Week 3 – Homework: Lab automation

Week 2 – Homework: DNA Read, Write, & Edit

Watercolor and then photoshopped image of the abstract architectural facade.

Part 1: Benchling & In-silico Gel Art

Create a pattern/image in the style of Paul Vanouse’s Latent Figure Protocol artworks.

For the gel art design, I arranged different restriction enzyme digests of Lambda DNA to create an abstract architectural façade. By combining single and triple digests, I created variations in band density and spacing that resemble structural columns, central voids, and layered material systems.

I also experimented with arranging digest patterns to form a heart-like shape, using band density and symmetry to create a subtle organic silhouette within the gel layout. However, it looks a bit wonky …

Part 3: DNA Design Challenge

3.1. Choose your protein.

I chose Cyanoexosortase B (CrtB) from Nostoc commune. This protein is involved in extracellular protein processing and surface-associated systems in cyanobacteria. Because Nostoc forms protective biofilms and extracellular matrices, CrtB plays a role in how the organism organises and stabilises its external environment. I am interested in how genetic information translates into material behaviour at environmental interfaces, so this protein connects molecular design to structural and ecological function. The amino acid sequence was obtained from UniProt (A0ABN6PZL9).

Image source: Benchling

3.2. Reverse Translate: Protein (amino acid) sequence to DNA (nucleotide) sequence.

For this exercise, I used the “EMBOSS BACKTRANSEQ” tool from www.ebi.ac.uk.

To reverse translate my protein, I used an online reverse translation tool. Since each amino acid is coded by three DNA bases (a codon), the tool converts the amino acid sequence back into a possible DNA sequence. Because multiple codons can code for the same amino acid, there isn’t only one correct DNA sequence. The tool selects codons based on the organism chosen and generates a DNA sequence that could realistically produce my protein.

ATGGTTTTACAACAACAAATTAAAAATCGTAATGCTTCTGGTTTATTAAATTTAGCTATTTTAGGTGTTTTATTATTATTATATGCTCCAATTTTATTACATTGGTTAGATGGTTGGTTATATAAAAATATTTCTACTGAACATGAATATTTTTCTCATGGTATTATTGGTTTACCATTTGCTGCTTATTTAGGTTGGATGAATCGTAAAAAATGGAAACGTTTACCAGATAATATTCATCCATTAGGTGCTGTTTTTTTATTATTAGGTGCTGTTTTTTATTTATCTGGTGTTACTGAATGGGTTAATTTATCTTTACCAGTTATTTTAGTTGGTTTATGTTTATGGTTTAAAGGTATTTCTGGTTTACGTTCTCAAGGTTTTCCATTATTATTAGTTTTTTTAGCTACTCCAACTGCTTTACCATATTTAATTGCTCCATATACTTTACCATTACAATCTTTTATTGCTGGTACTGCTGGTTTTATTTTAAATCAATTTGGTATGGAAGTTACTGTTGATGAAATTAATTTATATGTTGGTGGTCGTATTGTTGAAGTTGCTCCATATTGTGCTGGTTTAAAAATGTTATTTCTACTTTATATGTTGGTTTAATGTTATTATATTGGACTGATGCTTTATCTTCTCGTCGTACTGTTATTTCTTTTTTTCTTTAGCTGCTATTGTTTCTATTATTGCTAATATTATTCGTAATACTTTATTAACTTTTTTTCATGGTACTGGTCAAGAAGCTGCTTTTAAATGGTTACATGATGGTTGGGGTGGTGATGTTTATTCTGCTTGTATGTTAGTTTCTTTAGTTCCATTATTAAATGGTATTAATTCTTATTTTTCTGCTTCTTTAGAAACTGAACAAGAAGGTGAATCT

3.3. Codon optimization.

I used the “Codon Optimization Tool” from eu.idtdna.com for this exercise and a custom organism table from www.kazusa.or.jp (Nostoc commune DRH1).

Codon optimisation is needed because different organisms prefer different DNA codons for the same amino acids. Even though multiple codons can code for the same amino acid, some are used more often in certain species. If the DNA sequence uses codons that are rare in the host organism, the protein may not be made efficiently. I optimised my sequence for Nostoc commune so that the codons better match what this bacterium naturally prefers, which should help improve protein expression.

