Center for Biofilm Engineering and Department of Chemical and Biological Engineering, Montana State University Bozeman, Bozeman, MT 59717-3980, USA
Correspondence
Philip S. Stewart
phil_s{at}erc.montana.edu
![]() |
ABSTRACT |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
![]() |
INTRODUCTION |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
Among the explanations that have been offered for the reduced susceptibility of micro-organisms in biofilms are slow antimicrobial penetration, slow growth, and the formation of a protected subpopulation of persister cells (Spoering & Lewis, 2001; Stewart & Costerton, 2001
). Here we offer a few thoughts on each of these mechanisms before focusing our attention on the last.
Certain antimicrobial agents can fail to penetrate biofilms. This occurs when the antimicrobial is neutralized in the surface layers of the biofilm faster than it diffuses into the biofilm (Stewart et al., 2000). The rapid reaction required to prevent penetration has only been demonstrated for highly reactive antimicrobials, such as the oxidizing biocides chlorine and hydrogen peroxide. Most antimicrobial agents probably do penetrate the biofilm.
Biofilms are thought to contain cells in a spectrum of growth states from rapidly growing to not growing at all (Brown et al., 1988; Sufya et al., 2003
; Xu et al., 2000
). This variety of physiological states would be protective because non-growing or stationary-phase cells are known to be less susceptible to antimicrobial challenge. This mechanism surely contributes to biofilm protection from killing by those agents, notably antibiotics, which target macromolecular synthesis.
One of the newest hypotheses for the reduced susceptibility of biofilms to antimicrobials invokes the formation of a special class of protected cells termed persisters (Spoering & Lewis, 2001). Persisters are thought by some to be cells that have differentiated into an inactive, but highly protected state. Persisters might resemble spores in some ways. The persister hypothesis is attractive because it could explain protection from antimicrobial agents of very different chemistries and modes of action. The existence of persister cells is suggested by killing data that indicate most cells in a biofilm dying, with a subpopulation that persists even during prolonged exposure or with elevated concentrations of antimicrobial agent (Spoering & Lewis, 2001
). The persister population has been estimated to constitute perhaps 0·110 % of all cells in the biofilm. These cells, it is hypothesized, can survive a catastrophic antimicrobial challenge and reseed the biofilm.
Though we use the term persister in this article, an alternative and possibly synonymous term is phenotypic variant. Phenotypic variants are cells that have spontaneously switched from the wild-type state into a variant state in which the cell exhibits altered phenotypic properties. These properties may include enhanced antimicrobial tolerance (Drenkard & Ausubel, 2002; Balaban et al., 2004
).
Previous modelling work on antimicrobials and biofilms has addressed aspects of antimicrobial neutralization and penetration (Chen & Stewart, 1996; Dibdin et al., 1996
; Dodds et al., 2000
; Nichols et al., 1989
; Stewart et al., 1996
), slow growth (Roberts & Stewart, 2004
; Stewart, 1994
) and regrowth (Sanderson & Stewart, 1997
; Stewart et al., 1996
). No mathematical models of persister formation in biofilms have been described.
The main objective of this study was to investigate whether persister cell formation could confer increased protection from antimicrobial agents to a population of biofilm micro-organisms, compared to cells in free aqueous suspension. The comparison to free-floating cells is important. It is intuitively obvious that persister cell formation will reduce the antimicrobial susceptibility of any population, whether biofilm or planktonic. The observation that we seek to explain is that cells in a biofilm are less susceptible than planktonic cells. Can persister formation account for this difference? A second objective of this theoretical investigation was to predict spatial and temporal features of persister dynamics in biofilms. Such predictions might some day guide experimental tests of this protective mechanism.
![]() |
THEORY |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
We begin by considering the transformations between live and persister cell states. Transformations that produce dead cells will be added subsequently. One can imagine two broad possibilities for how persister formation could afford greater protection to biofilm populations compared to planktonic populations. One possibility is that the frequency of persister formation is higher in a biofilm than it is in a planktonic culture. This would require the existence of some biofilm-specific regulatory mechanism. The other possibility is that persister cells are formed at the same rate in biofilms, but are retained more effectively in biofilms. We have tested the second conjecture in this investigation. No difference in the rate of formation of persister cells in the planktonic and biofilm states was assumed. The rate of persister cell formation was simply taken to be directly proportional to the live cell concentration. The reversion of persister cells to the live cell state was assumed to depend on the presence of the metabolic substrate (Spoering & Lewis, 2001; Sufya et al., 2003
). Persister cells exposed to this substrate reverted to live cells faster than persister cells that were deprived of the substrate.
