Team:MichiganState/Contribution
Contribution
3D Printed Bee Feeder
For part of our project, the Device subteam designed a bee feeder that could be used to selectively administer the Bee-tox probiotic. For ease of replication and cost-effectiveness, the feeder was designed to be 3D printed. The file for the body of the device can be downloaded here. This design was successfully printed in dental resin and clear V4 resin. It includes a drainage hole for printing as well as a hole for filling the feeder. Typical rubber stoppers can be used for sealing the device before use. External dimensions are 10cm x 10cm x 6.5 cm. The filling and drainage holes are both 0.6 cm in diameter. The internal tank dimensions are 9.5 cm x 2.9 cm x 9.5 cm, leading to an approximate maximum volume of over 260 cm3.
This printer was designed to be compatible with a motorized cover and camera for image recognition as well. As a result, a separate motor cover was designed to be used with the feeder. This piece was also 3D printed using the same methodology. The .stl file for printing can be downloaded here.
This feeder is a cost-effective and simple device for any iGEM teams working with bees. We are not the first team to work on a bee probiotic and certainly will not be the last; having a mechanism to administer this probiotic is an integral part of a successful product and, to the best of our knowledge, no iGEM team has designed a feeder before. The ease and simplicity of 3D printing makes this option especially helpful for future teams.
Images of the printed feeder and motor cover using the files shared above can be seen here:
Multi-omics Approach
The bioinformatics team decided to take a basic approach to determine what imidacloprid-degrading enzyme candidates to incorporate within the Bee-tox system. Throughout our comprehensive literature review on our Design Page, we had found a wealth of knowledge on imidacloprid metabolism, yet we did not find an enzyme candidate that would have a high degree of engineering success within our chassis S. alvi. Enzymes with well-characterized mechanisms to metabolize imidacloprid were often accompanied by complex enzymatic machinery that limited engineering success within S. alvi, and simpler enzyme systems found to be associated with imidacloprid-resistance had limited experimental findings on the specific mechanisms of imidacloprid degradation.
In order to bridge this knowledge gap, we hope to develop a more in-depth understanding of imidacloprid metabolism by soil microbes by creating a detailed snapshot of P. putida EM371’s transcriptome and metabolome when exposed to imidacloprid. As described in depth within the Design Page and Engineering Page: using mass spectroscopy data collected with LC-MS/MS, we hope to create intricate metabolite networks to identify the imidacloprid metabolites generated by P. putida EM371. In parallel, we hope to determine which genes are involved in imidacloprid-degradation using the transcriptome developed from RT-qPCR and RNA-seq. Combining the information from both thrusts, we hope to be able to determine which enzymes are responsible for each step of imidacloprid’s transformation to 6-CNA.
Despite restrictions due to the ongoing COVID-19 pandemic, we have gathered promising results from our metabolomics studies that indicate the future applicability of molecular networking towards our project. Furthermore, we have developed in-depth documentation of the tools we used to create these networks within the GNPS environment. While we were unable to execute our transcriptomics experiments, we have curated a detailed outline of experimental protocols to develop a transcriptome of P. putida (Engineering Success and Experiments).
In addition to its application towards elucidating imidacloprid-degradation pathways, this multi-omics approach has future applications towards determining the efficacy of the fully-engineered Bee-tox system. Specifically, using metabolomics and transcriptomics in an untargeted manner allows us to study general changes in cellular behavior with the addition of the detoxifying enzyme system (e.g. studying changes in metabolite concentrations of commonly used metabolic pathways, observing gene expression changes in well-characterized regulatory systems, etc).
This basic approach taken on by MichiganState’s Bioinformatics team goes against the common strategy of iGEM teams to design and engineer systems that are well characterized. Through the experimental outline and protocols we have developed this Summer, we hope to encourage future iGEM teams to use metabolomics and transcriptomics to engineer future projects, especially as these technologies become more accessible to teams.