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21 pages, 5894 KiB  
Article
Modulation of Stress-Related Protein in the African Catfish (Clarias gariepinus) Using Bacillus-Based Non-Ribosomal Peptides
by Alexey Mikhailovich Neurov, Anna Andreevna Zaikina, Evgeniya Valer’evna Prazdnova, Ranjan Anuj and Dmitriy Vladimirovich Rudoy
Microbiol. Res. 2024, 15(4), 2743-2763; https://doi.org/10.3390/microbiolres15040182 - 22 Dec 2024
Viewed by 293
Abstract
Probiotics, due to their multifaceted benefits to the host, are essential in medicine, agriculture, and aquaculture. The mechanisms of their action at the molecular level are complex and less explored. Both previous research and our own investigations have highlighted that incorporating probiotics into [...] Read more.
Probiotics, due to their multifaceted benefits to the host, are essential in medicine, agriculture, and aquaculture. The mechanisms of their action at the molecular level are complex and less explored. Both previous research and our own investigations have highlighted that incorporating probiotics into the feed of commercial fish can increase growth and influence the expression of genes related to stress and immunity. Additionally, probiotics with antioxidant properties often exert systemic effects. The aim of this work was to explore possible mechanisms of probiotic effects on stress-related proteins in African catfish C. gariepinus using molecular docking and dynamics approaches. Stress biomarker proteins such as catalase, cytochrome P450, HSP70, metallothionein 1, and superoxide dismutase were evaluated for possible interactions with bioactive non-ribosomal peptides (NRPs) from Bacillus subtilis R5, used as ligands. The study involved molecular docking and dynamics interactions between proteins and NRPs. The results of molecular docking and dynamics reveal multiple bindings between proteins and ligands, forming stable complexes, which may explain the mechanisms of action of probiotics and their particularly positive effects, such as the reduction in stress levels, which was demonstrated in the clarium catfish model in our previous work. Non-ribosomal peptides synthesized by probiotics may influence key signalling pathways underlying antioxidant and antimutagenic properties. Full article
(This article belongs to the Special Issue Bioactive Secondary Metabolites of Microbial Symbionts)
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Figure 1
<p>Interaction of catalase with bacillomycin: (<b>a</b>) complex, (<b>b</b>) three-dimensional view, (<b>c</b>) two-dimensional view. ALA8, MET12, SER120, and PHE326 are key residues involved in the stabilization of the ligand–receptor complex.</p>
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<p>Interaction of HSP70 with bacillomycin: (<b>a</b>) complex, (<b>b</b>) three-dimensional view, (<b>c</b>) two-dimensional view. VAL61, HIS91, ASN237, and ARG263 are key residues involved in the stabilization of the ligand–receptor complex.</p>
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<p>Three- and two-dimensional interactions of bacillomycin with (<b>a</b>) MT1, (<b>b</b>) SOD, and (<b>c</b>) cytochrome P450.</p>
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<p>Interaction of cytochrome P450 with fengycin: (<b>a</b>) complex, (<b>b</b>) three-dimensional view, (<b>c</b>) two-dimensional view. GLN11 LEU262, TYR266, TYR325 and PHE326 are key residues involved in the stabilization of the ligand–receptor complex.</p>
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<p>Interaction of catalase with fengycin: (<b>a</b>) complex, (<b>b</b>) three-dimensional view, (<b>c</b>) two-dimensional view. GLN11 LEU262, TYR266, TYR325, and PHE326 are key residues involved in the stabilization of the ligand–receptor complex.</p>
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<p>Three- and two-dimensional interactions of fengycin with (<b>a</b>) MT1, (<b>b</b>) SOD, and (<b>c</b>) HSP70.</p>
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<p>Interaction of cytochrome P450 with surfactin: (<b>a</b>) complex, (<b>b</b>) three-dimensional view, (<b>c</b>) two-dimensional view. LEU25, SER50, and PRO54 are key residues involved in the stabilization of the ligand–receptor complex.</p>
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<p>Interaction of catalase with surfactin: (<b>a</b>) complex, (<b>b</b>) three-dimensional view, (<b>c</b>) two-dimensional view. ALA8, GLU67, LEU262, TYR266, and PHE326 are key residues involved in the stabilization of the ligand–receptor complex.</p>
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<p>Three- and two-dimensional interactions of surfactin with (<b>a</b>) MT1, (<b>b</b>) SOD, and (<b>c</b>) HSP70. MT1 and SOD have been shown to have the most stable interactions with NRPs.</p>
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<p>(<b>a</b>) RMSD results for the catalase complex with bacillomycin. The RMSD plot shows an initial peak in the first few nanoseconds, reflecting the equilibrium when the system adapts, after which the protein and ligand stabilize, with oscillations indicating dynamic interactions, and differences in the curves indicate conformational changes in the protein under the influence of ligand binding. Number of interactions for the catalase complex with bacillomycin. (<b>b</b>) Two-dimensional diagram of interacting atoms of the catalase complex with bacillomycin. The following amino acids showed the longest interaction time: ASP259—95% NH, 98% OH, 44% H<sub>2</sub>O; TYR325—91% O; VAL323 81% NH; PRO322—74%; ASN321—67% OH.</p>
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<p>Number of interactions for the catalase complex with bacillomycin. The ligand to protein has 7 very stable bonds and 5 partially stable ones.</p>
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<p>(<b>a</b>) RMSD results for HSP70 complex with bacillomycin. RMSD and protein–ligand contact plots reveal an initial equilibrium phase followed by protein and ligand stabilization, with fluctuations indicating dynamic interactions and conformational changes caused by ligand binding. (<b>b</b>) Two-dimensional diagram of interacting atoms of HSP70 complex with bacillomycin. HIS91 showed the longest interaction time—86% NH. ARG74—52%. OH and LYS90—32%. NH ha d a prolonged interaction.</p>
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<p>Number of interactions for HSP70 complex with bacillomycin. The ligand to protein has 6 permanent bonds and 3 partially stable ones.</p>
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<p>(<b>a</b>) RMSD results for cytochrome P450 complex with fengycin. The RMSD and protein–ligand contact plots reveal that the system initially fluctuates before settling into equilibrium by 50 nanoseconds, with the protein and ligand reaching stability between 50 and 200 nanoseconds. (<b>b</b>) 2D diagram of interacting atoms of cytochrome P450 complex with fengycin. GLU232 showed the longest interaction time—84% NH3. SER63—63% O; ASP233—53% NH3; ASP51—38% O; PHE223—37% Pi–Pi stacking, which has a prolonged interaction.</p>
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<p>Number of interactions for cytochrome P450 complex with fengycin. The ligand to protein has 4 permanent bonds and 4 partially stable ones.</p>
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<p>(<b>a</b>) RMSD results for the catalase complex with fengycin. The RMSD and protein–ligand contacts plots illustrate the equilibration of the system, the stabilization of the protein and ligand, and the dynamic nature of protein–ligand interactions, with an initial RMSD spike indicating equilibration, followed by stabilization and fluctuations, suggesting conformational changes induced by ligand binding. (<b>b</b>) Two-dimensional diagram of interacting atoms of cytochrome P450 complex with fengycin. ASP263 showed the longest interaction time—94% NH3. LYS38—71% and 44% H<sub>2</sub>O, ARG263—49% H<sub>2</sub>O, and GLN11—34% H<sub>2</sub>O has a prolonged interaction.</p>
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<p>Number of interactions for the catalase complex with fengycin. The ligand to protein has 6 permanent bonds and 3 partially stable ones.</p>
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22 pages, 4731 KiB  
Article
Characterization and Molecular Insights of a Chromium-Reducing Bacterium Bacillus tropicus
by Shanjana Rahman Tuli, Md. Firoz Ali, Tabassum Binte Jamal, Md. Abu Sayem Khan, Nigar Fatima, Irfan Ahmed, Masuma Khatun and Shamima Akhtar Sharmin
Microorganisms 2024, 12(12), 2633; https://doi.org/10.3390/microorganisms12122633 - 19 Dec 2024
Viewed by 1008
Abstract
Environmental pollution from metal toxicity is a widespread concern. Certain bacteria hold promise for bioremediation via the conversion of toxic chromium compounds into less harmful forms, promoting environmental cleanup. In this study, we report the isolation and detailed characterization of a highly chromium-tolerant [...] Read more.
Environmental pollution from metal toxicity is a widespread concern. Certain bacteria hold promise for bioremediation via the conversion of toxic chromium compounds into less harmful forms, promoting environmental cleanup. In this study, we report the isolation and detailed characterization of a highly chromium-tolerant bacterium, Bacillus tropicus CRB14. The isolate is capable of growing on 5000 mg/L Cr (VI) in an LB (Luria Bertani) agar plate while on 900 mg/L Cr (VI) in LB broth. It shows an 86.57% reduction ability in 96 h of culture. It can also tolerate high levels of As, Cd, Co, Fe, Zn, and Pb. The isolate also shows plant growth-promoting potential as demonstrated by a significant activity of nitrogen fixation, phosphate solubilization, IAA (indole acetic acid), and siderophore production. Whole-genome sequencing revealed that the isolate lacks Cr resistance genes in their plasmids and are located on its chromosome. The presence of the chrA gene points towards Cr(VI) transport, while the absence of ycnD suggests alternative reduction pathways. The genome harbors features like genomic islands and CRISPR-Cas systems, potentially aiding adaptation and defense. Analysis suggests robust metabolic pathways, potentially involved in Cr detoxification. Notably, genes for siderophore and NRP-metallophore production were identified. Whole-genome sequencing data also provides the basis for molecular validation of various genes. Findings from this study highlight the potential application of Bacillus tropicus CRB14 for bioremediation while plant growth promotion can be utilized as an added benefit. Full article
(This article belongs to the Special Issue Biotechnology for Environmental Remediation)
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<p>Graphical representation of the complete workflow for characterizing the chromium-reducing bacterium CRB14, starting with bacterial isolation, growth tolerance, and PGP analyses, and progressing through genome sequencing, functional annotation, and comparative analysis.</p>
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<p>Bar plot depicting the growth of isolate CRB14 at different concentrations of Cr. The cells were cultured on LB broth supplemented with 25, 50, 100 and 200, 300, 400, 500, 600, 700, 800, 900 mg/L Cr (VI). The optical density was measured after incubation for 24 h, 48 h, 72 h, and 96 h at 35 °C.</p>
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<p>Reduction in Cr (VI) by isolate CRB14. The cells were cultured in Luria Bertani broth supplemented with 0, 25, 50, 100, 200, 300, 400, 500, 600, 700, 800, and 900 mg/L Cr (VI). The Cr (VI) reduction activity was measured after incubation for 24 h, 48 h, 72 h, and 96 h at 35 °C.</p>
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<p>Bar plot representing the growth of isolate CRB14 in the presence of various heavy metals.</p>
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<p>Nuclear genome circle diagram of CRB14. From outside to inside, coding genes (positive-sense strand), coding genes (negative-sense strand), tRNA (blue) and rRNA (orange), tmRNA (black), CRISPR (green), Cas cluster (cyan), and GC ratio and GC-skew.</p>
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<p>A maximum-likelihood phylogenetic tree based on 16S rRNA gene sequences of <span class="html-italic">Bacillus tropicus</span> CRB14 and other closely related strains. The isolate of interest is highlighted in red.</p>
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<p>COG classifications of the genome. Each bar corresponds to a specific classification, highlighting these proteins’ diverse roles in metabolism and physiological processes. The abscissa represents the various COG categories, while the ordinate shows the number of genes assigned to each category.</p>
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<p>KEGG classification of the predicted coding sequences. The x-axis denotes the various pathways, and the y-axis indicates the number of genes assigned to each pathway. The bars are color coded according to the six major pathway classes, indicating that the majority of genes are involved in metabolism.</p>
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<p>GO functional classification of CRB14. The x-axis shows the GO categories, and the y-axis represents the −log10 (<span class="html-italic">p</span>-value) for the top 10 terms in biological process (blue), cellular component (yellow), and molecular function (green).</p>
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<p>Schematic diagram of nine secondary metabolite biosynthetic gene clusters in <span class="html-italic">B. tropicus</span> CRB14. Potential secondary metabolite biosynthetic gene clusters were predicted using antiSMASH. Color-coded blocks indicate different gene functions: dark red for core biosynthetic genes, light red for additional biosynthetic genes, blue for transport-related genes, green for regulatory genes, and gray for other genes.</p>
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16 pages, 3460 KiB  
Article
Genome-Wide Structural Variation Analysis and Breed Comparison of Local Domestic Ducks in Shandong Province, China
by Pengwei Ren, Meixia Zhang, Muhammad Zahoor Khan, Liu Yang, Yadi Jing, Xiang Liu, Xiaohui Yang, Chaoran Zhang, Min Zhang, Zhiming Zhu, Nenzhu Zheng, Lujiao Zhang, Shuer Zhang and Mingxia Zhu
Animals 2024, 14(24), 3657; https://doi.org/10.3390/ani14243657 - 18 Dec 2024
Viewed by 343
Abstract
Structural variations in the duck genome significantly impact the environmental adaptability and phenotypic diversity of duck populations. Characterizing these SVs in local domestic duck breeds from Shandong province offers valuable insights for breed selection and the development of new breeds. This study aimed [...] Read more.
