Difference between revisions of "Team:Sheffield/Hardware"

Introduction

Current, common lab equipment is very expensive. Due to this, some labs that have a smaller budget are limited with the amount of equipment they are able to provide, and as the equipment is very expensive to replace, labs that do have many pieces of equipment rarely update this machinery, resulting in outdated hardware and software.

Our team wanted to devise a solution for this problem, and thus we started investigating the different types of methods currently employed for the detection of bacterial growth. This is a relatively simple experiment, which we believe everyone should be able to perform without the need for expensive lab equipment. This will then allow future iGEM teams, who perhaps do not have access to these technologies, to be able to build and design this device from our open-source manual. Other teams will then be able to perform essential experiments for the development of their projects, without the need for a large sum of money.

We focused on detection methods that could be adjusted to allow us to make automated measurements within a warm room. We felt this was important as one of our desired applications was to be able to use this device for overnight experiments, giving us the freedom to run more experiments with the bacteria day-to-day.

Detection Methods

Detection methods that we considered are listed in the table below:

Table 1: This table shows the different types of methods that are able to detect bacterial growth that we investigated.

Impedance microbiology involves using electrodes to measure the electrical resistance through a bacterial solution. As the bacteria grow the resistance changes.

The measurement of capacitance also involves using electrodes to measure the amount of stored electrical charge across the bacterial solution. As the bacteria grow the capacitance increases.

Opacity refers to the transmittance of light through a sample. As the bacteria grow, the solution becomes more turbid and less light is transmitted through the sample which can be detected by a light-sensitive sensor.

Light Microscopy refers to the viewing of small objects, bacteria in this case, at a magnified view with the use of lenses. A camera could then be set up to take automated photos of the bacteria which allows the user to watch them grow over time.

A pH meter can be used to measure the pH increases during bacterial growth.

Impedance Microbiology:

One of the methods we considered using to measure the bacterial growth was by measuring the change of the impedance, or the electrical resistance, across the bacterial sample. As bacteria grow they release soluble ionic compounds, known as electrolytes, into their growth medium. As the concentration of the electrolytes in the solution increases the impedance of the solution decreases. As a result, this decrease in impedance has a direct correlation to the increase in the number of bacterial and can be quite sensitive (Grossi et al., 2008). As electronic components can be relatively cheap to source, our team investigated whether the construction of a low-cost impedance microbiology kit would be feasible to implement.

To investigate the feasibility of this idea we decided to run a Monte Carlo simulation to see sample resistance curves with bacterial growth for various types of bacteria. We derived a model from literature to show expected resistance changes for our sample size and used well plate data to determine parameters such as expected final bacterial number.

Figure 1: This graph shows how various different bacteria with different specific growth rates could affect the change in resistance of the solution as the bacteria grow.

As you can see the resistance changes are on the micro-ohm scale. These small changes are very difficult to measure accurately at a low cost so we decided not to pursue impedance as a measure of bacterial growth.

Capacitance:

After realising that measuring the change in impedance would not be feasible, we could use similar equipment to measure the capacitance of the bacterial solution instead. Capacitance occurs when two conductor plates (ie: able to transmit electric current) are separated by an insulator, and a current is applied to the conductors, creating an electric field between the plates; with positive charge collecting on one plate and the negative charge collecting on the other (Miller and Simon, 2008).

Figure 2: shows how an electric field is produced across the two plates after a current has been applied to them.

When a pair of electrodes are placed into an electrolyte solution a charge separation occurs across the interface of the electrodes, which is analogous to that of a capacitor. This is where charge separation, and therefore capacitance is developed in the solution. As the bacteria grow, an increase of electrolytes are released into the solution, and this causes the capacitance to increase as the bacteria grow (Zourob, Elwary and Turner, 2008).

However as with the impedance design, due to the very small size of a well in a 96 well-plate, the change of capacitance across the solution will be minuscule and therefore would require very expensive, sensitive equipment with a very precise set-up to be able to read the capacitance changes. For this reason, we investigated other detection methods that would be suitable for a low budget, open-source project design.

Opacity:

One other method of measurement that we looked at was opacity, or rather, the transmittance of light through a sample. As bacteria grow, the turbidity of the solution increases. We can measure this change by measuring the transmittance of light through the solution. This principle is used in both plate readers and spectrophotometers.

As we wanted a device to make measurements from our well plate, we will focus on the discussion of a standard well plate reader vs. our device. Plate readers have an automated x,y stage which moves a plate, well-by-well, over a single sensor, usually a silicon photodiode. This is placed directly underneath a light source, which is usually a tungsten halogen lamp or a xenon flash lamp, as both these light sources are able to produce a high-quality range of wavelengths.

