Polybrominated diphenyl ethers (PBDEs) levels in environmental matrices have generally declined following their phaseout as flame retardants. The objective of this study was to determine the absorp...

Post-harvest storage loss in sugar beets due to root rot and respiration can cause >20% sugar loss. Breeding strategies focused on factors contributing to improved post-harvest storage quality are of great importance to prevent losses. Using 16S rRNA and ITS sequencing and sugar beet mutational breeding lines with high disease resistance (R), along with a susceptible (S) commercial cultivar, the role of root microbiome and metabolome in storage performance was investigated. The R lines in general showed higher abundances of bacterial phyla, Patescibacteria at the M time point, and Cyanobacteria and Desulfobacterota at the L time point. Amongst fungal phyla, Basidiomycota (including Athelia) and Ascomycota were predominant in diseased samples. Linear discriminant analysis Effect Size (LEfSe) identified bacterial taxa such as Micrococcales, Micrococcaceae, Bacilli, Glutamicibacter, Nesterenkonia, and Paenarthrobacter as putative biomarkers associated with resistance in the R lines. Further functional enrichment analysis showed a higher abundance of bacteria, such as those related to the super pathway of pyrimidine deoxyribonucleoside degradation, L-tryptophan biosynthesis at M and L, and fungi, such as those associated with the biosynthesis of L-iditol 2-dehydrogenase at L in the R lines. Metabolome analysis of the roots revealed higher enrichment of pathways associated with arginine, proline, alanine, aspartate, and glutamate metabolism at M, in addition to beta-alanine and butanoate metabolism at L in the R lines. Correlation analysis between the microbiome and metabolites indicated that the root’s biochemical composition, such as the presence of nitrogen-containing secondary metabolites, may regulate relative abundances of key microbial candidates contributing to better post-harvest storage.