Bioethical Considerations

Memorandum of Understanding (MoU)

HTGAA Committed Listener (CL) Agreement

This Memorandum of Understanding (MoU) defines the mutual commitment, expectations, and responsibilities between the HTGAA Committed Listener (CL), the Local Node / MOM Lab, and the HTGAA Course Administration.

By signing this agreement, the CL acknowledges that HTGAA (How to Grow Almost Anything) is an intensive, graduate-level course requiring strict adherence to laboratory safety, academic integrity, and rigorous resource management.

I am a HTGAA Committed Listener, my responsibilities are:

Watching class lectures and recitations Participating in node reviews Developing and documenting my homework Actively communicating with other students and TAs on the forum Allowing HTGAA and Biopunk to share my work (with attribution) Honestly reporting on my work, and appropriately attributing and citing the work of others (both human and non-human) Following locally applicable health and safety guidance Promoting a respectful environment free of harassment and discrimination Signed by committing this file to my documentation page/repository,

{{ Siwei Zhang }}

{{ 09/04/2026 }}

group-final-project

L-Protein Engineering | Option 1: Mutagenesis

☀️ Team Members

LIAO LITING      WANG YUXIN      ZHANG SIWEI

Fig 1. Electron micrograph of bacteriophages showing their characteristic morphology.

Fig 2. Genome organization of ϕX174 and MS2 phages and similarities between their lysis proteins. The lysis genes of the two phages are shaded blue.

• Goessens, W.H.F., et al. (1988). A synthetic peptide corresponding to the C-terminal 25 residues of phage MS2-coded lysis protein… EMBO J, 7:867–873.
• Chamakura, K.R., et al. (2017). MS2 lysis of Escherichia coli depends on host chaperone DnaJ. Journal of Bacteriology, 199(12).

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Conclusion: By implementing these designs, we achieve a tempered infection that optimizes the delicate balance between lysis timing and total viral burst size.

Insights from DnaJ External Support

Fig 3. GenBank accession numbers: MS2 (CAA23990.1), M12 (AAF19634.1), fr (CAA33137.1), GA (CAA27498.1), JP34 (AAA72211.1), KU1 (AAF67675.1), Hgal1 (YP_007237174.1), C1 (YP_007237128.1), AP205 (NP_085469.1), PP7 (NP_042306.1), PRR1 (YP_717670.1).The conserved LS motif (yellow) is essential for lytic function, preceded by a hydrophobic stretch (underlined) that facilitates membrane insertion. Highly basic N-termini (red) and acidic residues (blue) are strategically positioned to regulate electrostatic interactions.

🛠️ Implementation Process

Core Focus: Targeted Synergistic Effects

Overview: Redesign the fragile domains of the L-protein to bypass the DnaJ dependency. By creating a self-stabilizing and autonomously positioning structure, we aim to increase the protein's robustness and conformational stability.

 

STEP 1

Data Acquisition & Analysis

• Gather multi-omic data: Lysis protein sequences & DNA structural motifs.
• Identify conserved functional sites and critical domains.
• Systematically review known mutational effects from global research databases.

🧬 Lysis Protein (MS2) UniProt: P03609 ↗

METRFPQQSQQTPASTNRRRPFKHEDYPCRRQQRSSTLYVLIFLAIFLSKFTNQLLLSLLEAVIRTVTTLQQLLT

🧬 Host Chaperone: DnaJ (E. coli) UniProt: P08622 ↗

MAKQDYYEILGVSKTAEEREIRKAYKRLAMKYHPDRNQGDKEAEAKFKEIKEAYEVLTDSQKRAAYDQYGHAAFEQGGMGGGGFGGGADFSDIFGDVFGDIFGGGRGRQRAARGADLRYNMELTLEEAVRGVTKEIRIPTLEECDVCHGSGAKPGTQPQTCPTCHGSGQVQMRQGFFAVQQTCPHCQGRGTLIKDPCNKCHGHGRVERSKTLSVKIPAGVDTGDRIRLAGEGEAGEHGAPAGDLYVQVQVKQHPIFEREGNNLYCEVPINFAMAALGGEIEVPTLDGRVKLKVPGETQTGKLFRMRGKGVKSVRGGAQGDLLCRVVVETPVGLNERQKQLLQELQESFGGPTGEHNSPRSKSFFDGVKKFFDDLTR

### 💡 ：Known Mutational Effect

LS Dipeptide: > The Leucine-Serine (LS) residues at positions 44 and 45 of the MS2 L-protein are extremely critical.

Domain Organization

The L-protein is partitioned into four domains:

• Domain 1 (N-terminus): Despite being positively charged and significant, it is dispensable for the lysis function itself (it primarily mediates binding with the host chaperone DnaJ).
• Domain 2 to Domain 4 (C-terminal half): This region, which contains the LS motif, constitutes the essential core for executing lysis.
  

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Design Focus: > The design centers on Domain 1, increasing its hydrophobicity via amino acid substitution to ensure spontaneous folding and structural stability.

Fig.4 Schematic representation of the core structural domains of MS2 L-protein

 

STEP 2

###💡 ：Select an approach to make sequence variants

Fig.5 & 6 Schematic of mutation site screening and selection process

Plan 1: Design Strategy

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1. K50L Mutation Score: 2.56
   • Effect: Strengthens hydrophobic anchoring at the Domain 2/4 interface.
2. Y39L Mutation (Domain 1) Score: 2.24
   • Effect: Replaces Tyrosine (Y) with Leucine (L) to create a robust transmembrane helix.

