 compounds whose expression had changed following the selection of rats based on their resistance to DCS. 63 compounds are sex related. 39 are in common. This study shows the spectral fingerprint of the fecal metabolome from the caecum of a strain of rats resistant to decompression sickness. This study also confirms a difference linked to sex in the metabolome of non-selected rats, which disappear with selective breeding. Results suggest hormonal and energetic reshuffle, including steroids sugars or antibiotic compounds, whether in the host or in the microbial community.

In scuba diving or when working under pressure, the inhaled gases dissolve in the organism tissues as pressure increases. These gases may then give rise to bubbles during the desaturation phase. Symptoms of decompression sickness (DCS) may appear following an excessive quantities of bubbles in the organism 1 . It is recognized that the amount of venous bubbles is a positively correlated to the risk of DCS 2,3 . However, for a same dive profile, the intra-and inter-individual variability is high in terms of bubble quantity and occurrence of DCS.

 .

 . The present study is particularly devoted to the selection of a fecal metabolome operated upon generation of rat strains resistant to DCS. Metabolomics analysis was

Animals. 39 DCS-resistant (Res) animals (21 females and 18 males), aged 14 weeks, bred at the university animal house were used in this study. They were compared to 18 age-matched standard (Std) Wistar rats (10 females and 8 males), i.e., the same as those we used for the founding stock, obtained from the same breeder (Janvier Labs, St Genêts, France). Because our aim was to study the differences in the fecal metabolome associated with resistance to DCS independently of possible persistent modifications induced by diving itself [START_REF] Eftedal | Acute and potentially persistent effects of scuba diving on the blood transcriptome of experienced divers[END_REF][START_REF] Montcalm-Smith | Acclimation to decompression sickness in rats[END_REF][START_REF] De Maistre | Cecal metabolome fingerprint in a rat model of decompression sickness with neurological disorders[END_REF] none of these individuals were previously exposed to hyperbaric treatment. The standard rats were acclimated with the facility for at least 2 weeks. All animals were housed three per cage under controlled temperature (21 ± 1 °C) and lighting (12 h of light per day, 0600-1800) at the university animal housing facility until the day of the day of cecal content harvesting. They were fed standard rat chow and water ad libitum.

Fecal metabolome. Animals were anaesthetized first by administration of gaseous isoflurane (4.0% in 100% air flow at 2.0 l/min) through face mask for 5 min before intraperitoneal injection of ketamine (100 mg kg -1 body weight) and xylazine (10 mg kg -1 body weight). Anaesthesia level was determined by testing the lack of withdrawal reflexes in response to pinches of the distal hind limbs. The cecum was separated from the rest of the digestive tract after ligation. The cecum was weighed and then opened using a scalpel. Part of its contents was placed in a 1.5-ml Eppendorf tube and kept at -80 °C until metabolomic analysis. Finally, animals were euthanized with a lethal dose of anesthetic.

This technique is similar to that previously used in our studies [START_REF] De Maistre | Cecal metabolome fingerprint in a rat model of decompression sickness with neurological disorders[END_REF] . 100-150 mg of cecal content were homogenized in cooled methanol (3µL/mg feces) at -20 °C. Samples were vortexed for 1 min and incubated at -20 °C for 30 min. Samples were then centrifuged for 15 min (11,000 × g, 4 °C). The supernatant recovered from each sample was filtered through 10 KDa filter tubes by centrifuging for 45 min (11,000 × g, 4 °C). The extracts obtained were then dried using a stream of nitrogen and then frozen at -80 °C.

LCMS metabolomic analyses were performed essentially as described earlier [START_REF] Rosique | Assessment of the effects of repeated doses of potassium iodide intake during pregnancy on male and female rat offspring using metabolomics and lipidomics[END_REF] . All the dried polar extracts were first reconstituted with 150 µl acetonitrile/water (50:50; v:v). The samples were separated using high performance liquid chromatography (UPLC) ultimate 3000 (Thermo Scientific), coupled to a high-resolution Q-Exactive Plus quadrupole-orbitrap hybrid mass spectrometer (HRMS), equipped with electrospray ionization source (H-ESI II). The chromatographic separation was performed on a binary solvent system using a HILIC column (Merk,SeQuant ZIC-HILIC, 150 mm × 2.1 mm, 5 μm, 200 A) at 25 °C with a flow rate of 0.25 ml min -1 . The injection volume was 5 μl. The mobile phase consisted of a combination of solvent A (100% water, 16 mM ammonium formate) and solvent B (100% acetonitrile 0.1% formic acid). The following gradient conditions were used: 0 to 2 min, isocratic 97% B;, 2 to 10 min, linear from 97 to 70% B; 10 to 15 min, linear 70 to 10% B; 15 to 17 min, isocratic 10% B; 17 to 18 min linear from 10 to 97% B; from 18 to 22 min isocratic 97% B. The separated molecules were analyzed in both positive and negative ionization modes in the same run (switch mode). The repeatability of the analysis was checked by analyzing interspaced (1 out of every 5 samples) quality control samples (QC).

