# Exploring the role of food-source microRNAs as potential nutritional bioactives in humans

Christine Leroux, J. Bruce German, David A Mills, Dragan Milenkovic

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Christine Leroux, J. Bruce German, David A Mills, Dragan Milenkovic. Exploring the role of food-source microRNAs as potential nutritional bioactives in humans. npj Science of Food, 2026, 10 (1), pp.50. 10.1038/s41538-025-00699-y. hal-05538174

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https://doi.org/10.1038/s41538-025-00699-y

# Exploring the role of food-source microRNAs as potential nutritional bioactives in humans

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Christine Leroux<fnref n="1" />,², J. Bruce German², David A. Mills² & Dragan Milenkovic³

MicroRNAs (miRNAs), small noncoding RNAs that regulate gene expression, are mediators of intercellular and cross-kingdom communication. They are detected in foods, and studies argue for their uptake by intestinal cells. To investigate the cumulative influence of food-derived miRNAs on human health, we performed a bioinformatic analysis of miRNomes of eight commonly consumed foods: four fruits (apple, banana, grape, orange) and four animal products (beef, chicken, pork, milk). We identified 2 and 4 common miRNAs among the 20 most abundant in fruits and animal foods, respectively. Functional predictions revealed that miRNAs are likely involved in regulating cell adhesion, cellular organization, or metabolism. Several miRNAs were shown, in the literature, when overexpressed, to exert beneficial effects on physiological functions and to contribute to disease prevention. This study suggests that food-derived miRNAs may act as novel dietary bioactives contributing to the health-promoting properties of whole foods, and when these foods are consumed in combinations.

Gene expression differs according to cell type, timing, cellular physiology, pathology status, genetic variability, and nutrition<fnref n="1" />. The study of nutritional factors revealed that variations in macronutrient content (like, for example, a western-type diet) can significantly modulate expression of miRNAs in brain microvascular endothelial cells in the mouse hippocampus, in both C57 mice and LDR-/- female mice². In the mouse hippocampus, plant food bioactives, like epicatechin, can modulate miRNA expression, which has been affected by a high-fat diet³. In human peripheral blood mononuclear cells, grapefruit juice consumption by volunteers affected the expression of six miRNAs that were associated with positive health effects, including a decrease in arterial stiffness, a risk factor for cardiovascular disease⁴. Moreover, it has been reported that miRNA contained within extracellular vesicles, participates in the crosstalk between cells in the same organ, and also participates in the crosstalk between organs²,⁶. Therefore, scientific consensus views miRNAs to be critical mediators of cell-to-cell communication involved in physiological and pathological processes important to health⁶,⁷.

miRNAs are present in animals and plants, therefore in foods consumed by humans⁸. For instance, miRNAs were detected in rice, one of the most important food crops in the world⁹. miRNAs were also detected in sweet oranges, one of the most consumed fruit crops worldwide, representing 75% of citrus production consumed both as fresh fruit and

processed juice¹⁰. Likewise, miRNAs have been detected in commonly consumed animal milks or meats, including chicken, the most important source of meat worldwide¹¹. Milk is one of the body fluids with the highest concentration of miRNAs¹², with up to 1400 miRNAs detected in cow's milk¹³. Moreover, the different fractions of milk, such as milk fat globules, extracellular vesicles, skim, and cells, each contain miRNAs¹⁴. Furthermore, bovine dairy products like butter¹⁵, cheese, or yogurt¹⁶ also contain miRNAs, although their profile can be different than that of miRNAs found in whole milk.

Interestingly, miRNAs present in diets, both of plant and animal origin, were identified in the bloodstream after their consumption by humans, as well as the sera and tissues of various animals, including mouse, rat, calf, horse, and sheep⁵,¹⁷. An abundant miRNA in rice (*miR-168a*) was detected in the sera and tissues of human participants consuming rice⁵. This miRNA has been described to target the low-density lipoprotein receptor adapter protein 1 (*LDLRAP1*) mRNA, inhibiting its expression in the liver. Similarly, after drinking a fruit mix juice, 6 among the 16 studied miRNAs showed a dynamic physiological pattern in the plasma of the consumers¹⁸. Maize miRNAs were detected in the blood and tissues of pigs fed fresh maize¹⁹. In aggregate, these studies suggest that miRNAs in food are transferred to humans during digestion and therefore may influence gene expression in organs. However, several studies have not reproduced these observations.

