[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
You seem to have javascript disabled. Please note that many of the page functionalities won't work as expected without javascript enabled.
 
 
Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

Article Types

Countries / Regions

Search Results (111)

Search Parameters:
Keywords = ribosome methylation

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
15 pages, 1736 KiB  
Review
Emerging Roles of m7G-Cap Hypermethylation and Nuclear Cap-Binding Proteins in Bypassing Suppression of eIF4E-Dependent Translation
by Kathleen Boris-Lawrie, Jessica Liebau, Abdullgadir Hayir and Xiao Heng
Viruses 2025, 17(3), 372; https://doi.org/10.3390/v17030372 - 5 Mar 2025
Viewed by 120
Abstract
Translation regulation is essential to the survival of hosts. Most translation initiation falls under the control of the mTOR pathway, which regulates protein production from mono-methyl-guanosine (m7G) cap mRNAs. However, mTOR does not regulate all translation; hosts and viruses alike employ alternative pathways, [...] Read more.
Translation regulation is essential to the survival of hosts. Most translation initiation falls under the control of the mTOR pathway, which regulates protein production from mono-methyl-guanosine (m7G) cap mRNAs. However, mTOR does not regulate all translation; hosts and viruses alike employ alternative pathways, protein factors, and internal ribosome entry sites to bypass mTOR. Trimethylguanosine (TMG)-caps arise from hypermethylation of pre-existing m7G-caps by the enzyme TGS1 and are modifications known for snoRNA, snRNA, and telomerase RNA. New findings originating from HIV-1 research reveal that TMG-caps are present on mRNA and license translation via an mTOR-independent pathway. Research has identified TMG-capping of selenoprotein mRNAs, junD, TGS1, DHX9, and retroviral transcripts. TMG-mediated translation may be a missing piece for understanding protein synthesis in cells with little mTOR activity, including HIV-infected resting T cells and nonproliferating cancer cells. Viruses display a nuanced interface with mTOR and have developed strategies that take advantage of the delicate interplay between these translation pathways. This review covers the current knowledge of the TMG-translation pathway. We discuss the intimate relationship between metabolism and translation and explore how this is exploited by HIV-1 in the context of CD4+ T cells. We postulate that co-opting both translation pathways provides a winning strategy for HIV-1 to dictate the sequential synthesis of its proteins and balance viral production with host cell survival. Full article
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Discovery timeline of TMG-capped RNAs in humans and viruses. (<b>a</b>) Chemical structures of mono-methyl guanosine (m7G)- and trimethylguanosine (m2,2,7G, TMG)-caps attached to the transcription start site. Pre-existing m7G-caps are hypermethylated to m2,2,7G-cap by trimethylguanosine synthase 1 (TGS1). Methyl groups: blue, at the 7-position of the m7G-cap; red, at the 2,2 positions of the TMG-cap. (<b>b</b>) Timeline of publications. Human RNAs: snRNA in 1983 [<a href="#B10-viruses-17-00372" class="html-bibr">10</a>,<a href="#B11-viruses-17-00372" class="html-bibr">11</a>,<a href="#B12-viruses-17-00372" class="html-bibr">12</a>] and snoRNA in 1987 [<a href="#B13-viruses-17-00372" class="html-bibr">13</a>,<a href="#B14-viruses-17-00372" class="html-bibr">14</a>]; in vitro translation of synthetic TMG-mRNA in 1988 [<a href="#B15-viruses-17-00372" class="html-bibr">15</a>]; telomerase RNA in 2004 [<a href="#B16-viruses-17-00372" class="html-bibr">16</a>]; host mRNAs in 2014 [<a href="#B17-viruses-17-00372" class="html-bibr">17</a>]. Viral RNAs: Sindbis in 1976 [<a href="#B8-viruses-17-00372" class="html-bibr">8</a>]; Semliki-Forest virus in 1986 [<a href="#B9-viruses-17-00372" class="html-bibr">9</a>]; HIV-1 in 2010 [<a href="#B7-viruses-17-00372" class="html-bibr">7</a>]. Specialized translation licensed by TMG-cap was characterized in 2022.</p>
Full article ">Figure 2
<p>Pathways for host translation initiation. (<b>a</b>) eIF4E binds the m7G-cap, which recruits eIF4G and eIF4A to form eIF4F. The 43S ribosome is recruited, scans the mRNA to find a start codon, and then recruits the 60S ribosomal subunit to form the 80S ribosome. (<b>b</b>) The internal ribosome entry sequence (IRES) within the 5′UTR experiences direct binding of 43S ribosome, followed by 60S ribosome joining. (<b>c</b>) TMG-mediated translation requires RNA helicase A/DHX9 (RHA) recognition of a three-way junction structure within the HIV 5′UTR for retention of the NCBP3/CBP80 heterodimer. Following 43S recruitment, either through ribosome scanning or internal ribosome entry, the 60S subunit joins to form the 80S complex, which initiates protein synthesis.</p>
Full article ">Figure 3
<p>Model for hypermethylation of HIV m7G-cap to m2,2,7G TMG-cap. The m7G-cap-binding complex (CBC) is composed of heterodimeric CBP80 (orange) and CBP20, which directly binds m7G-cap (mauve). RNA helicase A/DHX9 (RHA, tan) recognizes a three-way junction structure within the HIV 5′ untranslated region and facilitates the exchange of CBC to TGS1 (green). The m7G-TGS1 complex is shown with RHA binding the three-way junction for m7G hypermethylation to m2,2,7G (red, TMG-cap). The TGS1 binding pocket does not accommodate the bulkier TMG structure and is released. The TMG-CBP80/NCBP3 complex results from the cap exchange to NCBP3 (blue) and CBP80.</p>
Full article ">Figure 4
<p>Model for the HIV translation shift across T cell states. mTOR activity supports provirus formation, transcription and processing of viral transcripts. Translation of m7G-capped mRNA (blue) is synchronous with mTOR activity, whereas TMG-capped viral and host mRNAs engage in constitutive translation (red). As metabolic resources decline or antigen levels wane, mTOR inhibition Effector T cells progress toward a memory state. Translation of HIV m7G-capped mRNAs encoding regulatory proteins diminishes, limiting the viral burst size. Constitutive translation of residual TMG-capped Rev/RRE-dependent viral mRNAs sustains progeny virions, seeding the latent viral reservoir. New mTOR activity in reactivated Effector T cells reactivates productive viral infection and spread.</p>
Full article ">
13 pages, 996 KiB  
Article
Biosynthesis of a Novel Diketopiperazine Aspkyncin Incorporating a Kynurenine Unit from Aspergillus aculeatus
by Dekun Kong, Xin Wang and Li Liu
J. Fungi 2025, 11(3), 171; https://doi.org/10.3390/jof11030171 - 20 Feb 2025
Viewed by 359
Abstract
The simplest cyclo-peptides, also known as diketopiperazines (DKPs), are widespread in nature. The growing interest in these simplest cyclo-peptides is driven by their significant potential for therapeutic applications. In this study, we identified a biosynthetic gene cluster from Aspergillus aculeatus CRI323-04 through genome [...] Read more.
The simplest cyclo-peptides, also known as diketopiperazines (DKPs), are widespread in nature. The growing interest in these simplest cyclo-peptides is driven by their significant potential for therapeutic applications. In this study, we identified a biosynthetic gene cluster from Aspergillus aculeatus CRI323-04 through genome mining and heterologous expression in Aspergillus nidulans. The two core genes, aacA and aacB, within the gene cluster were characterized for their role in the biossoynthesis of aspkyncin, a novel DKP compound that incorporates a l-kynurenine (l-Kyn) unit. Furthermore, we successfully reconstituted the activities of the minimal bimodular non-ribosomal peptide synthetase (NRPS) AacA and the methyltransferase AacB both in vivo and in vitro. Our findings demonstrate that AacA catalyzes the condensation and cyclization of two non-proteinogenic amino acids, l-Kyn and N-methyl-l-alanine, to produce aspkyncin without the involvement of any release domain. Notably, the N-methyl-l-alanine is generated by a specialized l-alanine N-methyltransferase AacB prior to NRP assembly. This study reveals an unconventional pathway for the biosynthesis of fungal DKPs. Full article
(This article belongs to the Special Issue Discovery and Biosynthesis of Fungal Natural Products, 2nd Edition)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>The structures and activities of representative 2,5-diketopiperazines.</p>
Full article ">Figure 2
<p>(<b>A</b>) Schematic representation of the <span class="html-italic">aac</span> cluster and homologous gene clusters in <span class="html-italic">Aspergillus</span>. AacA: NRPS; AacB: methyltransferase (MT); AacC: cytochrome P450, AacD: amino-acid oxidase; AacE: hypothetical protein; AacF: transcription factor; AacG: carboxylesterase; IDO: indoleamine-2,3-dioxygenase. (<b>B</b>) Structure of 1 (aspkyncin). (<b>C</b>) <sup>1</sup>H−<sup>1</sup>H COSY and HMBC correlations in aspkyncin. (<b>D</b>) In vivo reconstitution of <span class="html-italic">aac</span>. Shown is HPLC analysis (λ = 366 nm) of metabolites extracted from 3-day cultures of (i) untransformed <span class="html-italic">A. nidulans</span> LO8030, (ii) <span class="html-italic">A. nidulans</span> LO8030 expressing AacA, (iii) <span class="html-italic">A. nidulans</span> LO8030 expressing AacAB, and (iv) <span class="html-italic">A. nidulans</span> LO8030 expressing AacABCDG.</p>
Full article ">Figure 3
<p>Characterization of AacB: (<b>A</b>) amino acid derivatization diagram; (<b>B</b>) in vitro reconstitution of AacB. Shown are LC-MS analyses of compounds from the extraction of reaction mixtures after Marfey’s method of (i) AacB + <span class="html-small-caps">l</span>-alanine, (ii) no enzyme control, (iii) <span class="html-italic">N</span>-methyl-<span class="html-small-caps">l</span>-alanine, and (iv) <span class="html-small-caps">l</span>-alanine.</p>
Full article ">Figure 4
<p>Characterization of AacA: (<b>A</b>) SDS-PAGE analyses of AacA (~194.3 kDa) with 8 × His-tag; (<b>B</b>) in vitro reconstitution of AacA. Shown are HPLC analyses (λ = 366 nm) of compounds from the extraction of reaction mixtures of (i) AacA + <span class="html-small-caps">l</span>-alanine + <span class="html-small-caps">l</span>-Kyn; (ii) AacA + AacB + <span class="html-small-caps">l</span>-alanine + <span class="html-small-caps">l</span>-Kyn; (iii) AacA + <span class="html-italic">N</span>-methyl-<span class="html-small-caps">l</span>-alanine + <span class="html-small-caps">l</span>-Kyn; (iv) no enzyme control (only <span class="html-italic">N</span>-methyl-<span class="html-small-caps">l</span>-alanine + <span class="html-small-caps">l</span>-Kyn in reaction buffer); and (v) standard of aspkyncin.</p>
Full article ">Figure 5
<p>The proposed biosynthetic pathway of aspkyncin.</p>
Full article ">
19 pages, 2821 KiB  
Article
Genetic Code Expansion for Controlled Surfactin Production in a High Cell-Density Bacillus subtilis Strain
by Alexander Hermann, Eric Hiller, Philipp Hubel, Lennart Biermann, Elvio Henrique Benatto Perino, Oscar Paul Kuipers, Rudolf Hausmann and Lars Lilge
Microorganisms 2025, 13(2), 353; https://doi.org/10.3390/microorganisms13020353 - 6 Feb 2025
Viewed by 829
Abstract
Background: In biotechnology, B. subtilis is established for heterologous protein production. In addition, the species provides a variety of bioactive metabolites, including the non-ribosomally produced surfactin lipopeptide. However, to control the formation of the target product-forming enzyme, different expression systems could be introduced, [...] Read more.
Background: In biotechnology, B. subtilis is established for heterologous protein production. In addition, the species provides a variety of bioactive metabolites, including the non-ribosomally produced surfactin lipopeptide. However, to control the formation of the target product-forming enzyme, different expression systems could be introduced, including the principle of genetic code expansion by the incorporation of externally supplied non-canonical amino acids. Methods: Integration of an amber stop codon into the srfA operon and additional chromosomal integration of an aminoacyl-tRNA synthetase/tRNA mutant pair from Methanococcus jannaschii enabled site-directed incorporation of the non-canonical amino acid O-methyl-L-tyrosine (OMeY). In different fed-batch bioreactor approaches, OMeY-associated surfactin production was quantified by high-performance thin-layer chromatography (HPTLC). Physiological adaptations of the B. subtilis production strain were analyzed by mass spectrometric proteomics. Results: Using a surfactin-forming B. subtilis production strain, which enables high cell density fermentation processes, the principle of genetic code expansion was introduced. Accordingly, the biosynthesis of the surfactin-forming non-ribosomal peptide synthetase (NRPS) was linked to the addition of the non-canonical amino acid OMeY. In OMeY-associated fed-batch bioreactor fermentation processes, a maximum surfactin titre of 10.8 g/L was achieved. In addition, the effect of surfactin induction was investigated by mass spectrometric proteome analyses. Among other things, adaptations in the B. subtilis motility towards a more sessile state and increased abundances of surfactin precursor-producing enzymes were detected. Conclusions: The principle of genetic code expansion enabled a precise control of the surfactin bioproduction as a representative of bioactive secondary metabolites in B. subtilis. This allowed the establishment of inducer-associated regulation at the post-transcriptional level with simultaneous use of the native promoter system. In this way, inductor-dependent control of the production of the target metabolite-forming enzyme could be achieved. Full article
Show Figures

