A single-center, single-arm, open-label, proof-of-concept study, testing the effect of guar gum on microbiota metabolism and adaptation, was performed in healthy men. The study consisted of pre-administration and 18-day administration phases (Figure 1). The following outcomes were measured during evaluation periods pre-administration, at initial administration and late administration: (a) anal gas evacuations (number/day); (b) subjective (digestive sensations) and objective consumer measures (bowel function) by daily scales; and (c) fecal gut microbiota taxonomy and metabolic functions by shotgun sequencing (Figure 1). The research was conducted according to the Declaration of Helsinki. The protocol for the study was previously approved by the Institutional Review Board of the University Hospital Vall d’Hebron, [Comitè d’Ètica d’Investigació Clinica, Vall d’Hebron Institut de Recerca; protocol number PR(AG)33/2021B approved February 1, 2021] and all participants provided written informed consent. The protocol was registered with ClinicalTrials.gov (NCT05195255).

The primary aim of the study was to determine the change in gas production (evaluated by daily number of gas evacuations per anus using an event marker) from early versus late administration of guar gum. In a previous study, the number of daily anal gas evacuations during administration of a prebiotic (resistant dextrin) decreased from 21.1 evacuations at initial intake to 13.3 evacuation by 18 days administration (mean difference 7.80 evacuations per day, SD of difference 8.44) (14). Based on these data, it was estimated that a sample size of 12 subjects (paired) would be required to detect a change in the daily number of anal gas evacuations with 80% power and a 5% significance threshold. Participants were recruited following the inclusion and non-inclusion criteria described below (see the section 2.3). The secondary aims were to determine the effect of guar gum administration on the perception of digestive sensations (flatulence, bloating, abdominal distension, borborygmi, and abdominal discomfort/pain), digestive well-being and mood, bowel habit (stool weight, frequency, and consistency), and gut microbiota composition and functionality.

Healthy men without gastrointestinal symptoms or a history of gastrointestinal disorders participated in the study. Given the gender differences in the responses to meal ingestion (15, 16); in this proof-of-concept study only men were included for the sake of homogeneity. All participants were instructed to complete a clinical questionnaire based on Rome IV criteria, and only subjects not fulfilling criteria of functional gastrointestinal disorders (no symptom ≥ 2 on a 0–10 scale and normal bowel habits) were included. This questionnaire has been previously shown to discriminate patients from healthy subjects (17, 18). Non-inclusion criteria were: (i) antecedents of digestive surgery, excluding appendicectomy; (ii) antibiotic, prebiotic, or probiotic consumption during the previous 2 months; (iii) current use of any medications with potential central nervous system effects (e.g., antidepressants, anxiolytics, and opiate pain medications) or drugs that might modify gastrointestinal function; and (iv) change of dietary habits within the preceding 4 weeks.

Guar gum powder (8 g/day; Now Foods; Bloomingdale, IL) was administered in the morning and evening (4 g per dose dissolved in water, juice or milk) during the 18-day administration phase.

During 4-day evaluation periods (Monday to Thursday) in the pre-administration phase (days-7 to -4), initial administration (days 1–4), and late administration phase (days 15–18), participants were put on a standard diet (Figure 1) restricted to the following foodstuffs: (i) meat, fish, fowl, and eggs; (ii) salad; (iii) rice, pasta, and bread; (iv) dairy products; and (v) strained orange juice, tangerine, pears, and apples. This low-residue diet (7 g fiber per day) was complemented with one portion per day of the following: whole crackers, lentils, chickpeas, beans, peas, artichoke, Brussels’ sprouts, banana, peach, or prunes; the portion size of each specific foodstuff was adjusted to contain 12 g fiber (18). The rest of the study participants consumed their habitual diet (Figure 1). During the study, participants were asked to avoid fermented dairy products (yogurts with living strains or probiotics-containing products), and any tablets, pills, or foods supplements containing fiber, pre or probiotics other than those provided. Dietary instructions were reinforced at each visit to ensure adherence to the study.

