I’m a biology and biomath major at William & Mary, one of the new HTGAA nodes! I was on W&M’s 2025 iGEM team and plan to pursue a career in synthetic biology. Some fields of interest include: SynBio, Microbiology, Phage Biology, Genomics, Transcriptomics, and Bioinformatics. Currently, I’m working with cyanobacteria and RNAseq data from microcosm experiments.
Week 1 HW: Principles and Practices
Week 2 HW: Read, Write, Edit DNA
DNA Design Challenge 3.1. Choose your protein. I’ve chosen PprA, a protein that contributes to radiation resistence in the extremophile bacterium Deinococcus radiodurans, which can survive exposure to space conditions, via DNA repair mechanisms. PprA and other proteins involved in D. radiodurns’s space response could have space biotechnology applications–e.g., engineering space-tolerant food sources and terraforming Martian soil for agriculture. (Note that other research groups have successfully expressed PprA in E. coli before. I’m interested in eventually engineering PprA into a different chassis with direct relevance to space travel or exploring alternative proteins that enhance space (radiation, microgravity, vacuum, etc.) tolerance.)
Python Script and Design Post-Lab Questions 1) Find and describe a published paper that utilizes the Opentrons or an automation tool to achieve novel biological applications. This paper https://pmc.ncbi.nlm.nih.gov/articles/PMC7886139/ (Lazaro-Perona et al., 2021) tests the efficacy of RNA extraction and PCR-based bulk Covid-19 testing procedures, including an Opentron method. They did not find a significant difference in the ability of the Opentron method vs. other protocols to detect Covid, however they point out that the Opentron method is cost-effective and less labor-intensive than its non-automated counterparts.
Effective wastewater treatment is essential for clean waterways, environmental health, and safe drinking water. However, rapid urbanization and population growth have overloaded our capacity to manage aquatic waste, jeopardizing clean water access and biodiversity as pathogens, heavy metals, and algal bloom-inducing nutrients get flushed into waterways. Additionally, current water treatment strategies do not effectively remove a number of harmful compounds, including some drugs and dyes (Renganathan et al., 2025).
Engineered microbial consortia, harnessing and enhancing bacterial communities’ innate capacity to degrade harmful compounds, may offer a promising way to strengthen our current wastewater management approaches and expand the variety of pollutants that we can effectively remove and remediate. I am especially interested in using cyanobacterial species for this purpose—I worked briefly with Nostoc and Oscillatoria species, both of which have promising nitrogen-fixation and biodegradation capabilities (Atoku et al., 2021), over the summer, and I am also studying Acinetobacter baylyi (not a cyanobacterium), which has strong catabolic capabilities and can degrade harmful toxins and aromatic compounds (Baugh et al., 2025; Li et al., 2021). I’m curious about how these species might interact as a microbial community and how we could potentially harness their interactions for better wastewater treatment.
A wastewater remediation project would both expand upon my research as a member of William & Mary’s 2025 iGEM team, which focused on developing design principles to apply SynBio to water-related problems, and is relevant to my local community in Williamsburg: Surrounding cities in Virginia and the broader Chesapeake Bay Watershed suffer from frequent water quality and sewage issues.
Goal 1: Ensure feasibility and effectiveness of deploying engineered microbes in a wastewater context.
Goal 2: Ensure effective containment of engineered microbes and prevent off-target ecological harm.
Proposed governance actions:
Based on the above rubric, I would prioritize a governance framework that integrates rigorous scientific testing and safety assessment with discussion between stakeholders, developing regulations that take into account both scientific data and the perspectives of regulators and the public. This framework would create a network of accountability between groups—e.g., ensuring that regulatory decisions are scientifically backed but also that deployment of scientific solutions doesn’t outpace the development of mechanisms to ensure their safety and sustainability. The system involves a tradeoff between testing/safety and the speed of development, but is necessary to ensure that solutions are effective and that we do not deploy them in haste.
