Biology subjects

Schaffter, S. W.

Publications and source records attributed to Schaffter, S. W..

9 recordsLinked to original sources

bioRxiv2026

Towards interoperable modeling of toehold-mediated strand exchange circuits across DNA nanotechnology and engineering biology

Originally developed for DNA nanotechnology, toehold-mediated strand exchange (TMSE) circuits are gaining traction in synthetic biology due to their high programmability, seamless integration with biological components, and robust operation across diverse environments and cell types. However, while forward-engineering in synthetic biology has benefited from automated genetic circuit modeling pipelines, there is currently a lack of accessible, automated tools for the mechanistic modeling of TMSE circuits integrated with these systems, hindering the development of new biotechnologies. The TMSE-BioCRNpyler Library allows TMSE molecules to be transcribed RNAs or fixed-concentration nucleic acids while leveraging existing BioCRNpyler features, such as upstream transcription regulation and downstream gene regulation. We demonstrate this librarys applicability by modeling published applications of TMSE circuits spanning a wide range of applications, including simple in vitro reactions, cell-free biosensors, and in vivo microbial and mammalian systems. Additionally, we validated that models compiled using the TMSE-BioCRNpyler Library produced results with < 0.2 % relative error compared to multiple models of TMSE previously developed in the literature. Finally, to streamline interoperability with existing models, we developed txt2biocrnpyler. This accompanying tool converts chemical reaction networks from the literature into a BioCRNpyler-ready source script and a Systems Biology Markup Language XML file -- a standard data format for sharing and simulating biological models. The TMSE-BioCRNpyler Library serves as a powerful new resource for the rational, automated design of molecular information processing systems.

bioengineering↗

bioRxiv2025

Cell-free systems enable mechanistic characterization of genetically encoded RNA strand exchange circuits for programmable protein expression

Nucleic acid circuits are powerful tools for programming biology, but the design principles for operating these circuits in complex cellular environments remain poorly understood compared to simple in vitro settings. Cell-free expression systems (CFES) are uniquely suited to address this challenge, as they can integrate measurements ideal for either in vitro or in cyto settings. Further, because CFES are open systems, they enable a level of control over component concentration unattainable in cells. Here, we use cell-free systems to characterize genetically encoded RNA circuits that operate via toehold-mediated strand exchange (TMSE). These circuits have been extensively characterized in vitro and were recently deployed as translational riboregulators in E. coli, revealing key differences between the two environments. By systematically modulating the design parameters of these RNA circuits in both purified protein and lysate-based CFES, we elucidate the mechanisms linking TMSE to protein expression. Further, we combine measurements and alterations in CFES composition that are infeasible in cells to investigate interactions between cellular components and RNA circuit components, identifying a potential interaction with ribosomes that informs circuit design. Our results establish a unified set of principles for designing and operating genetically encoded TMSE circuits across in vitro, CFE, and bacterial environments, which should catalyze the widespread adoption of this platform for new applications in molecular programming, synthetic biology, and biotechnology.

bioengineering↗

bioRxiv2025

Genetically encoded RNA strand exchange circuits for programmable protein expression and computation in cells

Programmable cellular information processing could advance biomanufacturing of chemicals and medicine, and enable smart, living therapeutics and diagnostics1,2. Nucleic acids circuits based on toehold mediated strand exchange (TMSE) show tremendous potential for cellular programming due to their scalable, composable, and biocompatible parts3-6. However, these circuits are constrained primarily to in vitro applications because genetically encoding them is challenging and the principles of TMSE in cells remain unknown. Here we show the first demonstration of genetically encoded RNA strand exchange circuits, designed analogously to state-of-the-art TMSE circuits, in living cells. To elucidate the design principles of TMSE in cells, we develop toehold exchange riboregulators, which convert TMSE to protein expression, enabling precise control of protein translation rate. We find many of the design principles and parts used for TMSE in vitro transfer to Escherichia coli, allowing construction of multi-layer cascades and logic elements. We also identify caveats where strand exchange in cells differ substantially from cell-free systems, even in lysate from the same bacterial strain7, suggesting active cellular processes are involved. Our results further highlight bounds on strand exchange circuit architectures feasible in cells. We anticipate this study will lay the groundwork for developing advanced cellular circuits, bringing nucleic acid computing from the test tube to the cell8-10 and enabling new applications by connecting TMSE to gene expression. More broadly, our results have implications for RNA:RNA interactions and gene regulation in bacteria and provide a synthetic system for exploring such phenomena.