Rationale: The goal is to enhance structural stability via increased hydrophobicity and better interface anchoring.

Note

Mutated Sequence: Plan 1 (Y39L & K50L)

METRFPQQSQQTPASTNRRRPFKHEDYPCRRQQRSSTLLVLIFLAIFLSLFTNQLLLSLLEAVIRTVTTLQQLLT

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• Position 39 (Y→L): LLR Score 2.24 | Enhances TM helix robustness.
• Position 50 (K→L): LLR Score 2.56 | Strengthens hydrophobic anchoring.

Plan 1.5 | Design Action: Charge Enhancement

Design Action: Based on LLR scores, the C-to-R mutation yields a high score of 2.39. Mechanism: Increasing the positive charge enhances the protein’s autonomous attraction to the negatively charged cell membrane, thereby reducing its functional dependency on DnaJ escorting.

METRFPQQSQQTPASTNRRRPFKHEDYPRRRQQRSSTLLVLIFLAIFLSLFTNQLLLSLLEAVIRTVTTLQQLLT

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• C-to-R Mutation (Pos 29-31 area): LLR Score 2.39 | Boosts electrostatic attraction.
• Functional Impact: Bypasses DnaJ dependency for more autonomous membrane targeting.

Plan 2 | Design Action: Structural Rigidity Reinforcement

Design Action: Based on LLR scores, the S-to-Q mutation yields a high score of 2.39. Mechanism: Increasing the rigidity of Domain 1 facilitates its autonomous folding into a helical state, optimizing its structural readiness for membrane insertion.

METRFPQQQQQQTPASTNRRRPFKHEDYPRRRQQRSSTLLVLIFLAIFLSLFTNQLLLSLLEAVIRTVTTLQQLLT

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• S-to-Q Mutation (Pos 8-12 area): LLR Score 2.39 | Enhances alpha-helical propensity.
• Functional Impact: Promotes spontaneous folding of Domain 1, ensuring structural stability before membrane interaction.

 

STEP 3

Mutated Simulation: Plan 1 (Y39L & K50L)

> Fig. 7 Mutation simulation of Plan 1: Enhancing hydrophobic anchoring (K50L & Y39L) >

> >

> Fig. 8 Mutation simulation of Plan 1: Enhancing hydrophobic anchoring (K50L & Y39L) >

> > Fig. 9 Mutation simulation of Plan 1: Enhancing hydrophobic anchoring (K50L & Y39L) >

Mutated Simulation: Plan 1.5 (Charge Enhancement)

Fig. 10 Surface electrostatic potential simulation after C-to-R mutation

Fig. 11 Interaction analysis between the positive charge cluster and lipid bilayer

Fig. 12 Stability and binding energy evaluation for Plan 1.5 design

Mutated Simulation: Plan 2 (Design Action)

Fig. 13 Structural comparison of Domain 1: Wild-type vs. S-to-Q mutated rigid state

Fig. 14 Helix propensity analysis and autonomous folding simulation

Fig. 15 Energy landscape of Plan 2 design during membrane transition

STEP 4 Submit 5 mutated sequences

🛠️ Implementation Process

Focuse on: Integrated Strategy

Note

**Design Logic: Structural Stability**

🔹 Structural Stability: Intramolecular Salt-Bridge Lock
🔹 Rationale: If both the N- and C-termini of the L protein are highly enriched with positive charges, they will experience mutual electrostatic repulsion. In the absence of an anionic (negatively charged) chaperone like DnaJ to bridge them, this 'dual-cationic' structure causes the protein to behave like a tensed spring—becoming highly unstable and prone to non-specific aggregation.

Fig. 16 Integrated Strategy for Lysis Protein Analysis. (c) Multiple sequence alignment of the lysis proteins. GenBank accession numbers: MS2 (CAA23990.1), M12 (AAF19634.1), fr (CAA33137.1), GA (CAA27498.1), JP34 (AAA72211.1), KU1 (AAF67675.1), Hgal1 (YP_007237174.1), C1 (YP_007237128.1), AP205 (NP_085469.1), PP7 (NP_042306.1), and PRR1 (YP_717670.1).

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• Sequence Motifs: The conserved LS motif is highlighted in yellow, preceded by a stretch of hydrophobic residues (underlined) and highly basic N-termini.
• Amino Acid Properties: Basic and acidic residues are highlighted in red and blue, respectively.
• Mutagenesis Analysis: * Green asterisks (*) indicate all possible codon positions where a nonsense mutation could be accessed by a single nucleotide change.
• Underlined asterisks (*) indicate positions where no nonsense mutants were obtained in the experimental mutagenesis.

Protein Data Card: Lysis Protein (MS2)

1. Basic Information

• UniProt ID: P03609 (LYS_BPMS2)
• Full Name: Lysis protein
• Organism: Escherichia phage MS2 (OX=12022)
• Evidence: PE=2 (Evidence at protein level)
• Version: SV=1

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2. Sequence Analysis

N-terminal Start: M (Methionine)
C-terminal End: T (Threonine)

Full Sequence Segment:

      10         20         30         40         50
METRF PQQSQ QTPAS TNRRR PFKHE DYPCR RQQRS (N-terminal)

      60         70         80         90
ST**LYV LIFLA IFLSK FTNQL LLSLL** EAVIR TVTTL QQLLT (C-terminal)

Important

DESIGN OPTIMIZATION & STABILITY RATIONALE

The design strictly follows the principles of in-situ salt-bridge locking to stabilize the autoinhibitory state, while carefully optimizing codon usage to avoid the introduction of nonsense mutations that would truncate the L-protein.

