Effect of Diet on the Gut Microbiota: Rethinking Intervention Duration
Abstract
:1. Introduction
2. Acute Dietary Exposure and the Gut Microbiome
2.1. The Gut Microbiota Responds Rapidly to Dietary Changes
2.2. Effect of Short-Term Dietary Interventions on the Gut Microbiota
2.3. The Impact of Probiotics on Microbial Communities Is Individualised and Transient
2.4. Prebiotics Induce Changes in Microbial Composition and Metabolite Production
3. Long-Term diet and the Gut Microbiome
3.1. Evidence for Long Lasting Effect of Diet on the Gut Microbiome
3.2. Capturing Long-Term Effect of Diet on the Gut Microbiota
3.2.1. Dietary Diversity
3.2.2. Singular and Combined Nutrients
3.2.3. Dietary Indices
4. Limitations of Knowledge and Recommendations for the Future
4.1. Increasing Emphasis on Habitual Diet Prior to Dietary Interventions and Analyses
4.2. Nutrient Centred Designs vs. Whole Food Approaches to Dietary Interventions
4.3. Symbiotics Provide an Opportunity to Selectively Alter Microbiome Composition
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Primary Author | Year | Organism | Participants | Design | Dietary Data | Dietary Investigation | Length | Faecal Sample | Post-Intervention Faecal Sample | Change to Microbiome |
---|---|---|---|---|---|---|---|---|---|---|
Short-term dietary interventions | ||||||||||
C. Thiass [22] | 2014 | Mouse | 10 | Longitudinal | NA | Circadian rhythm: Ad libitum intake, for two light-dark cycles (12 h light, 12 h dark) | 2 days | Every 6 h for two days | No | Significant (p < 0.05) diurnal fluctuations in the abundance of more than 15% of all bacterial operational taxonomic units (OTUs). |
D. Zeevi [63] | 2015 | Humans | 800 | Longitudinal | FFQ, daily 24-h records | 6898 habitual meals (total), and standardised meal per day | 1 week | once | NA | People eating identical meals presented variability in post-meal blood glucose response. |
G. Wu [6] | 2011 | Humans | 10 | Randomised, controlled feeding study | NA | Two treatment groups: (1) high-fat/low-fibre diet; (2) low-fat/high-fibre diet | 10 days | 10 days | No | Microbiome composition changed within 24 h of initiating a high-fat/low-fibre or low-fat/high-fibre diet, but enterotype remained stable throughout. |
A. Johnson [35] | 2019 | Humans | 34 | Longitudinal | daily 24-h food records | Habitual diet | 17 days | 17 days | NA | Dietary diversity associates with microbiome stability. Daily dietary intake and microbiome composition are highly variable and personalised. |
M. Ukhanova [64] | 2014 | Humans | 18,16 | Two controlled feeding, randomized, crossover studies (almond or pistachios) | NA | Three treatment groups: (1) no nuts; (2) 1.5 servings/d either almonds or pistachios; (3) 3 servings/d of either almonds or pistachios. 18-day intervention period. Inbetween: 2-week washout period. | 18 days | 6× samples: first and last day of each treatment period | No | Pistachio consumption had a greater impact on gut microbiota composition than almond consumption, including an increase in the number of potentially beneficial butyrate-producing bacteria. Pistachio consumption was associated with a decrease in the number of lactic acid bacteria. |
L. David [18] | 2013 | Humans | 11 (9 both diet arms) | Cross-over | Daily diet log with visual serving size portion guide, National Cancer Institute’s Diet History Questionnaire II (DHQ) | Two treatment groups: (1) Plant-based diet (5-days); (2) Animal-based diet (5-days). Prior to intervention: 4-days baseline habitual diet. Between: 6-days washout period. Post: 6-days washout period. | 20 days | One sample a day: three baseline days and 2 days on each experimental diet selected. | Collected for 6 day washout period post each diet study arm | Short-term consumption of diets composed entirely of animal or plant products alters microbial community structure and overwhelms interindividual differences in microbial gene expression. However, microbiota composition returned to baseline within 3 days post intervention. |
