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.

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. Toward 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 noninvasive monitoring of physiological signals for a range of diagnostic applications.

Genetically encoding multiple functionalities into extracellular vesicles for the targeted delivery of biologics to T cells

The genetic modification of T cells has advanced cellular immunotherapies, yet the delivery of biologics specifically to T cells remains challenging. Here we report a suite of methods for the genetic engineering of cells to produce extracellular vesicles (EVs)-which naturally encapsulate and transfer proteins and nucleic acids between cells-for the targeted delivery of biologics to T cells without the need for chemical modifications. Specifically, the engineered cells secreted EVs that actively loaded protein cargo via a protein tag and that displayed high-affinity T-cell-targeting domains and fusogenic glycoproteins. We validated the methods by engineering EVs that delivered Cas9-single-guide-RNA complexes to ablate the gene encoding the C-X-C chemokine co-receptor type 4 in primary human CD4+ T cells. The strategy is amenable to the targeted delivery of biologics to other cell types.

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.

Teaching systematic, reproducible model development using synthetic biology

We present an educational unit to teach computational modeling, a vital part of chemical engineering curricula, through the lens of synthetic biology. Lectures, code, and homework questions provide conceptual and practical introductions to each computational method involved in the model development process, along with perspectives on how methods can be iterated upon to arrive at a final model. Ultimately, this content can be applied broadly to address questions in synthetic biology and classical chemical engineering.

Comparative Evaluation of Synthetic Cytokines for Enhancing Production and Performance of NK92 Cell-Based Therapies

Off-the shelf immune cell therapies are potentially curative and may offer cost and manufacturing advantages over autologous products, 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 cells lose activity post-injection, limiting efficacy. This may be addressed by engineering NK92 cells to express stimulatory factors, and comparative analysis is needed. Thus, we systematically explored the expression of synthetic cytokines for enhancing NK92 cell 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 cell cytotoxicity. Engineered cells were preferentially expanded by expressing membrane-bound but not soluble synthetic cytokines, without compromising the radiosensitivity required for safety. 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 cells.

The sound of silence: Transgene silencing in mammalian cell engineering

To elucidate principles operating in native biological systems and to develop novel biotechnologies, synthetic biology aims to build and integrate synthetic gene circuits within native transcriptional networks. The utility of synthetic gene circuits for cell engineering relies on the ability to control the expression of all constituent transgene components. Transgene silencing, defined as the loss of expression over time, persists as an obstacle for engineering primary cells and stem cells with transgenic cargos. In this review, we highlight the challenge that transgene silencing poses to the robust engineering of mammalian cells, outline potential molecular mechanisms of silencing, and present approaches for preventing transgene silencing. We conclude with a perspective identifying future research directions for improving the performance of synthetic gene circuits.

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.

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. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presents an urgent need wherein several variants of concern resist neutralization by monoclonal antibody (mAb) 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, quantitative understanding as to how design features impact performance of these therapeutics is lacking. To address this gap, this study presents 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 investigates 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 mAbs 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.

The evolution of synthetic receptor systems

Receptors enable cells to detect, process and respond to information about their environments. Over the past two decades, synthetic biologists have repurposed physical parts and concepts from natural receptors to engineer synthetic receptors. These technologies implement customized sense-and-respond programs that link a cell's interaction with extracellular and intracellular cues to user-defined responses. When combined with tools for information processing, these advances enable programming of sophisticated customized functions. In recent years, the library of synthetic receptors and their capabilities has substantially evolved-a term we employ here to mean systematic improvement and expansion. Here, we survey the existing mammalian synthetic biology toolkit of protein-based receptors and signal-processing components, highlighting efforts to evolve and integrate some of the foundational synthetic receptor systems. We then propose a generalized strategy for engineering and improving receptor systems to meet defined functional objectives called a 'metric-enabled approach for synthetic receptor engineering' (MEASRE).

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 the potential impact and inhibiting further model development and collaboration. To help practitioners manage these challenges, we introduce the Generation and Analysis of Models for Exploring Synthetic Systems (GAMES) workflow, which 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.

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.

Synthetic biology: at the crossroads of genetic engineering and human therapeutics-a Keystone Symposia report

Synthetic biology has the potential to transform cell- and gene-based therapies for a variety of diseases. Sophisticated tools are now available for both eukaryotic and prokaryotic cells to engineer cells to selectively achieve therapeutic effects in response to one or more disease-related signals, thus sparing healthy tissue from potentially cytotoxic effects. This report summarizes the Keystone eSymposium "Synthetic Biology: At the Crossroads of Genetic Engineering and Human Therapeutics," which took place on May 3 and 4, 2021. Given that several therapies engineered using synthetic biology have entered clinical trials, there was a clear need for a synthetic biology symposium that emphasizes the therapeutic applications of synthetic biology as opposed to the technical aspects. Presenters discussed the use of synthetic biology to improve T cell, gene, and viral therapies, to engineer probiotics, and to expand upon existing modalities and functions of cell-based therapies.

