Metabolic engineering for sustainability and health.

Bio-based production of chemicals and materials has attracted much attention due to the urgent need to establish sustainability and enhance human health. Metabolic engineering (ME) allows purposeful modification of cellular metabolic, regulatory, and signaling networks to achieve enhanced production of desired chemicals and degradation of environmentally harmful chemicals. ME has significantly progressed over the past 30 years through further integration of the strategies of synthetic biology, systems biology, evolutionary engineering, and data science aided by artificial intelligence. Here we review the field of ME from its emergence to the current state-of-the-art, highlighting its contribution to sustainable production of chemicals, health, and the environment through representative examples. Future challenges of ME and perspectives are also discussed.

MALDI-TOF MS-based total serum protein fingerprinting for liver cancer diagnosis.

Serum is one of the most commonly used samples in many studies to identify protein biomarkers to diagnose cancer. Although conventional enzyme-linked immunosorbent assay (ELISA) or liquid chromatography-mass spectrometry (LC-MS)-based methods have been applied as clinical tools for diagnosing cancer, there have been troublesome problems, such as inferior multiplexing capabilities, high development costs and long turnaround times, which are inappropriate for high-throughput analytical platforms. Here, we developed a simple and robust cancer diagnostic method using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS)-based total serum protein fingerprinting. First, serum samples were simply diluted with distilled water and subsequently spotted onto a MALDI plate without prior chromatographic purification or separation. The sample preparation method was enough to collect reproducible total serum protein fingerprints and would be highly advantageous for high-throughput assay. Each of the integrated main spectrum profiles (MSPs), which are representative of liver cancer patients (n = 40) or healthy controls (n = 80), was automatically generated by the MALDI Biotyper 3 software. The reliability of the integrated MSPs was successfully evaluated in comparison with a blind test set (n = 31), which consisted of 13 liver cancer patients and 18 healthy controls. Additionally, our partial least squares discriminant analysis (PLS-DA) demonstrated a statistically significant difference in MALDI-TOF MS-based total serum protein fingerprints between liver cancer patients and healthy controls. Taken together, this work suggests that this method may be an effective high-throughput platform technology for various cancer diagnoses and disease evaluations.

Discovery of glycocholic acid and taurochenodeoxycholic acid as phenotypic biomarkers in cholangiocarcinoma.

Although several biomarkers can be used to distinguish cholangiocarcinoma (CCA) from healthy controls, differentiating the disease from benign biliary disease (BBD) or pancreatic cancer (PC) is a challenge. CCA biomarkers are associated with low specificity or have not been validated in relation to the biological effects of CCA. In this study, we quantitatively analyzed 15 biliary bile acids in CCA (n = 30), BBD (n = 57) and PC (n = 17) patients and discovered glycocholic acid (GCA) and taurochenodeoxycholic acid (TCDCA) as specific CCA biomarkers. Firstly, we showed that the average concentration of total biliary bile acids in CCA patients was quantitatively less than in other patient groups. In addition, the average composition ratio of primary bile acids and conjugated bile acids in CCA patients was the highest in all patient groups. The average composition ratio of GCA (35.6%) in CCA patients was significantly higher than in other patient groups. Conversely, the average composition ratio of TCDCA (13.8%) in CCA patients was significantly lower in all patient groups. To verify the biological effects of GCA and TCDCA, we analyzed the gene expression of bile acid receptors associated with the development of CCA in a CCA cell line. The gene expression of transmembrane G protein coupled receptor (TGR5) and sphingosine 1-phosphate receptor 2 (S1PR2) in CCA cells treated with GCA was 8.6-fold and 3.4-fold higher compared with control (untreated with bile acids), respectively. Gene expression of TGR5 and S1PR2 in TCDCA-treated cells was not significantly different from the control. Taken together, our study identified GCA and TCDCA as phenotype-specific biomarkers for CCA.

Three-dimensional brain-like microenvironments facilitate the direct reprogramming of fibroblasts into therapeutic neurons.

Biophysical cues can improve the direct reprogramming of fibroblasts into neurons that can be used for therapeutic purposes. However, the effects of a three-dimensional (3D) environment on direct neuronal reprogramming remain unexplored. Here, we show that brain extracellular matrix (BEM) decellularized from human brain tissue facilitates the plasmid-transfection-based direct conversion of primary mouse embryonic fibroblasts into induced neuronal (iN) cells. We first show that two-dimensional (2D) surfaces modified with BEM significantly increase the generation efficiency of iN cells and enhance neuronal transdifferentiation and maturation. Moreover, in an animal model of ischaemic stroke, iN cells generated on the BEM substrates and transplanted into the brain led to significant improvements in locomotive behaviours. We also show that compared with the 2D BEM substrates, 3D BEM hydrogels recapitulating brain-like microenvironments further promote neuronal conversion and potentiate the functional recovery of the animals. Our findings suggest that 3D microenvironments can boost nonviral direct reprogramming for the generation of therapeutic neuronal cells.