This protocol was developed for the COST-Action “Super-B”, whose purpose was to coordinate research, outreach and policy towards sustainable pollination1-3. The protocol addresses the detection of parasites and pathogens across bee species, as one of several possible drivers of bee decline4,5. It consists of four major components:
1. A sample collecting protocol, based around a dominant bee species driving pathogen distribution among other bee species
2. A sample processing protocol, based on analyzing nucleic acids from individual bees
3. A pathogen detection protocol, based on RT-qPCR with broad-range primers for several common pathogens
4. A barcoding protocol, for accurate bee species identification
The protocols have largely been adapted from existing knowledge and protocols but also include two key innovations: the use of passive reference nucleic acids and synthetic positive controls, that significantly improve the quality and robustness of the raw data, and thus the reliability of the analyses and conclusions.
Figure 1
Figure 2

Figure 3
Figure 4
This is a list of supplementary files associated with this preprint. Click to download.
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Posted 30 Apr, 2021
Posted 30 Apr, 2021
This protocol was developed for the COST-Action “Super-B”, whose purpose was to coordinate research, outreach and policy towards sustainable pollination1-3. The protocol addresses the detection of parasites and pathogens across bee species, as one of several possible drivers of bee decline4,5. It consists of four major components:
1. A sample collecting protocol, based around a dominant bee species driving pathogen distribution among other bee species
2. A sample processing protocol, based on analyzing nucleic acids from individual bees
3. A pathogen detection protocol, based on RT-qPCR with broad-range primers for several common pathogens
4. A barcoding protocol, for accurate bee species identification
The protocols have largely been adapted from existing knowledge and protocols but also include two key innovations: the use of passive reference nucleic acids and synthetic positive controls, that significantly improve the quality and robustness of the raw data, and thus the reliability of the analyses and conclusions.
Figure 1
Figure 2

Figure 3
Figure 4
This is a list of supplementary files associated with this preprint. Click to download.
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