Biology subjects

Leonard, J. N.

Publications and source records attributed to Leonard, J. N..

At least 19 recordsLinked to original sources

bioRxiv2026

Genetically inducible coordinators of cytokine signaling pathways for interrogating T cell motility

Chimeric antigen receptor (CAR) T cell therapy is promising for treating hematologic malignancies, but extending this success to treat solid tumors is challenging. Improving T cell phenotype to address this need is desirable, and one such property is increasing T cell infiltration into tumors. A promising potential approach comprises rewiring cytokine signaling using engineered receptors to change how the T cell responds to environmental cues. However, we currently lack the tools and mechanistic understanding to iterate and improve upon such strategies. Notably, receptors that rewire signaling make it challenging to decouple paracrine effects from those conferred by the signaling inducer. To address this gap, we developed a genetically inducible toolkit of proteins termed Constitutive Activators of Motility-associated Pathways (CAMPs). Building on prior knowledge, CAMPs incorporate domains from IL5R (interleukin-5 receptor) and TNFR (tumor necrosis factor receptor) to place cytokine-associated signaling under direct genetic control, such that expression of a CAMP using a small molecule cue or a condition-responsive promoter induces CAMP signaling. We first identified receptor configurations driving constitutive signaling through targeted pathways. TNFR-based signaling modules drove NF-{kappa}B activation across diverse receptor designs, while IL5R-based signaling modules exhibited stringent requirements for membrane-proximity and organization of subunits. We engineered primary human T cells with inducible CAMP circuits, enabling us to probe pathway-specific effects on motility and transcriptomic responses. Pharmacological induction of motility-associated programs downstream of PKC (protein kinase C) was shown to be feasible and dependent on T cell activation state. CAMP induction drove an inflammatory program, particularly when signaling through both NF-{kappa}B and STAT5, but none of the conditions tested enhanced 3D motility in our assay. Altogether, our findings are consistent with a model in which migratory behavior may be coupled and regulated by multiple stimuli. These findings and new CAMP tools provide a foundation for interrogating and ultimately harnessing motility for improved T cell therapy performance.

synthetic biology↗

bioRxiv2026

CELLISA - a cell-cell binding assay for evaluation of nanovesicle targeting proteins

Enhancing targeted delivery of biomedicines improves efficacy and can reduce off-target effects by lowering the effective dose, but achieving targeting is challenging. Extracellular vesicles (EVs) are promising biological nanovesicles which can be targeted by displaying binding proteins and are being developed as therapeutics. Currently, discovering EV targeting constructs is limited by low throughput and resource-intensive EV production and isolation. To accelerate discovery, we developed a screening pipeline to identify EV targeting constructs without requiring EV production. This approach is premised on the hypothesis that cell-cell interactions may predict some cell-EV interactions. Our cell binding assay (CELLISA) quantifies binding of a cell surface-displayed targeting protein to its cognate receptor on a target cell, employing a microscopy-based analysis pipeline. After validating the premise using existing T cell-targeting reagents, we develop CELLISA for either adherent or suspension EV producer cells. Finally, we use CELLISA to evaluate new binders and validate that hits mediate targeting and/or delivery of genetic cargo to natural killer cells and T cells. CELLISA increased throughput > 6-fold and decreased time by 40% compared to standard EV screens, and it identified a T-cell binder conferring efficient gene delivery. CELLISA is easily adaptable to other laboratories and can accelerate EV research.

bioengineering↗

bioRxiv2025

GCAD: a Computational Framework for Mammalian Genetic Program Computer-Aided Design

Genetic programs can direct living systems to perform diverse, pre-specified functions. As the library of parts available for building such programs continues to expand, computation-guided design is increasingly helpful and necessary. Predictive models aid the challenging design process, but iterative simulation and experimentation are intractable for complex functions. Computer-aided design accelerates this process, but existing tools do not yet capture the behavior of mammalian-specific parts and population-level effects needed for mammalian synthetic biologists. To address these needs, we developed a framework for mammalian genetic program computer-aided design. Starting with a user-defined design specification to quantify circuit performance, the framework uses a genetic algorithm to search through possible designs. Circuit space is defined by a library of experimentally characterized parts and dynamical systems models for gene expression in a heterogeneous cell population. We developed this genetic algorithm using a directed graph-based formulation with biologically constrained rules to explore regulatory connections and parts. We evaluated the framework for design problems of varying complexity, including programs we describe as an amplifier, signal conditioner, and pulse generator, demonstrating that the algorithm can successfully find optimal circuit designs. Finally, we experimentally evaluated selected circuits, demonstrating the path from a predicted circuit design to experimental testing and highlighting the importance of characterization for enabling predictive design. Overall, this framework establishes general approaches that can be refined and expanded, accelerating the design and implementation of mammalian genetic programs.

