Week 1 HW: Principles and Practices

1. First, describe a biological engineering application or tool you want to develop and why.

I want to work with Geobacter bacteria to create a living soil contaminate sensor: where electric signals modulate based on the prescence of heavy metals in the ground. Geobacters are already well studied bacterias that produce electric signals under ground. This makes them a useful organism to modify and use as a biosensor.

Heavy metal soil tests exist but by having living bacteria that emit electric signals one can track the growth and spread of these metals. This can lead to better pollutant mapping and detection of the source of the issue. With genetic engineering we can also customize the bacteria to respond to local problems by genetically modifiying the GeoBacters to respond to specific heavy metals.

The specific mechanism I would study would be how to add a metal-inducible promoter to express the gene in Geobacters related to their electron transfer (electricity) trait. That way the electricity would increase when there are heavy metal contaminants present in the ground and this would be a measurable way of tracking soil health overtime.

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.

Environmental Health: Non-malfeasance to ecosystems. This living soil contaminate sensor will improve environmental health by providing constant monitoring about the state of soil health.

Reduced Inequality: Making the sensors accessible to all. By having a living biosensor that is all around us, it removes the barrier of entry when it comes to education about soil quality. Tracking the changes in electric signals in the modified Geobacters requires limited technology.

Human Health: Protect people from heavy metal exposure. By having constant, easy to understand living soil sensors, communities of people will be empowered with data and knowledge to advocate for better environmental protections from their lawmakers. The monitoring will also allow them to know which parts of their community have been most impacted and how to avoid harmful proximity.

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

Biocontainment and a Kill-Switch for Geobacters

Purpose: To have a mechanism in place to stop Geobacters from spreading and ruining the balance in the ecosystem they are introduced in. Or to keep them contained in one specific area.

Design: This would involve engineering a specific kill-switch for the modified Geobacter bacteria. This could be having the bacteria be susceptible to a specific type of antibiotic, or making the bacteria be dependent on a specific synthetic nutrient that has to be administered regularly to ensure geobacter survival.

Assumptions: The assumption is that this kind of kill-switch would be effective. And the assumption is that having a specific antibiotic for geobacter would not affect other nearby living organisms.

Risks of Failure & Success: Failure would be if the engineered Geobacteria spread uncontrollably and endangered the balance of the microorganism ecosystem. Success looks like well contained Geobacters that do not harm any other living organism but instead works symbiotically with them.

Open Source Community Science

Purpose: To make sure that the information being collected from the Geobacter soil sensors is open to all members of the nearby communities and beyond.

Design: There would be public dashboards accessible to all that show the data collected by the sensors. There would also have to be open source documentation about how to create your own low-cost “readers” that would be able to evaluate the electronic signals emitted by the sensors.

Assumptions: Communities implicated have basic knowledge of electronics, and have access to digital media.

Risks of Failure & Success: Failure would be if this information became privatized and used in a way that would be harmful or exploitative of local communities. Success would be if all the data collected remained transparent and accessible to all.

Reporting System for High Heavy Metal Levels

Purpose: To ensure that there is a way that authorities are notified when toxic metal detection reaches a dangerous threshold. To encourage action is taken if a threat to human or animal health is detected.

Design: Create a policy where there is a threshold level that activates an alert system either to the local community, the relevant environmental authorities, etc. Also have a trigger that would alert a non-profit or similar body of scientists to verify the findings from the biosensors.

Assumptions: The biosensors are accurate and reporting correctly. There are competent authorities in the area that are able to help restrict dangerous high-contaminant areas, to prevent people from being affected.

Risks of Failure & Success: A failure would be if the system works improperly and gives false negatives or false positives, eroding trust in the biosensors. A success would be if the biosensors report accurately and their findings can be confirmed by a third body in the case of heavy metal detection, and communities and people become more aware of the quality of their soil and issues related to pollution.

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:

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.