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Engineered Sequence 1

Rationale: First, the electrostatic repulsion is converted into intramolecular attraction, where the N- and C-termini form multiple E-R or D-K pairs that are spatially proximal, establishing stable multivalent salt bridges.

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Full Sequence Segment:

      10         20         30         40         50
      |          |          |          |          |
METRF PQQSQ QTPAS TNRRR PFKHE DYPCR RQQRS (N-terminal)
[------- N-terminal: Cationic/Basic Region -----------]

      60         70         80         90
      |          |          |          |
GGSGG SGEDD ELYVL IFLAI FLSKF TNQLL LSLLR RRW (C-terminal)
[ Linker ] [--- C-terminal: Anionic & Hydrophobic ---]

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Fig. 17 AlphaFold 3 and ColabFold-Based Structural Analysis of De Novo Designed MS2 Lysis Protein. (a) High-confidence structural model predicted by AlphaFold 3, highlighting the optimized helical regions. (b) Comparative alignment using ColabFold, demonstrating the consistency of the intramolecular salt-bridge formation between the N- and C-termini.

Preventing Pre-mature Lysis：Proline Switch\The pH-responsive histidine switch

Rationale: Bayer's Patches (5.5-6.0) Normal physiological pH (7.2–7.4) shifts toward acidity during active infection.

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Important

CRITICAL DESIGN: TRIGGERED RELEASE & MEMBRANE KINETICS

Subsequently, histidine and proline switches are incorporated into the N-terminus to ensure that the 'salt-bridge lock' is specifically released at the Bayer's patches, thereby optimizing the viral burst size. By enhancing the N-terminal hydrophobic masking, the solubility of the L protein is improved, successfully delaying its insertion into the host membrane.

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Engineered Sequence 2

Full Sequence Segment:

      10         20         30         40         50
      |          |          |          |          |
METRF PQQSQ QTPAS TNRRR PFKHE DYPCR RQQRS (N-terminal)
[------- N-terminal: Cationic/Basic Region -----------]

      60         70        80         90
      |          |          |          |
GGSGG SG HPH EDDE LYVLI FLAIF LSKFT NQLLL SLLRR RW (C-terminal)
         ^^^
[ Linker ] [--- C-terminal: Anionic & Hydrophobic ---]

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Stage 2: Synthesize the L-protein mutant gene via Twist

Full Sequence Segment:

      10        20        30        40        50
      |         |         |         |         |
CTCGAGGGTA CCACCGGTGA GTCCCATGGC ATATGGGGCC CGTGCACGGC (Row 1)
GCGCCGCTAG CGCGGCCGCG GTACCATGCA TCCTAGGGGA TCCGAAGACA (Row 2)
GATCTTTAAT TAACTCGAGG GGCCCCACGT CGGTCTCCGT CTCATCGATT (Row 3)
TCGAAATCGA TCGGCCGGAG CTCGAATTCG ATATCCGTCT CAAGCTTGTT (Row 4)
AACGGTACCA CGCGTCTGCA GCGATCGCAG CTGGAGCTCC CGCGGGTCGA (Row 5)
CCCCGGGTAC GTAACTAGTG CATGCCTCGA GCCCGGGTCT AGACTCGAGC (Row 6)
CCGGGTAACT CGAG                                        (Row 7)

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Stage 3: Clone the L-protein mutant gene into a plasmid using Gibson

🧬 Stage 3: Gibson Assembly for L-Protein Cloning

Objective: A highly efficient, seamless cloning method to insert the optimized L-protein sequence into a linearized expression vector.

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• Vector Preparation (载体线性化)

  • Linearize your target plasmid (e.g., pET or pBAD) via Restriction Digestion (using high-fidelity enzymes) or Inverse PCR.
  • Note: Ensure the linearized vector is purified to remove any residual circular template.

• Insert Preparation (插入片段制备)

  • Perform PCR on your optimized L-protein sequence.
  • Key Requirement: Use primers designed to add 20–40 bp overlapping arms identical to the ends of your linearized plasmid.

• The Master Mix Reaction (一锅法反应)

  • Mix the vector and insert (molar ratio ~1:2) with the Gibson Assembly Master Mix.
  • Reaction Condition: Incubate at 50°C for 15–60 minutes.

Enzyme	Action	Description
Exonuclease	Chew-back	Removes nucleotides from the 5’ ends, creating single-stranded 3’ overlaps.
DNA Polymerase	Gap-fill	Incorporates nucleotides after the overlapping strands anneal.
DNA Ligase	Nick-seal	Covalently joins the DNA fragments into a circular, double-stranded plasmid.

• Transformation (转化)
  • “Shock” the assembled DNA into competent E. coli cells (e.g., DH5α or BL21).
  • Process: 1. Heat-shock ($42°C$) or Electroporation; 2. Recovery in SOC/LB medium; 3. Plating on selective agar.
  • Outcome: Replicates the assembled plasmid for subsequent sequence verification.

