Difference between revisions of "Team:Newcastle/Software/OT"

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                         Interlab Study
 
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                         MIC
 
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                         E.coli Transformation  
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                         <i>E.coli</i> Transformation  
 
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                     <p style="font-size:100%">As part of our lab work a number of the team members have become familiar with the Opentrons OT-2 liquid handling robot. This required learning python, the coding language used for the robots API. A 10 µL and 300 µL pipette was installed allowing for a range of pipetting volumes to be used. We also acquired a Peltier thermocycler (TempDeck), allowing temperature modulation between 4 and 95 ℃. Using the OT-2 and the TempDeck, a robust a transformation buffer (TB) was developed that could be used to rapidly transform Escherichia coli DH5a in a microtitre plate format. This was developed as part of a Biodesign Automation (BDA) workflow that would allow us to optimise TB using a Design of Experiments (DoE) methodology. As a result, we have been able to automate a number of protocols, increasing the accuracy of our experiments and saving time in the labs. There has also been a number of kill curves performed on pseudomonas to identify a suitable antibiotic which can then be used as our test to identify if our transformations have worked. Gentamycin and Streptomycin being two that were a success.</p>
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                     <p style="font-size:100%">As part of our lab work a number of the team members have become familiar with the Opentrons OT-2 liquid handling robot. This required learning python, the coding language used for the robot’s API. A 10 µL and 300 µL pipette were installed allowing for a range of pipetting volumes to be used. We also acquired a Peltier thermocycler (TempDeck), allowing temperature modulation between 4 and 95 ℃. Using the OT-2 and the TempDeck, a robust a transformation buffer (TB) was developed that could be used to rapidly transform <i>E. coli</i> DH5α in a microtitre plate format. This was developed as part of a Bio-Design Automation (BDA) workflow that would allow us to optimise TB using a Design of Experiments (DoE) methodology. As a result, we have been able to automate a number of protocols, increasing the accuracy of our experiments and saving time in the labs. The OT-2 has also been used to set up minimum inhibitory concentration (MIC) assays which have been used throughout the project including: antibiotic testing in <i>Pseudomonas</i> sp. and part characterisation in <i>E. coli</i>.</p>
  
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                     <p style="font-size:100%">In addition to stock parts and modules, we have 3D printed custom labware which can hold a variety of beakers and tubes through a removable acrylic lid cut to specification (Figure 1 and 2). This equipment also doubles up as a cold box when filled with ice, allowing us hold culture on ice just as we would carrying out manual protocols. All python script and protocols can be found <a href="https://github.com/jbird1223/Newcastle-iGEM/tree/master/OT-2%20Protocol" class="black">here</a>. The code has been done in a way where it can be easily adapted for alternate uses. The results and their contribution to our measurement study can be found <a href="https://2018.igem.org/Team:Newcastle/Measurement" class="black">here</a>. </p>
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                     <p style="font-size:100%">In addition to stock parts and modules, we have 3D printed custom labware which can hold a variety of beakers and tubes through a removable acrylic lid cut to specification. This equipment also doubles up as a cold box when filled with ice, allowing us to hold cultures on ice, just as we would when carrying out manual protocols. All the python scripts and protocols can be found <a style="padding:0px;" href="https://github.com/jbird1223/Newcastle-iGEM/tree/master/OT-2%20Protocol" class="black">here</a>. The code has been written in a way where it can be easily adapted for alternate uses. The results and their contribution to our measurement study can be found <a href="https://2018.igem.org/Team:Newcastle/Measurement" class="black">here</a>.</p>
 
                    
 
                    
 
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             <h3 class="subhead">2018 Interlab Cell Measurement</h3>
 
             <h3 class="subhead">2018 Interlab Cell Measurement</h3>
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                 <p style="font-size:100%"> The 2018 Interlab focused on reproducibility and to identify and correct sources of variability. The protocol itself focused on standardised and exact measurement, even accounting for variation found between different brands of plate reader. However what it couldn’t take into account is the innate variation of human error. This may be from simple mistakes such as mixing the wrong solutions together, or from smaller sources of variation such as µL different uncalibrated pipettes. Over the course of a long experiment, this variation can compound, leading to a much different outcome than the intended. The OT-2 helps minimise this variation, allowing highly reproducible pipetting over a long period of time. As such, we took the main cell measurement protocol of the Interlab and converted it into an automated protocol. In future Interlabs, this could be an entirely new avenue to explore as lab to lab variation in liquid handling would be removed from the variation equation. </p>
  
