Background: Our daily intake of food provides nutrients for the maintenance of health, growth, and development. The field of nutrigenomics aims to link dietary intake/nutrients to changes in epigenetic status and gene expression. Summary: Although the relationship between our diet and our genes in under intense investigation, there is still a significant aspect of our genome that has received little attention with regard to this. In the past 15 years, the importance of genome organization has become increasingly evident, with research identifying small-scale local changes to large segments of the genome dynamically repositioning within the nucleus in response to/or mediating change in gene expression. The discovery of these dynamic processes and organization maybe as significant as dynamic plate tectonics is to geology, there is little information tying genome organization to specific nutrients or dietary intake. Key Messages: Here, we detail key principles of genome organization and structure, with emphasis on genome folding and organization, and link how these contribute to our future understand of nutrigenomics.

We have known for centuries that diet and health are closely related. From the application of lime juice by the royal navy to combat scurvy during the Napoleonic wars to current practices in fortifying milk with vitamin D, prophylactic management of malnutrition is a well-established and efficacious practice. While there is significant information available on roles of essential and nonessential nutrients associated with health, we are now only beginning to understand the cellular and molecular processes that govern these effects. Included in this new information are insights into relationships between nutrients and our genes. Diet is the primary environmental factor influencing the timing and level of expression of many genes, through modulating transcription factor binding and epigenetics. However, little information is available regarding the impact of nutrients on overall genome folding and organization. With the development of novel tools, such as chromosome conformation capture [1] and high throughput sequencing technologies [2‒5], it is evident that genome organization is an essential component of genome biology. Using a nutrigenomics framework, we review the current evidence on how dietary compounds impact global genome organization and the relationship with health and lifespan.

It is undeniable that the primary sequence of our genome encodes all the biological potential of what we can become. Rosalind Franklin’s diffraction data, and subsequent modelling by Watson and Crick, identified the fundamental double helical structure of DNA, marking the first association of genome structure with function. Since this time, we have studied the relationship between the primary sequences of DNA to gain information on the genes it encodes. With the Herculean effort of the Human Genome Project as well as the 1,000 Genomes Project, we have now begun to truly understand how this primary sequence provides the blueprint for all the biological potential within an organism. Within this code, we have natural variations that do not necessarily cause disease but changes how our biology responds to our ever-changing environment. A classical definition of nutrigenetics is the study of how genetic variations effect how our cells “interpret” nutrients and by extension the impact on health, disease, and lifespan (Fig. 1). Genetic testing now identifies numerous markers that indicate how an individual will respond to specific dietary compounds [6, 7]. Such studies use genome-wide association assays to identify variations within populations correlated with the phenotype in question, focusing on single nucleotide polymorphisms (SNPs) to establish a functional relationship [8, 9]. Caffeine metabolism is an excellent example of how specific SNPs within a subset of genes relate to a phenotypic outcome [10]. In 2012, Josse and colleagues identified 3 SNPs linking increased caffeine consumption and increased risk of coronary heart disease, two near the in the aryl-hydrocarbon receptor (AHR) gene and one in the cytochrome P450 1A1 and 1A2 (CYP1A1-CYP1A2) genes [11]. The AA allele conveyed lowered risk of coronary heart disease. In athletes, the AA allele provided an increase in performance after caffeine consumption while those with AC or CC alleles exhibited either no benefit or suffered detrimental impacts to performance [12]. Numerous other SNPs associated with metabolism or disease have been identified using similar approaches, including those associated with Celiac’s Disease, alcohol metabolism, amino acid metabolism disorders such phenylketonuria, folate metabolism [13], and lipid metabolism [8, 14]. These approaches have also been employed to find genes or SNPs associated with increased longevity. For example, genome-wide association assays of the population of Okinawa, Japan, have identified SNPS that correlate with higher life expectance than anywhere else on the planet (https://orcls.org).

Fig. 1.

Nutrigenetics versus nutrigenomics. Nutrigenetics is the study of how genetic variation impacts how cells interpret/use essential and nonessential nutrients whereas nutrigenomics is the study of how these nutrients modulate the function of the genome through organizational changes.