J. Karl [65] | 2017 | Humans | 81 | Randomized, controlled, parallel, controlled feeding | The Three-Factor Eating Questionnaire (weeks 2, 8), visual analog scales for hunger, satiety, prospective consumption, and diet satisfaction (weekly) | Two treatment groups: (1) whole grain diet; (2) refined grain diet. Prior to intervention: 2 week run in | 6 weeks | All stools produced over 72 h during diet arm | No | Alpha-diversity and beta-diversity differed between groups at baseline (P < 0.05) but not after the intervention. Relative abundance of En- terobacteriaceae decreased and butyrate-producing Lachnospira and Roseburia increased in the WG compared with in the RG. |
Y. Sanz [66] | 2010 | Humans | 10 | Preliminary | NA | Gluten-free diet (GFD) | 30 days | Not reported | No | Numbers of beneficial bacteria decreased, while numbers of unhealthy bacteria increased parallel to reductions in the intake of polysaccharides after following the GFD. |
F. De Filippis [67] | 2015 | Humans | 153 | Longitudinal | 7-day food record | Three habitual diet groups: (1) Omnivore (n = 51); (2) vegetarian (n = 51); (3) vegan (n = 51) | 3 weeks | 3 samples: 1 per week | NA | High-level consumption of plant foods are associated with beneficial microbiome-related metabolomic profiles. Significant associations were detected between consumption of vegetable-based diets and increased levels of faecal short-chain fatty acids, Prevotella and Firmicutes. |
J. Kaczmarek [68] | 2019 | Humans | 18 | controlled feeding, randomized, crossover study | NA | Treatment group: 200 g broccoli and 20 g daikon radish per day. Control: traditional American diet excluding all brassicas. Treatment/control period: 18 days; between: 24-day washout | 60 days | 3× samples: baseline, end of each treatment period | No | Broccoli consumption decreased the relative abundance of Firmicutes by 9% compared to control (p < 0.05), increased the relative abundance of Bacteroidetes by 10% compared to control (p < 0.03) and increased Bacteroides by 8% relative to control (p < 0.02). |
S. Duncan [69] | 2016 | Humans | 19 | Experimental | NA | Two treatment groups: (1) high protein/medium carbohydrate (4weeks); (2) high protein/low carbohydrate (4 weeks). Prior to intervention: maintenance diet (3 days) | 9 weeks | 3× samples: 3 post first maintenance period, during last 2 days on each of the main diets | No | No significant change was seen in the relative counts of the Bacteroides, clostridial cluster XIVa, cluster IX, or cluster IV groups. In contrast, the Roseburia spp. and Eubacterium rectale subgroup of cluster XIVa and bifidobacteria decreased as carbohydrate intake decreased. |
W. Russell [70] | 2011 | Humans | 17 | Randomised cross-over | NA | Two treatment groups: (1) high-protein and moderate-carbohydrate diet (HPMC) (4 weeks); (2) high-protein and low carbohydrate diet (HPLC) (4 weeks). Prior to intervention: weight maintenance diet (7 days) | 9 weeks | 3× samples: end of maintenance, HPMC and HPLC diet periods | No | The HPLC diet decreased the proportion of butyrate in faecal short-chain fatty acid concentrations, which was concomitant with a reduction in the Roseburia/Eubacterium rectale group of bacteria, and greatly reduced concentrations of fibre-derived, antioxidant phenolic acids such as ferulate and its derivatives. |
