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16 pages, 997 KiB  
Article
Quinolone and Tetracycline-Resistant Biofilm-Forming Escherichia coli Isolates from Slovak Broiler Chicken Farms and Chicken Meat
by Nikola Dančová, Gabriela Gregová, Tatiana Szabóová, Ivana Regecová, Ján Király, Vanda Hajdučková and Patrícia Hudecová
Appl. Sci. 2024, 14(20), 9514; https://doi.org/10.3390/app14209514 - 18 Oct 2024
Abstract
Escherichia coli isolates from intensive poultry production are associated with antimicrobial resistance and worldwide health problems. The aim of the study was to detect and evaluate the phenotypic and genotypic antimicrobial resistance, biofilm formation, phylogenetic typing, and virulence factors in E. coli isolates [...] Read more.
Escherichia coli isolates from intensive poultry production are associated with antimicrobial resistance and worldwide health problems. The aim of the study was to detect and evaluate the phenotypic and genotypic antimicrobial resistance, biofilm formation, phylogenetic typing, and virulence factors in E. coli isolates from the rectal swabs of chickens from two farms and swabs of chicken meat purchased from Slovakian food markets. Interpretative readings of minimal inhibitory concentration (MIC) revealed dominant resistance to ampicillin (>50%) in both groups. We also detected higher resistance to ciprofloxacin (45%), tetracycline, ampicillin + sulbactam, and trimethoprim + sulfonamide (each >30%). Here, 28.57% of the strains studied were multidrug-resistant (MDR). The formation of weak biofilms was confirmed in 8.8% of E. coli, while one of the strains obtained from chicken cloacal swabs was classified as a strong biofilm producer. The most frequently confirmed phylogenetic groups in E. coli were B1 and A1 in all groups. PCR detection revealed the presence of genes encoding tetracycline resistance (tetAB) and plasmid-mediated quinolone resistance (qnrABS), and Int1 (52.9%), Tn3 (76.5%), kpsMT II (8.8%), fimA (97.1%), cvaC (38.2%), and iutA (76.5%) genes in the strains studied. Our results demonstrate that chickens and chicken meat were the source of antibiotic-resistant, biofilm-forming, and virulent E. coli, representing a potential risk from the point of view of the One Health concept. Full article
(This article belongs to the Section Applied Microbiology)
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<p>The values of percentage of resistance and MIC xG in E. coli of broiler chicken cloacal swabs and chicken thigh muscle meat. Abbreviations: AMP = ampicillin; SAM = ampicillin + sulbactam; TZP = piperacillin + tazobactam; CXM = cefuroxime; CTX = cefotaxime; CAZ = ceftazidime; SPZ = cefoperazone + sulbactam; FEP = cefepime; ETP = ertapenem; MEM = meropenem; GEN = gentamicin; TOB = tobramycin; AMI = amikacin; CIP = ciprofloxacin; TET = tetracycline; TGC = tigecycline; COL = colistin and COT = trimethoprim + sulfonamide.</p>
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<p>Antimicrobial resistance phenotype mechanisms of <span class="html-italic">E. coli</span> isolates from cloacal swabs and chicken thigh muscle meat.</p>
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16 pages, 30847 KiB  
Article
Notch3 and Its Clinical Importance in Ovarian Cancer
by Bimal Prasad Jit, Alisha Behera, Sahar Qazi, Khushi Mittal, Subhadip Kundu, Babul Bansal, MD Ray and Ashok Sharma
Drugs Drug Candidates 2024, 3(4), 707-722; https://doi.org/10.3390/ddc3040040 - 16 Oct 2024
Viewed by 197
Abstract
Background: Ovarian cancer (OC) is the most prevalent gynecological malignancy in women, often diagnosed at an advanced stage due to the absence of specific clinical biomarkers. Notch signaling, particularly Notch3, is frequently activated in OC and contributes to its oncogenic role. Despite its [...] Read more.
Background: Ovarian cancer (OC) is the most prevalent gynecological malignancy in women, often diagnosed at an advanced stage due to the absence of specific clinical biomarkers. Notch signaling, particularly Notch3, is frequently activated in OC and contributes to its oncogenic role. Despite its known association with poor clinical outcomes, the biomarker potential of Notch3 remains inadequately explored. Methods: We investigated the biomarker potential of Notch3 in OC using multiple databases, including ONCOMINE, GEPIA, Human Protein Atlas, UALCAN, Kaplan–Meier Plotter, and LinkedOmics. We analyzed Notch3 expression levels, survival correlations, and clinicopathological parameters. Results: Notch3 expression was significantly upregulated in OC, as well as other cancers. Correlation analysis demonstrated that high Notch3 mRNA levels were associated with poor overall survival (OS) (p < 0.05) and relapse-free survival (p < 0.05) in OC patients. Human Protein Atlas data showed elevated Notch3 protein levels in OC tissues compared to healthy controls. Clinicopathological analysis indicated significant associations between Notch3 expression and patient age (p < 0.5), TP53 mutation status (p < 0.5), and cancer stage (p < 0.1). Additionally, genes such as WIZ, TET1, and CHD4 were found to be co-expressed with Notch3 in OC. Notch3 expression also correlated with immune cell infiltration in OC. Conclusions: Our bioinformatics analysis highlights Notch3 as a potential biomarker for poor prognosis in OC. However, further in vitro and in vivo studies, along with validation using larger tissue samples, are necessary to confirm its biomarker utility. Full article
(This article belongs to the Section Preclinical Research)
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<p>NOTCH3 expression level across cancers from TCGA data in TIMER2.0. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001 (Wilcoxon test). Blue: Normal tissue; Red: Tumor tissue; Purple: Metastatic tumor tissue; Grey: Groups for which statistical analysis was performed.</p>
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<p>Notch3 expression in OC: (<b>a</b>) comparative expression of Notch3 between tumor and normal tissues using GEPIA (* <span class="html-italic">p</span> &lt; 0.05) and (<b>b</b>) Human Protein Atlas data in patients with OC show IHC of Notch3 in normal, endometroid, serous, and mucinous phenotypes. OV: Ovarian dataset; num(T): Number of tumor samples; num(N): Number of normal samples. Red box: Tumor tissues; Grey box: Normal tissue.</p>
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<p>The UALCAN data shows the association of different clinical indicators with NOTCH3 expression: (<b>a</b>) tumor stage, (<b>b</b>) age, (<b>c</b>) race, (<b>d</b>) tumor grade, and (<b>e</b>) TP53 mutation.</p>
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<p>The correlation analysis of NOTCH3 expression with tumor purity and immune infiltration level in immune cells of CD4<sup>+</sup> T cells, Treg cells, B cells, neutrophils, macrophages, myeloid dendritic cells, NK cells, cancer-associated fibroblasts, endothelial cells, hematopoietic stem cells, and myeloid-derived suppressor cells in OC. <span class="html-italic">p</span> &lt; 0.05 is considered statistically significant [Blue line: linear regression; Grey area: confidence interval; each Circle: correlation between Notch3 and individual immune cell for each sample].</p>
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<p>(<b>a</b>) The overall survival status for the expression of NOTCH3 from the GEPIA database and (<b>b</b>) the disease-free survival status for the expression of NOTCH3 from the GEPIA database. Dotted line: 95% confidence interval.</p>
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<p>Coexpression analysis of NOTCH3 by LinkedOmics dataset in OC: (<b>a</b>,<b>b</b>) identification of coexpression profile of NOTCH3; (<b>c</b>) correlation analysis of NOTCH3 with WIZ expression; (<b>d</b>) correlation of NOTCH3 with TET1 expression; and (<b>e</b>) correlation of NOTCH3 with CHD4 expression Red line represents the line of regression.</p>
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<p>Expression and survival analysis of WIZ, TET1, and CHD4 in OC: (<b>a</b>) expression of WIZ using GEPIA database. Red box: Tumor tissues; Grey box: Normal tissue; (<b>b</b>) OS status for expression of WIZ using Kaplan–Meier Plotter; (<b>c</b>) PFS status of WIZ using Kaplan–Meier Plotter; (<b>d</b>) expression of TET1 using GEPIA database; (<b>e</b>) OS status of TET1 using Kaplan–Meier Plotter; (<b>f</b>) PFS of TET1 using Kaplan–Meier Plotter; (<b>g</b>) expression of CHD4 using GEPIA database; (<b>h</b>) OS status of CHD4 using Kaplan–Meier Plotter; and (<b>i</b>) PFS status of CHD4 using Kaplan–Meier Plotter.</p>
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<p>Phylogenetic relationship assessment of NOTCH3 with (<b>a</b>) positively correlated genes and (<b>b</b>) negatively correlated genes OC using Clustal W.</p>
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<p>Spearman correlation analysis of NOTCH3: (<b>a</b>) with lymphocytes, i.e., TILs (<span class="html-italic">y</span> axis), across human cancers (<span class="html-italic">x</span> axis), (<b>b</b>) MHCs (<span class="html-italic">y</span> axis) across human cancers (<span class="html-italic">x</span> axis), (<b>c</b>) and receptors (<span class="html-italic">y</span> axis) across human cancers (<span class="html-italic">x</span> axis).</p>
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<p>Spearman correlation analysis of NOTCH3 with immunomodulators across various cancer types: (<b>a</b>) Spearman correlations analysis of NOTCH3 and immune inhibitors (<span class="html-italic">y</span> axis) across human cancers (<span class="html-italic">x</span> axis), (<b>b</b>) Spearman correlations analysis of NOTCH3 and immunostimulators (<span class="html-italic">y</span> axis) across human cancers (<span class="html-italic">x</span> axis), (<b>c</b>) Spearman correlation analysis of NOTCH3 and chemokines (<span class="html-italic">y</span> axis) across human cancers (<span class="html-italic">x</span> axis).</p>
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21 pages, 6105 KiB  
Article
Guanethidine Restores Tetracycline Sensitivity in Multidrug-Resistant Escherichia coli Carrying tetA Gene
by Xiaoou Zhao, Mengna Zhang, Zhendu Zhang, Lei Wang, Yu Wang, Lizai Liu, Duojia Wang, Xin Zhang, Luobing Zhao, Yunhui Zhao, Xiangshu Jin, Xiaoxiao Liu and Hongxia Ma
Antibiotics 2024, 13(10), 973; https://doi.org/10.3390/antibiotics13100973 - 15 Oct 2024
Viewed by 474
Abstract
The worrying issue of antibiotic resistance in pathogenic bacteria is aggravated by the scarcity of novel therapeutic agents. Antibiotic adjuvants offer a promising solution due to their cost-effectiveness and high efficacy in addressing this issue, such as the β-lactamase inhibitor sulbactam (a β-lactam [...] Read more.
