Biology subjects

Elowitz, M. B.

Publications and source records attributed to Elowitz, M. B..

At least 19 recordsLinked to original sources

bioRxiv2026

Engineered caspases directly rewire mutant Ras to cell death

As central executioners of cell death, caspases that activate exclusively in diseased cells would provide powerful and specific therapeutic agents. Natural caspase regulation exhibits two universal features that facilitate the engineering of such caspases: proximity-induced subunit assembly and modular separation of substrate recruitment from catalysis. Here, we take advantage of these features to engineer "Raspases," split effector caspases that conditionally reconstitute active complexes upon detection of mutant Ras, an oncogene altered in roughly a quarter of all cancers. When delivered as mRNA in lipid nanoparticles, Raspases selectively eliminate Ras-mutant human cancer lines while sparing wild-type cells. The system is built entirely from human protein domains, can be encoded as a single polyprotein, and can be adapted to trigger pyroptosis. Critically, Raspases match or exceed the potency of alternative Ras-targeting interventions in vitro. These results establish retargeted caspases as a generalizable sense-and-kill platform for selective elimination of diseased cells.

synthetic biology↗

bioRxiv2026

Adenylyl cyclases combinatorially integrate opposing dopamine receptor signals

Dopamine receptors are divided into two families which exert opposing effects on the second messenger cyclic AMP (cAMP). While most neuronal cell types express a single receptor subtype, some neurons co-express opposing receptor subtypes. It remains unclear how these cells could resolve simultaneous stimulatory and inhibitory inputs. Here, we introduce a multiplexed assay that quantifies surface receptor abundance and dynamic cAMP output in single cells. Using this assay, together with mathematical modeling, we demonstrate that signals from opposing receptor subtypes are integrated flexibly by downstream adenylyl cyclases (ACs) rather than at the receptor level. Because AC isoforms exhibit unique biochemical properties, a cells AC expression profile determines whether conflicting inputs are cancelled, suppressed, or amplified. Brain transcriptome analysis indicates that co-expression of opposing dopamine receptors is associated with expression of specific AC isoforms predicted to sustain signaling during multi-receptor activation. Our results show that dopamine signal integration depends on the expression profiles of receptors and AC isoforms in a predictable way.

systems biology↗

bioRxiv2026

De novo design of selective kinase modulators

Protein kinases are critical regulators of cellular signaling, but precise modulation of their activity remains challenging due to their high structural conservation. Here, we present de novo designed genetically encoded miniproteins capable of activating or inhibiting focal adhesion kinase (FAK) by directly targeting the kinase domain itself. Among 96 binders designed to stabilize distinct conformational states of FAK, 33 modulated kinase activity. Biochemical characterization of the four most potent modulators revealed that two designs inhibit FAK with low-nanomolar IC50 values while the remaining two potentiated FAK activity by more than two-fold. When expressed in cells, the modulators preserved the same inhibitory and activating effects observed in vitro, establishing that designed conformational binders can directly tune FAK signaling in living cells. Taking advantage of the high similarity between kinases, we redesigned the FAK inhibitors to inhibit Src kinase. Our approach establishes a versatile platform for selective and genetically encoded kinase control as a way to rewire cell signaling and as a starting point for the discovery of novel modulatory sites of kinases.

biochemistry↗

bioRxiv2026

Regenerative base editing enables deep lineage recording

Reconstructing the lineage histories of individual cells can reveal the dynamics of developmental and disease processes. In engineered recording systems, cells stochastically edit synthetic barcode sequences as they proliferate, creating distinct, heritable edit patterns that can be used to reconstruct the lineage trees relating individual cells in a manner analogous to phylogenetic reconstruction. However, recording depth is often limited by the kinetics of the editing process: the rate of editing declines exponentially over time for an array of independently editable targets, leading to most edits occurring in early generations. Here, we introduce the hypercascade, a regenerative molecular recording system that takes advantage of the predictability of A-to-G base editing to progressively create new target sites over time. The hypercascade packs 4 editable target sites in every 20 bp of sequence, enabling high density information storage. More importantly, the hypercascades regenerative logic leads to an approximately constant rate of mutation accumulation over time. This in turn facilitates reconstruction of deep lineage relationships. We demonstrate this by reconstructing trees spanning 23 days of editing and approximately 17 generations after a single polyclonal engineering step. Finally, simulations show that the hypercascade has the potential to record chromatin state transition dynamics across multiple genomic loci in parallel. The hypercascade thus provides a flexible and broadly useful tool for molecular recording.

