[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
Next Issue
Volume 24, February-2
Previous Issue
Volume 24, January-2
You seem to have javascript disabled. Please note that many of the page functionalities won't work as expected without javascript enabled.
 
 
ijms-logo

Journal Browser

Journal Browser

Int. J. Mol. Sci., Volume 24, Issue 3 (February-1 2023) – 1250 articles

Cover Story (view full-size image): Cardiovascular disease, the leading cause of death worldwide, is characterized by alterations at the molecular and cellular level, which play a critical role in the development of atherosclerosis, cardiac remodeling, and age-related heart failure. However, the role of epigenetic mechanisms in this context, which have been highly implicated in the loss of homeostasis and the aberrant activation of many cellular pathways, remains elusive. Recently, non-coding RNAs have been gaining significant attention as epigenetic regulators of various pathologies. In recent years, ncRNAs involved in cell-to-cell communication have become a compelling target for the study of various pathologies, therefore rendering the use of epigenetic drugs a promising target for novel therapeutic strategies. View this paper
  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.
Order results
Result details
Section
Select all
Export citation of selected articles as:
12 pages, 342 KiB  
Article
Serum Neurofilament Light Chain and Glial Fibrillary Acidic Protein as Potential Diagnostic Biomarkers in Autism Spectrum Disorders: A Preliminary Study
by Marta Simone, Andrea De Giacomo, Roberto Palumbi, Claudia Palazzo, Giuseppe Lucisano, Francesco Pompamea, Stefania Micella, Mara Pascali, Alessandra Gabellone, Lucia Marzulli, Paola Giordano, Concetta Domenica Gargano, Lucia Margari, Antonio Frigeri and Maddalena Ruggieri
Int. J. Mol. Sci. 2023, 24(3), 3057; https://doi.org/10.3390/ijms24033057 - 3 Feb 2023
Cited by 12 | Viewed by 3850
Abstract
Autism spectrum disorder (ASD) is one of the most common neurodevelopment disorders, characterized by a multifactorial etiology based on the interaction of genetic and environmental factors. Recent evidence supports the neurobiological hypothesis based on neuroinflammation theory. To date, there are no sufficiently validated [...] Read more.
Autism spectrum disorder (ASD) is one of the most common neurodevelopment disorders, characterized by a multifactorial etiology based on the interaction of genetic and environmental factors. Recent evidence supports the neurobiological hypothesis based on neuroinflammation theory. To date, there are no sufficiently validated diagnostic and prognostic biomarkers for ASD. Therefore, we decided to investigate the potential diagnostic role for ASD of two biomarkers well known for other neurological inflammatory conditions: the glial fibrillary acidic protein (GFAP) and the neurofilament (Nfl). Nfl and GFAP serum levels were analyzed using SiMoA technology in a group of ASD patients and in a healthy control group (CTRS), age- and gender-matched. Then we investigated the distribution, frequency, and correlation between serum Nfl and GFAP levels and clinical data among the ASD group. The comparison of Nfl and GFAP serum levels between ASD children and the control group showed a mean value of these two markers significantly higher in the ASD group (sNfL mean value ASD pt 6.86 pg/mL median value ASD pt 5.7 pg/mL; mean value CTRS 3.55 pg/mL; median value CTRS 3.1 pg; GFAP mean value ASD pt 205.7 pg/mL median value ASD pt 155.4 pg/mL; mean value CTRS 77.12 pg/mL; median value CTRS 63.94 pg/mL). Interestingly, we also found a statistically significant positive correlation between GFAP levels and hyperactivity symptoms (p-value <0.001). Further investigations using larger groups are necessary to confirm our data and to verify in more depth the potential correlation between these biomarkers and ASD clinical features, such as the severity of the core symptoms, the presence of associated symptoms, and/or the evaluation of a therapeutic intervention. However, these data not only might shed a light on the neurobiology of ASD, supporting the neuroinflammation and neurodegeneration hypothesis, but they also might support the use of these biomarkers in the early diagnosis of ASD, to longitudinally monitor the disease activity, and even more as future prognostic biomarkers. Full article
(This article belongs to the Special Issue From Molecular Mechanism to Therapy in Autism Spectrum Disorder)
Show Figures

Figure 1

Figure 1
<p>Comparisons of sNfl (<bold>a</bold>) and sGFAP (<bold>b</bold>) values between ASD patients and control group. Mann Whitney test *** <italic>p</italic> value &lt; 0.001.</p>
Full article ">Figure 2
<p>Workflow of the assessment of this study.</p>
Full article ">
19 pages, 13629 KiB  
Article
Phylogeny and Historical Biogeography of the East Asian Clematis Group, Sect. Tubulosae, Inferred from Phylogenomic Data
by Rudan Lyu, Jiamin Xiao, Mingyang Li, Yike Luo, Jian He, Jin Cheng and Lei Xie
Int. J. Mol. Sci. 2023, 24(3), 3056; https://doi.org/10.3390/ijms24033056 - 3 Feb 2023
Cited by 2 | Viewed by 3031
Abstract
The evolutionary history of Clematis section Tubulosae, an East Asian endemic lineage, has not been comprehensively studied. In this study, we reconstruct the phylogeny of this section with a complete sampling using a phylogenomic approach. The genome skimming method was applied to [...] Read more.
The evolutionary history of Clematis section Tubulosae, an East Asian endemic lineage, has not been comprehensively studied. In this study, we reconstruct the phylogeny of this section with a complete sampling using a phylogenomic approach. The genome skimming method was applied to obtain the complete plastome sequence, the nuclear ribosomal DNA (nrDNA), and the nuclear SNPs data for phylogenetic reconstruction. Using a Bayesian molecular clock approach and ancestral range reconstruction, we reconstruct biogeographical history and discuss the biotic and abiotic factors that may have shaped the distribution patterns of the section. Both nuclear datasets better resolved the phylogeny of the sect. Tubulosae than the plastome sequence. Sect. Tubulosae was resolved as a monophyletic group sister to a clade mainly containing species from the sect. Clematis and sect. Aspidanthera. Within sect. Tubulosae, two major clades were resolved by both nuclear datasets. Two continental taxa, C. heracleifolia and C. tubulosa var. ichangensis, formed one clade. One continental taxon, C. tubulosa, and all the other species from Taiwan island, the Korean peninsula, and the Japanese archipelago formed the other clade. Molecular dating results showed that sect. Tubulosae diverged from its sister clade in the Pliocene, and all the current species diversified during the Pleistocene. Our biogeographical reconstruction suggested that sect. Tubulosae evolved and began species diversification, most likely in mainland China, then dispersed to the Korean peninsula, and then expanded its range through the Japanese archipelago to Taiwan island. Island species diversity may arise through allopatric speciation by vicariance events following the range fragmentation triggered by the climatic oscillation and sea level change during the Pleistocene epoch. Our results highlight the importance of climatic oscillation during the Pleistocene to the spatial-temporal diversification patterns of the sect. Tubulosae. Full article
(This article belongs to the Special Issue Plant Phylogenomics and Genetic Diversity)
Show Figures

Figure 1

Figure 1
<p>Distributions of the <span class="html-italic">Clematis</span> sect. <span class="html-italic">Tubulosae</span> (with the exclusion of known hybrid taxa), according to the specimen records.</p>
Full article ">Figure 2
<p>Phylogenies of <span class="html-italic">Clematis</span> sect. <span class="html-italic">Tubulosae</span>, inferred from the complete plastid genome sequences (<b>A</b>), nrDNA (<b>B</b>), and SNPs (Geneious-0.05MS) (<b>C</b>) datasets using the maximum likelihood (ML) method. Phylograms of the ML trees are shown left below, respectively. ML bootstrap values/posterior probability (PP) values of Bayesian Inference are shown at each node. Internal branches that are fully supported by both analyses were marked with *. ML bootstrap values &lt; 50 and PP values &lt; 0.95 are shown as-. Sectional classifications of <span class="html-italic">Clematis</span> samples are listed at the right side of the tree, and samples of sect. <span class="html-italic">Tubulosae</span> are also highlighted with the color purple: continental species; blue: island (including Korean peninsula) species. Section abbreviations are as follows: sect. <span class="html-italic">Fruticella</span> (FRU), sect. <span class="html-italic">Viorna</span> (VIO), sect. <span class="html-italic">Campanella</span> (CAM), sect. <span class="html-italic">Meclatis</span> (MEC), sect. <span class="html-italic">Atragene</span> (ATR), sect. <span class="html-italic">Cheiropsis</span> (CHE), sect. <span class="html-italic">Naraveliopsis</span> (NAO), sect. <span class="html-italic">Clematis</span> (CLE), sect. <span class="html-italic">Flammula</span> (FLA), sect. <span class="html-italic">Viticella</span> (VIT), sect. <span class="html-italic">Tubulosae</span> (TUB), sect. <span class="html-italic">Naravelia</span> (NAR), sect. <span class="html-italic">Angustifolia</span> (ANG), sect. <span class="html-italic">Archiclematis</span> (ARC), sect. <span class="html-italic">Lasiantha</span> (LAS), sect. <span class="html-italic">Aspidanthera</span> (ASP) [<a href="#B40-ijms-24-03056" class="html-bibr">40</a>,<a href="#B41-ijms-24-03056" class="html-bibr">41</a>].</p>
Full article ">Figure 3
<p>BEAST chronogram of <span class="html-italic">Clematis</span> sect. <span class="html-italic">Tubulosae</span> constructed by the SNPs sequences (Geneious-0.05MS, only one sample was kept for each species). The mean divergence times (Mya) and 95% high posterior density (HPD) are shown at the branches. Climatic events, including aridification of Central Asia (pink shade), the establishment of a monsoon system (blue shade), and a global average δ<sup>18</sup>O curve (leaf-hand axis) derived from benthic foraminifera which mirror the major global temperature trends during the 23 Mya (red line) [<a href="#B7-ijms-24-03056" class="html-bibr">7</a>,<a href="#B62-ijms-24-03056" class="html-bibr">62</a>,<a href="#B63-ijms-24-03056" class="html-bibr">63</a>] are shown below the tree. Samples of sect. <span class="html-italic">Tubulosae</span> are highlighted with color, as in <a href="#ijms-24-03056-f002" class="html-fig">Figure 2</a>. Blue triangles are calibration points.</p>
Full article ">Figure 4
<p>Ancestral range reconstructions of <span class="html-italic">Clematis</span> sect. <span class="html-italic">Tubulosae</span> inferred by the SNPs sequences (Geneious-0.05MS) using BioGeoBEARS implemented in RASP. Samples of sect. <span class="html-italic">Tubulosae</span> are highlighted with color, as in <a href="#ijms-24-03056-f002" class="html-fig">Figure 2</a>. Morphological characters and their states were marked at the right side of the tree.</p>
Full article ">Figure 5
<p>Ancestral morphological character reconstruction of <span class="html-italic">Clematis</span> sect. <span class="html-italic">Tubulosae</span> using Mesquite onto the phylogeny inferred by the SNPs sequences. (<b>A</b>) Pollen. (<b>B</b>) Sexuality. (<b>C</b>) Flower number. (<b>D</b>) Pedicel. (<b>E</b>) Calyx. (<b>F</b>) Sepal. (<b>G</b>) Persistent style. (<b>H</b>) Leaflet margin.</p>
Full article ">
16 pages, 3046 KiB  
Article
The Phytochemical α-Mangostin Inhibits Cervical Cancer Cell Proliferation and Tumor Growth by Downregulating E6/E7-HPV Oncogenes and KCNH1 Gene Expression
by Lorenza Díaz, Samantha V. Bernadez-Vallejo, Rafael Vargas-Castro, Euclides Avila, Karla A. Gómez-Ceja, Rocío García-Becerra, Mariana Segovia-Mendoza, Heriberto Prado-Garcia, Galia Lara-Sotelo, Javier Camacho, Fernando Larrea and Janice García-Quiroz
Int. J. Mol. Sci. 2023, 24(3), 3055; https://doi.org/10.3390/ijms24033055 - 3 Feb 2023
Cited by 12 | Viewed by 3672
Abstract
Cervical cancer is the fourth most common cancer among women worldwide. The main factor associated with the onset and progression of this neoplasia is the human papillomavirus (HPV) infection. The HPV-oncogenes E6 and E7 are critical drivers of cellular transformation, promoting the expression [...] Read more.
Cervical cancer is the fourth most common cancer among women worldwide. The main factor associated with the onset and progression of this neoplasia is the human papillomavirus (HPV) infection. The HPV-oncogenes E6 and E7 are critical drivers of cellular transformation, promoting the expression of oncogenes such as KCNH1. The phytochemical α-mangostin (AM) is a potent antineoplastic and antiviral compound. However, its effects on HPV oncogenes and KCNH1 gene expression remain unknown. This study evaluated the effects of AM on cell proliferation, cell cycle distribution and gene expression, including its effects on tumor growth in xenografted mice. AM inhibited cell proliferation in a concentration-dependent manner, being the most sensitive cell lines those with the highest number of HPV16 copies. In addition, AM promoted G1-cell cycle arrest in CaSki cells, while led to cell death in SiHa and HeLa cells. Of interest was the finding of an AM-dependent decreased gene expression of E6, E7 and KCNH1 both in vitro and in vivo, as well as the modulation of cytokine expression, Ki-67, and tumor growth inhibition. On these bases, we suggest that AM represents a good option as an adjuvant for the treatment and prevention of cervical cancer. Full article
(This article belongs to the Special Issue Role of Phytochemicals in Cancer Chemoprevention and Therapeutics)
Show Figures

Figure 1

Figure 1
<p>Effect of AM on cervical cancer cell proliferation. The antiproliferative effects of α-mangostin (AM) were tested in a panel of cervical cancer cells with different HPV viral load. The antiproliferative effect of AM was evaluated using a range of concentration from 1 to 10 µM. The phytochemical significantly inhibited cancer cell proliferation in a concentration-dependent manner. Results are depicted as the mean ± SD of at least three independent experiments. The data from the vehicle-treated cells were normalized to 100%. * <span class="html-italic">p</span> &lt; 0.05 vs. vehicle.</p>
Full article ">Figure 2
<p>Effects of AM on the cell cycle distribution of cervical cancer cells. Cells were treated with α-mangostin (AM) at its respective inhibitory concentration at 50% (IC<sub>50</sub>), and after 48 h, the cell cycle distribution was analyzed by flow cytometry. (<b>a</b>) Representative flow cytometry histograms of SiHa and CaSki cells treated with either vehicle or AM. The G1-cell cycle phase is shown in purple, the S-region in yellow, and the G2/M in green. The SubG1 subpopulation, indicating cell death, is represented by the white color. The pink line shows how well the mathematical model Dean-Jett-Fox fits the histogram (black line). (<b>b</b>) Graphics show the mean percentage of cells ± SD per cell cycle-phase in three replicates of at least three independent experiments. * <span class="html-italic">p</span> &lt; 0.05 vs. vehicle group.</p>
Full article ">Figure 3
<p>AM modulates cytokines and vimentin gene expression in CaSki cells. α-mangostin (AM) significantly differentially regulated tumor necrosis factor α (<span class="html-italic">TNFα</span>), interleukin-6 (<span class="html-italic">IL-6</span>) and vimentin (<span class="html-italic">VIM</span>) gene expression. The results are the mean ± SEM of relative <span class="html-italic">TNFα, IL-6,</span> and <span class="html-italic">VIM</span> mRNA levels after normalizing against the housekeeping gene glyceraldehyde 3-phosphate dehydrogenase (<span class="html-italic">GAPDH</span>) mRNA expression. N ≥ 3 independent experiments. * <span class="html-italic">p</span> &lt; 0.05 vs. vehicle-treated cells.</p>
Full article ">Figure 4
<p>AM administration slows cervical tumor growth. SiHa cervical cancer cells were subcutaneously xenografted (2 × 10<sup>6</sup> cells) into the lower limb of each mouse. Mice were randomly divided into two groups when the tumors reached a palpable mass of ~5 mm in diameter, and received either vehicle (0.1% of DMSO/day, black circles) or α-mangostin (AM, 8 mg/kg of body weight/day, white circles) in the drinking water for four weeks. (<b>a</b>) The tumors were measured every week with a caliper, and the tumor volume was estimated. The results are the mean ± SEM of tumor volume. (<b>b</b>) Representative pictures depict the tumor’s final size at the end of the treatment. In the vehicle and AM-treated groups, 9 and 10 mice were included, respectively. * <span class="html-italic">p</span> &lt; 0.05 vs. vehicle.</p>
Full article ">Figure 5
<p>AM decreases <span class="html-italic">E6/E7</span>-HPV16 oncogenes and <span class="html-italic">KCNH1</span> tumor gene expression. After four weeks of treatment with vehicle (0.1% DMSO, black bars) or α-mangostin (AM, 8 mg/kg of body weight/day, white bars), the mice were euthanized and the tumor tissue was collected and submitted to RT-qPCR experiments. Gene expression level was normalized against the housekeeping gene RPL32. The results are the mean ± SEM of at least nine tumors per treatment group. * <span class="html-italic">p</span> &lt; 0.05 vs. vehicle.</p>
Full article ">Figure 6
<p>Immunohistochemical analysis of Ki-67 in the tumor tissue of vehicle and AM-treated mice. SiHa cervical cancer cells were subcutaneously xenografted into the lower limb of each mouse. Mice were randomly divided into two groups: vehicle-treated and α-mangostin (AM) -treated. After four weeks of treatment, the mice were euthanized and the tumor tissue was collected and fixed in formaldehyde for immunohistochemical staining. The proliferation marker Ki-67 was expressed in a lesser degree and by fewer tumoral cells of mice treated with AM for 4 weeks, as compared to controls. Representative 20× and 40× magnification photographs are shown for each group.</p>
Full article ">
20 pages, 3799 KiB  
Article
A Cross-Species Analysis Reveals Dysthyroidism of the Ovaries as a Common Trait of Premature Ovarian Aging
by Marco Colella, Danila Cuomo, Valeria Nittoli, Angela Amoresano, Alfonsina Porciello, Carla Reale, Luca Roberto, Filomena Russo, Nicola Antonino Russo, Mario De Felice, Massimo Mallardo and Concetta Ambrosino
Int. J. Mol. Sci. 2023, 24(3), 3054; https://doi.org/10.3390/ijms24033054 - 3 Feb 2023
Cited by 2 | Viewed by 2733
Abstract
Although the imbalance of circulating levels of Thyroid Hormones (THs) affects female fertility in vertebrates, its involvement in the promotion of Premature Ovarian Aging (POA) is debated. Therefore, altered synthesis of THs in both thyroid and ovary can be a trait of POA. [...] Read more.
Although the imbalance of circulating levels of Thyroid Hormones (THs) affects female fertility in vertebrates, its involvement in the promotion of Premature Ovarian Aging (POA) is debated. Therefore, altered synthesis of THs in both thyroid and ovary can be a trait of POA. We investigated the relationship between abnormal TH signaling, dysthyroidism, and POA in evolutionary distant vertebrates: from zebrafish to humans. Ovarian T3 signaling/metabolism was evaluated by measuring T3 levels, T3 responsive transcript, and protein levels along with transcripts governing T3 availability (deiodinases) and signaling (TH receptors) in distinct models of POA depending on genetic background and environmental exposures (e.g., diets, pesticides). Expression levels of well-known (Amh, Gdf9, and Inhibins) and novel (miR143/145 and Gas5) biomarkers of POA were assessed. Ovarian dysthyroidism was slightly influenced by genetics since very few differences were found between C57BL/6J and FVB/NJ females. However, diets exacerbated it in a strain-dependent manner. Similar findings were observed in zebrafish and mouse models of POA induced by developmental and long-life exposure to low-dose chlorpyrifos (CPF). Lastly, the T3 decrease in follicular fluids from women affected by diminished ovarian reserve, as well as of the transcripts modulating T3 signaling/availability in the cumulus cells, confirmed ovarian dysthyroidism as a common and evolutionary conserved trait of POA. Full article
(This article belongs to the Special Issue Ovarian Reserve Disorders: Molecular Mechanisms and Regulation)
Show Figures

