Abstract
The operational harmony between living beings and their circumstances, their ever-changing environment, is a constitutive condition of their existence. Nutrition and symbiosis are two essential aspects of this harmony. Disruption of the symbiosis between host and gut microbiota, the so-called dysbiosis, as well as the inadequate diet from which it results, contribute to the etiology of immunometabolic disorders. Research into the development of these diseases is highly influenced by our understanding of the evolutionary roots of metabolic functioning, thereby considering that chronic non-communicable diseases arise from an evolutionary mismatch. However, the lens has been mostly directed toward energy availability and metabolism, but away from our closest environmental factor, the gut microbiota. Thus, this paper proposes a narrative thread that places symbiosis in an evolutionary perspective, expanding the traditional framework of humans’ adaptation to their food environment.
Introductory Paragraph
Starting from the premise that metabolic disorders are the result of an evolutionary mismatch, the present essay is an attempt to follow an argumentative line that underscores symbiosis position throughout human evolutionary trajectory. The argumentative line is as follows:
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In the first part, a definition of evolutionary mismatch is given and the historical use of the evolutionary angle to apprehend metabolic diseases is summarised.
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The second part emphasizes the crucial need for symbiosis, its durability in evolution and raises the question of its role in natural selection.
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The third part outlines how an inadequate diet theoretically leads to dysbiosis and immunometabolic abnormalities.
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In the fourth part, the main prehistoric shifts in the human dietary niche are described.
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The fifth part is an attempt to include symbiosis in the complex web of trade-offs between traits.
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Using the life history framework, the sixth part highlights the uniqueness of Homo sapiens, which may explain its vulnerability to dysbiosis and associated immunometabolic abnormalities.
Metabolic Syndrome, an Evolutionary Mismatch?
The metabolic syndrome (MetS) is a multifactorial condition clustering several interrelated immunometabolic abnormalities increasing the risk of developing chronic non-communicable diseases (CNCDs) (Alberti et al., 2009). The growing prevalence of MetS is often viewed from an evolutionary perspective, which provides a unifying explanation. Nutritional ecology, a field of evolutionary medicine (Raubenheimer et al., 2009), observes MetS through the prism of evolutionary mismatch, which has been defined as follows: mismatch occurs when the time scale and/or magnitude of environmental change exceeds the combined capacity of adaptation owing to homeostatic mechanisms, phenotypic plasticity and transgenerational adaptation (Raubenheimer et al., 2012). Adaptation is defined here in terms of whether a diet maximises fitness.
The thrifty gene hypothesis constituted a theoretical foundation for the explanation of the escalating levels of metabolic disorders and obesity (Neel, 1962). A subsequent thrifty phenotype hypothesis explains the increased incidence of type 2 diabetes by a developmental origin, underpinned by epigenetically mediated parental effects (Hales & Barker, 1992; Costa-Júnior et al., 2021; Christopher W. Kuzawa & Kim, 2022). Indeed, ecological conditions, including the food environment, can change on multiple time scales, implying a continuum of levels of biological organisation on which living beings can adapt their functioning to match an evolving environment (C. W. Kuzawa & Thayer, 2011). There are thus as many time scales of mismatch as there are levels of biological organisation involved in phenotype-environment congruence, but in the present essay the focus will mostly be on the simple evolutionary mismatch that falls under the time scale of transgenerational genomic adaptation by natural selection.
Since humans and chimpanzees split from a common ancestor 5–8 million years ago, the human metabolism has changed dramatically, adapting primarily to occasional food insecurity, maintenance of an energetically expensive brain, as well as to a macronutrient-dense diet (Besenbacher et al., 2019; Langergraber et al., 2012; Pontzer et al., 2016). Selective forces of a different nature would then have led to changes in the frequency of alleles predisposing the human metabolism to store energy during periods of food abundance, in order to compensate for periods of food shortage. Thus, the thrifty gene hypothesis, as well as all the refined assumptions and hypotheses arisen from it, have focused their explanations on gene-based metabolic adaptations to food scarcity (Hales & Barker, 2001; Stöger, 2008). Indeed, many studies have highlighted the genetic adaptations of Homo sapiens to its evolutionary food environment (Brown, 2012; Hancock et al., 2010), but the focal point has always been on the nutrient composition of diet and on metabolism.
Thus, whether it is a matter of genetics, epigenetics or any other level of biological organisation, the food environment to which Homo sapiens has adapted and which has shaped its evolution has been understood mainly from this binary angle of energy availability. It is proposed here to broaden this framework to also include adaptation to a changing gut microbiota, and hence to emphasize the importance of symbiosis breakdown in the MetS evolutionary mismatch.
The Primate-Gut Microbiota Symbiosis and its Nutritional Environment
All pluricellular species form transient or long-lasting associations with microbial species to carry out biological processes (Rosenberg & Zilber-Rosenberg, 2016). Living at the interface between the environment and the host, the microbiota reflects changes generated by both on host functioning, which suggests that, on an evolutionary scale, it exerts selection pressures on host species (Bang et al., 2018; Shapira, 2016).
Studies investigating the cophylogenetic patterns between animals and their microbiota demonstrated congruent phylogenies for many species, suggesting that these animals and their microbiota had parallel evolutionary histories (Brooks et al., 2016; Easson & Thacker, 2014; Groussin et al., 2017; Kohl et al., 2018; Phillips et al., 2012). More specifically, co-diversification between the Hominidae and their microbiota indicates the existence of symbiosis in a common ancestor to all hominids. Thus, this symbiosis has persisted over time, with the microbial composition of hominids being phylogenetically conserved, and the divergence times of microbiota co-speciation being congruent with those of hominids (Moeller et al., 2016; Ochman et al., 2010). Interestingly, the human microbiota has undergone substantial change since the human–chimpanzee split, diverging from the ancestral state at an accelerated rate, having its diversity drastically reduced (Moeller et al., 2014). This depletion of the human microbiota and its accelerated divergence compared to that of great apes raises questions about the causes of this phenomenon, and therefore about the magnitude of the reciprocal influences that the human host, its microbiota and their nutritional environment exert on one another.
Throughout evolution, the longest conserved nutritional environment of primates was mainly composed of plants, and thus may have preferentially selected certain species and metabolic functions within gut bacterial ecosystems, as well as individuals able to benefit from their presence and functions (Eaton et al., 1997; Walter & Ley, 2011; Milton, 1993; E. D. Sonnenburg & Sonnenburg, 2019). Hence, the evolution of the primates-microbiota symbiosis may have shaped the genetic architecture of the host immune system and the digestive tract to allow a tolerogenic response towards microbial ecosystems suited for ecological niches generated by a large proportion of plant consumption, and to respond properly to stimuli generated from those, in order to ensure their containment inside the gut (Duerkop et al., 2009; Johansson et al., 2011; Mowat, 2018; Sansonetti, 2011).