The following outcomes were measured during the last 2 days of the evaluation periods pre-administration (day-5 and -4), initial administration (days 3, 4), and late administration (days 17, 18; Figure 1).

Descriptive statistics were performed for the parameters measured. The means (±SE) of the variables measured were calculated. The Kolmogorov–Smirnov test was used to check the normality of the data distribution. Parametric normally-distributed data were compared by Student’s t-test for paired or unpaired data. Otherwise, the Wilcoxon signed-rank test was used for paired data, and the Mann–Whitney U test for unpaired data. Correlations between microbial composition and clinical metadata were expressed as Pearson correlation coefficients. In this sense, correlations between microbial clades modulated by guar gum administration and clinical parameters were determined. Tests were performed using a significance level of 5% (two-sided). For clarity, only significant differences are denoted in the figures.

Twelve healthy men (20–40 years age range; 20–29 kg/m² body mass index range) were included in the study. Body weight ranged from 60 to 91 Kg, and hence, the absolute 8 mg daily dose of guar gum administered, corresponded to an actual dose ranging between 133 and 88 mg per Kg body weight per day. All the participants completed the studies, delivered the clinical questionnaires and fecal samples, and were included for analysis.

Before administration (day-5 and -4 of the pre-administration phase), participants registered 7.7 ± 1.0 anal gas evacuations per day using the event marker (Figure 2). At initial exposure (days 3 and 4 of the administration phase), consumption of guar gum was associated with a small but significant increase in the number of anal gas evacuations (10.5 ± 1.9 evacuations/day; p = 0.014 vs. pre-administration; Figure 2). After continous administration (days 17 and 18), anal gas evacuation decreased and reverted to the level before administration (7.1 ± 1.5 evacuations/d; p = 0.013 vs. early administration; Figure 2). No differences were observed between the two consecutive evaluation days during each evaluation period.

Before administration (day-4 and -5), participants marked on the daily scales low scores of digestive sensations (Figure 3). At initial exposure (days 3 and 4), consumption of guar gum was associated with a mild increase in digestive sensation, which was statistically significant for abdominal bloating (p = 0.034 vs. pre-administration; Figure 3). After continuous administration (days 17 and 18), digestive sensations tended to decrease, but the differences between initial and late administration were not statistically significant (Figure 3). Interestingly, flatulence sensation paralleled intestinal gas evacuation and reverted to the level before administration, but the other sensations remained above pre-ingestion level; the differences between late ingestion and pre- ingestion levels were small and did not reach statistical significance, except for abdominal discomfort (p = 0.041). No significant differences were detected between the two consecutive evaluation days during each evaluation period.

Hedonic sensations moved opposite to digestive sensations. Before administration (day-4 and -5), participants reported on the daily scales sensation of digestive well-being and positive mood (Figure 4). At initial exposure (days 3 and 4), consumption of guar gum was associated with a small but significant drop in digestive well-being p = 0.038 vs. pre-administration) and light, non-significant impairment of mood (Figure 4). By the late administration phase (days 17 and 18), both digestive well-being and mood significantly increased (p = 0.003 and p = 0.011 vs. initial ingestion phase, respectively) and returned back to the pre-ingestion levels (Figure 4). No significant differences were detected between the 2 consecutive evaluation days during each evaluation period.

No effects of guar gum on normal bowel habit were observed: the number of stools per day, stool weight, and stool consistency, evaluated by the Bristol stool form scale, were similar before (days -4 and -5), at the beginning (days 3 and 4), and by the end (days 17 and 18) of the administration period (Figure 5).

