| Detection and identification of bacteria using antibiotic susceptibility and a multi-array electrochemical sensor with pattern recognition. | |
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MedLine Citation:
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PMID: 17169547 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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This work proposes the use of amperometric signals generated by a 96-well multi-array dissolved oxygen multi-electrode sensor (DOX) coupled with principal component analysis for continuous monitoring, identification and differentiation of bacteria. Two types of differentiation mechanisms were tested: (1) direct monitoring of respiratory activity via oxygen consumption and (2) quantification of the effect of three broad-spectrum antibiotics on bacteria growth and respiration over time. Five species of bacteria were examined including: Escherichia coli, Escherichia adecarboxylata, Comamonas acidovorans, Corynebacterium glutamicum and Staphylococcus epidermidis. The addition of small concentrations of antibiotics to the growth medium alters the oxygen consumption of the cells and a unique fingerprint is created for a specific cell. This fingerprint is shown to evolve over a specific concentration range that is dependant of instrumental constraints of the DOX system. The application of principal component analysis (PCA) to classify the data was also examined. It was shown that bacteria could be classified simply by their oxygen consumption rates over a varying concentration range. Discrimination between species can also be increased by the effects of the antibiotics on the oxygen consumption of varying concentrations of cells. The proposed DOX-PCA system illustrates a generic template that can be tailored to meet specific research goals by the selection of specific cell/antibiotic combinations and concentrations. |
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Authors:
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Jason Karasinski; Leslie White; Yachao Zhang; Eric Wang; Silvana Andreescu; Omowunmi A Sadik; Barry K Lavine; Mehul Vora |
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Publication Detail:
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Type: Evaluation Studies; Journal Article; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S. Date: 2006-12-12 |
Journal Detail:
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Title: Biosensors & bioelectronics Volume: 22 ISSN: 0956-5663 ISO Abbreviation: Biosens Bioelectron Publication Date: 2007 May |
Date Detail:
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Created Date: 2007-04-02 Completed Date: 2007-06-27 Revised Date: 2009-07-14 |
Medline Journal Info:
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Nlm Unique ID: 9001289 Medline TA: Biosens Bioelectron Country: England |
Other Details:
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Languages: eng Pagination: 2643-9 Citation Subset: IM |
Affiliation:
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Department of Chemistry, State University of New York-Binghamton, P.O. Box 6000, Binghamton, NY 13902, USA. |
Export Citation:
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APA/MLA Format Download EndNote Download BibTex |
| MeSH Terms | |
Descriptor/Qualifier:
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Algorithms Anti-Bacterial Agents / administration & dosage* Artificial Intelligence Bacteria / classification, drug effects, isolation & purification*, metabolism* Biosensing Techniques / instrumentation*, methods Cell Culture Techniques / instrumentation, methods Electrochemistry / instrumentation*, methods Equipment Design Equipment Failure Analysis Flow Injection Analysis / instrumentation, methods Microbial Sensitivity Tests / instrumentation*, methods Oxygen Consumption / physiology Pattern Recognition, Automated / methods* Robotics / instrumentation, methods |
| Chemical | |
Reg. No./Substance:
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0/Anti-Bacterial Agents |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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