Thus, it can be assumed that a nutritional environment composed predominantly of ripe and unripe fruits, young leaves, flowers, seeds and, occasionally, roots and tubers, would have selected the most suitable individuals to tolerate microbial species capable of forming ecosystems equipped with enzymatic repertoires adapted to the degradation of most of the non-digestible components of this diet. Indeed, a significant proportion of the health benefits of plant consumption is attributed to the modulation of the gut microbiota (J. L. Sonnenburg & Backhed, 2016; Van Hul & Cani, 2019). Short-chain fatty acids produced by gut microbes through the fermentation of non-digestible carbohydrates are essential to the preservation of the gut barrier function, thus preventing uncontrolled permeability and bacterial translocation (Chambers et al., 2018; Doré & Blottière, 2015; Johansson et al., 2011). In addition, strong epidemiological studies have shown an inverse association between CNCDs and the consumption of phytochemicals (Arts & Hollman, 2005), whose biotransformation into low molecular weight metabolites by gut microbes results in an increased bioavailability (Cardona et al., 2013; Dixit et al., 2021). Moreover, diets low in non-digestible components promote the depletion of microbial diversity (E. D. Sonnenburg et al., 2016), thus illustrating the mutual benefits offered to the microbiota and the host when a congruent nutritional environment sustains the symbiotic link.
While hosts may impose selective pressures on their microbiota on short time scales (Zhao et al., 2019); over a longer time scale, has a changing microbiota reshaped host functioning, thereby selecting differently adapted hosts? This could be suggested by their “cophylogenetic” patterns, which illustrate the cohesiveness of their symbiotic link over evolutionary time scales: thus, did co-evolution drive the continuation of symbiosis (Groussin et al., 2020)? Theoretically, co-evolution implies a reciprocal application of selection pressures of both parties, favouring a continuous adaptation to their symbiotic relationship and, consequently, the persistence of a mutual benefit (Janzen, 1980). Interestingly, experts in host-microbiota interactions research consider this explanation implausible and even propose that, regarding mammals, host-microbiota co-speciation resulted from allopatric speciation of hosts, and that the dispersal of their microbes generated cophylogenetic patterns (Groussin et al., 2020). However, the evidence presented in the next section highlights the role of the microbiota in immunometabolic disorders. This would suggest that if there is a mismatch between the human genome and the selective forces arising from its current nutritional environment, a substantial proportion of these selective forces is attributable to the microbiota, making their action not negligible.
Dysbiotic Features and Immunometabolic Abnormalities
Dysbiosis can be defined as an altered state of host–microbe crosstalk with auto-aggravating signals from both sides that may induce circular causalities and thereby durably altered symbiosis (Malard et al., 2021). Current knowledge about mechanisms linking this symbiosis disruption to immunometabolic dysregulations (more specifically in primates) are summarized below.
Evidence in humans and nonhuman primates indicates that nutritional patterns collectively termed “Western diet” characterised by a high caloric intake, richness in animal proteins, fats and monosaccharides and low fibres intake promote the pathogenesis of immunometabolic abnormalities (Christ et al., 2019; Kavanagh et al., 2013). In addition, observational studies in humans have shown that obesity, MetS and CNCDs are associated with changes in microbial composition and significantly reduced diversity compared to healthy subjects (Aron-Wisnewsky et al., 2019; Fromentin et al., 2022; Le Chatelier et al., 2013).
Finally, the discovery of metabolic endotoxemia and its associated intestinal permeability through animal studies established a causal relationship between the Western diet, dysbiosis and immunometabolic disorders (Cani et al., 2007, 2008, 2009). This association was further confirmed in humans (Amar et al., 2008; Amar et al., 2011; Rainone et al., 2016; Rémy Burcelin et al., 2022; Lecerf & Cani, 2022; Määttä et al., 2021). Indeed, numerous animal studies, including rodent models of the human microbiota, have shown that switching from a diet rich in non-digestible carbohydrates to a "Western" diet elicits immunometabolic abnormalities along with dysbiosis (Arias-Jayo et al., 2018; Bortolin et al., 2018; Devkota et al., 2012; Qiao et al., 2013; Turnbaugh et al., 2009; Zeng et al., 2017).
Thus, based on the assumption that the primate host is designed to tolerate certain microbial ecosystems it can be assumed that the adoption of a Western diet, which should result in a shift towards microbial ecosystems for which the host immune system is not designed to provide a tolerogenic response, could trigger a local inflammatory response, which in turn would amplify dysbiosis (Claesson et al., 2012; Cotillard et al., 2013; Frankel et al., 2019). In addition, inappropriate stimuli provided by these novel microbial ecosystems would cause an impairment of the gut barrier function, resulting in an increased inflow of pathogen-associated molecular patterns and pathogens into the bloodstream, the so-called metabolic endotoxemia (Amar et al., 2008; Lyte et al., 2016; Régnier et al., 2021; Vemuri et al., 2022). Lastly, this may drive the onset of low-grade systemic inflammation, which can become chronic if gut homeostasis is not restored (van de Guchte et al., 2018; Malard et al., 2021). This causal chain of pathophysiology places the maladjustment of the primate host to Western-induced microbial ecosystems as a primary cause of immunometabolic dysregulation. Thus, exposure to a nutritional environment for which the primate-microbiota symbiosis is not adapted could cause the breakdown of this symbiosis, leading to this chronic low-grade systemic inflammation, which is known to be associated with the development of the MetS and CNCDs (Belizario et al., 2018; Christ et al., 2019; Gregor & Hotamisligil, 2011).
The exact factors driving the development of this inflammatory state have not been pinpointed yet, though, both inappropriate diet and dysbiosis, which are interrelated, are meant to be among the main determining factors. In practice, however, despite the absence of framework to precisely explain to what extent dysbiosis contributes to the development of MetS (Brussow, 2020), the existence of a relationship between gut microbiota and MetS has been clearly demonstrated (R. Burcelin, 2016; Régnier et al., 2021). Consequently, it is broadly accepted that an inadequate nutrition is implicated, through dysbiosis, in the increasing propensity for metabolic endotoxemia that ultimately leads to the development of insulin resistance and low-grade inflammation, laying the foundation for MetS and CNCDs (Hosseinkhani et al., 2021).
A mismatch between the primates’ genome and the selection pressures of this Western nutritional environment could explain much of the immunometabolic dysregulations that occur when primates are exposed to such a diet. Although non-human primates living in captivity can develop metabolic disorders and undergo microbiota changes similar to humans (Frankel et al., 2019; Kavanagh et al., 2013; Vemuri et al., 2022), epidemiology of MetS and CNCDs in humans tends to indicate a greater prominence of this adaptive mismatch in humans (Kones & Rumana, 2017; Saklayen, 2018). The question then arises as to human’s vulnerability and thus specificities compared with other primates.
Revolutions of the Human Dietary Niche
Humans come from a lineage of primates whose diet was mostly composed of plant foods (as described earlier), with perhaps some opportunistic intake of animal matter (Milton, 1993). Early hominins adaptations have been linked to the need for providing adequate energetic resources to their larger brains. This way, evolving larger brains happened along with a dietary shift towards more meat and cooked food (Ben-Dor et al., 2021). The use of fire became habitual and planned between 350,000 and 320,000 years ago (Shimelmitz et al., 2014). It may have, on the one hand, reduced the selective forces exerted onto microbial ecosystems relying on plant consumption, promoting therefore species suited for other ecological niches and, on the other hand, disrupted previous means of acquisition and transmission of microbes (Gillings et al., 2015).
