Week 1 HW: Principles and Practices

Assignments: Class 1 Assignment

Question 1

I propose a high-throughput microscopy tool to estimate intracellular PHA accumulation from granule count and size. Current standart quantification methods are slow, labor-intensive, and often require hazardous solvent-based extraction. By pairing PHA staining (e.g., Sudan Black B or Nile Red A) with automated imaging and machine-learning (ML) image segmentation, this approach could rapidly screen large libraries of environmental isolates and recombinant strains for high PHA producers.

Future upgrades, offered as a premium beta for testing, could add a “material profile” output by predicting PHA chain-length class (SCL, MCL, or LCL) from staining/fluorescence response patterns using the lipophilic dyes. This would enable not only faster strain selection but also early-stage differentiation of polymer type, which is critical for downstream biotechnology applications.

A further upgrade could generate image-driven optimization suggestions from microscopy images. For example, if it detects a high level of extracellular debris consistent with cell lysis, or a high abundance of product granules outside the cells, it could recommend exploring strain-engineering strategies that alter cell membrane composition to increase tolerance to mechanical stress and support higher intracellular polymer accumulation as cytoplasmic granules.

Question 2

Gov / Policy Goal 1: Prevent harmful misuse

• Sub-goal 1.1 - Limit repurposability: Reduce the extent to which the tool can be used as a general-purpose and high-throughput optimization engine outside its intended PHA scope, for example by restricting supported dyes and limiting microscopy calibration parameters to validated settings.

• Sub-goal 1.2 - Increase accountability: ensure high-impact uses are traceable and that institutions have a mechanism to intervene if misuse is suspected.

Gov / Policy Goal 2: Promote safe, responsible operation and research integrity

• Sub-goal 2.1 - Standardize safe use: Require adherence to Standard Operating Procedures (SOPs) for staining, imaging, and waste handling.

• Sub-goal 2.2 - Ensure competent users: Require completion of a short training module, including lab safety + tool-specific quality control (QC) before users can access advanced features or export “final” reports.

• Sub-goal 2.3 - Maintain data quality: Require basic QC checks (controls, calibration, and logging of model version and imaging settings) to reduce false positives/negatives and prevent misinterpretations.

Gov / Policy Goal 3: Maintain access for constructive uses (equity and scientific progress)

• Sub-goal 3.1 - Preserve legitimate research utility: avoid governance mechanisms that unnecessarily slow routine PHA research and screening.

• Sub-goal 3.2 - Proportional governance: apply stricter controls only to higher-impact capabilities (e.g., advanced optimization suggestions), rather than restricting all use.

Question 3

Option 1:

General action: Norms combined with oversight mechanisms (social/regulatory governance)

Purpose: Currently, PHA quantification is typically validated through chemical extraction and analytical methods rather than standardized image-based measurement. A robust image-analysis tool like this would significantly increase throughput and expand where and how screening can be performed. If an image-analysis approach is positioned as a scalable screening tool, it should include safeguards to prevent use outside validated conditions. A responsible-use policy with “red flag” triggers would provide a proportional oversight mechanism.

Design:

• Actors: principal investigators (PIs) and laboratory personnel (primary users), microscopy core facility staff, the university biosafety office (or equivalent), and an institutional ethics/biosafety committee.

• Mechanism: implement a short pre-use declaration form and a responsible-use policy that defines “red flag” contexts (e.g., high-throughput work on unverified environmental isolates without provenance, use outside standard biosafety environments, or attempts to generalize the tool beyond PHA workflows).

• Trigger response: if a red flag is triggered, require review by the biosafety/ethics committee (or the biosafety office) and compliance with institutional requirements before experiments or tool access continue.

Assumptions:

• Users will accurately disclose the intended use and experimental context (or there will be sufficient deterrence to reduce misreporting).

• Red-flag criteria can be defined clearly enough to be actionable and consistent across labs.

• The institution has capacity to perform timely reviews without creating major delays for legitimate projects.

• Some level of auditing is feasible (e.g., metadata logs or usage reporting), which may require limited access to usage data.

Risks of failure and “success”:

• The policy becomes symbolic and is not followed; criteria are too vague to enforce; or users misreport their purpose to avoid review.

• Overly broad triggers could make oversight routine, slowing research and disproportionately burdening smaller or under-resourced labs (equity and access concerns).

Option 2:

Restrict advanced features: High-impact features require auditable access (accountability governance) Purpose: Adding accountability for higher-impact features while keeping basic screening broadly accessible.

Design:

• Actors: tool developers (academic or company), institutions adopting the tool.

• Baseline access: basic PHA screening module available for standard use.

• Advanced access (premium/beta): requires institutional opt-in (verified affiliation, training completion, and standard operating procedures adherence).

• Logging: maintain run logs with technical metadata only (model version, stain, imaging settings, quality control pass/fail, solvent/waste metadata etc).

• Incident response: provide an incident-reporting channel so access can be suspended if misuse is suspected.

Assumptions:

• Logging and gating deter misuse without driving users to ungoverned copies.

• Metadata-only logs are sufficient for accountability without compromising privacy.

• Institutions are willing to administer opt-in and training requirements.

Risks of failure and “success”:

• Users bypass controls by using modified versions or alternative tools; logging becomes incomplete.

• Reduced accessibility and higher admin burden, potentially concentrating access in well-resourced labs.

• Analogy: similar to “KYC tiers” in financial systems: more powerful capabilities require stronger verification and auditability.