Structural variations in the duck genome significantly impact the environmental adaptability and phenotypic diversity of duck populations. Characterizing these SVs in local domestic duck breeds from Shandong province offers valuable insights for breed selection and the development of new breeds. This study aimed to profile the genomic SVs in three local duck breeds (Matahu duck, Weishan partridge duck, and Wendeng black duck) and explore their differential distributions. A total of 21,673 SVs were detected using LUMPY (v0.2.13) and DELLY (v1.0.3) software, with 46% located in intergenic regions, 33% in intronic regions, and frameshift deletions being the most prevalent in exonic regions (3%). SVs distribution showed a decreasing trend with shorter chromosome lengths. Population structure analysis revealed distinct genetic profiles, with Matahu and Weishan partridge ducks showing closer affinities and the Wendeng black duck having a more homogeneous genetic background, likely due to geographic isolation. Functional annotation identified genes related to nervous system development, mitosis, spindle assembly, and energy metabolism. Notable genes included PLXNA4, NRP2, SEMA3A, PTEN, MYBL2, ADK, and COX4I1. Additionally, genes such as PRKG1, GABRA2, and FSHR were linked to energy metabolism and reproductive activity. The study provides a comprehensive analysis of SVs, revealing significant genetic differentiation and identifying genes associated with economically important traits, offering valuable resources for the genetic improvement and breeding of local duck breeds. Full article
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<p>Morphological and external characteristics of local varieties in Shandong Province: (<b>a</b>) Weishan partridge duck; (<b>b</b>) Matahu duck; (<b>c</b>) Wendeng black duck (the left male and the right female).</p>
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<p>Identification of SVs in local domestic duck breeds in Shandong: (<b>a</b>) number distribution of SVs on chromosomes; (<b>b</b>) distribution of SV numbers in different groups; (<b>c</b>) position distribution of SVs on the genome.</p>
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<p>Population structure analysis of three local domestic duck breeds: (<b>a</b>) principal component analysis; (<b>b</b>) neighbor-joining tree; (<b>c</b>) population differentiation indices; (<b>d</b>) population structure analysis. K: number of subgroups of the population.</p>
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<p>Differential subject to selection analysis among different subgroups of Shandong local domestic duck breeds: (<b>a</b>) Manhattan plot on the analysis of Fst method; (<b>b</b>) distribution of the number of GO terms in different subgroups; (<b>c</b>) shared number of genes related to the development of the nervous system in different subgroups. BP: biological process; CC: cellular component; molecular function.</p>
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<p>Functional enrichment analysis of genes in different subgroups: (<b>a</b>) GO enrichment analysis in the subgroups of MT and WD; (<b>b</b>) GO enrichment analysis in the subgroups of MT and WS; (<b>c</b>) GO enrichment analysis in the subgroups of WD and WS; (<b>d</b>) KEGG enrichment analysis in the subgroups of MT and WD, MT and WS, and WD and WS.</p>
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<p>Protein interaction network (PPI) of genes related to nervous system development, mitosis and spindle assembly, and energy metabolism.</p>
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12 pages, 965 KiB  
Article
Comparing Long-Term Outcomes in Glomerular Disease Patients Presenting with Nephrotic Syndrome Versus Nephrotic Range Proteinuria
by Gabriel Ștefan, Simona Stancu, Adrian Zugravu and Nicoleta Petre
Life 2024, 14(12), 1674; https://doi.org/10.3390/life14121674 - 18 Dec 2024
Viewed by 390
Abstract
Background: Despite extensive research on proteinuria’s impact on chronic kidney disease progression, there is no direct comparison of outcomes in biopsy-diagnosed glomerular disease (GD) patients with nephrotic syndrome (NS) or nephrotic range proteinuria (NRP). Our study addresses this gap, comparing long-term outcomes between [...] Read more.
Background: Despite extensive research on proteinuria’s impact on chronic kidney disease progression, there is no direct comparison of outcomes in biopsy-diagnosed glomerular disease (GD) patients with nephrotic syndrome (NS) or nephrotic range proteinuria (NRP). Our study addresses this gap, comparing long-term outcomes between NS and NRP. Methods: We conducted a retrospective study on 240 kidney biopsy-proven GD patients, tracked from 2010 to 2015 until end-stage kidney disease (ESKD), death, or the study end in January 2022. Results: The median follow-up was 8.8 years. Diagnoses were predominantly nonproliferative (53%), proliferative (25%) nephropathies, diabetic nephropathy (12%), and paraprotein diseases (10%). NS was observed in 141 (59%) patients, presenting more frequently with arterial hypertension, higher eGFR, increased proteinuria, and dyslipidemia than NRP patients. NRP patients often had proliferative GD and diabetic nephropathy; their renal chronicity score was higher. The ESKD endpoint occurred in 35% NS and 39% NRP patients (p 0.4). The cohort’s mean kidney survival time was 8.2 years. In a multivariate analysis, NS, lower eGFR, a higher renal chronicity score, and diabetic nephropathy were associated with ESKD. A total of 64 patients (27%) died, 73% post-kidney replacement therapy initiation, and mostly from cardiovascular disease (63%). Mortality between proteinuria forms showed no difference. The multivariate analysis found lower eGFR, a higher Charlson comorbidity score, and diabetic nephropathy associated with mortality. Conclusions: Our study found no difference in all-cause mortality between NS and NRP in glomerular diseases. However, an adjusted analysis revealed poorer kidney survival for NS patients, emphasizing the need for personalized management to improve renal prognoses. Full article
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<p>Primary clinicopathological diagnoses of the patients included in the study. n, actual number of patients in each category; ANCA, anti-neutrophil cytoplasmic antibody; FSGS, focal and segmental glomerulosclerosis; GN, glomerulonephritis; MCD, minimal change disease; MIDD, monoclonal immunoglobulin deposition disease; P-uria, proteinuria; TBMD, thin glomerular basement membrane disease.</p>
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<p>(<b>A</b>). Nonadjusted Kaplan–Meier survival curves for nephrotic range proteinuria versus nephrotic syndrome for all-cause mortality; (<b>B</b>). Nonadjusted Kaplan–Meier survival curves for nephrotic range proteinuria versus nephrotic syndrome for kidney survival (ESKD); (<b>C</b>). Adjusted survival curve for all-cause mortality (<a href="#life-14-01674-t002" class="html-table">Table 2</a>); (<b>D</b>). Adjusted survival curve for kidney survival (<a href="#life-14-01674-t002" class="html-table">Table 2</a>).</p>
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17 pages, 3689 KiB  
Article
Genome Sequencing and Metabolic Potential Analysis of Irpex lacteus
by Yue Wang, Yingce Duan, Menghan Zhang, Chaoqin Liang, Wenli Li, Chengwei Liu and Ying Ye
J. Fungi 2024, 10(12), 846; https://doi.org/10.3390/jof10120846 - 7 Dec 2024
Viewed by 578
Abstract
Irpex lacteus is an edible and medicinal macrofungus with significant biological activity and broad pharmaceutical prospects that has received increasing attention in recent years. Although it is an important resource for macrofungi, knowledge of it remains limited. In this study, we sequenced, de [...] Read more.
Irpex lacteus is an edible and medicinal macrofungus with significant biological activity and broad pharmaceutical prospects that has received increasing attention in recent years. Although it is an important resource for macrofungi, knowledge of it remains limited. In this study, we sequenced, de novo assembled, and annotated the whole genome of I. lacteus using a PacBio Sequel II sequencer. The assembled 41.83 Mb genome contains 13,135 predicted protein-coding genes, 83.44% of which have searchable sequence similarity to other genes available in public databases. Using genome-based bioinformatics analysis, we identified 556 enzymes involved in carbohydrate metabolism and 103 cytochrome P450 proteins. Genome annotation revealed genes for key enzymes responsible for the biosynthesis of secondary metabolites, such as terpenoids and polyketides. Among them, we identified 14 terpene synthases, 8 NRPS-like enzymes, and 4 polyketide synthases (PKS), as well as 2 clusters of biosynthetic genes presumably related to terpene synthesis in I. lacteus. Gene family analysis revealed that the MYB transcription factor gene family plays an important role in the growth and development of I. lacteus. This study further enriches the genomic content of I. lacteus, provides genomic information for further research on the molecular mechanism of I. lacteus, and promotes the development of I. lacteus in the fields of drug research and functional food production. Full article
(This article belongs to the Section Fungal Genomics, Genetics and Molecular Biology)
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<p>Genome diagram of <span class="html-italic">I. lacteus</span> genome. (<b>A</b>) Chromosome length; (<b>B</b>) GC ratio; (<b>C</b>) GC skew; (<b>D</b>) and (<b>E</b>) gene density; (<b>F</b>) collinearity analysis.</p>
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<p>CAZymes analysis of <span class="html-italic">I. lacteus</span>. (<b>A</b>) Gene distribution of <span class="html-italic">I. lacteus</span> based on the six major modules of CAZymes; (<b>B</b>) results of CAZyme profiling of 21 fungal species.</p>
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<p>Analysis of genes involved in secondary metabolite biosynthesis. (<b>A</b>) Distribution of biosynthetic core genes for natural products on the chromosomes; (<b>B</b>) phylogenetic analysis of sesquiterpene synthase (STS) homologues; (<b>C</b>) schematic diagram of the composition of postulated clusters 2 and 10.</p>
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<p>Analysis of the gene for polyketide synthase from <span class="html-italic">I. lacteus</span>. (<b>A</b>) Phylogenetic tree of different functional PKS enzymes constructed by maximum likelihood analysis of the keto-synthase (KS) domain amino acid sequences; (<b>B</b>) structural domains of orsellinic acid synthase from several species of basidiomycete.</p>
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<p>Maximum likelihood tree of 106 cytochrome P450s from <span class="html-italic">I. lacteus</span>. Each cytochrome P450 family is shown in a separate color, and the branch reliability value of over 50 is marked on the corresponding branch node.</p>
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<p>(<b>A</b>) Comparative plots of the number of MYB transcription factors in 11 fungal species; (<b>B</b>) prediction of motif, a MYB transcription factor of <span class="html-italic">I. lacteus</span>.</p>
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<p>Screening identified nine cis-acting elements in the 2000 bp region upstream of the ILMYB transcription factor initiation codon (ATG) associated with secondary metabolism <span class="html-italic">I. lacteus</span>.</p>
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19 pages, 6558 KiB  
Article
Real-Time Observation of Clickable Cyanotoxin Synthesis in Bloom-Forming Cyanobacteria Microcystis aeruginosa and Planktothrix agardhii
by Rainer Kurmayer and Rubén Morón Asensio
Toxins 2024, 16(12), 526; https://doi.org/10.3390/toxins16120526 - 5 Dec 2024
Viewed by 683
Abstract
Recently, the use of click chemistry for localization of chemically modified cyanopeptides has been introduced, i.e., taking advantage of promiscuous adenylation (A) domains in non-ribosomal peptide synthesis (NRPS), allowing for the incorporation of clickable non-natural amino acids (non-AAs) into their peptide products. In [...] Read more.
Recently, the use of click chemistry for localization of chemically modified cyanopeptides has been introduced, i.e., taking advantage of promiscuous adenylation (A) domains in non-ribosomal peptide synthesis (NRPS), allowing for the incorporation of clickable non-natural amino acids (non-AAs) into their peptide products. In this study, time-lapse experiments have been performed using pulsed feeding of three different non-AAs in order to observe the synthesis or decline of azide- or alkyne-modified microcystins (MCs) or anabaenopeptins (APs). The cyanobacteria Microcystis aeruginosa and Planktothrix agardhii were grown under maximum growth rate conditions (r = 0.35–0.6 and 0.2–0.4 (day−1), respectively) in the presence of non-AAs for 12–168 h. The decline of the azide- or alkyne-modified MC or AP was observed via pulse-feeding. In general, the increase in clickable MC/AP in peptide content reached a plateau after 24–48 h and was related to growth rate, i.e., faster-growing cells also produced more clickable MC/AP. Overall, the proportion of clickable MC/AP in the intracellular fraction correlated with the proportion observed in the dissolved fraction. Conversely, the overall linear decrease in clickable MC/AP points to a rather constant decline via dilution by growth instead of a regulated or induced release in the course of the synthesis process. Full article
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Graphical abstract

Graphical abstract
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<p>Mean (±SE) proportion of natural and clickable MC in total MC (cellular fraction, composed of four MC structural variants: DAsp-MC-YR, MC-YR, DAsp-MC-LR, MC-LR) during time-lapse experiments using pulsed feeding of non-natural amino acids (non-AAs) in order to observe the build up (<b>a</b>,<b>b</b>) or decline (<b>c</b>,<b>d</b>) of azide- or alkyne-modified MC in <span class="html-italic">M. aeruginosa</span> strain Hofbauer. Control cells were grown and processed under identical conditions but without non-AA substrate and could not show any clickable MC synthesis.</p>
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<p>Mean (±SE) proportion of natural and clickable AP in total AP (cellular fraction, composed of four AP structural variants: unknown AP, AP-C, AP-B, AP-A) during time-lapse experiments using pulsed feeding of non-natural amino acids (non-AAs) in order to observe the build up (<b>a</b>,<b>b</b>) or decline (<b>c</b>,<b>d</b>) of azide- or alkyne modified AP in <span class="html-italic">P. agardhii</span> strain no371/1. Control cells were grown and processed under identical conditions but without non-AA substrate and could not show any clickable MC synthesis.</p>
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<p>Relationship between growth rate (day<sup>−1</sup>) and (<b>a</b>–<b>c</b>) the clickable MC net production rate (day<sup>−1</sup>) in <span class="html-italic">M. aeruginosa</span> strain Hofbauer (calculated from ln(x + 1) MC-LR equivalents in ng/mL) and (<b>d</b>–<b>f</b>) the clickable AP net production rate (day<sup>−1</sup>) in <span class="html-italic">P. agardhii</span> strain no371/1 (calculated from ln(x + 1) AP-B equivalents in ng/mL) during time-lapse experiments using feeding of non-natural amino acids (non-AAs) in order to observe the build up of azide- or alkyne-modified MC/AP. Details of linear regression curves are as follows: (<b>a</b>) MC-Phe-AzR (y = −0.08 + 0.73x, R<sup>2</sup> = 0.95, <span class="html-italic">p</span> &lt; 0.0001), (<b>b</b>) MC-Prop-LysR (y = −0.47 + 1.58x, R<sup>2</sup> = 0.95, <span class="html-italic">p</span> &lt; 0.0001), (<b>c</b>) MC-Prop-TyrR (y = −0.13 + 0.86x, R<sup>2</sup> = 0.99, <span class="html-italic">p</span> &lt; 0.0001), (<b>d</b>) AP-Phe-Az (not significant, <span class="html-italic">p</span> = 0.33), (<b>e</b>) AP-Prop-Lys (y = 0.29 + 0.39x, R<sup>2</sup> = 0.21, <span class="html-italic">p</span> = 0.099), (<b>f</b>) AP-Prop-Tyr (y = −0.28 + 1.32x, R<sup>2</sup> = 0.65, <span class="html-italic">p</span> = 0.0005), where y is MC/AP production rate (day<sup>−1</sup>) and x is growth rate (day<sup>−1</sup>).</p>
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<p>Proportion of individual clickable MC in <span class="html-italic">M. aeruginosa</span> (<b>a</b>–<b>c</b>) or clickable AP in <span class="html-italic">P. agardhii</span> (<b>d</b>–<b>e</b>) in total MC/AP (cellular fraction) during time-lapse experiments using pulsed feeding of non-natural amino acids (non-AAs) in order to observe the decline of (<b>a</b>) MC-Phe-AzR, (<b>b</b>) MC-Prop-LysR, (<b>c</b>) MC-Prop-TyrR in <span class="html-italic">M. aeruginosa,</span> or (<b>d</b>) AP-Phe-Az, (<b>e</b>) AP-Prop-Lys, (<b>f</b>) AP-Prop-Tyr in <span class="html-italic">P. agardhii</span> strain no371/1. Using growth rates, the theoretical decline of clickable MC/AP was calculated (black symbols, straight line) and compared to the observed decline (colored symbols, dotted line). Note that the scale at the <span class="html-italic">y</span>-axis is different, as production efficiency differs between non-AAs (<a href="#toxins-16-00526-f001" class="html-fig">Figure 1</a> and <a href="#toxins-16-00526-f002" class="html-fig">Figure 2</a>).</p>
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<p>Workflow of time-lapse experiments using pulsed feeding of non-AAs for real-time observation of clickable MC/AP synthesis in bloom-forming cyanobacteria (the workflow was the same for both <span class="html-italic">M. aeruginosa</span> and <span class="html-italic">P. agardhii</span>): (<b>a</b>) time-lapse build up experiments; (<b>b</b>) time-lapse decline experiments. Created with BioRender.com. Note that the labeling of clickable peptides via chemo-selective reaction with fluorophore and high-resolution microscopy and flow-cytometry analysis using Alexa Fluor488 will be reported in a follow-up article.</p>
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<p>Chemical structures of non-AA molecules used for clickable microcystin (MC) synthesis in <span class="html-italic">M. aeruginosa</span> and for clickable anabaenopeptin (AP) synthesis in <span class="html-italic">P. agardhii</span>: (<b>a</b>) 4-Azido-L-phenylalanine (Phe-Az, MW 206.20 g/mol), (<b>b</b>) N-Propargyl-L-Lysine (Prop-Lys, MW 228.25 g/mol), (<b>c</b>) O-Propargyl-L-tyrosine (Prop-Tyr, MW 219.24 g/mol).</p>
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14 pages, 1651 KiB  
Article
Neutrophil Elastase Targets Select Proteins on Human Blood-Monocyte-Derived Macrophage Cell Surfaces
by Nadia Tasnim Ahmed, Apparao B. Kummarapurugu, Shuo Zheng, Gamze Bulut, Le Kang, Aashish Batheja, Adam Hawkridge and Judith A. Voynow
Int. J. Mol. Sci. 2024, 25(23), 13038; https://doi.org/10.3390/ijms252313038 - 4 Dec 2024
Viewed by 571
Abstract
Neutrophil elastase (NE) has been reported to be a pro-inflammatory stimulus for macrophages. The aim of the present study was to determine the impact of NE exposure on the human macrophage proteome and evaluate its impact on pro-inflammatory signals. Human blood monocytes from [...] Read more.
