Prospects Overviews Is eating behavior manipulated by the gastrointestinal microbiota? Evolutionary pressures and potential mechanisms Joe Alcock", Carlo C Maley/3/4*and C. Athena Aktip/s2)3) 4)5) Microbes in the gastrointestinal tract are under selective Introduction: Evolutionary conflict pressure to manipulate host eating behavior to increase their between host and microbes leads to fitness,sometimes at the expense of host fitness. Microbes host manipulation may do this through two potential strategies: generating cravings for foods that they specialize on or foods that The struggle to resist cravings for foods that are high in sugar suppress their competitors, or( inducing dysphoria until and fat is part of daily life for many people. Unhealthy eating is we eat foods that enhance their fitness. We review several a major contributor to health problems including obesity [1] as well as sleep apnea, diabetes, heart disease and cancer 2-4 potential mechanisms for microbial control over eating Despite negative effects on health and survival, unhealthy behavior including microbial influence on reward and satiety eating patterns are often difficult to change The resistance to pathways, production of toxins that alter mood, changes to change is frequently framed as a matter of"self-control, "and receptors including taste receptors and hijacking of the it has been suggested that multiple "selves"or cognitive vagus nerve, the neural axis between the gut and the brain. modules exist [51 each vying for control over our eating We also review the evidence for alternative explanations for behavior. Here, we suggest another possibility: that evolution ry conflict between host and microbes in the gut leads cravings and unhealthy eating behavior. Because microbiota microbes to divergent interests over host eating behavior.Gut are easily manipulatable by prebiotics, probiotics, anti- microbes may manipulate host eating behavior in ways that biotics,fecal transplants, and dietary changes, altering our promote their fitness at the expense of host fitness. Others microbiota offers a tractable approach to otherwise intractable problems of obesity and unhealthy eating. behavior [6-8 though not in the context of competing fitness interests and evolutionary conflict Conflict over resource acquisition and resource allocation Keywords can occur as a result of conflict between different genetic cravings; evolutionary conflict; host manipulation; interests within an organism. For example, genetic conflict microbiome; microbiota; obesity between maternal and paternal genes is hypothesized to play a role in the unusual eating behavior that characterizes the childhood genetic diseases Beckwith-Wiedemann syndrome and Prader-Willi syndrome. These syndromes are character Dol10.1002/bies.201400071 ized by altered appetite and differences in infant suckling that can result from overexpression of genes of paternal Emergency Medicine University of New Mexico, or maternal origin, respectively [9, 10]. In parent-of-origin enter for Evolution and Cancer, Helen Diller Family Compr genetic conflict, paternally imprinted genes are thought to drive increased demands for extracting resources from tment of Surgery, University of California San Francisco, San the mother, and maternally imprinted genes tend to resist Francisco, CA, US Wissenschaftskolleg zu Berlin, (Institute for Advanced Study Berlin).Berlin, these effects. Metagenomic conflict between host and microbiome can be considered an extension of this genetic 6)Department of Psychology, Arizona State University, Tempe, AZ, USA conflict framework, but one that includes other genomes (i.e. microbes in the gut) with genes that affect the physiology and behavior of a host organism, potentially altering host eating E-mail: carlo. maley@ucsfmedctr. org, cmaley @ alum. mit. edu behavior in ways that benefit microbe fitness 940www.bioessays-journal.comBioessays36:940-949,@2014The pen access article under the terms distribution and reproduction in any m led the original work is properly
Prospects & Overviews Is eating behavior manipulated by the gastrointestinal microbiota? Evolutionary pressures and potential mechanisms Joe Alcock1), Carlo C. Maley2)3)4) and C. Athena Aktipis2)3)4)5) Microbes in the gastrointestinal tract are under selective pressure to manipulate host eating behavior to increase their fitness, sometimes at the expense of host fitness. Microbes may do this through two potential strategies: (i) generating cravings for foods that they specialize on or foods that suppress their competitors, or (ii) inducing dysphoria until we eat foods that enhance their fitness. We review several potential mechanisms for microbial control over eating behavior including microbial influence on reward and satiety pathways, production of toxins that alter mood, changes to receptors including taste receptors, and hijacking of the vagus nerve, the neural axis between the gut and the brain. We also review the evidence for alternative explanations for cravings and unhealthy eating behavior. Because microbiota are easily manipulatable by prebiotics, probiotics, antibiotics, fecal transplants, and dietary changes, altering our microbiota offers a tractable approach to otherwise intractable problems of obesity and unhealthy eating. Keywords: .cravings; evolutionary conflict; host manipulation; microbiome; microbiota; obesity Introduction: Evolutionary conflict between host and microbes leads to host manipulation The struggle to resist cravings for foods that are high in sugar and fat is part of daily life for many people. Unhealthy eating is a major contributor to health problems including obesity [1] as well as sleep apnea, diabetes, heart disease, and cancer [2–4]. Despite negative effects on health and survival, unhealthy eating patterns are often difficult to change. The resistance to change is frequently framed as a matter of “self-control,” and it has been suggested that multiple “selves” or cognitive modules exist [5] each vying for control over our eating behavior. Here, we suggest another possibility: that evolutionary conflict between host and microbes in the gut leads microbes to divergent interests over host eating behavior. Gut microbes may manipulate host eating behavior in ways that promote their fitness at the expense of host fitness. Others have hypothesized that microbes may be affecting our eating behavior [6–8], though not in the context of competing fitness interests and evolutionary conflict. Conflict over resource acquisition and resource allocation can occur as a result of conflict between different genetic interests within an organism. For example, genetic conflict between maternal and paternal genes is hypothesized to play a role in the unusual eating behavior that characterizes the childhood genetic diseases Beckwith–Wiedemann syndrome and Prader–Willi syndrome. These syndromes are characterized by altered appetite and differences in infant suckling that can result from overexpression of genes of paternal or maternal origin, respectively [9, 10]. In parent-of-origin genetic conflict, paternally imprinted genes are thought to drive increased demands for extracting resources from the mother, and maternally imprinted genes tend to resist these effects. Metagenomic conflict between host and microbiome can be considered an extension of this genetic conflict framework, but one that includes other genomes (i.e., microbes in the gut) with genes that affect the physiology and behavior of a host organism, potentially altering host eating behavior in ways that benefit microbe fitness. DOI 10.1002/bies.201400071 1) Department of Emergency Medicine, University of New Mexico, Albuquerque, NM, USA 2) Center for Evolution and Cancer, Helen Diller Family Comprehensive Cancer Center, San Francisco, CA, USA 3) Department of Surgery, University of California San Francisco, San Francisco, CA, USA 4) Wissenschaftskolleg zu Berlin, (Institute for Advanced Study Berlin), Berlin, Germany 5) Department of Psychology, Arizona State University, Tempe, AZ, USA *Corresponding author: Carlo Maley E-mail: carlo.maley@ucsfmedctr.org, cmaley@alum.mit.edu 940 www.bioessays-journal.com Bioessays 36: 940–949, 2014 The Authors. Bioessays published by WILEY Periodicals, Inc. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Review essays
■■■口 Prospects& Overviews J. Alcock et al Microbial genes outnumber human genes by 100 to 1 in the casei in participants whose mood was initially in the lowest intestinal microbiome, leading some to propose that it is a tertile [ 21] microbial organ"that performs important functions for the There are many other examples of microbes affecting their host, such as nutrient harvesting and immune develop- hosts'mood and behavior, mostly from animal studies(Fig. 1). ment [11]. However, as with any complex and intimate Butyrate a short chain fatty acid largely produced by the interaction, there is a mixture of common and divergent microbiota, has been shown to have profound central nervous interests with opportunities for mutual benefit [11] and system effects on mood and behavior in mice[22]. Microbiota manipulation [12]. Fitness interests of gut microbes are also transfer to germ free mice leads to timid behavior when fed often not aligned, because members of the microbiota feces from mice with anxiety-like behavior. When germ-free compete with one another over habitat and nutrients. This mice from an anxious strain were fed with a fecal pellet from a means that highly diverse populations of gut microbes may be control mouse, the inoculated mice exhibited behavior that ≤o≤o0 nore likely to expend energy and resources in competition, was more exploratory, and more like their fecal donors [23 .In compared to a less diverse microbial population. A less diverse addition, a probiotic formulation with Lactobacillus helveticus microbial population is likely to have species within it that Ro052 and Bifidobacterium longum Ro175 alleviated psycho- have large population sizes and more resources available for logical distress [24]. This effect can be altered by diet and host manipulation. Moreover, the larger a particular microbial inflammation (25 If one feeds Lactobacillus rhamnosus B-1) population is, the more power it would have to manipulate to mice, not only does it reduce their stress- induced he host through higher levels of factor production or other corticosterone hormone levels, but it also makes them more strategies (see below) and large scale coordination of these dogged: L rhamnosus B-1)fed mice swim longer than the activities (e.g, through quorum sensing). Therefore, we control fed mice when put in a glass cylinder filled with 15cm hypothesize that lower diversity in gut microbiome should of water and no means of escape[26]. This effect disappeared be associated with more unhealthy eating behavior and when the experimenters severed the vagus nerve, suggesting a greater obesity (i. e, decreased host fitnes role for the vagus nerve in microbial manipulation of host behavior. In contrast, severing the vagus nerve had no effect on swimming behavior of control mice that were not fed Evidence indicates many potential L. rhamnosus (B-1)[26]. In a widely cited example of mechanisms of manipulation microbes affecting behavior, Toxoplasma gondii suppresses rats, normal fear of cat smells often to the detriment of the There is a selective influence of diet on rats, but to the benefit of the microbes that are ingested into microbiota their new feline host. T. gondii infected rats are reported to become sexually aroused by cat urine [271, a propensity that Individual members of the microbiota, and consortia of those promotes transmission of T gondii at the expense of the fitness microbes, have been shown to be highly dependent on the of the rat. nutrient composition of the diet. Prevotella grows best on carbohydrates; dietary fiber provides a competitive advantage to Bifidobacteria [131, and Bacteroidetes has a substrate Microbes can induce dysphoria that changes preference for certain fats [14]. Some specialist microbes, e.g. feeding behavior ucin degrading bacteria such as Akkermansia mucinophila thrive on secreted carbohydrates provided by host cells. Other Although