Homework
Weekly homework submissions:
Week 1 HW: Principles and Practices
NiMap-S: An Engineered Streptomyces System for Mapping and Monitoring Nickel Contaminated Areas In this project I propose NiMap-S, a synthetic microbial biosensor system designed to identify local patterns of nickel contamination in soil. The system is based on a genetically modified, soil native Streptomyces strain that functions as a biological reporter. Streptomyces is selected because it is already well adapted to soil environments and because its rich secondary metabolism allows sensing and reporting functions to be integrated without introducing a completely foreign organism into the soil ecosystem. The engineered bacteria are intended to be physically contained within biodegradable biobeads, allowing controlled interaction with the surrounding soil while limiting dispersal. In NiMap-S, bioavailable nickel ions (Ni2+) are detected through a nickel-responsive genetic circuit in which metal sensing is coupled to regulated expression of a methyl salicylate biosynthesis pathway. As local nickel availability increases, the circuit drives a corresponding increase in the production and release of methyl salicylate (C8H8O3), a volatile compound commonly involved in plant signalling. This chemical output is chosen intentionally, as it enables nondestructive sensing and creates a functional link between microbial detection and existing plant-soil communication processes. One of the main limitations of phytoremediation is limited information on how contaminants are distributed across an area. Soil contamination is spatially heterogeneous, yet existing analysis methods rely on destructive sampling, slow laboratory workflows, limited information, and high costs when applied at field scale. As a result, remediation strategies are often applied uniformly, even when contamination varies sharply across short distances. NiMap-S is therefore conceived as a premapping system that operates before phytoremediation plants, such as sunflowers, are introduced. The system generates a chemical heat map of bioavailable nickel hotspots across the field. These signals can be detected using low-altitude drone platforms equipped with gas-sensing instruments that are already used in environmental monitoring. Importantly, the choice of methyl salicylate avoids reliance on speculative or custom built detection hardware, grounding the system by utilizing approaches that are already in practical use. NiMap-S makes it possible to adjust remediation inputs with greater precision, for example by applying chelators only where and in the amounts needed, selecting appropriate plant varieties for specific locations, reducing unnecessary inputs, and overall remediation costs. Conceptual overview of the NiMap-S system
Week 2 HW: DNA Read, Write & Edit
Part 1: Gel Art I searched for the lambda DNA sequence registered in NCBI using its RefSeq accession number and clicked import. Then I selected the enzymes listed on the HTGAA site and added them to the tool. After clicking Run digest, a lot of restrictions appeared and the sequences were too short. I realized I was not supposed to select all enzymes at once because the system used all at the same time, so I ran each digestion separately.
Part 1: Python Script for Opentrons Artwork First, I created my design on the website and drew a bacteriophage Then, I copied the coordinates of my design I also published my design to the gallery. After that, I went to colab
Week 4 HW: Protein Design Part I
Part A. Conceptual Questions 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) Most red meat contains about 20% protein, so 500 g of meat contains roughly 100 g of protein. Since 1 Da=1.66×10-24 g, an amino acid with a mass of about 100 Da has a mass of 1.66×10-22 g. Dividing 100 g by 1.66×10-22 g gives approximately 6×1023 amino acids.
Week 5 HW: Protein Design Part II
SOD1 Binder Peptide Design (From Pranam) Part 1: Generate Binders with PepMLM Colab link: https://colab.research.google.com/drive/1_l-gF1EFDOHIyetFlJT4wAGmYJr-raXB Sequence (non-mutated): MATKAVCVLKGDGPVQGIINFEQKESNGPVKVWGSIKGLTEGLHGFHVHEFGDNTAGCTSAGPHFNPLSRKHGGPKDEERHVGDLGNVTADKDGVADVSIEDSVISLSGDHCIIGRTLVVHEKADDLGKGGNEESTKTGNAGSRLACGVIGIAQ Sequence (A4V): MATKVVCVLKGDGPVQGIINFEQKESNGPVKVWGSIKGLTEGLHGFHVHEFGDNTAGCTSAGPHFNPLSRKHGGPKDEERHVGDLGNVTADKDGVADVSIEDSVISLSGDHCIIGRTLVVHEKADDLGKGGNEESTKTGNAGSRLACGVIGIAQ Peptide Sequence Perplexity Peptide 1 WHHVYAAAAEWG 11.965 Peptide 2 WRYYAVVVALGA 14.209 Peptide 3 WHYPVTGAELKA 9.093 Peptide 4 WRPYAVALEHKE 13.523 Known peptide FLYRWLPSRRGG - Part 2: Evaluate Binders with AlphaFold3