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The Role of Micronutrients in Metabolic and Infectious Diseases

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Biology".

Deadline for manuscript submissions: 20 April 2025 | Viewed by 1716

Special Issue Editor


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Guest Editor
1. Department of Nutrition and Food Science, Faculty of Pharmacy, University of Granada, 18071 Granada, Spain
2. Institute of Nutrition and Food Technology (INYTA) ‘José Mataix’, Biomedical Research Centre, University of Granada, Avenida del Conocimiento s/n, 18071 Granada, Spain
3. Instituto de Investigación Biosanitaria ibs.GRANADA, 18012 Granada, Spain
4. CIBER de Epidemiología y Salud Pública (CIBERESP), 28029 Madrid, Spain
Interests: nutrition; molecular epidemiology; chronic diseases
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Micronutrients, such as vitamins and minerals, play a crucial role in human health and have garnered increasing attention in scientific research. Deficiencies in certain micronutrients, such as vitamin D or zinc, have been linked to a higher risk of metabolic diseases like type 2 diabetes and infectious diseases such as viral infections.

Molecular studies enable the investigation of how these nutrients impact cellular function, immune response, and inflammation. Furthermore, they provide valuable insights for the development of therapeutic strategies based on the modulation of micronutrient levels. Research on cell cultures has demonstrated that micronutrients play an essential role in the prevention and treatment of metabolic and infectious diseases, opening new avenues for improving human health.

Therefore, this monograph focuses on the role of micronutrients in metabolic and infectious diseases, assessed through in vitro and in vivo studies, including cell culture assays, as well as in silico studies via computational approaches.

Dr. Esther Molina-Montes
Guest Editor

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Keywords

  • micronutrients
  • metabolic diseases
  • infectious diseases
  • cell culture

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Published Papers (2 papers)

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18 pages, 4306 KiB  
Article
The Synergic Immunomodulatory Effect of Vitamin D and Chickpea Protein Hydrolysate in THP-1 Cells: An In Vitro Approach
by Ángela Alcalá-Santiago, Rocío Toscano-Sánchez, José Carlos Márquez-López, José Antonio González-Jurado, María-Soledad Fernández-Pachón, Belén García-Villanova, Justo Pedroche and Noelia María Rodríguez-Martín
Int. J. Mol. Sci. 2024, 25(23), 12628; https://doi.org/10.3390/ijms252312628 - 25 Nov 2024
Viewed by 161
Abstract
Vitamin D (VD), a crucial micronutrient, regulates bone health and immune responses. Recent studies suggest that VD may confer protective effects against chronic inflammatory diseases. Additionally, plant-based peptides can show biological activities. Furthermore, the supplementation of protein hydrolysates with VD could potentially enhance [...] Read more.
Vitamin D (VD), a crucial micronutrient, regulates bone health and immune responses. Recent studies suggest that VD may confer protective effects against chronic inflammatory diseases. Additionally, plant-based peptides can show biological activities. Furthermore, the supplementation of protein hydrolysates with VD could potentially enhance the bioactivity of peptides, leading to synergistic effects. In this study, THP-1 cells were exposed to low concentrations of Lipopolysaccharide (LPS) to induce inflammation, followed by treatment with vitamin D at different concentrations (10, 25, or 50 nM) or a chickpea protein hydrolysate (“H30BIO”) supplemented with VD. The cytotoxicity of VD was evaluated using viability assay to confirm its safety. The cytokine secretion of TNF-α, IL-1β, and IL6 was assessed in the cell supernatant, and the gene expression of TNF-α, IL-1β, IL6, IL8, CASP-1, COX2, NRF2, NF-ĸB, NLRP3, CCL2, CCR2, IP10, IL10, and RANTES was quantified by qRT-PCR. Treatment with VD alone significantly decreased the expression of the pro-inflammatory genes TNF-α and IL6, as well as their corresponding cytokine levels in the supernatants. While IL-1β gene expression remained unchanged, a reduction in its cytokine release was observed upon VD treatment. No dose-dependent effects were observed. Interestingly, the combination of VD with H30BIO led to an increase in TNF-α expression and secretion in contrast with the LPS control, coupled with a decrease in IL-1β levels. Additionally, genes such as IP10, NF-κB, CCL2, COX2, NRF2, and CASP-1 exhibited notable modulation, suggesting that the combination treatment primarily downregulates NF-κB-related gene activity. This study demonstrates a synergistic interaction between VD and H30BIO, suggesting that this combination may enhance pathways involving TNF-α, potentially aiding in the resolution and modulation of inflammation through adaptive processes. These findings open new avenues for research into the therapeutic applications of enriched protein hydrolysates with VD to manage low-grade inflammatory-related conditions. Full article
(This article belongs to the Special Issue The Role of Micronutrients in Metabolic and Infectious Diseases)
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Figure 1