certain Lactobacillus appear to reduce anxiety butyrate producing microbes, e.g. Roseburia spp, fare better colonization of the gut with the pathogen Campylobacter when they are delivered polysaccharide growth substrates in jejuni increased anxiety-like behavior in mice[28, raising the he diet. Specialist microbes that digest seaweed have been possibility that microbe- induced dysphoria might also affect isolated from humans in Japan [15. African children raised human behavior. Recent studies have linked the inconsolable on sorghum have unique microbes that digest cellulose [16]. crying of infant colic with changes in gut microbiota including Many other examples exist [17 Even microbes with a reduced overall diversity, increased density of Proteobacteria generalist strategy tend to do better on some combinations and decreased numbers of Bacteroidetes compared to of nutrients than others, and competition will determine controls [29]. Colic has been reported to result in increased which microbes survive[18, 19 energy delivery to infants, sometimes resulting in accelerated weight gain [ 30]. If infant crying has a signaling function that increases parental attention and feeding [31, 32 colic may Microbes can manipulate host behavior increase the resource delivery to the gut and hence microbial access to nutrients There is circumstantial evidence for a connection between One potential mechanism by which dysphoria can cravings and the composition of gut microbiota. Individuals influence eating involves bacterial virulence gene expression who are " chocolate desiring" have different microbial and host pain perception. This mode of manipulation is metabolites in their urine than " chocolate indifferent" plausible because production of virulence toxins often is individuals, despite eating identical diets [20]. There is also triggered by a low concentration of growth-limiting nutrients. evidence for effects of microbes on mood. A double-blind, Detection of simple sugars and other nutrients regulates randomized placebo controlled trial found that mood was virulence and growth for a variety of human-associated significantly improved by drinking probiotic Lactobacillus microbes [33-37 These commensals directly injure the Bioessays 36: 940-949, 2014 The Authors Bioessays published by WILEY Periodicals, Inc. 941
Microbial genes outnumber human genes by 100 to 1 in the intestinal microbiome, leading some to propose that it is a “microbial organ” that performs important functions for the host, such as nutrient harvesting and immune development [11]. However, as with any complex and intimate interaction, there is a mixture of common and divergent interests with opportunities for mutual benefit [11] and manipulation [12]. Fitness interests of gut microbes are also often not aligned, because members of the microbiota compete with one another over habitat and nutrients. This means that highly diverse populations of gut microbes may be more likely to expend energy and resources in competition, compared to a less diverse microbial population. A less diverse microbial population is likely to have species within it that have large population sizes and more resources available for host manipulation. Moreover, the larger a particular microbial population is, the more power it would have to manipulate the host through higher levels of factor production or other strategies (see below) and large scale coordination of these activities (e.g., through quorum sensing). Therefore, we hypothesize that lower diversity in gut microbiome should be associated with more unhealthy eating behavior and greater obesity (i.e., decreased host fitness). Evidence indicates many potential mechanisms of manipulation There is a selective influence of diet on microbiota Individual members of the microbiota, and consortia of those microbes, have been shown to be highly dependent on the nutrient composition of the diet. Prevotella grows best on carbohydrates; dietary fiber provides a competitive advantage to Bifidobacteria [13], and Bacteroidetes has a substrate preference for certain fats [14]. Some specialist microbes, e.g. mucin degrading bacteria such as Akkermansia mucinophila, thrive on secreted carbohydrates provided by host cells. Other butyrate producing microbes, e.g. Roseburia spp., fare better when they are delivered polysaccharide growth substrates in the diet. Specialist microbes that digest seaweed have been isolated from humans in Japan [15]. African children raised on sorghum have unique microbes that digest cellulose [16]. Many other examples exist [17]. Even microbes with a generalist strategy tend to do better on some combinations of nutrients than others, and competition will determine which microbes survive [18, 19]. Microbes can manipulate host behavior There is circumstantial evidence for a connection between cravings and the composition of gut microbiota. Individuals who are “chocolate desiring” have different microbial metabolites in their urine than “chocolate indifferent” individuals, despite eating identical diets [20]. There is also evidence for effects of microbes on mood. A double-blind, randomized, placebo controlled trial found that mood was significantly improved by drinking probiotic Lactobacillus casei in participants whose mood was initially in the lowest tertile [21]. There are many other examples of microbes affecting their hosts’ mood and behavior, mostly from animal studies (Fig. 1). Butyrate, a short chain fatty acid largely produced by the microbiota, has been shown to have profound central nervous system effects on mood and behavior in mice [22]. Microbiota transfer to germ free mice leads to timid behavior when fed feces from mice with anxiety-like behavior. When germ-free mice from an anxious strain were fed with a fecal pellet from a control mouse, the inoculated mice exhibited behavior that was more exploratory, and more like their fecal donors [23]. In addition, a probiotic formulation with Lactobacillus helveticus R0052 and Bifidobacterium longum R0175 alleviated psychological distress [24]. This effect can be altered by diet and inflammation [25]. If one feeds Lactobacillus rhamnosus (JB-1) to mice, not only does it reduce their stress-induced corticosterone hormone levels, but it also makes them more dogged: L. rhamnosus (JB-1) fed mice swim longer than the control fed mice when put in a glass cylinder filled with 15 cm of water and no means of escape [26]. This effect disappeared when the experimenters severed the vagus nerve, suggesting a role for the vagus nerve in microbial manipulation of host behavior. In contrast, severing the vagus nerve had no effect on swimming behavior of control mice that were not fed L. rhamnosus (JB-1) [26]. In a widely cited example of microbes affecting behavior, Toxoplasma gondii suppresses rats’ normal fear of cat smells, often to the detriment of the rats, but to the benefit of the microbes that are ingested into their new feline host. T. gondii infected rats are reported to become sexually aroused by cat urine [27], a propensity that promotes transmission of T. gondii at the expense of the fitness of the rat. Microbes can induce dysphoria that changes feeding behavior Although certain Lactobacillus appear to reduce anxiety, colonization of the gut with the pathogen Campylobacter jejuni increased anxiety-like behavior in mice [28], raising the possibility that microbe-induced dysphoria might also affect human behavior. Recent studies have linked the inconsolable crying of infant colic with changes in gut microbiota including reduced overall diversity, increased density of Proteobacteria and decreased numbers of Bacteroidetes compared to controls [29]. Colic has been reported to result in increased energy delivery to infants, sometimes resulting in accelerated weight gain [30]. If infant crying has a signaling function that increases parental attention and feeding [31, 32], colic may increase the resource delivery to the gut and hence microbial access to nutrients. One potential mechanism by which dysphoria can influence eating involves bacterial virulence gene expression and host pain perception. This mode of manipulation is plausible because production of virulence toxins often is triggered by a low concentration of growth-limiting nutrients. Detection of simple sugars and other nutrients regulates virulence and growth for a variety of human-associated microbes [33–37]. These commensals directly injure the ....Prospects & Overviews J. Alcock et al. Bioessays 36: 940–949, 2014 The Authors. Bioessays published by WILEY Periodicals, Inc. 941 Review essays
J. Alcock et al Prospects& Overviews■■■■ Figure 1. Like microscopic puppetmasters RECEPTOR ALTERATION REWARD nisms including microbial manipulation of eward pathways, production of toxins alter mood(shown in pink, diffusing from a microbe), changes to receptors including VAGAL taste receptors, and hijacking of neL otrans mission via the vagus nerve(gray), which is CONTROL the main neural axis between the gut and the brain Negative mood n gut[43] Enteric receptors respond to specific bacteria [48] intestinal epithelium when certain nutrients are absent, increased intestinal expression of cannabinoid and opioid raising the possibility that microbes manipulate behaviors receptors in mouse and rat intestines, and had similar through pain signaling. In accord with this hypothesis, effects in human epithelial cell culture [43. These results bacterial virulence proteins have been shown to activate pain suggest that microbes could influence food preferences by receptors [38]. Moreover, pain perception (nociception) altering receptor expression or transduction. Changes in requires the presence of an intestinal microbiota in mice [39 taste receptor expression and activity have been reported and fasting has been shown to increase nociception in rodents after gastric bypass surgery, a procedure that also changes by a vagal nerve mechanism [40] gut microbiota and alters satiety and food preferences (reviewed in [44D Microbes modulate host receptor expression Microbes can influence hosts through neural One route to manipulation of host eating behavior is to alter mechanisms the preferences of hosts through changing receptor expres- sion. One study found that germ-free mice had altered taste Gut microbes may manipulate eating behavior by hijacking eceptors for fat on their tongues and in their intestines their host's nervous system. Evidence shows that microbes compared to mice with a normal microbiome [41]. In another can have dramatic effects on behavior through the micro- experiment, germ free mice preferred more sweets and biome-gut-brain axis [6, 45, 46]. The vagus nerve is a central had greater numbers of sweet taste receptors in the gastro- actor in this communication axis, connecting the 100 million intestinal tract compared to normal mice [42. In addition, neurons of the enteric nervous system in the gut [47] to the L. acidophilus NCFM, administered orally as a probiotic, base of the brain at the medulla. Enteric nerves have receptors 942 Bioessays 36: 940-949, C 2014 The Authors Bioessays published by WLEY Perodicals, Inc