The mathematical form for the cell transformations described above is conveyed below through the material balances derived for planktonic cultures. In a planktonic continuous stirred-tank reactor (chemostat) at steady state, the live cell balance simplifies to
![]() |
![]() |
|
![]() |
![]() |
![]() |
Killing of persister cells followed the same form, but the disinfection rate coefficient was different, and smaller, than that used for live cells. Persister cell killing in batch culture is described by
![]() |
![]() |
The basic biofilm model used in this investigation, and its solution, have been described in detail elsewhere (Stewart, 1994; Stewart et al., 1996
). The model was based on the conceptual and mathematical formulation derived by Wanner & Gujer (1986)
. The model described the growth of a uniformly thick biofilm in a continuous-flow stirred-tank reactor a chemostat with wall growth. Biologically, the system was conceptualized as a single species whose growth rate was determined by the concentration of a single substrate, according to Monod kinetics. Some of the processes integrated in this model included bulk flow into and out of the reactor, transport of solutes into the biofilm by Fickian diffusion, substrate consumption by the micro-organism, microbial growth, transport of cells within the biofilm by advective displacement, detachment of biomass from the surface of the film, and killing of micro-organisms in the presence of an antibiotic. Macroscopic material balances around the entire reactor vessel were coupled to one-dimensional differential material balances that described processes occurring within the biofilm at the microscale.
Base-case parameter values are summarized in Table 1. For this study, the dilution rate was set to a very large value (417 h1, 1000 times the maximum specific growth rate of 0·42 h1). This means that there can be essentially no growth of planktonic cells in the reactor vessel and that the bulk fluid concentration of substrate or antibiotic that the biofilm is exposed to is essentially equal to the influent concentration.
The dynamics of biofilm thickness were determined by the balance of net growth and detachment. In this model, detachment is treated as erosion from the surface of the biofilm at an erosion velocity proportional to the square of the biofilm thickness. The initial biofilm thickness was set to the desired simulation thickness by adjusting the detachment rate coefficient. The value of the detachment coefficient used was the value that yielded the desired steady-state thickness in a simulation in which only live cells were present.
The initial volume fractions of live, persister and dead cells were set to 0·2, 108 and 108, respectively.
![]() |
RESULTS AND DISCUSSION |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
|
|
The same mathematical descriptions of persister formation and reversion that were used in the biofilm model can also be solved in a chemostat with no biofilm present. In continuous planktonic culture, the fraction of persisters was predicted to increase as the dilution rate was decreased (Fig. 3). The minimum persister fraction was calculated to occur at the washout dilution rate. For the parameter values used in this study, the minimum persister cell fraction in a chemostat was calculated to be 0·0046. To reach the same level of persisters computed for a 100 µm thick biofilm (fP=0·165), the dilution rate in the chemostat would have to be just under 0·01 h1. To reach the same level of persisters computed for a 400 µm thick biofilm, the chemostat dilution rate would need to be 0·0037 h1. Such low dilution rates are rarely, if ever, applied in experimental studies. These calculations demonstrate, however, that the degree of protection afforded by persister cell formation in a biofilm could be realized in a very slowly growing planktonic culture.
|
|
We wish to emphasize that accumulation and retention of persisters in the biofilm does not depend on specific regulatory mechanisms that increase the rate of persister formation specifically in the biofilm mode of growth. Our results do not disprove such a mechanism, but they do show that it is not necessary to assume such regulation. Our predictions regarding persister competition in biofilms are conservative in that we have assumed that persisters do not grow at all. If persister cells can grow, their ability to compete for space in the biofilm would only be improved.
Persisters continue to accumulate even after biofilm thickness has plateaued (Fig. 1). The time scale for this accumulation, which confers steadily decreasing susceptibility of the biofilm population, was several to many days. This is believed to be the first theoretical description of an explanation for the increased antimicrobial tolerance of ageing biofilms.
When an antimicrobial treatment was simulated, bacteria near the biofilm surface were rapidly killed (Fig. 2b). Persister cells, which were assumed to be invulnerable to the antimicrobial, were unaffected. After prolonged (24 h) antimicrobial exposure, the biofilm contained mostly dead cells and persister cells (Fig. 2c
). The remaining persister cells quickly reverted and allowed the biofilm to regrow after antibiotic treatment ceased (Fig. 5
). During the day-long antimicrobial exposure, the biofilm thickness decreased from 100 µm to 19·4 µm. This decrease was due to continuing biofilm detachment during a period when growth had been greatly suppressed. Within 24 h after the end of antimicrobial dosing, the biofilm thickness was back to 98 µm, nearly its original thickness. This recovery reflects the rapid growth of the surviving cells.
