Impact of diet on human intestinal microbiota and health.

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Review in Advance first posted online on January 2, 2014. (Changes may still occur before final publication online and in print.)

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Annu. Rev. Food Sci. Technol. 2014.5. Downloaded from www.annualreviews.org by WIB6242 - Universitaets- und Landesbibliothek Duesseldorf on 01/15/14. For personal use only.

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Impact of Diet on Human Intestinal Microbiota and Health ∗

Anne Salonen1, and Willem M. de Vos1,2,3 1

Department of Bacteriology and Immunology, University of Helsinki, 00014 Helsinki, Finland; email: anne.salonen@helsinki.fi, [email protected]

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Department of Veterinary Biosciences, University of Helsinki, 00014 Helsinki, Finland

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Laboratory of Microbiology, Wageningen University, 6703 HB Wageningen, the Netherlands

Annu. Rev. Food Sci. Technol. 2014. 5:6.1–6.24

Keywords

The Annual Review of Food Science and Technology is online at http://food.annualreviews.org

enterotypes, dietary intervention, short-chain fatty acids, bile acids, high-fat diet, Akkermansia muciniphila

This article’s doi: 10.1146/annurev-food-030212-182554 c 2014 by Annual Reviews. Copyright All rights reserved ∗

Corresponding author

Abstract Our intestinal microbiota is involved in the breakdown and bioconversion of dietary and host components that are not degraded and taken up by our own digestive system. The end products generated by our microbiota fuel our enterocytes and support growth but also have signaling functions that generate systemic immune and metabolic responses. Due to the immense metabolic capacity of the intestinal microbiota and its relatively high plasticity, there is great interest in identifying dietary approaches that allow intentional and predictable modulation of the microbiota. In this article, we review the current insights on dietary influence on the human intestinal microbiota based on recent high-throughput molecular studies and interconnections with health. We focus especially on the emerging data that identify the amount and type of dietary fat as significant modulators of the colonic microbiota and its metabolic output.

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Changes may still occur before final publication online and in print

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1. INTRODUCTION


Microbiota: assembly of microorganisms that inhabit a certain habitat such as the human gut 16S rRNA gene component of the 30S small subunit of prokaryotic ribosome used in molecular analyses to determine bacterial phylogeny, i.e., evolutionary relationships Microbiome: refers to the genomes of the microbiota (the metagenome) and is also a synonym for microbiota (the biome of microbes) Enterotypes: specific assemblages of intestinal bacteria that group individual microbiomes into three categories

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Humans are inhabited by a rich consortium of microbes, the majority of which live in the gastrointestinal (GI) tract. The diversity of the intestinal microbiota has been unraveled during the two past decades following the development of molecular methods. These are mainly used for phylogenetic analyses based on 16S rRNA gene sequences, allowing detection and identification of all intestinal microbes, including those that have not yet been cultured. While the pioneering community-level microbiota studies were based on few individuals (Eckburg et al. 2005, Gill et al. 2006, Zoetendal et al. 1998), technological advancements have enabled high-throughput analyses, including metagenome studies of hundreds of individuals using second-generation sequencing technologies and phylogenetic microarrays (Huttenhower et al. 2012; Qin et al. 2010, 2012; Rajilić-Stojanović et al. 2011; Salonen et al. 2012). These studies have confirmed that each adult has a unique intestinal microbiota that is relatively stable and includes thousands of species-level phylotypes. Immediately after birth, babies are colonized with microbes mainly derived from the birth canal and fecal material, or skin, depending on the birth mode (Scholtens et al. 2012). The microbes colonizing the human gut are likely acquired from the mother and other caregivers. Hence, the intestinal microbiome has coevolved with the human genome for a million years, explaining in part its subject specificity and stability. The permanent intestinal colonizers are dominated vastly by Firmicutes (mainly members of the order Clostridiales) and Bacteroidetes (members of the order Bacteroidales). Other subdominant or minor phyla include Actinobacteria, Proteobacteria, Fusobacteria, and Verrucomicrobia. In addition to bacteria, methanogenic archaea and eukaryotic microorganisms occupy the human gut. It is assumed that several hundred species-level bacterial phylotypes assemble to each individual in highly variable proportions, resulting in an individual microbial composition that remains stable in time ( Jalanka-Tuovinen et al. 2011, Rajilić-Stojanović et al. 2013a). The temporal stability of the intestinal ecosystem is likely maintained by host-encoded mechanisms in parallel with colonization resistance, as a balanced climax community is not susceptible to new (invading) species. The temporal variation of the microbiota is mostly due to an altered abundance of existing species instead of a flux in the species composition (Rajilić-Stojanović et al. 2013a). Due to the complexity and uniqueness of each individual’s microbiota, we currently lack a definition for a normal or healthy microbiota. However, two approaches have been undertaken to reduce the complexity of the accumulating microbiota data; they focus on features most relevant for health. One approach has been the assessment of the core microbiota shared across healthy or diseased individuals, potentially representing the principal microbes associated with a given health state (Salonen et al. 2012, Tap et al. 2009). Targeted characterization of these microbes could follow their identification within such a core. However, the definition of the general core microbiota is strongly dependent on the analytical depth and threshold for detecting microbes at low abundance (Salonen et al. 2012), as the relative abundance of common bacteria can vary up to 2,000-fold (Qin et al. 2010). On the basis of a sensitive phylogenetic microarray analysis, a healthy core microbiota of several hundred phylotypes was defined (de Vos & de Vos 2012, Salonen et al. 2012). Another approach is to reduce the dimensionality of the microbiota data by sorting individual microbial profiles into a limited set of categories according to common features. A pioneering study by Arumugam et al. (2011) defined the so-called enterotypes that are specific assemblages of bacterial networks. Three enterotypes have been described and are named after the genera of their main drivers (Bacteroides, Prevotella, or Ruminococcus). These enterotypes are found in the GI microbiota of both healthy and diseased subjects and can be considered high-level solutions of the intestinal ecosystem. Although there has been discussion about the number of enterotypes,

