# Reframing nutritional microbiota studies to reflect an inherent metabolic flexibility of the human gut: A narrative review focusing on high-fat diets

Jonathan Sholl, L.J. Mailing, T.R. Wood

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Jonathan Sholl, L.J. Mailing, T.R. Wood. Reframing nutritional microbiota studies to reflect an inherent metabolic flexibility of the human gut: A narrative review focusing on high-fat diets. mBio, 2021, 12 (2), pp.e00579-21. 10.1128/mBio.00579-21. hal-03662360

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# Reframing Nutritional Microbiota Studies To Reflect an Inherent Metabolic Flexibility of the Human Gut: a Narrative Review Focusing on High-Fat Diets

Jonathan Sholl,ª Lucy J. Mailing,ᵇ Thomas R. Woodᶜ,ᵈ,e

Jonathan Sholl and Lucy J. Mailing contributed equally. Author order was based on relative contributions to drafting and editing the manuscript.

**ABSTRACT** There is a broad consensus in nutritional-microbiota research that high-fat (HF) diets are harmful to human health, at least in part through their modulation of the gut microbiota. However, various studies also support the inherent flexibility of the human gut and our microbiota's ability to adapt to a variety of food sources, suggesting a more nuanced picture. In this article, we first discuss some problems facing basic translational research and provide a different framework for thinking about diet and gut health in terms of metabolic flexibility. We then offer evidence that well-formulated HF diets, such as ketogenic diets, may provide healthful alternative fuel sources for the human gut. We place this in the context of cancer research, where this concern over HF diets is also expressed, and consider various potential objections concerning the effects of lipopolysaccharides, trimethylamine-N-oxide, and secondary bile acids on human gut health. We end by providing some general suggestions for how to improve research and clinical practice with respect to the gut microbiota when considering the framework of metabolic flexibility.

**KEYWORDS** cancer, gut health, high-fat diets, metabolic flexibility, microbiota

It is generally accepted that diet is a major factor shaping both the composition and the function of the human gut microbiota. However, much debate focuses on the health effects of dietary components, with fiber generally being seen as not only beneficial but necessary and animal fat (and sometimes protein) from “high-fat (HF) diets” being singled out as detrimental to the gut microbiota (1–9). As a result, concerns over HF diets feature heavily in the framing of studies on the microbiota and health. For instance, HF or even “high-protein, low-carbohydrate” diets are often suggested to play a causal role in various forms of cancer, cardiovascular disease, immunological dysregulation, and diabetes, through a variety of mechanisms (10–14). This concern is expressed by international authorities on gut health, e.g., the European Society of Neurogastroenterology and Motility (15), and in consensus statements by groups like the International Cancer Microbiome Consortium (16).

It seems safe to say that the consensus is that HF diets are harmful to human health, at least in part through their modulation of our gut microbiota. Put differently, the primary substance that feeds “beneficial” gut microbes is “microbiota-accessible carbohydrates” (17), and in the absence of these, protein and fat will deteriorate our gut health. One of the most cited studies used to support this consensus is that of David et al. (18). While this study demonstrates how quickly the human gut microbiota adapts to

**Citation** Sholl J, Mailing LJ, Wood TR. 2021. Reframing nutritional microbiota studies to reflect an inherent metabolic flexibility of the human gut: a narrative review focusing on high-fat diets. mBio 12:e00579-21. https://doi.org/10.1128/mBio.00579-21.

**Editor** Danielle A. Garsin, University of Texas Health Science Center at Houston

**Copyright** © 2021 Sholl et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

Address correspondence to Jonathan Sholl, jonathan.sholl@u-bordeaux.fr, or Thomas R. Wood, tommyrw@uw.edu.

**Published** 13 April 2021

<footnote>ªUniversité Bordeaux, CNRS, ImmunoConcEpT, UMR 5164, Bordeaux, France</footnote>

<footnote>ᵇIndependent Researcher, Milwaukee, Wisconsin, USA</footnote>

<footnote>ᶜInstitute for Human and Machine Cognition, Pensacola, Florida, USA</footnote>

<footnote>ᵈCenter on Human Development and Disability, University of Washington, Seattle, Washington, USA</footnote>

<footnote>ᵉDepartment of Pediatrics, University of Washington, Seattle, Washington, USA</footnote>
dietary changes, what is less clear is how this should be interpreted (9). As we will discuss, this study highlights the need to consider the metabolic flexibility of the gut (19, 20). We are still far from being able to precisely define a “healthy” gut microbiota (21–25), and it is quite likely that the human gut and its microbial symbionts evolved to adapt to a variety of macronutrient patterns. Acknowledging this flexibility will help to expand research and guide clinical interventions.

Here, we suggest one way in which translational research on nutrition and the microbiota can be misleading (1st section) and provide a way to reframe this research in terms of metabolic flexibility (2nd section). We then offer evidence supporting the potential healthfulness of alternative fuel sources derived from HF ketogenic diets (KDs) (3rd section) and question the harmful role of these diets in diseases such as cancer (4th section). After addressing some likely objections (5th section), we end by raising the concern that the consensus on dietary fat may reflect a research bias more than physiological reality and provide suggestions for future research.

## LOST IN TRANSLATION: OF MICE AND JUNK FOOD

We are not the first to point out the limitations of preclinical nutritional microbiota research or the ubiquitous problem of HF diets in animal models. These diets are typically composed of soybean oil, lard, refined sugar, and little to no fiber (26, 27), which Craig Warden called “the mouse equivalent of pork rinds, ribs, and coke” (28). The classic animal HF diet is therefore much more reflective of the standard American diet than nutritionally replete high-fat diets, such as therapeutic KDs (29, 30). Evidence for the role of simple sugars in harmfully disrupting the gut microbiota is growing (31), and this alone should provide ample reason not to draw conclusions based solely on fat content without considering other macronutrients or dietary quality.

While human metabolism can adapt to diets higher in either fats or carbohydrates, the natural diet of a mouse is low in fat and high in carbohydrates. It is therefore unsurprising that mice develop issues when eating a species-inappropriate diet. The strain of mice commonly used for such studies, C57BL/6, has also been genetically selected for its ability to gain weight in response to a HF diet. While humans are capable of weight loss or gain on a variety of dietary patterns (32–34), C57BL/6 mice have greater weight gain and metabolic disruptions on low-carbohydrate diets (35). Consequently, “...rodent models of obesity may be most valuable in the understanding of how metabolic mechanisms can work in ways different from the effect in humans” (35). Broadly translating findings from inbred mice fed a highly refined HF diet to humans is therefore fraught with potential for misunderstanding.

Similar problems exist in the clinical literature examining effects of the diet on the gut microbiota and associated disease risk. For instance, in the Malmö Offspring Study, Ericson et al. identified “health-conscious” and “sugar and high-fat dairy” dietary patterns associated with decreased and increased risk of having prediabetes, respectively (36). The latter pattern was characterized by high intakes of pastry/desserts, high-fat milk/cream, low-fiber bread, potatoes, and processed/red meat, with the overarching assumption that these components all equally and significantly contribute to the potential negative effects of this dietary pattern. Though these foods may cluster together frequently on the population level, we cannot assume that they contribute equally to any associated health outcomes since each of them would be expected to have very different effects on both the gut microbiota and on general health. As highlighted in the commentary accompanying reference 36, the association between the health-conscious dietary pattern and prediabetes was lost after adjusting for body mass index (BMI) (2), suggesting that a primary driver of differences between dietary patterns may be caloric intake. Any attempt to assess the effects of dietary components on health must consider food processing and energy density, both of which appear to contribute to increased caloric intake beyond the effect of individual macronutrients (37, 38). One must also consider whether it is the presence or absence of certain foods that drives downstream effects (2). Without a nuanced approach examining dietary quality and individual dietary components, we are
left making assumptions about fat in human diets similar to those made when we attrib-
ute the effects of HF diets in rodents purely to fat content.

We largely agree that the "Western" diet full of processed food causes problems for both the mouse and the human gut microbiota. However, there are a variety of ways to construct an HF diet, with data from humans suggesting that well-formulated therapeutic KDs, which in some clinical trials contain between 3 and 5 servings of non-starchy vegetables per day (39, 40), may be more beneficial for our gut and overall health than some animal studies suggest (30, 41, 42). What is needed, then, is a way to reframe the debate to better reflect the overall evidence.

REFRAMING A HEALTHY GUT IN TERMS OF EVOLVED FLEXIBILITY

New technologies and greater interest in gut health in recent years have dramati-
cally increased our understanding of gut microbes. Nevertheless, we are still unable to
define a "healthy" gut microbiota (22, 25). On average, any two individuals share only
about a third of their gut microbiota, with the other two-thirds varying depending on
genetics, geographical location, history of antibiotic and medication use, mode of
delivery at birth, diet, and other undetermined factors (43, 44). It is even possible that
two otherwise-healthy individuals can show no overlap in microbiota composition
(44). Thus, outside clear instances of dysbiosis, we have insufficient information to say
that one individual's "two-thirds" is any better than another's.

While it is generally believed that diversity and community stability are key compo-
nents of a healthy gut ecosystem, even these can sometimes be associated with dis-
eased states (45, 46). Some of the keystone microbes commonly considered crucial for
gut health, such as *Bifidobacterium*, are completely absent from the guts of traditional
cultures, like the Hadza, who are otherwise virtually free of chronic disease (47). Gut
health and dysbiosis thus remain vague and sometimes contested concepts (25, 48,
49); if there is a healthy "core" microbiota, it may be at the level of microbial functions,
not species (23, 43). Part of this relative lack of insight may result from technologies
such as 16S rRNA sequencing, which do not provide accurate information beyond the
genus level and provide little insight into microbial functions (50). While there is hope
that higher-resolution technologies (e.g., metagenomics, metabolomics), larger data
sets, and advanced computing techniques will bring us closer to defining a healthy micro-
biota, many researchers call for moving away from cataloguing species and toward an
approach that considers the intricate nature of microbiota-host interactions (22, 51).

While technological advances are eagerly awaited, some initial clarity might come
from placing the human microbiota in its evolutionary context. Our relationship with
our gut microbes is the product of thousands of generations of close coevolution (52,
53). The environments in which we evolved also required regular adaptation to chang-
ing conditions. Our ancestors may not always have had steady access to food and
would likely have undergone occasional bouts of significant deprivation when food
was scarce (54, 55). Similarly, diets changed seasonally and geographically, as is
reflected by the seasonal changes in the guts of traditional populations, like the Hadza
(56), or in the specific adaptations in cultures known to eat relatively few plant foods,
such as the Inuit (57, 58). This variability can be explained in terms of metabolic flexibil-
ity (19), which is the evolved ability to shift our metabolism to changes in dietary intake:
to burn and use carbohydrates when they are plentiful and to turn dietary fat or stored
body fat into ketones for energy when food or carbohydrates are scarce. Consequently,
it seems likely that our guts also exhibit the flexibility to adapt to changing food sources
rather than suffer significant gut dysfunction whenever fiber is absent.

In line with this evolutionary perspective on the compositional and functional
adaptability of our gut and its microbiota, David et al. write (18),

Our findings that the human gut microbiome can rapidly switch between
herbivorous and carnivorous functional profiles may reflect past selective pressures
during human evolution. Consumption of animal foods by our ancestors was likely
volatile, depending on season and stochastic foraging success, with readily available
plant foods offering a fallback source of calories and nutrients. Microbial communities that could quickly, and appropriately, shift their functional repertoire in response to diet change would have subsequently enhanced human dietary flexibility.

In other words, a “healthy” gut microbiota adapts to a wide range of food sources and does not necessarily become more or less pathogenic depending on the amount of carbohydrate or fat in the diet. Moreover, while short-term dietary changes tend to produce significant changes in the gut microbiota (18), long-term studies suggest a relative resilience of the microbiota to shifts in diet (59). Due to the aforementioned factors shaping gut microbiota (43, 44), we should consider whether a dietary change must produce significant physiological changes in the host before a new microbial stability is achieved, with diet-induced fluctuations merely an expression of the gut’s ability to adapt to ensure optimal function. If human guts are inherently metabolically flexible, short-term diet-induced changes in microbiota composition could be considered a potential hallmark of gut health (60). We should thus determine whether the short- and long-term taxonomic changes resulting from this metabolic flexibility are predictive of overall health outcomes and how/whether the microbiota drives those outcomes (61–63).

## EVIDENCE FOR HIGH-FAT KETOGENIC DIETS—CONSIDERING ALTERNATIVE PATHWAYS

Gut bacteria metabolize complex carbohydrates to produce short-chain fatty acids (SCFAs), like acetate, propionate, and butyrate, with the last being the preferred fuel source for gut epithelial cells. Published estimates suggest that butyrate provides about 70% of colonic epithelial cell energy requirements (64), with a regular supply of butyrate required to maintain gut barrier function. What remains to be seen is how different diets modulate SCFA production and whether this results in different downstream health effects.