This notwithstanding, subsistence data from hunter-gatherer societies outside of circumpolar regions, indicate a dietary ratio of 65–70% plant to 30–35% animal; it was thus assumed that fruits, roots, legumes, nuts and other non-cereals would have provided 65–70% of the subsistence base for Palaeolithic diets (Eaton & Konner, 1985; Eaton et al., 1997). Furthermore, it is likely that no hunter-gatherer society suffered from immunometabolic abnormalities. Thus, the near absence of MetS and CNCDs in present-day hunter-gatherers, coupled with marked gut metagenomic differences from Westernized populations, suggests that plant-based subsistence strategies prevent both dysbiosis and immunometabolic disorders (Pontzer et al., 2018; Rampelli et al., 2015).
The transition from a hunter-gatherer lifestyle to dependence on agricultural production, which happened in separate locations worldwide, starting around 12,000 years ago, is believed to have impacted several aspects of human disease and biology (Bocquet-Appel, 2008; Franck et al., 2022; Wells & Stock, 2020). Thus the modification of the human niche induced by the Neolithic transition markedly altered nutritional patterns. Indeed, agricultural societies obtained the major part of their daily energy from a single cooked cereal grain (Cordain, 1999). In this way, the selection pressures to which Homo sapiens was subjected, particularly those associated with the nutritional environment, including those induced by the microbiota, may have been radically reshaped. Metabolic genetic adaptations to this dietary shift induced by the Neolithic transition have been widely studied (Mathieson & Mathieson, 2018; Perry et al., 2007; Ségurel & Bon, 2017; Ségurel et al., 2013). However, aside from any genetic changes induced by altered macro- and micro-nutrient intakes and ratios, the transition to agriculture could also have altered the proportions of microbial species ingested by Homo sapiens, as well as the content of non-digestible components of its diet, thereby disrupting the ecological niches assigned to the microbiota. As an example of this ecological niches reshuffle, sequencing of calcified dental plaque from ancient teeth has shown that changes in carbohydrate intake appear to have altered the balance between ecological niches of the oral microbiota in favour of cariogenic bacteria (Adler et al., 2013). In addition, elevated infectious disease burden that came with the Neolithic transition including among others higher population concentration, sedentariness and contact with domesticated animals imposed novel selection pressures on the immune system (Bocquet-Appel, 2008; Stone, 2020), whose adaptation may have altered its responsiveness, in particular the tolerogenic response, to the microbiota, and thus the parameters for maintaining symbiosis.
Comparison of coexisting BaAka hunter-gatherers, Bantu agriculturalists and US Americans showed that BaAka’ and Bantu’ microbiotas were more similar to each other than to that of westerners (Gomez et al., 2016). However a convergence of features between the microbiota profiles of Bantu and Americans was observed, suggesting that agriculture has slowly triggered a loss of traditional microbes that has accelerated in industrial societies over the last few centuries, in parallel with this westernization of human’s nutritional environment.
Evolutionary Trade-Offs Across a Nutritional Geometric Space: The Scope of Symbiosis
Organisms are coordinated wholes of multiple traits facing conflicting selection pressures. Because some traits share a functional relationship or a genetic covariance and because resources are limited, these coexisting traits are subject to trade-offs, across time scales (from short-term homeostasis regulation to long-term evolutionary adaptation) (Roff & Fairbairn, 2007). Hence, trade-offs arise because certain limiting resources are allocated with a higher priority to one trait at the expense of others. However, organisms nutritional needs extend beyond energy requirements, many micronutrients, certain polyunsaturated fatty acids and amino acids, being precursors for different vital biomolecules. Thus, to meet the multidimensional nutritional demands of traits that have differing nutritional optima, organisms are oriented by nutrient-specific appetites.
The geometric framework for nutrition, a method developed in nutritional ecology (Simpson & Raubenheimer, 1995), has been used to demonstrate how organisms, driven by nutrient-specific appetites, select foods, control food intake and utilize ingested nutrients to attain their needs (Simpson et al., 2017). This geometric analysis situates traits in nutrient space, thus allowing to identify trade-offs and to apprehend how the environment exerts selection pressures on nutrient appetites to optimally balance these traits. In insects and mice, geometric framework for nutrition experiments demonstrated that the protein to carbohydrate ratio affects consumption and allocation to traits associated with longevity and fertility, thus mediating a trade-off between these life history programs (Hosking et al., 2019). Similarly, in humans, intake of proteins seems to be prioritised over that of other macronutrients, which is consistent with the existence of a protein-specific appetite (Simpson & Raubenheimer, 2005). Many micronutrients that do not seem to be specifically regulated are however, coupled in foods with other regulated nutrients, thus ensuring adequate intakes.
Likewise, non-digestible components do not elicit appetitive responses. As explained previously, they constitute the cornerstone of symbiosis maintenance. This notwithstanding, they are by definition not nutrients and some phytochemical compounds are even classified as “toxins” (e.g., alkaloids, polyphenolics, terpenoids) (Simpson & Raubenheimer, 2012). When selecting foods, nonhuman primates even appear to prioritise energy and protein maximization while limitating non-digestible components (Felton et al., 2009). Accordingly, non-digestible components seem unlikely to be a limiting resource for any trait, except the maintenance of symbiosis, and thus to mediate any trade-off. Living at the interface between the environment and the host, the gut microbiota does not really belong to one or the other. So, it is not entirely clear whether the maintenance of symbiosis should be apprehended as a trait, which could therefore be subject to trade-offs. Nonetheless, symbiosis being a core feature of the maintenance of immunometabolic homeostasis, it necessarily does affect life history traits. Moreover, as a result of non-digestible carbohydrates fermentation and phytochemicals biotransformation, non-digestible components could perhaps, through percolation mediated by the microbiota, operate in the web of trade-offs that exists among nutrients. Therefore, in a westernized nutritional environment with a trend towards reduced non-digestible components, Homo sapiens evolved food appetites may be inadequate for the preservation of symbiosis. Besides, due to the ubiquity of non-digestible components in Homo sapiens dietary niche throughout evolution, it seems reasonable to infer that natural selection against the “underconsumption” of non-digestible components was virtually non-existent.
Evolution of Sapiens Life History Strategy and Symbiosis
The evolutionary trajectory of the Homo genus and especially Homo sapiens, is distinguishable by some trade‐offs that are relevant to consider when attempting to understand the evolutionary dynamics of the host-microbiota symbiosis. Trade-offs are fundamental to life history theory, a central framework of evolutionary ecology (Flatt & Heyland, 2011; Snell-Rood et al., 2015; Wells & Stock, 2020). The life history strategy of an organism determines its fitness by affecting its main biological programs that are growth, survival, and reproduction; it can be seen as a sequence of energy allocation decisions towards traits that underpin these programs.
