Metabolic engineering of "last-line antibiotic" colistin in Paenibacillus polymyxa.

Colistin, also known as polymyxin E, is a lipopeptide antibiotic used to treat infections caused by multidrug-resistant gram-negative bacteria. It is considered a "last-line antibiotic", but its clinical development is hindered by low titer and impurities resulting from the presence of diverse homologs in microbial fermentation. To ensure consistent pharmaceutical activity and kinetics, it is crucial to have high-purity colistin active pharmaceutical ingredient (API) in the pharmaceutical industry. This study focused on the metabolic engineering of a natural colistin producer strain to produce colistin with a high titer and purity. Guided by genome mining, we identified Paenibacillus polymyxa ATCC 842 as a natural colistin producer capable of generating a high proportion of colistin A. By systematically inactivating seven non-essential biosynthetic gene clusters (BGCs) of peptide metabolites that might compete precursors with colistin or inhibit colistin production, we created an engineered strain, P14, which exhibited an 82% increase in colistin titer and effectively eliminated metabolite impurities such as tridecaptin, paenibacillin, and paenilan. Additionally, we engineered the L-2,4-diaminobutyric acid (L-2,4-DABA) pathway to further enhance colistin production, resulting in the engineered strain P19, which boosted a remarkable colistin titer of 649.3 mg/L - a 269% improvement compared to the original strain. By concurrently feeding L-isoleucine and L-leucine, we successfully produced high-purity colistin A, constituting 88% of the total colistin products. This study highlights the potential of metabolic engineering in improving the titer and purity of lipopeptide antibiotics in the non-model strain, making them more suitable for clinical use. These findings indicate that efficiently producing colistin API in high purity directly from fermentation can now be achieved in a straightforward manner.

Systematic genetic modifications of cell wall biosynthesis enhanced the secretion and surface-display of polysaccharide degrading enzymes in Saccharomyces cerevisiae.

Saccharomyces cerevisiae is a robust cell factory to secrete or surface-display cellulase and amylase for the conversion of agricultural residues into valuable chemicals. Engineering the secretory pathway is a well-known strategy for overproducing these enzymes. Although cell wall biosynthesis can be tightly linked to the secretory pathway by regulation of all involved processes, the effect of its modifications on protein production has not been extensively studied. In this study, we systematically studied the effect of engineering cell wall biosynthesis on the activity of cellulolytic enzyme ß-glucosidase (BGL1) by comparing seventy-nine gene knockout S. cerevisiae strains and newly identified that inactivation of DFG5, YPK1, FYV5, CCW12 and KRE1 obviously improved BGL1 secretion and surface-display. Combinatorial modifications of these genes, particularly double deletion of FVY5 and CCW12, along with the use of rich medium, increased the activity of secreted and surface-displayed BGL1 by 6.13-fold and 7.99-fold, respectively. Additionally, we applied this strategy to improve the activity of the cellulolytic cellobiohydrolase and amylolytic α-amylase. Through proteomic analysis coupled with reverse engineering, we found that in addition to the secretory pathway, regulation of translation processes may also involve in improving enzyme activity by engineering cell wall biosynthesis. Our work provides new insight into the construction of a yeast cell factory for efficient production of polysaccharide degrading enzymes.

Knockdown of CLAUDIN-6 Inhibited Apoptosis and Induced Proliferation of Bovine Cumulus Cells.

