Week 1 HW: Principles and Practices

1. First, describe a biological engineering application or tool you want to develop and why.

Paratransgenic symbiont to block dengue transmission in Aedes aegypti

Mosquito-borne dengue is a global threat, yet current control measures have a vector elimination focus increasingly undermined by insecticide resistance. Vaccines have shown limited efficacy, and with no broadly effective antivirals, dengue prevention still relies heavily on mosquito and larvae control (Hu et al., 2025). Considering this, researchers are leveraging synthetic biology to develop paratransgenic strategies that render A. aegypti mosquitoes refractory to infection by delivering anti-pathogen molecules inside the mosquito, thereby blocking virus replication and transmission (Gao et al., 2025). The biological engineering tool proposed is a synthetic paratransgenic bacterial symbiont designed to live in the gut of A. aegypti mosquitoes and actively block dengue virus transmission. The purpose is to use a naturally mosquito-associated bacterium (such as Asaia spp.) genetically engineered to sense mosquito feeding conditions and secrete antiviral effector molecules directly into the midgut lumen. The gut of A. aegypti offers a strategic intervention point. Dengue virus first encounters the midgut epithelium after a blood meal, and if viral entry is blocked at this stage, systemic infection of the mosquito can be prevented by secretion of viral entry inhibitors, such as peptides. It is an ecologically targeted solution, because it doesn’t intend to eradicate the mosquito populations from their ecosystems, as every part of the trophic network needs to stay in balance.

Sources

Gao, H., Hu, W., Cui, C., Wang, Y., Zheng, Y., Jacobs-Lorena, M., & Wang, S. (2025). Emerging challenges for mosquito-borne disease control and the promise of symbiont-based transmission-blocking strategies. PLoS Pathogens, 21(8), e1013431. https://doi.org/10.1371/journal.ppat.1013431 Hu, W., Gao, H., Cui, C., Wang, L., Wang, Y., Li, Y., Li, F., Zheng, Y., Xia, T., & Wang, S. (2025). Harnessing engineered symbionts to combat concurrent malaria and arboviruses transmission. Nature Communications, 16(1), 2104. https://doi.org/10.1038/s41467-025-57343-2

2. Next, describe one or more governance/policy goals related to ensuring that this application or tool contributes to an “ethical” future, like ensuring non-malfeasance (preventing harm). Break big goals down into two or more specific sub-goals

1. Minimize Ecological Disruption.

Ecuador’s laws have a strong precautionary approach. The 2008 Constitution explicitly bans any genetically modified organisms (GMOs) that may be harmful to human health, food sovereignty or ecosystems and requires precautionary measures against activities that could drive species to extinction or destroy ecosystems. At a regulatory level, the Organic Environmental Code from 2017 mandates that competent authorities issue detailed biosafety regulations and conduct case-by-case risk assessments for all modern biotechnology products to prevent impacts on biodiversity and the environment

1.1 Ensure that genetically modified symbionts do not unintentionally affect non-target mosquito species or other organisms through horizontal gene transfer or ecological spillover.

1.2 Implement long-term ecological monitoring of mosquito populations and their predators to confirm that the intervention does not disrupt local food webs or biodiversity

2. Contain and Control Engineered Microorganisms

Ecuador’s biosafety regulations require rigorous containment and risk management for any GMOs. The Environmental Code’s biosafety chapter in articles 229 to 233 states the requirement for institutions to evaluate and manage risks of GMOs to prevent or avoid any adverse effects on the environment, biodiversity or public health. Proponents of any GMO activity must submit comprehensive risk assessments and follow government‐defined risk-management parameters at each stage. Locally, the Comisión Nacional de Bioseguridad (CONABIO) has been established to coordinate interagency oversight of such activities, and Galápagos Biosecurity Agency (ABG) would similarly screen any exotic microbes for release.

2.1 Develop and enforce biosafety standards that require the engineered microbial strains to have built-in biocontainment systems to prevent uncontrolled environmental spread.