Figure 1

Figure 1
<p>The principle of surfactin biosynthesis based on genetic code expansion. Under control conditions, a canonical amino acid (cAA) is incorporated into the nascent polypeptide chain, while the release factor (RF) recognizes the stop codons, such as the amber stop codon (UAG), which leads to an end of the translation process. By introducing an orthogonal aaRS/tRNA system, both the release factor and the incorporation of a non-canonical amino acid (ncAA) are able to target the amber stop codon.</p>
Full article ">Figure 2
<p>Validation of the correlation between surfactin production and the addition of OMeY. Shake flask cultures were performed using a mineral salt medium containing 8 g/L glucose and 0, 0.25, 0.5, 0.75 and 1 mM of OMeY. <span class="html-italic">B. subtilis</span> strain AH2 was cultured for 12 h. Samples were taken regularly for quantitative surfactin measurement. All cultivation approaches were performed in biological triplicates.</p>
Full article ">Figure 3
<p>Development of bioreactor processes with feeding strategies allowing OMeY-dependent surfactin production. The engineered <span class="html-italic">B. subtilis</span> surfactin production strain AH2 was cultivated in a batch fermentation until the glucose was depleted and the feeding process was started (black dashed line). When the culture reached an OD<sub>600</sub> of approximately 100, surfactin production was activated by adding OMeY as an inducer (red dashed line) at a final concentration of 0.75 mM (<b>a</b>) followed by volume-associated co-feeding (<b>b</b>). The entire bioreactor process was stopped when the 6-litre glucose feed solution was consumed.</p>
Full article ">Figure 4
<p>Proteome analysis regarding physiological adaptations based on OMeY-derived induction of surfactin production. (<b>a</b>) Heatmap without normalization as an overview of the protein signal intensities determined between the OMeY-induced and control time points. Volcano plots represent different groups of proteins, namely SrfA proteins for surfactin biosynthesis (<b>b</b>), enzymes for biosynthesis of branched-chain amino acids (<b>c</b>) and fatty acids (<b>d</b>), proteins associated with motility (<b>e</b>) and iron acquisition (<b>f</b>), and their changes in abundance after 10 (blue), 30 (green) and 60 min (red) of inducting surfactin production.</p>
Full article ">Figure 4 Cont.
<p>Proteome analysis regarding physiological adaptations based on OMeY-derived induction of surfactin production. (<b>a</b>) Heatmap without normalization as an overview of the protein signal intensities determined between the OMeY-induced and control time points. Volcano plots represent different groups of proteins, namely SrfA proteins for surfactin biosynthesis (<b>b</b>), enzymes for biosynthesis of branched-chain amino acids (<b>c</b>) and fatty acids (<b>d</b>), proteins associated with motility (<b>e</b>) and iron acquisition (<b>f</b>), and their changes in abundance after 10 (blue), 30 (green) and 60 min (red) of inducting surfactin production.</p>
Full article ">
17 pages, 11911 KiB  
Article
Cooperative and Independent Functionality of tmRNA and SmpB in Aeromonas veronii: A Multifunctional Exploration Beyond Ribosome Rescue
by Taipeng Bai, Juanjuan Li, Xue Chi, Hong Li, Yanqiong Tang, Zhu Liu and Xiang Ma
Int. J. Mol. Sci. 2025, 26(1), 409; https://doi.org/10.3390/ijms26010409 - 6 Jan 2025
Viewed by 686
Abstract
The trans-translation system, mediated by transfer-messenger RNA (tmRNA, encoded by the ssrA gene) and its partner protein SmpB, helps to release ribosomes stalled on defective mRNA and targets incomplete protein products for hydrolysis. Knocking out the ssrA and smpB genes in various pathogens [...] Read more.
The trans-translation system, mediated by transfer-messenger RNA (tmRNA, encoded by the ssrA gene) and its partner protein SmpB, helps to release ribosomes stalled on defective mRNA and targets incomplete protein products for hydrolysis. Knocking out the ssrA and smpB genes in various pathogens leads to different phenotypic changes, indicating that they have both cooperative and independent functionalities. This study aimed to clarify the functional relationships between tmRNA and SmpB in Aeromonas veronii, a pathogen that poses threats in aquaculture and human health. We characterized the expression dynamics of the ssrA and smpB genes at different growth stages of the pathogen, assessed the responses of deletion strains ΔssrA and ΔsmpB to various environmental stressors and carbon source supplementations, and identified the gene-regulatory networks involving both genes by integrating transcriptomic and phenotypic analyses. Our results showed that the gene ssrA maintained stable expression throughout the bacterial growth period, while smpB exhibited upregulated expression in response to nutrient deficiencies. Compared to the wild type, both the ΔssrA and ΔsmpB strains exhibited attenuated resistance to most stress conditions. However, ΔssrA independently responded to starvation, while ΔsmpB specifically showed reduced resistance to lower concentrations of Fe3+ and higher concentrations of Na+ ions, as well as increased utilization of the carbon source β-Methyl-D-glucoside. The transcriptomic analysis supported these phenotypic results, demonstrating that tmRNA and SmpB cooperate under nutrient-deficient conditions but operate independently in nutrient-rich environments. Phenotypic experiments confirmed that SsrA and SmpB collaboratively regulate genes involved in siderophore synthesis and iron uptake systems in response to extracellular iron deficiency. The findings of the present study provide crucial insights into the functions of the trans-translation system and highlight new roles for tmRNA and SmpB beyond trans-translation. Full article
(This article belongs to the Section Molecular Biology)
Show Figures

Figure 1

Figure 1
<p>The genes <span class="html-italic">ssrA</span> and <span class="html-italic">smpB</span> exhibit different expression patterns in response to nutrient deficiency. RT-qPCR was used to determine the relative expression levels of <span class="html-italic">ssrA</span> (<b>A</b>,<b>C</b>) or <span class="html-italic">smpB</span> (<b>B</b>,<b>D</b>) at different times under LB conditions (<b>A</b>,<b>B</b>) or M9 conditions (<b>C</b>,<b>D</b>). Tukey’s post-test was used for statistical analysis, with ** representing <span class="html-italic">p</span> &lt; 0.01 and *** representing <span class="html-italic">p</span> &lt; 0.005 in one-way ANOVA.</p>
Full article ">Figure 2
<p>tmRNA and SmpB cooperate or independently participate in the responses to starvation, osmotic pressure, and low iron stress. For the determination of the growth curve, the bacteria were transferred to standard LB medium (<b>A</b>, right panel) or LB medium supplemented with 200 μM 2,2′-bipyridine (<b>C</b>, right panel) or 0.5 M sodium chloride (<b>D</b>, right panel). Data are presented as the mean ± SD from three replicates. For the plate experiment, after the overnight culture was washed with PBS, a ten-fold serial dilution of the bacterial suspension was prepared, and 3 μL of each dilution was spotted onto LB agar plates supplemented with different concentrations of 2,2’-bipyridine (<b>C</b>, left panel) or sodium chloride (<b>D</b>, left panel). For the starvation treatments, bacterial suspensions were allowed to stand in PBS buffer and dotted on LB plates after 24 h or 72 h (<b>B</b>).</p>
Full article ">Figure 3
<p>tmRNA and SmpB participate in the metabolism of different types of carbon sources cooperatively or independently. WT, Δ<span class="html-italic">tmRNA</span>, and Δ<span class="html-italic">smpB</span> were inoculated on a BIOLOG ECO microplate at 30 °C with L-aspartate (<b>A</b>), β-Methyl-D-glucoside (<b>B</b>), D-mannitol (<b>C</b>), and Tween 40 (<b>D</b>) as the sole carbon sources. The absorption values were recorded at 590 nm at an interval of 24 h. Data are presented as the mean ± SD from three replicates. Tukey’s post-test was used for statistical analysis, with * representing <span class="html-italic">p</span> &lt; 0.05 and ** representing <span class="html-italic">p</span> &lt; 0.01 in one-way ANOVA.</p>
Full article ">Figure 4
<p>tmRNA and SmpB exhibit enhanced collaboration under nutrient deficiency conditions, but show significant independence in nutrient enrichment conditions. Total numbers of differential genes of Δ<span class="html-italic">smpB</span> or Δ<span class="html-italic">ssrA</span> compared with wild type were analyzed through histogram (<b>A</b>,<b>B</b>) or Venn analysis (<b>C</b>,<b>D</b>) under LB medium (<b>A</b>,<b>C</b>) or M9 medium (<b>B</b>,<b>D</b>) conditions.</p>
Full article ">Figure 5
<p>Functional enrichment analysis of DEGs based on the KEGG database. Top 20 statistics of pathway enrichment for Δ<span class="html-italic">ssrA</span> vs. WT (<b>A</b>,<b>C</b>) and Δ<span class="html-italic">smpB</span> vs. WT (<b>B</b>,<b>D</b>) in LB medium (<b>A</b>,<b>B</b>) and M9 medium (<b>C</b>,<b>D</b>).</p>
Full article ">Figure 5 Cont.
<p>Functional enrichment analysis of DEGs based on the KEGG database. Top 20 statistics of pathway enrichment for Δ<span class="html-italic">ssrA</span> vs. WT (<b>A</b>,<b>C</b>) and Δ<span class="html-italic">smpB</span> vs. WT (<b>B</b>,<b>D</b>) in LB medium (<b>A</b>,<b>B</b>) and M9 medium (<b>C</b>,<b>D</b>).</p>
Full article ">Figure 6
<p>A model of the changes in cellular processes in Δ<span class="html-italic">ssrA</span> (<b>A</b>) and Δ<span class="html-italic">smpB</span> (<b>B</b>) as compared with the wild type based on the highly enriched pathways under M9 culture conditions. Red, green, and black marked genes indicate those with significant upregulation (FC &gt; 2 and <span class="html-italic">p</span>-value &lt; 0.05), significant downregulation (FC &lt; 0.5 and <span class="html-italic">p</span>-value &lt; 0.05), and no significant regulation (0.5 ≤ FC ≤ 2 or <span class="html-italic">p</span>-value ≥ 0.05), respectively.</p>
Full article ">Figure 7
<p>tmRNA and SmpB cooperatively regulate siderophore synthesis. RT-qPCR validation of genes involved in siderophore synthesis in Δ<span class="html-italic">ssrA</span> (<b>A</b>) and Δ<span class="html-italic">smpB</span> (<b>B</b>). Qualitative and quantitative analysis of siderophore formation. For qualitative analysis (<b>C</b>), 5 μL bacterial suspensions were cultured on CAS agar plates at 30 °C for 5 days. The yellow halo shows that siderophores produced by bacteria can strip the blue complex formed by cas and Fe<sup>3+</sup> from the medium, and the wild type produces a darker yellow halo. For quantitative analysis (<b>D</b>), the bacteria were cultured in LB medium for 36 h, followed by centrifugation at 10,000 rpm for 10 min. Then, 100 μL supernatant was mixed with an equal volume of cas detection solution, and the absorption value at 630 nm was measured after standing in the dark for 1 h. Error bars represent standard deviations of triplicate experiments. Tukey’s post-test was used to assess statistical significance, with *** representing <span class="html-italic">p</span> &lt; 0.005 in one-way ANOVA.</p>
Full article ">
20 pages, 4089 KiB  
Article
Epigenetic and Cellular Reprogramming of Doxorubicin-Resistant MCF-7 Cells Treated with Curcumin
by Paola Poma, Salvatrice Rigogliuso, Manuela Labbozzetta, Aldo Nicosia, Salvatore Costa, Maria Antonietta Ragusa and Monica Notarbartolo
Int. J. Mol. Sci. 2024, 25(24), 13416; https://doi.org/10.3390/ijms252413416 - 14 Dec 2024
Viewed by 986
Abstract
The MCF-7R breast cancer cell line, developed by treating the parental MCF-7 cells with increasing doses of doxorubicin, serves as a model for studying acquired multidrug resistance (MDR). MDR is a major challenge in cancer therapy, often driven by overexpression of the efflux [...] Read more.
The MCF-7R breast cancer cell line, developed by treating the parental MCF-7 cells with increasing doses of doxorubicin, serves as a model for studying acquired multidrug resistance (MDR). MDR is a major challenge in cancer therapy, often driven by overexpression of the efflux pump P-glycoprotein (P-gp) and epigenetic modifications. While many P-gp inhibitors show promise in vitro, their nonspecific effects on the efflux pump limit in vivo application. Curcumin, a natural compound with pleiotropic action, is a nontoxic P-gp inhibitor capable of modulating multiple pathways. To explore curcumin’s molecular effects on MCF-7R cells, we analyzed the expression of genes involved in DNA methylation and transcription regulation, including ABCB1/MDR1. Reduced representation bisulfite sequencing further unveiled key epigenetic changes induced by curcumin. Our findings indicate that curcumin treatment not only modulates critical cellular processes, such as ribosome biogenesis and cytoskeletal dynamics, but also reverses the resistant phenotype, toward that of sensitive cells. This study highlights curcumin’s potential as an adjuvant therapy to overcome chemoresistance, offering new avenues for pharmacological strategies targeting epigenetic regulation to re-sensitize resistant cancer cells. Full article
(This article belongs to the Special Issue The Role of Omics in Cancer Diagnosis and Treatment)
Show Figures

