Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-18T20:18:50.799Z Has data issue: false hasContentIssue false

Understanding the interplay between food structure, intestinal bacterial fermentation and appetite control

Published online by Cambridge University Press:  08 May 2020

A. Dagbasi*
Affiliation:
Department of Medicine, Section for Nutrition Research, Imperial College London, Hammersmith Hospital, London, UK
A. M. Lett
Affiliation:
Department of Medicine, Section for Nutrition Research, Imperial College London, Hammersmith Hospital, London, UK
K. Murphy
Affiliation:
Department of Medicine, Section of Endocrinology and Investigative Medicine, Imperial College London, Hammersmith Hospital, London, UK
G. Frost
Affiliation:
Department of Medicine, Section for Nutrition Research, Imperial College London, Hammersmith Hospital, London, UK
*
*Corresponding author: A. Dagbasi, email [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Epidemiological and clinical evidence highlight the benefit of dietary fibre consumption on body weight. This benefit is partly attributed to the interaction of dietary fibre with the gut microbiota. Dietary fibre possesses a complex food structure which resists digestion in the upper gut and therefore reaches the distal gut where it becomes available for bacterial fermentation. This process yields SCFA which stimulate the release of appetite-suppressing hormones glucagon-like peptide-1 and peptide YY. Food structures can further enhance the delivery of fermentable substrates to the distal gut by protecting the intracellular nutrients during upper gastrointestinal digestion. Domestic and industrial processing can disturb these food structures that act like barriers towards digestive enzymes. This leads to more digestible products that are better absorbed in the upper gut. As a result, less resistant material (fibre) and intracellular nutrients may reach the distal gut, thus reducing substrates for bacterial fermentation and its subsequent benefits on the host metabolism including appetite suppression. Understanding this link is essential for the design of diets and food products that can promote appetite suppression and act as a successful strategy towards obesity management. This article reviews the current evidence in the interplay between food structure, bacterial fermentation and appetite control.

Type
Conference on ‘Malnutrition in an Obese World: European Perspectives’
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © The Authors 2020. Published by Cambridge University Press on behalf of The Nutrition Society

The global obesity epidemic is presenting a major risk to global health. Currently, more than 1⋅9 billion adults are estimated to be obese or overweight(1). It is projected that the prevalence of obesity will double in the next 30 years, further increasing the burden of this epidemic. Obesity is associated with an increased risk of developing a range of chronic diseases such as CVD, type 2 diabetes and certain cancers(Reference Peeters, Barendregt and Willekens2). The UK National Health Service spends £6⋅1 billion on obesity-related ill-health every year, which is predicted to reach £9⋅7 billion by 2050(3). Nevertheless, an effective, non-invasive obesity treatment is yet to be found.

Current dietary and lifestyle interventions fail to provide clinically significant (5–10 %) and sustained weight loss (minimum of 1 year)(Reference Hassan, Head and Jacob4Reference Franz, VanWormer and Crain12). The most effective weight loss strategy remains as bariatric surgery, which is an invasive procedure that may lead to undesirable side effects such as dumping syndrome and nutritional deficiencies(Reference Douketis, Macie and Thabane8, Reference Sjöström, Narbro and Sjöström13, Reference Ma and Madura14). The most commonly performed bariatric surgeries are Roux-en-Y gastric bypass, vertical sleeve gastrectomy and gastric banding which achieve 32, 25 and 20 % weight loss 1–2 years post-surgery, respectively(Reference Sjöström, Narbro and Sjöström13).

The aetiology of obesity is multifactorial and relies on the complex interaction of genetic, behavioural and environmental factors(Reference Selassie and Sinha15). This makes the identification of treatment options challenging. In principle, obesity is the result of a chronic imbalance between energy intake and energy expenditure(Reference Romieu, Dossus and Barquera16). The human body is equipped with an intricate homeostatic mechanism that works to balance energy intake and expenditure and maintain body weight(Reference Keesey and Powley17). Nevertheless, even a small but sustained positive energy balance may lead to weight gain. Using data from national surveys, Hill et al. estimated that a positive energy balance of 418·4 kJ (100 kcal)/d may be the cause of slow weight gain (0⋅5–1 kg/year) and development of obesity in US adults over recent decades(Reference Hill, Wyatt and Reed18). One factor proposed to contribute to this energy imbalance is the drastic change in diets, characterised by the increased consumption of processed foods and reduced consumption of dietary fibre(Reference Mozaffarian, Hao and Rimm19). Over past decades, diets have rapidly evolved to accommodate ‘fast foods’ or processed foods that have now become the hallmarks of western diets(Reference Kearney20, Reference Rahat-Rozenbloom, Fernandes and Gloor21). Such foods are typically energy dense and low in fibre. Accordingly, only 9 % of UK adults are estimated to meet the recommended fibre intake of 30 g/d (average intake 19 g/d)(22).

Fibre is a plant-based dietary component found in fruit, vegetables, legumes and whole grains(Reference Dhingra, Michael and Rajput23). Epidemiological studies highlight that individuals consuming high-fibre diets have lower body weights(Reference Newby, Maras and Bakun24Reference Du, van der and Boshuizen27). This is suggested to be partly the result of an interaction between dietary fibre and the resident gut microbiota. The human gut is host to a rich, diverse and complex community of microorganisms(Reference Sender, Fuchs and Milo28). The number of gut microbes increases along the gut, with the colon having the largest population. The gut microbiota has been shown to impact its host's metabolism and confer several benefits to its host. One example is a result of its interaction with dietary fibre. Owing to its complex food structure, fibre resists digestion in the upper gut and reaches the bacteria-rich distal gut where it becomes available for bacterial fermentation(Reference Robertson, Bickerton and Dennis29). Products of bacterial fermentation have been shown to interact with the homeostatic mechanisms controlling energy metabolism. In relation to energy intake, these interactions can result in appetite suppression and reduced food intake(Reference Chambers, Viardot and Psichas30). This means that high-fibre diets may be more appetite suppressing, which may partly explain the epidemiological observations. Conversely, industrial processing of foods typically disturbs the food structures that act as barriers to digestive enzymes and results in more digestible products that are better absorbed in the upper gut. As a result, less food may reach the distal gut, thus lowering fermentation and the subsequent appetite suppression(Reference Edwards, Grundy and Grassby31Reference Grassby, Mandalari and Grundy37). This means that, despite being more energy dense, these foods may be less appetite suppressing.

Processed foods are major components of modern diets. Understanding the relationship between food structures and appetite control may facilitate the design of foods and dietary regimens that promote appetite suppression and reduce food intake. This may provide new tools to reverse the small but sustained positive energy balance that is proposed to lead weight gain. This report reviews our current understanding of the links between food structure, the gut microbiota, with a focus on bacterial fermentation and appetite suppression.

Appetite regulation

The gastrointestinal (GI) tract is the body's largest endocrine organ and the largest interface between the human body and the external environment(Reference Ahlman and Nilsson38). This external environment includes foods and the products of digestion, and the GI tract is thus one of the key players in the body's regulation of appetite(Reference Cummings and Overduin39). The surface of the GI tract provides the means for detecting luminal nutrients and generates endocrine and neuronal signals to inform the body of their presence(Reference Helander and Fändriks40). Ultimately, these signals are transmitted to the central nervous system where they are integrated to orchestrate the short-term feelings of hunger and satiety.

Central regulation of appetite

The hypothalamus is regarded as the main ‘appetite centre’ in the central nervous system(Reference Ahima and Antwi41). Several hypothalamic regions have been shown to play a role in appetite regulation, but in particular, the arcuate nucleus (ARC) has been highlighted as important(Reference Timper and Brüning42). The ARC is strategically located near a region of the brain with an incomplete blood–brain barrier(Reference Yin and Gore43). This enables ARC to sense and integrate hormonal and metabolic signals from the peripheral circulation with the neuronal inputs from the central nervous system and periphery. The ARC contains two functionally opposing types of neurones involved in the regulation of energy balance: anorexigenic pro-opiomelanocortin (POMC) neurones and orexigenic neuropeptide Y (NPY)/agouti-related peptide (AgRP) neurones(Reference Schwartz, Woods and Porte44). Both types of neurones project to second-order neurones in other parts of hypothalamus and in extra-hypothalamic brain regions(Reference Timper and Brüning42).

Following food intake, the POMC neurones are activated(Reference Millington45). Activation of these neurones indicates the ‘fed state’ and leads to a decrease in appetite and an increase in energy expenditure(Reference Schwartz, Woods and Porte44). Conversely, the ‘fasting state’ activates orexigenic NPY/AgRP neurones(Reference Aponte, Atasoy and Sternson46). These neurons co-release NPY and AgRP which stimulate hunger and reduce energy expenditure(Reference Betley, Cao and Ritola47). Acute pharmacological activation of NPY/AgRP neurones dramatically increases energy intake in mice(Reference Krashes, Koda and Ye48). In addition, NPY/AgRP neurones directly inhibit the activity of POMC neurons in ARC through the release of inhibitory neurotransmitter γ-aminobutyric acid (Fig. 1)(Reference Cowley, Smart and Rubinstein49). The deletion of vesicular γ-aminobutyric acid transporter genes in the AgRP/NPY neurones results in a lean and obesity-resistant mouse, highlighting the physiological importance of this pathway(Reference Tong, Ye and Jones50).

Fig. 1. (Colour online) Central regulation of appetite. Activation of pro-opiomelanocortin (POMC) neurones reduces appetite. Activation of neuropeptide Y/agouiti-related peptide (NPY/AgRP) neurones increases appetite. NPY/AgRP neurones directly inhibit the activity of POMC neurones through the release of inhibitory neurotransmitter γ-aminobutyric acid (GABA). Both neurones project to other brain regions. Vagus nerve carries signals from the periphery to the brain. ARC, arcuate nucleus; NTC, nucleus of the solitary tract.

Neuronal signals from the GI tract are transmitted to the brain via the vagus nerve. The nucleus of the solitary tract in the brainstem receives vagal afferent signals and transmits these to downstream brain regions, including the hypothalamus(Reference ter Horst, Luiten and Kuipers51). The importance of the vagus nerve has been highlighted by studies demonstrating that surgical transection of vagus nerve increases food intake and feeding duration in rodents(Reference Phillips and Powley52, Reference Schwartz53).

Peripheral control of appetite

Following food ingestion, signals are generated to increase the efficiency of digestion and reduce subsequent feeding and meal size. The entry of food in the GI tract (stomach and proximal small intestine) causes distention which stimulates mechanoreceptors(Reference Delzenne, Blundell and Brouns54). Activation of these receptors generates neuronal signals that act to slow gastric motility, allowing more time for digestion and creating a feeling of fullness(Reference Browning, Verheijden and Boeckxstaens55). In addition to this, upper GI-hormones such as cholecystokinin are released in response to the presence of food. Together, these signals are thought to provide the initial, short-lived appetite suppression.

More sustained appetite suppression is believed to be brought about by the actions of other gut hormones. The two major anorexigenic hormones implicated in appetite regulation are peptide YY (PYY) and glucagon-like peptide-1 (GLP-1)(Reference De Silva and Bloom56). Both hormones are secreted from the intestinal enteroendocrine L-cells, which express the necessary molecular machinery to sense luminal nutrients and other digestive secretions such as bile acids(Reference Spreckley and Murphy57). The density of L-cells increases along the GI tract, with the highest numbers found in the colon. In response to the detection of nutrients and other digestive factors, L-cells release GLP-1 and PYY(Reference Degen, Oesch and Casanova58, Reference Orskov, Rabenhoj and Wettergren59). All three macronutrients, their by-products and other digestive factors such as bile acids have been shown to stimulate the release of both hormones(Reference Steinert, Feinle-Bisset and Asarian60).

PYY is a peptide hormone from the pancreatic polypeptide family. There are two biologically active forms of PYY in the human body(Reference Ballantyne61). PYY (1-36) is released from L-cells and cleaved by dipeptidyl peptidase IV to form PYY (3-36). Anorectic effects of PYY (3-36) are believed to be mediated by the Y2 receptor, which is found throughout the central nervous system, including the ARC, as well as on vagal neurones(Reference Batterham, Cowley and Small62, Reference Koda, Date and Murakami63). Binding of PYY to the Y2 receptors on NPY/AgRP neurones was shown to prevent their orexigenic activity and their inhibitory effects on POMC neurones, increasing anorexigenic activity(Reference Batterham, Cowley and Small62). Increased levels of PYY decrease appetite, delay gastric emptying and reduce GI motility, contributing to the ‘ileal brake’(Reference Batterham, Cowley and Small62, Reference Batterham, Cohen and Ellis64Reference Batterham, ffytche and Rosenthal66). Following a meal, a rise in PYY concentrations can be observed within 15 min. Given that the L-cells are mainly located in the distal gut, this early phase release is believed to be the result of neuronal stimulation or perhaps another hormone acting on L-cells, rather than reflecting the effects of direct contact of nutrients with the L-cells(Reference Suzuki, Iwasaki and Murata67). A second phase or peak of PYY is usually observed about 90 min following food intake, which is likely driven by the arrival of nutrients to the distal gut and their direct effects on L-cells(Reference Adrian, Ferri and Bacarese-Hamilton68).

