• Biofilm;
  • Direct laser interference patterning;
  • Flow chamber;
  • Fluorescence microscopy;
  • Nontransparent surfaces


  1. Top of page
  2. Abstract
  3. 1 Introduction
  4. 2 Materials and methods
  5. 3 Results and discussion
  6. 4 Concluding remarks
  7. Practical application
  8. Acknowledgments
  9. 5 References

Biofilms can cause numerous problems, hence it is important to understand their formation on surfaces in order to develop resistant materials and avoidance strategies. Therefore, information is required regarding adhesion processes on surfaces generally and innovative anti-adhesive coatings in particular. Our flow cell system allows biofilms to be monitored in continuous flow conditions, without removing material for postflow imaging. The shown laminar flow ensures the maintenance of highly controlled conditions for biofilm growth. However, carried simulations of the oxygen demands of Escherichia coli cultivated as biofilms under the chosen regime indicate that conditions may become anaerobic, at least at the outlet of the flow cell, after a certain period of time. We report data on the biofouling tendencies on coatings generated with the help of direct laser interference patterning on stainless steel surfaces. Data were estimated from images acquired by fluorescence microscopy. Differences between patterned and unpatterned surfaces were not found, which is in accordance with the attachment point theory. Nevertheless, it is particularly important to elucidate in future studies the behavior of microorganisms during their attachment and the effects of variables of potentially sensitive surfaces (such as hydrophobicity, nanotopography, and charge) on their adhesion.

1 Introduction

  1. Top of page
  2. Abstract
  3. 1 Introduction
  4. 2 Materials and methods
  5. 3 Results and discussion
  6. 4 Concluding remarks
  7. Practical application
  8. Acknowledgments
  9. 5 References

Microorganisms live in both planktonic cultures and communities on surfaces called biofilms [1, 2]. Biofilms can be formed by bacteria or other organisms, such as protista or fungi [3-6], and they grow on diverse biotic [5, 7] and abiotic surfaces, including those of both natural and industrial aquatic systems, such as pipelines, bioreactors, ship hulls, and the water-cooled sides of heat exchangers. Biofilms are also found on various medical biomaterials implanted in patients, including plastic, rubber, or metallic materials [8-10]. They can cause numerous problems [11-13], hence it is important to understand biofilm formation and development processes on surfaces in order to develop resistant materials and avoidance strategies. But they are used for biotechnological applications as well [6, 14, 15].

The formation of biofilm communities begins with the initial adhesion of contaminants to a surface. Therefore, it is particularly important to elucidate the behavior of microorganisms during their attachment and the effects of variables of potentially sensitive surfaces (such as hydrophobicity, nanotopography, and charge) on their adhesion. Clearly, studies of these phenomena conditions should be controlled as far as possible to minimize variance due to unknown factors.

Diverse procedures and devices, of varying complexity and applicability, have been applied for investigating microbial adhesion on surfaces (e.g. [16, 17]). They differ widely in experimental conditions, detection equipment, and the variables that can be measured. For example, biofilms may be simply grown and weighed or visually observed on slides [18, 19] or hydroxy-apatite beads [20]. However, during experimental procedures even slight rinsing or dipping may lead to the destruction or removal of the adhering microorganisms from the substrate, thereby disrupting the studied processes and impairing the measurements. Furthermore, the hydrodynamic and mass transport conditions are interrupted during the measurements, and the adhering microbes cannot be monitored directly in situ. Thus, such discontinuous systems have major drawbacks for fundamental studies of microbial adhesion.

To counter these drawbacks, various continuous flow devices have been developed to investigate microbial adhesion and biofilm development (or associated phenomena), including stagnation point flow collectors [21], radial [22-24] and parallel plate flow chambers [25-30], annular biofilm reactors [31-33], the Fowler cell [20], the modified Robbins device [34-36], the constant-depth fermenter [37-39], a microfluidic device with glass beads [40-43], and the PDMS-based two-layer microfluidic flow cell device [44].

