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. Author manuscript; available in PMC: 2024 Jun 1.
Published in final edited form as: Exp Gerontol. 2023 Apr 7;176:112164. doi: 10.1016/j.exger.2023.112164

Effects of an Inulin Fiber Diet on the Gut Microbiome, Colon, and Inflammatory Biomarkers in Aged Mice

Noah T Hutchinson 1, Selena S Wang 2, Laurie A Rund 3, Maria Elisa Caetano-Silva 3, Jacob M Allen 1,2, Rodney W Johnson 1,3, Jeffrey A Woods 1,2
PMCID: PMC10159939  NIHMSID: NIHMS1892875  PMID: 37011713

Abstract

Due to the increasing human life expectancy and limited supply of healthcare resources, strategies to promote healthy aging and reduce associated functional deficits are of public health importance. The gut microbiota, which remodels with age, has been identified as a significant contributor to the aging process that is modifiable by diet. Since prebiotic dietary components such as inulin have been shown to impart positive benefits with regards to aging, this study used C57B16 mice to investigate whether 8 weeks on a 2.5% inulin enhanced AIN-93M 1% cellulose diet could offset age-associated changes in gut microbiome composition and markers of colon health and systemic inflammation in comparison to a AIN 93M 1% cellulose diet with 0% inulin. Our results demonstrated that, in both age groups, dietary inulin significantly increased production of butyrate in the cecum and induced changes in the community structure of the gut microbiome but did not significantly affect systemic inflammation or other markers of gastrointestinal health. Aged mice had different and less diverse microbiomes when compared to adult mice and were less sensitive to inulin-induced microbiome community shifts, evidenced by longitudinal differences in differentially abundant taxa and beta diversity. In aged mice, inulin restored potentially beneficial taxa including Bifidobacterium and key butyrate producing genera (e.g. Faecalibaculum). Despite inducing notable taxonomic changes, however, the 2.5% inulin diet reduced alpha diversity in both age groups and failed to reduce overall community compositional differences between age groups. In conclusion, a 2.5% inulin enhanced diet altered gut microbiome α and β diversity, composition, and butyrate production in both adult and aged mice, with more potent effects on β diversity and greater number of taxa significantly altered in adult mice. However, significant benefits in age-associated changes in systemic inflammation or intestinal outcomes were not detected.

Keywords: aging, inulin, microbiome, inflammation, colon

1. INTRODUCTION

The average life expectancy of humans has doubled over the last 200 years (Oeppen et al., 2002), but the length of the health span has not increased equivalently. The last decade of human life is often associated with chronic diseases, morbidity, and reduced quality of life (Crimmins, 2015), driving the rising demand for primary care (Dall et al., 2013). This trend projects to continue indefinitely (Dall et al., 2013), making strategies to combat age-associated diseases and improve the quality of later stages of life of particular public health interest. Concomitant with age-associated diseases and functional deficits are impairments in gastrointestinal barrier function, nutrient absorption, and ‘dysbiosis’ (i.e. impairments in gut microbial diversity, stability, and metabolite production) (Claesson et al., 2011). Age-associated dysbiosis is a contributor to cognitive decline, immune dysregulation, and physical frailty (Mossad et al., 2022; Thevaranjan et al., 2017; Casati et al., 2019). Fortunately, a variety of modifiable behavioral factors, namely diet, can influence gut microbial composition and metabolite production, and consequentially gastrointestinal physiology. Due to its accessibility, bioactivity, malleability, and ability to affect peripheral tissues, the gut microbiota is an attractive target for interventional strategies attempting to decelerate aging and mitigate associated functional deficits.

Dietary fiber has long been identified as a positive contributor to mammalian health through a multitude of metabolic, cognitive, immunologic, and gastrointestinal benefits (Spychala et al., 2018). A fiber-deficient diet has been shown to induce cognitive decline (Shi et al., 2021), while also increasing risk of obesity (Mossad et al., 2022) and colon cancer (O’Keefe, 2019). Inulin is a prebiotic fructooligosaccharide composed of β(2,1) linked fructosyl units that is found in a wide variety of dietary fruits and vegetables, and serves as a substrate for microbial fermentation and short-chain fatty acid (SCFA) production. When supplemented as an additional nutritional ingredient, inulin has been shown to promote gut barrier repair, carcinogen detoxification, blooms of ‘beneficial’ microbes, and butyrate production in multiple species (Beisner et al., 2021; Uerlings et al., 2020; Sauer et al., 2007; Hoffman et al., 2019; Guo et al., 2021; Uerlings et al., 2020). However, its differential effects on gut physiology along with fecal microbiome composition in young adult and old animals have yet to be investigated and compared in a controlled manner.