synthetic biology↗

bioRxiv2025

Experimental Evaluation of AI-Driven Protein Design Risks Using Safe Biological Proxies

Advances in machine learning are providing leaps forward for beneficial applications of protein engineering, while also raising concerns about biosecurity. Recently, Wittmann et al. described an in silico pipeline of generative AI tools to reformulate sequences of concern (SOCs) as synthetic homologs that may evade detection by biosecurity screening software (BSS) used by nucleic acid synthesis providers. Experimental testing of synthetic homologs is required to ascertain the true severity of this vulnerability. We present a generalizable framework to assess biosecurity risk consisting of testing, evaluation, validation, and verification (TEVV) of AI-assisted protein design (AIPD). We determine that common AIPD models in use at the time this study was initiated (early 2024) are not yet powerful enough to reliably rewrite the sequence of a given protein, while both maintaining activity and evading detection by BSS.

synthetic biology↗

bioRxiv2025

Comparative Transcriptomic Analysis of Perfluoroalkyl Substances-Induced Responses of Exponential and Stationary Phase Escherichia coli

Per- and polyfluoroalkyl substances (PFAS) are highly stable chemical contaminants of emerging concern for human and environmental health due to their non-natural chemistry, widespread use, and environmental persistence. Despite conventional metrology, mitigation strategies, and removal technologies, the complexity of this growing problem necessitates the need for alternative approaches to tackle the immense challenges associated with complex environmental PFAS contamination. Recently, biology has emerged as an alternative approach to detect and mitigate PFAS and understand the molecular-level responses of living organisms, including microorganisms, to these compounds. However, further study is needed to understand how microorganisms in different environments and growth phases respond to PFAS. In this study, we performed RNA sequencing at mid-exponential, early stationary phase, and late stationary phase of bacterial growth to determine the global transcriptional response of a model chassis, Escherichia coli MG1655, induced by two PFAS, perfluorooctanoic acid (PFOA) and perfluorododecanoic acid (PFDoA), and equivalent non-fluorinated carboxylic acids (NFCA), octanoic acid and dodecanoic acid. Differential gene expression analysis revealed PFOA and PFDoA induced distinct changes in gene expression throughout cultivation. Specifically, we identified significant changes in expression of the formate regulon and sulfate assimilation at mid-exponential phase and ferrous iron transport, central metabolism, the molecular chaperone network, and motility processes during stationary phase. Importantly, many of these changes are not induced by NFCAs. In summary, we found PFAS induced a system-level change in gene expression, and our results expand the understanding of bacterial-PFAS interactions that could enable the development of future real-time environmental monitoring and mitigation technologies. ImportanceThe prevalence and persistence of PFAS in the environment is a growing area of concern. However, little is understood of the impacts of PFAS on the environment, particularly impacts on microorganisms that play pivotal roles in nearly every ecosystem. Thus, comprehensive measurements that provide systems-level insight into how microorganisms respond and adapt to PFAS in the environment are paramount. Here, we use RNA sequencing to study the global transcriptional response of E. coli MG1655 to two PFAS and non-fluorinated equivalent compounds across growth phases. We find that PFAS induce system-level changes in metabolic, transport, and gene regulatory pathways, providing insight into how these non-natural chemicals interact with a model bacterium. Additionally, the transcriptomic dataset associated with this work provides the community with PFSA-specific gene expression patterns and possible PFAS degradation pathways for the development of future whole-cell biosensors and mitigation efforts.

genomics↗

bioRxiv2024

Prevention of ribozyme catalysis through cDNA synthesis enables accurate RT-qPCR measurements of context-dependent ribozyme activity

