Diets, Gut Microbiota and Metabolites

Abstract

The gut microbiota refers to the gross collection of microorganisms, estimated trillions of them, which reside within the gut and play crucial roles in the absorption and digestion of dietary nutrients. In the past decades, the new generation ‘omics’ (metagenomics, transcriptomics, proteomics, and metabolomics) technologies made it possible to precisely identify microbiota and metabolites and describe their variability between individuals, populations and even different time points within the same subjects. With massive efforts made, it is now generally accepted that the gut microbiota is a dynamically changing population, whose composition is influenced by the hosts’ health conditions and lifestyles. Diet is one of the major contributors to shaping the gut microbiota. The components in the diets vary in different countries, religions, and populations. Some special diets have been adopted by people for hundreds of years aiming for better health, while the underlying mechanisms remain largely unknown. Recent studies based on volunteers or diet-treated animals demonstrated that diets can greatly and rapidly change the gut microbiota. The unique pattern of the nutrients from the diets and their metabolites produced by the gut microbiota has been linked with the occurrence of diseases, including obesity, diabetes, nonalcoholic fatty liver disease, cardiovascular disease, neural diseases, and more. This review will summarize the recent progress and current understanding of the effects of different dietary patterns on the composition of gut microbiota, bacterial metabolites, and their effects on the host's metabolism.

Introduction

There are more than 160 species of microorganisms in the human gastrointestinal tract (Laterza et al. 2016). Piles of evidence had demonstrated that the disorder of gut microbiota might result in diseases, such as obesity (Ley et al. 2005), type 2 diabetes mellitus (T2DM) (Pascale et al. 2019), nonalcoholic fatty liver disease (NAFLD) (Ma et al. 2017), cardiovascular disease (CVD) (Tang et al. 2019), neural diseases (Olson et al. 2018), polycystic ovary syndrome (Qi et al. 2019), and cancer (Raza et al. 2019). Accumulating evidence, which was well reviewed by Wu et al. (2021), suggests that the metabolites produced by the gut microbiota may be one of the major contributors. These metabolites, including lipopolysaccharide (LPS), branched-chain amino acid (BCAA), short-chain fatty acid (SCFA), trimethylamine (TMA), secondary bile acid (sBA), and so on, are often associated with the metabolic states, activation of inflammation, and regulation of the hosts’ genes involved in energy storage and consumption (Blaut 2015; Gentile and Weir 2018; Manco et al. 2010; Neis et al. 2015; Tsukumo et al. 2009; Zhu et al. 2016).

Diets have a great influence on the gut microbiota (Bibbo et al. 2016; Requena et al. 2018). Due to the availability, tradition, religion, and special purposes related to diseases or lifestyles, the nutrients in the diets vary in different countries and populations. Among the popular diets studied, the different proportion of nutrients features these diets and was believed to contribute to physiological consequence in the consumers of these diets, mainly the ketogenic diet (KD), the high-fat diet (HFD), the western diet (WD), the high-glucose diet (HGD), the high-fructose diet (HFrD), the vegan diet (VD), the vegetarian diet (VeD), the Mediterranean diet (MD), and the gluten-free diet (GFD) (Rinninella et al. 2019). KD contains the highest proportion of fat (generally over 70%) and the lowest proportion of carbohydrates (less than 10%) among the aforementioned diets (Veech 2004). Both HFD and WD have higher levels of fat than other diets except KD (Bortolin et al. 2018; Woodie and Blythe 2018), while HGD and HFrD contain high levels of carbohydrates (Johnston et al. 2013). VD, VeD and MD are featured with a high level of dietary fiber but low in animal-derived fat and protein (Haddad et al. 1999; Kastorini et al. 2011). GFD is a diet lacking a specific class of proteins and gluten (Biesiekierski 2017). The dietary fats, carbohydrates, proteins and dietary fibers were believed to impact gut microbiota (Candido et al. 2018; Deng et al. 2022; Kim et al. 2016). In general, the composition of the gut microbiota changes rapidly and frequently and shifts over one to two days when the hosts switch their diets (David et al. 2014; Walker et al. 2011; Wu et al. 2011). Long-term consumption of these diets plays a dominant role in shaping the hosts' gut microbiota and forming a stable and distinguished enterotype (Wu et al. 2011). For example, HFD increases the abundance of Firmicutes but decreases the abundance of Verrucomicrobia (Bisanz et al. 2019). On the contrary, KD decreases the abundance of Firmicutes but increases the abundance of Verrucomicrobia (Xie et al. 2017; Zhang et al. 2018b). In the last decade, tremendous efforts have been made to extend our knowledge of how these diets impact the gut microbiota and the host's metabolism. In this review, we will summarize the large body of data on how these diets affect gut microbiota and metabolites. We will also discuss how the metabolic status of the hosts will be impacted by these diets and the underlying mechanisms.

High-Fat Diet

HFD refers to the dietary pattern with the fat content generally being 40–60%. Consumption of HFD profiles a pattern on gut microbiota and results in a different collection of bacterial metabolites, which has been proven to contribute to the prevalence of overweight, and lead to obesity, T2DM, and CVD (Stocks et al. 2013; Wan et al. 2019; Woodie and Blythe 2018).