synthetic biology↗

bioRxiv2025

Distinguishing Protein and Gene Delivery Enables Characterization and Bioengineering of Extracellular Vesicle-Adeno-Associated Virus Vectors

Adeno-associated virus (AAV) gene therapies have achieved some clinical success, with multiple products reaching regulatory approval. Encapsulation of AAV vectors within engineered extracellular vesicles (EVs) is an emerging strategy which could help overcome challenges including pre-existing anti-capsid immunity and the need for controlling targeting and tropism. To guide the development of EV-AAV technologies, we developed an assay for quantifying and controlling for the contribution of pseudotransduction to evaluations of EV-AAV-mediated transduction. We developed an AAV vector that switches its transgene output from one reporter to another when acted upon by Cre recombinase expressed in a recipient cell. Using this platform, we investigated EV-AAV transduction as a function of various engineered EV surface modifications. For actively endocytic cells (HEK293FTs), modifications that enhance EV uptake and membrane fusion influence pseudotransduction but not true transduction. Conversely, in less endocytic Jurkat T cells, modifications enhancing EV uptake enhanced both pseudotransduction and true transduction. These conclusions held across two AAV serotypes. Our results provide new insight into prior reports and suggest that effects of enhancing uptake and membrane fusion of EV-AAV vectors are recipient cell type-specific. The methods developed here unambiguously dissect EV-AAV transduction mechanisms and can guide future bioengineering of EV-AAV vectors.

bioengineering↗

bioRxiv2024

Exploring structure-function relationships in engineered receptor performance using computational structure prediction

Engineered receptors play increasingly important roles in transformative cell-based therapies. However, the structural mechanisms that drive differences in performance across receptor designs are often poorly understood. Recent advances in protein structural prediction tools have enabled the modeling of virtually any user-defined protein, but how these tools might build understanding of engineered receptors has yet to be fully explored. In this study, we employed structural modeling tools to perform post hoc analyses to investigate whether predicted structural features might explain observed functional variation. We selected a recently reported library of receptors derived from natural cytokine receptors as a case study, generated structural models, and from these predictions quantified a set of structural features that plausibly impact receptor performance. Encouragingly, for a subset of receptors, structural features explained considerable variation in performance, and trends were largely conserved across structurally diverse receptor sets. This work indicates potential for structure prediction-guided synthetic receptor engineering.

synthetic biology↗

bioRxiv2024

Engineered Feedback Employing Natural Hypoxia-Responsive Factors Enhances Synthetic Hypoxia Biosensors

DNA-based hypoxia biosensors conditionally express a gene of interest when a cell is in a state of inadequate oxygen supply, which is a feature of several acute and chronic diseases. These biosensors can be deployed in engineered cells to study or treat disease. Although the central mediators of hypoxia responsiveness have been characterized, the dynamics of this response are generally less understood, and there is no general approach to modulate hypoxia biosensors to tune their performance to meet application-specific needs. To address the need for high-performing hypoxia biosensors, we investigated strategies to enhance biosensor performance by identifying minimal promoter choices and positive feedback circuits that both achieved low background and amplified hypoxia-induced gene expression. To generate insight into the mechanisms by which feedback drives differential performance, we developed an explanatory mathematical model. Our analysis suggests a previously unreported dual regulatory mechanism that was necessary to explain the full set of experimental observations and that provides new insights into regulatory dynamics in chronic hypoxia. This study exemplifies the potential of using synthetic gene circuits to perturb natural systems in a manner that uniquely enables the elucidation of novel facets of natural regulation.

synthetic biology↗

bioRxiv2024

Developing, characterizing and modelingCRISPR-based point-of-use pathogen diagnostics

