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14 pages, 3020 KiB  
Article
PSPC1 Binds to HCV IRES and Prevents Ribosomal Protein S5 Binding, Inhibiting Viral RNA Translation
by Sachin Kumar Tripathi, Ashish Aneja, Teji Borgaonkar and Saumitra Das
Viruses 2024, 16(5), 738; https://doi.org/10.3390/v16050738 - 7 May 2024
Viewed by 1591
Abstract
Hepatitis C virus (HCV) infects the human liver, and its chronic infection is one of the major causes of Hepatocellular carcinoma. Translation of HCV RNA is mediated by an Internal Ribosome Entry Site (IRES) element located in the 5’UTR of viral RNA. Several [...] Read more.
Hepatitis C virus (HCV) infects the human liver, and its chronic infection is one of the major causes of Hepatocellular carcinoma. Translation of HCV RNA is mediated by an Internal Ribosome Entry Site (IRES) element located in the 5’UTR of viral RNA. Several RNA Binding proteins of the host interact with the HCV IRES and modulate its function. Here, we demonstrate that PSPC1 (Paraspeckle Component 1), an essential paraspeckle component, upon HCV infection is relocalized and interacts with HCV IRES to prevent viral RNA translation. Competition UV-crosslinking experiments showed that PSPC1 interacts explicitly with the SLIV region of the HCV IRES, which is known to play a vital role in ribosomal loading to the HCV IRES via interaction with Ribosomal protein S5 (RPS5). Partial silencing of PSPC1 increased viral RNA translation and, consequently, HCV replication, suggesting a negative regulation by PSPC1. Interestingly, the silencing of PSPC1 protein leads to an increased interaction of RPS5 at the SLIV region, leading to an overall increase in the viral RNA in polysomes. Overall, our results showed how the host counters viral infection by relocalizing nuclear protein to the cytoplasm as a survival strategy. Full article
(This article belongs to the Special Issue Functional and Structural Features of Viral RNA Elements)
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Figure 1

Figure 1
<p>Localization of PSPC1 and its effect on HCV-JFH1 RNA transfection. (<b>A</b>) Huh7.5 cells were transfected with HCV-JFH1 RNA followed by immunofluorescence. Alexa Fluor conjugated secondary antibodies against PSPC1 (Red) and NS5B (Green) were used for detection. The nucleus was counterstained with DAPI. (<b>B</b>) A representative image of HCV JFH1 RNA (adapted from Matsui et al. J Virol. 2012) [<a href="#B31-viruses-16-00738" class="html-bibr">31</a>]. (<b>C</b>) Huh7.5 cells were transfected with siNsp and siPSPC1, and after 24 h transfection, HCV-JFH1 RNA was transfected; at 48 h post-transfection, cells were harvested for RNA isolation and Western blotting. A positive strand of HCV RNA was detected via qRT-PCR upon siPSPC1. (<b>D</b>) A negative strand of HCV RNA was detected upon siPSPC1 treatment using qRT-PCR. (<b>E</b>) Western blot analysis showing the effect of the silencing of PSPC1 (** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001).</p>
Full article ">Figure 1 Cont.
<p>Localization of PSPC1 and its effect on HCV-JFH1 RNA transfection. (<b>A</b>) Huh7.5 cells were transfected with HCV-JFH1 RNA followed by immunofluorescence. Alexa Fluor conjugated secondary antibodies against PSPC1 (Red) and NS5B (Green) were used for detection. The nucleus was counterstained with DAPI. (<b>B</b>) A representative image of HCV JFH1 RNA (adapted from Matsui et al. J Virol. 2012) [<a href="#B31-viruses-16-00738" class="html-bibr">31</a>]. (<b>C</b>) Huh7.5 cells were transfected with siNsp and siPSPC1, and after 24 h transfection, HCV-JFH1 RNA was transfected; at 48 h post-transfection, cells were harvested for RNA isolation and Western blotting. A positive strand of HCV RNA was detected via qRT-PCR upon siPSPC1. (<b>D</b>) A negative strand of HCV RNA was detected upon siPSPC1 treatment using qRT-PCR. (<b>E</b>) Western blot analysis showing the effect of the silencing of PSPC1 (** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001).</p>
Full article ">Figure 2
<p>Binding of PSPC1 with HCV RNA. (<b>A</b>) UV cross-linking assay using recombinant PSPC1 and radio-labeled 5’ UTR RNA. Lane 1 corresponds to the interaction between RNA and recombinant PSPC1 protein. For competition, 50- and 100-fold molar excesses of unlabeled 5’ UTR RNA (lanes 2 and 3) or HCV 3’ UTR as non-specific RNA (lanes 4 and 5) were also included in the reaction. (<b>B</b>) Densitometry of the competition UV-crosslinking. (<b>C</b>) IP-RT assay was performed by incubating protein G beads with IgG, PSPC1, and HuR antibodies, followed by incubation with Huh7.5 cell lysate. Further, the complex was processed for RNA isolation and Western blotting. HCV RNA levels were detected using HCV-specific primer in semi-quantitative PCR, and Western blotting was performed to check the pulldown by anti-PSPC1 and anti-HuR antibodies. (P = NS, not significant; * <span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 3
<p>Binding of PSPC1 with different stem loops of HCV 5’ UTR and competition with RPS5. (<b>A</b>) A schematic representation of the HCV IRES showing interaction with RPS5 and ribosome loading. (<b>B</b>) UV-crosslinking assay with α-<sup>32</sup>P-labeled full-length 5’UTR of HCV RNA alone or in the presence of the indicated molar excess (50× and 100×) of unlabeled stem–loop RNAs of HCV 5’ UTR. (<b>C</b>) Densitometry of UV crosslinking experiment from (B) represented in graphical format. (<b>D</b>) Competition UV cross-linking of HCV IRES and PSPC1 in the presence of rRPS5 (lane 1–4). Competition UV cross-linking of HCV IRES and RPS5 in the presence of rPSPC1 (lane 5–8). (<b>E</b>) Western blot showing PSPC1 and RPS5 protein after HCV-JFH1 RNA transfection in Huh7.5 cells, followed by immunoprecipitation using anti-PSPC1 antibody, anti-RPS5 antibody, or IgG isotype antibody (as a negative control) in the presence of siPSPC1 or siNsp. (<b>F</b>) qRT-PCR data showing fold change in viral RNA upon immune-precipitation with anti-RPS5 antibody. (<b>G</b>) Fold change in viral RNA using qRT-PCR upon immune precipitation with anti-PSPC1 antibody. (* <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> &lt; 0.01).</p>
Full article ">Figure 3 Cont.
<p>Binding of PSPC1 with different stem loops of HCV 5’ UTR and competition with RPS5. (<b>A</b>) A schematic representation of the HCV IRES showing interaction with RPS5 and ribosome loading. (<b>B</b>) UV-crosslinking assay with α-<sup>32</sup>P-labeled full-length 5’UTR of HCV RNA alone or in the presence of the indicated molar excess (50× and 100×) of unlabeled stem–loop RNAs of HCV 5’ UTR. (<b>C</b>) Densitometry of UV crosslinking experiment from (B) represented in graphical format. (<b>D</b>) Competition UV cross-linking of HCV IRES and PSPC1 in the presence of rRPS5 (lane 1–4). Competition UV cross-linking of HCV IRES and RPS5 in the presence of rPSPC1 (lane 5–8). (<b>E</b>) Western blot showing PSPC1 and RPS5 protein after HCV-JFH1 RNA transfection in Huh7.5 cells, followed by immunoprecipitation using anti-PSPC1 antibody, anti-RPS5 antibody, or IgG isotype antibody (as a negative control) in the presence of siPSPC1 or siNsp. (<b>F</b>) qRT-PCR data showing fold change in viral RNA upon immune-precipitation with anti-RPS5 antibody. (<b>G</b>) Fold change in viral RNA using qRT-PCR upon immune precipitation with anti-PSPC1 antibody. (* <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> &lt; 0.01).</p>
Full article ">Figure 4
<p>Effect of partial silencing of PSPC1 in ribosome loading on HCV RNA. (<b>A</b>) Polysome profiling of JFH1 RNA transfected cells upon of siNsp and siPSPC1 transfections conditions using sucrose density centrifugation. (<b>B</b>,<b>C</b>) Fold change in the viral RNA in monosomes and polysomes upon the silencing of PSPC1. (P = NS, not significant; ** <span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 5
<p>PSPC1 level upon HCV-JFH1 RNA transfection. Huh7.5 cells were transfected with HCV-JFH1 RNA, followed by cells harvested at different time points and processed for Western blotting. PSPC1 protein levels were detected at 24 h, 48 h, and 72 h post-transfection.</p>
Full article ">Figure 6
<p>Model illustrating PSPC1, a paraspeckle protein, in the life cycle of HCV. Upon entry into the cell through receptor-mediated endocytosis, HCV undergoes uncoating, releasing its positive-strand RNA genome into the cytoplasm for translation. Translational initiation of HCV RNA occurs via its internal ribosome entry site (IRES). RPS5 is essential for locating the HCV RNA on the 40S ribosomal subunit at the start of translation. Upon HCV infection, PSPC1 relocates to cytoplasm and interacts with the 5’ UTR SLIV region of HCV IRES. As soon as it binds to the HCV IRES, it replaces the protein RPS5, which is necessary for HCV translation, which leads to a decrease in HCV RNA. It appears that PSPC1 lowers the levels of HCV RNA as a host response, and as a viral tactic, HCV lowers the level of PSPC1 protein.</p>
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14 pages, 4325 KiB  
Article
Dynamic Localization of Paraspeckle Components under Osmotic Stress
by Aysegul Yucel-Polat, Danae Campos-Melo, Asieh Alikhah and Michael J. Strong
Non-Coding RNA 2024, 10(2), 23; https://doi.org/10.3390/ncrna10020023 - 12 Apr 2024
Cited by 1 | Viewed by 1903
Abstract
Paraspeckles are nuclear condensates formed by NEAT1_2 lncRNA and different RNA-binding proteins. In general, these membraneless organelles function in the regulation of gene expression and translation and in miRNA processing, and in doing this, they regulate cellular homeostasis and mediate pro-survival in the [...] Read more.