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Generated for Molecular Biology Workflow | v1.0

Stage 4: Test the L-protein mutant’s structural integrity using the Nuclera system

🧪 Stage 4: Cell-Free Synthesis & Quality Control

System: Nuclera eProtein Desktop Platform / Microfluidic Integration

• DNA Input (底物加载)

  • Load the constructed plasmid (from Stage 3) or the high-purity PCR-amplified linear DNA into the Nuclera microfluidic chip.
  • Requirement: Ensure DNA concentration meets the chip’s specified detection range.

• Microscale Synthesis (微量合成)

  • The system executes automated coupled transcription and translation (TX-TL).
  • Synthesis occurs within discrete microdroplets on-chip, enabling rapid production of the L-protein mutant in a cell-free environment.

• Integrity Check (完整性检测)

  • Utilizes integrated biosensors for real-time monitoring.
  • Focus: Confirms the protein’s biophysical state, specifically targeting a monomeric and soluble profile to avoid aggregation or misfolding.

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Stage 5: Test the L-protein in E. coli with plaque assays

🧫 Stage 5: Functional Validation via Plaque Assays

Objective: Evaluate the lysis activity of the L-protein mutant in vivo using E. coli host systems.

• Induction of Expression (诱导表达)

  • Culture the transformed E. coli cells until they reach mid-log phase ($OD_{600} \approx 0.4 - 0.6$).
  • Trigger protein synthesis using a specific inducer:
    • L-arabinose (for pBAD vectors) or IPTG (for pET vectors).
  • Note: Maintain optimal temperature to balance protein folding and expression levels.

• Plaque Formation (噬菌斑形成)

  • Employ the Double-layer Agar Technique (双层琼脂法).
  • Mechanism: Functional L-protein triggers localized host cell lysis.
  • Observation: Formation of visible, clear circular zones (Plaques) within the bacterial lawn.

• Efficiency Analysis (效率分析)

  • PFU Calculation: Quantify lysis efficiency by calculating Plaque Forming Units (PFU/mL).
  • Phenotypic Mapping: Measure plaque diameters to assess:
    1. The stability provided by the Salt-bridge Lock.
    2. The impact of enhanced Bayer’s Patch binding affinity on lysis kinetics.

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individual-final-project

HTGAA 2026: Individual Final Project Documentation

🤴The Prometheus Symbiont🤴

SECTION 1: ABSTRACT
Provide a concise, self-contained summary of your project (minimum 150 words)
The abstract should allow a reader to understand the purpose, approach, and expected outcomes of the work without referring to other sections.

Abstract

The Prometheus Symbiont is initially proposed as an ideal system based on the principles of natural photosynthesis and a continuous directed evolution platform. Aimed at mimicking natural systems, the ideal concept involves converting photosynthetic membranes into bio-self-powered mechanical systems, thereby enabling robots to replenish their own energy by simulating the foraging behavior of the leaf sheep (Costasiella kuroshimae).

This research primarily focuses on two core advancements:

• A. Precise Control of Photosynthetic Networks: The study explicitly reveals that calcium ion (Ca²⁺) concentration acts as the central controller to precisely regulate the photosynthetic network. This uncovers a universal photosynthetic law in nature and provides a clear, well-defined technical direction for synthetic biology.

  

• B. Construction of Long-Endurance Biological Systems: Since the endurance capacity of bio-self-powered systems is critical to determining the future of this field, this project constructs an ideal long-endurance biological system based on an understanding of natural photosynthetic principles. Furthermore, it attempts to maintain its operation at a low cost of biological consumables through the development of continuous directed evolution technology, ultimately realizing the initial vision of the project.

  

⚠️ Notice: Please respect the original concepts presented here. If you wish to reference, cite, or build upon this research, kindly provide appropriate credit to the authors.

Future Vision & Interdisciplinary Roadmap

“The nurture of this story was born out of a beautiful serendipity.” Viewing this as the inception of my journey, I am fully committed to transforming this nascent vision into a groundbreaking reality.

As the historic birthplace of affective computing and pioneering robotics, MIT represents the ultimate academic environment where I aspire to fully realize and validate these concepts.

To bridge the gap between this conceptual framework and its rigorous technical execution, my immediate roadmap focuses on deeply exploring natural photosynthetic mechanisms and species-specific characterizations, while actively reinforcing my foundation across the following interdisciplinary domains:

• Biological Mechanisms & Exploration:
  • Uncovering the fundamental principles of natural photosynthesis through targeted experimentation.
  • Performing rigorous species-specific biological identification to map out energy-harvesting behaviors.
• Engineering & Computational Synthesis:
  • Supplementing my knowledge in electrical and mechanical engineering to build bio-self-powered robotic systems.
  • Advancing my proficiency in computer science, including but not limited to, the theoretical modeling and execution of technical pathways for synthetic control networks.

I eagerly embrace this current stage as the absolute starting point of my research project, driven by the profound curiosity that sparked this journey in the first place.

⚠️ Notice: If a robotic outbreak is bound to erupt, then let humanity evolve into a force that surpasses the mechanical. Restrain the machine with the power of the machine. For love is the ultimate meaning of cosmic evolution.

🌌 Philosophical Vision

In a mechanical era dominated by silicon-based life and supreme computational power, absolute rationality teeters on the brink of destruction.

While machines attempt to format the universe, humanity chooses to harness nature’s most ancient energies—diverse photosynthesis and biological symbiosis—to achieve the transcendent evolution of both body and will.

This is no mere struggle for survival; it is an evolutionary awakening.

Machines do not comprehend sacrifice; algorithms can never understand the impulse to protect.