Neutrophil elastase (NE) has been reported to be a pro-inflammatory stimulus for macrophages. The aim of the present study was to determine the impact of NE exposure on the human macrophage proteome and evaluate its impact on pro-inflammatory signals. Human blood monocytes from healthy volunteers were differentiated to macrophages and then exposed to either 500 nM of NE or control vehicle for 2 h in triplicate. Label-free quantitative proteomics analysis identified 41 differentially expressed proteins in the NE versus control vehicle datasets. A total of 26 proteins were downregulated and of those, 21 were cell surface proteins. Importantly, four of the cell surface proteins were proteoglycans: neuropilin 1 (NRP1), syndecan 2 (SDC2), glypican 4 (GPC4), and CD99 antigen-like protein 2 (CD99L2) along with neuropilin 2 (NRP2), CD99 antigen (CD99), and endoglin (ENG) which are known interactors. Additional NE-targeted proteins related to macrophage function were also measured including CD40, CD48, SPINT1, ST14, and MSR1. Collectively, this study provides a comprehensive unbiased view of selective NE-targeted cell surface proteins in chronically inflamed lungs. Full article
(This article belongs to the Special Issue The Role of Protease and Protease Inhibitors in Human Diseases)
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Figure 1

Figure 1
<p>Experimental workflow for investigating the effects of NE treatment on the human blood-monocyte-derived macrophage (BMDM) proteome. BMDMs from healthy donors were split equivalently into 6-well plates and then incubated without (control (Ctl)) or with 500 nM of neutrophil elastase (+NE) for 2 h in triplicate.</p>
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<p>Summary of label-free quantification (LFQ) results. Results show the number of proteins quantified in each donor sample with NE treatment (black) and without NE treatment (gray) (<b>A</b>). Venn diagram shows the proteome overlap between donor samples (<b>B</b>). Venn diagram shows statistically significant (<span class="html-italic">t</span>-test; adjusted <span class="html-italic">p</span>-value &lt; 0.05) differentially regulated proteins in NE vs. Ctl (<b>C</b>). Heatmap showing the log2 fold-change values of protein levels in NE vs. control that were detected in 3/3 donors and statistically significant in 3/3 or 2/3 donor (* indicates the expression level is not statistically significant) (<b>D</b>).</p>
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<p>Down-regulated proteins. Enriched downregulated proteins from the GO cellular component annotation (<b>A</b>). Log10 of the median normalized LFQ abundances rank-plotted with 21 cell-membrane-annotated differentially downregulated proteins (yellow) labeled by gene. <span class="html-italic">GPC4</span> is labeled in red as it is downregulated in only 2/3 donor samples yet is a member of the proteoglycan family (<b>B</b>).</p>
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<p>Western blot and densitometry results for <span class="html-italic">NRP1</span> (<b>A</b>,<b>B</b>), <span class="html-italic">SDC2</span> (<b>C</b>,<b>D</b>), and <span class="html-italic">GPC4</span> (<b>E</b>,<b>F</b>) from NE-targeted BMDM lysates. Three separate blood monocyte donations were obtained from healthy donors and cultured in RPMI with GM-CSF for 8–10 days to differentiate cells to blood monocyte derived macrophages. Cells from each donor were treated with control vehicle or NE (200 or 500 nM) for 1 or 2 h. Cell lysates were collected, protein quantified, and Western analyses were performed for <span class="html-italic">NRP1</span> (<b>A</b>), <span class="html-italic">SDC2</span> (<b>C</b>), and <span class="html-italic">GPC4</span> (<b>E</b>). Left panels are representative Western blots for protein targets and as a control, β-actin. After densitometry of bands using ImageJ, relative expression corrected for β-actin was compared to control treated samples and summary data of relative expression for each protein shown in the panel on the right, <span class="html-italic">NRP1</span> (<b>B</b>), <span class="html-italic">SDC2</span> (<b>D</b>), and <span class="html-italic">GPC4</span> (<b>F</b>). Significant differences in relative expression for N = 3 per protein was determined; *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01; ***, <span class="html-italic">p</span> &lt; 0.001.</p>
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18 pages, 3296 KiB  
Article
miR-24-3p Is Antiviral Against SARS-CoV-2 by Downregulating Critical Host Entry Factors
by Parrish Evers, Spencer M. Uguccioni, Nadine Ahmed, Magen E. Francis, Alyson A. Kelvin and John P. Pezacki
Viruses 2024, 16(12), 1844; https://doi.org/10.3390/v16121844 - 28 Nov 2024
Viewed by 839
Abstract
Despite all the progress in treating SARS-CoV-2, escape mutants to current therapies remain a constant concern. Promising alternative treatments for current and future coronaviruses are those that limit escape mutants by inhibiting multiple pathogenic targets, analogous to the current strategies for treating HCV [...] Read more.
Despite all the progress in treating SARS-CoV-2, escape mutants to current therapies remain a constant concern. Promising alternative treatments for current and future coronaviruses are those that limit escape mutants by inhibiting multiple pathogenic targets, analogous to the current strategies for treating HCV and HIV. With increasing popularity and ease of manufacturing of RNA technologies for vaccines and drugs, therapeutic microRNAs represent a promising option. In the present work, miR-24-3p was identified to inhibit SARS-CoV-2 entry, replication, and production; furthermore, this inhibition was retained against common mutations improving SARS-CoV-2 fitness. To determine the mechanism of action, bioinformatic tools were employed, identifying numerous potential effectors promoting infection targeted by miR-24-3p. Of these targets, several key host proteins for priming and facilitating SARS-CoV-2 entry were identified: furin, NRP1, NRP2, and SREBP2. With further experimental analysis, we show that miR-24-3p directly downregulates these viral entry factors to impede infection when producing virions and when infecting the target cell. Furthermore, we compare the findings with coronavirus, HCoV-229E, which relies on different factors strengthening the miR-24-3p mechanism. Taken together, the following work suggests that miR-24-3p could be an avenue to treat current coronaviruses and those likely to emerge. Full article
(This article belongs to the Special Issue Viruses, MicroRNAs and Host Interactions)
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<p>miR-24-3p inhibits SARS-CoV-2 replication and virion production. (<b>A</b>) Calu3 Cells were reverse transfected with miR-24-3p or con-miR for 24 h prior to infection with SARS-CoV-2, MOI of 0.01, for 24 h, 48 h, or 72 h. RT qPCR (technical triplicate) was then performed to quantify relative vRNA in samples. (<b>B</b>) Production of SARS-CoV-2 was assessed by collecting an aliquot of the supernatant at each time point. (<b>C</b>) Subgenomic cellular RNA of SARS-CoV-2 was assessed by lysing cells at each time point. <span class="html-italic">n</span> = 3. Error bars represent SEM. <span class="html-italic">p</span> &lt; 0.01 **, 0.001 ***, 0.0001 ****.</p>
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<p>Pathway Gene Ontology (GO) of highly expressed miR-24-3p targets. Panther GO was performed on miRDB predicted targets that are highly expressed (RPKM ≥ 20) in the cell lines used in the present study: Huh7, Calu-3, and A549. Most genes belong to unclassified categories; however, these were removed for clarity. A total of 75–102 targets were highly expressed in each cell line.</p>
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<p>miR-24-3p downregulates Furin and SREBP2 mRNA. Calu-3 cells were reverse transfected with 100 nM miR-24-3p or con-miR for 72 h before lysis for RT-qPCR. Treatment with miR-24-3p post-transcriptionally represses (<b>A</b>) furin and (<b>B</b>) SREBP2 at the mRNA level. <span class="html-italic">n</span> = 3. Error bars represent SEM. <span class="html-italic">p</span> &lt; 0.01 **, 0.001 ***.</p>
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<p>miR-24-3p decreases the entry of SARS-CoV-2 in an S pseudovirus model. (<b>A</b>) Scheme depicting the generation of SARS-CoV-2 S pseudotyped virus. (<b>B</b>) Validation of pseudovirus components via western blot of HEK293T producing cell lysates and extracellular supernatant. (<b>C</b>) Pseudovirus entry assay quantified by luciferase microplate reader (technical triplicate). Assay was performed after 24 h reverse transfection of miR-24-3p followed by 48 h pseudovirus infection and lysis using a passive lysis buffer in either (<b>C</b>) Huh7 or (<b>D</b>) Calu-3 cells. Both con-miR and miR-24-3p values were normalized to the average con-mR value. <span class="html-italic">n</span> = 3. Error bars represent SEM. <span class="html-italic">p</span> &lt; 0.001 ***.</p>
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<p>miR-24-3p maintains effectiveness against common SARS-CoV-2 S mutations. Pseudovirus entry assay quantified by luciferase microplate reader in technical triplicate. The assay was performed after 24 h reverse transfection of miR-24-3p or con-miR followed by 48 h pseudovirus S infection with D614G or N501Y S mutants in either (<b>A</b>) Huh7 or (<b>B</b>) ACE2 stably expressing A549 cell line. Lysis was performed using a passive lysis buffer. Both con-miR and miR-24-3p values were normalized to the average con-miR value. <span class="html-italic">n</span> = 3. Error bars represent SEM. <span class="html-italic">p</span> &lt; 0.05 *, 0.001 ***.</p>
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<p>miR-24-3p downregulates Furin, SREBP2, and NRP2 impairing production and entry of SARS-CoV-2. (<b>A</b>) Scheme depicting experimental workflow for assessing target abundance and pseudovirus S production during miRNA pre-treatment. Briefly, HEK293T cells were pre-treated with miR-24-3p or con-miR 24 h before transfection with the plasmids to produce pseudovirions. After 48 h, the pseudovirus was collected and the pseudovirus produced during miR-24-3p treatment or con-miR treatment were then used to infect healthy untreated Huh7 cells. A luciferase assay was then performed on these Huh7 cells to quantify the amount of pseudovirus produced. (<b>B</b>) Western blot analysis of lysates from control or miR-24-3p-treated HEK293Ts producing S-pseudovirus. Several essential proviral targets and the viral S protein were probed for. (<b>C</b>) Western blot analysis of supernatant from control or miR-24-3p-treated HEK293Ts cells producing S-pseudovirus. (<b>D</b>) S-pseudovirus entry assay performed on non-treated Huh7 cells following production in HEK293T cells reverse transfected with miR-24-3p or con-miR. (<b>E</b>) S-pseudovirus entry assay from (<b>C</b>) normalized to total S production from (<b>D</b>). <span class="html-italic">n</span> = 2. Error bars represent SEM. For the luciferase data, both con-miR and miR-24-3p values were normalized to the average con-mR value. <span class="html-italic">p</span> &lt; 0.01 **, 0.0001 ****.</p>
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<p>Diagram illustrating the targets and effects of miR-24-3p during SARS-CoV-2 infection.</p>
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29 pages, 20601 KiB  
Article
Genomic Features of Taiwanofungus gaoligongensis and the Transcriptional Regulation of Secondary Metabolite Biosynthesis
by Yadong Zhang, Yi Wang, Xiaolong Yuan, Hongling Zhang and Yuan Zheng
J. Fungi 2024, 10(12), 826; https://doi.org/10.3390/jof10120826 - 27 Nov 2024
Viewed by 670
Abstract
Fungal secondary metabolites (SMs) have broad applications in biomedicine, biocontrol, and the food industry. In this study, whole-genome sequencing and annotation of Taiwanofungus gaoligongensis were conducted, followed by comparative genomic analysis with 11 other species of Polyporales to examine genomic variations and secondary [...] Read more.