**Animal-based diets.** The work of David et al. (18) has been instrumental in highlighting how quickly and reliably the human gut microbiota adapts to dietary changes. What is unclear is whether this study should be used to support the avoidance of diets high in fat or protein. Ten healthy human volunteers were placed on a short-term plant-based diet (PBD) consisting of 300 g of carbohydrate per day from cereal, vegetables, rice, lentils, and fruit or on an animal-based diet (ABD) consisting of less than 3 g of carbohydrates per day, with 30% of calories from protein and 70% of calories from fat from eggs, meat, and cheese. Subjects on the ABD group were confirmed to be in ketosis by day 2 of the diet, with distinct gut microbial communities emerging in both diet groups within 3 days.

The most interesting and perhaps contentious finding was that there was no significant change in alpha-diversity in either group (18). Those on the ABD saw an increase in the relative abundance of bile-tolerant microorganisms, like *Bilophila*, *Alistipes*, and *Bacteroides* spp., and a decrease in the relative abundance of microbes known to metabolize complex dietary plant fibers, such as *Roseburia*, *Eubacterium*, and *Ruminococcus* spp. While often cited as evidence that an ABD is harmful, this is far from conclusive. The PBD, despite being supposedly uniquely capable of producing butyrate from microbiota-accessible carbohydrate metabolism, produced only slightly more butyrate than did the ABD, with the ABD also resulting in significantly greater production of isovalerate and isobutyrate (Fig. 1) (18). Isobutyrate has been shown to activate many of the same receptors as butyrate (see "Considering alternative pathways" below), weakening the notion that PBDs are significantly "better" for the gut due to butyrate/SCFA production.

**Mucus barrier.** Another recent study by Ang et al. confirmed that a ketogenic diet (KD) can alter the structure and function of the gut microbiota (65). In humans, among the most significant changes of the fecal microbiota following a KD was a dramatic reduction in the abundance of several *Bifidobacterium* species. In controlled-feeding studies of mice, the researchers found that KDs had a unique impact on the gut microbiota relative to conventional HF diets, with the abundance of *Bifidobacterium* organisms decreasing with increasing carbohydrate restriction. Further experiments found
<figure><img src="image_4.png" /><figcaption>**FIG 1** Short-chain fatty acid (SCFA) production in humans eating low-fat, plant-based and high-fat, animal-based diets. (a) Plant-based diets result in roughly twice the production of acetate and butyrate. (b) Animal-based diets result in roughly twice the production of isovalerate and isobutyrate, which have metabolic functions overlapping those of the traditional SCFAs acetate and butyrate. (Republished from reference 18 with the permission of the publisher.)</figcaption></figure>

that both a KD or ketone ester supplementation increased beta-hydroxybutyrate (βHB) in the lumen of the gut and in colon tissue (65), with ketone bodies directly inhibiting the growth of *Bifidobacterium*. Ketosis was also associated with a reduction in small intestinal Th17 cells, which help maintain the gut mucosal barrier and contribute to pathogen clearance at mucosal surfaces. However, Th17 cells have also been implicated in autoimmune and inflammatory disorders (66).

Next, Ang et al. (65) sought to determine whether the change in Th17 cells was dependent on the ketone-induced changes in the microbiota. Mice that received a fecal transplant of the ketone-fed microbiota from human donors had significantly fewer intestinal Th17 cells. Contrary to previous findings that mice fed fiber-free diets had a significant breakdown of the colonic mucus layer (67, 68), Ang et al. write, "A ketogenic diet maintains a robust mucus layer despite the lack of fermentable carbohydrates" (65). The KD maintained not only the thickness of the mucus layer but also the expression of Muc2, the primary constituent of gut mucus. Nutritional ketosis might actually support the gut mucus layer.

**Multiple sclerosis and epilepsy.** There are various levels of support for therapeutic KDs on the gut and overall health in longer-term studies, for instance, the long-term effects of a KD on the fecal microbiota in 25 patients with multiple sclerosis (MS) (69). Like many autoimmune diseases, MS is associated with gut pathologies, with gut dysbiosis and intestinal permeability potentially preceding the development of autoimmune (70). Swidsinski et al. (69) found that patients with MS tended to have reduced numbers of *Roseburia*, *Bacteroides*, and *Faecalibacterium prausnitzii* organisms at baseline than healthy individuals. The effects of a 6-month therapeutic KD were biphasic: "In the short term, bacterial concentrations and diversity were further reduced. They
<figure><img src="image_5.png" /><figcaption>**FIG 2** The many substrates and pathways that contribute to energy production in the intestinal epithelium. TCA, tricarboxylic acid.</figcaption></figure>

started to recover at week 12 and exceeded significantly the baseline values after 23 to 24 weeks on the ketogenic diet" (69). Such studies are inconclusive since they are relatively uncontrolled, but they nevertheless further support the need to consider the time course of dietary adaptation before determining whether a diet is beneficial or detrimental for the gut microbiota.

In another context, researchers investigated whether the beneficial effects of a therapeutic KD on epilepsy are mediated through the gut microbiota (71). The KD reduced microbial diversity but increased the abundance of *Akkermansia muciniphila* and *Parabacteroides* spp. By treating mice fed a normal high-carbohydrate diet with these specific microbes, the researchers demonstrated that these taxa were at least partly responsible for the antiepileptic effects of the KD. Similar microbial changes, as well as increases in butyrate and propionate, have been observed when using a modified Mediterranean ketogenic diet in Alzheimer's patients (72).

Together with the David et al. study (18), these findings suggest that, while short-term dietary changes can rapidly shift the composition of the gut microbiota, these changes may not be detrimental and may provide benefit. They also underline the need to look at long-term dietary changes and collect samples at multiple time points to determine the true effect of an intervention like a therapeutic KD, including whether the benefits or any risks are mediated through changes in the microbiota.

**Considering alternative pathways.** Multiple strands of evidence question an assumption about "normal" metabolic pathways in the gut. Alongside the SCFAs mentioned above, there are several other molecules that can serve as sources of fuel for gut epithelial cells. The very idea of a "preferred" fuel source may be skewed from studying people (and rodents) who eat a large amount of microbiota-accessible carbohydrates. In other words, while butyrate production may be reduced on a KD, other molecules can potentially take butyrate's place to help maintain gut barrier function.

This shift to an alternative pathway is what we might expect from the perspective of metabolic flexibility, where we see a potential analogy between the butyrate-gut connection and glucose-brain connection. While glucose is a necessary fuel for the brain, we have known for some time that in the (relative) absence of carbohydrates, the body will shift its metabolism from glucose to fatty acids, producing ketone bodies,
such as βHB, to support brain metabolism (73). This kind of fatty acid-based metabo-
lism appears to have numerous neurological benefits and may be a "preferred" fuel for
the brain during both development (74) and aging (75). Similarly, while researchers
repeatedly stress that gut epithelial cells are uniquely fueled by the butyrate produced
by our resident microbiota after consuming "microbiota-accessible carbohydrates"
(17), here too the body is flexible, with βHB also being capable of supporting energy
requirements in the gut.

In fact, there are at least four molecules that can replace butyrate: isobutyrate, ace-
toacetate, βHB, and bile-derived acylcarnitines (Fig. 2). Isobutyrate is a metabolite of
protein fermentation that is typically produced at lower levels than butyrate. When bu-
tyrate is less abundant, isobutyrate can be absorbed from the gut lumen by gut epithe-
lial cells and metabolized for energy (76). Fecal isobutyrate was found to be elevated
in humans consuming a KD (18). Moreover, isobutyrate can stimulate the same recep-
tors as butyrate in the gut (GPR41, GPR43, and GPR109a) to influence mucus secretion,
antimicrobial peptide release, and immune regulation (77), and while isobutyrate may
be produced at lower levels on a moderately high-protein diet than butyrate would be
produced on a high-carbohydrate diet (18), isobutyrate appears to be a more potent
stimulator of butyrate receptor GPR41 (FFAR3) than butyrate itself (78). In other words,
what isobutyrate lacks in concentration relative to butyrate, it may make up for in po-
tency. Relatedly, this may provide a reason not to confuse high-protein and refined HF
diets, since the most abundant end products of protein fermentation or catabolism are
SCFAs, such as isobutyrate (79). As suggested by David et al., it might be the overall
context in which protein fermentation occurs that is important to downstream health
outcomes rather than the protein fermentation itself.

Like butyrate, βHB can also stimulate GPR109a, reducing intestinal inflammation (80, 81). Most notably, however, both βHB and its related ketone body acetoacetate are intermediates in the pathway for butyrate metabolism; when butyrate is taken up by gut epithelial cells, it is converted into βHB first and then acetoacetate before being broken down further for energy (Fig. 2) (82). Gut epithelial cells express the monocarboxylate transporter MCT1, a primary ketone body transporter on the basolateral surface (83), and several papers suggest that gut epithelial cells are capable of utilizing ketone bodies from the vascular bed (84, 85). As gastrointestinal inflammation and mucosal damage can impair butyrate uptake from the intestinal lumen (86, 87), circulating ketones may provide a potential therapeutic option in certain patients with gastrointestinal disease.

To our knowledge, no studies have assessed the effects of ketones or a KD on gut
barrier function. However, a recent study found that ketone body signaling regulates
the normal function of intestinal stem cells (ISC) and their ability to respond to injury
(88). In this study, β-hydroxy β-methylbutyryl-coenzyme A (HMG-CoA) synthase 2
(HMGCS2), a rate-limiting step in ketone production, was enriched in small intestinal
stem cells. Ablating the *Hmgcs2* gene in mice diminished βHB levels in the crypts,
compromising ISC function and regeneration of the gut epithelium after injury.
Exogenous βHB rescued ISC function and partially restored intestinal regeneration. A
KD also increased HMGCS2 expression and ISC number, function, and postinjury
regeneration. In contrast, a glucose-supplemented diet suppressed ISC ketogenesis
and skewed the differentiation of ISC toward goblet and Paneth cells. Notably, once
stem cells had differentiated into mature epithelial cells and migrated out of the
crypt, they expressed very little HMGCS2. This suggests that mature epithelial cells
do not possess the ability to generate large amounts of ketones through the classical
ketogenic pathway (via condensation of two molecules of acetyl-CoA), though we
know that they have the ability to utilize ketones.

Thus, it follows that if (i) a KD produces high levels of ketones in mature intestinal
epithelial cells (as Ang et al. [65] found) and (ii) these are not being generated in
mature epithelial cells (as is suggested by the lack of HMGCS2 in the work of Chen et
al. [88]), then the ketones are almost certainly coming from circulation. Along these
lines, the authors write, "Because exogenous ketones rectify Hmgcs2 loss in vitro and in
vivo, liver or other nonintestinal sources of ketones may substitute or supplement ISC-generated ketones in KTD-mediated regeneration, where circulating ketone levels are highly elevated" (88).

Lastly, it has recently been shown that not only can colonic epithelial cells oxidize both short- and long-chain fatty acids but also, through mitochondrial metabolism, these cells can oxidize medium- and long-chain acyl-carnitines that are delivered from biliary secretions (89). This has clinical relevance in that a reduction in these metabolites may contribute to colonic inflammation. Importantly, this provides yet another host-derived energy source for the epithelium during low-carbohydrate diets to complement the three discussed above. We will return to this below since bile acid secretion is a common concern with HF diets.

To conclude, we suggest that a more nuanced picture of how HF diets impact gut and overall health is required, with particular attention being paid to therapeutic KDs. By considering the alternative pathways by which ketones and KDs can influence gut function, we can move toward a more evolutionarily consistent picture of human gut variability. Nevertheless, research needs to clarify whether the benefits of lower carbohydrate or KDs come directly from increasing βHB, reducing inflammation, modifying insulin and glucose metabolism, reducing caloric intake, altering the gut microbiota, or other undetermined factors.

## HIGH-FAT DIETS, THE GUT, AND CRC— SETTLED SCIENCE?

We now briefly discuss colorectal cancer (CRC), where the HF diet-microbiota link is commonly highlighted. While the 2019 consensus statement by the International Cancer Microbiome Consortium acknowledges the need for better human studies into how the microbiota influences carcinogenesis (16), it nevertheless implicates a high-fat, low-fiber Western-style diet in changes in mucosal biomarkers of cancer risk (90). This follows the WHO's 2015 classification of "red and processed meat" as a (class 2A) probable carcinogen, which relies heavily on preclinical and mechanistic data due to our current inability to isolate the effects of individual foods in clinical epidemiological studies (91, 92). A recent review in *Nature* echoes the WHO's position on processed and red meat and cancer, aiming to establish an "oncogenic" CRC-associated microbiota (93).