We sought to investigate the effects of 8 weeks of inclusion of 2.5% inulin in the AIN-93M diet on the gut microbiome, cecal SCFA concentrations, distal colon inflammatory status, and circulating inflammatory biomarkers in adult and aged C57BL/6 mice. In doing so, we analyzed production of SCFA in the cecum in both fasted and post-prandial state, and analyzed the fecal microbiome to draw connections between the two. Additionally, we measured plasma lipopolysaccharide binding protein (LBP) and serum amyloid A (SAA) as markers of gut barrier function and systemic inflammation respectively, distal colon gene expression of a wide panel of metabolic, immunologic, and aging associated genes, and associated intestinal histopathology. We hypothesized that dietary inulin would alter the microbiome and cecal SCFA, offsetting changes in gut physiology and blood biomarkers associated with age.

2. METHODS

2.1. Experimental design and animals.

All mice were housed in an Association for Assessment and Accreditation of Laboratory Animal Care (AAALAC)-accredited facility and all care and handling procedures were approved by the University of Illinois Institutional Animal Care and Use Committee. C57BL/6J mice of both sexes were received at either 1–2 months or 21–22 months of age from an in-house colony and the National Institute on Aging’s rodent colony (Bethesda, MD, United States), respectively. To stabilize inter-individual variability in microbiota composition (Laukens et al., 2016) mice were housed in the same room under a reverse 12h light:dark cycle and fed an AIN-93M diet (Envigo, Indianapolis, IN, United States) and water ad libitum for 8 weeks. During weekly cage changes, used bedding (e.g., litter and feces) from each mouse was collected, homogenized, mixed with clean bedding, and redistributed to each cage within their respective age groups. Weekly body weights were recorded. For fecal sample collection, mice were placed in an empty clean cage four hours after the onset of the dark cycle and fecal samples were collected and frozen. Body weights of adult mice increased over time (p<0.001) and were smaller than aged mice (p<0.001), and were unaffected by the inulin diet (p=0.73), thus are only included in the supplementary and not discussed in the results section (Supplemental Figure 1).

Following the acclimation period, adult (3–4 months old) and aged (23–24 months old) male and female mice were fed a modified AIN-93M diet with 1% cellulose (12.4% protein, 68.3% carbohydrate, 4.1% fat) or the same diet with 2.5% inulin (Envigo, Indianapolis, IN, United States) ad libitum for 8 weeks. Diet formulas are described in Supplemental Table 1. The 8 treatment groups comprised the 2 × 2 × 2 factorial arrangement of age (adult and aged), diet (0 or 2.5% inulin), and sex (male or female). Mice were euthanized four hours after the onset of the dark phase by CO2 asphyxiation and trans-cardially perfused with sterile ice-cold phosphate buffered saline (PBS). Blood was drawn via cardiac puncture, and gut tissues were collected and either snap frozen or placed in fixative for histological processing. Cecal contents were collected, weighed, diluted 1:5 with 6.25% metaphosphoric acid (e.g., 4 mL acid per 1 g gut contents), and stored at −20°C until SCFA analysis.

2.2. Fecal DNA isolation and microbiome analysis.

Fecal samples were collected both pre- and post-intervention. Fecal DNA was isolated with a Powersoil Pro Kit (Qiagen, MD) and concentrations of resultant solutions were measured on a qubit fluorometer with high sensitivity dsDNA reagents. Samples were then diluted in DEPC water and the V3-V4 region of the 16s rRNA gene was sequenced from fecal DNA on a Miseq Nano. Using DADA2 for phyloseq, reads were truncated at 240 base pairs from each end and filtered at a minimum quality score of 20. Identical sequences were then dereplicated, sequences were merged, and chimeras were removed. Taxonomy was then assigned as amplicon sequence variants (ASVs) using Silva 138.1 taxonomic database. Phyloseq Version 1.37 and Vegan for R were used in all downstream analyses, and DESEQ2 was used to calculate differential abundance with the addition of a pseudocount. In all outcomes aside from alpha diversity and family+genus level differential abundance where DESEQ2 normalization was used, ASVs not present at least 3 times in 20% of the samples were filtered out, and samples were rarefied to even sampling depth. Phylum level abundance was compared via Wilcoxon test on filtered and rarefied data. To correct for multiple comparisons, family+genus taxonomic assignments were considered significantly different at an adjusted p value < 0.001. Alpha diversity was calculated with both Shannon and Chao1 Indices, and beta diversity was calculated and plotted via Bray-Curtis ordination and compared with Adonis PERMANOVA testing. Dissimilarity percentages were calculated using the Simper function from the vegan package.

