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15 pages, 2875 KiB  
Article
Genome-Wide Analysis and Genomic Prediction of Chilling Tolerance of Maize During Germination Stage Using Genotyping-by-Sequencing SNPs
by Shiliang Cao, Tao Yu, Gengbin Yang, Wenyue Li, Xuena Ma and Jianguo Zhang
Agriculture 2024, 14(11), 2048; https://doi.org/10.3390/agriculture14112048 - 14 Nov 2024
Viewed by 259
Abstract
Chilling injury during the germination stage (CIGS) of maize significantly hinders production, particularly in middle- and high-latitude regions, leading to slow germination, seed decay, and increased susceptibility to pathogens. This study dissects the genetic architecture of CIGS resistance expressed in terms of the [...] Read more.
Chilling injury during the germination stage (CIGS) of maize significantly hinders production, particularly in middle- and high-latitude regions, leading to slow germination, seed decay, and increased susceptibility to pathogens. This study dissects the genetic architecture of CIGS resistance expressed in terms of the relative germination rate (RGR) in maize through association mapping using genotyping-by-sequencing (GBS) single-nucleotide polymorphisms (SNPs). A natural panel of 287 maize inbred lines was evaluated across multiple environments. The results revealed a broad-sense heritability of 0.68 for chilling tolerance, with 12 significant QTLs identified on chromosomes 1, 3, 5, 6, and 10. A genomic prediction analysis demonstrated that the rr-BLUP model outperformed other models in accuracy, achieving a moderate prediction accuracy of 0.44. This study highlights the potential of genomic selection (GS) to enhance chilling tolerance in maize, emphasizing the importance of training population size, marker density, and significant markers on prediction accuracy. These findings provide valuable insights for breeding programs aimed at improving chilling tolerance in maize. Full article
(This article belongs to the Section Crop Genetics, Genomics and Breeding)
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<p>Violin plots of RGR for AM population.</p>
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<p>Quantile–quantile plot of GWAS result of RGRs under four models.</p>
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<p>Manhattan plot of GWAS of RGRs. The dots mean −log(<span class="html-italic">p</span>) of each markers, the solid line stands for the threshold of significant level and the value is 6.74.</p>
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<p>Comparison of the prediction accuracy of different models for RGR: the red triangle represents the mean of the prediction accuracy, while the black solid line indicates the median of the prediction accuracy, the dot of circle type represents outliers.</p>
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<p>Influence of training population size on the prediction accuracy of the natural population (the red triangle symbol is the mean prediction accuracy, and the black long horizontal solid line is the median prediction accuracy, the dot of circle type represents outliers).</p>
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<p>Influence of number of significant markers and random markers on prediction accuracy to natural population.</p>
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<p>Influence of MAF on prediction accuracy of natural population. (The red triangle symbol is the mean prediction accuracy, and the black long horizontal solid line is the median prediction accuracy, the dot of circle type represents outliers).</p>
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<p>Influence of MAF 0.40–0.50 marker and random marker on prediction accuracy of natural population. The black solid dot represents outliers.</p>
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15 pages, 4713 KiB  
Article
The Gene Cluster Cj0423Cj0425 Negatively Regulates Biofilm Formation in Campylobacter jejuni
by Zhi Wang, Yuwei Wu, Ming Liu, Ling Chen, Kaishan Xiao, Zhenying Huang, Yibing Zhao, Huixian Wang, Yu Ding, Xiuhua Lin, Jiahui Zeng, Feiting Peng, Jumei Zhang, Juan Wang and Qingping Wu
Int. J. Mol. Sci. 2024, 25(22), 12116; https://doi.org/10.3390/ijms252212116 - 12 Nov 2024
Viewed by 360
Abstract
Abstract: Campylobacter jejuni (C. jejuni) is a zoonotic foodborne pathogen that is widely distributed worldwide. Its optimal growth environment is microaerophilic conditions (5% O2, 10% CO2), but it can spread widely in the atmospheric environment. Biofilms [...] Read more.
Abstract: Campylobacter jejuni (C. jejuni) is a zoonotic foodborne pathogen that is widely distributed worldwide. Its optimal growth environment is microaerophilic conditions (5% O2, 10% CO2), but it can spread widely in the atmospheric environment. Biofilms are thought to play an important role in this process. However, there are currently relatively few research works on the regulatory mechanisms of C. jejuni biofilm formation. In this study, a pan-genome analysis, combined with the analysis of biofilm phenotypic information, revealed that the gene cluster Cj0423Cj0425 is associated with the negative regulation of biofilm formation in C. jejuni. Through gene knockout experiments, it was observed that the Cj0423Cj0425 mutant strain significantly increased biofilm formation and enhanced flagella formation. Furthermore, pull-down assay revealed that Cj0424 interacts with 93 proteins involved in pathways such as fatty acid synthesis and amino acid metabolism, and it also contains the quorum sensing-related gene luxS. This suggests that Cj0423Cj0425 affects fatty acid synthesis and amino acid metabolism, influencing quorum sensing and strain motility, ultimately inhibiting biofilm formation. Full article
(This article belongs to the Section Molecular Biology)
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<p>Distribution of <span class="html-italic">Cj0423</span>–<span class="html-italic">Cj0425</span> in <span class="html-italic">C. jejuni</span> and its relationship with biofilm. (<b>a</b>) Pan-genome analysis of 234 <span class="html-italic">C. jejuni</span> genomes in the NCBI genome database; (<b>b</b>) <span class="html-italic">Cj0423</span>–<span class="html-italic">Cj0425</span> is not present in all <span class="html-italic">C. jejuni</span>; (<b>c</b>) Association analysis between <span class="html-italic">Cj0423</span>–<span class="html-italic">Cj0425</span> and biofilm formation; most of the strong biofilm formation strains do not contain <span class="html-italic">Cj0423</span>–<span class="html-italic">Cj0425</span>; red color indicates the presence of this gene, blue color indicates that the gene is absent, mauve color represents strong biofilm formation ability strain, gray-green color represents weak biofilm formation ability strain; (<b>d</b>) Distribution of <span class="html-italic">Cj0423</span>–<span class="html-italic">Cj0425</span> and biofilm forming ability.</p>
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<p><span class="html-italic">Cj0423</span>–<span class="html-italic">Cj0425</span> negatively regulates biofilm formation. (<b>a</b>) Determining the growth curves of the wild strain and knockout strain by shaking culture under microaerophilic conditions. (<b>b</b>) Scanning Electron Microscope observation of biofilm. (<b>c</b>) Crystal violet method to determine its biofilm formation ability. (<b>d</b>) Observation of biofilm under laser confocal microscope. SYTO-9 is green fluorescence and stains live cells, while PI is red fluorescence and stains dead cells. “ns” means the <span class="html-italic">p</span> value is greater than 0.05; “****” means the <span class="html-italic">p</span> value is less than 0.0001.</p>
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<p><span class="html-italic">Cj0423</span>–<span class="html-italic">Cj0425</span> inhibits the mobility of <span class="html-italic">C. jejuni</span>. (<b>a</b>) Wild-type strain on the left, mutant strain on the right. (<b>b</b>) The diameter of the mobility was measured, and the significance was analyzed using <span class="html-italic">t</span>-test. “***” means the <span class="html-italic">p</span> value is less than 0.0001.</p>
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<p>RT-qPCR verifies the results of pull-down, extracts DNA from biofilms at different times, and verifies related genes such as motility, chemotaxis, and quorum sensing. “ns” means the <span class="html-italic">p</span> value is greater than 0.05; “*” means the <span class="html-italic">p</span> value is less than 0.05; “**” means the <span class="html-italic">p</span> value is less than 0.01; “***” means the <span class="html-italic">p</span> value is less than 0.001; “****” means the <span class="html-italic">p</span> value is less than 0.0001.</p>
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<p>Protein purification and exogenous addition. (<b>a</b>) SDS-PAGE of the protein purification, in which Lane 1 is the 500 mM imidazole eluate. (<b>b</b>–<b>e</b>) The purified protein Cj0424 was added to ∆<span class="html-italic">Cj0423–Cj0425</span> and wild-type strain for culture, and the amount of biofilm formation at different times was measured. “ns” means the <span class="html-italic">p</span> value is greater than 0.05; “*” means the <span class="html-italic">p</span> value is less than 0.05; “**” means the <span class="html-italic">p</span> value is less than 0.01; “***” means the <span class="html-italic">p</span> value is less than 0.001; “****” means the <span class="html-italic">p</span> value is less than 0.0001.</p>
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<p>Pull-down identification of interacting proteins: (<b>a</b>) Experimental flow chart for pull-down, including ① the bait protein and whole bacterial protein, ② interaction between the bait protein and whole bacterial protein, ③ use of a nickel column to remove unbound proteins and elute interacting proteins, ④ electrophoresis identification of protein interaction results, and ⑤ protein identification using mass spectrometry. (<b>b</b>) SDS-PAGE identification of pull-down results, where Lane 1 represents protein Cj0424, Lane 2 is <span class="html-italic">C. jejuni</span> whole bacterial protein, Lanes 3–5 depict the impurity washing process, and Lane 6 represents the eluate containing Cj0424-interacting proteins. (<b>c</b>) Enrichment of protein pathways. (<b>d</b>) Construction of a protein interaction map.</p>
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<p>Cj0424 affects biofilm formation through multiple pathways. Cj0424 can regulate biofilm formation through quorum sensing, chemotaxis, motility, and oxidative stress.</p>
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17 pages, 2544 KiB  
Article
Microbial Basis for Suppression of Soil-Borne Disease in Crop Rotation
by Boxi Wang and Shuichi Sugiyama
Microorganisms 2024, 12(11), 2290; https://doi.org/10.3390/microorganisms12112290 - 11 Nov 2024
Viewed by 436
Abstract
The effect of crop rotation on soil-borne diseases is a representative case of plant–soil feedback in the sense that plant disease resistance is influenced by soils with different cultivation histories. This study examined the microbial mechanisms inducing the differences in the clubroot (caused [...] Read more.
