Biology subjects

Green, A. A.

Publications and source records attributed to Green, A. A..

12 recordsLinked to original sources

bioRxiv2026

Crowdsourced riboregulators reveal design principles for programmable RNA switching

RNA-based sensors offer powerful and programmable control of gene expression, yet our understanding of the structural principles that govern their potential design space remains incomplete. Here, we challenged a community of designers to generate novel riboregulators capable of activating translation in response to specific RNA targets. Participants submitted diverse sequence architectures, which were synthesized and evaluated in a cell-free transcription-translation system. Across 100 designs, community-generated riboregulators displayed wide variability in activation dynamics, fold change, and structural features, outperforming some canonical toehold-switch designs and achieving up to 80-fold activation. Structural ensemble analyses identified accessibility patterns near the ribosome binding site that distinguish high- from low-performing regulators, highlighting the central role of RBS sequestration and release in modulating expression. Together, we demonstrate community-driven design can expand the accessible structural space of riboregulators and uncover mechanistic features governing translational activation. Our findings establish quantitative links between RNA folding energetics and gene expression output, providing design principles for next-generation programmable RNA sensors.

synthetic biology↗

bioRxiv2026

Rapid Isothermal Detection of Heavy Metals via Transcription-Factor-Gated DNA Strand Synthesis

Conventional methods for monitoring toxic heavy metals typically require sophisticated laboratory instrumentation and leave a critical gap for rapid, on-site detection. Herein we present Transcription-factor-Occluded Nick Extension or TONE, a rapid, isothermal biosensing platform for heavy metal detection that exploits allosteric transcription factor (aTF) regulation to gate DNA strand-displacement amplification. In this approach, operator sequences modified with deoxyinosine (dI) substitutions are employed. When bound by an aTF, the dI sites are shielded from cleavage by Endonuclease V. Upon exposure to target heavy metals, the aTF dissociates, permitting the enzyme to nick the DNA and trigger a strand-displacement reaction. The amplified DNA is then detected via an instrument-free lateral flow assay, delivering a visual readout within 25 minutes at room temperature. We demonstrate the utility of TONE using the TetR aTF and further adapt the assay for copper and lead detection through the transcription factors CsoR and CadC, respectively, achieving detection limits as low as 40 nM and 80 nM, respectively. TONE offers a sensitive, low-cost, and field-deployable solution for environmental monitoring and other applications requiring rapid heavy metal analysis.

synthetic biology↗

bioRxiv2026

Bispecific Coiled-Coil Reporters Enable Rapid, Multiplexed Detection of Mycoplasma via Toehold Switch Sensors

Cell-free synthetic biology offers a rapid prototyping environment for molecular diagnostics, yet the utility of these systems is often limited by the slow kinetics and restricted multiplexing capabilities of traditional protein reporters. Here, we report the BINOCULAR (BIspecific Novel Orthogonal Coiled-coil-Using LAteral flow Reporter) system based on supramolecular coiled-coil peptide conjugates that dramatically accelerates signal generation and enables robust multiplexing in cell-free transcription-translation reactions. Using BINOCULARs as toehold switch outputs, we achieve visible readout times of less than 5 minutes in lateral flow assays, achieving a [≥]12-fold increase in speed compared to standard cell-free reporters like {beta}-galactosidase or fluorescent proteins. To demonstrate the utility of this platform, we integrated the bispecific reporters with loop-mediated isothermal amplification (LAMP) and a lateral flow assay for the detection of mycoplasma, a common adventitious agent in biomanufacturing. The integrated system demonstrates exceptional sensitivity, achieving a detection limit of 1 copy/{micro}L for Mycoplasma 16S rRNA and a mammalian internal control gene. Cell-free assay results are available within 5 minutes following a 20-minute amplification step, and we successfully achieved the simultaneous detection of three distinct targets in a single reaction. Crucially, the platform maintains reliable performance in complex matrices and after lyophilization, making it more accessible for point-of-use need. Our findings suggest that the modular BINOCULAR architecture can overcome current bottlenecks in cell-free sensing systems, providing a versatile and scalable framework for rapid, point-of-use screening across clinical and industrial applications.