Figure 1
<p>Cell viability analysis of THP-1 cells treated with different compounds at 24 and 48 h. The graph shows the 24 h viability of THP-1 cells treated with various concentrations of VD (1–50 nM) (<b>A</b>) and 48 h viability at the same concentrations for VD (<b>B</b>). Data are expressed as the mean (percentage of absorbance compared with that obtained in the control (non-treated cells)) ± SD, and different letters (a,b) were assigned in the multiple comparison test across all groups, indicating significant differences in a <span class="html-italic">p</span> value &lt; 0.05, <span class="html-italic">n</span> ≥ 4. DC corresponds to the dead cells control and LC to the live cells control.</p>
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<p>Pro-inflammatory cytokines and genes in LPS-induced inflammation THP-1 cells treated with VD. The figure shows the mRNA of <span class="html-italic">Tumor Necrotic Factor-α</span> (<span class="html-italic">TNF-α</span>) levels (<b>A</b>), as well as the content of TNF-α in the supernatant of the treated cells described below (<b>B</b>). In (<b>C</b>), the figure shows the expression levels of <span class="html-italic">Interleukin-1β</span> (<span class="html-italic">IL-1β</span>) and the release of the IL-1β in cellular supernatants after the treatments (<b>D</b>). (<b>E</b>,<b>F</b>) show mRNA levels and content in the supernatant of Interleukin 6 (IL6), respectively. Data are expressed as the mean ± SD, and different letters (a–c) indicate statistical differences in the multiple comparison test across all groups using a <span class="html-italic">p</span> value &lt; 0.05, <span class="html-italic">n</span> = 6. Treatments conducted were C: without reactive; C+: Lipopolysaccharide (LPS) (50 ng/mL); T1: LPS (50 ng/mL) + vitamin D (VD) (10 nM); T2: LPS (50 ng/mL) + VD (25 nM); T3: LPS (50 ng/mL) + VD (50 nM).</p>
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<p>Pro-inflammatory cytokines and genes in LPS-induced inflammation THP-1 cells treated with H30BIO, alone and supplemented with vitamin D. The figure shows the mRNA of <span class="html-italic">Tumor Necrotic Factor-α</span> (<span class="html-italic">TNF-α</span>) levels (<b>A</b>), as well as the content of TNF-α in the supernatant of the treated cells described below (<b>B</b>). In (<b>C</b>), the figure shows the expression levels of <span class="html-italic">Interleukin-1β</span> (<span class="html-italic">IL-1β</span>) and the release of the IL-1β in cellular supernatants after the treatments (<b>D</b>). (<b>E</b>,<b>F</b>) show mRNA levels and content in the supernatant of <span class="html-italic">Interleukin-6 (IL-6)</span>, respectively. Data are expressed as the mean ± SD, and different letters (a–c) indicates statistical differences in the multiple comparison test across all groups using a <span class="html-italic">p</span> value &lt; 0.05, <span class="html-italic">n</span> = 6. Treatments conducted were C: without reactive; C++: Lipopolysaccharide (LPS) (100 ng/mL); T4: LPS (100 ng/mL) + H30BIO (250 µg/mL); T5: LPS (100 ng/mL) + vitamin D (10 nM) + H30BIO (250 µg/mL).</p>