For our device, we didn’t want to create an automated x,y stage as this can be time-consuming, costly, and confusing to build from for a simple open-source project. Instead, we thought it would be best to create an array of photodiodes that can align with each well of the well plate. We then placed an array of white LEDs directly above the well plate, so that light from an LED can shine through a well directly beneath in and onto a sensor located under the well.

This set up of photodiode array are described in more detail in the sensors section below.

Light Source

In order to achieve a reliable and affordable light source, we investigated multiple options. These included Light Emitting Diodes (LEDs), an Electroluminescent (EL) Panel and a standard halogen lamp. The advantages and disadvantages are shown in the table below.

Table 2: This table shows the different light sources that we investigated for use in our device.

All light sources considered were capable of emitting white light. However, for detecting the concentration of bacteria in a sample, a light of wavelength 600nm is required. At this length, the waves get scattered by the bacteria in the solution, causing a much greater change in light detected by the sensors under the wells. As such, the chosen light source was provided with a plastic “orange” filter that only allowed 600nm waves to filter through.

Alternatively, plate readers allow for the measurement of a multitude of types of biological experiments such as protein and enzyme assays. Our device then requires different filters for alternative wavelengths to allow for use as an affordable plate reader. Fortunately, these plastic filters with specifically designated wavelengths can be purchased from the link below for under £10 ($~13). For laboratories wishing to use the plate reader at multiple wavelengths, they can purchase as many filters as required, although a standard range of 400-650nm should be sufficient and cost-effective. Within the device the filters are easily exchangeable, simply slotting into place.

019 Fire - 600nm filter

Tests were completed in order to investigate whether the light was being lost from the device. Preventing excess light from entering the wells would allow the results to be more accurate. As shown in the figures below, we completed tests in an open lab, in a Styrofoam box, and in an opaque, black Perspex box.

We also tested the brightness of the individual LEDs in order to calibrate them.

Wells

One of the assets of our device is that the design is based on standard well plates. Instead of reinventing the wheel we decided to choose a more commercially available solution. However, there are a wide variety of well plates on the market, the design of which differs in three key aspects:
Number of wells
Well cross section
Well Depth

Number of wells:

Common well plates exist in 24, 48 and 96 well formats. We knew we wanted our device to fit one of these configurations so as to keep the barrier to wider adoption of our product as low as possible. After speaking to various teaching and diagnostics labs we decided on the 96 well configuration. This has a variety of advantages, for example, in our AMR case study ideally, we will be able to test up to 10 types of antibiotic with 2 controls at various concentrations (12*8) requiring 96 wells.

Well cross section:

The shape of the cross-section of the well was important to consider for a variety of reasons. We decided to go for circular wells as when designing the 3D printed construct realised they would provide the best solution with regards to the structural integrity of the device and light leakage between wells. Having circular wells allowed us to add dividers that separate out wells so as to remove any light leakage between wells leading to inaccuracies in our data.

Well depth:

After speaking to various academics it was highlighted to us that to increase the accuracy of our device the volume of liquid in each well is irrelevant, what is more impactful is the path length of the light rays (the length of light that travels through the well). We decided to derive and simulate a simple monte carlo model showing the difference in sensitivity of our device at different attenuation lengths using Beer Lambert's law. Here is the graph that our simulation produced showing absorbance at different concentrations for various well depths. The well depth increases as we move up the graph so wells with a greater depth have a greater gradient.

Figure 3: A graph to show how as the path length of the light increases, so does the attenuation of the light.

In order to increase and show the maximum potential accuracy we utilised deep well plates and contacted a company called eppendorf to get their advice and test various sample before settling on a specific well plate.

Sensors

The different sensors that we considered are listed in the table below:

Table 3: This table shows the different sensors that are able to detect changes in light brightness, which we investigated for use in our device.

Photodiodes are a type of transducer that can convert light into an electrical current proportionally to the amount of like that falls onto it. How a photodiode does this is explained in more detail below.

Light Dependent Resistors (LDRs) are components that can vary the levels of resistance across it depending on how much incident light is hitting the component. Usually, the LDR's resistance will decrease as the brightness of the light increases, and then this change of resistance can be calculated by measuring the voltage and current change across it.

Photomultiplier Tubes are the most sensitive of the sensors choices investigated. This is because a small amount of light coming into the device will cause the releasing of an electron (a small negatively charged particle). Once an electron inside the device is released a massive amplification is generated by using electrical components inside known as dynodes. This will give a very large output signals which are directly proportional to a very small input signals, however, this type of sensor is much more expensive than the others we investigated.

