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Pichia pastoris growth-coupled heme biosynthesis analysis using metabolic modelling.

ABSTRACT: Soy leghemoglobin is one of the most important and key ingredients in plant-based meat substitutes that can imitate the colour and flavour of the meat. To improve the high-yield production of leghemoglobin protein and its main component-heme in the yeast Pichia pastoris, glycerol and methanol cultivation conditions were studied. Additionally, in-silico metabolic modelling analysis of growth-coupled enzyme quantity, suggests metabolic gene up/down-regulation strategies for heme production. First, cultivations and metabolic modelling analysis of P. pastoris were performed on glycerol and methanol in different growth media. Glycerol cultivation uptake and production rates can be increased by 50% according to metabolic modelling results, but methanol cultivation-is near the theoretical maximum. Growth-coupled metabolic optimisation results revealed the best feasible upregulation (33 reactions) (1.47% of total reactions) and 66 downregulation/deletion (2.98% of total) reaction suggestions. Finally, we describe reaction regulation suggestions with the highest potential to increase heme production yields.

SUBMITTER: Pentjuss A

PROVIDER: S-EPMC10516909 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Pichia pastoris growth-coupled heme biosynthesis analysis using metabolic modelling.

Pentjuss Agris A Bolmanis Emils E Suleiko Anastasija A Didrihsone Elina E Suleiko Arturs A Dubencovs Konstantins K Liepins Janis J Kazaks Andris A Vanags Juris J

Scientific reports 20230922 1

Soy leghemoglobin is one of the most important and key ingredients in plant-based meat substitutes that can imitate the colour and flavour of the meat. To improve the high-yield production of leghemoglobin protein and its main component-heme in the yeast Pichia pastoris, glycerol and methanol cultivation conditions were studied. Additionally, in-silico metabolic modelling analysis of growth-coupled enzyme quantity, suggests metabolic gene up/down-regulation strategies for heme production. First, ...[more]

PMID: 37739976

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Project description:Over the past three decades, due to the universal application of Pichia yeast in the fermentation industry as well as the establishment of Pichia pastoris fermentation process for more than 30 years, the technology of the whole process has become very mature and has now reached a stagnated period of growth. However, studies and research conducted on the genomics of the classic fermentation process and the uncovering of the biological phenomena in the fermentation process from the point of view of high-throughput gene or protein is still in its early stages, and there is still insufficient data within this field. First, in collaboration with Agilent Company, we designed and prepared an expression microarray that could be used for the detection of Pichia pastoris transcriptomics. The transcriptomic changes in the five key technology steps (time points), during the fermentation process of Pichia pastoris would then be detected with the aid of an expression microarray. The five key steps of technology described above formed two important biological processes, namely, the limiting carbon source replacement and secondly, the fermentative production of exogenous proteins. The biological phenomena involved in these two processes were displayed and analyzed at the transcriptional level. In addition to this, with regard to the most important function in the fermentation process of Pichia pastoris, oxid-reduction, the metabolic drift process was analyzed and the important genes that might dominate the changes in the metabolic flux were discovered creatively by using the function tree method in this paper. This study was undertaken from the point of view of the transcriptome and the biological phenomena in the fermemntation process of Pichia pastoris. Both of which, were thoroughly explained during this study. The hope is for many more researchers to optimize the strain fermentation process, to produce proteins at the genetic level, as well as providing and obtaining new perspectives and detailed scientific data for the continued development within this field.

Project description:BackgroundPichia pastoris has been recognized as an effective host for recombinant protein production. A number of studies have been reported for improving this expression system. However, its physiology and cellular metabolism still remained largely uncharacterized. Thus, it is highly desirable to establish a systems biotechnological framework, in which a comprehensive in silico model of P. pastoris can be employed together with high throughput experimental data analysis, for better understanding of the methylotrophic yeast's metabolism.ResultsA fully compartmentalized metabolic model of P. pastoris (iPP668), composed of 1,361 reactions and 1,177 metabolites, was reconstructed based on its genome annotation and biochemical information. The constraints-based flux analysis was then used to predict achievable growth rate which is consistent with the cellular phenotype of P. pastoris observed during chemostat experiments. Subsequent in silico analysis further explored the effect of various carbon sources on cell growth, revealing sorbitol as a promising candidate for culturing recombinant P. pastoris strains producing heterologous proteins. Interestingly, methanol consumption yields a high regeneration rate of reducing equivalents which is substantial for the synthesis of valuable pharmaceutical precursors. Hence, as a case study, we examined the applicability of P. pastoris system to whole-cell biotransformation and also identified relevant metabolic engineering targets that have been experimentally verified.ConclusionThe genome-scale metabolic model characterizes the cellular physiology of P. pastoris, thus allowing us to gain valuable insights into the metabolism of methylotrophic yeast and devise possible strategies for strain improvement through in silico simulations. This computational approach, combined with synthetic biology techniques, potentially forms a basis for rational analysis and design of P. pastoris metabolic network to enhance humanized glycoprotein production.

Dataset Information

Pichia pastoris growth-coupled heme biosynthesis analysis using metabolic modelling.

Publications

Pichia pastoris growth-coupled heme biosynthesis analysis using metabolic modelling.

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