Ultra-high efficiency T cell reprogramming at multiple loci with SEED-Selection.

Multiplexed reprogramming of T cell specificity and function can generate powerful next-generation cellular therapies. However, current manufacturing methods produce heterogenous mixtures of partially engineered cells. Here, we develop a one-step process to enrich for unlabeled cells with knock-ins at multiple target loci using a family of repair templates named Synthetic Exon/Expression Disruptors (SEEDs). SEED engineering associates transgene integration with the disruption of a paired endogenous surface protein, allowing non-modified and partially edited cells to be immunomagnetically depleted (SEED-Selection). We design SEEDs to fully reprogram three critical loci encoding T cell specificity, co-receptor expression, and MHC expression, with up to 98% purity after selection for individual modifications and up to 90% purity for six simultaneous edits (three knock-ins and three knockouts). These methods are simple, compatible with existing clinical manufacturing workflows, and can be readily adapted to other loci to facilitate production of complex gene-edited cell therapies.

Peptide-mediated delivery of CRISPR enzymes for the efficient editing of primary human lymphocytes.

CRISPR-mediated genome editing of primary human lymphocytes is typically carried out via electroporation, which can be cytotoxic, cumbersome and costly. Here we show that the yields of edited primary human lymphocytes can be increased substantially by delivering a CRISPR ribonucleoprotein mixed with an amphiphilic peptide identified through screening. We evaluated the performance of this simple delivery method by knocking out genes in T cells, B cells and natural killer cells via the delivery of Cas9 or Cas12a ribonucleoproteins or an adenine base editor. We also show that peptide-mediated ribonucleoprotein delivery paired with an adeno-associated-virus-mediated homology-directed repair template can introduce a chimaeric antigen receptor gene at the T-cell receptor α constant locus, and that the engineered cells display antitumour potency in mice. The method is minimally perturbative, does not require dedicated hardware, and is compatible with multiplexed editing via sequential delivery, which minimizes the risk of genotoxicity. The peptide-mediated intracellular delivery of ribonucleoproteins may facilitate the manufacturing of engineered T cells.

An evolved AAV variant enables efficient genetic engineering of murine T cells.

Precise targeting of large transgenes to T cells using homology-directed repair has been transformative for adoptive cell therapies and T cell biology. Delivery of DNA templates via adeno-associated virus (AAV) has greatly improved knockin efficiencies, but the tropism of current AAV serotypes restricts their use to human T cells employed in immunodeficient mouse models. To enable targeted knockins in murine T cells, we evolved Ark313, a synthetic AAV that exhibits high transduction efficiency in murine T cells. We performed a genome-wide knockout screen and identified QA2 as an essential factor for Ark313 infection. We demonstrate that Ark313 can be used for nucleofection-free DNA delivery, CRISPR-Cas9-mediated knockouts, and targeted integration of large transgenes. Ark313 enables preclinical modeling of Trac-targeted CAR-T and transgenic TCR-T cells in immunocompetent models. Efficient gene targeting in murine T cells holds great potential for improved cell therapies and opens avenues in experimental T cell immunology.

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.

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.

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.

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.

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.

Network inference performance complexity: a consequence of topological, experimental and algorithmic determinants.

MOTIVATION: Network inference algorithms aim to uncover key regulatory interactions governing cellular decision-making, disease progression and therapeutic interventions. Having an accurate blueprint of this regulation is essential for understanding and controlling cell behavior. However, the utility and impact of these approaches are limited because the ways in which various factors shape inference outcomes remain largely unknown. RESULTS: We identify and systematically evaluate determinants of performance-including network properties, experimental design choices and data processing-by developing new metrics that quantify confidence across algorithms in comparable terms. We conducted a multifactorial analysis that demonstrates how stimulus target, regulatory kinetics, induction and resolution dynamics, and noise differentially impact widely used algorithms in significant and previously unrecognized ways. The results show how even if high-quality data are paired with high-performing algorithms, inferred models are sometimes susceptible to giving misleading conclusions. Lastly, we validate these findings and the utility of the confidence metrics using realistic in silico gene regulatory networks. This new characterization approach provides a way to more rigorously interpret how algorithms infer regulation from biological datasets. AVAILABILITY AND IMPLEMENTATION: Code is available at http://github.com/bagherilab/networkinference/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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.

The Modifier of Transcription 1 (Mot1) ATPase and Spt16 Histone Chaperone Co-regulate Transcription through Preinitiation Complex Assembly and Nucleosome Organization.

Modifier of transcription 1 (Mot1) is a conserved and essential Swi2/Snf2 ATPase that can remove TATA-binding protein (TBP) from DNA using ATP hydrolysis and in so doing exerts global effects on transcription. Spt16 is also essential and functions globally in transcriptional regulation as a component of the facilitates chromatin transcription (FACT) histone chaperone complex. Here we demonstrate that Mot1 and Spt16 regulate a largely overlapping set of genes in Saccharomyces cerevisiae. As expected, Mot1 was found to control TBP levels at co-regulated promoters. In contrast, Spt16 did not affect TBP recruitment. On a global scale, Spt16 was required for Mot1 promoter localization, and Mot1 also affected Spt16 localization to genes. Interestingly, we found that Mot1 has an unanticipated role in establishing or maintaining the occupancy and positioning of nucleosomes at the 5' ends of genes. Spt16 has a broad role in regulating chromatin organization in gene bodies, including those nucleosomes affected by Mot1. These results suggest that the large scale overlap in Mot1 and Spt16 function arises from a combination of both their unique and shared functions in transcription complex assembly and chromatin structure regulation.