This material was originally published in the Purdue Cytometry CD-ROM Series
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Flow Cytometry and Microbiology


Antibiotic sensitivity using LIVE/DEAD BacLight Viability kit.


James R. Cornelius and George F. Babcock
Shriners Burn Institute
3229 Burnet Avenue
Cincinnati, OH 45229-3095, USA

email: babcocgf@ucbeh.san.uc.edu


Introduction
With the movement of flow cytometry into the clinical microbiology lab, the need for a rapid method for antibiotic sensitivity testing has emerged. Recently, several dyes used to determine cell viability have become available making flow cytometry an attractive option in measuring bacterial viability. A major weakness of the methods currently used is their inability to adequately account for heterogeneity in microbial populations.

The LIVE/DEAD BacLight Viability Kit (Molecular Probes, Inc.) enables distinction of live and dead bacteria even in mixed populations containing a variety of bacterial types. The kit incorporates two proprietary nucleic acid stains which differ in their ability to penetrate bacterial cell membranes. Bacteria with intact membranes allow only one dye to enter the cell and fluoresce green, whereas those with damaged membranes allow both dyes to enter and fluoresce red or red/green. The heterogeneous staining pattern produced by the BacLight kit has not been fully defined as to which populations represent viable and which represent non-viable organisms. This matter is further complicated when testing antibiotics which can be bacteriostatic or bactericidal.

In this study, we examined the viability of various populations of bacteria as defined by the staining patterns produced by the BacLight kit following treatment with disinfectants, heat, or antibiotics. Bacterial populations (histogram regions) were defined by the staining pattern observed by flow cytometric analysis. Viability was determined by sorting and plating on media or autocloning directly into broth. Each region was arbitrarily numbered (1-5) and characterized as viable, non-viable, or mixed.


Data Examples



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