Metformin Reduces Aging-Related Leaky Gut and Improves Cognitive Function by Beneficially Modulating Gut Microbiome/Goblet Cell/Mucin Axis

Abstract

Aging-related illnesses are increasing and effective strategies to prevent and/or treat them are lacking. This is because of a poor understanding of therapeutic targets. Low-grade inflammation is often higher in older adults and remains a key risk factor of aging-related morbidities and mortalities. Emerging evidence indicates that abnormal (dysbiotic) gut microbiome and dysfunctional gut permeability (leaky gut) are linked with increased inflammation in older adults. However, currently available drugs do not treat aging-related microbiome dysbiosis and leaky gut, and little is known about the cellular and molecular processes that can be targeted to reduce leaky gut in older adults. Here, we demonstrated that metformin, a safe Food and Drug Administration-approved antidiabetic drug, decreased leaky gut and inflammation in high-fat diet-fed older obese mice, by beneficially modulating the gut microbiota. In addition, metformin increased goblet cell mass and mucin production in the obese older gut, thereby decreasing leaky gut and inflammation. Mechanistically, metformin increased the goblet cell differentiation markers by suppressing Wnt signaling. Our results suggest that metformin can be used as a regimen to prevent and treat aging-related leaky gut and inflammation, especially in obese individuals and people with western-style high-fat dietary lifestyle, by beneficially modulating gut microbiome/goblet cell/mucin biology.

Illnesses associated with aging are increasing worldwide as the population grows older, but optimal treatments remain elusive. Hence, a better understanding of the factors underlying these disorders and novel therapeutic strategies are urgently needed. Chronic low-grade inflammation is common in older individuals and is a strong risk factor for aging-related disorders that cause high morbidity and mortality (1,2). We and others have shown that increased inflammation is associated with abnormally increased gut permeability (leaky gut) in older adults (3–6) and that both systemic inflammation and leaky gut increase with age and are associated with age-related declines in cognition and/or physical function in older adults (3,4,7). Recent evidence shows that leaky gut, in which microbial and dietary antigens can leak into the bloodstream from gut lumen, causes an increase in low-grade inflammation, and these conditions are common in older people (8–10). Inflammation is also a major risk factor for cognitive decline and Alzheimer’s pathology in older adults (11–15), suggesting that suppressing inflammation and leaky gut could ameliorate the cognitive decline in the aging brain. Intestinal permeability is controlled primarily by the physical barrier of mucus layer and tight-junction proteins (16,17). The intestinal mucus layer is primarily made of mucin (specifically mucin 2 [Muc2]) glycoproteins that are secreted by epithelial goblet cells and covers the intestinal epithelia by forming a viscoelastic gel layer which protects the invasion of dietary and microbial antigens and lumen contents (17,18). Thus, intestinal mucosal layer is a critical spot to regulate inflammatory response (18). Disruption of the mucus layer results in an increase in intestinal permeability (leaky gut), followed by heightened bacterial translocation and local and systemic inflammatory responses. Reduced thickness of mucus layer in the gut of older adults is linked with the risk of impaired intestinal barrier function and inflammation (19,20). Therefore, maintaining gut microbiome homeostasis and promoting mucin production in the gut can be an ideal target to reduce aging-related leaky gut and inflammation and promote healthy aging; however, effective strategies to treat aging-related microbiome dysbiosis and promote mucus production to reduce leaky gut and inflammation are not known.

Metformin, the most widely prescribed antidiabetic drug, has beneficial effects for aging-related disorders and extends life span in several animal models (21–24). Hence, it is being studied in older adults as a potential tool that may target biological aging and reduce age-related morbidities and mortality (24). Metformin has been in wide use for over 60 years with an exceptional safety record and is available as an inexpensive generic drug (24). It has pleiotropic effects that target various aging-related mechanisms. Of particular relevance to aging, metformin leads to decreased insulin levels, decreased insulin/insulin-like growth factor-1 signaling (25), inhibition of mammalian target of rapamycin (mTOR) (26), inhibition of mitochondrial complex I in the electron transport chain and reduction of endogenous production of reactive oxygen species, activation of AMP-activated kinase (27), and less DNA damage (28). Metformin favorably influences metabolic and cellular processes closely associated with the development of age-related conditions, such as autophagy (29) and cellular senescence (30). These effects extend well beyond metformin’s known actions on glucose homeostasis (24). Nevertheless, metformin’s precise mechanisms of action are still unclear. Since intravenous metformin is less or not effective than oral dosing (31), it is likely that the action of metformin may be centered in the gut. Multiple lines of emerging evidence from nematodes, rodents, and humans, suggest that metformin predominantly changes gut microbiota and promotes specific bacterial populations (32), which may play central role in metformin action mediated through gut. It is currently unclear whether metformin has multiple effects on multiple pathways, or modulates a single or a few key mechanisms of aging. Specifically, metformin’s role in reducing aging-related leaky gut and its mechanistic underpinnings remain unknown. Here, we demonstrated that metformin beneficially modulates gut microbiota and promotes mucus production in older obese mice on high-fat diet (HFD), which in turn ameliorates aging-related leaky gut and inflammation.