Figure 1

Figure 1
<p>T3 levels changes in C57BL/6J and FVB/NJ mice fed different diets. (<b>a</b>,<b>b</b>) The dietary effects on circulating T3 (cfT3) levels were determined by ELISA assay (<span class="html-italic">n</span> = 5/group). Significant differences are indicated with * <span class="html-italic">p</span> &lt; 0.005; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001 using Student’s <span class="html-italic">t-</span>test (<b>c</b>–<b>l</b>). The mRNAs implicated in THs metabolism (<span class="html-italic">Dio2</span> and <span class="html-italic">Dio3</span>) and signaling (<span class="html-italic">Thra</span>, <span class="html-italic">Thrb,</span> and <span class="html-italic">Spot14</span>) were detected by RT-qPCR. Data are reported as the ratio between mRNA content in different diets and control groups normalized to β-actin. Data are mean ± s.d. with five animals per group. Significant differences are indicated with * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001 using Student’s <span class="html-italic">t</span>-test. Student’s <span class="html-italic">t-</span>test for different relative to the cfT3 between C57BL6/J and FVB/NJ strain is indicated with # <span class="html-italic">p</span> &lt; 0.05.</p>
Full article ">Figure 2
<p>Developmental and lifelong exposure to CPF in zebrafish ovaries promotes POA. (<b>a</b>) Graph represents the fertilization percentage estimated by counting the number of fertilized eggs obtained from five independent matings involving zebrafish females exposed to CPF vs. females not exposed (Vehicle). (<b>b</b>) Granulosa cell markers (<span class="html-italic">amh</span>) were detected by RT-qPCR. (<b>c</b>–<b>e</b>) OAGS genes (<span class="html-italic">dre-mir-143</span>, <span class="html-italic">dre-mir-145,</span> and <span class="html-italic">gas5</span>) were verified by RT-qPCR. (<b>f</b>,<b>g</b>) Representative Western blot analysis showing the level of Foxo3a/P-Foxo3a protein following CPF treatment (<span class="html-italic">n</span> = 3/group). (<b>h</b>) Telomere length was measured from total genomic ovaries DNA by using a qPCR. Data were obtained normalizing using <span class="html-italic">tubaI</span> for mRNA, β-actin for proteins, and <span class="html-italic">U6</span> for miRNA). Data are mean ± s.d. with five animals per group. Significant differences are indicated with * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, and **** <span class="html-italic">p</span> &lt; 0.0001 using Student’s <span class="html-italic">t</span>-test.</p>
Full article ">Figure 3
<p>Exposure to CPF modulates THs levels and metabolism in zebrafish ovaries. (<b>a</b>) Ovarian fT3 levels (O-fT3) were measured by ELISA assay in adult ovaries from Vehicle and exposed females (<span class="html-italic">n</span> = 5 ovaries/group), as described in M&amp;M section. (<b>b</b>–<b>g</b>) Levels of the mRNAs of T3 responsive genes (<span class="html-italic">igfbp1a</span> and <span class="html-italic">esr1)</span> and enzymes involved in THs metabolism (<span class="html-italic">dio1</span>, <span class="html-italic">dio2, dio3a,</span> and <span class="html-italic">dio3b)</span> in ovaries of zebrafish exposed to CPF. RT-qPCR tests were performed on five biological samples (<span class="html-italic">n</span> = 5 ovaries/group). Data are reported as fold change values calculated as a ratio between average relative gene expression in exposed and control ovaries after normalization on <span class="html-italic">tubaI</span> mRNA. Significant differences are indicated with * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 using Student’s <span class="html-italic">t</span>-test.</p>
Full article ">Figure 4
<p>Developmental and life-long exposure to CPF affects OAGS in mice. (<b>a</b>–<b>f</b>) RT-qPCR analyses of the levels of markers of granulosa cells (<span class="html-italic">Amh, Inha,</span> and <span class="html-italic">Inhbb</span>) and markers of oocytes (<span class="html-italic">Gdf9, Bmp15,</span> and <span class="html-italic">Zp2</span>). (<b>g</b>–<b>j</b>) OAGS genes (<span class="html-italic">miR143</span>, <span class="html-italic">miR145, miR505,</span> and <span class="html-italic">Gas5</span>) were verified by RT-qPCR. RT-qPCR tests were performed on five biological samples (<span class="html-italic">n</span> = 5 ovaries/group). Data are reported as fold change values calculated as a ratio between average relative gene expression in exposed and control ovaries after normalization on <span class="html-italic">β-actin</span> mRNA (<span class="html-italic">U6</span> for miRNA). Significant differences are indicated with * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001 using Student’s <span class="html-italic">t</span>-test.</p>
Full article ">Figure 5
<p>Mice developmentally and long-life exposed to CPF exhibit ovarian TH signaling and metabolism alterations. (<b>a</b>–<b>c</b>) RT-qPCR analysis of the levels of T3 responsive transcripts (<span class="html-italic">Spot14, Cpt1a,</span> and <span class="html-italic">Cyp19a1).</span> (<b>d</b>–<b>f”</b>) Staining for Esr1 on mice ovaries sections (5×, 10×, 20× magnification), showing the alteration of Esr1 level in exposed groups (<span class="html-italic">n</span> = 3 ovaries/group). (<b>d</b>–<b>d”</b>) Staining in CTRL groups. (<b>e</b>–<b>e”</b>) Staining in exposed group to 1 mg/kg/day. (<b>f</b>–<b>f”</b>) Staining in exposed group to 10 mg/Kg/day (<b>g</b>–<b>i</b>) TH inactivation and activation enzymes (<span class="html-italic">Dio1</span> and <span class="html-italic">Dio2)</span> and <span class="html-italic">Thrb</span> receptor expression were analyzed by RT-qPCR (<span class="html-italic">n</span> = 5 ovaries/group). Data are reported as fold change values calculated as a ratio between average relative gene expression in exposed and control ovaries after normalization on β-actin mRNA. Significant differences are indicated with * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 and **** <span class="html-italic">p</span> &lt; 0.0001 using Student’s <span class="html-italic">t</span>-test.</p>
Full article ">Figure 6
<p>TH variation in FF and CCs of women with DOR. (<b>a</b>–<b>c</b>) Hormones levels (fT4, fT3, E2) detected by ELISA assay in FF from DOR-affected and healthy women. (<b>d</b>,<b>e</b>) <span class="html-italic">AMH</span> mRNA and <span class="html-italic">MIR505</span> levels were tested by RT-qPCR. Data are reported as the ratio between mRNA/miRNA content DOR and control groups normalized to <span class="html-italic">GAPDH/U6</span>. (<b>f</b>,<b>g</b>) Expression of the genes (<span class="html-italic">DIO2</span> and <span class="html-italic">CYP19A1</span>) detected by RT-qPCR. (<b>h</b>) Spearman’s rank correlation is indicated in color depth (number ranger from −1 to +1). Data are reported as fold change values calculated as a ratio between average relative gene expression in 5 pz per control group and 7 pz DOR-affected. Significant differences are indicated with * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, and **** <span class="html-italic">p</span> &lt; 0.0001 using Student’s <span class="html-italic">t</span>-test.</p>
Full article ">
14 pages, 3642 KiB  
Article
Long-Term Soil Drought Limits Starch Accumulation by Altering Sucrose Transport and Starch Synthesis in Sweet Potato Tuberous Root
by Minfei Sheng, Houqiang Xia, Huizi Ding, Dongyu Pan, Jinping He, Zongyun Li and Jingran Liu
Int. J. Mol. Sci. 2023, 24(3), 3053; https://doi.org/10.3390/ijms24033053 - 3 Feb 2023
Cited by 9 | Viewed by 2814
Abstract
In this study, the influences of long-term soil drought with three levels [soil-relative water content (SRWC) (75 ± 5)%, as the control; SRWC (55 ± 5)%, mild drought; SRWC (45 ± 5)%, severe drought] were investigated on sucrose-starch metabolism in sweet [...] Read more.
In this study, the influences of long-term soil drought with three levels [soil-relative water content (SRWC) (75 ± 5)%, as the control; SRWC (55 ± 5)%, mild drought; SRWC (45 ± 5)%, severe drought] were investigated on sucrose-starch metabolism in sweet potato tuberous roots (TRs) by pot experiment. Compared to the control, drought stress increased soluble sugar and sucrose content by 4–60% and 9–75%, respectively, but reduced starch accumulation by 30–66% through decreasing the starch accumulate rate in TRs. In the drought-treated TRs, the inhibition of sucrose decomposition was attributed to the reduced activities of acid invertase (AI) and alkaline invertase (AKI) and the IbA-INV3 expression, rather than sucrose synthase (SuSy), consequently leading to the increased sucrose content in TRs. In addition, starch synthesis was inhibited mainly by reducing ADP-glucose pyrophosphorylase (AGPase), granular starch synthase (GBSS) and starch branching enzyme (SBE) activities in TRs under drought stress, and AGPase was the rate-limiting enzyme. Furthermore, soil drought remarkably up-regulated the IbSWEET11, IbSWEET605, and IbSUT4 expressions in Jishu 26 TRs, while it down-regulated or had no significant differences in Xushu 32 and Ningzishu 1 TRs. These results suggested that the sucrose-loading capability in Jishu 26 TRs were stronger than that in Xushu 32 and Ningzishu 1 TRs. Moreover, IbA-INV3, IbAGPS1, IbAGPS2, IbGBSSI and IbSBEII play important roles in different drought-tolerant cultivars under drought stress. Full article
(This article belongs to the Special Issue Response to Environmental Stress in Plants)
Show Figures

Figure 1

Figure 1
<p>Sugar contents in sweet potato TRs under long-term soil drought stress in 2018 and 2019. * means significant at <span class="html-italic">p</span> &lt; 0.05 among the three <span class="html-italic">SRWC</span> levels; ** means significant at <span class="html-italic">p</span> &lt; 0.01 among the three <span class="html-italic">SRWC</span> levels.</p>
Full article ">Figure 2
<p>Changes of starch content (amylose and amylopectin) and starch accumulation in TRs under long-term soil drought stress in 2018 and 2019. * means significant at <span class="html-italic">p</span> &lt; 0.05 among the three <span class="html-italic">SRWC</span> levels; ** means significant at <span class="html-italic">p</span> &lt; 0.01 among the three <span class="html-italic">SRWC</span> levels.</p>
Full article ">Figure 3
<p>Changes of SuSy, AI and AKI activities in sweet potato TRs under long-term soil drought stress in 2018 and 2019. * means significant at <span class="html-italic">p</span> &lt; 0.05 among the three <span class="html-italic">SRWC</span> levels; ** means significant at <span class="html-italic">p</span> &lt; 0.01 among the three <span class="html-italic">SRWC</span> levels.</p>
Full article ">Figure 4
<p>Changes of AGPase, GBSS and SSS activities in sweet potato TRs under long-term soil drought stress in 2018 and 2019. * means significant at <span class="html-italic">p</span> &lt; 0.05 among the three <span class="html-italic">SRWC</span> levels; ** means significant at <span class="html-italic">p</span> &lt; 0.01 among the three <span class="html-italic">SRWC</span> levels.</p>
Full article ">Figure 5
<p>Changes of SBE and DBE activities in sweet potato TRs under long-term soil drought stress in 2018 and 2019. * means significant at <span class="html-italic">p</span> &lt; 0.05 among the three <span class="html-italic">SRWC</span> levels; ** means significant at <span class="html-italic">p</span> &lt; 0.01 among the three <span class="html-italic">SRWC</span> levels.</p>
Full article ">Figure 6
<p>Heat map of the genes’ expression levels in sucrose-starch conversion in TRs. Purple–blue represents increased expression levels, and red represents reduced expression levels. Values followed by different lowercases among the three <span class="html-italic">SRWC</span> levels are markedly different at <span class="html-italic">p</span> &lt; 0.05 levels.</p>
Full article ">Figure 7
<p>Daily weather in Xuzhou during sweet potato growing period in 2018 and 2019.</p>
Full article ">
14 pages, 2279 KiB  
Article
Selection of Novel Reference Genes by RNA-Seq and Their Evaluation for Normalising Real-Time qPCR Expression Data of Anthocyanin-Related Genes in Lettuce and Wild Relatives
by Inés Medina-Lozano, María Soledad Arnedo, Jérôme Grimplet and Aurora Díaz
Int. J. Mol. Sci. 2023, 24(3), 3052; https://doi.org/10.3390/ijms24033052 - 3 Feb 2023
Cited by 4 | Viewed by 3012
Abstract
Lettuce is a popular vegetable source of bioactive compounds, like anthocyanins, powerful antioxidants present in red and semi-red varieties. Selection of reliable reference genes (RGs) for the normalization of real-time quantitative PCR (qPCR) data is crucial to obtain accurate gene expression results. Among [...] Read more.
Lettuce is a popular vegetable source of bioactive compounds, like anthocyanins, powerful antioxidants present in red and semi-red varieties. Selection of reliable reference genes (RGs) for the normalization of real-time quantitative PCR (qPCR) data is crucial to obtain accurate gene expression results. Among the genes with totally unrelated biological functions, six candidate RGs (ADF2, CYB5, iPGAM, SCL13, TRXL3-3, and VHA-H) with low variation in expression according to RNA-seq analyses, were selected for future expression studies of anthocyanin-related genes in three different experiments: leaf colour comparison (green vs. red) in commercial varieties; tissue comparison (leaf vs. stem) in a wild relative; and drought stress experiment in commercial and traditional varieties, and a wild relative. Expression profiles of the candidate RGs were obtained by qPCR and their stability was assessed by four different analytical tools, geNorm, NormFinder, BestKeeper, and Delta Ct method, all integrated in RefFinder. All results considered, we recommend CYB5 to be used as RG for the leaf colour experiment and TRXL3-3 for the tissue and drought stress ones, as they were the most stable genes in each case. RNA-seq is useful to preselect novel RGs although validation by qPCR is still advisable. These results provide helpful information for gene expression studies in Lactuca spp. under the described conditions. Full article
(This article belongs to the Section Molecular Plant Sciences)
Show Figures

Figure 1

Figure 1
<p>Expression levels, Cq (quantification cycle) values assessed by real-time qPCR (quantitative PCR), of six tested candidate RGs across the samples in three experiments: (<b>A</b>) comparison of leaf colour in green and red lettuce commercial varieties; (<b>B</b>) comparison of tissues (leaf and stem) in a wild relative species; and (<b>C</b>) drought stress in a commercial variety, a traditional variety, and a wild relative species. Lower and upper ends of the boxes represent the 25th and 75th percentiles, respectively, and whisker caps indicate the minimum and maximum values. Horizontal bars and black and grey dots depict the median, mean and outliers, respectively.</p>
Full article ">Figure 2
<p>Expression stability of six tested candidate reference genes (RGs) calculated by (<span class="html-fig-inline" id="ijms-24-03052-i001"><img alt="Ijms 24 03052 i001" src="/ijms/ijms-24-03052/article_deploy/html/images/ijms-24-03052-i001.png"/></span>) geNorm (M), (<span class="html-fig-inline" id="ijms-24-03052-i002"><img alt="Ijms 24 03052 i002" src="/ijms/ijms-24-03052/article_deploy/html/images/ijms-24-03052-i002.png"/></span>) NormFinder, (<span class="html-fig-inline" id="ijms-24-03052-i003"><img alt="Ijms 24 03052 i003" src="/ijms/ijms-24-03052/article_deploy/html/images/ijms-24-03052-i003.png"/></span>) BestKeeper, and (<span class="html-fig-inline" id="ijms-24-03052-i004"><img alt="Ijms 24 03052 i004" src="/ijms/ijms-24-03052/article_deploy/html/images/ijms-24-03052-i004.png"/></span>) ΔCt (SV) methods in three experiments: (<b>A</b>) comparison of leaf colour (green and red) in lettuce commercial varieties; (<b>B</b>) comparison of tissues (leaf and stem) in a wild relative species; and (<b>C</b>) under drought stress in a commercial variety, a traditional variety, and a wild relative. The most stable genes are represented on the left and the least stable on the right of the graph.</p>
Full article ">
13 pages, 1132 KiB  
Review
Circulating Microbial Cell-Free DNA in Health and Disease
by Bernadeta Pietrzak, Iwona Kawacka, Agnieszka Olejnik-Schmidt and Marcin Schmidt
Int. J. Mol. Sci. 2023, 24(3), 3051; https://doi.org/10.3390/ijms24033051 - 3 Feb 2023
Cited by 16 | Viewed by 4245
Abstract
Human blood contains low biomass of circulating microbial cell-free DNA (cfmDNA) that predominantly originates from bacteria. Numerous studies have detected circulating cfmDNA in patients with infectious and non-infectious diseases, and in healthy individuals. Remarkable differences were found in the microbial composition of healthy [...] Read more.
Human blood contains low biomass of circulating microbial cell-free DNA (cfmDNA) that predominantly originates from bacteria. Numerous studies have detected circulating cfmDNA in patients with infectious and non-infectious diseases, and in healthy individuals. Remarkable differences were found in the microbial composition of healthy subjects and patients compared to cohorts with various diseases or even patients with diversified prognoses, implying that these alterations may be associated with disease development. Although the function of circulating cfmDNA needs to be elucidated (whether it acts as a bystander of dysbiosis or a key player in disease development), several studies have demonstrated its potential as a non-invasive biomarker that may improve diagnosis and treatment efficacy. The origin of circulating cfmDNA is still the subject of much deliberation, but studies have identified members of various microbiome niches, including the gut, oral cavity, airways, and skin. Further studies investigating the origin and function of circulating cfmDNA are needed. Moreover, low-biomass microbiome studies are prone to contamination, therefore stringent negative experimental control reactions and decontamination frameworks are advised in order to detect genuine circulating cfmDNA. Full article
(This article belongs to the Special Issue Latest Review Papers in Molecular and Cellular Biology 2023)
Show Figures

Figure 1

Figure 1
<p>Microorganisms colonizing various body niches, including gastrointestinal, respiratory, and genitourinary tract, oral cavity, and skin, may translocate into the bloodstream through impaired epithelial barrier, as a consequence of toothbrushing, dental treatment, medical procedures, skin injuries, and body piercing.</p>
Full article ">
27 pages, 1367 KiB  
Review
The Tumorigenic Role of Circular RNA-MicroRNA Axis in Cancer
by Woo Ryung Kim, Eun Gyung Park, Du Hyeong Lee, Yun Ju Lee, Woo Hyeon Bae and Heui-Soo Kim
Int. J. Mol. Sci. 2023, 24(3), 3050; https://doi.org/10.3390/ijms24033050 - 3 Feb 2023
Cited by 22 | Viewed by 3521
Abstract
Circular RNAs (circRNAs) are a class of endogenous RNAs that control gene expression at the transcriptional and post-transcriptional levels. Recent studies have increasingly demonstrated that circRNAs act as novel diagnostic biomarkers and promising therapeutic targets for numerous cancer types by interacting with other [...] Read more.
Circular RNAs (circRNAs) are a class of endogenous RNAs that control gene expression at the transcriptional and post-transcriptional levels. Recent studies have increasingly demonstrated that circRNAs act as novel diagnostic biomarkers and promising therapeutic targets for numerous cancer types by interacting with other non-coding RNAs such as microRNAs (miRNAs). The miRNAs are presented as crucial risk factors and regulatory elements in cancer by regulating the expression of their target genes. Some miRNAs are derived from transposable elements (MDTEs) that can transfer their location to another region of the genome. Genetic interactions between miRNAs and circular RNAs can form complex regulatory networks with various carcinogenic processes that play critical roles in tumorigenesis and cancer progression. This review focuses on the biological regulation of the correlative axis among circular RNAs, miRNAs, and their target genes in various cancer types and suggests the biological importance of MDTEs interacting with oncogenic or tumor-suppressive circRNAs in tumor progression. Full article
(This article belongs to the Special Issue Latest Review Papers in Molecular Genetics and Genomics 2023)
Show Figures

Figure 1

Figure 1
<p>Biosynthetic mechanisms of circular RNAs. Circular RNAs are produced via several induction mechanisms: (<b>A</b>) direct back-splicing, (<b>B</b>) intron-pairing-driven circularization, (<b>C</b>) exon skipping, and (<b>D</b>) debranching-resistant intron lariat. EIcircRNA; Exon-intron circRNA.</p>
Full article ">Figure 2
<p>Regulatory processes that involve circular RNAs at the molecular level. Circular RNAs act as significant regulators by interacting with several components that control the vital biological processes, such as: (<b>A</b>) Regulation of alternative splicing, (<b>B</b>) Regulation of transcription, (<b>C</b>) Protein translation, (<b>D</b>) RBPs sponge/scaffold (<b>E</b>) miRNA sponge. pol 2, RNA polymerase 2; RBP, RNA-binding protein; AGO, argonaute protein.</p>
Full article ">Figure 3
<p>Impact of correlation between oncogenic circular RNA and miRNA in cancer.</p>
Full article ">
16 pages, 606 KiB  
Review
Microsomal Prostaglandin E Synthase-1 and -2: Emerging Targets in Non-Alcoholic Fatty Liver Disease
by Dimitrios Kotsos and Konstantinos Tziomalos
Int. J. Mol. Sci. 2023, 24(3), 3049; https://doi.org/10.3390/ijms24033049 - 3 Feb 2023
Cited by 3 | Viewed by 3486
Abstract
Nonalcoholic fatty liver disease (NAFLD) affects a substantial proportion of the general population and is even more prevalent in obese and diabetic patients. NAFLD, and particularly the more advanced manifestation of the disease, nonalcoholic steatohepatitis (NASH), increases the risk for both liver-related and [...] Read more.
Nonalcoholic fatty liver disease (NAFLD) affects a substantial proportion of the general population and is even more prevalent in obese and diabetic patients. NAFLD, and particularly the more advanced manifestation of the disease, nonalcoholic steatohepatitis (NASH), increases the risk for both liver-related and cardiovascular morbidity. The pathogenesis of NAFLD is complex and multifactorial, with many molecular pathways implicated. Emerging data suggest that microsomal prostaglandin E synthase-1 and -2 might participate in the development and progression of NAFLD. It also appears that targeting these enzymes might represent a novel therapeutic approach for NAFLD. In the present review, we discuss the association between microsomal prostaglandin E synthase-1 and -2 and NAFLD. Full article
Show Figures

