Proteins: strong evidence for defence of situation-specific target intake

Proteins are crucially important for growth and most of their building blocks, the amino acids, cannot easily be synthesised by the body. Therefore, intake of protein needs to be defended similarly to salt and vitamins. A number of studies have focused on the effect of variations in dietary protein quality and quantity on food intake. The consensus of this literature is that dietary protein can have a profound impact on food intake, via two similar but potentially separate mechanisms. The first mechanism is via absolute protein content, with high-protein diets tending to suppress food intake and moderately low-protein diets increasing food intake. For instance, it is well described that protein is the most satiating macronutrient on a per energy basis, and a large number of studies suggest that high-protein diets can decrease food intake and promote weight loss while maintaining lean mass⁽ Reference Westerterp-Plantenga, Nieuwenhuizen and Tome ^{17 ,} Reference Potier, Darcel and Tome ^{18 )}. The second mechanism operates through protein quality: the amino acid profile. In particular, it seems clear that many species have the ability to rapidly detect and avoid diets that are severely imbalanced in their amino acid profile, and therefore unhealthy⁽ Reference Sanahuja and Harper ^{19 –} Reference Harper and Peters ^{21 )}. This phenomenon has been demonstrated following the depletion of multiple amino acids and appears to represent a learned aversion⁽ Reference Koehnle, Russell and Gietzen ^{22 ,} Reference Gietzen, Hao and Anthony ^{23 )}. Gietzen and co-workers have demonstrated that this learned aversion is mediated by critical molecular events within the anterior piriform cortex (APC), in particular, the accumulation of uncharged tRNA and the resulting activation of the kinase GCN2 (general control non-depressible-2)⁽ Reference Hao, Sharp and Ross-Inta ^{24 ,} Reference Rudell, Rechs and Kelman ^{25 )}. Thus, it is clear that variations in both dietary protein quantity and quality can have significant effects on food intake. It also seems likely that protein intake is regulated within general upper and lower limits to ensure a sufficient supply to support life⁽ Reference Harper and Peters ^{21 )}.

Stronger evidence that protein selection is regulated comes from work testing whether protein selection is sensitive to changes in the need or demand for protein. These data collectively demonstrate that animals will increase their selection and consumption of protein when there is an increased need for protein, e.g., following a period of protein restriction, in growing animals, and during chronic injections of growth hormone, and that this regulation occurs independently from the regulation of energy intake⁽ Reference Musten, Peace and Anderson ^{26 )}.

Perhaps the most convincing data supporting the ability of an animal to navigate through ‘nutrient space’ derives from the Geometric Framework, developed by Steven Simpson and David Raubenheimer⁽ Reference Cheng, Simpson and Raubenheimer ^{27 –} Reference Simpson and Raubenheimer ^{29 )}. Studies of macronutrient selection are impaired by the fact that an increase of one macronutrient must be offset by a decrease in a different macronutrient in order to maintain diets that are isoenergetic. The geometric approach addresses this and other concerns by using a geometric state–space model to quantify the intake of individual nutrients across a range of diets and choices. Consumption of any individual nutrient can be plotted relative to other components in the diet (e.g. protein v. carbohydrate or protein v. energy), with this analysis easily extended to the selection between multiple diets. The data suggest that species as diverse as insects, fish, rodents and pigs seek to consume a fixed amount of both protein and carbohydrate, and thus regulate intake around a specific protein:carbohydrate target⁽ Reference Simpson and Raubenheimer ²⁸ ,30–Reference Sorensen, Mayntz and Raubenheimer ^{32 )}. In addition, when faced with diets that do not allow an individual to simultaneously reach its protein and carbohydrate targets, evidence in insects and rodents indicates that protein intake is prioritised over carbohydrate intake. This effect has been termed ‘protein leveraging’, as small changes in protein content can induce profound changes in energy intake⁽ Reference Simpson and Raubenheimer ^{28 ,} Reference Simpson and Raubenheimer ^{29 ,} Reference Sorensen, Mayntz and Raubenheimer ^{32 )}. From this perspective, the hyperphagia detected on a low-protein diet is due to the leveraging in an effort to consume a target amount of protein. The concept of protein leveraging has recently been extended to human subjects, with reductions in dietary protein leading to increases in energy intake, at least over the short term⁽ Reference Simpson, Batley and Raubenheimer ^{33 ,} Reference Gosby, Conigrave and Lau ^{34 )}. Taken together, these data provide a compelling case for both the regulation of protein intake and a potential role for protein in the regulation of energy intake and obesity⁽ Reference Simpson and Raubenheimer ^{29 ,} Reference Brooks, Simpson and Raubenheimer ^{35 )}.