Fig. 1.

Nutrigenetics versus nutrigenomics. Nutrigenetics is the study of how genetic variation impacts how cells interpret/use essential and nonessential nutrients whereas nutrigenomics is the study of how these nutrients modulate the function of the genome through organizational changes.

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Although there are examples where a single base-pair change dictates a severe phenotype, such as that observed with the premature aging disease Hutchinson-Gilford progeria syndrome (HGPS), analysis of a single locus rarely proves sufficient to predict observable phenotypes. Most phenotypes/diseases are associated with defects or changes in multiple genes involved with a single pathway. More accurate methods for linking small genetic changes with phenotype have been developed to reflect this. For example, polygenic scores aggregate the impact of multiple genetic variations into a single score to predict a phenotype (https://pgscatalog.org). Although associating multiple loci and SNPs is a more comprehensive approach to linking genotype with phenotype and attempts are being made to include clinically relevant information on the impact of environmental factors such as diet, there is still large gap in how specific nutrients impact genome function and organization. For example, a recent study identified ∼7,000 SNPs in 90 genes related to plasma vitamin B12 levels in children and adolescence [15]. 36 variants were used to create a polygenic score that accounted for 42% of the B12 plasma level changes. Although an intriguing study with important information, it is unclear if changes in dietary B12 levels could compensate for any variations in the genetic background and what impact this has on genome function and organization.

Where nutrigenetics identifies how nutrients are interpreted or processed, nutrigenomics endeavors to identify the mechanisms by which nutrients modulate genome function and organization. Although most nutrigenomics studies focus on changes in gene expression, the mechanisms underpinning these changes involve an array of processes. However, the impact of nutrients on genome organization within the nuclear volume and how this impacts changes in gene expression is commonly overlooked. Here, we take a genomics/cell biology approach to the impact of dietary compounds. Although only a few examples exist as to how nutrients govern genome folding and its impact on gene expression, our hypothesis is that change in dietary compounds and nutrients will have a significant impact on the folding of the genome. Given the numerous examples of dynamic genome folding and organization in different biological systems, and the importance of diet and dietary compounds on gene expression, it is highly probable that genome dynamics will be responsive to the presence or absence of specific nutrients.

To fully appreciate 3-dimensional genome organization and its dynamics, we first need to review the fundamental principles of genome biology. In eukaryotic systems, DNA is complexed with positively charged histone proteins to form chromatin. The most basic structure of chromatin is the nucleosome (Table 1); ∼146 bp of DNA wrapped around a histone octamer (two of each H2A, H2B, H3, and H4) proteins [16‒19]. With the 3.6 billion base pairs of DNA measuring ∼2 m in a single cell, some theories suggest that the primary driver for chromatin evolution was to allow for efficient packing. However, electron micrographs measuring the volume of the nucleus occupied by chromatin reveals that this is only ∼16.5% of the total volume [20], indicating that compaction is not the primary driver. In addition, the association of DNA with histones actually increases the total volume occupied, further providing evidence against this theory. One possible explanation for chromatin evolution may be that the primary sequence of DNA alone does not contain sufficient functionality to guide gene regulation. Although the primary DNA sequence contains essential sequence motifs for DNA binding proteins and transcription factors, this is only one critical step in gene regulation. As such, the tails of histones that protrude from the nucleosomal core likely evolved to provide the additional levels of regulation and structures for controlling gene expression. Modification of these histone tails by post-translation modifications provide information indicating if a gene is to be transcribed or repressed. These histone modifications, in combination with CpG island methylation and noncoding RNAs (not discussed here) constitute the epigenome. In contrast to the relatively stable nature of the primary DNA sequence, the epigenome is extremely dynamic and can change within minutes in response to cells receiving stimuli. Although epigenetic changes are central to mediating genome response to dietary compounds, there are several excellent review articles [21‒24] discussing this topic, and we will focus on genome structure and organization.

Table 1.

