Multiomics approaches and genetic engineering of metabolism for improved biorefinery and wastewater treatment in microalgae

Microalgae, a group of photosynthetic microorganisms rich in diverse and novel bioactive metabolites, have been explored for the production of biofuels, high value‐added compounds as food and feeds, and pharmaceutical chemicals as agents with therapeutic benefits. This article reviews the development of omics resources and genetic engineering techniques including gene transformation methodologies, mutagenesis, and genome‐editing tools in microalgae biorefinery and wastewater treatment (WWT). The introduction of these enlisted techniques has simplified the understanding of complex metabolic pathways undergoing microalgal cells. The multiomics approach of the integrated omics datasets, big data analysis, and machine learning for the discovery of objective traits and genes responsible for metabolic pathways was reviewed. Recent advances and limitations of multiomics analysis and genetic bioengineering technology to facilitate the improvement of microalgae as the dual role of WWT and biorefinery feedstock production are discussed. Graphical and Lay Summary Multi‐omics analysis with the aid of machine learning for metabolic modeling of pathway network to discover the key steps for targeted metabolites in microalgae has accelerated in the recent past. The development of genetic engineering techniques including gene transformation methodologies, mutagenesis, and genome‐editing tools to facilitate the improvement of microalgae as the dual role of wastewater treatment and biorefinery feedstock production is urgently needed.