Biology subjects

Dray, K. E.

Publications and source records attributed to Dray, K. E..

3 recordsLinked to original sources

bioRxiv2025

GCAD: a Computational Framework for Mammalian Genetic Program Computer-Aided Design

Genetic programs can direct living systems to perform diverse, pre-specified functions. As the library of parts available for building such programs continues to expand, computation-guided design is increasingly helpful and necessary. Predictive models aid the challenging design process, but iterative simulation and experimentation are intractable for complex functions. Computer-aided design accelerates this process, but existing tools do not yet capture the behavior of mammalian-specific parts and population-level effects needed for mammalian synthetic biologists. To address these needs, we developed a framework for mammalian genetic program computer-aided design. Starting with a user-defined design specification to quantify circuit performance, the framework uses a genetic algorithm to search through possible designs. Circuit space is defined by a library of experimentally characterized parts and dynamical systems models for gene expression in a heterogeneous cell population. We developed this genetic algorithm using a directed graph-based formulation with biologically constrained rules to explore regulatory connections and parts. We evaluated the framework for design problems of varying complexity, including programs we describe as an amplifier, signal conditioner, and pulse generator, demonstrating that the algorithm can successfully find optimal circuit designs. Finally, we experimentally evaluated selected circuits, demonstrating the path from a predicted circuit design to experimental testing and highlighting the importance of characterization for enabling predictive design. Overall, this framework establishes general approaches that can be refined and expanded, accelerating the design and implementation of mammalian genetic programs.

synthetic biology↗

bioRxiv2024

Engineered Feedback Employing Natural Hypoxia-Responsive Factors Enhances Synthetic Hypoxia Biosensors

DNA-based hypoxia biosensors conditionally express a gene of interest when a cell is in a state of inadequate oxygen supply, which is a feature of several acute and chronic diseases. These biosensors can be deployed in engineered cells to study or treat disease. Although the central mediators of hypoxia responsiveness have been characterized, the dynamics of this response are generally less understood, and there is no general approach to modulate hypoxia biosensors to tune their performance to meet application-specific needs. To address the need for high-performing hypoxia biosensors, we investigated strategies to enhance biosensor performance by identifying minimal promoter choices and positive feedback circuits that both achieved low background and amplified hypoxia-induced gene expression. To generate insight into the mechanisms by which feedback drives differential performance, we developed an explanatory mathematical model. Our analysis suggests a previously unreported dual regulatory mechanism that was necessary to explain the full set of experimental observations and that provides new insights into regulatory dynamics in chronic hypoxia. This study exemplifies the potential of using synthetic gene circuits to perturb natural systems in a manner that uniquely enables the elucidation of novel facets of natural regulation.

synthetic biology↗

bioRxiv2024

Developing, characterizing and modelingCRISPR-based point-of-use pathogen diagnostics

Recent years have seen intense interest in the development of point-of-care nucleic acid diagnostic technologies to address the scaling limitations of laboratory-based approaches. Chief among these are combinations of isothermal amplification approaches with CRISPR-based detection and readouts of target products. Here, we contribute to the growing body of rapid, programmable point-of-care pathogen tests by developing and optimizing a one-pot NASBA-Cas13a nucleic acid detection assay. This test uses the isothermal amplification technique NASBA to amplify target viral nucleic acids, followed by Cas13a-based detection of amplified sequences. We first demonstrate an in-house formulation of NASBA that enables optimization of individual NASBA components. We then present design rules for NASBA primer sets and LbuCas13a guide RNAs for fast and sensitive detection of SARS-CoV-2 viral RNA fragments, resulting in 20 - 200 aM sensitivity without any specialized equipment. Finally, we explore the combination of high-throughput assay condition screening with mechanistic ordinary differential equation modeling of the reaction scheme to gain a deeper understanding of the NASBA-Cas13a system. This work presents a framework for developing a mechanistic understanding of reaction performance and optimization that uses both experiments and modeling, which we anticipate will be useful in developing future nucleic acid detection technologies.

synthetic biology↗