intestinal epithelium when certain nutrients are absent, raising the possibility that microbes manipulate behaviors through pain signaling. In accord with this hypothesis, bacterial virulence proteins have been shown to activate pain receptors [38]. Moreover, pain perception (nociception) requires the presence of an intestinal microbiota in mice [39] and fasting has been shown to increase nociception in rodents by a vagal nerve mechanism [40]. Microbes modulate host receptor expression One route to manipulation of host eating behavior is to alter the preferences of hosts through changing receptor expression. One study found that germ-free mice had altered taste receptors for fat on their tongues and in their intestines compared to mice with a normal microbiome [41]. In another experiment, germ free mice preferred more sweets and had greater numbers of sweet taste receptors in the gastrointestinal tract compared to normal mice [42]. In addition, L. acidophilus NCFM, administered orally as a probiotic, increased intestinal expression of cannabinoid and opioid receptors in mouse and rat intestines, and had similar effects in human epithelial cell culture [43]. These results suggest that microbes could influence food preferences by altering receptor expression or transduction. Changes in taste receptor expression and activity have been reported after gastric bypass surgery, a procedure that also changes gut microbiota and alters satiety and food preferences (reviewed in [44]). Microbes can influence hosts through neural mechanisms Gut microbes may manipulate eating behavior by hijacking their host’s nervous system. Evidence shows that microbes can have dramatic effects on behavior through the microbiome-gut-brain axis [6, 45, 46]. The vagus nerve is a central actor in this communication axis, connecting the 100 million neurons of the enteric nervous system in the gut [47] to the base of the brain at the medulla. Enteric nerves have receptors TOXINS REWARD VAGAL CONTROL RECEPTOR ALTERATION Negative mood induced by toxins [38,39] may increase eating [109] Microbes release toxins in absence of nutrients [33-37] Taste receptors altered by microbes, affect eating behavior [41-44] Microbes alter cannabinoid and opioid receptors in gut [43] Vagus nerve interruption leads to weight loss [49,50] Enteric receptors respond to specific bacteria [48] High levels of dopamine and serotonin in gut [58,59] Microbes have genes for human neurotransmitters [8,55-57,60] Figure 1. Like microscopic puppetmasters, microbes may control the eating behavior of hosts through a number of potential mechanisms including microbial manipulation of reward pathways, production of toxins that alter mood (shown in pink, diffusing from a microbe), changes to receptors including taste receptors, and hijacking of neurotransmission via the vagus nerve (gray), which is the main neural axis between the gut and the brain. J. Alcock et al. Prospects & Overviews .... 942 Bioessays 36: 940–949, 2014 The Authors. Bioessays published by WILEY Periodicals, Inc. Review essays
Prospects Overviews J. Alcock et al. 48] and to the hypothalamus [67]. Germ-free mice were also shown to have lower levels of leptin, cholecystokinin, and other satiety 0 sometime Microbes can analogs of behavior nges N-glycated in the gut. B. to increase ly for and host mic of obesity. In wed that mice plasma producing produce GABA activ anti-anxie A for manipu treatment mixture of Lac hormones AgRP (agouti re n the microbiota Bioessays 36: 940-949, 2014 The Autl 943
that react to the presence of particular bacteria [48] and to bacterial metabolites such as short-chain fatty acids. Evidence suggests that the vagus nerve regulates eating behavior and body weight. For example, blockade or transection of the vagus nerve has been reported to cause drastic weight loss [49, 50]. On the other hand, vagus nerve activity appears to drive excessive eating behavior in satiated rats when they are stimulated by norepinephrine [51]. These results suggest that gut microbes that produce adrenergic neurochemicals (discussed below) may contribute to overeating via mechanisms involving vagal nerve activity. Together these results suggest that microbes have opportunities to manipulate vagus nerve traffic in order to control host eating. Intriguingly, many practices that are known to enhance parasympathetic outflow from the vagus nerve, e.g. exercise, yoga, and meditation, are also thought to strengthen willpower [52] and improve accuracy of food intake relative to energy expenditure [53]. However, increased vagus activity is not always associated with health. One study linked parasympathetic vagus activity with weight loss in patients with anorexia nervosa [54], suggesting that vagus nerve signaling is important in regulating body weight, and sometimes can lead to pathological anorexia. Microbes can influence hosts through hormones Microbes produce a variety of neurochemicals that are exact analogs of mammalian hormones involved in mood and behavior [8, 55–57]. More than 50% of the dopamine and the vast majority of the body’s serotonin have an intestinal source [58, 59]. Many transient and persistent inhabitants of the gut, including Escherichia coli, [8, 55, 56] Bacillus cereus, B. mycoides, B. subtilis, Proteus vulgaris, Serratia marcescens, and Staphylococcus aureus [60] have been shown to manufacture dopamine. Concentrations of dopamine in culture of these bacteria were reported to be 10–100 times higher than the typical concentration in human blood [60]. B. subtilis appears to secrete both dopamine and norepinephrine into their environment, where it interacts with mammalian cells. Transplant of the microbiome from a male to an immature female mouse significantly and stably increases testosterone levels in the recipient [61]. In turn, host enzymes are known to degrade neurotransmitters of bacterial origin. For instance, mammals use monoamine oxidase to silence exogenous signaling molecules, among other functions [62, 63]. This may be evidence for selection on hosts to counteract microbial interference with host signaling. Certain probiotic strains alter the plasma levels of other neurochemicals. B. infantis 35624 raises tryptophan levels in plasma, a precursor to serotonin [64]. The lactic acid producing bacteria found in breast milk and yogurt also produce the neurochemicals histamine [65] and GABA [66]. GABA activates the same neuroreceptors that are targeted by anti-anxiety drugs such as valium and other benzodiazepines. Appetite-regulating hormones are another potential avenue for manipulation of mammalian eating behavior. In mice, treatment with VSL#3, a dietary supplement consisting of a mixture of Lactobacillus strains, reduced hunger-inducing hormones AgRP (agouti related protein) and neuropeptide Y in the hypothalamus [67]. Germ-free mice were also shown to have lower levels of leptin, cholecystokinin, and other satiety peptides [41], hormones that control hunger and food intake partly by affecting vagus nerve signaling. Numerous commensal and pathogenic bacteria manufacture peptides that are strikingly similar to leptin, ghrelin, peptide YY, neuropeptide Y, mammalian hormones that regulate satiety and hunger [68]. Moreover, humans and other mammals produce antibodies directed against these microbial peptides, a phenomenon that could have evolved as a mammalian counter-adaptation to microbial manipulation. Anti-hormone antibody production may be important in maintaining the fidelity of host signaling systems. However, these antibodies also act as auto-antibodies against mammalian hormones [68]. This autoimmune response implies that microbes have the capacity to manipulate human eating behavior (i) directly with peptide mimics of satiety regulating hormones, or (ii) indirectly by stimulating production of auto-antibodies that interfere with appetite regulation. The antibody response to microbial analogs of human hormones supports the hypothesis that conflict between host and microbiota influences the regulation of eating behavior. Mucin foraging bacteria control their nutrient supply Several commensal bacteria are known to induce their hosts to provide their preferred nutrients through direct manipulation of intestinal cells. For example, Bacteroides thetaiotaomicron is found on host mucus, where it scavenges N-glycated oligosaccharides secreted by goblet cells in the gut. B. thetaiotaomicron induces its mammalian host to increase goblet cell secretion of glycated carbohydrates [69, 70]. Investigators have shown that another mucin-feeding species, A. muciniphila, also increases the number of mucus producing goblet cells when inoculated in to mice [71]. On the other hand Faecalibacterium prausnitzii, a non-mucus-degrading bacterium that is co-associated with B. thetaiotaomicron, inhibits mucus production by goblet cells [70]. These species provide a proof of principle that gut bacteria can control their nutrient delivery, involving a mechanism that is energetically costly for the host [72]. Intestinal microbiota can affect obesity Evolutionary conflict between the gut microbiome and host may be an important contributor to the epidemic of obesity. In a landmark paper, Backhed and colleagues showed that mice genetically predisposed to obesity remained lean when they were raised without microbiota [73]. These germfree mice were transformed into obese mice when fed a fecal pellet from a conventionally raised obese mouse [74]. Inoculation of germfree mice with microbiota from an obese human produced similar results [75]. Mice lacking the toll-like receptor TLR5 became obese and developed altered gut microbiota, hyperphagia, insulin resistance, and pro-inflammatory gene expression [76]. Fecal pellets from these TLR5 knockout mice, when fed to wild type mice, induced the same phenotype. The gut microbes of obese humans are less diverse than the microbiota ....Prospects & Overviews J. Alcock et al. Bioessays 36: 940–949, 2014 The Authors. Bioessays published by WILEY Periodicals, Inc. 943 Review essays
J. Alcock et al Prospects& Overviews■■■■ of their lean twins [77], consistent with the hypothesis that Cravings should be associated with lower lower diversity may affect eating behavior and satiety. parasympathetic (vagal)tone, and blocking the vagus nerve should reduce food cravings Probiotics are associated with weight loss If microbial control is mediated through the vagus nerve, then microbial signals should interfere to some extent with the The addition of probiotics (i.e. purportedly beneficial ingest- physiological regulation coordinated by the vagus nerve. ible microbes)to the diet tends to decrease food intake Vagal tone can be easily measured through respiratory sinus 0> consistent with the hypothesis that greater gut diversity may arrhythmia [87 the extent to which the heart rate changes in limit microbial control over eating behavior. Some Lactoba. response to inspiration and exhalation. We predict that people cillus probiotics have been reported to reduce fat mass and experiencing cravings should have lower vagal tone. Further- improve insulin sensitivity and glucose tolerance, although more, it is possible to block or sever the vagus, which we these effects are not universally reported for all Lactobacillus predict would subdue microbial signaling via the vagus nerve, species [78, 79 a recent study demonstrated that the and thereby alter food preferences. This would be consistent probiotic VSL#3 caused mice to decrease food intake [67]. with studies showing that blocking the vagus nerve can lead Similarly, the probiotic Bifidobacterium breve inhibited weight to weight loss 149, 501 gain in mice given a high fat diet in a dose-dependent manner[80]. Several studies suggest a role for probiotics in weight loss in humans. In one trial, a probiotic yogurt Microbial diversity should affect food choices produced weight loss that was not due to change in energy and satiet intake or exercise [81. Similarly, yogurt was the food most associated with reduced weight gain in a study that monitored Certain features of microbial ecology, such as population size he diet and health of 120, 000 nurses for over 12-20 years [82]. would be expected to influence a microbe s capacity to Further, a randomized, placebo-controlled trial found that manipulate the host. Microbial communities with low alpha probiotic treatment in pregnancy, using L rhamnosus GG and (intrasample) diversity might be more prone to overgrowth by Bifidobacterium lactis along with dietary counseling, reduced one or more species, giving those organisms increased ability abdominal fat at 6 months post-partum [83]. Together these to manufacture behavior-altering neurochemicals and hor results demonstrate that probiotics can lead to weight loss and mones. by comparison, in microbial communities with high regulate energy balance alpha diversity any single microbial species will tend to occur at lower abundance. Highly diverse gut microbiotas tend to be more resistant to invasion by pathogenic species than Predictions and experiments less diverse microbiotas [88]. In addition, a phylogenetically diverse community will likely contain competing groups Changing the microbiota composition will whose influences may counteract each other. Furthermore, change eating behavior in