As discussed in literature [45-47], flow chambers with parallel plates are among the best systems, as they are specifically designed to examine microbial adhesion processes on surfaces under highly controlled hydrodynamic conditions. They provide controlled mass transport, with minimal sample volumes and no liquid–air interfaces. Key variables such as flow velocity, Reynolds number, and shear rate can be easily calculated, and chemicals such as antimicrobial agents and detergents can be easily introduced to assess their effects on contaminants’ adhesion and biofilm formation in situ throughout entire incubations [48]. Furthermore, adsorption and desorption kinetics of the microbes can be readily monitored, they can be observed microscopically, and abundant data regarding their states and spatial arrangements can be acquired by appropriate image analysis. These advantages are consistent with the concept of the “miniaturized total analysis system’’ presented by Manz et al. [49] and used by Goel et al. [50].

2 Materials and methods

  1. Top of page
  2. Abstract
  3. 1 Introduction
  4. 2 Materials and methods
  5. 3 Results and discussion
  6. 4 Concluding remarks
  7. Practical application
  8. Acknowledgments
  9. 5 References

2.1 Strains and culture conditions

The organism used in the tests was green fluorescence protein tagged Escherichia coli strain SM2029 (genotype: ara, ∆(lac-pro), thi attb::bla-Pa1/04/03-gfp*-T0/pOX38km traD411) [51], kindly provided by Søren Molin's group (Infection Microbiology Group, Centre for Systems Microbiology, Technical University of Denmark). The cells were cultured overnight in LB medium (Carl Roth GmbH), with 50 μL/mL Kanamycin. The biofilm medium consisted of one volume of A10-solution (11 mM (NH4)2SO4, 199 mM Na2HPO4·2H2O, 220 mM KH2PO4, 0.54 mM NaCl) to nine volumes of FB medium (1 mM MgCl2, 0.1 mM CaCl2, 3.7 mg/L 10 000× Fe-EDTA [1.83 g in 50 mL H2O]), with 0.1 mM glucose as a carbon source, 1 μg/mL thiamine, and 10 μg/mL proline. The temperature was kept at 30°C for both the overnight cultures and biofilm experiments. Following overnight culture, the bacteria were filtered through a 5 μm sterile filter (Minisart®, Sartorius Stedim Biotech S.A.) to avoid clusters forming in the inoculum. The filtrate was diluted in PBS to 8 × 104 cfu/mL for inoculation. During the following experiments, the pump's speed was set to 0.548 × 10−3 or 2.74 × 10−3 m/s, respectively.

2.2 Surfaces

The surfaces used in our flow cell studies were made of cold-rolled stainless spring band steel (VA 1.4301). The regular periodic surface structures were fabricated using direct laser interference patterning. This utilizes the interference of two or more laser beams, which offers rapid fabrication along with a high degree of design flexibility [52]. This is only possible with accurate spatial and temporal overlap of the laser pulses from all interfering laser beams. As high-energy laser pulses are used, the materials can be processed in a single step, thereby avoiding the need for a photoresist in subsequent stages of developing and etching the substrate. When metals are being processed, this manufacturing method exploits local melting and selective ablation, at the positions of maximum interference [52].

By adjusting the angle between the laser beams, line-like arrays with 5.0 μm pitch were directly patterned on the steel surfaces, using a single laser pulse at a laser energy density of 1500 mJ/cm2 (laser wavelength λ = 355 nm).

Experiments were performed with both unstructured and structured foil [(Fig. 1B and C, respectively) Fig. 1A shows a large area of steel substrate with 5 μm periodic structure].


Figure 1. Steel substrates used in the experiments. (A) Large area of steel substrate with 5 μm periodic structure. The colors arise from diffraction effects due to the repetitive pattern. (B, C) Scanning electron micrographs of the unstructured and structured substrates, respectively.

