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17 pages, 2834 KiB  
Article
The Anti-Metastatic Potential of Aronia Leaf Extracts on Colon Cancer Cells
by Katarzyna Owczarek, Miłosz Caban, Dorota Sosnowska, Dominika Kajszczak and Urszula Lewandowska
Nutrients 2024, 16(23), 4110; https://doi.org/10.3390/nu16234110 - 28 Nov 2024
Abstract
Background/Objectives: Numerous studies have demonstrated the health benefits of polyphenols found in aronia fruits; however, little is known about how aronia leaf polyphenols impact colorectal cancer (CRC). This study aimed to evaluate the in vitro anti-metastatic and anti-invasive activity of crude aronia leaf [...] Read more.
Background/Objectives: Numerous studies have demonstrated the health benefits of polyphenols found in aronia fruits; however, little is known about how aronia leaf polyphenols impact colorectal cancer (CRC). This study aimed to evaluate the in vitro anti-metastatic and anti-invasive activity of crude aronia leaf extract (ACE) and purified phenolic-rich aronia leaf extract (APE) against two CRC cell lines (SW-480 and HT-29). Methods: Migration and invasion potential of ACE and APE were evaluated. Moreover, ELISA and gelatin zymography were performed to detect translational and activity changes in CRC cells after aronia extracts treatment. Results: We found that a 100 µg/mL concentration of ACE and APE almost entirely downregulated the migration and invasion of SW-480 cells, showing greater effectiveness than HT-29 cells. The observed inhibition was concentration-dependent and statistically significant. Additionally, extracts reduced the product of MMP-2 and MMP-9 gene expression at the protein level and simultaneously inhibited the activity of both MMPs. An APE at 300 µg/mL for SW-480 and 600 µg/mL for HT-29 resulted in a notable reduction in MMP-2 protein synthesis by 72% and 50%, respectively. In contrast, MMP-9 protein synthesis decreased by 48% and 59% in HT-29 cells treated with 300 µg/mL and 600 µg/mL of ACE, respectively. The levels of gelatinase activity were similar for both CRC lines, and the APE tested at a concentration of 300 µg/mL reached almost the IC50 value after 48 h of incubation. Conclusions: Based on the presented results, we provided an experimental foundation for future in vitro and in vivo studies on the potential effects and activities of aronia leaves. Full article
(This article belongs to the Section Phytochemicals and Human Health)
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Figure 1

Figure 1
<p>Aronia leaf extracts modulated the migration of human SW-480 (<b>A</b>) and HT-29 (<b>B</b>) cells. The inhibitory effects of ACE and APE (50 and 100 µg/mL) on the migration of CRC cells were determined using a Transwell assay. Cells were seeded in inserts with a chemoattractant in the lower chamber. After 48 h (SW-480) or 96 h (HT-29) incubation, migratory cells that passed through the membranes were stained, photographed, and measured using NIH ImageJ analysis software. Negative and positive controls were obtained from untreated SW-480 cells (CTRL) and cells treated with 50 µM EGCG. At the same time, negative and positive controls for HT-29 were obtained after stimulation with 50 ng/mL TNF/TPA (CTRL) and with 100 µM EGCG, respectively. Each value represents mean ± SEM, n = 3 independent experiments (each performed in duplicate). Significance of differences between means: **** <span class="html-italic">p</span> &lt; 0.0001 versus CTRL (one-way ANOVA followed by Newman–Keuls post hoc test).</p>
Full article ">Figure 2
<p>Aronia leaf extracts modulated the invasion of human SW-480 (<b>A</b>) and HT-29 (<b>B</b>) cells. The inhibitory effects of ACE and APE (50 and 100 µg/mL ) on the invasion of CRC cells were determined using a Transwell assay. Cells were seeded in Matrigel-coated inserts with a chemoattractant in the lower chamber. After 48 h (SW-480) or 96 h (HT-29) incubation, invaded cells that passed through the membranes were stained, photographed, and measured using NIH ImageJ analysis software. Negative and positive controls were obtained from untreated SW-480 cells (CTRL) and cells treated with 50 µM EGCG. In contrast, negative and positive controls for HT-29 were obtained after stimulation with 50 ng/mL TNF/TPA (CTRL) and 100 µM EGCG, respectively. Each value represents mean ± SEM, n = 3 independent experiments (each performed in duplicate). Significance of differences between means: *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001 versus CTRL (one-way ANOVA followed by Newman–Keuls post hoc test).</p>
Full article ">Figure 3
<p>Aronia leaf extracts modulated the product of MMP-2 and MMP-9 gene expression at the protein level, which was determined using ELISAs. After 48 h of incubation, the level of both metalloproteinases in SW-480 cells (<b>A</b>,<b>C</b>) was examined after chokeberry extracts treatment at concentrations of 200 and 300 µg/mL, whereas in HT-29 cells (<b>B</b>,<b>D</b>) at concentrations of 300 and 600 µg/mL. Negative controls for SW-480 cells (CTRL) were obtained from untreated cells. In the case of HT-29 cells, negative controls were obtained from cells stimulated with 50 ng/mL TNF/TPA (CTRL). Both cell lines were cultured in a 3% FBS medium. An amount of 50 or 100 µM EGCG was used as a positive control for SW-480 or HT-29 cells. Each value represents mean ± SEM, n = 3 independent experiments (each performed in duplicate). Significance of differences between means: * <span class="html-italic">p &lt;</span> 0.1, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001 versus CTRL (one-way ANOVA followed by Newman–Keuls post hoc test).</p>
Full article ">Figure 4
<p>Aronia leaf extracts modulated MMP-2 (<b>A</b>) and MMP-9 (<b>B</b>) activities in SW-480 cells. The ACE and APE inhibitory effect was determined using zymography assays. The activity levels of MMPs were analyzed in culture supernatants. SW-480 cells were treated with aronia leaf extracts at 200, 300, and 500 µg/mL concentrations for 24 and 48 h. Negative and positive controls were obtained from untreated cells (CTRL) and cells treated with 50 µM EGCG cultured in a medium containing 3% FBS. The lower panel (<b>C</b>) shows the representative zymograms obtained for SW-480 cells after ACE and APE treatment for 48 h. Each value represents mean ± SEM, n = 3 independent experiments (each performed in duplicate). Results are expressed as a percentage of MMP levels compared to CTRL, calculated after scanning densitometry and computerized analysis of gels. Significance of differences between means: ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001 versus CTRL (one-way ANOVA followed by Newman–Keuls post hoc test).</p>
Full article ">Figure 5
<p>Aronia leaf extracts modulated MMP-2 (<b>A</b>) and MMP-9 (<b>B</b>) activities in HT-29 cells. The ACE and APE inhibitory effect was determined using zymography assays. The activity levels of MMPs were analyzed in culture supernatants. HT-29 cells were treated with aronia leaf extracts at 300, 600, and 900 µg/mL concentrations for 24 and 48 h. Negative and positive controls were obtained from cells stimulated with TNF/TPA (CTRL) and cells treated with 100 µM EGCG cultured in a medium containing 3% FBS. The lower panel (<b>C</b>) shows the representative zymograms obtained for HT-29 cells after ACE and APE treatment for 48 h. Each value represents mean ± SEM, n = 3 independent experiments (each performed in duplicate). Results are expressed as a percentage of MMP levels compared to CTRL, calculated after scanning densitometry and computerized analysis of gels. Significance of differences between means: *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001 versus CTRL (one-way ANOVA followed by Newman–Keuls post hoc test).</p>
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9 pages, 1354 KiB  
Brief Report
Mutation in Wzz(fepE) Linked to Altered O-Antigen Biosynthesis and Attenuated Virulence in Rough Salmonella Infantis Variant
by Nneka Vivian Iduu, Steven Kitchens, Stuart B. Price and Chengming Wang
Vet. Sci. 2024, 11(12), 603; https://doi.org/10.3390/vetsci11120603 - 28 Nov 2024
Viewed by 207
Abstract
Salmonella enterica serovar Infantis has emerged as a prevalent foodborne pathogen in poultry with significant global health implications. This study investigates the molecular characteristics influencing virulence in a S. Infantis rough variant collected from a poultry farm in the USA. In this study, whole [...] Read more.
