Homework
Weekly homework submissions:
Week 1 HW: Principles and Practices
- First, describe a biological engineering application or tool you want to develop and why. My plan for the final project is a synthetic membrane that has Mesenchymal Stem Cells Microvesicules (which have scientifically proven regenerative and other positive properties) intercalating inbetween the membrane’s layers. Which could be used for burn wounds and/or donation organs preservation while in transportation.
Week 2 HW: DNA Read Write and Edit
Part 1: Benchling & In-silico Gel Art: Simulate Restriction Enzyme Digestion with the following Enzymes: Create a pattern/image in the style of Paul Vanouse’s Latent Figure Protocol artworks. I tried to make a pattern that looked like a staircase going down by using logic but couldn’t quite seem to get it right…
Part 1: Python Script for Opentrons Artwork I used Ronan’s provided GUI and a nice little pixelart of a kidney to try out the design and figure out coordinates. Python coding was new and quite… surprising. But using the toad.py provided by the USFQ node I figured out how to get the code to work. This is a kidney art that i’ll try to print. Hopefully it actually resembles something!
Part A. Conceptual Questions How many molecules of amino acids do you take with a piece of 500 grams of meat? Roughly 3 x 10^24 individual amino acid molecules. 1- Why do humans eat beef but do not become a cow, eat fish but do not become fish? Because digestion is a disassembly line. We completely chop up their proteins into individual amino acid building blocks, then use our own DNA blueprints to rebuild them into human.
Week 5 HW: Protein Design Part II
Part A: SOD1 Binder Peptide Design (From Pranam) Part 1: Generate Binders with PepMLM Uniprot (P00441) Sequence: MATKAVCVLKGDGPVQGIINFEQKESNGPVKVWGSIKGLTEGLHGFHVHEFGDNTAGCTSAGPHFNPLSRKHGGPKDEERHVGDLGNVTADKDGVADVSIEDSVISLSGDHCIIGRTLVVHEKADDLGKGGNEESTKTGNAGSRLACGVIGIAQ Mutated (A4V) Sequence: MATVKAVCVLKGDGPVQGIINFEQKESNGPVKVWGSIKGLTEGLHGFHVHEFGDNTAGCTSAGPHFNPLSRKHGGPKDEERHVGDLGNVTADKDGVADVSIEDSVISLSGDHCIIGRTLVVHEKADDLGKGGNEESTKTGNAGSRLACGVIGIAQ The peptides are as follow: Index Binder Pseudo Perplexity 1 WHYYAAALAHKX 10.964450319068074 2 WHVVAAAVRWKE 20.08596911389436 3 KHYPVVAAELKX 8.536125306474528 4 HHSVVVALRHGE 18.149273540792894 5 FLYRWLPSRRGG n/a I’ll change the X’es to A (alanines) since Alphafold doesn’t allow X’es.
Week 6 HW: Genetic Circuits Part I: Assembly Technologies
Assignment: DNA Assembly 1. What are some components in the Phusion High-Fidelity PCR Master Mix and what is their purpose? Phusion High-Fidelity PCR Master Mix Components: Phusion DNA Polymerase: A high-accuracy enzyme with 3′→5′ exonuclease (proofreading) activity that minimizes mutations during amplification dNTPs (Deoxynucleotide Triphosphates): The nucleotide building blocks (A, T, C, G) used to synthesize the new DNA strand.
Week 7 HW: Genetic Circuits Part II: Neuromorphic Circuits
Assignment Part 1: Intracellular Artificial Neural Networks (IANNs) 1. What advantages do IANNs have over traditional genetic circuits, whose input/output behaviors are Boolean functions? Intracellular Artificial Neural Networks (IANNs) transcend the limitations of binary Boolean logic by enabling analog and graded signal processing within a cell. While traditional genetic gates are restricted to “ON/OFF” states, IANNs can integrate multiple continuous environmental inputs and assign them specific “weights,” allowing the cell to make nuanced decisions based on a threshold of combined signals. This analog capability is particularly superior for pattern recognition and processing complex biomarkers, as it mimics natural biological decision-making more closely than rigid digital circuits. Furthermore, IANNs can often achieve high levels of computational complexity with fewer genetic parts, as they leverage the inherent non-linearities of biochemical reactions as natural “activation functions,” thereby reducing the metabolic burden on the host organism compared to massive, multi-gate Boolean architectures.
General homework questions 1- 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. In traditional in vivo (inside the cell) methods, the cell’s own survival is the priority. In CFPS, your protein is the priority. You can add non-natural amino acids, chaperones, or labeling molecules directly to the mix without worrying about transport across a cell membrane. You can monitor and tweak variables like pH, temperature, and redox potential in real-time. If a protein is lethal to a living cell (e.g., a pore-forming toxin), CFPS is the only way to produce it because there is no “cell” to kill. You can go from a linear DNA template (PCR product) to a protein in hours, whereas cell production requires days for cloning and transformation.
Week 11 HW: Bioproduction and Cloud Labs
Part A: The 1,536 Pixel Artwork Canvas | Collective Artwork I missed the date to contribute :c Will try my best to become a TA next year! Part B: Cell-Free Protein Synthesis | Cell-Free Reagents Referencing the cell-free protein synthesis reaction composition (the middle box outlined in yellow on the image above, also listed below), provide a 1-2 sentence description of what each component’s role is in the cell-free reaction. Component Roles Component Category and their role in the Reaction: