Overview

"When it comes to software, I much prefer free software, because I have very seldom seen a program that has worked well enough for my needs, and having sources available can be a life-saver."

Linus Torvalds

An important part of our project was the screening for substrates All this data was generated using a Hamilton robot for liquid handling. This robot enabled us to compare the growth characteristics Yarrowia lipolytica and Saccharomyces cerevisae. Such experiments are generally a great tool, to validate the growth on particular substrates or the degradation of toxic compounds. Furthermore, they can be used to compare different strains. However, we realized that it is a technology not everyone has access to.

To challenge this, we started a hardware project aiming to develop a cheap alternative to the Hamilton robot. A small device, that would enable hackerspaces and high schools to easily acquicire and compare growth data for their projects. To make this device as cheap as possible, we reduced the Hamilton to its key features:

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Figure 1: The reference: Hamilton robot for liquid handling

Results

We managed to create a working prototype over the summer. It is stable and has all the features we aimed for. This wiki page will introduce you to the development process and enable you to recreate your own version.

The following points are the key achievements we have

• Instruction to make it for US$ 150
• Tested all functions
• Integrate feedback from prospective users
• Provide source files for other developers

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Figure 2: Our microfermentation platform

Features

The Microfermentation Platform is a simplistic device that can run up to three batch cultures, while automatically measuring OD\(_{600}\), where custom settings such as duration of experiment are determined by the user and the program is controlled by a microcontroller.

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Figure 3: Side view of the robot.

Theory

Growth rates and spectrophotometry

Basic Concept - Measuring Optical Density

When assessing growth of microorganisms, it is necessary to be able to obtain and interpret information about population size, or at least concentration at a given time. Optical Density (OD\(_{600}\)) measurement is a widely used, suitable method known by everyone familiar with biotechnology. This principle is based on spectrophotometry, where a light transmission of 600 nm passes through biological material and the resulting transmittance, \(\Phi\), is measured at the receiver end. Because biological material reflects light, higher biological density reflects more light, giving lower transmittance readings. Thus, at full transmittance, \(\Phi_{\text{ref}}\), OD\(_{600}\) should be equal to 0.

For the Microfermentation Platform, OD\(_{600}\) at time t is calculated from the Beer-Lambert law¹: $$ \text{OD}_{600,t} = -\log\Bigg(\frac{\Phi_t}{\Phi_{\text{ref}}}\Bigg) $$ Where the light source is an LED, with its intensity controlled by some input voltage, and the transmittance is measured by a sensor and recorded as a voltage.

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Figure 4: Brief outline on how spectophotometric measurements for calculation of OD\(_{600}\) are carried out by the Microfermentation Platform.

Maximal Saturation - Calibration of Light Emission

The sensor recording the transmittance has a maximal saturation level. Transmittance of higher intensity than this level will yield the same constant reading. Thus, the input voltage must be calibrated, such that the emission from the LED matches the maximal saturation level of the sensor exactly when tested under conditions considered as reference.

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Figure 5: The maximal saturation level phenomenon. The graph shows sensor reading as a function of input voltage. Only in a limited range of input voltage gives linearly increasing sensor readings. The lowest input voltage yielding the maximal sensor reading is denoted maxpwm (for ‘maximal PWM’) and the corresponding sensor reading is called refmsm (for ‘reference measurement’).

Growth Curves of Microorganisms

Growth course across species of microorganisms exhibit some common characteristic behaviour. Typically, the growth curve of a population has an initial lag phase, with limited growth, and exponential phase, where the doubling time is constant, and finally, a stationary phase, where the population capacity has been reached, either because of limitation on resources or physical space.

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Figure 6: A typical growth curve with lag, exponential and stationary phase.

User Testing

This device is meant to go out to fellow iGEMers and Hackerspaces. To validate the assumptions we had when building the prototype, we brought it to our friends from the local hackerspace Biologigaragen and our highschool student Tobias.

Higschool Student: Tobias

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Figure 7: Tobias inoculating Y. lipolytica in the cuvettes.

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Figure 8: Tobias fitting the top on the measuring chambers before starting the run.

Hackerspace: Biologigaragen

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Figure 9: Keenan from Biologigaragen taking apart the robot, literally.

Proof of Concept

The figure shows two distinct exponential phases, representing the diauxic growth of S. cerevisiae. Based on the data recorded by the Arduino, we were able to compute the growth rates, shown in Fig. 4.

Prototyping

The prototype was build using laser cutting, 3D-printing and printed custom boards (PCB). It is controlled by an Arduino UNO R3 that was programmed using the Arduino IDE. All the files are created in the native formats of open source programs. We have used the programs listed below and recomend them, as the source files are in the respective native formats.

In addition, all these programs have great communities to help, if you get stuck.

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Software

• Inkscape to create vectorgraphics for laser cutting
• FreeCAD to make CAD drawings for 3D-printing
• ArduinoIDE for programming the microcontroler
• KiCAD for PCB design

Source Files

The source files can be downloaded as compressed folders(*.zip):

• Housing and Shield
• Arduino code and libraries

History

This is a brief overview of the development history. For a chronological order, see the notebook

Starting point

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Figure 13: First experimental set-up

Together with Docent Erik Vilain Thomsen and Associate professor Martin Dufva, we developed a first prototype. In this version, a single cuvette was stirried with a small magnetic pellet in a black measuring chamber. The light intensity was regulated manualy using a very precise geared potentiometer. The microcontroler received the voltage level from the photodiode, converted it into a 10bit number and send this via USB to the laptop which wrote the output to a file.

We learned the following:

• The LED remains constant during the whole duration of the experiment, giving constant light output.
• The Arduino requires an external power supply larger than 5 V to supply stable voltages
• Magnetic stirring in a cuvette is insufficient

Martin changed the container to a small glas flask which was giving sufficient stirring and demonstrated that the measuring unit was functional. However, the measuring cell grew even bigger. In order to reach our initial goal, we continued working on our own. We wanted to keep cuvettes as containers because they are cheap and easily available. Also our design needed the following changes

• No magnetic stirring
• No manually controlled potentiometer
• Data logging on µSD-card

New concepts

We could demonstrate that aeriation via common disposable syringes and needles was possible and sufficient to homogenize a S. cerevisiae culture at a tolarable amount of foaming.

In addition, we managed to replace the potentiometer by a set of low-pass filters combined with the 8bit PMW output-pins of the Arduino. This cut down the cost for the potentiometer and enabled us to use an automatic calibration routine to find the level of saturation for the photodiode.

We designed our own measuring cell. Compared to Martin's version it has a simpler locking mechanism to hold LEDs and photodiodes in place. It is also much smaler, takes three cuvettes and has connectors for aeration.

After debugging our circuit on breadboards, we designed printed circuit boards. Ten boards only cost US$ 10, plus shipping.

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An early experiment: The two cuvettes to the right were not covered with parafilm causing most liquid to go out. The protocol was updated afterwards.

Make Your Own

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Attributions

We have worked very hard this summer to create the robot and achieved something that seemed totally out of reach only a few months ago. This would not have been possible without the help of other people. We would especially like to thank our supervisor Chris, Martin and Erik to get us started in the right direction. To see all credits, pleas go to the Attributions page.

References

1. Beer-Lambert Law