Salmonella enterica serovar Infantis has emerged as a prevalent foodborne pathogen in poultry with significant global health implications. This study investigates the molecular characteristics influencing virulence in a S. Infantis rough variant collected from a poultry farm in the USA. In this study, whole genome sequencing and comparative genomics were performed on smooth and rough poultry S. Infantis isolates, while chicken embryo lethality assay was conducted to assess their virulence. Comparative genomics between isolates was analyzed using Mauve pairwise Locally Collinear Blocks to measure the genetic conservation. Embryo survival rates between the isolates were compared using the Kaplan–Meier curves. High genomic conservation was observed between the two isolates, but a frameshift mutation was detected in the Wzz(fepE) gene of the rough variant, resulting in early protein truncation. The chicken embryo lethality assay showed that the lethality rate of the smooth strain was higher than that of the rough strain (p < 0.05). This study identifies a frameshift mutation in the Wzz(fepE) gene, leading to protein truncation, which may reduce bacterial virulence by impacting O-antigen biosynthesis in the rough Salmonella Infantis variant. These findings deepen our understanding of S. Infantis pathogenesis and suggest that targeting the Wzz(fepE) gene or related pathways could be a promising strategy for developing effective vaccines and therapeutic interventions. Full article
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Figure 1

Figure 1
<p>High genomic similarities between the whole genome sequences of <span class="html-italic">Sal</span>_smooth and <span class="html-italic">Sal</span>_rough. Pairwise alignment of the <span class="html-italic">Sal</span>_smooth and <span class="html-italic">Sal</span>_rough genomes was conducted using Mauve software. Colored blocks represent homologous (similar) regions, with connecting lines indicating shared sequences between the two genomes. Blocks below the center line indicate regions aligned in reverse complement (inverse) orientation. These homologous regions are called Locally Collinear Blocks (LCBs). A total of ten (<span class="html-italic">n</span> = 10) LCBs were identified, with a minimum weight of 3099, indicating strong homology and high similarity between the strains.</p>
Full article ">Figure 2
<p>Frameshift mutation in the <span class="html-italic">Wzz(fepE)</span> gene of <span class="html-italic">S.</span> Infantis rough strain. The grey highlighted chromatogram region shows an adenine (A) insertion after nucleotide position 32, extending the gene length in <span class="html-italic">Sal</span>_rough from 1137 to 1138 bp as observed in <span class="html-italic">Sal</span>_smooth. This insertion introduces an early stop codon at amino acid position 26, truncating the protein from 378 to 25 amino acids.</p>
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<p>Chicken embryo lethality rate of <span class="html-italic">S.</span> Infantis strains. Twelve (12) eggs were used in each experimental group except the negative control (10 eggs used) with an inoculum concentration of 10<sup>3</sup> CFU/mL and sterile Dulbecco’s phosphate-buffered saline (PBS) for the control group. Kaplan–Meier plot displaying the chicken embryo lethality when inoculated with sterile PBS (black line), smooth strain <span class="html-italic">Sal</span>_smooth (red line), and rough variant <span class="html-italic">Sal</span>_rough (blue line), for 5 days post-inoculation. Results show that the embryo lethality rate of the <span class="html-italic">Sal</span>_smooth group was higher than the negative control group and <span class="html-italic">Sal</span>_rough (<span class="html-italic">p &lt;</span> 0.05). No difference in embryo lethality rates was observed between the negative control and <span class="html-italic">Sal</span>_rough (<span class="html-italic">p</span> = 0.721). Statistical analysis was performed using the log-rank test.</p>
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15 pages, 9422 KiB  
Article
Oxygenase Ppo-Regulated Moldy Volatiles Affect Growth, Pathogenicity and Patulin Biosynthesis of Penicillium expansum Through G Protein Signaling
by Di Gong, Tingting Yan, Xuexue Wang, Dov Prusky, Danfeng Long, Ying Zhang and Yang Bi
J. Fungi 2024, 10(12), 827; https://doi.org/10.3390/jof10120827 - 27 Nov 2024
Viewed by 228
Abstract
Precocious sexual inducer (psi)-producing oxygenases (Ppos) participate in the production of C8 moldy volatile compounds (MVOCs), and these compounds could act as signal molecules modulating G protein signaling cascades, which participates in the growth and development, secondary metabolisms and pathogenicity of filamentous fungi. [...] Read more.
Precocious sexual inducer (psi)-producing oxygenases (Ppos) participate in the production of C8 moldy volatile compounds (MVOCs), and these compounds could act as signal molecules modulating G protein signaling cascades, which participates in the growth and development, secondary metabolisms and pathogenicity of filamentous fungi. In this study, PePpoA and PePpoC proteins were identified in Penicillium expansum. The deletion of ppoA decreased C8 MVOC production in P. expansum, while they were not detected in the ΔppoC strain (p < 0.05). In addition, down-regulated cAMP/PKA and PKC/PLC signaling showed in the two mutants (p < 0.05). The two mutants showed slow colony growth and down-regulated expression of genes regulating spore development (abaA, wetA, brlA and vosA) with broken morphology of spore and hyphae. In addition, the two mutants had decreased pathogenicity on apple fruit and less patulin production in vitro and in vivo. Compared with ΔppoA strain, the deletion of ppoC inhibited G protein signaling pathways more, and the ΔppoC strain had more defective growth and development as well as reduced pathogenicity and patulin production (p < 0.05). Therefore, PePpoC proteins affect more growth and development, patulin biosynthesis and pathogenicity of P. expansum by regulating C8 MVOC-mediated G protein signaling transduction. Full article
(This article belongs to the Special Issue Control of Postharvest Fungal Diseases)
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Figure 1
<p>Phylogenetic tree and conserved structural domains of PePpoA and PePpoC protein with other fungal PpoA (<b>A</b>) and PpoC (<b>B</b>). The multiple sequence comparison of PePpoA (<b>C</b>) and PePpoC (<b>D</b>) protein with other fungi. The number of Bootstrap iterations is 1000, which increases the node support value and improves the reliability of homology.</p>
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<p>Production of C8 MVOCs in the <span class="html-italic">ΔppoA</span> and <span class="html-italic">ΔppoC</span> strain. Bars indicate the standard error. Different letters indicate significant differences in different groups (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Gene expression involved in the cAMP/PKA (<b>A</b>) and PLC (<b>B</b>) signaling pathway in the <span class="html-italic">ΔppoA</span> and <span class="html-italic">ΔppoC</span> strain. Bars indicate the standard error. Different letters indicate significant differences in different groups (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Pictures of radial growth (<b>A</b>), colony diameter (<b>B</b>) and hyphal morphology (<b>C</b>) in the <span class="html-italic">ΔppoA</span> and <span class="html-italic">ΔppoC</span> strains. Bars indicate the standard error. Different letters indicate significant differences in different groups at the same time (<span class="html-italic">p</span> &lt; 0.05). Red arrows indicate changes in hyphal morphology.</p>
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<p>Sporulation (<b>A</b>), spore morphology (<b>B</b>), and sporulation-related genes expression (<b>C</b>) in the <span class="html-italic">ΔppoA</span> and <span class="html-italic">ΔppoC</span> strains. Bars indicate the standard error. Different letters indicate significant differences in different groups (<span class="html-italic">p</span> &lt; 0.05). Red arrows indicate changes in spore morphology.</p>
Full article ">Figure 6
<p>Decay symptoms (<b>A</b>) and lesion diameter (<b>B</b>) on apple fruits inoculated with <span class="html-italic">ΔppoA</span> and <span class="html-italic">ΔppoC</span> strains. Bars indicate the standard error. Different letters indicate significant differences in different groups (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 7
<p>The patulin production of strains in vitro and in vivo, and expression levels of patulin biosynthetic cluster genes in the <span class="html-italic">ΔppoA</span> and <span class="html-italic">ΔppoC</span> strain. Bars indicate the standard error. Different letters indicate significant differences in different groups (<span class="html-italic">p</span> &lt; 0.05).</p>
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18 pages, 3967 KiB  
Article
Occurrence, Antibiotic Resistance and Biofilm-Forming Ability of Listeria monocytogenes in Chicken Carcasses and Cuts
by Sarah Panera-Martínez, Rosa Capita, Ángela Pedriza-González, María Díez-Moura, Félix Riesco-Peláez and Carlos Alonso-Calleja
Foods 2024, 13(23), 3822; https://doi.org/10.3390/foods13233822 - 27 Nov 2024
Viewed by 379
Abstract
A total of 104 samples of chicken meat acquired on the day of slaughter from two slaughterhouses in northwestern Spain were analyzed. These comprised 26 carcasses and 26 cuts from each of the two establishments. An average load of 5.39 ± 0.61 log [...] Read more.
A total of 104 samples of chicken meat acquired on the day of slaughter from two slaughterhouses in northwestern Spain were analyzed. These comprised 26 carcasses and 26 cuts from each of the two establishments. An average load of 5.39 ± 0.61 log10 cfu/g (total aerobic counts) and 4.90 ± 0.40 log10 cfu/g (psychrotrophic microorganisms) were obtained, with differences (p < 0.05) between types of samples and between slaughterhouses. Culturing methods involving isolation based on the UNE-EN-ISO 11290-1:2018 norm and identification of isolates by polymerase chain reaction (PCR) to detect the lmo1030 gene allowed the detection of Listeria monocytogenes in 75 samples (72.1% of the total; 50.0% of the carcasses and 94.2% of the cuts). The 75 isolates, one for each positive sample, were tested for resistance against a panel of 15 antibiotics of clinical interest by the disc diffusion method. All isolates belonged to the serogroup IIa (multiplex PCR assay) and showed resistance to between four and ten antibiotics, with an average value of 5.7 ± 2.0 resistances per isolate, this rising to 7.0 ± 2.1 when strains with resistance and reduced susceptibility were taken together. A high prevalence of resistance was observed for antibiotics belonging to the cephalosporin and quinolone families. However, the level of resistance was low for antibiotics commonly used to treat listeriosis (e.g., ampicillin or gentamicin). Nine different resistance patterns were noted. One isolate with each resistance pattern was tested for its ability to form biofilms on polystyrene during 72 h at 12 °C. The total biovolume of the biofilms registered through confocal laser scanning microscopy (CLSM) in the observation field of 16,078.24 μm2 ranged between 13,967.7 ± 9065.0 μm3 and 33,478.0 ± 23,874.1 μm3, and the biovolume of inactivated bacteria between 0.5 ± 0.4 μm3 and 179.1 ± 327.6 μm3. A direct relationship between the level of resistance to antibiotics and the ability of L. monocytogenes strains to form biofilms is suggested. Full article
