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95 results for “Biosensors”
Biosensor-driven strain engineering reveals key cellular processes for maximizing isoprenol production in <em>Pseudomonas putida</em>
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Fibronectin-Based Nanomechanical Biosensors to Map 3D Surface Strains in Live Cells and Tissue (Raw Data)
<p>This is the raw microscope imaging data for the manuscript titled "Fibronectin-Based Nanomechanical Biosensors to Map 3D Surface Strains in Live Cells and Tissue."</p>
Porous Silicon Biosensor for the Detection of Bacteria Through Their Lysate: Data
<p>This file contains:</p> <p>- Characterization data of porous silicon layer based on different etching parameters</p> <p>- Relative EOT shift on PSi layers for different analytes</p> <p>- Relative EOT shift on PSi membranes for different analytes</p> <p>- EOT shift on PSi membranes with respect to refractive index changes</p>
Supplementary Movie 1 from: A genetically encoded biosensor to monitor dynamic changes of c-di-GMP with high temporal resolution
<p>This record contains<strong> Supplementary Movie 1</strong> from:</p> <p><strong>A genetically encoded biosensor to monitor dynamic changes of c-di-GMP with high temporal resolution</strong></p> <p>Andreas Kaczmarczyk, Simon van Vliet, Roman Peter Jakob, Raphael Dias Teixeira, Inga Scheidat, Alberto Reinders, Alexander Klotz, Timm Maier, Urs Jenal</p> <p>Biozentrum, University of Basel, 4056 Basel, Switzerland</p> <p>Correspondence to: urs.jenal[at]unibas.ch, andreas.kaczmarczyk[at]unibas.ch</p> <p> </p>
Data for 'Ranking Single Fluorescent Protein Based Calcium Biosensor Performance by Molecular Dynamics Simulations'
<h2>Melike Berksoz, Canan Atilgan* </h2> <h3>Faculty of Engineering and Natural Sciences, Sabanci University </h3> <p><strong>*Correspondance:</strong> Canan Atilgan, Faculty of Natural Sciences and Engineering, Sabancı University, Tuzla 34956 Istanbul, Türkiye, E-mail: canan@sabanciuniv.edu</p> <p>Genetically Encoded Fluorescent Biosensors (GEFBs) have become indispensable tools for visualizing biological processes <em>in</em> <em>vivo.</em> A typical GEFB is composed of a sensory domain (SD) which undergoes a conformational change upon ligand binding and a genetically fused fluorescent protein (FP). Ligand binding in the SD allosterically modulates the chromophore environment and changes its spectral properties. Single fluorescent (FP)-based biosensors, a subclass of GEFBs, offer a simple experimental setup; they are easy to produce in living cells, structurally stable and simple due to their single-wavelength operation. However, they pose a significant challenge for structure optimization, especially concerning the length and residue content of linkers between the FP and SD which effect how well the chromophore responds to conformational change in the SD. In this work, we use classical all-atom molecular dynamics simulations to analyze the dynamic properties of a series of calmodulin-based calcium biosensors, all with different FP-SD interaction interfaces and varying degrees of calcium binding dependent fluorescence change. Our results indicate that biosensor performance can be predicted based on distribution of water molecules around the chromophore and shifts in hydrogen bond occupancies between the ligand-bound and ligand-free sensor structures.</p> <p>Hydrogen bond occupancies were calculated with merging_bonds.py script. Double counted hydrogen bonds where a residue acts both as acceptor and donor are merged into a single entry with merge_files.py. To run sasa.tcl, you need VMD software. Trajectories were created with NAMD2 with a dcdfrequency of 5000 timesteps (every 10 ps) and strided in a 1:100 ratio (every 1 ns=1 frame in dcd). </p>
Data from the paper "A turquoise fluorescence lifetime-based biosensor for quantitative imaging of intracellular calcium"
<p>Data that belongs to the paper "A turquoise fluorescence lifetime-based biosensor for quantitative imaging of intracellular calcium"</p> <p> </p>
Discovery of thermostable fluorescently responsive glucose biosensors by structure-assisted function extrapolation