Extensive evidence has demonstrated the influence of HFD consumption on the composition of gut microbiota. At the phylum level, HFD consumption decreases the abundance of Verrucomicrobia (Everard et al. 2014), but increases the abundance of Proteobacteria (Hildebrandt et al. 2009). At the genus level, the abundance of Bilophila, Butyrivibrio, Parabacteroides, and Roseburia were increased, but the abundance of Allobaculum, Coprococcus, Eubacterium, Lactobacillus, and Prevotella were decreased by HFD consumption (Everard et al. 2014). At the species level, HFD consumption increases the abundance of Bilophila wadsworthia (Devkota et al. 2012), and decreases the abundance of Bacteroides fragilis (Sun et al. 2018) and Akkermansia muciniphila (Schneeberger et al. 2015). However, the reported effects of HFD on microbiota vary across studies. The reason might be the different sources of major nutrients in the HFD, different times on HFD, different animal handling policies, etc. To find out the robust and reproducible changes in microbial composition induced by HFD feeding, Bisanz et al. performed a meta-analysis based on 27 studies involving 1, 101 samples (including mouse and human samples) (Bisanz et al. 2019). Their analysis demonstrated that HFD consumption induces reproducible shifts in the gut microbiota and revealed an increased ratio of Firmicutes: Bacteroidetes in all of those analyzed datasets from mice. This increased ratio of Firmicutes: Bacteroidetes was later reaffirmed by Munch et al. when they analyzed 16s ribosomal RNA of the fecal samples from mice fed with a chow diet (CD) or HFD for 30 weeks (Munch et al. 2019). The impact of HFD on human gut microbiota is more complicated and addresses more debates without a consensus (Magne et al. 2020). Another concern about HFD-induced changes in microbiota is whether the changes in the microbial composition are directly caused by HFD consumption or the obese state of the hosts resulting from HFD consumption. Hildebrandt et al. distinguished these two scenarios by using resistin-like molecule β (RELMβ) knockout mice, which are resistant to diet-induced obesity, and they concluded that the high-fat diet itself, and not the obese state, was responsible for the altered microbiota (Hildebrandt et al. 2009).

Gut microbiota can impact the host through the metabolites they produced, including LPS, BCAAs, SCFAs, TMA, sBA, and so on (Gentile and Weir 2018; Manco et al. 2010; Neis et al. 2015; Zhu et al. 2016).

HFD consumption increases the circulating level of LPS and BCAAs by enhancing intestinal permeability and decreases SCFA by suppressing the abundance of SCFA-producing bacteria such as Akkermansia muciniphila (Alzaben et al. 2015; Cani et al. 2008). LPS is mainly produced by Gram-negative bacteria (Kirkland and Ziegler 1984). Previous studies have shown that high LPS levels would cause subclinical inflammation, insulin resistance, and an increase in fat mass (Horton et al. 2014; Pedersen et al. 2016). In the liver, LPS activates nuclear factor-κB (NF-κB) and myeloid differentiation factor 88 (MyD88), and leads to NAFLD (Ma et al. 2017). In adipocytes, LPS will cause insulin resistance by activating the MyD88- interleukin 1 receptor associated kinase (IRAK)-tumor necrosis factor receptor associated factor 6 (TRAF6)-transforming growth factor β activated kinase 1 (TAK1)-insulin receptor substrate 1/2 (IRS1/2) signaling axis (Saad et al. 2016). BCAAs, including valine, leucine, and isoleucine, mainly come from food and intestinal flora. BCAAs contribute to the development of obesity-associated insulin resistance in humans and rodents (Goffredo et al. 2017; Newgard et al. 2009), which are associated with the progression of obesity-related metabolic disorders, including T2DM (Asghari et al. 2018) and NAFLD (Li et al. 2013). There are two proposed mechanisms by which BCAAs may impair insulin sensitivity (Newgard et al. 2009). One is that BCAAs activate mammalian target of rapamycin (mTOR) signaling, and they lead to insulin resistance. Another proposed mechanism is that the increased BCAAs turnover drives the production of toxic mitochondrial BCAAs catabolites (e.g., propionyl CoA, succinyl CoA, branched-chain keto acids), which are in turn proposed to impair mitochondrial oxidative metabolism and thereby induce mitochondrial stress and lead to insulin resistance (Asghari et al. 2018).

HFD consumption decreases the circulating level of SCFAs by suppressing the abundance of SCFAs-producing bacteria, Akkermansia Muciniphila (Alzaben et al. 2015; Cani et al. 2008; Derrien et al. 2004). The bacteria ferment and degrade indigestible carbohydrates to produce SCFAs, including acetate, propionate, and butyrate (Macfarlane and Macfarlane 2011). It has been demonstrated that propionate and butyrate concentrations correlate inversely with the risk of obesity, insulin resistance, and NAFLD (Ampong et al. 2020). Mechanistically, the SCFAs bind to their receptors and increase the production of glucagon-like peptide-1(GLP-1) and peptide tyrosine tyrosine, which affect host's energy balance and lipid metabolism (Hernandez et al. 2019; Koh et al. 2016; Liu et al. 2020; Sircana et al. 2018).

With the extensive research on gut microbiota in the context of HFD consumption, it seems safe to say that HFD consumption can rapidly and reproducibly alter the mouse's gut microbiota and metabolites, which have a major impact on both immunological and metabolic status of the hosts (Table 1).

Table 1.

The impacts of HFD on gut microbiota, secondary metabolites and metabolic status

	Microbiota			Secondary metabolites	Metabolic status
	Phylum	Genus	Species
HFD	Firmicutes↑ Proteobacteria↑ Bacteroidetes↓ Verrucomicrobia↓	Bilophila↑ Butyrivibrio↑ Parabacteroides↑ Roseburia↑ Allobaculum↓ Coprococcus↓ Eubacterium↓ Lactobacillus↓ Prevotella↓	B. wadsworthia↑ B. fragilis↓ A. Muciniphila↓	LPS↑ BCAA↑ SCFA↓	Subclinical inflammation↑ Insulin resistance↑ Adipose mass↑ Metabolic disorders↑ T2DM↑ NAFLD↑

HFD high fat diet, LPS lipopolysaccharide, BCAA branched chain amino acid, SCFA short chain fatty acid, T2DM type 2 diabetes mellitus, NAFLD Nonalcoholic fatty liver disease

Western Diet

WD is a typical diet pattern in western countries. It is high in both saturated fats (> 40%) and refined carbohydrates (> 40%) and has higher efficiency to induce obesity, increase visceral adipose tissue, hepatic steatosis, inflammation, fasting hyperglycemia, and dyslipidemia in rats compared to HFD mentioned above (Bortolin et al. 2018; Tiniakos et al. 2010).

