Week 1 HW: Principles and Practices

Inspired by the MELiSSA project (Micro-Ecological Life Support System Alternative) from ESA, this project proposes an ecosystem composed of microorganisms and higher plants using their metabolic waste products as a substrate for the next compartment. This project is designed to study the behavior of artificial ecosystems and to develop the technologies required for future regenerative life-support systems in long-duration human space missions, such as lunar bases or missions to Mars. The system comprises five different compartments, each one colonized respectively by anoxygenic thermophilic bacteria, photoheterotrophic bacteria, nitrifying bacteria, photosynthetic bacteria, higher plants, and the human crew. I would like to conceptually integrate these microorganisms and higher plants with a plasmids-based control system, through the use of reporter genes and inducible regulatory elements. This would increase the security (allowing real-time monitoring of metabolics states, for example) and predictability of the system.

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. A) Safety The goal is to guarantee that biotechnological systems used in closed life-support environments do not cause biological, ecological, or health-related harm. Sub-goals: -Biological control: Establish that all microorganisms used in the system are strictly contained within closed bioreactors, with multiple physical and genetic safeguards to prevent unintended survival outside the system. -Genetic stability and monitoring: Ensure continuous monitoring protocols to detect mutations, horizontal gene transfer, or loss of function in engineered plasmids and microbial strains over long mission durations. -Human health protection: Assess and regulate potential risks to astronaut health, including allergenicity, toxin production, or unintended interactions with the human microbiome in confined environments. B) Promote responsible and transparent use of synthetic biology Goal: Ensure that the development of biotechnological life-support systems are governed transparently and responsibly. Sub-goals: -Ethical oversight and review: Require interdisciplinary ethical review (including biologists, engineers, ethicists, and policymakers) before implementing genetically modified organisms in space missions. -Clear responsibility and accountability: Define who is responsible for the design, maintenance, and emergency response related to biotechnological failures during long-term missions. -Open scientific communication: Promote the publication and sharing of safety data, failures, and best practices to avoid repetition of risks and to foster responsible innovation in space biotechnology.

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

Actors: Academic institutions & research ethics committees

Purpose: This action proposes to develop a standardized requirement for ethical and biosafety review (chosen by researchers, universities and space agencies) before deploying or publishing biotechnological applications.

Design: Universities and research institutions must require approval from ethics and biosafety committees. Funding agencies could condition grants on compliance. Researchers must submit risk assessments and mitigation plans.

Assumptions: Assumes ethics committees have sufficient expertise and resources. Assumes researchers will comply honestly. Training and standardization significantly reduce human error.

Risks of Failure & “Success”: Failure: Bureaucratic delays could slow innovation. Success risk: Over-standardization may discourage exploratory or low-risk research.

Action: Incentives for safety-by-design practices

Actors: Biotech companies & funding bodies

Purpose: Currently, safety features are often added after development. This action encourages integrating safety mechanisms from the design stage.

Design: Grant programs, tax benefits, or certifications for companies that implement safety-by-design standards. Requires collaboration between engineers, biologists, and policymakers.

Assumptions: Assumes financial incentives are strong enough to change behavior. Assumes safety-by-design standards can be clearly defined across technologies.

Risks of Failure & “Success”: Failure: Incentives may be insufficient. Success risk: Companies may focus on “checking boxes” rather than meaningful safety improvements.

Action: Controlled access and monitoring of biotechnological tools

Actors: Federal regulators & law enforcement

Purpose: At present, access to certain tools or data may be insufficiently monitored. This action proposes tiered access controls to prevent misuse while allowing legitimate research.

Design: Regulators define categories of risk. Developers implement user verification, logging, and auditing systems. Law enforcement intervenes only in cases of credible misuse.

Assumptions: Assumes misuse can be detected through monitoring. Assumes access controls do not excessively burden legitimate users.

