DNA

In animals and humans, nutrients influence signaling cascades, transcriptional programs, chromatin dynamics, and mitochondrial function, collectively shaping traits related to growth, immunity, reproduction, and stress resilience. This review synthesizes evidence supporting nutrient-mediated regulation of DNA methylation, histone modifications, non-coding RNAs, and mitochondrial biogenesis, and emphasizes their integration within metabolic and developmental pathways. Recent advances in epigenome-wide association studies (EWAS), single-cell multi-omics, and systems biology approaches have revealed how diet composition and timing can reprogram gene networks, sometimes across generations. Particular attention is given to central metabolic regulators (e.g., PPARs, mTOR) and to interactions among methyl donors, fatty acids, vitamins, and trace elements that maintain genomic stability and metabolic homeostasis. Nutrigenetic evidence further shows how genetic polymorphisms (SNPs) in loci such as IGF-1, MSTN, PPARs, and FASN alter nutrient responsiveness and influence traits like feed efficiency, body composition, and egg quality, information that can be exploited via marker-assisted or genomic selection. Mitochondrial DNA integrity and oxidative capacity are key determinants of feed conversion and energy efficiency, while dietary antioxidants and mitochondria-targeted nutrients help preserve bioenergetic function. The gut microbiome acts as a co-regulator of host gene expression through metabolite-mediated epigenetic effects, linking diet, microbial metabolites (e.g., SCFAs), and host genomic responses via the gut–liver axis. Emerging tools such as whole-genome and transcriptome sequencing, EWAS, integrated multi-omics, and CRISPR-based functional studies are transforming the field and enabling DNA-informed precision nutrition. Integrating genetic, epigenetic, and molecular data will enable genotype-specific feeding strategies, maternal and early-life programming, and predictive models that enhance productivity, health, and sustainability in poultry production. Translating these molecular insights into practice offers pathways to enhance animal welfare, reduce environmental impact, and shift nutrition from empirical feeding toward mechanistically informed precision approaches.

The cannabinoid receptor type 2 (CB₂) is increasingly recognized as a crucial regulator of neuroimmune balance in the brain. In addition to its well-established role in immunity, the CB₂ receptor has been identified in specific populations of neurons and glial cells throughout various brain regions, and its expression is dynamically increased during inflammatory and neuropathological conditions, positioning it as a potential non-psychoactive target for modifying neurological diseases. The expression of the CB₂ gene (CNR2) is finely tuned by epigenetic processes, including promoter CpG methylation, histone modifications, and non-coding RNAs, which regulate receptor availability and signaling preferences in response to stress, inflammation, and environmental factors. CB₂ signaling interacts with TRP channels (such as TRPV1), nuclear receptors (PPARγ), and orphan G Protein-Coupled Receptors (GPCRs, including GPR55 and GPR18) within the endocannabinoidome (eCBome), influencing microglial characteristics, cytokine production, and synaptic activity. We review how these interconnected mechanisms affect neurodegenerative and neuropsychiatric disorders, underscore the species- and cell-type-specificities that pose challenges for translation, and explore emerging strategies, including selective agonists, positive allosteric modulators, and biased ligands, that leverage the signaling adaptability of the CB₂ receptor while reducing central effects mediated by the CB₁ receptor. This focus on the neuro-centric perspective repositions the CB₂ receptor as an epigenetically informed, context-dependent hub within the eCBome, making it a promising candidate for precision therapies in conditions featuring neuroinflammation.

Background/Objectives: Goat and sheep farming is an important agro-economic resource in Benin. However, their milk is both underutilized and insufficiently characterized, which limits the development of innovative dairy products and raises concerns about its safety. Against this backdrop, our pioneering study set out to investigate, for the first time in Benin and using an advanced metagenomic approach, the microbial diversity present in goat and sheep raw milk. The aim was to lay the groundwork for safer and more efficient dairy valorization. Methods: To achieve this, metagenomic DNA was extracted from 20 pooled milk samples representing both animal species, followed by shotgun sequencing. Results: Analyses revealed seven dominant phyla: Bacillota (17.44–27.23%), Pseudomonadota (12.39–15.55%), Campylobacterota (3.65–5.29%), Actinomycetota (1.47–6.03%), Spirochaetota (1.14–2.02%), Apicomplexa (0.28–0.50%), and Bacteroidota (0.17–0.22%) in the raw milk of both species. However, their proportions differ. Bacillota, which was the most dominant in both types of milk, was significantly more abundant in goat (27.23 ± 5.33) than in sheep milk (17.44 ± 8.44). In sheep milk, Enterobacteriaceae (11.36 ± 5.79) were the most predominant family, followed by Streptococcaceae (5.57 ± 2.29) and Staphylococcaceae (4.51 ± 3.63). Goat milk, on the other hand, presents a different hierarchy. Streptococcaceae (6.65 ± 2.19) and Staphylococcaceae (6.43 ± 2.33) were the most abundant families, surpassing Enterobacteriaceae (5.33 ± 1.66). The genus Escherichia was the most abundant in sheep milk (6.18 ± 5.33). The genera Staphylococcus (4.50 ± 3.63) and Streptococcus (5.05 ± 1.98) were also present. In contrast, in goat milk, the genera Streptococcus (6.54 ± 2.35) and Staphylococcus (6.42 ± 2.32) were the most dominant, while the average abundance of Escherichia was much lower (1.98 ± 1.28). In terms of species, Sheep milk was dominated by Escherichia coli (6.14 ± 5.28) and Staphylococcus aureus (5.17 ± 2.28) while Klebsiella pneumoniae (2.82 ± 1.72), Streptococcus pneumoniae (1.92 ± 1.36), and Campylobacter coli (1.52 ± 1.27) were also found. In addition to a relatively high abundance of Staphylococcus aureus (6.40 ± 2.45), goat milk was characterized by the presence of Corynebacterium praerotentium (5.32 ± 2.28) and Clostridium perfringens (3.39 ± 2.09). Additional pathogens identified included Clostridioides difficile (1.17–2.00%), Clostridium botulinum (0.27–0.43%), Listeria monocytogenes, Mycobacterium tuberculosis, Helicobacter pylori (0.36–0.62%), Salmonella enterica (0.22–0.26%). As for fungi, Ascomycota were predominant, with the presence of Aspergillus fumigatus, Saccharomyces cerevisiae, Trichophyton mentagrophytes, and Candida auris. Moreover, lactic acid bacteria with technological interest such as Oenococcus oeni (0.60–0.97%), Levilactobacillus namurensis (0.25–0.44%), Lactobacillus agrestimuris, and Lacticaseibacillus rhamnosus were also detected. Conclusions: These findings provide essential insights into the technological potential and health risks associated with these milks, which are key to developing safer and more efficient local dairy value chains.