The main theme of this thesis was to explore the regulatory landscape of CAM using systems biology approaches. The scope of the regulatory landscape was drawn around the mesophyll metabolism of the dicotyledonous obligate CAM genus, Kalanchoe, even though the computational frameworks that had been developed here can also be applied to other species.

The first result chapter presented the Ordinary Differential Equation modelling of Crassulacean acid metabolism (Chapter 2) which was developed to capture the classical gas-exchange patterns as well as the responses to perturbation conditions. The findings suggested that the model was sufficient to explain the classical gas-exchange pattern whilst was also responsive to the perturbations. Nonetheless, the model parameters which represented the protein activities indirectly captured the upstream regulatory controls. Thus, the following result chapter shifted the focus to explore a more upstream level of regulations at the level of gene expression.

The second result chapter presented the Gene Regulatory Network Inference of Kalanchoe fedtschenkoi (Chapter 3). This chapter identified potential transcriptional regulators on different functional compartments of CAM including the following: Carboxylation subnetwork, Decarboxylation subnetwork, Circadian subnetwork and Stomatal subnetwork. This chapter highlighted the potential transcriptional regulators of key CAM genes, for example, PEPCarboxylase (PEPC), PEPCkinase (PPCK), pyruvate orthophosphate dikinase (PPDK), and pyruvate orthophosphate dikinase regulatory protein (PPDK-RP). Overall, the Gene Regulatory Network Inference provided the ranking of the potential transcriptional regulatory candidates on CAM genes. Hence, a reasonable step forward would be to probe for direct binding evidence through molecular approaches. The first step towards accessing the chromatin landscape with ATAC-sequencing technique was the Nuclei isolation followed by the flow cytometry separation technique for Kalanchoe fedtschenkoi which was presented as the final result chapter (Chapter 4).

To conclude, this thesis showed that the minimal mechanistic model at the level of protein functions can capture CAM gas-exchange patterns under various scenarios. Subsequently, a more upstream level of regulatory controls was explored across the genome with the Gene Regulatory Network Inference method. The key findings highlighted the potential transcriptional regulations of key CAM genes in addition to the regulations at the level of protein activities. Finally, the nuclei isolation was conducted as an initial step for a future molecular experiment to probe for chromatin accessibility for the CAM model species.