Metabolic regulatory network kinetic modeling with multiple isotopic tracers for iPSCs

The rapidly expanding market for regenerative medicines and cell therapies highlights the need to advance the understanding of cellular metabolisms and improve the prediction of cultivation production process for human induced pluripotent stem cells (iPSCs). In this paper, a metabolic kinetic model was developed to characterize the underlying mechanisms of iPSC culture process, which can predict cell response to environmental perturbation and support process control. This model focuses on the central carbon metabolic network, including glycolysis, pentose phosphate pathway, tricarboxylic acid cycle, and amino acid metabolism, which plays a crucial role to support iPSC proliferation. Heterogeneous measures of extracellular metabolites and multiple isotopic tracers collected under multiple conditions were used to learn metabolic regulatory mechanisms. Systematic cross-validation confirmed the model's performance in terms of providing reliable predictions on cellular metabolism and culture process dynamics under various culture conditions. Thus, the developed mechanistic kinetic model can support process control strategies to strategically select optimal cell culture conditions at different times, ensure cell product functionality, and facilitate large-scale manufacturing of regenerative medicines and cell therapies.

A comprehensive metabolic map reveals major quality regulations in red-flesh kiwifruit (Actinidia chinensis)

Kiwifruit (Actinidia chinensis) is one of the popular fruits world-wide, and its quality is mainly determined by key metabolites (sugars, flavonoids, and vitamins). Previous works on kiwifruit are mostly done via a single omics approach or involve only limited metabolites. Consequently, the dynamic metabolomes during kiwifruit development and ripening and the underlying regulatory mechanisms are poorly understood. In this study, using high-resolution metabolomic and transcriptomic analyses, we investigated kiwifruit metabolic landscapes at 11 different developmental and ripening stages and revealed a parallel classification of 515 metabolites and their co-expressed genes into 10 distinct metabolic vs gene modules (MM vs GM). Through integrative bioinformatics coupled with functional genomic assays, we constructed a global map and uncovered essential transcriptomic and transcriptional regulatory networks for all major metabolic changes that occurred throughout the kiwifruit growth cycle. Apart from known MM vs GM for metabolites such as soluble sugars, we identified novel transcription factors that regulate the accumulation of procyanidins, vitamin C, and other important metabolites. Our findings thus shed light on the kiwifruit metabolic regulatory network and provide a valuable resource for the designed improvement of kiwifruit quality.