Week 1 HW: Principles and Practices

1) Proposed application (technical summary)

What: An engineered endophytic bacterium intended to inoculate high-Andean tubers (e.g. Solanum tuberosum, Oxalis tuberosa, Tropaeolum tuberosum) that senses environmental signals inside plant tissue (temperature, water stress, osmotic status) and responds by producing protective factors.

While initially designed for high-Andean tuber crops, the same platform could be adapted to other frost- or stress-sensitive crops (e.g. Andean grains, legumes, or horticultural species) by modifying the endophytic chassis and/or the stress-response modules, without altering the core governance and biosafety framework.

Possible protective outputs:

• Antifreeze proteins (AFPs) and/or protective molecules (osmoprotectants), or
• Functional RNAs (e.g. sRNA/siRNA or short mRNA) that modulate plant gene expression to induce protective mechanisms (increased compatible solutes, membrane modifications, protective enzymes).

How (practical routes):

• Direct secretion: the bacterium synthesizes and secretes AFPs into the apoplast/tissues.
• Cross-kingdom RNA delivery (cross-kingdom RNAi / mRNA): the bacterium produces sRNAs or packages mRNAs in vesicles that are transferred to plant cells and trigger protective pathways. This approach has conceptual precedent in literature on bacterium-mediated RNAi (see Goodfellow et al., 2019).
• Non-living fallback: foliar formulation (permeable capsules containing proteins/RNA) for temporary application when frost is forecast — an alternative for contexts with restrictions on live organisms.

Why it may be valuable:

• Enables localized, temporary protection without altering the plant genome (relevant where transgenic crops are restricted or socially contested).
• Scalable solution appropriate for smallholder agriculture (low infrastructure investment) and adaptable to other crops.

Known technical limitations: transgenic plant studies with AFPs show modest improvements (~1–3 °C), so activity must be optimized and synergized with cellular solutes to achieve meaningful protection; AFP selection and tissue distribution must be studied.
Scientific support for endophytes: endophytes show strong potential to modulate stress tolerance in crops.

2) Governance / policy objectives (main + sub-objectives)

Objective A : Environmental & health safety (non-maleficence)

• A1. Prevent sustained release and proliferation outside target fields.
• A2. Minimize horizontal gene transfer to wild microbiota.
• A3. Ensure non-toxicity to pollinators, soil fauna and water.

Objective B : Promote constructive and equitable use

• B1. Ensure access and benefits for smallholders (participatory governance and benefit-sharing).
• B2. Avoid economic dependency or loss of seed/inoculant sovereignty.

Objective C : Transparency, traceability & accountability

• C1. Public registry of releases and trials.
• C2. Clear monitoring protocols and contingency plans.
• C3. Labeling/information standards for farmers and consumers.

Objective D : Technical & scientific responsibility

• D1. Minimum proven biocontainment requirements before field testing.
• D2. Standards for molecular monitoring (markers, eDNA/metagenomics).

3) Governance actions : each with Purpose / Design / Assumptions / Risks

Action 1 : Phased testing: confined trials + gradual scale-up with independent monitoring

Purpose: produce rigorous ecological and agronomic evidence before wide release.
Design:

1. Phases: (i) controlled greenhouse, (ii) confined field plots (fencing, buffer zones), (iii) community pilots with explicit agreements.
2. Molecular monitoring (soil, root and water sampling; strain-specific genetic markers; periodic metagenomic sequencing).
3. Local biosafety committee with scientists, environmental authorities (e.g. Ministry/INIA), farmer organizations and NGOs.
   Actors: university researchers, INIA/Ministry of Environment, municipalities, farmer cooperatives.
   Assumptions: greenhouse results predict field behavior; resources exist for long-term monitoring.
   Failure risks: accidental escape without early detection; insufficient data quality/statistics; social rejection without participation.
   Success outcome: safe scale-up and community acceptance via participation and demonstrable benefits.

Background note: AFP research and plant applications typically rely on controlled trials; field improvements are hard to predict from greenhouse data.

Action 2 : Mandatory multi-layer biological containment (redundant biocontainment)

Purpose: drastically reduce survival probability outside target environment using multiple genetic safety layers.
Design (technical mix):

• Synthetic auxotrophy for a compound absent in natural ecosystems (dependence on a supplied metabolite).
• Inducible kill-switch that triggers lysis if the bacterium detects absence of a “permissive” signal (e.g. a co-applied chemical or specific temperature/ion).
• Reduced genetic mobility: removal of mobile elements (plasmids, transposons); use of safe chromosomal loci.
• Traceable genetic tags (neutral sequences) to detect the strain in the environment.
  Actors: R&D labs, regulators (requiring biocontainment tests), funders (condition funding on redundancy proofs).
  Assumptions: containment tech can be implemented without losing agronomic function; evolution will not defeat all safeguards simultaneously.
  Failure risks: escape via mutations restoring biosynthesis; horizontal transfer to native microbes; selection for compensatory variants.
  Success outcome: substantially lower establishment probability outside target; greater public and regulatory trust.