Figure 1

Figure 1
<p>Schematic representation of the reaction catalyzed by microsomal prostaglandin E synthase-1 and -2. Their downstream position in the molecular pathway as terminal regulators of the prostaglandin E<sub>2</sub> synthesis renders them ideal pharmacological targets. Figure has been created with BioRender.com (<a href="http://www.biorender.com" target="_blank">www.biorender.com</a>, accessed on 5 January 2023).</p>
Full article ">
15 pages, 4575 KiB  
Article
Aquaporin-4 Expression Switches from White to Gray Matter Regions during Postnatal Development of the Central Nervous System
by Francisco Mayo, Lourdes González-Vinceiro, Laura Hiraldo-González, Claudia Calle-Castillejo, Sara Morales-Alvarez, Reposo Ramírez-Lorca and Miriam Echevarría
Int. J. Mol. Sci. 2023, 24(3), 3048; https://doi.org/10.3390/ijms24033048 - 3 Feb 2023
Cited by 9 | Viewed by 3271
Abstract
Aquaporin-4 (AQP4) is the most abundant water channel in the central nervous system and plays a fundamental role in maintaining water homeostasis there. In adult mice, AQP4 is located mainly in ependymal cells, in the endfeet of perivascular astrocytes, and in the glia [...] Read more.
Aquaporin-4 (AQP4) is the most abundant water channel in the central nervous system and plays a fundamental role in maintaining water homeostasis there. In adult mice, AQP4 is located mainly in ependymal cells, in the endfeet of perivascular astrocytes, and in the glia limitans. Meanwhile, its expression, location, and function throughout postnatal development remain largely unknown. Here, the expression of AQP4 mRNA was studied by in situ hybridization and RT-qPCR, and the localization and amount of protein was studied by immunofluorescence and western blotting, both in the brain and spinal cord. For this, wild-type mice of the C57BL/6 line, aged 1, 3, 7, 11, 20, and 60 days, and 18 months were used. The results showed a change in both the expression and location of AQP4 in postnatal development compared to those during adult life. In the early stages of postnatal development it appears in highly myelinated areas, such as the corpus callosum or cerebellum, and as the animal grows, it disappears from these areas, passing through the cortical regions of the forebrain and concentrating around the blood vessels. These findings suggest an unprecedented possible role for AQP4 in the early cell differentiation process, during the first days of life in the newborn animal, which will lead to myelination. Full article
(This article belongs to the Special Issue Aquaporins in Brain Disease)
Show Figures

Figure 1

Figure 1
<p>The pattern of AQP4 mRNA induction in brain during the first postnatal week differs from the adult transcript distribution. Identification of AQP4 mRNA molecules by in situ hybridization in cerebral sagittal sections from neonatal mice at P1 (<b>A</b>), P3 (<b>B</b>), P7 (<b>C</b>), and juvenile mice at P56 ((<b>D</b>), image obtained from Allen Brain Atlas). High magnification of corpus callosum (comprised between the dashed point lines), surrounding areas of P7 and P56 brains are shown in (<b>C’</b>) and (<b>D’</b>). The arrows indicate AQP4+ stained cells in both (<b>C’</b>,<b>D’</b>). Scale bar = 1 mm (<b>A</b>–<b>D</b>) and 150 µm in the insets (<b>C’</b>,<b>D’</b>).</p>
Full article ">Figure 2
<p>The stability of AQP4 mRNA levels during brain development in the cortex con-trasts with a reduction in gene expression in the corpus callosum. Relative expression changes of AQP4 mRNA measured by RT-qPCR in cortex (<b>A</b>) and CC (<b>B</b>) across different developmental stages. n = 6–7 animals per group. Mean values are represented with the standard error of the mean (SEM). Statistically significant differences between mean values were assessed by ANOVA test with post hoc TUKEY multiple comparison test (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001).</p>
Full article ">Figure 3
<p>Adult brain undergoes an AQP4 protein increase in the cortex but remains at the same protein levels in corpus callosum. Western blot analysis of AQP4 protein amount at different age groups was performed in the cortex (<b>A</b>) and corpus callosum (<b>B</b>). Data shown are representative for 3 independent experiments. n = 3–5 animals per group. Mean values are represented with the standard error of the mean (SEM). Statistically significant differences between mean values were assessed by ANOVA test with post hoc TUKEY multiple comparison test (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01).</p>
Full article ">Figure 4
<p>AQP4 immunofluorescence signal shifts from the corpus callosum at early developmental stages to the cortical vasculature in the adult brain. (<b>A</b>) Fluorescence Immunohistochemistry showing spatiotemporal AQP4 protein distribution (red) in corpus callosum and cortex from coronal sections at P1, P3, P7, P11, P20, P60 and 18 M. Scale bar = 150 µm. Detailed images of the cortical vasculature were added at P11, P20, P60, and 18M. Inset scale bar = 30 µm. (<b>B</b>) Quantification of AQP4 signal was measured by optical density and the intensity levels obtained were compared between different developmental groups in both cortex and corpus callosum regions. Data represent the mean ± SEM from n = 4 analyzed for each age. Statistically significative differences between mean values were assessed by ANOVA test with post hoc TUKEY multiple comparison test. (*** <span class="html-italic">p</span> &lt; 0.001). Illustration of the coronal brain section was designed with BioRender (Accessed on 22 November 2022, <a href="https://biorender.com/" target="_blank">https://biorender.com/</a>).</p>
Full article ">Figure 5
<p>AQP4 protein presence is increased in highly myelinated areas of the cerebellum and spinal cord during postnatal maturation. Fluorescence Immunohistochemistry showing spatiotemporal AQP4 protein distribution (red) in cerebellum (<b>A</b>) and lumbar spinal cord (<b>B</b>) sections at P1, P3, P7, P11, P20, P60 and 18M. Scale bar = 150 µm. Illustrations of the cerebellum and spinal cord sections were designed with BioRender (Accessed on 22 November 2022, <a href="https://biorender.com/" target="_blank">https://biorender.com/</a>).</p>
Full article ">Figure 6
<p>AQP4 overexpression in the postnatal corpus callosum coincides with the emergence of a maturing astrocyte population. Fluorescence immunhistochemistry of GFAP (green) and AQP4 (red) in corpus callosum at P7 (<b>A</b>) and P60 (<b>B</b>). Higher magnifications show an increased number of astrocytes (GFAP+/AQP4+ cells) at P7 that correlates with postnatal astrocytogenesis. Scale bar = 150 µm; scale bar in the inset = 30 µm. Volumes representing AQP4 and GFAP stained areas in higher magnification were generated by 3D rendering (<b>C</b>). Detailed cellular characterizations in each stage indicate differences in glial morphology and AQP4 distribution between premature (p7) and mature fibrous astrocytes (p60). Grid line increment = 5 µm.</p>
Full article ">
16 pages, 3289 KiB  
Article
LncRNA CASC19 Enhances the Radioresistance of Nasopharyngeal Carcinoma by Regulating the miR-340-3p/FKBP5 Axis
by Hongxia Liu, Qianping Chen, Wang Zheng, Yuchuan Zhou, Yang Bai, Yan Pan, Jianghong Zhang and Chunlin Shao
Int. J. Mol. Sci. 2023, 24(3), 3047; https://doi.org/10.3390/ijms24033047 - 3 Feb 2023
Cited by 9 | Viewed by 3279
Abstract
Radioresistance remains a serious obstacle encountered in the radiotherapy of nasopharyngeal carcinoma (NPC). Both mRNAs and non-coding RNAs (ncRNAs), including long ncRNA (lncRNA) and microRNA (miRNA), play essential roles in radiosensitivity. However, the comprehensive expression profiles and competing endogenous RNA (ceRNA) regulatory networks [...] Read more.
Radioresistance remains a serious obstacle encountered in the radiotherapy of nasopharyngeal carcinoma (NPC). Both mRNAs and non-coding RNAs (ncRNAs), including long ncRNA (lncRNA) and microRNA (miRNA), play essential roles in radiosensitivity. However, the comprehensive expression profiles and competing endogenous RNA (ceRNA) regulatory networks among lncRNAs, miRNAs, and mRNAs in NPC radioresistance are still bewildering. In this study, we performed an RNA-sequencing (RNA-seq) assay in the radioresistant NPC cells CNE2R and its parental cells CNE2 to identify the differentially expressed lncRNAs, miRNAs, and mRNAs. The ceRNA networks containing lncRNAs, miRNAs, and mRNAs were predicted on the basis of the Pearson correlation coefficients and authoritative miRanda databases. In accordance with bioinformatic analysis of the data of the tandem mass tag (TMT) assay of CNE2R and CNE2 cells and the gene chip assay of radioresistant NPC samples in pre- and post-radiotherapy, the radioresistance-related signaling network of lncRNA CASC19, miR-340-3p, and FKBP5 was screened and further verified using an RT-qPCR assay. CASC19 was positively associated with FKBP5 expression while negatively correlated with miR-340-3p, and the target binding sites of CASC19/miR-340-3p and miR-340-3p/FKBP5 were confirmed using a dual-luciferase reporter assay. Moreover, using an mRFP–GFP–LC3 maker, it was found that autophagy contributed to the radioresistance of NPC. MiR-340-3p inhibition or FKBP5 overexpression could rescue the suppression of autophagy and radioresistance induced by CASC19 knockdown in CNE2R cells. In conclusion, the CASC19/miR-340-3p/FKBP5 network may be instrumental in regulating NPC radioresistance by enhancing autophagy, which provides potential new therapeutic targets for NPC. Full article
(This article belongs to the Special Issue RNA Regulatory Networks at the Crossroad of Human Diseases 3.0)
Show Figures

Figure 1

Figure 1
<p>RNA profile analyses of CNE2 and its paired radioresistance CNE2R cells: (<b>A</b>) colony formation assay was performed to evaluate the radiosensitivity of CNE2 and CNE2R cells. * <span class="html-italic">p</span> &lt; 0.05 between indicated groups; (<b>B</b>) volcano plots of the DElncRNAs, DEmRNAs, and DEmiRNAs between CNE2 and CNE2R cells based on RNA−seq assay; (<b>C</b>) volcano plot of differentially expressed genes (DEGs) between CNE2 and CNE2R cells based on TMT assay.</p>
Full article ">Figure 2
<p>CASC19−related ceRNA networks were constructed on the basis of mRNAs screen: (<b>A</b>) CASC19−related ceRNA networks of 6 common upregulated genes (CBX5, CTSD, FKBP5, FKBP10, DHTKD1, and HSP90B1) based on the intersection of RNA−seq and TMT assays; (<b>B</b>) the heatmap of DEGs between tumor samples of NPC radioresistant patients before and after radiotherapy (n = 3); (<b>C</b>) Venny chart of the intersection of the common genes among the upregulated mRNAs regulated by lncRNAs-miRNAs in CNE2R cells (RNA−seq assay), the upregulated genes in CNE2R cells compared with CNE2 cells (TMT assay), and the upregulated genes in the patients post-radiotherapy compared with pre-radiotherapy (clinic gene chip assay). The intersection only contains one gene FKBP5; (<b>D</b>) the expressions of FKBP5 in the tumor tissues of NPC and its adjacent normal tissues (data from GEO databases of GSE12452 and GSE13597); (<b>E</b>) the expressions of FKBP5 in the head and neck squamous cell carcinoma (HNSC) and its adjacent normal tissues (data from GEPIA).</p>
Full article ">Figure 3
<p>The expressions of CASC19, miR-340-3p, and FKBP5 in CNE2 and CNE2R cells: (<b>A</b>–<b>C</b>) the expressions of CACS19, FKBP5, and miR-340-3p detected using RT-PCR. * <span class="html-italic">p</span> &lt; 0.05 compared with CNE2 cells; (<b>D</b>) the expression of FKBP5 protein detected with Western blot assay. * <span class="html-italic">p</span> &lt; 0.05 compared with CNE2 cells; (<b>E</b>–<b>G</b>) the expressions of CASC19, FKBP5, and miR-340-3p in CNE2 cells irradiated with different doses. * <span class="html-italic">p</span> &lt; 0.05 compared with nonirradiated control.</p>
Full article ">Figure 4
<p>CASC19 enhanced autophagy and promoted the radioresistance of NPC by negatively regulating miR-340-3p: (<b>A</b>) verification of the interference efficiency of CASC19 smart silencer (siCASC19) in CNE2R cells; (<b>B</b>,<b>C</b>) the expression of miR-340-3p in CNE2R cells after transfection of miR-340-3p mimics (<b>B</b>) or miR-340-3p inhibitor (<b>C</b>); (<b>D</b>) the expression of CASC19 in CNE2R cells after transfection of miR-340 mimics; (<b>E</b>) survival curves of irradiated CNE2R cells transfected with siCASC19, miR-340 inhibitor, or its control; (<b>F</b>) prediction of the target binding sites of CASC19 and miR-340-3p was verified using the dual-luciferase reporter assay; (<b>G</b>) autophagy assay using mRFP-GFP-LC3 in CNE2R cells transfected with siCASC19, miR-340 inhibitor, or their controls; (<b>H</b>) Western blot assay of P62 and LC3 proteins in CNE2R cells transfected with siCASC19, miR-340 inhibitor, or their controls. * <span class="html-italic">p</span> &lt; 0.05 compared with corresponding control or between indicated groups.</p>
Full article ">Figure 5
<p>CASC19 positively regulated the expression of FKBP5 through miR-340-3p: (<b>A</b>,<b>B</b>) RT-qPCR (<b>A</b>) and Western blot (<b>B</b>) assay of the expression of FKBP5 in CNE2R cells transfected with miR-340-3p mimics or its control; (<b>C</b>) prediction of the target binding sites of FKBP5 and miR-340-3p was verified with the dual-luciferase reporter assay; (<b>D</b>) the expression of FKBP5 in CNE2R cells with or without transfection of siCASC19; (<b>E</b>) the expression of CACS19 in CNE2R cells with or without transfection of siFKBP5; (<b>F</b>) Western blot assay of FKBP5, P62, and LC3 protein in CNE2R cells co-transfected with siCASC19 and FKBP5 overexpression plasmid. * <span class="html-italic">p</span> &lt; 0.05 compared with the corresponding control.</p>
Full article ">Figure 6
<p>Knockdown FKBP5 enhanced the radiosensitivity of NPC cells by inhibiting autophagy: (<b>A</b>,<b>B</b>) RT-qPCR (<b>A</b>) and Western blot (<b>B</b>) assay of the expression of FKBP5 in CNE2R and CNE2 cells transfected with siFKBP5; (<b>C</b>) colony formation assay was performed to evaluate the influence of siFKBP5 on the survival fractions of CNE2R and CNE2 cells after irradiation; (<b>D</b>) fluorescence images of CNE2R cells transfected with siFKBP5 and mRFP-GFP-LC3-tagged adenovirus (×40); (<b>E</b>) Western blot assay of LC3 proteins in CNE2R cells after transfection with siFKBP5. * <span class="html-italic">p</span> &lt; 0.05 compared with corresponding siNC or between indicated groups.</p>
Full article ">Figure 7
<p>Schematic model of the pathways regulated the radioresistance of NPC cells. CASC19, as a competing endogenous RNA, bound to miR-340-3p via the lncRNA sponging mechanism and abolished the suppression of FKBP5 expression caused by miR-340-3p. FKBP5 may bind with BECN1 or regulate AKT/FOXO3 pathway, resulting in an increase in autophagy, thereby enhancing the radioresistance of NPC. The signaling pathways in the dashed box are derived from studies in the literature.</p>
Full article ">
23 pages, 10468 KiB  
Article
Prunus Knotted-like Genes: Genome-Wide Analysis, Transcriptional Response to Cytokinin in Micropropagation, and Rootstock Transformation
by Giulio Testone, Emilia Caboni, Simone D’Angeli, Maria Maddalena Altamura and Donato Giannino
Int. J. Mol. Sci. 2023, 24(3), 3046; https://doi.org/10.3390/ijms24033046 - 3 Feb 2023
Cited by 1 | Viewed by 2311
Abstract
Knotted1-like homeobox (KNOX) transcription factors are involved in plant development, playing complex roles in aerial organs. As Prunus species include important fruit tree crops of Italy, an exhaustive investigation of KNOX genes was performed using genomic and RNA-seq meta-analyses. Micropropagation is an [...] Read more.
Knotted1-like homeobox (KNOX) transcription factors are involved in plant development, playing complex roles in aerial organs. As Prunus species include important fruit tree crops of Italy, an exhaustive investigation of KNOX genes was performed using genomic and RNA-seq meta-analyses. Micropropagation is an essential technology for rootstock multiplication; hence, we investigated KNOX transcriptional behavior upon increasing 6-benzylaminopurine (BA) doses and the effects on GF677 propagules. Moreover, gene function in Prunus spp. was assessed by Gisela 6 rootstock transformation using fluorescence and peach KNOX transgenes. Based on ten Prunus spp., KNOX proteins fit into I-II-M classes named after Arabidopsis. Gene number, class member distribution, and chromosome positions were maintained, and exceptions supported the diversification of Prunus from Cerasus subgenera, and that of Armeniaca from the other sections within Prunus. Cytokinin (CK) cis-elements occurred in peach and almond KNOX promoters, suggesting a BA regulatory role in GF677 shoot multiplication as confirmed by KNOX expression variation dependent on dose, time, and interaction. The tripled BA concentration exacerbated stress, altered CK perception genes, and modified KNOX transcriptions, which are proposed to concur in in vitro anomalies. Finally, Gisela 6 transformation efficiency varied (2.6–0.6%) with the genetic construct, with 35S:GFP being more stable than 35S:KNOPE1 lines, which showed leaf modification typical of KNOX overexpression. Full article
(This article belongs to the Special Issue State-of-the-Art Molecular Plant Sciences in Italy)
Show Figures