WD consumption has adverse effects on gut microbiota, which include disorder of intestinal flora, damage of intestinal mucosal, increased intestinal permeability, and consequent inflammation (Chassaing et al. 2015; Schroeder et al. 2018; Zinocker and Lindseth 2018). In 2021, Low et al. comprehensively compared the gut microbiota between the mice fed with WD and normal diets and found that these changes are largely reversible and repeatable (Low et al. 2021). At the phylum level, Firmicutes and Verrucomicrobiota showed significantly higher abundances, while Bacteroidota and Cyanobacteria have lower abundances in WD-fed mice than in control mice (Low et al. 2021). At the family level, eight families have significantly higher abundances while 16 families were significantly less abundant in WD-fed mice than in normal diets-fed mice (Low et al. 2021). Nine families were similarly abundant among the groups (Low et al. 2021). In 2022, Romualdo et al. analyzed the impacts of WD on mouse's gut microbiota and linked the changes in gut bacteria with liver steatosis. Their data confirmed the WD-induced alteration in mouse's gut microbiota with differences in phyla and families (Romualdo et al. 2022). The combined information from the abovementioned studies were listed in Table 2.

Table 2.

The impacts of WD on gut microbiota, secondary metabolites and metabolic status

	Microbiota					Secondary metabolites	Metabolic status
	Phylum	Class	Order	Family	Genus
WD	Firmicutes↑ Proteobacteria↑ Verrucomicrobia↑ Actinobacteria↓ Bacteroidetes↓ Cyanobacteria↓ Fusobacteria↓	Clostridia↑ Deltaproteobacteria↑ Bacili↑ Bacterioidia↓ Fusobacteria↓	Clostridiales↑ Desulfovibrionales↑ Lactobacillales↑ Bacterioidales↓ Fusobacteriales↓	Erysipelotrichaceae↑ Streptococcaceae↑ Clostridiaceae↑ Eubacterium coprostanoligenes group↑ Enterococcaceae↑ Christensenellaceae↑ Staphylococcaceae↑ Akkermansiaceae↑ Ruminococcaceae↑ Desulfovibrionaceae↑ Lachnospiraceae↓ Lactobacillaceae↓ Clostridia UCG-014↓ Butyricicoccaceae↓ Clostridia vadinBB60 group↓ Acholeplasmataceae↓ Monoglobaceae↓ RF39↓ Peptococcaceae↓ Bacteroidaceae↓ Rikenellaceae↓ Muribaculaceae↓ Bifidobacteriaceae↓ Coriobacteriales Incertae Sedis↓ Eggerthellaceae↓ Gastranaerophilales↓ Prevotellaceae↓ Porphyromonadaceae↓ Fusobacteriaceae↓	Coprococcus↑ Ruminococcus↑ Desulfovibrio↑ Faecalibacterium↓ Fusobacterium↓ Bacteroides↓ Prevotella↓ Alloprevotella↓ Alistipes↓ RC9 gut group↓ Parabacteroides↓ Odoribacter↓	LPS↑ SCFA↓	vWAT↑ Body weight↑ Plasma triglycerides↑ Liver triglycerides↑ Plasma cholesterol↑ Liver cholesterol↑ Insulin resistance↑ Adipose mass↑

WD western diet, LPS lipopolysaccharide, SCFA short chain fatty acid, vWAT visceral adipose tissue

Similar to HFD, WD increases the plasma level of LPS and decreases the level of SCFAs (Kaye et al. 2020; Simkin 2019), which contribute to the increased insulin resistance, body weight, plasma and liver triglycerides, cholesterol, and risk of CVD (Baena et al. 2017). The direct comparison of the gut microbiota between WD- and HFD-fed rats showed minor differences between the two groups (Bortolin et al. 2018). Overall, WD induced similar alterations in gut microbiota and metabolites when compared with HFD (Table 2). Nevertheless, a closer look at the features of gut microbiota and metabolites in WD-fed mammals will be helpful for us to understand the mechanisms of this popular obesogenic diet.

Ketogenic Diet

KD is a normal caloric diet that is high in fat (over 70% in most cases), low in carbohydrates, and moderate in protein. KD consumption results in a very low carbohydrate uptake (less than 10% of total caloric intake), and forces ketone production (Veech 2004). KD is initially introduced as an effective treatment for drug-resistant epilepsy (Hohn et al. 2019). Later, KD is also applied as a treatment for other neuronal diseases (Rusek et al. 2019). But nowadays, KD is prevalently used by people aiming to lose weight, and the mechanism is under investigation (Badman et al. 2009; Garbow et al. 2011; Kosinski and Jornayvaz 2017). Meanwhile, some studies raised the concern that the consumption of KD might cause some adverse effects such as NAFLD and insulin resistance (Dashti et al. 2003; Ellenbroek et al. 2014; Jornayvaz et al. 2010).

