Week 1 HW: Principles and Practices
Step 1: Biological Engineering Application. “What do you want to develop and why?”.
Name of the project: “Puente Bio-Sintético Lacustre: Un circuito Dinámico de Biorremediación y Control Fágico Dirigido. (Lacustrine Bio-Synthetic Bridge: Dynamic Bioremediation Circuit and Targeted Phage Control)
My proposal is to develop a “synthetic biological bridge” to remediate fecal pollutant discharge into Lake Budi. Leveraging the resilience of native halotolerant microorganisms—the biological “hardware” already adapted to saline stress—I aim to update their genetic “software” using logic circuits (AND gates) that function as intelligent biosensors. These circuits will allow the bacteria to activate the production of cleaning enzymes (hydrolases) only upon detecting critical concentrations of pollutants or hydrogen sulfide, thus maximizing their metabolic efficiency. Additionally, I will integrate a bacteriophage module into the biochar matrix, designed to selectively eliminate human pathogens, clearing the ecological niche for the remediation consortium to thrive. This technology will be deployed using a dual matrix of clay and pumice to simultaneously treat the deep sediment and the water surface, applying Occam’s Razor: it is more robust to enhance existing local biology than to introduce foreign organisms into the ecosystem.
Step 2: Governance and Policy Goals. “How to ensure an “ethical” future?”.
The overarching goal is to ensure that biological intervention in an open ecosystem contributes to an ethical future through Non-Misappropriation and Environmental Justice.
Sub-goal A: Biocontainment and Orthogonality. Guarantee that genetic modifications and phage agents remain confined exclusively to the discharge area, preventing the escape of synthetic material into the main body of the lake or the food chain.
Sub-goal B: Sovereignty and Local Technological Autonomy. Ensure that the community of Puerto Domínguez and the Municipality of Saavedra have the tools to monitor, validate, and understand the system’s operation, avoiding dependence on external and opaque technology providers.
Step 3: Governance Actions. Propose three different strategies.
Action 1: Technical Strategy of “Suicide Switches” (Kill-Switches) Purpose: Currently, the released microorganisms lack a programmed end-of-life. I propose the integration of a toxin-antitoxin system that induces cell lysis if the bacteria move away from the chemical signature (salinity/contaminant) of the discharge zone.
Design: Academic researchers should design and validate these circuits before any field testing. Funding should be contingent upon the existence of this “self-destruction” mechanism.
Assumptions: It is assumed that the evolutionary stability of the circuit is greater than the mutation rate that could deactivate it.
Risks of failure: An “escape” mutation could allow the consortium to persist in the environment. Extreme “success” could clean the area so quickly that the system shuts down before treating the deeper sludge layers.
Action 2: Supervised Phage Firewall Regulation Purpose: To replace generic bioaugmentation with a specific biocontrol protocol approved by health and environmental regulators.
Design: Creation of regulations requiring the characterization of the host range of the phages used, ensuring they do not infect the lake’s beneficial microbiota. Requires approval from federal health agencies.
Assumptions: It is assumed that the phages will maintain their specificity and there will be no horizontal transfer of virulence genes.
Risks of failure: Rapid co-evolution of resistance in coliforms could invalidate the phage cocktail, requiring constant and costly monitoring.
Action 3: Incentive for Citizen Monitoring with Bio-Logic Sensors Purpose: To democratize environmental oversight by using technology itself as an indicator.
Design: Incorporate a visual output, such as chromoprotein expression, into the genetic circuit, which the local community can observe. The success of the remediation will be indicated by a visible color change in the matrix.
Assumptions: It is assumed that the community has the interest and capacity to report these changes through a simple digital platform.
Risks of failure: Misuse of information by the community to generate unnecessary alarm or vandalism of the treatment matrices.