2.3. SCFA Analysis.

Cecal contents were collected and acidified in 6.25% metaphosphoric acid at both the beginning of the dark cycle (fasted), and 4 hours after onset (post prandial). Acidified cecal contents were analyzed on an Agilent 7890 (Agilent Inc., Palo Alto, CA, United States) gas chromatograph, with an Agilent 5975 mass selective detector and Agilent 7683B autosampler. One microliter of sample was injected in a split mode (15:1), and analyzed on a 30 m HP-INNOWAX column with 0.25 mm inner diameter (I.D.) and 0.25 μm film thickness (Agilent, Palo Alto, CA, United States) with an injection temperature of 200°C, MSD transfer line of 200°C, and the ion source adjusted to 230°C. The helium carrier gas was set at a constant flow rate of 1 ml min−1. The temperature program was 2 min at 70°C, followed by an oven temperature ramp of 10°C min−1 to 190°C and 40°C to 240°C for a final 2 min. The mass spectrometer operated in positive electron impact mode (EI) at 69.9 eV ionization energy in m/z 30–300 scan range in combined scan and selected ion monitoring (SIM) modes. SIM targeted m/z 43, 45, 46, 60, 74. Target peaks were evaluated using Mass Hunter Quantitative Analysis B.08.00 (Agilent Inc., United States) software. Standard curves were generated for 0.1–50 mg L−1 range. At collection, an aliquot of each sample was weighed and used for dry matter (DM) analysis. Concentrations obtained from the chromatographer were then corrected for DM content and expressed as mmol g −1.

2.4. Histological Analyses.

Cross sections of ileum, distal colon, and proximal colon tissue were cut and placed in methacarn fixative prior to being paraffin embedded and mounted by the University of Illinois at Urbana-Champaign (UIUC) Veterinary Diagnostics Lab. Slides were scanned with a nanozoomer (Hamamatsu, Shizuoka, Japan) and resulting images were scored by two separate blinded observers, with the scores being corroborated by a third researcher. Images were given scores from 0-4 for inflammatory infiltrate, goblet cell loss, disruption of architecture, and submucosal infiltrate, and composite scores were created from their total score for each variable, in an adaptation of multiple previously used protocols (Koelink et al, 2018; Erben et al., 2014; Matt et al, 2018). Only composite scores are reported in the present study.

2.5. Distal Colon RT-qPCR.

RNA was isolated from frozen distal colon samples using an RNeasy minikit (Qiagen, MD). cDNA was then prepared using a High-Capacity cDNA Reverse Transcription Kit (Thermo Fisher, Waltham, MA, United States). cDNA samples were then submitted to the UIUC Functional Genomics Unit of the W.M. Keck Center for Fluidigm analysis, using a 96 × 96 chip with taqman primers and reagents. Three technical replicates were run for each combination of sample and assay. After an initial pre-amplification using a pool of all primers, data were acquired using the Fluidigm Real-Time PCR Analysis software 3.0.2 (Fluidigm, San Francisco, CA, United States). Delta CT values from the software were then used to calculate fold changes, of which adult 0% inulin values were then subtracted from each value for visualization.

2.6. Serum lipopolysaccharide binding protein (LBP) ELISA.

Serum LBP is a proxy for gut barrier function as it represents the internal exposure of bacterial lipopolysaccharide (LPS) (Gonzalez-Quintela, 2013). An ELISA kit (Hycult Biotech, Catalog No. HK205-02) was used to quantify LBP in mouse blood serum using the sandwich method. The ELISA was performed following the manufacturer’s instructions. All serum samples were diluted 500x with the provided dilution buffer prior to loading and run in duplicate, with resulting concentrations of LBP (μg/mL) calculated from the standard curve.

