- CRC
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colorectal cancer
- GI
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gastrointestinal
- RS
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resistant starch
- TLR
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Toll-like receptor
The colonic microbiota is likely to play an important role in health maintenance or progression to diseases such as colorectal cancer (CRC). Furthermore, the gut microbial community has been proposed by a number of studies to play a role in the development of obesity. Diet is a significant driver both for the composition of the gut microbiota( Reference Walker, Ince and Duncan 1 – Reference Flint, Duncan, Scott and Louis 3 ) and for the development of obesity and cancer. This makes it challenging to untangle causative factors that may be due to dietary components, individual gut microbes and the metabolic products of microbial metabolism that are largely derived from dietary components. The diversity of bacterial species in the colon means that collectively they perform an impressive array of metabolic activities, as is evident from both metabolomic and metagenomic analyses( Reference Qin, Li and Raes 4 – Reference Holmes, Li and Athanasiou 6 ). There is an increasing awareness that in addition to understanding the composition of the microbiota, their metabolic output will have a profound impact in modulating both gut and systemic health( Reference Duncan, Belenguer and Holtrop 2 , Reference Fleissner, Huebel and Abd El-Bary 7 , Reference Russell, Gratz and Duncan 8 ). Functional analysis of microbial metabolites will therefore be crucial to understanding the impact of diet and of gut micro-organisms on maintenance of health and prevention of disease. This review will focus on the importance of the microbial metabolome in the development of obesity-linked co-morbidities.
The gut microbiota
From birth, the gastrointestinal (GI) tract becomes colonised by a succession of bacterial species and the composition of the microbiota is similar to that of adults from around the time of weaning. In the days following birth, the baby GI tract is primarily colonised by facultative anaerobes and microaerophiles, followed later by obligate anaerobes. In breast-fed infants, for example, Bifidobacterium species generally predominate while appreciable numbers of Bacteroides species are only detected after weaning. In early life Bacteroides species may persist in the gut largely through their ability to utilise host-derived substrates, followed after weaning by the utilisation of plant-derived polysaccharides from the diet( Reference Bjursell, Martens and Gordon 9 ).
The adult human large intestine usually contains more than 200 g of contents and is colonised by hundreds of bacterial species, reaching a total cell density of about 1011 bacterial cells/ml thereby outnumbering host cells about 10-fold. This complex microbial community also harbours about 100-fold more genes than the human genome( Reference O'Hara and Shanahan 10 ). This dense community of bacteria mainly comprise the Gram-negative Bacteroidetes and the Gram-positive Firmicutes and Actinobacteria( Reference Duncan, Belenguer and Holtrop 2 ) with the Bacteroidetes accounting for about one-quarter of the microbiota. Most of the remainder belong to the Firmicutes, which mainly comprise the Lachnospiraceae and Ruminococcaceae families. The next most abundant phylum of Gram-positive bacteria is Actinobacteria that includes the Bifidobacterium species( Reference Flint, Duncan, Scott and Louis 3 ). Inter-individual variation is observed for the gut microbiota and may be greater in infants than in adults( Reference Kurokawa, Itoh and Kuwahara 11 ). Nevertheless, a dominant group of bacterial species has been identified in faecal samples from healthy adult individuals( Reference Walker, Ince and Duncan 1 , Reference Qin, Li and Raes 4 , Reference Tap, Mondot and Levenez 12 ). The top ten most abundant phylotypes or species make up about 30% of the faecal microbiota( Reference Walker, Ince and Duncan 1 , Reference Flint, Scott and Duncan 13 ). Two of the most dominant species are Faecalibacterium prausnitzii and Eubacterium rectale, which employ the butyryl CoA: acetate CoA transferase route for butyrate formation( Reference Duncan, Hold and Barcenilla 14 – Reference Louis, Duncan and McCrae 16 ). These species appear to be present in a majority of individuals although F. prausnitzii abundance is diminished in Crohn's sufferers( Reference Willing, Dicksved and Halfvarson 17 , Reference Sokol, Pigneur and Watterlot 18 ) and in the elderly( Reference van Tongeren, Slaets and Harmsen 19 ). Two other dominant species, Eubacterium hallii and new Anaerostipes species are butyrate producers that can utilise lactate( Reference Duncan, Louis and Flint 15 ). Microbiota variation may be a consequence of several factors including acquisition of bacteria at birth( Reference Ley, Backhed and Turnbaugh 20 ), host immune responses, antibiotic usage( Reference Relman 21 ) and diet( Reference Walker, Ince and Duncan 1 ,Reference Duncan, Belenguer and Holtrop 2 , Reference Abell, Cooke and Bennett 22 –Reference Davis, Martinez and Walter 24 ).
