Assessment of the Antibacterial Efficacy of Halicin against Pathogenic Bacteria

Artificial intelligence (AI) is a new technology that has been employed to screen and discover new drugs. Using AI, an anti-diabetic treatment (Halicin) was nominated and proven to have a unique antibacterial activity against several harmful bacterial strains, including multidrug-resistant bacteria. This study aims to explore the antibacterial effect of halicin and microbial susceptibility using the zone of inhibition and the minimum inhibition concentration (MIC) values while assessing the stability of stored halicin over a period of time with cost-effective and straightforward methods. Linear regression graphs were constructed, and the correlation coefficient was calculated. The new antibacterial agent was able to inhibit all tested gram-positive and gram-negative bacterial strains, but in different concentrations-including the A. baumannii multidrug-resistant (MDR) isolate. The MIC of halicin was found to be 16 μg/mL for S. aureus (ATCC BAA-977), 32 μg/mL for E. coli (ATCC 25922), 128 μg/mL for A. baumannii (ATCC BAA-747), and 256 μg/mL for MDR A. baumannii. Upon storage, the MICs were increased, suggesting instability of the drug after approximately a week of storage at 4 °C. MICs and zones of inhibition were found to be high (R = 0.90 to 0.98), suggesting that halicin has a promising antimicrobial activity and may be used as a wide-spectrum antibacterial drug. However, the drug's pharmacokinetics have not been investigated, and further elucidation is needed.

Accurate assessment of antibiotic susceptibility and screening resistant strains of a bacterial population by linear gradient plate

The dynamics of a bacterial population exposed to the minimum inhibitory concentration (MIC) of an antibiotic is an important issue in pharmacological research. Therefore, a novel antibiotic susceptibility test is urgently needed that can both precisely determine the MIC and accurately select antibiotic-resistant strains from clinical bacterial populations. For this purpose, we developed a method based on Fick's laws of diffusion using agar plates containing a linear gradient of antibiotic. The gradient plate contained two layers. The bottom layer consisted of 15 mL agar containing the appropriate concentration of enrofloxacin and allowed to harden in the form of a wedge with the plate slanted such that the entire bottom was just covered. The upper layer consisted of 15 mL plain nutrient agar added with the plate held in the horizontal position. After allowing vertical diffusion of the drug from the bottom agar layer for 12 h, the enrofloxacin concentration was diluted in proportion to the ratio of the agar layer thicknesses. The uniform linear concentration gradient was verified by measuring the enrofloxacin concentration on the agar surface. When heavy bacterial suspensions were spread on the agar surface and incubated for more than 12 h, only resistant cells were able to form colonies beyond the boundary of confluent growth of susceptible cells. In this way, the true MIC of enrofloxacin was determined. The MICs obtained using this linear gradient plate were consistent with those obtained using conventional antibiotic susceptibility tests. Discrete colonies were then spread onto a gradient plate with higher antibiotic concentrations; the boundary line increased significantly, and gene mutations conferring resistance were identified. This new method enables the rapid identification of resistant strains in the bacterial population. Use of the linear gradient plate can easily identify the precise MIC and reveal the dynamic differentiation of bacteria near the MIC. This method allows the study of genetic and physiological characteristics of individual strains, and may be useful for early warning of antibiotic resistance that may occur after use of certain antimicrobial agents, and guide clinical treatment.

Calibration of fusidic acid disk diffusion susceptibility testing of Staphylococcus areus

Single strain regression analysis, SRA, was used to calibrate disk diffusion fusidic acid susceptibility testing of Staphylococcus aureus in two laboratories using different standard methods but the same interpretative MIC limits. SRA equation constants were calculated using five different fusidic acid disk contents (1.5, 5, 15, 50, 150 microg). These disks were tested on five separate occasions against quality control strain S. aureus ATCC 29213. The National Committee for Clinical Laboratory Standards (NCCLS) method was employed in Tartu, Estonia (TE) and the Swedish Reference Group for Antibiotics (SRGA) method in Sweden at the Karolinska Hospital (KS). SRA constants obtained were used for calculating zone breakpoints corresponding to MIC breakpoints recommended by the SRGA (S < or = 0.5 mg/L, R > or = 1 mg/L). Zone diameter histograms from KS, performed with a 50 microg disk, and from TE, using a 10 microg disk, showed a clustering of wild type strains around 41 mm and 30 mm, respectively, reflecting differences in methodology. Zone breakpoints calculated from the equations were validated by comparison with the histograms. Breakpoints were also calculated for a suggested lower disk content in Sweden, 10 microg, and validated in tests of clinical isolates and by histogram analysis.