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their existence has been confirmed by the two major international consortia that addressed the human microbiome, the MetaHIT consortium sponsored by the EU and the Human Microbiome Project funded by the NIH. Together, they characterized more than 1,000 subjects (Arumugam et al. 2011, Huttenhower et al. 2012, Wu et al. 2011). With first baseline analysis of the intestinal metagenome’s coding capacity (Qin et al. 2010), the discovery of the enterotypes is a conceptual breakthrough that allows segmentation of subjects according to their intestinal microbiome. The intestinal metagenome surpasses the coding capacity of the human genome by a factor of 100, with now close to 5 million genes (de Vos & Nieuwdorp 2013; Huttenhower et al. 2012; Karlsson et al. 2012, 2013). Although most of the microbial functions are currently unknown, a substantial portion of the intestinal metagenome is involved in food metabolism in parallel with activities involving vitamin synthesis, bioconversion of xenobiotics and polyphenols, immunomodulation, and pathogen exclusion. Hence, the GI microbiota has the remarkable potential to influence the nutritional, physiological, and immunological status of the host (Nicholson et al. 2012, Vipperla & O’Keefe 2012). The high metabolic potential, close proximity with the intestinal mucosa, and intimate interaction with the underlying immune system render the GI microbiota a natural and important actor in human health. Accordingly, the intestinal microbiota has been associated with a wide range of intestinal and systemic diseases, ranging from inflammatory bowel disease (IBD) to metabolic syndrome and allergies (de Vos & de Vos 2012). So far, causality has been demonstrated for only few of these cases (metabolic syndrome and recurrent infection of Clostridium difficile) (van Nood et al. 2013, Vrieze et al. 2012) with the use of fecal transplantation, a useful but imperfect method (de Vos 2013). Various mechanistic explanations for the impact of the intestinal microbiota on disease have been provided. Microbes significantly contribute to systemic diseases, for example, through signal transduction and activation of the mucosal immune system (Carvalho et al. 2012) or via circulating metabolites that reach the hepatic or systemic circulatory system though the portal vein (Wikoff et al. 2009). Diet has long been considered one of the major external modulators of the adult human intestinal microbiota in parallel with medication. The human digestive system cannot digest most of the plant-derived complex carbohydrates included in the cereals, vegetables, and fruits we eat. Instead, our intestinal bacteria encode an arsenal of catabolic enzymes to degrade and ferment a wide range of polysaccharides and glycans of dietary or host origin that enter the colon (Koropatkin et al. 2012). The current medical and nutritional interests in the dietary modulation of the intestinal microbiota stem from the fact that the type and biological activity of the bacterial metabolites released in our gut depend heavily on diet. For example, colonic fermentation of dietary fiber results in the production of short-chain fatty acids (SCFAs) of which butyrate and propionate have well-documented beneficial effects on gut and systemic health (Cummings & Macfarlane 1991) (see Section 4.1 for more details). Conversely, bacteria can convert dietary protein into metabolites that increase the risk for atherosclerosis (Koeth et al. 2013) and cancer (Vipperla & O’Keefe 2012) (see Section 4.2 for more details). Hence, intestinal bacteria appear pivotal in mediating the health effects of foods. Only very recently have community-wide molecular analyses been performed to obtain empirical data on dietary influences on the microbiota. A series of studies have shown that in laboratory mice, a change of diet leads to large and rapid changes in the composition of the microbiota (Everard et al. 2011, Faith et al. 2011, Hildebrandt et al. 2009, Turnbaugh et al. 2009b, Zhang et al. 2009). In humans, the intestinal microbiota appears to respond to dietary shifts in a largely individualistic and less pronounced manner (see Section 3.2). In inbred and age-standardized laboratory animals, the sources of variation in the microbiota are limited principally to the experimental diets, whereas in humans, a notably smaller proportion of the www.annualreviews.org • Impact of Diet on Intestinal Microbiota


Short-chain fatty acids (SCFAs): bacterial metabolites such as acetate, propionate, and butyrate that are derived mainly from carbohydrate fermentation

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% of total variance explained

70 60 50 40 30 20 10 0

Subject

VLCD

NSP

RS

LGG

Intervention diet Figure 1 Impact of dietary interventions on the total microbiota variation, estimated with the coefficient of determination of the HITChip phylogenetic microarray (Rajilić-Stojanović et al. 2009) data. The variation that is not explained by the subject or diet is attributable to their combined effect and technical noise. Abbreviations and references to intervention trials: LGG, Lactobacillus rhamnosus GG intervention (Lahti et al. 2013); NSP, nonstarch polysaccharide-enriched diet (Walker et al. 2011); RS, resistant starch-enriched diet (Walker et al. 2011); VLCD, very low calorie diet (A. Salonen & W.M. de Vos, unpublished data).

total variance in microbiota is explained by the diet, varying from 300) study reported that stool pH was significantly lower in vegans (average of 6.3) compared to omnivores (6.8) (Zimmer et al. 2012). Correlation analysis between stool pH and culture-based bacterial counts did not identify marked dependence between pH and the amount of Bacteroides spp.; instead, the stool pH showed significant inverse association with the abundance of Enterobacteriaceae (Zimmer et al. 2012). Hence, the true in vivo impact of the pH in controlling the Bacteroides populations remains to be investigated. Another example of the indirect impact of food on the intestinal microbiota involves bile. Bile acids, the major constituents of bile, are cholesterol-derived detergents that play an essential role in the digestion and absorption of fats as well as in the elimination and excretion of numerous waste products from the body. Bile acids are antibacterial and create strong selective forces for the intestinal microbiota, as different bacteria, even within a single species, exhibit differential sensitivity to bile (Begley et al. 2005, Floch et al. 1972, Kurdi et al. 2006). The fat and protein contents of the diet regulate the excretion of bile (Reddy 1981) and can thus indirectly shape the microbiota, as discussed in more detail in Section 4.3. In addition, our diet typically contains www.annualreviews.org • Impact of Diet on Intestinal Microbiota


Bile acids: major constituents of bile produced from cholesterol in the liver and secreted into the duodenum to facilitate fat digestion and adsorption

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Mucins: glycosylated proteins that form gel-like structures in the epithelial lining of the gut

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several presumably antimicrobial substances, such as plant polyphenols. Some of these compounds reach the colon and may affect the ecosystem. Mucins secreted from goblet cells and digestive enzymes of pancreatic origin, together with secretory IgA (Ouwehand et al. 2005), represent substantial polysaccharide and protein sources for the colonic microbes (Barnett et al. 2012, Cummings & Macfarlane 1991). The colonic supply and quality of dietary nutrients, and consequently the digestive enzymes, vary substantially between individuals and throughout time, whereas mucins provide a more stable resource and may constitute half of the carbon flux in the intestinal tract. The utilization of mucus is cooperative as most known intestinal microbes do not have the capacity for all catabolic cleavages required to grow on the mucin. Several Bacteroides spp. and bifidobacteria can degrade the mucin, but only Akkermancia muciniphila can use the mucin as a sole carbon source (Derrien et al. 2004) (see Section 3.3 for more details). Bacteria that we eat in food can at least theoretically contribute to the intestinal microbiota (Table 1). In babies, where colonization of the intestinal tract is still developing, breast milk– derived bacteria readily colonize the gut (Mart´ın et al. 2012). In adults, the well-established microbiota possesses high colonization resistance and low susceptibility to nonindigenous species. Functional foods, especially fermented products and probiotic supplements, are believed to confer their health benefits at least partially through modulation of the indigenous intestinal microbiota. Although most probiotics survive the intestinal tract, they do not alter the community composition, at least in the colon (Kim et al. 2013, Lahti et al. 2013). However, the probiotic activity may, in parallel with direct interaction with the host, involve modification of the indigenous microbiota activity (McNulty et al. 2011). The impact of diet on host gene expression and its possible effects on the microbiota are not in the scope of this review but have been summarized recently by others (Kussmann & Van Bladeren 2011). The studies on the impact of diet on the gene expression of the microbiota have focused on the carbohydrate metabolism of Bacteroidetes (Martens et al. 2009). Transcriptional profiling has confirmed that the substrate-specific, glycan-metabolizing genes are expressed in vivo in an inducible manner. In summary, it is evident that diet introduces numerous and partly interconnected selective forces for the intestinal microbiota far beyond the sole regulation of substrate availability.

