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20 pages, 4631 KiB  
Article
Global Transcriptomic Analysis of Inbred Lines Reveal Candidate Genes for Response to Maize Lethal Necrosis
by Ann Murithi, Gayathri Panangipalli, Zhengyu Wen, Michael S. Olsen, Thomas Lübberstedt, Kanwarpal S. Dhugga and Mark Jung
Plants 2025, 14(2), 295; https://doi.org/10.3390/plants14020295 - 20 Jan 2025
Viewed by 400
Abstract
Maize lethal necrosis (MLN) is a significant threat to food security in Sub-Saharan Africa (SSA), with limited commercial inbred lines displaying tolerance. This study analyzed the transcriptomes of four commercially used maize inbred lines and a non-adapted inbred line, all with varying response [...] Read more.
Maize lethal necrosis (MLN) is a significant threat to food security in Sub-Saharan Africa (SSA), with limited commercial inbred lines displaying tolerance. This study analyzed the transcriptomes of four commercially used maize inbred lines and a non-adapted inbred line, all with varying response levels to MLN. RNA-Seq revealed differentially expressed genes in response to infection by maize chlorotic mottle virus (MCMV) and sugarcane mosaic virus (SCMV), the causative agents of MLN. Key findings included the identification of components of the plant innate immune system, such as differentially regulated R genes (mainly LRRs), and activation/deactivation of virus resistance pathways, including RNA interference (RNAi) via Argonaute (AGO), Dicer-like proteins, and the ubiquitin–proteasome system (UPS) via RING/U-box and ubiquitin ligases. Genes associated with redox signaling, WRKY transcription factors, and cell modification were also differentially expressed. Additionally, the expression of translation initiation and elongation factors, eIF4E and eIF4G, correlated with the presence of MLN viruses. These findings provide valuable insights into the molecular mechanisms of MLN resistance and highlight potential gene candidates for engineering or selecting MLN-resistant maize germplasm for SSA. Full article
(This article belongs to the Special Issue Crop Functional Genomics and Biological Breeding)
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<p>Phenotypic effect of MLN. Average field MLN phenotypic scores of five lines collected in Naivasha, Kenya.</p>
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<p>Heatmap clustering of 2503 differentially expressed genes based on their normalized counts. Each row of the heatmap represents the gene count in each genotype before and after inoculation. Red indicates high counts of a gene in a biological replicate, while green indicates lower counts of a gene. “Null” indicates the expression before inoculation, and “treated” indicates expression after MLN inoculation.</p>
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<p>Principal component analysis: Plot generated from normalized gene expression counts of each genotype under MLN.</p>
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<p>Differentially expressed genes (DEGs). (<b>A</b>) Venn diagram of the DEGs in five lines under MLN stress, (<b>B</b>) Venn diagram of the DEGs in CIMMYT lines, and (<b>C</b>) Venn diagram of the DEGs of the genotype vs. genotype comparison.</p>
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<p>Gene Ontology (GO) enrichment of differentially expressed genes (DEGs) after MLN. A Fisher’s exact test and Bonferroni correction were used to identify the significantly (<span class="html-italic">p</span>-value &lt; 0.05) enriched GO terms from the total DEGs across the CIMMYT lines relative to all genes in the maize genome. The first group represents enriched GO terms in each genotype, while the second group represents GO enrichment after contrasting expressions between the lines. The <span class="html-italic">Y</span>-axis represents the DEGs’ biological functions, biological process (green), molecular function (orange), and cellular component (purple). The <span class="html-italic">X</span>-axis represents the positive values of the estimated <span class="html-italic">p</span>-values, calculated as −log10(<span class="html-italic">p</span>-value) via GO term analysis.</p>
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<p>Gene Ontology (GO) and KEGG enrichment of DEGs in KS23-6. Column (<b>A</b>) shows the GO terms and KEGG of DEGs in KS23-6 after comparing the control vs. treatment groups, and column (<b>B</b>) shows GO terms and KEGG pathways after comparing KS23-6 DEGs to CML543 and CML536. In both, a Fisher’s exact test and Bonferroni correction were used to identify the significantly (<span class="html-italic">p</span>-value &lt; 0.05) enriched GO terms and KEGG pathways. In the GO term bar charts, the <span class="html-italic">Y</span>-axis represents the DEGs’ biological process (green), molecular function (orange), and cellular component (purple), while the <span class="html-italic">X</span>-axis represents the positive values of the estimated <span class="html-italic">p</span>-values, calculated as −log10(<span class="html-italic">p</span>-value) via Go term analysis.</p>
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<p>Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. A Fisher’s exact test and Bonferroni correction were used to identify the significantly (<span class="html-italic">p</span>-value &lt; 0.05) enriched KEGG terms from the total DEGs. The first group represents enriched GO terms in each genotype, while the second group represents GO enrichment after contrasting expressions between the lines. The <span class="html-italic">Y</span>-axis represents the KEGG terms. The <span class="html-italic">X</span>-axis represents the positive values of the estimated <span class="html-italic">p</span>-values, calculated as −log10(<span class="html-italic">p</span>-value).</p>
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<p>Differential expression of eukaryotic translation initiation factors (eIF4) across the genotypes based on the log2foldchange. The <span class="html-italic">x</span>-axis represents the genotypes. The <span class="html-italic">Y</span>-axis represents the expression value of each gene within a genotype based on the log2foldchange. (The numbers after the underscores indicate the chromosome locations).</p>
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22 pages, 4614 KiB  
Review
DICER1: The Argonaute Endonuclease Family Member and Its Role in Pediatric and Youth Pathology
by Consolato M. Sergi and Fabrizio Minervini
Biology 2025, 14(1), 93; https://doi.org/10.3390/biology14010093 - 18 Jan 2025
Viewed by 315
Abstract
In 2001, two enzyme-encoding genes were recognized in the fruit fly Drosophila melanogaster. The genetic material, labeled Dicer-1 and Dicer-2, encodes ribonuclease-type enzymes with slightly diverse target substrates. The human orthologue is DICER1. It is a gene, which has been [...] Read more.
In 2001, two enzyme-encoding genes were recognized in the fruit fly Drosophila melanogaster. The genetic material, labeled Dicer-1 and Dicer-2, encodes ribonuclease-type enzymes with slightly diverse target substrates. The human orthologue is DICER1. It is a gene, which has been positioned on chromosome 14q32.13. It contains 27 exons, which are linking the two enzyme domains. DICER1 is found in all organ systems. It has been proved that it is paramount in human development. The protein determined by DICER1 is a ribonuclease (RNase). This RNase belongs to the RNase III superfamily, formally known as ’endoribonuclease’. It has been determined that the function of RNase III proteins is set to identify and degrade double-stranded molecules of RNA. DICER1 is a vital “housekeeping” gene. The multi-domain enzyme is key for small RNA processing. This enzyme functions in numerous pathways, including RNA interference paths, DNA damage renovation, and response to viruses. At the protein level, DICER is also involved in several human diseases, of which the pleuro-pulmonary blastoma is probably the most egregious entity. Numerous studies have determined the full range of DICER1 functions and the corresponding relationship to tumorigenic and non-neoplastic diseases. In fact, genetic mutations (somatic and germline) have been detected in DICER1 and are genetically associated with at least two clinical syndromes: DICER1 syndrome and GLOW syndrome. The ubiquity of this enzyme in the human body makes it an exquisite target for nanotechnology-supported therapies and repurposing drug approaches. Full article
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<p>RNAi. RNA interference (RNAi), also known as PTGS or Post-Transcriptional Gene Silencing (PTGS) or Genetic Perturbation Platform, is a preserved biological mechanism that responds to dsRNA or double-stranded RNA, enabling resistance to both parasite of endogenous origin and exogenous harmful nucleic acids, while regulating the expression of genes, which codify proteins. This innate process for sequence-explicit gene silencing has the potential to transform experimental biology. It may have significant applications in genomics and functional genomics, as well as therapeutic intervention and other fields. Endogenous activators of the RNAi path including foreign DNA or dsRNA of viral origin, inconsistent transcripts from repeating genomic sequences (e.g., transposons), and pre-miRNA (miRNA, microRNA). In plants, RNAi underpins virus-induced gene silencing (VIGS), indicating a significant role in disease resistance. Investigations on <span class="html-italic">C. elegans</span> (<span class="html-italic">Caenorhabditis elegans</span>) has proposed a potential method for the control of endogenous genes by the RNAi machinery. In mammalian cells, large double-stranded RNAs (&gt;30 nt) typically elicit an interferon response. A streamlined model for the RNAi process consists of two stages. Both stages involve a ribonuclease enzyme. The first step is for the RNase II enzymes Dicer and Drosha to transform the trigger RNA (which could be dsRNA or miRNA primary transcript) into short interference RNA (siRNA). The RNA-induced silencing complex (RISC) is an effector complex that incorporates siRNAs in the following step. As the RISC is assembled, the siRNA is unwound, allowing the single-stranded RNA to hybridize with the mRNA target. Argonaute, an RNase H enzyme, destroys the target mRNA, resulting in gene silencing (Slicer). The messenger RNA stays uncleaved if the siRNA/mRNA duplex displays mismatches. When translational inhibition occurs, genes are silenced. This illustration depicting RNA interference was adapted from the NCBI website: RNA Interference (RNAi) [<a href="#B4-biology-14-00093" class="html-bibr">4</a>,<a href="#B5-biology-14-00093" class="html-bibr">5</a>,<a href="#B6-biology-14-00093" class="html-bibr">6</a>,<a href="#B7-biology-14-00093" class="html-bibr">7</a>,<a href="#B8-biology-14-00093" class="html-bibr">8</a>,<a href="#B9-biology-14-00093" class="html-bibr">9</a>]. Functional studies of the mammalian genome can show how genetic changes cause changes in phenotype, and the Genetic Perturbation Platform (GPP), formerly known as the RNA interference (RNAi) Platform, supports these investigations.</p>
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<p>Various dsRNA. Schematic depiction of the characteristics and origins of various dsRNA substrates. There are two possible sources for genomic transcripts that produce double-stranded RNA (dsRNA): repeated transcripts in pathways that maintain genome integrity and genetic sequences in pathways that control gene expression (adapted from an Open Access source: Zapletal D, Kubicek K, Svoboda P, Stefl R. Dicer structure and function: conserved and evolving features. EMBO Rep. 2023 Jul 5;24(7):e57215. doi:10.15252/embr.202357215. Epub 2023 Jun 13. PMID: 37310138; PMCID: PMC10328071) [<a href="#B3-biology-14-00093" class="html-bibr">3</a>].</p>
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<p>Substrate Cleaning. There are two ways to clean the substrate. During its processive mode, Dicer “feeds” its substrate by slicing lengthy dsRNA molecules in a series of sequential steps that are powered by the helicase domain’s ATP activity. Dicer attaches a new substrate after performing a single cleavage when in distributive mode (adapted from an Open Access source: Zapletal D, Kubicek K, Svoboda P, Stefl R. Dicer structure and function: conserved and evolving features. EMBO Rep. 2023 Jul 5;24(7):e57215. doi:10.15252/embr.202357215. Epub 2023 Jun 13. PMID: 37310138; PMCID: PMC10328071) [<a href="#B3-biology-14-00093" class="html-bibr">3</a>].</p>
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<p>CT Imaging and Macroscopic View of Pleuropulmonary Blastoma. (<b>a</b>) CT scan of a 21-year-old female patient with a pleuropulomonary blastoma causing a mediastinal shift (arrow pointing to the mediastinal shift). (<b>b</b>) The figure shows the resected pleuropulmonary blastoma (arrow pointing to the bulk of the tumor) just after surgery. No copyright issue. The images come from the personal archive of Dr. F. Minervini.</p>
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<p>Microphotographs of Pleuropulmonary Blastoma. A heterogeneous solid tumor (<b>a</b>) abutting (arrow) the fibrotic pleura showing on higher magnification blastema-like area (arrow) infiltrating the soft tissue and exhibiting small-to-medium sized cells to very large cells (round, ovoid, slightly spindle) with hyperchromatic nuclei, high nucleus to cytoplasm ratio, and frequent mitotic bodies (<b>b</b>). In this case, foci of very large anaplastic cells (red arrow) with pleomorphic nuclei and mitotic figures as well as apoptotic figures (black arrow) were also observed (figure and inset). Hematoxylin and eosin staining, scale bar embedded in the microphotographs. No copyright issue. The images come from the personal archive of Dr. C. Sergi.</p>
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<p>DICER1 associated lung cysts (arrows) in an asymptomatic 22-year-old male patient. No copyright issue. The image comes from the personal archive of Dr. F. Minervini.</p>
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11 pages, 1385 KiB  
Article
Argonaute2 and Argonaute4 Involved in the Pathogenesis of Kawasaki Disease via mRNA Expression Profiles
by Zon-Min Lee, Hui-Chuan Chang, Shih-Feng Liu, Ying-Hsien Huang and Ho-Chang Kuo
Children 2025, 12(1), 73; https://doi.org/10.3390/children12010073 - 8 Jan 2025
Viewed by 417
Abstract
Background: Argonautes (AGOs) are a type of protein that degrade specific messenger RNAs, consequently reducing the expression of a specific gene. These proteins consist of small, single-stranded RNA or DNA and may provide a route for detecting and silencing complementary mobile genetic elements. [...] Read more.
