One of the main projects during my PhD at ETH Zurich was the development of a receptor for caffeine in mammalian cells by protein engineering. Expanding the toolkit of synthetic biology by one more inducer of gene expression and controlling all kinds of cell implants and experiments with coffee was a lot of fun (involving drinking a lot of coffee!) and eventually led to a publication in the journal Nature Communications. Our work was also reported on by quite a few media outlets, for instance by The Guardian or New Scientist. A while ago I wrote a blog post about the work (and never got the chance to publish it somewhere), so if you don’t feel like reading the actual paper feel free to try the account below!
Treating Diabetes with a Cup of Coffee
Synthetic Biology – The Fusion of Engineering and Biology
When Gardner et al. built a genetic toggle switch in the humble bacterium Escherichia coli all the way back in the year 2000 (a simple gene switch which has two stable states of gene expression that can be alternated by the addition of inputs), it wouldn’t have crossed their mind that they kickstarted a whole scientific discipline in the process (Gardner et al., 2000). In the years since then, this new field of synthetic biology has made tremendous leaps. Making use of extensive genetic modifications in bacteria, plants or even mammalian cells, researchers such as myself equip living organisms with genetic circuits that reprogram them (Bojar and Fussenegger, 2016). Inducing gene expression with orthogonal small molecules or biomarker levels has resulted in novel cell-based therapies for diseases such as psoriasis (Schukur et al., 2015), Grave’s disease (Saxena et al., 2016) or Parkinson’s disease (Kojima et al., 2018). For these endeavors our laboratory and others implant engineered mammalian cells into mouse disease models to conduct pre-clinical trials. Engulfing these cells with an alginate-based gel matrix allows us to evade the immune system of the animal, which would otherwise react to the human cells.
Building a Caffeine-Sensing Receptor
Even though there are many inducers of gene expression available by now, the field of cell-based therapies is still lacking a side effect-free, inexpensive and easy-to-handle inducer for in vivo applications. As the control over gene expression is crucial for the future of cell-based therapies, I decided to work on this problem. Thinking of an everyday substance which is nonetheless specific to a few sources, non-toxic and inexpensive I came up with the humble molecule caffeine. Present only in coffee, tea and some other select sources, caffeine in the form of coffee is generally regarded as safe and has been shown to be without detrimental effects, even after decades of continuous usage (Poole et al., 2017). Relying on a camelid single-domain antibody, which binds caffeine in the nanomolar range and homodimerizes in the presence of caffeine (referred to as aCaffVHH) (Franco et al., 2010; Sonneson and Horn, 2009), I set out to build the first specific caffeine receptor in mammalian cells (Bojar et al., 2018).
First, I fused aCaffVHH to the DNA-binding domain from Tet Repressor protein (TetR) as well as several repeats of the transcription-transactivating viral peptide VPmin. This setup, mimicking the classical yeast two-hybrid system (Young, 1998), created a caffeine-sensing synthetic transcription factor which, in the presence of caffeine, would recruit VPmin to the binding site of TetR. Cloning the reporter gene human placental secreted alkaline phosphatase (SEAP) after this binding site allowed for an easy readout of gene expression. This design was indeed functional and resulted in caffeine-dependent gene expression in the presence of high micromolar concentrations of caffeine.
Yet as the caffeine concentration in vivo seldom exceeds the low micromolar range, I needed to optimize the sensitivity of the caffeine receptor. To achieve this, I decided to capitalize on the powers of signal transduction, which can potentiate a signal and potentially increase the sensitivity of the receptor. Thus I fused aCaffVHH to a range of receptors: a heterodimer between the Interleukin-4 receptor subunit alpha and the Interleukin-13 receptor subunit alpha-1 resulting in the activation of STAT6; a homodimer of Fibroblast growth factor receptor 1 resulting in the activation of the MAPK pathway; and finally a homodimer of a fusion of Erythropoietin receptor and Interleukin-6 receptor subunit beta (EpoR-IL6ST) resulting in the activation of STAT3 (Scheller et al., 2018).
The fusion to EpoR-IL6ST resulted in the best performing receptor, leading to strong activation in the presence of nanomolar concentrations of caffeine. Calling it caffeine-stimulated advanced regulators (C-STAR), I went on to characterize its dynamics. Gene expression induced by activation of the C-STAR system was reversible and dose-dependent. In fact I could show that with a standard curve generated with pure caffeine, the system was able to quantify the caffeine concentrations in a whole range of commercial products (Nespresso® capsules, Coca Cola®, Starbucks® products etc.). Additionally, decaffeinated coffee was unable to activate the caffeine receptor. At this point, everything seemed to be ready for an in vivo test.
Treating Type-2 Diabetes with Mammalian Designer Cells Responsive to Caffeine
Encapsulating human designer cells, stably genetically modified by transposase-mediated insertion of the C-STAR genes into the genome, allowed me to implant them into mice. There, the consumption of coffee also led to an induction of SEAP expression, which confirmed the functionality of the C-STAR system in vivo. Measuring of inflammatory markers such as TNF-α and IL6 by ELISA confirmed that the implant itself was not immunogenic.