In their *Nature* review, Janney et al. rely on the finding that CRC etiology is largely environmental, potentially accounting for 70 to 90% of the disease risk (93). Here, "diet" is strongly implicated, and the authors stress those diets that are low in fiber and high in fat and "red meat." However, in the two references used to support this claim, only one mentions "red meat" (94) and only in the context of epidemiological associations, which are often plagued by healthy-user bias and significant reporting error (95, 96). Moreover, Janney et al. (93) vacillate between the terms "high-fat" and "Westernized high-fat," which introduces confounders. Some mechanistic studies in mice do appear to support this HF diet-cancer link (97–100), but this might be tumor type specific (101, 102). As the "HF diets" studied are admixtures of refined sugars and/or hydrogenated oils, as mentioned above, this conflates a junk food-mimicking diet with any diet high in fat. Such results thus remain inconclusive (103), as we discuss below. Some of the suggested mechanisms connecting diet and CRC are protein fermentation, secondary bile acids, and increased levels of reactive oxygen species and reactive nitrogen species due to increased bile acid, heme iron, decreases in SCFAs, and specific microbial changes, e.g., an increased *Bilophila* abundance. As discussed above and explored in more detail below, the first three mechanisms are not clearly pathogenic, the putative antitumorigenic properties of butyrate (104) can also be obtained through alternative mechanisms, the relevance of heme iron remains to be seen (105, 106), and the significance of microbial changes depends on the broader physiological context and the relative abundances of microbes.

Since various conditions, such as irritable bowel syndrome (IBS), ulcerative colitis, and Crohn's disease, appear to increase one's risk for developing CRC (107–109), further
research might consider the role of KDs in these contexts (110). Unfortunately, few such studies have been performed, and we are often left with case studies (111, 112).

We can, however, piece together various strands of evidence suggesting a more nuanced picture on animal fats as CRC risk factors. First, some mouse models and pre-clinical studies show KDs or ketones to be cancer suppressive (113, 114), perhaps primarily through glucose restriction (103) and by increasing intratumoral oxidative stress, leading to tumor cell apoptosis (115). Variations of therapeutic KDs might provide benefits for breast cancer by decreasing tumor necrosis factor alpha (TNF-α) and insulin while increasing interleukin 10 (IL-10) (116) and may be a promising adjuvant therapy for various cancers (117–121). However, as many of these studies are in animal models, caution is warranted (122, 123). At the least, these studies and recent reviews suggest a variety of mechanisms by which animal-food-based KDs may have beneficial effects on colorectal and other cancers.

This evidence converges with studies suggesting that reducing red meat and total fat consumption, while increasing fruit and grain consumption, does not reduce the risk for polyp reoccurrence even after 8 to 16 years (124–126) and has unclear risk benefits for CRC or any kind of cancer (127–129). Animal models suggesting that beef consumption does not promote cancer, that bacon may be protective, and that unsaturated fat may have carcinogenic effects (130, 131) all increase the likelihood that strong statements on animal foods and cancer are premature. Similarly, a growing number of reviews and meta-analyses weaken the links between meat consumption and cancer (132–136) and possibly overall health (137, 138), with some showing inverse correlations between meat intake and overall mortality in specific cohorts (139) and lower rates of CRC in meat eaters than in vegetarians (140). Studies that correlate meat intake with CRC also suggest a complex etiology due to contributing factors, such as obesity and hyperinsulinemia (141). As most of these studies have limitations, more research will be needed (142, 143), with the overall balance of evidence not currently appearing to support an independent effect of animal-based foods on the incidence of CRC. Given meat's long-term presence in the hominid diet (144–147), it is more likely that modern dietary components and cooking techniques are driving cancer risk factors through their effects on our guts and general physiology.

## POSSIBLE OBJECTIONS AND CONCERNS

We acknowledge that there are likely to be various objections concerning the effects of fat and protein on our gut microbiota. We will address three of these, lipo-polysaccharides, trimethylamine-N-oxide (TMAO), and secondary bile acids, and end with a cautionary note concerning KDs and hydrogen sulfide ($H_2S$).

**LPS.** High-fat diets are commonly said to increase intestinal absorption of lipopolysaccharides (LPS), which are a group of endotoxins found in the cell walls of Gram-negative bacteria. If LPS gets into circulation, it can cause low-grade systemic inflammation (148), with the type and extent of the response dependent on the microbial source and LPS subtype (149). When we consume more long-chain fatty acids, our body makes more chylomicrons, which can carry LPS (150). Indeed, fat-enriched meals have been shown to moderately increase serum levels of LPS in both mice and humans (151, 152). While worth considering, we believe that, for several reasons, this is unlikely to contribute significantly to systemic inflammation in those consuming KDs.

First, several studies suggest that the transport of LPS by chylomicrons may confer an advantage because it favors the clearance of LPS by the liver, reducing LPS toxicity (153, 154). Moreover, chylomicrons have an innate ability to inactivate LPS (155), and the increased absorption of LPS appears to reduce inflammation in the gut mucosa (156). Similar beneficial adaptations can be seen with exercise, which increases LPS translocation but also LPS clearance, for instance via upregulation of anti-LPS immunoglobulins (157). This is important since the primary mode of systemic exposure to LPS is not through fat absorption but through reduced gut barrier function (158). When
the gut is permeable, large amounts of LPS can leak into the submucosa and blood-stream, causing localized gut immune responses and systemic inflammation (159). This is likely to be a consequence, rather than a cause, of the metabolic endotoxemia associated with metabolic syndrome and cardiovascular disease, with poor systemic health subsequently impairing gut barrier function (160). Certain LPS subtypes have also been suggested to have beneficial immunomodulating roles (161). In other words, compared to the intestinal permeability associated with inflammatory gastrointestinal conditions, chylomicron-induced LPS absorption is likely minimal. One hypothesis emerging from these various studies that can be tested in humans is whether, for patients dealing with severe intestinal permeability, chylomicron-induced detoxification of LPS reduces inflammation enough to facilitate healing of the gut epithelium.

Importantly, many of the above-described studies are preclinical, but they nevertheless point to promising mechanisms that are being pursued in human studies to better contextualize the various roles of LPS. If fat-induced LPS absorption were an issue, we would expect to see increased systemic inflammation in those fed a KD. In contrast, humans consuming therapeutic KDs generally experience a reduction in systemic inflammation (162), with possible anti-inflammatory mechanisms, including NLRP3 inflammasome inactivation (163), modulation of TNF-α, IL-6, IL-8, MCP1, E-selectin, I-CAM, and PAI-1 (all studied in a registered clinical trial [164]), and an improved cytosolic NADH/ NAD⁺ ratio (165). Taken together, these studies should assuage some concerns of LPS absorption following fat intake.

**TMAO.** Conventional nutrition science has long considered diets rich in animal-based foods a risk factor for cardiovascular disease. A recent mechanism of interest is TMAO (61). Increased concentrations of TMAO in circulation have been shown to contribute to atherosclerosis in animal models and correlate with cardiovascular disease risk in human studies (166). Certain gut bacteria convert choline and carnitine, both prominent in animal foods, to trimethylamine (TMA), which is then absorbed and oxidized in the liver to TMAO. However, some *in vitro* and animal evidence points to an altered small intestinal microbiota characterized by an overabundance of choline-consuming, TMA-producing *Escherichia coli* as the culprit for high TMAO, rather than excess consumption of animal products (167).

More importantly, a recent study suggests that gut microbiota composition can influence the amount of TMAO produced with an animal-based diet. Bacteria in the genus *Bilophila*, which tend to increase in subjects on an animal-based diet, may be able to help circumvent TMAO production by degrading TMA to dimethylamine (DMA) (168). Further analysis revealed that in a human cohort, *Bilophila* was significantly more abundant in the microbiotas of healthy individuals than in those with cardiovascular disease. As such, *Bilophila*'s pathogenicity may be context dependent, and it may even be beneficial for mitigating cardiovascular disease. Additionally, recent Mendelian randomization studies have suggested that increased TMAO in those at risk of cardiovascular disease may be a consequence of metabolic dysfunction, rather than an independent risk factor for disease risk (169). For multiple reasons, we thus believe that TMAO may not be a significant independent contribution to cardiovascular disease, with gut and overall health more likely to be the critical drivers of any associations.

**Bile acids.** It is commonly argued that an HF diet might be detrimental to the gut microbiota and gut barrier because it stimulates increased secretion of secondary bile acids (170). While some studies have shown that sustained exposure of the gut barrier to high concentrations of bile acids (above 400 µM) results in intestinal permeability (171), physiologic doses of bile acids (which may be nontoxic up to 50 to 100 µM [172]) have several potential benefits. For instance, bile acids have been shown to support barrier function by inducing the secretion of mucus from goblet cells, promoting epithelial cell migration, and boosting gut innate immune defenses (173). They can have antimicrobial properties, helping to regulate the gut microbiota, and may protect against small intestinal dysbiosis (174, 175). Several studies even suggest that bile acids activate enteroendocrine cells to release serotonin, which helps promote gut motility
(176). Evidence for the physiological role of biliary secretions in producing an alternative fuel (acyl-carnitines) for gut epithelial cells was discussed above (89).

Exploring the complexities of every type of conjugated and deconjugated bile acid is beyond the scope of this article (177), but this should be sufficient to question the assumption that bile acid secretion resulting from the consumption of animal foods is inherently pathogenic.

**H**₂*S*. There is one important caveat concerning KDs and individuals with H₂S-associated bacterial overgrowth. H₂S is normally produced in the body and acts as an important signaling molecule. Certain gut bacteria can also produce H₂S, which at low concentrations has been shown to protect the gut against injury, stimulate gut motility, and support ulcer healing (178). However, an overabundance of these bacteria can lead to excess H₂S, which has been linked to diarrhea, gut hypersensitivity, IBS, irritable bowel disease (IBD), and colorectal cancer (179), thereby suggesting pleotropic and dose-dependent effects (178). Some of the common H₂S producers in the human gut, *Desulfovibrio* spp., *Bilophila wadsworthia*, and *Fusobacterium nucleatum*, tend to thrive on a diet that is high in animal protein and fat (180, 181). Thus, in patients with an overabundance of these microbes, it is probably best to avoid a ketogenic or high-fat diet until they can address this issue. Adding fiber to the diet (e.g., *Brassica* vegetables) may reduce the abundance of sulfate-reducing bacteria (182), further suggesting that the dietary context accompanying protein and fat consumption be considered.

Overall, we do not believe that there is sufficient evidence to suggest that the production of TMAO or LPS following animal protein/fat consumption or the physiologic increase of bile acids seen on a KD is harmful to the gut microbiota or gut barrier function. These metabolites might exacerbate ongoing pathological conditions of dysbiosis, but there are reasons to believe that they are not harmful under physiological conditions.

## LOOKING AHEAD: REDIRECTING RESEARCH FOR NUANCE

We conclude by suggesting how nutritional microbiota research might proceed in terms of what questions need to be asked or answered and how studies could be carried out.

1. Researchers should be more explicit about the kind of HF diets used. A diet mimicking a Western diet is not nutritionally equivalent to all HF diets, which vary in terms of fat sources and overall diet quality. Even changing the language in articles from "high-fat" to "high-fat, high-sugar" would better reflect the diet studied and could alter perceptions. From there, it will be helpful to study levels of fiber in HF or animal-based diets, which represent variations on the theme of nutritionally replete low-carbohydrate or therapeutic KDs.

2. While studies are starting to focus on different fat sources (4, 183, 184), still more are needed with as few confounders as possible. Some of the most problematic for mechanistic studies include the use of refined/hydrogenated fats and seed oils, which likely have rather different metabolic effects than fats from whole plant and animal foods, especially when these oils are mixed with refined sugars. Nutritional epidemiology should not only account for fat sources and dietary patterns/context but should explicitly address (un)healthy-user biases. The problem is not that such biases exist, as some may be unavoidable. The problem is that they remain under-discussed.

3. We should clearly acknowledge the limitations of animal research to inform human health/nutrition and our limited knowledge of what constitutes a "healthy" gut microbiota. Since it is likely that gut health encompasses more variability than is often acknowledged, we need to further test the evidence that humans evolved to tolerate, adapt to, and perhaps thrive on a variety of dietary patterns, with varying proportions of fiber, protein, and fat. An interdisciplinary approach may better elucidate the health effects of diet-gut interactions.
4. Researchers should explicitly state whether their interpretation considers the physiological context or makes claims based solely on isolated mechanisms and nutritional epidemiology. Properly labeling evidence and placing observations in the broader context of research can help prevent potentially biased interpretations.

5. Similarly, researchers might carefully consider the differences in host and microbial metabolism. For instance, studies relying on fecal samples might skew towards microbes found in the large intestine or colon, where carbohydrates are digested and metabolized. This may obscure the role of microbial and host responses in the small intestine (9, 185), thereby underrepresenting the microbes that are more involved in fatty acid catabolism or the production of lipase coenzymes in the jejunum. Similarly, by focusing largely on microbial metabolism of carbohydrates and fiber, we might be overlooking host-specific metabolism, which appears to be highly adaptable to relative levels of dietary fat and protein.

