Symbiotic gut microorganisms (microbiome) interact closely with the mammalian host's metabolism and are important determinants of human health. Here, we decipher the complex metabolic effects of microbial manipulation, by comparing germfree mice colonized by a human baby flora (HBF) or a normal flora to conventional mice. We perform parallel microbiological profiling, metabolic profiling by 1H nuclear magnetic resonance of liver, plasma, urine and ileal flushes, and targeted profiling of bile acids by ultra performance liquid chromatography–mass spectrometry and short‐chain fatty acids in cecum by GC‐FID. Top‐down multivariate analysis of metabolic profiles reveals a significant association of specific metabotypes with the resident microbiome. We derive a transgenomic graph model showing that HBF flora has a remarkably simple microbiome/metabolome correlation network, impacting directly on the host's ability to metabolize lipids: HBF mice present higher ileal concentrations of tauro‐conjugated bile acids, reduced plasma levels of lipoproteins but higher hepatic triglyceride content associated with depletion of glutathione. These data indicate that the microbiome modulates absorption, storage and the energy harvest from the diet at the systems level. ### Synopsis The symbiotic gut microbiome acts as an extended genome ([Lederberg, 2000][1]) and has evolved to exert control on a number of important mammalian metabolic regulatory functions ([Backhed et al , 2004][2]; [Eckburg et al , 2005][3]; [Holmes and Nicholson, 2005][4]; [Nicholson et al , 2005][5]; [Martin et al , 2006][6]; [Nicholson, 2006][7]; [Turnbaugh et al , 2006][8]). Gut microbial composition is now known to vary significantly in obese animal ([Turnbaugh et al , 2006][8]) and human ([Ley et al , 2006][9]) populations, and recent studies have shown that the exact state of the gut microbial ecology and metabolic activities may be of fundamental importance in the control of calorific absorption ([Xu et al , 2003][10]; [Backhed et al , 2004][2]) and in the development of insulin resistance and non‐alcoholic fatty liver disease ([Dumas et al , 2006][11]). The integrated mammalian microbial co‐metabolism of the bile acid pool is a good example of the complex biochemical interactions between host and resident symbionts, as summarized in [Figure 1][12]. Bile acids are crucial for the absorption of dietary fats and lipid‐soluble vitamins in the intestine ([Staggers et al , 1982][13]) and might have an essential role in regulating obesity or type II diabetes ([Houten et al , 2006][14]; [Watanabe et al , 2006][15]). Many so‐called secondary bile acids (deoxycholic, lithocholic, hyodeoxycholic and ω‐muricholic acids) can be regarded as examples of mammalian–microbiotal co‐metabolism ([Nicholson et al , 2005][5]) and have different metabolic fates via enterohepatic recirculation ([Nicholson et al , 2004][16]). The aim of the study is to assess the effects of the induction of a non‐adapted microflora in a murine model (human baby flora (HBF)) on the host metabolism by comparison with animals colonized with a natural, conventional gut microflora, the result of a long period of co‐evolution. Here, we have integrated the effects of modulation of the microbiome in mouse models on the co‐metabolism of the major bile acids and the general metabolic profiles of the animals. We acquired parallel metabolic profiles of plasma, urine, liver, fecal extracts and ileal flushes using nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry to characterize a broad range of metabolites across these multiple compartments and 14 bile acids, which were also specifically measured in ileal flushes. The application of high‐resolution 1H NMR spectroscopy of biofluids and tissues coupled with multivariate statistical methods is a well‐established tool for differential metabolic pathway profiling ([Nicholson et al , 2002][17]; [Nicholson et al , 2005][5]; [Nicholson and Wilson, 1989][18]; [Wang et al , 2005][19]). Hyphenated chromatographic‐mass spectrometric methods such as ultra‐performance liquid chromatography–mass spectrometry (UPLC–MS)‐based profiling techniques have also been recently used effectively for functional genomic discrimination ([Plumb et al , 2005][20]; [Wilson et al , 2005][21]). We have now developed and enhanced bile acid analysis method using UPLC–MS, which gives superior chromatographic resolution and sensitivity ([Wilson et al , 2005][21]; [Plumb et al , 2006][22]). We show here a significant association of specific metabotypes obtained from urine, plasma, intact liver tissue and ileal flushes with changes of the gut microbiome in mice colonized naturally with a conventional microflora or with a defined population of microbes in a pathogen‐free environment, that is, exposing germ‐free mice to normal environment to be naturally re‐colonized by bacteria or fed with an HBF. Such exhaustive metabolic profiling revealed that re‐conventionalized mice, that is, those germ‐free mice allowed to equilibrate to a conventional flora, tend to converge metabolically and ecologically towards conventional mice and a healthy physiology. We also report that the re‐colonization of germ‐free mice with a non‐adapted microflora (HBF) modifies the physiology of the murine host towards a pre‐pathologic state (compared to conventional animals) and maintains the gut tract and the liver outside a sustainable mouse ecological equilibrium. Using a transgenomic bipartite graph model highlighting functional relationships between fecal bacteria profiles and bile acid profiles, we show that HBF flora has a remarkably simple microbiome/metabolome correlation network, impacting directly on the host's ability to metabolize fats. The metabolic consequences for the host...