a diverse microbial environment, microbes will likely expend resources on competing and cooperating(e.g. via Prebiotics (i.e. non-digestible compounds that stimulate cross-feeding), rather than on manipulating their host. growth of beneficial microbes), probiotics, antibiotics, fecal Supporting the hypothesis that a more diverse microbiota transplant, and diet changes are potential strategies to alter causes fewer cravings, gastric bypass surgery has a twofold he microbiota. In addition to the proposal that microbiota effect: increasing alpha diversity in the gut microbiota as well transplantation should result in adoptive transfer of food as reducing preference for high fat, high carbohydrate preferences [84], we further predict that inoculation of an foods [89-91]. Food preferences of germfree mice inoculated experimental animal with a microbe that has a specialized with low versus high diversity microbial communities could nutrient requirement, such as seaweed [15, 85, would lead to provide a test of this prediction. Similarly, probiotics that preference for that novel food. increase microbiota diversity in humans are predicted to reduce cravings more than control treatments that do not increase diversity. A consistent diet will select for microbial specialists and lead to preference for those foods Excess energy delivery to the gut may reduce microbial diversity Raising an experimental animal on a simple diet with few types of foods, should select for microbes that specialize on Besides affecting cravings for specific nutrients, conflict those foods. Our hypothesis as to the microbial origin of food between host and microbiota is expected to impact satiety and preferences predicts that these microbes will influence their overall calorie consumption because optimal energy intake is host to choose the foods upon which they specialize. An likely to differ between the host and members of the gut alternative hypothesis, that food cravings result from nutrient microbiota. Excess energy delivered to the gut, beyond what is shortages [86], predicts the opposite: preference for novel optimal for the host, might provide energy substrates fo foods rich in micronutrients that had been lacking in the microbial growth, permitting certain species to bloom previous simple diet. potentially overwhelming inhibition by competitor organisms 944 Bioessays 36: 940-949, C 2014 The Authors Bioessays published by WLEY Perodicals, Inc
of their lean twins [77], consistent with the hypothesis that lower diversity may affect eating behavior and satiety. Probiotics are associated with weight loss The addition of probiotics (i.e. purportedly beneficial ingestible microbes) to the diet tends to decrease food intake, consistent with the hypothesis that greater gut diversity may limit microbial control over eating behavior. Some Lactobacillus probiotics have been reported to reduce fat mass and improve insulin sensitivity and glucose tolerance, although these effects are not universally reported for all Lactobacillus species [78, 79]. A recent study demonstrated that the probiotic VSL#3 caused mice to decrease food intake [67]. Similarly, the probiotic Bifidobacterium breve inhibited weight gain in mice given a high fat diet in a dose-dependent manner [80]. Several studies suggest a role for probiotics in weight loss in humans. In one trial, a probiotic yogurt produced weight loss that was not due to change in energy intake or exercise [81]. Similarly, yogurt was the food most associated with reduced weight gain in a study that monitored the diet and health of 120,000 nurses for over 12–20 years [82]. Further, a randomized, placebo-controlled trial found that probiotic treatment in pregnancy, using L. rhamnosus GG and Bifidobacterium lactis along with dietary counseling, reduced abdominal fat at 6 months post-partum [83]. Together these results demonstrate that probiotics can lead to weight loss and regulate energy balance. Predictions and experiments Changing the microbiota composition will change eating behavior Prebiotics (i.e. non-digestible compounds that stimulate growth of beneficial microbes), probiotics, antibiotics, fecal transplant, and diet changes are potential strategies to alter the microbiota. In addition to the proposal that microbiota transplantation should result in adoptive transfer of food preferences [84], we further predict that inoculation of an experimental animal with a microbe that has a specialized nutrient requirement, such as seaweed [15, 85], would lead to preference for that novel food. A consistent diet will select for microbial specialists and lead to preference for those foods Raising an experimental animal on a simple diet with few types of foods, should select for microbes that specialize on those foods. Our hypothesis as to the microbial origin of food preferences predicts that these microbes will influence their host to choose the foods upon which they specialize. An alternative hypothesis, that food cravings result from nutrient shortages [86], predicts the opposite: preference for novel foods rich in micronutrients that had been lacking in the previous simple diet. Cravings should be associated with lower parasympathetic (vagal) tone, and blocking the vagus nerve should reduce food cravings If microbial control is mediated through the vagus nerve, then microbial signals should interfere to some extent with the physiological regulation coordinated by the vagus nerve. Vagal tone can be easily measured through respiratory sinus arrhythmia [87], the extent to which the heart rate changes in response to inspiration and exhalation. We predict that people experiencing cravings should have lower vagal tone. Furthermore, it is possible to block or sever the vagus, which we predict would subdue microbial signaling via the vagus nerve, and thereby alter food preferences. This would be consistent with studies showing that blocking the vagus nerve can lead to weight loss [49, 50]. Microbial diversity should affect food choices and satiety Certain features of microbial ecology, such as population size, would be expected to influence a microbe’s capacity to manipulate the host. Microbial communities with low alpha (intrasample) diversity might be more prone to overgrowth by one or more species, giving those organisms increased ability to manufacture behavior-altering neurochemicals and hormones. By comparison, in microbial communities with high alpha diversity any single microbial species will tend to occur at lower abundance. Highly diverse gut microbiotas tend to be more resistant to invasion by pathogenic species than less diverse microbiotas [88]. In addition, a phylogenetically diverse community will likely contain competing groups whose influences may counteract each other. Furthermore, in a diverse microbial environment, microbes will likely expend resources on competing and cooperating (e.g. via cross-feeding), rather than on manipulating their host. Supporting the hypothesis that a more diverse microbiota causes fewer cravings, gastric bypass surgery has a twofold effect: increasing alpha diversity in the gut microbiota as well as reducing preference for high fat, high carbohydrate foods [89–91]. Food preferences of germfree mice inoculated with low versus high diversity microbial communities could provide a test of this prediction. Similarly, probiotics that increase microbiota diversity in humans are predicted to reduce cravings more than control treatments that do not increase diversity. Excess energy delivery to the gut may reduce microbial diversity Besides affecting cravings for specific nutrients, conflict between host and microbiota is expected to impact satiety and overall calorie consumption because optimal energy intake is likely to differ between the host and members of the gut microbiota. Excess energy delivered to the gut, beyond what is optimal for the host, might provide energy substrates for microbial growth, permitting certain species to bloom, potentially overwhelming inhibition by competitor organisms J. Alcock et al. Prospects & Overviews .... 944 Bioessays 36: 940–949, 2014 The Authors. Bioessays published by WILEY Periodicals, Inc. Review essays
■■■口 Prospects& Overviews J. Alcock et al and the immune system Energy excess is predicted to reduce any specialist gut microbes adapted to that diet would then diversity as a result, leading to a vicious cycle of reduced tend to flourish in the other household members. Even worse diversity, increased manipulation and chronic energy excess. the obesity epidemic could be contagious as a result of Such a positive feedback mechanism could drive long-term obesity-causing microbes transmitted from person to person changes in satiety harming the host by causing obesity a social network study of 12, 067 people found that a person's D Experimental increases in gut microbiota diversity are chance of becoming obese increased by 57% if a friend had expected to change the satiety setpoint, favoring decreased become obese [99 This raises up the possibility that cravings food intake by the host 92 ind associated obesity might not be socially contagious (e. g network study microbial manitu may inhibit density-dependent cold i75). This proposition could be tested by experimentally preference in animals, as above. As others have proposed One explanation for the health benefits of intestinal diversity if food preferences are contagious, then co-housing those is the inhibition of quorum sensing microbes from achieving a manipulated animals with germ-free animals should lead to quorum. Quorum sensing is a cell-cell communication system transmission of food preference [7, 100 used by many gut bacteria to regulate density-dependent conditional strategies, including virulence factor expression and changes in growth. For instance, the common human commensal and pathogen S ases the accessory gene Alternative hypotheses for unhealthy regulator system(AGR)of quorum sensing to regulate toxin eating and obesity and other virulence genes. When S. aureus reaches high density, aGR switches from expression of genes involved in There are a number of existing hypotheses for the prevalence colonization and attachment to those involved in tissue of obesity and our cravings for unhealthy foods, including invasion [93]. Quorum sensing may be one route that microbes addiction/lack of willpower, environmental mismatch, and can use to coordinate behavior in order to manipulate host nutrient shortages. A microbial cause is not mutually eating behavior and enhance resource delivery. It is in the exclusive of other alternatives such as nutrient deprivation host's interest to prevent bacteria from reaching the threshold In this section, we review each of these alternative hypothe- density for expression of virulence toxins and proteases From ses. We find that none of these hypotheses is completely translational perspective, treatments that increase microbial consistent with the data on cravings, food preferences, and diversity might prevent some microbe populations from obesity reaching the density required for a quorum, thus limiting their capacity to manipulate host behavior. Lack of willpower is not sufficient to explain unhealthy eating Interrogation of host and microbiota genomes should reveal a signaling arms race Conventional wisdom often blames unhealthy eating on a lack of willpower. However, binge eating is not just a matter of There has been little work to study the co-evolution of the mental control [101; food cravings are unlike other cravings microbiome and their host genomes [11, 94], and what there is Many other addictions, such as drugs and alcohol, require has tended to focus on mutualism rather than evolutionary ever-increasing doses to maintain the same mood-altering onflict between microbes and their hosts. We hypothesize that effect. This habituation does not happen with food. For some there has been a genomic arms race in which microbes have individuals, the more they indulge their food cravings, the evolved genes to manipulate their hosts(particularly analogs of more enjoyment they get from them [102]. These results, and human signaling molecules such as neuropeptides and recent work showing distinct mechanisms of food-reward and hormones)and corresponding host genes have evolved to morphine sensitization in mice suggest that overeating has a prevent that manipulation where it conflicts with the host's different underlying mechanism from drug abuse, and is not fitness interests. Comparative genomic analyses may reveal consistent with an addiction [103] such co-evolutionary patterns, and they have already identified adaptations specific to obligate commensal microbes [ 95, 96 Mismatch with scarce resources in our ancestral environment is not sufficient to explain unhealthy Food preferences may be contagious eating One intriguing implication of microbially induced cravings Food preferences are thought to arise from a complex is that preferences for certain foods may be contagious [97 interaction between genes, environment, and culture. The Both the fecal and oral microbiota are more similar among modern food environment is vastly different from that of our cohabiting family members compared to non-cohabiting evolutionary ancestors: the human ancestral diet is thought individuals [98]. If the food preferences of one person in a to contain foods far lower in salt, simple carbohydrates, household influence the food consumption of the household, and saturated fat than the typical Western diet [104]. This Bioessays 36: 940-949, 2014 The Authors Bioessays published by WILEY Periodicals, Inc. 945
