Comparative metabolomics and transcriptomics analyses provide insights into the high-yield mechanism of phenazines biosynthesis in Pseudomonas chlororaphis GP72.

AIMS: Phenazines, such as phenazine-1-carboxylic acid (PCA), phenazine-1-carboxamide (PCN), 2-hydroxyphenazine-1-carboxylic acid (2-OH-PCA), 2-hydroxyphenazine (2-OH-PHZ), are a class of secondary metabolites secreted by plant-beneficial Pseudomonas. Ps. chlororaphis GP72 utilizes glycerol to synthesize PCA, 2-OH-PCA and 2-OH-PHZ, exhibiting broad-spectrum antifungal activity. Previous studies showed that the addition of dithiothreitol (DTT) could increase the phenazines production in Ps. chlororaphis GP72AN. However, the mechanism of high yield of phenazine by adding DTT is still unclear. METHODS AND RESULTS: In this study, untargeted and targeted metabolomic analysis were adopted to determine the content of metabolites. The results showed that the addition of DTT to GP72AN affected the content of metabolites of central carbon metabolism, shikimate pathway and phenazine competitive pathway. Transcriptome analysis was conducted to investigate the changed cellular process, and the result indicated that the addition of DTT affected the expression of genes involved in phenazine biosynthetic cluster and genes involved in phenazine competitive pathway, driving more carbon flux into phenazine biosynthetic pathway. Furthermore, genes involved in antioxidative stress, phosphate transport system and mexGHI-opmD efflux pump were also affected by adding DTT. CONCLUSION: This study demonstrated that the addition of DTT altered the expression of genes related to phenazine biosynthesis, resulting in the change of metabolites involved in central carbon metabolism, shikimate pathway and phenazine competitive pathway. SIGNIFICANCE AND IMPACT OF THE STUDY: This work expands the understanding of high yield of phenazine by the addition of DTT and provides several targets for increasing phenazine production.

[Thirty years development of ¹³C metabolic flux analysis: a review].

¹³C metabolic flux analysis (¹³C-MFA) enables the precise quantification of intracellular metabolic reaction rates by analyzing the distribution of mass isotopomers of proteinogenic amino acids or intracellular metabolites through ¹³C labeling experiments. ¹³C-MFA has received much attention as it can help systematically understand cellular metabolic characteristics, guide metabolic engineering design and gain mechanistic insights into pathophysiology. This article reviews the advances of ¹³C-MFA in the past 30 years and discusses its potential and future perspective, with a focus on its application in industrial biotechnology and biomedicine.

CRISPR base editing and prime editing: DSB and template-free editing systems for bacteria and plants.

CRISPR-Cas (Clustered Regularly Interspaced Short Palindromic Repeats-CRISPR associated) has been extensively exploited as a genetic tool for genome editing. The RNA guided Cas nucleases generate DNA double-strand break (DSB), triggering cellular repair systems mainly Non-homologous end-joining (NHEJ, imprecise repair) or Homology-directed repair (HDR, precise repair). However, DSB typically leads to unexpected DNA changes and lethality in some organisms. The establishment of bacteria and plants into major bio-production platforms require efficient and precise editing tools. Hence, in this review, we focus on the non-DSB and template-free genome editing, i.e., base editing (BE) and prime editing (PE) in bacteria and plants. We first highlight the development of base and prime editors and summarize their studies in bacteria and plants. We then discuss current and future applications of BE/PE in synthetic biology, crop improvement, evolutionary engineering, and metabolic engineering. Lastly, we critically consider the challenges and prospects of BE/PE in PAM specificity, editing efficiency, off-targeting, sequence specification, and editing window.

Engineered bacterial biofloc formation enhancing phenol removal and cell tolerance.

A microbial floc consisting of a community of microbes embedded in extracellular polymeric substances matrix can provide microbial resistances to toxic chemicals and harsh environments. Phenol is a toxic environmental pollutant and a typical lignin-derived phenolic inhibitor. In this study, we genetically engineered Escherichia coli cells by expressions of diguanylate cyclases (DGCs) to promote proteinaceous and aliphatic biofloc formation. Compared with the planktonic E. coli cells, the biofloc-forming cells improved phenol removal rate by up to 2.2-folds, due to their substantially improved tolerance (up to 149%) to phenol and slightly enhanced cellular activity (20%) of phenol hydroxylase (PheH). The engineered bioflocs also improved E. coli tolerance to other toxic compounds such as furfural, 5-hydroxymethylfurfural, and guaiacol. Additionally, the strategy of the engineered biofloc formation was applicable to Pseudomonas putida and enhanced its tolerance to phenol. This study highlights a strategy to form engineered bioflocs for improved cell tolerance and removal of toxic compounds, enabling their universality of use in bioproduction and bioremediation.