To study the modulatory effect of guar gum on human microbiota, a shotgun metagenomics analysis of fecal samples of participants collected at pre-and late administration periods was carried out. A taxonomic profiling of the microbiota was first performed. To measure the variability of species within a sample, Chao1 indexes, indicating the number of species represented by only one individual in the sample, were calculated. The global Chao1 index was 103 ± 14 while specific Chao1 indexes for pre- (103 ± 15) and late (104 ± 14) periods showed no major differences. Other alpha diversity estimators were compared, including Shannon, Simpson, and Inverse Simpson indexes (Figure 6A). These coefficients showed similar patterns in the core microbiota, confirming the results from the different analyses (Figure 6B). In general, no statistically significant (p > 0.05) changes in microbial diversity between pre-and late intervention periods were observed due to the high intra-sample variability. To further characterize microbial diversity between samples, beta diversity estimators based on Bray-Curtis distances were computed (Figure 7). Similar to the alpha diversity study, no statistically significant (p > 0.05) differences in the beta-diversity coefficients of samples collected at pre-and late intervention periods were observed (Figure 7A). Microbiota samples were then clustered according to the diversity distances calculated by the Bray–Curtis dissimilarity method (Supplementary Figure S1A). Some samples corresponding to the same intervention period were grouped, although several metagenomes were grouped with samples from different periods corresponding to the same participant. These results reflect the high inter-individual variability in the gut microbiota composition.

The most abundant taxa found in fecal metagenomes included several Bacteroides species (B uniformis, B. dorei, and B. vulgatus) as well as Faecalibacterium prausnitzii, Alistipes putredinis, Ruminococcus bromii, and Parabacteroides distasonis (Figure 8). PCoA plots could not elucidate characteristic patterns in the complete microbiota profiles of samples according to the intervention time (pre-and late administration periods, Supplementary Figure S2A).

Functional analysis of metagenomes revealed no major differences in the gene count of samples collected at pre- (79,562 ± 21,175) and late (78,659 ± 22,213) administration periods. Similarly, no statistically significant (p > 0.05) differences in beta-diversity estimators of samples were observed (Figures 7B,C) and cluster analysis (Supplementary Figures S1B,C) and PCoA ordination plots (Supplementary Figures S2B,C) of functional data confirmed the high inter-individual variability observed in the taxonomic profiling.

Statistical analysis of taxonomic and functional data revealed significant differences in the abundances of some microbial clades (Tables 1–4) and genes (Table 5) after guar gum administration. Up to 35 microbial clades promoted by guar gum administration (Tables 1–4). Among these clades, Parabacteroides, Ruminococcus, Barnesiella, Lachnospira, Akkermansia, Bacteroides, Collinsella and Agathobaculum as well as Oscillibacter sp. 57 20 strain showed significantly (p < 0.05 and p_adj < 0.25) higher abundances at final period than basal period. Therefore, these taxa were increased after the intervention. These clades showed abundance increments higher than 10% although most of these increments were moderate. Linear Discriminant Analysis (LDA) scores revealed differences in the abundances of these taxa among samples corresponding to pre-and late administration periods (Supplementary Figure S3). In contrast, other taxa including Faecalibacterium, Alistipes, Fusicatenibacter, and Eubacterium species showed no significant (p > 0.05) differences in their abundances.

With regard to the functional analysis, the abundances of a total 11,232 microbial gene families and 473 microbial metabolic pathways significantly (p < 0.05 and p_adj < 0.25) higher abundances at final period than basal period (Table 5). These genes and pathways corresponded to Bacteroides, Parabacteroides, Phascolarctobacterium, Collinsella, Oscillibacter, and Ruminococcus species in agreement with the statistical differences determined in the taxonomic analysis (Tables 1–4). These metabolic pathways involved a wide range of functions (Table 5), including amino acid and ribonucleotide biosynthesis and carbohydrate metabolism.

Once statistical differences in microbial taxonomic and functional profiles at pre-and late administration periods were elucidated, statistically significant (p < 0.05) associations between microbial species modulated by guar guam and clinical metadata of participants were determined (Figure 9). In this regard, some microbial species including Akkermansia muciniphila, Bacteroides caccae, and Barnesiella intestinihominis showed negative association with BMI and fecal weight, and positive associations with abdominal discomfort/pain and distension. Similarly, Bacteroides finegoldii positive associations with borborygmi, abdominal discomfort/pain, distension, and flatulence. On the other hand, positive associations between Agathobaculum butyriciproducens and Lachnospira pectinoschiza and participant mood and well-being were found. L. pectinoschiza also showed positive associations with the number of anal gas evacuations.