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      Gut microbiota’s effect on mental health: The gut-brain axis

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          Competing interest statement Conflict of interest: the authors declare no potential conflict of interest. Abstract The bidirectional communication between the central nervous system and gut microbiota, referred to as the gut-brain-axis, has been of significant interest in recent years. Increasing evidence has associated gut microbiota to both gastrointestinal and extragastrointestinal diseases. Dysbiosis and inflammation of the gut have been linked to causing several mental illnesses including anxiety and depression, which are prevalent in society today. Probiotics have the ability to restore normal microbial balance, and therefore have a potential role in the treatment and prevention of anxiety and depression. This review aims to discuss the development of the gut microbiota, the linkage of dysbiosis to anxiety and depression, and possible applications of probiotics to reduce symptoms. Introduction Healthy gut function has been linked to normal central nervous system (CNS) function. 1-4 Hormones, neurotransmitters and immunological factors released from the gut are known to send signals to the brain either directly or via autonomic neurons. The existence of the gut-brain axis was proposed in the landmark study by Sudo and colleagues that discovered the impaired stress response in germ-free mice. Other studies using germ-free mice not only supported this existence, but also the idea that the gut-brain-axis (GBA) extends even beyond these two systems into the endocrine, neural, and immune pathways. 2,5 Recently, studies have emerged focusing on variations in the microbiome and the effect on various CNS disorders, including, but not limited to anxiety, depressive disorders, schizophrenia, and autism. 2,8,9 This review focuses on the GBA in the context of anxiety and depressive disorders. Therapeutic interventions to treat dysbiosis, or disturbance in the gut, and mitigate its effects on the GBA are only recently coming to the forefront as more is known about this unique relationship. As a result, research has been done on the use of probiotics in treatment of anxiety and depression both as standalone therapy and as adjunct to commonly prescribed medications. These findings as well as their potential impact on treatment are discussed in this paper. 4,9 An overview of the role of the gut microbiome, from its development, to its relationship with the emotional and cognitive centers of the brain, while also providing ideas for future research, are included in this review. The microbiome is defined as all microorganisms in the human body and their respective genetic material. The microbiota is defined as all microorganisms in a particular location, such as the GI tract or skin. 10,11 This distinction is relevant as this review will focus on the microbiota of the gut in the context of the gut-brain axis, though there will be discussion of the human microbiome where appropriate. Materials and Methods This literature review is based on English-language articles sourced from PubMed. Keywords searched included: microbiome development, neonatal microbiome, negative aspects of probiotic use, anxiety and depressive disorders, gut brain axis, anxiety, depression, hypothalamic-pituitary axis (HPA), stress and the microbiome, microbiome composition, intestinal bowel disease, cytokines, TNF-a, interleukins, leaky gut, anxiety, depression, and prostaglandins. Antibiotics were not included in the search as the authors felt it was beyond the scope of the discussion regarding the existing microbiome, stress responses, and their relationship with depression and anxiety disorders. No geographical limitations were included in the search. Publications were initially excluded if they were published before 2010. However, in order to include an in depth understanding of the research, articles published before 2010 were included if they were cited in research published after 2010. This review contains articles published through July of 2017. Results and Discussion Development of the microbiome The microbiome is initially developed via vertical transmission through the placenta, amniotic fluid, and meconium. 12-14 Two animal study suggested that fetuses exposed to prenatal stress in the form of maternal stress develop a gut microbiota with decreased Bifidobacterium. 14,15 Two separate studies concluded that the mode of delivery affects the initial microbiome and gut microbiota. Infants delivered vaginally had higher amounts of bacteria in their gut compared to infants delivered by Cesarean section. 12,13 Beginning with the first week of life, gastric colonization is highly dynamic. This critical period during birth and GI development is essential for newborn health and immunity. 16 Microbiota underdevelopment during this period has been correlated with numerous stress states including lateonset sepsis, 17 cardiovascular disease, and atopic disease. 18 Early nutrition also appears to play a role in shaping the developing gut microbiota. Studies found that breastfeeding was directly correlated with both IgA levels and the number of organisms in the Bifidobacterium genus present in the gut and indirectly correlated with IL-6 levels. 13,15 IgA is predominantly a secretory immunoglobulin that provides immunity within the intestines and other mucosal membranes. In contrast, IL-6 is a proinflammatory cytokine that normally presents in acute and chronic inflammation. Bifidobacterium is an important part of the infant microbiome, 19 and together with species in the Lactobacillus genus, is key in producing gamma-Aminobutyric acid (GABA), an inhibitory regulator of various neural pathways. 20 Breastmilk’s ability to increase IgA and Bifidobacterium species and to decrease IL-6 levels, and subsequently inflammation, reduces the risk of age-related gastroenteritis. 13 In comparison, infants fed formula during their first four weeks of life demonstrated a decrease in total number of bacterial species. 15 Breast milk oligosaccharides includes lactose as well as over 1000 distinct non-digestible molecules. 21 Researchers suggest the non-digestible sugars of breast milk provide a prime nutritional source for bacterial fermentation. 12 Breast milk had similar effects in preterm infants who were shown to have a different bacterial makeup, with a predominance of proteobacteria rather than Bifidobacterium and Lactobacillus. Preterm infants fed breast milk showed an increase only in the number of Bifidobacterium, supporting the concept that breast milk’s non-digestible sugars create an environment better suited for of specific species. 20 Cessation of breastfeeding is the primary diet change that leads to an adult-like microbiome. 22 Children who were weaned from breast milk up to age four showed similar patterns of microbiota development as children weaned at an earlier age, indicating that the length of time to transition from breast milk to solid foods was not as important as the transition itself. 22 The key relationship between the gut microbiota and diet continues throughout life. Diet alterations can have significant impact on the gut bacterial composition in as little as 24 hours. 20 However, the bacterial composition is restored if the change in diet is only temporary. Regardless of the species inhabiting the gut, as long as their symbiotic role is the same, the human host will be able to function as normal. 20 Symbiotic bacteria assist with immune tolerance, intestinal homeostasis, amino acid and vitamin synthesis of the host, leading to a healthy metabolism. 13 The adult microbiome As infants consume increasing amounts of solid food, the microbiome is exposed to diverse energy substrates, developing its carbon metabolism. 22,23 The adult microbiome becomes dominated by the Bacteroidetes and Firmicutes phyla, rather than the Lactobacillus and Bifidobacterium genera. 24 Relatively smaller quantities of the Proteobacteria, Verrucomicrobia, Actinobacteria, and Cyanobactera phyla, and Fusobacteria genus can also be found. 13 However, due to many factors including diet, environment, season, health status, it is almost impossible to define a “normal” microbiome for the average human population. It is important to note that although microbiomes differ between every individual due to genetic diversity, researchers have found that every microbiome falls into one of three enterotypes. These enterotypes differ by which species dominates one’s bacterial composition, and include Bacteroides, Prevotella, or Ruminococcus species. The dominant species and therefore enterotype results from the composition of a person’s diet. Prevotella species enterotype is associated with diets high in carbohydrates versus people eating high amounts of protein are more likely to possess a Bacteriodes species enterotype. 25 Interestingly, these enterotypes are independent of environmental components such as age, body-mass index, gender and geographic location and seem to only be dependent on diet and genetics. 26 A Danish study of the gut microbiome created the concept of high gene count (HGC) and low gene count (LGC), both of which are implicated in digestive health. 