KD dramatically influences the composition of gut microbiota (Table 3). At the phylum level, KD decreases the abundance of Firmicutes but increases the abundance of Bacteroidetes and Proteobacteria (Xie et al. 2017; Zhang et al. 2018b). At the family level, KD decreases the abundance of Enterobacteriaceae, Sinobacteraceae, and Comamonadaceae, but increases the abundance of Ruminococcaceae and Mogibacteriaceae (Gutierrez-Repiso et al. 2019). At the genus level, KD decreases the abundance of Serratia, Erwinia, and Citrobacter, and increases the abundance of Oscillospira and Butyricimonas (Gutierrez-Repiso et al. 2019). KD was also reported to decrease the abundance of Dialister and Cronobacter and increases the abundance of Desulfovibrio, Prevotella, Lactobacillus, and Parabacteroides (Lindefeldt et al. 2019; Ma et al. 2018; Olson et al. 2018; Tagliabue et al. 2017; Xie et al. 2017). At the species level, KD decreases the abundance of Bifidobacteria, but increases the abundance of Akkermansia muciniphila (Ma et al. 2018; Olson et al. 2018), which has been reported to be associated with weight loss, improved insulin sensitivity, alleviated insulinemia, decreased plasma total cholesterol, and the development of T2DM and hypertension (Brahe et al. 2015; Dao et al. 2016; Depommier et al. 2019; Kong et al. 2021; Li et al. 2017; Liu et al. 2017; Yassour et al. 2016; Zhang et al. 2013). However, to what extent the regulated abundance of Akkermansia muciniphila contributes to the physiological impact of KD remains unclear.

Table 3.

The impacts of KD on gut microbiota, secondary metabolites and metabolic status

	Microbiota				Secondary metabolites	Metabolic status
	Phylum	Family	Genus	Species
KD	Bacteroidetes↑ Proteobacteria↑ Firmicutes↓	Ruminococcaceae↑ Mogibacteriaceae ↑ Enterobacteriaceae↓ Sinobacteraceae↓ Comamonadaceae↓	Oscillospira↑ Butyricimonas↑ Desulfovibrio↑ Prevotella↑ Lactobacillus↑ Parabacteroides↑ Bifidobacteria↓ Serratia↓ Erwinia↓ Citrobacter↓ Dialister↓ Cronobacter↓	A. muciniphila↑	SCFA↑ sBA↓	Insulin resistance↓

KD ketogenic diet, SCFA short chain fatty acid, sBA secondary Bile Acids

The consumption of KD leads to the change of metabolites of gut microbiota. Akkermansia muciniphila is regarded as a key propionate-producing bacterium and butyrate production is dominated by Ruminococcus bromii (Morrison and Preston 2016). However, a recent study reported a reduction of SCFAs in KD-fed mice when compared to normal chow diet-fed mice (Li et al. 2021). In their report, Li et al. also revealed that KD feeding decreased four main tryptophan metabolites and changed the levels of 10 sBAs, among the 40 sBAs monitored (Li et al. 2021). Further studies will be needed to clarify the impacts of KD on the metabolism of SCFAs, sBAs and tryptophan, and the consequences on the hosts' metabolic status. In 2018, Olson et al. reported that the consumption of KD decreased systemic gamma-Aminobutyric acid (GABA) and elevated hippocampal GABA/glutamate levels, which play critical roles in the anti-seizure effect induced by KD (Olson et al. 2018).

Although more and more attention was put on the impact of KD on the gut microbiota and their metabolites, there are still several critical questions and concerns remained unanswered. First, as partially addressed by Li et al. in their report, both the sources and proportions of fat in the KD are critical for the KD-induced alteration in gut microbiota and their metabolites (Li et al. 2021). The differential alteration that would impact the hosts differently will be an intriguing topic for future investigation. Second, it has been shown that there is a biphasic effect of KD in microbiota: a quick but dramatic decrease in the richness and diversity of the bacteria, followed by a slow recovery of bacterial concentration (Swidsinski et al. 2017). Thus, the microbiota analyzed at different time points may show different results. Third, the proportion of fat, carbohydrates, and proteins varies a lot in different versions of KDs. The KDs used in animal studies are generally more extreme than the KD used in patients, and the KDs used by patients with epilepsy are generally more extreme than the KDs used by weight losers, which may cause inconsistency in the conclusion from animal studies and clinical trials (Li et al. 2021; Zhu et al. 2022).

High-Glucose or Fructose Diet

Excessive sugar intake contributes to the development of NAFLD, CVD, and T2DM in both direct and indirect manners (Stanhope 2016). Consumption of two commonly used high-sugar diets: HGD or HFrD results in similar fatty liver parameters, including elevated levels of hepatic triacylglycerol and insulin resistance (Johnston et al. 2013). Data from multiple groups suggested that fructose consumption is specifically linked to gut microbial dysbiosis, which mediated the hosts' metabolic changes (Di Luccia et al. 2015; Do et al. 2018; Mastrocola et al. 2018; Vasques-Monteiro et al. 2021). However, this idea was challenged by Bier et al. (2020). They claimed that antibiotic treatment significantly reduced microbial diversity and altered the microbial composition, but had minimal or no effect on the metabolic phenotypes of the HFrD-treated rats (Bier et al. 2020). Further investigation will be needed to find out the cause of this inconsistency. Nevertheless, there's no doubt that HFD or HFrD has a great impact on gut microbiota. At the phylum level, HGD- or HFrD-fed mice had a significantly lower abundance of Bacteroidetes and a higher abundance of Proteobacteria compared to normal diet-fed mice after 12 weeks of feeding (Do et al. 2018). At the family levels, the levels of nine different families were significantly changed in the feces of C57BL/6J mice fed with HFrD for 12 weeks (Table 4) (Ahn et al. 2020). While at the genus level, they found HFrD feeding increased the abundance of Akkemansia but decreased the abundance of Dehalobacterium and an unknown genus in Mogibacteriaeae (Ahn et al. 2020). At the species level, HFrD-fed mice had higher levels of Akkermansia muciniphila, Clostridium sp, Lachnoclostridium clostridium aldenense, Roseburia sp, Lachnoclostridium clostridium scindens, and lower levels of Clostridium disporicum, Lactobacillus johnsonii, Bacteroides acidifaciens, Allobaculum sp in their feces after one-week feeding. Different mice strains may also respond differently to fructose (Montrose et al. 2021).

