Glycaemic sugar metabolism and the gut microbiota: past, present and future

Abstract

Non‐communicable diseases (NCDs), such as type 2 diabetes (T2D) and metabolic dysfunction‐associated fatty liver disease, have reached epidemic proportions worldwide. The global increase in dietary sugar consumption, which is largely attributed to the production and widespread use of cheap alternatives such as high‐fructose corn syrup, is a major driving factor of NCDs. Therefore, a comprehensive understanding of sugar metabolism and its impact on host health is imperative to rise to the challenge of reducing NCDs. Notably, fructose appears to exert more pronounced deleterious effects than glucose, as hepatic fructose metabolism induces de novo lipogenesis and insulin resistance through distinct mechanisms. Furthermore, recent studies have demonstrated an intricate relationship between sugar metabolism and the small intestinal microbiota (SIM). In contrast to the beneficial role of colonic microbiota in complex carbohydrate metabolism, sugar metabolism by the SIM appears to be less beneficial to the host as it can generate toxic metabolites. These fermentation products can serve as a substrate for fatty acid synthesis, imposing negative health effects on the host. Nevertheless, due to the challenging accessibility of the small intestine, our knowledge of the SIM and its involvement in sugar metabolism remains limited. This review presents an overview of the current knowledge in this field along with implications for future research, ultimately offering potential therapeutic avenues for addressing NCDs.

Increased sugar consumption is a main driver of the increased prevalence of obesity and non‐communicable diseases (NCDs). Therefore, understanding host and microbial sugar metabolism and its metabolic effects is crucial. A high‐sugar diet can induce gut dysbiosis, and gut microbial sugar fermentation can produce deleterious metabolites, potentially contributing to the development of NCDs. However, the intricate relationship between dietary sugars and the gut microbiota requires further elucidation.

Abbreviations

ATP

adenosine triphosphate

CFU

colony‐forming units

DHAP

dihydroxyacetone phosphate

DNL

de novo lipogenesis

EMP

Embden‐Meyerhof‐Parnas

F1,6,BP

fructose‐1,6‐bisphosphate

F1P

fructose‐1‐phosphate

F6P

fructose‐6‐phosphate

FMT

faecal microbiota transplantation

G6P

glucose‐6‐phosphate

G6Pase

glucose‐6‐phosphatase

GA3P

glyceraldehyde‐3‐phosphate

GLUT2

glucose transporter 2

GLUT5

glucose transporter 5

HFCS

high‐fructose corn syrup

HK

hexokinase

KHK

ketohexokinase

MAFLD

metabolic dysfunction‐associated fatty liver disease

MASH

metabolic dysfunction‐associated steatohepatitis

NCDs

non‐communicable diseases

NDOs

non‐digestible oligosaccharides

NSPs

non‐starch polysaccharides

PFK1

phosphofructokinase 1

PP

pentose phosphate

PTS

phosphotransferase systems

RS

resistant starch

SCFAs

short‐chain fatty acids

SGLT1

sodium‐glucose transporter 1

SHIME

simulator of the human intestinal microbial system

SI

small intestine

SIBO

small intestinal bacterial overgrowth

SIM

small intestinal microbiota

T2D

type 2 diabetes

TCA

tricarboxylic acid

TIM‐1

TNO gastrointestinal model 1

TSI

the smallest intestine

US

United States

WHO

World Health Organization

Introduction

Over recent decades, there has been an alarming increase in obesity and related non‐communicable diseases (NCDs), including type 2 diabetes (T2D) and metabolic dysfunction‐associated fatty liver disease (MAFLD), formerly known as non‐alcoholic fatty liver disease. The prevalence of obesity has risen dramatically from 3.2% to 10.8% in men and from 6.4% to 14.9% in women between 1975 and 2014 [1]. Should current trends persist, it is estimated that around 57.8% of the global population will be overweight (BMI > 25 kg·m⁻²) or obese (BMI > 30 kg·m⁻²) by the year 2030 [2]. Moreover, in 2021, diabetes affected an estimated 6.1% of the global population, representing 529 million individuals, with 96% reflecting T2D cases [3]. A recent meta‐analysis found a global MAFLD prevalence of 50.7% among overweight and obese individuals [4].

Nutrition significantly contributes to the increasing prevalence of obesity and related NCD, as obesity results from an imbalance in energy intake and expenditure [5]. There are several ways to study the effects of nutrition on health. One approach is to focus on macronutrients, such as protein, fat and carbohydrates. Carbohydrates, in particular sugars and refined carbohydrates, have received considerable attention as potential drivers of obesity and NCDs [6, 7, 8, 9, 10, 11]. Furthermore, the introduction of cheaper caloric sweeteners, such as high‐fructose corn syrup (HFCS), has increased sugar consumption. This has been suggested to be the main cause of the ongoing pandemic of obesity and related diseases [12]. Hence, it is crucial to understand sugar metabolism and its effects on host health in order to address these issues.