Figure 1

Figure 1
<p>(<b>A</b>) Phylogenetic tree of PRUNOX deduced proteins, clustered into classes I, II, and M (blue, orange, and green shades) and named based on the presence of <span class="html-italic">A. thaliana</span> (bold) members in the clade. (<b>B</b>) Plots of amino acid variability within KNOX subgroups. The peach proteins were schemed (top of each panel) together with key domains (colored boxes) and used as reference for KNOX of other species. Identity variation (percent) of amino acids within <span class="html-italic">Prunus</span> spp. proteins (Y-axis) refers to amino acid positions (X-axis). Orange, KNOX1 (PF03790); red, KNOX2 (PF03791); grey, ELK (PF03789); blue, homeodomain (PF05920).</p>
Full article ">Figure 2
<p>Comparative schematic maps of <span class="html-italic">KNOX</span> genome distribution occurring in species of the <span class="html-italic">Armeniaca</span> section (e.g., <span class="html-italic">P. mume</span>, Pm) vs. that in other <span class="html-italic">Prunus</span> spp. (e.g., <span class="html-italic">P. persica</span>, Pp). The gene <span class="html-italic">KNOPE2.1</span> is located in the unplaced scaffold1397 (Scf1397) in <span class="html-italic">P. mume</span> but in Chr 7 in <span class="html-italic">P. armeniaca</span>. The scale on the left represents chromosome lengths in megabases (Mb).</p>
Full article ">Figure 3
<p>Exon–intron structure and conserved motifs in <span class="html-italic">PRUNOX</span> genes. The organization of each class was compared to <span class="html-italic">A. thaliana</span> counterparts (grey-shaded). Boxes, coding sequences; gray lines, introns. KNOX conserved motifs are colored.</p>
Full article ">Figure 4
<p>Cytokinin binding motifs residing on <span class="html-italic">PRUNOX</span> genes’ promoters of <span class="html-italic">P. persica</span> and <span class="html-italic">P. dulcis</span> (left and right panels). The score accounts (covering 1.5 kb region before the start codon in <a href="#app1-ijms-24-03046" class="html-app">Table S4</a>) refer to the experimentally determined extended (ECRM; blue) and core (CRM; light blue) motifs [<a href="#B38-ijms-24-03046" class="html-bibr">38</a>], as well as octameric sequences (yellow/orange/brown) enriched in CK-responsive promoters [<a href="#B39-ijms-24-03046" class="html-bibr">39</a>].</p>
Full article ">Figure 5
<p><span class="html-italic">Prunus</span> genome-wide transcription analysis of <span class="html-italic">PRUNOX</span> genes active in aerial organs. The expression profiles refer to 10 species through heat maps of the z-scores, where orange and blue indicate higher and lower expression, respectively. fl., flower.</p>
Full article ">Figure 6
<p>Effects of BA supply on GF677 microcuttings (<b>A</b>,<b>F</b>,<b>K</b>). Explants of the GF677 rootstock were grown on media without BA (<b>A</b>–<b>E</b>) or containing BA at concentrations of 1.7 (<b>F</b>–<b>J</b>) and 5.1 µM (<b>K</b>–<b>O</b>). Ten days post-treatment, the effects of BA dosage in increasing the numbers of side shoots and leaves (compare (<b>F</b>,<b>K</b>) vs. (<b>A</b>)) were visible. (<b>B</b>–<b>E</b>,<b>G</b>–<b>J</b>,<b>L</b>–<b>O</b>) Histological analyses of longitudinal sections at early stages (3 days after treatment). Median section through the dome of control (<b>B</b>) and BA-treated apices (<b>G</b>,<b>L</b>). Leaf axillary buds showed a plethora of phenotypes, including normal (<b>C</b>,<b>D</b>,<b>H</b>,<b>M</b>), elongating (<b>I</b>), and swollen (<b>O</b>). Section of stems portions adjacent to medium (<b>E</b>,<b>J</b>). Bar sizes: 0.5 cm in (<b>A</b>,<b>F</b>,<b>K</b>); 150 µm in (<b>D</b>,<b>I</b>,<b>L</b>–<b>N</b>); 160 µm in (<b>B</b>,<b>G</b>,<b>H</b>,<b>J</b>,<b>L</b>,<b>O</b>); 170 µm in (<b>C</b>).</p>
Full article ">Figure 7
<p>Gene expression analyses of <span class="html-italic">KNOPE</span> and marker genes under different BA dosages. Expression levels of stress- (<b>A</b>,<b>B</b>) and CK-responsive (<b>C</b>,<b>D</b>) markers and of <span class="html-italic">KNOPE</span> (<b>E</b>,<b>H</b>) and <span class="html-italic">BELL</span> (<b>I</b>,<b>J</b>) genes in response to 1.7 µM (<b>A</b>,<b>C</b>,<b>E</b>,<b>G</b>,<b>I</b>) and 5.1 µM (<b>B</b>,<b>D</b>,<b>F</b>,<b>H</b>,<b>J</b>) of BA at 24 and 72 h post-treatment (hpt). Each value represents the mean ± standard error of three replicates. For each gene, different letters mean significant differences (<span class="html-italic">p</span> ≤ 0.05).</p>
Full article ">Figure 8
<p>Correlation plot between TALE and marker gene expression levels. Correlogram representing Pearson’s correlation coefficients (r) between TALE (<span class="html-italic">PRUNOXI</span>: <span class="html-italic">STMlike1</span>, <span class="html-italic">STMlike2</span>, <span class="html-italic">KNOPE1</span>, <span class="html-italic">KNOPE2</span>, <span class="html-italic">KNOPE2.1</span>, <span class="html-italic">KNOPE6</span>; <span class="html-italic">PRUNOXII</span>: <span class="html-italic">KNOPE3, KNOPE4</span>, <span class="html-italic">KNOPE7</span>; <span class="html-italic">BELL</span>: <span class="html-italic">PpBEL1, PpBLH1, PpBLH2, PpBLH3, PpBLH5, PpBLH6, PpBLH8)</span> and marker (stress-responsive: <span class="html-italic">PpCAT1</span>, <span class="html-italic">PpCAT2</span>; CK-responsive: <span class="html-italic">PpCKX6</span>, <span class="html-italic">PpARR12, PpHK1)</span> expression levels. Heat map is used to indicate the strength of correlation between the variables with ordering determined by hierarchical clustering. Red and blue indicate negative and positive correlations, respectively. Only significant (<span class="html-italic">p</span> ≤ 0.05) Pearson’s coefficients were reported in the colored squares. *, **, and *** = significant at <span class="html-italic">p</span> ≤ 0.05, 0.01, and 0.001, respectively.</p>
Full article ">Figure 9
<p>Genetic transformation of Gisela 6. (<b>A</b>–<b>J</b>) Examples of GFP fluorescence analysis in leaves and roots of Gisela 6 transgenic clones. (<b>A</b>–<b>D</b>) P1 clone. (<b>E</b>–<b>H</b>) P3 clone. Analysis of leaf margins (<b>A</b>,<b>C</b>,<b>E</b>,<b>G</b>) and lateral roots (<b>B</b>,<b>D</b>,<b>F</b>,<b>H</b>) under visible microscopy (<b>A</b>,<b>B</b>,<b>E</b>,<b>F</b>) and fluorescence (<b>C</b>,<b>D</b>,<b>G</b>,<b>H</b>). (<b>K</b>–<b>Q</b>) <span class="html-italic">35S:KNOPE1</span> phenotypes in Gisela 6. Regenerated clones (<b>K</b>,<b>N</b>) and details of leaf margins (<b>L</b>–<b>O</b>) and lamina vasculature (<b>M</b>,<b>P</b>) in nontransformed (<b>K</b>–<b>M</b>) and <span class="html-italic">35S:KNOPE1</span> (<b>N</b>–<b>P</b>) lines. (<b>Q</b>) <span class="html-italic">35S:KNOPE1</span> clone that reverted phenotype with time. (<b>R</b>) Vector schemes of <span class="html-italic">pCAMBIA1302</span> (above) and <span class="html-italic">pBA002 + KNOPE1</span> (below); dark grey bars, probes used in Southern blots which are reported in <a href="#app1-ijms-24-03046" class="html-app">Figure S3</a>; arrowheads, primers used to check for transgene integrity (black) and expression (red). (<b>S</b>) Upper panel, a check for <span class="html-italic">p35S:KNOPE1:NOSt</span> cassette integrity by PCR with gDNA. Six clones were rescued and analyzed; on the left, size of bands of DNA ladder in base pairs (bp); on the right, the amplicon size is specified. Mid panel, a check for <span class="html-italic">KNOPE1</span> transgene expression in the six clones by RT-PCR using leaf blade RNA. Peach (Chiripa) <span class="html-italic">KNOPE1</span>-specific primers fell between the 5’UTR and the first exon (<b>R</b>). The constitutive <span class="html-italic">RPII</span> expression was assayed to check for correct retrotranscription and usage of equal cDNA amounts. The amplicon sizes are reported.</p>
Full article ">
14 pages, 2384 KiB  
Article
Culturing the Chicken Intestinal Microbiota and Potential Application as Probiotics Development
by Ke Ma, Wei Chen, Xiao-Qi Lin, Zhen-Zhen Liu, Tao Wang, Jia-Bao Zhang, Jian-Gang Zhang, Cheng-Kai Zhou, Yu Gao, Chong-Tao Du and Yong-Jun Yang
Int. J. Mol. Sci. 2023, 24(3), 3045; https://doi.org/10.3390/ijms24033045 - 3 Feb 2023
Cited by 11 | Viewed by 3544
Abstract
Pure cultures of chicken intestinal microbial species may still be crucial and imperative to expound on the function of gut microbiota, and also contribute to the development of potential probiotics and novel bioactive metabolites from gut microbiota. In this study, we isolated and [...] Read more.
Pure cultures of chicken intestinal microbial species may still be crucial and imperative to expound on the function of gut microbiota, and also contribute to the development of potential probiotics and novel bioactive metabolites from gut microbiota. In this study, we isolated and identified 507 chicken intestinal bacterial isolates, including 89 previously uncultured isolates. Among these, a total of 63 Lactobacillus strains, belonging to L. vaginalis, L. crispatus, L. gallinarum, L. reuteri, L. salivarius, and L. saerimneri, exhibited antibacterial activity against S. Pullorum. Acid tolerance tests showed Limosilactobacillus reuteri strain YPG14 (L. reuteri strain YPG14) has a particularly strong tolerance to acid. We further characterized other probiotic properties of L. reuteri strain YPG14. In simulated intestinal fluid, the growth of L. reuteri strain YPG14 remained stable after incubation for 4 h. The auto-aggregation test showed the auto-aggregation percentage of L. reuteri strain YPG14 was recorded as 15.0  ±  0.38%, 48.3  ±  2.51%, and 75.1  ±  4.44% at 3, 12, and 24 h, respectively. In addition, the mucin binding assay showed L. reuteri strain YPG14 exhibited 12.07 ±  0.02% adhesion to mucin. Antibiotic sensitivity testing showed that L. reuteri strain YPG14 was sensitive to the majority of the tested antibiotics. The anti-Salmonella Pullorum (S. Pullorum) infection effect in vivo revealed that the consumption of L. reuteri strain YPG14 could significantly improve body weight loss and survival rate of chicks infected by S. Pullorum; reduce the loads of S. Pullorum in the jejunum, liver, spleen, and feces; and alleviate the jejunum villi morphological structure damage, crypt loss, and inflammatory cell infiltration caused by S. Pullorum. Overall, this study may help us to understand the diversity of chicken intestinal microflora and provide some insights for potential probiotic development from gut microbiota and may find application in the poultry industry. Full article
Show Figures

Figure 1

Figure 1
<p>Diversity of the chicken intestinal microbiota strain collection. (<b>A</b>) Taxonomic distribution of genus level of total pure cultured bacteria isolated from chicken intestine; (<b>B</b>) The percentage of previously cultured and uncultured chicken intestinal bacteria.</p>
Full article ">Figure 2
<p>The antimicrobial activity of <span class="html-italic">Lactobacillus</span> isolates against <span class="html-italic">Salmonella</span> Pullorum. (<b>A</b>–<b>F</b>) represent the antimicrobial activity of <span class="html-italic">L. vaginalis</span>, <span class="html-italic">L. crispatus</span>, <span class="html-italic">L. gallinarum</span>, <span class="html-italic">L. reuteri</span>, <span class="html-italic">L. salivarius</span>, and <span class="html-italic">L. saerimneri</span>, respectively.</p>
Full article ">Figure 3
<p>The acid tolerance properties of the selected <span class="html-italic">Lactobacillus</span> strains. (<b>A</b>–<b>F</b>) represent the acid tolerance properties of <span class="html-italic">L. vaginalis</span>, <span class="html-italic">L. crispatus</span>, <span class="html-italic">L. gallinarum</span>, <span class="html-italic">L. reuteri</span>, <span class="html-italic">L. salivarius</span>, and <span class="html-italic">L. saerimneri</span>, respectively.</p>
Full article ">Figure 4
<p>Phylogenetic analysis of the strain YPG14. (<b>A</b>) Colony morphology of the strain YPG14; (<b>B</b>) Neighbor-joining and (<b>C</b>) maximum likelihood phylogenetic tree based on the 16S rRNA gene sequence of the strain YPG14 (1445 bp) showed the taxonomic position of the strain YPG14 and closely related taxa. Bootstrap values (percentages of 1000 replications) are shown at branch points. <span class="html-italic">Bacillus subtilis</span> DSM 10T (GenBank accession no. AJ276351) was used as outgroup. The bar, 0.01 and 0.02 nucleotide substitutions per site.</p>
Full article ">Figure 5
<p>The growth determination of the strain YPG14. (<b>A</b>) The growth time curve of the strain YPG14; (<b>B</b>) The pH value change of media during growth of the strain YPG14.</p>
Full article ">Figure 6
<p>The characterization of partial probiotic properties of the strain YPG14. (<b>A</b>) The tolerance of the strain YPG14 to simulated intestinal juice; (<b>B</b>) The auto-aggregation percentage of the strain YPG14; (<b>C</b>) The adhesion of the strain YPG14 to mucin.</p>
Full article ">Figure 7
<p>Study design and protective effect of the strain YPG14 against <span class="html-italic">Salmonella</span> Pullorum infections. (<b>A</b>) The experimental design and treatment procedure; (<b>B</b>) The determination of body weight change (<span class="html-italic">n</span> = 15/group); (<b>C</b>) The determination of survival rate (<span class="html-italic">n</span> = 15/group); (<b>D</b>) The determination of <span class="html-italic">S</span>. Pullorum bacterial burden in tissues and feces infected with <span class="html-italic">S</span>. Pullorum on 5-day post-infection (dpi). All data are shown as mean ± SEM. Student’s <span class="html-italic">t</span>-test was performed. Statistical significance is indicated by * <span class="html-italic">p</span> &lt; 0.05 and *** <span class="html-italic">p</span> &lt; 0.001.</p>
Full article ">Figure 8
<p>Histopathological changes of jejunum tissues. (<b>A</b>) Histopathological changes in jejunum tissues were examined by H&amp;E staining (scale bar = 200 μm); (<b>B</b>) The determination of villus length of jejunum tissues (10 villi per histology section); (<b>C</b>) The histological score of jejunum tissues. All data are shown as mean ± SEM. Student’s t-test was performed. Statistical significance is indicated by *** <span class="html-italic">p</span> &lt; 0.001.</p>
Full article ">
20 pages, 53897 KiB  
Article
Substituent Effects of the Nitrogen Heterocycle on Indole and Quinoline HDN Performance: A Combination of Experiments and Theoretical Study
by Shujiao Jiang, Sijia Ding, Yasong Zhou, Shenghua Yuan, Xinguo Geng and Zhengkai Cao
Int. J. Mol. Sci. 2023, 24(3), 3044; https://doi.org/10.3390/ijms24033044 - 3 Feb 2023
Cited by 1 | Viewed by 2083
Abstract
Hydrodenitrogenation (HDN) experiments and density functional theory (DFT) calculations were combined herein to study the substituent effects of the nitrogen heterocycle on the HDN behaviors of indole and quinoline. Indole (IND), 2-methyl-indole (2-M-IND), 3-methyl-indole (3-M-IND), quinoline (QL), 2-methyl-quinoline (2-M-QL) and 3-methyl-quinoline (3-M-QL) were [...] Read more.
Hydrodenitrogenation (HDN) experiments and density functional theory (DFT) calculations were combined herein to study the substituent effects of the nitrogen heterocycle on the HDN behaviors of indole and quinoline. Indole (IND), 2-methyl-indole (2-M-IND), 3-methyl-indole (3-M-IND), quinoline (QL), 2-methyl-quinoline (2-M-QL) and 3-methyl-quinoline (3-M-QL) were used as the HDN reactant on the NiMo/γ-Al2O3 catalyst. Some key elementary reactions in the HDN process of these nitrogen compounds on the Ni-Mo-S active nanocluster were calculated. The notable difference between IND and QL in the HDN is that dihydro-indole (DHI) can directly convert to O-ethyl aniline via the C–N bond cleavage, whereas tetrahydro-quinoline (THQ) can only break the C–N single bond via the full hydrogenation saturation of the aromatic ring. The reason for this is that the –NH and C=C groups of DHI can be coplanar and well adsorbed on the Ni-Mo-edge simultaneously during the C–N bond cleavage. In comparison, those of THQ cannot stably simultaneously adsorb on the Ni-Mo-edge because of the non-coplanarity. Whenever the methyl group locates on the α-C or the β-C atom of indole, the hydrogenation ability of the nitrogen heterocycle will be evidently weakened because the methyl group increases the space requirement of the sp3 carbon, and the impaction of the C=C groups on the Ni-S-edge cannot provide enough space. When the methyl groups are located on the α-C of quinoline, the self-HDN behavior of 2-M-QL is similar to quinoline, whereas the competitive HDN ability of 2-M-QL in the homologs is evidently weakened because the methyl group on the α-C hinders the contact between the N atom of 2-M-QL and the exposed metal atom of the coordinatively unsaturated active sites (CUS). When the methyl group locates on the β-C of quinoline, the C–N bond cleavage of 3-methyl-quinoline becomes more difficult because the methyl group on the β-C increases the steric hindrance of the C=C group. However, the competitive HDN ability of 3-M-QL is not evidently influenced because the methyl group on the β-C does not evidently hinder the adsorption of 3-M-QL on the active sites. Full article
Show Figures

Figure 1

Figure 1
<p>Configuration of the model Ni-Mo-S nanocluster: (<b>a</b>) schematic of the nanocluster; (<b>b</b>) side view of the Ni-Mo-edge; (<b>c</b>) side view of the Ni-S-edge.</p>
Full article ">
17 pages, 5075 KiB  
Article
Stable Enzymatic Nanoparticles from Nucleases, Proteases, Lipase and Antioxidant Proteins with Substrate-Binding and Catalytic Properties
by Olga V. Morozova, Nikolay A. Barinov and Dmitry V. Klinov
Int. J. Mol. Sci. 2023, 24(3), 3043; https://doi.org/10.3390/ijms24033043 - 3 Feb 2023
Cited by 6 | Viewed by 2479
Abstract
Limited membrane permeability and biodegradation hamper the intracellular delivery of the free natural or recombinant enzymes necessary for compensatory therapy. Nanoparticles (NP) provide relative protein stability and unspecific endocytosis-mediated cellular uptake. Our objective was the fabrication of NP from 7 biomedicine-relevant enzymes, including [...] Read more.
Limited membrane permeability and biodegradation hamper the intracellular delivery of the free natural or recombinant enzymes necessary for compensatory therapy. Nanoparticles (NP) provide relative protein stability and unspecific endocytosis-mediated cellular uptake. Our objective was the fabrication of NP from 7 biomedicine-relevant enzymes, including DNase I, RNase A, trypsin, chymotrypsin, catalase, horseradish peroxidase (HRP) and lipase, the analysis of their conformation stability and enzymatic activity as well as possible toxicity for eukaryotic cells. The enzymes were dissolved in fluoroalcohol and mixed with 40% ethanol as an anti-solvent with subsequent alcohol evaporation at high temperature and low pressure. The shapes and sizes of NP were determined by scanning electron microscopy (SEM), atomic force microscopy (AFM) and dynamic light scattering (DLS). Enzyme conformations in solutions and in NP were compared using circular dichroism (CD) spectroscopy. The activity of the enzymes was assayed with specific substrates. The cytotoxicity of the enzymatic NP (ENP) was studied by microscopic observations and by using an MTT test. Water-insoluble ENP of different shapes and sizes in a range 50–300 nm consisting of 7 enzymes remained stable for 1 year at +4 °C without any cross-linking. CD spectroscopy of the ENP permitted us to reveal changes in proportions of α-helixes, β-turns and random coils in comparison with fresh enzyme solutions in water. Despite the minor conformation changes of the proteins in the ENP, the enzymes retained their substrate-binding and catalytic properties. Among the studied bioactive ENP, only DNase NP were highly toxic for 3 cell lines with granulation in 1 day posttreatment, whereas other NP were less toxic (if any). Taken together, the enzymes in the stable ENP retained their catalytic activity and might be used for intracellular delivery. Full article
(This article belongs to the Special Issue From Nanotechnology to Nanomedicine: Past, Present and Future)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Scanning electron microscopy (SEM) images of ENP consisting of horseradish peroxidase (HRP), catalase, trypsin and chymotrypsin. Scale bar 1 μm and a single ENP with the corresponding diameter are shown for each image.</p>
Full article ">Figure 2
<p>Atomic force microscopy (AFM) images of the original trypsin NP immediately after fabrication and in 1 year of storage at +4 °C.</p>
Full article ">Figure 3
<p>AFM data of the original chymotrypsin NP immediately after fabrication and in 1 year of storage at +4 °C.</p>
Full article ">Figure 4
<p>Dynamic light scattering (DLS) measurements of the catalase and HRP NP sizes before and after storage in water for 9 months.</p>
Full article ">Figure 5
<p>Analysis of the nuclease activities of ENP. (<b>A</b>) Electropherogram of PCR product of 153 bp long before (lane 1) and after treatment with DNase NP 0.001 mg/mL (lane 2), 0.01 mg/mL (lane 3) and 1 mg/mL (lane 4) in 2% agarose gel 1× TBE buffer with ethidium bromide staining. (<b>B</b>) Data of reverse transcription with real-time PCR for β-coronavirus SARS-CoV-2 RNA from COVID-19 patient blood leukocytes in the presence of the ENP consisting of DNase I, RNase A or trypsin. Calculation of the fluorescence threshold cycles (Ct) for each well is shown in <a href="#app1-ijms-24-03043" class="html-app">Supplementary Materials Table S1</a>.</p>
Full article ">Figure 6
<p>Comparison of enzymatic activity of two antioxidant enzymes in the fluoroalcohol HFIP solution and ENP. Optical density at 450 nm of TMB solution in the presence of H<sub>2</sub>O<sub>2</sub> and catalase in HFIP solution, catalase NP, HRP in HFIP solution or HRP NP.</p>
Full article ">Figure 7
<p>Comparison of enzymatic activity of HRP (<b>A</b>) and catalase (<b>B</b>) in solutions in water and fluoroalcohol, as well as in ENP.</p>
Full article ">Figure 8
<p>Comparison of lipase activity in water, HFIP solutions and in the ENP using two substrates—OxiRed dye by measurements of optical densities at 570 nm (<b>A</b>) and 4-nitrophenol yellow with spectrophotometric measurements at 410 nm (<b>B</b>).</p>
Full article ">Figure 9
<p>Viability of Vero cells in the presence of 0.1 mg/mL ENP. Optical microscopy images (×400).</p>
Full article ">Figure 10
<p>Cytotoxicity of the ENP for HEp-2, HT-29 and Vero cells in the presence of ENP at 3 days posttreatment. Part (<b>A</b>) corresponds to HEp-2 cells, part (<b>B</b>)—HT-29 cells, part (<b>C</b>)—Vero cells.</p>
Full article ">Figure 10 Cont.
<p>Cytotoxicity of the ENP for HEp-2, HT-29 and Vero cells in the presence of ENP at 3 days posttreatment. Part (<b>A</b>) corresponds to HEp-2 cells, part (<b>B</b>)—HT-29 cells, part (<b>C</b>)—Vero cells.</p>
Full article ">
17 pages, 2666 KiB  
Article
Transcriptome-Based Traits of Radioresistant Sublines of Non-Small Cell Lung Cancer Cells
by Margarita Pustovalova, Philipp Malakhov, Anastasia Guryanova, Maxim Sorokin, Maria Suntsova, Anton Buzdin, Andreyan N. Osipov and Sergey Leonov
Int. J. Mol. Sci. 2023, 24(3), 3042; https://doi.org/10.3390/ijms24033042 - 3 Feb 2023
Cited by 5 | Viewed by 2835
Abstract
Radioresistance is a major obstacle for the successful therapy of many cancers, including non-small cell lung cancer (NSCLC). To elucidate the mechanism of radioresistance of NSCLC cells and to identify key molecules conferring radioresistance, the radioresistant subclones of p53 wild-type A549 and p53-deficient [...] Read more.
Radioresistance is a major obstacle for the successful therapy of many cancers, including non-small cell lung cancer (NSCLC). To elucidate the mechanism of radioresistance of NSCLC cells and to identify key molecules conferring radioresistance, the radioresistant subclones of p53 wild-type A549 and p53-deficient H1299 cell cultures were established. The transcriptional changes between parental and radioresistant NSCLC cells were investigated by RNA-seq. In total, expression levels of 36,596 genes were measured. Changes in the activation of intracellular molecular pathways of cells surviving irradiation relative to parental cells were quantified using the Oncobox bioinformatics platform. Following 30 rounds of 2 Gy irradiation, a total of 322 genes were differentially expressed between p53 wild-type radioresistant A549IR and parental A549 cells. For the p53-deficient (H1299) NSCLC cells, the parental and irradiated populations differed in the expression of 1628 genes and 1616 pathways. The expression of genes associated with radioresistance reflects the complex biological processes involved in clinical cancer cell eradication and might serve as a potential biomarker and therapeutic target for NSCLC treatment. Full article
(This article belongs to the Special Issue Effects of Ionizing Radiation in Cancer Radiotherapy)
Show Figures