Methodologies used to study the microbial genome: metagenomics
Large genome programmes including the National Institutes of Health-funded Human Microbiome Project (nihroadmap.nih.gov/hmp/) and the EU funded MetaHIT project (www.metahit.eu/) have sequenced more than fifty Bacteroides and Prevotella species and many Gram-positive bacterial species. The increasing speed and decreasing cost of sequencing is now making metagenomic analysis of the whole microbial community a popular option( Reference Qin, Li and Raes 4 , Reference Kurokawa, Itoh and Kuwahara 11 ). A recent metagenomic analysis of faecal samples of volunteers from four countries suggested that the microbiota belonged to three distinct clusters or ‘enterotypes’( Reference Arumugam, Raes and Pelletier 25 ). On the other hand, another study detected only two putative enterotypes among the ninety-eight adults examined, and presented evidence that these were in fact diet-driven( Reference Wu, Chen and Hoffmann 26 ). While metagenomic analyses can provide an incredible amount of information, interpretation of the data is very much dependent on information gained from previously isolated and characterised bacteria. Functional screening of metagenomic libraries can be achieved using high-throughput screening assays, as have been employed in other ecosystems such as soil( Reference Riesenfeld, Schloss and Handelsman 27 ).
Methodologies used to study the microbial metabolome: metabolomics
Metabolomics is a comprehensive and non-selective analytical chemistry approach aimed at providing a global description of all the metabolites present in a given biological sample. Although metabolic profiling has been used for decades, modern instrumentation and statistical methodology has found recent application in predicting the outcome of dietary and clinical studies. In particular, metabolomics can prove valuable where the lack of effective biomarkers has made it difficult to establish the long-term implications of intervention, e.g. in outwardly healthy individuals. Human genotyping can give useful information regarding the predisposition to disease and proteomics can provide indicators of disease occurrence. However, metabolites have always been an excellent indicator of human disease, and for this reason they are also likely to be a useful predictor of human health. In addition, metabolomic data provide vital information on the overall function of the gut microbiota. Metabolomic analysis can rely on NMR spectroscopy which can be coupled to liquid chromatography, allowing separation of the metabolites prior to detection. The main advantages of MS over NMR are sensitivity and the ability to perform quantitative and targeted analysis. Recent advances in MS have resulted in robust and powerful methods to study the human metabolome( Reference Villas-Bôas, Mas and Åkesson 28 , Reference Hollywood, Brison and Goodacre 29 ) and the real potential of MS has been achieved through prefacing to GC–MS and liquid chromatography–MS. The plethora of ionisation techniques (e.g. electron ionisation and chemical ionisation) and wide availability of mass analysers make modern MS analysis an extremely versatile technique( Reference Villas-Bôas, Mas and Åkesson 28 , Reference Hollywood, Brison and Goodacre 29 ).
Influence of host and dietary factors on the gut metabolome
The composition of the gut microbiota may be is subject to selective pressure from the host and diet, which can alter the ecosystem homoeostasis affecting the abundance of specific groups. Many factors have the potential to influence the microbiome and these could include sex, age, BMI, gut physiology and immune/inflammatory status (Fig. 1). The colonic microbiota is found to be relatively stable in individuals consuming their normal diet but it is evident that dietary change can influence the abundance of specific bacterial groups( Reference Walker, Ince and Duncan 1 ). There are major compositional differences in the gut microbiota between population groups depending upon staple food intake, as suggested by a study on Italian and African children( Reference De Filippo, Cavalieri and Di Paolo 30 ). The amount and type of the three main macronutrients, carbohydrate, protein and fat, consumed in our diets will impact on the composition of the gut microbiota. The ability of gut microbes to utilise and transform these macro- and micronutrients, however, has consequences for human health that may be more important than the detailed taxonomic changes in the microbiota.
Fig. 1. Host factors with potential to impact on the gut microbiota.
Macronutrient influences on the gut microbiota
Carbohydrate is critical for the host and is the major energy source for the gut microbiota. The principal carbohydrate sources for individuals consuming a western-style diet are resistant starch (RS) with usually lower amounts of NSP, which are consumed mainly in cereals. In addition, oligosaccharides such as fructans are consumed in foods including onions and artichokes. The extent of dietary starch breakdown in the colon is dependent on a number of factors that include amylose content and state of gelatinisation which is mainly determined by the cooking process( Reference Englyst, Kingman and Cummings 31 ). Starch is a complex polysaccharide consisting of a mixture of amylose (1,4-α-linked glucose residues) and amylopectin, a branched polymer composed of amylose chains linked to an amylose backbone by 1,6-α-linkages. The relative proportion of amylose and amylopectin has an effect on the availability of different types of starch for bacterial growth. In a model system, 80% of sequences recovered from starch particles belonged to Ruminococcus bromii, E. rectale and Bifidobacterium species( Reference Leitch, Walker and Duncan 32 ).
