Age-related loss of intestinal barrier integrity plays an integral role in Thymic involution and T cell ageing

Age-related loss of intestinal barrier integrity plays an integral role in Thymic involution and T cell ageing | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Age-related loss of intestinal barrier integrity plays an integral role in Thymic involution and T cell ageing Jessica Conway, Erica N DeJong, Andrea Andrea J White, Ben Dugan, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3845290/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The intestinal epithelium serves as a physical and functional barrier against harmful substances, preventing their entry into the circulation and subsequent induction of a systemic immune response. Gut barrier dysfunction has recently emerged as a feature of ageing linked to declining health, and increased intestinal membrane permeability has been shown to promote heightened systemic inflammation in aged hosts. Concurrent with age-related changes in the gut microbiome, the thymic microenvironment undergoes a series of morphological, phenotypical and architectural alterations with age, including disorganisation of the corticomedullary junction, increased fibrosis, increased thymic adiposity and the accumulation of senescent cells. However, a direct link between gut barrier dysbiosis and thymic involution leading to features of immune ageing has not been explored thus far. Herein, we identify several strong associations between enhanced microbial translocation and the peripheral accumulation of terminally differentiated, senescent and exhausted T cells and the compensatory expansion of regulatory T cells in older adults. Most importantly, we confirm a direct effect of mucosal permeability on the regulation of thymic ageing and hyperactivation of the immune system by demonstrating that aged germ-free mice are protected from age-related intestinal membrane permeability. Together, these findings establish a mechanism by which gut barrier dysfunction drives systemic activation of the immune system during ageing, via causing thymic involution, extending our understanding of the consequences of intestinal membrane permeability and opening up the possibility for the use of microbiome-based interventions to restore immune homeostasis in older adults. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 BACKGROUND The epithelium of the gastrointestinal tract represents the largest mucosal lining in the body that effectively limits the permeation of luminal microorganisms, antigens and toxins through its paracellular space, a process that is regulated by intercellular tight junctions [ 1 ]. Advancing age is accompanied by physiological changes to the intestine, including mucus layer thinning and remodelling of intestinal epithelial tight junction proteins, such as zonulin, which contribute towards the breakdown of intestinal barrier function in aged worms, flies, fish, rodents, non-human primates and humans [ 2 ]. Impaired intestinal barrier integrity in aged hosts permits commensal bacteria and their products, such as LPS, from the gut lumen into the bloodstream (referred to as a leaky gut) [ 3 ]. Age-related intestinal barrier dysfunction is closely linked to the progressive deterioration of systemic health and the gradual appearance of metabolic defects and behavioural impairments [ 4 ]. Moreover, recent evidence from animal studies indicates that it is a major contributor to low-grade systemic inflammation, termed inflammaging [ 5 , 6 ], and possibly a driver of age-related diseases [ 7 ]. Human intestinal barrier dysfunction, determined by elevated circulating lipopolysaccharide-binding protein (LBP) levels, is also associated with impaired physical function and inflammaging in healthy aged adults [ 8 ]. Therefore, it remains of vital interest that we develop a clear understanding of the relevance of intestinal barrier dysfunction in human ageing, which is still poorly understood. Concurrently with changes to intestinal homeostasis, ageing is accompanied by remodelling of the immune system that attenuates the host’s ability to mount robust immune responses, resulting in an immunocompromised state, termed immunesenescence. Age-related immune dysfunction contributes towards increased susceptibility to poor outcomes during bacterial and viral infections and increases the risk of autoimmunity and poor response to vaccination [ 9 ]. Recently, immunesenescence has been recognised as a contributing factor towards the ageing of non-lymphoid organs, such as skeletal muscle and recognised as a potential driver of an aged phenotype and increasing the risk of morbidity and mortality in older adults [ 10 ]. One of the most striking features of immune ageing is the progressive shrinkage (involution) of the thymus that is characterised by the loss of thymic epithelial cells (TECs), expansion of perivascular spaces, increased thymic adiposity and the accumulation of senescent cells; together resulting in a loss of functional spaces for the development of thymocytes [ 11 – 13 ]. In addition to thymic architectural disorganisation, alterations in the thymic stromal cell microenvironment, including elevated levels of thymopoiesis-suppressing cytokines (e.g. IL6 and tumour necrosis factor alpha (TNFα) also occur with age [ 14 ]. Collectively this compromises the process of thymopoiesis and result in a reduced thymic output of naïve T cells and the homeostatic expansion of peripheral memory T cell subsets [ 15 ]. Further, chronic lifelong antigenic stimulation leads to the accumulation of senescent T cells in the periphery [ 16 , 17 ], which impair tissue immunosurveillance and drive a state of prolonged basal inflammation in aged individuals, termed inflammageing. This is further exacerbated by the age-related expansion of pro-inflammatory Th17 cells and anti-inflammatory regulatory T cells (Tregs) [ 18 , 19 ]. Despite these interesting findings, the relationship between intestinal barrier dysfunction and immune ageing is poorly understood. Herein we report that intestinal membrane permeability increases with age in humans and is accompanied by enhanced systemic microbial translocation that contributes to the lifelong antigenic burden, driving a reduction in naïve T cell thymic output and an accumulation of terminally differentiated, senescent T cells in the periphery. The emergence of these hallmarks of T cell ageing hinders the ability of these cells to fight invading pathogens and enhances their ability to produce pro-inflammatory cytokines, which ultimately contribute to the inflammatory state of the aged host. Further, we demonstrate that aged germ-free mice, which do not exhibit age-related intestinal barrier dysfunction, are protected from the accumulation of microbial products in the thymus and maintain their thymic architecture. Together, these findings provide novel evidence of a causal relationship between intestinal barrier dysfunction and T cell ageing. RESULTS Ageing is accompanied by increased microbial translocation Twenty-seven healthy young individuals (age range 19–37 years) and 55 community-dwelling healthy old individuals (age range 63–84 years) were recruited into this study, from whom blood samples were collected to assess microbial translocation and immune cell profiles (Fig. 1 A). Occludin is an integral tight junction protein located on the basolateral membrane of intestinal epithelial cells, whose presence in the circulation is a biomarker of increased intestinal membrane permeability [ 20 ]. In this study, we found a significant age-associated increase in circulating occludin levels (p < 0.0001) (Fig. 1 B). Serum LBP is a surrogate biomarker of intestinal permeability and microbial translocation [ 8 ]. We observed a trend towards elevated circulating LBP levels with age; however, this did not reach statistical significance (p = 0.12) (Fig. 1 C). Soluble CD14 (sCD14) is shed from the surface of antigen-stimulated monocytes and was measured as a reactive biomarker of microbial translocation and subsequent monocyte activation in this study [ 21 ]. On assessment, we found a significant age-related increase in circulating sCD14 levels (p = 0.01) (Fig. 1 D). Interestingly, elevated circulating LBP levels were linked to low dietary fibre intake (R = -0.33, p = 0.04) (Fig. 1 E). We next investigated potential associations between markers of microbial translocation and potential drivers of increased gut permeability, including age, sex, body mass index (BMI), diet, physical activity levels, sedentary behaviour, sleep quality and mental health (Supplementary Table 1). Upon assessment of the faecal microbiome, older adults displaying high microbial translocation had lower relative abundances of Bifidobacterium (p = 0.0002), Blautia (p = 0.002) and Lachnospiraceae (p = 0.01) and greater relative abundances of Christensenellaceae R-7 group (p = 0.02) and Ruminococcaceae (p = 0.03) in stool compared to young adults (Fig. 2 A, Supplementary Table 2). Low levels of the short-chain fatty acid butyrate (p = 0.02), propionate (p = 0.03) and the secondary bile acid glycodeoxycholic acid (GDCA) (R = -0.33, p = 0.04) in stool were also strongly linked with elevated circulating levels of occludin in older adults (Fig. 1 H and 1 I, respectively). Furthermore, were split our older adults’ cohort into two sub-groups: low Microbial Translocation (MT) old (n = 24, age range 60–88 years) and high MT old (n = 31, age range 63–82 years) (Fig. 1 A). Low MT (similar levels to healthy young individuals) was defined as circulating occludin levels ≤ 4.5 ng/ml, which was the mean value observed in young participants. High MT was defined as circulating occludin levels > 4.5 ng/ml. Demographic characteristics for each subgroup are shown in Table 1. T cell immunesenescence and microbial translocation In this study, we hypothesised that an increase in circulating microbial products would perpetuate repeated T cell activation and, the subsequent differentiation of T cells and induction of replicative senescence, all recognised as features of T cell ageing. Therefore, we reasoned that older adults with lower levels of intestinal barrier leakage would exhibit fewer features of T cell ageing. Previous studies have reported an age-related decline in peripheral PTK7 + ve CD45RA +ve recent thymic emigrants (RTEs), which are antigenically naïve CD4 T cells that egress from the thymus into the periphery following intrathymic development and thus a surrogate marker for human thymic output [ 23 ]. Interestingly, we report that there is a significant reduction in the proportion of circulating RTEs in the presence of high microbial translocation in older adults (p = 0.002) compared to young participants, but not in those with low MT (Fig. 3 A). Further, older participants with high MT presented with greater proportions of central memory CD8 T cells (p = 0.03), effector memory CD4 and CD8 T cells (p < 0.0001 for both) (Supplementary Tables 3 and 4) and terminally differentiated effector memory re-expressing RA (EMRA) CD4 (p < 0.0001) and CD8 T cells (p = 0.0005; Fig. 3 B and C), compared to low MT young individuals CD69 is an early activation marker expressed by activated lymphocytes [ 24 ]. Here, we observed an age-associated increase in the percentage of CD69 + ve CD8 T cells (p = 0.01), which was even greater in older adults displaying high MT (p < 0.0001) (Fig. 3 D); suggesting that translocated bacterial might induce polyclonal T cell activation. Advancing age is accompanied by the loss of CD28 and the gain of CD57 expression on the surface of CD8 T cells (known markers of T cell senescence), which have low proliferative capacity and are highly pro-inflammatory [ 16 ]. In this study, we observed a significant increase in CD28 − ve CD57 +ve senescent CD8 T cells in older adults with high MT compared to old adults with low MT (p = 0.04) (Fig. 3 E and F). A similar increase in CD28 − ve CD57 +ve senescent CD4 T cells was also seen in older adults displaying high MT relative to young adults (p = 0.02) (Supplementary Table 2). Another hallmark of T cell immunesenescence is an increase in programmed cell death-1 (PD1) +ve exhausted CD8 T cells with reduced cytotoxic capability and reduced proliferative potential [ 17 ]. Older adults with low MT possessed significantly greater percentages of PD1 + ve CD8 T cells compared to young adults (p = 0.04), but not older donors with high MT (p = 0.6) (Supplementary Table 4). CD4 T helper cells are important mediators of inflammatory responses, secreting effector cytokines upon activation. RORγ +ve Th17 cells, defined by their ability to secrete IL17, are pro-inflammatory and have been associated with several autoimmune disorders [ 25 ]. Upon examination of CD4 T helper cell subsets, we observed comparable proportions of RORγ +ve Th17 cells (p = 0.94) (Fig. 4 A) between the three participant groups, but older adults with increased microbial translocation had higher intracellular IL17 expression levels than young and old participants displaying low MT (p = 0.04 for both) (Fig. 4 B; gating strategy Supplementary Fig. 1). CD25 + ve Foxp3 +ve Tregs are another subpopulation of CD4 T helper cells that maintain homeostasis and immune tolerance through multiple mechanisms, one of them being secretion of the anti-inflammatory cytokine IL10 [ 26 ]. In this study, the peripheral frequency of CD25 + ve Foxp3 +ve Tregs was significantly higher in high MT older adults compared to young and old participants with low MT (p < 0.0001 and p = 0.01, respectively) (Fig. 4 C). However, the proportion of anti-inflammatory IL10-producing Tregs (p = 0.21) and intracellular IL10 expression levels (p = 0.6) were similar between the three groups (Fig. 4 D; Supplementary Table 3). Treg expansion is thought to occur as a compensatory mechanism against a pro-inflammatory cytokine milieu, as is the case with advancing age. Further, peripheral LBP levels were positively associated with the accumulation of IL10-expressing Tregs (R = 0.57, p = 0.0003) (Fig. 4 E) in older people. On assessing the impact of microbial translocation on serum cytokine levels, circulating concentrations of IL1β, IL4, IL6, IL15, TNFα, CRP, IFNγ, CXCL9 and GM-CSF were unaltered by advancing age and the presence of intestinal barrier dysfunction (Supplementary Table 5). Although the peripheral frequency of Th17 cells and intracellular IL17 levels were comparable between groups, older adults with high MT displayed lower systemic levels of IL17 compared to other participants with low MT (p = 0.02) (Supplementary Table 5)[ 7 ]. Links between microbial translocation and the IMM-AGE score The IMM-AGE score is a recently developed metric that describes an individual’s cellular immune profile about their chronological age and has been recognised as a reliable predictor of all-cause mortality in older adults [ 27 ]. Here, we used a modified version that requires only eight T cell subsets: total T cells, naïve CD4 T cells, effector memory CD4 and CD8 T cells, EMRA CD8 T cells, CD28 − ve CD8 T cells, CD57 + ve CD8 T cells and Tregs [ 28 ]. IMM-AGE scores were significantly higher in older adults relative to young controls (p < 0.0001) (Fig. 4 F). When investigating potential associations between IMM-AGE scores and markers of gut permeability and microbial translocation, we found that high IMM-AGE scores were positively correlated with circulating LBP (R = 0.28, p = 0.05) (Fig. 4 G). Transcriptome signatures of older adults with low and high microbial translocation To identify molecular signalling pathways in peripheral immune cells that might contribute towards enhanced immune ageing in older adults with high microbial translocation, we used the NanoString nCounter ® gene expression assay. This allowed for the detection of 770 genes in peripheral blood mononuclear cells (PBMCs) from healthy young individuals displaying low MT (n = 6), healthy old individuals with low MT (n = 6) and healthy old individuals displaying high MT (n = 6). In total, 49 genes significantly differed between low MT young, low MT old and high MT old participants (Fig. 5 A). Upon comparing expression levels between low MT young adults and older adults with low MT, we observed a significant downregulation in the expression of seven genes controlling cell adhesion/migration (ALCAM, p = 0.05), apoptosis (BID, p = 0.04), immune suppression (LRRN3, p = 0.05) and immune-mediated pathology (NT5E, p = 0.04; TNFRSF13B, p = 0.05) (Supplementary Table 6). We also observed reduced expression of complement system components (CR1, CR2), irrespective of microbial translocation status (Fig. 4 ), that play an important role in immunomodulation and defence against pathogens [ 29 ]. Furthermore, 27 genes were differentially expressed between young individuals and high MT older adults (Supplementary Table 7). For instance, we observed downregulated expression of autophagy-related genes (ATG7, p = 0.05; LAMP, p = 0.03) and DNA repair machinery (ATM, p = 0.05; G6PD, p = 0.03) along with an upregulation of pro-apoptotic molecules (CASP3, p = 0.05; BID, p = 0.04) only in aged individuals with high MT (Fig. 5 A). Importantly, we saw increased expression of co-stimulatory molecules expressed on activated T cells (ICOS, p = 0.05), cellular senescence markers (gain of KLRG1, p = 0.04; loss of CD28, p = 0.05) and accelerators of cell cycle arrest (TXNIP, p = 0.05) only in older adults with high MT (Fig. 5 A). It was previously reported that p53 inhibits mitogen-activated protein kinase (MAPK) activity by inducing phosphatases, such as the dual-specificity phosphatases (DUSPs) [ 30 ]. Supporting this, we observed a downregulation of MAPK3 (p = 0.04) and upregulated expression of DUSP4 (p = 0.04) and DUSP6 (p = 0.05) in older adults with high MT relative to young and aged individuals with low MT (Supplementary Table 8). Additionally, older participants with high MT displayed increased expression of inflammatory molecules (HMBG1, p = 0.01) and T cell ageing markers (RORA, p = 0.03) compared to low MT older adults (Fig. 4 ). Gene enrichment analysis revealed that the top enriched terms in high MT olds were the intrinsic pathways for apoptosis (BCL2, BID and CD99), the cytochrome c-mediated apoptotic response (CASP3 and CASP8), cellular senescence (CD28, DUSP4, DUSP6, KLRG1, MAPK3 and TXNIP), suggesting that these pathways might be involved in driving T cell immunesenescence during age-related intestinal barrier dysfunction. Thymic tissue architecture, adiposity and senescence in aged germ-free mice protected from intestinal permeability To determine whether an age-related increase in circulating microbial products drives thymic involution, we used an aged germ-free mouse model that was previously shown to be protected from increased gut permeability [ 6 ]. We hypothesised that these aged germ-free mice (20–22 months) would also be protected from key features of thymic involution (Fig. 6 A). The FITC-dextran assay is a well-established method for measuring in vivo intestinal permeability [ 31 ]. In this study, we confirmed that aged wild-type mice display enhanced translocation of FITC-dextran into the blood compared to young wild-type mice (p = 0.004), whereas aged germ-free mice maintained intestinal barrier function (p = 0.14) (Fig. 6 B). Whilst there was no gross difference in intestinal architecture, we found that aged wild-type mice exhibit decreased expression of the tight junction protein occludin compared to young wild-type and aged germ-free mice (Fig. 6 C). Additionally, aged germ-free mice that were protected from intestinal membrane permeability displayed lower relative mRNA expression levels of Escherichia coli in the thymus compared to aged wild-type mice (p = 0.33), which exhibited increased thymic E. coli mRNA expression levels relative to young mice (p = 0.1) (Fig. 6 D). Age-related thymic involution disrupts the structural integrity and cellular architecture of the thymus, resulting in the shrinkage of medullary regions and impaired thymopoiesis [ 11 , 12 ]. Additionally, the corticomedullary junction, which separates the cortex and medulla and serves as a site for progenitor (CD4 − ve CD8 −ve ) immigration and naïve T cell emigration [ 32 ], becomes disorganised with age and there is increased thymic adiposity [ 14 ]. In this study, the morphological analysis showed medullary shrinkage [Figure 6 E], disruption of the corticomedullary junction and the appearance of vacuoles in aged wild-type mouse thymuses, but not in those from aged germ-free mice (Fig. 6 F). Oil-red O staining, which