The “cognitive buffer hypothesis” highlights the advantages of behavioural responses adaptability in the face of the vagaries of the environment to explain why some animals, such as primates and especially Homo sapiens, have evolved larger brains despite substantial energetic and developmental costs (Allman, 1999). Indeed, evolving greatly expanded and highly complex brains has been constrained by trade‐offs, pushing to consider the brain as a life history trait (Snell-Rood et al., 2015). Thus, based on the observation that the human digestive tract is proportionally smaller than that of other primates, a trade-off between brain size and gut size has been hypothesized. Specifically, the human colon is 77% smaller, and the small intestine is 64% longer than in chimpanzees (Aiello & Wheeler, 1995). The small intestine being the site of absorption of lipids, proteins and carbohydrates, whose proportion progressively increased with Homo genus high-quality diet. Accordingly, compared with chimpanzees and other apes, humans have a higher metabolism (Gibbons, 2016); and primates extract much of their energy from short-chain fatty acids derived from colonic fermentation of non-digestible carbohydrates, the proportion of metabolisable energy from it being estimated for instance around 57% in gorilla (Popovich et al., 1997). Furthermore, pathogen-associated molecular patterns seem to be absorbed most frequently via small intestine, and often along with chylomicrons, diets rich in fats promoting therefore metabolic endotoxemia (Erridge, 2011; Ghoshal et al., 2009; Laugerette et al., 2011). One may then suppose that these human anatomic specificities with regard to digestive tract, along with a higher energy intake, notably coming from fats, make human more vulnerable than other primates to metabolic endotoxemia and the immunometabolic dysregulation resulting therefrom (Amar et al., 2008).
In a related manner, transition to agriculture involved profound transformations in human life history strategies: trade-offs could have occurred in response, on the one hand, to changes in nutrient intakes and ratios, as well as to increased risk of famine, and on the other hand, to the elevated infectious disease burden (Wells & Stock, 2020). It was proposed that these profound transformations of the human niche may have promoted life histories allocating more energy to immune function and reproduction, at the expense of growth and maintenance (Wells & Stock, 2020). With regard to the symbiosis perspective, what emerges from this is that, throughout its evolution, the energy allocation decisions adopted by Homo sapiens, as a species, to increase its fitness and prolificity, dramatically amplified, in return, its vulnerability to dysbiosis and immunometabolic dysregulations:
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First, by increasing its propensity to metabolic endotoxemia (owing to its digestive tract evolution).
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Second, by decreasing its tolerogenic response capability as a result of a higher immune reactivity, and by moving gradually away from the microbial ecosystems to which it was adapted due to its dietary modifications.
Overall, several parameters pertaining to symbiosis have been altered, thus narrowing the range of its maintenance. Trade-offs are processes of natural selection, so they do not occur if they are not operative, signifying that for Homo sapiens, as a species, the benefits of reorganising its life history strategy outweighed the costs. However, these costs have increased drastically owing to the westernization of the human nutritional environment, drawing up the outlines of this mismatch that underpins the epidemiology of MetS and CNDCs.
Perspectives and Concluding Remarks
On the whole, despite the cohesiveness of primates-microbiota symbiotic link throughout evolution, the human microbiota underwent an accelerated divergence and depletion. The shifts in human’s dietary niche throughout evolution have played a major role in this phenomenon. Finally, human’s singular evolutionary history tends to make him more vulnerable to symbiosis disruption, metabolic endotoxemia and the immunometabolic dysregulation resulting therefrom. Going back to the introductory mismatch perspective, one may consider the possibility of further including symbiosis and the conditions of its preservation in a nutritional ecology prism while looking at MetS and low-grade inflammation.
Clarifying the genetic basis of human adaptations to diverse microbial ecosystems, and thus symbiosis maintenance, could help to delineate more tangible evolutionary mismatches. However, establishing a clear picture of adaptation is challenging, as this involves delineating the conditions driving the selection, the phenotype on which selection acts and the genomic regions that are subject to selection. In addition, identifying causal links between specific selective forces, phenotypic adaptations, and thus specific genetic variants, will remain a controversial issue since adaptations may be constrained by trade‐offs.
References
Adler, C. J., Dobney, K., Weyrich, L. S., Kaidonis, J., Walker, A. W., Haak, W., et al. (2013). Sequencing ancient calcified dental plaque shows changes in oral microbiota with dietary shifts of the Neolithic and Industrial revolutions. Nature Genetics, 45(4), 450–455. https://doi.org/10.1038/ng.2536
Aiello, L. C., & Wheeler, P. (1995). The expensive-tissue hypothesis: The brain and the digestive system in human and primate evolution. Current Anthropology, 36(2), 199–221. https://doi.org/10.1086/204350
Alberti, K. G., Eckel, R. H., Grundy, S. M., Zimmet, P. Z., Cleeman, J. I., Donato, K. A., et al. (2009). Harmonizing the metabolic syndrome: A joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation, 120(16), 1640–1645. https://doi.org/10.1161/CIRCULATIONAHA.109.192644
Allman, J. M. (1999). Evolving brains. Scientific American Library.
Amar, J., Burcelin, R., Ruidavets, J. B., Cani, P. D., Fauvel, J., Alessi, M. C., et al. (2008). Energy intake is associated with endotoxemia in apparently healthy men. American Journal of Clinical Nutrition, 87(5), 1219–1223. https://doi.org/10.1093/ajcn/87.5.1219
Amar, J., Chabo, C., Waget, A., Klopp, P., Vachoux, C., Bermudez-Humaran, L. G., et al. (2011). Intestinal mucosal adherence and translocation of commensal bacteria at the early onset of type 2 diabetes: Molecular mechanisms and probiotic treatment. EMBO Molecular Medicine, 3(9), 559–572. https://doi.org/10.1002/emmm.201100159
Arias-Jayo, N., Abecia, L., Alonso-Saez, L., Ramirez-Garcia, A., Rodriguez, A., & Pardo, M. A. (2018). High-fat diet consumption induces microbiota dysbiosis and intestinal inflammation in Zebrafish. Microbial Ecology, 76(4), 1089–1101. https://doi.org/10.1007/s00248-018-1198-9
Aron-Wisnewsky, J., Prifti, E., Belda, E., Ichou, F., Kayser, B. D., Dao, M. C., et al. (2019). Major microbiota dysbiosis in severe obesity: Fate after bariatric surgery. Gut, 68(1), 70–82. https://doi.org/10.1136/gutjnl-2018-316103
Arts, I. C., & Hollman, P. C. (2005). Polyphenols and disease risk in epidemiologic studies. American Journal of Clinical Nutrition, 81(1 Suppl), 317S-325S. https://doi.org/10.1093/ajcn/81.1.317S
Bang, C., Dagan, T., Deines, P., Dubilier, N., Duschl, W. J., Fraune, S., et al. (2018). Metaorganisms in extreme environments: Do microbes play a role in organismal adaptation? Zoology (jena, Germany), 127, 1–19. https://doi.org/10.1016/j.zool.2018.02.004
Belizario, J. E., Faintuch, J., & Garay-Malpartida, M. (2018). Gut microbiome dysbiosis and immunometabolism: New frontiers for treatment of metabolic diseases. Mediators of Inflammation, 2018, 2037838. https://doi.org/10.1155/2018/2037838
Ben-Dor, M., Sirtoli, R., & Barkai, R. (2021). The evolution of the human trophic level during the Pleistocene. American Journal of Physical Anthropology, 175(Suppl 72), 27–56. https://doi.org/10.1002/ajpa.24247
Besenbacher, S., Hvilsom, C., Marques-Bonet, T., Mailund, T., & Schierup, M. H. (2019). Direct estimation of mutations in great apes reconciles phylogenetic dating. Nat Ecol Evol, 3(2), 286–292. https://doi.org/10.1038/s41559-018-0778-x
Bocquet-Appel, J.-P. (2008). Explaining the Neolithic Demographic Transition. In J.-P. Bocquet-Appel & O. Bar-Yosef (Eds.), The Neolithic Demographic Transition and its Consequences (pp. 35–55). Springer, Netherlands.