Atoku, D. I., Ojekunle, O. Z., Taiwo, A. M., & Shittu, O. B. (2021). Evaluating the efficiency of Nostoc commune, Oscillatoria Limosa and chlorella vulgaris in a phycoremediation of heavy metals contaminated industrial wastewater. Scientific African, 12. https://doi.org/10.1016/j.sciaf.2021.e00817
Baugh, A. C., Tumen-Velasquez, M. P., Zempel, I. R., Duscent-Maitland, C. V., Slarks, L. E., Defalco, J. B., Johnson, C. W., Beckham, G. T., & Neidle, E. L. (2025). Rewiring aromatic compound consumption: Chromosomal amplification and evolution of a foreign pathway in acinetobacter baylyi ADP1. ACS Synthetic Biology, 14(9), 3543–3556. https://doi.org/10.1021/acssynbio.5c00341
Li, H., Yang, Y., Zhang, D., Li, Y., Zhang, H., Luo, J., & Jones, K. C. (2021). Evaluating the simulated toxicities of metal mixtures and hydrocarbons using the alkane degrading bioreporter Acinetobacter Baylyi adpwh_reca. Journal of Hazardous Materials, 419, 126471. https://doi.org/10.1016/j.jhazmat.2021.126471
Renganathan, P., Gaysina, L. A., García Gutiérrez, C., Rueda Puente, E. O., & Sainz-Hernández, J. C. (2025). Harnessing engineered Microbial Consortia for xenobiotic bioremediation: Integrating multi-omics and AI for next-generation wastewater treatment. Journal of Xenobiotics, 15(4), 133. https://doi.org/10.3390/jox15040133
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1. 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?
DNA polymerase’s error rate is 1:10^6 bp. The human genome is 3 billion bp, so cells have evolved DNA repair mechanisms to correct errors when they occur. For example, the protein MutS identifies incorrect DNA base pairings and starts the repair processes alongside other proteins.
2. 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?
There are 20 amino acids and, because of codon redundancy, about two to four different ways to encode each of them. If the average protein is about 300 amino acids long, this would mean about 3^300 different possible ways to encode the protein. In reality, these codes don’t all work because the specific codons are translated at different rates—and translation speed may affect protein folding.
1. What’s the most commonly used method for oligo synthesis currently?
The Phosphoramidite DNA Synthesis method
2. Why is it difficult to make oligos longer than 200nt via direct synthesis?
It takes a long time and the yield is low due to the long coupling time and capping process.
3. Why can’t you make a 2000bp gene via direct oligo synthesis?
The yield and time constraints make this impossible.
1. 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 are arginine, histidine, isoleucine, leucine, lysine, methionine, phenylalanine, threonine, tryptophan, and valine. Animals must obtain the “essential” amino acids through their diet. The “Lysine Contingency” does not make sense because it involves a scientist removing dinosaurs’ ability to produce lysine, which they could not produce in the first place.
I’ve chosen PprA, a protein that contributes to radiation resistence in the extremophile bacterium Deinococcus radiodurans, which can survive exposure to space conditions, via DNA repair mechanisms. PprA and other proteins involved in D. radiodurns’s space response could have space biotechnology applications–e.g., engineering space-tolerant food sources and terraforming Martian soil for agriculture. (Note that other research groups have successfully expressed PprA in E. coli before. I’m interested in eventually engineering PprA into a different chassis with direct relevance to space travel or exploring alternative proteins that enhance space (radiation, microgravity, vacuum, etc.) tolerance.)
PprA DNA sequence, from D. radiodurns refseq NC_001264.1, below:
(http://ncbi.nlm.nih.gov/nuccore/NC_001264.1?from=381165&to=382067) (Note that the above nt sequence is the forward strand, but the protein is encoded by the reverse. See the AA seq for the product that it encodes. Note also that D. radiodurans sometimes uses non-standard start codons.)
Codon optimization ensures that the codons in an engineered construct’s nucleotide sequence correspond with tRNAs that the host species commonly uses and that maximize the efficiency of translation (without changing the resulting amino acid sequence). To account for the NCBI nt sequence’s reverse strand location and D. radiodurans’s non-standard start codons, I optimized directly from the amino acid sequence using the IDT codon optimization tool. (Note that I needed to add a stop codon (TAA) manually because, given the lack of a corresponding AA, the protein seq does NOT encode one.)