Summary of the levels of genome organization

 Summary of the levels of genome organization
 Summary of the levels of genome organization

Chromatin fibers have been proposed to exist in a large array of different conformations. For example, cryo-TEM studies demonstrate with striking resolution, the potential solenoid and 2-start models of the 30 nm chromatin fiber. Although these structures have been described with phenomenal detail, analyses focus on either in vitro reconstituted chromatin or chromatin isolated from cells, treated with extremely high levels of salts, including magnesium ions. Although these studies demonstrate that these structures can form, it is unclear if they are present in vivo. Surprisingly, there are only two levels of organization in terms of chromatin fibers that we can confirm in vivo; the nucleosome and the 10 nm fiber. Electron micrographic studies from the Bazzet-Jones [25, 26] and Maeshima [27] laboratories indicate that there is no chromatin fiber above that of 10 nm, even in the mitotic chromosomes.

Heterochromatin versus Euchromatin

The concepts of “open” transcriptionally active chromatin (euchromatin) and “closed” transcriptionally silent chromatin (heterochromatin) are decades old. It has been proposed that transcriptionally active euchromatin have a more open structure in that the adjacent nucleosomes on the fiber are farther apart, much like a spring being stretched [25, 26]. Heterochromatin is represented by the spring being collapsed, pushing adjacent nucleosomes together and forming interactions that protect the fiber and prevent proteins, such as transcription factors and transcriptional machinery from accessing these sequences (Fig. 2). Classic chromatin experiments, such as DNAse I protection assays seem to support this model, where transcriptionally silent regions of the genome are “protected” from nucleases. However, electron microscopy indicates that adjacent fibers are simply pushed together and that this is not the result of higher order structures forming in the chromatin. Data generated from the assay for transposase accessible chromatin-sequencing, which uses the Tn5 retro-transposase to add a DNA sequence tag to open chromatin, provide evidence that regions such as promoters and enhancers are more accessible [28]. However, instead of nucleosome packing, this euchromatin could be represented by fibers being further distanced from each other or a disruption of nucleosome structure. Heterochromatin may also be more inaccessible as these fibers are generally coated with transcriptionally repressive complexes, such as the Polycomb repressive complex 2 (PRC2) [29, 30], limiting access of proteins to the sequences beneath. The nature of chromatin in terms of “open” or “closed” is likely represented by a combination of the factors listed above.

Fig. 2.

Sub-chromosomal folding of the genome into TADs and LADs. In addition to the genome being organized into chromosome territories (represented by the red, blue, and green lines) within the nucleus, the genome is organized into locally folded compartments called topologically associated domains (TADs). TADs (10s–100s of Kb in size) that are transcriptionally active cluster with other transcriptionally active TADs (A compartment) while transcriptionally inactive TADs cluster (B compartment). Inset: TADs that are organized by chromatin interaction with the nuclear lamina (grey wavy line) are called lamina-associated domains (LADs) and are generally comprised of transcriptionally silent chromatin.

Fig. 2.

Sub-chromosomal folding of the genome into TADs and LADs. In addition to the genome being organized into chromosome territories (represented by the red, blue, and green lines) within the nucleus, the genome is organized into locally folded compartments called topologically associated domains (TADs). TADs (10s–100s of Kb in size) that are transcriptionally active cluster with other transcriptionally active TADs (A compartment) while transcriptionally inactive TADs cluster (B compartment). Inset: TADs that are organized by chromatin interaction with the nuclear lamina (grey wavy line) are called lamina-associated domains (LADs) and are generally comprised of transcriptionally silent chromatin.

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Chromosome Territories

Textbooks often represent entire chromosomes as either the iconic structures observed as cells undergoing mitosis or unorganized jumbles of fibers resembling a bowl of spaghetti. Reality; however, is much more complex. Chromosomes occupy their own discrete volumes of the nucleus called chromosome territories (Table 1). Using DNA fluorescence in situ hybridization, Bolzer and colleagues [31] observed that each chromosome occupied its own position within the volume of the nucleus of human lymphoblasts. In addition, each chromosome had preferential “neighbors;” chromosomes pairs that were often found adjacent to each other within nuclei. Using a combination of DNA fluorescence in situ hybridization and cryo-electron microscopy, Branco and Pombo identified that although chromosomes did occupy their own volumes, loops of chromatin on the periphery of these territories could invade the adjacent territory [32].