A. Walker [19] | 2010 | Humans | 14 | Randomised cross-over design | NA | Two cross-over treatment groups: (1) Diet high in resistant starch (RS) (3 weeks); (2) Diet high in non-starch polysaccharides (NSP) (3 weeks); Prior to intervention: Initial maintenance diet protein/carbohydrate/fat% 13:52:35 and 27.7 g NSP (1 week). Post intervention: High protein, reduced carbohydrate weight loss (WL) diet (3 weeks). | 10 weeks | Twice each week | No | Relatives of Ruminococcus bromii increased in most participants on the RS diet, accounting for a mean of 17% of total bacteria compared with 3.8% on the NSP diet, whereas the uncultured Oscillibacter group increased on the RS and WL diets. Relatives of Eubacterium rectale increased on RS (to mean 10.1%) but decreased, along with Collinsella aerofaciens, on WL. |
E. Bellikci-koyu [71] | 2019 | Humans | 22 | Randomised parallel, controlled trial | 24-h food recall × 2 (week 0, week 12) | Two treatment groups: (1) 180 mL/day kefir (12); (2) unfermented milk (10) control | 12 weeks | 2× samples: baseline, end of intervention | No | Kefir was associated with a significant increase in the relative abundance of Actinobacteria (p = 0.023) only. No significant change in the relative abundance of Bacteroidetes, Proteobacteria or Verrucomicrobia was obtained. |
A. Cotillard [72] | 2013 | Humans | 49 | Control | 7-day food record with interview by a dietitian | Intervention: energy-restricted high-protein diet (6 weeks). Control: weight-maintenance diet (6 weeks) | 12 weeks | 3× samples: baseline, 6 and 12 week | No | A significant increase of abundance of most gene clusters on energy restricted diet, however on weight-maintenance diet the abundance of 14 species decreased. |
A. Salonen [73] | 2014 | Humans | 14 | Randomised cross-over design for RS and NSP interventions | NA | Two cross-over treatment groups: (1) Diet high in resistant starch (RS) (3 weeks); (2) Diet high in non-starch polysaccharides (NSP) (3 weeks); Prior to intervention: Initial maintenance diet protein/carbohydrate/fat% 13:52:35 and 27.7 g NSP (1 week). Post intervention: High protein, reduced carbohydrate weight loss (WL) diet (3 weeks). | 10 weeks | 4× samples: at end of each diet regimen | No | Multiple Ruminococcaceae phylotypes increased on the RS diet, whereas mostly Lachnospiraceae phylotypes increased on the NSP diet. Bifidobacteria decreased significantly on the WL diet. The RS diet decreased the diversity of the microbiota significantly. The dietary responsiveness of the individual’s microbiota varied substantially and associated inversely with its diversity. |
M. Dao [74] | 2016 | Humans | 49 | Control | 3× 7-day food records (prior to baseline, week 6 and week 12) | Intervention: calorie restricted diet (CR) enriched with fibre and protein (6 weeks). Control: weight stabilisation diet (6 weeks) | 12 weeks | 3× samples: baseline, week 6, week 12 | No | Individuals with higher baseline A. muciniphila displayed greater improvement in insulin sensitivity markers and other clinical parameters after CR. |
Long-term dietary studies | ||||||||||
H. Roager [75] | 2014 | Humans | 62 | Parallel randomised control trial | NA | Intervention: ad libitum New Nordic Diet (NND) (n = 36) (24–28 weeks). Control: ad libitum Average Danish Diet (ADD) (n = 26) (24–28 weeks). Prior to intervention: ADD (7–10 days) | 6 months | 2× samples: baseline, end of intervention | No | Negative association between Prevotella spp. and Bacteroides spp. did not reveal significant changes in 35 selected bacterial taxa resulting from the dietary interventions. |
L. David [5] | 2014 | Humans | 2 | Longitudinal | daily 24-h food records | Habitual diet | 1 year | Subject A: day 0–364. Subject B: day 0–252 | NA | Human gut microbial landscapes are generally stable, but they can be quickly and profoundly altered. |
