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20 pages, 7853 KiB  
Article
RTL4, a Retrovirus-Derived Gene Implicated in Autism Spectrum Disorder, Is a Microglial Gene That Responds to Noradrenaline in the Postnatal Brain
by Fumitoshi Ishino, Johbu Itoh, Ayumi Matsuzawa, Masahito Irie, Toru Suzuki, Yuichi Hiraoka, Masanobu Yoshikawa and Tomoko Kaneko-Ishino
Int. J. Mol. Sci. 2024, 25(24), 13738; https://doi.org/10.3390/ijms252413738 - 23 Dec 2024
Abstract
Retrotransposon Gag-like 4 (RTL4), a gene acquired from a retrovirus, is a causative gene in autism spectrum disorder. Its knockout mice exhibit increased impulsivity, impaired short-term spatial memory, failure to adapt to novel environments, and delayed noradrenaline (NA) recovery in the [...] Read more.
Retrotransposon Gag-like 4 (RTL4), a gene acquired from a retrovirus, is a causative gene in autism spectrum disorder. Its knockout mice exhibit increased impulsivity, impaired short-term spatial memory, failure to adapt to novel environments, and delayed noradrenaline (NA) recovery in the frontal cortex. However, due to its very low expression in the brain, it remains unknown which brain cells express RTL4 and its dynamics in relation to NA. We addressed these issues using knock-in mice carrying endogenous Rtl4 fused to Venus, which encodes a fluorescent protein. The RTL4-Venus fusion protein was detected as a secreted protein in the midbrain, hypothalamus, hippocampus and amygdala in the postnatal brain. Its signal intensity was high during critical periods of neonatal adaptation to novel environments. It was upregulated by various stimuli, including isoproterenol administration, whereas it was decreased by anesthesia but was maintained by milnacipran administration, suggesting its highly sensitive response to stressors, possible dependence on the arousal state and involvement in the NA reuptake process. In vitro mixed glial culture experiments demonstrated that Rtl4 is a microglial gene and suggested that RTL4 secretion responds rapidly to isoproterenol. Microglial RTL4 plays an important role in the NA response and possibly in the development of the NAergic neuronal network in the brain. Full article
(This article belongs to the Special Issue Molecular Research on Human Retrovirus Infection: 2nd Edition)
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Figure 1

Figure 1
<p>Detection of RTL4CV protein in the postnatal brain. (<b>A</b>) Production of the <span class="html-italic">Rtl4</span>CV knock-in mouse. Schematic representation of wild-type <span class="html-italic">Rtl4</span> and the modified genome structure of the <span class="html-italic">Rtl4</span> CV mouse. The mouse <span class="html-italic">Rtl4</span> open reading frame (gray box) is located on exon 7 (white box). The Venus coding sequence (yellow box) was inserted in front of the <span class="html-italic">Rtl4</span> stop codon together with a (GGS)x4 linker (light green box). See the details in <a href="#app1-ijms-25-13738" class="html-app">Figure S1 and Table S1</a>. (<b>B</b>) Immunoaffinity experiment of the RTL4-CV protein in the 2 w brain (indicated by an arrow). Immunoprecipitation was performed using an anti-GFP antibody. The estimated molecular weight of the RTL4CV protein is 61 kDa (RTL4 and Venus, 34 and 27 kDa, respectively). (<b>C</b>) Detection of RTL4CV in P15 brain. Left: Venus fluorescence image. Right: autofluorescence image. Amg: amygdala; Cb: cerebellum; Cc: cerebral cortex; dHP: dorsal hippocampus region; Ht: hypothalamus; Mb: midbrain; Md: medulla oblongata; Ob: olfactory bulb; Th: thalamus; vHp: ventral hippocampus region. (<b>D</b>,<b>E</b>) Venus signal detected by LSM880 confocal laser scanning microscopy. The Venus signal (530 nm) was detected as the second strongest peak (<b>D</b>) in the hypothalamus (<b>E</b>). ACE: Automatic Composition Extraction. (<b>F</b>) Dispersed dot-like signals observed in the hypothalamus. Top: Venus image. Bottom: Venus image merged with transmission image. See also <a href="#app1-ijms-25-13738" class="html-app">Figure S6</a>. (<b>G</b>) Granules of 1 μm containing RTL4CV in P2 brain. Several 1 μm granules were observed in the early postnatal periods. See also <a href="#app1-ijms-25-13738" class="html-app">Figure S7</a>. Top left: Venus image. Bottom left: merged image of autofluorescence and Venus. Right: granules in the hippocampus. Merged images of transmission and Venus. Hip: hippocampus; H-It: habenulo-interpedincular tract; Lsn: lateral septal nucleus; Re: thalamus nucleus reuniens; Tec: Tectal commissure.</p>
Full article ">Figure 1 Cont.
<p>Detection of RTL4CV protein in the postnatal brain. (<b>A</b>) Production of the <span class="html-italic">Rtl4</span>CV knock-in mouse. Schematic representation of wild-type <span class="html-italic">Rtl4</span> and the modified genome structure of the <span class="html-italic">Rtl4</span> CV mouse. The mouse <span class="html-italic">Rtl4</span> open reading frame (gray box) is located on exon 7 (white box). The Venus coding sequence (yellow box) was inserted in front of the <span class="html-italic">Rtl4</span> stop codon together with a (GGS)x4 linker (light green box). See the details in <a href="#app1-ijms-25-13738" class="html-app">Figure S1 and Table S1</a>. (<b>B</b>) Immunoaffinity experiment of the RTL4-CV protein in the 2 w brain (indicated by an arrow). Immunoprecipitation was performed using an anti-GFP antibody. The estimated molecular weight of the RTL4CV protein is 61 kDa (RTL4 and Venus, 34 and 27 kDa, respectively). (<b>C</b>) Detection of RTL4CV in P15 brain. Left: Venus fluorescence image. Right: autofluorescence image. Amg: amygdala; Cb: cerebellum; Cc: cerebral cortex; dHP: dorsal hippocampus region; Ht: hypothalamus; Mb: midbrain; Md: medulla oblongata; Ob: olfactory bulb; Th: thalamus; vHp: ventral hippocampus region. (<b>D</b>,<b>E</b>) Venus signal detected by LSM880 confocal laser scanning microscopy. The Venus signal (530 nm) was detected as the second strongest peak (<b>D</b>) in the hypothalamus (<b>E</b>). ACE: Automatic Composition Extraction. (<b>F</b>) Dispersed dot-like signals observed in the hypothalamus. Top: Venus image. Bottom: Venus image merged with transmission image. See also <a href="#app1-ijms-25-13738" class="html-app">Figure S6</a>. (<b>G</b>) Granules of 1 μm containing RTL4CV in P2 brain. Several 1 μm granules were observed in the early postnatal periods. See also <a href="#app1-ijms-25-13738" class="html-app">Figure S7</a>. Top left: Venus image. Bottom left: merged image of autofluorescence and Venus. Right: granules in the hippocampus. Merged images of transmission and Venus. Hip: hippocampus; H-It: habenulo-interpedincular tract; Lsn: lateral septal nucleus; Re: thalamus nucleus reuniens; Tec: Tectal commissure.</p>
Full article ">Figure 2
<p>RTL4CV expression in the brain. (<b>A</b>) The effect of handling on RTL4CV protein expression in P21 brain. Venus and autofluorescence images of WT (left), <span class="html-italic">Rtl4</span>CV with “the minimal stimulation” (middle) and <span class="html-italic">Rtl4</span>CV in “the normal condition” (right). Top: inner side of the brain hemisphere. Bottom: brain slice of 1.5 mm width. (<b>B</b>) Measurement of Venus signal intensity at different parts of the P21 brain (see also <a href="#app1-ijms-25-13738" class="html-app">Figure S10</a> for regional analysis method and <a href="#app1-ijms-25-13738" class="html-app">Figure S11</a> for another example). Blue: WT; yellow: <span class="html-italic">Rtl4</span>CV with “the minimal stimulation” (min); orange: <span class="html-italic">Rtl4</span>CV under “the normal conditions” (nor). Green: <span class="html-italic">Rtl4</span>CV with isoproterenol cerebroventricular injection (iso, 10 μg/P21 mice). Each bar represents one P21 individual. The intensity of <span class="html-italic">Rtl4</span>CV in the hypothalamus and midbrain under “the normal conditions” (mean ± standard deviation (SD): 4004 ± 352 and 2970 ± 146) is significantly higher than that of <span class="html-italic">Rtl4</span>CV with “the minimal stimulation” (mean ± SD: 1805 ± 687 and 2231 ± 300) (<span class="html-italic">p</span> = 0.0036 and 0.019, two-tailed <span class="html-italic">t</span>-test), respectively. The intensity of <span class="html-italic">Rtl4</span>CV in the hypothalamus and midbrain is further increased after isoproterenol injection (mean ± SD: 5478 ± 381 and 3944 ± 175) (<span class="html-italic">p</span> = 0.021 and 0.008, respectively, two-tailed <span class="html-italic">t</span>-test). (<b>C</b>) Effect of isoproterenol on RTL4CV expression in P21 brain. Venus image of <span class="html-italic">Rtl4</span>CV under “the normal condition” (left) and <span class="html-italic">Rtl4</span>CV with isoproterenol injection (right). Top: inner side of the brain hemisphere. Bottom: brain slice of 1.5 mm in width. (<b>D</b>) Effect of anesthesia and milnacipran on RTL4CV intensity. Venus image of <span class="html-italic">Rtl4</span>CV under anesthesia (left) and anesthesia with milnacipran injection (right). Top: inner side of the brain hemisphere. Bottom: brain slice of 1.5 mm in width. (<b>E</b>) Graphic representation of (<b>D</b>)<b>.</b> Left: WT (P28), <span class="html-italic">Rtl4</span>CV (P25) and <span class="html-italic">Rtl4</span>CV (P25) under isoflurane anesthesia. Right: WT (P30), <span class="html-italic">Rtl4</span>CV (P27), <span class="html-italic">Rtl4</span>CV (P27) with saline injection (CV + S) and <span class="html-italic">Rtl4</span>CV (P27) with milnacipran injection (CV + M). After the <span class="html-italic">Rtl4</span>CV mice were anesthetized with isoflurane for 1 min, 10 μL of saline or milnacipran (total 167 μg) was administered intraventricularly, followed by additional anesthesia for 5 min. The signal intensity of the hypothalamus (blue), cerebral cortex (orange), midbrain, (gray) amygdala (yellow), hippocampus (light blue) and background (light green) are presented. See also <a href="#app1-ijms-25-13738" class="html-app">Figure S12</a> for regional analysis and <a href="#app1-ijms-25-13738" class="html-app">Figure S13</a> for another example.</p>
Full article ">Figure 2 Cont.
<p>RTL4CV expression in the brain. (<b>A</b>) The effect of handling on RTL4CV protein expression in P21 brain. Venus and autofluorescence images of WT (left), <span class="html-italic">Rtl4</span>CV with “the minimal stimulation” (middle) and <span class="html-italic">Rtl4</span>CV in “the normal condition” (right). Top: inner side of the brain hemisphere. Bottom: brain slice of 1.5 mm width. (<b>B</b>) Measurement of Venus signal intensity at different parts of the P21 brain (see also <a href="#app1-ijms-25-13738" class="html-app">Figure S10</a> for regional analysis method and <a href="#app1-ijms-25-13738" class="html-app">Figure S11</a> for another example). Blue: WT; yellow: <span class="html-italic">Rtl4</span>CV with “the minimal stimulation” (min); orange: <span class="html-italic">Rtl4</span>CV under “the normal conditions” (nor). Green: <span class="html-italic">Rtl4</span>CV with isoproterenol cerebroventricular injection (iso, 10 μg/P21 mice). Each bar represents one P21 individual. The intensity of <span class="html-italic">Rtl4</span>CV in the hypothalamus and midbrain under “the normal conditions” (mean ± standard deviation (SD): 4004 ± 352 and 2970 ± 146) is significantly higher than that of <span class="html-italic">Rtl4</span>CV with “the minimal stimulation” (mean ± SD: 1805 ± 687 and 2231 ± 300) (<span class="html-italic">p</span> = 0.0036 and 0.019, two-tailed <span class="html-italic">t</span>-test), respectively. The intensity of <span class="html-italic">Rtl4</span>CV in the hypothalamus and midbrain is further increased after isoproterenol injection (mean ± SD: 5478 ± 381 and 3944 ± 175) (<span class="html-italic">p</span> = 0.021 and 0.008, respectively, two-tailed <span class="html-italic">t</span>-test). (<b>C</b>) Effect of isoproterenol on RTL4CV expression in P21 brain. Venus image of <span class="html-italic">Rtl4</span>CV under “the normal condition” (left) and <span class="html-italic">Rtl4</span>CV with isoproterenol injection (right). Top: inner side of the brain hemisphere. Bottom: brain slice of 1.5 mm in width. (<b>D</b>) Effect of anesthesia and milnacipran on RTL4CV intensity. Venus image of <span class="html-italic">Rtl4</span>CV under anesthesia (left) and anesthesia with milnacipran injection (right). Top: inner side of the brain hemisphere. Bottom: brain slice of 1.5 mm in width. (<b>E</b>) Graphic representation of (<b>D</b>)<b>.</b> Left: WT (P28), <span class="html-italic">Rtl4</span>CV (P25) and <span class="html-italic">Rtl4</span>CV (P25) under isoflurane anesthesia. Right: WT (P30), <span class="html-italic">Rtl4</span>CV (P27), <span class="html-italic">Rtl4</span>CV (P27) with saline injection (CV + S) and <span class="html-italic">Rtl4</span>CV (P27) with milnacipran injection (CV + M). After the <span class="html-italic">Rtl4</span>CV mice were anesthetized with isoflurane for 1 min, 10 μL of saline or milnacipran (total 167 μg) was administered intraventricularly, followed by additional anesthesia for 5 min. The signal intensity of the hypothalamus (blue), cerebral cortex (orange), midbrain, (gray) amygdala (yellow), hippocampus (light blue) and background (light green) are presented. See also <a href="#app1-ijms-25-13738" class="html-app">Figure S12</a> for regional analysis and <a href="#app1-ijms-25-13738" class="html-app">Figure S13</a> for another example.</p>
Full article ">Figure 3
<p>RTL4CV expression in cultured microglial cells. (<b>A</b>) Different types of microglia expressing RTL4CV in the mixed glial culture: (left) flat type, (middle) spindle type and (right) floating round type (see also <a href="#app1-ijms-25-13738" class="html-app">Figure S14</a>). Top: Venus images. Middle: merged images of transmission and Venus. Bottom: transmission images. (<b>B</b>) Measurement of Venus signal intensity of microglial cells isolated from WT (blue) and <span class="html-italic">Rtl4</span>CV (yellow) mice (left) and that of culture media from WT (light blue) and Rtl4CV (pale yellow) mice (right). The intensity of <span class="html-italic">Rtl4</span>CV microglia (3901 ± 648) is significantly higher than that of WT microglia (567 ± 96) (<span class="html-italic">p</span> = 0.001, two-tailed <span class="html-italic">t</span>-test). The same is true for the culture media (CV: 1162 ± 106, WT: 53.5 ± 21.5) (<span class="html-italic">p</span> = 0.003, two-tailed <span class="html-italic">t</span>-test). (<b>C</b>) Rapid secretion of RTL4CV in response to isoproterenol administration. Each of the 3D-section intensity data (at 0.5 μm intervals, a total of 19 Z positions) from the mixed glial culture dishes was obtained in the time-lapse experiment (90 s interval). Isoproterenol (20 μM) was added to the culture media during the 90 s interval between T1 and T2. Therefore, the T2 data were obtained 30 s after administration. As shown in the top label, the astrocyte feeder layers were located at Z7–Z8, and the microglial cells were located from Z8 (within the feeder) to Z11–Z12 (on the feeder) according to their morphology. The signals at the Z position numbers Z5–Z8, Z9–Z12 and Z13–19 are displayed. The results of the two microglial cells (No. 1 and 3 in <a href="#app1-ijms-25-13738" class="html-app">Figure S15</a>) are shown. The results of Z1–Z4 (bottom side) and BG are shown in <a href="#app1-ijms-25-13738" class="html-app">Figure S15</a>.</p>
Full article ">
22 pages, 5115 KiB  
Article
Mimicking the Effects of Antimicrobial Blue Light: Exploring Single Stressors and Their Impact on Microbial Growth
by Beata Kruszewska-Naczk, Mariusz Grinholc and Aleksandra Rapacka-Zdonczyk
Antioxidants 2024, 13(12), 1583; https://doi.org/10.3390/antiox13121583 - 23 Dec 2024
Abstract
Antimicrobial blue light (aBL) has become a promising non-invasive method that uses visible light, typically within the 405–470 nm wavelength range, to efficiently inactivate a wide variety of pathogens. However, the mechanism of antimicrobial blue light (aBL) has not been fully understood. In [...] Read more.