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 multiple uracils at the end of RNA transcripts are required for Pol III termination, the effects of upstream RNA secondary structure in the nascent transcript on transcriptional termination is still unclear. To address this, we developed an in cellulo Pol III transcription termination assay using the recently developed Tornado-Corn RNA aptamer system 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. For transcription from Pol III type 3 promoters, we found that only poly-U tracts longer than the average length found in the human genome efficiently terminate Pol III transcription without RNA secondary structure elements. We observed that RNA secondary structure elements placed in proximity to shorter poly-U tracts induced termination, and RNA secondary structure by itself was not sufficient to induce termination. For Pol III type 2 promoters, we found that the shorter poly-U tract lengths of 4 uracils were 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.

Computation-guided optimization of split protein systems

Splitting bioactive proteins into conditionally reconstituting fragments is a powerful strategy for building tools to study and control biological systems. However, split proteins often exhibit a high propensity to reconstitute even without the conditional trigger, limiting their utility. Current approaches for tuning reconstitution propensity are laborious, context-specific, or often ineffective. Here, we report a computational design strategy grounded in fundamental protein biophysics to guide experimental evaluation of a sparse set of mutants to identify an optimal functional window. We hypothesized that testing a limited set of mutants would direct subsequent mutagenesis efforts by predicting desirable mutant combinations from a vast mutational landscape. This strategy varies the degree of interfacial destabilization while preserving stability and catalytic activity. We validate our method by solving two distinct split protein design challenges, generating both design and mechanistic insights. This new technology will streamline the generation and use of split protein systems for diverse applications.

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 multifunctional proteins integrating both transcriptional and posttranslational 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.

Nanofountain Probe Electroporation Enables Versatile Single-Cell Intracellular Delivery and Investigation of Postpulse Electropore Dynamics

Introducing exogenous molecules into cells with high efficiency and dosage control is a crucial step in basic research as well as clinical applications. Here, the capability of the nanofountain probe electroporation (NFP-E) system to deliver proteins and plasmids in a variety of continuous and primary cell types with appropriate dosage control is reported. It is shown that the NFP-E can achieve fine control over the relative expression of two cotransfected plasmids. Finally, the dynamics of electropore closure after the pulsing ends with the NFP-E is investigated. Localized electroporation has recently been utilized to demonstrate the converse process of delivery (sampling), in which a small volume of the cytosol is retrieved during electroporation without causing cell lysis. Single-cell temporal sampling confers the benefit of monitoring the same cell over time and can provide valuable insights into the mechanisms underlying processes such as stem cell differentiation and disease progression. NFP-E parameters that maximize the membrane resealing time, which is essential for increasing the sampled volume and in meeting the challenge of monitoring low copy number biomarkers, are identified. Its application in CRISPR/Cas9 gene editing, stem cell reprogramming, and single-cell sampling studies is envisioned.

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.

Macrophages employ quorum licensing to regulate collective activation

Macrophage-initiated inflammation is tightly regulated to eliminate threats such as infections while suppressing harmful immune activation. However, individual cells’ signaling responses to pro-inflammatory cues are heterogeneous, with subpopulations emerging with high or low activation states. Here, we use single-cell tracking and dynamical modeling to develop and validate a revised model for lipopolysaccharide (LPS)-induced macrophage activation that invokes a mechanism we term quorum licensing. The results show that bimodal phenotypic partitioning of macrophages is primed during the resting state, dependent on cumulative history of cell density, predicted by extrinsic noise in transcription factor expression, and independent of canonical LPS-induced intercellular feedback in the tumor necrosis factor (TNF) response. Our analysis shows how this density-dependent coupling produces a nonlinear effect on collective TNF production. We speculate that by linking macrophage density to activation, this mechanism could amplify local responses to threats and prevent false alarms.

Macrophage activation is tightly regulated to maintain immune homeostasis, yet activation is also heterogeneous. Here, the authors show that macrophages coordinate activation by partitioning into two phenotypes that can nonlinearly amplify collective inflammatory cytokine production as a function of cell density.

The COMET toolkit for composing customizable genetic programs in mammalian cells

Engineering mammalian cells to carry out sophisticated and customizable genetic programs requires a toolkit of multiple orthogonal and well-characterized transcription factors (TFs). To address this need, we develop the COmposable Mammalian Elements of Transcription (COMET)-an ensemble of TFs and promoters that enable the design and tuning of gene expression to an extent not, to the best of our knowledge, previously possible. COMET currently comprises 44 activating and 12 inhibitory zinc-finger TFs and 83 cognate promoters, combined in a framework that readily accommodates new parts. This system can tune gene expression over three orders of magnitude, provides chemically inducible control of TF activity, and enables single-layer Boolean logic. We also develop a mathematical model that provides mechanistic insights into COMET performance characteristics. Altogether, COMET enables the design and construction of customizable genetic programs in mammalian cells.