Resources

Bazhenov, S. V., Novoyatlova, U. S., Scheglova, E. S., Prazdnova, E. V., Mazanko, M. S., Kessenikh, A. G., Kononchuk, O. V., Gnuchikh, E. Y., Liu, Y., Al Ebrahim, R., Zavilgelsky, G. B., Chistyakov, V. A., & Manukhov, I. V. (2023). Bacterial lux-biosensors: Constructing, applications, and prospects. Biosensors and Bioelectronics: X, 13, 100323. https://doi.org/10.1016/j.biosx.2023.100323

Webster, C. F., Kim, W.-J., Reguera, G., Friesen, M., & Beyenal, H. (2024). Can bioelectrochemical sensors be used to monitor soil microbiome activity and fertility? Current Opinion in Biotechnology, 90, 103222. https://doi.org/10.1016/j.copbio.2024.103222

Week 2 Lecture Prep

Homework Questions from Professor Jacobson:

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?

The error rate of polymerase is 1:10⁶. The length of the human genome is approximately 3.2 gigabase pairs (gbp). This discrepancy is fixed in part by error correcting polymerase that go back and “check their work.” There is also the MutS Repair System which is where a protein (MutS) detects mismatches in DNA and activates other proteins to “cut out” the mismatched protein allowing the DNA polymerase to recreate the missing segment.

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 in biology. An average human protein is about 300 - 400 amino acids long. An amino acid can have 4 possible codons which means the number of different ways to code for an average human protein would be (using the upper limit) 4⁴⁰⁰ which is huge. There are many reasons why not all the different codons would work. One of the reasons is some organisms prefere use of certain codons over others. Another reason is that protein folding is sensitive, and not all codon pairings would work.

Homework Questions from Dr. LeProust:

1. What’s the most commonly used method for oligo synthesis currently?

Currently the most commonly used method for oligo synthesis is solid‑phase phosphoramidite. This refers to a way of growing DNA in a way where it is on a stable support using chemically protected DNA letters to create a smooth process.

2. Why is it difficult to make oligos longer than 200nt via direct synthesis?

It’s difficult to make oligos longer than 200nt via direct synthesis because the number of errors accumulates with the length of the oligonucleotide.

3. Why can’t you make a 2000bp gene via direct oligo synthesis?

According to slide 59 there is an error rate of 1:2000 nt. Which means the likely hood of errors in making a 2000bp gene is high and its better to synthesize small fragments and stitch them together later.

Homework Questions from George Church:

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 in all animals are: phenylalanine, valine, threonine, tryptophan, isoleucine, methionine, histidine, arginine (non-essential for mammals though), leucine and lysine.

The Lysine Contingency is an idea from the fictional book/movie Jurassic Park which was about how engineered dinosaurs could not make their own lysine so they depended on human’s supplementing it for them. So there was a sort of kill-switch for the engineered dinosaurs.

However lysine is already an essential amino acid for animals, meaning they can’t make it on their own and need to supplement it. So the dinosaurs would naturally get lysine from their environment – not such a great fail-safe in the end!

Week 2 HW: DNA Read, Write, & Edit

Part 1: Benchling & In-silico Gel Art

I made a free account on benchling and then imported the Lambda DNA (see below).

I simulated the restriction enzyme digestion with the following enzymes: EcoRI, EcoRV, SacI, SacII, KpnI, BamHI, HindIII.

I made an attempt at a pattern/image in the style of Paul Vanouse’s Latent Figure Protocol artworks.
It was supposed to be a semi circle of sorts, I’ve decided it’s ski goggles now. I suppose it’s a bit of a Rorschach Test and you can see what you want to see.

Here are the enzymes and enzyme combinations used for the ski goggles:

Part 2: Gel Art - Restriction Digests and Gel Electrophoresis

Not applicable – No Lab Access

Part 3: DNA Design Challenge

3.1. Choose your protein.

In recitation, we discussed that you will pick a protein for your homework that you find interesting. Which protein have you chosen and why?

I am choosing the PilA protein which is derived from the bacteria Geobacter Sulfurreducens. PilA is the protein that is the main building block in the conductive nanowires (called e-pili) on Geobacter bacteria. Interestingly in a lab setting it is easier to work with the water-friendly shortened version of the protein, called PilA19, which can then used in bacteria such as E.coli. I will be finding my protein based on what is studied in the “Bottom-Up Fabrication of Protein Nanowires via Controlled Self-Assembly of Recombinant Geobacter Pilins” research paper.