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<p>Gene transcription levels of NF-κB pathway in LPS-induced inflammation THP-1 cells treated with vitamin D. The figure shows the relative levels of gene expression of <span class="html-italic">Nuclear Factor Kappa B Subunit 1</span> (<span class="html-italic">NF-κB</span>) (<b>A</b>), <span class="html-italic">Nuclear Factor Erythroid 2-related Factor 2</span> (<span class="html-italic">NRF2</span>) (<b>B</b>), <span class="html-italic">Caspase-1</span> (<span class="html-italic">CASP-1</span>) (<b>C</b>), <span class="html-italic">C-C Motif Chemokine Receptor 2</span> (<span class="html-italic">CCR2</span>) (<b>D</b>), <span class="html-italic">C-C Motif Chemokine Ligand 2</span> (<span class="html-italic">CCL2</span>) (<b>E</b>), <span class="html-italic">Interleukin 8</span> (<span class="html-italic">IL8</span>) (<b>F</b>), <span class="html-italic">Cyclooxygenase-2</span> (<span class="html-italic">COX2</span>) (<b>G</b>), <span class="html-italic">Interleukin 10</span> (<span class="html-italic">IL10</span>) (<b>H</b>), and <span class="html-italic">C-X-C motif chemokine ligand 10</span> (<span class="html-italic">CXCL10</span>, <span class="html-italic">IP10</span>) (<b>I</b>). Data are expressed as the mean ± SD, and different letters (a–c) were assigned in the multiple comparison test across all groups, indicating significant differences at a <span class="html-italic">p</span> value &lt; 0.05; and ‘ns’ indicates non-statistical differences in the multiple comparison test, <span class="html-italic">n</span> = 6. Treatments conducted were C: without reactive; C+: Lipopolysaccharide (LPS) (50 ng/mL); T1: LPS (50 ng/mL) + vitamin D (VD) (10 nM); T2: LPS (50 ng/mL) + VD (25 nM); T3: LPS (50 ng/mL) + VD (50 nM).</p>
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<p>Gene transcription levels of NF-κB pathway in LPS-induced inflammation in THP-1 cells treated with H30BIO alone and supplemented with vitamin D. The figure shows the relative levels of gene expression of <span class="html-italic">Nuclear Factor Kappa B Subunit 1</span> (<span class="html-italic">NF-κB</span>) (<b>A</b>), <span class="html-italic">Nuclear Factor Erythroid 2-related Factor 2</span> (<span class="html-italic">NRF2</span>) (<b>B</b>), <span class="html-italic">Caspase-1</span> (<span class="html-italic">CASP-1</span>) (<b>C</b>), <span class="html-italic">C-C Motif Chemokine Receptor 2</span> (<span class="html-italic">CCR2</span>) (<b>D</b>), <span class="html-italic">C-C Motif Chemokine Ligand 2</span> (<span class="html-italic">CCL2</span>) (<b>E</b>), <span class="html-italic">Interleukin 8</span> (<span class="html-italic">IL8</span>) (<b>F</b>), <span class="html-italic">Cyclooxygenase-2</span> (<span class="html-italic">COX2</span>) (<b>G</b>), <span class="html-italic">Interleukin 10</span> (<span class="html-italic">IL10</span>) (<b>H</b>), and <span class="html-italic">C-X-C motif chemokine ligand 10</span> (<span class="html-italic">CXCL10</span>, <span class="html-italic">IP10</span>) (<b>I</b>). Data are expressed as the mean ± SD, and different letters (a–c) were assigned in the multiple comparison test across all groups, indicating significant differences at a <span class="html-italic">p</span> value &lt; 0.05, <span class="html-italic">n</span> = 6. Treatments conducted were C: without reactive; C++: Lipopolysaccharide (LPS) (100 ng/mL); T4: LPS (100 ng/mL) + H30BIO (250 µg/mL); T5: LPS (100 ng/mL) + VD (10 nM) + H30BIO (250 µg/mL).</p>
Full article ">Figure 6