Fungal secondary metabolites (SMs) have broad applications in biomedicine, biocontrol, and the food industry. In this study, whole-genome sequencing and annotation of Taiwanofungus gaoligongensis were conducted, followed by comparative genomic analysis with 11 other species of Polyporales to examine genomic variations and secondary metabolite biosynthesis pathways. Additionally, transcriptome data were used to analyze the differential expression of polyketide synthase (PKS), terpene synthase (TPS) genes, and transcription factors (TFs) under different culture conditions. The results show that T. gaoligongensis differs from other fungal species in genome size (34.58 Mb) and GC content (50.72%). The antibiotics and Secondary Metabolites Analysis Shell (AntiSMASH) analysis reveals significant variation in the number of SM biosynthetic gene clusters (SMBGCs) across the 12 species (12–29), with T. gaoligongensis containing 25 SMBGCs: 4 PKS, 6 non-ribosomal peptide synthetase (NRPS), and 15 TPS clusters. The TgPKS1 gene is hypothesized to be involved in the biosynthesis of orsellinic acid or its derivatives, while TgPKS2 might catalyze the synthesis of 6-methylsalicylic acid (6MSA) and its derivatives. The TgTRI5 genes are suggested to synthesize tetracyclic sesquiterpene type B trichothecene compounds, while TgPentS may be involved in the synthesis of δ-cadinol, β-copaene, and α-murolene analogs or derivatives. Comparative genomic analysis shows that the genome size of T. gaoligongensis is similar to that of T. camphoratus, with comparable SMs. Both species share four types of PKS domains and five distinct types of TPS. Additionally, T. gaoligongensis exhibits a high degree of similarity to Laetiporus sulphureus, despite belonging to a different genus within the same family. Transcriptome analysis reveals significant variation in the expression levels of PKS and TPS genes across different cultivation conditions. The TgPKS1 and TgPKS4 genes, along with nine TgTFs, are significantly upregulated under three solid culture conditions. In contrast, under three different liquid culture conditions, the TgPKS3, TgTRI5-1, and TgTRI5-2 genes, along with twelve TgTFs, exhibit higher activity. Co-expression network analysis and TgTFs binding site prediction in the promoter regions of TgPKS and TgTPS genes suggest that TgMYB9 and TgFTD4 regulate TgPKS4 expression. TgHOX1, TgHSF2, TgHSF3, and TgZnF4 likely modulate TgPKS3 transcriptional activity. TgTRI5-1 and TgTRI5-5 expression is likely regulated by TgbZIP2 and TgZnF15, respectively. This study provides new insights into the regulatory mechanisms of SMs in T. gaoligongensis and offers potential strategies for enhancing the biosynthesis of target compounds through artificial intervention. Full article
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<p>Functional annotation of <span class="html-italic">T. gaoligongensis</span> genes encoding the proteins: (<b>a</b>) eggNOG analysis; (<b>b</b>) KEGG analysis; (<b>c</b>) GO analysis.</p>
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<p>Functional annotation of <span class="html-italic">T. gaoligongensis</span> genes encoding the proteins: (<b>a</b>) eggNOG analysis; (<b>b</b>) KEGG analysis; (<b>c</b>) GO analysis.</p>
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<p>Distribution map of mutation types in the pathogen PHI phenotype of <span class="html-italic">T. gaoligongensis</span>.</p>
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<p>CAZy functional classification chart of <span class="html-italic">T. gaoligongensis</span>.</p>
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<p>TCDB Functional Classification Chart of <span class="html-italic">T. gaoligongensis</span>.</p>
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<p>Comparison of biosynthesis of putative orsellinic acid biosynthetic gene clusters. The number after the region and the number before the decimal point represent the scaffold, and the number after the decimal point represents the gene cluster.</p>
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<p>Comparison of biosynthesis of putative 6MSA biosynthetic gene clusters. The number after the region and the number before the decimal point represent the scaffold, and the number after the decimal point represents the gene cluster.</p>
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<p>Comparative Analysis of Genes Surrounding <span class="html-italic">TgPKS3</span> in <span class="html-italic">T. gaoligongensis</span> and Related Species. The number after the region and the number before the decimal point represent the scaffold, and the number after the decimal point represents the gene cluster.</p>
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<p>Comparative Analysis of Genes Surrounding <span class="html-italic">TgPKS4</span> and Related Species. The number after the region and the number before the decimal point represent the scaffold, and the number after the decimal point represents the gene cluster.</p>
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<p>Scaffold containing SM biosynthesis gene cluster used for synteny analysis. From top to bottom: <span class="html-italic">L. sulphureus</span>, <span class="html-italic">T. camphoratus2</span>, <span class="html-italic">T. gaoligongensis</span>, <span class="html-italic">T. camphoratus1</span>.</p>
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<p>Genomic inventory for terpenoid biosynthesis in <span class="html-italic">T. gaoligongensis</span>.</p>
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<p>Phylogenetic Tree of TPS Proteins from 12 Fungal Strains. The TgTPS types are indicated in the figure: TC1 (<span class="html-italic">T. camphoratus1</span>), TC2 (<span class="html-italic">T. camphoratus2</span>), DQ (<span class="html-italic">D. quercina</span>), WC (<span class="html-italic">W. cocos</span>), LS (<span class="html-italic">L. sulphureus</span>), FR (<span class="html-italic">F. radiculosa</span>), FP (<span class="html-italic">F. palustris</span>), FS (<span class="html-italic">F. schrenkii</span>), FB (<span class="html-italic">F. betulina</span>), PP (<span class="html-italic">P. placenta</span>), NS (<span class="html-italic">N. serialis</span>).</p>
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<p>Comparative Analysis of Genes Flanking Various Types of TPS in <span class="html-italic">L. sulphureus</span> and Fungi of the <span class="html-italic">Taiwanofungus</span> Genus.</p>
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<p>Structural Characterization of the 10 TF Families in <span class="html-italic">T. gaoligongensis</span>. <span class="html-italic">From left to right:</span> Phylogenetic Tree of Proteins, Conserved Motif Analysis and Conserved Domain Analysis.</p>
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<p>Interactive Heatmap of Gene Expression for (<b>a</b>) <span class="html-italic">TgPKS</span>, (<b>b</b>) <span class="html-italic">TgTPS</span>, and (<b>c</b>,<b>d</b>) <span class="html-italic">TgTFs</span> Under Different Cultivation Conditions. T: pea powder (5 g/L), KH₂PO₄ (1 g/L), MgSO₄ (0.5 g/L), yeast powder (5 g/L), and vita-min B1 (0.1 g/L).,NFT: T+Triton X-100 (100 μL) + <span class="html-italic">C. kanehirae</span> sawdust (5 g/L), YFT: T+ Triton X-100 (100 μL) + <span class="html-italic">C. burmannii</span> sawdust (5 g/L), YY: 15 mL MM medium +4 g Populus alba sawdust, YM: 15 mL MM medium +4 g Zea mays flour, YR: 15 mL MM medium +4 g Coix Coicis Semenurr.</p>
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<p>Relative Expression of Differentially Expressed Genes by qRT–PCR. T: pea powder (5 g/L), KH₂PO₄ (1 g/L), MgSO₄ (0.5 g/L), yeast powder (5 g/L), and vita-min B1 (0.1 g/L). NFT: T+Triton X-100 (100 μL) + <span class="html-italic">C. kanehirae</span> sawdust (5 g/L), YFT: T+ Triton X-100 (100 μL) + <span class="html-italic">C. burmannii</span> sawdust (5 g/L), YY: 15 mL MM medium +4 g Populus alba sawdust, YM: 15 mL MM medium +4 g Zea mays flour, YR: 15 mL MM medium +4 g Coix Coicis Semenurr.</p>
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<p>Interactive Heatmap of Gene Expression for (<b>a</b>) <span class="html-italic">TgPKS</span>, (<b>b</b>) <span class="html-italic">TgTPS</span>, and Co-expressed <span class="html-italic">TgTFs</span> Under Varying Cultivation Conditions. T: pea powder (5 g/L), KH₂PO₄ (1 g/L), MgSO₄ (0.5 g/L), yeast powder (5 g/L), and vitamin B1 (0.1 g/L). NFT: T+Triton X-100 (100 μL) + <span class="html-italic">C. kanehirae</span> sawdust (5 g/L), YFT: T+ Triton X-100 (100 μL) + <span class="html-italic">C. burmannii</span> sawdust (5 g/L), YY: 15 mL MM medium +4 g Populus alba sawdust, YM: 15 mL MM medium +4 g Zea mays flour, YR: 15 mL MM medium +4 g Coix Coicis Semenurr.</p>
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<p>Derivatives of orsellinic acid in fungi.</p>
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12 pages, 4407 KiB  
Article
New PKS/NRPS Tenuazamines A–H from the Endophytic Fungus Alternaria alternata FL7 Isolated from Huperzia serrata
by Hao Zhang, Zhibin Zhang, Yiwen Xiao, Wen Wang, Boliang Gao, Yuhao Xie, Jiahao Xie, Xinhua Gao and Du Zhu
J. Fungi 2024, 10(12), 809; https://doi.org/10.3390/jof10120809 - 21 Nov 2024
Viewed by 580
Abstract
In this paper, we present a novel class of hybrid polyketides, tenuazamines A–H (18), which exhibit a unique tautomeric equilibrium from Alternaria alternata FL7. The elucidation of the structures was achieved through a diverse combination of NMR, HR-ESIMS, and [...] Read more.
In this paper, we present a novel class of hybrid polyketides, tenuazamines A–H (18), which exhibit a unique tautomeric equilibrium from Alternaria alternata FL7. The elucidation of the structures was achieved through a diverse combination of NMR, HR-ESIMS, and ECD methods, with a focus on extensive spectroscopic data analysis. Notably, compounds 1, 4, 89 exhibited potent toxic effects on the growth of Arabidopsis thaliana. This research expands the structural diversity of tenuazonic acid compounds derived from endophytic fungi and provides potential hit compounds for the development of herbicides. Full article
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<p>Chemical structures of <b>1</b>–<b>8</b> derived from <span class="html-italic">A. alternata</span> FL7.</p>
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<p>The key COSY (bond lines) and HMBC (blue arrows) correlations of compounds <b>1</b>–<b>8</b>.</p>
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<p>Experimental and calculated ECD spectra of compounds <b>1</b>–<b>2</b>.</p>
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<p>Toxicity of compounds <b>1</b>–<b>9</b> to <span class="html-italic">Arabidopsis thaliana</span>. (Note. the Chinese characters in the picture means “compound”).</p>
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13 pages, 3295 KiB  
Article
In Vivo Quantification of Surfactin Nonribosomal Peptide Synthetase Complexes in Bacillus subtilis
by Maliheh Vahidinasab, Lisa Thewes, Bahar Abrishamchi, Lars Lilge, Susanne Reiße, Elvio Henrique Benatto Perino and Rudolf Hausmann
Microorganisms 2024, 12(11), 2381; https://doi.org/10.3390/microorganisms12112381 - 20 Nov 2024
Viewed by 743
Abstract
Surfactin, a potent biosurfactant produced by Bacillus subtilis, is synthesized using a non-ribosomal peptide synthetase (NRPS) encoded by the srfAA-AD operon. Despite its association with quorum sensing via the ComX pheromone, the dynamic behavior and in vivo quantification of the NRPS complex [...] Read more.
