Mining of wastewater metagenomic data to identify population health and disease trends (MiWaGen)
Wastewater-based epidemiology (WBE) is a tool that provides a novel disease surveillance strategy at population level in a cost-effective manner. Wastewater treatment plants (WWTPs) are hotspots for all anthropogenic actions; WWTPs receive wastewater from households, industries, and hospitals, and constitute perfect collection points of composite samples containing human excreta (feces, urine, spit, nasal secretion, skin rashes etc.) and thus combines a myriad of potential disease markers in the community.
New ways of utilizing the metagenomics data are needed in order to produce models that could be used to simulate the phenomena and consequently extrapolate outside the datasets’ limits. This project will explore the potential of total metagenome from WWTPs as a trusted source of population health data at the community level.
Objectives
- To expand the wastewater environmental sample and data collection
- To produce a representative collection of community wastewater-based metagenome with corresponding health register data
- To map the population-level spatial and temporal differences in human microbiome by using metagenomic signatures from wastewater
- To investigate the metagenomic risk indicators for communicable and chronic diseases by comparing wastewater data to health registers
- To test if a machine learning model can forecast disease incidence from metagenomic wastewater signatures
- To achieve the goals set for the project, and to utilize and store the outputs of the research
Implementation
The project is divided into four work packages:
- Metagenomic sequence data retrieval from community wastewater
- Preparing, processing and analyzing metagenome and health register data
- Associations between population health statistics and wastewater-based metagenomic signatures
- Project dissemination and management
Partners
Tampere University
Funding
Research Council of Finland
Contact information
Tarja Pitkänen
chief specialist
Phone: +358 29 524 6315
[email protected]