Results

Metformin Ameliorated HFD-Induced Metabolic Dysfunctions and Improved Cognitive Function in Older Mice

Older adults are at high risk of developing type 2 diabetes (T2D) characteristics such as glucose intolerance, hepatic steatosis (fat accumulation in the liver), adipocyte hypertrophy, and inflammatory macrophage infiltration in adipose tissues (33–35). Although metformin is known to reduce the risk of T2D in young adults, its interactions with different fat content diets and aging are not well defined. We demonstrated that metformin reduced the body weight in older mice (~20 months old) fed with low-fat diet (LFD), while it slightly increased the body weight gain in HFD-fed older mice (Figure 1a), suggesting that metformin effects on body weight and obesity can differ based on fat contents in the diets. Metformin treatment also significantly reduced the glucose intolerance during the glucose tolerance test (GTT) in HFD-fed older mice (Figure 1b and c). While no significant differences were observed among metformin-treated versus nontreated groups in the insulin sensitivity measured by insulin tolerance test (ITT; Supplementary Figure S1a–c). In addition, food and water intake, fat mass, lean mass, fasting blood glucose and energy expenditure did not differ upon metformin treatment in older mice fed with LFD and HFD (Supplementary Figure S1d–j). Further, the fat accumulation in liver (hepatic steatosis or nonalcoholic fatty liver disease [NAFLD]) was significantly reduced in metformin-treated HFD-fed older mice compared to their untreated controls (Figure 1d). In addition, the size of adipocytes and crown-like structures (markers of inflammation) were significantly reduced in the white adipose tissue (gonadal) of metformin-treated older mice, specifically in HFD-fed mice compared to their untreated controls (Figure 1e–h). These results demonstrated that metformin protected against HFD-induced metabolic dysfunctions in older mice along with reduced hepatic steatosis/NAFLD and inflammation in white adipose tissue.

Figure 1.

Metformin reduced high-fat diet (HFD)-induced glucose intolerance, hepatic steatosis, hypertrophy, and inflammation in adipocytes in older mice. (a) Metformin treatment significantly increased body weight in HFD-fed mice, while decreased in low-fat diet (LFD)-fed mice. (b) Metformin treatment also decreased glucose tolerance (b), the area under curve (c) in glucose tolerance test, fat accumulation in the liver (hepatic steatosis) (d), adipocyte size (e–g), and inflammation indicated by crown-like structures (e,h). (i) Metformin-treated HFD-fed mice showed reduced escape latency time (s) as an indicator of improved learning-memory behavior measured during the Water–Morris Maze test compared to their controls. (j) The rate of fluorescein isothiocyanate (FITC) appearance in the blood from the gut as a marker of leaky gut was significantly reduced in metformin-treated mice. (k–m) The mRNA expression of inflammatory markers such as TNF-α, IL-1β, and IL-6 were significantly reduced in metformin-treated mice compared to their untreated controls, specifically more significant in HFD-fed mice. Values are mean of n = 5–8 mice per group ± SEM (error bars). Values with *p < .05, **p < .01, and ***p < .001 are statistically significant between LFD-metformin versus LFD controls, while values with ^#p < .05, ^##p < .01, and ^###p < .001 are statistically significant between HFD-metformin versus HFD controls. The values indicated with ‘ns’ are not statistically significantly different.

The decline in cognitive function is common in older adults (36) and obesity/T2D further increases the risk of cognitive decline in the older adults (37,38). Our data also showed that metformin significantly improved the learning and memory behavior in older mice, specifically in HFD-fed obese mice (Figure 1i), suggesting that metformin might be beneficial to ameliorate cognitive decline in older obese subjects.

Metformin Reduced Leaky Gut and Inflammation and Increased Mucin Expression in the Gut of Older Mice

Emerging evidence indicates that leaky gut is often higher in older adults as well as in obese individuals, which is linked with increased low-grade chronic inflammation (3,39). We found that the gut permeability (measured by FITC-dextran assay) was significantly increased in older mice (~21 months old) fed with HFD compared to their LFD-fed counterparts; however, metformin treatment significantly reduced the leakiness and maintained it close to normal levels (Figure 1j). Similarly, the expression of inflammatory markers such as tumor necrosis factor-alpha (TNF-α) and interleukin (IL)-1beta (IL-1β) was significantly increased in the intestine (colon) of HFD-fed mice compared to LFD-fed controls, and metformin treatment maintained the expression of these genes close to the normal levels (Figure 1k and l). The expression of IL-6 was significantly decreased in the intestine of both HFD- and LFD-fed older mice compared to their untreated controls (Figure 1m). These results indicate that the metformin treatment reduced leaky gut and inflammation in older mice. Furthermore, to determine the mechanism(s) by which metformin reduces leaky gut, we measured the expression of tight-junction proteins such as Zonulin-1 (Zo-1) and Occludin (Ocln), and mucin-2 (Muc2; a major component of mucus in the gut). Interestingly, we found that the expression of Muc2 was significantly increased in the intestine (colon) of metformin-treated older mice compared to their controls (Figure 2a). A significant increase was also observed in the expression of Ocln, while Zo-1 expression remains unaffected in the gut of metformin-treated mice compared to their nontreated controls (Figure 2b and c), suggesting that metformin action might be through increasing the mucin production to thickening of the mucus layer as a physical barrier to decrease leaky gut and inflammation.

Figure 2.