|
![]() |
ACKNOWLEDGEMENTS |
---|
![]() |
REFERENCES |
---|
![]() ![]() ![]() ![]() ![]() ![]() |
---|
Brown, M. R. W., Allison, D. G. & Gilbert, P. (1988). Resistance of bacterial biofilms to antibiotics: a growth-rate related effect? J Antimicrob Chemother 22, 777783.[Medline]
Chen, X. & Stewart, P. S. (1996). Chlorine penetration into artificial biofilm is limited by a reaction-diffusion interaction. Environ Sci Technol 30, 20782083.[CrossRef]
Dibdin, G. H., Assinder, S. J., Nichols, W. W. & Lambert, P. A. (1996). Mathematical model of beta-lactam penetration into a biofilm of Pseudomonas aeruginosa while undergoing simultaneous inactivation by released beta-lactamases. J Antimicrob Chemother 38, 757769.[Abstract]
Dodds, M. G., Grobe, K. J. & Stewart, P. S. (2000). Modeling biofilm antimicrobial resistance. Biotechnol Bioeng 68, 456465.[CrossRef][Medline]
Drenkard, E. & Ausubel, F. M. (2002). Pseudomonas biofilm formation and antibiotic resistance are linked to phenotypic variation. Nature 416, 740742.[CrossRef][Medline]
Kissel, J. C., McCarty, P. L. & Street, R. L. (1984). Numerical simulation of mixed-culture biofilm. J Environ Eng 110, 393411.
Laspidou, C. S. & Rittmann, B. E. (2004a). Modeling the development of biofilm density including active bacteria, inert biomass, and extracellular polymeric substances. Water Res 38, 33493361.[CrossRef][Medline]
Laspidou, C. S. & Rittmann, B. E. (2004b). Evaluating trends in biofilm density using the UMCCA model. Water Res 38, 33623372.[CrossRef][Medline]
Nichols, W. W., Evans, M. J., Slack, M. P. E. & Walmsley, H. L. (1989). The penetration of antibiotics into aggregates of mucoid and non-mucoid Pseudomonas aeruginosa. J Gen Microbiol 135, 12911303.[Medline]
Picioreanu, C., Kreft, J.-U. & van Loosdrecht, M. C. M. (2004). Particle-based multidimensional multispecies biofilm model. Appl Environ Microbiol 70, 30243040.
Rittmann, B. E. & Manem, J. A. (1992). Development and experimental evaluation of a steady-state, multispecies biofilm model. Biotechnol Bioeng 39, 914922.[CrossRef]
Roberts, M. E. & Stewart, P. S. (2004). Modeling antibiotic tolerance in biofilms by accounting for nutrient limitation. Antimicrob Agents Chemother 48, 4852.
Sanderson, S. S. & Stewart, P. S. (1997). Evidence of bacterial adaptation to monochloramine in Pseudomonas aeruginosa biofilms and evaluation of biocide action model. Biotechnol Bioeng 56, 201209.[CrossRef]
Spoering, A. L. & Lewis, K. (2001). Biofilms and planktonic cells of Pseudomonas aeruginosa have similar resistance to killing by antimicrobials. J Bacteriol 183, 67466751.
Stewart, P. S. (1994). Biofilm accumulation model that predicts antibiotic resistance of Pseudomonas aeruginosa biofilms. Antimicrob Agents Chemother 38, 10521058.[Abstract]
Stewart, P. S. & Costerton, J. W. (2001). Antibiotic resistance of bacteria in biofilms. Lancet 358, 135138.[CrossRef][Medline]
Stewart, P. S., Hamilton, M. A., Goldstein, B. R. & Schneider, B. T. (1996). Modeling biocide action against biofilms. Biotechnol Bioeng 49, 445455.[CrossRef]
Stewart, P. S., McFeters, G. A. & Huang, C.-T. (2000). Biofilm control by antimicrobial agents. In Biofilms II: Process Analysis and Applications, pp. 373405. Edited by J. D. Bryers. New York: Wiley-Liss.
Sufya, N., Allsion, D. G. & Gilbert, P. (2003). Clonal variation in maximum specific growth rate and susceptibility towards antimicrobials. J Appl Microbiol 95, 12611267.[CrossRef][Medline]
Wanner, O. & Gujer, W. (1986). A multispecies biofilm model. Biotechnol Bioeng 28, 314328.
Xu, K. D., McFeters, G. A. & Stewart, P. S. (2000). Biofilm resistance to antimicrobial agents. Microbiology 146, 547549.[Medline]
Received 7 June 2004;
revised 28 September 2004;
accepted 29 September 2004.
HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
INT J SYST EVOL MICROBIOL | MICROBIOLOGY | J GEN VIROL |
J MED MICROBIOL | ALL SGM JOURNALS |