Photosynthetic production of α-farnesene by engineered Synechococcus elongatus UTEX 2973 from carbon dioxide.

Cyanobacteria are the prospective biosolar cell factories to produce a range of bioproducts through CO2 sequestration. Farnesene is a sesquiterpene with an array of applications in biofuels, pest management, cosmetics, flavours and fragrances. This is the first time a codon-optimized farnesene synthase (AFS) gene is engineered into the genomic neutral site of Synechococcus elongatus UTEX 2973 for farnesene synthesis through its endogenous methylerythritol phosphate (MEP) pathway, rendering UTEX AFS strain. Similarly, bottleneck gene(s) of the MEP pathway, 1-deoxy-D-xylulose-5-phosphate synthase (dxs) and/or fusion of isopentenyl diphosphate isomerase and farnesyl diphosphate synthase (idispA) were engineered engendering UTEX AFS::dxs, UTEX AFS::idispA and UTEX AFS::dxs::idispA strains. UTEX AFS::dxs::idispA achieves farnesene productivity of 2.57 mg/L/day, the highest among engineered cyanobacterial strains studied so far. It demonstrates farnesene production, which is 31.3-times higher than the UTEX AFS strain. Moreover, the engineered strains show similar productivity over a three-month period, stipulating the genetic stability of the strains.

Enhancement of isoprene production in engineered Synechococcus elongatus UTEX 2973 by metabolic pathway inhibition and machine learning-based optimization strategy.

An engineered Synechococcus elongatus UTEX 2973-IspS.IDI is used to enhance isoprene production through geranyl diphosphate synthase (CrtE) inhibition and process parameters (light intensity, NaHCO3 and growth temperature) optimization approach. A cumulative isoprene production of 1.21 mg/gDCW was achieved with productivity of 12.6 µg/gDCW/h in culture supplemented with 20 µg/mL alendronate. This inhibition strategy improvises the cumulative isoprene production 5.76-fold in presence of alendronate. The maximum cumulative production of isoprene is observed to be 5.22 and 6.20 mg/gDCW (54.4 and 64.6 µg/gDCW/h) at statistical and artificial neural network genetic algorithm (ANN-GA) optimized conditions, respectively. The overall increase of isoprene production is found to be 29.52-fold using an integrated approach of inhibition and ANN-GA optimization in comparison to unoptimized cultures without alendronate. This study reveals that alendronate use as a potential inhibitor and machine learning based optimization is a better approach in comparison to statistical optimization to enhance the isoprene production.

Emerging trends in the pretreatment of microalgal biomass and recovery of value-added products: A review.

Microalgae are a promising source of raw material (i.e., proteins, carbohydrates, lipids, pigments, and micronutrients) for various value-added products and act as a carbon sink for atmospheric CO2. The rigidity of the microalgal cell wall makes it difficult to extract different cellular components for its applications, including biofuel production, food and feed supplements, and pharmaceuticals. To improve the recovery of products from microalgae, pretreatment strategies such as biological, physical, chemical, and combined methods have been explored to improve whole-cell disruption and product recovery efficiency. However, the diversity and uniqueness of the microalgal cell wall make the pretreatment process more species-specific and limit its large-scale application. Therefore, advancing the currently available technologies is required from an economic, technological, and environmental perspective. Thus, this paper provides a state-of-art review of the current trends, challenges, and prospects of sustainable microalgal pretreatment technologies from a microalgae-based biorefinery concept.