Recent years have seen intense interest in the development of point-of-care nucleic acid diagnostic technologies to address the scaling limitations of laboratory-based approaches. Chief among these are combinations of isothermal amplification approaches with CRISPR-based detection and readouts of target products. Here, we contribute to the growing body of rapid, programmable point-of-care pathogen tests by developing and optimizing a one-pot NASBA-Cas13a nucleic acid detection assay. This test uses the isothermal amplification technique NASBA to amplify target viral nucleic acids, followed by Cas13a-based detection of amplified sequences. We first demonstrate an in-house formulation of NASBA that enables optimization of individual NASBA components. We then present design rules for NASBA primer sets and LbuCas13a guide RNAs for fast and sensitive detection of SARS-CoV-2 viral RNA fragments, resulting in 20 - 200 aM sensitivity without any specialized equipment. Finally, we explore the combination of high-throughput assay condition screening with mechanistic ordinary differential equation modeling of the reaction scheme to gain a deeper understanding of the NASBA-Cas13a system. This work presents a framework for developing a mechanistic understanding of reaction performance and optimization that uses both experiments and modeling, which we anticipate will be useful in developing future nucleic acid detection technologies.

synthetic biology↗

bioRxiv2024

Conversion of natural cytokine receptors into orthogonal synthetic biosensors

Synthetic receptors enable bioengineers to build cell-based therapies that perform therapeutic functions in a targeted or conditional fashion to enhance specificity and efficacy. Although many synthetic receptors exist, it remains challenging to generate new receptors that sense soluble cues and relay that detection through orthogonal mechanisms independent of native pathways. Towards this goal, we investigated co-opting natural cytokine receptor ectodomains into Modular Extracellular Sensor Architecture receptors (yielding natural ectodomain, NatE MESA receptors). We generated multiple high-performing, orthogonal synthetic cytokine receptors, identified design principles and constraints, and propose guidance for extending this approach to other natural receptors. We demonstrate utility of NatE MESA by engineering T cells to sense an immunosuppressive cue and respond with customized transcriptional output to support CAR T-cell activity. Finally, we multiplex NatE MESA to logically evaluate multiple cues associated with the tumor microenvironment. These technologies and learnings will enable engineering cellular functions for new applications.

synthetic biology↗

bioRxiv2023

Building synthetic biosensors using red blood cell proteins

As the use of engineered cell therapies expands from pioneering efforts in cancer immunotherapy to other applications, an attractive but less explored approach is the use of engineered red blood cells (RBCs). Compared to other cells, RBCs have a very long circulation time and reside in the blood compartment, so they could be ideally suited for applications as sentinel cells that enable in situ sensing and diagnostics. However, we largely lack tools for converting RBCs into biosensors. A unique challenge is that RBCs remodel their membranes during maturation, shedding many membrane components, suggesting that an RBC-specific approach may be needed. Towards addressing this need, here we develop a biosensing architecture built on RBC membrane proteins that are retained through erythropoiesis. This biosensor employs a mechanism in which extracellular ligand binding is transduced into intracellular reconstitution of a split output protein (including either a fluorophore or an enzyme). By comparatively evaluating a range of biosensor architectures, linker types, scaffold choices, and output signals, we identify biosensor designs and design features that confer substantial ligand-induced signal in vitro. Finally, we demonstrate that erythroid precursor cells engineered with our RBC protein biosensors function in vivo. This study establishes a foundation for developing RBC-based biosensors that could ultimately address unmet needs including non-invasive monitoring of physiological signals for a range of diagnostic applications.

synthetic biology↗

bioRxiv2023

HaloTag display enables quantitative single-particle characterization and functionalization of engineered extracellular vesicles

Extracellular vesicles (EVs) play key roles in diverse biological processes, transport biomolecules between cells, and have been engineered for therapeutic applications. A useful EV bioengineering strategy is to express engineered proteins on the EV surface to confer targeting, bioactivity, and other properties. Measuring how incorporation varies across a population of EVs is important for characterizing such materials and understanding their function, yet it remains challenging to quantitatively characterize the absolute number of engineered proteins incorporated at single-EV resolution. To address these needs, we developed a HaloTag-based characterization platform in which dyes or other synthetic species can be covalently and stoichiometrically attached to engineered proteins on the EV surface. To evaluate this system, we employed several orthogonal quantification methods, including flow cytometry and fluorescence microscopy, and found that HaloTag-mediated quantification is generally robust across EV analysis methods. We compared HaloTag-labeling to antibody-labeling of EVs using single vesicle flow cytometry, enabling us to measure the substantial degree to which antibody labeling can underestimate proteins present on an EV. Finally, we demonstrate the use of HaloTag to compare between protein designs for EV bioengineering. Overall, the HaloTag system is a useful EV characterization tool which complements and expands existing methods.

bioengineering↗

bioRxiv2023

Comparative evaluation of synthetic cytokines for enhancing production and performance of NK92 cell-based therapies