is used for the enumeration of lipid-laden tissues, also revealed an increase in the size and number of lipid deposits in the cortex and medullary regions of thymuses of aged wild-type mice (p = 0.01) compared to young mice, whereas aged germ-free mice were protected from lipid accumulation (p = 0.06) (Fig. 6 G and 6 H). Stromal components of the thymus include specialized TECs that provide signals that induce the development and functional maturation of T lymphocytes. However, the aged thymus displays an enlargement of non-cellular perivascular spaces and TEC reductions [ 14 , 33 ]. Although perivascular spaces enable easy trafficking of cells and soluble proteins through the medulla, an increase in non-cellular space permits the infiltration of pro-inflammatory adipocytes and circulating senescent cells in the aged thymus [ 34 ]. Morphological analysis revealed that CD205 + ve cortical and ERTR5 + ve medullary epithelial regions shrink and become less dense with age followed by the appearance of epithelial-free areas in aged wild-type mouse thymuses, though this did not occur in aged germ-free mice (Fig. 7 A-C). Next, we assessed the presence of senescent cells in the thymus of aged wild-type and germ-free mice to elucidate a potential mechanism underpinning the changes in thymus architecture. Lamin B1 is a structural protein that supports TEC development and maintains thymic architecture [ 35 ], and reduced lamin B1 expression is a marker of cellular senescence and thymic involution [ 36 ]. Aged wild-type mice exhibited tissue disorganisation and fewer lamin B1-expressing cells in the cortex compared to young mice, but these ageing features were not present in aged germ-free mice (Fig. 7 D). Further, we observed lower lamin B1 expression levels (mean fluorescent staining intensity (MFI)) in the cortex of aged wild-type mice (p = 0.04), but not in aged germ-free mice (p = 0.57), compared to young wild-type mice (Fig. 6 E). In contrast, lamin B1 expression levels (MFI) in the medulla were unaffected by ageing (p = 0.22) or microbiota composition (p ≥ 0.1) (Fig. 7 F). Transcriptional profiling of aged wild-type mouse thymuses revealed increased mRNA expression levels of the cellular senescence marker p16 relative to young mice (p = 0.01), which were even lower in aged germ-free mice (p = 0.04) (Fig. 7 G). Elevated IL6 levels found in the thymuses of aged mice are associated with poorer thymic function and involution [ 37 ]. However, aged germ-free mice were previously shown to be protected from inflammageing, lacking high circulating levels of IL6 [ 6 ]. Here we confirm that compared to young mice, aged wild-type mice exhibit increased IL6 mRNA expression levels in the thymus (p = 0.05), which were lower in aged germ-free thymuses (p = 0.55) (Fig. 7 H). Compared to young mice, mRNA expression levels of the apoptosis-promoting gene BCL2 associated X (BAX) were also significantly higher in aged wild-type mice (p = 0.0001) but not in aged germ-free mice (p < 0.0001) (Fig. 7 I), suggesting a possible mechanism by which increased apoptosis drives TEC loss with age. Lastly, we examined the distribution of CD4 and CD8 expressing thymocytes in the thymus, where CD4 + CD8 + cells would typically reside in cortical areas while more mature CD4 + CD8 − and CD4 − CD8 + would reside in medullary areas. While CD4 + CD8 + and single positive CD4 + and CD8 + thymocytes were distributed normally within thymus tissue, we found that aged wild-type mice display a loss of CD4 + CD8 + cortical regions in the thymus (Fig. 8 A). However, the proportion of CD8-expressing thymocytes is higher in aged germ-free mice compared to aged wild-types in medullary regions (Fig. 8 C). A similar decline in the proportion of CD4-expressing thymocytes was also observed in the medulla with age, though aged germ-free mice displayed a higher proportion of CD4 + ve areas (Fig. 8 E). In conclusion, our data demonstrate the presence of bacterial products within the aged thymus, possibly as the result of increased intestinal membrane permeability and subsequent systemic microbial translocation, that contributes towards a disrupted thymic architecture, build-up of thymic inflammation and the accumulation of senescent cells; culminating in an altered thymic microenvironment for T cell development. (Fig. 9 ). DISCUSSION It is becoming increasingly clear that impaired intestinal barrier integrity is a major pathophysiological feature of ageing that contributes to the decline of organismal health. Whilst recent publications have demonstrated a significant role for microbial translocation in driving chronic immune cell activation and inflammageing [ 5 , 6 ], the potential links between age-related intestinal barrier dysfunction and immunesenescence are still largely unknown. In this study, we demonstrate that older adults with higher levels of intestinal barrier leakage are more likely to display hallmarks of T cell ageing, contributing to high IMM-AGE scores in these individuals. Importantly, aged germ-free mice that display reduced intestinal membrane permeability and bacterial translocation preserve their thymic architecture and have an unaltered thymic microenvironment, possibly driving high thymic output in old age (Fig. 8 ). These novel findings take us a step further in understanding the age-related changes in the microbiome-immune axis and provide evidence for therapeutic restoration of intestinal barrier homeostasis to preserve immune function in aged individuals. To the best of our knowledge, this study is the first to report an age-associated increase in intestinal membrane permeability and systemic microbial translocation in healthy aged individuals in line with findings from non-human primate studies [ 38 , 39 ]. Dietary components play an integral role in modulating intestinal barrier integrity. For instance, there is mounting evidence that excessive consumption of dietary fats enhances intestinal membrane permeability [ 40 ], predisposing individuals to local and systemic inflammation. Interestingly, high adherence to the MedDiet and consumption of a high-quality diet were inversely correlated with intestinal barrier dysfunction in this study, possibly due to the anti-inflammatory and health-promoting properties of dietary fibre [ 41 , 42 ]. This is supported by a study that reported improvements in intestinal barrier integrity in middle-aged women following high adherence to the MedDiet [ 43 ]. Furthermore, high intake of dietary fibre and omega-3 polyunsaturated fatty acids (both enriched in MedDiet foods like fruits, vegetables, fish and nuts) has been shown to restore gut barrier function in non-obese diabetic mice, thereby restoring intestinal immune homeostasis (i.e. reduced gut inflammation, expansion of IL10-producing Tregs, decline in pro-inflammatory Th17 cells) [ 44 ]. However, these beneficial effects on the immune system have yet to be confirmed in aged humans. Changes in gut microbiota composition with age are also closely linked with the onset of intestinal barrier leakage in mice [ 6 ]. Accordingly, intestinal barrier leakage was correlated with higher relative abundances of pro-inflammatory Escherichia-Shigella , Peptostreptococcaceae and Paraprevotella in stool. On the other hand, robust intestinal barrier integrity was positively associated with high faecal levels of propionate and GDCA, both of which exert immunomodulatory and anti-inflammatory effects on the immune system. These results suggest a possible role of age-related microbial dysbiosis in promoting increased gut permeability through inflammation-induced epithelial damage. In this study, we propose that age-related microbial translocation induces a state of persistent T-cell activation. These results are supported by an earlier study that reported loss of gut mucosa homeostasis and increased bacterial translocation in HIV patients, resulting in chronic immune system activation and systemic inflammation [ 45 ]. Therefore, we hypothesise that persistent stimulation caused by microbial translocation promotes the terminal differentiation of T cells and induces cellular senescence in aged T cells, together accelerating immune ageing. These observations are in line with those from another study reporting close links between microbial translocation and memory T cell expansion in adult mice [ 46 ]. Furthermore, in vitro studies have confirmed that gut microbial secretory factors induce cellular senescence via the activation of cell cycle inhibitors (p16 INK4a , p21 WAF1 and p53) and the DNA damage response, resulting in the development of a senescence-associated secretory phenotype (SASP) [ 47 , 48 ]. In agreement with other ageing studies [ 19 , 49 ], we observed an age-related increase in the percentage of Tregs that was correlated with increased gut permeability. There is emerging evidence of a potential link between the expansion of senescent T cells and Tregs, with studies demonstrating that Tregs trigger DNA damage in effector T cells via metabolic competition during cross-talk, resulting in cellular senescence and functional exhaustion [ 50 ]. Thus, we propose that increased microbe recognition caused by enhanced bacterial translocation might contribute to dysregulated ROS production and altered glucose metabolism in aged Tregs, promoting aberrant Treg interactions and senescent cell accumulation. Consistent with the findings discussed above, we identified several hallmarks of ageing in circulating immune cells, including upregulation of pro-inflammatory signalling markers (HMBG1), defective autophagy processes (ATG7 and LAMP), reduced DNA damage repair (ATM), increased cellular senescence (gain of KLRG1 and loss of CD28), enhanced apoptosis (BCL2, CASP3 and CASP8), loss of proliferation regulators (DUSP4 and DUSP6) and upregulation of cell-cycle arrest regulators (TXNIP), that were only present in older adults with high microbial translocation. These results are in line with those from a study that demonstrated that microbial products disrupt autophagosome formation and trigger mitochondrial dysfunction by interfering with Rab1A signalling and reducing mitochondrial coupling [ 51 , 52 ]. T cells are continuously produced by the thymus throughout life. However, the thymus undergoes accelerated atrophy with advancing age, resulting in a reduced thymic output of naïve T cells that limits the host’s ability to respond to neoantigens [ 15 , 53 ]. In this study, we report a significant age-related loss of RTEs in older adults with high MT, supporting our hypothesis that circulating bacterial products have deleterious effects on thymopoiesis. To confirm that microbial products contribute towards age-related thymic involution, we used aged germ-free mice which are protected from loss of intestinal barrier function. Here, we demonstrate for the first time that ageing is accompanied by increased thymic translocation of E . coli in wild-type mice but not in germ-free mice. Importantly, hallmarks of thymic involution, including the loss of functional thymic niches due to the depletion of TECs, adipocyte infiltration and senescent cell accumulation, were less pronounced in aged germ-free mice. In vitro analysis reveals that LPS, found on the surface of gram-negative bacteria such as E . coli , promotes the accumulation of lipid droplets in endothelial cells [ 54 ], induces cellular senescence and enhances the SASP of senescent cells [ 55 , 56 ]. Thus, elevated circulating levels of microbes and microbial products, like LPS, could promote increased thymic adiposity and cellular senescence in aged hosts. Accumulation of senescent cells and adipocytes during ageing is believed to hinder thymic function through increased secretion of pro-inflammatory cytokines, such as IL6 and TNFα [ 36 , 38 ]. In this study, ageing was accompanied by increased thymic expression of IL6 in wild-type mice. However, aged germ-free mice exhibited comparable IL6 expression levels to those in young wild-type mice, indicating a role for microbial translocation in the age-dependent upregulation of thymopoiesis-suppressing cytokines. Indeed, LPS treatment and E . coli enterotoxin cause thymic atrophy, leading to the loss of single positive (CD4 − ve CD8 +ve and CD4 + ve CD8 −ve ) thymocytes as well as double positive (CD4 + ve CD8 +ve ) and double negative (CD4 − ve CD8 −ve ) thymocytes [ 57 , 58 ]. One mechanism by which this occurs is through LPS-induced apoptosis of thymocytes [ 59 ]. Supporting this, thymic expression of the apoptotic gene BAX increased with age in wild-type mice, whereas aged germ-free mice were unaffected. Although therapeutic manipulation of the gut microbiota might improve health in aged hosts, it remains unclear how restoring intestinal barrier function possibly by targeting microbiome dysbiosis could reverse features of immune ageing. For instance, studies have reported links between microbial composition, intestinal membrane permeability and circulating cytokine levels in aged hosts, but have not investigated their impact on immune health [ 60 ]. Our data demonstrates that transferring healthy gut microbiota into Clostridium difficile infected older adults is sufficient to improve intestinal barrier integrity. Moreover, faecal microbiota transplantation promotes the expansion of peripheral naïve T cells and reduces the senescent T cell burden in recipients, suggesting potential anti-immunesenescence effects [ 61 ]. Microbial dysbiosis in HIV patients, characterised by the loss of beneficial Bifidobacterium and the overrepresentation of Clostridium clusters, is also alleviated in response to probiotic administration, resulting in reduced microbial translocation and improved immune cell function [ 62 ]. The appearance of opportunistic microbial communities in the aged gut is related to dietary changes, such as low consumption of fibre-rich fruits and vegetables and increased consumption of meats and processed foods [ 60 ]. Moreover, studies have reported rebalancing of the gut flora, reduced systemic inflammation and improved health status in older adults who consume a MedDiet [ 63 , 64 ]. Therefore, high adherence to a MedDiet rich in fibre, polyunsaturated fats, minerals and vitamins could strengthen gut barrier function and improve immune function in the elderly. This study has a few limitations, the first being that the exact mechanisms linking intestinal membrane permeability to immune ageing remain to be fully elucidated. Secondly, although we report an increase in microbial translocation with age, we do not know the nature of these microbial products. Thus, further work is required to determine the impact of individual bacterial products on immune ageing. Like all research studies, ours has a few limitations that should be noted. Firstly, our use of strict inclusion criteria excluded older adults with any underlying comorbidities, immune-mediated diseases and gastrointestinal disorders. Our cohort of older adults, who were interested in biogerontology research and keen to partake in our study, are all extremely healthy, consume a high-quality diet rich in dietary fibres and engage in regular physical activity (only one individual was sedentary). Unfortunately, this might not be a true representation of the ageing population, which is considered to be malnourished, largely sedentary and ridden with multimorbidity. However, this strategy dissected the intrinsic effects of ageing and highlighted the novel interactions that we observed are features of intestinal barrier dysfunction and T-cell ageing. However, in a current ongoing study, we are addressing this by recruiting older individuals with underlying comorbidities to identify immune-intestinal barrier signatures and interactions that differ between individuals on healthy vs unhealthy ageing trajectories. Another key limitation is that our results are based on a cohort of Caucasian participants, and we would like to validate our findings in a larger study (enabling us to dissect sex differences) conducted on older adults with more ethically and geographically diverse backgrounds. In conclusion, age-related thymic involution is a known hallmark of T cell ageing that contributes significantly toward immunesenescence. Although we have made progress in understanding the molecular mechanisms that instigate thymic involution, the detailed molecular regulation network is still unclear. Nevertheless, we suggest that systemic microbial translocation due to increased intestinal barrier leakage contributes towards a reduced thymic output and the emergence of T cell ageing features Thus, our findings advocate for targeting intestinal barrier integrity as a novel strategy for promoting thymic rejuvenation and combating T cell ageing in the elderly. Exploiting the restoration ability of these targets provides new opportunities to cope with lagging health span developments of individualised dietary, probiotic and postbiotic interventions. METHODS Participants and study design This is an observational, cross-sectional study in healthy young (aged 18–37 years) and 55 healthy old (aged ≥ 60 years) adults, the latter of whom were enrolled from the Birmingham 1000 Elders group, were recruited into this study from November 2019 to December 2020. The exclusion criteria for healthy participants included self-reported infections, comorbidities (e.g. chronic inflammatory/autoimmune conditions and cancer), use of immunosuppressants, antibiotic usage in the past two months, hospitalisation in the past three months and/or having travelled outside of the UK in the month leading up to recruitment. Written informed consent was obtained from all eligible volunteers prior to sampling and additional participant demographics, including height, weight, BMI, physical activity levels (hours of TV watched and stairs climbed), sleep quality, mental health status (anxiety and depression) and diet, were gathered via self-assessed questionnaires (Fig. 1 A). Blood samples (30 ml) were collected from all participants between 9:00–11:00am in BD vacutainers containing lithium heparin. Complete blood cell counts were obtained using a Sysmex XN-1000 automated haematology analyser (Sysmex). Isolation and freezing of peripheral blood mononuclear cells (PBMCs) PBMCs were isolated from whole blood samples via density gradient centrifugation using Ficoll-Paque™ PLUS density gradient media (GE Healthcare). Isolated PBMCs were frozen by resuspending the cells in freezing medium consisting of 10% dimethyl sulfoxide (Sigma Aldrich) in heat-inactivated fetal calf serum (HiFCS) (Biosera) and stored at -80°C. Serum microbial translocation and cytokine analysis Blood collected in anti-coagulant free BD vacutainers was left upright for 30 minutes prior to centrifugation at 1620 x g for 10 minutes at room temperature, after which the serum was removed and stored at -80°C prior to analysis. The concentration of serum proteins (occludin, LBP, sCD14 and sCD25) and cytokines (IL1β, IL4, IL6, IL7, IL10, IL15, IL17, TNFα, IFNγ, CRP, CXCL9 and GM-CSF) was determined using commercially available Enzyme-Linked Immunosorbent Assays (DL Develop, R&D Systems and Invitrogen) and a Human Premixed Multi-Analyte Magnetic Luminex Assay (R&D Systems). The absorbance of the wells was measured using wavelengths specified by the manufactures’ instructions on a spectrophotometer (BioTek). Protein and cytokine concentrations were extrapolated from a standard curve created using known concentrations via GraphPad Prism software v9 (GraphPad Software Inc.). Stool 16S rRNA gene amplification via RT-qPCR DNA was extracted from 500 mg aliquots of stool using a commercially available FastDNA ™ SPIN Kit for Soil (MP Biomedicals,) according to the manufacturer’s instructions. DNA concentrations were determined on a calibrated Qubit 4 Fluorometer (Invitrogen ™ ). RT-qPCR was used to amplify the V4 region of the 16S rRNA gene using desalted 515F and 806R primer pairs (Sigma-Aldrich) to create an amplicon library. Stool DNA samples (0.16–14.48 ng/µl) were amplified in triplicate under the following PCR thermocycler conditions using a SensoQuest Basic Thermal Labcycler (with gradient; Geneflow Ltd, UK): initial denaturation at 94°C for 3 minutes followed by 35 cycles of denaturation at 94°C for 45 seconds, annealing at 50°C for 60 seconds, elongation at 72°C for 90 seconds and an extended elongation step at 72°C for 10 minutes. After pooling triplicate PCR reactions, RT-qPCR products were purified using the GeneJET PCR Purification Kit (Thermo Scientific ™ ) according to the manufacturer’s instructions. The quality of the DNA library was checked via TapeStation D1000 ScreenTape → (Agilent Technologies) using TapeStation Analysis Software A.02.02 (SR1) (Agilent Technologies). High-thorough 16S rRNA sequencing on the Illumina MiSeq platform (Illumina, Inc.) was done by Genomics Birmingham (University of Birmingham) using pooled DNA library and the MiSeq v2 500 sequencing kit (Illumina, Inc.). 