Jason Karasinski | PubMed Health

PubMed2006

Detection and identification of bacteria using antibiotic susceptibility and a multi-array electrochemical sensor with pattern recognition.

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.

Algorithms↗

PubMed2005

Multiarray sensors with pattern recognition for the detection, classification, and differentiation of bacteria at subspecies and strain levels.

This work describes the integration of a fully autonomous electrochemical biosensor with pattern recognition techniques for the detection and classification of bacteria at subspecies and strain level. The system provides a continuous, real-time monitoring of bacteria activity upon exposure to antibiotics. The system utilizes 96-well-type electrodes array (DOX-dissolved oxygen sensor) with principal component analysis (PCA) for rapid and routine classification of different classes of bacteria and related strains. A representative sample of a section of the bacteria kingdom has been analyzed and classified using the proposed DOX-PCA system, including the following: Corynebacterium glutamicum, Micrococcus luteus, Staphylococcus epidermidis, Yersinia ruckeri, Escherichia adecarboxylata, Comamonas acidovorans, Alcaligenes odorans, Bacillus globigii, and three strains of Escherichia coli (K12, SM10, ATCC 25922). The new classification scheme is based on the hypothesis that, under identical experimental conditions, various bacteria consume oxygen at different rates and are affected in different ways by selected antibiotics. Thus, the response of the individual electrode in the array is indirectly altered, compared to that of cells growing on medium, by the addition of the antibiotic. By using three different antibiotics in separate wells, a unique fingerprint can be created for a specific bacterium. With the proposed DOX-PCA system, classification of bacteria was achieved at subspecies and strain level in real time. This study represents a basic research tool that may allow researchers to rapidly detect, quantify, and classify bacteria type at subspecies and strain levels.

Ampicillin↗