S. Smits [76] | 2017 | Humans | 188 | Longitudinal | NA | Habitual hunter-gatherer diet of the Hadza tribe, Tanzania | >1year | 350 samples | NA | Annual cyclic reconfiguration of the microbiome; some taxa became undetectable only to reappear in a subsequent season. Comparison of the Hadza data set with data collected from 18 populations in 16 countries reveals that gut community membership corresponds to modernization. |
Cross-sectional dietary studies | ||||||||||
N. Griffin [77] | 2016 | Humans | 170 (34 CRON, 198 AMER) | Cross-sectional | Food journals | Habitual dietary patterns (DP): (1) chronic calorie restriction with optimized intake of nutrients (CRON); (2) without prescribed or self-imposed dietary restrictions (AMER). | NA | 1 sample | NA | AMER displayed less diverse faecal microbiota than those of individuals adhering to CRON. |
D. McDonald [78] | 2018 | Humans | >10,000 | Cross-sectional | FFQ, primary diet survey | Habitual diet | NA | 1 sample | NA | The diversity of plants consumed are associated with microbial diversity with improved explanatory power vs. categorical variables (such as veganism). |
C. Le Roy [79] | 2019 | Humans | 916 | Cross-sectional | FFQ | Beer, cider, red wine, white wine, spirits and total alcohol (sum) | NA | 1 sample | NA | Red wine consumption was positively associated in a frequency dependent manner with alpha-diversity with even rare consumption displaying an effect |
J. Shikany [80] | 2019 | Humans | 517 | Cross-sectional | FFQ | Habitual dietary patterns (DP) based on factor analysis: (Factor 1) ‘Western’ pattern (processed meats, refined grains, potatoes, eggs, sweets and salty snacks); (2) (Factor 2) ’prudent’ pattern (fruits, vegetables, nuts, fish, chicken and turkey without skin) | NA | 1 sample | NA | Greater adherence to the Western pattern was positively associated with families Mogibacteriaceae and Veillonellaceae and genera Alistipes, Anaerotruncus, CC-115, Collinsella, Coprobacillus, Desulfovibrio, Dorea, Eubacterium, and Ruminococcus, while greater adherence to the prudent pattern was positively associated with order Streptophyta, family Victivallaceae, and genera Cetobacterium, Clostridium, Faecalibacterium, Lachnospira, Paraprevotella, and Veillonella |
M. Claesson [81] | 2012 | Humans | 178 | Cross-sectional | FFQ | Habitual dietary patterns (DP): (1) low fat/high fibre; (2) moderate fat/high fibre; (3) moderate fat/low fibre; (4) high fat/low fibre. Residential location was also considered (community vs. long-term care homes) | Na | 1 sample | NA | The healthy food diversity index (HFD23) positively correlated with three microbiota diversity indices and all four indices showed significant differences between community and long-stay subjects indicating that a healthy, diverse diet promotes a more diverse gut microbiota. |
G. Wu [6] | 2011 | Humans | 98 | Cross-sectional | FFQ × 1, 24-h food record × 3 | Habitual diet | NA | 1 sample | NA | 72 and 97 microbiome-associated nutrients were identified in 24-h recall and FFQ. Long-term diet was correlated with enterotype clustering. |
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Leeming, E.R.; Johnson, A.J.; Spector, T.D.; Le Roy, C.I. Effect of Diet on the Gut Microbiota: Rethinking Intervention Duration. Nutrients 2019, 11, 2862. https://doi.org/10.3390/nu11122862
Leeming ER, Johnson AJ, Spector TD, Le Roy CI. Effect of Diet on the Gut Microbiota: Rethinking Intervention Duration. Nutrients. 2019; 11(12):2862. https://doi.org/10.3390/nu11122862
Chicago/Turabian StyleLeeming, Emily R, Abigail J Johnson, Tim D Spector, and Caroline I Le Roy. 2019. "Effect of Diet on the Gut Microbiota: Rethinking Intervention Duration" Nutrients 11, no. 12: 2862. https://doi.org/10.3390/nu11122862