| Title |
Rapid detection and differentiation of Staphylococcus colonies using an optical scattering technology
|
|---|---|
| Published in |
Analytical & Bioanalytical Chemistry, May 2018
|
| DOI | 10.1007/s00216-018-1133-4 |
| Pubmed ID | |
| Authors |
Tawfiq S. Alsulami, Xingyue Zhu, Maha Usama Abdelhaseib, Atul K. Singh, Arun K. Bhunia |
| Abstract |
Staphylococcus species are a major pathogen responsible for nosocomial infections and foodborne illnesses. We applied a laser-based BARDOT (bacterial rapid detection using optical scattering technology) for rapid colony screening and detection of Staphylococcus on an agar plate and differentiate these from non-Staphylococcus spp. Among the six growth media tested, phenol red mannitol agar (PRMA) was found most suitable for building the Staphylococcus species scatter image libraries. Scatter image library for Staphylococcus species gave a high positive predictive value (PPV 87.5-100%) when tested against known laboratory strains of Staphylococcus spp., while the PPV against non-Staphylococcus spp. was 0-38%. A total of nine naturally contaminated bovine raw milk and ready-to-eat chicken salad samples were tested, and BARDOT detected Staphylococcus including Staphylococcus aureus with 80-100% PPV. Forty-five BARDOT-identified bacterial isolates from naturally contaminated foods were further confirmed by tuf and nuc gene-specific PCR and 16S rRNA gene sequence. This label-free, non-invasive on-plate colony screening technology can be adopted by the food industries, biotechnology companies, and public health laboratories for Staphylococcus species detection including S. aureus from various samples for food safety and public health management. Graphical abstract. |
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 % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 29 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 17% |
| Student > Master | 4 | 14% |
| Student > Doctoral Student | 3 | 10% |
| Other | 2 | 7% |
| Researcher | 2 | 7% |
| Other | 3 | 10% |
| Unknown | 10 | 34% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 6 | 21% |
| Engineering | 3 | 10% |
| Nursing and Health Professions | 2 | 7% |
| Veterinary Science and Veterinary Medicine | 2 | 7% |
| Immunology and Microbiology | 2 | 7% |
| Other | 4 | 14% |
| Unknown | 10 | 34% |
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 14 August 2018.
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#22,767,715
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Outputs from Analytical & Bioanalytical Chemistry
#7,543
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Outputs of similar age
#302,276
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Outputs of similar age from Analytical & Bioanalytical Chemistry
#136
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