Risks of Failure & “Success”: Failure: Overly strict controls may push users toward unregulated alternatives. Success risk: Normalization of surveillance could raise privacy and academic freedom concerns.

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. The following is one framework but feel free to make your own:

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. The most important governance option for me would be a combination of the three, emphasizing “Safety-by-design” and “Ethical and biosafety protocols” supported by “Controlled access and monitoring” as a complementary safeguard. For complex projects such as MELiSSA, it is not enough to have only one governance idea, we need some of them in order to control each step properly during the project. Safety-by-design is important because it encourages the integration of biosafety from the beginning, for example through the use of plasmids-based mechanisms as a way to control the metabolic pathways in each step. Ethical and biosafety protocols are more than just formalities; they are tools that ensure shared responsibility and protect scientific integrity through risk prevention and accountability mechanisms.

Prioritizing these governance actions required balancing competing interests. While ‘safety-by-design’ might delay early research and increase budgets, these trade-offs are necessary given the high stakes of life-support failures in space. This strategy relies on the assumption that institutional incentives work and that standards remain consistent across platforms. Despite lingering uncertainties about how space environments affect genetic stability, merging technical guardrails with institutional oversight creates a more resilient framework than relying on a single approach.

Target Audience: This proposal targets international bodies like NASA and ESA, which have the strategic power to align regulations and funding for space biotech. Ethical Reflection: A core concern is accountability within semi-autonomous systems. In setups like MELiSSA, failures might stem from unpredictable biological behaviors rather than human oversight, blurring the lines of responsibility. Furthermore, we must prevent the ‘silent’ transfer of extreme bio-engineering to Earth without public oversight. Proposed Actions: We need explicit accountability frameworks, scenario-based ethical reviews for off-Earth missions, and transparent protocols for knowledge sharing. These steps ensure that space biotech evolves safely and ethically."

Note: This assignment was developed with the assistance of an AI language model (ChatGPT, Gemini), used to help structure ideas and refine wording. The concepts and final decisions were critically reviewed and adapted by the author.

week 2 HW: DNA Read, Write and Edit

Week 02 - Lecture Questions

Professor Jacobson

1. The fidelity of DNA replication is governed by DNA polymerase and its associated repair systems. The intrinsic error rate of DNA polymerase, in the absence of proofreading, is approximately 10^{-4 to 10}-5 per nucleotide. In eukaryotes, replicative polymerases utilize 3’ —} 5’ exonuclease activity for proofreading, which enhances fidelity to an error rate of approximately 10^{-7. When integrated with post-replicative mismatch repair (MMR) mechanisms, the effective error rate is further optimized to roughly 10}-9 to 10^{-10 per nucleotide.Given that the human genome comprises approximately 3.2 x 10}9 base pairs, replication without these multi-layered fidelity mechanisms would result in a mutational load incompatible with cellular viability. Biological systems mitigate this risk through a hierarchy of safeguards—polymerase proofreading, mismatch repair, and various DNA damage response pathways—ensuring that the mutation rate per genome remains within a range that sustains evolutionary stability and life.
2. A typical human protein consists of approximately 300 to 400 amino acids. Due to the degeneracy of the genetic code—where 64 codons encode 20 amino acids—the theoretical number of DNA sequences capable of encoding a single protein is exceptionally high.

However, functional constraints significantly restrict this theoretical diversity. Key limiting factors include:

-Codon Usage Bias: Variations in tRNA availability that influence translation efficiency.

-mRNA Secondary Structure: Folding patterns that may impede ribosome binding or elongation.

-GC Content: Extreme ratios that affect both sequence stability and the feasibility of synthesis.

-Regulatory Interference: The unintended presence of cryptic splice sites or premature termination signals.

-Metabolic Burden: High expression levels that may lead to cellular stress or protein misfolding.

Consequently, while the sequence space is vast, the biological context dictates a much narrower range of viable genetic sequences.