synthetic biology↗

bioRxiv2026

Cell-type specific impact of opioid use disorder and HIV on the human forebrain and cerebellum

Opioid use disorder (OUD), which frequently co-occurs with HIV infection, causes long-term neurological disease, yet the epigenetic and transcriptomic effects of OUD and HIV on specific cell types and regions of the brain are poorly understood. To assess the cell-type specific impacts of OUD and HIV across the human brain, we measured single cell transcriptomes and epigenomes of 580,353 cells in the prefrontal cortex, amygdala and cerebellum of 44 donors. We cataloged over 750k candidate cis-regulatory elements (cCREs) and identified gene regulatory networks (GRNs) of transcription factor activity across 35 neuronal and non-neuronal cell types. We identified specific neuronal and glial populations whose cCREs were significantly enriched for genetic risk of addiction-related traits. In OUD donors, we found evidence for reduced metabolic function in neurons in the PFC and cerebellum as well as increased gene expression related to voltage-gated calcium channel activity in the cerebellum. Using a cerebellar organoid model, fentanyl treatment reduced metabolic activity while increasing neuronal activity. Across brain regions, HIV activated immune-related pathways in glial populations, while comorbid OUD and HIV exacerbated metabolic changes in cortical glial cells. Cerebellum-specific Bergmann glia, in addition to forebrain microglia and astrocytes, showed expansion of reactive state identity in HIV. These results highlight shared and specific changes to immune, synaptic, and metabolic processes in OUD and HIV across brain regions and reveal that cerebellar cell types are distinctly affected by opioid abuse.

genomics↗

bioRxiv2025

pH-responsive synthetic cells for controlled protein synthesis and release

Lipid membrane-bound synthetic cells provide programmable, cell-like compartments for on-demand biomolecule production. However, most cell-free gene expression systems in synthetic cells are regulated by user-imposed cues rather than signals associated with environmental or physiological states. Here, we present an acidity-transducing synthetic cell that converts external pH changes into nucleic acid information to drive in situ protein synthesis. The system integrates gramicidin A proton channels for pH sensing, triplex-forming single-stranded DNA (ssDNA) that releases a trigger ssDNA upon acidification, and a toehold switch RNA that activates translation in response to the released trigger ssDNA. This work further reveals that tuning the annealing length between the pH-responsive and trigger ssDNAs controls the trigger-release pH, which is critical for enabling acid-triggered protein synthesis. The synthetic cells retain their pH-responsive activity when embedded in alginate hydrogels, creating acidity-responsive materials that synthesize proteins in situ rather than release preloaded cargo. Cell-penetrating peptide tagging further enables selective protein release and target-specific binding. This work establishes a molecular transduction strategy for programming synthetic cell materials to sense environmentally relevant acidity and generate functional biomolecules on demand.

synthetic biology↗

bioRxiv2025

Automated Assembly of Programmable RNA-Based Sensors

Engineered programmable RNA sensors have been applied in low-cost diagnostics, endogenous RNA detection, and multi-input genetic circuits. However, designing, producing, and screening high-performance RNA sensors remains time consuming and labor intensive. Here, we present an automated plasmid assembly pipeline using liquid handling robotics to enable high-throughput construction of plasmids with arbitrary sequences. We compare automated and manual assembly methods using the NGS Hamilton Microlab STAR across two plasmid backbones to evaluate efficiency and reliability. As a proof of concept, we use this modular platform to construct 144 total plasmids encoding riboregulators targeting diverse viral targets along with their cognate trigger sequences. We further demonstrate that the assembled plasmids are functional in both bacterial and cell-free expression systems.

synthetic biology↗

bioRxiv2025

Toehold-VISTA: A machine learning approach to decipher programmable RNA sensor-target interactions

