The α-mating factor secretion signals and endogenous signal peptides for recombinant protein secretion in Komagataella phaffii.

BACKGROUND: The budding yeast Komagataella phaffii (Pichia pastoris) is widely employed to secrete proteins of academic and industrial interest. For secretory proteins, signal peptides are the sorting signal to direct proteins from cytosol to extracellular matrix, and their secretion efficiency directly impacts the yields of the targeted proteins in fermentation broth. Although the α-mating factor (MF) secretion signal from S. cerevisiae, the most common and widely used signal sequence for protein secretion, works in most cases, limitation exists as some proteins cannot be secreted efficiently. As the optimal choice of secretion signals is often protein specific, more secretion signals need to be developed to augment protein expression levels in K. phaffii. RESULTS: In this study, the secretion efficiency of 40 α-MF secretion signals from various yeast species and 32 endogenous signal peptides from K. phaffii were investigated using enhanced green fluorescent protein (EGFP) as the model protein. All of the evaluated α-MF secretion signals successfully directed EGFP secretion except for the secretion signals of the yeast D. hansenii CBS767 and H. opuntiae. The secretion efficiency of α-MF secretion signal from Wickerhamomyces ciferrii was higher than that from S. cerevisiae. 24 out of 32 endogenous signal peptides successfully mediated EGFP secretion. The signal peptides of chr3_1145 and FragB_0048 had similar efficiency to S. cerevisiae α-MF secretion signal for EGFP secretion and expression. CONCLUSIONS: The screened α-MF secretion signals and endogenous signal peptides in this study confer an abundance of signal peptide selection for efficient secretion and expression of heterologous proteins in K. phaffii.

Isolation and evaluation of strong endogenous promoters for the heterologous expression of proteins in Pichia pastoris.

BACKGROUND: The heterologous expression of biosynthetic pathway genes for pharmaceutical or fine chemical production usually requires to express more than one gene in the host cells. In eukaryotes, the pathway flux is typically balanced by controlling the transcript levels of the genes involved. It is difficult to balance the stoichiometric fine-tuning of the reaction steps of the pathway by acting on one or two promoters. Furthermore, the promoter used should not be identical to avoid loss of inserted genes by recombination or dilute its transcription factors. RESULTS: Based on RNA-seq data, 18 candidate genes with the highest transcription levels at three carbon sources (glucose, glycerol and methanol) were selected and their promoter regions were isolated from GS115 genome. The performance of these promoters on the level of protein production was evaluated using LacZ and EGFP genes as the reporters, respectively. These isolated promoters all exhibited activity to express LacZ gene. Using LacZ as a reporter, of the 18 promoter candidates, 9 promoters showed higher expression levels for the reporter compare to pGAP, a strong promoter widely used for constitutive expression of heterologous proteins in Pichia pastoris. These promoters with high expression levels were further employed to evaluate secreted expression using EGFP as a reporter. 6 promoters exhibited stronger protein expression compare to pGAP. Interestingly, the protein expression driven by pFDH1 was slightly higher than that of commonly used pAOX1 at methanol, and methanol-induced expression of pFDH1 was not repressed by glycerol. CONCLUSION: The various promoters identified in this study could be used for heterologous expression of biosynthetic pathway genes for pharmaceutical or fine chemical production. the methanol-induced pFDH1 that is not repressed by glycerol is an attractive alternative to pAOX1 and may provide a novel way to produce heterologous proteins in Pichia pastoris.

Codon pair optimization (CPO): a software tool for synthetic gene design based on codon pair bias to improve the expression of recombinant proteins in Pichia pastoris.