Data processing and molecule identification: All the raw data generated by the LCMS were converted to mzXML by ProteoWizard (Version 2.0), and then processed by MZmine 2.26.

The data processing was performed in different steps. The first step was peak picking and required the application of the "CentWave" algorithm, the method of choice for processing centroided data acquired by HRMS. After extracting the mass to charge ratio (m/z), the retention time and the intensity for every ion, the peak picking step is then followed by isotope grouping, alignment and gap filling. The data were further processed to eliminate artifacts such as signals found in the blank, peaks without Gaussian shape or corresponding to noise. The analytical drift over the sample runs is then corrected by applying a linear correction as described by Van der Kloet et al. [START_REF] Van Der Kloet | Analytical error reduction using single point calibration for accurate and precise metabolomic phenotyping[END_REF] . Then all features that represent over 30% of the deviation from the median by applying the relative standard deviation filtration were removed (a coefficient of variation less than 30% on QC samples peaks was applied to all samples). All these steps generally leave 10-20% of the initial features.

Metabolites annotation was then performed using the post-processed dataset. An in-house database referencing more than 800 metabolites with their chromatographic retention time acquired with a HILIC column, together with their exact mass and MSMS spectra obtained in positive and negative ionization modes, including their adducts and neutral losses. Matching the two datasets was performed using the "bank inhouse" tool of the W4M web application (https:// workfl ow4m etabo lomics. usega laxy. fr/) [START_REF] Giacomoni | Workflow4Metabolomics: a collaborative research infrastructure for computational metabolomics[END_REF] . Uncertainties were removed by comparing the MSMS spectra to that of our database or found in publicly available databases (HMDB, Mass Bank, MzCloud, Metlin). These led to Level 1 (MSMS, retention time, MS) or 2 identification (retention time, MS). Finally, 226 metabolites per rat were obtained.

Statistical analyses.

Statistical analyses were performed essentially as described in our previous study [START_REF] De Maistre | Cecal metabolome fingerprint in a rat model of decompression sickness with neurological disorders[END_REF] .

Most series of values fell between 0 and 1 and the distribution was positively skewed. Prior analysis, scalecontracting transformation was applied with log(X + 1). The difference was analyzed using 2-way ANOVA (type III SS) on clinical status and diet, comprising interactions, followed by post-hoc Tukey's (HSD) and Benjamini-Hochberg's (False Rate Discovery) tests. Principal component analysis (Pearson correlation coefficient), agglomerative hierarchical clustering (AHC) (dissimilarity; Euclidean distance; Ward's method) helped by k-means clustering were used to design the heat map and volcano plot, from normalized data of the 226 features of the 57 diving rats. A random forest classifier (Sampling: random with replacement; method: random input) was also used in order to extract the most contributing compounds. The software was XlStat Biomed from Addinsoft. Maximum accepted alpha level was 5%.

Results

Metabolic analysis of feces. 226 metabolites were analyzed. Principal component analysis (PCA; Pearson test) (Fig. 1) of the fecal metabolome from rat caecum reveals two partially overlapped groups, associated with DCS-resistance, where the axes F1 and F2 explain 25% of the variability. A similar PCA to reveal a gender effect did not show any effect for this factor.

An Ascending Hierarchical Classification (AHC) was carried out as part of the Heat Map established according to the intensity of the 226 compounds analyzed (Fig. 2). Following the evolution of the variances according to the number of classes, two inflection points are located in the 2nd and 4th class. The division into 2 classes explains 97% of the intragroup variability. According to this division, the first class (I) contains 18 Std and 3 Res rats, while the second class (II) contains only Res rats.

The division into 4 classes explains 74% of of the intragroup variability. Its first class Ia contains 10 Std rats with only females, and the second class (Ib) contains 8 male Std rats and 3 Res rats (including 1 female). The class IIa contains 17 Res rats with 7 females, and the last one (IIb) contains 19 Res with 11 females.

The level of metabolite expression is marked according to the strain, with also a pronounced dichotomy between males and females in standard rats. This difference between males and females is no longer observed in Res.

The AHC of the Heat Map allows to visualize on the abscissa a separation of the metabolites between the Std rats on the left (orange) and the Res rats on the right (green). In this same left part of the map in Std (orange), an over-expression of fecal compounds in female rats is visible in blue on the lower part. Offset, just above, an over-expression of the compounds (in blue) is visible in male Std rats. Differences between males and females are no longer so obvious in Res (lower part of the heat map, notably).

