Biological engineering application: PGPR Agriculture in northern climates, such as Canada, faces structural biological constraints, particularly short and unpredictable growing seasons, cold soil temperatures in early spring, and variable nutrient availability. These constraints limit crop maturation time and increase vulnerability to climate change.
I propose developing an engineered plant growth-promoting rhizobacterium (PGPR) to enhance early-stage plant growth, nutrient uptake, and cold-stress resilience. The literature has recognized the effectiveness of PGPR in improving the growth and quality of certain crops and plants (Singh et al, 2023; Zhang et al, 2024). However, the theories have not been applied to improving the early developmental rate in cold climates. Therefore, I believe this biological engineering approach not only leverages rhizosphere ecology but also aligns agricultural productivity and ecological systems thinking.
Part 1: Benchling & In-silico Gel Art
Enzymes Cuts Temp. 1.1 2.1 3.1 4/CS
BamHI 5 37°C 75* 100* 100 100*
EcoRI 5 37°C 25 100* 50 50*
EcoRV 21 37°C 10 50 100 10
HindIII 7 37°C 25 100 50 50
KpnI 2 — Not available for this vendor
SacI 2 — Not available for this vendor
SacII 4 37°C 10 100 10 100
I have difficulty creating a pattern/image in the style of Paul Vanouse’s Latent Figure Protocol artworks. I will use this image as a placeholder for now. Sorry about that.
Week 1 HW: Engineering a Soil Microbe to Support Short-Season Agriculture in Canada
Biological engineering application: PGPR
Agriculture in northern climates, such as Canada, faces structural biological constraints, particularly short and unpredictable growing seasons, cold soil temperatures in early spring, and variable nutrient availability. These constraints limit crop maturation time and increase vulnerability to climate change.
I propose developing an engineered plant growth-promoting rhizobacterium (PGPR) to enhance early-stage plant growth, nutrient uptake, and cold-stress resilience. The literature has recognized the effectiveness of PGPR in improving the growth and quality of certain crops and plants (Singh et al, 2023; Zhang et al, 2024). However, the theories have not been applied to improving the early developmental rate in cold climates. Therefore, I believe this biological engineering approach not only leverages rhizosphere ecology but also aligns agricultural productivity and ecological systems thinking.
Policy goal: Climate Adaptation Equity
To reduce vulnerability and enhance resilience, applying PGPR to crops in harsh climates can help promote agriculture for all Canadians. In particular, Northern, small-scale, and Indigenous agricultural communities face a harsher climate environment, are more vulnerable to climate change, and have fewer resources than industrial agriculture. Therefore, the development of an engineered PGPR can promote equity if the application is cost-effective, easy to adopt, and accounts for geographic, economic, and climatic realities.
Potential governance actions
a. Technical considerations
PGPR has been proposed to be useful in certain climates, but it cannot be assumed that it will be useful in Canada, given the harsh climate. Moreover, soil composition is a complex science that can change the technical and resource requirements for northern communities. Therefore, academic researchers and scientists need to apply current understanding and practices regarding PGPR to Canadian realities and tailor these potential solutions accordingly. To facilitate research, grants should target PGPR-focused research though Natural Sciences and Engineering Research Council of Canada. The risk is that PGPR is not a good fit for Canada due to the low return relative to cost; however, understanding failure is in itself a success, as it prevents further funding or widespread application and ensures that lessons are learned. The US government has an existing 5-year study through the National Institute of Food and Agriculture Annual in 2021. The project concludes this year, and the methodology, findings, and risks can be referenced by Canadian researchers.
b. Community and Indigenous co-governance mechanisms
Formal consultation and co-design frameworks should be established while funding PGPR-focused research. Indigenous agricultural knowledge and perspectives can provide valuable insights that no laboratory can produce. Moreover, respecting soil stewardship and intergenerational responsibility aligns with both ethical guidance and legal obligations. To facilitate this, the federal government, especially the Crown-Indigenous Relations and Northern Affairs Canada, should take the lead. The risk that the Indigenous communities do not support PGPR exists, which will result in the loss of a major market in Canada. However, success is reflected in understanding of the user base, respect for Indigenous communities, adherence to the principle of inclusion, and valuable knowledge on both the scientific and political dimensions.
c. National biosafety standard update
The current edition of the Canadian BiosafetyStandard was published in 2022. Microbe-related mentions are primarily about toxins and laboratory practices. There is no standard for assessing the safety of larger ecosystems for PGPR and potential ecosystem implications. Given that we are now in 2026 in the AI era, the standard is due for an update to consider ecological risk modelling, mandatory post-release surveillance, and data transparency requirements. National regulatory bodies, such as the Canadian Food Inspection Agency, should lead the revision of the standard to include an expanded scope. The risk is that the standard update proceeds slowly and may not apply to PGPR if it is scientifically sound and a wide application becomes feasible. However, regardless of what PGPR can or cannot do, the biosafety standard is due for an update, and such an update would be successful if its scope were expanded to meet current economic and environmental needs.