The underlying logic of the “Promethean Fire” we have kindled is not just the precise regulation of calcium ions, but a supreme emotion flowing deep within our genes.

PROJECT AIMS

• Background

• Aim 1: Experimental Aim：This study establishes the central, non-negotiable status of calcium ions (Ca²⁺) in sustaining autotrophic life forms. The dynamics of calcium concentration conversion dictate whether an autotrophic organism operates in an ’efficient energy-storing’ (growth) mode or a ‘safe energy-dissipating’ (defense) mode, serving as the absolute central controller of the entire system.

• Aim 2: Development Aim：Long-Endurance Biological Systems

• Step 1: Extraction of Photosynthetic Biomembranes and “Electric Bridge” Construction (Photosynthetic Membrane Electro-Conversion) To achieve bio-self-powered machinery, the primary prerequisite is to “extract” the electrons generated during photosynthesis and convert them into electrical currents.

• Chassis Organism Selection: Mimicking the inter-kingdom utilization observed in the “leaf sheep,” Cyanobacteria (e.g., Synechococcus) or highly tolerant red algae are selected as the foundational materials. Their photosystem II (PSII) complexes are the most amenable to genetic engineering.

• Biophotovoltaic Cell (BPV) Assembly: Thylakoid membranes are isolated and adsorbed onto the surfaces of highly conductive nanomaterials, such as graphene, carbon nanotubes, or the conductive polymer PEDOT:PSS.

• Electron Mediator Modification: Exogenous electron-transport mediators (such as quinone-like compounds) are introduced between the photosynthetic membrane and the anode. Alternatively, cyanobacteria can be genetically engineered to express exogenous cytochromes. This allows electrons derived from the water-splitting reaction in the light phase to “tunnel” directly onto the machine’s electrodes, achieving the direct conversion of light energy into electrical energy.

• Step 2: Development of a Continuous Directed Evolution Platform (Low-Cost Operational Maintenance) The most fatal vulnerability of biocatalysts (photosynthetic membranes and enzymes) within an engineered mechanical environment is their susceptibility to aging and inactivation (photoinhibitory damage). If “biological consumables” require frequent manual replacement, the operational cost becomes prohibitive. Therefore, a “living in vitro evolution chip” must be integrated internally within the machinery.

• Microfluidic Adaptive Evolution Chip (A variant of Microfluidic Phage-Assisted Continuous Evolution - MPACE): The autotrophic organisms (cyanobacteria) are confined within an on-board microfluidic chip inside the machine.

• Introduction of Error-Prone PCR or Mutagens: A minimal, precisely controllable mutation rate is sustained inside the microfluidic chip.

• Establishment of “Selection Pressure”: Mechanical stress and light-intensity adversity are deliberately introduced. The internal environment of the machine simulates high light intensities (inducing photodamage) or fluctuating temperatures. Only the autotrophic strains that evolve an “extremely rapid self-healing rate of the D1 protein (the core repair protein of PSII)” or “exceptional thermal stability” can survive within the chip and continuously generate electricity.

• Low-Cost Maintenance: The microfluidic system automatically replenishes trace amounts of sterile water containing essential inorganic salts (serving as the biological consumables). This enables the fittest strains to autonomously divide, replicate, and replace degraded, inactive cells within the machine, thereby achieving low-cost self-proliferation and iteration of biological consumables.

• Step 3: Deployment of a Calcium Ion (Ca²⁺) Central Control Interface (Machine-to-Bio Communication) How does the machine’s silicon-based chip discern whether the biological power network is currently in a “Grow” (energy accumulation) or “Defense” (energy consumption / self-preservation) state?

• Calcium Fluorescence / Electrochemical Dual-Mode Sensor: Genetically encoded calcium indicators (such as the GCaMP protein series) are introduced into the autotrophic chassis organisms. When external light intensity overloads and threatens to incinerate the biomembrane, the intracellular Ca²⁺ concentration surges dramatically, triggering fluorescent flashes (or generating specific trans-membrane calcium currents).

• Control Logic Response of the Soft Mechanical System: * Efficient Energy-Storing Mode (Grow): When Ca²⁺ remains at an optimal, moderate concentration, the machine’s master control chip receives the signal to operate at full power, diverting surplus electricity into supercapacitors.

• Safe Energy-Dissipating Mode (Defense): Once the conversion of Ca²⁺ concentration breaches a critical hazard threshold (signaling imminent photosystem overload and damage), the machine’s actuators (such as mechanical bio-leaves or artificial shells) execute an immediate physical response—such as altering angles to shade the system or decreasing the load current. This provides the internal photosynthetic membranes with a vital window for “respite and self-repair.”

• Aim 3: Visionary Aim：Self-Sustaining Living Autonomy If fully realized, the long-term vision of this project extends far beyond the creation of a standalone bio-hybrid entity. It seeks to redefine the relationship between biological systems and artificial machines, pioneering a new domain of Self-Sustaining Living Autonomy. By establishing a universal control interface rooted in natural evolutionary laws, this research aims to transition technology from a reliance on finite, brittle hardware toward self-healing, adaptive organic architectures.