 
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                 <p style="font-size:100%">A mainstay of our project was developing <i>Pseudomonas</i> sp. as a plant colonising chassis organism. The first step in chassis development was to identify antibiotics that <i>Pseudomonas</i> sp. was susceptible to. This would indicate which selectable markers were suitable for use in transformation procedures. Working antibiotic concentrations were determined by carrying out minimum inhibitory concentration (MIC) experiments where <i>Pseudomonas</i> sp. growth was tested against a range of antibiotic concentrations. To minimise variation between replicates MIC experiments were automated using an Opentrons OT-2 pipetting robot. Automation also allowed us to prepare to 2 plates simultaneously, doubling the number of antibiotic concentrations that could be tested in a single experiment.</p>
  
 
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             <h3 class="subhead">Design of Experiments Complex Solution Construction</h3>
 
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                     <a onclick="location.href='https://github.com/jbird1223/Newcastle-iGEM/blob/master/OT-2%20Protocol/96%20well%20plate%20DoE%20for%20complex%20solutions.py'" class="smoothscroll btn btn--stroke">
 
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                 <p style="font-size:100%">Using a Design of Experiments (DoE) methodology is ideal for investigations that require multiple, potentially interacting factors to be considered. It allows a complete design space to be covered, while minimising the number of experimental runs that are required for full statistical coverage. However the issue is that even with experimental runs minimised, investigating second, third or even fourth degree interactions leads to an exponential increase in runs required. As such, automation provides an exceptionally useful tool that efficiently utilise the power of DoE in a high-throughput manner.</p>
 
                 <p style="font-size:100%">Using a Design of Experiments (DoE) methodology is ideal for investigations that require multiple, potentially interacting factors to be considered. It allows a complete design space to be covered, while minimising the number of experimental runs that are required for full statistical coverage. However the issue is that even with experimental runs minimised, investigating second, third or even fourth degree interactions leads to an exponential increase in runs required. As such, automation provides an exceptionally useful tool that efficiently utilise the power of DoE in a high-throughput manner.</p>
  
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                 <p style="font-size:100%">In our investigation into the composition of transformation buffer (TB) and its effect on overall transformation efficiency (TrE), a DoE definitive screening test was utilised and an OT-2 DoE protocol was developed. This allowed for the high-throughput construction of 20 TBs that consisted of 11 different reagents, all in varying quantities. With simple alterations, this code can allow the user to assess 24 different reagents and construct 96 solutions of varying concentrations. Not only this, it can act as a foundation protocol for much larger investigations. For example during our investigation into <a href="https://2018.igem.org/Team:Newcastle/Measurement" class='black'>rich defined media</a>, our custom 20 mL universal tube labware was replaced with two 50 mL falcon tube, 24 slot racks, allowing the construction of 20 growth medias with 23 different reagents. </p>
+
                 <p style="font-size:100%">In our investigation into the composition of transformation buffer (TB) and its effect on overall transformation efficiency (TrE), a DoE definitive screening test was utilised and an OT-2 DoE protocol was developed. This allowed for the high-throughput construction of 20 TBs that consisted of 11 different reagents, all in varying quantities. With simple alterations, this code can allow the user to assess 24 different reagents and construct 96 solutions of varying concentrations. Not only this, it can act as a foundation protocol for much larger investigations. For example during our investigation into <a href="https://2018.igem.org/Team:Newcastle/Measurement" class='black'>rich defined media</a>, our custom 20 mL universal tube labware was replaced with two 50 mL falcon tube, 24 slot racks, allowing the construction of 20 growth media with 23 different reagents. </p>
  
 
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             <h3 class="subhead">Competent Cells</h3>
 
