ABSTRACT Enhanced tolerance of biofilm-associated bacteria to antibiotic treatments is likely due to a combination of factors, including changes in cell physiology as bacteria adapt to biofilm growth and the inherent physiological heterogeneity of biofilm bacteria. In this study, a transcriptomics approach was used to identify genes differentially expressed during biofilm growth of Pseudomonas aeruginosa . These genes were tested for statistically significant overlap, with independently compiled gene lists corresponding to stress responses and other putative antibiotic-protective mechanisms. Among the gene groups tested were those associated with biofilm response to tobramycin or ciprofloxacin, drug efflux pumps, acyl homoserine lactone quorum sensing, osmotic shock, heat shock, hypoxia stress, and stationary-phase growth. Regulons associated with Anr-mediated hypoxia stress, RpoS-regulated stationary-phase growth, and osmotic stress were significantly enriched in the set of genes induced in the biofilm. Mutant strains deficient in rpoS , relA and spoT , or anr were cultured in biofilms and challenged with ciprofloxacin and tobramycin. When challenged with ciprofloxacin, the mutant strain biofilms had 2.4- to 2.9-log reductions in viable cells compared to a 0.9-log reduction of the wild-type strain. Interestingly, none of the mutants exhibited a statistically significant alteration in tobramycin susceptibility compared to that with the wild-type biofilm. These results are consistent with a model in which multiple genes controlled by overlapping starvation or stress responses contribute to the protection of a P. aeruginosa biofilm from ciprofloxacin. A distinct and as yet undiscovered mechanism protects the biofilm bacteria from tobramycin.
A computer model of biofilm dynamics was adapted to incorporate the activity of an antimicrobial agent on bacterial biofilm. The model was used to evaluate the plausibility of two mechanisms of biofilm antibiotic resistance by qualitative comparison with data from a well-characterized experimental system (H. Anwar, J. L. Strap, and J. W. Costerton, Antimicrob. Agents Chemother. 36:1208-1214, 1992). The two mechanisms involved either depletion of the antibiotic by reaction with biomass or physiological resistance due to reduced bacterial growth rates in the biofilm. Both mechanisms predicted the experimentally observed resistance of 7-day-old Pseudomonas aeruginosa biofilms compared with that of 2-day-old ones. A version of the model that incorporated growth rate-dependent killing predicted reduced susceptibility of thicker biofilms because oxygen was exhausted within these biofilms, leading to very slow growth in part of the biofilm. A version of the model that incorporated a destructive reaction of the antibiotic with biomass likewise accounted for the relative resistance of thicker biofilms. Resistance in this latter case was due to depletion of the antibiotic in the bulk fluid rather than development of a gradient in the antibiotic concentration within the biofilm. The modeling results predicted differences between the two cases, such as in the survival profiles within the biofilm, that could permit these resistance mechanisms to be experimentally distinguished.
The penetration of ampicillin and ciprofloxacin through biofilms formed by Klebsiella pneumoniae was confirmed by transmission electron microscopic observation of antibiotic-affected cells at the distal edge of the biofilm. Because the bacteria nevertheless survived antibiotic treatment, some protective mechanism other than inadequate penetration must have been at work in the biofilm.
Abstract The growth of immobilized Escherichia coli was analyzed by pulse‐chase radioisotope labeling of the cell mass with 35 SO 4 2− and subsequent liquid emulsion autoradiography of thin cross sections of the cell aggregate. Bacteria were retained in a planar aggregate on a microporous membrane and grown anaerobically on a phosphate‐buffered medium with glucose as the sole carbon and energy source. A mathematical model of immobilized cell growth and convection was used to predict the distribution of label in the cell mass and permit information about both the magnitude and variation in the intrinsic growth rate to be extracted. Growing zone dimensions ranging from 4 to 48 μm and growth rates from 0.28 to 0.5 h −1 were found. Data collected at low glucose concentrations were consistent with a zero‐order description of intrinsic growth kinetics. At high glucose concentrations, conditions under which the system was subject to significant pH inhibition, the data were best described by the prediction of a first‐order kinetic model. When coupled with a suitable analytical framework, the combination of radioisotope labeling and autoradiography provides a general method for characterizing immobilized cell growth rates.
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