Team:Edinburgh OG/HP/Gold

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GOLD REQUIREMENT

How the investigation of biosafety issues have been integrated
into the design and execution of the ExpandED project.



CARE tool's updated code

This year’s Edinburgh OG iGEM team has worked on a program that allows the evaluation of curated secondary metabolites’ toxicity produced by a range of microorganisms (bacteria and fungi). The program is intended to complement the current risk assessment practices by constituting an additional precautionary step that is to be followed before any work in the laboratory with the reviewed host strain begins. Furthermore, it is intended to be accessible to a wide constituency of experts in the field, trainees, DIY biologists, other stakeholders and the general public.


This tool, named “CARE” – Chassis Assessment & Risk Evaluation
includes information about 30 microorganisms:


● The microorganisms from the Edinburgh OG 2016 iGEM team: the cyanobacterium Synechosistis sp. PCC 6803, the bacterium Rhodococcus jostii RHA1 and the fungus Penicillium roquefortii.

● The non-model organisms used by iGEM teams based in North America in 2014 and 2015 (as documented by the Yale 2015 iGEM team): Chlamydomonas reinhardtii, Chlorella kessleri, Chlorella vulgaris, Flavobacterium psychrophilum, Gilliamella apicola, Lactococcus lactis, Rhizobium tropici CIAT 899, Snodgrassella alvi and Synechococcus sp. PCC 7002.

● The industrially relevant Shewanella oneidensis, Saccharopolyspora erythraea, Myxococcus xanthus, Cupriavidus necator, Chromobacterium violaceum, Carnobacterium maltaromaticum, Sorangium cellulosum and Pseudomonas fluorescens.

● The model and non-model microorganisms with an annotated genome from a selection of this year’s iGEM teams (as seen in the Outreach section): E. coli BL21DE3, E. coli C41, E. coli MG1655, Yarrowia lipolytica, Saccharomyces cerevisiae W303, Dechloromonas aromatica, Pseudomonas putida KT2440, Synechococcus elongatus PCC 7942, Pichia pastoris, Myxococcus xanthus and Acinetobacter sp. ADP1.


Along with these microorganisms, a database with the related secondary metabolites information (i.e. the general class of secondary metabolite, the most similar biosynthetic gene cluster (BGC) related to the secondary metabolite, its location in the genome and the percentage of gene similarity for each annotated microorganism) was constructed using the Antibiotics & Secondary Metabolite Analysis Shell (antiSMASH) software.

It is worth mentioning that the databases will be able to be updated by integrating new microorganisms or editing existing ones simply by logging-in and waiting for the validation of the data by the program administrators.

TOXICITY CRITERIA




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According to the toxic effect of these compounds on human health, animal health and the environment, a quantitative criterion for clear toxicity scores was created using a scale from 1 to 5 and a “traffic light” colour scheme. If the reviewed information showed that the secondary metabolite did not affect in a negative manner any of the three parameters, it was considered non-toxic and categorised as a “1” (green). If the data showed that the compound exhibited some degree of toxicity but nothing considerably serious or untreatable, it was considered slightly to moderately toxic and scored as a “3” (yellow). And if it showed that the secondary metabolite was extremely toxic, it was considered as highly toxic and classified as a “5” (red). However, considering there were three parameters to be considered, combinations of those three scores could occur (e.g., a secondary metabolite being considered non-toxic for humans but slightly to moderately toxic to animals). Therefore, if a compound was non-toxic according to one parameter and slightly to moderately toxic for the others, it was categorised as a “2” (green-yellow). On the other hand, if it was slightly to moderately toxic according to some parameter and highly toxic for others, it was classified as a “4” (yellow-red). Finally, if the secondary metabolite had no documented toxicity information, or if there was no specific BGC exposed by antiSMASH and just the general class of secondary metabolite or microorganism, the compound was categorised as “?” (black) with the note to consider if, according to the precautionary principle, one should pursue the use of the given microorganism in the laboratory.

As a proof of concept, the 30 organisms were screened using the CARE tool and the results showed that, although some secondary metabolites were considered as toxic (e.g. roquefortine, PR-toxin, isofumigaclavine and mycophenolic acid for P. roqueforti), their amounts do not affect human health, meaning that these organisms were safe to work with in laboratory settings and we could proceed with the experimentation with them.

When a laboratory works on a non-model organism with the objective of harnessing its industrial potential, genome editing processes may be involved (e.g., CRISPR-Cas9 tool). Therefore, this tool could additionally be used in order to determine differences in toxicity between native and genetically modified organisms.

Outreach

In order to test the tool’s functionality, we contacted via social media this year’s iGEM teams and the following 25 teams engaged on our conversation: Vilnius, Dundee, Cardiff, Exeter, Imperial, Valencia UPV, UPO Sevilla, BIOSINT México, TEC Costa Rica, Tec Chihuahua, Emory, MQ, BGU, IIT Kharagpur, Technion, Barcelona, Leiden, TU Darmstadt, Queens, Evry Genopole, MSU, EPFL, Georgia State, DTU Denmark and LMU & TU Munich.

Special thanks go to the Tec Chihuahua, Tec Costa Rica and EPFL teams for being “CARE ambassadors” and helping us spread the word of our tool.

From a total of 29 organisms, the majority of the engaged teams used model organisms (81%) while 5% used non-model strains (Yarrowia lipolytica, Dechloromonas aromatica, Synechococcus elongatus PCC 7942 and Myxococcus xanthus). Some of those organisms were included in our program’s database depending on whether they had an annotated genome (accession number). It is also worth mentioning that the non-model chassis from this year was different from the list presented by the Yale iGEM team from the two previous years.

LIMITATIONS AND FURTHER IMPROVEMENTS

It is important, however, to establish the limitations of our program so that they can be addressed properly in the future. One limitation of the CARE tool is that it requires any microorganism to have an annotated genome for it to be screened, as the accession number is needed to build the database from antiSMASH.

Moreover, when performing the data mining for each secondary metabolite, we found that a significant number of the assessed secondary metabolites did not have clear data on their toxic effect on the surrounding environment, humans and animals (i.e. classified as “?” – unknown – to be managed according to the precautionary principle). These kind of results could spur further investigation into these compounds and corresponding biological functions and effects by the scientific community. Further, the utility of the tool is limited by the great number of as yet unknown secondary metabolites. In filamentous fungi alone the number of unknown mycotoxins is expected to be in the range of several hundred thousand (Barlow et al., 2007).

Furthermore, the program could be further refined by completing the missing front-ends and including a risk matrix for every secondary metabolite in which the risks are directly related to the probability of them happening. Furthermore, since the extent of the assessments on non-model organisms is not limited to their secondary metabolites, tools to screen for recombinases, virulent factors and CRISPR-Cas9 systems could be developed for them to be incorporated in the CARE program.