bioengineering↗

bioRxiv2025

Trainable computation in molecular networks

Reports of learning in single cells without genetic change span decades yet remain controversial, in part because there is no accepted general molecular mechanism for training comparable to gradient-based training or Hebbian learning in neural circuits. Here we identify a minimal set of ingredients sufficient to realize non-genetic learning, drawing inspiration from Boltzmann neural networks. First, dense reversible interaction networks provide an expressive substrate in which modulating the concentrations of a small set of mediator species can reprogram function without altering the underlying interaction parameters. Second, a simple rate-sensitive autoregulatory scheme that adjusts these mediator levels provides a local Hebbian-like training rule that can train the same network for diverse tasks, including Pavlovian conditioning, supervised classification, and generative tuning of bet-hedging ratios to match environmental statistics. We show that this autoregulatory training rule is model free and applies to reversible multimerization networks of arbitrary complexity, so training can compensate for unknown or unmodeled interactions present in vivo. These results suggest design principles for trainable synthetic cellular circuits and indicate how molecular systems could learn statistical features of their environments through experience.

systems biology↗

bioRxiv2025

Synaptic MEMOIR: mapping individual synapses of neurons with protein barcodes

Obtaining wiring diagrams of brains has been a major achievement for neuroscience. However, an underlying challenge in connectomics is the fundamental tradeoff between the imaging resolution needed to resolve synapses and the volume of the brain that can be imaged. For example, electron microscopy (EM) visualizes synaptic sites with ~5 nm resolution, but is difficult to scale beyond volumes of 1 mm3. Here, we present Synaptic MEMOIR (Memory with Engineered Mutagenesis with Optical in situ Readout) that enables imaging of neuronal projections in animal brains with single-synapse resolution. Synaptic MEMOIR is built around three key design features. First, protein barcodes are transported to synapses to allow matching of synaptic barcodes to cell body barcodes without high resolution imaging and the error-prone process of tracing neuronal processes across long distances. Second, Synaptic MEMOIR uses continuous mutagenesis to generate a large diversity of barcodes to uniquely label cell bodies and synapses. Last, the timing of recombination and transport can be tuned to record synaptic age or projection information. Combining these features, we demonstrated projection mapping of 113 neurons in the Drosophila melanogaster optic lobe in a volume of 9.5 million m3. Because synapses are identified by transported barcodes with optical microscopy at 300 nm resolution, this approach can potentially scale to much larger volumes, similar at least to those imaged in recent mouse brain transcriptomics atlases. In addition, synaptic MEMOIR can match barcodes across brain sections, and does not require tissue clearing to track long-range projections. Together, these results provide the foundation for a scalable optical image-based system for reconstructing the neural wiring diagrams of brains across different developmental stages, genetic backgrounds and perturbations. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=46 SRC="FIGDIR/small/690442v1_ufig1.gif" ALT="Figure 1"> View larger version (14K): org.highwire.dtl.DTLVardef@8363cdorg.highwire.dtl.DTLVardef@d3240org.highwire.dtl.DTLVardef@5e2793org.highwire.dtl.DTLVardef@1784f2a_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2025

Engineering Synthetic Phase Variation for Control of Microbial consortium

Some biochemical functions can be performed more efficiently when split into different tasks, each performed by distinct strains within a microbial consortium. Due to the distinct growth dynamics of each strain, uncontrolled consortia have unstable composition dynamics, leading to the rapid loss of the community level function. Several approaches have been developed to stabilize consortia, with most relying on communicated-mediated growth and death feedback. These approaches require accurate communication between strains to maintain control, something which is not guaranteed under non-well-mixed conditions. As such, these methods are of limited utility in consortia applications with poorly mixed environments e.g. industrial scale bioreactors or soil. Here, inspired by microbial phase variation dynamics, we introduce an alternative, communication-free approach in which a set of genetically identical cells switch stochastically between distinct phenotypes. In this scheme, the population composition is dynamically stable and determined by the rates of transitions between states. Mathematical modeling indicates that this approach can stabilize consortia. Experimentally, we used reversible DNA inversions catalyzed by serine recombinases to implement a dynamic consortium. We then characterized the dynamic properties of the consortium at the single cell and bulk levels, and demonstrated control in 2- and 3-state consortia. These results provide a composition control approach that does not rely on cell to cell communication, providing a foundation for deployment of engineered consortia in complex, and sometimes non-mixed, environments such as industrial scale bioreactors or the human gut.