(This article belongs to the Section Food Microbiology)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Prevalence of <span class="html-italic">Listeria monocytogenes</span> by type of sample (carcasses or cuts) and slaughterhouse (A or B).</p>
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<p>Percentage of <span class="html-italic">Listeria monocytogenes</span> isolates with resistance, reduced susceptibility or susceptibility to each antibiotic tested. Antibiotics (the data from the two slaughterhouses are compared separately) that do not share any letters present significant differences one from another (<span class="html-italic">p</span> &lt; 0.05). AMP (ampicillin; 10 µg), OX (oxacillin; 1 µg), FOX (cefoxitin; 30 µg), CTX (cefotaxime; 30 µg), FEP (cefepime; 30 µg), CN (gentamycin; 10 µg), E (erythromycin; 15 µg), VA (vancomycin; 30 µg), SXT (trimethoprim-sulfamethoxazole; 25 µg), RD (rifampicin; 5 µg), TE (tetracycline; 30 µg), C (chloramphenicol; 30 µg), CIP (ciprofloxacin; 5 µg), ENR (enrofloxacin; 5 µg), F (nitrofurantoin; 300 µg).</p>
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<p>Total biovolume (green bars; left-side <span class="html-italic">y</span>-axis) and biovolume of inactivated bacteria (red line; right-side <span class="html-italic">y</span>-axis) of the biofilms formed on polystyrene (72 h at 12 °C) for each <span class="html-italic">Listeria monocytogenes</span> isolate tested. Data (total biovolume and biovolume of inactivated bacteria were compared separately) with no letters in common are significantly different (<span class="html-italic">p</span> &lt; 0.05). One isolate from each of the resistance phenotypes was studied: (1) OX-FOX-CTX-FEP; (2) OX-FOX-CTX-FEP-RD; (3) OX-FOX-CTX-FEP-CIP; (4) OX-FOX-CTX-FEP-SXT; (5) OX-FOX-CTX-FEP-SXT-RD; (6) OX-FOX-CTX-FEP-CIP-ENR; (7) OX-FOX-CTX-FEP-CN-E-RD-TE; (8) OX-FOX-CTX-FEP-CN-E-SXT-RD-TE; (9) OX-FOX-CTX-FEP-CN-E-SXT-RD-TE-CIP. OX (oxacillin; 1 µg), FOX (cefoxitin; 30 µg), CTX (cefotaxime; 30 µg), FEP (cefepime; 30 µg), CN (gentamycin; 10 µg), E (erythromycin; 15 µg), SXT (trimethoprim-sulfamethoxazole; 25 µg), RD (rifampicin; 5 µg), TE (tetracycline; 30 µg), CIP (ciprofloxacin; 5 µg), ENR (enrofloxacin; 5 µg).</p>
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<p>Three-dimensional reconstructions of the biofilms formed on polystyrene (72 h; 12 °C) by <span class="html-italic">Listeria monocytogenes</span> isolates of different antibiotic resistance patterns. The total biovolume (μm<sup>3</sup>) observed by SYTO9 green staining is not in parentheses, while the biovolume (μm<sup>3</sup>) of inactivated bacteria observed after PI red staining is shown in parentheses. The images (126.8 μm × 126.8 μm) were reconstructed with the IMARIS 9.1 program, with virtual projections of the shadow on the right. OX (oxacillin; 1 µg), FOX (cefoxitin; 30 µg), CTX (cefotaxime; 30 µg), FEP (cefepime; 30 µg), CN (gentamycin; 10 µg), E (erythromycin; 15 µg), SXT (trimethoprim-sulfamethoxazole; 25 µg), RD (rifampicin; 5 µg), TE (tetracycline; 30 µg), CIP (ciprofloxacin; 5 µg), ENR (enrofloxacin; 5 µg).</p>
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17 pages, 2448 KiB  
Article
Functional Analysis of Promoters, mRNA Cleavage, and mRNA Secondary Structure on esxB-esxA in Mycolicibacterium smegmatis
by Ryan G. Peters, Jessica M. Kelly, Sarah Bibeau, Ying Zhou and Scarlet S. Shell
Pathogens 2024, 13(12), 1041; https://doi.org/10.3390/pathogens13121041 - 27 Nov 2024
Viewed by 191
Abstract
The ESX-1 secretion system is critical for the virulence of Mycobacterium tuberculosis as well as for conjugation in the saprophytic model Mycolicibacterium smegmatis. EsxB (CFP-10) and EsxA (ESAT-6) are secreted effectors required for the function of ESX-1 systems. While some transcription factors [...] Read more.
The ESX-1 secretion system is critical for the virulence of Mycobacterium tuberculosis as well as for conjugation in the saprophytic model Mycolicibacterium smegmatis. EsxB (CFP-10) and EsxA (ESAT-6) are secreted effectors required for the function of ESX-1 systems. While some transcription factors regulating the expression of esxB and esxA have been identified, little work has addressed their promoter structures or other determinants of their expression. Here, we defined two promoters, one located two genes upstream of esxB and one located immediately upstream, that contribute substantially to the expression of esxB and esxA. We also defined an mRNA cleavage site within the esxB 5′ untranslated region (UTR) and found that a single-nucleotide substitution reprogramed the position of this cleavage event without impacting esxB-esxA transcript abundance. We furthermore investigated the impact of a double stem-loop structure in the esxB 5′ UTR and found that it does not confer stability on a reporter gene transcript. Consistent with this, there was no detectable correlation between mRNA half-life and secondary structure near the 5′ ends of 5′ UTRs on a transcriptome-wide basis. Collectively, these data shed light on the determinants of esxB-esxA expression in M. smegmatis as well as provide broader insight into the determinants of mRNA cleavage in mycobacteria and the relationship between 5′ UTR secondary structure and mRNA stability. Full article
(This article belongs to the Section Bacterial Pathogens)
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Figure 1

Figure 1
<p>The <span class="html-italic">esxB</span> and <span class="html-italic">esxA</span> transcripts have higher abundance and longer half-lives than the transcripts encoded upstream. (<b>A</b>) RNAseq coverage for the <span class="html-italic">M. smegmatis</span> region encompassing <span class="html-italic">PE35<sub>MS</sub></span>, <span class="html-italic">PPE68<sub>MS</sub></span>, <span class="html-italic">esxB</span>, and <span class="html-italic">esxA</span> (<span class="html-italic">msmeg_0063-0066</span>). The data are from [<a href="#B15-pathogens-13-01041" class="html-bibr">15</a>]. The genes of interest are shown to scale above the transcript abundance plot. Two previously mapped transcription start sites (TSSs) and an RNA cleavage site are shown with dashed black and red lines, respectively [<a href="#B20-pathogens-13-01041" class="html-bibr">20</a>]. The second TSS appears at nearly the same position as the cleavage site in this graphic because they are only 4 nt apart. The coordinates are from NC.008596.1. (<b>B</b>) The degradation rates of the indicated transcripts were assessed by measuring transcript abundance following the addition of rifampicin (RIF) to block transcription. The slopes of the decay curves were compared by linear regression. The slopes of <span class="html-italic">PE35<sub>MS</sub></span> and <span class="html-italic">PPE68<sub>MS</sub></span> were steeper than the slopes of <span class="html-italic">esxB</span> and <span class="html-italic">esxA</span> (**** <span class="html-italic">p</span> &lt; 0.0001 for each pairwise comparison between the two groups), while the slopes of <span class="html-italic">PE35<sub>MS</sub></span> and <span class="html-italic">PPE68<sub>MS</sub></span> were not significantly different from each other nor were the slopes of <span class="html-italic">esxB</span> and <span class="html-italic">esxA</span> (<span class="html-italic">p</span> &gt; 0.05 for each pairwise comparison).</p>
Full article ">Figure 2
<p>A second promoter is present between <span class="html-italic">PPE68<sub>ms</sub></span> and <span class="html-italic">esxB</span>. (<b>A</b>) A schematic of a cassette cloned into an episomal plasmid lacking a promoter to test the expression of ESX-1 genes. The cassette contains the tsynA transcriptional terminator [<a href="#B21-pathogens-13-01041" class="html-bibr">21</a>] to block transcription from spurious promoter sequences in the plasmid backbone. TSS<sub>1</sub> and TSS<sub>2</sub> were previously mapped in [<a href="#B20-pathogens-13-01041" class="html-bibr">20</a>]. A previously mapped cleavage site (Martini et al. 2019) is indicated with scissors. The elements in the construct are not drawn to scale. The mutations to the putative promoter for TSS<sub>2</sub> are shown. (<b>B</b>) The plasmids harboring variations of the cassette shown in A were transformed into an <span class="html-italic">M. smegmatis</span> strain with a deletion of <span class="html-italic">msmeg_0062</span> (<span class="html-italic">eccC1b</span>) through <span class="html-italic">msmeg_0066</span> (<span class="html-italic">esxA</span>). RNA was harvested from biological triplicate cultures in log phase, and qPCR was used to measure the expression of three genes and a region spanning the cleavage site. The data are representative of three independent experiments.</p>
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<p>The promoter between <span class="html-italic">PPE68<sub>ms</sub></span> and <span class="html-italic">esxB</span> initiates transcription 3–4 nucleotides upstream of a major cleavage site. (<b>A</b>) A schematic of the RNA 5′ ends between <span class="html-italic">PPE68<sub>ms</sub></span> and <span class="html-italic">esxB</span> that arise from a previously mapped cleavage site [<a href="#B20-pathogens-13-01041" class="html-bibr">20</a>] and a promoter defined in <a href="#pathogens-13-01041-f002" class="html-fig">Figure 2</a> and here. (<b>B</b>) An example of Sanger sequencing traces from 5′ RACE used to map 5′ ends in the region between <span class="html-italic">PPE68<sub>ms</sub></span> and <span class="html-italic">esxB</span>. The 5′ RACE adapter sequence is shown and indicated with yellow boxes. The RNA sequences being mapped are boxed in purple. The top trace is an example of a clean trace that primarily reflects the previously mapped RNA cleavage site. The bottom trace is an example of a mixed-peak trace where three sequences can be seen: that arising from the cleaved RNA and those arising from two transcripts made from TSS<sub>2</sub>, which has two possible start positions. The sequencing traces are representative of at least three separately sequenced gel bands.</p>
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<p>mRNA cleavage can be reprogrammed by a point mutation but does not appear to affect the expression of <span class="html-italic">PPE68<sub>ms</sub></span>, <span class="html-italic">esxB</span>, and <span class="html-italic">esxA</span>. (<b>A</b>) The constructs shown in <a href="#pathogens-13-01041-f002" class="html-fig">Figure 2</a>A were subject to a point mutation immediately downstream of the cleavage site (C→G, red font). (<b>B</b>) 5′ RACE was used to map RNA 5′ ends in the vicinity of the cleavage site. Shown are two traces from a strain harboring a construct with the cleavage site C→G mutation. While both traces contain mixed peaks, in the upper trace, a sequence beginning 1 nt upstream of the normal cleaved 5′ end can be seen, while in the lower trace, a sequence beginning 28 nt upstream of the normal cleaved 5′ end can be seen. The sequencing traces are representative of at least three separately sequenced gel bands. (<b>C</b>) The data from <a href="#pathogens-13-01041-f002" class="html-fig">Figure 2</a> are shown with the addition of constructs with a point mutation downstream of the cleavage site. The data are representative of two independent experiments, each performed with biological triplicate cultures.</p>