Development of novel metabolite-responsive transcription factors via transposon-mediated protein fusion

Naturally evolved metabolite-responsive biosensors enable applications in metabolic engineering, ranging from screening large genetic libraries to dynamically regulating biosynthetic pathways. However, there are many metabolites for which a natural biosensor does not exist. To address this need, we developed a general method for converting metabolite-binding proteins into metabolite-responsive transcription factors-Biosensor Engineering by Random Domain Insertion (BERDI). This approach takes advantage of an in vitro transposon insertion reaction to generate all possible insertions of a DNA-binding domain into a metabolite-binding protein, followed by fluorescence activated cell sorting to isolate functional biosensors. To develop and evaluate the BERDI method, we generated a library of candidate biosensors in which a zinc finger DNA-binding domain was inserted into maltose binding protein, which served as a model well-studied metabolite-binding protein. Library diversity was characterized by several methods, a selection scheme was deployed, and ultimately several distinct and functional maltose-responsive transcriptional biosensors were identified. We hypothesize that the BERDI method comprises a generalizable strategy that may ultimately be applied to convert a wide range of metabolite-binding proteins into novel biosensors for applications in metabolic engineering and synthetic biology.

Advances, challenges, and opportunities in extracellular RNA biology: insights from the NIH exRNA Strategic Workshop

Extracellular RNA (exRNA) has emerged as an important transducer of intercellular communication. Advancing exRNA research promises to revolutionize biology and transform clinical practice. Recent efforts have led to cutting-edge research and expanded knowledge of this new paradigm in cell-to-cell crosstalk; however, gaps in our understanding of EV heterogeneity and exRNA diversity pose significant challenges for continued development of exRNA diagnostics and therapeutics. To unravel this complexity, the NIH convened expert teams to discuss the current state of the science, define the significant bottlenecks, and brainstorm potential solutions across the entire exRNA research field. The NIH Strategic Workshop on Extracellular RNA Transport helped identify mechanistic and clinical research opportunities for exRNA biology and provided recommendations on high priority areas of research that will advance the exRNA field.

Highly Stable, Ultrasmall Polymer-Grafted Nanobins (usPGNs) with Stimuli-Responsive Capability

Highly stable and stimuli/pH-responsive ultrasmall polymer-grafted nanobins (usPGNs) have been developed by grafting a small amount (10 mol %) of short (4.3 kDa) cholesterol-terminated poly(acrylic acid) (Chol-PAA) into an ultrasmall unilamellar vesicle (uSUV). The usPGNs are stable against fusion and aggregation over several weeks, exhibiting over 10-fold enhanced cargo retention in biologically relevant media at pH 7.4 in comparison with the parent uSUV template. Coarse-grained molecular dynamics (CGMD) simulations confirm that the presence of the cholesterol moiety can greatly stabilize the lipid bilayer. They also show extended PAA chain conformations that can be interpreted as causing repulsion between colloidal particles, thus stabilizing them against fusion. Notably, CGMD predicted a clustering of the Chol-PAA chains on the lipid bilayer under acidic conditions due to intra- and interchain hydrogen bonding, leading to the destabilization of local membrane areas. This explains the experimental observation that usPGNs can be triggered to release a significant amount of cargo upon acidification to pH 5. These developments put the lipid-bilayer-embedded Chol-PAA in stark contrast with traditional poly(acrylic acid) systems where the molar mass (Mn) of the polymer chains must exceed 16.5 kDa to achieve stimuli-responsive changes in conformation. They also distinguish the small usPGNs from the much-larger polymer-caged nanobin platform where the Chol-PAA chains must be covalently cross-linked to engender stimuli-responsive behaviors.

Multiplexing Engineered Receptors for Multiparametric Evaluation of Environmental Ligands

Engineered cell-based therapies comprise a promising, emerging biomedical technology. Broad utilization of this strategy will require new approaches for implementing sophisticated functional programs, such as sensing and responding to the environment in a defined fashion. Toward this goal, we investigated whether our self-contained receptor and signal transduction system (MESA) could be multiplexed to evaluate extracellular cues, with a focus on elucidating principles governing the integration of such engineered components. We first developed a set of hybrid promoters that exhibited AND gate activation by two transcription factors. We then evaluated these promoters when paired with two MESA receptors and various ligand combinations. Unexpectedly, although the multiplexed system exhibited distinct responses to ligands applied individually and in combination, the same synergy was not observed as when promoters were characterized with soluble transcription factors. Therefore, we developed a mechanistic computational model leveraging these observations, to both improve our understanding of how the receptors and promoters interface and to guide the design and implementation of future systems. Notably, the model explicitly accounts for the impact of intercellular variation on system characterization and performance. Model analysis identified key factors that affect the current receptors and promoters, and enabled an in silico exploration of potential modifications that inform the design of improved logic gates and their robustness to intercellular variation. Ultimately, this quantitative design-driven approach may guide the use and multiplexing of synthetic receptors for diverse custom biological functions beyond the case study considered here.

Building with intent: technologies and principles for engineering mammalian cell-based therapies to sense and respond

The engineering of cells as programmable devices has enabled therapeutic strategies that could not otherwise be achieved. Such strategies include recapitulating and enhancing native cellular functions and composing novel functions. These novel functions may be composed using both natural and engineered biological components, with the latter exemplified by the development of synthetic receptor and signal transduction systems. Recent advances in implementing these approaches include the treatment of cancer, where the most clinical progress has been made to date, and the treatment of diabetes. Principles for engineering cell-based therapies that are safe and effective are increasingly needed and beginning to emerge, and will be essential in the development of this new class of therapeutics.