Moreover, bacteria related to R. bromii increased almost two-fold in faecal samples when the volunteers switched from normal diets to starch enriched diets( Reference Abell, Cooke and Bennett 22 ). Faecal populations of the Roseburia/E. rectale group( Reference Aminov, Walker and Duncan 33 ) have been shown to respond to controlled variations in dietary carbohydrate intake( Reference Duncan, Belenguer and Holtrop 2 , Reference Russell, Gratz and Duncan 8 ) that may be explained by a dependence on RS for growth. Another recent study compared the effects of diets supplemented either with a type three RS or a source of NSP (wheat bran) in obese subjects. The groups showing the most significant responses to RS on average were Firmicutes bacteria related to R. bromii and E. rectale, with the former group increasing 10-fold on average as a percentage of total bacteria. Two of the fourteen individuals showed no detectable ruminococci in faecal samples, and carbohydrate analysis of these samples revealed <40% fermentation of RS compared with >95% in the other subjects( Reference Walker, Ince and Duncan 1 ).
High fibre diets increase faecal bulking, SCFA production and transit rates along the large intestine( Reference Lewis and Heaton 34 , Reference Lampe, Slavin and Melcher 35 ). Faecal butyrate concentrations have been shown to correlate with the abundance of the Roseburia/E. rectale group( Reference Duncan, Belenguer and Holtrop 2 ) which is likely to be a major contributor to butyrate formation from starch. This group is stimulated at mildly acidic pH in vitro largely because of the inhibition of competing Bacteroides species( Reference Duncan, Louis and Thomson 36 ) suggesting that its preferred niche may be in the proximal colon where rapid fermentation creates mildly acidic conditions. Active fermentation of other fibre sources and prebiotics also tends to decrease pH in the proximal large intestine( Reference Bown, Gibson and Sladen 37 ) and these shifts in pH can impact the gut microbial community structure( Reference Duncan, Louis and Thomson 36 , Reference Walker, Duncan and Leitch 38 , Reference Belenguer, Duncan and Holtrop 39 ).
There is much interest in modulating microbial metabolism in the intestine through dietary additives such as prebiotics that are defined as ‘a selectively fermented ingredient that allows specific changes, both in the composition and/or activity in the GI microbiota that confers benefits upon host well being and health’( Reference Gibson and Roberfroid 40 ). Current prebiotics are mainly carbohydrates of low digestibility that are found naturally in foodstuffs. Candidate prebiotics include xylo-oligosaccharides and galacto-oligosaccharides( Reference Macfarlane, Steed and Macfarlane 41 , Reference Macfarlane, Macfarlane and Cummings 42 ) with most studies focusing on the use of inulin and fructo-ologosaccharides. The high numbers of Bifidobacterium species in the faeces of breast-fed babies is thought to result from their ability to utilise oligosaccharides in breast milk, including galacto-oligosaccharides while formula fed infants tend to harbour a greater diversity of organisms including a higher abundance of enterococci( Reference Harmsen, Wildeboer-Veloo and Raangs 43 ). The metabolite profiles also differ with higher levels of NH3, amines and phenols in bottle fed babies compared with breast-fed infants( Reference Heavey, Savage and Parrett 44 ). Not all oligosaccharides, however, are highly selective( Reference Flint, Duncan, Scott and Louis 3 ) and fructans, for example, have been shown to promote one or more groups of bacteria in addition to their effects on bifidobacteria( Reference Kruse, Kleessen and Blaut 45 – Reference Apajalahti, Kettunen and Kettunen 47 ). As there is extensive inter-individual variation in composition of the gut microbiota there is likely to be inter-individual variation in the response of the microbial communities to prebiotics( Reference Ramirez-Farias, Slezak and Fuller 46 ). Recent evidence supports the view that there are likely to be detrimental health consequences of reduced carbohydrate intake especially when combined with an increase in the consumption of protein and/or fat, both of which have been potentially associated with an increased risk of colon cancer( Reference Russell, Gratz and Duncan 8 , Reference Bernstein, Bernstein and Payne 48 ).
Many protein- and protein-derived metabolites are considered to be potentially mutagenic and genotoxic and these include heterocyclic amines and N-nitroso compounds( Reference Russell, Gratz and Duncan 8 ). Studies with germ-free animals implied that the gut microbiota was essential in the formation of N-nitroso compounds( Reference Massey, Key and McWeeny 49 ) and the DNA damage by heterocyclic amines was decreased compared with that of conventional animals( Reference Kassie, Rabot and Kundi 50 ). Additional by-products of amino acid metabolism include polyamines (including putrescine, cadaverine, spermine, spermidine, pyrollidine and piperidine), indoles, NH3, hydrogen sulphide, branched chain fatty acids and the aromatic amino acid metabolites. Various species have been shown to produce these products( Reference Beerens and Romond 51 , Reference Smith and Macfarlane 52 ), but comprehensive screening of the predominant gut species has not been performed.
