About

Caleb Bashor is the Principal Investigator of the Bashor Lab at Rice University. He holds a Ph.D. in Biophysics from the University of California, San Francisco (UCSF), a Postdoctoral fellowship from the Massachusetts Institute of Technology (MIT), and a B.A. in Biochemistry from Reed College. His academic background spans biochemistry and biophysics, providing a strong foundation for his research activities. The Bashor Lab includes graduate and undergraduate students from diverse fields such as bioengineering, biochemistry, pharmaceutical sciences, and materials engineering, indicating a multidisciplinary approach to research under his leadership.

Research topics

• Biology
• Computational biology
• Computer Science
• Cell biology
• Data science
• Genetics
• Medicine
• Business
• Immunology
• Nanotechnology
• Risk analysis (engineering)
• Cancer research
• Materials science

Selected publications

• Opportunities for artificial intelligence and synthetic biology in designing living drug delivery systems

  Advanced Drug Delivery Reviews · 2026-04-27

  articleOpen accessSenior authorCorresponding

  Advances in artificial intelligence (AI) and synthetic biology are transforming biological research and biotechnology. These fields are for the first time enabling the design and development of human and bacterial cells that can serve as "living" drug delivery vehicles that perform sustained release of therapeutic cargo with spatiotemporal control. In recent years, human and bacterial cells have been engineered to deliver peptides, proteins, and biologics for treating a wide range of human diseases using synthetic biology approaches. To engineer effective living drug delivery systems, detailed knowledge is required about how to design receptors that can specifically sense the tissues targeted for drug delivery, signaling networks that can process signals from these receptors, and gene circuits that can control therapeutic cargo production and release. However, elucidating such receptors, signal processing and gene regulatory elements, and gene circuit compositions by traditional design-build-test-learn approaches is difficult and low throughput. Here we review how advances in AI and synthetic biology are meeting these challenges. We describe examples of how human cells and bacteria are engineered to become living drug delivery vehicles. We discuss how AI and synthetic biology approaches are being applied to discover the sequence-to-function design principles for engineering synthetic receptors, signaling proteins, and gene regulatory elements and the composition-to-function design principles for engineering synthetic gene circuits. We share an outlook on opportunities for AI and synthetic biology to synergize for creating next-generation living drug delivery systems.

  PublisherDOI

• Ultra-high-throughput mapping of genetic design space

  Nature · 2026-01-14 · 4 citations

  articleSenior author
  PublisherDOI

• Engineering synthetic phosphorylation signaling networks in human cells

  Science · 2025-01-02 · 26 citations

  articleSenior authorCorresponding

  Protein phosphorylation signaling networks have a central role in how cells sense and respond to their environment. We engineered artificial phosphorylation networks in which reversible enzymatic phosphorylation cycles were assembled from modular protein domain parts and wired together to create synthetic phosphorylation circuits in human cells. Our design scheme enabled model-guided tuning of circuit function and the ability to make diverse network connections; synthetic phosphorylation circuits can be coupled to upstream cell surface receptors to enable fast-timescale sensing of extracellular ligands, and downstream connections can regulate gene expression. We engineered cell-based cytokine controllers that dynamically sense and suppress activated T cells. Our work introduces a generalizable approach that allows the design of signaling circuits that enable user-defined sense-and-respond function for diverse biosensing and therapeutic applications.

  PublisherDOI

• Enhancing the safety and efficacy of cell therapy with programmed sense‐and‐respond function

