Sustainable bioenergy from microalgal lipid remodeling: An AI and genetic engineering approach for the circular economy

Microalgal bioenergy shows great potential for meeting global energy needs but faces economic limits due to low biofuel precursor yields. Optimizing microalgal biomass and lipid accumulation is vital for sustainable bioenergy production; however, the trade-off between growth and lipid synthesis remains a major challenge. Therefore, this review examines the integration of genetic engineering and artificial intelligence (AI) strategies to address these challenges within a circular bioeconomy framework aimed at maximizing the bioenergy potential of microalgae. Key advancements in genetic transformation approaches targeting lipid biosynthetic pathways and associated enzymes [acetyl-CoA carboxylase (ACCase), malonyl-CoA ACP transacylase (MAT), acyl-ACP thioesterase (TE), glycerol phosphate acyltransferase (GPAT), lysophosphatidic acid acyltransferase (LPAAT), and diacylglycerol acyltransferase (DGAT)] are discussed in detail to enhance lipid productivity. Furthermore, strategies to remove stumbling blocks such as suppressing carbohydrate biosynthesis, inhibiting lipid degradation, and modulating acetyl-CoA pathways along with photosynthetic engineering (reduction of antenna size and manipulation of Calvin cycle) approaches were explored to more effectively channel carbon flux toward lipid biosynthesis. The review also examines lipid engineering approaches aimed at modifying fatty acid composition and enhancing lipid secretion, along with the manipulation of lipogenic transcription factors (Dof-type, bZIP, NRR, and MYB) to facilitate transcriptomic reprogramming. Additionally, AI algorithms have been introduced for their potential to optimize biorefinery systems by enhancing microalgal species selection, biomass harvesting, and the optimization of cultivation and biorefinery conversion processes, while simultaneously minimizing operational costs, risks, and environmental impacts. Thus, this review highlights the potential of genetic engineering and AI in microalgae to enhance bioenergy precursors, thereby advancing sustainable biofuel production within a circular bioeconomy framework for future development.