synthetic biology↗

bioRxiv2025

Genome-wide chromatin recording resolves dynamic cell state changes

Understanding how the chromatin state of a cell influences its future behavior is a major challenge throughout biology. However, most chromatin profiling methods are limited to endpoint assays. Here, we present LagTag, a method for recovery of earlier and endpoint chromatin states in the same mammalian cells. In this approach, transient expression of bacterial adenine methyltransferase fusions records the DNA binding profiles of chromatin-associated proteins of interest at earlier timepoints. Subsequent tagmentation and sequencing recovers the earlier chromatin profile from adenine methylation profiles, alongside endpoint profiles of endogenous chromatin-associated proteins. We verified that LagTag profiles aligned with those from established methods in mouse and human cells. We then applied LagTag to record and recover dynamic chromatin state transitions during mouse embryonic stem cell differentiation, capturing transcriptional signatures from pre- and post-differentiation timepoints within the same cell population. LagTag thus provides a foundation for temporally resolved chromatin profiling.

genomics↗

bioRxiv2025

Pathway Sculptor for Compact and Versatile Combinatorial Genetic Perturbation

The Transforming Growth Factor beta (TGF-{beta}) superfamily, like other biological pathways, relies on families of co-expressed, partially redundant protein components, such as receptor subunits. The inability to systematically modulate multi-gene component expression profiles has made it difficult to understand how components and sets of components collectively process information. To overcome this, we developed Pathway Sculptor, a dCas12a-based epigenetic editing system that achieves simultaneous same-cell knockdown of at least twelve target genes. Programming TGF-{beta} receptor profiles, by knocking down different receptor subsets, revealed functional interactions between the canonical BMP and TGF-{beta} pathway branches. Unexpectedly, signaling within each branch depended on receptors in the opposite branch. Further, different receptor subsets played distinct roles: ACVR-class receptors modulated signaling magnitude, whereas BMPRs and TGFBRs discriminated among ligand variants. These results show how the two branches of the TGF-{beta} superfamily collaboratively process signals, and establish Pathway Sculptor as a general platform for high-order combinatorial perturbation.

synthetic biology↗

bioRxiv2025

Engineered protein circuits for cancer therapy

A central challenge in cancer therapy is selectively killing cancer cells while minimizing resistance. Here, we engineer modular protease-based protein circuits that sense mutant RAS, the most frequently mutated oncogene in cancer, and conditionally activate cell death. Delivered transiently as mRNA in lipid nanoparticles (LNPs), circuits selectively eliminated RAS-mutant cancer cells in culture and suppressed aggressive, multifocal RAS-driven liver tumors. Compared to RAS inhibitors, circuits killed cancer cells independently of oncogene addiction, achieved potent cytotoxicity rather than cytostasis, and functioned at low RAS occupancy through catalysis rather than stoichiometric inhibition. Critically, circuits acquired minimal to no resistance under prolonged selection, while remaining potent against prevalent drug-resistance mechanisms including RAS amplification and bypass signaling. Together, these results establish design principles for engineering therapeutic protein circuits and highlight their potential to overcome longstanding limitations of existing therapeutic modalities.

synthetic biology↗

bioRxiv2024

Cellular and molecular networks of intercellular signaling in bone marrow hematopoiesis

Hematopoietic stem and progenitor cells (HSPCs) rely on intercellular signaling to maintain and adjust their production of blood and immune cells. This process occurs in the semi-fluidic bone marrow, hosting dozens of cell types that constantly migrate and interact. To elucidate the dynamic network of cell-cell interaction and signaling transduction underlying hematopoiesis, we developed an algorithm to measure Cell-cell Spatial Interaction Probability (CellSIP) by integrating data on ligand and receptor expression, cell type abundance, and cellular spatial positioning. Using new and published mouse datasets, we validated CellSIP and uncovered signaling transductions indicating feedback mechanisms underlying hematopoiesis. Moreover, we identified significant correlations between signaling pathways across individual HSPCs at the same hematopoiesis stage. These pathway correlations illuminate the organization of cellular and signaling networks underlying hematopoiesis, revealing new regulators through their associations with established ones. The signaling quantification and correlation data are available through the Hematopoiesis Intercellular Signaling Explorer (HISE).

