Week 14

Node participant note: I am a remote Genspace node listener based in Nigeria without onsite lab access. Week 14 was the final project presentation and course close. I engaged with the Bio Design and Fabrication lecture content and document the ÌṢỌ final project summary below.

Class Assignment — Week 14

Part A. Bio Design and Fabrication: Course Notes

Christina Agapakis and Design as Practice

The framing that resonated most from Agapakis’s work is that design in biology is not just about making functional things. It is about making legible things. A biosensor that works but whose logic no one outside the lab can follow is not a complete design. A containment system that is technically sound but whose failure modes have not been communicated to non-specialist stakeholders is not a complete design.

ÌṢỌ has been designed with this in mind from the start, though the pressure to make the design legible to different audiences becomes concrete at the final project stage. The ODE model is legible to a computational biologist. The construct map is legible to a molecular biologist. The public health framing (reducing childhood diarrhoeal mortality in West Africa) is legible to a clinician or a funder. Making all three levels of legibility available simultaneously, without compromising the technical rigour of any one layer, is the actual design challenge that this week crystallised for me.

Christopher Chen and Fabrication Thinking

Chen’s work on biofabrication brought a question I had not fully resolved in my own design: at what point does a computational model become a fabrication plan? The answer is not when you have high confidence in the model parameters. It is when you have a clear path from model output to physical substrate. For ÌṢỌ, that path runs through the Twist construct, through a collaborating lab for transformation and selection, through a plate reader for expression verification, and through co-culture assays for kill kinetics. Each step is specified in the Week 10 measurement framework. The fabrication story is there. What it lacks is the first physical artefact to anchor it.

That artefact is the Twist order. It is the one non-computational output from this course, and it represents the transition from design to fabrication in the most minimal possible sense.

Part B. ÌṢỌ Final Project Summary

What was built

A model-first, constraint-aware computational framework for engineering E. coli Nissle 1917 as a gut sentinel: sensing context, responding with targeted antimicrobials, and remaining governable through built-in containment.

Deliverables produced during HTGAA 2026:

  • ODE model of the tetrathionate biosensor response circuit (Tellurium, Week 7)
  • Moran process simulation of containment escape probability under selection pressure
  • ESMFold structural model of TolC-MccH47 export pathway (Week 4)
  • ProteinMPNN alternative sequences for TolC backbone (Week 4)
  • Benchling construct: MccH47_pUC19_EcN_v1, with primer design and Gibson assembly annotation (Week 6)
  • Twist gene synthesis order submitted: MccH47_pUC19_EcN_construct_v1 (Week 7)
  • Measurement framework mapping every model parameter to a specific future assay (Week 10)
  • Cloud lab job specification for mScarlet-I oxygen supplementation experiment (Week 11)

Key design decisions documented:

  • ΔdapA auxotrophy as the primary containment mechanism, with Luria-Delbrück escape frequency modelling
  • pSC101 backbone preferred over pUC19 for evolutionary stability in EcN, with pUC19 used for initial sequence verification
  • BsaI site removal from MccH47 structural gene for Golden Gate compatibility in downstream modular assembly
  • mScarlet-I as the co-reporter for expression verification, with oxygen supplement hypothesis for 36-hour cell-free validation

What was learned

The course reinforced one principle above all others: biological engineering requires holding three timescales simultaneously. The ODE timescale (minutes to hours, biosensor activation kinetics) is the one most computational tools optimise for. The evolutionary timescale (generations to months, fitness cost and containment stability) is the one most computational tools ignore. The clinical timescale (years to decades, disease burden, treatment gap) is the one that determines whether any of it matters.

ÌṢỌ was designed to hold all three. The model optimises circuit output while tracking fitness cost and escape probability. The choice of pathogen target (Salmonella-induced tetrathionate, relevant to diarrhoeal disease in high-burden settings) anchors the clinical timescale. Whether the design is good will ultimately be judged not by the pTM score of the AlphaFold model but by whether a child in Osogbo is less likely to be admitted with severe dehydration because of it.

That is a long road from where ÌṢỌ currently sits. But the design choices made during HTGAA 2026 are load-bearing steps on that road, and they were made with that destination in mind.

Part C. Project Feedback (Summary)

Feedback received during the course on ÌṢỌ design:

How do you see the tool been deployed in real-life contexts and what do you see are the challenges towards achieving that?

I think the tool would most realistically be deployed as an oral living therapeutic, possibly as a tablet, hydrogel system, chewable capsule, or another ingestible probiotic formulation designed to survive long enough to function within the gut environment.

Beyond treatment itself, I also see potential use in preclinical synthetic biology R&D, where the framework could help researchers evaluate stability, burden, and containment before moving into expensive wet-lab development. It may also contribute to antimicrobial resistance stewardship by supporting more targeted microbial therapies rather than broad-spectrum antibiotic exposure.

The main challenges would likely be biosafety, regulation, and public trust. Even with built-in containment strategies, there would still be concerns about unintended ecological spread or cross-contamination of the engineered microbe, however unlikely that may be. I also think socio-cultural acceptance would matter significantly (in a post-COVID world), especially in communities where genetically engineered therapeutics may be viewed with caution. Because of this, any real deployment would need strong public-health communication, transparency, and long-term safety validation alongside the science itself.

Works Cited

Ba, F., Zhang, Y., Ji, X., Liu, W.-Q., Ling, S., & Li, J. (2023). Expanding the toolbox of probiotic Escherichia coli Nissle 1917 for synthetic biology. bioRxiv. https://doi.org/10.1101/2023.06.05.543671

Lynch, J. P., Goers, L., & Lesser, C. F. (2022). Emerging strategies for engineering Escherichia coli Nissle 1917-based therapeutics. Trends in Pharmacological Sciences, 43(9). https://doi.org/10.1016/j.tips.2022.02.002

Palmer, J. D., Piattelli, E., McCormick, B. A., Silby, M. W., Brigham, C. J., & Bucci, V. (2017). Engineered probiotic for the inhibition of Salmonella via tetrathionate-induced production of Microcin H47. ACS Infectious Diseases, 4(1), 39–45. https://doi.org/10.1021/acsinfecdis.7b00114

Weibel, N., Curcio, M., Schreiber, A., et al. (2024). Engineering a novel probiotic toolkit in Escherichia coli Nissle 1917 for sensing and mitigating gut inflammatory diseases. ACS Synthetic Biology, 13(8), 2376–2390. https://doi.org/10.1021/acssynbio.4c00036

AI Prompts Employed (Claude AI)

  • Synthesise the ÌṢỌ project deliverables from across HTGAA 2026 into a coherent final project summary that identifies what was built, what was decided, and what remains unresolved
  • Explain the concept of biological legibility and apply it to the three-audience problem in ÌṢỌ (computational biologist, molecular biologist, public health)