Investigating the effect of carbon source on rabies virus glycoprotein production inPichia pastorisby a transcriptomic approach

Abstract

Several factors affect protein expression in Pichia pastoris, one among them is the carbon source. In this work, we studied the effect of this factor on the expression level of rabies virus glycoprotein (RABV‐G) in two recombinant clones harboring seven copies of the gene of interest. The expression was driven either by the constitutive glyceraldehyde‐3‐phosphate dehydrogenase (GAP) promoter or the inducible alcohol oxidase1 ( AOX1) promoter. Clones were compared in terms of cell physiology and carbon source metabolism. The transcription levels of 16 key genes involved in the central metabolic pathway, the methanol catabolism, and the oxidative stress were investigated in both clones. Cell size, as a parameter reflecting cell physiological changes, was also monitored. Our results showed that when glucose was used as the sole carbon source, large cells were obtained. Transcript levels of the genes of the central metabolic pathway were also upregulated, whereas antioxidative gene transcript levels were low. By contrast, the use of methanol as a carbon source generated small cells and a shift in carbon metabolism toward the dissimilatory pathway by the upregulation of formaldehyde dehydrogenase gene and the downregulation of those of the central metabolic. These observations are in favor of the use of glucose to enhance the expression of RABV‐G in P. pastoris.

Methanol addition after glucose depletion improves rPOXA 1B production under the pGap in P. pastoris X33: breaking the habit

“…Biomass production only doubled at the end of culture (A, B, C and D with methanol), depending on culture media composition ( Table 3). In contrast, depending on culture media composition, volumetric enzyme activity (U L −1 ) increased during methanol supplementation, ranging between 3339.02 ± 64.36 and 14,868.06 ± 461.58 U L −1 at 192 h, suggesting methanol addition was less critical for cell growth (Table 3), as has been previously investigated [7]. However, its main importance is based on the fact that methanol metabolism generates formaldehyde, which is transferred to xylulose-5-phosphate (Xu5P), generating G3P and DHA.…”

“…Azoun and Kallel [7] studied by a transcriptomic approach in P. pastoris the effect a carbon source would have on rabies virus glycoprotein (RABV-G) production. Their results demonstrated the transcription levels of genes involved in central metabolism were upregulated when glucose was used as a carbon source (pGap-RABV-G), while the transcription levels of anti-oxidative genes were lower.…”

“…This demonstrated that methanol stimulates pGap, thereby increasing the recombinant enzyme production under the control of this promoter. Furthermore, pGap and pAOX1 efficiencies have been previously addressed [7,69,76]; however, other authors have obtained contradictory results [9,57,66], suggesting that many other uncontrolled factors can interfere with recombinant protein expression, such as the nature of the protein and intrinsic characteristics [10].…”

“…Successful strategies have been used to improve recombinant protein expression under the control of pAOX1 (Mut s phenotype, slow methanol utilization) and/ or the pGap promoter. For example, integration of several gene copies within P. pastoris' genome [7], culture with mixed-carbon sources, such as glucose/methanol [44], glycerol/methanol [30,73] or sorbitol/methanol [31,53] under pAOX1 expression control. Additional strategies include the combined use of pGap and pAOX1 within the same strain [71] to induce pAOX1 after glucose depletion, and a strategy also used to sequentially express and recover the cloned protein separately (extraand intracellular), [16,71,72].…”

Transcriptomic Analysis of Pichia pastoris (Komagataella phaffii) GS115 During Heterologous Protein Production Using a High-Cell-Density Fed-Batch Cultivation Strategy

“…Furthermore, increasing productivity during scale-up of processes largely depends on trial and Abbreviations: 6PG, gluconate-6P; CTS, citrate synthase; DAK, triose/dihydroxyacetone kinase; DAS, dihydroxyacetone synthase; DHA, dihydroxyacetone; DHAP, dihydroxyacetone-P; DLD, dihydrolipoamide dehydrogenase; E4P, erytgrose-4P; ENOI, enolase I; F1,6BP, fructose-1, 6-P2; F6P, fructose-6P; FBAII, fructose-bisphosphate aldolase, class II; FBPI, fructose-1,6-bisphosphatase I; FCH, S-formylglutathione hydrolase; FDH, formate dehydrogenase; FLD1, S-(hydroxymethyl)glutathione dehydrogenase; Form, formaldehyde; FUM, fumarate; G1,3P, glycerate-1,3P2; G2P, glycerate-2P; G3P, glycerate-3P; G6P, glucose-6P; GAP, glyceraldehyde-3P; GAPD, glyceraldehyde 3-phosphate dehydrogenase; GPI, glucose-6-phosphate isomerase; GS-CH 2 OH, S-hydroxymethylglutathione; GS-CHO, S-formylglutathione; ISO, isocitrate; MAL, malate; MDH, malate dehydrogenase; ODE, 2-oxoglutarate dehydrogenase E2; OXA, oxaloacetate; OXAL, oxalosuccinate; PDE, pyruvate dehydrogenase E; PEP, phosphoenolpyrvate; PEX, peroxisomal; PGK, phosphoglycerate kinase; R5P, ribose-5P; RKI, ribose-5-phosphate ketol-isomerase; Rul5P, ribulose-5P; S7P, sedoheptulose-7p; SCS1, succinyl-CoA synthetase 1; SCS2, succinyl-CoA synthetase 2; SDH, succinate dehydrogenase; SUC, succinate; TAL, transaldolase; TK, transketolase; X5P, xylulose-5P. error; process optimization has been somewhat refined through the deployment of multifactorial experimental design (Ben Azoun and Kallel, 2017).…”