bioinformatics↗

bioRxiv2024

Synthetic dosage-compensating miRNA circuits for quantitative gene therapy

A longstanding challenge in gene therapy is expressing a dosage-sensitive gene within a tight therapeutic window. For example, loss of MECP2 function causes Rett syndrome, while its duplication causes MECP2 duplication syndrome. Viral gene delivery methods generate variable numbers of gene copies in individual cells, creating a need for gene dosage-invariant expression systems. Here, we introduce a compact miRNA-based, incoherent feed-forward loop circuit that achieves precise control of Mecp2 expression in cells and brains, and improves outcomes in an AAV-based mouse model of Rett syndrome gene therapy. Single molecule analysis of endogenous and ectopic Mecp2 mRNA revealed precise, sustained expression across a broad range of gene dosages. Delivered systemically in a brain-targeting AAV capsid, the circuit strongly suppressed Rett behavioral symptoms for over 24 weeks, outperforming an unregulated gene therapy. These results demonstrate that synthetic miRNA-based regulatory circuits can enable precise in vivo expression to improve the safety and efficacy of gene therapy. One sentence description: A synthetic miRNA-based incoherent feed-forward loop circuit embedded in a gene delivery vector overcomes the challenge of overexpression toxicity in a mouse model of Rett syndrome gene therapy.

synthetic biology↗

bioRxiv2024

miRNA circuit modules for precise, tunable control of gene expression

Accurate control of transgene expression is important for research and therapy but challenging to achieve in most settings. miRNA-based regulatory circuits can be incorporated within transgenes for improved control. However, the design principles, performance limits, and applications of these circuits in research and biotechnology have not been systematically determined. Here, combining modeling and experiments, we introduce miRNA-based circuit modules, termed DIMMERs, that establish precise, tunable control of transgene expression across diverse cell types to facilitate imaging, editing, and gene therapy. The circuits use multivalent miRNA regulatory interactions to achieve nearly uniform, tunable, protein expression over two orders of magnitude variation in gene dosage. They function across diverse cell types, and can be multiplexed for independent regulation of multiple genes. DIMMERs reduce off-target CRISPR base editing, improve single-molecule imaging, and allow live tracking of AAV-delivered transgene expression in mouse cortical neurons. DIMMERs thus enable accurate regulation for research and biotechnology applications.

synthetic biology↗

bioRxiv2024

Simultaneous protein and RNA analysis in single extracellular vesicles, including viruses: SPIRFISH

Interest in using nanoparticles for delivery of therapeutic RNA has been steadily growing, provoking a need to precisely understand their structure and contents. Single-particle and single-molecule analysis techniques provide snapshots of single biological nanoparticles, including viruses, liposomes, and extracellular vesicles (EVs). While existing methods primarily focus on protein detection, RNA delivery is becoming increasingly prevalent. A method to simultaneously detect protein and internal RNA in the same particle would reveal variability in size, structure, and RNA packaging efficiency, enabling optimization of nanoparticle delivery. Here, we introduce SPIRFISH, a high-throughput method for single-particle protein and RNA analysis, combining single particle interferometric reflectance imaging sensor (SP-IRIS) with single-molecule fluorescence in-situ hybridization (smFISH). Using SPIRFISH, we detect HIV-1 envelope protein and genomic RNA within single infectious virions, allowing resolution against EV background and noninfectious virions. We further show that SPIRFISH can be used to detect specific RNA within EVs. SPIRFISH should enable single particle analysis of a broad class of RNA-containing nanoparticles. Teaser: A new single particle analysis technique simultaneously detects specific RNA and protein in biological nanoparticles.

molecular biology↗

bioRxiv2024

Reconstructing cell histories in space with image-readable base editor recording

Knowing the ancestral states and lineage relationships of individual cells could unravel the dynamic programs underlying development. Engineering cells to actively record information within their own genomic DNA could reveal these histories, but existing recording systems have limited information capacity or disrupt spatial context. Here, we introduce baseMEMOIR, which combines base editing, sequential hybridization imaging, and Bayesian inference to allow reconstruction of high-resolution cell lineage trees and cell state dynamics while preserving spatial organization. BaseMEMOIR stochastically and irreversibly edits engineered dinucleotides to one of three alternative image-readable states. By genomically integrating arrays of editable dinucleotides, we constructed an embryonic stem cell line with 792 bits of recordable, image-readable memory, a 50-fold increase over the state of the art. Simulations showed that this memory size was sufficient for accurate reconstruction of deep lineage trees. Experimentally, baseMEMOIR allowed precise reconstruction of lineage trees 6 or more generations deep in embryonic stem cell colonies. Further, it also allowed inference of ancestral cell states and their quantitative cell state transition rates, all from endpoint images. baseMEMOIR thus provides a scalable framework for reconstructing single cell histories in spatially organized multicellular systems.

