Homeworktype: chapter

Weekly homework submissions:

  1. Biological Engineering Application This project proposes the development of an intestinal spheroid culture platform derived from cell lines (e.g., Caco-2 spheroid or organoid-like cultures), combined with multi-omics profiling (transcriptomics, proteomics, and metabolomics) computational modeling using systems biology and machine-learning approaches. The platform is intended to support research on drug absorption, inflammatory bowel disease (IBD) diagnostics, and predictive analysis of treatment outcomes. Initially, the system will be used to generate hypotheses from experimental data, with the long-term goal of becoming a predictive research tool.

  • Week 2 HW: DNA Read, Write, & Edit

    1-Benchling-in-silico-gel-art Using Benchling.com, Lambda DNA, Paul Vanouse’s Latent Figure Protocol artworks, and Ronan’s website as references, and incorporating creative design principles, simulations of restriction enzyme digests of the Lambda genome were performed using EcoRI, HindIII, BamHI, KpnI, EcoRV, SacI, and SalI: Figure 1. Virtual restriction digest of Lambda DNA. Once the banding patterns were characterized, images inspired by the previously mentioned works were created:

  • Week 3 HW: Lab automation

    Assignment: Python Script for Opentrons Artwork Based on the Lissajous function, the figure to be created on the agar will be the following: Post-Lab Questions — DUE BY START OF FEB 24 LECTURE Paper: Automation of biochemical assays using an open-sourced, inexpensive robotic liquid handler Moukarzel et al. 2024

  • Week 4 HW: protein desing part 1

    Part A. Conceptual Questions 1. How many molecules of amino acids do you take with a piece of 500 grams of meat? (on average an amino acid is ~100 Daltons) If we assume that meat contains approximately 20% protein, then 500 g of meat provides around 100 g of protein. Since the average molecular weight of an amino acid is approximately 100 Daltons (approx 100 g/mol), that 100 g corresponds to approximately 1 mole of amino acids. One mole contains approx 6.02 × 10²³ molecules, so you would ingest approximately 6 × 10²³ molecules of amino acids.

  1. Why do humans eat beef but do not become a cow, eat fish but do not become fish? Because when we eat meat, the animal’s proteins (from cows, fish, etc.) are not incorporated intact into our bodies. Instead, they are digested in the gastrointestinal tract into their basic components: amino acids and small peptides. These are absorbed, and then our own cells reuse them to synthesize human proteins according to the information encoded in our DNA. In other words, we don’t incorporate the “biological identity” of the animal we eat, but rather molecular raw material that our genome reorganizes according to the instructions specific to the human species.
  2. Why are there only 20 natural amino acids? There are only 20 standard “natural” amino acids because the universal genetic code that has evolved encodes precisely these 20 building blocks for protein synthesis (with rare exceptions such as selenocysteine and pyrrolysine). This selection is not chemical but evolutionary: among many possible molecules, these 20 offered an optimal balance between structural diversity (charges, sizes, polarity, hydrophobicity), chemical stability, and biosynthetic efficiency. With this set, an enormous variety of protein structures and functions can be generated, so evolution did not need to significantly expand the basic alphabet to support biological complexity.
  3. Can you make other non-natural amino acids? Design some new amino acids. Yes, it is possible to create non-natural amino acids both chemically and by expanding the genetic code in biological systems. From a design perspective, it is sufficient to maintain the α-amino acid backbone (amino group, carboxyl group, and chiral α-carbon) and modify the side chain to introduce new physicochemical properties. For example, one could design (1) an amino acid with a bulky fluorinated side group to increase hydrophobic stability and resistance to degradation, (2) one with a photoreactive side chain (such as an azide or diazirine group) to allow light-induced cross-linking, (3) an amino acid with a chelating metal group to create artificial catalytic sites, or (4) one with a redox-active side chain capable of participating in electron transfer. In fact, synthetic biology has already incorporated hundreds of non-natural amino acids into proteins through reassigned codons or modified tRNA/synthetase systems, functionally expanding the protein “alphabet” beyond the standard 20.
  4. Where did amino acids come from before enzymes that make them, and before life started? Before enzymes and cellular life existed, amino acids could have formed through abiotic prebiotic chemistry. Classic experiments like the Miller-Urey experiment demonstrated that, under conditions simulating the early atmosphere (simple gases such as methane, ammonia, water vapor, and electrical discharges), several amino acids can be spontaneously synthesized. Furthermore, amino acids have been found in meteorites such as the Murchison meteorite, indicating that they can also form in space through interstellar chemistry and then reach Earth via impacts. Other possible environments include oceanic hydrothermal vents and mineral surfaces that catalyze organic reactions. Taken together, the evidence suggests that amino acids arose through natural physicochemical processes before the emergence of enzymes and were part of the molecular inventory that preceded the origin of life.
  5. If you make an α-helix using D-amino acids, what handedness (right or left) would you expect? If you build an α-helix exclusively from D-amino acids, you would expect it to adopt a left-handed helix. In natural proteins made from L-amino acids, the stable α-helix is typically right-handed due to stereochemical constraints of the α-carbon and the allowed φ and ψ angles in conformational space. By inverting the chirality (using D instead of L), the geometric preference for folding is also reversed, producing the mirror image: a stable α-helix but with the opposite orientation.
  6. Can you discover additional helices in proteins? Yes, in principle, additional helices beyond the classical conformations can be discovered or engineered. Helical conformation depends on the allowed φ/ψ angles, hydrogen bonding patterns, and the chemistry of the peptide backbone. Modifying these variables, for example, by using non-natural amino acids, changing the backbone length, or applying specific steric constraints, can lead to the emergence of new, stable helical geometries. In fact, helical architectures not commonly found in natural proteins have been observed in synthetic peptides and foldamers. However, within proteins composed of the 20 standard amino acids and the natural peptide backbone, the repertoire of helices is strongly restricted by the stereochemistry and physics of the peptide bond, so additional variants tend to be rare or less stable.
  7. Why are most molecular helices right-handed? Most molecular helices are right-handed because they are built from chiral building blocks with a predominant stereochemical configuration. In terrestrial biology, almost all amino acids are L-shaped, and this chirality imposes specific geometric constraints on the angles of the peptide backbone, favoring a right-handed α-helix as the most energetically and sterically stable conformation. In other words, the molecular asymmetry of the monomers is amplified at the macroscopic level in the secondary structure. If life had predominantly adopted D-amino acids, the predominant helices would most likely have been left-handed.
  8. Why do β-sheets tend to aggregate? What is the driving force for β-sheet aggregation? β-sheets tend to aggregate because their geometry exposes repeating patterns of amide and carbonyl groups in the backbone that can form extensive networks of intermolecular hydrogen bonds. When several polypeptide chains adopt extended conformations, they can readily align and stabilize each other through these bonds, forming larger sheets and, in extreme cases, amyloid-like fibrils. The primary driving force for aggregation is the minimization of the system’s free energy: the cooperative formation of hydrogen bonds, along with hydrophobic interactions between side chains and the burial of nonpolar surfaces, offsets the entropic cost of ordering the chains. Taken together, geometric complementarity and intermolecular stabilization make β-sheets particularly prone to aggregation when they are partially unfolded or misfolded.

