Dataset Information

A modular yeast biosensor for low-cost point-of-care pathogen detection.

ABSTRACT: The availability of simple, specific, and inexpensive on-site detection methods is of key importance for deployment of pathogen surveillance networks. We developed a nontechnical and highly specific colorimetric assay for detection of pathogen-derived peptides based on Saccharomyces cerevisiae-a genetically tractable model organism and household product. Integrating G protein-coupled receptors with a visible, reagent-free lycopene readout, we demonstrate differential detection of major human, plant, and food fungal pathogens with nanomolar sensitivity. We further optimized a one-step rapid dipstick prototype that can be used in complex samples, including blood, urine, and soil. This modular biosensor can be economically produced at large scale, is not reliant on cold-chain storage, can be detected without additional equipment, and is thus a compelling platform scalable to global surveillance of pathogens.

SUBMITTER: Ostrov N

PROVIDER: S-EPMC5489263 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

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A modular yeast biosensor for low-cost point-of-care pathogen detection.

Ostrov Nili N Jimenez Miguel M Billerbeck Sonja S Brisbois James J Matragrano Joseph J Ager Alastair A Cornish Virginia W VW

Science advances 20170628 6

The availability of simple, specific, and inexpensive on-site detection methods is of key importance for deployment of pathogen surveillance networks. We developed a nontechnical and highly specific colorimetric assay for detection of pathogen-derived peptides based on <i>Saccharomyces cerevisiae</i>-a genetically tractable model organism and household product. Integrating G protein-coupled receptors with a visible, reagent-free lycopene readout, we demonstrate differential detection of major hu ...[more]

PMID: 28782007

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Project description:BackgroundCarotid Artery Stenting (CAS) is increasingly being used in selected patients as a minimal invasive approach to carotid endarterectomy. Despite the long standing tradition of endovascular treatments, visual feedback during stent-deployment is impossible to obtain as deployment is performed under fluoroscopic imaging. Furthermore, the concept of stent-placement is often still unclear to patients. 3D Printing allows to replicate patient-specific anatomies and deploy stents inside them to simulate procedures. As such these models are being used for endovascular training as well as patient education.PurposeTo our knowledge, this study reports the first use of a low-cost patient-specific 3D printed model for teaching CAS deployment under direct visualization, without fluoroscopy.MethodologyA CT-angiogram was segmented and converted to STL format using Mimics inPrint™ software. The carotid arteries were bilaterally truncated to fit the whole model on a Formlabs 2 printer without omitting the internal vessel diameter. Next, this model was offset using a 1 mm margin. A ridge was modelled on the original vessel anatomy which was subsequently subtracted from the offset model in order to obtain a deroofed 3D model. All vessels were truncated to facilitate post-processing, flow and guide wire placement.ResultsCarotid artery stents were successfully deployed inside the vessel. The deroofing allows for clear visualization of the bottlenecks and characteristics of CAS deployment and positioning, including stent foreshortening, tapering and recoil. This low-cost 3D model provides visual insights in stent deployment and positioning, and can allow for patient-specific procedure planning.ConclusionsThe presented approach demonstrates the use of low-cost 3D Printed CAS models in teaching complex stent behavior as observed during deployment. Two main findings are illustrated. On one hand, the feasibility of low-cost in-hospital model production is shown. On the other hand, the teaching of CAS deployment bottlenecks at the carotid level without the need for fluoroscopic guidance, is illustrated. The observed stent characteristics as shown during deployment are difficult to assess in radiologic models. Furthermore, printing patient-specific 3D models preoperatively could possibly assist in accurate patient selection, preoperative planning, case-specific training and patient education.

Dataset Information

A modular yeast biosensor for low-cost point-of-care pathogen detection.

Publications

A modular yeast biosensor for low-cost point-of-care pathogen detection.

Similar Datasets

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