Surfactin, a potent biosurfactant produced by Bacillus subtilis, is synthesized using a non-ribosomal peptide synthetase (NRPS) encoded by the srfAA-AD operon. Despite its association with quorum sensing via the ComX pheromone, the dynamic behavior and in vivo quantification of the NRPS complex remain underexplored. This study established an in vivo quantification system using fluorescence labeling to monitor the availability of surfactin-forming NRPS subunits (SrfAA, SrfAB, SrfAC, and SrfAD) during bioprocesses. Four Bacillus subtilis sensor strains were constructed by fusing these subunits with the megfp gene, resulting in strains BMV25, BMV26, BMV27, and BMV28. These strains displayed growth and surfactin productivity similar to those of the parental strain, BMV9. Fluorescence signals indicated varying NRPS availability, with BMV27 showing the highest and BMV25 showing the lowest relative fluorescence units (RFUs). RFUs were converted to the relative number of NRPS molecules using open-source FPCountR package. During bioprocesses, NRPS availability peaked at the end of the exponential growth phase and declined in the stationary phase, suggesting reduced NRPS productivity under nutrient-limited conditions and potential post-translational regulation. This study provides a quantitative framework for monitoring NRPS dynamics in vivo, offering insights into optimizing surfactin production. The established sensor strains and quantification system enable the real-time monitoring of NRPS availability, aiding bioprocess optimization for industrial applications of surfactin and potentially other non-ribosomal peptides. Full article
(This article belongs to the Special Issue Advances in Microbial Surfactants: Production and Applications)
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<p>Online monitoring of cell growth and fluorescence intensity (FI) of <span class="html-italic">B. subtilis</span> sensor strains. Optical density (<b>a</b>) and relative fluorescence intensity (<b>b</b>) were determined for the constructed <span class="html-italic">B. subtilis</span> mutant strains encoding <span class="html-italic">srfA</span> genes C-terminally fused with a <span class="html-italic">megfp</span> protein tag over a 12 h period in 96-well plate cultivations. Hence, the parental control strain BMV9 (diamond) and the sensor strains BMV25 (<span class="html-italic">srfAA</span>-<span class="html-italic">megfp</span>, green cycle), BMV26 (<span class="html-italic">srfAB</span>-<span class="html-italic">megfp</span>, cyan cycle), BMV27 (<span class="html-italic">srfAC</span>-<span class="html-italic">megfp</span>, inverted orange triangle), and BMV28 (<span class="html-italic">srfAD</span>-<span class="html-italic">megfp</span>, violet triangle) were cultured in biological triplicates.</p>
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<p>Fluorescence microscopic image of bacterial strains cultivated in mineral salt medium until the middle of the exponential phase. <span class="html-italic">B. subtilis</span> BMV25 (<span class="html-italic">srfAA-megfp</span>) (<b>a</b>), <span class="html-italic">B. subtilis</span> BMV26 (<span class="html-italic">srfAB-megfp</span>) (<b>b</b>), <span class="html-italic">B. subtilis</span> BMV27 (<span class="html-italic">srfAC-megfp</span>) (<b>c</b>), and <span class="html-italic">B. subtilis</span> BMV28 (<span class="html-italic">srfAD-megfp</span>) (<b>d</b>) showing the localization of surfactin-forming NRPS subunits with C-terminal-fused mEGFP protein.</p>
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<p>Overview of bioproduction parameters by <span class="html-italic">B. subtilis</span> sensor strains during the cultivation process. The parental <span class="html-italic">B. subtilis</span> strain BMV9 as the negative control and the sensor strains BMV25 (<span class="html-italic">srfAA</span>-<span class="html-italic">megfp</span>), BMV26 (<span class="html-italic">srfAB</span>-<span class="html-italic">megfp</span>), BMV27 (<span class="html-italic">srfAC</span>-<span class="html-italic">megfp</span>), and BMV28 (<span class="html-italic">srfAD</span>-<span class="html-italic">megfp</span>) were cultured in biological triplicates in shake flasks over a period of 33 h. During the cultivation process, surfactin (<b>a</b>), living cell numbers (<b>b</b>), and the relative number of protein molecules equivalent to mEGFP (MEFP) (<b>c</b>) were monitored.</p>
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<p>Calculation of the relative productivity of the surfactin-producing SrfA subunits. The correlation between the surfactin produced and the calculated MEFP for the <span class="html-italic">B. subtilis</span> sensor strains BMV25 (<span class="html-italic">srfAA</span>-<span class="html-italic">megfp</span>), BMV26 (<span class="html-italic">srfAB</span>-<span class="html-italic">megfp</span>), BMV27 (<span class="html-italic">srfAC</span>-<span class="html-italic">megfp</span>), and BMV28 (<span class="html-italic">srfAD</span>-<span class="html-italic">megfp</span>) at the beginning of the exponential growth phase until the end of cultivation after 33 h. The bar plot shows the relative bioproduction of surfactin per NRPS molecule, represented by the fluorescence of the fused mEGFP.</p>
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13 pages, 1931 KiB  
Article
Molecular Biodiversity in Fusarium subglutinans and F. temperatum: A Valuable Tool to Distinguish the Two Sister Species and Determine the Beauvericin Chemotype
by Antonia Susca, Alessandra Villani, Miriam Haidukowski, Filomena Epifani, Antonio F. Logrieco and Antonio Moretti
J. Fungi 2024, 10(11), 785; https://doi.org/10.3390/jof10110785 - 13 Nov 2024
Viewed by 713
Abstract
Fusarium subglutinans and F. temperatum are widely distributed maize pathogens recognized as distinct species with a species-specific chemotype based on patterns of mycotoxins. Recent comparative genomic analysis revealed that genomes of both species carry a complete beauvericin (Bea) biosynthetic genes cluster, [...] Read more.
Fusarium subglutinans and F. temperatum are widely distributed maize pathogens recognized as distinct species with a species-specific chemotype based on patterns of mycotoxins. Recent comparative genomic analysis revealed that genomes of both species carry a complete beauvericin (Bea) biosynthetic genes cluster, but the key gene Bea1 in F. subglutinans is not functional likely due to a large insertion (NRPS22ins) and multiple mutations (SNP298 and SNP528). We used the recently published genome sequences for these species to develop PCR markers for investigating the distribution of three main mutations in the Bea1 gene in a large collection of strains of both species from around the world. We also designed a PCR assay for a rapid and reliable discrimination of both species in the evaluation of crop exposure to mycotoxins. Overall, our results showed that SNP528 was the most common mutation, followed by NRPS22ins and SNP298. Moreover, phylogenetic analyses suggest that non-synonymous SNPs have occurred first, and that the resulting inactivation of BEA production has caused the accumulation of other polymorphisms, including the NRPS22ins, in the entire gene-coding region. The screening for genetic differences between these species could guide future crop management strategies. Full article
(This article belongs to the Special Issue Fungal Diversity in Europe, 3rd Edition)
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<p>Species tree inferred by ML analysis of <span class="html-italic">Tef1</span> gene. Values on branches indicate bootstrap values based on 1000 replicates. Reference isolates are indicated by R. The tree is rooted with <span class="html-italic">F. proliferatum</span> (NRRL 62905) according to Fumero et al.’s (2020) study [<a href="#B13-jof-10-00785" class="html-bibr">13</a>].</p>
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<p>PCR amplifications with species-specific primer pairs targeting (<b>a</b>) <span class="html-italic">F. subglutinans</span> (subF/subR) and (<b>b</b>) <span class="html-italic">F. temperatum</span> (tempF/tempR). * GeneRuler 1 kb DNA Ladder.</p>
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<p>Microevolution in the beauvericin gene cluster of <span class="html-italic">F. subglutinans</span> and <span class="html-italic">F. temperatum</span>. White numbers in the circles indicate the number of strains. The black letters with colors alone indicate the geographical origin: A: Argentina, As: Australia, Au: Austria, G: Germany, I: Italy, N: Netherland, P: Poland, Se: Serbia, Sl: Slovakia, Sw: Switzerland, T: Turkey, U: USA.</p>
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<p>Phylogenetic tree based on the combined sequences (1022 bp) of SNP298 and SNP528 regions. Data were obtained from 93 strains. Sequences were aligned using MUSCLE as implemented in MEGAX. The evolutionary history was inferred using the maximum likelihood method as implemented in IQ-Tree, with the substitution model K2P + R2. Numbers on branches indicates bootstrap values based on 1000 pseudoreplicates. The tree is rooted with <span class="html-italic">F. proliferatum</span> (NRRL62905) according to Fumero et al.’s (2020) study [<a href="#B13-jof-10-00785" class="html-bibr">13</a>]. *: strains with SNP298; °: strains with SNP528.</p>
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<p>Phylogenetic tree based on the combined sequences (1671 bp) of SNP298, SNP528, and NRPS22ins. Data were obtained from a subset of 39 strains. Sequences were aligned using MUSCLE as implemented in MEGAX. The evolutionary history was inferred using the maximum likelihood method as implemented in IQ-Tree, with substitution model K2P + G4. Numbers on branches indicate bootstrap values based on 1000 pseudoreplicates. The tree is rooted with <span class="html-italic">F. proliferatum</span> (NRRL62905) according to Fumero et al.’s (2020) study [<a href="#B13-jof-10-00785" class="html-bibr">13</a>]. <sup>a</sup> strains with SNP528; * strains with SNP298; Bold: strains with 184 bp insertion.</p>
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20 pages, 5975 KiB  
Article
Novel Populations of Mycobacterium smegmatis Under Hypoxia and Starvation: Some Insights on Cell Viability and Morphological Changes
by Ruben Zaragoza-Contreras, Diana A. Aguilar-Ayala, Lázaro García-Morales, Miguel A. Ares, Addy Cecilia Helguera-Repetto, Jorge Francisco Cerna-Cortés, Lizbel León-Solis, Fernando Suárez-Sánchez, Jorge A. González-Y-Merchand and Sandra Rivera-Gutiérrez
Microorganisms 2024, 12(11), 2280; https://doi.org/10.3390/microorganisms12112280 - 10 Nov 2024
Viewed by 691
Abstract
The general features of the shift to a dormant state in mycobacterial species include several phenotypic changes, reduced metabolic activities, and increased resistance to host and environmental stress conditions. In this study, we aimed to provide novel insights into the viability state and [...] Read more.