<p>Accurate assignment of protein function from sequence remains a fascinating and difficult challenge. The periplasmic binding protein (PBP) superfamily present an interesting case of function prediction, because they are both ubiquitous in prokaryotes, and they tend to diversify through gene duplication "explosions" that can lead to large numbers of paralogs in a genome. An engineered version of the moderately thermostable glucose-binding PBP from <i>Escherichia coli</i> has been used successfully as a reagentless fluorescent biosensor both <i>in vitro</i> and <i>in vivo</i>. To develop more robust sensors that meet the challenges of real-world applications, we report the discovery of thermostable homologs that retain a glucose-mediated conformationally coupled fluorescence response. Accurately identifying a glucose-binding PBP homolog among closely related paralogs is challenging. We demonstrate that a structure-based method that filters sequences by residues that bind glucose in an archetype structure is highly effective. Using fully sequenced bacterial genomes we found that this filter reduced high paralog numbers to single hits in a genome, consistent with accurate separation of glucose binding from other functions. We expressed engineered proteins for eight homologs, chosen to represent different degrees of sequence identity and tested their glucose-mediated fluorescence responses. We accurately predicted the presence of glucose binding down to 31% sequence identity. We also have successfully identified suitable candidates for next-generation robust, fluorescent glucose sensors.</p>
Absolute measurement of cellular activities using photochromic single-fluorophore biosensors and intermittent quantification: data and code example
<p>Minimal code example, raw and derived data for the publication on 'Absolute measurement of cellular activities using photochromic single-fluorophore biosensors and intermittent quantification'.</p>
Applications of machine learning tools for ultra-sensitive detection of lipoarabinomannan with plasmonic grating biosensors in clinical samples of tuberculosis
Background <p>Tuberculosis is one of the top ten causes of death globally and the leading cause of death from a single infectious agent. Eradicating the Tuberculosis epidemic by 2030 is one of the top United Nations Sustainable Development Goals. Early diagnosis is essential to achieving this goal because it improves individual prognosis and reduces transmission rates of asymptomatic infected. We aim to support this goal by developing rapid and sensitive diagnostics using machine learning algorithms to minimize the need for expert intervention. </p> Methods and Findings <p>A single-molecule fluorescence immunosorbent assay was used to detect the Tuberculosis biomarker lipoarabinomannan from a set of twenty clinical patient samples and a control set of spiked human urine. Tuberculosis status was separately confirmed by GeneXpert MTB/RIF and cell culture. Two machine learning algorithms, an automatic and a semiautomatic model, were developed and trained by the calibrated lipoarabinomannan titration assay data and then tested against the ground truth patient data. The semiautomatic model differed from the automatic model by an expert review step in the former, which calibrated the lower threshold to determine single molecules from background noise. The semiautomatic model was found to provide 88.89% clinical sensitivity, while the automatic model resulted in 77.78% clinical sensitivity.</p> Conclusions <p>The semiautomatic model outperformed the automatic model in clinical sensitivity as a result of the expert intervention applied during calibration and both models vastly outperformed manual expert counting in terms of time-to-detection and completion of analysis. Meanwhile, the clinical sensitivity of the automatic model could be improved significantly with a larger training dataset. In short, semiautomatic, and automatic Gaussian Mixture Models have a place in supporting rapid detection of Tuberculosis in resource-limited settings without sacrificing clinical sensitivity.</p>
Raw Confocal Images for "A quantitative gibberellin signaling biosensor reveals a role for gibberellins in internode specification at the shoot apical meristem"