ATGGTTTTGCAACAACAAATCAAGAACCGCAATGCTTCTGGTTTACTTAATTTAGCGATTCTAGGAGTTCTATTACTACTATATGCGCCTATTTTGCTTCATTGGTTGGATGGTTGGCTATATAAGAATATTTCCACAGAACACGAATACTTTAGTCACGGCATTATCGGTCTACCATTTGCGGCGTATCTTGGATGGATGAATCGTAAAAAATGGAAGCGCCTGCCCGATAATATCCACCCTCTGGGAGCGGTTTTTTTACTGTTAGGAGCTGTATTCTATCTTTCTGGTGTTACTGAATGGGTCAATCTTAGTCTGCCGGTCATCTTAGTTGGTTTGTGCCTGTGGTTCAAGGGTATTTCTGGTTTGCGATCTCAAGGTTTTCCTCTGCTATTGGTATTTTTGGCAACTCCAACTGCCTTGCCTTACCTGATCGCACCATACACATTGCCCTTACAATCTTTCATTGCAGGTACTGCGGGTTTTATCTTAAACCAATTCGGCATGGAAGTTACCGTCGATGAAATTAACCTATATGTTGGTGGTAGAATTGTGGAAGTAGCGCCATACTGTGCAGGTTTGAAAATGTTGTTCACTACATTATATGTGGGCCTTATGCTGCTATACTGGACAGACGCTCTGTCTTCTAGACGTACTGTCATTTCTTTTCTTTCCCTAGCTGCAATTGTATCTATTATTGCCAATATTATCCGTAACACTCTGTTGACCTTTTTCCACGGCACTGGTCAAGAAGCTGCGTTTAAATGGTTACATGATGGATGGGGTGGTGACGTGTACTCAGCTTGTATGTTAGTCTCATTGGTGCCATTACTGAACGGTATTAATTCTTACTTTTCAGCAAGTCTTGAAACAGAGCAAGAAGGTGAATCT

The following restriction enzyme sites have been found in the selected reading frame: AseI (ATTAAT) BbsI (GAAGAC) DraI (TTTAAA) MfeI (CAATTG) SspI (AATATT) XbaI (TCTAGA)

3.4. You have a sequence! Now what?

After designing and codon-optimising the DNA sequence, the gene could first be chemically synthesised using modern DNA synthesis technologies. The synthesised gene would then be assembled into a plasmid vector containing a promoter, ribosome-binding site, and terminator. This plasmid could be introduced into Nostoc commune using standard transformation techniques. Inside the cell, RNA polymerase transcribes the DNA into mRNA, and ribosomes translate the mRNA into Cyanoexosortase B according to the genetic code.

Alternatively, the DNA could be used in a cell-free transcription–translation system, where purified molecular machinery produces the protein outside of living cells. Both approaches rely on the same central dogma process: DNA is transcribed into RNA, and RNA is translated into protein.

Part 5: DNA Read/Write/Edit

5.1 DNA Read

(i) What DNA would you want to sequence (e.g., read) and why?

I would like to sequence environmental DNA from biological soil crusts, with a focus on Nostoc commune and related cyanobacteria. The goal would be to identify genes involved in extracellular matrix production, stress tolerance, and surface adhesion. This would allow me to better understand which genetic pathways contribute to soil stabilisation and how microbial community composition changes under environmental stress.

(ii) In the lecture, a variety of sequencing technologies were mentioned. What technology or technologies would you use to perform sequencing on your DNA, and why?

To sequence environmental DNA from biological soil crust samples, I would use Illumina sequencing, potentially combined with Oxford Nanopore sequencing. Illumina provides high accuracy and depth for microbial community profiling, while Nanopore offers long reads that help resolve full-length genes and structural variation.

Illumina is a second-generation (next-generation) sequencing technology. It performs massively parallel sequencing of short DNA fragments, enabling the simultaneous reading of millions of sequences. Oxford Nanopore is considered a third-generation sequencing technology, as it sequences single DNA molecules in real-time without the need for amplification.