3. STRATEGIES TO STUDY THE INTERACTIONS BETWEEN DIET, MICROBIOTA, AND HEALTH 3.1. Habitual Diets to Infer Long-Term and Persisting Effects To explore the dietary impact on the human microbiota, long- and short-term effects can be investigated based on dietary information derived from habitual diets or dietary interventions, respectively. Comparison of animal species or human populations that have different habitual diets shows that vertebrates have a tendency to adapt to the diet so that their digestive capacity, that is, the repertoire of digestive enzymes and related transporters, matches largely the prevailing dietary load (Karasov et al. 2011). In human populations in which adults consume milk, lactase activity does not decline after weaning due to single-nucleotide polymorphisms that maintain lactose tolerance in adults (Enattah et al. 2008). Moreover, the genomic copy number of salivary amylase is positively correlated with the amount of starch in the diet (Perry et al. 2007). As such, it is evident that the diet acts as an ecological driving force also for the microbiota (Walter & Ley 2011), making it adapt to the diet to which it is constantly exposed. Recent molecular analysis of the microbiota of nonlaboratory carni-, herbi-, and omnivorous animals confirms that their gut microbes reflect habitual diet and gut architecture and physiology (Ley et al. 2008, Muegge et al. 2011). 6.6

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The impact of predominant dietary components is apparent in breast-fed babies, whose microbiota specialized in the utilization of human milk oligosaccharides and lactate (Marcobal & Sonnenburg 2012). However, the infant gut microbiome is already abundant with plant polysaccharide-degrading genes before the introduction of solid foods (Hehemann et al. 2010, Koenig et al. 2010, Vaishampayan et al. 2010, Yatsunenko et al. 2012). This suggests that the microbiota reflects evolutionary and possibly epigenetic adaptation and/or maternally acquired metabolic traits in parallel with the ones that reflect recent dietary exposure. A comparison of Italian and African children revealed that the latter were enriched with Bacteroidetes, especially Prevotella spp., at the expense of Firmicutes, and had a significantly lower amount of enterobacteria (De Filippo et al. 2010). The original finding about the enrichment of Prevotella in non-Western microbiomes has been since reproduced in African adults (Ou et al. 2012, Yatsunenko et al. 2012), as well as in Bangladeshi children (Lin et al. 2013). The rural African and Asian diets are rich in dietary fiber and contain 35–40% less energy than their Western counterparts. Hence, there is strong evidence that high levels of Prevotella characterize all microbiomes that are exposed mainly to complex, plant-derived carbohydrates. When the microbiomes of the adult inhabitants of rural communities in Africa, small villages in Amazonas, and metropolitan areas in the United States were compared, marked differences in the bacterial compositions and gene repertoires were detected (Yatsunenko et al. 2012). Reflecting the Western diet, the American microbiomes were enriched with genes degrading amino acids and simple sugars, whereas the starch-degrading amylases were significantly more abundant in developing populations, on the basis of the 26 adults surveyed. In this metagenomic analysis, the non-Western microbiomes did not show overrepresentation of genes devoted to the metabolism of complex carbohydrates or butyrate production (Yatsunenko et al. 2012). However, other studies have found the amount of fecal SCFAs and the capacity for butyrate production to be significantly higher in African inhabitants (De Filippo et al. 2010, Ou et al. 2013). Although true biological differences may underlie the observed differences, they likely also reflect the lower probability of reaching statistical significance in a high-dimensional metagenomic data set compared to targeted quantification studies. Studies have also been carried out on individuals from the same geographic areas and similar cultural backgrounds, but with distinctly different dietary patterns. On the basis of approximately 100 Americans and a false discovery rate of 25% (one out of four detected associations expected to be false-positive), the Prevotella enterotype associated positively with high intake of carbohydrates and simple sugars and negatively with high intake of protein and fat of animal origin (Wu et al. 2011). Further mining of the same data revealed that also Methanobrevibacter, the dominant methanogenic archaeon in the gut, correlated positively with high carbohydrate intake (Hoffmann et al. 2013). Comparisons of microbiomes in omnivores and vegetarians currently include mainly targeted studies that have quantified the dominant and fermentative bacteria, intuitively assumed to be more abundant in vegetarians as a result of high intake of plant-derived polysaccharides. However, the amounts of Clostridium clusters IV and XIVa (Hippe et al. 2011), or the specifically addressed butyrate producers Roseburia spp./Eubacterium rectale (Kabeerdoss et al. 2011) and Faecalibacterium spp. (Liszt et al. 2009), have been found to be significantly lower in vegetarians than in omnivores. Direct comparison of the butyrate-producing capacity of vegetarians and omnivores has yielded mixed results. In an Austrian cohort, the amount and diversity of the butyryl CoA:acetate CoA-transferase gene were the most abundant and variable in vegetarians (Hippe et al. 2011), whereas in an Indian cohort the gene was significantly more abundant in omnivores (Kabeerdoss et al. 2011). The Indian study also examined the associations between the butyryl CoA-transferase gene copy number and dietary intake; the only significant, yet weak, association was observed in www.annualreviews.org • Impact of Diet on Intestinal Microbiota


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Inflammatory bowel disease (IBD): includes Crohn’s disease and ulcerative colitis Parenteral nutrition: feeding a person intravenously, bypassing the digestive system

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fat intake (r = 0.29, p = 0.03), and there was also a tendency for a positive correlation with fiber intake (r = 0.23, p = 0.09). Although not discussed in the paper by Kabeerdoss et al. (2011), it should be noted that the intake of complex carbohydrates was significantly lower in the vegetarians studied compared to the omnivores. This highlights the need to use the dietary information based on actual food intake rather than to rely on predefined dietary groups where the typically large within-group variation easily confounds the study. When the culturable microbiota were studied in more than 300 German individuals, the total bacterial counts were similar in vegans, vegetarians, and omnivores, but the amounts of Bacteroidetes, bifidobacteria, and Enterobacteriaceae were significantly reduced in diets with limited or omitted animal products (Zimmer et al. 2012). Recently, functional implications of microbiota differences related to vegetarian diet have been identified. Vegans and vegetarians did not only have lower fasting baseline levels of red meat– derived proatherogenic trimethylamine-N-oxide (TMAO), but their microbiota also had lower capacity to synthetize it from ingested carnitine (Koeth et al. 2013). This finding provides direct evidence for the postulation that the beneficial or detrimental health effects of particular foods do not only depend on their intake rate but also on the individual’s microbiota. Interestingly, in this American cohort, a high proportion of Prevotella was more common in omnivores than vegetarians and was associated with high plasma TMAO concentration. None of the other studies focusing on vegetarians in Western countries has reported different prevalence or abundance of Prevotella compared to omnivores. However, this may simply reflect the use of targeted methods that did not specifically capture Prevotella, which gained attention only after the introduction of the enterotypes.

