Details zur Publikation

Kategorie Textpublikation
Referenztyp Zeitschriften
DOI 10.1007/s11306-023-01973-4
Lizenz creative commons licence
Titel (primär) Multi-country metabolic signature discovery for chicken health classification
Autor Wolthuis, J.C.; Magnúsdóttir, S. ORCID logo ; Stigter, E.; Tang, Y.F.; Jans, J.; Gilbert, M.; van der Hee, B.; Langhout, P.; Gerrits, W.; Kies, A.; de Ridder, J.; van Mil, S.
Quelle Metabolomics
Erscheinungsjahr 2023
Department UMB
Band/Volume 19
Heft 2
Seite von art. 9
Sprache englisch
Topic T7 Bioeconomy
Keywords Mass spectrometry; Machine learning; Gut; Inflammation; Enrichment; Chicken


To decrease antibiotic resistance, their use as growth promoters in the agricultural sector has been largely abandoned. This may lead to decreased health due to infectious disease or microbiome changes leading to gut inflammation.


We aimed to generate a m/z signature classifying chicken health in blood, and obtain biological insights from the resulting m/z signature.


We used direct infusion mass-spectrometry to determine a machine-learned metabolomics signature that classifies chicken health from a blood sample. We then challenged the resulting models by investigating the classification capability of the signature on novel data obtained at poultry houses in previously unseen countries using a Leave-One-Country-Out (LOCO) cross-validation strategy. Additionally, we optimised the number of mass/charge (m/z) values required to maximise the classification capability of Random Forest models, by developing a novel ranking system based on combined univariate t-test and fold-change analyses and building models based on this ranking through forward and reverse feature selection.


The multi-country and LOCO models could classify chicken health. Both resulting 25-m/z and 3784-m/z signatures reliably classified chicken health in multiple countries. Through mummichog enrichment analysis on the large m/z signature, we found changes in amino acid metabolism, including branched chain amino acids and polyamines.


We reliably classified chicken health from blood, independent of genetic-, farm-, feed- and country-specific confounding factors. The 25-m/z signature can be used to aid development of a per-metabolite panel. The extended 3784-m/z version can be used to gain a deeper understanding of the metabolic causes and consequences of low chicken health. Together, they may facilitate future treatment, prevention and intervention.

dauerhafte UFZ-Verlinkung
Wolthuis, J.C., Magnúsdóttir, S., Stigter, E., Tang, Y.F., Jans, J., Gilbert, M., van der Hee, B., Langhout, P., Gerrits, W., Kies, A., de Ridder, J., van Mil, S. (2023):
Multi-country metabolic signature discovery for chicken health classification
Metabolomics 19 (2), art. 9 10.1007/s11306-023-01973-4