The transgenomic metabolic effects of exposure to either Lactobacillus paracasei or Lactobacillus rhamnosus probiotics have been measured and mapped in humanized extended genome mice (germ‐free mice colonized with human baby flora). Statistical analysis of the compartmental fluctuations in diverse metabolic compartments, including biofluids, tissue and cecal short‐chain fatty acids (SCFAs) in relation to microbial population modulation generated a novel top‐down systems biology view of the host response to probiotic intervention. Probiotic exposure exerted microbiome modification and resulted in altered hepatic lipid metabolism coupled with lowered plasma lipoprotein levels and apparent stimulated glycolysis. Probiotic treatments also altered a diverse range of pathways outcomes, including amino‐acid metabolism, methylamines and SCFAs. The novel application of hierarchical‐principal component analysis allowed visualization of multicompartmental transgenomic metabolic interactions that could also be resolved at the compartment and pathway level. These integrated system investigations demonstrate the potential of metabolic profiling as a top‐down systems biology driver for investigating the mechanistic basis of probiotic action and the therapeutic surveillance of the gut microbial activity related to dietary supplementation of probiotics. ### Synopsis The gut microbiome–mammalian ‘Superorganism’ ([Lederberg, 2000][1]) represents the highest level of biological evolutionary development in which there is extensive ‘transgenomic’ modulation of metabolism and physiology, which is a characteristic of true symbiosis. By definition, superorganisms contain multiple cell types and the coevolved interacting genomes can only be effectively studied as an in vivo unit in situ using top‐down systems biology approaches ([Nicholson, 2006][2]; [Martin et al , 2007a][3]). Interest in the impact of gut microbial activity on human health is expanding rapidly and many mammalian–microbial associations, both positive and negative, have been reported ([Dunne, 2001][4]; [Verdu et al , 2004][5]; [Nicholson et al , 2005][6]; [Gill et al , 2006][7]; [Ley et al , 2006][8]). As the microbiome interacts strongly with the host to determine the metabolic phenotype ([Holmes and Nicholson, 2005][9]; [Gavaghan McKee et al , 2006][10]) and metabolic phenotype influences outcomes of drug interventions ([Nicholson et al , 2004][11]; [Clayton et al , 2006][12]) there is clearly an important role of understanding these interactions as part of personalized healthcare solutions ([Nicholson, 2006][2]). Probiotics, most commonly Lactobacillus and Bifidobacteria , is one of the current approaches used to modulate the balance of the intestinal microflora in a beneficial way ([Collins and Gibson, 1999][13]). However, the functional effects of probiotic interventions cannot be fully assessed without probing the biochemistry of the host at multiple compartmental levels and we propose that top‐down systems biology provides an ideal approach to further understanding in this field. The microbiota observed in human baby flora mice has a number of similarities with that found in formula‐fed neonates ([Mackie et al , 1999][14]) that makes it be a well‐adapted and simplified model to assess probiotics impact on gut microbial functional ecosystem (in particular on metabolism of Bifidobacteria and potential pathogens) and subsequent effects on host metabolism. Metabolic profiling using high‐density data generating spectroscopic techniques, in combination with multivariate mathematical modelling is a tool that is well suited to generating metabolic profiles that encapsulate the top‐down system response of an organism to a stressor or intervention ([Nicholson and Wilson, 2003][15]). Recently, metabolic profiling strategies have been successfully applied to investigating the effects of the gut microflora on mammalian metabolism ([Martin et al , 2007a][3]), including probiotic treatment on germ‐free mice ([Martin et al , 2007b][16]), modulation of Trichinella spiralis ‐induced gut disorders ([Martin et al , 2006][17]) and mechanisms of insulin‐resistance ([Dumas et al , 2006][18]). In the current study, both 1H nuclear magnetic resonance spectroscopy and ultra performance liquid chromatography‐mass spectrometry analysis have been applied to characterize the global metabolic responses of humanized microbiome mice subsequently exposed to placebo, Lactobacillus paracasei or Lactobacillus rhamnosus supplementation. Correlation of the response across