After exchanging the reporter gene SEAP with the Type-2 diabetes drug glucagon-like peptide 1 (shGLP-1), I implanted my C-STAR-equipped cells into a genetic leptin receptor-deficient (db/db) as well as a high fat diet-induced obesity (DIO) mouse model for Type-2 diabetes. Characterized by insulin resistance and resulting high blood glucose levels, shGLP-1 is proposed to restore insulin sensitivity and thereby lower blood glucose levels (Xie et al., 2016). I was enthusiastic to see a restoration of glucose homeostasis in mice receiving the C-STAR-equipped cells and regular doses of coffee, in comparison to untreated control mice. These experiments showed a possible treatment of Type-2 diabetes with coffee-controlled human designer cells.
The efficient functionality of caffeine as an inducer molecule makes me confident that it can be used as a tool in cell-based therapies. In addition to the benefits already mentioned, the different sensitivities achieved by the different receptors allow for a personalized therapy and the everyday quality of caffeine might even allow for a perfect blend of therapy and patient lifestyle and increase patient compliance, which is an important issue (Hugtenburg et al., 2013). One of my biggest takeaways of this project is the modular caffeine-dependent protein dimerization system relying on aCaffVHH. It worked very well and flexible in all orientations tested during this project and I’m continuing to use it in new projects.
Bojar, D., Fussenegger, M., 2016. The best of both worlds: reaping the benefits from mammalian and bacterial therapeutic circuits. Curr. Opin. Chem. Biol. 34, 11–19. https://doi.org/10.1016/j.cbpa.2016.05.012
Bojar, D., Scheller, L., Hamri, G.C.-E., Xie, M., Fussenegger, M., 2018. Caffeine-inducible gene switches controlling experimental diabetes. Nat. Commun. 9. https://doi.org/10.1038/s41467-018-04744-1
Franco, E.J., Sonneson, G.J., DeLegge, T.J., Hofstetter, H., Horn, J.R., Hofstetter, O., 2010. Production and characterization of a genetically engineered anti-caffeine camelid antibody and its use in immunoaffinity chromatography. J. Chromatogr. B 878, 177–186. https://doi.org/10.1016/j.jchromb.2009.06.017
Gardner, T.S., Cantor, C.R., Collins, J.J., 2000. Construction of a genetic toggle switch in Escherichia coli. Nature 403, 339–342. https://doi.org/10.1038/35002131
Hugtenburg, J.G., Timmers, L., Elders, P.J., Vervloet, M., van Dijk, L., 2013. Definitions, variants, and causes of nonadherence with medication: a challenge for tailored interventions. Patient Prefer. Adherence 7, 675–682. https://doi.org/10.2147/PPA.S29549
Kojima, R., Bojar, D., Rizzi, G., Hamri, G.C.-E., El-Baba, M.D., Saxena, P., Ausländer, S., Tan, K.R., Fussenegger, M., 2018. Designer exosomes produced by implanted cells intracerebrally deliver therapeutic cargo for Parkinson’s disease treatment. Nat. Commun. 9. https://doi.org/10.1038/s41467-018-03733-8
Poole, R., Kennedy, O.J., Roderick, P., Fallowfield, J.A., Hayes, P.C., Parkes, J., 2017. Coffee consumption and health: umbrella review of meta-analyses of multiple health outcomes. BMJ 359, j5024. https://doi.org/10.1136/bmj.j5024
Saxena, P., Charpin-El Hamri, G., Folcher, M., Zulewski, H., Fussenegger, M., 2016. Synthetic gene network restoring endogenous pituitary-thyroid feedback control in experimental Graves’ disease. Proc. Natl. Acad. Sci. U. S. A. 113, 1244–1249. https://doi.org/10.1073/pnas.1514383113
Scheller, L., Strittmatter, T., Fuchs, D., Bojar, D., Fussenegger, M., 2018. Generalized extracellular molecule sensor platform for programming cellular behavior. Nat. Chem. Biol. https://doi.org/10.1038/s41589-018-0046-z
Schukur, L., Geering, B., Charpin-El Hamri, G., Fussenegger, M., 2015. Implantable synthetic cytokine converter cells with AND-gate logic treat experimental psoriasis. Sci. Transl. Med. 7, 318ra201. https://doi.org/10.1126/scitranslmed.aac4964
Sonneson, G.J., Horn, J.R., 2009. Hapten-Induced Dimerization of a Single-Domain VHH Camelid Antibody. Biochemistry (Mosc.) 48, 6693–6695. https://doi.org/10.1021/bi900862r
Xie, M., Ye, H., Wang, H., Charpin-El Hamri, G., Lormeau, C., Saxena, P., Stelling, J., Fussenegger, M., 2016. β-cell-mimetic designer cells provide closed-loop glycemic control. Science 354, 1296–1301. https://doi.org/10.1126/science.aaf4006
Young, K.H., 1998. Yeast Two-hybrid: So Many Interactions, (in) So Little Time…. Biol. Reprod. 58, 302–311. https://doi.org/10.1095/biolreprod58.2.302