Predicting the Dynamics and Heterogeneity of Genomic DNA Content within Bacterial Populations across Variable Growth Regimes

For many applications in microbial synthetic biology, optimizing a desired function requires careful tuning of the degree to which various genes are expressed. One challenge for predicting such effects or interpreting typical characterization experiments is that in bacteria such as E. coli, genome copy number varies widely across different phases and rates of growth, which also impacts how and when genes are expressed from different loci. While such phenomena are relatively well-understood at a mechanistic level, our quantitative understanding of such processes is essentially limited to ideal exponential growth. In contrast, common experimental phenomena such as growth on heterogeneous media, metabolic adaptation, and oxygen restriction all cause substantial deviations from ideal exponential growth, particularly as cultures approach the higher densities at which industrial biomanufacturing and even routine screening experiments are conducted. To meet the need for predicting and explaining how gene dosage impacts cellular functions outside of exponential growth, we here report a novel modeling strategy that leverages agent-based simulation and high performance computing to robustly predict the dynamics and heterogeneity of genomic DNA content within bacterial populations across variable growth regimes. We show that by feeding routine experimental data, such as optical density time series, into our heterogeneous multiphasic growth simulator, we can predict genomic DNA distributions over a range of nonexponential growth conditions. This modeling strategy provides an important advance in the ability of synthetic biologists to evaluate the role of genomic DNA content and heterogeneity in affecting the performance of existing or engineered microbial functions.

A Systematic Evaluation of Factors Affecting Extracellular Vesicle Uptake by Breast Cancer Cells

Extracellular vesicles (EVs) are nanometer-scale particles that are secreted by cells and mediate intercellular communication by transferring biomolecules between cells. Harnessing this mechanism for therapeutic biomolecule delivery represents a promising frontier for regenerative medicine and other clinical applications. One challenge to realizing this goal is that to date, our understanding of which factors affect EV uptake by recipient cells remains incomplete. In this study, we systematically investigated such delivery questions in the context of breast cancer cells, which are one of the most well-studied cell types with respect to EV delivery and therefore comprise a facile model system for this investigation. By displaying various targeting peptides on the EV surface, we observed that although displaying GE11 on EVs modestly increased uptake by MCF-7 cells, neuropeptide Y (NPY) display had no effect on uptake by the same cells. In contrast, neurotensin (NTS) and urokinase plasminogen activator (uPA) display reduced EV uptake by MDA-MB-231 cells. Interestingly, EV uptake rate did not depend on the source of the EVs; breast cancer cells demonstrated no increase in uptake on administration of breast cancer-derived EVs in comparison to HEK293FT-derived EVs. Moreover, EV uptake was greatly enhanced by delivery in the presence of polybrene and spinoculation, suggesting that maximal EV uptake rates are much greater than those observed under basal conditions in cell culture. By investigating how the cell's environment might provide cues that impact EV uptake, we also observed that culturing cells on soft matrices significantly enhanced EV uptake, compared to culturing on stiff tissue culture polystyrene. Each of these observations provides insights into the factors impacting EV uptake by breast cancer cells, while also providing a basis of comparison for systematically evaluating and perhaps enhancing EV uptake by various cell types.

Engineering Modular Biosensors to Confer Metabolite-Responsive Regulation of Transcription

Efforts to engineer microbial factories have benefitted from mining biological diversity and high throughput synthesis of novel enzymatic pathways, yet screening and optimizing metabolic pathways remain rate-limiting steps. Metabolite-responsive biosensors may help to address these persistent challenges by enabling the monitoring of metabolite levels in individual cells and metabolite-responsive feedback control. We are currently limited to naturally evolved biosensors, which are insufficient for monitoring many metabolites of interest. Thus, a method for engineering novel biosensors would be powerful, yet we lack a generalizable approach that enables the construction of a wide range of biosensors. As a step toward this goal, we here explore several strategies for converting a metabolite-binding protein into a metabolite-responsive transcriptional regulator. By pairing a modular protein design approach with a library of synthetic promoters and applying robust statistical analyses, we identified strategies for engineering biosensor-regulated bacterial promoters and for achieving design-driven improvements of biosensor performance. We demonstrated the feasibility of this strategy by fusing a programmable DNA binding motif (zinc finger module) with a model ligand binding protein (maltose binding protein), to generate a novel biosensor conferring maltose-regulated gene expression. This systematic investigation provides insights that may guide the development of additional novel biosensors for diverse synthetic biology applications.

Rewiring human cellular input-output using modular extracellular sensors

Engineered cell-based therapies comprise a promising emerging strategy for treating diverse diseases. Realizing this promise requires new tools for engineering cells to sense and respond to soluble extracellular factors, which provide information about both physiological state and the local environment. Here, we report such a biosensor engineering strategy, leveraging a self-contained receptor-signal transduction system termed modular extracellular sensor architecture (MESA). We developed MESA receptors that enable cells to sense vascular endothelial growth factor (VEGF) and, in response, secrete interleukin 2 (IL-2). By implementing these receptors in human T cells, we created a customized function not observed in nature-an immune cell that responds to a normally immunosuppressive cue (VEGF) by producing an immunostimulatory factor (IL-2). Because this platform utilizes modular, engineerable domains for ligand binding (antibodies) and output (programmable transcription factors based upon Cas9), this approach may be readily extended to novel inputs and outputs. This generalizable approach for rewiring cellular functions could enable both translational applications and fundamental biological research.