Autologous immune cell therapies are potentially curative, but cost and manufacturing complexity limit access. Off-the-shelf therapies may address these gaps, but further development is needed. The NK92 cell line has a natural killer-like phenotype, has efficacy in cancer clinical trials, and is safe after irradiation. However, NK92 lose activity post-injection, limiting efficacy. This may be addressed by engineering NK92 to express stimulatory factors, for which comparative analysis is needed. Thus, we systematically explored expression of synthetic cytokines for enhancing NK92 production and performance. All synthetic cytokines evaluated (membrane-bound IL2 and IL15, and engineered versions of Neoleukin-2/15, IL15, IL12, and decoy resistant IL18) enhanced NK92 cytotoxicity. Genetically modified cells preferentially expanded by expressing membrane-bound but not soluble synthetic cytokines, and all engineered cells remained sensitive to irradiation. Interestingly, some membrane-bound cytokines conferred cell-contact independent paracrine activity partly attributable to extracellular vesicles. Finally, we characterized interactions within consortia of differently engineered NK92.

bioengineering↗

bioRxiv2023

Enhancing extracellular vesicle cargo loading and functional delivery by engineering protein-lipid interactions

Naturally generated lipid nanoparticles termed extracellular vesicles (EVs) hold significant promise as engineerable therapeutic delivery vehicles. However, active loading of protein cargo into EVs in a manner that is useful for delivery remains a challenge. Here, we demonstrate that by rationally designing proteins to traffic to the plasma membrane and associate with lipid rafts, we can enhance loading of protein cargo into EVs for a set of structurally diverse transmembrane and peripheral membrane proteins. We then demonstrate the capacity of select lipid tags to mediate increased EV loading and functional delivery of an engineered transcription factor to modulate gene expression in target cells. We envision that this technology could be leveraged to develop new EV-based therapeutics that deliver a wide array of macromolecular cargo.

bioengineering↗

bioRxiv2022

Bioengineering multifunctional extracellular vesicles for targeted delivery of biologics to T cells

Genetically modifying T cells can enable applications ranging from cancer immunotherapy to HIV treatment, yet delivery of T cell-targeted therapeutics remains challenging. Extracellular vesicles (EVs) are nanoscale particles secreted by all cells that naturally encapsulate and transfer proteins and nucleic acids, making them an attractive and clinically-relevant platform for engineering biocompatible delivery vehicles. We report a suite of technologies for genetically engineering cells to produce multifunctional EV vehicles--without employing chemical modifications that complicate biomanufacturing. We display high affinity targeting domains on the EV surface to achieve specific, efficient binding to T cells, identify a protein tag to confer active cargo loading into EVs, and display fusogenic glycoproteins to increase EV uptake and fusion with recipient cells. We demonstrate integration of these technologies by delivering Cas9-sgRNA complexes to edit primary human T cells. These approaches could enable targeting vesicles to a range of cells for the efficient delivery of cargo.

bioengineering↗

bioRxiv2022

Mapping CAR T-cell design space using agent-based models

Chimeric antigen receptor (CAR) T-cell therapy shows promise for treating liquid cancers and increasingly for solid tumors as well. While potential design strategies exist to address translational challenges, including the lack of unique tumor antigens and the presence of an immunosuppressive tumor microenvironment, testing all possible design choices in vitro and in vivo is prohibitively expensive, time consuming, and laborious. To address this gap, we extended the modeling framework ARCADE (Agent-based Representation of Cells And Dynamic Environments) to include CAR T-cell agents (CAR T-cell ARCADE, or CARCADE). We conducted in silico experiments to investigate how clinically relevant design choices and inherent tumor features--CAR T-cell dose, CD4+:CD8+ CAR T-cell ratio, CAR-antigen affinity, cancer and healthy cell antigen expression--individually and collectively impact treatment outcomes. Our analysis revealed that tuning CAR affinity modulates IL-2 production by balancing CAR T-cell proliferation and effector function. It also identified a novel multi-feature tuned treatment strategy for balancing selectivity and efficacy and provided insights into how spatial effects can impact relative treatment performance in different contexts. CARCADE facilitates deeper biological understanding of treatment design and could ultimately enable identification of promising treatment strategies to accelerate solid tumor CAR T-cell design-build-test cycles.

bioengineering↗

bioRxiv2021

Elucidating design principles for engineering cell-derived vesicles to inhibit SARS-CoV-2 infection