Background note: synthetic auxotrophy and CRISPR-based kill switches are documented strategies but require redundant design due to evolutionary risk.

Action 3 : Legal-institutional framework & socio-economic governance scheme

Purpose: protect farmer rights, ensure equity, and define legal responsibilities and compensation mechanisms.
Design:

• National registry of releases and a public database (by crop, strain, location, dates).
• Informed consent and use contracts with farmers (clauses on inoculant handling, obligations, and training).
• Transparency requirements for companies: safety data, trial results, and access to strains for independent verification.
• Benefit-sharing instruments (fair pricing, non-exclusive community licenses, contingency funds).
  Actors: legislators, Ministry of Environment/INIA, NGOs, farmer cooperatives, regulators/tribunals.
  Assumptions: political will exists to regulate (in moratoria contexts, policy may limit or condition trials); institutions can supervise.
  Failure risks: weak laws, regulatory capture by private interests, exclusion of smallholders.
  Success outcome: empowered end users and a clear legal framework enabling responsible trials and equitable scaling.

Practical note for Peru: Peru has a history of strict regulations and moratoria on some GMOs; any plan must map current laws and engage authorities early.

Action 4 : Genomic monitoring & rapid response network (surveillance & mitigation)

Purpose: detect unauthorized presence/establishment and trigger responses (material removal, kill-switch activation or targeted bactericide).
Design:

• qPCR/eDNA panel + periodic metagenomic surveillance in pilot sites and surroundings.
• Predefined action thresholds and communication channels between extension agents, labs and regulators.
• Mobile response teams (kits to activate kill-switch or apply specific bactericides in affected plots).
  Actors: national labs, seed/inoculant banks, municipalities, environmental NGOs.
  Assumptions: early detection enables effective mitigation; technical responses (kill-switch activation, bactericides) work in field conditions.
  Failure risks: late detection; ineffective action at scale; legal constraints to intervene on private plots.
  Success outcome: rapid containment of incidents and increased public confidence.

4) Brief technical & ethical considerations

• AFP selection: highly active insect- or fish-derived AFPs might be needed, but their expression/stability in plant tissues/apoplast must be validated.
• Physiological synergies: combining AFPs with controlled increases in compatible solutes (e.g. sugars) likely outperforms AFP alone; requires understanding tuber physiology.
• Alternatives if GEMs are prohibited: non-living formulations (encapsulated proteins or RNA) or locally isolated, non-engineered bacteria enriched for beneficial traits (note: live isolates still require evaluation).
• Indigenous participation & local rights: mandatory in Andean communities: Free, Prior and Informed Consent (FPIC) and benefit-sharing agreements are essential.

5) Suggested next roadmap (brief)

1. Review national regulations (map Peru / Cartagena Protocol requirements).
2. In vitro studies: select AFP candidate(s), test activity and stability in plant extracts.
3. Choose a native endophytic chassis (preferably isolated from Andean potatoes) to reduce incompatibility risks.
4. Design redundant biocontainment (auxotrophy + kill-switch + removal of mobile elements). Test in microcosms.
5. Implement phased trial protocol with local committees and molecular monitoring.

Selected key references

• Duman, J. G., & Wisniewski, M. J. (2014). The use of antifreeze proteins for frost protection in sensitive crop plants (review on AFPs in plants and efficacy limitations).
• White, J. F., et al. (2019). Endophytic microbes and their potential applications (review: endophyte potential in stress tolerance).
• Goodfellow, S., Zhang, D., Wang, M. B., & Zhang, R. (2019). Bacterium-mediated RNA interference: potential application in plant protection. Plants, 8(12), 572.
• Mandell, D. J., et al. (2015). Biocontainment by synthetic auxotrophy.
• Rottinghaus, A. G., et al. (2022). Genetically stable CRISPR-based kill switches for… (examples of lysis/killswitch circuits).
• Regulatory overview (Peru): reports on moratoria and legislation (e.g. USDA GAIN Report 2012 and later legal analyses).

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

Justifications

Enhance Biosecurity

• By preventing incidents (Option 1): Redundant genetic containment and phased trials reduce the probability of establishment and horizontal gene transfer (HGT).
• By helping respond (Option 1): Genomic surveillance and a defined rapid-response network enable early detection and targeted mitigation.

Foster Lab Safety

• By preventing incidents (Option 1): Clear lab standards, training, and built-in safeguards (e.g., kill-switches) lower accidental release risk during R&D.
• By helping respond (Option 1): Incident protocols, recall/neutralization measures, and independent monitoring enable rapid corrective action.

Protect the Environment

• By preventing incidents (Option 1): Use of native chassis, removal of mobile genetic elements, and non-cellular alternatives minimize ecological establishment and gene flow.
• By helping respond (Option 1): Environmental monitoring plus field mitigation (selective removal, activation of kill-switches, or targeted treatments) limit impacts if escapes occur.

