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Label-free NIR-SERS discrimination and detection of foodborne bacteria by in situ synthesis of Ag colloids

Overview of attention for article published in Journal of Nanobiotechnology, June 2015
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Title
Label-free NIR-SERS discrimination and detection of foodborne bacteria by in situ synthesis of Ag colloids
Published in
Journal of Nanobiotechnology, June 2015
DOI 10.1186/s12951-015-0106-4
Pubmed ID
Authors

Longyan Chen, Nawfal Mungroo, Luciana Daikuara, Suresh Neethirajan

Abstract

Rapid detection and discrimination of bacteria for biomedical and food safety applications remain a considerable challenge. We report a label-free near infrared surface-enhanced Raman scattering (NIR-SERS) method for the discrimination of pathogenic bacteria from drinking water. The approach relies on the in situ synthesis of silver nanoparticles (Ag NPs) within the bacterial cell suspensions. Pre-treatment of cells with Triton X-100 significantly improved the sensitivity of the assay. Using this method, we were able to discriminate several common pathogenic bacteria such as Escherichia coli, Pseudomonas aeruginosa, Methicillin-resistant Staphylococcus aureus (MRSA) and Listeria spp. A comparison of the SERS spectra allowed for the discrimination of two Listeria species, namely L. monocytogenes and L. innocua. We further report the application of the method to discriminate two MRSA strains from clinical isolates. The complete assay was completed in a span of 5 min. The proposed analytical method proves to be a rapid tool for selective and label-free identification of pathogenic bacterium. Pre-treatment of bacterial cells with Triton X-100 resulted in new features on the SERS spectra, allowing for a successful discrimination of common disease related bacteria including E. coli, P. aeruginosa, Listeria and MRSA. We also demonstrate that the spectral features obtained using in situ synthesis of nanoparticles could be could be used to differentiate two species of listeria. By using L. innocua as a model sample, we found the limit of detection of our assay to be 10(3) CFU/mL. The method can selectively discriminate different bacterial species, and has a potential to be used in the development of point-of-care diagnostics with biomedical and food safety applications.

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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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 92 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 1 1%
Unknown 91 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 29%
Researcher 19 21%
Student > Master 8 9%
Student > Doctoral Student 5 5%
Student > Bachelor 3 3%
Other 13 14%
Unknown 17 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 18%
Chemistry 16 17%
Engineering 8 9%
Materials Science 6 7%
Physics and Astronomy 4 4%
Other 13 14%
Unknown 28 30%
Attention Score in Context

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 26 June 2015.
All research outputs
#20,281,599
of 22,815,414 outputs
Outputs from Journal of Nanobiotechnology
#1,219
of 1,415 outputs
Outputs of similar age
#219,909
of 263,904 outputs
Outputs of similar age from Journal of Nanobiotechnology
#11
of 12 outputs
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So far Altmetric has tracked 1,415 research outputs from this source. They receive a mean Attention Score of 3.5. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.