Significant changes in the gut metabolome were observed for volunteers consuming diets in which the protein and carbohydrate ratios were modulated( Reference Russell, Gratz and Duncan 8 ). Using liquid chromatography–MS, derivatives of a wide range of plant phenolics considered to be cancer-protective were reduced in diets high in protein (137 g/d) and low in carbohydrate (22 g/d). Phenylacetic acid, a major metabolite related to protein metabolism was found to have significantly increased. Increasing the carbohydrate content (181 g/d) resulted in significantly increasing some phenolic acids and their derivatives, principally fibre-related phenolics, namely, ferulic acid, 4-hydroxy-3-methoxyphenylpropionic acid and 3-hydroxyphenylpropionic acid.
Bile metabolism, along with lipase activity, are likely to be major factors affecting the delivery of lipids to the colon. Bile acids are predominantly deconjugated and dehydroxylated to secondary bile acids and Bacteroides intestinalis, Bacteroides fragilis and Escherichia coli have been shown to be involved in the production of deoxycholic and lithocholic acid( Reference Fukiya, Arata and Kawashima 53 ). Two major lipid metabolism pathways have been identified; hydration and reduction. The species responsible for the formation of hydrated lipids (i.e. hydroxy fatty acids) were predominantly Clostridium perfringens ( Reference Pearson, Drasar and Wiggins 54 ) and Roseburia species( Reference Devillard, McIntosh and Duncan 55 ), although some other species could produce these metabolites to a lesser extent( Reference Devillard, McIntosh and Duncan 55 ). The species catalysing fatty acid reduction are less well characterised; only species responsible for the conversion of linoleic acid to vaccenic acid have been identified, namely Butyrivibrio fibrisolvens and Roseburia species( Reference McIntosh, Shingfield and Devillard 56 ).
Micronutrient influences on the gut microbiota
It has been shown that the microbiota can synthesise some vitamin B (B3, B5 and B6) and related molecules including biotin, tetrahydrofolate, vitamin K and the corrinoids( Reference O'Keefe, Ou and Aufreiter 57 ). Microbes are considered to affect absorption of certain dietary minerals, with many studies demonstrating that carbohydrate and associated SCFA modulate uptake of Na, Ca and K. Many bacteria also actively accumulate Fe as a siderophore complex( Reference Neilands 58 ). There is very little information regarding the direct effect of the gut microbiota on mineral uptake and the species associated have not been identified.
Non-nutrient/phytochemical influences on the gut microbiota
Epidemiological studies suggest that there is an inverse association between the intake of phytochemical-rich diets and the incidence of CVD, diabetes and cancer( Reference Boeing, Bechthold and Bub 59 ). Edible plant material contains hundreds of compounds most of which play an important role for the plant including protection against pathogens. Biochemically, they can be broadly categorised according to their structure and biosynthetic pathways, but it should be appreciated that many secondary metabolites are derived by combining elements from all of these biosynthetic routes. Some of these compounds particularly if available as small molecules or as their aglycones, may be absorbed in the upper GI tract and directly enter systemic circulation. However, many and in particular those bound to other plant components such as carbohydrates will be available in the colon. Within the colon these phytochemicals are extensively metabolised. Gut microbiota are capable of performing many transformations including: hydrolysis, deamination, dehydrogenation, demethylation, decarboxylation, ring cleavage and chain shortening.
Impact of the gut metabolome on the human host
It is becoming increasingly important to determine which microbial-derived products are responsible for disease development and/or progression (Fig. 2). Once identified these molecules may be used as a potential diagnostic/prognostic tool for inflammatory diseases and related co-morbidities.
Fig. 2. Potential impact of the gut microbiota on the human host.