The worrying issue of antibiotic resistance in pathogenic bacteria is aggravated by the scarcity of novel therapeutic agents. Antibiotic adjuvants offer a promising solution due to their cost-effectiveness and high efficacy in addressing this issue, such as the β-lactamase inhibitor sulbactam (a β-lactam adjuvant) and the dihydrofolate reductase inhibitor trimethoprim (a sulfonamide adjuvant). This study aimed to discover potential adjuvants for tetracyclines from a list of previously approved drugs to restore susceptibility to Escherichia coli carrying the tetA gene. We have screened guanethidine, a compound from the Chinese pharmacopoeia, which effectively potentiates the activity of tetracyclines by reversing resistance in tetA-positive Escherichia coli, enhancing its antibacterial potency, and retarding the development of resistance. Guanethidine functions via the inhibition of the TetA efflux pump, thereby increasing the intracellular concentration of tetracyclines. Our findings suggest that guanethidine holds promise as an antibiotic adjuvant. Full article
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<p>The antibacterial activity of guanethidine in combination with tetracyclines against <span class="html-italic">tetA</span>-positive <span class="html-italic">E. coli</span> C3. (<b>A</b>) The FIC index of guanethidine and tetracyclines. The FIC index (fractional inhibitory concentration index) is commonly used to define the interactions between two bioactive compounds. The FIC index is commonly used to assess the synergistic or antagonistic effects of antibiotics when used in combination with other antibiotics or antibiotic adjuvants against microorganisms. Synergy is defined as an FIC index of ≤0.5. (<b>B</b>) The MICs of tetracyclines with or without guanethidine (2.5 mg/mL), the fold of decrease in MICs, and whether sensitivity can be restored. MIC ≤ 4 μg/mL is sensitive, refer to CILS 2020. All experiments were conducted with four biological replicates.</p>
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<p>The antimicrobial efficiency of guanethidine in combination with tetracyclines against <span class="html-italic">E. coli</span> C3. (<b>A</b>) Time–Survivor Curves of guanethidine in combination with tetracyclines within 24 h. (<b>B</b>) Growth curves in 24 h. All experiments were conducted with three biological replicates.</p>
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<p>The FIC indices of guanethidine and tetracycline against various sources of <span class="html-italic">E. coli</span> with or without <span class="html-italic">tetA</span>. Synergy was defined as an FIC index of ≤0.5. All experiments were conducted with four biological replicates.</p>
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<p>The MICs of tetracyclines against <span class="html-italic">E. coli</span> in the DMEM or MH medium, with or without guanethidine (2.5 mg/mL). MIC ≤ 4 μg/mL is sensitive, refer to CILS 2020. All experiments were conducted with four biological replicates.</p>
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<p>Emergence in <span class="html-italic">E. coli</span> ATCC25922 of resistance to tetracycline (<b>A</b>), doxycycline (<b>B</b>), and minocycline (<b>C</b>) with or without guanidine (2.5 mg/mL) after successive passages for 30 days.</p>
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<p>Effects of guanethidine (0–2.5 mg/mL) on the permeability of <span class="html-italic">E. coli</span> C3 cell membrane: (<b>A</b>) outer membrane and (<b>B</b>) inner membrane. The significance of the differences was analyzed by one-way ANOVA: ns, <span class="html-italic">p</span> &gt; 0.05; *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01; and ***, <span class="html-italic">p</span> &lt; 0.001. All experiments were performed with five biological replicates.</p>
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<p>Effects of guanethidine (0–2.5 mg/mL) on the PMF of <span class="html-italic">E. coli</span> C3: (<b>A</b>) the transmembrane potential gradient (ΔΨ) and (<b>B</b>) pH gradient (ΔpH). The significance of the differences was analyzed by one-way ANOVA: ns, <span class="html-italic">p</span> &gt; 0.05; *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01; and ***, <span class="html-italic">p</span> &lt; 0.001. All experiments were performed with three biological replicates.</p>
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<p>Effects of guanethidine (0–2.5 mg/mL) on the intracellular ATP and ROS of <span class="html-italic">E. coli</span> C3: (<b>A</b>) effects on intracellular ATP and (<b>B</b>) effects on intracellular ROS levels. The significance of the differences was analyzed by one-way ANOVA: ns, <span class="html-italic">p</span> &gt; 0.05; *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01; and ***, <span class="html-italic">p</span> &lt; 0.001. All experiments were performed with three biological replicates.</p>
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<p>An increased intracellular accumulation of tetracycline in <span class="html-italic">E. coli</span> caused by guanethidine. (<b>A</b>) An intracellular accumulation of tetracycline with guanethidine (0–2.5 mg/mL) in <span class="html-italic">E. coli</span> C3. (<b>B</b>) An intracellular accumulation of tetracycline with guanethidine (0–2.5 mg/mL) in <span class="html-italic">E. coli</span> ATCC25922. (<b>C</b>) An intracellular accumulation of guanethidine in <span class="html-italic">E. coli</span> C3 or <span class="html-italic">E. coli</span> ATCC25922. The significance of the differences was analyzed by one-way ANOVA: ns, <span class="html-italic">p</span> &gt; 0.05; *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01; and ***, <span class="html-italic">p</span> &lt; 0.001. All experiments were performed with three biological replicates.</p>
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<p>The effect of guanethidine (0–2.5 mg/mL) on the expression of the tetracycline-efflux pump gene <span class="html-italic">tetA</span>. The significance of the differences was analyzed by one-way ANOVA: ns, <span class="html-italic">p</span> &gt; 0.05; *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01; and ***, <span class="html-italic">p</span>&lt; 0.001. All experiments were performed with three biological replicates.</p>
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<p>(<b>A</b>) The screening procedure of <span class="html-italic">E. coli</span> DH5α-ZMN1 (<b>B</b>) The FIC index of guanethidine and tetracyclines. Synergy is defined as an FIC index of ≤0.5. (<b>C</b>) The MICs of tetracyclines with or without guanethidine (2.5 mg/mL), folds decrease in MICs are shown in red. All experiments were performed with four biological replicates.</p>
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<p>The predicted binding mode of protein TetA with the compound guanidine by molecular docking. The protein framework is tubular and stained bright blue, guanethidine is depicted in gray, and the yellow dashed line indicates hydrogen bond distances.</p>
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<p>Checkerboard microdilution method to test the antimicrobial effect of tetracycline in combination with guanethidine and its derivatives. (<b>A</b>) The effect of tetracycline in combination with guanethidine. (<b>B</b>) The effect of tetracycline in combination with guanidine. (<b>C</b>) The effect of tetracycline in combination with azacyclooctane. (<b>D</b>) The effect of tetracycline in combination with guanethidine with the addition of additional subinhibitory concentrations of guanidine (1.25 mg/mL). (<b>E</b>) The effect of tetracycline in combination with guanethidine with the addition of additional subinhibitory concentrations of azacyclooctane (1.25 mg/mL). (<b>F</b>) The chemical formulas of guanethidine and its derivatives guanidine and azacyclooctane. All experiments were performed with three biological replicates.</p>
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<p>(<b>A</b>) The cytotoxicity of different concentrations of guanethidine in combination with tetracycline, and (<b>B</b>) the hemolysis of different concentrations of guanethidine in combination with tetracycline. (<b>A</b>) and (<b>B</b>) are illustrated using the same colour markings. All experiments were performed with three biological replicates.</p>
Full article ">Figure 15
<p>(<b>A</b>) The survival rate of Galleria mellonella larvae infected with <span class="html-italic">E. coli</span> C3 (10<sup>6</sup>CFU/mL). Each group was treated with tetracycline (35 mg/kg) or guanethidine (10 mg/kg) alone or in combination (35 mg/kg +10 mg/kg) (<span class="html-italic">n</span> = 8 per group). (<b>B</b>) The survival of mice infected with <span class="html-italic">E. coli</span> C3 (10<sup>8</sup>CFU/mL). Each group was treated with tetracycline (35 mg/kg) or guanethidine (10 mg/kg) alone or in combination (35 mg/kg +10 mg/kg) (<span class="html-italic">n</span> = 8 per group). <span class="html-italic">p</span> values were tested using the Mantel–Cox test, with <span class="html-italic">p</span> &lt; 0.05 indicating a significant change. (<b>C</b>) <span class="html-italic">E. coli</span> C3 (10<sup>6</sup> CFU/mL) infected mice were treated with tetracycline (35 mg/kg) or guanidine combined with tetracycline (35 mg/kg + 10 mg/kg) to determine the bacterial load in the heart, liver, spleen, lung, and kidney (<span class="html-italic">n</span> = 6 per group). In the <span class="html-italic">t</span>-test, * indicates <span class="html-italic">p</span> &lt; 0.05, a significant difference, and ** indicates <span class="html-italic">p</span> &lt; 0.01, indicating a highly significant difference.</p>
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11 pages, 869 KiB  
Article
Immune Checkpoint Inhibitor Therapy and Associations with Clonal Hematopoiesis
by Abhay Singh, Nuria Mencia Trinchant, Rahul Mishra, Kirti Arora, Smit Mehta, Teodora Kuzmanovic, Maedeh Zokaei Nikoo, Inderpreet Singh, Amanda C. Przespolewski, Mahesh Swaminathan, Marc S. Ernstoff, Grace K. Dy, Lunbiao Yan, Eti Sinha, Shruti Sharma, Duane C. Hassane, Elizabeth A. Griffiths, Eunice Wang, Monica L. Guzman and Swapna Thota
Int. J. Mol. Sci. 2024, 25(20), 11049; https://doi.org/10.3390/ijms252011049 - 15 Oct 2024
Viewed by 283
Abstract
Cancer cohorts are now known to be associated with increased rates of clonal hematopoiesis (CH). We sort to characterize the hematopoietic compartment of patients with melanoma and non-small cell lung cancer (NSCLC) given our recent population level analysis reporting evolving rates of secondary [...] Read more.
