Bioinformatics applied to biotechnology: A review towards bioenergy research

Highlights: • Bioinformatics has revealed as powerful approaches for biotechnological applications. • We present an organized view of state-of-the-art pipelines on bioinformatics. • Advances on computational capabilities are promising for solving pipeline bottlenecks. -- Abstract: The ever-increasing demand for energy, along with worldwide policies aiming sustainability, resulted in an escalation of research projects focusing on alternative routes for energy production. Among the available options, microorganism fermentation using lignocellulosic biomass as a carbon source to generate bioproducts is considered a promising technology for industrial applications, with potential to replace several sources of non-renewable origin that are widely used today. In this context, various new industrial processes have been developed, such as the second-generation ethanol technology, which allows bioethanol production from lignocellulosic biomass by genetically modified microorganisms. In recent years, fields in biotechnology were mainly driven by advances in molecular biology and genetic engineering tools, which culminated in the 'omics' revolution. Recent developments in DNA sequencing and liquid/mass spectrometry technologies, supported by research in bioinformatics and high-performance computing, allowed the identification of new organisms and metabolic processes, expanding the human knowledge about biological systems. The result of this newly gained understanding is the ability to perform genetic modifications focusing on the obtention of interesting phenotypes with increased productivity and resistance or the synthesis of new compounds that were previously produced using non-renewable routes. In this context, this review presents the bioinformatics workflows and applications of 'omics' approaches in biotechnological research, focusing on genomics, metagenomics, phylogenomics, transcriptomics, proteomics, metabolomics and their integration to enable a holistic overview of biological systems.