Other Considerations

• Minimizing costs and burdens (Option 2): Non-cellular formulations (proteins/RNA) lower long-term surveillance and regulatory costs; therefore, Option 2 scores better.
• Feasibility (Option 2): Regulatory and logistical hurdles are smaller for cell-free products, making short-term deployment in Peru more practical.
• Not impede research (Option 1): The proposed safeguards allow continued R&D while managing risks.
• Promote constructive applications (Option 1): FPIC, a public registry, and benefit-sharing provisions encourage equitable and responsible use.

Homework 1 (meta)

Title: Homework 1
Weight: 5

HW - Questions from Professor Jacobson1 (meta)

Title: HW - Questions from Professor Jacobson1
Weight: 2

1. Nature’s machinery for copying DNA is called polymerase. What is the error rate of polymerase? How does this compare to the length of the human genome. How does biology deal with that discrepancy?

Respuesta

DNA Replication and Error Rate

The natural mechanism for copying DNA is the DNA polymerase. The intrinsic error rate of a DNA polymerase during nucleotide incorporation is approximately 1 × 10⁻⁶ (one error per 10^6 bases) in the absence of proofreading, according to classic structural and biochemical studies (Beese et al., 1993).

The human genome has an approximate size of 3.2 × 10⁹ base pairs. If replication occurred only with that raw error rate, ~3,200 errors would be expected per genome replication, which would be incompatible with the observed genetic stability.

Biology resolves this discrepancy through multiple layers:

• Proofreading: many DNA polymerases have 3′→5′ exonuclease activity that removes misincorporated nucleotides.
• Mismatch repair (MMR): corrects errors left after replication.
• Combined, these reduce the effective error rate to ~10⁻⁹ – 10⁻¹⁰ per base, yielding on the order of 1–3 mutations per diploid genome per replication (Kunkel & Erie, 2005).

Other buffering factors: redundancy of the genetic code, non-coding DNA, diploidy, and the fact that many mutations are neutral (Kimura, 1983).

Referencias

• Beese, L. S., Derbyshire, V., & Steitz, T. A. (1993). Structure of DNA polymerase I Klenow fragment bound to duplex DNA. Science, 260(5106), 352–355.
• Kunkel, T. A., & Erie, D. A. (2005). DNA mismatch repair. Annual Review of Biochemistry, 74, 681–710.
• Alberts, B., et al. (2015). Molecular Biology of the Cell (6th ed.).
• Kimura, M. (1983). The neutral theory of molecular evolution. Cambridge Univ. Press.

2. How many different ways are there to code (DNA nucleotide code) for an average human protein? In practice what are reasons that all of these different codes don’t work to code for the protein of interest?

Respuesta

Because of degeneracy of the genetic code, the same amino acid can be encoded by multiple synonymous codons. An average human protein contains ~300–350 amino acids; each amino acid can be encoded by 1–6 codons. Assuming an average of ~3 synonymous codons per amino acid, the number of possible coding sequences is on the order of (3^{300}) to (3^{350}) — astronomically large.

Why many synonymous sequences don’t work equally in practice:

• Codon usage bias: organisms prefer certain codons; rare codons can reduce translation efficiency due to low tRNA abundance.
• mRNA structure and stability: sequence affects secondary structure, stability, and interaction with RNA-binding proteins.
• Cryptic signals: sequences can create unintended splice sites, premature polyadenylation, or regulatory motifs.
• Translation kinetics and folding: synonymous changes alter ribosomal pausing and co-translational folding, affecting protein folding and function.

Referencias

• Alberts, B., et al. (2015). Molecular Biology of the Cell.
• Plotkin, J. B., & Kudla, G. (2011). Nat Rev Genet, 12, 32–42.
• Ikemura, T. (1985). Mol Biol Evol, 2, 13–34.
• Chamary, J. V., Parmley, J. L., & Hurst, L. D. (2006). Nat Rev Genet, 7, 98–110.
• Komar, A. A. (2009). Trends Biochem Sci, 34, 16–24.

HW - Questions from Dr. LeProust (meta)

Title: HW - Questions from Dr. LeProust
Weight: 2

1. What’s the most commonly used method for oligo synthesis currently?

Respuesta
The most widely used method is phosphoramidite solid-phase chemical synthesis, consisting of cycles (deprotection → coupling → capping → oxidation) on a solid support (CPG). Industrial standard since the 1980s (Beaucage & Caruthers).

2. Why is it difficult to make oligos longer than 200 nt via direct synthesis?

Respuesta
Because per-cycle efficiency <100% and failures accumulate multiplicatively. Example: if per-base efficiency = 99.5%, then yield for 200 nt ≈ 0.995^200 ≈ 36% full-length product. Beyond ~200 nt, correct product is overwhelmed by truncated sequences.

3. Why can’t you make a 2000 bp gene via direct oligo synthesis?

Respuesta
Because yield becomes effectively zero: 0.995^2000 ≈ 0.00004 (0.004%). Additionally, cumulative chemical degradation and sequence errors make direct synthesis of very long sequences impractical; instead, assemble multiple oligos using PCR/Gibson assembly and correct errors.

Referencias

• Beaucage, S. L., & Caruthers, M. H. (1981).
• Kosuri, S., & Church, G. M. (2014).
• Hughes, R. A., & Ellington, A. D. (2017).