<footnote n="1">¹INRAE, Université Clermont Auvergne, Vetagro Sup, UMRH, Saint-Genès-Champanelle, France. ²Department of Food Science and Technology, University of California Davis, Davis, CA, USA. ³Plants for Human Health Institute, Department of Food Bioprocessing & Nutrition Sciences, NC State University, Kannapolis, NC, USA. ☒e-mail: dmilenk@ncsu.edu</footnote>
For example, the Zhang and collaborators' study was debated by Dickinson and collaborators²⁰, who did not reproduce the previous results reported. Similarly, transfer of miRNA from milk to tissues was not detected in transgenic mice²¹. The discrepancy between the two competing hypotheses could be due to the specific miRNAs studied, their quantities, or their packaging in extracellular vesicles (EVs), which play an important role in the miRNAs' protection during digestion, as well as in the transport and uptake²²,²³. In line with this assumption, the potential effects of milk EVs containing miRNAs have been shown in vitro and in vivo²⁴, once again highlighting the function of dietary miRNAs. Human miRNAs in milk EVs can survive digestion by the infant and be taken up by intestinal cells²²,²⁵. The functional and nutritive role of milk EV miRNAs was also suggested by the detection in vivo of labeled synthetic miRNAs administered in milk exosomes in mice and pig tissues such as intestinal mucosa, spleen, liver, heart, and brain²⁶.

Despite the need for more research to offer a definitive framework for the transfer of food-source miRNAs, there is evidence that they can influence human gene expression after absorption, migration via plasma, and delivery to cells in various organs. For example, miR-375 in human milk is reported to be associated with protection from atopy in infants²⁷. Bovine milk-derived exosomes that contain miRNAs were suggested to inhibit inflammatory processes in cartilage from osteoarthritis patients²⁸. miR-148a, one of the most abundant milk miRNAs, exhibited an inverse association with infant weight, fat mass, and fat-free mass at 1 month, while miR-30b was positively associated with infant weight, percent body fat, and fat mass at the same age of babies²⁹. Similarly, a negative correlation between miR-159a from Arabidopsis thaliana and breast cancer was reported in humans³⁰. These health effects could be associated with the interaction between plant-food miRNAs and mammalian mRNAs. For example, miR156a, abundant in broccoli, was reported to target the human junctional adhesion molecule A (JAM-A), regulating the epithelial-mesenchymal transition involved in migration abilities in breast cancer³¹. Functional study using human aortic endothelial cells showed that miR156a could be a repressor of monocyte recruitment on inflamed human endothelial cells³². Similarly, rice miR168a was suggested to target the low-density lipoprotein receptor adapter protein 1 (LDLRAP1) mRNA, reducing the LDLRAP1 protein level in the blood and liver, in mice⁵. These studies showed a cross-kingdom action of dietary miRNAs³¹,³², and therefore evidence of the impact of food-source miRNAs on consumers' health. Nevertheless, molecular effects of these food-source miRNAs are usually examined by focusing on only one food and only on a few specific miRNAs, whereas the effects of total dietary intake are poorly documented. The objective of this study was to identify, using bioinformatic analyses, potential cellular processes that could be impacted by the most abundant food-source miRNAs following the consumption of common fruits and animal products. To achieve this objective, we identified the most abundant miRNAs in four fruits: banana, orange, apple, and grape, and the most consumed four animal products: beef, pork, chicken meat, and milk, predicted their potential target genes, and performed functional analyses to draw cellular processes in which these target genes are involved.

# Results

## Most consumed plant and animal foods for miRNA analysis

We selected the foods based on their consumption. Chicken, pork, and beef are the most often consumed meats by humans, along with milk and dairy products. Fruits are an important source of plant food, with apples, oranges, bananas, and grapes being the most popular U.S. fruits. As a result, we concentrated our research on chicken, pig, and beef muscle and milk for animal foods, and apples, bananas, grapes, and oranges for fruit foods.

