Synthetic repetitive extragenic palindromic (REP) sequence as an efficient mRNA stabilizer for protein production and metabolic engineering in prokaryotic cells

Recognition of cyanobacteria promoters via Siamese network-based contrastive learning under novel non-promoter generation

It is a vital step to recognize cyanobacteria promoters on a genome-wide scale. Computational methods are promising to assist in difficult biological identification. When building recognition models, these methods rely on non-promoter generation to cope with the lack of real non-promoters. Nevertheless, the factitious significant difference between promoters and non-promoters causes over-optimistic prediction. Moreover, designed for E. coli or B. subtilis, existing methods cannot uncover novel, distinct motifs among cyanobacterial promoters. To address these issues, this work first proposes a novel non-promoter generation strategy called phantom sampling, which can eliminate the factitious difference between promoters and generated non-promoters. Furthermore, it elaborates a novel promoter prediction model based on the Siamese network (SiamProm), which can amplify the hidden difference between promoters and non-promoters through a joint characterization of global associations, upstream and downstream contexts, and neighboring associations w.r.t. k-mer tokens. The comparison with state-of-the-art methods demonstrates the superiority of our phantom sampling and SiamProm. Both comprehensive ablation studies and feature space illustrations also validate the effectiveness of the Siamese network and its components. More importantly, SiamProm, upon our phantom sampling, finds a novel cyanobacterial promoter motif ('GCGATCGC'), which is palindrome-patterned, content-conserved, but position-shifted.

Engineering serine hydroxymethyltransferases for efficient synthesis of L-serine in Escherichia coli

L-serine is a high-value amino acid widely used in the food, medicine, and cosmetic industries. However, the low yield of L-serine has limited its industrial production. In this study, a cellular factory for efficient synthesis of L-serine was obtained by engineering the serine hydroxymethyltransferases (SHMT). Firstly, after screening the SHMT from Alcanivorax dieselolei by genome mining, a mutant AdSHMTE266M with high thermal stability was identified through rational design. Subsequently, an iterative saturating mutant library was constructed by using coevolutionary analysis, and a mutant AdSHMTE160L/E193Q with enzyme activity 1.35 times higher than AdSHMT was identified. Additionally, the target protein AdSHMTE160L/E193Q/E266M was efficiently overexpressed by improving its mRNA stability. Finally, combining the substrate addition strategy and system optimization, the optimized strain BL21/pET28a-AdSHMTE160L/E193Q/E266M-5'UTR-REP3S16 produced 106.06 g/L L-serine, which is the highest production to date. This study provides new ideas and insights for the engineering design of SHMT and the industrial production of L-serine.

Engineering Corynebacterium glutamicum for the efficient production of N-acetylglucosamine

N-acetylglucosamine (GlcNAc) is significant functional monosaccharides with diverse applications in medicine, food, and cosmetics. In this study, the GlcNAc synthesis pathway was constructed in Corynebacterium glutamicum and its reverse byproduct pathways were blocked. Simultaneously the driving force of GlcNAc synthesis was enhanced by screening key gene sources and inhibiting the GlcNAc consumption pathway. To maximize carbon flux, some competitive pathways (Pentose phosphate pathway, Glycolysis pathway and Mannose pathway) were weakened and the titer of GlcNAc reached 23.30 g/L in shake flasks. Through transcriptome analysis, it was found that dissolved oxygen was an important limiting factor, which was optimized in a 5 L bioreactor. Employing optimal fermentation conditions and feeding strategy, the titer of GlcNAc reached 138.9 g/L, with the yeild of 0.44 g/g glucose. This study significantly increased the yield and titer of GlcNAc, which lay a solid foundation for the industrial production of GlcNAc in C. glutamicum.