Bortolin, R. C., Vargas, A. R., Gasparotto, J., Chaves, P. R., Schnorr, C. E., Martinello, K. B., et al. (2018). A new animal diet based on human Western diet is a robust diet-induced obesity model: Comparison to high-fat and cafeteria diets in term of metabolic and gut microbiota disruption. International Journal of Obesity, 42(3), 525–534. https://doi.org/10.1038/ijo.2017.225
Brooks, A. W., Kohl, K. D., Brucker, R. M., van Opstal, E. J., & Bordenstein, S. R. (2016). Phylosymbiosis: Relationships and functional effects of microbial communities across host evolutionary history. PLoS Biology, 14(11), e2000225. https://doi.org/10.1371/journal.pbio.2000225
Brown, E. A. (2012). Genetic explorations of recent human metabolic adaptations: Hypotheses and evidence. Biological Reviews of the Cambridge Philosophical Society, 87(4), 838–855. https://doi.org/10.1111/j.1469-185X.2012.00227.x
Brussow, H. (2020). Problems with the concept of gut microbiota dysbiosis. Microbial Biotechnology, 13(2), 423–434. https://doi.org/10.1111/1751-7915.13479
Burcelin, R. (2016). Gut microbiota and immune crosstalk in metabolic disease. Mol Metab, 5(9), 771–781. https://doi.org/10.1016/j.molmet.2016.05.016
Burcelin, R., Minty, M., Thomas, C., & Blasco, V. (2022). Implication des bactéries orales et intestinales dans le décours des maladies cardio-métaboliques et du diabète de type 2. Médecine Des Maladies Métaboliques, 16(2), 121–133. https://doi.org/10.1016/j.mmm.2022.01.003
Cani, P. D., Amar, J., Iglesias, M. A., Poggi, M., Knauf, C., Bastelica, D., et al. (2007). Metabolic endotoxemia initiates obesity and insulin resistance. Diabetes, 56(7), 1761–1772. https://doi.org/10.2337/db06-1491
Cani, P. D., Bibiloni, R., Knauf, C., Waget, A., Neyrinck, A. M., Delzenne, N. M., et al. (2008). Changes in gut microbiota control metabolic endotoxemia-induced inflammation in high-fat diet-induced obesity and diabetes in mice. Diabetes, 57(6), 1470–1481. https://doi.org/10.2337/db07-1403
Cani, P. D., Possemiers, S., Van de Wiele, T., Guiot, Y., Everard, A., Rottier, O., et al. (2009). Changes in gut microbiota control inflammation in obese mice through a mechanism involving GLP-2-driven improvement of gut permeability. Gut, 58(8), 1091–1103. https://doi.org/10.1136/gut.2008.165886
Cardona, F., Andres-Lacueva, C., Tulipani, S., Tinahones, F. J., & Queipo-Ortuno, M. I. (2013). Benefits of polyphenols on gut microbiota and implications in human health. Journal of Nutritional Biochemistry, 24(8), 1415–1422. https://doi.org/10.1016/j.jnutbio.2013.05.001
Chambers, E. S., Preston, T., Frost, G., & Morrison, D. J. (2018). Role of gut microbiota-generated short-chain fatty acids in metabolic and cardiovascular health. Curr Nutr Rep, 7(4), 198–206. https://doi.org/10.1007/s13668-018-0248-8
Christ, A., Lauterbach, M., & Latz, E. (2019). Western diet and the immune system: An inflammatory connection. Immunity, 51(5), 794–811. https://doi.org/10.1016/j.immuni.2019.09.020
Claesson, M. J., Jeffery, I. B., Conde, S., Power, S. E., O’Connor, E. M., Cusack, S., et al. (2012). Gut microbiota composition correlates with diet and health in the elderly. Nature, 488(7410), 178–184. https://doi.org/10.1038/nature11319
Cordain, L. (1999). Cereal grains: Humanity’s double-edged sword. World Review of Nutrition and Dietetics, 84, 19–73. https://doi.org/10.1159/000059677
Costa-Júnior, J. M., Ferreira, S. M., Kurauti, M. A., Bernstein, D. L., Ruano, E. G., Kameswaran, V., et al. (2021). Paternal exercise improves the metabolic health of offspring via epigenetic modulation of the germline. International Journal of Molecular Sciences, 23(1), 1. https://doi.org/10.3390/ijms23010001
Cotillard, A., Kennedy, S. P., Kong, L. C., Prifti, E., Pons, N., Le Chatelier, E., et al. (2013). Dietary intervention impact on gut microbial gene richness. Nature, 500(7464), 585–588. https://doi.org/10.1038/nature12480
Devkota, S., Wang, Y., Musch, M. W., Leone, V., Fehlner-Peach, H., Nadimpalli, A., et al. (2012). Dietary-fat-induced taurocholic acid promotes pathobiont expansion and colitis in Il10-/- mice. Nature, 487(7405), 104–108. https://doi.org/10.1038/nature11225
Dixit, T., Tiwari, A., Bose, S., Kulkarni, H., Suthar, J., & Ravindran, S. (2021). Metabolism of Phytochemicals. Drug Metabolism. https://doi.org/10.5772/intechopen.100569
Doré, J., & Blottière, H. (2015). The influence of diet on the gut microbiota and its consequences for health. Current Opinion in Biotechnology, 32, 195–199. https://doi.org/10.1016/j.copbio.2015.01.002
Duerkop, B. A., Vaishnava, S., & Hooper, L. V. (2009). Immune responses to the microbiota at the intestinal mucosal surface. Immunity, 31(3), 368–376. https://doi.org/10.1016/j.immuni.2009.08.009
Easson, C. G., & Thacker, R. W. (2014). Phylogenetic signal in the community structure of host-specific microbiomes of tropical marine sponges. Frontiers in Microbiology, 5, 532. https://doi.org/10.3389/fmicb.2014.00532
Eaton, S. B., Eaton, S. B., 3rd., & Konner, M. J. (1997). Paleolithic nutrition revisited: A twelve-year retrospective on its nature and implications. European Journal of Clinical Nutrition, 51(4), 207–216. https://doi.org/10.1038/sj.ejcn.1600389
Eaton, S. B., & Konner, M. (1985). Paleolithic nutrition. A consideration of its nature and current implications. New England Journal of Medicine, 312(5), 283–289. https://doi.org/10.1056/NEJM198501313120505
Erridge, C. (2011). Diet, commensals and the intestine as sources of pathogen-associated molecular patterns in atherosclerosis, type 2 diabetes and non-alcoholic fatty liver disease. Atherosclerosis, 216(1), 1–6. https://doi.org/10.1016/j.atherosclerosis.2011.02.043
Felton, A. M., Felton, A., Lindenmayer, D. B., & Foley, W. J. (2009). Nutritional goals of wild primates. Functional Ecology, 23(1), 70–78. https://doi.org/10.1111/j.1365-2435.2008.01526.x