GLP-1 is a peptide hormone that is also produced by intestinal L-cells, and by a population of neurones in the nucleus of the solitary tract of the brain stem. The nucleus of the solitary tract neurones are believed to be the primary source of GLP-1 in the brain, and have been shown to receive direct input from vagal afferents(Reference Holt, Richards and Cook69, Reference Hisadome, Reimann and Gribble70). The peripheral release of GLP-1 follows a similar biphasic pattern to PYY. Carbohydrate absorption in the proximal gut and other neuronal inputs are believed to contribute to its initial rise(Reference Smeets, Soenen and Luscombe-Marsh71). GLP-1 acts as an incretin hormone through binding GLP-1 receptors on pancreatic β-cells to stimulate glucose-induced insulin release(Reference Holst, Orskov and Nielsen72). GLP-1 analogues such as Exenatide and Liraglutide have been approved as diabetes treatments since 2005 and 2010, respectively(Reference Neumiller73, Reference Gupta74). GLP-1 also slows gastric emptying, inhibits glucagon secretion and suppresses appetite(Reference Tang-Christensen, Vrang and Larsen75, Reference Kreymann, Williams and Ghatei76). GLP-1 receptors are found on the vagus nerve and in the brain including the ARC(Reference Müller, Finan and Bloom77). GLP-1 infusion in the hepatic portal vein has not been shown to change the activity of POMC or NPY/AgRP neurones, suggesting intestinal GLP-1 may not directly act on the ARC but rely on vagal afferent activation to modulate the central control of appetite(Reference Müller, Finan and Bloom77, Reference Baumgartner, Pacheco-López and Rüttimann78). The pathways by which GLP-1 and PYY work to modulate the central control of appetite are still unclear.

Obese individuals have been reported to have a blunted postprandial secretion or lower fasting levels of PYY and GLP-1(Reference le Roux, Batterham and Aylwin65, Reference Carr, Larsen and Jelic79Reference Zwirska-Korczala, Konturek and Sodowski82), which may contribute to weight gain. Bariatric surgery has also been shown to increase the postprandial release of PYY and GLP-1(Reference Svane, Jorgensen and Bojsen-Moller83). This is believed to contribute to the dramatic weight loss observed following surgery(Reference Hutch and Sandoval84). As a result, peripheral administration of GLP-1 and/or PYY has been suggested as a way to correct the low levels observed in obese individuals to encourage weight reduction, or to mimic the weight loss effects of surgery. Indeed, peripheral administration of PYY and GLP-1 has been shown to suppress appetite and reduce food intake in both rodents and lean and obese human subjects(Reference Batterham, Cowley and Small62, Reference Batterham, Cohen and Ellis64, Reference Tan, Behary and Tharakan85, Reference Verdich, Flint and Gutzwiller86). The chronic administration of these hormones also resulted in weight loss in animal and human models(Reference Batterham, Cowley and Small62, Reference Behary, Tharakan and Alexiadou87Reference Vilsbøll, Christensen and Junker89). GLP-1 analogue Liraglutide has been approved as a weight loss treatment in patients without diabetes since 2015(Reference Dar, Tahrani and Piya90). These highlight that GLP-1 and PYY are key regulators of appetite regulation and that their manipulation may have an effect on energy intake and body weight.

Bacterial fermentation and energy metabolism

The human GI tract harbours a rich and dynamic community of microorganisms (gut microbiota) living in a symbiotic manner. Gut microbiota relies on hosts' dietary intake as an energy source to grow and multiply. The main source of energy for microbiota is a dietary fibre which becomes available for bacterial fermentation in the distal gut. The complex interplay between dietary fibre, gut microbiota and microbial-produced metabolites has an impact on hosts' energy metabolism. In relation to specific energy intake, these interactions can result in appetite suppression and reduced food intake, reducing the risk of excess energy intake and weight gain(Reference Chambers, Viardot and Psichas30).

Dietary fibre and bacterial fermentation

Dietary fibre is an umbrella term for the group of carbohydrates that cannot be digested by the endogenous enzymes in the human body. There are several definitions of dietary fibre proposed by different countries and organisations(91). The most recent, and one of the most detailed, definitions has been made by the Australia New Zealand Food Authority(92): Dietary fibre is that fraction of the edible part of plants or their extracts, or synthetic analogues, that are resistant to digestion and absorption in the human small intestine, usually with complete or partial fermentation in the large intestine. Dietary fibre promotes one or more of these beneficial physiological effects: laxation, reduction in blood cholesterol, and/or modulation of blood glucose. The term includes polysaccharides, oligosaccharides (degrees of polymerization >2), and lignin.

Epidemiological studies have repeatedly identified that high-fibre diets are associated with lower body weight(Reference Newby, Maras and Bakun24Reference Du, van der and Boshuizen27). This inverse relationship can also be observed for weight gain(Reference Koh-Banerjee, Franz and Sampson93), visceral adiposity(Reference Davis, Alexander and Ventura94), cardiometabolic diseases(Reference Ludwig, Pereira and Kroenke26), type 2 diabetes(95) and colorectal cancer(Reference Murphy, Norat and Ferrari96). Clinical trials with animals and human subjects have investigated the causal role of fibre in these effects. Animal studies find supplementation with dietary fibre reduces energy intake and protects against weight gain(Reference Arora, Loo and Anastasovska97Reference Delzenne, Cani and Daubioul100). A meta-analysis of twelve randomised controlled trials identified a reduction in body weight of obese/overweight human subjects when their diets were supplemented with soluble fibre(Reference Thompson, Hannon and An101).

Dietary fibre has been proposed to exert its benefits on host metabolism partly through its interaction with the gut microbiota. As previously stated, dietary fibres resist digestion in the human gut and reach the distal gut. The number of bacteria increases along the gut, with colon having the highest numbers. Thus in the distal gut, bacteria is at a capacity to see marked bacterial fermentation of dietary fibre. This process yields energy for bacterial growth along with gases and the side products called SCFA. The most abundant SCFA are acetate (C2), propionate (C3) and butyrate (C4), which are present in the colon in the approximate ratio of 3:1:1 although this ratio depends on the amount and type of dietary fibre and the composition of gut microbiota(Reference Cummings, Pomare and Branch102). While SCFA are waste by-products for the microbiota, for the host, their production represents the extraction of energy from the undigested material that would otherwise be wasted in the stool. Species that consume plant-rich, high-fibre diets such as gorillas (75–80 g/d) rely on this system as their main energy source(Reference Popovich, Jenkins and Kendall103). In the western world human subjects, SCFA are estimated to contribute 2–10 % of daily energy intake(Reference Bergman104). In the large intestine, most of the SCFA (mainly butyrate) are rapidly absorbed and used as an energy substrate by the colonocytes. The remaining SCFA reach the liver via hepatic portal vein where they are used as substrates for gluconeogenesis or metabolised through other pathways(Reference den Besten, Lange and Havinga105). Only a small proportion of SCFA enter the peripheral circulation. A study quantified systemic availability of colonic acetate, propionate and butyrate as 36, 9 and 2 %, respectively(Reference Boets, Gomand and Deroover106).

SCFA and appetite regulation

In the human body, SCFA are more than merely a source of energy. SCFA have been shown to act as signalling molecules through their interactions with the NEFA receptors 2 and 3 (FFAR2 and FFAR3). Acetate and propionate activate FFAR2, whereas FFAR3 can also be activated by butyrate(Reference Brown, Goldsworthy and Barnes107Reference Nilsson, Kotarsky and Owman109). FFAR are expressed in key areas involved in the regulation of energy metabolism, including the gut, adipose tissue and skeletal muscle(Reference Brown, Goldsworthy and Barnes107, Reference Alia, Aaron and Gary110, Reference Li, Su and Zhou111).

In the gut, the FFAR are expressed in GLP-1 and PYY secreting L-cells. This discovery led to the suggestion that SCFA could stimulate the release of appetite-suppressing hormones which could explain the mechanism by which fibre influences body weight. Indeed, studies using rodent and human cell lines confirmed SCFA acted on FFAR on L-cells to stimulate the release of GLP-1 and PYY(Reference Chambers, Viardot and Psichas30, Reference Psichas, Sleeth and Murphy112, Reference Karaki, Mitsui and Hayashi113). This finding was further strengthened by FFAR2 and/or FFAR3 knock-out rodent models which showed attenuated GLP-1 and PYY secretions in response to intra-colonic propionate infusions(Reference Psichas, Sleeth and Murphy112, Reference Tolhurst, Heffron and Lam114, Reference Lin, Frassetto and Kowalik115). Dietary supplementation with fermentable carbohydrates or SCFA increased the circulating concentrations of PYY and GLP-1 in animal models and activated neurones in hypothalamic regions involved in appetite regulation(Reference Cani, Neyrinck and Maton98, Reference Tolhurst, Heffron and Lam114, Reference Anastasovska, Arora and Sanchez Canon116Reference Reimer, Maurer and Eller118).

SCFA and energy intake

Despite the well-established link between SCFA and anorectic gut hormone release, the effect of SCFA on energy intake has been inconsistent. Several studies investigated the effect of supplementing rodent diets with SCFA on energy intake and found no effect(Reference den Besten, Bleeker and Gerding119Reference Henagan, Stefanska and Fang122). One study supplemented high-fat diets with acetate, butyrate or propionate and showed a significant reduction in energy intake of mice following butyrate and propionate supplementations (22 and 9 %, respectively)(Reference Lin, Frassetto and Kowalik115). However, studies using oral supplementation of SCFA should be interpreted with care as the bitter taste of these supplements may cause food aversion. In another study, intragastric gavage of butyrate was found to significantly reduce food intake of mice(Reference Li, Yi and Katiraei123). Frost et al. also demonstrated that intraperitoneal administration of acetate acutely reduced food intake for 2 h although colonic administrations showed no effect(Reference Frost, Sleeth and Sahuri-Arisoylu124).

Oral SCFA failed to show an effect on food intake in human subjects(Reference Darzi, Frost and Robertson125). This may be due to SCFA being quickly absorbed in the upper gut, and thus not reaching the distal gut where they are proposed to interact with the L-cells to drive anorectic hormone release. Our research group has used inulin-propionate ester for the targeted delivery of propionate to the distal gut. In a randomised controlled study, 7 d supplementation with the inulin-propionate resulted in a reduction in ad libitum energy intake(Reference Polyviou, MacDougall and Chambers126). In another study, consumption of 10 g inulin-propionate ester reduced ad libitum food intake and increased plasma GLP-1 and PYY concentrations compared to an inulin control(Reference Chambers, Viardot and Psichas30). These results suggest that not oral but targeted colonic administration of SCFA may reduce food consumption in human subjects.

SCFA and body weight

Animal studies indicated a beneficial effect of SCFA on body weight. Studies with rodents highlighted that colonic infusions, intragastric gavage and oral supplementation of SCFA attenuated high-fat diet-induced weight gain(Reference den Besten, Lange and Havinga105, Reference Gao, Yin and Zhang120Reference Li, Yi and Katiraei123, Reference Zhou, Pan and Xin127Reference Hong, Jia and Pan129). Lu et al. supplemented high-fat diets with acetate, propionate, butyrate or a mixture of all three SCFA, and fed these to mice for 16 weeks. All SCFA significantly attenuated high-fat diet-induced weight gain, with acetate having the largest effect (72 % less weight gain)(Reference Lu, Fan and Li128). In one study, germ-free mice received faecal transplants from obese and lean human subjects which resulted in the development of a similar phenotype in the recipient mice(Reference Ridaura, Faith and Rey130). The lean mice had significantly higher caecal levels of propionate and butyrate, suggesting a potential benefit of SCFA in mediating the observed difference in body weight(Reference Ridaura, Faith and Rey130). Similar results were observed following faecal transplantation between mice that undergone Roux-en-Y gastric bypass and germ-free mice(Reference Liou, Paziuk and Luevano131). However, other studies have found weight gain following acetate supplementation(Reference Perry, Peng and Barry132, Reference Sahuri-Arisoylu, Brody and Parkinson133). In addition, studies using FFAR2/3 knock out animal models reported inconsistent outcomes on body weight(Reference Lin, Frassetto and Kowalik115, Reference Samuel, Shaito and Motoike134).

Only one human study has investigated the link with SCFA and body weight. Long-term (24 weeks) supplementation of inulin-propionate ester was shown to significantly reduce body weight gain in overweight participants compared to the inulin control as part of a habitual diet(Reference Chambers, Viardot and Psichas30). Only 4 % of participants in the inulin-propionate group gained significant weight (>3 % body weight) compared to 25 % in the control group.

Overall, these data highlight that SCFA stimulate the release of appetite-suppressing hormones. In human subjects, increasing colonic levels of SCFA may reduce food intake and protect against weight gain. Manipulating the colonic levels of SCFA is also possible through dietary modification since increasing fibre consumption has been shown to increase SCFA production. However, in addition to the fibre content, gut microbial composition can have a strong impact on SCFA production.