16S rRNA sequencing data was analysed on the web-based Galaxy platform (version 23.01.dev0) using the Mothur toolset according to the online-based tutorial [ 65 – 67 ], unique sequences were aligned to the SILVA v132 reference alignment to improve clustering of the operational taxonomic units (OTUs) [ 68 ], using the Needleman-Wunsch algorithm. Next, taxonomic classification was performed using the SILVA v132 reference taxonomy and the Bayesian classifier and bacterial sequences were clustered into OTUs at the phylum level using a 97% similarity threshold and the relative abundance (%) of each phylum and genus was calculated. Liquid chromatography-mass spectrometry Faecal SCFA (acetate, butyrate and propionate) and secondary bile acid (deoxycholic acid (DCA), glycodeoxycholic acid (GDCA), hyodeoxycholic acid (HDCA), lithocholic acid (LCA) and ursodeoxycholic acid (UDCA)) concentrations were assessed in all participants via liquid chromatography-mass spectrometry (LC-MS) performed by the Quadrum Institute (Norwich, UK). In preparation, stool samples were thawed and 1 ml of extraction solvent (0.5% (v/v) orthophosphoric acid) was added to each tube followed by centrifugation and passing the supernatants through a Mini-UniPrep filter vial (0.45 µm; Whatman plc) prior to SCFA analysis via LC-MS. For the analysis of secondary bile acids, thawed stool (100 mg) was homogenised in a MaxQ ™ 6000 incubated shaker (Thermo Fischer Scientific) at 500 rpm for 30 minutes at 20°C using 5–10 ceramic beads and 1 ml of methanol:water (9:1, v/v). Afterwards, 25 µl of 40 µg/ml D4-glycocholic acid was added to 500 µl of isolated stool supernatant. The mixtures were passed through a 10 mg capacity Oasis PriME HLB 96-well cartridge (Waters ™ ) to remove phospholipids before LC-MS. LC-MS was carried out on purified faecal samples and stool supernatant samples alongside a set of internal standards (D4-acetic acid, D2-propionic acid and D4- glycocholic acid) using an ACQUITY ultra-high-performance liquid chromatography system (Waters ™ ) coupled to a Xevo TQ-S micro triple quadrupole mass spectrometer (Waters ™ ). The mass spectrometer was operated in positive multiple reaction mode for SCFA quantification, while negative electrospray selected ion monitoring mode was used for D4-glycocholic acid (m/z 468.2), DCA and UDCA (m/z 391.2) and LCA (m/z 375.2) during secondary bile acid analysis. T cell phenotyping Frozen PBMCs were surface stained with a combination of anti-human monoclonal antibodies for a 20 minute incubation at 4°C in the dark: 2 µg/ml CD3-PEcy7 (clone UCHT1; eBioscience™), 5 µg/ml CD4-eFluor 450 (clone OKT4 (OKT-4); eBioscience™), 3 µg/ml CD45RA-PerCP/cy5.5 (clone HI100; Biolegend) and 8 µg/ml CCR7-APCcy7 (clone G043H7; Biolegend), 4.5 µg/ml PTK7-PE (clone 188B; Miltenyi Biotec), 8 µg/ml CD25-APCcy7 (clone M-A251; BD Pharmingen), 0.5 µg/ml CD28-APC (clone CD28.2; eBioscience™), 6 µg/ml CD57-FITC (clone TB01 (TB01); Biolegend), 4 µg/ml PD1-APCcy7 (clone EH12.2H7; Biolegend) 0.5 µg/ml CD69-PEcy5 (clone FN50; Biolegend) and 16 µg/ml CD154-APCcy7 (clone 24–31; Biolegend). Post incubation, the cells were fixed, permeabilised and intracellularly stained with 4 µg/ml anti-human RORγ-APC antibody and 10 ng/ml anti-human Foxp3-PE antibody (clone PCH101; eBioscience™) using the Foxp3 Transcription Factor Staining Buffer Set (eBioscience™) to examine the frequency of peripheral Th17 cells and Tregs. Flow cytometric analysis was carried out on a MACSQuant Analyzer 10 benchtop flow cytometer (Miltenyi Biotec). Prior to data acquisition, concentration-matched isotype controls were used to set the gates, and fluorescence spectral overlap was corrected via compensation during multi-colour flow cytometry. Data analysis was performed using FlowJo software v10.8.1 (BD). T cells were defined as CD3 + ve cells and 10,000 cells were gated and divided into CD4 + ve and CD8 + ve , which were further divided into four subsets based on CD45RA and CCR7 expression and denoted as naive (CD45RA + ve CCR7 +ve) , central memory (CD45RA − ve CCR7 +ve ), effector memory (CD45RA − ve CCR7 −ve ) and EMRA (CD45RA + ve CCR7 −ve ) (see Supplementary Fig. 1 for gating strategy). CD3 + ve CD28 −ve CD57 +ve cells were denoted as senescent T cells [ 65 ]. T cell functional analysis Thawed PBMCs were washed with RPMI-1640 medium supplemented with 10% heat inactivated foetal calf serum (HiFCS), 2 mM L-glutamine, 100 U/ml penicillin and 100 µg/ml streptomycin (300 x g for 10 minutes at 20°C). Post centrifugation, the cells were incubated with Benzonase® Nuclease (Sigma-Aldrich) for 1 hour at 37°C with 5% CO 2 before being transferred to the wells of a 96-well U-bottom plate pre-coated with 0.5 µg/ml anti-human CD3 monoclonal antibody (clone UCHT1; eBioscience™) and 5 µg/ml anti-human CD28 monoclonal antibody (clone CD28.2; eBioscience™). Following a 20 hour incubation at 37°C, 5% CO 2 , 10 µg/ml brefeldin A from Penicllium brefeldianum (Sigma-Aldrich), 50 ng/ml phorbol 12-myristate 13-acetate (Sigma-Aldrich) and 500 ng/ml ionomycin from Streptomyces conglobatus (Sigma-Aldrich) were added to the wells and the PBMCs were incubated for an additional 4 hours. Post incubation, the cells were washed with phosphate buffered saline (PBS) and stained with LIVE/DEAD™ Fixable Near-IR Dead Cell Stain (Invitrogen) and 2 µg/ml CD3-PEcy7 (clone UCHT1) for 20 minutes in the dark at 4°C. The PBMCs were then washed with PBS prior to being fixed and permeabilised using the Foxp3 Transcription Factor Staining Buffer Set. To examine IL10-producing Tregs, the cells were stained with 2 µg/ml anti-human CD4-BV421 (clone RPA-T4; BD Biosciences), 10 ng/ml anti-human Foxp3-PE (clone PCH101) and 100 ng/ml anti-human IL10-APC (clone JES3-19F1; Biolegend) for 30 minutes in the dark at room temperature. Then, the PBMCs were washed and resuspended in 300 µl of PBS. Functional T cell data was assessed using FlowJo software. The percentage positive cells and MFI values were recorded for each antigen. RNA isolation from PBMCs RNA was isolated from 2 million frozen PBMCs according to the instructions of a commercially available RNeasy Mini Kit (Qiagen) and the purified RNA was eluted into 15 µl of RNase-free water. RNA quantity and quality were determined using a NanoDrop One Spectrophotometer (Thermo Fischer Scientific) and a 2100 Bioanalyser (Agilent Technologies), respectively. RNA samples were considered pure if the A260/280 and A260/230 ratios were ≥ 1.8. Purified RNA samples were stored at -80°C for further analysis. NanoString nCounter ® gene expression analysis NanoString nCounter ® was utilised for multiple gene expression profiling in RNA samples using the nCounter ® Human PanCancer Immune Profiling Panel, consisting of 729 genes related to cytokine and chemokine signalling, cellular senescence, immune cell profiling, lymphoid cell function and innate and adaptive immune responses (Nanostring Technologies). 80 ng of unamplified RNA per sample was processed by the Birmingham Tissue Analytics at the University of Birmingham. Normalization and data analysis of count numbers were carried out with NanoString nSolver® Analysis. Qlucore Omics Explorer software v3.8 (Qlucore) was used to create a heatmap using log2 fold-change values to visualise unique gene expression patterns between cohorts. Genes were included if p-values were statistically significant. Mouse experiments Male and female young (10–16 weeks) and aged (20–22 months) wild-type C57BL/6 mice (originally from Jackson Laboratories) were fed a low protein diet (i.e. Teklad Irradiated Global 14% protein Maintenance Diet) and bred in-house. Sex and age-matched germ-free mice (20–22 months) were housed in pathogen-free conditions in the Gnotobiotic Facility of McMaster. All experiments were performed in accordance with the Institutional Animal Utilization protocols [ protocol number 21-04-13] approved by McMaster University’s Animal Research Ethics Board as per the recommendations of the Canadian Council for Animal Care. Thymus and ileum tissues were collected from young wild-type (n = 6), aged wild-type (n = 6) and aged germ-free mice (n = 3). FITC-dextran trans-epithelial intestinal permeability assay Mice were fasted (no food or water) for 6 hours prior to oral gavage of 150 µl of 80 mg/ml tracer labelled FITC-dextran (Sigma-Aldrich) to assess in vivo intestinal permeability. After 4 hours, blood was collected and diluted 2-fold with PBS. Fluorescent intensity was measured on a SpectraMax i3 microplate reader (Molecular Devices, USA) with an excitation wavelength of 493 nm and an emission wavelength of 518 nm. Occludin staining for intestinal membrane permeability assessment Sections of ileum were excised and embedded in OCT compound at -80°C. Tissue blocks were cut into 7 µm sections that were fixed with ice-cold acetone. After blocking with 10% goat serum, the samples were stained with 4 µg/ml mouse anti-mouse occludin antibody (clone E-5; Santa Cruz Biotechnology) overnight, followed by incubation with 40 µg/ml goat anti-mouse Alexa Fluor ® 555 secondary antibody (Thermo Fischer ™ ). Images were acquired using an Olympus IX71 inverted fluorescence microscope at 10X and 40X magnification. Histological analysis and oil red O staining of mouse thymus sections Frozen mouse thymuses embedded in OCT compound were sectioned to a thickness of 7 µm and mounted onto microscope slides before staining with haematoxylin and eosin (H&E) and the percentage of medullary areas was calculated as a percentage. Thymus sections were also stained for lipid droplets using an Oil Red O Staining Kit. Each thymus sample was stained in triplicate and six images were acquired using a Zeiss Primovert inverted light microscope at 10X and 40X magnification. The number of oil red O stained lipid droplets per µm 2 was determined using Fiji software. Nuclear lamin B1 staining Microscope slides containing mouse thymus sections were fixed with ice-cold acetone and stained with recombinant anti-mouse lamin B1 antibody (clone EPR22165-121; Abcam) consisting of 10% HiFCS and 0.2% triton-X 100 in PBS overnight followed by staining with 6.6 µg/ml anti-rabbit IgG conjugated to Alexa Fluor ® 555 (clone H + L, F(ab’) 2 ; Cell Signalling Technology). Post wash, tissues were stained with 1 µg/ml DAPI solution (Thermo Fischer ™ ). Images were acquired using an Olympus IX71 inverted fluorescence microscope at 10X and 40X magnification and imaging analysis was performed using Image J software. Thymocyte and thymic epithelial cell (TEC) staining Frozen thymus sections fixed with ice-cold acetone were stained with a combination of anti-mouse monoclonal antibodies for 30 minutes in the dark at room temperature: 2.5 µg/ml CD4 Alexa Fluor 647 (clone RM4-5; Biolegend), 1.7 µg/ml CD8α biotin (clone 53 − 6.7; eBioscience ™ ), ERTR5 rat IgM [ 67 ], 10 µg/ml CD205 biotin (clone 205yeka; eBiosience ™ ) and 10 µg/ml Aire Alexa Fluor 488 (clone 5H12; Thermo Fischer Scientific). Post incubation, the slides were incubated with the following secondary antibodies: 2 µg/ml streptavidin Alexa Fluor 555 (Thermo Fischer Scientific), 2.5 µg/ml goat anti-rat IgM Alexa Fluor 488 (Thermo Fischer Scientific) and 10 µg/ml goat anti-rat IgM Alexa-Fluor 647 (Thermo Fischer Scientific). The slides were then washed and incubated with 1 µg/ml DAPI solution (Thermo Fischer ™ ) in preparation for confocal microscopy. Each thymus sample was stained in triplicate and six images of the medullary and cortical regions were acquired on Zeiss LSM 880 with Airyscan Fast confocal microscope at 10X and 40X magnification. Before image acquisition, primary antibody-only controls and secondary antibody-only controls were used to detect possible non-specific binding and autofluorescence. Confocal imaging analysis was performed using Zeiss Zen Black software to calculate the positively staining ERTr5 and CD205 pixels were expressed as a percentage of the total pixels in the picture. RNA isolation and quantitative real time-PCR RNA was isolated from thymus samples using a commercially available RNeasy Mini Kit as per the manufacturer’s instructions (Qiagen). RNA quantity and quality were determined using a NanoDrop One Spectrophotometer and a 2100 Bioanalyser.Quantitative. Quantitative real time-PCR was carried out on 5 ng/µl RNA isolated from mouse thymus samples using the iTaq Universal SYBR Green One-Step Kit (Biorad) on a CFX384 Tough Real-Time PCR Detection System (Biorad). Primer sequences (5’–3’) were p16 (TTGGCCCAAGAGCGGGGACA), IL6 (CTGCAAGAGACTTCCATCCAG), BAX (AGGATGAGTCCACCAAGAAGCT) and housekeeping gene Epcam (TTGCTCCAAACTGGCGTCTAA). The PCR thermocycler condition was as follows: initial reverse transcription at 50°C for 10 minutes, polymerase activation at 95°C for 5 minutes, 40 cycles of denaturation at 95°C for 10 seconds, annealing at 60°C for 30 seconds and initial elongation at 65°C for 31 seconds followed by 60 cycles of elongation at 65°C for 5 seconds. All samples were run in triplicate. Relative gene expression was calculated using the ΔΔCt method followed by normalisation of the values to the relative gene expression of Epcam. Statistical analysis All statistical analysis was performed using GraphPad Prism® software (GraphPad Software Inc.). Data distribution was examined using Kolmogorov-Smirnov normality test before parametric and non-parametric tests were performed. Parametric tests were carried out on normally distributed data, while non-parametric tests were used when the data was not normally distributed. Unpaired Student’s T test (parametric test) and Mann-Whitney U test (non-parametric) were used to compare means between young and old adults and the Benjamini-Hochberg method was used to calculate adjusted p-values. Chi-square test was used to compare categorical data, such as sex and smoking status, between the groups. One-way analysis of variance (ANOVA) was used to compare means between low MT young, low MT old and high MT old adults as well as means between young wild-type, aged wild-type and aged germ-free mice. Following one-way ANOVA, Bonferroni (parametric test) and Dunn’s (non-parametric) multiple comparison tests were performed to calculate adjusted p-values. Spearman correlation-based linear regression analysis was performed to determine the strength of associations between all combinations of intestinal barrier dysfunction surrogate markers and hallmarks of immunesenescence [ 68 ]. For pathway enrichment analysis, the Benjamin-Hochberg false discovery rate was used to calculate adjusted p-values. Statistical significance was accepted as p ≤ 0.05. Declarations Ethical approval Human study was approved by the North West - Haydock Research Ethics Committee [ REC reference: 22/NW/0187]. Written consent was obtained from all participants. All procedures involving animals were approved by approved by McMaster University’s Animal Research Ethics Board as per the recommendations of the Canadian Council for Animal Care. Acknowledgements We are grateful to the participants that have made this research possible. We thank Joe Flint from Birmingham Tissue Analytics at the University of Birmingham, for technical assistance in the generation of nCounter data. Funding This work was supported by funding from the Academy of Medical Sciences Springboard Award and the MRC-Versus Arthritis Centre for Musculoskeletal Ageing Research. GA is supported by an MRC Programme Grant to GA (MR/T029765/1). The views expressed here are those of the authors and not necessarily those of the Department for Health and Social care. The funders provided financial support to this research but had no role in the design of the study, analysis, interpretations of the data and in writing the manuscript. Availability of data and materials Raw flow cytometry will be made available upon request. Conflicts of Interest The authors declare that they have no conflicts of interest connected to this paper. References Paray, B. A., Albeshr, M. 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Wu, C., Sakorafas, P., Miller, R., McCarthy, D., Scesney, S., Dixon, R. & Ghayur, T. IL-18 receptor beta-induced changes in the presentation of IL-18 binding sites affect ligand binding and signal transduction. J Immunol 170, 5571–5577 (2003). Chiang, H. Y., Chu, P. H. & Lee, T. H. MFG-E8 mediates arterial aging by promoting the proinflammatory phenotype of vascular smooth muscle cells. J Biomed Sci 26, 61 (2019). Corcoran, L., Emslie, D., Kratina, T., Shi, W., Hirsch, S., Taubenheim, N. & Chevrier, S. Oct2 and Obf1 as facilitators of B:T cell collaboration during a humoral immune response. Front Immunol 5, 108 (2014). Tewari, R., Shayahati, B., Fan, Y. & Akimzhanov, A. M. T cell receptor-dependent S-acylation of ZAP-70 controls activation of T cells. J Biol Chem 296, 100311 (2021). Tables Table 1 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table1.pptx Table 1: Participant demographics. Data are mean ± standard error mean. One-way ANOVA with Bonferroni’s multiple comparison test and Dunn’s multiple comparison test along with Chi-square test were used. Significant p-values are highlighted in red. Abbreviations: BMI, body mass index; CMV, cytomegalovirus; HADS, Hospital Anxiety and Depression Score; IgG, immunoglobulin G; MET, metabolic equivalent of task; PSQI, Pittsburgh Sleep Quality Index. SupplementaryFigure1.pptx Supplementary Figure 1: T cell subset gating strategy. After excluding double cells and dead cells (A) CD3 +ve T cells were gated on using forward scatter (FSC) parameters. Naïve T cells and memory T cell subsets were identified within the (B) CD4 and CD8 T cell pools based on differential surface expression of CCR7 and CD45RA (C): naive (CD45RA +ve CCR7 +ve) , central memory (CM) (CD45RA -ve CCR7 +ve ), effector memory (EM) (CD45RA -ve CCR7 -ve ) and terminally differentiated effector memory re-expressing RA (EMRA) (CD45RA +ve CCR7 -ve ) (D) Recent thymic emigrants are expressed as PTK7 +ve naïve CD4 T cells (E) Activated CD69 +ve (F) Regulatory Foxp3 +ve (G) Th17 RORγ +ve helper CD4 T cells. SupplementaryTable1.pptx Supplementary Table 1: Links between microbial translocation and lifestyle habits. Correlations (Spearman) between surrogate markers for microbial translocation (occludin, LBP and sCD14) and lifestyle/behavioural parameters in young (n = 27) and old (n = 55) adults. Positive correlations are bold in green, while negative correlations are bold in red. Abbreviations: BMI, body mass index; CMV, cytomegalovirus; HADS, Hospital Anxiety and Depression Score; IgG, immunoglobulin G; MET, metabolic equivalent of task; PSQI, Pittsburgh Sleep Quality Index. SupplementaryTable2.pptx Supplementary Table 2: Faecal microbiota composition of young and old adults displaying low and high microbial translocation. Summary of differences in the distribution of bacterial species in stool samples from low MT young (n = 27), low MT old (n = 24) and high MT old (n = 31) individuals. Data are mean ± standard error mean. One-way ANOVA with Bonferroni’s multiple comparison test and Dunn’s multiple comparison test were used. Significant p-values are highlighted in red. SupplementaryTable3.pptx Supplementary Table 3: CD4 T cell subset distribution.Summary of differences in the distribution of naïve and memory CD4 T cell subsets between low MT young (n = 27), low MT old (n = 24) and high MT old (n = 31) individuals. Data are mean ± standard error mean. One-way ANOVA with Bonferroni’s multiple comparison test and Dunn’s multiple comparison test were used. Significant p-values are highlighted in red. Abbreviations: CM, central memory; EM, effector memory; EMRA, effector memory cells re-expressing CD45RA; IFNγ, interferon gamma; PD1, programmed cell-death 1. SupplementaryTable4.pptx Supplementary Table 4: CD8 T cell subset distribution. Summary of differences in the distribution of naïve and memory CD8 T cell subsets between low MT young (n = 27), low MT old (n = 24) and high MT old (n = 31) individuals. Data are mean ± standard error mean. One-way ANOVA with Bonferroni’s multiple comparison test and Dunn’s multiple comparison test were used. Significant p-values are highlighted in red. Abbreviations: CM, central memory; EM, effector memory; EMRA, effector memory cells re-expressing