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

High-throughput technologies have revolutionized medical research. The advent of genotyping arrays enabled large-scale genome-wide association studies and methods for examining global transcript levels, which gave rise to the field of “integrative genetics”. Other omics technologies, such as proteomics and metabolomics, are now often incorporated into the everyday methodology of biological researchers. In this review, we provide an overview of such omics technologies and focus on methods for their integration across multiple omics layers. As compared to studies of a single omics type, multi-omics offers the opportunity to understand the flow of information that underlies disease.

Microalgae have received much interest as a biofuel feedstock in response to the uprising energy crisis, climate change and depletion of natural sources. Development of microalgal biofuels from microalgae does not satisfy the economic feasibility of overwhelming capital investments and operations. Hence, high-value co-products have been produced through the extraction of a fraction of algae to improve the economics of a microalgae biorefinery. Examples of these high-value products are pigments, proteins, lipids, carbohydrates, vitamins and anti-oxidants, with applications in cosmetics, nutritional and pharmaceuticals industries. To promote the sustainability of this process, an innovative microalgae biorefinery structure is implemented through the production of multiple products in the form of high value products and biofuel. This review presents the current challenges in the extraction of high value products from microalgae and its integration in the biorefinery. The economic potential assessment of microalgae biorefinery was evaluated to highlight the feasibility of the process.

The metabolome, the small molecule chemical entities involved in metabolism, has traditionally been studied with the aim of identifying biomarkers in the diagnosis and prediction of disease. However, the value of metabolomics has been redefined from a simple biomarker identification tool to a technology for the discovery of active drivers of biological processes. In this review, we describe the molecular mechanisms by which the active cell metabolome affects cellular physiology through modulation of other ‘omic’ levels, including the genome, epi-genome, transcriptome and proteome. This concept of activity screening guided by metabolomics to identify biologically active metabolites, or “activity metabolomics”, is having broad impact on biology.