Gut microbiota composition and its effect on fermentation

Gut microbiota is a combined community of several types of microorganisms, including viruses, yeast and bacteria, with the latter being the most heavily researched and the most abundant(Reference Rinninella, Raoul and Cintoni135). This is why the gut microbiota is sometimes referred to as the gut bacteria. The human gut microbiota is dominated by six bacterial phyla: Bacteroidetes, Firmicutes, Proteobacteria, Verrucomicrobia, Fusobacteria and Actinobacteria, with the Bacteroidetes and Firmicutes making up about 90 % of the whole community(Reference Arumugam, Raes and Pelletier136, Reference Qin, Li and Raes137). Although the complete repertoire of the gut microbiota remains unrevealed, more than 500 species are estimated to reside in the GI tract(Reference Almeida, Mitchell and Boland138). The composition of the gut microbiota dictates its overall metabolism and functional capabilities including SCFA production. Indeed, the gut microbial composition has been shown to lead variations in SCFA productions(Reference Rahat-Rozenbloom, Fernandes and Gloor21, Reference Aguirre, Bussolo de Souza and Venema139Reference Venkataraman, Sieber and Schmidt142). However, it should be noted that this area of research mainly relies on in vitro models or stool SCFA measurements due to a lack of studies directly measuring luminal SCFA production in healthy human subjects.

Many bacterial species are capable of producing acetate whereas propionate and butyrate productions are more conserved and substrate-dependent. Butyrate producers are mainly from the Firmicutes phylum(Reference Qin, Li and Raes137, Reference Barcenilla, Pryde and Martin143, Reference Louis, Young and Holtrop144). Faecalibacterium prausnitzii, Eubacterium rectale and Eubacterium hallii are primary butyrate-producing species in the human gut(Reference Barcenilla, Pryde and Martin143, Reference Louis, Young and Holtrop144). Resistant starch fermentation is believed to contribute to butyrate production by generating intermediate products that are fermentable by butyrate producers. Ruminococcus bromii (Firmicutes) and Bifidobacterium (Actinobacteria) are regarded as the main resistant starch-degrading bacteria(Reference Rossi, Corradini and Amaretti145Reference Belenguer, Duncan and Calder147). Individuals with higher R. bromii abundance have been shown to produce more total SCFA and butyrate(Reference Baxter, Schmidt and Venkataraman140, Reference Venkataraman, Sieber and Schmidt142, Reference Ze, Duncan and Louis146). Similarly, it has been shown that individuals with a higher Firmicutes abundance have a greater SCFA production capacity marked by increased acetate and butyrate productions(Reference Rahat-Rozenbloom, Fernandes and Gloor21, Reference Aguirre, Bussolo de Souza and Venema139, Reference Venkataraman, Sieber and Schmidt142, Reference Turnbaugh, Ley and Mahowald148).

Although shared by a number of phyla, Bacteroidetes dominates the propionate producers(Reference Qin, Li and Raes137, Reference Louis, Young and Holtrop144, Reference Reichardt, Duncan and Young149). In line with this, one study showed a positive correlation between faecal propionate concentrations and the abundance of Bacteroidetes (Reference Salonen, Lahti and Salojärvi141). Other species such as Akkermansia muciniphila and the phylum Firmicutes (mainly class Negativicutes) have also been associated with propionate production(Reference Reichardt, Duncan and Young149, Reference Derrien, Vaughan and Plugge150). In particular, A. muciniphila has been identified as a key propionate producer and drew attention as a potential probiotic due to its negative correlations with diabetes and obesity(Reference Derrien, Vaughan and Plugge150Reference Hansen, Krych and Nielsen153). Bacteroidetes mainly produce propionate from the fermentation of polysaccharides although they are also able to ferment peptides(Reference Louis, Young and Holtrop144). Accordingly, diets high in protein and lower in fibre have been associated with an increase in Bacteroidetes, reflecting a switch from carbohydrate to protein fermentation(Reference Aguirre, Eck and Koenen154, Reference David, Maurice and Carmody155).

Although relatively stable during adulthood, gut microbiota is susceptible to changes by dietary intake, which can in turn affect SCFA production. In diet switching studies, it was elegantly shown that the composition of the gut microbiota and the magnitude of bacterial fermentation can be altered using high- and low-fibre diets(Reference Robertson, Bickerton and Dennis29, Reference David, Maurice and Carmody155, Reference O'Keefe, Li and Lahti156). High-fibre diets increase SCFA production and increase gut microbiota diversity(Reference David, Maurice and Carmody155, Reference Brinkworth, Noakes and Clifton157Reference Wu, Chen and Hoffmann161). Unsurprisingly these diets also stimulate the growth of carbohydrate fermenting bacterial species from the Firmicutes phylum(Reference David, Maurice and Carmody155, Reference Duncan, Belenguer and Holtrop158, Reference Reichardt, Vollmer and Holtrop162, Reference Walker, Ince and Duncan163). Diets high in resistant starch were found to stimulate the growth of R. bromii and Bifidobacterium (Reference Salonen, Lahti and Salojärvi141, Reference Brinkworth, Noakes and Clifton157, Reference Hald, Schioldan and Moore159, Reference Reichardt, Vollmer and Holtrop162Reference Leitch, Walker and Duncan165). Conversely, western-style low-fibre, high-protein/fat diets lowered bacterial fermentation, reduced bacterial diversity and increased the numbers of Bacteroidetes (Reference Aguirre, Eck and Koenen154, Reference David, Maurice and Carmody155, Reference Wu, Chen and Hoffmann161, Reference Sonnenburg, Smits and Tikhonov166).

These studies highlight that diet and gut microbiota act together to impact SCFA production, and thus the subsequent effects of SCFA in the human body, including energy intake and body weight. Differences have been observed between the gut microbial composition of lean and obese subjects, highlighting the potential impact of gut microbiota on body weight(Reference Ley, Backhed and Turnbaugh167Reference Schwiertz, Taras and Schäfer169). In addition, bariatric surgery has been shown to modulate gut microbial composition which is proposed to contribute to the weight loss following surgery(Reference Zhang, DiBaise and Zuccolo170, Reference Furet, Kong and Tap171). However, this topic is beyond the scope of the present paper and reviewed in detail elsewhere(Reference Castaner, Goday and Park172, Reference Ulker and Yildiran173).

Food structure

Nutritional research has largely considered the effect of food and diets on human health based on the chemical compositions of foods (i.e. macronutrients and energy). However, this approach alone is insufficient as demonstrated by the variability in metabolic response to foods with the same energy and macronutrient profiles. Beyond macronutrient composition, food structure is fundamental for dictating the food behaviour, and thus how it is digested and processed within the GI tract. This in turn can impact on postprandial response and metabolism, such as microbial fermentation and appetite control.

Food structure and digestion

Food structure relates to the assembly of molecules making up food which can be a result of natural formation, domestic processing (cooking, blending, etc.), industrial processing or a combination. There are different levels of food structures which can impact digestion and subsequent postprandial metabolism. As previously mentioned, the main substrate for microbial fermentation is carbohydrate. Therefore, this review will focus on carbohydrate structures.

Molecular level: starch

Starch is a glucose polymer, and the main form of carbohydrate storage within plants. The glucose units can be linked with α-1,4 glycosidic bonds to form straight helical chains called amylose(Reference Berg, Tymoczko and Stryer174). Alternatively, the glucose units can be linked with a combination of α-1,4 and α-1,6 glycosidic bonds to form branched polymers called amylopectin. The proportion of these starch configurations differs between different plants and starch types(Reference Fishman, Cooke and White175). In general, starchy foods such as barley, rice, wheat would contain 20–30 % amylose and 70–80 % amylopectin(Reference Svihus, Uhlen and Harstad176). Amylose is a straight chain, and thus with less surface area available for enzymatic actions, its digestion is slower compared to the highly branched amylopectin(Reference Lovegrove, Edwards and De Noni177). In vitro digestion studies have demonstrated this eloquently, for example, the digestion rate of different rice grains being shown to increase with the increasing ratio of amylose to amylopectin(Reference Syahariza, Sar and Hasjim178). In clinical human studies, high amylose starch supplementation resulted in attenuated postprandial glucose and insulin responses compared to high amylopectin starch, indicative of slower digestion from the former(Reference Behall and Howe179, Reference Behall, Scholfield and Yuhaniak180).

At greater length scale, amylose and amylopectin chains are further assembled into granules consisting of a ratio of highly organised, dense pseudo-crystalline regions and less organised amorphous structures(Reference Mishra, Hardacre and Monro181). The pseudo-crystalline regions are abundant in raw vegetables such as potatoes and unripe bananas and they are more resistant to digestion by α-amylase resulting in slower and sometimes incomplete digestion. In a study that investigated the in vitro digestion of potato, pea, maize, rice, barley and wheat starches, the digestion rate was found to decrease with the increasing amount of crystalline structures(Reference Martens, Gerrits and Bruininx182).

Food cellular structure

At its most basic, food cellular structures include animal, fungal and plant cells. Unlike animal cells, plant cells have cell walls providing structural support and shielding intracellular nutrients(Reference Brett and Waldron183). These cell walls are made up of indigestible carbohydrates (i.e. fibres) such as cellulose, hemicellulose, pectin and non-carbohydrates such as lignin, proteins and water(Reference Burton, Gidley and Fincher184). The relative proportion of these building blocks differs based on the type, function and maturity of plant tissue, which in turn dictates the permeability and strength of the cell wall and the digestive fate of these foods(Reference Padayachee, Day and Howell185). For example, high amounts of cell wall lignin relate to the string-like structure of asparagus reducing the permeability of cell wall and thus hindering digestive enzyme access and nutrient bioaccessibility(Reference Harris and Smith186).

Bioaccessibility is defined as the proportion of consumed nutrients available for absorption in the human gut. Food cellular structures have been shown to impact bioaccessibility(Reference Parada and Aguilera187). Digestive enzymes need direct contact with the nutrients inside the cellular structures to be able to digest them. Endogenous enzymes in the human body are unable to digest plant cell walls (i.e. fibre), and therefore enzymes can only act to break down macronutrients within plant cells if they diffuse through the cell walls or if the cell walls are ruptured as part of the digestion process. As a result, plants with strong and less permeable cell walls may undergo more attenuated and incomplete digestion within the GI tract which results in a slower and lower nutrient release. In vitro digestion studies have shown slower hydrolysis of cellular starch compared to extracellular starch(Reference Edwards, Grundy and Grassby31), and in applied food examples, kidney bean and chickpea cells, which have remained intact following cooking, have resulted in a slower and incomplete in vitro digestion(Reference Mishra, Hardacre and Monro181). In vivo, human studies demonstrated an attenuated postprandial glycaemia and lipidaemia following the consumption of foods with intact cellular structures compared to macronutrient and energy-matched foods with disrupted structures, indicating a slower nutrient release from the former(Reference Edwards, Grundy and Grassby31, Reference Berry, Tydeman and Lewis188Reference Jenkins, Wesson and Wolever190). In some cases, intact cells may protect cellular starch from digestion both of which reach the distal gut. Ileal samples from healthy human subjects were found to contain intact cells with cellular starch molecules, indicating that these cells escaped digestion in the upper gut(Reference Noah, Guillon and Bouchet191). Food cellular structures are further organised into tissues at greater length scales, which further dictates their digestive behaviour.

Mechanical processing in human body

During digestion, food structures are altered due to mechanical stress, actions of digestive enzymes and physicochemical conditions of the GI tract such as pH(Reference Grundy, Edwards and Mackie192). Oral processing (chewing) is the first stage of digestion and reduces the particle size of food, thus increasing the surface area for enzymatic digestion. This process changes the food matrices by separating tissues, and on a cellular level separating and/or rupturing cell wall surfaces. Depending on cell wall structure and conformation, such structures have different strengths of intracellular adherence and tendencies to rupture or separate under mechanical stress(Reference Swackhamer and Bornhorst193). For example, high pectin levels in the cell walls usually indicate greater potential for cell separation. Under digestion, the cells of nuts, raw hard vegetables and seeds have a greater tendency to rupture, whereas cells of cooked foods such as legumes tend to separate and remain intact(Reference Grundy, Grassby and Mandalari194, Reference Grundy, Carrière and Mackie195). This means that most legume cells remain intact following chewing, the result of which can provide one possible mechanism to explain their attenuated postprandial glycaemic response, due to lower enzymatic exposure to intracellular starch. Conversely, ruptured cell walls provide greater enzymatic exposure to intracellular starch (Fig. 2). Studies where foods have been swallowed without oral processing have demonstrated such, through reduced postprandial glycaemia, indicating a slower nutrient release due to the protection of cell walls(Reference Read, Welch and Austen196).

Fig. 2. (Colour online) The digestion of (a) intact and (b) disrupted food structures. (a) Digestive enzymes in the body have limited access to the intracellular nutrients, hindered by intact food structures and cell walls. (b) Digestive enzymes have access to acellular nutrients released from ruptured/disrupted cellular structures. Separated cells remain intact and limit enzyme access to intracellular nutrients.