Antimicrobial blue light (aBL) has become a promising non-invasive method that uses visible light, typically within the 405–470 nm wavelength range, to efficiently inactivate a wide variety of pathogens. However, the mechanism of antimicrobial blue light (aBL) has not been fully understood. In this study, our research group investigated the sensitivity of Escherichia coli BW25113 single-gene deletion mutants to individual stressors generated by aBL. Sixty-four aBL-sensitive mutants were tested under conditions mimicking the stress generated by irradiation with aBL, with their growth defects compared to the wild-type strain. Results revealed no positive correlation between aBL and single stressors, indicating that aBL’s effectiveness is due to the simultaneous generation of multiple stressors. This multifactorial effect suggests that aBL targets microbial cells more precisely than single stressors such as hydrogen peroxide. No single gene knockout conferred specific resistance, highlighting aBL’s potential as an antimicrobial strategy. Full article
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Graphical abstract

Graphical abstract
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<p>The experimental workflow.</p>
Full article ">Figure 2
<p>Correlograms illustrate the correlation between aBL and stressors: (<b>a</b>) H<sub>2</sub>O<sub>2</sub>, (<b>b</b>) O<sub>2</sub><sup>−</sup>, (<b>c</b>) NO•, (<b>d</b>) Acidic pH, (<b>e</b>) membrane stress, and (<b>f</b>) •OH. The X-axis represents aBL sensitivity values [log<sub>10</sub> CFU/mL], while the Y-axis growth defect [%] for each stressor.</p>
Full article ">Figure 3
<p>Scree plot. The X-axis shows the number of dimensions, while the Y-axis shows the percentage of variance explained by each dimension. The scree point is observed where variance starts to level off after the second dimension.</p>
Full article ">Figure 4
<p>Cosine distances heatmap: On the X-axis, mutants are listed from left to right in order: <span class="html-italic">tolA</span>, <span class="html-italic">pfkA</span>, <span class="html-italic">yhhH</span>, <span class="html-italic">narL</span>, <span class="html-italic">rpe</span>, <span class="html-italic">metR</span>, <span class="html-italic">deoB</span>, <span class="html-italic">rnt</span>, <span class="html-italic">oxyR</span>, <span class="html-italic">nuoN</span>, <span class="html-italic">cydD</span>, <span class="html-italic">holD</span>, <span class="html-italic">atpC</span>, <span class="html-italic">thyA</span>, <span class="html-italic">dacA</span>, <span class="html-italic">pgi</span>, <span class="html-italic">pgm</span>, <span class="html-italic">atpG</span>, <span class="html-italic">truA</span>, <span class="html-italic">phoQ</span>, <span class="html-italic">umuD</span>, <span class="html-italic">gmhB</span>, <span class="html-italic">rfaD</span>, <span class="html-italic">tpiA</span>, <span class="html-italic">yihE</span>, <span class="html-italic">rfaE</span>, <span class="html-italic">rfaG</span>, <span class="html-italic">atpE</span>, <span class="html-italic">yfgL</span>, <span class="html-italic">ybaP</span>, <span class="html-italic">atpB</span>, <span class="html-italic">atpH</span>, <span class="html-italic">dnaJ</span>, <span class="html-italic">yfbB</span>, <span class="html-italic">priA</span>, <span class="html-italic">rbfA</span>, <span class="html-italic">ubiC</span>, <span class="html-italic">yegS</span>, <span class="html-italic">atpF</span>, <span class="html-italic">rfaC</span>, <span class="html-italic">cpxA</span>, <span class="html-italic">yccM</span>, <span class="html-italic">ppc</span>, <span class="html-italic">yjeK</span>, <span class="html-italic">pyrE</span>, <span class="html-italic">sstT</span>, <span class="html-italic">dnaK</span>, <span class="html-italic">yheM</span>, <span class="html-italic">ecnB</span>, <span class="html-italic">ydcX</span>, <span class="html-italic">atpD</span>, <span class="html-italic">ydcE</span>, <span class="html-italic">atpA</span>, ypjD, <span class="html-italic">fabH</span>, <span class="html-italic">surA</span>, <span class="html-italic">purA</span>, <span class="html-italic">fimB</span>, <span class="html-italic">ydeU</span>, <span class="html-italic">yigL</span>, <span class="html-italic">gntK</span>, <span class="html-italic">yfeH</span>, <span class="html-italic">yncA</span>. The Y-axis mutants are presented in the opposite order than on the X-axis.</p>
Full article ">Figure 5
<p>The WSS plot for determining the number of clusters. WSS—Within-Cluster Sum of Squares. The number of 3 clusters was chosen as the optimal value.</p>
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<p>Silhouette plot for determining the number of clusters. The Y-axis shows the silhouette score for each cluster shown on the X-axis.</p>
Full article ">Figure 7
<p>Results of k-means++ algorithm for both principal components (PC1—X-axis and PC2—Y-axis) summarizing clustering analysis. Bolded dots in the center of each cluster represent their centroids placed at the longest distance from other clusters.</p>
Full article ">Figure 8
<p>Cluster silhouette plot representing the silhouette width for each mutant in every cluster. The red line indicates the average value for the entire set.</p>
Full article ">Figure 9
<p>Growth defects of mutants by clusters: (<b>a</b>) characterization of growth defect profiles for 3 clusters; and (<b>b</b>) characterization of cluster profiles for each stressor.</p>
Full article ">Figure 10
<p>Protein–protein functional interaction networks and gene co-expression. Protein–protein functional interaction networks of the proteins are divided into 3 clusters: (<b>a</b>) Gene co-expression within cluster 1; (<b>b</b>) protein–protein functional interaction networks within cluster 1; (<b>c</b>) gene co-expression within cluster 2; (<b>d</b>) protein–protein functional interaction networks within cluster 2; (<b>e</b>) gene co-expression within cluster 3; (<b>f</b>) protein–protein functional interaction networks within cluster 3. The analysis was performed with the STRING database (<a href="https://string-db.org" target="_blank">https://string-db.org</a>). The colors of the lines denote the following: light blue, interactions known from curated databases; pink, interactions experimentally determined; bright green, predicted reaction (gene neighborhood); red, gene fusions; dark blue, gene co-occurrence; green, textmining; black, co-expression; and blue, protein homology.</p>
Full article ">
16 pages, 13174 KiB  
Article
MicroRNA-150 Deletion from Adult Myofibroblasts Augments Maladaptive Cardiac Remodeling Following Chronic Myocardial Infarction
by Satoshi Kawaguchi, Marisa N. Sepúlveda, Jian-peng Teoh, Taiki Hayasaka, Bruno Moukette, Tatsuya Aonuma, Hyun Cheol Roh, Meena S. Madhur and Il-man Kim
Biomolecules 2024, 14(12), 1650; https://doi.org/10.3390/biom14121650 - 22 Dec 2024
Viewed by 274
Abstract
MicroRNA (miR: small noncoding RNA)-150 is evolutionarily conserved and is downregulated in patients with diverse forms of heart failure (HF) and in multiple mouse models of HF. Moreover, miR-150 is markedly correlated with the outcome of patients with HF. We previously reported that [...] Read more.
MicroRNA (miR: small noncoding RNA)-150 is evolutionarily conserved and is downregulated in patients with diverse forms of heart failure (HF) and in multiple mouse models of HF. Moreover, miR-150 is markedly correlated with the outcome of patients with HF. We previously reported that systemic or cardiomyocyte-derived miR-150 in mice elicited myocardial protection through the inhibition of cardiomyocyte death, without affecting neovascularization and T cell infiltration. Our mechanistic studies also showed that the protective roles of miR-150 in ischemic mouse hearts and human cardiac fibroblasts were, in part, attributed to the inhibition of fibroblast activation via the repression of multiple profibrotic genes. However, the extent to which miR-150 expression in adult myofibroblasts (MFs) modulates the response to myocardial infarction (MI) remains unknown. Here, we develop a novel 4-hydroxytamoxifen-inducible MF-specific miR-150 conditional knockout mouse model and demonstrate that the mouse line exhibits worse cardiac dysfunction after MI. Our studies further reveal that miR-150 ablation selectively in adult MFs exacerbates cardiac damage and apoptosis after chronic MI. Lastly, MF-specific miR-150 deletion in adult mice promotes the expression of proinflammatory and profibrotic genes as well as cardiac fibrosis following chronic MI. Our findings indicate a key protective role for MF-derived miR-150 in modulating post-MI responses. Full article
(This article belongs to the Special Issue Heart Diseases: Molecular Mechanisms and New Therapies)
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Figure 1

Figure 1
<p>Establishment of a novel inducible myofibroblast-specific miR-150 knockout mouse line. (<b>A</b>) Targeting scheme, mouse crossing, and establishment of 4-hydroxytamoxifen (4-OH-TAM)-inducible myofibroblast (MF)-restricted conditional knockout (cKO) of miR-150 in vivo. (<b>B</b>) Experimental timeline with myocardial infarction (MI) and 4-OH-TAM injection (20 mg/kg/day for 5 days) followed by echocardiography and harvest. 4-OH-TAM injection was initiated immediately after MI. (<b>C</b>) QRT-PCR analyses of miR-150 in left ventricles from miR-150 <sup>fl/fl</sup> or miR-150 cKO mice that were intraperitoneally injected with vehicle or 4-OH-TAM. Left ventricles were harvested at 4 weeks after MI. N = 5–7 per group. Data are presented as mean ± SEM. One-way ANOVA with Turkey multiple comparison test. * <span class="html-italic">p</span> &lt; 0.05 or ** <span class="html-italic">p</span> &lt; 0.01 vs. 4-OH-TAM-inducuble MF-restricted miR-150 cKO mice.</p>
Full article ">Figure 2
<p>Inducible myofibroblast-restricted miR-150 deletion in adult mice augments cardiac dysfunction after myocardial infarction. (<b>A</b>) Kaplan–Meier survival curve at 0–28 days (d) following myocardial infarction (MI) in 4-OH-TAM-inducible miR-150 cKO mice or 4-OH-TAM-treated miR-150 <sup>fl/fl</sup> littermates. N = 3–11 per group. Log-rank test. * <span class="html-italic">p</span> &lt; 0.05 vs. other three groups. (<b>B</b>–<b>D</b>), Transthoracic echocardiography was conducted on the four experimental groups (sham and MI of 4-OH-TAM-treated miR-150 <sup>fl/fl</sup> and 4-OH-TAM-inducible miR-150 cKO) at 0–28 days (d) post-MI. Quantification of left ventricular (LV) ejection fraction (EF: (<b>B</b>)), fractional shortening (FS: (<b>C</b>)), and end-systolic volume (LVESV: (<b>D</b>)) is shown. N = 3–11 per group. Data are presented as mean ± SD. Two-way ANOVA with Tukey’s multiple comparison test. *** <span class="html-italic">p</span> &lt; 0.001 vs. Sham of same genotype (denoted by two different colors for sham within same group); <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01, or <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 vs. MI 4-OH-TAM-treated miR-150 <sup>fl/fl</sup> (denoted by red).</p>
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<p>Selective deletion of miR-150 in adult myofibroblasts induces damage and the expression of inflammatory genes in the heart after chronic myocardial infarction. (<b>A</b>), Representative hematoxylin and eosin (H&amp;E) staining of heart sections of the peri-ischemic border area at 4 weeks after MI reveals increased disorganized structure in 4-OH-TAM-inducible miR-150 cKO hearts compared to 4-OH-TAM-treated miR-150 <sup>fl/fl</sup> controls. Scale bars: 100 μm. (<b>B</b>–<b>D</b>) QRT-PCR analysis of <span class="html-italic">Nppa</span>, <span class="html-italic">Nppb</span>, and <span class="html-italic">Acta1</span> expression representing cardiac damage in ischemic areas from 4-OH-TAM-inducible miR-150 cKO hearts compared to 4-OH-TAM-miR-150 <sup>fl/fl</sup> controls at 4 weeks after MI. (<b>E</b>,<b>F</b>), QRT-PCR analysis of <span class="html-italic">Il-6</span> and <span class="html-italic">Il-1b</span> expression for cardiac inflammation in ischemic areas from 4-OH-TAM-inducible miR-150 cKO hearts compared to 4-OH-TAM-treated miR-150 <sup>fl/fl</sup> controls at 4 weeks after MI. N = 5–6 per group. QRT-PCR data are presented as fold induction of gene expression normalized to <span class="html-italic">Gapdh</span>. Data are shown as mean ± SEM. Two-way ANOVA with Tukey’s multiple comparison test. * <span class="html-italic">p</span> &lt; 0.05 or ** <span class="html-italic">p</span> &lt; 0.01 vs. sham of same genotype; <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 or <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01 vs. MI 4-OH-TAM-treated miR-150 <sup>fl/fl</sup>.</p>
Full article ">Figure 4
<p>Inducible myofibroblast-specific miR-150 loss in adult mice exacerbates apoptosis in the heart following chronic myocardial infarction. (<b>A</b>,<b>B</b>) Representative cleaved-caspase 3 staining images in heart sections of the peri-ischemic border area at 4 weeks after MI (<b>A</b>) and quantification of apoptosis in six 20× fields (<b>B</b>). Scale bars: 100 μm. (<b>C</b>,<b>D</b>) QRT-PCR analysis of proapoptotic <span class="html-italic">Bak1</span> and <span class="html-italic">Egr2</span> expression in the ischemic areas from 4-OH-TAM-inducible miR-150 cKO hearts compared to 4-OH-TAM-treated miR-150 <sup>fl/fl</sup> controls at 4 weeks after MI. QRT-PCR data are presented as fold induction of gene expression normalized to <span class="html-italic">Gapdh</span>. N = 5–6 per group. Data are shown as mean ± SEM. Two-way ANOVA with Tukey’s multiple comparison test. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, or *** <span class="html-italic">p</span> &lt; 0.001 vs. sham of same genotype; <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01, or <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 vs. 4-OH-TAM-treated miR-150 <sup>fl/fl</sup>.</p>
Full article ">Figure 5
<p>Selective ablation of miR-150 in adult myofibroblasts promotes cardiac fibrosis after chronic myocardial infarction. Representative Masson’s Trichrome staining (<b>A</b>,<b>B</b>) in heart sections from the four experimental groups at 4 weeks after MI and fibrosis quantification (<b>C</b>) in whole left ventricles. Fibrosis histology images from whole heart longitudinal sections ((<b>A</b>): Scale bars: 1 mm) and zoomed in images of the peri-ischemic border area ((<b>B</b>): Scale bars: 100 μm). N = 5–6 per group. Data are shown as the mean ± SEM. Two-way ANOVA with Tukey’s multiple comparison test. *** <span class="html-italic">p</span> &lt; 0.001 vs. sham of same genotype; <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 vs. MI 4-OH-TAM-treated miR-150 <sup>fl/fl</sup>.</p>
Full article ">Figure 6
<p>Inducible myofibroblast-specific miR-150 ablation in adult mice worsens cardiac fibrosis following chronic myocardial infarction. Representative Picro Sirius Red staining (<b>A</b>,<b>B</b>) in heart sections from the four groups at 4 weeks after MI and fibrosis quantification (<b>C</b>) in whole left ventricles. Fibrosis histology images from whole heart longitudinal sections ((<b>A</b>): Scale bars: 1 mm) and zoomed in images of the peri-ischemic border area ((<b>B</b>): Scale bars: 100 μm). N = 5–6 per group. Data are shown as the mean ± SEM. Two-way ANOVA with Tukey’s multiple comparison test. *** <span class="html-italic">p</span> &lt; 0.001 vs. sham of same genotype; <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 vs. MI 4-OH-TAM-treated miR-150 <sup>fl/fl</sup>.</p>
Full article ">Figure 7
<p>Selective loss of miR-150 in adult myofibroblasts activates the cardiac expression of profibrotic genes post-MI. QRT-PCR analysis of profibrotic <span class="html-italic">Ctgf</span> (<b>A</b>), <span class="html-italic">Snail</span> (<b>B</b>), <span class="html-italic">Runx3</span> (<b>C</b>), or <span class="html-italic">Sprr1a</span> (<b>D</b>) expression in ischemic areas from 4-OH-TAM-treated miR-150 <sup>fl/fl</sup> and 4-OH-TAM-inducible miR-150 cKO mouse left ventricles at 4 weeks after MI. Data are presented as the fold induction of gene expression normalized to <span class="html-italic">Gapdh</span>. N = 5–6 per group. Data are shown as the mean ± SEM. Two-way ANOVA with Tukey’s multiple comparison test. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, or *** <span class="html-italic">p</span> &lt; 0.001 vs. sham of same genotype; <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 or <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 vs. 4-OH-TAM-treated miR-150 <sup>fl/fl</sup>.</p>
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17 pages, 3441 KiB  
Article
Identification and Functional Analysis of the Ph-2 Gene Conferring Resistance to Late Blight (Phytophthora infestans) in Tomato
by Chunyang Pan, Xin Li, Xiaoxiao Lu, Junling Hu, Chen Zhang, Lianfeng Shi, Can Zhu, Yanmei Guo, Xiaoxuan Wang, Zejun Huang, Yongchen Du, Lei Liu and Junming Li
Plants 2024, 13(24), 3572; https://doi.org/10.3390/plants13243572 - 21 Dec 2024
Viewed by 241
Abstract
Late blight is a destructive disease affecting tomato production. The identification and characterization of resistance (R) genes are critical for the breeding of late blight-resistant cultivars. The incompletely dominant gene Ph-2 confers resistance against the race T1 of Phytophthora infestans in tomatoes. [...] Read more.