6. Clinicians can also remain open-minded to alternative dietary approaches. One implication of considering alternative energy sources is that in the presence of a "healthy" microbiota and gut mucosa, butyrate is probably sufficient to fuel the gut. However, if patients (i) have ulcerative colitis or other mucosal damage, with impaired butyrate uptake, (ii) have gut dysbiosis characterized by a lack of butyrate producers, or (iii) are on a restrictive diet, such as a low-FODMAP (fermentable oligosaccharides, disaccharides, monosaccharides, and polyols) diet or the specific carbohydrate diet (SCD), resulting in reduced butyrate production, it may be wise for clinicians to consider "nontraditional" therapeutic options, such as KDs, to support gut epithelial metabolism, at least until treating the underlying gut pathologies and healing the gut mucosa.

7. Finally, it will be important to objectively weigh the evidence concerning plants, animal fats, and proteins. Conventional wisdom holds the belief that plants are definitively healthful and animal products are at least potentially harmful. The effects of this belief can lead to conflicts of interest in nutrition studies more generally (186) and may influence the decision-making leading to dietary guideline statements that provide strong recommendations despite abundant evidence supporting the idea that humans can thrive on a diverse range of diets (187).

In the end, we hope that more time and research will help to uncover these biases and lead to a more accurate depiction of the responsiveness of the human gut and its microbes to nutritional variations.

## ACKNOWLEDGMENTS

Jonathan Sholl received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement 637647), IDEM. Once this grant was completed, he received funding from the Université de Bordeaux, Région Nouvelle-Aquitaine, and SIRIC BRIO.

## REFERENCES

1. Redondo-Useros N, Nova E, González-Zancada N, Díaz LE, Gómez-Martínez S, Marcos A. 2020. Microbiota and lifestyle: a special focus on diet. *Nutrients* 12:1776. https://doi.org/10.3390/nu12061776

2. Maskarinec G, Hullar MAJ. 2020. Understanding the interaction of diet quality with the gut microbiome and their effect on disease. *J Nutr* 150:654–655. https://doi.org/10.1093/jn/nxaa015

3. Kolodziejczyk AA, Zheng D, Elinav E. 2019. Diet-microbiota interactions and personalized nutrition. *Nat Rev Microbiol* 17:742–753. https://doi.org/10.1038/s41579-019-0256-8

4. Wolters M, Ahrens J, Romani-Pérez M, Watkins C, Sanz Y, Benítez-Páez A, Stanton C, Günther K. 2019. Dietary fat, the gut microbiota, and metabolic health—a systematic review conducted within the MyNewGut project. *Clin Nutr* 38:2504–2520. https://doi.org/10.1016/j.clnu.2018.12.024

5. Rinninella E, Cintoni M, Raoul P, Lopetuso LR, Scaldaferris F, Pulcini G, Miggiano GAD, Gasbarrini A, Mele MC. 2019. Food components and

dietary habits: keys for a healthy gut microbiota composition. *Nutrients* 11:2393. https://doi.org/10.3390/nu11102393

6. Valdes AM, Walter J, Segal E, Spector TD. 2018. Role of the gut microbiota in nutrition and health. *BMJ* 361:k2179. https://doi.org/10.1136/bmj.k2179

7. Gentile CL, Weir TL. 2018. The gut microbiota at the intersection of diet and human health. *Science* 362:776–780. https://doi.org/10.1126/science.aau5812

8. Singh RK, Chang H-W, Yan D, Lee KM, Ucmak D, Wong K, Abrouk M, Farahnik B, Nakamura M, Zhu TH, Bhutani T, Liao W. 2017. Influence of diet on the gut microbiome and implications for human health. *J Transl Med* 15:73. https://doi.org/10.1186/s12967-017-1175-y

9. Sonnenburg JL, Bäckhed F. 2016. Diet-microbiota interactions as moderators of human metabolism. *Nature* 535:56–64. https://doi.org/10.1038/nature18846
10. Dzutsev A, Badger JH, Perez-Chanona E, Roy S, Salcedo R, Smith CK, Trinchieri G. 2017. Microbes and cancer. Annu Rev Immunol 35:199-228. https://doi.org/10.1146/annurev-immunol-051116-052133.

11. Schwabe RF, Jobin C. 2013. The microbiome and cancer. Nat Rev Cancer 13:800-812. https://doi.org/10.1038/nrc3610.

12. Barrett M, Hand CK, Shanahan F, Murphy T, O'Toole PW. 2020. Mutagenesis by microbe: the role of the microbiota in shaping the cancer genome. Trends Cancer 6:277-287. https://doi.org/10.1016/j.trecan.2020.01.019.

13. Holmes E, Kinross J, Gibson GR, Burcelin R, Jia W, Pettersson S, Nicholson JK. 2012. Therapeutic modulation of microbiota-host metabolic interactions. Sci Transl Med 4:137rv6. https://doi.org/10.1126/scitranslmed.3004244.

14. Xavier JB, Young VB, Skufca J, Ginty F, Testerman T, Pearson AT, Macklin P, Mitchell A, Shmulevich I, Xie L, Caporaso JG, Crandall KA, Simone NL, Godoy-Vitorino F, Griffin TJ, Whiteson KL, Gustafson HH, Slade DJ, Schmidt TM, Walther-Antonio MRS, Korem T, Webb-Robertson B-JM, Styczynski MP, Johnson WE, Jobin C, Ridlon JM, Koh AY, Yu M, Kelly L, Wargo JA. 2020. The cancer microbiome: distinguishing direct and indirect effects requires a systemic view. Trends Cancer 6:192-204. https://doi.org/10.1016/j.trecan.2020.01.004.

15. European Society of Neurogastroenterology and Motility. The influence of diet on gut microbiota. European Society of Neurogastroenterology and Motility, Vienna, Austria.

16. Scott AJ, Alexander JL, Merrifield CA, Cunningham D, Jobin C, Brown R, Alverdy J, O'Keefe SJ, Gaskins HR, Teare J, Yu J, Hughes DJ, Verstraelen H, Burton J, O'Toole PW, Rosenberg DW, Marchesi JR, Kinross JM. 2019. International Cancer Microbiome Consortium statement on the role of the human microbiome in carcinogenesis. Gut 68:1624-1632. https://doi.org/10.1136/gutjnl-2019-318556.

17. Sonnenburg ED, Sonnenburg JL. 2014. Starving our microbial self: the deleterious consequences of a diet deficient in microbiota-accessible carbohydrates. Cell Metab 20:779-786. https://doi.org/10.1016/j.cmet.2014.07.003.

18. David LA, Maurice CF, Carmody RN, Gootenberg DB, Button JE, Wolfe BE, Ling AV, Devlin AS, Varma Y, Fischbach MA, Biddinger SB, Dutton RJ, Turnbaugh PJ. 2014. Diet rapidly and reproducibly alters the human gut microbiome. Nature 505:559-563. https://doi.org/10.1038/nature12820.

19. Smith RL, Soeters MR, Wüst RCI, Houtkooper RH. 2018. Metabolic flexibility as an adaptation to energy resources and requirements in health and disease. Endocr Rev 39:489-517. https://doi.org/10.1210/er.2017-00211.

20. Storlien L, Oakes ND, Kelley DE. 2004. Metabolic flexibility. Proc Nutr Soc 63:363-368. https://doi.org/10.1079/PNS2004349.

21. Berg G, Rybakova D, Fischer D, Cernava T, Vergès M-CC, Charles T, Chen X, Cocolin L, Eversole K, Corral GH, Kazou M, Kinkel L, Lange L, Lima N, Loy A, Macklin JA, Maguin E, Mauchline T, McClure R, Mitter B, Ryan M, Sarand I, Smidt H, Schelkle B, Roume H, Kiran GS, Selvin J, de Souza RSC, van Overbeek L, Singh BK, Wagner M, Walsh A, Sessitsch A, Schloter M. 2020. Microbiome definition re-visited: old concepts and new challenges. Microbiome 8:103. https://doi.org/10.1186/s40168-020-00905-x.

22. Proctor L. 2019. Priorities for the next 10 years of human microbiome research. Nature 569:623-625. https://doi.org/10.1038/d41586-019-01654-0.

23. Bäckhed F, Fraser CM, Ringel Y, Sanders ME, Sartor RB, Sherman PM, Versalovic J, Young V, Finlay BB. 2012. Defining a healthy human gut microbiome: current concepts, future directions, and clinical applications. Cell Host Microbe 12:611-622. https://doi.org/10.1016/j.chom.2012.10.012.

24. McBurney MI, Davis C, Fraser CM, Schneeman BO, Huttenhower C, Verbeke K, Walter J, Latulippe ME. 2019. Establishing what constitutes a healthy human gut microbiome: state of the science, regulatory considerations, and future directions. J Nutr 149:1882-1895. https://doi.org/10.1093/jjn/nxz154.

25. Shanahan F, Ghosh TS, O'Toole PW. 2021. The healthy microbiome—what is the definition of a healthy gut microbiome? Gastroenterology 160:483-494. https://doi.org/10.1053/j.gastro.2020.09.057.

26. Warden CH, Fisler JS. 2008. Comparisons of diets used in animal models of high-fat feeding. Cell Metab 7:277. https://doi.org/10.1016/j.cmet.2008.03.014.

27. Pellizzoni MA, Ricci MR. 2018. Effects of rodent diet choice and fiber type on data interpretation of gut microbiome and metabolic disease research. Curr Protoc Toxicol 77:e55. https://doi.org/10.1002/cptx.55.

28. Jones D. 2008. In research: mice diet studies faulted. UC Davis, Davis, CA. https://www.ucdavis.edu/news/research-mice-diet-studies-faulted-%E2%80%98endless-possibilities%E2%80%99.

29. Paoli A, Rubini A, Volek JS, Grimaldi KA. 2013. Beyond weight loss: a review of the therapeutic uses of very-low-carbohydrate (ketogenic) diets. Eur J Clin Nutr 67:789-796. https://doi.org/10.1038/ejcn.2013.116.

30. Ludwig DS. 2020. The ketogenic diet: evidence for optimism but high-quality research needed. J Nutr 150:1354-1359. https://doi.org/10.1093/jn/nxz308.

31. Khan S, Waliullah S, Godfrey V, Khan MAW, Ramachandran RA, Cantarel BL, Behrendt C, Peng L, Hooper LV, Zaki H. 2020. Dietary simple sugars alter microbial ecology in the gut and promote colitis in mice. Sci Transl Med 12:eay6218. https://doi.org/10.1126/scitranslmed.aay6218.

32. Gardner CD, Kiazand A, Alhassan S, Kim S, Stafford RS, Balise RR, Kraemer HC, King AC. 2007. Comparison of the Atkins, Zone, Ornish, and LEARN diets for change in weight and related risk factors among overweight premenopausal women: the A to Z Weight Loss Study: a randomized trial. JAMA 297:969. https://doi.org/10.1001/jama.297.9.969.

33. Gardner CD, Trepanowski JF, Del Gobbo LC, Hauser ME, Rigdon J, Ioannidis JPA, Desai M, King AC. 2018. Effect of low-fat vs low-carbohydrate diet on 12-month weight loss in overweight adults and the association with genotype pattern or insulin secretion: the DIETFITS randomized clinical trial. JAMA 319:667-679. https://doi.org/10.1001/jama.2018.0245.

34. Wright N, Wilson L, Smith M, Duncan B, McHugh P. 2017. The BROAD Study: a randomised controlled trial using a whole food plant-based diet in the community for obesity, ischaemic heart disease or diabetes. Nutr Diabetes 7:e256. https://doi.org/10.1038/nutd.2017.3.

35. Borghjid S, Feinman R. 2012. Response of C57BI/6 mice to a carbohydrate-free diet. Nutr Metab (Lond) 9:69. https://doi.org/10.1186/1743-7075-9-69.

36. Ericson U, Brunkwall L, Hellstrand S, Nilsson PM, Orho-Melander M. 2020. A health-conscious food pattern is associated with prediabetes and gut microbiota in the Malmö Offspring Study. J Nutr 150:861-872. https://doi.org/10.1093/jn/nxz293.

37. Brunstrom JM, Drake ACL, Forde CG, Rogers PJ. 2018. Undervalued and ignored: are humans poorly adapted to energy-dense foods? Appetite 120:589-595. https://doi.org/10.1016/j.appet.2017.10.015.

38. Hall KD, Ayuketah A, Brychta R, Cai H, Cassimatis T, Chen KY, Chung ST, Costa E, Courville A, Darcey V, Fletcher LA, Forde CG, Gharib AM, Guo J, Howard R, Joseph PV, McGehee S, Ouwerkerk R, Raisinger K, Rozga I, Stagliano M, Walter M, Walter PJ, Yang S, Zhou M. 2019. Ultra-processed diets cause excess calorie intake and weight gain: an inpatient randomized controlled trial of ad libitum food intake. Cell Metab 30:67-77.e3. https://doi.org/10.1016/j.cmet.2019.05.008.