Carbohydrates: despite a strong basic attraction to sweets and learned avoidance if utilisation is chronically impaired, there is only weak defence of target intake

Glucose is the preferred nutrient for the brain and typically accounts for most of the energy requirements in human subjects. Furthermore, sugars are highly palatable and desired. Yet carbohydrate intake is not essential for survival per se, as energy and glucose can be derived from both fat and protein. However, a modest level of carbohydrate intake is necessary to avoid ketosis, and it seems likely that prolonged ketosis is at least undesirable. This may be the reason for animals to eat towards a carbohydrate target as determined in the geometric paradigm⁽ Reference Simpson and Raubenheimer ^{28 ,} Reference Raubenheimer and Simpson ^{31 ,} Reference Sorensen, Mayntz and Raubenheimer ^{32 ,} Reference Mayntz, Raubenheimer and Salomon ^{36 )}. However, protein takes priority over carbohydrate in this model.

Changes in food preferences when carbohydrate metabolism is impaired could also be interpreted as carbohydrate-specific regulation of intake. There is a large literature on food selection in diabetic rats⁽ Reference Bartness and Rowland ^{37 –} Reference Tordoff, Tepper and Friedman ^{42 )}, and the general consensus is that rats learn to avoid carbohydrates and instead prefer fat and protein, because of their inability to efficiently metabolise carbohydrates. Interestingly, in one report, induction of diabetes initially increased carbohydrate and protein intake, but after 3 weeks, rats switched to fat consumption⁽ Reference Kanarek and Ho ^{40 )}. This suggests an initial attempt to overcome blocked glucose utilisation by increased carbohydrate intake, before they learn to circumvent glucose utilisation as the better strategy. This interpretation is consistent with the increased carbohydrate intake after systemic 2-deoxy-glucose-induced acute blockade of glucose utilisation⁽ Reference Singer, York and Bray ^{43 )} (but see⁽ Reference Ritter, Ritter and Cromer ^{44 )} for different outcome).

There is also evidence that carbohydrate is not regulated. Although animals restricted for both energy and protein actively seek the missing nutrient, there is no evidence for carbohydrate-seeking in carbohydrate-restricted animals. Hamsters with restricted access to carbohydrate but provided with sufficient energy showed no preference for carbohydrate⁽ Reference DiBattista ^{45 )}, in contrast to a strong preference for protein following protein restriction. A similar observation was made for hypothalamic neuropeptide-Y expression, which increased in response to both protein and energy restriction, but not following the isoenergetic restriction of carbohydrate⁽ Reference White, He and Dean ^{46 )}. Taken together, the earlier data support the concept that carbohydrate is avoided if its utilisation is chronically impaired, but provide only limited support for the hypothesis that animals defend a specific intake of carbohydrate.

Fats: despite strong basic attraction to fatty foods, evidence for defence of target intake is lacking for fats in general, although it may exist for specific essential fatty acids

Fatty foods are very palatable and strongly preferred over dry foods with less creamy textures by human subjects and rodents. Most fatty acids are non-essential and thus can be synthesised by the body with the exception of α-linolenic and linoleic acids whose production requires desaturase enzymes that are lacking in many animal species including human subjects. Rats fed an n-3 fatty acid-deficient diet showed a robust preference to consume an n-3 fatty acid replete diet when given the choice over the n-3-deficient diet⁽ Reference Dunlap and Heinrichs ^{47 )}. Moreover, intake of the replete-diet progressively increased over 4 d of preference testing, indicating the contribution of post-ingestive learning. In another study, it was shown that mice with a genetic deletion of the fatty acid transporter CD36 were not able to detect and prefer another essential fatty acid, linoleic acid⁽ Reference Gaillard, Laugerette and Darcel ^{48 )}. These results provide evidence that rodents may possess a mechanism for regulating the intake of essential fatty acids just as they defend intake of thiamine.