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                 <p style="font-size:100%">Competent cells are of paramount importance in synthetic biology and the design of genetically engineered machines. Preparation is notoriously irreproducible, with a myriad of different ‘gold standard’ protocols that have been suggested generate ultra competent cells (TrE of >1 x 10<sup>8</sup>) that can be used with ligation reaction mixtures. Protocols also tend to be long winded, or if rapid, sacrifice TrE for convenience. To remove the hassle of carrying such protocols out, many labs buy in their competent cells, which can be hundreds of dollars for only 10 aliquots. To combat this, an automated competent cell protocol was developed that could provide competent cells, while being high-throughput and robust. Set up to use the TBs designed by the definitive screening, this protocol allowed for the one-step preparation of competent  cells, using  25 different TBs for the generation of 25, 100 µL competent cell aliquots. Like previous protocols, this can be easily modified to use even more TBs, or only 1 TB and up to 96 individual competent cell aliquots.</p>
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                 <p style="font-size:100%">Competent cells are of paramount importance in synthetic biology and the design of genetically engineered machines. Preparation is notoriously irreproducible, with a myriad of different ‘gold standard’ protocols that have been suggested generate ultra competent cells (TrE of >1 x 10<sup>8</sup>) that can be used with ligation reaction mixtures. Protocols also tend to be long winded, or if rapid, sacrifice TrE for convenience. To remove the hassle of carrying such protocols out, many labs buy in their competent cells, which is a very costly solution. To combat this, an automated competent cell protocol was developed that could produce competent cells, while being high-throughput and robust. Set up to use the TBs designed by the definitive screening, this protocol allowed for the one-step preparation of competent  cells, using  25 different TBs for the generation of 25, 100 µL competent cell aliquots. Like previous protocols, this can be easily modified to use even more TBs, or only 1 TB and up to 96 individual competent cell aliquots.</p>
  
 
                  
 
                  
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             <h3 class="subhead">Transformations</h3>
 
             <h3 class="subhead">Transformations</h3>
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                 <p style="font-size:100%">While competent cell quality is important, the actual transformation of the organism (inserting the DNA) is what is required to generate recombinant organisms. As such, a large number of transformations need to be carried out regularly in wetlab experiments. However carrying out transformation protocols is tedious and long-winded, requiring large amounts of pipetting. Some choose to shorten incubation times to increase throughput, however shortening steps leads to a rapid decrease in TrE (sacrificing TrE for convenience again). Automating transformations would be ideal, allowing for maximal throughput and optimum incubation. It would be unanimously useful for the SynBio community. </p>
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                 <p style="font-size:100%">While competent cell quality is important, the actual transformation of the organism (inserting the DNA) is what is required to generate recombinant organisms. As such, a large number of transformations need to be carried out regularly in wetlab experiments. However carrying out transformation protocols is tedious and long-winded, requiring high numbers of pipetting steps and increasing the risk of human error. Some choose to shorten incubation times to increase throughput, however shortening steps leads to a rapid decrease in TrE (sacrificing TrE for convenience again). Automating transformations would provide a solution to this, allowing for maximal throughput and optimum incubation. It would be unanimously useful for the SynBio community. </p>
  
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                 <p style="font-size:100%">For reference, we carried out the iGEM recommended competent cell and transformation protocol (<a href="http://parts.igem.org/Help:Protocols/Competent_Cells" class="black">Competent Cell protocol </a> and <a href="http://parts.igem.org/Help:Protocols/Transformation" class="black"> Transformation protocol</a>). In our lab, we only managed to reach a maximum TrE of 5.05 x 10<sup>6</sup> with this method, and most attempts failed to produce any colonies. Our initial automated transformation workflow using the CaCl2-MgCl2 method produced E. coli with a TrE of 1.89 x 10<sup>4</sup> and scoping experiments determined that the 96 well plate format decreases TrE by a factor of 100. With optimisation of the TB, automated TrE was increased to 2.21 x 10<sup>6</sup>, a 100x increase on the initial workflow. Whilst an ultracompetent standard was not reached, more importantly it appeared to be highly robust, with every aliquot producing some successful transformants. This protocol was also rapid, requiring minimal input.  </p>
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                 <p style="font-size:100%">For reference, we carried out the iGEM recommended competent cell and transformation protocol (<a href="http://parts.igem.org/Help:Protocols/Competent_Cells" class="black">Competent Cell protocol </a> and <a href="http://parts.igem.org/Help:Protocols/Transformation" class="black"> Transformation protocol</a>). In our lab, we only managed to reach a maximum TrE of 5.05 x 10<sup>6</sup> with this method, and most attempts failed to produce any transformants. Our initial automated transformation workflow using the CaCl2-MgCl2 method produced <i>E. coli</i> with a TrE of 1.89 x 10<sup>4</sup> and scoping experiments determined that the 96 well plate format decreases TrE by a factor of 100. With optimisation of the TB, automated TrE was increased to 2.21 x 10<sup>6</sup>, a 100x increase on the initial workflow. Whilst an ultracompetent standard was not reached, more importantly it appeared to be highly robust, with every aliquot producing some successful transformants. This protocol was also rapid, requiring minimal input.  </p>
  
