Integrated Metabolomic and Transcriptomic Analyses Identify Elevated Tryptophan Metabolism and Altered Sugar...

Jujube flower disease (JFD) is a recurrent disorder affecting honeybees during the flowering period of Ziziphus jujuba, but its molecular basis remains unclear. To characterize JFD-associated molecular changes, we integrated widely targeted metabolomics and RNA sequencing (RNA-seq) in exposed asymptomatic jujube flower foragers (HC) and in bees showing characteristic JFD symptoms. Filtered metabolomic profiles showed clear separation between HC and JFD samples and revealed two major metabolite-level alterations. Tryptophan metabolism was the strongest enriched pathway among differentially abundant metabolites (Rich Factor = 14/16; FDR = 9.15×10-7), whereas metabolites decreased in JFD were enriched mainly in galactose metabolism (Rich Factor = 7/16; FDR = 1.23×10-4), amino sugar and nucleotide sugar metabolism (Rich Factor = 5/15; FDR = 0.00762), biosynthesis of nucleotide sugars (Rich Factor = 4/15; FDR = 0.0318), and starch and sucrose metabolism (Rich Factor = 3/8; FDR = 0.0318). RNA-seq detected 10,259 genes and identified 23 differentially expressed genes under the selected threshold, including 20 increased and 3 decreased genes in JFD bees. Although individual-gene differential expression was limited, preranked gene-set enrichment analysis identified moderate negative enrichment of the sugar supply/storage gene set (NES = -1.96; FDR = 0.024). The tryptophan/aromatic amino acid gene set was not enriched at the transcriptomic level, indicating that the tryptophan-related alteration was mainly observed at the metabolite level. Within these gene sets, HK showed the largest downward RNA-seq trend among the five displayed sugar-axis enzyme genes and a directionally concordant qRT-PCR trend; on this basis, HK was retained only as a candidate for future functional validation. Overall, these findings suggest that JFD is associated with altered tryptophan-related metabolism and reduced carbohydrate/nucleotide sugar-related metabolite abundance, with partial transcriptomic support for altered sugar supply and storage. This molecular profile provides candidate pathways and genes for future mechanistic investigation rather than established biomarkers, regulatory mechanisms, or evidence of disease causation.