The input for Illumina sequencing would be environmental DNA extracted from soil crust samples. The DNA is prepared by adding sequencing adapters and amplifying the fragments to create a sequencing library. During sequencing, the DNA binds to a flow cell and is copied while fluorescently labelled nucleotides are incorporated one base at a time. Each incorporated base is detected by its fluorescence signal and converted into a nucleotide sequence. The output consists of millions of short DNA reads that can be analysed to identify genes and microbial composition.

5.2 DNA Write

(i) What DNA would you want to synthesize (e.g., write) and why?

I would synthesise a codon-optimised version of the Cyanoexosortase B (CrtB) gene from Nostoc commune. The goal would be to study and potentially enhance extracellular matrix organisation in cyanobacteria, which is relevant to soil stabilisation and biofilm formation.

(ii) What technology or technologies would you use to perform this DNA synthesis, and why?

To synthesise the CrtB gene, I would use phosphoramidite-based oligonucleotide synthesis, followed by gene assembly.

The essential steps include stepwise chemical addition of protected nucleotides to build short oligonucleotides on a solid support, cleavage and deprotection, purification, and assembly of overlapping oligos into a full-length gene using PCR-based methods. The assembled gene can then be sequence-verified before use.

The main limitations of this method are synthesis errors that accumulate with increasing length, practical limits on direct synthesis length (typically ~200 nt per oligo), and the need for assembly and error correction for longer constructs. Although scalable and highly automated, accuracy and yield decrease as sequence length increases.

References:

Beaucage, S.L. and Caruthers, M.H., 1981. Deoxynucleoside phosphoramidites—A new class of key intermediates for deoxypolynucleotide synthesis. Tetrahedron Letters, 22(20), pp.1859–1862.

Gibson, D.G., Young, L., Chuang, R.-Y., Venter, J.C., Hutchison, C.A. and Smith, H.O., 2009. Enzymatic assembly of DNA molecules up to several hundred kilobases. Nature Methods, 6, pp.343–345.

Kosuri, S. and Church, G.M., 2014. Large-scale de novo DNA synthesis: Technologies and applications. Nature Methods, 11(5), pp.499–507.

LeProust, E.M., Peck, B.J., Spirin, K., McCuen, H.B., Moore, B., Namsaraev, E. and Caruthers, M.H., 2010. Synthesis of high-quality libraries of long (150-mer) oligonucleotides by a novel depurination-controlled process. Nucleic Acids Research, 38(8), pp.2522–2540.

5.3 DNA Edit

(i) What DNA would you want to edit and why?

I would focus on editing regulatory regions of genes involved in extracellular matrix production in Nostoc commune, rather than altering core metabolic pathways. For example, modifying promoter regions could allow increased or more controlled expression of genes associated with surface adhesion or polysaccharide production. The goal would be to fine-tune existing biological functions rather than introduce foreign traits, maintaining ecological compatibility.

(ii) What technology or technologies would you use to perform these DNA edits, and why?

I would use CRISPR-Cas9 to edit regulatory regions of the Nostoc commune genome. CRISPR-Cas9 uses a guide RNA to direct the Cas9 nuclease to a specific DNA sequence, where it introduces a double-strand break. The cell then repairs the break either through non-homologous end joining, which can introduce small mutations, or through homology-directed repair if a donor template is supplied.

The preparation includes designing a guide RNA targeting the promoter region, constructing a plasmid carrying Cas9 and the guide RNA, and introducing it into the host cells. If precise edits are required, a repair template DNA is also provided.

Limitations include variable editing efficiency, dependence on cellular repair pathways, and potential off-target effects where unintended DNA regions may be modified.

References:

Cong, L. et al., 2013. Multiplex genome engineering using CRISPR/Cas systems. Science, 339(6121), pp.819–823.

Jinek, M. et al., 2012. A programmable dual-RNA–guided DNA endonuclease in adaptive bacterial immunity. Science, 337(6096), pp.816–821.

Doudna, J.A. and Charpentier, E., 2014. The new frontier of genome engineering with CRISPR-Cas9. Science, 346(6213), 1258096.