3.2 Dietary Interventions Until recently, the impact of diet on the intestinal microbiota was studied mainly in dietary interventions that aim for physiological benefit. Such interventions typically include supplementation of a normal diet with prebiotic or other dietary fibers or a change in the macronutrient load or ratios. Table 2 provides an overview of the documented dietary effects on the intestinal microbiota. The levels of bifidobacteria and butyrate-producing E. rectale/Roseburia group show strong and seemingly generic positive association with carbohydrate intake. In contrast, the other major butyrate-producing taxon, Faecalibacterium prausnitzii, is not affected by most dietary switches but can be specifically stimulated with the intake of fructans. As there are very few published intervention studies on the impact of protein and fat on the human microbiota, we discuss these macronutrients in Section 4, on the basis of recent data from observational studies.

3.3. Impact of Total Energy Supply: Specific Role of Akkermansia muciniphila Even drastic dietary shifts do not seem to profoundly alter the microbiota configuration in adults. After strict adherence to an elemental diet (liquid diet composed of dextrin, amino acids, soybean oil, and micronutrients), low-resolution microbiota profiling showed that the similarity of the microbiota of the treated IBD patients remained comparable to those of healthy controls without dietary change (Shiga et al. 2012). When the same formula was given via parenteral nutrition, the stability of GI microbiota profiles decreased significantly. Notably, however, neither the elemental diet nor parenteral feeding changed the amount of total bacteria or the dominant groups, including Clostridium clusters IV and XIVa (Table 2). These results suggest that the adult intestinal microbiota, even if strongly reduced in diversity, as was the case with the IBD patients (Shiga et al. 2012), has tremendous capacity to resist perturbations. This refers to the existence of resilience systems that allow the microbiota to adapt to an extremely altered nutrient load and still prevent the ecosystem from collapse. 6.8

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Table 2 Summary of selected intervention studies analyzing dietary impact on human microbiota with the use of molecular methods that were used to target the entire or dominant microbiota Main analysis


Diet

Cohort type

method

Main effect on microbiota References

composition

Addition of plant-based polysaccharides

Mainly healthy adults; >10 studies; details have been summarized in Flint et al. (2012b), Scott et al. (2012), and Roberfroid et al. (2010).

Profiling, qPCR,b pyrosequencing, phylogenetic microarray

Summary of findings: Resistant starch: increase in Ruminococcus bromii, Eubacterium rectale and bifidobacteria Fructans (inulin and FOS): Increase in bifidobacteria and Faecalibacterium prausnitzii Non-starch polysaccharides: minor effects

References for original studies can be found in the following reviews: Flint et al. (2012b), Scott et al. (2012), and Roberfroid et al. (2010); see also Dewulf et al. (2012)

Gluten-free diet

British healthy adults (Na = 10, 1 month)

FISH, flow cytometry

Decrease in total bacteria, especially Firmicutes and bifidobacteria; increase in enterobacteria

De Palma et al. (2009)

FODMAPrestricted diet

British IBS patients (N = 19, 4 weeks)

FISH

Decrease in bifidobacteria

Staudacher et al. (2012)

Change in whole-grain intake

1. Finnish adults with MetS (N = 51, 12 weeks) 2. US healthy adults (N = 28, 4 weeks) 3. British healthy adults (N = 31, 3 weeks) 4. Swiss adults (N = 17, 2 weeks)

1. Phylogenetic microarray 2. Pyrosequencing 3. FISH 4. qPCR

1. Small increase in Clostridium leptum, C. cellulosi, and Collinsella 2. Increase of Firmicutes (Blautia, Roseburia, Roseburia spp.), and bifidobacteria 3. Increase in bifidobacteria 4. Increase in C. leptum

1. Lappi et al. (2013) 2. Mart´ınez et al. (2012) 3. Costabile et al. (2008) 4. Ross et al. (2011)

British adults at increased MetS risk (N = 50, 4 + 24 weeks) British adults with MetS (N = 14, 3 weeks)

FISH qPCR, sequencing

Both diets induced alterations, e.g., in bifidobacteria; however, the role of fat is unclear as the diets also had altered carbohydrate content.

1. Fava et al. (2012) 2. Walker et al. (2011)

High-protein diet

1. Healthy subjects (N = 20, 2 weeks) 2. Obese British adults (N = 17, 4 weeks)

1. Profiling 2. FISH

1. No effects 2. Decrease in Roseburia/ E. rectale and Bacteroides spp.

1. Windey et al. (2012a) 2. Russell et al. (2011)

Parenteral feeding (of Crohn’s disease patients)

1. Japanese adults (N = 8, 26–48 days) 2. British hospitalized elderly (N = 20, 2 weeks) 3. Children from Europe and Australia (N = 5–6, 8 weeks)

1. Profiling, qPCR 2. FISH 3. Profiling

1. Decreased stability, no quantitative changes 2. Individual responses, no significant changes 3. Detectable alterations, especially in Bacteroides spp.

1. Shiga et al. (2012) 2. Whelan et al. (2009) 3. Day et al. (2013)

Withdrawal1 or supplementation2–4

Change in fat intake High saturated fat1 or low-fat diet2

(Continued )

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Diet

Cohort type

Change in total energy supply Low-energy, weight-loss diets1–3 or overindulging4


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1. British obese adults (N = 20, 4 weeks) 2. British obese adults (N = 17, 4 weeks) 3. British adults with MetS (N = 14, 3 weeks) 4. British healthy adults (N = 14, 1 week)

Main analysis method 1. FISH 2. FISH 3. Profiling, qPCR, sequencing 4. FISH

Main effect on microbiota composition 1–2. Decrease in E.rectale, Roseburia spp. and bifidobacteria 3. Decrease in Collinsella spp., E. rectale, and Roseburia spp. 4. Increase in total bacteria and Bacteroides spp.