Option 3:

Just for PHA: Scope capabilities through validated workflows (technical strategy / design constraint). Purpose: General-purpose screening tools are easier to repurpose. One way to limit their repurposability is by restricting the tool to validated PHA workflows.

Design:

• Actors: tool developers and maintainers; optionally journals or core facilities that require validated workflows for reporting.

• Technical constraint: restrict supported dyes and workflows to PHA-relevant staining and analysis; lock calibration parameters to validated microscopy settings; exclude generic “optimize any phenotype” modules.

• Reporting constraint: outputs are labeled as screening support, with clear limits on claims and recommended confirmatory methods for final quantification.

Assumptions:

• Technical restrictions meaningfully reduce repurposability.

• The validated workflow remains useful across common lab setups and organisms.

• Users accept constraints rather than abandoning the tool.

Risks of failure and “success”:

• Restrictions are easily removed in forks / hacks etc; scope limits become ineffective.

• Reduced scientific and commercial usefulness, including for ethically beneficial non-PHA applications; may slow innovation.

• This is analogous to 3D printers that restrict materials and firmware settings: the core function remains available, but out-of-scope production becomes harder without intentional modification.

Question 4

Question 5

I would prioritize Option 3 as the primary governance approach, aimed at tool developers and maintainers. Although Option 3 has the weakest overall score, I assign higher weight to practical implementability and consistent adoption, since governance mechanisms that require sustained oversight or significant administrative capacity are often applied inconsistently in real research settings. Option 3 can be implemented directly in software and routine workflows by restricting the tool to validated PHA use cases (supported dyes, locked calibration ranges, and scoped outputs). This reduces repurposability by design rather than relying on user compliance, making the default use safer and more predictable while preserving the core constructive application: scalable PHA screening.

The key trade-off is that Option 3 scores poorly on “helping respond” (biosecurity and lab safety), because it provides limited traceability and fewer mechanisms for intervention after deployment. It also narrows beneficial extensions beyond PHA, potentially limiting constructive applications in adjacent domains.

This recommendation also rests on several assumptions and uncertainties: that capability scoping meaningfully reduces repurposability in practice; that users will not widely circumvent constraints via modified versions or alternative tools; and that the validated workflow generalizes across common microscopes, organisms, and staining conditions.

Final Reflection

The main new ethical concern for me was how quickly a tool designed for a narrow, constructive purpose (PHA screening) can become a general “scale-up enabler” once it is automated and paired with machine-learning image analysis. To address this, I would recommend capability scoping by restricting the tool to validated PHA workflows (supported dyes, locked calibration ranges, and scoped outputs)

Week 2 Lecture Prep

Homework Questions from Professor Jacobson:

Question 1 High-fidelity, proofreading-proficient replicative DNA polymerases have an error rate of ≈ 10⁻⁶ during synthesis under standard conditions. The human nuclear genome is about 3.2 × 10⁹ base pairs per haploid set. If errors happened at 10⁻⁶ per base, you’d expect roughly 3.2 × 10⁹ × 10⁻⁶ ≈ 3.2 × 10³ (≈ 3,200) errors per haploid genome copy. However, in living cells, the effective replication error rate is far lower once proofreading (3′→5′ exonuclease) and post-replication repair (such as mismatch repair, MMR) are included: a commonly cited order of magnitude is ≈ 10⁻⁹ to 10⁻¹⁰ errors per base pair per replication.

Question 2 Because of codon degeneracy, the same amino-acid sequence can be encoded by many DNA coding sequences. A rough average multiplicity per amino acid is about 3.05 synonymous codons. Given an average human protein of 1036 bp and that coding DNA uses 3 bp per amino acid, 1036 bp / 3 ≈ 345 codons. So the number of different DNA coding sequences that produce the exact same protein is on the order of ≈ 10¹⁶⁷. In practice, though, synonymous variants are not always functionally equivalent. Some synonymous changes produce transcripts with different stability and structure. For example, synonymous substitutions can lead to hairpins or repetitive motifs that increase recombination and reduce construct stability. They can also change ribosome speed patterns (which can alter co-translational folding and lead to misfolding, aggregation, or altered activity). In addition, synonymous changes can inadvertently create or disrupt regulatory sequence motifs (e.g., polyadenylation signals or splicing enhancer/silencer elements in eukaryotes).

Homework Questions from Dr. LeProust:

The golden standard for synthesis of oligonucleotides is the solid-phase oligonucleotide synthesis (SPOS) based on phosphoramidite chemistry (Walther et al. 2020). However, this method struggles beyond ~200nt because every nucleotide is added in a multi-step cycle and small inefficiencies and side reactions compound with length.

Homework Question from George Church:

Question: What are the 10 essential amino acids in all animals and how does this affect your view of the “Lysine Contingency”?

Answer: The 10 essential amino acids in all animals are Arginine, Histidine, Isoleucine, Leucine, Lysine, Methionine, Phenylalanine, Threonine, Tryptophan, and Valine. Considering this, Jurassic Park’s biocontainment method is a joke, since it doesn’t create a unique dependency in animals: animals already can’t synthesize lysine. Also, as containment-by-dependency, it’s ecologically leaky because they did not consider the possibility that lysine was readily available in the environment. Lysine is available via plants and prey, so escape doesn’t remove access. OBS: I answered this by consulting a Jurassic Park subreddit discussion.