Biosensors are predicted to play a significant role in the detection and treatment of cancer in the coming years. The sooner cancer can be detected in a patient, the better the outcome of treatment. Biosensor technology holds the potential to provide fast and reliable methods for detection of cancer cell metabolites, potentially well before tumor formation and metastasis has occurred. However, despite their potential, biosensors for many important cancer related molecules are currently unavailable. Furthermore, a general method for the design of biosensors has yet to be established. The goal of the proposed research project is to develop fluorescent, switch-based biosensors for the emerging cancer biomarkers lysophosphatidic acid (LPA) and sphingosine-1-phosphate (S1P). These two phospholipid signaling molecules have been implicated in the establishment and progression of a number of cancers. LPA and S1P biosensors will be designed using a combination of computational and experimental methods. Initially, the Rosetta software suite for macromolecular structure prediction and design will be employed to engineer proteins that bind LPA and S1P with a high degree of specificity and affinity. Those designs that display affinity for LPA or S1P will have their binding properties optimized through directed evolution and yeast surface display. After generating the LPA and S1P ligand binders, the final biosensors will be constructed by attaching a cyan and yellow fluorescent protein (CFP, YFP) Forster Resonance Energy Transfer (FRET) pair to the termini of the ligand binding domain. The CFP-YFP pair was chosen so that the biosensors will be both label-free (not requiring any additional cofactors for fluorescence) and entirely genetically encoded. This will enable the biosensors to be highly versatile, usable in a number of basic research settings (in vitro, in vivo) as well as diagnostics. The LPA and S1P biosensors will be switch-based, so that their fluorescence will be off (no FRET) or on (FRET) in the absence or presence of ligand, respectively. The results of the experiments outlined in this proposal will be immediately beneficial to cancer research. The LPA and S1P biosensors will be useful in a laboratory setting, to determine the effectiveness of chemotherapeutic agents, for example. In the clinic they will aid in the early detection of cancer as powerful diagnostics. Information gleaned during the course of experimentation will be used for future design of other protein-based ligand binders, both within the scope of this project and beyond. Consequently, this research should have far reaching impacts within the biological sciences that will extend beyond the project described above.
The current proposal ultimately seeks to engineer protein-based biosensors for two important makers of cancer, using computational and experimental methods. The results of this research will greatly aid in the early detection of specific types of cancer, and will serve as a foundation for the development of biosensors for additional cancer metabolites, as well as other medically relevant molecules.
|Bick, Matthew J; Greisen, Per J; Morey, Kevin J et al. (2017) Computational design of environmental sensors for the potent opioid fentanyl. Elife 6:|