From transcriptomics to digital twins of organ function.

Cell level functions underlie tissue and organ physiology. Gene expression patterns offer extensive views of the pathways and processes within and between cells. Single cell transcriptomics provides detailed information on gene expression within cells, cell types, subtypes and their relative proportions in organs. Functional pathways can be scalably connected to physiological functions at the cell and organ levels. Integrating experimentally obtained gene expression patterns with prior knowledge of pathway interactions enables identification of networks underlying whole cell functions such as growth, contractility, and secretion. These pathways can be computationally modeled using differential equations to simulate cell and organ physiological dynamics regulated by gene expression changes. Such computational systems can be thought of as parts of digital twins of organs. Digital twins, at the core, need computational models that represent in detail and simulate how dynamics of pathways and networks give rise to whole cell level physiological functions. Integration of transcriptomic responses and numerical simulations could simulate and predict whole cell functional outputs from transcriptomic data. We developed a computational pipeline that integrates gene expression timelines and systems of coupled differential equations to generate cell-type selective dynamical models. We tested our integrative algorithm on the eicosanoid biosynthesis network in macrophages. Converting transcriptomic changes to a dynamical model allowed us to predict dynamics of prostaglandin and thromboxane synthesis and secretion by macrophages that matched published lipidomics data obtained in the same experiments. Integration of cell-level system biology simulations with genomic and clinical data using a knowledge graph framework will allow us to create explicit predictive models that mechanistically link genomic determinants to organ function. Such integration requires a multi-domain ontological framework to connect genomic determinants to gene expression and cell pathways and functions to organ level phenotypes in healthy and diseased states. These integrated scalable models of tissues and organs as accurate digital twins predict health and disease states for precision medicine.

The Specificity of Downstream Signaling for A1 and A2AR Does Not Depend on the C-Terminus, Despite the Importance of This Domain in Downstream Signaling Strength.

Recent efforts to determine the high-resolution crystal structures for the adenosine receptors (A1R and A2AR) have utilized modifications to the native receptors in order to facilitate receptor crystallization and structure determination. One common modification is a truncation of the unstructured C-terminus, which has been utilized for all the adenosine receptor crystal structures obtained to date. Ligand binding for this truncated receptor has been shown to be similar to full-length receptor for A2AR. However, the C-terminus has been identified as a location for protein-protein interactions that may be critical for the physiological function of these important drug targets. We show that variants with A2AR C-terminal truncations lacked cAMP-linked signaling compared to the full-length receptor constructs transfected into mammalian cells (HEK-293). In addition, we show that in a humanized yeast system, the absence of the full-length C-terminus affected downstream signaling using a yeast MAPK response-based fluorescence assay, though full-length receptors showed native-like G-protein coupling. To further study the G protein coupling, we used this humanized yeast platform to explore coupling to human-yeast G-protein chimeras in a cellular context. Although the C-terminus was essential for Gα protein-associated signaling, chimeras of A1R with a C-terminus of A2AR coupled to the A1R-specific Gα (i.e., Gαi1 versus Gαs). This surprising result suggests that the C-terminus is important in the signaling strength, but not specificity, of the Gα protein interaction. This result has further implications in drug discovery, both in enabling the experimental use of chimeras for ligand design, and in the cautious interpretation of structure-based drug design using truncated receptors.

Functional Expression of Adenosine A3 Receptor in Yeast Utilizing a Chimera with the A2AR C-Terminus.

The adenosine A3 receptor (A3R) is the only adenosine receptor subtype to be overexpressed in inflammatory and cancer cells and therefore is considered a novel and promising therapeutic target for inflammatory diseases and cancer. Heterologous expression of A3R at levels to allow biophysical characterization is a major bottleneck in structure-guided drug discovery efforts. Here, we apply protein engineering using chimeric receptors to improve expression and activity in yeast. Previously we had reported improved expression and trafficking of the chimeric A1R variant using a similar approach. In this report, we constructed chimeric A3/A2AR comprising the N-terminus and transmembrane domains from A3R (residues 1-284) and the cytoplasmic C-terminus of the A2AR (residues 291-412). The chimeric receptor showed approximately 2-fold improved expression with a 2-fold decreased unfolded protein response when compared to wild type A3R. Moreover, by varying culture conditions such as initial cell density and induction temperature a further 1.7-fold increase in total receptor yields was obtained. We observed native-like coupling of the chimeric receptor to Gai-Gpa1 in engineered yeast strains, activating the downstream, modified MAPK pathway. This strategy of utilizing chimeric receptor variants in yeast thus provides an exciting opportunity to improve expression and activity of "difficult-to-express" receptors, expanding the opportunity for utilizing yeast in drug discovery.

Improved ligand-binding- and signaling-competent human NK2R yields in yeast using a chimera with the rat NK2R C-terminus enable NK2R-G protein signaling platform.

The tachykinin 2 receptor (NK2R) plays critical roles in gastrointestinal, respiratory and mental disorders and is a well-recognized target for therapeutic intervention. To date, therapeutics targeting NK2R have failed to meet regulatory agency approval due in large part to the limited characterization of the receptor-ligand interaction and downstream signaling. Herein, we report a protein engineering strategy to improve ligand-binding- and signaling-competent human NK2R that enables a yeast-based NK2R signaling platform by creating chimeras utilizing sequences from rat NK2R. We demonstrate that NK2R chimeras incorporating the rat NK2R C-terminus exhibited improved ligand-binding yields and downstream signaling in engineered yeast strains and mammalian cells, where observed yields were better than 4-fold over wild type. This work builds on our previous studies that suggest exchanging the C-termini of related and well-expressed family members may be a general protein engineering strategy to overcome limitations to ligand-binding and signaling-competent G protein-coupled receptor yields in yeast. We expect these efforts to result in NK2R drug candidates with better characterized signaling properties.