Dr. LeProust

1. Modern oligonucleotide synthesis primarily relies on solid-phase phosphoramidite chemistry. In this process, DNA is synthesized in the 3’ to 5’ direction through iterative cycles of deprotection, coupling, capping, and oxidation.Direct chemical synthesis is currently limited to approximately 150–200 nucleotides. This constraint arises because coupling efficiency is never 100%; as the sequence length increases, the yield of full-length, error-free molecules decreases exponentially. Furthermore, the accumulation of truncated products and point mutations makes the purification of long, high-fidelity oligonucleotides technically prohibitive.To produce longer sequences, such as a 2,000 bp gene, researchers must assemble multiple overlapping short oligonucleotides using enzymatic techniques like PCR assembly or Gibson assembly, followed by sequence verification and cloning.
2. Animals cannot synthesize certain amino acids de novo and must acquire them through their diet. The ten commonly recognized essential amino acids are: Histidine, Isoleucine, Leucine, Lysine, Methionine, Phenylalanine, Threonine, Tryptophan, Valine, and Arginine. Notably, lysine is universally essential across all animal species, representing a fundamental and highly conserved metabolic dependency.

George Church

Question 1: The “Lysine Contingency,” a biocontainment framework proposed by George Church, leverages the metabolic dependency on lysine to prevent the unintended proliferation of engineered organisms. By disabling endogenous lysine biosynthesis, the survival of the organism becomes contingent upon an external supply of this amino acid.

The universal necessity of lysine in animals reinforces the robustness of this strategy, as the evolutionary pressure to bypass such a deeply rooted biochemical constraint is significant. However, because many microorganisms possess the innate ability to synthesize lysine, effective biocontainment requires the knockout of redundant pathways and the implementation of multi-layered genetic safeguards. Thus, the lysine contingency is most effective when integrated into a broader, polygenic containment architecture rather than acting as a singular point of failure.

Week 2 - DNA Read, Write and Edit HM

Part 1: Benchling & In-silico Gel Art

By reordering restriction digest lanes of Lambda DNA, I created a symmetrical gel pattern resembling a butterfly!

Part 2: Gel Art - Restriction Digests and Gel Electrophoresis

Unfortunately No Lab Access

Part 3: DNA Design Challenge

3.1 Chosen Protein: GFP

I chose Green Fluorescent Protein (GFP) because it is widely used as a reporter protein in molecular biology. Since MELiSSA involves plasmid-based control systems and monitoring metabolic states, GFP represents a practical and symbolic example of how biological systems can be visually tracked in real time. GFP was originally isolated from Aequorea victoria and is commonly used as a fluorescent marker in genetic engineering experiments. Using UniProt, I obtained the amino acid sequence for GFP (UniProt ID: P42212).

Amino Acid Sequence: >sp|P42212|GFP_AEQVI Green fluorescent protein OS=Aequorea victoria MSKGEELFTGVVPILVELDGDVNGHKFSVSGEGEGDATYGKLTLKFICTTGKLPVPWPTLVTT LSYGVQCFSRYPDHMKQHDFFKSAMPEGYVQERTIFFKDDGNYKTRAEVKFEGDTLVNRIELK GTDFKEDGNILGHKLEYNYNSHNVYIMADKQKNGIKVNFKIRHNIEDGSVQLADHYQQNTPIG DGPVLLPDNHYLSTQSALSKDPNEKRDHMVLLEFVTAAGITHGMDELYK

3.2 Using an online reverse translation tool, I converted the GFP amino acid sequence into a possible coding DNA sequence. Because of codon degeneracy, multiple DNA sequences can encode the same protein. The sequence below represents one possible nucleotide sequence using standard codon usage.