Chromosome territories are also not static but are highly dynamic and responsive to cellular stimuli. Normal human dermal fibroblasts (NDFs) reposition chromosomes within nuclei within 15 min of serum removal. In proliferating cells, Mehta and colleagues identified that chromosome 18 moved from the periphery of the nucleus to the center with chromosome 10 moving from an intermediate position between the periphery and the core, to the periphery [33, 34]. This rapid movement implies an active mechanism(s), but what could provide this type of directed movement rapidly? Numerous studies document the presence of a large pool of nuclear actin (reviewed in [35]). Furthermore, there are several genes encoding motor proteins called nuclear myosins [36‒38]. Knockdown of nuclear myosin I-β (NM1β) or the presence of jaspakinolide [39, 40], which stabilizes actin polymers, inhibits the repositioning of chromosomes [33]. Although more research is required to pin down exactly how these molecules are involved, observations (as well as those from the analysis of sub-chromosomal reorganization) strongly indicate that nuclear actin and myosin play a major role in chromosome territory dynamics.

What does this movement mean in terms of gene expression? Chromosomes 10 and 18 also move in response to disruption of cellular nutrient sensing using rapamycin or metformin [41, 42] similar to that observed with serum removal. Although chromosome repositioning was similar, pathway analysis using differential gene expression demonstrated that there was very little overlap between the genes changing expression between serum deprivation, rapamycin, and metformin [41‒43]. In addition, there were no specific biases to the proportions of genes encoded on any one chromosome changing expression. Although the repositioning of chromosomes in response to these stimuli is likely driven by transcriptional requirements, the precise link between these two events remains to be elucidated.

In addition to the large-scale reorganization of the genome observed with chromosome territory repositioning, there are also locally folded chromatin environments that are observed between distal enhancer elements and gene promoters. The paradigm for this is the interaction of the globin genes during development, with the distal upstream locus control regions (LCR) [44‒48]. Located ∼60 kB upstream of the globin genes, the LCR consists of open chromatin domains encoding transcription factor binding sites, that when bound, fold to make the LCR forms long-range chromatin interactions with globin promoters. In mouse experiments, deletion of the LCR disrupts the long-range interactions, resulting in a 95% reduction in globin transcription and embryonic lethality due to severe anemia. In mice, the globin genes are located on chromosome 7, along with other erythroid-specific genes Eraf and Uros. Both genes can be in close physical proximity to the globin genes, although they are located >25 MB away on the linear chromosome [3]. Other genes located in the intervening sequences along this chromosome that are not involved with erythroid development are not found in proximity. These observations demonstrate that like-regulated regions of the genome are brought together in the nuclear volume and establish local chromatin environment. Several other cell types also exhibit specific folding patterns, including T helper cells [49, 50], olfactory gene interactions in mouse olfactory bulbs [51], as well as V(D)J recombination in immature B cells to generate antibody repertoires [52]. Chromatin interactions are also dynamic and responsive to stimuli and are not limited to the same chromosome. In resting B cells, the cMyc (chromosome 12) and IgH (chromosome 15) loci are not in physical contact; however, when stimulated with interleukin-4 (Il-4), these genes are found to be in contact at high frequency [53]. Furthermore, the cMyc and IgH loci can form translocations resulting in plasmocytoma and Burrkits Lymphoma. This only occurs in stimulated B cells and not in unstimulated cells, indicating that the proximity is key and that these chromatin interactions are dynamic. Further evidence for the impact of genome organization is provided within a comprehensive study demonstrating that genes that have a high frequency of forming translocations are often found in close spatial proximity within the nuclear volume [54]. This makes sense; you would not expect to find the same high frequencies of specific translocations if these gene pairs were not organized into the same local nuclear environment.