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<p>The secondary structure in the <span class="html-italic">esxB</span> 5′ UTR does not impact transcript half-life. Constructs were made, in which variants of the <span class="html-italic">esxB</span> 5′ UTR were linked to the coding sequence of <span class="html-italic">yfp</span> in integrating plasmids and transformed into wildtype <span class="html-italic">M. smegmatis</span>. (<b>A</b>) The predicted secondary structure of the <span class="html-italic">esxB</span> 5′ UTR and start codon (red) following cleavage. The hairpin structures are indicated in yellow and orange. This is designated “Full UTR” in subsequent experiments. The variants lacked one or both hairpins. The graphic was made with the ViennaRNA Web Services tool <span class="html-italic">forna</span>. (<b>B</b>) The abundance of the <span class="html-italic">yfp</span> transcript fused to the indicated <span class="html-italic">esxB</span> 5′ UTR variants was measured by quantitative PCR and expressed relative to the housekeeping gene <span class="html-italic">sigA</span>. The mean and SD of triplicate samples are shown. The means were compared by ANOVA followed by Dunnett’s multiple comparisons test to compare “Full UTR” to each of the variants. **, <span class="html-italic">p</span> &lt; 0.01; ns, <span class="html-italic">p</span> &gt; 0.05. (<b>C</b>) Half-lives of the <span class="html-italic">yfp</span> transcript when fused to the indicated <span class="html-italic">esxB</span> 5′ UTR variants were measured by quantitative PCR. The mean and 95% CI of triplicate datasets are shown. The upper error bar for the ∆hairpin 1 sample was clipped for visualization purposes. The differences between strains were not statistically significant (linear regression). (<b>D</b>) YFP protein abundance from transcripts with the indicated 5′ UTRs was measured by flow cytometry. A promoterless <span class="html-italic">yfp</span> gene was used as a control for autofluorescence. The median fluorescence from each of three biological replicates was determined and the mean and SD of those medians are shown. The means were compared by ANOVA, followed by Dunnett’s multiple comparisons test to compare “Full UTR” to each of the variants. ***, <span class="html-italic">p</span> &lt; 0.001; **, <span class="html-italic">p</span> &lt; 0.01; ns, <span class="html-italic">p</span> &gt; 0.05.</p>
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<p>The extent of secondary structure near the 5′ ends of 5′ UTRs does not generally correlate with transcript stability. The half-lives of ~1800 leadered <span class="html-italic">M. smegmatis</span> genes were previously reported and plotted here as a function of two metrics of 5′ UTR secondary structure [<a href="#B34-pathogens-13-01041" class="html-bibr">34</a>]. Relationships were assessed by Spearman’s correlation. (<b>A</b>) The 20 nt at the 5′ end of each 5′ UTR was computationally folded by RNAfold (Vienna RNA Package) as described [<a href="#B34-pathogens-13-01041" class="html-bibr">34</a>]. The minimum free energy (MFE) of the MFE structure for each 5′ UTR is plotted. (<b>B</b>) The 5′ third of each 5′ UTR was computationally folded in 20 nt windows with 10 nt overlaps using RNAfold (Vienna RNA Package) as described [<a href="#B34-pathogens-13-01041" class="html-bibr">34</a>]. For each 5′ UTR, the mean MFE of the resulting structures is plotted.</p>
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14 pages, 1001 KiB  
Case Report
Decoding Chemotherapy Resistance of Undifferentiated Pleomorphic Sarcoma at the Single Cell Resolution: A Case Report
by Timur I. Fetisov, Maxim E. Menyailo, Alexander V. Ikonnikov, Anna A. Khozyainova, Anastasia A. Tararykova, Elena E. Kopantseva, Anastasia A. Korobeynikova, Maria A. Senchenko, Ustinia A. Bokova, Kirill I. Kirsanov, Marianna G. Yakubovskaya and Evgeny V. Denisov
J. Clin. Med. 2024, 13(23), 7176; https://doi.org/10.3390/jcm13237176 - 26 Nov 2024
Viewed by 273
Abstract
Background: Undifferentiated pleomorphic sarcoma (UPS) is a highly malignant mesenchymal tumor that ranks as one of the most common types of soft tissue sarcoma. Even though chemotherapy increases the 5-year survival rate in UPS, high tumor heterogeneity frequently leads to chemotherapy resistance and [...] Read more.
Background: Undifferentiated pleomorphic sarcoma (UPS) is a highly malignant mesenchymal tumor that ranks as one of the most common types of soft tissue sarcoma. Even though chemotherapy increases the 5-year survival rate in UPS, high tumor heterogeneity frequently leads to chemotherapy resistance and consequently to recurrences. In this study, we characterized the cell composition and the transcriptional profile of UPS with resistance to chemotherapy at the single cell resolution. Methods: A 58-year-old woman was diagnosed with a 13.6 × 9.3 × 6.0 cm multi-nodular tumor with heterogeneous cysto-solid structure at the level of the distal metadiaphysis of the left thigh during magnetic resonance tomography. Morphological and immunohistochemical analysis led to the diagnosis of high-grade (G3) UPS. Neoadjuvant chemotherapy, surgery (negative resection margins), and adjuvant chemotherapy were conducted, but tumor recurrence developed. The UPS sample was used to perform single-cell RNA sequencing by chromium-fixed RNA profiling. Results: Four subpopulations of tumor cells and seven subpopulations of tumor microenvironment (TME) have been identified in UPS. The expression of chemoresistance genes has been detected, including KLF4 (doxorubicin and ifosfamide), ULK1, LUM, GPNMB, and CAVIN1 (doxorubicin), and AHNAK2 (gemcitabine) in tumor cells and ETS1 (gemcitabine) in TME. Conclusions: This study provides the first description of the single-cell transcriptome of UPS with resistance to two lines of chemotherapy, showcasing the gene expression in subpopulations of tumor cells and TME, which may be potential markers for personalized cancer therapy. Full article
(This article belongs to the Section Oncology)
17 pages, 1733 KiB  
Article
Identification and Confirmation of Virulence Factor Production from Fusarium avenaceum, a Casual Agent of Root Rot in Pulses
by Thomas E. Witte, Anne Hermans, Amanda Sproule, Carmen Hicks, Tala Talhouni, Danielle Schneiderman, Linda J. Harris, Anas Eranthodi, Nora A. Foroud, Syama Chatterton and David P. Overy
J. Fungi 2024, 10(12), 821; https://doi.org/10.3390/jof10120821 - 26 Nov 2024
Viewed by 264
Abstract
Fusarium avenaceum is an aggressive pathogen of pulse crops and a causal agent in root rot disease that negatively impacts Canadian agriculture. This study reports the results of a targeted metabolomics-based profiling of secondary metabolism in an 18-strain panel of Fusarium avenaceum cultured [...] Read more.
Fusarium avenaceum is an aggressive pathogen of pulse crops and a causal agent in root rot disease that negatively impacts Canadian agriculture. This study reports the results of a targeted metabolomics-based profiling of secondary metabolism in an 18-strain panel of Fusarium avenaceum cultured axenically in multiple media conditions, in addition to an in planta infection assay involving four strains inoculated on two pea cultivars. Multiple secondary metabolites with known roles as virulence factors were detected which have not been previously associated with F. avenaceum, including fungal decalin-containing diterpenoid pyrones (FDDPs), fusaoctaxins, sambutoxin and fusahexin, in addition to confirmation of previously reported secondary metabolites including enniatins, fusarins, chlamydosporols, JM-47 and others. Targeted genomic analysis of secondary metabolite biosynthetic gene clusters was used to confirm the presence/absence of the profiled secondary metabolites. The detection of secondary metabolites with diverse bioactivities is discussed in the context of virulence factor networks potentially coordinating the disruption of plant defenses during disease onset by this generalist plant pathogen. Full article
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<p>Molecular structures of <span class="html-italic">F. avenaceum</span> secondary metabolites produced from in vitro culturing and in planta pathogenicity challenge in pea seedlings.</p>
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<p>Targeted metabolomics analysis of 16 <span class="html-italic">Fusarium avenaceum</span> strains and two enniatin synthase (ENN) gene deletion mutants (blue strain IDs) generated from parental strain FaLH27. The heatmap on the left shows representative mass feature peak heights detected across all media conditions used in the experiment; the heatmap on the right (in green) shows peak heights detected from infected pea root tissue. In planta inoculations were performed on two pea cultivars: CDC Meadow (M) and CDC Dakota (D).</p>
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<p>Annotated mycotoxin/metabolite biosynthetic gene clusters (BGCs) in <span class="html-italic">F. avenaceum</span> genomes. (<b>A</b>) Presence/absence heatmap of BGCs in all strains included in this study. (<b>B</b>) Syntenic comparison of <span class="html-italic">F. graminearum</span> FDDP BGC to one FDDP-producing strain and all non-producing <span class="html-italic">F. avenaceum</span> strains. (<b>C</b>) Syntenic comparison of the fusarin BGC from <span class="html-italic">F. fujikuroi</span> to one fusarin-producing strain and all non-producing <span class="html-italic">F. avenaceum</span> strains. (<b>D</b>) Syntenic comparison of the fusaristatin BGC from <span class="html-italic">F. graminearum</span> to a producing and a non-producing <span class="html-italic">F. avenaceum</span> strain. (<b>E</b>) Syntenic comparison of solanapyrone BGC from <span class="html-italic">Alternaria solani</span> to the <span class="html-italic">PKS44</span> BGC in one chlamydosporol-producing strain and all non-producing <span class="html-italic">F. avenaceum</span> strains.</p>
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13 pages, 1744 KiB  
Article
USP8 Mutations Associated with Cushing’s Disease Alter Protein Structure Dynamics
by Natalia Petukhova, Anastasia Poluzerova, Dmitry Bug, Elena Nerubenko, Anna Kostareva, Uliana Tsoy and Renata Dmitrieva
Int. J. Mol. Sci. 2024, 25(23), 12697; https://doi.org/10.3390/ijms252312697 - 26 Nov 2024
Viewed by 228
Abstract
The adenomas in Cushing’s disease frequently exhibit mutations in exon 14, within a binding motif for the regulatory protein 14-3-3 located between the catalytic domain (DUB), responsible for ubiquitin hydrolysis, and the WW-like domain that mediates autoinhibition, resulting in constantly active USP8. The [...] Read more.