The effect of crop rotation on soil-borne diseases is a representative case of plant–soil feedback in the sense that plant disease resistance is influenced by soils with different cultivation histories. This study examined the microbial mechanisms inducing the differences in the clubroot (caused by Plasmodiophora brassicae pathogen) damage of Chinese cabbage (Brassica rapa subsp. pekinensis) after the cultivation of different preceding crops. It addresses two key questions in crop rotation: changes in the soil bacterial community induced by the cultivation of different plants and the microbial mechanisms responsible for the disease-suppressive capacity of Chinese cabbage. Twenty preceding crops from different plant families showed significant differences in the disease damage, pathogen density, and bacterial community composition of the host plant. Structural equation modelling revealed that the relative abundance of four key bacterial orders in Chinese cabbage roots can explain 85% and 70% of the total variation in pathogen density and disease damage, respectively. Notably, the relative dominance of Bacillales and Rhizobiales, which have a trade-off relationship, exhibited predominant effects on pathogen density and disease damage. The disease-suppressive soil legacy effects of preceding crops are reflected in compositional changes in key bacterial orders, which are intensified by the bacterial community network. Full article
(This article belongs to the Section Plant Microbe Interactions)
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<p>Schematic design of the experiment based on plant–soil feedback, in which 20 preceding crops were used for soil conditioning, which were individually planted in pots filled with identical soil, and then Chinese cabbage seedlings were raised in the conditioned soil that was inoculated with the clubroot pathogen.</p>
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<p>Plots depicting the principal coordinate analysis (PCoA) of soil and root bacterial communities among the 20 preceding crop treatments. (<b>a</b>) Scatter diagram of the first and second components in the soil (closed circles) and root communities (triangles), including the original soil before conditioning (Osoil, open circle). (<b>b</b>) Correlation between the score of the second component of the root bacterial community and PD. lnPD represents the ln-transformed copy number of pathogen density. ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Linear discriminant analysis effect size (LEfSe) identifying biomarkers (microbial taxa) related to high- or low-PD and their enrichment patterns. (<b>a</b>) Cladogram representing the taxonomic distribution of biomarkers characterising high- and low-PD; (<b>b</b>) plot of the effect size of detected biomarkers represented by linear discriminant analysis (LDA) score; (<b>c</b>) heatmap of high- and low-PD abundant biomarkers. The preceding crop treatments were ordered by PD value, and the detected biomarkers were clustered according to Bray–Curtis distance dissimilarity.</p>
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<p>Rank–abundance curve and the correlation network among the top 20 bacterial orders, PD and DSI. Rank–abundance curve of 90 bacterial orders in the soil (blue) and root (red) microbial communities (<b>a</b>) and the relative abundances of the top 20 orders in the soil (blue) and root (red) bacterial communities (<b>b</b>). The numbers in networks of the soil (<b>c</b>) and root communities (<b>d</b>) refer to (<b>b</b>). The size of each circle represents relative abundance. The blue, red, and grey circles represent the co-present, mutually exclusive, and neutral groups in terms of their relationships with PD, respectively. The lines show the presence of significant correlation. The red and blue lines between the circles indicate the presence of significantly negative and positive correlations, respectively. Solid lines indicate the correlations with PD and DSI, and dotted lines indicate correlations between bacterial orders.</p>
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<p>(<b>a</b>) Schematic representation of structural equation modelling (SEM) explaining the microbial basis of clubroot suppression during the conditioning and feedback phases. The model at the feedback phase indicated that the key bacterial order (Bacillales) and two other orders (Xanthomonodales and Sphingomonadales) explained 70% of the variation in clubroot damage (DSI) and 85% of the variation in PD. The model at the conditioning phase showed that the abundance differences in Bacillales in the Chinese cabbage roots were mainly the result of a weak colonisation effect from the soil to the root and the enhancement of the initial difference by a strong antagonistic relationship with Rhizobiales. The values of the arrows represent the standardised regression coefficient. (<b>b</b>) Plot depicting the relationships between PD and the relative abundance of Bacillales (red, <span class="html-italic">r</span> = −0.747 ***) and Rhizobiales (black, <span class="html-italic">r</span> = 0.623 **). lnPD represents the ln-transformed copy number of pathogen density. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Plots showing the relationships between the relative abundances of the soil and root communities for Bacillales (<b>a</b>) and Rhizobiales (<b>b</b>), and the relationships between the abundances of the two orders in the soil (<b>c</b>) and root communities (<b>d</b>). Open circles represent anomalous samples of Rhizobiales in the soil community, which were omitted from the analysis. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01.</p>
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7 pages, 1244 KiB  
Brief Report
Kallmann Syndrome: Functional Analysis of a CHD7 Missense Variant Shows Aberrant RNA Splicing
by Josianne Nunes Carriço, Catarina Inês Gonçalves, José Maria Aragüés and Manuel Carlos Lemos
Int. J. Mol. Sci. 2024, 25(22), 12061; https://doi.org/10.3390/ijms252212061 - 10 Nov 2024
Viewed by 411
Abstract
Kallmann syndrome is a rare disorder characterized by hypogonadotropic hypogonadism and an impaired sense of smell (anosmia or hyposmia) caused by congenital defects in the development of the gonadotropin-releasing hormone (GnRH) and olfactory neurons. Mutations in several genes have been associated with Kallmann [...] Read more.
Kallmann syndrome is a rare disorder characterized by hypogonadotropic hypogonadism and an impaired sense of smell (anosmia or hyposmia) caused by congenital defects in the development of the gonadotropin-releasing hormone (GnRH) and olfactory neurons. Mutations in several genes have been associated with Kallmann syndrome. However, genetic testing of this disorder often reveals variants of uncertain significance (VUS) that remain uninterpreted without experimental validation. The aim of this study was to analyze the functional consequences of a heterozygous missense VUS in the CHD7 gene (c.4354G>T, p.Val1452Leu), in a patient with Kallmann syndrome with reversal of hypogonadism. The variant, located in the first nucleotide of exon 19, was analyzed using minigene assays to determine its effect on ribonucleic acid (RNA) splicing. These showed that the variant generates two different transcripts: a full-length transcript with the missense change (p.Val1452Leu), and an abnormally spliced transcript lacking exon 19. The latter results in an in-frame deletion (p.Val1452_Lys1511del) that disrupts the helicase C-terminal domain of the CHD7 protein. The variant was reclassified as likely pathogenic. These findings demonstrate that missense variants can exert more extensive effects beyond simple amino acid substitutions and underscore the critical role of functional analyses in VUS reclassification and genetic diagnosis. Full article
(This article belongs to the Special Issue Reproductive Endocrinology Research)
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<p>Functional analysis of the <span class="html-italic">CHD7</span> missense variant. (<b>A</b>) The patient harbored a heterozygous missense variant in the <span class="html-italic">CHD7</span> gene (c.4354G&gt;T), located at the first nucleotide of exon 19 (highlighted in bold). An 850-base-pair (bp) genomic fragment from the patient, encompassing exon 19 (with and without the variant) and flanking intronic sequences, was cloned into the pcAT7-Glo1 minigene vector (containing a modified version of the human β-globin gene) at the NdeI and BglII restriction sites, between globin exons 1 (GloE1) and 2 (GloE2). The constructed minigene plasmid was transfected into COS-7 cells, and the resulting ribonucleic acid (RNA) was analyzed using reverse transcriptase polymerase chain reaction (RT-PCR) with primers Act and ActT7R. (<b>B</b>) Electrophoresis and sequencing of the amplified complementary deoxyribonucleic acid (cDNA) fragments showed that the wild-type allele generated a single, normally spliced transcript (769 bp). In contrast, the mutant allele produced two distinct transcripts: one corresponding to the normally spliced transcript containing the missense variant (769 bp), and another with an aberrantly spliced transcript with a deletion (del) of exon 19 (589 bp). PCR amplification of the GloE3 exon served as an internal control. The asterisk indicates heteroduplex fragments. (<b>C</b>) Densitometric analysis of the amplified cDNA demonstrated that the wild-type allele exclusively generated normally spliced transcripts (100%), while the mutant allele expressed both the missense and exon-skipped transcripts in proportions of 59% and 41%, respectively. (<b>D</b>) SWISS-MODEL-generated three-dimensional representation of the CHD7 protein showing the wild-type (normal) protein containing a valine at position 1452, the missense protein containing a leucine at this position, and the deleted protein which lacks a sequence of 60 amino acids (in red).</p>
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24 pages, 2970 KiB  
Review
piRNA Defense Against Endogenous Retroviruses
by Milky Abajorga, Leonid Yurkovetskiy and Jeremy Luban
Viruses 2024, 16(11), 1756; https://doi.org/10.3390/v16111756 - 9 Nov 2024
Viewed by 862
Abstract
Infection by retroviruses and the mobilization of transposable elements cause DNA damage that can be catastrophic for a cell. If the cell survives, the mutations generated by retrotransposition may confer a selective advantage, although, more commonly, the effect of new integrants is neutral [...] Read more.