What is driving these features to be in close spatial proximity? In the vast majority of chromatin interactions identified, active transcription appears to be the key. Our textbook view has been that transcription factors and machinery “scan” the genome for open available promoters to bind. Numerous lines of evidence now indicate that transcription occurs at specific sites within the nuclear volume called transcription factories [45, 55‒63], where several polymerase complexes are recruited within a metastable structure. Upon activation, like-regulated genes are then recruited to the surface of these factories for transcription. For example, tumor necrosis factor α (TNFα) stimulation of human umbilical vein endothelial cells induces the activation of several genes regulated by the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) [64]. One of these genes, SAMD4A (226,185 bp in size) initiates transcription and takes ∼70 min to transcribe. Papantonis and Cook identified that after induction, the promoter of the TNFAIP2 gene (15,964 bp in size) is in close proximity to the SAMD4A promoter; genes that are separated by ∼ 50 MB on the linear chromosome. During a single round of SAMD4A transcription, TNFAIP2 completes several rounds of transcription, with the TNFAIP2 promoter making contact with different regions of the SAMD4A gene as it proceeds through is transcriptional cycle. These observations indicate that the transcription factories tether actively transcribing regions of these genes within close proximity and initiation of transcription is enough to drive genes together [60]. These observations indicate that transcription at factories is central for genome organization.

The aforementioned examples demonstrate that genome folding is mediated by long-range chromatin interactions that are functionally linked to gene expression. But does this only occur at a few scattered loci or is the entire genome folded into functional domains smaller than chromosome territories? Chromosome conformation capture [1], a proximity-based ligation assay and its high throughput sequencing variations [2, 65‒67] demonstrate that chromosome territories consist of clusters of locally folded regions called topologically associated domains (TADs) (Table 1). TADs range in size from tens to hundreds of kilobases and are generally comprised of co-regulated genes (Fig. 3). The margins of TADs are defined by boundary elements which prevent the inappropriate regulation, either activation or repression, of genes outside of that domain. Chromatin interactions within each TAD occur at high frequencies with intra-TAD interactions decreasing following the power law [54, 65, 68]. TADs consisting of transcriptionally active/euchromatin are found to group together within the nucleus with transcriptionally silent TADs also physically clustering. The clustering of transcriptionally active/euchromatin TADs away from transcriptionally inactive/heterochromatin TADs leads to the establishment of “A” and “B” compartments, respectively (Table 1) [65, 69, 70]. Examples of inter-TAD interactions are the long-range interaction between the TAD containing the LCR and the globin genes, with the TAD containing either Eraf or Uros, with the intervening TADs excluded from interactions.

Fig. 3.

Circadian rhythms: Linking genome organization with cellular energy, diet, and sleep. During the day and high levels of cellular energy (left side), the CLOCK/BMAL is active and promotes the transcription of the Period(Per1and Per2) and Cryptochrome(Cry1and Cry2) genes. As the day proceeds, Per and Cry proteins accumulate, which function to inhibit CLOCK/BMAL function. Melatonin, either from ingestion or naturally produced by the brain in response to longer light wavelengths, “resets” cells, promoting rest and night-associated gene expression profiles (right side). During the night, PER/CRY proteins are degraded leading to increase CLOCK/BMAL function. These changes lead not only to epigenetic regulation of gene expression but specific reorganization of the genome in response to day/night cycles.

Fig. 3.

Circadian rhythms: Linking genome organization with cellular energy, diet, and sleep. During the day and high levels of cellular energy (left side), the CLOCK/BMAL is active and promotes the transcription of the Period(Per1and Per2) and Cryptochrome(Cry1and Cry2) genes. As the day proceeds, Per and Cry proteins accumulate, which function to inhibit CLOCK/BMAL function. Melatonin, either from ingestion or naturally produced by the brain in response to longer light wavelengths, “resets” cells, promoting rest and night-associated gene expression profiles (right side). During the night, PER/CRY proteins are degraded leading to increase CLOCK/BMAL function. These changes lead not only to epigenetic regulation of gene expression but specific reorganization of the genome in response to day/night cycles.