This study aims to investigate the effects of CLAUDIN-6 (CLDN6) on cell apoptosis and proliferation of bovine cumulus cells (CCs). Immunofluorescence staining was used to localize CLDN6 protein in CCs. Three pairs of siRNA targeting CLDN6 and one pair of siRNA universal negative sequence as control were transfected into bovine CCs. Then, the effective siRNA was screened by real-time quantitative PCR (RT-qPCR) and Western blotting. The mRNA expression levels of apoptosis related genes (CASPASE-3, BAX and BCL-2) and proliferation related genes (PCNA, CDC42 and CCND2) were evaluated by RT-qPCR in CCs with CLDN6 knockdown. Cell proliferation, apoptosis and cell cycle were detected by flow cytometry with CCK-8 staining, Annexin V-FITC staining and propidium iodide staining, respectively. Results showed that the CLDN6 gene was expressed in bovine CCs and the protein was localized in cell membranes and cytoplasms. After CLDN6 was knocked down in CCs, the cell apoptosis rate significantly decreased and the pro-apoptotic genes BAX and CASPASE-3 were down-regulated significantly, whereas the anti-apoptotic gene BCL-2 was markedly up-regulated (p < 0.05). Additionally, CLDN6 knockdown significantly enhanced cell proliferation of CCs at 72 h after siRNA transfection. The mRNA levels of proliferation-related genes PCNA, CCND2 and CDC42 increased obviously in CCs with CLDN6 knockdown (p < 0.05). After CLDN6 was down-regulated, the percentage of CCs at S phase was significantly increased (p < 0.05). However, there was no remarkable difference in the percentages of cells at the G0/G1 phase and G2/M phase between CCs with or without CLDN6 knockdown (p > 0.05). Therefore, the expression of CLDN6 and its effects on cell proliferation, apoptosis and cell cycle of bovine CCs were first studied. CLDN6 low expression inhibited cell apoptosis, induced cell proliferation and cell cycle arrest of bovine CCs.

A synthetic promoter system for well-controlled protein expression with different carbon sources in Saccharomyces cerevisiae.

BACKGROUND: Saccharomyces cerevisiae is an important synthetic biology chassis for microbial production of valuable molecules. Promoter engineering has been frequently applied to generate more synthetic promoters with a variety of defined characteristics in order to achieve a well-regulated genetic network for high production efficiency. Galactose-inducible (GAL) expression systems, composed of GAL promoters and multiple GAL regulators, have been widely used for protein overexpression and pathway construction in S. cerevisiae. However, the function of each element in synthetic promoters and how they interact with GAL regulators are not well known. RESULTS: Here, a library of synthetic GAL promoters demonstrate that upstream activating sequences (UASs) and core promoters have a synergistic relationship that determines the performance of each promoter under different carbon sources. We found that the strengths of synthetic GAL promoters could be fine-tuned by manipulating the sequence, number, and substitution of UASs. Core promoter replacement generated synthetic promoters with a twofold strength improvement compared with the GAL1 promoter under multiple different carbon sources in a strain with GAL1 and GAL80 engineering. These results represent an expansion of the classic GAL expression system with an increased dynamic range and a good tolerance of different carbon sources. CONCLUSIONS: In this study, the effect of each element on synthetic GAL promoters has been evaluated and a series of well-controlled synthetic promoters are constructed. By studying the interaction of synthetic promoters and GAL regulators, synthetic promoters with an increased dynamic range under different carbon sources are created.

Overexpression of the regulatory subunit of protein kinase A increases heterologous protein expression in Pichia pastoris.

OBJECTIVE: Translational regulation plays an important role in protein synthesis. Our goal was to screen translation-related factors to improve heterologous protein expression in Pichia pastoris. RESULTS: Twenty-eight translation-related factors were overexpressed in P. pastoris GS115 expressing enhanced green fluorescent protein (eGFP). The results showed that overexpression of Bcy1, the regulatory subunit of protein kinase A (PKA), significantly increased both eGFP expression and cell biomass by 20% under methanol induction for 120 h. Additionally, overexpression of Bcy1 elevated the growth rate by 18% and increased production of the industrial enzyme Phytase (Phy) by 26%. Transcriptome analysis indicated that the overall expression of ribosomal protein genes was significantly downregulated and that postdiauxic shift genes and stress response element genes were upregulated. CONCLUSIONS: Bcy1 regulates ribosome protein genes, postdiauxic shift genes and stress response element genes, leading to improved cell growth and heterologous protein expression. This study provides a convenient and universal factor for heterologous protein production.

Engineering an Efficient Expression Using Heterologous GAL Promoters and Transcriptional Activators in Saccharomyces cerevisiae.