CD45RA; PD1, programmed cell-death 1. SupplementaryTable5.pptx Supplementary Table 5: Circulating inflammatory markers. Summary of differences in circulating pro- and anti-inflammatory cytokines between low MT young (n = 15), low MT old (n = 14) and high MT old (n = 20) participants. Data are mean ± standard error mean. One-way ANOVA with Bonferroni’s multiple comparison test and Dunn’s multiple comparison test were used. Significant p-values are highlighted in red. Abbreviations: CRP, C reactive protein; CXCL9, chemokine receptor ligand 9; GM-CSF, granulocyte-macrophage colony-stimulating factor. SupplementaryTable6.pptx Supplementary Table 6: Genes differentially expressed in PBMCs from low MT young and low MT old adults. Summary of comparison of differentially expressed genes in PBMCs between low MT young (n = 6) and low MT old (n = 6). Data are expressed as mean and log2 fold change. One-way ANOVA with Bonferroni’s multiple comparison test and Dunn’s multiple comparison test were used. Significant p-values are highlighted in red. Abbreviations: ALCAM, activated leukocyte cell adhesion molecule; BCR, B cell receptor; BID, BH3 interacting-domain death agonist; BLNK, B cell linker; CR2, complement C3d receptor 2; LRRN3, leucine rich repeat neuronal 3; NT5E, 5’-nucleotidase ecto; TNFRSF13B, TNF receptor superfamily member 13B. SupplementaryFigure7.pptx Supplementary Table 7: Genes differentially expressed in PBMCs from low MT young and high MT old adults. Summary of comparison of differentially expressed genes in PBMCs between low MT young (n = 6) and high MT old (n = 6). Data are expressed as mean and log2 fold change. One-way ANOVA with Bonferroni’s multiple comparison test and Dunn’s multiple comparison test were used. Significant p-values are highlighted in red. Abbreviations: ALCAM, activated leukocyte cell adhesion molecule; AMICA1, adhesion molecule interacting with CXADR antigen 1; ATG7, autophagy related 7; ATM, ataxia telangiectasia mutated; BCL2, B cell lymphoma 2; CASP3, caspase 3; CCR7, C-C motif chemokine receptor 7; CD, cluster of differentiation; CLEC6A, C-type lectin domain containing 6A; CR1, complement C3b/C4b receptor 1; DUSP4, dual specificity phosphatase 4; DUSP6, dual specificity phosphatase 6; EGR1, early growth response 1; FOS, Fos proto-oncogene AP-1 transcription factor subunit; ICOS, inducible T cell costimulatory; IRF5, interferon regulatory factor 5; KLRG1, killer cell lectin like receptor G1; LAMP1, lysosomal associated membrane protein 1; MAPK3, mitogen-activated protein kinase 3; MEFV, Mediterranean fever; NEFL, neurofilament light polypeptide; PTGS2, prostaglandin-endoperoxide synthase 2; RORA, RAR related orphan receptor A; TLR4, toll-like receptor 4; TLR8, toll-like receptor 8; TXNIP, thioredoxin interacting protein. SupplementaryFigure8.pptx Supplementary Table 8: Genes differentially expressed in PBMCs from low MT old and high MT old adults. Summary of comparison of differentially expressed genes in PBMCs between low MT old (n = 6) and high MT old (n = 6). Data are expressed as mean and log2 fold change. One-way ANOVA with Bonferroni’s multiple comparison test and Dunn’s multiple comparison test were used. Significant p-values are highlighted in red. Abbreviations: ATG7, autophagy related 7; BID, BH3 interacting-domain death agonist; BLNK, B cell linker; CASP8, caspase 8; CD99 cluster of differentiation 99; CLEC6A, C-type lectin domain containing 6A; CR1, complement C3b/C4b receptor 1; DAMP, damage-associated molecular pattern; DUSP4, dual specificity phosphatase 4; DUSP6, dual specificity phosphatase 6; G6PD, glucose-6-phosphate dehydrogenase; HAVCR2, hepatitis A virus cellular receptor 2; HLA-DRB4, major histocompatibility complex class II DR beta 4; HMGB1, high mobility group box 1 protein; ICOS, inducible T cell costimulatory; IL12RB, interleukin 12 receptor subunit beta; IL18R1, interleukin 18 receptor 1; IRF5, interferon regulatory factor 5; LILRB2, leukocyte immunoglobulin like receptor B2; MHC, major histocompatibility complex; POU2AF1, POU class 2 homeobox associating factor 1; TCR, T cell receptor; TLR4, toll-like receptor 4; ZAP70, zeta chain of T cell receptor associated protein kinase 70. 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McMaster University","correspondingAuthor":false,"prefix":"","firstName":"Erica","middleName":"N","lastName":"DeJong","suffix":""},{"id":267084373,"identity":"9c4c9ec8-42d8-4bfd-821e-bb1776d92706","order_by":2,"name":"Andrea Andrea J White","email":"","orcid":"","institution":"Institute for Immunology and Immunotherapy, University of Birmingham","correspondingAuthor":false,"prefix":"","firstName":"Andrea","middleName":"Andrea J","lastName":"White","suffix":""},{"id":267084374,"identity":"2ef55829-32a8-4bbf-9755-ae21c00f6c67","order_by":3,"name":"Ben Dugan","email":"","orcid":"","institution":"Institute of Inflammation and Ageing, University of Birmingham","correspondingAuthor":false,"prefix":"","firstName":"Ben","middleName":"","lastName":"Dugan","suffix":""},{"id":267084375,"identity":"f12c4e7b-6cfd-401b-8bc8-57bf436335bf","order_by":4,"name":"Nia Paddison Rees","email":"","orcid":"","institution":"Institute of Inflammation and Ageing, University of 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11:44:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3845290/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3845290/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49671172,"identity":"71b7377e-4e7d-4a34-9f2d-4bc771271555","added_by":"auto","created_at":"2024-01-16 08:55:32","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":149021,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAge-related microbial translocation and potential contributors\u003c/strong\u003e. (A) Study design and exclusion criteria for participant recruitment. Circulating levels of occludin (B), LBP (C), sCD14 (D) in young (n = 27) and old (n = 55) participants. Unpaired Student’s T test and Mann-Whitney U test were used. *p ≤0.05, ***p ≤0.001. Spearman-based correlations between LBP levels and the relative abundances of \u003cem\u003eEscherichia-Shigella\u003c/em\u003e (E), \u003cem\u003ePeptostreptococcaceae\u003c/em\u003e (F) and \u003cem\u003eParaprevotella\u003c/em\u003e (G) in the faecal microbiome. Spearman-based correlations between occludin levels and propionate (H) and GDCA (I).\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-3845290/v1/8a3ab07f44dd1158367ff776.png"},{"id":49672093,"identity":"8d552e6c-dbce-494a-a579-65f9735521a2","added_by":"auto","created_at":"2024-01-16 09:03:32","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":49734,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLinks between age-related intestinal barrier dysfunction and gut microbiome composition. \u003c/strong\u003eFaecal levels of (A) bacterial species (B) short-chain fatty acids (SCFAs) (C) and secondary bile acids (E) in low MT young (blue), low MT old (red) and high MT old (green) adults. One-way ANOVA with Bonferroni’s multiple comparison test was used. * p ≤0.05, **** p ≤0.0001. Abbreviations: DCA, deoxycholic acid; HDCA, hyodeoxycholic acid; LCA, lithocholic acid; UDCA, ursodeoxycholic acid.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-3845290/v1/df78be40f00475e64859b1fe.png"},{"id":49671173,"identity":"6210745f-ba8c-43a3-b85c-9baa69e7b93a","added_by":"auto","created_at":"2024-01-16 08:55:32","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":88862,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAge-related microbial translocation and T cell subset distribution.\u003c/strong\u003e (A) The percentage of PTK7\u003csup\u003e+ve\u003c/sup\u003eCD45RA\u003csup\u003e+ve\u003c/sup\u003e RTEs within the CD4 T cell pool in low MT young adults (n = 20), low MT old adults (n = 14) and high MT old adults (n = 15). (B) The proportion of EMRA CD4 T cells and CD8 T cells (C) and CD69\u003csup\u003e+ve\u003c/sup\u003e CD8 T cells (D). (E) Representative flow cytometric plots showing CD28\u003csup\u003e-ve\u003c/sup\u003eCD57\u003csup\u003e+ve\u003c/sup\u003e senescent CD8 T cells in a young adult with low microbial translocation and a healthy old individual displaying high microbial translocation. (F) The peripheral frequency of CD28\u003csup\u003e-ve\u003c/sup\u003eCD57\u003csup\u003e+ve\u003c/sup\u003e senescent CD8 T cells. (H) Means are shown as solid lines. One-way ANOVA with Bonferroni’s multiple comparison test and Dunn’s multiple comparisons test were used. *p ≤0.05, ** p ≤0.01, ***p ≤0.001, ****p ≤0.0001.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-3845290/v1/35e1601deea02aedd736895d.png"},{"id":49671176,"identity":"421c497e-092d-4844-a121-79f9e80d5313","added_by":"auto","created_at":"2024-01-16 08:55:32","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":49269,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAge-related microbial translocation and T cell ageing \u003c/strong\u003e(A) The percentage of RORγ\u003csup\u003e+ve\u003c/sup\u003e Th17 cells in low MT young adults (n = 25), low MT old adults (n = 13) and high MT old adults (n = 23). (B) Intracellular IL17 expression levels (MFI) in CD4 T cells from young (n = 22) and old (n = 11) donors with low MT and high MT (n = 24). (C) The peripheral frequency of CD25\u003csup\u003e+ve\u003c/sup\u003eFoxp3\u003csup\u003e+ve\u003c/sup\u003e Tregs. (D) Intracellular IL10 expression levels (MFI) in CD4 T cells from young (n = 22) and old (n = 11) donors with low MT and high MT (n = 24). (A-D) Means are shown as solid bars. One-way ANOVA with Bonferroni’s multiple comparison test and Dunn’s multiple comparisons test were used. *p ≤0.05, **p ≤0.01, ****p ≤0.0001.(E) Linear regression plot showing correlations (Spearman) between the circulating LBP levels and the and IL10-producing Tregs. (F) Comparison of immunological age (IMM-AGE score) between young (n = 40) and old (n = 40) volunteers using Unpaired Student’s T test. ****p ≤0.0001. (G) Spearman’s rank-based correlation plots depicting associations between surrogate markers for intestinal barrier dysfunction and the IMM-AGE score.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-3845290/v1/fc33c455726058dbe55b7b2c.png"},{"id":49671177,"identity":"723dc974-2648-4f88-81b7-e55f112b4cb6","added_by":"auto","created_at":"2024-01-16 08:55:32","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":104738,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMolecular mechanisms underpinning microbial translocation-induced T cell ageing. \u003c/strong\u003eHeat map showing fold change log(2) of differentially expressed genes in low MT young (n = 6), low MT old (n = 6) and high MT old (n = 6) participants.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-3845290/v1/b9e5a61d20c1a991c399ab8f.png"},{"id":49672647,"identity":"7d506c1a-d930-420a-b222-659eb8e25119","added_by":"auto","created_at":"2024-01-16 09:11:32","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":728299,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThymic tissue organisation and adiposity in aged germ-free mice protected from intestinal barrier dysfunction. \u003c/strong\u003e(A) Experimental design for the mouse model used. (B) Intestinal permeability in young (n = 6) and aged (n = 6) wild-type mice and aged germ-free mice (n = 2) measured via FITC-dextran fluorescence in blood by Erica DeJong following oral gavage. (C) Representative immunohistochemical images of tight junction protein, occludin-1 (red staining) and nuclei (blue staining) in intestinal villi of mouse ileum sections taken at 10X magnification (top row) and 40X magnification (bottom row). (D) Relative mRNA expression levels of \u003cem\u003eE.\u003c/em\u003e \u003cem\u003ecoli\u003c/em\u003e in young (n = 5) and aged (n = 2) wild-type and aged germ-free (n = 2) mouse thymuses. (E) Representative H\u0026amp;E stained images of mouse thymus sections with medullary regions stained light purple (indicated by M) and cortical regions stained dark purple (indicated by C). (F) Percentages of medullary regions in thymuses from young wild-type (n = 3), aged wild-type (n = 3) and aged germ-free (n = 3) mice. Images on the top row were taken at a 4X magnification, and a higher 40X magnification was used for the cortex region shown on the bottom row. Arrows point to vacuoles. (G) Representative immunohistochemical images of oil red O stained mouse thymus sections at 40X magnification. (H) The number of lipid droplets per μm\u003csup\u003e2\u003c/sup\u003e in young and aged wild-type mice (n = 6 for both) and aged germ-free mice (n = 3). Statistical significance was determined using one-way ANOVA followed by Dunns’ multiple comparison test. **p ≤0.01.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-3845290/v1/c5703d43d49d880fa21b62cc.png"},{"id":49672094,"identity":"eac906fa-9c98-4dd4-99d2-07cb1b219eec","added_by":"auto","created_at":"2024-01-16 09:03:32","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":501948,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThymic involution and underlying mechanisms in aged wild-type and aged-germ free mice.\u003c/strong\u003e (A) Representative mouse thymus images depicting the distribution of CD205\u003csup\u003e+ve\u003c/sup\u003e cTECs (red), ERTR5\u003csup\u003e+ve\u003c/sup\u003e mTECs (blue) and AIRE\u003csup\u003e+ve\u003c/sup\u003e mature mTECs (green) at 4X magnification (left) and 40X magnification (right). Percentages of ERT5\u003csup\u003e+ve\u003c/sup\u003e areas (B) and CD205\u003csup\u003e+ve\u003c/sup\u003e areas (C) in thymuses from young wild-type (n = 3), aged wild-type (n = 3) and aged germ-free (n = 3) mice. (D) Lamin B1 (red) and DAPI (blue) stained mouse thymus sections imaged at 4X magnification (left) and 40X magnification (right). Medullary islands are marked by ‘M’ and dotted lines, while cortical regions are marked by ‘C’. Lamin B1 thymic expression levels (MFI) in the cortex (C) and medulla (D). Relative mRNA expression levels of IL6 (E), p16 (F) and BAX (G) in thymuses from young wild-type (n = 6), aged wild-type (n = 6) and aged germ-free (n = 3) mice. Statistical significance was determined using one-way ANOVA followed by Dunns’ multiple comparison test. *p ≤0.05, ** p ≤0.01, ***p ≤0.001, ****p ≤0.0001.\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-3845290/v1/bf72a41a6ac43ad81144e5c3.png"},{"id":49671183,"identity":"f8968886-6d5e-44dc-b98e-ceebbb783566","added_by":"auto","created_at":"2024-01-16 08:55:32","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":447049,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThymocyte distribution in aged wild-type and aged germ-free mice. \u003c/strong\u003e(A)Mouse thymus sections stained with CD4 (blue), CD8 (red) and ERTR5 (green) to assess the distribution of thymocytes in ERTR5\u003csup\u003e-ve\u003c/sup\u003e cortical (marked as ‘C’) and ERTR5\u003csup\u003e+ve\u003c/sup\u003e medullary (marked as ‘M’) regions. Images on the left were taken at 10X magnification, while images on the right were taken at 40X magnification. Percentages of CD8\u003csup\u003e+ve\u003c/sup\u003e areas in the (B) cortex and (C) medullary regions in thymuses from young wild-type (n = 3), aged wild-type (n = 3) and aged germ-free (n = 3) mice. Percentages of CD4\u003csup\u003e+ve\u003c/sup\u003e areas in the (D) cortex and (E) medullary regions in thymuses from young wild-type (n = 3), aged wild-type (n = 3) and aged germ-free (n = 3) mice. Statistical significance was determined using one-way ANOVA *p ≤0.05.\u003c/p\u003e","description":"","filename":"Figure8.png","url":"https://assets-eu.researchsquare.com/files/rs-3845290/v1/8d7ff39f5d03a5709a03e29c.png"},{"id":49672646,"identity":"3aea9422-1ea5-4bab-ab10-1d737769940a","added_by":"auto","created_at":"2024-01-16 09:11:32","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":172125,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGraphical summary of the impact of age-associated gut barrier dysfunction on thymic involution and T cell ageing.\u003c/strong\u003e Loss of intestinal barrier integrity with age permits the translocation of microbes and microbial products, such as LPS, into the circulation. These microbial products are then trafficked through the blood, contributing to persistent antigenic stimulation that leads to the accumulation of senescent T cells. Through their senescence-associated secretory phenotype (SASP), senescent T cells promote systemic inflammation and induce a bystander effect in the thymus, contributing to age-related thymic involution and a reduced thymic output of naïve T cells (RTEs). Loss of naïve T cells and chronic antigenic stimulation result in skewing towards T cell senescence, which accelerates immunological ageing (high IMM-AGE score) in older adults.\u003c/p\u003e","description":"","filename":"Figure9.png","url":"https://assets-eu.researchsquare.com/files/rs-3845290/v1/6e122e7f1b477e9bc4516741.png"},{"id":56467583,"identity":"9611fa16-1dd5-42bb-93fd-b358674f4379","added_by":"auto","created_at":"2024-05-14 15:03:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3317442,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3845290/v1/d2f9b11b-d44b-4720-8924-1e2209fb6ff6.pdf"},{"id":49671174,"identity":"6ff8fa03-3e5e-46e7-aa93-a6818810ad04","added_by":"auto","created_at":"2024-01-16 08:55:32","extension":"pptx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":46680,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable 1: Participant demographics.\u003c/strong\u003e Data are mean ± standard error mean. One-way ANOVA with Bonferroni’s multiple comparison test and Dunn’s multiple comparison test along with Chi-square test were used. Significant p-values are highlighted in red. Abbreviations: BMI, body mass index; CMV, cytomegalovirus; HADS, Hospital Anxiety and Depression Score; IgG, immunoglobulin G; MET, metabolic equivalent of task; PSQI, Pittsburgh Sleep Quality Index.\u003c/p\u003e","description":"","filename":"Table1.pptx","url":"https://assets-eu.researchsquare.com/files/rs-3845290/v1/d29f34328b50b0f2776ac208.pptx"},{"id":49672096,"identity":"b9e01f3f-6af8-47e1-8c05-2c6204cd8915","added_by":"auto","created_at":"2024-01-16 09:03:32","extension":"pptx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1310759,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure 1: T cell subset gating strategy. \u003c/strong\u003eAfter excluding double cells and dead cells (A) CD3\u003csup\u003e+ve\u003c/sup\u003e T cells were gated on using forward scatter (FSC) parameters. Naïve T cells and memory T cell subsets were identified within the (B) CD4 and CD8 T cell pools based on differential surface expression of CCR7 and CD45RA (C): naive (CD45RA\u003csup\u003e+ve\u003c/sup\u003eCCR7\u003csup\u003e+ve)\u003c/sup\u003e, central memory (CM) (CD45RA\u003csup\u003e-ve\u003c/sup\u003eCCR7\u003csup\u003e+ve\u003c/sup\u003e), effector memory (EM) (CD45RA\u003csup\u003e-ve\u003c/sup\u003eCCR7\u003csup\u003e-ve\u003c/sup\u003e) and terminally differentiated effector memory re-expressing RA (EMRA) (CD45RA\u003csup\u003e+ve\u003c/sup\u003eCCR7\u003csup\u003e-ve\u003c/sup\u003e) (D) Recent thymic emigrants are expressed as PTK7\u003csup\u003e+ve \u003c/sup\u003enaïve CD4 T cells (E) Activated CD69\u003csup\u003e+ve \u003c/sup\u003e(F) Regulatory Foxp3\u003csup\u003e+ve \u003c/sup\u003e(G) Th17 RORγ\u003csup\u003e+ve\u003c/sup\u003e helper CD4 T cells.\u003c/p\u003e","description":"","filename":"SupplementaryFigure1.pptx","url":"https://assets-eu.researchsquare.com/files/rs-3845290/v1/37a29ae36e00746e1a51e96b.pptx"},{"id":49671180,"identity":"a363f823-fb9c-4641-a7e2-23e516e19be5","added_by":"auto","created_at":"2024-01-16 08:55:32","extension":"pptx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":46257,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 1: Links between microbial translocation and lifestyle habits.\u003c/strong\u003e Correlations (Spearman) between surrogate markers for microbial translocation (occludin, LBP and sCD14) and lifestyle/behavioural parameters in young (n = 27) and old (n = 55) adults. Positive correlations are bold in green, while negative correlations are bold in red. Abbreviations: BMI, body mass index; CMV, cytomegalovirus; HADS, Hospital Anxiety and Depression Score; IgG, immunoglobulin G; MET, metabolic equivalent of task; PSQI, Pittsburgh Sleep Quality Index.\u003c/p\u003e","description":"","filename":"SupplementaryTable1.pptx","url":"https://assets-eu.researchsquare.com/files/rs-3845290/v1/2bb4eb5405676f6553d31aaf.pptx"},{"id":49671184,"identity":"57b75ba7-33b0-4c66-be93-506651ef23e4","added_by":"auto","created_at":"2024-01-16 08:55:32","extension":"pptx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":47245,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 2: Faecal microbiota composition of young and old adults displaying low and high microbial translocation.