Date Published: October 15, 2012
Publisher: Public Library of Science
Author(s): Atsushi Wada, Mari Kono, Sawako Kawauchi, Yuri Takagi, Takashi Morikawa, Kunihiro Funakoshi, Markus M. Heimesaat. http://doi.org/10.1371/journal.pone.0047093
For precise diagnosis of urinary tract infections (UTI), and selection of the appropriate prescriptions for their treatment, we explored a simple and rapid method of discriminating gram-positive and gram-negative bacteria in liquid samples.
We employed the NaOH-sodium dodecyl sulfate (SDS) solution conventionally used for plasmid extraction from Escherichia coli and the automated urine particle analyzer UF-1000i (Sysmex Corporation) for our novel method. The NaOH-SDS solution was used to determine differences in the cell wall structures between gram-positive and gram-negative bacteria, since the tolerance to such chemicals reflects the thickness and structural differences of bacterial cell walls. The UF-1000i instrument was used as a quantitative bacterial counter. We found that gram-negative bacteria, including E. coli, in liquid culture could easily be lysed by direct addition of equal volumes of NaOH-SDS solution. In contrast, Enterococcus faecalis, which is a gram-positive bacterium, could not be completely lysed by the solution. We then optimized the reaction time of the NaOH-SDS treatment at room temperature by using 3 gram-positive and 4 gram-negative bacterial strains and determined that the optimum reaction time was 5 min. Finally, in order to evaluate the generalizability of this method, we treated 8 gram-positive strains and 8 gram-negative strains, or 4 gram-positive and 4 gram-negative strains incubated in voluntary urine from healthy volunteers in the same way and demonstrated that all the gram-positive bacteria were discriminated quantitatively from gram negative bacteria using this method.
Using our new method, we could easily discriminate gram-positive and gram-negative bacteria in liquid culture media within 10 min. This simple and rapid method may be useful for determining the treatment course of patients with UTIs, especially for those without a prior history of UTIs. The method may be easily applied in order to obtain additional information for clinical prescriptions from bacteriuria.
During the initial treatment of infectious diseases, including urinary tract infections (UTIs), physicians prescribe antibiotics empirically because of a lack of information on the pathogen. Although the burden of UTIs for most otherwise healthy patients is usually not considerable, prompt diagnosis and treatment are important, especially for certain subpopulations, such as children, pregnant women, and the elderly. Delays in the diagnosis and treatment of UTIs increase the risk of severe outcomes, such as tissue invasion and sepsis –.
In this paper, we described a rapid and simple method for discriminating gram-positive and gram-negative bacteria in liquid media. This method was based on 2 components. The first was the use of the NaOH-SDS lysis solution of the plasmid extraction method for Gram discrimination. The NaOH-SDS lysis solution was developed for the plasmid extraction method of E. coli more than 30 years ago , . The method, which is also called the alkaline method, is by far the most popular method because of its simplicity, relatively low cost, and reproducibility. However, it is well known among molecular biologists that have experience studying gram-positive bacteria that the NaOH-SDS lysis solution of the original plasmid extraction method for E. coli does not lyse gram-positive bacteria effectively , . The second was the use of the automated urine particle analyzer UF-1000i as a flow cytometer for bacterial cell counting. The UF-1000i can count the numbers of bacteria in a urine specimen in 1 min with its separate flow channel in which the nucleic acids of the bacteria are stained with a specific fluorescent dye and discriminated from cell debris . The results were shown in the main window of its analytical software and the operator can get the numbers of bacteria and the pattern of the bacterial counting channel at a glance (Figure S3).