Late blight is a destructive disease affecting tomato production. The identification and characterization of resistance (R) genes are critical for the breeding of late blight-resistant cultivars. The incompletely dominant gene Ph-2 confers resistance against the race T1 of Phytophthora infestans in tomatoes. Herein, we identified Solyc10g085460 (RGA1) as a candidate gene for Ph-2 through the analysis of sequences and post-inoculation expression levels of genes located within the fine mapping interval. The RGA1 was subsequently validated to be a Ph-2 gene through targeted knockout and complementation analyses. It encodes a CC-NBS-LRR disease resistance protein, and transient expression assays conducted in the leaves of Nicotiana benthamiana indicate that Ph-2 is predominantly localized within the nucleus. In comparison to its susceptible allele (ph-2), the transient expression of Ph-2 can elicit hypersensitive responses (HR) in N. benthamiana, and subsequent investigations indicate that the structural integrity of the Ph-2 protein is likely a requirement for inducing HR in this species. Furthermore, ethylene and salicylic acid hormonal signaling pathways may mediate the transmission of the Ph-2 resistance signal, with PR1- and HR-related genes potentially involved in the Ph-2-mediated resistance. Our results could provide a theoretical foundation for the molecular breeding of tomato varieties resistant to late blight and offer valuable insights into elucidating the interaction mechanism between tomatoes and P. infestans. Full article
(This article belongs to the Section Horticultural Science and Ornamental Plants)
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Figure 1

Figure 1
<p>Analysis of gene expression within the candidate interval (<b>A</b>) Heatmap of expression of genes within the candidate interval after inoculation; (<b>B</b>) Heatmap–bubble of the 15 genes stably expressed in the candidate interval.</p>
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<p>Targeted knockout and Complementation analysis of the <span class="html-italic">RGA1</span> (<b>A</b>) <span class="html-italic">RGA1</span> mutations generated through <span class="html-italic">CRISPR/Cas9</span> gene editing; (<b>B</b>) Comparison of phenotypes after inoculations between <span class="html-italic">RGA1cr-1</span>, <span class="html-italic">RGA1cr-6</span> and LA3152; (<b>C</b>) Comparison of phenotypes after inoculations between MM (<span class="html-italic">Ph-2</span>) and MM (<span class="html-italic">ph-2</span>); (<b>D</b>) Comparison of disease index after inoculations between resistant and susceptible genotypes. Asterisks indicate a significant difference (****, <span class="html-italic">p</span> &lt; 0.0001).</p>
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<p>Identification of resistance to <span class="html-italic">Ph</span>-2 driven by the 35S promoter.</p>
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<p>The subcellular localization of Ph-2 and ph-2.</p>
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<p>Evaluation of the capacity of Ph-2 and its domains to induce HR (<b>A</b>) HR response elicited by the transient expression of Ph-2; (<b>B</b>) Trypan blue staining; (<b>C</b>) Evaluation of the capacity of the Ph-2 domains to elicit HR; (<b>D</b>) Trypan blue staining.</p>
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<p>Comparative transcriptome analysis of NILs in <span class="html-italic">Ph-2</span> (<b>A</b>) The Venn diagram of DEGs of resistant and susceptible genotypes at 24 hpi; (<b>B</b>) The Venn diagram of DEGs of resistant and susceptible genotypes at 48 hpi; (<b>C</b>) The specific DEGs enriched in the ko04626 pathway at 48 hpi in the resistant genotype; (<b>D</b>) The specific DEGs enriched in the ko04626 pathway at 48 hpi in the susceptible genotype.</p>
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24 pages, 17809 KiB  
Article
Transcriptomic Characterization Reveals Mitochondrial Involvement in Nrf2/Keap1-Mediated Osteoclastogenesis
by Eiko Sakai and Takayuki Tsukuba
Antioxidants 2024, 13(12), 1575; https://doi.org/10.3390/antiox13121575 - 20 Dec 2024
Viewed by 206
Abstract
Although osteoclasts play crucial roles in the skeletal system, the mechanisms that underlie oxidative stress during osteoclastogenesis remain unclear. The transcription factor Nrf2 and its suppressor, Keap1, function as central mediators of oxidative stress. To further elucidate the function of Nrf2/Keap1-mediated oxidative stress [...] Read more.
Although osteoclasts play crucial roles in the skeletal system, the mechanisms that underlie oxidative stress during osteoclastogenesis remain unclear. The transcription factor Nrf2 and its suppressor, Keap1, function as central mediators of oxidative stress. To further elucidate the function of Nrf2/Keap1-mediated oxidative stress regulation in osteoclastogenesis, DNA microarray analysis was conducted in this study using wild-type (WT), Keap1 knockout (Keap1 KO), and Nrf2 knockout (Nrf2 KO) osteoclasts. Principal component analysis showed that 403 genes, including Nqo1, Il1f9, and Mmp12, were upregulated in Keap1 KO compared with WT osteoclasts, whereas 24 genes, including Snhg6, Ccdc109b, and Wfdc17, were upregulated in Nrf2 KO compared with WT osteoclasts. Moreover, 683 genes, including Car2, Calcr, and Pate4, were upregulated in Nrf2 KO cells compared to Keap1 KO cells. Functional analysis by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis showed upregulated genes in Nrf2 KO osteoclasts were mostly enriched in oxidative phosphorylation. Furthermore, GeneMANIA predicted the protein–protein interaction network of novel molecules such as Rufy4 from genes upregulated in Nrf2 KO osteoclasts. Understanding the complex interactions between these molecules may pave the way for developing promising therapeutic strategies against bone metabolic diseases caused by increased osteoclast differentiation under oxidative stress. Full article
(This article belongs to the Special Issue Role of Nrf2 and ROS in Bone Metabolism)
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Figure 1

Figure 1
<p>Microarray analysis of WT, <span class="html-italic">Nrf2</span> KO, and <span class="html-italic">Keap1</span> KO cells. (<b>A</b>) Splenic macrophages from WT, <span class="html-italic">Keap1</span> KO, and <span class="html-italic">Nrf2</span> KO mice were cultured with 30 ng/mL M-CSF and 50 ng/mL RANKL for three days, followed by TRAP staining. Representative photographs showing red-colored osteoclasts. (<b>a</b>) WT, (<b>b</b>) <span class="html-italic">Keap1</span> KO, and (<b>c</b>) <span class="html-italic">Nrf2</span> KO mice. Scale bars: 100 μm. (<b>B</b>) Splenic macrophages from two mice each of WT, <span class="html-italic">Keap1</span> KO, and <span class="html-italic">Nrf2</span> KO were cultured with 30 ng/mL M-CSF and 50 ng/mL RANKL for three days, and RNA was collected from each cell for DNA microarray analysis (single microarray analysis for each cell). Graphs showing scatter plots of (<b>a</b>) <span class="html-italic">Keap1</span> KO cells vs. WT osteoclasts, (<b>b</b>) <span class="html-italic">Nrf2</span> KO osteoclasts vs. WT osteoclasts, and (<b>c</b>) <span class="html-italic">Nrf2</span> KO osteoclasts vs. <span class="html-italic">Keap1</span> KO cells. Green lines indicate log<sub>2</sub>2 or log<sub>2</sub>0.5.</p>
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<p>Validation of microarray data. Upregulated genes in <a href="#antioxidants-13-01575-t001" class="html-table">Table 1</a> were confirmed by qRT-PCR. The relative mRNA levels of <span class="html-italic">Nqo1</span>, <span class="html-italic">Il1f9</span>, <span class="html-italic">Mmp12</span>, <span class="html-italic">Slc39a4</span>, <span class="html-italic">Fabp7</span>, <span class="html-italic">Cxcl14</span>, <span class="html-italic">Gsta3</span>, <span class="html-italic">Rnf128</span>, <span class="html-italic">Ly6g</span>, <span class="html-italic">Tanc2</span>, and <span class="html-italic">Gclm</span> in <span class="html-italic">Keap1</span> KO were confirmed. Data are presented as the mean ± SD from three independent experiments (* <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>Validation of microarray data. Downregulated genes in <a href="#antioxidants-13-01575-t002" class="html-table">Table 2</a> were confirmed by qRT-PCR. The relative mRNA levels of <span class="html-italic">Calcr</span>, <span class="html-italic">Scin</span>, <span class="html-italic">Ctsk</span>, <span class="html-italic">Pate4</span>, <span class="html-italic">Ocstamp</span>, <span class="html-italic">Ccr3</span>, <span class="html-italic">Tm4sf19</span>, and <span class="html-italic">Steap4</span> in <span class="html-italic">Keap1</span> KO were confirmed. Data are presented as the mean ± SD from three independent experiments (* <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01).</p>
Full article ">Figure 4
<p>Validation of microarray data. Upregulated genes in <a href="#antioxidants-13-01575-t003" class="html-table">Table 3</a> were confirmed by qRT-PCR. (<b>A</b>) Significant upregulation of <span class="html-italic">Snhg6</span> and <span class="html-italic">ccdc109b</span> in <span class="html-italic">Nrf2</span> KO osteoclasts derived from splenocyte were confirmed. <span class="html-italic">Ppbp</span> gene expression tended to increase. (<b>B</b>) Significant upregulation of <span class="html-italic">Snhg6</span>, <span class="html-italic">Wfdc17</span>, <span class="html-italic">Ppbp</span>, and <span class="html-italic">Ctsk</span> in <span class="html-italic">Nrf2</span> KO osteoclasts derived from BMMs were confirmed. Data are presented as the mean ± SD from three independent experiments (* <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>Validation of microarray data. Downregulated genes in <a href="#antioxidants-13-01575-t004" class="html-table">Table 4</a> were confirmed by qRT-PCR. Significant downregulation of <span class="html-italic">Ctse</span>, <span class="html-italic">Ifi202b</span>, <span class="html-italic">Me1</span>, <span class="html-italic">Cbr3</span>, <span class="html-italic">Thy1</span>, <span class="html-italic">Lrrc32</span>, <span class="html-italic">Rnf128</span>, <span class="html-italic">Cxcl14</span>, <span class="html-italic">Slc7a11</span>, and <span class="html-italic">Nqo1</span> in <span class="html-italic">Nrf2</span> KO osteoclasts were confirmed. Data are presented as the mean ± SD from three independent experiments (* <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01).</p>
Full article ">Figure 6
<p>Validation of microarray data. Upregulated genes in <a href="#antioxidants-13-01575-t005" class="html-table">Table 5</a> were confirmed by qRT-PCR. Significant upregulation of <span class="html-italic">Calcr</span>, <span class="html-italic">Pate4</span>, <span class="html-italic">Oscar</span>, <span class="html-italic">Scin</span>, <span class="html-italic">Akr1c18</span>, <span class="html-italic">Ctsk</span>, <span class="html-italic">Steap4</span>, <span class="html-italic">Adck3</span>, <span class="html-italic">Tm4sf19</span>, <span class="html-italic">Atp6v0d2</span>, and <span class="html-italic">Ccr3</span> in <span class="html-italic">Nrf2</span> KO osteoclasts were confirmed. Data are presented as the mean ± SD from three independent experiments (** <span class="html-italic">p</span> &lt; 0.01).</p>
Full article ">Figure 7
<p>Validation of microarray data. Downregulated genes in <a href="#antioxidants-13-01575-t006" class="html-table">Table 6</a> were confirmed by qRT-PCR. Significant downregulation of <span class="html-italic">Nqo1</span>, <span class="html-italic">Ctse</span>, <span class="html-italic">Cxcl14</span>, <span class="html-italic">Rnf128</span>, <span class="html-italic">Me1</span>, <span class="html-italic">Mmp12</span>, <span class="html-italic">Slc39a4</span>, <span class="html-italic">Gclm</span>, <span class="html-italic">Slc7a11</span>, <span class="html-italic">Cbr3</span>, and <span class="html-italic">Fabp7</span> in <span class="html-italic">Nrf2</span> KO osteoclasts were confirmed. Data are presented as the mean ± SD from three independent experiments (* <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01).</p>
Full article ">Figure 8
<p>GO enrichment analysis. (<b>A</b>) Up- or downregulated genes were analyzed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) for GO enrichment analysis in <span class="html-italic">Keap1</span> KO cells compared with WT osteoclasts. (<b>B</b>) Up- or downregulated genes were analyzed using DAVID for GO enrichment analysis in <span class="html-italic">Nrf2</span> KO osteoclasts compared with WT osteoclasts. (<b>C</b>) Up- or downregulated genes were analyzed using DAVID for GO enrichment analysis in <span class="html-italic">Nrf2</span> KO osteoclasts compared with <span class="html-italic">Keap1</span> KO cells.</p>
Full article ">Figure 8 Cont.
