Ultrasensitive point-of-care immunoassay for secreted glycoprotein detects Ebola infection earlier than PCR.
Date
2021-04
Journal Title
Journal ISSN
Volume Title
Repository Usage Stats
views
downloads
Citation Stats
Attention Stats
Abstract
Ebola virus (EBOV) hemorrhagic fever outbreaks have been challenging to deter due to the lack of health care infrastructure in disease-endemic countries and a corresponding inability to diagnose and contain the disease at an early stage. EBOV vaccines and therapies have improved disease outcomes, but the advent of an affordable, easily accessed, mass-produced rapid diagnostic test (RDT) that matches the performance of more resource-intensive polymerase chain reaction (PCR) assays would be invaluable in containing future outbreaks. Here, we developed and demonstrated the performance of a new ultrasensitive point-of-care immunoassay, the EBOV D4 assay, which targets the secreted glycoprotein of EBOV. The EBOV D4 assay is 1000-fold more sensitive than the U.S. Food and Drug Administration-approved RDTs and detected EBOV infection earlier than PCR in a standard nonhuman primate model. The EBOV D4 assay is suitable for low-resource settings and may facilitate earlier detection, containment, and treatment during outbreaks of the disease.
Type
Department
Description
Provenance
Subjects
Citation
Permalink
Published Version (Please cite this version)
Publication Info
Fontes, Cassio M, Barbara D Lipes, Jason Liu, Krystle N Agans, Aiwei Yan, Patricia Shi, Daniela F Cruz, Garrett Kelly, et al. (2021). Ultrasensitive point-of-care immunoassay for secreted glycoprotein detects Ebola infection earlier than PCR. Science translational medicine, 13(588). p. eabd9696. 10.1126/scitranslmed.abd9696 Retrieved from https://hdl.handle.net/10161/33667.
This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.
Collections
Scholars@Duke
Cassio Mendes Fontes
Barbara D Lipes
Kelli Luginbuhl
Carl F. Pieper
Analytic Interests.
1) Issues in the Design of Medical Experiments: I explore the use of reliability/generalizability models in experimental design. In addition to incorporation of reliability, I study powering longitudinal trials with multiple outcomes and substantial missing data using Mixed models.
2) Issues in the Analysis of Repeated Measures Designs & Longitudinal Data: Use of Hierarchical Linear Models (HLM) or Mixed Models in modeling trajectories of multiple variables over time (e.g., physical and cognitive functioning and Blood Pressure). My current work involves methodologies in simultaneous estimation of trajectories for multiple variables within and between domains, modeling co-occuring change.
Areas of Substantive interest: (1) Experimental design and analysis in gerontology and geriatrics, and psychiatry,
(2) Multivariate repeated measures designs,
Roarke Horstmeyer
Roarke Horstmeyer is an assistant professor within Duke's Biomedical Engineering Department. He develops microscopes, cameras and computer algorithms for a wide range of applications, from forming 3D reconstructions of organisms to detecting neural activity deep within tissue. His areas of interest include optics, signal processing, optimization and neuroscience. Most recently, Dr. Horstmeyer was a guest professor at the University of Erlangen in Germany and an Einstein postdoctoral fellow at Charitè Medical School in Berlin. Prior to his time in Germany, Dr. Horstmeyer earned a PhD from Caltech’s electrical engineering department in 2016, a master of science degree from the MIT Media Lab in 2011, and a bachelors degree in physics and Japanese from Duke University in 2006.
Michael Dee Gunn
Lab History
The lab started with our discovery of the lymphoid chemokines, which regulate the migration of lymphocytes and dendritic cells to and within secondary lymphoid organs. We identified the chemokine (CCL21) that mediates the entry of naïve T cells and activated dendritic cells into lymph nodes and the chemokine (CXCL13) that mediates the entry of B cells into lymphoid follicles. Our focus then shifted to understanding how specific cell types, primarily dendritic cells, and cell migration events regulate immune responses. We identified murine plasmacytoid dendritic cells; the cell type that causes pulmonary immune pathology during influenza infection; the dendritic cell type that stimulates Th1 immune responses; the cell type that induces neuronal injury in Alzheimer's disease, and the macrophage type that stimulates pulmonary hypertension. Our current work continues these basic studies while applying our findings to models of human disease.
Current Research
Development of recombinant antibodies as diagnostic reagents – Our lab has developed novel methods to generate recombinant single chain antibodies using phage display technology. We are currently using these methods to generate pathogen-specific antibodies for use in diagnostic tests for a variety of human bacterial, viral, and fungal infections. In collaboration with Duke Biomedical Engineering, we are deploying our antibodies in a novel diagnostic assay platform to develop point-of-care assays for the diagnosis of a variety of emerging pathogens. Our recently developed point-of-care assay for Ebola virus displays a sensitivity superior to PCR at a fraction of the per assay cost.
Ashutosh Chilkoti
Ashutosh Chilkoti is the Alan L. Kaganov Professor of Biomedical Engineering and Chair of the Department of Biomedical Engineering at Duke University.
My research in biomolecular engineering and biointerface science focuses on the development of new molecular tools and technologies that borrow from molecular biology, protein engineering, polymer chemistry and surface science that we then exploit for the development of applications that span the range from bioseparations, plasmonic biosensors, low-cost clinical diagnostics, and drug delivery.
Unless otherwise indicated, scholarly articles published by Duke faculty members are made available here with a CC-BY-NC (Creative Commons Attribution Non-Commercial) license, as enabled by the Duke Open Access Policy. If you wish to use the materials in ways not already permitted under CC-BY-NC, please consult the copyright owner. Other materials are made available here through the author’s grant of a non-exclusive license to make their work openly accessible.