Quaranskin, a combination of quarantine and skin, is a project based on the collection
and analysis of skin microbiome samples, collected from participants across Europe.
We aim to understand if there are correlations between behavioral characteristics that
involve activity, hygiene and human interaction, and the diversity and composition of
skin microbes at four body sites.
Study Pipeline
Participants recruitment
Emails are sent to all the members of our institution, the CRI, and all the european
iGEMers, by focusing on people form countries where confinement or social distanciation
are set up. The total number of participants expected is 70.
Participants enrollment
To be involved in the study each participants has to fill in a participation form and
link to it a signed and dated consent form.
A link is sent to them allowing them to create a account on the OpenHumans platform in
order to furnish them an ID code which we use to keep anonymity
Participants action
Once they are officially enroll in the study, we send to the participants by mail a kit
containing all tools needed to sample microbiome from 4 body sites and to send them back
to us, and by email a link to answer an online questionnaire asking questions covering 4
main topics : The intrinsic characteristic (age, sexe, nationality...), the hygiene
habits, the level of confinement and the skin disorder appeared since February 2020.
Microbiome sequencing
Once we receive the microbiome samples we send them directly to an external company,
Genewiz. They’ll extract bacterial DNA from the samples, amplify the V3-V4 regions of
the 16S RNA gene, and then sequence the amplicons.
Statistical analysis
After having analyzed the composition and diversity of each microbiome we’ll link these
results to the answer to the questionnaire to finally find some correlations between
some microbiome compositions and some characteristics of the lifestyle or some skin
disorder
Data Analysis
1. Diversity analysis by index of hygiene, personal information, level of restriction
The microbiomes in the generated database are grouped by index value in each of the 3
categories. By setting two indices, we can study the impact of the third element on the
diversity of the microbiome
2. Environmental factors which influence proportion of Staphylococcus
We define a proportion threshold, then we identify all the people who present a
population of Staphylococcus beyond this threshold. We finally look for parameters
common to these individuals,
3. Researching existing microbiome composition among our data set
We want to compare a typical composition of eczematic microbiome found in literature,
with our data
4. Analysis of data based on common symptoms
When a significant number of people present the same symptom, independently of the
environment and lifestyle, we want to make a synthesis of the typical composition of the
microbiome for this symptom.