Homework
Weekly homework submissions:
Week 1 HW: Principles & Practices
🦠Brighter Autonomous Bioluminescence🦠 I would love to improve the intensity of the glow that is emitted from autonomous bioluminescent organisms whether natural or synthetic. There are several different organisms that produce bioluminescence through various forms of luciferases (the enzyme that catalyzes the light emitting reaction) and luciferins (the substrate). However, most of them require the addition of the substrate to the growing medium to induce bioluminescence, typically coelenterazine or D-Luciferin. This to me just does not seem like the most convenient way to do this, so I am more interested in autonomous bioluminescent systems, such as Lux (bacterial luciferase) and Luz (fungal luciferase). These systems are the only two bioluminescent systems that have been fully elucidated. This means that they are fully genetically encoded, cells express luciferase and the enzymes necessary for substrate synthesis. This enables continuous supply of substrate without having to worry about adding the substrate to the growing medium or tissues to produce a glow.
Week 2 HW: DNA Read, Write, & Edit
Benchling & In-silico Gel Art Lambda DNA Restriction Digest Gel Art (Supposed to say “Hi”) DNA Design Challenge Protein: Luciferase 💡
Lab Automation Article of Interest: Deep reinforcement learning for the control of microbial co-cultures in bioreactors This study uses an automation tool in the form of AI-based process control, deep reinforcement learning. Instead of manually tuning bioreactor conditions, the authors train an algorithm to make control decisions that regulate nutrient inputs and maintain stable microbial populations in co-culture. The novel biological application is dynamic control of multi-species microbial communities, which is a major challenge in synthetic biology and biomanufacturing because species can outcompete each other or become unstable over time. The paper shows that reinforcement learning can effectively stabilize co-cultures and optimize bioprocess performance in silico, demonstrating a promising path toward autonomous bioreactor operation. This is significant because reliable co-culture control could improve production efficiency and enable more complex engineered biological systems.
Week 4 HW: Protein Design Part I
Conceptual Questions 1. Why are there only 20 natural amino acids? There aren’t only 20 amino acids. There are just 20 that biology standardized early on in evolution. Proteins are built using translation. Once that system had evolved changing it was difficult because every protein in every organism depended on it. That creates evolutionary lock-in often referred to as a “frozen standard.” The current amino acids were selected due to their component atoms, functional groups, biosynthetic cost, use in a protein core or on the surface, solubility and stability. There are reasons for the selection of every amino acid. 2. Where did amino acids come from before enzymes that make them, and before life started?
Week 5 HW: Protein Design Part II
SOD1 Binder Peptide Design PepMLM Peptide Perplexity Scores Binder Pseudo Perplexity KLYYPAALRHKE 20.698044578085693 WRVPAVAAAWKK 7.38320080665346 WLYYVVALALWX 17.40309350786337 WLYGATGAEHKK 11.275864207596417 FLYRWLPSRRGG* 20.63523127283615 *Known SOD1-binding peptide added for comparison Evaluating Binders with AlphaFold3 Binder: KLYYPAALRHKE ipTM score: 0.87
Week 6 HW: Genetic Circuits Part I
Questions 1. What are some components in the Phusion High-Fidelity PCR Master Mix and what is their purpose? Phusion DNA Polymerase: Catalyzes the synthesis of new DNA strands. Has 3′→5′ exonuclease proofreading activity, which removes incorrectly added nucleotides. Phusion polymerase is a genetically engineered DNA polymerase fused to a DNA-binding domain. The fusion domain increases DNA binding, which improves processivity. Reaction buffer: Help to maintain a stable pH. Also provides optimal ionic strength for polymerase activity. Stabilizes enzyme structure at high temperatures. Magnesium Chloride (MgCl₂): Essential cofactor for DNA polymerases. Coordinates with the phosphate groups of incoming nucleotides. Helps stabilize primer–template interactions. dNTPs: Provide the substrates used to synthesize new DNA strands. Each nucleotide carries three phosphates, providing the energy needed for polymerization. 2. What are some factors that determine primer annealing temperature during PCR?