<p>GO enrichment analysis. (<b>A</b>) Up- or downregulated genes were analyzed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) for GO enrichment analysis in <span class="html-italic">Keap1</span> KO cells compared with WT osteoclasts. (<b>B</b>) Up- or downregulated genes were analyzed using DAVID for GO enrichment analysis in <span class="html-italic">Nrf2</span> KO osteoclasts compared with WT osteoclasts. (<b>C</b>) Up- or downregulated genes were analyzed using DAVID for GO enrichment analysis in <span class="html-italic">Nrf2</span> KO osteoclasts compared with <span class="html-italic">Keap1</span> KO cells.</p>
Full article ">Figure 8 Cont.
<p>GO enrichment analysis. (<b>A</b>) Up- or downregulated genes were analyzed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) for GO enrichment analysis in <span class="html-italic">Keap1</span> KO cells compared with WT osteoclasts. (<b>B</b>) Up- or downregulated genes were analyzed using DAVID for GO enrichment analysis in <span class="html-italic">Nrf2</span> KO osteoclasts compared with WT osteoclasts. (<b>C</b>) Up- or downregulated genes were analyzed using DAVID for GO enrichment analysis in <span class="html-italic">Nrf2</span> KO osteoclasts compared with <span class="html-italic">Keap1</span> KO cells.</p>
Full article ">Figure 9
<p>KEGG pathway enrichment analysis. Compared to <span class="html-italic">Keap1</span> KO cells, <span class="html-italic">Nrf2</span> KO osteoclasts exhibited a marked increase in expression of genes (surrounded by red lines) involved in oxidative phosphorylation (<b>A</b>) and osteoclast differentiation (<b>B</b>), whereas marked decreased in expression of genes (surrounded by blue lines) involved in focal adhesion (<b>C</b>) and ECM–receptor interaction (<b>D</b>).</p>
Full article ">Figure 9 Cont.
<p>KEGG pathway enrichment analysis. Compared to <span class="html-italic">Keap1</span> KO cells, <span class="html-italic">Nrf2</span> KO osteoclasts exhibited a marked increase in expression of genes (surrounded by red lines) involved in oxidative phosphorylation (<b>A</b>) and osteoclast differentiation (<b>B</b>), whereas marked decreased in expression of genes (surrounded by blue lines) involved in focal adhesion (<b>C</b>) and ECM–receptor interaction (<b>D</b>).</p>
Full article ">Figure 9 Cont.
<p>KEGG pathway enrichment analysis. Compared to <span class="html-italic">Keap1</span> KO cells, <span class="html-italic">Nrf2</span> KO osteoclasts exhibited a marked increase in expression of genes (surrounded by red lines) involved in oxidative phosphorylation (<b>A</b>) and osteoclast differentiation (<b>B</b>), whereas marked decreased in expression of genes (surrounded by blue lines) involved in focal adhesion (<b>C</b>) and ECM–receptor interaction (<b>D</b>).</p>
Full article ">Figure 10
<p>Protein–protein interaction network analysis by GeneMANIA. (<b>A</b>) Predicted network of proteins that interact with proteins encoded by the top 40 upregulated genes in <span class="html-italic">Nrf2</span> KO osteoclast against <span class="html-italic">Keap1</span> KO cells. (<b>B</b>) Predicted network of proteins interacting with proteins encoded by genes upregulated in Nrf2 KO osteoclast compared with WT osteoclasts.</p>
Full article ">Figure 10 Cont.
<p>Protein–protein interaction network analysis by GeneMANIA. (<b>A</b>) Predicted network of proteins that interact with proteins encoded by the top 40 upregulated genes in <span class="html-italic">Nrf2</span> KO osteoclast against <span class="html-italic">Keap1</span> KO cells. (<b>B</b>) Predicted network of proteins interacting with proteins encoded by genes upregulated in Nrf2 KO osteoclast compared with WT osteoclasts.</p>
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16 pages, 3520 KiB  
Article
Construction and Validation of CRISPR/Cas Vectors for Editing the PDS Gene in Banana (Musa spp.)
by Marcelly Santana Mascarenhas, Fernanda dos Santos Nascimento, Luana Maria Pacheco Schittino, Livia Batista Galinari, Lucymeire Souza Morais Lino, Andresa Priscila de Souza Ramos, Leandro Eugenio Cardamone Diniz, Tiago Antônio de Oliveira Mendes, Claudia Fortes Ferreira, Janay Almeida dos Santos-Serejo and Edson Perito Amorim
Curr. Issues Mol. Biol. 2024, 46(12), 14422-14437; https://doi.org/10.3390/cimb46120865 - 20 Dec 2024
Viewed by 334
Abstract
Bananas and plantains are important staple food crops affected by biotic and abiotic stresses. The gene editing technique via Clustered Regularly Interspaced Short Palindromic Repeats associated with the Cas protein (CRISPR/Cas) has been used as an important tool for development of cultivars with [...] Read more.
Bananas and plantains are important staple food crops affected by biotic and abiotic stresses. The gene editing technique via Clustered Regularly Interspaced Short Palindromic Repeats associated with the Cas protein (CRISPR/Cas) has been used as an important tool for development of cultivars with high tolerance to stresses. This study sought to develop a protocol for the construction of vectors for gene knockout. Here we use the phytoene desaturase (PDS) gene as a case study in Prata-Anã banana by the nonhomologous end junction (NHEJ) method. PDS is a key gene in the carotenoid production pathway in plants and its knockout leads to easily visualized phenotypes such as dwarfism and albinism in plants. Agrobacterium-mediated transformation delivered CRISPR/Cas9 constructs containing gRNAs were inserted into embryogenic cell suspension cultures. This is the first study to provide an effective method/protocol for constructing gene knockout vectors, demonstrating gene editing potential in a Brazilian banana variety. The constitutive (CaMV 35S) and root-specific vectors were successfully assembled and confirmed in transformed Agrobacterium by DNA extraction and PCR. The specificity of transformation protocols makes it possible to use the CRISPR-Cas9 technique to develop Prata-Anã banana plants with enhanced tolerance/resistance to major biotic and abiotic factors. Full article
(This article belongs to the Special Issue Molecular Breeding and Genetics Research in Plants, 2nd Edition)
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<p>Partial alignment resulting from the sequencing of the <span class="html-italic">PDS</span> genes of the banana genotypes Bucaneiro (AA), Zebrina (AA), and Prata-Anã (AAB) and sequences of the <span class="html-italic">PDS</span> gene of <span class="html-italic">Musa acuminata</span> and <span class="html-italic">Musa balbisiana</span> for gRNA design. The blue arrows indicate the selected gRNAs. Yellow highlights represent the gRNA nucleotides and green highlights indicate the PAM sequences. * Correspondence between the compared sequences, indicating a high degree of conservation.</p>
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<p>Maps of the vectors with CaMV 35S promoter and Part 1 + Part 2 + PCR Cas9 + Part 3 + Vector pDIRECT-22C (<b>A</b>) and vector with root-specific promoter with Part 1 + Part 4 + PCR Cas9 + Part 3 + Vector pDIRECT-22C (<b>B</b>) for use in banana cisgenesis via <span class="html-italic">Agrobacterium</span> transformation. The outer part of the vector contains the possible restriction enzymes for digesting the vectors.</p>
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<p>Digestion of the parts and vectors of interest in Gibson Assembly. M: 1 kB Plus NeoBio molecular weight marker (CV-1000 kB); 1: miniprep from Part 1 (undigested control); 2: 699 bp fragment excised from Part 1; 3: miniprep from Part 2 (undigested control); 4 and 5: 697 bp fragments excised from Part 2; 6: Cas9 miniprep in pUC57 (undigested control); 7 and 8: 5115 bp fragments excised from Cas9; 9: pDIRECT-22C vector miniprep (undigested control); 10, 11, and 12: 5400 bp fragments excised from pDIRECT-22C.</p>
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<p>Extraction of plasmid DNA from the constructs inserted into <span class="html-italic">Agrobacterium tumefaciens</span>. M: molecular weight marker 1 kB DNA Ladder—MMK-105S (Cellco); 1 and 2: amplicons with more than 10,000 bp equivalent to construct 1 (<b>A</b>) and 2 (<b>B</b>).</p>
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<p>PCR amplification of the <span class="html-italic">Agrobacterium tumefaciens</span> strain transformed with constructs 1 and 2. (<b>A</b>) PCR with primer set VC9_Fw and VC9_Rv (M: molecular weight marker 1 kB Plus DNA Ladder—MMK-130S (Cellco); C(-): negative control of the reaction with water; 1 and 2: 1912 bp amplicons at 45 °C for constructs 1 and 2). (<b>B</b>) PCR for primers Vp3C9_Fw and Vp3C9_Rv; M: marker; C(-): negative control; 1 and 2: 1000 bp amplicons at 51 °C.</p>
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<p>Process of genetic transformation and regeneration of the Prata-Anã banana. (<b>A</b>) Embryogenic cell suspension used for transformation with the CRISPR/Cas9 plasmid; (<b>B</b>) embryos in 2,4-D culture medium and transforming <span class="html-italic">Agrobacterium</span>; (<b>C</b>) embryos in polyester membrane and 2,4-D + AS culture medium (T1) after 0 days and the different treatments (<b>D</b>–<b>G</b>) with BAP + AIA + Kan + Timentin culture medium ((<b>D</b>): T1, (<b>E</b>): T2, (<b>F</b>): T3, (<b>G</b>): T4) after 70 days of transformation, kept at 25 °C with a 16 h/8 h photoperiod.</p>
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12 pages, 1447 KiB  
Article
Proximity Proteomics Reveals USP44 Forms a Complex with BRCA2 in Neuroblastoma Cells and Is Required to Prevent Chromosome Breakage
by Asma Ali, Sajjad Hussain, Tibor Bedekovics, Raymond H. Jeon, Danielle G. May, Kyle J. Roux and Paul J. Galardy
Biomedicines 2024, 12(12), 2901; https://doi.org/10.3390/biomedicines12122901 - 20 Dec 2024
Viewed by 285
Abstract
Background/Objectives: The enzyme ubiquitin-specific protease 44 (USP44) is a deubiquitinating enzyme with identified physiological roles as a tumor suppressor and an oncogene. While some binding partners and substrates are known for USP44, the identification of other interactions may improve our understanding of its [...] Read more.
Background/Objectives: The enzyme ubiquitin-specific protease 44 (USP44) is a deubiquitinating enzyme with identified physiological roles as a tumor suppressor and an oncogene. While some binding partners and substrates are known for USP44, the identification of other interactions may improve our understanding of its role in cancer. We therefore performed a proximity biotinylation study that identified products of several known cancer genes that are associated with USP44, including a novel interaction between BRCA2 and USP44. Methods: We expressed a fusion protein that linked USP44 and mutant Escherichia coli biotin ligase BioID in SH-SY5Y neuroblastoma cells. Control experiments were performed using BioID alone. In duplicate experiments, cells were pulsed with biotin and biotinylated proteins were isolated under denaturing conditions and the proteins were identified by mass spectrometry. The resulting list of proteins were analyzed using Enrichr and cross-referenced with the COSMIC Cancer Gene Census. We validated the association with BRCA2 using immunoprecipitation. The role of USP44 in the Fanconi anemia DNA repair pathway was investigated using chromosome analysis of wild-type or Usp44-knockout cells after exposure to mitomycin C. Results: We identified 146 proteins that were selectively retrieved by the USP44 construct and compared with cells expressing the BioID ligase alone, including 15 gene products encoded by genes on tier 1 of the COSMIC Cancer Gene Census, including BRCA2. The association between USP44 and BRCA2 was validated through immunoprecipitation. We tested the functional role of USP44 in the Fanconi anemia DNA repair pathway through chromosome breakage analysis and found that cells lacking USP44 had a significant increase in chromosome breaks and radial chromosomes. We found that high BRCA2 transcript was correlated with poor survival in neuroblastoma, likely due to its tight association with proliferation in these tumors. Conclusions: Our results identified novel potential binding partners and potential substrates for USP44, including several with direct roles in cancer pathogenesis. Our results identified a novel association between BRCA2 and USP44, and a previously unknown role for USP44 in the Fanconi anemia DNA repair pathway that may contribute to its role in cancer. Full article
(This article belongs to the Special Issue Ubiquitylation and Deubiquitylation in Health and Diseases)
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<p>Expression of BioID or BioID-USP44 in SH-SY5Y cells. (<b>A</b>) Cells of the neuroblastoma cell line SH-SY5Y were transduced with lentivirus encoding the BioID biotin ligase alone, or as an N-terminal fusion with USP44. The expression of both was monitored by immunoblotting to detect the MYC-tag encoded in BioID. (<b>B</b>) SH-SY5Y cells as in (<b>A</b>) were incubated with biotin for 16 h and the presence of biotinylated proteins was monitored by probing blots with streptavidin-HRP.</p>
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<p>The proximity proteome of USP44 identified a novel function in the Fanconi anemia DNA repair pathway. (<b>A</b>,<b>B</b>) Enrichr analysis using the list of biotinylated proteins recovered (enrichment &gt; 3-fold) from SH-SY5Y cells expressing the USP44-BioID fusion compared with those expressing BioID alone. Adjusted <span class="html-italic">p</span>-values (correction for multiple hypothesis testing) are shown. (<b>C</b>,<b>D</b>) SH-SY5Y cells expressing BRCA2-GFP (<b>C</b>) or not (<b>D</b>) were transduced with lentivirus-encoding USP44-HA followed by HA immunoprecipitation and immunoblotting for the indicated proteins. In (<b>C</b>), a short or long exposure of the blot was performed as indicated. The results are representative of at least three independent experiments.</p>
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<p>The proximity proteome of USP44 identifies a novel function in the Fanconi anemia DNA repair pathway. (<b>A</b>,<b>B</b>) Chromosome analysis was performed on colcemid-prepared metaphase preparations from murine embryonic fibroblasts (MEFs) with the indicated genotypes, with pre-treatment with the indicated concentrations of mitomycin C. The graphs represent the means +/− SEM of three independent MEF lines (prepared from independent embryos) and depict the number of chromosome breaks (<b>A</b>) or radial chromosome forms (<b>B</b>) <span class="html-italic">p</span>-values calculated using an unpaired Student’s <span class="html-italic">t</span>-test comparing <span class="html-italic">Usp44-</span>null to the other conditions at each concentration of MMC. (<b>C</b>) A representative metaphase spread from a <span class="html-italic">Usp44-</span>null culture treated with mitomycin C with a chromosome break (upper inset; indicated by arrow) and radial chromosome form (lower inset).</p>
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<p>High <span class="html-italic">BRCA2</span> predicts poor outcomes and rapid proliferation in neuroblastoma. (<b>A</b>) The event-free survival is shown for patients in the SEQC dataset (<span class="html-italic">n</span> = 498) stratified by <span class="html-italic">BRCA2</span> expression (median). <span class="html-italic">p</span>-value calculated with the log-rank test. (<b>B</b>–<b>D</b>) Mean <span class="html-italic">BRCA2</span> transcript level is shown in patients from SEQC dataset separated by clinical stage (<b>B</b>), Shimada histology (<b>B</b>), and <span class="html-italic">MYCN</span> gene status (<b>C</b>). <span class="html-italic">p</span>-values calculated using the unpaired <span class="html-italic">t</span>-test. (<b>E</b>) Correlation between the transcript level of <span class="html-italic">BRCA2</span> and the Whitfield proliferation signature score. Each dot represents the BRCA2 level and the proliferation signature score for an individual tumor. The R-value represents the Pearson correlation value, and the corresponding 2-tailed <span class="html-italic">p</span>-value. (<b>F</b>) The event-free survival is shown for patients from the SEQC dataset with low Whitfield proliferation signature scores (&lt;median; <span class="html-italic">n</span> = 249) stratified on BRCA2 expression (median).</p>
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14 pages, 9361 KiB  
Article
H3K4me3 Genome-Wide Distribution and Transcriptional Regulation of Transposable Elements by RNA Pol2 Deposition
by Xiaowei Chen, Hua Yang, Liqin Wang, Ying Chen, Yingnan Yang, Haonan Chen, Feng Wang, Yanli Zhang and Mingtian Deng
Int. J. Mol. Sci. 2024, 25(24), 13545; https://doi.org/10.3390/ijms252413545 - 18 Dec 2024
Viewed by 252
Abstract
Zygotic genome activation (ZGA) is critical for early embryo development and is meticulously regulated by epigenetic modifications. H3K4me3 is a transcription-permissive histone mark preferentially found at promoters, but its distribution across genome features remains incompletely understood. In this study, we investigated the genome-wide [...] Read more.