Background: Argonautes (AGOs) are a type of protein that degrade specific messenger RNAs, consequently reducing the expression of a specific gene. These proteins consist of small, single-stranded RNA or DNA and may provide a route for detecting and silencing complementary mobile genetic elements. In this research, we investigated which AGO(s) were involved in Kawasaki disease (KD). Methods and Materials: We obtained mRNA-level gene expression profiles from leukocyte samples that had previously been gathered in another study and uploaded to the NCBI GEO database. The Human Transcriptome Array (HTA 2.0) analysis included 50 children with KD prior to IVIG (KD1), 18 children with KD three weeks post-IVIG (KD3), 18 non-febrile controls (HC), and 18 febrile controls (FC), which were arranged in the quoted publications for all materials and methods in order to collect data. We used the default value of the commercialized microarray tool Partek to perform an analysis of variance and determine any significant fold changes (KD1, KD3, HC, and FC individually). Results: The data revealed that the AGO2 and AGO4 genes displayed significant within-group differences with p = 0.034 and 0.007, respectively. In AGO2, significant differences were observed between KD1 vs. HC + FC with p = 0.034. KD1 appears higher than the other specimens in AGO4, with significant differences between KD1 and HC (p = 0.033), KD1 and FC (p = 0.033), KD1 and KD3 (p = 0.013), and KD1 and HC + FC (p = 0.007). We observed no substantial differences in AGO1 or AGO3 (p > 0.05). There were no significant differences between AGO(s) and coronary artery lesions or intravenous immunoglobulin resistance. (p > 0.05) Conclusion: Endothelial cell inflammation and injury, two basic pathological mechanisms, are thought to be involved in coronary endothelial dysfunction in KD. AGO2 and AGO4 are likely to participate in the endothelial dysfunction of children with KD, with AGO4 potentially playing a key role, while AGO1 and AGO3 appear not to participate. Full article
(This article belongs to the Section Pediatric Cardiology)
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<p>Flowchart of study.</p>
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<p>Expression analysis of AGO1 ((<b>A</b>): TC01000463.hg.1; (<b>B</b>): TC01000464.hg.1; and (<b>C</b>): TC01004315.hg.1), AGO2 ((<b>D</b>): TC08001684.hg.1; and ((<b>E</b>): TC08002130.hg.1), AGO3 ((<b>F</b>): TC01000465.hg.1), and AGO4 ((<b>G</b>): TC01000462.hg.1) in the leukocytes of Kawasaki disease patients and controls. HC, non-febrile (healthy) control; FC, febrile control; KD1, children with KD within 24 h before IVIG (intravenous immunoglobulin) infusion; KD3, children with KD at least three weeks post-IVIG infusion. (ANOVA, analyses of variance). * indicated <span class="html-italic">p</span> &lt; 0.05, ** indicated <span class="html-italic">p</span> &lt; 0.01.</p>
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15 pages, 2887 KiB  
Communication
Generation of Cas9 Knock-In Culex quinquefasciatus Mosquito Cells
by Elizabeth Walsh, Tran Zen B. Torres, Brian C. Prince and Claudia Rückert
DNA 2025, 5(1), 1; https://doi.org/10.3390/dna5010001 - 1 Jan 2025
Viewed by 697
Abstract
Background/Objectives: Culex species mosquitoes are globally distributed and transmit several pathogens that impact animal and public health, including West Nile virus, Usutu virus, and Plasmodium relictum. Despite their relevance, Culex species are less widely studied than Aedes and Anopheles mosquitoes. To [...] Read more.
Background/Objectives: Culex species mosquitoes are globally distributed and transmit several pathogens that impact animal and public health, including West Nile virus, Usutu virus, and Plasmodium relictum. Despite their relevance, Culex species are less widely studied than Aedes and Anopheles mosquitoes. To expand the genetic tools used to study Culex mosquitoes, we previously developed an optimized plasmid for transient Cas9 and single-guide RNA (sgRNA) expression in Culex quinquefasciatus cells to generate gene knockouts. Here, we established a monoclonal cell line that consistently expresses Cas9 and can be used for screens to determine gene function or antiviral activity. Methods: We used this system to perform the successful gene editing of seven genes and subsequent testing for potential antiviral effects, using a simple single-guide RNA (sgRNA) transfection and subsequent virus infection. Results: We were able to show antiviral effects for the Cx. quinquefasciatus genes dicer-2, argonaute-2b, vago, piwi5, piwi6a, and cullin4a. In comparison to the RNAi-mediated gene silencing of dicer-2, argonaute-2b, and piwi5, our Cas9/sgRNA approach showed an enhanced ability to detect antiviral effects. Conclusions: We propose that this cell line offers a new tool for studying gene function in Cx. quinquefasciatus mosquitoes that avoids the use of RNAi. This short study also serves as a proof-of-concept for future gene knock-ins in these cells. Our cell line expands the molecular resources available for vector competence research and will support the design of future research strategies to reduce the transmission of mosquito-borne diseases. Full article
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Graphical abstract
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<p>Cas9 integration and expression in Cas9 knock-in Hsu cells. (<b>a</b>) Schematic of integrated vasa-Cas9 construct [<a href="#B26-dna-05-00001" class="html-bibr">26</a>]. (<b>b</b>) Detection of dsRed by fluorescence microscopy in Cas9 knock-in Hsu cells. Cells were stained with DAPI. (<b>c</b>) A 3148 bp PCR product was produced from genomic DNA of Cas9 knock-in Hsu cells, with PCR primers designed to amplify the region flanking the integration site (3148 bp product), visualized here on a 1% agarose gel. (<b>d</b>) RT-PCR was performed on RNA of Cas9 knock-in Hsu cells, with PCR primers designed to amplify a region of <span class="html-italic">cas9</span> mRNA. Visualized here on a 1% agarose gel. Black arrows in (<b>c</b>,<b>d</b>) indicate the anticipated PCR product of the correct size.</p>
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<p>Evaluation of gene editing in Cas9 knock-in Hsu cells. Cas9 knock-in Hsu cells were transfected with a gene-specific sgRNA and a non-targeting control sgRNA. Three days post-transfection, a T7 endonuclease I assay was used to determine CRISPR/Cas9 activity. (<b>a</b>) Schematic of experimental design. T7 cleavage after targeting genomic loci of <span class="html-italic">dcr-2</span> (<b>b</b>), <span class="html-italic">ago-2b</span> (<b>c</b>), <span class="html-italic">vago</span> (<b>d</b>), <span class="html-italic">piwi5</span> (<b>e</b>), <span class="html-italic">piwi6a</span> (<b>f</b>), <span class="html-italic">spcs1</span> (<b>g</b>), and <span class="html-italic">cullin4a</span> (<b>h</b>). PCR products were visualized using a 1% agarose gel and a semi-quantitative assessment was performed by quantifying the signal intensity of the full-length uncut product in ImageJ (<b>i</b>).</p>
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<p>Cas9 knock-in Hsu cells for antiviral screens. First, wildtype Hsu cells were transfected with either siRNA targeting <span class="html-italic">dcr</span>-2 (<b>a</b>,<b>b</b>) or dsRNA targeting <span class="html-italic">ago-2</span> (<b>c</b>,<b>d</b>) and infected with LACV (MOI 10) 48 h post transfection. Gene silencing was validated (<b>a</b>,<b>c</b>) and LACV RNA quantified (<b>b</b>,<b>d</b>) by qRT-PCR 48 h post infection. Then, wildtype Hsu cells were transfected with dsRNA targeting <span class="html-italic">dcr</span>-2 (<b>e</b>,<b>f</b>) or <span class="html-italic">ago-2</span> (<b>g</b>,<b>h</b>) and infected with USUV (MOI 50) 48 h post transfection. Gene silencing was validated (<b>e</b>,<b>g</b>) and USUV RNA quantified (<b>f</b>,<b>h</b>) by qRT-PCR 48 h post infection. Cas9 knock-in Hsu cells were transfected with sgRNAs targeting seven different genes and two controls (GFP and mCherry). Then, 72 h later, cells were infected with either LACV at MOI 10 (<b>i</b>) or USUV at MOI 50 (<b>j</b>). RNA was extracted 48 h post infection, and LACV (<b>i</b>) or USUV (<b>j</b>) RNA was quantified using qRT-PCR and normalized to the GFP control. Mean values from at least two separate experiments with three replicates each are shown. Error bars indicate SEM. Statistical significance was determined using one-way ANOVA and is indicated as ns means non-significant, * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.0005, and **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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14 pages, 3748 KiB  
Article
Using Recombinase-Aid Amplification Combined with Pyrococcus furiosus Argonaute for Rapid Sex Identification in Flamingo (Phoenicopteridae)
by Shenluan Tan, Fanwen Zeng, Wanhuan Zhong, Tanzipeng Chen, Xuanjiao Chen, Li Li, Hengxi Wei and Shouquan Zhang
Animals 2025, 15(1), 7; https://doi.org/10.3390/ani15010007 - 24 Dec 2024
Viewed by 383
Abstract
Flamingos (Phoenicopteridae) are among the oldest birds worldwide and are loved by people for their bright red feathers. In addition, flamingos are sexually monomorphic birds, and distinguishing between males and females is difficult. The polymerase chain reaction (PCR) is widely used [...] Read more.
Flamingos (Phoenicopteridae) are among the oldest birds worldwide and are loved by people for their bright red feathers. In addition, flamingos are sexually monomorphic birds, and distinguishing between males and females is difficult. The polymerase chain reaction (PCR) is widely used for sex identification. However, the PCR method requires a precise thermal cycler in the laboratory and is time-consuming. Therefore, developing a rapid, sensitive, and accurate method to identify the sex of flamingos is crucial. In this study, we established a sex identification system using a recombinase-aided amplification-Pyrococcus furiosus Argonaute (RAA-PfAgo) technique for greater flamingo (Phoenicopterus roseus). The greater flamingo-RAA-PfAgo system can identify unknown-sex greater flamingos in less than 1 h and can be visualized using a fluorescent detector or blue light. The results showed that optimal RAA-PfAgo conditions could detect 0.6 ng of genomic DNA and effectively differentiate between males and females. Random sample evaluations revealed that the system had a 100% coincidence rate compared with conventional PCR. In conclusion, this study provides a sensitive, specific, and accurate reference method for greater flamingo sexing. Full article
(This article belongs to the Section Birds)
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<p>Schematic diagram of RAA-<span class="html-italic">Pf</span>Ago assay on greater flamingo sexing. The RAA followed a kit used at 40 °C for 30 min. Then, the RAA amplicons were added to the <span class="html-italic">Pf</span>Ago assay and maintained at 95 °C for 30 min. The results were observed via a fluorescence detector or blue light. Positive results appeared, and the fluorescence signal indicated female samples; negative results appeared, and no signal indicated male samples.</p>
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<p>Primer selection using RAA-AGE. The RAA products, by the basic RAA kit with the four primer sets, were subjected to electrophoresis on a 1.5% agarose gel.</p>
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<p>Optimization of the RAA assay. (<b>A</b>) Evaluation of different incubation temperatures. (<b>B</b>) Evaluation of the effect of different incubation times. The RAA products by the basic RAA kit with the four primer sets were subjected to electrophoresis on a 1.5% agarose gel.</p>
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<p>gDNA selection. (<b>A</b>) Bar chart illustrating the endpoint fluorescence values of different gDNA. (<b>B</b>) Line chart illustrating temporal variation in fluorescence intensity for different gDNA.</p>
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<p>Establishment of the RAA-<span class="html-italic">Pf</span>Ago assay. ♀: Female; ♂: Male; NC: ddH<sub>2</sub>O.</p>
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<p>Optimization of Mg<sup>2+</sup> concentrations (<b>A</b>) Bar chart illustrating the endpoint fluorescence values at different concentrations of Mg<sup>2+</sup>. (<b>B</b>) Line chart illustrating temporal variation in fluorescence intensity for different concentrations of Mg<sup>2+</sup>.</p>
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<p>Optimization of <span class="html-italic">Pf</span>Ago and gDNA concentrations. (<b>A</b>,<b>C</b>) Bar charts illustrating endpoint fluorescence values for different concentrations of <span class="html-italic">Pf</span>Ago and gDNA. (<b>B</b>,<b>D</b>) Line charts illustrating the temporal variation in fluorescence intensity at different concentrations of <span class="html-italic">Pf</span>Ago and gDNA.</p>
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<p>Specificity evaluation of RAA-<span class="html-italic">Pf</span>Ago detected both female and male samples. (<b>A</b>) Endpoint fluorescence values for RAA-<span class="html-italic">Pf</span>Ago sensitivity. (<b>B</b>) Observations under blue light.</p>
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<p>Sensitivity evaluation of RAA-<span class="html-italic">Pf</span>Ago. (<b>A</b>) Endpoint fluorescence values for RAA-<span class="html-italic">Pf</span>Ago sensitivity. (<b>B</b>) Results under blue light. NC: negative control. Error bars represent SEM; n = 3; **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Field tests using conventional PCR and RAA-<span class="html-italic">Pf</span>Ago. (<b>A</b>) Field samples were tested using conventional PCR on a 1.5% agarose gel. (<b>B</b>) The same samples were tested using RAA-<span class="html-italic">Pf</span>Ago and visualized under blue light. NC: negative control.</p>
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17 pages, 9585 KiB  
Article
Identification of the Brassinazole-Resistant (BZR) Gene Family in Wheat (Triticum aestivum L.) and the Molecular Cloning and Functional Characterization of TaBZR2.1
by Yan Zhang, Jingzi Qin, Jinna Hou, Congcong Liu, Shenghui Geng, Maomao Qin, Wenxu Li, Ziju Dai, Zhengqing Wu, Zhensheng Lei and Zhengfu Zhou
Int. J. Mol. Sci. 2024, 25(23), 12545; https://doi.org/10.3390/ijms252312545 - 22 Nov 2024
Viewed by 549
Abstract
Brassinazole-resistant (BZR) transcription factors are important transcription factors in Brassinosteroid (BR)-responsive gene expression. However, limited knowledge exists regarding the BZR genes in wheat and a limited number of BZR family genes have been previously reported in wheat. In this study, the synteny analyses [...] Read more.