  • Week 5 HW: protein desing part 2

    Homework — DUE BY START OF MAR 10 LECTURE Part A: SOD1 Binder Peptide Design (From Pranam) Introduction Superoxide dismutase 1 (SOD1) is a cytosolic antioxidant enzyme that converts superoxide radicals into hydrogen peroxide and oxygen. In its native state, it forms a stable homodimer and binds copper and zinc. Mutations in SOD1 cause familial Amyotrophic Lateral Sclerosis (ALS). Among them, the A4V mutation (Alanine → Valine at residue 4) leads to one of the most aggressive forms of the disease. The mutation subtly destabilizes the N-terminus, perturbs folding energetics, and promotes toxic aggregation.

  • Week 6 HW: genetic-circuits-part-i

    Assignment: DNA Assembly What are some components in the Phusion High-Fidelity PCR Master Mix and what is their purpose? Phusion High-Fidelity PCR Master Mix is a pre-mixed PCR solution containing several essential components for high-precision DNA amplification. Its main components and functions are:

  • Week 7 HW: genetic-circuits-part-ii

    Task Part 1: Intracellular Artificial Neural Networks (IANN) 1. Advantages of IANNs vs. Boolean Logic Continuous/gradual response (not just ON/OFF) Integrate multiple weighted signals (weighted sum type) Allow thresholds, nonlinearity, and fine-tuning Greater robustness to biological noise Scalability for complex functions (not just AND/OR) 2. Useful Application (example: intelligent intestinal biosensor) Input: X1 = microbial metabolites (SCFAs) X2 = inflammatory signal (NF-κB) X3 = drug present Behavior: The IANN integrates signals → calculates an “activation” If it exceeds the threshold → activates the expression of a therapeutic (or fluorescent) protein

  • Week 9 HW: Cell-Free Sistem

    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 offers key advantages over in vivo systems by eliminating the complexity and limitations of the cell as a “black box.” In these systems, all components are defined and manipulable, allowing direct control over variables such as DNA concentrations, expression levels, biochemical composition, cofactors, and reaction conditions. In fact, expression can be precisely adjusted simply by varying the DNA concentration, achieving proportional regulation of each protein—something difficult to achieve in living cells. Furthermore, the system is fully customizable, allowing modification of the internal chemistry and each molecular component, which provides a level of experimental control and predictability far superior to that of traditional cell systems.

  • Week 10 HW: imaging and measurement

    Proposed set of measurements to be implemented in the project, subject to refinement as the study progresses. Homework: Waters Part I — Molecular Weight Based on the predicted amino acid sequence of eGFP (see below) and any known modifications, what is the calculated molecular weight? You can use an online calculator like the one at https://web.expasy.org/compute_pi/ 28,006.6 Da. It is calculated by summing the average masses of all amino acids in the sequence, including the His-tag, and accounting for water loss during peptide bond formation. No major modifications significantly change the total mass, so this value matches the expected intact mass of eGFP.

  • Week 11 HW: building-genomes

    Part A: The 1,536 Pixel Artwork Canvas | Collective Artwork what about this collaborative art experiment could be made better for next year. I didn’t have the opportunity to contribute. I think it would be useful to design a protocol with https://rcdonovan.com and then calculate the volumes per well, concentrations, or data that can be used later.