Regulation of the IL-10-driven macrophage phenotype under incoherent stimuli

Macrophages are ubiquitous innate immune cells that play a central role in health and disease by adopting distinct phenotypes, which are broadly divided into classical inflammatory responses and alternative responses that promote immune suppression and wound healing. Although macrophages are attractive therapeutic targets, incomplete understanding of this functional choice limits clinical manipulation. While individual stimuli, pathways, and genes involved in macrophage functional responses have been identified, how macrophages evaluate complex in vivo milieus comprising multiple divergent stimuli remains poorly understood. Here, we used combinations of "incoherent" stimuli-those that individually promote distinct macrophage phenotypes-to elucidate how the immunosuppressive, IL-10-driven macrophage phenotype is induced, maintained, and modulated under such combinatorial stimuli. The IL-10-induced immunosuppressive phenotype was largely insensitive to co-administered IL-12, which has been reported to modulate macrophage phenotype, but maintaining the immunosuppressive phenotype required sustained exposure to IL-10. Our data implicate the intracellular protein, BCL3, as a key mediator of the IL-10-driven phenotype. Notably, co-administration of IFN-γ disrupted an IL-10-mediated positive feedback loop that may reinforce the immunosuppressive phenotype. This novel combinatorial perturbation approach thus generated new insights into macrophage decision making and local immune network function.

Adding energy minimization strategy to peptide-design algorithm enables better search for RNA-binding peptides: Redesigned λ N peptide binds boxB RNA

Our previously developed peptide-design algorithm was improved by adding an energy minimization strategy which allows the amino acid sidechains to move in a broad configuration space during sequence evolution. In this work, the new algorithm was used to generate a library of 21-mer peptides which could substitute for λ N peptide in binding to boxB RNA. Six potential peptides were obtained from the algorithm, all of which exhibited good binding capability with boxB RNA. Atomistic molecular dynamics simulations were then conducted to examine the ability of the λ N peptide and three best evolved peptides, viz. Pept01, Pept26, and Pept28, to bind to boxB RNA. Simulation results demonstrated that our evolved peptides are better at binding to boxB RNA than the λ N peptide. Sequence searches using the old (without energy minimization strategy) and new (with energy minimization strategy) algorithms confirm that the new algorithm is more effective at finding good RNA-binding peptides than the old algorithm. © 2016 Wiley Periodicals, Inc.

Engineering cell-based therapies to interface robustly with host physiology

Engineered cell-based therapies comprise a rapidly growing clinical technology for treating disease by leveraging the natural capabilities of cells, including migration, information transduction, and biosynthesis and secretion. There now exists a substantial portfolio of intracellular and extracellular sensors that enable bioengineers to program cells to execute defined responses to specific changes in state or environmental cues. As our capability to construct more sophisticated cellular programs increases, assessing and improving the degree to which cell-based therapies perform as desired in vivo will become an increasingly important consideration and opportunity for technological advancement. In this review, we seek to describe both current capabilities and potential needs for building cell-based therapies that interface with host physiology in a manner that is robust - a phrase we use in this context to describe the achievement of therapeutic efficacy across a range of patients and implementations. We first review the portfolio of sensors and outputs currently available for use in cell-based therapies by highlighting key advancements and current gaps. Then, we propose a conceptual framework for evaluating and pursuing robust clinical performance of engineered cell-based therapies.

A platform for actively loading cargo RNA to elucidate limiting steps in EV-mediated delivery

Extracellular vesicles (EVs) mediate intercellular communication through transfer of RNA and protein between cells. Thus, understanding how cargo molecules are loaded and delivered by EVs is of central importance for elucidating the biological roles of EVs and developing EV-based therapeutics. While some motifs modulating the loading of biomolecular cargo into EVs have been elucidated, the general rules governing cargo loading and delivery remain poorly understood. To investigate how general biophysical properties impact loading and delivery of RNA by EVs, we developed a platform for actively loading engineered cargo RNAs into EVs. In our system, the MS2 bacteriophage coat protein was fused to EV-associated proteins, and the cognate MS2 stem loop was engineered into cargo RNAs. Using this Targeted and Modular EV Loading (TAMEL) approach, we identified a configuration that substantially enhanced cargo RNA loading (up to 6-fold) into EVs. When applied to vesicles expressing the vesicular stomatitis virus glycoprotein (VSVG) – gesicles – we observed a 40-fold enrichment in cargo RNA loading. While active loading of mRNA-length (>1.5 kb) cargo molecules was possible, active loading was much more efficient for smaller (~0.5 kb) RNA molecules. We next leveraged the TAMEL platform to elucidate the limiting steps in EV-mediated delivery of mRNA and protein to prostate cancer cells, as a model system. Overall, most cargo was rapidly degraded in recipient cells, despite high EV-loading efficiencies and substantial EV uptake by recipient cells. While gesicles were efficiently internalized via a VSVG-mediated mechanism, most cargo molecules were rapidly degraded. Thus, in this model system, inefficient endosomal fusion or escape likely represents a limiting barrier to EV-mediated transfer. Altogether, the TAMEL platform enabled a comparative analysis elucidating a key opportunity for enhancing EV-mediated delivery to prostate cancer cells, and this technology should be of general utility for investigations and applications of EV-mediated transfer in other systems.