Brassinazole-resistant (BZR) transcription factors are important transcription factors in Brassinosteroid (BR)-responsive gene expression. However, limited knowledge exists regarding the BZR genes in wheat and a limited number of BZR family genes have been previously reported in wheat. In this study, the synteny analyses of the TaBZR genes suggested that gene duplication events have played an essential role in the TaBZR family during evolution. The results of RT-qPCR and transcriptome data analyses exhibited remarkable expression patterns in the BZR genes in different tissues and under different treatments. The yeast two-hybrid (Y2H) screen result showed that the TaBZR2.1 protein interacts with Argonaute 4 (AGO4). Taken together, our results not only provide us a basis for understanding the molecular characteristics and expression patterns of the TaBZR family genes but also offered the functional characterization of TaBZR2.1 in wheat. Full article
(This article belongs to the Special Issue Genetic Engineering of Plants for Stress Tolerance)
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<p>The chromosome distribution of the <span class="html-italic">TaBZR</span> genes.</p>
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<p>The genomic structure of <span class="html-italic">TaBZR</span> genes. The blue boxes in the schematic diagram represent the upstream/downstream sequences; the exon sequences and the introns are represented by yellow boxes and black lines, respectively.</p>
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<p>The tertiary structure prediction of the BZR protein in wheat. The tertiary structures of the TaBZR proteins were generated using the SWISS-MODEL. Twenty BZR proteins were modeled based on GMQE.</p>
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<p>The interchromosomal relationships of the <span class="html-italic">TaBZR</span> gene family in wheat. In the middle of the figure, the black lines indicate the <span class="html-italic">TaBZR</span> gene pairs, and the gray lines represent all of the synteny blocks in the wheat genome. The green bars on each chromosome represent gene density. The number of each chromosome is indicated in green.</p>
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<p>The cis-elements in the promoter regions of the <span class="html-italic">TaBZR</span> genes.</p>
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<p>Distribution of the conserved motifs of the TaBZRs. (<b>A</b>). Conserved motif analysis of TaBZR was performed in this study. The different colored boxes numbered 1–10 indicate different motifs. The annotations of the motifs are listed on the right. (<b>B</b>). The conserved amino acid sequences in each motif.</p>
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<p>The wheat <span class="html-italic">BZR</span> gene expression profiles. Hierarchical clustering of the wheat <span class="html-italic">BZR</span> gene expression profiles in 45 of the samples, including different tissues and development stages. The numbers in the schematic diagram represent the development stages of the same tissue.</p>
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<p>Expression analysis of the <span class="html-italic">TaBZR</span> genes in response to different treatments by qRT-PCR. Seeds of wheat cultivar Zhengmai366 (ZM366) were germinated for 3 days in the dark and then transferred to Hoagland liquid solution. The nutrient solution was changed every three days. At the trefoil stage (about three weeks old), seedlings were transferred to Hoagland liquid nutrient solution with ABA (200 mM), NaCl (200 mM), 20% PEG, and epi-BR (1μM) for ABA, NaCl, PEG, and epi-BR treatment, and seedlings were transferred to chambers at 37 °C or 4 °C to initiate heat and cold stress. The data were normalized with <span class="html-italic">TaACTIN</span> and <span class="html-italic">TaGAPDH</span>. The white and black columns in the diagrams represent the control and treatment groups, respectively. *, <span class="html-italic">p</span> &lt; 0.05. **, <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Subcellular localization of the TaBZR2.1-GFP fusion protein in the protoplast and TaBZR2.1 tissue-specific expressions. (<b>A</b>). TaBZR2.1-GFP protein driven by the 35S promoter were transiently expressed in protoplast cells of wheat, and they were observed using a confocal microscope. The GFP signals are represented by a green color; the red color represents the mCherry signals. Scale bars = 5 μM. (<b>B</b>). TaBZR2.1 tissue-specific expression profiles. Samples of the three-leaf and filling stages were collected, respectively, and the transcription levels of <span class="html-italic">TaBZR2.1</span> were measured using RT-qPCR assays, which were normalized with <span class="html-italic">TaACTIN</span> and <span class="html-italic">TaGAPDH</span>. The letters indicated significant at <span class="html-italic">p</span> &lt; 0.05. Data are the mean ± SD (n = 3).</p>
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<p>Overexpression of the <span class="html-italic">TaBZR2.1</span> gene in <span class="html-italic">Arabidopsis</span> negatively regulated the brassinazole-induced stress tolerance. (<b>A</b>). Seedling photographs of the 6-day-old Col-0 and TaBZR2.1-overexpressing <span class="html-italic">Arabidopsis</span> grown on 1/2 MS with brassinazole (1 μM). (<b>B</b>,<b>C</b>). The root length and leaf area of the seedlings in (<b>A</b>). The letters indicated significance at <span class="html-italic">p</span> &lt; 0.05 (n = 30). (<b>D</b>,<b>E</b>). The expression levels of <span class="html-italic">Hsp17.8</span>, <span class="html-italic">Hsp17.6A</span>, <span class="html-italic">Hsp17.B</span>, <span class="html-italic">Hsp17.C</span>, <span class="html-italic">SOS1</span>, and <span class="html-italic">CAT2</span> in the seedlings under control (<b>D</b>) and brassinazole (<b>E</b>) treatment. ***, <span class="html-italic">p</span> &lt; 0.001. ns, not significant.</p>
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<p>TaBZR2.1 physically interacting with AGO4. (<b>A</b>). Gel electrophoresis results for the identification of the insert fragments from the yeast library. (<b>B</b>). Yeast library titration. In the experiment, 100 μL of the 1/10, 1/100, 1/1000, and 1/10,000 dilutions and 100 μL of the yeast library were plated on SD/-Trp medium. Dilution factor = 10<sup>−1</sup> (<b>a</b>), 10<sup>−2</sup> (<b>b</b>), 10<sup>−3</sup> (<b>c</b>), and 10<sup>−4</sup> (<b>d</b>). (<b>C</b>). Yeast two-hybrid assay of TaBZR2.1 interacting with AGO4. BD-TaBZR2.1 (bait) and AD-AGO4 (prey) plasmids were transformed into the yeast (Y2H-gold) competent cell, as indicated and grown on the selection medium. (<b>D</b>). Split-LUC assay of TaBZR2.1 interacting with AGO4 in the tobacco leaves.</p>
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24 pages, 6532 KiB  
Article
Genome-Wide Identification of AGO, DCL, and RDR Genes and Their Expression Analysis in Response to Drought Stress in Peach
by Mohammad Belal, Charmaine Ntini, Cherono Sylvia, Misganaw Wassie, Mahmoud Magdy, Collins Ogutu, Mohamed Ezzat, Md Dulal Ali Mollah, Yunpeng Cao, Weihan Zhang, Elsayed Nishawy and Yuepeng Han
Horticulturae 2024, 10(11), 1228; https://doi.org/10.3390/horticulturae10111228 - 20 Nov 2024
Viewed by 1070
Abstract
Small RNAs (sRNAs) control a wide range of development and physiological pathways in plants. To address the response of sRNA biogenesis to drought stress, we identified sRNA biogenesis genes, including 11 encoding argonautes (AGO), 8 encoding Dicer-like proteins (DCL), and 9 encoding RNA-dependent [...] Read more.
Small RNAs (sRNAs) control a wide range of development and physiological pathways in plants. To address the response of sRNA biogenesis to drought stress, we identified sRNA biogenesis genes, including 11 encoding argonautes (AGO), 8 encoding Dicer-like proteins (DCL), and 9 encoding RNA-dependent RNA polymerases (RDR) in the peach genome. Notably, the largest numbers of sRNA biogenesis genes are located to chromosome 1. The PAZ, PIWI, and MID domains were identified in PpAGOs, while the ribonuclease IIIa and IIIb domains were characterized in PpDCLs. The RDRP domain was recognized in PpRDRs. Orthologous similarity and collinearity analyses between Arabidopsis and peach revealed 5, 1, and 2 collinear blocks in AGOs, DCLs, and RDRs, respectively. Moreover, 41, 40, and 42 cis-acting elements were located in the promoters of PpAGOs, PpDCLs, and PpRDRs, respectively, with the majority related to drought stress response. Analysis of RNA sequencing (RNA-seq) data revealed that sRNA biogenesis genes were involved in drought stress response in different tissues. Furthermore, the expression of candidate genes was verified in two peach cultivars, Beijing 2-7 (BJ2-7) and Sinai (SN), which are tested as drought-tolerant and sensitive cultivars, respectively, based on the physiological and biochemical analyses, which revealed that the Chinese peach cultivar ‘BJ2-7’ exhibits greater drought resistance compared to the Egyptian peach cultivar ‘SN’. Interestingly, the expression of PpAGO2b, PpDCL2b, PpDCL4, and PpRDR4 genes was induced in ‘BJ2-7’ but inhibited in ‘SN’ under drought stress. Overall, this study provides insight into the roles of sRNA biogenesis genes in response to drought stress in peach. Full article
(This article belongs to the Section Genetics, Genomics, Breeding, and Biotechnology (G2B2))
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Figure 1
<p>Phylogenetic analysis of peach AGOs, DCLs, and RDRs. (<b>A</b>) Phylogenetic tree for AGO deduced proteins from <span class="html-italic">P. persica</span> and <span class="html-italic">A. thaliana</span>. (<b>B</b>) Phylogenetic tree for DCL deduced proteins from <span class="html-italic">P. persica</span> and <span class="html-italic">A. thaliana</span>. (<b>C</b>) Phylogenetic tree for RDR deduced proteins from <span class="html-italic">P. persica</span>. and <span class="html-italic">A. thaliana</span>. All the phylogenetic trees were constructed using the neighbor-joining method, and the numbers at the nodes indicate the percentages of bootstrap values from 1000 replications. The clades of each tree were divided ascendingly by names using I, II, III, etc.</p>
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<p>Phylogenetic analysis and gene chromosomal locations. (<b>A</b>) AGO protein family in Rosaceae. The AGO1/5/10, AGO2/3/7, AGO4/6/8/9 clades were named according to the 10 Arabidopsis AGOs. Blue fonts refer to the identified <span class="html-italic">AGO</span> genes. (<b>B</b>) RDR protein family in Rosaceae. The unrooted NJ tree was constructed in Geneious Prime 2023.1.1. with 1000 bootstrap replicates. RTL1 is rooted as an outgroup (No color), while the colored clades indicate the identified RDR gene members. (<b>C</b>) Chromosomal location of PpAGOs, PpDCLs, and PpRDRs. Tandemly duplicates are shown in square parenthesis.</p>
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<p>Illustrates the gene structure and crystal modeling of PpAGO6 (<b>A</b>,<b>B</b>), PpDCL4 (<b>C</b>,<b>D</b>), and PpRDR2 (<b>E</b>,<b>F</b>) proteins. (<b>A</b>) Schematic domain architecture of PpAGO6 proteins. (<b>B</b>) Representative crystal structure of full-length PpAGO6 protein. (<b>C</b>) Schematic domain architecture of PpDCL4 proteins. (<b>D</b>) Representative crystal structure of full-length PpDCL4 protein. (<b>E</b>) Schematic domain architecture of PpRDR2 proteins. (<b>F</b>) Representative crystal structure of full-length PpRDR2 protein. The displayed colors were similarly applied from the 3D forms into the protein structure.</p>