SCFA
Active fermentation of carbohydrates in the colon results in the formation of SCFA( Reference Barry, Hoebler and Macfarlane 60 ) together with gases, mainly H2, CO2 and methane. The SCFA detected in stool samples are a sub group of fatty acids with aliphatic tails with less than six carbons and include fornic, acetic, propionic, butyric and valeric acid. Branched-chain examples include isovaleric and isobutyric acid. There are also substituted short-chain carboxylic acids such as lactic acid. The total concentration of SCFA in the large intestine may reach upwards of 100 mm ( Reference Macfarlane and Macfarlane 61 ). Dietary shifts can result in changes in SCFA production rates and in the molar proportions of different SCFA detected in faeces. Weight loss diets that are high in protein but low in carbohydrates, for example, were recently shown to reduce faecal butyrate up to four-fold( Reference Duncan, Belenguer and Holtrop 2 ) while higher proportions of propionate and butyrate and lower acetate have been reported to result from increasing prebiotic or fibre intake( Reference Queenan, Stewart and Smith 62 ). SCFA are likely to have several effects upon health. Butyrate is largely considered beneficial for gut health as it is the major energy source for the colonocytes and has a role in CRC prevention as discussed later( Reference Pryde, Duncan and Hold 63 – Reference Sleeth, Thompson and Ford 65 ). Propionate is metabolised in the liver and is gluconeogenic. Activation of the gut receptors G protein-coupled receptor (GPR) 41 and GPR43 (also known as NEFA receptors NEFA2 and NEFA3) by SCFA influences gut motility as well as reducing inflammatory responses( Reference Brown, Goldsworthy and Barnes 66 , Reference Tazoe, Otomo and Kaji 67 ). Acetate is metabolised in the peripheral tissues and is a precursor for cholesterol metabolism and lipid formation. A shift in fermentation products away from acetate (normally present at the highest concentration) towards propionate and butyrate may therefore be beneficial and explain the decrease in cholesterol levels in volunteers consuming fibre( Reference Brown, Rosner and Willett 68 ). Increased SCFA concentrations may also increase the solubility of certain minerals such as Ca, and enhance absorption and expression of Ca-binding proteins( Reference Scholz-Ahrens and Schrezenmeir 69 ). Changes in intestinal microbial metabolism following the consumption of inulin fructans has also been shown to improve bone health by increasing Ca absorption while β-glucans may lower total cholesterol levels( Reference Smith, Queenan and Thomas 70 ).
Phytochemicals
There is a vast amount of literature suggesting that plant secondary metabolites have properties beneficial to health( Reference Russell and Duthie 71 ) In particular, almost all plant foods considered to have cancer-preventative properties are rich in compounds derived from the phenylpropanoid pathway. Most of this information is obtained from in vitro data and there is very little evidence from both pre-clinical and human interventions to support this. Bioavailability may be defined as the fraction of an ingested nutrient or metabolite that reaches systemic circulation and specific sites where it can exert specific biological activity. The most abundant phytochemicals consumed may not, however, be the most bio-available to the host. Bioavailability may be influenced by food composition as most of the phytochemicals are likely to be complexed with other plant components. Host factors will also influence bioavailability including enzyme activity and gut transit time. Following ingestion, the absorption of certain phytochemicals will occur in the small intestine where some glycosides will be hydrolysed. Rapidly absorbed plant metabolites will enter systemic circulation following methylation, sulphation and/or glucuronidation. However, many phytochemicals escape absorption early in the GI tract and in particular those bound to plant polymers reach the colon and are metabolised and released by the gut microbiota( Reference Russell, Scobbie and Labat 72 ). Data regarding the metabolism and bioavailability of these products are severely lacking, particularly with reference to the mechanisms of transformation and the species responsible. The involvement of the gut microbiota in conversion of these plant metabolites is demonstrated by the fact that their metabolites appear after 6–8 h in systemic circulation( Reference Russell, Gratz and Duncan 8 ). The majority of plant metabolites present in the form of glycosides will be converted to aglycones prior to further transformation. It is likely that the compounds that reach the functional sites such as cells and tissues will be chemically different from those consumed in the diet. To evaluate their potential role in cancer prevention, the structure, concentration and site of action must be established. In the colon, they can exert a direct action such as an anti-inflammatory effect on the gut mucosa or be absorbed from the colon via hepatic circulation and suppress low-level chronic systemic inflammation.
Both the parent compounds and the metabolites produced have the potential to influence specific microbial groups. Of the secondary metabolites, the group most widely studied are products of the phenylpropanoid pathway, as nearly all plant foods considered to have cancer-preventative properties are rich in these compounds( Reference Russell, Scobbie and Labat 73 ) including cinnamic, phenylacetic, phenylpropionic, coumarins, flavonoids and anthocyanidins( Reference Russell, Scobbie and Labat 72 ).
Although these phenylpropanoid derivatives are most widely studied, many other secondary metabolites and their derivatives are present in the human colon. Moreover, glucosinolates and their metabolites (isothiocyanates and indoles) have also been extensively studied in relation to protection against carcinogenesis and mutagenesis( Reference Higdonm, Delage and Williams 74 , Reference Mithen, Dekker and Verkerk 75 ), while many other N- and S-related compounds have been generally overlooked in terms of metabolism. For some studies, the presence of specific gut metabolites was detected in plasma and urine by MS indicating that these compounds have entered systemic circulation via enterohepatic circulation. For example, urinary phenolic acid metabolites, measured by GC–MS, were significantly increased following consumption of red wine and red grape juice extracts( Reference van Dorsten, Grün and van Velzen 76 ). The best markers of intake included syringic acid, 3- and 4-hydroxyhippuric acid and 4-hydroxymandelic acid. Reductions in p-cresol sulphate, 3-indoxylsulphuric acid and increases in indole-3-acetic acid and nicotinic acid were also observed in urine following consumption of red wine and grape extracts( Reference Jacobs, Fuhrmann and van Dorsten 77 ). In addition, sesamin, a major bioactive lignin found in sesame seeds was metabolised to enterolactone by in vitro incubation with mixed faecal microbiota. Sesamin consumption also demonstrated that this compound was a precursor to enterolactone in vivo ( Reference Peñalvo, Heinonen and Aura 78 ). Ingestion of a range of ellagitannin-rich foods, demonstrated that the microbial metabolite 3,8-dihydroxy-6H-dibenzo[b,d]pyran-6-one (urolithin B) conjugated with glucuronic acid was detected in urine by liquid chromatography–MS( Reference Cerdá, Tomás-Barberán and Espín 79 ). These urolithin metabolites were also presently found to be present in human plasma( Reference Seeram, Henning and Zhang 80 ).