Week 1 – Homework: Principles and Practices

1. Biological Engineering Application or Tool

I want to develop a site-attuned microbial engineering approach to accelerate the formation of biological soil crusts (biocrusts) in erosion-prone or degraded soils, to reduce topsoil loss and support early plant establishment. The core biological intervention is a minimal, targeted enhancement of extracellular polymeric substance (EPS) production within site-derived or ecologically matched microbial consortia.

BSCs play a critical role in stabilising soil surfaces, binding particles, retaining moisture at the microscale, and creating conditions that allow plants to establish. However, in many degraded environments, natural biocrust formation is slow and fragile, leaving soils vulnerable to wind and water erosion. Over the past year, I have explored material and process-based strategies (such as surface carriers, textures, and hydration regimes) to support crust formation, but these approaches have shown limited and inconsistent success. This suggests that a key bottleneck lies in the rate and robustness of microbial aggregation, rather than the absence of microbes or materials themselves.

EPS is central to soil particle aggregation and early crust cohesion. By modestly increasing EPS production in microbial consortia that are native to, or in this case, well-matched with a given site, this project aims to accelerate an existing ecological function rather than introduce a new one. Genetic modification is therefore used not to create novel traits or new ecological roles, but to tune a single, well-understood mechanism that directly contributes to soil stability.

The application is designed to fit within a circular economy framework, using biodegradable carriers and locally appropriate inputs that safely reintegrate into the soil system. Ultimately, the goal is to develop a tool that improves soil resilience and plant establishment while remaining environmentally compatible, reversible, and ethically governable.

2. Governance and Policy Goals

Goal 1: Non-malfeasance and prevention of harm

Ensure that the system does not cause unintended biological, ecological, or social harm.

1.1 Prevent biological misuse or diversion

Ensure that organisms, genetic constructs, and protocols cannot be easily repurposed for harmful or unintended applications.

1.2 Minimise accidental harm

Reduce risks associated with lab work, handling, transport, and early deployment through clear safety practices, documentation, and incident reporting norms.

Goal 2: Environmental protection and ecological integrity

Ensure that the intervention supports soil function without destabilising local ecosystems or creating irreversible environmental effects.

2.1 Preserve existing ecological roles

Ensure that genetic modification enhances an existing microbial function (EPS production for aggregation) rather than introducing new ecological roles or behaviours.

2.2 Constrain spatial and temporal impact

Limit how long and how far the modified microbes can exert their enhanced function, reducing the risk of unintended persistence or spread beyond the target site.

2.3 Detect and respond to unintended effects

Establish monitoring and response mechanisms to identify ecological changes early and enable corrective action or remediation if adverse effects emerge.

Goal 3: Proportionate and justified use of genetic modification

Ensure that synthetic biology is applied only where necessary, at an appropriate level of intervention, and with explicit recognition of its added ethical and governance burden.

3.1 Necessity-based justification

Require clear evidence that genetic modification is addressing a specific, well-defined functional limitation (e.g., insufficient EPS-mediated aggregation) that cannot be adequately resolved through non-genetic approaches alone.

3.2 Scope and intensity limitation

Constrain genetic modification to the minimum effective change, focused on a single functional trait, and avoid escalating intervention complexity without renewed justification.

3.3 Ongoing re-evaluation

Periodically reassess whether genetic modification remains justified as materials, ecological understanding, or any alternative methods improve, rather than treating engineering choices as permanent.

Goal 4: Accountability, transparency, and institutional responsibility

Ensure that responsibility for the development and deployment of the system is clearly assigned, traceable, and sustained over time, rather than diffused across actors or stages of work.

4.1 Clear attribution of responsibility

Define who is responsible for organism sourcing, genetic modification decisions, deployment oversight, and post-deployment monitoring at each stage of the project’s LC.

4.2 Documentation and traceability

Maintain accessible records of design decisions, genetic modifications, deployment contexts, and monitoring plans so actions and outcomes can be reconstructed if concerns arise.

4.3 Knowledge stewardship

Ensure that insights gained from development and deployment, including negative or inconclusive results, are preserved and shared in ways that support collective learning rather than isolated success narratives.

Goal 5: Equity, autonomy, and fair distribution of benefits and risks

Ensure that decisions about development and deployment respect local agency and that the benefits and risks of technology are not unfairly distributed.