39. Hallberg SJ, McKenzie AL, Williams PT, Bhanpuri NH, Peters AL, Campbell WW, Hazbun TL, Volk BM, McCarter JP, Phinney SD, Volek JS. 2018. Effectiveness and safety of a novel care model for the management of type 2 diabetes at 1 year: an open-label, non-randomized, controlled study. Diabetes Ther 9:583-612. https://doi.org/10.1007/s13300-018-0373-9.

40. Phinney S, Bailey B, Volek J. 2018. The ten defining characteristics of a well-formulated ketogenic diet. Virta Health Corp, San Francisco, CA. https://www.virtahealth.com/blog/well-formulated-ketogenic-diet.

41. Ludwig DS, Willett WC, Volek JS, Neuhouse ML. 2018. Dietary fat: from foe to friend? Science 362:764-770. https://doi.org/10.1126/science.aau2096.

42. Athinarayanan SJ, Hallberg SJ, McKenzie AL, Lechner K, King S, McCarter JP, Volek JS, Phinney SD, Krauss RM. 2020. Impact of a 2-year trial of nutritional ketosis on indices of cardiovascular disease risk in patients with type 2 diabetes. Cardiovasc Diabetol 19:208. https://doi.org/10.1186/s12933-020-01178-2.

43. Clemente JC, Ursell LK, Parfrey LW, Knight R. 2012. The impact of the gut microbiota on human health: an integrative view. Cell 148:1258-1270. https://doi.org/10.1016/j.cell.2012.01.035.

44. Gilbert JA, Blaser MJ, Caporaso JG, Jansson JK, Lynch SV, Knight R. 2018. Current understanding of the human microbiome. Nat Med 24:392-400. https://doi.org/10.1038/nm.4517.

45. Jiang H, Ling Z, Zhang Y, Mao H, Ma Z, Yin Y, Wang W, Tang W, Tan Z, Shi J, Li L, Ruan B. 2015. Altered fecal microbiota composition in patients with major depressive disorder. Brain Behav Immun 48:186-194. https://doi.org/10.1016/j.bbi.2015.03.016.

46. Johnson KV-A, Burnet PWJ. 2016. Microbiome: should we diversify from diversity? Gut Microbes 7:455-458. https://doi.org/10.1080/19490976.2016.1241933.

47. Schnorr SL, Candela M, Rampelli S, Centanni M, Consolandi C, Basaglia G, Turroni S, Biagi E, Peano C, Severgnini M, Fiori J, Gotti R, Bellis GD, Luiselli D, Brigidi P, Mabulla A, Marlowe F, Henry AG, Crittenden AN. 2014. Gut
microbiome of the Hadza hunter-gatherers. Nat Commun 5:3654. https://doi.org/10.1038/ncomms4654.

48. Petersen C, Round JL. 2014. Defining dysbiosis and its influence on host immunity and disease. Cell Microbiol 16:1024–1033. https://doi.org/10.1111/cmi.12308.

49. Hooks KB, O'Malley MA. 2017. Dysbiosis and its discontents. mBio 8: e01492-17. https://doi.org/10.1128/mBio.01492-17.

50. Laudadio I, Fulci V, Palone F, Stronati L, Cucchiara S, Carissimi C. 2018. Quantitative assessment of shotgun metagenomics and 16S rDNA amplicon sequencing in the study of human gut microbiome. OMICS 22:248–254. https://doi.org/10.1089/omi.2018.0013.

51. Litvak Y, Bäumler AJ. 2019. Microbiota-nourishing immunity: a guide to understanding our microbial self. Immunity 51:214–224. https://doi.org/10.1016/j.immuni.2019.08.003.

52. Foster KR, Schlüter J, Coyte KZ, Rakoff-Nahoum S. 2017. The evolution of the host microbiome as an ecosystem on a leash. Nature 548:43–51. https://doi.org/10.1038/nature23292.

53. McFall-Ngai M, Hadfield MG, Bosch TCG, Carey HV, Domazet-Lošo T, Douglas AE, Dubilier N, Eberl G, Fukami T, Gilbert SF, Hentschel U, King N, Kjelleberg S, Knoll AH, Kremer N, Mazmanian SK, Metcalf JL, Nealson K, Pierce NE, Rawls JF, Reid A, Ruby EG, Rumpho M, Sanders JG, Tautz D, Wernegreen JJ. 2013. Animals in a bacterial world, a new imperative for the life sciences. Proc Natl Acad Sci U S A 110:3229–3236. https://doi.org/10.1073/pnas.1218525110.

54. Mattson MP, Allison DB, Fontana L, Harvie M, Longo VD, Malaisse WJ, Mosley M, Notterpek L, Ravussin E, Scheer FAJL, Seyfried TN, Varady KA, Panda S. 2014. Meal frequency and timing in health and disease. Proc Natl Acad Sci U S A 111:16647–16653. https://doi.org/10.1073/pnas.1413965111.

55. Mattson MP, Moehl K, Ghena N, Schmaedick M, Cheng A. 2018. Intermittent metabolic switching, neuroplasticity and brain health. Nat Rev Neurosci 19:81–94. https://doi.org/10.1038/nrn.2017.156.

56. Smits SA, Leach J, Sonnenburg ED, Gonzalez CG, Lichtman JS, Reid G, Knight R, Manjurano A, Changalucha J, Elias JE, Dominguez-Bello MG, Sonnenburg JL. 2017. Seasonal cycling in the gut microbiome of the Hadza hunter-gatherers of Tanzania. Science 357:802–806. https://doi.org/10.1126/science.aan4834.

57. Fumagalli M, Moltke I, Grarup N, Racimo F, Bjerregaard P, Jorgensen ME, Korneliussen TS, Gerbault P, Skotte L, Linneberg A, Christensen C, Brandslund I, Jorgensen T, Huerta-Sanchez E, Schmidt EB, Pedersen O, Hansen T, Albrechtsen A, Nielsen R. 2015. Greenlandic Inuit show genetic signatures of diet and climate adaptation. Science 349:1343–1347. https://doi.org/10.1126/science.aab2319.

58. Girard C, Tomas N, Amyot M, Shapiro BJ. 2017. Gut microbiome of the Canadian Arctic Inuit. mSphere 2:e00297-16. https://doi.org/10.1128/mSphere.00297-16.

59. Fragiadakis GK, Wastyk HC, Robinson JL, Sonnenburg ED, Sonnenburg JL, Gardner CD. 2020. Long-term dietary intervention reveals resilience of the gut microbiota despite changes in diet and weight. Am J Clin Nutr 111:1127–1136. https://doi.org/10.1093/ajcn/nqaa046.

60. López-Otín C, Kroemer G. 2021. Hallmarks of health. Cell 184:33–63. https://doi.org/10.1016/j.cell.2020.11.034.

61. Frame LA, Costa E, Jackson SA. 2020. Current explorations of nutrition and the gut microbiome: a comprehensive evaluation of the review literature. Nutr Rev 78:798–812. https://doi.org/10.1093/nutrit/nuz106.

62. Krajmalnik-Brown R, Ilhan Z-E, Kang D-W, DiBaise JK. 2012. Effects of gut microbes on nutrient absorption and energy regulation. Nutr Clin Pract 27:201–214. https://doi.org/10.1177/0885336114361116.

63. Walker AW, Ince J, Duncan SH, Webster LM, Holtrop G, Ze X, Brown D, Stares MD, Scott P, Bergerat A, Louis P, McIntosh F, Johnstone AM, Lobley GE, Parkhill J, Flint HJ. 2011. Dominant and diet-responsive groups of bacteria within the human colonic microbiota. ISME J 5:220–230. https://doi.org/10.1038/ismej.2010.118.

64. Donohoe DR, Garge N, Zhang X, Sun W, O'Connell TM, Bunger MK, Bultman SJ. 2011. The microbiome and butyrate regulate energy metabolism and autophagy in the mammalian colon. Cell Metab 13:517–526. https://doi.org/10.1016/j.cmet.2011.02.018.

65. Ang QY, Alexander M, Newman JC, Tian Y, Cai J, Upadhyay V, Turnbaugh JA, Verdin E, Hall KD, Leibel RL, Ravussin E, Rosenbaum M, Patterson AD, Turnbaugh PJ. 2020. Ketogenic diets alter the gut microbiome resulting in decreased intestinal Th17 cells. Cell 181:1263–1275.e16. https://doi.org/10.1016/j.cell.2020.04.027.

66. Zambrano-Zaragoza JF, Romo-Martínez EJ, de Jesús Durán-Avelar M, García-Magallanes N, Vibanco-Pérez N. 2014. Th17 cells in autoimmune

and infectious diseases. Int J Inflamm 2014:651503. https://doi.org/10.1155/2014/651503.

67. Schroeder BO, Birchenough GMH, Ståhlman M, Arike L, Johansson MEV, Hansson GC, Bäckhed F. 2018. Bifidobacteria or fiber protects against diet-induced microbiota-mediated colonic mucus deterioration. Cell Host Microbe 23:27–40.e7. https://doi.org/10.1016/j.chom.2017.11.004.

68. Desai MS, Seekatz AM, Koropatkin NM, Kamada N, Hickey CA, Wolter M, Pudlo NA, Kitamoto S, Terrapon N, Muller A, Young VB, Henrissat B, Wilmes P, Stappenbeck TS, Núñez G, Martens EC. 2016. A dietary fiber-deprived gut microbiota degrades the colonic mucus barrier and enhances pathogen susceptibility. Cell 167:1339–1353.e21. https://doi.org/10.1016/j.cell.2016.10.043.

69. Swidsinski A, Dörffel Y, Loening-Baucke V, Gille C, Göktö Ö, Reißhauer A, Neuhaus J, Weylandt KH, Guschin A, Bock M. 2017. Reduced mass and diversity of the colonic microbiome in patients with multiple sclerosis and their improvement with ketogenic diet. Front Microbiol 8:1141. https://doi.org/10.3389/fmicb.2017.01141.

70. Fasano A, Shea-Donohue T. 2005. Mechanisms of disease: the role of investigational barrier function in the pathogenesis of gastrointestinal autoimmune diseases. Nat Clin Pract Gastroenterol Hepatol 2:416–422. https://doi.org/10.1038/nccpgasthep0259.

71. Olson CA, Vuong HE, Yano JM, Liang QY, Nusbaum DJ, Hsiao EY. 2018. The gut microbiota mediates the anti-seizure effects of the ketogenic diet. Cell 173:1728–1741.e13. https://doi.org/10.1016/j.cell.2018.04.027.

72. Nagpal R, Neth BJ, Wang S, Craft S, Yadav H. 2019. Modified Mediterranean-ketogenic diet modulates gut microbiome and short-chain fatty acids in association with Alzheimer's disease markers in subjects with mild cognitive impairment. EBioMedicine 47:529–542. https://doi.org/10.1016/j.ebiom.2019.08.032.

73. Cahill GF. 1976. Starvation in man. Clin Endocrinol Metab 5:397–415. https://doi.org/10.1016/s0300-595x(76)80028-x.

74. Wood TR, Stubbs BJ, Juul SE. 2018. Exogenous ketone bodies as promising neuroprotective agents for developmental brain injury. Dev Neurosci 40:451–462. https://doi.org/10.1159/000499563.

75. Cunnane SC, Courchesne-Loyer A, Vandenberghe C, St-Pierre V, Fortier M, Hennebelle M, Croteau E, Bocti C, Fulop T, Castellano C-A. 2016. Can ketones help rescue brain fuel supply in later life? Implications for cognitive health during aging and the treatment of Alzheimer's disease. Front Mol Neurosci 9:53. https://doi.org/10.3389/fnmol.2016.00053.

76. Jaskiewicz J, Zhao Y, Hawes JW, Shimomura Y, Crabb DW, Harris RA. 1996. Catabolism of isobutyrate by colonocytes. Arch Biochem Biophys 327:265–270. https://doi.org/10.1006/abbi.1996.0120.

77. Brown AJ, Jupe S, Briscoe CP. 2005. A family of fatty acid binding receptors. DNA Cell Biol 24:54–61. https://doi.org/10.1089/dna.2005.24.54.

78. Le Poul E, Loison C, Struyf S, Springael J-Y, Lannoy V, Decobecq M-E, Brezillon S, Dupriez V, Vassart G, Van Damme J, Parmentier M, Dethex M. 2003. Functional characterization of human receptors for short chain fatty acids and their role in polymorphonuclear cell activation. J Biol Chem 278:25481–25489. https://doi.org/10.1074/jbc.M301403200.

79. Oliphant K, Allen-Vercoe E. 2019. Macronutrient metabolism by the human gut microbiome: major fermentation by-products and their impact on host health. Microbiome 7:91. https://doi.org/10.1186/s40168-019-0704-8.

80. Graff EC, Fang W, Wanders D, Judd RL. 2016. Anti-inflammatory effects of the hydroxycarboxylic acid receptor 2. Metabolism 65:102–113. https://doi.org/10.1016/j.metabol.2015.10.001.