27 Due to a functionally more prosperous microbiome, the HGC group had a decreased risk of both metabolic disease and obesity. Important microbiome functions of the HGC group included an increased proportion of butyrate producing organisms, increased propensity for hydrogen production, and reduced production of hydrogen sulfide. It has also been shown that short chain fatty acids offer relevant benefits in terms of regulatory T cell induction as well as blood-brain barrier integrity. 28,29 In contrast, the LGC group had a larger proportion of pro-inflammatory bacteria which predisposed them to IBD and related disorders. 30,31 The Human Microbiome Project confirms this notion with studies of stool specimens demonstrating that humans with a less diverse microbiome were more likely to be diagnosed with IBD. 25 When the human microbiome is challenged with changes in diet, stress, or antibiotics, the physiology of the normal microbiome undergoes change. A dysbiotic state leads to increased intestinal permeability and allows contents such as bacterial metabolites and molecules as well as bacteria themselves to leak through the submucosa and into the systemic circulation, a phenomenon aptly named leaky gut syndrome. A study by Zoppi et al. demonstrated that the gut microbiota uses the intestinal endocannabinoid system to control the degree of intestinal permeability. 32 A separate study was able to reduce translocation of bacterial antigens such as LPS by using antagonists to the intestinal cannabinoid type 1 receptor in mice. Specifically, the CB1R antagonists cannabidiol and tetrahydrocannabidiol were protective against intestinal permeability, suggesting that cannabinoids could play an important role in treating inflammatory gastrointestinal diseases such as IBD. 33 Increased intestinal permeability leads to detrimental effects on the host immune system, which have been demonstrated in diseases such as inflammatory bowel disease (IBD), diabetes, asthma, and psychiatric disorders including depression, anxiety, and autism. 2,4,10,34,35 Although most of these studies have focused on bacterial species in the gut microbiome, other studies have elucidated the importance of other microorganisms, such as yeast. A study done by Burrus and colleagues suggested that colonization with Candida species may contribute to Autism spectrum disorders. 36 By preventing absorption of carbohydrates and minerals and allowing excessive build-up of toxins, colonization with Candida albicans was shown to increase autistic behaviors in children with autistic spectrum disorder. A similar study suggested that it is the interaction between propionic acid and ammonia released by Candida albicans that results in increased autistic behaviors. 37 This interaction produces an excessive amount of betaalanine, which is similar in structure to GABA and has been proposed to be an important contributor to autism spectrum disorders. The inflammatory response Inflammation of the GI tract places stress on the microbiome through the release of cytokines and neurotransmitters. Coupled with the increase in intestinal permeability, these molecules then travel systemically. Elevated blood levels of cytokines TNF-a and MCP (monocyte chemoattractant protein) increase the permeability of the blood-brain barrier, enhancing the effects of rogue molecules from the permeable gut. 38,39 Their release influences brain function, leading to anxiety, depression, and memory loss. 39-41 Depressive disorders are characterized by both neuroplastic, organizational changes, and neurochemical dysfunction. 42 Illness is thought to begin when there is deregulation of these systems and can largely be attributed to cytokine release secondary to an exaggerated systemic response to stressors. 39,41 Endotoxin infusions to healthy subjects with no history of depressive disorders triggered cytokine release and subsequent emergence of classical depressive symptoms. The study established a direct correlation between increased levels of IL-6 and TNF-a with symptoms of depression and anxiety, 43 indicating that pro-inflammatory cytokines play a role in the development of anxiety and depression. These effects correlated with a state of chronic inflammation and altered immune cells in the peripheral blood. However, TNF-a administered to healthy subjects resulted in no depressive symptoms, 38 suggesting that toxin induced inflammation caused the mood disturbance. Pro-inflammatory cytokines are also important stimulators of the hypothalamic-pituitary-adrenal (HPA) axis (Figure 1). The hypothalamus releases corticotropin releasing factor from the hypothalamus, stimulating the adenohypophysis to release adreno-corticotropic hormone (ACTH). In turn, ACTH stimulates the adrenal release of cortisol, a known stress hormone that acts as a negative feedback signal in the pro-inflammatory signal transduction machinery. 3,41 Hyperactivity or dysregulation of the HPA axis is one of the most reliable biological readouts in major depression and anxiety. 39 Rats with activated stress circuits demonstrated anxiety and depressive-like behaviors. Removal of the stimulus normalized HPA hyper-reactivity, as measured by their endogenous corticosterone levels, and in turn reversed or mitigated their abnormal behaviors. 10 The interconnection of the endocrine, neural, and immune pathways is demonstrated in the relationship between brain derived neurotrophic factor (BDNF) mRNA in the dentate gyrus of the hippocampus and the stress response in germ free mice. BDNF supports the development of neurons and synapses involved in regulation of emotions and cognition; male germ free mice have an increased stress response associated with decreased hippocampus BDNF, which could be reversed by recolonization with Bifidobacteria species. Futhermore, the Bifidobacteria was shown to alter mRNA expression of GABA receptors and decrease serum cortisol. This change was not seen after the mice underwent vagatomies, suggesting that the parasympathetic nervous system was imperative for the bacteria’s effects on their stress response. 24 Probiotics, inflammation, and the HPA axis Probiotics are living microorganisms, typically yeasts and bacteria, that have been utilized as supplements to other medications or as alternative treatments for anxiety and depression. 44 Probiotics have also been studied in the context of suppression of inflammatory cytokines. Some studies have found that human patients suffering from chronic inflammation responded positively to the ingestion of probiotics, as they decreased production of TNF-a. 45.46 In patients with inflammatory bowel disease, probiotics correlated with suppressed levels of pro-inflammatory cytokines, and improved intestinal barrier integrity. This led to a decrease in differentiation of CD4+ T cells into Th2 cells, and inhibition of nuclear factor kappa B, both of which are highly involved in inflammation 47 (Figure 2). Mothers who consumed probiotics compared to controls were found to have an altered gene expression associated with improved inflammatory responsiveness in the placenta and neonatal gut. 20 Probiotic usage in late pregnancy led to a decrease in IL-4, IL-10, and Atopbium, a species of the Actinobacteria phylum, with a concurrent increase in Bifidobacterium species. 48 Mothers who consumed probiotics two weeks prior to delivery had babies with altered expression of TLR-related genes in the placenta and neonatal gut; the TLR gene expression varied based on the type of probiotics the mother consumed. 49 These infants were found to directly respond and modify their inflammatory responses to pathogenic bacteria compared to controls. 49 Thus, providing mothers with specific probiotic formulas may protect the infant from persistent metabolic and immunologic disease processes. Though human symptomatology is the primary interest, animal studies have elucidated the mechanisms underlying the relationship between probiotics and the immune response. Mice with B and T lymphocytes deficient in Rag1, a gene responsible for B and T cell maturation, had increased colonic ion transport, resulting in a state of dysbiosis and altered HPA axis status. These mice were treated with probiotics containing Lactobacillus species and demonstrated reduced intestinal permeability and restored microbiome and HPA-axis functionality. 50 A separate study used mice with a stress-induced reduction of HPA axis function and neuronal firing. Probiotic therapy maintained neurogenesis and synaptic plasticity in the hippocampus, allowing the survival and differentiation of cells into neurons. These mice also produced lower amounts of stress hormones, and preserved intestinal permeability. The Lactobacillus strain in the administered probiotic upregulated BDNF and resulted in increased glucocorticoid regulation of the HPA axis. Probiotics provide a neuroprotective role by preventing stress-induced synaptic dysfunction between neurons. Treatment for as little as two weeks created an appreciable decrease in ACTH and corticosterone levels in rats, illustrating the suppressive effects of probiotics on HPA axis. 1,4 Probiotics have the potential to diminish the HPA axis response to chronic stressors, and prevent or reverse physiologic damage. 