References 1. Duncan et al. (2007) 2. Russell et al.(2011) 3. (Walker et al. 2011) 4. Gougoulias et al. (2009)

a

N refers to number of individuals in the intervention group and the subsequent number to the duration of the specified intervention period. Abbreviations: FISH, fluorescence in situ hybridization; FODMAP, fermentable oligo-, di- and monosaccharides and polyols; IBS, irritable bowel syndrome; MetS, metabolic syndrome; qPCR, quantitative polymerase chain reaction.

b

An emerging key organism in the adaptation of the microbiota to fluctuating dietary nutrients is mucus-degrading Akkermansia muciniphila. In several model animals, a shortage of food-derived nutrients stimulates the growth of A. muciniphila (Belzer & de Vos 2012), indicating that specialization on endogenous substrates provides a competitive advantage when exogenous substrates are scarce. The amount of A. muciniphila has not been addressed in the published weight-loss studies in humans. We detected overrepresentation of A. muciniphila in human volunteers following a very low calorie weight-loss diet (A. Salonen & W.M. de Vos, unpublished data). Overall, such a diet had a surprisingly small impact on the overall variance of the microbiota (Figure 1), indicating the ability of the microbiota to efficiently switch to the use of alternative, host-derived substrates. Because A. muciniphila produces oligosaccharides and SCFAs as a result of mucus degradation (Derrien et al. 2004), it releases usable energy for the other intestinal microbes and thus emerges as a keystone contributor in maintaining the stability of the gut ecosystem. Recently, also, the systemic influence of A. muciniphila on the metabolic control of the host has been documented. Remarkably, recent mice studies have shown that the intestinal permeability and inflammation that are evoked in response to a high-fat diet are strongly reduced when live A. muciniphila cells are provided simultaneously (Everard et al. 2013). Interestingly, A. muciniphila is strongly (approximately 100-fold) reduced in the mucosal layer and to a lesser extent (fivefold) in the fecal samples of patients suffering from ulcerative colitis (Png et al. 2010, Rajilić-Stojanović et al. 2013b). Similar, but less pronounced, effects in the mucosa of Crohn’s disease patients were reported (Png et al. 2010). These results can be explained in terms of signal transduction via propionate or other factors produced by A. muciniphila (Belzer & de Vos 2012, Everard et al. 2013). Germ-free mice monoassociated with A. muciniphila showed increased immune signaling, notably in the colon (Derrien et al. 2011). Recently, this has been confirmed in an independent study where an increase of A. muciniphila was found to improve the metabolic capacity of mice with high-fat-diet-induced obesity via the anti-inflammatory activity of regulatory T cells in visceral adipose tissue (Shin et al. 2013). In mice on a high-fat diet, prebiotic fiber as well as the antidiabetic drug metformin have been shown to increase levels of A. muciniphila (Shin et al. 2013, Everard et al. 2013). The prebiotic effect could reflect the diet-induced changes in the intestinal mucus layer, as both prebiotic fiber and SCFAs can stimulate mucin secretion (Barnett et al. 2012). It is tempting to speculate that the increased A. muciniphila levels after starvation and other treatments in humans and animal models operate via the same mechanism and affect similarly metabolic and immune signaling. This would allow the development of novel therapies based on this and other intestinal bacteria. 6.10

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Dietary components Mucus and other host components

Poly- and oligosaccharides

Protein

Monosaccharides

Amino acids

Fat

Phytochemicals

Degradation Bioconversion


Fermentation H2 CO2

SCFA

Hydrogen disposal H2S

CH4

Acetate

Breath, flatus

Lactate

Ethanol

BCFA NH3 Amines Phenols Indoles

Bioactive compounds

Adsorbtion & excretion plasma, urine, feces

Figure 2 Schematic overview of the degradation of the macronutrients carbohydrate and protein and bioconversion of fat and phytochemicals by the intestinal microbiota. Abbreviations: BCFA, branched-chain fatty acid; SCFA, short-chain fatty acid.

4. BACTERIAL INTERACTIONS WITH MAJOR DIETARY COMPONENTS AND THEIR RELATION TO HOST PHYSIOLOGY The metabolism of dietary macronutrients by the intestinal microbiota can be divided into three operational levels: primary degradation, fermentation, and hydrogen disposal (Figure 2). Phylogenetic groups show considerable functional overlap in their metabolic activities, but the thusfar identified, principal primary degraders include Bacteroides, Prevotella, and Ruminococcus spp., whereas the predominant fermentative bacteria represent families Lachnospiraceae and Ruminococcaceae as well as genera Bacteroides, Bifidobacterium, and Akkermansia (Flint et al. 2012b). Hydrogen gas (H2 ), produced by many bacteria during hydrolysis and fermentation, has a central role in thermodynamic control of upstream fermentation. Three alternative and potentially competing low-abundant microbial groups dispose of the colonic H2 (Nakamura et al. 2010). These include acetogenic bacteria (numerous, e.g., Blautia spp.), methanogenic archaea (mainly Methanobrevibacter smithii ), and sulfate-reducing bacteria (mainly Desulfovibrio spp.). However, many anaerobes, including the abundant ones that produce butyrate, are able to produce or use H2 via the action of reversible hydrogenases. The health implications of different H2 disposal routes and potential dietary influences on them have been reviewed elsewhere (Nakamura et al. 2010, Rajilić-Stojanović 2013). The intermediate and end products of microbial food metabolism provide the host with energy, mainly in the form of SCFAs. They also contain bioactive molecules that act either locally in the gut or systemically via the circulatory system. The roles of the intestinal microbiota in energy harvest, host fat storage, and obesity have been reviewed extensively in recent years; hence, the reader is referred to Kootte et al. (2012) and Krajmalnik-Brown et al. (2012). Here, we focus on the bacterial interactions with dietary macronutrients—carbohydrates, proteins, and fats—with reference to some known health implications. www.annualreviews.org • Impact of Diet on Intestinal Microbiota