Cancer cohorts are now known to be associated with increased rates of clonal hematopoiesis (CH). We sort to characterize the hematopoietic compartment of patients with melanoma and non-small cell lung cancer (NSCLC) given our recent population level analysis reporting evolving rates of secondary leukemias. The advent of immune checkpoint blockade (ICB) has dramatically changed our understanding of cancer biology and has altered the standards of care for patients. However, the impact of ICB on hematopoietic myeloid clonal expansion remains to be determined. We studied if exposure to ICB therapy affects hematopoietic clonal architecture and if their evolution contributed to altered hematopoiesis. Blood samples from patients with melanoma and NSCLC (n = 142) demonstrated a high prevalence of CH. Serial samples (or post ICB exposure samples; n = 25) were evaluated in melanoma and NSCLC patients. Error-corrected sequencing of a targeted panel of genes recurrently mutated in CH was performed on peripheral blood genomic DNA. In serial sample analysis, we observed that mutations in DNMT3A and TET2 increased in size with longer ICB exposures in the melanoma cohort. We also noted that patients with larger size DNMT3A mutations with further post ICB clone size expansion had longer durations of ICB exposure. All serial samples in this cohort showed a statistically significant change in VAF from baseline. In the serial sample analysis of NSCLC patients, we observed similar epigenetic expansion, although not statistically significant. Our study generates a hypothesis for two important questions: (a) Can DNMT3A or TET2 CH serve as predictors of a response to ICB therapy and serve as a novel biomarker of response to ICB therapy? (b) As ICB-exposed patients continue to live longer, the myeloid clonal expansion may portend an increased risk for subsequent myeloid malignancy development. Until now, the selective pressure of ICB/T-cell activating therapies on hematopoietic stem cells were less known and we report preliminary evidence of clonal expansion in epigenetic modifier genes (also referred to as inflammatory CH genes). Full article
(This article belongs to the Special Issue Hematological Malignancies: Molecular Mechanisms and Therapy)
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<p>(<b>A</b>) Description of clinical, hematological, and genetic characteristics of patients with melanoma. (<b>B</b>) Description of clinical, hematological, and genetic characteristics of patients with non-small cell lung cancer. ANC (absolute neutrophil count); Hgb (hemoglobin); MCV (mean corpuscular volume, fL); RDW (red cell distribution width, %); CV (cardiovascular disease); DVT/PE (Deep vein thrombosis/Pulmonary embolism); AID (Autoimmune disease); IrAE (Immune-related adverse events). Race (AA: African American; O: other; W: White), SCC: Squamous cell cancer; NOS (Not otherwise specified); CVD/PAD (cardiovascular disease/Peripheral arterial disease).</p>
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<p>(<b>a</b>) Change in clonal architecture in serial blood samples after exposure to immune checkpoint inhibitor (ICB) in five patients with melanoma. Spider plot depicts difference in variant allele frequencies (VAF) (y-axis) in blood samples pre- and post-ICB therapy ICB (Immune checkpoint inhibitor) plotted against time between pre- and post-sample collection (x-axis); Pre-ICB sample collection at day 0. (<b>b</b>) Age, hematological and treatment characteristics in patients with melanoma and clonal hematopoiesis mutations, at baseline. ANC (absolute neutrophil count, 10<sup>3</sup>/µL); Hgb (hemoglobin, gm/dL); MCV (mean corpuscular volume, fL); RDW (red cell distribution width, %); VAF (Variant allele frequency).</p>
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<p>(<b>a</b>) Change in clonal architecture in serial blood samples after exposure to immune checkpoint inhibitor (ICB) in five patients with melanoma. Spider plot depicts difference in variant allele frequencies (VAF) (y-axis) in blood samples pre- and post-ICB therapy ICB (Immune checkpoint inhibitor) plotted against time between pre- and post-sample collection (x-axis); Pre-ICB sample collection at day 0. (<b>b</b>) Age, hematological and treatment characteristics in patients with melanoma and clonal hematopoiesis mutations, at baseline. ANC (absolute neutrophil count, 10<sup>3</sup>/µL); Hgb (hemoglobin, gm/dL); MCV (mean corpuscular volume, fL); RDW (red cell distribution width, %); VAF (Variant allele frequency).</p>
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15 pages, 1685 KiB  
Article
Prevalence, Virulence Genes, Drug Resistance and Genetic Evolution of Trueperella pyogenes in Small Ruminants in Western China
by Yuchen Wei, Bin Wang, Ke Wu, Chenxiao Wang, Xindong Bai, Juan Wang and Zengqi Yang
Animals 2024, 14(20), 2964; https://doi.org/10.3390/ani14202964 (registering DOI) - 14 Oct 2024
Viewed by 290
Abstract
Trueperella pyogenes is a significant opportunistic pathogen that causes substantial economic losses in animal agriculture due to its ability to infect various animal tissues and organs. Limited research has been conducted on the prevalence and biological characteristics of T. pyogenes isolated from sheep [...] Read more.
Trueperella pyogenes is a significant opportunistic pathogen that causes substantial economic losses in animal agriculture due to its ability to infect various animal tissues and organs. Limited research has been conducted on the prevalence and biological characteristics of T. pyogenes isolated from sheep and goats. This study aimed to isolate T. pyogenes from clinical samples of sheep and goats in western China, examining genetic evolutionary relationships, antibiotic resistance, and virulence genes. Between 2021 and 2023, standard bacteriological methods were used to isolate and identify T. pyogenes from 316 samples (209 from goats and 107 from sheep) collected from 39 farms. Susceptibility to 14 antibiotics was tested using broth microdilution per CLSI guidelines, and PCR detected eight virulence genes. Whole-genome sequencing analyzed genetic relationships and gene carriage status in 39 isolates. The results indicated that 86 strains of T. pyogenes were isolated from 316 samples, yielding an isolation rate of 27.2% (goats n = 47, 22.5%; sheep n = 39, 36.4%). The virulence genes plo, cbpA, nanH, nanP, fimA, fimC, and fimE were present in 100%, 66.7%, 64.1%, 71.8%, 69.2%, 59.0%, and 82.1% of isolates, respectively, with none carrying the fimG gene. The dominant virulence genotype was plo/nanH/nanP/fimA/fimC/fimE. The isolates exhibited resistance to erythromycin (44.2%, 38/86), gentamicin (38.4%, 33/86), sulfamethoxazole/trimethoprim (37.2%, 32/86), tetracycline (32.6%, 28/86), and streptomycin (32.6%, 28/86), and low resistance to chloramphenicol (14.0%, 12/86), ciprofloxacin (7.0%, 6/86), penicillin (5.8%, 5/86), and clindamycin (4.7%, 4/86). All isolates were susceptible to cefotaxime, vancomycin, and linezolid. Among the 86 isolates, 37 (43.0%) displayed multidrug resistance (MDR) characteristics. The whole genome sequencing of 39 isolates identified eight types of resistance genes, including ant(2″)-Ia, ant(3″)-Ia, cmlA1, cmx, erm(X), lnu(A), sul1, and tet(W). Except for tet(W), erm(X), and sul1, the other resistance genes were reported for the first time in T. pyogenes isolated in China. The drug susceptibility test results and resistance gene detection for the isolated strains were consistent for tetracycline, erythromycin, gentamicin, and sulfisoxazole. Similar allelic profiles and genetic evolutionary relationships were found among isolates from different farms. This study highlights the antibiotic resistance status and virulence gene-carrying rate of Trueperella pyogenes, providing a basis for clinical medication. Full article
(This article belongs to the Section Veterinary Clinical Studies)
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<p>Prevalence rate of <span class="html-italic">T. pyogenes</span> for different clinical manifestations in sheep and goats (** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>Different virulence gene prevalence rates of <span class="html-italic">T. pyogenes</span> isolates derived from sheep and goats (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>Graphical representation of MIC distribution of 14 antimicrobial agents against <span class="html-italic">T. pyogenes</span> isolated from sheep and goats. All the isolates from goats (●), sheep (▲), and origin are represented on the abscissa axis, and every spot represents one single isolate. The results of MIC (μg/mL) of each antimicrobial against the isolates under study are indicated on the ordinate axis. The median is shown with a horizontal black line. * Statistically significant difference among the MIC distribution of <span class="html-italic">T. pyogenes</span> populations (* <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). Abbreviations PEN: Penicillin; A/C: amoxicillin and clavulanate potassium; E: erythromycin; CLI: clindamycin; CTX: cefotaxime; CIP: ciprofloxacin; VAN: vancomycin; SXT: Sulfamethoxazole/Trimethoprim (19/1); TE: tetracycline; FFC: florfenicol; CPL: chloramphenicol; SM: streptomycin; GEN: gentamicin; LZD: linezolid.</p>
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<p>Antimicrobial susceptibility of <span class="html-italic">T. Pyogenes</span> isolated from uterine lavage fluid in China. White, green, and grey bars represent the proportion of sensitive strains, moderately resistant strains, and resistant strains, respectively. Dark gray bars represent the respective strain’s proportion of multidrug resistance (MDR ≥ 3).</p>
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<p>Phylogenetic tree and distribution of virulence genes and antimicrobial resistance genes of the 39 <span class="html-italic">T. pyogenes</span> isolates from goats and sheep.</p>
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12 pages, 1596 KiB  
Perspective
Lactobacillus Eats Amyloid Plaque and Post-Biotically Attenuates Senescence Due to Repeat Expansion Disorder and Alzheimer’s Disease
by Suresh C. Tyagi
Antioxidants 2024, 13(10), 1225; https://doi.org/10.3390/antiox13101225 - 12 Oct 2024
Viewed by 556
Abstract
Patients with Alzheimer’s disease and related dementia (ADRD) are faced with a formidable challenge of focal amyloid deposits and cerebral amyloid angiopathy (CAA). The treatment of amyloid deposits in ADRD by targeting only oxidative stress, inflammation and hyperlipidemia has not yielded significant positive [...] Read more.