Zygotic genome activation (ZGA) is critical for early embryo development and is meticulously regulated by epigenetic modifications. H3K4me3 is a transcription-permissive histone mark preferentially found at promoters, but its distribution across genome features remains incompletely understood. In this study, we investigated the genome-wide enrichment of H3K4me3 during early embryo development and embryonic stem cells (ESCs) in both sheep and mice. We discovered that broad H3K4me3 domains were present in MII stage oocytes and were progressively diminished, while promoter H3K4me3 enrichment was increased and correlated with gene upregulation during ZGA in sheep. Additionally, we reported the dynamic distribution of H3K4me3 at the transposable elements (TEs) during early embryo development in both sheep and mice. Specifically, the H3K4me3 distribution of LINE1 and ERVL, two subsets of TEs, was associated with their expression during early embryo development in sheep. Furthermore, H3K4me3 enrichment in TEs was greatly increased during ZGA following Kdm5b knockdown, and the distribution of RNA polymerase II (Pol2) in TEs was also markedly increased in Kdm5b knockout ESCs in mice. These findings suggest that H3K4me3 plays important roles in regulating TE expression through interaction with RNA Pol2, providing valuable insights into the regulation of ZGA initiation and cell fate determination by H3K4me3. Full article
(This article belongs to the Special Issue Molecular Genetic Biology in Embryonic Development)
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<p>Genome-wide profiling of H3K4me3 during sheep early embryo development. (<b>A</b>) Snapshot of H3K4me3 distribution in chromosome 8 in the oocyte, 2-, 8-, and 16-cell stage embryos, morula embryos, blastocyst embryos, and ESCs in sheep. (<b>B</b>) Boxplot of H3K4me3 signals in sheep early embryos. (<b>C</b>) PCA plot showed that H3K4me3 enriched regions of 2-, 4-, 8-, and 16-cell stage embryos, MII stage oocytes, morula, blastocyst, and ESCs were clearly separated from each other. (<b>D</b>) Frequency of H3K4me3 enrichment of the early embryo in the genome features. (<b>E</b>) Metaplot of H3K4me3 in transcription start site (start) and transcription end sites (end) in the oocyte, 2-, 8-, and 16-cell stage embryos, morula embryos, blastocyst embryos, and ESCs in sheep. (<b>F</b>) Heatmap and Gene Ontology analysis of the promoter H3K4me3 in the oocyte, 2-, 8-, and 16-cell stage embryos, morula embryos, blastocyst embryos, and ESCs in sheep. (<b>G</b>) Motif analysis revealed H3K4me3 enrichment in Gata3 in blastocyst and Sox2 in ESC. MII, MII stage oocytes; 2C/8C/16C, 2-, 8-, and 16-cell stage embryos; Mo, morula embryos; BL, blastocyst embryos; ESC, embryonic stem cell.</p>
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<p>Removal of H3K4me3 broad domains during early embryo development. (<b>A</b>) Snapshot revealing that H3K4me3 broad domains occurred in sheep MII stage oocytes and were shifted to sharp peaks after fertilization. (<b>B</b>,<b>C</b>) Heatmaps and boxplot showing removal of H3K4me3 broad domains during early embryo development. (<b>D</b>) The distribution of H3K4me3 broad domain-deposited genes during early embryo development in sheep.</p>
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<p>Increased H3K4me3 distribution correlates with gene upregulation during ZGA (<b>A</b>) Identification of morula-higher H3K4me3 peaks by comparing the distribution of H3K4me3 in the MII stage oocytes and the morula embryos. (<b>B</b>) Morula-specific H3K4me3 signal in various genome features. (<b>C</b>) Frequency of morula-higher H3K4me3 regions in the genome features. (<b>D</b>) Gene Ontology analysis of morula-higher H3K4me3 peaks. (<b>E</b>) Identification of oocyte-higher H3K4me3 peaks by comparing the distribution of H3K4me3 in the MII stage oocytes and the morula embryos. (<b>F</b>) Boxplot of H3K4me3 signal in morula-higher peaks and gene expression of morula-higher peak-deposited genes in the MII stage oocytes and the morula embryos. (<b>G</b>) Boxplot of H3K4me3 signal in oocyte-higher peaks and gene expression of morula-higher peak-deposited genes in the MII stage oocytes and the morula embryos.</p>
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<p>Dynamic H3K4me3 changes at TEs during early embryo development. (<b>A</b>) Metaplot and boxplot of H3K4me3 in LINE1 in oocyte, 2-, 8-, and 16-cell stage embryos, morula embryos, blastocyst embryos, and ESCs in sheep. (<b>B</b>) Expression of LINE1 during early embryo development in sheep. (<b>C</b>) Metaplot and boxplot of H3K4me3 in ERVL in oocytes, 2-, 8-, and 16-cell stage embryos, morula embryos, blastocyst embryos, and ESCs in sheep. (<b>D</b>) Expression of ERVL during early embryo development in sheep. (<b>E</b>) Metaplot and boxplot of H3K4me3 in LINE1 in oocytes, 2-, and 8-cell stage embryos, morula embryos, ICM. TE, and ESCs in mice. (<b>F</b>) Metaplot and boxplot of H3K4me3 in ERVL in oocytes, 2-, and 8-cell stage embryos, morula embryos, ICM, TE, and ESCs in mice. (<b>G</b>) Expression of LINE1 and ERVL in the control and the Kdm5b knockdown embryos at the 2-cell stage. (<b>H</b>) Metaplot and boxplot of H3K4me3 in upregulation and/or downregulation genes after ERVL was knocked down in mouse 2-cell stage embryos. MII, MII stage oocytes; 2C/8C/16C, 2-, 8-, and 16-cell stage embryos; Mo, morula embryos; BL, blastocyst embryos; ICM, inner cell mass; TE, trophectoderm; ESC, embryonic stem cell. RPKM, Reads Per Kilobase per Million mapped reads.</p>
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<p>Increment RNA Pol2 distribution in TEs in Kdm5b knockout ESCs. (<b>A</b>,<b>B</b>) Metaplot and boxplot of H3K4me3 in LINE1 and/or ERVL in Kdm5b knockdown ESCs. (<b>C</b>) Metaplot and boxplot of RNA Pol2 in LTR, ERV1, ERVL, and ERVK in Kdm5b knockdown ESCs. (<b>D</b>) Metaplot and boxplot of RNA Pol2 in LINE1 and LINE2 in Kdm5b knockdown ESCs. (<b>E</b>) Metaplot and boxplot of RNA Pol2 in SINE B2 and Alu in Kdm5b knockdown ESCs. (<b>F</b>) Metaplot and boxplot of RNA Pol2 Ser2P in ERV1, ERVL, LTR, and Alu in Kdm5b knockdown ESCs.</p>
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15 pages, 3634 KiB  
Article
Chemogenetic Inhibition of Prefrontal Cortex Ameliorates Autism-Like Social Deficits and Absence-Like Seizures in a Gene-Trap Ash1l Haploinsufficiency Mouse Model
by Kaijie Ma, Kylee McDaniel, Daoqi Zhang, Maria Webb and Luye Qin
Genes 2024, 15(12), 1619; https://doi.org/10.3390/genes15121619 - 18 Dec 2024
Viewed by 335
Abstract
Background: ASH1L (absent, small, or homeotic-like 1), a histone methyltransferase, has been identified as a high-risk gene for autism spectrum disorder (ASD). We previously showed that postnatal Ash1l severe deficiency in the prefrontal cortex (PFC) of male and female mice caused seizures. However, [...] Read more.
Background: ASH1L (absent, small, or homeotic-like 1), a histone methyltransferase, has been identified as a high-risk gene for autism spectrum disorder (ASD). We previously showed that postnatal Ash1l severe deficiency in the prefrontal cortex (PFC) of male and female mice caused seizures. However, the synaptic mechanisms underlying autism-like social deficits and seizures need to be elucidated. Objective: The goal of this study is to characterize the behavioral deficits and reveal the synaptic mechanisms in an Ash1l haploinsufficiency mouse model using a targeted gene-trap knockout (gtKO) strategy. Method: A series of behavioral tests were used to examine behavioral deficits. Electrophysiological and chemogenetic approaches were used to examine and manipulate the excitability of pyramidal neurons in the PFC of Ash1l+/GT mice. Results: Ash1l+/GT mice displayed social deficits, increased self-grooming, and cognitive impairments. Epileptiform discharges were found on electroencephalograms (EEGs) of Ash1l+/GT mice, indicating absence-like seizures. Ash1l haploinsufficiency increased the susceptibility for convulsive seizures when Ash1l+/GT mice were challenged by pentylenetetrazole (PTZ, a competitive GABAA receptor antagonist). Whole-cell patch-clamp recordings showed that Ash1l haploinsufficiency increased the excitability of pyramidal neurons in the PFC by altering intrinsic neuronal properties, enhancing glutamatergic synaptic transmission, and diminishing GABAergic synaptic inhibition. Chemogenetic inhibition of pyramidal neurons in the PFC of Ash1l+/GT mice ameliorated autism-like social deficits and abolished absence-like seizures. Conclusions: We demonstrated that increased neural activity in the PFC contributed to the autism-like social deficits and absence-like seizures in Ash1l+/GT mice, which provides novel insights into the therapeutic strategies for patients with ASH1L-associated ASD and epilepsy. Full article
(This article belongs to the Special Issue The Genetic and Epigenetic Basis of Neurodevelopmental Disorders)
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<p>Validation of gene-trap knockout of <span class="html-italic">Ash1l</span> in the brain. (<b>A</b>) A schematic diagram showing gene-trap cassette insertion into the intron 1 of the <span class="html-italic">Ash1l</span> gene. SA: splicing acceptor; β-geo: β-galactosidase; Neo, neomycin; pA: polyadenylation sequence. (<b>B</b>) A representative PCR analysis showing the genotyping of mice with indicated genotypes. (<b>C</b>) A representative image showing LacZ signals in the whole brain from a Ash1l<sup>+/GT</sup> mouse. (<b>D</b>) Quantitative PCR showing <span class="html-italic">Ash1l</span> mRNA levels in PFC of Ash1l<sup>+/+</sup> and Ash1l<sup>+/GT</sup> mice. *** <span class="html-italic">p</span> &lt; 0.001, unpaired two-tailed <span class="html-italic">t</span>-test. n = 12 mice (6 males and 6 females)/group. (<b>E</b>) Western blot showing Ash1l protein levels in PFC of Ash1l<sup>+/+</sup> and Ash1l<sup>+/GT</sup> mice. ** <span class="html-italic">p</span> &lt; 0.01, unpaired two-tailed <span class="html-italic">t</span>-test. n = 8 mice (4 males and 4 females)/group.</p>
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<p><span class="html-italic">Ash1l</span> haploinsufficiency causes autism-like behavioral deficits in male and female mice. Bar graphs showing the investigation time (<b>A</b>) and social preference index (<b>B</b>) in the three-chamber sociability test. A: *** <span class="html-italic">p</span> &lt; 0.001, Soc versus NS; ### <span class="html-italic">p</span> &lt; 0.001, Ash1l<sup>+/GT</sup> versus Ash1l<sup>+/+</sup> mice. B: *** <span class="html-italic">p</span> &lt; 0.001, Ash1l<sup>+/GT</sup> versus Ash1l<sup>+/+</sup> mice. (<b>C</b>) Representative heatmaps illustrating the time spent in different locations during social preference test. (<b>D</b>) Bar graphs showing the self-grooming time in Ash1l<sup>+/+</sup> and Ash1l<sup>+/GT</sup> mice. ** <span class="html-italic">p</span> &lt; 0.01, Ash1l<sup>+/GT</sup> versus Ash1l<sup>+/+</sup> mice. (<b>E</b>) Bar graphs showing the discrimination index and representative heatmaps (<b>F</b>) showing the time spent exploring the familiar and novel object during the NOR test. (<b>G</b>) Bar graphs showing the spatial memory index (T1/T2) and representative heatmaps (<b>H</b>) illustrating the time spent in different locations of the arena in Barnes maze test. *** <span class="html-italic">p</span> &lt; 0.001, Ash1l<sup>+/GT</sup> versus Ash1l<sup>+/+</sup> mice. (<b>I</b>,<b>J</b>) Bar graphs and representative trajectory diagrams (<b>K</b>) showing time spent in center and total distance traveled during open field test. (<b>L</b>) Bar graphs showing the latency to fall in the rotarod test. Ash1l<sup>+/+</sup> mice: n = 15 mice (7 males and 8 females); Ash1l<sup>+/GT</sup> mice: n = 14 mice (7 males and 7 females).</p>
