Week 7 HW: Genetic Circuits Part II: Neuromorphic Circuits

Part 1: Intracellular Artificial Neural Networks (IANNs)

Advantages of IANNs over traditional Boolean genetic circuits

Intracellular Artificial Neural Networks (IANNs) differ from traditional genetic circuits because they process information in a graded, weighted, and adaptive manner rather than using only binary ON/OFF logic.

  1. Analog signal processing Traditional Boolean circuits treat inputs as discrete states (0 or 1). IANNs can respond continuously to varying molecular concentrations. It allows finer control, tunable responses, and probabilistic decision-making.
  2. Ability to integrate many inputs Boolean circuits become increasingly complex as the number of inputs grows because each logical relationship requires additional gates. IANNs naturally combine many weighted inputs similarly to biological signaling pathways, which enables scalable intracellular computation.
  3. Learning-like behavior and adaptability Traditional logic circuits are static once constructed. IANNs can theoretically mimic neural-network properties such as weighting, feedback adaptation, memory, nonlinear classification etc.
  4. Noise tolerance Boolean circuits are often fragile under noise because they depend on strict thresholds, while biological systems are noisy.
  5. Compact implementation of complex behaviors Complex Boolean functions often require many genes and regulatory parts. A multilayer IANN can sometimes implement the same classification behavior with fewer regulatory interactions, reusable regulatory motifs, and hierarchical processing.
  6. Overall, better representation of natural biology

Useful application of an IANN

Application: Smart cancer-targeting therapeutic cell

The engineered cell should:

  1. Detect a cancer-specific molecular signature
  2. Distinguish cancer cells from healthy cells
  3. Release a therapeutic payload only when confidence is high

Inputs (molesular factors):

  1. High lactate concentration
  2. Hypoxia marker
  3. miRNA associated with tumors
  4. Elevated TGF
  5. Inflammatory cytokine pattern

The hidden layer processing serves for weighted integration, since tumor detection goes not after definig “Is marker A AND marker B present?” but according to molecular pattern recognition where general context affects each factor importance.

Outputs Each Input could regulate transcription factors, CRISPR effectors, RNA regulators, riboswitches etc. If the weighted activation exceeds a threshold, the output gene is expressed, e.g.:

  1. Apoptosis-inducing protein
  2. CAR-T activation signal
  3. Cytokine release
  4. Fluorescent reporter
  5. Drug synthesis enzyme The output could also be graded.

Since cancer biomarkers are noisy, heterogeneous, and overlapping with healthy tissue in its molecular signature, Boolean logic risks to fail. However, there are several limitations:

  1. Biological noise (affects precision)
  2. Activation Response Crosstalk (regulatory molecules may unintentionally interact with endogenous pathways)
  3. Limited orthogonal components (which coexist without interference)
  4. Metabolic burden (utilizing of ATP, ribosomes, and transcriptional capacity)
  5. Evolutionary instability (probability of synthetic circuits silencing over time)

Intracellular multilayer perceptron diagram

Layer 1 Input X1 encodes an endoribonuclease (for example Csy4-like). The endoribonuclease processes or represses an intermediate RNA regulator

X1 DNA ──Tx/Tl──> Endoribonuclease E1 │ ▼ Cleaves/regulates intermediate RNA

Layer 2 The processed intermediate regulates translation of a fluorescent protein output

Intermediate RNA ──Tx/Tl──> Fluorescent protein Y

In other words,

Input Layer

X1 → Endoribonuclease E1 X2 → Regulatory RNA R1

Hidden Layer

E1 modifies R1 R1 acts as weighted regulatory signal

Output Layer

R1 regulates translation of fluorescent protein Y ↓ Fluorescence output

Part 2: Fungal Materials

Existing fungal materials, uses, advantages, and disadvantages

Fungal materials are typically made from mycelium, the filamentous root-like network of fungi. Mycelium can grow through agricultural waste and form lightweight, biodegradable composite materials.

  1. Mycelium packaging Companies grow mycelium around agricultural byproducts (corn husks, hemp hurds, sawdust) to produce protective packaging.

Uses

  • Replacement for Styrofoam
  • Shipping protection
  • Insulation

Advantages over plastic foam

  • Biodegradable
  • Compostable
  • Renewable
  • Low-energy manufacturing
  • Lower carbon footprint

Disadvantages

  • Less water resistant
  • Lower durability over long periods
  • Can deform under moisture or heavy loads
  • Shorter shelf life
  1. Mycelium leather Fungal biomass is processed into leather-like sheets.

Uses:

  • Fashion products
  • Shoes
  • Bags
  • Upholstery

Advantages over animal leather:

  • No animal agriculture
  • Lower greenhouse gas emissions
  • Faster production
  • Reduced water usage
  • Potentially customizable texture

Disadvantages:

  • Usually less durable than high-quality leather
  • May require synthetic coatings
  • Mechanical properties still improving
  • Scaling production remains expensive
  1. Fungal food products Fungi are already widely used as biomaterials in food.

Examples:

  • Quorn™ mycoprotein
  • Tempeh fermentation fungi
  • Mushroom-derived proteins

Uses:

  • Meat substitutes
  • Protein supplements

Advantages:

  • High protein yield
  • Lower environmental impact than livestock
  • Efficient land use

Disadvantages:

  • Texture/flavor limitations
  • Allergen concerns
  • Consumer acceptance barriers

In comparison with traditional counterparts, fungal materials are more ecologically sustainable, require relatively few resources, are capable of self-assembly and biodegradation. Growth conditions can alter their density, flexibility, porosity, and texture. However, many fungal composites are less resistant than plastics, metals, or concrete. Relatively high fungal water absorption could also be detrimental in some contexts. Finally, mycellium grows relatively slow and not totally reproducible, which is a disadvantage in terms of industrial mass production.

Why genetically engineer fungi?

Fungi are extremely versatile organisms that already produce enzymes, antibiotics, pigments, organic acids, structural biomaterials etc.

  1. Improved biomaterials, such as:
  • stronger mycelium
  • water-resistant composites
  • elastic or flexible materials
  • conductive biomaterials

Why? This could replace:

  • plastics
  • synthetic foams
  • petroleum-derived textiles
  1. Drug production, such as:
  • penicillin
  • cyclosporine
  • statins

Why?

  • lower manufacturing costs
  • faster drug discovery
  • sustainable bioproduction
  1. Environmental remediation, by degrading:
  • plastics
  • oil pollutants
  • pesticides
  • toxic chemicals

Why? Fungi can access environments difficult for bacteria to colonize

  1. Biosensors to detect
  • toxins
  • explosives
  • pathogens
  • heavy metals

Fungi vs. bacteria in synthetic biology

Advantages of fungal synthetic biology over bacteria:

  1. Ability to grow large multicellular structures
  2. Superior secretion capabilities
  3. Complex post-translational modifications
  4. Better degradation of complex substrates
  5. Filamentous growth
  6. Higher tolerance for some harsh environments

Disadvantages:

  1. Slower growth
  2. More complex genetics
  3. Difficult scaling and control
  4. Fewer standardized tools

Part 3: First DNA Twist Order