2.7. Serum Amyloid A (SAA) ELISA.

An ELISA kit (Biotechne, Catalog no. MSAA00) was used to quantify the inflammatory marker SAA using the sandwich method. The ELISA was performed following the manufacturer’s instructions. All samples were diluted 200x with the provided dilution buffer prior to loading and run in duplicate, with resulting optical density at 450 nm utilized to calculate concentrations (ng/mL) from the standard curve.

2.8. Statistics.

General Linear Model univariate analysis of variance (GLM ANOVA) was performed on data that satisfied parametric assumptions using a 2 (age) x 2 (diet) factor analysis. Post-hoc comparison were performed with Bonferroni correction for multiple comparisons. Serum biomarkers failed to meet parametric assumptions, so they were log10 transformed prior to GLM ANOVA. Gene expression data was also abnormally distributed, but transformations could not fix this, thus they were compared using and aligned rank transformation ANOVA, followed by Tukey’s HSD for pairwise comparisons. Analyses including sex as a factor were also performed for every outcome and reported in the manuscript only when significant. Alpha was set at p ≤ 0.05. All analyses were done with SPSS v27 (SPSS, Chicago, IL). Data are presented as mean ± SE.

3. RESULTS

3.1. Fecal Microbiome.

Aging resulted in a highly significant reduction in fecal microbiome α diversity as determined by Shannon (p=0.007) and Chao1 (p<0.001) indices, indicating reduced community evenness and richness, respectively (Figure 1a, b). Contrary to our hypothesis, the 2.5% inulin diet reduced α diversity both aged and adult animals over the treatment period (time x diet p<0.001 for both indices). Bray-Curtis dissimilarity (beta diversity index) revealed differences in microbial community composition between adult and aged mice regardless of dietary inulin (p=0.001, R2=0.36, dissimilarity percentage-54.7%) (Figure 1c). While inclusion of dietary inulin during the intervention also altered community composition and dissimilarity scores, the effect was more modest (p=0.009, R2=0.035). There was also a slight interaction effect between the two (p=0.036, R2=0.025), indicating that fecal microbiomes from aged mice were less sensitive to the effects of dietary inulin. This is also reflected by a greater post treatment dissimilarity percentage between 2.5% inulin fed mice and 0% inulin fed mice in adult mice (56.3%) versus aged mice (47.7%).

Figure 1. Gut microbiome diversity in aged and adult mice in response to dietary inulin.

Figure 1.

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Alpha diversity metrics which take into account community richness a) Chao 1 Index, and evenness b) Shannon Index. *(with line) indicates a significant (p<0.05) age-induced decrease in both indices. *indicates a significant decrease due to dietary inulin in both indices. c) Bray-Curtis dissimilarity scores indicating highly significantly different microbiomes between aged and adult mice. The 2.5% Inulin diet also affected the microbiome, more so in the adult than the aged mice and the effect was orthogonal. At each timepoint, N = 7, 11, 7, and 7 for adult 0% inulin, adult 2.5% inulin, aged 0% inulin, and aged 2.5% inulin respectively.

Phylum level analysis indicated that, at baseline, an aged microbiome is more represented by the Bacteroidota (38.5%) and Verrucomicrobiota (9.3%) compared to adult mice (22.0% and 1.8%, respectively) (p<0.001 for both). Adult mice exhibited higher abundance of Firmicutes (59.9%) and Actinobacteria (15.6%) than their aged counterparts (51.1% and 0.1%, respectively) (p=0.003 and p<0.001, respectively) (Figure 2a). Differential abundance testing of baseline fecal microbiome samples revealed, 117 amplicon sequence variants (ASVs) from 37 unique family + genus taxonomic assignments that differed between adult versus aged mice. A majority of the microbial taxa that differed by age (n=20) were classified in the Firmicutes phylum (Figure 2b). In adult mice, dietary inulin treatment increased Verrucomicrobiota, which was driven by the increase of the genus Akkermansia, (Figure 2c, Supplemental Figure 2a). The 2.5% inulin diet altered 24 ASVs from 20 unique family/genus assignments in microbiomes of adult mice, compared with only 11 ASVs from 8 family/genus assignments altered in microbiomes from aged mice (Figure 2c,d). Other ASVs which displayed a net change through both cross sectional and longitudinal comparisons in aged and adult mice are predominated by the Firmicutes phylum. Adult mice exhibited decreases in the families Clostridiaceae, Lachnospiraceae and Erysipelotrichaceae, with the genus Clostridium Sensu Stricto 1 also showing a decrease when compared both cross sectionally and longitudinally (Figure 2c, Supplemental Figure 2a). The family Muribaculaceae also showed a net increase (Figure 2c, Supplemental Figure 2a). In aged mice, the families Lachnospiraceae, Ruminococcaceae and Erysipelotrichaceae were particularly sensitive to dietary inulin, as 4 of the genera altered by inulin in both the cross sectional and longitudinal comparison come from these families (Figure 2d, Supplemental Figure 2b). At the genus level, Parasutterella, Bifidobacterium, and Faecalibaculum were significantly increased both longitudinally and cross-sectionally in aged samples, while an unidentified Lachnospiraceae genus decreased through both comparisons. Other genus level changes which occurred between aged pre and post inulin samples include an increase of HT002 from the Lactobacilliceae family and decreases of the genera Dubosiella, Eisenbergiella and an unclassified taxa from the Lactobacillaceae family and the Muribaculaceae family, with another from the Firmicutes phylum from an unknown family or genus (Figure 2d, Supplemental Figure 2b).