4 Human and animal studies of probiotics show similar reductions in anxiety and depressive symptoms. Human patients suffering from chronic stress were given a three-week probiotic treatment containing Bifidobacteria species. Subjects in the bottom third of the elated/depressed scale demonstrated the most improvement with treatment. These patients rated an overall happier mood on daily analogue scales using six dimensions of mood including energetic/tired, composed/anxious, elated/depressed, clearheaded/muddled, confident/unsure, and agreeable/angry. 51 In a 30-day study, healthy volunteers with no previous depressive symptoms were given either probiotics or antidepressants. Those given probiotics showed reduced cortisol levels and improved self-reported psychological effects to a similar degree as participants administered Diazepam, a commonly used anti-anxiety medication. 52 Analogous studies found that probiotic therapy reduced depressive symptoms and improved HPA-axis functionality as well as Citalopram and Diazepam. 53,54 Comparing probiotics to the antidepressant escitalopram in mice, the probiotics were discovered to have similar effects. They were equally successful in anxiety reduction and were more effective than the escitalopram in maintaining healthy metabolism and body weight. 55 Though researchers have not determined the mechanism of action in humans, those who studied probiotics in rats found that oral ingestion of Bifidobacterium infantis resulted in increased tryptophan, a serotonin precursor, 9 and GABA. 56 Despite treatment with multiple antidepressants, each with different methods of action, roughly 20% of patients do not show improvement in reduction of anxiety or depressive symptoms. 57 The human and mouse studies cited above indicated that probiotics normalize cortisol levels, regulate the HPA axis and reduce circulating pro-inflammatory cytokines. These mechanisms suggest probiotic therapies may confer certain benefits over therapeutic drugs. Advantages include ease of availability, lower cost, less dependence, and fewer side effects compared to pharmaceutics. Regulation of the microflora composition offers the possibility to improve immune function, homeostasis, and gut inflammation. 58 Despite numerous studies citing the benefits of probiotic treatment, their specific mechanisms of action are often unknown and understudied, unlike prescription drugs. 59 Thus, dosage becomes an issue, as the mechanisms and long-term effects have yet to be studied in a human population. 60 Probiotics enhance resistance to infectious diseases via excretion of antimicrobial components and increase the concentration of anaerobic gram positive bacteria. However, in some studies, subjects administered probiotics reported fever, headaches, and nausea with increased frequency after a bacterial challenge. 61,62 One study indicated that the probiotics administered in mouse subjects were not sufficient to prevent maleffects from a second immune challenge. This suggests that while probiotics may be helpful in the acute phase, they are not a cure-all in the long term. 50 Prebiotics such as fructo-oligosaccharides and galacto-oligosaccharides are soluble fibers used to stimulate the preexisting gut microbiota. Additional studies in recent years have shown that prebiotics confer similar anxiolytic and antidepressant effects as probiotics as they also diminish stress-induced changes to the colonic microbiota and create stabilized levels of Bifidobacteria and Lactobacilli populations. 63 Conclusions The bidirectional link between the brain, gut, and microbiome has come to the forefront of the medical research community in the past few years. The growing amount of evidence substantiating this link indicates it will be a valuable area for future medical and nutritional practice, and research. This review demonstrates the importance of a healthy microbiome, particularly the gut microbiota, for patients suffering from anxiety and depression, as dysbiosis and inflammation in the CNS have been linked as potential causes of mental illness. Of note, studies have shown that probiotics effectively mitigated anxiety and depressive symptoms similar to conventional prescription medications. 7,51,53,54,56 However, several weaknesses are identified in the course of this selected review. First, research linking TNF, cytokines, and other stressors to the pathogenesis of mental health disorders, particularly anxiety and depression, is lacking, and thus provides an area for future research, particularly regarding levels of intestinal bacteria and their correlation with levels of circulating cytokines. The utility of probiotics is questionable as no form is currently regulated by the FDA, including natural sources such as yogurt, kefir, or sauerkraut. Patients may be more likely to use these natural sources of probiotics both due to increased accessibility as well as the resurgence in food trends of a return to more ancient food preparation techniques. Recent research has shown that the use of fermented foods in diets did confer gastrointestinal and cognitive benefits. 64,65 However, until more evidence behind the use of probiotics as therapy for anxiety and depressive disorders is available, probiotics in any form cannot be considered a reliable therapy to anxiety and depressive disorders as compared to psychiatric medications. Furthermore, gender differences as well as comorbidities such as obesity, lifestyle, and tobacco and alcohol use may impact the overall benefit of probiotics. Despite the lack of regulations, patients prescribed mood-altering drugs may benefit from concomitant use of probiotics. The dysbiosis created by the prescribed medications, or resulting from the neurological disturbance itself, may be mitigated by the introduction of beneficial gut flora in a probiotic form. Ultimately, the question that needs to be addressed is can probiotics alone fix the problem, or do they need to be used with mood stabilizers? The findings above, coupled with the recent surge of interest of gut health in the media, underscore the importance of future research in understanding the gut flora. Anxiety and depression are rising global issues, effective and accessible treatments would benefit millions of people worldwide.

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          The gut-brain axis: interactions between enteric microbiota, central and enteric nervous systems

          The gut-brain axis (GBA) consists of bidirectional communication between the central and the enteric nervous system, linking emotional and cognitive centers of the brain with peripheral intestinal functions. Recent advances in research have described the importance of gut microbiota in influencing these interactions. This interaction between microbiota and GBA appears to be bidirectional, namely through signaling from gut-microbiota to brain and from brain to gut-microbiota by means of neural, endocrine, immune, and humoral links. In this review we summarize the available evidence supporting the existence of these interactions, as well as the possible pathophysiological mechanisms involved. Most of the data have been acquired using technical strategies consisting in germ-free animal models, probiotics, antibiotics, and infection studies. In clinical practice, evidence of microbiota-GBA interactions comes from the association of dysbiosis with central nervous disorders (i.e. autism, anxiety-depressive behaviors) and functional gastrointestinal disorders. In particular, irritable bowel syndrome can be considered an example of the disruption of these complex relationships, and a better understanding of these alterations might provide new targeted therapies.
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            Defining the core Arabidopsis thaliana root microbiome.

            Land plants associate with a root microbiota distinct from the complex microbial community present in surrounding soil. The microbiota colonizing the rhizosphere (immediately surrounding the root) and the endophytic compartment (within the root) contribute to plant growth, productivity, carbon sequestration and phytoremediation. Colonization of the root occurs despite a sophisticated plant immune system, suggesting finely tuned discrimination of mutualists and commensals from pathogens. Genetic principles governing the derivation of host-specific endophyte communities from soil communities are poorly understood. Here we report the pyrosequencing of the bacterial 16S ribosomal RNA gene of more than 600 Arabidopsis thaliana plants to test the hypotheses that the root rhizosphere and endophytic compartment microbiota of plants grown under controlled conditions in natural soils are sufficiently dependent on the host to remain consistent across different soil types and developmental stages, and sufficiently dependent on host genotype to vary between inbred Arabidopsis accessions. We describe different bacterial communities in two geochemically distinct bulk soils and in rhizosphere and endophytic compartments prepared from roots grown in these soils. The communities in each compartment are strongly influenced by soil type. Endophytic compartments from both soils feature overlapping, low-complexity communities that are markedly enriched in Actinobacteria and specific families from other phyla, notably Proteobacteria. Some bacteria vary quantitatively between plants of different developmental stage and genotype. Our rigorous definition of an endophytic compartment microbiome should facilitate controlled dissection of plant-microbe interactions derived from complex soil communities.