<p>Heat map of gene expression in LPS-induced inflammation THP-1 cells treated with vitamin D and/or H30BIO. The heat map represents gene expression normalized to the overstimulated control (C+ (<b>A</b>) or C++ (<b>B</b>)), with a color scale ranging from 0% (minimal expression, blue) to 150% (expression 50% higher than the C+ or C++ controls, red), <span class="html-italic">n</span> = 6. More intense red indicates higher levels of relative expression, while more light blue indicates lower levels. Treatments conducted were C: without reactive; C+: Lipopolysaccharide (LPS) (50 ng/mL); T1: LPS (50 ng/mL) + VD (10 nM); T2: LPS (50 ng/mL) + VD (25 nM); T3: LPS (50 ng/mL) + vitamin D (VD) (50 nM); C++: Lipopolysaccharide (LPS) (100 ng/mL); T4: LPS (100 ng/mL) + H30BIO (250 µg/mL); T5: LPS (100 ng/mL) + VD (10 nM) + H30BIO (250 µg/mL).</p>
Full article ">Figure 7
<p>Enrichment analysis using Biocarta (<b>A</b>), Hallmark (<b>B</b>), and KEGG (<b>C</b>) databases. Enrichment adjusted log-transformed <span class="html-italic">p</span>-values and proportions of overlapping genes are displayed alongside corresponding pathway names. Key pathways include cytokine signaling, NF-κB activation, inflammatory response, and apoptosis. The results provide insights into the molecular and cellular processes associated with the analyzed gene set.</p>
Full article ">
29 pages, 4932 KiB  
Article
Molecular Mechanisms Linking Genes and Vitamins of the Complex B Related to One-Carbon Metabolism in Breast Cancer: An In Silico Functional Database Study
by José María Gálvez-Navas, Esther Molina-Montes, Miguel Rodríguez-Barranco, MCarmen Ramírez-Tortosa, Ángel Gil and María-José Sánchez
Int. J. Mol. Sci. 2024, 25(15), 8175; https://doi.org/10.3390/ijms25158175 - 26 Jul 2024
Viewed by 1177
Abstract
Carcinogenesis is closely related to the expression, maintenance, and stability of DNA. These processes are regulated by one-carbon metabolism (1CM), which involves several vitamins of the complex B (folate, B2, B6, and B12), whereas alcohol disrupts the cycle due to the inhibition of [...] Read more.
Carcinogenesis is closely related to the expression, maintenance, and stability of DNA. These processes are regulated by one-carbon metabolism (1CM), which involves several vitamins of the complex B (folate, B2, B6, and B12), whereas alcohol disrupts the cycle due to the inhibition of folate activity. The relationship between nutrients related to 1CM (all aforementioned vitamins and alcohol) in breast cancer has been reviewed. The interplay of genes related to 1CM was also analyzed. Single nucleotide polymorphisms located in those genes were selected by considering the minor allele frequency in the Caucasian population and the linkage disequilibrium. These genes were used to perform several in silico functional analyses (considering corrected p-values < 0.05 as statistically significant) using various tools (FUMA, ShinyGO, and REVIGO) and databases such as the Kyoto Encyclopedia of Genes and Genomes (KEGG) and GeneOntology (GO). The results of this study showed that intake of 1CM-related B-complex vitamins is key to preventing breast cancer development and survival. Also, the genes involved in 1CM are overexpressed in mammary breast tissue and participate in a wide variety of biological phenomena related to cancer. Moreover, these genes are involved in alterations that give rise to several types of neoplasms, including breast cancer. Thus, this study supports the role of one-carbon metabolism B-complex vitamins and genes in breast cancer; the interaction between both should be addressed in future studies. Full article
(This article belongs to the Special Issue The Role of Micronutrients in Metabolic and Infectious Diseases)
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Figure 1