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The edges of the nucleus are postulated to have a significant role in mediating the organization of the genome. A major constituent of the nuclear periphery is the nuclear lamina, a protein layer under the inner nuclear membrane. Consisting of filamentous A and B type lamin proteins that form a mesh-like network, the lamina is home to numerous proteins that have DNA binding domains that directly tether chromatin. These domains, called lamina-associated domains (LADs) (Table 1), are generally thought to be repressive environments where transcription is downregulated. Mapping techniques have identified >1,300 LADs ranging in size from 0.1 to 10 MB [71] (see [72] for a comprehensive review). The importance of these interactions is seen in diseases called laminopathies, where mutations occur in the lamin A/C gene or genes encoding specific lamina-associated proteins, preventing chromatin interactions. The most striking of these diseases in HGPS, a premature aging disease where patients age ∼8 times faster and die of age-related pathologies, such as heart attack or stroke. Caused by a single point mutation that results in an aberrant A type lamin protein, called progerin, disrupting the lamina structure concomitantly with the loss of heterochromatin and dysregulation of gene expression patterns genome wide. In addition, HGPS cells not only exhibit LADs disruption [73] but also have entire chromosomes mislocalized within the nuclear volume [74, 75]. The severe phenotypes observed in HGPS cells are an extreme but significant example of the impact of proper organization of the genome on gene regulation and the overall impact this can have on cellular and organismal health. Disruption of cellular nutrient sensing with rapamycin causes progerin degradation leading to increased cellular lifespan and the reversal of several cellular phenotypes of premature cellular aging [75, 76]. Intriguingly, this links nutrient sensing and availability with gene expression and organization, implicating the potential application of dietary strategies and nutrient sensing pathways as targets for both premature aging diseases as well as to combat normal aging processes.

The presence or absence of specific nutrients [77‒82] as well as caloric restriction (decreased caloric intake without causing malnutrition) has been linked with increased health and lifespan [78, 79, 83‒86]. One of the major cellular nutrient and energy sensing hubs is the mammalian target of rapamycin complex 1 (mTORC1) [87‒89]. mTORC1 is active when energy levels and nutrients are high (fed state), driving cellular proliferation and protein translation. In times of low nutrients (fasting state), such as decreased levels of essential amino acids (such as methionine and arginine), mTORC1 is repressed, leading to significant decreases in protein translation and increased in autophagy (cellular self-eating) [90‒92]. High levels of NAD+ and AMP, activate Sirtuin 1 (SIRT1) [93‒96] and the adenosine monophosphate kinase (AMPK) [91, 97, 98], respectively, which act upstream to inhibit mTORC1 function. Decreased mTORC1 function and increased function of SIRT1, AMPK, and autophagy are all associated with increased cellular and organismal lifespan. Not only are all of these linked mechanistically but they also all have impacts on gene expression. For example, activation of AMPK leads to increased nuclear translocation and DNA binding of the forkhead box family O 3A (FOXO3a) driving genes associated with stress tolerance and increased cell survival [99‒101]. Metformin, the nutraceutical drug, originally isolated from French lilac and a common treatment for type II diabetes. In NDF, metformin resulted in genome-wide changes in gene expression via FOXO3a and the AP1 family of transcription factors but also chromosome territory repositioning [42]. Parallel to this, rapamycin, a caloric restriction mimetic, results in significant changes in gene expression and chromosome positioning but also the reorganization of specific regions of the genome, including a cluster of cytokine genes on chromosome 4 [43].

Significant research has been dedicated to examining the free radical scavenging ability of phenolic compounds. Defined as molecules containing an aromatic ring with at least one hydroxyl group, phenolics have diverse applications in multiple settings. For example, phenolics can act as protective agents in the food industry and have health-promoting properties attributed to their ability to scavenge reactive oxygen species intra- and extracellularly [102, 103]. Although this has been the major focus, phenolic compounds have other properties. Multiple studies demonstrate a link between phenolic compound consumption or exposure to cells in culture with increased autophagy [104‒107] or apoptosis [103, 108].