<p>Abstract: Growth at the shoot apical meristem (SAM) is essential for shoot architecture construction. The phytohormones gibberellins (GA) play a pivotal role in coordinating plant growth, but their role in the SAM remainsmostly unknown. Here, we developed a ratiometric GA signaling biosensor by engineering one of the DELLA proteins, to suppress its master regulatory function in GA transcriptional responses while preserving its degradation upon GA sensing. We demonstrate that this degradation-based biosensor accurately reports on cellular changes inGA levels and perception during development.Weused this biosensor to map GA signaling activity in the SAM. We show that high GA signaling is found primarily in cells located between organ primordia that are the precursors of internodes. By gain- and loss-of-function approaches, we further demonstrate that GAs regulate cell division plane orientation to establish the typical cellular organization of internodes, thus contributing to internode speci<span>fi</span>cation in the SAM.</p>
Conformational changes in insulin receptor illuminated by live-cell linear dichroism imaging and a FLIP biosensor
<p>Response of GP2(1)-eGFP-CD59, a FLIP biosensor co transfected with insulin receptor against anatgonists and agonists of IR was measured and qunatified using polarization-resolved fluorescence microscopy. Linear dichoirism values were measured by analyinzing cells using already published imageJ macros (Bondar, Rybakova et al. 2021). This data set contains both raw images obtained from polarization micrscopy and analyzed data.</p>
Plasmid sequences for the paper "A FRET based biosensor for measuring Gα13 activation in single cells"
<p>Plasmid sequences for the paper "A FRET based biosensor for measuring Gα13 activation in single cells"</p>
Engineered acetoacetate-inducible whole-cell biosensors based on the AtoSC two-component system
<p>Data and code for manuscript.</p>
Data related to the manuscript "Visualizing endogenous Rho activity with an improved localization-based, genetically encoded biosensor"
<p>These are the data that are related to the manuscript "Visualizing endogenous Rho activity with an improved localization-based, genetically encoded biosensor" by </p> <p>Eike K. Mahlandt<sup>1,*</sup>, Janine J. G. Arts<sup>1,2</sup>,Werner J. van der Meer<sup>1</sup>, Franka H. van der Linden<sup>1</sup>, Simon Tol<sup>2</sup>, Jaap D. van Buul<sup>1,2</sup>, Theodorus W. J. Gadella Jr.<sup>1</sup>, Joachim Goedhart<sup>1,*</sup></p> <p><sup>1</sup> Swammerdam Institute for Life Sciences, Section of Molecular Cytology, van Leeuwenhoek Centre for Advanced Microscopy, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, The Netherlands</p> <p><sup>2</sup> Molecular Cell Biology Lab at Dept. Molecular Hematology, Sanquin Research and Landsteiner Laboratory, Amsterdam, The Netherlands</p>
Achieving high hybridization density at DNA biosensor surfaces using branched spacer and click chemistry
<p>Raw data and metadata associated to the study " Achieving high hybridization density at DNA biosensor surfaces using branched spacer and click chemistry".</p> <p>Copy of labbook for synthetic procedures and surface functionalization procedures.</p> <p>Data for surface characterizations (XPS measurements and fluorescent quantification).</p> <p>Data for molecular characterizations: NMR and Mass Spectrometry.</p>
Molecular Biosensors for Detection of Bladder Cancer
ClinicalTrials.gov study NCT02957370. IPD Sharing: Not stated. Countries: 1. Publications: 38.
Analysis of Exhaled Breath by Biosensors in Adults With Asthma
ClinicalTrials.gov study NCT00819676. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Objective Pain Measurement Using a Wearable Biosensor and a Mobile Platform in Patients With Endometriosis
ClinicalTrials.gov study NCT04318275. IPD Sharing: NO. Countries: 3. Publications: 13.
Towards a Wearable Alcohol Biosensor: Examining the Accuracy of BAC Estimates From New-Generation Transdermal Technology Using Large-Scale Human Testing and Machine Learning Algorithms
ClinicalTrials.gov study NCT05692830. IPD Sharing: UNDECIDED. Countries: 1. Publications: 27.
Detection of Gastrointestinal Bleeding in Intensive Care Patients Via Biosensor Watch
ClinicalTrials.gov study NCT03874169. IPD Sharing: NO. Countries: 1. Publications: 1.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.