| Title |
Gold nanoparticle-labeled biosensor for rapid and sensitive detection of bacterial pathogens
|
|---|---|
| Published in |
Journal of Biological Engineering, October 2015
|
| DOI | 10.1186/s13036-015-0014-z |
| Pubmed ID | |
| Authors |
Yun Wang, Evangelyn C. Alocilja |
| Abstract |
Escherichia coli O157:H7 is one of the major foodborne bacterial pathogens and also a biodefense agent. To ensure food safety and public health, it is very important to develop rapid methods for E. coli O157:H7 detection. In this study, we designed a nanoparticle-labeled biosensor for the rapid detection of E. coli O157:H7 in broth. Magnetic nanoparticles (MNPs) were conjugated with monoclonal antibodies (Abs) to separate target E. coli O157:H7 cells from broth samples. Gold nanoparticles (AuNPs) were conjugated with polyclonal Abs, and were then introduced to the MNP-target complex to form a sandwich MNP-target-AuNP. By measuring the amount of AuNPs through an electrochemical method, the presence and the amount of the target bacteria were determined. Results showed a sensitivity of 10(1) colony forming units per milliliter (cfu/ml) with a linear range of 10(1)-10(6) cfu/ml. Compared to conventional culture plating methods, the biosensor reduced the detection time from 2 to 4 days to less than 1 hour with a simple target extraction method. The AuNP-labeled biosensor has potential applications in the rapid detection of infectious agents for public health, biodefense, and food/water safety. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 224 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Korea, Republic of | 1 | <1% |
| United States | 1 | <1% |
| China | 1 | <1% |
| Unknown | 221 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 47 | 21% |
| Researcher | 30 | 13% |
| Student > Bachelor | 26 | 12% |
| Student > Master | 25 | 11% |
| Other | 8 | 4% |
| Other | 32 | 14% |
| Unknown | 56 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 31 | 14% |
| Chemistry | 29 | 13% |
| Agricultural and Biological Sciences | 26 | 12% |
| Biochemistry, Genetics and Molecular Biology | 25 | 11% |
| Immunology and Microbiology | 9 | 4% |
| Other | 35 | 16% |
| Unknown | 69 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 October 2015.
All research outputs
#15,348,067
of 22,829,683 outputs
Outputs from Journal of Biological Engineering
#182
of 260 outputs
Outputs of similar age
#161,221
of 275,403 outputs
Outputs of similar age from Journal of Biological Engineering
#5
of 7 outputs
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So far Altmetric has tracked 260 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
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