Biosynthesis of the antioxidant γ-glutamyl-cysteine with engineered Yarrowia lipolytica.

The dipeptide γ-glutamylcysteine (γ-GC), the first intermediate of glutathione (GSH) synthesis, is considered as a promising drug to reduce or prevent plethora of age-related disorders such as Alzheimer and Parkinson diseases. The unusual γ-linkage between the two constitutive amino acids, namely cysteine and glutamate, renders its chemical synthesis particularly challenging. Herein, we report on the metabolic engineering of the non-conventional yeast Yarrowia lipolytica for efficient γ-GC synthesis. The yeast was first converted into a γ-GC producer by disruption of gene GSH2 encoding GSH synthase and by constitutive expression of GSH1 encoding glutamylcysteine ligase. Subsequently genes involved in cysteine and glutamate anabolism, namely MET4, CYSE, CYSF, and GDH1 were overexpressed with the aim to increase their intracellular availability. With such a strategy, a γ-GC titer of 464 nmol mg-1 protein (93 mg gDCW-1 ) was obtained within 24 h of cell growth.

Predictors of COVID-19 vaccine acceptability among health professions students in Vietnam.

BACKGROUND: The COVID-19 vaccine hesitancy or refusal has actually been a threat to global health. In the current situation, health professions students are at risk for SARS-CoV-2 infection during their internship at healthcare facilities. Furthermore, those future healthcare workers will advise people to accept the COVID-19 vaccination. Therefore, the attitude of students towards vaccine acceptance and the predicting factors needs to be elucidated. This study applied the Health Belief Model to determine predictors of COVID-19 vaccine acceptability among health professions students. METHODS: Nine hundred eleven students participated in a cross-sectional online survey in Vietnam. Data were collected from 1st April to 30th June 2021. Data analysis was performed using SPSS software version 20.0 with Chi-square and Kruskal-Wallis tests before executing multinomial logistic regression to identify predictors of the COVID-19 vaccine acceptability RESULTS: The overall vaccine acceptance, hesitancy, and refusal rates were 58% (95% CI: 54.7% - 61.3%), 40.4% (95% CI: 37.2% - 43.7%) and 1.5% (95% CI: 0.8% - 2.6%), respectively. Regarding vaccination hesitancy, a predictor such as "Receiving recent flu shots" had a negative correlation, whereas "Vaccines have little efficacy & serious adverse effects" (Perceived barriers), nationality, and majors were positive correlates. For refusal, "Unvaccinated students feasibly infected COVID-19 during hospital internship" (Perceived susceptibility) was a negative correlate. For predicting both hesitancy and refusal, "Mass media appreciating effectiveness and safety of vaccines" (Cues to action), and " Health professions students get serious complications of COVID-19 if not vaccinated" (Perceived severity) were negative predictors. In contrast, "Manufacturers do not disclose adverse effects of vaccines" (Cues to action), and "Adverse effect causes death" (Perceived barrier) were recognized as positive predictors. Strong Health Belief Model predictors of vaccine refusal were "Manufacturers do not disclose adverse effects of vaccines" (Cues to action) with OR= 5.299(95% CI: 1.687-16.641, p= 0.004), and "Adverse effect causes death" (Perceived barrier) with OR= 10.255 (95% CI = 3.528-29.814, p= 0.0005). CONCLUSION: Health professions students' acceptability of COVID-19 vaccination might be based on the perceived susceptibility to and severity of COVID-19, concerns about vaccine efficacy and safety, and the influence levels of information from various sources. Health education and measures to prevent the harmful effects of COVID-19 vaccine misinformation could potentially improve the acceptance rate of the COVID-19 vaccine.

Improvement of glutathione production by a metabolically engineered Yarrowia lipolytica strain using a small-scale optimization approach.

OBJECTIVE: In this study, we aimed to maximize glutathione (GSH) production by a metabolically engineered Yarrowia lipolytica strain using a small-scale optimization approach. RESULTS: A three levels four factorial Box-Behnken Design was used to assess the effect of pH, inulin extract, yeast extract and ammonium sulfate concentrations on cell growth and to generate a mathematical model which predict optimal conditions to maximize biomass production and thus GSH titer. The obtained results revealed that only yeast and inulin extract concentrations significantly affect biomass production. Based on the generated model, a medium composed of 10 g/L of yeast extract and 10 g/L of inulin extract from Jerusalem artichoke was used to conduct batch cultures in 2 L bioreactor. After 48 h of culture, the biomass and the glutathione titer increased by 55% (5.8 gDCW/L) and 61% (1011.4 mg/L), respectively, as compared to non-optimized conditions. CONCLUSION: From the obtained results, it could be observed that the model established from small scale culture (i.e. 2 mL) is able to predict performance at larger scale (i.e. 2 L bioreactor, two orders of magnitude scale-up). Moreover, the results highlight the ability of the optimized process to ensure high titer of glutathione using a low-cost carbon source.

Engineering Yarrowia lipolytica for the Synthesis of Glutathione from Organic By-Products.

Tripeptide glutathione, which plays important roles in many cellular mechanisms, is also a biotechnology-oriented molecule with applications in medicine, food and cosmetic. Here, the engineering of the yeast Yarrowia lipolytica for the production of this metabolite at high titer values from various agro-industrial by-products is reported. The constitutive overexpression of the glutathione biosynthetic genes GSH1 and GSH2 encoding respectively γ-glutamylcysteine synthetase and glutathione synthetase, together with the INU1 gene from Kluyveromyces marxianus encoding inulinase yielded a glutathione titer value and a productivity of 644 nmol/mg protein and 510 µmol/gDCW, respectively. These values were obtained during bioreactor batch cultures in a medium exclusively comprising an extract of Jerusalem artichoke tuber, used as a source of inulin, and ammonium sulfate, used as a nitrogen source.

Organic Wastes as Feedstocks for Non-Conventional Yeast-Based Bioprocesses.

Non-conventional yeasts are efficient cell factories for the synthesis of value-added compounds such as recombinant proteins, intracellular metabolites, and/or metabolic by-products. Most bioprocess, however, are still designed to use pure, ideal sugars, especially glucose. In the quest for the development of more sustainable processes amid concerns over the future availability of resources for the ever-growing global population, the utilization of organic wastes or industrial by-products as feedstocks to support cell growth is a crucial approach. Indeed, vast amounts of industrial and commercial waste simultaneously represent an environmental burden and an important reservoir for recyclable or reusable material. These alternative feedstocks can provide microbial cell factories with the required metabolic building blocks and energy to synthesize value-added compounds, further representing a potential means of reduction of process costs as well. This review highlights recent strategies in this regard, encompassing knowledge on catabolic pathways and metabolic engineering solutions developed to endow cells with the required metabolic capabilities, and the connection of these to the synthesis of value-added compounds. This review focuses primarily, but not exclusively, on Yarrowia lipolytica as a yeast cell factory, owing to its broad range of naturally metabolizable carbon sources, together with its popularity as a non-conventional yeast.