81. Thangaraju M, Cresci GA, Liu K, Ananth S, Gnanaprasakam JP, Browning DD, Mellinger JD, Smith SB, Digby GJ, Lambert NA, Prasad PD, Ganapathy V. 2009. GPR109A is a G-protein-coupled receptor for the bacterial fermentation product butyrate and functions as a tumor suppressor in colon. Cancer Res 69:2826–2832. https://doi.org/10.1158/0008-5472.CAN-08-4466.

82. Henning SJ, Hird FJ. 1972. Ketogenesis from butyrate and acetate by the caecum and the colon of rabbits. Biochem J 130:785–790. https://doi.org/10.1042/bj1300785.

83. Iwanaga T, Kishimoto A. 2015. Cellular distributions of monocarboxylate transporters: a review. Biomed Res 36:279–301. https://doi.org/10.2220/biomedres.36.279.

84. Roediger WEW. 1982. Utilization of nutrients by isolated epithelial cells of the rat colon. Gastroenterology 83:424–429. https://doi.org/10.1016/S0016-5085(82)80339-9.

85. Hanson PJ, Parsons DS. 1978. Factors affecting the utilization of ketone bodies and other substrates by rat jejunum: effects of fasting and of diabetes. J Physiol 278:55–67. https://doi.org/10.1113/jphysiol.1978.sp012292.
86. Ferrer-Picón E, Dotti I, Corraliza AM, Mayorgas A, Esteller M, Perales JC, Ricart E, Masamunt MC, Carrasco A, Tristán E, Esteve M, Salas A. 2020. Intestinal inflammation modulates the epithelial response to butyrate in patients with inflammatory bowel disease. Inflamm Bowel Dis 26:43–55. https://doi.org/10.1093/ibd/izz119.

87. Thibault R, De Coppet P, Daly K, Bourreille A, Cuff M, Bonnet C, Mosnier J, Galmiche J, Shirazi-Beechey S, Segain J. 2007. Down-regulation of the monocarboxylate transporter 1 is involved in butyrate deficiency during intestinal inflammation. Gastroenterology 133:1916–1927. https://doi.org/10.1053/j.gastro.2007.08.041.

88. Cheng C-W, Biton M, Haber AL, Gunduz N, Eng G, Gaynor LT, Tripathi S, Calibasi-Kocal G, Rickelt S, Butty VL, Moreno-Serrano M, Iqbal AM, Bauer-Rowe KE, Imada S, Ulutas MS, Mylonas C, Whary MT, Levine SS, Basbinar Y, Hynes RO, Mino-Kenudson M, Deshpande V, Boyer LA, Fox JG, Terranova C, Rai K, Piwnica-Worms H, Mihaylova MM, Regev A, Yilmaz ÖH. 2019. Ketone body signaling mediates intestinal stem cell homeostasis and adaptation to diet. Cell 178:1115–1131.e15. https://doi.org/10.1016/j.cell.2019.07.048.

89. Smith SA, Ogawa SA, Chau L, Whelan KA, Hamilton KE, Chen J, Tan L, Chen EZ, Keilbaugh S, Fogt F, Bewtra M, Braun J, Xavier RJ, Clish CB, Slaff B, Weljie AM, Bushman FD, Lewis JD, Li H, Master SR, Bennett MJ, Nakagawa H, Wu GD. 2020. Mitochondrial dysfunction in inflammatory bowel disease alters intestinal epithelial metabolism of hepatic acylcarcinines. J Clin Invest 131:e133371. https://doi.org/10.1172/JCI133371.

90. O'Keefe SJD, Li JV, Lahti L, Ou J, Carbonero F, Mohammed K, Posma JM, Kinross J, Wahl E, Ruder E, Vipperla K, Naidoo V, Mtshali L, Tims S, Puylaert PGB, DeLany J, Krasinskas A, Benefiel AC, Kaseb HO, Newton K, Nicholson JK, de Vos WM, Gaskins HR, Zoetendal EG. 2015. Fat, fibre and cancer risk in African Americans and rural Africans. Nat Commun 6:6342. https://doi.org/10.1038/ncomms7342.

91. Domingo JL, Nadal M. 2016. Carcinogenicity of consumption of red and processed meat: what about environmental contaminants? Environ Res 145:109–115. https://doi.org/10.1016/j.envres.2015.11.031.

92. IARC. 2015. IARC Monographs evaluate consumption of red meat and processed meat. Press release 240. World Health Organization, International Agency for Research on Cancer, Geneva, Switzerland.

93. Janney A, Powrie F, Mann EH. 2020. Host-microbiota maladaptation in colorectal cancer. Nature 585:509–517. https://doi.org/10.1038/s41586-020-2729-3.

94. Safiri S, Sepanlou SG, Ikuta KS, Bisignano C, Salimzadeh H, Delavari A, Ansari R, Roshandel G, Merat S, Fitzmaurice C, Force LM, Nixon MR, Abbastabar H, Abegaz KH, Afarideh M, Ahmadi A, Ahmed MB, Akinyemiju T, Ahlhabf D, Ali R, Alikhani M, Alipour V, Aljunid SM, Almadi MAH, Almasi-Hashiani A, Al-Raddadi RM, Alvis-Guzman N, Amini S, Anber NH, Ansari-Moghaddam A, Arabloo J, Arefi Z, Asghari Jafarabadi M, Azadmehr A, Badawi A, Baheiraei N, Bärnighausen TW, Basaleem H, Behzadifar M, Behzadifar M, Belayneh YM, Berhe K, Bhattacharyya K, Biadgo B, Bijani A, Biondi A, Bjorge T, Borzi AM, Bosetti C, Bou-Orm IR, Brenner H, Briko AN, et al. 2019. The global, regional, and national burden of colorectal cancer and its attributable risk factors in 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet Gastroenterol Hepatol 4:913–933. https://doi.org/10.1016/S2468-1253(19)30345-0.

95. Shrank WH, Patrick AR, Alan Brookhart M. 2011. Healthy user and related biases in observational studies of preventive interventions: a primer for physicians. J Gen Intern Med 26:546–550. https://doi.org/10.1007/s11606-010-1609-1.

96. Archer E, Pavela G, Lavie CJ. 2015. The inadmissibility of what we eat in America and NHANES dietary data in nutrition and obesity research and the scientific formulation of national dietary guidelines. Mayo Clin Proc 90:911–926. https://doi.org/10.1016/j.mayocp.2015.04.009.

97. Beyaz S, Mana MD, Roper J, Kedrin D, Saadatpour A, Hong S-J, Bauer-Rowe KE, Xifaras ME, Akkad A, Arias E, Pinello L, Katz Y, Shinagare S, Abu-Remaileh M, Mihaylova MM, Lamming DW, Dogum R, Guo G, Bell GW, Selig M, Nielsen GP, Gupta N, Ferrone CR, Deshpande V, Yuan G-C, Orkin SH, Sabatini DM, Yilmaz ÖH. 2016. High-fat diet enhances stemness and tumorigenicity of intestinal progenitors. Nature 531:53–58. https://doi.org/10.1038/nature17173.

98. Luo C, Puigserver P. 2016. Dietary fat promotes intestinal dysregulation. Nature 531:42–43. https://doi.org/10.1038/531042a.

99. Schulz MD, Atay Ç, Heringer J, Romrig FK, Schwitalla S, Aydin B, Ziegler PK, Varga J, Reindl W, Pommerenke C, Salinas-Riester G, Böck A, Alpert C, Blaut M, Polson SC, Brandl L, Kirchner T, Greten FR, Polson SW, Arkan MC. 2014. High-fat-diet-mediated dysbiosis promotes intestinal carcinogenesis

independently of obesity. Nature 514:508–512. https://doi.org/10.1038/nature13398.

100. Doerner SK, Reis ES, Leung ES, Ko JS, Heaney JD, Berger NA, Lambris JD, Nadeau JH. 2016. High-fat diet-induced complement activation mediates intestinal inflammation and neoplasia, independent of obesity. Mol Cancer Res 14:953–965. https://doi.org/10.1158/1541-7786.MCR-16-0153.

101. Carracedo A, Cantley LC, Pandolfi PP. 2013. Cancer metabolism: fatty acid oxidation in the limelight. Nat Rev Cancer 13:227–232. https://doi.org/10.1038/nrc3483.

102. Currie E, Schulze A, Zechner R, Walther TC, Farese RV. 2013. Cellular fatty acid metabolism and cancer. Cell Metab 18:153–161. https://doi.org/10.1016/j.cmet.2013.05.017.

103. Kanarek N, Petrova B, Sabatini DM. 2020. Dietary modifications for enhanced cancer therapy. Nature 579:507–517. https://doi.org/10.1038/s41586-020-2124-0.

104. Louis P, Hold GL, Flint HJ. 2014. The gut microbiota, bacterial metabolites and colorectal cancer. Nat Rev Microbiol 12:661–672. https://doi.org/10.1038/nrmicro3344.

105. Bastide NM, Pierre FHF, Corpet DE. 2011. Heme iron from meat and risk of colorectal cancer: a meta-analysis and a review of the mechanisms involved. Cancer Prev Res (Phila) 4:177–184. https://doi.org/10.1158/1940-6207.CAPR-10-0113.

106. Kruger C, Zhou Y. 2018. Red meat and colon cancer: a review of mechanistic evidence for heme in the context of risk assessment methodology. Food Chem Toxicol 118:131–153. https://doi.org/10.1016/j.fct.2018.04.048.

107. Hu L-Y, Ku F-C, Lu T, Shen C-C, Hu Y-W, Yeh C-M, Tzeng C-H, Chen T-J, Chen P-M, Liu C-J. 2015. Risk of cancer in patients with irritable bowel syndrome: a nationwide population-based study. Ann Epidemiol 25:924–928. https://doi.org/10.1016/j.annepidem.2015.07.006.

108. Jess T, Gamborg M, Matzen P, Munkholm P, Sørensen TIA. 2005. Increased risk of intestinal cancer in Crohn's disease: a meta-analysis of population-based cohort studies. Am J Gastroenterol 100:2724–2729. https://doi.org/10.1111/j.1572-0241.2005.00287.x.

109. Nørgaard M, Farkas DK, Pedersen L, Erichsen R, de la Cour ZD, Gregersen H, Sørensen HT. 2011. Irritable bowel syndrome and risk of colorectal cancer: a Danish nationwide cohort study. Br J Cancer 104:1202–1206. https://doi.org/10.1038/bjc.2011.65.

110. Austin GL, Dalton CB, Hu Y, Morris CB, Hankins J, Weinland SR, Westman EC, Yancy WS, Drossman DA. 2009. A very low-carbohydrate diet improves symptoms and quality of life in diarrhea-predominant irritable bowel syndrome. Clin Gastroenterol Hepatol 7:706–708.e1. https://doi.org/10.1016/j.cgh.2009.02.023.

111. Töth C, Dabóczi A, Howard M, J Miller N, Clemens Z. 2016. Crohn's disease successfully treated with the paleolithic ketogenic diet. Int J Case Rep Imag 7:570. https://doi.org/10.5348/ijcri-2016102-CR-10690.

112. Lowery RP, Wilson JM, Sharp MH, Wilson GJ, Wagner R. 2017. The effects of exogenous ketones on biomarkers of Crohn's disease: a case report. J Gastroenterol Dig Dis 2:8–11.

113. Poff AM, Ari C, Arnold P, Seyfried TN, D'Agostino DP. 2014. Ketone supplementation decreases tumor cell viability and prolongs survival of mice with metastatic cancer. Int J Cancer 135:1711–1720. https://doi.org/10.1002/ijc.28809.

114. Weber DD, Aminazdeh-Gohari S, Kofler B. 2018. Ketogenic diet in cancer therapy. Aging (Albany NY) 10:164–165. https://doi.org/10.18632/aging.101382.

115. Zhang N, Liu C, Jin L, Zhang R, Wang T, Wang Q, Chen J, Yang F, Siebert H-C, Zheng X. 2020. Ketogenic diet elicits antitumor properties through inducing oxidative stress, inhibiting MMP-9 expression, and rebalancing M1/M2 tumor-associated macrophage phenotype in a mouse model of colon cancer. J Agric Food Chem 68:11182–11196. https://doi.org/10.1021/acs.jafc.0c04041.

116. Khodabakhshi A, Akbari ME, Mirzaei HR, Seyfried TN, Kalamian M, Davoodi SH. 2020. Effects of ketogenic metabolic therapy on patients with breast cancer: a randomized controlled clinical trial. Clin Nutr 40:751–758. https://doi.org/10.1016/j.cnlu.2020.06.028.

117. Martin-McGill KJ, Marson AG, Tudur Smith C, Young B, Mills SJ, Cherry MG, Jenkinson MD. 2020. Ketogenic diets as an adjuvant therapy for glioblastoma (KEATING): a randomized, mixed methods, feasibility study. J Neurooncol 147:213–227. https://doi.org/10.1007/s11060-020-03417-8.