Infection by retroviruses and the mobilization of transposable elements cause DNA damage that can be catastrophic for a cell. If the cell survives, the mutations generated by retrotransposition may confer a selective advantage, although, more commonly, the effect of new integrants is neutral or detrimental. If retrotransposition occurs in gametes or in the early embryo, it introduces genetic modifications that can be transmitted to the progeny and may become fixed in the germline of that species. PIWI-interacting RNAs (piRNAs) are single-stranded, 21–35 nucleotide RNAs generated by the PIWI clade of Argonaute proteins that maintain the integrity of the animal germline by silencing transposons. The sequence specific manner by which piRNAs and germline-encoded PIWI proteins repress transposons is reminiscent of CRISPR, which retains memory for invading pathogen sequences. piRNAs are processed preferentially from the unspliced transcripts of piRNA clusters. Via complementary base pairing, mature antisense piRNAs guide the PIWI clade of Argonaute proteins to transposon RNAs for degradation. Moreover, these piRNA-loaded PIWI proteins are imported into the nucleus to modulate the co-transcriptional repression of transposons by initiating histone and DNA methylation. How retroviruses that invade germ cells are first recognized as foreign by the piRNA machinery, as well as how endogenous piRNA clusters targeting the sequences of invasive genetic elements are acquired, is not known. Currently, koalas (Phascolarctos cinereus) are going through an epidemic due to the horizontal and vertical transmission of the KoRV-A gammaretrovirus. This provides an unprecedented opportunity to study how an exogenous retrovirus becomes fixed in the genome of its host, and how piRNAs targeting this retrovirus are generated in germ cells of the infected animal. Initial experiments have shown that the unspliced transcript from KoRV-A proviruses in koala testes, but not the spliced KoRV-A transcript, is directly processed into sense-strand piRNAs. The cleavage of unspliced sense-strand transcripts is thought to serve as an initial innate defense until antisense piRNAs are generated and an adaptive KoRV-A-specific genome immune response is established. Further research is expected to determine how the piRNA machinery recognizes a new foreign genetic invader, how it distinguishes between spliced and unspliced transcripts, and how a mature genome immune response is established, with both sense and antisense piRNAs and the methylation of histones and DNA at the provirus promoter. Full article
(This article belongs to the Special Issue The Diverse Regulation of Transcription in Endogenous Retroviruses)
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<p>Retroviral genomic RNA and its transformations. Shown are schematic diagrams for the virion-associated genomic RNA, the viral cDNA, and the unspliced and spliced transcripts that are common to all retroviruses. All retroviruses possess at least the three genes, <span class="html-italic">gag</span>, <span class="html-italic">pol</span>, and <span class="html-italic">env</span>. Note that during reverse transcription, two sequential strand-exchange reactions extend the 5’ and 3’ ends of the cDNA beyond the limits of the genomic RNA template.</p>
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<p>Structure of recKoRV. The koala retrovirus, KoRV-A (shown in gray), encodes gag, pol, and env with long terminal repeats at the ends. PhER (shown in blue), is an endogenous retrovirus with no protein coding capacity. Recombinant KoRV (recKoRV) typically contains the KoRV-A 5’ LTR, truncated gag, truncated env, and 3’ LTR with the 3’end of PhER in the middle.</p>
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<p>Host restriction factors and retroviral antagonists. Restriction factors are shown in red and viral antagonists are shown in blue. CypA: cyclophilin A; KZFPs: Kruppel-associated box (KRAB)-containing zinc finger proteins; HUSH: human silencing hub (HUSH) complex; Vpr: Viral protein R: Vif: Viral infectivity factor; Vpu: Viral protein U; APOBEC3G (apolipoprotein B mRNA editing enzyme, catalytic subunit 3G); SAMHD1: SAM domain and HD domain-containing protein 1.</p>
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<p>piRNA biogenesis in nurse cells of Drosophila ovaries. <span class="html-italic">D. melanogaster</span> ovaries contain a series of developing egg chambers in linearly arranged repetitive strings called ovarioles. An egg chamber is characterized by a germline cyst, which contains 15 germline nurse cells and an oocyte that is surrounded by somatic follicle cells. In the nurse cells, germline dual-strand clusters decorated with H3K9me3 marks bound by Rhino-Deadlock-Cutoff (RDC) complex are transcribed by RNA Polymerase II. These transcripts are exported into the cytoplasm, where they are processed into mature piRNAs by the ping-pong amplification loop or phasing. (<b>a</b>) Ping-pong amplification: The feed forward cleavage of complementary transcripts by Aub and Ago3 results in piRNAs with a 10-nucleotide overlap. (<b>b</b>) Phasing: Armi shuttles Aub bound to a piRNA precursor to the mitochondria where Zucchini generates piRNA intermediates through cleavage adjacent to uridines along the length of the precursor. These piRNA intermediates loaded on Piwi are then processed into mature piRNAs.</p>
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<p>Spermatogenic defects of PIWI mutants in mice and hamsters. In mice, PIWIL2 and PIWIL4 mutants arrest at the zygotene stage of meiosis I and PIWIL1 mutants arrest at the round spermatid stage. In hamsters, PIWIL3-KO does not cause any defect in the testes. PIWIL1-KO results in arrest at the pachytene stage. PIWIL2 and PIWIL4 defective hamsters arrest during mitosis as gonocytes. Solid lines show normal development; red crosses (x) indicate the stage of developmental block.</p>
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<p>Oogenic defects of PIWI mutants in hamsters. PIWIL1 deficiency results in arrest at the 2-cell stage. PIWIL2-KO mutants have no defects in oocytes. PIWIL3 deficient hamsters arrest at the 2-cell stage, but some fertilized oocytes complete development. Solid lines show normal development; red crosses (x) indicate the stage of developmental block.</p>
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<p>Model of innate and adaptive piRNA genome defense. Upon invasion of the germline by a novel retrovirus, the retroviral transcript is directly processed into positive sense piRNAs. Later, the adaptive piRNA response is established where antisense piRNAs are made. These antisense piRNAs can directly target the sense transcript resulting in the co-transcriptional repression of the transposon.</p>
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19 pages, 5212 KiB  
Article
Targeting Bacterial Communication: Evaluating Phytochemicals as LuxS Inhibitors to Disrupt Quorum Sensing
by Yiannis Sarigiannis and Christos Papaneophytou
Macromol 2024, 4(4), 753-771; https://doi.org/10.3390/macromol4040045 - 5 Nov 2024
Viewed by 687
Abstract
Bacterial quorum sensing (QS) is a critical communication process that regulates gene expression in response to population density, influencing activities such as biofilm formation, virulence, and antibiotic resistance. This study investigates the inhibitory effects of five phytochemicals—apigenin, carnosol, chlorogenic acid, quercetin, and rosmarinic [...] Read more.
Bacterial quorum sensing (QS) is a critical communication process that regulates gene expression in response to population density, influencing activities such as biofilm formation, virulence, and antibiotic resistance. This study investigates the inhibitory effects of five phytochemicals—apigenin, carnosol, chlorogenic acid, quercetin, and rosmarinic acid—on the S-ribosylhomocysteinase (LuxS) enzyme, a key player in AI-2 signaling across both Gram-positive and Gram-negative bacteria. Using molecular docking studies, we identified that these phytochemicals interact with the LuxS enzyme, with apigenin, carnosol, chlorogenic acid, and rosmarinic acid binding within the substrate-binding pocket and exhibiting binding scores below −7.0 kcal/mol. Subsequent in vitro assays demonstrated that these compounds inhibited AI-2 signaling and biofilm formation in Escherichia coli MG1655 in a concentration-dependent manner. Notably, carnosol and chlorogenic acid showed the most potent effects, with IC50 values of approximately 60 μM. These findings suggest that these phytochemicals may serve as potential QS inhibitors, providing a foundation for developing new anti-pathogenic agents to combat bacterial infections without promoting antibiotic resistance. Further studies are warranted to explore the therapeutic applications of these compounds in both clinical and agricultural settings. Full article
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Graphical abstract

Graphical abstract
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<p>(<b>A</b>) The predicted 3D structure of <span class="html-italic">E. coli</span> MG1655 LuxS. The enzyme is depicted as a dimer, consisting of two identical monomers shown in red (Chain A) and green (Chain B) ribbon diagrams. Each chain coordinates an Fe<sup>2+</sup> ion, represented as grey spheres. (<b>B</b>) The active site of the enzyme, formed by contributions from amino acids of both chains, is highlighted using stick models. The red and green colors indicate Chains A and B, respectively. (<b>C</b>) Multiple sequence alignment of LuxS from <span class="html-italic">E. coli</span> MG1655 (UniProt: P45578) with LuxS proteins from related species, including <span class="html-italic">Haemophilus influenzae</span> (UniProt: P44007), <span class="html-italic">Salmonella typhi</span> (UniProt: Q8Z4D7), <span class="html-italic">Vibrio cholerae</span> (UniProt: Q9KUG4), <span class="html-italic">Campylobacter concisus</span> (UniProt: A7ZGE2), and <span class="html-italic">Neisseria meningitidis</span> (UniProt: A9M0P7). The alignment was performed using Clustal Omega (<a href="https://www.ebi.ac.uk/Tools/msa/clustalo/" target="_blank">https://www.ebi.ac.uk/Tools/msa/clustalo/</a>, accessed on 1 August 2024). Arrows indicate key amino acids involved in catalysis (substrate binding or enzyme activity). Identical amino acids are marked with an asterisk (*), conserved amino acids with a colon (:), and semi-conserved amino acids with a period (.).</p>