In addition to essential fatty acids, there is some evidence for the regulation of total dietary lipids. For example, in free-living human subjects, it was found that fat intake on a given day was negatively correlated with fat intake 2 d later, suggesting some sort of delayed negative feedback regulation of fat intake⁽ Reference de Castro, Berthoud and Seeley ^{15 )}. The existence of a fat-specific appetite was suggested in studies using Pavlovian conditioning by pairing separate conditioned stimuli to either fatty or sweet food rewards acting as unconditioned stimuli. Specifically, rats treated with intracerebroventricular agouti-related protein were observed to show, in the absence of food intake, enhanced appetitive responding towards stimuli that had been previously paired with fat and reduced responding towards stimuli previously paired with sucrose⁽ Reference Tracy, Clegg and Johnson ^{49 )}. However, studies using the geometric model have consistently found a lack of support for regulation of fat intake in a number of species⁽ Reference Simpson, Raubenheimer, Berthoud and Seeley ^{14 )}. Therefore, with the exception of essential fatty acids, there is mixed evidence for physiological monitoring and precise regulation of fat intake.

When fats cannot be metabolised, the post-oral effects of ingested fat can become negative, thereby conditioning a reduction in fat intake. For example, a genetic mutation in Acads−/− mice renders them deficient in short-chain acyl-CoA dehydrogenase and therefore unable to oxidise SCFA. In a food choice situation, Acads-deficient mice shift consumption away from fat- and towards carbohydrate-containing diets, thus effectively preventing a reduction in total energies⁽ Reference Smith Richards, Belton and York ^{50 )}. This genetic model provides a tool for determining how signals from impaired SCFA oxidation are sensed and translated into feeding behaviour. The results from Acads−/− mice indicate that a deficiency in fatty acid oxidation can drive macronutrient selection and is similar to what has been reported in experimental diabetes where carbohydrate utilisation is impaired (see discussion earlier).

Several lines of evidence indicate that fat oxidation pathways are involved in the control of food intake, but whether or not these pathways regulate intake in a fat-specific manner is less clear. For example, the acute blockade of long-chain fatty acid oxidation potently stimulates food intake, and this response can be activated experimentally by using a variety of drugs that inhibit fatty acid oxidation including β-mercaptoacetate (MA). In a macronutrient choice paradigm, MA-treated rats increased their intake of protein and carbohydrate and decreased intake of fat⁽ Reference Singer, York and Bray ^{43 )}. MA-treated rats did not eat more fat, even if fat was the only macronutrient source available, thus, MA increased only the intake of nutrients that could be metabolised.

None of the earlier studies suggest a macronutrient-specific appetite because blocking oxidation of SCFA (Acads-deficient mice) or long-chain fatty acids (pharmacological antagonists) does not produce a specific need for fat. Instead, the behavioural feeding response appears to be directed at: (1) locating the diet or nutrient that can provide sufficient energy; (2) avoiding the diet/nutrient that cannot provide sufficient energy or (3) exhibiting hyperphagia in response to the only diet/nutrient available when there is no choice. One exception appears to be that MA-treated rats fail to increase their intake of fat when it is the only macronutrient source available⁽ Reference Singer, York and Bray ^{43 )}.