I optimized the sequence for use in E. coli. E. coli could be engineered to exhibit extremophile characteristics in order to enhance its viability as a chassis for space applications. Note also that I avoided BbsI, BsaI, BsmBI cut sites. Below is the optimized sequence:
What technologies could be used to produce this protein from your DNA? The most straightforward way to transcribe and translate this DNA sequence into protein would be to engineer it into a plasmid, or order it as part of a plasmid, and then transform it into a model bacterium such as E. coli, which could then produce the protein.
I’ve included the BBa_J23106 promoter for high constitutive expression in E. coli, the BBa_B0034 RBS, and BBa_B0015 Terminator. If I were to order this construct, I might look into E. coli promoters that are UV or general radiation or DNA damage-inducible, as this might reduce the burden of constitutive expression and ensure that the cell only diverts resources to producing the protein under conditions where it is useful.
Selected pTwist Amp high copy vector on Twist
(i) What DNA would you want to sequence (e.g., read) and why?
I would like to perform metagenomic sequencing (or metatranscriptomics, though this would be RNAseq) on one of the harmful algal blooms (HABs) that frequently affect local lakes in Virginia. I studied HABs as part of the William & Mary iGEM project last year and am currently working with transcriptomic data from HAB microcosms. Local stakeholders told me that we still cannot fully predict when these blooms might happen and what factors contribute to their duration and severity. Understanding the Virginia blooms’ taxonomic composition (via metagenomics) and functional roles of the relevant microbes (via metatranscriptomics) would inform public safety measures and bloom mitigation strategies.
(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?
1) Is your method first-, second- or third-generation or other? How so?
I would use PacBio HiFi sequencing, which is a third-generation/long read method. Longer reads make it easier to accurately identify the taxa present in the sample and to de novo assemble metagenomes, while shorter, fragmented reads provide less information and and may be more likely to yield false matches.
2) What is your input? How do you prepare your input (e.g. fragmentation, adapter ligation, PCR)? List the essential steps.
My input would be DNA extracted from the lakewater (probably via an extraction kit designed for water samples) and prepared via the following steps:
3) What are the essential steps of your chosen sequencing technology, how does it decode the bases of your DNA sample (base calling)?
In PacBio HiFi sequencing 1) the scientist performs library prep (see above), 2) DNA molecules stick to “zero-mode waveguides,” which are wells in the sequencing device, the “SMRT Cell”, and 3) DNA polymerase adds fluorescent nucleotides to each individual DNA molecule, emitting light that indicates the sequence.
4) What is the output of your chosen sequencing technology?
PacBio HiFi sequencing produces long-read raw sequence data as output.
(i) What DNA would you want to synthesize (e.g., write) and why?
The cyanobacterium N. commmune has a number of qualities–such as relative tolerance to vacuum conditions, radiation, dry environments, and extreme heat, anti-inflammatory properties, and the ability to promote plant growth–that make it promising for space travel applications, including terraforming Martian soil and providing a sustainable food source. However, the species is extremely slow-growing, difficult to engineer, and may produce toxins harmful to human health–so on its own may be difficult to deploy/apply. I would like to either engineer Nostoc to be faster-growing and more manageble as a chassis–or would synthesize relevant Nostoc genes and pathways (e.g., extracellular polymeric substance production mechanisms, nutrient content, and survival under extreme conditions) and express them in model organisms, which we could then more-easily manipulate and use as chassis for space, nutrition, agriculture, wastewater-management, and more.
(ii) What technology or technologies would you use to perform this DNA synthesis and why?
I would use clonal gene sythesis methods (e.g., from Twist) to order the relevant genes and/or circuits in plasmid form so that I could easily express them in a chassis of choice. Producing the plasmids would involve synthesizing the relevant fragments (e.g., with the phosphoramidite method) and then assembling them together (e.g., via Gibson or Golden Gate).