Figure 1

Figure 1
<p>Western blotting analysis of P-gp levels. Cells were treated with curcumin (30 µM) for 24 h. “CTR” refers to the MCF-7 doxorubicin-resistant cells and “CUR” refers to the MCF-7 doxorubicin-resistant cells treated with curcumin for 24 h. The results are expressed as the mean ± standard error of two different experiments. Differences when treatment is compared to control: * <span class="html-italic">p</span> &lt; 0.05 (one-way ANOVA followed by Tukey’s test).</p>
Full article ">Figure 2
<p>Evaluation of P-gp mRNA expression levels by qRT-PCR. For each condition, N = 3 technical replicates were used. Data are expressed as mean ± standard error of two experiments. Cells were treated with curcumin (30 µM) at the indicated time. ** (<span class="html-italic">p</span> &lt; 0.01) represent significant differences among the times (one-way ANOVA followed by Tukey’s test).</p>
Full article ">Figure 3
<p>Reduced representation bisulfite sequencing (RRBS) results. Statistical analysis of global data of a representative MCF-7R untreated cell line (R1, (<b>a</b>)) and an MCF-7R sample treated with curcumin (RC2, (<b>b</b>)).</p>
Full article ">Figure 4
<p>Annotations of all DMRs (aggregated DMCs and tiles). (<b>A</b>) CpG island annotation, (<b>B</b>) ENCODE candidate Cis-Regulatory Elements annotation, (<b>C</b>) gene annotation, (<b>D</b>) gene class annotation.</p>
Full article ">Figure 5
<p>GO enrichment analysis performed on 33 differentially methylated genes belonging to Chromatin or Chromosome GO terms.</p>
Full article ">Figure 6
<p>Distribution of differentially methylated CpGs per chromosome.</p>
Full article ">Figure 7
<p>UCSC genome browser view of the 45S ribosomal DNA. This gene represents a copy of the 45S ribosomal RNA on chromosome 21 (chr21:8,204,556–8,220,997). The 45S rDNA repeat unit encodes a 45S rRNA precursor, transcribed by RNA polymerase I, which is processed to form the 18S, 5.8S and 28S rRNAs. Under the chromosome scale, the following are shown: RRBS data (methylation difference R-S: significant DMCs, 200 bp tiles and 100 bp tiles; methylation difference RC-R: significant DMCs, 200 bp tiles and 100 bp tiles), HUGO gene annotation, CGI, Fantom5 CAGE peaks (mapped TSS: total counts in several cell types and MCF-7 data—forward in red and reverse in blue), ReMap Atlas of Regulatory Regions filtered by MCF-7, and DNAseI hypersensitivity in MCF-7.</p>
Full article ">Figure 8
<p>UCSC genome browser view of the 5S ribosomal DNA locus. In this region, there are 17 copies of the 5S ribosomal RNA (chr1:228,607,600–228,650,600). The 5S rDNA is transcribed by RNA polymerase III. On the right, the upstream TSS for RHOU is visible. Under the chromosome scale, the following are shown: RRBS data (methylation difference R-S: significant DMCs, 200 bp tiles and 100 bp tiles; methylation difference RC-R: significant DMCs, 200 bp tiles and 100 bp tiles), HUGO gene annotation, CGI, ENCODE cCRE, Fantom5 CAGE peaks (mapped TSS: total counts in several cell types and MCF-7 data—forward in red and reverse in blue), ReMap Atlas of Regulatory Regions complete and filtered by MCF-7, and DNAseI hypersensitivity in MCF-7.</p>
Full article ">Figure 9
<p>UCSC genome browser view of the differentially methylated CGI on chromosome 1 containing 23 tRNA genes (chr1: 161,440,000–161,472,000). Transfer RNA precursors are transcribed by RNA polymerase III. Under the chromosome scale, the following are shown: RRBS data (methylation difference R-S: significant DMCs, 200 bp tiles and 100 bp tiles; methylation difference RC-R: significant DMCs, 200 bp tiles and 100 bp tiles), HUGO gene annotation, CGI, CTCF binding sites in MCF-7, and cCRE (CTCF-only ENCODE Classification is blue).</p>
Full article ">Figure 10
<p>Results of RT-qPCR experiments performed on <span class="html-italic">ABCB1</span> regulators and chromatin regulators. ***: <span class="html-italic">p</span> value &lt; 0.0005, *: <span class="html-italic">p</span> value &lt; 0.05.</p>
Full article ">
18 pages, 5747 KiB  
Article
Comparative Transcriptome Analysis of Non-Organogenic and Organogenic Tissues of Gaillardia pulchella Revealing Genes Regulating De Novo Shoot Organogenesis
by Yashika Bansal, A. Mujib, Mahima Bansal, Mohammad Mohsin, Afeefa Nafees and Yaser Hassan Dewir
Horticulturae 2024, 10(11), 1138; https://doi.org/10.3390/horticulturae10111138 - 25 Oct 2024
Viewed by 1020
Abstract
Gaillardia pulchella is an important plant species with pharmacological and ornamental applications. It contains a wide array of phytocompounds which play roles against diseases. In vitro propagation requires callogenesis and differentiation of plant organs, which offers a sustainable, alternative synthesis of compounds. The [...] Read more.
Gaillardia pulchella is an important plant species with pharmacological and ornamental applications. It contains a wide array of phytocompounds which play roles against diseases. In vitro propagation requires callogenesis and differentiation of plant organs, which offers a sustainable, alternative synthesis of compounds. The morphogenetic processes and the underlying mechanisms are, however, known to be under genetic regulation and are little understood. The present study investigated these events by generating transcriptome data, with de novo assembly of sequences to describe shoot morphogenesis molecularly in G. pulchella. The RNA was extracted from the callus of pre- and post-shoot organogenesis time. The callus induction was optimal using leaf segments cultured onto MS medium containing α-naphthalene acetic acid (NAA; 2.0 mg/L) and 6-benzylaminopurine (BAP; 0.5 mg/L) and further exhibited a high shoot regeneration/caulogenesis ability. A total of 68,366 coding sequences were obtained using Illumina150bpPE sequencing and transcriptome assembly. Differences in gene expression patterns were noted in the studied samples, showing opposite morphogenetic responses. Out of 10,108 genes, 5374 (53%) were downregulated, and there were 4734 upregulated genes, representing 47% of the total genes. Through the heatmap, the top 100 up- and downregulating genes’ names were identified and presented. The up- and downregulated genes were identified using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. Important pathways, operative during G. pulchella shoot organogenesis, were signal transduction (13.55%), carbohydrate metabolism (8.68%), amino acid metabolism (5.11%), lipid metabolism (3.75%), and energy metabolism (3.39%). The synthesized proteins displayed phosphorylation, defense response, translation, regulation of DNA-templated transcription, carbohydrate metabolic processes, and methylation activities. The genes’ product also exhibited ATP binding, DNA binding, metal ion binding, protein serine/threonine kinase -, ATP hydrolysis activity, RNA binding, protein kinase, heme and GTP binding, and DNA binding transcription factor activity. The most abundant proteins were located in the membrane, nucleus, cytoplasm, ribosome, ribonucleoprotein complex, chloroplast, endoplasmic reticulum membrane, mitochondrion, nucleosome, Golgi membrane, and other organellar membranes. These findings provide information for the concept of molecular triggers, regulating programming, differentiation and reprogramming of cells, and their uses. Full article
(This article belongs to the Special Issue Plant Tissue and Organ Cultures for Crop Improvement in Omics Era)
Show Figures

Figure 1

Figure 1
<p>(<b>A</b>) Non-organogenic callus, and (<b>B</b>) organogenic callus of <span class="html-italic">G. pulchella</span> with arrow indicating the origin of shoot from the callus mass.</p>
Full article ">Figure 2
<p>Workflow and tools used for mRNA sequence analysis of non-organogenic and organogenic callus of <span class="html-italic">G. pulchella</span>.</p>
Full article ">Figure 3
<p>Length distribution of primary assembly and unigenes of <span class="html-italic">G. pulchella</span>.</p>
Full article ">Figure 4
<p>KEGG pathway classification for <span class="html-italic">G. pulchella</span>.</p>
Full article ">Figure 5
<p>Top hit species distribution pattern showing the number of genes identified in <span class="html-italic">G. pulchella</span> matching with the other plant species.</p>
Full article ">Figure 6
<p>Gene ontology annotation for all a ssembled unigenes in the <span class="html-italic">G. pulchella</span> transcriptome.</p>
Full article ">Figure 7
<p>Volcano plot showing the comparison of differential expressed genes.</p>
Full article ">Figure 8
<p>Heatmap representing the gene expression of the top 100 differentially expressed genes in the non-organogenic and organogenic calluses of <span class="html-italic">G. pulchella</span>.</p>
Full article ">Figure 9
<p>Principal component analysis (PCA) plot showing the relationship between the non-organogenic and organogenic calluses of <span class="html-italic">G. pulchella</span>.</p>
Full article ">
20 pages, 6865 KiB  
Review
R-Methylation in Plants: A Key Regulator of Plant Development and Response to the Environment
by Clément Barré-Villeneuve and Jacinthe Azevedo-Favory
Int. J. Mol. Sci. 2024, 25(18), 9937; https://doi.org/10.3390/ijms25189937 - 14 Sep 2024
Viewed by 1227
Abstract
Although arginine methylation (R-methylation) is one of the most important post-translational modifications (PTMs) conserved in eukaryotes, it has not been studied to the same extent as phosphorylation and ubiquitylation. Technical constraints, which are in the process of being resolved, may partly explain this [...] Read more.
Although arginine methylation (R-methylation) is one of the most important post-translational modifications (PTMs) conserved in eukaryotes, it has not been studied to the same extent as phosphorylation and ubiquitylation. Technical constraints, which are in the process of being resolved, may partly explain this lack of success. Our knowledge of R-methylation has recently evolved considerably, particularly in metazoans, where misregulation of the enzymes that deposit this PTM is implicated in several diseases and cancers. Indeed, the roles of R-methylation have been highlighted through the analyses of the main actors of this pathway: the PRMT writer enzymes, the TUDOR reader proteins, and potential “eraser” enzymes. In contrast, R-methylation has been much less studied in plants. Even so, it has been shown that R-methylation in plants, as in animals, regulates housekeeping processes such as transcription, RNA silencing, splicing, ribosome biogenesis, and DNA damage. R-methylation has recently been highlighted in the regulation of membrane-free organelles in animals, but this role has not yet been demonstrated in plants. The identified R-met targets modulate key biological processes such as flowering, shoot and root development, and responses to abiotic and biotic stresses. Finally, arginine demethylases activity has mostly been identified in vitro, so further studies are needed to unravel the mechanism of arginine demethylation. Full article
(This article belongs to the Special Issue Study on Post-translational Modifications of Protein)
Show Figures