Gut metabolites and human disease
Obesity and cancer are characterised by chronic low-grade inflammation and the products of microbial metabolism have the ability to modulate these effects (Fig. 3). Although the molecular mechanisms are still uncertain, particular receptors appear to have a clear role. These include Toll-like receptor (TLR) 4 and TLR5. The lipopolysaccharide of B. fragilis is unusual and likely to be at least 100–1000-times less toxic than that of E. coli. There is currently much interest in the role of bacterial lipopolysaccharide signalling via TLR4 and invoking a low grade inflammatory response which in turn may impact on metabolic health. Mice deficient in TLR5( Reference Vijay-Kumar, Aitken and Carvalho 81 ) showed increased adipose-tissue mass, reduced insulin sensitivity, increased blood lipids and higher blood pressure when compared with normal mice and a high-fat diet exacerbated these effects and demonstrated features of human metabolic syndrome. Interestingly, when germ-free normal mice were inoculated with the microbiota obtained from TLR5 deficient mice, these mice also developed symptoms of metabolic syndrome( Reference Vijay-Kumar, Aitken and Carvalho 81 ). In this case, the ligands acting on these receptors are unknown.
Fig. 3. Effect of the gut microbiota on the relationship between obesity and cancer.
Bacteria ferment dietary residues to SCFA and acetate, propionate and butyrate are the major acids detected. In addition to being the major energy source for the colonocytes( Reference Hamer, Jonkers and Venema 82 ), butyrate has a role in inhibition colonic inflammation and oxidative stress. At the molecular level, the anticarcinogenic effect of butyrate is a result of regulation of gene expression and the inhibition of histone deacetylease activity. Butyrate is transported across the colonic epithelium by two specific carrier-mediated transport systems both of which have been reported to function as tumour suppressors. SCFA generated by the microbiota modulate the immune response through GPR43( Reference Masklowski, Vieira and Ng 83 ) which are expressed in a wide range of host tissues. In particular, butyrate and propionate, have been identified as physiological ligands. Activation of GPR43 by SCFA contributes to the inhibition of lipolysis and to adipocyte differentiation which may be modulated by fructo-oligosaccharides( Reference Sleeth, Thompson and Ford 65 , Reference Delzenne and Cani 84 , Reference Tang, Chen and Jiang 85 ). Peptidoglycan released from the microbiota has also been shown to prime the innate immune system through NOD1( Reference Clarke, Davis and Lysenko 86 ).
In this context, the potential impact of dietary metabolites extends beyond gut health to include cardiovascular and metabolic health. This includes Type 2 diabetes mellitus which was found to be associated with changes in the gut microbiota regardless of BMI. Specifically, clostridial species were reduced and the ratio of Bacteroides to Firmicutes correlated positively with plasma glucose concentration, but not with BMI( Reference Larsen, Vogensen and van den Berg 87 ). Bacteroides vulgatus and Bifidobacterium species were also lower in the diabetic group( Reference Wu, Wang and Sun 88 ). Subjects with Type 2 diabetes mellitus were also found to have reduced numbers of F. prausnitzii, which correlated with increased inflammatory markers( Reference Furet, Kong and Tap 89 ). Evidence also supports the hypothesis that host recognition of the gut microbiota is essential in preventing onset and progression of Type 1 diabetes. This is likely to involve the myeloid differentiation factor 88 signalling pathway, but the microbial product initiating the response is yet to be identified.