More generally, dichotomies appear at the ends of the abscissa between the Std and the Res, as well as between the compounds presented at the ends of the ordinate. Std females are clearly separated from Std males (black, orange), but this is no more true in Res animals (green). Metabolomic analysis on gender. Graph 4 (Volcano Plot, Fig. 4) shows the level of metabolite expression in rat feces by sex. Metabolites located on the left (n = 17) of the vertical axis are significantly (p < 0.05) higher in females and those on the right are lower in males (n = 46). We emphasized that all metabolites except two influenced by Sex*Strain (16 green dots) are greater in males. Among these two exceptions, Cis-aconitate has a p-value near 0.05 and a low fold-change, while cortisol (in the upper left corner) has a very significant p-value and a great fold-change. Concretely, cortisol levels are higher in Std females but they decrease with resistance to DCS to approximate males (Std and Res). Red dot on its immediate right closeness represents another product of the cortisol metabolism: 21-deoxycortisol. 21-deoxycortisol levels are higher in Standard females but they decrease with resistance to approximate males. This last decreased between Std and Res animals but in a lesser extent. Then, both yellow dot (Sex) on the right of cortisol metabolites, are litocholate and 5b-cholanic acid -3-one. In the upper right corner, cortexolone has higher fold-change ratio and p-value. On its left, dots of suberate (yellow; Sex) and enterolactone (green; Sex*Strain) are overlapped. Enterodiol (red) is just below, on the p-value scale. Blue points (Sex*Interaction) below mark aminoacid (Taurine and tyramine).

In order to access enrichment statistics and to analyze differential expression rates, we submitted these results to the ChemRICH database [START_REF] Barupal | Chemical similarity enrichment analysis (ChemRICH) as alternative to biochemical pathway mapping for metabolomic datasets[END_REF] (www. chemr ich. fiehn lab. ucdav is. edu). 226 compounds accompanied by their variation factor and their p-values were uploaded to the ChemRICH server. 219 compounds were accepted. We analyzed the effects of the sex and those linked to the strain resistance. The ChemRich graphics aggregate metabolites that are significantly altered (depending on gender or resistance) according to their chemical similarity.

The ChemRich graph (Fig. 5) based on gender shows a global overexpression (red circles) in the quantity of cholic acids (8 of the 12 identified compounds are altered) in males. The key compound is litocholate (a bile acid which is, however, underexpressed in males). Dipeptides are also overexpressed in the feces of male rats. Also noteworthy is the group of hexosamines (4/4 overexpressed in males), the key compound of which is glucosamine, useful in glycosylation. There is an underexpression of disaccharides (5/7) in males compared to females. Concerning pregnenediones, the 4 (out of 4) metabolites analyzed are significantly altered. This group includes cortisol and its derivate (21-deoxycortisol), both overrepresented in females but whose amounts decrease over generations, and also phytohormones overexpressed in males (17a-Hydroxyprogesterone and cortexolone). Cortexolone, an inhibitor of testosterone receptors, is particularly overexpressed in males with a fold-change of approximately 11. It decreases in amount in resistant individuals to approach the stable values of females. In another red circle in the graphic, it can be seen that enterodiol, a phytoestrogen from the benzyl compound family, is overexpressed in males. Enterodiol concentration profiles are similar to those of cortexolone. Regarding phenols, 2 of the 7 metabolites analyzed are significantly altered. The first, presented by the Chem-Rich database as a key derivative, is 4-aminophenol. The other compound is 2-aminophenol. Both are overexpressed in males. Also in this family, phloretin was initially overexpressed in males, while tyrosol was initially overexpressed in females: they decreased with resistance to DCS.

Metabolomic analysis on DCS-resistance.

According to the Volcano Plot dedicated to the resistance to DCS (Fig. 6), 57 metabolites appearing on the right of the graph are significantly under-expressed in Res group compared to the Std animals while 24 other metabolites (on the left) are increased in resistant individuals. All the red dots (Sex*Strain*Interaction) are located to the right of the graph, which implies that they are expressed more in standard than in DCS-resistant animals. These red values of males and females converge on the downside with resistance to DCS. The metabolite which decreases the most in proportion, in the right upper corner (in red), and which diminished according to Sex*Strain*Interaction is enterodiol. On its left, glucose-6-P is in dark green, followed by dehydro-shikimate (light green), 3-hydroxyphenyl propionic acid (dark green), 3-(2-hydroxyphenyl)propanoate (red), biliverdin (dark green), and then 2 variant of raffinose (red). The red dots (Sex*Strain*Interaction) are more or less evenly distributed on both sides of the axis.