Paraspeckles are nuclear condensates formed by NEAT1_2 lncRNA and different RNA-binding proteins. In general, these membraneless organelles function in the regulation of gene expression and translation and in miRNA processing, and in doing this, they regulate cellular homeostasis and mediate pro-survival in the cell. Despite evidence showing the importance of paraspeckles in the stress response, the dynamics of paraspeckles and their components under conditions of osmotic stress remain unknown. We exposed HEK293T cells to sorbitol and examined NEAT1_2 expression using real-time PCR. Localization and quantification of the main paraspeckle components, NEAT1_2, PSPC1, NONO, and SFPQ, in different cellular compartments was performed using smFISH and immunofluorescence. Our findings showed a significant decrease in total NEAT1_2 expression in cells after osmotic stress. Sorbitol shifted the subcellular localization of NEAT1_2, PSPC1, NONO, and SFPQ from the nucleus to the cytoplasm and decreased the number and size of NEAT1_2 foci in the nucleus. PSPC1 formed immunoreactive cytoplasmic fibrils under conditions of osmotic stress, which slowly disassembled under recovery. Our study deepens the paraspeckle dynamics in response to stress, suggesting a novel role for NEAT1_2 in the cytoplasm in osmotic stress and physiological conditions. Full article
(This article belongs to the Section Long Non-Coding RNA)
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Figure 1

Figure 1
<p>NEAT1_2 expression decreases under the conditions of osmotic stress in HEK293T cells. (<b>A</b>) qPCR shows that total NEAT1_2 expression was significantly reduced under conditions of osmotic stress (sorbitol, 4 h) and returned to control levels after 4 h of recovery (Rec, 4 h) (ΔCt values were used for statistical analyses, one-way ANOVA, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, <span class="html-italic">n</span> = 5, error bars indicate SEM). (<b>B</b>) Single-molecule FISH (smFISH) using Stellaris RNA probes against the NEAT1_2 middle segment shows that the number of NEAT1_2 foci in the cells decreased under conditions of osmotic stress (<span class="html-italic">t</span>-test, ** <span class="html-italic">p</span> &lt; 0.01).</p>
Full article ">Figure 2
<p>NEAT1_2 localizes in the cytoplasm of HEK293T cells forming typical shell–core structures. (<b>A</b>) Schematic representations of the positions of the smFISH probes used to identify distinct segments of NEAT1. (<b>B</b>) NEAT1_2 foci are observed in the cytoplasm at baseline and under conditions of osmotic stress (arrows). (<b>C</b>) The shell–core structure of NEAT1_2 (5′ segment in the shell and middle segment in the core) was detected in both cytoplasmic and nuclear NEAT1_2 foci in the control and sorbitol samples. Insets show the patchy pattern of the 5′ segment of NEAT1_2 foci. (asterisk used to demonstrate the granules in the insets) (<b>D</b>) 3D reconstruction shows NEAT1_2 foci of varying sizes and conformations in both the nuclear and cytosolic compartments. This includes clusters (arrows in 1 and 3) and single granules (arrowhead in 4) with shell–core structures in the nucleus (1) and cytoplasm (3 and 4) in the sorbitol samples. Small granules that, which lack the shell–core structure and showed the 5′ and middle segments of NEAT1_2 side by side, were also observed in the nucleus and cytosol under conditions of osmotic stress (asterisk in 4). Some NEAT1_2 clusters were observed partially residing within the nucleus and extending into the cytoplasm (arrow in 2).</p>
Full article ">Figure 3
<p>The number and size of NEAT1_2 foci change in HEK293T cells under osmotic stress. (<b>A</b>) Quantification of smFISH experiments showed that the number of nuclear NEAT1_2 foci decreased under conditions of osmotic stress, while the cytoplasmic foci increased (100 cells per n, n = 3, one-way ANOVA, ** <span class="html-italic">p</span> &lt; 0.01). (<b>B</b>) Violin plots show the distribution of NEAT1_2 foci size under different conditions. A decrease in NEAT1_2 foci size in the nucleus was observed under osmotic stress compared to the control and 4 h recovery (C: control; S: 4 h sorbitol; Rec: recovery-4 h; 100 cells per n, n = 3, One-way ANOVA, * <span class="html-italic">p</span> &lt; 0.05, error bars indicate SEM). (<b>C</b>) Under conditions of osmotic stress, cytoplasmic NEAT1_2 foci were significantly larger than nuclear NEAT1_2 foci (100 cells per n, n = 3, <span class="html-italic">t</span>-test, ** <span class="html-italic">p</span> &lt; 0.01, error bars indicate SEM).</p>
Full article ">Figure 4
<p>Paraspeckle proteins colocalize in the cytoplasm of HEK293T cells after osmotic stress. (<b>A</b>) Under conditions of osmotic stress, PSPC1, NONO, and SFPQ redistributed from the nucleus to the cytoplasm where they colocalized. Pictures show the merging of the PSP staining. (<b>B</b>) After osmotic stress, PSPC1 immunoreactive fibrils were formed in the cytoplasm (arrows). After 8 h of recovery, cytoplasmic PSPC1(+) fibrils were observed partially assembled (arrowhead), and SFPQ and NONO returned to the nucleus. Nuclei were stained using Hoechst (blue).</p>
Full article ">Figure 5
<p>Colocalization of NEAT1_2 with PSPs in the nucleus and cytoplasm of HEK293T cells. (<b>A</b>) smFISH/IF experiments showed that PSPC1, NONO, and NEAT1_2 form paraspeckles in the nucleus as expected in the baseline condition. After 30 min of incubation with sorbitol, PSPC1 and NONO redistributed to the cytosol, and paraspeckles began to disappear. After 4 h of sorbitol treatment, paraspeckles were barely visible in the nucleus. (<b>B</b>) NEAT1_2 localizes in small granules in the cytosol with (arrowheads) or without PSPC1, NONO, and SFPQ (arrows) under osmotic stress.</p>
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<p>Paraspeckle components colocalize with stress granules in the cytoplasm under conditions of osmotic stress. (<b>A</b>) Colocalization images showed that cytoplasmic NEAT1_2 rarely colocalizes in G3BP1(+) SGs (I and II, asterisk). No extensive colocalization was observed (III and IV, arrowhead). (<b>B</b>) PSPC1, NONO, and SFPQ were present together in SGs after osmotic stress but only in a small subpopulation of the cells. Line profiles of the fluorescence intensities on the right show the colocalization of PSPs with TIA-1 and G3BP1 in areas in the squares.</p>
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13 pages, 1585 KiB  
Review
Established and Evolving Roles of the Multifunctional Non-POU Domain-Containing Octamer-Binding Protein (NonO) and Splicing Factor Proline- and Glutamine-Rich (SFPQ)
by Danyang Yu, Ching-Jung Huang and Haley O. Tucker
J. Dev. Biol. 2024, 12(1), 3; https://doi.org/10.3390/jdb12010003 - 5 Jan 2024
Cited by 6 | Viewed by 3078
Abstract
It has been more than three decades since the discovery of multifunctional factors, the Non-POU-Domain-Containing Octamer-Binding Protein, NonO, and the Splicing Factor Proline- and Glutamine-Rich, SFPQ. Some of their functions, including their participation in transcriptional and posttranscriptional regulation as well as their contribution [...] Read more.
It has been more than three decades since the discovery of multifunctional factors, the Non-POU-Domain-Containing Octamer-Binding Protein, NonO, and the Splicing Factor Proline- and Glutamine-Rich, SFPQ. Some of their functions, including their participation in transcriptional and posttranscriptional regulation as well as their contribution to paraspeckle subnuclear body organization, have been well documented. In this review, we focus on several other established roles of NonO and SFPQ, including their participation in the cell cycle, nonhomologous end-joining (NHEJ), homologous recombination (HR), telomere stability, childhood birth defects and cancer. In each of these contexts, the absence or malfunction of either or both NonO and SFPQ leads to either genome instability, tumor development or mental impairment. Full article
(This article belongs to the Special Issue The 10th Anniversary of JDB: Feature Papers)
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Figure 1
<p>DBHS family nomenclature. NonO has also been termed the 54 kDa Nuclear RNA-Binding Protein (p54nrb) and the 55 kDa Nuclear Matrix Protein (nmt55). SFPQ was originally named the PTB-associated splicing factor (PSF). NonO and SFPQ are two members of the DBHS family. The DBHS conserved regions contain two RNA recognition motifs (RRMs, in red), a NONA/ParaSpeckle (NOPS) domain (in purple) and a coiled coil region (in blue). SFPQ also contains an N-terminal Arginine Glycine (RGG) region (in pink) and an uncharacterized DNA-binding domain (DBD, in green) at the N-terminus of its DBHS region. NonO has a highly charged helix–turn–helix (HTH in blue) C-terminal to its DBHS region, which has been suggested to have DNA-binding activity [<a href="#B19-jdb-12-00003" class="html-bibr">19</a>,<a href="#B20-jdb-12-00003" class="html-bibr">20</a>,<a href="#B21-jdb-12-00003" class="html-bibr">21</a>,<a href="#B22-jdb-12-00003" class="html-bibr">22</a>,<a href="#B24-jdb-12-00003" class="html-bibr">24</a>].</p>
Full article ">Figure 2
<p>Alignment of DBHS family proteins. (<b>A</b>) Structural elements of DBHS family proteins: NonO, SFPQ, PSPC1, NonA, hrp65 and NonO-1a. Their C-termini contain the conserved DBHS region (shown in green) consisting of (from N-terminus to C-terminus) RNA-binding domains (RRM1, 2), NONA/ParaSpeckle domains (NOPSs, not pictured) and coiled coil domains. Also pictured are positively/negatively charged residue regions (+/−, brown), HTH domains (blue) and NLS regions (yellow). (<b>B</b>). NonO, SFPQ and TFE3 chimeric proteins. Structural representations of the wild-type NonO, SFPQ and TFE3 (transcription factor binding to IGHM enhancer 3) chimeric proteins. The TFE3 protein contains acidic activation (AAD) and DNA-binding domains (bHLH; Z) and has an overall length of 575 amino acids. Scales in (<b>A</b>,<b>B</b>) are indicated with scale bars representing 100 amino acids (aa) at the lower right.</p>
Full article ">Figure 3
<p>Various mutations across the human <span class="html-italic">NONO</span> locus are associated with birth defects. The top line shows, to scale, the coding (yellow) and noncoding (blue) exons of <span class="html-italic">NONO</span> located at Xq13.1. The numerals a–p denote the positions of pathologic point and/or deletion mutations within coding regions; q denotes the deletion of exons 1–3, which includes part of the 5′ noncoding region. Details of the various mutations and their clinical ramifications are provided in references [<a href="#B52-jdb-12-00003" class="html-bibr">52</a>,<a href="#B53-jdb-12-00003" class="html-bibr">53</a>,<a href="#B92-jdb-12-00003" class="html-bibr">92</a>,<a href="#B93-jdb-12-00003" class="html-bibr">93</a>,<a href="#B94-jdb-12-00003" class="html-bibr">94</a>,<a href="#B95-jdb-12-00003" class="html-bibr">95</a>].</p>
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18 pages, 6181 KiB  
Article
PSPC1 Inhibition Synergizes with Poly(ADP-ribose) Polymerase Inhibitors in a Preclinical Model of BRCA-Mutated Breast/Ovarian Cancer
by Mithun Ghosh, Min Sil Kang, Nar Bahadur Katuwal, Sa Deok Hong, Yeong Gyu Jeong, Seong Min Park, Seul-Gi Kim and Yong Wha Moon
Int. J. Mol. Sci. 2023, 24(23), 17086; https://doi.org/10.3390/ijms242317086 - 3 Dec 2023
Cited by 2 | Viewed by 2533
Abstract
Poly (ADP-ribose) polymerase (PARP) inhibitors are effective against BRCA1/2-mutated cancers through synthetic lethality. Unfortunately, most cases ultimately develop acquired resistance. Therefore, enhancing PARP inhibitor sensitivity and preventing resistance in those cells are an unmet clinical need. Here, we investigated the ability of [...] Read more.
Poly (ADP-ribose) polymerase (PARP) inhibitors are effective against BRCA1/2-mutated cancers through synthetic lethality. Unfortunately, most cases ultimately develop acquired resistance. Therefore, enhancing PARP inhibitor sensitivity and preventing resistance in those cells are an unmet clinical need. Here, we investigated the ability of paraspeckle component 1 (PSPC1), as an additional synthetic lethal partner with BRCA1/2, to enhance olaparib sensitivity in preclinical models of BRCA1/2-mutated breast and ovarian cancers. In vitro, the combined olaparib and PSPC1 small interfering RNA (siRNA) exhibited synergistic anti-proliferative activity in BRCA1/2-mutated breast and ovarian cancer cells. The combination therapy also demonstrated synergistic tumor inhibition in a xenograft mouse model. Mechanistically, olaparib monotherapy increased the expressions of p-ATM and DNA-PKcs, suggesting the activation of a DNA repair pathway, whereas combining PSPC1 siRNA with olaparib decreased the expressions of p-ATM and DNA-PKcs again. As such, the combination increased the formation of γH2AX foci, indicating stronger DNA double-strand breaks. Subsequently, these DNA-damaged cells escaped G2/M checkpoint activation, as indicated by the suppression of p-cdc25C (Ser216) and p-cdc2 (Tyr15) after combination treatment. Finally, these cells entered mitosis, which induced increased apoptosis. Thus, this proves that PSPC1 inhibition enhances olaparib sensitivity by targeting DNA damage response in our preclinical model. The combination of olaparib and PSPC1 inhibition merits further clinical investigation to enhance PARP inhibitor efficacy. Full article
(This article belongs to the Special Issue Molecular Mechanisms of Breast Cancer: Toward Advanced Therapy)
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<p>PSPC1 inhibition synergizes with olaparib in <span class="html-italic">BRCA1/2</span>-mutated PSPC1-expressing cells. (<b>A</b>) Correlation between PSPC1 expression and olaparib sensitivity, which was defined as IC<sub>50</sub> ≤ 3.2 µM, in BRCA1/2-mutated ovarian cancer cell lines using GDSC data. <span class="html-italic">p</span>-values were analyzed by Student’s <span class="html-italic">t</span>-test. (<b>B</b>,<b>C</b>) MTT assay showed that combined PSPC1 siRNA and olaparib enhanced the antiproliferative effects in (<b>B</b>) BT−474 and (<b>C</b>) SNU−251 cells. Cells were treated with 5 nM of PSPC1 siRNA and indicated concentrations of olaparib and incubated for 72 h. (<b>D</b>,<b>E</b>) Apoptosis assay carried out by flow cytometry after staining with annexin V-APC/PI, representative scatter plots of PI (<span class="html-italic">y</span>-axis) and annexin V (<span class="html-italic">x</span>-axis). The number of total apoptotic cells were increased after the treatment with combined PSPC1 siRNA (5 nM) and olaparib (IC<sub>50</sub> concentration in BT−474 and half IC<sub>50</sub> concentration in SNU−251) for 72 h in (<b>D</b>) BT−474 and (<b>E</b>) SNU−251 cells. The data shown here were representative of three independent experiments. The bar graphs depicted the average of total apoptotic cells of three independent experiments. <span class="html-italic">p</span>-values were calculated by one-way ANOVA analysis, indicating ** <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. Data are presented as mean ± standard deviation from three independent experiments. (<b>F</b>,<b>G</b>) The expressions of apoptosis markers, caspase−3 and cleaved caspase−3 were analyzed with Western blot in (<b>F</b>) BT−474 and (<b>G</b>) SNU−251 cells. Cells were treated for 72 h with PSPC1 siRNA (5 nM), olaparib (IC<sub>50</sub> concentration in BT−474 and half IC<sub>50</sub> concentration in SNU−251) and their combination. GAPDH was used as a loading control.</p>
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<p>PSPC1 inhibition enhances DNA DSBs by inhibiting olaparib-induced DDR. (<b>A</b>,<b>B</b>) Western blot was performed to analyze the expressions of DDR-related proteins in (<b>A</b>) BT−474 and (<b>B</b>) SNU−251 cells. Cells were treated with 5 nM of PSPC1 siRNA, olaparib (IC<sub>50</sub> concentration in BT−474 and half IC<sub>50</sub> concentration in SNU−251) and their combination for 72 h. GAPDH was used as a loading control. (<b>C</b>,<b>D</b>) Immunofluorescence was carried out to capture the ɣH2AX foci formation in (<b>C</b>) BT−474 and (<b>D</b>) SNU−251 cells as a DNA DSBs marker. The cells were incubated for 48 h after treatment with PSPC1 siRNA (5 nM), olaparib (IC<sub>50</sub> concentration in BT−474 and half IC<sub>50</sub> concentration in SNU−251), and their combination. The images were taken at 100x magnification. The images shown here were representative of three independent experiments. The bar graphs depicted the average foci number per cell of three independent experiments. The foci were counted in 10 cells for each group. <span class="html-italic">P</span>-values were calculated by one-way ANOVA analysis, indicating **** <span class="html-italic">p</span> &lt; 0.0001. Data are presented as mean ± standard deviation from 3 independent experiments.</p>
Full article ">Figure 3
<p>Mitotic catastrophe caused by combination treatment could explain the synergistic mechanisms. (<b>A</b>,<b>B</b>) BT−474 and SNU−251 cells were treated with 5 nM of PSPC1 siRNA, olaparib (IC<sub>50</sub> concentration in BT−474 and half IC<sub>50</sub> concentration in SNU−251), and their combination for 72 h. Cell cycle distribution was assessed by flow cytometry after staining with PI. The histogram exhibited the distribution of cells in various phases (G0/G1, S, and G2/M) and the bar graphs represented the percentage of cells in G0/G1, S, and G2/M phases of cell cycle. (<b>C</b>,<b>D</b>) Western blot was carried out to check the expression of cell cycle progression-related proteins such as p-cdc25C and p-cdc2. (<b>C</b>) BT−474 and (<b>D</b>) SNU−251 cells were treated with 5 nM of PSPC1 siRNA, olaparib (IC<sub>50</sub> concentration in BT-474 and half IC<sub>50</sub> concentration in SNU−251), and their combination for 72 h. GAPDH was used as a loading control. (<b>E</b>) Graphical view of the proposed mechanism. Olaparib induced inhibitory phosphorylation of CDK1 causes mitotic exit which is reversed by PSPC1 inhibition (due to PSPC1 inhibition induced ATM and DNA-PKcs suppression), eventually premature mitotic entry occurred of the DNA-damaged cells, leading to mitotic catastrophe.</p>
Full article ">Figure 3 Cont.