Obesity
Obesity is a major health problem both in developed and in developing nations and arises when energetic content of food ingested is in excess of energy expenditure. Excess body fat is associated with a number of metabolic diseases such as diabetes, CVD and cancer and can also have a major impact on longevity and quality of life. There has been much interest in the potential role of non-digestible dietary carbohydrates for body weight control and obesity( Reference Nilsson, Ostman and Holst 90 ). Drastic reduction in total dietary carbohydrate intake in weight loss diets alters the composition of the colonic microbial community as well as faecal metabolite profiles( Reference Duncan, Belenguer and Holtrop 2 , Reference Duncan, Lobley and Holtrop 91 ). Colonic fermentation provides an additional source of energy to the host via absorption of SCFA that is estimated to contribute about 10% of dietary energetic intake( Reference Bergman 92 ) and bacterial fermentative activity in the colon may contribute to fat deposition( Reference Backhed, Ley and Sonnenburg 93 , Reference Turnbaugh, Ley and Mahowald 94 ). The energy recovered from ingested sugar by this route is, however, less than that for sugar directly absorbed in the small intestine( Reference Roberfroid 95 ). The net effect must therefore depend largely on how alternative sources of dietary carbohydrate influence satiety. High intakes of monosaccharides such as glucose and fructose present in soft drinks appear to increase serum ghrelin, activating hunger signals and decreasing satiety( Reference Dornonville de la Cour, Lindqvist and Egecioglu 96 , Reference Robertson, Bickerton and Dennis 97 ). It has been suggested that fructo-ologosaccharides intake, on the other hand, results in decreased ghrelin levels that may help in the control of food intake( Reference Delzenne, Cani and Neyrinck 98 ).
Obese human subjects on weight loss diets were shown to have altered microbial profiles( Reference Ley, Backhed and Turnbaugh 20 , Reference Ley 99 ). Also, drastic reduction in total dietary carbohydrate intake in weight loss diets alters the composition of the colonic microbial community as well as faecal metabolite profiles( Reference Duncan, Belenguer and Holtrop 2 , Reference Duncan, Lobley and Holtrop 91 ). Microbial metabolites associated with increased weight gain include increased excretion of hypoxanthine, hippurate, dimethylglycine and creatinine in the urine( Reference Zhang, Yan and Gao 100 ). Studies where weight loss was achieved via gastric bypass surgery demonstrated that asparagine, lysophosphatidylcholine (C18:2), nervonic (C24:1) acid, p-cresol sulfate, lactate, lycopene, glucose and mannose were all significantly reduced( Reference Mutch, Fuhrmann and Rein 101 ).
Cancer
CRC accounts for approximately 17 000 deaths in the UK annually and progression of the disease is likely to result from a combination of genetic and environmental factors. The majority of CRC is thought to be sporadic in origin with the most common form, adenocarcinoma, developing from glandular cells lining the colonic wall. There are several genetic events commonly occurring in CRC at the molecular level that include inactivation of the tumour suppressor genes such as p53 along with activation of oncogenes including the ras family of genes. Not all colorectal polyps progress to cancer, suggesting that perhaps other factors can influence malignant transformation. There is increasing evidence supporting the role of inflammation in the pathogenesis of the gut, including diseases such as CRC. Compared with healthy subjects, patients suffering from inflammatory bowel disease are considerably more likely to develop CRC( Reference Rhodes and Campbell 102 ). One of the similarities between inflammatory bowel disease-associated and sporadic CRC is the importance of cyclooxygenase-2 induction and this enzyme is induced in response to mediators of inflammation, cytokines and endotoxins. In the healthy colon, the thick mucin layer helps to protect the epithelial cells from direct contact with bacterial cells( Reference Johansson, Johansson-Haque and Okret 103 ). Moreover, tight junctions are located in the epithelium that create a barrier which regulates permeability of the epithelial layer in response to various signals including cytokines. Maintenance of an intact epithelial layer is one of the mechanisms that limit bacterial translocation. Bacterial cells may also provide a source of regulatory signals that, for example, direct the differentiation of T-helper cells producing IL-17 (T-helper 17 cells) and T-regulatory cell activity. These signals influence the maturation of the gut and the immune system. In the absence of bacteria these defence systems are likely to be weakened.
Most of the bacteria in the colon possess a number of microbial-associated molecular pattern moieties that are well recognised by cells of the innate immune system. These molecular motifs are recognised by TLR. For example, bacterial lipopolysaccharide, an endotoxin is recognised by TLR4, a recognition receptor of the innate immune system. Bacterial flagellin is recognised by TLR5 and lipoteichoic acid by TLR2. Deficiency in TLR2 has been reported to lead to both increased tumour burden and size in mice with dextran sodium sulphate-induced colitis. This has been related to increased cytokine levels of, for example, IL-6; TNFα that may drive inflammation and induce CRC. Separately, both TLR2 and TLR5 play a role in the suppression of tumour formation, via the activation of specific anti-tumour immunity. Mice deficient in TLR4 were protected against the development of neoplasia as TLR4 signalling can promote colon carcinogenesis by stimulating tumour infiltration of T-helper 17 cells. One of the key lipopolysaccharide producing species in the colon is E. coli ( Reference Erridge, Duncan and Bereswill 104 ) although the abundance of this species is likely to be a small proportion of the total bacterial load. There have been a number of bacterial species associated with CRC including the Gram-positive Streptococcus species and the Gram-negative Helicobacter species, B. fragilis and E. coli. It is not only the balance of bacterial species in the colon that is important for maintaining gut health; in addition the impact of changing bacterial composition in response to dietary intake also drives bacterial metabolite formation.
