Automated Learning and Testing with Synthetic Biology

Please be aware that the name of this course will change in 2026-27 and this course guide reflects the new course design. The new course name will be: Advanced Bioengineering.

The current state-of-the-art for bioengineering technologies combines automated workflows, high throughput experimentation, genetic engineering, synthetic biology, and statistics. By utilising these approaches, strain development for bioprocesses has accelerated with the final engineered systems possessing, e.g., improved product yields and titres compared to natural systems. As a consequence of high throughput experimentation, the generated data sets can be vast and span large design spaces, necessitating the need of statistical models to find patterns and aid experimental design. In this course, we emphasise how biological systems can be tested at scale and the datasets can be analysed to direct new experiments and strain design. This includes how to design high-throughput screening (HTS) for (biotechnologically) relevant parameters and strain design. You will also learn how to efficiently analyse datasets generated by HTS using statistical models. To highlight the use of these methods in current research, students will review and assess recent publications. After introduction, the new concepts will be practiced in dry labs using simulation environments. Eventually this newly gained knowledge can be used to design hypothetical bioprocesses based on microbial strains. The results of this analysis will be presented in a scientific paper format, and with conference-style poster presentations.

• Analyse experimental datasets with modelling approaches

• Integrate bioengineering and statistics to design new, optimised microbial strains

• Explain key elements of the strain design process for biotechnology

• Design strategies to test biotechnological relevant parameters

• Explain different experimental screening methodologies commonly applied in strain engineering and optimisation

• Implement Design of Experiment approaches

• Assess and peer-review scientific research

• Assignment poster (20%) Students produce a poster detailing their project work that will be presented at a course symposium. Posters will be assessed by examiners and peers following a rubric. Students can resubmit this work during resit periods or the following year.
• Assignment oral presentation (20%) Students will be assessed by examiners and asked to explain their project idea and defend related questions. Oral presentation will take place during course symposium. Students can resubmit this work during resit periods or the following year.
• Assignment other (10%) Students will be asked to provide peer-reviewed feedback to others in their project team following a rubric.
• Assignment report (50%) Students will write up their project research in the form of a scientific paper. This will be assessed by examiners following a rubric. Students can resubmit this work during resit periods.

It is advantageous to have followed one of the following: Introduction to Systems & Synthetic Biology (SSB32806), Applied Molecular Microbiology (MIB30806), Molecular Systems Biology (SSB30306) or Metabolic Engineering of Industrial Microorganisms (BPE34306) before the course as these cover different aspects we will build on, but these are not required. At least basic molecular biology, computer programming (as in, e.g., INF22306), mathematical skills (as taught in, e.g., BCT20306 or SSB30806), and/or statistics (as in, e.g., MAT20306) are needed prior to this course.

• Any relevant literature and materials will be provided via the Brightspace page.