One possible nucleotide sequence: ATGAGCAAAGGTGAAGAACTGTTTACCGGTGTTGTCCCAATTCTGGTTGAATTGGGTGATGGT AATGGTCATAAATTTTCTGTCTCTGGCGGAGAAGGTGATGCTACCTATAAGCTGACACTGAAA TTTATTTGCACCACTGGAAAATTGCCAGTTCCATGGCCAACACTGGTTACTACTCTGTCTTAT GGTGTTCAGTGCTTCTCTCGCTACCCAGATCATATGAAACATGATTTTTTTAAATCTGCCATG CCAGAGGGTTATGTTCAGGAGCGTACTATTTTTAAAGATGATGGTAATTATAAAACACGTGCT GAAGTCAAATTTGAAGGTGATACACTGGTAAATCGCATTGAGCTGAAAGGTACCGACTTTAAG GAAGATGGTAATATTCTGGGTCATAAACTGGAATACAATTATAACTCTCATAATGTCTATATT ATGGCTGATAAACAGAAGAATGGTATTAAAGTTAATTTTAAAATTCGTCATAATATTGAAGAT GGTTCTGTTCAGCTGGCTGATCACTACCAGCAGAATACTCCAATTGGAGATGGTCCTGTTCTG CTGCCAGATAATCACTATCTGAGTACTCAGTCTGCTCTGTCTAAGGATCCAAATGAAAAGCGA GATCATATGGTTCTGCTGGAATTTGTTACTGCTGCAGGTATTACCCATGGTATGGATGAGCTG TATAAATAA

3.3 Codon optimization is important to improve protein development in the chosen host organism.

As we know, multiple DNA sequences can encode the same protein due to the degeneracy of the genetic code, but not all codons are used equally in all organisms. This is due to the abundance of tRNA pools. If a gene contains codons that are rare for the organism, translation may decrease leading to slower protein production or ribosome stalling. I optimized the codon sequence for Escherichia coli (E. coli) because it grows rapidly, it is inexpensive and has a fully sequenced and well-characterized genome. Optimizing the gene for E. coli ensures that the codons match the organism’s tRNA abundance, thereby maximizing expression efficiency.

3.4 Cell-Free Protein Expression (In Vitro)

In this method: The DNA template is added to a reaction mixture containing: RNA polymerase, ribosomes, tARNs, aminoacids, energy sources. Transcription and translation occur in a test tube without living cells. The protein is synthesized directly in vitro.

Advantages: Faster expression No need to maintain living cells Useful for toxic proteins More controllable environment

Limitations: Higher cost Typically lower yield than in vivo systems

How DNA Becomes A Protein? In both systems (cell- dependent or cell-free), the process follows the Central Dogma: DNA → mRNA → Protein 1)The DNA sequence is transcribed into messenger RNA (mRNA). 2)The ribosome reads the mRNA in codons (sets of three nucleotides). 3)Transfer RNAs (tRNAs) match each codon with the corresponding amino acid. 4)The amino acids are linked together to form a polypeptide chain in a specific site in the ribosome. 5)The polypeptide folds into a functional protein.

Part 4: Prepare a Twist DNA Synthesis Order

For this design, I prepared a linear expression cassette in Benchling containing: Constitutive promoter, ribosome Binding Site (RBS), start codon, codon-optimized GFP coding sequence, 6xHis tag, stop codon, T7 terminator

This cassette would be ordered as a clonal gene through Twist Bioscience. I would select a high-copy plasmid backbone such as pTwist Amp High Copy, which provides: Ampicillin resistance for selection, high-copy origin of replication and efficient propagation in E. coli

Ordering as a clonal gene would allow direct transformation into E. coli without additional cloning steps, accelerating experimental validation.

Part 5: DNA Read/Write/Edit

5.1 DNA READ

(i) What DNA would you want to sequence and why? I would like to sequence environmental microbial DNA from closed ecological life-support systems, such as bioreactors used in regenerative environments (similar to MELiSSA-type systems). Specifically, I would sequence microbial community DNA to monitor biodiversity, metabolic stability, and potential pathogenic shifts. (ii) What sequencing technology would you use and why? I would use a combination of:

• Illumina sequencing • Oxford Nanopore sequencing

Illumina provides high accuracy short reads, ideal for detecting small mutations and precise taxonomic profiling. Oxford Nanopore provides long reads, which are useful for assembling genomes, detecting structural variants, and monitoring plasmids or gene clusters. Using both increases robustness and ecological insight.

