AUTHOR=Amer Bashar , Baidoo Edward E. K. 

TITLE=Omics-Driven Biotechnology for Industrial Applications

JOURNAL=Frontiers in Bioengineering and Biotechnology

VOLUME=Volume 9 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2021.613307

DOI=10.3389/fbioe.2021.613307

ISSN=2296-4185

ABSTRACT=Biomanufacturing is a key component of biotechnology that uses biological systems to produce bioproducts of commercial relevance, which are of great interest to the energy, material, pharmaceutical, food, and agriculture industries. Biotechnology-based approaches such as synthetic biology and metabolic engineering are heavily reliant on “omics” driven systems biology to characterize and understand metabolic networks. Knowledge gained from systems biology experiments aids the development of synthetic biology tools and the advancement of metabolic engineering studies towards establishing robust industrial biomanufacturing platforms. In this review, we examine the influence of “omics” technologies on biotechnology-related research areas and their respective industries during the last 20 years. From our findings, genomics appears to be the dominant “omics” technology that is being utilized for biotechnology and related research areas. In addition to this, proteomics and metabolomics appear to have a higher impact on synthetic and systems biology, whereas adaptive laboratory evolution (ALE) has benefited from genomics, transcriptomics, and metabolic flux analysis. Genomics, transcriptomics, metabolic flux analysis, and metabolomics (to some extent) appear to have a higher impact on bioenergy related research areas such as biofuel/green fuel, bioethanol, and biodiesel. The genomics and proteomics multi-omics approach had the greatest impact on biomanufacturing. In general, the application of uni-omics approaches had a significantly higher impact on biotechnology approaches and industrial research areas than multi-omics, which could be a consequence of the cost of added “omics” technologies, and the need for additional “omics” expertise, as well as challenging multi-omics data integration and interpretation. The information gained from this review could help to facilitate the experimental design of individual “omics” and multi-omics studies towards improving industrial biotechnology research.