High-throughput sequencing, bioinformatics and machine learning as a soil health diagnostic tool
Die Auswirkungen der landwirtschaftlichen Praktiken und des Pestizideinsatzes auf die Bodenqualität sind ein wachsendes Anliegen von Verbrauchern, Landwirten und Bodenmanagern. To assess this impact, bioindicators, such as protists, have great potential, but their use remains limited because current methods do not allow detailed and rapid analysis of soil samples. To overcome these drawbacks, species identification based on DNA sequences ("barcoding") coupled with new ultra-high throughput sequencing techniques represents a promising approach. Die enorme Menge an Sequenzen und ihre hohe Komplexität machen es jedoch schwierig, sie mit herkömmlichen Mitteln zu verarbeiten. It is therefore essential to develop methods combining bioinformatics and Machine Learning (ML) to (i) quantify, analyze and process protist sequences; (ii) identify and select bioindicators (a subset of protists) associated with different stressors; but also to (iii) model their relative abundance under different conditions, leading to the development of predictive diagnostic models.
We analyzed the composition of protist communities in 28 vineyards in Valais using metabarcoding and compared the predictive performance of different ML algorithms for several variables characterizing soil quality. Our innovative results show that the composition of protist communities can be used to predict a wide range of variables, including the presence of pesticides (copper) in soils. Taxonomisch gesehen waren Ciliophora und Cercozoadie protist groups mit der höchsten Anzahl an Bioindikatoren. Functionally, the majority of bioindicators corresponded to heterotrophic taxa, but some variables (plant biomass and soil pH) were mainly predicted by photosynthetic taxa. Unsere Analysen ermöglichten uns die Entwicklung von Skripten zur Identifizierung von Biomarkern und zur Vorhersage verschiedener Bodenparameter.
Aufwertung
PEÑA C.-A., BROCHET X., FOURNIER B., HEGER T., Quantitative monitoring of agricultural soils using protist communities, SIB day 2020, 8 - 10 June 2020, Lausanne, Switzerland
HEGER T. J., JIBRIL M., STEINER M., XAVIER B., LAMY F., MOTA M., NOLL D., BACHER S., PENA C., Protist communities in vineyard soils: what do they tell us about soil quality and health? Joint meeting of the phycological society of America and the international society of protistologists, 29. Juli - 2. August 2018, Vancouver, Kanada.
MAMMERI J., BROCHET X., HEGER T., BACHER S., STEINER M., PENA C., MaLDIveS: Machine Learning Diagnostic Soil . SIB days 2018 (Swiss Institute of Bioinformatics), 26. bis 27. Juni 2018, Lausanne, Schweiz.
2017 - in progress
Partner: HEIG-VD
Funding: HES-SO