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<p><span class="html-italic">Ash1l</span> haploinsufficiency causes absence-like seizures and increases the susceptibility for PTZ-induced convulsive seizures. (<b>A</b>) Representative EEG recordings showing the neural activity in the PFC of freely moving Ash1l<sup>+/+</sup> and Ash1l<sup>+/GT</sup> mice. (<b>B</b>) Comparison of percentage of total power in each EEG frequency band between Ash1l<sup>+/+</sup> and Ash1l<sup>+/GT</sup> mice. EEG band: Delta (0.1–4 Hz), Theta (4–8 Hz), Alpha (8–13 Hz), Beta (13–30 Hz), and Gamma (30–60 Hz). ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, unpaired two-tailed <span class="html-italic">t</span> test, Ash1l<sup>+/GT</sup> versus Ash1l<sup>+/+</sup> mice. n = 6 mice (3 males and 3 females)/group. (<b>C</b>) Plots showing the Racine score of seizure activity in Ash1l<sup>+/+</sup> and Ash1l<sup>+/GT</sup> mice induced by PTZ. * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001, Ash1l<sup>+/GT</sup> versus Ash1l<sup>+/+</sup> mice. n = 20 mice (10 males and 10 females)/group, two-way ANOVA.</p>
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<p><span class="html-italic">Ash1l</span> haploinsufficiency significantly increases the intrinsic excitability of pyramidal neurons in the PFC of male and female mice. (<b>A</b>) Quantification of the number of evoked action potentials in the pyramidal neurons from Ash1l<sup>+/+</sup> and Ash1l<sup>+/GT</sup> mice. *** <span class="html-italic">p</span> &lt; 0.001, two-way ANOVA. n = 20 neurons/2 male and 3 female mice/group. (<b>B</b>) Representative action potential traces. Bar graphs showing rheobase (<b>C</b>), first spike delay (<b>D</b>), threshold (<b>E</b>), resting membrane potential (<b>F</b>), capacitance (<b>G</b>), input resistance (<b>H</b>), and membrane time constant (<b>I</b>) in the pyramidal neurons from Ash1l<sup>+/+</sup> and Ash1l<sup>+/GT</sup> mice. *** <span class="html-italic">p</span> &lt; 0.001, unpaired two-tailed <span class="html-italic">t</span>-test. n = 20 neurons/2 male and 3 female mice/group.</p>
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<p><span class="html-italic">Ash1l</span> haploinsufficiency elevates the balance of excitatory and inhibitory synaptic transmission. (<b>A</b>) Bar graphs showing the frequency of synaptic-driven sAP in pyramidal neurons of PFC from Ash1l<sup>+/+</sup> and Ash1l<sup>+/GT</sup> mice. *** <span class="html-italic">p</span> &lt; 0.001, unpaired two-tailed <span class="html-italic">t</span>-test. n = 20 neurons/2 male and 3 female mice/group. (<b>B</b>) Representative sAP traces. Bar graphs of spontaneous EPSC amplitude (<b>C</b>) and frequency (<b>D</b>) in pyramidal neurons of PFC from Ash1l<sup>+/+</sup> and Ash1l<sup>+/GT</sup> mice. *** <span class="html-italic">p</span> &lt; 0.001, unpaired two-tailed <span class="html-italic">t</span>-test. n = 20 cells/2 male and 3 female mice/group. (<b>E</b>) Representative sEPSC traces. Bar graphs of spontaneous IPSC amplitude (<b>F</b>) and frequency (<b>G</b>) in pyramidal neurons of PFC from Ash1l<sup>+/+</sup> and Ash1l<sup>+/GT</sup> mice. *** <span class="html-italic">p</span> &lt; 0.001, unpaired two-tailed <span class="html-italic">t</span>-test. n = 20 neurons/2 male and 3 female mice/group. (<b>H</b>) Representative sIPSC traces.</p>
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<p><span class="html-italic">Ash1l</span> haploinsufficiency alters the transcriptional levels of the key synaptic genes in the PFC of Ash1l<sup>+/+</sup> and Ash1l<sup>+/GT</sup> mice. Quantitative real-time PCR showing the transcriptional level of the key excitatory (<b>A</b>) and inhibitory (<b>B</b>) synaptic genes in the PFC of Ash1l<sup>+/+</sup> and Ash1l<sup>+/GT</sup> mice. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, unpaired two-tailed <span class="html-italic">t</span>-test. n = 12 mice (6 males and 6 females)/group.</p>
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<p>Chemogenetic inhibition of PFC ameliorates autism-like social deficits and abolishes absence-like seizures in Ash1l<sup>+/GT</sup> mice. (<b>A</b>) A confocal image showing the expression of Gi-DREADD in the medial PFC (stained with DAPI, blue) from a Ash1l<sup>+/GT</sup> mouse. Scale bar: 300 µm. Bar graphs showing the time spent investigating social (Soc) and non-social (NS) stimulus (<b>B</b>) and social preference index (<b>C</b>) in the three-chamber sociability test of Ash1l<sup>+/GT</sup> mice (Gi-DREADD) treated with saline or CNO. A: *** <span class="html-italic">p</span> &lt; 0.001, Soc versus NS; ### <span class="html-italic">p</span> &lt; 0.001, CNO versus saline. B: *** <span class="html-italic">p</span> &lt; 0.001, CNO versus saline. n = 12 mice (6 males and 6 females)/group. (<b>D</b>) Representative heatmaps illustrating the time spent in different locations from the social preference test. (<b>E</b>) Representative EEG recordings showing chemogenetic inhibition of PFC abolishes epileptiform discharges in freely moving Ash1l<sup>+/GT</sup> mice infected with Gi-DREADD. (<b>F</b>) Comparison of percentage of total power in each EEG frequency band between Ash1l<sup>+/GT</sup> mice (Gi-DREADD) treated with saline or CNO. EEG band: Delta (0.1–4 Hz), Theta (4–8 Hz), Alpha (8–13 Hz), Beta (13–30 Hz), and Gamma (30–60 Hz). ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, CNO versus saline, unpaired two-tailed <span class="html-italic">t</span>-test. n = 6 mice (3 males and 3 females)/group.</p>
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12 pages, 2939 KiB  
Article
Bombyx mori Metal Carboxypeptidases12 (BmMCP12) Is Involved in Host Protection Against Viral Infection
by Liang Tang, Qiong-Qiong Wei, Yu Xiao, Ming-Yan Tang, Yan Zhu, Man-Gui Jiang, Peng Chen and Zhi-Xin Pan
Int. J. Mol. Sci. 2024, 25(24), 13536; https://doi.org/10.3390/ijms252413536 - 18 Dec 2024
Viewed by 307
Abstract
Baculoviruses, the largest studied insect viruses, are highly pathogenic to host insects. Bombyx mori nucleopolyhedrovirus (BmNPV) is the main cause of nuclear polyhedrosis of silkworm, a viral disease that causes significant economic losses to the sericulture industry. The anti-BmNPV mechanism of the silkworm [...] Read more.
Baculoviruses, the largest studied insect viruses, are highly pathogenic to host insects. Bombyx mori nucleopolyhedrovirus (BmNPV) is the main cause of nuclear polyhedrosis of silkworm, a viral disease that causes significant economic losses to the sericulture industry. The anti-BmNPV mechanism of the silkworm has not yet been characterized. Carboxypeptidase is an enzyme that is involved in virtually all life activities of animals and plants. Studies have shown that the carboxypeptidase family is related to insect immunity. There are few reports on the role of carboxypeptidase in the defense of silkworms against pathogen invasion. In this study, we identified the homologous gene Bombyx mori metal carboxypeptidases12 (BmMCP12) related to mammalian carboxypeptidase A2 (CPA2) and found that BmMCP12 had a Zn-pept domain. The BmMCP12 gene was primarily located in the cytoplasm and was highly expressed in the midgut of silkworms, and the expression level in BmN-SWU1 cells was upregulated after infection with BmNPV. After overexpression of the BmMCP12 gene, quantitative real-time (qRT)-PCR and Western blots showed that BmMCP12 could inhibit BmNPV replication, whereas knockout of the gene had the opposite effect. In addition, we constructed transgenic silkworm strains with a knockout of BmMCP12, and the transgenic strains had reduced resistance to BmNPV. These findings deepen the functional study of silkworm carboxypeptidase and provide a new target for BmNPV disease prevention in silkworms. Full article
(This article belongs to the Section Molecular Microbiology)
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<p>Identification of <span class="html-italic">BmMCP12</span> gene. (<b>A</b>) Gene structure of <span class="html-italic">BmMCP12</span> gene. (<b>B</b>) Prediction of BmMCP12 protein domains. (<b>C</b>) Carboxypeptidase A protein Zn_pept domain’s multiple-sequence alignment. Bm, <span class="html-italic">Bombyx mori</span>; Hs, <span class="html-italic">Homo sapiens</span>; Mm, <span class="html-italic">Mus musculus</span>; Ms, <span class="html-italic">Manduca sexta</span>; Of, <span class="html-italic">Ostrinia furnacalis</span>; Am, <span class="html-italic">Apis mellifera</span>; Mv, <span class="html-italic">Musca vetustissima</span>; Dc, <span class="html-italic">Diaphorina citri</span>. *, 10 amino acids apart. (<b>D</b>) Phylogenetic tree analysis of BmMCP12. Pink represents Vertebrata; yellow represents Diptera; green represents Lepidoptera; orange represents Hemiptera; and blue represents Hymenoptera.</p>
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<p>Expression patterns of <span class="html-italic">BmMCP12</span> gene. (<b>A</b>) Period expression analysis of <span class="html-italic">BmMCP12</span>. (<b>B</b>) Expression of <span class="html-italic">BmMCP12</span> in tissues, including epidermis, fat body, gonad, head, hemolymph, Malpighian tubule, midgut, silk glands, and trachea, of 5th-instar larvae on first day. (<b>C</b>) Subcellular localization of BmMCP12.</p>
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<p>Effects of overexpression of <span class="html-italic">BmMCP12</span> on BmNPV replication. (<b>A</b>) Quantitative real-time (qRT)-PCR analysis of <span class="html-italic">BmMCP12</span> gene after BmNPV supplementation. (<b>B</b>) qRT-PCR analysis of BmNPV <span class="html-italic">ie1</span> gene after overexpression of <span class="html-italic">BmMCP12</span>. (<b>C</b>) qRT-PCR analysis of BmNPV <span class="html-italic">vp39</span> gene after overexpression of <span class="html-italic">BmMCP12</span>. (<b>D</b>) qRT-PCR analysis of genome copies of BmNPV after overexpression of <span class="html-italic">BmMCP12</span>. (<b>E</b>,<b>F</b>) Western blot analysis of BmNPV Polh protein after overexpression of <span class="html-italic">BmMCP12</span>. *** <span class="html-italic">p</span> &lt; 0.001; ** <span class="html-italic">p</span> &lt; 0.01; * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Effects of knockout of <span class="html-italic">BmMCP12</span> on BmNPV replication. (<b>A</b>) Schematic diagram of <span class="html-italic">BmMCP12</span> gene’s CRISPR/Cas9 knockout vector. (<b>B</b>) qRT-PCR analysis of BmNPV <span class="html-italic">ie1</span> gene after knockout of <span class="html-italic">BmMCP12</span>. (<b>C</b>) qRT-PCR analysis of BmNPV <span class="html-italic">vp39</span> gene after knockout of <span class="html-italic">BmMCP12</span>. (<b>D</b>) qRT-PCR analysis of genome copies of BmNPV after knockout of <span class="html-italic">BmMCP12</span>. (<b>E</b>,<b>F</b>) Western blot analysis of BmNPV Polh protein after knockout of <span class="html-italic">BmMCP12</span>. *** <span class="html-italic">p</span> &lt; 0.001; ** <span class="html-italic">p</span> &lt; 0.01; * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>The effects of <span class="html-italic">BmMCP12</span> on BmNPV infection at the individual level. (<b>A</b>) The construction of transgenic lines. The plasmid containing the <span class="html-italic">enhanced green fluorescent protein</span> (<span class="html-italic">EGFP</span>) gene and the <span class="html-italic">Cas9</span> gene was injected into the silkworms to produce transgenic silkworm moths with green fluorescence in their eyes. The plasmid containing the red fluorescence gene (DsRed) and sgBmMCP12 was injected into silkworms to obtain transgenic silkworms with red fluorescence in their eyes. (<b>B</b>) qRT-PCR analysis showed the expression of <span class="html-italic">BmMCP12</span> in the transgenic knockout lines (Cas9(+)/sgBmMCP12(+)) and control lines (Cas9(−)/sgBmMCP12(−)). (<b>C</b>,<b>D</b>) Statistics on the mortality rate of the transgenic knockout lines (Cas9(+)/sgBmMCP12(+)) and control lines (Cas9(−)/sgBmMCP12(−)). *** <span class="html-italic">p</span> &lt; 0.001; * <span class="html-italic">p</span> &lt; 0.05.</p>
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16 pages, 6782 KiB  
Article
Functional Characterization of FgAsp, a Gene Coding an Aspartic Acid Protease in Fusarium graminearum
by Ping Li, Zhizhen Fu, Mengru Wang, Tian Yang, Yan Li and Dongfang Ma
J. Fungi 2024, 10(12), 879; https://doi.org/10.3390/jof10120879 - 17 Dec 2024
Viewed by 342
Abstract
Aspartic proteases (APs), hydrolases with aspartic acid residues as catalytic active sites, are closely associated with processes such as plant growth and development and fungal and bacterial pathogenesis. F. graminearum is the dominant pathogenic fungus that causes Fusarium head blight (FHB) in wheat. [...] Read more.