<p>Mitotic catastrophe caused by combination treatment could explain the synergistic mechanisms. (<b>A</b>,<b>B</b>) BT−474 and SNU−251 cells were treated with 5 nM of PSPC1 siRNA, olaparib (IC<sub>50</sub> concentration in BT−474 and half IC<sub>50</sub> concentration in SNU−251), and their combination for 72 h. Cell cycle distribution was assessed by flow cytometry after staining with PI. The histogram exhibited the distribution of cells in various phases (G0/G1, S, and G2/M) and the bar graphs represented the percentage of cells in G0/G1, S, and G2/M phases of cell cycle. (<b>C</b>,<b>D</b>) Western blot was carried out to check the expression of cell cycle progression-related proteins such as p-cdc25C and p-cdc2. (<b>C</b>) BT−474 and (<b>D</b>) SNU−251 cells were treated with 5 nM of PSPC1 siRNA, olaparib (IC<sub>50</sub> concentration in BT-474 and half IC<sub>50</sub> concentration in SNU−251), and their combination for 72 h. GAPDH was used as a loading control. (<b>E</b>) Graphical view of the proposed mechanism. Olaparib induced inhibitory phosphorylation of CDK1 causes mitotic exit which is reversed by PSPC1 inhibition (due to PSPC1 inhibition induced ATM and DNA-PKcs suppression), eventually premature mitotic entry occurred of the DNA-damaged cells, leading to mitotic catastrophe.</p>
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<p>Combination of PSPC1 siRNA and olaparib inhibits tumor growth in a PSPC1-expressing BRCA2-mutated breast cancer xenograft model. (<b>A</b>) Graphical view of drug treatment schedule and animal experimental procedure. (<b>B</b>) The body weights of mice exhibited that the treated doses were well tolerated as weight loss was not observed (<b>C</b>) Mean tumor growth inhibition curves in mice which were treated with olaparib, PSPC1 siRNA, and their combination. Tumor volumes were measured three times a week by a vernier caliper. Indicated <span class="html-italic">p</span>-values were calculated by one-way ANOVA analysis on day 16 of treatment, whereas ** <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. (<b>D</b>) Individual tumor volumes were shown on day 16. Data are presented as the mean ± SEM. (<b>E</b>) Photo of the excised tumors of each group shown after sacrificing on day 16. The red dotted circles indicate complete regression of the tumor (<b>F</b>) Western blot using BT−474 xenografted tumors after 16 days of treatment. Combination treatment suppressed the expression of DDR-associated genes, such as p-ATM, DNA-PKcs, p-cdc25C, and p-cdc2 compared to monotherapy. (<b>G</b>) Western blot using BT−474 xenografted tumors after 16 days of treatment. The expression of the apoptosis marker cleaved caspase-3 was increased after combination treatment compared to monotherapy.</p>
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<p>High PSPC1 expression is associated with poor prognosis in breast and ovarian cancer. (<b>A</b>,<b>B</b>) Kaplan–Meier survival curve of RFS in breast cancer according to relative PSPC1 mRNA expression; the data were analyzed using online platform Kaplan–Meier plotter: <a href="https://kmplot.com/analysis/" target="_blank">https://kmplot.com/analysis/</a> (accessed on 01 August 2023). (<b>C</b>–<b>E</b>) Kaplan–Meier survival curve of OS in ovarian cancer according to relative <span class="html-italic">PSPC1</span> mRNA expression; the data were analyzed using online platform Kaplan–Meier plotter.</p>
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16 pages, 2386 KiB  
Review
G-Quadruplexes in Nuclear Biomolecular Condensates
by Iuliia Pavlova, Mikhail Iudin, Anastasiya Surdina, Vjacheslav Severov and Anna Varizhuk
Genes 2023, 14(5), 1076; https://doi.org/10.3390/genes14051076 - 13 May 2023
Cited by 7 | Viewed by 3182
Abstract
G-quadruplexes (G4s) have long been implicated in the regulation of chromatin packaging and gene expression. These processes require or are accelerated by the separation of related proteins into liquid condensates on DNA/RNA matrices. While cytoplasmic G4s are acknowledged scaffolds of potentially pathogenic condensates, [...] Read more.
G-quadruplexes (G4s) have long been implicated in the regulation of chromatin packaging and gene expression. These processes require or are accelerated by the separation of related proteins into liquid condensates on DNA/RNA matrices. While cytoplasmic G4s are acknowledged scaffolds of potentially pathogenic condensates, the possible contribution of G4s to phase transitions in the nucleus has only recently come to light. In this review, we summarize the growing evidence for the G4-dependent assembly of biomolecular condensates at telomeres and transcription initiation sites, as well as nucleoli, speckles, and paraspeckles. The limitations of the underlying assays and the remaining open questions are outlined. We also discuss the molecular basis for the apparent permissive role of G4s in the in vitro condensate assembly based on the interactome data. To highlight the prospects and risks of G4-targeting therapies with respect to the phase transitions, we also touch upon the reported effects of G4-stabilizing small molecules on nuclear biomolecular condensates. Full article
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<p>Molecular grammar of the biomolecular condensates and presumed G4 contacts within the condensates. (<b>a</b>) Schematic representation of the condensate formation through the liquid–liquid phase separation (LLPS). (<b>b</b>) Typical constituents and their interactions. (<b>c</b>) Major types of transient LLPS-driving contacts. (<b>d</b>) Schematic representation of the G4 structures. (<b>e</b>) Typical examples of the transient contacts in the protein mixtures with ss/dsNA and G4 NA.</p>
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<p>Effects of the G4s on the conformational transitions of the LLPS-driving proteins. (<b>a</b>) Nucleophosmin (NPM). The IDR- and ND-mediated binding of NPM to the G4 prevents intramolecular contacts within the NPM IDR, promotes intermolecular NPM–RM interactions, and thus facilitates the LLPS. (<b>b</b>) Heterochromatin protein 1α (HP1α). The HR-mediated binding of HP1α to the G4 prevents HP1α HR–CTE contacts, stabilizes the extended HP1α conformation, promotes intermolecular HP1α–H3Kme2/3 conformation, and thus facilitates the LLPS and heterochromatinization.</p>
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<p>G4s in nuclear biomolecular condensates. (<b>a</b>) Schematic representation of typical nuclear condensates with G4-prone DNA/RNA. (<b>b</b>) Details on the nucleoli organization. (<b>c</b>) Details on the organization of sub-telomeric heterochromatin and shelterin. (<b>d</b>) Presumed organization of Pol II condensates upon active transcription.</p>
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13 pages, 2446 KiB  
Article
NEAT1–SOD2 Axis Confers Sorafenib and Lenvatinib Resistance by Activating AKT in Liver Cancer Cell Lines
by Hiroyuki Tsuchiya, Ririko Shinonaga, Hiromi Sakaguchi, Yutaka Kitagawa and Kenji Yoshida
Curr. Issues Mol. Biol. 2023, 45(2), 1073-1085; https://doi.org/10.3390/cimb45020071 - 29 Jan 2023
Cited by 8 | Viewed by 2566
Abstract
This study investigated the effects of a long noncoding RNA, nuclear paraspeckle assembly transcript 1 (NEAT1) variant 1 (NEAT1v1) on drug resistance in liver cancer cell lines. NEAT1 knockdown activated mitogen-activated protein kinase (MAPK) signaling pathways, including MAPK kinase (MEK)/extracellular signal-regulated kinase (ERK), [...] Read more.
