Foundations of Synthetic Biology

Learning Outcomes

After successful completion of the course, students will be able to:

• Explain the principles of synthetic biology as an engineering discipline, including abstraction, modularity, and standardization.
• Describe and apply the Design–Build–Test–Learn (DBTL) framework in the design of biological systems.
• Identify and evaluate biological parts and DNA assembly methods used in synthetic biology.
• Explain the principles of genome engineering, including CRISPR/Cas-based approaches.
• Analyze and conceptually design genetic circuits using principles of biological logic and regulatory networks.
• Apply basic quantitative reasoning to describe system behavior (e.g., transfer functions, Hill-type responses).
• Evaluate system-level properties such as robustness, noise, and host–circuit interactions.
• Describe strategies for pathway and metabolic engineering in engineered organisms.
• Compare different chassis organisms and biological platforms, including cell-free systems.
• Explain the concepts of minimal cells, synthetic genomes, and bottom-up synthetic biology.
• Describe the role of automation, high-throughput platforms, and biofoundries in modern synthetic biology.
• Explain approaches to expanding biological function, including orthogonal systems and non-canonical biochemistry.
• Critically analyze representative synthetic biology applications and design strategies.
• Communicate synthetic biology concepts effectively using appropriate terminology and design frameworks.

Module Syllabus

Introduction to Synthetic Biology. History, scope and relationship to biotechnology and systems biology.

Engineering Principles in Biology. Abstraction hierarchies, modularity, orthogonality, standardization, SBOL, and the DBTL cycle.

Foundations of Biological Design and DNA Assembly. Standardized biological parts (promoters, RBS, CDS, terminators); Design frameworks and the BioBrick concept; Next-Generation assembly technologies (from idempotent BioBrick assembly to Gibson and GoldenGate); precision editing tools (CRISPR/Cas9 basics).

Chassis Organisms & Biological Platforms. The “Host” perspective. Pros/cons of E. coli vs. Yeast; Mammalian cell engineering (CHO, HEK); Non-model organisms; Intro to cell-free as a platform.

Quantitative Modeling & Genetic Logic (The “Unit” Level). Hill Functions & ODEs; Transfer functions; Designing AND/OR/NOT gates.

Complex Genetic Circuits (The “System” Level). Feedback loops; The Repressilator; Toggle Switches; Robustness and Noise in biology; Input/Output matching; resource burden/ host-circuit interaction.

Metabolic Engineering (From Circuits to Pathways). Flux Balance Analysis; Pathway modularity; Directed Evolution. Case studies: Artemisinin, Biofuels, Human Hormones, Sitagliptin synthesis optimization.

The Bottom-Up Approach. Minimal cells and synthetic genomes. Genome reduction, minimal genomes, synthetic chromosomes, and cellular engineering.

Automation & Biofoundries. Laboratory automation, high-throughput construction, robotic pipelines, and synthetic biology foundries.

Cell-Free Synthetic Biology. TX-TL systems; Prototyping circuits outside the cell; Paper-based diagnostics; Biosensors.

Orthogonality & Xenobiology. Expanded genetic codes; Non-canonical amino acids; XNA; Orthogonal translation systems, alternative genetic codes, and expanded biological chemistry.

iGEM & Global Innovation. The International Genetically Engineered Machine competition and the educational ecosystem of the iGEM Foundation.

Future Directions and Responsible Innovation. Engineered Living Materials (ELMs); Microbiome engineering; Biocontainment & Genetic Firewalls.

Suggested Bibliography

• Synthetic Biology – A Primer (Revised Edition, 2015) by Baldwin G, Bayer T, Dickinson R, Ellis T, Freemont PS, Kirney RI, Polizzi K, Stan G-B. ISBN: 978-1783268795.
• Synthetic Biology AI-Driven Design and Optimization (Genesis Protocol: Next Generation Technology for Biological and Life Sciences) by Jamie Flux. Edition 2024. ISBN: 979-8336931457.
• An Introduction to Systems Biology by Uri Alon (Chapman & Hall/CRC Computational Biology Series) 2nd Edition (2019). ISBN: 978-1439837177.