2.2 Require pre-release risk assessments and phased field trials under regulatory oversight to evaluate microbial persistence, gene stability, and potential unintended interactions.

3. Promote Transparency and Public Engagement

The Ecuadorian Constitution guarantees that “all persons have the right to freely access information generated by public entities. No information shall be withheld except as established by law.”. Environmental laws require public consultation. The secondary Environmental Code regulations mandate coordination of citizen participation mechanisms and formal public consultations for decisions on living modified organisms. In practice this means communities, including indigenous and local stakeholders, must be informed and consulted before releases.

3.1 Establish open communication channels with affected communities, including clear explanations of the goals, risks, and safeguards of the paratransgenic approach.

3.2 Include local stakeholders in ethical review and governance frameworks to ensure culturally appropriate consent and benefit sharing.

4. Align with Global Health and Equity Principles

Ecuador’s strategies for biotechnology are framed by broader commitments to public health and social equity. Internationally, the Sustainable Development Goals and WHO’s health strategies call for universal, affordable access to health innovations. WHO’s latest vector-control frameworks explicitly focus on safety, affordability and effectiveness of new tools

4.1 Ensure that the tool is accessible and affordable to dengue-endemic low- and middle-income countries (LMICs) and not monopolized by private patent holders.

4.2 Align the deployment strategy with WHO guidelines and regional vector control programs to ensure coordinated, ethically governed interventions

Sources

CONSTITUCION DE LA REPUBLICA DEL ECUADOR 2008 as a download

REGLAMENTO AL CODIGO ORGANICO DEL AMBIENTE

3. Next, describe at least three different potential governance “actions” by considering the four aspects below (Purpose, Design, Assumptions, Risks of Failure & “Success”)

4. Next, score (from 1-3 with, 1 as the best, or n/a) each of your governance actions against your rubric of policy goals.

5. Last, drawing upon this scoring, describe which governance option, or combination of options, you would prioritize, and why. Outline any trade-offs you considered as well as assumptions and uncertainties.

Based on the scoring and analysis, I would prioritize a combined governance approach—anchored in Option 2 (Mandatory Risk Protocols) as the foundation, supported by Option 1 (Tiered Registry) and Option 3 (Community Engagement)—to be recommended to international biosafety regulators and global health bodies, such as the Secretariat of the Cartagena Protocol, the World Health Organization (WHO), and national biosafety authorities in dengue-endemic countries like Ecuador’s Ministry of Environment and Health.

Weekly Reflections

This week’s class opened my eyes to the ethical complexities of deploying engineered biological tools like synthetic symbionts in real-world environments. While nearly everything was new to me, one concern stood out most: how weak or misaligned regulatory systems can unintentionally hinder national scientific progress.

As someone who has interned at Ecuador’s Ministry of the Environment, I’ve seen firsthand how delays in permits and biosafety evaluations, especially for research involving genetic engineering does not come from bad intentions but from a lack of technical expertise and understaffing. These issues have worsened since the Ministry was merged with the Ministry of Energy and Mines, creating additional bureaucratic burden without increasing biosafety capacity. This disconnect risks turning regulation into a barrier rather than a guide for safe innovation.

This raises an ethical concern I hadn’t considered before: when poor governance prevents life-saving science, especially in countries heavily affected by vector-borne diseases, it becomes a form of structural injustice. Innovation should not be a privilege reserved for countries with better infrastructure.

Proposed Governance Actions

• Re-establish a dedicated, well-funded national biosafety office, independent from industrial portfolios like mining or energy.
• Develop specialized biosafety training programs for regulatory personnel, in partnership with universities and international biosafety experts.
• Streamline approval pathways for public-interest research, with fast-track options for projects aligned with national health or environmental priorities.
• Create a scientific advisory board to support regulators with risk assessments, especially for synthetic biology proposals.