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<p>Multiple sequence alignment results of AGOs, DCLs, and RDRs showing conserved bases in the motifs. The phylogenetic clades are shown on the left. (<b>A</b>) Functionally conserved positions within MID, PAZ, and PIWI domains of <span class="html-italic">A. thaliana</span> and peach AGO proteins. Residues within the MID domain (indicated by red arrows) crucial for sRNA-target interaction (I996), 5′ terminal nucleotide selection (N991), and 5′-phosphate-binding (YKQK) residues. PIWI domain (blue arrows) highlights the catalytic tetrad (EHDDE) and QF-V motif. Residue numbers correspond to AtAGO1 amino acid positions. (<b>B</b>) Conservation of functionally critical amino acids between <span class="html-italic">A. thaliana</span> and peach DCL proteins. Conserved residues involved in enzyme catalysis within RNase IIIa (E1513, D1517, D1642, E1645; red arrows), RNase IIIb (E1737, D1741, D1745, E1838; green shading and arrows), and RNA-binding motifs (H-S motif; yellow shading and arrows). (<b>C</b>) Presence of functionally critical amino acid residues in peach RDR proteins. The catalytic domain (D[L/F]DGD) within RdRP is highlighted.</p>
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<p>Orthologous similarity and collinearity analysis of sRNA biogenesis genes in peach and Arabidopsis. (<b>A</b>) Circos plot depicting the similarity among identified AGO orthologs. (<b>B</b>) Circos plot illustrating the similarity among identified RDR orthologs. The highlighted arcs in the center of the Circos plots connect orthologous sRNA biogenesis genes. Interprotein arcs represent significant similarities with <span class="html-italic">p</span>-values &lt; 0.05, distinguished by red (&gt;99% identity), brown (95–99%), and gray lines (90–95%) indicating tandem, WGD/segmental duplicates, and other similarities, respectively. (<b>C</b>) Genome-wide collinearity of AGOs (blue), DCLs (green), and RDRs (red) between Arabidopsis and peach chromosomes. Lines connect collinear blocks of gene pairs.</p>
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<p>Tissues and temporal FPKM expression trends. FPKM analysis of <span class="html-italic">PpAGO</span> (<b>A</b>,<b>B</b>), <span class="html-italic">PpDCL</span> (<a href="#app1-horticulturae-10-01228" class="html-app">Figure S3</a>), and <span class="html-italic">PpRDR</span> (<b>C</b>,<b>D</b>) genes in various peach tissues under drought stress. Left panels show high expression levels of <span class="html-italic">PpAGO</span>, <span class="html-italic">PpDCL</span>, and <span class="html-italic">PpRDR</span> genes observed in peach seeds, fruits, roots, leaves, phloem, and flowers. Right panels depict temporal expression trends of <span class="html-italic">AGO</span>, <span class="html-italic">DCL</span>, and <span class="html-italic">RDR</span> genes in the fruit flesh of <span class="html-italic">P. persica</span> exposed to drought stress over a 14-day period, with 0 h as the control. Expression profiles are categorized into three clusters (EC1, EC2, and EC3) based on standardized relative expression levels. RNA data were used to assess the expression of <span class="html-italic">PpAGO</span>, <span class="html-italic">PpDCL</span>, and <span class="html-italic">PpRDR</span> genes.</p>
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<p>Relative expression of candidate genes in the leaves (-L) and roots (-R) of ‘BJ2-7’ and ‘SN’ peach cultivars under drought stress. (<b>A</b>) Expression of <span class="html-italic">PpAGO</span> genes. (<b>B</b>) Expression of <span class="html-italic">PpDCL</span> genes. (<b>C</b>) Expression of <span class="html-italic">PpRDR</span> genes. Plants were exposed to drought stress for 14 days, with control plants receiving regular watering. Data are presented as means ± standard errors (<span class="html-italic">n</span> = 3). Asterisks indicate significant differences at * <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 based on Student’s <span class="html-italic">t</span>-test.</p>
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<p>Physiological and biochemical traits analysis. (<b>A</b>) Biomass analysis. (<b>B</b>) Electrolyte leakage percentage. (<b>C</b>) Proline content. (<b>D</b>) Soluble sugar contents. Data are presented as means ± standard errors (<span class="html-italic">n</span> = 3). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, and **** <span class="html-italic">p</span> &lt; 0.0001 based on Student’s <span class="html-italic">t</span>-test.</p>
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24 pages, 2970 KiB  
Review
piRNA Defense Against Endogenous Retroviruses
by Milky Abajorga, Leonid Yurkovetskiy and Jeremy Luban
Viruses 2024, 16(11), 1756; https://doi.org/10.3390/v16111756 - 9 Nov 2024
Viewed by 1864
Abstract
Infection by retroviruses and the mobilization of transposable elements cause DNA damage that can be catastrophic for a cell. If the cell survives, the mutations generated by retrotransposition may confer a selective advantage, although, more commonly, the effect of new integrants is neutral [...] Read more.
Infection by retroviruses and the mobilization of transposable elements cause DNA damage that can be catastrophic for a cell. If the cell survives, the mutations generated by retrotransposition may confer a selective advantage, although, more commonly, the effect of new integrants is neutral or detrimental. If retrotransposition occurs in gametes or in the early embryo, it introduces genetic modifications that can be transmitted to the progeny and may become fixed in the germline of that species. PIWI-interacting RNAs (piRNAs) are single-stranded, 21–35 nucleotide RNAs generated by the PIWI clade of Argonaute proteins that maintain the integrity of the animal germline by silencing transposons. The sequence specific manner by which piRNAs and germline-encoded PIWI proteins repress transposons is reminiscent of CRISPR, which retains memory for invading pathogen sequences. piRNAs are processed preferentially from the unspliced transcripts of piRNA clusters. Via complementary base pairing, mature antisense piRNAs guide the PIWI clade of Argonaute proteins to transposon RNAs for degradation. Moreover, these piRNA-loaded PIWI proteins are imported into the nucleus to modulate the co-transcriptional repression of transposons by initiating histone and DNA methylation. How retroviruses that invade germ cells are first recognized as foreign by the piRNA machinery, as well as how endogenous piRNA clusters targeting the sequences of invasive genetic elements are acquired, is not known. Currently, koalas (Phascolarctos cinereus) are going through an epidemic due to the horizontal and vertical transmission of the KoRV-A gammaretrovirus. This provides an unprecedented opportunity to study how an exogenous retrovirus becomes fixed in the genome of its host, and how piRNAs targeting this retrovirus are generated in germ cells of the infected animal. Initial experiments have shown that the unspliced transcript from KoRV-A proviruses in koala testes, but not the spliced KoRV-A transcript, is directly processed into sense-strand piRNAs. The cleavage of unspliced sense-strand transcripts is thought to serve as an initial innate defense until antisense piRNAs are generated and an adaptive KoRV-A-specific genome immune response is established. Further research is expected to determine how the piRNA machinery recognizes a new foreign genetic invader, how it distinguishes between spliced and unspliced transcripts, and how a mature genome immune response is established, with both sense and antisense piRNAs and the methylation of histones and DNA at the provirus promoter. Full article
(This article belongs to the Special Issue The Diverse Regulation of Transcription in Endogenous Retroviruses)
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<p>Retroviral genomic RNA and its transformations. Shown are schematic diagrams for the virion-associated genomic RNA, the viral cDNA, and the unspliced and spliced transcripts that are common to all retroviruses. All retroviruses possess at least the three genes, <span class="html-italic">gag</span>, <span class="html-italic">pol</span>, and <span class="html-italic">env</span>. Note that during reverse transcription, two sequential strand-exchange reactions extend the 5’ and 3’ ends of the cDNA beyond the limits of the genomic RNA template.</p>
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<p>Structure of recKoRV. The koala retrovirus, KoRV-A (shown in gray), encodes gag, pol, and env with long terminal repeats at the ends. PhER (shown in blue), is an endogenous retrovirus with no protein coding capacity. Recombinant KoRV (recKoRV) typically contains the KoRV-A 5’ LTR, truncated gag, truncated env, and 3’ LTR with the 3’end of PhER in the middle.</p>
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<p>Host restriction factors and retroviral antagonists. Restriction factors are shown in red and viral antagonists are shown in blue. CypA: cyclophilin A; KZFPs: Kruppel-associated box (KRAB)-containing zinc finger proteins; HUSH: human silencing hub (HUSH) complex; Vpr: Viral protein R: Vif: Viral infectivity factor; Vpu: Viral protein U; APOBEC3G (apolipoprotein B mRNA editing enzyme, catalytic subunit 3G); SAMHD1: SAM domain and HD domain-containing protein 1.</p>
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<p>piRNA biogenesis in nurse cells of Drosophila ovaries. <span class="html-italic">D. melanogaster</span> ovaries contain a series of developing egg chambers in linearly arranged repetitive strings called ovarioles. An egg chamber is characterized by a germline cyst, which contains 15 germline nurse cells and an oocyte that is surrounded by somatic follicle cells. In the nurse cells, germline dual-strand clusters decorated with H3K9me3 marks bound by Rhino-Deadlock-Cutoff (RDC) complex are transcribed by RNA Polymerase II. These transcripts are exported into the cytoplasm, where they are processed into mature piRNAs by the ping-pong amplification loop or phasing. (<b>a</b>) Ping-pong amplification: The feed forward cleavage of complementary transcripts by Aub and Ago3 results in piRNAs with a 10-nucleotide overlap. (<b>b</b>) Phasing: Armi shuttles Aub bound to a piRNA precursor to the mitochondria where Zucchini generates piRNA intermediates through cleavage adjacent to uridines along the length of the precursor. These piRNA intermediates loaded on Piwi are then processed into mature piRNAs.</p>
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<p>Spermatogenic defects of PIWI mutants in mice and hamsters. In mice, PIWIL2 and PIWIL4 mutants arrest at the zygotene stage of meiosis I and PIWIL1 mutants arrest at the round spermatid stage. In hamsters, PIWIL3-KO does not cause any defect in the testes. PIWIL1-KO results in arrest at the pachytene stage. PIWIL2 and PIWIL4 defective hamsters arrest during mitosis as gonocytes. Solid lines show normal development; red crosses (x) indicate the stage of developmental block.</p>
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<p>Oogenic defects of PIWI mutants in hamsters. PIWIL1 deficiency results in arrest at the 2-cell stage. PIWIL2-KO mutants have no defects in oocytes. PIWIL3 deficient hamsters arrest at the 2-cell stage, but some fertilized oocytes complete development. Solid lines show normal development; red crosses (x) indicate the stage of developmental block.</p>
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<p>Model of innate and adaptive piRNA genome defense. Upon invasion of the germline by a novel retrovirus, the retroviral transcript is directly processed into positive sense piRNAs. Later, the adaptive piRNA response is established where antisense piRNAs are made. These antisense piRNAs can directly target the sense transcript resulting in the co-transcriptional repression of the transposon.</p>
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13 pages, 1914 KiB  
Article
Utilizing Short Interspersed Nuclear Element as a Genetic Marker for Pre-Harvest Sprouting in Wheat
by Purnima Kandpal, Karminderbir Kaur, Raman Dhariwal, Simranjeet Kaur, Gagandeep Kaur Brar, Harpinder Randhawa and Jaswinder Singh
Plants 2024, 13(21), 2981; https://doi.org/10.3390/plants13212981 - 25 Oct 2024
Viewed by 3239
Abstract
Pre-harvest sprouting (PHS) is a complex abiotic stress caused by multiple exogenous and endogenous variables that results in random but significant quality and yield loss at the terminal crop stage in more than half of the wheat-producing areas of the world. Systematic research [...] Read more.