Mechanical digestion continues in the stomach and small intestine where the digesta is constantly mixed by peristaltic gut movements. Plant foods with strong food structures can endure the contractions created by the GI tract and reach the distal gut relatively undigested. One study using intubation technique to collect samples from the distal ileum of healthy volunteers found ileal digesta contained intact bean cells encapsulating starch molecules, indicating that these cells were resistant to digestion in the upper GI tract(Reference Noah, Guillon and Bouchet191). Another study with healthy ileostomy patients demonstrated intact carrot cells containing intracellular nutrients in the ileal effluents(Reference Tydeman, Parker and Faulks197). Such findings, further highlighting intact cellular structures with encapsulated nutrients reaching the distal ileum, have been repeatedly confirmed within ileostomy patients(Reference Edwards, Grundy and Grassby31, Reference Mandalari, Faulks and Rich198Reference Birkett, Mathers and Jones200). Theoretically, the greater the protective effect of food structure, the greater is the amount of fermentable substrates delivered to the distal gut for fermentation. This may be indicating the beneficial role of food structure in stimulating appetite suppression through the proposed mechanisms within this review.

Industrial and domestic processing

Food processing has been shown to change food structures, typically leading to more digestible products. Thermal treatment in the presence of water (boiling) has been shown to cause gelatinisation of starch(Reference Olkku and Rha201). Gelatinisation results in the loss of intermolecular bonds and pseudo crystalline structures, resulting in a more digestible compound. For example, raw potato starch or raw oats eaten as muesli are almost completely indigestible to human subjects. Upon cooking, the starch in these foods gelatinises and can be easily digested, marked by a higher postprandial glycaemia(Reference Mishra, Hardacre and Monro181). However, if the gelatinised starch is left to cool down, the dissociated starch molecules randomly re-crystallise in a disorganised manner (retrograding). This generates compounds more resistant to digestion (resistant starch). In a study with healthy ileostomy patients, cooked potatoes resulted in 3 % starch losses in the ileal effluents whereas cooked and cooled potatoes resulted in 12 %(Reference Englyst and Cummings202).

Beyond starch structures, processing has been shown to alter cell walls, typically leading to more permeable, weak or ruptured structures(Reference Edwards, Grundy and Grassby31Reference Grassby, Mandalari and Grundy37). For example, the fine milling process has been shown to rupture cell walls(Reference Edwards, Grundy and Grassby31, Reference Moelants, Cardinaels and Van Buggenhout203). Others such as homogenisation, canning and cooking were shown to denature cell walls leading to rupture or weakening(Reference Padayachee, Day and Howell185). As previously explained, without the hindrance of rigid, impermeable cell walls, digestive enzymes can easily access the intracellular nutrients and hydrolyse them into absorbable molecules. Weak cell walls may also be more susceptible to rupture under mechanical digestion in the GI tract. This can lead to more digestible and bioaccessible food products(Reference Parada and Aguilera187). Singh and coworkers reviewed the effect of different types of food processing on starch digestibility and found an increase in digestibility with processing(Reference Lin, Frassetto and Kowalik115). In another study, in vitro digestion of whole and finely milled almonds resulted in higher energy extraction from the milled almonds(Reference Mandalari, Faulks and Rich198). This was supported by microscopic analysis of almonds finding ruptured almond cells following the milling process while the whole almonds contained intact cells with encapsulated nutrients. Another in vitro digestion study estimated that only 5⋅5 % of lipids were released from whole almonds compared to 42 % from almond starch(Reference Grassby, Picout and Mandalari204). These results were repeated in a healthy ileostomy patient who digested 96⋅5 % of lipids from milled almonds compared to only 56⋅5 % from whole almonds(Reference Grassby, Mandalari and Grundy37). Increased nutrient availability of processed foods has been demonstrated by other studies using cooked, pasteurised and milled products(Reference Edwards, Grundy and Grassby31Reference Langkilde, Champ and Andersson36).

More efficient digestion and absorption in the upper gut translates into lower levels of nutrients reaching the distal gut. In a study with healthy ileostomy patients, Livesey et al. demonstrated that the starch losses in the ileal effluents decreased 3-fold following the consumption of finely milled barley compared to coarse barley(Reference Livesey, Wilkinson and Roe199). An analysis of the ileal effluents found that the lost nutrients were still encapsulated within the intact cellular structures. Langkilde et al. repeated this finding in an experiment where ileostomy patients were fed cooked and raw banana starch(Reference Langkilde, Champ and Andersson36). Raw banana starch consumption resulted in more than three times higher amounts of starch losses in the ileal effluents (6⋅3 (sd 0⋅4) v. 21⋅4 (sd 0⋅6)). Intact cellular structures with encapsulated nutrients were found in the ileal effluents of raw banana starch group. This indicated that the observed differences in both of these studies could be due to more nutrients being absorbed from the disrupted structures of processed foods while the intact cellular structures protected the nutrients in the raw diets.

Two studies showed contradictory results. Edwards et al. fed coarse and finely milled porridge to healthy ileostomy patients and found no difference in the starch losses in the ileal effluents(Reference Edwards, Grundy and Grassby31). This was explained by the finding of intact but empty cellular structures in the effluents following the consumption of coarse oats. Combined with the in vitro findings, this indicated that the cell walls were permeable to digestive enzymes although they were resistant to digestion. Another study found no difference between the ileal effluents following cooked and raw carrot consumption(Reference Tydeman, Parker and Faulks197). This was explained by the failure of cooking to disrupt cellular structures and highlighted that not all food processing results in the disruption of cellular structures.

Food structure, microbial fermentation and appetite control

It is well established that food structures dictate the digestive fate of consumed nutrients(Reference Grundy, Edwards and Mackie192). It is therefore unsurprising that food structures can also influence appetite control. Foods with rigid structures may require a longer chewing time while others may be consumed rapidly. Accordingly, diets high in plant matter (fibre) have been shown to reduce eating rate(Reference Louis, Young and Holtrop144). A slow eating rate prolongs the oral exposure of food which transmits orosensory satiety signals to the brain, resulting in a prolonged appetite suppression(Reference Rossi, Corradini and Amaretti145). The importance of this is demonstrated by the attenuated appetite suppression observed following direct infusion of foods into the stomach or duodenum(Reference Ze, Duncan and Louis146, Reference Belenguer, Duncan and Calder147). Li et al. also demonstrated that increasing oral exposure of food (15 v. 40 chews) resulted in higher postprandial GLP-1 concentrations and reduced ad libitum energy intake in obese and lean subjects(Reference Turnbaugh, Ley and Mahowald148). In another study, eating at a slower rate increased the postprandial GLP-1 and PYY levels(Reference Reichardt, Duncan and Young149). Food structure was also found to impact gastric emptying which contributes to appetite suppression. In a randomised cross-over study, Mackie and coworkers demonstrated slower gastric emptying following the consumption of semi-solid meals compared to liquid(Reference Derrien, Vaughan and Plugge150).

As previously described, food structures can alter the amount of nutrients reaching the distal gut which can impact bacterial fermentation (Fig. 3). While cell walls are indigestible by human enzymes, they are susceptible to bacterial enzymes and fermentation, producing SCFA(Reference Reichardt, Vollmer and Holtrop162). The composition of the plant cell wall is a major determinant of bacterial fermentation since different fibres have different fermentation capacities. Complex, insoluble fibres such as cellulose and hemicellulose are fermented slowly and poorly by the gut bacteria whereas soluble fibres such as pectin and β-glucan are highly fermentable(Reference Reichardt, Vollmer and Holtrop162, Reference Holscher205). Bacterial degradation of plant cell walls may also expose the intracellular starch that also acts as an efficient substrate for bacterial fermentation. However, as previously mentioned, gut microbiota composition is also a determinant of SCFA production. The presence of certain microbial groups may enhance the fermentation of complex structures such as resistant starches(Reference Rossi, Corradini and Amaretti145Reference Belenguer, Duncan and Calder147).

Fig. 3. The interplay between food structures, digestion, microbial fermentation and appetite regulation. Intact cellular structures arrive large intestine where they become available for bacterial fermentation. This process yields SCFA that stimulate the release of peptide YY (PYY) and glucagon-like peptide 1 (GLP-1) from intestinal L-cells. PYY and GLP-1 signal to the brain to reduce appetite.

In one study, ileal effluents with higher fibre and starch losses were found to result in higher in vitro SCFA production(Reference Silvester, Englyst and Cummings206). This study highlights that the amount of nutrients reaching the distal gut is a determinant of microbial fermentation. In a previously mentioned study, ileal effluents were collected from healthy ileostomy patients following the consumption of raw or cooked banana starch(Reference Langkilde, Champ and Andersson36). The in vitro fermentation of the effluents resulted in significantly higher SCFA production following the inoculation of raw banana effluents which contained higher amounts of fibre and starch. In another study, the effect of food processing was investigated using native and finely milled whole grains(Reference Hernot, Boileau and Bauer207). It was found that processing reduced the resistant starch components of foods which in turn reduced their in vitro SCFA production. These studies highlighted that macronutrient, fibre and energy-matched foods can lead to different microbial fermentation due to a difference in food structure brought by food processing with more ‘resistant’ food structures resulting in greater SCFA production (Fig. 3). In addition, it highlighted that cooking and milling (processing) can reduce the amount of fibre/starch reaching the distal gut and reduce bacterial fermentation through increasing digestibility. This can in return reduce appetite suppression.

These findings indicate that generally, processed foods could be less satiating compared to raw, unprocessed alternatives. Evidence from cross-sectional studies suggests that high consumption of highly processed foods is associated with excess body weight(Reference Juul, Martinez-Steele and Parekh208Reference Canella, Levy and Martins213). One study found an inverse correlation between the degree of processing and the satiety index of ninety-eight commonly consumed foods(Reference Fardet214). Another study used subjective measures of appetite and demonstrated higher satiety following the consumption of raw carrots compared to cooked carrots(Reference Gustafsson, Asp and Hagander215). In a randomised cross-over trial, Mori et al. demonstrated that whole almonds reduced ad libitum food intake in healthy volunteers more than energy, macronutrient and fibre-matched almond butter(Reference Mori, Considine and Mattes216). The authors commented that this difference may be due to increased orosensory time and reduced gastric emptying. In another study, it was shown that supplementation with native banana starch, which has been previously shown to carry intact cellular structures to the distal gut(Reference Langkilde, Champ and Andersson36), reduced ad libitum food intake compared to supplementation with available banana starch indicative of appetite suppression(Reference Ble-Castillo, Juarez-Rojop and Tovilla-Zarate217). In a recently published randomised cross-over study, Hall et al. fed participants energy, macronutrient and fibre-matched ultra-processed (as per NOVA classification) and unprocessed diets for 14 d(Reference Hall, Ayuketah and Brychta218). Ad libitum energy intake was found to be about 2092 kJ (500 kcal)/d greater in the ultra-processed diet group. This translated into participants' body weight and fat mass increase in the ultra-processed diet group. Fasting PYY levels were also found to be significantly higher in the unprocessed diet group. Furthermore, the eating rate was also significantly lower in this group.

However, evidence in this area remains inconclusive and limited. There are still no studies investigating the causal link between food structures, bacterial fermentation and appetite suppression directly, with current hypothesis being based on the mechanistic link proposed in this review.

Conclusion

Current evidence highlights the beneficial effects of dietary fibre intake on energy metabolism. This benefit is partly mediated by the interaction of fibre with the gut microbiota which produces SCFA. These bacterial metabolites have been shown to stimulate the release of appetite-suppressing hormones GLP-1 and PYY. The limited evidence in human subjects highlights that increasing colonic levels of SCFA may reduce food intake and protect against weight gain. Processing can alter food structures, typically reducing the amount of fibre reaching the distal gut and thus reducing substrates for bacterial fermentation and its subsequent benefits on the host metabolism including appetite suppression. Observational studies show an association between high processed food consumption and higher body weight. One randomised controlled trial in human subjects demonstrated a higher ad libitum energy intake from processed foods compared to unprocessed foods which resulted in weight gain over 2 weeks. However, scientific evidence linking food structure, bacterial fermentation and appetite control is scarce. The small amount of available evidence is mostly dependent on ileostomy studies which do not reflect the conditions of an intact gut. More studies in healthy human subjects are needed to grow understanding in this area.

Acknowledgement

I would like to acknowledge the support and help of my colleagues and supervisors at Imperial College London for me to compete at the FENS postgraduate competition and write this review article.

Financial Support

This article presents a review on a topic that is researched by our team. This work is funded by UK Biotechnology & Biological Sciences Research Council (BBSRC) (BB/N016847/1) and Nestec Ltd and supported by the NIHR CRF and BRC at Imperial College Healthcare NHS Trust. The views expressed are those of the authors and not necessarily those of our funders, the NHS, the NIHR or the Department of Health. The Section of Endocrinology and Investigative Medicine is funded by grants from the MRC, BBSRC, NIHR, an Integrative Mammalian Biology (IMB) Capacity Building Award, an FP7-HEALTH-2009-241592 EuroCHIP grant and is supported by the NIHR Biomedical Research Centre Funding Scheme. G. F. holds an NIHR Senior Investigator Award.

Conflict of Interest

None.

Authorship

The authors had joint responsibility for all aspects of preparation of this paper.