BACKGROUND: Codon optimization is a common method to improve protein expression levels in Pichia pastoris and the current strategy is to replace rare codons with preferred codons to match the codon usage bias. However, codon-pair contexts have a profound effect on translation efficiency by influencing both translational elongation rates and accuracy. Until now, it remains untested whether optimized genes based on codon pair bias results in higher protein expression levels compared to codon usage bias. RESULTS: In this study, an algorithm based on dynamic programming was introduced to develop codon pair optimization (CPO) which is a software tool to provide simple and efficient codon pair optimization for synthetic gene design in Pichia pastoris. Two reporters (MT1-MMP E2C6 and ADAM17 A9B8 scFvs) were employed to test the effects of codon pair bias and CPO optimization on their protein expression levels. Four variants of MT1-MMP E2C6 and ADAM17 A9B8 for each were generated, one variant with the best codon-pair context, one with the worst codon-pair context, one with unbiased codon-pair context, and another optimized based on codon usage. The expression levels of variants with the worst codon-pair context were almost undetectable by Western blot and the variants with the best codon-pair context were expressed well. The expression levels on MT1-MMP E2C6 and ADAM17 A9B8 were more than five times and seven times higher in the optimized sequences based on codon-pair context compared to that based on codon usage, respectively. The results indicated that the codon-pair context-based codon optimization is more effective in enhancing expression of protein in Pichia pastoris. CONCLUSIONS: Codon-pair context plays an important role on the protein expression in Pichia pastoris. The codon pair optimization (CPO) software developed in this study efficiently improved the protein expression levels of exogenous genes in Pichia pastoris, suggesting gene design based on codon pair bias is an alternative strategy for high expression of recombinant proteins in Pichia pastoris.

The Expression and Prognostic Value of SUMO1-Activating Enzyme Subunit 1 and Its Potential Mechanism in Triple-Negative Breast Cancer.

Background: Triple-negative breast cancer (TNBC) is the most invasive and metastatic subtype of breast cancer. SUMO1-activating enzyme subunit 1 (SAE1), an E1-activating enzyme, is indispensable for protein SUMOylation. SAE1 has been found to be a relevant biomarker for progression and prognosis in several tumor types. However, the role of SAE1 in TNBC remains to be elucidated. Methods: In the research, the mRNA expression of SAE1 was analyzed via the cancer genome atlas (TCGA) and gene expression omnibus (GEO) database. Cistrome DB Toolkit was used to predict which transcription factors (TFs) are most likely to increase SAE1 expression in TNBC. The correlation between the expression of SAE1 and the methylation of SAE1 or quantity of tumor-infiltrating immune cells was further invested. Single-cell analysis, using CancerSEA, was performed to query which functional states are associated with SAE1 in different cancers in breast cancer at the single-cell level. Next, weighted gene coexpression network (WGCNA) was applied to reveal the highly correlated genes and coexpression networks of SAE1 in TNBC patients, and a prognostic model containing SAE1 and correlated genes was constructed. Finally, we also examined SAE1 protein expression of 207 TNBC tissues using immunohistochemical (IHC) staining. Results: The mRNA and protein expression of SAE1 were increased in TNBC tissues compared with adjacent normal tissues, and the protein expression of SAE1 was significantly associated with overall survival (OS) and disease-free survival (DFS). Correlation analyses revealed that SAE1 expression was positively correlated with forkhead box M1 (FOXM1) TFs and negatively correlated with SAE1 methylation site (cg14042711) level. WGCNA indicated that the genes coexpressed with SAE1 belonged to the green module containing 1,176 genes. Through pathway enrichment analysis of the module, 1,176 genes were found enriched in cell cycle and DNA repair. Single-cell analysis indicated that SAE1 and its coexpression genes were associated with cell cycle, DNA damage, DNA repair, and cell proliferation. Using the LASSO COX regression, a prognostic model including SAE1 and polo-like kinase 1 (PLK1) was built to accurately predict the likelihood of DFS in TNBC patients. Conclusion: In conclusion, we comprehensively analyzed the mRNA and protein expression, prognosis, and interaction genes of SAE1 in TNBC and constructed a prognostic model including SAE1 and PLK1. These results might be important for better understanding of the role of SAE1 in TNBC. In addition, DNA methyltransferase and TFs inhibitor treatments targeting SAE1 might improve the survival of TNBC patients.