Publications by authors named "M Pospisek"
Study Question: Which actively translated maternal transcripts are differentially regulated between clinically relevant in vitro and in vivo maturation (IVM) conditions in mouse oocytes and zygotes?
Summary Answer: Our findings uncovered significant differences in the global transcriptome as well as alterations in the translation of specific transcripts encoding components of energy production, cell cycle regulation, and protein synthesis in oocytes and RNA metabolism in zygotes.
What Is Known Already: Properly regulated translation of stored maternal transcripts is a crucial factor for successful development of oocytes and early embryos, particularly due to the transcriptionally silent phase of meiosis.
Study Design, Size, Duration: This is a basic science study utilizing an ICR mouse model, best suited for studying in vivo maturation.
Article Synopsis
- * Researchers created Huh7.5 ADAR1 knockout (KO) cell lines to explore ADAR1's function in liver cells and found that these cells experienced growth arrest and failed to recover after IFN treatment.
- * Analysis revealed significant changes in the transcriptome and translatome of the KO cells, particularly impacting RNA polymerase III transcription and small RNA levels, indicating ADAR1's vital role in small RNA metabolism and ribosome production.
Article Synopsis
- Translation is essential for development, particularly during the silenced transcription phase of oocytes and early embryos.
- A genome-wide translatome analysis revealed that while global protein synthesis decreases during M-phases, the initiation and elongation of translation are activated, showing a dynamic shift in how specific mRNAs are translated.
- This study provides new insights into gene expression regulation during oocyte meiosis and the first two embryonic mitoses, marking a significant step towards understanding the molecular mechanisms of translation control in early development.
Article Synopsis
- Metagenomics allows scientists to analyze environmental DNA for insights into microbiomes, but eukaryotic organisms like fungi are often underrepresented due to challenges with intron-rich genes.
- Researchers developed a machine learning algorithm, SVMmycointron, to accurately predict fungal introns, improving gene annotations in metagenomic datasets by up to 9.1%.
- This tool enhances understanding of the role of fungi and other eukaryotes in microbiome function and is accessible for researchers working with metagenomics data.
Article Synopsis
- * The maturation-promoting factor (MPF), made up of CDK1 and Cyclin B1, is crucial for resuming meiosis, but the mechanisms behind its activation are not fully understood.
- * This study identifies SGK1, a specific kinase expressed in mouse oocytes, as a key player that influences CDK1 activation; inhibiting SGK1 delays meiotic progression, but introducing active CDK1 can reverse this effect, shedding light on how meiosis is regulated.