Aspartic proteases (APs), hydrolases with aspartic acid residues as catalytic active sites, are closely associated with processes such as plant growth and development and fungal and bacterial pathogenesis. F. graminearum is the dominant pathogenic fungus that causes Fusarium head blight (FHB) in wheat. However, the relationship of APs to the growth, development, and pathogenesis of F. graminearum is not clear. Therefore, we selected the FGSG_09558 gene, whose function annotation is aspartate protease, for further study. In this study, FGSG_09558 was found to contain a conserved structural domain and signal peptide sequence of aspartic acid protease and was therefore named FgAsp. The function of FgAsp in F. graminearum was investigated by constructing the knockout and complementation mutants of this gene. The results showed that with respect to the wild type (PH-1), the knockout mutant showed a significant reduction in mycelial growth, asexual spore production, and sexual spore formation, highlighting the key role of FgAsp in the growth and development of F. graminearum. In addition, the mutants showed a significant reduction in the virulence and accumulation level of deoxynivalenol (DON) content on maize whiskers, wheat germ sheaths, and wheat ears. DON, as a key factor of virulence, plays an important role in the F. graminearum infection of wheat ears, suggesting that FgAsp is involved in the regulation of F. graminearum pathogenicity by affecting the accumulation of the DON toxin. FgAsp had a significant effect on the ability of F. graminearum to utilize various sugars, especially arabinose. In response to the stress, hydrogen peroxide inhibited the growth of the mutant most significantly, indicating the important function of FgAsp in the strain’s response to environmental stress. Finally, FgAsp plays a key role in the regulation of F. graminearum growth and development, pathogenicity, and environmental stress response. Full article
(This article belongs to the Special Issue Growth and Virulence of Plant Pathogenic Fungi)
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<p>The <span class="html-italic">FgAsp</span> gene deletion and complementation strategies.</p>
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<p>Description of <span class="html-italic">FgAsp</span>. (<b>A</b>) Conserved functional domain. (<b>B</b>) Identification of transmembrane domains. (<b>C</b>) Three-dimensional homology modeling. (<b>D</b>) Signal peptide prediction results. (<b>E</b>) Gene expression level of <span class="html-italic">FgAsp</span> in <span class="html-italic">F. graminearum</span>.</p>
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<p>(<b>A</b>) Colony morphology of PH-1, Δ<span class="html-italic">FgAsp</span>, and CΔ<span class="html-italic">FgAsp</span>. (<b>B</b>) Growth rates of wild-type PH-1, Δ<span class="html-italic">FgAsp</span>, and CΔ<span class="html-italic">FgAsp</span> strains. (<b>C</b>) PH-1, Δ<span class="html-italic">FgAsp</span>, and CΔ<span class="html-italic">FgAsp</span> hyphal edge morphology. Scale bar = 20 μm. Means and standard errors were calculated using <span class="html-italic">t</span>-tests based on data from three independent biological replicates. Different letters indicate significant difference at the level of 0.05.</p>
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<p>(<b>A</b>) Conidiophores of PH-1, Δ<span class="html-italic">FgAsp</span>, and CΔ<span class="html-italic">FgAsp</span>. The red arrows indicate the attached conidia on the conidial peduncle of each strain. Scale bar = 25 μm. (<b>B</b>) The sporogenesis rates of PH-1, Δ<span class="html-italic">FgAsp</span>, and CΔ<span class="html-italic">FgAsp</span>. Different lowercase letters a and b represent significant differences. (<b>C</b>) Statistics of the number of septa in conidia of PH-1, Δ<span class="html-italic">FgAsp</span>, and CΔ<span class="html-italic">FgAsp</span>. Scale bar = 25 μm. (<b>D</b>) Conidia germination statistics of PH-1, Δ<span class="html-italic">FgAsp</span>, and CΔ<span class="html-italic">FgAsp</span>.</p>
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<p>Pathogenicity and lesion length of PH-1, Δ<span class="html-italic">FgAsp</span>, and CΔ<span class="html-italic">FgAsp</span>: (<b>A1</b>,<b>A2</b>) Wheat coleoptiles, (<b>B1</b>,<b>B2</b>) wheat leaves, (<b>C1</b>,<b>C2</b>) wheat ears, (<b>D1</b>,<b>D2</b>) corn silks. The images above show the pathogenicity and lesion pictures, and the violin plot of lesion length is displayed below.</p>
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<p>Sexual reproduction of PH-1, Δ<span class="html-italic">FgAsp</span>, and CΔ<span class="html-italic">FgAsp</span>: (<b>A</b>) Number of ascospores produced by sexual reproduction of PH-1, Δ<span class="html-italic">FgAsp</span>, and CΔ<span class="html-italic">FgAsp</span>. (<b>B</b>) Eruption of ascocarp primordia. Scale bar = 2000 μm. (<b>C</b>) Ascospores. Scale bar = 50 μm. (<b>D</b>) Number of ascospores per asci (individuals). Different lowercase letters a and b represent significant differences.</p>
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<p>(<b>A</b>) DON toxin content in TBI medium of PH-1, Δ<span class="html-italic">FgAsp</span>, and CΔ<span class="html-italic">FgAsp</span>. (<b>B</b>) DON toxin content in wheat kernels of PH-1, Δ<span class="html-italic">FgAsp</span>, and CΔ<span class="html-italic">FgAsp</span>. (<b>C</b>) Expression levels of TRI gene clusters in PH-1, Δ<span class="html-italic">FgAsp</span>, and CΔ<span class="html-italic">FgAsp</span> after 6 days of TBI culture. Means and standard errors were calculated using <span class="html-italic">t</span>-tests based on data from three independent biological replicates. Different letters indicate significant difference at the level of 0.05.</p>
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<p>(<b>A</b>) Colony morphology of PH-1, Δ<span class="html-italic">FgAsp</span>, and CΔ<span class="html-italic">FgAsp</span> on PSA medium containing NaCl, KCl, MgCl<sub>2</sub>, CaCl<sub>2</sub>, and H<sub>2</sub>O<sub>2</sub>. (<b>B</b>) Stress growth inhibition rate analysis. Means and standard errors were calculated using <span class="html-italic">t</span>-tests based on data from three independent biological replicates. An asterisk (*) indicates a <span class="html-italic">p</span> value of less than 0.05, that is, the difference is significant at the 5% significance level. Two asterisks (**) indicate a <span class="html-italic">p</span> value of less than 0.01, that is, significant at the 1% significance level. Three asterisks (***) indicate a <span class="html-italic">p</span> value of less than 0.001, which is extremely significant at the 0.1% significance level. ns indicates no difference.</p>
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<p>(<b>A</b>) Colony morphology of PH-1, Δ<span class="html-italic">FgAsp</span>, and CΔ<span class="html-italic">FgAsp</span> on PSA medium containing sucrose, arabinose, mannose, glucose, and galactose. (<b>B</b>) Analysis of different glycogen inhibition rates of wild-type PH-1, Δ<span class="html-italic">FgAsp</span>, and CΔ<span class="html-italic">FgAsp</span> strains. Data were tested by <span class="html-italic">t</span>-test, and error bars represent the standard deviation (SD). Different letters indicate a significant difference at the level of 0.05.</p>
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17 pages, 5180 KiB  
Article
Sulfur Amino Acid Restriction Mitigates High-Fat Diet-Induced Molecular Alterations in Cardiac Remodeling Primarily via FGF21-Independent Mechanisms
by Filipe Pinheiro, Hannah Lail, João Sérgio Neves, Rita Negrão and Desiree Wanders
Nutrients 2024, 16(24), 4347; https://doi.org/10.3390/nu16244347 - 17 Dec 2024
Viewed by 391
Abstract
Background/Objectives: Dietary sulfur amino acid restriction (SAAR) elicits various health benefits, some mediated by fibroblast growth factor 21 (FGF21). However, research on SAAR’s effects on the heart is limited and presents mixed findings. This study aimed to evaluate SAAR-induced molecular alterations associated with [...] Read more.
Background/Objectives: Dietary sulfur amino acid restriction (SAAR) elicits various health benefits, some mediated by fibroblast growth factor 21 (FGF21). However, research on SAAR’s effects on the heart is limited and presents mixed findings. This study aimed to evaluate SAAR-induced molecular alterations associated with cardiac remodeling and their dependence on FGF21. Methods: Male C57BL/6J wild-type and FGF21 knockout mice were randomized into four dietary regimens, including normal fat and high-fat diets (HFDs) with and without SAAR, over five weeks. Results: SAAR significantly reduced body weight and visceral adiposity while increasing serum FGF21 levels. In the heart, SAAR-induced molecular metabolic alterations are indicative of enhanced lipid utilization, glucose uptake, and mitochondrial biogenesis. SAAR also elicited opposing effects on the cardiac gene expression of FGF21 and adiponectin. Regarding cellular stress responses, SAAR mitigated the HFD-induced increase in the cardiac expression of genes involved in oxidative stress, inflammation, and apoptosis, while upregulating antioxidative genes. Structurally, SAAR did not induce alterations indicative of cardiac hypertrophy and it counteracted HFD-induced fibrotic gene expression. Overall, most alterations induced by SAAR were FGF21-independent, except for those related to lipid utilization and glucose uptake. Conclusions: Altogether, SAAR promotes cardiac alterations indicative of physiological rather than pathological remodeling, primarily through FGF21-independent mechanisms. Full article
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<p>SAAR reduced body weight and visceral adiposity independently of FGF21. Body weight (<span class="html-italic">n</span> = 10–14 animals per group) was measured prior to sacrifice. The weights of eWAT and rpWAT were measured post-sacrifice (<span class="html-italic">n</span> = 7–11 animals per group). Statistical analysis was performed using one-way ANOVA followed by Tukey–Kramer post-hoc multiple comparison tests. Significance levels to the NFD group are denoted by the * symbol: * <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, **** <span class="html-italic">p</span> &lt; 0.0001. Significance levels to the HFD group are denoted by the <sup>#</sup> symbol: <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001, and <sup>####</sup> <span class="html-italic">p</span> &lt; 0.0001. Abbreviations: eWAT, epididymal white adipose tissue; rpWAT, retroperitoneal white adipose tissue.</p>
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<p>SAAR modulated the expression levels of the cardioprotective hormones FGF21 and Adiponectin. Serum FGF21 levels were quantified using an ELISA kit (<span class="html-italic">n</span> = 4–6 animals per group). mRNA expression levels were quantified via RT-PCR (<span class="html-italic">n</span> = 7–11 animals per group). Statistical analysis was performed using one-way ANOVA followed by Tukey–Kramer post-hoc multiple comparison tests. Significance levels to the NFD group are denoted by the * symbol: * <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; 0.0001. Significance levels to the HFD group are denoted by the <sup>#</sup> symbol: <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 and <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Serum FGF21 levels are associated with Liver <span class="html-italic">Fgf21</span> mRNA expression but not with Cardiac <span class="html-italic">Fgf21</span> mRNA expression. Serum FGF21 levels were quantified using an ELISA kit. mRNA expression levels were quantified via RT-PCR. Relationship between serum FGF21 concentrations and liver Fgf21 (<span class="html-italic">n</span> = 20) and cardiac Fgf21 (<span class="html-italic">n</span> = 19) mRNA concentrations was determined with linear regression analysis. The errors of the linear regression lines are denoted in yellow.</p>
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<p>SAAR enhanced the expression of cardiac lipid utilization genes and <span class="html-italic">Slc2a1</span> in WT mice but not in <span class="html-italic">Fgf21<sup>−</sup><sup>/</sup><sup>−</sup></span> mice. mRNA expression levels were quantified via RT-PCR (<span class="html-italic">n</span> = 6–11 animals per group). Statistical analysis was performed using one-way ANOVA followed by Tukey–Kramer post-hoc multiple comparison tests. Significance levels to the NFD group are denoted by the * symbol: * <span class="html-italic">p</span> &lt; 0.05. Significance levels to the HFD group are denoted by the <sup>#</sup> symbol: <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01 and <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>SAAR modulated the expression of genes related to mitochondrial biogenesis across both genotypes in the heart. mRNA expression levels were quantified via RT-PCR (<span class="html-italic">n</span> = 7–11 animals per group). Protein quantification was conducted using Western blot (<span class="html-italic">n</span> = 6–11 animals per group). Statistical analysis was performed using one-way ANOVA followed by Tukey–Kramer post-hoc multiple comparison tests. Significance levels to the NFD group are denoted by the * symbol: * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01. Significance levels to the HFD group are denoted by the <sup>#</sup> symbol: <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01 and <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>SAAR abrogated the HFD-induced expression of genes associated with abnormal cellular stress responses across both genotypes in the heart. mRNA expression levels were quantified via RT-PCR (<span class="html-italic">n</span> = 6–11 animals per group). Statistical analysis was performed using one-way ANOVA followed by Tukey–Kramer post-hoc multiple comparison tests. Significance levels to the NFD group are denoted by the * symbol: * <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, **** <span class="html-italic">p</span> &lt; 0.0001. Significance levels to the HFD group are denoted by the <sup>#</sup> symbol: <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01, <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001, and <sup>####</sup> <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>SAAR modulated the expression of genes associated with cardiac hypertrophy and fibrosis pathways in both genotypes. mRNA expression levels were quantified via RT-PCR (<span class="html-italic">n</span> = 7–11 animals per group). Statistical analysis was performed using one-way ANOVA followed by Tukey–Kramer post-hoc multiple comparison tests. Significance levels to the NFD group are denoted by the * symbol: * <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, **** <span class="html-italic">p</span> &lt; 0.0001. Significance levels to the HFD group are denoted by the <sup>#</sup> symbol: <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01 and <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>SAAR-induced molecular alterations in the heart are more indicative of physiological than pathological cardiac remodeling. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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11 pages, 2273 KiB  
Article
KOnezumi-AID: Automation Software for Efficient Multiplex Gene Knockout Using Target-AID
by Taito Taki, Kento Morimoto, Seiya Mizuno and Akihiro Kuno
Int. J. Mol. Sci. 2024, 25(24), 13500; https://doi.org/10.3390/ijms252413500 - 17 Dec 2024
Viewed by 362
Abstract
With the groundbreaking advancements in genome editing technologies, particularly CRISPR-Cas9, creating knockout mutants has become highly efficient. However, the CRISPR-Cas9 system introduces DNA double-strand breaks, increasing the risk of chromosomal rearrangements and posing a major obstacle to simultaneous multiple gene knockout. Base-editing systems, [...] Read more.