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4.1. Carbohydrates


FODMAPs: fermentable oligo-, di-, monosaccharides, and polyols

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Most intestinal bacteria forage on complex polysaccharides that escape human digestion. These include plant cell wall components, such as cellulose and xylans, and storage polysaccharides, such as resistant starch and inulin, which are collectively referred to as dietary fiber. Bacterial carbohydrate metabolism occurs in a highly cooperative manner within and between the three trophic levels (Figure 2). Current knowledge on the degradation of complex carbohydrates by the intestinal microbiota and its physiological consequences has been reviewed extensively elsewhere (Chassard & Lacroix 2013; Louis et al. 2007; Scott et al. 2011, 2012), with specific attention paid to metabolic conversions (Cummings & Macfarlane 1991, Flint et al. 2012a, Macfarlane & Gibson 1997) or degradation mechanisms (Koropatkin et al. 2012; Flint et al. 2007, 2012a). The main metabolic output of colonic fermentation consists of SCFAs with variable amounts of H2 and carbon dioxide. The physiological effects of the major SCFAs (acetate, propionate, and butyrate) have been reviewed extensively (Cummings & Macfarlane 1991; Macfarlane & Macfarlane 2011, 2012). In brief, SCFAs mediate energy to the host from otherwise unusable dietary components. While butyrate is used in situ by the colonocytes, propionate and acetate are largely absorbed and transported to liver, the latter also to muscles and other peripheral tissues. Acetate is largely utilized by butyrate-producing bacteria and when absorbed by the host, supports de novo lipid synthesis in the liver, whereas propionate is an important substrate for gluconeogenesis (Vipperla & O’Keefe 2012). Butyrate in particular has received significant attention due to its pluripotent nature in maintaining gut integrity and overall health. Butyrate has various documented effects that make it an anticarcinogenic and anti-inflammatory molecule. It is also the preferred energy source for colonocytes. In controlled intervention studies, the production of butyrate linearly correlates with the carbohydrate intake (Duncan et al. 2007); however, in free living individuals the interactions between the dietary elements and microbiota seem far more complex, and total dietary pattern may be more decisive than the quality and quantity of carbohydrates. In addition to long-chain carbohydrates, fermentable oligo-, di- and monosaccharides and polyols (FODMAPs) (Gibson & Shepherd 2005) as well as artificial sweeteners and rare sugars (Payne et al. 2012) can be abundant in the colon and potentially modify the microbiota and its metabolic output. Although some FODMAPs are used simply as prebiotic supplements, they have emerged as novel and targeted strategy to manage bloating and flatulence in irritable bowel syndrome (IBS) and other functional gut disorders. FODMAPs are poorly absorbed in the small intestine and rapidly fermented by the colonic microbiota, leading to extensive H2 production (Gibson & Shepherd 2010). A recent study that addressed the gut microbiota composition during controlled intake of FODMAPs reported a selective reduction of Bifidobacteria (Table 2) and a parallel relief of symptoms, especially bloating, after a 4-week FODMAP restriction (Staudacher et al. 2012). It is unclear, however, what microbes contributed to the relief of symptoms, as bifidobacteria do not produce gas during growth on fructans or other substrates. The diet did not affect the amount of total bacteria or any other bacterial groups assayed, including the main butyrate producers (the E. rectale/Roseburia group and Faecalibacterium prausnitzii ), or that of the SCFAs. Flint et al. (2012a) have reviewed recently the current knowledge on the carbohydrate metabolizing mechanisms of the dominant phyla Firmicutes, Bacteroidetes, and Actinobacteria. The cleavage enzymes and sensor-regulator proteins and transporters appear to be very specific for particular types of carbohydrates and thus determine which types bacteria can metabolize (Martens et al. 2011). As an example, Prevotella spp., which drive one of the enterotypes (see above) and characterizes populations with a high intake of plant-based complex carbohydrates, has the capacity to utilize xylan through numerous mechanisms that are conserved in the Bacteroidetes phylum

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(Dodd et al. 2011). As xylan is a highly abundant plant cell wall polysaccharide, high proportions of Prevotella allow efficient harvest of energy from otherwise indigestible food components. CRC: colorectal cancer


4.2. Protein Most of the dietary protein is digested in the small intestine, but excessive intake leads to higher colonic input (Macfarlane et al. 1986). A variety of protein sources from dietary and host origin are potentially available for the colonic microbes (Cummings & Macfarlane 1991). Colonic fermentation of protein is much less studied than that of carbohydrates; culture-based analyses have identified at least Bacteroides spp. and propionibacteria, as well as various bacilli, to be proteolytic (Macfarlane et al. 1986, Scott et al. 2012). Many of those bacteria carry genes for serine and other proteases in their genomes. However, no detailed molecular studies have been carried out to specify or broaden the implicated phylogenetic groups. Bacterial protein fermentation occurs in the distal colon and produces a variety of metabolites, including sulphur, N-nitroso, phenolic and indolic compounds, as well as ammonia, organic acids, and heterocyclic amides, depending on the amino acid content of the proteins (Nyangale et al. 2012). Many of the released compounds are toxic and detrimental to gut health at least within in vitro settings, where individual metabolites are exposed to cell cultures (Windey et al. 2012b). It is assumed that prolonged exposure of protein-derived, toxic bacterial metabolites to epithelial cells promotes disease development, especially colorectal cancer (CRC; Gill & Rowland 2002, Vipperla & O’Keefe 2012). However, there is a lack of conclusive evidence of a causative relationship between protein intake and CRC. In recent studies that also addressed the impact of protein intake on the gut microbiota (Table 2), high-protein diets were found to either increase detrimental metabolites in feces (Russell et al. 2011) or have no impact on fecal water toxicity (Windey et al. 2012a). High-protein intake has also been connected to other microbiota-associated diseases. In a large prospective study, high intake of animal protein was associated with an increased risk of incident IBD ( Jantchou 2010). Recently, L-carnitine, an abundant nutrient in red meat, was shown to be metabolized by the intestinal microbiota to TMAO, which promotes atherosclerosis (Koeth et al. 2013). There is no human in vivo data on how the source of protein (meat, fish, plants) affects the microbiota. However, animal and batch culture experiments suggest that both the amount and type of dietary protein modify at least the metabolic output of the microbiota (Scott et al. 2012).

4.3. Fat As the degradation and adsorption of dietary fat mainly take place in the small intestine by host enzymes, in healthy individuals, little if any dietary fat should reach the colon. Hence, the intestinal microbiota is not expected to interact substantially with dietary fat. Metagenomic analyses confirm that the abundant lipid metabolism–associated genes within the human intestinal microbiome are mainly biosynthetic or involved in bioconversions (Qin et al. 2010, Turnbaugh et al. 2009a). In mice, the intestinal bacteria affect profoundly the emulsification, absorption, and transport of dietary fat, as well as their storage and peroxidation through the metabolic and signaling properties of bile acids (Martin et al. 2007). Moreover, ruminant bacteria carry out extensive lipid hydrolysis, isomerization, and biohydrogenation (Bauman et al. 2003, Harfoot & Hazlewood 1988), implying that the still uncharacterized part of the human GI microbiome may encode for similar functions. Recent observational studies have identified fat as a modulator of the composition of the human microbiota (Lappi et al. 2013, Simoes ˜ et al. 2013, Wu et al. 2011). Specifically, the variance of Bacteroides spp. has been associated with the intake of polyunsaturated fatty acids (Lappi et al.