References

World Health Organization (2016). Obesity and overweight – fact sheet at World Health Organisation Media Centre 2016. Available from: http://www.who.int/mediacentre/factsheets/fs311/en/ (accessed November 2019).Google Scholar
Peeters, A, Barendregt, JJ, Willekens, F et al. (2003) Obesity in adulthood and its consequences for life expectancy: a life-table analysis. Ann Intern Med 138, 2432.CrossRefGoogle ScholarPubMed
Hassan, Y, Head, V, Jacob, D et al. (2016) Lifestyle interventions for weight loss in adults with severe obesity: a systematic review. Clin Obes 6, 395403.CrossRefGoogle ScholarPubMed
Wing, RR & Phelan, S (2005) Long-term weight loss maintenance. Am J Clin Nutr 82, 222S225S.CrossRefGoogle ScholarPubMed
Wing, RR, Lang, W, Wadden, TA et al. (2011) Benefits of modest weight loss in improving cardiovascular risk factors in overweight and obese individuals with type 2 diabetes. Diabetes Care 34, 14811486.CrossRefGoogle ScholarPubMed
Cleo, G, Beller, E, Glasziou, P et al. (2019) Efficacy of habit-based weight loss interventions: a systematic review and meta-analysis. J Behav Med [Epublication ahead of print version].Google ScholarPubMed
Douketis, JD, Macie, C, Thabane, L et al. (2005) Systematic review of long-term weight loss studies in obese adults: clinical significance and applicability to clinical practice. Int J Obes 29, 11531167.CrossRefGoogle ScholarPubMed
Jospe, MR, Roy, M, Brown, RC et al. (2019) Intermittent fasting, Paleolithic, or Mediterranean diets in the real world: exploratory secondary analyses of a weight-loss trial that included choice of diet and exercise. Am J Clin Nutr 111, 503514.CrossRefGoogle Scholar
Obert, J, Pearlman, M, Obert, L et al. (2017) Popular weight loss strategies: a review of four weight loss techniques. Curr Gastroenterol Rep 19, 61.CrossRefGoogle ScholarPubMed
Abete, I, Parra, MD, Zulet, MA et al. (2006) Different dietary strategies for weight loss in obesity: role of energy and macronutrient content. Nutr Res Rev 19, 517.CrossRefGoogle ScholarPubMed
Franz, MJ, VanWormer, JJ, Crain, AL et al. (2007) Weight-loss outcomes: a systematic review and meta-analysis of weight-loss clinical trials with a minimum 1-year follow-up. J Am Diet Assoc 107, 17551767.CrossRefGoogle ScholarPubMed
Sjöström, L, Narbro, K, Sjöström, CD et al. (2007) Effects of bariatric surgery on mortality in Swedish obese subjects. N Engl J Med 357, 741752.CrossRefGoogle ScholarPubMed
Ma, IT & Madura, JA II (2015) Gastrointestinal complications after bariatric surgery. Gastroenterol Hepatol 11, 526535.Google ScholarPubMed
Selassie, M & Sinha, AC (2011) The epidemiology and aetiology of obesity: a global challenge. Best Pract Res Clin Anaesthesiol 25, 19.CrossRefGoogle ScholarPubMed
Romieu, I, Dossus, L, Barquera, S et al. (2017) Energy balance and obesity: what are the main drivers? Cancer Causes 28, 247258.CrossRefGoogle ScholarPubMed
Keesey, RE & Powley, TL (2008) Body energy homeostasis. Appetite 51, 442445.CrossRefGoogle ScholarPubMed
Hill, JO, Wyatt, HR, Reed, GW et al. (2003) Obesity and the environment: where do we go from here? Science 299, 853855.CrossRefGoogle Scholar
Mozaffarian, D, Hao, T, Rimm, EB et al. (2011) Changes in diet and lifestyle and long-term weight gain in women and men. N Engl J Med 364, 23922404.CrossRefGoogle ScholarPubMed
Kearney, J (2010) Food consumption trends and drivers. Philos Trans R Soc Lond B Biol Sci 365, 27932807.CrossRefGoogle ScholarPubMed
Rahat-Rozenbloom, S, Fernandes, J, Gloor, GB et al. (2014) Evidence for greater production of colonic short-chain fatty acids in overweight than lean humans. Int J Obes 38, 15251531.CrossRefGoogle ScholarPubMed
Public Health England (2018) National Diet and Nutrition Survey, Results from Years 7 and 8 (combined) of the Rolling Programme (2014/2015 to 2015/2016). Available at: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/699241/NDNS_results_years_7_and_8.pdf (accessed January 2020).Google Scholar
Dhingra, D, Michael, M, Rajput, H et al. (2012) Dietary fibre in foods: a review. J Food Sci Technol 49, 255266.CrossRefGoogle ScholarPubMed
Newby, PK, Maras, J, Bakun, P et al. (2007) Intake of whole grains, refined grains, and cereal fiber measured with 7-d diet records and associations with risk factors for chronic disease. Am J Clin Nutr 86, 17451753.CrossRefGoogle ScholarPubMed
Liu, S, Willett, WC, Manson, JE et al. (2003) Relation between changes in intakes of dietary fiber and grain products and changes in weight and development of obesity among middle-aged women. Am J Clin Nutr 78, 920927.CrossRefGoogle ScholarPubMed
Ludwig, DS, Pereira, MA, Kroenke, CH et al. (1999) Dietary fiber, weight gain, and cardiovascular disease risk factors in young adults. JAMA 282, 15391546.CrossRefGoogle ScholarPubMed
Du, H, van der, AD, Boshuizen, HC et al. (2010) Dietary fiber and subsequent changes in body weight and waist circumference in European men and women. Am J Clin Nutr 91, 329336.CrossRefGoogle ScholarPubMed
Sender, R, Fuchs, S & Milo, R (2016) Revised estimates for the number of human and bacteria cells in the body. PLoS Biol 14, e1002533–e.CrossRefGoogle ScholarPubMed
Robertson, MD, Bickerton, AS, Dennis, AL et al. (2005) Insulin-sensitizing effects of dietary resistant starch and effects on skeletal muscle and adipose tissue metabolism. Am J Clin Nutr 82, 559567.CrossRefGoogle ScholarPubMed
Chambers, ES, Viardot, A, Psichas, A et al. (2015) Effects of targeted delivery of propionate to the human colon on appetite regulation, body weight maintenance and adiposity in overweight adults. Gut 64, 1744.CrossRefGoogle ScholarPubMed
Edwards, CH, Grundy, MM, Grassby, T et al. (2015) Manipulation of starch bioaccessibility in wheat endosperm to regulate starch digestion, postprandial glycemia, insulinemia, and gut hormone responses: a randomized controlled trial in healthy ileostomy participants. Am J Clin Nutr 102, 791800.CrossRefGoogle ScholarPubMed
Würsch, P, Del Vedovo, S & Koellreutter, B (1986) Cell structure and starch nature as key determinants of the digestion rate of starch in legume. Am J Clin Nutr 43, 2529.CrossRefGoogle ScholarPubMed
Golay, A, Coulston, AM, Hollenbeck, CB et al. (1986) Comparison of metabolic effects of white beans processed into two different physical forms. Diabetes Care 9, 260266.CrossRefGoogle ScholarPubMed
Stinco, CM, Fernandez-Vazquez, R, Escudero-Gilete, ML et al. (2012) Effect of orange juice's processing on the color, particle size, and bioaccessibility of carotenoids. J Agr Food Chem 60, 14471455.CrossRefGoogle ScholarPubMed
Berg, T, Singh, J, Hardacre, A et al. (2012) The role of cotyledon cell structure during in vitro digestion of starch in navy beans. Carbohydr Polym 87, 16781688.CrossRefGoogle Scholar
Langkilde, AM, Champ, M & Andersson, H (2002) Effects of high-resistant-starch banana flour (RS(2)) on in vitro fermentation and the small-bowel excretion of energy, nutrients, and sterols: an ileostomy study. Am J Clin Nutr 75, 104111.CrossRefGoogle Scholar
Grassby, T, Mandalari, G, Grundy, MM et al. (2017) In vitro and in vivo modeling of lipid bioaccessibility and digestion from almond muffins: the importance of the cell-wall barrier mechanism. J Func Foods 37, 263271.CrossRefGoogle ScholarPubMed
Ahlman, H & Nilsson, (2001) The gut as the largest endocrine organ in the body. Ann Oncol 12 Suppl 2, S63S68.CrossRefGoogle Scholar
Cummings, DE & Overduin, J (2007) Gastrointestinal regulation of food intake. J Clin Invest 117, 1323.CrossRefGoogle ScholarPubMed
Helander, HF & Fändriks, L (2014) Surface area of the digestive tract – revisited. Scand J Gastroenterol 49, 681689.CrossRefGoogle ScholarPubMed
Ahima, RS & Antwi, DA (2008) Brain regulation of appetite and satiety. Endocrinol Metab Clin North Am 37, 811823.CrossRefGoogle ScholarPubMed
Timper, K & Brüning, JC (2017) Hypothalamic circuits regulating appetite and energy homeostasis: pathways to obesity. Dis Model Mech 10, 679689.CrossRefGoogle ScholarPubMed
Yin, W & Gore, AC (2010) The hypothalamic median eminence and its role in reproductive aging. Ann N Y Acad Sci 1204, 113122.CrossRefGoogle ScholarPubMed
Schwartz, MW, Woods, SC, Porte, D Jr et al. (2000) Central nervous system control of food intake. Nature 404, 661671.CrossRefGoogle ScholarPubMed
Millington, GWM (2007) The role of proopiomelanocortin (POMC) neurones in feeding behaviour. Nutr Metab 4, 18.CrossRefGoogle ScholarPubMed
Aponte, Y, Atasoy, D & Sternson, SM (2011) AGRP Neurons are sufficient to orchestrate feeding behavior rapidly and without training. Nat Neurosci 14, 351355.CrossRefGoogle ScholarPubMed
Betley, JN, Cao, ZF, Ritola, KD et al. (2013) Parallel, redundant circuit organization for homeostatic control of feeding behavior. Cell 155, 13371350.CrossRefGoogle ScholarPubMed
Krashes, MJ, Koda, S, Ye, C et al. (2011) Rapid, reversible activation of AgRP neurons drives feeding behavior in mice. J Clin Invest 121, 14241428.CrossRefGoogle ScholarPubMed
Cowley, MA, Smart, JL, Rubinstein, M et al. (2001) Leptin activates anorexigenic POMC neurons through a neural network in the arcuate nucleus. Nature 411, 480484.CrossRefGoogle ScholarPubMed
Tong, Q, Ye, CP, Jones, JE et al. (2008) Synaptic release of GABA by AgRP neurons is required for normal regulation of energy balance. Nat Neurosci 11, 9981000.CrossRefGoogle ScholarPubMed
ter Horst, GJ, Luiten, PG & Kuipers, F (1984) Descending pathways from hypothalamus to dorsal motor vagus and ambiguus nuclei in the rat. J Auton Nerv Syst 11, 5975.CrossRefGoogle ScholarPubMed
Phillips, RJ & Powley, TL (1998) Gastric volume detection after selective vagotomies in rats. Am J Physiol 274, R1626R1R38.Google ScholarPubMed
Schwartz, GJ (2000) The role of gastrointestinal vagal afferents in the control of food intake: current prospects. Nutrition 16, 866873.CrossRefGoogle ScholarPubMed
Delzenne, N, Blundell, J, Brouns, F et al. (2010) Gastrointestinal targets of appetite regulation in humans. Obes Rev 11, 234250.CrossRefGoogle ScholarPubMed
Browning, KN, Verheijden, S & Boeckxstaens, GE (2017) The vagus nerve in appetite regulation, mood, and intestinal inflammation. Gastroenterology 152, 730744.CrossRefGoogle ScholarPubMed
De Silva, A & Bloom, SR (2012) Gut hormones and appetite control: a focus on PYY and GLP-1 as therapeutic targets in obesity. Gut Liver 6, 1020.CrossRefGoogle ScholarPubMed
Spreckley, E & Murphy, KG (2015) The L-cell in nutritional sensing and the regulation of appetite. Front Nutr 2, 23–.CrossRefGoogle ScholarPubMed
Degen, L, Oesch, S, Casanova, M et al. (2005) Effect of peptide YY3-36 on food intake in humans. Gastroenterology 129, 14301436.CrossRefGoogle ScholarPubMed
Orskov, C, Rabenhoj, L, Wettergren, A et al. (1994) Tissue and plasma concentrations of amidated and glycine-extended glucagon-like peptide I in humans. Diabetes 43, 535539.CrossRefGoogle ScholarPubMed
Steinert, RE, Feinle-Bisset, C, Asarian, L et al. (2017) Ghrelin, CCK, GLP-1, and PYY(3-36): secretory controls and physiological roles in eating and glycemia in health, obesity, and after RYGB. Physiol Rev 97, 411463.CrossRefGoogle ScholarPubMed
Ballantyne, GH (2006) Peptide YY(1-36) and peptide YY(3-36): part I. Distribution, release and actions. Obs Surg 16, 651658.CrossRefGoogle ScholarPubMed
Batterham, RL, Cowley, MA, Small, CJ et al. (2002) Gut hormone PYY(3-36) physiologically inhibits food intake. Nature 418, 650654.CrossRefGoogle ScholarPubMed
Koda, S, Date, Y, Murakami, N et al. (2005) The role of the vagal nerve in peripheral PYY3-36-induced feeding reduction in rats. Endocrinology 146, 23692375.CrossRefGoogle ScholarPubMed
Batterham, RL, Cohen, MA, Ellis, SM et al. (2003) Inhibition of food intake in obese subjects by peptide YY3-36. N Engl J Med 349, 941948.CrossRefGoogle ScholarPubMed
le Roux, CW, Batterham, RL, Aylwin, SJB et al. (2006) Attenuated peptide YY release in obese subjects is associated with reduced satiety. Endocrinology 147, 38.CrossRefGoogle ScholarPubMed
Batterham, RL, ffytche, DH, Rosenthal, JM et al. (2007) PYY Modulation of cortical and hypothalamic brain areas predicts feeding behaviour in humans. Nature 450, 106109.CrossRefGoogle ScholarPubMed
Suzuki, K, Iwasaki, K, Murata, Y et al. (2018) Distribution and hormonal characterization of primary murine L cells throughout the gastrointestinal tract. J Diabetes Investig 9, 2532.CrossRefGoogle ScholarPubMed
Adrian, TE, Ferri, GL, Bacarese-Hamilton, AJ et al. (1985) Human distribution and release of a putative new gut hormone, peptide YY. Gastroenterology 89, 10701077.CrossRefGoogle ScholarPubMed
Holt, MK, Richards, JE, Cook, DR et al. (2019) Preproglucagon neurons in the nucleus of the solitary tract are the main source of brain GLP-1, mediate stress-induced hypophagia, and limit unusually large intakes of food. Diabetes 68, 2133.CrossRefGoogle ScholarPubMed
Hisadome, K, Reimann, F, Gribble, FM et al. (2010) Leptin directly depolarizes preproglucagon neurons in the nucleus tractus solitarius. Diabetes 59, 18901898.CrossRefGoogle ScholarPubMed
Smeets, AJ, Soenen, S, Luscombe-Marsh, ND et al. (2008) Energy expenditure, satiety, and plasma ghrelin, glucagon-like peptide 1, and peptide tyrosine-tyrosine concentrations following a single high-protein lunch. J Nutr 138, 698702.CrossRefGoogle ScholarPubMed
Holst, JJ, Orskov, C, Nielsen, OV et al. (1987) Truncated glucagon-like peptide I, an insulin-releasing hormone from the distal gut. FEBS Lett 211, 169174.CrossRefGoogle ScholarPubMed
Neumiller, JJ (2009) Differential chemistry (structure), mechanism of action, and pharmacology of GLP-1 receptor agonists and DPP-4 inhibitors. J Am Pharm Assoc 49(5, Suppl 1), S16S29.CrossRefGoogle Scholar
Gupta, V (2013) Glucagon-like peptide-1 analogues: an overview. Indian J Endocrinol Metab 17, 413421.CrossRefGoogle ScholarPubMed
Tang-Christensen, M, Vrang, N & Larsen, PJ (1998) Glucagon-like peptide 1(7-36) amide's central inhibition of feeding and peripheral inhibition of drinking are abolished by neonatal monosodium glutamate treatment. Diabetes 47, 530537.CrossRefGoogle ScholarPubMed
Kreymann, B, Williams, G, Ghatei, MA et al. (1987) Glucagon-like peptide-1 7-36: a physiological incretin in man. Lancet (London. England) 2, 13001304.CrossRefGoogle ScholarPubMed
Müller, TD, Finan, B, Bloom, SR et al. (2019) Glucagon-like peptide 1 (GLP-1). Mol Metab 30, 72130.CrossRefGoogle Scholar
Baumgartner, I, Pacheco-López, G, Rüttimann, EB et al. (2010) Hepatic-portal vein infusions of glucagon-like peptide-1 reduce meal size and increase c-Fos expression in the nucleus tractus solitarii, area postrema and central nucleus of the amygdala in rats. J Neuroendocrinol 22, 557563.CrossRefGoogle ScholarPubMed