Protein: there are excellent sensors for individual amino acids before and after ingestion, but quantitatively measuring protein intake is a challenging task

The umami (savory) flavour is often associated with protein-rich foods, and involves principally the detection of the amino acid glutamic acid or its salt, monosodium glutamate by members of the T1R taste receptor family, specifically the T1R1/T1R3 heterodimer⁽ Reference Damak, Rong and Yasumatsu ^{54 ,} Reference Palmer ^{55 )}, with additional involvement of the olfactory system. The complexity of this system should be noted in that: (1) umami is also represented by a rather diverse set of compounds⁽ Reference Delay, Eddy and Eschle ^{56 )}, (2) the T1R1/T1R3 heterodimer appears to be capable of responding to amino acids other than glutamate⁽ Reference Nelson, Chandrashekar and Hoon ^{57 )} and (3) umami is also detected in the absence of T1R3⁽ Reference Damak, Rong and Yasumatsu ^{54 )}. Thus, there is likely more than one receptor mediating umami taste, and individual amino acids besides monosodium glutamate represent unique tastes⁽ Reference Chaudhari, Pereira and Roper ^{58 ,} Reference Maruyama, Pereira and Margolskee ^{59 )}.

Protein selection is complicated by the fact that protein is more than a single substrate and because it is unclear whether animals are selecting for sensory cues from specific amino acids or crude protein (nitrogen). Infusing protein directly into the stomach or small intestine, thereby bypassing the oral cavity, is sufficient to condition learned flavour preferences similar to fat or carbohydrate⁽ Reference Perez, Ackroff and Sclafani ^{60 –} Reference Sclafani ^{62 )}. Because attempts to produce the same effects with infusion of glucose into the hepatic portal system have been less successful, it is thought that sensors at pre-absorptive sites, or linked to the absorptive process, can detect the arrival of all three macronutrients in the gut. The same sweet, umami, fat and bitter taste receptors found in the mouth are also expressed in select enterocytes throughout the small and large intestines where they can signal to primary afferent nerves or stimulate the release of gut hormones. In addition, after being absorbed into the bloodstream, macronutrients and their metabolites can generate hormonal signals by acting on the pancreas, liver and other organs, and can act directly on the brain. Collectively, these signalling mechanisms are thought to represent the post-ingestive consequences of a specific food or macronutrient which can be learned to be liked.

Learned associations between the post-ingestive effects of protein and flavours specific to that protein source may strongly influence protein intake and selection⁽ Reference Miller and Teates ^{63 )}. For instance, DiBattista demonstrated that the strong protein preference demonstrated by protein-deprived hamsters was driven by the association of the high-protein diet with flavours associated with that diet⁽ Reference DiBattista and Mercier ^{64 )}. These data suggest that protein intake is not a specific, hard-wired appetite for protein, but instead a learned association between dietary cues and post-ingestive consequences.

Carbohydrates: while the human subjects gustatory system is largely blind to complex non-sweet carbohydrates there is abundant sensing of glucose, the major common currency of carbohydrates, in periphery and brain

The pre-ingestive detection of sugars is thought to involve both olfaction and taste⁽ Reference Zukerman, Touzani and Margolskee ^{65 ,} Reference Rhinehart-Doty, Schumm and Smith ^{66 )}. The T1R2/T1R3 heterodimer is responsible for mammalian sweet taste perception, and its location in the oral cavity mediates at least short-term preference for sugars⁽ Reference Zukerman, Touzani and Margolskee ^{65 ,} Reference Nelson, Hoon and Chandrashekar ^{67 )}. However, intragastric glucose infusions, bypassing the oral cavity, can also condition flavour preferences in rats⁽ Reference Sclafani, Glass and Margolskee ^{68 )}. Post-oral sugar conditioning could depend on sweet taste receptors or, alternatively, the Na-GLUT, expressed in specialised gut epithelial cells that release specific gut hormones to communicate with the brain. For instance, sweet taste receptors are expressed on enteroendocrine cells within the gut, providing a potential mechanism for carbohydrate to induce changes in gut hormone secretion⁽ Reference Steinert, Gerspach and Gutmann ^{69 ,} Reference Kokrashvili, Mosinger and Margolskee ^{70 )}. Whether any of these identified or yet unidentified receptor mechanisms for the detection of simple carbohydrates in the gut contributes to the regulation of carbohydrate intake or balance remains an open question.

