Temporal Dynamics of the Intestinal Microbiome Following Short-Term Dietary Restriction

Abstract

Short-term dietary restriction has been proposed as an intriguing pre-operative conditioning strategy designed to attenuate the surgical stress response and improve outcomes. However, it is unclear how this nutritional intervention influences the microbiome, which is known to modulate the systemic condition. Healthy individuals were recruited to participate in a four-day, 70% protein-restricted, 30% calorie-restricted diet, and stool samples were collected at baseline, after the restricted diet, and after resuming normal food intake. Taxonomy and functional pathway analysis was performed via shotgun metagenomic sequencing, prevalence filtering, and differential abundance analysis. High prevalence species were altered by the dietary intervention but quickly returned to baseline after restarting a regular diet. Composition and functional changes after the restricted diet included the decreased relative abundance of commensal bacteria and a catabolic phenotype. Notable species changes included Faecalibacterium prausnitzii and Roseburia intestinalis, which are major butyrate producers within the colon and are characteristically decreased in many disease states. The macronutrient components of the diet might have influenced these changes. We conclude that short-term dietary restriction modulates the ecology of the gut microbiome, with this modulation being characterized by a relative dysbiosis.

Keywords: caloric restriction; dietary intervention; dietary restriction; intestinal microbiome; microbiome; pre-operative care.

Figure 1

Study Timeline. Ten participants followed a four-day, calorie and protein restriction diet followed by three days of a normal, unrestricted diet. Stool samples were collected at Baseline, on Day-4, and on Day-7. A total of 10 stool samples were available at Baseline and on Day-7. A total of 6 Stool samples were able to be provided on Day-4.

Figure 2

Alpha Diversity. Average number of observed species was not found to be different between conditions.

Figure 3

Principal component analysis of species abundance after prevalence filtering. Dietary restriction caused unique species composition, while Baseline and Day-7 conditions showed adjacent clustering, representing group similarities.

Figure 4

Network analysis of high prevalent species. A total of 136 high prevalent species are depicted by individual nodes, and each node color represents relative abundance by condition. Edges are significant species correlations (p < 0.05). Edge intensity depicts the value of the correlation coefficient.

Figure 5

Heatmap of significantly different species (FDR p < 0.05). A total of 77 species were found to have differences between conditions (FDR p < 0.05). Species grouped well by condition. Most species present at Baseline decreased in abundance on Day-4 and trended toward baseline levels by Day-7. Several species were unique to the Day-4 condition.

Figure 6

Baseline v. Day-4. Principal component analysis of species present between the two conditions (A). Effect size graph of significantly different species (FDR p < 0.05, effect size > 1) (B).

Figure 7

Principal component analysis of MetaCyc pathway abundance after prevalence filtering. Similar to the findings of taxonomy analysis, dietary restriction created unique clustering on Day-4, while Baseline and Day-7 conditions showed overlap clustering, representing group similarities.

Figure 8

Heatmap of significantly different pathways (FDR p < 0.05). Based on MetaCyc ontology classification, pathways were categorized as biosynthesis (A), degradation (B), or precursor metabolic pathways (C).