Metformin increased goblet cells, mucin via suppressing Wnt signaling and increasing goblet cell precursor markers in the gut of older obese mice. (a,b) mRNA expression of mucin 2 (Muc2) was significantly increased in the intestine (colon) of metformin-treated older mice compared to their untreated controls (a), while mRNA expression of occludin (Ocln) was also significantly increased, but only in high-fat diet (HFD)-fed mice compared to their HFD-fed controls (b). (c) No significant changes were observed in the mRNA expression of Zonulin-1 among all the groups. (d–g) Goblet cell staining with AB/PAS stain indicated that the intestinal goblet cell mass in the ileum (d,e) and colon (f,g) were significantly increased in metformin-treated older mouse gut compared to their controls. (h) Mucin 2 protein levels measured by western blots were also significantly increased in the colon and ileum of metformin-treated older mice. (i–k) Interestingly, the mRNA expression of goblet cell precursor markers like Elf3, Spdef, and Gfi1 were significantly increased in the intestine (colon) of metformin-treated older mice. (l) The protein expression of Wnt signaling mediators like Wnt3a, Wnt5a and Axin levels were significantly decreased in the gut of metformin-treated mice compared to their controls. Values are mean of n = 5–8 mice per group ± SEM (error bars). Values with *p < .05, **p < .01, and ***p < .001 are statistically significant between low-fat diet (LFD)-metformin versus LFD controls, while values with ^#p < .05, ^##p < .01, ^###p < .001 are statistically significant between HFD-metformin versus HFD controls. The values indicated with ‘ns’ are not statistically significantly different.

Metformin Increased Goblet Cell Mass and Mucin Production by Suppressing Wnt Signaling and Goblet Cell Differentiation Markers

To further demonstrate the cause of increased Muc2 expression, we analyzed the goblet cell numbers in the intestinal epithelial (colon). Interestingly, we found that the HFD feeding significantly decreased the goblet cell numbers in the ileum and colon regions of older mice, while metformin treatment preserved the goblet cell mass (Figure 2d–g). As mucin 2 is the major protein of mucus layer produced by goblet cells in the gut, we found that the protein expression of mucin 2 was significantly increased in both ileum and colon of older mice treated with metformin (Figure 2h). These results indicated that the metformin treatment increased the goblet cell mass and mucin 2 protein expression in the intestine, which was linked to increase expression of Muc2 gene and reduced leaky gut and inflammation in the older mice.

To decipher the mechanism by which goblet cell mass was impacted, we tested a hypothesis that HFD diet decreases differentiation of intestinal stem cells (iSCs) to goblet cell precursors and goblet cells, while metformin restores or promotes goblet cell formation by increasing goblet cell precursor pool. Interestingly, we found that the expression of goblet cell precursor markers such as Elf3 (E74 like ETS transcription factor 3), Spdef (SAM pointed domain containing ETS transcription factor), and Gfi1 (Growth factor independent 1 transcriptional repressor) were significantly decreased in the colon of HFD-fed mice compared to their LFD-fed counterparts (Figure 2i–k). While the expression of these markers were significantly increased in the intestine of both metformin-treated HFD- and LFD-fed older mice compared to untreated controls, suggesting that metformin may have promoted the differentiation of iSCs to form more goblet cell precursors which ultimately form more goblet cells and produces higher mucin to reduce leaky gut. The Wnt signaling is one of the critical signaling pathways that regulate iSCs differentiation to goblet cells. Suppression of Wnt signaling is known to promote differentiation of iSCs to form new goblet cell precursors and mature goblet cells (40,41). We found that metformin treatment significantly reduced the expression of Wnt5a and Wnt3a proteins along with its signaling mediators like Axin1 (Figure 2l). These results suggest that metformin increased the goblet cell mass by suppressing Wnt signaling and increasing iSCs differentiation to form oblet cells, thereby ultimately increasing the mucin formation and reducing the leaky gut.

Metformin Beneficially Modulated Gut Microbiome in Older Mice

To determine the impact of LFD–HFD diets and metformin interactions on the gut microbiome of older mice (~21 months old), our 16S rRNA metagenomic analyses suggested that the feeding of LFD and HFD developed dramatically different gut microbiome signatures as indicated by β-diversity in terms of principal coordinate analysis (Figure 3a). Interestingly, gut microbiome signature of HFD-fed older mice treated with metformin show significantly different gut microbiome clustering than their untreated HFD-fed counterparts, while gut microbiome of LFD-fed older mice remains indistinguishable between metformin-treated and untreated groups. Further, LFD significantly decreased microbiome α-diversity in terms of α-diversity measures such as PD whole tree, Chao1, observed OTUs (operational taxonomic units) and Shannon index compared to HFD-fed counterparts. However, metformin treatment slightly improved α-diversity measures only in LFD-fed mice, while no significant differences were observed in these measures of HFD-fed older mice (Supplementary Figure S2a–d). As expected, the abundance of Firmicutes was increased and that of Bacteroidetes was decreased in HFD-fed older mice compared to LFD-fed mice; however, metformin treatment slightly increased Bacteroidetes in HFD-fed mice compared to their untreated HFD-fed counterparts (Figure 3b). In addition, the abundance of genera belonging to S24_7, Ruminococcaceae and Lactococcus were increased, while that of Coriobacteriaceae, Lactobacillus, Dorea, SMB53, Roseburia and Veilonellaceae, and Dehalobacterium was significantly decreased in the gut of metformin-treated HFD-fed older mice compared to their HFD-fed controls. Similarly, the proportion of Clostridiales;g, Lachnospiraceae;g, and Ruminococcus was significantly increased while that of genus Sutterella was significantly decreased in metformin-treated LFD-fed mice compared to their LFD-fed counterparts (Figure 3c and d). LDA effect size (LEfSe) analysis further suggested that gut microbiome signature was significantly changed by metformin treatment, especially in the HFD-fed mice group, and that the metformin effect on microbiome signature was more prominent than dietary effects (Figure 3e, Supplementary Figure S2e).

