Homework
Weekly homework submissions:
Week 1 HW: Principles and Practices
Part 1: Class Assignment 1. “The Big Idea” In the world of Big Farm, nutrient pollution is a big problem, particularly near farms where fertilizers and manure release excess phosphorus and nitrogen into the environment. This leads to issues like eutrophication, dead zones, and human health impacts. This also leads to losses in other industries such as fishing or recreational activity. Paradoxically, we also frequently see cases of nutrient depletion, particularly in the context of agriculture. Monocropping and poor agricultural practices has led to the depletion of topsoil, making it one of the scarcest resources in the world. According to the UN Food and Agricultural Organization, 90% of our world’s topsoil is at risk by 2050. To combat this, I’m interested in seeing if a circular nutrient economy is possible:
Week 10 HW: Imaging and Measurement
Part 1: Final Project To validate my “Aragonite Anchor” this semester, I’ll first confirm protein expression and localization using SDS-PAGE and Western Blotting. By fractionating the cells and targeting my specific gene tags, I can prove the OmpA-CBP-1 fusion is actually reaching the outer membrane. To measure the binding affinity to CaCO3, I’ll use Fluorescence Spectroscopy; by tagging the protein with a marker like GFP, I can quantify exactly how much “glue” stays stuck to the crystals after washing.For structural characterization, I’ll use XRD to verify I’ve successfully formed the aragonite phase and SEM to get the “money shot” of the layered, nacre-like morphology. Finally, I’ll test the mechanical strength of the composite via Nanoindentation. This will let me measure the Young’s Modulus and fracture toughness, providing the quantitative data needed to prove my engineered protein actually makes the material stronger than a standard mineral control.
Nothing to see here… Please refer to WEEK 12.
Part 1: Global Pixel Art So, unfortunately I didn’t receive an email to contribute to this, and I saw the homework posting AFTER the deadline. I guess I will just have to TA next year instead! Part 2: Cell Free Synthesis E. coli Lysate BL21 (DE3) Star Lysate: Provides the essential cellular machinery, including ribosomes, tRNAs, and initiation/elongation factors, required for translation. T7 RNA Polymerase: Specifically transcribes the target DNA template into mRNA, driving high-level protein expression. Salts/BufferPotassium Glutamate: Acts as the primary salt to maintain ionic strength and provides potassium ions, which are vital for ribosomal activity. HEPES-KOH (pH 7.5): A buffering agent that stabilizes the pH of the reaction, ensuring enzymatic activity remains optimal as metabolic byproducts accumulate. Magnesium Glutamate: Supplies $Mg^{2+}$ ions, which are critical cofactors for polymerase activity and the structural stability of ribosomes. Potassium Phosphate (Monobasic/Dibasic): Works alongside HEPES to provide secondary buffering capacity and maintains inorganic phosphate levels for energy cycling. Energy / Nucleotide System Ribose & Glucose: Serve as carbon and energy sources that the lysate’s endogenous pathways use to regenerate ATP. AMP, CMP, GMP, UMP (NMPs): These monophosphate nucleotides are the raw building blocks that the system phosphorylates into NTPs for RNA synthesis. Guanine: Acts as a precursor to maintain the pool of guanosine nucleotides, which are essential for the initiation and translocation steps of translation. Translation Mix (Amino Acids)17 Amino Acid Mix / Tyrosine / Cysteine: These are the physical building blocks of the protein; Tyrosine and Cysteine are often added separately due to lower solubility or specific stability requirements. Additives & Backfill Nicotinamide: Helps stabilize and regenerate $NAD^{+}$ levels, supporting the metabolic flux required for sustained energy production.Nuclease Free Water: Acts as the solvent for the reaction, ensuring no residual enzymes degrade the DNA template or mRNA products. Comparing Master Mixes The 1-hour PEP/NTP mix is designed for speed and immediate energy, utilizing pre-formed NTPs and Phosphoenolpyruvate (PEP) as a direct, high-energy phosphate donor for rapid, short-burst reactions. In contrast, the 20-hour NMP-Ribose-Glucose mix is optimized for sustainability and cost-effectiveness, using cheaper precursors (NMPs and sugars) that the system slowly converts into energy via endogenous metabolism to support protein production over a much longer duration. While the 1-hour mix prioritizes a quick “sprint” for rapid results, the 20-hour mix facilitates a “marathon” by recycling energy through more complex biochemical pathways.
