Engineering Biological Circuits: The Future of Wearable Biotechnology
An exploration of synthetic biology, biological circuits, and wearable biotechnology
Decoding Biology is currently read in 49 US states and 92 countries. If you enjoy today’s newsletter, help me achieve my goal of reaching 4,000 subscribers by sharing it with a friend. Thank you!
🦠 Engineering Biological Circuits: Past, Present, and Future
Nearly 65 years ago, scientists began to appreciate how firmly established ideas from the discipline of electrical engineering could be applied to biological pathways, which are the series of interactions between molecules in cells, leading to specific products or cellular changes, as demonstrated in the figure below
These scientists aimed to build biological circuits, much like electrical circuits, that could be toggled on and off to perform specific tasks like sensing environmental signals, processing information, and eliciting cellular responses at will. However, it wasn't until the genomics revolution of the late 1990s and early 2000s that a formalized system for designing, constructing, and programming cellular circuits began to take form, leading to the birth of synthetic biology, a field that has seen remarkable growth year after year since its inception.
For a more comprehensive take on synthetic biology and its potential to accelerate scientific discovery, check out Drew Endy’s paper titled Foundations for Engineering Biology.
Synthetic biology is poised to revolutionize the biotechnology industry, leading to cheaper targeted therapeutics, greener fuels and more sustainable materials, enhanced abilities to sense biological molecules in our bodies and environment, and even reintroduce previously endangered species such as the Dodo bird. In this article, I'll provide an overview of synthetic biology and how the basic technology of building biological circuity works. Additionally, I’ll discuss interesting emerging research areas, such as wearable biotechnology.
◈ ◈ ◈
🦠 Deconstructing Biological Circuits
A biological circuit is an interconnected network of molecular components within a living organism that functions in an analogous manner to electronic circuits found in electrical systems.
Biological circuits can exhibit various architectures, including positive and negative feedback loops, feedforward loops, and more complex network structures. The design of these circuits is inspired by principles from electrical engineering and computer science, where the goal is to achieve predictable and controllable cellular behaviors.
Biological circuits generally consist of genetic elements, such as DNA, RNA, and proteins, that interact with each other to process information and regulate cellular activities. These circuits can be engineered to perform specific tasks, such as sensing signals from the surrounding environment, processing information, and triggering cellular responses. The image below demonstrates a natural biological circuit known as the Lac Operon:
The lac operon is a textbook example of an inducible biological circuit, which encodes for genes that transport and metabolize lactose in E. coli and many other enteric bacteria. Describing the lac operon through the language of biological circuits involves drawing parallels between the components and interactions in the lac operon system and those in electronic circuits.
The LacI repressor acts as an ON and OFF switch in the biological circuit by blocking or allowing the RNA polymerase to bind to the promoter. When the LacI repressor “switch” is OFF, it prevents RNA polymerase from binding to the promoter. Alternatively, when lactose sugars are present, the lacI repressor “switch” goes from OFF to ON, allowing the RNA polymerase to bind to its promoter and initiate transcription. Once transcription is activated, structural genes are transcribed, resulting in the production of enzymes that carry out lactose metabolism. Then, once all of the lactose is metabolized, the LacI repressor switches back to the OFF position, preventing RNA polymerase from binding the promoter and effectively breaking the connection in the circuit.
◈ ◈ ◈
🦠 Building and Simulating Biological Circuits
As previously mentioned, in synthetic biology, researchers aim to design, construct, and manipulate biological circuits to achieve specific, programmable functions within cells or organisms. A biological circuit has three fundamental components: input modules, processing units, and output modules.
Input modules detect signals from the environment or within the cell and can include sensors or receptors that recognize specific molecules and changes in environmental conditions, among other cues. Processing units and output modules, on the other hand, translate the processed information into a cellular response. In practice, this could involve activating or repressing specific genes, producing proteins, or other changes in cellular behavior.
Genetic regulatory elements, such as promoters, enhancers, and transcription factors, often govern the interactions between these input and output modules. These elements act as ON/OFF switches that control the expression of genes in response to specific signals. For example, consider a simple biological circuit designed to respond to a specific environmental signal, such as a nutrient or a chemical. In this hypothetical circuit, the input module would be a sensor protein that detects the environmental signal, the processing unit would be a genetic switch that activates the expression of a fluorescent protein in response to the signal, and the output module could be a fluorescent protein, whose expression serves as a visual indicator of the presence of the environmental signal.
As you can see from the example above, biological circuits, like those found in living organisms, share similarities with electronic circuits in terms of performing logical operations. While not as rigid or precisely engineered as computer circuits, biological systems exhibit logic-like behaviors that allow cells to process information and respond to their environment. Here are some ways in which biological circuits use logic:
Boolean and combinatorial logic in gene regulation: Boolean logic is a form of algebra in which results are declared TRUE or FALSE. Interestingly, the expression of certain genes, such as the lac operon, follows boolean logic by behaving like binary ON or OFF switches based on the presence of certain molecules (in this case, lactose). Alternatively, combinatorial logic involves the integration of multiple inputs to determine a specific output. For example, the combination of transcription factors acting on a gene's promoter represents a form of biological combinatorial logic where gene regulation involves the integration of multiple inputs to determine the expression of a particular gene.
Feedback loops in biological systems: A feedback loop is a process in which the outputs of a system are circled back and used as inputs. In biological systems feedback loops help to regulate signaling processes, maintain homeostasis, and control the timing of cellular events.
Conditionals in signal transduction pathways: In programming languages condition statements such as if, then, and else allows you to control the flow of a program. Signal transduction pathways often use conditional-based logic in their “decision making”, which ultimately controls how genes are expressed.
