week-07-hw-genetic-circuits-part-ii

< Assignment Part 1: Intracellular Artificial Neural Networks (IANNs)

Assignment Part 1: Intracellular Artificial Neural Networks (IANNs)

1. Advantages of IANNs over Traditional Boolean Genetic Circuits

Continuous Input/Output Behavior

Traditional genetic circuits operate as Boolean functions a gene is either ON or OFF (0 or 1). IANNs instead process continuous values, meaning inputs and outputs can exist across a full range (like protein concentrations or expression levels). This is much closer to how biological systems actually work, where gene expression is rarely all or nothing but rather graded and proportional to stimuli.

Non-Linear Computation

IANNs can compute non-linear functions of their inputs, meaning they can capture complex, threshold-based, and context dependent behaviors. For example, a cell differentiating in response to a morphogen gradient doesn’t just respond to “present/absent” it responds proportionally and with threshold effects that require non-linear processing.

Weighted Multi-Input Integration

IANNs can simultaneously integrate multiple inputs with different weights, meaning some signals contribute more than others to the final output. Boolean circuits would require an exponentially growing number of logic gates to approximate this, making them impractical at scale.

Scalability and Efficiency

As the number of inputs grows, Boolean circuits become combinatorially complex. IANNs handle additional inputs more elegantly because the same architecture naturally accommodates new weighted signals without redesigning the entire circuit.

2. Application: Assessing Metastatic Potential of a Localized Tumor

An IANN could be engineered into cells to continuously monitor the expression levels of multiple biomarkers associated with metastatic progression, such as matrix metalloproteinases (MMPs), epithelial-mesenchymal transition (EMT) markers like E-cadherin and vimentin, and hypoxia inducible factors (HIFs).

Input Behavior

The inputs would be the continuous concentration levels of these biomarkers inside or around the tumor cell. Each input would carry a different weight depending on its known contribution to metastatic risk for example, high MMP expression might be weighted more heavily than moderate HIF levels.

Output Behavior

The output would be a graded, continuous signal such as the expression level of a fluorescent reporter protein proportional to the calculated metastatic risk. A low fluorescence signal would indicate low risk, while high fluorescence would indicate high metastatic potential, allowing spatial visualization of the tumor.

Limitations

• Biological noise: natural fluctuations in gene expression inside cells could produce false positives or inconsistent readings
• Delivery: engineering and delivering the IANN circuit into tumor cells in vivo remains technically challenging
• Crosstalk: circuit components could interfere with endogenous cellular pathways, affecting accuracy
• Response time: protein concentration changes are slow compared to electronic systems, potentially delaying the output signal
• Stability: the engineered circuit may be lost or silenced over cell divisions due to epigenetic changes or plasmid dilution

3. Multilayer Perceptron Diagram

Diagram: An intracellular multilayer perceptron where Layer 1 outputs an endoribonuclease (e.g., Csy4) that regulates a fluorescent protein output in Layer 2.

Layer 1: X1, X2 → Tx → mRNA → Tl → Csy4 (endoribonuclease)

Layer 2: Csy4 → regulates mRNA of fluorescent protein → Tl → Fluorescent Protein Output

Assignment Part 2: Fungal Materials

1. Existing Fungal Materials and Their Uses

Some examples of fungal materials include Ecovative, used for packaging and construction, and Mylo, a leather made from mycelium used in clothing and accessories.

Advantages over Traditional Materials

• Biodegradable: they do not pollute the environment
• Can grow into any desired shape
• Produced from cheap agricultural waste such as straw or rice husks

Disadvantages over Traditional Materials

• Sensitive to moisture
• Lower mechanical resistance than traditional counterparts such as plastic or animal leather
• Large-scale production cost remains high

2. Genetic Engineering of Fungi and Advantages over Bacteria

Fungi could be genetically engineered to improve their ability to degrade plastic more efficiently, helping reduce environmental contamination. They could also be engineered to produce complex medicines or to make their mycelium materials more resistant to moisture.

Advantages of Synthetic Biology in Fungi vs. Bacteria

• Fungi are eukaryotic organisms: they have a nucleus and are more complex cells, similar to human cells which allows them to produce more complex proteins correctly
• Fungi can grow as 3D structures through their mycelium network, which bacteria cannot, making them better suited for material production and large-scale industrial applications

Assignment Part 3: First DNA Twist Order

Review Part 3: DNA Design Challenge of the week 2 homework. Design at least 1 insert sequence and place it into the Benchling/Kernel/Other folder you shared in the Google Form above. Document the backbone vector it will be synthesized in on your website.

Insert Design: HSP90-GFP Fusion Biosensor

The insert sequence consists of a fusion protein between the chaperone HSP90 and Green Fluorescent Protein (GFP). To create this fusion, the HSP90 stop codon was removed and replaced with a short linker sequence, followed by the GFP sequence without its start codon, creating a continuous fusion protein where GFP fluorescence directly indicates HSP90 presence and expression levels.

Biological purpose: HSP90 stabilizes oncogenic proteins such as BCR-ABL. When cancer cells develop resistance to imatinib, they frequently overexpress HSP90 to protect mutated BCR-ABL. This biosensor allows real-time visualization of HSP90 levels the brighter the fluorescence, the higher the HSP90 expression and the higher the likelihood of emerging imatinib resistance.

Backbone vector: The insert was placed into the pET-28a(+) backbone vector within the Multiple Cloning Site (MCS). This vector provides a T7 promoter for strong expression, a kanamycin resistance marker for bacterial selection, and a His-tag for protein purification.

https://benchling.com/majobolivar/f_/7qelUF55UQ-week-7-dna-order/