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Bile salt hydrolase (BSH): enzyme that mediates resistance to bile via a deconjugation reaction

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2013) and saturated fatty acids (Simoes ˜ et al. 2013). Correlation analyses have found a positive correlation between the abundance of Bacteroides spp. and consumption of plant- (Lappi et al. 2013) and animal-derived fat (Wu et al. 2011). Somewhat conflicting the emerging human data, most mouse studies have reported depletion of Bacteroidetes and increases of Firmicutes during high-fat diet (Cani et al. 2007, de Wit et al. 2012, Hildebrandt et al. 2009, Turnbaugh et al. 2008). This mimics the bacterial profile claimed to characterize obesity (Ley et al. 2005). However, a marked increase of Bacteroidetes has also been observed during high-fat diets (de La Serre et al. 2010, Devkota et al. 2012). Altogether, these studies indicate that high fat intake, rather than obesity per se, has a direct effect on the microbiota (de Wit et al. 2012, Ravussin et al. 2012). Not only the amount, but also the type of fat (saturated versus unsaturated), determines its impact on the microbiota and interlinked clinical outcomes (de Wit et al. 2012, Devkota et al. 2012, Fleissner et al. 2010). In human intervention studies the impact of fat intake on the microbiota is hard to estimate based on published trials in which the test diets were simultaneously altered also in carbohydrate or protein content (Table 2). As a general theme from mouse studies, high-fat diets seem to simplify the microbiota by decreasing the diversity and in some reports also the total amount of intestinal bacteria. In ruminants, the direct antimicrobial and antifermentative impacts of diet-derived fatty acids are well-recognized phenomena ( Jenkins 1993). Other potential mechanistic explanations for the suppression of microbiota during high-fat diet include a low supply of fermentable substrates and the induction of bile acids, well known for their bactericidal activities (Begley et al. 2005; see also Section 2.1). When rats were orally fed with cholic acid, the most common bile acid, their microbiota showed a similar decrease of Bacteroidetes and increase of Firmicutes that have been associated with high-fat diets and obesity (Islam et al. 2011). The authors suggest that not the fat but the induced bile may exert the microbiota alterations during high-fat diets. This hypothesis, and the body of data reporting a reduction of Bacteroidetes during high-fat diet, contradicts the general belief that gram-negative bacteria (here Bacteroidetes) are inherently more resistant to bile (Begley et al. 2005). It supports, instead, the few studies that have identified dietary fat as a stimulating agent for Bacteroides spp. (de La Serre et al. 2010, Devkota et al. 2012, Lappi et al. 2013). Further research is needed to clarify the actual effect of fat on Bacteroides and proteobacteria, as well as the other members of the intestinal microbiota. Bile acids not only suppress the microbiota but are also subject to extensive bacterial transformation in the colon. High-fat diet increases the excretion of bile (Reddy 1981) and presumably the amount of bile acids that reach the colon and interact with the microbiota. Various intestinal bacteria encode bile salt hydrolases (BSHs), which mediate resistance to bile via deconjugation reactions ( Jones et al. 2008). Further bacterial modification via dehydroxylation produces secondary bile acids, mainly deoxycholic acid and lithocholic acid (Ridlon et al. 2006). Secondary bile acids are biologically highly active and are associated with the development of gallstones and CRC (Bernstein et al. 2005, Gill & Rowland 2002). Comparison of populations that have low and high incidences of CRC, for instance native Africans and African Americans, respectively, showed that the American diet high in fat and low in complex carbohydrates promotes the production of secondary bile acids and branched-chain fatty acids (BCFAs) (Ou et al. 2012). (See Section 3.1 for a discussion on the link to the Prevotella and Bacteroides-driven enterotypes in these populations.) A recent reciprocal dietary intervention with these groups has shown a causal relationship between high-fat diets, Bacteroides-driven enterotypes, and markers of CRC (S.J.D. O’Keefe, L. Lahti, J.V. Li, J. Kinross, J. Ou, K.H. Mohammed, F. Carbonero, E. Ruder, K. Vipperla, V. Naidoo, L. Mtshali, S. Tims, P. Puylaert, J. DeLany, A. Krasinskas, K. Newton, J.K. Nicholson, W.M. de Vos, H.R. Gaskins, & E.G. Zoetendal, submitted manuscript). Salonen

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Recent studies provide evidence that interactions between intestinal bacteria, dietary fat, and bile acids may be significant factors in IBD as well. In a mouse study, saturated, but not polyunsaturated, dietary fat promoted the growth of intestinal deltaproteobacteria that elicited a proinflammatory response and increased incidence of colitis in genetically susceptible mice (Devkota et al. 2012). The mechanism was pinpointed to involve saturated fat–induced change in the pool of bile acids, more specifically, increased levels of taurocholic acid, which in turn stimulated the growth and release of toxic hydrogen sulfide (H2 S) by the proteobacterium Bilophila wadsworthia. Hydrogen sulfide interferes with butyrate utilization of colonocytes and has been implicated in both IBD and CRC (Medani et al. 2011). In Crohn’s disease patients, the bile resistance capacity in Firmicutes was shown to be reduced significantly, based on quantification of BSH in the metagenome data (Ogilvie & Jones 2012). There were no differences in BSH levels of Actinobacteria or Bacteroidetes. As Crohn’s disease is characterized by markedly reduced abundance and diversity of Firmicutes (Manichanh et al. 2006), it could be speculated that the abundance of BSH may be a key regulator of microbiota diversity. However, the study requires confirmation with larger data sets; it was based on only four patients’ microbiota. Interactions between dietary fat and intestinal microbiota can contribute to the development of chronic diseases also via other mechanisms than bile. It is well documented that high intake of dietary fat induces the diffusion of lipopolysaccharides and other structural components of bacteria from the gut to circulatory system, in both mice and humans, resulting in the chronic subclinical inflammation underlying type 2 diabetes and obesity (i.e., metabolic endotoxemia; see Moreira et al. 2012). It is assumed that proteobacteria contribute to endotoxemia, and at least in mice, the intake of prebiotics can augment the harmful effects of high-fat diet (Neyrinck et al. 2011). Similar to L-carnitine (discussed in Section 4.2), dietary lipid phosphatidylcholine is also converted by intestinal bacteria to proatherosclerotic TMAO (Wang et al. 2011). In summary, strong evidence, mainly from animal studies but increasingly from human interventions, exists for the reciprocal dietary fat-microbiota interactions. On one hand, the fat quantity and quality shapes the microbiota; on the other hand, microbial activities are involved in the physiological fate and health impact of dietary and endogenous lipids (Fava et al. 2006, Martin et al. 2007). In addition to the known role of the gut bacteria in cholesterol metabolism via bile acids, global monitoring of the serum and organ lipidomes of germ-free and conventionally raised mice suggests far more widespread and profound microbial influence on host lipid metabolism (Velagapudi et al. 2010). We recently identified numerous correlations also between the human intestinal bacteria and serum lipids in healthy individuals (Lahti et al. 2013).

4.4. Phytochemicals Dietary phytochemicals (non-nutrient bioactive plant compounds) include, but are not limited to, phenolic and flavonoid compounds that may have various potential health-promoting effects ranging from antioxidants to anticarcinogens. The metabolic fate and bioactivity of the phytochemicals are regulated by the GI microbiota (Table 2). The known microbiota-phytochemical interactions and their relevance to human health are summarized elsewhere (Laparra & Sanz 2010, Moco et al. 2012, Possemiers et al. 2011).