118. Branco AF, Ferreira A, Simões RF, Magalhães-Novais S, Zehowski C, Cope E, Silva AM, Pereira D, Sardão VA, Cunha-Oliveira T. 2016. Ketogenic
diets: from cancer to mitochondrial diseases and beyond. Eur J Clin Invest 46:285-298. https://doi.org/10.1111/eci.12591.

119. Weber DD, Aminzadeh-Gohari S, Tulipan J, Catalan L, Feichtinger RG, Kofler B. 2020. Ketogenic diet in the treatment of cancer—where do we stand? Mol Metab 33:102–121. https://doi.org/10.1016/j.molmet.2019.06.026.

120. Allen BG, Bhatia SK, Anderson CM, Eichenberger-Gilmore JM, Sibenaller ZA, Mapuskar KA, Schoenfeld JD, Buatti JM, Spitz DR, Fath MA. 2014. Ketogenic diets as an adjuvant cancer therapy: history and potential mechanism. Redox Biol 2:963-970. https://doi.org/10.1016/j.redox.2014.08.002.

121. Martuscello RT, Vedam-Mai V, McCarthy DJ, Schmoll ME, Jundi MA, Louviere CD, Griffith BG, Skinner CL, Suslov O, Deleyrolle LP, Reynolds BA. 2016. A supplemented high-fat low-carbohydrate diet for the treatment of glioblastoma. Clin Cancer Res 22:2482-2495. https://doi.org/10.1158/1078-0432.CCR-15-0916.

122. Minzer S. 2020. Effectiveness of ketogenic diets on the survival of adult oncological patients. Nutr Cancer 2020:1-11. https://doi.org/10.1080/01635581.2020.1836243.

123. Erickson N, Boscheri A, Linke B, Huebner J. 2017. Systematic review: isocaloric ketogenic dietary regimes for cancer patients. Med Oncol 34:72. https://doi.org/10.1007/s12032-017-0930-5.

124. Schatzkin A, Lanza E, Corle D, Lance P, Iber F, Caan B, Shike M, Weissfeld J, Burt R, Cooper MR, Kikendall JW, Cahill J, Freedman L, Marshall J, Schoen RE, Slattery M. 2000. Lack of effect of a low-fat, high-fiber diet on the recurrence of colorectal adenomas. N Engl J Med 342:1149-1155. https://doi.org/10.1056/NEJM200004203421601.

125. Fuchs CS, Giovannucci EL, Colditz GA, Hunter DJ, Stampfer MJ, Rosner B, Speizer FE, Willett WC. 1999. Dietary fiber and the risk of colorectal cancer and adenoma in women. N Engl J Med 340:169-176. https://doi.org/10.1056/NEJM199901213400301.

126. Lanza E, Yu B, Murphy G, Albert PS, Caan B, Marshall JR, Lance P, Paskett ED, Weissfeld J, Slattery M, Burt R, Iber F, Shike M, Kikendall JW, Brewer BK, Schatzkin A. 2007. The polyp prevention trial—continued follow-up study: no effect of a low-fat, high-fiber, high-fruit, and -vegetable diet on adenoma recurrence eight years after randomization. Cancer Epidemiol Biomarkers Prev 16:1745-1752. https://doi.org/10.1158/1055-9965.EPI-07-0127.

127. Beresford SAA, Johnson KC, Ritenbaugh C, Lasser NL, Snetselaar LG, Black HR, Anderson GL, Assaf AR, Bassford T, Bowen D, Brunner RL, Brzyski RG, Caan B, Chlebowski RT, Gabb M, Harrigan RC, Hays J, Heber D, Heiss G, Hendrix SL, Howard BV, Hsia J, Hubbell FA, Jackson RD, Kotchen JM, Kuller LH, LaCroix AZ, Lane DS, Langer RD, Lewis CE, Manson JE, Margolis KL, Mossavar-Rahmani Y, Ockene JK, Parker LM, Perri MG, Phillips L, Prentice RL, Robbins J, Rossouw JE, Sarto GE, Stefanick ML, Van Horn L, Vitolins MZ, Wactawski-Wende J, Wallace RB, Whitlock E. 2006. Low-fat dietary pattern and risk of colorectal cancer: the Women's Health Initiative Randomized Controlled Dietary Modification Trial. JAMA 295:643-654. https://doi.org/10.1001/jama.295.6.643.

128. Prentice RL, Thomson CA, Caan B, Hubbell FA, Anderson GL, Beresford SAA, Pettinger M, Lane DS, Lessin L, Yasmeen S, Singh B, Khandekar J, Shikany JM, Satterfield S, Chlebowski RT. 2007. Low-fat dietary pattern and cancer incidence in the Women's Health Initiative Dietary Modification Randomized Controlled Trial. J Natl Cancer Inst 99:1534-1543. https://doi.org/10.1093/jnci/djm159.

129. Prentice RL, Caan B, Chlebowski RT, Patterson R, Kuller LH, Ockene JK, Margolis KL, Limacher MC, Manson JE, Parker R, Paskett E, Phillips L, Robbins J, Rossouw JE, Sarto GE, Shikany JM, Stefanick ML, Thomson CA, Van Horn L, Vitolins MZ, Wactawski-Wende J, Wallace RB, Wassertheil-Smoller S, Whitlock E, Yano K, Adams-Campbell L, Anderson GL, Assaf AR, Beresford SAA, Black HR, Brunner RL, Brzyski RG, Ford L, Gass M, Hays J, Heber D, Heiss G, Hendrix SL, Hsia J, Hubbell FA, Jackson RD, Johnson KC, Kotchen JM, LaCroix AZ, Lane DS, Langer RD, Lasser NL, Henderson MM. 2006. Low-fat dietary pattern and risk of invasive breast cancer: the Women's Health Initiative Randomized Controlled Dietary Modification Trial. JAMA 295:629-642. https://doi.org/10.1001/jama.295.6.629.

130. Parnaud G, Peiffer G, Taché S, Corpet DE. 1998. Effect of meat (beef, chicken, and bacon) on rat colon carcinogenesis. Nutr Cancer 32:165-173. https://doi.org/10.1080/016355890809514736.

131. Sakaguchi M, Hiramatsu Y, Takada H, Yamamura M, Hioki K, Saito K, Yamamoto M. 1984. Effect of dietary unsaturated and saturated fats on azoxymethane-induced colon carcinogenesis in rats. Cancer Res 44:1472-1477.

132. Johnston BC, Zeraatkar D, Han MA, Vernooij RWM, Valli C, El Dib R, Marshall C, Stover PJ, Fairweather-Taitt S, Wójcik G, Bhatia F, de Souza R, Brotons C, Meerpohl JJ, Patel CJ, Djulbegovic B, Alonso-Coello P, Bala MM, Guyatt GH. 2019. Unprocessed red meat and processed meat consumption: dietary guideline recommendations from the Nutritional Recommendations (NutriRECS) Consortium. Ann Intern Med 171:756-764. https://doi.org/10.7326/M19-1621.

133. Alexander DD, Cushing CA, Lowe KA, Sceurman B, Roberts MA. 2009. Meta-analysis of animal fat or animal protein intake and colorectal cancer. Am J Clin Nutr 89:1402-1409. https://doi.org/10.3945/ajcn.2008.26838.

134. Mejborn H, Møller SP, Thygesen LC, Biltoft-Jensen A. 2020. Dietary intake of red meat, processed meat, and poultry and risk of colorectal cancer and all-cause mortality in the context of dietary guideline compliance. Nutrients 13:32. https://doi.org/10.3390/nu13010032.

135. Turner ND, Lloyd SK. 2017. Association between red meat consumption and colon cancer: a systematic review of experimental results. Exp Biol Med (Maywood) 242:813-839. https://doi.org/10.1177/1535370217693117.

136. Han MA, Zeraatkar D, Guyatt GH, Vernooij RWM, El Dib R, Zhang Y, Algarni A, Leung G, Storman D, Valli C, Rabassa M, Rehman N, Parvization MK, Zworth M, Bartoszko JJ, Lopes LC, Sit D, Bala MM, Alonso-Coello P, Johnston BC. 2019. Reduction of red and processed meat intake and cancer mortality and incidence: a systematic review and meta-analysis of cohort studies. Ann Intern Med 171:711-720. https://doi.org/10.7326/M19-0699.

137. Astrup A, Magkos F, Bier DM, Brenna JT, de Oliveira Otto MC, Hill JO, King JC, Mente A, Ordovas JM, Volek JS, Yusuf S, Krauss RM. 2020. Saturated fats and health: a reassessment and proposal for food-based recommendations. J Am Coll Cardiol 76:844-857. https://doi.org/10.1016/j.jacc.2020.05.077.

138. Dehghan M, Mente A, Zhang X, Swaminathan S, Li W, Mohan V, Iqbal R, Kumar R, Wentzel-Viljoen E, Rosengren A, Amma LI, Avezum A, Chifamba J, Diaz R, Khatib R, Lear S, Lopez-Jaramillo P, Liu X, Gupta R, Mohammadifar N, Gao N, Oguz A, Ramli AS, Seron P, Sun Y, Szuba A, Tsolekile L, Wielgosz A, Yusuf R, Hussein Yusufali A, Teo KK, Rangarajan S, Dagenais G, Bangdiwala SI, Islam S, Anand SS, Yusuf S, Diaz R, Thorlandini A, Linetsky B, Toscanelli S, Casaccia G, Cuneo JM, Rahman O, Yusuf R, Azad A, Rabbani K, Cherry H, Mannan A, Hassan I, et al. 2017. Associations of fats and carbohydrate intake with cardiovascular disease and mortality in 18 countries from five continents (PURE): a prospective cohort study. Lancet 390:2050-2062. https://doi.org/10.1016/S0140-6736(17)32252-3.

139. Lee JE, McLerran DF, Rolland B, Chen Y, Grant EJ, Vedanthan R, Inoue M, Tsugane S, Gao Y-T, Tsuji I, Kakizaki M, Ahsan H, Ahn Y-O, Pan W-H, Ozasa K, Yoo K-Y, Sasazuki S, Yang G, Watanabe T, Sugawara Y, Parvez F, Kim D-H, Chuang S-Y, Ohishi W, Park SK, Feng Z, Thorqurist M, Boffetta P, Zheng W, Kang D, Potter J, Sinha R. 2013. Meat intake and cause-specific mortality: a pooled analysis of Asian prospective cohort studies. Am J Clin Nutr 98:1032-1041. https://doi.org/10.3945/ajcn.113.062638.

140. Key TJ, Appleby PN, Spencer EA, Travis RC, Roddam AW, Allen NE. 2009. Cancer incidence in vegetarians: results from the European Prospective Investigation into Cancer and Nutrition (EPIC-Oxford). Am J Clin Nutr 89:1620S-1626S. https://doi.org/10.3945/ajcn.2009.26736M.

141. Singh PN, Fraser GE. 1998. Dietary risk factors for colon cancer in a low-risk population. Am J Epidemiol 148:761-774. https://doi.org/10.1093/oxfordjournals.aje.a00967.

142. Qian F, Riddle MC, Wylie-Rosett J, Hu FB. 2020. Red and processed meats and health risks: how strong is the evidence? Diabetes Care 43:265-271. https://doi.org/10.2337/dci19-0063.

143. West-Denning J, Prochazka AV. 2020. NutriRECS Consortium provides weak recommendations for continuing current red meat and processed meat consumption. Ann Intern Med 172:JC15. https://doi.org/10.7326/ACPJ202002180-015.

144. Ferraro JV, Plummer TW, Pobiner BL, Oliver JS, Bishop LC, Braun DR, Ditchfield PW, Seaman JW, Binetti KM, Seaman JW, Hertel F, Potts R. 2013. Earliest archaeological evidence of persistent hominin carnivory. PLoS One 8:e62174. https://doi.org/10.1371/journal.pone.0062174.

145. Cordain L, Eaton S, Miller JB, Mann N, Hill K. 2002. The paradoxical nature of hunter-gatherer diets: meat-based, yet non-atherogenic. Eur J Clin Nutr 56:542-S52. https://doi.org/10.1038/sj.ejcn.1601353.

146. Mann N. 2007. Meat in the human diet: an anthropological perspective. Nutr Diet 64:S102-S107. https://doi.org/10.1111/j.1747-0080.2007.00194.x.

147. Milton K. 2003. The critical role played by animal source foods in human (Homo) evolution. J Nutr 133:3886S-3892S. https://doi.org/10.1093/jn/133.11.3886S.
148. Creely SJ, McTernan PG, Kusminski CM, Fisher Ff M, Da Silva NF, Khanolkar M, Evans M, Harte AL, Kumar S. 2007. Lipopolysaccharide activates an innate immune system response in human adipose tissue in obesity and type 2 diabetes. Am J Physiol-Endocrinol Metab 292:E740-E747. https://doi.org/10.1152/ajpendo.00302.2006.