This study investigated the effects of a long noncoding RNA, nuclear paraspeckle assembly transcript 1 (NEAT1) variant 1 (NEAT1v1) on drug resistance in liver cancer cell lines. NEAT1 knockdown activated mitogen-activated protein kinase (MAPK) signaling pathways, including MAPK kinase (MEK)/extracellular signal-regulated kinase (ERK), but suppressed AKT. Moreover, NEAT1 knockdown sensitized liver cancer cells to sorafenib and lenvatinib, both clinically used for treating hepatocellular carcinoma, whereas it conferred resistance to an AKT-targeted drug, capivasertib. NEAT1v1 overexpression suppressed MEK/ERK and activated AKT, resulting in resistance to sorafenib and lenvatinib and sensitization to capivasertib. Superoxide dismutase 2 (SOD2) knockdown reverted the effects of NEAT1v1 overexpression on the sensitivity to the molecular-targeted drugs. Although NEAT1 or SOD2 knockdown enhanced endoplasmic reticulum (ER) stress, concomitant with the suppression of AKT, taurodeoxycholate, an ER stress suppressor, did not restore AKT activity. Although further in vivo and clinical studies are needed, these results suggested that NEAT1v1 switches the growth modality of liver cancer cell lines from MEK/ERK-dependent to AKT-dependent mode via SOD2 and regulates sensitivity to the molecular-targeted drugs independent of ER stress. Full article
(This article belongs to the Special Issue Molecules at Play in Cancer)
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<p>NEAT1 knockdown induces sorafenib and lenvatinib resistance. (<b>A</b>) Representative Western blot images for the indicated proteins. GAPDH is shown as an internal control. HLF and HuH6 cell lines were transduced with adenoviruses expressing nontargeting shRNA [shNT (N)] or NEAT1-specific shRNAs [shNEAT1a (Na) and shNEAT1b (Nb)] for 48 h. (<b>B</b>) Viabilities of HLF and HuH6 cells treated with sorafenib or lenvatinib at the concentrations indicated in the figure for 48 h relative to cells treated with dimethyl sulfoxide (DMSO; 100%). Cells were transduced with adenoviruses expressing shNT, shNEAT1a, and shNEAT1b 48 h before drug treatment. * <span class="html-italic">p</span> &lt; 0.05 vs. shNT vs. shNEAT1a; # <span class="html-italic">p</span> &lt; 0.05 shNT vs. shNEAT1b (Dunnett’s test; <span class="html-italic">n</span> = 4).</p>
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<p>NEAT1 knockdown induces resistance against an AKT-targeted drug, capivasertib. (<b>A</b>) Representative Western blot images for the indicated proteins. GAPDH is shown as an internal control. HLF and HuH6 cell lines were transduced with adenoviruses expressing non-targeting shRNA [shNT (N)] or NEAT1-specific shRNAs [shNEAT1a (Na) and shNEAT1b (Nb)] for 48 h. (<b>B</b>) Viabilities of HLF and HuH6 cells treated with capivasertib at the concentrations indicated in the figure for 48 h relative to cells treated with DMSO (100%). Cells were transduced with adenoviruses expressing shNT, shNEAT1a, and shNEAT1b 48 h before drug treatment. * <span class="html-italic">p</span> &lt; 0.05 vs. shNT vs. shNEAT1a; # <span class="html-italic">p</span> &lt; 0.05 shNT vs. shNEAT1b (Dunnett’s test; <span class="html-italic">n</span> = 4).</p>
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<p>NEAT1v1 plays a role as a molecular switch of cell growth modality. (<b>A</b>,<b>C</b>) Representative Western blot images for the indicated proteins in control (<b>C</b>) or NEAT1v1-overexpressing (V1) cells. GAPDH is shown as an internal control. (<b>B</b>,<b>D</b>) Viabilities of control (CTRL) or NEAT1v1-overexpressing (NEAT1v1) cells treated with sorafenib (<b>B</b>), lenvatinib (<b>B</b>), or capivasertib (<b>D</b>) at the concentrations indicated in the figure for 48 h relative to cells treated with DMSO (100%). * <span class="html-italic">p</span> &lt; 0.05 vs. CTRL (Student’s <span class="html-italic">t</span>-test; <span class="html-italic">n</span> = 4).</p>
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<p>NEAT1v1 regulates cell growth modality through SOD2. (<b>A</b>) Representative Western blot images for SOD2 expression in HLF and HuH6 cells transduced with adenoviruses expressing shNT (N), shNEAT1a (Na), or shNEAT1b (Nb) for 48 h. GAPDH is shown as an internal control. (<b>B</b>) Representative Western blot images for SOD2 expression in control (<b>C</b>) or NEAT1v1-overexpressing (V1) HLF and HuH6 cells. (<b>C</b>,<b>E</b>) Representative Western blot images for the indicated proteins in NEAT1v1-overexpressing cells transduced with adenoviruses expressing shNT (N) or SOD2-specific shRNAs [shSOD2a (Sa) and shSOD2b (Sb)] for 48 h. (<b>D</b>,<b>F</b>) Viabilities of cells treated with sorafenib (<b>D</b>), lenvatinib (<b>D</b>), or capivasertib (<b>F</b>) at the concentrations indicated in the figure for 48 h relative to cells treated with DMSO (100%). NEAT1v1-overexpressing cells were transduced with adenoviruses expressing shNT, shSOD2a, and shSOD2b 48 h before drug treatment. * <span class="html-italic">p</span> &lt; 0.05 vs. shNT vs. shSOD2a; # <span class="html-italic">p</span> &lt; 0.05 shNT vs. shSOD2b (Dunnett’s test; n = 4).</p>
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<p>NEAT1v1 or SOD2 knockdown suppresses AKT activity independent of ER stress. (<b>A</b>) mRNA expression of ER stress target genes (BIP, CHOP, and ERO1α). HLF and HuH6 cell lines were transduced with adenoviruses expressing shNT, shNEAT1a, or shSOD2a in the presence of 0 mM (H2O; CTRL) or 2 mM TUDC for 48 h. * <span class="html-italic">p</span> &lt; 0.05 vs. shNT; # <span class="html-italic">p</span> &lt; 0.05 vs. CTRL (Tukey’s test; <span class="html-italic">n</span> = 3). (<b>B</b>) Representative Western blot images for the indicated proteins. βTUB is shown as an internal control. HLF and HuH6 cell lines were transduced with adenoviruses expressing shNT (N), shNEAT1a (Na), or shSOD2a (Sa) for 48 h. (<b>C</b>) Representative Western blot images for the indicated proteins. GAPDH is shown as an internal control. HuH6 cell lines were transduced with adenoviruses expressing shNT (N), shNEAT1a (Na), or shSOD2a (Sa) in the presence of 0 mM (H2O; CTRL) or 2 mM TUDC for 48 h.</p>
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<p>NEAT1v1 activates the AKT pathway through SOD2, thereby conferring sorafenib and lenvatinib resistance in liver cancer cells, which are concomitantly sensitized to capivasertib. This result suggests that NEAT1v1 switches the growth modality of liver cancer cells from MEK/ERK-dependent to AKT-dependent mode via SOD2. Consistently, NEAT1 or SOD2 knockdown results in MEK/ERK activation, thereby sensitizing liver cancer cells to sorafenib and lenvatinib and conferring capivasertib resistance. NEAT1v1 or SOD2 knockdown also exacerbates ER stress; however, AKT is suppressed in an ER stress-independent manner.</p>
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17 pages, 2472 KiB  
Article
The KDET Motif in the Intracellular Domain of the Cell Adhesion Molecule L1 Interacts with Several Nuclear, Cytoplasmic, and Mitochondrial Proteins Essential for Neuronal Functions
by Ralf Kleene, Gabriele Loers and Melitta Schachner
Int. J. Mol. Sci. 2023, 24(2), 932; https://doi.org/10.3390/ijms24020932 - 4 Jan 2023
Cited by 5 | Viewed by 2142
Abstract
Abnormal functions of the cell adhesion molecule L1 are linked to several neural diseases. Proteolytic L1 fragments were reported to interact with nuclear and mitochondrial proteins to regulate events in the developing and the adult nervous system. Recently, we identified a 55 kDa [...] Read more.
Abnormal functions of the cell adhesion molecule L1 are linked to several neural diseases. Proteolytic L1 fragments were reported to interact with nuclear and mitochondrial proteins to regulate events in the developing and the adult nervous system. Recently, we identified a 55 kDa L1 fragment (L1-55) that interacts with methyl CpG binding protein 2 (MeCP2) and heterochromatin protein 1 (HP1) via the KDET motif. We now show that L1-55 also interacts with histone H1.4 (HistH1e) via this motif. Moreover, we show that this motif binds to NADH dehydrogenase ubiquinone flavoprotein 2 (NDUFV2), splicing factor proline/glutamine-rich (SFPQ), the non-POU domain containing octamer-binding protein (NonO), paraspeckle component 1 (PSPC1), WD-repeat protein 5 (WDR5), heat shock cognate protein 71 kDa (Hsc70), and synaptotagmin 1 (SYT1). Furthermore, applications of HistH1e, NDUFV2, SFPQ, NonO, PSPC1, WDR5, Hsc70, or SYT1 siRNAs or a cell-penetrating KDET-carrying peptide decrease L1-dependent neurite outgrowth and the survival of cultured neurons. These findings indicate that L1’s KDET motif binds to an unexpectedly large number of molecules that are essential for nervous system-related functions, such as neurite outgrowth and neuronal survival. In summary, L1 interacts with cytoplasmic, nuclear and mitochondrial proteins to regulate development and, in adults, the formation, maintenance, and flexibility of neural functions. Full article
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<p>L1-55 interacts with MeCP2, HP1, and HistH1 but not with other verified or putative L1 binding partners in cultured cortical neurons. Neurons were treated with the vehicle dimethyl sulfoxide (DMSO) (+DMSO) or with the γ-secretase inhibitor DAPT and were then subjected to proximity ligation with L1 antibodies and antibodies against NDUFV2, SFPQ, NonO, PSPC1, WDR5, TOP1, hnRNP A isoforms, HistH1, Nup93, Hsc70, SYT1, impβ1, ERα, RXR, PPARγ, AR, VDR, MeCP2, or HP1γ. Nuclei are stained with DAPI (4′,6-diamidino-2-phenylindole). (<b>a</b>,<b>b</b>) Representative images of DMSO- and DAPT-treated neurons stained with mouse L1 antibody C-2 and a rabbit antibody against hnRNP A isoforms (<b>a</b>) or HistH1 (<b>b</b>) are shown. Scale bar: 10 µm. (<b>c</b>) The mean values + SD are from two independent experiments and show average numbers of red dots per cell after DAPT-treatment relative to control (values of vehicle control set to 100%) (**** <span class="html-italic">p</span> &lt; 0.001; one-way ANOVA with Dunn’s multiple comparison test). Values obtained for proteins known to bind to L1-55 served as positive controls and are marked in dark gray. (<b>d</b>) Non-nuclear fractions from wild-type (WT) and L1-deficient (KO) mice were used for immunoprecipitation with mouse HistH1 or NDUFV2 antibodies immobilized to Protein G. Fractions (input) and immunoprecipitates (IP) were subjected to Western blot analysis with L1 antibody C-2. Arrows indicate L1-55 and L1-70, and the arrowhead indicates an unknown L1 band of approximately 75 kDa.</p>
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<p>L1-ICD binds to several binding partners via its KDET motif. Recombinant L1-binding partners were substrate-coated and incubated with a constant L1-ICD concentration in the absence or presence of the KDET peptide or QNQS control peptide (<b>a</b>) or with increasing L1-ICD concentrations (<b>b</b>–<b>f</b>). Binding was determined by ELISA using mouse L1 antibody C-2 and horseradish peroxidase-conjugated secondary antibodies. The mean values ± SD from three independent experiments carried out in triplicate are shown for the binding relative to control (values in the absence of peptides set to 100%). *** <span class="html-italic">p</span> &lt; 0.005, **** <span class="html-italic">p</span> &lt; 0.001; one-way ANOVA with Bonferroni´s multiple comparison test.</p>
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<p>In cultured cortical neurons, L1 interacts with several binding partners via its KDET motif. Cultured cortical neurons were treated with vehicle, tat-KDET peptide, or tat-QNQS control peptide, followed by treatment without (<b>a</b>) and with (<b>b</b>) L1 antibody 557 and proximity ligation with a L1 antibody and an antibody against MeCP2, NDUFV2, SFPQ, NonO, PSPC1, WDR5, TOP1, HistH1, Nup93, Hsc70, SYT1, ERα, or PPARγ. Mean values + SD from two independent experiments are shown for the average numbers of red dots per cell relative to control (values of treatment with vehicle set to 100%) (**** <span class="html-italic">p</span> &lt; 0.001; one-way ANOVA with Bonferroni´s multiple comparison test).</p>
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<p>The KDET-mediated interaction of L1 with its binding partners is essential for L1-dependent neurite outgrowth and neuronal cell survival. Cerebellar (<b>a</b>,<b>c</b>) and cortical (<b>b</b>,<b>d</b>) neurons were treated with 0, 0.5, 1, 2, 5, 10, 20, 50, or 100 µg/mL tat-KDET peptide (<b>a</b>,<b>b</b>), with 0 or 50 µg/mL tat-KDET peptide (P<sup>WT</sup>) or with 0 or 50 µg/mL tat-QNQS peptide (P<sup>mut</sup>) (<b>c</b>,<b>d</b>). Neurons were then treated without or with antibody 557. Mean values + SEM from three independent experiments are shown for total neurite lengths (**** <span class="html-italic">p</span> &lt; 0.0001 relative to stimulated neurons not treated with tat-KDET peptide, §§§§ <span class="html-italic">p</span> &lt; 0.0001 relative to non-stimulated neurons not treated with tat-KDET peptide or tat-QNQS peptide; one-way ANOVA with Dunn’s multiple comparison test). (<b>e</b>) Cerebellar neurons were first treated with 0, 2, 10, 20, 50, or 100 µg/mL tat-KDET peptide and then treated without or with antibody 557 in the absence or presence of H<sub>2</sub>O<sub>2</sub>. Mean values + SEM from three independent experiments are shown for the relative numbers of dead cells (**** <span class="html-italic">p</span> &lt; 0.0001 relative to stimulated neurons not treated with tat-KDET peptide in the presence of H<sub>2</sub>O<sub>2</sub>, §§§§ <span class="html-italic">p</span> &lt; 0.0001 relative to non-stimulated neurons not treated with tat-KDET peptide in the presence of H<sub>2</sub>O<sub>2</sub>, #### <span class="html-italic">p</span> &lt; 0.0001 relative to unstimulated neurons not treated with tat-KDET peptide in the absence of H<sub>2</sub>O<sub>2</sub>; one-way ANOVA with Dunn´s multiple comparison test).</p>
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<p>Reduction of SFPQ, NonO, WDR5, NDUFV2, SYT1, Hsc70, and HistH1e expression by siRNAs inhibits L1-dependent neurite outgrowth. Cortical neurons were not treated (no), treated without (mock), or treated with siRNAs specific for SFPQ, NonO, PSPC1, WDR5, NDUFV2, SYT1, Hsc70, and HistH1e. Neurons were then treated without or with antibody 557. (<b>a</b>) Mean values + SEM from three independent experiments are shown for total neurite lengths (**** <span class="html-italic">p</span> &lt; 0.0001 relative to L1 antibody-stimulated mock-transfected neurons, #### <span class="html-italic">p</span> &lt; 0.0001 relative to non-stimulated mock-transfected neurons; one-way ANOVA with Dunn´s multiple comparison test). (<b>b</b>) Western blot analysis of lysates from mock-transfected neurons or neurons transfected with siRNAs using the corresponding antibodies. Ponceau S staining of a prominent 35-kDa band served as loading control. (<b>c</b>) Immunostaining of mock-transfected neurons or neurons transfected with NDUFV2 siRNA using a NDUFV2 antibody. Scale bar: 10 µm.</p>
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<p>Schematic representation of L1-55 and L1-70. Full-length L1 (L1-200) consists of an extracellular portion with 6 Ig-like (Ig) and 5 FNIII (FN) domains, a transmembrane domain (TMD), and an intracellular domain (ICD), which contains the KDET motif. L1-200 is cleaved by a proteolytically active myelin basic protein in the first FNIII domain at position 687, leading to the generation of L1-70, which comprises part of the first FNIII domain, the second, third, fourth, and fifth FNIII domains, as well as the TMD and ICD with the KDET motif. Sequential cleavage of L1-200 by metalloproteases, the β-site of an amyloid precursor protein cleaving enzyme and ɣ-secretase generates L1-55, which comprises amino acids of the TMD and the entire ICD with the KDET motif.</p>
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18 pages, 755 KiB  
Review
The Involvement of Long Non-Coding RNAs in Glutamine-Metabolic Reprogramming and Therapeutic Resistance in Cancer
by Jungwook Roh, Mijung Im, Yeonsoo Chae, JiHoon Kang and Wanyeon Kim
Int. J. Mol. Sci. 2022, 23(23), 14808; https://doi.org/10.3390/ijms232314808 - 26 Nov 2022
Cited by 8 | Viewed by 2539
Abstract
Metabolic alterations that support the supply of biosynthetic molecules necessary for rapid and sustained proliferation are characteristic of cancer. Some cancer cells rely on glutamine to maintain their energy requirements for growth. Glutamine is an important metabolite in cells because it not only [...] Read more.