RNA-based biosensors have emerged as essential tools in synthetic biology and diagnostics, enabling precise and programmable responses to diverse RNA inputs. However, the time to design, produce, and screen high-performance RNA sensors remains a critical challenge. The fundamental rules governing RNA-RNA interactions--specifically the structure-function relationships that determine sensor performance--remain poorly understood. Here, we present a method enabling versatile in-silico RNA-targeting analysis (VISTA), a machine learning-guided framework for the rapid design of RNA sensors. VISTA integrates biophysical modeling of both sensor and target RNAs with a partial least squares discriminant analysis (PLS-DA) machine learning framework. Using high-throughput experimental measurements with sequence-structure feature extraction to train predictive models, we capture the key determinants of RNA sensor performance. We find that by using toehold switches as a model RNA sensor, Toehold-VISTA successfully designs RNA sensors with improved function against SARS-CoV-2 RNA. These findings establish a broadly applicable, target-aware design strategy for accelerating RNA sensor engineering across biotechnology and diagnostic applications. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/669990v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@1f33be7org.highwire.dtl.DTLVardef@1e1f523org.highwire.dtl.DTLVardef@1a4d914org.highwire.dtl.DTLVardef@1a7eb5c_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2025

A generalized and efficient approach for complete mRNA design improves translation, stability and specificity

End-to-end, machine-learning-based design of mRNA molecules offers a powerful means to tailor their properties for specific tasks. mRNA expression level, immunogenicity, tissue specificity, stability, and localization strongly depend on sequence, providing a rich set of properties amenable to optimization. Despite this potential, the components of mRNA are governed by distinct grammatical and functional rules that hinder a unified approach to complete mRNA design. While machine learning and generative AI techniques can excel on individual sequence design tasks, out-of-distribution design, where the biological objective shifts substantially from the original training data, remains difficult. Moreover, there is a disconnect between available sequence generation technologies and the diverse body of biological datasets needed to form and test mechanistic hypotheses. In this work, we describe a simple and powerful alteration to integrated gradients (Design by Integrated Gradients or DIGs) that serves as the foundation for several mRNA design tasks and an agentic hypothesis engine, the Structured RNA Evidence Aggregation Module (STREAM), which enables rapid adaptation of this technique to new contexts. Using this framework, we demonstrate complete model-informed mRNA design and reveal the underexplored rules governing the assembly of mRNA components into high-performance transcripts. By linking neural-network-based design to independent datasets, we design complete mRNA sequences in shifted settings, culminating in up to 6-fold increases in intramuscular expression compared to state-of-the-art methods in vivo. Together, DIGs and STREAM enable automated mRNA design in increasingly complex settings.

synthetic biology↗

bioRxiv2025

A Rapid and Modular Nanobody Assay for Plug-and-Play Antigen Detection

Rapid and portable antigen detection is essential for managing infectious diseases and responding to toxic exposures, yet current methods face significant limitations. Highly sensitive platforms like the Enzyme-Linked Immunosorbent Assay (ELISA) are time- and cost-prohibitive for point-of-need detection, while portable options like lateral flow assays (LFAs) require systemic overhauls for new targets. Furthermore, the complex infrastructure, high production costs, and extended timelines for assay development constrain manufacturing of traditional diagnostic platforms in low-resource settings. To address these challenges, we describe the Rapid and Modular Nanobody Assay (RAMONA) as a versatile antigen detection platform that leverages nanobody-coiled coil fusion proteins for modular integration with downstream readout methods. RAMONA merges the portability of LFAs with the benefits of nanobodies, such as their smaller size, improved solubility, and compatibility with cell-free protein synthesis systems, enabling on-demand biomanufacturing and rapid adaptation for diverse targets. We demonstrate assay generalizability through the detection of three distinct protein targets, robustness across various temperatures and incubation periods, and compatibility with saliva samples and cell-free synthesis. Detection occurs in under 30 minutes, with results strongly and positively correlating to ELISA data while requiring minimal resources. Moreover, RAMONA supports multiplexed detection of three antigens simultaneously using orthogonal capture probes. By overcoming several limitations of traditional immunoassays, RAMONA represents a significant advancement in rapid, adaptable, and field-deployable antigen detection technologies.