Fats: novel lipid sensors found in mouth and gut have not yet been characterised in the brain

Historically, the orosensory perception of fat has been attributed mainly to trigeminal⁽ Reference Laugerette, Gaillard and Passilly-Degrace ^{71 )} or olfactory⁽ Reference Kinney and Antill ^{72 ,} Reference Ramirez ^{73 )} mechanisms. More recently, two lines of evidence for fat taste transduction mechanisms in taste receptor cells have been described: the delayed-rectifying K channel which is sensitive to PUFA⁽ Reference Gilbertson, Fontenot and Liu ^{74 )}, and fatty acid translocase (CD36) which is localised in lingual taste buds. In addition, the transient receptor potential type M5 was shown to be essential for fat taste in the mouse⁽ Reference Liu, Shah and Croasdell ^{75 )}, suggesting involvement of G-protein-coupled receptors, possibly GPR40 and GPR120⁽ Reference Cartoni, Yasumatsu and Ohkuri ^{76 )}. CD36 knockout mice do not prefer a fatty acid emulsion as wild-type mice do, in two bottle 48 h preference tests⁽ Reference Laugerette, Passilly-Degrace and Patris ^{77 ,} Reference Sclafani, Ackroff and Abumrad ^{78 )} but do learn to prefer a flavoured solution paired with intragastric soyabean oil infusions⁽ Reference Sclafani, Ackroff and Abumrad ^{78 )}, thus supporting a role of CD36 as a signalling protein for fat taste but not required for post-oral fat conditioning.

Based on systemic treatment with the fatty acid β-oxidation blocker mercaptoacetate, it has been proposed that mice may be able to detect fat via its oxidation products within taste receptor cells, independent of post-oral conditioning⁽ Reference Matsumura, Saitou and Miyaki ^{79 )}. Contrary to this idea is the finding that mice with genetically impaired SCFA oxidation respond normally to maize oil in 5-s lick tests, where post-ingestive learning is unlikely, but reduce responding in longer-term tests⁽ Reference Smith Richards, Belton and York ^{50 )}. However, such a mechanism needs to be verified by demonstrating a direct action of fatty acid oxidation inhibitors on taste receptor cell function.

Rats and mice do not discriminate between the oral effects of a nutritive or non-nutritive fat solution during brief presentations. However, rodents prefer a nutritive fat solution when post-oral consequences are allowed, e.g., when solutions are presented for a longer period of time to allow for post-oral consequences to occur⁽ Reference Ackroff, Vigorito and Sclafani ^{80 )}, and during gastric conditioning when an oral flavour is paired with intragastric infusions of fat solutions (thus avoiding oral effects)⁽ Reference Lucas, Ackroff and Sclafani ^{81 ,} Reference Ackroff, Lucas and Sclafani ^{82 )}. These data support the view that post-oral processes communicate the nutritional value of ingested fat solutions to the body. In gastric conditioning paradigms, fats that are high in PUFA and low in SCFA content are the most reinforcing⁽ Reference Ackroff, Lucas and Sclafani ^{82 )}, supporting the idea that oral as well as post-oral sensing helps to satisfy the evolutionary pressure to ingest sufficient amounts of the essential PUFA.

Post-oral effects of fat may involve processes in the stomach and gastrointestinal tract which could regulate the release of gut hormones (ghrelin, peptide YY and glucagon-like peptide-1), modulation of vagal afferents, absorption of nutrients into the circulation and subsequent communication with liver, pancreas or other peripheral tissues, which would then alter the release of hormones relevant to fat storage and glucose homoeostasis (e.g. leptin, insulin and glucagon). Individual nutrients affect incretin secretion⁽ Reference Wu, Rayner and Jones ^{83 )}. Enterocytes may sense TAG via fatty acid oxidation and influence eating through changes in intestinal vagal afferent activity⁽ Reference Langhans, Leitner and Arnold ^{84 )}.