Step 4: Scoring (Rubric). Rate your actions from 1 (best) to 3.
| Does the option: | Option 1 | Option 2 | Option 3 |
|---|---|---|---|
| Enhance Biosecurity | |||
| • By preventing incidents | 1 | 2 | 3 |
| • By helping respond | 3 | 2 | 1 |
| Foster Lab Safety | |||
| • By preventing incident | 2 | 1 | 3 |
| • By helping respond | 2 | 2 | 2 |
| Protect the environment | |||
| • By preventing incidents | 1 | 1 | 2 |
| • By helping respond | 3 | 2 | 1 |
| Other considerations | |||
| • Minimizing costs and burdens to stakeholders | 3 | 2 | 1 |
| • Feasibility? | 3 | 2 | 1 |
| • Not impede research | 2 | 3 | 1 |
| • Promote constructive applications | 1 | 1 | 1 |
Prioritization and Final Reflection
I would prioritize the combination of Action 1 (Kill-Switch) and Action 3 (Citizen Monitoring).
Justification and Trade-offs: The main trade-off is technical feasibility versus safety. The kill-switch is complex to implement (feasibility score of 3), but it is the only real guarantee of biosafety in an open ecosystem like Lake Budi. However, this technical complexity must be balanced with the simplicity of Action 3, which guarantees social acceptability, a determining factor in local intervention projects.
Uncertainties: The greatest uncertainty lies in the evolutionary stability of the synthetic biology circuit under real field conditions, where fluctuating salinity and competition with wild strains could pressure the deactivation of the biocontainment mechanisms designed in the laboratory.
Proposed Governance Action: Create a Lake Ethics and Biosafety Committee made up of academics, local Mapuche community leaders and municipal technicians, whose function is to audit the design of genetic circuits before their transition from the microcosm to the field.
AI Attribution This homework was developed with the assistance of Gemini (Google AI). I utilized Google Gemini (Model 2.0 Pro) as a thought partner to help structure my original TRL 2 project data into the specific format required for this assignment. The AI assisted in refining the technical terminology regarding genetic circuits and phage therapy, as well as editing the text for clarity and conciseness in English.
In preparation for Week 2’s lecture on “DNA Read, Write, and Edit,” please review these materials:
Lecture 2 slides as posted below. The associated papers that are referenced in those slides.
In addition, answer these questions in each faculty member’s section:
Homework Questions from Professor Jacobson: a. 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?
Error Rate and Genome Comparison Nature’s machinery for copying DNA, the DNA polymerase, operates with an error rate of approximately 1 in 10 6 (one mistake for every million base pairs added) when utilizing its error-correcting capabilities. In contrast, the human genome is approximately 3.2 billion base pairs (3.2 Gbp) in length. This creates a significant discrepancy: at a 10 −6 error rate, a single replication of the human genome would result in roughly 3,000 mutations. Without additional correction, such a high mutation rate would likely be unsustainable for maintaining genetic integrity across generations. Biological Solution to the Discrepancy Biology manages this discrepancy through high-fidelity mechanisms. The sources highlight that polymerase maintains its accuracy through: • 3’-5’ proofreading exonuclease activity: This allows the enzyme to “check” the last added nucleotide and remove it if it is a mismatch. • 5’-3’ error-correcting exonuclease activity: Additional enzymatic pathways serve to identify and repair errors during or after the synthesis process.
b.How many different ways are there to code (DNA nucleotide code) for an average human protein? In practice what are some of the reasons that all of these different codes don’t work to code for the protein of interest?
Ways to Code for a Protein An average human protein is approximately 1,036 base pairs long. While the sources do not provide a specific total number of possible DNA sequences for this length, they discuss the Genetic Code as a system where multiple codons can often code for the same amino acid (redundancy). This redundancy technically allows for a vast number of synonymous DNA sequences to produce the same primary protein structure. Reasons Why Different Codes May Not Work In practice, many of these synonymous codes fail to produce the protein of interest effectively due to several biological and physical constraints identified in the sources: • Secondary Structure Interference: The DNA or transcribed RNA sequence may form stable secondary structures, such as hairpins or stems, based on its Minimum Free Energy (MFE). For instance, sequences with high GC content (e.g., 90%) form very stable structures (with free energies as low as -41.51 kcal/mol) that can physically block the machinery of transcription or translation. • RNA Cleavage Rules: Certain sequences may inadvertently match “cleavage rules” for cellular enzymes. For example, in E. coli, RNase III follows specific in vivo cleavage rules that can lead to the degradation of mRNA before it can be translated into the desired protein. • Optimal Complexity and Balance: There is a theoretical balance between codon redundancy and diversity required to maximize the “complexity” of biological constructs; if a code is too repetitive or poorly balanced, it may not function optimally within the cellular environmen
Homework Questions from Dr. LeProust: What’s the most commonly used method for oligo synthesis currently? Why is it difficult to make oligos longer than 200nt via direct synthesis? Why can’t you make a 2000bp gene via direct oligo synthesis?