In the code sample below, I’ll demonstrate how basic programming logic can be used to construct gene circuits:
Now, let’s break the code down one step at a time to understand how it works:
class BacterialGeneCircuit:
def __init__(circuit):
circuit.signal_detected = False
circuit.green_fluorescent_protein = 0First, a class named BacterialGeneCircuit is defined, which represents a simplified biological circuit in a bacterial cell. Next, the _init_ command initialized the circuit with two attributes including signal_detected, which represents whether a signal is detected, and green_fluorescent_protein, which represents whether green fluorescent protein has been produced.
def detect_signal(circuit, chemical_signal):
if chemical_signal == "chemical present":
circuit.signal_detected = TrueNext, a function named detect_signal is defined, which simulates the detection of a specific chemical signal. If the chemical_signal is equal to ‘chemical present’, it sets signal_detected to True.
def activate_circuit(circuit):
if circuit.signal_detected:
circuit.green_fluorescent_protein = 1Then, a function named activate_circuit checks if signal_detected is True, and if so it turns on the gene for the green fluorescent protein by setting green_fluorescent_protein to 1.
gene_circuit = BacterialGeneCircuit()
environmental_signal_present = random.choice(["no chemical present", "chemical present"])
gene_circuit.detect_signal(environmental_signal_present)
gene_circuit.activate_circuit()Finally, an instance of the BacterialGeneCircuit class is created with the code gene_circuit = BacterialGeneCircuit(), representing an individual biological circuit within a bacterial cell.
Then the code environmental_signal_present = random.choice([…etc.]) simulates the presence of an environmental signal by randomly choosing between "no chemical present" and "chemical present."
After that, the code uses the detect_signal function is called on the gene_circuit instance to simulate the detection of the environmental signal based on the previously simulated value. Following that, the activate_circuit function is called on the gene_circuit instance to turn the gene for green flour sent protein on if the chemical signal was detected. Lastly, the code prints the result of the simulation.
◈ ◈ ◈
🦠Current Applications of Synthetic Biology
Up to this point, we've covered what synthetic biology is, the broad strokes of building biological circuits, and how biological circuity relies on logical operations like those used in traditional engineering disciplines. In this last section, I’m going to talk about my favorite emerging research area within synthetic biology: biosensing.
Biosensing refers to the use of engineered biological systems to detect and respond to specific environmental signals, which can range from small molecules to complex environmental cues. As a field, biosensing aims to create biological circuits that act as sensors, mimicking or enhancing the natural sensing capabilities of living organisms.
In nature, cells evolve various receptors to detect environmental changes. In synthetic biology, these natural components are modified or combined to create custom biosensors or detection modules that recognize a specific target chemical. Detection modules are often engineering proteins or nucleic acids that bind to the target molecules. Once a biosensor detects a specific target chemical, the biosensor relays the information as a measurable signal. This could involve a change in gene expression or the production of a fluorescent protein whose expression is proportional to the amount of the target chemical that is sensed. Finally, an output module detects the aforementioned measurement signal. For example, in a biosensor expressing green fluorescent protein in response to a chemical signal, the output module may consist of photodiodes that measure light emission.
◈ ◈ ◈
🦠 Engineering Wearable Biological Circuits
As previously mentioned, biosensing refers to the use of engineered biological systems to detect and respond to specific environmental signals, which can range from small molecules to complex environmental cues. Imagine if we created a smartwatch-like wearable biosensor that combines biological sensing elements with electronic components to create a device capable of detecting specific chemicals or analytes in the environment. Here's how it may be achieved:
Modify biological receptors for wearable use:First, we want to select or engineer receptors, such as proteins or nucleic acids, that are stable and easily integrated into a wearable device. We then want to miniaturize the detection modules housing our receptors to fit within the constraints of a wearable device while retaining full functionality. This may involve using microfluidics or nanomaterials.
Develop a reliable signal transduction mechanism:Next, a signal transduction mechanism must be developed, which converts the binding of the target chemical to its receptor into a measurable signal. This could involve electronic sensors based on field effect transistors or photodiodes. For example, let's say the biosensor induces a change in gene expression or produces a fluorescent protein in response to the target chemical. Then, the signal transduction mechanism must detect and quantify this change with its on-device sensors and integrate the signal.
Integrate the output module: After developing a biosensor and signal transduction mechanism, a wearable device must have an output module to disobey or transmit the detected information. For example, if the biosensor expresses a fluorescent protein, and the signal transduction mechanism consists of photodiodes that measure the emitted light, the output could be displayed on the smartwatch screen or transmitted to a connected smartphone app. Importantly, the user interface should be user-friendly, provide real-time feedback on the detected environmental changes, and include notifications, visual displays, or other alerts.
Account for power needs and ensure biocompatibility:Continuous real-time biosensors can be exceptionally power-hungry. As a result, it's important to deeply consider the power requirements for the biosensor and integrate an appropriate power source into the wearable device. This could involve small batteries or energy harvesting technologies to ensure sustained operation. Additionally, you need to consider the biocompatibility and safety of the materials used in the wearable device, especially those that come in contact with the user's skin.
Ensure connectivity for optimal functionality: Finally, ensure that the wearable device has connectivity features, allowing it to share data with other devices, such as smartphones or cloud platforms. This enables continuous monitoring and data analysis.
By integrating these previously mentioned elements, a smartwatch-like wearable biosensor could provide users with real-time information about specific environmental chemicals, making it valuable for applications like personal environmental monitoring, health tracking, or workplace safety.