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<p>Chemical structures of the main components detected in the ethanolic extracts of oregano, rosemary, and common sage from Cyprus flora.</p>
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<p>Docking studies of the five phytochemicals with the LuxS protein. (<b>A</b>) Overall representation of the binding sites for the five compounds. The LuxS protein is shown in ribbon representation, with Chain A in red and Chain B in green. The phytochemicals are depicted in stick representation with different colors: apigenin (yellow), carnosol (brown), chlorogenic acid (purple), quercetin (cyan), and rosmarinic acid (blue). (<b>B</b>,<b>C</b>) The locations of the five phytochemicals relative to Chain A and Chain B, respectively. All compounds, except quercetin, are positioned within the same active site located in the cavity between the two chains.</p>
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<p>Molecular interactions of LuxS with five phytochemicals, namely apigenin (<b>A</b>), carnosol (<b>B</b>), chlorogenic acid (<b>C</b>), quercetin (<b>D</b>) and rosmarinic acid (<b>E</b>), displayed as 2D images. The binding score (in kcal/mol) for each compound is indicated below their respective interaction diagram. The amino acid residues of LuxS of Chains A and B involved in the interactions are labeled and highlighted in colored circles. These circles correspond to different interactions indicated at the top right panel of this figure. Docking studies were carried out using PyRx v1.1 (AutoDock Vina). The 2D images were obtained using BIOVIA Discovery Studio.</p>
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<p>Inhibition of AI-2 signaling by apigenin (<b>A</b>), carnosol (<b>B</b>), chlorogenic acid (<b>C</b>), quercetin (<b>D</b>), and rosmarinic acid (<b>E</b>). The percentage of AI-2 inhibition is plotted against the concentration of each compound (ranging from 0 to 200 μM). Each graph also includes the chemical structure of the corresponding phytochemical. The IC<sub>50</sub> values indicate the concentration of each compound required to inhibit 50% of AI-2 signaling, highlighting differences in their inhibitory potencies.</p>
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<p>Effects of five phytochemicals—apigenin, carnosol, chlorogenic acid (chlor. acid), quercetin (querc.), and rosmarinic acid (rosm. acid)—on biofilm formation by <span class="html-italic">E. coli</span> MG1655, as quantified by crystal violet staining and measuring absorbance at 570 nm. Data are presented as the percentage inhibition of biofilm formation compared with the control (no compound). Results are shown as mean values ± standard deviation from three independent experiments. Error bars represent standard deviations. Statistical analysis was performed using ANOVA followed by Tukey’s multiple-comparison test. Only statistically significant differences are shown and indicated by asterisks: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Effects of the phytochemicals apigenin, carnosol, chlorogenic acid (chlor. acid), quercetin, and rosmarinic acid (rosm. acid) on <span class="html-italic">E. coli</span> MG1655 growth. (<b>A</b>) <span class="html-italic">E. coli</span> MG1655 was incubated in the absence and presence of 200 μM of each phytochemical in a 96-well plate (200 μL per well) for 20 h. (<b>B</b>) The effects of the phytochemicals at a final concentration of 200 μM on bacterial growth were also determined using viable plate counts after 24 h of incubation, as described in the text. Results are presented as mean values ± SD, with n = 3.</p>
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15 pages, 2224 KiB  
Article
Chromosomal Type II Toxin–Antitoxin Systems May Enhance Bacterial Fitness of a Hybrid Pathogenic Escherichia coli Strain Under Stress Conditions
by Jessika C. A. Silva, Lazaro M. Marques-Neto, Eneas Carvalho, Alejandra M. G. Del Carpio, Camila Henrique, Luciana C. C. Leite, Thais Mitsunari, Waldir P. Elias, Danielle D. Munhoz and Roxane M. F. Piazza
Toxins 2024, 16(11), 469; https://doi.org/10.3390/toxins16110469 - 1 Nov 2024
Viewed by 684
Abstract
The functions of bacterial plasmid-encoded toxin–antitoxin (TA) systems are unambiguous in the sense of controlling cells that fail to inherit a plasmid copy. However, its role in chromosomal copies is contradictory, including stress-response-promoting fitness and antibiotic treatment survival. A hybrid pathogenic Escherichia coli [...] Read more.
The functions of bacterial plasmid-encoded toxin–antitoxin (TA) systems are unambiguous in the sense of controlling cells that fail to inherit a plasmid copy. However, its role in chromosomal copies is contradictory, including stress-response-promoting fitness and antibiotic treatment survival. A hybrid pathogenic Escherichia coli strain may have the ability to colonize distinct host niches, facing contrasting stress environments. Herein, we determined the influence of multiple environmental stress factors on the bacterial growth dynamic and expression profile of previously described TA systems present in the chromosome of a hybrid atypical enteropathogenic and extraintestinal E. coli strain. Genomic analysis revealed 26 TA loci and the presence of five type II TA systems in the chromosome. Among the tested stress conditions, osmotic and acid stress significantly altered the growth dynamics of the hybrid strain, enhancing the necessary time to reach the stationary phase. Using qPCR analyses, 80% of the studied TA systems were differentially expressed in at least one of the tested conditions, either in the log or in the stationary phase. These data indicate that type II TA systems may contribute to the physiology of pathogenic hybrid strains, enabling their adaptation to different milieus. Full article
(This article belongs to the Special Issue Toxins: 15th Anniversary)
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Figure 1
<p>(<b>A</b>) Experimental design for bacterial growth under stress. The illustration depicts how the experiments were designed for cultivation under stress conditions, the media employed for bacterial growth, and the bacterial cultivation phase in which samples were collected for qPCR analyses. Created with BioRender.com. Count of BA1250 Colony Forming Units (CFUs/mL) under different culture conditions in the (<b>B</b>) logarithmic and (<b>C</b>) stationary phase. Statistical analysis was performed using the non-parametric <span class="html-italic">t</span>-test, compared to bacteria growth in the LB medium. * <span class="html-italic">p</span>-value &lt; 0.02; ** <span class="html-italic">p</span>-value &lt; 0.002.</p>
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<p>Relative expression of toxin–antitoxins in a log growth phase in duplicates of three independent experiments. <span class="html-italic">E. coli</span> BA1250 toxin–antitoxin gene pairs (<span class="html-italic">ccdB</span>/<span class="html-italic">ccdA</span>, <span class="html-italic">yhaV/prlF</span>, <span class="html-italic">mazE/mazF</span>, <span class="html-italic">yoeB/yefM</span>, and <span class="html-italic">pasT/pasI</span>) were evaluated in the log growth phase under nutritional scarcity, oxidative stress, acid shock, osmotic stress, and LB medium condition. Genes were considered up/downregulated when relative average expression was −1 &gt; Log2Fc &gt; 1 in comparison to the LB group. Statistical significance was considered when the <span class="html-italic">p</span> value &lt; 0.05 in 2-way ANOVA test comparing toxin and antitoxin at the same condition. (*) Represent statistical significance with <span class="html-italic">p</span> &lt; 0.05; (**) represent statistical significance with <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Relative expression of toxin–antitoxins in the stationary growth phase in duplicates of three independent experiments. <span class="html-italic">E. coli</span> BA1250 toxin–antitoxin gene pairs (<span class="html-italic">ccdB/ccdA</span>, <span class="html-italic">yhaV/prlF</span>, <span class="html-italic">mazE/mazF</span>, <span class="html-italic">yoeB/yefM</span>, and <span class="html-italic">pasT/pasI</span>) were evaluated in the stationary growth phase under nutritional scarcity, oxidative stress, acid shock, osmotic stress, and stress-free LB medium condition. Genes were considered up/downregulated when relative average expression was −1 &gt; Log2Fc &gt; 1 in comparison to the LB group. Statistical significance was considered when the <span class="html-italic">p</span> value &lt; 0.05 in a 2-way ANOVA test comparing toxin and antitoxin at the same condition. (*) Represent statistical significance with <span class="html-italic">p</span> &lt; 0.05; (****) represent statistical significance with <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>(<b>A</b>) Barplot demonstrating the predicted presence and absence of the 39 gene components of TA systems detected into aEPEC, ExPEC, Hybrid, and tEPEC strains chromosomes and plasmids. Bars indicate the percentage of predicted gene presence among the bacterial strains within each pathotype. Gene predicted rate of type I, II, IV, and V TA system components present in aEPEC, ExPEC, Hybrid, and tEPEC strains in the (<b>B</b>) chromosome and in the (<b>C</b>) plasmid. Bars indicate the percentage of predicted gene presence among the bacterial strains within each TA system type. * <span class="html-italic">p</span> &lt; 0.05, as determined by a non-parametric one-way ANOVA test.</p>
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34 pages, 2800 KiB  
Review
Recent Progress in Nanomaterial-Based Surface-Enhanced Raman Spectroscopy for Food Safety Detection
by Hagar S. Bahlol, Jiawen Li, Jiamin Deng, Mohamed F. Foda and Heyou Han
Nanomaterials 2024, 14(21), 1750; https://doi.org/10.3390/nano14211750 - 31 Oct 2024
Viewed by 657
Abstract
Food safety has recently become a widespread concern among consumers. Surface-enhanced Raman scattering (SERS) is a rapidly developing novel spectroscopic analysis technique with high sensitivity, an ability to provide molecular fingerprint spectra, and resistance to photobleaching, offering broad application prospects in rapid trace [...] Read more.