Regulation of Bacterial Gene Expression by Protease-Alleviated Spatial Sequestration (PASS)

In natural microbial systems, conditional spatial sequestration of transcription factors enables cells to respond rapidly to changes in their environment or intracellular state by releasing presynthesized regulatory proteins. Although such a mechanism may be useful for engineering synthetic biology technologies ranging from cell-based biosensors to biosynthetic platforms, to date it remains unknown how or whether such conditional spatial sequestration may be engineered. In particular, based upon seemingly contradictory reports in the literature, it is not clear whether subcellular spatial localization of a transcription factor within the cytoplasm is sufficient to preclude regulation of cognate promoters on plasmid-borne or chromosomal loci. Here, we describe a modular, orthogonal platform for investigating and implementing this mechanism using protease-alleviated spatial sequestration (PASS). In this system, expression of an exogenous protease mediates the proteolytic release of engineered transcriptional regulators from the inner face of the Escherichia coli cytoplasmic membrane. We demonstrate that PASS mediates robust, conditional regulation of either transcriptional repression, via tetR, or transcriptional activation, by the λ phage CI protein. This work provides new insights into a biologically important facet of microbial gene expression and establishes a new strategy for engineering conditional transcriptional regulation for the microbial synthetic biology toolbox.

Spatial and functional heterogeneities shape collective behavior of tumor-immune networks

Tumor growth involves a dynamic interplay between cancer cells and host cells, which collectively form a tumor microenvironmental network that either suppresses or promotes tumor growth under different conditions. The transition from tumor suppression to tumor promotion is mediated by a tumor-induced shift in the local immune state, and despite the clinical challenge this shift poses, little is known about how such dysfunctional immune states are initiated. Clinical and experimental observations have indicated that differences in both the composition and spatial distribution of different cell types and/or signaling molecules within the tumor microenvironment can strongly impact tumor pathogenesis and ultimately patient prognosis. How such “functional” and “spatial” heterogeneities confer such effects, however, is not known. To investigate these phenomena at a level currently inaccessible by direct observation, we developed a computational model of a nascent metastatic tumor capturing salient features of known tumor-immune interactions that faithfully recapitulates key features of existing experimental observations. Surprisingly, over a wide range of model formulations, we observed that heterogeneity in both spatial organization and cell phenotype drove the emergence of immunosuppressive network states. We determined that this observation is general and robust to parameter choice by developing a systems-level sensitivity analysis technique, and we extended this analysis to generate other parameter-independent, experimentally testable hypotheses. Lastly, we leveraged this model as an in silico test bed to evaluate potential strategies for engineering cell-based therapies to overcome tumor associated immune dysfunction and thereby identified modes of immune modulation predicted to be most effective. Collectively, this work establishes a new integrated framework for investigating and modulating tumor-immune networks and provides insights into how such interactions may shape early stages of tumor formation.

Over the course of tumor growth, cancer cells interact with normal cells via processes that are difficult to understand by experiment alone. This challenge is particularly pronounced at early stages of tumor formation, when experimental observation is most limited. Elucidating such interactions could inform both understanding of cancer and clinical practice. To address this need we developed a computational model capturing the current understanding of how individual metastatic tumor cells and immune cells sense and contribute to the tumor environment, which in turn enabled us to investigate the complex, collective behavior of these systems. Surprisingly, we discovered that tumor escape from immune control was enhanced by the existence of small differences (or heterogeneities) in the responses of individual immune cells to their environment, as well as by heterogeneities in the way that cells and the molecules they secrete are arranged in space. These conclusions held true over a range of model formulations, suggesting that this is a general feature of these tumor-immune networks. Finally, we used this model as a test bed to evaluate potential strategies for enhancing immunological control of early tumors, ultimately predicting that specifically modulating tumor-associated immune dysfunction may be more effective than simply enhanced tumor killing.