Week 2 HW: DNA READ, WRITE & EDIT
PART 0: BASICS I have attended all lectures and recitation necessary to prepare for this week. PART 1: GEL ART & BENCHLING I made my free account on Benchling, following Ice’s tutorial in class on Lambda DNA. I then played around with Ronan’s website and Benchling’s Digest feature to try to come up with something I liked. Ultimately, I came up with something that looks vaguely like a lucky cat (if you squint).
Part 1: Python Script Despite having taking 6.100A, I am still not very adept with Python. I am even less skilled with Google Colab, so I had no choice but to use the GUI to generate my Python script. I produced this beautiful piece of art: I also created this one:
Week 4 HW: Protein Design Part I
Part 1: Conceptual Questions Assuming protein mass of meat is 20%, 0.20 x 500=100g of actual protein in this meat. If average residue is roughly 100 Da, I can probably assume that’s roughly 100g/mol, meaning I now have 1 mol of residue. In one mole, there’s roughly 6 x 1023 molecules. Thus, there are roughly 6 x 1023 molecules of amino acids in 500 grams of meat We digest these proteins, not incorporate them into our bodies. We rebuild our own proteins using molecular tools in our body, that may or may not come from what we eat. There are only 20 “natural” amino acids because that’s what biology standardized our amino acids as. These amino acids have good chemical diversity, synthetic accessibility and different constraints. Now that we have evolutionarily reached this place, it is difficult to incorporate more without rewiring our whole system. As to why there’s only 20 versus like 100, this could be because if there were too many, it would be rather costly and inefficient, so it’s better to keep our biological systems simple. Yes, noncanonical amino acids are frequently made, and they can also probably be genetically encoded as well. For example, fluoroleucine or p-iodo-phenylalanine. Before enzymes & life, amino acids came from multiple plausible sources. For example, strecker synthsis in watery environments, delivery by meteorites (they were found in chondrites), or even atomsphere/UV activity. They are left handed Yes, proteins contain other helical motiefs like π-helix, collagen triple helix, β-helix / solenoid-like helices. New helical patterns can be found by analyzing high resolution structures. Most molecular helices are right hanaded because of chirality bias in L-amino acids. Another reason could be that right-handed packing avoids clashes and are better for L residues in general (so as a result of sterics). They have sticky edges where backbone hydrogen bond donors/acceptors are exposed at the sheet edges, and adding on another strand would satisfy H-bonds. This allows β-sheets to extend into larger assemblies easily. Drivers include bacbkone hydrogen bonding, hydrophobic effect and shape complentarity. Growth is probably also kinetically favorable. Amyloid diseases tend to form β-sheets because the cross-β amyyloid architecture is very stable and can form many sequences once misfolded. This ultimately templates further misfolding and thus createspersistent aggregates that disrupt cells. Yes, they are often found in nanofibers, hydrogels, templates for mineralization, etc. A simple, reliable design is a β-hairpin that self-assembles with controlled registry: Design rules:
Week 5 HW: Protein Design Part II
Part 1: SOD1 Binder Peptide Design Part A: The retrieved SOD1 sequence is: MATKAVCVLKGDGPVQGIINFEQKESNGPVKVWGSIKGLTEGLHGFHVHEFGDNTAGCTSAGPHFNPLSRKHGGPKDEERHVGDLGNVTADKDGVADVSIEDSVISLSGDHCIIGRTLVVHEKADDLGKGGNEESTKTGNAGSRLACGVIGIAQ Upon introducing the A4V Mutation, we get: MATKVVCVLKGDGPVQGIINFEQKESNGPVKVWGSIKGLTEGLHGFHVHEFGDNTAGCTSAGPHFNPLSRKHGGPKDEERHVGDLGNVTADKDGVADVSIEDSVISLSGDHCIIGRTLVVHEKADDLGKGGNEESTKTGNAGSRLACGVIGIAQ The following amino acids were generated with their subsequent perplexity scores:
Week 6 HW: Genetic Circuits Part I
Part 1: Homework Questions Phusion High-Fidelity PCR Master Mix contains several components required for DNA amplification. The Phusion DNA polymerase is the enzyme that synthesizes new DNA strands; it has proofreading (3’→5’ exonuclease) activity, which greatly reduces mutation rates compared with standard Taq polymerase. The mix also includes dNTPs (deoxynucleotide triphosphates), which are the nucleotide building blocks incorporated into the newly synthesized DNA. A reaction buffer provides the correct chemical environment (pH, salts, stabilizers) to maximize enzyme activity and fidelity. Mg²⁺ ions (usually from MgCl₂) act as essential cofactors for polymerase function and influence enzyme efficiency. Primer annealing temperature is mainly determined by the melting temperature (Tm) of the primers, which depends on their sequence composition. Primers with higher GC content generally have higher Tm because G–C pairs form three hydrogen bonds compared with two in A–T pairs. Primer length also affects Tm, as longer primers form more stable duplexes with the template. Salt concentration and Mg²⁺ levels in the reaction buffer influence DNA duplex stability and therefore the optimal annealing temperature. Additionally, primer secondary structure or mismatches can reduce binding stability and may require lower annealing temperatures. PCR and restriction enzyme digestion both produce linear DNA fragments but operate through different mechanisms. PCR