Figure 1

Figure 1
<p>Radiosensitivity of parental and radioresistant NSCLC cells growing in (<b>a</b>) anchorage-dependent (solid surface) and in (<b>b</b>) anchorage-independent (soft agar) conditions. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001. Data are means ± SEM for more than three independent experiments (published previously [<a href="#B10-ijms-24-03042" class="html-bibr">10</a>]).</p>
Full article ">Figure 2
<p>Differential gene intersection showing: (<b>a</b>) up-regulated genes in A549IR cells ∩ H1299IR cells; (<b>b</b>) down-regulated genes in A549IR cells ∩ H1299IR cells. Red asterisk indicate statistical significance * <span class="html-italic">p</span> &lt; 0.05.</p>
Full article ">Figure 3
<p>PAL chart of A549 and H1299 cells: (<b>a</b>) Top 10 up- and down-regulated pathways in A549IR and (<b>b</b>) H1299IR cells, Benjamini Hochberg adjusted <span class="html-italic">p</span>-value &lt; 0.05 (only pathways containing 10 and more genes).</p>
Full article ">Figure 4
<p>Overlap between differentially regulated molecular pathways between A549IR and H1299IR cells. Overlap of significantly (<b>a</b>) up-regulated (PAL &gt; 0) and (<b>b</b>) down-regulated (PAL &lt; 0) molecular pathways between A549IR and H1299IR cells are shown; * denotes significance at <span class="html-italic">p</span> &lt; 0.05 for the overlaps obtained in perturbation.</p>
Full article ">Figure 5
<p>Heat map of RNA-Seq transcriptome analysis for 22 selected pathways in A549IR and H1299IR cells. The most significant differences between H1299IR and A549IR sublines are highlighted in red. Benjamini Hochberg adjusted <span class="html-italic">p</span>-value &lt; 0.05.</p>
Full article ">Figure 6
<p>Changes in the proportion of SA-β-Gal positive cells in A549IR and H1299IR. Data are means ± SEM for more than three independent experiments. **** <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">
25 pages, 9463 KiB  
Review
Finding the Needle in the Haystack: Serological and Urinary Biomarkers in Behçet’s Disease: A Systematic Review
by Marta Arbrile, Massimo Radin, Davide Medica, Paolo Miraglia, Letizia Rilat, Irene Cecchi, Silvia Grazietta Foddai, Alice Barinotti, Elisa Menegatti, Dario Roccatello and Savino Sciascia
Int. J. Mol. Sci. 2023, 24(3), 3041; https://doi.org/10.3390/ijms24033041 - 3 Feb 2023
Cited by 2 | Viewed by 2709
Abstract
Urinary and serological markers play an essential role in the diagnostic process of autoimmune diseases. However, to date, specific and reliable biomarkers for diagnosing Behçet’s disease (BD) are still lacking, negatively affecting the management of these patients. To analyze the currently available literature [...] Read more.
Urinary and serological markers play an essential role in the diagnostic process of autoimmune diseases. However, to date, specific and reliable biomarkers for diagnosing Behçet’s disease (BD) are still lacking, negatively affecting the management of these patients. To analyze the currently available literature on serological and urinary BD biomarkers investigated in the last 25 years, we performed a systematic literature review using the Population, Intervention, Comparison, and Outcomes (PICO) strategy. One hundred eleven studies met the eligibility criteria (6301 BD patients, 5163 controls). Most of them were retrospective, while five (5%) were prospective. One hundred ten studies (99%) investigated serological biomarkers and only two (2%) focused on urinary biomarkers. One hundred three studies (93%) explored the diagnostic potential of the biomolecules, whereas sixty-two (56%) tested their effect on disease activity monitoring. Most articles reported an increase in inflammatory markers and pro-oxidant molecules, with a decrease in antioxidants. Promising results have been shown by the omics sciences, offering a more holistic approach. Despite the vast number of investigated markers, existing evidence indicates a persistent gap in BD diagnostic/prognostic indices. While new steps have been taken in the direction of pathogenesis and disease monitoring, international efforts for the search of a diagnostic marker for BD are still needed. Full article
(This article belongs to the Special Issue New Advances in Thrombosis)
Show Figures

Figure 1

Figure 1
<p>Flowchart of the literature search strategy.</p>
Full article ">Figure 2
<p>Graphical representation of the number of studies per year included in this systematic review. The scatter plot was established using the package Ggplot2 [<a href="#B12-ijms-24-03041" class="html-bibr">12</a>] of R studio [<a href="#B13-ijms-24-03041" class="html-bibr">13</a>].</p>
Full article ">Figure 3
<p>Graphical representation of the global origin of the publication rate of the analyzed studies per country, colored by BD study rate. The graphical representation was computed by log-transforming the number of research papers published by each country. It is possible to recognize the Silk Road pattern. The map was created using the package Ggplot2 [<a href="#B124-ijms-24-03041" class="html-bibr">124</a>] of R studio [<a href="#B12-ijms-24-03041" class="html-bibr">12</a>].</p>
Full article ">Figure 4
<p>Mechanisms underlying Behçet’s disease’s etiopathogenesis.</p>
Full article ">
19 pages, 4939 KiB  
Article
Effects of Positive Fighting Experience and Its Subsequent Deprivation on the Expression Profile of Mouse Hippocampal Genes Associated with Neurogenesis
by Olga E. Redina, Vladimir N. Babenko, Dmitry A. Smagin, Irina L. Kovalenko, Anna G. Galyamina, Vadim M. Efimov and Natalia N. Kudryavtseva
Int. J. Mol. Sci. 2023, 24(3), 3040; https://doi.org/10.3390/ijms24033040 - 3 Feb 2023
Cited by 2 | Viewed by 2315
Abstract
The hippocampus is known as the brain region implicated in visuospatial processes and processes associated with learning and short- and long-term memory. An important functional characteristic of the hippocampus is lifelong neurogenesis. A decrease or increase in adult hippocampal neurogenesis is associated with [...] Read more.
The hippocampus is known as the brain region implicated in visuospatial processes and processes associated with learning and short- and long-term memory. An important functional characteristic of the hippocampus is lifelong neurogenesis. A decrease or increase in adult hippocampal neurogenesis is associated with a wide range of neurological diseases. We have previously shown that in adult male mice with a chronic positive fighting experience in daily agonistic interactions, there is an increase in the proliferation of progenitor neurons and the production of young neurons in the dentate gyrus (in hippocampus), and these neurogenesis parameters remain modified during 2 weeks of deprivation of further fights. The aim of the present work was to identify hippocampal genes associated with neurogenesis and involved in the formation of behavioral features in mice with the chronic experience of wins in aggressive confrontations, as well as during the subsequent 2-week deprivation of agonistic interactions. Hippocampal gene expression profiles were compared among three groups of adult male mice: chronically winning for 20 days in the agonistic interactions, chronically victorious for 20 days followed by the 2-week deprivation of fights, and intact (control) mice. Neurogenesis-associated genes were identified whose transcription levels changed during the social confrontations and in the subsequent period of deprivation of fights. In the experimental males, some of these genes are associated with behavioral traits, including abnormal aggression-related behavior, an abnormal anxiety-related response, and others. Two genes encoding transcription factors (Nr1d1 and Fmr1) were likely to contribute the most to the between-group differences. It can be concluded that the chronic experience of wins in agonistic interactions alters hippocampal levels of transcription of multiple genes in adult male mice. The transcriptome changes get reversed only partially after the 2-week period of deprivation of fights. The identified differentially expressed genes associated with neurogenesis and involved in the control of a behavior/neurological phenotype can be used in further studies to identify targets for therapeutic correction of the neurological disturbances that develop in winners under the conditions of chronic social confrontations. Full article
(This article belongs to the Special Issue Regulation and Function of Adult Neurogenesis)
Show Figures

Figure 1

Figure 1
<p>Differences in the transcription profile of the hippocampus between winners and control animals (principal coordinate analysis using Euclidean distances). C: Control mice without the experience of agonistic interactions; A20: males with consecutive 20 days of wins in the daily agonistic interactions; AD: A20 mice after subsequent 14 days of fighting deprivation.</p>
Full article ">Figure 2
<p>KEGG pathways for the 72 genes associated with neurogenesis and found to be differentially expressed in our comparison of the hippocampal transcription profile between control male mice and males with consecutive 20 days of wins in daily agonistic interactions.</p>
Full article ">Figure 3
<p>(<b>a</b>) Axes maximizing distances between control and A20 mice (males with consecutive 20 days of wins in daily agonistic interactions); (<b>b</b>) distribution of expressed genes along the axis representing the correlation between gene expression and PLS-DA Axis 1. DEGs: differentially expressed genes.</p>
Full article ">Figure 4
<p>KEGG pathways related to the 31 genes associated with neurogenesis and found to be differentially expressed in our comparison of the hippocampal transcription profile between control male mice and males with consecutive 20 days of wins in daily agonistic interactions and then deprived of fighting for 14 days.</p>
Full article ">Figure 5
<p>Functional enrichment analysis of the neurogenesis network constructed for the C_AD comparison. This analysis suggests that the DEGs in question may contribute to the signaling and response to stress. The functional enrichment network was constructed by means of the STRING database (<a href="https://string-db.org/" target="_blank">https://string-db.org/</a>; accessed on 7 November 2022) using the DEGs associated with neurogenesis. Each node represents all the proteins produced by a single protein-coding gene. Edges are protein–protein associations. Purple lines indicate experimentally determined interactions; blue lines denote known interactions from curated databases; dark blue lines represent gene co-occurrence; black lines indicate coexpression; and green lines represent results of text mining. Protein–protein interaction (PPI) enrichment <span class="html-italic">p</span>-value &lt; 1.0 × 10<sup>−16</sup>. FDR: false discovery rate.</p>
Full article ">Figure 6
<p>Genes that significantly changed their levels of transcription during the period of agonistic interactions (C_A20 DEGs), whose expression did not get restored during the fighting deprivation (C_AD differences are statistically significant). FPKM, fragments per kilobase of transcript per million mapped reads; value C: expression in control mice (no experience of agonistic interactions); value_A20: expression in males with consecutive 20 days of wins in daily agonistic interactions; value_AD: expression in males with consecutive 20 days of wins in daily agonistic interactions deprived of fighting for 14 days.</p>
Full article ">Figure 7
<p>Neurogenesis-associated C_AD DEGs whose expression changed during the fighting deprivation. * DEGs in the A20_AD comparison; <sup>#</sup> DEGs in the C_A20 comparison. FPKM, fragments per kilobase of transcript per million mapped reads; value C: expression in control mice (no experience of agonistic interactions); value_A20: expression in males with consecutive 20 days of wins in daily agonistic interactions; value_AD: expression in males with consecutive 20 days of wins in daily agonistic interactions and then deprived of fighting for 14 days.</p>
Full article ">Figure 8
<p>(<b>a</b>) Axes maximizing the distances between control and AD mice (males with consecutive 20 days of wins in daily agonistic interactions and then deprived of fighting for 14 days). (<b>b</b>) Distribution of expressed genes along the axis representing the correlation between gene expression and PLS-DA Axis 1. DEGs: differentially expressed genes.</p>
Full article ">Figure 9
<p>Graphical representation of the experiment. A20: males with consecutive 20 days of wins in daily agonistic interactions; AD: the A20 mice after subsequent 14 days of fighting deprivation; Control: mice without the experience of agonistic interactions. Control males were housed one per cage for 5 days, which enabled them to feel dominant and potentially able to demonstrate aggressive behavior in a conflict situation.</p>
Full article ">
19 pages, 2231 KiB  
Article
Modulation of the Circulating Extracellular Vesicles in Response to Different Exercise Regimens and Study of Their Inflammatory Effects
by Serena Maggio, Barbara Canonico, Paola Ceccaroli, Emanuela Polidori, Andrea Cioccoloni, Luca Giacomelli, Carlo Ferri Marini, Giosuè Annibalini, Marco Gervasi, Piero Benelli, Francesco Fabbri, Laura Del Coco, Francesco Paolo Fanizzi, Anna Maria Giudetti, Francesco Lucertini and Michele Guescini
Int. J. Mol. Sci. 2023, 24(3), 3039; https://doi.org/10.3390/ijms24033039 - 3 Feb 2023
Cited by 13 | Viewed by 3646
Abstract
Exercise-released extracellular vesicles (EVs) are emerging as a novel class of exerkines that promotes systemic beneficial effects. However, slight differences in the applied exercise protocols in terms of mode, intensity and duration, as well as the need for standardized protocols for EV isolation, [...] Read more.
Exercise-released extracellular vesicles (EVs) are emerging as a novel class of exerkines that promotes systemic beneficial effects. However, slight differences in the applied exercise protocols in terms of mode, intensity and duration, as well as the need for standardized protocols for EV isolation, make the comparison of the studies in the literature extremely difficult. This work aims to investigate the EV amount and EV-associated miRNAs released in circulation in response to different physical exercise regimens. Healthy individuals were subjected to different exercise protocols: acute aerobic exercise (AAE) and training (AT), acute maximal aerobic exercise (AMAE) and altitude aerobic training (AAT). We found a tendency for total EVs to increase in the sedentary condition compared to trained participants following AAE. Moreover, the cytofluorimetric analysis showed an increase in CD81+/SGCA+/CD45 EVs in response to AAE. Although a single bout of moderate/maximal exercise did not impact the total EV number, EV-miRNA levels were affected as a result. In detail, EV-associated miR-206, miR-133b and miR-146a were upregulated following AAE, and this trend appeared intensity-dependent. Finally, THP-1 macrophage treatment with exercise-derived EVs induced an increase of the mRNAs encoding for IL-1β, IL-6 and CD163 using baseline and immediately post-exercise EVs. Still, 1 h post-exercise EVs failed to stimulate a pro-inflammatory program. In conclusion, the reported data provide a better understanding of the release of circulating EVs and their role as mediators of the inflammatory processes associated with exercise. Full article
(This article belongs to the Special Issue Translational Myology: Cellular, Genetic, Molecular Aspects)
Show Figures

Figure 1

Figure 1
<p>(<b>a</b>) Schematic representation of AT protocol. (<b>b</b>) VO<sub>2max</sub> values, Heart rate at rest (HRrest) and body weight variations following aerobic training. Values are mean ± SD. * significant difference Pre- vs. Post-Training (<span class="html-italic">p</span> &lt; 0.05, paired <span class="html-italic">t</span>-test).</p>
Full article ">Figure 2
<p>Modulation of IL-6 (<b>a</b>) and Creatine Kinase M-type systemic level (<b>b</b>) in response to an acute aerobic exercise in sedentary and trained subjects. The assays were performed at steady state (baseline), immediately after physical activity (Post Ex), after 2 (2 h Post Ex), and 6 h (6 h Post Ex) subsequently the end of the exercise. Values are mean ± SE. * significant difference from baseline (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 3
<p>Acute aerobic exercise affects plasma EV concentration and EV-derived miRNAs. Typical size distribution plot of EVs isolated from plasma by serial ultracentrifugation (<b>a</b>). Quantification of the circulating EVs by NTA in sedentary and trained subjects at steady state (baseline), immediately after physical activity (Post Ex), after 1 h (1 h Post Ex), 2 h (2 h Post Ex), 6 h (6 h Post Ex), and 24 h (24 h Post Ex) subsequently the end of the exercise. The results are represented as mean ± SE (<b>b</b>). Expression profile of specific EV-miRNAs analyzed at baseline condition, immediately after physical activity and after 2, 6 and 24 h in pre- and post-training conditions. MiRNA expression levels were reported as log2(2^−ΔΔCq) (<b>c</b>). Values are mean ± SE. * significant difference from baseline (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 4
<p>Evaluation of IL-6 systemic level in response to an acute maximal aerobic exercise (AMAE) in sedentary subjects at steady state (baseline), immediately after physical activity (Post Ex), after 1 (1 h Post Ex), and 2 h (2 h Post Ex) after the end of exercise (<b>a</b>). Quantification of the circulating EVs by NTA in response to AMAE in sedentary subjects at steady state (baseline), immediately after physical activity (Post Ex), after 1 h (1 h Post Ex), and 2 h (2 h Post Ex) subsequently the end of exercise (<b>b</b>). The results are represented as mean ± SE. * significant difference compared with baseline (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 5
<p>EV-miRNA quantification using real-time PCR following AMAE at baseline condition, immediately (Post Ex), after physical activity and after 1 (1 h Post Ex), and 2 h (2 h Post Ex) from the end of the exercise. MiRNA expression levels were reported as log2(2^−ΔΔCq). The results are represented as mean ± SE. * significant difference versus baseline (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 6
<p>VO<sub>2max</sub> values measured Pre- and Post-Training; ** significant difference Pre- vs. Post-Training <span class="html-italic">p</span> &lt; 0.01, paired <span class="html-italic">t</span>-test (<b>a</b>). Nanoparticle tracking quantification of the circulating EVs pre- and post-AAT, the results are represented as mean ± SE (<b>b</b>). EV-miRNA quantification using real-time PCR following AAT; miRNA expression levels were reported as log2(2^−ΔΔCq) (<b>c</b>).</p>
Full article ">Figure 7
<p>Size exclusion chromatography separation of EVs from plasma at baseline, Post-Exercise and 1 h Post-Exercise (<b>a</b>). NTA size distribution plot of EVs collected from Fr. 7 (<b>b</b>). Western blot analysis of Fr. 5–Fr. 12 using antibodies against CD9, ApoA4 and BSA (<b>c</b>).</p>
Full article ">Figure 8
<p>MACS plex analysis for each EV marker of circulating vesicles isolated by SEC (Fr. 7) at baseline and following aerobic exercise (immediately and 1 h after the end of exercise bout) (<b>a</b>). Contour plot FSC vs. SSC of EV preparations derived from baseline (left panel) and post-exercise (right panel) samples. Green and blue clusters represent the area of beads sized 500 nm and 1 micron, respectively. Such beads were acquired previously and dispersed in the filtered buffer in which each sample is prepared (see <a href="#app1-ijms-24-03039" class="html-app">Supplementary Materials Figure S2</a>). The red circle represents counting beads (DakoCyto-Count), whereas pink and violet events represent the EVs further characterised for CDs expression (<b>b</b>). Then, a protocol of gating strategy is applied in (<b>b</b>), both on the baseline and post-exercise samples: Violet events (histogram) are those from the area identified using size beads; Pink events (histogram) are those enclosed by P5, drawn in the violet histogram, virtually corresponding to appropriate-sized events, positive for CD81. This histogram focuses on CD45 expression. Green events (histogram) are those enclosed by P6, drawn in the pink histogram, virtually corresponding to appropriate-sized events, positive for CD81, and SGCA and negative for CD45 (<b>d</b>). The absolute counts of CD81<sup>+</sup>/CD45<sup>−</sup>/SGCA + EVs are reported in the subfigure (<b>c</b>). Real-time PCR quantification of mitochondrial (<span class="html-italic">ND1</span> and <span class="html-italic">COX1</span>) and nuclear (<span class="html-italic">36B4</span>) genes in SEC fractions (<b>e</b>) and in Fr. 7 obtained from plasma samples of baseline and 1 h post-exercise subjects (<b>f</b>). The results are represented as mean ± SE. * significant difference from baseline (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 9
<p>Size exclusion chromatography separation of EVs from plasma, separated EVs were quantified using NTA, whereas soluble factors were estimated by using Bradford protein assay (<b>a</b>). Size distribution plot of EVs collected from Fr. 7 and Fr. 13 (<b>b</b>). Partial least squares discriminant (PLS-DA) (<b>c</b>) and orthogonal partial least squares discriminant (OPLS-DA) (<b>d</b>) analyses performed on a partial dataset of EV lipid extracts. (<b>e</b>) Inflammatory effect of vesicular (Fr. 7–8) and soluble (Fr 12–13) factors isolated following acute aerobic exercise; THP-1 cells were incubated for 18 h with circulating factors and mRNA expression levels <span class="html-italic">IL-1β</span>, <span class="html-italic">IL-6</span> and <span class="html-italic">CD163</span> were evaluated by real-time qPCR. ANOVA test followed by Dunnett’s post hoc analysis vs. Ctrl; <span class="html-italic">* p</span> ≤ 0.05; *<span class="html-italic">* p</span> ≤ 0.001; <span class="html-italic"># p</span> ≤ 0.05, <span class="html-italic">### p</span> ≤ 0.001 Fr 7–8 vs. Fr 12–13).</p>
Full article ">
16 pages, 1669 KiB  
Review
Comprehensive Insight into Lichen Planus Immunopathogenesis
by Marijana Vičić, Nika Hlača, Marija Kaštelan, Ines Brajac, Vlatka Sotošek and Larisa Prpić Massari
Int. J. Mol. Sci. 2023, 24(3), 3038; https://doi.org/10.3390/ijms24033038 - 3 Feb 2023
Cited by 36 | Viewed by 11543
Abstract
Lichen planus is a chronic disease affecting the skin, appendages, and mucous membranes. A cutaneous lichen planus is a rare disease occurring in less than 1% of the general population, while oral illness is up to five times more prevalent; still, both forms [...] Read more.
Lichen planus is a chronic disease affecting the skin, appendages, and mucous membranes. A cutaneous lichen planus is a rare disease occurring in less than 1% of the general population, while oral illness is up to five times more prevalent; still, both forms equally impair the patient’s quality of life. The etiology of lichen planus is not entirely understood. Yet, immune-mediated mechanisms have been recognized since environmental factors such as hepatitis virus infection, mechanical trauma, psychological stress, or microbiome changes can trigger the disease in genetically susceptible individuals. According to current understanding, lichen planus immunopathogenesis is caused by cell-mediated cytotoxicity, particularly cytotoxic T lymphocytes, whose activity is further influenced by Th1 and IL-23/Th-17 axis. However, other immunocytes and inflammatory pathways complement these mechanisms. This paper presents a comprehensive insight into the actual knowledge about lichen planus, with the causal genetic and environmental factors being discussed, the immunopathogenesis described, and the principal effectors of its inflammatory circuits identified. Full article
(This article belongs to the Special Issue Recent Advances in Skin Disease and Comorbidities)
Show Figures