Figure 2. Phylum level changes in aging and in response to dietary inulin.

Figure 2.

Figure 2.

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a) Relative major bacterial phylum abundance pre- and post-2.5% or 0% inulin diet, b) differentially altered gut microbiome taxa as a result of aging, c) differentially altered gut microbiome taxa in adult mice as a result of 8 weeks of a 2.5% inulin diet, and d) differentially altered gut microbiome taxa in aged mice as a result of 8 weeks of a 2.5% inulin diet.

3.2. Cecal Short Chain Fatty Acids.

Post-prandial cecal SCFA data have been published in Vailati-Riboni et al (2022) but are presented here aside a different cohort to display the differences between values obtained from samples collected in the fasted state. Fecal samples collected post-prandially exhibited higher concentrations of cecal butyrate (p<0.001), acetate (p=0.001), and propionate (p<0.001) versus samples collected in a fasted state. Aging resulted in decreased post-prandial acetate, irrespective of diet (p=0.02). Measurements in the fasted state did not reveal any effects of aging or dietary inulin on concentration of acetate, propionate, or butyrate (Figure 3). In the post-prandial samples, dietary inulin increased concentrations of butyrate in both age groups (p=0.000), but not acetate (p=0.56, Figure 3). Post prandial propionate was only increased by the inulin diet in aged females (p=0.02, Supplemental Figure 3). Main effects of sex were detected in post prandial acetate (p=0.01) and butyrate (p <0.001). Female mice exhibited reduced post-prandial butyrogenic response to the 2.5% inulin diet, and tended to have lower baseline concentrations of acetate (Supplemental Figure 3).

Figure 3. Cecal SCFA concentrations.

Figure 3.

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(mean±sem) for (a) acetate, (b) propionate, and (c) butyrate as mg/g cecal contents (dry weight) in adult and aged mice in response to an inulin diet. * (with line) indicates significant (p<0.05) difference between fasted and post-prandial samples, indicates significant (p<0.05) difference due to diet (i.e. inulin increased cecal butyrate post-prandial). N = 12,11, 10, and 11 for adult 0% inulin, adult 2.5% inulin, aged 0% inulin, and aged 2.5% inulin in fasted samples, respectively. N = 22, 20, 33, and 17 for adult 0% inulin, adult 2.5% inulin, aged 0% inulin, and aged 2.5% inulin in post-prandial samples, respectively.

3.3. Gut Histology and Gene Expression.

Histopathology of colonic samples failed to reveal effects of age or dietary inulin (Figure 4a). Aged mice exhibited higher distal colon expression of nitric oxide synthase 2 (NOS2) (p=0.001), tumor necrosis factor α (TNFα) (p=0.01), forkhead Box P3 (p=0.01) (FOXP3), and Cyclin Dependent Kinase Inhibitor 2a (Cdkn2a) (p=0.01), but lower expression of Adhesion G protein-coupled receptor E1 (Adgre1) (p=0.03). CDKN2a Interleukin 17a (IL-17a), Chemokine Ligand 2 (CCl2), peroxisome proliferator receptor gamma (Pparg), and transformation related protein 53 (Trp53) tended to be reduced by diet (p=0.06, 0.10, 0.07, and 0.10, respectively). (Figure 4b and Supplemental Table 2).

Figure 4. Diet and age related changes in distal colon gene expression and histopathology.