13C metabolic flux analysis-guided metabolic engineering of Escherichia coli for improved acetol production from glycerol.

BACKGROUND: Bioprocessing offers a sustainable and green approach to manufacture various chemicals and materials. Development of bioprocesses requires transforming common producer strains to cell factories. 13C metabolic flux analysis (13C-MFA) can be applied to identify relevant targets to accomplish the desired phenotype, which has become one of the major tools to support systems metabolic engineering. In this research, we applied 13C-MFA to identify bottlenecks in the bioconversion of glycerol into acetol by Escherichia coli. Valorization of glycerol, the main by-product of biodiesel, has contributed to the viability of biofuel economy. RESULTS: We performed 13C-MFA and measured intracellular pyridine nucleotide pools in a first-generation acetol producer strain (HJ06) and a non-producer strain (HJ06C), and identified that engineering the NADPH regeneration is a promising target. Based on this finding, we overexpressed nadK encoding NAD kinase or pntAB encoding membrane-bound transhydrogenase either individually or in combination with HJ06, obtaining HJ06N, HJ06P and HJ06PN. The step-wise approach resulted in increasing the acetol titer from 0.91 g/L (HJ06) to 2.81 g/L (HJ06PN). To systematically characterize and the effect of mutation(s) on the metabolism, we also examined the metabolomics and transcriptional levels of key genes in four strains. The pool sizes of NADPH, NADP+ and the NADPH/NADP+ ratio were progressively increased from HJ06 to HJ06PN, demonstrating that the sufficient NADPH supply is critical for acetol production. Flux distribution was optimized towards acetol formation from HJ06 to HJ06PN: (1) The carbon partitioning at the DHAP node directed gradually more carbon from the lower glycolytic pathway through the acetol biosynthetic pathway; (2) The transhydrogenation flux was constantly increased. In addition, 13C-MFA showed the rigidity of upper glycolytic pathway, PP pathway and the TCA cycle to support growth. The flux patterns were supported by most metabolomics data and gene expression profiles. CONCLUSIONS: This research demonstrated how 13C-MFA can be applied to drive the cycles of design, build, test and learn implementation for strain development. This succeeding engineering strategy can also be applicable for rational design of other microbial cell factories.

CRISPR-Cas9/Cas12a biotechnology and application in bacteria.

CRISPR-Cas technologies have greatly reshaped the biology field. In this review, we discuss the CRISPR-Cas with a particular focus on the associated technologies and applications of CRISPR-Cas9 and CRISPR-Cas12a, which have been most widely studied and used. We discuss the biological mechanisms of CRISPR-Cas as immune defense systems, recently-discovered anti-CRISPR-Cas systems, and the emerging Cas variants (such as xCas9 and Cas13) with unique characteristics. Then, we highlight various CRISPR-Cas biotechnologies, including nuclease-dependent genome editing, CRISPR gene regulation (including CRISPR interference/activation), DNA/RNA base editing, and nucleic acid detection. Last, we summarize up-to-date applications of the biotechnologies for synthetic biology and metabolic engineering in various bacterial species.

Engineering and systems-level analysis of Pseudomonas chlororaphis for production of phenazine-1-carboxamide using glycerol as the cost-effective carbon source.

BACKGROUND: Glycerol, an inevitable byproduct of biodiesel, has become an attractive feedstock for the production of value-added chemicals due to its availability and low price. Pseudomonas chlororaphis HT66 can use glycerol to synthesize phenazine-1-carboxamide (PCN), a phenazine derivative, which is strongly antagonistic to fungal phytopathogens. A systematic understanding of underlying mechanisms for the PCN overproduction will be important for the further improvement and industrialization. RESULTS: We constructed a PCN-overproducing strain (HT66LSP) through knocking out three negative regulatory genes, lon, parS, and prsA in HT66. The strain HT66LSP produced 4.10 g/L of PCN with a yield of 0.23 (g/g) from glycerol, which was of the highest titer and the yield obtained among PCN-producing strains. We studied gene expression, metabolomics, and dynamic 13C tracer in HT66 and HT66LSP. In response to the phenotype changes, the transcript levels of phz biosynthetic genes, which are responsible for PCN biosynthesis, were all upregulated in HT66LSP. Central carbon was rerouted to the shikimate pathway, which was shown by the modulation of specific genes involved in the lower glycolysis, the TCA cycle, and the shikimate pathway, as well as changes in abundances of intracellular metabolites and flux distribution to increase the precursor availability for PCN biosynthesis. Moreover, dynamic 13C-labeling experiments revealed that the presence of metabolite channeling of 3-phosphoglyceric acid to phosphoenolpyruvate and shikimate to trans-2,3-dihydro-3-hydroxyanthranilic acid in HT66LSP could enable high-yielding synthesis of PCN. CONCLUSIONS: The integrated analysis of gene expression, metabolomics, and dynamic 13C tracer enabled us to gain a more in-depth insight into complex mechanisms for the PCN overproduction. This study provides important basis for further engineering P. chlororaphis for high PCN production and efficient glycerol conversion.

