Research Papers: Sensing

Reagent-free bacterial identification using multivariate analysis of transmission spectra

[+] Author Affiliations
Jennifer M. Smith, Debra E. Huffman, Dayanis Acosta, Yulia Serebrennikova, Luis García-Rubio

Claro Scientific, LLC, 10100 Dr. Martin Luther King Jr. Street North, St. Petersburg, Florida 33710

German F. Leparc

Florida Blood Services, A Division of OneBlood, Inc., 10100 Dr. Martin Luther King Jr. Street North, St. Petersburg, Florida 33710

J. Biomed. Opt. 17(10), 107002 (Oct 01, 2012). doi:10.1117/1.JBO.17.10.107002
History: Received June 12, 2012; Revised August 3, 2012; Accepted September 5, 2012
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Abstract.  The identification of bacterial pathogens from culture is critical to the proper administration of antibiotics and patient treatment. Many of the tests currently used in the clinical microbiology laboratory for bacterial identification today can be highly sensitive and specific; however, they have the additional burdens of complexity, cost, and the need for specialized reagents. We present an innovative, reagent-free method for the identification of pathogens from culture. A clinical study has been initiated to evaluate the sensitivity and specificity of this approach. Multiwavelength transmission spectra were generated from a set of clinical isolates including Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Staphylococcus aureus. Spectra of an initial training set of these target organisms were used to create identification models representing the spectral variability of each species using multivariate statistical techniques. Next, the spectra of the blinded isolates of targeted species were identified using the model achieving >94% sensitivity and >98% specificity, with 100% accuracy for P. aeruginosa and S. aureus. The results from this on-going clinical study indicate this approach is a powerful and exciting technique for identification of pathogens. The menu of models is being expanded to include other bacterial genera and species of clinical significance.

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© 2012 Society of Photo-Optical Instrumentation Engineers

Citation

Jennifer M. Smith ; Debra E. Huffman ; Dayanis Acosta ; Yulia Serebrennikova ; Luis García-Rubio, et al.
"Reagent-free bacterial identification using multivariate analysis of transmission spectra", J. Biomed. Opt. 17(10), 107002 (Oct 01, 2012). ; http://dx.doi.org/10.1117/1.JBO.17.10.107002


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