Regular consumption of lacto-fermented vegetables has greater effects on the gut metabolome compared with the microbiome

Abstract

The industrialisation of Western food systems has reduced the regular consumption of lacto-fermented vegetables (LFV). Consuming LFV may exert health benefits through the alteration of the gut microbiome, but the mechanisms involved remain unclear. To start understanding the possible benefits of LFV, we compared faecal microbial diversity and composition, as well as dietary habits between individuals who regularly consume LFV (n = 23) and those who do not (n = 24). We utilised microbial DNA amplicon sequencing (16S rRNA and ITS2) and untargeted metabolomics (LC-MS) to analyse stool samples. Study participants also provided three consecutive days of dietary data. Results show minor effects on microbiome composition; with the enrichment of a few microorganisms potentially associated with vegetable ferments, such as Leuconostoc mesenteroides and Rhodotorula mucilaginosa (P < 0.05), in LFV consumers. However, LFV consumption had greater effects on the faecal metabolome, with higher abundances of butyrate, acetate, and valerate (P < 0.05) and significantly greater metabolome diversity (P < 0.001). Overall, the observations of minor changes in the faecal microbiome and greater effects on the faecal metabolome from LFV consumption warrant further investigations on the health significance of LFV as regular components of the daily diet in humans.

Keywords: dietary diversity; fermented foods; gut metabolome; gut microbiome; lacto-fermented vegetables; short-chain fatty acids.

Figure 1.

LFV consumers display only minor differences in background diet compared to non-consumers. (A) The food trees are phenetic representations of dietary groups for multivariate analysis of 24-hour food records across three consecutive days. Outer edges represent the relative abundance of each food. (B) Volcano plot showing results from differential abundance analysis in dietary composition between consumers and non-consumers – X axis shows log2 fold changes (FC) and Y axis shows -log10 P-value (−log10 > 1 represents P < 0.05). (C) The majority of fermented vegetables consumed came from locally produced sources or were homemade. (D) Alpha diversity analysis showing higher food diversity in fermented vegetable consumers – ** indicates P-value ≤ 0.01 (E) Healthy Eating Index Score (59 out of 100 for LFV consumers and 55 out of 100 for non-consumers (HEI-2015).

Figure 2.

Gut bacteriome shows minor differences between LFV consumers compared to non-consumers (A) Alpha diversity analysis shows no significant difference between groups. (B) Distances from centroid show no differences in inter-individual variation in bacterial composition. (C) Weighted Bray–Curtis distances between the consumers and non-consumers. (D) Volcano plot reveals microbes commonly found in LFV such as Leuconostoc mesenteroides – X axis shows log2 fold changes (FC) and Y axis shows – log10 P-value (−log10 > 1 represents P < 0.05).

Figure 3.

Gut mycobiome composition between groups (A) Alpha diversity analysis shows no significant difference between groups. (B) Distances from centroid show no differences in inter-individual variation in fungal composition. (C) Weighted Bray–Curtis distances show no significance between the consumers and non-consumers. (D) Volcano plot reveals fungal genera and species found in the consumers of LFV – X axis shows log2 fold changes (FC) and Y axis shows -log10 P-value (−log10 > 1 represents P < 0.05). No fungi were found to differentiate the non-consumers.

Figure 4.

LFV consumers display a distinct faecal metabolome. (A) Box plots show high faecal metabolome diversity in the consumers. (B) PLS-DA model shows distinct separation in the faecal metabolome between the two groups, confirmed by permutation test statistic. (C) Volcano plot reveals discriminant faecal metabolites found the consumers and non-consumers of fermented vegetables – X axis shows log2 fold changes (FC) and Y axis shows -log10 P-value (−log10 > 1 represents FDR ≤ 0.05). (D) Box plots show relative abundances of short-chain fatty acids – valeric acid, butyric acid, and acetic acid, to be higher in the consumers, while propionic acid showed no statistical significance between the two groups: ** indicates P-value ≤ 0.01; * indicates P-value ≤ 0.05.

Figure 5.

Co-occurrence probability networks between bacterial taxa and metabolites found in the LFV consumers and non-consumers. MMVEC analysis considering only the highest positive conditionals found (4.0–4.43). (A) Consumers demonstrate stronger but fewer interactions with butyric acid, while (B) non-consumers demonstrate more interactions with butyric acid and acetic acid, but strongest interactions within the latter. Color code in the shape of the node represents bacterial phylum. Edge thickness represents conditional or interaction (co-abundance) strength; node size represents degree of connectivity.