Each year, almost half of all beehives suffer from colony collapse disorder (CCD) (1). CCD is a complex problem caused by various factors like disease, temperature, and food availability. However, one significant contributor to CCD is Varroa mites. These mites infiltrate beehives by entering as adult females and laying eggs inside brood cells (8). Once the eggs hatch and the bees emerge, the female mites attach themselves to the bees, reproducing and infesting the colony. If left untreated, these mites eventually lead to mass population loss, culminating in CCD.
Currently, there are only two main diagnostic methods for detecting Varroa mites: the powdered sugar test and the alcohol test. Both methods involve taking around one cup of bees out of the hive and placing them in a container. The bees are then covered in confectioners’ sugar or ethanol, depending on the method used. The container is vigorously shaken to make the mites fall off, and a mesh cover is used to separate the mites from the bees. The mites are then counted to determine the infestation rate (number of mites per 100 bees). Unfortunately, these methods are highly disruptive and prone to inaccuracy.
Our project aims to address this diagnostic challenge by developing a biosensor-based testing method to detect Varroa mites. We exploit the fact that Varroa mite excrement consists of 95% guanine, which provides us with a suitable target (3). Our biosensor functions by triggering a genetic pathway in the presence of guanine, resulting in the production of mScarlet-I, a protein that can be visually analyzed or measured using a spectrophotometer. This allows us to determine the number of Varroa mites present. The data obtained can then assist beekeepers in making informed treatment decisions.
We chose this project for this year's iGEM because our home state, North Dakota, is the top honey-producing state in the United States (9). North Dakota also has the second highest number of bee colonies and the highest number of bee colonies per capita. Moreover, North Dakota's economy is heavily focused on agriculture and has recently embraced autonomous systems and agricultural technology (Agtech). Therefore, we believe our project can provide significant value to the local beekeeping and agricultural ecosystems.
The first genetic approach was based on the Guanine-II Riboswitch (2). Riboswitches are regulatory agents located within mRNA that modify the production of the protein produced by its mRNA based on the concentration of an effector molecule. In this case, the effector molecule of Guanine-II Riboswitch is guanine. If the concentration of guanine is high enough, the riboswitch upregulates production of the protein it is attached to. In our case, it increases protection of our bioreporter mScarlet-I, a red fluorescent protein that is also easily visible to the naked eye.
The second genetic approach was based on the purR Purine Sensor (4,5,6,7). This system depends on the purR purine sensor and a tetR regulation switch to produce the same mScarlet-I reporter. If the guanine concentration is high enough, then the purR sensor upregulates production of the PurR repressor protein. The PurR repressor protein represses production of the TetR protein. With a lack of TetR repressor protein, expression of mScarlet-I is upregulated.