Figure 3.

Metformin treatment beneficially modulated the gut microbiome. (a) Principal coordinate analysis showing the β-diversity clustering of the gut microbiome from older obese mice fed with low-fat diet (LFD) and high-fat diet (HFD) and treated with metformin was significantly different. (b,c) Significant changes were observed in major bacterial phyla (b), and genera (c) in the feces of older mice fed with HFD and LFD and treatment with metformin compared to their controls. (d) Linear discrimination analysis (LDA) effect size (LEfSe) analysis showing through cladogram the significantly different clustering of the gut microbiome in metformin-treated versus untreated and their diet consumption groups. (e) The abundance of major genera differed according to metformin treatment and LFD versus HFD feeding in the gut of older mice. Values are mean of n = 5 mice per group ± SEM (error bars). Values are mean of n = 5–8 mice per group ± SEM (error bars). Values with *p < .05, are statistically significant between LFD-metformin versus LFD/HFD controls.

Metformin Increased the Production of Beneficial Metabolites in the Gut of Older Mice

The functional unit of the microbiome to impact host cells are the metabolites that bacteria either produce by fermenting dietary ingredients or synthesize through commensal relationship and cross-feeding. To decipher the impact of metformin on metabolites in the gut, we performed the untargeted global metabolomics on mouse fecal specimens and found significantly different profiles of the fecal metabolites in metformin-treated mice compared to their untreated counterparts (Figure 4a). LFD versus HFD had major impact on fecal metabolites; however, metformin-induced dramatically distinct clustering of metabolite profiles in LFD as well as HFD-fed older mice (Figure 4a and b). Further, to unbiasedly discover the microbial metabolites that were significantly impacted by metformin, we applied random forest analysis that revealed butyrate and taurine as the two major metabolites that were significantly impacted upon metformin treatment in the gut of older mice (Figure 4c; Supplementary Table S3). Further analyses of differentially upregulated and downregulated metabolites (upon metformin treatment) found that the abundance of 5-aminopantanoate_1, propionate and butyrate was increased while that of 5-aminopentanoate_2, ethanol, sarcosine, formate, creatinine, propylene glycol, and several others were decreased in metformin-treated LFD-fed older mice compared to untreated LFD-fed controls (Figure 5d). Similarly, the abundance of taurine, butyrate, total bile acids_1, propionate, and leucine was increased while that of creatinine, sarcosine, glutamate, pyruvate, and formate was significantly decreased in the feces of metformin-treated HFD-fed older mice compared to their untreated HFD-fed counterparts (Figure 4e–i). Metformin caused highest increase in butyrate and taurine and highest decrease in creatinine and sarcosine abundance in the gut of older mice (Figure 4f–i). These results demonstrate that metformin treatment dramatically changed the metabolite profile and promoted the production of beneficial metabolites in the gut of older mice.

Figure 4.

Metformin modulated gut metabolome and increased the production of beneficial metabolites in the gut of older mice. (a–c) Untargeted–unbiased fecal metabolomics analyses show that metformin treatment significantly changed the production of array of metabolites shown by principal component analysis (PCA) (a), group clustering (b), and random forest analyses (c). (d,e) Similarly, volcano graph showing significantly upregulated and downregulated metabolites in metformin-treated and low-fat diet (LFD) (d) and high-fat diet (HFD)-fed older mice compared to their corresponding controls. (f–i) Abundance of butyrate (f) and taurine (g) was increased, whereas, the abundance of creatinine (h) and sarcosine (i) were in the feces of metformin-treated older mice compared to untreated controls. Values are mean of n = 5–8 mice per group ± SEM (error bars). Values with *p < .05, **p < .01, and ***p < .001 are statistically significant between LFD-metformin versus LFD controls, while values with ^#p < .05, ^##p < .01, and ^###p < .001 are statistically significant between HFD-metformin versus HFD controls. The values indicated with ‘ns’ are not statistically significantly different.

Figure 5.

Metformin modulated gut microbiome plays a causal role in increasing goblet cell mass and mucin. (a) The gut microbiome composition in terms of b-diversity clustering in Principal coordinate analyses indicated significantly different gut microbiome after fecal microbiome transplantation in the recipient mice. (b) Cladogram of LefSe analysis also shows that gut microbiome composition is significantly different in recipient mice received fecal microbiome transplantation (FMT) from metformin-treated and untreated older mice. (c) Metformin-treated FMT significantly increased the intestinal goblet cell mass indicated by AB/PAS staining (blue) (c) and counting (d). (e–h) FMT of metformin-treated microbiome also significantly increased the mRNA expression of Muc2, and goblet cell precursor markers, that is, Spdef, Atoh, and Gfi1 in the gut of recipient mice compared to their controls. (i) A purported model based on our results showing that metformin improved metabolic dysfunctions, and cognitive decline by modulating gut microbiome and increasing production of beneficial metabolites which in turn can suppress Wnt signaling resulting in increased goblet cell precursors, goblet cells and mucin formation, ultimately reducing leaky gut and inflammation. Values are mean of n = 5–8 mice per group ± SEM (error bars). Values with *p < .05, **p < .01, and ***p < .001 are statistically significant between low-fat diet (LFD)-metformin versus LFD controls, while values with ^#p < .05, ^##p < .01, are statistically significant between high-fat diet (HFD)-metformin versus HFD controls. The values indicated with “ns” are not statistically significantly different.