## Comparison of the most abundant miRNAs in each kingdom

A total of 2693 known miRNAs are referenced in humans (Homo sapiens) miRBase. Among animal-based foods highly consumed by humans, chicken is the most consumed meat and the species with the

most known miRNAs, with 1238 known miRNAs³³. Then, 1045 and 461 known miRNAs were identified in beef³⁴ and pig³⁵ meat, respectively. In Holstein milk, 1038 miRNAs were identified³⁶. Apple, banana, grape, and orange are among the fruits most consumed, and studies have identified miRNAs in apple³⁷, in banana³⁸, grape³⁹, and orange¹⁰. Over 100 mature miRNAs were identified in these fruits, with apple and orange showing the largest number of known miRNAs (322 and 252 known miRNAs, respectively) while the smallest number of miRNAs has been identified in grapes, with 186 known miRNAs. Surprisingly, bananas are not included in miRbase, consequently, we used a list of identified miRNAs in banana from a publication ref. 38 for our study.

## Comparison of the most abundant miRNAs in each kingdom

Given that the 20 most abundant miRNAs present in the most consumed foods represent at least 80% of total miRNA abundance, we hypothesize that this set of miRNAs are most likely to have the greatest influence among food-source miRNAs. Due to the knowledge evolution of miRbase, which is not the same in every species, we compared the list of top 20 miRNAs, keeping only the family name.

First, the comparison of the top 20 miRNAs from the 4 most consumed fruits highlighted two miRNAs (miR162 and miR168) in common between apple³⁷, banana³⁸, grape³⁹, and orange¹⁰. Focusing on miRNAs shared by 3 fruits, we observed five miRNAs (miR156, miR159, miR166, miR171, and miR396) in common between apple, banana, and grape, and one miRNA (miR482) between apple, grape and orange (Fig. 1A). The comparison of top 20 miRNAs from the 4 most consumed animal foods highlighted four (miR-21, -26, -27, and let-7) common between chicken²³, pork²⁵ and beef³⁴ meat, and milk³⁶ (Fig. 1D). We identified 9 miRNAs shared by 3 animal products. Of these, five miRNAs (miR-1, -206, -133, -126, and -10) were common to chicken, beef, and pork, 2 miRNAs (miR-378 and miR-143) in common between beef and pork and milk, and 2 miRNAs (miR-148 and miR-30) in common between milk, chicken, and pork. These two last miRNAs are known to be very highly present in milk³⁶.

## Identification of potential target genes of the most common abundant miRNAs

The next step of our analysis was to identify, by homology of sequences, potential target genes of the two and four miRNAs shared between fruits and animal products, respectively. The interaction network of the common miRNAs in fruits and animals showed large hubs of regulation involving the predicted targets with many genes/mRNAs (Fig. 1B, E, for more detail see Supplementary Fig. 1). The target genes of the common miRNAs were then subjected to pathway analysis. Among the pathways influenced by those miRNAs is the MAPK-signaling pathway, as the most enrichment in both fruits and animal products. Similarly, insulin, interleukin IL-1, and p38 MAPK-signaling pathways were identified in both pathways influenced (Fig. 1C, F).

We further aimed to identify if food miRNAs could be detected in human blood that would be suggestive of their role after absorption from the digestive system during digestion. Of the top 20 miRNAs in animal products, between 13 (in chicken meat) and 17 (in milk) miRNAs were also detected in human blood (Supplementary Fig. 2). As far as fruits are concerned (Supplementary Fig. 2), 11 miRNA sequences detected at least in one fruit are also reported in blood miRNome⁴⁰.

## Functional analysis of the top five miRNAs of the studied food—gene ontology

Following the comparisons of miRNAs present in the most abundant foods, the next step of our investigation was focused on the top five miRNAs of each food, representing between 51% (in milk) to 97% (in banana) of the total counts of miRNAs (Table 1).