and the immune system. Energy excess is predicted to reduce diversity as a result, leading to a vicious cycle of reduced diversity, increased manipulation and chronic energy excess. Such a positive feedback mechanism could drive long-term changes in satiety, harming the host by causing obesity. Experimental increases in gut microbiota diversity are expected to change the satiety setpoint, favoring decreased food intake by the host [92]. High gut diversity may inhibit density-dependent microbial manipulation One explanation for the health benefits of intestinal diversity is the inhibition of quorum sensing microbes from achieving a quorum. Quorum sensing is a cell–cell communication system used by many gut bacteria to regulate density-dependent conditional strategies, including virulence factor expression and changes in growth. For instance, the common human commensal and pathogen S. aureus uses the accessory gene regulator system (AGR) of quorum sensing to regulate toxin and other virulence genes. When S. aureus reaches high density, AGR switches from expression of genes involved in colonization and attachment to those involved in tissue invasion [93]. Quorum sensing may be one route that microbes can use to coordinate behavior in order to manipulate host eating behavior and enhance resource delivery. It is in the host’s interest to prevent bacteria from reaching the threshold density for expression of virulence toxins and proteases. From a translational perspective, treatments that increase microbial diversity might prevent some microbe populations from reaching the density required for a quorum, thus limiting their capacity to manipulate host behavior. Interrogation of host and microbiota genomes should reveal a signaling arms race There has been little work to study the co-evolution of the microbiome and their host genomes [11, 94], and what there is has tended to focus on mutualism rather than evolutionary conflict between microbes and their hosts. We hypothesize that there has been a genomic arms race in which microbes have evolved genes to manipulate their hosts (particularly analogs of human signaling molecules such as neuropeptides and hormones) and corresponding host genes have evolved to prevent that manipulation where it conflicts with the host’s fitness interests. Comparative genomic analyses may reveal such co-evolutionary patterns, and they have already identified adaptations specific to obligate commensal microbes [95, 96]. Food preferences may be contagious One intriguing implication of microbially induced cravings is that preferences for certain foods may be contagious [97]. Both the fecal and oral microbiota are more similar among cohabiting family members compared to non-cohabiting individuals [98]. If the food preferences of one person in a household influence the food consumption of the household, any specialist gut microbes adapted to that diet would then tend to flourish in the other household members. Even worse, the obesity epidemic could be contagious as a result of obesity-causing microbes transmitted from person to person. A social network study of 12,067 people found that a person’s chance of becoming obese increased by 57% if a friend had become obese [99]. This raises up the possibility that cravings and associated obesity might not be socially contagious (e.g. through changes in norms) as the authors of the social network study suggest [99], but rather truly infectious, like a cold [75]. This proposition could be tested by experimentally selecting for a microbiome that generates a particular food preference in animals, as above. As others have proposed, if food preferences are contagious, then co-housing those manipulated animals with germ-free animals should lead to transmission of food preference [7, 100]. Alternative hypotheses for unhealthy eating and obesity There are a number of existing hypotheses for the prevalence of obesity and our cravings for unhealthy foods, including addiction/lack of willpower, environmental mismatch, and nutrient shortages. A microbial cause is not mutually exclusive of other alternatives such as nutrient deprivation. In this section, we review each of these alternative hypotheses. We find that none of these hypotheses is completely consistent with the data on cravings, food preferences, and obesity. Lack of willpower is not sufficient to explain unhealthy eating Conventional wisdom often blames unhealthy eating on a lack of willpower. However, binge eating is not just a matter of mental control [101]; food cravings are unlike other cravings. Many other addictions, such as drugs and alcohol, require ever-increasing doses to maintain the same mood-altering effect. This habituation does not happen with food. For some individuals, the more they indulge their food cravings, the more enjoyment they get from them [102]. These results, and recent work showing distinct mechanisms of food-reward and morphine sensitization in mice suggest that overeating has a different underlying mechanism from drug abuse, and is not consistent with an addiction [103]. Mismatch with scarce resources in our ancestral environment is not sufficient to explain unhealthy eating Food preferences are thought to arise from a complex interaction between genes, environment, and culture. The modern food environment is vastly different from that of our evolutionary ancestors: the human ancestral diet is thought to contain foods far lower in salt, simple carbohydrates, and saturated fat than the typical Western diet [104]. This ....Prospects & Overviews J. Alcock et al. Bioessays 36: 940–949, 2014 The Authors. Bioessays published by WILEY Periodicals, Inc. 945 Review essays
J. Alcock et al Prospects& Overviews■■■■ discordance, or environmental mismatch, has been cited as changes drastically within 24 hours of changing diet [ 14, 1151 the source of"diseases of civilization, "including obesity, or administration of antibiotics [116]. Fecal transplants have cancer, and cardiovascular disease [105. Similar logic shown efficacy in treating a variety of diseases [117 The best postulates that past scarcity of calorie dense foods and approaches to managing our microbiota are still open critical micronutrients has also shaped modern food prefer. questions. Many studies of the effects of gut microbes on ences. The traditional diet of pre-agricultural humans relied health have focused on identifying individual taxa that are on low-carbohydrate plant foods and game, low in fat. Among responsible for human diseases, an approach that has been hunter gatherers, food acquisition efforts have been shown largely unsuccessful in generating predictive hypotheses to prioritize energy dense foods, gathered in a pattern that Studies have identified conflicting different groups of a maximizes energy capture relative to energy expenditure. microbes associated with various diseases, including obesi This strategy, described as optimal foraging theory, is fitness ty [118, 119 In other domains, it has proven useful to shift the enhancing in an environment where energy dense foods were level of analysis from properties of the individual to properties oL rare and hard to acquire [106 Under this hypothesis, in the of the population, e. g. diversity [120]. Until we have a better modern food environment with abundant food and sedentary understanding of the contributions and interactions between lifestyles, once-adaptive physiologic mechanisms regulating individual microbial taxa, it may be more effective to focus energy intake and expenditure have gone awry, leading to interventions on increasing microbial diversity in the gut. overeating and obesity Competition between genomes is likely to produce a Despite the intuitive appeal of this hypothesis, a number variety of conflicts, and we propose that one important area of food preferences and cravings are not in accord with its impacting human health, is in host eating behavior and predictions. For example, one of the most common modern nutrient acquisition. Genetic conflict between host and cravings involves a food that ancient hominids never knew microbiota selecting for microbes that manipulate host and which fulfills no nutritional requirement: chocolate [ 102]. eating behavior adds a new dimension to current view The hypothesis that environmental mismatch explains points, e.g. host-microbiota mutualism [11], that can explain diseases caused by diet has also been criticized by others mechanisms involved in obesity and related diseases as overly simplistic [86] Nutrient deprivation is not sufficient to explain The authors thank A. Boddy, A. Caulin, R. Datta, and M. unhealthy eating Fischbach as well as A. moore and the anonymous reviewers for helpful feedback, suggestions, and discussions. This work A similar hypothesis proposes that cravings result from was supported in part by the wissenschaftskolleg zu Berlin nutrient shortage [84]. For instance, fruit flies seek out specific (Institute for Advanced Study), a Research Scholar Grant nutrients after deprivation [107 However, this hypothesis #117209-RSG-09-163-01-CNE from the American Cancer Socie. does not explain many findings regarding cravings in humans. ty, the Bonnie J. Addario Lung Cancer Foundation, and NIH Food cravings strike even in times of plenty [108, 109 and grants F32 CA132450, PO1 CA91955, RO1 CA149566, Ro1 often foods that would satisfy a supposed nutrient shortage CA170595, and Ro1 CA140657 are not the ones that are craved [110. Furthermore fasting reduces cravings [111-113] rather than increasing them, as The authors have declared no conflict of interest. would be expected from the nutrient shortage hypothesis. The same pattern holds for cravings of non-food items such as clay and earth [114]. Young and colleagues subjected geophagy References (earth-eating) to a systematic review and concluded that human geophagy is not driven by nutrient scarcity [114] 1. Flegal KM, Carroll MD, ogden CL, Curtin LR. 2010. Prevalence and trends in obesity among US adults, 1999-2008. JAMA 303: 235-41 2. Calle EE, Kaaks R. 2004. Overweight, obesity and cancer: epidemio- Nat Rev Cancer 4: Conclusions Modern biology suggests that our bodies are composed of a omen. N Engl J Med 322: 882- diversity of organisms competing for nutritional resources. 4. Anderson Jw, Kendall Cw, Jenkins DJ. 2003. Importance of weight Evolutionary conflict between the host and microbiota may lead to cravings and cognitive conflict with regard to food n R, Aktipis CA. 2007. Modularity and the social mind choice. Exerting self-control over eating choices may be partly 6. Rhee SH, Pothoulakis C, Mayer EA. 2009. Principles and clinical a matter of suppressing microbial signals that originate in the ut. Acquired tastes may be due to the acquisition of microbes that benefit from those foods. Our review suggests that one Norris v, Molina F, Gewirtz AT 2013. Hypothesis: bacteria control host ay to change eating behavior is by intervening in our 8. Lyte M 2011. Probiotics function mechanistically as delivery vehicles microbiota for neuroactive compounds: microbial endocrinology in the design and It is encouraging that the microbiota can be changed by ays33574-81 nany interventions, hence facilitating translation to the clinic 9. Haig D. 2010. Transfers and transitions: parent-offspring conflict, and the evolution of human life history. Proc Nati and public health efforts. Microbiota community structure Acad Sci USA 107: 1731- 946 Bioessays 36: 940-949, C 2014 The Authors Bioessays published by WLEY Perodicals, Inc
