Biology subjects

Sutton, S.

Publications and source records attributed to Sutton, S..

4 recordsLinked to original sources

bioRxiv2026

Agrochemical-responsive gene expression control systems for modulating plant development and metabolism

Precise temporal control of gene expression is critical for studying plant biology and engineering complex crop traits. Current systems enable chemically inducible regulation but rely on costly or agriculturally impractical inducers and lack the flexibility needed to regulate combinations of native loci and transgenes. In this work, we elucidate the design rules for control systems, based on Cas9 and Cre recombinase fused to the ecdysone receptor (EcR), which respond to a widely used agrochemical methoxyfenozide (MF). First, we validated the function of both circuits in transient assays and explored how transduction properties can be modulated by engineering nuclear trafficking dynamics. We next characterized both the Cas9-based and recombinase-based systems by using them to regulate fluorescent reporters in transgenic Arabidopsis thaliana plants. Here, we demonstrate systemic activation following root application of MF, validating the use of an agriculturally compatible inducer for whole-plant gene regulation. Finally, we validated the utility of the inducible Cas-based SynTF system to regulate multigene pathways and control both metabolic flux and developmental circuits. Together, these results establish design principles for agrochemical-inducible control systems and demonstrate their utility for temporally regulating plant phenotypes. These synthetic circuits provide a versatile framework for engineering complex traits using an agriculturally compatible inducer.

synthetic biology↗

bioRxiv2025

Molecular Bonsai: Elucidating the design principles for engineering plant organ size

Enhancements to crop morphology, such as the semi-dwarfing that helped drive the green revolution, are often driven by changes in gene expression. These are challenging to translate across species, which slows the rate of crop improvement. Synthetic transcription factors (SynTFs) offer a rapid alternative to generate targeted alterations to gene expression. However, the complexity of developmental pathways makes it unclear how to best apply them to predictably engineer morphology. In this work, we explore whether mathematical modeling can guide SynTF-based gene expression modulation to help elucidate the design principles of engineering organ size. We targeted genes in the phytohormone, gibberellin (GA), signaling pathway, which is a central regulator of cell expansion. We demonstrate that modulation of GA signaling gene expression can generate consistent dwarfing across tissues and environments in Arabidopsis thaliana, and that the degree of dwarfing is dependent on the strength of regulation, as predicted by modeling. We further validate the models predictive power by demonstrating its capacity to predict the qualitative impacts of different regulatory architectures for engineering organ size. Additionally, we develop expression parameterized models to quantitatively predict organ size and elucidate how temperature will affect growth. Finally, we show that these insights can be generalized for engineering organ size in tomato (Solanum lycopersicum). This work creates a framework for predictable engineering of an agriculturally important trait across tissues and plant species. It also serves as a proof-of-concept for how mathematical models can guide SynTF-based alterations in gene expression to enable bottom-up design of plant phenotypes. Significance StatementWhile traditional breeding approaches have identified mutations that enhance crop performance via targeted gene expression changes, these are not easily translated across varieties and species. Synthetic transcription factors (SynTFs) offer an avenue to generate such changes de novo, but the optimal regulatory architectures necessary to generate desired phenotypes remain unclear. We demonstrate how mathematical models can be used to guide SynTF deployment and elucidate the design principles for engineering organ size, an agriculturally important trait, via modulation of gibberellin signaling. In addition to revealing regulatory architectures that can consistently increase or decrease organ size across a range of tissues, environments, and plant species, this work demonstrates how model-guided SynTF-based modulation of gene dosage can be used to predictably engineer plants.

synthetic biology↗

bioRxiv2020

Mono- and bi-allelic protein truncating variants in alpha-actinin 2 cause cardiomyopathy through distinct mechanisms

Alpha-actinin 2 (ACTN2) anchors actin within cardiac sarcomeres. The mechanisms linking ACTN2 mutations to myocardial disease phenotypes are unknown. Here, we characterize patients with novel ACTN2 mutations to reveal insights into the physiological function of ACTN2. Patient-derived iPSC-cardiomyocytes harboring ACTN2 protein-truncating variants were hypertrophic, displayed sarcomeric structural disarray, impaired contractility, and aberrant Ca2+-signaling. In heterozygous indel cells, the truncated protein incorporates into cardiac sarcomeres, leading to aberrant Z-disc structure. In homozygous stop-gain cells, affinity-purification mass spectrometry reveals an intricate ACTN2 interactome with sarcomere and sarcolemma-associated proteins. Loss of the C-terminus of ACTN2 disrupts interaction with ACTN1 and GJA1, two sarcolemma-associated proteins, that may lead to the clinical arrhythmic and relaxation defects. The causality of the stop-gain mutation was verified using CRISPR-Cas9 gene editing. Together, these data advance our understanding of the role of ACTN2 in the human heart and establish recessive inheritance of ACTN2 truncation as causative of disease.

genetics↗

bioRxiv2019

Development and clinical validation of a targeted RNAseq panel (Fusion-STAMP) for diagnostic and predictive gene fusion detection in solid tumors

RNA sequencing is emerging as a powerful technique to detect a diverse array of fusions in human neoplasia, but few clinically validated assays have been described to date. We designed and validated a hybrid-capture RNAseq assay for FFPE tissue (Fusion-STAMP). It fully targets the transcript isoforms of 43 genes selected for their known impact as actionable targets of existing and emerging anti-cancer therapies (especially in lung adenocarcinomas), prognostic features, and/or utility as diagnostic cancer biomarkers (especially in sarcomas). 57 fusion results across 34 samples were evaluated. Fusion-STAMP demonstrated high overall accuracy with 98% sensitivity and 94% specificity for fusion detection. There was high intra- and inter-run reproducibility. Detection was sensitive to approximately 10% tumor, though this is expected to be impacted by fusion transcript expression levels, hybrid capture efficiency, and RNA quality. Challenges of clinically validating RNA sequencing for fusion detection include a low average RNA quality in FFPE specimens, and variable RNA total content and expression profile per cell. These challenges contribute to highly variable on-target rates, total read pairs, and total mapped read pairs. False positive results may be caused by intergenic splicing, barcode hopping / index hopping, or misalignment. Despite this, Fusion-STAMP demonstrates high overall performance metrics for qualitative fusion detection and is expected to provide clinical utility in identifying actionable fusions.

genomics↗