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A lab-on-paper biosensor using a two-step enzymatic amplification strategy for ultrasensitive detection of active BoNT/A in complex matrices
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Recent advances on functional nucleic acid-based biosensors for detection of food contaminants
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Polymer Domains Control Diffusion in Protein-Polymer Conjugate Biosensors
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Streamlined detection of Nipah virus antibodies using a split NanoLuc biosensor
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Quantitative comparison between sub-millisecond time resolution single-molecule FRET measurements and 10-second molecular simulations of a biosensor protein
Molecular Dynamics (MD) simulations seek to provide atomic-level insights into conformationally dynamic biological systems at experimentally relevant time resolutions, such as those afforded by single-molecule fluorescence measurements. However, limitations in the time scales of MD simulations and the time resolution of single-molecule measurements have challenged efforts to obtain overlapping temporal regimes required for close quantitative comparisons. Achieving such overlap has the potential to provide novel theories, hypotheses, and interpretations that can inform idealized experimental designs that maximize the detection of the desired reaction coordinate. Here, we report MD simulations at time scales overlapping with in vitro single-molecule Förster (fluorescence) resonance energy transfer (smFRET) measurements of the amino acid binding protein LIV-BP SS at sub-millisecond resolution. Computationally efficient all-atom structure-based simulations, calibrated against explicit solvent simulations, were employed for sampling multiple cycles of LIV-BP SS clamshell-like conformational changes on the time scale of seconds, examining the relationship between these events and those observed by smFRET. The MD simulations agree with the smFRET measurements and provide valuable information on local dynamics of fluorophores at their sites of attachment on LIV-BP SS and the correlations between fluorophore motions and large-scale conformational changes between LIV-BP SS domains. We further utilize the MD simulations to inform the interpretation of smFRET data, including Förster radius (R 0 ) and fluorophore orientation factor (κ 2 ) determinations. The approach we describe can be readily extended to distinct biochemical systems, allowing for the interpretation of any FRET system conjugated to protein or ribonucleoprotein complexes, including those with more conformational processes, as well as those implementing multi-color smFRET.
Biological and Molecular Components for Genetically Engineering Biosensors in Plants
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New Enzymes for Plastics Recycling from Biosensor-Guided Evolution and Machine Learning: Cooperative Research and Development Final Report, CRADA Number CRD-23-24335
The Agile BioFoundry (ABF) is a consortium of national laboratories dedicated to accelerating biomanufacturing and enabling the bioeconomy. The ABF operates a flexible biotechnology platform that can adjust to the needs of numerous government, academic, and industrial partners, thus enabling them to rapidly develop and optimize the production of a wide range of bioproducts. In this project, the ABF partnered with Birch Biosciences, Inc. to use ABF technology to assist in the development of high-performance enzymes that enable circular, sustainable recycling of poly(ethylene terephthalate) (PET) plastics. A primary goal of this project is to enable cost-effective, high yield, sustainable recycling of PET plastic packaging products.
Developing yeast whole-cell biosensor for potential pathogen detection
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Electrospun porous La–Sr–Co–Ni–O nanofibers for highly sensitive non-enzymatic glucose detection
Glucose biosensors are widely used for clinical, industrial, and environmental applications. Nonenzymatic electrochemical glucose biosensors based on metal oxides with a perovskite structure have exhibited high sensitivity, excellent stability, and cost efficiency. In this work, porous La–Sr–Co–Ni–O (LSCNO) nanofibers, with an ABO 3 -type perovskite structure, were prepared through optimizing the A-site and B-site elements by electrospinning, followed with calcination at 700 °C for 5 h. Characterized by scanning and transmission electron microscopy, X-ray diffraction, and X-ray photoelectron spectroscopy, fabricated nanofibers were confirmed to be porous and nanosized polycrystalline grains with high crystallinity. A novel La 0.75 Sr 0.25 Co 0.5 Ni 0.5 O 3 -based nonenzymatic electrochemical biosensor was developed, which is sensitive to glucose because of an electrochemically catalytic mechanism, a mediated electron transfer involving Ni(II)/Ni(III) or Co(II)/Co(III), accompanying with gluconic acid complexation. The glucose biosensor presented a linear response in the range of 0.1–1.0 mM with a calibration sensitivity of 924 ± 28 μA mM –1 , a proportion of the variance of 0.9926, and a lower limit of detection of 0.083 mM, respectively, demonstrating an outstanding analytical performance. The biosensor showed no response to the most widely used anionic surfactant, sodium dodecyl sulfate, and low sensitivity to other biomolecules, such as fructose, lactose, galactose, mannose, dopamine, and ascorbic acid. A urine sample was tested by this novel nonenzymatic electrochemical biosensor by standard addition method, suggesting a potential application for clinical test.