Carr, RD, Larsen, MO, Jelic, K et al. (2010) Secretion and dipeptidyl peptidase-4-mediated metabolism of incretin hormones after a mixed meal or glucose ingestion in obese compared to lean, nondiabetic men. J Clin Endocrinol Metab 95, 872878.CrossRefGoogle ScholarPubMed
Lugari, R, Dei Cas, A, Ugolotti, D et al. (2004) Glucagon-like peptide 1 (GLP-1) secretion and plasma dipeptidyl peptidase IV (DPP-IV) activity in morbidly obese patients undergoing biliopancreatic diversion. Horm Metab Res 36, 111115.Google ScholarPubMed
Adam, TCM & Westerterp-Plantenga, MS (2005) Glucagon-like peptide-1 release and satiety after a nutrient challenge in normal-weight and obese subjects. Br J Nutr 93, 845851.CrossRefGoogle ScholarPubMed
Zwirska-Korczala, K, Konturek, SJ, Sodowski, M et al. (2007) Basal and postprandial plasma levels of PYY, ghrelin, cholecystokinin, gastrin and insulin in women with moderate and morbid obesity and metabolic syndrome. J Physiol Pharmacol 58 Suppl 1, 1335.Google ScholarPubMed
Svane, MS, Jorgensen, NB, Bojsen-Moller, KN et al. (2016) Peptide YY and glucagon-like peptide-1 contribute to decreased food intake after Roux-en-Y gastric bypass surgery. Int J Obes (2005) 40, 16991706.CrossRefGoogle ScholarPubMed
Hutch, CR & Sandoval, D (2017) The role of GLP-1 in the metabolic success of bariatric surgery. Endocrinology 158, 41394151.CrossRefGoogle ScholarPubMed
Tan, T, Behary, P, Tharakan, G et al. (2017) The effect of a subcutaneous infusion of GLP-1, OXM, and PYY on energy intake and expenditure in obese volunteers. J Clin Endocrinol Metab 102, 23642372.CrossRefGoogle ScholarPubMed
Verdich, C, Flint, A, Gutzwiller, JP et al. (2001) A meta-analysis of the effect of glucagon-like peptide-1 (7-36) amide on ad libitum energy intake in humans. J Clin Endocrinol Metab 86, 43824389.Google ScholarPubMed
Behary, P, Tharakan, G, Alexiadou, K et al. (2019) Combined GLP-1, oxyntomodulin, and peptide YY improves body weight and glycemia in obesity and prediabetes/type 2 diabetes: a randomized, single-blinded, placebo-controlled study. Diabetes Care 42, 14461453.CrossRefGoogle ScholarPubMed
Zander, M, Madsbad, S, Madsen, JL et al. (2002) Effect of 6-week course of glucagon-like peptide 1 on glycaemic control, insulin sensitivity, and beta-cell function in type 2 diabetes: a parallel-group study. Lancet (London, England) 359, 824830.CrossRefGoogle ScholarPubMed
Vilsbøll, T, Christensen, M, Junker, AE et al. (2012) Effects of glucagon-like peptide-1 receptor agonists on weight loss: systematic review and meta-analyses of randomised controlled trials. Br Med J 344, d7771–d.CrossRefGoogle ScholarPubMed
Dar, S, Tahrani, AA & Piya, MK (2015) The role of GLP-1 receptor agonists as weight loss agents in patients with and without type 2 diabetes. Practical Diabetes 32, 297300b.CrossRefGoogle Scholar
Institute of Medicine (US) Panel on the Definition of Dietary Fiber and the Standing Committee on the Scientific Evaluation of Dietary Reference Intakes (2001) Dietary Reference Intakes Proposed Definition of Dietary Fiber, pp. 2–12. Washington (DC): National Academies Press (US).Google Scholar
Standards ANZF. Labelling Review Recommendation 14 – Supporting Document 1. Available at: https://www.foodstandards.gov.au/consumer/labelling/review/Documents/Labelling%20review%20recommendation%2014%20-%20supporting%20document%201.pdf (accessed February 2020).Google Scholar
Koh-Banerjee, P, Franz, M, Sampson, L et al. (2004) Changes in whole-grain, bran, and cereal fiber consumption in relation to 8-y weight gain among men. Am J Clin Nutr 80, 12371245.CrossRefGoogle ScholarPubMed
Davis, JN, Alexander, KE, Ventura, EE et al. (2009) Inverse relation between dietary fiber intake and visceral adiposity in overweight Latino youth. Am J Clin Nutr 90, 11601166.CrossRefGoogle ScholarPubMed
Interact Consortium (2015) Dietary fibre and incidence of type 2 diabetes in eight European countries: the EPIC-InterAct Study and a meta-analysis of prospective studies. Diabetologia 58, 13941408.CrossRefGoogle Scholar
Murphy, N, Norat, T, Ferrari, P et al. (2012) Dietary fibre intake and risks of cancers of the colon and rectum in the European prospective investigation into cancer and nutrition (EPIC). PLoS ONE 7, e39361.CrossRefGoogle Scholar
Arora, T, Loo, RL, Anastasovska, J et al. (2012) Differential effects of two fermentable carbohydrates on central appetite regulation and body composition. PLoS ONE 7, e43263.CrossRefGoogle ScholarPubMed
Cani, PD, Neyrinck, AM, Maton, N et al. (2005) Oligofructose promotes satiety in rats fed a high-fat diet: involvement of glucagon-like Peptide-1. Obes Res 13, 10001007.CrossRefGoogle ScholarPubMed
Cani, PD, Dewever, C & Delzenne, NM (2004) Inulin-type fructans modulate gastrointestinal peptides involved in appetite regulation (glucagon-like peptide-1 and ghrelin) in rats. Br J Nutr 92, 521526.CrossRefGoogle ScholarPubMed
Delzenne, NM, Cani, PD, Daubioul, C et al. (2005) Impact of inulin and oligofructose on gastrointestinal peptides. Br J Nutr;93 Suppl 1, S157S161.CrossRefGoogle ScholarPubMed
Thompson, SV, Hannon, BA, An, R et al. (2017) Effects of isolated soluble fiber supplementation on body weight, glycemia, and insulinemia in adults with overweight and obesity: a systematic review and meta-analysis of randomized controlled trials. Am J Clin Nutr 106, 15141528.CrossRefGoogle ScholarPubMed
Cummings, JH, Pomare, EW, Branch, WJ et al. (1987) Short chain fatty acids in human large intestine, portal, hepatic and venous blood. Gut 28, 12211227.CrossRefGoogle ScholarPubMed
Popovich, DG, Jenkins, DJA, Kendall, CWC et al. (1997) The western lowland gorilla diet has implications for the health of humans and other hominoids. J Nutr 127, 20002005.CrossRefGoogle ScholarPubMed
Bergman, EN (1990) Energy contributions of volatile fatty acids from the gastrointestinal tract in various species. Physiol Rev 70, 567590.CrossRefGoogle ScholarPubMed
den Besten, G, Lange, K, Havinga, R et al. (2013) Gut-derived short-chain fatty acids are vividly assimilated into host carbohydrates and lipids. Am J Physiol Gastrointest Liver Physiol 305, G900G910.CrossRefGoogle ScholarPubMed
Boets, E, Gomand, SV, Deroover, L et al. (2017) Systemic availability and metabolism of colonic-derived short-chain fatty acids in healthy subjects: a stable isotope study. J Physiol 595, 541555.CrossRefGoogle ScholarPubMed
Brown, AJ, Goldsworthy, SM, Barnes, AA et al. (2003) The Orphan G protein-coupled receptors GPR41 and GPR43 are activated by propionate and other short chain carboxylic acids. J Biol Chem 278, 11312–9.CrossRefGoogle ScholarPubMed
Le Poul, E, Loison, C, Struyf, S et al. (2003) Functional characterization of human receptors for short chain fatty acids and their role in polymorphonuclear cell activation. J Biol Chem 278, 25481–9.CrossRefGoogle ScholarPubMed
Nilsson, NE, Kotarsky, K, Owman, C et al. (2003) Identification of a free fatty acid receptor, FFA2R, expressed on leukocytes and activated by short-chain fatty acids. Biochem Biophys Res Commun 303, 10471052.CrossRefGoogle ScholarPubMed
Alia, HS, Aaron, ML, Gary, F et al. (2019) Regulation of energy expenditure and substrate oxidation by short-chain fatty acids. J Endocrinol 242, R1R8.Google Scholar
Li, G, Su, H, Zhou, Z et al. (2014) Identification of the porcine G protein-coupled receptor 41 and 43 genes and their expression pattern in different tissues and development stages. PLoS ONE 9, e97342.CrossRefGoogle ScholarPubMed
Psichas, A, Sleeth, ML, Murphy, KG et al. (2015) The short chain fatty acid propionate stimulates GLP-1 and PYY secretion via free fatty acid receptor 2 in rodents. Int J Obes 39, 424429.CrossRefGoogle ScholarPubMed
Karaki, S-I, Mitsui, R, Hayashi, H et al. (2006) Short-chain fatty acid receptor, GPR43, is expressed by enteroendocrine cells and mucosal mast cells in rat intestine. Cell Tissue Res 324, 353360.CrossRefGoogle ScholarPubMed
Tolhurst, G, Heffron, H, Lam, YS et al. (2012) Short-chain fatty acids stimulate glucagon-like peptide-1 secretion via the G-protein-coupled receptor FFAR2. Diabetes 61, 364371.CrossRefGoogle ScholarPubMed
Lin, HV, Frassetto, A, Kowalik, EJ Jr et al. (2012) Butyrate and propionate protect against diet-induced obesity and regulate gut hormones via free fatty acid receptor 3-independent mechanisms. PLoS ONE 7, e35240–e.CrossRefGoogle ScholarPubMed
Anastasovska, J, Arora, T, Sanchez Canon, GJ et al. (2012) Fermentable carbohydrate alters hypothalamic neuronal activity and protects against the obesogenic environment. Obesity (Silver Spring, Md) 20, 10161023.CrossRefGoogle ScholarPubMed
So, PW, Yu, WS, Kuo, YT et al. (2007) Impact of resistant starch on body fat patterning and central appetite regulation. PLoS ONE 2, e1309.CrossRefGoogle ScholarPubMed
Reimer, RA, Maurer, AD, Eller, LK et al. (2012) Satiety hormone and metabolomic response to an intermittent high energy diet differs in rats consuming long-term diets high in protein or prebiotic fiber. J Proteom Res 11, 40654074.CrossRefGoogle ScholarPubMed
den Besten, G, Bleeker, A, Gerding, A et al. (2015) Short-chain fatty acids protect against high-fat diet–induced obesity via a PPARγ-dependent switch from lipogenesis to fat oxidation. Diabetes 64, 23982408.CrossRefGoogle Scholar
Gao, Z, Yin, J, Zhang, J et al. (2009) Butyrate improves insulin sensitivity and increases energy expenditure in mice. Diabetes 58, 15091517.CrossRefGoogle ScholarPubMed
De Vadder, F, Kovatcheva-Datchary, P, Goncalves, D et al. (2014) Microbiota-generated metabolites promote metabolic benefits via gut-brain neural circuits. Cell 156, 8496.CrossRefGoogle ScholarPubMed
Henagan, TM, Stefanska, B, Fang, Z et al. (2015) Sodium butyrate epigenetically modulates high-fat diet-induced skeletal muscle mitochondrial adaptation, obesity and insulin resistance through nucleosome positioning. Br J Pharmacol 172, 27822798.CrossRefGoogle ScholarPubMed
Li, Z, Yi, CX, Katiraei, S et al. (2018) Butyrate reduces appetite and activates brown adipose tissue via the gut-brain neural circuit. Gut 67, 12691279.CrossRefGoogle ScholarPubMed
Frost, G, Sleeth, ML, Sahuri-Arisoylu, M et al. (2014) The short-chain fatty acid acetate reduces appetite via a central homeostatic mechanism. Nat Commun 5, 3611.CrossRefGoogle Scholar
Darzi, J, Frost, GS & Robertson, MD (2012) Effects of a novel propionate-rich sourdough bread on appetite and food intake. Eur J Clin Nutr 66, 789794.CrossRefGoogle ScholarPubMed
Polyviou, T, MacDougall, K, Chambers, ES et al. (2016) Randomised clinical study: inulin short-chain fatty acid esters for targeted delivery of short-chain fatty acids to the human colon. Aliment Pharmacol Ther 44, 662672.CrossRefGoogle ScholarPubMed
Zhou, D, Pan, Q, Xin, FZ et al. (2017) Sodium butyrate attenuates high-fat diet-induced steatohepatitis in mice by improving gut microbiota and gastrointestinal barrier. World J Gastroenterol 23, 6075.CrossRefGoogle ScholarPubMed
Lu, Y, Fan, C, Li, P et al. (2016) Short chain fatty acids prevent high-fat-diet-induced obesity in mice by regulating G protein-coupled receptors and gut microbiota. Sci Rep 6, 37589.CrossRefGoogle ScholarPubMed
Hong, J, Jia, Y, Pan, S et al. (2016) Butyrate alleviates high fat diet-induced obesity through activation of adiponectin-mediated pathway and stimulation of mitochondrial function in the skeletal muscle of mice. Oncotarget 7, 5607156082.CrossRefGoogle ScholarPubMed
Ridaura, VK, Faith, JJ, Rey, FE et al. (2013) Gut microbiota from twins discordant for obesity modulate metabolism in mice. Science (New York, NY) 341, 1241214.CrossRefGoogle ScholarPubMed
Liou, AP, Paziuk, M, Luevano, J-M Jr et al. (2013) Conserved shifts in the gut microbiota due to gastric bypass reduce host weight and adiposity. Sci Transl Med 5, 178ra41178ra41.CrossRefGoogle ScholarPubMed
Perry, RJ, Peng, L, Barry, NA et al. (2016) Acetate mediates a microbiome-brain-beta-cell axis to promote metabolic syndrome. Nature 534, 213217.CrossRefGoogle ScholarPubMed
Sahuri-Arisoylu, M, Brody, LP, Parkinson, JR et al. (2016) Reprogramming of hepatic fat accumulation and ‘browning’ of adipose tissue by the short-chain fatty acid acetate. Int J Obes (2005) 40, 955963.CrossRefGoogle ScholarPubMed
Samuel, BS, Shaito, A, Motoike, T et al. (2008) Effects of the gut microbiota on host adiposity are modulated by the short-chain fatty-acid binding G protein-coupled receptor, Gpr41. Proc Natl Acad Sci USA 105, 1676716772.CrossRefGoogle ScholarPubMed
Rinninella, E, Raoul, P, Cintoni, M et al. (2019) What is the healthy gut microbiota composition? A changing ecosystem across age, environment, diet, and diseases. Microorganisms 7, 14.CrossRefGoogle Scholar
Arumugam, M, Raes, J, Pelletier, E et al. (2011) Enterotypes of the human gut microbiome. Nature 473, 174180.CrossRefGoogle ScholarPubMed
Qin, J, Li, R, Raes, J et al. (2010) A human gut microbial gene catalogue established by metagenomic sequencing. Nature 464, 5965.CrossRefGoogle ScholarPubMed
Almeida, A, Mitchell, AL, Boland, M et al. (2019) A new genomic blueprint of the human gut microbiota. Nature 568, 499504.CrossRefGoogle ScholarPubMed
Aguirre, M, Bussolo de Souza, C & Venema, K (2016) The gut microbiota from lean and obese subjects contribute differently to the fermentation of arabinogalactan and inulin. PLoS ONE 11, e0159236–e.CrossRefGoogle ScholarPubMed
Baxter, NT, Schmidt, AW, Venkataraman, A et al. (2019) Dynamics of human gut microbiota and short-chain fatty acids in response to dietary interventions with three fermentable fibers. mBio 10, e02566–18.CrossRefGoogle ScholarPubMed
Salonen, A, Lahti, L, Salojärvi, J et al. (2014) Impact of diet and individual variation on intestinal microbiota composition and fermentation products in obese men. ISME J 8, 22182230.CrossRefGoogle ScholarPubMed
Venkataraman, A, Sieber, JR, Schmidt, AW et al. (2016) Variable responses of human microbiomes to dietary supplementation with resistant starch. Microbiome 4, 33.CrossRefGoogle ScholarPubMed
Barcenilla, A, Pryde, SE, Martin, JC et al. (2000) Phylogenetic relationships of butyrate-producing bacteria from the human gut. Appl Environ Microbiol 66, 16541661.CrossRefGoogle ScholarPubMed
Louis, P, Young, P, Holtrop, G et al. (2010) Diversity of human colonic butyrate-producing bacteria revealed by analysis of the butyryl-CoA:acetate CoA-transferase gene. Environ Microbiol 12, 304314.CrossRefGoogle ScholarPubMed
Rossi, M, Corradini, C, Amaretti, A et al. (2005) Fermentation of fructooligosaccharides and inulin by bifidobacteria: a comparative study of pure and fecal cultures. Appl Environ Microbiol 71, 61506158.CrossRefGoogle ScholarPubMed
Ze, X, Duncan, SH, Louis, P et al. (2012) Ruminococcus bromii is a keystone species for the degradation of resistant starch in the human colon. ISME J 6, 15351543.CrossRefGoogle ScholarPubMed