Figure 1

Figure 1
<p>The different types of PRMTs and their structure. (<b>A</b>) Depiction of the different types of arginine methylations. MMA: monomethylation; aDMA: asymmetric dimethylation; sDMA: symmetric dimethylation. The production of dimethyl-R marks is a two-step process with an R-monomethylated intermediate form, illustrated here by the double red arrows [<a href="#B6-ijms-25-09937" class="html-bibr">6</a>]. (<b>B</b>) Linear representation of the different PRMTs of <span class="html-italic">Arabidopsis thaliana</span>. aa: amino acids, ZnF: zinc finger domain. Based on PROSITE database (<a href="https://prosite.expasy.org/" target="_blank">https://prosite.expasy.org/</a>, accessed on 31 May 2023). (<b>C</b>) The PRMT core is conserved in different PRMTs from different eukaryotes. Three-dimensional structures and linear depictions, from left to right: PRMT1 from <span class="html-italic">Rattus norvegicus</span>; PRMT10 from <span class="html-italic">A. thaliana</span>; PRMT5 from <span class="html-italic">Caenorhabditis elegans</span>. The AdoMet-binding domain (purple) interacts with the methyl group donor molecule (AdoMet), and the active site of PRMT catalyses the transfer of the methyl group from AdoMet to the target arginine residue of the substrate [<a href="#B4-ijms-25-09937" class="html-bibr">4</a>,<a href="#B17-ijms-25-09937" class="html-bibr">17</a>]. The active site is in a hairpin loop located between the AdoMet-binding domain and the β-barrel domain (in green) [<a href="#B4-ijms-25-09937" class="html-bibr">4</a>]. The active-site-containing structure is generally called the “double-E loop” since the key residues of this catalytic domain are two glutamate (E) residues, which are highly conserved among PRMTs [<a href="#B4-ijms-25-09937" class="html-bibr">4</a>,<a href="#B16-ijms-25-09937" class="html-bibr">16</a>]. Finally, the last domain of the PRMT core, the dimerisation arm (in yellow), allows PRMT dimerisation, which is essential for PRMT activity [<a href="#B4-ijms-25-09937" class="html-bibr">4</a>,<a href="#B15-ijms-25-09937" class="html-bibr">15</a>,<a href="#B17-ijms-25-09937" class="html-bibr">17</a>]. The TIM-barrel domain (in pink) is only present in PRMT5 homologs. The linear depictions are scaled and the residue numbers bordering each domain are labelled. The 3D structures showed come from Zhang et al. (2003) [<a href="#B38-ijms-25-09937" class="html-bibr">38</a>], Cheng et al. (2011) [<a href="#B17-ijms-25-09937" class="html-bibr">17</a>], and Sun et al. (2011) [<a href="#B16-ijms-25-09937" class="html-bibr">16</a>].</p>
Full article ">Figure 2
<p>Overview of the roles of PRMTs in housekeeping mechanisms in the cell of <span class="html-italic">A. thaliana</span>. PRMT enzymes have been shown to be active as homodimers [<a href="#B17-ijms-25-09937" class="html-bibr">17</a>,<a href="#B38-ijms-25-09937" class="html-bibr">38</a>]. Interestingly, in <span class="html-italic">A. thaliana</span>, PRMT4 and PRMT1, which are duplicated as PRMT1a and PRMT1b, and PRMT4a and PRMT4b, respectively, form heterodimers [<a href="#B10-ijms-25-09937" class="html-bibr">10</a>,<a href="#B44-ijms-25-09937" class="html-bibr">44</a>]. All the PRMTs are localised in both the nucleus and cytoplasm, except for PRMT6, which is only present in the nucleus [<a href="#B7-ijms-25-09937" class="html-bibr">7</a>,<a href="#B10-ijms-25-09937" class="html-bibr">10</a>,<a href="#B23-ijms-25-09937" class="html-bibr">23</a>,<a href="#B43-ijms-25-09937" class="html-bibr">43</a>,<a href="#B44-ijms-25-09937" class="html-bibr">44</a>,<a href="#B51-ijms-25-09937" class="html-bibr">51</a>]. All the PRMTs studied in <span class="html-italic">A. thaliana</span>, except PRMT3, can methylate arginine residues on histone. In this context, an arginine residue can be targeted by several type I enzymes, with the exception of the H4R3 residue, which can also be modified by the PRMT5 type II enzyme. Thus, H4R3 can be regulated by PRMT1, PRMT5, and PRMT10 [<a href="#B10-ijms-25-09937" class="html-bibr">10</a>,<a href="#B11-ijms-25-09937" class="html-bibr">11</a>,<a href="#B14-ijms-25-09937" class="html-bibr">14</a>]. Histone H3 can be regulated by PRMT4 (H3R2, H3R17, and H3R26) and PRMT6 (H3R2) [<a href="#B43-ijms-25-09937" class="html-bibr">43</a>,<a href="#B44-ijms-25-09937" class="html-bibr">44</a>]. Considering non-histone targets, PRMT1 can regulate the epigenetic regulator MBD7 [<a href="#B52-ijms-25-09937" class="html-bibr">52</a>] and the nucleolar enzyme FIB2 involved in rRNA maturation [<a href="#B10-ijms-25-09937" class="html-bibr">10</a>]. PRMT3 is involved in the production of functional ribosomes [<a href="#B23-ijms-25-09937" class="html-bibr">23</a>]. Along with histone regulation, the control of mRNA splicing is the other main focus of PRMT regulation and so far involves PRMT4 and PRMT5 [<a href="#B53-ijms-25-09937" class="html-bibr">53</a>,<a href="#B54-ijms-25-09937" class="html-bibr">54</a>]. With regard to the other post-transcriptional steps, PRMT5 has also been implicated in the regulation of RNA silencing through the symmetric dimethylation of AGO1 and AGO2 [<a href="#B34-ijms-25-09937" class="html-bibr">34</a>,<a href="#B35-ijms-25-09937" class="html-bibr">35</a>]. Interestingly, AGO1 can also be asymmetrically dimethylated by one or more unknown type I PRMT(s) [<a href="#B35-ijms-25-09937" class="html-bibr">35</a>]. Finally, PRMT5 may also be involved in DNA damage response [<a href="#B55-ijms-25-09937" class="html-bibr">55</a>]. The brown dashed arrows indicate a methylation shown only in vitro. The full brown arrows indicate an involvement. The double black arrows indicate a dual localisation in the cytoplasm and in the nucleus. The red and green circles indicate symmetric (sDMA) and asymmetric dimethylation on arginine (aDMA), respectively. The yellow circle indicates DNA methylation.</p>
Full article ">Figure 3
<p>Prediction of the structures of HsSND1 and AtTSN1. AlphaFold predicted 3D structures of (<b>A</b>) SND1 from <span class="html-italic">Homo sapiens</span> and (<b>B</b>) TSN1 from <span class="html-italic">A. thaliana</span>. The different conserved domains of the HsSND1 and AtTSN1 proteins are represented by different colours; from left to right, in light green, the first SN-like domain; in cyan, the second SN-like domain; in dark green, the third SN-like domain; in dark blue, the fourth SN-like domain; and in orange, the fifth SN-like domain, which is interrupted by the canonical Tudor domain, in purple. The residues forming the aromatic cage of the canonical Tudor domain are highlighted in yellow. The positions of the residues delimiting each domain are indicated on the linear representations below. They were obtained from the UniProt database (<a href="https://www.uniprot.org/uniprotkb" target="_blank">https://www.uniprot.org/uniprotkb</a> accessed on 31 May 2023) using Q8VZG7 TSN1_ARATH and Q7KZF4 SND1_HUMAN accessions and from information obtained in Shaw et al. (2007) [<a href="#B90-ijms-25-09937" class="html-bibr">90</a>]. The predicted 3D structures of AtTSN1 and HsSND1 are produced using AlphaFold version 2, Jumper et al. (2021) [<a href="#B91-ijms-25-09937" class="html-bibr">91</a>], and Varadi et al. (2022) [<a href="#B92-ijms-25-09937" class="html-bibr">92</a>]. The position of the residues forming the aromatic cage in HsSND1 comes from Liu et al. (2010) [<a href="#B84-ijms-25-09937" class="html-bibr">84</a>], while for AtTSN1, they were deduced from observation of the 3D structure of the canonical Tudor domain. SN: SN-like domain, aa: amino acids.</p>
Full article ">
18 pages, 3058 KiB  
Article
Increased Motility in Campylobacter jejuni and Changes in Its Virulence, Fitness, and Morphology Following Protein Expression on Ribosomes with Altered RsmA Methylation
by Agnieszka Sałamaszyńska-Guz, Małgorzata Murawska, Paweł Bącal, Agnieszka Ostrowska, Ewelina Kwiecień, Ilona Stefańska and Stephen Douthwaite
Int. J. Mol. Sci. 2024, 25(18), 9797; https://doi.org/10.3390/ijms25189797 - 10 Sep 2024
Viewed by 1389
Abstract
Infection with Campylobacter jejuni is the major cause of human gastroenteritis in the United States and Europe, leading to debilitating autoimmune sequelae in many cases. While considerable progress has been made in detailing the infectious cycle of C. jejuni, a full understanding [...] Read more.
Infection with Campylobacter jejuni is the major cause of human gastroenteritis in the United States and Europe, leading to debilitating autoimmune sequelae in many cases. While considerable progress has been made in detailing the infectious cycle of C. jejuni, a full understanding of the molecular mechanisms responsible for virulence remains to be elucidated. Here, we apply a novel approach by modulating protein expression on the pathogen’s ribosomes by inactivating a highly conserved rRNA methyltransferase. Loss of the RsmA methyltransferase results in a more motile strain with greater adhesive and cell-invasive properties. These phenotypical effects correlate with enhanced expression of specific proteins related to flagellar formation and function, together with enzymes involved in cell wall/membrane and amino acid synthesis. Despite the enhancement of certain virulent traits, the null strain grows poorly on minimal media and is rapidly out-competed by the wild-type strain. Complementation with an active copy of the rsmA gene rescues most of the traits changed in the mutant. However, the complemented strain overexpresses rsmA and displays new flaws, including loss of the spiral cell shape, which is distinctive for C. jejuni. Proteins linked with altered virulence and morphology are identified here by mass spectrometry proteomic analyses of the strains. Full article
(This article belongs to the Section Molecular Microbiology)
Show Figures

Figure 1

Figure 1
<p>Inactivation of <span class="html-italic">rsmA</span> in the <span class="html-italic">C. jejuni</span> chromosome. (<b>A</b>) <span class="html-italic">C. jejuni</span> 81-176 <span class="html-italic">rsmA</span> gene locus. The Δ<span class="html-italic">rsmA</span> mutant was constructed from the wild-type (WT) strain by deleting 10 bp of <span class="html-italic">rsmA</span> and inserting the <span class="html-italic">cat</span> (Cm<sup>R</sup>) cassette at the same site. In the complemented strain, Δ<span class="html-italic">rsmA::rsmA</span>, an active copy of the <span class="html-italic">rsmA</span> gene under its own promoter, was inserted together with the <span class="html-italic">aphA</span> (Km<sup>R</sup>) cassette at the intergenic region between <span class="html-italic">cjj0680</span> and <span class="html-italic">cjj0681</span> (lower right)<span class="html-italic">.</span> (<b>B</b>) Gel autoradiograms of primer extensions on 16S rRNA from WT (wild-type) strain, the Δ<span class="html-italic">rsmA</span> mutant strain, and the Δ<span class="html-italic">rsmA</span>::<span class="html-italic">rsmA</span> strain complemented with an active copy of <span class="html-italic">rsmA.</span> (<b>C</b>) Kasugamycin MIC determination in liquid cultures for WT, the <span class="html-italic">rsmA</span> mutant, and the complemented strains.</p>
Full article ">Figure 2
<p>Growth of <span class="html-italic">C. jejuni</span> strains in liquid medium. (<b>A</b>) Strains grown in MH broth at 37 °C. All strains started from an initial optical density (OD) of 0.02 and were measured after 12, 24, 48, and 72 h. There was no significant difference in the growth of strains in MH broth. (<b>B</b>) Strains grown in MH broth with a sub-inhibitory concentration of kasugamycin (400 µg mL<sup>−1</sup>): <span class="html-italic">p</span> &lt; 0.005 for WT versus Δ<span class="html-italic">rsmA</span> and <span class="html-italic">p</span> &lt; 0.05 for Δ<span class="html-italic">rsmA</span> versus Δ<span class="html-italic">rsmA::rsmA</span>. (<b>C</b>) Growth competition assay. The WT and Δ<span class="html-italic">rsmA</span> strains were grown together through four 24 h cycles in MH broth with and without kasugamycin at 400 µg mL<sup>−1</sup>. The proportion of each strain was determined by PCR with one of the primers fluorescently labeled. Upper row, no drug; lower row, with kasugamycin. Each data set is representative of a minimum of three growth assays. (<b>D</b>) Strains grown in the minimal medium MCLMAN: after 24, 48, and 72 h, <span class="html-italic">p</span> &lt; 0.001 for WT versus Δ<span class="html-italic">rsmA</span>; no significant difference was observed for Δ<span class="html-italic">rsmA</span> versus Δ<span class="html-italic">rsmA::rsmA</span>. (<b>E</b>) Strains grown in the MCLAN medium: after 24, 48, and 72 h, <span class="html-italic">p</span> &lt; 0.001 for WT versus Δ<span class="html-italic">rsmA</span> and <span class="html-italic">p</span> &lt; 0.05 for Δ<span class="html-italic">rsmA</span> versus Δ<span class="html-italic">rsmA::rsmA</span>. (<b>F</b>) Cell growth competition assay with WT and Δ<span class="html-italic">rsmA</span> strains grown together through four cycles in MCLMAN and MCLAN. Each data set is representative of a minimum of three growth assays.</p>
Full article ">Figure 3
<p>Effects of <span class="html-italic">rsmA</span> inactivation on <span class="html-italic">C. jejuni</span> biofilm formation at 37 °C. (<b>A</b>) Biofilm formed on polystyrene surfaces after 48 h, quantified by crystal violet staining (color-coded as in <a href="#ijms-25-09797-f002" class="html-fig">Figure 2</a>); <span class="html-italic">p</span> &lt; 0.05 for wild-type (WT) versus Δ<span class="html-italic">rsmA</span> and <span class="html-italic">p</span> &lt; 0.05 for Δ<span class="html-italic">rsmA</span> versus Δ<span class="html-italic">rsmA</span>::<span class="html-italic">rsmA</span>. (<b>B</b>) Biofilm produced by <span class="html-italic">C. jejuni</span> on cover glass after 48 h under microaerobic conditions visualized by Field-Emission Scanning Electron Microscopy. (<b>C</b>) Biofilms of <span class="html-italic">C. jejuni</span> strains formed in the minimal media MCLMAN and MCLAN after 48 h. In MCLMAN, <span class="html-italic">p</span> &lt; 0.01 for WT versus Δ<span class="html-italic">rsmA</span>; <span class="html-italic">p</span> &lt; 0.001 for Δ<span class="html-italic">rsmA</span> versus Δ<span class="html-italic">rsmA</span>::<span class="html-italic">rsmA</span>. In MCLAN, <span class="html-italic">p</span> &lt; 0.001 for WT versus Δ<span class="html-italic">rsmA</span> and for Δ<span class="html-italic">rsmA</span> versus Δ<span class="html-italic">rsmA</span>::<span class="html-italic">rsmA</span>. Values represent means ± S.E.M. of three independent experiments. (<b>D</b>) Biofilm produced by <span class="html-italic">C. jejuni</span> in MCLMAN on cover glass after 48 h under microaerobic conditions visualized by Field-Emission Scanning Electron Microscopy; biofilms formed under the same conditions in MCLAN remained scanter for all three strains.</p>
Full article ">Figure 4
<p>Motility of the <span class="html-italic">C. jejuni</span> strains. (<b>A</b>) Motility of the <span class="html-italic">C. jejuni</span> strains on agar plates after 48 h growth. Strain motility is summarized in the histogram; values represent the means ± SEM of three independent experiments. Significant differences were observed for migration of the wild-type (WT) strain compared to the Δ<span class="html-italic">rsmA</span> null strain (<span class="html-italic">p</span> &lt; 0.005) and for the Δ<span class="html-italic">rsmA</span> versus the complemented Δ<span class="html-italic">rsmA</span>::<span class="html-italic">rsmA</span> strain (<span class="html-italic">p</span> &lt; 0.005). There was no significant difference between the wild-type and the complemented strains. (<b>B</b>) Representative Transmission Electron Micrographs of <span class="html-italic">C. jejuni</span> strains showing cell morphology and flagella.</p>
Full article ">Figure 5
<p>Invasive properties of the <span class="html-italic">C. jejuni rsmA</span> mutant. (<b>A</b>) Invasion of <span class="html-italic">C. jejuni</span> into Caco-2 epithelial cells was significantly increased by <span class="html-italic">rsmA</span> inactivation; <span class="html-italic">p</span> &lt; 0.0001 for WT versus Δ<span class="html-italic">rsmA</span>, and also <span class="html-italic">p</span> &lt; 0.0001 for Δ<span class="html-italic">rsmA</span> versus Δ<span class="html-italic">rsmA</span>::<span class="html-italic">rsmA.</span> (<b>B</b>) Survival of <span class="html-italic">C. jejuni</span> strains within macrophage RAW264.7 cells. The macrophages were infected with 10<sup>7</sup> cfu of the <span class="html-italic">C. jejuni</span> strains (time zero). Viable intracellular <span class="html-italic">C. jejuni</span> cells are tabulated with shading to indicate &gt;200,000, 50,000 to 200,000, 2000 to 50,000, 200 to 2000, and 20 to 200 surviving cells over 24 h. No viable <span class="html-italic">C. jejuni</span> cells were detected at 48 h. <span class="html-italic">p</span> &lt; 0.001 for the wild-type (WT) strain versus the Δ<span class="html-italic">rsmA</span> strain; <span class="html-italic">p</span> &lt; 0.01 for Δ<span class="html-italic">rsmA</span> versus Δ<span class="html-italic">rsmA</span>::<span class="html-italic">rsmA</span>. The cfu values are means ± SEM of three independent experiments.</p>
Full article ">Figure 6
<p>Structure of the <span class="html-italic">C. jejuni</span> flagella. (<b>A</b>) Significant changes in the expression of <span class="html-italic">C. jejuni</span> flagellar assembly components after <span class="html-italic">rsmA</span> deletion. The abundances of upregulated and downregulated proteins, compared with the wild-type strain, are marked in shades of red and blue, respectively. Further details can be found in <a href="#ijms-25-09797-t001" class="html-table">Table 1</a> and <a href="#app1-ijms-25-09797" class="html-app">Table S1</a>. (<b>B</b>) KEGG pathway for flagellar assembly in <span class="html-italic">C. jejuni</span>. Only proteins with significant changes (<span class="html-italic">p</span> &lt; 0.05) are indicated. Schematic of the <span class="html-italic">C. jejuni</span> flagellum and its sequential assembly, adapted from the KEGG website (<a href="https://www.genome.jp/kegg/pathway.html" target="_blank">https://www.genome.jp/kegg/pathway.html</a> (accessed on 25 November 2020)).</p>
Full article ">
14 pages, 2014 KiB  
Article
Genome Mining and Biological Engineering of Type III Borosins from Bacteria
by Kuang Xu, Sijia Guo, Wei Zhang, Zixin Deng, Qi Zhang and Wei Ding
Int. J. Mol. Sci. 2024, 25(17), 9350; https://doi.org/10.3390/ijms25179350 - 29 Aug 2024
Cited by 1 | Viewed by 961
Abstract
Borosins are a class of ribosomally synthesized and post-translationally modified peptides (RiPPs) with α-N-methylated backbones. Although the first mature compound of borosin was reported in 1997, the biosynthetic pathway was elucidated 20 years later. Until this work, borosins have been able to be [...] Read more.
Borosins are a class of ribosomally synthesized and post-translationally modified peptides (RiPPs) with α-N-methylated backbones. Although the first mature compound of borosin was reported in 1997, the biosynthetic pathway was elucidated 20 years later. Until this work, borosins have been able to be categorized into 11 types based on the features of their protein structure and core peptides. Type III borosins were reported only in fungi initially. In order to explore the sources and potential of type III borosins, a precise genome mining work of type III borosins was conducted in bacteria and KchMA’s self-methylation activity was validated by biochemical experiment. Furthermore, a commercial protease and AI-assisted rational design was employed to engineer KchMA for the capacity to produce various N-methylated peptides. Our work demonstrates that type III borosins are abundant not only in eukaryotes but also in bacteria and have immense potential as a tool for synthetic biology. Full article
(This article belongs to the Section Molecular Microbiology)
Show Figures