Figure 1

Figure 1
<p>Etiological factors involved in the pathogenesis of LP. The disease affects the carrier of predisposing genes, in whom the various environmental factors trigger the immune response disorder resulting in specific LP phenotypes. The influences of genetic, environmental, and immune factors in LP development are dependent and mutually interconnected.</p>
Full article ">Figure 2
<p>LP immunopathogenesis: major effector cells and signaling pathways included in the LP complex inflammatory network. LP inflammation begins as an antigen-directed reaction, finally resulting in the differentiation and activation of effector T lymphocytes. Th1 and Th17 lymphocytes form part of the Th1 and IL-23/Th-17 axis and influence this pathway by secreting key inflammatory cytokines such as IFN-γ and IL-17. At the same time, the key effector CD8+ lymphocytes (Tc1 and Tc17) mediate epidermal injury by the Fas-FasL and TNF-α-TNF-α receptors interaction, but primarily by engaging cytotoxic mechanisms through granule exocytosis. The release of cytotoxic molecules such as perforin, granzyme B, and granulysin causes keratinocyte apoptosis with consequent epidermal and dermal changes and the development of specific LP lesions. Other inflammatory cells such as DCs, macrophages, and NK cells also initiate and maintain the inflammatory process.</p>
Full article ">
18 pages, 9065 KiB  
Review
Hypoxia-Inducible Factor Prolyl Hydroxylase Inhibitors and Iron Metabolism
by Chie Ogawa, Ken Tsuchiya and Kunimi Maeda
Int. J. Mol. Sci. 2023, 24(3), 3037; https://doi.org/10.3390/ijms24033037 - 3 Feb 2023
Cited by 21 | Viewed by 6101
Abstract
The production of erythropoietin (EPO), the main regulator of erythroid differentiation, is regulated by hypoxia-inducible factor (HIF). HIF2α seems to be the principal regulator of EPO transcription, but HIF1α and 3α also may have additional influences on erythroid maturation. HIF is also involved [...] Read more.
The production of erythropoietin (EPO), the main regulator of erythroid differentiation, is regulated by hypoxia-inducible factor (HIF). HIF2α seems to be the principal regulator of EPO transcription, but HIF1α and 3α also may have additional influences on erythroid maturation. HIF is also involved in the regulation of iron, an essential component in erythropoiesis. Iron is essential for the organism but is also highly toxic, so its absorption and retention are strictly controlled. HIF also induces the synthesis of proteins involved in iron regulation, thereby ensuring the availability of iron necessary for hematopoiesis. Iron is a major component of hemoglobin and is also involved in erythrocyte differentiation and proliferation and in the regulation of HIF. Renal anemia is a condition in which there is a lack of stimulation of EPO synthesis due to decreased HIF expression. HIF prolyl hydroxylase inhibitors (HIF-PHIs) stabilize HIF and thereby allow it to be potent under normoxic conditions. Therefore, unlike erythropoiesis-stimulating agents, HIF-PHI may enhance iron absorption from the intestinal tract and iron supply from reticuloendothelial macrophages and hepatocytes into the plasma, thus facilitating the availability of iron for hematopoiesis. The only HIF-PHI currently on the market worldwide is roxadustat, but in Japan, five products are available. Clinical studies to date in Japan have also shown that HIF-PHIs not only promote hematopoiesis, but also decrease hepcidin, the main regulator of iron metabolism, and increase the total iron-binding capacity (TIBC), which indicates the iron transport capacity. However, concerns about the systemic effects of HIF-PHIs have not been completely dispelled, warranting further careful monitoring. Full article
(This article belongs to the Special Issue Iron Metabolism in Health and Disease)
Show Figures

Figure 1

Figure 1
<p>Differentiation process of erythroid cells. BFU-E, burst-forming unit-erythroid; CFU-E, colony-forming unit-erythroid. <span class="html-fig-inline" id="ijms-24-03037-i001"><img alt="Ijms 24 03037 i001" src="/ijms/ijms-24-03037/article_deploy/html/images/ijms-24-03037-i001.png"/></span>, effect of HIF1α; <span class="html-fig-inline" id="ijms-24-03037-i002"><img alt="Ijms 24 03037 i002" src="/ijms/ijms-24-03037/article_deploy/html/images/ijms-24-03037-i002.png"/></span>, effect of HIF2α; <span class="html-fig-inline" id="ijms-24-03037-i003"><img alt="Ijms 24 03037 i003" src="/ijms/ijms-24-03037/article_deploy/html/images/ijms-24-03037-i003.png"/></span>, indirect effect of HIF2α.</p>
Full article ">Figure 2
<p>General iron metabolism. Tf, transferrin; TfR1, transferrin receptor1 (<span class="html-fig-inline" id="ijms-24-03037-i004"><img alt="Ijms 24 03037 i004" src="/ijms/ijms-24-03037/article_deploy/html/images/ijms-24-03037-i004.png"/></span>); FPN, ferroportin (<span class="html-fig-inline" id="ijms-24-03037-i005"><img alt="Ijms 24 03037 i005" src="/ijms/ijms-24-03037/article_deploy/html/images/ijms-24-03037-i005.png"/></span>). <span class="html-fig-inline" id="ijms-24-03037-i006"><img alt="Ijms 24 03037 i006" src="/ijms/ijms-24-03037/article_deploy/html/images/ijms-24-03037-i006.png"/></span>, Hepcidin; <span class="html-fig-inline" id="ijms-24-03037-i007"><img alt="Ijms 24 03037 i007" src="/ijms/ijms-24-03037/article_deploy/html/images/ijms-24-03037-i007.png"/></span>, effect of HIF1α; <span class="html-fig-inline" id="ijms-24-03037-i008"><img alt="Ijms 24 03037 i008" src="/ijms/ijms-24-03037/article_deploy/html/images/ijms-24-03037-i008.png"/></span>, effect of HIF2α; <span class="html-fig-inline" id="ijms-24-03037-i009"><img alt="Ijms 24 03037 i009" src="/ijms/ijms-24-03037/article_deploy/html/images/ijms-24-03037-i009.png"/></span>, indirect effect of HIF2α.</p>
Full article ">Figure 3
<p>Intestinal epithelium (<b>a</b>) and cellular iron metabolism (<b>b</b>). DCYTB, duodenal cytochrome B; DMT1, divalent metal transporter 1; HCP1, heme carrier protein1; FPN, ferroportin; LIP, labile iron pool; Tf, transferrin; TfR1, transferrin receptor 1 (<span class="html-fig-inline" id="ijms-24-03037-i010"><img alt="Ijms 24 03037 i010" src="/ijms/ijms-24-03037/article_deploy/html/images/ijms-24-03037-i010.png"/></span>); ZIP14, ZRT/IRT-like protein 14; PCBP, poly(rC)-binding protein; NCOA4, nuclear receptor co-activator; STEAP3, 6-transmembrane epithelial antigen of the prostate; NIBI, non-transferrin-bound iron; <span class="html-fig-inline" id="ijms-24-03037-i011"><img alt="Ijms 24 03037 i011" src="/ijms/ijms-24-03037/article_deploy/html/images/ijms-24-03037-i011.png"/></span>, Hepcidin; <span class="html-fig-inline" id="ijms-24-03037-i012"><img alt="Ijms 24 03037 i012" src="/ijms/ijms-24-03037/article_deploy/html/images/ijms-24-03037-i012.png"/></span>, effect of HIF1α; <span class="html-fig-inline" id="ijms-24-03037-i013"><img alt="Ijms 24 03037 i013" src="/ijms/ijms-24-03037/article_deploy/html/images/ijms-24-03037-i013.png"/></span>, effect of HIF2α; <span class="html-fig-inline" id="ijms-24-03037-i014"><img alt="Ijms 24 03037 i014" src="/ijms/ijms-24-03037/article_deploy/html/images/ijms-24-03037-i014.png"/></span>, effect of HIF1α + HIF 2α; <span class="html-fig-inline" id="ijms-24-03037-i015"><img alt="Ijms 24 03037 i015" src="/ijms/ijms-24-03037/article_deploy/html/images/ijms-24-03037-i015.png"/></span>, indirect effect of HIF2α.</p>
Full article ">Figure 4
<p>IRE–IRP system. When an IRP binds to an IRE in the 5′ untranslated region (5′ UTR), translation is inhibited, whereas when it binds to an IRE in the 3′ UTR, mRNA stability is increased and translation is enhanced. IRPs are activated and bind to IREs only under iron deficiency. Proteins with IREs in the 5′ UTR include ferritin, ferroportin, ARAS2, and ACO2. Proteins with IREs in the 3′ UTR include transferrin receptor and DMT1. ARAS2, erythroid-specific delta-aminolevulinate synthase; ACO2, mitochondrial aconitase 2; IRE, iron-responsive element; IRP, iron regulatory protein.</p>
Full article ">
14 pages, 2505 KiB  
Article
SARS-CoV-2 Spike Protein Activates Human Lung Macrophages
by Francesco Palestra, Remo Poto, Renato Ciardi, Giorgia Opromolla, Agnese Secondo, Valentina Tedeschi, Anne Lise Ferrara, Rosa Maria Di Crescenzo, Maria Rosaria Galdiero, Leonardo Cristinziano, Luca Modestino, Gianni Marone, Alfonso Fiorelli, Gilda Varricchi and Stefania Loffredo
Int. J. Mol. Sci. 2023, 24(3), 3036; https://doi.org/10.3390/ijms24033036 - 3 Feb 2023
Cited by 11 | Viewed by 3860
Abstract
COVID-19 is a viral disease caused by SARS-CoV-2. This disease is characterized primarily, but not exclusively, by respiratory tract inflammation. SARS-CoV-2 infection relies on the binding of spike protein to ACE2 on the host cells. The virus uses the protease TMPRSS2 as an [...] Read more.
COVID-19 is a viral disease caused by SARS-CoV-2. This disease is characterized primarily, but not exclusively, by respiratory tract inflammation. SARS-CoV-2 infection relies on the binding of spike protein to ACE2 on the host cells. The virus uses the protease TMPRSS2 as an entry activator. Human lung macrophages (HLMs) are the most abundant immune cells in the lung and fulfill a variety of specialized functions mediated by the production of cytokines and chemokines. The aim of this project was to investigate the effects of spike protein on HLM activation and the expression of ACE2 and TMPRSS2 in HLMs. Spike protein induced CXCL8, IL-6, TNF-α, and IL-1β release from HLMs; promoted efficient phagocytosis; and induced dysfunction of intracellular Ca2+ concentration by increasing lysosomal Ca2+ content in HLMs. Microscopy experiments revealed that HLM tracking was affected by spike protein activation. Finally, HLMs constitutively expressed mRNAs for ACE2 and TMPRSS2. In conclusion, during SARS-CoV-2 infection, macrophages seem to play a key role in lung injury, resulting in immunological dysfunction and respiratory disease. Full article
(This article belongs to the Special Issue 25th Anniversary of IJMS: Advances in Biochemistry)
Show Figures

Figure 1

Figure 1
<p>Effects of spike protein on cytokine and chemokine release from human lung macrophages (HLMs). HLMs (1 × 10<sup>6</sup> cells/well) were incubated (18 h, 37 °C) with complete medium (CTR), or increasing concentrations of spike protein (0.01–10 μg/mL), or LPS (1 μg/mL). CXCL8 (<b>A</b>), IL-6 (<b>B</b>), TNF-α (<b>C</b>), and IL-1β (<b>D</b>) proteins in supernatants were evaluated by ELISA. Data are the mean ± SD of 8 experiments obtained from different donors. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001 vs. CTR.</p>
Full article ">Figure 2
<p>Effect of polymixin B on spike protein and LPS-induced release of CXCL8 and IL-1β from HLMs. HLMs were incubated (37 °C, 5% CO<sub>2</sub>, 16 h) with medium alone (CTR), spike protein (1 µg/mL), or LPS (1 µg/mL) either in the absence or in the presence of polymyxin B (50 µg/mL). Data are the mean ± SD of 3 experiments obtained from different donors. CXCL8 (<b>A</b>) and IL-1β (<b>B</b>) proteins in supernatants were evaluated by ELISA. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001 vs. respective untreated (CTR) § <span class="html-italic">p</span> &lt; 0.05 vs. LPS alone.</p>
Full article ">Figure 3
<p>Effects of spike protein genes expression in human lung macrophages (HLMs). HLMs (3 × 10<sup>6</sup> cells/well) were incubated (6 h, 37 °C) with complete media (CTR) or spike protein (1 μg/mL). At the end of incubation, HLMs were lysed and RNA was extracted. mRNA expression for CXCL8 (<b>A</b>), IL-6 (<b>B</b>), TNF-α (<b>C</b>), and IL-1β (<b>D</b>) was evaluated by quantitative RT-PCR. The red dotted line for each panel represents the control values. Data are the mean ± SD of 4 experiments obtained from different donors.</p>
Full article ">Figure 4
<p>Effects of spike protein on cytosolic and lysosomal Ca<sup>2+</sup> levels in human lung macrophages (HLMs). (<b>A</b>) Representative traces showing the effect of GPN (300 µM) on intracellular Ca<sup>2+</sup> concentration [Ca<sup>2+</sup>]<sub>i</sub>) in HLMs stimulated (18 h, 37 °C) with RPMI alone (CTR) or spike protein (1 μg/mL). [Ca<sup>2+</sup>]<sub>i</sub> was determined by a single-cell computer-assisted video imaging system. The insert depicts representative bright-field and ratiometric images of the HLMs loaded with Fura-2. (<b>B</b>) Bar graph depicting the quantification of [Ca<sup>2+</sup>]<sub>i</sub> increase after GPN perfusion (300 µM). Each bar represents the mean ± SE (n = 15 cells for each treatment studied in three different experimental sessions). * <span class="html-italic">p</span> &lt; 0.05 vs. CTR. (<b>C</b>) Bar graph depicting the basal values of [Ca<sup>2+</sup>]<sub>i</sub> in CTR- and spike protein-activated HLMs. Each bar represents the mean ± SE (n = 25 cells for each treatment studied in three different experimental sessions). * <span class="html-italic">p</span> &lt; 0.05 vs. CTR.</p>
Full article ">Figure 5
<p>Effects of spike protein on kinetic properties of human lung macrophages (HLMs). HLMs (150 × 10<sup>3</sup> cells/well) were incubated (6 h, 37 °C) with RPMI alone (CTR) or spike protein (1 μg/mL). The incubation was carried out with time-lapse and high-content microscopy Operetta High-Content Imaging System (PerkinElmer) to investigate the tracking characteristics as current displacement X (<b>A</b>), displacement X mean per well (<b>B</b>), current displacement Y (<b>C</b>), displacement Y mean per well (<b>D</b>), current square displacement (<b>E</b>), current speed (<b>F</b>) and speed mean per well (<b>G</b>). Data are the mean ± SD of 5 experiments obtained from different donors. * <span class="html-italic">p</span> &lt; 0.05.</p>
Full article ">Figure 6
<p>Effects of spike protein on human lung macrophages (HLMs) phagocytosis. HLMs (1 × 10<sup>6</sup> cells/well) were incubated (37 °C, 5% CO<sub>2</sub>) with RPMI alone (CTR), and with spike protein (1 µg/mL) (<b>A</b>), or LPS (1 µg/mL) (<b>B</b>) one day before phagocytosis assay. The day after, the cell culture medium was removed and pHrodo™ Green <span class="html-italic">E. coli</span> BioParticles™ Conjugate suspension was added to the wells. The plate was placed in an EnSpire Multimode Plate Reader (PerkinElmer). The data were expressed as Relative Fluorescence Units (RFU) measured up to 3 h with a 1 h span at an excitation wavelength of 509 nm, and emission at 533 nm. Data are the mean ± SD of 5 experiments obtained from different donors. * <span class="html-italic">p</span> &lt; 0.05 when compared to the corresponding value of CTR.</p>
Full article ">Figure 7
<p>Constitutive expression of ACE2 and TMPRSS2 mRNAs in human lung macrophages (HLMs). HLMs (5 × 10<sup>6</sup> cells) were lysed and RNA was extracted. ACE2 and TMPRSS2 mRNAs were determined by quantitative RT-PCR (<b>A</b>). HLMs (5 × 10<sup>6</sup> cells/well) were incubated (6 h, 37 °C) with complete media (CTR), or spike protein (1 μg/mL). At the end of incubation, HLMs were lysed and RNA was extracted. mRNAs expression for ACE2 (<b>B</b>) and TMPRSS2 (<b>C</b>) was evaluated by quantitative RT-PCR. The red dotted line for each panel represents the control values. Data are the mean ± SD of 4 experiments obtained from different donors.</p>
Full article ">
15 pages, 15975 KiB  
Article
Supt16 Haploinsufficiency Impairs PI3K/AKT/mTOR/Autophagy Pathway in Human Pluripotent Stem Cells Derived Neural Stem Cells
by Junwen Wang, Ziyi Wang, Limeng Dai, Xintong Zhu, Xingying Guan, Junyi Wang, Jia Li, Mao Zhang, Yun Bai and Hong Guo
Int. J. Mol. Sci. 2023, 24(3), 3035; https://doi.org/10.3390/ijms24033035 - 3 Feb 2023
Cited by 2 | Viewed by 2754
Abstract
The maintenance of neural stem cells (NSCs) plays a critical role in neurodevelopment and has been implicated in neurodevelopmental disorders (NDDs). However, the underlying mechanisms linking defective human neural stem cell self-renewal to NDDs remain undetermined. Our previous study found that Supt16 haploinsufficiency [...] Read more.
The maintenance of neural stem cells (NSCs) plays a critical role in neurodevelopment and has been implicated in neurodevelopmental disorders (NDDs). However, the underlying mechanisms linking defective human neural stem cell self-renewal to NDDs remain undetermined. Our previous study found that Supt16 haploinsufficiency causes cognitive and social behavior deficits by disrupting the stemness maintenance of NSCs in mice. However, its effects and underlying mechanisms have not been elucidated in human neural stem cells (hNSCs). Here, we generated Supt16+/− induced pluripotent stem cells (iPSCs) and induced them into hNSCs. The results revealed that Supt16 heterozygous hNSCs exhibit impaired proliferation, cell cycle arrest, and increased apoptosis. As the RNA-seq analysis showed, Supt16 haploinsufficiency inhibited the PI3K/AKT/mTOR pathway, leading to rising autophagy, and further resulted in the dysregulated expression of multiple proteins related to cell proliferation and apoptotic process. Furthermore, the suppression of Supt16 heterozygous hNSC self-renewal caused by autophagy activation could be rescued by MHY1485 treatment or reproduced in rapamycin-treated hNSCs. Thus, our results showed that Supt16 was essential for hNSC self-renewal and its haploinsufficiency led to cell cycle arrest, impaired cell proliferation, and increased apoptosis of hNSCs by regulating the PI3K/AKT/mTOR/autophagy pathway. These provided a new insight to understand the causality between the Supt16 heterozygous NSCs and NDDs in humans. Full article
Show Figures

