Mechanistic Modelling and Bayesian Inference Elucidates the Variable Dynamics of Double-Strand Break Repair

Abstract

DNA double-strand breaks are lesions that form during metabolism, DNA replication and exposure to mutagens. When a double-strand break occurs one of a number of repair mechanisms is recruited, all of which have differing propensities for mutational events. Despite DNA repair being of crucial importance, the relative contribution of these mechanisms and their regulatory interactions remain to be fully elucidated. Understanding these mutational processes will have a profound impact on our knowledge of genomic instability, with implications across health, disease and evolution. Here we present a new method to model the combined activation of non-homologous end joining, single strand annealing and alternative end joining, following exposure to ionising radiation. We use Bayesian statistics to integrate eight biological data sets of double-strand break repair curves under varying genetic knockouts and confirm that our model is predictive by re-simulating and comparing to additional data. Analysis of the model suggests that there are at least three disjoint modes of repair, which we assign as fast, slow and intermediate. Our results show that when multiple data sets are combined, the rate for intermediate repair is variable amongst genetic knockouts. Further analysis suggests that the ratio between slow and intermediate repair depends on the presence or absence of DNA-PKcs and Ku70, which implies that non-homologous end joining and alternative end joining are not independent. Finally, we consider the proportion of double-strand breaks within each mechanism as a time series and predict activity as a function of repair rate. We outline how our insights can be directly tested using imaging and sequencing techniques and conclude that there is evidence of variable dynamics in alternative repair pathways. Our approach is an important step towards providing a unifying theoretical framework for the dynamics of DNA repair processes.

Ionizing Radiation and Complex DNA Damage: Quantifying the Radiobiological Damage Using Monte Carlo Simulations

“…Woods et al [159] presented a new method to model the NHEJ, single strand annealing, and alternative end-joining mechanisms that are initiated after exposure to IR. The model was validated using biological experimental datasets and Bayesian statistics.…”

Kinetics and Fidelity of the Repair of Cas9-Induced Double-Strand DNA Breaks

“…Time courses of such bulk measurements in mammalian cells have consistently shown that DSBs are generally repaired with a half-life of 10–60 min ( DiBiase et al., 2000 , Metzger and Iliakis, 1991 , Núñez et al., 1995 , Schwartz et al., 1988 , Stenerlöw et al., 2003 , Wang et al., 2006 ). Computational modeling of such datasets has indicated that a small sub-fraction of DSBs is rejoined more slowly, over several hours ( Cucinotta et al., 2008 , Metzger and Iliakis, 1991 , Núñez et al., 1995 , Woods and Barnes, 2016 ). A-EJ pathways are thought to be largely responsible for this population of more slowly repaired DSBs ( Sharma et al., 2015 , Wang et al., 2003 ).…”

Modeling the architecture of the regulatory system controlling methylenomycin production in Streptomyces coelicolor

“…ABC-SysBio convergence is dependent on the sequential satisfaction of a predefined series of decreasing error thresholds by a predefined number of solutions (see Methods ). Here, the number of solutions required to satisfy each error threshold is 500 [ 24 ] in order to reduce the time frame required for convergence; the number of models subject to selection coupled with the inability to parallelize the process presents a particularly time consuming computational workload. The user-defined error function designed to measure the accuracy of simulations takes the mean absolute value of the difference between model outputs and data values: …”