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2.3 Flow cell and its setup

The modular flow cell (see Fig. 2) is based on a MicCell system from GeSiM, Germany, adjusted to provide fluidic contact with planar, 75 mm × 25 mm chips (schematic diagram in Fig. 2, labeled 4). For fluidic access, the connecting plate contains two holes with seals, into which HPLC-connectors (Watson-Marlow-Bredel Pumps, Cornwall, England) can be inserted, to connect the flow cell with tubes, and there are four screws to bolt the connecting plate in place. To allow use of chips of different heights, we employ a spring-loaded pressure plate with an online monitoring “window” (10 mm × 54 mm), maintaining a constant connecting pressure. As also shown in the schematic diagram (Fig. 2, right), the chip consists of a glass slide (2). The fluidic layer (3) is made with three layers of double-faced adhesive tape (3M Deutschland GmbH, Neuss, Germany), 600 μm thick in total, in which channels can be flexibly and rapidly created using a laser. In the experiments reported here, we used a scanner-coupled Avia X laser (Coherent Inc., USA), at 355 nm wavelength, to create one- or three-channel configurations.


Figure 2. Experimental setup. Left: Photograph of the flow cell and peripheral equipment: (1) outlet with clamp, (2) T-connector, (3) inoculation tube with clamp, (4) flow chamber with metallic substrate, ready to start an experiment after inoculation, and (5) inlet. Right: schematic diagram of the flow chamber components: (1) base, (2) glass slide, (3) tape, (4) substrate, (5) gaskets, (6) pressure plate, and (7) HPLC connectors.

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The glass slide and the substrate (4), containing holes for the liquid access, are glued together with the double-faced adhesive fluidic layer, and placed on the pressure plate. The MicCell has to be screwed together so that the fluidic access points align with the holes in the substrate, then the flow chip is pressed on to eliminate leakage.

The assembled flow chamber is attached to the rest of the experimental apparatus with small tubes (Microtube PTFE) in the HPLC connectors (7).

2.4 Biofilm system setup

The complete setup consists of the flow cell (Fig. 2, left), a peristaltic pump (Watson-Marlow 205S; Watson-Marlow-Bredel Pumps), and bubble traps in the inlet tubing (Department of Systems Biology, Technical University of Denmark) to avoid bubbles forming in the flow cell, connectors, and medium and waste bottles. For additional information, see [53]. These parts are connected by silicon tubes. The tubes in the bottles have an inner diameter of di = 2 mm, an outer diameter of dout = 4 mm, and are connected to smaller Marprene tubes (Watson-Marlow-Bredel Pumps) (di = 1 mm and dout = 3 mm) at the inlet and outlet of the flow cell. The “inoculation tube” (Fig. 2, left photograph, labeled 3) is of the same type as in the bottles, and is connected with a T-connector (Fig. 2, left photograph, labeled 2) to the system. It must be clamped off during most of the experimental time.

2.5 Inoculation and experimental procedure

A procedural difference between our novel and innovative setup and previously published systems [51, 53] is in the inoculation. To minimize unwanted growth of microorganisms in the inlet tubes, the test organisms are introduced from the outlet of the flow chamber, via the inoculation tube mentioned above, as follows. The pump is stopped, the inlet tube is clamped off in front of the T-connector, then the outlet tube is clamped off and the “inoculation tube” clamp is loosened. A 125 μL portion (equivalent to two-thirds of the chamber volume) of a diluted overnight culture, containing 104 cfu/mL in total, is introduced with a syringe (MYJECTOR® 1 mL U-100 Insulin, 29G × 1/2″, 0.33 × 12 mm, Terumo Europe N.V., Belgium) into the outlet tube, and hence into the flow cell. Thus, the medium in the flow cell is replaced by the culture and flows into the “inoculation tube.” After all the inoculum has been injected, any leakage from the needle is cleaned with ethanol and the fissure is closed with silicone glue (732 Multi-Purpose Sealant, Dow Corning®, USA). The clamp on the “inoculation tube” is then fastened, and the flow cell is inverted, so the microorganisms can sediment, settling on the substrate. After a prescribed adhesion time, the flow cell is re-inverted and the substrate is then on the top of the flow chip. Finally, the clamps on the inlet and outlet tubes are loosened, the pump is started, and the whole system is incubated at 30°C for a prescribed period of time.

