Outsmarting and outmuscling cancer cells with synthetic and systems immunology

Elucidation and refinement of synthetic receptor mechanisms

Synthetic receptors are powerful tools for engineering mammalian cell-based devices. These biosensors enable cell-based therapies to perform complex tasks such as regulating therapeutic gene expression in response to sensing physiological cues. Although multiple synthetic receptor systems now exist, many aspects of receptor performance are poorly understood. In general, it would be useful to understand how receptor design choices influence performance characteristics. In this study, we examined the modular extracellular sensor architecture (MESA) and systematically evaluated previously unexamined design choices, yielding substantially improved receptors. A key finding that might extend to other receptor systems is that the choice of transmembrane domain (TMD) is important for generating high-performing receptors. To provide mechanistic insights, we adopted and employed a Förster resonance energy transfer-based assay to elucidate how TMDs affect receptor complex formation and connected these observations to functional performance. To build further insight into these phenomena, we developed a library of new MESA receptors that sense an expanded set of ligands. Based upon these explorations, we conclude that TMDs affect signaling primarily by modulating intracellular domain geometry. Finally, to guide the design of future receptors, we propose general principles for linking design choices to biophysical mechanisms and performance characteristics.

Systematic Multi-Omics Integration (MOI) Approach in Plant Systems Biology

Across all facets of biology, the rapid progress in high-throughput data generation has enabled us to perform multi-omics systems biology research. Transcriptomics, proteomics, and metabolomics data can answer targeted biological questions regarding the expression of transcripts, proteins, and metabolites, independently, but a systematic multi-omics integration (MOI) can comprehensively assimilate, annotate, and model these large data sets. Previous MOI studies and reviews have detailed its usage and practicality on various organisms including human, animals, microbes, and plants. Plants are especially challenging due to large poorly annotated genomes, multi-organelles, and diverse secondary metabolites. Hence, constructive and methodological guidelines on how to perform MOI for plants are needed, particularly for researchers newly embarking on this topic. In this review, we thoroughly classify multi-omics studies on plants and verify workflows to ensure successful omics integration with accurate data representation. We also propose three levels of MOI, namely element-based (level 1), pathway-based (level 2), and mathematical-based integration (level 3). These MOI levels are described in relation to recent publications and tools, to highlight their practicality and function. The drawbacks and limitations of these MOI are also discussed for future improvement toward more amenable strategies in plant systems biology.

Engineering T Cells to Treat Cancer: The Convergence of Immuno-Oncology and Synthetic Biology

T cells engineered to recognize and kill tumor cells have emerged as powerful agents for combating cancer. Nonetheless, our ability to engineer T cells remains relatively primitive. Aside from CAR T cells for treating B cell malignancies, most T cell therapies are risky, toxic, and often ineffective, especially those that target solid cancers. To fulfill the promise of cell-based therapies, we must transform cell engineering into a systematic and predictable science by applying the principles and tools of synthetic biology. Synthetic biology uses a hierarchical approach—assembling sets of modular molecular parts that can be combined into larger circuits and systems that perform defined target tasks. We outline the toolkit of synthetic modules that are needed to overcome the challenges of solid cancers, progress in building these components, and how these modules could be used to reliably engineer more effective and precise T cell therapies.

Engineering primary T cells with chimeric antigen receptors for rewired responses to soluble ligands

The expression of synthetic receptors in primary T cells enables the programming of user-defined responses when designing T-cell therapies. Chimeric antigen receptors (CARs) are synthetic receptors that have demonstrated efficacy in cancer therapy by targeting immobilized antigens on the surface of malignant cells. Recently, we showed they can also rewire T-cell responses to soluble ligands. In contrast to other synthetic receptors, CARs are not only readily engineered by rational design, but also clinically translatable, with robust function in primary human T cells. This protocol discusses design principles for CARs responsive to soluble ligands and delineates steps for producing T cells expressing synthetic receptors. Functional assays for quantifying the ability of CAR T cells to sense and respond to soluble ligands are also presented. This protocol provides a framework for proficient immune-cell researchers to test novel T-cell therapies targeting soluble ligands in <2 weeks.