Construction of an Escherichia coli strain to degrade phenol completely with two modified metabolic modules

Phenol is a common water pollutant because of its broad industrial applications. Biological method is a promising alternative to conventional physical and chemical methods for removing this toxic pollutant from the environment. In this study, two metabolic modules were introduced into Escherichia coli, the widely used host for various genetic manipulations, to elucidate the metabolic capacity of E. coli for phenol degradation. The first module catalysed the conversion of phenol to catechol, whereas the second module cleaved catechol into the three carboxylic acid circulating intermediates by the ortho-cleavage pathway. Phenol was completely degraded and imported into the tricarboxylic acid cycle by the engineered bacteria. Proteomics analysis showed that all genes in the phenol degradation pathway were over-expressed and affected cell division and energy metabolism of the host cells. Phenol in coking wastewater was degraded powerfully by BL-phe/cat. The engineered E. coli can improve the removal rate and shorten the processing time for phenol removal and has considerable potential in the treatment of toxic and harmful pollutants.

Reconstruction of metabolic module with improved promoter strength increases the productivity of 2-phenylethanol in Saccharomyces cerevisiae

Background

2-phenylethanol (2-PE) is an important aromatic compound with a lovely rose-like scent. Saccharomyces cerevisiae is a desirable microbe for 2-PE production but its natural yield is not high, and one or two crucial genes’ over-expression in S. cerevisiae did not improve 2-PE greatly.

Results

A new metabolic module was established here, in which, permease Gap1p for l-phenylalanine transportation, catalytic enzymes Aro8p, Aro10p and Adh2p in Ehrlich pathway respectively responsible for transamination, decarboxylation and reduction were assembled, besides, glutamate dehydrogenase Gdh2p was harbored for re-supplying another substrate 2-oxoglutarate, relieving product glutamate repression and regenerating cofactor NADH. Due to different promoter strengths, GAP1, ARO8, ARO9, ARO10, ADH2 and GDH2 in the new modularized YS58(G1-A8-A10-A2)-GDH strain enhanced 11.6-, 15.4-, 3.6-, 17.7-, 12.4- and 7.5-folds respectively, and crucial enzyme activities of aromatic aminotransferases and phenylpyruvate decarboxylase were 4.8- and 7-folds respectively higher than that of the control.

Conclusions

Under the optimum medium and cell density, YS58(G1-A8-A10-A2)-GDH presented efficient 2-PE synthesis ability with ~ 6.3 g L⁻¹ of 2-PE titer in 5-L fermenter reaching 95% of conversation ratio. Under fed-batch fermentation, 2-PE productivity at 24 h increased 29% than that of single-batch fermentation. Metabolic modularization with promoter strategy provides a new prospective for efficient 2-PE production.

A novel metabolic balance model for describing the metabolic disruption of and interactions between cardiovascular-related markers during acute myocardial infarction

OBJECTIVE

After acute myocardial infarction (AMI), an integral evaluation of risk using multimarker approach and the understanding of the pathophysiological processes involved have recently received much attention. This study aimed to develop a model to integrally evaluate the metabolic disruption of cardiovascular-related markers and unveil their interactions after AMI.

METHODS

AMI was induced in rats by coronary artery ligation. Several cardiovascular-related markers in plasma and the heart were determined during AMI. A metabolic balance model was developed using matrix equations to assess the metabolic disturbance of, and interactions between, these markers.

RESULTS

Metabolic balance maps intuitively depicted the metabolic disruption of cardiovascular-related markers after AMI. The deviation and magnitude of the disruption were quantitatively and integrally described by φ and k (the dynamic parameter of metabolic balance disruption), respectively. The metabolic balance was disturbed in both the circulatory system and the heart post-AMI. All of the measured markers appeared to be interactional. Among these markers, kidney function and dimethylarginine dimethylaminohydrolase (DDAH) activity in the heart showed a potent effect on the other markers, whereas asymmetric dimethylarginine (ADMA) levels in plasma and adenosine triphosphate (ATP) contents in the heart were susceptible to the effects of the other markers.

CONCLUSION

A metabolic balance model was developed to integrally evaluate the disruption of cardiovascular-related markers after AMI, which proposes a new method for evaluating the disease state post-AMI using a multimarker approach. The unveiled interactions between these cardiovascular-related markers are helpful in understanding the pathophysiological processes.