Food safety has recently become a widespread concern among consumers. Surface-enhanced Raman scattering (SERS) is a rapidly developing novel spectroscopic analysis technique with high sensitivity, an ability to provide molecular fingerprint spectra, and resistance to photobleaching, offering broad application prospects in rapid trace detection. With the interdisciplinary development of nanomaterials and biotechnology, the detection performance of SERS biosensors has improved significantly. This review describes the advantages of nanomaterial-based SERS detection technology and SERS’s latest applications in the detection of biological and chemical contaminants, the identification of foodborne pathogens, the authentication and quality control of food, and the safety assessment of food packaging materials. Finally, the challenges and prospects of constructing and applying nanomaterial-based SERS sensing platforms in the field of food safety detection are discussed with the aim of early detection and ultimate control of foodborne diseases. Full article
(This article belongs to the Section Biology and Medicines)
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Graphical abstract

Graphical abstract
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<p>Illustration of multidimensional spectroscopy and nanomaterial dimensions: Schematic of multidimensional spectroscopy setup. A laser generates pulses to excite a sample on a substrate, producing vibrational signals that are subsequently captured by a spectrometer. Nanomaterials, categorized by their dimensions, include 0D spherical and cubic nanoparticles, 1D nanotubes and nanorods, 2D graphene and other layered materials, and 3D nanostructured arrays. Reprinted with permission from ACS Mater. Au 2022, 2, 5, 552–557 [<a href="#B15-nanomaterials-14-01750" class="html-bibr">15</a>].</p>
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<p>Overall advantages of SERS in food safety detection.</p>
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<p>Detection of pesticides on fruit using Raman spectroscopy. Illustration of pesticide detection in apples using Raman spectroscopy. The inset shows pesticide molecules on the apple surface. A laser from the Raman spectrometer was used to target the surface to produce the Raman spectrum. The graph indicates the presence of pesticides (TMTD, MPT, and MG) with distinct peaks at specific Raman shifts (e.g., 1348, 1379, and 1617 cm<sup>−1</sup>), enabling the precise identification and quantification of pesticide residues. Reprinted with permission from Analytical Chemistry, 2017, 89(4), 2424–2431 [<a href="#B180-nanomaterials-14-01750" class="html-bibr">180</a>].</p>
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<p>Fabrication process of the cauliflower-inspired 3D SERS substrate. Reprinted with permission from Analytical Chemistry, 2019, 91.6: 3885–3892 [<a href="#B181-nanomaterials-14-01750" class="html-bibr">181</a>].</p>
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<p>A schematic experimental setup for the detection of antibiotics using Raman spectroscopy and SERS substrates. Reprinted with permission from Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2023, 122584 [<a href="#B107-nanomaterials-14-01750" class="html-bibr">107</a>].</p>
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<p>Schematic diagrams show the creation of COF-based Raman tags (<b>A</b>) and their application in simultaneous immuno-SERS detection of <span class="html-italic">E. coli</span> and <span class="html-italic">S. enteritidis</span> (<b>B</b>). Reprinted with permission from Talanta, 243 (2022): 123369 [<a href="#B116-nanomaterials-14-01750" class="html-bibr">116</a>].</p>
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<p>(<b>a</b>) Raman spectra of three samples: (i) SLGO capture substrate, (ii) 4-MBA on an untreated glass slide, and (iii) SLGO-4MBA substrate. (<b>b</b>) TEM image illustrating the sandwich-type immunocomplex consisting of mag-MoO<sub>3</sub>/NoV-LPs/4-MBA-antibody-SLGO. Reprinted with permission from ACS Applied Materials and Interfaces (2020), 12(39):43522-43534 [<a href="#B123-nanomaterials-14-01750" class="html-bibr">123</a>].</p>
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21 pages, 4046 KiB  
Article
Phosphonates of Pectobacterium atrosepticum: Discovery and Role in Plant–Pathogen Interactions
by Olga Parfirova, Polina Mikshina, Olga Petrova, Andrey Smolobochkin, Alexander Pashagin, Alexander Burilov and Vladimir Gorshkov
Int. J. Mol. Sci. 2024, 25(21), 11516; https://doi.org/10.3390/ijms252111516 - 26 Oct 2024
Viewed by 524
Abstract
Many phytopathogens’ gene products that contribute to plant–pathogen interactions remain unexplored. In one of the most harmful phytopathogenic bacterium Pectobacterium atrosepticum (Pba), phosphonate-related genes have been previously shown to be among the most upregulated following host plant colonization. However, phosphonates, compounds [...] Read more.
Many phytopathogens’ gene products that contribute to plant–pathogen interactions remain unexplored. In one of the most harmful phytopathogenic bacterium Pectobacterium atrosepticum (Pba), phosphonate-related genes have been previously shown to be among the most upregulated following host plant colonization. However, phosphonates, compounds characterized by a carbon–phosphorus bond in their composition, have not been described in Pectobacterium species and other phytopathogenic bacteria, with the exception of Pseudomonas syringae and Pantoea ananatis. Our study aimed to determine whether Pba synthesizes extracellular phosphonates and, if so, to analyze their physiological functions. We demonstrated that Pba produces two types of extracellular phosphonates: 2-diethoxyphosphorylethanamine and phenylphosphonic acid. Notably, such structures have not been previously described among natural phosphonates. The production of Pba phosphonates was shown to be positively regulated by quorum sensing and in the presence of pectic compounds. Pba phosphonates were found to have a positive effect on Pba stress resistance and a negative effect on Pba virulence. The discovered Pba phosphonates are discussed as metabolites that enable Pba to control its “harmful properties”, thereby maintaining its ecological niche (the host plant) in a relatively functional state for an extended period. Full article
(This article belongs to the Section Molecular Microbiology)
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<p>The expression levels of the <span class="html-italic">fom1</span> gene in <span class="html-italic">Pectobacterium atrosepticum</span> SCRI1043 cells (<b>A</b>) and <sup>31</sup>P NMR spectra of the preparations of supernatants of <span class="html-italic">P. atrosepticum</span> cultures (<b>B</b>,<b>C</b>) grown under different conditions. The expression levels were determined after 24 h of growth in LB medium, minimal medium (MM), and MM supplemented with plant extract (MM + PE). The expression level of the <span class="html-italic">fom1</span> gene in the cells grown in LB is equated to one. Asterisks (*) show a significant difference (Mann–Whitney two-sided test, <span class="html-italic">p</span> &lt; 0.05, five biological replicates) from the variant grown in LB or between the variants designated by bracket. The presence of <sup>31</sup>P NMR signals at 15–25 ppm was assayed in the preparations of supernatants of cultures grown for 48 h in minimal medium (MM) and MM supplemented with plant extract (MM + PE). The <sup>31</sup>P NMR spectrum of the preparation of plant extract is shown in (<b>D</b>). The detection of phosphonates was performed in at least five independent experiments.</p>
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<p><sup>31</sup>P NMR spectra of the preparations of cultural supernatants of the wild-type <span class="html-italic">Pectobacterium atrosepticum</span> SCRI1043 (WT) (<b>A</b>), <span class="html-italic">P. atrosepticum</span> Δ<span class="html-italic">fom1</span> mutant (<b>B</b>), and complemented Δ<span class="html-italic">fom1</span> mutant carrying the <span class="html-italic">fom1</span> gene within the recombinant plasmid (<b>C</b>) grown for 48 h in minimal medium supplemented with plant extract (MM + PE). The detection of phosphonates was performed in at least five independent experiments.</p>
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<p>NMR spectra of the phosphonate-containing fraction of the <span class="html-italic">Pectobacterium atrosepticum</span> cultural supernatant. (<b>A</b>) Difference <sup>13</sup>C spectrum of the cultural supernatant of wild-type <span class="html-italic">P. atrosepticum</span> and its phosphonate-deficient Δ<span class="html-italic">fom1</span> mutant. (<b>B</b>) <sup>1</sup>H spectrum of the cultural supernatant of wild-type <span class="html-italic">P. atrosepticum</span>.</p>
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<p>ESI-QTOF spectra of the phosphonate-containing fraction of the <span class="html-italic">Pectobacterium atrosepticum</span> cultural supernatant. (<b>A</b>) Mass spectra of the sample in negative and positive modes. (<b>B</b>) MS/MS spectra of major ions 374<sup>1−</sup> and 339<sup>1+</sup> and the scheme of their possible fragmentation.</p>
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<p>Fragments of the <sup>13</sup>C spectrum of the phosphonate-containing fraction of the <span class="html-italic">Pectobacterium atrosepticum</span> cultural supernatant purified by chromatography and the molecular structures of the identified phosphonates (marked by red frames). EtO—ethyl group.</p>
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<p>Effect of quorum sensing on phosphonate production in <span class="html-italic">Pectobacterium atrosepticum</span> SCRI1043. (<b>A</b>) Expression levels of the <span class="html-italic">fom1</span> gene in wild-type <span class="html-italic">P. atrosepticum</span> (WT) and <span class="html-italic">P. atrosepticum</span> quorum-deficient Δ<span class="html-italic">expI</span> mutant grown for 24 h in minimal medium (MM), and MM supplemented with plant extract (MM + PE). The expression level of the <span class="html-italic">fom1</span> gene in the WT cells grown in MM is equated to one. The presented values were obtained from five biological replicates. The table located under the diagram shows significant differences (<span class="html-italic">p</span>-values) between the designated experimental groups (Mann–Whitney two-sided test with Bonferroni correction for multiple comparisons, <span class="html-italic">p</span> &lt; 0.05, five biological replicates). NS—non-significant. (<b>B</b>,<b>C</b>) <sup>31</sup>P NMR spectra of the preparations of cultural supernatants of the wild-type <span class="html-italic">P. atrosepticum</span> (WT) (<b>B</b>) and <span class="html-italic">P. atrosepticum</span> Δ<span class="html-italic">expI</span> mutant (<b>C</b>) grown for 48 h in minimal medium with plant extract (MM + PE). The detection of phosphonates was performed in at least three independent experiments.</p>