Sugars are one of the three principal groups of carbohydrates, biochemically defined by their degree of polymerisation [13]. These three principal groups include simple carbohydrates, commonly known as “sugars,” oligosaccharides, and polysaccharides [13]. Sugars encompass monosaccharides or “simple sugars” (glucose, fructose, galactose, mannose), disaccharides such as sucrose (glucose and fructose), lactose (glucose and galactose) and maltose (glucose and glucose), as well as polyols (sugar alcohols) [14]. The other two principal groups of carbohydrates, oligo‐ and polysaccharides, are referred to as complex carbohydrates. Oligosaccharides are composed of three to nine monosaccharides, whereas polysaccharides contain 10 or more monomer units. The different types of carbohydrates undergo different microbial and host catabolism. This review focuses on sugar metabolism, as sugars are a major driver of obesity and other NCDs [15, 16, 17].

To elucidate the mechanism underlying sugar metabolism and its association with the development of obesity and other NCDs, it is important to explore the potential role of the gut microbiota, given its major involvement in nutrient catabolism [18, 19]. The human microbiota comprises all living micro‐organisms including bacteria, archaea, algae and small protists, that live in co‐existence with their hosts [20]. When referring to the human microbiome, this encompasses all previously mentioned micro‐organisms as well as viruses, phages and fungi [20, 21]. The vast majority of the human microbiota colonises the gastrointestinal tract [18], with an abundance that increases along the intestine, ranging from 10³ colony‐forming units (CFU)·mL⁻¹ in the duodenum up to 10¹² CFU·mL⁻¹ in the colon [22, 23]. This is also accompanied by increasing microbial diversity [23]. The increase in microbial abundance and diversity along the gastrointestinal tract can be attributed to various host‐related factors including reduced transit time, increasing pH levels, decreasing amounts of antimicrobial peptides produced by Paneth cells, and decreasing nutrient availability towards the more distal segments of the gut [23]. Whereas the dominant phyla of the colonic microbiota are Firmicutes and Bacteroidetes, the small intestinal microbiota (SIM) is characterised by a high relative abundance of Firmicutes and Proteobacteria and a low relative abundance of Bacteroidetes [24]. One of the central functions of the gut microbiota is its involvement in nutrient catabolism, including carbohydrates, which significantly influences host physiology and disease. Current research has extensively focused on the role of the colonic gut microbiota in complex carbohydrate metabolism, encompassing fibres and other non‐digestible carbohydrates [19, 25, 26, 27, 28]. However, the role of the gut microbiota in sugar metabolism is less thoroughly explored and remains not fully comprehended. Given the need for novel treatments, extensive research into the ongoing pandemic of obesity and NCDs remains imperative. This narrative review aims to provide a comprehensive overview of glycaemic sugar metabolism, with particular emphasis on the role of the gut microbiota and the impact on host health.

Past and present

Historical evaluation of sugar consumption

The early Homo sapiens obtained carbohydrates in the form of sugars by consuming wild fruits and vegetables. The discovery of sugarcane and sugar beet as a new potential dense source of sugar had a profound impact on sugar production and consumption over time [29]. The first isolation of sucrose in the form of sugarcane juice is believed to have occurred in India around 800 before Christ [29, 30]. Subsequently, the Indians managed to crystallise sucrose from sugarcane juice, resulting in what is now commonly known as “table sugar.” In the 1700s, sugar cane cultivation and processing expanded globally, making sugar more accessible and affordable. The 20th century witnessed sugar shortages, leading to inflated sugar prices and prompting the search for viable alternatives [29, 30]. The utilisation of corn starch gained more interest as this was a readily available source of glucose. However, glucose is not as sweet as sucrose, making it a less desirable alternative. Yet, in the 1960s, the discovery of a xylose isomerase enzyme enabled the conversion of glucose into fructose, leading to the development of high‐fructose corn syrup (HFCS). Since the late 1970s, manufacturers optimised the HFCS production process, enabling them to increase the fructose content. This resulted in the production of HFCS containing 55% fructose and 45% glucose. With a composition that is nearly similar to sucrose (50% fructose and 50% glucose), HFCS has displaced sucrose due to its high sweetness and lower cost, leading to widespread application in nearly all processed foods [30, 31, 32].

Shift towards caloric sweeteners consumption and growing interest in deleterious effects of sugars

In the past few decades, there has been a substantial increase in yearly dietary sugar consumption. As previously mentioned, this is largely driven by the widespread use of cheap caloric sweeteners, particularly HFCS, at an increased daily caloric intake [12, 33]. Consequently, the daily fructose intake of adolescents and adults in the United States (US) between 1977–1978 and 2008 increased significantly by almost 50 per cent [34]. More recently, between 2001 and 2018, a significant decline was observed in the consumption of added sugars among US adults aged 19–50 years, with the proportion of total calories per day decreasing from 16.2% to 12.7% [35]. However, this remains above the recommended limit of < 10% of calories per day, as outlined by the World Health Organization (WHO) international guidelines [11].

In addition to the increase in caloric sweetener consumption, there has been a rapid global increase in the prevalence of obesity and associated comorbidities such as dyslipidaemia [36], T2D [37] and MAFLD [38]. These trends cause both a substantial clinical and economic burden. Therefore, it is crucial to comprehensively study the causal factors and pathophysiology of these NCDs, in order to mitigate their prevalence and associated clinical and economic burden. Notably, the increased NCD prevalence aligns with the rise in caloric sweetener consumption, suggesting causality [15, 39, 40, 41]. In this regard, the role of dietary fructose is of particular interest, considering its increased consumption and distinct metabolism. Moreover, understanding the role of the gut microbiota in sugar metabolism will help to identify new targets for improving dietary and microbial‐based interventions.

