Biomedical Engineering Reference
In-Depth Information
important to distinguish between continuous and discontinuous biofilms to
have a more accurate prediction for spatial distribution and permeability
reduction (Rittmann 1993). It should be assumed that a biofilm is composed
of two different parts, that is, base and surface films. The base film com-
ponents are packed and continuous, while the surface film is discontinuous
(Gujer and Wanner 1990). One of the very common discrete-stochastic meth-
ods used in this field is cellular automata (CA), in which nutrient and biomass
are simulated as individual particles (Wanner et al. 2006). In this approach,
the biofilm is represented as a continuous layer and its properties primarily
change in vertical direction.
A number of studies focused on the estimation of the steady state thick-
ness of biofilms (Fouad and Bhargava 2005; Qi and Morgenroth 2005; Gapes
et al. 2006). In some of these (Rittmann and McCarty 1980; Rittmann and
Manem 1992), it was assumed that there is a minimum substrate concentra-
tion that can support biofilm development and that below that level biofilm
will not develop. Wanner and Gujer (1986) developed a multicomponent but
homogeneous model to predict biofilm growth. Later, they expanded their
model (Gujer and Wanner 1990) to consider liquid and solid phases within
the biofilm. The model was modified to include the solid (particulate) phase
diffusive flux and the liquid (dissolved) phase advective flux (Wanner et al.
1995; Alpkvist et al. 2006; Lee and Park 2007).
Detailed metabolic information on the microscale is critical to understand-
ing and exploiting beneficial biofilms and combat antibiotic-resistant, disease-
associated biofilm-forming species. These temporally and spatially variable
metabolic gradients, which occur at the microscale, are extremely dicult to
measure. Microelectrodes offer a mean to map a single chosen parameter, for
example, pH or pO 2 (Revsbech 2005); it should be mentioned, however, that
these probes physically perforate the sample, thereby changing its permeabil-
ity and metabolism. Confocal laser scanning microscopy (CLSM) is widely
used for biofilm investigations because of its noninvasive nature and its three-
dimensional resolution capability. In spite of some technical limitations, for
example, limited optical penetration depth due to optical absorption and scat-
tering, it is widely used (Vroom et al. 1999). Two-photon CLSM methods over-
come and improve depth penetration. Both two-photon and CLSM require,
however, the addition of fluorescent tracers when detecting metabolic activity
that may have undesirable effects on cellular functions (Ullrich et al. 1996).
Fluorescence in situ hybridization and microautoradiography provide species
and substrate-uptake information at the single-cell level, but are destructive
and detect just one substrate per sample. Thus, very few techniques can con-
tinuously detect biofilm metabolite profiles in a truly noninvasive and nonde-
structive manner with adequate time and spatial resolution.
Nuclear magnetic resonance is a noninvasive method that provides a non-
invasive, subatomic view of molecular, chemical, physical, and transport pro-
cesses. NMR is nondestructive, nonsample consuming, and is insensitive to
sample opacity. NMR spectroscopy techniques provide detailed metabolic
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