Biology subjects

Linton, J. M.

Publications and source records attributed to Linton, J. M..

6 recordsLinked to original sources

bioRxiv2026

Synthetic reaction-diffusion patterning in mammalian cells

During development, periodic patterns arise through reaction-diffusion (RD) circuits involving local activation and long-range inhibition (LALI). Natural systems are complex, typically entangling regulation and transport in the same morphogens. It remains unclear what minimal circuits are sufficient for LALI patterning in mammalian cells, and whether they can be implemented in a modular fashion, allowing independent control of regulation and transport. Here, we designed synthetic LALI circuits using three natural and synthetic signaling systems, BMP, Activin, and the SNIPR pathway, and showed that they generate spatial patterns with distinct characteristic spatial scales. Model-guided design allowed flexible morphogen reassignment, with BMP4 acting as either short-range activator or long-range inhibitor. Gene expression noise degraded long-range order but preserved the dominant local spatial scale. Together, these results provide a modular, extensible synthetic framework for engineered patterning in mammalian cells.

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

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↗

bioRxiv2022

A synthetic protein-level neural network in mammalian cells

Artificial neural networks provide a powerful paradigm for information processing that has transformed diverse fields. Within living cells, genetically encoded synthetic molecular networks could, in principle, harness principles of neural computation to classify molecular signals. Here, we combine de novo designed protein heterodimers and engineered viral proteases to implement a synthetic protein circuit that performs winner-take-all neural network computation. This "perceptein" circuit includes modules that compute weighted sums of input protein concentrations through reversible binding interactions, and allow for self-activation and mutual inhibition of protein components using irreversible proteolytic cleavage reactions. Altogether, these interactions comprise a network of 310 chemical reactions stemming from 8 expressed protein species. The complete system achieves signal classification with tunable decision boundaries in mammalian cells. These results demonstrate how engineered protein-based networks can enable programmable signal classification in living cells. One-Sentence SummaryA synthetic protein circuit that performs winner-take-all neural network computation in mammalian cells

synthetic biology↗

bioRxiv2020

Ligand-receptor promiscuity enables cellular addressing

In multicellular organisms, secreted ligands selectively activate, or "address," specific target cell populations to control cell fate decision-making and other processes. Key cell-cell communication pathways use multiple promiscuously interacting ligands and receptors, provoking the question of how addressing specificity can emerge from molecular promiscuity. To investigate this issue, we developed a general mathematical modeling framework based on the bone morphogenetic protein (BMP) pathway architecture. We find that promiscuously interacting ligand-receptor systems allow a small number of ligands, acting in combinations, to address a larger number of individual cell types, each defined by its receptor expression profile. Promiscuous systems outperform seemingly more specific one-to-one signaling architectures in addressing capacity. Combinatorial addressing extends to groups of cell types, is robust to receptor expression noise, grows more powerful with increasing receptor multiplicity, and is maximized by specific biochemical parameter relationships. Together, these results identify fundamental design principles governing cell addressing by ligand combinations.

systems biology↗

bioRxiv2020

The context-dependent, combinatorial logic of BMP signaling

Cell-cell communication systems typically comprise families of ligand and receptor variants that function together in combinations. Pathway activation depends in a complex way on which ligands are present and what receptors are expressed by the signal-receiving cell. To understand the combinatorial logic of such a system, we systematically measured pairwise Bone Morphogenetic Protein (BMP) ligand interactions in cells with varying receptor expression. Ligands could be classified into equivalence groups based on their profile of positive and negative synergies with other ligands. These groups varied with receptor expression, explaining how ligands can functionally replace each other in one context but not another. Context-dependent combinatorial interactions could be explained by a biochemical model based on competitive formation of alternative signaling complexes with distinct activities. Together, these results provide insights into the roles of BMP combinations in developmental and therapeutic contexts and establish a framework for analyzing other combinatorial, context-dependent signaling systems.

systems biology↗