To gain insight into the potential biological effects of food-sourced miRNAs, we first identified potential target genes of the five most abundant miRNAs for each food by performing base-pairing analysis with the human reference mRNA to predict influence on biological
<figure><img src="image_4.png" /><figcaption>**Fig. 1 |** Comparison of the top 20 miRNAs from selected fruit and animal foods. A Venn diagram of the top 20 miRNAs from apple (Visser et al. ³⁷), banana (Bi et al. ³⁸), grape (Wang et al. ³⁹), and orange (Liu et al. ¹⁰). B Network of interactions between the two common miRNAs (purple square) and the predicted target miRNAs (green circle). C Histogram showing the pathways of the target genes of the</figcaption></figure>

two common miRNAs. D Venn diagram of the top 20 from beef (Li et al. ³⁴), chicken (Li et al. ³³) and pork (Hou et al. ³⁵ muscle, and milk (Le Guillou et al. ³⁶). E Network of interactions between the four common miRNAs (purple square) and predicted target mRNA (pink circle). F Histogram showing the pathways of the four common miRNAs.

<table><caption>**Table 1 |** Top five most abuyndant miRNAs in selected foods</caption><thead><tr><th>Food</th><th colspan="5">miRNA name</th></tr></thead><tbody><tr><td>Apple</td><td>mir159</td><td>mi396</td><td>mir164</td><td>mir167</td><td>mir166</td></tr><tr><td>Banana</td><td>mir319</td><td>mir159</td><td>mir166</td><td>mir156</td><td>mir162</td></tr><tr><td>Grape</td><td>mir166</td><td>mir167</td><td>mir156</td><td>mir168</td><td>mir535</td></tr><tr><td>Orange</td><td>mir166</td><td>mir164c</td><td>mir479</td><td>mir390a</td><td>mir477a</td></tr><tr><td>Cow milk</td><td>miR-26</td><td>miR-22</td><td>miR-27</td><td>miR-30</td><td>miR-148</td></tr><tr><td>Beef muscle</td><td>miR-1</td><td>miR-133</td><td>miR-206</td><td>miR-378</td><td>miR-3600</td></tr><tr><td>Chicken breast</td><td>let-7f</td><td>miR-133</td><td>miR26</td><td>miR-133</td><td>miR-148</td></tr><tr><td>Porc muscle</td><td>let-7a</td><td>miR-133</td><td>miR-143</td><td>miR-206</td><td>miR-378</td></tr></tbody></table>

processes in humans (H-BP). Using such an approach, we identified between 478 and 493 target genes for each miRNA from fruits and between 482 and 491 target genes for each miRNA from animals (Fig. 2). Comparison of the lists of miRNAs' targets revealed 8 genes in common for fruits (Fig. 2A), whereas 13 genes for animal products (Fig. 2B). We then focused on the H-BP influenced by the 8 and 13 shared targeted genes, respectively in fruits and animal products. The most enriched H-BP was "gene expression" and "metabolic processes" for fruits and animal products, respectively. The second rank was the "cellular processes" for both fruits and animal products (Fig. 2C, D).

To ascertain the potential biological actions of the top five miRNAs, we carried out a functional analysis by performing the gene ontology analysis for H-BPs. Orange is the fruit with the greatest potential influence, with 427 H-BP, followed by the other fruits (around 320 H-BP). Among the studied animal products, chicken (422 H-BP) has the greatest influence (Fig. 3). The comparison analysis of the H-BP by kingdom identified 23 and 14 in common in fruits and animal products, respectively (Fig. 3A, B). Among the H-BP identified are those involved in the regulation of cell adhesion, or the regulation of cellular component organization.

## Pathway analysis of the top five miRNAs of the studied food

The subsequent phase of our study was the identification of the cellular pathways in which target genes of the top five miRNAs are involved. The pathways predicted to be influenced by the top five miRNAs of each food were almost double between fruit miRNAs (99 pathways) and animal products (51 pathways). Among the pathways identified are those involved in cell signaling and metabolism. When compared, 11 pathways are in common for miRNAs from fruits and animal products, with 88 pathways specific to miRNAs of fruits and 40 for animal foods. Then we grouped the pathways according to their cellular functions, identifying those involved in cell signaling, cell-cell interactions, metabolism, cancer, neurological function, and inflammation (Fig. 4A, B). Among these functions, pathways related to cancer and neurological function were identified with miRNAs from fruits but not from animal foods. Moreover, the number of pathways related to cell signaling was higher with miRNAs from fruits, while the number of pathways related to cell-cell interactions was higher with miRNAs from animal products. Among the cell signaling pathways are calcium signaling, MAPK signaling, Notch signaling, and the Nrf2 signaling pathway. Regarding the cell-cell interactions pathways, we observed actin cytoskeleton and cell adhesion molecules pathways with miRNAs from animal products and ECM-receptor interactions with miRNAs from fruits. Moreover, among metabolism-related pathways are cholesterol metabolism, arachidonic acid metabolism, but also insulin resistance, insulin secretion, and type 2 diabetes.

