Abstract
State-of-the-art virus detection technology has advanced a lot, yet technology to evaluate the impacts of viruses on bee physiology and health is basically lacking. However, such technology is sorely needed to understand how multi-host viruses can impact the composition of the bee community. Here, we evaluated the potential of hemolymph metabolites as biomarkers to identify the viral infection status in bees. A metabolomics strategy based on ultra-high-performance liquid chromatography coupled to high-resolution mass spectrometry was implemented. First, we constructed a predictive model for standardized bumble bees, in which non-infected bees were metabolically differentiated from an overt Israeli acute paralysis virus (IAPV) infection (R2Y = 0.993; Q2 = 0.906), as well as a covert slow bee paralysis virus (SBPV) infection (R2Y = 0.999; Q2 = 0.875). Second, two sets of potential biomarkers were identified, being descriptors for the metabolomic changes in the bee’s hemolymph following viral infection. Third, the biomarker sets were evaluated in a new dataset only containing wild bees and successfully discriminated virus infection versus non-virus infection with an AUC of 0.985. We concluded that screening hemolymph metabolite markers can underpin physiological changes linked to virus infection dynamics, opening promising avenues to identify, monitor, and predict the effects of virus infection in a bee community within a specific environment.
Highlights
Viruses are etiological agents of diseases and infect bee species [1]
In bees receiving 50% sugar water, models had a predictive power to (1) find an overt (IAPV) and covert (SBPV) infection (Table 1, model 5 for Israeli acute paralysis virus (IAPV), model 9 for slow bee paralysis virus (SBPV)) and (2) discriminate between the two viruses (Table 1, model 15). These results revealed that UHPLC-Orbitrap-MS-based metabolomics could successfully establish and distinguish the metabolic fingerprints of virus-infected bees from that of the non-virus-infected phosphate buffer saline (PBS) controls, even in the asymptomatic SBPV covertlyinfected bees
This study provided the first evidence of biomarker discovery for predicting virus infection in bees
Summary
Viruses are etiological agents of diseases and infect bee species [1]. The current diagnostic arsenal of virus infection in bees exhibits high sensitivity (e.g., high-throughput sequencing can detect down to a single targeted molecule), and new viral sequences are being reported at a higher rate than ever before [4,5,6]. This raises two questions about bee viral disease monitoring. The covert infection by deformed wing virus (DWV) represents a sword of Damocles permanently threatening the survival of honey bee colonies, and any factors affecting the honey bee’s antiviral defences can turn this pathogen into a dangerous killer [13]
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