Week 2 HW: DNA Read, Write and Edit

Part 1: Benchling & In-silico Gel Art

Preliminary notebook sketches illustrating the conceptual design process for the intended latent figure.

Final Product

Part 3: DNA Design Challenge

Protein

Depolymerase 2 MLDNFNQPKGSTIGVLKDGRTIQEAFDSLPRLESFSGSTATDKLRAAITLGVSEVAIGPVEGNGGRPYEFGDVVIPYPLRIVGCGSQGINVTKGTVLKRSAGASFMFHFTGEGQAQRPMGGGLFNINLNGDTATALGDIIKVTQWSYFKANNCAFQNMAGWGIRLKDVMESNISGNLFRRLGGPSGGGILFDDVRSAVTDNVNNLHIEDNTFALMSGPWIGSTANSNPDLIWIVRNKFEFDGTPAAPNTVDSYVLDFQQLSRAFIQDNGFTHFTTERNRYVGVLRVGATAVGTIKFEDNLLFACESAGLIAGGIVVSRGNVNNQGSATTAIKQFTNTSSKLCKLERVINVQSNGNVSVGQQILPDGYINMAELPGNTRLPSEYDADGETTSVLRVPANTQVRQWSVPKMYKDGLTVTKVTVRAKGAAAGAILSLQSGSTVLSTKSIDAGVWKNYVFYVKANQLQETLQLRNTGTADVLADGMVFGKVDYIDWDFAIAPGTLAAGAKYTTPNQSYLDVAGMRVQAVSIPMFDGPTTGLQVWVEATSANGSFVVVMKNDTGSELVTTVTRCRVRAFVS

Reverse Translate ATGATGTTAGATAATTTTAATCAACCTAAAGGTTCTACTATTGGTGTTTTAAAAGATGGTCGTACTATTCAAGAAGCTTTTGATTCTTTACCTCGTTTAGAATCTTTTTCTGGTTCTACTGCTACTGATAAATTACGTGCTGCTATTACTTTAGGTGTTTCTGAAGTTGCTATTGGTCCTGTTGAAGGTAATGGTGGTCGTCCTTATGAATTTGGTGATGTTGTTATTCCTTATCCTTTACGTATTGTTGGTTGTGGTTCTCAAGGTATTAATGTTACTAAAGGTACTGTTTTAAAACGTTCTGCTGGTGCTTCTTTTATGTTTCATTTTACTGGTGAAGGTCAAGCTCAACGTCCTATGGGTGGTGGTTTATTTAATATTAATTTAAATGGTGATACTGCTACTGCTTTAGGTGATATTATTAAAGTTACTCAATGGTCTTATTTTAAAGCTAATAATTGTGCTTTTCAAAATATGGCTGGTTGGGGTATTCGTTTAAAAGATGTTATGGAATCTAATATTTCTGGTAATTTATTTCGTCGTTTAGGTGGTCCTTCTGGTGGTGGTATTTTATTTGATGATGTTCGTTCTGCTGTTACTGATAATGTTAATAATTTACATATTGAAGATAATACTTTTGCTTTAATGTCTGGTCCTTGGATTGGTTCTACTGCTAATTCTAATCCTGATTTAATTTGGATTGTTCGTAATAAATTTGAATTTGATGGTACTCCTGCTGCTCCTAATACTGTTGATTCTTATGTTTTAGATTTTCAACAATTATCTCGTGCTTTTATTCAAGATAATGGTTTTACTCATTTTACTACTGAACGTAATCGTTATGTTGGTGTTTTACGTGTTGGTGCTACTGCTGTTGGTACTATTAAATTTGAAGATAATTTATTATTTGCTTGTGAATCTGCTGGTTTAATTGCTGGTGGTATTGTTGTTTCTCGTGGTAATGTTAATAATCAAGGTTCTGCTACTACTGCTATTAAACAATTTACTAATACTTCTTCTAAATTATGTAAATTAGAACGTGTTATTAATGTTCAATCTAATGGTAATGTTTCTGTTGGTCAACAAATTTTACCTGATGGTTATATTAATATGGCTGAATTACCTGGTAATACTCGTTTACCTTCTGAATATGATGCTGATGGTGAAACTACTTCTGTTTTACGTGTTCCTGCTAATACTCAAGTTCGTCAATGGTCTGTTCCTAAAATGTATAAAGATGGTTTAACTGTTACTAAAGTTACTGTTCGTGCTAAAGGTGCTGCTGCTGGTGCTATTTTATCTTTACAATCTGGTTCTACTGTTTTATCTACTAAATCTATTGATGCTGGTGTTTGGAAAAATTATGTTTTTTATGTTAAAGCTAATCAATTACAAGAAACTTTACAATTACGTAATACTGGTACTGCTGATGTTTTAGCTGATGGTATGGTTTTTGGTAAAGTTGATTATATTGATTGGGATTTTGCTATTGCTCCTGGTACTTTAGCTGCTGGTGCTAAATATACTACTCCTAATCAATCTTATTTAGATGTTGCTGGTATGCGTGTTCAAGCTGTTTCTATTCCTATGTTTGATGGTCCTACTACTGGTTTACAAGTTTGGGTTGAAGCTACTTCTGCTAATGGTTCTTTTGTTGTTGTTATGAAAAATGATACTGGTTCTGAATTAGTTACTACTGTTACTCGTTGTCGTGTTCGTGCTTTTGTTTCTTAA