Figure 4.

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a) Neither aging or dietary inulin altered histological scores in the ileum, distal colon, or proximal colon, b)* indicates mRNA of the respective gene was significantly (p<0.05) altered, with red indicating an effect of age, and blue indicating an effect of diet. + indicates a tendency (p=0.05-0.10), with the same color code. Genes significantly affected by age include Adgre1, Cdkn2a, Nos2, TNFα, and FoxP3. Only Cdkn2a was significantly affected by diet, but CCl2, IL17a, Pparg all showed tendencies toward a diet effect. Means, SDs, and P values are available in Supplemental Table 2. Data are 2^-DDCT – adult 0% inulin 2^-DDCT. N = 11, 14, 18, and 16 for adult 0% inulin, adult 2.5% inulin, aged 0% inulin, and aged 2.5% inulin respectively.

3.4. Serum Markers.

Aging resulted in an increase in plasma LBP (p < 0.000) and SAA (p<0.001) (Figure 5a,b). Dietary inulin increased plasma LBP in aged mice (p<0.05) but did not affect concentrations in adult mice. Further, the 2.5% inulin diet did not affect SAA in either age group but did tend to reduce it.

Figure 5. Effects of age and inulin feeding on blood biomarkers.

Figure 5.

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a) lipopolysaccharide binding protein (LBP) and b) serum amyloid A (SAA). For LBP, N = 10, 8, 12, and 10 for Adult 0% inulin, Adult 2.5% Inulin, Aged 0% inulin, Aged 2.5% Inulin, respectively. For SAA, N = 8, 11, 7, and 4 for Adult 0% inulin, Adult 2.5% Inulin, Aged 0% Inulin, Aged 2.5% Inulin, respectively. Data are log10 concentrations presented as mean ± sem. *signifies a significant effect of age (p<0.001), #signifies a difference between aged CON and aged 2.5% inulin for LBP.

4. DISCUSSION

In this study, we found that a 2.5% inulin-enhanced diet modified fecal microbial composition and SCFA profiles regardless of age. While we identified differential taxonomic responses to inulin that were dependent on age, we were not able to detect any effect of inulin in mitigating age-associated inflammation in the colon or circulation. These results suggest that the microbiota of aged mice is less sensitive to dietary inulin supplementation, and that the downstream physiologic changes resulting from shifts in microbial community structure in response to the 8 week inulin treatment were either not of sufficient duration or magnitude to affect the selected measures, or do not occur at all. The prandial nature of cecal SCFA concentrations suggest their dependence on the immediate availability of dietary fermentative substrate. SCFA, primarily butyrate, function as the major fuel source for colonocytes and can be utilized by other host tissues such as hepatocytes (Wong et al, 2006). In the case of acetate, it may also be consumed by resident microbes (Detman et al, 2019). Lower concentrations in the fasted state indicate that microbial production is likely less potent, but future studies would be needed to understand how SCFA concentrations are influenced by and/or influence rate of utilization by the aforementioned methods. Building off of recent work by Vailati-Riboni et al (2022) which established that dietary inulin and resultant increases in butyrate production were capable of offsetting age-related inflammatory status in brain microglia, we hypothesized that an underlying ‘gut-brain-axis’ of gut-derived signaling was responsible for this neuroimmune regulation. Our expectations were that the same dietary treatment that was able to correct microglial function would be accompanied by parallel regulatory shifts in the gastrointestinal microenvironment, driven by taxonomic and metabolomic alterations to the gut microbiota.