5.1 Local decision-making authority

Ensure that land stewards and affected communities have meaningful influence over whether, where, and how the system is tested or deployed, rather than being treated solely as sites of experimentation.

5.2 Fair allocation of risk and benefit

Avoid situations in which environmental or social risks are borne locally while scientific, economic, or reputational benefits accrue primarily to external actors.

5.3 Accessibility and non-exclusivity

Design governance and deployment pathways that do not restrict participation or benefit to well-resourced institutions, regions, or communities.

3. Governance Actions

To support the ethical development and potential deployment of an EPS-enhanced, site-derived microbial system, I propose three complementary governance actions. Together, these combine design constraints, regulatory staging, and incentive-based oversight and involve different actors across the research, deployment, and accountability landscape.

Option 1. Safety-by-design requirement for environmental synthetic biology

Purpose

Environmental synthetic biology often relies on general biosafety frameworks not tailored to open ecosystems. This action introduces a formal safety-by-design requirement that explicitly constrains the use of genetic modification in soil-interacting systems.

Design

Actors: Researchers, university biosafety committees, funders, and journals.

Mechanisms:

• Explicit definition of organism provenance (site-derived or ecologically matched).
• Limitation of genetic modification to a single functional enhancement (EPS production).
• Exclusion of traits linked to persistence, dispersal, or competitive dominance.
• Risk assessments and stop/go decision points before field exposure.

Analogy: Privacy-by-design or chemical safety-by-design frameworks.

Assumptions

Early design constraints reduce downstream risk and are adopted when tied to funding and publication norms.

Risk of failure and success

Failure: Box-ticking compliance with weak enforcement.
Success risk: Compliance burden disadvantages smaller research groups.

Option 2. Tiered field testing and deployment pathway

(Regulatory staging; regulators and local governance)

Purpose

Transitions from lab to environment are currently inconsistent. This action introduces a tiered pathway where oversight scales with ecological exposure and deployment size.

Design

Actors: Environmental regulators, land managers, research institutions.

Mechanisms:

• Defined tiers (lab, contained trials, small pilots, scaled deployment).
• Clear progression criteria based on monitoring data.
• Pre-defined rollback or halt conditions.
• Local stakeholder engagement for open-environment pilots.

Analogy: Phased clinical trials or drone flight regulation.

Assumptions

Regulators have sufficient capacity, and researchers will not bypass formal pathways.

Risk of failure and success

Failure: Delays lead to work being pushed into informal channels.
Success risk: Overly rigid processes slow low-risk research.

Option 3. Traceability and post-deployment monitoring incentives

(Incentive-based governance; funders, journals, institutions)

Purpose

Accountability often weakens after laboratory development. This action extends responsibility into real-world contexts through traceability and monitoring incentives.

Design

Actors: Funders, journals, universities, standards bodies.

Mechanisms:

• A lightweight registry for environmental pilots above a defined scale.
• Mandatory monitoring plans tied to funding or approval.
• Incentives for transparent reporting, including negative or inconclusive results.

Analogy: Post-market surveillance in medical devices or financial reporting requirements.

Assumptions

Incentives can encourage compliance without heavy enforcement.

Risks of failure and success

Failure: Low participation or superficial monitoring.
Success risk: Administrative complexity favours large institutions.

4. Scoring

Rationale (brief):

• Option 1 scores strongest for prevention (especially lab safety) by constraining design early.
• Option 2 scores strongest for environmental prevention but weakest on burden and research friction.
• Option 3 scores strongest for response and learning, but less so for prevention.

5. Prioritisation

Based on the scoring, I would prioritise Option 1 (safety-by-design requirements) and Option 3 (traceability and post-deployment monitoring incentives), with Option 2 (tiered field testing) applied only to higher-risk or larger-scale deployments. Constraining genetic modification at the design stage is the most effective way to prevent harm, while traceability and monitoring ensure accountability and learning once systems interact with real environments. Although tiered regulatory pathways are important as ecological exposure increases, applying them universally would risk slowing low-risk research. This approach balances innovation with restraint and is best implemented by MIT research leadership and funding bodies through grant conditions and review processes, while acknowledging ongoing uncertainty around long-term ecological effects.

Week 1 Lab: Pipetting

Individual Final Project

Group Final Project