>tr|Q74D23|Q74D23_GEOSL Geopilin domain 1 protein OS=Geobacter sulfurreducens (strain ATCC 51573 / DSM 12127 / PCA) OX=243231 GN=pilA-N PE=1 SV=1
MANYPHTPTQAAKRRKETLMLQKLRNRKGFTLIELLIVVAIIGILAAIAIPQFSAYRVKA
YNSAASSDLRNLKTALESAFADDQTYPPES

References:
Cosert KM, Castro-Forero A, Steidl RJ, Worden RM, Reguera G. Bottom-Up Fabrication of Protein Nanowires via Controlled Self-Assembly of Recombinant Geobacter Pilins. mBio. 2019 Dec 10;10(6):e02721-19. doi: 10.1128/mBio.02721-19. PMID: 31822587; PMCID: PMC6904877.

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

Using the reverse translate tool from bioinformatics.org I was able to get the most likely codons from my protein sequence.

>reverse translation of tr|Q74D23|Q74D23_GEOSL Geopilin domain 1 protein OS=Geobacter sulfurreducens (strain ATCC 51573 / DSM 12127 / PCA) OX=243231 GN=pilA-N PE=1 SV=1 to a 270 base sequence of most likely codons.
atggcgaactatccgcataccccgacccaggcggcgaaacgccgcaaagaaaccctgatg
ctgcagaaactgcgcaaccgcaaaggctttaccctgattgaactgctgattgtggtggcg
attattggcattctggcggcgattgcgattccgcagtttagcgcgtatcgcgtgaaagcg
tataacagcgcggcgagcagcgatctgcgcaacctgaaaaccgcgctggaaagcgcgttt
gcggatgatcagacctatccgccggaaagc

3.3. Codon optimization.

I have used VectorBuilder’s online codon optimization tool to optimize my above protein sequence to be used in E.coli. I chose E.coli because it is one of the most commonly used chassis when it comes to genetic engineering and therefore it will make experimenting with the PilA protein easier. The codon optimization is important because different organisms have preferences for different codons. For example some organisms have more available tRNA’s for specific codons. By optimizing codon usage, you can take advantage of what is more available in the organism, which speeds up the protein-making process.

PilA protein DNA sequence with Codon-Optimization
ATGGCGAACTATCCGCATACCCCGACCCAGGCCGCGAAACGCCGCAAAGAAACCCTGATGCTGCAGAAACTGCGCAATCGTAAAGGCTTTACCCTGATTGAACTGCTGATTGTGGTGGCGATTATTGGCATTCTGGCGGCGATTGCGATTCCGCAGTTTAGCGCGTATCGCGTTAAAGCCTACAATAGCGCGGCGAGCAGCGATCTGCGTAATCTGAAAACCGCGCTGGAATCCGCCTTTGCGGATGATCAGACCTATCCGCCGGAAAGC

3.4. You have a sequence! Now what?

What technologies could be used to produce this protein from your DNA? Describe in your words the DNA sequence can be transcribed and translated into your protein. You may describe either cell-dependent or cell-free methods, or both.

To produce the PilA protein from its DNA sequence, I could use the cell-dependent method. So the PilA19 (the adapted version of PilA) plasmid gene would be in the E.coli host. What the Central Dogma tells us is that the PilA DNA will be next to a promoter, which wil allow RNA polymersae to read the DNA sequence and make an mRNA copy. This copy can be scanned by a ribosomes in sets of 3 (codons) Each codon represents an amino acid (which is fetched by tRNA) and compiled by the ribosome to create a chain of amino acids which folds and becomes the PilA19 protein.

I would to use cell-dependent production with E.coli because E.coli can give higher yields for the protein as opposed to cell-free methods. It is also less expensive. And it is the method used in the reserach paper I referenced above.

Part 4: Prepare a Twist DNA Synthesis Order

I am creating a DNA sequence that would use GFP with PilA to create glowing green conductive nanowires that in theory could be visually detected and tested for conductivity via Scanning Tunneling Microscopes (STM).

I will be basing myself on several papers that have worked with these proteins before, which I will reference below.