Our observations parallel previous work showing that aged microbiome is less diverse and less sensitive to dietary fiber intervention (Claesson et al., 2011). We hypothesized that inulin would mitigate age-associated differences in microbiota diversity. To the contrary, we found that dietary inulin exacerbated age-associated declines in alpha diversity. Other groups have observed reduced alpha diversity after inulin consumption, but this was done in young transgenic mice with longer treatment periods and/or higher fiber portions (4% and 17.3%, respectively) (Hoffman et al., 2019; Muthyala et al., 2022). Some work in humans has shown inulin consumption to increase microbiome alpha diversity (Kiewiet et al., 2021). However, a meta-analysis compiled by Le Bastard et al concluded that dietary inulin did not affect alpha diversity of microbiomes from healthy adult humans (Le Bastard et al., 2019), while So et al concluded the same with dietary fiber as a whole (2018). Ingesting greater proportions of a singular prebiotic substrate in lieu of a complex food matrix may cultivate a more ‘unidimensional’ community that is preferentially inhabited by microbes capable of reproducing and surviving in an environment rich in inulin, and thus producing butyrate. Yet, the observed increase in cecal butyrate and existing literature citing benefits of dietary inulin including enhanced nutrient absorption (Knudsen et al., 2018), prevention of neurodegeneration (Hoffman et al., 2019; Matt et al., 2018; Vailati-Riboni et al., 2022), and regulation of host metabolism (Hoffman et al., 2019) call into question the functional relevance of this observation alone. Though decreased with aging, alpha diversity has been both positively and negatively correlated with a variety of neurologic and metabolic disorders (Li et al., 2022; Menni et al., 2017), so the physiologic relevance of this measure alone remains unclear. Taken together, the present study and available literature support the notion that the implications of microbiome associated outcomes such as alpha diversity are likely context dependent, and under most circumstances cannot alone substantiate claims regarding the ‘quality’ of a given microbiota.

Markers of gut physiology in this study did not appear to be significantly impacted by dietary inulin. In aged mice, the 2.5% inulin diet resulted in higher plasma LBP but did not affect SAA, while also resulting in increased butyrate and decreased microbial richness. Plasma LBP is often used to indicate endotoxemia potentially due to gut barrier disruption, and is associated with obesity, insulin resistance, chronic inflammation, and dyslipidemia (Lassenius et al., 2011). However, human studies investigating the effects of inulin on LBP have generally shown no effect but have shown a tendency for dietary fiber to increase serum LBP (Mitchell et al., 2021). Studies included in this meta-analysis also reported a decrease in acute phase inflammatory marker C-Reactive Protein (Ojo et al., 2021). Muthyala et al (2022) also showed that dietary inulin did not influence circulating IL-6, IL-1α, or TNFα, but did decrease Chemokine C-X-C motif Ligand 1 (CXCL1) concentrations in both young and old mice. Largely negative results in measurements such as whole tissue rt-qPCR and histopathology may result from the lack of a potent stimulus such as chemically induced colitis for inulin to “overcome”, and the effects of inulin being too subtle to show up in whole tissue measurements or methods designed to detect pathology and not changes at the cellular level. Groups such as Sauer et al. have shown differential gene expression in response to inulin consumption in primary cells isolated from the colonic epithelium, so cell population specific effects may not always manifest upon whole tissue measurements (Sauer et al., 2007).

Many of the inulin-induced taxa level changes observed in fecal microbiomes in the present study serve to corroborate findings from other studies, but relatively few studies investigate taxonomic changes in aged populations. The Firmicutes phylum was the most affected by dietary inulin in both age groups, which agrees with the increase of cecal butyrate production and the findings of Guo et al., which demonstrated an increase in Akkermansia, Bifidobacterium, and Parasutterella genera as a result of once daily inulin gavage (9.5 g/kg/day) (2021). A recent review by Le Bastard et al stated that Bifidobacterium and Faecalibacterium, which increased in aged mice in the present study, are frequently increased due to inulin feeding interventions. Studies included in this review frequently cited that Anaerostipes and Lactobacillus increase, while Bacteroides tend to decrease following inulin consumption (Le Bastard et al., 2019). However, the two included studies which measured fecal SCFA did not record an increase in butyrate. Frequently cited following inulin consumption is an increase in the genus associated with benefits in gastrointestinal function and metabolism, Akkermansia, but this was only observed in adult mice (Depommier et al., 2021). In the absence of confirmed functional outcomes, one could hypothesize that the inulin induced taxonomic increases in Ruminococcus, Bifidobacterium, Faecalibaculum, and Parsutterella genera suggest that the intervention used in this study may benefit aged mice primarily through increased SCFA production, competitive pathobiont exclusion, and tumor suppression, but may not offer benefits with regards to host metabolism or improvements in gut barrier function due to the lack of change in Akkermansia abundance (La Reau et al., 2018;O’Callaghan et al., 2016; Zagato et al., 2020; Henneke et al., 2022; Depommier et al., 2021). It may require intervention prior to aging to maintain optimal ‘flexibility’ and susceptibility to the full extent of positive shifts, as it has been shown before in human participants that long-term dietary patterns correlate more effectively with microbiome composition than do short-term interventions (Wu et al., 2011). Further, though inulin did alter beta diversity in both age groups, it did not seem to induce convergence in dissimilarity scores between adult and aged mice, though it did appear to have a tendency to reduce circulating SAA to concentrations closer to those observed in adult 0% inulin mice. These results suggest the need to pair microbiome changes with corollary functional outcomes to ascertain physiologic relevance, as they may be compositionally orthogonal, but induce convergence when it comes to functional outcomes between age groups. The above taxa based functional hypotheses can only be confirmed once they are verified by studies of this nature.