2.6 Microscopic analysis of adhesion and biofilm formation

The system is designed for online observation by a microscope equipped with long-range objectives. If there is sufficient space around the microscope to keep the temperature in the entire system constant, or if the flow cell can be tempered, the experiment may continue without halting the flow. Otherwise, the flow cell must be temporarily clamped off and disconnected to allow microscopic observation.

For microscopic investigation, and imaging of the biofilm, we used an Axioscope equipped with an ApoTome slider module (Carl Zeiss MicroImaging GmbH, Germany), which projects a grid into the focal plane. In our biofilm investigations, it was automatically moved into three positions, a digital image was acquired at each position, then an algorithm included in the system's software package (AxioVision) was used to combine these three images into a single image with improved contrast and resolution ( In our study, images of four adjacent parts of the examined biofilm were combined using the software's MosaiX tool into a single image of an area covering 0.13 mm2, from which z-stacks (images of planes at various depths within the sample) were taken (z > 4). This procedure was repeated 15 times for every flow channel and at each measurement.

We then used Imaris image analysis software ( to create 3D pictures from the image stacks, together with the optical cross-section technique to reduce blurring and shiny fragments, which improves biomass estimates. Finally, the COMSTAT 2 image analysis program ( (threshold of 40) was used to obtain biofilm volume data, following Heydorn et al. [54].

3 Results and discussion

  1. Top of page
  2. Abstract
  3. 1 Introduction
  4. 2 Materials and methods
  5. 3 Results and discussion
  6. 4 Concluding remarks
  7. Practical application
  8. Acknowledgments
  9. 5 References

In proof-of-principle experiments, we used the system to investigate the initial phases of E. coli biofilm formation on opaque stainless steel foils, with periodic 5 μm surface features fabricated using direct laser interference patterning [52], which may affect biofilm formation. In addition, we calculated the oxygen concentration in the flow chamber, taking into account bacterial growth. To the best of our knowledge, no oxygen profile in a flow chamber of the type presented here has been previously presented. Some models of oxygen distribution in a flow device with an oxygen diffusible PDMS layer have been published [55, 56], but they are not relevant to a microfluidic system such as ours. Simulated and empirically determined oxygen consumption rates by films of mammalian cells have also been published [35], but again the system used was not comparable to the one described here.

3.1 Hydrodynamics characterization

To establish optimal experimental conditions, we first characterized the hydrodynamics within the flow chamber, because for a uniform flow profile the flow must be incompressible, steady, and laminar [57]. We estimated the flow velocity within the chip using the continuity equation presented by Costerton et al. [58], simplified by assuming that the medium had a constant density approximating that of water at 30°C (ρ = 995.7 kg/m3). Therefore, the continuity equation can be expressed as:

  • display math(1)

where inline image is the change in biomass over time t, S is the surface area, V is the time-dependent liquid volume in terms of S, u is the velocity vector in terms of S, and n is the outward normal vector in terms of S.

The following assumptions were made. First, the system is in a steady state and there is a constant liquid density. This leads to the following simplification [Eq. (2)].

  • display math(2)

Second, flow velocity perpendicular to the channel surfaces is zero, and the surface areas of the volumes the flow pass through are designated A1 for the tube and A2 for the chamber channel. Accordingly, Eq. (3) is obtained:

  • display math(3)

Transposing Eq. (3), the following term is obtained:

  • display math(4)

The incoming flow u is calculated from the volumetric flow rate q and the flow cross-section of the tubing (A), with Eq. (5).