## Potential link between food miRNAs and diseases in humans

To increase the overview of the predicted influence of the top five miRNAs in each food, the next step of our study was to identify potential diseases associated with target genes of miRNAs using a toxicogenomic database. We searched potential association between diseases to in one hand the target genes of top five miRNAs which were shared by the four fruits and in another hand, those shared by the four animal products (Fig. 5 and Supplementary Fig. 3). Among the identified diseases are vascular diseases, liver
<figure><img src="image_5.png" /><figcaption>**Fig. 2 |** Comparison of the target genes of the top five miRNAs from consumed foods. Venn diagram of the predicted targets of top five miRNAs from A four fruits: apple (Visser et al. ³⁷), banana (Bi et al. ³⁸), grape (Wang et al. ³⁹), and orange (Liu et al. ¹⁰) and B four animal products: beef (Li et al. ³⁴), bovine milk (Le Guillou et al. ³⁶), pig muscle (Hou et al., 2015³⁵), chicken breast muscle (Li et al. ³³).</figcaption></figure>

<figure><img src="image_6.png" /></figure>

The targets were predicted by base pairing search using NCBI blast analysis. The names of the common genes are on the right of each Venn diagram. C, D Histogram showing the biological processes influenced by the common targets of the top five miRNAs. C using the 13 common target genes with fruit and D using the 8 common target genes with animals.

<figure><img src="image_7.png" /><figcaption>**Fig. 3 |** Comparison of all GO biological processes influenced by the top five miRNAs from consumed foods. Venn diagram of the biological processes influenced by the top five miRNAs from A four fruits: apple (Visser et al. ³⁷), banana (Bi et al. ³⁸), grape (Wang et al. ³⁹), and orange (Liu et al. ¹⁰) and B four animal products:</figcaption></figure>

<figure><img src="image_8.png" /></figure>

beef (Li et al. ³⁴), bovine milk (Le Guillou et al. ³⁶), pig muscle (Hou et al., 2015³⁵), chicken breast muscle (Li et al. ³³). The biological processes are indicated in the box under each diagram. The biological process gene ontologies were obtained using Gentrail.

diseases, hearth diseases or digestive system diseases identified in common between fruits, while diseases like coronary disease or cardiovascular abnormalities were identified for three fruits, or atherosclerosis, hyperlipidemia or aortic aneurysm for two of the four fruits. Regarding animal products, we identified cardiomyopathies, vascular diseases, brain diseases,

or heart valve diseases common for the miRNAs, or heart failure, thrombosis, or gastro-enteritis for three animal foods, as well as ventricular dysfunction, cerebral arterial diseases, or hepatic insufficiency for two of the animal foods. Among these diseases, some were common for miRNAs from fruits and animals, including heart disease, cardiovascular disease, metabolic
<figure><img src="image_9.png" /><figcaption>Fig. 4 | Pathways influenced by the top five miRNAs of four fruits and four animal-source foods. A Pathways predicted to be influenced by the top five miRNAs from each fruit and B from each animal product.</figcaption></figure>

<figure><img src="image_10.png" /><figcaption>Fig. 5 | Circos representation of the potential diseases associated identified using the target genes of the top five miRNAs. A Potential diseases identified using the top five miRNAs of the four fruits and B potential diseases identified using the top five miRNAs of the four animal-source foods.</figcaption></figure>
<figure><img src="image_11.png" /><figcaption>**Fig. 6** | Analysis of the common genes predicted to be influenced by the top five miRNAs from fruits and animal products. A Venn diagram of fruits (green) and animal products (pink) targets. B List of the common target genes. C Radar representation of the pathways involving the common target genes.</figcaption></figure>

disease, and liver disease, which were pointed out as being influenced by the four fruits and the four animal products.