The Metformin-Modulated Gut Microbiome Is Causal for Promoting Goblet Cell Mass and Mucin

To further decipher whether the metformin-induced changes in the gut microbiome are causal or consequential to promote goblet cell precursors, goblet cell mass, and mucin expression in the gut of older mice, we transplanted fecal microbiome from metformin-treated and untreated controls to gut cleansed mice. After 1 week of fecal microbiome transplantation (FMT), the microbiome signature in recipient mice was significantly different among the groups but found to be closure to the donor mice (Figure 5a and b; Supplementary Figure S3a–h). Interestingly, the goblet cell mass was significantly increased in the gut of mice that received metformin-treated FMT compared to control-FMT-recipient mice (Figure 5c and d). The expression of Muc2 and goblet cell differentiation gene markers such as Spdef, Atoh, and Gfi1 were also significantly increased in the intestine (colon) of metformin-treated FMT-recipient mice compared to control-FMT recipients (Figure 5e–h). These results indicated that the metformin-modulated gut microbiome plays a causal role in promoting goblet cells and mucin formation, which ultimately reduce leaky gut and inflammation in the older gut (Figure 5i).

Discussion

Increased inflammation in aging (also termed as inflammaging) is one of the key risk factors for age-related diseases such as obesity, T2D, NAFLD, and cognitive decline in older adults and is tightly linked with abnormal (dysbiotic) gut microbiome and increased leaky gut. However, no treatments are known to prevent or treat aging-related microbiome dysbiosis, and leaky gut in older adults. Herein, we demonstrated that metformin reduces aging-related microbiome dysbiosis, promotes the production of beneficial metabolites, and reduces leaky gut and inflammation by promoting mucin formation and goblet cell mass via suppressing Wnt signaling.

Diet is one of the major modulators of the gut microbiome, and HFD feeding induces dysbiosis in the gut microbiome and increases T2D characteristics such as glucose intolerance, hepatic steatosis, hypertrophy of adipocytes, and increased inflammation (33–35). Older adults are more susceptible for high-calorie diet-induced T2D characteristics (42,43). Metformin is commonly used to treat early T2D in young adults; however, its role in the prevention of HFD-induced T2D in the older adults, and its interaction with different fat content diets feeding are not well-defined. Herein, we demonstrated that the metformin treatment significantly reduced glucose intolerance, hepatic steatosis, and inflammation in adipose tissue in older mice, suggesting that metformin is also effective to suppress HFD-induced metabolic dysfunctions in the older adults. The impact of metformin to reduce metabolic dysfunctions was more prominent in HFD-fed mice compared to LFD, suggesting that metformin differentially interacts with diets to regulate metabolic functions. Cognitive function often declines in older adults (44,45); and obesity further increases the risk of cognitive decline. Interestingly, we show that metformin treatment significantly improved the cognitive function in the older mice, suggesting that metformin’s effects are extended beyond the metabolic improvements, and further support the notion that metformin can be a beneficial therapy for prevention and treatment of aging-related health ailments including suppressed cognitive function.

Higher inflammation is linked with increased risk of metabolic dysfunctions like T2D and cognitive decline in the older adults (46), and leaky gut is one of the key factors to stimulate inflammation. Leaky gut appears due to compromised intestinal barrier function such as reduced thickness of mucus layer and less tight-junction protein formation (18). Interestingly, we found that metformin treatment significantly increased mucin expression in the intestine (colon) of older mice, over the tight-junction proteins, suggesting that metformin action to reduce leaky gut may be through increased mucin formation to reduce gut leakiness. The increase in mucin was associated with an increase in the goblet cell mass in metformin-treated mice, suggesting that metformin promoted the goblet cell mass which in turn increased mucin formation and reduced leaky gut. We also demonstrated that increased goblet cell mass was associated with increased expression of goblet cell precursor markers such as Spdef, Elf3, Gfi1, and Atoh, suggesting that metformin promoted differentiation of iSCs to form more goblet cells which in turn increased mucin formation and reduced leaky gut and inflammation. The differentiation of iSCs to goblet cells is a multiple-step process and regulated by multiple networks of signaling pathways; however, Wnt signaling is one of the key signaling pathways contributing in this process (47). The suppression of Wnt signaling increases the differentiation of iSCs to form goblet cell precursors, which ultimately form new goblet cell formation. We have seen that the Wnt signaling ligands like Wnt3a and Wnt5a, and their signaling mediator- Axin1 were significantly reduced in metformin-treated intestinal tissues, suggesting that metformin-induced goblet cell mass and increased the expression of goblet cell precursor markers by suppressing Wnt signaling. However, further studies are needed to precisely define how metformin and Wnt signaling interactions promote the differentiation patterns of iSCs to form goblet cells. Although we have looked on the targeted Wnt signaling pathway, it is possible that other signaling pathways, as well as intestinal cellular systems like endocrine cells and immune cells might also have affected by metformin treatment, which can also impact the formation of goblet cells, leaky gut and inflammation phenotype. Further studies are needed to decipher this.