  Clinical and Translational Medicine · 2025-04-28 · 1 citations

  letterOpen accessSenior authorCorresponding

  Over the past decade, cell-based therapies have emerged as a transformative pharmaceutical modality, offering unprecedented potential for treating previously incurable diseases.1 Whilst most cell-based therapies rely on intrinsic cell properties to achieve their therapeutic effects, genetic modification has gained traction as a strategy to enhance treatment safety and efficacy.2, 3 Amongst the most impactful therapeutic advancements are genetic engineering of adoptive T cell therapeutics, particularly for liquid tumour malignancies.4 Key breakthroughs include the development of chimeric antigen receptors (CARs) that reprogram T cell cytotoxicity towards tumour cells,5 protein-based safety switches that trigger apoptosis upon administration of a small-molecule drug6 and, most recently, synthetic multi-gene circuits that enable T cells to detect tumour antigens or soluble factors and conditionally deliver anti-tumour or immunomodulatory payloads in response.7 The continued evolution of this dynamic cell technology for broader clinical applications hinges on ongoing engineering innovations that enhance circuit precision and expand target detection capabilities. Towards this goal, we recently reported a circuit engineering toolkit that uses phosphorylation to drive circuit function, opening the door to engineering therapeutic sense-and-respond functionality that operates with the speed and precision of native cellular signalling pathways.8 Advantages of programming therapeutic cells to sense and respond. The implementation of synthetic sense-and-respond circuitry in therapeutic cells represents a paradigm shift in precision medicine, and has the potential to address long-standing challenges in drug delivery.1 Traditional therapeutic modalities, such as small molecules and biologics, can suffer from short in vivo half-lives and unfortunate side effects. Many cell therapies are challenged by invasive administration requirements for hard-to-reach tissues and significant off-target toxicities, including cytokine release syndrome and on-target, off-tissue toxicity.5 Synthetic circuits offer a potential solution to these challenges by furnishing cells with the ability to sense disease- or tissue-specific markers and respond by delivering therapeutic payloads with precisely defined spatial, temporal and dose profiles. Beyond enhancing therapeutic precision and minimising side effects, this approach effectively decouples therapeutic mode-of-action from the intrinsic properties of the host cell, facilitating programmable, context-specific responses to be engineered independently from the myriad complexities of native cellular function (Figure 1). Current state of engineering sense and respond for cell therapies. Pre-clinical efforts to engineer synthetic sense-and-respond circuits have followed two broad design approaches9 (Figure 2A). The first introduces programs that harness the activity of native signalling pathways to drive therapeutic transgene expression.10 Whilst these strategies benefit from the speed and robustness of endogenous signalling networks, they are inherently limited by pathway crosstalk, as native signalling components can be readily activated by non-specific stimuli. A second class of sense-and-respond circuits has been constructed primarily from synthetic protein components. Most of these designs rely on receptor-induced proteolysis to release synthetic transcription factors (TFs) that activate transgene expression or initiate other cellular functions.7 These circuits, some of which have recently advanced into clinical trials (NCT06245915), offer several benefits, including the ability to quantitatively tune the response function, and to configure inputs and outputs for diverse indications. However, the inherent non-reversibility of protease cleavage presents a significant limitation: once the ligand is removed, the cleaved synthetic TF can persist in the cell, resulting in slower rates of activation and deactivation, reducing the circuit's responsiveness to fluctuations in input. Phosphorylation-mediated sense-and-respond circuits. We developed our phosphorylation-based circuits to retain the tunability and configurability of protease-based designs whilst addressing their performance limitations8 (Figure 2A, right). Although phosphorylation serves as the primary mechanism by which all cells naturally sense fluctuations in their environment, there has been little progress in phosphorylation-based synthetic circuit design. Our work addressed this gap by developing a streamlined protein domain toolkit for constructing reversible phosphorylation cycles, wherein kinase and phosphatase activities precisely phosphorylate and dephosphorylate a protein substrate. As we demonstrated, these cycles can be linked together into multi-layered pathways that couple synthetic receptor sensing to downstream cellular outputs such as molecular condensation and transcription. In one demonstration, we engineered a closed-loop cytokine control circuit that can dynamically suppress activated T cells by detecting tumor necrosis factor (TNF)-α and secreting interleukin (IL)-10. Our engineering solution has multiple potential translational benefits (Figure 2B). First, the modularity of our protein domain toolkit allows circuits to function as orthogonal information channels that operate independently from the cell, whilst the use of human-derived protein domains to construct our circuits minimises the risk of immunogenicity. Second, these circuits function effectively in clinically relevant cell types, facilitating their use across multiple indications. Third, the use of entirely artificial proteins enables seamless reconfiguration of circuit inputs (e.g., disease biomarkers) and outputs (e.g., therapeutic biologics). Finally, rapid and reversible on/off dynamics enabled by phosphorylation offers superior spatiotemporal control over therapeutic response. Moving dynamic cell therapies into the clinic. Whilst our phosphorylation-based circuits represent a significant advancement in cellular engineering, translating them into clinical applications will require overcoming several key challenges. First, as multi-protein systems, they necessitate large DNA payloads that exceed the packaging capacity of many commonly used DNA delivery vectors. To enable more efficient delivery, we are developing compact circuit designs compatible with transposon systems and CRISPR knock-in approaches. A major hurdle for clinical translation is the efficient transfection and transgene expression in primary cells, which can be difficult to manipulate. Currently, we can achieve functional phosphorylation circuit expression in multiple cell types, including retinal pigment epithelium (RPE) cells and mesenchymal stem cells (MSC). However, the manufacturability of cell therapies that incorporate synthetic circuits must be prioritised alongside circuit performance to ensure successful clinical scaling. Through our work, we have identified several factors that critically impact manufacturability, including the toxicity of the DNA delivery method, the size of the genetic payload, and the cellular burden associated with transgene expression, all of which must be carefully considered in order to develop viable, cost-effective clinical pipelines. Conclusions. The outlook for cell therapies engineered with synthetic sense-and-respond circuits is promising, with the potential to address some of medicine's most pressing challenges. Our work establishes a foundation for user-defined therapeutic responses that behave with natural-like precision, and we are optimistic that these advancements will drive significant progress in treating a wide range of complex diseases. We acknowledge colleagues and collaborators who helped develop the phosphorylation circuit platform and contributed to the ideas in this piece, including Passa Pungchai, Jason Rocks, Kaiyi Jiang, Pankaj Mehta, and Chibawanye Ene. This work was supported by grants from NIH R01 EB029483 (C.J.B.), NIH R01 EB032272 (C.J.B.), NIH R21 NS116302 (S.D.O. and C.J.B) ONR N00014-21-1-4006 (C.J.B.) and the Robert J. Kleberg Jr. and Helen C. Kleberg Foundation (C.J.B.), and NSF GRFP award 1842494 (A.J.W.). A provisional patent application that covers technologies described in this manuscript has been filed by Rice University.

