Post Lab Questions | Mandatory for All Students

One of the great parts about having an automated robot is being able to precisely mix, deposit, and run reactions without much intervention. This year, a greater emphasis will be placed on utilizing the Opentrons to accelerate your final projects.

For this week, we’d like for you to do the following

1. Write a description about what you intend to do with automation tools for your final project. You may include example pseudocode or Python scripts, procedures you may need to automate, 3D printed holders you may need, and more.
2. Find and describe a published paper that utilizes the Opentrons or similar automation tools to achieve novel biological applications (eg automated PACE)

While your idea doesn’t need to be set in stone, we would like to see core details of what you would automate. This is due right before class and does not need to be tested on the Opentrons for now.

Automation in My Final Project

For my final project, I plan to integrate automation tools to streamline biological experiments and enhance efficiency in data collection and analysis. Specifically, I aim to utilize Opentrons, a widely used open-source liquid-handling robot, to automate experimental procedures related to e-textiles, biofabrication, or synthetic biology.

Key Automation Goals

1. Automating Pipetting Procedures
   • Reduce human error in liquid handling.
   • Improve consistency in sample preparation and reagent distribution.
   • Example: Automating PCR setup or DNA assembly workflows.
2. Integrating Real-time Data Collection
   • Use sensors to monitor experimental conditions (e.g., pH, temperature).
   • Automate the logging and analysis of results via Python scripts.
3. 3D-Printed Holders for Experimental Components
   • Design and print custom racks for holding reaction tubes, microfluidic chips, or textile samples.
   • Ensure precise positioning for robotic arms and sensors.

Example Pseudocode for Automated Pipetting

python
CopyEdit
from opentrons import protocol_api

metadata = {'apiLevel': '2.0'}

def run(protocol: protocol_api.ProtocolContext):
    # Define pipette and labware
    tip_rack = protocol.load_labware('opentrons_96_tiprack_300ul', 1)
    plate = protocol.load_labware('corning_96_wellplate_360ul_flat', 2)
    pipette = protocol.load_instrument('p300_single', 'right', tip_racks=[tip_rack])

    # Pipetting procedure: Transfer 50µl from well A1 to B1
    pipette.pick_up_tip()
    pipette.aspirate(50, plate['A1'])
    pipette.dispense(50, plate['B1'])
    pipette.drop_tip()

Future Enhancements

• Implement computer vision for real-time quality control.
• Utilize machine learning for optimizing reaction conditions.
• Develop custom GUI interfaces for experiment monitoring.

This project will leverage automation to increase reproducibility, minimize human intervention, and enhance experimental efficiency.