Codon optimization ATG TTG GAT AAT TTC AAC CAG CCA AAA GGC TCG ACG ATC GGG GTG CTG AAG GAC GGC CGT ACA ATT CAG GAA GCG TTT GAC AGC CTG CCG CGC CTT GAA TCT TTT TCG GGC AGT ACG GCA ACT GAT AAA CTG CGT GCG GCG ATC ACT CTT GGC GTT AGT GAA GTT GCG ATC GGT CCA GTG GAA GGT AAT GGC GGC CGT CCG TAT GAA TTT GGG GAT GTT GTG ATT CCC TAT CCA TTG CGC ATT GTG GGC TGC GGC AGC CAA GGG ATC AAT GTA ACT AAA GGT ACG GTC TTA AAA CGT AGT GCC GGA GCG TCC TTT ATG TTC CAT TTT ACT GGG GAA GGT CAG GCC CAG CGC CCG ATG GGA GGC GGT CTG TTT AAT ATT AAC CTG AAC GGC GAT ACC GCG ACC GCA CTG GGC GAT ATC ATT AAA GTA ACT CAG TGG AGT TAT TTT AAA GCG AAC AAT TGC GCT TTT CAA AAT ATG GCG GGG TGG GGC ATC CGT CTG AAG GAC GTG ATG GAA AGC AAT ATC AGC GGA AAC TTG TTC CGT CGC CTG GGA GGC CCG TCT GGG GGT GGC ATC TTG TTC GAT GAC GTC CGT AGC GCG GTA ACA GAC AAT GTA AAC AAT TTA CAC ATT GAA GAT AAC ACT TTT GCG TTA ATG AGC GGC CCC TGG ATT GGT AGC ACC GCG AAT AGT AAC CCG GAT CTG ATC TGG ATC GTG CGT AAT AAA TTC GAA TTT GAT GGC ACT CCA GCT GCA CCG AAC ACT GTT GAT AGC TAC GTC CTG GAT TTT CAA CAG CTT AGC CGC GCA TTT ATC CAG GAC AAT GGG TTC ACG CAC TTT ACC ACG GAA CGT AAC CGT TAC GTT GGT GTG TTA CGT GTA GGC GCA ACG GCC GTT GGC ACC ATT AAA TTC GAA GAT AAC CTG CTG TTC GCC TGC GAA AGC GCC GGC CTG ATC GCG GGC GGC ATC GTT GTT AGT CGC GGT AAC GTG AAC AAC CAG GGC TCC GCT ACG ACG GCC ATT AAA CAG TTC ACG AAT ACG TCC AGC AAA TTG TGT AAA CTG GAA CGT GTT ATT AAC GTG CAG AGT AAT GGC AAT GTG TCG GTG GGC CAA CAA ATC CTG CCG GAC GGG TAT ATC AAT ATG GCT GAG CTG CCT GGC AAC ACC CGC TTA CCG AGC GAA TAT GAC GCA GAT GGT GAA ACT ACC AGT GTA TTA CGC GTG CCA GCA AAC ACC CAG GTC CGC CAG TGG TCG GTG CCT AAA ATG TAT AAA GAC GGC TTG ACC GTA ACG AAA GTG ACG GTC CGT GCA AAA GGG GCA GCC GCC GGT GCC ATC CTG AGC TTG CAG AGC GGC TCG ACC GTG CTG TCT ACG AAA AGC ATT GAT GCT GGC GTG TGG AAG AAT TAT GTT TTC TAT GTT AAA GCG AAT CAG CTT CAG GAA ACT CTG CAG CTT CGC AAT ACA GGT ACT GCA GAC GTA CTT GCG GAC GGT ATG GTT TTT GGC AAG GTG GAT TAT ATC GAC TGG GAT TTC GCG ATT GCC CCG GGG ACC CTG GCG GCC GGT GCG AAA TAT ACG ACC CCT AAT CAG TCG TAC CTG GAT GTC GCG GGC ATG CGT GTG CAA GCG GTC TCG ATT CCC ATG TTT GAT GGC CCT ACG ACT GGA TTA CAG GTC TGG GTA GAA GCC ACC AGC GCG AAC GGT AGT TTC GTG GTG GTC ATG AAA AAC GAC ACG GGT TCA GAA TTG GTC ACC ACC GTG ACT CGC TGC CGT GTG CGC GCG TTT GTA TCA

