Research and innovation for environmental solutions deployment.

EBIC is undertaking innovative research to tackle pressing environmental challenges using synthetic biology, biotechnology, computational modelling, and engineering. By applying genetic and metabolic engineering, researchers enhance microorganisms to break down pollutants such as plastics, hydrocarbons, and metals. These engineered “microbial factories” offer sustainable and cost-effective solutions for bioremediation, supporting safer pollutant removal and a cleaner environment.

EBIC’s research also focuses on developing biosensors and biodevices that detect and respond to pollutants in real time, enabling rapid intervention to protect ecosystems and human health. Using advanced genome editing, researchers can enhance or design organisms to perform environmental tasks such as converting waste into valuable resources. By integrating synthetic biology with environmental biotechnology, EBIC aims to deliver deployable solutions for pollution from sources like wastewater and industrial effluents through improved detection, targeted degradation, and resilient biosystems.

EBIC plans to leverage expertise and technologies through four defined technical pillars:

Engineering DNA

Aims to develop rapid plasmid assembly systems for engineering environmentally relevant microbes. Modular cloning suites will be adapted to facilitate efficient plasmid assembly, incorporating CRISPR-Cas9 systems, selectable markers, and promoters/terminators for precise gene expression. This will enable precise genetic modifications in a range of bacteria.

Biomolecular Engineering

Focuses on manipulating individual biomolecules to achieve enhanced functionalities. It involves producing functional macromolecules using natural and synthetic components and designing intricate circuits and pathways. The goal is to engineer biomolecules to meet specific functional requirements and explore a wide range of applications.

Host and Consortia Engineering

Aims to develop robust and flexible synthetic biology systems for diverse biochemical reactions. This includes adapting single-cell hosts, engineering traits in multicellular organisms, and manipulating microbial consortia. Overcoming challenges related to biofilm formation, stability, scalability, and pollutant capture is essential for successful application in wastewater and waste treatments.

The Data Science/Mind Map System Biology

Integrates data science, modelling, artificial intelligence, and automation to support the design, build, test, learn (DBTL) methodology. It involves developing computational infrastructure for predicting design outcomes, optimising manufacturing processes, and integrating diverse datasets using specialised software suites, such as Infobiotics Workbench, Synbiotics, and NUFEB, facilitate computer-aided design for the simulation of microbial communities, and metabolic engineering.

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