Contributions of unique intracellular domains to switchlike biosensing by Toll-like receptor 4

Toll-like receptors (TLRs) mediate immune recognition of both microbial infections and tissue damage. Aberrant TLR signaling promotes disease; thus, understanding the regulation of TLR signaling is of medical relevance. Although downstream mediators of TLR signaling have been identified, the detailed mechanism by which ligand binding-mediated dimerization induces downstream signaling remains poorly understood. Here, we investigate this question for TLR4, which mediates responsiveness to bacterial LPS and drives inflammatory disease. TLR4 exhibits structural and functional features that are unique among TLRs, including responsiveness to a wide variety of ligands. However, the connection between these structural features and the regulation of signaling is not clear. Here, we investigated how the unique intracellular structures of TLR4 contribute to receptor signaling. Key conclusions include the following. 1) The unique intracellular linker of TLR4 is important for achieving LPS-inducible signaling via Toll/IL-1 receptor (TIR) domain-containing adapter-inducing interferon-β (TRIF) but less so for signaling via myeloid differentiation primary response 88 (MyD88). 2) Membrane-bound TLR4 TIR domains were sufficient to induce signaling. However, introducing long, flexible intracellular linkers neither induced constitutive signaling nor ablated LPS-inducible signaling. Thus, the initiation of TLR4 signaling is regulated by a mechanism that does not require tight geometric constraints. Together, these observations necessitate refining the model of TLR4 signal initiation. We hypothesize that TLR4 may interact with an inhibitory partner in the absence of ligand, via both TIR and extracellular domains of TLR4. In this speculative model, ligand binding induces dissociation of the inhibitory partner, triggering spontaneous, switchlike TIR domain homodimerization to initiate downstream signaling.

Stabilization of exosome-targeting peptides via engineered glycosylation

Exosomes are secreted extracellular vesicles that mediate intercellular transfer of cellular contents and are attractive vehicles for therapeutic delivery of bimolecular cargo such as nucleic acids, proteins, and even drugs. Efficient exosome-mediated delivery in vivo requires targeting vesicles for uptake by specific recipient cells. Although exosomes have been successfully targeted to several cellular receptors by displaying peptides on the surface of the exosomes, identifying effective exosome-targeting peptides for other receptors has proven challenging. Furthermore, the biophysical rules governing targeting peptide success remain poorly understood. To evaluate one factor potentially limiting exosome delivery, we investigated whether peptides displayed on the exosome surface are degraded during exosome biogenesis, for example by endosomal proteases. Indeed, peptides fused to the N terminus of exosome-associated transmembrane protein Lamp2b were cleaved in samples derived from both cells and exosomes. To suppress peptide loss, we engineered targeting peptide-Lamp2b fusion proteins to include a glycosylation motif at various positions. Introduction of this glycosylation motif both protected the peptide from degradation and led to an increase in overall Lamp2b fusion protein expression in both cells and exosomes. Moreover, glycosylation-stabilized peptides enhanced targeted delivery of exosomes to neuroblastoma cells, demonstrating that such glycosylation does not ablate peptide-target interactions. Thus, we have identified a strategy for achieving robust display of targeting peptides on the surface of exosomes, which should facilitate the evaluation and development of new exosome-based therapeutics.

Modular extracellular sensor architecture for engineering mammalian cell-based devices

Engineering mammalian cell-based devices that monitor and therapeutically modulate human physiology is a promising and emerging frontier in clinical synthetic biology. However, realizing this vision will require new technologies enabling engineered circuitry to sense and respond to physiologically relevant cues. No existing technology enables an engineered cell to sense exclusively extracellular ligands, including proteins and pathogens, without relying upon native cellular receptors or signal transduction pathways that may be subject to crosstalk with native cellular components. To address this need, we here report a technology we term a Modular Extracellular Sensor Architecture (MESA). This self-contained receptor and signal transduction platform is maximally orthogonal to native cellular processes and comprises independent, tunable protein modules that enable performance optimization and straightforward engineering of novel MESA that recognize novel ligands. We demonstrate ligand-inducible activation of MESA signaling, optimization of receptor performance using design-based approaches, and generation of MESA biosensors that produce outputs in the form of either transcriptional regulation or transcription-independent reconstitution of enzymatic activity. This systematic, quantitative platform characterization provides a framework for engineering MESA to recognize novel ligands and for integrating these sensors into diverse mammalian synthetic biology applications.

Therapeutic applications of extracellular vesicles: clinical promise and open questions

This review provides an updated perspective on rapidly proliferating efforts to harness extracellular vesicles (EVs) for therapeutic applications. We summarize current knowledge, emerging strategies, and open questions pertaining to clinical potential and translation. Potentially useful EVs comprise diverse products of various cell types and species. EV components may also be combined with liposomes and nanoparticles to facilitate manufacturing as well as product safety and evaluation. Potential therapeutic cargoes include RNA, proteins, and drugs. Strategic issues considered herein include choice of therapeutic agent, means of loading cargoes into EVs, promotion of EV stability, tissue targeting, and functional delivery of cargo to recipient cells. Some applications may harness natural EV properties, such as immune modulation, regeneration promotion, and pathogen suppression. These properties can be enhanced or customized to enable a wide range of therapeutic applications, including vaccination, improvement of pregnancy outcome, and treatment of autoimmune disease, cancer, and tissue injury.