Phototransistors work much the same as photodiodes in that they are able to respond to light by generating a current that is directly proportional to the brightness of the light. They are also able to amplify the current so that there is a larger output for a small input.

Photodiodes:

A photodiode is a semiconductor component. This means that it has a conductivity (ability to conduct electric current) that is between that of an insulating material and a very conductive material, such as a metal. This can arise due to the presence of conductive impurities in a non-conductive material. One such example of a semiconductor is silicon, which is frequently used in photodiodes.

By combining two different types of semiconductor material together a p-n junction can be formed as the boundary layer between these two different materials. One material, known as n-type has fewer holes (a particle with a negative charge) in it and therefore has a negative charge, while the other material, known as p-type, has more holes (a positively charged electric charge carrier) in it and therefore is more positive.

When light hits the photodiode, and an electron is dislodged and an electron-hole pair is generated. The hole (positive charge) then migrates towards the anode electrode of the photodiode and the electron (negative charge) migrates towards the cathode electrode due to the electric field, therefore a small current can be seen. This current is directly proportional to the amount, and therefore the brightness, of the light. In our device, we connected the photodiodes were connected in reverse biased (input voltage to the anode) as this ensures the photodiodes will work correctly as light sensors.

We chose the photodiodes as our sensor, because they were cheaper than other sensor options, such as the phototransistors, and they are able to make quick readings so that we may collect data frequently.

We set up the photodiode array by connecting all the anodes and the cathodes together as shown below:

Figure 4: This schematic shows how the photodiodes are connected in the array. All of the cathodes of the photodiodes are soldered together and are shown as orange in the diagram above. They are connected to both the input voltage and the multiplexer that connects them to the analog input pin on the microcontroller. All of the anodes are soldered together and connected to the multiplexer that puts them to ground.

Figure 5: A photo of the actual soldered device.

To see more about how these photodiode circuits work please go to the Multiplexing section of the page.

Casing

Construction:

As our device is being designed to aid in providing research, teaching and diagnostic labs with a cheap, DIY, cloud-integrated plate reader, our design criteria include:

• Easily obtainable and reasonably priced materials
• Straightforward build
• Simple operation

We decided to use a standard 96 well-plate to design our device around as it’s the most commonly available well-plate in the average microbiology lab.

LED and Photodiode Casings:

We developed a casing for the LEDs and photodiodes in an array that complements a 96 well-plate, such that each well has an LED above and a photodiode below it. These were designed using Autodesk Fusion 360 Software, as shown below:

Figure 6: LED casing as shown on CAD software

Figure 7: Photodiode casing as shown on CAD software

Exporting of the files from CAD to .step files, followed by conversion to a .stl file resulted in an ability to print the casings in blue and red PLA, using an Ultimaker 3D-printer. However, this can also be ordered from other 3D printing sources for prices from ~$18.60(£14).

Figure 8: Casings being printed in PLA using an Ultimaker 3D printer

The links below provide access to the .stl files for downloading. This should allow any teams access for future attempts to build the device. We’ve also included files for LED and photodiode casings for 48 well plates due to their use within biology laboratories.

Download link for 96 well-plate LED casing

Download link for 96 well-plate photodiode casing

Download link for 48 well-plate LED casing

Download link for 48 well-plate photodiode casing

When complete, these casings containing the photodiodes and LEDs were able to simply slide in and out of the lower and upper layers, respectively, of the box. These are then retained in place for the duration of the readings.

Figure 9: LED and Photodiode arrays in 3D printed casings

The box for the device had parts individually laser-cut from an opaque, black Perspex acrylic sheet, sourced from a local company in Sheffield, that aided in addressing the previous light-escaping issue with the design. The perspex cost ~$26.57 (~£20). This took 2-3 hours to assemble, simply allowing for the glue to dry.

Figure 10: Black, Perspex box

The figures below show the overall layout of the device casings both as initially developed on Autocad software and a photo of the end result.

Figure 11: Device as shown on CAD software

Figure 12: Completed device

References:

Grossi, M., Lanzoni, M., Pompei, A., Lazzarini, R., Matteuzzi, D. and Riccò, B. (2008). Detection of microbial concentration in ice-cream using the impedance technique. Biosensors and Bioelectronics, 23(11), pp.1616-1623.

Miller, J. and Simon, P. (2008). MATERIALS SCIENCE: Electrochemical Capacitors for Energy Management. Science, 321(5889), pp.651-652.

Zourob, M., Elwary, S. and Turner, A. (2008). Principles of bacterial detection. New York: Springer.