Branch point control at malonyl-CoA node: A computational framework to uncover the design principles of an ideal genetic-metabolic switch

Living organism is an intelligent system encoded by hierarchically-organized information to perform precisely-controlled biological functions. Biophysical models are important tools to uncover the design rules underlying complex genetic-metabolic circuit interactions. Based on a previously engineered synthetic malonyl-CoA switch (Xu et al, PNAS 2014), we have formulated nine differential equations to unravel the design principles underlying an ideal metabolic switch to improve fatty acids production in E. coli. By interrogating the physiologically accessible parameter space, we have determined the optimal controller architecture to configure both the metabolic source pathway and metabolic sink pathway. We determined that low protein degradation rate, medium strength of metabolic inhibitory constant, high metabolic source pathway induction rate, strong binding affinity of the transcriptional activator toward the metabolic source pathway, weak binding affinity of the transcriptional repressor toward the metabolic sink pathway, and a strong cooperative interaction of transcriptional repressor toward metabolic sink pathway benefit the accumulation of the target molecule (fatty acids). The target molecule (fatty acid) production is increased from 50% to 10-folds upon application of the autonomous metabolic switch. With strong metabolic inhibitory constant, the system displays multiple steady states. Stable oscillation of metabolic intermediate is the driving force to allow the system deviate from its equilibrium state and permits bidirectional ON-OFF gene expression control, which autonomously compensates enzyme level for both the metabolic source and metabolic sink pathways. The computational framework may facilitate us to design and engineer predictable genetic-metabolic switches, quest for the optimal controller architecture of the metabolic source/sink pathways, as well as leverage autonomous oscillation as a powerful tool to engineer cell function.

Metabotyping: A New Approach to Investigate Rapeseed (Brassica napus L.) Genetic Diversity in the Metabolic Response to Clubroot Infection

Clubroot disease affects all Brassicaceae spp. and is caused by the obligate biotroph pathogen Plasmodiophora brassicae. The development of galls on the root system is associated with the establishment of a new carbon metabolic sink. Here, we aimed to deepen our knowledge of the involvement of primary metabolism in the Brassica napus response to clubroot infection. We studied the dynamics and the diversity of the metabolic responses to the infection. Root system metabotyping was carried out for 18 rapeseed genotypes displaying different degrees of symptom severity, under inoculated and noninoculated conditions at 42 days postinoculation (dpi). Clubroot susceptibility was positively correlated with clubroot-induced accumulation of several amino acids. Although glucose and fructose accumulated in some genotypes with minor symptoms, their levels were negatively correlated to the disease index across the whole set of genotypes. The dynamics of the metabolic response were studied for the susceptible genotype ‘Yudal,’ which allowed an “early” metabolic response (established from 14 to 28 dpi) to be differentiated from a “late” response (from 35 dpi). We discuss the early accumulation of amino acids in the context of the establishment of a nitrogen metabolic sink and the hypothetical biological role of the accumulation of glutathione and S-methylcysteine.