Flatt, T., & Heyland, A. (2011). Mechanisms of life history evolution: The genetics and physiology of life history traits and trade-offs. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199568765.001.0001
Franck, R., Galor, O., Moav, O., & Özak, Ö. (2022). The shadow of the neolithic revolution on life expectancy: A double-edged sword. https://doi.org/10.2139/ssrn.4046280
Frankel, J. S., Mallott, E. K., Hopper, L. M., Ross, S. R., & Amato, K. R. (2019). The effect of captivity on the primate gut microbiome varies with host dietary niche. American Journal of Primatology, 81(12), e23061. https://doi.org/10.1002/ajp.23061
Fromentin, S., Forslund, S. K., Chechi, K., Aron-Wisnewsky, J., Chakaroun, R., Nielsen, T., et al. (2022). Microbiome and metabolome features of the cardiometabolic disease spectrum. Nature Medicine, 28(2), 303–314. https://doi.org/10.1038/s41591-022-01688-4
Ghoshal, S., Witta, J., Zhong, J., de Villiers, W., & Eckhardt, E. (2009). Chylomicrons promote intestinal absorption of lipopolysaccharides. Journal of Lipid Research, 50(1), 90–97. https://doi.org/10.1194/jlr.M800156-JLR200
Gibbons, A. (2016). Humans are the highest energy apes, making us smarter—but also fatter. Science. https://doi.org/10.1126/science.aaf5692
Gillings, M. R., Paulsen, I. T., & Tetu, S. G. (2015). Ecology and evolution of the human microbiota: Fire Farming and Antibiotics. Genes (basel), 6(3), 841–857. https://doi.org/10.3390/genes6030841
Gomez, A., Petrzelkova, K. J., Burns, M. B., Yeoman, C. J., Amato, K. R., Vlckova, K., et al. (2016). Gut microbiome of coexisting baaka pygmies and bantu reflects gradients of traditional subsistence patterns. Cell Reports, 14(9), 2142–2153. https://doi.org/10.1016/j.celrep.2016.02.013
Gregor, M. F., & Hotamisligil, G. S. (2011). Inflammatory mechanisms in obesity. Annual Review of Immunology, 29, 415–445. https://doi.org/10.1146/annurev-immunol-031210-101322
Groussin, M., Mazel, F., & Alm, E. J. (2020). Co-evolution and co-speciation of host-gut bacteria systems. Cell Host & Microbe, 28(1), 12–22. https://doi.org/10.1016/j.chom.2020.06.013
Groussin, M., Mazel, F., Sanders, J. G., Smillie, C. S., Lavergne, S., Thuiller, W., et al. (2017). Unraveling the processes shaping mammalian gut microbiomes over evolutionary time. Nature Communications, 8, 14319. https://doi.org/10.1038/ncomms14319
Hales, C. N., & Barker, D. J. (1992). Type 2 (non-insulin-dependent) diabetes mellitus: The thrifty phenotype hypothesis. Diabetologia, 35(7), 595–601. https://doi.org/10.1007/BF00400248
Hales, C. N., & Barker, D. J. (2001). The thrifty phenotype hypothesis. British Medical Bulletin, 60, 5–20. https://doi.org/10.1093/bmb/60.1.5
Hancock, A. M., Witonsky, D. B., Ehler, E., Alkorta-Aranburu, G., Beall, C., Gebremedhin, A., et al. (2010). Colloquium paper: Human adaptations to diet, subsistence, and ecoregion are due to subtle shifts in allele frequency. Proceedings of the National Academy of Sciences USA, 107(Suppl 2), 8924–8930. https://doi.org/10.1073/pnas.0914625107
Hosking, C. J., Raubenheimer, D., Charleston, M. A., Simpson, S. J., & Senior, A. M. (2019). Macronutrient intakes and the lifespan-fecundity trade-off: A geometric framework agent-based model. Journal of the Royal Society, Interface, 16(151), 20180733. https://doi.org/10.1098/rsif.2018.0733
Hosseinkhani, F., Heinken, A., Thiele, I., Lindenburg, P. W., Harms, A. C., & Hankemeier, T. (2021). The contribution of gut bacterial metabolites in the human immune signaling pathway of non-communicable diseases. Gut Microbes, 13(1), 1–22. https://doi.org/10.1080/19490976.2021.1882927
Janzen, D. H. (1980). When Is It Coevolution? Evolution, 34(3), 611–612. https://doi.org/10.1111/j.1558-5646.1980.tb04849.x
Johansson, M. E., Larsson, J. M., & Hansson, G. C. (2011). The two mucus layers of colon are organized by the MUC2 mucin, whereas the outer layer is a legislator of host-microbial interactions. Proceedings of the National Academy of Sciences USA, 108(Suppl 1), 4659–4665. https://doi.org/10.1073/pnas.1006451107
Kavanagh, K., Wylie, A. T., Tucker, K. L., Hamp, T. J., Gharaibeh, R. Z., Fodor, A. A., et al. (2013). Dietary fructose induces endotoxemia and hepatic injury in calorically controlled primates. American Journal of Clinical Nutrition, 98(2), 349–357. https://doi.org/10.3945/ajcn.112.057331
Kohl, K. D., Varner, J., Wilkening, J. L., & Dearing, M. D. (2018). Gut microbial communities of American pikas (Ochotona princeps): Evidence for phylosymbiosis and adaptations to novel diets. Journal of Animal Ecology, 87(2), 323–330. https://doi.org/10.1111/1365-2656.12692
Kones, R., & Rumana, U. (2017). Cardiometabolic diseases of civilization: History and maturation of an evolving global threat. An update and call to action. Annals of Medicine, 49(3), 260–274. https://doi.org/10.1080/07853890.2016.1271957
Kuzawa, C. W., & Kim, A. W. (2022). Early environments, developmental plasticity, and chronic degenerative disease. Elsevier. https://doi.org/10.1016/b978-0-12-822652-0.00020-1
Kuzawa, C. W., & Thayer, Z. M. (2011). Timescales of human adaptation: The role of epigenetic processes. Epigenomics, 3(2), 221–234. https://doi.org/10.2217/epi.11.11
Langergraber, K. E., Prufer, K., Rowney, C., Boesch, C., Crockford, C., Fawcett, K., et al. (2012). Generation times in wild chimpanzees and gorillas suggest earlier divergence times in great ape and human evolution. Proceedings of the National Academy of Sciences USA, 109(39), 15716–15721. https://doi.org/10.1073/pnas.1211740109
Laugerette, F., Vors, C., Geloen, A., Chauvin, M. A., Soulage, C., Lambert-Porcheron, S., et al. (2011). Emulsified lipids increase endotoxemia: Possible role in early postprandial low-grade inflammation. Journal of Nutritional Biochemistry, 22(1), 53–59. https://doi.org/10.1016/j.jnutbio.2009.11.011
