Week 7 HW: Genetic Circuits Part 1

Assignment Part 1: Intracellular Artificial Neural Networks (IANNs)

1.IANNs vs. Traditional Genetic Circuits (Boolean Functions)

Traditional genetic circuits are typically Boolean logic (0 or 1), meaning the output is only triggered when both inducers reach high concentrations simultaneously. In contrast, IANNs offer the following advantages:

Analog/Graded Response Processing: Traditional circuits are prone to abrupt changes near a threshold. IANNs can handle analog inputs, achieving “weighted summarization,” allowing cells to respond linearly or with finer nonlinear responses to subtle changes in signal strength.

High-Dimensional Integration: The intracellular environment is extremely complex. With each additional input to a Boolean gate, circuit complexity and crosstalk increase exponentially; IANNs, however, can aggregate signals through multiple “weak connections,” leveraging the robustness of neural networks to filter biological noise.

2.Potential Applications, Inputs, Outputs, and Limitations of IANNs

IANN can be used for precise multi-signal cancer detection. It takes three different concentrations of microRNAs (miRNAs) in the cell as input and outputs apoptosis-inducing proteins only when multiple indicators are abnormal at the same time. However, it has obvious limitations. Maintaining the deep network requires the expression of a large number of intermediate proteins, which puts metabolic pressure on the cell and consumes too much energy. Also, because transcription and translation of each layer takes time, the more layers there are, the more obvious the cell response delay becomes.

3.Draw a diagram for an intracellular multilayer perceptron where layer 1 outputs an endoribonuclease that regulates a fluorescent protein output in layer

This design depicts a two-layer Intracellular Artificial Neural Network (IANN) where Layer 1 (X1) produces an intermediate endoribonuclease (ERNA) that acts as a hidden inhibitory signal; this signal modulates the combined transcriptional activity of Layer 2 (X2) and the bias term (B1), collectively determining the final expression level of the fluorescent protein output (Y).

Assignment Part 2: Fungal Materials

What are some examples of existing fungal materials and what are they used for? What are their advantages and disadvantages over traditional counterparts?

The mycelium (fungal mycelium) as a practical application of sustainable and environmentally friendly packaging materials. By mixing the mycelium (the root-like structure of fungi) with agricultural waste (such as straw or rice husks) and placing it in a specific-shaped mold to grow, custom protective packaging blocks can be created. It is completely biodegradable and compostable: as an alternative to traditional plastic packaging such as Styrofoam, it can be safely returned to nature after use. Compared with other materials:

1. It is customizable: Specific molds can be used to grow packaging blocks of any shape and size as needed, to precisely cushion and protect delicate or fragile items.
2. Excellent protective performance: The mycelial network is not only sturdy but also has certain elasticity and shock absorption properties, making it highly suitable for use as protective packaging.

What might you want to genetically engineer fungi to do and why? What are the advantages of doing synthetic biology in fungi as opposed to bacteria?

I would like do Engineered Fungal Logic Gates for Environmental Monitoring

Objective: To genetically engineer a fungal mycelium network that functions as a biological “Logic Gate” to detect and report environmental pollution (e.g., heavy metals and pesticide runoff).

Why Fungi for this task?

Bioremediation Integration: Fungi don’t just detect pollution; they often naturally break down hydrocarbons or accumulate heavy metals. We are essentially giving a “voice” to an organism already doing the cleanup work.

Large Scale Sensing: A single fungal colony can span acres. By engineering the network, we create a “living sensor” that can monitor an entire forest floor or industrial site without needing electronic sensors or batteries.

Durability: Unlike sensitive electronic equipment, a fungal logic gate is self-healing and can survive in acidic or fluctuating soil conditions where traditional sensors might corrode.