I will be using a basic T7 promoter, found one here: https://parts.igem.org/Part:BBa_I719005.
I will be using the native RBS (Shine-Delgarno): https://parts.igem.org/Help:Ribosome_Binding_Sites/Mechanism.
I will be using this linker for my fusion protein (GFP-tag): https://parts.igem.org/Part:BBa_K5283021.
I will be linking it to this already e.coli optimized version of GFP (sfGFP): https://www.ncbi.nlm.nih.gov/nuccore/HQ873313.1?report=fasta.
That will be followed by the 7x His-Tag used in the homework example as well as the Terminator used in the example: https://parts.igem.org/Part:BBa_B0015.

Link for Twist Order (using the homework example + pilA): https://benchling.com/s/seq-HNOuv8nh3BZpdko0cxxR?m=slm-Ei5fR7bWZIBnKBNornvb.
Link for Twist Order (PilA with sfGFP tag): https://benchling.com/s/seq-T1jlrWcLtLrD49qmLQDv?m=slm-ck0HqucQWeYd28sFDf3T.

There were some redundancies that Twist Bioscience optimized for with my PilA with sfGFP tag DNA sequence. The GenBank file, which I’ve added to my assets folder is the optimized version.

References:

Cosert, K. M., Castro-Forero, A., Steidl, R. J., Worden, R. M., & Reguera, G. (2019). Bottom-Up Fabrication of Protein Nanowires via Controlled Self-Assembly of Recombinant Geobacter Pilins. mBio, 10(6), 10.1128/mbio.02721-19. https://doi.org/10.1128/mbio.02721-19.

Ueki, T., Walker, D. J. F., Woodard, T. L., Nevin, K. P., Nonnenmann, S. S., & Lovley, D. R. (2020). An Escherichia coli Chassis for Production of Electrically Conductive Protein Nanowires. ACS Synthetic Biology, 9(3), 647–654. https://doi.org/10.1021/acssynbio.9b00506.

Wahlfors, J., Loimas, S., Pasanen, T., & Hakkarainen, T. (2001). Green fluorescent protein (GFP) fusion constructs in gene therapy research. Histochemistry and Cell Biology, 115(1), 59–65. https://doi.org/10.1007/s004180000219.

Part 5: DNA Read/Write/Edit

5.1 DNA Read

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

I have two projects that inspire me: one by Carolina Reyes about fungal batteries, another one by Tanguy Chotel about ressurecting ancestral proteins that were better suited at carbon capture and using them to do a “reboot” of the traditional Calvin Cycle. He uses Chlamydomonas reinhardtii as his chassis which is a microalgae.

References: Reyes, C., Fivaz, E., Sajó, Z., Schneider, A., Siqueira, G., Ribera, J., Poulin, A., Schwarze, F. W. M. R., & Nyström, G. (2024). 3D Printed Cellulose-Based Fungal Battery. ACS Sustainable Chemistry & Engineering, 12(43), 16001–16011. https://doi.org/10.1021/acssuschemeng.4c05494

Inckemann, R., Chotel, T., Brinkmann, C. K., Burgis, M., Andreas, L., Baumann, J., Sharma, P., Klose, M., Barrett, J., Ries, F., Paczia, N., Glatter, T., Willmund, F., Mackinder, L. C. M., & Erb, T. J. (2024). Advancing chloroplast synthetic biology through high-throughput plastome engineering of Chlamydomonas reinhardtii (p. 2024.05.08.593163). bioRxiv. https://doi.org/10.1101/2024.05.08.593163

(i) Building off the aforementioned fungal battery, I would be interestied in sequencing the white-rot fungus Trametes pubescens – which in the fungal battery serves as a cathode. There are laccase enzymes in the white-rot fugus that capture the electrons and close the circuit. I’d be curious to sequence other fungi and compare with the Trametes pubescens to see if there are other laccase enzymes in other species that could prove even more adept for bio-batteries. I could sequence specifically the laccase enzymes (lap1/2). Laccase enzymes have copper atoms that capture the electrons. Those electrons then are used to turn airborne oxygen to harmless water (no issue of hydrogen peroxide).

ii) I think I would use NGS (Next Generation Sequencing) to read the DNA from Trametes pubescens because it is one of the more cost-effective solutions and it also handles multiple samples well (for if I want to compare laccase enzymes from different fungi.) However if the genome is very long I should use Oxford Nanopore Technologies which can handle long reads.