On the opposite, from the left to the right (in light green), agmatine sulfate, 5-hydroxyindoleacetate, lysoPI(16:0) (palmitoyl lysophosphatidylinositol), tryptamine and 2,6 quinolediol increase with resistance to DCS. Enterolactone is the upper dot in green on the left of the graph which is link to the Strain*Sex effect.

We then set up and trained a random forest classification (machine learning) on whole data (Sampling: random with replacement; method: random input; number of trees: 300; Sample size: 30; Min Node: 2; Max depth: 25; Mtry: 5; Cp: 0.0001) in order to extracted most contributing compounds for the description of breeding, i.e. resistance. We have chosen the algorithm and the hyperparameters with the lowest error rate. The Out-Of-Bag (OOB), i.e. error rate, value of random forest was of 3.51% and the algorithm predicted correctly, according to the confusion matrix, 95.1% of observed classes. We have chosen to select the first ten compounds, that is to say those having the greatest importance in the algorithm. The compounds selected in decreasing order of importance are: 5-hydroxyindolacetate, enterodiol, sucrose, 2,6-quinolinediol, 3-dehydroshikimate, galacturonate, azelate, maltose, agmatine sulfate, L-gulonolactone. The other algorithms presented slightly different results depending on the settings of the hyperparameters, but in the end 8 compounds come back redundantly. 5-hydroxyindolacetate and enterodiol had the greatest importance values in the algorithm.

The ChemRich graph (Fig. 7 + supp data 2 for details) based on resistance of strains shows a global underexpression in Resistant individuals compared to non-selected ones (red circles) in the quantity of cholic acids For example, more adipate is found in the feces of male rats compared to females. Metabolite families are also scattered according to their increasing hydrophobicity (or decreasing hydrophilicity), from left to right along the abscissa (expressed as log P value).

(3 compounds are significant). Dipeptides (9 decreased on 10 significantly altered, with N-acetyl asparagine as key compound) disaccharides (7/7 decreased, with sucrose as key compound) pregnenediones (cortisol, 21 deoxycortisol, cortexolone) hexosamines (with glucosamine and glucosamine 6-P) hydroxybutyrate and phenols (including phloretin and tyrosol) are underrepresented in Res groups.

In contrast, overexpressions (blue disc) are visible in the feces of DCS-resistant animals for 2 basic amino acids (L-glutamine and asparagine), 2 purines nucleosides (guanosine and inosine), and 2 dicarboxylic acids (denoted 0 = FA in the graph, including azelate and undecanedioic acid).

Enterodiol, the phytoestrogen of the benzyl compound family (purple circle), is overexpressed in Std rats, while enterolactone is overexpressed in Res animals. In the biogenic monoamine cluster (purple circle) tryptamine increases while histamine decreases in DCS-resistant animals.

Discussion

Influence of DCS-resistance. The DCS-resistant animal breeding program resulted in a strain of Wistar rats that was 3 times less likely to develop signs suggestive of DCS [START_REF] Lautridou | Evidence of heritable determinants of decompression sickness in rats[END_REF][START_REF] Lautridou | Physiological characteristics associated with increased resistance to decompression sickness in male and female rats[END_REF] , independently from any preconditioning strategy or diving acclimatization. This unique model of resistance to DCS makes therefore possible the study its physiological background, and particularly its fecal metabolome from caecum, associated with resistance to DCS by comparing these "spontaneous" DCS-resistant Wistar rats with standard non-selected ones. The main result of this analysis is a difference between the standard and DCS-resistant rats in their fecal composition from caecum.

Sex was previously described as a factor contributing to DCS [START_REF] Buzzacott | A ternary model of decompression sickness in rats[END_REF][START_REF] Hagberg | Incidence and risk factors for symptoms of decompression sickness among male and female dive masters and instructors-a retrospective cohort study[END_REF] . Our AHC analysis also confirms differences between males and females in the non-selected animals but it fades in the rats selected for their resistance to DCS. This concerns 63 metabolites, 25 of which are unrelated to resistance. Although it may be of interest elsewhere, the differences in the metabolome linked only to sex, and therefore not linked to selection, does not represent the objective of this work. The significant influences of Sex, Sex*Interaction, and also pure Interaction, will not be discussed here. By postulating that the fruit of the breeding is the result of the selection of rats resistant to DCS, we can consider that 81 fecal compounds are related to this phenotypical outcome. Of course, some of them (n = 39) are also influenced by sex. This confirms that a sex-related fecal metabolism may also be linked to a phenotype at risk for DCS. This implies that the expression of these metabolites must be able to be influenced by the presence of the genome linked to X or Y, directly or indirectly. This should be in the 16 (Sex*Strain) and 23 (Sex*Strain*Interaction) compounds. While the analysis is obviously not exhaustive, these 39 compounds represent an important part of the 81 substances whose level of expression has been modified by breeding. There may also be mutual, or cascading, interactions among all these metabolites that alter their respective levels of expression. For the other compounds (36 Strain and 6 Strain*Interaction), it must also be possible to suggest that their content, although being able to be modulated elsewhere, must also be modulated by the autosomal part of the genome. The gut microbiota has not yet been discussed, but obviously it must have a role in the expression of fecal metabolites.

