Evolution of opposing regulatory interactions underlies the emergence of eukaryotic cell cycle checkpoints

A comprehensive review of computational cell cycle models in guiding cancer treatment strategies

This article reviews the current knowledge and recent advancements in computational modeling of the cell cycle. It offers a comparative analysis of various modeling paradigms, highlighting their unique strengths, limitations, and applications. Specifically, the article compares deterministic and stochastic models, single-cell versus population models, and mechanistic versus abstract models. This detailed analysis helps determine the most suitable modeling framework for various research needs. Additionally, the discussion extends to the utilization of these computational models to illuminate cell cycle dynamics, with a particular focus on cell cycle viability, crosstalk with signaling pathways, tumor microenvironment, DNA replication, and repair mechanisms, underscoring their critical roles in tumor progression and the optimization of cancer therapies. By applying these models to crucial aspects of cancer therapy planning for better outcomes, including drug efficacy quantification, drug discovery, drug resistance analysis, and dose optimization, the review highlights the significant potential of computational insights in enhancing the precision and effectiveness of cancer treatments. This emphasis on the intricate relationship between computational modeling and therapeutic strategy development underscores the pivotal role of advanced modeling techniques in navigating the complexities of cell cycle dynamics and their implications for cancer therapy.

Multiwell-based G0-PCC assay for radiation biodosimetry

In cytogenetic biodosimetry, assessing radiation exposure typically requires over 48 hours for cells to reach mitosis, significantly delaying the administration of crucial radiation countermeasures needed within the first 24 hours post-exposure. To improve medical response times, we incorporated the G0-Premature Chromosome Condensation (G0-PCC) technique with the Rapid Automated Biodosimetry Tool-II (RABiT-II), creating a faster alternative for large-scale radiation emergencies. Our findings revealed that using a lower concentration of Calyculin A (Cal A) than recommended effectively increased the yield of highly-condensed G0-PCC cells (hPCC). However, integrating recombinant CDK1/Cyclin B kinase, vital for chromosome condensation, proved challenging due to the properties of these proteins affecting interactions with cellular membranes. Interestingly, Cal A alone was capable of inducing chromosome compaction in some G0 cells even in the absence of mitotic kinases, although these chromosomes displayed atypical morphologies. This suggests that Cal A mechanism for compacting G0 chromatin may differ from condensation driven by mitotic kinases. Additionally, we observed a correlation between radiation dose and extent of hPCC chromosome fragmentation, which allowed us to automate radiation damage quantification using a Convolutional Neural Network (CNN). Our method can address the need for a same-day cytogenetic biodosimetry test in radiation emergency situations.

Molecular Mechanism of Overcoming Host Resistance by the Target of Rapamycin Gene in Leptographium qinlingensis

Leptographium qinlingensis is a fungal symbiont of the Chinese white pine beetle (Dendroctonus armandi) and a pathogen of the Chinese white pine (Pinus armandii) that must overcome the terpenoid oleoresin defenses of host trees to invade and colonize. L. qinlingensis responds to monoterpene flow with abundant mechanisms that include the decomposing and use of these compounds as a nitrogen source. Target of Rapamycin (TOR) is an evolutionarily conserved protein kinase that plays a central role in both plants and animals through integration of nutrients, energies, hormones, growth factors and environmental inputs to control proliferation, growth and metabolism in diverse multicellular organisms. In this study, in order to explore the relationship between TOR gene and carbon sources, nitrogen sources, host nutrients and host volatiles (monoterpenoids) in L. qinlingensis, we set up eight carbon source treatments, ten nitrogen source treatments, two host nutrients and six monoterpenoids (5%, 10% and 20%) treatments, and prepared different media conditions. By measuring the biomass and growth rate of mycelium, the results revealed that, on the whole, the response of L. qinlingensis to nitrogen sources was better than carbon sources, and the fungus grew well in maltose (carbon source), (NH₄)₂C₂O₄ (inorganic nitrogen source), asparagine (organic nitrogen source) and P. armandii (host nutrient) versus other treatments. Then, by analyzing the relationship between TOR expression and different nutrients, the data showed that: (i) TOR expression exhibited negative regulation in response to carbon sources and host nutrition. (ii) The treatments of nitrogen sources and terpenoids had positively regulatory effects on TOR gene; moreover, the fungus was most sensitive to β-pinene and 3-carene. In conclusion, our findings reveal that TOR in L. qinlingensis plays a key role in the utilization of host volatiles as nutrient intake, overcoming the physical and chemical host resistances and successful colonization.