The ability of pathogens to develop drug resistance is a global health challenge. The SARS-CoV-2 virus presents an urgent need wherein several variants of concern resist neutralization by monoclonal antibody therapies and vaccine-induced sera. Decoy nanoparticles--cell-mimicking particles that bind and inhibit virions--are an emerging class of therapeutics that may overcome such drug resistance challenges. To date, we lack quantitative understanding as to how design features impact performance of these therapeutics. To address this gap, here we perform a systematic, comparative evaluation of various biologically-derived nanoscale vesicles, which may be particularly well-suited to sustained or repeated administration in the clinic due to low toxicity, and investigate their potential to inhibit multiple classes of model SARS-CoV-2 virions. A key finding is that such particles exhibit potent antiviral efficacy across multiple manufacturing methods, vesicle subclasses, and virus-decoy binding affinities. In addition, these cell-mimicking vesicles effectively inhibit model SARS-CoV-2 variants that evade monoclonal antibodies and recombinant protein-based decoy inhibitors. This study provides a foundation of knowledge that may guide the design of decoy nanoparticle inhibitors for SARS-CoV-2 and other viral infections.

bioengineering↗

bioRxiv2021

GAMES: A dynamic model development workflow for rigorous characterization of synthetic genetic systems

Mathematical modeling is invaluable for advancing understanding and design of synthetic biological systems. However, the model development process is complicated and often unintuitive, requiring iteration on various computational tasks and comparisons with experimental data. Ad hoc model development can pose a barrier to reproduction and critical analysis of the development process itself, reducing potential impact and inhibiting further model development and collaboration. To help practitioners manage these challenges, we introduce GAMES: a workflow for Generation and Analysis of Models for Exploring Synthetic systems that includes both automated and human-in-the-loop processes. We systematically consider the process of developing dynamic models, including model formulation, parameter estimation, parameter identifiability, experimental design, model reduction, model refinement, and model selection. We demonstrate the workflow with a case study on a chemically responsive transcription factor. The generalizable workflow presented in this tutorial can enable biologists to more readily build and analyze models for various applications. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=129 SRC="FIGDIR/small/465216v2_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@b1c8feorg.highwire.dtl.DTLVardef@29d13org.highwire.dtl.DTLVardef@1967eb7org.highwire.dtl.DTLVardef@1593bdd_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2020

Model-guided design of mammalian genetic programs

Genetically engineering cells to perform customizable functions is an emerging frontier with numerous technological and translational applications. However, it remains challenging to systematically engineer mammalian cells to execute complex functions. To address this need, we developed a method enabling accurate genetic program design using high-performing genetic parts and predictive computational models. We built multi-functional proteins integrating both transcriptional and post-translational control, validated models for describing these mechanisms, implemented digital and analog processing, and effectively linked genetic circuits with sensors for multi-input evaluations. The functional modularity and compositional versatility of these parts enable one to satisfy a given design objective via multiple synonymous programs. Our approach empowers bioengineers to predictively design mammalian cellular functions that perform as expected even at high levels of biological complexity.

synthetic biology↗

bioRxiv2020

RNA sequence and structure determinants of Pol III transcriptional termination in human cells

The precise mechanism of transcription termination of the eukaryotic RNA polymerase III (Pol III) has been a subject of considerable debate. Although previous studies have clearly shown that at the end of RNA transcripts, tracts comprised of multiple uracils are required for Pol III termination, whether upstream RNA secondary structure in the nascent transcript is necessary for robust transcriptional termination is still subject to debate. We sought to address this directly through the development of an in cellulo Pol III transcription termination assay using a synthetic biology approach. Specifically, we utilized the recently developed Tornado expression system and a stabilized Corn RNA aptamer to create a Pol III-transcribed RNA that produces a detectable fluorescent signal when transcribed in human cells. To study the effects of RNA sequence and structure on Pol III termination, we systematically varied the sequence context upstream of the aptamer and identified sequence characteristics that enhance or diminish termination. We found that in the absence of predicted secondary structure, only poly-U tracts longer than then the average length found in the human genome (4-5 nucleotides), efficiently terminate Pol III transcription. We found that shorter poly-U tracts could induce termination when placed in proximity to secondary structural elements, while secondary structure by itself was not sufficient to induce termination. These findings demonstrate a key role for sequence and structural elements within Pol III-transcribed nascent RNA for efficient transcription termination, and demonstrate a generalizable assay for characterizing Pol III transcription in human cells.

molecular biology↗