Self-cleaving ribozymes are important tools in synthetic biology, biomanufacturing, and nucleic acid therapeutics. These broad applications deploy ribozymes in many genetic and environmental contexts, which can influence activity. Thus, accurate measurements of ribozyme activity across diverse contexts are crucial for validating new ribozyme sequences and ribozyme-based biotechnologies. Ribozyme activity measurements that rely on RNA extraction, such as RNA sequencing or reverse transcription-quantitative polymerase chain reaction (RT-qPCR), are generalizable to most applications and have high sensitivity. However, the activity measurement is indirect, taking place after RNA is isolated from the environment of interest and copied to DNA. So these measurements may not accurately reflect the activity in the original context. Here we develop and validate an RT-qPCR method for measuring context-dependent ribozyme activity using a set of self-cleaving RNAs for which context-dependent ribozyme cleavage is known in vitro. We find that RNA extraction and reverse transcription conditions can induce substantial ribozyme cleavage resulting in incorrect activity measurements with RT-qPCR. To restore the accuracy of the RT-qPCR measurements, we introduce an oligonucleotide into the sample preparation workflow that inhibits ribozyme activity. We then apply our method to measure ribozyme cleavage of RNAs produced in Escherichia coli (E. coli). These results have broad implications for many ribozyme measurements and technologies.

synthetic biology↗

bioRxiv2023

Plug-and-play protein biosensors using aptamer-regulated in vitro transcription

Molecular biosensors that accurately measure protein concentrations without external equipment are critical for solving numerous problems in diagnostics and therapeutics. Modularly transducing the binding of protein antibodies, protein switches or aptamers into a useful output remains challenging. Here, we develop a biosensing platform based on aptamer-regulated transcription in which aptamers integrated into transcription templates serve as inputs to molecular circuits that can be programmed to a produce a variety of responses. We modularly design molecular biosensors using this platform by swapping aptamer domains for specific proteins and downstream domains that encode different RNA transcripts. By coupling aptamer-regulated transcription with diverse transduction circuits, we rapidly construct analog protein biosensors or digital protein biosensors with detection ranges that can be tuned over two orders of magnitude. Aptamer-regulated transcription is a straightforward and inexpensive approach for constructing programmable protein biosensors suitable for diverse research and diagnostic applications. One sentence summaryWe develop a modular platform for biosensing across a wide dynamic range using aptamer-regulated transcription to detect different proteins and molecular circuits to process the RNA transcript outputs.

bioengineering↗

bioRxiv2023

Design approaches to expand the toolkit for building cotranscriptionally encoded RNA strand displacement circuits

Cotranscriptionally encoded RNA strand displacement (ctRSD) circuits are an emerging tool for programmable molecular computation with potential applications spanning in vitro diagnostics to continuous computation inside living cells. In ctRSD circuits, RNA strand displacement components are continuously produced together via transcription. These RNA components can be rationally programmed through base pairing interactions to execute logic and signaling cascades. However, the small number of ctRSD components characterized to date limits circuit size and capabilities. Here, we characterize 220 ctRSD gate sequences, exploring different input, output, and toehold sequences and changes to other design parameters, including domain lengths, ribozyme sequences, and the order in which gate strands are transcribed. This characterization provides a library of sequence domains for engineering ctRSD components, i.e., a toolkit, enabling circuits with up to four-fold more inputs than previously possible. We also identify specific failure modes and systematically develop design approaches that reduce the likelihood of failure across different gate sequences. Lastly, we show ctRSD gate design is robust to changes in transcriptional encoding, opening a broad design space for applications in more complex environments. Together, these results deliver an expanded toolkit and design approaches for building ctRSD circuits that will dramatically extend capabilities and potential applications.

synthetic biology↗

bioRxiv2021

Co-transcriptional RNA strand displacement circuits

Engineered molecular circuits that process information in biological systems could address emerging human health and biomanufacturing needs. However, such circuits can be difficult to rationally design and scale. DNA-based strand displacement reactions have demonstrated the largest and most computationally powerful molecular circuits to date but are limited in biological systems due to the difficulty in genetically encoding components. Here, we develop scalable co-transcriptional RNA strand displacement (ctRSD) circuits that are rationally programmed via base pairing interactions. ctRSD addresses the limitations of DNA-based strand displacement circuits by isothermally producing circuit components via transcription. We demonstrate the programmability of ctRSD in vitro by implementing logic and amplification elements, and multi-layer signaling cascades. Further, we show ctRSD kinetics are accurately predicted by a simple model of coupled transcription and strand displacement, enabling model-driven design. We envision ctRSD will enable rational design of powerful molecular circuits that operate in biological systems, including living cells.

synthetic biology↗