Minimization and optimization of α-amylase terminator for heterologous protein production in Bacillus licheniformis

Terminators serve as the regulatory role in gene transcription termination; however, few researches about terminator optimization have been conducted, which leads to the lack of available and universal terminator for gene expression regulation in Bacillus. To solve this problem and expand synthetic biology toolbox of Bacillus licheniformis, the terminator T1 of endogenous α-amylase gene (amyL) was characterized in this research, with a termination efficiency of 87.81%. Then, we explored and optimized the termination strength of terminator T1 from four aspects: the distance between stop codon and terminator, GC content at the bottom of stem structure, loop size, and U-tract length, and the best terminator T24 was attained by combination optimization strategy, which termination efficiency was increased to 97.97%, better than the commonly used terminator T7 (T7P) from Escherichia coli. Finally, terminator T24 was applied to protein expression, which, respectively, led to 33.00%, 25.93%, and 11.78% increases of green fluorescence intensity, red fluorescence intensity, and keratinase activity, indicating its universality in protein expression. Taken together, this research not only expands a plug-and-play synthetic biology toolbox in B. licheniformis but also provides a reference for the artificial design of versatile intrinsic terminator.

Synergistic improvement of N-acetylglucosamine production by engineering transcription factors and balancing redox cofactors

The regulation of single gene transcription level in the metabolic pathway is often failed to significantly improve the titer of the target product, and even leads to the imbalance of carbon/nitrogen metabolic network and cofactor network. Global transcription machinery engineering (gTME) can activate or inhibit the synergistic expression of multiple genes in specific metabolic pathways, so transcription factors with specific functions can be expressed according to different metabolic regulation requirements, thus effectively increasing the synthesis of target metabolites. In addition, maintaining intracellular redox balance through cofactor engineering can realize the self-balance of cofactors and promote the efficient synthesis of target products. In this study, we rebalanced the central carbon/nitrogen metabolism and redox metabolism of Corynebacterium glutamicum S9114 by gTME and redox cofactors engineering to promote the production of the nutraceutical N-acetylglucosamine (GlcNAc). Firstly, it was found that the overexpression of the transcription factor RamA can promote GlcNAc synthesis, and the titer was further improved to 16 g/L in shake flask by using a mutant RamA (RamAM). Secondly, a CRISPR interference (CRISPRi) system based on dCpf1 was developed and used to inhibit the expression of global negative transcriptional regulators of GlcNAc synthesis, which promoted the GlcNAc titer to 27.5 g/L. Thirdly, the cofactor specificity of the key enzymes in GlcNAc synthesis pathway was changed by rational protein engineering, and the titer of GlcNAc in shake flask was increased to 36.9 g/L. Finally, the production of GlcNAc was scaled up in a 50-L fermentor, and the titer reached 117.1 ± 1.9 g/L, which was 6.62 times that of the control group (17.7 ± 0.4 g/L), and the yield was increased from 0.19 g/g to 0.31 g/g glucose. The results obtained here highlight the importance of engineering the global regulation of central carbon/nitrogen metabolism and redox metabolism to improve the production performance of microbial cell factories.

The essential role of mRNA degradation in understanding and engineering E. coli metabolism

Metabolic engineering strategies are crucial for the development of bacterial cell factories with improved performance. Until now, optimal metabolic networks have been designed based on systems biology approaches integrating large-scale data on the steady-state concentrations of mRNA, protein and metabolites, sometimes with dynamic data on fluxes, but rarely with any information on mRNA degradation. In this review, we compile growing evidence that mRNA degradation is a key regulatory level in E. coli that metabolic engineering strategies should take into account. We first discuss how mRNA degradation interacts with transcription and translation, two other gene expression processes, to balance transcription regulation and remove poorly translated mRNAs. The many reciprocal interactions between mRNA degradation and metabolism are also highlighted: metabolic activity can be controlled by changes in mRNA degradation and in return, the activity of the mRNA degradation machinery is controlled by metabolic factors. The mathematical models of the crosstalk between mRNA degradation dynamics and other cellular processes are presented and discussed with a view towards novel mRNA degradation-based metabolic engineering strategies. We show finally that mRNA degradation-based strategies have already successfully been applied to improve heterologous protein synthesis. Overall, this review underlines how important mRNA degradation is in regulating E. coli metabolism and identifies mRNA degradation as a key target for innovative metabolic engineering strategies in biotechnology.