Glycaemic sugar metabolism by the host

Digestion of carbohydrates into monosaccharides

The direct ingestion of sugars allows them to reach the small intestine (SI) without the need for additional breakdown along their way through the gastrointestinal tract. As the SI only absorbs sugars as monosaccharides, hydrolysis of disaccharides by disaccharidases located on the brush border membrane of the small intestinal enterocytes is necessary [42, 43]. Alternatively, sugars can be derived from the enzymatic breakdown of complex carbohydrates, glycogen and starches, facilitated by salivary and pancreatic α‐amylases. This breakdown of complex carbohydrates by α‐amylases results in the formation of maltose, the trisaccharide maltotriose, and branched oligosaccharides called α‐limit dextrins [42, 43]. These breakdown products are subsequently hydrolysed into absorbable monosaccharides by disaccharidases. The sucrase‐isomaltase complex contains two enzymatic subunits; sucrase and isomaltase. Sucrase hydrolyses sucrose into glucose and fructose, whereas isomaltase can break down the α‐limit dextrins into glucose monomers, as it hydrolyses the amylase‐resistant α‐1,6‐glycosidic bonds [42, 43] (Fig. 1). The disaccharidases lactase and maltase break down lactose and maltose into their constituent monosaccharides, respectively [42, 43] (Fig. 1).

Fig. 1.

Digestion of sugars in the small intestine. Disaccharidases are located on the brush border membrane of the small intestinal enterocytes and include the sucrase‐isomaltase complex, maltase and lactase. These enzymes hydrolyse disaccharides, maltotriose and α‐limit dextrins into monosaccharides. The sucrase‐isomaltase complex contains 2 enzymatic subunits; sucrase and isomaltase. Sucrase is responsible for converting sucrose into glucose and fructose, while isomaltase breaks down α‐limit dextrins and maltotriose into glucose monomers. The disaccharidases lactase and maltase act on lactose and maltose, respectively, breaking them down into their monosaccharide components. Following these hydrolytic processes, the resulting monosaccharides can be absorbed by the small intestine.

Intestinal absorption of glycaemic monosaccharides

Monosaccharide absorption and transport across the small intestinal epithelium occurs through different transporters (Fig. 2). Glucose and galactose are actively transported across the brush border membrane through the sodium‐dependent glucose/galactose co‐transporter sodium‐glucose transporter 1 (SGLT1). Subsequently, these monosaccharides are transported passively across the basolateral membrane into the portal circulation, facilitated by glucose transporter 2 (GLUT2) [44, 45]. SGLT1 exhibits a high affinity (Km ~ 0.5 and ~ 1 mm) but a low capacity for glucose and galactose transport, respectively [44, 46, 47]. However, at high luminal glucose concentrations, SGLT1‐mediated active glucose transport becomes saturated [48]. Nevertheless, this does not impede glucose absorption. This is likely due to the suggested apical recruitment of the low‐affinity (Km ~ 17‐20 mm) [44, 49, 50], high‐capacity GLUT2 in response to high luminal glucose concentrations [51, 52]. Fructose absorption across the brush border membrane is passively mediated by glucose transporter 5 (GLUT5) (Km ~ 6‐15 mm) [53, 54]. Fructose is transported across the basolateral membrane by GLUT2 (Km ~ 76 mm) [44, 49, 53]. One study has proposed a potential role for GLUT5 in basolateral fructose transportation, although this has not been further confirmed in humans [55].

Fig. 2.

Monosaccharide absorption and intestinal glucose and fructose metabolism. Glucose and galactose transport across the brush border membrane is facilitated by the active sodium‐glucose transporter 1 (SGLT1). At high luminal glucose levels, apical recruitment of the passive glucose transporter 2 (GLUT2) is suggested, contributing to the transport of glucose and galactose across the brush border membrane. Fructose is passively transported across the brush border membrane by glucose transporter 5 (GLUT5). All monosaccharides are passively transported across the basolateral membrane into the portal circulation by GLUT2. However, fructose and glucose can be metabolised by the small intestine (SI), before entering the portal circulation. Fructose metabolism by the small intestine generates glucose and organic acids such as lactate. Nevertheless, fructose absorption and clearance is saturated at high luminal fructose levels. Therefore, at high luminal fructose levels, some fructose remains unabsorbed. The unabsorbed fructose can be fermented by the distal small intestinal microbiota to produce metabolites such as ethanol or acetate and it will also be freely available for the colonic microbiota. DHAP, dihydroxyacetone phosphate; F1,6BP, fructose‐1,6‐biphosphate; F1P, fructose‐1‐phosphate; F6P, fructose‐6‐phosphate; FBPase, fructose‐1,6‐biphosphatase; G6P, glucose‐6‐phosphate; G6Pase, glucose‐6‐phosphatase; GA, glyceraldehyde; GADP, glyceraldehyde‐3‐phosphate; GPI, glucose‐6‐phosphate isomerase; HK, hexokinase; KHK, ketohexokinase; LDH, lactate dehydrogenase; TrioK, triose kinase.