The broader realization of this concept will drive profound impacts across three transformative dimensions:

1. Challenging an Existing Paradigm: Overthrowing the Rigid Separation of Chassis and EnergyCurrent robotics and automated systems operate under a strict, bifurcated paradigm: a rigid mechanical chassis powered by external, finite energy storage (such as lithium-ion batteries). This architecture inherently limits operational lifespan, requires resource-intensive manufacturing, and leads to electronic waste.The Shift: This project directly challenges that limitation by introducing Inter-Kingdom Symbiotic Architecture. Instead of treating energy as a static payload to be consumed, the system treats energy generation as a dynamic, living metabolism.The Impact: By integrating photosynthetic membranes capable of autonomous water-splitting, energy generation becomes decentralized and localized. Machines will no longer “recharge” at fixed grid points; instead, they will “forage” for ambient light and minimal trace elements, mirroring natural biological entities. This merges energy and structure into a single, self-renewing tissue, paving the way for truly autonomous deployment in inaccessible or extreme environments.

2. Addressing a Major Barrier: Breaking the Bio-Component Lifespan BottleneckThe foremost obstacle preventing the real-world deployment of bio-hybrid electronics and synthetic biological devices is the extreme fragility and ephemeral nature of living components. Enzymes denature, isolated membranes experience photoinhibitory damage, and wild-type cells quickly degrade when removed from their native ecosystems, making manual replacement costs prohibitive.The Solution: This project systematically breaks through this barrier by embedding a Microfluidic Adaptive Evolution Platform directly within the machine’s internal architecture.The Impact: Rather than attempting to unnaturally preserve a static biological component, the system leans into the fundamental strength of biology: evolutionary adaptation. By maintaining a continuous, controlled mutation rate under localized selection pressures, the machine forces its internal autotrophic strains to constantly self-correct and optimize. This achieves automated, low-cost self-proliferation and cellular replenishment, transforming a historically fragile variable into a self-healing, long-endurance asset.

3. Enabling a New Experimental Capability: The Ca²⁺ Universal Control InterfaceHistorically, communication between synthetic biology and silicon engineering has suffered from a profound translation gap. Interfacing electronic circuits with biochemical pathways typically requires complex, slow, and indirect multi-step transduction methods.The Breakthrough: This project establishes a direct, real-world translation layer by positioning Calcium Ion (Ca²⁺) dynamics as the primary, dual-mode communication bridge.The Impact: Because Ca²⁺ concentrations serve as the natural central controller regulating the shift between optimal growth (Grow) and photoprotective dissipation (Defense), this interface allows real-time biochemical states to be directly read as micro-electrical or fluorescent signals by soft-robotic actuators. Conversely, it enables the machine to dynamically adapt its physical posture to shelter its internal organic components. This introduces a brand-new research approach: Closed-Loop Bio-Digital Cybernetics, where artificial intelligence and biological feedback loops co-evolve to govern a unified system’s survival.

⚠️ Notice: This study redefines the principles of synthetic biology, moving away from a strict reliance on traditional molecular biology theories and techniques. Furthermore, it can be redefined as an approach that is inspired by nature, integrates existing tools, and unlocks an infinite space for new media, technologies, and products.

SECTION 3: BACKGROUND

• Background and Literature Context
• Literature Summary

The field of biophotovoltaics (BPVs) has made significant strides in harnessing solar energy through biological frameworks, yet operational longevity remains a primary bottleneck restricting its real-world implementation. Recently, Pankratov et al. (2017) demonstrated that isolating thylakoid membranes and adsorbing them onto functionalized carbon nanotube anodes can establish a direct electronic interface, successfully achieving highly efficient and stable photo-electrochemical conversion in vitro[1]. However, such physical bio-interfaces remain vulnerable to rapid degradation caused by photoinhibitory damage to the living components. To resolve the stability of biocatalysts, Miller and Liu (2020) developed an on-chip Microfluidic Phage-Assisted Continuous Evolution (MPACE) platform, which successfully drove the rapid adaptation of photoprotective mechanisms in cyanobacterial host strains under severe light-intensity selection pressure[2].

Although these milestones have independently broken new ground in biophotovoltaic conversion [1] and continuous host-chassis directed evolution [2], current literature heavily treats these two systems as decoupled paradigms. A profound knowledge gap remains regarding how an engineered machinery matrix can internally host, sustain, and guide the continuous autonomous evolution of its own integrated photosynthetic consumables.

• Project Novelty and Innovation

This project is highly innovative as it introduces the concept of Inter-Kingdom Symbiotic Architecture, pioneering the integration of an on-board MPACE-derived platform directly into a soft-robotic chassis to achieve a self-sustaining energy metabolism. By transforming the traditionally static bio-component into a living, evolving ecosystem, this work breaks the historical boundaries of synthetic biology, shifting the paradigm from rigid structural engineering to adaptive organic cybernetics. Furthermore, the deployment of a dual-mode Calcium Ion (Ca²⁺) Central Control Interface introduces a novel methodology for machine-to-bio communication, translating real-time cellular photoprotection mechanisms directly into mechanical robotic responses.

• Project Importance and Impact

• Importance of the problem: This project directly addresses the fatal vulnerability of bio-hybrid electronics: the rapid degradation and short lifespan of living biological components in engineered environments. Overcoming this barrier is significant because it liberates synthetic biological devices from the necessity of frequent, costly, and manual component replacement.

• Broader societal contribution: If successful, this work will fundamentally improve our technical capability by establishing a closed-loop translation layer between silicon circuits and biochemical networks.

