General aim
To develop and validate mathematical models to numerically simulate the interplay between microbiome, lifestyle, culture and environment and their effects on oral and metabolic health during the first 1000 days of life.
Objectives at micro level
To model the dynamics and species competition within the microbiome communities (gut and oral) using inputs from in-vivo (WP2) and in-vitro studies (WP4) at functional and taxonomic levels.
Objectives at meso level
To model the interplay between host and microbiome in both directions: how does the microbiome influence the host’s health and vice versa.
Objectives at macro level
To model the links between various macro level parameters (lifestyle, dietary habits, demographics, sociocultural factors) and the models in the micro level.
Active period
Year 3-8
UvA-SILS, UvA-IBED, AUMC, TNO Microbiology & Systems Biology, TNO Child Health.
BaseClear, NIBI, Onkolyze, Supabase, Bètapartners.
A project on FAIR database development for human microbiome data samples has been performed at the UvA in collaboration with the co-funding partner Supabase. This has led to a manuscript. The manuscript has been submitted to the journal “Frontiers in Cellular and Infection Microbiology” and is currently under peer-review.
Meetings have been organized with GGD Amsterdam and data scientists to build and deploy a data delivery pipeline for the microbiome sequencing and demographics data.
Authors: Mathieu Dorst, Nathan Zeevenhooven, Rory Wilding, Daniel Mende, Bernd W. Brandt, Egija Zaura, Alfons Hoekstra, Last author: Vivek M. Sheraton
The authors have developed tools for creating big, organized library (database) for microbiome data (germs that live in and on our bodies) that can be easily accessed and used by researchers. This will help scientists share information and come up with new ways to tackle health issues, while also following privacy laws and protecting people’s personal information. They use a special platform to build the database and create a helpful set of tools that even non-experts can use to understand and work with the data. Below is a technical summary of the work.
The article proposes the creation of a real-time FAIR (Findable, Accessible, Interoperable, Reusable) compliant database for the handling and storage of human microbiome and host-associated data. This database development pipeline aims to facilitate innovation and reduce costs in research by making standardized, transparent, and readily available (meta)data.
The authors discuss potential conflicts arising from privacy laws and possible human genome sequences in metagenome shotgun data and propose alternate pathways for achieving compliance in such cases. They identify sensitive microbiome data, such as DNA sequences or geolocalized metadata, and consider the role of GDPR data regulations. The database is implemented using an open-source development platform, Supabase, allowing researchers to access, upload, download, and interact with human microbiome data in a FAIR compliant manner. Additionally, a large language model (LLM) is deployed to enable knowledge dissemination and non-expert usage of the database.