Belenguer, A, Duncan, SH, Calder, AG et al. (2006) Two routes of metabolic cross-feeding between Bifidobacterium adolescentis and butyrate-producing anaerobes from the human gut. Appl Environ Microbiol 72, 35933599.CrossRefGoogle ScholarPubMed
Turnbaugh, PJ, Ley, RE, Mahowald, MA et al. (2006) An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 444, 10271031.CrossRefGoogle ScholarPubMed
Reichardt, N, Duncan, SH, Young, P et al. (2014) Phylogenetic distribution of three pathways for propionate production within the human gut microbiota. ISME J 8, 13231335.CrossRefGoogle ScholarPubMed
Derrien, M, Vaughan, EE, Plugge, CM et al. (2004) Akkermansia muciniphila gen. nov., sp. nov., a human intestinal mucin-degrading bacterium. Int J Syst Evol Microbiol 54, 14691476.CrossRefGoogle ScholarPubMed
Depommier, C, Everard, A, Druart, C et al. (2019) Supplementation with Akkermansia muciniphila in overweight and obese human volunteers: a proof-of-concept exploratory study. Nat Med 25, 10961103.CrossRefGoogle ScholarPubMed
Everard, A, Belzer, C, Geurts, L et al. (2013) Cross-talk between Akkermansia muciniphila and intestinal epithelium controls diet-induced obesity. Proc Natl Acad Sci USA 110, 90669071.CrossRefGoogle ScholarPubMed
Hansen, CHF, Krych, L, Nielsen, DS et al. (2012) Early life treatment with vancomycin propagates Akkermansia muciniphila and reduces diabetes incidence in the NOD mouse. Diabetologia 55, 22852294.CrossRefGoogle ScholarPubMed
Aguirre, M, Eck, A, Koenen, ME et al. (2016) Diet drives quick changes in the metabolic activity and composition of human gut microbiota in a validated in vitro gut model. Res Microbiol 167, 114125.CrossRefGoogle Scholar
David, LA, Maurice, CF, Carmody, RN et al. (2014) Diet rapidly and reproducibly alters the human gut microbiome. Nature 505, 559563.CrossRefGoogle ScholarPubMed
O'Keefe, SJ, Li, JV, Lahti, L et al. (2015) Fat, fibre and cancer risk in African Americans and rural Africans. Nat Commun 6, 6342.CrossRefGoogle ScholarPubMed
Brinkworth, GD, Noakes, M, Clifton, PM et al. (2009) Comparative effects of very low-carbohydrate, high-fat and high-carbohydrate, low-fat weight-loss diets on bowel habit and faecal short-chain fatty acids and bacterial populations. Br J Nutr 101, 14931502.CrossRefGoogle ScholarPubMed
Duncan, SH, Belenguer, A, Holtrop, G et al. (2007) Reduced dietary intake of carbohydrates by obese subjects results in decreased concentrations of butyrate and butyrate-producing bacteria in feces. Appl Environ Microbiol 73, 10731078.CrossRefGoogle ScholarPubMed
Hald, S, Schioldan, AG, Moore, ME et al. (2016) Effects of arabinoxylan and resistant starch on intestinal microbiota and short-chain fatty acids in subjects with metabolic syndrome: a randomised crossover study. PLoS ONE 11, e0159223–e.CrossRefGoogle ScholarPubMed
McOrist, AL, Abell, GCJ, Cooke, C et al. (2008) Bacterial population dynamics and faecal short-chain fatty acid (SCFA) concentrations in healthy humans. Br J Nutr 100, 138146.CrossRefGoogle ScholarPubMed
Wu, GD, Chen, J, Hoffmann, C et al. (2011) Linking long-term dietary patterns with gut microbial enterotypes. Science 334, 105108.CrossRefGoogle ScholarPubMed
Reichardt, N, Vollmer, M, Holtrop, G et al. (2018) Specific substrate-driven changes in human faecal microbiota composition contrast with functional redundancy in short-chain fatty acid production. ISME J 12, 610622.CrossRefGoogle ScholarPubMed
Walker, AW, Ince, J, Duncan, SH et al. (2011) Dominant and diet-responsive groups of bacteria within the human colonic microbiota. ISME J 5, 220230.CrossRefGoogle ScholarPubMed
Abell, GCJ, Cooke, CM, Bennett, CN et al. (2008) Phylotypes related to Ruminococcus bromii are abundant in the large bowel of humans and increase in response to a diet high in resistant starch. FEMS Microbiol Ecol 66, 505515.CrossRefGoogle ScholarPubMed
Leitch, ECM, Walker, AW, Duncan, SH et al. (2007) Selective colonization of insoluble substrates by human faecal bacteria. Environ Microbiol 9, 667679.CrossRefGoogle ScholarPubMed
Sonnenburg, ED, Smits, SA, Tikhonov, M et al. (2016) Diet-induced extinctions in the gut microbiota compound over generations. Nature 529, 212215.CrossRefGoogle ScholarPubMed
Ley, RE, Backhed, F, Turnbaugh, P et al. (2005) Obesity alters gut microbial ecology. Proc Natl Acad Sci USA 102, 11070–5.CrossRefGoogle ScholarPubMed
Ley, RE, Turnbaugh, PJ, Klein, S et al. (2006) Human gut microbes associated with obesity. Nature 444, 10221023.CrossRefGoogle ScholarPubMed
Schwiertz, A, Taras, D, Schäfer, K et al. (2010) Microbiota and SCFA in lean and overweight healthy subjects. Obesity 18, 190195.CrossRefGoogle ScholarPubMed
Zhang, H, DiBaise, JK, Zuccolo, A et al. (2009) Human gut microbiota in obesity and after gastric bypass. Proc Natl Acad Sci 106, 23652370.CrossRefGoogle ScholarPubMed
Furet, J-P, Kong, L-C, Tap, J et al. (2010) Differential adaptation of human gut microbiota to bariatric surgery-induced weight loss. Links with metabolic and low-grade inflammation markers. Diabetes 59, 30493057.CrossRefGoogle ScholarPubMed
Castaner, O, Goday, A, Park, Y-M et al. (2018) The gut microbiome profile in obesity: a systematic review. Int J Endocrinol 2018, 4095789.Google ScholarPubMed
Ulker, İ & Yildiran, H (2019) The effects of bariatric surgery on gut microbiota in patients with obesity: a review of the literature. Biosci Microbiota Food Health 38, 39.CrossRefGoogle ScholarPubMed
Berg, JM, Tymoczko, JL & Stryer, L (2002) Biochemistry, 5th ed. New York: W.H. Freeman.Google Scholar
Fishman, ML, Cooke, P, White, B et al. (1995) Size distributions of amylose and amylopectin solubilized from corn starch granules. Carbohydr Polym 26, 245253.CrossRefGoogle Scholar
Svihus, B, Uhlen, AK & Harstad, OM (2005) Effect of starch granule structure, associated components and processing on nutritive value of cereal starch: a review. Anim Feed Sci Tech 122, 303320.CrossRefGoogle Scholar
Lovegrove, A, Edwards, CH, De Noni, I et al. (2017) Role of polysaccharides in food, digestion, and health. Crit Rev Food Sci 57, 237253.CrossRefGoogle ScholarPubMed
Syahariza, ZA, Sar, S, Hasjim, J et al. (2013) The importance of amylose and amylopectin fine structures for starch digestibility in cooked rice grains. Food Chem 136, 742749.CrossRefGoogle ScholarPubMed
Behall, KM & Howe, JC (1995) Effect of long-term consumption of amylose vs amylopectin starch on metabolic variables in human subjects. Am J Clin Nutr 61, 334340.CrossRefGoogle ScholarPubMed
Behall, KM, Scholfield, DJ, Yuhaniak, I et al. (1989) Diets containing high amylose vs amylopectin starch: effects on metabolic variables in human subjects. Am J Clin Nutr 49, 337344.CrossRefGoogle ScholarPubMed
Mishra, S, Hardacre, A & Monro, J (2012) Food structure and carbohydrate digestibility. In Comprehensive Studies on Glycobiology, pp. 289316. Available at https://www.intechopen.com/books/carbohydrates-comprehensive-studies-on-glycobiology-and-glycotechnology/food-structure-and-carbohydrate-digestibilityGoogle Scholar
Martens, BMJ, Gerrits, WJJ, Bruininx, EMAM et al. (2018) Amylopectin structure and crystallinity explains variation in digestion kinetics of starches across botanic sources in an in vitro pig model. J Anim Sci Biotech 9, 91.CrossRefGoogle Scholar
Brett, CT & Waldron, KW (1996) Physiology and Biochemistry of Plant Cell Walls. Dordrecht, Netherlands: Springer Science & Business Media.Google Scholar
Burton, RA, Gidley, MJ & Fincher, GB (2010) Heterogeneity in the chemistry, structure and function of plant cell walls. Nat Chem Biol 6, 724732.CrossRefGoogle ScholarPubMed
Padayachee, A, Day, L, Howell, K et al. (2017) Complexity and health functionality of plant cell wall fibers from fruits and vegetables. Crit Rev Food Sci Nutr 57, 5981.CrossRefGoogle ScholarPubMed
Harris, PJ & Smith, BG (2006) Plant cell walls and cell-wall polysaccharides: structures, properties and uses in food products. Int J Food Sci Tech 41, 129143.CrossRefGoogle Scholar
Parada, J & Aguilera, JM (2007) Food microstructure affects the bioavailability of several nutrients. J Food Sci 72, R21R32.CrossRefGoogle ScholarPubMed
Berry, SE, Tydeman, EA, Lewis, HB et al. (2008) Manipulation of lipid bioaccessibility of almond seeds influences postprandial lipemia in healthy human subjects. Am J Clin Nutr 88, 922929.CrossRefGoogle ScholarPubMed
Jarvi, AE, Karlstrom, BE, Granfeldt, YE et al. (1995) The influence of food structure on postprandial metabolism in patients with non-insulin-dependent diabetes mellitus. Am J Clin Nutr 61, 837842.CrossRefGoogle ScholarPubMed
Jenkins, DJ, Wesson, V, Wolever, TM et al. (1988) Wholemeal versus wholegrain breads: proportion of whole or cracked grain and the glycaemic response. Br Med J 297, 958960.CrossRefGoogle ScholarPubMed
Noah, L, Guillon, F, Bouchet, B et al. (1998) Digestion of carbohydrate from white beans (Phaseolus vulgaris L.) in healthy humans. J Nutr 128, 977985.CrossRefGoogle Scholar
Grundy, MML, Edwards, CH, Mackie, AR et al. (2016) Re-evaluation of the mechanisms of dietary fibre and implications for macronutrient bioaccessibility, digestion and postprandial metabolism. Br J Nutr 116, 816833.CrossRefGoogle ScholarPubMed
Swackhamer, C & Bornhorst, GM (2019) Fracture properties of foods: experimental considerations and applications to mastication. J Food Eng 263, 213226.CrossRefGoogle Scholar
Grundy, MM, Grassby, T, Mandalari, G et al. (2015) Effect of mastication on lipid bioaccessibility of almonds in a randomized human study and its implications for digestion kinetics, metabolizable energy, and postprandial lipemia. Am J Clin Nutr 101, 2533.CrossRefGoogle Scholar
Grundy, MML, Carrière, F, Mackie, AR et al. (2016) The role of plant cell wall encapsulation and porosity in regulating lipolysis during the digestion of almond seeds. Food Funct 7, 6978.CrossRefGoogle ScholarPubMed
Read, NW, Welch, IM, Austen, CJ et al. (1986) Swallowing food without chewing; a simple way to reduce postprandial glycaemia. Br J Nutr 55, 4347.CrossRefGoogle ScholarPubMed
Tydeman, EA, Parker, ML, Faulks, RM et al. (2010) Effect of carrot (Daucus carota) microstructure on carotene bioaccessibility in the upper gastrointestinal tract. 2. In vivo digestions. J Agric Food Chem 58, 98559860.CrossRefGoogle ScholarPubMed
Mandalari, G, Faulks, RM, Rich, GT et al. (2008) Release of protein, lipid, and vitamin E from almond seeds during digestion. J Agric Food Chem 56, 34093416.CrossRefGoogle ScholarPubMed
Livesey, G, Wilkinson, JA, Roe, M et al. (1995) Influence of the physical form of barley grain on the digestion of its starch in the human small intestine and implications for health. Am J Clin Nutr 61, 7581.CrossRefGoogle ScholarPubMed
Birkett, AM, Mathers, JC, Jones, GP et al. (2000) Changes to the quantity and processing of starchy foods in a Western diet can increase polysaccharides escaping digestion and improve in vitro fermentation variables. Br J Nutr 84, 6372.CrossRefGoogle Scholar
Olkku, J & Rha, C (1978) Gelatinisation of starch and wheat flour starch – a review. Food Chem 3, 293317.CrossRefGoogle Scholar
Englyst, HN & Cummings, JH (1987) Digestion of polysaccharides of potato in the small intestine of man. Am J Clin Nutr 45, 423431.CrossRefGoogle Scholar
Moelants, KR, Cardinaels, R, Van Buggenhout, S et al. (2014) A review on the relationships between processing, food structure, and rheological properties of plant-tissue-based food suspensions. Compr Rev Food Sci Food Saf 13, 241260.CrossRefGoogle Scholar
Grassby, T, Picout, DR, Mandalari, G et al. (2014) Modelling of nutrient bioaccessibility in almond seeds based on the fracture properties of their cell walls. Food Funct 5, 30963106.CrossRefGoogle ScholarPubMed
Holscher, HD (2017) Dietary fiber and prebiotics and the gastrointestinal microbiota. Gut Microbes 8, 172184.CrossRefGoogle ScholarPubMed
Silvester, KR, Englyst, HN & Cummings, JH (1995) Ileal recovery of starch from whole diets containing resistant starch measured in vitro and fermentation of ileal effluent. Am J Clin Nutr 62, 403411.CrossRefGoogle ScholarPubMed
Hernot, DC, Boileau, TW, Bauer, LL et al. (2008) In vitro digestion characteristics of unprocessed and processed whole grains and their components. J Agri Food Chem 56, 1072110726.CrossRefGoogle ScholarPubMed
Juul, F, Martinez-Steele, E, Parekh, N et al. (2018) Ultra-processed food consumption and excess weight among US adults. Br J Nutr 120, 90100.CrossRefGoogle ScholarPubMed
Mendonça, R, Pimenta, AM, Gea, A et al. (2016) Ultraprocessed food consumption and risk of overweight and obesity: the University of Navarra Follow-Up (SUN) cohort study. Am J Clin Nutr 104, 14331440.CrossRefGoogle ScholarPubMed
Mendonca, RD, Lopes, AC, Pimenta, AM et al. (2017) Ultra-processed food consumption and the incidence of hypertension in a Mediterranean cohort: the Seguimiento Universidad de Navarra project. Am J Hypertens 30, 358366.Google Scholar
Costa, CS, Del-Ponte, B, Assunção, MCF et al. (2018) Consumption of ultra-processed foods and body fat during childhood and adolescence: a systematic review. Public Health Nutr 21, 148159.CrossRefGoogle ScholarPubMed
Melo, I, Costa, CACB, Santos, JVLD et al. (2017) Consumption of minimally processed food is inversely associated with excess weight in adolescents living in an underdeveloped city. PLoS ONE 12, e0188401.CrossRefGoogle Scholar
Canella, DS, Levy, RB, Martins, APB et al. (2014) Ultra-processed food products and obesity in Brazilian households (2008–2009). PLoS ONE 9, e92752.CrossRefGoogle Scholar
Fardet, A (2016) Minimally processed foods are more satiating and less hyperglycemic than ultra-processed foods: a preliminary study with 98 ready-to-eat foods. Food Funct 7, 23382346.CrossRefGoogle ScholarPubMed
Gustafsson, K, Asp, NG, Hagander, B et al. (1995) Influence of processing and cooking of carrots in mixed meals on satiety, glucose and hormonal response. Int J Food Sci Nutr 46, 312.CrossRefGoogle ScholarPubMed
Mori, AM, Considine, RV & Mattes, RD (2011) Acute and second-meal effects of almond form in impaired glucose tolerant adults: a randomized crossover trial. Nutr Metab 8, 6.CrossRefGoogle ScholarPubMed
Ble-Castillo, JL, Juarez-Rojop, IE, Tovilla-Zarate, CA et al. (2017) Acute consumption of resistant starch reduces food intake but has no effect on appetite ratings in healthy subjects. Nutrients 9, 696.CrossRefGoogle ScholarPubMed
Hall, KD, Ayuketah, A, Brychta, R, et al. (2019) Ultra-processed diets cause excess calorie intake and weight gain: an inpatient randomized controlled trial of ad libitum food intake. Cell Metab 30, 6777.CrossRefGoogle ScholarPubMed
Figure 0