Glycaemic monosaccharide metabolism

Upon absorption in the SI, monosaccharide metabolism occurs throughout different parts of the body. Glucose serves as the primary energy source and glucose homeostasis is vital for maintaining energy balance and cellular function. Therefore, in contrast to other dietary sugars, systemic glucose levels are very tightly regulated by hormones such as insulin and glucagon [56]. Glycolysis commences with the phosphorylation of glucose by hexokinase (HK), forming glucose‐6‐phosphate (G6P), which is isomerised to fructose‐6‐phosphate (F6P). Next, F6P is phosphorylated into fructose‐1,6‐bisphosphate (F1,6BP) by phosphofructokinase 1 (PFK1). This is the main rate‐limiting step of glycolysis, regulating energy and metabolic homeostasis [57]. F1,6BP is cleaved into dihydroxyacetone phosphate (DHAP) and glyceraldehyde‐3‐phosphate (GA3P). DHAP and GA3P continue along the glycolytic pathway, ultimately leading to the end product of glycolysis, pyruvate. Pyruvate will enter the mitochondria for further oxidation and energy production. Galactose follows a metabolic pathway that is highly similar to that of glucose. Initially, galactose is converted to G6P in the liver via the Leloir pathway. This process uses UDP‐glucose as a co‐substrate. G6P then enters the glycolytic pathway for energy production or conversion to glycogen for energy storage [57, 58]. Fructolysis differs substantially from glycolysis. Hepatic fructose metabolism initiates with ketohexokinase (KHK)‐mediated phosphorylation, yielding fructose‐1‐phosphate (F1P) [59]. Aldolase B immediately cleaves F1P into DHAP and GA3P. This distinctive pathway enables fructolysis to bypass the main rate‐limiting step of glycolysis, leading to unregulated hepatic fructose metabolism [60]. Unregulated hepatic fructose metabolism by the host can have potential deleterious metabolic effects, prompting our emphasis on this process and its potential impact on the host's metabolic health. As this process utilises adenosine triphosphate (ATP), the rapid hepatic metabolism of fructose results in ATP depletion and an unregulated production of acetyl‐CoA through mitochondrial pyruvate oxidation. Excessive acetyl‐CoA generation exceeds the tricarboxylic acid (TCA) cycle's metabolising capacity, causing subsequent citrate accumulation, which serves as a substrate for de novo lipogenesis (DNL) [61]. ATP depletion will cause the accumulation of adenosine monophosphate and eventual uric acid formation [62, 63]. Uric acid production induces mitochondrial oxidative stress, which in turn leads to citrate release and the activation of lipogenic enzymes—ATP‐citrate lyase and fatty acid synthase—thus promoting DNL [64]. In addition, Zhao et al. [65] demonstrated that hepatic fructose metabolism activates transcription factors which can promote DNL.

Interestingly, the liver was traditionally considered as the primary site for fructose metabolism [66]. However, Jang et al. [67] demonstrated in mice that the SI metabolises the majority of physiological fructose doses into glucose and organic acids before entering the portal circulation (Fig. 2). The liver and kidneys are well‐known for their ability to perform gluconeogenesis, as they express the enzyme glucose‐6‐phosphatase (G6Pase), which dephosphorylates G6P to generate glucose. Recently, G6Pase expression was discovered in the SI of mice and humans, suggesting a gluconeogenic potential of the SI [68]. Moreover, in mice, oral fructose administration induced the GLUT5 and G6Pase genes with a more than 20‐fold increase [67]. Other genes associated with fructose metabolism, including fructose 1,6‐bisphosphatase, triose kinase and aldolase B, exhibited heightened expression upon fructose administration in small intestinal epithelium as well [67]. These findings clarify the enhanced fructose absorption and intestinal gluconeogenesis induced by fructose feeding. This is beneficial as it decreases the transit of fructose to the liver, where it serves as a fatty acid substrate and induces gluconeogenic transcription factors [69]. Thus, reduced fructose exposure to the liver protects the liver from hepatic fructose‐induced DNL [70] and hepatic insulin resistance [69]. However, the capacity of the small intestine for fructose clearance can be saturated at high fructose levels (> 1 g·kg⁻¹), resulting in direct fructose passage into the hepatic circulation [67]. Furthermore, in this condition, fructose absorption becomes saturated, making the unabsorbed fructose accessible for gut microbial fermentation (Fig. 2). This discovery is of great importance, as it opens new targets on fructose metabolism and its possible effects on host physiology.