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<p>Effect of pectic compounds on phosphonate production in <span class="html-italic">Pectobacterium atrosepticum</span> SCRI1043. (<b>A</b>) The expression levels of the <span class="html-italic">fom1</span> gene in <span class="html-italic">P. atrosepticum</span> cells grown for 24 h in (1) minimal medium (MM), (2) MM supplemented with plant extract (MM + PE), (3) modified minimal medium where sucrose was substituted with pectin (MMM), (4) MMM supplemented with plant extract (MMM + PE). The expression level of the <span class="html-italic">fom1</span> gene in the cells grown in MM is equated to one. The presented values were obtained from five biological replicates. The table located under the diagram shows significant differences (<span class="html-italic">p</span>-values) between the designated experimental groups (Mann–Whitney two-sided test with Bonferroni correction for multiple comparisons, <span class="html-italic">p</span> &lt; 0.05, five biological replicates). NS—non-significant. (<b>B</b>,<b>C</b>) <sup>31</sup>P NMR spectra of the preparations of supernatants of <span class="html-italic">P. atrosepticum</span> cultures grown for 48 h in MMM (<b>B</b>) and MMM supplemented with plant extract (MMM + PE) (<b>C</b>). The detection of phosphonates was performed in at least three independent experiments.</p>
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<p>Virulence of the wild-type <span class="html-italic">Pectobacterium atrosepticum</span> SCRI1043 (WT) (green column), <span class="html-italic">P. atrosepticum</span> Δ<span class="html-italic">fom1</span> mutant (red column), and complemented Δ<span class="html-italic">fom1</span> mutant carrying the <span class="html-italic">fom1</span> gene within the recombinant plasmid (yellow column) toward tobacco plants non-treated (0 mM) with salicylic acid (SA) or primed with 0.2 or 1.0 mM of SA. Plants were pretreated with SA (or water) one day before infection. The percentage of plants with visible disease symptoms (tissue maceration) was assessed on the fifth day after infection. The presented results were obtained from 7 independent experiments; in each experiment, 20–25 plants were assessed for each experimental variant. Asterisks (*) show a significant difference (Mann–Whitney two-sided test, <span class="html-italic">p</span> &lt; 0.05) from the variant where SA-non-treated plants were infected with the wild-type <span class="html-italic">P. atrosepticum</span> (first column); asterisks above the brackets show a significantly higher disease incidence rate in plants primed with 1.0 mM SA following infection with Δ<span class="html-italic">fom1</span> mutant than with WT or complemented Δ<span class="html-italic">fom1</span> mutant. The dark blue line shows the level of hydrogen peroxide in plants one day after treatment with 0, 0.2, or 1.0 mM of SA.</p>
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<p>Resistance of the wild-type <span class="html-italic">Pectobacterium atrosepticum</span> SCRI1043 (WT) (green column), <span class="html-italic">P. atrosepticum</span> Δ<span class="html-italic">fom1</span> mutant (red column), and complemented Δ<span class="html-italic">fom1</span> mutant carrying the <span class="html-italic">fom1</span> gene within the recombinant plasmid (yellow column) to oxidative stress (H<sub>2</sub>O<sub>2</sub>). Cells were cultured in modified minimal medium supplemented with plant extract (MMM + PE) for 24 h in the presence of 0, 0.15, and 0.30 mM of H<sub>2</sub>O<sub>2</sub> before plating for CFU titer analysis. The presented values are the means of five biological replicates. Inoc—inoculation titer. Asterisks (*) show the significance of the difference (Mann–Whitney two-sided test, <span class="html-italic">p</span> &lt; 0.05) in cell titer between variants designated by brackets.</p>
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<p>Relative levels of extracellular pectate lyase (PL), protease (Prt), cellulase (Cel), and polygalacturonase (PG) activities in the wild-type <span class="html-italic">Pectobacterium atrosepticum</span> SCRI1043 (WT) (green column), <span class="html-italic">P. atrosepticum</span> Δ<span class="html-italic">fom1</span> mutant (red column), and complemented Δ<span class="html-italic">fom1</span> mutant carrying the <span class="html-italic">fom1</span> gene within the recombinant plasmid (yellow column). Enzymatic activities were determined in the cultural supernatants after one day of cultivation of bacteria in the modified minimal medium supplemented with plant extract (MMM + PE). The presented values are the means of at least five biological replicates. The activity levels of the wild type were equated to one. Asterisks (*) show the significance of the difference (Mann–Whitney two-sided test, <span class="html-italic">p</span> &lt; 0.05) between variants designated by brackets.</p>
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19 pages, 3781 KiB  
Article
Endophytic Penicillium oxalicum AUMC 14898 from Opuntia ficus-indica: A Novel Source of Tannic Acid Inhibiting Virulence and Quorum Sensing of Extensively Drug-Resistant Pseudomonas aeruginosa
by Hoda S. Nouh, Nessma A. El-Zawawy, Mohamed Halawa, Ebrahim M. Shalamesh, Sameh Samir Ali, Grażyna Korbecka-Glinka, Awad Y. Shala and Shimaa El-Sapagh
Int. J. Mol. Sci. 2024, 25(20), 11115; https://doi.org/10.3390/ijms252011115 - 16 Oct 2024
Viewed by 974
Abstract
Pseudomonas aeruginosa is a harmful pathogen that causes a variety of acute and chronic infections through quorum sensing (QS) mechanisms. The increasing resistance of this bacterium to numerous antibiotics has created a demand for new medications that specifically target QS. Endophytes can be [...] Read more.
Pseudomonas aeruginosa is a harmful pathogen that causes a variety of acute and chronic infections through quorum sensing (QS) mechanisms. The increasing resistance of this bacterium to numerous antibiotics has created a demand for new medications that specifically target QS. Endophytes can be the source of compounds with antibacterial properties. This research is the first to examine tannic acid (TA) produced by endophytic fungus as a potential biotherapeutic agent. A novel endophytic fungal isolate identified as Penicillium oxalicum was derived from the cladodes of Opuntia ficus-indica (L.). The species identification for this isolate was confirmed through sequencing of the internal transcribed spacer region. The metabolites from the culture of this isolate were extracted using ethyl acetate, then separated and characterized using chromatographic methods. This led to the acquisition of TA, a compound that shows strong anti-QS and excellent antibacterial effects against extensively drug-resistant P. aeruginosa strains. Furthermore, it was shown that treating P. aeruginosa with the obtained TA reduced the secretion of virulence factors controlled by QS in a dose-dependent manner, indicating that TA inhibited the QS characteristics of P. aeruginosa. Simultaneously, TA significantly inhibited the expression of genes associated with QS, including rhlR/I, lasR/I, and pqsR. In addition, in silico virtual molecular docking showed that TA could efficiently bind to QS receptor proteins. Our results showed that P. oxalicum could be a new source of TA for the treatment of infections caused by extensively drug-resistant P. aeruginosa. Full article
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<p>Experimental design used in this study.</p>
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<p>Morphological and molecular identification of <span class="html-italic">Penicillium oxalicum</span> AUMC 14898: (<b>A</b>) Colonies grown on potato dextrose agar at 30 °C for 7days. (<b>B</b>) Conidiophores and conidia at 40× magnification. (<b>C</b>) Phylogenetic tree based on ITS sequences of 18S rDNA, including the fungal strain isolated in this study (<span class="html-italic">Penicillium oxalicum</span> AUMC14898, arrowed).</p>
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<p>HPLC chromatogram of purified compound (<b>A</b>) and standard compound (<b>B</b>).</p>
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<p>TEM images of <span class="html-italic">P. aeruginosa</span> PA-05 strain at 5000× magnification. (<b>A</b>) Untreated cells with intact cell membranes. (<b>B</b>) Treated cells with TA resulted in great morphological changes of the bacteria and lysis of cells (black arrows) in addition to development of vacuoles (red arrows).</p>
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<p>(<b>A</b>) Reduction of several virulence characteristics of <span class="html-italic">P. aeruginosa</span> PA-05 isolate by baicalein (BCL) and tannic acid (TA). (<b>B</b>) RT-qPCR analysis of various genes involved in quorum sensing (QS) of PA-05 isolate. The results are represented as ratios corresponding to the fold change of genes treated with tannic acid (TA) at sub-MIC value (75 µg/mL), as well as control (without treatment). For comparison of the experimental groups, two-way ANOVA was performed followed by Šídák’s multiple comparisons test. **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Effect of tannic acid (TA) and baicalein (BCL) at sub-MIC concentrations on motility of <span class="html-italic">P. aeruginosa</span> strain PA-05. Swimming (<b>A</b>) and swarming (<b>B</b>). Bar graphs show the average percentages of triplicate results. Values are mean ± standard error. For comparison of the experimental groups, one-way ANOVA was performed followed by Tukey’s multiple comparison test. ** <span class="html-italic">p</span>-value &lt; 0.01 and **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Molecular docking of tannic acid with LasR, RhlR and PqsR proteins represented in 3D and 2D conformations.</p>
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<p>A proposed mechanism of antibacterial and anti-QS actions of tannic acid against <span class="html-italic">P. aeruginosa</span>.</p>
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27 pages, 2386 KiB  
Review
Detection Methods for Pine Wilt Disease: A Comprehensive Review
by Sana Tahir, Syed Shaheer Hassan, Lu Yang, Miaomiao Ma and Chenghao Li
Plants 2024, 13(20), 2876; https://doi.org/10.3390/plants13202876 - 14 Oct 2024
Viewed by 1117
Abstract
Pine wilt disease (PWD), caused by the nematode Bursaphelenchus xylophilus, is a highly destructive forest disease that necessitates rapid and precise identification for effective management and control. This study evaluates various detection methods for PWD, including morphological diagnosis, molecular techniques, and remote [...] Read more.