  PublisherOA PDFDOI

• Integrating synthetic biology to understand and engineer the heart, lung, blood, and sleep systems

  Cell Systems · 2025-12-01

  articleOpen access
  PublisherOA PDFDOI

• Using machine learning to enhance and accelerate synthetic biology

  Current Opinion in Biomedical Engineering · 2024-08-02 · 25 citations

  reviewSenior authorCorresponding
  PublisherDOI

• Author response: pYtags enable spatiotemporal measurements of receptor tyrosine kinase signaling in living cells

  2023-03-15

  peer-reviewOpen access

  pYtags are novel biosensors that can be used to measure the activity of a receptor tyrosine kinase of interest in live cells with high spatiotemporal resolution and are applied to reveal rapid activity dynamics of EGFR/ErbB2 signaling.

  PublisherDOI

• Tumor-associated macrophages induce inflammation and drug resistance in a mechanically tunable engineered model of osteosarcoma

  Biomaterials · 2023 · 42 citations

  • Cancer research
  • Biology
  • Cell biology
  PublisherOA PDFDOI

• pYtags enable spatiotemporal measurements of receptor tyrosine kinase signaling in living cells

  eLife · 2023-04-25 · 18 citations

  articleOpen access

  Receptor tyrosine kinases (RTKs) are major signaling hubs in metazoans, playing crucial roles in cell proliferation, migration, and differentiation. However, few tools are available to measure the activity of a specific RTK in individual living cells. Here, we present pYtags, a modular approach for monitoring the activity of a user-defined RTK by live-cell microscopy. pYtags consist of an RTK modified with a tyrosine activation motif that, when phosphorylated, recruits a fluorescently labeled tandem SH2 domain with high specificity. We show that pYtags enable the monitoring of a specific RTK on seconds-to-minutes time scales and across subcellular and multicellular length scales. Using a pYtag biosensor for epidermal growth factor receptor (EGFR), we quantitatively characterize how signaling dynamics vary with the identity and dose of activating ligand. We show that orthogonal pYtags can be used to monitor the dynamics of EGFR and ErbB2 activity in the same cell, revealing distinct phases of activation for each RTK. The specificity and modularity of pYtags open the door to robust biosensors of multiple tyrosine kinases and may enable engineering of synthetic receptors with orthogonal response programs.

  PublisherDOI

• Ultra-high throughput mapping of genetic design space

  bioRxiv (Cold Spring Harbor Laboratory) · 2023-03-17 · 22 citations

  preprintOpen accessSenior authorCorresponding

  ABSTRACT Massively parallel genetic screens have been used to map sequence-to-function relationships for a variety of genetic elements. However, because these approaches only interrogate short sequences, it remains challenging to perform high throughput (HT) assays on constructs containing combinations of multiple sequence elements arranged across multi-kb length scales. Overcoming this barrier could accelerate synthetic biology; by screening diverse gene circuit designs and learning “composition-to-function” mappings that reveal genetic part composability rules and enable rapid identification of behavior-optimized variants. Here, we introduce CLASSIC, a genetic screening platform that combines long- and short-read next-generation sequencing (NGS) modalities to quantitatively assess pools of constructs of arbitrary length containing diverse part compositions. We show that CLAS-SIC can measure expression profiles of >10 5 gene circuit designs (from 5-20 kb) in a single experiment in human cells. The resulting datasets can be used to train ML models that accurately predict circuit behavior across expansive circuit design landscapes, revealing part composability rules that govern circuit performance. Our work shows that by expanding the throughput of each design-build-test-learn (DBTL) cycle, CLASSIC enhances the pace and scale of synthetic biology and establishes an experimental basis for data-driven design of complex genetic systems.

  PublisherOA PDFDOI

Recent grants

• A synthetic signaling pathway engineering platform for creating precision cell-based sense-and-response devices

  NIH · $1.4M · 2021–2025

Frequent coauthors

• James J. Collins

  Massachusetts Institute of Technology

  37 shared

• Ahmad S. Khalil

  Harvard University Press

  27 shared

• Wendell A. Lim

  University of California, San Francisco

  15 shared

• Cherie L. Ramirez

  Simmons University

  10 shared

• J. Keith Joung

  Center for Cancer Research

  10 shared

• Arnold M. Falick

  University of California, Berkeley

  9 shared

• Roby P. Bhattacharyya

  Harvard University

  9 shared

• Attila Reményi

  Institute of Organic Chemistry

  9 shared

Labs

• The Bashor LabPI

  Using the tools of synthetic biology, we construct artificial regulatory circuits and test their function in living cells.