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              The endocannabinoid system links gut microbiota to adipogenesis

              Introduction Obesity and type II diabetes have reached epidemic proportions. Recent data have shown that these metabolic disorders are characterised by low-grade inflammation of unknown molecular origin (Hotamisligil and Erbay, 2008; Shoelson and Goldfine, 2009); therefore, it is of the utmost importance to identify the link between inflammation and adipose tissue metabolism, and plasticity. Emerging data have implicated gut microbiota (Ley et al, 2005; Turnbaugh et al, 2006; Cani et al, 2007a, 2007b, 2008; Cani and Delzenne, 2009) and the endocannabinoid (eCB) system (Lambert and Muccioli, 2007; Di Marzo, 2008) as modulators of obesity and energy homeostasis. During the past several years, our group and others have provided evidence that gut microbiota influence whole-body metabolism by affecting energy balance (Ley et al, 2005; Turnbaugh et al, 2006; Claus et al, 2008), gut permeability (Cani et al, 2008, 2009) and low-grade inflammation (Cani et al, 2007a, 2007b) associated with obesity and related metabolic disorders. Recently, studies performed in gnotobiotic mice have emphasised the contributions of gut microbiota to fat storage (Backhed et al, 2004, 2007; Samuel et al, 2008). Obesity is characterised by the massive expansion of adipose tissues and is associated with inflammation (Weisberg et al, 2003). It is possible that both this expansion and the associated inflammation are controlled by microbiota and lipopolysaccharide (LPS) (Cani et al, 2007a, 2008), a cell wall component of Gram-negative bacteria that is among the most potent inducers of inflammation. On the other hand, obesity is also characterised by greater eCB system tone, that is increased eCB plasma levels, altered expression of the cannabinoid receptor 1 (CB1 mRNA) and increased eCB levels in adipose tissues (Engeli et al, 2005; Bluher et al, 2006; Matias et al, 2006; Cote et al, 2007; D'Eon et al, 2008; Starowicz et al, 2008; Di Marzo et al, 2009; Izzo et al, 2009). Several studies have suggested a close relationship between LPS and the eCB system. LPS controls the synthesis of eCBs both in vivo (Hoareau et al, 2009) and in vitro (Di Marzo et al, 1999; Maccarrone et al, 2001) through mechanisms that depend on LPS receptor signalling (Liu et al, 2003). Although genetic and pharmacological impairments of CB1 receptor have been shown to protect against the development of obesity, steatosis and related inflammation (Osei-Hyiaman et al, 2005, 2008; Gary-Bobo et al, 2007; DeLeve et al, 2008), the molecular link between eCB system activation and disorders associated with obesity remains elusive. There is accumulating evidence that the eCB system, inflammation and obesity are interconnected (Scherer and Buettner, 2009); however, the convergent molecular mechanisms that may affect adiposity remain to be clarified. Here, we tested the hypothesis that gut microbiota and the eCB system control gut permeability and adipogenesis through an LPS-dependent mechanism under physiological and obesity-related conditions. Results Gut microbiota modulate colon CB1 receptor mRNA expression in normal and obese mice To determine the contributions of gut microbiota to the regulation of the intestinal eCB system in both physiological and obese conditions, we investigated selective models (e.g. prebiotic treatment (Cani et al, 2007b, 2009; Martin et al, 2008) and a high-fat diet (HFD) (Cani et al, 2007a, 2008)) and drastic models (e.g. antibiotic treatment (Seki et al, 2007; Cani et al, 2008; Membrez et al, 2008) and germ-free mice (Backhed et al, 2004)) of gut microbiota modulation, in addition to mice bearing specific mutations in Myd88, an important gene involved in toll-like receptor (TLR)-mediated bacteria–host interactions. Tissue-specific changes in colonic CB1 mRNA expression were observed in all five models (Figure 1A–C, E, G), whereas expression in the jejunum was unaffected (Figure 1D and F). In contrast, altered colonic expression of the second cannabinoid receptor CB2 was not observed in any of the models tested (Supplementary Figure S1A–D), suggesting that gut microbiota selectively modulate colonic CB1 mRNA expression. Anandamide (AEA) and 2-arachidonoylglycerol (2-AG) (Devane et al, 1992; Mechoulam et al, 1995) are endogenous CB1 and CB2 ligands, and the main enzymes responsible for their degradation are fatty acid amide hydrolase (FAAH) (Cravatt et al, 1996) and monacylglycerol lipase (MGL) (Dinh et al, 2002), respectively. Consistent with the tissue-specific modulation of CB1 mRNA expression, we found that FAAH and MGL expression levels were affected by gut microbiota in the colon (Supplementary Figure S2A, C, D and E), but not in the jejunum (Supplementary Figure S2B and F). We earlier showed that gut microbiota, at least in part, contribute to the systemic and hepatic inflammation associated with obesity (Cani et al, 2008, 2009) by increasing gut permeability, resulting in elevated LPS levels (defined as metabolic endotoxaemia). Obesity is also characterised by altered tone of the intestinal eCB system (Izzo et al, 2009). Thus, we hypothesised that the eCB system could link the development of gut permeability to the higher plasma LPS levels associated with obesity. To support these observations, we measured the intestinal AEA and 2-AG tissue content in genetically obese mice (B6.V-Lep ob /J; ob/ob) and in ob/ob mice fed prebiotics. Consistent with the decrease in colonic CB1 mRNA expression, we found that AEA content was reduced, whereas FAAH mRNA expression was increased (Figure 2A) in obese mice fed prebiotics. On the other hand, 2-AG content was not affected, despite a decrease in MGL mRNA expression (Figure 2A). Furthermore, these markers were not affected in the jejunum (Supplementary Figure S3A and B), strengthening the link between the eCB system (as indicated by CB1 mRNA, FAAH mRNA and AEA levels) and gut microbiota. Accordingly, we found that the reduced plasma LPS levels in obese mice fed prebiotics (Figure 2B) correlated with both AEA levels and CB1 mRNA expression in the colon (Pearson's correlation between LPS and CB1 mRNA was r=0.46, P=0.04, whereas the correlation between LPS and AEA was r=0.43, P=0.05). CB1 receptor controls gut permeability To clearly show that the eCB system regulates gut barrier function, we designed two in vivo experiments in obese and lean mice. In the first experiment, we blocked the CB1 receptor with a specific, selective antagonist (SR141716A) in obese ob/ob mice with disrupted gut barrier and metabolic endotoxaemia (Brun et al, 2007; Cani et al, 2009) (Figure 2C and F; Ob-CT versus CT, P 0.05, for LPS-HU and LPS-HU-SR2, respectively). Taken together, these in vivo and in vitro experiments support the hypothesis that the eCB system has an important function in the regulation of gut permeability through a CB1 receptor-dependent mechanism. Gut microbiota modulation decreases CB1 expression in adipose tissue and fat mass and controls adipogenesis Given that obesity is characterised by the dysregulation of eCB system tone in adipose tissue (Engeli et al, 2005; Bluher et al, 2006; Matias et al, 2006; Cote et al, 2007; D'Eon et al, 2008; Starowicz et al, 2008; Di Marzo et al, 2009; Izzo et al, 2009), we investigated this phenomenon in ob/ob mice compared with their lean littermates. In adipose tissues of the obese mice, there was a significant increase in the mRNA expression of N-acylphophatidylethanolamine phospholipase D (NAPE-PLD), the primary enzyme involved in AEA synthesis (Muccioli, 2010), and