To investigate the possible mechanisms by which specific phenolics influence cells, we exposed NDFs to the oat-specific phenolic avenanthramide C (AVNC) as well as to phenolic fractions isolated from Canadian bred haskap berries. Both AVNC and haskap phenolic fractions reduce the levels of intra cellular reactive oxygen species; however, only AVNC activated the nuclear erythroid factor krupple-like factor 2 (NRF2) resulting in chromatin binding and increased transcription of the heme-oxygenase 1 (HMOX1) gene [109‒111]. In addition, AVNC and a subset of phenolic fractions decreased levels of NF-κB phosphorylation and DNA binding. This is further supported by the observations that the different phenolic structures were able to induce SIRT1 deacetylase activity. The activation of SIRT1 was indirect in whole cells, as none of the fractions could activate either purified enzyme or active SIRT1 in cell lysates. Knockdown of SIRT1 via siRNA resulted in a lack of cellular responsiveness revealing SIRT1 as the central mediator of phenolic signaling. The function of AVNC and haskap phenolics is not unique; several phenolic compounds having biological impacts beyond mere free radical scavenging. Resveratrol [112, 113], a stilbene compound found in several foods, most notably the skin and seeds of red grapes, is directly bound by SIRT1 resulting in activation [114]. The activation of SIRT1 is significant and has been associated with decreased NF-κB activity and pro-inflammatory signaling [115, 116] as well as decreased mTORC1 activity [117, 118] and increased autophagy [119, 120]. Also of significant interest is epigallocatechin-3-gallate found in green tea. Epigallocatechin-3-gallate has also been reported to increase autophagy [91], NRF2-mediated suppression of pro-inflammatory genes [121, 122], and promote the turnover of protein accumulation in Alzheimer’s disease [123] and ALS [124] models. There is an extensive body of literature regarding other unique phenolics from foods that are proposed to support health and lifespan of several model organisms, highlighting the importance of these compounds. More investigation is required to directly link the mechanism by which these changes occur and the impact on overall genome organization and to identify how each specific phenolic structure is able to elicit cellular responses.

Although humans can synthesize vitamin D in response to sunlight, dietary supplementation may have significant benefits [125]. Vitamin D is of particular interest for our discussion of nutrigenomics as the vitamin D receptor functions as a transcription factor [126, 127]. Predictions state that once the vitamin D receptor binds its ligand, it enters the nucleus and complexes with the Retinoid-X receptor, binding promotors containing a vitamin D response element. Recent research employed the HiChiP assay in human acute monocytic leukemia cells (THP1) supplemented with an active metabolite of vitamin D (1,25(OH)2D3) to study its impact on genome organization. Warwick and colleagues [128] reported that the binding of 1,25(OH)2D3 to the vitamin D receptor induced functionally significant changes in the 3D genome organization, specifically those changes associated with CCCT binding factor mediated chromatin folding, in particular those mediating enhancer-promoter contacts. Mutations that reduce vitamin D metabolism result in an increase in all-cause mortality, with approximately 5% of human genes predicted to be regulated by vitamin D and its receptor. Knockout of the vitamin D receptor in mice demonstrates significantly accelerated aging and early death [129]. Furthermore, climates such as northern Canada have high rates of multiple sclerosis (MS). Although there is likely a genetic component that contributes to this, the high latitudes and the lack of light in winter maybe be an important environmental factor, and as such dietary supplementation of vitamin D is a potential preventative measure for MS development [130]. Given this, it is of vital importance we understand the impact of vitamin D and its receptor on genome folding and long-range chromatin interactions. This will not only identify key genes but also noncoding elements that are important for vitamin D-mediated genome function in MS disease development.