Elucidation of the co-metabolism of glycerol and glucose in Escherichia coli by genetic engineering, transcription profiling, and (13)C metabolic flux analysis.

BACKGROUND: Glycerol, a byproduct of biodiesel, has become a readily available and inexpensive carbon source for the production of high-value products. However, the main drawback of glycerol utilization is the low consumption rate and shortage of NADPH formation, which may limit the production of NADPH-requiring products. To overcome these problems, we constructed a carbon catabolite repression-negative ΔptsGglpK* mutant by both blocking a key glucose PTS transporter and enhancing the glycerol conversion. The mutant can recover normal growth by co-utilization of glycerol and glucose after loss of glucose PTS transporter. To reveal the metabolic potential of the ΔptsGglpK* mutant, this study examined the flux distributions and regulation of the co-metabolism of glycerol and glucose in the mutant. RESULTS: By labeling experiments using [1,3-(13)C]glycerol and [1-(13)C]glucose, (13)C metabolic flux analysis was employed to decipher the metabolisms of both the wild-type strain and the ΔptsGglpK* mutant in chemostat cultures. When cells were maintained at a low dilution rate (0.1 h(-1)), the two strains showed similar fluxome profiles. When the dilution rate was increased, both strains upgraded their pentose phosphate pathway, glycolysis and anaplerotic reactions, while the ΔptsGglpK* mutant was able to catabolize much more glycerol than glucose (more than tenfold higher). Compared with the wild-type strain, the mutant repressed its flux through the TCA cycle, resulting in higher acetate overflow. The regulation of fluxomes was consistent with transcriptional profiling of several key genes relevant to the TCA cycle and transhydrogenase, namely gltA, icdA, sdhA and pntA. In addition, cofactor fluxes and their pool sizes were determined. The ΔptsGglpK* mutant affected the redox NADPH/NADH state and reduced the ATP level. Redox signaling activated the ArcA regulatory system, which was responsible for TCA cycle repression. CONCLUSIONS: This work employs both (13)C-MFA and transcription/metabolite analysis for quantitative investigation of the co-metabolism of glycerol and glucose in the ΔptsGglpK* mutant. The ArcA regulatory system dominates the control of flux redistribution. The ΔptsGglpK* mutant can be used as a platform for microbial cell factories for the production of biofuels and biochemicals, since most of fuel molecule (e.g., alcohols) synthesis requires excess reducing equivalents.

Rapid Prediction of Bacterial Heterotrophic Fluxomics Using Machine Learning and Constraint Programming.

13C metabolic flux analysis (13C-MFA) has been widely used to measure in vivo enzyme reaction rates (i.e., metabolic flux) in microorganisms. Mining the relationship between environmental and genetic factors and metabolic fluxes hidden in existing fluxomic data will lead to predictive models that can significantly accelerate flux quantification. In this paper, we present a web-based platform MFlux (http://mflux.org) that predicts the bacterial central metabolism via machine learning, leveraging data from approximately 100 13C-MFA papers on heterotrophic bacterial metabolisms. Three machine learning methods, namely Support Vector Machine (SVM), k-Nearest Neighbors (k-NN), and Decision Tree, were employed to study the sophisticated relationship between influential factors and metabolic fluxes. We performed a grid search of the best parameter set for each algorithm and verified their performance through 10-fold cross validations. SVM yields the highest accuracy among all three algorithms. Further, we employed quadratic programming to adjust flux profiles to satisfy stoichiometric constraints. Multiple case studies have shown that MFlux can reasonably predict fluxomes as a function of bacterial species, substrate types, growth rate, oxygen conditions, and cultivation methods. Due to the interest of studying model organism under particular carbon sources, bias of fluxome in the dataset may limit the applicability of machine learning models. This problem can be resolved after more papers on 13C-MFA are published for non-model species.