Build Your DNA Insert Sequence

Choose Your Vector

What DNA would you want to sequence (e.g., read) and why?

I would like to sequence viral metagenomic DNA (environmental virome) collected from aquatic ecosystems, such as wastewater effluent, hospital discharge sites, and agricultural runoff. Rather than focusing exclusively on bacterial genomes, this approach prioritizes complete bacteriophage genomes present in these environments.

Phages are major drivers of bacterial evolution, influencing antimicrobial resistance dissemination, virulence modulation, and horizontal gene transfer. By sequencing environmental phage DNA, it becomes possible to identify functional genetic modules such as receptor-binding proteins, depolymerases, integrases, and transducing elements that shape bacterial populations.

This intends shifts surveillance from reactive pathogen detection to a predictive aproach. Environmental virome sequencing could serve as an early-warning system, detecting emerging resistance dynamics or novel virulence-associated genetic elements before they become clinically dominant.

In lecture, a variety of sequencing technologies were mentioned. What technology or technologies would you use to perform sequencing on your DNA and why?

To sequence environmental viral metagenomic DNA, It would be ideal to use a combination of third-generation long-read sequencing (Oxford Nanopore or PacBio) and second-generation high-throughput short-read sequencing (Illumina) in a hybrid strategy.

I think that this approach would leverage the strengths of both platforms: long reads enabling assembly of complete phage genomes and the resolution of structural variants, while short reads provide high accuracy for polishing and variant correction.

Input: purified viral DNA extracted from environmental water samples.

Essential preparation steps:

• viral particle enrichment (filtration and DNase treatment to remove non-viral DNA)

• viral DNA extraction

• library preparation

• fragmentation (for short-read platforms)

• end repair and adapter ligation

• quality control and quantification

Illumina (second generation):

• DNA fragments bind to a flow cell.

• Bridge amplification creates clusters.

• Sequencing by synthesis occurs using fluorescently labeled reversible terminator nucleotides.