Patients with Alzheimer’s disease and related dementia (ADRD) are faced with a formidable challenge of focal amyloid deposits and cerebral amyloid angiopathy (CAA). The treatment of amyloid deposits in ADRD by targeting only oxidative stress, inflammation and hyperlipidemia has not yielded significant positive clinical outcomes. The chronic high-fat diet (HFD), or gut dysbiosis, is one of the major contributors of ADRD in part by disrupted transport, epigenetic DNMT1 and the folate 1-carbon metabolism (FOCM) cycle, i.e., rhythmic methylation/de-methylation on DNA, an active part of epigenetic memory during genes turning off and on by the gene writer (DNMT1) and eraser (TET2/FTO) and the transsulfuration pathway by mitochondrial 3-mercaptopyruvate sulfur transferase (3MST)-producing H2S. The repeat CAG expansion and m6A disorder causes senescence and AD. We aim to target the paradigm-shift pathway of the gut–brain microbiome axis that selectively inhibits amyloid deposits and increases mitochondrial transsulfuration and H2S. We have observed an increase in DNMT1 and decreased FTO levels in the cortex of the brain of AD mice. Interestingly, we also observed that probiotic lactobacillus-producing post-biotic folate and lactone/ketone effectively prevented FOCM-associated gut dysbiosis and amyloid deposits. The s-adenosine-methionine (SAM) transporter (SLC25A) was increased by hyperhomocysteinemia (HHcy). Thus, we hypothesize that chronic gut dysbiosis induces SLC25A, the gene writer, and HHcy, and decreases the gene eraser, leading to a decrease in SLC7A and mitochondrial transsulfuration H2S production and bioenergetics. Lactobacillus engulfs lipids/cholesterol and a tri-directional post-biotic, folic acid (an antioxidant and inhibitor of beta amyloid deposits; reduces Hcy levels), and the lactate ketone body (fuel for mitochondria) producer increases SLC7A and H2S (an antioxidant, potent vasodilator and neurotransmitter gas) production and inhibits amyloid deposits. Therefore, it is important to discuss whether lactobacillus downregulates SLC25A and DNMT1 and upregulates TET2/FTO, inhibiting β-amyloid deposits by lowering homocysteine. It is also important to discuss whether lactobacillus upregulates SLC7A and inhibits β-amyloid deposits by increasing the mitochondrial transsulfuration of H2S production. Full article
(This article belongs to the Special Issue Oxidative Stress as a Therapeutic Target of Alzheimer’s Disease)
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<p>Chronic high fat dysbiosis diet leads to increase methionine and long-chain fatty acids (LCFA). This causes hyperhomocysteinemia (HHcy), lowers short chain fatty acids (SCFA), folate, ketone/lactone, hydrogen sulfide (H<sub>2</sub>S). The probiotic lactobacillus reveres.</p>
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<p>Schematics of how gut dysbiosis leads to epigenetic methylation alterations and causes Alzheimer’s disease (AD). ADAR, adenosine deaminase acting on RNA; CAG, cytidine-adenosine-guanidine), m<sup>1</sup>A, methyl-1-adinosine; SAM, s-adenosine methionine; SAH, s-adenosine homocysteine; SAHH, s-adenosine homocysteine hydrolase; DNMT, DNA methyltransferase; TET, ten eleven translocators; HDAC, histone de-acetylase; SIRT, Histone-protein de-acetylase; H3K4, histone-3 lysine 4 [<a href="#B21-antioxidants-13-01225" class="html-bibr">21</a>,<a href="#B60-antioxidants-13-01225" class="html-bibr">60</a>,<a href="#B61-antioxidants-13-01225" class="html-bibr">61</a>].</p>
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<p>Repeat nucleotide sequences (CAG) cause random mutations, leading to ALS and AD. The tannic acid inhibits transporter SLC25A and mitigates ALS and AD.</p>
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<p>During ischemic conditions such as COPD, sleep apnea and decrease pulmonary function, initially mitochondrial synthesizes H<sub>2</sub>S and coups with dys-bioenergetics. COPD, chronic obstructive pulmonary diseases; TCA, tri-carboxylic acid; CAT, cysteine transferase; 3MST, 3mercaprtopyruvate sulfotransferase; CBS, cystathionine beta transferase; Piezo, mechano-thermal Na/Ca/Mg and transient receptor potential receptor/channels.</p>
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<p>The probiotics lactobacillus mitigates folate deficiency and improves mitochondrial pyruvates and H<sub>2</sub>S levels, post-biotically. PCP, phosphatidylcartinine phosphatase; BHMT, betaine homocysteine methyl transferase.</p>
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<p>The hypothesis is that the chronic gut-dysbiosis induces SLC25A, <b>gene writer (DNMT1)</b>, HHcy and decreases gene eraser (TET2/FTO), leading to decrease SLC7A and mitochondrial transsulfuration H<sub>2</sub>S production and bioenergetics. Lactobacillus, a tri-directional, <b>folic acid (an inhibitor of beta amyloid deposits</b>, reduces Hcy levels), and lactate ketone-body (fuel for mitochondria) producer <b>increases SLC7A and</b> H<sub>2</sub>S production and inhibits amyloid deposits.</p>
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14 pages, 2854 KiB  
Article
Serotype Distribution and Antimicrobial Resistance of Salmonella Isolates from Poultry Sources in China
by Chu Wang, Xianwen Wang, Juyuan Hao, He Kong, Liyuan Zhao, Mingzhen Li, Ming Zou and Gang Liu
Antibiotics 2024, 13(10), 959; https://doi.org/10.3390/antibiotics13100959 - 11 Oct 2024
Viewed by 407
Abstract
Background: Salmonella is an important zoonotic pathogen, of which poultry products are important reservoirs. This study analyzed the prevalence, antimicrobial resistance, and characterization of Salmonella from broiler and laying hen sources in China. Methods: A total of 138 (12.27%) strains of Salmonella were [...] Read more.
Background: Salmonella is an important zoonotic pathogen, of which poultry products are important reservoirs. This study analyzed the prevalence, antimicrobial resistance, and characterization of Salmonella from broiler and laying hen sources in China. Methods: A total of 138 (12.27%) strains of Salmonella were isolated from 1125 samples from broiler slaughterhouses (20.66%, 44/213), broiler farms (18.21%, 55/302), and laying hen farms (6.39%, 39/610). Multiplex PCR was used to identify the serotypes. Antibiotic susceptibility testing to a set of 21 antibiotics was performed and all strains were screened by PCR for 24 selected antimicrobial resistance genes (ARGs). In addition, 24 strains of Salmonella were screened out by whole-genome sequencing together with 65 released Salmonella genomes to evaluate phylogenetic characteristics, multilocus sequence typing (MLST), and plasmid carriage percentages. Results: A total of 11 different serotypes were identified, with the dominance of S. Enteritidis (43/138, 31.16%), S. Newport (30/138, 21.74%), and S. Indiana (19/138, 13.77%). The results showed that S. Enteritidis (34.34%, 34/99) and S. Newport (51.28%, 20/39) were the dominant serotypes of isolates from broilers and laying hens, respectively. The 138 isolates showed the highest resistance to sulfisoxazole (SXZ, 100%), nalidixic acid (NAL, 54.35%), tetracycline (TET, 47.83%), streptomycin (STR, 39.86%), ampicillin (AMP, 39.13%), and chloramphenicol (CHL, 30.43%), while all the strains were sensitive to both tigacycline (TIG) and colistin (COL). A total of 45.65% (63/138) of the isolates were multidrug-resistant (MDR) strains, and most of them (61/63, 96.83%) were from broiler sources. The results of PCR assays revealed that 63.77% of the isolates were carrying the quinolone resistance gene qnrD, followed by gyrB (58.70%) and the trimethoprim resistance gene dfrA12 (52.17%). Moreover, a total of thirty-four ARGs, eighty-nine virulence genes, and eight plasmid replicons were detected in the twenty-four screened Salmonella strains, among which S. Indiana was detected to carry the most ARGs and the fewest plasmid replicons and virulence genes compared to the other serotypes. Conclusions: This study revealed a high percentage of multidrug-resistant Salmonella from poultry sources, stressing the importance of continuous monitoring of Salmonella serotypes and antimicrobial resistance in the poultry chain, and emergency strategies should be implemented to address this problem. Full article
(This article belongs to the Special Issue Antimicrobial Resistance and Infections in Animals)
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<p>Area, source, and overall isolation percentages of <span class="html-italic">Salmonella</span>. The Y-axis represents the positive percentage of <span class="html-italic">Salmonella</span>, and the X-axis represents the sampling area. The three different-colored columns represent the overall, broiler source, and laying hen source. There were no laying hen samples from Shandong Province, so the overall positivity percentage was consistent with the positivity percentage of the broiler samples.</p>
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<p>Sankey diagram of the regional distribution, source, serotype, and MDR index of all strains. The diameter of the line is proportional to the number of isolates from a given source, which is also shown in parentheses on the right. MDR denotes multidrug resistance.</p>
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<p>Antibiotic susceptibility pattern of <span class="html-italic">Salmonella</span> isolates. The X-axis represents the antibiotics used, and the Y-axis represents the proportion of strains with different sensitivities to the drugs. Red represents resistance, orange represents intermediate, and gray represents susceptible.</p>
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<p>Heatmap showing the AMR gene profiles identified in this study. Different groups of serotype strains are color-coded. The heatmap shows the profile of drug resistance genes detected in the studied isolates. The Y-axis shows the drug resistance gene detected, and the X-axis shows the serotype to which the detected strain belongs. Light gray, negative.</p>
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<p>Phylogenetic structure, region, sample source, serotype, MLST, antibiotic resistance genotype, virulence genotype, and replicon typing of 24 <span class="html-italic">Salmonella</span> strains. Hollow cells do not carry the relevant gene. Circles, replicon typing.</p>
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<p>Phylogenetic tree of strains of the same serotype and origin from the NCBI database worldwide. Different-colored branches represent closer relationships. The red highlights are the strains used in this study. The circles from inside to outside represent the regional year of the strain (circle 1), the geographical origin of the strain (circle 2), the sample source of the strain (circle 3), the serotype of the strain (circle 4), and the number of drug resistance genes carried by the strain (bar graph).</p>
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14 pages, 1644 KiB  
Article
Characteristics and Prognosis of “Acute Promyelocytic Leukemia-like” Nucleophosmin-1-Mutated Acute Myeloid Leukemia in a Retrospective Patient Cohort
by Vasiliki Papadopoulou, Giulia Schiavini, Gregoire Stalder, Valentin Basset, Jacqueline Schoumans, Mitja Nabergoj and Muriel Schaller
Biomedicines 2024, 12(10), 2282; https://doi.org/10.3390/biomedicines12102282 - 9 Oct 2024
Viewed by 385
Abstract
Background: AML with NPM1 mutation is the largest subcategory of AML, representing about 35% of AML cases. It is characterized by CD34 negativity, which suggests a relatively differentiated state of the bulk of leukemic blasts. Notably, a significant subset of NPM1-mutated AML cases [...] Read more.