discordance, or environmental mismatch, has been cited as the source of “diseases of civilization,” including obesity, cancer, and cardiovascular disease [105]. Similar logic postulates that past scarcity of calorie dense foods and critical micronutrients has also shaped modern food preferences. The traditional diet of pre-agricultural humans relied on low-carbohydrate plant foods and game, low in fat. Among hunter gatherers, food acquisition efforts have been shown to prioritize energy dense foods, gathered in a pattern that maximizes energy capture relative to energy expenditure. This strategy, described as optimal foraging theory, is fitness enhancing in an environment where energy dense foods were rare and hard to acquire [106]. Under this hypothesis, in the modern food environment with abundant food and sedentary lifestyles, once-adaptive physiologic mechanisms regulating energy intake and expenditure have gone awry, leading to overeating and obesity. Despite the intuitive appeal of this hypothesis, a number of food preferences and cravings are not in accord with its predictions. For example, one of the most common modern cravings involves a food that ancient hominids never knew and which fulfills no nutritional requirement: chocolate [102]. The hypothesis that environmental mismatch explains diseases caused by diet has also been criticized by others as overly simplistic [86]. Nutrient deprivation is not sufficient to explain unhealthy eating A similar hypothesis proposes that cravings result from nutrient shortage [84]. For instance, fruit flies seek out specific nutrients after deprivation [107]. However, this hypothesis does not explain many findings regarding cravings in humans. Food cravings strike even in times of plenty [108, 109], and often foods that would satisfy a supposed nutrient shortage are not the ones that are craved [110]. Furthermore, fasting reduces cravings [111–113] rather than increasing them, as would be expected from the nutrient shortage hypothesis. The same pattern holds for cravings of non-food items such as clay and earth [114]. Young and colleagues subjected geophagy (earth-eating) to a systematic review and concluded that human geophagy is not driven by nutrient scarcity [114]. Conclusions Modern biology suggests that our bodies are composed of a diversity of organisms competing for nutritional resources. Evolutionary conflict between the host and microbiota may lead to cravings and cognitive conflict with regard to food choice. Exerting self-control over eating choices may be partly a matter of suppressing microbial signals that originate in the gut. Acquired tastes may be due to the acquisition of microbes that benefit from those foods. Our review suggests that one way to change eating behavior is by intervening in our microbiota. It is encouraging that the microbiota can be changed by many interventions, hence facilitating translation to the clinic and public health efforts. Microbiota community structure changes drastically within 24 hours of changing diet [14, 115] or administration of antibiotics [116]. Fecal transplants have shown efficacy in treating a variety of diseases [117]. The best approaches to managing our microbiota are still open questions. Many studies of the effects of gut microbes on health have focused on identifying individual taxa that are responsible for human diseases, an approach that has been largely unsuccessful in generating predictive hypotheses. Studies have identified conflicting different groups of microbes associated with various diseases, including obesity [118, 119]. In other domains, it has proven useful to shift the level of analysis from properties of the individual to properties of the population, e.g. diversity [120]. Until we have a better understanding of the contributions and interactions between individual microbial taxa, it may be more effective to focus interventions on increasing microbial diversity in the gut. Competition between genomes is likely to produce a variety of conflicts, and we propose that one important area, impacting human health, is in host eating behavior and nutrient acquisition. Genetic conflict between host and microbiota – selecting for microbes that manipulate host eating behavior – adds a new dimension to current viewpoints, e.g. host-microbiota mutualism [11], that can explain mechanisms involved in obesity and related diseases. Acknowledgements The authors thank A. Boddy, A. Caulin, R. Datta, and M. Fischbach as well as A. Moore and the anonymous reviewers for helpful feedback, suggestions, and discussions. This work was supported in part by the Wissenschaftskolleg zu Berlin (Institute for Advanced Study), a Research Scholar Grant #117209-RSG-09-163-01-CNE from the American Cancer Society, the Bonnie J. Addario Lung Cancer Foundation, and NIH grants F32 CA132450, P01 CA91955, R01 CA149566, R01 CA170595, and R01 CA140657. The authors have declared no conflict of interest. References 1. Flegal KM, Carroll MD, Ogden CL, Curtin LR. 2010. Prevalence and trends in obesity among US adults,1999–2008. JAMA 303: 235–41. 2. Calle EE, Kaaks R. 2004. Overweight, obesity and cancer: epidemiological evidence and proposed mechanisms. Nat Rev Cancer 4: 579–91. 3. Manson JE, Colditz GA, Stampfer MJ, Willett WC, et al. 1990. A prospective study of obesity and risk of coronary heart disease in women. N Engl J Med 322: 882–9. 4. Anderson JW, Kendall CW, Jenkins DJ. 2003. Importance of weight management in type 2 diabetes: review with meta-analysis of clinical studies. J Am Coll Nutr 22: 331–9. 5. Kurzban R, Aktipis CA. 2007. Modularity and the social mind: are psychologists too self-ish? Pers Soc Psychol Rev 11: 131–49. 6. Rhee SH, Pothoulakis C, Mayer EA. 2009. Principles and clinical implications of the brain-gut-enteric microbiota axis. Nat Rev Gastroenterol Hepatol 6: 306–14. 7. Norris V, Molina F, Gewirtz AT. 2013. Hypothesis: bacteria control host appetites. J Bacteriol 195: 411–6. 8. Lyte M. 2011. Probiotics function mechanistically as delivery vehicles for neuroactive compounds: microbial endocrinology in the design and use of probiotics. BioEssays 33: 574–81. 9. Haig D. 2010. Transfers and transitions: parent-offspring conflict, genomic imprinting, and the evolution of human life history. Proc Natl Acad Sci USA 107: 1731–5. J. Alcock et al. Prospects & Overviews .... 946 Bioessays 36: 940–949, 2014 The Authors. Bioessays published by WILEY Periodicals, Inc. Review essays
■■■口 Prospects& Overviews J. Alcock et al 10. Haig D, wharton R. 2003. Alli syndrome and the evolution of 35. Medzhitov R, Schneider DS, Soares MP 2012. Disease tolerance as a ackhed F, Ley Re, son son DA, et al. 2005. Host- 12. Dethlefsen L, McFall-Ngai M, Relman DA. 2007. An ecological and volutionary perspective on human-microbe mutualism and disease. 37. Njoroge J, Sperandio V. 2012. Enterohemorrhagic Eschenchia coll I3. Gonzalez-Rodriguez L, Ruiz L, Gueimonde M, Margolles A, et al. mmun80:688-703. 38. Chiu IM, Heesters BA, Ghasemlou N, Von Hehn CA, et al. 2013. o≤0 gastrointestinal tract. FEMS Microbiol Lett 340: 1-10 sensory neurons that modulate pain and inflammatio 14. Wu GD, Chen J, Hoffmann C, Bittinger K, et al. 2011. Linking long. term dietary patterns with gut microbial enterotypes. Science 334: 39. Amaral FA, Sachs D, Costa W, Fagundes CT, et al. 2008. Cc 2010. of diet in shaping gut microbiota reveale 41. Duca FA, Swartz TD, Sakar Y, Covas M. 2012. Ine in children from Europe and rural Africa. Proc Natl Acad Sci USA 07:14691 crobiota. PLoS ONE 7: e3974 17. Fava F, Gitau R, Griffin B, Gibson G, et al. 2012. The ty 2. Swartz F, de Wouters T, Sakar Y, et aL. 2012. Up-regulation( of dietary fat and carbohydrate alter faecal microbiome and short-chair te receptor 3 and sodi tty acid excretion in a metabolic syndrome 'at-risk population. Int J transporter-1 expression and increased sucrose intake in mice lacking Dbes(Lond) 37: 216-23 18. McNulty NP, wu M, Erickson AR, Pan C, et al. 201 43. Rousseaux C, Thuru x, Gelot A, Barnich N, et al. 2007. Lactobacillus resource utilization by a model human gut mict acteroides cellulolyticus WH2, a symbiont oid receptors. M ates intestinal pain and induces opioid and cannabi- glycobiome. PLos Bia 11: e10016c lying weight loss after 19. Walter J, Ley R. 2011. The human gut microbiome: ecology and recent bariatric surgery. Nat Rev Gastroenterol Hepatol 10. 575-84 yolutionary changes. Annu Rev Microbiol 65: 411-2 45. Collins SM. Surette M. bercik P. 2012. The int 20. Rezzi s, Ramadan Z, Martin FP, Fay LB, et al. 2007. Human testinal microbiota and the brain Nat Rev microbio/ 10: 735-42 directly to specific dietary preferences in healthy 6. Bercik P, Collins SM, Verdu EF 2012. Microbes and the gut-brain axis. 21. Benton D, williams C, Brown A. 2007. Impact of consuming a mill 47. M urogastroent Motil 24: 405-13 Mayer EA. 2011. Gut feelings: the emerging biology of gut-brain fractions between gut 22. Schroeder FA, Lin CL, Crusio WE, Akbarian S 2007. Antidepressant- endocrine cells and visceral afferents. Auton Neurosci 153: 41-6 Biol Psychiatry 62: 55-64 ical results with a new 23. Bercik P, Denou E, Collins J, Jackson w, et al. 2011. The intestinal plantable medical device. Surgery 143: 723-31 microbiota affect central levels of brain-derived neurotropic factor and 50. Sarr MG, Billington Cu, Brancatisano R, Br 4. Messaoudi M, Lalonde r, violle N, Javelot H, et al. 2011. Assessment enter trial of vagal blockade to induce weight loss in morbid obesity ibowitz SF 1981 eating elicited by 25. ohland CL, Kish L, Bel H, Thiesen A, et al. 2013. Effects of paraventricular nucleus. Brain Res 225: 249-69. or are dependent on die genotype and correlate with alterations in the gut microbiome. counteracts self-control depletion Conscious Cogn 21: 1016-22. 53. Long SJ, Hart K, Morgan LM. 2002. The ability of habitual exercise to sponse to high-and low-energ I behavior and central GABa in man. Br J Nutr 87: 517-2 t eptor expression in a mouse via the vagus nerve. Proc Nat Acad Sci 54. Kollai M, Bonyhay l, Jokkel G, Szonyi L. 1994. Cardiac louse PK, Vyas A, Sapolsky R. 2011. Predator cat odors activate 55. Baraldi M, Avallone R, Corsi L, Venturini l, et al. 2009. ways in brains of Toxoplasma gondi infected rats. endogenous ligands for benzodiazepine receptors in hepatic encepha- LOS ONE 6: e23277 lopathy Metab Brain Dis 24: 81-93 er LE, Gaykema RP, Opitz N, Reddaway R, et al. 2005. 56. Roth J, LeRoith D, Collier ES, Weaver NR, et al. 1985. Evolutionary esponses to intestinal infection with Campylobacter jejuni Brain Beha ons to immunology. J Immuno 135: 816s-9s. 57. Clarke G, Stilling RM, Kennedy PJ, stanton C, et al. 2014. Gut 9. de weerth C, Fuentes s, Puylaert P, de Vos wM. icrobiota of infants with colic: development and specific signatures 58. Eisenhofer G, Aneman A, Friberg P, Hooper D, et al. 1997. Subst 30. Crowcroft NS, Strachan DP. 1997. The social origins of infantile colic oning conflict theory, signaling of need, and 59. Kim DY, Can 4. 2000. Serotonin a mediator of the brain-gut eight gain in early life. Q Rev Bio/ 78: 169-202. connection. Am J Gastroentero 95: 2698-709 32. Soltis J. 2004. The signal functions of early infant crying. Behav Brain T, Netrusov A. 2006. Sci 27: 443-58: discussion ormones and hormone-like substances of microorganisms a review. Pande K f et al. 2011 n CE. et al. 2013. Sex ent regulation Kncremsaes the athegen ic potent l o almsmea t ron and othey? 62. adero v. cales-Enniq z M, Fernandez M. Alvarez MA. 2010 steric pathogens at the intestinal epith ines. CuT Nutr Food sci Bioessays 36: 940-949, 2014 The Authors Bioessays published by WILEY Periodicals, Inc. 947