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                 <p style="font-size:100%">Further work can also work on the optimisation of the 96-well plate conditions. With updates to OT-2 API, this protocol could be fully automated, producing 96 100 uL transformant aliquots without any human interaction. </p>
+
                 <p style="font-size:100%">Further work can also work on the optimisation of the 96-well plate conditions. With updates to OT-2 API, this protocol could be fully automated, producing 96 100 µL transformant aliquots without any human interaction. </p>
  
 
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                <h1 class="display-2">References & Attributions</h1>
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<p class="about-para"><font size="2"><strong>Attributions: Matthew Burridge, Frank Eardley, Luke Waller, Umar Farooq
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Latest revision as of 01:47, 18 October 2018

Alternative Roots/Software

Software

Opentrons OT-2

The OT-2 Interlab Study MIC Definitive Screening Competent cells E.coli Transformation

The OT-2

As part of our lab work a number of the team members have become familiar with the Opentrons OT-2 liquid handling robot. This required learning python, the coding language used for the robot’s API. A 10 µL and 300 µL pipette were installed allowing for a range of pipetting volumes to be used. We also acquired a Peltier thermocycler (TempDeck), allowing temperature modulation between 4 and 95 ℃. Using the OT-2 and the TempDeck, a robust a transformation buffer (TB) was developed that could be used to rapidly transform E. coli DH5α in a microtitre plate format. This was developed as part of a Bio-Design Automation (BDA) workflow that would allow us to optimise TB using a Design of Experiments (DoE) methodology. As a result, we have been able to automate a number of protocols, increasing the accuracy of our experiments and saving time in the labs. The OT-2 has also been used to set up minimum inhibitory concentration (MIC) assays which have been used throughout the project including: antibiotic testing in Pseudomonas sp. and part characterisation in E. coli.

In addition to stock parts and modules, we have 3D printed custom labware which can hold a variety of beakers and tubes through a removable acrylic lid cut to specification. This equipment also doubles up as a cold box when filled with ice, allowing us to hold cultures on ice, just as we would when carrying out manual protocols. All the python scripts and protocols can be found here. The code has been written in a way where it can be easily adapted for alternate uses. The results and their contribution to our measurement study can be found here.

2018 Interlab Cell Measurement


Cell Measurement Protocol

The 2018 Interlab focused on reproducibility and to identify and correct sources of variability. The protocol itself focused on standardised and exact measurement, even accounting for variation found between different brands of plate reader. However what it couldn’t take into account is the innate variation of human error. This may be from simple mistakes such as mixing the wrong solutions together, or from smaller sources of variation such as µL different uncalibrated pipettes. Over the course of a long experiment, this variation can compound, leading to a much different outcome than the intended. The OT-2 helps minimise this variation, allowing highly reproducible pipetting over a long period of time. As such, we took the main cell measurement protocol of the Interlab and converted it into an automated protocol. In future Interlabs, this could be an entirely new avenue to explore as lab to lab variation in liquid handling would be removed from the variation equation.

