Introduction
Synthetic biology is a vast field that leverages the strengths of various disciplines to study biological systems. Among these, engineering is perhaps the one that most significantly revolutionizes the traditional approach to biology. Drawing inspiration from engineering methods to address diverse problems makes it possible to design biological systems with new or improved behaviors, while also ensuring simplicity and greater control. Engineering, therefore, provides the tools to move from simply observing life to actually constructing it.
What is meant by the engineering method?
We could define engineering as a philosophy, so versatile that it can be applied in many fields. In fact, we can talk about various types of engineering: mechanical, computer, chemical, and many more. Among these, there is even genetic engineering, a branch that focuses on modifying the genome of living organisms to solve various issues, such as environmental or health-related problems.
But why call engineering a philosophy? Engineering can be thought of as a set of frameworks and methods that structure a particular logical reasoning process aimed at solving any type of problem. Below are the main frameworks that define the engineer’s perspective when facing a problem:
- Decomposition: every complex problem is composed of multiple sub-problems. Therefore, it is possible to break down the larger set, the complex problem, into many smaller sets, sub-problems. These, by definition, are less complex. Applying this principle results in more individual problems, but ones that are easier to handle and logically distinct. By solving the sub-problems independently and then integrating them, it becomes possible to solve the initially complex problem;
- Modularity: this involves designing components that are simple, function independently, and are also integrable with one another. A concrete example: a car, which is a complex system, is made up of simpler parts like wheels, an engine, pipes, etc., all of which can exist both individually and as parts of other complex systems;
- Abstraction: the idea is to hide the complexity of a system, showing only the relevant information at a given level of interaction. Returning to the car example, when we press the accelerator, we know the vehicle will move forward, but we are unaware of the series of mechanisms that are triggered to make that happen. The accelerator pedal thus represents a simplified interface that allows us to control a complex system without needing to understand its inner workings;
- Standardization: this means establishing rules and protocols that allow an entity to be reused in environments and conditions different from those for which it was originally designed. The goal is to create a unified language capable of providing structure and organization to any new system
To apply the above frameworks effectively, engineering uses mathematical and physical models to design, analyze, and support decision-making in a precise and analytical manner.
However, frameworks alone are not enough to organize thought. A reasoning method is also needed. The engineering approach can be summarized in a simple, cyclical four-phase model known as the DBTL cycle:
- D (Design): the design phase, where the next steps are planned;
- B (Build): the implementation phase, where what was planned in theory is concretely realized;
- T (Test): the experimentation phase, where results are gathered to validate the model;
- L (Learn): the analysis phase, where results from the previous step are examined. This helps assess the progress of the project and identify the strengths and weaknesses of the current system. These insights are then used to improve the next “Design” phase of the DBTL cycle
The goal is to achieve small intermediate targets with each cycle, eventually leading to the final iteration that meets the main objective.
The Role of Engineering in Synthetic Biology
Engineering is at the core of synthetic biology. Biology studies extremely complex systems, but through the engineering principle of simplification, that complexity can be reduced. By treating DNA, RNA, proteins, and other key biological elements as modular components, it becomes possible to program cells as if they were circuits.
Principles like decomposition, modularity, abstraction, and standardization are applied to design organisms with specific functions, such as bacteria that produce medicine, detect diseases, or break down pollutants.
The systemic and iterative approach of the DBTL cycle also makes it possible to progressively refine biological designs, improving their effectiveness in the lab or in real-world environments.
On a practical level, think of the concrete results achieved thanks to synthetic biology: we now have bacteria programmed to detect and fight cancer, microorganisms capable of absorbing CO₂, or breaking down plastics, contributing to the fight against climate change.
Conclusions
From what we’ve seen, the engineering approach ensures efficiency, reproducibility, and scalability. This integration between disciplines, until recently quite separate, is enabling the achievement of previously unattainable results. The partnership between biology and engineering, as a metaphor for the convergence of reality and technology, is a prime example of multidisciplinarity.
As mentioned at the beginning, engineering spans multiple fields, making it a bridge between the various islands of scientific theory. This gives rise to a broad and comprehensive framework of multidisciplinarity, a cultural and scientific transformation that, if embraced with awareness, responsibility, and long-term vision, can lead to revolutionary solutions.