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Perecin Nociti, R.

Publications and source records attributed to Perecin Nociti, R..

3 recordsLinked to original sources

Artificial environment impact: O2 concentration changes between IVM and IVF alter embryo production, metabolism, and epigenetic marks

Creating an optimal in vitro cell culture environment requires careful simulation of all critical components, especially the gaseous atmosphere. Although it is well-documented that embryonic culture under low oxygen tension promotes embryonic development, little is known about the effect of changes in in vitro maturation (IVM) and fertilization (IVF) on the epigenome. This study explores the role of oxygen tension variation in the early stages of in vitro production of bovine embryos and its impact on oxidative stress and epigenetic remodeling. We initially validated our system by scrutinizing the epigenetic effects on bovine fibroblasts. We observed that cell cultures under 20% O2 exhibited reduced H3K9me2 levels in early passages, which stabilized with prolonged cultivation and elevated gene expression of HIF2a and KDM5C. Our results reveal that oocytes maturing in 20% O2 environments have heightened levels of reactive oxygen species (ROS) and glutathione (GSH), whereas blastocyst embryos maturing under reduced oxygen tension exhibit increased oxidative stress markers (NRF2, SOD1, SOD2), with upregulated transcripts observed in epigenetic remodelers (KDM5A, TET1). Elevated O2 levels in both IVM and IVF processes showcase improved embryo production. Maintaining consistent O2 levels at either 5% or 20% between IVM and IVF results in heightened GSH, reduced ROS, and increased levels of H3K9me2/3 in embryos. Finally, distinct DNA methylation patterns emerge, indicating higher levels in groups matured under low O2 tension and increased DNA hydroxymethylation in groups fertilized under low O2 tension. In conclusion, our comprehensive investigation underscores the critical role of oxygen concentration in shaping the epigenetic landscape during the early stages of in vitro culture. These findings provide valuable insights for optimizing conditions in assisted reproductive technologies.

developmental biology↗

The central role of pyruvate metabolism on the epigenetic and molecular maturation of bovine cumulus-oocytes complexes.

Pyruvate, the end-product of glycolysis in aerobic conditions, is produced by cumulus cells, and is converted in Acetyl-CoA into the mitochondria of both cumulus cells (CCs) and oocytes as a master fuel input for the tricarboxylic acid cycle (TCA). The citrate generated in the TCA cycle can be directed to the cytoplasm and converted back to acetyl-CoA, being driven to lipid synthesis or, still, being used as the substrate for histones acetylation. This work aimed to verify the impact of pyruvate metabolism on the dynamic of lysine 9 histone 3 acetylation (H3K9ac) and RNA transcription in bovine cumulus-oocyte complexes during in vitro maturation (IVM). Bovine oocytes were IVM for 24h in three experimental groups: Control [IVM medium], sodium dichloroacetate [DCA, a stimulator of pyruvate oxidation in acetyl-CoA] or sodium iodoacetate [IA, a glycolysis inhibitor]. Our results show that both treatments change the metabolic profile of oocytes and CCs, stimulating the use of lipids for energy metabolism in the gamete. This leads to changes in the dynamics of H3K9ac during the IVM in both oocytes and CCs with impact on the synthesis of new transcripts in CCs. A total of 148 and 356 differentially expressed genes were identified in DCA and IA oocytes groups, respectively, when compared to the control group. In conclusion, disorders in pyruvate metabolism during maturation stimulate the beta-oxidation pathway, altering the mitochondrial metabolism, with consequences for the mRNA content of bovine oocytes.

molecular biology↗

CeTF: an R package to Coexpression forTranscription Factors using Regulatory ImpactFactors (RIF) and Partial Correlation andInformation (PCIT) analysis

SummaryFinding meaningful gene-gene associations and the main Transcription Factors (TFs) in co-expression networks is one of the most important challenges in gene expression data mining. CeTF is an R package that integrates the Partial Correlation with Information Theory (PCIT) and Regulatory Impact Factors (RIF) algorithms applied to gene expression data from microarray, RNA-seq, or single-cell RNA-seq platforms. This approach allows identifying the transcription factors most likely to regulate a given network in different biological systems -- for example, regulation of gene pathways in tumor stromal cells and tumor cells of the same tumor. This pipeline can be easily integrated into the high-throughput analysis. AvailabilityCeTF is available as R package in Bioconductor (https://bioconductor.org/packages/CeTF), GitHub (https://github.com/cbiagii/CeTF) and as docker image (https://hub.docker.com/r/biagii/cetf). More information on how to use the package can be found in the Supplemental File 1.

bioinformatics↗