Week 7 HW: Genetic Circuits Part II
Intracellular Artificial Neural Networks (IANNs) Questions What advantages do IANNs have over traditional genetic circuits, whose input/output behaviors are Boolean functions? IANNs offer several advantages over traditional genetic circuits. Unlike the Boolean systems that produce binary ON/OFF outputs, IANNs generate continuous, graded responses that better reflect the analog nature of biological systems. They can also be trained by adjusting weights, allowing them to learn complex input–output relationships rather than relying on fixed logic. This enables IANNs to handle nonlinear interactions and integrate multiple inputs more effectively. Additionally, IANNs are more scalable and robust to biological noise, as their distributed architecture reduces sensitivity to fluctuations. Overall, IANNs enable more sophisticated information processing, such as pattern recognition and prediction, which is difficult to achieve with traditional genetic circuits. Describe a useful application for an IANN; include a detailed description of input/output behavior, as well as any limitations an IANN might face to achieve your goal.
General and Lecturer-Specific Questions General homework questions Explain the main advantages of cell-free protein synthesis over traditional in vivo methods, specifically in terms of flexibility and control over experimental variables. Name at least two cases where cell-free expression is more beneficial than cell production. Cell-free protein synthesis has a big advantage over in vivo methods because it gives you direct control over the reaction environment without needing to keep cells alive. You can precisely tune things like DNA concentration, energy sources, cofactors, salts, and even add or remove specific components in real time, which is much harder to do inside living cells where metabolism and regulation get in the way. It’s also faster since you skip cloning, transformation, and cell growth steps. This makes it especially useful for expressing toxic proteins that would kill or stress cells, and for rapid prototyping or screening large libraries of genetic constructs where you want quick, iterative testing without waiting on cultures to grow. Describe the main components of a cell-free expression system and explain the role of each component. A cell-free expression system is mainly made up of a cell extract, a DNA template, and a reaction mix that supports transcription and translation. The cell extract provides the core molecular machinery, like ribosomes, tRNAs, aminoacyl-tRNA synthetases, transcription and translation factors, which are all needed to actually make protein. The DNA template contains the gene of interest along with the regulatory sequences needed for expression. The reaction mix supplies the raw materials and energy needed to drive the system, including amino acids, nucleotides, salts, cofactors, ATP regeneration components, and buffering agents to keep conditions stable. Together, these components recreate the basic protein production machinery of a cell, but in a much more controllable format. Why is energy provision regeneration critical in cell-free systems? Describe a method you could use to ensure continuous ATP supply in your cell-free experiment. Energy provision and regeneration are critical in cell-free systems because transcription and translation burn through ATP and GTP fast, so without a way to replenish that energy, protein synthesis stalls. Since there are no living cells to continuously regenerate energy through metabolism, the reaction depends entirely on whatever energy system you build into it. Basically, if the reaction runs out of usable energy, the whole system stalls, so energy regeneration is what keeps protein production going for longer and improves overall yield. One common way to maintain ATP supply is to include an energy regeneration substrate such as phosphoenolpyruvate (PEP), which can be used to help regenerate ATP during the reaction. In the reaction, PEP transfers a phosphate group to ADP through the enzyme pyruvate kinase, which regenerates ATP that can then be used to keep transcription and translation going. Compare prokaryotic versus eukaryotic cell-free expression systems. Choose a protein to produce in each system and explain why. Prokaryotic and eukaryotic cell-free systems each have different strengths depending on the type of protein being produced. Prokaryotic systems, like E. coli extracts, are usually faster, cheaper, and great for making simple proteins that do not need complex folding or post-translational modifications. In contrast, eukaryotic cell-free systems are better for proteins that require more advanced folding, disulfide bond formation, or modifications that bacteria cannot do well. For a prokaryotic system, a strong candidate would be Luz (luciferase) from the fungal bioluminescence