Background: AML with NPM1 mutation is the largest subcategory of AML, representing about 35% of AML cases. It is characterized by CD34 negativity, which suggests a relatively differentiated state of the bulk of leukemic blasts. Notably, a significant subset of NPM1-mutated AML cases also exhibit HLA-DR negativity, classifying them as “double-negative”, and mimicking, therefore, the CD34 HLA-DR immunophenotype of acute promyelocytic leukemia (APL). Objectives: This study focuses on the “acute promyelocytic leukemia-like” (“APL-like”) subset of NPM1-mutated AML, which can be challenging to distinguish from APL at presentation, prior to confirming RARa translocations. We aim to investigate the hematologic and immunophenotypic parameters that may aid to its distinction from APL. Additionally, we explore differences in genetic profile and prognosis between “APL-like” and “non-APL-like” NPM1-mutated AML cases. Methods: We conducted a retrospective evaluation of 77 NPM1-mutated AML cases and 28 APL cases. Results: Morphological characteristics, hematologic parameters (such as DD/WBC and PT/WBC), and specific immunophenotypic markers (including SSC, CD64, and CD4) can assist in the early distinction of “APL-like” NPM1-mutated AML from APL. Regarding differences in genetic profiles and outcomes between “APL-like” and non-“APL-like” NPM1-mutated AML cases, we observed a significantly higher incidence of IDH1/2 /TET2 mutations, along with a significantly lower incidence of DNMT3A mutations in the “APL-like” subset compared to the non-“APL-like” subset. The frequency of Ras-pathway and FLT3 mutations did not differ between these last two groups, nor did their prognoses. Conclusions: Our findings contribute to a comprehensive characterization of NPM1-mutated AML, enhancing diagnostic accuracy and aiding in the detailed classification of the disease. This information may potentially guide targeted therapies or differentiation-based treatment strategies. Full article
(This article belongs to the Special Issue Molecular Research on Acute Myeloid Leukemia (AML) Volume II)
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<p><b>Morphology of peripheral blood (PB) blasts in APL and in “APL-like” NPM1m AML.</b> (<b>A</b>) Peripheral blast of patient with APL, featuring a typical bilobed nucleus with typically overlapping lobes and an inconspicuous Auer rod, as is often the case in APL in PB. (<b>B</b>) Peripheral blasts in “APL-like” (CD34- HLADR-) NPM1-mutated AML case, displaying a prominent Auer rod and a tendency to “cup-like” nuclei. (<b>C</b>) Peripheral blast from another patient with APL, showing a typical bilobed nucleus with typically overlapping lobes and non-readily visible Auer rods. (<b>D</b>) Peripheral blasts in an “APL-like” (CD34- HLADR-) NPM1-mutated AML case, characterized by typical “cup-like” nuclei.</p>
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<p><b>Distribution and differences in DDs/WBC and PT/WBC ratios between APL and “APL-like” NPM1m AML</b> (***: <span class="html-italic">p</span> &lt; 0.001). (<b>A</b>) Box plot of ratios DDs/WBC (mg/L / G/L) in our acute promyelocytic leukemia (APL) cases and “APL-like” NPM1-mutated cases (APL-like NPM1m). Difference is statistically significant between the two groups (<span class="html-italic">p</span> &lt; 0.001, Wilcoxon’s rank-sum test). (<b>B</b>) Box plot of ratios PT/WBC (s/G/L) in our acute promyelocytic leukemia (APL) cases and “APL-like” NPM1-mutated cases. Difference is statistically significant between the two groups (<span class="html-italic">p</span> &lt; 0.001, Wilcoxon’s rank-sum test). (<b>C</b>) DDs/WBC ratios of APL cases shown with black circles, and DDs/WBC ratios of “APL-like” NPM1-mutated cases are shown with red triangles. Cases with ratio &gt; 4.92 (mg/L/G/L) are always APL. (<b>D</b>) PT/WBC ratios of APL cases are shown with black circles, and PT/WBC ratios of “APL-like” NPM1-mutated cases are shown with red triangles. Cases with ratio &gt; 8.54 (s/G/L) are always APL.</p>
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<p><b>Differences in expression of immunophenotypic markers between APL and “APL-like” NPM1m-AML.</b> (<b>A</b>–<b>C</b>) The expression levels of CD117, MPO, and CD38 did not differ significantly between acute promyelocytic leukemia (APL) cases and “acute promyelocytic leukemia-like” NPM1-mutated AML cases (ns: non-significant, **: <span class="html-italic">p</span> &lt; 0.01, ***: <span class="html-italic">p</span> &lt; 0.001). (<b>D</b>–<b>F</b>) Significant differences were observed in the expression of CD4 and CD64 and in SSC values between the two cohorts, with APL cases showing higher CD64 expression and SSC values, and “APL-like” NPM1m AML cases showing higher CD4 expression. Comparisons were made using Wilcoxon’s rank-sum test. It is important to note that “APL-like” NPM1-mutated AML, as immunophenotypically defined in this study (CD34- HLADR-), is “by definition” CD64-negative (CD64-positive NPM1-mutated cases exhibit a monocytic phenotype expressing HLA-DR).</p>
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<p><b>Differences in the proportion of mutated versus wild-type cases for genes <span class="html-italic">IDH1/2/TET2</span>, “Ras-pathway genes”, <span class="html-italic">DNMT3A,</span> and <span class="html-italic">FLT3</span> among “APL-like” and “non-APL-like” NPM1m AML.</b> ns: non-significant, *: <span class="html-italic">p</span> &lt; 0.05, **: <span class="html-italic">p</span> &lt; 0.01. (<b>A</b>) Proportion of <span class="html-italic">IDH1/2/TET2</span>-mutated cases among “APL-like” NPM1m AML and “non-APL-like” NPM1m AML. “APL-like” NPM1m AML exhibits a significantly higher rate of <span class="html-italic">IDH1/2/TET2</span> mutations (chi-square, <span class="html-italic">p</span> = 0.0143). (<b>B</b>) Proportion of Ras-pathway-mutated cases among “APL-like” NPM1m AML and “non-APL-like” NPM1m AML. No significant difference in the frequency of Ras-pathway mutations (chi-square, <span class="html-italic">p</span> = 0.1391) was observed between the two entities. (<b>C</b>) Proportion of DNMT3A-mutated cases among “APL-like” NPM1m AML and “non-APL-like” NPM1m AML. “APL-like” NPM1m-AML shows a significantly lower rate of <span class="html-italic">DNMT3A</span> mutations (chi-square, <span class="html-italic">p</span> = 0.0018). (<b>D</b>) Proportion of FLT3-mutated cases among “APL-like” NPM1m AML and “non-APL-like” NPM1m AML. No significant difference in the frequency of <span class="html-italic">FLT3</span> mutations (chi-square, <span class="html-italic">p</span> = 0.4344) was found between the two entities.</p>
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<p><b>Event-free survival (EFS) and overall survival (OS) of “APL-like” and “non-APL-like” NPM1m AML in our cohorts.</b> (<b>A</b>) Event-free survival: no statistically significant difference was observed between “APL-like” and “non-APL-like” NPM1-mutated AML cases (<span class="html-italic">p</span> = 0.5 log-rank test). (<b>B</b>) Overall survival: no statistically significant difference was observed between “APL-like” and “non-APL-like” NPM1-mutated AML cases (<span class="html-italic">p</span> = 0.7, log-rank test).</p>
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14 pages, 2676 KiB  
Article
Concurrence of Inactivation Enzyme-Encoding Genes tet(X), blaEBR, and estT in Empedobacter Species from Chickens and Surrounding Environments
by Chong Chen, Yilin Lv, Taotao Wu, Jing Liu, Yanan Guo and Jinlin Huang
Foods 2024, 13(19), 3201; https://doi.org/10.3390/foods13193201 - 9 Oct 2024
Viewed by 480
Abstract
The emergence of inactivation enzyme-encoding genes tet(X), blaEBR, and estT challenges the effectiveness of tetracyclines, β-lactams, and macrolides. This study aims to explore the concurrence and polymorphism of their variants in Empedobacter sp. strains from food-producing animals and surrounding environments. [...] Read more.