In silico Design of Linear DNA for Robust Cell-Free Gene Expression

Cell-free gene expression systems with linear DNA expression templates (LDETs) have been widely applied in artificial cells, biochips, and high-throughput screening. However, due to the degradation caused by native nucleases in cell extracts, the transcription with linear DNA templates is weak, thereby resulting in low protein expression level, which greatly limits the development of cell-free systems using linear DNA templates. In this study, the protective sequences for stabilizing linear DNA and the transcribed mRNAs were rationally designed according to nucleases' action mechanism, whose effectiveness was evaluated through computer simulation and cell-free gene expression. The cell-free experiment results indicated that, with the combined protection of designed sequence and GamS protein, the protein expression of LDET-based cell-free systems could reach the same level as plasmid-based cell-free systems. This study would potentially promote the development of the LDET-based cell-free gene expression system for broader applications.

Increasing metabolic pathway flux by using machine learning models

Machine learning is transforming many industries through self-improving models that are fueled by big data and high computing power. The field of metabolic engineering, which uses cellular biochemical network to manufacture useful small molecules, has also witnessed the first wave of machine learning applications in the past five years, covering reaction route design, enzyme selection, pathway engineering and process optimization. This review focuses on pathway engineering, and uses a few recent studies to illustrate (1) how machine learning models can be useful in overcoming an evident rate-limiting step, and (2) how the models may be used to exhaustively search - or guide optimization algorithms to search - a large design space when the cellular regulation of the reaction network is more convoluted.

Development of a DNA double-strand break-free base editing tool in Corynebacterium glutamicum for genome editing and metabolic engineering

As a traditional amino acid producing bacterium, Corynebacterium glutamicum is a platform strain for production of various fine chemicals. Based on the CRISPR (Clustered regularly interspaced short palindromic repeats)-Cas9 system, gene editing tools that enable base conversion in the genome of C. glutamicum have been developed. However, some problems such as genomic instability caused by DNA double-strand break (DSB) and off-target effects need to be solved. In this study, a DSB-free single nucleotide genome editing system was developed by construction of a bi-directional base conversion tool TadA-dCas9-AID. This system includes cytosine base editors (CBEs): activation-induced cytidine deaminase (AID) and adenine deaminase (ABEs): tRNA adenosine deaminase (TadA), which can specifically target the gene through a 20-nt single guide RNA (sgRNA) and achieve the base conversion of C-T, C-G and A-G in the 28-bp editing window upstream of protospacer adjacent motif. Finally, as a proof-of-concept demonstration, the system was used to construct a mutant library of zwf gene in C. glutamicum S9114 genome to improve the production of a typical nutraceutical N-acetylglucosamine (GlcNAc). The GlcNAc titer of the mutant strain K293R was increased by 31.9% to 9.1 ​g/L in shake flask. Here, the developed bases conversion tool TadA-dCas9-AID does not need DNA double-strand break and homologous template, and is effective for genome editing and metabolic engineering in C. glutamicum.

•

A DNA double-strand break-free base editing tool was developed in Corynebacterium glutamicum S9114, which can produce diverse single base mutations.

•

The base editing tool can be used for base mutations on genome and metabolic engineering of C. glutamicum S9114.

•

High efficiency 20N target sequence linking strategy was developed.

•

The base editing tool is used to increase the titer of GlcNAc.

Easily readable palindromic sequence-defined polymers built by cascade thiol-maleimide Michael couplings

The rational combination of cascade thiol-maleimide Michael couplings (CTMMC) with iterative exponential chain growth was demonstrated as an efficient way to synthesize palindromic sequence-defined polymers.

