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Enyedi, M. Z.

Publications and source records attributed to Enyedi, M. Z..

2 recordsLinked to original sources

Comprehensive Bulk and Single-Cell RNA Sequencing Uncovers Senescence-Associated Biomarkers in Therapeutic Mesenchymal Stem Cells

BackgroundMesenchymal stem cells (MSCs) hold great promise in cell therapy, but their effectiveness declines with repeated cell divisions due to senescence. Canines, sharing aging characteristics with humans, serve as a valuable model to study this process in a translational context. MethodsIn the present study, we performed an in-depth characterization of senescence in canine MSCs using a combination of morphological, molecular, and transcriptomic analyses. Early (P2) and late-passage (P6) canine MSCs were characterized using a combination of senescence-associated {beta}-galactosidase staining, cell cycle profiling, and both bulk and single-cell RNA sequencing to capture global transcriptional changes. ResultsBy employing a passage-based in vitro approach, the present study demonstrates that late-passage cells (P6) compared to early-passage cells (P2) exhibit hallmark features of senescence, including morphological alterations, elevated SA-{beta}-galactosidase activity, and considerable transcriptional changes. These changes were represented by significant upregulation of established senescence marker genes, alongside potential novel candidates and downregulation of genes associated with cell cycle progression and proliferation. Moreover, single-cell RNA sequencing uncovered heterogeneous distribution of senescent subpopulations, upregulation of SASP-related genes and reduced proliferation markers. ConclusionsOur findings demonstrate that combining classical markers with bulk and single-cell RNA sequencing facilitates senescent cell identification while improving quality control for clinical MSC samples.

cell biology↗

Antibiotics of the future are prone to resistance in Gram-negative pathogens

Despite the ongoing development of new antibiotics, the future evolution of bacterial resistance may render them ineffective. We demonstrate that antibiotic candidates currently under development are as prone to resistance evolution in Gram-negative pathogens as clinically employed antibiotics. Resistance generally stems from both genomic mutations and the transfer of antibiotic resistance genes from microbiomes associated with humans, both factors carrying equal significance. The molecular mechanisms of resistance overlap with those found in commonly used antibiotics. Therefore, these mechanisms are already present in natural populations of pathogens, indicating that resistance can rapidly emerge through selection of pre-existing bacterial variants. However, certain combinations of antibiotics and bacterial strains are less prone to developing resistance, emphasizing the potential of narrow-spectrum antibacterial therapies that could remain effective. Our comprehensive framework allows for predicting future health risks associated with bacterial resistance to new antibiotics.

microbiology↗