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. 2021 May 8;113(5):1332-1342.
doi: 10.1093/ajcn/nqaa388.

Remodeling of the gut microbiome during Ramadan-associated intermittent fasting

Junhong Su  1   2 , Yueying Wang  3 , Xiaofang Zhang  2 , Mingfu Ma  4 , Zhenrong Xie  5 , Qiuwei Pan  1 , Zhongren Ma  3 , Maikel P Peppelenbosch  1
Affiliations

Remodeling of the gut microbiome during Ramadan-associated intermittent fasting

Junhong Su et al. Am J Clin Nutr. .

Abstract

Background: Intermittent fasting is a popular dietary intervention with perceived relatively easy compliance and is linked to various health benefits, including weight loss and improvement in blood glucose concentrations. The mechanistic explanations underlying the beneficial effects of intermittent fasting remain largely obscure but may involve alterations in the gut microbiota.

Objectives: We sought to establish the effects of 1 mo of intermittent fasting on the gut microbiome.

Methods: We took advantage of intermittent fasting being voluntarily observed during the Islamic faith-associated Ramadan and sampled feces and blood, as well as collected longitudinal physiologic data in 2 cohorts, sampled in 2 different years. The fecal microbiome was determined by 16S sequencing. Results were contrasted to age- and body weight-matched controls and correlated to physiologic parameters (e.g., body mass and calorie intake).

Results: We observed that Ramadan-associated intermittent fasting increased microbiome diversity and was specifically associated with upregulation of the Clostridiales order-derived Lachnospiraceae [no fasting 24.6 ± 13.67 compared with fasting 39.7 ± 15.9 in relative abundance (%); linear discriminant analysis = 4.9, P < 0.001 by linear discriminant analysis coupled with effect size measurements] and Ruminococcaceae [no fasting 13.4 ± 6.9 compared with fasting 23.2 ± 12.9 in relative abundance (%); linear discriminant analysis = 4.7, P < 0.001 by linear discriminant analysis coupled with effect size measurements] bacterial families. Microbiome composition returned to baseline upon cessation of intermittent feeding. Furthermore, changes in Lachnospiraceae concentrations mirrored intermittent fasting-provoked changes in physiologic parameters.

Conclusions: Intermittent fasting provokes substantial remodeling of the gut microbiome. The intermittent fasting-provoked upregulation of butyric acid-producing Lachnospiraceae provides an obvious possible mechanistic explanation for health effects associated with intermittent fasting.

Keywords: Lachnospiraceae; Ramadan; butyrate; calorie intake; gut microbiota; healthy volunteers; intermittent fasting.

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Figures

FIGURE 1
FIGURE 1
Intermittent fasting–shaped gut microbiota in a young adult cohort. (A) Study design of the cohort (n = 30). During the study, any individual who used antibiotics during fasting or missed 1 or more time points for fecal collection was excluded. Boxplot for body weight (B) and gut microbiota diversity (C) shows the minimum, the first quantile, median, mean (+), the third quantile, and the maximum values for samples at day 0, day 15, or day 30; n = 30 per time point. The diversity of gut microbiota was assessed by calculating the Shannon index. The significance between groups was estimated by using a 2-tailed paired Student t test. (D) A principal coordinates analysis was generated based on the Bray–Curtis distance. Each point corresponds to a community from a single individual. Colors indicate community identity. Statistically significant differences were calculated using an analysis of similarities test; n = 30 per time point.
FIGURE 2
FIGURE 2
Intermittent fasting–shaped gut microbiota in a middle-aged cohort. (A) Study design of the cohort (no fasting, n = 10; fasting, n = 27). Fecal and blood samples were collected before (T1), after (T2), and 1 mo after the cessation of fasting (T3). At T3, 2 participants in the fasting group were not included for analysis due to unwillingness to continue the study. Another 2 participants failed to provide their fecal samples at this time point. (B) Boxplot for gut microbiota diversity, as determined by calculating the Shannon–Weaver index, shows the minimum, the first quantile, median, mean (+), the third quantile, and the maximum Shannon index values for samples at T1 (n = 10 for no fasting compared with n = 27 for fasting), T2 (n = 10 for no fasting compared with n = 27 for fasting), and T3 (n = 10 for no fasting compared with n = 23 for fasting). Significance between groups was estimated by using a 2-tailed paired Student t test for intragroup or Mann–Whitney test for intergroup testing. (C) Principal coordinates analyses on Bray–Curtis dissimilarities of bacterial communities from fasted participants at 3 time points are shown (n = 27 for T1 and T2; n = 23 for T3). Each point corresponds to a community from a single individual. Colors indicate community identity. Ellipses show the 95% confidence intervals. Differences in community shifts using an analysis of similarities test were indicated as well.
FIGURE 3
FIGURE 3
Intermittent fasting–provoked changes of bacterial taxa in the young cohort. (A) Taxa that show alternative abundance before and after fasting are depicted. Taxa with a log linear discriminant analysis (LDA) score above 4.00 as determined by using linear discriminant analysis coupled with effect size measurements (LEfSe). Data shown are the 10Log LDA scores following LEfSe analyses; n = 30 per time point. The hierarchy of the discriminating taxonomic levels was visualized as cladograms allowing taxonomic comparisons before and after fasting. A correlation matrix between microbiota and BMI before (B) or at the end of fasting (C) is depicted; n = 30 per time point. Positive correlations are displayed in blue and negative correlations in red. Color density is proportional to the correlation coefficients (bottom score). The size of the dots is inversely proportional to the P value. Only correlations with a P value less than 0.05 are shown. All the correlations shown are statistically significant (Spearman correlation, P < 0.05).
FIGURE 4
FIGURE 4
Intermittent fasting–provoked changes of bacterial taxa in the middle-aged cohort. (A) The most differentially abundant taxa at the different time points in fasted participants are shown. Taxa that show alternative abundance at 3 time points were determined using linear discriminant analysis coupled with effect size measurements (LEfSe). The hierarchy of discriminating taxa was visualized by cladograms allowing for taxonomic comparisons between the 3 time points (n = 27 for T1 and T2; n = 23 for T3). Data shown are the 10Log linear discriminant analysis score above 4.00 following LEfSe analyses. (B) Boxplot for relative abundance of the order Clostridiales shows the minimum, the first quantile, median, mean (+), the third quantile, and the maximum abundance values for samples at T1 (n = 10 for no fasting compared with n = 27 for fasting), T2 (n = 10 for no fasting compared with n = 27 for fasting), and T3 (n = 10 for no fasting compared with n = 23 for fasting). Significance between groups was estimated by using a 2-tailed paired Student t test intragroup or Mann–Whitney test for intergroup testing. (C) Correlation matrix between microbiota (used in Figure 2E) and changed host physiology (see Table 3) as a consequence of fasting. All the correlations shown are statistically significant (n = 26; Spearman correlation, P < 0.05). (D) Calorie intake measured by FFQs was reduced during fasting. Boxplot shows the minimum, the first quantile, median, mean (+), the third quantile, and the maximum calorie intake values for samples at 3 time points (no fasting, n = 10; fasting, n = 23). Significance between groups was estimated by using a 2-tailed paired Student t test for intragroup or Mann–Whitney test for intergroup testing.
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