  • display math(5)

With a volumetric flow rate q of 1.23 × 10−8 m3/s and the tube's inner diameter of 1 mm, the average flow velocity in the flow chamber is 2.05 × 10−3 m/s for a fluidic chip with no subdivision into separate channels (10 mm × 0.6 mm), and 2.74 × 10−3 m/s for a fluidic chip with subdivision into three channels with the same cross-section (i.e. three times 2.5 mm × 0.6 mm).

The Reynold's number (inline image), often used to describe flow characteristics, can be calculated using Eq. (6), with the hydraulic diameter of the flow cross-section inline image.

  • display math(6)

The estimated Re values were 2.90 (without subdivision) and 3.31 (with subdivision), assuming that the density (ρ) and viscosity (η) parameters of the medium were equal to those of water at 30°C (995.7 kg/m3 and 7.977·10−4 kg/ms, respectively). This describes a laminar flow, since the transition from laminar to turbulent flow in pipes occurs at Re > 2300 [31].

In addition, we constructed a laminar model using Comsol Multiphysics 3.2 software, which we applied to calculate the flow and associated Reynolds numbers within the flow chamber (Fig. 3). For this simulation, we used an incoming flow u of 1.57 × 10−2 m/s, in order to compare the results of the calculations and simulations.


Figure 3. Results of simulations of the hydrodynamics in the flow chip (with subdivision) using Comsol Multiphysics, with a volumetric flow rate q of 1.23 × 10−8 m3/s and incoming flow u of 1.57 × 10−2 m/s. The simulated channels had a cross-section of 2.5 mm × 0.6 mm. Relatively high flow velocities are shown in red. (A) The liquid flowing over the entire chip and (B) the inlet region.

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As can be seen in Fig. 3, under the chosen conditions there is no turbulence, the flow velocity inside the channels is regular and laminar (shown in blue and green). The maximal Reynolds number is 30, well within the laminar flow regime. Nevertheless, the microscopic analysis focused on the second half of the channel to minimize any disturbance of the growth that might have been caused by turbulence and irregularities. A simulation of the hydrodynamics in the chip with no subdivision yielded identical results for the flow regime (data not shown).

3.2 Characterization of oxygen consumption

To estimate oxygen consumption rates within the flow chamber during the microbial growth period, changes over time in the oxygen concentration were simulated as a function of the maximal oxygen uptake rate and initial biomass (1 h after inoculation) and time, assuming that the specific growth rate at a given time was exponentially related to the maximal growth rate (μmax).

Equation (7) describes the temporal change of the mass of oxygen in the flow chamber as shown in Fig. 4.

  • display math(7)

where inline image is the change in mass of oxygen in the flow cell with time, inline image and inline imageare the mass flow of oxygen at the inlet and outlet (g/h), respectively, μ is the specific growth rate, inline image is the initial adhered biomass (1 h after inoculation [g]), and inline image is the biomass yield in relation to the oxygen consumed.


Figure 4. Schematic diagram of the oxygen distribution in the flow channel. inline image = mass flow of oxygen at the inlet (g/h); inline image = mass flow of oxygen at the outlet (g/h); μ = specific growth rate (h−1); inline image = starting biomass (g); inline image = oxygen consumption of the biomass; FL= volumetric flow (L/h).

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Assuming a quasi-steady state inline image, Eq. (7) can be transformed into Eq. (8).

  • display math(8)


  • display math(9)

With the flow inline imagedefined in Eq. (9), where inline image is the mass concentration (g/L) and FL is the volumetric flow (L/h), Eq. (8) can be transformed into Eq. (10).

  • display math(10)

If inline image in Eq. (10) becomes negative, the system becomes increasingly anaerobic, starting from the outlet, and moving toward the inlet.

The yield for oxygen inline image is calculated from inline image and the maximal inline image with Eq. (11).

  • display math(11)

The maximum inline image value can be estimated at approximately 1.07 gO2/gS, from the stoichiometry of the aerobic breakdown of glucose [59], assuming that the microbes use oxygen purely for metabolic energy transformation and none for growth processes. Therefore, using inline image = 0.45 gx/gS [60], inline image is around 0.42 gx/gO2.