Pre-harvest sprouting (PHS) is a complex abiotic stress caused by multiple exogenous and endogenous variables that results in random but significant quality and yield loss at the terminal crop stage in more than half of the wheat-producing areas of the world. Systematic research over more than five decades suggests that addressing this challenge requires tools beyond the traditional genetic manipulation approach. Previous molecular studies indicate a possible role of epigenetics in the regulation of seed dormancy and PHS in crops, especially through RNA-directed DNA methylation (RdDM) pathways mediated by Argonaute (AGO) proteins. In this study, we explore the role of the AGO802B gene associated with PHS resistance in wheat, through the presence of a SINE retrotransposon insertion. The current study found the SINE insertion at 3′UTR of the TaAGO802B present in 73.2% of 41 cultivars analyzed and in 92.6% of the resistant cultivar subset. The average expression of TaAGO802B in cultivars with the SINE insertion was 73.3% lower than in cultivars without insertion. This study also indicated a significant positive correlation between the PHS score and methylation levels in the cultivars. The resistant cultivars with the SINE insertion recorded 54.7% lower methylation levels than susceptible cultivars. Further analysis of a DH population (Sadash × P2711) reveals that SINE insertion co-segregates with PHS resistance. This sets forth the SINE insertion in TaAGO802B as a genetic marker for screening wheat germplasm and as an efficient tool for breeding PHS-resistant wheat cultivars. Full article
(This article belongs to the Section Crop Physiology and Crop Production)
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Graphical abstract
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<p>PHS score levels in diverse Canadian wheat germplasm. The pink line represents the distribution of scores on the scale represented by the radius. A higher score denotes high susceptibility to PHS, while values approaching 0 reflect increasing resistance.</p>
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<p>Analysis of SINE insertion in <span class="html-italic">AGO802B.</span> (<b>a</b>) Agarose gel displaying polymorphism in a subset of wheat cultivars. (<b>b</b>) Graphical representation of the association of SINE insertion with PHS tolerance in Canadian wheat cultivars.</p>
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<p>Expression of <span class="html-italic">AGO802</span> gene in various wheat cultivars. (<b>a</b>) Relative fold change in various wheat cultivars with varying levels of PHS. The lowercase letters above the bar indicate a significant difference (<span class="html-italic">p</span> ≤ 0.05). (<b>b</b>) Boxplot distribution of SINE insertion in PHS-resistant and PHS-susceptible wheat cultivars.</p>
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<p>The study of global 5-mC% methylation levels in Canadian wheat cultivar panel: (<b>a</b>) 5-mC% in wheat cultivars having different levels of PHS. The lowercase letter above the bar indicates the significant difference (<span class="html-italic">p</span> ≤ 0.05). (<b>b</b>) Boxplot distribution of SINE insertion in PHS-resistant and susceptible wheat cultivars.</p>
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<p>PHS level and SINE polymorphism seen in DH population (Sadash × P2711).</p>
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15 pages, 1268 KiB  
Review
MicroRNA and Rare Human Diseases
by Himanshu Goel and Amy Goel
Genes 2024, 15(10), 1243; https://doi.org/10.3390/genes15101243 - 25 Sep 2024
Cited by 1 | Viewed by 1557
Abstract
Background: The role of microRNAs (miRNAs) in the pathogenesis of rare genetic disorders has been gradually discovered. MiRNAs, a class of small non-coding RNAs, regulate gene expression by silencing target messenger RNAs (mRNAs). Their biogenesis involves transcription into primary miRNA (pri-miRNA), processing by [...] Read more.
Background: The role of microRNAs (miRNAs) in the pathogenesis of rare genetic disorders has been gradually discovered. MiRNAs, a class of small non-coding RNAs, regulate gene expression by silencing target messenger RNAs (mRNAs). Their biogenesis involves transcription into primary miRNA (pri-miRNA), processing by the DROSHA–DGCR8 (DiGeorge syndrome critical region 8) complex, exportation to the cytoplasm, and further processing by DICER to generate mature miRNAs. These mature miRNAs are incorporated into the RNA-induced silencing complex (RISC), where they modulate gene expression. Methods/Results: The dysregulation of miRNAs is implicated in various Mendelian disorders and familial diseases, including DICER1 syndrome, neurodevelopmental disorders (NDDs), and conditions linked to mutations in miRNA-binding sites. We summarized a few mechanisms how miRNA processing and regulation abnormalities lead to rare genetic disorders. Examples of such genetic diseases include hearing loss associated with MIR96 mutations, eye disorders linked to MIR184 mutations, and skeletal dysplasia involving MIR140 mutations. Conclusions: Understanding these molecular mechanisms is crucial, as miRNA dysregulation is a key factor in the pathogenesis of these conditions, offering significant potential for the diagnosis and potential therapeutic intervention. Full article
(This article belongs to the Special Issue Genetics and Therapy of Neurodevelopmental Disorders)
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<p>Biogenesis of miRNA: Transcription and primary miRNA formation: miRNA genes are transcribed by RNA polymerase II (or sometimes III) into pri-miRNA transcripts, which are capped and polyadenylated. Nuclear processing: In the nucleus, pri-miRNA is processed by DROSHA and DGCR8 into pre-miRNA, which is then exported to the cytoplasm by Exportin-5. Cytoplasmic processing: In the cytoplasm, DICER processes pre-miRNA into an miRNA duplex. The guide strand (mature miRNA) is loaded into the RNA-induced silencing complex (RISC), while the passenger strand is typically degraded. Incorporation into RISC and target regulation: The guide strand in RISC, containing AGO proteins, guides the complex to complementary sequences on target mRNAs, leading to mRNA degradation or translational repression. Seed sequence: The seed sequence (nucleotides 2–7 from the 5′ end) is crucial for target recognition and miRNA-mediated gene regulation.</p>
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<p>Mature hsa-miR-96-5p and miR-96 (+13G&gt;A) and (+14C&gt;A) mutations are shown to be aligned. The reference base “G” is written in black and the variant base “A” is written in red. The top 5 genes that are regulated by hsa-miR-96-5p genes are also aligned.</p>
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<p>Hughes et al. (2011) identified heterozygosity for a n.57C&gt;T in the <span class="html-italic">MIR184</span> precursor sequence. The heterozygous C-to-T transition (n.57C&gt;T) within miR-184 is in the central nucleotide of the functionally essential seven base miRNA seed region (GGACGG) (in bold letters). The mutation was not found in unaffected family members or in controls. Mir-184_5p* is the passenger strand (miRNA*), that is generally degraded.</p>
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<p>A variant in the 3′-UTR of the <span class="html-italic">HDAC6</span> gene in a proband with X-linked dominant chondrodysplasia is depicted here. The sequence alignment of the hsa-miR-433-3p with the wild-type (WT) and variant <span class="html-italic">HDAC6</span> 3′ UTR region of mRNA are shown here concerning the seed region of miRNA that is shown in red. The <span class="html-italic">HDAC6</span> variant is within the 3′-UTR A&gt;T mutation. The variant has loosened the binding of miRNA with the <span class="html-italic">HDAC6</span> 3′ UTR mRNA. Blue vertical lines denote the hydrogen bonds between <span class="html-italic">HDAC6</span> DNA and miR-433 RNA seed sequence. Underlined bases represent the sequence change in <span class="html-italic">HDAC6</span> (3′-UTR A&gt;T mutation).</p>
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14 pages, 6818 KiB  
Communication
UTRs and Ago-2/miR-335 Complex Restricts Amylin Translation in Insulinoma and Human Pancreatic β-Cells
by Zhanar Kudaibergenova, Satyabrata Pany, Elizabeth Placheril and Aleksandar M. Jeremic
Int. J. Mol. Sci. 2024, 25(17), 9614; https://doi.org/10.3390/ijms25179614 - 5 Sep 2024
Viewed by 950
Abstract
Amylin promoter and transcriptional factors are well-established, inducible factors in the production of the main amyloidogenic pancreatic hormone, human islet amyloid peptide (hIAPP) or amylin. However, posttranscriptional mechanisms driving hIAPP expression in pancreas remain enigmatic, and hence were explored here. The translational assay [...] Read more.
Amylin promoter and transcriptional factors are well-established, inducible factors in the production of the main amyloidogenic pancreatic hormone, human islet amyloid peptide (hIAPP) or amylin. However, posttranscriptional mechanisms driving hIAPP expression in pancreas remain enigmatic, and hence were explored here. The translational assay revealed that both 5′ and 3′ untranslated regions (UTRs) of hIAPP restricted expression of the luciferase constructs only in constructs driven by the hIAPP promoter. Bioinformatics analysis revealed several putative seed sequences for a dozen micro RNAs (miRNAs) in hIAPP’s 3′ UTR. miR-182, miR-335, and miR-495 were the most downregulated miRNAs in stressed human islets exposed to endoplasmic reticulum (ER) or metabolic stressors, thapsigargin (TG) or high glucose (HG). Correspondingly, miR-335 mimics alone or in combination with miR-495 and miR-182 mimics significantly and potently (>3-fold) reduced hIAPP protein expression in HG-treated cultured human islets. siRNA-mediated silencing of Ago2 but not Ago1 significantly stimulated hIAPP expression and secretion from transfected, HG-treated human islets. Conversely, ectopic expression of Ago2 in hIAPP-expressing RIN-m5F cell line driven by CMV promoter reduced hIAPP intracellular protein levels. Collectively, the results point to a novel and synergistic role for hIAPP promoter, 5/3′ UTRs and Ago-2/miR-335 complex in post-transcriptional regulation of hIAPP gene expression in normal and metabolically active β-cells. Full article
(This article belongs to the Special Issue Molecular Research on Diabetes)
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Figure 1

Figure 1
<p>hIAPP 5′ and 3′ UTRs regulate protein translation in pancreatic cells. RIN cells were co-transfected with the designated plasmid constructs encoding firefly luciferase and the renilla vector ((<b>A</b>) for short-term (3 h, (<b>B</b>)) or longer incubation times (12 h, (<b>C</b>)). (<b>A</b>) Design map of vectors containing IAPP promoter and control or IAPP 5′/3′-UTRs. (<b>B</b>) Short term (3 h) expression analysis of IAPP-promoter-driven translation constructs. (<b>C</b>) Prolonged (12 h) expression analysis of IAPP-promoter-driven translation constructs. Normalized translational activities of IAPP-promoter-driven constructs containing hIAPP 5′ and/or 3′ UTRs were statistically compared to control IAPP construct featuring generic 5′3′ UTRs. Significance established at ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001 (IAPP vs. IAPP UTRs) n = 3, ANOVA followed by Tukey post hoc comparison test.</p>
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<p>Translational activity of SV40-promoter-driven constructs in RIN cells. RIN cells were co-transfected with the designated plasmid constructs encoding firefly luciferase and the renilla vector ((<b>A</b>) for short-term (3 h, (<b>B</b>)) or longer incubation times (12 h, (<b>C</b>)). (<b>A</b>) Design map of vectors containing viral, SV40 promoter, and control or IAPP 5′/3′-UTRs. (<b>B</b>) Short term (3 h) expression analysis of SV40-promoter-driven translation constructs. (<b>C</b>) Prolonged (12 h) expression analysis of SV40-promoter-driven translation constructs. Normalized translational activities of SV40-driven constructs containing hIAPP 5′ and 3′ UTRs with respect to control vector containing generic 5′3′ UTRs (SV40) were determined and statistically compared. Significance established at * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 (SV40-control vs. SV40-IAPP UTRs) n = 3, ANOVA followed by Tukey post hoc comparison test.</p>
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<p>miRNAs expression analysis in HG-challenged human islets. Freshly isolated non-diabetic human islets were cultured in the presence of high (20 mM) glucose (HG) or 1 μM thapsigargin (TG) for 24 h. Relative miRNA levels were analyzed by RT-qPCR and changes in miRNA expression levels in treatments, after normalizing to a ubiquitously expressed miRNA SNORD44, were expressed as a fold change (FC) relative to control (normal glucose, NG) cells. Significance established at # <span class="html-italic">p</span> &lt; 0.05, n = 3 (HG vs. NG), and * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001, n = 3 (TG vs. NG), ANOVA followed by Tukey post hoc comparison test.</p>
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<p>Western blot analysis of miRNA-driven hIAPP expression in human islets. (<b>A</b>) Freshly isolated non-diabetic human islets were cultured in the presence of high (20 mM) glucose (HG) or normal (5 mM) glucose (NG) supplemented with scrambled (SC) or antisense miRNAs (182, 335, 495) or their combination (miRs comb.) for 72 h, and changes in hIAPP protein expression analyzed by western blot. (<b>B</b>) hIAPP signal was normalized against beta-actin and expressed as fold change from control (NG) samples (set to 1). Significance established at ** <span class="html-italic">p</span> &lt; 0.01, n = 3, (HG + SC vs. HG + miR-335) and * <span class="html-italic">p</span> &lt; 0.05, n = 3, (HG + SC vs. HG + miRs combination), ANOVA followed by Tukey post hoc comparison test.</p>
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<p>Effect of Ago-1/2 siRNAs on β-cell hormone protein expression and secretion in human islets. The human islets were cultured under normal- (NG) or high-glucose (HG) conditions supplemented with scrambled (SC) or Ago1/2 siRNAs for 72 h, and changes in human amylin (hIAPP) and insulin protein expression were analyzed by western blot. (<b>A</b>) Intracellular and extracellular hIAPP signals were normalized against beta-actin and expressed as fold change from control normal glucose (NG) samples (set to 1). (<b>B</b>) Representative western blots of intracellular and extracellular hIAPP contents under various conditions. (<b>C</b>) Intracellular and extracellular insulin signals were normalized against beta-actin and expressed as fold change from control (NG) samples (set to 1). (<b>D</b>) Representative western blots of intracellular and extracellular insulin protein contents under various conditions. Significance established at * <span class="html-italic">p</span> &lt; 0.05, n = 3 (HG + Ago2 vs. HG + SC), and # <span class="html-italic">p</span> &lt; 0.05, n = 3 (HG + Ago1 vs. HG + SC), ANOVA followed by Tukey post hoc comparison test.</p>
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<p>Ago-2 controls hIAPP expression in RINm5F cells. Changes in protein levels of hIAPP in lentivirus-transfected cells encoding Ago2 was analyzed by western blot. Cells were transfected at 5 and 10 MOIs. hIAPP signal was normalized to a housekeeping gene (beta-actin) and expressed as fold change from control RIN cells. Significance established at * <span class="html-italic">p</span> &lt; 0.05, n = 3, ANOVA followed by Tukey post hoc comparison test.</p>
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27 pages, 5317 KiB  
Article
ARGONAUTE2 Localizes to Sites of Sporocysts in the Schistosome-Infected Snail, Biomphalaria glabrata
by Phong Phan, Conor E. Fogarty, Andrew L. Eamens, Mary G. Duke, Donald P. McManus, Tianfang Wang and Scott F. Cummins
Genes 2024, 15(8), 1023; https://doi.org/10.3390/genes15081023 - 3 Aug 2024
Viewed by 1629
Abstract
MicroRNAs (miRNAs) are a class of small regulatory RNA that are generated via core protein machinery. The miRNAs direct gene-silencing mechanisms to mediate an essential role in gene expression regulation. In mollusks, miRNAs have been demonstrated to be required to regulate gene expression [...] Read more.