The emergence of inactivation enzyme-encoding genes tet(X), blaEBR, and estT challenges the effectiveness of tetracyclines, β-lactams, and macrolides. This study aims to explore the concurrence and polymorphism of their variants in Empedobacter sp. strains from food-producing animals and surrounding environments. A total of eight tet(X) variants, seven blaEBR variants, and seven estT variants were detected in tet(X)-positive Empedobacter sp. strains (6.7%) from chickens, sewage, and soil, including 31 Empedobacter stercoris and 6 novel species of Taxon 1. All of them were resistant to tigecycline, tetracycline, colistin, and ciprofloxacin, and 16.2% were resistant to meropenem, florfenicol, and cefotaxime. The MIC90 of tylosin, tilmicosin, and tildipirosin was 128 mg/L, 16 mg/L, and 8 mg/L, respectively. Cloning expression confirmed that tet(X6) and the novel variants tet(X23), tet(X24), tet(X25), tet(X26), and tet(X26.2) conferred high-level tigecycline resistance, while all of the others exhibited relatively low-level activities or were inactivated. The bacterial relationship was diverse, but the genetic environments of tet(X) and blaEBR were more conserved than estT. An ISCR2-mediated tet(X6) transposition structure, homologous to those of Acinetobacter sp., Proteus sp., and Providencia sp., was also identified in Taxon 1. Therefore, the tet(X)-positive Empedobacter sp. strains may be ignored and pose a serious threat to food safety and public health. Full article
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Graphical abstract

Graphical abstract
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<p>Phylogenetic relationship and heatmap of <span class="html-italic">tet</span>(X)-positive <span class="html-italic">Empedobacter</span> sp. isolates. The bacterial strains belonging to <span class="html-italic">E. falsenii</span>, <span class="html-italic">E. stercoris</span>, and Taxon 1 are marked in green, purple, and pink, respectively. Their accession numbers and antibiotic resistance genes (solid circles) are also present. Bar, 0.3 nucleotide substitutions per site.</p>
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<p>Structural characteristics of Tet(X) variants. (<b>A</b>) Multiple sequence alignment of Tet(X) variants. Secondary structure elements of Tet(X2) (2XDO) are present on top, with triangles indicating the reported key amino acid sites. Identical residues are boxed in red. Similar residues in a group or across groups are marked with red characters and blue frames, respectively; (<b>B</b>) homology modelling of Tet(X) variants with Tet(X2) (4A6N). The substrate-binding domain (green), FAD-binding domain (pink), and C-terminal helix (blue) are marked, and the reported key amino acid sites are also displayed.</p>
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<p>Structural characteristics of Tet(X) variants. (<b>A</b>) Multiple sequence alignment of Tet(X) variants. Secondary structure elements of Tet(X2) (2XDO) are present on top, with triangles indicating the reported key amino acid sites. Identical residues are boxed in red. Similar residues in a group or across groups are marked with red characters and blue frames, respectively; (<b>B</b>) homology modelling of Tet(X) variants with Tet(X2) (4A6N). The substrate-binding domain (green), FAD-binding domain (pink), and C-terminal helix (blue) are marked, and the reported key amino acid sites are also displayed.</p>
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<p>Conserved genetic backgrounds of <span class="html-italic">tet</span>(X24), <span class="html-italic">tet</span>(X25), <span class="html-italic">tet</span>(X26), and <span class="html-italic">tet</span>(X26.2) genes in <span class="html-italic">Empedobacter</span> sp. isolates. Regions of &gt;76% nucleotide identity are marked by shading.</p>
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<p>IS<span class="html-italic">CR2</span>-related transposition events across different bacterial species. Regions of &gt;79% nucleotide identity are marked by shading. The Δ symbol indicates that the gene is truncated.</p>
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17 pages, 3157 KiB  
Article
Epigenetic Reprogramming and Inheritance of the Cellular Differentiation Status Following Transient Expression of a Nonfunctional Dominant-Negative Retinoblastoma Mutant in Murine Mesenchymal Stem Cells
by Mikhail Baryshev, Irina Maksimova and Ilona Sasoveca
Int. J. Mol. Sci. 2024, 25(19), 10678; https://doi.org/10.3390/ijms251910678 - 3 Oct 2024
Viewed by 482
Abstract
The retinoblastoma gene product (Rb1), a master regulator of the cell cycle, plays a prominent role in cell differentiation. Previously, by analyzing the differentiation of cells transiently overexpressing the ΔS/N DN Rb1 mutant, we demonstrated that these cells fail to differentiate into mature [...] Read more.
The retinoblastoma gene product (Rb1), a master regulator of the cell cycle, plays a prominent role in cell differentiation. Previously, by analyzing the differentiation of cells transiently overexpressing the ΔS/N DN Rb1 mutant, we demonstrated that these cells fail to differentiate into mature adipocytes and that they constitutively silence Pparγ2 through CpG methylation. Here, we demonstrate that the consequences of the transient expression of ΔS/N DN Rb1 are accompanied by the retention of Cebpa promoter methylation near the TSS under adipogenic differentiation, thereby preventing its expression. The CGIs of the promoters of the Rb1, Ezh2, Mll4, Utx, and Tet2 genes, which are essential for adipogenic differentiation, have an unmethylated status regardless of the cell differentiation state. Moreover, Dnmt3a, a de novo DNA methyltransferase, is overexpressed in undifferentiated ΔS/N cells compared with wild-type cells and, in addition to Dnmt1, Dnmt3a is significantly upregulated by adipogenic stimuli in both wild-type and ΔS/N cells. Notably, the chromatin modifier Ezh2, which is also involved in epigenetic reprogramming, is highly induced in ΔS/N cells. Overall, we demonstrate that two major genes, Pparγ2 and Cebpa, which are responsible for terminal adipocyte differentiation, are selectively epigenetically reprogrammed to constitutively silent states. We hypothesize that the activation of Dnmt3a, Rb1, and Ezh2 observed in ΔS/N cells may be a consequence of a stress response caused by the accumulation and malfunctioning of Rb1-interacting complexes for the epigenetic reprogramming of Pparγ2/Cebpa and prevention of adipogenesis in an inappropriate cellular context. The failure of ΔS/N cells to differentiate and express Pparγ2 and Cebpa in culture following the expression of the DN Rb1 mutant may indicate the creation of epigenetic memory for new reprogrammed epigenetic states of genes. Full article
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<p>The ΔS/N cells with ILYAS amino acid deletion overexpress Rb1 in the undifferentiated state. (<b>a</b>) Schematic diagram representing the structural domains of the Rb1 protein along with the 27 exons of the gene and showing the location of the 6-amino acid deletion in exon 22. (<b>b</b>) Ribbon diagrams of the 3D atomic structure of the RB tumor suppressor bound to the transactivation domain of E2F. Deletion of the ILQYAS amino acid of the alpha helix of the RB1 B pocket domain at positions 768-763 of human RB1 resulted in 761-766 ILQYAS in mice. Adapted from 1n4m PDBe complex ID: PDB-CPX-139032. (<b>c</b>) Real-time PCR demonstrated that the p130 mRNA expression level was not changed in ΔS/N cells. (<b>d</b>) Real-time qPCR revealed that the mRNA expression level of Rb1 was greater in ΔS/N cells than in wild-type cells (n = 3); n, number of biological replicates. The error bars indicate the SEMs. (<b>e</b>) The ATF-2 binding site in the Rb1 promoter contains a CpG. (<b>f</b>) Partial chromatogram of the Rb1 promoter demonstrating that the ATF-2 binding site is not methylated.</p>
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<p>Real-time qPCR revealed that the mRNA expression levels of Dnmt3a and Ezh2 are greater in undifferentiated ΔS/N cells than in wild-type cells (n = 3); n, number of biological replicates. The error bars indicate the SEMs. (<b>a</b>) Comparison of Dnmts expression in differentiated und undifferentiated ΔS/N cells and wild-type cells. (<b>b</b>) Comparison of Ezh2 and Utx expression in differentiated und undifferentiated ΔS/N cells and wild-type cells.</p>
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<p>The hypermethylated promoter of <span class="html-italic">Cebpa</span> retained CG methylation near the TSS in differentiated ΔS/N cells. (<b>a</b>) Gel photograph showing amplification of the proximal region of the <span class="html-italic">Cebpa</span> gene and adipogenic-related gene promoters using bisulfite-treated DNA as a template and a pair of bisulfite-specific primers. (<b>b</b>) Bisulfite sequencing analyses of the <span class="html-italic">Cebpa</span> promoter. The distribution of CpG sites in differentiated and undifferentiated 10T1/2 and ΔS/N cells is shown. At the bottom of the illustrations, the methylation status of the CpGs is shown. (<b>c</b>) Real-time qPCR revealed that the mRNA expression level of <span class="html-italic">Cebpa</span> was lower in both undifferentiated and differentiated ΔS/N cells than in wild-type cells (n = 3); n, number of biological replicates. The error bars indicate the SEMs.</p>
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<p>The putative Nrf1 binding site preserves the methylation of two CG sites of methylation-sensitive Nrf1. (<b>a</b>) The <span class="html-italic">Cebpa</span> promoter region contains the putative Nrf1 binding site. Unerased CG sites detected via <span class="html-italic">Cebpa</span> promoter methylation analysis upon stimulation of adipogenesis in ΔS/N cells are shown as a pictogram. (<b>b</b>) Analysis of a 35-bp region containing an unerased methylated CpG located downstream of the TSS using the UCSC Genome Browser transcription factor binding search tool in mice (GRCm39/mm39). (<b>c</b>) JASPAR NRF1 profile summary, Matrix ID MA0506.1.</p>
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<p>The unerased CpG methylation observed in the <span class="html-italic">Cebpa</span> promoter upstream of the TSS may represent a target for methylation-dependent Cebpg/b transcription factors. (<b>a</b>) Analysis of a 35-bp region containing an unerased methylated CpG located upstream of the TSS using the UCSC Genome Browser transcription factor binding search tool in mice (GRCm39/mm39). (<b>b</b>) JASPAR CEBPG/B profile summary, Matrix ID MA0838.1/MA0466.2.</p>
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<p>Bisulfite sequencing analyses of the <span class="html-italic">Pparγ2</span> promoter. The distribution of CpG sites in differentiated and undifferentiated 10T1/2 and ΔS/N cells is shown. At the bottom of the illustrations, the methylation status of the CpGs is shown.</p>
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20 pages, 908 KiB  
Review
Histone Deacetylase Inhibitors for Peripheral T-Cell Lymphomas
by Ruxandra Irimia and Pier Paolo Piccaluga
Cancers 2024, 16(19), 3359; https://doi.org/10.3390/cancers16193359 - 30 Sep 2024
Viewed by 420
Abstract
Histone deacetylase inhibitors (HDACis) are being recognized as a potentially effective treatment approach for peripheral T-cell lymphomas (PTCLs), a heterogeneous group of aggressive malignancies with an unfavorable prognosis. Recent evidence has shown that HDACis are effective in treating PTCL, especially in cases where [...] Read more.