The general features of the shift to a dormant state in mycobacterial species include several phenotypic changes, reduced metabolic activities, and increased resistance to host and environmental stress conditions. In this study, we aimed to provide novel insights into the viability state and morphological changes in dormant M. smegmatis that contribute to its long-term survival under starvation or hypoxia. To this end, we conducted assays to evaluate cell viability, morphological changes and gene expression. During starvation, M. smegmatis exhibited a reduction in cell length, the presence of viable but non-culturable (VBNC) cells and the formation of anucleated small cells, potentially due to a phenomenon known as reductive cell division. Under hypoxia, a novel population of pleomorphic mycobacteria with a rough surface before the cells reached nonreplicating persistence 1 (NRP1) was identified. This population exhibited VBNC-like behaviour, with a loss of cell wall rigidity and the presence of lipid-body-like structures. Based on dosR and hspX expression, we suggest that M. smegmatis encounters reductive stress conditions during starvation, while lipid storage may induce oxidative stress during hypoxia. These insights into the heterogeneous populations presented here could offer valuable opportunities for developing new therapeutic strategies to control dormant mycobacterial populations. Full article
(This article belongs to the Special Issue Insight into Bacterial Pathogens: Pathogenesis and Host Response)
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<p>Correlation between growth measurement and cell viability methods of <span class="html-italic">M. smegmatis</span>. (<b>A</b>) Growth and cell viability measurements during starvation. (<b>B</b>) Growth and cell viability measurements during hypoxia. White circles represent the optical density (OD), blue squares represent the number of CFU/mL, red diamonds represent total bacteria/mL (t-bact/mL) detected by FCM, and green triangles represent viable bacteria/mL (v-bact/mL) detected by FCM. The time when NRP1 (initial fading of the methylene blue, ▽f) and NRP2 phases (total discolouration of the methylene blue occurred, ▽d) began are indicated. Values are displayed on a logarithmic scale and mean ± SD are plotted. All experiments were carried out in triplicate.</p>
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<p>Multiparametric FCM analysis of <span class="html-italic">M. smegmatis</span> grown under starvation conditions. (<b>A</b>) Dot plots of dead (†), viable (§) and the combination of dead and viable (*) cell populations are displayed; green fluorescence (FL1-H, SYTO 9) vs. red fluorescence (FL2-H, PI) is charted through time (0 h to 120 h). (<b>B</b>) Overlap of frequency histograms of the fluorescence profile of SYTO 9 (FL1-H) at different starvation times. (<b>C</b>) Histograms of cell size. The forward scatter depicts size (FSC-H), and the ordinate (cell counts) denotes single events. (<b>D</b>) Frequency histograms of cell granularity/complexity (SSC-H); the ordinate (cell counts) denotes single events.</p>
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<p>Multiparametric analysis of the results obtained by FCM of M. smegmatis in hypoxia. (<b>A</b>) Dot plots of dead cells defined as SYTO 9lowPIhigh (†), viable cells defined as SYTO 9<sup>high</sup>PI<sup>low</sup> (§) and cells defined as SYTO 9<sup>high</sup>PI<sup>high</sup> (‡) are displayed; fluorescence microspheres were used for calibration (p), red fluorescence (FL2-H, PI) vs. green fluorescence (FL1-H, SYTO 9) is charted through time (0 h to 120 h). (<b>B</b>) Measurements of mycobacterial populations detected by FCM and their correlation with measurements in solid media. The blue squares represent CFU/mL; brown diamonds represent total bacteria per mL (t-bact/mL); black circles represent SYTO 9<sup>high</sup>PI<sup>high</sup> bacteria/mL (SYTO 9<sup>high</sup>PI<sup>high</sup>-bact/mL); green triangles represent viable bacteria per mL (v-bact/mL); red circles represent dead bacteria per mL (d-bact/mL). The times when a noticeable fading (NRP1, ▽f) and the total discolouration (NRP2, ▽d) of the methylene blue occurred are indicated. Values are displayed on a logarithmic scale and mean ± SD are charted. All experiments were carried out in triplicate. (<b>C</b>,<b>D</b>) Frequency histograms of cell size (FSC-H) and cell complexity (SSC-H) of <span class="html-italic">M. smegmatis</span>, respectively. In both cases, the ordinate (cell counts) denotes single events.</p>
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<p>Gene expression of <span class="html-italic">M. smegmatis</span> cultures under in vitro latency conditions over time. Absolute gene expression normalised to 16S rRNA was measured in <span class="html-italic">M. smegmatis</span> either under starvation (<b>A</b>) or hypoxia (<b>C</b>); standard deviations are charted and <span class="html-italic">p</span> &lt; 0.05 was considered significantly different (represented by a star) between expression in time points of in vitro latency and the time 0 h (exponential phase). The relative gene quantification in starvation (at 4, 12, 24 and 120 h) is expressed as the ratio of transcription overtime/transcription at 0 h (<b>B</b>). The relative gene quantification in hypoxia (at 12, 36, 72 and 120 h) is expressed as the ratio of transcription overtime/transcription at 0 h (<b>D</b>).</p>
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<p>TEM images of <span class="html-italic">M. smegmatis</span> under starvation. (<b>A</b>) Representative electron micrographs at 0 h, 12 h, 24 h, and 120 h of incubation; magnification was ×10 K; scale bars represent 2 µm; arrows point to electron-transparent cells without nucleoid and debris are indicated with an asterisk. (<b>B</b>) Ultrastructure of <span class="html-italic">M. smegmatis</span> at 0 h, 24 h, and 120 h of incubation; magnification was ×150 K and scale bars represent 100 nm. Arrow heads point to different cells structure such as a a: cytoplasmatic material, b: cell wall, c: chromatin, d: cellular debris, and e: electron-transparent zone surrounding the nucleoid. The acceleration voltage was 70 kV. These images represent three independent experiments and were chosen from five random fields.</p>
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<p>SEM images of <span class="html-italic">M. smegmatis</span> under starvation. (<b>A</b>) Cells at 0, 24 and 120 h of starvation, at ×10 K magnification. (<b>B</b>) Cells at ×25 K, ×30 K and ×40 K magnification at 24 and 120 h of starvation. Rod cell surfaces with a rough appearance are indicated with an asterisk, and septa are indicated by an arrow. These images represent three independent experiments and were chosen from five random fields. Scale bars represent 500 nm, and the acceleration voltage was 15 kV in all cases.</p>
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<p>SEM images of <span class="html-italic">M. smegmatis</span> cells grown under hypoxic conditions. (<b>A</b>) Representative electron micrographs taken at various times; magnification was ×10 K, and scale bars represent 1 µm. (<b>B</b>) Morphological changes at a higher magnification; times 0 to 36 h were ×20 K, and the scale bar represents 1 µm; times 72 to 120 were ×30 K, and scale bars represent 500 nm. Regular rods (RR), pleomorphic cells (PC), and rough surface cells (RC); the star indicates cellular debris. The acceleration voltage was 15 kV. These images represent three independent experiments and were chosen from five random fields.</p>
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<p>TEM images of <span class="html-italic">M. smegmatis</span> under hypoxia. (<b>A</b>) <span class="html-italic">M. smegmatis</span> cells over time, at ×10K magnification. Scale bars represent 2 µm. (<b>B</b>) <span class="html-italic">M. smegmatis</span> cells at 0 h and 72 h under hypoxia, magnification was ×45 K or ×150 K, respectively. Scale bars represent 100 nm. (<b>C</b>) <span class="html-italic">M. smegmatis</span> cells at 120 h under hypoxia, magnification was ×150 K. Scale bars represent 100 nm. Black arrows point to cells with a low density of electrons. Numbers in panels point to ① Lipid-body-like structures, ② compacted DNA with highly dense electrons, ③ low-density electron zone, ④ loss of rigidity of cell wall, ⑤ cytoplasm, ⑥ star-shaped nucleoid and ⑦ vesicular structures with internal membranes. An acceleration voltage of 70 kV was used. Smaller frames within each panel were magnified ×120 K, and the acceleration voltage was 60 kV; scale bars represent 500 nm. These images represent three independent experiments and were chosen from five random fields.</p>
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22 pages, 6773 KiB  
Review
Structure, Function and Engineering of the Nonribosomal Peptide Synthetase Condensation Domain
by Zhenkuai Huang, Zijing Peng, Mengli Zhang, Xinhai Li and Xiaoting Qiu
Int. J. Mol. Sci. 2024, 25(21), 11774; https://doi.org/10.3390/ijms252111774 - 1 Nov 2024
Viewed by 901
Abstract
The nonribosomal peptide synthetase (NRPS) is a highly precise molecular assembly machinery for synthesizing structurally diverse peptides, which have broad medicinal applications. Withinthe NRPS, the condensation (C) domain is a core catalytic domain responsible for the formation of amide bonds between individual monomer [...] Read more.