MicroRNAs (miRNAs) are a class of small regulatory RNA that are generated via core protein machinery. The miRNAs direct gene-silencing mechanisms to mediate an essential role in gene expression regulation. In mollusks, miRNAs have been demonstrated to be required to regulate gene expression in various biological processes, including normal development, immune responses, reproduction, and stress adaptation. In this study, we aimed to establishment the requirement of the miRNA pathway as part of the molecular response of exposure of Biomphalaria glabrata (snail host) to Schistosoma mansoni (trematode parasite). Initially, the core pieces of miRNA pathway protein machinery, i.e., Drosha, DGCR8, Exportin-5, Ran, and Dicer, together with the central RNA-induced silencing complex (RISC) effector protein Argonaute2 (Ago2) were elucidated from the B. glabrata genome. Following exposure of B. glabrata to S. mansoni miracidia, we identified significant expression up-regulation of all identified pieces of miRNA pathway protein machinery, except for Exportin-5, at 16 h post exposure. For Ago2, we went on to show that the Bgl-Ago2 protein was localized to regions surrounding the sporocysts in the digestive gland of infected snails 20 days post parasite exposure. In addition to documenting elevated miRNA pathway protein machinery expression at the early post-exposure time point, a total of 13 known B. glabrata miRNAs were significantly differentially expressed. Of these thirteen B. glabrata miRNAs responsive to S. mansoni miracidia exposure, five were significantly reduced in their abundance, and correspondingly, these five miRNAs were determined to putatively target six genes with significantly elevated expression and that have been previously associated with immune responses in other animal species, including humans. In conclusion, this study demonstrates the central importance of a functional miRNA pathway in snails, which potentially forms a critical component of the immune response of snails to parasite exposure. Further, the data reported in this study provide additional evidence of the complexity of the molecular response of B. glabrata to S. mansoni infection: a molecular response that could be targeted in the future to overcome parasite infection and, in turn, human schistosomiasis. Full article
(This article belongs to the Special Issue Evolution of Non-coding Elements in Genome Biology)
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Figure 1
<p>Identification and expression analysis of core pieces of protein machinery of the <span class="html-italic">Biomphalaria glabrata</span> miRNA pathway 16 and 42 h after its exposure to <span class="html-italic">Schistosoma mansoni</span> miracidia. (<b>A</b>) Schematic of the production (nucleus; grey-colored shaded region) and action (cytoplasm; pale-yellow-colored shaded region) stages of the <span class="html-italic">B. glabrata</span> miRNA pathway with the functional position within the pathway of <span class="html-italic">Bgl</span>-Drosha, <span class="html-italic">Bgl</span>-DGCR8, <span class="html-italic">Bgl</span>-Exp5, <span class="html-italic">Bgl</span>-Ran, <span class="html-italic">Bgl</span>-Dcr, and <span class="html-italic">Bgl</span>-Ago2 indicated. (<b>B</b>) Schematic outlining the functional domain structure of the core pieces of protein machinery of the <span class="html-italic">B. glabrata</span> miRNA pathway, including <span class="html-italic">Bgl</span>-Drosha, <span class="html-italic">Bgl</span>-DGCR8, <span class="html-italic">Bgl</span>-Exp5, <span class="html-italic">Bgl</span>-Ran, <span class="html-italic">Bgl</span>-Dcr, and <span class="html-italic">Bgl</span>-Ago2. RIBOc, ribonuclease III C terminal domain; DSRM, double-stranded RNA motif; OBD/WW, origin-binding domain/tryptophan-tryptophan domain; XPO, Exportin domain; IBN_N, Importin-β N-terminal domain; Ran, Ras-related nuclear domain; Dcr/Dcr, Dicer dimerization domain, HELICc, helicase superfamily C-terminal domain; PAZ, PIWI, Argonaute, and Zwille domain; N, Ago protein amino-terminal region domain; DUF1785, domain of unknown function 1785 domain; PIWI, P-element-induced wimpy testis domain; L2, linker region 2; MID, middle domain. (<b>C</b>) RNA-Seq assessment of the altered expression of <span class="html-italic">Bgl-Drosha</span>, <span class="html-italic">Bgl-DGCR8</span>, <span class="html-italic">Bgl-Exp5</span>, <span class="html-italic">Bgl-Ran</span>, <span class="html-italic">Bgl-Dcr</span>, and <span class="html-italic">Bgl-Ago2</span>, 16 and 42 h after exposure of <span class="html-italic">B. glabrata</span> animals to the <span class="html-italic">S. mansoni</span> parasite. Error bars represent the standard error of the mean, and an asterisk (*) denotes significantly altered transcript abundance (<span class="html-italic">p</span>-value ≤ 0.05) at either the 16 or 42 h time point compared to the level of expression of each core piece of protein machinery in control (unexposed) <span class="html-italic">B. glabrata</span> animals.</p>
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<p>Expression analysis and tissue localization of the Ago2 protein in <span class="html-italic">Biomphalaria glabrata</span> animals following their short- and long-term exposure to the <span class="html-italic">Schistosoma mansoni</span> parasite. (<b>A</b>) Western blot hybridization analysis of Ago2 protein abundance in whole-protein extracts from unexposed (control) and exposed <span class="html-italic">B. glabrata</span> whole animals and <span class="html-italic">S. mansoni</span> miracidia. (<b>B</b>) Western blot hybridization analysis of Ago2 protein abundance in unexposed <span class="html-italic">B. glabrata</span> whole animals (control) and in exposed animals 16 and 42 h after their exposure to <span class="html-italic">S. mansoni</span> miracidia, an analysis that was performed in triplicate for quantification (<b>C</b>) to definitively demonstrate significantly altered Ago2 protein abundance in <span class="html-italic">S. mansoni</span>-exposed <span class="html-italic">B. glabrata</span> whole animals. An asterisk (*) denotes significantly altered Ago2 protein abundance (<span class="html-italic">p</span>-value ≤ 0.05) at either the 16 or 42 h time point compared to the level of Ago2 protein in control (unexposed) <span class="html-italic">B. glabrata</span> animals. (<b>D</b>) Light-field and fluorescent microscopic analysis of the intestinal digestive gland of sectioned <span class="html-italic">B. glabrata</span> animals 16 h post exposure to <span class="html-italic">S. mansoni</span> miracidia. Specifically, (<b>Di</b>,<b>Dii</b>) show different magnifications of bright-field microscopic analysis of H&amp;E-stained regions of the <span class="html-italic">B. glabrate</span> intestinal digestive gland. No fluorescence was observed in the intestinal digestive gland of sectioned <span class="html-italic">B. glabrata</span> animals 16 h post exposure to <span class="html-italic">S. mansoni</span> miracidia (<b>Diii</b>,<b>Div</b>), nor were fluorescent signals observed in negative control samples (<b>Dv</b>,<b>Dvi</b>). (<b>E</b>) Light-field microscopic analysis and fluorescent microscopic analysis of the intestinal digestive gland of sectioned <span class="html-italic">B. glabrata</span> animals 20 days post exposure to the <span class="html-italic">S. mansoni</span> parasite. Specifically, (<b>Ei</b>,<b>Eii</b>) show different magnifications of bright-field microscopic analysis of H&amp;E-stained regions of the intestinal digestive gland of sectioned <span class="html-italic">B. glabrate</span> animals, with the black arrows indicating sporocysts. Readily observable fluorescence was observed in the intestinal digestive gland of sectioned <span class="html-italic">B. glabrata</span> animals (yellow arrows), specifically around the sporocysts that had formed at this long-term exposure time point (<b>Eiii</b>,<b>Eiv</b>). As shown in (<b>Dv</b>,<b>Dvi</b>), no fluorescence was observed in the intestinal digestive gland sectioned of <span class="html-italic">B. glabrata</span> animals 20 days post exposure to <span class="html-italic">S. mansoni</span> miracidia in the negative control samples (<b>Eiv</b>,<b>Ev</b>).</p>
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<p>Profiling of the microRNA landscape of <span class="html-italic">Biomphalaria glabrata</span> whole animals 16 h after their exposure to <span class="html-italic">Schistosoma mansoni</span> miracidia. (<b>A</b>) Heat map of the 66 miRNAs with altered abundance (up- (orange) or down-regulated (blue) abundance) 16 h post exposure of <span class="html-italic">B. glabrata</span> to <span class="html-italic">S. mansoni</span> miracidia, with the intensity of shading of each tile indicating the degree of change to miRNA abundance. (<b>B</b>) Elevated (n = 8) or reduced (n = 5) levels of the 13 miRNAs with significantly altered abundance 16 h post exposure of <span class="html-italic">B. glabrata</span> to <span class="html-italic">S. mansoni</span> miracidia, with orange-colored columns showing up-regulated miRNAs and blue-colored columns representing down-regulated miRNAs. (<b>C</b>) Schematic demonstrating that miRNA abundance was altered in <span class="html-italic">B. glabrata</span> whole animals after their exposure to <span class="html-italic">S. mansoni</span> miracidia regardless of the genomic context of their encoding gene, with altered miRNAs originating from <span class="html-italic">MIR</span> gene clusters or positioned at isolated <span class="html-italic">MIR</span> gene loci in both intragenic and intergenic genomic contexts. (<b>D</b>) Pie chart outlining the genomic context of <span class="html-italic">MIR</span> genes from which the 66 miRNAs with altered abundance 16 h post the exposure of <span class="html-italic">B. glabrata</span> whole animals to <span class="html-italic">S. mansoni</span> miracidia are derived.</p>
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<p>Interaction map of the putative target genes of the five <span class="html-italic">Biomphalaria glabrata</span> miRNAs with significantly reduced abundance 16 h post exposure to <span class="html-italic">Schistosoma mansoni</span> miracidia. (<b>A</b>) Venn diagram showing the number of predicted target genes for the five significantly reduced <span class="html-italic">B. glabrata</span> miRNAs 16 h post exposure to <span class="html-italic">S. mansoni</span> miracidia following target gene assessment using the miRanda and RNAhybrid prediction tools, respectively. (<b>B</b>) miRNA/target gene interaction map for the five significantly reduced <span class="html-italic">B. glabrata</span> miRNAs (blue blocks) post exposure to <span class="html-italic">S. mansoni</span> miracidia, including putative target genes both with down-regulated (yellow blocks) and up-regulated (red blocks) levels of expression.</p>
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21 pages, 2729 KiB  
Article
Anti-Adenoviral Effect of Human Argonaute 2 Alone and in Combination with Artificial microRNAs
by Philipp Ausserhofer, Izabella Kiss, Angela Witte and Reinhard Klein
Cells 2024, 13(13), 1117; https://doi.org/10.3390/cells13131117 - 28 Jun 2024
Viewed by 1043
Abstract
During infection, adenoviruses inhibit the cellular RNA interference (RNAi) machinery by saturating the RNA-induced silencing complex (RISC) of the host cells with large amounts of virus-derived microRNAs (mivaRNAs) that bind to the key component of the complex, Argonaute 2 (AGO2). In the present [...] Read more.