multiple biofluids and tissue, using plasma, urine, fecal extracts, liver tissues and ileal flushes as the biological matrices for the detection of dietary intervention, generates a top‐down systems biology view of the response to probiotics intervention. Significant associations between host metabolic phenotypes and a nutritionally modified gut‐microbiota strongly supports the idea that changes across a whole range of metabolic pathways are the products of extended genome perturbations that can be oriented using probiotic supplementation, and which may play a role in host metabolic health. Here, we show that probiotics supplementation of humanized mice resulted in a decrease in the plasma concentrations of VLDL and low density lipoproteins (LDL), and increased triglyceride concentrations ([Figure 1][19]), through inducing changes in the enterohepatic recirculation of bile acids, which were shown to lower cholesterol and systemic levels of blood lipids ([Pereira and Gibson, 2002][20]). In particular, the Lactobacillus supplementation resulted in decreased fecal excretion of bile acids ([Figure 1C][19]), that may be caused by accumulation of bile acids in Lactobacillus probiotics ([Kurdi et al , 2000][21]). Moreover, probiotic‐specific modulation of the ileal...

To characterize the impact of gut microbiota on host metabolism, we investigated the multicompartmental metabolic profiles of a conventional mouse strain (C3H/HeJ) ( n =5) and its germ‐free (GF) equivalent ( n =5). We confirm that the microbiome strongly impacts on the metabolism of bile acids through the enterohepatic cycle and gut metabolism (higher levels of phosphocholine and glycine in GF liver and marked higher levels of bile acids in three gut compartments). Furthermore we demonstrate that (1) well‐defined metabolic differences exist in all examined compartments between the metabotypes of GF and conventional mice: bacterial co‐metabolic products such as hippurate (urine) and 5‐aminovalerate (colon epithelium) were found at reduced concentrations, whereas raffinose was only detected in GF colonic profiles. (2) The microbiome also influences kidney homeostasis with elevated levels of key cell volume regulators (betaine, choline, myo ‐inositol and so on) observed in GF kidneys. (3) Gut microbiota modulate metabotype expression at both local (gut) and global (biofluids, kidney, liver) system levels and hence influence the responses to a variety of dietary modulation and drug exposures relevant to personalized health‐care investigations. ### Synopsis The gut microbiota (microbiome) form a complex and dynamic ecosystem that constantly interacts with host metabolism ([Dunne, 2001][1]; [Hooper and Gordon, 2001][2]; [Bourlioux et al , 2003][3]). The microbiome provides trophic ([Hooper and Gordon, 2001][2]) and protective ([Umesaki and Setoyama, 2000][4]) functions and impact on the host's energy metabolism ([Savage, 1986][5]), facilitating the absorption of complex carbohydrates (fiber breakdown) and influencing the homeostasis of amino acids ([Hooper et al , 2002][6]). But despite their evident important contribution to host biology and function, some bacterial species contained in the gut also have the potential to generate carcinogens or can be the source of opportunistic infections ([Berg, 1996][7]). We have recently demonstrated a close relationship between the metabolism of gut microbiota and the susceptibility of rodents to insulin resistance in high‐fat diet studies ([Dumas et al , 2006a][8]). In this context, recent investigations have shown that even subtle changes in the gut microbiota have an impact on the host phenotype ([Holmes and Nicholson, 2005][9]; [Robosky et al , 2005][10]; [Rohde et al , 2007][11]). Germ‐free (GF) animal studies have been widely used as a source of knowledge on the gut microbiota contributions to host homeostatic controls ([Wostmann, 1981][12]). GF mice display unusual gut morphology, as well as physiological and immunological abnormalities. However, despite the extensive use of GF models, the exact mechanisms involved in the morphologic, physiologic and immunologic modifications in GF animals remain unclear. The characterization of the metabolic differences between conventional and GF mice is, therefore, an essential step toward better understanding the interaction between host and gut microbiota. Metabonomic approaches combining spectroscopic profiling techniques with pattern recognition analysis have proved useful in the assessment of the systemic metabolic responses of organisms to drugs or