» Articles » PMID: 28684745

Mie Scatter Spectra-based Device for Instant, Contact-free, and Specific Diagnosis of Bacterial Skin Infection

Overview
Journal Sci Rep
Specialty Science
Date 2017 Jul 8
PMID 28684745
Citations 5
Authors
Affiliations
Soon will be listed here.
Abstract

Rapid and specific diagnostic techniques are needed to expedite specific treatment of bacterial skin infections with narrow-spectrum antibiotics, rather than broad-spectrum. Through this work a device was developed to determine the presence of and species responsible for a bacterial skin infection using differences in Mie scatter spectra created by different bacterial species. A 650 nm LED at five different incident angles is used to illuminate the tissue, with Mie scatter being detected by PIN photodiodes at eight different detection angles. Mie scatter patterns are collected at all photodiode angles for each of the incident light angles, resulting in a Mie scatter spectra. Detectable differences in Mie scatter spectra were found using the device developed between commensal bacteria (no infection) and bacteria inoculated (infection) on the surface of both porcine and human cadaveric epidermis. Detectable differences were found between species of infection, specifically Escherichia coli and Staphylococcus aureus, with differences summarized through principle component analysis. Mie scatter spectra can be detected within a few seconds without skin contact. This device is the first to rapidly and specifically diagnose bacterial skin infections in a contact-less manner, allowing for initial treatment with narrow spectrum antibiotics, and helping to reduce the likelihood of resistance.

Citing Articles

Global burden of bacterial skin diseases from 1990 to 2045: an analysis based on global burden disease data.

Gu J, Wang J, Li Y, Li L, Zou Y, Guo Y Arch Dermatol Res. 2025; 317(1):266.

PMID: 39820797 DOI: 10.1007/s00403-025-03804-z.


Paper-based sensors for bacteria detection.

Mazur F, Tjandra A, Zhou Y, Gao Y, Chandrawati R Nat Rev Bioeng. 2023; 1(3):180-192.

PMID: 36937095 PMC: 9926459. DOI: 10.1038/s44222-023-00024-w.


Machine learning classification of bacterial species using mix-and-match reagents on paper microfluidic chips and smartphone-based capillary flow analysis.

Kim S, Day A, Yoon J Anal Bioanal Chem. 2022; 414(13):3895-3904.

PMID: 35347355 DOI: 10.1007/s00216-022-04031-5.


Label-free Mie Scattering Identification of Tumor Tissue Using an Angular Photodiode Array.

Bills M, Yoon J IEEE Sens Lett. 2021; 4(7).

PMID: 33748652 PMC: 7974318. DOI: 10.1109/lsens.2020.3001489.


Interfacial Effect-Based Quantification of Droplet Isothermal Nucleic Acid Amplification for Bacterial Infection.

Ulep T, Day A, Sosnowski K, Shumaker A, Yoon J Sci Rep. 2019; 9(1):9629.

PMID: 31270374 PMC: 6610113. DOI: 10.1038/s41598-019-46028-8.


References
1.
ROTH R, James W . Microbiology of the skin: resident flora, ecology, infection. J Am Acad Dermatol. 1989; 20(3):367-90. DOI: 10.1016/s0190-9622(89)70048-7. View

2.
Cardona A, Wilson S . Skin and soft-tissue infections: a critical review and the role of telavancin in their treatment. Clin Infect Dis. 2015; 61 Suppl 2:S69-78. DOI: 10.1093/cid/civ528. View

3.
Pardos de la Gandara M, Raygoza Garay J, Mwangi M, Tobin J, Tsang A, Khalida C . Molecular Types of Methicillin-Resistant Staphylococcus aureus and Methicillin-Sensitive S. aureus Strains Causing Skin and Soft Tissue Infections and Nasal Colonization, Identified in Community Health Centers in New York City. J Clin Microbiol. 2015; 53(8):2648-58. PMC: 4508410. DOI: 10.1128/JCM.00591-15. View

4.
Liang P, Park T, Yoon J . Rapid and reagentless detection of microbial contamination within meat utilizing a smartphone-based biosensor. Sci Rep. 2014; 4:5953. PMC: 4121612. DOI: 10.1038/srep05953. View

5.
Grice E, Kong H, Renaud G, Young A, Bouffard G, Blakesley R . A diversity profile of the human skin microbiota. Genome Res. 2008; 18(7):1043-50. PMC: 2493393. DOI: 10.1101/gr.075549.107. View