Although metformin’s mechanisms of action are highly debatable, one of the common notions has emerged that the metformin action lies in the gut through the modulation of the gut microbiome. We also observed that the metformin treatment significantly reduced HFD-induced abnormalities in the gut microbiome, suggesting that the beneficial effects of metformin were linked with modulation of the gut microbiome. We also demonstrated that the changes in gut microbiome by metformin not only remain correlational, since our FMT studies demonstrated that the metformin effects to induce goblet cell mass and mucin formation were able to be transferred by transplanting microbiome, suggesting that the gut microbiome changes induced by metformin could play a causal role in promoting goblet cell mass and mucin biology, which in turn reduces leakiness in the older gut. However, the precise mechanism(s) still remains unknown such as how metformin changed the gut microbiome and how these changes led to changes in goblet cells and mucin biology. Microbiome-produced metabolites are the key functional units to impact host cells (48). We found that metformin significantly changed the metabolite profiles in the gut of older mice, irrespective of different dietary consumptions. Interestingly, metformin significantly increased the production of beneficial metabolites such as butyrate and taurine that are known to promote beneficial health outcomes in several aging models (3,49,50). Earlier human studies also demonstrated that metformin treatment in T2D patients promotes butyrate and butyrate-producing bacteria in their gut (51), further supporting that the metformin’s effects on gut microbiome may be through increasing butyrate and butyrate-producing bacteria. However, precise mechanisms by which metformin promotes butyrate-producing bacterial population in the gut need further investigation.

Overall, our studies present compelling evidence that metformin reduced aging-related metabolic dysfunctions, cognitive decline, leaky gut and inflammation by beneficially modulating gut microbiome and metabolome and promoting goblet cell mass and mucin formation in a diet-depending manner. We also defined the mechanism that the metformin suppressed Wnt signaling which is linked to promoting the differentiation of iSCs to form goblet cells, resulting in increased goblet cell mass and mucin formation and reduced leakiness and inflammation in the older gut (Figure 5i). These evidence support that metformin could be used as a therapeutic regimen for aging-related leaky gut and inflammation as well as to ameliorate cognitive decline along with metabolic dysfunctions in older obese adults.

Methods

Animals

The male C57BL/6J mice of 78 weeks (~20 months) of age were purchased from the Jackson Laboratory (Bar Harbor, ME). After 2–3 weeks acclimatization, mice were randomized into four groups (n = 5–7 in each group): (a) LFD, fed with LFD (10 kcal% fat from Research Diets Inc., Cat#: D12450J [matching sucrose to D12492]); (b) LFD-Met, fed with LFD and given 100 mg/kg body weight dose of metformin through drinking water; (c) HFD, fed with HFD (60 kcal% fat from Research Diets Inc., Cat#: D12492); and (e) HFD-Met, fed with HFD along with 100 mg/kg body weight metformin through drinking water. Food and water were fed ad-libitum. Water was changed freshly every day. We choose to give metformin through the water instead of oral gavage to avoid stress and throat wounds in the mice, which are common in long-term studies. Water intake was measured daily. Food intake and body weight were measured weekly. The GTT, ITT, fasting blood glucose, body composition, and mouse metabolic phenotyping were measured, as described below. After 11 weeks of treatments, mice (~23 months old) were euthanized and tissues were collected and stored in −80°C, or indicated otherwise for further analyses. All the animal studies and protocols were approved by the Wake Forest Animal Research Program’s Institutional Animal Care and Use Committee.

GTT and ITT

Oral GTT was performed in mice fasted for 12–14 hours, by ingesting glucose solution (2.5 g/kg body weight) through oral gavage, and measuring blood glucose at before (0 minute) and after 15, 30, 60, and 120 minutes (52). The ITT was performed in ~4 hours fasted mice and intraperitoneally injecting insulin (Humilin @ dose of 0.75U of kg body weight), and measure blood glucose at before (0 minute) and after 15, 30, 60, and 120 minutes of insulin injection. Blood glucose was measured by drawing blood from the tail vein and using Truetrack glucometer system (Nipro Diagnostics). The area under curve (AUCs) were calculated using a formula: AUC (mg h/dL) = (BG [0] + 2 × BG [30] + 2 × BG [60] + 2 × BG [90] + 2 × BG [120])/4 (53).

Body Composition

Total body fat mass and lean mass were determined using EchoMRI (EchoMRI, MRI that Counts, Houston, TX) in live mice, as described in our earlier studies (52).

Indirect Calorimetry

To measure whole-body energy expenditure in live mice, all the mice were individually housed in metabolic chambers of TSE PhenoMaster caging systems and acclimatized for 3 days. The water and food was provided ad-libitum. The energy expenditure and resting metabolic rates were calculated from the volume of oxygen consumption (VO2) and carbon dioxide production (VCO2), by continuous and simultaneous measurements. The ratio of VO2 and VCO2 used to determine the ratio between fat and glucose utilization for energy expenditure in terms of resting exchange ratio (52).

Intestinal Permeability Test

To measure intestinal permeability (leaky gut), mice fasted for 4–6 hours, and then administered 60 mg/100 g body weight of fluorescein isothiocyanate (FITC) dextran (4 kDa) solution. After 4 hours of FITC-dextran administration, blood is collected from tail vein puncture and the concentration of the FITC-dextran was determined in the obtained plasma using fluorescence spectroscopy at 530 nm and the excitation at 485 nm. Concentrations were presented as the percent change in metformin-treated animals compared to their control groups (54).