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSummary of differences in the distribution of bacterial species in stool samples from low MT young (n = 27), low MT old (n = 24) and high MT old (n = 31) individuals. Data are mean ± standard error mean. One-way ANOVA with Bonferroni’s multiple comparison test and Dunn’s multiple comparison test were used. Significant p-values are highlighted in red.\u003c/p\u003e","description":"","filename":"SupplementaryTable2.pptx","url":"https://assets-eu.researchsquare.com/files/rs-3845290/v1/aa0d61c93b6382dc05a530fa.pptx"},{"id":49672097,"identity":"de9a62bb-05c8-4da5-b4c0-dd7459efd07f","added_by":"auto","created_at":"2024-01-16 09:03:32","extension":"pptx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":47224,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 3: CD4 T cell subset distribution.\u003c/strong\u003eSummary of differences in the distribution of naïve and memory CD4 T cell subsets between low MT young (n = 27), low MT old (n = 24) and high MT old (n = 31) individuals. Data are mean ± standard error mean. One-way ANOVA with Bonferroni’s multiple comparison test and Dunn’s multiple comparison test were used. Significant p-values are highlighted in red. Abbreviations: CM, central memory; EM, effector memory; EMRA, effector memory cells re-expressing CD45RA; IFNγ, interferon gamma; PD1, programmed cell-death 1.\u003c/p\u003e","description":"","filename":"SupplementaryTable3.pptx","url":"https://assets-eu.researchsquare.com/files/rs-3845290/v1/debe3688820ce8571ca91e9f.pptx"},{"id":49672099,"identity":"b6b04abd-b2ae-43d5-bdfa-daa2a6d4c702","added_by":"auto","created_at":"2024-01-16 09:03:32","extension":"pptx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":47420,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 4: CD8 T cell subset distribution.\u003c/strong\u003e Summary of differences in the distribution of naïve and memory CD8 T cell subsets between low MT young (n = 27), low MT old (n = 24) and high MT old (n = 31) individuals. Data are mean ± standard error mean. One-way ANOVA with Bonferroni’s multiple comparison test and Dunn’s multiple comparison test were used. Significant p-values are highlighted in red. Abbreviations: CM, central memory; EM, effector memory; EMRA, effector memory cells re-expressing CD45RA; PD1, programmed cell-death 1.\u003c/p\u003e","description":"","filename":"SupplementaryTable4.pptx","url":"https://assets-eu.researchsquare.com/files/rs-3845290/v1/4dfe1496cc652a269bf24ee2.pptx"},{"id":49671181,"identity":"17984443-a110-4aee-8ed9-02011164511f","added_by":"auto","created_at":"2024-01-16 08:55:32","extension":"pptx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":46484,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 5: Circulating inflammatory markers.\u003c/strong\u003e Summary of differences in circulating pro- and anti-inflammatory cytokines between low MT young (n = 15), low MT old (n = 14) and high MT old (n = 20) participants. Data are mean ± standard error mean. One-way ANOVA with Bonferroni’s multiple comparison test and Dunn’s multiple comparison test were used. Significant p-values are highlighted in red. Abbreviations: CRP, C reactive protein; CXCL9, chemokine receptor ligand 9; GM-CSF, granulocyte-macrophage colony-stimulating factor.\u003c/p\u003e","description":"","filename":"SupplementaryTable5.pptx","url":"https://assets-eu.researchsquare.com/files/rs-3845290/v1/ceea4bec34a397a5a886b762.pptx"},{"id":49672100,"identity":"57c9056c-1a73-4b9a-ba2a-27caa890cb8e","added_by":"auto","created_at":"2024-01-16 09:03:32","extension":"pptx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":45276,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 6: Genes differentially expressed in PBMCs from low MT young and low MT old adults. \u003c/strong\u003eSummary of comparison of differentially expressed genes in PBMCs between low MT young (n = 6) and low MT old (n = 6). Data are expressed as mean and log2 fold change. One-way ANOVA with Bonferroni’s multiple comparison test and Dunn’s multiple comparison test were used. Significant p-values are highlighted in red. Abbreviations: ALCAM, activated leukocyte cell adhesion molecule; BCR, B cell receptor; BID, BH3 interacting-domain death agonist; BLNK, B cell linker; CR2, complement C3d receptor 2; LRRN3, leucine rich repeat neuronal 3; NT5E, 5’-nucleotidase ecto; TNFRSF13B, TNF receptor superfamily member 13B.\u003c/p\u003e","description":"","filename":"SupplementaryTable6.pptx","url":"https://assets-eu.researchsquare.com/files/rs-3845290/v1/5ffb870428a85aa0954f767d.pptx"},{"id":49671188,"identity":"189dbfc1-cd6d-4a5c-a08c-3692f87e2119","added_by":"auto","created_at":"2024-01-16 08:55:32","extension":"pptx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":47710,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 7: Genes differentially expressed in PBMCs from low MT young and high MT old adults.\u003c/strong\u003e Summary of comparison of differentially expressed genes in PBMCs between low MT young (n = 6) and high MT old (n = 6). Data are expressed as mean and log2 fold change. One-way ANOVA with Bonferroni’s multiple comparison test and Dunn’s multiple comparison test were used. Significant p-values are highlighted in red. Abbreviations: ALCAM, activated leukocyte cell adhesion molecule; AMICA1, adhesion molecule interacting with CXADR antigen 1; ATG7, autophagy related 7; ATM, ataxia telangiectasia mutated; BCL2, B cell lymphoma 2; CASP3, caspase 3; CCR7, C-C motif chemokine receptor 7; CD, cluster of differentiation; CLEC6A, C-type lectin domain containing 6A; CR1, complement C3b/C4b receptor 1; DUSP4, dual specificity phosphatase 4; DUSP6, dual specificity phosphatase 6; EGR1, early growth response 1; FOS, Fos proto-oncogene AP-1 transcription factor subunit; ICOS, inducible T cell costimulatory; IRF5, interferon regulatory factor 5; KLRG1, killer cell lectin like receptor G1; LAMP1, lysosomal associated membrane protein 1; MAPK3, mitogen-activated protein kinase 3; MEFV, Mediterranean fever; NEFL, neurofilament light polypeptide; PTGS2, prostaglandin-endoperoxide synthase 2; RORA, RAR related orphan receptor A; TLR4, toll-like receptor 4; TLR8, toll-like receptor 8; TXNIP, thioredoxin interacting protein.\u003c/p\u003e","description":"","filename":"SupplementaryFigure7.pptx","url":"https://assets-eu.researchsquare.com/files/rs-3845290/v1/a22b0ac4a60b8a70e4b18deb.pptx"},{"id":49671190,"identity":"69422f74-ea56-4c35-a495-663fa3233d11","added_by":"auto","created_at":"2024-01-16 08:55:32","extension":"pptx","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":47025,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 8: Genes differentially expressed in PBMCs from low MT old and high MT old adults.\u003c/strong\u003e Summary of comparison of differentially expressed genes in PBMCs between low MT old (n = 6) and high MT old (n = 6). Data are expressed as mean and log2 fold change. One-way ANOVA with Bonferroni’s multiple comparison test and Dunn’s multiple comparison test were used. Significant p-values are highlighted in red. Abbreviations: ATG7, autophagy related 7; BID, BH3 interacting-domain death agonist; BLNK, B cell linker; CASP8, caspase 8; CD99 cluster of differentiation 99; CLEC6A, C-type lectin domain containing 6A; CR1, complement C3b/C4b receptor 1; DAMP, damage-associated molecular pattern; DUSP4, dual specificity phosphatase 4; DUSP6, dual specificity phosphatase 6; G6PD, glucose-6-phosphate dehydrogenase; HAVCR2, hepatitis A virus cellular receptor 2; HLA-DRB4, major histocompatibility complex class II DR beta 4; HMGB1, high mobility group box 1 protein; ICOS, inducible T cell costimulatory; IL12RB, interleukin 12 receptor subunit beta; IL18R1, interleukin 18 receptor 1; IRF5, interferon regulatory factor 5; LILRB2, leukocyte immunoglobulin like receptor B2; MHC, major histocompatibility complex; POU2AF1, POU class 2 homeobox associating factor 1; TCR, T cell receptor; TLR4, toll-like receptor 4; ZAP70, zeta chain of T cell receptor associated protein kinase 70.\u003c/p\u003e","description":"","filename":"SupplementaryFigure8.pptx","url":"https://assets-eu.researchsquare.com/files/rs-3845290/v1/e32da03b84544c8d19a83c9c.pptx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Age-related loss of intestinal barrier integrity plays an integral role in Thymic involution and T cell ageing","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eThe epithelium of the gastrointestinal tract represents the largest mucosal lining in the body that effectively limits the permeation of luminal microorganisms, antigens and toxins through its paracellular space, a process that is regulated by intercellular tight junctions [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Advancing age is accompanied by physiological changes to the intestine, including mucus layer thinning and remodelling of intestinal epithelial tight junction proteins, such as zonulin, which contribute towards the breakdown of intestinal barrier function in aged worms, flies, fish, rodents, non-human primates and humans [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Impaired intestinal barrier integrity in aged hosts permits commensal bacteria and their products, such as LPS, from the gut lumen into the bloodstream (referred to as a leaky gut) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Age-related intestinal barrier dysfunction is closely linked to the progressive deterioration of systemic health and the gradual appearance of metabolic defects and behavioural impairments [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Moreover, recent evidence from animal studies indicates that it is a major contributor to low-grade systemic inflammation, termed inflammaging [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], and possibly a driver of age-related diseases [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Human intestinal barrier dysfunction, determined by elevated circulating lipopolysaccharide-binding protein (LBP) levels, is also associated with impaired physical function and inflammaging in healthy aged adults [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Therefore, it remains of vital interest that we develop a clear understanding of the relevance of intestinal barrier dysfunction in human ageing, which is still poorly understood.\u003c/p\u003e \u003cp\u003eConcurrently with changes to intestinal homeostasis, ageing is accompanied by remodelling of the immune system that attenuates the host\u0026rsquo;s ability to mount robust immune responses, resulting in an immunocompromised state, termed immunesenescence. Age-related immune dysfunction contributes towards increased susceptibility to poor outcomes during bacterial and viral infections and increases the risk of autoimmunity and poor response to vaccination [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Recently, immunesenescence has been recognised as a contributing factor towards the ageing of non-lymphoid organs, such as skeletal muscle and recognised as a potential driver of an aged phenotype and increasing the risk of morbidity and mortality in older adults [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. One of the most striking features of immune ageing is the progressive shrinkage (involution) of the thymus that is characterised by the loss of thymic epithelial cells (TECs), expansion of perivascular spaces, increased thymic adiposity and the accumulation of senescent cells; together resulting in a loss of functional spaces for the development of thymocytes [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In addition to thymic architectural disorganisation, alterations in the thymic stromal cell microenvironment, including elevated levels of thymopoiesis-suppressing cytokines (e.g. IL6 and tumour necrosis factor alpha (TNFα) also occur with age [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Collectively this compromises the process of thymopoiesis and result in a reduced thymic output of na\u0026iuml;ve T cells and the homeostatic expansion of peripheral memory T cell subsets [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Further, chronic lifelong antigenic stimulation leads to the accumulation of senescent T cells in the periphery [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], which impair tissue immunosurveillance and drive a state of prolonged basal inflammation in aged individuals, termed inflammageing. This is further exacerbated by the age-related expansion of pro-inflammatory Th17 cells and anti-inflammatory regulatory T cells (Tregs) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite these interesting findings, the relationship between intestinal barrier dysfunction and immune ageing is poorly understood. Herein we report that intestinal membrane permeability increases with age in humans and is accompanied by enhanced systemic microbial translocation that contributes to the lifelong antigenic burden, driving a reduction in na\u0026iuml;ve T cell thymic output and an accumulation of terminally differentiated, senescent T cells in the periphery. The emergence of these hallmarks of T cell ageing hinders the ability of these cells to fight invading pathogens and enhances their ability to produce pro-inflammatory cytokines, which ultimately contribute to the inflammatory state of the aged host. Further, we demonstrate that aged germ-free mice, which do not exhibit age-related intestinal barrier dysfunction, are protected from the accumulation of microbial products in the thymus and maintain their thymic architecture. Together, these findings provide novel evidence of a causal relationship between intestinal barrier dysfunction and T cell ageing.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eAgeing is accompanied by increased microbial translocation\u003c/h2\u003e \u003cp\u003eTwenty-seven healthy young individuals (age range 19\u0026ndash;37 years) and 55 community-dwelling healthy old individuals (age range 63\u0026ndash;84 years) were recruited into this study, from whom blood samples were collected to assess microbial translocation and immune cell profiles (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Occludin is an integral tight junction protein located on the basolateral membrane of intestinal epithelial cells, whose presence in the circulation is a biomarker of increased intestinal membrane permeability [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In this study, we found a significant age-associated increase in circulating occludin levels (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Serum LBP is a surrogate biomarker of intestinal permeability and microbial translocation [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. We observed a trend towards elevated circulating LBP levels with age; however, this did not reach statistical significance (p\u0026thinsp;=\u0026thinsp;0.12) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Soluble CD14 (sCD14) is shed from the surface of antigen-stimulated monocytes and was measured as a reactive biomarker of microbial translocation and subsequent monocyte activation in this study [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. On assessment, we found a significant age-related increase in circulating sCD14 levels (p\u0026thinsp;=\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). Interestingly, elevated circulating LBP levels were linked to low dietary fibre intake (R = -0.33, p\u0026thinsp;=\u0026thinsp;0.04) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe next investigated potential associations between markers of microbial translocation and potential drivers of increased gut permeability, including age, sex, body mass index (BMI), diet, physical activity levels, sedentary behaviour, sleep quality and mental health (Supplementary Table\u0026nbsp;1). Upon assessment of the faecal microbiome, older adults displaying high microbial translocation had lower relative abundances of \u003cem\u003eBifidobacterium\u003c/em\u003e (p\u0026thinsp;=\u0026thinsp;0.0002), \u003cem\u003eBlautia\u003c/em\u003e (p\u0026thinsp;=\u0026thinsp;0.002) and \u003cem\u003eLachnospiraceae\u003c/em\u003e (p\u0026thinsp;=\u0026thinsp;0.01) and greater relative abundances of \u003cem\u003eChristensenellaceae R-7 group\u003c/em\u003e (p\u0026thinsp;=\u0026thinsp;0.02) and \u003cem\u003eRuminococcaceae\u003c/em\u003e (p\u0026thinsp;=\u0026thinsp;0.03) in stool compared to young adults (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, Supplementary Table\u0026nbsp;2). Low levels of the short-chain fatty acid butyrate (p\u0026thinsp;=\u0026thinsp;0.02), propionate (p\u0026thinsp;=\u0026thinsp;0.03) and the secondary bile acid glycodeoxycholic acid (GDCA) (R = -0.33, p\u0026thinsp;=\u0026thinsp;0.04) in stool were also strongly linked with elevated circulating levels of occludin in older adults (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eH and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eI, respectively).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFurthermore, were split our older adults\u0026rsquo; cohort into two sub-groups: low Microbial Translocation (MT) old (n\u0026thinsp;=\u0026thinsp;24, age range 60\u0026ndash;88 years) and high MT old (n\u0026thinsp;=\u0026thinsp;31, age range 63\u0026ndash;82 years) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Low MT (similar levels to healthy young individuals) was defined as circulating occludin levels\u0026thinsp;\u0026le;\u0026thinsp;4.5 ng/ml, which was the mean value observed in young participants. High MT was defined as circulating occludin levels\u0026thinsp;\u0026gt;\u0026thinsp;4.5 ng/ml. Demographic characteristics for each subgroup are shown in Table\u0026nbsp;1.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eT cell immunesenescence and microbial translocation\u003c/h2\u003e \u003cp\u003eIn this study, we hypothesised that an increase in circulating microbial products would perpetuate repeated T cell activation and, the subsequent differentiation of T cells and induction of replicative senescence, all recognised as features of T cell ageing. Therefore, we reasoned that older adults with lower levels of intestinal barrier leakage would exhibit fewer features of T cell ageing.\u003c/p\u003e \u003cp\u003ePrevious studies have reported an age-related decline in peripheral PTK7\u003csup\u003e+\u0026thinsp;ve\u003c/sup\u003eCD45RA\u003csup\u003e+ve\u003c/sup\u003e recent thymic emigrants (RTEs), which are antigenically na\u0026iuml;ve CD4 T cells that egress from the thymus into the periphery following intrathymic development and thus a surrogate marker for human thymic output [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Interestingly, we report that there is a significant reduction in the proportion of circulating RTEs in the presence of high microbial translocation in older adults (p\u0026thinsp;=\u0026thinsp;0.002) compared to young participants, but not in those with low MT (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Further, older participants with high MT presented with greater proportions of central memory CD8 T cells (p\u0026thinsp;=\u0026thinsp;0.03), effector memory CD4 and CD8 T cells (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 for both) (Supplementary Tables\u0026nbsp;3 and 4) and terminally differentiated effector memory re-expressing RA (EMRA) CD4 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and CD8 T cells (p\u0026thinsp;=\u0026thinsp;0.0005; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB and C), compared to low MT young individuals\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCD69 is an early activation marker expressed by activated lymphocytes [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Here, we observed an age-associated increase in the percentage of CD69\u003csup\u003e+\u0026thinsp;ve\u003c/sup\u003e CD8 T cells (p\u0026thinsp;=\u0026thinsp;0.01), which was even greater in older adults displaying high MT (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD); suggesting that translocated bacterial might induce polyclonal T cell activation.