Fig. 1. (Colour online) Central regulation of appetite. Activation of pro-opiomelanocortin (POMC) neurones reduces appetite. Activation of neuropeptide Y/agouiti-related peptide (NPY/AgRP) neurones increases appetite. NPY/AgRP neurones directly inhibit the activity of POMC neurones through the release of inhibitory neurotransmitter γ-aminobutyric acid (GABA). Both neurones project to other brain regions. Vagus nerve carries signals from the periphery to the brain. ARC, arcuate nucleus; NTC, nucleus of the solitary tract.

Figure 1

Fig. 2. (Colour online) The digestion of (a) intact and (b) disrupted food structures. (a) Digestive enzymes in the body have limited access to the intracellular nutrients, hindered by intact food structures and cell walls. (b) Digestive enzymes have access to acellular nutrients released from ruptured/disrupted cellular structures. Separated cells remain intact and limit enzyme access to intracellular nutrients.

Figure 2

Fig. 3. The interplay between food structures, digestion, microbial fermentation and appetite regulation. Intact cellular structures arrive large intestine where they become available for bacterial fermentation. This process yields SCFA that stimulate the release of peptide YY (PYY) and glucagon-like peptide 1 (GLP-1) from intestinal L-cells. PYY and GLP-1 signal to the brain to reduce appetite.