## Common targets of fruit and animal food miRNAs

To complete our study and estimate the miRNA predicted action of a diet containing fruit and animal products, we examined all of the targets of the top five miRNAs of the fruits and animal products, by comparing the total list of targets of fruits with the total list of targets of animal products (Fig. 6). The 119 common target genes were predicted to influence different pathways of which the main ones being involved in focal adhesion, insulin signaling, metabolic pathways, and axon guidance, and regulation of microtubule cytoskeleton.

## Discussion

Human diets are complex and multicomponent; thus, it is necessary to look at the diet in its entirety to appreciate how health responds to dietary intake. Human diets have changed during evolution throughout history, and more specifically, these last few decades of food processing. Diets are usually composed of animal and vegetable source foods and sometimes enriched with seeds. Nutrition is one of the factors influencing human health. Fruit is universally considered healthy, thus its consumption is widely recommended⁴¹. Consumption of meat, and more specifically red meat, is more controversial, however, when included as part of a healthy and varied diet, red meat can be viewed as a rich source of essential nutrients and high biological value protein¹². Similarly, milk, previously attacked for its saturated fatty acid content, often associated with detrimental properties for human health, is now known to provide a wide range of polyunsaturated fatty acids (PUFA). Milk monounsaturated fatty acids and saturated fatty acids are associated with diverse beneficial health effects⁴³, as well as delivering milk fat globule membranes and complex lipids associated with even more distinct effects on health⁴⁴. Besides the essential nutrients, numerous fields of science interrogating diet and health are now beginning to consider all food components, including lesser-known ones such as miRNAs. This approach of identifying, quantifying, and annotating all food components, is termed foodomics, and in the present study, we focused on miRNAs in foods, choosing specifically the most consumed foods. Global meat consumption is expected to increase by more than 70% in 2050, and chicken, pig, and beef are the most consumed meats (FAO, https://www.fao.org/4/i2373e/i2373e.pdf). Milk and dairy products also constitute an important

source of foods of animal origin. In the United States, cheese now accounts for most dairy products consumed (USDA, https://www.ers.usda.gov/data-products/chart-gallery/gallery/chart-detail/?chartId=58322). Among vegetables, fruits constitute an increasing source of recommended foods. Among them, apples, oranges, bananas, and grapes were the top U.S. fruits consumed in 2021, and they were among the top 6 most popular fruits in the world in 2018 (USDA, https://www.ers.usda.gov/data-products/chart-gallery/gallery/chart-detail/?chartId=58322). Therefore, we focused our analysis on chicken, pig, and beef muscle and milk for animal products and on apple, banana, grape, and orange for fruit foods. We also note that muscle miRNomes were used to represent cooked meat due to the lack of data for all studied species. However, miRNAs were shown to survive the heat-based preparation methods of meat⁴⁵.

The low level of representation of miRNAs among total RNAs (~0.01%), is countered by their small size and a large number of copies of the most abundant miRNAs, giving them a potential influence on the biological processes in which they are involved⁴⁶,⁴⁷. Elsewhere, evidence suggests food-derived miRNAs can transit from the digestive tract into the bloodstream to act on host health. In the present study, we identified miRNA sequences shared between fruit and animal products miRNomes and human (Supplementary Fig. 2), supporting the potential effects of those miRNAs on the host consumers. It is worth noting that human milk is the richest body fluid in miRNAs¹² and shares 15 of its top 20 most abundant miRNAs with the human blood miRNome. This interesting observation could be related to the well-known role of milk for infant development⁴⁸.

