Contribution

Project Forget Me Not contributes to the iGEM 2023 competition and creates resources for future teams in the following ways:

1. Furthering the understanding of precision microbiome editing using CRISPR

Comprehensive literature review and analysis of the gut-brain axis, CRISPR systems and editing the gut microbiome.

During our initial literature review, we studied teams that had tackled neurodegenerative diseases via the gut-brain axis. The UCL iGEM 2013 team, Team Lund 2021 iGEM team and finally iGEM Nottingham 2020.

CRISPR editing the microbiome for particular therapeutic outcomes such as alleviating childhood asthma is relatively new but well established (TED Audacious project).

This seemed to be the next logical step in the trajectory of Synbio tools for neurodegenerative diseases (from inhibiting biofilm, using logic gates plus kill switches for metabolic engineering) and we aimed to design a CRISPR system that is capable of precision microbiome editing for neurodegenerative diseases.

Throughout our wiki, you can see well documented instances of using CRISPR for precision gut microbiome editing to be the next frontier. Well documented literature and design review on CRISPR microbiome editing, contributing to future iGEM teams.



2. Creating an drug discovery software tool using Quantum Machine learning

Dry Lab created a researcher oriented Drug discovery software tool, allowing future iGEM teams to more find viable drug targets in Alzheimer’s disease.



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To encourage future iGEM teams to capitalize on the progress we have made with this project, a hybrid Quantum Machine Learning model is being used to identify Acetylcholinesterase inhibitors.This will be available as a tool for all future iGEM teams looking to classify AChE drug targets for their project.

Read about drug discovery tool

3. Improved upon 2019 University of Nottingham iGEM team’s riboswitch for better induction and genetic editing in Clostridium genus

BBa_K4543058 Adapted the riboswitch system to be compatible with the codon optimized Sp. Cas9. This is the first layer of control and safety on our project



Engineering safe parts, first layer of control (Riboswitch):

Building upon the work done by Nottingham iGEM 2019, we adapted the system to work with our dual-plasmid induced CRISPR Cas9 toolkit for Clostridia.



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Explanation:

  1. Expression of the cas9 gene is controlled by a theophylline-inducible riboswitch on the plasmid (Ines et. al, 2019).

  2. The riboswitch allows temporal control of Cas9 induction, reducing toxicity during cloning and allowing time for recombination to occur before cleavage.

  3. Reduces toxicity during cloning and allows time for recombination before cleavage

  4. Edited cells avoiding Cas9 cleavage are positively selected

  5. Enables precise, scarless genomic integrations mediated by CRISPR/Cas9 and recombination



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Construction:

  1. pMTL-IC101 is an E. coli /Clostridium shuttle plasmid containing the catP reporter gene under control of the Fdx promoter.

  2. The plasmid contains both Gram-negative (ColE1) and Gram-positive (pBP1) replicons for replication in E. coli and Clostridium respectively.

  3. Different theophylline-responsive riboswitches E (Topp et. al, 2017) were inserted downstream of the catP transcription start site. Riboswitch- GGUGAUACCAGCAUCGUCUUGAUGCCCUUGGCAGCACCCUGCUAAGGAGGCAACAACAUG

  4. In the absence of theophylline, the riboswitch forms a stem-loop structure that sequesters the ribosome binding site (RBS) in the mRNA transcript, preventing translation of catP.

  5. When theophylline binds to the aptamer domain of the riboswitch, it conforms to the riboswitch to release the RBS, allowing binding of ribosomes and translation of catP.

4. Outreach efforts (Neuroethics report and ‘Synbio in Space’ material)

Continued discourse on responsibility and ethics. Creating reliable educational material for future teams.

To show the importance of revisiting ethical discussions over time as technology advances, our human practices team created a ‘neuroethics report’ building upon the UCL iGEM 2013 report,’Spotless mind.’ Our report contributes an evolved perspective building upon this initial report. We have provided an up-to-date reference on the ethics of gene editing that new iGEM teams can build further upon. The work is peer reviewed and can be directly incorporated into training new members. Continuing the discussion of responsibility and ethics amongst young scientists is important to foster innovation safely.

Read about HP neuroethics report here

During our educational drive, ‘Synthetic biology in space’- we created a primer on synthetic biology tools and their uses in space exploration and survival.These are hosted on wiki and Youtube as an accessible and reliable way for future iGEM teams to gather information. Overall the resources generated, connections made and framework established ease the onboarding process for future iGEM teams, encouraging their work with Synthetic Biology.

Read about education here

5. Enhanced biosecurity for future teams: Improved safety parts in wet and dry lab

Federated learning and multi layer governance to tackle dual use research of concern with AI in Biology.

Dry Lab: In a recent paper by Urbina, et.al- the authors demonstrated that AI models for drug discovery could easily be repurposed to design lethal chemical weapons, highlighting the dual use risks (Urbina et. al, 2022) of this technology. We propose a multi-layered policy framework, with the technical guardrails of federated learning to combat these insufficiencies. Federated learning allows decentralized training on localized data, preventing central aggregation of sensitive biological information that could enable bioweapons development if compromised. This still permits collaborative model improvement and evaluation. Thus balancing openness and security.

We conducted a simulation of this approach by passing our drug discovery ML model through the Flower federated learning framework by Cambridge. Results and report on our safety page.

Read our complete report on AI Safety in Bio here:

Wet Lab:  A modular toxin-antitoxin auxotrophy system provides a generalizable approach to improve the biosafety of engineered probiotics.

We designed a Clostridium strain dependent on the unnatural amino acid 3-iodo-L-tyrosine (IY) for viability by manipulating the toxin and antitoxin genes. Insertion of an amber codon should disrupt antitoxin translation, leading to toxin activation and cell death (Kato et. al, 2015).

Read about our auxotrophy part here

References

  1. Urbina, F., Lentzos, F., Invernizzi, C. et al. Dual use of artificial-intelligence-powered drug discovery. Nat Mach Intell 4, 189–191 (2022). https://doi.org/10.1038/s42256-022-00465-9
  2. Authors, T. F. (n.d.-b). A friendly federated learning framework. Flower. https://flower.dev/
  3. Kato Y. An engineered bacterium auxotrophic for an unnatural amino acid: a novel biological containment system. PeerJ. 2015 Sep 15;3:e1247. doi: 10.7717/peerj.1247. PMID: 26401457; PMCID: PMC4579030.
  4. Vento JM, Crook N, Beisel CL. Barriers to genome editing with CRISPR in bacteria. J Ind Microbiol Biotechnol. 2019 Oct;46(9-10):1327-1341. doi: 10.1007/s10295-019-02195-1. Epub 2019 Jun 5. PMID: 31165970; PMCID: PMC7301779.