Preparation (Essential Steps)

1. DNA extraction from environmental sample
2. Fragmentation (if needed for Illumina)
3. Adapter ligation
4. PCR amplification (Illumina)
5. Library preparation
6. Loading onto flow cell In closed systems, small microbial imbalances can lead to system instability or health risks. Sequencing allows early detection of contamination, horizontal gene transfer, or harmful mutations. Therefore, DNA sequencing becomes a tool for real-time biosurveillance and ecological control.

Essential Steps of Sequencing Technology -Illumina (Second-generation)

• DNA fragments attach to flow cell • Bridge amplification creates clusters • Sequencing-by-synthesis with fluorescent reversible terminators • Camera detects fluorescence • Base calling via signal interpretation Output: Short reads (FASTQ files with quality scores)

-Oxford Nanopore (Third-generation) • DNA passes through nanopore • Changes in ionic current measured • Signal processed into nucleotide sequence

Output: Long reads (FASTQ, real-time data)

5.2 DNA WRITE

(i) What DNA would you want to synthesize and why? I would synthesize a plasmid-based genetic circuit encoding: • A fluorescent reporter (e.g., GFP) • A stress-responsive promoter • A regulatory element sensitive to metabolic imbalance The purpose would be to create a biosensor that detects environmental stress inside a microbial ecosystem and produces a measurable fluorescence output. This construct could function as an early warning system in closed bioreactors.

(ii) What technology or technologies would you use to perform this DNA synthesis and why? I would use commercial gene synthesis through Twist Bioscience Why? • High accuracy • Scalable synthesis • Codon optimization • Assembly-ready fragments Essential Steps of DNA Synthesis

1. Digital DNA design
2. Oligonucleotide synthesis
3. Assembly (e.g., Gibson assembly)
4. Sequence verification
5. Plasmid construction

Limitations • GC-rich or repetitive sequences are difficult • Length constraints • Cost increases with size • Biosecurity screening restrictions

5.3 DNA Edit

(i) What DNA would you want to edit and why? I would edit the GFP gene expressed in E. coli to modify its fluorescence intensity. By introducing targeted mutations into the GFP coding sequence, it is possible to alter protein folding efficiency or chromophore structure, potentially enhancing fluorescence output. This modification would allow better signal detection and improved reporter performance in synthetic biology applications. (ii) I would use CRISPR-Cas9 genome editing CRISPR-Cas9 uses a guide RNA (gRNA) designed to match a specific DNA sequence within the GFP gene. The Cas9 enzyme introduces a double-strand break at that location. To introduce a precise modification, a donor DNA template containing the desired mutation would be supplied. The bacterial cell then repairs the break, incorporating the modified sequence. Essential inputs include: Guide RNA targeting GFP, Cas9 nuclease (plasmid or protein form), Donor DNA template containing the intended mutation and Competent E. coli cells

Limitations of this method include potential off-target effects, variable editing efficiency, and the need for downstream screening to confirm successful edits.

Note: This assignment was developed with the assistance of an AI language model (ChatGPT, Gemini), used to help structure ideas and refine wording. The concepts and final decisions were critically reviewed and adapted by the author.

Week 3 HW: Lab Atomation

Week 03 - Python Script for Opentrons Artwork

I was not able to write the code entirely by myself. The closest I got was generating concentric circles, wich reminded me of the Argentine “Escarapela” (with the help AI). My original idea, however, was to made an Argentine Mate which I did in https://opentrons-art.rcdonovan.com/ I also did a Cherry!