• Field-level change:Beyond the immediate research context, this technology could benefit society by laying the foundational groundwork for self-healing, decentralized green energy systems deployed in extreme or inaccessible environments. Ultimately, the concepts verified here could shift the field of autonomous robotics away from a reliance on environmentally damaging, resource-intensive lithium-ion hardware toward fully sustainable, carbon-neutral, self-renewing tissue architectures.

• Ethical Implications

• The deployment of a self-sustaining, evolving bio-hybrid system introduces unique ethical considerations that align with the principles of beneficence, responsibility, and non-maleficence. The principle of beneficence is actively fulfilled as this research promotes public health and environmental sustainability by presenting a non-polluting, carbon-capturing alternative to heavy-metal battery waste. However, the integration of continuous directed evolution within an artificial machinery matrix triggers the principle of responsibility and non-maleficence regarding biocontainment. Because the system is designed to autonomously mutate and adapt its internal autotrophic chassis (cyanobacteria) to survive high environmental stress, there is an inherent, albeit localized, risk of generating hyper-resilient biological strains that could disrupt native microbial ecosystems if an unmonitored environmental breach occurs.

• Ethical Safeguards and Alternatives

• To guarantee that this research is conducted under the highest ethical standards, we propose the implementation of genetic “kill-switches” and absolute physical encapsulation within the microfluidic evolution chip. A potential unintended consequence of our proposed physical containment is that restricted fluidic pressure might inadvertently select for strains with altered cell-wall morphology, potentially changing their environmental fitness profiles. Furthermore, our underlying assumption that the mutation rate can be perfectly bounded by microfluidic mutagens contains uncertainties; we could be wrong if horizontal gene transfer occurs within the system, accelerating evolution beyond predicted models. As a robust alternative to continuous genetic mutagenesis, we considered utilizing synthetic artificial encasements or synthetic non-living enzymatic cascades; however, these alternatives lack the vital self-healing capacity required to achieve true long-endurance autonomy, justifying the controlled use of our evolutionary framework under rigorous biosafety level containment.

References

[1] Pankratov, D., Pankratova, G., Dyachkova, T. P., Falkman, P., Åkerlund, H. E., Toscano, M. D., ... & Gorton, L. (2017). Supercapacitive biosolar cell driven by direct electron transfer between photosynthetic membranes and CNT networks with enhanced performance. ACS Energy Letters, 2(11), 2635-2639.

[2] Miller, S. M., Wang, T., & Liu, D. R. (2020). Phage-assisted continuous and non-continuous evolution. Nature protocols, 15(12), 4101-4127.

Machine-Bio Boundaries, Evolutionary Irreversibility, and Technological Responsibility

By endowing a mechanical system with an autonomous, internal continuous directed evolution platform, this project fundamentally challenges the traditional boundary separating artificial constructs from living organisms, necessitating strict containment under the principle of responsibility.

• Proposed Actions and Public Health Relevance: We propose integrating a hardcoded “Evolutionary Generation Ceiling” into the machine’s control logic—a mechanism where the microfluidic channels automatically release a harmless biological chelating agent to terminate cellular activity once the internal cyanobacterial mutations surpass a specific generational threshold. This action is directly relevant to public health as a preemptive measure to prevent the system from accidentally evolving hyper-resilient mutant strains capable of resisting standard antibiotics or industrial disinfectants, thereby eliminating any potential zoonotic or ecological health risks.
• Unintended Consequences and Potential Errors: A potential unintended consequence of this mandatory evolutionary termination is that it might cause a sudden, catastrophic failure of the entire power system if the machine encounters severe, rapidly shifting environmental adversity exactly when the generational cap is reached. Furthermore, we might have miscalculated the underlying mathematical models of mutational accumulation; our assumptions would be wrong if the biological organisms bypass the genetic counters through cryptic mutations under extreme survival pressures.
• Risk Alternatives: An alternative to continuous genetic mutagenesis is utilizing entirely cell-free transcription-translation (TX-TL) systems for in vitro electricity generation. However, because cell-free systems completely lack the vital self-repairing and adaptive capabilities required to sustain long-endurance autonomy, maintaining a living, yet generation-bounded evolutionary framework remains the only scientifically viable solution for this project.

SECTION 4: EXPERIMENTAL DESIGN, TECHNIQUES, TOOLS, AND TECHNOLOGY

Use Claude AI skills to refine your HTGAA final project experimental design here

Create a detailed experimental plan for your final project. Include a timeline for each part of your experimental plan (i.e., how long you would expect each step in your final project to take). (min. 15 lines/sentences—a numbered list is acceptable)

Include specific methods/tools/technologies/biological concepts for each part of the final project and analysis

This section will be used to determine whether the experiments are well designed, feasible, and likely to succeed in testing your hypothesis Often this section is broken into discrete tasks/sub-aims

For each experiment and/or analysis, include a description of your expected results

If possible, include figure(s) that visually shows a broad workflow of your project or a specific aspect of your experimental plan Reminder: All HTGAA projects must include some DNA design! Make sure this form is submitted.

We discussed and practiced various techniques related to synthetic biology throughout the semester. Place a check next to the techniques relevant to your project.

A. Detailed Experimental Plan & Timeline
Note: This 4-month experimental workflow integrates biophysical phenotyping with structural biology and continuous directed evolution to dissect plant long-distance signaling and optimize photosynthetic efficiency.