CB1, along with reduced mRNA expression of FAAH (Figure 5A–C). Consistent with these findings, we found a significant increase in AEA content (Figure 5D). Taken together, these data show for the first time that ob/ob mice display altered eCB system tone in adipose tissues. Our laboratory and others have earlier shown that gut microbiota participate in the development of adipose tissue under both physiological and pathological conditions (Backhed et al, 2004, 2007; Cani et al, 2007a, 2008, 2009; Samuel et al, 2008). The molecular events linking the gut microbiota to adipogenesis, however, remain unidentified. Here, we confirm that changing the gut microbiota using prebiotics decreases fat mass development in obese mice (Figure 6A). Similar to the effects on colonic CB1 receptor expression, changes in gut microbiota significantly decreased CB1 mRNA expression in adipose tissues (Figure 6B). Given the recognised functions of AEA in metabolic processes controlled by the eCB system (Osei-Hyiaman et al, 2005; Buettner et al, 2008) and our present findings, we measured AEA levels and FAAH mRNA expression in adipose tissue. Prebiotics strongly decreased AEA levels and tended to increase FAAH mRNA levels (Figure 6C), further supporting the link between changes in gut microbiota and modulation of the eCB system. Given that CB1 receptor activation is known to increase lipogenesis-induced lipid accumulation in both liver (Osei-Hyiaman et al, 2005, 2008) and fat cells (Cota et al, 2003; Bouaboula et al, 2005; Gary-Bobo et al, 2006; Matias et al, 2006; Bellocchio et al, 2008; Pagano et al, 2008), we investigated whether reduced AEA levels and CB1 mRNA expression during adipose tissue development could be linked to the diminution of adipogenesis and/or lipogenesis. To that end, we used qRT–PCR to determine the expression levels of the following adipogenic markers: CCAAT/enhancer-binding protein-α (C/EBP-α), peroxisome proliferator activated receptor-γ (PPAR-γ) and adipocyte fatty acid-binding protein (aP2, also known as FABP4, or AFABP). We also examined the following lipogenic markers: sterol regulatory element-binding protein-1c (SREBP-1c), a crucial transcription factor controlling the transcriptional regulation of both acetyl-CoA carboxylase (ACC) and fatty acid synthase (FAS) (Osei-Hyiaman et al, 2005). Strikingly, we found that the decreased fat mass, reduced CB1 mRNA expression and reduced AEA levels observed after the modulation of gut microbiota in obese mice were associated with increases in markers of adipocyte differentiation (PPAR-γ, aP2, C/EBP-α) and lipogenesis (SREBP-1c, ACC, FAS) (Figure 6D and E). Similar results were obtained (also in obese mice) by blocking CB1 receptor signalling (Figure 6F and G). Under physiological conditions, on the other hand, activation of the eCB system by a cannabinoid receptor agonist (HU-210) increased adipogenesis in lean mice. Indeed, we found that activation of the cannabinoid receptors markedly increased the expression of genes involved in adipocyte differentiation (PPAR-γ, aP2, C/EBP-α) (Figure 7B) and lipogenesis (SREBP-1c, ACC, FAS), without affecting CB1 mRNA levels (Figure 7C). Meanwhile, we observed a trend towards an increase in the adiposity index (Figure 7A). These effects were associated with smaller adipocyte size and an increased number of adipocytes as determined by histological analysis (Figure 7D). Finally, a heat map profile examination and dendrogram analysis performed on the basis of adipocyte differentiation, lipogenesis and adipocyte size clearly showed two separate clusters between CT mice and those treated with the cannabinoid receptor agonist (Figure 7E). Consistent with the results obtained using the cannabinoid receptor agonist, inhibition of AEA degradation by administration of a potent FAAH inhibitor, URB597 (Kathuria et al, 2003), significantly increased AEA levels (CT: 100±7.4%; URB597: 117.5±4.9; P<0.05) and promoted adipogenesis (Supplementary Figure S6). This observation further supports the putative function of AEA and FAAH in regulating adipogenesis. These findings show that cannabinoid receptor activation induces adipogenesis in vivo under physiological conditions, thus confirming earlier data obtained in vitro (Matias et al, 2006; Pagano et al, 2007; Bellocchio et al, 2008). Recent studies have proposed that obesity and its associated inflammation dysregulate adipose tissue metabolism by impairing adipogenesis (Gustafson et al, 2009; Isakson et al, 2009; McLaughlin et al, 2009). This phenomenon is associated with increased eCB system tone. Understanding the molecular mechanisms responsible for altered adipogenesis is essential to avoid the associated metabolic complications. Here, we show that selective changes in gut microbiota or CB1 receptor antagonist reduce the inflammatory tone in obese mice by impacting the strength of the gut barrier and plasma LPS levels. This process may participate in the restoration of adipogenesis after reducing eCB system tone (e.g. with prebiotics or CB1 receptor antagonists) in pathological situations such as obesity. Stimulation of the eCB system leads to adipogenesis through an LPS-regulated mechanism Our in vivo experiments suggest a link between gut microbiota, gut permeability, LPS, the eCB system and control of adipogenesis. Indeed, LPS receptor activation has been shown to decrease adipocyte differentiation and lipogenesis (Chung et al, 2006; Poulain-Godefroy and Froguel, 2007; Poulain-Godefroy et al, 2008) and to activate the production of eCBs (Di Marzo et al, 1999; Maccarrone et al, 2001; Liu et al, 2003; Hoareau et al, 2009). Given that the amount of circulating LPS is under positive control by CB1 through the regulation of eCB system tone in the gut and gut permeability, in this case, it is likely that LPS acts as an additional factor (dependent on the gut microbiota) in the control of adipogenesis and eCB system regulation. To evaluate this putative mechanism, we investigated the effects of cannabinoid receptor modulation and the involvement of LPS in the control of adipocyte differentiation and lipogenesis in cultured adipose tissue explants. Consistent with the in vivo data, activation of CB1 receptors increased adipogenic markers in adipose tissue explants from wild-type mice (Figure 8A and B). In accordance with the hypothesis that LPS acts as a regulator of adipose tissue differentiation and lipogenesis, LPS decreased adipocyte differentiation markers, but had only a minor impact on lipogenesis markers (Figure 8A and B). Furthermore, LPS completely abolished the adipogenic effects (e.g. adipocyte differentiation and lipogenesis) of cannabinoid receptor activation. This latter observation shows that LPS acts as a master signal in eCB regulation of adipogenesis. Moreover, CB1 mRNA levels were significantly increased by LPS (Figure 8C), supporting earlier observations that LPS increases eCB system tone (Di Marzo et al, 1999; Maccarrone et al, 2001; Liu et al, 2003; Hoareau et al, 2009). To ascertain whether LPS could interfere with eCB system-induced activation of adipogenesis (HU) in vivo, we treated lean wild-type mice with LPS (HU-LPS) under the same experimental conditions as in Figure 7D. As before, increased LPS levels caused a decrease in adipogenesis markers (Figure 8D). Taken together, these data suggest that the eCB system regulates adipogenesis and that this regulation is controlled by LPS. Given that increased LPS levels completely abolished the adipogenic effects of cannabinoid receptor activation, we wondered whether LPS could also act as a regulator of the well-characterised PPAR-γ-induced adipogenesis. In fact, LPS