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Rapid Visual Screening and Programmable Subtype Classification of Ebola Virus Biomarkers
Author(s) -
Balcioglu Mustafa,
Rana Muhit,
Hizir Mustafa Salih,
Robertson Neil M.,
Haque Kashfia,
Yigit Mehmet V.
Publication year - 2017
Publication title -
advanced healthcare materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.288
H-Index - 90
eISSN - 2192-2659
pISSN - 2192-2640
DOI - 10.1002/adhm.201600739
Subject(s) - ebola virus , virology , computational biology , computer science , medicine , virus , biology
The massive outbreaks of the highly transmissible and lethal Ebola virus disease were caused by infection with one of the Ebolavirus species. It is vital to develop cost‐effective, highly sensitive and selective multitarget biosensing platforms that allow for both the detection and phenotyping. Here, a highly programmable, cost‐efficient and multianalyte sensing approach is reported that enables visual detection and differentiation of conserved oligonucleotide regions of all Ebolavirus subtypes known to infect human primates. This approach enables the detection of as little as 400 amols (24 × 10 6 molecules) of target sequences with the naked eye. Furthermore, the detection assay can be used to classify four virus biomarkers using a single nanoprobe template. This can be achieved by using different combinations of short single stranded initiator molecules, referred to as programming units, which also enable the simultaneous and rapid identification of the four biomarkers in 16 different combinations. The results of 16 × 5 array studies illustrate that the system is extremely selective with no false‐positive or false‐negative. Finally, the target strands in liquid biopsy mimics prepared from urine specimens are also able to be identified and classified.