Microbial metabolites may be a key factor in regulating inflammatory and immunological responses in the colon. Metabolism of dietary carbohydrates will result in the formation of SCFA and as discussed earlier butyrate plays an important role in health maintenance. Increasing the protein content of the diet particularly by increasing red meat intake is likely to result in increased levels of toxic metabolites that include heterocyclic amines, fecapentaenes, nitrosamines, super oxide radicals and hydrogen sulphide( Reference Gill and Rowland 105 ). Fecapentaenes are mutagens that are reportedly synthesised by Bacteroides species that may alkylate DNA to form mutagenic adducts. Hydrogen sulphide is also a toxic microbial metabolite formed by sulphate reducing bacteria, including Desulfovibrio piger, in the colon. D. piger can metabolise lactic acid that may accumulate in bowel disease( Reference Vernia, Caprilli and Latella 106 , Reference Vernia and Cittadini 107 ) while reducing sulphate to sulphide( Reference Marquet, Duncan and Chassard 108 ) and meat is a major source of sulphur that promotes the growth of sulphate reducing bacteria( Reference Christl, Gibson and Cummings 109 ). The genotoxic potential of hydrogen sulphide is in part mediated by oxidative free radicals and cyclooxygenase-2 is up-regulated in epithelial cells following administration of hydrogen sulphide at physiological concentrations( Reference Magee, Richardson and Hughes 110 ). Colonic bacteria also play a role in the formation of N-nitroso compounds, the levels of which are elevated following intake of high protein diets, particularly meat( Reference Russell, Gratz and Duncan 8 ). Cooking meat generates heterocyclic amines that can be further transformed to genotoxic intermediates. The production of these products is likely to be linked to increased risk of CRC( Reference Hughes, Magee and Bingham 111 ).
Secondary bile acids, mainly deoxycholic acid and chenodeoxycholic acid, are formed by microbial conversion of the primary acids that are formed in the liver and secreted into the duodenum. Approximately one litre of bile enters the duodenum each day; however, bile acid excretion is related to fat and red meat intake that are potential risk factors for CRC( Reference Reddy 112 ). Epidemiological studies reported higher concentrations of secondary bile acids in CRC patients compared with healthy controls( Reference Gill and Rowland 105 ). Secondary bile acids can cause DNA damage( Reference Gill and Rowland 105 ) by the production of oxygen radicals and reactive nitrogen species( Reference Payne, Bernstein and Bernstein 113 , Reference Dvorak, Payne and Chavarria 114 ). Bile acids enter enterohepatic circulation therefore the concentration decreases along the GI tract, however, elevated bile acid levels may modulate the abundance of certain bacterial species including F. prausnitzii ( Reference Lopez-Siles, Khan and Duncan 115 ) that has been reported to have potent anti-inflammatory activity( Reference Sokol, Pigneur and Watterlot 116 ).
Conclusions
The large intestine may appear to be a hostile environment for bacteria to inhabit, but nonetheless represents a densely populated microbial ecosystem. Moreover, on balance the host is likely to benefit from these multi-species communities in the gut when the balance of species provides mostly beneficial metabolites. Microbial imbalance however may well result in a less favourable metabolic output that will make an impact on inflammatory status and disease progression. As an example, carefully controlled dietary intervention studies have revealed that high protein diets (mainly meat-based) result in elevated levels of hazardous metabolites and a decrease in cancer protective metabolites. High protein diets are satiating and therefore, in the short term may be efficacious in achieving weight loss( Reference Johnstone, Horgan and Murison 117 ). In addition, the health risks associated with consuming high meat protein diets may be partially ameliorated by including cereals in the diet and/or exchanging meat protein for plant protein. The phenolic content of the latter may afford some health benefits. Understanding of the microbial ecosystem of the human colon will continue to benefit from a range of molecular approaches which should be developed in parallel with metabolomic approaches. Our dietary intake clearly has an important influence on the species composition of gut microbiota, but this appears insufficient to explain the extent of variation that is seen between individuals. As MS methodologies continue to develop and its usage increases a clearer and much needed understanding of the complex interplay between diet, the gut microbiota and human health will be achieved. There is also a need to link detailed microbial diversity to metabolic functionality to ascertain if general dietary advice is sufficient or there may be a need, in certain circumstances, to provide personalised nutritional advice.
Acknowledgements
The authors are grateful for funding from the Scottish Government Food, Land and People Programme. The authors declare no conflict of interest and contributed equally to the writing of this manuscript.