The most commonly used method for oligonucleotide synthesis currently is the phosphoramidite method. This chemical approach, originally developed in the 1980s, typically utilizes a solid-phase cycle involving coupling, capping, oxidation, and deblocking steps to build DNA sequences one nucleotide at a time. The difficulty in making oligos longer than 200nt via direct synthesis—and the reason a 2000bp gene cannot be synthesized in a single continuous chain—stems from the following factors: • Cumulative Efficiency and Truncation Products: Direct synthesis is a multi-step chemical process where each added base has a specific coupling efficiency. In baseline processes, as the chain length increases, the accumulation of incomplete sequences leads to a significant amount of truncation products. While boundary-pushing methods have recently demonstrated the direct synthesis of 700mers, standard commercial offerings from competitors often remain limited to around 170 nucleotides. • Error Rates: Traditional synthesis methods struggle with maintaining sequence integrity over long stretches. For example, while advanced platforms can achieve low error rates (such as 1:3,000 bp), maintaining this accuracy across very long direct synthesis runs is technically challenging. • The Need for Assembly: Because of the limitations in length and purity for direct synthesis, large genes (like those 2000bp or longer) are produced through gene assembly. This process involves synthesizing many smaller oligos (e.g., 40-mers) and then using techniques like PCR-based gene assembly or enzymatic assembly to stitch them together into a single, full-length double-stranded DNA fragment
Homework Question from George Church: Choose one question. What are the 10 essential amino acids in all animals and how does this affect your view of the “Lysine Contingency”?
The 10 essential amino acids generally recognized for most animals (including humans, though some are only essential under specific conditions like infancy) are Arginine, Histidine, Isoleucine, Leucine, Lysine, Methionine, Phenylalanine, Threonine, Tryptophan, and Valine. (Note: This information is from general biological knowledge and is not explicitly listed in the provided sources.) The “Lysine Contingency” is a well-known plot device from the book and film Jurassic Park, where dinosaurs were genetically engineered to be unable to synthesize the amino acid lysine (represented by the letter K in the sources). This was intended as a “fail-safe” to ensure they would die if they escaped the island and lost access to their lysine-supplemented diet. However, the knowledge of essential amino acids significantly undermines the scientific logic of this contingency. All animals, including the humans and modern birds/reptiles upon which the fictional dinosaurs were based, are already incapable of synthesizing lysine. Because lysine is a standard essential amino acid, it is readily available in the natural environment (e.g., in meat or various plants), meaning any escaped animal would simply find it in its new diet. This makes the fictional contingency biologically redundant and ineffective. In contrast, the technology presented in Prof. Church’s slide #4 and related research offers a sophisticated, real-world version of this concept: • Expanding the Genetic Alphabet: Slide #4 describes the development of semi-synthetic organisms that use an expanded genetic code with unnatural base pairs, such as dNaM-dTPT3, which do not rely on traditional hydrogen bonding. • Non-Standard Amino Acids (NSAAs): This expanded alphabet (using bases like X and Y) allows for the ribosomal incorporation of non-standard amino acids (NSAAs) into proteins. • Real Biocontainment: Unlike the failed “Lysine Contingency,” modern synthetic biology creates metabolic isolation by engineering organisms to be dependent on these synthetic NSAAs. Because these amino acids do not exist in nature, the organism has a true “synthetic dependency”; it cannot survive outside a controlled environment where the specific synthetic monomer is provided. This transition from relying on a common, natural amino acid to a unique, synthetic one represents the shift from fictional “fail-safes” to robust, engineered biocontainment strategies.
Zhang, Y., et al. (2017). “A semi-synthetic organism that stores and retrieves increased genetic information.” Nature. Google NotebookLM was utilized to syntetice information.