Cherry Pyhton Code: https://edit.htgaa.org/2026a-ariadna-abigail-ruiz-castro/webpages/src/branch/main/content/homework/Week-03-hw-Lab-Automation/Cherry%20OTDesign_02-24-26_21-05-54.py

Post-Lab Questions

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

Case Study: Automation in Drug Discovery Paper Title: Improving an Open-Sourced Automated Microplate Assay for our Drug Discovery Process Authors: M. Yunos Alizai, Brianna N. Davis, and Paul H. Davis (University of Nebraska at Omaha).

In order to discover new medicines (mainly against infections), scientifics must try hundreds of chemical compounds against different pathogens and cells. These assays are performed using manual microplate techniques, which are labor-intensive and highly susceptible to user-associated variations and human error, limiting the speed and the reliability of the drug discovery process. The solution? In this paper the authors developed an automated wide-spectrum screening assay utilizing the Opentrons liquid handling platform. The robot was programmed to automate the preparation of microplate assays, handling precise liquid transfers for: a-Compound Screening: Rapidly evaluating the effectiveness of various substances against specific pathogens. b-Cytotoxicity Testing: Measuring the impact of these compounds on host cell metabolism to determine potential toxicity. The significance of this study lies in the optimization of an open-source tool to achieve high-throughput screening (HTS) capabilities that were previously reserved for labs with much more expensive, proprietary equipment. Key achievements described in the paper include: -Scalability: The ability to process a significantly larger number of samples in a reduced timeframe. -Precision: A marked reduction in human-induced variability, leading to more reproducible data. -Feasibility: Proving that open-source automation is a robust and viable tool for complex clinical applications in combating infections

Write a description about what you intend to do with automation tools for your final project. You may include example pseudocode, Python scripts, 3D printed holders, a plan for how to use Ginkgo Nebula, and more. You may reference this week’s recitation slide deck for lab automation details

Final Project Proposal: Plasmid-Based Autonomous Control Loops for the MELiSSA Ecosystem The goal of this project is to implement an autonomous biological regulation system within the MELiSSA (Micro-Ecological Life Support System Alternative) framework. By engineering specific plasmids to act as “genetic controllers,” we can regulate metabolic flux and resource production in response to environmental fluctuations (such as CO2 levels or nutrient concentration). This ensures the stability of the artificial ecosystem during long-term space missions. A central component of this project is the use of GFP (Green Fluorescent Protein) as a reporter. The plasmids will be designed with sensor-promoter systems that trigger GFP expression when specific conditions are met (e.g., a stress-induced promoter). a) Real-time Monitoring: The fluorescence intensity will serve as a direct proxy for the “health” of a specific compartment (like the cyanobacteria loop). b) Feedback Loop: Automation tools will be used to measure this fluorescence. If the signal deviates from the setpoint, the system can automatically trigger a corrective action, such as adjusting the flow of nutrients or light intensity.

Automation Tools

The complexity of characterizing these genetic circuits requires high-throughput automation: a) Opentrons Platform: The OT-2 will be utilized to automate the DNA Assembly (Golden Gate or Gibson Assembly) of the plasmid variants. It will also handle the transformation protocols, ensuring high reproducibility when inserting these controllers into the target microbial strains. b) Custom 3D-Printed Hardware: To bridge the gap between automation and biology, I will design and 3D-print custom modular tube holders and adapters. These will allow the Opentrons to interface directly with specialized bioreactor sampling tubes, maintaining the required thermal conditions for sensitive enzymes and reagents. c) Ginkgo Nebula Integration: For large-scale characterization, Ginkgo Nebula will be used to test the plasmids under a vast array of simulated space environments. This high-throughput data will allow for the fine-tuning of the genetic “gain” and “sensitivity” of the controllers before they are deployed in a physical MELiSSA prototype. By replacing electronic sensors with biological ones (plasmids + GFP), we reduce the reliance on external hardware that can fail in deep space. This “living” control system makes the MELiSSA loop more resilient, self-healing, and inherently integrated into the biological processes it aims to sustain.