Cecal content of metabolites linked to the breeding. Of the 81 metabolites linked to breeding, 39 are sex-linked and 23 of which are synergistically modulated.

These 23 compounds (in red, Sex*Strain*Interaction) present a homogeneous group effect with a general downward trend in DCS-resistant rats, even if this drop is sometimes true only in one sex. Specifically, it can be said that none of these 23 metabolites significantly increase in Res group and that the male and female profiles (the variation of which sometimes affects only one sex) converge in individuals resistant to DCS, which gives an average downward trend.

The male and female profiles of the 16 compounds (in green, Sex*Strain) also tend to converge in DCSresistant groups except for 2 metabolites which diverge: enterolactone and methyl succinic acid.

Concerning the 36 Strain and the 6 Strain*Interaction compounds, one cannot apply a general tendency to increase or decrease, but only an aptitude to vary with the selection breeding.

Expression of metabolites essentially linked to the microbial community. We found 8 metabolites specific to the gut microbial community that are also under pressure from selection.

Among them, enterodiol (Sex*Strain*Interaction) _highlighted as a key factor in the algorithm generated by the random forest classification_ enterolactone (Sex*Strain) and phloretin (Strain) are described to be endocrinedisrupting chemicals, or as phytoestrogen, because they are thought to interfere with estrogen metabolism in animals and humans [START_REF] Thomson | Endocrine-Disrupting Chemicals in Food 211-258[END_REF] . Although not specific of the microbial community, another sexual hormone, cortexolone (Sex*Strain*Interaction) which is androgen antagonist, decreased. These compounds could participate in blurring the difference between the sexes. Their role is still unclear, while inhibitory actions on aromatase [START_REF] Barakat | [END_REF] or blocking cell-membrane hormones-receptors were reported 30 . These three gut-microbiota products have also weak antioxidant activity 31 like another compound azelate, a byproduct of pityrosporum fungal mycelia metabolism [START_REF] Schulte | Azelaic acid: evidence-based update on mechanism of action and clinical application[END_REF] .

Trehalose [START_REF] Elbein | New insights on trehalose: a multifunctional molecule[END_REF] as shikimate and its derivative 3-dehydroshikimate [START_REF] Herrmann | The shikimate pathway[END_REF] , the three being down-regulated in DCSresistant individuals, are produced by plants yeast, fungi, insects, invertebrates and bacteria but never by animals. The polyamine cadaverine also comes from colonic bacteria [START_REF] Davila | Re-print of "Intestinal luminal nitrogen metabolism: role of the gut microbiota and consequences for the host[END_REF] . They all decreased with resistance to DCS.

As the diet was the same for standard animals and selected animals during at least 2 weeks before the sampling of cecal content, it is likely that changes in the fecal composition come from a reorganization of the activity of the intestinal microbiota community.

Metabolites indicative of a reshuffle of the DCS-resistant animals.

A change in fecal composition may result from the rearrangement of the microbial community in relation to the change in the physiological characteristics of the host. The host has the ability to modulate the development of microbial populations through a number of chemical compounds with antibiotic or anti-fungal properties [START_REF] Li | Host genetics influence the rumen microbiota and heritable rumen microbial features associate with feed efficiency in cattle[END_REF] . Self-regulation of the different microbial communities is also true [START_REF] Cao | A metabolome-and metagenome-wide association network reveals microbial natural products and microbial biotransformation products from the human microbiota[END_REF] . Thus, we notice in animals resistant to DCS an increase in 2,6-quinolediol [START_REF] Aldred | Mechanism of quinolone action and resistance[END_REF] and Azelate [START_REF] Schulte | Azelaic acid: evidence-based update on mechanism of action and clinical application[END_REF] , while m-coumaric acid, i.e. trans-3-hydroxycinnamic acid (3-coumarate) et 4-coumarate [START_REF] Nostro | Antimicrobial activity and phenolic content of natural site and micropropagated Limonium avei (De Not.) Brullo & Erben plant extracts[END_REF][START_REF] Stachelska | Inhibitory properties of lithium, sodium and potassium o-, m-and p-coumarates against Escherichia coli O157: H7[END_REF] , decrease, all compounds with antibiotic properties.