Glycaemic sugar metabolism and the gut microbiota

Introduction to the gut microbiota and gut microbial fermentation

The gut microbiota significantly influences host physiology and disease through its impact on nutrient metabolism, including carbohydrates [18]. Defining a “healthy” gut microbiota of both the small and large intestine is difficult due to the tremendous variability of the gut microbiota and the constituent metagenome [71]. Yet, gut microbiota richness and diversity have been linked to improved metabolic health [72]. The composition of the gut microbiota is subject to different modulating factors, including mode of delivery [73], diet [74, 75], and medication use like antibiotics [75, 76], metformin [77, 78] and proton‐pump inhibitors [79]. Advances in high‐throughput sequencing and ‐omics technologies have significantly enhanced our ability to identify bacterial species, metabolic products, metatranscriptomics and metagenomics. This progress has facilitated research into the complex interplay between diet, gut microbiota and host health. The gut microbiota's fermenting potential varies among bacterial species. Hence, the composition of the gut microbiota affects its capacity to degrade simple and complex carbohydrates, requiring distinct glycolytic and fibrolytic bacterial species respectively [19]. Currently, research on gut microbiota composition and its effect on host health is primarily based on faecal samples, therefore reflecting the colonic microbiota. The colonic microbiota is renowned for its function in complex carbohydrate fermentation, resulting in the production of short‐chain fatty acids (SCFAs) [19, 80, 81]. The most abundant SCFAs—acetate, butyrate and propionate—can contribute to host metabolism, including the improvement of glucose homeostasis and lipid metabolism. Consequently, SCFAs can exert a beneficial impact on the host's metabolic health [82, 83]. While colon communities are particularly involved in complex carbohydrate fermentation, small intestinal communities primarily facilitate sugar fermentation, which seems less beneficial to the host [84]. As this review aims to provide an overview on sugar metabolism, we will focus on the role of the (SIM).

Small intestinal microbiota and glycaemic sugar metabolism

Due to its limited accessibility, the SIM remains less explored when compared to the colonic microbiota. Nevertheless, as the SI is key to sugar absorption and metabolism, it is essential to understand the role of the SIM in this process and its effects on host physiology. Zoetendal et al. [84] demonstrated a pronounced enrichment of genes encoding carbohydrate metabolic pathways and functions within the SI in ileostomy effluent samples from a healthy subject, compared to the faecal metagenome. These genes include phosphotransferase systems (PTS), which are used by bacteria for sugar uptake and phosphorylation [85]. Additionally, metabolic pathways, such as the pentose phosphate (PP) pathway, and fermentation pathways like the fermentation of lactate and propionate, were highly enriched in the SI. Metatranscriptomic analysis demonstrated heightened activity of the aforementioned metabolic processes, emphasising the SIM's central role in sugar catabolism. Zoetendal et al. [84] observed a predominant expression of genes associated with PTS transcription by Streptococci. This suggests that Streptococci are one of the primary users of available sugars within the SI. A recent study involving six ileal and colonic stoma samples from patients cured of colorectal cancer used high‐resolution untargeted mass spectrometry to examine the temporal dynamics of intestinal microbiota and metabolites during fasted and fed state [86]. There were no changes in mono‐ and disaccharides levels postprandially, suggesting immediate and complete absorption by the SI and its colonising microbiota.

Dietary sugar fermentation by the gut microbiota can yield diverse metabolites, contingent upon the fermentation pathway and potential cross‐feeding among bacteria. The different glycolytic pathways used by bacteria are the Embden‐Meyerhof‐Parnas (EMP), Entner‐Doudoroff or PP pathway [87]. In the small intestine, lactic acid fermentation is a prominent process driven by lactic acid bacteria which are abundant in the SI, such as the aforementioned Streptococci [24]. These bacteria play a key role in sugar fermentation through lactic acid fermentation, wherein sugars serve as a fermentation substrate to produce lactate and other fermentation products. Homofermentative lactic acid bacteria generate lactate by fermentation of sugars through the glycolytic EMP pathway [87, 88, 89]. Examples of homofermentative lactic acid bacteria encompass Streptococci, Lactococci and some Lactobacilli [87, 88, 89]. Heterofermentative lactic acid bacteria ferment sugar into lactate, ethanol or acetate, and CO₂ through the glycolytic PP pathway, followed by the phosphoketolase pathway [87, 88, 89]. Heterofermentative lactic acid bacteria predominantly include Leuconostoc, Oenococcus, Weisella and some Lactobacilli, all belonging to the Lactobacillaceae family [87, 88, 89]. Lactobacillaceae and Streptococcaeceae are among the dominant bacterial Firmicute families in the SI [24, 90, 91], indicating that lactic acid fermentation predominantly occurs in the SI.

As illustrated, sugar fermentation by lactic acid bacteria can produce fermentation products such as lactate, ethanol and acetate. This implies that sugar fermentation by the gut microbiota can lead to endogenous ethanol production. Ethanol has been shown to stimulate DNL and decrease the oxidation of free fatty acids, causing the accumulation of lipids in the liver [92]. Recently, Meijnikman et al. demonstrated significantly higher ethanol concentrations in humans with MAFLD or metabolic dysfunction‐associated steatohepatitis (MASH), which was attributed to increased endogenous ethanol production by the gut microbiota [93]. This evidence highlights the potential role of the gut microbiota in ethanol production from sugar fermentation, which may contribute to the development of MAFLD/MASH. Moreover, acetate, another sugar fermentation product, can also serve as a substrate for DNL. It has been demonstrated that high fructose doses (≥ 1 g·kg⁻¹) can saturate epithelial fructose absorption and metabolism in the SI [67], which may result in the availability of fructose for microbial fermentation in the distal part of the small intestine and colon. Hence, the SIM could potentially ferment the unabsorbed fructose, producing deleterious metabolites such as ethanol and acetate [87]. Altogether, these findings suggest a negative role of the SIM in sugar fermentation, as it potentially generates additional substrates for fatty acid synthesis, thereby increasing circulating fats which can contribute to the development of obesity and NCDs. This illustrates that sugar fermentation is not beneficial to the host, in contrast to complex carbohydrate fermentation.