Metabolic engineering of Escherichia coli to enhance acetol production from glycerol.

Acetol, a C3 keto alcohol, is an important intermediate used to produce polyols and acrolein. To enhance acetol production from glycerol by Escherichia coli, a mutant (HJ02) was constructed by replacing the native glpK gene with the allele from E. coli Lin 43 and overexpression of yqhD, which encodes aldehyde oxidoreductase YqhD that converts methylglyoxal to acetol. Compared to the control strain without the glpK replacement, HJ02 had 5.5 times greater acetol production and a 53.4 % higher glycerol consumption rate. Then, glucose was added as a co-substrate to enhance NADPH availability and the ptsG gene was deleted in HJ02 (HJ04) to alleviate carbon catabolite repression, which led to a 30 % increase in the NADPH level and NADPH/NADP(+). Consequently, HJ04 accumulated up to 1.20 g/L of acetol, which is 69.0 % higher than that of HJ02. Furthermore, the gapA gene in HJ04 was silenced by antisense RNA (HJ05) to further enhance acetol production. The acetol concentration produced by HJ05 reached 1.82 g/L, which was 2.1 and 1.5 times higher than that of HJ02 and HJ04.Real-time PCR analysis indicates that glucose catabolism was rerouted from glycolysis to the oxidative pentose phosphate pathway in HJ05.

Catabolic regulation analysis of Escherichia coli and its crp, mlc, mgsA, pgi and ptsG mutants.

BACKGROUND: Most bacteria can use various compounds as carbon sources. These carbon sources can be either co-metabolized or sequentially metabolized, where the latter phenomenon typically occurs as catabolite repression. From the practical application point of view of utilizing lignocellulose for the production of biofuels etc., it is strongly desirable to ferment all sugars obtained by hydrolysis from lignocellulosic materials, where simultaneous consumption of sugars would benefit the formation of bioproducts. However, most organisms consume glucose prior to consumption of other carbon sources, and exhibit diauxic growth. It has been shown by fermentation experiments that simultaneous consumption of sugars can be attained by ptsG, mgsA mutants etc., but its mechanism has not been well understood. It is strongly desirable to understand the mechanism of metabolic regulation for catabolite regulation to improve the performance of fermentation. RESULTS: In order to make clear the catabolic regulation mechanism, several continuous cultures were conducted at different dilution rates of 0.2, 0.4, 0.6 and 0.7 h⁻¹ using wild type Escherichia coli. The result indicates that the transcript levels of global regulators such as crp, cra, mlc and rpoS decreased, while those of fadR, iclR, soxR/S increased as the dilution rate increased. These affected the metabolic pathway genes, which in turn affected fermentation result where the specific glucose uptake rate, the specific acetate formation rate, and the specific CO2 evolution rate (CER) were increased as the dilution rate was increased. This was confirmed by the ¹³C-flux analysis. In order to make clear the catabolite regulation, the effect of crp gene knockout (Δcrp) and crp enhancement (crp⁺) as well as mlc, mgsA, pgi and ptsG gene knockout on the metabolism was then investigated by the continuous culture at the dilution rate of 0.2 h⁻¹ and by some batch cultures. In the case of Δcrp (and also Δmlc) mutant, TCA cycle and glyoxylate were repressed, which caused acetate accumulation. In the case of crp⁺ mutant, glycolysis, TCA cycle, and gluconeogenesis were activated, and simultaneous consumption of multiple carbon sources can be attained, but the glucose consumption rate became less due to repression of ptsG and ptsH by the activation of Mlc. Simultaneous consumption of multiple carbon sources could be attained by mgsA, pgi, and ptsG mutants due to increase in crp as well as cyaA, while glucose consumption rate became lower. CONCLUSIONS: The transcriptional catabolite regulation mechanism was made clear for the wild type E. coli, and its crp, mlc, ptsG, pgi, and mgsA gene knockout mutants. The results indicate that catabolite repression can be relaxed and crp as well as cyaA can be increased by crp⁺, mgsA, pgi, and ptsG mutants, and thus simultaneous consumption of multiple carbon sources including glucose can be made, whereas the glucose uptake rate became lower as compared to wild type due to inactivation of ptsG in all the mutants considered.