Metabolic alterations that support the supply of biosynthetic molecules necessary for rapid and sustained proliferation are characteristic of cancer. Some cancer cells rely on glutamine to maintain their energy requirements for growth. Glutamine is an important metabolite in cells because it not only links to the tricarboxylic acid cycle by producing α-ketoglutarate by glutaminase and glutamate dehydrogenase but also supplies other non-essential amino acids, fatty acids, and components of nucleotide synthesis. Altered glutamine metabolism is associated with cancer cell survival, proliferation, metastasis, and aggression. Furthermore, altered glutamine metabolism is known to be involved in therapeutic resistance. In recent studies, lncRNAs were shown to act on amino acid transporters and glutamine-metabolic enzymes, resulting in the regulation of glutamine metabolism. The lncRNAs involved in the expression of the transporters include the abhydrolase domain containing 11 antisense RNA 1, LINC00857, plasmacytoma variant translocation 1, Myc-induced long non-coding RNA, and opa interacting protein 5 antisense RNA 1, all of which play oncogenic roles. When it comes to the regulation of glutamine-metabolic enzymes, several lncRNAs, including nuclear paraspeckle assembly transcript 1, XLOC_006390, urothelial cancer associated 1, and thymopoietin antisense RNA 1, show oncogenic activities, and others such as antisense lncRNA of glutaminase, lincRNA-p21, and ataxin 8 opposite strand serve as tumor suppressors. In addition, glutamine-dependent cancer cells with lncRNA dysregulation promote cell survival, proliferation, and metastasis by increasing chemo- and radio-resistance. Therefore, understanding the roles of lncRNAs in glutamine metabolism will be helpful for the establishment of therapeutic strategies for glutamine-dependent cancer patients. Full article
(This article belongs to the Special Issue Signaling Transduction in Cancer Metabolism)
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<p>A schematic illustration showing the contributions of lncRNAs to glutamine metabolic reprogramming and therapeutic resistance. LncRNA UCA1, TMPO-AS1, ATXN8OS, NEAT1, and OIP5-AS1 are associated with the regulation of chemosensitivity, and lncRNA UCA1, NEAT1, and lincRNA-p21 are involved in the regulation of radiation sensitivity.</p>
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14 pages, 3438 KiB  
Communication
NEAT1 Confers Radioresistance to Hepatocellular Carcinoma Cells by Inducing PINK1/Parkin-Mediated Mitophagy
by Hiroyuki Tsuchiya, Ririko Shinonaga, Hiromi Sakaguchi, Yutaka Kitagawa, Kenji Yoshida and Goshi Shiota
Int. J. Mol. Sci. 2022, 23(22), 14397; https://doi.org/10.3390/ijms232214397 - 19 Nov 2022
Cited by 14 | Viewed by 2664
Abstract
A long noncoding RNA, nuclear paraspeckle assembly transcript 1 (NEAT1) variant 1 (NEAT1v1), confers radioresistance to hepatocellular carcinoma (HCC) cells by inducing autophagy via γ-aminobutyric acid A receptor-associated protein (GABARAP). Radiation induces oxidative stress to damage cellular components and organelles, but it remains [...] Read more.
A long noncoding RNA, nuclear paraspeckle assembly transcript 1 (NEAT1) variant 1 (NEAT1v1), confers radioresistance to hepatocellular carcinoma (HCC) cells by inducing autophagy via γ-aminobutyric acid A receptor-associated protein (GABARAP). Radiation induces oxidative stress to damage cellular components and organelles, but it remains unclear how NEAT1v1 protects HCC cells from radiation-induced oxidative stress via autophagy. To address this, we precisely investigated NEAT1v1-induced autophagy in irradiated HCC cell lines. X-ray irradiation significantly increased cellular and mitochondrial oxidative stress and mitochondrial DNA content in HCC cells while NEAT1v1 suppressed them. NEAT1v1 concomitantly induced the phosphatase and tensin homolog-induced kinase 1 (PINK1)/parkin-mediated mitophagy. Interestingly, parkin expression was constitutively upregulated in NEAT1v1-overexpressing HCC cells, leading to increased mitochondrial parkin levels. Superoxide dismutase 2 (SOD2) was also upregulated by NEAT1v1, and GABARAP or SOD2 knockdown in NEAT1v1-overexpressing cells increased mitochondrial oxidative stress and mitochondrial DNA content after irradiation. Moreover, it was suggested that SOD2 was involved in NEAT1v1-induced parkin expression, and that GABARAP promoted parkin degradation via mitophagy. This study highlights the unprecedented roles of NEAT1v1 in connecting radioresistance and mitophagy in HCC. Full article
(This article belongs to the Special Issue The Role of Autophagy Processes in Human Diseases)
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<p>Protective effects of NEAT1v1 on radiation-induced mitochondrial damage. (<b>A</b>) Radiation dose-dependent increases in cellular (left) and mitochondrial (right) oxidative stress. * <span class="html-italic">p</span> &lt; 0.05 (Dunnett’s test vs. 0 Gy; <span class="html-italic">n</span> = 4). (<b>B</b>) Suppression of radiation-induced cellular (left) and mitochondrial (right) oxidative stress. * <span class="html-italic">p</span> &lt; 0.05 [Student’s <span class="html-italic">t</span>-test, control (CTRL) vs. NEAT1v1-overexpressing cells; <span class="html-italic">n</span> = 4]. (<b>C</b>) Relative copy number of mitochondrially encoded genes (<span class="html-italic">ND1</span> and <span class="html-italic">ND5</span>). * <span class="html-italic">p</span> &lt; 0.05 (Student’s <span class="html-italic">t</span>-test, CTRL vs. NEAT1v1-overexpressing cells; <span class="html-italic">n</span> = 3).</p>
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<p>Induction of PINK1/parkin-mediated mitophagy by NEAT1v1 in irradiated cells. (<b>A</b>) Representative images of mitophagy staining. Mitophagy was stained with Mitophagy Dye (red). Nuclei were counterstained with Hoechst (blue). Scale bar, 100 µm. (<b>B</b>) Representative Western blot images for mitochondrial and cytosolic PINK1, parkin, GRP75 (mitochondrial marker), and ERK1/2 (cytosolic marker). C, CTRL; NEAT, NEAT1v1-overexpressing cells.</p>
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<p>Involvement of SOD2 in NEAT1v1-induced radioresistance. (<b>A</b>) MRNA expression levels of genes encoding antioxidative enzymes in NEAT1v1-overexpressing cells. * <span class="html-italic">p</span> &lt; 0.05 [Student’s <span class="html-italic">t</span>-test, control (CTRL) vs. NEAT1v1-overexpressing cells; <span class="html-italic">n</span> = 3]. (<b>B</b>) Expression levels of SOD2 mRNA in control (C) or NEAT1v1-overexpressing cells (N) transduced with adenoviruses expressing nontarget shRNA (shNT) or NEAT1-specific shRNAs (shNEAT1a and shNEAT1b). * <span class="html-italic">p</span> &lt; 0.05 (Dunnett’s test vs. shNT; <span class="html-italic">n</span> = 3). (<b>C</b>) Representative Western blot images for SOD2 and GAPDH (internal control) using whole-cell lysates after 0 or 5 Gy irradiation. (<b>D</b>) Representative Western blot images for SOD1, SOD2, and GAPDH (internal control) using whole-cell lysates of cells transduced with adenoviruses expressing shNT or SOD2-specific shRNAs (shSOD2a and shSOD2b). (<b>E</b>) Colony formation abilities of NEAT1v1-overexpressing cells knocked down for SOD2 after 2.5 Gy irradiation. * <span class="html-italic">p</span> &lt; 0.05 (Dunnett’s test vs. shNT; <span class="html-italic">n</span> = 6).</p>
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<p>Involvement of GABARAP and SOD2 in the suppressive effects of NEAT1v1 on radiation-induced mitochondrial damage. (<b>A</b>,<b>B</b>) Cellular (left) and mitochondrial (right) oxidative stress (<b>A</b>) and relative copy number of mitochondrially encoded genes (ND1 and ND5); (<b>B</b>) in NEAT1v1-overexpressing HLF and HuH6 cells knocked down for GABARAP (shGBRPa and shGBRPb) or SOD2 (shSOD2a and shSOD2b) after 5 Gy irradiation. * <span class="html-italic">p</span> &lt; 0.05 [Dunnett’s test vs. shNT; <span class="html-italic">n</span> = 6 (<b>A</b>) and 3 (<b>B</b>)].</p>
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<p>Involvement of GABARAP and SOD2 in NEAT1v1-induced mitophagy. (<b>A</b>) Representative Western blot images for mitochondrial and cytosolic PINK1, parkin, SOD2, GABARAP, GRP75 (mitochondrial marker), and ERK1/2 (cytosolic marker). C, CTRL, control cells; NEAT, NEAT1v1-overexpressing cells. (<b>B</b>) Schematic representation of NEAT1v1-induced radioresistance via the PINK1/parkin-mediated mitophagy. NEAT1v1 upregulates GABARAP and SOD2 in HCC cells. GABARAP is a critical factor for mitophagy, whereas SOD2 reduces oxidative stress by its antioxidative activity and induces parkin expression.</p>
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<p>Involvement of GABARAP and SOD2 in NEAT1v1-induced mitophagy. (<b>A</b>) Representative Western blot images for mitochondrial and cytosolic PINK1, parkin, SOD2, GABARAP, GRP75 (mitochondrial marker), and ERK1/2 (cytosolic marker). C, CTRL, control cells; NEAT, NEAT1v1-overexpressing cells. (<b>B</b>) Schematic representation of NEAT1v1-induced radioresistance via the PINK1/parkin-mediated mitophagy. NEAT1v1 upregulates GABARAP and SOD2 in HCC cells. GABARAP is a critical factor for mitophagy, whereas SOD2 reduces oxidative stress by its antioxidative activity and induces parkin expression.</p>
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19 pages, 3280 KiB  
Article
Melatonin Attenuates H2O2-Induced Oxidative Injury by Upregulating LncRNA NEAT1 in HT22 Hippocampal Cells
by Qiang Gao, Chi Zhang, Jiaxin Li, Han Xu, Xiaocheng Guo, Qi Guo, Chen Zhao, Haixu Yao, Yuhan Jia and Hui Zhu
Int. J. Mol. Sci. 2022, 23(21), 12891; https://doi.org/10.3390/ijms232112891 - 25 Oct 2022
Cited by 4 | Viewed by 2060
Abstract
More research is required to understand how melatonin protects neurons. The study aimed to find out if and how long non-coding RNA (lncRNA) contributes to melatonin’s ability to defend the hippocampus from H2O2-induced oxidative injury. LncRNAs related to oxidative [...] Read more.