The adenomas in Cushing’s disease frequently exhibit mutations in exon 14, within a binding motif for the regulatory protein 14-3-3 located between the catalytic domain (DUB), responsible for ubiquitin hydrolysis, and the WW-like domain that mediates autoinhibition, resulting in constantly active USP8. The exact molecular mechanism of deubiquitinase activity disruption in Cushing’s disease remains unclear. To address this, Sanger sequencing of USP8 was performed to identify mutations in corticotropinomas. These mutations were subjected to computational screening, followed by molecular dynamics simulations to assess the structural alterations that might change the biological activity of USP8. Eight different variants of the USP8 gene were identified both within and outside the “hotspot” region. Six of these had previously been reported in Cushing’s disease, while two were detected for the first time in our patients with CD. One of the two new variants, initially classified as benign during screening, was found in the neighboring SH3 binding motif at a distance of 20 amino acids. This variant demonstrated pathogenicity patterns similar to those of known pathogenic variants. All USP8 variants identified in our patients caused conformational changes in the USP8 protein in a similar manner. The identified mutations, despite differences in annotation results—including evolutionary conservation assessments, automated predictor data, and variations in localization within exon 14—exhibit similar patterns of protein conformational change. This suggests a pathogenic effect that contributes to the development of CD. Full article
(This article belongs to the Special Issue Advances in Protein Dynamics)
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<p>Schematic representation of the protein structure, highlighting functional domains (MIT, Rhod, WW−like, DUB), 14-3-3 and SH3 binding motifs, and the localization and spectrum of detected mutations in our patient cohort. Newly identified mutations (P720−D721delinsR and T739A) are marked with an asterisk (*).</p>
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<p>Evolutionary analysis and conservation assessment of positions of interest: (<b>a</b>) Phylogenetic tree of USP8, USP50, and USP2. (<b>b</b>) Alignment segment of positions 708–740. The alignment uses the “Turn” color scheme from iTOL, where the gradient from red to cyan indicates the propensity to form turns. Red represents the highest propensity, while cyan represents the lowest. Gray shades indicate intermediate propensities.</p>
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<p>Structural and functional analysis of the USP8 protein using molecular dynamics illustrates the differences in protein behavior between WT and mutants. (<b>a</b>) Root mean square deviation (RMSD) of the protein backbone; (<b>b</b>) radius of gyration; (<b>c</b>) root mean square fluctuation (RMSF) plot comparing WT and mutant USP8 proteins, with the shaded areas highlighting regions of interest, including the catalytic domain (DUB), which demonstrates reduced flexibility in mutants, shaded in pink.</p>
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13 pages, 792 KiB  
Article
Could SLC26A7 Be a Promising Marker for Preoperative Diagnosis of High-Grade Papillary Thyroid Carcinoma?
by Sergei E. Titov, Evgeniya S. Kozorezova, Sergei A. Lukyanov, Sergei V. Sergiyko, Pavel S. Demenkov, Yulia A. Veryaskina, Sergey L. Vorobyev, Ilya V. Sleptsov, Roman A. Chernikov, Natalia I. Timofeeva, Svetlana V. Barashkova, Elena L. Lushnikova, Anna A. Uspenskaya, Anna V. Zolotoukho, Olga V. Romanova and Igor F. Zhimulev
Diagnostics 2024, 14(23), 2652; https://doi.org/10.3390/diagnostics14232652 - 25 Nov 2024
Viewed by 336
Abstract
Background/Objectives: A modern classification distinguishes between two nosological entities posing an intermediate risk between differentiated and anaplastic carcinoma: poorly differentiated thyroid carcinoma and differentiated high-grade thyroid carcinoma. There are currently few studies searching for the preoperative molecular genetic markers of high-grade papillary thyroid [...] Read more.
Background/Objectives: A modern classification distinguishes between two nosological entities posing an intermediate risk between differentiated and anaplastic carcinoma: poorly differentiated thyroid carcinoma and differentiated high-grade thyroid carcinoma. There are currently few studies searching for the preoperative molecular genetic markers of high-grade papillary thyroid carcinoma (PTC HG), primarily because of a recent WHO reclassification and singling out of a separate entity: high-grade follicular cell-derived nonanaplastic thyroid carcinoma. Therefore, this work was aimed at identifying PTC HG-specific microRNAs and mRNAs that reliably distinguish them from differentiated papillary thyroid carcinoma in preoperative cytology specimens (fine-needle aspiration biopsies). Methods: A molecular genetic profile (expression levels of 14 genes and eight microRNAs) was studied in 110 cytology specimens from patients with PTC: 13 PTCs HG and 97 PTCs without features of HG. Results: Of the examined eight microRNAs and 14 genes, significant differences in the expression levels between the PTC and PTC HG groups were revealed for genes SLC26A7, TFF3, and TPO. Only one gene (SLC26A7) proved to be crucial for detecting PTC HG. It showed the largest area under the ROC curve (0.816) in differentiation between the PTC and PTC HG groups and was the key element of the decision tree by ensuring 54% sensitivity and 87.6% specificity. Conclusions: Early preoperative diagnosis of PTC HG in patients with early stages of this cancer type will allow clinicians to modify a treatment strategy toward a larger surgery volume and lymph node dissection and may provide indications for subsequent radioactive iodine therapy. Full article
(This article belongs to the Special Issue Head and Neck Surgery: Diagnosis and Management)
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<p>Relative expression levels of eight genes and the mtDNA/nDNA ratio in PTC and PTC HG specimens. The median, upper, and lower quartiles (box), a nonoutlier range (whiskers), and outliers (circles) are indicated. The <span class="html-italic">p</span>-values at the significance level chosen in this study (&lt;0.0022) are shown in bold.</p>
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<p>Areas under the ROC curves (ROC AUC) for eight mRNAs for assessing the distinguishability of groups PTC and PTC HG. Whiskers denote 95% confidence intervals.</p>
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<p>The decision tree for classifying samples into benign or malignant ones followed by cancer typing. + or −: exceeding the chosen cutoff or not exceeding it.</p>
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23 pages, 5051 KiB  
Article
Delayed Sowing Reduced Verticillium Wilt by Altering Soil Temperature and Humidity to Enhance Beneficial Rhizosphere Bacteria of Sunflower
by Jianfeng Yang, Shuo Jia, Tie Li, Jian Zhang, Yuanyuan Zhang, Jianjun Hao and Jun Zhao
Microorganisms 2024, 12(12), 2416; https://doi.org/10.3390/microorganisms12122416 - 25 Nov 2024
Viewed by 296
Abstract
Sunflower Verticillium Wilt (SVW) caused by Verticillium dahliae is a significant threat to sunflower production in China. This soilborne disease is difficult to control. It has been observed that delayed sowing reduces the severity of SVW on different varieties and across various locations. [...] Read more.