Figure 1

Figure 1
<p>The architecture of different types of borosins. Core peptides that were not well defined were colored pale yellow. Type XI is a newly discovered borosin in this work. Class 1: the methyltransferase domain, BBD (borosin-binding domain), and core peptide are all fused within a single protein. Class 2: the methyltransferase domain and BBD are covalently linked into one protein, while the core peptide is a separate protein. Class 3: the BBD and core peptide are fused into one protein, with the methyltransferase being a distinct protein. Class 4: the methyltransferase and core peptide are individual proteins, and no BBD has been identified within their biosynthetic gene clusters. GGDEF, GGDEF-sequence-containing domain. BGC, biosynthetic gene cluster.</p>
Full article ">Figure 2
<p>The colored sequence similarity network for mining type III borosins. Proteins with higher than 90% similarity are consolidated into one single node, and the edges connecting the nodes indicate sequence similarity. Borosins characterized in the literature are highlighted by triangles. Borosins characterized in this work are highlighted by diamonds.</p>
Full article ">Figure 3
<p>The methylation pattern of KchMA. An example of LC-MS/MS data and relative abundance for KchMA. The fragmentation patterns of the methylated peptide, as elucidated by LC-MS/MS, are also depicted. Methylated amino acids confirmed by MS/MS are marked with red fonts. The sequences that LC-MS/MS does not cover are gray fonts. Further information can be found in <a href="#app1-ijms-25-09350" class="html-app">Figure S2 and the Supplementary Data</a>.</p>
Full article ">Figure 4
<p>(<b>a</b>) Protein domain architecture and sequence of KchMA<sub>TEV</sub>. The N-terminus of KchMA, TEV cleavage site, and the core peptide are represented by red, yellow, and green rectangles, respectively. The TEV cleavage site is inserted between the wild-type KchMA T747 and D748 and is highlighted in yellow. (<b>b</b>) The methylation result of KchMA<sub>TEV</sub>. The methylated amino acids confirmed by MS/MS are marked with red fonts. Detailed information for each ion (<span class="html-italic">m</span>/<span class="html-italic">z</span>, charge state, and deviation) can be found in the <a href="#app1-ijms-25-09350" class="html-app">Supplementary Data</a>.</p>
Full article ">Figure 5
<p>The catalytic activity of KchMA<sub>TEV</sub>’s methyltransferase domain for different 3-site mutant core peptides. The relative abundance was determined by integrating the EIC peaks and calculating the ratio between the integration of a one-methylation product and the sum of the zero and one-methylation core peptides. Each experiment was conducted in triplicate. The label on the ox-axis represents the single-letter abbreviations for amino acids. Amino acids without corresponding bars on the graph indicated that methylation modifications were not detected.</p>
Full article ">Figure 6
<p>The extracted ion chromatogram (EIC) of two-methylation product of each mutant. The EIC peak for <span class="html-italic">m</span>/<span class="html-italic">z</span> 1701.8065 [M + H]<sup>+</sup> revealed accumulation of the peptides with two backbone-N-methylations.</p>
Full article ">Figure 7
<p>Phylogenetic tree of representative borosins. The type of each borosin is indicated in front of its name, with the split borosins marked in yellow and the fused borosins marked in red. The background color of the phylogenetic tree clades represents the source of the proteins, with those from fungi colored blue and those from bacteria colored green.</p>
Full article ">
16 pages, 1577 KiB  
Article
The RNA Demethylases ALKBH5 and FTO Regulate the Translation of ATF4 mRNA in Sorafenib-Treated Hepatocarcinoma Cells
by Pauline Adjibade, Sergio Di-Marco, Imed-Eddine Gallouzi and Rachid Mazroui
Biomolecules 2024, 14(8), 932; https://doi.org/10.3390/biom14080932 - 1 Aug 2024
Cited by 1 | Viewed by 1596
Abstract
Translation is one of the main gene expression steps targeted by cellular stress, commonly referred to as translational stress, which includes treatment with anticancer drugs. While translational stress blocks the translation initiation of bulk mRNAs, it nonetheless activates the translation of specific mRNAs [...] Read more.
Translation is one of the main gene expression steps targeted by cellular stress, commonly referred to as translational stress, which includes treatment with anticancer drugs. While translational stress blocks the translation initiation of bulk mRNAs, it nonetheless activates the translation of specific mRNAs known as short upstream open reading frames (uORFs)-mRNAs. Among these, the ATF4 mRNA encodes a transcription factor that reprograms gene expression in cells responding to various stresses. Although the stress-induced translation of the ATF4 mRNA relies on the presence of uORFs (upstream to the main ATF4 ORF), the mechanisms mediating this effect, particularly during chemoresistance, remain elusive. Here, we report that ALKBH5 (AlkB Homolog 5) and FTO (FTO: Fat mass and obesity-associated protein), the two RNA demethylating enzymes, promote the translation of ATF4 mRNA in a transformed liver cell line (Hep3B) treated with the chemotherapeutic drug sorafenib. Using the in vitro luciferase reporter translational assay, we found that depletion of both enzymes reduced the translation of the reporter ATF4 mRNA upon drug treatment. Consistently, depletion of either protein abrogates the loading of the ATF3 mRNA into translating ribosomes as assessed by polyribosome assays coupled to RT-qPCR. Collectively, these results indicate that the ALKBH5 and FTO-mediated translation of the ATF4 mRNA is regulated at its initiation step. Using in vitro methylation assays, we found that ALKBH5 is required for the inhibition of the methylation of a reporter ATF4 mRNA at a conserved adenosine (A235) site located at its uORF2, suggesting that ALKBH5-mediated translation of ATF4 mRNA involves demethylation of its A235. Preventing methylation of A235 by introducing an A/G mutation into an ATF4 mRNA reporter renders its translation insensitive to ALKBH5 depletion, supporting the role of ALKBH5 demethylation activity in translation. Finally, targeting either ALKBH5 or FTO sensitizes Hep3B to sorafenib-induced cell death, contributing to their resistance. In summary, our data show that ALKBH5 and FTO are novel factors that promote resistance to sorafenib treatment, in part by mediating the translation of ATF4 mRNA. Full article
(This article belongs to the Special Issue The Structure and Function of Proteins, Lipids and Nucleic Acids)
Show Figures