Score (from 1-3 with, 1 as the best, or n/a) each of your governance actions
Does the option:
Option 1
Option 2
Option 3
Enhance Biosecurity
• By preventing incidents
3
2
1
• By helping respond
1
2
3
Foster Lab Safety
• By preventing incident
2
3
1
• By helping respond
3
2
1
Protect the environment
• By preventing incidents
1
2
3
• By helping respond
1
3
2
Other considerations
• Minimizing costs and burdens to stakeholders
1
2
3
• Feasibility?
2
1
3
• Not impede research
1
2
3
• Promote constructive applications
2
1
3
Combination of options
The three governance options have distinguished focuses on research, collaboration, and policy. A scientific innovation needs a holistic governance structure to ensure its scientific feasibility and credibility, respect for diverse knowledge and legal obligation, and policy alignment to ensure safety. Therefore, I believe all three options should be incorporated without prioritizing. The biggest trade-off is the need and the time invested. No scientific innovation and testing can happen overnight, but uncertainties about theories and feasibility may lead stakeholders to question whether investments are worth the uncertain returns, while many innovative ideas do not require long waits for research on feasibility and can deliver immediate returns. This is misleading, as immediate implementation does not guarantee immediate returns, and understanding the science and technology is essential, even if it takes time. Therefore, the main audience for this approach is the Canadian federal government, which invests in research, understands wait times, leads engagement, and updates standards. Given that the result can potentially benefit the national interest of Canada, especially in today’s trade environment,
I have difficulty creating a pattern/image in the style of Paul Vanouse’s Latent Figure Protocol artworks. I will use this image as a placeholder for now. Sorry about that.
Part 3: DNA Design Challenge
3.1. Choose your protein.
I chose the cold shock protein CspA from Bacillus subtilis because it plays a role in cellular adaptation to low temperatures. Since my Week 1 homework focused on enhancing crop growth in short-season Canadian climates, selecting a protein involved in cold resilience aligns conceptually with my broader engineering interests.
I obtained the following protein sequence from Uniprot under the protein name Cold shock protein CspC, gene name cspC, BSU0520, CSPC_BACSU, P39158.
3.2. Reverse Translate: Protein (amino acid) sequence to DNA (nucleotide) sequence.
One result from Bioinformatics.org shows
reverse translation of sp|P39158|CSPC_BACSU Cold shock protein CspC OS=Bacillus subtilis (strain 168) OX=224308 GN=cspC PE=1 SV=1 to a 198 base sequence of most likely codons.
Codon optimization is necessary because different organisms preferentially use specific codons to encode the same amino acid. Although the genetic code is universal, codon usage bias affects translation efficiency and protein yield. I optimized the Bacillus subtilis expression sequence to improve expression efficiency in a soil bacterium relevant to my project proposed in Week 1 homework. The selection of Bacillus subtilis used help from GenAI. The tool is IDT Codon Optimization Tool https://www.idtdna.com/CodonOpt. The product type is gBlocks Gene Fragments. Restriction sites to avoid are Bsal, BsmBL, and Bbsl.
I will explore the cell-free method, as it does not require living organisms, so that the system can be more controlled. In this way, cell-free expression systems could synthesize the protein directly from the DNA template without using living cells.
I will have to revisit this part, once I go through the lecture again. Currently, the answers have relied heavily on Google and GenAI.
5.1 DNA Read
(i) What DNA would you want to sequence and why?
I would want to sequence DNA used in DNA-based digital data storage, which was used in the homework example. This would allow verification of synthesis accuracy, detection of errors introduced during storage or replication, and complete recovery of the original encoded information.
(ii) In lecture, a variety of sequencing technologies were mentioned. What technology or technologies would you use to perform sequencing on your DNA and why?
(I sought help from ChatGPT to answer this question.)
Illumina Sequencing by Synthesis (SBS) due to the parallel sequencing of fragment libraries and accuracy.
Also answer the following questions:
Is your method first-, second- or third-generation or other? How so?
Second-generation due to the generated short reads.
What is your input? How do you prepare your input (e.g. fragmentation, adapter ligation, PCR)? List the essential steps.
DNA molecules (synthetic oligo libraries) as input, adapter ligation to both ends, and PCR to create clusters.
What are the essential steps of your chosen sequencing technology, how does it decode the bases of your DNA sample (base calling)?
DNA fragments bind to a flow cell and form clusters by bridge amplification.
What is the output of your chosen sequencing technology?
FASTQ files with short reads.
5.2 DNA Write
(i) What DNA would you want to synthesize (e.g., write) and why?
I would synthesize DNA constructs encoding digitally compressed cultural content because it enables long-term digital archiving.
(ii) What technology or technologies would you use to perform this DNA synthesis and why? Also answer the following questions:
I would use chip-based solid-phase oligonucleotide synthesis, such as the platforms developed by Twist Bioscience and others. These use phosphoramidite chemistry in a massively parallel microarray format.