Figure 1
<p>One-carbon metabolism pathway. DHF: dihydrofolate, THF: tetrahydrofolate, IMP: inosine monophosphate, Met: methionine, SAM: S-adenosylmethionine, SAH: S-adenosylhomocysteine, HCY: homocysteine, DMG: dimethylglycine, dATP: deoxyadenosine triphosphate, dGTP: deoxyguanosine triphosphate, dTMP: deoxythymidine monophosphate, dUMP: deoxyuridine monophosphate, Ser: serine.</p>
Full article ">Figure 2
<p>Heat-map of the one-carbon metabolism-related genes average expression pattern in different tissues and cells. The expression profiles are based on GTEx v8 RNA-seq data for 54 tissue and cell types. Scale bar represents gene expression measured in TPM (Transcripts Per Million). Cells in darker red mean higher expression of the gene compared to a darker blue color. This allows for comparison across tissue/cell labels and genes. Source: FUMA.</p>
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<p>Tissue specificity expression of one-carbon metabolism-related genes in different tissues. The upper diagram shows the up-regulation of the 1CM-related genes in different tissues; meanwhile, the second diagram refers to the tissues where the genes involved in 1CM are down-regulated. Finally, the bottom diagram shows the differential expression of the genes (DEG) of the interrogated genes in all the tissues. Input genes were tested against each of the DEG sets using a hypergeometric test. The background genes are those that have an average expression value &gt; 1 in at least one of the tissue labels and exist in the selected background genes (all). Tissues with significant enrichment at Bonferroni corrected <span class="html-italic">p</span>-value ≤ 0.05 are colored in red. Bonferroni correction is performed for each of the up-regulated, down-regulated, and both-sided DEG sets separately. Source: FUMA.</p>
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<p>Functional and enrichment analysis for the one-carbon metabolism-related genes in the cellular and molecular mechanisms from GeneOncology. In the diagram above is represented the association of the one-carbon-related genes and the different mechanisms in which they are involved after FDR correction. Dot size refers to the number of genes involved in the pathway. FDR value is defined through a color scale. Thus, the closer to red, the bigger the association is, and the reverse for blue. Fold enrichment is defined as the percentage of the selected genes involved in one pathway divided by the percentage of the reference genes. It assesses the enrichment magnitude, so a higher value means a stronger enrichment. Source: ShinyGO.</p>
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<p>In silico enrichment analysis in the one-carbon metabolism-related genes on the main genetic and biochemical alterations (MsigDB). Figures were created according to the comparison between the interrogated genes and the reference genome through KEGG and MsigDB. The overlapping genes related to one-carbon metabolism (in yellow), the FDR <span class="html-italic">p</span>-value after the enrichment analysis (in blue), and the proportion of overlapping genes compared to the reference genome in each associated pathway (in red) are shown. Source: FUMA.</p>
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<p>Kaplan–Meier plot of overall survival curves from in silico enrichment analysis according to <span class="html-italic">TCN1</span> expression in breast cancer patients from TCGA Study. Source: GEPIA.</p>
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<p>Kaplan–Meier plot of overall survival curves from in silico enrichment analysis according to <span class="html-italic">TCN1</span> expression in patients diagnosed with invasive breast carcinoma. Source: UALCAN.</p>
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<p>Kaplan–Meier plot of overall survival curves from in silico enrichment analysis according to <span class="html-italic">SLC25A32</span> expression level in patients diagnosed with invasive breast carcinoma. Source: UALCAN.</p>
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<p>Kaplan–Meier plot of overall survival curves from in silico enrichment analysis according to <span class="html-italic">SHMT2</span> expression level in patients diagnosed with invasive breast carcinoma. Source: UALCAN.</p>
Full article ">Figure 10
<p>Workflow of the bibliographic search and data analysis.</p>
Full article ">
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