Pine wilt disease (PWD), caused by the nematode Bursaphelenchus xylophilus, is a highly destructive forest disease that necessitates rapid and precise identification for effective management and control. This study evaluates various detection methods for PWD, including morphological diagnosis, molecular techniques, and remote sensing. While traditional methods are economical, they are limited by their inability to detect subtle or early changes and require considerable time and expertise. To overcome these challenges, this study emphasizes advanced molecular approaches such as real-time polymerase chain reaction (RT-PCR), droplet digital PCR (ddPCR), and loop-mediated isothermal amplification (LAMP) coupled with CRISPR/Cas12a, which offer fast and accurate pathogen detection. Additionally, DNA barcoding and microarrays facilitate species identification, and proteomics can provide insights into infection-specific protein signatures. The study also highlights remote sensing technologies, including satellite imagery and unmanned aerial vehicle (UAV)-based hyperspectral analysis, for their capability to monitor PWD by detecting asymptomatic diseases through changes in the spectral signatures of trees. Future research should focus on combining traditional and innovative techniques, refining visual inspection processes, developing rapid and portable diagnostic tools for field application, and exploring the potential of volatile organic compound analysis and machine learning algorithms for early disease detection. Integrating diverse methods and adopting innovative technologies are crucial to effectively control this lethal forest disease. Full article
(This article belongs to the Special Issue Biotechnology and Genetic Engineering in Forest Trees)
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<p>PWN undergoes a multistage lifecycle, commencing as an egg and progressing through four distinct larval phases (L1 to L4) before ultimately maturing into an adult. Under optimal environmental conditions, these nematodes possess the capability to complete their lifecycle in as few as 4 to 5 days. They rapidly spread to new host trees via their primary vector, the <span class="html-italic">Monochamus</span> beetle, and reproduce within the host tree while primarily feeding on its vascular tissues.</p>
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<p>Disease progression typically involves a series of stages that delineate the advancement and worsening of a condition over time. In the context of infectious diseases, these stages include the incubation, prodromal, acute, and convalescence periods. Each stage is characterized by distinct symptoms and physiological alterations that influence the strategies employed for treatment and management.</p>
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<p>The techniques employed for nematode protein identification have the potential to significantly enhance the accuracy and efficiency of diagnostic procedures for species such as <span class="html-italic">B. xylophilus</span> and <span class="html-italic">B. mucronatus</span>. These advancements could substantially impact pest management strategies and ecological research. However, the labor-intensive nature of these techniques and the necessity for a positive reference sample may limit their practical application in rapid field assessments and routine monitoring.</p>
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<p>Research on <span class="html-italic">B. xylophilus</span> has focused on characterizing its secretome and identifying potential indicators of virulence. Comparative analyses of secretomes and proteomes across multiple <span class="html-italic">B. xylophilus</span> isolates reveal variations in protein expression patterns, which may contribute to differences in nematode pathogenicity and host specificity.</p>
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<p>Satellite-, aircraft-, or ground-based sensors capture and record reflected or emitted energy across multiple wavelengths of the electromagnetic spectrum to remotely sense an object or area. These remote sensing techniques detect surface features, vegetation health, soil moisture, and other critical properties. The data obtained through these methods is invaluable for applications such as land use mapping, environmental monitoring, and natural resource management.</p>
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<p>Endophytic fungi and plants collaborate through a biological pathway initiated by plant receptors detecting fungal signals. This recognition triggers a cascade of defense responses and metabolic alterations that mutually benefit both organisms, including enhanced nutrient acquisition and pathogen resistance. During this interaction, metabolites are exchanged, and gene expression is modulated in both partners, facilitating the establishment of a stable symbiotic relationship.</p>
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<p>This study aims to enhance early detection methods, streamline management strategies, and mitigate the global impact of PWD on pine forest ecosystems.</p>
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16 pages, 4340 KiB  
Article
“Grafting-from” and “Grafting-to” Poly(N-isopropyl acrylamide) Functionalization of Glass for DNA Biosensors with Improved Properties
by Pauline Skigin, Perrine Robin, Alireza Kavand, Mounir Mensi and Sandrine Gerber-Lemaire
Polymers 2024, 16(20), 2873; https://doi.org/10.3390/polym16202873 - 11 Oct 2024
Viewed by 619
Abstract
Surface-based biosensors have proven to be of particular interest in the monitoring of human pathogens by means of their distinct nucleic acid sequences. Genosensors rely on targeted gene/DNA probe hybridization at the surface of a physical transducer and have been exploited for their [...] Read more.
Surface-based biosensors have proven to be of particular interest in the monitoring of human pathogens by means of their distinct nucleic acid sequences. Genosensors rely on targeted gene/DNA probe hybridization at the surface of a physical transducer and have been exploited for their high specificity and physicochemical stability. Unfortunately, these sensing materials still face limitations impeding their use in current diagnostic techniques. Most of their shortcomings arise from their suboptimal surface properties, including low hybridization density, inadequate probe orientation, and biofouling. Herein, we describe and compare two functionalization methodologies to immobilize DNA probes on a glass substrate via a thermoresponsive polymer in order to produce genosensors with improved properties. The first methodology relies on the use of a silanization step, followed by PET-RAFT of NIPAM monomers on the coated surface, while the second relies on vinyl sulfone modifications of the substrate, to which the pre-synthetized PNIPAM was grafted to. The functionalized substrates were fully characterized by means of X-ray photoelectron spectroscopy for their surface atomic content, fluorescence assay for their DNA hybridization density, and water contact angle measurements for their thermoresponsive behavior. The antifouling properties were evaluated by fluorescence microscopy. Both immobilization methodologies hold the potential to be applied to the engineering of DNA biosensors with a variety of polymers and other metal oxide surfaces. Full article
(This article belongs to the Section Polymer Applications)
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<p>Characterization of PET-RAFT polymerization in solution (DMSO)<b>:</b> (<b>a</b>) <sup>1</sup>H NMR of PET-RAFT after 1 to 5 h of polymerization. The peaks used for the computation of monomer conversion are highlighted in green. (<b>b</b>) Kinetic study of PET-RAFT PNIPAM polymerization, with monomer conversion as a function of time. (<b>c</b>) Relationship between ln([M]<sub>0</sub>/[M]) and time for the PET-RAFT polymerization of PNIPAM. (<b>d</b>) Molecular weight of PNIPAM synthetized via PET-RAFT polymerization measured by GPC.</p>
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<p>(<b>a</b>) High-resolution XPS spectra of C 1s signal on <b>S-Sil-CTA</b>. (<b>b</b>) High-resolution XPS spectra of N 1s signal on <b>S-Sil-CTA</b>. (<b>c</b>) High-resolution XPS spectra of P 2p signal on <b>S-Sil-PNIPAM-COOH</b> and <b>S-Sil-PNIPAM-DNA</b>.</p>
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<p>High-resolution XPS spectra of (<b>a</b>) C 1s and (<b>b</b>) N 1s signal of <b>S-Sulf</b>.</p>
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<p>High-resolution XPS spectra of the P 2p signal of <b>S-Sulf</b>, <b>S-Sulf-PNIPAM-COOH</b>, and <b>S-Sulf-PNIPAM-DNA</b> slides.</p>
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<p>Contact angle pictures of borosilicate, <b>S-Sil-PNIPAM-DNA</b>, and <b>S-Sulf-PNIPAM-DNA</b> below and above the LCST.</p>
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<p>(<b>a</b>) Fluorescence images of <b>S-Sil-PNIPAM-DNA</b> and <b>S-Sulf-PNIPAM-DNA</b> after incubation with BSA-AF488 at 22 °C or 42 °C. (<b>b</b>) Fluorescence levels measured on the different surfaces (n = 4 independent measurements).</p>
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<p>Functionalization of PNIPAM-coated glass substrates with oligonucleotides via “grafting-from” and “grafting-to” pathways.</p>
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<p>Post functionalization of PNIPAM polymer in solution.</p>
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<p>Schematic illustration of DNA hybridization density quantification, here with <b>S-Sil-PNIPAM-DNA.</b> During the procedure, an <b>S-Sil/Sulf-PNIPAM-COOH</b> slide serves as a negative control. This illustration was made with Biorender.com (accessed on 1 September 2024).</p>
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10 pages, 1438 KiB  
Review
Genotype–Phenotype Correlation of GNAS Gene: Review and Disease Management of a Hotspot Mutation
by Lorenzo Cipriano, Rosario Ferrigno, Immacolata Andolfo, Roberta Russo, Daniela Cioffi, Maria Cristina Savanelli, Valeria Pellino, Antonella Klain, Achille Iolascon and Carmelo Piscopo
Int. J. Mol. Sci. 2024, 25(20), 10913; https://doi.org/10.3390/ijms252010913 - 10 Oct 2024
Viewed by 651
Abstract
Defects of the GNAS gene have been mainly associated with pseudohypoparathyroidism Ia. To date, pathogenic missense, frameshift, non-sense and splicing variants have been described in all the 13 exons of the GNAS gene. Of them, a specific mutation, namely the 4 bp deletion [...] Read more.