\u003c/p\u003e \u003cp\u003eAdvancing age is accompanied by the loss of CD28 and the gain of CD57 expression on the surface of CD8 T cells (known markers of T cell senescence), which have low proliferative capacity and are highly pro-inflammatory [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In this study, we observed a significant increase in CD28\u003csup\u003e\u0026minus;\u0026thinsp;ve\u003c/sup\u003eCD57\u003csup\u003e+ve\u003c/sup\u003e senescent CD8 T cells in older adults with high MT compared to old adults with low MT (p\u0026thinsp;=\u0026thinsp;0.04) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE and F). A similar increase in CD28\u003csup\u003e\u0026minus;\u0026thinsp;ve\u003c/sup\u003eCD57\u003csup\u003e+ve\u003c/sup\u003e senescent CD4 T cells was also seen in older adults displaying high MT relative to young adults (p\u0026thinsp;=\u0026thinsp;0.02) (Supplementary Table\u0026nbsp;2). Another hallmark of T cell immunesenescence is an increase in programmed cell death-1 (PD1)\u003csup\u003e+ve\u003c/sup\u003e exhausted CD8 T cells with reduced cytotoxic capability and reduced proliferative potential [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Older adults with low MT possessed significantly greater percentages of PD1\u003csup\u003e+\u0026thinsp;ve\u003c/sup\u003e CD8 T cells compared to young adults (p\u0026thinsp;=\u0026thinsp;0.04), but not older donors with high MT (p\u0026thinsp;=\u0026thinsp;0.6) (Supplementary Table\u0026nbsp;4).\u003c/p\u003e \u003cp\u003eCD4 T helper cells are important mediators of inflammatory responses, secreting effector cytokines upon activation. RORγ\u003csup\u003e+ve\u003c/sup\u003e Th17 cells, defined by their ability to secrete IL17, are pro-inflammatory and have been associated with several autoimmune disorders [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Upon examination of CD4 T helper cell subsets, we observed comparable proportions of RORγ\u003csup\u003e+ve\u003c/sup\u003e Th17 cells (p\u0026thinsp;=\u0026thinsp;0.94) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA) between the three participant groups, but older adults with increased microbial translocation had higher intracellular IL17 expression levels than young and old participants displaying low MT (p\u0026thinsp;=\u0026thinsp;0.04 for both) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB; gating strategy Supplementary Fig.\u0026nbsp;1).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCD25\u003csup\u003e+\u0026thinsp;ve\u003c/sup\u003eFoxp3\u003csup\u003e+ve\u003c/sup\u003e Tregs are another subpopulation of CD4 T helper cells that maintain homeostasis and immune tolerance through multiple mechanisms, one of them being secretion of the anti-inflammatory cytokine IL10 [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In this study, the peripheral frequency of CD25\u003csup\u003e+\u0026thinsp;ve\u003c/sup\u003eFoxp3\u003csup\u003e+ve\u003c/sup\u003e Tregs was significantly higher in high MT older adults compared to young and old participants with low MT (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 and p\u0026thinsp;=\u0026thinsp;0.01, respectively) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). However, the proportion of anti-inflammatory IL10-producing Tregs (p\u0026thinsp;=\u0026thinsp;0.21) and intracellular IL10 expression levels (p\u0026thinsp;=\u0026thinsp;0.6) were similar between the three groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD; Supplementary Table\u0026nbsp;3). Treg expansion is thought to occur as a compensatory mechanism against a pro-inflammatory cytokine milieu, as is the case with advancing age. Further, peripheral LBP levels were positively associated with the accumulation of IL10-expressing Tregs (R\u0026thinsp;=\u0026thinsp;0.57, p\u0026thinsp;=\u0026thinsp;0.0003) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE) in older people.\u003c/p\u003e \u003cp\u003eOn assessing the impact of microbial translocation on serum cytokine levels, circulating concentrations of IL1β, IL4, IL6, IL15, TNFα, CRP, IFNγ, CXCL9 and GM-CSF were unaltered by advancing age and the presence of intestinal barrier dysfunction (Supplementary Table\u0026nbsp;5). Although the peripheral frequency of Th17 cells and intracellular IL17 levels were comparable between groups, older adults with high MT displayed lower systemic levels of IL17 compared to other participants with low MT (p\u0026thinsp;=\u0026thinsp;0.02) (Supplementary Table\u0026nbsp;5)[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eLinks between microbial translocation and the IMM-AGE score\u003c/h2\u003e \u003cp\u003eThe IMM-AGE score is a recently developed metric that describes an individual\u0026rsquo;s cellular immune profile about their chronological age and has been recognised as a reliable predictor of all-cause mortality in older adults [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Here, we used a modified version that requires only eight T cell subsets: total T cells, na\u0026iuml;ve CD4 T cells, effector memory CD4 and CD8 T cells, EMRA CD8 T cells, CD28\u003csup\u003e\u0026minus;\u0026thinsp;ve\u003c/sup\u003e CD8 T cells, CD57\u003csup\u003e+\u0026thinsp;ve\u003c/sup\u003e CD8 T cells and Tregs [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. IMM-AGE scores were significantly higher in older adults relative to young controls (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF). When investigating potential associations between IMM-AGE scores and markers of gut permeability and microbial translocation, we found that high IMM-AGE scores were positively correlated with circulating LBP (R\u0026thinsp;=\u0026thinsp;0.28, p\u0026thinsp;=\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eG).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eTranscriptome signatures of older adults with low and high microbial translocation\u003c/h2\u003e \u003cp\u003eTo identify molecular signalling pathways in peripheral immune cells that might contribute towards enhanced immune ageing in older adults with high microbial translocation, we used the NanoString nCounter\u003csup\u003e\u0026reg;\u003c/sup\u003e gene expression assay. This allowed for the detection of 770 genes in peripheral blood mononuclear cells (PBMCs) from healthy young individuals displaying low MT (n\u0026thinsp;=\u0026thinsp;6), healthy old individuals with low MT (n\u0026thinsp;=\u0026thinsp;6) and healthy old individuals displaying high MT (n\u0026thinsp;=\u0026thinsp;6).\u003c/p\u003e \u003cp\u003eIn total, 49 genes significantly differed between low MT young, low MT old and high MT old participants (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Upon comparing expression levels between low MT young adults and older adults with low MT, we observed a significant downregulation in the expression of seven genes controlling cell adhesion/migration (ALCAM, p\u0026thinsp;=\u0026thinsp;0.05), apoptosis (BID, p\u0026thinsp;=\u0026thinsp;0.04), immune suppression (LRRN3, p\u0026thinsp;=\u0026thinsp;0.05) and immune-mediated pathology (NT5E, p\u0026thinsp;=\u0026thinsp;0.04; TNFRSF13B, p\u0026thinsp;=\u0026thinsp;0.05) (Supplementary Table\u0026nbsp;6). We also observed reduced expression of complement system components (CR1, CR2), irrespective of microbial translocation status (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), that play an important role in immunomodulation and defence against pathogens [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFurthermore, 27 genes were differentially expressed between young individuals and high MT older adults (Supplementary Table\u0026nbsp;7). For instance, we observed downregulated expression of autophagy-related genes (ATG7, p\u0026thinsp;=\u0026thinsp;0.05; LAMP, p\u0026thinsp;=\u0026thinsp;0.03) and DNA repair machinery (ATM, p\u0026thinsp;=\u0026thinsp;0.05; G6PD, p\u0026thinsp;=\u0026thinsp;0.03) along with an upregulation of pro-apoptotic molecules (CASP3, p\u0026thinsp;=\u0026thinsp;0.05; BID, p\u0026thinsp;=\u0026thinsp;0.04) only in aged individuals with high MT (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Importantly, we saw increased expression of co-stimulatory molecules expressed on activated T cells (ICOS, p\u0026thinsp;=\u0026thinsp;0.05), cellular senescence markers (gain of KLRG1, p\u0026thinsp;=\u0026thinsp;0.04; loss of CD28, p\u0026thinsp;=\u0026thinsp;0.05) and accelerators of cell cycle arrest (TXNIP, p\u0026thinsp;=\u0026thinsp;0.05) only in older adults with high MT (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). It was previously reported that p53 inhibits mitogen-activated protein kinase (MAPK) activity by inducing phosphatases, such as the dual-specificity phosphatases (DUSPs) [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Supporting this, we observed a downregulation of MAPK3 (p\u0026thinsp;=\u0026thinsp;0.04) and upregulated expression of DUSP4 (p\u0026thinsp;=\u0026thinsp;0.04) and DUSP6 (p\u0026thinsp;=\u0026thinsp;0.05) in older adults with high MT relative to young and aged individuals with low MT (Supplementary Table\u0026nbsp;8). Additionally, older participants with high MT displayed increased expression of inflammatory molecules (HMBG1, p\u0026thinsp;=\u0026thinsp;0.01) and T cell ageing markers (RORA, p\u0026thinsp;=\u0026thinsp;0.03) compared to low MT older adults (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGene enrichment analysis revealed that the top enriched terms in high MT olds were the intrinsic pathways for apoptosis (BCL2, BID and CD99), the cytochrome c-mediated apoptotic response (CASP3 and CASP8), cellular senescence (CD28, DUSP4, DUSP6, KLRG1, MAPK3 and TXNIP), suggesting that these pathways might be involved in driving T cell immunesenescence during age-related intestinal barrier dysfunction.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eThymic tissue architecture, adiposity and senescence in aged germ-free mice protected from intestinal permeability\u003c/h2\u003e \u003cp\u003eTo determine whether an age-related increase in circulating microbial products drives thymic involution, we used an aged germ-free mouse model that was previously shown to be protected from increased gut permeability [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. We hypothesised that these aged germ-free mice (20\u0026ndash;22 months) would also be protected from key features of thymic involution (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). The FITC-dextran assay is a well-established method for measuring \u003cem\u003ein vivo\u003c/em\u003e intestinal permeability [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In this study, we confirmed that aged wild-type mice display enhanced translocation of FITC-dextran into the blood compared to young wild-type mice (p\u0026thinsp;=\u0026thinsp;0.004), whereas aged germ-free mice maintained intestinal barrier function (p\u0026thinsp;=\u0026thinsp;0.14) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). Whilst there was no gross difference in intestinal architecture, we found that aged wild-type mice exhibit decreased expression of the tight junction protein occludin compared to young wild-type and aged germ-free mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). Additionally, aged germ-free mice that were protected from intestinal membrane permeability displayed lower relative mRNA expression levels of \u003cem\u003eEscherichia coli\u003c/em\u003e in the thymus compared to aged wild-type mice (p\u0026thinsp;=\u0026thinsp;0.33), which exhibited increased thymic \u003cem\u003eE. coli\u003c/em\u003e mRNA expression levels relative to young mice (p\u0026thinsp;=\u0026thinsp;0.1) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAge-related thymic involution disrupts the structural integrity and cellular architecture of the thymus, resulting in the shrinkage of medullary regions and impaired thymopoiesis [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Additionally, the corticomedullary junction, which separates the cortex and medulla and serves as a site for progenitor (CD4\u003csup\u003e\u0026minus;\u0026thinsp;ve\u003c/sup\u003eCD8\u003csup\u003e\u0026minus;ve\u003c/sup\u003e) immigration and na\u0026iuml;ve T cell emigration [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], becomes disorganised with age and there is increased thymic adiposity [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In this study, the morphological analysis showed medullary shrinkage [Figure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE], disruption of the corticomedullary junction and the appearance of vacuoles in aged wild-type mouse thymuses, but not in those from aged germ-free mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF). Oil-red O staining, which is used for the enumeration of lipid-laden tissues, also revealed an increase in the size and number of lipid deposits in the cortex and medullary regions of thymuses of aged wild-type mice (p\u0026thinsp;=\u0026thinsp;0.01) compared to young mice, whereas aged germ-free mice were protected from lipid accumulation (p\u0026thinsp;=\u0026thinsp;0.06) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eG and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eH).\u003c/p\u003e \u003cp\u003eStromal components of the thymus include specialized TECs that provide signals that induce the development and functional maturation of T lymphocytes. However, the aged thymus displays an enlargement of non-cellular perivascular spaces and TEC reductions [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Although perivascular spaces enable easy trafficking of cells and soluble proteins through the medulla, an increase in non-cellular space permits the infiltration of pro-inflammatory adipocytes and circulating senescent cells in the aged thymus [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Morphological analysis revealed that CD205\u003csup\u003e+\u0026thinsp;ve\u003c/sup\u003e cortical and ERTR5\u003csup\u003e+\u0026thinsp;ve\u003c/sup\u003e medullary epithelial regions shrink and become less dense with age followed by the appearance of epithelial-free areas in aged wild-type mouse thymuses, though this did not occur in aged germ-free mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA-C).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eNext, we assessed the presence of senescent cells in the thymus of aged wild-type and germ-free mice to elucidate a potential mechanism underpinning the changes in thymus architecture. Lamin B1 is a structural protein that supports TEC development and maintains thymic architecture [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], and reduced lamin B1 expression is a marker of cellular senescence and thymic involution [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Aged wild-type mice exhibited tissue disorganisation and fewer lamin B1-expressing cells in the cortex compared to young mice, but these ageing features were not present in aged germ-free mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD). Further, we observed lower lamin B1 expression levels (mean fluorescent staining intensity (MFI)) in the cortex of aged wild-type mice (p\u0026thinsp;=\u0026thinsp;0.04), but not in aged germ-free mice (p\u0026thinsp;=\u0026thinsp;0.57), compared to young wild-type mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE). In contrast, lamin B1 expression levels (MFI) in the medulla were unaffected by ageing (p\u0026thinsp;=\u0026thinsp;0.22) or microbiota composition (p\u0026thinsp;\u0026ge;\u0026thinsp;0.1) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eF). Transcriptional profiling of aged wild-type mouse thymuses revealed increased mRNA expression levels of the cellular senescence marker p16 relative to young mice (p\u0026thinsp;=\u0026thinsp;0.01), which were even lower in aged germ-free mice (p\u0026thinsp;=\u0026thinsp;0.04) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eG).\u003c/p\u003e \u003cp\u003eElevated IL6 levels found in the thymuses of aged mice are associated with poorer thymic function and involution [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. However, aged germ-free mice were previously shown to be protected from inflammageing, lacking high circulating levels of IL6 [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Here we confirm that compared to young mice, aged wild-type mice exhibit increased IL6 mRNA expression levels in the thymus (p\u0026thinsp;=\u0026thinsp;0.05), which were lower in aged germ-free thymuses (p\u0026thinsp;=\u0026thinsp;0.55) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eH). Compared to young mice, mRNA expression levels of the apoptosis-promoting gene BCL2 associated X (BAX) were also significantly higher in aged wild-type mice (p\u0026thinsp;=\u0026thinsp;0.0001) but not in aged germ-free mice (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eI), suggesting a possible mechanism by which increased apoptosis drives TEC loss with age.\u003c/p\u003e \u003cp\u003eLastly, we examined the distribution of CD4 and CD8 expressing thymocytes in the thymus, where CD4\u003csup\u003e+\u003c/sup\u003eCD8\u003csup\u003e+\u003c/sup\u003e cells would typically reside in cortical areas while more mature CD4\u003csup\u003e+\u003c/sup\u003eCD8\u003csup\u003e\u0026minus;\u003c/sup\u003e and CD4\u003csup\u003e\u0026minus;\u003c/sup\u003eCD8\u003csup\u003e+\u003c/sup\u003e would reside in medullary areas. While CD4\u003csup\u003e+\u003c/sup\u003eCD8\u003csup\u003e+\u003c/sup\u003e and single positive CD4\u003csup\u003e+\u003c/sup\u003e and CD8\u003csup\u003e+\u003c/sup\u003e thymocytes were distributed normally within thymus tissue, we found that aged wild-type mice display a loss of CD4\u003csup\u003e+\u003c/sup\u003eCD8\u003csup\u003e+\u003c/sup\u003e cortical regions in the thymus (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA). However, the proportion of CD8-expressing thymocytes is higher in aged germ-free mice compared to aged wild-types in medullary regions (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eC). A similar decline in the proportion of CD4-expressing thymocytes was also observed in the medulla with age, though aged germ-free mice displayed a higher proportion of CD4\u003csup\u003e+\u0026thinsp;ve\u003c/sup\u003e areas (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eE). In conclusion, our data demonstrate the presence of bacterial products within the aged thymus, possibly as the result of increased intestinal membrane permeability and subsequent systemic microbial translocation, that contributes towards a disrupted thymic architecture, build-up of thymic inflammation and the accumulation of senescent cells; culminating in an altered thymic microenvironment for T cell development. (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIt is becoming increasingly clear that impaired intestinal barrier integrity is a major pathophysiological feature of ageing that contributes to the decline of organismal health. Whilst recent publications have demonstrated a significant role for microbial translocation in driving chronic immune cell activation and inflammageing [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], the potential links between age-related intestinal barrier dysfunction and immunesenescence are still largely unknown. In this study, we demonstrate that older adults with higher levels of intestinal barrier leakage are more likely to display hallmarks of T cell ageing, contributing to high IMM-AGE scores in these individuals. Importantly, aged germ-free mice that display reduced intestinal membrane permeability and bacterial translocation preserve their thymic architecture and have an unaltered thymic microenvironment, possibly driving high thymic output in old age (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). These novel findings take us a step further in understanding the age-related changes in the microbiome-immune axis and provide evidence for therapeutic restoration of intestinal barrier homeostasis to preserve immune function in aged individuals.