Protein: individual amino acid sensing in the piriform cortex and metabolism-coupled protein effects in the hypothalamus – search for the missing link

The most straight-forward mechanism for protein detection would be a direct effect of amino acids on brain areas regulating food intake⁽ Reference Mellinkoff, Frankland and Boyle ^{96 )}, as both dietary and circulating amino acids clearly have access to the brain⁽ Reference Choi, Chang and Fletcher ^{97 ,} Reference Hawkins, O'Kane and Simpson ^{98 )}. As described previously, exposure to a diet that is devoid of an essential amino acid induces a rapid, learned aversion that requires critical signalling events within the APC⁽ Reference Hao, Sharp and Ross-Inta ^{24 ,} Reference Rudell, Rechs and Kelman ^{25 )}. Lesions of the APC block the aversive response to an imbalanced diet, as does replacement of the missing amino acid locally within the APC⁽ Reference Hao, Sharp and Ross-Inta ²⁴ ,99–Reference Leung and Rogers ^{101 )}, thus indicating the APC as a direct detector of essential amino acids. Subsequent studies indicate that a build-up of uncharged tRNA and the activation of the general control non-depressible-2 kinase are the key cellular mechanism involved. Indeed, general control non-depressible-2-deficient mice fail to exhibit the aversive response to a diet devoid of essential amino acids⁽ Reference Maurin, Jousse and Averous ^{99 )}. These studies provide a clear neuroanatomical and cellular model for the avoidance of imbalanced and thus unhealthy diets, but it is unclear whether this mechanism contributes more generally to the selection of protein.

In addition, there is strong evidence that the branched-chain amino acid (BCAA) leucine acts locally within the hypothalamus to suppress food intake⁽ Reference Blouet, Jo and Li ^{102 –} Reference Ropelle, Pauli and Fernandes ^{105 )}, at least in part via activation of mammalian target of rapamycin/S6 kinase 1, inhibition of AMP-regulated kinase signalling⁽ Reference Cota, Proulx and Smith ^{103 ,} Reference Ropelle, Pauli and Fernandes ^{105 ,} Reference Morrison, White and Wang ^{106 )}, and via activation of BCAA metabolism⁽ Reference Blouet, Jo and Li ^{102 ,} Reference Purpera, Shen and Taghavi ^{107 )}. Thus the hypothalamus is clearly capable of responding to amino acids, suggesting that BCAA may provide a unique circulating signal of dietary protein content⁽ Reference Ropelle, Pauli and Fernandes ^{105 ,} Reference Newgard, An and Bain ^{108 )}. However, anorectic leucine effects are primarily observed when it is added in excess, and whether circulating amino acids provide a specific signal of protein status remains unclear. Mice with defects in BCAA metabolism and resulting increases in circulating BCAA show normal protein intake, even when allowed to self-select between high- and low-protein diets supplemented with or without BCAA⁽ Reference Purpera, Shen and Taghavi ^{107 )}. Thus, despite the clear anorexigenic effects of pharmacological leucine doses on food intake, its role as a physiological protein signal is unclear.

The intriguing possibility that orexin and other lateral hypothalamic neurons might provide a link between the specific protein-deficient state and the motivational system has not been explored. However, both the APC⁽ Reference Blevins, Truong and Gietzen ^{109 )} and the medial hypothalamic sites responding to leucine, project directly to the lateral hypothalamus, including orexin neurons⁽ Reference Elias, Saper and Maratos-Flier ^{110 )}. Thus, protein-deficiency may engage similar neural pathways as Na deficiency⁽ Reference Liedtke, McKinley and Walker ^{9 )}.

Carbohydrate: hypothalamic glucose sensing may generate need state and drive specific appetite by engaging with mesolimbic dopamine system