10. Haig D, Wharton R. 2003. Prader Willi syndrome and the evolution of human childhood. Am J Hum Biol 15: 320–9. 11. Ba¨ ckhed F, Ley RE, Sonnenburg JL, Peterson DA, et al. 2005. Hostbacterial mutualism in the human intestine. Science 307: 1915–20. 12. Dethlefsen L, McFall-Ngai M, Relman DA. 2007. An ecological and evolutionary perspective on human-microbe mutualism and disease. Nature 449: 811–8. 13. Gonzalez-Rodriguez I, Ruiz L, Gueimonde M, Margolles A, et al. 2013. Factors involved in the colonization and survival of bifidobacteria in the gastrointestinal tract. FEMS Microbiol Lett 340: 1–10. 14. Wu GD, Chen J, Hoffmann C, Bittinger K, et al. 2011. Linking longterm dietary patterns with gut microbial enterotypes. Science 334: 105–8. 15. Hehemann JH, Correc G, Barbeyron T, Helbert W, et al. 2010. Transfer of carbohydrate-active enzymes from marine bacteria to Japanese gut microbiota. Nature 464: 908–12. 16. De Filippo C, Cavalieri D, Di Paola M, Ramazzotti M, et al. 2010. Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa. Proc Natl Acad Sci USA 107: 14691–6. 17. Fava F, Gitau R, Griffin B, Gibson G, et al. 2012. The type and quantity of dietary fat and carbohydrate alter faecal microbiome and short-chain fatty acid excretion in a metabolic syndrome ‘at-risk’ population. Int J Obes (Lond) 37: 216–23. 18. McNulty NP, Wu M, Erickson AR, Pan C, et al. 2013. Effects of diet on resource utilization by a model human gut microbiota containing Bacteroides cellulosilyticus WH2, a symbiont with an extensive glycobiome. PLoS Biol 11: e1001637. 19. Walter J, Ley R. 2011. The human gut microbiome: ecology and recent evolutionary changes. Annu Rev Microbiol 65: 411–29. 20. Rezzi S, Ramadan Z, Martin FP, Fay LB, et al. 2007. Human metabolic phenotypes link directly to specific dietary preferences in healthy individuals. J Proteome Res 6: 4469–77. 21. Benton D, Williams C, Brown A. 2007. Impact of consuming a milk drink containing a probiotic on mood and cognition. Eur J Clin Nutr 61: 355–61. 22. Schroeder FA, Lin CL, Crusio WE, Akbarian S. 2007. Antidepressantlike effects of the histone deacetylase inhibitor, sodium butyrate, in the mouse. Biol Psychiatry 62: 55–64. 23. Bercik P, Denou E, Collins J, Jackson W, et al. 2011. The intestinal microbiota affect central levels of brain-derived neurotropic factor and behavior in mice. Gastroenterology 141: 599–609 e1-3. 24. Messaoudi M, Lalonde R, Violle N, Javelot H, et al. 2011. Assessment of psychotropic-like properties of a probiotic formulation (Lactobacillus helveticus R0052 and Bifidobacterium longum R0175) in rats and human subjects. Br J Nutr 105: 755–64. 25. Ohland CL, Kish L, Bell H, Thiesen A, et al. 2013. Effects of Lactobacillus helveticus on murine behavior are dependent on diet and genotype and correlate with alterations in the gut microbiome. Psychoneuroendocrinology 38: 1738–47. 26. Bravo JA, Forsythe P, Chew MV, Escaravage E, et al. 2011. Ingestion of Lactobacillus strain regulates emotional behavior and central GABA receptor expression in a mouse via the vagus nerve. Proc Natl Acad Sci USA 108: 16050–5. 27. House PK, Vyas A, Sapolsky R. 2011. Predator cat odors activate sexual arousal pathways in brains of Toxoplasma gondii infected rats. PLoS ONE 6: e23277. 28. Goehler LE, Gaykema RP, Opitz N, Reddaway R, et al. 2005. Activation in vagal afferents and central autonomic pathways: early responses to intestinal infection with Campylobacter jejuni. Brain Behav Immun 19: 334–44. 29. de Weerth C, Fuentes S, Puylaert P, de Vos WM. 2013. Intestinal microbiota of infants with colic: development and specific signatures. Pediatrics 131: e550–8. 30. Crowcroft NS, Strachan DP. 1997. The social origins of infantile colic: questionnaire study covering 76 747 infants. BMJ 314: 1325–8. 31. Wells JC. 2003. Parent-offspring conflict theory, signaling of need, and weight gain in early life. Q Rev Biol 78: 169–202. 32. Soltis J. 2004. The signal functions of early infant crying. Behav Brain Sci 27: 443–58; discussion 59–90. 33. Chen C, Pande K, French SD, Tuch BB, et al. 2011. An iron homeostasis regulatory circuit with reciprocal roles in Candida albicans commensalism and pathogenesis. Cell Host Microbe 10: 118–35. 34. Kortman GA, Boleij A, Swinkels DW, Tjalsma H. 2012. Iron availability increases the pathogenic potential of Salmonella typhimurium and other enteric pathogens at the intestinal epithelial interface. PLoS ONE 7: e29968. 35. Medzhitov R, Schneider DS, Soares MP. 2012. Disease tolerance as a defense strategy. Science 335: 936–41. 36. Njoroge JW, Nguyen Y, Curtis MM, Moreira CG, et al. 2012. Virulence meets metabolism: Cra and KdpE gene regulation in enterohemorrhagic Escherichia coli. mBio 3: e00280–12. 37. Njoroge J, Sperandio V. 2012. Enterohemorrhagic Escherichia coli virulence regulation by two bacterial adrenergic kinases, QseC and QseE. Infect Immun 80: 688–703. 38. Chiu IM, Heesters BA, Ghasemlou N, Von Hehn CA, et al. 2013. Bacteria activate sensory neurons that modulate pain and inflammation. Nature 501: 52–7. 39. Amaral FA, Sachs D, Costa VV, Fagundes CT, et al. 2008. Commensal microbiota is fundamental for the development of inflammatory pain. Proc Natl Acad Sci USA 105: 2193–7. 40. Khasar SG, Reichling DB, Green PG, Isenberg WM, et al. 2003. Fasting is a physiological stimulus of vagus-mediated enhancement of nociception in the female rat. Neuroscience 119: 215–21. 41. Duca FA, Swartz TD, Sakar Y, Covasa M. 2012. Increased oral detection, but decreased intestinal signaling for fats in mice lacking gut microbiota. PLoS ONE 7: e39748. 42. Swartz T, Duca F, de Wouters T, Sakar Y, et al. 2012. Up-regulation of intestinal type 1 taste receptor 3 and sodium glucose luminal transporter-1 expression and increased sucrose intake in mice lacking gut microbiota. Br J Nutr 107: 621. 43. Rousseaux C, Thuru X, Gelot A, Barnich N, et al. 2007. Lactobacillus acidophilus modulates intestinal pain and induces opioid and cannabinoid receptors. Nat Med 13: 35–7. 44. Miras AD, le Roux CW. 2013. Mechanisms underlying weight loss after bariatric surgery. Nat Rev Gastroenterol Hepatol 10: 575–84. 45. Collins SM, Surette M, Bercik P. 2012. The interplay between the intestinal microbiota and the brain. Nat Rev Microbiol 10: 735–42. 46. Bercik P, Collins SM, Verdu EF. 2012. Microbes and the gut-brain axis. Neurogastroent Motil 24: 405–13. 47. Mayer EA. 2011. Gut feelings: the emerging biology of gut-brain communication. Nat Rev Neurosci 12: 453–66. 48. Raybould HE. 2010. Gut chemosensing: interactions between gut endocrine cells and visceral afferents. Auton Neurosci 153: 41–6. 49. Camilleri M, Toouli J, Herrera MF, Kulseng B, et al. 2008. Intraabdominal vagal blocking (VBLOC therapy): clinical results with a new implantable medical device. Surgery 143: 723–31. 50. Sarr MG, Billington CJ, Brancatisano R, Brancatisano A, et al. 2012. The EMPOWER study: randomized, prospective, double-blind, multicenter trial of vagal blockade to induce weight loss in morbid obesity. Obes Surg 22: 1771–82. 51. Sawchenko PE, Gold RM, Leibowitz SF. 1981. Evidence for vagal involvement in the eating elicited by adrenergic stimulation of the paraventricular nucleus. Brain Res 225: 249–69. 52. Friese M, Messner C, Schaffner Y. 2012. Mindfulness meditation counteracts self-control depletion. Conscious Cogn 21: 1016–22. 53. Long SJ, Hart K, Morgan LM. 2002. The ability of habitual exercise to influence appetite and food intake in response to high-and low-energy preloads in man. Br J Nutr 87: 517–23. 54. Kollai M, Bonyhay I, Jokkel G, Szonyi L. 1994. Cardiac vagal hyperactivity in adolescent anorexia nervosa. Eur Heart J 15: 1113–8. 55. Baraldi M, Avallone R, Corsi L, Venturini I, et al. 2009. Natural endogenous ligands for benzodiazepine receptors in hepatic encephalopathy. Metab Brain Dis 24: 81–93. 56. Roth J, LeRoith D, Collier ES, Weaver NR, et al. 1985. Evolutionary origins of neuropeptides, hormones, and receptors: possible applications to immunology. J Immunol 135: 816s–9s. 57. Clarke G, Stilling RM, Kennedy PJ, Stanton C, et al. 2014. Gut microbiota: the neglected endocrine organ. Mol Endocrinol me20141108. 58. Eisenhofer G, Aneman A, Friberg P, Hooper D, et al. 1997. Substantial production of dopamine in the human gastrointestinal tract. J Clin Endocrinol Metab 82: 3864–71. 59. Kim DY, Camilleri M. 2000. Serotonin: a mediator of the brain-gut connection. Am J Gastroenterol 95: 2698–709. 60. Tsavkelova E, Klimova SY, Cherdyntseva T, Netrusov A. 2006. Hormones and hormone-like substances of microorganisms: a review. Appl Biochem Microbiol 42: 229–35. 61. Markle JG, Frank DN, Mortin-Toth S, Robertson CE, et al. 2013. Sex differences in the gut microbiome drive hormone-dependent regulation of autoimmunity. Science 339: 1084–8. 62. Ladero V, Calles-Enriquez M, Fernandez M, Alvarez MA. 2010. Toxicological effects of dietary biogenic amines. Curr Nutr Food Sci 6: 145–56. ....Prospects & Overviews J. Alcock et al. Bioessays 36: 940–949, 2014 The Authors. Bioessays published by WILEY Periodicals, Inc. 947 Review essays
J. Alcock et al Prospects& Overviews■■■■ 3. Sanchez-Jimenez F, Ruiz-Perez M, Urdiales J, Medina M. 2013. 87. Berntson GG, Cacioppo JT, Quigley KS. 1993. Respiratory sinus Pharmacological potential polyamine interactions and psycho- eyond neurotransmission. Br J Pharmaco/ 170: 4-1 physiological implications. Psychophysiology 30: 183-96 ernal epression Neuroscience 170: 1179-88. 89. Kong LC, Tap J, Aron-Wisnewsky J, Pelloux V, et al. 2013. Gut 5. Thomas CM, Hong T, van Pijkeren JP, Hemarajata P, et al. 2012. INE tions of bacterial genera with adipose tissue genes. Am J nd ERK signaling PLOS ONE 7: e31951 Clin Nut98:16-24 66. Lyte M, v ova L, Brown DR. 2011. Stress at the 90. Bueter M, Miras AD, Chichger H, Fenske w, et aL. 2011. Alterations of olamines and mucosa-bacteria interactions Cell Tissue 67. Yadav H, Lee JH, Lloyd J, Walter P, et al. 2013. Beneficial metabolic 91. Mathes CM, Spector AC. 2012. Food selection and taste changes in umans after Roux-en-Y gastric bypass surgery: a direct-measures 68. Fetissov so, Hamze Sinno M, Coeffier M, Bole-Feysot C, et al. 2008. 92. Yatsunenko T, Rey Fe, Manary MJ, Trehan l, et al. 2012. Human utoantibodies against app eptides: putative modulation by gut microflora. Nutrition 24: 222-7 93. Reading NC, Sperandio v. 2006. Quorum sensing: the many languages 69. Bry L, Falk PG, Midtvedt T, Gordon JI. 1996. A model of host ial interactions in an open mammalian ecosystem Science 273: 94. Ley RE, Lozupone CA, Hamady M, Knight R, et al. 2008. Worlds within worlds: evolution of the vertebrate gut microbiota. Nat Re 70. Wrzosek L, Miquel s, Noordine M-L, Bouet s, et al. 2013 a K, Itoh T, Kuwahara T, Oshima K, et al. 2007. Comparative nce the production of mucus glycans and the development of goblet cells in the colonic epithelium of a gnotobiotic model rodent. metagenomics revealed commonly enriched gene sets in human gu 96. Qin J, Li R, Raes J, Arumugam M, et al. 2010. A human gut microbial 1. Shin N-R, Lee J-C, Lee H-Y, Kim M-s, et al. 2013. An increase in gene catalogue established by metagenomic sequencing. Nature 464 the Akkermansia spp. population induced by metformin treatment roves glucose homeostasis in diet-induced obese mice. Gut 63: 97. Hill AL, Rand DG, Nowak MA, christakis NA. 2010. Infectious disease 72. Linden SK, Sutton P, Karlsson NG, Korolik V, et al. 2008. Mucins in the cosa/ immuno 1: 183-9 98. Song sJ, Lauber C, Costello EK, 73. Backhed F, Ding H, Wang T, Hooper Lv, et al. 2004. The gut ng family members share microbiota with one another and ctor that regulates fat storage. Pl s eLfe 2: Nat Acad sci USA 101: 15718-23 spread of obesity in a large social 74. Turnbaugh PJ, Ley Re, Mahowald MA, Magrini v, et al. 2006. A network over 32 years. N Engl J Med 357: 370-9 harvest. Nature 444: 10 ew mechanisms by which diet can infiuence gut-to-brain communica- 75. Ridaura VK, Faith JJ, Rey FE, cheng J, et al. 2013. Gut microbiota tion. Pharma№ evelopment of a measure to assess coping with negative affect by 76. Vijay-Kumar M, Aitken JD, Carvalho FA, Cullender TC, et al. 2010 ating. Int J Eat Disord 18: 79-90 in mice lacking Toll-like 77. Turnbaugh PJ, Hamady M, Yatsunenko T, Cantarel BL, et al. 2009. A 103. Har Almeida OF. 2014. Pavlovian conditioning and cros core gut microbiome in obese and lean twins. Nature 457: 480-4. sensitization studies raise challenges to the hypothesis that overeating Delzenne NM, Neyrinck AM, Backhed F, Cani PD 2011. Targeting gut microbiota in obesity: effects of prebiotics and probiotics. Nat Rev 104. Cordain L, Miller JB, Eaton SB, Mann N, et al. 2000. Plant-animal Endocrinol 7: 639-46 rer diets. Am J Clin Nutr 80. Kondo s, xiao JZ, Satoh T, OdamakiT, et al. 20 besity effects 106. Hawkes K, Hill K, O'Connell JF. 1982. Why hunt optimal foraging and the Ache of eastern Paraguay. An m signor g with high-fat diet-induced obesity. Biosci Biotechnol Biochem 74: 79-98. 