Team:Imperial College/Contribution
contribution
With our Human Practises values determining our project's progression at every step, we ensured the usefulness of the various aspects of our project. Many of the aspects of our project have contributed to current and future IGEM teams, but
also the wider synthetic biology community. Here, we elaborate on those contributions.
Soap lab
Our software web-app was designed with end-users in mind, IGEM teams being our primary market. By collaborating with a number of teams and integrating their feedback into our project, we were able to establish a target market, and adapt our
tool according to the functionality required by that group. Our tool enables small labs like IGEM teams to access large design spaces and combinatorial derivations, taking advantage of the benefits of automation without needing the specific
training, so teams can focus on the creativity of design and analysis, not the menial labour. We also sought to make it accessible to teams without liquid handlers, and even teams without much experience of developing DNA assembly protocols,
such as high school teams. We therefore included a manual script output, so all IGEM teams can use our tool!
We have ensured the code is accessible and well documented. By using SBOL, we also enable the tool to be integrated into
larger pipelines. We have been transparent about its limitations, and provided a plan of how it could be developed in the future. Our project is therefore ideal for future teams to build upon.
education
We invested a lot of time into developing the educational aspects of our project. In a year where lab access is so limited, in silico simulation data is essential. Modelling in synthetic biology is challenging, and also a niche field of study.
There are currently very few, if not no synthetic biology modelling resources aimed at high school students and undergraduates. Our mentorship programme, aimed at current IGEM teams, empowered five teams to develop models for their projects.
Alongside this, we developed the Introduction to Mathematical Modelling in Synthetic Biology package, aimed at future IGEM teams. By having the content be entirely feedback-defined by our mentees, we have validated its usefulness, and
hope future IGEM teams benefit from our package. We also recognise there is room for expansion, so have provided the source LaTeX file for future teams to develop further as part of their own human practises. We hope it will continue to
develop until it is a truly comprehensive guide.
We also contributed to the general public, as well as current IGEM teams, by participating in Heidelberg's Science Slam, as well as hosting two of our own Webinars. These sought to
engage the public in the conversation, and discuss not the science, but the implications of the science. We wanted to consider why automation and software tools in general are slow to be adopted, and the ethical implications behind automation.
sbol
Standardised data formats are an essential consideration for the integrability and interoperability of software tools. SBOL as a data standard is extremely powerful, due to it's modularity and capabilities to encode for combinatorial designs.
However, it is a new standard, one which is still in development and one which is yet to have widespread use. We have contributed to the education of SBOL as a standard, the development of its tools and even directly in the development
of the standard itself.
SBOL Designer is one of the first interfaces to utilise SBOL to its full extent. However, we found it wasn't very approachable to the teams we collaborated with, especially the combinatorial design feature.
Paris_Bettencourt, Linkoping and Hamburg were all able to express their designs in SBOL Designer with some guidance. To make it more approachable, we re-packaged it to be usable in the browser, and created a Learn page on our web-app,
as well as an on-screen tutorial to aid users in its use.
The large concern of our collaborators and end-users was integration with current popular software tools, specifically digital lab notebooks like Benchling. This was further emphasised by our external collaborator Alberto Scarampi
from Cambridge. We spoke directly with the developers of SBOL and Benchling's developer team to stress the importance of compatibility between them, specifically asking Benchling to integrate SBOL version 2. While we were not able
to resolve this issue for us, we hope future teams will reap these benefits.
As SBOL itself is much more than just a design interface and symbolic language, our docs include guidance to using the SBOL software API specifically
aimed at iGEM teams. The intricacies and the design choices behind SBOL Data presented a significant learning curve for us that we wanted to let future iGEM teams benefit from. Our SBOL Parser is the driving force behind our design-based
liquid handler script generation, helping to interpret SBOL design files correctly and transforming for the downstream protocol parsing. We built features supporting the extended use of combinatorial design, such as an enumerator for
finding all individual possible constructs, and adopted the established and popular labware library Plateo to define and store intermediate SBOL objects, which then connect with our downstream code. This standardized intermediate presents
a powerful and easily understandable way of using the SBOL Parser for other applications than automating DNA assembly protocols and brings the SBOL standard into another use context. The enumeration and combinatorial variation features
from our SBOL Parser have also been added to the official pySBOL library in a pull request for general public use. While libSBOLj, the equivalent Java library, is complete, pySBOL is still in development. Python is far more widely
used in scientific research, so by aiding in the expansion of pySBOL, we have worked directly on the expansion of SBOL as a usable standard, and therefore its integrability into future workflows and software projects.
New Parts
In designing our Tryptophan optimisation project, we designed a series of new basic and composite parts for the iGEM registry. All of these parts have been designed to be compatible with both BioBrick assembly and BASIC assembly. The synthesis through either Twist or IDT has given us high confidence on sequence accuracy.
So we decided to upload new and composite parts
to the iGEM registry!
| Name | Type | Description | Length |
|---|---|---|---|
| BBa_K3559000 |
Coding | BioBrick_BASIC_DAHP Synthase (Aro4) (K229L) |
1163 |
| BBa_K3559001 |
Composite | BioBrick_BASIC_tENO1 |
261 |
| BBa_K3559002 |
Regulatory | BioBrick_BASIC_Aro4_tENO1 |
1424 |
| BBa_K3559003 |
Regulatory |
BioBrick_BASIC_pCCW12 |
736 |
| BBa_K3559004 |
Regulatory |
BioBrick_BASIC_pHTB2 |
735 |
| BBa_K3559005 |
Regulatory |
BioBrick_BASIC_pPAB1 |
736 |
| BBa_K3559006 |
Regulatory |
BioBrick_BASIC_pPGK1 |
736 |
| BBa_K3559007 |
Regulatory |
BioBrick_BASIC_pPOP6 |
736 |
| BBa_K3559008 |
Regulatory |
BioBrick_BASIC_pREV1 |
736 |
| BBa_K3559009 |
Regulatory |
BioBrick_BASIC_pTEF1 |
736 |
| BBa_K3559010 |
Terminator |
BioBrick_BASIC_tTDH1 |
260 |
| BBa_K3559011 |
Coding |
BioBrick_BASIC_Trp2 (S65R; S76L) |
1574 |
| BBa_K3559012 |
Terminator |
BioBrick_BASIC_tENO2 |
261 |
| BBa_K3559013 |
Composite | BioBrick_BASIC_Trp2_tENO2 |
1835 |
| BBa_K3559014 |
RNA | BioBrick_BASIC_gRNA_Aro7_1 |
246 |
| BBa_K3559015 |
RNA |
BioBrick_BASIC_gRNA_Aro7_2 |
246 |
| BBa_K3559016 |
RNA |
BioBrick_BASIC_gRNA_Aro7_3 |
246 |
| BBa_K3559017 |
RNA |
BioBrick_BASIC_gRNA_Aro8_1 |
246 |
| BBa_K3559018 |
RNA |
BioBrick_BASIC_gRNA_Aro8_2 |
246 |
| BBa_K3559019 |
RNA |
BioBrick_BASIC_gRNA_Aro8_3 |
246 |
| BBa_K3559020 |
RNA |
BioBrick_BASIC_gRNA_CDC19_1 |
246 |
| BBa_K3559021 |
RNA |
BioBrick_BASIC_gRNA_CDC19_2 |
246 |
| BBa_K3559022 |
RNA |
BioBrick_BASIC_gRNA_CDC19_3 |
246 |
Unfortunately, due to Covid-19 we did not get the chance to characterise our parts in the lab to confirm that they work as intended ...
We still hope to be able to use these parts in the near future and update the registry at a later date!