During infection, adenoviruses inhibit the cellular RNA interference (RNAi) machinery by saturating the RNA-induced silencing complex (RISC) of the host cells with large amounts of virus-derived microRNAs (mivaRNAs) that bind to the key component of the complex, Argonaute 2 (AGO2). In the present study, we investigated AGO2 as a prominent player at the intersection between human adenovirus 5 (HAdV-5) and host cells because of its ability to interfere with the HAdV-5 life cycle. First, the ectopic expression of AGO2 had a detrimental effect on the ability of the virus to replicate. In addition, in silico and in vitro analyses suggested that endogenous microRNAs (miRNAs), particularly hsa-miR-7-5p, have similar effects. This miRNA was found to be able to target the HAdV-5 DNA polymerase mRNA. The inhibitory effect became more pronounced upon overexpression of AGO2, likely due to elevated AGO2 levels, which abolished the competition between cellular miRNAs and mivaRNAs for RISC incorporation. Collectively, our data suggest that endogenous miRNAs would be capable of significantly inhibiting viral replication if adenoviruses had not developed a mechanism to counteract this function. Eventually, AGO2 overexpression-mediated relief of the RISC-saturating action of mivaRNAs strongly enhanced the effectiveness of artificial miRNAs (amiRNAs) directed against the HAdV-5 preterminal protein (pTP) mRNA, suggesting a substantial benefit of co-expressing amiRNAs and AGO2 in RNAi-based strategies for the therapeutic inhibition of adenoviruses. Full article
(This article belongs to the Section Cell and Gene Therapy)
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Graphical abstract

Graphical abstract
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<p>Schematic representation of the adenoviral vectors used in this study. All vectors were based on the HAd5V-derived vectors pAd/PL-DEST ™ (ThermoFisher Scientific, Vienna, Austria) lacking the E1 and E3 genes. Expression cassettes were inserted into the deleted E1 region in antisense orientation with respect to the left inverted terminal repeat (ITR). The expression cassettes contain EGFP [<a href="#B34-cells-13-01117" class="html-bibr">34</a>] or AGO2 (this study) open reading frames, either alone or in conjunction with six tandemly repeated, either targeting (pTP-mi5) or non-targeting (NT), amiRNA hairpins incorporated into the 3′ UTR of the EGFP and AGO2 transcripts, respectively. Expression is driven by a CMV promoter (pCMV).</p>
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<p>AGO2 negatively affects the HAdV-5 life cycle. (<b>A</b>) Overexpression of AGO2 decreases the wt HAdV-5 genome copy numbers. 1.5 × 10<sup>4</sup> HeLa cells were simultaneously transfected with 250 ng plasmid and infected with wt HAdV-5 at an MOI of 0.1, respectively. Concentrations of HAdV-5 genome copy numbers were measured at 96 h post-transfection/infection using an E3-probe qPCR. The data display means and standard deviations from a total of 3 independent experiments. Each independent experiment’s EGFP control preparation measurement was set as a reference at 100%. ** (<span class="html-italic">p</span> &lt; 0.01). (<b>B</b>) Overexpression of AGO2 has no effect on the adenovirus mutant dl-sub720. Same as in (<b>A</b>), except that cells were infected with the HAdV-5 mutant dl-sub720 instead of wt HAdV-5. ns (not significant). (<b>C</b>) Compared to wt AGO2 mutants defective for miRNA binding, they differ in their ability to decrease wt HAdV-5 genome copy numbers. 1.5 × 10<sup>4</sup> HeLa cells were simultaneously transfected with 250 ng plasmid expressing either AGO2 or mutants thereof and were infected with wt HAdV-5 at an MOI of 0.1. Concentrations of HAdV-5 genome copy numbers were measured at 96 h post-transfection/infection using an E3-probe qPCR. The data represent the means of 3 representative experiments, including standard deviations. The mean value for the AGO2 measurements was set as a reference at 100%. * (<span class="html-italic">p</span> &lt; 0.05); ** (<span class="html-italic">p</span> &lt; 0.01). (<b>D</b>) The inhibition of HAdV-5 replication by AGO2 is comparable in A549 and HeLa cells. 1.5 × 10<sup>4</sup> A549 or HeLa cells were transduced with AGO2-expressing rAdV vectors at an MOI of 100. 12 h after transduction wt HAdV-5 was added at an MOI of 0.1. Concentrations of HAdV-5 genome copy numbers were measured at 48 h post-infection using an E3-probe qPCR. The data were derived from a total of 3 representative experiments and display mean ± standard deviations. Each experiment’s EGFP control preparation measurement was set as a reference at 100%. * (<span class="html-italic">p</span> &lt; 0.05); ** (<span class="html-italic">p</span> &lt; 0.01); ns (not significant).</p>
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<p>Putative target sites of cellular miRNAs within HAdV-5 early mRNA transcripts Pol and pTP as per in silico TargetScan analysis. In addition to putative target sites of cellular miRNAs (red arrows), the target sites of the previously described siRNAs Pol-si2 (blue arrow) and pTP-si8 [<a href="#B42-cells-13-01117" class="html-bibr">42</a>] with their corresponding amiRNA pTPmi5 (green arrow) [<a href="#B34-cells-13-01117" class="html-bibr">34</a>] are indicated.</p>
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<p>Targeting of HAdV-5 DNA polymerase and pTP sequences by cellular miRNAs and their impact on viral replication. (<b>A</b>) Schematic representation of the dual-luciferase reporter vector system employed in this study. Reporter vectors contain sequences of the HAdV-5 DNA polymerase and pTP genes (Pol; pTP) inserted into the 3′UTR of a Renilla luciferase reporter gene (RLuc). MiRNAs capable of recognizing the respective target mRNAs are expected to knock down Renilla luciferase expression relative to the expression of a non-targeted firefly luciferase gene (FLuc) present on the same vector. (<b>B</b>) Targeting of the HAdV-5 DNA polymerase mRNA by miRNA mimics in reporter assays. 1.5 × 10<sup>4</sup> HeLa cells were simultaneously transfected with a HAdV-5 DNA polymerase reporter vector carrying the DNA polymerase sequence inserted into the 3′UTR of a Renilla luciferase reporter gene and endogenous miRNA mimics, respectively. A non-targeting (NT) miRNA mimic was used as a control. Readout as per manufacturers’ instructions was conducted at 48 h post-transfection and relative light units (RLUs) for the Renilla luciferase reporter gene were normalized to those of the firefly luciferase reporter gene. Each experiment’s NT control preparation measurement was set as a reference at 100%. The data represent means ± standard deviation of 3 experiments. * (<span class="html-italic">p</span> &lt; 0.05). (<b>C</b>) Targeting of the HAdV-5 pTP mRNA by miRNA mimics in reporter assays. Same as in (<b>B</b>) except that a reporter vector carrying the HAdV-5 pTP sequence was used. (<b>D</b>) Effect of the hsa-miR-7 mimic on HAdV-5 genome copy numbers. 1.5 × 10<sup>4</sup> HeLa cells were simultaneously transfected with an hsa-miR-7 mimic at a concentration of 10 nM and infected with HAdV-5 at an MOI of 0.1. Concentrations of HAdV-5 genome copy numbers were measured at 48 h post-transfection/infection using an E3-probe qPCR. Data represent mean ± standard deviations of a representative experiment carried out in triplicate. The non-targeting (NT) control preparation measurement was set as a reference at 100%. ** (<span class="html-italic">p</span> &lt; 0.01).</p>
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<p>Inhibition of miRNA function with miRNA inhibitors and enhancement of miRNA-mediated effects on HAdV-5 by overexpression of AGO2. (<b>A</b>) Inhibition of the action of miRNA mimics with miRNA inhibitors in reporter assays. 1.5 × 10<sup>4</sup> HeLa cells were simultaneously transfected with (i) a HAdV-5 DNA polymerase reporter vector carrying the DNA polymerase sequence inserted into the 3′UTR of a Renilla luciferase reporter gene, (ii) miRNA mimics, and (iii) corresponding miRNA Power Inhibitors (PI). Readout as per manufacturers’ instructions was conducted at 48 h post-transfection. Data (relative light units; RLU) derives from a total of 3 experiments and displays means ± standard deviations. Each experiment’s non-targeting (NT) control preparation measurement was set as a reference at 100%. ** (<span class="html-italic">p</span> &lt; 0.01). (<b>B</b>) Effect of miRNA inhibitors in the absence of miRNA mimics in reporter assays. Same as in (<b>A</b>) except that no miRNA mimics directed against the reporter transcript were employed. ** (<span class="html-italic">p</span> &lt; 0.01). (<b>C</b>) Effect of miRNA mimics on HAdV-5 replication. 1.5 × 10<sup>4</sup> HeLa cells were simultaneously transfected with 5 nM miRNA mimics and transduced with an AGO2- or EGFP-expressing adenoviral vector at an MOI of 100. 24 h later, wt HAdV-5 was added at an MOI of 0.1. Concentrations of wt HAdV-5 genome copy numbers were measured at 48 h post-infection using an E3-probe qPCR. Data represent means ± standard deviations of a representative experiment carried out in triplicate. * (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Improved amiRNA-mediated inhibition of wt HAdV-5 replication upon co-transduction with an AGO2-expressing rAdV vector. (<b>A</b>) The potency of an amiRNA targeting the adenoviral pTP mRNA is significantly improved upon overexpression of AGO2. 1.5 × 10<sup>4</sup> cells were simultaneously transduced with (i) a rAdV expressing HAdV-5-targeting (pTP-mi5) or non-targeting (NT) amiRNAs and (ii) a rAdV expressing AGO2 or EGFP at an MOI of 250, before being exposed to wt HAdV-5 at an MOI of 1. Concentrations of wt HAdV-5 genome copy numbers were measured at 72 h post-infection using an E3-probe qPCR. Each experiment’s EGFP control preparation measurement was set as a reference at 100%. The inhibition by AGO2 alone in the absence of any targeting or non-targeting amiRNA is shown for comparison. Data were derived from a total of 3 representative experiments and display mean ± standard deviations. * (<span class="html-italic">p</span> &lt; 0.05); ns (not significant). AGO2-mediated differences between 6xNT and 6xpTP-mi5 were significant in all instances. (<b>B</b>) Evaluation of the impact of adenoviral vector MOIs in relation to wt HAdV-5 MOIs on viral replication and vector mobilization. 1.5 × 10<sup>4</sup> HeLa cells were simultaneously transduced with rAdVs at MOIs as per the X-axis and infected with wt HAdV-5 as per the Y-axis. Concentrations of wt HAdV-5 and vector genome copy numbers were measured at 48 h post-infection using E3- and CMV promoter-specific qPCR probes, respectively.</p>
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<p>Improvement of rAdV amiRNA vector performance by inclusion of an AGO2 expression cassette. (<b>A</b>) In a prophylactic treatment scenario, 1.5 × 10<sup>4</sup> HeLa cells were transduced with vectors at an MOI of 100 24 h prior to infection with HAdV-5 at an MOI of 0.1. Concentrations of wt HAdV-5 infectious particles (TCID50/mL) were measured at timepoints 0 (D0), 48 h (D2), 96 h (D4), and 144 h (D6). Data were derived from a total of 3 experiments and display mean ± standard deviations. **** (<span class="html-italic">p</span> &lt; 0.0001). Significances in green: 6xNT+EGFP vs. 6xpTP-mi5+EGFP; significances in red: 6xNT+AGO2 vs. 6xpTP-mi5+AGO2. (<b>B</b>) In a therapeutic treatment scenario 1.5 × 10<sup>4</sup> HeLa cells underwent concomitant transduction and infection with vectors at an MOI of 100 as well as HAdV-5 at an MOI of 0.1, respectively. Concentrations of wt HAdV-5 infectious particles (TCID50/mL) were measured at timepoints 0 (D0), 48 h (D2), 96 h (D4), and 144 h (D6). Data were derived from a total of 3 experiments and display mean ± standard deviations. **** (<span class="html-italic">p</span> &lt; 0.0001); ** (<span class="html-italic">p</span> &lt; 0.01); * (<span class="html-italic">p</span> &lt; 0.05). Significances in green: 6xNT+EGFP vs. 6xpTP-mi5+EGFP; significances in red: 6xNT+AGO2 vs. 6xpTP-mi5+AGO2.</p>
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15 pages, 4347 KiB  
Article
DNA Hypomethylation Underlies Epigenetic Swapping between AGO1 and AGO1-V2 Isoforms in Tumors
by Jean S. Fain, Camille Wangermez, Axelle Loriot, Claudia Denoue and Charles De Smet
Epigenomes 2024, 8(3), 24; https://doi.org/10.3390/epigenomes8030024 - 22 Jun 2024
Viewed by 1930
Abstract
Human tumors progress in part by accumulating epigenetic alterations, which include gains and losses of DNA methylation in different parts of the cancer cell genome. Recent work has revealed a link between these two opposite alterations by showing that DNA hypomethylation in tumors [...] Read more.