Table 4.

The impacts of HGD or HFrD on gut microbiota, secondary metabolites and metabolic status

	Microbiota				Secondary metabolites	Metabolic status
	Phylum	Family	Genus	Species
HGD or HFrD	Proteobacteria↑ Bacteroidetes↓	S24-7↑ Pseudomonadaceae↑ Verrucomicrobiaceae↑ Rikenellaceae↓ Dehalobacteriaceae↓ Lachnospiraceae↓ Mogibacteriaceae↓ Ruminococcaceae↓ Turicibacteraceae↓	Akkermansia↑ Dehalobacterium↓ Unknown genus (Mogibacteriaceae)↓	A. muciniphila↑ C. sp↑ L. clostridium aldenense↑ R. sp↑ L. clostridium scindens↑ C. disporicum↓ L. johnsonii↓ B. acidifaciens↓ A. sp↓	LPS↑	Insulin resistance↑ Hepatic inflammation↑ Hepatic lipid accumulation↑ Enlargement of adipocytes↑

HGD or HFrD high glucose diet or high fructose diet, LPS lipopolysaccharide

The intestinal permeability of HGD or HFrD group mice was enhanced due to the lower expression of tight junction proteins, such as zonula occludens-1 and occluding, which can increase the intestinal permeability and contribute to the translocation of LPS (Cani et al. 2008; Do et al. 2018). Given the increased abundance of Proteobacteria (Do et al. 2018), one of the major producers of LPS (Rizzatti et al. 2017), it is not a surprise that HFrD increases plasma LPS (Rivero-Gutierrez et al. 2017), and the increased plasma levels of LPS leads to insulin resistance in murine fed with HGD or HFrD (Pedersen et al. 2016; Rivero-Gutierrez et al. 2017). Silva et al. also compared the fecal metabolites from mice fed with ND, HGD or HFrD, and found that high glucose or fructose feeding caused different alterations in fecal SCFAs (Silva et al. 2018). Their results indicated that both high glucose- and high fructose-feeding caused higher levels of fecal acetate. But only high fructose-, not high glucose-fed mice had lower levels of fecal butyrate. On the other side, high glucose- but not high fructose-fed mice had significantly higher levels of fecal propionate compared to normal chow diet-fed mice (Silva et al. 2018). Ahn et al. also raised the concern of substantial variability in both fecal metabolites and microbial profiles between animals within the same feeding group, as well as at different time points for one animal across the feeding interval (Ahn et al. 2020). Thus, it is recommended to have multiple feces sampling collected during a feeding trial to obtain representative levels of fecal metabolites and microbial populations.

In recent decades, the introduction of high-fructose corn syrup in the food industry dramatically increased the consumption of fructose. How the HFrD would change our lives and the safe limit of daily fructose consumption remains largely unknown. Further investigation on fructose-induced alteration of microbiota and their metabolites is needed for a better understanding of the impact of fructose consumption.

Vegan or Vegetarian Diet

There are two kinds of vegetarianism: one is vegetarian, and the population are on the traditional vegetarian diet; the other one is vegan, also named a strict vegetarian, and a vegan avoids all animal and animal-derived products. Accordingly, these two plant foods-based diets are featured a high level of fiber and carbohydrates but low in fat and protein (Haddad et al. 1999). Both vegan diet and vegetarian diet are advocated as a dietary strategy for maintaining good health and treating metabolic disorders, including obesity, diabetes, and CVD (Craig 2009; Jenkins et al. 2014; Le and Sabate 2014; Tonstad et al. 2013).

The influence of vegan and vegetarian diets on gut microbiota has been studied in many laboratories, and the results are somewhat contradictory. The overall differential microbiota composition in vegans or vegetarians, when compared to omnivores, and inconsistency were well summarized in a systematic review (Trefflich et al. 2020). The reasons for the inconsistency could be the different ways the vegan or vegetarian were defined, the different regions the subjects were recruited, the time the subjects stayed on the diets, and how the samples were collected and analyzed. One single study with the biggest number of differences in microbiota composition is from Zhang et al. (2018a). They recruited 29 healthy volunteers and divided them into three groups (a study group with 15 members normally consume an omnivorous but were put on a three-months lacto-ovo-vegetarian diet, an omnivorous group with seven members stayed on an omnivorous diet and a vegetarian group with seven members stayed on a vegetarian diet). They collected samples on day 0 and day 91 from each group and surveyed the effect on the diversity of gut microbiota by metagenomic sequencing (Zhang et al. 2018a). A combined short-term effect (Day 91 vs Day 0 in the study group) and long-term effects (the omnivorous group vs the vegetarian group at Day 91 and Day 0) on gut microbiota were listed in Table 5.

Table 5.

