Team:Imperial College/Human Practices
Human practices
Human practices is an essential element in any project. For us, human practices is the infrastructure within which our project develops. It should play an integral role from the offset, informing the project design at every step.
It acts as a means to ensure our project remains relevant, valuable, and trustworthy, taking into consideration the interests of all, not just our own.
In order to achieve this, we developed a set of core values to abide to:
Communication
We sought to set a precedent for a strong line of communication between our team and end-users throughout the design process, and for all aspects of our project.
Accessibility
We sought to ensure the accessibility of our project, both so our end-users can utilise our product agnostic of their experience, and future teams can build on our progress.
Vaildation
We sought to provide proof for the validity and therefore trustworthiness of all aspects of our project, seeking input and feedback from external sources to remove bias.
By abiding to these values in all aspects of the project, our products will be provably useful to our end-users.
integrated human practice
In order to uphold our core values in the development of the different aspects of our tool, we needed to get user input and feedback at every stage. In this way, our products encompass an informed design, and our progress can remain on track
to maintain trustworthiness and usefulness. We therefore followed an iterative loop of speaking with experts, designing and reimplementing based on their input, and then testing our product on potential end-users. We used our own team
members as daily test cases for immediate input, then at significant milestones we would share our progress with external sources, such as our collaborators, in order to remove bias. For our software tool, part of our wet-lab team acted
as our internal test case for potential end-users. Through our Tryptophan Optimisation project, they helped develop the design and determine the requirements of our software from this project.
Below, we elaborate on the key external individuals and teams who aided in our projects development. We are very grateful to all who provided guidance and feedback. We remained in contact with them throughout the project, and while we couldn't
possibly elaborate on the entire extent of their input, we have included the key insights each provided.
Soap Lab
Initial Insights from Experts in the field
Professor Guy-Bart Stan from the Center of Synthetic Biology at Imperial College provided insights into front-line research in synthetic biology, and the direction that current research is headed. On automation he elaborated that "the key
is mainly to change the status quo in terms of reproducibility and quality control of what is done in the lab, i.e. to increase the level of confidence on results and enable proper traceability/version control and debugging of experiments".
This provided us a with a more nuanced idea of the user requirements and the direction of our project, especially on error logging and transparency, as the "trackability of data analysis would be utterly useful". Well executed automation
can be extremely powerful, but to many it is untrustworthy and inaccessible practically and financially. Our tool must therefore work to alleviate the current hurdles automation faces by overcoming the manual hurdles on the software side
researchers currently face and thus proving its trustworthiness and reliability.
Dr Goksel Misirli, a lecturer in computing at Keele University, stated "programmable robots exchanging data in standard formats such as SBOL would
contribute to reproducibility and to the creation of complex workflows involving different tools". This gave us great insight into the importance of standard data formats. We quickly determined SBOL was the most suitable for our tool due
to its richness of data, its modularity and its interoperability with other software tools based on the same standard, enabling our tool to be integrated into larger software pipelines.
Dr Glen Gowers, co-founder at Basecamp Research,
and Jean Loup Falon, creator of Galaxy-SynBioCAD, both stressed the importance of establishing when automation is better than manual protocols by weighing up the benefits of each. For example, accounting for prep and calibration time,
a manual protocol may be quicker and simpler to perform, yet still lack the meta-information of liquid handlers. It was this insight that led us to provide extensive functionality for large design spaces and combinatorial designs, since
long and repetitive protocols bring automation far above manual protocols in its benefits.
Dr Glen Gowers also suggested we wait before using the automated transformation protocols, as there can be serious issues, and calibration
must be done every time. As a result, for our validation we have been doing manual transformation as we do not have time to risk our transformations failing due to Opentrons issues.
Dr Zoltan Tuza, post-doc at the Imperial College
Centre for Synthetic Biology, stressed the importance of the traceability of errors and data collection to more broadly provide a summary of performance, for the sake of error logging and promoting trust in our tool.
In an interview
with Alice Boo, PhD at Imperial College and alumni of the 2016 Imperial College Grand Prize winning Ecolibrium team, described the drive for automation in the field of synthetic biology and biology as a whole as comparable to that of the
industrial revolution. Currently, investing in automation just isn't worth it for many labs, since "the amount of automation that a lab requires will depend on their research aims". However, as design spaces become larger and data-driven
algorithms such as machine learning become more popular, more and more labs will turn to automation. She elaborated that "A dialogue between software developers, hardware developers and lab users is most definitely essential" for driving
that change. We therefore sought to sustain a strong line of communication with our end-users, both so that our design remains informed, but also to show them the benefits that our tool and automation as a whole can provide.
At
the IWBDA conference in August, the DAMP Lab presented their paper on an Opentrons MoClo tool, converting from CSV to Opentrons OT-2 v1 protocols. This tool became the basis of our MoClo script generator. They also compared traditional
and isothermal thermocycling, mentioning the Opentrons thermocycler module as a possibility in future. This inspired us to integrate an option to use the Opentrons thermocycler module in our scripts, which we see as a very useful feature
since having integrated thermocycling increases automation efficiency and reduces risk of sample mishandling.