The quantity of food-derived miRNAs provided both by fruits and animal products may have a cumulative effect, in particular if they are provided by a mixture of foods representative of the human diet, and could exert a positive effect on human health. For instance, the consumption of animal products provided 4 common miRNAs (*miR-21*, -26, -27, and *let-7*) of the top 20 most abundant miRNAs (Fig. 1). Increased *miR-26* expression level was reported to inhibit the proliferation of myeloma cells⁴⁹ and that of *miR-21* was described to have protective effect against ischemia-induced cardiac myocyte damage⁵⁰, protects neurons from ischemic death⁵¹, or has anti-inflammatory effect by decreasing activation of NF-κB⁵². Similarly, several studies have revealed the potential beneficial effect of an increase in the expression of *miR-21* and to is related to human cardiomyopathy⁵³. As for *mir-27*, it has been shown, in rats, that *miR-27* expression reduces hypoxia-induced apoptosis in neuronal cells by modulating apoptotic
<figure><img src="image_12.png" /><figcaption>**Fig. 7** | Workflow of analyses. Each relevant figure number is reported at each step of corresponding analyses.</figcaption></figure>

pathways, offering neuroprotection⁵⁴. An increase in *miR-27* can increase vascularization, decrease fibrosis, and increase ejection fraction, improve tissue re-vascularization and perfusion, decrease macrophage recruitment, therefore play a role in the treatment of cardiovascular disease⁵⁵, or regulate hepatic lipid metabolism and potentially alleviate non-alcoholic fatty liver disease in mice⁵⁶. The final shared animal product miRNA belongs to the *let-7* family, which is known to be involved in many biological processes and diseases⁵⁷. Moreover, overexpression of *let-7* has been suggested to have the capacity to inhibit cancer cell proliferation⁵⁸ or be a therapeutic target for cardiovascular diseases⁵⁹. Our bioinformatic analysis of target genes predicted that they are associated with these diseases, including cardiovascular diseases and metabolic disorders. Together, we hypothesize that these foods are sources of miRNAs and, once absorbed, could exert a positive impact on human health and prevent or diminish the development of diseases. This would suggest that miRNAs could be considered as important bioactive molecules like vitamins, polyphenols, or fibers involved in the observed health effects of foods.

In addition, miRNAs provided by several foods could also have an accumulative effect. This is the case of the two common miRNAs shared between the four fruits studied. Indeed, miR162 and miR168 could regulate the expression of genes involved in miRNA biosynthesis. Indeed, miR162 was shown to target DICER-LIKE1 (DCL1), inhibiting its cleavage in low night temperature and influencing abscisic acid (ABA) signaling pathway in transgenic tomatoes⁶⁰. Mir168 is a key miRNA that targets Argonaute1 (AGO1), a major component of the RNA-induced silencing complex, in rice⁶¹. We noted that these two miRNAs are associated with DICER and AGO, which are involved in miRNA biosynthesis.

Besides common miRNAs, the cumulative effect could be increased by
targeting the same mRNAs. Thus, we have identified 8 and 13 common

targets of the top five miRNA fruits and animal products, respectively. The three most enriched H-BP in which these targets are involved are metabolic processes, gene expression, and cellular processes (Fig. 2). In addition, we also identified 119 common target genes between fruits and animal products showing a predicted involvement in metabolic pathways, insulin signaling, focal adhesion, axon guidance, and regulation of microtubule cytoskeleton (Fig. 6).

The common influence of fruit and animal miRNAs on pathways was narrower when comparing the pathways influenced by the top five miRNAs. Indeed, among the 11 common pathways predicted to be influenced by the top five miRNAs, four are classified in cell signaling pathways (Fig. 4). In addition to cell signaling, metabolism pathways were also enriched with fruit and animal miRNAs. Analysis of fruit miRNAs also revealed pathways related to neurofunction-related and cell-cell interaction pathways, which were not enriched with animal products. Conversely, toxicogenomics analysis showed that the top five miRNAs of animal products could have a stronger influence (Fig. 5 and Supplementary Fig. 3). However, it is important to note that the impact on health, either beneficial or adverse, could not be deduced from this predictive function analysis and therefore needs to be investigated.

This study presents several limitations. These analyses were based on the data described and present in public databases. To date, there are few in vivo experimental validations of miRNA functions. As described above, while we identified pathways and functions potentially modulated by miRNAs supplied by fruit and animal products, we cannot determine how they influence health, nor predict which effects are beneficial or not to consumers. Therefore, in vitro and in vivo studies are needed to validate the hypothesis raised
from the bioinformatic analyses of this study. In addition, the
mechanisms of action of miRNAs are complex, as one miRNA
could target several mRNAs and one mRNA could be targeted by
several miRNAs. In this first approach, we set out to mimic the diets
of developed countries but were unable to take into account all the
foods consumed. A broader study, taking into account all foods,
needs to be carried out, as well as similar studies of nutrition in
developing countries. The validation of the health effects of the
miRNAs present in foods could be achieved by overexpressing a
specific miRNA in foods and testing the impact on health in pre-
clinical models of diseases.

