An adaptable in silico ensemble model of the arachidonic acid cascade.

Eicosanoids are a family of bioactive lipids, including derivatives of the ubiquitous fatty acid arachidonic acid (AA). The intimate involvement of eicosanoids in inflammation motivates the development of predictive in silico models for a systems-level exploration of disease mechanisms, drug development and replacement of animal models. Using an ensemble modelling strategy, we developed a computational model of the AA cascade. This approach allows the visualisation of plausible and thermodynamically feasible predictions, overcoming the limitations of fixed-parameter modelling. A quality scoring method was developed to quantify the accuracy of ensemble predictions relative to experimental data, measuring the overall uncertainty of the process. Monte Carlo ensemble modelling was used to quantify the prediction confidence levels. Model applicability was demonstrated using mass spectrometry mediator lipidomics to measure eicosanoids produced by HaCaT epidermal keratinocytes and 46BR.1N dermal fibroblasts, treated with stimuli (calcium ionophore A23187), (ultraviolet radiation, adenosine triphosphate) and a cyclooxygenase inhibitor (indomethacin). Experimentation and predictions were in good qualitative agreement, demonstrating the ability of the model to be adapted to cell types exhibiting differences in AA release and enzyme concentration profiles. The quantitative agreement between experimental and predicted outputs could be improved by expanding network topology to include additional reactions. Overall, our approach generated an adaptable, tuneable ensemble model of the AA cascade that can be tailored to represent different cell types and demonstrated that the integration of in silico and in vitro methods can facilitate a greater understanding of complex biological networks such as the AA cascade.

Defining informative priors for ensemble modeling in systems biology.

Ensemble modeling in molecular systems biology requires the reproducible translation of kinetic parameter data into informative probability distributions (priors), as well as approaches that sample parameters from these distributions without violating the thermodynamic consistency of the overall model. Although a number of pioneering frameworks for ensemble modeling have been published, the issue of generating informative priors has not yet been addressed. Here, we present a protocol that aims to fill this gap. This protocol discusses the collection of parameter values from a diverse range of sources (literature, databases and experiments), assessment of their plausibility, and creation of log-normal probability distributions that can be used as informative priors in ensemble modeling. Furthermore, the protocol enables sampling from the generated distributions while maintaining thermodynamic consistency. Once all parameter values have been retrieved from literature and databases, the protocol can be implemented within ~5-10 min per parameter. The aim of this protocol is to facilitate the design and use of informative distributions for ensemble modeling, especially in fields such as synthetic biology and systems medicine.

Metabolism of steroidal lactones by the fungus Corynespora cassiicola CBS 161.60 results in a mechanistically unique intramolecular ring-D cyclization resulting in C-14 spiro-lactones.

The fungus Corynespora cassiicola metabolises exogenous steroids in a unique and highly specific manner. Central to this, is the ability of this organism to functionalise substrates (androgens, progestogens) at the highly stereochemically hindered 8ß-position of the steroid nucleus. A recent study has identified that 8ß-hydroxylation occurs through inverted binding in a 9α-hydroxylase. In order to discern the metabolic fate of more symmetrical molecules, we have investigated the metabolism of a range of steroidal analogues functionalised with ring-D lactones, but differing in their functional group stereochemistry at carbon-3. Remarkably, the 3α-functionalised steroidal lactones underwent a mechanistically unique two step intramolecular cyclisation resulting in the generation of a ring-D spiro-carbolactone. This rapid rearrangement initiated with hydroxylation at carbon 14 followed by transesterification, resulting in ring contraction with formation of a butyrolactone at carbon-14. Remarkably this rearrangement was found to be highly dependent on the stereochemistry at carbon-3, with the ß-analogues only undergoing 9α-hydroxylation. The implications of these findings and their mechanistic bases are discussed.