Mammalian cell-based therapies represent a promising emerging technology that leverage the natural capabilities of cells – including sensing, secretion, and biosynthesis – for the treatment of diseases such as arthritis, infectious diseases, and cancer. A particularly exciting class of these therapies, cancer immunotherapy, strives to leverage the natural properties of the immune system to seek and destroy cancer cells. One such example, genetically engineered T cells, is especially promising, and for patients with certain types of cancers, this approach has already delivered astounding clinical benefits. Looking forward, a major challenge will be extending these benefits to other types of cancer, as well as to other diseases, which will require new therapeutic capabilities. Specifically, there exists a need for technologies enabling one to program cells to sense and respond to their environment in a defined fashion, beyond native responses. Towards this goal, our lab has developed a platform for engineering novel protein biosensors for extracellular cues, which we have termed modular extracellular sensor architecture (MESA). MESA comprises a two chain, self-contained receptor-signal transduction system in which ligand binding induces receptor dimerization, which then releases a sequestered transcription factor to regulate expression of an “output†gene or genes. We have demonstrated the ability of MESA to detect a soluble extracellular cue (via scFv antibody fragment-based ligand binding domains) and in response, modulate the activity of an endogenous gene (via a Cas9-based transcription factor). As a proof-of-concept experiment, we utilized these receptors to functionally “rewire†T cells to secrete an immune-potentiating factor when these cells are exposed to an immunosuppressive cue – a functionality that is not observed in nature. Thus, this work demonstrated the possibility of engineering or custom-rewiring cellular input/output for a range of applications. However, how one could rapidly develop of suite of novel MESA biosensors that respond to physiologically-relevant and functionally related environmental cues to enable detection of a diverse range of ligands remains an open and important question that applies to MESA as well as many other cellular engineering technologies.
Here, we report the exploration of strategies for optimizing the MESA mechanism to render this platform readily generalizable to sensing any given novel ligand of interest. To this end, we systematically investigated each key part of the MESA architecture to diminish background signaling and improve modularity. To explore background signaling, we evaluated various native and synthetic transmembrane domains (TMDs) which greatly impacted background and ligand-inducible signaling propensity of the MESA receptors. Additionally, we evaluated whether modifying the fundamental MESA mechanism to require an additional enzymatic reconstitution step would decrease the background signaling in the absence of ligand. We next investigated how the composition and structure of the extracellular linkers, which connect the binding domain to the TMD, affect the MESA chain expression and association in the absence of ligand. We identified design variants that dramatically improve MESA expression and appear to generally suppress problematic phenomena such as aggregation in the absence of ligand. Overall, this study makes great strides toward the goal of generalizing MESA technology to aid in efficiently designing, building, and evaluating custom receptors based upon MESA or conceivably related platforms. Ultimately this will enable the rapid development of a diverse array of synthetic biology technologies for engineering cells to be responsive to ligands of interest for diverse applications in medicine and fundamental research.