Figure 1

Figure 1
<p><span class="html-italic">Supt16</span> haploinsufficiency disrupts the self−renewal of human iPSC−derived NSCs. (<b>A</b>) Sanger sequencing of <span class="html-italic">Supt16</span> heterozygous hNSCs clone after CRISPR/Cas9−mediated. (<b>B</b>) <span class="html-italic">Supt16</span><sup>+/−</sup> hNSCs exhibit a point mutation in the form of an adenine nucleotide insertion (red hyphen). (<b>C</b>) Representative pictures of neural rosettes derived from <span class="html-italic">Supt16</span><sup>+/−</sup> haploinsufficiency and wild-type iPSCs; scale bar, 100 μm. (<b>D</b>) Representative immunofluorescence images of EdU incorporation assay (<span class="html-italic">n</span> = 3 samples per genotype. Green: EdU−positive cells. Blue: DAPI. Scale bar, 100 μm). (<b>E</b>) Representative flow cytometry analysis picture of hNSCs cell cycle (left). Quantitative analysis of hNSCs cell cycle distribution (right) (<span class="html-italic">n</span> = 3 samples of each genotype). (<b>F</b>) Representative flow cytometry analysis picture and quantification of hNSCs apoptotic rate (<span class="html-italic">n</span> = 3 samples of each genotype). The error bars represented the mean ± SD and the significance level was calculated by Student’s t−test (two−tailed, equal variance) (ns means not statistically significant, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01).</p>
Full article ">Figure 2
<p><span class="html-italic">Supt16</span> haploinsufficiency impaired hNSC self−renewal by activating PI3K/AKT/mTOR−mediated autophagy. (<b>A</b>) Volcano plots showed all differential expression genes detected by DESeq2 in <span class="html-italic">Supt16</span> heterozygous hNSCs. Each point represents an individual gene, of which 1629 genes are upregulated and 1976 genes are downregulated (p−value &lt; 0.05; |log2foldchange| &gt; 1). <span class="html-italic">n</span> = 3. (<b>B</b>) KEGG pathway analysis found that differential expression genes in <span class="html-italic">Supt16</span><sup>+/−</sup> hNSCs are enriched in the PI3K/AKT signaling pathway. (<b>C</b>) Heatmap analysis of PI3K/AKT signaling pathway−related differential expression genes enriched in KEGG analysis. (<b>D</b>) GSEA plot of differentially expressed genes for the list of mTOR signaling pathway genes (NES, normalized enrichment score; FDR, false discovery rate. NES = −1.79, FDR = 0.055). (<b>E</b>) GSEA analysis showing the expression pattern of autophagy−related genes in WT and <span class="html-italic">Supt16</span><sup>+/−</sup> hNSCs (NES, normalized enrichment score; FDR, false discovery rate. NES = 1.358, FDR = 0.254). (<b>F</b>) Western blot analysis showing AKT, P−akt, P−mTOR, and LC3 expression in hNSCs treated with different treatments (<span class="html-italic">n</span> = 3 samples per genotype). (<b>G</b>) Quantification analysis of AKT and P−akt protein relative to GAPDH. Data are means ± standard deviation of three independent experiments. (<b>H</b>) The P−mTOR expression was calculated relative to GAPDH. Data are means ± standard deviation of three independent experiments. (<b>I</b>) Quantification of LC3 protein relative to GAPDH. Data are means ± standard deviation of three independent experiments. The error bars represented the mean ± SD and the significance level was calculated by Student’s t-test (two-tailed, equal variance) (ns means not statistically significant, ** <span class="html-italic">p</span> &lt; 0.01).</p>
Full article ">Figure 3
<p>Wild−type hNSCs treated by rapamycin reproduced the phenotype of <span class="html-italic">Supt16</span> haploinsufficient hNSCs. (<b>A</b>) Western blot analysis showing P−mTOR, LC3, PAX6, SOX2, and P53 protein expression in hNSCs treated with different treatments (<span class="html-italic">n</span> = 3). (<b>B</b>) Quantification analysis of P−mTOR, LC3I protein relative to GAPDH. Data are means ± standard deviation of three independent experiments. (<b>C</b>) Quantification analysis of LC3II and LC3II/LC3I protein relative to GAPDH. Data are means ± standard deviation of three independent experiments. (<b>D</b>) Quantification analysis of PAX6 and SOX2 proteins relative to GAPDH. Data are means ± standard deviation of three independent experiments. (<b>E</b>) Quantification of P53 protein relative to GAPDH. Data are means ± standard deviation of three independent experiments. (<b>F</b>) Immunofluorescence staining showed that the absence of <span class="html-italic">Supt16</span> in hNSCs suppressed the proliferation. Rapamycin treatment reproduced the inhibitory effect of <span class="html-italic">Supt16</span> haploinsufficiency on the proliferation of hNSCs. (<b>G</b>) Cell cycle analysis using PI staining in WT, <span class="html-italic">Supt16</span> heterozygous and rapamycin-treated WT hNSCs (<span class="html-italic">n</span> = 3). The different cell cycle phases were calculated in FlowJo (v10.4.0). The error bars represented the mean ± SD and the significance level was calculated by Student’s t-test (two-tailed, equal variance) (ns means not statistically significant, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01).</p>
Full article ">Figure 4
<p>MHY1485 treatment rescued the phenotypes of <span class="html-italic">Supt16</span> haploinsufficient hNSCs. (<b>A</b>) Western blot analysis showed the protein expressions of P−mTOR, LC3, PAX6, and SOX2 in hNSCs treated with different treatments. (<b>B</b>) Representative quantification analysis of P−mTOR and LC3I in different hNSCs. (<b>C</b>) Quantification analysis of LC3II and LC3II/LC3I in different hNSCs. Data are means ± standard deviation of three independent experiments. (<b>D</b>) Quantification analysis of PAX6 and SOX2 in different hNSCs. Data are means ± standard deviation of three independent experiments. (<b>E</b>) Cell cycle analysis performed by flow cytometry to calculate the distribution of cell cycle phase (<span class="html-italic">n</span> = 3). (<b>F</b>) Flow cytometric analysis using PI and Annexin−V double staining showed the cell apoptotic rate in hNSCs treated with different treatments (<span class="html-italic">n</span> = 3). The error bars represented the mean ± SD and the significance level was calculated by Student’s t-test (two-tailed, equal variance) (ns means not statistically significant, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01).</p>
Full article ">
25 pages, 3542 KiB  
Article
Effects of a Novel Infant Formula on the Fecal Microbiota in the First Six Months of Life: The INNOVA 2020 Study
by Francisco Javier Ruiz-Ojeda, Julio Plaza-Diaz, Javier Morales, Guillermo Álvarez-Calatayud, Eric Climent, Ángela Silva, Juan F. Martinez-Blanch, María Enrique, Marta Tortajada, Daniel Ramon, Beatriz Alvarez, Empar Chenoll and Ángel Gil
Int. J. Mol. Sci. 2023, 24(3), 3034; https://doi.org/10.3390/ijms24033034 - 3 Feb 2023
Cited by 5 | Viewed by 4062
Abstract
Exclusive breastfeeding is highly recommended for infants for at least the first six months of life. However, for some mothers, it may be difficult or even impossible to do so. This can lead to disturbances in the gut microbiota, which in turn may [...] Read more.
Exclusive breastfeeding is highly recommended for infants for at least the first six months of life. However, for some mothers, it may be difficult or even impossible to do so. This can lead to disturbances in the gut microbiota, which in turn may be related to a higher incidence of acute infectious diseases. Here, we aimed to evaluate whether a novel starting formula versus a standard formula provides a gut microbiota composition more similar to that of breastfed infants in the first 6 months of life. Two hundred and ten infants (70/group) were enrolled in the study and completed the intervention until 12 months of age. For the intervention period, infants were divided into three groups: Group 1 received formula 1 (INN) with a lower amount of protein, a proportion of casein to whey protein ratio of about 70/30 by increasing the content of α-lactalbumin, and with double the amount of docosahexaenoic acid/arachidonic acid than the standard formula; INN also contained a thermally inactivated postbiotic (Bifidobacterium animalis subsp. lactis). Group 2 received the standard formula (STD) and the third group was exclusively breastfed (BF) for exploratory analysis. During the study, visits were made at 21 days, 2, 4, and 6 months of age, with ±3 days for the visit at 21 days of age, ±1 week for the visit at 2 months, and ±2 weeks for the others. Here, we reveal how consuming the INN formula promotes a similar gut microbiota composition to those infants that were breastfed in terms of richness and diversity, genera, such as Bacteroides, Bifidobacterium, Clostridium, and Lactobacillus, and calprotectin and short-chain fatty acid levels at 21 days, 2 and 6 months. Furthermore, we observed that the major bacteria metabolic pathways were more alike between the INN formula and BF groups compared to the STD formula group. Therefore, we assume that consumption of the novel INN formula might improve gut microbiota composition, promoting a healthier intestinal microbiota more similar to that of an infant who receives exclusively human milk. Full article
Show Figures

Figure 1

Figure 1
<p>Description of the global balance for groups. The two groups of taxa that form the global balance are specified at the top of the plot. The box plot represents the distribution of the balance scores for INN and BF group (<b>A</b>), STD and BF groups (<b>B</b>), and INN and STD groups (<b>C</b>). The right part of the figure contains the ROC curve with its AUC (mean area under the ROC curve) value and the density curve for each group.</p>
Full article ">Figure 1 Cont.
<p>Description of the global balance for groups. The two groups of taxa that form the global balance are specified at the top of the plot. The box plot represents the distribution of the balance scores for INN and BF group (<b>A</b>), STD and BF groups (<b>B</b>), and INN and STD groups (<b>C</b>). The right part of the figure contains the ROC curve with its AUC (mean area under the ROC curve) value and the density curve for each group.</p>
Full article ">Figure 2
<p>Secretory IgA and calprotectin in feces, including INNOVA formula (INN), standard formula (STD), and breastfeeding (BF) at 21 days, 2 months, and 6 months. (<b>A</b>) IgA; (<b>B</b>) Calprotectin. **** <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 3
<p>Lactate, acetate, propionate, and butyrate in feces, including INNOVA formula (INN), standard formula (STD), and breastfeeding (BF) at 21 days, 2 months, and 6 months. (<b>A</b>) Lactate, (<b>B</b>) Acetate, (<b>C</b>) Propionate, (<b>D</b>) Butyrate, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 and **** <span class="html-italic">p</span> &lt; 0.001.</p>
Full article ">Figure 3 Cont.
<p>Lactate, acetate, propionate, and butyrate in feces, including INNOVA formula (INN), standard formula (STD), and breastfeeding (BF) at 21 days, 2 months, and 6 months. (<b>A</b>) Lactate, (<b>B</b>) Acetate, (<b>C</b>) Propionate, (<b>D</b>) Butyrate, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 and **** <span class="html-italic">p</span> &lt; 0.001.</p>
Full article ">Figure 4
<p>Major metabolic pathway categories relative to the abundance of each sample, including INNOVA formula (INN), standard formula (STD), and breastfeeding (BF). (<b>A</b>) NAD biosynthesis (21 days), and Catechol degradation (21 days), (<b>B</b>) Octane oxidation (2 months) and (S)-propane-1,2-diol deg (2 months), (<b>C</b>) NAD biosynthesis (6 months), dTDP-N-acetylthomosamine biosynthesis (6 months), L-Tryptophan biosynthesis, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 and **** <span class="html-italic">p</span> &lt; 0.001.</p>
Full article ">
19 pages, 6230 KiB  
Article
Identification of Key Biomarkers Associated with Immunogenic Cell Death and Their Regulatory Mechanisms in Severe Acute Pancreatitis Based on WGCNA and Machine Learning
by Zhengjian Wang, Jin Liu, Yuting Wang, Hui Guo, Fan Li, Yinan Cao, Liang Zhao and Hailong Chen
Int. J. Mol. Sci. 2023, 24(3), 3033; https://doi.org/10.3390/ijms24033033 - 3 Feb 2023
Cited by 24 | Viewed by 5515
Abstract
Immunogenic cell death (ICD) is a form of programmed cell death with a strong sense of inflammatory detection, whose powerful situational awareness can cause the reactivation of aberrant immunity. However, the role of ICD in the pathogenesis of severe acute pancreatitis (SAP) has [...] Read more.
Immunogenic cell death (ICD) is a form of programmed cell death with a strong sense of inflammatory detection, whose powerful situational awareness can cause the reactivation of aberrant immunity. However, the role of ICD in the pathogenesis of severe acute pancreatitis (SAP) has yet to be investigated. This study aims to explore the pivotal genes associated with ICD in SAP and how they relate to immune infiltration and short-chain fatty acids (SCFAs), in order to provide a theoretical foundation for further, in-depth mechanistic studies. We downloaded GSE194331 datasets from the Gene Expression Omnibus (GEO). The use of differentially expressed gene (DEG) analysis; weighted gene co-expression network analysis (WGCNA) and least absolute shrinkage and selection operator (LASSO) regression analysis allowed us to identify a total of three ICD-related hub genes (LY96, BCL2, IFNGR1) in SAP. Furthermore, single sample gene set enrichment analysis (ssGSEA) demonstrated that hub genes are closely associated with the infiltration of specific immune cells, the activation of immune pathways and the metabolism of SCFAs (especially butyrate). These findings were validated through the analysis of gene expression patterns in both clinical patients and rat animal models of SAP. In conclusion, the first concept of ICD in the pathogenesis of SAP was proposed in our study. This has important implications for future investigations into the pro-inflammatory immune mechanisms mediated by damage-associated molecular patterns (DAMPs) in the late stages of SAP. Full article
(This article belongs to the Special Issue Immune Factors, Immune Cells and Inflammatory Diseases)
Show Figures

Figure 1

Figure 1
<p>Volcano plot showing DEGs in SAP patients versus healthy controls (<b>A</b>) and the heatmap of TOP20 differential genes (upregulated and downregulated, (<b>B</b>)).</p>
Full article ">Figure 2
<p>Construction of the co-expression network. (<b>A</b>) The sample dendrogram and feature heat map were drawn based on the Euclidean distance using the average clustering method for hierarchical clustering of samples, with each branch representing a sample, Height in the vertical coordinate being the clustering distance, and the horizontal coordinate being the clinical grouping information. (<b>B</b>) Soft threshold (power = 20) and scale-free topology fit index (R<sup>2</sup> = 0.89). (<b>C</b>) Histogram of connectivity distribution. The scale-free topology is checked at a soft threshold of 20. (<b>D</b>) Gene hierarchy tree-clustering diagram. The graph indicates different genes horizontally and the uncorrelatedness between genes vertically, the lower the branch, the less uncorrelated the genes within the branch, i.e., the stronger the correlation. (<b>E</b>) Heatmap showing the relations between the module and SAP features. The values in the small cells of the graph represent the two-calculated correlation values cor coefficients between the eigenvalues of each trait and each module as well as the corresponding statistically significant <span class="html-italic">p</span>-values. Color corresponds to the size of the correlation; the darker the red, the more positive the correlation; the darker the green, the more negative the correlation. (<b>F</b>) Scatter plot between gene salience (GS) and module members (MM) in turquoise.</p>
Full article ">Figure 3
<p>Screening for ICD-related signature genes in SAP and functional enrichment analysis. (<b>A</b>) Venn diagram of the intersection of DEGs, turquoise module genes, and ICD-related genes. (<b>B</b>) GO functional annotation of signature genes. (<b>C</b>) Functional annotation of the Kegg signaling pathway of signature genes. For all enriched GO and KEGG terms, <span class="html-italic">p</span> &lt; 0.05.</p>
Full article ">Figure 4
<p>The final hub genes were identified by LASSO regression analysis. (<b>A</b>) Path diagram of the LASSO coefficients for the three hub genes in SAP. Each curve represents the trajectory of each hub gene, the vertical coordinate is the value of the gene, the lower horizontal coordinate is log(λ), and the upper horizontal coordinate is the number of non-zero hub genes in the model at this time. (<b>B</b>) LASSO regression cross-validation curve. Optimal λ values were determined using 10-fold cross-validation.</p>
Full article ">Figure 5
<p>Validation of the importance of ICD in the pathogenesis of SAP through the hub gene. (<b>A</b>–<b>C</b>) Expression levels of three hub genes in SAP patients compared with healthy controls, *** <span class="html-italic">p</span> &lt; 0.01. (<b>D</b>–<b>F</b>) ROC analysis of three hub genes. (<b>G</b>) Nomogram for measuring the significance of ICD in SAP based on hub genes. (<b>H</b>) Calibration curve plot for the nomogram. The X-axis represents the predictable probability, and the Y-axis represents the actual probability. Perfect prediction corresponds to the ideal dashed line. The apparent dashed line represents the entire queue, bias-corrected solid line is bias-corrected by bootstrapping (1000 repetitions) and represents the observed performance of the nomogram.</p>
Full article ">Figure 6
<p>Analysis of immune infiltration in SAP patient samples and its correlation with hub genes using ssGSEA. (<b>A</b>) Heat map showing the immune scores of 26 immune cells. Red indicates immune cell infiltration and blue indicates suppressed immune cells. (<b>B</b>) Violin plot showing immune scores of 26 immune cells in SAP patients and healthy controls. (<b>C</b>) Correlation between immune cell infiltration and three hub genes. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
Full article ">Figure 7
<p>Analysis of immune functions in SAP patient samples and their correlation with hub genes using ssGSEA. (<b>A</b>) Heatmap showing immune scores for 10 immune functions in SAP patients and healthy controls. Red indicates activation of this immune function, green indicates functional inhibition. (<b>B</b>) Violin plot showing immune scores for 10 immune functions in SAP patients and healthy controls. (<b>C</b>) Association between immune cell function and three hub genes; * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
Full article ">Figure 8
<p>Correlation of hub genes with SCFAs in SAP patient samples analyzed using ssGSEA. (<b>A</b>–<b>C</b>) Lollipop plots of three hub genes with genes related to the metabolism of SCFAs. (<b>D</b>–<b>F</b>) Lollipop plots of three hub genes and the star pathway associated with the metabolism of SCFAs. (<b>G</b>–<b>I</b>) Molecular docking assemblies of three hub genes interacting with butyric acid. Hub genes (<span class="html-italic">LY96</span>, <span class="html-italic">BCL2</span>, <span class="html-italic">IFNGR1</span>) interact with butyric acid mainly through hydrogen bonding and hydrophobic forces, with binding energies of −3.9 kcal/mol, −3.5 kcal/mol, and −3.9 kcal/mol, respectively. The lower the binding energy, the stronger the stability.</p>
Full article ">Figure 9
<p>Clinical and animal experimental validation of ICD-related hub genes. (<b>A</b>) Relative mRNA expression of the three hub genes in SAP patients versus healthy controls; (<b>B</b>) Representative HE-stained micrographs of the pancreas and lungs (original magnification ×100 and ×200); (<b>C</b>–<b>E</b>) Serum expressional levels of α-amylase, IL-1β, TNF-α by ELISA. (<b>F</b>) Immunohistochemical plots showing hub genes in SAP rats and controls (original magnification ×100 and ×200); (<b>F</b>) Semiquantitative results of hub genes based on immunohistochemistry. (<b>G</b>) Immunohistochemical plots showing hub genes in SAP rats and controls (original magnification ×100 and ×200). Data are shown as mean ± SEM, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
Full article ">Figure 10
<p>The study flowchart of the whole experiment. GSE, gene expression omnibus series; WGCNA, weighted gene co-expression network analysis; DEGs, differentially expressed genes; ICD, immunogenic cell death; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; LASSO, least absolute shrinkage and selection operator; SCFAs, short-chain fatty acids; ssGSEA, single sample gene set enrichment analysis; IHC, immunohistochemistry.</p>
Full article ">
9 pages, 885 KiB  
Article
MicroRNA Expression in Subretinal Fluid in Eyes Affected by Rhegmatogenous Retinal Detachment
by Paolo Carpineto, Ester Sara Di Filippo, Agbeanda Aharrh Gnama, Danilo Bondi, Carla Iafigliola, Arturo Maria Licata and Stefania Fulle
Int. J. Mol. Sci. 2023, 24(3), 3032; https://doi.org/10.3390/ijms24033032 - 3 Feb 2023
Cited by 3 | Viewed by 1700
Abstract
Proliferative vitreoretinopathy (PVR) is an abnormal intraocular scarring process that can complicate cases of rhegmatogenous retinal detachment (RRD). Although previous studies have examined the relevance of microRNAs (miRNAs) in ophthalmic diseases, only a few studies have evaluated the expression profiles of microRNAs in [...] Read more.
Proliferative vitreoretinopathy (PVR) is an abnormal intraocular scarring process that can complicate cases of rhegmatogenous retinal detachment (RRD). Although previous studies have examined the relevance of microRNAs (miRNAs) in ophthalmic diseases, only a few studies have evaluated the expression profiles of microRNAs in subretinal fluid. We hypothesized that the expression profiles of specific miRNAs may change in response to RRD, in the subretinal fluid that is directly in contact with photoreceptors and the retinal pigment epithelium (RPE). We looked for a potential correlation between the expression of specific miRNAs in eyes with RRD and known clinical risk factors of PVR. A total of 24 patients (59 ± 11 years) who underwent scleral buckling procedure were enrolled in this prospective study. Twenty-four undiluted subretinal fluid samples were collected, RNA was isolated and qRT-PCR was performed to analyze the expression of 12 miRNAs. We found the existence of a positive association between the expression of miR-21 (p = 0.017, r = 0.515) and miR-34 (p = 0.030, r = 0.624) and the duration of symptoms related to retinal detachment. Moreover, the expression of miR-146a tended to decrease in patients who developed PVR. Subretinal fluid constitutes an intriguing biological matrix to evaluate the role of miRNAs leading to the development of PVR. Full article
(This article belongs to the Special Issue Advanced Research in Retina)
Show Figures