Figure 1

Figure 1
<p>The RNA demethylases ALKBH5 and FTO are required for SOR-induced ATF4 expression. (<b>A</b>) Conserved consensus m<sup>6</sup>A site in the 5′UTR of ATF4 mRNA. R = A or G; H = A, C, or U, as described [<a href="#B18-biomolecules-14-00932" class="html-bibr">18</a>,<a href="#B19-biomolecules-14-00932" class="html-bibr">19</a>,<a href="#B20-biomolecules-14-00932" class="html-bibr">20</a>]. * corresponds to the conserved nucleotides, including the methylated adenosine in bold. (<b>B</b>–<b>D</b>) Hep3B was treated with 10 µM SOR for two hours. (<b>B</b>) Left panels: Cells were harvested and lysed, and protein extracts were analyzed by western blot for the expression of ALKBH5, ATF4, p-eIF2α, pan-eIF2α, and tubulin (Tub; loading control) using the corresponding antibodies. Right panel: The expression level of ATF4 was estimated by densitometry quantification of the film signal using Image Studio™ Lite Software (version 4.0.21) and standardized against total tubulin. **** <span class="html-italic">p</span> ≤ 0.0001 (Student’s <span class="html-italic">t</span>-test). (<b>C</b>) Left panels: Cells were harvested and lysed, and protein extracts were analyzed by western blot for the expression of the indicated proteins using the corresponding antibodies. Tubulin serves as a loading control. Right panel: The expression level of ATF4 was estimated by densitometry quantification of the film signal using Image Studio™ Lite Software and standardized against total tubulin. *** <span class="html-italic">p</span> ≤ 0.001; **** <span class="html-italic">p</span> ≤ 0.0001 (Student’s <span class="html-italic">t</span>-test). (<b>D</b>) Total RNA was isolated from harvested Hep3B, and the level of ATF4 mRNA relative to GAPDH mRNA was quantified by real-time q(RT)-PCR using the ΔΔCt method. The presented results are the mean of at least triplicate measurements, with error bars corresponding to the S.D. (<b>E</b>,<b>F</b>) Hep3B were treated with 10 µM SOR for twenty-four hours. (<b>E</b>) Clonogenic survival assays. After treatment, cells were trypsinized, counted, and seeded in the absence of the drug and incubated for 10 days. Populations &gt; 20 cells were counted as one surviving colony. Data were calculated as the percentage of surviving colonies relative to the number found in plates corresponding to mock-depleted cell plates. Data shown are representative of at least 3 separate experiments, and values are given as mean ± SD. (Student’s <span class="html-italic">t</span>-test). ** <span class="html-italic">p</span> ≤ 0.01; * <span class="html-italic">p</span> ≤ 0.05. (<b>F</b>) Cell viability, assessed by MTT assay, shows the viability of Hep3B cells stably expressing shALKBH5 or shFTO after exposure to SOR for twenty-four hours. Data shown are representative of at least 3 separate experiments, and values are given as mean ± SD. (Student’s <span class="html-italic">t</span>-test). ** <span class="html-italic">p</span> ≤ 0.01; **** <span class="html-italic">p</span> ≤ 0.0001. Original images can be found in <a href="#app1-biomolecules-14-00932" class="html-app">Supplementary Materials</a>.</p>
Full article ">Figure 2
<p>Both ALKBH5 and FTO are required for the association of ATF4 mRNA with polysomes in SOR-treated Hep3B. (<b>A</b>) Analysis of ALKBH5 and FTO association with polysomes. Top panels: cytoplasmic extracts prepared from either untreated or SOR-treated Hep3B were fractionated through 15–55% (<span class="html-italic">w</span>/<span class="html-italic">v</span>) sucrose density gradients, and their polysome profiles were monitored by measuring the OD254. M: monosomes. LP: light polysomes. HP: heavy polysomes. Bottom panels: Western blot analysis of the collected fractions for the distribution of FMRP, ALKBH5, and FTO using specific antibodies. RPS14 and RPL22 ribosomal proteins are used as controls for the integrity of the polysome profiles. The results are representative of two independent experiments. Original images can be found in <a href="#app1-biomolecules-14-00932" class="html-app">Supplementary Materials</a>. (<b>B</b>,<b>C</b>) Analysis of the ATF4 mRNA association with polysomes in the absence of the RNA demethylases ALKBH5 and FTO. Hep3B stably expressing shRNAs against ALKBH5 or FTO or a non-specific shRNA (NT) control were treated with SOR (10 µM, two hours) as above. Cytoplasmic extracts were fractionated through 15–55% sucrose gradients, and their polysome profiles were recorded as above. (<b>B</b>) Polysome profile of SOR-treated Hep3B shNT, shALKBH5 and shFTO. (<b>C</b>) RNA content was isolated from pooled LP and HP fractions, and associated ATF4 mRNA was quantified by RT-qPCR using the ΔΔCt method. ATF4 mRNA levels were normalized against 18S ribosomal RNA and expressed as indicated. The results are representative of two independent experiments.</p>
Full article ">Figure 3
<p>Role of ALKBH5 in ATF4 mRNA methylation level. (<b>A</b>) Methylated RNA immunoprecipitation (MeRIP)-qPCR analysis. Hep3B were treated with sorafenib (SOR; 10 μM) for two hours or left untreated (unt), lysed, and their extracts were subjected to MeRIP using m<sup>6</sup>A antibodies. Immunoprecipitated m<sup>6</sup>A RNAs are then quantified by RT-qPCR using oligos specific to the main ORF of ATF4 mRNA. The amounts of m<sup>6</sup>A ATF4 mRNA were normalized against IgG precipitate and then expressed relative to untreated conditions. ** <span class="html-italic">p</span> ≤ 0.01. (<b>B</b>) Schematic representation of the 5’UTR ATF4 RNA reporter. (<b>C</b>) MeRIP-qPCR analysis of m<sup>6</sup>A level of the biotinylated 5′UTR ATF4 RNA reporter incubated with protein extracts prepared from either untreated (unt) or sorafenib (SOR)-treated Hep3B. RNA is then subjected to MeRIP using m<sup>6</sup>A antibodies. Immunoprecipitated m<sup>6</sup>A RNA is then incubated with streptavidin-agarose beads to purify the biotinylated reporter RNA, which is quantified by RT-qPCR using oligos specific to the 5′end of ATF4 mRNA. The amounts of m<sup>6</sup>A ATF4 reporter RNA were normalized against IgG precipitate and then expressed relative to the mock condition. Data are representative of 3 separate experiments, and values are given as mean ± SD. ** <span class="html-italic">p</span> ≤ 0.01, *** <span class="html-italic">p</span> ≤ 0.001, ns: not significant. (<b>D</b>) MeRIP-qPCR analysis of m<sup>6</sup>A level of 5′UTR ATF4 RNA reporter incubated with proteins extracts from Hep3B stably expressing either a control shRNA (shNT) or shALKBH5 and treated with SOR (10 µM, 2 h). Depletion of ALKBH5 is validated by western blot using specific antibodies as described in <a href="#biomolecules-14-00932-f001" class="html-fig">Figure 1</a> (left panels). m<sup>6</sup>A methylated ATF4 reporter RNAs were isolated and quantified by RT-qPCR (right graphs) as above. The amounts of m<sup>6</sup>A ATF4 reporter RNA were normalized against IgG precipitate and then expressed relative to the shNT condition. Data are representative of 3 separate experiments, and values are given as mean ± SD. ** <span class="html-italic">p</span> ≤ 0.01, ns: not significant. Original images can be found in <a href="#app1-biomolecules-14-00932" class="html-app">Supplementary Materials</a>.</p>
Full article ">Figure 4
<p>(<b>A</b>) Schematic representation of the human 5’UTR ATF4 Luciferase reporters (WT- and mut-ATF4 FLuc) consisting of the human WT- and A235G (mut)- ATF4 5′-UTR fused to Firefly luciferase (FLuc) gene. (<b>B</b>) Hep3B cells are co-transfected with either Fluc-expressing vectors or the control plasmid expressing <span class="html-italic">Renilla</span> luciferase (RLuc). Cells are then treated with Thapsigargin (thap) to induce translation of FLuc, the activity of which is measured in the cell extracts and expressed relative to RLuc. The relative values of firefly luciferase were shown as the average of three biological replicates. Error bars correspond to the S.D. ** <span class="html-italic">p</span> ≤ 0.01, *** <span class="html-italic">p</span> ≤ 0.001, **** <span class="html-italic">p</span> ≤ 0.0001. (<b>C</b>) Hep3B stably expressing either a control shRNA (shNT; left panels), shALKBH5 (middle panels), or shFTO (right panels) are co-transfected with a luciferase-expressing vector containing either the WT- or A235G (mut)- ATF4 5′-UTR fused to FLuc gene, and the control plasmid expressing RLuc. Cells are then treated with Thap to induce translation of FLuc, the activity of which is measured. The relative values of firefly luciferase were shown as the average of three biological replicates. Error bars correspond to the S.D. **** <span class="html-italic">p</span> ≤ 0.0001, ns: not significant. Original images can be found in <a href="#app1-biomolecules-14-00932" class="html-app">Supplementary Materials</a>.</p>
Full article ">
25 pages, 2652 KiB  
Review
SnoRNAs: Exploring Their Implication in Human Diseases
by Waseem Chauhan, Sudharshan SJ, Sweta Kafle and Rahima Zennadi
Int. J. Mol. Sci. 2024, 25(13), 7202; https://doi.org/10.3390/ijms25137202 - 29 Jun 2024
Cited by 2 | Viewed by 2534
Abstract
Small nucleolar RNAs (snoRNAs) are earning increasing attention from research communities due to their critical role in the post-transcriptional modification of various RNAs. These snoRNAs, along with their associated proteins, are crucial in regulating the expression of a vast array of genes in [...] Read more.
Small nucleolar RNAs (snoRNAs) are earning increasing attention from research communities due to their critical role in the post-transcriptional modification of various RNAs. These snoRNAs, along with their associated proteins, are crucial in regulating the expression of a vast array of genes in different human diseases. Primarily, snoRNAs facilitate modifications such as 2′-O-methylation, N-4-acetylation, and pseudouridylation, which impact not only ribosomal RNA (rRNA) and their synthesis but also different RNAs. Functionally, snoRNAs bind with core proteins to form small nucleolar ribonucleoproteins (snoRNPs). These snoRNAs then direct the protein complex to specific sites on target RNA molecules where modifications are necessary for either standard cellular operations or the regulation of pathological mechanisms. At these targeted sites, the proteins coupled with snoRNPs perform the modification processes that are vital for controlling cellular functions. The unique characteristics of snoRNAs and their involvement in various non-metabolic and metabolic diseases highlight their potential as therapeutic targets. Moreover, the precise targeting capability of snoRNAs might be harnessed as a molecular tool to therapeutically address various disease conditions. This review delves into the role of snoRNAs in health and disease and explores the broad potential of these snoRNAs as therapeutic agents in human pathologies. Full article
(This article belongs to the Section Molecular Pathology, Diagnostics, and Therapeutics)
Show Figures

Figure 1

Figure 1
<p><b>Diagrammatic representation of snoRNA biogenesis.</b> (A) After the transcription process, newly formed mRNA undergoes a splicing process to remove the introns. (B,C) These introns undergo further nucleolytic processing, then lariat structure formation evolves as either C/D box snoRNAs or H/ACA snoRNAs. (C) The snoRNAs specifically bind to the SNU13 (aka 15.5K), NOP56, NOP58 and FBL proteins to become C/D box snoRNPs, while the assembly of H/ACA snoRNPs involves core proteins such as Nap57, Cbf5p (dyskerin), and GAR1.</p>
Full article ">Figure 2
<p><b>Depicting H/ACA snoRNP modifying various RNAs.</b> (A,G) The H/ACA box snoRNP formed after the snoRNA is associated with multiple proteins (e.g., Nhp2, Nop10, Dyskerin and Gar1), are actively involved in the modification of various RNAs (miRNA, tRNA, mRNA, rRNA or/and sdRNA). (B,C) These H/ACA box snoRNAs are also involved in modifications (N4-acetylation, 2′-O-methylation and Pseudouridylation) on rRNA, and then help in the biogenesis of ribosomes. (D) Alternative splicing of mRNA is one of the important functions of these snoRNAs as well. (E,F) These H/ACA box snoRNAs are in addition actively involved in the pseudouridylation of mRNAs and tRNAs and help in their maturation.</p>
Full article ">Figure 3
<p><b>Box C/D snoRNA-guided 2′-O-methylation of various RNAs.</b> Once the box C/D snoRNAs are bound to the SNU13 (aka 15.5K), NOP56, NOP58 and FBL proteins to become C/D box snoRNPs, these proteins are guided by snoRNAs to target RNAs and bind to a complementary sequence on the RNA target through a short antisense element. The RNA target then undergoes 2′-O-methylation at a specific site mediated by FBL. Nm modification occurs on various RNA types.</p>
Full article ">Figure 4
<p><b>Acetylation of 18S ribosomal RNA.</b> Acetylation is one of the other important modifications required for the proper assembly of the ribosome or ribosomal biogenesis. In this figure, it is evident that snoRNA makes the Watson–Crick base pairing with 18S rRNA but prior to the interaction with RNA acetyltransferase. RNA acetyltansferase helps then the 18S rRNA to be navigated, prior to acetylate cytidine residues.</p>
Full article ">Figure 5
<p><b>snoRNAs with associated proteins participate in multiple cellular functions including cell proliferation in AML.</b> (A) AML cells lack SNORA21 and thereby do not show pseudouridylation that hampered the ribosomal synthesis needed for regulatory proteins. (B) AML cells also show chromosomal translocation t(8;21) causing chimeric protein (AML1-ETO) formation. AES shows oncogenic activity of this chimeric protein after the association with snoRNPs via interaction with DDX21. (C) Approximately, 30% of AML patients shows frameshift mutation in nucleophosmin (NPM1) protein, B23, which is destined to be in the nucleus but after frameshift mutation, B23 protein localizes in the cytosol. Thus, without B23 protein in the nucleus, C/D box RNPs are unable to process modification of the mRNA and chromatin remodeling.</p>
Full article ">Figure 6
<p><b>Figure representing the anti-cancerous nature of some snoRNAs.</b> In hepatoblastoma, SNORA14A (H/ACA box snoRNA) is overexpressed and enhanced the ribosomal biogenesis required for the expression of succinate dehydrogenase subunit B (SDSB) protein. SDSB can reduce the cellular proliferation and exerts apoptotic effects in hepatoblastoma cells. Similarly, the C/D box snoRNAs, SNORD76 and SNORD44, also exhibit antiproliferative effect in multiple cancers.</p>
Full article ">
22 pages, 3319 KiB  
Article
DNA Damage Checkpoints Govern Global Gene Transcription and Exhibit Species-Specific Regulation on HOF1 in Candida albicans
by Yan Zhang, Huaxin Cai, Runlu Chen and Jinrong Feng
J. Fungi 2024, 10(6), 387; https://doi.org/10.3390/jof10060387 - 29 May 2024
Viewed by 1091
Abstract
DNA damage checkpoints are essential for coordinating cell cycle arrest and gene transcription during DNA damage response. Exploring the targets of checkpoint kinases in Saccharomyces cerevisiae and other fungi has expanded our comprehension of the downstream pathways involved in DNA damage response. While [...] Read more.
DNA damage checkpoints are essential for coordinating cell cycle arrest and gene transcription during DNA damage response. Exploring the targets of checkpoint kinases in Saccharomyces cerevisiae and other fungi has expanded our comprehension of the downstream pathways involved in DNA damage response. While the function of checkpoint kinases, specifically Rad53, is well documented in the fungal pathogen Candida albicans, their targets remain poorly understood. In this study, we explored the impact of deleting RAD53 on the global transcription profiles and observed alterations in genes associated with ribosome biogenesis, DNA replication, and cell cycle. However, the deletion of RAD53 only affected a limited number of known DNA damage-responsive genes, including MRV6 and HMX1. Unlike S. cerevisiae, the downregulation of HOF1 transcription in C. albicans under the influence of Methyl Methanesulfonate (MMS) did not depend on Dun1 but still relied on Rad53 and Rad9. In addition, the transcription factor Mcm1 was identified as a regulator of HOF1 transcription, with evidence of dynamic binding to its promoter region; however, this dynamic binding was interrupted following the deletion of RAD53. Furthermore, Rad53 was observed to directly interact with the promoter region of HOF1, thus suggesting a potential role in governing its transcription. Overall, checkpoints regulate global gene transcription in C. albicans and show species-specific regulation on HOF1; these discoveries improve our understanding of the signaling pathway related to checkpoints in this pathogen. Full article
(This article belongs to the Special Issue New Trends in Yeast Metabolic Engineering)
Show Figures