1656-61 107. Gough NR. 2010. Even flies hav 3:ec178. 81. Kadooka Y, Sato M, Imaizumi K, ogawa A, et al. 2010. Regulation of 108. Pelchat ML, Schaefer S. 2000. D abdominal adiposity by probiotics(Lactobacillus gasseri SBT2055)in duits with obese tendencies in a randomized controlled trial. Eur J CHin 109. Hill Aj, weaver CF, Blundell JE. ood craving, dietary restraint ut64:636-43 and mood. Appetite 17: 187-97 82. Mozaffarian D, Hao T, Rimm EB, willett wc, et al. 2011. Changes in 110. Weingarten HP, Elston D. 1990. The phenomenology of food cravings. Med364:2392-404 11. Benton D. 2010. The pla 83. lImonen J, Isolauri E, Poussa T, Laitinen K. 2011. Impact of dietary orders. Cin Nutr 29: 288-303 hemal anthropometric 112. Batra P, Das sK, salinardi T, Robinson L, et al. 2013. Relationship of measurements during and after pregnancy: a randomized placebo- R↓smH2Fd和如13h8: ts from a 6 month worksite 14. w, Lucks JB, Pelto GH. 2011. Why on earth?: 85. Hollants J, Leliaert F, clerck O, willems A 2013. w about the physiological functions of huma bjo/ Ecol 83: 1-16 115.S ko T, Manary MJ, Trehan I, et al. 2013. Gut 86. Zuk M. 2013. Paleofantasy: What Evolution Really Tells Us About Sex, microbiomes of Malawian twin pairs discordant for kwashiorkor. Diet, and How We Live. New York, NY: Ww Norton& Company 948 Bioessays 36: 940-949, C 2014 The Authors Bioessays published by WLEY Perodicals, Inc
63. Sanchez-Jimenez F, Ruiz-Perez M, Urdiales J, Medina M. 2013. Pharmacological potential of biogenic amine-polyamine interactions beyond neurotransmission. Br J Pharmacol 170: 4–16. 64. Desbonnet L, Garrett L, Clarke G, Kiely B, et al. 2010. Effects of the probiotic Bifidobacterium infantis in the maternal separation model of depression. Neuroscience 170: 1179–88. 65. Thomas CM, Hong T, van Pijkeren JP, Hemarajata P, et al. 2012. Histamine derived from probiotic Lactobacillus reuteri suppresses TNF via modulation of PKA and ERK signaling. PLoS ONE 7: e31951. 66. Lyte M, Vulchanova L, Brown DR. 2011. Stress at the intestinal surface: catecholamines and mucosa-bacteria interactions. Cell Tissue Res 343: 23–32. 67. Yadav H, Lee JH, Lloyd J, Walter P, et al. 2013. Beneficial metabolic effects of a probiotic via butyrate-induced GLP-1 hormone secretion. J Biol Chem 288: 25088–97. 68. Fetissov SO, Hamze Sinno M, Coeffier M, Bole-Feysot C, et al. 2008. Autoantibodies against appetite-regulating peptide hormones and neuropeptides: putative modulation by gut microflora. Nutrition 24: 348–59. 69. Bry L, Falk PG, Midtvedt T, Gordon JI. 1996. A model of hostmicrobial interactions in an open mammalian ecosystem. Science 273: 1380–3. 70. Wrzosek L, Miquel S, Noordine M-L, Bouet S, et al. 2013. Bacteroides thetaiotaomicron and Faecalibacterium prausnitzii influence the production of mucus glycans and the development of goblet cells in the colonic epithelium of a gnotobiotic model rodent. BMC Biol 11: 61. 71. Shin N-R, Lee J-C, Lee H-Y, Kim M-S, et al. 2013. An increase in the Akkermansia spp. population induced by metformin treatment improves glucose homeostasis in diet-induced obese mice. Gut 63: 727–35. 72. Linden SK, Sutton P, Karlsson NG, Korolik V, et al. 2008. Mucins in the mucosal barrier to infection. Mucosal Immunol 1: 183–97. 73. Backhed F, Ding H, Wang T, Hooper LV, et al. 2004. The gut microbiota as an environmental factor that regulates fat storage. Proc Natl Acad Sci USA 101: 15718–23. 74. Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, et al. 2006. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 444: 1027–31. 75. Ridaura VK, Faith JJ, Rey FE, Cheng J, et al. 2013. Gut microbiota from twins discordant for obesity modulate metabolism in mice. Science 341: 1241214. 76. Vijay-Kumar M, Aitken JD, Carvalho FA, Cullender TC, et al. 2010. Metabolic syndrome and altered gut microbiota in mice lacking Toll-like receptor 5. Science 328: 228–31. 77. Turnbaugh PJ, Hamady M, Yatsunenko T, Cantarel BL, et al. 2009. A core gut microbiome in obese and lean twins. Nature 457: 480–4. 78. Delzenne NM, Neyrinck AM, Backhed F, Cani PD. 2011. Targeting gut microbiota in obesity: effects of prebiotics and probiotics. Nat Rev Endocrinol 7: 639–46. 79. Kootte RS, Vrieze A, Holleman F, Dallinga-Thie GM, et al. 2012. The therapeutic potential of manipulating gut microbiota in obesity and type 2 diabetes mellitus. Diabetes Obes Metab 14: 112–20. 80. Kondo S, Xiao JZ, Satoh T, Odamaki T, et al. 2010. Antiobesity effects of Bifidobacterium breve strain B-3 supplementation in a mouse model with high-fat diet-induced obesity. Biosci Biotechnol Biochem 74: 1656–61. 81. Kadooka Y, Sato M, Imaizumi K, Ogawa A, et al. 2010. Regulation of abdominal adiposity by probiotics (Lactobacillus gasseri SBT2055) in adults with obese tendencies in a randomized controlled trial. Eur J Clin Nutr 64: 636–43. 82. Mozaffarian D, Hao T, Rimm EB, Willett WC, et al. 2011. Changes in diet and lifestyle and long-term weight gain in women and men. N Engl J Med 364: 2392–404. 83. Ilmonen J, Isolauri E, Poussa T, Laitinen K. 2011. Impact of dietary counselling and probiotic intervention on maternal anthropometric measurements during and after pregnancy: a randomized placebocontrolled trial. Clin Nutr 30: 156–64. 84. Rogers PJ, Smit HJ. 2000. Food craving and food “addiction”: a critical review of the evidence from a biopsychosocial perspective. Pharmacol Biochem Behav 66: 3–14. 85. Hollants J, Leliaert F, Clerck O, Willems A. 2013. What we can learn from sushi: a review on seaweed-bacterial associations. FEMS Microbiol Ecol 83: 1–16. 86. Zuk M. 2013. Paleofantasy: What Evolution Really Tells Us About Sex, Diet, and How We Live. New York, NY: WW Norton & Company. 87. Berntson GG, Cacioppo JT, Quigley KS. 1993. Respiratory sinus arrhythmia: autonomic origins, physiological mechanisms, and psychophysiological implications. Psychophysiology 30: 183–96. 88. Ursell LK, Van Treuren W, Metcalf JL, Pirrung M, et al. 2013. Replenishing our defensive microbes. BioEssays 35: 810–7. 89. Kong LC, Tap J, Aron-Wisnewsky J, Pelloux V, et al. 2013. Gut microbiota after gastric bypass in human obesity: increased richness and associations of bacterial genera with adipose tissue genes. Am J Clin Nutr 98: 16–24. 90. Bueter M, Miras AD, Chichger H, Fenske W, et al. 2011. Alterations of sucrose preference after Roux-en-Y gastric bypass. Physiol Behav 104: 709–21. 91. Mathes CM, Spector AC. 2012. Food selection and taste changes in humans after Roux-en-Y gastric bypass surgery: a direct-measures approach. Physiol Behav 107: 476–83. 92. Yatsunenko T, Rey FE, Manary MJ, Trehan I, et al. 2012. Human gut microbiome viewed across age and geography. Nature 486: 222–7. 93. Reading NC, Sperandio V. 2006. Quorum sensing: the many languages of bacteria. FEMS Microbiol Lett 254: 1–11. 94. Ley RE, Lozupone CA, Hamady M, Knight R, et al. 2008. Worlds within worlds: evolution of the vertebrate gut microbiota. Nat Rev Microbiol 6: 776–88. 95. Kurokawa K, Itoh T, Kuwahara T, Oshima K, et al. 2007. Comparative metagenomics revealed commonly enriched gene sets in human gut microbiomes. DNA Res 14: 169–81. 96. Qin J, Li R, Raes J, Arumugam M, et al. 2010. A human gut microbial gene catalogue established by metagenomic sequencing. Nature 464: 59–65. 97. Hill AL, Rand DG, Nowak MA, Christakis NA. 2010. Infectious disease modeling of social contagion in networks. PLoS Comput Biol 6: e1000968. 98. Song SJ, Lauber C, Costello EK, Lozupone CA, et al. 2013. Cohabiting family members share microbiota with one another and with their dogs. eLife 2: e00458. 99. Christakis NA, Fowler JH. 2007. The spread of obesity in a large social network over 32 years. N Engl J Med 357: 370–9. 100. Lyte M. 2013. Microbial endocrinology and nutrition: a perspective on new mechanisms by which diet can influence gut-to-brain communication. PharmaNutrition 1: 35–9. 101. Arnow B, Kenardy J, Agras WS. 1995. The emotional eating scale: the development of a measure to assess coping with negative affect by eating. Int J Eat Disord 18: 79–90. 102. Weingarten HP, Elston D. 1991. Food cravings in a college population. Appetite 17: 167–75. 103. Harb MR, Almeida OF. 2014. Pavlovian conditioning and crosssensitization studies raise challenges to the hypothesis that overeating is an addictive behavior. Transl Psychiatry 4: e387. 104. Cordain L, Miller JB, Eaton SB, Mann N, et al. 2000. Plant-animal subsistence ratios and macronutrient energy estimations in worldwide hunter-gatherer diets. Am J Clin Nutr 71: 682–92. 105. Gluckman P, Hanson M. 2006. Mismatch: Why Our World No Longer Fits Our Bodies. Oxford, UK: Oxford University Press. 106. Hawkes K, Hill K, O’Connell JF. 1982. Why hunters gather: optimal foraging and the Ache of eastern Paraguay. Am. Ethnol. 9: 379–98. 107. Gough NR. 2010. Even flies have cravings. Sci. Signal. 3: ec178. 108. Pelchat ML, Schaefer S. 2000. Dietary monotony and food cravings in young and elderly adults. Physiol Behav 68: 353–9. 109. Hill AJ, Weaver CF, Blundell JE. 1991. Food craving, dietary restraint and mood. Appetite 17: 187–97. 110. Weingarten HP, Elston D. 1990. The phenomenology of food cravings. Appetite 15: 231–46. 111. Benton D. 2010. The plausibility of sugar addiction and its role in obesity and eating disorders. Clin Nutr 29: 288–303. 112. Batra P, Das SK, Salinardi T, Robinson L, et al. 2013. Relationship of cravings with weight loss and hunger. Results from a 6 month worksite weight loss intervention. Appetite 69: 1–7. 113. Ramirez I. 1990. Why do sugars taste good? Neurosci Biobehav Rev 14: 125–34. 114. Young SL, Sherman PW, Lucks JB, Pelto GH. 2011. Why on earth?: evaluating hypotheses about the physiological functions of human geophagy. Q Rev Biol 86: 97–120. 115. Smith MI, Yatsunenko T, Manary MJ, Trehan I, et al. 2013. Gut microbiomes of Malawian twin pairs discordant for kwashiorkor. Science 339: 548–54. J. Alcock et al. Prospects & Overviews .... 948 Bioessays 36: 940–949, 2014 The Authors. Bioessays published by WILEY Periodicals, Inc. Review essays
■■■口 Prospects& Overviews J. Alcock et al 116. Peterfreund GL, vandiv inha R, Ma AJ, et al. 2012. 119. Schwiertz A, Taras D, Schafer K, Beijer s, et al. 2010. and ScFA therapies for Clostridium difficile. PLoS ONE 7: 846966 117 says35:508- 118. Ley RE, Turnbaugh PJ, Klein S, Gordon JL. 2006. Microbial ecology. human gut microbes associated with obesity. Nature 444: 1022-3 Prev Res ≤oso< Bioessays 40-949, 2014 The Authors. Bioessays published by WILEY Periodicals, Inc. 949
116. Peterfreund GL, Vandivier LE, Sinha R, Marozsan AJ, et al. 2012. Succession in the gut microbiome following antibiotic and antibody therapies for Clostridium difficile. PLoS ONE 7: e46966. 117. Ettinger G, Burton JP, Reid G. 2013. If microbial ecosystem therapy can change your life, what’s the problem? BioEssays 35: 508–12. 118. Ley RE, Turnbaugh PJ, Klein S, Gordon JI. 2006. Microbial ecology: human gut microbes associated with obesity. Nature 444: 1022–3. 119. Schwiertz A, Taras D, Scha¨ fer K, Beijer S, et al. 2010. Microbiota and SCFA in lean and overweight healthy subjects. Obesity 18: 190–5. 120. Merlo LM, Shah NA, Li X, Blount PL, et al. 2010. A comprehensive survey of clonal diversity measures in Barrett’s esophagus as biomarkers of progression to esophageal adenocarcinoma. Cancer Prev Res (Phila) 3: 1388–97. ....Prospects & Overviews J. Alcock et al. Bioessays 36: 940–949, 2014 The Authors. Bioessays published by WILEY Periodicals, Inc. 949 Review essays