This change could reveal a deeper host metabolic shuffle. The composition of the gut microbiota is strongly impacted by the genetic background of the animal strain [START_REF] Korach-Rechtman | Murine genetic background has a stronger impact on the composition of the gut microbiota than maternal inoculation or exposure to unlike exogenous microbiota[END_REF] .

Concretely, we recorded a new shape in hormonal (steroid) profile including decrease in cortisol (glucocorticoid), 21-deoxycortisol [START_REF] Miller | Congenital adrenal hyperplasia: time to replace 17OHP with 21-deoxycortisol[END_REF] , and also cortexolone a precursor of cortisol when catalyzed by the enzyme cytochrome P450 [START_REF] Pubchem | PubChem Compound Summary for CID 440707[END_REF] . There is a concomitant change in the energy metabolism of sugars, energy metabolism in general, which results in decrease of xylose, sucrose, raffinose, cellobiose, trehalose [START_REF] Yadav | The sucrose-trehalose 6-phosphate (Tre6P) nexus: specificity and mechanisms of sucrose signalling by Tre6P[END_REF] or of glucose-6-phosphate [START_REF] Ohno | Kinetic trans-omic analysis reveals key regulatory mechanisms for insulin-regulated glucose metabolism in adipocytes[END_REF] . The decrease in glucose-6-phosphate could be linked to the increase in 6-aminopyridine-3-carboxylic acid (Strain*Interaction), also known as 6-aminonicotinamide (6-AN). It is used in order to disrupt NADPH production in the pentose phosphate pathway [START_REF] Bradshaw | Cytoplasmic and mitochondrial NADPH-coupled redox systems in the regulation of aging[END_REF][START_REF] Rey | The pentose phosphate pathway regulates the circadian clock[END_REF][START_REF] Parkhitko | Autophagy-dependent metabolic reprogramming sensitizes TSC2-deficient cells to the antimetabolite 6-aminonicotinamide[END_REF] . This compound is metabolized into an analog of NADP + , thus competitively inhibiting the critical NADPH-producing enzymes 6-phosphogluconate dehydrogenase (PGD) and glucose 6-phosphate dehydrogenase (G6PD) [START_REF] Köhler | Inhibition of NADP dependent oxidoreductases by the 6-aminonicotinamide analogue of NADP[END_REF] . Interestingly, a study linking the oxidative stress to the pentose phosphate pathway demonstrated that its inhibition through 6-AN has improved the oxidative stress response [START_REF] Vimercati | Beneficial effects of acute inhibition of the oxidative pentose phosphate pathway in the failing heart[END_REF] . Oxidative stress has been regularly evoked in diving [START_REF] Eftedal | Acute and potentially persistent effects of scuba diving on the blood transcriptome of experienced divers[END_REF][START_REF] Blatteau | Reduction in the level of plasma mitochondrial DNA in human diving, followed by an increase in the event of an accident[END_REF][START_REF] Thom | Oxidative stress is fundamental to hyperbaric oxygen therapy[END_REF][START_REF] Morabito | Effect of pre-breathing oxygen at different depth on oxidative status and calcium concentration in lymphocytes of scuba divers[END_REF][START_REF] Wang | Reactive oxygen species, mitochondria, and endothelial cell death during in vitro simulated dives[END_REF] . Elsewhere, the decreases in gulonolactone galacturonate and glucuronate may also be of interest for their link to the vitamin C pathway and its antioxidative properties [START_REF] Badejo | Translocation and the alternative D-galacturonate pathway contribute to increasing the ascorbate level in ripening tomato fruits together with the D-mannose/L-galactose pathway[END_REF] . The decrease in xanthine [START_REF] Xu | The role of reactive oxygen species in cognitive impairment associated with sleep apnea[END_REF][START_REF] Hassan | Heat stress as an innovative approach to enhance the antioxidant production in Pseudooceanicola and Bacillus isolates[END_REF] and tyrosol [START_REF] Paulo | New insights in the in vitro release of phenolic antioxidants: the case study of the release behavior of tyrosol from tyrosol-loaded ethylcellulose microparticles during the in vitro gastrointestinal digestion[END_REF][START_REF] Qi | Upregulation of Sirt1 by tyrosol suppresses apoptosis and inflammation and modulates extracellular matrix remodeling in interleukin-1β-stimulated human nucleus pulposus cells through activation of PI3K/Akt pathway[END_REF] in DCS-resistant rats could also be interpreted as an antioxidant response reshuffle. Another overexpressed metabolite in these animals, undecanedioic acid, in an analysis conducted in urine has been linked to the mitochondrial activity [START_REF] Dong | Urine Metabonomic analysis of interventions effect of soy isoflavones on rats exposed to di-(2-ethylhexyl) phthalate[END_REF] , or else it could be linked to a higher proportion of bacteria in the caecum [START_REF] Chen | Microbiota and metabolome responses in the cecum and serum of broiler chickens fed with plant essential oils or virginiamycin[END_REF] .