5. FUTURE PROSPECTS Observational studies have provided convincing evidence that at least in the long term, diet can modify the microbiota composition in parallel with host-determined selection forces. The mechanisms range from the control of substrate availability to alteration of the physicochemical www.annualreviews.org • Impact of Diet on Intestinal Microbiota


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microenvironment in the gut. Exactly which components of complex foods contribute to the abundance of certain bacteria and how this modulates host physiology can nonetheless be studied only in intervention studies that allow causality to be addressed. This is not an easy task for various reasons. First, selective increase or removal of certain dietary components is expected to affect numerous taxa as a result of cross-feeding (Louis et al. 2007). Second, bacterial end products vary greatly within a single fermentable substrate; for example, both Bacteroides and Roseburia effectively ferment xylan but produce different organic acids and gases that vary even between different species within the genus (Chassard et al. 2007). Third, not only the diet or baseline microbiota but also the host genotype will affect how food choices translate into physiological benefit or impairment. For these reasons, it is unlikely that any dietary component conveys a universal effect on all individuals. Therefore, the focus of future research should be on identifying microbiota and host features that allow stratification of individuals to predict the extent and direction of their dietary response. The use of enterotypes has been shown to be instrumental, and further refinements in the segmentation of subjects by their intestinal microbiota are to be expected. There is no information about the impact of very short-term dietary changes such as meal-tomeal variation or overnight fasting, or about which timescale(s) allows long-lasting or permanent diet-driven adaptation of the microbiota. As a reference, the diet-driven adaptive evolution of the human genome takes hundreds to thousands of years. The addition of fermentable carbohydrates to diet induced alterations to the human microbiota within 3–4 days (Walker et al. 2011), whereas another human study reported detectable changes in the microbiota within 24 hours (Wu et al. 2011). However, in most individuals, food does not reach the colon within 24 hours, and the impact on the microbiota may derive from specific signaling. In any case, the human microbiota is not resistant to dietary modulation, but it is highly resilient as it has a strong tendency to return to its ground state after dietary perturbation. In this respect, the adult intestinal microbiota represents a state of dynamic equilibrium, in which short-term fluctuations occur in response to dietary and other changes. The original stable state can change to an alternative state when the timing, intensity, duration, and/or frequency of dietary pressure reach certain points. Such points likely vary among individuals, and identification of the ecosystem features that determine modulation is of central interest for better understanding the link between health, diet, and the microbiota. In conclusion, the significance of intestinal bacteria for our health is now well established. Future research challenges are to identify bacteria that are affected by diet, food components, foods or dietary patterns that have an impact on the microbiota, and microbes that are key players in mediating the health effects of different dietary components. That information can be used to design successful dietary strategies to benefit health.


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SUMMARY POINTS 1. The intestinal microbiota is a complex ecosystem that has tremendous genetic potential, exceeding the coding capacity of the human genome. 2. The microbiota participates in numerous nutritional, immunological, and protective functions in the human body. 3. Due to the systemic impact on human physiology, the microbiota is now recognized as one factor in the development of many chronic diseases in parallel with host genotype and diet. 4. The intestinal microbes feed on diet- and host-derived substrates, and by doing so release energy and bioactive molecules that are not limited to the gut but also reach systemic circulation.

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5. The causal relationships between diet, microbiota, and health are far from understood, but microbial fermentation of carbohydrates largely creates beneficial metabolites, whereas particularly excessive protein fermentation yields potentially harmful substances. 6. Recent data show that the amount and type of fat shape the colonic microbiota and its metabolic output.


7. Long-term diets, especially the intake levels of dietary fiber, modify the human intestinal microbiota; short-term dietary changes seem to have modest and reversible impact. 8. The dietary responses of the microbiota are highly variable among individuals, which limits their practical utilization in nutrition and medicine.

FUTURE ISSUES 1. Whereas mice studies are informative mechanistically, human trials are essential to identify associations between particular dietary patterns or compounds with specific signatures of the human microbiota. 2. The role of the microbiota in the metabolism and health implications of dietary fat should be analyzed. 3. Well-designed intervention studies are needed to identify the causal links between diet, intestinal microbiota, and health. 4. To overcome the high individuality of the human microbiota and its dietary responses, stratification of individuals should be attempted based on microbiota, as well as host features. 5. The intestinal microbiota should be considered in the development of personalized nutrition and medicine in parallel with the human genome. 6. Integrated analysis of the host genotype and the microbiota is needed for system-level understanding of the associations between diet and health.

DISCLOSURE STATEMENT The authors are not aware of any affiliations, memberships, funding, or financial holdings that might be perceived as affecting the objectivity of this review.

ACKNOWLEDGMENTS We thank Dr. Jarkko Salojärvi for the data analysis presented in Figure 2. We apologize for all the colleagues whose research could not be appropriately cited due to space limitations. This applies especially to the numerous original studies on the impact of carbohydrates on the gut microbiota that have been reviewed extensively elsewhere. This work was supported in part by grants 137389 and 141140 from the Academy of Finland, grant ERC 250172 - Microbes Inside from the European Research Council, and the unrestricted Spinoza Award from the Netherlands Organization for Scientific Research. www.annualreviews.org • Impact of Diet on Intestinal Microbiota


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Intestinal microbiota during early life - impact on health and disease.

The impact of diet and lifestyle on gut microbiota and human health.

Impact of diet and individual variation on intestinal microbiota composition and fermentation products in obese men.

Dysbiotic events in gut microbiota: impact on human health.

Pilot study of diet and microbiota: interactive associations of fibers and polyphenols with human intestinal bacteria.

Impact of a High-Fat or High-Fiber Diet on Intestinal Microbiota and Metabolic Markers in a Pig Model.

Intestinal microbiota and health in childhood.

Intestinal microbiota and diet in IBS: causes, consequences, or epiphenomena?

Dynamic efficiency of the human intestinal microbiota.

Diet-Intestinal Microbiota Axis in Osteoarthritis: A Possible Role.

Human gut microbiota: does diet matter?

The Impact of Western Diet and Nutrients on the Microbiota and Immune Response at Mucosal Interfaces.

How diet can impact gut microbiota to promote or endanger health.

Impact of birth weight and postnatal diet on the gut microbiota of young adult guinea pigs.

Impact of Westernized Diet on Gut Microbiota in Children on Leyte Island.

Detrimental Impact of Microbiota-Accessible Carbohydrate-Deprived Diet on Gut and Immune Homeostasis: An Overview.

Impact of experimental hookworm infection on the human gut microbiota.

Ecological impact of MCB3837 on the normal human microbiota.

Impact of Prematurity and Perinatal Antibiotics on the Developing Intestinal Microbiota: A Functional Inference Study.

Changing views on diverticular disease: impact of aging, obesity, diet, and microbiota.

Modeling the impact of antibiotic exposure on human microbiota.

Correlation network analysis reveals relationships between diet-induced changes in human gut microbiota and metabolic health.

Effects of diet on gut microbiota profile and the implications for health and disease.

Intestinal microbiota impact sepsis associated encephalopathy via the vagus nerve.