bioengineering↗

bioRxiv2023

Generative and predictive neural networks for the design of functional RNA molecules

RNA is a remarkably versatile molecule that has been engineered for applications in therapeutics, diagnostics, and in vivo information-processing systems. However, the complex relationship between the sequence and structural properties of an RNA molecule and its ability to perform specific functions often necessitates extensive experimental screening of candidate sequences. Here we present a generalized neural network architecture that utilizes the sequence and structure of RNA molecules (SANDSTORM) to inform functional predictions. We demonstrate that this approach achieves state-of-the-art performance across several distinct RNA prediction tasks, while learning interpretable abstractions of RNA secondary structure. We paired these predictive models with generative adversarial RNA design networks (GARDN), allowing the generative modelling of novel mRNA 5 untranslated regions and toehold switch riboregulators exhibiting a predetermined fitness. This approach enabled the design of novel toehold switches with a 43-fold increase in experimentally characterized dynamic range compared to those designed using classic thermodynamic algorithms. SANDSTORM and GARDN thus represent powerful new predictive and generative tools for the development of diagnostic and therapeutic RNA molecules with improved function.

synthetic biology↗

bioRxiv2018

De-Novo-Designed Translational Repressors for Multi-Input Cellular Logic

Synthetic biology aims to apply engineering principles toward the development of novel biological systems for biotechnology and medicine. Despite efforts to expand the set of high-performing parts for genetic circuits, achieving more complex circuit functions has often been limited by the idiosyncratic nature and crosstalk of commonly utilized parts. Here, we present a molecular programming strategy that implements RNA-based repression of translation using de-novo-designed RNAs to realize high-performance orthogonal parts with mRNA detection and multi-input logic capabilities. These synthetic post-transcriptional regulators, termed toehold repressors and three-way junction (3WJ) repressors, efficiently suppress translation in response to cognate trigger RNAs with nearly arbitrary sequences using thermodynamically and kinetically favorable linear-linear RNA interactions. Automated in silico optimization of thermodynamic parameters yields improved toehold repressors with up to 300-fold repression, while in-cell SHAPE-Seq measurements of 3WJ repressors confirm their designed switching mechanism in living cells. Leveraging the absence of sequence constraints, we identify eight- and 15-component sets of toehold and 3WJ repressors, respectively, that provide high orthogonality. The modularity, wide dynamic range, and low crosstalk of the repressors enable their direct integration into ribocomputing devices that provide universal NAND and NOR logic capabilities and can perform multi-input RNA-based logic. We demonstrate these capabilities by implementing a four-input NAND gate and the expression NOT((A1 AND A2) OR (B1 AND B2)) in Escherichia coli. These features make toehold and 3WJ repressors important new classes of translational regulators for biotechnological applications.

synthetic biology↗

bioRxiv2018

Size control of the inner ear via hydraulic feedback

Animals make organs of precise size, shape, and symmetry despite noise in underlying molecular and cellular processes. How developing organs manage this noise is largely unknown. Here, we combine quantitative imaging, physical theory, and physiological measurement of hydrostatic pressure and fluid transport in zebrafish to study size control of the developing inner ear. We find that fluid accumulation creates hydrostatic pressure in the lumen leading to stress in the epithelium and expansion of the otic vesicle. Pressure, in turn, inhibits fluid transport into the lumen. This negative feedback loop between pressure and transport allows the otic vesicle to change growth rate to control natural or experimentally-induced size variation. Spatiotemporal patterning of contractility modulates pressure-driven strain for regional tissue thinning. Our work connects moleculardriven mechanisms, such as osmotic pressure driven strain and actomyosin tension, to the regulation of tissue morphogenesis via hydraulic feedback to ensure robust control of organ size.

developmental biology↗