Human tumors progress in part by accumulating epigenetic alterations, which include gains and losses of DNA methylation in different parts of the cancer cell genome. Recent work has revealed a link between these two opposite alterations by showing that DNA hypomethylation in tumors can induce the expression of transcripts that overlap downstream gene promoters and thereby induce their hypermethylation. Preliminary in silico evidence prompted us to investigate if this mechanism applies to the locus harboring AGO1, a gene that plays a central role in miRNA biogenesis and RNA interference. Inspection of public RNA-Seq datasets and RT-qPCR experiments show that an alternative transcript starting 13.4 kb upstream of AGO1 (AGO1-V2) is expressed specifically in testicular germ cells, and becomes aberrantly activated in different types of tumors, particularly in tumors of the esophagus, stomach, and lung. This expression pattern classifies AGO1-V2 into the group of “Cancer-Germline” (CG) genes. Analysis of transcriptomic and methylomic datasets provided evidence that transcriptional activation of AGO1-V2 depends on DNA demethylation of its promoter region. Western blot experiments revealed that AGO1-V2 encodes a shortened isoform of AGO1, corresponding to a truncation of 75 aa in the N-terminal domain, and which we therefore referred to as “∆NAGO1”. Interestingly, significant correlations between hypomethylation/activation of AGO1-V2 and hypermethylation/repression of AGO1 were observed upon examination of tumor cell lines and tissue datasets. Overall, our study reveals the existence of a process of interdependent epigenetic alterations in the AGO1 locus, which promotes swapping between two AGO1 protein-coding mRNA isoforms in tumors. Full article
(This article belongs to the Special Issue New Insights into Epigenetic Regulation in Cancer)
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Figure 1

Figure 1
<p><span class="html-italic">AGO1-V2</span> structure and germline-specific expression. (<b>A</b>) RNA-Seq data of tissues were analyzed with IGV. Positions of transcription start sites (broken arrows) and exons (boxes) of the two transcript isoforms are depicted. (<b>B</b>) Expression profiles of <span class="html-italic">AGO1-V2</span> and <span class="html-italic">AGO1</span> mRNAs in normal human tissues, based on GTEx junction expression analyses. (<b>C</b>) RT-qPCR analysis of <span class="html-italic">AGO1-V2</span> and <span class="html-italic">AGO1</span> mRNAs (normalized to <span class="html-italic">ACTB</span> mRNA levels × 10,000). (<b>D</b>) Mean relative mRNA levels of indicated genes were calculated from RNA-Seq data of control and germ cell-free NOA testis samples. Student’s <span class="html-italic">t</span>-test with adjusted <span class="html-italic">p</span> value (****: <span class="html-italic">p</span> ≤ 0.0001; **: <span class="html-italic">p</span> ≤ 0.01; ns: not significant).</p>
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<p><span class="html-italic">AGO1-V2</span> expression analysis in tumor tissues and cell lines. (<b>A</b>) RNA-Seq data from the TCGA were downloaded and reads matching the specific 5′-exon of <span class="html-italic">AGO1-V2</span> were counted to evaluate its expression level: dots represent log2(RPKM + 1) in each of the normal (green) and tumor (black) tissue samples. Numbers below indicate number of samples. Tumor types are ordered according to frequency (indicated above the graph) of <span class="html-italic">AGO1-V2</span> transcriptional activation (considered positive when RPKM was ≥0.5, as indicated by the red dotted line). Welch’s <span class="html-italic">t</span>-test with adjusted <span class="html-italic">p</span> value was used to analyze differences in expression levels between normal and tumors (****: <span class="html-italic">p</span> ≤ 0.0001; ***: <span class="html-italic">p</span> ≤ 0.001; **: <span class="html-italic">p</span> ≤ 0.01; *: <span class="html-italic">p</span> ≤ 0.05; ns: not significant). (<b>B</b>) IGV analysis of RNA-Seq data from tumor cell lines that do not or do show expression of <span class="html-italic">AGO1-V2</span>. (<b>C</b>) Frequency (%) of <span class="html-italic">AGO1-V2</span> activation in ESCA, STAD, and LUSC tumor cell lines was inferred from RNA-Seq data of the CCLE, using the same threshold as in (<b>A</b>).</p>
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<p><span class="html-italic">AGO1-V2</span> encodes a truncated isoform of AGO1. (<b>A</b>) Schematic depiction of <span class="html-italic">left</span>, <span class="html-italic">AGO1</span> and <span class="html-italic">AGO1-V2</span> exons (boxes) and ORFs (bleu); <span class="html-italic">right</span>, expected domains (yellow) in the encoded protein. (<b>B</b>) Two cell lines expressing either <span class="html-italic">AGO1</span> (HEK293) or <span class="html-italic">AGO1-V2</span> (U2OS), as shown by RT-qPCR experiments, were used for Western blot analysis using antibodies directed against the C-terminal portion of AGO1 (anti-Vinculin was used as loading control). (<b>C</b>) U2OS cells were transfected with control siRNAs or siRNAs directed against all <span class="html-italic">AGO1</span> mRNA variants or only <span class="html-italic">AGO1-V2</span> (inhibition validated by RT-qPCR, <span class="html-italic">n</span> = 3, **: <span class="html-italic">p</span> ≤ 0.01, ANOVA test), and submitted to Western blot as in (<b>B</b>).</p>
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<p><span class="html-italic">AGO1-V2</span> transcription is correlated with promoter DNA demethylation. (<b>A</b>) Bisulfite-Seq data (NIH Roadmap epigenomics) revealing the methylation level of CpG sites (histograms) surrounding <span class="html-italic">AGO1-V2</span> and <span class="html-italic">AGO1</span> TSS (broken arrows) in normal tissues. (<b>B</b>) Methylomic (RRBS) and transcriptomic (RNA-Seq) datasets of indicated types of tumor cell lines (CCLE) were downloaded to evaluate correlation between levels of <span class="html-italic">AGO1-V2</span> promoter methylation (% methylation) and mRNA expression (log2(RPKM + 1)). Pearson’s correlation coefficient (<span class="html-italic">r</span>) with <span class="html-italic">p</span>-value (<span class="html-italic">p</span>) and linear regression line are shown. (<b>C</b>) Tumor tissue samples were analyzed as in B, except that datasets from the TCGA interrogate the methylation level (ß value) of only one CpG in the <span class="html-italic">AGO1-V2</span> promoter. Each dot corresponds to a normal (green) or tumor (black) tissue sample. (<b>D</b>) RNA-Seq data from two tumor cell lines treated or not with 5-aza-2′-deoxycytidine (5-azadC) were downloaded and analyzed with IGV. Positions of <span class="html-italic">AGO1-V2</span> and <span class="html-italic">AGO1</span> TSS are indicated (broken arrows).</p>
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<p>Activation of <span class="html-italic">AGO1-V2</span> is correlated with <span class="html-italic">AGO1</span> promoter hypermethylation and transcriptional repression. (<b>A</b>) Methylomic datasets (RRBS, CCLE) were downloaded to evaluate correlation between <span class="html-italic">AGO1-V2</span> and <span class="html-italic">AGO1</span> promoter mean methylation levels (%) in each tumor cell line. Pearson’s correlation coefficient (<span class="html-italic">r</span>) with <span class="html-italic">p</span>-value (<span class="html-italic">p</span>) and linear regression line are shown. A color code indicates the level of <span class="html-italic">AGO1</span> mRNA expression (log2(RPKM + 1)) in tumor cell lines. (<b>B</b>) Tumor tissue samples (TCGA) of indicated types were divided into two groups according to <span class="html-italic">AGO1-V2</span> expression status (positive: RPKM ≥ 0.5; negative: &lt;0.5), and mean methylation levels (ß values) of CpGs surrounding <span class="html-italic">AGO1</span> start site (position relative to TSS) were compared. One-tailed Welch’s <span class="html-italic">t</span>-test with adjusted <span class="html-italic">p</span> value was used to assess significance of differences (***: <span class="html-italic">p</span> ≤ 0.001; **: <span class="html-italic">p</span> ≤ 0.01; *: <span class="html-italic">p</span> ≤ 0.05; ns: not significant). (<b>C</b>) TCGA tumor tissue samples were divided into <span class="html-italic">AGO1-V2</span> positive and negative groups as described in B, and mean <span class="html-italic">AGO1</span> mRNA expression levels were compared. One-tailed Student’s <span class="html-italic">t</span>-test, adjusted <span class="html-italic">p</span> value (***: <span class="html-italic">p</span> ≤ 0.001; **: <span class="html-italic">p</span> ≤ 0.01; *: <span class="html-italic">p</span> ≤ 0.05). (<b>D</b>) For each indicated tumor type, tumor tissue samples (TCGA) were divided into two groups according to <span class="html-italic">AGO1-V2</span> promoter CpG methylation status (hypomethylated: 10th percentile of ß value; methylated: 90th percentile), and mean mRNA expression levels (log2(RPKM + 1)) of either <span class="html-italic">AGO1</span> or <span class="html-italic">AGO1-V2</span> were compared. Paired <span class="html-italic">t</span>-test, adjusted <span class="html-italic">p</span> value (**: <span class="html-italic">p</span> ≤ 0.01).</p>
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13 pages, 3971 KiB  
Communication
Comprehensive Analysis of Antiphage Defense Mechanisms: Serovar-Specific Patterns
by Pavlo Petakh, Valentyn Oksenych, Yevheniya Khovpey and Oleksandr Kamyshnyi
Antibiotics 2024, 13(6), 522; https://doi.org/10.3390/antibiotics13060522 - 3 Jun 2024
Cited by 1 | Viewed by 1535
Abstract
Leptospirosis is a major zoonotic disease caused by pathogenic spirochetes in the genus Leptospira, affecting over a million people annually and causing approximately 60,000 deaths. Leptospira interrogans, a key causative agent, likely possesses defense systems against bacteriophages (leptophages), yet these systems are [...] Read more.
Leptospirosis is a major zoonotic disease caused by pathogenic spirochetes in the genus Leptospira, affecting over a million people annually and causing approximately 60,000 deaths. Leptospira interrogans, a key causative agent, likely possesses defense systems against bacteriophages (leptophages), yet these systems are not well understood. We analyzed 402 genomes of L. interrogans using the DefenseFinder tool to identify and characterize the antiphage defense systems. We detected 24 unique systems, with CRISPR-Cas (Clustered Regularly Interspaced Short Palindromic Repeats and CRISPR-associated proteins), PrrC, Borvo, and Restriction-Modification (R-M) being the most prevalent. Notably, Cas were identified in all strains, indicating their central role in phage defense. Furthermore, there were variations in the antiphage system distribution across different serovars, suggesting unique evolutionary adaptations. For instance, Retron was found exclusively in the Canicola serovar, while prokaryotic Argonaute proteins (pAgo) were only detected in the Grippotyphosa serovar. These findings significantly enhance our understanding of Leptospira’s antiphage defense mechanisms. They reveal the potential for the development of serovar-specific phage-based therapies and underscore the importance of further exploring these defense systems. Full article
(This article belongs to the Special Issue Antibiotics vs. Phage Therapy, 2nd Edition)
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Figure 1

Figure 1
<p>Tree inferred with FastME 2.1.6.1 from GBDP distances calculated from genome sequences. The branch lengths are scaled in terms of GBDP distance formula d5. The numbers above the branches are GBDP pseudo-bootstrap support values &gt; 60% from 100 replications, with average branch support of 62.9%. The tree was rooted at the midpoint.</p>
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<p>Voronoi treemaps of antiphage defense system distribution. In total, we identified 24 antiphage systems. Four major antiphage systems are present in the vast majority of strains, namely Cas, PrrC, Borvo, and R-M. The image was generated using SrPlot (<a href="https://www.bioinformatics.com.cn/" target="_blank">https://www.bioinformatics.com.cn/</a>, accessed on 12 January 2024). Voronoi treemaps visualize hierarchical data by recursively partitioning convex polygons using weighted centroidal Voronoi diagrams. The polygon areas are proportional to the relative weights of their corresponding nodes. The size of each polygon indicates the frequency of the corresponding antiphage system. The clustering within the treemap represents the hierarchical relationships among different antiphage systems, and the color scale is used to differentiate between various systems and their prevalence.</p>
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<p>Distribution of defense systems across 6 main serovars (Venn diagram). The most diverse system was found for serovar Copenhageni (n = 15) and serovar Pyrogenes (n = 13), while the least diverse system was found for serovar Icterohemorrhagiae (n = 8). The images were generated using jvenn [<a href="#B27-antibiotics-13-00522" class="html-bibr">27</a>].</p>
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<p>Heatmap of the distribution of defense systems across 6 main serovars. The Cas system stands out for its uniform presence across all serovars, indicating its widespread occurrence as a defense mechanism with a 100% (1.0) frequency. Conversely, certain antiphage systems, such as Retron, Shedu, PD-T4-7, Dsr, pAgo, CBASS, Lamassu-Fam, PD-T4-1, Wadjet, AVAST, and RloC, demonstrate lower frequencies and are occasionally exclusive to specific serovars. The images were generated using SrPlot.</p>
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<p>General outline of leptospiral defense strategies targeting different stages of the leptophage cycle. Leptospira strains possess various anti-leptophage systems, such as CRISPR-Cas, R-M, pAgo, and Shedu, which affect DNA degradation. Additionally, they exhibit antiphage systems that lead to abortive infection, as exemplified by Borvo and Shosta. The images were generated using BioRender (<a href="https://www.biorender.com" target="_blank">https://www.biorender.com</a>, accessed on 12 January 2024).</p>
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