Figure 1

Figure 1
<p>Main results from regression analyses; grey area around the linear tendency line is delimited by standard error.</p>
Full article ">Figure 2
<p>The graphs show miRNA expression stratified by severe myopia (on the <b>left</b>) or PVR (on the <b>right</b>); the 12 miRNAs are reported on the <span class="html-italic">x</span>-axis. Blue lines refer to the presence, while green lines indicate the absence, of myopia or PVR. For PVR, miR-96 values are missing because all the analyses in this group resulted in undetermined values.</p>
Full article ">
15 pages, 1419 KiB  
Review
WGS Data Collections: How Do Genomic Databases Transform Medicine?
by Zbigniew J. Król, Paula Dobosz, Antonina Ślubowska and Magdalena Mroczek
Int. J. Mol. Sci. 2023, 24(3), 3031; https://doi.org/10.3390/ijms24033031 - 3 Feb 2023
Cited by 4 | Viewed by 4226
Abstract
As a scientific community we assumed that exome sequencing will elucidate the basis of most heritable diseases. However, it turned out it was not the case; therefore, attention has been increasingly focused on the non-coding sequences that encompass 98% of the genome and [...] Read more.
As a scientific community we assumed that exome sequencing will elucidate the basis of most heritable diseases. However, it turned out it was not the case; therefore, attention has been increasingly focused on the non-coding sequences that encompass 98% of the genome and may play an important regulatory function. The first WGS-based datasets have already been released including underrepresented populations. Although many databases contain pooled data from several cohorts, recently the importance of local databases has been highlighted. Genomic databases are not only collecting data but may also contribute to better diagnostics and therapies. They may find applications in population studies, rare diseases, oncology, pharmacogenetics, and infectious and inflammatory diseases. Further data may be analysed with Al technologies and in the context of other omics data. To exemplify their utility, we put a highlight on the Polish genome database and its practical application. Full article
Show Figures

Figure 1

Figure 1
<p>New databases reported in <span class="html-italic">Nucleic Acids Research</span> database issue in the last 10 years.</p>
Full article ">Figure 2
<p>Number of results of the PubMed search query “Name of database” for two databases described in the review.</p>
Full article ">Figure 3
<p>Sources of genomic data (existing databases) described in the review. Note that not all of the databases mentioned above contain WGS-derived data; some of them were created on the basis of other techniques.</p>
Full article ">
16 pages, 2688 KiB  
Article
Functional Characterization of Lobularia maritima LmTrxh2 Gene Involved in Cold Tolerance in Tobacco through Alleviation of ROS Damage to the Plasma Membrane
by Rania Ben Saad, Walid Ben Romdhane, Narjes Baazaoui, Mohamed Taieb Bouteraa, Yosra Chouaibi, Wissem Mnif, Anis Ben Hsouna and Miroslava Kačániová
Int. J. Mol. Sci. 2023, 24(3), 3030; https://doi.org/10.3390/ijms24033030 - 3 Feb 2023
Cited by 8 | Viewed by 2385
Abstract
Cold stress is a key environmental factor affecting plant growth and development, crop productivity, and geographic distribution. Thioredoxins (Trxs) are small proteins that are ubiquitously expressed in all organisms and implicated in several cellular processes, including redox reactions. However, their role in the [...] Read more.
Cold stress is a key environmental factor affecting plant growth and development, crop productivity, and geographic distribution. Thioredoxins (Trxs) are small proteins that are ubiquitously expressed in all organisms and implicated in several cellular processes, including redox reactions. However, their role in the regulation of cold stress in the halophyte plant Lobularia maritima remains unknown. We recently showed that overexpression of LmTrxh2, which is the gene that encodes the h-type Trx protein previously isolated from L. maritima, led to an enhanced tolerance to salt and osmotic stress in transgenic tobacco. This study functionally characterized the LmTrxh2 gene via its overexpression in tobacco and explored its cold tolerance mechanisms. Results of the RT-qPCR and western blot analyses indicated differential temporal and spatial regulation of LmTrxh2 in L. maritima under cold stress at 4 °C. LmTrxh2 overexpression enhanced the cold tolerance of transgenic tobacco, as evidenced by increased germination rate, fresh weight and catalase (CAT), superoxide dismutase (SOD) and peroxidase (POD) activities; reduced malondialdehyde levels, membrane leakage, superoxide anion (O2), and hydrogen peroxide (H2O2) levels; and higher retention of chlorophyll than in non-transgenic plants (NT). Furthermore, the transcript levels of reactive oxygen species (ROS)-related genes (NtSOD and NtCAT1), stress-responsive late embryogenis abundant protein 5 (NtLEA5), early response to dehydration 10C (NtERD10C), DRE-binding proteins 1A (NtDREB1A), and cold-responsive (COR) genes (NtCOR15A, NtCOR47, and NtKIN1) were upregulated in transgenic lines compared with those in NT plants under cold stress, indicating that LmTrxh2 conferred cold stress tolerance by enhancing the ROS scavenging ability of plants, thus enabling them to maintain membrane integrity. These results suggest that LmTrxh2 promotes cold tolerance in tobacco and provide new insight into the improvement of cold-stress resistance to cold stress in non-halophyte plants and crops. Full article
(This article belongs to the Section Molecular Plant Sciences)
Show Figures

Figure 1

Figure 1
<p><span class="html-italic">LmTrxh2</span> expression profiles and protein accumulation in response to cold stress (4 °C). (<b>A</b>) Pattern of expression of the <span class="html-italic">LmTrxh2</span> gene and (<b>B</b>) the production of LmTrxh2 protein in the leaves and roots of <span class="html-italic">L. maritima</span> plants following the application of cold stress for 48 h. A western blot analysis of the total protein extracts (10 µg) was performed using anti-LmTrxh2 rabbit IgG (H + L) antibodies on leaves and roots tissues. The upper panel shows the detection of LmTrxh2, and the lower panel shows anti-β-actin for loading control. Vertical bars indicate the standard deviation calculated from three replicates. Values are mean ± SEM (<span class="html-italic">n</span> = 3). Different lowercases indicate a significant difference at <span class="html-italic">p</span> &lt; 0.05.</p>
Full article ">Figure 2
<p>Assessment of NT and <span class="html-italic">LmTrxh2</span> transgenic lines performance at germination stage under cold stress conditions. (<b>A</b>) Photographs were taken two weeks after seed germination. (<b>B</b>) Seed germination rates were determined for <span class="html-italic">LmTrxh2</span> overexpressors lines and NT plants under normal (25 °C) and cold stress (4 °C) conditions. The results presented are the means of three independent biological replicates, and a minimum of 30 seeds were counted for each experiment. (<b>C</b>) Comparison of the growth of transgenic and NT plants on plates. Tobacco seedlings were grown vertically for two weeks, and the fresh weight (<b>D</b>) and total chlorophyll content were measured (<b>E</b>) under normal and cold stress conditions. Data are expressed as the mean ± SEM (<span class="html-italic">n</span> = 3). Different lowercases indicate a significant difference at <span class="html-italic">p</span> &lt; 0.05.</p>
Full article ">Figure 3
<p>The <span class="html-italic">LmTrxh2</span> overexpressing plant had increased cold tolerance. (<b>A</b>) The phenotypic appearance of 45-day old seedlings for NT and transgenic plants following the application of cold stress (4 °C) for 7 days, followed by recovery at 25 °C for 15 days. (<b>B</b>) Quantification of MDA, (<b>C</b>) H<sub>2</sub>O<sub>2,</sub> and (<b>D</b>) O<sub>2</sub><sup>−</sup> accumulation in the leaves of NT and transgenic tobacco lines under control or subjected to cold stress (4 °C for 48 h). (<b>E</b>) The electrolyte leakage analysis of NT and <span class="html-italic">LmTrxh2</span> transgenic lines under normal growth conditions and after cold treatment (4 °C for 48 h). The average of three independent experiments ± SEM is shown. Different lowercases indicate a significant difference at <span class="html-italic">p</span> &lt; 0.05.</p>
Full article ">Figure 4
<p>Physiological indices of NT and <span class="html-italic">LmTrxh2</span> transgenic plants under control and cold stress conditions. The leaves were sampled from plants grown under normal growth conditions and plants subjected to 48 h of cold stress (4 °C). (<b>A</b>) NBT and (<b>B</b>) DAB staining of leaves. (<b>C</b>) CAT activity. (<b>D</b>) SOD activity. (<b>E</b>) POD activity. Values are presented as means ± SEM values (<span class="html-italic">n</span> = 3). Different letters indicate a significant difference at <span class="html-italic">p</span> &lt; 0.05.</p>
Full article ">Figure 5
<p>Relative expression of ROS-related (<span class="html-italic">NtSOD</span> and <span class="html-italic">NtCAT1</span>) and cold-responsive genes (<span class="html-italic">NtERD10C</span>, <span class="html-italic">NtLEA5</span>, <span class="html-italic">NtDREB1A</span>, <span class="html-italic">NtCOR15A</span>, <span class="html-italic">NtCOR47</span>, and <span class="html-italic">NtKIN1</span>) in NT and transgenic lines before and after 48 h of cold stress (4 °C). Values are presented as means ± SEM values (<span class="html-italic">n</span> = 3). Different letters indicate a significant difference at <span class="html-italic">p</span> &lt; 0.05.</p>
Full article ">
13 pages, 1286 KiB  
Review
How the Innate Immune DNA Sensing cGAS-STING Pathway Is Involved in Apoptosis
by Wanglong Zheng, Anjing Liu, Nengwen Xia, Nanhua Chen, François Meurens and Jianzhong Zhu
Int. J. Mol. Sci. 2023, 24(3), 3029; https://doi.org/10.3390/ijms24033029 - 3 Feb 2023
Cited by 29 | Viewed by 6505
Abstract
The cGAS–STING signaling axis can be activated by cytosolic DNA, including both non-self DNA and self DNA. This axis is used by the innate immune system to monitor invading pathogens and/or damage. Increasing evidence has suggested that the cGAS-STING pathway not only facilitates [...] Read more.
The cGAS–STING signaling axis can be activated by cytosolic DNA, including both non-self DNA and self DNA. This axis is used by the innate immune system to monitor invading pathogens and/or damage. Increasing evidence has suggested that the cGAS-STING pathway not only facilitates inflammatory responses and the production of type I interferons (IFN), but also activates other cellular processes, such as apoptosis. Recently, many studies have focused on analyzing the mechanisms of apoptosis induced by the cGAS-STING pathway and their consequences. This review gives a detailed account of the interplay between the cGAS-STING pathway and apoptosis. The cGAS-STING pathway can induce apoptosis through ER stress, NLRP3, NF-κB, IRF3, and IFN signals. Conversely, apoptosis can feed back to regulate the cGAS-STING pathway, suppressing it via the activation of caspases or promoting it via mitochondrial DNA (mtDNA) release. Apoptosis mediated by the cGAS-STING pathway plays crucial roles in balancing innate immune responses, resisting infections, and limiting tumor growth. Full article
(This article belongs to the Special Issue Innate Immune Cell Effector Responses)
Show Figures

Figure 1

Figure 1
<p>The schematic mechanism of cGAS-STING pathway-mediated apoptosis. ➀ cGAS-STING pathway can induce apoptosis through ER stress, ➁ through NLRP3 pathway, ➂ through NF-κB pathway, ➃ through the interaction of IRF3 and Bax, ➄ and through IFN-I production.</p>
Full article ">Figure 2
<p>Apoptosis can feed back to regulate the cGAS-STING pathway. (1) Apoptosis can suppress the cGAS-STING pathway through the activation of caspases including caspase-3 and caspase-8. (2) Apoptosis can promote the cGAS-STING pathway through the release of mtDNA.</p>
Full article ">
12 pages, 8768 KiB  
Article
Role of Transcription Factor EB in Mitochondrial Dysfunction of Cisplatin-Induced Acute Kidney Injury
by Shujun Wang, Yanse Chen, Hongluan Wu, Xiaoyu Li, Haiyan Xiao, Qingjun Pan and Hua-Feng Liu
Int. J. Mol. Sci. 2023, 24(3), 3028; https://doi.org/10.3390/ijms24033028 - 3 Feb 2023
Cited by 6 | Viewed by 2289
Abstract
Cisplatin, a widely used anticancer agent, can cause nephrotoxicity, including both acute kidney injury (AKI) and chronic kidney diseases, by accumulating in renal tubular epithelial cells (TECs). Mitochondrial pathology plays an important role in the pathogenesis of AKI. Based on the regulatory role [...] Read more.
Cisplatin, a widely used anticancer agent, can cause nephrotoxicity, including both acute kidney injury (AKI) and chronic kidney diseases, by accumulating in renal tubular epithelial cells (TECs). Mitochondrial pathology plays an important role in the pathogenesis of AKI. Based on the regulatory role of transcription factor EB (TFEB) in mitochondria, we investigated whether TFEB is involved in cisplatin-induced TEC damage. The results show that the expression of TFEB decreased in a concentration-dependent manner in both mouse kidney tissue and HK-2 cells when treated with cisplatin. A knockdown of TFEB aggravated cisplatin-induced renal TEC injury, which was partially reversed by TFEB overexpression in HK-2 cells. It was further observed that the TFEB knockdown also exacerbated cisplatin-induced mitochondrial damage in vitro, and included the depolarization of membrane potential, mitochondrial fragmentation and swelling, and the production of reactive oxygen species. In contrast, TFEB overexpression alleviated cisplatin-induced mitochondrial damage in TECs. These findings suggest that decreased TFEB expression may be a key mechanism of mitochondrial dysfunction in cisplatin-induced AKI, and that upregulation of TFEB has the potential to act as a therapeutic target to alleviate mitochondrial dysfunction and cisplatin-induced TEC injury. This study is important for developing therapeutic strategies to manipulate mitochondria through TFEB to delay AKI progression. Full article
(This article belongs to the Special Issue Advanced Molecular Insights into Renal Disorders)
Show Figures

Figure 1

Figure 1
<p>Cisplatin inhibits TFEB expression in mice kidney tissues and HK-2 cells. (<b>A</b>,<b>B</b>) Western blot assay and quantitative analysis of TFEB protein in kidney tissues of cisplatin-treated mice (intraperitoneal injection of cisplatin 0, 25, and 30 mg/kg). (<b>C</b>,<b>D</b>) Western blot assay and quantification of TFEB levels in HK-2 cells after exposure to increasing concentrations (0, 10, 20, 40, and 80 μM) of cisplatin for 24 h. Bars represent the mean ± SEM for at least three independent experiments. Cis: cisplatin. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, NS, non significant.</p>
Full article ">Figure 2
<p>TFEB knockdown exacerbates HK-2 cells damage caused by cisplatin. (<b>A</b>) Western blot assay of TFEB expression in HK-2 cells with or without TFEB knockdown. (<b>B</b>) HK-2 cells with or without TFEB knockdown were exposed to cisplatin (20 μM) for 24 h. The CCK-8 assay was used to detect cell viability. (<b>C</b>,<b>D</b>) Flow cytometry and quantitative analysis of apoptosis in HK-2 cells. Each bar represents mean ± SEM of at least three independent experiments. siTFEB: TFEB-siRNA; Cis: cisplatin. * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001, NS, non significant.</p>
Full article ">Figure 3
<p>TFEB overexpression alleviates cisplatin-induced damage of HK-2 cells. (<b>A</b>) Western blot assay of TFEB expression in HK-2 cells infected with or without TFEB lentivirus. (<b>B</b>) After infection with lentivirus with or without TFEB, HK-2 cells were exposed to cisplatin (20 μM) for 24 h. The CCK-8 assay was used to detect cell viability. (<b>C</b>,<b>D</b>) Flow cytometry and quantitative analysis of apoptosis in HK-2 cells. (<b>E</b>,<b>F</b>) Immunoblotting analysis and quantitative data for PARP protein in HK-2 cells. Each bar represents mean ± SEM of at least three independent experiments. OE-TFEB: overexpressing TFEB; Cis: cisplatin. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, NS, non significant.</p>
Full article ">Figure 4
<p>TFEB knockdown aggravates cisplatin-induced mitochondrial damage in HK-2 cells. HK-2 cells with or without TFEB knockdown were exposed to cisplatin (20 μM) for 24 h. (<b>A</b>,<b>B</b>) Flow cytometry analysis of TMRE fluorescence intensity to detect mitochondrial membrane potential in HK-2 cells. (<b>C</b>) Immunofluorescence staining with MitoTracker to detect mitochondrial morphology in HK-2 cells treated as indicated. Scale bar: 10 μm. (<b>D</b>) Percentage of cells with fragmented mitochondria in HK-2 cells. Each bar represents mean ± SEM of at least three independent experiments. siTFEB: TFEB-siRNA; Cis: cisplatin. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
Full article ">Figure 5
<p>TFEB overexpression attenuates mitochondrial damage in HK-2 cells caused by cisplatin. After infection with lentivirus with or without TFEB, HK-2 cells were exposed to cisplatin (20 μM) for 24 h. (<b>A</b>) Representative images of mitochondrial membrane potential measurement with immunofluorescence staining for TMRE in HK-2 cells. Scale bar: 10 μm. (<b>B</b>,<b>C</b>) Flow cytometry analysis of TMRE fluorescence intensity to detect mitochondrial membrane potential in HK-2 cells. (<b>D</b>) Immunofluorescence staining with MitoTracker was used to detect mitochondrial morphology in HK-2 cells treated with the indicated treatments. Scale bar: 10 μm. (<b>E</b>) The percentage of cells with fragmented mitochondria in each group. Each bar represents mean ± SEM of at least three independent experiments. OE-TFEB: overexpressing TFEB; Cis: cisplatin. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
Full article ">Figure 6
<p>Effect of TFEB overexpression on ROS and MitoSOX in cisplatin-induced HK-2 cells. (<b>A</b>,<b>B</b>) Flow cytometry analysis and quantitative data of ROS in HK-2 cells infected by lentivirus carrying with or without TFEB followed by cisplatin (20 μM) exposure for 24 h. (<b>C</b>,<b>D</b>) Mitochondrial ROS (mtROS) were measured by incubation with MitoSOX in HK-2 cells with indicated treatments. Each bar represents the mean ± SEM for at least three independent experiments. OE-TFEB: overexpressing TFEB; Cis: cisplatin. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
Full article ">
Previous Issue
Back to TopTop