Biology subjects

Puskas, L.

Publications and source records attributed to Puskas, L..

4 recordsLinked to original sources

bioRxiv2024

Dominant suppressor genes of p53-induced apoptosis in Drosophila melanogaster

Apoptosis, the programmed cell death, is responsible for the removal of cells seriously damaged or unwanted in development. A major function of apoptosis is the removal of cells which suffered oncogenic mutations, thereby preventing cancerous transformation. By making use of the DEP transposon, a P element derivative made in our laboratory, we made an insertional mutagenesis screen in Drosophila melanogaster to identify genes which, when overexpressed, suppress the p53-activated apoptosis. The DEP element has Gal4-activatable, outward-directed UAS-promoters at both ends which can be deleted separately in vivo. In the DEP insertion mutants, we used the GMR-Gal4 driver to induce transcription from both UAS-promoters and tested the suppression effect on the apoptotic rough eye phenotype generated by an activated UAS-p53 transgene. By DEP insertions, seven genes were identified which suppressed the p53-induced apoptosis. In four mutants, the suppression effect was resulted by single genes activated by one UAS-promoter (Pka-R2, Rga, crol, Spt5). In the other three (Orct2, Polr2M, stg), deleting either UAS-promoter eliminated the suppression effect. In qPCR experiments we found that the genes in the vicinity of the DEP insertion also showed an elevated expression level. This suggested an additive effect of the nearby genes on suppressing apoptosis. In the eucaryotic genomes there are co-expressed gene clusters. Three of the DEP insertion mutants are included and two are in close vicinity of separate co-expressed gene clusters. This raises the possibility that the activity of some of the genes in these clusters may help the suppression of the apoptotic cell death.

genetics↗

bioRxiv2021

Patient-specific Boolean models of signaling networks guide personalized treatments

Prostate cancer is the second most occurring cancer in men worldwide. To better understand the mechanisms of tumorigenesis and possible treatment responses, we developed a mathematical model of prostate cancer which considers the major signalling pathways known to be deregulated. We personalised this Boolean model to molecular data to reflect the heterogeneity and specific response to perturbations of cancer patients. 488 prostate samples were used to build patient-specific models and compared to available clinical data. Additionally, eight prostate cell-line-specific models were built to validate our approach with dose-response data of several drugs. The effects of single and combined drugs were tested in these models under different growth conditions. We identified 15 actionable points of interventions in one cell-line-specific model whose inactivation hinders tumorigenesis. To validate these results, we tested nine small molecule inhibitors of five of those putative targets and found a dose-dependent effect on four of them, notably those targeting HSP90 and PI3K. These results highlight the predictive power of our personalized Boolean models and illustrate how they can be used for precision oncology.

systems biology↗

bioRxiv2021

Candida albicans enhances the progression of oral squamous cell cancrinoma in vitro and in vivo

Oral squamous cell carcinoma (OSCC) is a serious health issue worldwide. OSCC is highly associated with oral candidiasis, although it is unclear whether the fungus promotes the genesis and progression of OSCC or cancer facilitates the growth of the fungus. Therefore, we investigated whether Candida could directly influence OSCC development and progression. Our in vitro results suggest that the presence of live C. albicans, but not C. parapsilosis, enhances the progression of OSCC by stimulating the production of matrix metalloproteinases, oncometabolites, pro-tumor signaling routes, and overexpression of prognostic marker genes associated with metastatic events. We also found that oral candidiasis triggered by C. albicans enhanced the progression of OSCC in vivo through the induction of inflammation and overexpression of metastatic genes and markers of epithelial-mesenchymal transition. Taken together, these results suggest that C. albicans actively participates in the complex process of OSCC progression.

microbiology↗

bioRxiv2020

Automatic deep learning driven label-free image guided patch clamp system for human and rodent in vitro slice physiology

Patch clamp recording of neurons is a labor-intensive and time-consuming procedure. We have developed a tool that fully automatically performs electrophysiological recordings in label-free tissue slices. The automation covers the detection of cells in label-free images, calibration of the micropipette movement, approach to the cell with the pipette, formation of the whole-cell configuration, and recording. The cell detection is based on deep learning. The model was trained on a new image database of neurons in unlabeled brain tissue slices. The pipette tip detection and approaching phase use image analysis techniques for precise movements. High-quality measurements were performed on hundreds of human and rodent neurons. We also demonstrate that further molecular and anatomical analysis can be performed on the recorded cells. The software has a diary module that automatically logs patch clamp events. Our tool can multiply the number of daily measurements to help brain research. ONE SENTENCE SUMMARYNovel deep learning and image analysis algorithms for automated patch clamp systems to reliably measure neurons in human and rodent brain slices.

neuroscience↗