The impacts of VD or VeD on gut microbiota, secondary metabolites and metabolic status

	Microbiota			Secondary metabolites	Metabolic status
	Phylum	Genus	Species
VD or VeD	Firmicutes↑ Proteobacteria↑ Bacteroidetes↓ Verrucomicrobia↓	Prevotella↑ Capnocytophaga↑ Porphyromonas↑ Roseburia↑ Faecalibacterium↑ Lachnospira↑ Veillonella↑ Actinobacillus↑ Atopobium↑ Actinoplanes↑ Cryptobacterium↑ Micrococcus↑ Aggregatibacter↑ Aeromonas/Pseudomona↑ Campylobacter↑ Haemophilus↑ Klebsiella↑ Neisseria↑ Alistipes↓ Parabacteroides↓ Peptostreptococcus↓ Desulfitobacterium↓ Ruminococcus↓ Dialister↓ Phascolarctobacterium↓ Acetobacterium↓ Bulleidia↓ Holdemania↓ Dorea↓ Caldanaerobacter↓ Lachnoclostridium↓ Lactobacillus↓ Lactococcus↓ Oscillospira↓ Bifidobacterium↓ Eggerthella↓ Corynebacterium↓ Oxalobacter↓ Ruegeria↓ Taylorella↓ Syntrophobacter↓ Ralstonia↓ Campylobacter↓ Desulfovibrio↓ Bilophila↓ Succinivibrio↓ Halomas↓ Methanosphaera↓ Dehalogenimona↓ Streptobacillus ↓ Akkermansia ↓	P. copri↑ B. Hydrogenotrophica↑ C. Ramosum↑ C. Symbiosum↑ P. duerdenii↑ S. peroris↑ V. dispar↑ V. parvula↑ V. atypica↑ M. luteus↑ A. Segnis↑ A. actinomycetemcomitans↑ C. concisus↑ H. haemolyticus↑ H. influenzae↑ H. parainfluenzae↑ K. pneumonia↑ N. mucosa↑ B. Vulgatus↓ B. fragilis↓ B. Dorei↓ B. Thetaiotaomicron ↓ B. Uniformis↓ B. Finegoldii↓ B. Stercoris↓ P. gingivalis↓ P. Distasonis↓ P. buccalis↓ P. oris↓ P. tannerae↓ L. amylovorus↓ C. Clostridioforme↓ C. Kluyveri↓ C. coccoides-E. rectale↓ C. Innocuum↓ C. Paraputrificum↓ R. torques↓ D. invisus↓ P. Succinatutens↓ E. Coli↓ E. faecium↓ R. Eubacterium rectale↓ D. longicatena↓ B. hansenii↓ A. caccae↓ F. magna↓ T. pseudo ethanolicus↓ P. denticolens↓ M. curtisii↓ E. hermannii↓ S. fumaroxidans↓ A. baumannii↓ D. piger↓ D. alaskensis↓ D. aespoeensis↓ B. wadsworthia↓ E. ictaluri/ tarda↓ M. stadtmanae↓ D. lykanthroporepellens↓ F. ulcerans↓	SCFA↑ TMA↓ sBA↓	Insulin sensitivity↑

VD or VeD vegan diet or vegetarian diet, SCFA short chain fatty acid, sBA secondary Bile Acids, TMA trimethylamine

Bacterial metabolites were more abundant while lipid and amino acid metabolites were less abundant in the plasma metabolome of vegans when compared to omnivores (Wu et al. 2016). A vegetarian diet increases the abundance of Prevotella, which produces SCFAs (de Moraes et al. 2017; Rios-Covian et al. 2016). The elevation of SCFAs may contribute to diet-induced weight loss and increased insulin sensitivity in vegans (De Filippo et al. 2010; Pilis et al. 2014; Tindall et al. 2018; Xie et al. 2017). The vegetarian or vegan diets are low in choline, phosphatidylcholine, and L-carnitine, which cause the reduction of TMA in the hosts. TMA can be further oxidized to trimethylamine N-oxide, which could trigger insulin resistance and increase the risk of T2DM and NAFLD in humans and rodents (Barrea et al. 2018; Fu et al. 2020; Heianza et al. 2019; Schugar et al. 2017; Shan et al. 2017). Primary bile acids are produced by the liver and secreted into the intestine, and then converted to sBAs by gut microbiota. The increased level of sBAs has been reported to positively correlate with the risk of insulin resistance and T2DM (Sircana et al. 2018). sBAs activate farnesoid X receptor (FXR) and G protein-coupled bile acid receptor-1 (also named TGR5), which are both expressed in endocrine L cells. The activation of FXR and TGR5 stimulates the secretion of GLP-1, which improves insulin sensitivity (Pathak et al. 2018). Vegans had lower levels of total BA and sBA in their feces than omnivores (Trefflich et al. 2019), which might be because of the high intake of fibers and low intake of fat (O'Keefe et al. 2015). Whether a plant-derived diet improves insulin sensitivity by impacting the levels of sBA remains unknown.

Mediterranean Diet

MD is a diet with a high level of vegetables, fruits, fish, whole grains, beans, wine and olive oil, popular in southern European countries around the olive-tree-bearing regions of the Mediterranean basin. It has been reported that higher adherence to the MD is associated with a lower risk of CVD and metabolic syndrome (Kastorini et al. 2011; Ryan et al. 2013; Salas-Salvado et al. 2014; Wang et al. 2021).