Le Chatelier, E., Nielsen, T., Qin, J., Prifti, E., Hildebrand, F., Falony, G., et al. (2013). Richness of human gut microbiome correlates with metabolic markers. Nature, 500(7464), 541–546. https://doi.org/10.1038/nature12506
Lecerf, J.-M., & Cani, P. D. (2022). Nutrition et microbiote dans le diabète de type 2. De la symbiose à la dysfonction métabolique. Médecine des Maladies Métaboliques, 16(2), 114–120. https://doi.org/10.1016/j.mmm.2022.01.002
Lyte, J. M., Gabler, N. K., & Hollis, J. H. (2016). Postprandial serum endotoxin in healthy humans is modulated by dietary fat in a randomized, controlled, cross-over study. Lipids in Health and Disease, 15(1), 186. https://doi.org/10.1186/s12944-016-0357-6
Määttä, A. M., Salminen, A., Pietiainen, M., Leskela, J., Palviainen, T., Sattler, W., et al. (2021). Endotoxemia is associated with an adverse metabolic profile. Innate Immunity, 27(1), 3–14. https://doi.org/10.1177/1753425920971702
Malard, F., Doré, J., Gaugler, B., & Mohty, M. (2021). Introduction to host microbiome symbiosis in health and disease. Mucosal Immunology, 14(3), 547–554. https://doi.org/10.1038/s41385-020-00365-4
Mathieson, S., & Mathieson, I. (2018). FADS1 and the timing of human adaptation to agriculture. Molecular Biology and Evolution, 35(12), 2957–2970. https://doi.org/10.1093/molbev/msy180
Milton, K. (1993). Diet and primate evolution. Scientific American, 269(2), 86–93. https://doi.org/10.1038/scientificamerican0893-86
Moeller, A. H., Caro-Quintero, A., Mjungu, D., Georgiev, A. V., Lonsdorf, E. V., Muller, M. N., et al. (2016). Cospeciation of gut microbiota with hominids. Science, 353(6297), 380–382. https://doi.org/10.1126/science.aaf3951
Moeller, A. H., Li, Y., Mpoudi Ngole, E., Ahuka-Mundeke, S., Lonsdorf, E. V., Pusey, A. E., et al. (2014). Rapid changes in the gut microbiome during human evolution. Proceedings of the National Academy of Sciences USA, 111(46), 16431–16435. https://doi.org/10.1073/pnas.1419136111
Mowat, A. M. (2018). To respond or not to respond - a personal perspective of intestinal tolerance. Nature Reviews Immunology, 18(6), 405–415. https://doi.org/10.1038/s41577-018-0002-x
Neel, J. V. (1962). Diabetes mellitus: A “thrifty” genotype rendered detrimental by “progress”? American Journal of Human Genetics, 14, 353–362.
Ochman, H., Worobey, M., Kuo, C. H., Ndjango, J. B., Peeters, M., Hahn, B. H., et al. (2010). Evolutionary relationships of wild hominids recapitulated by gut microbial communities. PLoS Biology, 8(11), e1000546. https://doi.org/10.1371/journal.pbio.1000546
Perry, G. H., Dominy, N. J., Claw, K. G., Lee, A. S., Fiegler, H., Redon, R., et al. (2007). Diet and the evolution of human amylase gene copy number variation. Nature Genetics, 39(10), 1256–1260. https://doi.org/10.1038/ng2123
Phillips, C. D., Phelan, G., Dowd, S. E., McDonough, M. M., Ferguson, A. W., Delton Hanson, J., et al. (2012). Microbiome analysis among bats describes influences of host phylogeny, life history, physiology and geography. Molecular Ecology, 21(11), 2617–2627. https://doi.org/10.1111/j.1365-294X.2012.05568.x
Pontzer, H., Brown, M. H., Raichlen, D. A., Dunsworth, H., Hare, B., Walker, K., et al. (2016). Metabolic acceleration and the evolution of human brain size and life history. Nature, 533(7603), 390–392. https://doi.org/10.1038/nature17654
Pontzer, H., Wood, B. M., & Raichlen, D. A. (2018). Hunter-gatherers as models in public health. Obesity Reviews, 19(Suppl 1), 24–35. https://doi.org/10.1111/obr.12785
Popovich, D. G., Jenkins, D. J., Kendall, C. W., Dierenfeld, E. S., Carroll, R. W., Tariq, N., et al. (1997). The western lowland gorilla diet has implications for the health of humans and other hominoids. Journal of Nutrition, 127(10), 2000–2005. https://doi.org/10.1093/jn/127.10.2000
Qiao, Y., Sun, J., Ding, Y., Le, G., & Shi, Y. (2013). Alterations of the gut microbiota in high-fat diet mice is strongly linked to oxidative stress. Applied Microbiology and Biotechnology, 97(4), 1689–1697. https://doi.org/10.1007/s00253-012-4323-6
Rainone, V., Schneider, L., Saulle, I., Ricci, C., Biasin, M., Al-Daghri, N. M., et al. (2016). Upregulation of inflammasome activity and increased gut permeability are associated with obesity in children and adolescents. International Journal of Obesity, 40(6), 1026–1033. https://doi.org/10.1038/ijo.2016.26
Rampelli, S., Schnorr, S. L., Consolandi, C., Turroni, S., Severgnini, M., Peano, C., et al. (2015). Metagenome sequencing of the hadza hunter-gatherer gut microbiota. Current Biology, 25(13), 1682–1693. https://doi.org/10.1016/j.cub.2015.04.055
Raubenheimer, D., Simpson, S. J., & Mayntz, D. (2009). Nutrition, ecology and nutritional ecology: Toward an integrated framework. Functional Ecology, 23(1), 4–16. https://doi.org/10.1111/j.1365-2435.2009.01522.x
Raubenheimer, D., Simpson, S. J., & Tait, A. H. (2012). Match and mismatch: Conservation physiology, nutritional ecology and the timescales of biological adaptation. Philosophical Transactions of the Royal Society of London. Series b, Biological Sciences, 367(1596), 1628–1646. https://doi.org/10.1098/rstb.2012.0007
Régnier, M., Van Hul, M., Knauf, C., & Cani, P. D. (2021). Gut microbiome, endocrine control of gut barrier function and metabolic diseases. Journal of Endocrinology, 248(2), R67–R82. https://doi.org/10.1530/JOE-20-0473
Roff, D. A., & Fairbairn, D. J. (2007). The evolution of trade-offs: Where are we? Journal of Evolutionary Biology, 20(2), 433–447. https://doi.org/10.1111/j.1420-9101.2006.01255.x
Rosenberg, E., & Zilber-Rosenberg, I. (2016). Microbes drive evolution of animals and plants: The hologenome concept. MBio, 7(2), e01395. https://doi.org/10.1128/mBio.01395-15