• After each nucleotide incorporation, fluorescence is detected.

• Base calling is determined by the emitted fluorescent signal.

Nanopore (third generation):

• Single DNA molecules pass through a protein nanopore.

• Each nucleotide alters ionic current differently.

• Electrical signal changes are recorded in real time.

• Machine learning algorithms convert signal patterns into base calls.

The output consists of:

• FASTQ files containing sequence reads with quality scores

• Assembled phage genomes

• Annotated functional gene predictions

• Comparative genomic datasets for surveillance

What DNA would you want to edit and why?

For this project, I would love to synthesize a phage-derived receptor-binding domain (RBD) fused to a fluorescent reporter, essentially creating a highly specific bacterial detection module inspired by bacteriophages.

Phages are incredibly precise when it comes to recognizing their bacterial hosts — their tail fibers or tailspikes bind very specific surface structures like capsules or LPS. Instead of synthesizing a whole phage genome (which would be unnecessary and unsafe), I would isolate just the receptor-binding domain of a phage tail fiber that targets a clinically relevant bacterium, such as Klebsiella pneumoniae. Then I would fuse that domain to a reporter protein like GFP.

The idea is that this synthetic gene would encode a fusion protein that binds specifically to its bacterial target and produces a fluorescent signal. So instead of using antibodies for detection, we would be using phage specificity as a biosensing tool. I think that’s incredibly powerful because phage receptor-binding proteins are often more specific than antibodies and can distinguish even subtle differences like capsule types.

To synthesize the phage receptor-binding domain–GFP fusion construct, I would use commercial gene synthesis based on phosphoramidite solid-phase DNA synthesis, followed by enzymatic DNA assembly (such as Gibson Assembly).

Phosphoramidite chemistry is the standard method used to chemically synthesize short DNA oligonucleotides. These oligos can then be assembled enzymatically into a full-length gene construct. This approach is highly accurate and allows complete sequence customization, including codon optimization and addition of regulatory elements.

I would choose this method because it enables precise design of non-replicative, modular constructs without needing a natural template, which is ideal for synthetic biology applications.

What DNA would you want to edit and why?

I would want to edit bacteriophage genomes, specifically lytic phages that infect clinically relevant bacteria such as Klebsiella pneumoniae or other multidrug-resistant pathogens.

Phages naturally evolve to recognize and infect bacteria, but their host range is often narrow and their therapeutic use can be limited by bacterial resistance mechanisms. By editing phage DNA, we could enhance desirable properties such as host specificity, lytic efficiency, or anti-virulence activity, while maintaining safety.

• The types of edits I would focus on include:

• Modifying tail fiber or receptor-binding protein genes to expand or retarget host range.

• Inserting capsule depolymerase genes to improve penetration of protective bacterial capsules.

• Deleting lysogeny-related genes (if present) to ensure strictly lytic behavior.

• Optimizing regulatory elements to increase stability and predictability of infection dynamics.

The goal would not be to make phages more harmful, but rather more precise and controllable as therapeutic or ecological tools. In a One Health context, engineered phages could be used to reduce pathogenic bacteria in clinical, agricultural, or environmental settings without relying solely on antibiotics.

To edit bacteriophage genomes, I would use CRISPR-Cas–based genome editing combined with homologous recombination in bacterial host cells.

CRISPR-Cas systems are precise and programmable, making them ideal for modifying specific genes such as tail fiber or depolymerase genes. This approach allows targeted edits without randomly mutating the phage genome. CRISPR-Cas works by using a guide RNA to direct the Cas nuclease to a specific DNA sequence. The Cas enzyme creates a cut at that location. If a repair template containing the desired modification is provided, the cell’s natural DNA repair machinery incorporates the new sequence.

• For phage editing, the general process would involve:

• Designing a guide RNA targeting the phage gene of interest.

• Designing a donor DNA template containing the desired modification.

• Introducing the CRISPR system and donor template into a bacterial host.

• Infecting the bacteria with the phage.