149. Vatanen T, Kostic AD, d'Hennezel E, Siljander H, Franzosa EA, Yassour M, Kolde R, Vlamakis H, Arthur TD, Hämäläinen A-M, Peet A, Tillmann V, Uibo R, Mokurov S, Dorshakova N, Ilonen J, Virtanen SM, Szabo SJ, Porter JA, Lähdesmäki H, Huttenhower C, Gevers D, Cullen TW, Knip M, Xavier RJ, DIA-BIMMUNE Study Group. 2016. Variation in microbiome LPS immunogenicity contributes to autoimmunity in humans. Cell 165:842-853. https://doi.org/10.1016/j.cell.2016.04.007.

150. Ghoshal S, Witta J, Zhong J, de Villiers W, Eckhardt E. 2009. Chylomicrons promote intestinal absorption of lipopolysaccharides. J Lipid Res 50:90-97. https://doi.org/10.1194/jlr.M800156-JLR200.

151. Erridge C, Attina T, Spickett CM, Webb DJ. 2007. A high-fat meal induces low-grade endotoxemia: evidence of a novel mechanism of postprandial inflammation. Am J Clin Nutr 86:1286-1292. https://doi.org/10.1093/ajcn/86.5.1286.

152. Laugerette F, Vors C, Géloën A, Chauvin M-A, Soulage C, Lambert-Porcheron S, Peretti N, Alligier M, Burcelin R, Laville M, Vidal H, Michalski M-C. 2011. Emulsified lipids increase endotoxemia: possible role in early postprandial low-grade inflammation. J Nutr Biochem 22:53-59. https://doi.org/10.1016/j.jnutbio.2009.11.011.

153. Harris HW, Grunfeld C, Feingold KR, Read TE, Kane JP, Jones AL, Eichbaum EB, Bland GF, Rapp JH. 1993. Chylomicrons alter the fate of endotoxin, decreasing tumor necrosis factor release and preventing death. J Clin Invest 91:1028-1034. https://doi.org/10.1172/JCI116259.

154. Manco M, Putignani L, Bottazzo GF. 2010. Gut microbiota, lipopolysaccharides, and innate immunity in the pathogenesis of obesity and cardiovascular risk. Endocr Rev 31:817-844. https://doi.org/10.1210/er.2009-0030.

155. Vreugdenhil ACE, Rousseau CH, Hartung T, Greve JWM, van 't Veer C, Buurman WA. 2003. Lipopolysaccharide (LPS)-binding protein mediates LPS detoxification by chylomicrons. J Immunol 170:1399-1405. https://doi.org/10.4049/jimmunol.170.3.1399.

156. Parlesak A, Schaeckeler S, Moser L, Bode C. 2007. Conjugated primary bile salts reduce permeability of endotoxin through intestinal epithelial cells and synergize with phosphatidylcholine in suppression of inflammatory cytokine production. Crit Care Med 35:2367-2374. https://doi.org/10.1097/01.ccm.0000284586.84952.fb.

157. Lim CL, Pyne D, Horn P, Kalz A, Saunders P, Peake J, Suzuki K, Wilson G, Mackinnon LT. 2009. The effects of increased endurance training load on biomarkers of heat intolerance during intense exercise in the heat. Appl Physiol Nutr Metab 34:616-624. https://doi.org/10.1139/H09-021.

158. Cani PD, Bibiloni R, Knauf C, Waget A, Neyrinck AM, Delzenne NM, Burcelin R. 2008. Changes in gut microbiota control metabolic endotoxemia-induced inflammation in high-fat diet-induced obesity and diabetes in mice. Diabetes 57:1470-1481. https://doi.org/10.2337/db07-1403.

159. Yue C, Ma B, Zhao Y, Li Q, Li J. 2012. Lipopolysaccharide-induced bacterial translocation is intestine site-specific and associates with intestinal mucosal inflammation. Inflammation 35:1880-1888. https://doi.org/10.1007/s10753-012-9510-1.

160. Thaiss CA, Levy M, Grosheva I, Zheng D, Soffer E, Blacher E, Braverman S, Tengeler AC, Barak O, Elazar M, Ben-Zeev R, Lehavi-Regev D, Katz MN, Pevsner-Fischer M, Gertler A, Halpern D, Harmelin A, Aamar S, Serradas P, Grosfeld A, Shapiro H, Geiger B, Elinav E. 2018. Hyperglycemia drives intestinal barrier dysfunction and risk for enteric infection. Science 359:1376-1383. https://doi.org/10.1126/science.aar3318.

161. d'Hennezel E, Abubucker S, Murphy LO, Cullen TW. 2017. Total lipopolysaccharide from the human gut microbiome silences Toll-like receptor signaling. mSystems 2:e00046-17. https://doi.org/10.1128/mSystems.00046-17.

162. Pinto A, Bonucci A, Maggi E, Corsi M, Businaro R. 2018. Anti-oxidant and anti-inflammatory activity of ketogenic diet: new perspectives for neuroprotection in Alzheimer's disease. Antioxidants (Basel) 7:63. https://doi.org/10.3390/antiox7050063.

163. Youm Y-H, Nguyen KY, Grant RW, Goldberg EL, Bodogai M, Kim D, D'Agostino D, Planavsky N, Lupfer C, Kanneganti TD, Kang S, Horvath TL, Fahmy TM, Crawford PA, Biragyn A, Alnemri E, Dixit VD. 2015. The ke-tone metabolite β-hydroxybutyrate blocks NLRP3 inflammasome-mediated inflammatory disease. Nat Med 21:263-269. https://doi.org/10.1038/nm.3804.

164. Forsythe CE, Phinney SD, Fernandez ML, Quann EE, Wood RJ, Bibus DM, Kraemer WJ, Feinman RD, Volek JS. 2008. Comparison of low fat and low carbohydrate diets on circulating fatty acid composition and markers of inflammation. Lipids 43:65-77. https://doi.org/10.1007/s11745-007-3132-7.

165. Shen Y, Kapfhamer D, Minnella AM, Kim J-E, Won SJ, Chen Y, Huang Y, Low LH, Massa SM, Swanson RA. 2017. Bioenergetic state regulates innate inflammatory responses through the transcriptional co-repressor CtBP. Nat Commun 8:624. https://doi.org/10.1038/s41467-017-00707-0.

166. Qi J, You T, Li J, Pan T, Xiang L, Han Y, Zhu L. 2018. Circulating trimethylamine N-oxide and the risk of cardiovascular diseases: a systematic review and meta-analysis of 11 prospective cohort studies. J Cell Mol Med 22:185-194. https://doi.org/10.1111/jcmm.13307.

167. Romano KA, Martinez-del Campo A, Kasahara K, Chittim CL, Vivas El, Amador-Noguez D, Balskus EP, Rey FE. 2017. Metabolic, epigenetic, and transgenerational effects of gut bacterial choline consumption. Cell Host Microbe 22:279-290.e7. https://doi.org/10.1016/j.chom.2017.07.021.

168. Kivenson V, Giovannoni SJ. 2020. An expanded genetic code enables trimethylamine metabolism in human gut bacteria. mSystems 5:e00413-20. https://doi.org/10.1128/mSystems.00413-20.

169. Jia J, Dou P, Gao M, Kong X, Li C, Liu Z, Huang T. 2019. Assessment of causal direction between gut microbiota-dependent metabolites and cardiometabolic health: a bidirectional Mendelian randomization analysis. Diabetes 68:1747-1755. https://doi.org/10.2337/db19-0153.

170. Wan Y, Yuan J, Li J, Li H, Zhang J, Tang J, Ni Y, Huang T, Wang F, Zhao F, Li D. 2020. Unconjugated and secondary bile acid profiles in response to higher-fat, lower-carbohydrate diet and associated with related gut microbiota: a 6-month randomized controlled-feeding trial. Clin Nutr 39:395-404. https://doi.org/10.1016/j.clnu.2019.02.037.

171. Raimondi F, Santoro P, Barone MV, Pappacoda S, Barretta ML, Nanayakkara M, Apicella C, Capasso L, Paludetto R. 2008. Bile acids modulate tight junction structure and barrier function of Caco-2 monolayers via EGFR activation. Am J Physiol Gastrointest Liver Physiol 294:G906-G913. https://doi.org/10.1152/ajpgi.00043.2007.

172. Santoro P, Raimondi F, Annunziata S, Paludetto R, Annella T, Ciccimarra F. 2002. Unconjugated bile acids modulate adult and neonatal neutrophil chemotaxis induced in vitro by N-formyl-Met-Leu-Phe-peptide. Pediatr Res 51:392-396. https://doi.org/10.1203/00006450-200203000-00020.

173. Keating N, Keely SJ. 2009. Bile acids in regulation of intestinal physiology. Curr Gastroenterol Rep 11:375-382. https://doi.org/10.1007/s11894-009-0057-8.

174. D'Aldebert E, Biyeyeme Bi Mve M-J, Mergey M, Wendum D, Firrincieli D, Coilly A, Fouassier L, Corpehot C, Poupon R, Housset C, Chignard N. 2009. Bile salts control the antimicrobial peptide cathelicidin through nuclear receptors in the human biliary epithelium. Gastroenterology 136:1435-1443. https://doi.org/10.1053/j.gastro.2008.12.040.

175. Lorenzo-Zúñiga V. 2003. Oral bile acids reduce bacterial overgrowth, bacterial translocation, and endotoxemia in cirrhotic rats. Hepatology 37:551-557. https://doi.org/10.1053/jhep.2003.50116.

176. Kidd M, Modlin IM, Gustafsson BI, Drozdov I, Hauso O, Pfragner R. 2008. Luminal regulation of normal and neoplastic human EC cell serotonin release is mediated by bile salts, amines, tastants, and olfactants. Am J Physiol Gastrointest Liver Physiol 295:G260-272. https://doi.org/10.1152/ajpgi.00056.2008.

177. Liu T, Song X, Khan S, Li Y, Guo Z, Li C, Wang S, Dong W, Liu W, Wang B, Cao H. 2020. The gut microbiota at the intersection of bile acids and intestinal carcinogenesis: an old story, yet mesmerizing. Int J Cancer 146:1780-1790. https://doi.org/10.1002/ijc.32563.

178. Blachier F, Beaumont M, Kim E. 2019. Cysteine-derived hydrogen sulfide and gut health: a matter of endogenous or bacterial origin. Curr Opin Clin Nutr Metab Care 22:68-75. https://doi.org/10.1097/MCO.0000000000000526.

179. Singh S, Lin H. 2015. Hydrogen sulfide in physiology and diseases of the digestive tract. Microorganisms 3:866-889. https://doi.org/10.3390/microorganisms3040866.

180. Devkota S, Wang Y, Musch MW, Leone V, Fehlner-Peach H, Nadimpalli A, Antonopoulos DA, Jabri B, Chang EB. 2012. Dietary-fat-induced tauro-cholic acid promotes pathobiont expansion and colitis in Il10⁻/⁻ mice. Nature 487:104-108. https://doi.org/10.1038/nature11225.

181. Magee EA, Richardson CJ, Hughes R, Cummings JH. 2000. Contribution of dietary protein to sulfide production in the large intestine: an in vitro and a controlled feeding study in humans. Am J Clin Nutr 72:1488-1494. https://doi.org/10.1093/ajcn/72.6.1488.

182. Kellingray L, Tapp HS, Saha S, Doleman JF, Narbad A, Mithen RF. 2017. Consumption of a diet rich in Brassica vegetables is associated with a
reduced abundance of sulphate-reducing bacteria: a randomised cross-
over study. Mol Nutr Food Res 61:1600992. https://doi.org/10.1002/mnfr
.201600992.

183. Costantini L, Molinari R, Farinon B, Merendino N. 2017. Impact of omega-3 fatty acids on the gut microbiota. Int J Mol Sci 18:2645. https://doi.org/10.3390/ijms18122645.

184. Mokkala K, Houttu N, Cansev T, Laitinen K. 2020. Interactions of dietary fat with the gut microbiota: evaluation of mechanisms and metabolic consequences. Clin Nutr 39:994–1018. https://doi.org/10.1016/j.clnu.2019.05.003.

185. Lichtman JS, Alsentzer E, Jaffe M, Sprockett D, Masutani E, Ikwa E, Fragiadakis GK, Clifford D, Huang BE, Sonnenburg JL, Huang KC, Elias JE. 2016. The effect of microbial colonization on the host proteome varies by gastrointestinal location. ISME J 10:1170–1181. https://doi.org/10.1038/ ismej.2015.187.

186. Ludwig DS, Kushi LH, Heymsfield SB. 2018. Conflicts of interest in nutrition research. JAMA 320:93. https://doi.org/10.1001/jama.2018.5658.

187. Klurfeld DM. 2018. What is the role of meat in a healthy diet? Anim Front 8:5–10. https://doi.org/10.1093/af/vfy009.