Assuming that a single E. coli cell has a volume of 1 μm3 and dry weight of ca. 3 × 10−13 g [61], the biomass volumes obtained from COMSTAT 2 can be converted into biomass values with Eq. (12). The assumptions applied for this are that the bacteria grow evenly over the whole channel surface area, that their size is constant, and that the medium has a saturated oxygen concentration (inline image = 7.55 mg/L at 30°C):

  • display math(12)

where 1.25 × 108 μm2 is the surface area of the flow channel.

Equation (13) describes the exponential growth of the bacteria. Thus, their maximal growth rate μmax can be calculated, when the measured biomass (μm3/μm2) after 17 h incubation is transformed into biomass (g), using Eq. (12).

  • display math(13)

Mean measured and calculated biomass values are shown in Table 1, based (inter alia) on simulated oxygen consumption rates, obtained after transforming the Comstat biomass values (in μm3/μm2) into biomass values in grams.

Table 1. Mean measured biomass (XComstat) and calculated biomass (mx) values, assuming that a single cell of Escherichia coli has a volume of 1 μm3 and dry weight of ca. 3 × 10−13 g [61]), after 1 h and at the end of the experiments (17 h) with estimated μmax [Eq. (13)]
 μmax (h−1)XComstat, 1h (μm2/μm3)inline image (g)XComstat, 17h (μm2/μm3)inline image (g)
  1. DLIP = direct laser interference patterning.

Unpatterned spring band steel0.300.000722.7 × 10−80.08653.24 × 10−6
DLIP-structured steel (lines perpendicular to the flow direction)0.280.001043.9 × 10−80.09933.73 × 10−6
DLIP-structured steel (lines in the flow direction)0.150.00592.21 × 10−70.06522.44 × 10−6

We have estimated the specific growth rate μ of E. coli in the flow cell under the chosen conditions from Eq. (10) using Berkeley Madonna software (, assuming that the bacteria were growing exponentially over the course of the experiments. The following experimental findings were taken: inline image of 2.2 × 10−7 inline image or 2.7 × 10−8 g, respectively, inline image 7.55 mg/L, and inline image 0.42 gx/gO2. Results are shown in Fig. 5.


Figure 5. Simulation of the oxygen concentration at the outlet performed with Berkeley Madonna and Eq. (10), while varying starting biomass and the specific growth rate μ. (A) Based on the higher starting biomass inline image = 2.2 × 10−7 g (μ from top to bottom: 0.1, 0.2, 0.3, 0.5, and 0.7 h−1) and (B) based on the lower starting biomass inline image = 2.7 × 10−8 g (μ from top to bottom: 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, and 0.7 h−1).

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Clearly, if the initial biomass is high (Fig. 5A), oxygen depletion occurs within the experimental time of 17 h, with μ > 0.2 h−1. However, with lower initial biomass (Fig. 5B), oxygen depletion occurs with μ > 0.3 h−1. This confirms our calculated data in Table 1.

3.3 Experimental results

The aim of the initial proof-of-principle experiments presented here was to assess the utility of our flow cell for studying the initial phase of biofilm formation on microstructured surfaces in order to characterize their anti-adhesive properties. To ensure that the biofilm patches originated solely from the inoculum, and not from bacteria that had left the grown biofilm and formed new colonies, a short cultivation time of 17 h was chosen.

Figure 6 shows 3D images taken from an unstructured surface (A) and a surface structured in the flow direction (B). At the end of the experiments, patches of biomass could be clearly distinguished from their surroundings, but they were also clearly unevenly distributed. The 15 randomly taken microscopic images cover only about 1/64 of the entire channel surface. Furthermore, the calculated oxygen consumption rates (see above) clearly indicate that there were probably regions in the flow cell, at least at the outlet end, where bacteria could not grow under aerobic conditions throughout the experiments. This may explain the large deviations of biomass we found on both microstructured and unstructured reference surfaces (Fig. 7).