Taken together, the functional and health influence of ingested miRNAs on humans consuming them has already emerged as a new signaling system affecting the physiology of consumers through modulation of host gene expression profiles. The originality of this study is to anticipate investigations to establish the effects of major miRNAs contributed by foods ingested during a complete meal on the health of consumers and thus consider the possibility of modulating their quantity by selected foods.

Methods

Identification of miRNAs in the most consumed fruits and animal products

The most consumed animal-source foods were selected from the FAO data (https://www.fao.org/4/i2373e/i2373e.pdf), and the most consumed fruits were identified from the Economic Research Service of the U.S. Department of Agriculture (USDA; https://www.ers.usda.gov/data-products chart-gallery gallery /chart -detail/?chartId=58322) data. These databases, as well as the availability of miRNomes of the foods identified, served as the final criteria for identifying four fruits and four animal products for the study. The miRNome of the eight food items was searched in the literature (https://pubmed.ncbi.nlm.nih.gov). miRBase_v 22.1⁶² was used to identify the number of known miRNAs in each product.

Identification of target genes of miRNAs

The workflow of this study is described in Fig. 7. To identify potential
target genes in humans of plant or animal miRNAs, blastn was per-
formed using the NIH's Basic Local Alignment Search Tool (BLAST)
(https://blast.ncbi.nlm.nih.gov/Blast.cgi). We used this strategy to
homogenize the analyses between plants and animals. miRNA sequences
were obtained from identified published papers. The search for homo-
logous sequences was performed against the “reference RNA sequences
(refseq_rna) database”. The top 100 most significant homolog sequences
were selected, and coding genes were considered as target genes of
miRNAs.

Network building

The interaction networks between miRNAs and potential target genes were constructed with Cytoscape software, version 3.7.2. (https://cytoscape.org). The visualization of elements that are in common between investigated data sets was performed using Venny version 2.1 (https://bioinfogp.cnb.csic.es/tools/venny).

Functional analyses: gene ontology and pathway analyses

Gene ontology enrichment analysis was conducted using the bioin-
formatic tool ShinyGO, version 0.741 (http://bioinformatics.sdstate.
edu/go) and applying the following settings: *p*-value cut-off = 0.05; # of
top pathways to show = 50. Pathway enrichment analyses were con-
ducted using GeneTrail 3, version 3.2 (https://genetrail.bioinf.uni-sb.
de) against Kyoto Encyclopedia of Genes and Genomes (KEGG) and
WikiPathways databases and applying the following settings: over-
representation analysis; null hypothesis (for *p*-value computation)—
two-sided; method to adjust *p*-values: Benjamini–Hochberg; sig-
nificance level: 0.05.

Balloon plots of the pathways and the circos plot for associated diseases were made using the SRplot tool (http://www.bioinformatics.com.cn/en)⁶³. Histograms were made using standard Excel tools.

Data availability

All data are available upon request.

Received: 31 July 2025; Accepted: 27 December 2025;

Published online: 10 January 2026

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Acknowledgements

This work was funded by the French National Research Institute for Agriculture, Food, and the Environment (INRAE), University of California Davis (UCD), and North Carolina State University (NCSU). D.M. was
supported by the United States Department of Agriculture, National Institute of Food and Agriculture (USDA-NIFA), Hatch project 7010153.

**Author contributions**

Conceptualization, writing original draft, review and editing: D.M. and C.L.
Supervision: D.M. and C.L. Writing and reviewing: B.G. and D.A.M. Final
validation before submission: C.L., B.G., D.A.M., and D.M.

**Competing interests**

The authors declare no competing interests.

**Additional information**

**Supplementary information** The online version contains supplementary material available at https://doi.org/10.1038/s41538-025-00699-y.

**Correspondence** and requests for materials should be addressed to Dragan Milenkovic.

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