As discussed earlier, the presence of carbohydrates in the diet and in the circulation are is detected by at least two distinct mechanisms, sweet taste and the metabolic effects of glucose and other simple sugars. Glucose-sensing neurons, through a mechanism involving GLUT2 and glucokinase, are either excited or inhibited by surrounding glucose (see⁽ Reference Levin, Magnan and Dunn-Meynell ^{86 )} for a recent review). If brain glucose-sensing would be critically involved in the regulation or defence of carbohydrate intake, one would expect that loss-of-function manipulation would selectively stimulate carbohydrate seeking. Unfortunately, in the majority of studies that demonstrate increased food intake induced by impairment of brain glucosensing such as insulin or 2-deoxy-d-glucose⁽ Reference Berthoud and Mogenson ^{111 )} administration and genetic deletion of glucokinase⁽ Reference Bady, Marty and Dallaporta ^{112 )}, only total food intake, but not macronutrient selection, was measured. In only one experiment, systemic administration of 2-deoxy-d-glucose induced a selective hunger for carbohydrate⁽ Reference Singer, York and Bray ^{43 )}, but it is not clear whether impaired brain glucosensing was responsible. However, third ventricular administration of insulin which, in contrast to 2-deoxy-glucose, enhances glucosensing and decreases total food intake⁽ Reference Woods, Lotter and McKay ^{113 )}, selectively reduced fat, not carbohydrate, intake in a three-choice paradigm⁽ Reference Chavez, Riedy and Van Dijk ^{114 )}. Thus, although brain glucosensing would be in an ideal position to modulate carbohydrate intake selectively, there is no direct evidence for such a mechanism.

As glucose on the tongue and carbohydrates in the gut can powerfully stimulate the mesolimbic dopamine system and condition flavour preferences⁽ Reference Lenoir, Serre and Cantin ^{115 –} Reference Sclafani, Touzani and Bodnar ^{117 )}, it will be interesting to look for a role of hypothalamic orexin neurons as potential mediators.

Fat: are fat-specific neuropeptides pharmacological artefacts or do they serve regulation of fat intake?

The possibility that essential fatty acids are detected directly in the brain, similar to amino acids⁽ Reference Gietzen, Hao and Anthony ^{23 )}, is suggested by the observation that consumption of an n-3 fatty acid deficient diet was accompanied by a decline in forebrain n-3 fatty acid content⁽ Reference Dunlap and Heinrichs ^{47 )}; however, this possibility needs to be validated by targeted repletion of the missing fatty acid in specific brain sites. In analogy to Na depletion, it would be particularly interesting to look for molecular changes in orexin and other hypothalamic neurons possibly encoding the specific need state.

Initially, there was excitement about the possibility that specific neurotransmitters and peptides drive selective intake of macronutrients, e.g. that the neuropeptides galanin and orexin stimulate lipid intake, and that norepinephrine via the α2-receptor as well as neuropeptide-Y stimulate carbohydrate intake⁽ Reference Tempel, Leibowitz and Leibowitz ^{118 ,} Reference Clegg, Air and Woods ^{119 )}. It would be interesting to test the effects of these neuropeptides with the geometric model to determine whether the observed preferences were mainly due to the specific sensory properties of the macronutrient samples rather than a defended target intake. It is clear that certain neuropeptides and transmitters change their expression levels with diets enriched with certain macronutrients. In particular, high-fat diets via elevated circulating TAG levels increase expression of galanin, enkephalin and dynorphin in paraventricular neurons, as well as orexin in lateral hypothalamic neurons. However, rather than providing negative feedback to curb further fat intake as would be expected in a regulated system, these mechanisms are apparently working in a positive feedback fashion to further enhance high-fat intake⁽ Reference Wortley, Chang and Davydova ^{120 ,} Reference Chang, Karatayev and Ahsan ^{121 )}.

A more likely mechanism that could be responsible for a homoeostatic-like negative feedback regulation of fat intake may use the same general system outlined earlier (Fig. 1). Low-fat oxidation detected in the periphery⁽ Reference Langhans, Leitner and Arnold ^{84 )} and/or directly in the brain⁽ Reference Obici, Feng and Morgan ^{122 )} may activate hypothalamic energy sensor neurons via AMP-regulated kinase phosphorylation. This would in turn lead to activation of the agouti-related protein system and possibly fat-specific molecular changes in orexin and other lateral hypothalamic neurons as demonstrated for Na deficiency⁽ Reference Liedtke, McKinley and Walker ^{9 )}. In support of such molecular changes, our preliminary observations suggest that mice with genetic deletion of the ability to oxidise SCFA show elevated hypothalamic AMP-regulated kinase expression on high-fat diet compared with wild-type mice (BK Richards, unpublished results).