Figure 1

Figure 1
<p>Functional characterization of checkpoint kinases responding to genotoxic stresses in <span class="html-italic">C. albicans</span>. (<b>A</b>) Phenotypic assay of the <span class="html-italic">RAD53</span> deletion, the <span class="html-italic">RAD9</span> deletion, and the <span class="html-italic">DUN1</span> deletion strains under genotoxic stresses. Two independent mutants for each strain were used for phenotypic assays, thus showing consistent results. (<b>B</b>) Nuclei separation of the wild type (SN148), the <span class="html-italic">RAD53</span> deletion, the <span class="html-italic">RAD9</span> deletion, and the <span class="html-italic">DUN1</span> deletion strains. The log phase cells were treated with 0.02% MMS for 120 min and then stained with DAPI. Cells with buds containing different types of nuclei were divided into three groups as indicated. The result was averaged from two independent experiments. (<b>C</b>) Filamentous growth of the <span class="html-italic">DUN1</span> strain induced by genotoxic stress. The wild-type and the <span class="html-italic">DUN1</span> deletion cells were treated with 0.02% MMS or 40 mM HU for the indicated time. The cell morphology was checked and imaged (400×). (<b>D</b>) The long bud of the <span class="html-italic">DUN1</span> deletion cells induced by 40 mM HU for 6 h was measured using Image J software 1.42. Over 30 cells were checked for each strain. The difference was compared using a paired <span class="html-italic">t</span> test with GraphPad Prism 8.0.1 software. ** represents <span class="html-italic">p</span> &lt; 0.01.</p>
Full article ">Figure 2
<p>Overview of <span class="html-italic">RAD53</span>-related transcriptome under MMS stress in <span class="html-italic">C. albicans</span>. (<b>A</b>) Volcano plot showing the global transcriptional changes affected by Rad53 under the stress of MMS. (<b>B</b>) Top-20 KEGG terms of differed genes in response to MMS by deleting <span class="html-italic">RAD53</span>. Cell cycle-involved genes (<b>C</b>), DNA replication-involved genes (<b>D</b>), and ribosome biogenesis-involved genes (<b>E</b>) affected by Rad53 in <span class="html-italic">C. albicans</span>. The fold change for each gene under the normal condition (first column) or the MMS stress condition (second column) is shown after the gene name, with blanks indicating no significant change based on transcriptome data. Genes highlighted in red indicate consistent changes between normal and MMS stress conditions. (<b>F</b>) DNA damage repair genes were affected by deleting <span class="html-italic">RAD53</span> under MMS stress conditions. The fold change for each gene is shown after the gene name.</p>
Full article ">Figure 3
<p>Uncovering <span class="html-italic">RAD53</span>-dependent DNA damage responsive genes in <span class="html-italic">C. albicans</span>. (<b>A</b>) Overview of MMS-responsive genes affected by deleting <span class="html-italic">RAD53</span>. The number without brackets represents the defined MMS-responsive genes, while the number with brackets represents the putative MMS-responsive genes. (<b>B</b>) List of MMS-induced (left panel) or -repressed genes (right panel) affected by Rad53 in <span class="html-italic">C. albicans</span>. The fold change for each gene affected by MMS stress in wild-type strain (left column) or by deleting <span class="html-italic">RAD53</span> upon exposure to MMS (right column) is listed after the gene name. Genes highlighted in red represent the defined MMS-responsive genes, and those genes in black represent the putative MMS-responsive genes. (<b>C</b>) Relative transcription of MMS-responsive genes affected by deleting <span class="html-italic">RAD53</span> in MMS stress conditions. The transcription of indicated genes in wild-type strain under MMS stress was compared to the level in wild-type strain without MMS treatment, and the transcription of indicated genes in the <span class="html-italic">RAD53</span> deletion strain was compared to the level in wild-type strain with or without MMS treatment. (<b>D</b>) Relative transcription levels of Rad53-regulated genes affected by deleting <span class="html-italic">RAD9</span> or <span class="html-italic">DUN1</span> in the MMS stress condition. The transcriptional levels of indicated genes in the <span class="html-italic">RAD9</span> or <span class="html-italic">DUN1</span> deletion strains were compared to those in wild-type strain under MMS treatment. The qRT-PCR assays for each strain were repeated at least 3 times. The difference between each group was compared using paired <span class="html-italic">t</span> test with GraphPad Prism 8.0.1 software. * represents <span class="html-italic">p</span> &lt; 0.05, ** represents <span class="html-italic">p</span> &lt; 0.01, *** represents <span class="html-italic">p</span> &lt; 0.001, **** represents <span class="html-italic">p</span> &lt; 0.0001. NS represents no significant difference.</p>
Full article ">Figure 4
<p>Checkpoint kinases Rad53 and Rad9 regulate the transcription of <span class="html-italic">HOF1</span> in <span class="html-italic">C. albicans</span>. (<b>A</b>) The transcription of <span class="html-italic">HOF1</span> after deleting <span class="html-italic">RAD9</span>, <span class="html-italic">RAD53</span>, and <span class="html-italic">DUN1</span> was checked by qRT-PCR. The wild-type strain (SN148), the <span class="html-italic">RAD9</span> deletion strain, the <span class="html-italic">RAD53</span> deletion strain, and the <span class="html-italic">DUN1</span> deletion strain were treated with 0.015% MMS for 90 min before being harvested for RNA extraction. The transcription of <span class="html-italic">HOF1</span> in each strain was compared to the level in wild type with no MMS stress. (<b>B</b>) The transcription of <span class="html-italic">HOF1</span> after deleting <span class="html-italic">DUN1</span> was checked by qRT-PCR. The wild-type strain (SN148) and the <span class="html-italic">DUN1</span> deletion strain were treated with 40 mM HU for 90 min before being harvested for RNA extraction. The transcription of <span class="html-italic">HOF1</span> in each strain was compared to the level in wild type without MMS stress. (<b>C</b>) The transcription of <span class="html-italic">HOF1</span> after overexpressing <span class="html-italic">DUN1</span>. The wild-type strain or the <span class="html-italic">RAD53</span> deletion strain with or without the <span class="html-italic">DUN1</span> overexpression cassette was treated with MMS, as mentioned in panel A. The qRT-PCR assay for each strain was repeated at least 3 times. The transcription of <span class="html-italic">HOF1</span> in each group was compared to the level in wild type without MMS stress. The difference between each group was compared using paired <span class="html-italic">t</span> test with GraphPad Prism 8.0.1 software. * represents <span class="html-italic">p</span> &lt; 0.05, ** represents <span class="html-italic">p</span> &lt; 0.01, and *** represents <span class="html-italic">p</span> &lt; 0.001. NS represents no significant difference. (<b>D</b>) Phenotypic assay of the <span class="html-italic">HOF1 RAD9</span> double deletion and the <span class="html-italic">HOF1 DUN1</span> double deletion strains to MMS stress.</p>
Full article ">Figure 5
<p>Transcription of <span class="html-italic">HOF1</span> affected by Mcm1 and Fkh2. (<b>A</b>) The transcription of <span class="html-italic">HOF1</span> was affected by deleting (left panel) or overexpressing <span class="html-italic">FKH2</span> (right panel). The log phase cells of indicated strains were used for qRT-PCR assays. (<b>B</b>) The transcription of <span class="html-italic">HOF1</span> was affected by repressing (left panel) or overexpressing <span class="html-italic">MCM1</span> (right panel). The promoter of <span class="html-italic">MCM1</span> was replaced by a <span class="html-italic">MET3</span> promoter in SN148 background. The overnight culture of the indicated strains was inoculated into SC media plus Met/Cys (5 mM for each) or SC-Met/Cys for 4 h before being harvested for RNA extraction. The qRT-PCR assay for each strain was repeated at least 3 times. The transcription of indicated genes was compared to the level in wild type using a paired <span class="html-italic">t</span> test with GraphPad Prism 8.0.1 software. * represents <span class="html-italic">p</span> &lt; 0.05, and ** represents <span class="html-italic">p</span> &lt; 0.01.</p>
Full article ">Figure 6
<p>Transcription factors Mcm1 and Fkh2 bind to the promoter of <span class="html-italic">HOF1</span>. (<b>A</b>,<b>B</b>) Detection of the binding of Mcm1 or Fkh2 to the promoter of <span class="html-italic">HOF1</span> by ChIP analysis. The log phase wild-type cells (SN148) carrying Mcm1–HA or Fkh2–HA fusion, with or without 0.02% MMS treatment, were fixed with 1% formaldehyde. A wild-type strain without an HA tag was used as a control. Immunoprecipitated pellets were used as templates for PCR with the primer pairs HOF1–Chip-F and R. The intensity of the band was quantified using ImageJ software. Under no stress conditions, the ratio of the band in the ChIP group to the input group was normalized as 1. The result was averaged from two independent experiments. (<b>C</b>,<b>D</b>) The enrichment of <span class="html-italic">HOF1</span> to Mcm1 and Fkh2 was checked by ChEC assay coupled with qPCR. Wild-type cells carrying Mcm1–Mnase or Fkh2–Mnase fusions were used. The extracted DNA fragments around 100 bp to 400 bp from cells with or without MMS treatment were applied for qPCR assays, and the GAPDH level was used as a control. The difference was compared using a paired <span class="html-italic">t</span> test with GraphPad Prism 8.0.1 software. ** represents <span class="html-italic">p</span> &lt; 0.01. (<b>E</b>) Rad53 regulates the dynamic enrichment of the <span class="html-italic">HOF1</span> promoter to Mcm1. The <span class="html-italic">RAD53</span> deletion cells carrying Mcm1–Mnase fusions were used. The extracted DNA fragments around 100 bp to 400 bp from cells with or without MMS treatment were applied to check the signal of the <span class="html-italic">HOF1</span> promoter with primers HOF1–pro-F/R, and the GAPDH level was used as a control. The difference was compared using a paired <span class="html-italic">t</span> test with GraphPad Prism 8.0.1 software. NS represents no significant difference.</p>
Full article ">Figure 7
<p>Rad53 is involved in the direct regulation of <span class="html-italic">HOF1</span>. (<b>A</b>) Diagram of yeast one-hybrid assay. (<b>B</b>) The FHA2 region of Rad53 binds to the promoter of <span class="html-italic">HOF1</span>. The different domains of Rad53 were cloned into the pGADT7 plasmid, and various regions of the <span class="html-italic">HOF1</span> promoter were cloned into the pHIS2 plasmid before being transformed into the yeast Y187 strain. The transformants were dissolved in distilled water and dropped onto SC–Trp–Leu–His plates containing different concentrations of 3-AT. The plates were kept at 30 °C for 2–3 days. (<b>C</b>) Checkpoint kinase Rad53 binds to the promoter of <span class="html-italic">HOF1</span>. The log phase wild-type cells carrying the Rad53–HA fusion, with or without 0.02% MMS treatment, were fixed with 1% formaldehyde. A wild-type strain without an HA tag was used as a control. Immunoprecipitated pellets were used as templates for PCR with the primer pairs HOF1–pro-F/R. The band intensity was quantified using ImageJ software. Under no stress conditions, the ratio of the band in the ChIP group to the input group was normalized as 1. The result was averaged from two independent experiments.</p>
Full article ">Figure 8
<p>Overview of checkpoint-related regulation on <span class="html-italic">HOF1</span> in response to MMS in <span class="html-italic">C. albicans</span>. (<b>A</b>) The dynamic binding of Rad53 and Mcm1/Fkh2 to the promoter of <span class="html-italic">HOF1</span>. Under normal conditions, Mcm1 and Fkh2 bind to the promoter of <span class="html-italic">HOF1</span> and regulate the transcription of <span class="html-italic">HOF1</span> to ensure regular and timely cytokinesis. Upon DNA damage stress, Mcm1 or Fkh2 dissociates from the promoter of <span class="html-italic">HOF1</span> either by activated Rad53 or through a competition with activated Rad53, thereby subsequently diminishing the transcription of <span class="html-italic">HOF1</span> to impede cytokinesis and giving enough time for cells to repair damaged DNA. (<b>B</b>) The binding region for Rad53 and Mcm1/Fkh2 in the <span class="html-italic">HOF1</span> promoter. The red box represents the binding region of Rad53, and the green box represents the detected binding region for Mcm1 and Fkh2.</p>
Full article ">
16 pages, 2003 KiB  
Article
Loss of Conserved rRNA Modifications in the Peptidyl Transferase Center Leads to Diminished Protein Synthesis and Cell Growth in Budding Yeast
by Margus Leppik, Liisa Pomerants, Anett Põldes, Piret Mihkelson, Jaanus Remme and Tiina Tamm
Int. J. Mol. Sci. 2024, 25(10), 5194; https://doi.org/10.3390/ijms25105194 - 10 May 2024
Cited by 1 | Viewed by 1709
Abstract
Ribosomal RNAs (rRNAs) are extensively modified during the transcription and subsequent maturation. Three types of modifications, 2′-O-methylation of ribose moiety, pseudouridylation, and base modifications, are introduced either by a snoRNA-driven mechanism or by stand-alone enzymes. Modified nucleotides are clustered at the functionally important [...] Read more.
Ribosomal RNAs (rRNAs) are extensively modified during the transcription and subsequent maturation. Three types of modifications, 2′-O-methylation of ribose moiety, pseudouridylation, and base modifications, are introduced either by a snoRNA-driven mechanism or by stand-alone enzymes. Modified nucleotides are clustered at the functionally important sites, including peptidyl transferase center (PTC). Therefore, it has been hypothesised that the modified nucleotides play an important role in ensuring the functionality of the ribosome. In this study, we demonstrate that seven 25S rRNA modifications, including four evolutionarily conserved modifications, in the proximity of PTC can be simultaneously depleted without loss of cell viability. Yeast mutants lacking three snoRNA genes (snR34, snR52, and snR65) and/or expressing enzymatically inactive variants of spb1(D52A/E679K) and nop2(C424A/C478A) were constructed. The results show that rRNA modifications in PTC contribute collectively to efficient translation in eukaryotic cells. The deficiency of seven modified nucleotides in 25S rRNA resulted in reduced cell growth, cold sensitivity, decreased translation levels, and hyperaccurate translation, as indicated by the reduced missense and nonsense suppression. The modification m5C2870 is crucial in the absence of the other six modified nucleotides. Thus, the pattern of rRNA-modified nucleotides around the PTC is essential for optimal ribosomal translational activity and translational fidelity. Full article
(This article belongs to the Special Issue Advanced Studies in Ribosomal RNA)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Structure of the <span class="html-italic">S. cerevisiae</span> 80S ribosome with the rRNA modifications investigated in this study. (<b>A</b>) Overview of the <span class="html-italic">S. cerevisiae</span> 80S ribosome. The rRNA of 60S and 40S subunits, respectively, are shown in wheat and light grey. The 5S rRNA is shown in teal. The location of the eight rRNA modifications absent in <span class="html-italic">3ΔsnR nop2* spb1*</span> mutant is indicated (red). (<b>B</b>) Zoomed-in view of 60S subunit peptidyl transferase center region. The rRNA modifications that are affected in <span class="html-italic">3ΔsnR nop2* spb1*</span> mutant are shown. Evolutionarily conserved modifications are shown in red, non-conserved modifications in light green. The ribosome structure was generated by PyMOL [<a href="#B30-ijms-25-05194" class="html-bibr">30</a>] using the coordinates form [<a href="#B31-ijms-25-05194" class="html-bibr">31</a>] PDB ID: 4V88.</p>
Full article ">Figure 2
<p>Phenotypic characterisation of rRNA modification mutants. (<b>A</b>) Serial dilutions of wild-type (WT) and indicated mutant strains were spotted onto rich medium. Cells were grown at the indicated temperatures for 2–8 days. (<b>B</b>) Analysis of levels of global translation. The incorporation of radioactive isotope-labelled amino acids into newly synthesised polypeptides was measured in exponentially growing cells at 30 °C. Samples were TCA-precipitated and the incorporation of radioactive label was measured over time. The obtained values of DPM were normalised to the optical density values of the sample, and the slope was calculated. The average slope values (mean ± SD) from at least nine biological replicates are plotted and are shown relative to the wild-type. The numbers in parentheses next to the strain names indicate the number of missing modifications in the 25S rRNA. Statistical significance was determined by the unpaired two-sample Student’s <span class="html-italic">t</span>-test (** <span class="html-italic">p</span> &lt; 0.01; **** <span class="html-italic">p</span> &lt; 0.0001; NS, not significant).</p>
Full article ">Figure 3
<p>Translational fidelity of rRNA modification mutants. Wild-type cells (WT) and indicated mutants were transformed with dual-luciferase reporters and control plasmid. The activities of both luciferases were measured. The ratio of firefly luciferase to <span class="html-italic">Renilla</span> luciferase activities was normalised to the control plasmid and is shown relative to the wild-type. The numbers in parentheses next to the strain names indicate the number of missing modifications in the 25S rRNA. (<b>A</b>) +1 PRF was measured using the Ty1 frameshift signal. (<b>B</b>) The rate of missense suppression was evaluated by the incorporation of an arginine near-cognate amino acid instead of a cognate serine at the catalytic codon 218 in the firefly luciferase. (<b>C</b>,<b>D</b>) Termination codon readthrough was measured using reporters containing in-frame UAA and UAG termination codons between the <span class="html-italic">Renilla</span> and firefly luciferase coding regions. Each dataset represents the average (mean ± SD) of at least 15 biological replicates. Asterisks above columns indicate statistically significant changes compared to wild-type as determined by the unpaired two-sample Student’s <span class="html-italic">t</span>-test (*** <span class="html-italic">p</span> &lt; 0.001; **** <span class="html-italic">p</span> &lt; 0.0001). A 1.2-fold difference in wild-type was counted as biologically different, as described earlier [<a href="#B34-ijms-25-05194" class="html-bibr">34</a>].</p>
Full article ">Figure 4
<p>Ribosome-polysome profiles of rRNA modification mutants. Analysis of ribosome-polysome profiles of wild-type (WT) and indicated mutants by sedimentation in sucrose density gradient. (<b>A</b>) Cells were grown in rich medium at 30 °C to mid-exponential phase and analysed. (<b>B</b>) Cells were cultured at 30 °C to mid-exponential phase and shifted to 20 °C for 2 h (WT) or 4 h (mutant <span class="html-italic">3ΔsnR nop2* spb1*</span>) and analysed. The whole-cell extracts were prepared from cycloheximide-treated cells and analysed in 7–47% sucrose gradients. The absorbance at 260 nm (A260 nm) was recorded. Sedimentation is from left to right. The peaks of free 40S ribosomal subunits, monosomes (80S), and polysomes are indicated. To determine the P/M ratio, the areas under the monosome and polysome peaks were quantified by ImageJ, and the ratio was calculated. The average (mean ± SD) ratios of at least three biological replicates are indicated. The numbers in parentheses next to the strain names indicate the number of missing modifications in the 25S rRNA.</p>
Full article ">
19 pages, 7460 KiB  
Article
DNA Methylation Analysis of Growth Differences between Upright and Inverted Cuttings of Populus yunnanensis
by Haiyang Guo, Tiansu Guo, Hailin Li, Shaojie Ma, Xiaolin Zhang, Chengzhong He and Dan Zong
Int. J. Mol. Sci. 2024, 25(10), 5096; https://doi.org/10.3390/ijms25105096 - 7 May 2024
Viewed by 1372
Abstract
DNA methylation is an important mechanism for epigenetic modifications that have been shown to be associated with responses to plant development. Previous studies found that inverted Populus yunnanensis cuttings were still viable and could develop into complete plants. However, the growth status of [...] Read more.
DNA methylation is an important mechanism for epigenetic modifications that have been shown to be associated with responses to plant development. Previous studies found that inverted Populus yunnanensis cuttings were still viable and could develop into complete plants. However, the growth status of inverted cuttings was weaker than that of upright cuttings, and the sprouting time of inverted cuttings was later than that of upright cuttings. There is currently no research on DNA methylation patterns in inverted cuttings of Populus yunnanensis. In this study, we detected genome-wide methylation patterns of stem tips of Populus yunnanensis at the early growth stage and the rapid growth stage by Oxford Nanopore Technologies (ONT) methylation sequencing. We found that the methylation levels of CpG, CHG, CHH, and 6mA were 41.34%, 33.79%, 17.27%, and 12.90%, respectively, in the genome of inverted poplar cuttings, while the methylation levels of the four methylation types were higher in the genome of upright poplar cuttings than in inverted cuttings, 41.90%, 34.57%, 18.09%, and 14.11%, suggesting important roles for DNA methylation in poplar cells. In all comparison groups, CpG-type methylation genes in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were annotated to pathways associated with carbon metabolism, ribosome biogenesis in eukaryotes, glycolysis/gluconeogenesis, pyruvate metabolism, and mRNA detection pathways, suggesting that different biological processes are activated in upright and inverted cuttings. The results show that methylation genes are commonly present in the poplar genome, but only a few of them are involved in the regulation of expression in the growth and development of inverted cuttings. From this, we screened the DET2 gene for significant differences in methylation levels in upright or inverted cuttings. The DET2 gene is a key gene in the Brassinolide (BRs) synthesis pathway, and BRs have an important influence on the growth and development process of plants. These results provide important clues for studying DNA methylation patterns in P. yunnanensis. Full article
(This article belongs to the Section Molecular Plant Sciences)
Show Figures