uses primers and a DNA polymerase to amplify a specific DNA region from a template through thermal cycling. This method is highly flexible because primers can introduce mutations, overhangs, or homologous regions, making PCR useful when generating fragments for cloning or modifying sequences. In contrast, restriction enzyme digestion uses enzymes that recognize specific short DNA sequences and cut at those sites, producing predictable fragments with defined ends (often sticky or blunt). The digest protocol is simpler and faster if the required restriction sites already exist in the DNA. PCR is preferable when amplifying small regions, adding sequences, or working from low DNA amounts, while restriction digests are preferable when cutting large plasmids or isolating fragments with existing restriction sites without introducing polymerase errors. For Gibson Assembly, DNA fragments must have overlapping homologous sequences at their ends so they can anneal during the assembly reaction. These overlaps are usually designed into PCR primers, ensuring that adjacent fragments share complementary sequences. After PCR amplification or digestion, the fragments should be checked by gel electrophoresis to confirm the correct size and purity. It is also important to verify that the overlaps match the intended assembly order and that no incompatible restriction sites remain within the overlaps. Golden Gate Assembly is a DNA cloning method that uses Type IIS restriction enzymes and DNA ligase in a single reaction to assemble multiple DNA fragments in a defined order. Unlike standard restriction enzymes, Type IIS enzymes cut outside their recognition site, producing custom overhangs that can be designed to be unique for each fragment. During the reaction, the restriction enzyme cuts the DNA to create compatible overhangs, and DNA ligase simultaneously joins the fragments together. Because the recognition sites are removed after ligation, the final assembled product cannot be cut again, allowing the reaction to proceed efficiently toward the correct construct. To model this, I just chose two random sequences (LACMG that we worked with once, and a gibberish one that I have for some reason). I went to Benchling to model the assembly, and this is what came out of it:
Week 7 HW: Genetic Circuits Part II
Part 1: Homework Questions IANNs allow cells to perform analog, weighted, decision-making rather than simple binary logic. Traditional genetic circuits usually implement Boolean gates, where inputs are treaed as on/ofof signals and outputs are discrete. In contrast, IANNS use components whose activities can vary continuously, allowing inputs to contribute different weights to a final output. This allows cells to integrate multiple signals simultaneously, filter noise and produce grade responses. IANNs overall can scale more easily to complex behaviors, making them better suited for biological environments with continuos noisy signals. A useful application of IANN would be a smart probioitic diagnostic cell that detects complex disease states in the gut. Inputs: The circuit could receive several molecular signals associatied with inflammation, such as nitric oxide levels, reactive oxygen species or other responsive promoters. Each input drives production of regulators that act with different weights on the expression of a reporter gene. Processing: Each regulator modifies the stability or translation of the reporter mRNA. If the combined signal exceeds a threshold, the cell expresses a fluorescent protein or therapeutic molecule. This allows the cell to classify complex physiological states, rather than triggering on a single biomarker that might fluctuate naturally. Output: Low combined signal → little or no reporter expression. Moderate signal → weak expression. High combined signal → strong reporter or drug release. Limitations: There are several constraints that could limit implementation. For example, gene expression fluctuations can distort weights and thresholds, making outputs inconsistent. Promoters and translation systems may saturate, preventing precise analog weighting. Large networks can slow cell grwoth or destabilize circuits. Furhtermore, large networks could slow cell growth or dsetabilize circuits and tuning these weights rqequires iterative experimental optimization. stuff Part 2: Fungal Materials Several commercial materials are made from fungal mycelium. One example is mycelium-based packaging produced by Ecovative, which grows fungal mycelium through agricultural waste to create molded protective packaging that replaces polystyrene foam. Mycelium composites are also used for insulation panels and structural building materials, such as mycelium bricks and boards that can be grown into shape. Another emerging product is mycelium leather, developed by companies like MycoWorks and Bolt Threads, which produces flexible sheet materials that mimic animal leather for fashion products. These fungal materials offer several advantages over traditional materials. They are renewable and biodegradable, can be grown from agricultural waste, and require much lower energy input than plastics or synthetic foams. Mycelium materials can also be grown directly into molds, reducing manufacturing steps and waste. However, they also have disadvantages: mechanical strength and durability are generally lower than plastics or synthetic