(i) What DNA would you want to edit and why?
I would like to modify genes and pathways that regulate bacterial growth, particularly in the cyanobacterium N. commune. The bacterium’s slow growth rate is a major barrier to engineering, deployment as a chassis, and basic science. Modifying growth rate may be difficult because of potential off-target effects on bacterial performance (e.g., the species may need to grow slowly in order to produce an essential compound) and would likely require me to edit regulatory components of genes involved in metabolism and nutrient uptake–and potentially could involve knocking out non-essential genes that might slow down bacterial growth.
(ii) What technology or technologies would you use to perform these DNA edits and why?
I might use a combination of CRISPR and TALENs to potentially 1) replace sequences relevant to metabolic regulation (e.g., that promote nutrient uptake and processing) with more-active counterparts via homology-directed repair with template sequences of interest and 2) knock out sequences that are not essential to bacterial survival/performance and that may impose a burden on bacterial growth.
1) Find and describe a published paper that utilizes the Opentrons or an automation tool to achieve novel biological applications.
This paper https://pmc.ncbi.nlm.nih.gov/articles/PMC7886139/ (Lazaro-Perona et al., 2021) tests the efficacy of RNA extraction and PCR-based bulk Covid-19 testing procedures, including an Opentron method. They did not find a significant difference in the ability of the Opentron method vs. other protocols to detect Covid, however they point out that the Opentron method is cost-effective and less labor-intensive than its non-automated counterparts.
2) 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.
I’m interested in engineering model bacteria to produce extracellular polymeric substances (EPS) similar to those of the cyanobacterium Nostoc. Nostoc’s EPS gives it natural metal-chelating abilities, high tolerance to stress, dessication, and space conditions, and high nutritional content. However, Nostoc is extremely slow-growing and very difficult to engineer, so is not an optimal chassis. Adding specific Nostoc-like properties to other species would make it possible to take advantage of these characteristics for engineering without dealing with its slow growth rate.
Automation would be most important in the testing phase of my project. To assess EPS formation in bulk, I might use an Opentron-like system to screen a portion of samples, potentially containing different versions of my circuit (or under various conditions and/or including controls that are uninduced or without a circuit present), for production of EPS, and EPS-composition (i.e., presence of carbohydrate compounds vs proteins) via chemical and colorimetric assays. These assays might involve using the opentron to add relevant reagents to each sample, then using a plate reader or spectrophotometer for downstream absorbance and fluoresence measurements.
Engineering synthetic microbial consortia, including A. baylyi, N. commune, and Oscillatoria sp., for wastewater treatment and bioremediation
Engineering production of elements of Nostoc’s extracellular polymeric substance composition into fast-growing, genetically-tractable bacteria for applications in space travel, bioremediation, nutrition, and agriculture.
Developing a bioengineering toolkit for space travel using genes from extremophile species.
Week 2 Lab: Restriction Digests
Protocol Part 0: Design Note: Ignore EcoRI lane: for visualization Note: We are using DNA from mycobacteriophage Kampy Part 1a: Gel prep Setting up a 1% agarose gel:
Note: Ignore EcoRI lane: for visualization
Note: We are using DNA from mycobacteriophage Kampy
Setting up a 1% agarose gel:
Chemicals
Digest requirements
our DNA = 324 ng/uL = 0.324 ug/uL– to get 1.5 ug, we need 4.62 uL of DNA
Plan for Mixtures
4.62 uL DNA
2 ul 10x buffer
BstXI: to get final amt 15 ug – 37 – H buffer
KpnI: to get final amt 15 ug – 37 – MC buffer
SfiI: to get final amt 15 ug – 50 – B buffer
Notes/Scratch work
Done: NFW, DNA, Buffer, Enzyme
Running
BstXI – + assoc buffer – 37oC
BstXI – + assoc buffer – 37oC
KpnI – + assoc buffer – 37oC
SfiI – + assoc buffer – 50oC
See chart on site for reagent concs and quantities