blunted PPAR-γ-induced adipogenesis (Figure 8E–G). Discussion Obesity is characterised by a massive expansion of adipose tissues, in addition to metabolic and inflammatory complications (Hotamisligil and Erbay, 2008). Here, we characterise the crosstalk between gut microbiota and the regulation of adipogenesis by the eCB system and provide evidence that gut microbiota physiologically regulate the activity of the peripheral eCB system in intestinal and adipose tissue. The peripheral eCB system, in turn, controls gut barrier function and adipogenesis. Obesity is characterised by dysregulated eCB system tone (Figure 5) (Engeli et al, 2005; Bluher et al, 2006; Matias et al, 2006; Cote et al, 2007; D'Eon et al, 2008; Starowicz et al, 2008; Di Marzo et al, 2009; Izzo et al, 2009), altered gut permeability and increased plasma LPS levels (Cani et al, 2008, 2009). Pharmacological blockade of the CB1 receptor has been shown to reduce obesity associated with inflammation by an unresolved mechanism (Gary-Bobo et al, 2007; Caraceni et al, 2009). In this study, we evaluated the function of intestinal eCB system activation in the development of gut permeability, a major source of metabolic inflammation. Evidence of a link between gut microbiota and the eCB system tone Intestinal eCB system tone variations in response to gut microbiota modulation were observed in germ-free mice and in mouse models of bacterial–host interactions in colonic tissue, but almost no effects were seen in the small intestine. This reflects the higher microbial load found in the colon (Claus et al, 2008). The specific changes in gut microbiota or genetic disruptions of gut bacteria–host interactions selectively decreased CB1 mRNA expression in the colon, without significant modulation of CB2 mRNA expression. Interestingly, it has been shown that the administration of a very specific strain of bacteria, Lactobacillus acidophilus NCFM, increases CB2 receptor expression in the colon in mice, whereas four other bacteria strains (well known as probiotics) belonging to the Lactobacillus and Bifidobacterium genera (L. salivarius Ls-33, L. paracasei Lpc-37, B. lactis Bi-07 and B. lactis Bi-04) and two Escherichia coli strains have no effect on CB2 receptor expression (Rousseaux et al, 2007). It is noteworthy that the lack of effect on CB2 expression observed in our study could merely be explained by the fact that Rousseaux et al (2007) used a specific strain and did not investigate the modulation of gut microbiota. Given that they did not report effects on colonic eCB system tone (CB1 and FAAH mRNA), we designed a similar experiment. Despite at least a 100-fold increase in the probiotic strains in the caecal content of the mice, we did not find any changes in CB1 or FAAH mRNA expression in the colon (Supplementary Figure S5A and B). Still, CB2 mRNA expression tended to increase (Supplementary Figure S5C) (P=0.136). Taken together, our data support the hypothesis that gut microbiota participate in the regulation of the intestinal eCB system and also provide evidence that specific changes in gut microbiota known to reduce obesity and related metabolic disorders (Cani et al, 2007b, 2008, 2009; Membrez et al, 2008) are sufficient to decrease peripheral eCB system tone in two models of obesity (genetic and nutritional). In this study, we confirmed that changes in gut microbiota after prebiotic ingestion reduce gut permeability in obese mice. Blocking the CB1 receptor in obese mice also ameliorated gut barrier function as shown by improved distribution and localisation of tight junction proteins (ZO-1 and occludin). Importantly, this effect was dependent on CB1 receptor blockade as pair feeding had no effect. Confirming these results, CB1 activation increased gut permeability markers in vivo and in vitro. This demonstration that CB1 receptors control gut permeability suggests a new eCB system-dependent mechanism in the pathogenesis of obesity-associated inflammation (systemic and hepatic). Impact of eCB system tone on adipogenesis in obese and lean mice: the function of LPS Numerous mechanisms have been suggested to explain the regulation of physiological and pathological adipose tissue development. Recently, gut microbiota have been suggested to modulate the onset of obesity (Ley et al, 2005; Turnbaugh et al, 2006; Cani et al, 2007a, 2007b, 2008; Cani and Delzenne, 2009) and contribute to fat storage (Backhed et al, 2004, 2007; Martin et al, 2007; Samuel et al, 2008). Although it is clear that genetic or pharmacological blockade of the CB1 cannabinoid receptor protects against the development of obesity (Osei-Hyiaman et al, 2005, 2008; Gary-Bobo et al, 2007; DeLeve et al, 2008), the molecular function of the eCB system in adipose tissue is still under investigation. Here, we identify several in vivo mechanisms by which the eCB system controls adipose tissue development through a putative gut microbiota-to-adipose tissue regulatory loop. An important result of these studies is the demonstration that peripheral (e.g. intestine and adipose tissue) eCB system tone (as indicated by CB1 mRNA, FAAH mRNA and AEA levels) is under the control of gut microbiota. We can speculate that the altered profile of gut microbiota found in obesity (Ley et al, 2006; Cani et al, 2007a, 2007b; Turnbaugh et al, 2009) is, in part, responsible for increased eCB system tone. In conjunction with greater eCB system tone, increased inflammation and plasma LPS levels were observed in obese mice. In contrast, changes in gut microbiota after prebiotic feeding or CB1 receptor blockade decreased inflammation and eCB tone. Hence, the greater eCB system tone found in obesity may participate in the regulation of adipogenesis not only directly by acting on adipose tissue, but also indirectly by increasing plasma LPS levels. The latter would consequently impair adipogenesis and promote inflammatory states. In accordance with this putative regulatory loop, it has been shown that adipogenesis-related genes are downregulated in the adipose tissue of obese and type II diabetic individuals (Yang et al, 2004; Dubois et al, 2006). Furthermore, recent studies have shown that the inflammatory tone associated with obesity leads to the dysregulation of adipogenesis (Gustafson et al, 2009; Isakson et al, 2009; McLaughlin et al, 2009). Here, both specific modulation of gut microbiota and CB1 receptor blockade decreased plasma LPS levels and increased adipocyte differentiation and lipogenesis. One possible explanation for these surprising data could be as follows: plasma LPS levels might be under the control of CB1 in the intestine (gut barrier function); therefore, under particular pathophysiological conditions (e.g. obesity), this could lead to higher circulating LPS levels. Furthermore, CB1 receptor blockade might paradoxically increase adipogenesis because of the ability of CB1 antagonist to reduce gut permeability and counteract the LPS-induced inhibitory effect on adipocyte differentiation and lipogenesis (i.e. a disinhibition mechanism). In summary, given that these treatments reduce gut permeability and, hence, plasma LPS levels and inflammatory tone, we hypothesised that LPS could act as a regulator in this process. This hypothesis was further supported in vitro and in vivo by the observation that cannabinoid-induced adipocyte differentiation and lipogenesis were directly altered (i.e. reduced) in the presence of physiological levels of LPS. Notably, whereas our data provide evidence that the consequences of obesity and gut microbiota dysregulation on gut permeability and metabolic endotoxaemia are clearly mediated by the eCB system, the