composites, they can be sensitive to moisture, and scaling production with consistent material properties remains challenging. One useful direction would be engineering fungi to produce stronger or more functional mycelium materials. For example, genes could be modified to increase chitin or glucan crosslinking in the cell wall to improve stiffness and toughness of mycelium composites used in construction or packaging. Fungi could also be engineered to produce functional biomaterials, such as mycelium that incorporates conductive proteins for bioelectronics or that secretes adhesives or antimicrobial compounds. Another application could be fungi engineered to capture pollutants, such as heavy metals or microplastics, allowing grown fungal materials to act as environmental filtration systems. Fungi offer several advantages as engineering hosts compared with bacteria. Because fungi are eukaryotes, they perform complex post-translational modifications and protein folding, which are necessary for many enzymes and biomaterials that bacteria cannot produce efficiently. Filamentous fungi naturally grow large structural networks (mycelium), allowing them to form macroscopic materials without external scaffolds, something bacteria generally cannot do. Fungi also secrete large amounts of enzymes and proteins, making them good platforms for producing extracellular biomolecules or structural polymers. However, fungi are generally harder to genetically manipulate than bacteria: transformation efficiencies are lower, genetic tools are less standardized, and growth is typically slower. Part 3: Proposal Draft Aim 1:
Part 1: General Homework Questions Cell’s survival is the priority. In CFPS, the “cell” is broken open, leaving only the machinery. The advantages include more direct access (adding non-canonical AA, detergents, chaperones) or an open system to monitor the reaction in real-time and adjust variables. One case where this is more beneificial would be in toxic proteins; if the protein kills a living host, it can still be produced in a cell-free system because there’s no “life” to extinguish. Another case could be for rapid prototyping, where CFPS allows for cycles in hours rather than the days required for usual cell transformation and growth. Major components: crude extract provides things like ribosomes, RNA polymerase, translation factors, the DNA template encodes the protein, the energy mix provides energy, amino acids provide building blocks for proteins and cofactors/salts provide ions that help stability and enzyme activity. Energy provision regeneration is critical because translation is energy-intensive. Every peptide bond requires the hydrolysis of multiple high-energy phosphate bonds. Without regeneration, ATP levels plummet in minutes, and the accumulation of inorganic phosphate inhibits the reaction. Something possible for continuous supply would be to use Secondary Energy Source, such as the Creatine Phosphate/Creatine Kinase system. Creatine kinase transfers a phosphate group from creatine phosphate back to ADP, maintaining a steady-state concentration of ATP throughout the batch reaction. Prokaryotic: High yield, fast and cheap. A protein that might be produced is GFP, that is simple and doesn’t require complex folding or glycolysations. Eukaryotic systems provide lower yield but are capable of complex post-translational modifications like glycosylation and proper disulfide bond formation. A protein that might be produced in one of these systems is human insulin, which requires specific folding and bridges that the eukaryotic machinery handles better. When encountering low protein yields in a cell-free system, the first step is often to investigate template stability. In many extracts, endogenous nucleases are present that can rapidly degrade linear DNA templates. A common troubleshooting strategy is to switch to a circular plasmid or supplement the reaction with nuclease inhibitors like Gam protein. A second common culprit is codon bias, where the genetic sequence of the target protein utilizes codons that are rare within the organism from which the extract was derived. This can be addressed through synonymous gene sequence optimization or by using specialized extracts supplemented with rare-target tRNAs. Finally, the concentration of magnesium ions is a critical variable that often requires a titration experiment. Because magnesium is essential for ribosome assembly but inhibitory at high concentrations, performing a series of reactions across a gradient is a standard strategy to find the “sweet spot” for a specific proteins. Part 2: Homework Questions from Kate Adamala Designing a cell-free experiment for membrane proteins introduces the unique challenge of hydrophobicity, as these proteins often aggregate or misfold without a lipid environment. To address this, one can incorporate synthetic surfactants or detergents into the reaction to keep the protein soluble during synthesis. Alternatively, a more biomimetic approach involves adding nanodiscs or liposomes directly into the cell-free mix, providing a membrane-like scaffold for the protein to insert into co-translationally. The primary advantage here is that the open nature of the system allows you to precisely control the lipid composition to optimize the stability and activity of the membrane protein without the toxicity issues often seen in living hosts.