Galactose-inducible (GAL) promoters have been widely used in metabolic engineering in Saccharomyces cerevisiae for production of valuable products. Endogenous GAL promoters and GAL transcription factors have often been engineered to improve GAL promoter activities. Heterologous GAL promoters and GAL activator (Gal4p-like transcriptional activators), although existing in other yeasts or fungi, have not been well explored. In this study, we comprehensively characterized the activation effects of Gal4p activators from different yeasts or fungi on a variant of GAL promoters. Overexpressing endogenous Gal4p driven by PHHF1 increased the activities of native PGAL1 and heterologous PSkGAL2 by 131.20% and 72.45%, respectively. Furthermore, eight transcriptional activators from different organisms were characterized and most of them exhibited functions that were consistent with ScGal4p. Expression of KlLac9p from Kluyveromyces lactis further increased the activity of PScGAL1 and PSkGAL2 by 41.56% and 100.63%, respectively, compared to ScGal4p expression, and was able to evade Gal80p inhibition. This optimized GAL expression system can be used to increase the production of ß-carotene by 9.02-fold in S. cerevisiae. Our study demonstrated that a combination of heterologous transcriptional activators and GAL promoters provided novel insights into the optimization of the GAL expression system.

PorcineAI-Enhancer: Prediction of Pig Enhancer Sequences Using Convolutional Neural Networks.

Understanding the mechanisms of gene expression regulation is crucial in animal breeding. Cis-regulatory DNA sequences, such as enhancers, play a key role in regulating gene expression. Identifying enhancers is challenging, despite the use of experimental techniques and computational methods. Enhancer prediction in the pig genome is particularly significant due to the costliness of high-throughput experimental techniques. The study constructed a high-quality database of pig enhancers by integrating information from multiple sources. A deep learning prediction framework called PorcineAI-enhancer was developed for the prediction of pig enhancers. This framework employs convolutional neural networks for feature extraction and classification. PorcineAI-enhancer showed excellent performance in predicting pig enhancers, validated on an independent test dataset. The model demonstrated reliable prediction capability for unknown enhancer sequences and performed remarkably well on tissue-specific enhancer sequences.The study developed a deep learning prediction framework, PorcineAI-enhancer, for predicting pig enhancers. The model demonstrated significant predictive performance and potential for tissue-specific enhancers. This research provides valuable resources for future studies on gene expression regulation in pigs.

Correlational networking guides the discovery of unclustered lanthipeptide protease-encoding genes.

Bacterial natural product biosynthetic genes, canonically clustered, have been increasingly found to rely on hidden enzymes encoded elsewhere in the genome for completion of biosynthesis. The study and application of lanthipeptides are frequently hindered by unclustered protease genes required for final maturation. Here, we establish a global correlation network bridging the gap between lanthipeptide precursors and hidden proteases. Applying our analysis to 161,954 bacterial genomes, we establish 5209 correlations between precursors and hidden proteases, with 91 prioritized. We use network predictions and co-expression analysis to reveal a previously missing protease for the maturation of class I lanthipeptide paenilan. We further discover widely distributed bacterial M16B metallopeptidases of previously unclear biological function as a new family of lanthipeptide proteases. We show the involvement of a pair of bifunctional M16B proteases in the production of previously unreported class III lanthipeptides with high substrate specificity. Together, these results demonstrate the strength of our correlational networking approach to the discovery of hidden lanthipeptide proteases and potentially other missing enzymes for natural products biosynthesis.

Promoter Architecture and Promoter Engineering in Saccharomyces cerevisiae.

Promoters play an essential role in the regulation of gene expression for fine-tuning genetic circuits and metabolic pathways in Saccharomyces cerevisiae (S. cerevisiae). However, native promoters in S. cerevisiae have several limitations which hinder their applications in metabolic engineering. These limitations include an inadequate number of well-characterized promoters, poor dynamic range, and insufficient orthogonality to endogenous regulations. Therefore, it is necessary to perform promoter engineering to create synthetic promoters with better properties. Here, we review recent advances related to promoter architecture, promoter engineering and synthetic promoter applications in S. cerevisiae. We also provide a perspective of future directions in this field with an emphasis on the recent advances of machine learning based promoter designs.