Sunflower Verticillium Wilt (SVW) caused by Verticillium dahliae is a significant threat to sunflower production in China. This soilborne disease is difficult to control. It has been observed that delayed sowing reduces the severity of SVW on different varieties and across various locations. Soil was collected from multiple locations with different sowing dates to understand the underlying biological mechanisms driving this phenomenon. The soil bacterial community was characterized through 16S rRNA gene amplicon sequencing performed on the Illumina MiSeq platform, followed by comprehensive bioinformatics analysis. Microsclerotia numbers in soil were detected using both NP-10 selective medium and quantitative polymerase chain reaction (qPCR). By delaying the sowing date, the number of microsclerotia in soil and the biomass of V. dahliae colonized inside sunflower roots were reduced during the early developmental stages (V2–V6) of sunflowers. Amplicon sequencing revealed an increased abundance of bacterial genera, such as Pseudomonas, Azoarcus, and Bacillus in soil samples collected from delayed sowing plots. Five bacterial strains isolated from the delayed sowing plot exhibited strong antagonistic effects against V. dahliae. The result of the pot experiments indicated that supplying two different synthetic communities (SynComs) in the pot did increase the control efficiencies on SVW by 19.08% and 37.82% separately. Additionally, soil temperature and humidity across different sowing dates were also monitored, and a significant correlation between disease severity and environmental factors was observed. In conclusion, delayed sowing appears to decrease microsclerotia levels by recruiting beneficial rhizosphere bacteria, thereby reducing the severity of SVW. Full article
(This article belongs to the Section Microbiomes)
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<p>Correlation between soil temperature, moisture, and disease severity. (<b>A</b>) Soil temperature changes from first (1 May) to last sowing date (10 June); (<b>B</b>) Soil humidity changes with delayed sowing date. (<b>C</b>) Soil pH (acidity and alkalinity) changes with delayed sowing date; differences between treatment means were analyzed using one-way ANOVA, followed by Tukey’s HSD test (<span class="html-italic">p</span> &lt; 0.05). Error bars represent standard deviation. The three points on each bar represent the mean values of three replicates. (<b>D</b>) Heatmap illustrating correlation between different environmental factors and disease index. DI, disease index; Temp., temperature; Hum., humidity. Correlation analysis was performed to evaluate the relationships between soil temperature, moisture, and disease severity using Pearson’s correlation coefficient. Graphs were generated using OriginPro 2021 and GraphPad Prism 8, and statistical significance is indicated by different letters. Numbers and circle sizes represent correlation coefficients and strength, separately. Negative sign represents a negative correlation.</p>
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<p>Correlations between microsclerotia number in rhizosphere soil and different sowing dates of sunflowers. (<b>A</b>) Number of microsclerotia in the rhizosphere soil when sunflowers reached V2 (fourth leaf) growth stage at different sowing date plots. (<b>B</b>) Number of microsclerotia in the rhizosphere soil when sunflowers reached V6 (eighth leaf) stage at different sowing date plots. (<b>C</b>) Number of microsclerotia in the rhizosphere soil when sunflowers reached R1 (early budding) stage at different sowing date plots. (<b>D</b>) Number of microsclerotia in rhizosphere soil when sunflowers reached R5 (mid-blooming) stage at different sowing date plots. Box plot illustrates the distribution of data, with the median represented by the central line in each box. The interquartile range (IQR), spanning from the first quartile (Q1) to the third quartile (Q3), captures the central 50% of values. Whiskers extend to smallest and largest values within 1.5 times the IQR from Q1 and Q3. Data points outside this range are displayed as outlier plots showing median and interquartile range of each treatment group. Statistical differences were analyzed using one-way ANOVA, followed by Tukey’s HSD test (<span class="html-italic">p</span> &lt; 0.05). Different letters mean significant differences among groups (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Quantification of biomass of <span class="html-italic">V. dahliae</span> in rhizosphere soil using qRT-PCR at different developmental stages at location 3. (i) Different growth stages of sunflower: V2 stage = fourth leaf stage; V6 stage = eighth leaf stage; R1 stage = early budding period; R5 stage = mid-blooming period. Treatment means were compared using one-way ANOVA, followed by Tukey’s HSD test (<span class="html-italic">p</span> &lt; 0.05). All statistical analyses were performed in SPSS (version 22.0, IBM Corp., Armonk, NY, USA). Different letters denote significant differences among treatments (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Quantification of the biomass of <span class="html-italic">V. dahliae</span> inside sunflower roots using qRT-PCR at different growth stages at location 3; V2 stage (fourth leaf stage), V6 stage (eighth leaf stage), R1 (early budding period) stage, and R5 (mid-blooming period). Treatment means were compared using one-way ANOVA, followed by Tukey’s HSD test (<span class="html-italic">p</span> &lt; 0.05). Different letters denote significant differences among treatments (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Quantification of <span class="html-italic">V. dahliae</span> biomass in the sunflower, detected by qRT-PCR in response to sunflower growth stages in a greenhouse. (i) V2 stage, fourth leaf stage; V6 stage, eighth leaf stage; R1 stage, early budding period; R5 stage, mid-blooming period; (ii) root, stem, and disc (capitula) represent plant sampling organs. Treatment means were compared using one-way ANOVA, followed by Tukey’s HSD test (<span class="html-italic">p</span> &lt; 0.05). Different letters denote significant differences among treatments (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Analysis of species composition in different rhizosphere soil of sunflower under different sowing dates. (<b>A</b>). Community barplot analysis:Relative abundance of dominant bacteria at phylum classification level in different groups; (<b>B</b>). Venn focused analysis: number of unique and shared species in different groups. Species were determined based on operational taxonomy unit (out) levels.</p>
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<p>Principal coordinates analysis (PCoA) of sunflower rhizosphere soil under different sowing dates analyzed based on Bray–Curtis distance at the operational taxonomy unit (out) level in the field.</p>
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<p>Community analysis at the genus level of sunflower rhizosphere soils under different sowing dates in the field.</p>
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<p>Bacterial species variability in sunflower rhizosphere soils across different combinations of sowing dates and growth stages. (<b>A</b>) Bar Plot of Multi-Species Differential Abundance Analysis. A bar chart was used to illustrate differences in the mean relative abundance of the same species across different groups, with significance levels (<span class="html-italic">p</span>-values) indicated by asterisks to denote statistically significant differences. This visualization provides a clear representation of the species’ significant differences among multiple groups. The Y-axis represents species names at a given taxonomic level, while the X-axis shows the mean relative abundance of the species across different groups. Bars of different colors correspond to distinct groups. The rightmost section displays the P-values, with significance levels indicated as follows: * 0.01 &lt; <span class="html-italic">p</span> ≤ 0.05. (<b>B</b>) Co-occurrence Network of Microbial Taxa Associated with Different Soil Samples. The co-occurrence network illustrates the relationships between microbial taxa at the genus level (green nodes) in two soil samples, S1_V6 (red node) and S5_V6 (blue node). Red lines indicate significant co-occurrence interactions. The size and connectivity of each node reflect the number of associations with other taxa. The network highlights the shared and unique microbial genera associated with each sample.</p>
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<p>Phylogenetic tree of 16 isolated bacterial strains constructed based on 16S rDNA sequences.</p>
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<p>Effect of different SynComs treatments on the growth of sunflowers and disease index of SVW. (<b>A</b>) Statistical chart of disease grade of sunflower by different SynCom treatments. DI (Diseae Index); (<b>B</b>) Effect of different SynCom treatments on sunflower growth. Data were analyzed by one-way ANOVA, followed by Tukey’s HSD test for multiple comparisons (<span class="html-italic">p</span> &lt; 0.05) using SPSS software (version 22.0). Error bars represent the standard deviation. Different lowercase letters indicate significant differences (Tukey’s multiple range test) (<span class="html-italic">p</span> &lt; 0.05).</p>
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16 pages, 4939 KiB  
Article
Development and Validation of RAA-CRISPR/Cas12a-Based Assay for Detecting Porcine Rotavirus
by Siyu Huang, Longhuan Du, Song Liu, Qingcheng Yang, Changwei Lei, Hongning Wang, Liu Yang and Xin Yang
Animals 2024, 14(23), 3387; https://doi.org/10.3390/ani14233387 - 25 Nov 2024
Viewed by 327
Abstract
Piglet diarrhea poses significant economic losses to the pig industry, posing a worldwide challenge that urgently needs to be addressed in pig breeding practices. Porcine rotavirus (PoRV) is an important viral diarrhea pathogen in piglets, with a high incidence rate and a tendency [...] Read more.
Piglet diarrhea poses significant economic losses to the pig industry, posing a worldwide challenge that urgently needs to be addressed in pig breeding practices. Porcine rotavirus (PoRV) is an important viral diarrhea pathogen in piglets, with a high incidence rate and a tendency to cause growth retardation. To enhance the sensitivity and specificity of PoRV detection, we sequenced the NSP3 gene of G5 and G9 genotypes of rotavirus A (RVA), enabling simultaneous detection of the two serotypes. Subsequently, we developed a rapid PoRV detection method using a combination of recombinase-aided amplification (RAA) and CRISPR/Cas12a. In this method, Cas12a binds to RAA amplification products, guided by CRISPR-derived RNA (crRNA), which activates its cleavage activity and releases fluorescence by cutting FAM-BHQ-labeled single-stranded DNA (ssDNA). In the optimized reaction system, the recombinant plasmid PoRV can achieve a highly sensitive reaction within 30 min at 37 °C, with a detection limit as low as 2.43 copies/μL, which is ten times higher in sensitivity compared to the qPCR method. Results from specificity testing indicate that no cross-reactivity was observed between the RAA-CRISPR/Cas12a analysis of PoRV and other viral pathogens, including PoRV G3, PoRV G4, porcine epidemic diarrhea virus (PEDV), porcine epidemic diarrhea (PDCoV), and porcine reproductive and respiratory syndrome virus (PRRSV). In the clinical sample detection using the RAA-CRISPR/Cas12a method and qPCR, Cohen’s Kappa value reached as high as 0.952. Furthermore, this approach eliminates the need for large-scale instrumentation, offering a visual result under an ultraviolet lamp through fluorescence signal output. Full article
(This article belongs to the Section Pigs)
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<p>Screening of primers for RAA and CRISPR/Cas12a detecting PoRV. (<b>a</b>) Gel electrophoresis of RAA primer screening (M: marker; P1–P4: Four different mutation types of PoRV plasmids designed); (<b>b</b>) Fluorescence images for feasibility assessment; (<b>c</b>) Fluorescent results of four different PoRV plasmids detected by the RAA-CRISPR/Cas12a assay were collected at 10 min for the Cas12a reaction. Three replicates were conducted for each test. Fluorescence intensity values are shown in the graph as mean ± SD (NTC: negative control, ddH<sub>2</sub>O; ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001).</p>
