Engineering Escherichia coli to produce aromatic chemicals from ethylene glycol.

Microbial overproduction of aromatic chemicals has gained considerable industrial interest and various metabolic engineering approaches have been employed in recent years to address the associated challenges. So far, most studies have used sugars (mostly glucose) or glycerol as the primary carbon source. In this study, we used ethylene glycol (EG) as the main carbon substrate. EG could be obtained from the degradation of plastic and cellulosic wastes. As a proof of concept, Escherichia coli was engineered to transform EG into L-tyrosine, a valuable aromatic amino acid. Under the best fermentation condition, the strain produced 2 g/L L-tyrosine from 10 g/L EG, outperforming glucose (the most common sugar feedstock) in the same experimental conditions. To prove the concept that EG can be converted into different aromatic chemicals, E. coli was further engineered with a similar approach to synthesize other valuable aromatic chemicals, L-phenylalanine and p-coumaric acid. Finally, waste polyethylene terephthalate (PET) bottles were degraded using acid hydrolysis and the resulting monomer EG was transformed into L-tyrosine using the engineered E. coli, yielding a comparable titer to that obtained using commercial EG. The strains developed in this study should be valuable to the community for producing valuable aromatics from EG.

Development of a novel 7 immune-related genes prognostic model for oral cancer: A study based on TCGA database.

Oral squamous cell carcinoma (OSCC) is an aggressive tumor whose prognosis has little improvement in the last three decades. Various immune-related genes have been suggested as significant roles in the development and progression of malignant cancers. In this study, we acquired and integrated differentially expressed genes of OSCC patients, including immune-related genes and transcription factors (TFs), from The Cancer Genome Atlas (TCGA) database. TF-mediated network was established to exploring the regulatory mechanisms of prognostic immune-related genes. A 7 immune-related genes prognostic model for OSCC was obtained, including CGB8, CTLA4, TNFRSF19, CCL26, NRG1, TPM2 and PLAU, which was further proved to be an independent prognostic indicator after adjusting for other clinical factors. The immune-related genes prognostic index was significantly negatively correlated to the infiltration abundances of B cells (P < 0.05) and CD8+ T cells (P < 0.05). The novel proposed immune-based prognostic model not only provided a promising biomarker and a way to monitor the long-term treatment of OSCC, but also gave a new insight into a potential immunotherapy strategy.