| Literature DB >> 31635365 |
James P Tauber1, William R Collins2, Ryan S Schwarz3, Yanping Chen4, Kyle Grubbs5, Qiang Huang6, Dawn Lopez7, Raymond Peterson8,9, Jay D Evans10.
Abstract
The western honey bee remains the most important pollinator for agricultural crops. Disease and stressors threaten honey bee populations and productivity during winter- and summertime, creating costs for beekeepers and negative impacts on agriculture. To combat diseases and improve overall bee health, researchers are constantly developing honey bee medicines using the tools of microbiology, molecular biology and chemistry. Below, we present a manifesto alongside standardized protocols that outline the development and a systematic approach to test natural products as 'bee medicines.' These will be accomplished in both artificial rearing conditions and in colonies situated in the field. Output will be scored by gene expression data of host immunity, bee survivorship, reduction in pathogen titers, and more subjective merits of the compound in question. Natural products, some of which are already encountered by bees in the form of plant resins and nectar compounds, provide promising low-cost candidates for safe prophylaxis or treatment of bee diseases.Entities:
Keywords: bee disease; colony loss; honey bees; natural product; screening; traditional medicine; virus
Year: 2019 PMID: 31635365 PMCID: PMC6835950 DOI: 10.3390/insects10100356
Source DB: PubMed Journal: Insects ISSN: 2075-4450 Impact factor: 2.769
Figure 1Natural product screening process.
qPCR primers for a standard set of measured transcripts.
| Disease/Host | Target | Forward Primer | Reverse Primer | Reference |
|---|---|---|---|---|
|
| AGTATGAGCAGTAGGTTTTATTATA | GCCAAACACCAATAACTGGTACT | [ | |
| Deformed wing virus- | DWV-A,-B | ACGCAACCCCAGGAAT | GTAGCTAATTTTACCCAATCTTTAAA | [ |
| Nosemosis |
| TATTGTAGAGAGGTGGGAGATT | GTCGCTATGATCGCTTGCC | [ |
| Bacterial infection | Bacteria (all), including | AGAGTTTGATCCTGGCTCAG | CTGCTGCCTCCCGTAGGAGT | [ |
| Reference gene (host) | Ribosomal protein S5a ( | AATTATTTGGTCGCTGGAATTG | TAACGTCCAGCAGAATGTGGTA | [ |
| Reference gene (host) | Actin related protein 1 ( | CCAAAGACCCAAGCTCCCTA | TGGCTTATTGGTTTATGTTTTTCGT | [ |
| Immunity gene (host) | Hymenoptaecin ( | CTCTTCTGTGCCGTTGCATA | GCGTCTCCTGTCATTCCATT | [ |
| Age/nutrition/immunity (host) | Vitellogenin ( | TCGACAACTGCGATCAAAGGA | TGGTCACCGACGATTGGATG | [ |
A simulated chart for checking qPCR data. For simplicity, a sample number code can be used on tubes and extraction bags with a spreadsheet containing the precise details. Technical duplicates of qPCR reactions for the specimen are run and the Cq determined by the qPCR software. If the technical duplicates are close to one another, similar to those in Table 2, then one can proceed to qPCR singlet reactions. The reference gene RPS5a was run and also the antimicrobial peptide (AMP) gene Hymenoptaecin (“Hym”). The ΔCq = Cq minus Cq gene of interest “) was calculated. We observe that the honey bees that were inoculated with Nosema followed by natural product dosing (+Nosema+NP) had a higher relative gene expression of hymenoptaecin than the control treatment of a Nosema infection without the natural product dosing (+Nosema-NP). qPCR data should be coupled with survival data. CoV: Coefficient of Variation; 1st: first of two technical qPCR reaction replicates; 2nd: second of two technical qPCR reaction replicates; Replicate difference: the Cq difference between each technical qPCR reaction; Average: the average of the two technical qPCR reaction runs (not done when run in singlets); ΔCq: the difference between the reference gene (Rps5a) and the target gene (e.g., Hym), whereby a higher number represents higher relative gene expression.
|
|
|
|
|
|
|
|
| |
| 1 | + | 1 | 20.19 | 19.75 | 19.97 | 0.44 | 1.557971876 | |
| 2 | + | 1 | 21.1 | 20.03 | 20.565 | 1.07 | 3.67908707 | |
|
|
|
|
|
|
|
|
| |
| 1 | + | 1 | 25.2 | 26.1 | 25.65 | −0.9 | 2.481076425 | −5.68 |
| 2 | + | 1 | 28.2 | 28.9 | 28.55 | −0.7 | 1.733711898 | −7.985 |