In recent years, melatonin has been touted as a natural sleep aid. This molecule is evolutionarily conserved from bacteria to humans, and specifically for this discussion can be found in high levels in foods such as gogi berries (Fig. 3). In humans, melatonin is produced and secreted by the pineal gland in the brain in response to red wave lengths of light. This secretion is part of the central clock that tells your body night and rest is approaching. Melatonin signals the cells in other tissues to prepare for rest, functioning to reset the peripheral clock. Intriguingly, cellular “clocks” are daily cyclic changes in gene expression profiles and epigenetic marks [131]. In diurnal mammals, circadian signaling is based on feedback loops. During light hours, CLOCK/BMAL complex upregulates several genes including the period (Per1 and Per2) and cryptochrome (Cry1 and Cry2) genes, while BMAL transcription is repressed by the REV-ERB complex. As the Per/Cry proteins accumulate during the day, they feed back to inhibit the CLOCK/BMAL complex. During dark hours, the CLOCK/BMAL complex is inhibited, Per and Cry gene expression decreases while their protein products are degraded. This slowly results in reactivation of the CLOCK/BMAL complex. Although this is simplified (for a comprehensive review please see [132]), this is an elegant display of dynamic gene expression and regulation. Importantly for this discussion, this is also linked to significant changes in genome organization [133]. Furlan-Magaril and colleagues identified that dynamic changes in 3-dimensional chromatin organization within the nuclei occurred parallel to changes in gene expression related to circadian rhythms [134]. Although the structure and boundaries of individual TADs did not change during a specific cycle, TADs encoding circadian genes moved between the active A compartment and the inactive B compartment.

The importance of circadian rhythms and the cyclic nature of the genes that are expressed cannot be overstated. For example, enamel deposition in developing teeth only occurs at night and is tightly regulated by the circadian clock [135]. Circadian rhythm signaling is also closely associated with cellular energy levels and nutrient sensing. Decreased levels of ATP and increased levels of cAMP lead to the activation of the cellular energy sensing complex AMPK [136] and activation of SIRT1 [137, 138], leading to the inhibition of CLOCK/BMAL. In addition, BMAL expression is also linked to repression of mTORC1 activity [139]. All of these complexes have been linked to cellular longevity and have been linked to lifespan and cancer development [140]. Furthermore, disruption of circadian rhythms in shift workers leads to higher incidents of type 2 diabetes as well as increased cancer rates [141‒146], further implicating environmental conditions, in this case light, diet, and sleep, with our genomes. This example provides interesting links between cellular nutrients, dietary phenolics, and other dietary compounds such as melatonin, with not only changes to gene expression but also to dramatic cyclical shifts in epigenetic patterns and 3D chromatin spatial organization.

Although our DNA sequence is established at conception, environmental conditions, most significant of which is diet, play critical roles in regulating the timing and levels of gene expression. Recent leaps forward in genomic tools, including new assays and technologies, have allowed us to begin untangling the Gordian knot which is dynamic genome structure and function. The mechanisms controlling specific gene expression are highly complex, with the 3-dimensional organization of the genome a fundamental contributing factor. To fully utilize dietary compounds and diet strategies (i.e. ketogenic diets), we must further understand the functional relationship(s) between genome folding and compounds available through the diet (Table 2). Like the theory of plate tectonics, 3-dimensional genome organization, although considerably more rapid, is no less complex or fundamental to global cellular processes and is equally earthshattering.

Table 2.

Summary of the nutrients discussed and their impacts on genome organization

 Summary of the nutrients discussed and their impacts on genome organization
 Summary of the nutrients discussed and their impacts on genome organization

The authors report no conflicts of interest.

We would like to thank the funding agencies that provide resources to our research: the Agricultural Development Fund (Application #: 20190076), Natural Sciences and Engineering Research Council (NSERC) of Canada Discovery Grant Program (Application #: 04930) and MITACs (Application #s: IT19437 and IT30954).

Morgan Fleming, Fina Nelson, and Iain Wallace each contributed equally to the synthesis and editing of the document. Morgan Fleming constructed the tables and illustration for the manuscript. Christopher Eskiw contributed content and assisted with the writing as well as editing of the document.

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