MIC (Kill Curve)


Kill Curve Protocol

A mainstay of our project was developing Pseudomonas sp. as a plant colonising chassis organism. The first step in chassis development was to identify antibiotics that Pseudomonas sp. was susceptible to. This would indicate which selectable markers were suitable for use in transformation procedures. Working antibiotic concentrations were determined by carrying out minimum inhibitory concentration (MIC) experiments where Pseudomonas sp. growth was tested against a range of antibiotic concentrations. To minimise variation between replicates MIC experiments were automated using an Opentrons OT-2 pipetting robot. Automation also allowed us to prepare to 2 plates simultaneously, doubling the number of antibiotic concentrations that could be tested in a single experiment.

Design of Experiments Complex Solution Construction


DoE Protocol

Using a Design of Experiments (DoE) methodology is ideal for investigations that require multiple, potentially interacting factors to be considered. It allows a complete design space to be covered, while minimising the number of experimental runs that are required for full statistical coverage. However the issue is that even with experimental runs minimised, investigating second, third or even fourth degree interactions leads to an exponential increase in runs required. As such, automation provides an exceptionally useful tool that efficiently utilise the power of DoE in a high-throughput manner.

In our investigation into the composition of transformation buffer (TB) and its effect on overall transformation efficiency (TrE), a DoE definitive screening test was utilised and an OT-2 DoE protocol was developed. This allowed for the high-throughput construction of 20 TBs that consisted of 11 different reagents, all in varying quantities. With simple alterations, this code can allow the user to assess 24 different reagents and construct 96 solutions of varying concentrations. Not only this, it can act as a foundation protocol for much larger investigations. For example during our investigation into rich defined media, our custom 20 mL universal tube labware was replaced with two 50 mL falcon tube, 24 slot racks, allowing the construction of 20 growth media with 23 different reagents.

Competent Cells


Competent Cell Protocol

Competent cells are of paramount importance in synthetic biology and the design of genetically engineered machines. Preparation is notoriously irreproducible, with a myriad of different ‘gold standard’ protocols that have been suggested generate ultra competent cells (TrE of >1 x 108) that can be used with ligation reaction mixtures. Protocols also tend to be long winded, or if rapid, sacrifice TrE for convenience. To remove the hassle of carrying such protocols out, many labs buy in their competent cells, which is a very costly solution. To combat this, an automated competent cell protocol was developed that could produce competent cells, while being high-throughput and robust. Set up to use the TBs designed by the definitive screening, this protocol allowed for the one-step preparation of competent cells, using 25 different TBs for the generation of 25, 100 µL competent cell aliquots. Like previous protocols, this can be easily modified to use even more TBs, or only 1 TB and up to 96 individual competent cell aliquots.

Transformations


Transformation Protocol

While competent cell quality is important, the actual transformation of the organism (inserting the DNA) is what is required to generate recombinant organisms. As such, a large number of transformations need to be carried out regularly in wetlab experiments. However carrying out transformation protocols is tedious and long-winded, requiring high numbers of pipetting steps and increasing the risk of human error. Some choose to shorten incubation times to increase throughput, however shortening steps leads to a rapid decrease in TrE (sacrificing TrE for convenience again). Automating transformations would provide a solution to this, allowing for maximal throughput and optimum incubation. It would be unanimously useful for the SynBio community.

For reference, we carried out the iGEM recommended competent cell and transformation protocol (Competent Cell protocol and Transformation protocol). In our lab, we only managed to reach a maximum TrE of 5.05 x 106 with this method, and most attempts failed to produce any transformants. Our initial automated transformation workflow using the CaCl2-MgCl2 method produced E. coli with a TrE of 1.89 x 104 and scoping experiments determined that the 96 well plate format decreases TrE by a factor of 100. With optimisation of the TB, automated TrE was increased to 2.21 x 106, a 100x increase on the initial workflow. Whilst an ultracompetent standard was not reached, more importantly it appeared to be highly robust, with every aliquot producing some successful transformants. This protocol was also rapid, requiring minimal input.

Further work can also work on the optimisation of the 96-well plate conditions. With updates to OT-2 API, this protocol could be fully automated, producing 96 100 µL transformant aliquots without any human interaction.





References & Attributions

Attributions: Matthew Burridge, Frank Eardley, Luke Waller, Umar Farooq