pathway, since it is a relatively compact enzyme that folds well in bacterial extracts and does not require eukaryotic post-translational modifications; producing it cell-free would allow rapid screening of variants and direct assay of luminescence activity by simply adding the 3-hydroxyhispidin substrate to the reaction. For a eukaryotic system, a suitable target would be H3H (hispidin-3-hydroxylase) or another upstream enzyme in the caffeic acid–to–luciferin pathway, since these fungal oxidative enzymes often depend on proper folding, cofactor incorporation, and a eukaryotic redox environment to remain active. Expressing the pathway enzymes in their appropriate systems enables modular prototyping of the bioluminescence circuit before committing to stable plant transformation. How would you design a cell-free experiment to optimize the expression of a membrane protein? Discuss the challenges and how you would address them in your setup. To optimize expression of a membrane protein in a cell-free system, I would design the reaction so it not only makes the protein but also gives it a membrane-like environment to fold into correctly. One of the main challenges with membrane proteins is that they tend to misfold, aggregate, or precipitate because their hydrophobic regions do not stay stable in plain aqueous solution. To deal with that, I would test conditions that include detergents, liposomes, or nanodiscs so the protein has somewhere to insert during or right after translation. I would also optimize variables like magnesium concentration, temperature, reaction time, and DNA concentration, since these can strongly affect yield and folding quality. On top of that, I would check expression using something like SDS-PAGE or a tagged reporter, then compare solubility and activity across conditions. Imagine you observe a low yield of your target protein in a cell-free system. Describe three possible reasons for this and suggest a troubleshooting strategy for each. Low protein yield in a cell-free reaction can arise from numerous sources, but three common causes are the following. First, degradation of the DNA template or mRNA transcript by nucleases present in the extract can sharply reduce output. This can be addressed by switching from linear PCR products to circular plasmid DNA, adding RNase inhibitors, and verifying template integrity by gel electrophoresis before use. Second, depletion of energy substrates or accumulation of inhibitory byproducts such as inorganic phosphate can stall translation mid-reaction. This is best addressed by switching to a more robust energy regeneration system (e.g., PEP/pyruvate kinase), adjusting the starting concentrations of NTPs and amino acids, and running time course sampling to identify when the reaction plateaus. Third, poor translation efficiency caused by suboptimal codon usage, weak ribosome binding site strength, or mRNA secondary structure near the start codon can limit ribosome loading. This can be addressed by codon optimizing the gene for the extract source, redesigning the 5’ UTR and RBS using established calculators, and introducing silent mutations to disrupt inhibitory secondary structures near the translation initiation site. Homework questions from Kate Adamala Design an example of a useful synthetic minimal cell as follows:
Week 10 HW: Advanced Imaging & Measurement Technology
Homework: Final Project For your final project: Please identify at least one (ideally many) aspect(s) of your project that you will measure. It could be the mass or sequence of a protein, the presence, absence, or quantity of a biomarker, etc. For Aim 1 of my final project, there are several things I’ll need to measure, from confirming the construct is correct, to confirming the cells are expressing it, to ultimately quantifying the light output that defines success or failure of the experiment. The most important measurement is luminescence intensity from the IPTG-induced cells co-expressing nnLuz v4 truncated and nnH3H v2 after hispidin supplementation. This is the readout that directly tests my hypothesis that the v4 mutations stacked with the truncation produce a brighter enzyme pair than either modification alone. Light output alone isn’t enough without knowing the cells are actually doing what I think they’re doing, so I’ll also measure cell density (OD600) and perform a colony PCR to confirm the insert is present in transformed colonies.
Week 11 HW: Bioproduction & Cloud Labs
Part A: The 1,536 Pixel Artwork Canvas | Collective Artwork I contributed a single pixel to the bioart project. It was one of the early additions—a red pixel placed in the bottom-left quadrant, about three rows down from the top of that section. At the time, the canvas was still mostly empty, and my contribution was eventually replaced as the artwork evolved into the final design, which included the word “Love.”