Insights from iGEM teams
We collaborated with Linköpings early on in the year, as they were also developing a software tool. They gave us insight into the importance of an intuitive user interface, something we took to heart and sought to create. This was something
we tested extensively on end-users as well. They also provided us with their feedback forms for us to use in our own beta testing.
SBOL and SBOL Designer as still under development at the moment, so we wanted to test their usability.
With Paris_Bettencourt, we guided them to create their parts in SBOL format, identified key points of confusion thanks to the questions in the beta testing questionnaire from Linköping. After explaining the issues they were having, they
were successfully able to create their parts. It was their insights which led us to include an on-screen tutorial for each section of our web-app, explaining their functionality.
Hamburg, our partner team, provided a number of insights
into our tool, as they were our primary test case. They utilised the full extent of the tool over a call, so we could observe their progress and note any issues they had, so as to rectify them. Their feedback about their experience of
the user interface was also excellent for us. They provided extensive, detailed analysis, such as dead volumes, and how to minimise cost while also minimising risk of cross-contamination.
SBOL is not a commonly used standard and
liquid handlers are still being popularised in undergraduate labs. We therefore spent time teaching our collaborators how to operate the Opentrons and SBOL, and from their feedback integrated a 'Learn' page into our web-app for addressing
points of confusion.
We found that many teams do not have access to liquid handlers. For the sake of accessibility, we integrated a manual protocol generation, so users are also able to carry out the generated protocols by hand.
In this way, users can still benefit from our tool without the need for Opentrons, meaning our tool doesn't necessitate liquid handlers. This feature also allows users to check the protocol the Opentrons is running, to check the it is
correct and to log any issues.
Introduction to mathematical modelling in synthetic biology
In a year where lab space is so scarce, in silico research is more important than ever. From the meetups we attended and the global slack, it became clear however, that modelling awareness was limited among IGEM teams. Gabe, who also participated
in 2017 as a high school student, struggled to develop a model for his team as well. It was only thanks to mentorship from Oxford University that he was able to formulate a model. To give back to the IGEM community, we sought to provide
a modelling mentorship programme. We mentored five teams throughout the summer, but the was a commonality in the hurdles they faced. It became clear that a general package would be invaluable not just for them, but for the IGEM community
and the Synthetic Biology community as a whole. The development of the package was at its core driven by the input and feedback of the five teams we mentored, giving insights into its usefulness at every stage. In this way, the package
is entirely user-driven, providing a comprehensive guide to modelling, enabling high school students to learn all the theory and applications of modelling and empowering them to create their own models.
For details of the insights
our mentees gave into its development, visit our Collaborations page
webinars
Ethics of automation
When we presented on the ethics of automation at the Heidelberg Science Slam, we gave the general public an accessible flavour of the topic. The ethics of automation is central to our project - we are aiming to bring automation to more scientists.
We need to know how we will affect our users, and whether we are delivery what they desire. We hosted a publicly available and advertised webinar on the ethics of automation, with our experts, so not only could we learn from these experts,
but others could too! Automation is a very complex and polarising topic, and we know we aren't the only ones with these questions.
In answer to one of our questions, Dr. Brandon Sepulvado responded that ethical discourse should be integrated in research, not independent of it.
This was very positive for us to hear, as our core values encompass this ideology. Therefore, by integrating human practices into our project and establishing our guiding values early on, we are ensuring that we are tailoring our product
to the ethical discourse around it.
Developing for bio
One of the key goals of our project is to connect wet-lab scientists with software developers. We therefore asked: how are wet-lab scientists and software developers collaborating right now? What can we learn from them? We hosted a second
webinar, with the aim to promote interoperability and communication between bench scientists and developers, and to learn for ourselves how the communication we want to promote is happening in the real world.
The benefits our experts
have observed from automation in biotechnology include higher workflow reproducibility, reliability, and throughput. They provided insight into how this, if implemented correctly, translates to increased throughput and therefore a reduced
timeline for drug discovery. This supports the results of our research about the benefits of automation, giving us an even stronger case of why automation is important!
Wet Lab
Dr. William Shaw's advice assisted us in greatly reducing our design space, informing us that the choice of promoter in front of gRNA is unimportant and won't significantly affect expression.
After receiving feedback from Dr. Rodrigo
Ledesma Amaro, we decided to do knockdowns by directing the gRNAs at the DNA level rather than the RNA level. He also suggested violacein as a proxy for tryptophan levels for screening, and helped us decide to use yeast rather than E.
Coli for tryptophan optimisation as CRISPR worked better in yeast.
Professor Tom Ellis informed our decision to simplify our wet lab plans rather than doing a gRNA array due to our limited time in the lab.