[in vitro activity of telithromycin against Haemophilus influenzae]

The aim of this study was to evaluate the in vitro activity of telithromycin against 142 strains of Haemophilus influenzae using determination of MICs by agar dilution method and to evaluate the correlation between MICs and inhibition diameter zones obtained by disk diffusion testing. MIC50 and MIC90 of telithromycin were 1 and 2 mg/L respectively. Telithromycin activity against H. influenzae was similar to that of azithromycin, superior to erythromycin and clarithromycin and irrespective of the susceptibility to betalactams. Distribution of diameter zones showed a similar pattern to that of MICs but correlation between MICs and diameter zones was poor with correlation coefficients inferior to 0.5 whatever the agar media used.

Disk diffusion susceptibility tests: need for laboratory-specific breakpoints

Significant changes were observed in the measured resistance levels of Escherichia coli and Staphylococcus aureus when the Biodisk disk susceptibility test method used in 1992 was replaced with another commercial method, Oxoid. For example, when non-species-specific breakpoints were used, the frequency of cephalotin-resistant E. coli was 12% of all isolates in 1992 but only 4% in 1993; the corresponding figures for the intermediately resistant isolates were 84% and 8%. The population distribution histograms were however, practically unchanged. Thus, the resistance percentages apparently did not reflect the real development of resistance. Similar findings were also made for several other antimicrobials. Susceptibility test breakpoints should therefore be examined separately for all bacterial species in each laboratory, and the application of adjusted laboratory-specific breakpoints should be considered. For this purpose, the WHONET computer program provides excellent assistance.

Antibiotic disk diffusion testing revisited. Single strain regression analysis. Review article

The standardized (NCCLS, ICS, DIN etc.) disk diffusion method is the most widespread technique for antibiotic susceptibility testing. Interpretive zone breakpoints are calculated from the regular regression line between minimum inhibitory concentrations (MIC) of bacterial isolates and the corresponding inhibition zone diameters around the disk containing the antibiotic. Studies of the regression line has revealed marked differences between different bacterial species. A newly described equation, the single strain regression analysis (SRA) equation, can be used to determine the regression line constants for individual strains. This method was applied to ciprofloxacin and S. aureus, E. faecalis, E. coli, P. mirabilis, P. aeruginosa, and P. maltophilia. The slope and intercept constants were determined for all 40 strains and showed a strong similarity within each species. A close similarity was also observed between the two Pseudomonas species and between S. aureus and E. faecalis. When the regression lines calculated by SRA for individual strains were extrapolated towards higher MIC values, the lines obtained for the more susceptible strains predicted the zones of more resistant strains within the species. The applications of SRA to several other antibiotics and bacterial species in earlier studies were reviewed. One exception to the predictive power of SRA has been detected earlier, H. influenzae and erythromycin. This led to the formulation of the standard curve regression analysis (SCA) equation which requires the use of two or more strains. Methodological aspects of SRA/SCA applications were presented. Three areas are particularly well suited for the use of SRA/SCA: 1. Calculation of interpretive zone breakpoints corresponding to recommended MIC limits in the individual laboratory. 2. Analysis of the effects of various disk contents of antibiotic on the resulting inhibition zones for various bacteria when new antibiotics are introduced. 3. Analytical tool as part of external quality control programmes.

Types of interpretive errors in susceptibility testing. Zone breakpoints for norfloxacin disk diffusion testing

A total of 548 strains of the eleven most common urinary tract pathogens were investigated for possible errors in norfloxacin susceptibility tests comparing MIC determinations with disk diffusion assays. Most strains were found to be sensitive with MIC-90 values below 1.0 for the Enterobacteriaceae while the classical nalidixic acid resistant species, the gram-positive bacteria and Pseudomonas aeruginosa, were less susceptible to norfloxacin with MIC-90 above 1.0 mg/l. MIC-values close to interpretive MIC-limits were recorded for S. faecalis and S. agalactiae using the recommendations of the national Committee for Clinical Laboratory Standards (NCCLS) (susceptible, S less than or equal to 4.0) and for P. aeruginosa and S. aureus using the Swedish Reference Group for Antibiotics (SRGA) standards (S less than or equal to 1.0). Susceptibility interpretations for these species showed a lack of accuracy consistent with methodological problems of reproducibility, an error called type I. The changes in the MIC-limits required for these strains to correct the error would be S less than or equal to 4 for P. aeruginosa and S. aureus, S less than or equal to 8 for S. agalactiae and S less than or equal to 0.5 for S. faecalis. A type II error, occurring when a bacterial species shows a regression line different from the regular line, was also identified for S. saprophyticus. The use of breakpoints derived from single strains regression analysis corrected this error and also reduced the frequency of similar misinterpretations in other species. The term "species-specific MIC-limits" should be introduced along with the established concept of "species-specific interpretive zone breakpoints" to allow for the correction of type I interpretive errors. Type II errors can be corrected by using species-specific interpretive breakpoints, either issued by reference laboratories or derived by calculations from single-strain regression analysis in the individual laboratory.