Histone deacetylase inhibitors (HDACis) are being recognized as a potentially effective treatment approach for peripheral T-cell lymphomas (PTCLs), a heterogeneous group of aggressive malignancies with an unfavorable prognosis. Recent evidence has shown that HDACis are effective in treating PTCL, especially in cases where the disease has relapsed or is resistant to conventional treatments. Several clinical trials have demonstrated that HDACis, such as romidepsin and belinostat, can elicit long-lasting positive outcomes in individuals with PTCLs, either when used alone or in conjunction with conventional chemotherapy. They exert their anti-tumor effects by regulating gene expression through the inhibition of histone deacetylases, which leads to cell cycle arrest, induction of programmed cell death, and,the transformation of cancerous T cells, as demonstrated by gene expression profile studies. Importantly, besides clinical trials, real-world evidence indicated that the utilization of HDACis presents a significant and beneficial treatment choice for PTCLs. However, although HDACis showed potential effectiveness, they could not cure most patients. Therefore, new combinations with conventional drugs as well as new targeted agents are under investigation. Full article
(This article belongs to the Special Issue Novel Targeted Therapies for T-cell Malignancies)
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<p>The histone or non-histone substrates and the integrated biological effects of HDACs. The acetylation of histone substrates modulates the chromatin structure to reduce the accessibility to transcriptional regulatory proteins and subsequent gene expression. For non-histone substrates, HDACs have an impact on their activity by acetylating. In general, HDACs contribute to proliferative effects (Adapted from Lu et al. [<a href="#B14-cancers-16-03359" class="html-bibr">14</a>]).</p>
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19 pages, 1474 KiB  
Article
Molecular Characterization of MDR and XDR Clinical Strains from a Tertiary Care Center in North India by Whole Genome Sequence Analysis
by Uzma Tayyaba, Shariq Wadood Khan, Asfia Sultan, Fatima Khan, Anees Akhtar, Geetha Nagaraj, Shariq Ahmed and Bhaswati Bhattacharya
J. Oman Med. Assoc. 2024, 1(1), 29-47; https://doi.org/10.3390/joma1010005 - 24 Sep 2024
Viewed by 374
Abstract
Whole genome sequencing (WGS) has the potential to greatly enhance AMR (Anti-microbial Resistance) surveillance. To characterize the prevalent pathogens and dissemination of various AMR-genes, 73 clinical isolates were obtained from blood and respiratory tract specimens, were characterized phenotypically by VITEK-2 (bioMerieux), and 23 [...] Read more.
Whole genome sequencing (WGS) has the potential to greatly enhance AMR (Anti-microbial Resistance) surveillance. To characterize the prevalent pathogens and dissemination of various AMR-genes, 73 clinical isolates were obtained from blood and respiratory tract specimens, were characterized phenotypically by VITEK-2 (bioMerieux), and 23 selected isolates were genotypically characterized by WGS (Illumina). AST revealed high levels of resistance with 50.7% XDR, 32.9% MDR, and 16.4% non-MDR phenotype. A total of 11 K. pneumoniae revealed six sequence types, six K-locus, and four O-locus types, with ST437, KL36, and O4 being predominant types, respectively. They carried ESBL genes CTX-M-15 (90.9%), TEM-1D (72.7%), SHV-11 (54.5%), SHV-1, SHV-28, OXA-1, FONA-5, and SFO-1; NDM-5 (72.7%) and 63.6%OXA48-like carbapenamases; 90.9%OMP mutation; dfrA12, sul-1, ermB, mphA, qnrB1, gyrA831, and pmrB1 for other groups. Virulence gene found were Yerisiniabactin (90.9%), aerobactin, RmpADC, and rmpA2. Predominant plasmid replicons were Col(pHAD28), IncFII, IncFIB(pQil), and Col440. A total of seven XDR A. baumannii showed single MLST type(2) and single O-locus type(OCL-1); with multiple AMR-genes: blaADC-73, blaOXA-66, blaOXA-23, blaNDM-1, gyrA, mphE, msrE, and tetB. Both S. aureus tested were found to be ST22, SCCmec IVa(2B), and spa type t309; multiple AMR-genes: blaZ, mecA, dfrC, ermC, and aacA-aphD. Non-MDR Enterococcus faecalis sequenced was ST 946, with multiple virulence genes. This study documents for the first-time prevalent virulence genes and MLST types, along with resistance genes circulating in our center. Full article
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<p>Distribution of bacterial isolates in different samples.</p>
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<p>Bacterial species isolated from clinical samples.</p>
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<p>Distribution of AMR phenotypes in clinical isolates.</p>
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<p>MDR, XDR, and non-MDR distribution in different bacterial isolates.</p>
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12 pages, 2159 KiB  
Article
Genomic Landscape of Myelodysplastic/Myeloproliferative Neoplasms: A Multi-Central Study
by Fei Fei, Amar Jariwala, Sheeja Pullarkat, Eric Loo, Yan Liu, Parastou Tizro, Haris Ali, Salman Otoukesh, Idoroenyi Amanam, Andrew Artz, Feras Ally, Milhan Telatar, Ryotaro Nakamura, Guido Marcucci and Michelle Afkhami
Int. J. Mol. Sci. 2024, 25(18), 10214; https://doi.org/10.3390/ijms251810214 - 23 Sep 2024
Viewed by 647
Abstract
The accurate diagnosis and classification of myelodysplastic/myeloproliferative neoplasm (MDS/MPN) are challenging due to the overlapping pathological and molecular features of myelodysplastic syndrome (MDS) and myeloproliferative neoplasm (MPN). We investigated the genomic landscape in different MDS/MPN subtypes, including chronic myelomonocytic leukemia (CMML; n = [...] Read more.
The accurate diagnosis and classification of myelodysplastic/myeloproliferative neoplasm (MDS/MPN) are challenging due to the overlapping pathological and molecular features of myelodysplastic syndrome (MDS) and myeloproliferative neoplasm (MPN). We investigated the genomic landscape in different MDS/MPN subtypes, including chronic myelomonocytic leukemia (CMML; n = 97), atypical chronic myeloid leukemia (aCML; n = 8), MDS/MPN-unclassified (MDS/MPN-U; n = 44), and MDS/MPN with ring sideroblasts and thrombocytosis (MDS/MPN-RS-T; n = 12). Our study indicated that MDS/MPN is characterized by mutations commonly identified in myeloid neoplasms, with TET2 (52%) being the most frequently mutated gene, followed by ASXL1 (38.7%), SRSF2 (34.7%), and JAK2 (19.7%), among others. However, the distribution of recurrent mutations differs across the MDS/MPN subtypes. We confirmed that specific gene combinations correlate with specific MDS/MPN subtypes (e.g., TET2/SRSF2 in CMML, ASXL1/SETBP1 in aCML, and SF3B1/JAK2 in MDS/MPN-RS-T), with MDS/MPN-U being the most heterogeneous. Furthermore, we found that older age (≥65 years) and mutations in RUNX1 and TP53 were associated with poorer clinical outcomes in CMML (p < 0.05) by multivariate analysis. In MDS/MPN-U, CBL mutations (p < 0.05) were the sole negative prognostic factors identified in our study by multivariate analysis (p < 0.05). Overall, our study provides genetic insights into various MDS/MPN subtypes, which may aid in diagnosis and clinical decision-making for patients with MDS/MPN. Full article
(This article belongs to the Section Molecular Pathology, Diagnostics, and Therapeutics)
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<p>The workflow and study design of our cohort. BM, bone marrow; PB, peripheral blood. (Abbreviations: aCML, atypical myeloid leukemia; AML, acute myeloid leukemia; CMML, chronic myelomonocytic leukemia; MDS/MPN-U, myelodysplastic/myeloproliferative neoplasm-unclassified; and MDS/MPN-RS-T, myelodysplastic/myeloproliferative neoplasm with ring sideroblasts and thrombocytosis.)</p>
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<p>Frequency of recurrent gene mutations in all myelodysplastic/myeloproliferative neoplasm (MDS/MPN) patients (n = 173).</p>
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<p>Molecular and cytogenetic characteristics among the different MDS/MPN subtypes (n = 173). An oncoplot showing the mutated genes among the different MDS/MPN subtypes. Each column represents a patient. Thirty-one genes are grouped into eight categories based on their functions: DNA methylation, chromatin modification, RNA splicing, transcription factors, receptor kinases, cohesion, RAS pathways, and others. Green depicts the different MDS/MPN subtypes: CMML, CMML-AML, aCML, MDS/MPN-U, and MDS/MPN-RS-T. Red depicts a single gene mutation; purple depicts more than one mutation in the same gene, mainly corresponding to biallelic <span class="html-italic">TET2</span> mutations. Cytogenetic findings are divided into three groups: normal karyotype, abnormal karyotype, and complex karyotype. Myelofibrosis (MF) status is divided into five groups: MF 0, MF 1, MF 2, MF 3, and N/A. The frequency of recurrent gene mutations among the different MDS/MPN subtypes. (Abbreviations: aCML, atypical myeloid leukemia; AML, acute myeloid leukemia; CMML, chronic myelomonocytic leukemia; MDS/MPN-U, myelodysplastic/myeloproliferative neoplasm-unclassified; MDS/MPN-RS-T, myelodysplastic/myeloproliferative neoplasm with ring sideroblasts and thrombocytosis; MF, myelofibrosis; and N/A, not applicable.)</p>
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<p>Frequency of mutations based on functional classification among different MDS/MPN subtypes. (<b>A</b>) CMML (n = 97); (<b>B</b>) CMML-AML (n = 12); (<b>C</b>) aCML (n = 8); (<b>D</b>) MDS/MPN-U (n = 44); and (<b>E</b>) MDS/MPN-RS-T (n = 12). (Abbreviations: aCML, atypical myeloid leukemia; AML, acute myeloid leukemia; CMML, chronic myelomonocytic leukemia; MDS/MPN-U, myelodysplastic/myeloproliferative neoplasm-unclassified; and MDS/MPN-RS-T, myelodysplastic/myeloproliferative neoplasm with ring sideroblasts and thrombocytosis).</p>
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10 pages, 1617 KiB  
Article
Prevalence and Characteristics of Plasmid-Mediated Fosfomycin Resistance Gene fosA3 among Salmonella Enteritidis Isolates from Retail Chickens and Children with Gastroenteritis in China
by Liyuan Liu, Shanrong Yi, Xuebin Xu, Liya Zheng, Hong Liu and Xiujuan Zhou
Pathogens 2024, 13(9), 816; https://doi.org/10.3390/pathogens13090816 - 21 Sep 2024
Viewed by 642
Abstract
A total of 265 Salmonella Enteritidis isolates collected from retail markets and children’s hospitals in Shanghai were used to investigate the prevalence and molecular epidemiology of plasmid-mediated fosfomycin resistance genes. Nine of the isolates—7 from the 146 (4.79%) retail chicken-related samples and 2 [...] Read more.
