ABSTRACT
Microalgae constitute a large and diverse group of unicellular phototrophic and heterotrophic organisms, which comprise the base of the food chain and are evolutionarily distinct from other species. They have emerged as a promising group in the production of bioproducts and biofuel, as well as for the remediation of efuents. Indigenous populations have used microalgae for centuries and the commercial application of microalgae has been extensively reviewed [1-4]. The efciency of the microalgal production process depends on higher biomass, yield, productivity, and process robustness. These parameters highly depend on the host microorganism. Natural screening, mutagenesis, selection, bioprocess development, genetic engineering, and metabolic engineering strategies have been adopted to increase the metabolic capabilities of the host microorganisms [5]. Nevertheless, problems such as the accumulation of toxic intermediates or metabolic stress resulting in a decreased cellular tness need to be solved. The lack of knowledge about the regulatory mechanisms of key enzymes and the complex relationships between genotype and phenotype are still barriers to the development of efcient cell factories. The overexpression, deletion, or introduction of heterologous genes in specic metabolic pathways does not always result in the desired phenotype. Recent remarkable innovations in platforms for omics-based research and application development have provided crucial solutions to these problems. A combinatorial approach using multiple omics platforms and the integration of their outcomes is now an effective strategy for clarifying the molecular systems that are integral to improving algal productivity.