1. The NGS method is second generation (massively parallel), which means that as opposed to Sanger sequencing (first generation) this method uses multiplexing (not just one tube per reaction).

References Jiang, S., Chen, Y., Han, S., Lv, L., & Li, L. (2022). Next-Generation Sequencing Applications for the Study of Fungal Pathogens. Microorganisms, 10(10), 1882. https://doi.org/10.3390/microorganisms10101882

5.2 DNA Write

(i) An example of a DNA I would want to synthesize is what I wrote above in the Twist order – a GFP-tag version of the pilA protein in order to understand visually how and where the nanowires are constructed.

The link for the Twist order of this synthesized DNA can be found here: https://benchling.com/s/seq-T1jlrWcLtLrD49qmLQDv?m=slm-ck0HqucQWeYd28sFDf3T

To take this project a step further (and align with the project I investigated in my first homework) I could make a genetic circuit that would take a promoter from another bacteria which is activated by high levels of toxic metals. One such example is the czcCBA promoter that comes from Pseudomonas putida bacteria. This promoter is activated by zinc, cadmium, or lead. I could place this promoter in front of the pilA-GFP protein so that these proteins are expressed only when heavy metals are detected. The GFP would be useful for debugging the circuit, the conductivity could be hooked up to electrodes or other electric components to create a bio-hybrid senor.

(ii) To perform this particular DNA synthesis I would use Twist Bioscience’s web platform. It would be a similar process to what I created in the Twist Example order above. There are other options, like using Golden Gate cloning to assemble DNA. But with Twist I can order the fully built plasmid. They verify the sequences and there’s a guarantee that the sequence delivered is 99.5% exact. Practically speaking this is the best option for me, even if it is more expensive.

5.3 DNA Edit

(i) What DNA would you want to edit and why? In a similar theme to my earlier responses I would edit DNA in order to be able to boost the conductive capabilities of Geobacter Sulfurreducens.

Based on a research paper I found there is a gene called ftsZ which limits the length of the host body. If this gene is repressed (according to the paper) the cell body becomes longer and more filamentous (ressembling a conductive thread). This creates a higher density of the nanowires which improves conductivity.

(ii) I’d use CRISPRi (CRISPR interference) witha dead or deactivated Cas9. CRISPRi is the perfect tool for this because it can pause certain genes without having to cut out parts of the DNA. This makes it perfect for testing.It functions similarly to CRISPR in that there is a “guide RNA” attached to the Cas9 that helps to find the target DNA. However instead of cutting out the DNA it blocks the transcription of that part of the DNA. In this way we can do gene silencing at the transcription level. Once I’ve tested with CRISPRi I can then move to CRISPR to do true gene editing. CRISPR is the same mechanism except is uses activated Cas9 protein which actually cuts out the DNA it is configured to cut out.

In order to do this (for either CRISPR or CRISPRi) I would need to: a. Find the sequence for the ftsZ gene. This will be the guide RNA for Cas9. b. Order the Cas9 proteins c. Grow host chassis (Geobacter or E.coli)

I would have to clone the guide RNA into the Cas9 plasmids. Then I would have to deliver that plasmid into the host cell, something I could do with electroporation.

CRISPR has some limitations, particularly that it does not always target the write cut. This is not only inefficient but can also cause bigger issues like cell death due to inaccurate cuts.

References:

Bird, L. J., Kundu, B. B., Tschirhart, T., Corts, A. D., Su, L., Gralnick, J. A., Ajo-Franklin, C. M., & Glaven, S. M. (2021). Engineering wired life: Synthetic biology for electroactive bacteria. ACS Synthetic Biology, 10(11), 2808–2823. https://doi.org/10.1021/acssynbio.1c00335

Week 3 HW: Lab Automation

Lab Questions: Due March 4th

Post-Lab Questions: Delayed till March 4th