More research is required to understand how melatonin protects neurons. The study aimed to find out if and how long non-coding RNA (lncRNA) contributes to melatonin’s ability to defend the hippocampus from H2O2-induced oxidative injury. LncRNAs related to oxidative injury were predicted by bioinformatics methods. Mouse hippocampus-derived neuronal HT22 cells were treated with H2O2 with or without melatonin. Viability and apoptosis were detected by Cell Counting Kit-8 and Hoechst33258. RNA and protein levels were measured by quantitative real-time PCR, Western blot, and immunofluorescence. Bioinformatics predicted that 38 lncRNAs were associated with oxidative injury in mouse neurons. LncRNA nuclear paraspeckle assembly transcript 1 (NEAT1) was related to H2O2-induced oxidative injury and up-regulated by melatonin in HT22 cells. The knockdown of NEAT1 exacerbated H2O2-induced oxidative injury, weakened the moderating effect of melatonin, and abolished the increasing effect of melatonin on the mRNA and protein level of Slc38a2. Taken together, melatonin attenuates H2O2-induced oxidative injury by upregulating lncRNA NEAT1, which is essential for melatonin stabilizing the mRNA and protein level of Slc38a2 for the survival of HT22 cells. The research may assist in the treatment of oxidative injury-induced hippocampal degeneration associated with aging using melatonin and its target lncRNA NEAT1. Full article
(This article belongs to the Special Issue Mitophagy in Neurodegeneration and Aging)
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Figure 1
<p>Microarray analysis for identification of differentially expressed lncRNA and mRNA during oxidative injury in mouse neurons. (<b>A</b>) The scatter plot of the expression distributions of lncRNA in the oxidative injury group and the control group. (<b>B</b>) The scatter plot of the expression distributions of mRNA in the oxidative injury group and the control group. In (<b>A</b>,<b>B</b>), the horizontal axis represents the value of lncRNA and mRNA in the control group, and the vertical axis represents the value of lncRNA and mRNA in the oxidative injury group. The red dots represent lncRNA or mRNA in each sample. The lncRNA or mRNA distributed near the intermediate line (x = y) represents a similar expression in the two groups. The points outside of the two edges (|y − x| &gt; 1) represent lncRNA or mRNA that are differentially expressed greater than a 2-fold change between the two groups. (<b>C</b>) The hierarchical clustering heat map of differentially expressed lncRNA between the oxidative injury group and the control group. (<b>D</b>) The hierarchical clustering heat map of differentially expressed mRNA between the oxidative injury group and the control group. In (<b>C</b>,<b>D</b>), the red color indicates high relative expression, and green indicates low relative expression. N = 5 for the control group, and N = 3 for the oxidative injury group. Con represents the control group.</p>
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<p>LncRNA nuclear paraspeckle assembly transcript 1 (NEAT1) and 1810026B05Rik were involved in melatonin protecting against H<sub>2</sub>O<sub>2</sub>-induced oxidative injury in HT22 cells. (<b>A</b>) HT22 cells were treated with 200 μM H<sub>2</sub>O<sub>2</sub> for 24 h. The relative expression of lncRNA NEAT1, 1810026B05Rik, 2900009J06Rik, small nucleolar RNA host gene 12 (SNHG12), SNHG1, and C130026L21Rik were detected by quantitative real-time PCR (qPCR). (<b>B</b>) HT22 cells were treated with 200 μM H<sub>2</sub>O<sub>2</sub> or 200 μM H<sub>2</sub>O<sub>2</sub> + 50 μM melatonin for 24 h. The relative expression of lncRNA NEAT1, SNHG12, and 1810026B05Rik was detected by qPCR. (<b>C</b>) HT22 cells were treated with 50 μM Melatonin for 24 h. The relative expression of lncRNA NEAT1, SNHG12, and 1810026B05Rik was detected by qPCR. Results were expressed by the relative content of the Control group. *, ** and *** respectively represents <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">p</span> &lt; 0.01 and <span class="html-italic">p</span> &lt; 0.001 compared with the Control group. # represents <span class="html-italic">p</span> &lt; 0.05 compared with the H<sub>2</sub>O<sub>2</sub> group.</p>
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<p>Gene ontology analysis for the potential functionalities of lncRNA NEAT1 during oxidative injury in mouse neurons. (<b>A</b>) Co-expression network of LncRNA NEAT1 and its related differentially expressed mRNAs. (<b>B</b>) Network of lncRNA NEAT1 and its related biological processes (BP). The yellow triangle represents lncRNA NEAT1, the blue round NEAT1-related mRNA, the pink rectangle biological processes related to NEAT1, and the red rectangle biological processes related to NEAT1 and proliferation, apoptosis, senescence or autophagy.</p>
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<p>The knockdown of lncRNA NEAT1 aggravated H<sub>2</sub>O<sub>2</sub>-induced oxidative injury in HT22 cells. After HT22 cells were transfected with shRNA-negative control (NC) and shRNA-NEAT expression vectors for 48 h, (<b>A</b>) the expression of green fluorescent protein (GFP) carried by the vectors was observed with fluorescence microscopy. The results were obtained at 100× magnification; (<b>B</b>) the expression level of NEAT1 was detected by qPCR. Then, HT22 cells were treated with H<sub>2</sub>O<sub>2</sub> for 24 h following the transfection of vectors. (<b>C</b>) The morphological change was observed under phase contrast microscopy. The results were obtained at 100× magnification. (<b>D</b>) Relative cellular viability was detected by Cell Counting Kit (CCK)-8. (<b>E</b>) Hoechst33258 staining was used to observe apoptosis. The white arrows indicate nuclear fragmentation and nuclear consolidation in HT22 cells. The result was obtained at 200× magnification. (<b>F</b>) Statistical results of (<b>E</b>). ** represents <span class="html-italic">p</span> &lt; 0.01 compared to the shRNA-NC group. ## represents <span class="html-italic">p</span> &lt; 0.01 and <span class="html-italic">p</span> &lt; 0.001 compared to the H<sub>2</sub>O<sub>2</sub> + shRNA-NC group.</p>
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<p>The knockdown of lncRNA NEAT1 inhibited the protective effect of melatonin on H<sub>2</sub>O<sub>2</sub>-induced oxidative injury. HT22 cells were transfected with shRNA-NEAT1 expression vectors for 48 h and then treated with H<sub>2</sub>O<sub>2</sub> or H<sub>2</sub>O<sub>2</sub> + melatonin for 24 h. (<b>A</b>) Cell morphology was observed by phase contrast microscopy. The result was obtained at 100× magnification. (<b>B</b>) Relative cellular viability was detected by CCK-8. (<b>C</b>) Apoptosis was observed by Hoechst33258 staining. The white arrows indicate nuclear fragmentation and nuclear consolidation in HT22 cells. The result was obtained at 200× magnification. (<b>D</b>) Statistical results of (<b>C</b>). * represents <span class="html-italic">p</span> &lt; 0.05 compared with the control group, # represents <span class="html-italic">p</span> &lt; 0.05 compared with the H<sub>2</sub>O<sub>2</sub> group, &amp; represents <span class="html-italic">p</span> &lt; 0.05 compared with the H<sub>2</sub>O<sub>2</sub> + melatonin group.</p>
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<p>The influence of H<sub>2</sub>O<sub>2</sub>, melatonin, and shRNA-NEAT1 on the expression of NEAT1 co-expressed mRNA. HT22 cells were transfected with or without shRNA-NC or shRNA-NEAT1 vector for 48 h, followed by treatment with melatonin, H<sub>2</sub>O<sub>2</sub>, or H<sub>2</sub>O<sub>2</sub> + melatonin for 24 h. Then, the mRNA level of <span class="html-italic">Atf4</span> (<b>A</b>), <span class="html-italic">Dap</span> (<b>B</b>), <span class="html-italic">Eif2ak3</span> (<b>C</b>), <span class="html-italic">Gata1</span> (<b>D</b>), <span class="html-italic">Ifn-γ</span> (<b>E</b>), and <span class="html-italic">Slc38a2</span> (<b>F</b>) was detected by qPCR. *, ** and ***, respectively, represent <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">p</span> &lt; 0.01 and <span class="html-italic">p</span> &lt; 0.001 compared with the control group. # and ##, respectively, represent <span class="html-italic">p</span> &lt; 0.05 and <span class="html-italic">p</span> &lt; 0.01 compared with the H<sub>2</sub>O<sub>2</sub> group. &amp; and &amp;&amp;, respectively, represent <span class="html-italic">p</span> &lt; 0.05 and <span class="html-italic">p</span> &lt; 0.01 compared with the H<sub>2</sub>O<sub>2</sub> + melatonin + shRNA-NC group.</p>
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<p>The influence of H<sub>2</sub>O<sub>2</sub>, melatonin, and shRNA-NEAT1 on the expression of sodium-coupled neutral amino acid transporter 2 (SLC38A2). HT22 cells were transfected with or without shRNA-NC or shRNA-NEAT1 vector for 48 h, followed by treatment with melatonin, H<sub>2</sub>O<sub>2,</sub> or H<sub>2</sub>O<sub>2</sub> + melatonin for 24 h. (<b>A</b>) The expression level of sodium-coupled neutral amino acid transporter 2 (SLC38A2) was detected by Western blot analysis. The relative optical density values of SLC38A2 to β-actin were quantified using Image J software version 1.46r. (<b>B</b>) The expression level of SLC38A2 on membranes was detected by immunofluorescence staining. * represents <span class="html-italic">p</span> &lt; 0.05 compared with the control group. # represents <span class="html-italic">p</span> &lt; 0.05 compared with the H<sub>2</sub>O<sub>2</sub> group. &amp; represents <span class="html-italic">p</span> &lt; 0.05 and <span class="html-italic">p</span> &lt; 0.01 compared with the H<sub>2</sub>O<sub>2</sub> + melatonin + shRNA-NC group.</p>
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21 pages, 12017 KiB  
Review
The Long and the Short of It: NEAT1 and Cancer Cell Metabolism
by Nadine E. Smith, Phaedra Spencer-Merris, Archa Hannah Fox, Janni Petersen and Michael Z. Michael
Cancers 2022, 14(18), 4388; https://doi.org/10.3390/cancers14184388 - 9 Sep 2022
Cited by 14 | Viewed by 4393
Abstract
The long noncoding RNA NEAT1 is known to be heavily dysregulated in many cancers. A single exon gene produces two isoforms, NEAT1_1 and NEAT1_2, through alternative 3′-end processing. As the longer isoform, NEAT1_2 is an essential scaffold for nuclear paraspeckle formation. It was [...] Read more.
The long noncoding RNA NEAT1 is known to be heavily dysregulated in many cancers. A single exon gene produces two isoforms, NEAT1_1 and NEAT1_2, through alternative 3′-end processing. As the longer isoform, NEAT1_2 is an essential scaffold for nuclear paraspeckle formation. It was previously thought that the short NEAT1_1 isoform only exists to keep the NEAT1 locus active for rapid paraspeckle formation. However, a recent glycolysis-enhancing function for NEAT1_1, contributing to cancer cell proliferation and the Warburg effect, has been demonstrated. Previous studies have mainly focused on quantifying total NEAT1 and NEAT1_2 expression levels. However, in light of the NEAT1_1 role in cancer cell metabolism, the contribution from specific NEAT1 isoforms is no longer clear. Here, the roles of NEAT1_1 and NEAT1_2 in metabolism and cancer progression are discussed. Full article
(This article belongs to the Topic Cancer Cell Metabolism)
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<p>The <span class="html-italic">NEAT1</span> gene gives rise to two isoforms with identical 5′ sequences. The paraspeckle-independent <span class="html-italic">NEAT1_1</span> undergoes canonical 3′ polyadenylation whilst the blocking of 3′ polyadenylation via competitive binding of hnRNPK to the CFIm complex yields the paraspeckle-essential <span class="html-italic">NEAT1_2</span>. The recruitment of paraspeckle proteins to the hydrophilic and hydrophobic regions of <span class="html-italic">NEAT1_2</span> leads to phase-separated paraspeckles.</p>
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<p>Nucleocytoplasmic transport of <span class="html-italic">NEAT1_1</span> enhances the Warburg effect via the binding to glycolytic enzymes. TDP-43, ARS2, and CFIm promote the canonical 3′ polyadenylation of <span class="html-italic">NEAT1_1,</span> which can then bind to pinin for nuclear export to the cytoplasm. Once in the cytoplasm, <span class="html-italic">NEAT1_1</span> can bind with the glycolytic enzymes PGK1 (<b>A</b>), PGAM1 (<b>B</b>), and ENO1 (<b>C</b>) to enhance glycolytic flux, and hence the Warberg effect, in transformed cells.</p>
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20 pages, 1235 KiB  
Review
Molecular Interactions of the Long Noncoding RNA NEAT1 in Cancer
by Jingtao Gu, Bo Zhang, Rui An, Weikun Qian, Liang Han, Wanxing Duan, Zheng Wang and Qingyong Ma
Cancers 2022, 14(16), 4009; https://doi.org/10.3390/cancers14164009 - 19 Aug 2022
Cited by 23 | Viewed by 3945
Abstract
As one of the best-studied long noncoding RNAs, nuclear paraspeckle assembly transcript 1 (NEAT1) plays a pivotal role in the progression of cancers. NEAT1, especially its isoform NEAT1-1, facilitates the growth and metastasis of various cancers, excluding acute promyelocytic leukemia. NEAT1 can be [...] Read more.
