RESUMEN
The study reports the exploration of the transcriptome landscape of the red oleaginous yeast Rhodotorula mucilaginosa IIPL32 coinciding with the fermentation kinetics of the yeast cultivated in a two-stage fermentation process to exploit the time-series approach to get the complete transcripts picture and reveal the persuasive genes for fatty acid and terpenoid synthesis. The finding displayed the molecular drivers with more than 2-fold upregulation in the nitrogen-limited stage than in the nitrogen-excess stage. The rate-limiting diphosphomevalonate decarboxylase, acetylCoA-citrate lyase, and acetyl-CoA C-acetyltransferase were significant in controlling the metabolic flux in the synthesis of reduced compounds, and acetoacetyl-CoA synthase, 3-ketoacyl-acyl carrier-protein reductase, and ß-subunit enoyl reductase catalyze the key starting steps of lipids or terpenoid synthesis. The last two catalyze essential reduction steps in fatty acid synthesis. These enzymes would be the prime targets for the metabolic engineering of the oleaginous yeast for enhanced fatty acids and terpenoid production.
Asunto(s)
Rhodotorula , Rhodotorula/genética , Rhodotorula/metabolismo , Glicerol/metabolismo , Transcriptoma/genética , Carotenoides/metabolismo , Levaduras/genética , Levaduras/metabolismo , Ácidos Grasos/metabolismo , Oxidorreductasas/metabolismo , Nitrógeno/metabolismoRESUMEN
History of metabolism originates with yeast making bread. In fact, study based on "Yeast" was so crucial in the development of the field of biochemistry that the word "enzyme" is derived from the Greek word meaning leavened (yeast). Yeast has always been a point of interest as a eukaryotic model system to demonstrate the metabolites and their function. In recent times their metabolites are widely studied to predict their role in various pathways. Many traditional and analytical techniques have been employed, but its study through metabolomics is of recent interest in research. The present review focuses on details about yeast metabolomics based on preliminary research on various analytical techniques along with computational approaches. The review also aimed to highlight machine learning and various inceptions of yeast metabolomics.