• Selecting for phages that incorporate the desired edit.

Preparation includes:

• Designing guide RNAs targeting specific phage genes.

• Designing a donor DNA repair template containing the edited sequence.

• Cloning CRISPR components into plasmids.

• Preparing competent bacterial host cells.

There are several limitations:

• Editing efficiency can vary depending on the phage and target gene.

• Some phages may escape editing due to rapid replication.

• Off-target effects are possible if guide RNAs are not carefully designed.

• Delivery of editing components must be optimized.

Week 2 LP: DNA Read, Write and Edit

In preparation for Week 2’s lecture on “DNA Read, Write, and Edit" answer the following questions in each faculty member’s section

Homework Questions from Professor Jacobson

Homework Questions from Dr. LeProust

Homework Questions from George Church

Hou, Y., & Wu, G. (2018). Nutritionally essential amino acids. Advances In Nutrition, 9(6), 849-851. https://doi.org/10.1093/advances/nmy054

Week 3 HW: Lab Automation

Opentron Art

Post-Lab Questions

Find and describe a published paper that utilizes the Opentrons or an automation tool to achieve novel biological applications.

Summary

This study introduces Pyhamilton, an open-source Python framework that enables flexible programming of liquid-handling robots for high-throughput biological experimentation. Unlike traditional robotic automation, which merely replicates hand-pipetting protocols, Pyhamilton allows for dynamic decision-making, asynchronous execution, and real-time feedback integration.

The authors demonstrate several novel applications:

• Complex liquid transfer patterns to simulate population dynamics.

• Real-time feedback-controlled turbidostats maintaining hundreds of bacterial cultures in log-phase growth.

• Automated metabolic fitness landscape mapping across 100 nutrient conditions in triplicate.

• Integration with plate readers to dynamically adjust media replacement based on optical density measurements.

Notably, the system enables maintenance of up to 480 parallel cultures with real-time monitoring and feedback control, transforming static protocols into adaptive experimental systems. The paper illustrates how automation becomes transformative when paired with programmable control logic, data-driven feedback, and asynchronous task execution, enabling experiments impossible to perform manually.

Citation

Chory EJ, Gretton DW, DeBenedictis EA, Esvelt KM. Enabling high-throughput biology with flexible open-source automation. Mol Syst Biol (2021).

Write a description about what you intend to do with automation tools for your final project.

Project Title: Automated Combinatorial Optimization of Programmable Host Cell Circuits for Viral Vector Manufacturing

What I Intend to Automate

The goal is to automate the tuning and validation of a programmable host-cell control circuit designed to dynamically regulate viral vector production. The automation workflow will focus on:

• Combinatorial helper plasmid ratio optimization

• Promoter and regulatory element tuning

• Viral yield vs cell viability quantification

• Iterative design–build–test cycles

Automated Workflow Overview

1. Construct Assembly & Preparation

• Use Opentrons to assemble combinatorial promoter/RBS variants.
• Prepare helper plasmid ratio matrices.
• Generate condition libraries across 96-well format.

2. Transfection Optimization Matrix

• Variable plasmid concentration gradients
• Helper gene ratio permutations
• Timing-dependent transfection panels

3. Automated Assay Execution

• Dispense transfection mixes
• Transfer media
• Sample supernatant for viral quantification
• Perform viability assays

4. Measurement Integration

• Reporter-based viral production proxy
• Cell viability (fluorescence / luminescence)
• Growth curves

for condition in design_matrix:
    assemble_transfection_mix(condition)
    dispense_to_plate(condition.well)
    incubate()

    viral_signal = measure_fluorescence(condition.well)
    viability = measure_viability(condition.well)

    record_results(condition, viral_signal, viability)

optimize_parameters(results)
generate_next_iteration()

This automation framework transforms viral vector manufacturing optimization from static parameter tuning into a programmable, feedback-driven engineering process aligned with scalable synthetic biology platforms.