What are the essential steps of your chosen sequencing methods?
-A DNA chain, protected nucleotides, and deprotection and coupling cycles.
What are the limitations of your sequencing method (if any) in terms of speed, accuracy, scalability?
-error and length
5.3 DNA Edit
(i) What DNA would you want to edit and why?
I would like to continue my proposed project in Week 1 homework and add this week’s work on Bacillus subtilis.
(ii) What technology or technologies would you use to perform these DNA edits and why?
Also answer the following questions:
I would like to employ CRISPR-Cas9, as mentioned in Professor Church’s slide. It is a tool that is frequently mentioned in the lecture, and I wish to explore more.
How does your technology of choice edit DNA? What are the essential steps?
-CRISPR-Cas9 uses a short guide RNA (gRNA) to direct Cas9 to a specific DNA sequence. Once bound, Cas9 introduces a double-strand break at the target site.
What preparation do you need to do (e.g. design steps) and what is the input (e.g. DNA template, enzymes, plasmids, primers, guides, cells) for the editing?
-1) Guide RNA(s) targeting loci involved in repair or replication; 2) Cas9 or base/prime editor constructs; 3) Donor DNA templates for HDR when introducing specific sequences; and 4) Competent cells capable of taking up editing components
What are the limitations of your editing methods (if any) in terms of efficiency or precision?
-Unintended edits can occur at similar sequences.
Week 1 Homework: Lecture 2 Preparation:
Professor Jacobson’s lecture:
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?
The error rate is 1:100,000 or 1,000,000 throughput: 10mS per Base Addition (according to the slide and Google).
Human Genome Length: A single human diploid cell contains roughly 6 million base pairs. The discrepancy without correction, if the error rate were 100,000, every cell division would introduce roughly 100,000-600,000 errors. This is drawn from Google AI Overview.
One way biology deals with the discrepancy is intrinsic proofreading (3’-5’ exonuclease), according to Google.
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?
(Directly from Google search)
Different ways: synonymous codons, mathematical combinations, and redundant genetic code.
Reasons not working: condon usage bias, protein folding defects, mRNA stability and decay, mRNA structure, and transcriptional efficiency.
Dr. LeProust’s lecture:
What’s the most commonly used method for oligo synthesis currently?
Solid-phase phosphoramidite chemistry. (Google)
Why is it difficult to make oligos longer than 200nt via direct synthesis?
It is difficult because the product’s yield and purity decrease exponentially with each added base. (Google)
Why can’t you make a 2000bp gene via direct oligo synthesis?
This is because conventional automated phosphoramidite synthesis is limited by the efficiency of nucleotide coupling and error accumulation. (Google)
George Church’s lecture (choose one to answer):
(Using Google & Prof. Church’s slide #4) What are the 10 essential amino acids in all animals and how does this affect your view of the “Lysine Contingency”
The ten essential amino acids are Arginine, Histidine, Isoleucine, Leucine, Lysine, Methionine, Phenylalanine, Threonine, Tryptophan, and Valine. The effect is that humans may be able to control nature if they control these ten amino acids, which is not true. (Google)
Note: I apologize for heavily relying on Google, but I am struggling to understand the material by myself.
pass this e.g. ‘Red’ and get back a Location which can be passed to aspirate()
def location_of_color(color_string):
for well,color in well_colors.items():
if color.lower() == color_string.lower():
return color_plate[well]
raise ValueError(f"No well found with color {color_string}")
For this lab, instead of calling pipette.dispense(1, loc) use this: dispense_and_detach(pipette, 1, loc)
def dispense_and_detach(pipette, volume, location):
"""
Move laterally 5mm above the plate (to avoid smearing a drop); then drop down to the plate,
dispense, move back up 5mm to detach drop, and stay high to be ready for next lateral move.
5mm because a 4uL drop is 2mm diameter; and a 2deg tilt in the agar pour is >3mm difference across a plate.
"""
assert(isinstance(volume, (int, float)))
above_location = location.move(types.Point(z=location.point.z + 5)) # 5mm above
pipette.move_to(above_location) # Go to 5mm above the dispensing location
pipette.dispense(volume, location) # Go straight downwards and dispense
pipette.move_to(above_location) # Go straight up to detach drop and stay high
The art is published at opentrons-art.rcdonovan.com/?id=89w6rb219717q1z
The code is generated with the help of GenAI.
Post-Lab Questions:
Article:
Bryant, J. A., Kellinger, M., Longmire, C., Miller, R., & Wright, R. C. (2023). AssemblyTron: flexible automation of DNA assembly with Opentrons OT-2 lab robots. Synthetic Biology (Oxford University Press), 8(1), ysac032. https://doi.org/10.1093/synbio/ysac032
The article presents AssemblyTron, an open-source automation platform that enables flexible and programmable DNA assembly workflows using Opentrons OT-2 liquid-handling robots. The system was developed to overcome common bottlenecks in synthetic biology — especially the manual, repetitive pipetting steps required for assembling DNA constructs.