As one of the best-studied long noncoding RNAs, nuclear paraspeckle assembly transcript 1 (NEAT1) plays a pivotal role in the progression of cancers. NEAT1, especially its isoform NEAT1-1, facilitates the growth and metastasis of various cancers, excluding acute promyelocytic leukemia. NEAT1 can be elevated via transcriptional activation or stability alteration in cancers changing the aggressive phenotype of cancer cells. NEAT1 can also be secreted from other cells and be delivered to cancer cells through exosomes. Hence, elucidating the molecular interaction of NEAT1 may shed light on the future treatment of cancer. Herein, we review the molecular function of NEAT1 in cancer progression, and explain how NEAT1 interacts with RNAs, proteins, and DNA promoter regions to upregulate tumorigenic factors. Full article
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Figure 1
<p>Classification of lncRNAs and structure of NEAT1: (<b>A</b>) LncRNAs can be categorized as enhancer lncRNAs, promoter upstream transcripts (PROMPTs), exon or intron sense-overlapping lncRNAs, long intergenic ncRNAs (lincRNAs), bidirectional lncRNAs, and natural antisense transcripts (NATs); (<b>B</b>) Locations of NEAT1-1, NEAT1-2, and Pre-miR-612 at the MEN locus; (<b>C</b>) Cross-sectional structure of paraspeckles.</p>
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<p>Function and Signaling Pathways of NEAT1. NEAT1 can recruit enzymes and TFs to the genome locus. NEAT1 can also sponge miRs and relocate enzymes and SFPQ to suppress the function of these molecules. In addition, NEAT1 can form a scaffold bridge between different TFs, which allows the enzymes to bind more tightly to the substrates.</p>
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<p>Regulation of NEAT1 at transcriptional level (<b>A</b>) and posttranslational level (<b>B</b>). (<b>A</b>) After being regulated by transcriptional activator or repressor, NEAT1 can also be stabilized or destabilized by some proteins. (<b>B</b>) When the polyadenylation (APA) of NEAT1-1 is activated, the transcription site cannot cross the end of NEAT1-1. Consequently, the expression level of NEAT1-1 will be elevated, and the generation of NEAT1-2 will be inhibited. In addition, PYBP3 can inhibit the cleaving of NEAT1-2 to reduce the generation of miR-612, thereby promoting cancer progression.</p>
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19 pages, 2467 KiB  
Article
The Interplay of NEAT1 and miR-339-5p Influences on Mesangial Gene Expression and Function in Various Diabetic-Associated Injury Models
by Simone Reichelt-Wurm, Matthias Pregler, Tobias Wirtz, Markus Kretz, Kathrin Holler, Bernhard Banas and Miriam C. Banas
Non-Coding RNA 2022, 8(4), 52; https://doi.org/10.3390/ncrna8040052 - 13 Jul 2022
Cited by 5 | Viewed by 3250
Abstract
Mesangial cells (MCs), substantial cells for architecture and function of the glomerular tuft, take a key role in progression of diabetic kidney disease (DKD). Despite long standing researches and the need for novel therapies, the underlying regulatory mechanisms in MCs are elusive. This [...] Read more.
Mesangial cells (MCs), substantial cells for architecture and function of the glomerular tuft, take a key role in progression of diabetic kidney disease (DKD). Despite long standing researches and the need for novel therapies, the underlying regulatory mechanisms in MCs are elusive. This applies in particular to long non-coding RNAs (lncRNA) but also microRNAs (miRNAs). In this study, we investigated the expression of nuclear paraspeckle assembly transcript 1 (NEAT1), a highly conserved lncRNA, in several diabetes in-vitro models using human MCs. These cells were treated with high glucose, TGFβ, TNAα, thapsigargin, or tunicamycin. We analyzed the implication of NEAT1 silencing on mesangial cell migration, proliferation, and cell size as well as on mRNA and miRNA expression. Here, the miRNA hsa-miR-339-5p was not only identified as a potential interaction partner for NEAT1 but also for several coding genes. Furthermore, overexpression of hsa-miR-339-5p leads to a MC phenotype comparable to a NEAT1 knockdown. In-silico analyses also underline a relevant role of NEAT1 and hsa-miR-339-5p in mesangial physiology, especially in the context of DKD. Full article
(This article belongs to the Section Computational Biology)
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<p><span class="html-italic">NEAT1_1</span>/2 expression in human mesangial cell (hMCs) under basal conditions and after stimulation. (<b>A</b>) In-situ detection of <span class="html-italic">NEAT1_1/2</span> (green) in untreated cultured hMCs. The nuclei are stained blue by DAPI. The scale bar indicates 5 µm. (<b>B</b>–<b>F</b>) Fold change of <span class="html-italic">NEAT1_1/2</span> (grey bars) expression in hMCs after stimulation with (<b>B</b>) 30 mM glucose normalized to mannitol, (<b>C</b>) TGFβ1 normalized to medium, (<b>D</b>) TNFα normalized to medium, (<b>E</b>) thapsigargin normalized to DMSO, and (<b>F</b>) tunicamycin normalized to DMSO. Bars represent x-fold changes + SD. Overall significance of differences was analyzed by ANOVA, followed by Student’s <span class="html-italic">t</span>-tests for post hoc pairwise comparisons. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.001 compared to corresponding control treatment; <span class="html-italic">n</span> = 3–4.</p>
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<p><span class="html-italic">NEAT1</span> silencing in human mesangial cells (hMCs) using siPools targeting both <span class="html-italic">NEAT1_1</span> and <span class="html-italic">NEAT1_2</span>. (<b>A</b>) Efficiencies of <span class="html-italic">NEAT1</span> knockdown (KD<span class="html-italic"><sub>NEAT1</sub></span>) after 24 or 48 h shown as x-fold changes + SD for <span class="html-italic">NEAT1_1</span> (black bars) and <span class="html-italic">NEAT1_2</span> (grey bars) RNA expression normalized to the expression after treatment with scrambled negative control (NC<span class="html-italic"><sub>NEAT1</sub></span>) siRNA; <span class="html-italic">n</span> = 3. (<b>B</b>) In-situ detection of <span class="html-italic">NEAT1_1/2</span> (green) in NC<span class="html-italic"><sub>NEAT1</sub></span> and KD<span class="html-italic"><sub>NEAT1</sub></span> treated hMCs. The nuclei are stained blue by DAPI. The scale bar indicates 5 µm. (<b>C</b>) Cell migration was analyzed by wound healing assay by measuring the gap width, directly after removing the cell culture insert (0 h) and 4 h, 8 h, and 12 h later. Black circles ± SD or grey triangles ± SD represent NC<span class="html-italic"><sub>NEAT1</sub></span> and KD<span class="html-italic"><sub>NEAT1</sub></span> treated hMCs, respectively; <span class="html-italic">n</span> = 3. (<b>D</b>) Proliferation rate of hMCs after KD<span class="html-italic"><sub>NEAT1</sub></span> (grey bar + SD) compared to NC<span class="html-italic"><sub>NEAT1</sub></span> (black bar). Proliferation was ascertained by a BrdU assay; <span class="html-italic">n</span> = 5. (<b>E</b>) Cell size in µm<sup>2</sup> of hMCs after KD<span class="html-italic"><sub>NEAT1</sub></span> (grey bar + SD) compared to NC<span class="html-italic"><sub>NEAT1</sub></span> (black bar + SD). Cell size measurement based on WGA immunostaining followed by morphometric analyses; <span class="html-italic">n</span> = 3. Overall significance of differences was analyzed by ANOVA, followed by Student’s <span class="html-italic">t</span>-tests for post hoc pairwise comparisons. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Analysis of differentially expressed coding genes (DECGs) in human mesangial cells (hMCs) after <span class="html-italic">NEAT1</span> silencing compared to negative control siRNA treated cells. (<b>A</b>) The Venn diagram depicts the number of DECGs 24 h (left) and 48 h (right) after the <span class="html-italic">NEAT1</span> knockdown in hMCs. The overlapping region between both circles represents genes which were differentially expressed at both times. The encircled value corresponds to the total number of DECGs, and the cyphers in the yellow or blue arrow represent the number of up- and downregulated DECGs, respectively; <span class="html-italic">n</span> = 3. (<b>B</b>–<b>D</b>) Validation of selected DECGs found in the microarray via qPCR, with (<b>B</b>) DECGs (<span class="html-italic">CDKN1A</span> and TGFb2) after 24 h, (<b>C</b>) DECGs (<span class="html-italic">CDK6</span> and <span class="html-italic">GNG4</span>) after 48 h, and (<b>D</b>) DECGs (<span class="html-italic">CTGF</span> and <span class="html-italic">CCND1</span>) after 24 h and 48 h. Black bars + SD show x-fold changes of gene expression in microarray (normalized to internal controls), grey bars + SD show x-fold changes of gene expression validated by qPCR (normalized to peptidylprolyl isomerase B); * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.001; <span class="html-italic">n</span> = 3–4. (<b>E</b>–<b>I</b>) In-silico enrichment analyses based on all DECGs detected by microarray analysis. Illustrations show selected significantly enriched terms (<span class="html-italic">p</span> &lt; 0.05; EASE score &lt; 0.05), which are relevant for mesangial physiology, sorted by count of DECGs. The complete list is shown in the <a href="#app1-ncrna-08-00052" class="html-app">Supplement</a>. (<b>E</b>) Functional enrichment analysis in terms of selected Genetic Association Database (GAD) diseases. (<b>F</b>–<b>H</b>) Functional enrichment analysis in terms of Gene Ontology (<b>GO</b>) with the aspects (<b>F</b>) Biological Processes (BP), (<b>G</b>) Cellular Component (CC), and (<b>H</b>) Molecular Function (MF). (<b>I</b>) Functional enrichment analysis in terms of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Abbreviations: HDL: high density lipoprotein; SMC: smooth muscle cell; ER: endoplasmic reticulum; bind.: binding.</p>
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<p>Analysis of differentially expressed miRNAs (DEmiRNAs) in human mesangial cells (hMCs) after <span class="html-italic">NEAT1</span> silencing compared to negative control siRNA treated cells. (<b>A</b>) The Venn diagram indicates the number of DEmiRNAs 24 h (left) and 48 h (right) after the second <span class="html-italic">NEAT1</span> knockdown in hMCs. The overlapping region between both circles represents miRNAs, which were differentially expressed at both times. The encircled value corresponds to the total number of DEmiRNAs, and the ciphers in the yellow or blue arrow represent the number of up- and downregulated DEmiRNAs, respectively; <span class="html-italic">n</span> = 3. (<b>B</b>) Validation of selected DEmiRNAs (miR-331-3p, miR-339-5p, miR-450b-5p) found in the microarray via qPCR. Black bars + SD show x-fold changes of gene expression in microarray (normalized to internal controls), grey bars + SD show x-fold changes of gene expression validated by qPCR (normalized to hsa-5S-rRNA); * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.001; n.s.: not significant; <span class="html-italic">n</span> = 3. (<b>C</b>,<b>D</b>) In-silico enrichment analyses based on DEmiRNAs, using DECGs detected by the microarray as filter. Illustrations show selected significantly enriched terms (<span class="html-italic">p</span> &lt; 0.05; EASE score &lt; 0.05), which are relevant for mesangial physiology, sorted by count. The complete list is shown in the <a href="#app1-ncrna-08-00052" class="html-app">Supplement</a>. (<b>C</b>) Functional enrichment analysis in terms of Gene Ontology (GO) Biological Processes (BP). (<b>D</b>) Functional enrichment analysis in terms of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Abbreviations: TGFb: transforming growth factor b; SMC: smooth muscle cell; PI3K-Akt: phosphatidylinositol 3-kinase—protein kinase B; FOXO: forkhead box O.</p>
