LB64
Using mathematical modelling to investigate the mechanisms regulating hypoxia-mediated DNA damage response
Rehan Ali1, Zuzana Benkocova1, Isabel Pires1, Alex Fletcher1, Helen Byrne2, Michael Brady1, Martin Christlieb1, Ester Hammond1
1University of Oxford, UK; 2University of Nottingham, UK
Background
Hypoxic conditions (pO2 < 0.02%) are known to induce a DNA
damage response mediated by both the ATR and ATM PI3 kinases (typified by the appearance
of γH2AX foci). However this occurs in the absence of physical DNA damage
in S-phase cells (Hammond et al, J. Biol. Chem (2003), 278:12207-13). Our data
suggests that this is due to replication fork stalling, but the precise
mechanism for this is unknown. Mathematical modelling has enabled us to gain
greater understanding of these processes and to generate testable hypotheses.
Method
A model of the possible events leading to formation of γH2AX foci was
developed. The model was used to produce a set of ordinary differential
equations whose behaviour was analysed for the presence of any trends that
matched the observed behaviour of the biological pathway.
Results
The model demonstrates that at a critical oxygen threshold, the stability of
the steady state changes. The stable system is characterised by high oxygen
levels which result in low levels of ssDNA, RPA and γH2AX. The unstable
system represents low oxygen levels which result in ssDNA levels increasing
unchecked, and levels of RPA and γH2AX increasing dramatically. Although
the critical oxygen level cannot yet be determined precisely, due to lack of
complete rate constant information, it is possible to show that it is of the
same order of magnitude as the experimentally observed value (0.02%). Significantly
the model predicts an oxygen-dependent step prior to the stalling of DNA
Polymerase (Pol). We investigated the activity of ribonucleotide reductase
under hypoxic conditions and found that nucleotide production is abrogated
under these conditions, which also induce replication arrest. Time dependent
model simulations are consistent with dynamic changes in metabolite levels
obtained from western blots, immunofluorescence microscopy assays and HPLC.
Conclusion
Mathematical modelling can be used to integrate multiple experimental
sources and generate predictions which can guide future experimental work.
Here, it has been used to predict that hypoxia-mediated replication fork
stalling is due to loss of a substrate, which has been determined via HPLC analysis
to be dNTPs. We intend to extend the model to incorporate further downstream
events, thus improving its predictive ability.