The high level of dietary fibers and low content of red meat in an MD orchestrate a special pattern of gut microbiota (Table 6), which is believed to mediate, at least partially, the beneficial effects of MD (De Filippis et al. 2016; Garcia-Mantrana et al. 2018; Ghosh et al. 2020; Mitsou et al. 2017; Rinninella et al. 2019; Tindall et al. 2018; Wang et al. 2021). De Filippis et al. first convincingly demonstrated the connection between MD and gut microbiota (De Filippis et al. 2016). In 2020, based on 16S rRNA sequencing data, Ghosh et al. reported that, at the species level, a 12-month MD intervention increased the abundance of Faecalibacterium prausnitzii, Roseburia hominis, Eubacterium rectale, Eubacterium eligens, Eubacterium xylanophilum, Bacteroides thetaiotaomicron, Prevotella copri, and Anaerostipes hadrus in 612 subjects across five European countries (Ghosh et al. 2020). These species positively associate with the production of SCFAs and negatively associate with the development of T2DM (Machiels et al. 2014; Qin et al. 2012). Consistently, better adherence to the MD was associated with significantly higher levels of total SCFA (Garcia-Mantrana et al. 2018). On the other side, MD decreased the abundance of Ruminococcus torques, Collinsella aerofaciens, Coprococcus comes, Dorea formicigenerans, Clostridium ramosum, Veillonella dispar, Flavonifractor plautii, and Actinomyces lingnae (Ghosh et al. 2020). In 2021, Wang et al. based on metagenomics sequencing analysis, confirmed the impacts of MD on these species, which were featured as fiber metabolizers and SCFA producers (Wang et al. 2021). Based on their analysis, the abundances of whole grams, vegetables, fruits and reduced red meat in MD were the determining components shaping the specific pattern of gut microbiota in MD-consuming individuals (Wang et al. 2021).

Table 6.

The impacts of MD on gut microbiota, secondary metabolites and metabolic status

	Microbiota				Secondary metabolites	Metabolic status
	Phylum	Family	Genus	Species
MD	Bacteroidetes↑	Lachnospiraceae↑	Lactobacillus ↑ Bifidobacteria↑ Clostridium ↓	C. albicans↑ F. prausnitzii↑ R. hominis↑ E. rectale↑ E. eligens↑ E. xylanophilum↑ B. thetaiotaomicron↑ P. copri↑ A. hadrus↑ R. torques↓ C. aerofaciens↓ C. comes↓ D. formicigenerans↓ C. ramosum↓ V. dispar↓ F. plautii↓ A. lingnae↓	SCFA↑ TMA↓ sBA↓	T2DM↓ Obesity↓ Insulin sensitivity↑

MD Mediterranean diet, SCFA short chain fatty acid, sBA secondary Bile Acids, TMA trimethylamine, T2DM type 2 diabetes mellitus

In addition to the aforementioned SCFAs, the other metabolites were also found to be affected by MD and play roles in hosts' pathophysiological conditions. Tindall et al. demonstrated that MD can reduce the plasma level of TMA, leading to a lower risk of insulin resistance (Tindall et al. 2018). Ghosh et al. demonstrated that MD can decrease the level of sBA (Ghosh et al. 2020), which is positively associated with insulin resistance (Sircana et al. 2018).

Gluten-Free Diet

Gluten is a mixture of hundreds of distinct proteins but is primarily made up of two different classes of proteins: gliadin and glutenin (Biesiekierski 2017). GFD is a diet that excludes all gluten-containing foods, such as pasta, pizza, beer, oatmeal, toast, sandwiches, cakes, bread, cookies, etc. GFD is the only efficient treatment available for Celiac disease, a chronic inflammatory pathology of the small intestine triggered by dietary gluten (Newnham 2017), which affects about 1% of the general population worldwide (Catassi et al. 2015; Lionetti et al. 2015). GFD is also taken by healthy people aiming for better health, but the potential usage of GFD in preventing obesity and diabetes is controversial (Haupt-Jorgensen et al. 2018).

Zafeiropoulou et al. (2020) compared the gut microbiota of celiac disease children on GFD (45 patients) and gluten-containing diets (20 patients). And then, among these 20 children on gluten-containing diets, 13 patients participated in a 12 months prospective study and started to consume GFD (Zafeiropoulou et al. 2020). Their fecal samples were collected at six months and 12 months on GFD and analyzed by 16s ribosomal RNA sequencing. In their cross-sectional study, Zafeiropoulou et al. identified 51 Operational taxonomic units (OTUs) with significantly higher abundance, and three OTUs with significantly lower abundance in GFD diet children (Zafeiropoulou et al. 2020). In the prospective study, they found seven significantly decreased and three increased OTUs in the samples at both six and 12 months on GFD compared to baseline samples.

The effects of GFD on healthy people were also investigated. The abundance of Bifidobacterium, Clostridium lituseburense, and Faecalibacterium prausnitzii was decreased but the abundance of Enterobacteriaceae and Escherichia coli was increased in healthy people after one month of GFD consumption (De Palma et al. 2009). The results from a similar clinical trial on healthy adults on GFD for one month demonstrated that GFD can decrease the abundance of some beneficial bacteria, such as Bifidobacterium longum and Lactobacillus, but also increase the abundance of Enterobacteriaceae, which is regarded as harmful bacteria (Sanz 2010). Bonder et al. (2016) investigated the change in intestinal microbiota of 21 healthy participants who were kept on GFD for four weeks, and their results showed that the abundance of Veillonellaceae changed most obviously in GFD and its abundance was markedly decreased. Besides, the abundance of Ruminicoccus bromii and Roseburia was also decreased by GFD (Bonder et al. 2016). On the contrary, the abundance of Victivallaceae, Clostridiaceae, and Coriobacteriaceae was increased (Bonder et al. 2016).