changes observed in adiposity are likely the result of two system interactions: an LPS-dependent pathway and dysregulation of eCB system tone. On the basis of our results, one might predict that restoring proper physiological levels of eCB and eCB system tone in obesity-related pathological situations would reduce gut permeability, low-grade inflammation and fat mass development. Still, some studies have shown no change, an increase or even a decrease in eCB system tone in different adipose depots (e.g. mesenteric, gonadal and subcutaneous) on the onset of obesity (Starowicz et al, 2008; Izzo et al, 2009; Sarzani et al, 2009; Bennetzen et al, 2010). These differences might be explained by the markers measured to evaluate eCB system tone (e.g. AEA, 2-AG, CB1 mRNA or proteins and FAAH mRNA) or by differences in the level of inflammation (e.g. systemic LPS levels). In the models tested in the present manuscript, we found a consistent increase in AEA and CB1 mRNA expression and a decrease in FAAH mRNA expression. We also performed additional experiments in mice with diet-induced obesity treated for 3 or 8 weeks and found a two- and threefold increase, respectively, in CB1 mRNA expression in subcutaneous adipose depots (PD Cani, 2009, personal communication). Furthermore, in two separate sets of experiments performed in obese and diabetic db/db mice, we observed a 2.5-fold increase in CB1 mRNA expression in subcutaneous adipose tissue and a similar increase in mesenteric fat. On the other hand, FAAH mRNA levels were decreased by about 90% (PD Cani, 2009, personal communication). Therefore, given that in all of these models we observed both increased inflammatory markers and eCB system tone, it is likely that inflammation is responsible for the discrepancies found in the literature and that this is a consequence of enhanced LPS levels as shown in this study. We propose the following model to illustrate how the eCB system links gut microbiota to adipogenesis (Figure 9). Activation of the eCB system in the intestine (e.g. through the gut microbiota) increases gut permeability, which enhances plasma LPS levels and exacerbates gut barrier disruption and peripheral eCB system tone in both the intestine and adipose tissues. Under the pathological conditions of obesity, the increased eCB tone and LPS levels participate in the dysregulation of adipogenesis, perpetuating the initial disequilibrium and leading to a vicious cycle (Figure 9). In conclusion, we have identified a new pathophysiological mechanism linking gut microbiota to the eCB system in intestinal and adipose tissues with a major function in controlling adipogenesis. In addition, we provide evidence that adipogenesis is under the control of an LPS-eCB system regulatory loop. As obesity is commonly characterised by increased eCB system tone, higher plasma LPS levels, altered gut microbiota and impaired adipose tissue metabolism, it is likely that the increased eCB system tone found in obesity is caused by a failure or a vicious cycle within the pathways controlling the eCB system. Modelling symbiotic systems biology such as gut microbiota–host interactions is the next great challenge in biological modelling, especially when aimed at trying to decipher the supersystem activities that will be crucial to understand gene–environment interactions and, thus, determine physiological and pathological consequences. Materials and methods Mice We used male mice between 6 and 9 weeks of age with genetic compositions of C57/BL/6J, B6.V-Lep ob /Jmice (from the Jackson Laboratory). We also used germ-free Swiss Webster and Myd88 −/−/C57BL/6 (bred in Pr. Backhed's laboratory, University of Gothenburg). Their diets consisted of a standard control diet (CT) (A04, Villemoisson sur Orge, France), an HFD or a control diet containing a mixture of prebiotics such as oligofructose (Pre) (Orafti, Tienen, Belgium) (Cani et al, 2007b, 2009). All animal use was approved by and performed in accordance with the local ethics committee. Housing conditions were as specified by the Belgian Law of 14 November 1993, regarding the protection of laboratory animals (agreement no. LA 1230314). Tissue sampling Mice were anesthetised using intraperitoneal (i.p.) ketamine and xylazine at concentrations of 100 and 10 mg/kg, respectively, after a 5-h fasting period. Blood samples and tissues were harvested for further analysis. Mice were killed by cervical dislocation. Epididymal, subcutaneous and visceral adipose depots were precisely dissected and weighed. The sum of the weights of these three adipose depots corresponded to the adiposity index. The intestinal segments (jejunum and colon) and adipose tissues were immersed in liquid nitrogen and stored at −80°C for further analysis. Antibiotic treatment Mice were treated with ampicillin (1 g/l; Sigma) and neomycin (0.5 g/l; Sigma) in their drinking water for 2 weeks (Cani et al, 2008). Surgical procedures for implantation of the osmotic mini-pumps Mice were implanted s.c. with an osmotic mini-pump (Alzet 2004, ALZA) as described earlier (Cani et al, 2006, 2007a). In vivo pharmacological treatments Mice were injected s.c. with HU-210 (100 μg/kg/day) (Tocris) using the osmotic mini-pumps for 4 weeks. The pumps also contained LPS from E. coli 055B:5 at a concentration of 300 μg/kg/day (Sigma) or a control vehicle (0.1% Tween/saline). Mice were injected i.p. with the CB1 receptor antagonist/inverse agonist SR141716A (10 mg/kg/day) or vehicle for 12 days. Mice were injected i.p. with the fatty acid amid hydrolase inhibitor URB597 (3 mg/kg/day) and killed after 24 h. Intestinal permeability in vivo Intestinal permeability was measured in mice that had fasted for 6 h and received dextran-4000-FITC (Sigma) by gavage (500 mg/kg body weight, 125 mg/ml). Measurements were taken as described earlier (Cani et al, 2009). Tight junction proteins (occludin and ZO-1) were assessed by immunohistochemistry as described earlier (Cani et al, 2009). All assessments were performed in duplicate in non-serial distant sections and analysed in a double-blind manner by two different investigators. Plasma LPS concentrations were determined using a kit based on a Limulus amaebocyte extract (LAL kit endpoint-QCL1000, Cambrex BioScience, Walkersville, MD). Determination of the non-inhibitory reaction and optimised sensitivity and specificity were performed as described earlier (Cani et al, 2009). An internal control for LPS recovery was included in each determination and calculation. Measurement of AEA and 2-AG tissue levels Tissues were homogenised in CHCl3 (10 ml), and a deuterated standard (d-AEA and 2-AG; 200 pmol) was added. Methanol (5 ml) and H2O (2.5 ml) were added, and the lipids were then extracted by vigorous mixing. After centrifugation, the organic layer was recovered, dried under a stream of N2 and purified by solid-phase extraction using silica, followed by elution with an EtOAc-Acetone (1:1) solution (Muccioli et al, 2007; Muccioli and Stella, 2008). The resulting lipid fraction was analysed by HPLC-MS using an LTQ Orbitrap mass spectrometer (ThermoFisher Scientific) coupled to an Accela HPLC system (ThermoFisher Scientific). Analyte separation was achieved using a C-18 Supelguard pre-column and a Supelcosil LC-18 column (3 μM, 4 × 150 mm) (Sigma-Aldrich). Mobile phases A and B were composed of MeOH-H2O-acetic acid 75:25:0.1 (v/v/v) and MeOH-acetic acid 100:0.1 (v/v), respectively. The gradient (0.5 ml/min) was designed as follows: transition from 100% A to 100% B linearly over 15 min, followed by 10 min at 100% B and subsequent re-equilibration at 100% A. We performed MS analysis in the positive mode with an