Week 3 HW: Lab Automation

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Week 3: Lab Automation

Lab Automation assignment

This week, we explored lab automation and its applications in synthetic biology.

1. Assignment: Python Script for Opentrons Artwork

I designed a “Pac-Man” themed piece of Bio-Art for the Opentrons OT-2 robot. The design features Pac-Man and several ghosts, mapped onto a circular canvas representing the output of the lab’s liquid handling.

Google Colab Link: HTGAA Week 3 - Pac-Man Opentrons Art

Art Preview: Pac-Man Opentrons Art Pac-Man Opentrons Art

Python Script Logic: The script iterates through a matrix of coordinates, assigning specific colored liquids (Yellow for Pac-Man, Red/Blue/Cyan/Orange for ghosts) to designated wells. I used the Opentrons Python API (v2) to handle the aspirate and dispense operations with the P300 single-channel pipette.

2. Post-Lab Questions

1. Published Paper Review

Paper: Direct SARS-CoV-2 detection using a portable, open-source robotic platform (Yue et al., Matter, 2021) Summary: This research describes the development of a fully automated, portable diagnostic platform for SARS-CoV-2 using the Opentrons OT-2 robot. It integrates CRISPR-Cas12a based detection (a “novel biological application”) with robotic liquid handling to perform sensitive and rapid virus screening. Novelty: The platform automates the entire process from sample preparation to fluorescence readout. By using an open-source robot like the OT-2, the authors created a system that is significantly more affordable and flexible than traditional diagnostic workstations. This demonstrates how automation can be deployed in “the field” or in resource-limited settings for high-stakes biological monitoring.

2. Automation for Final Project

For my final project, I am interested in optimizing LuxR-based biosensors. I intend to use automation to:

  1. High-Throughput Screening: Characterize dozens of LuxR variants against a library of AHL (Acyl-homoserine lactone) analogs.
  2. Serial Dilutions: Automatically perform precise serial dilutions of AHLs to calculate dose-response curves (EC50) for each variant.
  3. Combinatorial Mixing: Mix different signaling components to study crosstalk in multi-channel quorum sensing circuits.

Pseudocode Idea:

# Pseudo-code for LuxR sensitivity screening
concentrations = [0, 1e-9, 1e-8, 1e-7, 1e-6, 1e-5] # Molar
variants = ['LuxR_WT', 'LuxR_V1', 'LuxR_V2']

for variant in variants:
    for conc in concentrations:
        mix_variant_with_ahl(variant, conc)
        measure_fluorescence() # Integrated with reader

3. Final Project Ideas

As part of the assignment, I have proposed the following three directions for my individual final project:

  1. AI-Guided Evolution of LuxR Biosensors:
    • Using the LLR (Log-Likelihood Ratio) and sequence analysis I’ve been working on to predict mutations.
    • Using automation to screen these variants for shifted specificity.
  2. Automated Cell-Free Prototyping of Quorum Sensing Circuits:
    • Bypassing the cell transformation loop by testing LuxR-responsive promoters in a cell-free expression system.
    • Leveraging Opentrons for setup.
  3. Biological “Log” Memory via DNA Synthesis:
    • Designing a DNA synthesis cassette (like the one I designed for LuxR) that “records” chemical exposures into a DNA sequence that can be read out later.