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<p>Optimization of RAA. (<b>a</b>) Temperature of RAA; (<b>b</b>) Time of RAA (NTC: negative control, ddH<sub>2</sub>O).</p>
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<p>Optimization of CRISPR/Cas12a. (<b>a</b>) Time of Cas12a; (<b>b</b>) Concentration of Cas12a; (<b>c</b>) Concentration of crRNA; (<b>d</b>) Dosage of FQ-ssDNA (NTC: negative control, ddH<sub>2</sub>O; **** <span class="html-italic">p</span> &lt; 0.0001; *** <span class="html-italic">p</span> &lt; 0.001; ** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>Optimization of CRISPR/Cas12a. (<b>a</b>) Time of Cas12a; (<b>b</b>) Concentration of Cas12a; (<b>c</b>) Concentration of crRNA; (<b>d</b>) Dosage of FQ-ssDNA (NTC: negative control, ddH<sub>2</sub>O; **** <span class="html-italic">p</span> &lt; 0.0001; *** <span class="html-italic">p</span> &lt; 0.001; ** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>Specificity of RAA combined with Cas12a detecting PoRV. (<b>a</b>) Fluorescence image of the Cas12a assay (P1 and P4: Two different base mutant plasmids were designed); (<b>b</b>) fluorescent results of different porcine pathogens detected by the RAA-CRISPR/Cas12a assay were collected at 10 min for the Cas12a reaction. Three replicates were conducted for each test. Fluorescence intensity values are shown in the graph as mean ± SD. (NTC: negative control, ddH<sub>2</sub>O; *** <span class="html-italic">p</span> &lt; 0.001; ** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>Sensitivity of RAA combined with Cas12a for detecting four standard PoRV plasmids. (<b>a</b>) Sensitivity of PoRV1 standard. The fluorescence intensity of each sample was collected at 10 min for the Cas12a reaction; bar graphs represent fluorescent signals for the Cas12a reaction from the fluorescence image, and three replicates were conducted for each test. Fluorescence intensity values are shown in the graph as mean ± SD (NTC: negative control, ddH<sub>2</sub>O; * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001); (<b>b</b>) sensitivity of PoRV4 standard; (<b>c</b>) sensitivity of PoRV10 standard; (<b>d</b>) sensitivity of PoRV12 standard.</p>
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<p>Sensitivity of RAA combined with Cas12a for detecting four standard PoRV plasmids. (<b>a</b>) Sensitivity of PoRV1 standard. The fluorescence intensity of each sample was collected at 10 min for the Cas12a reaction; bar graphs represent fluorescent signals for the Cas12a reaction from the fluorescence image, and three replicates were conducted for each test. Fluorescence intensity values are shown in the graph as mean ± SD (NTC: negative control, ddH<sub>2</sub>O; * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001); (<b>b</b>) sensitivity of PoRV4 standard; (<b>c</b>) sensitivity of PoRV10 standard; (<b>d</b>) sensitivity of PoRV12 standard.</p>
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<p>Sensitivity of qPCR detection for PoRV. The PoRV1 standard sample was serially diluted in a 10-fold gradient from 10<sup>5</sup> copies/μL to 10<sup>0</sup> copies/μL, and PoRV1 continuous dilutions were amplified using a specific primer set. Concentration unit: copies/μL (NTC: negative control, ddH<sub>2</sub>O).</p>
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<p>The assay reproducibility of RAA-CRISPR/Cas12a detecting PoRV. (<b>a</b>) The fluorescence intensity of PoRV1 was detected by RAA-CRISPR/Cas12a at 10 min, and the method was replicated in triplicate at the same PoRV target concentration. Fluorescence intensity values are shown in the plot as mean ± SD (NTC: negative control, ddH<sub>2</sub>O; **** <span class="html-italic">p</span> &lt; 0.0001); (<b>b</b>) fluorescence image of PoRV assay reproducibility (P1: PoRV1 standard; +: positive sample; —: negative control).</p>
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<p>The RAA/Cas12a results of PoRV in some diarrhea samples. The bar chart displays the fluorescent signals detected by RAA-CRISPR/Cas12a for some PoRV samples at the 10-min point of the Cas12a reaction. (NTC: Negative control, ddH<sub>2</sub>O; R1–R30: the number of partial detection samples).</p>
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<p>qPCR detection results of PoRV in some samples. (NTC: negative control, ddH<sub>2</sub>O).</p>
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14 pages, 553 KiB  
Article
Characterizing Methicillin-Resistant Staphylococcus spp. and Extended-Spectrum Cephalosporin-Resistant Escherichia coli in Cattle
by Lisa Abdank, Igor Loncaric, Sascha D. Braun, Elke Müller, Stefan Monecke, Ralf Ehricht and Reinhild Krametter-Frötscher
Animals 2024, 14(23), 3383; https://doi.org/10.3390/ani14233383 - 25 Nov 2024
Viewed by 471
Abstract
In the field of cattle medicine in Austria, to date, few studies have investigated the presence of methicillin-resistant Staphylococcus aureus and extended-spectrum β-lactamase-producing Escherichia coli in Austria. For this reason, milk and nasal samples were examined for the presence of methicillin-resistant Staphylococcus aureus as well as [...] Read more.
In the field of cattle medicine in Austria, to date, few studies have investigated the presence of methicillin-resistant Staphylococcus aureus and extended-spectrum β-lactamase-producing Escherichia coli in Austria. For this reason, milk and nasal samples were examined for the presence of methicillin-resistant Staphylococcus aureus as well as fecal samples for extended-spectrum cephalosporin-resistant Escherichia coli. The nasal and fecal swabs were collected during the veterinary treatment of calf pneumonia and calf diarrhea. For the milk samples, the first milk jets were milked into a pre-milking cup and then the teats were cleaned and disinfected before the samples were taken. The cows were selected during the veterinary visits to the farms when treatment was necessary due to mastitis. Depending on the severity of the mastitis (acute mastitis or subclinical mastitis), antibiotics and non-steroidal anti-inflammatory drugs were given immediately (acute disease) or after completion of the antibiogram (subclinical disease). Isolates were characterized by a polyphasic approach including susceptibility pheno- and genotyping and microarray-based assays. No methicillin-resistant Staphylococcus aureus was found in the milk samples, but one nasal swab was positive for methicillin-resistant Staphylococcus aureus. Twenty-two Escherichia coli isolates were detected among the fecal samples. All the Escherichia coli isolates were resistant to ceftazidime. In all the Escherichia coli isolates, genes from the blaCTX family were detected with other bla genes or alone; the most frequently observed β-lactamase gene was blaCTX-M-1/15 (n = 20). In total, 63.6% (n = 14) of the isolates exhibited a multidrug-resistant phenotype and one E. coli isolate (4.5%) harbored the AmpC gene. Precisely because the presence of data regarding extended-spectrum cephalosporin-resistant Escherichia coli and methicillin-resistant Staphylococcus aureus in calves and cows in Austria is rare, this study further expands our understanding of antimicrobial resistance in Austrian cattle, which is highly relevant for successful antibiotic therapy in sick cattle. Full article
(This article belongs to the Section Cattle)
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<p>SplitsTree network of extended-spectrum cephalosporin-resistant <span class="html-italic">Escherichia coli</span>. Abbreviations: K, fecal sample.</p>
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9 pages, 1570 KiB  
Article
Antibiotic Resistance Genes Detection in Several Local Cyanobacteria Isolates
by Harith K. Buniya, Nuha A. Mohammed and Dhyauldeen Aftan Al-Hayani
Limnol. Rev. 2024, 24(4), 568-576; https://doi.org/10.3390/limnolrev24040033 - 23 Nov 2024
Viewed by 419
Abstract
Antibiotic resistance in cyanobacteria represents a global threat to public health. The widespread presence of cyanobacteria in aquatic environments exposes them to antibiotic contamination. Cyanobacteria are also in direct contact with pathogenic bacteria containing antibiotic-resistance genes (ARGs), which impart these characteristics to them. [...] Read more.
Antibiotic resistance in cyanobacteria represents a global threat to public health. The widespread presence of cyanobacteria in aquatic environments exposes them to antibiotic contamination. Cyanobacteria are also in direct contact with pathogenic bacteria containing antibiotic-resistance genes (ARGs), which impart these characteristics to them. This study aims to examine the presence of some ARGs in locally isolated cyanobacteria species, Spirulina laxa, Chroococcus minutes, Oscillatoria princeps, Oscillatoria proteus, Oscillatoria terebriformis, and Lyngbya epiphytica, and compare the presence of these genes in two pathogenic bacteria, Escherichia coli and Klebsiella pneumoniae. Ampicillin (Ap) and erythromycin (Em) resistance genes were detected in five algal samples. Meanwhile, Chloramphenicol (Cm) and gentamicin (Gm) resistance genes were apparent in only two species. Genes encoding resistance towards kanamycin (Km) and spectinomycin (Sp) were recorded in three specimens. It was also found that E. coli possessed resistance genes for four antibiotics, ampicillin (Ap), erythromycin (Em), gentamicin (Gm), and kanamycin (Km), whereas K. pneumoniae was resistant towards three antibiotics, ampicillin (Ap), gentamicin (Gm), and kanamycin (Km). The results show that there is a match in antibiotic-resistance genes in both cyanobacteria and pathogenic bacteria. Suggesting the possibility that cyanobacteria could acquire ARGs from the environment through horizontal gene transfer. Thus, freshwater cyanobacteria may play a significant role in the prevalence of ARGs in their environment. Full article
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<p>The agarose gel electrophoresis (1.5%, 60 min, 70 V/cm<sup>2</sup>) results of the ARGs in <span class="html-italic">Oscillatoria</span>; (1) <span class="html-italic">O. princeps</span>, (2) <span class="html-italic">O. proteus</span>, and (3) <span class="html-italic">O. terebriformis,</span> with 100 bp DNA ladder. aad: Sp<sup>R</sup>, erm: Em<sup>R</sup>, npt: Km<sup>R</sup>, bla: Ap<sup>R</sup>, grm: Gm<sup>R</sup>, cat: Cm<sup>R</sup>. each subfigure (<b>a</b>–<b>c</b>) represents two types of ARGs for 3 species belong genus Oscillatoria. the appearance of gene bands in PCR products refers to owned the freshwater cyanobacteria for characteristic of Antibiotic resistance. The ARGs bands is indicated by an arrow.</p>
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<p>The agarose gel electrophoresis (1.5%, 60 min, 70 V/cm<sup>2</sup>) results of the ARGs in (<b>a</b>) <span class="html-italic">Spirulinalaxa</span>, (<b>b</b>) <span class="html-italic">Lyngbyaepiphytica</span>, and (<b>c</b>) <span class="html-italic">Chroococcus minutes</span>, with 100 bp DNA ladder. aad: Sp<sup>R</sup>, erm: Em<sup>R</sup>, npt: Km<sup>R</sup>, bla: Ap<sup>R</sup>, grm: Gm<sup>R</sup>, cat: Cm<sup>R</sup>. The ARGs bands is indicated by an arrow.</p>
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<p>The agarose gel electrophoresis (1.5%, 60 min, 70 V/cm<sup>2</sup>) results of the ARGs in the pathogenic bacteria (<b>a</b>) <span class="html-italic">E. coli</span> and (<b>b</b>) <span class="html-italic">K. Pneumonia</span>, with 100 bp DNA ladder. aad: Sp<sup>R</sup>, erm: Em<sup>R</sup>, npt: Km<sup>R</sup>, bla: Ap<sup>R</sup>, grm: Gm<sup>R</sup>, cat: Cm<sup>R</sup>. The ARGs bands is indicated by an arrow.</p>
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26 pages, 3070 KiB  
Article
Development, Optimization, and Validation of a Quantitative PCR Assay for Borrelia burgdorferi Detection in Tick, Wildlife, and Human Samples
by Julie Lewis, Vett K. Lloyd and Gilles A. Robichaud
Pathogens 2024, 13(12), 1034; https://doi.org/10.3390/pathogens13121034 - 23 Nov 2024
Viewed by 349
Abstract
Tick-borne pathogens are growing in importance for human and veterinary research worldwide. We developed, optimized, and validated a reliable quantitative PCR (qPCR; real-time PCR) assay to assess Borrelia burgdorferi infection by targeting two B. burgdorferi genes, ospA and flaB. When assessing previously [...] Read more.
