Team:Nantes/Description

After talking with our grandparents and the elderly of our communities we realized that with age, people usually tend to need more medication. And with medicine such as pills that greatly resemble each other in color, shape and size a polymedicated patient can be lead into confusion which can lead to medication errors by omission and/or overdose.

A medication error is an unintended failure in the drug treatment process that leads to, or has the potential to lead to, harm to the patient (1) .

One doctor we talked to recalls treating an elderly man that had entered the hospital in a coma due to overdose on sleeping pills because he had mixed up his sleeping pills with his pills for cardiac deficiency.

To tackle this issue we decided to create a device that would deliver different medication at different doses for a very precise period of time and at given hours.

It is while doing research on this idea that we stumbled across an article from Guy Aidelberg (2) that shows the existence of this non glucose sugar hierarchy in E.coli and how our idea for the BiO’clock was born. We soon realized that our tool did not have to limit itself to the administration of medications but could also be used in other areas such as metabolic engineering or pharmaceutical/industrial production.

(1) : “Good practice guide on recording, coding, reporting and assessment of medication errors” European Medicines Agency, 23 October 2015, Pharmacovigilance Risk Assessment Committee (PRAC)
(2) “Hierarchy of non-glucose sugars in Escherichia Coli.” Aidelberg Guy et al, BMC Systems Biology., 2014 , PMID: 25539838

E.coli consumes non-glucose sugars according to a specific hierarchy. We used this hierarchy in our project to monitor the duration of gene expression.

To create our tool, we built four plasmidic constructs: each containing a sugar-responsive promoter (pLAC, pSRL, pARA or pRIB) (1) upstream of a fluorescent reporter protein (GFP, CFP, RFP or YFP) (2).

With these constructs, we characterized the activity of the promoters in different conditions, varying the medium with different concentrations of sugars. It allowed us to build a model predicting the amount of sugar needed in the medium to trigger gene expression at a certain time and for a certain duration. This fundamental tool could be used in a wide variety of fields such as administration of medicine, metabolic engineering and industrial and pharmaceutical production.

(1) pLAC : promoter from K12 MG1655 E.coli controlling the expression of the lactose operon
pARA : promoter from K12 MG1655 E.coli controlling the expression of the arabinose operon
pSRL : promoter from K12 MG1655 E.coli controlling the expression of the sorbitol operon
pRIB : promoter from K12 MG1655 E.coli controlling the expression of the ribose operon

(2)GFP : Green Fluorescent Protein
CFP : Cyan Fluorescent Protein
RFP : Red Fluorescent Protein
YFP : Yellow Fluorescent Protein