Figure 1

Figure 1
<p>Comparative box plot of the overall distribution of methylation levels for each sample.</p>
Full article ">Figure 2
<p>Genome-wide methylation levels of different samples. (<b>a</b>) JD (inverted cuttings at the early stage of growth); (<b>b</b>) JZ (upright cuttings at the early stage of growth); (<b>c</b>) SD (inverted cuttings at the rapid growth period); (<b>d</b>) SZ (upright cuttings at the rapid growth period). 1–8: Contig00021, Contig00387, Contig00139, Contig00070, Contig00237, Contig00121, Contig00246, Contig00109; The methylation levels of chromosomes, gene density in windows, CpG, CHH, CHG, and 6mA are indicated from outside to inside.</p>
Full article ">Figure 3
<p>Sequence distribution around the 5 mC site of samples and motif distribution in the 6 mA region of samples. From left to right, CG, CHG, CHH and 6 mA. (<b>a</b>) JD; (<b>b</b>) JZ; (<b>c</b>) SD; (<b>d</b>) SZ.</p>
Full article ">Figure 4
<p>Methylation levels in different regions of all genes. (<b>a</b>) CG; (<b>b</b>) CHG; (<b>c</b>) CHH; (<b>d</b>) 6mA.</p>
Full article ">Figure 5
<p>Statistics of DML of samples.</p>
Full article ">Figure 6
<p>Statistics of the DMR of the samples.</p>
Full article ">Figure 7
<p>(<b>A</b>) GO enrichment map of DMR-associated genes in comparison group JZ_vs_JD. (<b>a</b>) CG; (<b>b</b>) CHG; (<b>c</b>) CHH; (<b>d</b>) 6mA; (<b>B</b>) GO enrichment map of DMR-associated genes in comparison group SZ_vs_SD. (<b>a</b>) CG; (<b>b</b>) CHG; (<b>c</b>) CHH; (<b>d</b>) 6mA.</p>
Full article ">Figure 8
<p>GO enrichment map of DMR-associated genes of CpG type. (<b>a</b>) JD_vs_SD; (<b>b</b>) JZ_vs_JD; (<b>c</b>) JZ_vs_SZ; (<b>d</b>) SZ_vs_SD.</p>
Full article ">Figure 9
<p>Relative expression of genes. (<b>a</b>) inverted; (<b>b</b>) upright. “*” indicates significant differences (<span class="html-italic">p</span> &lt; 0.05); “**” indicates highly significant differences (<span class="html-italic">p</span> &lt; 0.01).</p>
Full article ">Figure 10
<p>Comparative analysis of homologous amino acid sequences of <span class="html-italic">DET2</span> in different plants.</p>
Full article ">Figure 11
<p>Phylogenetic tree of <span class="html-italic">DET2</span> homologous amino acid sequences of different plants.</p>
Full article ">
21 pages, 6659 KiB  
Review
Advancements in the Application of Ribosomally Synthesized and Post-Translationally Modified Peptides (RiPPs)
by Sang-Woo Han and Hyung-Sik Won
Biomolecules 2024, 14(4), 479; https://doi.org/10.3390/biom14040479 - 15 Apr 2024
Cited by 3 | Viewed by 4423
Abstract
Ribosomally synthesized and post-translationally modified peptides (RiPPs) represent a significant potential for novel therapeutic applications because of their bioactive properties, stability, and specificity. RiPPs are synthesized on ribosomes, followed by intricate post-translational modifications (PTMs), crucial for their diverse structures and functions. PTMs, such [...] Read more.
Ribosomally synthesized and post-translationally modified peptides (RiPPs) represent a significant potential for novel therapeutic applications because of their bioactive properties, stability, and specificity. RiPPs are synthesized on ribosomes, followed by intricate post-translational modifications (PTMs), crucial for their diverse structures and functions. PTMs, such as cyclization, methylation, and proteolysis, play crucial roles in enhancing RiPP stability and bioactivity. Advances in synthetic biology and bioinformatics have significantly advanced the field, introducing new methods for RiPP production and engineering. These methods encompass strategies for heterologous expression, genetic refactoring, and exploiting the substrate tolerance of tailoring enzymes to create novel RiPP analogs with improved or entirely new functions. Furthermore, the introduction and implementation of cutting-edge screening methods, including mRNA display, surface display, and two-hybrid systems, have expedited the identification of RiPPs with significant pharmaceutical potential. This comprehensive review not only discusses the current advancements in RiPP research but also the promising opportunities that leveraging these bioactive peptides for therapeutic applications presents, illustrating the synergy between traditional biochemistry and contemporary synthetic biology and genetic engineering approaches. Full article
Show Figures

Figure 1

Figure 1
<p>Representative therapeutic RiPPs and their classes. Letters in circles represent amino acids, and moieties undergoing modification are highlighted in red.</p>
Full article ">Figure 2
<p>Schematic representation of the RiPP biosynthetic pathway. The biosynthetic gene cluster, which includes various genes responsible for RiPP synthesis, is translated into a precursor peptide and tailoring enzymes. After translation, tailoring enzymes, recruited by the leader (and/or follower) peptide, modify the core peptide. Subsequently, a protease cleaves the leader (and/or follower) peptide, resulting in the production of the mature peptide. Red stars represent the occurrence of PTM.</p>
Full article ">Figure 3
<p>Genetic engineering for heterologous RiPP expression. (<b>A</b>) In DNA assembly methods such as Gibson assembly, multiple PCR products are ligated into an expression vector through a single isothermal reaction. (<b>B</b>) RecET facilitates homologous recombination between a lengthy linear fragment of a BGC and a vector (circular or linear) containing homologous regions. (<b>C</b>) ExoCET employs an exonuclease in addition to promoting recombination with longer fragments of BGC that carry non-homologous overhangs. (<b>D</b>) Upon transformation into yeast with fragments of BGC and a vector with homologous regions, the DNA fragments are assembled via the yeast’s native recombination system. (<b>E</b>) In the CAPTURE technique, the BGC fragment, isolated from genomic DNA by Cas12a, is ligated into synthetic receivers with <span class="html-italic">lox</span>P sites using DNA assembly methods, followed by circularization with the Cre enzyme. (<b>F</b>) Replacing native regulatory elements with uncharacterized mechanisms into well-understood systems facilitates the heterologous expression of selected BGC components, crucial for the biosynthesis of mature RiPP. (<b>G</b>) The expression of RiPP with bioactive properties triggers cell death in the host strain. However, by transporting a protease and a lytic protein to the periplasmic region and delaying the expression of the lytic protein, maturation of RiPP occurs, allowing the host cell to survive. (<b>H</b>) The addition of a fusion tag to a precursor peptide increases its stability and expression level, leading to an accumulation of mature RiPP in a heterologous cell.</p>
Full article ">Figure 4
<p>Strategies of RiPP engineering with respect to core peptides (<b>A</b>–<b>C</b>), leader peptides (<b>D</b>,<b>E</b>), and tailoring enzymes (<b>F</b>,<b>G</b>). (<b>A</b>–<b>C</b>) Addressing core peptides, substrate flexibilities of tailoring enzymes enable site-directed mutations (<b>A</b>), incorporation of foreign core peptides (<b>B</b>), and creation of hybrid core peptides with multiple domains (<b>C</b>), leading to a variety of RiPPs. (<b>D</b>,<b>E</b>) Utilizing leader peptides’ properties in guiding PTMs, diverse combinations of PTMs can be introduced on a single core peptide through chimeric leader peptides with multiple domains to guide PTMs (<b>D</b>) and leader peptide exchange using sortase A (<b>E</b>). (<b>F</b>) Protein engineering can enhance the substrate range of tailoring enzymes, broadening their application in generating RiPP variants. (<b>G</b>) The regulatory mechanism in tailoring enzyme activation can be simplified by introducing a free leader peptide and by fusing a tailoring enzyme with both a leader and a precursor peptide, simplifying the RiPP biosynthesis process.</p>
Full article ">Figure 5
<p>High-throughput screening methods utilized in RiPP research. (<b>A</b>) Phage display and (<b>B</b>) mRNA display techniques facilitate the straightforward detection of interactions between RiPPs and proteins or molecules. (<b>C</b>) The two-hybrid system can identify RiPPs that inhibit protein–protein interactions associated with diseases and infections. (<b>D</b>) Another in vivo screening method employs a genetic circuit based on intein, wherein the interaction between a RiPP and a target protein triggers the transcription of a reporter gene, allowing for the detection of RiPP–protein interactions. The antimicrobial activity of RiPPs can be assessed by their ability to inhibit the growth of (<b>E</b>) host cells and (<b>F</b>) neighboring cells. (<b>E</b>) Inhibition of host cell growth correlates with the concentration of RiPPs, as determined by NGS; a lower RiPP concentration signifies higher antimicrobial activity. (<b>F</b>) Inhibition of neighboring cell growth is evaluated using sensor cells that express a fluorescent protein; decreased fluorescence intensity indicates higher antimicrobial activity.</p>
Full article ">
Back to TopTop