Tick-borne pathogens are growing in importance for human and veterinary research worldwide. We developed, optimized, and validated a reliable quantitative PCR (qPCR; real-time PCR) assay to assess Borrelia burgdorferi infection by targeting two B. burgdorferi genes, ospA and flaB. When assessing previously tested tick samples, its performance surpassed the nested PCR in efficiency, sensitivity, and specificity. Since the detection of Borrelia is more difficult in mammalian samples, the qPCR assay was also assessed using wildlife tissues. For wildlife samples, the sensitivity and specificity of ospA primers, with the incorporation of a pre-amplification step, was equivalent or superior to the nested PCR. For human samples, no primer set was successful with human tissue without culture, but we detected Borrelia with ospA and flaB primers in 50% of the Lyme culture samples, corresponding to 60% of the participants with a Lyme disease diagnosis or suspicion. The specificity of amplification was confirmed by Sanger sequencing. The healthy participant culture samples were negative. This PCR-based direct detection assay performs well for the detection of Borrelia in different biological samples. Advancements in detection methods lead to a better surveillance of Borrelia in vectors and hosts, and, ultimately, enhance human and animal health. Full article
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<p>Quantitative PCR assay results for the optimization of the commercial qPCR master mix test. The SYBR Green SuperMix is represented in dark gray, the FastMix is in light gray, and the EvaGreen Mix is in white, for the <span class="html-italic">ospA</span> (<b>A</b>) and <span class="html-italic">flaB</span> (<b>B</b>) primers. The average Cq values were calculated from the technical triplicate Cq values and the error bars were calculated using the standard deviation of the technical triplicate Cq values. The NTC sample is a no-template control.</p>
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<p>Detection limit of the qPCR <span class="html-italic">Borrelia</span> primers. The average Cq values, calculated from the technical triplicate Cq values, are represented in gray for <span class="html-italic">ospA</span> and in white for <span class="html-italic">flaB</span>. Error bars were calculated using the standard deviation of the technical triplicate Cq values. The NTC sample is a no-template control.</p>
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<p>Optimization of hybridization temperature for the qPCR primers. The peak graphs show derivatives of the fluorescence as the melting temperature increases. The hybridization temperature gradient covered the following temperatures: 58, 59, 60, 61.2, 62.2, and 63 °C. The melt peaks for the two targeted <span class="html-italic">Borrelia</span> genes, <span class="html-italic">ospA</span> (<b>A</b>) and <span class="html-italic">flaB</span> (<b>B</b>), at different concentrations of <span class="html-italic">Borrelia</span> DNA (10, 1, and 0.1 ng) in 100 ng of human DNA and 100 ng of <span class="html-italic">Borrelia</span> DNA only are combined in these graphs. Hybridization temperatures were grouped (from 58 °C to 60 °C, 61.2 °C, and from 62.2 °C to 63 °C) in these graphs according to the changes observed in the peaks. More than one melt peak or the distortion of peaks indicate a non-specific amplification. The threshold line was placed by the CFX Maestro 1.1 software, version 4.1.2433.1219 based on default settings.</p>
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<p>Efficacy test for the primers used in this study. The efficacy percentage (E) is shown along with the goodness-of-fit (R<sup>2</sup>) and the linear equation for the primers <span class="html-italic">ospA</span> (<b>A</b>) and <span class="html-italic">flaB</span> (<b>B</b>), as determined by the Maestro software 1.1, version 4.1.2433.1219. Standards are samples from a serial dilution (1:10) of <span class="html-italic">Borrelia</span> DNA starting with 100 ng of <span class="html-italic">Borrelia</span> DNA, in a volume of 2 µL, tested with technical triplicates.</p>
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<p>Quantitative PCR results of tick samples. Quantitative PCR for positive ticks, negative ticks, and ambiguous ticks. The classification of ticks as positive, negative, and ambiguous is based on nPCR testing [<a href="#B100-pathogens-13-01034" class="html-bibr">100</a>]. The red line indicates the 35-cycle cut-off line; to be considered positive amplification, both genes must be non-zero values below this line. The average Cq results are shown in gray for <span class="html-italic">ospA</span> primers and in white for <span class="html-italic">flaB</span> primers. The samples starting with the letter “T” represent tick samples. The negative control consisted of a PCR reaction with molecular-grade water instead of DNA (NTC for no-template control) and the positive control was 100 ng of <span class="html-italic">Borrelia</span> DNA in a volume of 2 µL. The average Cq was calculated with the Cq values of technical triplicates and the error bars were calculated by using the standard deviation of the Cq values of the technical triplicates.</p>
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<p>Quantitative PCR results of Lyme BSK-H cultures. Quantitative PCR results for the testing of BSK-H culture derived from Lyme and control samples. These samples were tested for two <span class="html-italic">Borrelia</span> genes (<span class="html-italic">ospA</span> in gray and <span class="html-italic">flab</span> in white). The red line indicates the 35-cycle cut-off line; to be considered positive amplification, both genes must be non-zero values below this line. The samples starting with the letter “L” are Lyme samples and samples starting with the letter “C” are BSK-H culture controls. The sample ending with the letter “s” is the skin sample, “g” is for genital samples, “u” is for urine samples, “p” is for periodontal samples, “a” is for the ankle synovial fluid sample, and “k” is for knee synovial fluid samples. The numbers at the end of the sample’s names (1, 2, or 3) represent the biological replicates. Negative controls consisted in molecular-grade water (NTC for no-template control) and the BSK-H cultures derived from control samples, provided by study participants that were not diagnosed with Lyme disease. The positive control was 100 ng of <span class="html-italic">Borrelia</span> DNA in a volume of 2 µL. The average Cq was calculated from the Cq values of the technical triplicates, and the error bar was calculated by doing the standard deviation of the technical triplicates.</p>
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16 pages, 987 KiB  
Article
Analytical Validation and Performance Evaluation of Amplicon-Based Next-Generation Sequencing Assays for Detecting ERBB2 and Other Gene Amplifications in Solid Tumors
by Ekaterina Olkhov-Mitsel, Danny Chan, Kenneth J. Craddock, August Lin, Grace Luk, Rashmi S. Goswami, Hong Wang, Anna Plotkin, Sharon Nofech-Mozes, David M. Hwang and Weei-Yuarn Huang
Cancers 2024, 16(23), 3927; https://doi.org/10.3390/cancers16233927 - 23 Nov 2024
Viewed by 281
Abstract
Background: Targeted next-generation sequencing (NGS) panels are increasingly being utilized to identify actionable gene amplifications (copy number > 4) among solid tumors. Methods: This study validated the analytical performance of two amplicon-based NGS assays, the Oncomine Comprehensive Panel (OCAv3) and the Oncomine Focus [...] Read more.
Background: Targeted next-generation sequencing (NGS) panels are increasingly being utilized to identify actionable gene amplifications (copy number > 4) among solid tumors. Methods: This study validated the analytical performance of two amplicon-based NGS assays, the Oncomine Comprehensive Panel (OCAv3) and the Oncomine Focus Assay (OFA), for detecting gene amplification in formalin-fixed paraffin-embedded (FFPE) tumors of varying cellularity. OCAv3 was assessed for amplification detection in 756 FFPE samples comprising various tumor types. Results: We demonstrated that with standardized quality control metrics, including median absolute pairwise difference score, these assays can achieve a near-perfect positive predictive value, although their sensitivity for detecting amplifications significantly decreased in tumors with cellularity below 30%. Stratifying tumor cellularity into 10–30%, 31–60%, and 61–95% groups revealed significantly higher gene amplification detection rates in the 31–60% and 61–95% groups versus the 10–30% group (20.6% and 26.7% vs. 9.2%, p < 0.0001). When considering all detected gene amplifications, the average amplification calling per sample was nearly five-fold lower in the 10–30% group versus the 61–95% group (0.11 vs. 0.52; p < 0.0001). To further investigate the analytic performance of OCAv3 in detecting ERBB2 amplification, we analyzed a cohort of 121 uterine carcinomas with confirmed ERBB2 status by HER2 IHC or FISH, in which a threshold incorporating amplifications and tumor cellularity achieved 79% sensitivity and 100% specificity, potentially eliminating the need for FISH analysis in 34% of equivocal cases. In a separate validation cohort, similar analytical performance was observed, with the threshold demonstrating consistent sensitivity and specificity. Conclusions: This study highlights the strengths and limitations of amplicon-based NGS assays in detecting amplifications using real-world data. Full article
(This article belongs to the Special Issue Application of Genomic Testing in Precision Oncology)
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<p>Study design and methodology flowchart. CNV, copy number variations; FFPE, formalin-fixed paraffin-embedded; FISH, fluorescence in situ hybridization; IHC, immunohistochemistry; LOD, limit of detection; MAPD, median absolute pairwise difference; NGS, next-generation sequencing; OCAv3, Oncomine Comprehensive Assay v3; OFA, Oncomine Focus Assay; SNP, single nucleotide polymorphism; UC, uterine carcinoma.</p>
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<p>Decision algorithm for <span class="html-italic">ERBB2</span> amplification classification based on the Oncomine Comprehensive Assay v3 (OCAv3) copy number (CN) and tumor cellularity in uterine carcinoma. We propose a future HER2/<span class="html-italic">ERBB2</span> testing algorithm in which IHC remains the first-tier test, while NGS is used for molecular classification and detection of <span class="html-italic">ERBB2</span> amplifications. Cases with NGS-detected amplification will be classified as positive. For NGS-negative cases with equivocal IHC and/or low tumor cellularity, confirmatory FISH testing will be recommended. The 2.6–3.7 CN range may be considered a “gray zone” requiring further FISH evaluation.</p>
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