Furthermore, noted in DCS-resistant animals is decrease expression of cholic acids (ChemRich Fig. 7), chenodeoxycholate deoxycholate and hyodeoxycholic (Sex*Strain*Interaction), which are biliary acids or their co-products, the function of which is to help absorb dietary fats by the formation of An increase in 16-0-lysoPI (lysophopsholipids) is actually noted in feces from individuals resistant to DCS. Their second role is to inhibit (by an antiseptic or even antibiotic effect) the proliferation of the bacteria in the upper part of the digestive tract. However, a larger role is now attributed to biliary salts throughout the body [START_REF] Swann | Systemic gut microbial modulation of bile acid metabolism in host tissue compartments[END_REF] .

5-hydroxyindoleacetate or 5HIAA (Strain) was highlighted as a key factor in the algorithm generated by the random forest classification. It is overexpressed in DCS-resistant individuals and we wonder considering its place in the tryptophan pathway (from indole; cf ChemRich Analysis) and therefore in the metabolism of serotonin if it could have an influence on the colon mobility 62 but serotonin level is not altered (supp data 1). This does not exclude that serotonin turnover, as indicated by the 5-HIAA/5HT ratio could be altered [START_REF] O'mahony | Serotonin, tryptophan metabolism and the brain-gut-microbiome axis[END_REF] . Hence, we conducted a Mann-Whitney analysis and noticed a very significant difference between standard and selected rats ratio (p < 0.000001). This ratio is tenfold higher in selected animals (Figure in Supp data 3). The serotonergic system has been recognized for decades as an important signaling molecule in the gut [START_REF] Mawe | Serotonin signaling in the gastrointestinal tract[END_REF] , not just locally for its role on the gastrointestinal tract, but because it is clearly integrated in the brain-gut axis concept [START_REF] O'mahony | Serotonin, tryptophan metabolism and the brain-gut-microbiome axis[END_REF] . We lack evidence to evoke some mechanism in this study but this serotonergic dysregulation deserves attention, because the enzymes of these pathways are immune and stress responsive [START_REF] O'mahony | Serotonin, tryptophan metabolism and the brain-gut-microbiome axis[END_REF] . This remark should be put in parallel with the decrease in cortisol mentioned above. We could also have evoked a change due to the metabolism of tryptophan but its quantities do not change significantly (not shown).

The breeding of DCS-resistant rats did operate a reshuffle of the metabolome, including hormonal and energetic regulation, whether in the host or in the microbial community. Concerning metabolites exposed in this work, some compounds could be linked to sexual susceptibility-to-DCS, but the selection over generation participate in blurring the difference between the sexes.

Moderation. This work obviously has not analyzed all the metabolites composing the faeces, in terms of pure technical analysis or in terms of discussion of each of the compounds identified. It is therefore possible these missing metabolites may play a determinant role.

We wrote that a certain number of cecal compounds are linked to DCS-resistant strains and that may also may be link to the sex. However, as this work study fecal metabolome from caecum, it is not possible to exclude the fact that another diet could have an influence.

We assume that the diets of animals may differ very slightly, and that a two-week adaptation period may seem a little bit short regarding the microbiote community. This could induce inflammation and thus make the animals more susceptible to DCS [START_REF] De Maistre | Cecal metabolome fingerprint in a rat model of decompression sickness with neurological disorders[END_REF] . However, this does not seem sufficient to explain the increase in resistance over generations. At least, we had not demonstrated a difference in susceptibility to DCS in rats receiving two different diets [START_REF] De Maistre | Cecal metabolome fingerprint in a rat model of decompression sickness with neurological disorders[END_REF] .

We have mentioned "under" or "overexpression" suggesting a higher or a less absorption of metabolites, but it needs to be reminded that the compounds identified here are the result of the exogenous digestion (food bolus) and the endogenous digestion (including among other things debris from cells of the digestive system) substrates, which are themselves concerned with microbial activity, and that as such it remains difficult to identify their origin correctly. Characterizing the microbial community would partially clarify this point.

Although our results highlight various differences between DCS-resistant and non-resistant animals we have not yet experimentally questioned the relationship between these metabolomic changes and resistance to DCS. It is therefore probable that not all of these differences are directly related to DCS resistance and that some may represent collateral modifications only. This is the subject of continued experimentation by our research group and others.

