Computational Model Reveals How DNA Replication Adapts to Cellular Stress
Researchers developed a Monte Carlo simulation framework to model how eukaryotic DNA replication remains stable under thermal, chemical, and genotoxic stress in yeast cells. The model incorporates realistic variations in replication fork speeds and cellular resource availability, validated against experimental data. The findings explain observed patterns in replication timing across multiple organisms and could inform understanding of stress-induced genomic instability.
Scientists created a lattice-based stochastic computational model to simulate whole-genome DNA replication in Saccharomyces cerevisiae at single base-pair resolution, accounting for probabilistic origin firing, variable replication fork speeds, and time-dependent availability of cellular replication machinery. The model was quantitatively benchmarked against experimental replication profiles before being applied to stress conditions. The analysis reveals that heterogeneity in replication fork speeds explains the observed Erlang-distributed S-phase durations and rare, prolonged replication events previously documented in bacteria and human cells. The framework successfully predicts non-monotonic thermal responses, power-law scaling under hydroxyurea-induced stress, and replication dynamics under various genotoxic conditions using only two effective parameters.
What's missing
The study's own limitations and open questions are not detailed in the abstract provided, such as the scope of stress conditions tested, applicability to other organisms beyond those mentioned, or validation against additional experimental datasets.
What different sources said
- arXiv q-bioCenter
DNA Replication under Thermal, Chemical, and Genotoxic Stress
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