synthetic biology↗

bioRxiv2023

Diversity in Notch ligand-receptor signaling interactions

The Notch signaling pathway uses families of ligands and receptors to transmit signals to nearby cells. These components are expressed in diverse combinations in different cell types, interact in a many-to-many fashion, both within the same cell (in cis) and between cells (in trans), and their interactions are modulated by Fringe glycosyltransferases. A fundamental question is how the strength of Notch signaling depends on which pathway components are expressed, at what levels, and in which cells. Here, we used a quantitative, bottom-up, cell-based approach to systematically characterize trans-activation, cis-inhibition, and cis-activation signaling efficiencies across a range of ligand and Fringe expression levels in two mammalian cell types. Each ligand (Dll1, Dll4, Jag1, and Jag2) and receptor variant (Notch1 and Notch2) analyzed here exhibited a unique profile of interactions, Fringe-dependence, and signaling outcomes. All four ligands were able to bind receptors in cis and in trans, and all ligands trans-activated both receptors, although Jag1-Notch1 signaling was substantially weaker than other ligand-receptor combinations. Cis-interactions were predominantly inhibitory, with the exception of the Dll1-and Dll4-Notch2 pairs, which exhibited cis-activation stronger than trans-activation. Lfng strengthened Delta-mediated trans-activation and weakened Jagged-mediated trans-activation for both receptors. Finally, cis-ligands showed diverse cis-inhibition strengths, which depended on the identity of the trans-ligand as well as the receptor. The map of receptor-ligand-Fringe interaction outcomes revealed here should help guide rational perturbation and control of the Notch pathway.

systems biology↗

bioRxiv2022

Combinatorial expression motifs in signaling pathways

Cell-cell signaling pathways comprise sets of variant receptors that are expressed in different combinations in different cell types. This architecture allows one pathway to be used in a variety of configurations, which could provide distinct functional capabilities, such as responding to different ligand variants. While individual pathways have been well-studied, we have lacked a comprehensive understanding of what receptor combinations are expressed and how they are distributed across cell types. Here, combining data from multiple single-cell gene expression atlases, we analyzed the expression profiles of core signaling pathways, including TGF-{beta}, Notch, Wnt, and Eph-ephrin, as well as non-signaling pathways. In many pathways, a limited set of receptor expression profiles are used recurrently in many distinct cell types. While some recurrent profiles are restricted to groups of closely related cells, others, which we term pathway expression motifs, reappear in distantly related cell types spanning diverse tissues and organs. Motif usage was generally uncorrelated between pathways, remained stable in a given cell type during aging, but could change in sudden punctuated transitions during development. These results suggest a mosaic view of pathway usage, in which the same core pathways can be active in many or most cell types, but operate in one of a handful of distinct modes.

genomics↗

bioRxiv2022

Periodic spatial patterning with a single morphogen

Multicellular development employs periodic spatial patterning to generate repetitive structures such as digits, vertebrae, and teeth. Turing patterning has long provided a key paradigm for understanding such systems. The simplest Turing systems are believed to require at least two signals, or morphogens, that diffuse and react to spontaneously generate periodic patterns. Here, using mathematical modeling, we show that a minimal circuit comprising an intracellular positive feedback loop and a single diffusible morphogen is sufficient to generate stable, long-range spatially periodic cellular patterns. The model considers cells as discrete entities as a key feature, and incorporates transient boundary conditions. Linear stability analysis reveals that this single-morphogen Turing circuit can support a broad range of spatial wavelengths, including fine-grain patterns similar to those generated by classic lateral inhibition systems. Further, signals emanating from a boundary can initiate and stabilize propagating modes with a well-defined spatial wavelength. Once formed, patterns are self-sustaining and robust to noise. Finally, while noise can disrupt patterning in pre-patterned regions, its disruptive effect can be overcome by a bistable intracellular circuit loop, or by considering patterning in the context of growing tissue. Together, these results show that a single morphogen can be sufficient for robust spatial pattern formation, and should provide a foundation for engineering pattern formation in the emerging field of synthetic developmental biology.

synthetic biology↗