Timing of food intake impacts daily rhythms of human salivary microbiota: a randomized, crossover study

Abstract

The composition of the diet (what we eat) has been widely related to the microbiota profile. However, whether the timing of food consumption (when we eat) influences microbiota in humans is unknown. A randomized, crossover study was performed in 10 healthy normal-weight young women to test the effect of the timing of food intake on the human microbiota in the saliva and fecal samples. More specifically, to determine whether eating late alters daily rhythms of human salivary microbiota, we interrogated salivary microbiota in samples obtained at 4 specific time points over 24 h, to achieve a better understanding of the relationship between food timing and metabolic alterations in humans. Results revealed significant diurnal rhythms in salivary diversity and bacterial relative abundance ( i.e., TM7 and Fusobacteria) across both early and late eating conditions. More importantly, meal timing affected diurnal rhythms in diversity of salivary microbiota toward an inverted rhythm between the eating conditions, and eating late increased the number of putative proinflammatory taxa, showing a diurnal rhythm in the saliva. In a randomized, crossover study, we showed for the first time the impact of the timing of food intake on human salivary microbiota. Eating the main meal late inverts the daily rhythm of salivary microbiota diversity which may have a deleterious effect on the metabolism of the host.-Collado, M. C., Engen, P. A., Bandín, C., Cabrera-Rubio, R., Voigt, R. M., Green, S. J., Naqib, A., Keshavarzian, A., Scheer, F. A. J. L., Garaulet, M. Timing of food intake impacts daily rhythms of human salivary microbiota: a randomized, crossover study.

Keywords: alpha diversity; beta diversity; diurnal rhythm; eating time; feces.

Figure 1.

The study protocol. A) An overall longitudinal view of the randomized, crossover trial in which each participant (n = 10) was studied under 2 food timing conditions: EE (meal at 2:00 pm) and LE (meal at 5:30 pm) during 1 wk for each condition. B) A summary of what occurred in the last day of intervention in each condition (meal times, saliva samples, sleep hours). Sampling was based on each participant’s usual awakening time. SM = week (SM0: baseline week; SM1: intervention wk 1; SM2: washout wk 2, and SM3: intervention wk 3).

Figure 2.

Relative abundance of significant taxa in EE or LE conditions across time points: phylum TM7 (A); phylum Fusobacteria (B); genus Ruminococcaceae unclassified (C); genus TM7-3 unclassified (D); genus Porphyromonas (E); genus Leptotrichia (F); genus Prevotella (G); genus Lachnospiraceae unclassified (H). RM Friedman test indicated various individual taxa were significantly different across time in EE (A, C, D), LE (B, E, F, G, H) or both conditions (C). *Dunn’s multiple comparison test indicated significant differences between time points in either EE or LE. Error bars = SEM.

Figure 3.

The α-diversity diurnal oscillations in EE vs. LE between time points. Analysis of phylum level α-diversity data revealed a significant main effect of time and a significant experimental condition (EE vs. LE) × time interaction. Bonferroni post hoc tests indicated a significant difference between index groups at 4:00 pm. Two-way RM ANOVA. *P < 0.05 (Table 7). Significant comparisons according to the Shannon index (interaction; P = 0.0044) (A); the Simpson index (P = 0.0395) (B); the richness index (time; P = 0.0061) (C); and the evenness index (interaction, P = 0.0090; and time. P = 0.0434) (D). Error bars = sem.