GFD will lead to the change of metabolites of intestinal microbiota (Table 7). As mentioned above, GFD decreases the abundance of Bifidobacterium and Lactobacillus, both were the source of SCFAs. Therefore, it is not a surprise to see that GFD consumers have a lower circulating level of SCFAs (Di Cagno et al. 2011; Garcia-Mazcorro et al. 2018). Given the strong impacts of SCFAs on insulin sensitivity (Hernandez et al. 2019), logically, the decreased circulating level of SCFAs by GFD will increase the risk of metabolic diseases. Indeed, GFD consumption increased the risk of NAFLD in Celiac disease patients (Tovoli et al. 2018; Imperatore et al. 2018). Although some studies suggest that GFD consumption reduced the risk of obesity and diabetes (Haupt-Jorgensen et al. 2018), others argued that GFD might aggravate obesity, serum lipid levels, insulin resistance, and atherosclerosis (Alzaben et al. 2015; Anania et al. 2017; Kemppainen et al. 1995; Mariani et al. 1998). More studies are needed to increase our understanding of how a GFD is associated with metabolic disease and to apply GFD effectively and safely.

Table 7.

The impacts of GFD on gut microbiota, secondary metabolites and metabolic status

	Microbiota			Secondary metabolites	Metabolic status
	Family	Genus	Species
GFD	Enterobacteriaceae↑ Bacteroidaceae↑ Clostridiaceae↑ Victivallaceae↑ Lachnospiraceas↓ Veillonellaceae↓	Roseburia↓ Bifidobacterium↓ Lactobacillus↓	R. bromii↓ C. lituseburen↓ F. prausnitzii↓ E. coli↑ B. longum↓	SCFA↓	NAFLD↑ Hepatic steatosis↑ Serum Lipid levels↑ Insulin resistance↑ Atherosclerosis↑

GFD gluten-free diet, SCFA short chain fatty acid, NAFLD nonalcoholic fatty liver disease

Conclusion

Leveraging advanced technology, researchers have made huge progress in the identification and systematization of microbiota in the past decades. However, researchers realized a big obstacle when generalizing results from the previous literature: the inconsistency among different laboratories (Bier et al. 2020; Bisanz et al. 2019; Trefflich et al. 2020), or even within the same laboratory (Ahn et al. 2014). Many factors contribute to these inconsistencies. First, the techniques used for identifying the microbes are different, from real-time PCR, 16s ribosomal RNA sequencing to metagenomic sequencing. Second, the diets provided for the patients are different. For instance, the fat content and ratio in HFD vary from study to study, although they are all called HFD. Third, even though the diets fed to animals are better controlled, the diet storage condition also makes difference (Yi et al. 2022). Fourth, the environment in different animal facilities affects the microbiota in the animals. Fifth, the genetic background of the research objects also affects the microbiota (Ahn et al. 2014). A better description of the detailed materials and methods will be very helpful and necessary in future microbiota-related publications.

The differences in major components in the diets not only discriminate them from others but also shape specific patterns of gut microbiota in the hosts. The proportion of macronutrients, namely fats, carbohydrates and proteins in the diets varies in KD, HFD, WD, HGD/HFrD, and so does the gut microbiota. However, the composition of the microbiota does not necessarily match the contents of the macronutrients. For example, fat-rich HFD and WD both cause a significant increase in the abundance of Firmicutes in the hosts' gut (Bisanz et al. 2019; Low et al. 2021), but KD, with an even higher level of fat, induces a dramatic reduction of Firmicutes (Xie et al. 2017; Zhang et al. 2018b), and V/VeD, with an extremely low level of fat, surprisingly increased the abundance of Firmicutes in the gut (Zhang et al. 2018a). The precise connection between the components in the diets and the gut microbiota still needs a lot of work, with the consideration of the complicated ecological system in the gut.

Here, we review the large body of data that is structuring our understanding of how the diets alter the gut microbiota, bacterial metabolites, and the hosts' metabolic status. Given the large population and fast dynamic of the gut microbiota, what we have known about gut microbiota is just the tip of the iceberg. Many questions remain unanswered: How do these altered microbes crosstalk with each other and influence the hosts' pathophysiology? What are the key sensors or message receivers in the hosts that help the hosts quickly and harmoniously adapt to the dietary changes? Nowadays, more and more people acknowledge the featured diets as medical treatments or nutritional strategies aiming for better health. But, the potential adverse effects of some diets are underestimated. How the gut microbiota gets involved in these beneficial and/or harmful effects is largely unknown. Without any doubt, further research is warranted and will keep extending our knowledge of the gut microbiota.

Abbreviations

NAFLD

Nonalcoholic fatty liver disease

CVD

Cardiovascular disease

LPS

Lipopolysaccharide

BCAA

Branched-chain amino acid

SCFA

Short-chain fatty acid

TMA

Trimethylamine

sBA

Secondary bile acid

KD

Ketogenic diet

HFD

High-fat diet

WD

Western diet

HGD

High-glucose diet

HFrD

High-fructose diet

VD

Vegan diet

VeD

Vegetarian diet

MD

Mediterranean diet

GFD

Gluten-free diet

CD

Chow diet

RELMβ

Resistin-like molecule β

NF-κB

Nuclear factor-κB

MyD88

Myeloid differentiation factor 88

IRAK

Interleukin 1 receptor associated kinase

TRAF6

Tumor necrosis factor receptor associated factor 6

TAK1

Transforming growth factor β activated kinase 1

IRS1/2

Insulin receptor substrate 1/2

mTOR

Mammalian target of rapamycin

GABA

Gamma-aminobutyric acid

OTUs

Operational taxonomic units

GLP-1

Glucagon-like peptide-1

Authors' Contributions

SH concepted the idea for the article, all authors contributed to the literature search and data analysis, and YL, WZ, XL, FS, SH, YS drafted and/or critically revised the work. All authors read and approved the final manuscript.

Data availability

All data generated or analyzed during this study are included in this published article (and its supplementary information files).

Declarations

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.