APCI ionisation source. The capillary and APCI vaporiser temperatures were set at 250 and 400°C, respectively. AEA and 2-AG were quantified by isotope dilution using their respective deuterated standards with identical retention. The calibration curves were generated as earlier described (Muccioli and Stella, 2008), and the data were normalised by tissue sample weight. Caco-2 cell culture Caco-2 cells were grown in flasks containing DMEM supplemented with foetal bovine serum (10%), L-glutamine (1%) and non-essential amino acids (1%) at 37°C in a 5% CO2 atmosphere. For permeability testing purposes, the cells were seeded on the upper side of Transwell inserts (Costar) (1.6 × 105/1.12 cm2) and grown for 21 days using the same media with the addition of penicillin (100 IU/ml), streptomycin (100 μg/ml) and amphotericin B (2.5 μl/ml) (Invitrogen). The media in the upper and lower compartments were changed every other day. On day 21, basal TEER was measured using an EndohmTM tissue resistance chamber (World Precision Instruments, Sarasota, FL) connected to a Millicell®-RES (Millipore, Billerica, MA) ohmmeter before drugs were added (T=0 h). After a 24-h incubation in the presence of DMSO or LPS (E. coli 055:B5, 200 μg/ml) (Precourt et al, 2009) and drugs (1 μM HU-210, SR141716A, or SR144528), TEER was measured (T=24 h). Cells were recovered using TriPure reagent (Roche) for subsequent mRNA extraction. The TEER data are expressed as the per cent change from each individual baseline value. Probiotic treatment We orally administered probiotics belonging to the Lactobacillus and Bifidobacterium genera (L. acidophilus NCFM® Bifidobacterium lactis BI-07; Probactiol Plus, Metagenics, Ostende, Belgium) at doses of 1.2 × 109 colony-forming units (CFU) of each strain per day for 10 consecutive days (n=10 mice). Saline treatment was used as a control (n=10 mice). Microbial analysis after probiotic treatment The caecal contents of mice collected post mortem were stored at −80°C. Metagenomic DNA was extracted from the caecal content using the QIAamp DNA stool mini kit (Qiagen, Hilden, Germany) according to the manufacturer's instructions. The primers and probes used to detect Bifidobacterium and L. acidophilus were based on 16S rRNA gene sequences: F-Bifidobacterium spp. TCGCGTCYGGTGTGAAAG, R-Bifidobacterium spp. CCACATCCAGCRTCCAC, F-L. acidophilus CCTTTCTAAGGAAGCGAAGGAT and R-L. acidophilus AATTCTCTTCTCGGTCGCTCTA. PCR amplification was carried out as follows: 10 min at 95°C followed by 45 cycles of 3 s at 95°C, 26 s at 58°C or 60°C (L. acidophilus or Bifidobacterium, respectively) and 10 s at 72°C. Detection was achieved with an STEP one PLUS instrument and software (Applied Biosystems, Foster City, CA) using MESA FAST qPCR MasterMix Plus for SYBR Assay (Eurogentec, Verviers, Belgium). Each assay was performed in duplicate in the same run. The cycle threshold of each sample was then compared with a standard curve (performed in triplicate) made by diluting genomic DNA (fivefold serial dilution) (BCCM/LMG, Ghent, Belgium). The data are expressed as Log CFU/g of caecal content. Adipose tissue explant cultures Subcutaneous adipose depots from 25 mice were precisely dissected, and all visible vessels, particles and conjunctive tissue were removed. The fat tissue was then cut with scissors into small pieces (4 mm3), pooled and placed in Krebs buffer (pH 7.4) containing 2% (wt/vol) free-fatty acid BSA, penicillin (100 IU/ml), streptomycin (100 μg/ml) and amphotericin B (2.5 μl/ml) (Invitrogen). A total of 250 mg of adipose tissue was rinsed in phosphate-buffered saline and incubated in 100-mm Petri dishes containing 10 ml MEM with Earle's salts (Invitrogen) supplemented with 0.5% free-fatty acid-BSA, penicillin (100 IU/ml), streptomycin (100 μg/ml) and amphotericin B (2.5 μl/ml) (Invitrogen). All conditions were repeated in four to five different dishes (n=4–5). The dishes were cultured for 24 h at 37°C in a 5% CO2 atmosphere. The basal concentration of glucose in fresh media was 5 mmol/l, whereas the basal levels of cortisol and insulin were extremely low (∼0.5 nmol/l and 3 pmol/l, respectively). Different pharmacological agents were used in various combinations in accordance with the experimental protocols. LPS (E. coli 055:B5, 100 ng/ml) (Sigma), HU-210 (100 nM) (Tocris) and troglitazone (10 μM) (Sigma) were diluted in DMSO, which also served as a control. Cell viability did not change over the course of the experiment (data not shown). At the end of the experiment, the adipose material was rinsed in phosphate-buffered saline, collected, immediately frozen in liquid nitrogen and stored at −80°C until subsequent mRNA analysis. RNA preparation and real-time qPCR analysis Total RNA was prepared from tissues using TriPure reagent (Roche) as described earlier (Cani et al, 2008). cDNA was synthesised from 1 μg of total RNA using a reverse transcription kit (Promega Corp.). qPCR was performed with an STEP one PLUS instrument and software (Applied Biosystems) as described earlier (Cani et al, 2008). Primer sequences for the targeted mouse genes are shown in Supplementary Table 1. Statistical analysis The data are expressed as the mean±s.e.m. Differences between two groups were assessed using an unpaired, two-tailed Student's t-test. Data sets involving more than two groups were assessed by ANOVA followed by a Bonferroni's post hoc test. Correlations were analysed using Pearson's correlation. Data with different superscript letters were significantly different (P<0.05) according to the post hoc ANOVA statistical analysis. Data were analysed using GraphPad Prism version 5.00 for Windows (GraphPad Software, San Diego, CA) and JMP 8.0.1 (SAS Campus Drive, Cary, NC). The results were considered statistically significant for P<0.05. Supplementary Material Supplemental Table S1 Supplemental Table S1 Supplemental Figures Supplemental Figures
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                Journal
                Clin Pract
                CP
                Clinics and Practice
                PAGEPress Scientific Publications, Pavia, Italy
                2039-7275
                2039-7283
                15 September 2017
                15 September 2017
                : 7
                : 4
                : 987
                Affiliations
                [1 ]School of Medicine
                [2 ]Department of Psychiatry, Health Sciences Center, Texas Tech University , TX, USA
                Author notes
                Correspondence: Megan M. Clapp, 2928 Darlington Dr. Highland Village, TX 75077, USA. +1.214.923.5444. megan.clapp@ 123456ttuhsc.edu

                Contributions: MC initialized the concept of this literature review; MC, NA, LH, MB, EW all contributed to research, drafting, and editing of the review. SW offered guidance and editing.

                Article
                10.4081/cp.2017.987
                5641835
                29071061
                ea827b23-3cac-4b04-98cd-e3be51da7a7f
                ©Copyright A. Verentzioti et al., 2017

                This work is licensed under a Creative Commons Attribution NonCommercial 4.0 License (CC BY-NC 4.0).

                History
                : 09 June 2017
                : 15 August 2017
                : 21 August 2017
                Page count
                Figures: 2, Tables: 0, Equations: 0, References: 65, Pages: 6
                Categories
                Brief Report

                microbiome,depression,anxiety,gut-brain-axis,dysbiosis
                microbiome, depression, anxiety, gut-brain-axis, dysbiosis

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