Saklayen, M. G. (2018). The global epidemic of the metabolic syndrome. Current Hypertension Reports, 20(2), 12. https://doi.org/10.1007/s11906-018-0812-z
Sansonetti, P. J. (2011). To be or not to be a pathogen: That is the mucosally relevant question. Mucosal Immunology, 4(1), 8–14. https://doi.org/10.1038/mi.2010.77
Ségurel, L., Austerlitz, F., Toupance, B., Gautier, M., Kelley, J. L., Pasquet, P., et al. (2013). Positive selection of protective variants for type 2 diabetes from the neolithic onward: A case study in central Asia. European Journal of Human Genetics, 21(10), 1146–1151. https://doi.org/10.1038/ejhg.2012.295
Ségurel, L., & Bon, C. (2017). On the evolution of lactase persistence in humans. Annual Review of Genomics and Human Genetics, 18, 297–319. https://doi.org/10.1146/annurev-genom-091416-035340
Shapira, M. (2016). Gut microbiotas and host evolution: Scaling up symbiosis. Trends in Ecology & Evolution, 31(7), 539–549. https://doi.org/10.1016/j.tree.2016.03.006
Shimelmitz, R., Kuhn, S. L., Jelinek, A. J., Ronen, A., Clark, A. E., & Weinstein-Evron, M. (2014). “Fire at will”: The emergence of habitual fire use 350,000 years ago. Journal of Human Evolution, 77, 196–203. https://doi.org/10.1016/j.jhevol.2014.07.005
Simpson, S. J., Le Couteur, D. G., James, D. E., George, J., Gunton, J. E., Solon-Biet, S. M., et al. (2017). The Geometric framework for nutrition as a tool in precision medicine. Nutrition Healthy Aging, 4(3), 217–226. https://doi.org/10.3233/NHA-170027
Simpson, S. J., & Raubenheimer, D. (1995). The geometric analysis of feeding and nutrition: A user’s guide. Journal of Insect Physiology, 41(7), 545–553. https://doi.org/10.1016/0022-1910(95)00006-g
Simpson, S. J., & Raubenheimer, D. (2005). Obesity: The protein leverage hypothesis. Obesity Reviews, 6(2), 133–142. https://doi.org/10.1111/j.1467-789X.2005.00178.x
Simpson, S. J., & Raubenheimer, D. (2012). The Nature of Nutrition. Chapter Five. Beyond Nutrients. Princeton University Press. https://doi.org/10.1515/9781400842803.71
Snell-Rood, E., Cothran, R., Espeset, A., Jeyasingh, P., Hobbie, S., & Morehouse, N. I. (2015). Life-history evolution in the anthropocene: Effects of increasing nutrients on traits and trade-offs. Evolutionary Applications, 8(7), 635–649. https://doi.org/10.1111/eva.12272
Sonnenburg, E. D., Smits, S. A., Tikhonov, M., Higginbottom, S. K., Wingreen, N. S., & Sonnenburg, J. L. (2016). Diet-induced extinctions in the gut microbiota compound over generations. Nature, 529(7585), 212–215. https://doi.org/10.1038/nature16504
Sonnenburg, E. D., & Sonnenburg, J. L. (2019). The ancestral and industrialized gut microbiota and implications for human health. Nature Reviews Microbiology, 17(6), 383–390. https://doi.org/10.1038/s41579-019-0191-8
Sonnenburg, J. L., & Backhed, F. (2016). Diet-microbiota interactions as moderators of human metabolism. Nature, 535(7610), 56–64. https://doi.org/10.1038/nature18846
Stöger, R. (2008). The thrifty epigenotype: An acquired and heritable predisposition for obesity and diabetes? BioEssays, 30(2), 156–166. https://doi.org/10.1002/bies.20700
Stone, A. C. (2020). Getting sick in the Neolithic. Nat Ecology Evolution, 4(3), 286–287. https://doi.org/10.1038/s41559-020-1115-8
Turnbaugh, P. J., Ridaura, V. K., Faith, J. J., Rey, F. E., Knight, R., & Gordon, J. I. (2009). The effect of diet on the human gut microbiome: a metagenomic analysis in humanized gnotobiotic mice. Science Translation Medicine. https://doi.org/10.1126/scitranslmed.3000322
van de Guchte, M., Blottiere, H. M., & Dore, J. (2018). Humans as holobionts: Implications for prevention and therapy. Microbiome, 6(1), 81. https://doi.org/10.1186/s40168-018-0466-8
Van Hul, M., & Cani, P. D. (2019). Targeting carbohydrates and polyphenols for a healthy microbiome and healthy weight. Curr Nutr Rep, 8(4), 307–316. https://doi.org/10.1007/s13668-019-00281-5
Vemuri, R., Ruggiero, A., Whitfield, J. M., Dugan, G. O., Cline, J. M., Block, M. R., et al. (2022). Hypertension promotes microbial translocation and dysbiotic shifts in the fecal microbiome of nonhuman primates. American Journal of Physiology. Heart and Circulatory Physiology, 322(3), H474–H485. https://doi.org/10.1152/ajpheart.00530.2021
Walter, J., & Ley, R. (2011). The human gut microbiome: Ecology and recent evolutionary changes. Annual Review of Microbiology, 65, 411–429. https://doi.org/10.1146/annurev-micro-090110-102830
Wells, J. C. K., & Stock, J. T. (2020). Life history transitions at the origins of agriculture: A model for understanding how niche construction impacts human growth DEMOGRAPHY and Health. Front Endocrinol (lausanne), 11, 325. https://doi.org/10.3389/fendo.2020.00325
Zeng, M. Y., Inohara, N., & Nunez, G. (2017). Mechanisms of inflammation-driven bacterial dysbiosis in the gut. Mucosal Immunology, 10(1), 18–26. https://doi.org/10.1038/mi.2016.75
Zhao, S., Lieberman, T. D., Poyet, M., Kauffman, K. M., Gibbons, S. M., Groussin, M., et al. (2019). Adaptive evolution within gut microbiomes of healthy people. Cell Host & Microbe, 25(5), 656–667. https://doi.org/10.1016/j.chom.2019.03.007
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M.C.V. is Tier 1 Canada Research Chair in Genomics Applied to Nutrition and Metabolic Health. M.F. received a studentship from the Centre Nutrition, Santé et Société (NUTRISS).
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Franck, M., de Toro-Martín, J. & Vohl, MC. Eco-Evolutionary Dynamics of the Human-Gut Microbiota Symbiosis in a Changing Nutritional Environment. Evol Biol 49, 255–264 (2022). https://doi.org/10.1007/s11692-022-09569-x
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DOI: https://doi.org/10.1007/s11692-022-09569-x