\u003c/p\u003e \u003cp\u003eTo the best of our knowledge, this study is the first to report an age-associated increase in intestinal membrane permeability and systemic microbial translocation in healthy aged individuals in line with findings from non-human primate studies [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Dietary components play an integral role in modulating intestinal barrier integrity. For instance, there is mounting evidence that excessive consumption of dietary fats enhances intestinal membrane permeability [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], predisposing individuals to local and systemic inflammation. Interestingly, high adherence to the MedDiet and consumption of a high-quality diet were inversely correlated with intestinal barrier dysfunction in this study, possibly due to the anti-inflammatory and health-promoting properties of dietary fibre [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. This is supported by a study that reported improvements in intestinal barrier integrity in middle-aged women following high adherence to the MedDiet [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Furthermore, high intake of dietary fibre and omega-3 polyunsaturated fatty acids (both enriched in MedDiet foods like fruits, vegetables, fish and nuts) has been shown to restore gut barrier function in non-obese diabetic mice, thereby restoring intestinal immune homeostasis (i.e. reduced gut inflammation, expansion of IL10-producing Tregs, decline in pro-inflammatory Th17 cells) [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. However, these beneficial effects on the immune system have yet to be confirmed in aged humans.\u003c/p\u003e \u003cp\u003eChanges in gut microbiota composition with age are also closely linked with the onset of intestinal barrier leakage in mice [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Accordingly, intestinal barrier leakage was correlated with higher relative abundances of pro-inflammatory \u003cem\u003eEscherichia-Shigella\u003c/em\u003e, \u003cem\u003ePeptostreptococcaceae\u003c/em\u003e and \u003cem\u003eParaprevotella\u003c/em\u003e in stool. On the other hand, robust intestinal barrier integrity was positively associated with high faecal levels of propionate and GDCA, both of which exert immunomodulatory and anti-inflammatory effects on the immune system. These results suggest a possible role of age-related microbial dysbiosis in promoting increased gut permeability through inflammation-induced epithelial damage.\u003c/p\u003e \u003cp\u003eIn this study, we propose that age-related microbial translocation induces a state of persistent T-cell activation. These results are supported by an earlier study that reported loss of gut mucosa homeostasis and increased bacterial translocation in HIV patients, resulting in chronic immune system activation and systemic inflammation [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Therefore, we hypothesise that persistent stimulation caused by microbial translocation promotes the terminal differentiation of T cells and induces cellular senescence in aged T cells, together accelerating immune ageing. These observations are in line with those from another study reporting close links between microbial translocation and memory T cell expansion in adult mice [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Furthermore, \u003cem\u003ein vitro\u003c/em\u003e studies have confirmed that gut microbial secretory factors induce cellular senescence via the activation of cell cycle inhibitors (p16\u003csup\u003eINK4a\u003c/sup\u003e, p21\u003csup\u003eWAF1\u003c/sup\u003e and p53) and the DNA damage response, resulting in the development of a senescence-associated secretory phenotype (SASP) [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn agreement with other ageing studies [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e], we observed an age-related increase in the percentage of Tregs that was correlated with increased gut permeability. There is emerging evidence of a potential link between the expansion of senescent T cells and Tregs, with studies demonstrating that Tregs trigger DNA damage in effector T cells via metabolic competition during cross-talk, resulting in cellular senescence and functional exhaustion [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Thus, we propose that increased microbe recognition caused by enhanced bacterial translocation might contribute to dysregulated ROS production and altered glucose metabolism in aged Tregs, promoting aberrant Treg interactions and senescent cell accumulation.\u003c/p\u003e \u003cp\u003eConsistent with the findings discussed above, we identified several hallmarks of ageing in circulating immune cells, including upregulation of pro-inflammatory signalling markers (HMBG1), defective autophagy processes (ATG7 and LAMP), reduced DNA damage repair (ATM), increased cellular senescence (gain of KLRG1 and loss of CD28), enhanced apoptosis (BCL2, CASP3 and CASP8), loss of proliferation regulators (DUSP4 and DUSP6) and upregulation of cell-cycle arrest regulators (TXNIP), that were only present in older adults with high microbial translocation. These results are in line with those from a study that demonstrated that microbial products disrupt autophagosome formation and trigger mitochondrial dysfunction by interfering with Rab1A signalling and reducing mitochondrial coupling [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eT cells are continuously produced by the thymus throughout life. However, the thymus undergoes accelerated atrophy with advancing age, resulting in a reduced thymic output of na\u0026iuml;ve T cells that limits the host\u0026rsquo;s ability to respond to neoantigens [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. In this study, we report a significant age-related loss of RTEs in older adults with high MT, supporting our hypothesis that circulating bacterial products have deleterious effects on thymopoiesis. To confirm that microbial products contribute towards age-related thymic involution, we used aged germ-free mice which are protected from loss of intestinal barrier function. Here, we demonstrate for the first time that ageing is accompanied by increased thymic translocation of \u003cem\u003eE\u003c/em\u003e. \u003cem\u003ecoli\u003c/em\u003e in wild-type mice but not in germ-free mice. Importantly, hallmarks of thymic involution, including the loss of functional thymic niches due to the depletion of TECs, adipocyte infiltration and senescent cell accumulation, were less pronounced in aged germ-free mice.\u003c/p\u003e \u003cp\u003e \u003cem\u003eIn vitro\u003c/em\u003e analysis reveals that LPS, found on the surface of gram-negative bacteria such as \u003cem\u003eE\u003c/em\u003e. \u003cem\u003ecoli\u003c/em\u003e, promotes the accumulation of lipid droplets in endothelial cells [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e], induces cellular senescence and enhances the SASP of senescent cells [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Thus, elevated circulating levels of microbes and microbial products, like LPS, could promote increased thymic adiposity and cellular senescence in aged hosts. Accumulation of senescent cells and adipocytes during ageing is believed to hinder thymic function through increased secretion of pro-inflammatory cytokines, such as IL6 and TNFα [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. In this study, ageing was accompanied by increased thymic expression of IL6 in wild-type mice. However, aged germ-free mice exhibited comparable IL6 expression levels to those in young wild-type mice, indicating a role for microbial translocation in the age-dependent upregulation of thymopoiesis-suppressing cytokines. Indeed, LPS treatment and \u003cem\u003eE\u003c/em\u003e. \u003cem\u003ecoli\u003c/em\u003e enterotoxin cause thymic atrophy, leading to the loss of single positive (CD4\u003csup\u003e\u0026minus;\u0026thinsp;ve\u003c/sup\u003eCD8\u003csup\u003e+ve\u003c/sup\u003e and CD4\u003csup\u003e+\u0026thinsp;ve\u003c/sup\u003eCD8\u003csup\u003e\u0026minus;ve\u003c/sup\u003e) thymocytes as well as double positive (CD4\u003csup\u003e+\u0026thinsp;ve\u003c/sup\u003eCD8\u003csup\u003e+ve\u003c/sup\u003e) and double negative (CD4\u003csup\u003e\u0026minus;\u0026thinsp;ve\u003c/sup\u003eCD8\u003csup\u003e\u0026minus;ve\u003c/sup\u003e) thymocytes [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. One mechanism by which this occurs is through LPS-induced apoptosis of thymocytes [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. Supporting this, thymic expression of the apoptotic gene BAX increased with age in wild-type mice, whereas aged germ-free mice were unaffected.\u003c/p\u003e \u003cp\u003eAlthough therapeutic manipulation of the gut microbiota might improve health in aged hosts, it remains unclear how restoring intestinal barrier function possibly by targeting microbiome dysbiosis could reverse features of immune ageing. For instance, studies have reported links between microbial composition, intestinal membrane permeability and circulating cytokine levels in aged hosts, but have not investigated their impact on immune health [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Our data demonstrates that transferring healthy gut microbiota into \u003cem\u003eClostridium difficile\u003c/em\u003e infected older adults is sufficient to improve intestinal barrier integrity. Moreover, faecal microbiota transplantation promotes the expansion of peripheral na\u0026iuml;ve T cells and reduces the senescent T cell burden in recipients, suggesting potential anti-immunesenescence effects [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Microbial dysbiosis in HIV patients, characterised by the loss of beneficial \u003cem\u003eBifidobacterium\u003c/em\u003e and the overrepresentation of \u003cem\u003eClostridium\u003c/em\u003e clusters, is also alleviated in response to probiotic administration, resulting in reduced microbial translocation and improved immune cell function [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. The appearance of opportunistic microbial communities in the aged gut is related to dietary changes, such as low consumption of fibre-rich fruits and vegetables and increased consumption of meats and processed foods [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Moreover, studies have reported rebalancing of the gut flora, reduced systemic inflammation and improved health status in older adults who consume a MedDiet [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Therefore, high adherence to a MedDiet rich in fibre, polyunsaturated fats, minerals and vitamins could strengthen gut barrier function and improve immune function in the elderly.\u003c/p\u003e \u003cp\u003eThis study has a few limitations, the first being that the exact mechanisms linking intestinal membrane permeability to immune ageing remain to be fully elucidated. Secondly, although we report an increase in microbial translocation with age, we do not know the nature of these microbial products. Thus, further work is required to determine the impact of individual bacterial products on immune ageing.\u003c/p\u003e \u003cp\u003eLike all research studies, ours has a few limitations that should be noted. Firstly, our use of strict inclusion criteria excluded older adults with any underlying comorbidities, immune-mediated diseases and gastrointestinal disorders. Our cohort of older adults, who were interested in biogerontology research and keen to partake in our study, are all extremely healthy, consume a high-quality diet rich in dietary fibres and engage in regular physical activity (only one individual was sedentary). Unfortunately, this might not be a true representation of the ageing population, which is considered to be malnourished, largely sedentary and ridden with multimorbidity. However, this strategy dissected the intrinsic effects of ageing and highlighted the novel interactions that we observed are features of intestinal barrier dysfunction and T-cell ageing. However, in a current ongoing study, we are addressing this by recruiting older individuals with underlying comorbidities to identify immune-intestinal barrier signatures and interactions that differ between individuals on healthy vs unhealthy ageing trajectories. Another key limitation is that our results are based on a cohort of Caucasian participants, and we would like to validate our findings in a larger study (enabling us to dissect sex differences) conducted on older adults with more ethically and geographically diverse backgrounds.\u003c/p\u003e \u003cp\u003eIn conclusion, age-related thymic involution is a known hallmark of T cell ageing that contributes significantly toward immunesenescence. Although we have made progress in understanding the molecular mechanisms that instigate thymic involution, the detailed molecular regulation network is still unclear. Nevertheless, we suggest that systemic microbial translocation due to increased intestinal barrier leakage contributes towards a reduced thymic output and the emergence of T cell ageing features Thus, our findings advocate for targeting intestinal barrier integrity as a novel strategy for promoting thymic rejuvenation and combating T cell ageing in the elderly. Exploiting the restoration ability of these targets provides new opportunities to cope with lagging health span developments of individualised dietary, probiotic and postbiotic interventions.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eParticipants and study design\u003c/h2\u003e \u003cp\u003eThis is an observational, cross-sectional study in healthy young (aged 18\u0026ndash;37 years) and 55 healthy old (aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years) adults, the latter of whom were enrolled from the Birmingham 1000 Elders group, were recruited into this study from November 2019 to December 2020. The exclusion criteria for healthy participants included self-reported infections, comorbidities (e.g. chronic inflammatory/autoimmune conditions and cancer), use of immunosuppressants, antibiotic usage in the past two months, hospitalisation in the past three months and/or having travelled outside of the UK in the month leading up to recruitment. Written informed consent was obtained from all eligible volunteers prior to sampling and additional participant demographics, including height, weight, BMI, physical activity levels (hours of TV watched and stairs climbed), sleep quality, mental health status (anxiety and depression) and diet, were gathered via self-assessed questionnaires (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Blood samples (30 ml) were collected from all participants between 9:00\u0026ndash;11:00am in BD vacutainers containing lithium heparin. Complete blood cell counts were obtained using a Sysmex XN-1000 automated haematology analyser (Sysmex).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eIsolation and freezing of peripheral blood mononuclear cells (PBMCs)\u003c/h2\u003e \u003cp\u003ePBMCs were isolated from whole blood samples via density gradient centrifugation using Ficoll-Paque\u0026trade; PLUS density gradient media (GE Healthcare). Isolated PBMCs were frozen by resuspending the cells in freezing medium consisting of 10% dimethyl sulfoxide (Sigma Aldrich) in heat-inactivated fetal calf serum (HiFCS) (Biosera) and stored at -80\u0026deg;C.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSerum microbial translocation and cytokine analysis\u003c/h2\u003e \u003cp\u003eBlood collected in anti-coagulant free BD vacutainers was left upright for 30 minutes prior to centrifugation at 1620 x \u003cem\u003eg\u003c/em\u003e for 10 minutes at room temperature, after which the serum was removed and stored at -80\u0026deg;C prior to analysis. The concentration of serum proteins (occludin, LBP, sCD14 and sCD25) and cytokines (IL1β, IL4, IL6, IL7, IL10, IL15, IL17, TNFα, IFNγ, CRP, CXCL9 and GM-CSF) was determined using commercially available Enzyme-Linked Immunosorbent Assays (DL Develop, R\u0026amp;D Systems and Invitrogen) and a Human Premixed Multi-Analyte Magnetic Luminex Assay (R\u0026amp;D Systems). The absorbance of the wells was measured using wavelengths specified by the manufactures\u0026rsquo; instructions on a spectrophotometer (BioTek). Protein and cytokine concentrations were extrapolated from a standard curve created using known concentrations via GraphPad Prism software v9 (GraphPad Software Inc.).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStool 16S rRNA gene amplification via RT-qPCR\u003c/h2\u003e \u003cp\u003eDNA was extracted from 500 mg aliquots of stool using a commercially available FastDNA\u003csup\u003e\u0026trade;\u003c/sup\u003e SPIN Kit for Soil (MP Biomedicals,) according to the manufacturer\u0026rsquo;s instructions. DNA concentrations were determined on a calibrated Qubit 4 Fluorometer (Invitrogen\u003csup\u003e\u0026trade;\u003c/sup\u003e). RT-qPCR was used to amplify the V4 region of the 16S rRNA gene using desalted 515F and 806R primer pairs (Sigma-Aldrich) to create an amplicon library. Stool DNA samples (0.16\u0026ndash;14.48 ng/\u0026micro;l) were amplified in triplicate under the following PCR thermocycler conditions using a SensoQuest Basic Thermal Labcycler (with gradient; Geneflow Ltd, UK): initial denaturation at 94\u0026deg;C for 3 minutes followed by 35 cycles of denaturation at 94\u0026deg;C for 45 seconds, annealing at 50\u0026deg;C for 60 seconds, elongation at 72\u0026deg;C for 90 seconds and an extended elongation step at 72\u0026deg;C for 10 minutes. After pooling triplicate PCR reactions, RT-qPCR products were purified using the GeneJET PCR Purification Kit (Thermo Scientific\u003csup\u003e\u0026trade;\u003c/sup\u003e) according to the manufacturer\u0026rsquo;s instructions. The quality of the DNA library was checked via TapeStation D1000 ScreenTape\u003csup\u003e\u0026rarr;\u003c/sup\u003e (Agilent Technologies) using TapeStation Analysis Software A.02.02 (SR1) (Agilent Technologies). High-thorough 16S rRNA sequencing on the Illumina MiSeq platform (Illumina, Inc.) was done by Genomics Birmingham (University of Birmingham) using pooled DNA library and the MiSeq v2 500 sequencing kit (Illumina, Inc.). 16S rRNA sequencing data was analysed on the web-based Galaxy platform (version 23.01.dev0) using the Mothur toolset according to the online-based tutorial [\u003cspan additionalcitationids=\"CR66\" citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e], unique sequences were aligned to the SILVA v132 reference alignment to improve clustering of the operational taxonomic units (OTUs) [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e], using the Needleman-Wunsch algorithm. Next, taxonomic classification was performed using the SILVA v132 reference taxonomy and the Bayesian classifier and bacterial sequences were clustered into OTUs at the phylum level using a 97% similarity threshold and the relative abundance (%) of each phylum and genus was calculated.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eLiquid chromatography-mass spectrometry\u003c/h2\u003e \u003cp\u003eFaecal SCFA (acetate, butyrate and propionate) and secondary bile acid (deoxycholic acid (DCA), glycodeoxycholic acid (GDCA), hyodeoxycholic acid (HDCA), lithocholic acid (LCA) and ursodeoxycholic acid (UDCA)) concentrations were assessed in all participants via liquid chromatography-mass spectrometry (LC-MS) performed by the Quadrum Institute (Norwich, UK). In preparation, stool samples were thawed and 1 ml of extraction solvent (0.5% (v/v) orthophosphoric acid) was added to each tube followed by centrifugation and passing the supernatants through a Mini-UniPrep filter vial (0.45 \u0026micro;m; Whatman plc) prior to SCFA analysis via LC-MS. For the analysis of secondary bile acids, thawed stool (100 mg) was homogenised in a MaxQ\u003csup\u003e\u0026trade;\u003c/sup\u003e 6000 incubated shaker (Thermo Fischer Scientific) at 500 rpm for 30 minutes at 20\u0026deg;C using 5\u0026ndash;10 ceramic beads and 1 ml of methanol:water (9:1, v/v). Afterwards, 25 \u0026micro;l of 40 \u0026micro;g/ml D4-glycocholic acid was added to 500 \u0026micro;l of isolated stool supernatant. The mixtures were passed through a 10 mg capacity Oasis PriME HLB 96-well cartridge (Waters\u003csup\u003e\u0026trade;\u003c/sup\u003e) to remove phospholipids before LC-MS.