Secretory Expression Fine-Tuning and Directed Evolution of Diacetylchitobiose Deacetylase by Bacillus subtilis

Diacetylchitobiose deacetylase has great application potential in the production of chitosan oligosaccharides and monosaccharides. This work aimed to achieve high-level secretory production of diacetylchitobiose deacetylase by Bacillus subtilis and perform molecular engineering to improve catalytic performance. First, we screened 12 signal peptides for diacetylchitobiose deacetylase secretion in B. subtilis, and the signal peptide YncM achieved the highest extracellular diacetylchitobiose deacetylase activity of 13.5 U/ml. Second, by replacing the HpaII promoter with a strong promoter, the P43 promoter, the activity was increased to 18.9 U/ml. An unexpected mutation occurred at the 5' untranslated region of plasmid, and the extracellular activity reached 1,548.1 U/ml, which is 82 times higher than that of the original strain. Finally, site-directed saturation mutagenesis was performed for the molecular engineering of diacetylchitobiose deacetylase to further improve the catalytic efficiency. The extracellular activity of mutant diacetylchitobiose deacetylase R157T reached 2,042.8 U/ml in shake flasks. Mutant R157T exhibited much higher specific activity (3,112.2 U/mg) than the wild type (2,047.3 U/mg). The K_m decreased from 7.04 mM in the wild type to 5.19 mM in the mutant R157T, and the V _max increased from 5.11 μM s^-1 in the wild type to 7.56 μM s^-1 in the mutant R157T.IMPORTANCE We successfully achieved efficient secretory production and improved the catalytic efficiency of diacetylchitobiose deacetylase in Bacillus subtilis, and this provides a good foundation for the application of diacetylchitobiose deacetylase in the production of chitosan oligosaccharides and monosaccharides.

Metabolic engineering of Corynebacterium glutamicum S9114 based on whole-genome sequencing for efficient N-acetylglucosamine synthesis

Glucosamine (GlcN) and its acetylated derivative N-acetylglucosamine (GlcNAc) are widely used in the pharmaceutical industries. Here, we attempted to achieve efficient production of GlcNAc via genomic engineering of Corynebacterium glutamicum. Specifically, we ligated the GNA1 gene, which converts GlcN-6-phosphate to GlcNAc-6-phosphate by transferring the acetyl group in Acetyl-CoA to the amino group of GlcN-6-phosphate, into the plasmid pJYW4 and then transformed this recombinant vector into the C. glutamicum ATCC 13032, ATCC 13869, ATCC 14067, and S9114 strains, and we assessed the GlcNAc titers at 0.5 g/L, 1.2 g/L, 0.8 g/L, and 3.1 g/L from each strain, respectively. This suggested that there were likely to be significant differences among the key genes in the glutamate and GlcNAc synthesis pathways of these C. glutamicum strains. Therefore, we performed whole genome sequencing of the S9114 strain, which has not been previously published, and found that there are many differences among the genes in the glutamate and GlcNAc synthesis pathways among the four strains tested. Next, nagA (encoding GlcNAc-6-phosphate deacetylase) and gamA (encoding GlcN-6-phosphate deaminase) were deleted in C. glutamicum S9114 to block the catabolism of intracellular GlcNAc, leading to a 54.8% increase in GlcNAc production (from 3.1 to 4.8 g/L) when grown in a shaker flask. In addition, lactate synthesis was blocked by knockout of ldh (encoding lactate dehydrogenase); thus, further increasing the GlcNAc titer to 5.4 g/L. Finally, we added a key gene of the GlcN synthetic pathway, glmS, from different sources into the expression vector pJYW-4-ceN, and the resulting recombinant strain CGGN2-GNA1-CgglmS produced the GlcNAc titer of 6.9 g/L. This is the first report concerning the metabolic engineering of C. glutamicum, and the results of this study provide a good starting point for further metabolic engineering to achieve industrial-scale production of GlcNAc.