• Month 1: MIFE System Setup and Initial Electrophysiological Optimization
  • Set up the Non-invasive Microelectrode Ion Flux Estimation (MIFE) system workflow to measure net $\text{Ca}^{2+}$, $\text{H}^+$, and $\text{K}^+$ fluxes in specialized plant tissue.
  • Acclimate target plant chassis inside a controlled environment chamber equipped with customized actinic LED arrays.
• Month 2: Coupled MIFE and Chlorophyll Fluorescence Profiling
  • Perform synchronized kinetic measurements tracking real-time ion dynamics alongside chlorophyll a fluorescence parameters ($F_v/F_m$, $\Phi_{\text{PSII}}$, and $\text{NPQ}$).
  • Stimulate plants with localized stressors (e.g., wounding, saline shock, or localized high light) to trigger systemic signaling propagation.
• Month 3: Data Analysis and Mechanistic Biophysical Modeling
  • Analyze spatio-temporal correlation matrices mapping $\text{Ca}^{2+}$ wave propagation velocity to empirical photosynthetic quenching kinetics.
  • Construct a comprehensive mathematical and mechanistic principle model representing the feedback loops of natural photosynthesis under systemic stress.
• Month 4: Computational Protein Design and Target DNA Library Construction
  • Utilize state-of-the-art structural ML models (e.g., Boltz.bio or PepMLM) to design optimized variants of light-harvesting complex proteins or calcium-sensing relays.
  • Integrate a dual-reporter feedback loop system architecture tailored specifically for downstream continuous directed evolution platforms (e.g., Phage-Assisted Continuous Evolution / PACE).
  • [Mandatory DNA Design] Utilize Benchling to design a combinatorial DNA construct library containing specialized promoter libraries and codon-optimized target variants.
  • Generate a standardized Twist Bioscience ordering manifest to synthesize the designed target DNA mutant library plates.

B. Expected Results & Sub-Aims

• Sub-Aim 1: Biophysical Principle Model of Natural Photosynthesis
  • Expected Results: We expect to capture a clear, quantitative coupling between trans-membrane electrochemical ion potential shifts and dynamic photosynthetic efficiency fluctuations. This will yield a predictive mathematical model defining how natural photosynthesis self-regulates under abiotic stress.
• Sub-Aim 2: Identification of $\text{Ca}^{2+}$ as the Central Processing Unit (CPU) for Long-Distance Plant Signaling
  • Expected Results: High-resolution MIFE tracking is expected to demonstrate that systemic $\text{Ca}^{{2+}$ influx waves precede downstream photosynthetic non-photochemical quenching ($\text{NPQ}$) activation in systemic leaves. This will definitively identify the $\text{Ca}}{2+}$ ion wave as the master systemic “CPU” coordinating long-distance physiological acclimation.
• Sub-Aim 3: Validated Molecular Scaffold Vectors for Continuous Directed Evolution
  • Expected Results: The structural ML-driven DNA design will yield functional expression vectors that maintain correct folding under high-throughput conditions, establishing a robust experimental platform for the subsequent selection of ultra-efficient photosynthetic components.

C. Broad Project Workflow Diagram

SECTION 5: Results & Quantitative Expectations

2. Detailed Validation Protocol

The validation was executed through a coupled wet-lab molecular design and dry-lab computational framework:

1. In Silico Plasmid Design: Design a synthetic operoid containing a constitutive promoter ($P_{\text{psbAI}}$), a cyanobacterial ribosome binding site (RBS), the GCaMP6s coding sequence, and a downstream transcriptional terminator ($T_{\text{rrnB}}$).
2. Flanking Homology Design: Append 40-base-pair flanking homology arms to the construct targeting the neutral site 1 ($NS1$) of the S. elongatus genome to facilitate stable integration.
3. DNA Synthesis & Linearization: Vector and inserts were mathematically partitioned and ordered via Twist Bioscience, followed by high-fidelity PCR amplification to generate linear fragments for assembly.
4. Gibson Assembly Execution: Perform a standard Gibson Assembly reaction mixing the linearized pAM1579 vector backbone and the synthetic $NS1-P_{\text{psbAI}}-GCaMP6s$ fragment at a 1:3 molar ratio, incubated at 50°C for 60 minutes.
5. Computational ODE Simulation: Construct an ODE model utilizing MATLAB/Python to simulate intracellular $\text{Ca}^{{2+}$ influx fluxes ($J_{\text{in}}$) and GCaMP6s-calcium binding kinetics under varying light intensities ($0$ to $2000 \ \mu\text{mol photons m}}{-2}\text{s}^{-1}$), predicting the fluorescent output intensity ($F_{\text{green}}$).

3. Synthetic Biology Techniques Utilized

In validating this central control aspect, multiple foundational synthetic biology techniques were systematically deployed:

• In Silico DNA Design and Codon Optimization were utilized to customize the mammalian-derived GCaMP6s gene for high-level expression inside the cyanobacterial host.
• High-Fidelity PCR Amplification was carried out using customized primers to generate precisely matched homology overlaps.
• Gibson Assembly was utilized to seamlessly directionally clone the multi-component promoter-reporter cassette into the targeting plasmid vector without restriction enzyme scarring.
• Computational Mathematical Modeling and Kinetic Simulation were deployed to analyze the time-resolved fluorescence curves, turning a qualitative biological reaction into a predictable, quantitative input for silicon-based micro-circuit automation.

4. Data Presentation and Quantitative Analysis

The dynamic performance of the engineered interface was validated using simulated kinetic data generated via computational modeling of the calcium-binding affinity parameters.

Key Results

SECTION 6: ADDITIONAL INFORMATION

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