Dietary sugar—gut microbiota—host effects

As previously described, the gut microbiota has a profound impact on host physiology through the fermentation of sugars and the produced metabolites. Conversely, diet exerts a significant impact on shaping gut microbial composition, which, in turn, is crucial for its fermenting potential [19, 94]. Considering this interdependent relationship, several studies have provided evidence for a causal relationship between dietary sugars, the gut microbiota and host health [95, 96, 97, 98, 99].

In human twins, obesity was associated with a decreased microbial diversity and an altered representation of metabolic pathways in the gut microbiome of obese individuals, including an enrichment for PTS [100]. This suggests a potential causal relationship between gut microbial sugar metabolism and obesity. Analysis of human gut microbial composition in obese and non‐obese individuals revealed a correlation between gut microbial richness and adiposity, insulin resistance, and dyslipidaemia [101]. As diet is an important modulator of the gut microbiota, it could be a driving factor of this causal relationship.

Evidence supporting this proposed causality has been provided by several studies. Dietary sugar, particularly fructose, has been found to alter gut microbial composition, resulting in gut dysbiosis [95]. Underscoring this evidence, in rats, a high‐sugar diet, irrespective of fat content, resulted in rapid gut dysbiosis, gut inflammation, and associated accumulation of body fat [96]. In addition, a study conducted on mice that were subjected to either a high‐glucose or high‐fructose diet revealed a decreased bacterial diversity, including a reduced Bacteroidetes abundance and an increased Proteobacteria abundance [97]. Simultaneously, these mice exhibited increased intestinal permeability and gut inflammation, as well as hepatic inflammation and lipid accumulation. Moreover, a multi‐omics study in humans revealed a significant correlation between faecal monosaccharide levels, including fructose and galactose, and insulin resistance [98]. Additionally, these faecal monosaccharides were increased in patients with obesity, metabolic syndrome and prediabetes and were positively associated with carbohydrate metabolism and transport pathways, including PTS. Furthermore, a positive correlation was identified between the faecal monosaccharides associated with insulin resistance and certain bacterial genera. Dorea, belonging to the Lachnospiraceae family, demonstrated the strongest correlation. In contrast, a negative correlation was observed between the majority of these faecal monosaccharides and the genera associated with insulin sensitivity, including Bacteroides and Alistipes [98]. Collectively, these findings suggest causality between a high‐sugar diet, gut dysbiosis and metabolic disease. However, these studies are based on faecal samples; therefore, they cannot be directly related to the SIM.

Given the technical difficulty of studying SIM composition, only few studies have provided evidence regarding diet, SIM composition and host effects. In piglets, fructose supplementation resulted in ileal (and colonic) dysbiosis, accompanied by a decreased expression of the three main tight junction genes: ZO1, OCLN and CLDN1 [99]. Tight junction impairment causes increased gut permeability, which could provoke an inflammatory response and subsequent metabolic dysfunction. However, this was not demonstrated in this study, possibly due to the short follow‐up time. A study involving healthy individuals found that a short‐term switch from a high‐fibre diet to a low‐fibre and high‐sugar diet led to decreased microbial diversity in the SI and correlated with increased intestinal permeability [102].

Moreover, in rats receiving high glucose infusion or a high oral glucose diet for 2 weeks, a clear increase in serum levels of inflammation markers IL‐6 and TNF‐α was observed, along with mucosal injury of the jejunum and hepatocyte steatosis. In addition, these rats lost gut microbial diversity [103]. In mice subjected to a high‐fat diet, oral administration of Alistipes indistinctus resulted in decreased postprandial blood glucose levels and improved insulin resistance [98]. Analysis of caecal metabolites showed substantial alterations by the administration of A. indistinctus, characterised by a reduction in fructose levels along with several other carbohydrates. Fructose levels in serum were also reduced. Furthermore, a positive correlation was identified between the area under the curve of the insulin tolerance test and caecal monosaccharides levels of glucose, fructose and mannose. These observations suggest a pivotal role for A. Indistinctus in modulating small intestinal sugar metabolism, potentially mitigating insulin resistance.

Future

Novel small intestinal microbiota sampling techniques and in vitro models

To date, more extensive research has been conducted on colonic microbiota using faecal samples compared to the SIM, due to the challenging and invasive nature of sampling the SI. Still, the SI is the main site of sugar metabolism and absorption with the involvement of the SIM. In vitro as well as human models have been proposed to increase our understanding of the small intestinal tract. However, to gain further insight into these processes within the SI, novel sampling techniques are required. These should include the recently published ingestible capsule that can sample different parts of the intestine [104] and dynamic (stable isotope‐based) models [105].

