About This Project

We're studying how yeasts make decisions about their cellular fate during mating, a process that involves the integration of information with opposing effects.

To study how cells choose between mating and asexual reproduction, we observe and track single cells using automated time-course microscopy, over many different conditions.

To gain a deeper understanding of this process, we need a massive amount of data, and new open hardware tools, that also enable any lab to make these discoveries.

Ask the Scientists

What is the context of this research?

Our experiment requires observing several yeast strains over many conditions, which scales rapidly to dozens or hundreds of combinations.

Even though robots for automated high-throughput experiments have been built for experiments, but are closed source and prohibitively expensive.

Our open hardware pipetting robot already automates the preparations, but only prepare one condition at a time. This means that it still takes too long, and we often miss the decision making event, sometimes by hours.

Recently Edwin's nano-positioner project provided the ultimate solution. We can reuse the miniature piezoelectric devices to power 96-channel pipettes, and enable high-throughput experimentation on all pipetting robots.

What is the significance of this project?

Understanding cell biology is the key for next generation medicine and biotechnology. It is, however, a very complex system, and it is also hard to observe quantitatively. To face this challenge we need better and also affordable tools, enabling the average molecular biology lab to acquire them.

A 96-channel micropipette will make preparations a hundred times faster, which will let us catch every detail of the decision making process, and provide the data we need to understand it.

This project will conclude with the publication of open assembly documentation and design files for our tool. In this way, labs all over the world will be able to acquire or build it for a small fraction of the cost of proprietary devices.

What are the goals of the project?

Our first objective is to build a 96-channel micropipette with independently controlled channels, expanding the frontier of automation to reach science labs
everywhere.

We will then use the tool to prepare a 384-well microscopy plate with 16 yeast strains, over 48 experimental conditions. This will reduce the preparation time from hours to minutes, letting us observe the phenomena during its timescale, in high resolution.

The images will then be processed to identify single cells in the microscopy images, track them over time, and derive quantitative data (signal intensity, distribution, cell morphology, and cell-cycle events). Automated inference techniques will process the vast data, and extract causal new relationships explaining more of the cell's biology.