Homework
Weekly homework submissions:
PRE-LECTURE ABOUT CLASS 2 SLIDES ABOUT PROFESSOR JACOBSON -Question 1 When biological polymerase copies DNA, it makes about 1 mistake per million base pairs (1:10^6).Since the human genome has around 3.2 billion base pairs, that error rate would mean every time one of my cells divides, it would introduce over 3,000 mistakes if there weren’t any correction mechanisms. There’s a 3’-5’ exonuclease that catches and removes errors during DNA synthesis, and then the MutS repair system acts as a backup to fix any mismatches that slipped through afterward. Together, these mechanisms keep my genetic information stable across cell divisions.
Week 1 HW: Principles and Practices
- Biological engineering application: The development of various therapies in which they employ stem cells in Peru, to treat neurodegenerative diseases and chronic diseases. Along with this the appropriate regulations for this type of therapy. -> Why I chose this application: Because in Peru there is an increase in the development of various clinical therapies for diseases that have been very expensive to access, so the emergence of stem cell applications are recent. This is also due to a problem, this is more than anything focused on the little regulation on this type of treatment, which limits the creation of more trained centers, generating a delay in the access of new therapies and research.
Paper: Accelerated high-throughput imaging and phenotyping system for small organisms Link: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0287739 This paper details the creation of a high-throughput experimentation (HTE) platform built around duckweeds — specifically Lemna minor, a tiny aquatic plant with applications in bioremediation and biofuel research. To run large-scale evolutionary ecology experiments, the team combined an Opentrons OT-2 liquid handling robot with a custom autonomous imaging system, creating a pipeline capable of operating at a scale that would be practically impossible by hand. The central engineering challenge was that standard liquid handling robots are designed to work with, unsurprisingly, liquids. Duckweeds are solid floating plant fronds, which meant the OT-2 needed to be rethought for a very different kind of material. The researchers solved this by replacing the standard pipette tips on the OT-2’s P300 pipette heads with commercial inoculation loops. These loops exploit capillary action to gently lift individual fronds from the water’s surface, allowing the robot to pick and place solid biological matter with the same reliability it would otherwise bring to liquid transfers. This seemingly simple hardware modification had enormous practical consequences. By enabling automated handling of the plants, the team was able to design an experiment encompassing 6,000 individual microcosms spread across 2,000 distinct combinations of nutrients and microbes — a scale of experimental complexity that manual pipetting and plant placement could never realistically achieve, given how tedious and error-prone working with tiny floating organisms at high volume would be for human researchers.
Week 2 HW: DNA READ, WRITE, & EDIT
DNA Design Challenge Protein: GFP (Green Fluorescent Protein) Reason: Because GFP is commonly used as a biological marker to visualize various cellular processes due to its green fluorescence. sp|P42212|GFP_AEQVI Green fluorescent protein OS=Aequorea victoria OX=6100 GN=GFP PE=1 SV=1 MSKGEELFTGVVPILVELDGDVNGHKFSVSGEGEGDATYGKLTLKFICTTGKLPVPWPTL VTTFSYGVQCFSRYPDHMKQHDFFKSAMPEGYVQERTIFFKDDGNYKTRAEVKFEGDTLV NRIELKGIDFKEDGNILGHKLEYNYNSHNVYIMADKQKNGIKVNFKIRHNIEDGSVQLAD HYQQNTPIGDGPVLLPDNHYLSTQSALSKDPNEKRDHMVLLEFVTAAGITHGMDELYK Reverse Translate: Protein (amino acid) sequence to DNA (nucleotide) sequence GFP DNA >ATGTCCAAGGGTGAGGAGCTGTTTACCGGCGTGGTTCCGATTCTTGTGGAATTAGACGGCGATGTCAACGGCCACTTCTCCGTTTCT GGCGAGGGCGAGGGAGGCGACGCCACGTATGGCAAATTGACCCTGAAGTTTATTTGCACGACCGGAAAATTGCCTGTACCGTGGCCCACACTTTGGT CACTACCGTTATCAATGTTTCTCGCTATCCGGACCACATGAAGCAGCATGACTTCTTTAAAAGTGCAATGCCCGAGGGTTATGTTCAAGAGCGGACCA TCTTTTTTAAAAGACGACGGCAACTACAAGACGCGCGAGGTGAAGTTCGAGGGCGACACGCTGGTGAATCGGATTGAGTTAAAAGGAATTGACTTTAA AAGATGACGGCAACATCCTTGGACATAAGTTAGAGTACAATTATAATTCAAACCACGTGTACATCATGGCCGACAAACAAAAAAACGGCATCAAGGTA AACTTTAAAATTAGACATAATATCGAGGATGGCAGTGTTCAATTAGCCGACCATTACCAACAGAACACCGATAGGCGGACGGTCCTGTATTACCTGAC AACCATTACCTTAGCACGCAGTCTGCACTGTCCAAGGACCCAAATGAGAAACGAGGACCATATGGTGTTGCTAGAGTTCGTTACCGCAGCAGGAATAAC Codon optimization The selected organism: Escherichia coli (E. coli) Reason: This is because E. coli is a common model organism for the production of recombinant proteins due to its speed, low cost and ease of manipulation.