Background: A high mortality rate is associated with about 80% of all infections worldwide, mainly due to antimicrobial resistance. Various antimicrobial and cytotoxic activities have been proposed for Meliaceae species. This study aimed to evaluate the in vitro anti-virulence and cytotoxic effect of the leaf extracts of , and against five MRSA strains and on three cancer cell lines, followed by biological correlation to their encompassed phytoconstituents.
Material And Methods: We explored three plants of this family against a panel of Methicillin-resistant (MRSA) strains and several cancer cell lines to select the most promising candidates for further in vivo and preclinical studies. The phytochemical composition was evaluated by UHPLC-QTOF-MS untargeted profiling. Cell viability was assessed by SRB assay. Minimum Inhibitory Concentration was carried out by using the agar micro-dilution technique. Inhibition of biofilm formation and preformed biofilm disruption were assessed spectrophotomertically, according to the Sultan and Nabil method (2019).
Results: A total of 279 compounds were putatively annotated to include different phytochemical classes, such as flavonoids (108), limonoids/terpenoids (59), phenolic acids (49) and lower-molecular-weight phenolics (39). extract showed the most potent cytotoxic activity against Huh-7, DU-145 and MCF-7 cell lines (IC = 3, 3.5 and 13.4 µg mL, respectively), followed by , with no effect recorded for extract. Furthermore, both and extracts showed promising anti-virulence and antimicrobial activities, with being particularly active against MRSA. These two latter extracts could inhibit and disrupt the biofilm, formed by MRSA, at sub-lethal concentrations. Interestingly, the extracts inhibited hemolysin-α enzyme, thus protecting rabbit RBCs from lysis. extract reduced the pigmentation and catalase enzyme activity of tested pigmented strains better than at both tested sub-MICs. Consequently, susceptibility of the extract-treated cells to oxidant killing by 200 mM HO increased, leading to faster killing of the cells within 120 min as compared to the extract-non-treated cells, likely due to the lower antioxidant-scavenging activity of cells exhibiting less staphyloxanthin production.
Conclusion: These findings suggested that both and natural extracts are rich in bioactive compounds, mainly limonoids, phenolics and oxygenated triterpenoids, which can combat MRSA biofilm infections and could be considered as promising sources of therapeutic cytotoxic, antibiofilm and anti-virulence agents.
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http://dx.doi.org/10.3390/molecules27020435 | DOI Listing |
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Zentalis Pharmaceuticals, Inc., San Diego, CA, USA.
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January 2025
School of Medicine, Nankai University, Tianjin, 300071, China.
Cholangiocarcinoma (CCA), a highly aggressive form of cancer, is known for its high mortality rate. A Disintegrin and Metalloprotease Domain-like Protein Decysin-1 (ADAMDEC1) can promote the development and metastasis in various tumors by degrading the extracellular matrix. However, its regulatory mechanism in CCA remains unclear.
View Article and Find Full Text PDFAnn Hematol
January 2025
Department of Hematology, Navy Medical Center of PLA, Naval Medical University, No. 338 West Huaihai Road, Changning District, Shanghai, 200052, China.
Multiple myeloma(MM) remains incurable with high relapse and chemoresistance rates. Differentially expressed genes(DEGs) between newly diagnosed myeloma and secondary plasma cell leukemia(sPCL) were subjected to a weighted gene co-expression network analysis(WGCNA). Drug resistant myeloma cell lines were established.
View Article and Find Full Text PDFSci Rep
January 2025
School of Physics, Engineering and Technology, University of York, Heslington, York, YO10 5DD, UK.
Prostate cancer is a disease which poses an interesting clinical question: Should it be treated? Only a small subset of prostate cancers are aggressive and require removal and treatment to prevent metastatic spread. However, conventional diagnostics remain challenged to risk-stratify such patients; hence, new methods of approach to biomolecularly sub-classify the disease are needed. Here we use an unsupervised self-organising map approach to analyse live-cell Raman spectroscopy data obtained from prostate cell-lines; our aim is to exemplify this method to sub-stratify, at the single-cell-level, the cancer disease state using high-dimensional datasets with minimal preprocessing.
View Article and Find Full Text PDFNat Commun
January 2025
Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
Spatial protein expression technologies can map cellular content and organization by simultaneously quantifying the expression of >40 proteins at subcellular resolution within intact tissue sections and cell lines. However, necessary image segmentation to single cells is challenging and error prone, easily confounding the interpretation of cellular phenotypes and cell clusters. To address these limitations, we present STARLING, a probabilistic machine learning model designed to quantify cell populations from spatial protein expression data while accounting for segmentation errors.
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