Lentivirus delivery of IL-10 to promote and sustain macrophage polarization towards an anti-inflammatory phenotype

Gene delivery from biomaterials can create an environment that promotes and guides tissue formation. However, the immune response induced upon biomaterial implantation can be detrimental to tissue regeneration. Macrophages play a central role in mediating early phases of this response, and functional "polarization" of macrophages towards M1 (inflammatory) or M2 (anti-inflammatory) phenotypes may bias the local immune state at the implant site. Since gene delivery from biomaterial scaffolds can confer transgene expression in macrophages in vivo, we investigated whether transduction of macrophages with an IL-10 encoding lentivirus can (1) induce macrophage polarization toward an M2 phenotype even in an pro-inflammatory environment, and (2) prevent a shift in polarization from M2 to M1 following exposure to pro-inflammatory stimuli. IL-10 lentivirus delivery to pre-polarized M1 macrophages reduced TNF-α production 1.5-fold when compared to cells treated with either a control virus or a bolus delivery of recombinant IL-10 protein. IL-10 lentivirus delivery to naïve macrophages reduced the amount of TNF-α produced following an inflammatory challenge by 2.5-fold compared to cells treated with both the control virus and recombinant IL-10. At a mechanistic level, IL-10 lentivirus delivery mediated sustained reduction in NF-κB activation and, accordingly, reduced transcription of TNF-α. In sum, lentiviral delivery of IL-10 to macrophages represents a promising strategy for directing and sustaining macrophage polarization towards an M2 phenotype in order to promote local immune responses that facilitate tissue engineering.

Engineered cell-based therapies: a vanguard of design-driven medicine

Engineered cell-based therapies are uniquely capable of performing sophisticated therapeutic functions in vivo, and this strategy is yielding promising clinical benefits for treating cancer. In this review, we discuss key opportunities and challenges for engineering customized cellular functions using cell-based therapy for cancer as a representative case study. We examine the historical development of chimeric antigen receptor (CAR) therapies as an illustration of the engineering design cycle. We also consider the potential roles that the complementary disciplines of systems biology and synthetic biology may play in realizing safe and effective treatments for a broad range of patients and diseases. In particular, we discuss how systems biology may facilitate both fundamental research and clinical translation, and we describe how the emerging field of synthetic biology is providing novel modalities for building customized cellular functions to overcome existing clinical barriers. Together, these approaches provide a powerful set of conceptual and experimental tools for transforming information into understanding, and for translating understanding into novel therapeutics to establish a new framework for design-driven medicine.

Modulation of leukocyte infiltration and phenotype in microporous tissue engineering scaffolds via vector induced IL-10 expression

Biomaterial scaffolds are central to many tissue engineering strategies as they create a space for tissue growth and provide a support for cell adhesion and migration. However, biomaterial implantation results in unavoidable injury resulting in an inflammatory response, which can impair integration with the host and tissue regeneration. Toward the goal of reducing inflammation, we investigated the hypothesis that a lentiviral gene therapy-based approach to localized and sustained IL-10 expression at a scaffold could modulate the number, relative proportions, and cytokine production of infiltrating leukocyte populations. Flow cytometry was used to quantify infiltration of six leukocyte populations for 21 days following implantation of PLG scaffolds into intraperitoneal fat. Leukocytes with innate immune functions (i.e., macrophages, dendritic cells, neutrophils) were most prevalent at early time points, while T lymphocytes became prevalent by day 14. Reporter gene delivery indicated that transgene expression persisted at the scaffold for up to 28 days and macrophages were the most common leukocyte transduced, while transduced dendritic cells expressed the greatest levels of transgene. IL-10 delivery decreased leukocyte infiltration by 50% relative to controls, increased macrophage IL-10 expression, and decreased macrophage, dendritic cell, and CD4 T cell IFN-γ expression. Thus, IL-10 gene delivery significantly decreased inflammation following scaffold implant into the intraperitoneal fat, in part by modulating cytokine expression of infiltrating leukocytes.

FedExosomes: Engineering Therapeutic Biological Nanoparticles that Truly Deliver

Many aspects of intercellular communication are mediated through "sending" and "receiving" packets of information via the secretion and subsequent receptor-mediated detection of biomolecular species including cytokines, chemokines, and even metabolites. Recent evidence has now established a new modality of intercellular communication through which biomolecular species are exchanged between cells via extracellular lipid vesicles. A particularly important class of extracellular vesicles is exosomes, which is a term generally applied to biological nanovesicles ~30-200 nm in diameter. Exosomes form through invagination of endosomes to encapsulate cytoplasmic contents, and upon fusion of these multivesicular endosomes to the cell surface, exosomes are released to the extracellular space and transport mRNA, microRNA (miRNA) and proteins between cells. Importantly, exosome-mediated delivery of such cargo molecules results in functional modulation of the recipient cell, and such modulation is sufficiently potent to modulate disease processes in vivo. It is possible that such functional delivery of biomolecules indicates that exosomes utilize native mechanisms (e.g., for internalization and trafficking) that may be harnessed by using exosomes to deliver exogenous RNA for therapeutic applications. A complementary perspective is that understanding the mechanisms of exosome-mediated transport may provide opportunities for "reverse engineering" such mechanisms to improve the performance of synthetic delivery vehicles. In this review, we summarize recent progress in harnessing exosomes for therapeutic RNA delivery, discuss the potential for engineering exosomes to overcome delivery challenges and establish robust technology platforms, and describe both potential challenges and advantages of utilizing exosomes as RNA delivery vehicles.