With the groundbreaking advancements in genome editing technologies, particularly CRISPR-Cas9, creating knockout mutants has become highly efficient. However, the CRISPR-Cas9 system introduces DNA double-strand breaks, increasing the risk of chromosomal rearrangements and posing a major obstacle to simultaneous multiple gene knockout. Base-editing systems, such as Target-AID, are safe alternatives for precise base modifications without requiring DNA double-strand breaks, serving as promising solutions for existing challenges. Nevertheless, the absence of adequate tools to support Target-AID-based gene knockout highlights the need for a comprehensive system to design guide RNAs (gRNAs) for the simultaneous knockout of multiple genes. Here, we aimed to develop KOnezumi-AID, a command-line tool for gRNA design for Target-AID-mediated genome editing. KOnezumi-AID facilitates gene knockout by inducing the premature termination codons or promoting exon skipping, thereby generating experiment-ready gRNA designs for mouse and human genomes. Additionally, KOnezumi-AID exhibits batch processing capacity, enabling rapid and precise gRNA design for large-scale genome editing, including CRISPR screening. In summary, KOnezumi-AID is an efficient and user-friendly tool for gRNA design, streamlining genome editing workflows and advancing gene knockout research. Full article
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<p>Overview of KOnezumi-AID. (<b>A</b>) Preprocessing in KOnezumi-AID. A refFlat file and a reference sequence are processed into a format suitable for KOnezumi-AID search. (<b>B</b>) Main search process of KOnezumi-AID. Editable bases are indicated in blue. Bold and red stop marks indicate the premature termination codons (PTCs). Exons are marked in green. (<b>C</b>) Search process of KOnezumi-AID shown in a schema. Black box indicates the target window. Editable bases are indicated in blue. Regions where codons can be modified to introduce PTCs or target the GT–AG splice site consensus sequence are highlighted in bold. Exons are marked in green. (<b>D</b>) Filtering process in KOnezumi-AID. Red stop marks indicate the PTCs. Key filtering checkpoints are indicated in blue.</p>
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<p>Output of KOnezumi-AID. (<b>A</b>) Output of KOnezumi-AID for a multi-isoform gene. The output shows guide RNAs (gRNAs) inducing PTCs and those disrupting the acceptor or donor consensus nucleotides for genes with multiple isoforms. Multiple isoforms being searched simultaneously are indicated in red. Output columns are highlighted in bold. (<b>B</b>) Output of KOnezumi-AID for a single-isoform gene. The output shows gRNAs inducing PTCs and those disrupting the acceptor or donor consensus nucleotides for a gene with a single isoform. Columns that are specifically displayed when searching for single-isoform genes are highlighted in bold. (<b>C</b>) Scatter plot shows the relationship between the execution time (in seconds) and the total number of sequences containing “C” within the target window for each gene. The Pearson correlation coefficient is 0.87.</p>
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<p>Analysis of candidate gRNA-associated mouse genes and their distribution. (<b>A</b>) Number of genes with gRNA targetability. The total number of analysed genes (searchable genes), number of genes with at least one candidate gRNA (targetable genes), number of genes with candidate gRNAs inducing PTCs (targetable genes by PTC induction), and number of genes with candidate gRNAs disrupting splice sites (targetable genes by splice site disruption) are displayed. (<b>B</b>) Number of genes by number of candidate gRNAs. Distribution of genes based on the total number of candidate gRNAs, including those inducing PTC and those disrupting splice sites, is shown. For visualization, counts are capped at 10, even if the number of gRNAs per gene exceeds 10. (<b>C</b>) Number of genes by number of exons. Distribution of exons for genes targetable by gRNAs is shown. For visualization, counts are capped at 20, even for genes with more than 20 exons.</p>
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<p>Application of KOnezumi-AID to human gene data. (<b>A</b>) Number of genes with gRNA targetability. The total number of analysed genes (searchable genes), number of genes with at least one candidate gRNA (targetable genes), number of genes with candidate gRNAs inducing PTCs (targetable genes by PTC induction), and number of genes with candidate gRNAs disrupting splice sites (targetable genes by splice site disruption) are displayed. (<b>B</b>) Number of genes by number of candidate gRNAs. Distribution of genes based on the total number of candidate gRNAs, including those inducing PTCs and those disrupting splice sites, is shown. For visualization, counts are capped at 10, even if the number of gRNAs per gene exceeds 10. (<b>C</b>) Number of genes by number of exons. Distribution of exons for genes targetable by gRNAs is shown. For visualization, counts are capped at 20, even for genes with more than 20 exons.</p>
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<p>Batch processing. (<b>A</b>) Output of KOnezumi-AID for batch processing. The results of batch searches using an Excel file containing the gene abbreviations, <span class="html-italic">Trp53</span> and <span class="html-italic">Myc</span>, are shown. Two genes being searched sequentially are indicated in bold by arrows. (<b>B</b>) Scatter plot illustrates the relationship between the number of genes in batch processing and execution time (in seconds). Light blue dots represent the average execution time for each batch processing epoch, while black line shows the linear regression line. The coefficient of determination (R<sup>2</sup>) is 1.</p>
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19 pages, 1776 KiB  
Review
Decoding the Genes Orchestrating Egg and Sperm Fusion Reactions and Their Roles in Fertility
by Ranjha Khan, Muhammad Azhar and Muhammad Umair
Biomedicines 2024, 12(12), 2850; https://doi.org/10.3390/biomedicines12122850 - 15 Dec 2024
Viewed by 482
Abstract
Mammalian fertilization is a complex and highly regulated process that has garnered significant attention, particularly with advancements in assisted reproductive technologies such as in vitro fertilization (IVF). The fusion of egg and sperm involves a sequence of molecular and cellular events, including capacitation, [...] Read more.
Mammalian fertilization is a complex and highly regulated process that has garnered significant attention, particularly with advancements in assisted reproductive technologies such as in vitro fertilization (IVF). The fusion of egg and sperm involves a sequence of molecular and cellular events, including capacitation, the acrosome reaction, adhesion, and membrane fusion. Critical genetic factors, such as IZUMO1, JUNO (also known as FOLR4), CD9, and several others, have been identified as essential mediators in sperm–egg recognition and membrane fusion. Additionally, glycoproteins such as ZP3 within the zona pellucida are crucial for sperm binding and triggering the acrosome reaction. Recent gene-editing technologies, such as CRISPR/Cas9 and conditional knockout models, have facilitated the functional annotation of genes such as SPAM1 and ADAM family members, further elucidating their roles in capacitation and adhesion. Furthermore, the integration of CRISPR-Cas9 with omics technologies, including transcriptomics, proteomics, and lipidomics, has unlocked new avenues for identifying previously unknown genetic players and pathways involved in fertilization. For instance, transcriptomics can uncover gene expression profiles during gamete maturation, while proteomics identifies key protein interactions critical for processes such as capacitation and the acrosome reaction. Lipidomics adds another dimension by revealing how membrane composition influences gamete fusion. Together, these tools enable the discovery of novel genes, pathways, and molecular mechanisms involved in fertility, providing insights that were previously unattainable. These approaches not only deepen our molecular understanding of fertility mechanisms but also hold promise for refining diagnostic tools and therapeutic interventions for infertility. This review summarizes the current molecular insights into genes orchestrating fertilization and highlights cutting-edge methodologies that propel the field toward novel discoveries. By integrating these findings, this review aims to provide valuable knowledge for clinicians, researchers, and technologists in the field of reproductive biology and assisted reproductive technologies. Full article
(This article belongs to the Special Issue Molecular and Genetic Bases of Infertility)
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Figure 1
<p>Progesterone triggers the activation of the CatSper calcium channel within an alkaline environment, causing a rapid influx of Ca<sup>2+</sup> ions. This influx, combined with Ca<sup>2+</sup> release from internal storage sites, raises intracellular Ca<sup>2+</sup> levels. This elevated calcium concentration induces hyperactivated motility in sperm, enhancing its energy and mobility to facilitate successful fertilization.</p>
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<p>A representative outline of approaches used to discover genes that are essential for fertilization. This is the representative demonstration of genes that have been discovered through various techniques, and functional genomics analysis confirmed their role in egg–sperm fusion reactions. This figure also demonstrates the evolution of new approaches from 1950 to the present.</p>
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<p>Fertilization in mammals is a complex, multi-step process. It begins with sperm interacting with cumulus cells, followed by binding to the egg’s extracellular matrix (zona pellucida) and penetrating it. Once the sperm has reached the egg cell membrane, it binds and fuses with it, triggering polyspermy-blocking mechanisms to ensure successful fertilization. Crucial to this fusion process are three core molecules: Izumo1 on the sperm, Juno on the egg, and Cd9, which work in tandem to facilitate and regulate the fusion of sperm and egg cells.</p>
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23 pages, 7303 KiB  
Article
Functional and Biological Characterization of the LGR5Δ5 Splice Variant in HEK293T Cells
by Matthias Kappler, Laura Thielemann, Markus Glaß, Laura Caggegi, Antje Güttler, Jonas Pyko, Sarah Blauschmidt, Tony Gutschner, Helge Taubert, Sven Otto, Alexander W. Eckert, Frank Tavassol, Matthias Bache, Dirk Vordermark, Tom Kaune and Swetlana Rot
Int. J. Mol. Sci. 2024, 25(24), 13417; https://doi.org/10.3390/ijms252413417 - 14 Dec 2024
Viewed by 404
Abstract
The regulator of the canonical Wnt pathway, leucine-rich repeat-containing G protein-coupled receptor 5 (LGR5), is expressed in the stem cell compartment of several tissues and overexpressed in different human carcinomas. The isoform of the stem cell marker LGR5, named LGR5Δ5 and first described [...] Read more.
The regulator of the canonical Wnt pathway, leucine-rich repeat-containing G protein-coupled receptor 5 (LGR5), is expressed in the stem cell compartment of several tissues and overexpressed in different human carcinomas. The isoform of the stem cell marker LGR5, named LGR5Δ5 and first described by our group, is associated with prognosis and metastasis in oral squamous cell carcinoma (OSCC) and soft tissue sarcoma (STS). In a proof-of-principle analysis, the function of LGR5Δ5 was investigated in HEK293T cells, a model cell line of the Wnt pathway, compared to full-length LGR5 (FL) expression. The CRISPR/CAS knockout of LGR5 and LGR4 (thereby avoiding the side effects of LGR4) resulted in a loss of Wnt activity that cannot be restored by LGR5Δ5 but by LGR5FL rescue. The ability to migrate was not affected by LGR5Δ5, but was reduced by LGR5FL overexpression. The CRISPR/CAS of LGR4 and 5 induced radiosensitization, which was enhanced by the overexpression of LGR5FL or LGR5Δ5. RNA sequencing analysis revealed a significant increase in the ligand R-spondin 1 (RSPO1) level by LGR5Δ5. Furthermore, LGR5Δ5 appears to be involved in the regulation of genes related to the cytoskeleton, extracellular matrix stiffness, and angiogenesis, while LGR5FL is associated with the regulation of collagens and histone proteins. Full article
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<p>(<b>a</b>) Structures of full-length LGR5 and LGR5Δ5 splice variants. The triangles mark the spliced-out site in the mRNA. The corresponding potential proteins are labeled with the NCBI conserved domain search tool. The brackets indicate the spliced-out site in the protein [<a href="#B20-ijms-25-13417" class="html-bibr">20</a>]. The substrate binding site was predicted via comparison via NCBI conserved domains. <a href="https://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi" target="_blank">https://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi</a> (accessed on 8 February 2016). (<b>b</b>) Schematic representation of the possible interaction between RSPO1 and LGR5FL and LGR5Δ5. LGR5FL forms homodimers and is also capable of forming heterodimers with the splice variant LGR5Δ5. RSPO interacts with LGR5FL at three contact sites (1, 2, and 3 in blue, brown, and yellow, respectively). In the LGR5 splice variant Δ5, contact sites 1 and 2 are spliced out. Interaction with RSPO at contact site 3 is possible via heterodimerization with LGR5FL [<a href="#B20-ijms-25-13417" class="html-bibr">20</a>].</p>
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<p>(<b>a</b>) Time- and stimulant-dependent internalization of overexpressed LGR5FL and LGR5Δ5 in HEK293T cells. The samples were stained with a FITC-coupled anti-Myc-Tag antibody (green) and counterstained (nuclei) with DAPI solution (blue). (<b>b</b>) Inhibition of clathrin- and caveolin-mediated endocytosis in LGR5FL-overexpressing and LGR5Δ5-overexpressing HEK293T cells. The cells were treated with inhibitors of clathrin-mediated endocytosis (MDC and PitStop2) and with an inhibitor of caveolin-mediated endocytosis (filipin III). (The scale bar represent 10µm). [<a href="#B20-ijms-25-13417" class="html-bibr">20</a>].</p>
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<p>TOPFlash/FOPFlash reporter assay to measure Wnt pathway activity in modified HEK293T cells (<b>a</b>) overexpressing an empty vector (blue line), LGR5FL (black line), or LGR5Δ5 (red line). (<b>b</b>) siRNA-mediated knockdown of LGR4 and overexpression of an empty vector (light blue line), LGR5FL (black line), or LGR5Δ5 (red line). The control (dark blue line) corresponds to the empty vector control of (<b>a</b>).</p>
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<p>Sanger sequencing of one CRISPR/Cas9 monoclonal cell line of HEK293T cells compared with the wild-type sequence. LGR4 exon 1 (−4 nucleotides) resulted in a stop codon in 629 and a 141 base pair mRNA encoding a truncated protein of 46 As), and LGR5 (−1 nucleotide) resulted in a stop codon in 661 and a 378 base pair mRNA encoding a truncated protein of 125 As. (Please also see the sequence of the rescue clones in <a href="#app1-ijms-25-13417" class="html-app">Figure S1</a>).</p>
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<p>(<b>a</b>) TOP/FOP flash assay to measure Wnt pathway activity in modified HEK293T cells (empty vector (blue line), LGR5FL (black line), or LGR5Δ5 (red line) overexpression). (<b>b</b>) Screening of selected LGR4/5 CRISPR double-knockout clones via the TOPFlash/FOPFlash reporter assay after LGR5FL or LGRΔ5 rescue. Analysis of the chemiluminescence signals (luciferase activity) from transiently (pIRESpuro) LGR5FL- or LGR5Δ5-transfected cells with (+) and without (−) stimulation with 100 ng/mL Wnt3a and 100 ng/mL RSPO1. Control = knockout clones without transfection. Single-screen transfection was performed via ViaFect™. Clonal cell lines 1 and 3 were validated by sequencing analysis, whereas clone 2 was excluded.</p>
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<p>Western blot analysis to detect full-length LGR5 (FL) and LGR5Δ5 (Δ5) expression via the lentiviral transduction of HEK LGR4/5 CRISPR/Cas9 double-knockout cells in comparison with the empty vector control (C). Full-length LGR5 (FL) and LGR5Δ5 (Δ5) were each tagged with a c-Myc tag (&lt;1 kDa) or a YFP tag (27 kDa) for selection, visualization, and enrichment. The detection of LGR5 and LGR5Δ5 was carried out via a polyclonal anti-LGR5 antibody. ß actin was used as a loading control.</p>
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<p>Migration of a HEK-LGR4/5 double-knockout clone with stable LGR5FL or LGR5Δ5 expression compared with the empty vector control cell line or unmodified HEK293T cell line via a scratch assay.</p>
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<p>Radiosensitivity of the unmodified HEK293T cell line and the HEK-LGR4/5 double-knockout cell lines with stable LGR5FL or LGR5Δ5 expression or empty vector expression.</p>
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<p>(<b>a</b>) Venn diagram of the HEK293T-LGR4/5 knockout cell lines (empty vector PLVX, LGR5FL, or LGR5Δ5 clones). (<b>b</b>) Volcano plot showing genes differentially expressed between the empty vector PLVX and LGR5Δ5 of the HEK293T-LGR4/5 knockout cell lines. (<b>c</b>) Heatmap of the expression of 15 genes related to LGR5Δ5 and LGR5FL overexpression (HEK293T-LGR4/5 knockout cell lines).</p>
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<p>Western blot analysis of LGR5-regulated proteins in full-length LGR5 (FL)- and LGR5Δ5 (Δ5)-overexpressing HEK293T cells with single (LGR5) or double (LGR4/5) CRISPR Cas9 knockout with or without stimulation (Wnt3a and RSPO1) compared with control cells (PLVX) transfected with an empty vector. LGR5 and LGR5Δ5 were tagged with a YFP tag (27 kDa) for selection. ß actin was included as a loading control. Protein was isolated from adherent cells.</p>
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<p>Postulated pathways associated with LGR5FL or LGR5Δ5 overexpression. LGR5FL activated the Wnt pathway, but LGR5Δ5 did not. LGR5FL overexpression is related to lupus erythematosus disease and fibrillar collagen regulation, whereas LGR5Δ5 overexpression is related to angiogenesis and fibrillar collagen regulation pathways. Our data also suggest that LGR5FL influences the level of genes associated with protein modification, transcription efficiency, and DNA accessibility adaptation in terms of epigenetic modifications. LGR5Δ5 seems to affect RSPO1 (the ligand of LGR5), an autoregulatory feedback loop activity of RSPO1. (Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>).</p>
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