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<p>Functional enrichment analysis of differentially expressed coding genes (DECGs) in human mesangial cells (hMCs) with predicted miR-339-5p targeting site. Significant enriched terms in respect of (<b>A</b>) Genetic Association Database (GAD) diseases (the complete list is shown in the <a href="#app1-ncrna-08-00052" class="html-app">Supplement</a>), as well as (<b>B</b>) Molecular Function (MF). (<b>C</b>) Functional enrichment analysis in terms of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Abbreviation: HIF: hypoxia induced factor. Selected significant terms (according to DAVID integrated algorithms) are sorted by count. Additionally, significance regarding actual over-representation of a particular term was analyzed by hypergeometric testing. * <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; n.s. = not significant. (<b>D</b>) Predicted miR-399-5p targeting sites for <span class="html-italic">NEAT1_1/2</span> indicated by grey and black arrows. Loci marked with black arrows were analyzed via luciferase reporter gene assays. Information and result for the site with the framed black arrow are shown in (<b>E</b>,<b>F</b>) in this figure. (<b>E</b>) Potential interaction site of miR-339-5p and <span class="html-italic">NEAT1</span>. The sequences of miR-339-5p, wildtype (WT) <span class="html-italic">NEAT1</span> and designed mutated (MUT) <span class="html-italic">NEAT1</span> are shown. (<b>F</b>) Dual-luciferase reporter assay in hMCs showing the effect of miR-339-5p cotransfected with pmirGlo vector containing either WT or MUT <span class="html-italic">NEAT1</span> sequence, displayed by black bar + SD or grey bars + SD, respectively, <span class="html-italic">n</span> = 3–4. DECG (grey bars). Significance was analyzed by Student’s <span class="html-italic">t</span>-test. * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Effects of miR-399-5p overexpression (OE<sub>miR339-5p</sub>) on human mesangial cells (hMCs) using miR-339-5p mimics. (<b>A</b>) Reduced expression of <span class="html-italic">NEAT1_1/2</span> after OE<sub>miR339-5p</sub> was detected after 24 or 48 h, shown as x-fold changes + SD for <span class="html-italic">NEAT1_1</span> (black bars + SD) and <span class="html-italic">NEAT1_2</span> (grey bars + SD), normalized to the expression after treatment with negative control RNA (NC<sub>miR339-5p</sub>); <span class="html-italic">n</span> = 4. (<b>B</b>) Cell migration was analyzed by wound healing assay by measuring the gap width, directly after removing the cell culture insert (0 h) and 4 h, 8 h, 12 h, and 24 h later. Black circles ± SD or grey triangles ± SD represent hMCs subjected to NC<sub>miR339-5p</sub> and OE<sub>miR339-5p</sub>, respectively; <span class="html-italic">n</span> = 4. (<b>C</b>) Proliferation rate of hMCs after OE<sub>miR339-5p</sub> (grey bar + SD) compared to NC<sub>miR339-5p</sub> treated cells (black bar + SD). Proliferation was ascertained by a BrdU assay; <span class="html-italic">n</span> = 4. (<b>D</b>) Cell size in µm<sup>2</sup> of hMCs after OE<sub>miR339-5p</sub> (grey bar + SD) compared to NC<sub>miR339-5p</sub> treated cells (black bar+ SD). Cell size measurement based on WGA immunostaining followed by morphometric analyses; <span class="html-italic">n</span> = 3. (<b>E</b>) x-fold change of mRNA expression of selecteup- or downregulated differentially expressed coding genes with predicted miR-339-5p binding site after KD<span class="html-italic"><sub>NEAT1</sub></span> (black bars + SD) and OE<sub>miR339-5p</sub> (grey bars + SD), respectively, compared to the corresponding NC<span class="html-italic"><sub>NEAT1</sub></span> or NC<sub>miR339-5p</sub>, <span class="html-italic">n</span> = 3–4. (<b>F</b>) x-fold change of mRNA expression of selecteup- or downregulated differentially expressed coding genes without predicted miR-339-5p binding site after KD<span class="html-italic"><sub>NEAT1</sub></span> (black bars + SD) and OE<sub>miR339-5p</sub> (grey bars + SD) compared to the corresponding NC<span class="html-italic"><sub>NEAT1</sub></span> or NC<sub>miR339-5p</sub>, <span class="html-italic">n</span> = 3–4. Significance was analyzed by Student’s <span class="html-italic">t</span>-tests. * <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; n.s. = not significant.</p>
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13 pages, 4941 KiB  
Article
Molecular Modelling of NONO and SFPQ Dimerization Process and RNA Recognition Mechanism
by Tommaso Laurenzi, Luca Palazzolo, Elisa Taiana, Simona Saporiti, Omar Ben Mariem, Uliano Guerrini, Antonino Neri and Ivano Eberini
Int. J. Mol. Sci. 2022, 23(14), 7626; https://doi.org/10.3390/ijms23147626 - 10 Jul 2022
Cited by 7 | Viewed by 2653
Abstract
NONO and SFPQ are involved in multiple nuclear processes (e.g., pre-mRNA splicing, DNA repair, and transcriptional regulation). These proteins, along with NEAT1, enable paraspeckle formation, thus promoting multiple myeloma cell survival. In this paper, we investigate NONO and SFPQ dimer stability, highlighting the [...] Read more.
NONO and SFPQ are involved in multiple nuclear processes (e.g., pre-mRNA splicing, DNA repair, and transcriptional regulation). These proteins, along with NEAT1, enable paraspeckle formation, thus promoting multiple myeloma cell survival. In this paper, we investigate NONO and SFPQ dimer stability, highlighting the hetero- and homodimer structural differences, and model their interactions with RNA, simulating their binding to a polyG probe mimicking NEAT1guanine-rich regions. We demonstrated in silico that NONO::SFPQ heterodimerization is a more favorable process than homodimer formation. We also show that NONO and SFPQ RRM2 subunits are primarily required for protein–protein interactions with the other DBHS protomer. Simulation of RNA binding to NONO and SFPQ, beside validating RRM1 RNP signature importance, highlighted the role of β2 and β4 strand residues for RNA specific recognition. Moreover, we demonstrated the role of the NOPS region and other protomer’s RRM2 β2/β3 loop in strengthening the interaction with RNA. Our results, having deepened RNA and DBHS dimer interactions, could contribute to the design of small molecules to modulate the activity of these proteins. RNA-mimetics, able to selectively bind to NONO and/or SFPQ RNA-recognition site, could impair paraspeckle formation, thus representing a first step towards the discovery of drugs for multiple myeloma treatment. Full article
(This article belongs to the Section Molecular Biophysics)
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Figure 1
<p>NONO and SFPQ dimers are highly stable. Through MD, we assessed NONO and SFPQ dimers stability. (<b>a</b>) RMSD converges to a stable plateau of 2.5 Å within 1 µs for all systems. RMSD is reported for dimers (top) and individual chains of NONO (middle) and SFPQ (bottom). (<b>b</b>) RMSF is reported for individual chains in all dimer combinations; mobile regions overlap in all systems, with higher fluctuations at the N- and C-termini and NOPS region. (<b>c</b>) Secondary structure % over simulation time: ɑ helix (top), β strands (bottom). (<b>d</b>,<b>e</b>) NOPS helix in NONO and SFPQ superposed structures: homodimer (yellow and green), heterodimer (blue). (<b>f</b>) SFPQ homo- (yellow) and heterodimer (blue) interaction between RRM2 β2/β3 loop and NOPS.</p>
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<p>MD polar interactions. NONO::NONO (red), SFPQ::SFPQ (green), NONO::SFPQ (blue). Total number of polar interactions and their fluctuations was stable in all systems. The NONO::SFPQ heterodimer displayed a smaller count of total hydrogen bonds, compared to the other systems.</p>
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<p>The NONO::SFPQ heterodimer formation is thermodynamically favored, when compared to NONO and SFPQ homodimers. Decomposition of interaction energies: protein internal energy, protein::solvent interaction, protein::protein interaction. Zoomed pane is dimer formation energy. Energy values are averaged over the stable last 50% of MD trajectories, error bars represent the standard deviation.</p>
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<p>Comparison of MD interactions, single-point interaction energies, and alanine scan delta affinity. Time-persistence of hydrogen bonds, salt bridges, and pi–pi and pi–cation interactions was measured along MD trajectories, as a fraction of the simulation time. Single-point energy contributions and alanine scan delta affinity were computed on the MD medoids. The three complementary methodologies highlight the key residues responsible for inter-chain protein::protein interactions.</p>
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<p>Molecular dynamics interactions network. (<b>a</b>) Beta-clasp interactions between N-termini in NONO::NONO. (<b>b</b>) Backbone-to-backbone interactions between RRM1s helix 2. (<b>c</b>) RRM2-NOPS interactions. (<b>d</b>) RRM2 and NOPS interactions with coiled-coil. (<b>e</b>) Coil-coil interactions. Cartoon colors: RRM1 (blue), RRM2 (pink), NOPS (light blue), coiled-coil (yellow). Interaction tube colors: NONO::SFPQ (red), NONO::NONO (cyan), SFPQ::SFPQ (magenta).</p>
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<p>Stability of DBHS::polyG dimers during MD simulation. RMSD was calculated on polyG atoms after fitting each frame to the solute ɑ-carbons.</p>
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<p>DBHS::polyG MD interactions. (<b>a</b>) Comparison of DBHS::polyG binding modes: NONO-bound (green), SFPQ-bound (yellow). (<b>b</b>) Representative binding mode of SFPQ bound to polyG in NONO::SFPQ, which has the most stable configuration; interacting residues are represented with blue sticks; polyG (yellow). (<b>c</b>) Interaction existence over simulation time: most DBHS::polyG interactions happen within RRM1s; however, the other chain β2/β3 loop can assist with RNA binding. Sequence ordering: NONO bound to polyG in N::N (1) and N::S (2); NONO unbound in N::N (3) and N::S (4); SFPQ bound to polyG in S::S (5) and N::S (6); SFPQ unbound in S::S (7) and N::S (8).</p>
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20 pages, 2696 KiB  
Review
Regulation of Cellular Ribonucleoprotein Granules: From Assembly to Degradation via Post-translational Modification
by Pureum Jeon, Hyun-Ji Ham, Semin Park and Jin-A Lee
Cells 2022, 11(13), 2063; https://doi.org/10.3390/cells11132063 - 29 Jun 2022
Cited by 13 | Viewed by 4792
Abstract
Cells possess membraneless ribonucleoprotein (RNP) granules, including stress granules, processing bodies, Cajal bodies, or paraspeckles, that play physiological or pathological roles. RNP granules contain RNA and numerous RNA-binding proteins, transiently formed through the liquid–liquid phase separation. The assembly or disassembly of numerous RNP [...] Read more.
Cells possess membraneless ribonucleoprotein (RNP) granules, including stress granules, processing bodies, Cajal bodies, or paraspeckles, that play physiological or pathological roles. RNP granules contain RNA and numerous RNA-binding proteins, transiently formed through the liquid–liquid phase separation. The assembly or disassembly of numerous RNP granules is strongly controlled to maintain their homeostasis and perform their cellular functions properly. Normal RNA granules are reversibly assembled, whereas abnormal RNP granules accumulate and associate with various neurodegenerative diseases. This review summarizes current studies on the physiological or pathological roles of post-translational modifications of various cellular RNP granules and discusses the therapeutic methods in curing diseases related to abnormal RNP granules by autophagy. Full article
(This article belongs to the Special Issue The Autophagic Process in Human Physiology and Pathogenesis)
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Figure 1
<p>Cellular ribonucleoprotein (RNP) granules. (<b>a</b>,<b>b</b>) Schematic structural representation of cytoplasmic RNP granules. (<b>a</b>) Stress granules (SGs) containing untranslated mRNA, ribosomes, translational initiation factors, and RBPs. (<b>b</b>) P-bodies containing untranslated mRNAs and RBPs. (c and d) Schematic structure of nuclear RNP granules. (<b>c</b>) Paraspeckles containing lncRNA NEAT1 and nuclear-localized RBPs. (<b>d</b>) Cajal bodies containing snRNPs, snoRNPs, and nuclear RNPs.</p>
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<p>Physiological/pathological RNP granules regulated by PTMs. (<b>a</b>) Physiological RNP granules composed of proteins modified by PTMs, such as arginine methylation, phosphorylation, acetylation, ubiquitination, and glycosylation. PTMs can regulate RNP granule dynamics by affecting the interaction strength between proteins and nucleic acids. (<b>b</b>) RNP-binding proteins linked to neurodegenerative diseases can be modified by phosphorylation, acetylation, or PARylation (<a href="#cells-11-02063-f003" class="html-fig">Figure 3</a>), altering the biophysical properties. Accumulation of aggregates associated with altered RNP granules in neurons is a hallmark of several neurodegenerative diseases. (<b>c</b>) Abnormal RNP granules and aggregates can be degraded by granulophagy.</p>
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<p>PTMs on pathological RNP granules. (<b>a</b>) Increased aggregation property by PTMs on RBPs: phosphorylation of tau [<a href="#B114-cells-11-02063" class="html-bibr">114</a>] or TDP-43 [<a href="#B121-cells-11-02063" class="html-bibr">121</a>], acetylation of TDP-43 [<a href="#B122-cells-11-02063" class="html-bibr">122</a>], PARylation of TDP-43, or hnRNPA1 [<a href="#B103-cells-11-02063" class="html-bibr">103</a>] accelerate the solid transition. (<b>b</b>) Decreased aggregation property by PTMs on RBPs: methylation [<a href="#B85-cells-11-02063" class="html-bibr">85</a>,<a href="#B116-cells-11-02063" class="html-bibr">116</a>], phosphorylation [<a href="#B119-cells-11-02063" class="html-bibr">119</a>], or acetylation [<a href="#B120-cells-11-02063" class="html-bibr">120</a>] of FUS; phosphorylation [<a href="#B117-cells-11-02063" class="html-bibr">117</a>,<a href="#B118-cells-11-02063" class="html-bibr">118</a>,<a href="#B122-cells-11-02063" class="html-bibr">122</a>], or acetylation of tau [<a href="#B115-cells-11-02063" class="html-bibr">115</a>] prevent the phase to solid transition.</p>
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