From the point of view of clinical practice, it would be interesting to assess how much the reshuffle of the fecal metabolome affects the risk of DCS, and consequently whether a resetting of the Res metabolome into the Std one could be provocative. As a result, it could also impact DCS therapeutic with the aim to avoid degrading microbiota community, by limiting the side effects of hyperbaric oxygen therapy on anerobic species for example. At the same time, it should be reminded inter-species similarities of the gut microbiota (e.g. between human and rats) to make known that such a study can be useful to humans [START_REF] Alpert | Long-term stability of the human gut microbiota in two different rat strains[END_REF][START_REF] Albracht-Schulte | Systematic review of beef protein effects on gut microbiota: implications for health[END_REF] .

Conclusion

This study shows for the first time the spectral fingerprint of the fecal metabolome from caecum of a strain of rats resistant to decompression sickness. On the one hand, statistical analysis shows a panel of 81 compounds whose expression had changed following the selection of rats based on their resistance to DCS. These results

Figure 1 .

 1 Figure 1. Principal component analysis (PCA) plot of fecal metabolome as function of (A) strain (Std and Res) or (B) sex.

Figure 2 .

 2 Figure 2 . Heat Map, i.e. hierarchical clustering of fecal metabolomes from Std (orange) or Res (green) rats. Rats are on the ordinate where black squares note males. Fold-change for each metabolite (abscissa) is represented by a color. Intensity values are normalized, from red (Min: -2) to blue (Max: + 2).

Figure 3 .

 3 Figure 3. Venn diagram with metabolites influenced by sex or strain, and their interactions.

Figure 4 .

 4 Figure 4. Volcano plot showing metabolomic data in rats (n = 57) according to the gender. Fecal metabolites over-expressed in males are on the right and those of female rats are on the left. The dashed line shows where p = 0.05 with points above the line having p < 0.05 and points below the line having p > 0.05. Colors of the dots are in accordance with the Venn diagram and whose significance is true according to the 2-way ANOVA. Red dots are for Sex*Strain*Interaction, for example. Grey dots are not significant according to the 2-way ANOVA and the post-hoc testes.

Figure 5 .

 5 Figure 5. ChemRICH diagram according to the gender. Each disc reflects a significantly altered family of metabolites. These groups are developed from chemical similarities highlighted by a hierarchical Tanimoto map (not shown) accessible in the ChemRICH program. Enrichment p-values are given by the Kolmogorov-Smirnov test and displayed along the ordinate, with P values transformed in -log10. Disc sizes varies with the total number of metabolites. Red discs present groups of overexpressed metabolites in males while blue ones show overexpressed compounds in Females. Purple color represents both increased and decreased metabolites.For example, more adipate is found in the feces of male rats compared to females. Metabolite families are also scattered according to their increasing hydrophobicity (or decreasing hydrophilicity), from left to right along the abscissa (expressed as log P value).

Figure 6 .

 6 Figure 6. Volcano plot showing metabolomic data in rats (n = 57) according to the resistance of the strain. Fecal metabolites over-expressed in Std are on the right and those of the Res are on the left. The dashed line (green) shows where p = 0.05 with points above the line having p < 0.05 and points below the line having p > 0.05. Colors of the dots are in accordance with the Venn diagram and whose significance is true according to the 2-way ANOVA.

Figure 7 .

 7 Figure 7. ChemRICH diagram according to the strain resistance. Each disc reflects a significantly altered family of metabolites. These groups are developed from chemical similarities highlighted by a hierarchical Tanimoto map (not shown) accessible in the ChemRICH program. Enrichment p-values are given by the Kolmogorov-Smirnov test. Disc sizes varies with the total number of metabolites. Blue or red discs present groups of overexpressed or underexpressed metabolites in Res compared to Std animals, respectively. Purple color represents both increased and decreased metabolites. For example, there are less disaccharides in the feces of the DCS-resistant rats.

Scientific Reports | (2021) 11:8317 | https://doi.org/10.1038/s41598-021-87952-y

Funding

The work should be attributed to the "Institut de Recherches Biomédicales des Armées" laboratories. It is supported by Grant No. SAN-1-0516 from the Direction Générale de l' Armement of the French army, Paris, France.

| (2021) 11:8317 | https://doi.org/10.1038/s41598-021-87952-y

Author contributions

Competing interests

The authors declare no competing interests.

Additional information

Supplementary Information

The online version contains supplementary material available at https:// doi. org/ 10. 1038/ s41598-021-87952-y.

Correspondence and requests for materials should be addressed to N.V.

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