\u003c/p\u003e \u003cp\u003eLC-MS was carried out on purified faecal samples and stool supernatant samples alongside a set of internal standards (D4-acetic acid, D2-propionic acid and D4- glycocholic acid) using an ACQUITY ultra-high-performance liquid chromatography system (Waters\u003csup\u003e\u0026trade;\u003c/sup\u003e) coupled to a Xevo TQ-S micro triple quadrupole mass spectrometer (Waters\u003csup\u003e\u0026trade;\u003c/sup\u003e). The mass spectrometer was operated in positive multiple reaction mode for SCFA quantification, while negative electrospray selected ion monitoring mode was used for D4-glycocholic acid (m/z 468.2), DCA and UDCA (m/z 391.2) and LCA (m/z 375.2) during secondary bile acid analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eT cell phenotyping\u003c/h2\u003e \u003cp\u003eFrozen PBMCs were surface stained with a combination of anti-human monoclonal antibodies for a 20 minute incubation at 4\u0026deg;C in the dark: 2 \u0026micro;g/ml CD3-PEcy7 (clone UCHT1; eBioscience\u0026trade;), 5 \u0026micro;g/ml CD4-eFluor 450 (clone OKT4 (OKT-4); eBioscience\u0026trade;), 3 \u0026micro;g/ml CD45RA-PerCP/cy5.5 (clone HI100; Biolegend) and 8 \u0026micro;g/ml CCR7-APCcy7 (clone G043H7; Biolegend), 4.5 \u0026micro;g/ml PTK7-PE (clone 188B; Miltenyi Biotec), 8 \u0026micro;g/ml CD25-APCcy7 (clone M-A251; BD Pharmingen), 0.5 \u0026micro;g/ml CD28-APC (clone CD28.2; eBioscience\u0026trade;), 6 \u0026micro;g/ml CD57-FITC (clone TB01 (TB01); Biolegend), 4 \u0026micro;g/ml PD1-APCcy7 (clone EH12.2H7; Biolegend) 0.5 \u0026micro;g/ml CD69-PEcy5 (clone FN50; Biolegend) and 16 \u0026micro;g/ml CD154-APCcy7 (clone 24\u0026ndash;31; Biolegend). Post incubation, the cells were fixed, permeabilised and intracellularly stained with 4 \u0026micro;g/ml anti-human RORγ-APC antibody and 10 ng/ml anti-human Foxp3-PE antibody (clone PCH101; eBioscience\u0026trade;) using the Foxp3 Transcription Factor Staining Buffer Set (eBioscience\u0026trade;) to examine the frequency of peripheral Th17 cells and Tregs. Flow cytometric analysis was carried out on a MACSQuant Analyzer 10 benchtop flow cytometer (Miltenyi Biotec). Prior to data acquisition, concentration-matched isotype controls were used to set the gates, and fluorescence spectral overlap was corrected via compensation during multi-colour flow cytometry. Data analysis was performed using FlowJo software v10.8.1 (BD). T cells were defined as CD3\u003csup\u003e+\u0026thinsp;ve\u003c/sup\u003e cells and 10,000 cells were gated and divided into CD4\u003csup\u003e+\u0026thinsp;ve\u003c/sup\u003e and CD8\u003csup\u003e+\u0026thinsp;ve\u003c/sup\u003e, which were further divided into four subsets based on CD45RA and CCR7 expression and denoted as naive (CD45RA\u003csup\u003e+\u0026thinsp;ve\u003c/sup\u003eCCR7\u003csup\u003e+ve)\u003c/sup\u003e, central memory (CD45RA\u003csup\u003e\u0026minus;\u0026thinsp;ve\u003c/sup\u003eCCR7\u003csup\u003e+ve\u003c/sup\u003e), effector memory (CD45RA\u003csup\u003e\u0026minus;\u0026thinsp;ve\u003c/sup\u003eCCR7\u003csup\u003e\u0026minus;ve\u003c/sup\u003e) and EMRA (CD45RA\u003csup\u003e+\u0026thinsp;ve\u003c/sup\u003eCCR7\u003csup\u003e\u0026minus;ve\u003c/sup\u003e) (see Supplementary Fig.\u0026nbsp;1 for gating strategy). CD3\u003csup\u003e+\u0026thinsp;ve\u003c/sup\u003eCD28\u003csup\u003e\u0026minus;ve\u003c/sup\u003eCD57\u003csup\u003e+ve\u003c/sup\u003e cells were denoted as senescent T cells [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eT cell functional analysis\u003c/h2\u003e \u003cp\u003eThawed PBMCs were washed with RPMI-1640 medium supplemented with 10% heat inactivated foetal calf serum (HiFCS), 2 mM L-glutamine, 100 U/ml penicillin and 100 \u0026micro;g/ml streptomycin (300 x \u003cem\u003eg\u003c/em\u003e for 10 minutes at 20\u0026deg;C). Post centrifugation, the cells were incubated with Benzonase\u0026reg; Nuclease (Sigma-Aldrich) for 1 hour at 37\u0026deg;C with 5% CO\u003csub\u003e2\u003c/sub\u003e before being transferred to the wells of a 96-well U-bottom plate pre-coated with 0.5 \u0026micro;g/ml anti-human CD3 monoclonal antibody (clone UCHT1; eBioscience\u0026trade;) and 5 \u0026micro;g/ml anti-human CD28 monoclonal antibody (clone CD28.2; eBioscience\u0026trade;). Following a 20 hour incubation at 37\u0026deg;C, 5% CO\u003csub\u003e2\u003c/sub\u003e, 10 \u0026micro;g/ml brefeldin A from \u003cem\u003ePenicllium brefeldianum\u003c/em\u003e (Sigma-Aldrich), 50 ng/ml phorbol 12-myristate 13-acetate (Sigma-Aldrich) and 500 ng/ml ionomycin from \u003cem\u003eStreptomyces conglobatus\u003c/em\u003e (Sigma-Aldrich) were added to the wells and the PBMCs were incubated for an additional 4 hours. Post incubation, the cells were washed with phosphate buffered saline (PBS) and stained with LIVE/DEAD\u0026trade; Fixable Near-IR Dead Cell Stain (Invitrogen) and 2 \u0026micro;g/ml CD3-PEcy7 (clone UCHT1) for 20 minutes in the dark at 4\u0026deg;C. The PBMCs were then washed with PBS prior to being fixed and permeabilised using the Foxp3 Transcription Factor Staining Buffer Set. To examine IL10-producing Tregs, the cells were stained with 2 \u0026micro;g/ml anti-human CD4-BV421 (clone RPA-T4; BD Biosciences), 10 ng/ml anti-human Foxp3-PE (clone PCH101) and 100 ng/ml anti-human IL10-APC (clone JES3-19F1; Biolegend) for 30 minutes in the dark at room temperature. Then, the PBMCs were washed and resuspended in 300 \u0026micro;l of PBS. Functional T cell data was assessed using FlowJo software. The percentage positive cells and MFI values were recorded for each antigen.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eRNA isolation from PBMCs\u003c/h2\u003e \u003cp\u003eRNA was isolated from 2\u0026nbsp;million frozen PBMCs according to the instructions of a commercially available RNeasy Mini Kit (Qiagen) and the purified RNA was eluted into 15 \u0026micro;l of RNase-free water. RNA quantity and quality were determined using a NanoDrop One Spectrophotometer (Thermo Fischer Scientific) and a 2100 Bioanalyser (Agilent Technologies), respectively. RNA samples were considered pure if the A260/280 and A260/230 ratios were \u0026ge;\u0026thinsp;1.8. Purified RNA samples were stored at -80\u0026deg;C for further analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eNanoString nCounter\u003csup\u003e\u0026reg;\u003c/sup\u003e gene expression analysis\u003c/h2\u003e \u003cp\u003eNanoString nCounter\u003csup\u003e\u0026reg;\u003c/sup\u003e was utilised for multiple gene expression profiling in RNA samples using the nCounter\u003csup\u003e\u0026reg;\u003c/sup\u003e Human PanCancer Immune Profiling Panel, consisting of 729 genes related to cytokine and chemokine signalling, cellular senescence, immune cell profiling, lymphoid cell function and innate and adaptive immune responses (Nanostring Technologies). 80 ng of unamplified RNA per sample was processed by the Birmingham Tissue Analytics at the University of Birmingham. Normalization and data analysis of count numbers were carried out with NanoString nSolver\u0026reg; Analysis. Qlucore Omics Explorer software v3.8 (Qlucore) was used to create a heatmap using log2 fold-change values to visualise unique gene expression patterns between cohorts. Genes were included if p-values were statistically significant.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eMouse experiments\u003c/h2\u003e \u003cp\u003eMale and female young (10\u0026ndash;16 weeks) and aged (20\u0026ndash;22 months) wild-type C57BL/6 mice (originally from Jackson Laboratories) were fed a low protein diet (i.e. Teklad Irradiated Global 14% protein Maintenance Diet) and bred in-house. Sex and age-matched germ-free mice (20\u0026ndash;22 months) were housed in pathogen-free conditions in the Gnotobiotic Facility of McMaster. All experiments were performed in accordance with the Institutional Animal Utilization protocols [ protocol number 21-04-13] approved by McMaster University\u0026rsquo;s Animal Research Ethics Board as per the recommendations of the Canadian Council for Animal Care. Thymus and ileum tissues were collected from young wild-type (n\u0026thinsp;=\u0026thinsp;6), aged wild-type (n\u0026thinsp;=\u0026thinsp;6) and aged germ-free mice (n\u0026thinsp;=\u0026thinsp;3).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eFITC-dextran trans-epithelial intestinal permeability assay\u003c/h2\u003e \u003cp\u003eMice were fasted (no food or water) for 6 hours prior to oral gavage of 150 \u0026micro;l of 80 mg/ml tracer labelled FITC-dextran (Sigma-Aldrich) to assess \u003cem\u003ein vivo\u003c/em\u003e intestinal permeability. After 4 hours, blood was collected and diluted 2-fold with PBS. Fluorescent intensity was measured on a SpectraMax i3 microplate reader (Molecular Devices, USA) with an excitation wavelength of 493 nm and an emission wavelength of 518 nm.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eOccludin staining for intestinal membrane permeability assessment\u003c/h2\u003e \u003cp\u003eSections of ileum were excised and embedded in OCT compound at -80\u0026deg;C. Tissue blocks were cut into 7 \u0026micro;m sections that were fixed with ice-cold acetone. After blocking with 10% goat serum, the samples were stained with 4 \u0026micro;g/ml mouse anti-mouse occludin antibody (clone E-5; Santa Cruz Biotechnology) overnight, followed by incubation with 40 \u0026micro;g/ml goat anti-mouse Alexa Fluor\u003csup\u003e\u0026reg;\u003c/sup\u003e 555 secondary antibody (Thermo Fischer\u003csup\u003e\u0026trade;\u003c/sup\u003e). Images were acquired using an Olympus IX71 inverted fluorescence microscope at 10X and 40X magnification.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eHistological analysis and oil red O staining of mouse thymus sections\u003c/h2\u003e \u003cp\u003eFrozen mouse thymuses embedded in OCT compound were sectioned to a thickness of 7 \u0026micro;m and mounted onto microscope slides before staining with haematoxylin and eosin (H\u0026amp;E) and the percentage of medullary areas was calculated as a percentage. Thymus sections were also stained for lipid droplets using an Oil Red O Staining Kit. Each thymus sample was stained in triplicate and six images were acquired using a Zeiss Primovert inverted light microscope at 10X and 40X magnification. The number of oil red O stained lipid droplets per \u0026micro;m\u003csup\u003e2\u003c/sup\u003e was determined using Fiji software.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eNuclear lamin B1 staining\u003c/h2\u003e \u003cp\u003eMicroscope slides containing mouse thymus sections were fixed with ice-cold acetone and stained with recombinant anti-mouse lamin B1 antibody (clone EPR22165-121; Abcam) consisting of 10% HiFCS and 0.2% triton-X 100 in PBS overnight followed by staining with 6.6 \u0026micro;g/ml anti-rabbit IgG conjugated to Alexa Fluor\u003csup\u003e\u0026reg;\u003c/sup\u003e 555 (clone H\u0026thinsp;+\u0026thinsp;L, F(ab\u0026rsquo;)\u003csub\u003e2\u003c/sub\u003e; Cell Signalling Technology). Post wash, tissues were stained with 1 \u0026micro;g/ml DAPI solution (Thermo Fischer\u003csup\u003e\u0026trade;\u003c/sup\u003e). Images were acquired using an Olympus IX71 inverted fluorescence microscope at 10X and 40X magnification and imaging analysis was performed using Image J software.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eThymocyte and thymic epithelial cell (TEC) staining\u003c/h2\u003e \u003cp\u003eFrozen thymus sections fixed with ice-cold acetone were stained with a combination of anti-mouse monoclonal antibodies for 30 minutes in the dark at room temperature: 2.5 \u0026micro;g/ml CD4 Alexa Fluor 647 (clone RM4-5; Biolegend), 1.7 \u0026micro;g/ml CD8α biotin (clone 53\u0026thinsp;\u0026minus;\u0026thinsp;6.7; eBioscience\u003csup\u003e\u0026trade;\u003c/sup\u003e), ERTR5 rat IgM [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e], 10 \u0026micro;g/ml CD205 biotin (clone 205yeka; eBiosience\u003csup\u003e\u0026trade;\u003c/sup\u003e) and 10 \u0026micro;g/ml Aire Alexa Fluor 488 (clone 5H12; Thermo Fischer Scientific). Post incubation, the slides were incubated with the following secondary antibodies: 2 \u0026micro;g/ml streptavidin Alexa Fluor 555 (Thermo Fischer Scientific), 2.5 \u0026micro;g/ml goat anti-rat IgM Alexa Fluor 488 (Thermo Fischer Scientific) and 10 \u0026micro;g/ml goat anti-rat IgM Alexa-Fluor 647 (Thermo Fischer Scientific). The slides were then washed and incubated with 1 \u0026micro;g/ml DAPI solution (Thermo Fischer\u003csup\u003e\u0026trade;\u003c/sup\u003e) in preparation for confocal microscopy. Each thymus sample was stained in triplicate and six images of the medullary and cortical regions were acquired on Zeiss LSM 880 with Airyscan Fast confocal microscope at 10X and 40X magnification. Before image acquisition, primary antibody-only controls and secondary antibody-only controls were used to detect possible non-specific binding and autofluorescence. Confocal imaging analysis was performed using Zeiss Zen Black software to calculate the positively staining ERTr5 and CD205 pixels were expressed as a percentage of the total pixels in the picture.\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eRNA isolation and quantitative real time-PCR\u003c/h2\u003e \u003cp\u003eRNA was isolated from thymus samples using a commercially available RNeasy Mini Kit as per the manufacturer\u0026rsquo;s instructions (Qiagen). RNA quantity and quality were determined using a NanoDrop One Spectrophotometer and a 2100 Bioanalyser.Quantitative. Quantitative real time-PCR was carried out on 5 ng/\u0026micro;l RNA isolated from mouse thymus samples using the iTaq Universal SYBR Green One-Step Kit (Biorad) on a CFX384 Tough Real-Time PCR Detection System (Biorad). Primer sequences (5\u0026rsquo;\u0026ndash;3\u0026rsquo;) were p16 (TTGGCCCAAGAGCGGGGACA), IL6 (CTGCAAGAGACTTCCATCCAG), BAX (AGGATGAGTCCACCAAGAAGCT) and housekeeping gene Epcam (TTGCTCCAAACTGGCGTCTAA). The PCR thermocycler condition was as follows: initial reverse transcription at 50\u0026deg;C for 10 minutes, polymerase activation at 95\u0026deg;C for 5 minutes, 40 cycles of denaturation at 95\u0026deg;C for 10 seconds, annealing at 60\u0026deg;C for 30 seconds and initial elongation at 65\u0026deg;C for 31 seconds followed by 60 cycles of elongation at 65\u0026deg;C for 5 seconds. All samples were run in triplicate. Relative gene expression was calculated using the ΔΔCt method followed by normalisation of the values to the relative gene expression of Epcam.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll statistical analysis was performed using GraphPad Prism\u0026reg; software (GraphPad Software Inc.). Data distribution was examined using Kolmogorov-Smirnov normality test before parametric and non-parametric tests were performed. Parametric tests were carried out on normally distributed data, while non-parametric tests were used when the data was not normally distributed. Unpaired Student\u0026rsquo;s T test (parametric test) and Mann-Whitney U test (non-parametric) were used to compare means between young and old adults and the Benjamini-Hochberg method was used to calculate adjusted p-values. Chi-square test was used to compare categorical data, such as sex and smoking status, between the groups. One-way analysis of variance (ANOVA) was used to compare means between low MT young, low MT old and high MT old adults as well as means between young wild-type, aged wild-type and aged germ-free mice. Following one-way ANOVA, Bonferroni (parametric test) and Dunn\u0026rsquo;s (non-parametric) multiple comparison tests were performed to calculate adjusted p-values. Spearman correlation-based linear regression analysis was performed to determine the strength of associations between all combinations of intestinal barrier dysfunction surrogate markers and hallmarks of immunesenescence [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. For pathway enrichment analysis, the Benjamin-Hochberg false discovery rate was used to calculate adjusted p-values. Statistical significance was accepted as p\u0026thinsp;\u0026le;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHuman study was approved by the North West - Haydock Research Ethics Committee [ REC reference: 22/NW/0187]. Written consent was obtained from all participants. All procedures involving animals were approved by approved by McMaster University\u0026rsquo;s Animal Research Ethics Board as per the recommendations of the Canadian Council for Animal Care.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful to the participants that have made this research possible. We thank Joe Flint from Birmingham Tissue Analytics at the University of Birmingham, for technical assistance in the generation of nCounter data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by funding from the Academy of Medical Sciences Springboard Award and the MRC-Versus Arthritis Centre for Musculoskeletal Ageing Research. GA is supported by an MRC Programme Grant to GA (MR/T029765/1). The views expressed here are those of the authors and not necessarily those of the Department for Health and Social care. The funders provided financial support to this research but had no role in the design of the study, analysis, interpretations of the data and in writing the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRaw flow cytometry will be made available upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflicts of interest connected to this paper.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eParay, B. A., Albeshr, M. F., Jan, A. T. \u0026amp; Rather, I. A. Leaky Gut and Autoimmunity: An Intricate Balance in Individuals Health and the Diseased State. Int J Mol Sci 21, 9770 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSalazar, A. M., Aparicio, R., Clark, R. I., Rera, M. \u0026amp; Walker, D. W. Intestinal barrier dysfunction: an evolutionarily conserved hallmark of aging. Dis Model Mech 16, dmm049969 (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWilson, Q.N., Wells, M., Davis, A.T. Sherrill, C., Tsilimigras, M. C. B., Jones, R. B., Fodor, A. A. \u0026amp; Kavanagh, K. Greater Microbial Translocation and Vulnerability to Metabolic Disease in Healthy Aged Female Monkeys. Sci Rep 8, 11373 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRera, M., Azizi, M. J. \u0026amp; Walker, D. W. Organ-specific mediation of lifespan extension: more than a gut feeling? Ageing Res Rev 12, 436\u0026ndash;444 (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKlatt, N. R., Harris, L. D., Vinton, C. L., Sung, H., Briant, J. A., Tabb, B., Morcock, D., McGinty, J. W., Lifson, J. D., Lafont, B. A., Martin, M. A., Levine, A. D., Estes, J. D. \u0026amp; Brenchley, J. M. 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J Biol Chem 296, 100311 (2021).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-3845290/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3845290/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe intestinal epithelium serves as a physical and functional barrier against harmful substances, preventing their entry into the circulation and subsequent induction of a systemic immune response. Gut barrier dysfunction has recently emerged as a feature of ageing linked to declining health, and increased intestinal membrane permeability has been shown to promote heightened systemic inflammation in aged hosts. Concurrent with age-related changes in the gut microbiome, the thymic microenvironment undergoes a series of morphological, phenotypical and architectural alterations with age, including disorganisation of the corticomedullary junction, increased fibrosis, increased thymic adiposity and the accumulation of senescent cells. However, a direct link between gut barrier dysbiosis and thymic involution leading to features of immune ageing has not been explored thus far.\u003c/p\u003e \u003cp\u003eHerein, we identify several strong associations between enhanced microbial translocation and the peripheral accumulation of terminally differentiated, senescent and exhausted T cells and the compensatory expansion of regulatory T cells in older adults. Most importantly, we confirm a direct effect of mucosal permeability on the regulation of thymic ageing and hyperactivation of the immune system by demonstrating that aged germ-free mice are protected from age-related intestinal membrane permeability.\u003c/p\u003e \u003cp\u003eTogether, these findings establish a mechanism by which gut barrier dysfunction drives systemic activation of the immune system during ageing, via causing thymic involution, extending our understanding of the consequences of intestinal membrane permeability and opening up the possibility for the use of microbiome-based interventions to restore immune homeostasis in older adults.\u003c/p\u003e","manuscriptTitle":"Age-related loss of intestinal barrier integrity plays an integral role in Thymic involution and T cell ageing","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-16 08:55:27","doi":"10.21203/rs.3.rs-3845290/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8e4ae4a4-3231-4780-aaa0-65845319b1d3","owner":[],"postedDate":"January 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-05-14T14:54:56+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-16 08:55:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3845290","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3845290","identity":"rs-3845290","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}