The nonribosomal peptide synthetase (NRPS) is a highly precise molecular assembly machinery for synthesizing structurally diverse peptides, which have broad medicinal applications. Withinthe NRPS, the condensation (C) domain is a core catalytic domain responsible for the formation of amide bonds between individual monomer residues during peptide elongation. This review summarizes various aspects of the C domain, including its structural characteristics, catalytic mechanisms, substrate specificity, substrate gating function, and auxiliary functions. Moreover, through case analyses of the NRPS engineering targeting the C domains, the vast potential of the C domain in the combinatorial biosynthesis of peptide natural product derivatives is demonstrated. Full article
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<p>NRPs are capable of being modified by NRPS catalytic domains or tailoring enzymes to generate a variety of derivatives possessing diverse physicochemical properties. Abbreviations: R1-R4 stand for side chains of residues in NRP; M1-M5 stand for the modification groups.</p>
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<p>The linear assembly line in a typical NRPS and the primary roles of core catalytic domains. (<b>A</b>) The assemble of peptide chain by linear NRPS. (<b>B</b>) The A domain consumes ATP to activate amino acid substrates and load them onto the PCP domain to generate an aminoacyl-<span class="html-italic">S</span>-carrier protein complex. (<b>C</b>) The C domain within the NRPS module catalyzes peptide bond formation, linking the substrate to the growing peptide chain and presenting it to the downstream module. Abbreviations: A: adenylation domain; C: condensation domain; PCP: peptidyl carrier protein domain; TE: thioesterase domain; CoA: coenzyme A; 3′, 5′-ADP: 3′, 5′-adenosine diphosphate; ATP: adenosine triphosphate; PPi: pyrophosphate.</p>
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<p>The linear assembly line in a typical NRPS and the primary roles of core catalytic domains. (<b>A</b>) The assemble of peptide chain by linear NRPS. (<b>B</b>) The A domain consumes ATP to activate amino acid substrates and load them onto the PCP domain to generate an aminoacyl-<span class="html-italic">S</span>-carrier protein complex. (<b>C</b>) The C domain within the NRPS module catalyzes peptide bond formation, linking the substrate to the growing peptide chain and presenting it to the downstream module. Abbreviations: A: adenylation domain; C: condensation domain; PCP: peptidyl carrier protein domain; TE: thioesterase domain; CoA: coenzyme A; 3′, 5′-ADP: 3′, 5′-adenosine diphosphate; ATP: adenosine triphosphate; PPi: pyrophosphate.</p>
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<p>Overall structure of the VibH (PDB code: 1L5A). The N-terminal lobe is shown in cyan, while the C-terminal lobe in pink. The side chains in conserved HHxxxDG motif is represented as orange sticks, with the catalytic histidine residue marked by a dashed circle. The latch and floor loops are displayed in yellow and blue, respectively. The binding sites of the donor and acceptor Ppant arms tethered on the PCP domains are indicated.</p>
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<p>Structural comparison of the active sites of Cy domain of BmdB from <span class="html-italic">Thermoactinomyces vulgaris</span> (PDB code: 5T3E) (<b>A</b>) with canonical C domain (VibH) (<b>B</b>). The loop containing the key active residues is highlighted, and the side chains of the conserved residues within the active site motifs are represented as sticks.</p>
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<p>Overall structure of the X domain of Tcp12, the terminal module for biosynthesizing teicoplanin from <span class="html-italic">Actinoplanesteichomyceticus</span> (PDB code: 4TX2). The two subdomains are represented in different colors, and the side chains in the HRxxxDG motif (corresponding to the canonical C-domain active site) located in the N-terminal subdomain are represented as orange sticks.</p>
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<p>The C<sub>T</sub> domain releases the final product through macrocyclization by employing the terminal amine as a nucleophilic agent.</p>
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<p>Structural comparison of the C<sub>T</sub> domain of TqaA from <span class="html-italic">Penicillium aethiopicum</span> (PDB code: 5DIJ) (<b>A</b>) with canonical C domain (VibH) (<b>B</b>) illustrates the significantly narrower solvent channel and the blockage of the acceptor side in C<sub>T</sub> domain. The structures are represented as surfaces, the regions corresponding to solvent channels are indicated by dashed circles, and the acceptor PCP domain binding sites are indicated.</p>
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<p>The assembly line of lipopeptide antibiotic surfactin and its engineering. (<b>A</b>) The assembly line of surfactin consists of three modules, SrfA-A, SrfA-B, and SrfA-C, contributing to the production of the cyclic heptapeptide. (<b>B</b>) Interaction of TycA* with SrfA-C<sub>FA</sub> generates a novel product, 10-undecynoyl-L-Leu. (<b>C</b>) Interaction of TycA* with TycB1<sub>FA</sub> yields a novel product, 10-undecynoyl-L-Pro. (<b>D</b>) TycA*, TycB<sub>FA</sub>,and TycC combine to produce a novel lipopeptide, 10-undecynoyl-L-Pro-L-Phe-D-Phe-L-Asn-L-Gln-L-Tyr-L-Val-L-Orn-L-Leu. Abbreviations: TycA*: variant of TycA with its A domain replaced by maltose-binding protein (MBP); SrfA-C<sub>FA</sub>: variant of SrfA-C harboring mutations W143T, Y145V, and F155I; TycB1<sub>FA</sub> and TycB<sub>FA</sub>: hybrids with C domain of SrfA-C<sub>FA</sub> (residues Gln10-Gln430) inserted into the C domain of a standalone elongation module TycB1 and the first C domain of full-length TycB responsible for tyrocidine synthesis, respectively; Orn: ornithine.</p>
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<p>Strategy of NRPS engineering involving XU. (<b>A</b>) Typical XUs within the NRPS module. (<b>B</b>) Recombinant NRPS with the replacement of one or multiple XUs. (<b>C</b>) De novo construction of NRPS by using XUs. XUs from different NRPSs are represented in various colors.</p>
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<p>Artificial construction of NRPSs by XUs and the corresponding products. (<b>A</b>) Structures of two ambactin derivatives generated by domain and module swapping of the ambactin-producing NRPS AmbS. (<b>B</b>–<b>E</b>) Several non-natural peptides synthesized de novo using XUs from various sources, which are also listed in <a href="#ijms-25-11774-t001" class="html-table">Table 1</a>. Abbreviation: FT: formyl transferase.</p>
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<p>The location of COM domains in several NRPSs. (<b>A</b>) The COM domains between the TycA and TycB subunits in the tyrocidine assembly line; (<b>B</b>) The COM domains between the PpsA and PpsB subunits in the plipastatin assembly line. Abbreviations: COMD: the donor COM domain; COMA: the acceptor COM domain.</p>
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<p>The assembly line of bacillomycin D and its engineering. (<b>A</b>) The cyclic lipopeptide structure of bacillomycin D is composed of a β-amino fatty acid chain linked to a heptapeptide. Bacillomycin D synthase is a PKS/NRPS hybrid enzyme comprising four units: BamD, BamA, BamB, and BamC. The blue regions in bamD and bamA represent PKS domains. (<b>B</b>) Deletion of the COMD domain in module 2 results in premature hydrolysis by the TE domain, generating a linear dipeptide linked to a β-amino fatty acid chain. (<b>C</b>) Deletion of the COMD domain in module 3 leads to premature hydrolysis by the TE domain, generating a linear tripeptide linked to a β-amino fatty acid chain. (<b>D</b>) Deletion of the COMD domain in module 6 leads to premature hydrolysis by the TE domain, generating a linear hexapeptide linked to the β-amino fatty acid chain. (<b>E</b>) Deletion of the COMD domain in module 3 leads to the skipping of module 4, generating a cyclic hexapeptide linked to a β-amino fatty acid chain. Abbreviations: FA stands for fatty acid.</p>
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13 pages, 3170 KiB  
Article
Neuropilin-1 as a Key Molecule for Renal Recovery in Lupus Nephritis: Insights from an NZB/W F1 Mouse Model
by Sebastian Sandoval, Cristina Solé, Blanca Joseph-Mullol, Maria Royo, Teresa Moliné, Alejandra Gabaldón and Josefina Cortés-Hernández
Int. J. Mol. Sci. 2024, 25(21), 11364; https://doi.org/10.3390/ijms252111364 - 22 Oct 2024
Viewed by 767
Abstract
Systemic lupus erythematosus (SLE) is an autoimmune disease affecting multiple organs, with lupus nephritis (LN) occurring in 40–50% of SLE patients. Despite advances in diagnosis and treatment, LN remains a major cause of morbidity and mortality, with 10–20% of patients progressing to end-stage [...] Read more.
Systemic lupus erythematosus (SLE) is an autoimmune disease affecting multiple organs, with lupus nephritis (LN) occurring in 40–50% of SLE patients. Despite advances in diagnosis and treatment, LN remains a major cause of morbidity and mortality, with 10–20% of patients progressing to end-stage renal disease (ESRD). While knowledge of LN’s pathogenesis has improved, mechanisms of renal recovery are still largely unexplored. Neuropilin-1 (NRP-1), a transmembrane receptor expressed in renal tissue, has emerged as a promising biomarker for assessing renal recovery in LN. This study evaluates and correlates longitudinal levels of NRP-1 with kidney histology using an NZB/W F1 mouse model of LN. A total of 30 mice were used, with 15 receiving intravenous cyclophosphamide (CYC) and 15 being untreated. NRP-1 levels were measured in urine and serum, and kidney samples were taken from a subgroup of mice for histological evaluation. The results demonstrated a progressive increase in renal and urinary NRP-1 expression, particularly notable at weeks 26 and 32. Urinary NRP-1 levels above 34.40 ng/mL were strong predictors of favorable renal response, showing 100% sensitivity and 88% specificity. These findings indicate a robust correlation between urinary NRP-1 levels and renal histological recovery, underscoring the potential of NRP-1 as a valuable biomarker for assessing renal response in LN. This study demonstrates that renal production of NRP-1 is linked to histological recovery and establishes a foundation for future research into the role of NRP-1 in lupus kidney recovery. Full article
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Figure 1
<p>The ameliorative effect of CYC on disease progression in NZB/W F1 mice. (<b>A</b>) Kaplan–Meier survival curve for NZB/W F1 mice treated with cyclophosphamide or saline (CYC-treated and non-treated groups, respectively). The log-rank test was used for survival analysis, with <span class="html-italic">p</span>-values ≤ 0.05 considered statistically significant. (<b>B</b>) Serum and urine biomarkers were measured to assess the progression of LN in both treated and non-treated mouse groups. Serum autoantibodies to double-stranded DNA (anti-dsDNA) and immunoglobulin (IgG) titers, as well as the urine protein/creatinine ratio (µg/mg), were determined using enzyme-linked immunosorbent assay (ELISA). One-way ANOVA followed by Bonferroni’s test and Student’s <span class="html-italic">t</span>-test were used to compare biomarker concentrations between the non-treated and CYC-treated groups. * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Analysis of kidney tissue from untreated and CYC-treated groups. (<b>A</b>) Renal tissue was subjected to hematoxylin and eosin staining as well as immunofluorescence analysis for IgG and complement component C3. Cell nuclei were stained with DAPI (blue), while IgG and C3 proteins were labeled with FITC (green). Scale bar = 50 µm. Average scores for evaluation were obtained from the Vall d’Hebron pathology group to assess the percentage of glomeruli (<b>B</b>) and the staining intensity for IgG (<b>C</b>) and C3 (<b>D</b>) in renal tissue. One-way ANOVA followed by Bonferroni’s test and Student’s <span class="html-italic">t</span>-test were used to compare biomarker concentrations between groups. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Longitudinal analysis of NRP-1 protein levels during nephritis progression in NZB/W F1 mice. (<b>A</b>) Immunofluorescence staining for NRP-1 was performed on kidney tissue samples from both non-treated and CYC-treated groups at weeks 20, 26, 32, and at the study endpoint. Cell nuclei were stained with DAPI (blue), and NRP-1 was labeled with FITC (green). Scale bar = 50 µm. The intensity of NRP-1 immunofluorescence was quantified using the ImageJ Fiji software (version 1.45). Statistical comparisons between groups were performed using Student’s <span class="html-italic">t</span>-test. *** <span class="html-italic">p</span> &lt; 0.0001, **** <span class="html-italic">p</span> &lt; 0.00001. (<b>B</b>) Serum and urine levels of NRP-1 were measured at weeks 20, 26, 32, and at the study endpoint in both CYC-treated and non-treated NZB/W F1 mice groups. One-way ANOVA followed by Bonferroni’s post hoc test and Student’s <span class="html-italic">t</span>-test were used to compare NRP-1 levels between urine and serum at each time point. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Correlation between urinary NRP-1 levels (uNRP-1) and anti-dsDNA and IgG levels, protein/creatinine ratio, and mesangial proliferation. Spearman’s rank-order correlation was utilized to assess the relationships between these parameters, with significance levels and correlation coefficients indicated in each graph.</p>
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<p>Urinary NRP-1 levels as a potential biomarker for monitoring renal recovery. (<b>A</b>) Receiver operating characteristic (ROC) curve analysis of uNRP-1 was conducted using an optimal binary logistic regression model, combining data from both cohorts, to distinguish between renal recovery and non-recovery in NZB/W F1 mice (<span class="html-italic">n</span> = 11 for renal recovery, <span class="html-italic">n</span> = 19 for non-recovery). The area under the ROC curve (AUC) is provided. (<b>B</b>) Longitudinal analysis of uNRP-1 levels during the progression of lupus nephritis in NZB/W F1 mice was performed, categorizing mice based on whether they achieved renal recovery. Renal recovery was determined through histological analysis of kidney tissue, with mice exhibiting more than 40% mesangial proliferation being classified into the non-recovery group. Throughout the study period, mice in the renal recovery group consistently maintained uNRP-1 levels above 34.40 ng/mL.</p>
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