Morris Water–Maze (MWM) Test

To determine the impact of metformin on cognitive functions in older mice, the MWM test was performed in a 1.5-m-diameter pool with a 10-cm-diameter platform placed in the center. Mice were trained for 1 day with a visible platform and 1 day with both visible and hidden platforms, using four trials each day. Three sets of four trials were done with an interval of at least 2 minutes. Each mouse was allowed 60 seconds to search for the platform. If mouse was unable to locate platform, the examiner guided the mouse to the platform and allowed to rest for 15 seconds. On the day of the test, each mouse was left in the water pool, where platform was removed. The number of passes through the original place of the platform was recorded for 60 seconds. Learning and memory behavior was determined by measuring the number of crossing at the platform in the final trial (55).

Histochemistry

The liver, intestine, and white adipose tissue were collected, washed with PBS, and fixed in 10% formalin. Sections of 0.5-µm thickness were stained with hematoxylin and eosin (H&E). Adipocyte size and distribution were assessed in ~1,000 random adipocytes from each mouse with ImageJ software. Crown-like structures (CLS)—a marker of inflammation in white adipose tissue (56)—were counted in proportionate to the total number of adipocytes in each section. Goblet cell staining was performed using the Alcian Blue/PAS kit (Newcomer Supply, Middleton, WI) following manufacturer instructions. All slides were mounted mounting media (ThermoFisher Scientific), and imaged with AmScope microscope on 20× magnification. The number of goblet cells (stained with blue) per crypt in the colon were quantified.

Real-Time PCR

To determine the impact of metformin in gene expression in intestinal tissues, the total RNA was extracted from snap-frozen tissues using RNeasy kit (Qiagen, Maryland) and reverse transcribed to cDNA using High-Capacity cDNA Reverse Transcription Kit (ThermoFisher Scientific). The mRNA expression of tight-junction proteins (Zo1 and Ocln), inflammatory markers (IL-6, TNF-α, and IL-1β), and markers of goblet cell precursors (Elf3, Tff3, Spdef, Gfi1, Atoh [Math1], and Muc2) were quantified using primers listed in Supplementary Table S1 on real-time PCR system (ABI 7500; Applied Biosystems). Total RNA isolated from 5 to 7 tissues were pooled in three replicates and all reactions were carried out in triplicates. The 18S was used as an internal control. The relative expression was calculated using ddCt method by normalizing with 18S expression, as we published earlier (52).

Western Blotting

To determine the impact of metformin on protein expression of mucin 2, and Wnt signaling mediators, intestinal tissues were homogenized in a homogenization buffer containing 150 mM NaCl, 5 mM EDTA, 50 mM Tris (pH 7.4), 0.5% Triton X-100%, and 1% Nonidet P-40 and protease inhibitor tablet (ThermoFisher Scientific). Homogenized samples were spun at 20,000 × g in a microcentrifuge maintained at 4°C for 10 minutes. Clear supernatants were collected and total protein concentration was determined using BCA kit (Thermo Scientific). The samples containing equal amount of protein (50 µg) were boiled for 5 minutes and resolved on 10% SDS-PAGE gels and transferred onto polyvinylidene fluoride (PVDF) membranes (Sigma–Aldrich). After washing and blocking the membranes with 5% skim milk solution, primary antibodies (Supplementary Table S2) were blotted with an HRP-conjugated secondary antibody. Membrane was developed using the Pierce Fast Western Blot Kit, ECL Substrate (ThermoFisher Scientific) and imaged using Syngene Pxi (SYNGENE). Tubulin was used a loading control and used for normalization of band densities using ImageJ software.

Microbiome Analyses

The fecal microbiome was examined according to our previously described methods (57). Briefly, genomic DNA from 200 mg feces was extracted using MoBio Powerfecal DNA kit (Qiagen, Valencia, CA) per manufacturer’s instructions. The V4 hypervariable region of the 16S rDNA gene was amplified using the universal primers 515F (barcoded) and 806R; the amplicons were purified with AMPure magnetic purification beads kit (Agencourt); the purified products were quantified by Qubit-3 fluorimeter (InVitrogen); and the final amplicon library was generated as per the methods described elsewhere. The library was pooled in equal molar concentrations and sequenced on an Illumina MiSeq platform using 2 × 300 bp reagent kit (Miseq reagent kit v3; Illumina Inc.) for paired-end sequencing. The obtained sequences were de-multiplexed, quality-filtered, clustered, and analyzed using QIIME software package, using the Greengenes database. The microbiome diversity indices such α- and β-diversity, and microbiome composition in terms of major phyla, class, families and genera were compared between metformin and diet groups. LEfSE (linear discriminatory analysis [LDA] effect size) was executed to identify discriminative microbiome features (bacterial taxa) that drive differences in different groups.

Metabolomics Analyses

The untargeted metabolomics was performed in fecal samples extracted in water, as published elsewhere with minor changes (58). In brief, the extracted samples were mixed with a phosphate buffer (pH = 7.4), containing 10% D2O, 0.1 M phosphate, and 0.1 mM Trimethylsilyl propionate (TSP). The samples run on a Bruker Ascend 400 MHz high-resolution NMR instrument (Bruker Biospin, Germany), the NMR data acquired using a 1D first increment of a NOESY (noesygppr1d). The NMR spectra were phased and referenced to TSP in TopSpin 4.06 (Bruker BioSpin, Germany). The NMR spectra were further analyzed in Amix 3.9 (Bruker Biospin) and the metabolites were identified using Chenomx 8.4 (Chenomx Inc). The total intensity normalization method was applied before further data analysis. Principle component, clustering, and random forest analyses were performed to determine significant differences in metabolite signature and most important metabolite differing diet and metformin-treated groups. Volcano graph were plotted to determine the significant differences in metformin-treated and untreated groups on both diet groups. All the analyses were performed using R studio package.

