Evidence map›Paper›PMID 26108554›Full record

ArticleJournal of nanobiotechnology2015

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

Longyan Chen, Nawfal Mungroo, Luciana Daikuara, Suresh Neethirajan

Abstract readEvaluation Study
In one paragraph

Article in Journal of nanobiotechnology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Rapid, Label-Free Prediction of Antibiotic Resistance inInternational journal of molecular sciences · 2022
    Article
  8. Review
  9. Review
  10. Article
  11. Review
  12. Review on SERS of Bacteria.Biosensors · 2017
    Review
  13. Review
  14. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Longyan ChenBioNano Laboratory, School of Engineering, University of Guelph, Guelph, ON, N1G 2W1 12, Canada. longyan@uoguelph.ca.
Nawfal MungrooBioNano Laboratory, School of Engineering, University of Guelph, Guelph, ON, N1G 2W1 12, Canada. nmungroo@uoguelph.ca.
Luciana DaikuaraBioNano Laboratory, School of Engineering, University of Guelph, Guelph, ON, N1G 2W1 12, Canada. ldaikuara@mail.uoguelph.ca.
Suresh NeethirajanBioNano Laboratory, School of Engineering, University of Guelph, Guelph, ON, N1G 2W1 12, Canada. sneethir@uoguelph.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRapid 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.

resultsPre-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.

conclusionsThe 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.

Indexed as

BacteriaColloidsDrinking WaterEscherichia coliLimit of DetectionListeriaMetal NanoparticlesMethicillin-Resistant Staphylococcus aureusPseudomonas aeruginosaSilverSpectrum Analysis, RamanColloidsDrinking WaterSilver

Identifiers

PMID26108554
PMCPMC4479109

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.