Biotechnology aims to utilize biological systems to solve societal challenges ranging from sustainable production of fuels, chemicals and agricultural products to improving human health through diagnostic tools and therapeutics. Despite its great potential, biotechnological product development is challenging and time consuming due to our limited understanding of the biological systems that are employed for example for renewable chemical production. Past 20 years have seen a rapid development in so called omics technologies that allow comprehensive characterization biological systems at different levels from genes to transcripts to proteins and metabolites. These omics technologies allow building complete catalogues of parts of a biological system, the interactions between the parts, and the states of the system in any given condition. These catalogues can in turn be used to build predictive models of how biological systems function, and these models can be used to design improvements in biological systems that enhance the performance of the system. As an example, a model of cellular metabolism can be used to design how we should manipulate the gene complement of a microbial strain to optimize the flow of material from a feedstock such as a sugar to a specific chemical such as a vitamin.
Omics data is currently rapidly accumulating in public domain and proprietary databases and has the potential to accelerate development of biotechnology-based products significantly. However, omics data is not leveraged effectively in the biotechnology industry due to lack of tools to rapidly access public and private data and to design cellular manipulations or interventions based on the data. With this project we aim to make a broad spectrum of omics data useful to the biotechnology industry covering application areas ranging from industrial biotechnology to human health. Our approach is based on using omics data to develop, parameterize and constrain large-scale models of biological systems. We will develop novel approaches for omics data analysis using models to enable 1) Identification of novel enzymes and pathways by mining genomic data collected from environments such as oceans and soils, 2) Data-driven design of cell factories for the production of chemicals and proteins, and 3) Analysis and design of microbial communities relevant to human health, industrial biotechnology and agriculture.
All research efforts will be integrated in an interactive web-based DD-DeCaF platform that will be available for academic research and teaching as well as industrial product development communities. The DD-DeCaF platform will incorporate tools to analyze and visualize diverse omics datasets, and to use these datasets for designing cell factories and communities. This platform can be leveraged by biotechnology SMEs to increase their competitiveness through economizing resources and reducing time-to-market within their respective focus areas. The platform will be composed of standardized and interoperable components that service-oriented bioinformatics SMEs involved in the project can reuse in their own products. Two end-user companies will be involved in practical testing of the platform built within the project using proprietary omics data generated at the companies. These companies are involved in production of nutrition-related products (vitamins and other dietary supplements) in a renewable fashion and the project is expected to accelerate the development of new products within the companies.