Fecal Microbiome Transplantation

To determine the causal versus the consequential role of the gut microbiome in metformin action, we used gut cleansed mice model to transplant gut microbiome from older mice nontreated and treated with metformin. We choose this model compared to germ-free (GF) mice because GF mice have developmental issues: (a) their intestinal epithelial cells are not fully matured; (b) reconstitution of their gut microbiota creates dramatic changes in cell turnover of their intestinal epithelia; (c) old germ-free mice are not available since their life span is shorter than that of conventionally raised mice; (d) developing old GF mice is not cost-effective; (e) the intestinal phenotype in old GF mice is not known; and (f) GF mice have fewer goblet cells with increased mucin production, and thus have an abnormal phenotype for this study. We depleted the gut microbiome using an antibiotic solution (Ampicillin [1 g/L], Metronidazole [1 g/L], Neomycin [1 g/L], Vancomycin [0.5 g/L], and nonsugar sweeteners [3 g/L]) in drinking water for 4 days, following by orally administering polyethylene glycol (PEG) cleansing. One hour fasted mice were administered four doses PEG (200 µL PEG at 425 g/o) at every 20 minutes intervals. After 4 hours of the last dose of PEG, fecal slurry (200 µL; prepared by dissolving 500 mg of cecal contents of nontreated and treated old mice in 5 mL reduced PBS supplemented with 0.1% Resazurin and 0.05% L-cysteine-HCl in an anaerobic chamber) was given to corresponding groups. Then, three more doses were given once a day for additional 3 days by administering freshly prepared microbiome slurry. Fecal samples were collected for microbiome analyses. After 1 week, mice were euthanized and intestinal tissues were collected for gene and protein expression and histochemistry.

Statistical Analyses

Values presented throughout the manuscript are mean and standard error of the mean (SEM) for five to seven mice in each group and include a minimum of three to five replicates. The data of physiologic and metabolic measures, gene expression, microbiome alpha-diversity indices, bacterial abundance, and other measures were compared using a two-tailed unpaired student t-test when comparing two groups or Kruskal–Wallis test followed by pair-wise post hoc comparison for comparing more than two groups. Unless otherwise stated, all the values presented herein are means ± SEM. p < .05 was considered statistically significant unless specified.

Supplementary Material

Supplementary data are available at The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences online.

Supplementary Figure S1. Impact of metformin treatment and LFD/ HFD feeding on metabolic measures of older mice. (a-c) Insulin tolerance test, (a), the area under curve (AUC) (b), and percentage change in blood glucose during ITT of older mice treated with metformin and fed with LFD and HFD compared to their controls. d-g) Food intake (d), water intake (e), fat mass (f), lean mass (g), fasting blood glucose (h), total energy expenditure (i), and RER (j) were not significantly impacted by metformin treatment in the older mice fed with LFD and HFD compared to their nontreated controls. Values are mean of n = 5–8 mice per group ± SEM (error bars). Statistical significance (p values <0.05) were obtained using Student’s t-test and/or ANOVA. Values with ‘ns’ are not significant.

Supplementary Figure S2. Metformin modulated gut microbiome composition. (a-d) Metformin treatment modulated gut microbiome in terms of □-diversity indicated by phylogenetic degree (PD) whole tree (a), Chao1 (b), Observed OTUs (c) and Shannon index (d) in the gut of older mice compared to their controls. (e) The abundance of microbial composition was significantly distinct in metformin-treated versus untreated, as well as mice fed with LFD and HFD. Values with *p < .05, **p < .001 are statistically significant.

Supplementary Figure S3. FMT of metformin-treated microbiome transfer significantly microbiome signature in the gut of recipient mice. a-f) Transplantation of the microbiome from metformin-treated mice to recipient mice show significantly different microbiome signature in terms of α-diversity (PD whole tree, Chao1, Observed OTUs and Shannon index), major phyla (e) and genera (f) compared to their controls. g) The differential abundance of microbiome signature (f) and microbial genera (g) was changed in metformin-treated compared to untreated controls. Values are mean of n = 5–8 mice per group ± SEM (error bars). Values with *p < .05, ***p < .001 are statistically significant.

Funding

This study was supported by the National Institutes of Health—K01AG059837 (J.J.), RF1AG054474, U01AG060897, R01DK103531 (J.D.), R01DK081842 (D.A.M.), R01AG059416, U13AG040938, R01AG052419, U24AG058556, KL2TR001421 (S.B.K.), R01AG018915, R01AG045551, U24AG059624 (D.W.K.) and the Pepper Older Americans for Independence Center (P30AG21332), and the Department of Defense—W81XWH-18-1-0118 and W81XWH-19-1-0236 (H.Y.), as well funds and services provided from the Center for Diabetes, Obesity and Metabolism, Wake Forest Baptist Medical Center, and the National Center for Advancing Translational Sciences (NCATS), the National Institutes of Health-funded Wake Forest Clinical, and Translational Science Institute (WF CTSI) through Grant Award Number UL1TR001420.

Conflict of Interest

None reported.