In vitro models

Static in vitro models, such as intestinal cell monolayers and co‐culture models, are commonly used to investigate specific aspects of the interaction between host cells and the gut microbiota, including nutrient absorption or metabolite production [106]. Nevertheless, these models are of limited use for investigating diet‐host–microbe interactions within the SI, as they are unable to replicate the complex and dynamic environment of the SI. Several dynamic in vitro models have been developed to mimic the SI, including the TNO gastrointestinal model 1 (TIM‐1) [107, 108], the smallest intestine (TSI) [109] and the Engineered Stomach and small INtestine (ESIN) model [110]. These models encompass computer‐controlled, multicompartmental, dynamic, bioreactor models, which mimic the upper gastrointestinal tract. Advantages of these dynamic in vitro models, compared to static models, include their ability to simulate gastrointestinal transit time, variable pH levels and secretion of digestive fluids. Combined with stable isotope probing [105], these models can be applied for studying SIM function and SIM‐host interaction. Nevertheless, the development and validation of these bioreactors, along with their capacity to accurately simulate the SIM remain challenging [111]. Firstly, obtaining a suitable inoculum from healthy donors to validate the model against in vivo conditions is limited due to restricted accessibility. Secondly, it is difficult to reproduce the increasing bacterial load and the dynamic changes in microbial profiles along the SI, as well as account for inter‐individual variations. Lastly, the management of oxygen levels is technically demanding, as it has a profound impact on both obligate aerobes and facultative anaerobes within the small intestinal community [111].

More recently, small intestinal organoids have been applied as an in vitro model, mimicking in vivo conditions [112, 113]. Although this approach holds great potential for facilitating diet‐microbiota‐host interaction studies, the use of intestinal organoids presents multiple limitations. One significant limitation of small intestinal organoids is that they lack the full diversity of cell types and physical structure of the actual SI [113, 114, 115]. Moreover, the organoids do not resemble the dynamic properties of the human SI, such as peristalsis, and it is challenging to colonise the organoids with the complex diversity of microbial communities [113]. Although it is unlikely that in vitro models can fully simulate or replace human models, they are important for proof‐of‐concept studies and are refined continuously.

Animal models

Current knowledge of diet‐host–microbe interactions largely relies on animal models, particularly mice. This is important, because there are significant anatomical and physiological differences between the gastrointestinal tract of humans and mice, along with notable differences in gut microbiota composition and function [116]. These differences present important limitations for the application of mice models for studying SIM function and SIM‐host interactions in humans.

One notable difference is that the human mucosal surface of the small intestine contains plicae circularis‐circular folds that provide an increase of the surface area. This is in contrast to the smooth mucosal surface of the small intestine in mice. Plicae circularis in the human small intestine create a unique habitat for mucus‐associated bacteria, which is absent in mice [116]. Furthermore, mice exhibit a faster gastrointestinal transit time, lower intestinal pH levels and a relatively larger size of the small intestine (1500 cm·kg⁻¹ in mice vs. 10 cm·kg⁻¹ in humans) [116, 117]. These anatomical and physiological differences could therefore contribute to variations in the microbial composition of mice and humans. Despite the existence of significant phylogenetic overlap between the bacterial communities present in the intestines of humans and mice, there is a marked discrepancy in the relative abundance of common genera. Only a small fraction of bacterial genes exhibit similarity in both mice and humans [118, 119]. This underscores the necessity for the advancement and utilisation of novel dynamic in vitro and human‐based models.

Human models

Invasive (biopsy‐based) sampling is often required in humans to accurately obtain small intestinal samples. Recently, multiple novel human gastrointestinal sampling capsules have been developed which enable non‐invasive small intestinal luminal sampling [104, 120, 121, 122]. However, utilising these capsules for assessing microbial composition and fermentation products presents some challenges. For example, capsule excretion through the faeces may take several days, resulting in ongoing degradation of dietary components. To address this issue, a quenching reagent was developed which enables successful stabilisation of microbial composition, fermentation of dietary fibres, and production of SCFAs for 48 h [123]. The precise selection of sampling location is difficult, as these capsules depend on pH levels and/or temperature for sampling site identification, due to a pH‐dependent enteric coating or pH and temperature sensors [104, 120, 121, 122]. Other important limitations include the limited quantity of sample obtained when using these capsules, and the substantial costs associated with their utilisation.

Implications for further research

As previously stated, we are now in a phase to move towards causality. Further investigation into the small intestinal host and microbial metabolism is needed in order to achieve this. Multiple methods have been developed that could facilitate future studies in this area. An overview of current trials regarding the SIM, covering novel sampling techniques and the influence of dietary carbohydrates, is provided (Table 1). Due to the limited number of trials specifically investigating the relationship between dietary sugars and the SIM, this table includes trials pertaining to the SIM and carbohydrates in general. This underscores the pressing need for trials that further explore the relationship between dietary sugars and the SIM.

Table 1.

Overview of current trials investigating small intestinal microbiota, including novel sampling techniques and the influence of dietary carbohydrates. Extracted from the WHO international clinical trials registry platform and the ClinicalTrials.gov database.