To date, one other study has compared microbiome and metabolome responses to dietary inulin in mice across multiple age groups (Muthyala et al., 2022). In contrast to the present data which only showed effects of dietary inulin on post prandial butyrate, they observed diet induced increases in fecal acetate, propionate, butyrate, valerate, and isobutyrate. Similar to our data, in this study they observed an increase in Bifidobacterium in aged mice only. However, they saw diet induced increases in Akkermansia and decreases in Streptococcus across all age groups, observations which only occurred in adult mice in the present study. Additionally, their β diversity analysis displayed that diet induced more potent effects on overall composition than did age. These differences may be explained by utilization of a much higher proportion of inulin in the experimental diet (17.3%), measurement of SCFA in the feces, and the use a V1-V9 primer for 16s sequencing.

While informative, it is important to interpret the presented sequencing data with the understanding that the utilized methods have limitations. Sequencing quality in 16s rRNA sequencing often does not allow for species or strain level classifications and does not provide information on functional capacity. Future studies utilizing metagenomic profiling or more sensitive/comprehensive measures of gastrointestinal physiology to investigate whether these changes are detrimental to host health could either support or refute hypotheses surrounding supplementation of dietary inulin to support healthy aging. Given the context dependent nature of many variables within measurements of the gut microbiome, pairing 16s sequencing outcomes with measures of host health status will serve a great utility in making substantive conclusions on the relevance of respective aspects of microbiome status on host health, and aid in the creation of a sort of ‘composite score’ for convenient utilization of microbiome data by clinicians and health-conscious individuals.

In conclusion, a 2.5% inulin enhanced diet altered gut microbiome α and β diversity, community composition, and post prandial butyrate production in both adult and aged mice. These effects were more prominent in adult mice. While genera associated with beneficial health effects such as butyrate production, tumor suppression (Faecalibaculum and Bifidobacterium), SCFA production (Ruminococcus, Faecalibaculum), and competitive exclusion of pathobionts (Bifidobacterium) were enriched in aged mice, significant benefits in age-associated changes in systemic inflammation or intestinal physiology were not detected in the selected outcome measures, and thus ‘anti-aging’ properties could not be ascertained at a functional level. While aged mice may not reap benefits to the extent of adult mice, future studies may need to investigate alterations to specific subpopulations of cells in the gastrointestinal tract or utilize a different battery of functional assays to detect or rule out connections between inulin-induced taxonomic changes with potential ‘anti-aging’ benefits related to nutrient absorption, gut barrier function, regulation of inflammation, and attenuation of cellular senescence.

Supplementary Material

1

Highlights:

  • A 2.5% inulin enhanced diet significantly increased butyrate production and blooms of ‘beneficial’ microbes in the gastrointestinal tract.

  • The effects on the microbiome differed based on age, with the effects being more potent in young adult than aged mice.

  • Adult and aged microbiomes were different at baseline, and while dietary inulin altered composition, it did not reduce dissimilarity between the age groups.

  • None of these changes in microbiome composition or butyrate production resulted in significant changes in conducted measures of gut physiology or systemic inflammation.

Funding:

This work was supported by a National Institutes of Health (R01 AG059622) to RWJ and US Department of Agriculture National Needs Graduate Fellowship (ILLU-971-637) to NTH.

Abbreviations:

SAA

Serum Amyloid A

SCFA

Short-Chain Fatty Acids

LBP

lipopolysaccharide Binding Protein

ASV

Amplicon Sequence Variant

Footnotes

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Credit statement:

This study was conceptualized by RWJ, JAW and NTH. NTH and JAW conducted all formal analyses, data curation, supervision and visualization as well as creating the original draft. NTH and JMA created methodology. All authors contributed to Review and editing, investigation and resources. JMA, RWJ, NTH, and JAW validated reproducibility.

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Supplementary Materials

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NIHMS1892875-supplement-1.pptx (417.2KB, pptx)

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