nutrients ([Nicholson et al , 2002][13]; [Lindon et al , 2004][14]; [Dumas et al , 2006b][15]; [Rezzi et al , 2007][16]). In the current study, we employed a high‐resolution 1H NMR spectroscopic approach to investigate the metabolic phenotype, or metabotype ([Gavaghan et al , 2000][17]), of GF mice from urine and tissues (gut, liver and kidney) and to determine the biochemical consequences of the absent microbiome on these biological matrices. In the current study, we demonstrate that the metabolic impact of the microbiota extended beyond the intestinal tissue and biofluids to major organs such as the liver and kidney. In the gut, metabolic variations in response to microbial activity were observed in the biochemical profiles of intestinal tissue extracts with increasing effect along the continuous gastrointestinal tract. It was observed that duodenum and jejunum displayed fewer metabolic differences between GF and conventional mice, whereas ileum and particularly colon were the most affected. This reflects the higher microbial loads found in ileum and colon. The metabolite profiles of duodenum, jejunum and ileum were all characterized by a higher concentration of tauro‐conjugated bile acids in GF mice, which is not apparent in the colon profile. In conventional animals, tauro‐ and glycine‐conjugated bile acids are deconjugated by gut microbiota, facilitating their fecal elimination. Here, in the absence of microorganisms, primary bile acids are reabsorbed into the enterohepatic cycle, without deconjugation. This increased recycling of bile acids was also suggested by the significantly higher level of phosphocholine and by the observed trend of higher concentration of bile acids in the liver metabolic profile of GF mice. The colonic metabolite profile in GF mice was characterized by lower levels of choline and its phosphorylated derivatives, glycerophosphocholine and phosphocholine. This is likely due to the disturbance of the membrane of colonocytes in GF animals. We also observed raffinose accumulation in these cells, which is probably another consequence of the membrane disruption. Raffinose is an oligosaccharide that is only digested by the gut microbiota, as monogastric animals do not express pancreatic α‐galactosidase ([LeBlanc et al , 2004][18]). In GF animals, it seems that this trisaccharide is able to cross the epithelial membrane and accumulates in colonocytes where it induces a rise in osmotic pressure. This phenomenon provokes a well‐described signaling cascade that leads to the release of the mobile osmolytes GPC, myo ‐inositol and scyllo...

The aging phenotype in humans has been thoroughly studied but a detailed metabolic profiling capable of shading light on the underpinning biological processes of longevity is still missing. Here using a combined metabonomics approach compromising holistic ¹H-NMR profiling and targeted MS approaches, we report for the first time the metabolic phenotype of longevity in a well characterized human aging cohort compromising mostly female centenarians, elderly, and young individuals. With increasing age, targeted MS profiling of blood serum displayed a marked decrease in tryptophan concentration, while an unique alteration of specific glycerophospholipids and sphingolipids are seen in the longevity phenotype. We hypothesized that the overall lipidome changes specific to longevity putatively reflect centenarians' unique capacity to adapt/respond to the accumulating oxidative and chronic inflammatory conditions characteristic of their extreme aging phenotype. Our data in centenarians support promotion of cellular detoxification mechanisms through specific modulation of the arachidonic acid metabolic cascade as we underpinned increased concentration of 8,9-EpETrE, suggesting enhanced cytochrome P450 (CYP) enzyme activity. Such effective mechanism might result in the activation of an anti-oxidative response, as displayed by decreased circulating levels of 9-HODE and 9-oxoODE, markers of lipid peroxidation and oxidative products of linoleic acid. Lastly, we also revealed that the longevity process deeply affects the structure and composition of the human gut microbiota as shown by the increased extrection of phenylacetylglutamine (PAG) and p-cresol sulfate (PCS) in urine of centenarians. Together, our novel approach in this representative Italian longevity cohort support the hypothesis that a complex remodeling of lipid, amino acid metabolism, and of gut microbiota functionality are key regulatory processes marking exceptional longevity in humans.