Defects of the GNAS gene have been mainly associated with pseudohypoparathyroidism Ia. To date, pathogenic missense, frameshift, non-sense and splicing variants have been described in all the 13 exons of the GNAS gene. Of them, a specific mutation, namely the 4 bp deletion c.565_568delGACT, is currently considered a mutation hotspot. Recent articles performed genotype–phenotype correlations in patients with GNAS-related pseudohypoparathyroidism Ia (PHP1a) but a specific focus on this hotspot is still lacking. We reported two cases, from our department, of PHP1a associated with c.565_568delGACT deletion and performed a literature review of all the previously reported cases of the 4 bp deletion hotspot. We found a higher prevalence of brachydactyly, round face, intellectual disability and subcutaneous/heterotopic ossifications in patients with the c.565_568delGACT as compared to the other variants in the GNAS gene. The present study highlights the different prevalence of some clinical features in patients with the c.565_568delGACT variant in the GNAS gene, suggesting the possibility of a personalized diagnostic follow-up and surveillance for these patients. Full article
(This article belongs to the Special Issue Molecular Progression of Genome-Related Diseases)
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<p>Search strategy and selection.</p>
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<p>Prevalence of c.565_568delGACT-related disorders and clinical features associated with PHP1a due to c.565_568delGACT variant. Sub/het ossifications = subcutaneous/heterotopic ossifications.</p>
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<p>Specific surveillance in PHP1a disorders associated with the c.565_568delGACT variant.</p>
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12 pages, 3411 KiB  
Review
Riboswitch Mechanisms for Regulation of P1 Helix Stability
by Jason R. Stagno and Yun-Xing Wang
Int. J. Mol. Sci. 2024, 25(19), 10682; https://doi.org/10.3390/ijms251910682 - 4 Oct 2024
Viewed by 756
Abstract
Riboswitches are highly structured RNA regulators of gene expression. Although found in all three domains of life, they are particularly abundant and widespread in bacteria, including many human pathogens, thus making them an attractive target for antimicrobial development. Moreover, the functional versatility of [...] Read more.
Riboswitches are highly structured RNA regulators of gene expression. Although found in all three domains of life, they are particularly abundant and widespread in bacteria, including many human pathogens, thus making them an attractive target for antimicrobial development. Moreover, the functional versatility of riboswitches to recognize a myriad of ligands, including ions, amino acids, and diverse small-molecule metabolites, has enabled the generation of synthetic aptamers that have been used as molecular probes, sensors, and regulatory RNA devices. Generally speaking, a riboswitch consists of a ligand-sensing aptamer domain and an expression platform, whose genetic control is achieved through the formation of mutually exclusive secondary structures in a ligand-dependent manner. For most riboswitches, this involves formation of the aptamer’s P1 helix and the regulation of its stability, whose competing structure turns gene expression ON/OFF at the level of transcription or translation. Structural knowledge of the conformational changes involving the P1 regulatory helix, therefore, is essential in understanding the structural basis for ligand-induced conformational switching. This review provides a summary of riboswitch cases for which ligand-free and ligand-bound structures have been determined. Comparative analyses of these structures illustrate the uniqueness of these riboswitches, not only in ligand sensing but also in the various structural mechanisms used to achieve the same end of regulating switch helix stability. In all cases, the ligand stabilizes the P1 helix primarily through coaxial stacking interactions that promote helical continuity. Full article
(This article belongs to the Special Issue Structure, Dynamics, and Function of Nucleic Acids: 2nd Edition)
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<p>Adenine riboswitch. Comparison of the apo (PDB ID: 5E54) [<a href="#B18-ijms-25-10682" class="html-bibr">18</a>] and holo (PDB ID: 4TZX) [<a href="#B19-ijms-25-10682" class="html-bibr">19</a>] structures of the adenine riboswitch aptamer (<b>A</b>) and its ligand-binding site (<b>B</b>). All-atom RMSD between apo2 and holo structures is 3.6 Å. Adenine ligand is shown in cyan. Key residues are colored in magenta. Regions of coaxial stacking that stabilize P1 upon ligand binding are colored in yellow. Blue dots represent missing residues that are disordered in the crystal structure. Motion of conformational change from apo2 to holo states is indicated by the yellow arrow. See also Movie 1. (<b>C</b>) Secondary structure (PDB ID: 4TZX), generated using VARNA (v3-93) [<a href="#B20-ijms-25-10682" class="html-bibr">20</a>].</p>
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<p>FMN riboswitch. Comparison of the apo (PDB ID: 6WJR) [<a href="#B23-ijms-25-10682" class="html-bibr">23</a>] and holo (PDB ID: 3F2Q) [<a href="#B21-ijms-25-10682" class="html-bibr">21</a>] structures (all-atom RMSD: 2.1 Å) of the FMN riboswitch aptamer (<b>A</b>) and its ligand-binding site (<b>B</b>). Domains I and II are colored in blue and gray, respectively. Ligand is shown in cyan. Key residues are colored in magenta. Regions of coaxial stacking that stabilize P1 upon ligand binding are colored in yellow. Motion of conformational change from apo to holo states is indicated by the yellow arrow. Black dotted lines indicate the direction of coaxial stacking in each state. See also Movie 2. (<b>C</b>) Secondary structure (PDB ID: 3F2Q), generated using VARNA (v3-93).</p>
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<p>Gln riboswitch. Comparison of the apo (PDB ID: 5DDO) and holo (PDB ID: 5DDP) structures (all-atom RMSD 12.8 Å) of the Gln riboswitch aptamer [<a href="#B24-ijms-25-10682" class="html-bibr">24</a>] (<b>A</b>) and its ligand-binding site (<b>B</b>) Ligand is shown in cyan. Key residues are colored in magenta. Regions of coaxial stacking that stabilize P1 upon ligand binding are colored in yellow. Blue dots represent missing residues that are disordered in the crystal structure. Motion of conformational change from apo to holo states is indicated by the yellow arrow. See also Movie 3. (<b>C</b>) Secondary structure (PDB ID: 5DDP), generated using VARNA (v3-93).</p>
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<p>THF riboswitch. Comparison of the apo (PDB ID: 7KD1) [<a href="#B28-ijms-25-10682" class="html-bibr">28</a>] and holo (PDB ID: 4LVV) [<a href="#B25-ijms-25-10682" class="html-bibr">25</a>] structures (all-atom RMSD 3.6 Å) of the THF riboswitch aptamer (<b>A</b>) and its ligand-binding site (<b>B</b>). Ligand is shown in cyan. Key residues are colored in magenta, and the location of the pseudoknot (PK) is indicated. Regions of coaxial stacking that stabilize P1 upon ligand binding are colored in yellow. Motion of conformational change from apo to holo states is indicated by the yellow arrow. See also Movie 4. (<b>C</b>) Secondary structure (PDB ID: 4LVV), generated using VARNA (v3-93).</p>
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<p>TPP riboswitch. Comparison of the apo (PDB ID: 8F4O) [<a href="#B33-ijms-25-10682" class="html-bibr">33</a>] and holo (PDB ID: 2GDI) [<a href="#B31-ijms-25-10682" class="html-bibr">31</a>] structures (all-atom RMSD 11.2 Å) of the TPP riboswitch aptamer (<b>A</b>) and its ligand-binding site (<b>B</b>). Ligand is shown in cyan. Key residues are colored in magenta. Regions of coaxial stacking that stabilize P1 upon ligand binding are colored in yellow. Motion of conformational change from apo to holo states is indicated by the yellow arrow. See also Movie 5. (<b>C</b>) Secondary structure (PDB ID: 2HOJ) [<a href="#B35-ijms-25-10682" class="html-bibr">35</a>], generated using VARNA (v3-93).</p>
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24 pages, 4171 KiB  
Review
Spectral Intelligence: AI-Driven Hyperspectral Imaging for Agricultural and Ecosystem Applications
by Faizan Ali, Ali Razzaq, Waheed Tariq, Akhtar Hameed, Abdul Rehman, Khizar Razzaq, Sohaib Sarfraz, Nasir Ahmed Rajput, Haitham E. M. Zaki, Muhammad Shafiq Shahid and Gabrijel Ondrasek
Agronomy 2024, 14(10), 2260; https://doi.org/10.3390/agronomy14102260 - 30 Sep 2024
Viewed by 2770
Abstract
Ensuring global food security amid mounting challenges, such as population growth, disease infestations, resource limitations, and climate change, is a pressing concern. Anticipated increases in food demand add further complexity to this critical issue. Plant pathogens, responsible for substantial crop losses (up to [...] Read more.
Ensuring global food security amid mounting challenges, such as population growth, disease infestations, resource limitations, and climate change, is a pressing concern. Anticipated increases in food demand add further complexity to this critical issue. Plant pathogens, responsible for substantial crop losses (up to 41%) in major crops like wheat, rice, maize, soybean, and potato, exacerbate the situation. Timely disease detection is crucial, yet current practices often identify diseases at advanced stages, leading to severe infestations. To address this, remote sensing and Hyperspectral imaging (HSI) have emerged as robust and nondestructive techniques, exhibiting promising results in early disease identification. Integrating machine learning algorithms with image data sets enables precise spatial–temporal disease identification, facilitating timely detection, predictive modeling, and effective disease management without compromising fitness or climate adaptability. By harnessing these cutting-edge technologies and data-driven decision-making, growers can optimize input costs while achieving enhanced yields, making significant strides toward global food security in the face of climate change risks. This review will discuss some of the foundational concepts of remote sensing, several platforms used for remote sensing data collection, successful application of the approach, and its future perspective. Full article
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<p>(<b>A</b>) Satellite-based: Uses satellite imagery for large-scale crop monitoring, detecting diseases and pests over vast areas, but with lower resolution compared to other methods. (<b>B</b>) Airplane-base: Aerial sensors on airplanes offer medium-range, high-resolution imaging, ideal for identifying issues like water stress or pest damage over extensive fields. (<b>C</b>) Drone-based: Drones provide high-resolution, close-range crop monitoring, offering real-time data for precision farming tasks like targeted spraying and disease detection. (<b>D</b>) Ground-based: Ground-level sensors and systems collect detailed data on soil moisture, plant health, and nutrient levels, offering precise, continuous monitoring at the field level.</p>
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<p>(<b>A</b>) Supervised learning approach uses classification or regression technique to produce result output. (<b>B</b>) Unsupervised learning focuses on clustering and association techniques for result production.</p>
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<p>Several stages involved in the pre-processing of hyperspectral imagery data collection to disease detection modelling.</p>
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