Microbial spies and bloggers: programming cells to convert environmental information into discernible signals
Microbes regulate their dynamic behaviors using the chemical and physical characteristics of their environment. The ability of microbes to continuously convert this physicochemical information into biochemical information and to use organic matter in the environment as a power source makes these organisms attractive as chassis for building sensors. However, most biosensors have severe limitations when considering applications in hard-to-image settings like soils, sediments, and wastewater. Emerging technologies at the interface of biomolecular design, microbiome engineering, and synthetic biology offer new tools to program cells and communities as biosensors for these settings. Here, in this review, we describe innovations in biosensor outputs that are enabling new applications in complex environments, including reporters that are read out using electrochemical, gas chromatography, hyperspectral imaging, and next-generation sequencing methods. We also discuss computational advances that are accelerating the diversification of sensing components by mining metagenomics data for new transcriptional regulators and by designing allosteric protein switches that directly regulate reporter outputs using analytes. We highlight emerging opportunities for programming undomesticated microbes in communities to function as distributed sensors in the environment. Finally, we discuss the need for responsible biosensor development and to modernize regulatory frameworks to support evidence-based assessment of environmental biosensors.
Highly multiplexed design of an allosteric transcription factor to sense new ligands
Allosteric transcription factors (aTF) regulate gene expression through conformational changes induced by small molecule binding. Although widely used as biosensors, aTFs have proven challenging to design for detecting new molecules because mutation of ligand-binding residues often disrupts allostery. Here, we develop Sensor-seq, a high-throughput platform to design and identify aTF biosensors that bind to non-native ligands. We screen a library of 17,737 variants of the aTF TtgR, a regulator of a multidrug exporter, against six non-native ligands of diverse chemical structures – four derivatives of the cancer therapeutic tamoxifen, the antimalarial drug quinine, and the opiate analog naltrexone – as well as two native flavonoid ligands, naringenin and phloretin. Sensor-seq identifies biosensors for each of these ligands with high dynamic range and diverse specificity profiles. The structure of a naltrexone-bound design shows shape-complementary methionine-aromatic interactions driving ligand specificity. To demonstrate practical utility, we develop cell-free detection systems for naltrexone and quinine. Sensor-seq enables rapid and scalable design of new biosensors, overcoming constraints of natural biosensors.
CRAGE-mediated insertion of fluorescent chromosomal markers for accurate and scalable measurement of co-culture dynamics in Escherichia coli
Monitoring population dynamics in co-culture is necessary in engineering microbial consortia involved in distributed metabolic processes or biosensing applications. However, it remains difficult to measure strain-specific growth dynamics in high-throughput formats. This is especially vexing in plate-based functional screens leveraging whole-cell biosensors to detect specific metabolic signals. Here, we develop an experimental high-throughput co-culture system to measure and model the relationship between fluorescence and cell abundance, combining chassis-independent recombinase-assisted genome engineering (CRAGE) and whole-cell biosensing with a PemrR-green fluorescent protein (GFP) monoaromatic reporter used in plate-based functional screening. CRAGE was used to construct Escherichia coli EPI300 strains constitutively expressing red fluorescent protein (RFP) and the relationship between RFP expression and optical density (OD600) was determined throughout the EPI300 growth cycle. A linear equation describing the increase of normalized RFP fluorescence during deceleration phase was derived and used to predict biosensor strain dynamics in co-culture. Measured and predicted values were compared using flow cytometric detection methods. Induction of the biosensor lead to increased GFP fluorescence normalized to biosensor cell abundance, as expected, but a significant decrease in relative abundance of the biosensor strain in co-culture and a decrease in bulk GFP fluorescence. Taken together, these results highlight sensitivity of population dynamics to variations in metabolic activity in co-culture and the potential effect of these dynamics on the performance of functional screens in plate-based formats. The engineered strains and model used to evaluate these dynamics provide a framework for optimizing growth of synthetic co-cultures used in screening, testing and pathway engineering applications.