A total of 265 Salmonella Enteritidis isolates collected from retail markets and children’s hospitals in Shanghai were used to investigate the prevalence and molecular epidemiology of plasmid-mediated fosfomycin resistance genes. Nine of the isolates—7 from the 146 (4.79%) retail chicken-related samples and 2 from the 119 (1.68%) samples from clinical children—were fosfomycin-resistant (FosR). The fosA3 gene was detected in all of the nine FosR isolates, which were located on Inc F-type (8/9, 88.9%) and unknown-type (1/9, 11.1%) transferable plasmids. In total, five plasmid types, namely Inc HI2 (1/9, 11.1%), Inc I1 (3/9, 33.3%), Inc X (8/9, 88.9%), Inc FIIs (9/9, 100%), and Inc FIB (9/9, 100%), were detected in these FosR isolates, which possessed five S1 nuclease pulsed-field gel electrophoresis (S1-PFGE) profiles. The extended-spectrum β-lactamase determinant blaCTX-M-14 subtype was identified in one FosR S. Enteritidis isolate, which was located in a transferable unknown-type plasmid co-carrying fosA3 and tetR genes. Sequence homology analysis showed that this plasmid possessed high sequence similarity to previously reported blaCTX-M-14- and fosA3-positive plasmids from E. coli strains, implying that plasmids carrying the fosA3 gene might be disseminated among Enterobacterales. These findings highlight further challenges in the prevention and treatment of Enterobacteriaceae infections caused by plasmids containing fosA3. Full article
(This article belongs to the Special Issue Detection and Epidemiology of Drug-Resistant Bacteria)
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<p>S1 nuclease pulsed-field gel electrophoresis of FosR <span class="html-italic">S.</span> Enteritidis donors (1–5) and corresponding <span class="html-italic">E. coli</span> trans-conjugants (1′–5′). M: H9812; 1: SJTUF 10993 and SJTUF 10994; 2: SJTUF 10959 and SJTUF 10960; 3: SJTUF 11346; 4: SJTUF 11561; 5: SJTUF 11565, SJTUF 11642, and SJTUF 11653; 1′: trans-conjugants of SJTUF 10993 and SJTUF 10994; 2′: trans-conjugants of SJTUF 10959 and SJTUF 10960; 3′: trans-conjugants of SJTUF 11346; 4′: trans-conjugant of SJTUF 11561; and 5′: trans-conjugants of SJTUF 11565, SJTUF 11642, and SJTUF 11653.</p>
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<p>Genetic environment comparison of <span class="html-italic">fosA3</span> and <span class="html-italic">bla</span><sub>CTX-M-14</sub> genes in plasmids p11561A (this study), pC0121T (JX442753), and pN0863T (JQ823170). Gray shading indicates shared regions with a high degree of homology. Genes are represented by arrows and colored depending on gene function as depicted: red, antimicrobial resistance; yellow, mobile element; white, hypothetical protein; and gray, other protein (or genes).</p>
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32 pages, 6288 KiB  
Review
A Decade of Antimicrobial Resistance in Human and Animal Campylobacter spp. Isolates
by Rita Barata, Maria José Saavedra and Gonçalo Almeida
Antibiotics 2024, 13(9), 904; https://doi.org/10.3390/antibiotics13090904 - 21 Sep 2024
Viewed by 1683
Abstract
Objectives: Campylobacter spp. remain a leading cause of bacterial gastroenteritis worldwide, with resistance to antibiotics posing significant challenges to treatment and public health. This study examines profiles in antimicrobial resistance (AMR) for Campylobacter isolates from human and animal sources over the past [...] Read more.
Objectives: Campylobacter spp. remain a leading cause of bacterial gastroenteritis worldwide, with resistance to antibiotics posing significant challenges to treatment and public health. This study examines profiles in antimicrobial resistance (AMR) for Campylobacter isolates from human and animal sources over the past decade. Methods: We conducted a comprehensive review of resistance data from studies spanning ten years, analyzing profiles in resistance to key antibiotics, ciprofloxacin (CIP), tetracycline (TET), erythromycin (ERY), chloramphenicol (CHL), and gentamicin (GEN). Data were collated from various regions to assess global and regional patterns of resistance. Results: The analysis reveals a concerning trend of increasing resistance patterns, particularly to CIP and TET, across multiple regions. While resistance to CHL and GEN remains relatively low, the high prevalence of CIP resistance has significantly compromised treatment options for campylobacteriosis. Discrepancies in resistance patterns were observed between human and animal isolates, with variations across different continents and countries. Notably, resistance to ERY and CHL showed regional variability, reflecting potential differences in antimicrobial usage and management practices. Conclusions: The findings underscore the ongoing challenge of AMR in Campylobacter, highlighting the need for continued surveillance and research. The rising resistance prevalence, coupled with discrepancies in resistance patterns between human and animal isolates, emphasize the importance of a One Health approach to address AMR. Enhanced monitoring, novel treatment strategies, and global cooperation are crucial for mitigating the impact of resistance and ensuring the effective management of Campylobacter-related infections. Full article
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<p>Distribution of studies on human isolates of <span class="html-italic">Campylobacter</span> spp. by world region, methodologies used, and species identified.</p>
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<p>Distribution of studies on animal isolates (%) of <span class="html-italic">Campylobacter</span> spp. by world region, methodologies used, and species identified.</p>
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<p>Distribution of animal isolates (%) of <span class="html-italic">Campylobacter</span> spp. by animal type and species identified.</p>
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<p>Antibiotic resistance patterns of <span class="html-italic">Campylobacter</span> spp. isolates from human and animal data from Africa.</p>
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<p>(<b>A</b>) Antibiotic resistance patterns of <span class="html-italic">Campylobacter</span> spp. Isolates from humans from Africa between 2012 and 2022. (<b>B</b>) Antibiotic resistance patterns of <span class="html-italic">Campylobacter</span> spp. Isolates from animals from Africa between 2012 and 2022.</p>
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<p>Antibiotic resistance patterns of <span class="html-italic">Campylobacter</span> spp. isolates from human and animal data from Asia.</p>
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<p>(<b>A</b>) Antibiotic resistance patterns of <span class="html-italic">Campylobacter</span> spp. isolates from humans from Asia between 2012 and 2022. (<b>B</b>) Antibiotic resistance patterns of <span class="html-italic">Campylobacter</span> spp. isolates from animals from Asia between 2012 and 2022.</p>
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<p>Antibiotic resistance patterns of <span class="html-italic">Campylobacter</span> spp. isolates from human and animal data from Europe.</p>
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<p>(<b>A</b>) Antibiotic resistance patterns of <span class="html-italic">Campylobacter</span> spp. isolates from humans from Europe between 2012 and 2022. (<b>B</b>) Antibiotic resistance patterns of <span class="html-italic">Campylobacter</span> spp. isolates from animals from Europe between 2012 and 2022.</p>
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<p>Antibiotic resistance patterns of <span class="html-italic">Campylobacter</span> spp. isolates from human and animal data from North and Central America.</p>
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<p>(<b>A</b>) Antibiotic resistance patterns of <span class="html-italic">Campylobacter</span> spp. isolates from humans from North and Central America between 2012 and 2022. (<b>B</b>) Antibiotic resistance patterns of <span class="html-italic">Campylobacter</span> spp. isolates from animals from North and Central America between 2012 and 2022.</p>
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<p>Antibiotic resistance patterns of <span class="html-italic">Campylobacter</span> spp. isolates from South America.</p>
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<p>(<b>A</b>) Antibiotic resistance patterns of <span class="html-italic">Campylobacter</span> spp. isolates from humans from South America between 2012 and 2022. (<b>B</b>) Antibiotic resistance patterns of <span class="html-italic">Campylobacter</span> spp. isolates from animals from South America between 2012 and 2022.</p>
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<p>(<b>A</b>) Antibiotic resistance patterns of <span class="html-italic">Campylobacter</span> spp. isolates from humans from Oceania between 2012 and 2022. (<b>B</b>) Antibiotic resistance patterns of <span class="html-italic">Campylobacter</span> spp. isolates from animals from Oceania between 2012 and 2022.</p>
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