Figure 6. 3D images of biofilms on unstructured reference (A) and structured (B) surfaces in the direction of flow after 17 h experimental time.

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Figure 7. Comparison of biomass growth on unstructured spring band steel (VA 1.4301; reference material) and direct laser interference patterning (DLIP) structured steel (with lines both perpendicular to and in the flow direction). Inoculation time and flow velocity were varied. After 17 h incubation time, 15 image stacks (A = 0.13 mm2, z = 4) were randomly taken from each structure. The mean biomass volume was calculated initially from 3 × 5 image stacks, then mean values were calculated from all results of two independent experiments. (A) 10-min inoculation time, experiment run with a flow velocity of 0.548 mm/s. (B) 60-min inoculation time, experiment run with a flow velocity of 0.548 mm/s. (C) 10-min inoculation time, experiment run with a flow velocity of 2.74 mm/s. (D) 60-min inoculation time, experiment run with a flow velocity of 2.74 mm/s.

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Nevertheless, our observations are in accordance with the literature [62, 63]. Attachment point theory holds that it is difficult for a cell slightly larger than the microtexture wavelength of a surface to attach because there are only two theoretical attachment points. In the experiments reported here, line-like arrays with 5.0 μm pitch were directly patterned onto the steel surface, which are unlikely to have strong anti-adhesive properties.

4 Concluding remarks

  1. Top of page
  2. Abstract
  3. 1 Introduction
  4. 2 Materials and methods
  5. 3 Results and discussion
  6. 4 Concluding remarks
  7. Practical application
  8. Acknowledgments
  9. 5 References

Understanding the properties of opaque surfaces is becoming increasingly important, both to acquire fundamental data concerning industrial biofilm formation and to facilitate the development of surfaces with anti-adhesive properties. Using the flow cell system with a parallel plate flow chamber described here, which can be easily and rapidly adapted to meet different requirements (e.g. channels can be created with depths ranging from 100 μm to 10 mm), the adhesion, growth, and suppression of biofilms on surfaces with various structures and coatings can be examined on opaque surfaces within the same chamber, in a similar environment. The flow regime is laminar, thus contaminant adhesion and biofilm formation can be investigated under strictly controlled conditions.

Practical application

  1. Top of page
  2. Abstract
  3. 1 Introduction
  4. 2 Materials and methods
  5. 3 Results and discussion
  6. 4 Concluding remarks
  7. Practical application
  8. Acknowledgments
  9. 5 References

This research article presents a convenient, low-cost system that can be used for sensitive microscopic scale studies of the adhesion and the growth of microorganisms on solid opaque surfaces using fluorescence analysis. We present proof-of-concept analyses of biofilm formation on surfaces with novel, innovative anti-adhesive coatings intended, for example, for use in the food processing industry. The results show that the system can be readily applied to examine biofouling or biofilm behavior under selected conditions, and to characterize important features of modified surfaces, such as their anti-(bio)fouling properties and ease of cleaning.


  1. Top of page
  2. Abstract
  3. 1 Introduction
  4. 2 Materials and methods
  5. 3 Results and discussion
  6. 4 Concluding remarks
  7. Practical application
  8. Acknowledgments
  9. 5 References

We thank the following people from Fraunhofer IWS Dresden: Frank Sonntag's group for adapting the flow chip to our purposes and Mathias Busek for the flow simulations. The work was supported by AiF, Industrievereinigung für Lebensmitteltechnologie, und Verpackung e.V. (IGF-Vorhaben Nr. 16597 BR).

The authors have declared no conflict of interest.

5 References

  1. Top of page
  2. Abstract
  3. 1 Introduction
  4. 2 Materials and methods
  5. 3 Results and discussion
  6. 4 Concluding remarks
  7. Practical application
  8. Acknowledgments
  9. 5 References
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