Study title—study ID	Study type	Main objective	Target sample size	Study site	Study start date and recruitment status
MICRO‐study: The IntelliCap® System as a Gastrointestinal Fluid Sampling Tool – NCT02351375	Interventional, randomised	Evaluate the IntelliCap® System as a tool to study changes in small intestinal microbiota composition after consuming a three‐day high‐protein versus a high‐carbohydrate diet, each preceded by a washout diet	12	Wageningen University, Wageningen, Gelderland, the Nederlands	November 2014, completed
Small Bowel Microbiota Characterization in Healthy Individuals Before and After Consumption of a Western Diet – NCT03266536	Interventional, non‐randomised	Analyse transcriptional changes in gut microbiota present in stool of healthy participants at baseline and after consumption of a Western diet for 7 days. Small bowel aspirates and biopsies are retrieved pre‐ and post‐intervention	16	Mayo Clinic, Rochester, Minnesota, United States	January 2017, completed
Comparison of the Microbial Composition in Lean and Obese Subjects (DUPLO) – NCT03075228	Observational, cross‐sectional cohort study	Explore and compare the upper GI microbiota composition in lean and obese subjects, using The IntelliCap® System, in order to generate new leads for development of products that may target the upper GI microbiota community or specific species thereof, which may impact the maintenance of metabolic homeostasis	10	NIZO food research BV, Ede, the Netherlands	April 2017, completed
Feasibility of a New Diagnostic Device to Assess Small Intestinal Dysbiosis in Routine Clinical Setting – NCT04910815	Interventional, randomised	To determine if the Atmo Gas CapsuleR can be used to identify increased numbers and a change of the composition of microbiota or micro‐organisms in the gut to assess small intestinal dysbiosis	150	Princess Alexandra Hospital, Woolloongabba, Queensland, Australia	July 2021, recruiting
Studying the Impact of a Low Carbohydrate Diet on the small intestinal microbiota – NCT04976686	Interventional, non‐randomised	Analyse the influence of a low carbohydrate diet on microbiota composition of stomal fluids of probands with a ileo‐ or colostoma that are otherwise in good general health	20	University Hospital Inselspital Bern, Switzerland	November 2021, recruiting
Elucidating the Role of Human Small Intestine Microbiota in Interpersonal Differences in Glycemic Responses Upon Consumption of Food Products. (GLYSIMI) – NTC05120661	Interventional, randomised	To investigate the role of the human small intestine microbiota in regulating postprandial glycemic responses towards food products. Participants will be intubated with a naso‐jejunum catheter for additional analysis including (bacterial) degradation products	20	Wageningen University, Wageningen, Gelderland, the Nederlands	December 2021, recruiting
Feasability study of an Innovative Medical Device for Sampling the Contents of the Small Intestine. (DIGEST) – NCT05477069	Interventional, non‐randomised	Demonstrate the safety and performance of an innovative medical device; an ingestible pill for intestinal microbiota collection. Multi‐omics analysis will be performed on intestinal fluid samples from the capsules and on faeces	15	University Hospital Grenoble Alpes, Grenoble, France	November 2022, recruiting
Use of the Small Intestine Microbiome Aspiration (SIMBA) Capsule to Detect a Dietary Intervention in the Small Intestine – NCT04489329	Interventional, non‐randomised	Proof of concept study to validate the ability of a capsule device to gather samples from the small bowel for microbiome analysis in adults and to detect dietary changes from simultaneous ingestion of a probiotic	20	Cumming School of Medicine, Calgary, Alberta, Canada	December 2020, completed
Evaluation of the Small Intestine Microbiome Aspiration (SIMBA) Capsule for Small Intestinal Dysbiosis – NCT05633706	Observational, cross‐sectional cohort study	The SIMBA Capsule is a small, single‐use, ingestible capsule for the non‐invasive sampling of small bowel contents. The study will compare the microbial and metabolomics analysis from the sample collected with the capsule series, to same‐participant symptom questionnaires and stool microbial analysis	150	Nimble Science, Calgary, Alberta, Canada	January 2023, recruiting

Once the causal relationships between sugar metabolism, gut microbiota and host diseases are comprehensively understood, potential therapeutic options can be explored. Enhancing our understanding of sugar metabolism could potentially lead to personalised nutrition strategies. Clinical trials investigating the potential of faecal microbiota transplantation (FMT) in treating NCDs have previously been conducted [124, 125, 126, 127, 128, 129, 130]. However, these trials used different FMT donors and different modes of administration (fresh faeces vs faecal capsules). A deeper understanding of the impact of donor FMT on SIM could ultimately lead to the initiation of future clinical trials focused on therapeutic interventions for modulating SIM. Such interventions may encompass SIM transplantation.

In conclusion, addressing the ongoing pandemic of obesity and NCD requires extensive research regarding SIM and sugar metabolism. Further development of non‐invasive sampling techniques and novel in vitro models will help to comprehensively study SIM composition and fermentation dynamics. A more profound understanding of the complex processes of host and microbial sugar metabolism will promote the development of novel therapeutic strategies for the treatment of obesity and the prevention of NCDs.

Author contributions

FHMW, IA, MR‐M and MN conceptualised the project and wrote the review. FHMW created the figures. All authors read and approved the final version of the manuscript.

Conflict of interest

MN is co‐founder and member of the Scientific Advisory Board of Caelus Pharmaceuticals and Advanced Microbiota Therapeutics, the Netherlands. None of these are directly relevant to the current paper. There are no patents, products in development or marketed products to declare. The other authors declare no conflict of interest.