Xin Cui,
Hon Ming Yip,
Qian Zhu,
Chengpeng Yang and
Raymond H. W. Lam*
Department of Mechanical and Biomedical Engineering, City University of Hong Kong, Hong Kong. E-mail: rhwlam@cityu.edu.hk; Fax: +852-3442-0172; Tel: +852-3442-8577
First published on 25th March 2014
Dissolved oxygen is a critical micro-environmental factor to determine the growth characteristics of bacteria, such as cell viability, migration, aggregation and metabolic processes. Here, we report a microfluidic long-term oxygenator which can support high-throughput parallel cell cultures under multiple defined oxygenation conditions (0–42 ppm). An array of oxygen–nitrogen gas micro-mixers is developed and fabricated in the device to generate stable oxygen concentrations for the oxygenation process. A water-jacket layer located between the gas layer and the cell culture chamber is applied to block evaporation and maintain the conditions of the culture media in the chamber. Furthermore, we perform simulations and experiments to investigate the functions of the gas mixers and the water jackets. We also conduct culture experiments to study the long-term growth (up to one week) and aggregation of three selected dental bacteria (Streptococcus mutans, Actinomyces viscosus and Fusobacterium nucleatum) under ranges of oxygenation conditions. These particular results can provide important insights into their roles in dental biofilm formation. Overall, this work demonstrates that the long-term microfluidic oxygenation approach can effectively regulate defined dissolved-oxygen levels in cell microenvironments. Importantly, this oxygenation approach can be further applied to general long-term analyses of cells for their behavioral, metabolic and genetic responses, and their biofilm formation processes.
Microfluidics has been proven as an extremely effective technology for cell biology study, mainly due to its wide range of advantages over traditional macro-scale cell culture methods, e.g. high throughput analysis,15,16 shorter response time,17,18 automated sample operations, and reduced consumption of cells and reagents.15,19 In particular, microfluidics can achieve sample transport, manipulation and processing20–22 in the micro-meter scale, and therefore the local biological microenvironments such as DO levels can be regulated and mimicked relatively easily.18,23–25 Up to date, several approaches have been reported to generate different DO levels in multiple microchannels or microchambers for cell culture applications. Many of these microfluidic devices were made of polydimethylsiloxane (PDMS) mainly due to its material properties such as optically transparency, gas permeability, biocompatibility and fabrication feasibility based on soft lithography.26,27 Park et al. used different microelectrodes in underneath microchannels to obtain different oxygen production rates based on water electrolysis.28 Due to the diffusivity of oxygen through the membrane between a microchannel and an oxygen generation region, additional oxygen concentrations could be generated and diffuse into the microchannel. Though this method had a high oxygen generation rate, the fabrication of microelectrodes was relatively complicated and the precise DO level was hard to maintain. A small amount of hydrogen peroxide, which was harmful to cells, could be produced in the water electrolysis process.29 Recently, Chen et al. developed strategies to apply reactions to generate oxygen.7 They designed two channels for oxygen generation and oxygen removal on the both sides of a cell culture microchannel. This method required precise controls of flow rates of different chemical substances to maintain a specified DO concentration in the culture channel. Hydrogen peroxide was also involved in the oxygen generation. Droplets-based methods were implemented to improve efficiency of oxygen diffusion in microchannels, in which carrier oil functioned as a gas source of a predefined oxygen concentration;30 thereby DO in water droplets quickly equilibrated with that in the surrounding oil. However, this approach cannot be applied in long-term cell culture because of the limited nutrients in water droplets. A widely adopted strategy for oxygen concentration modulation was the two-layer microchannel structure containing a layer of gas mixing channels fabricated directly overhead the culture channels, separated by a gas-permeable PDMS membrane for the oxygen diffusion.31–33 Due to the small thickness of the diffusion membrane, oxygen with defined concentrations diffused quickly into the underneath microchannels. Because the DO level in media was determined by the ratio of oxygen along the gas channel, the DO level was stable under a fixed condition along the gas channel.
Although the two-layer structure provided stable oxygenation without the disadvantages of other mentioned approaches, it faced a technical challenge of preventing evaporation of culture media because the convective flow along overhead the gas channels continuously brought away water molecules evaporating through the diffusion membrane.34–37 Such moisture loss over time, even at a relatively small rate, reduced the relative osmolarity in culture media, resulting in increase of cell stress and even cell death.37,38 Although the moisture loss could be reduced by applying pre-humidification of the gases,39–41 experiments showed that overhead gas flow still induced significant moisture evaporation. Our previous work introduced pre-humidified oxygen and nitrogen into a differential oxygen concentration generator, by flowing the required gases (nitrogen and oxygen) through water reservoirs upstream of the device inlets. This approach could lengthen the cell culture period up to <10 h.42 The oxygenation approach is yet to be improved in order to support further investigations on long-term cell behaviors such as cell aggregation, biofilm formation, and mild cytotoxicity responses, which develop only after days or weeks of culture.43–45
In this work, we demonstrate a microfluidic strategy to implement long-term oxygenation and precisely define different oxygen concentrations in multiple culture chambers in a microfluidic device. We configure the differential oxygenator as a series of parallel gas mixing channels. A target oxygen concentration can be defined precisely in each mixer by regulating the flow resistances in the inlets channels for pure oxygen and pure nitrogen. This type of oxygenator has more robust performance than many other oxygen gradient generators.6,8,42,46–48 Further, in order to support the long-term cell culture, a water jacket layer is fabricated between the gas layer and the cell culture layer. This water jacket acts as a sacrificial layer of water molecules for blocking the evaporation of culture media via the gas-permeable PDMS. In the oxygenated culture experiments, Streptococcus mutans, Actinomyces viscosus and Fusobacterium nucleatum are selected due to their different oxygen concentration requirements and their critical roles in the dental biofilm formation. S. mutans assist growth of many other dental bacterial species in human oral cavities; and they likely cause the dental caries formation.49–51 A. viscosus bacteria have been proven by experiments for their capability of causing root surface caries and periodontal bone lesions.52,53 The anaerobic F. nucleatum can bridge aerobic bacteria and anaerobic bacteria to grow together in dental biofilms. Without F. nucleatum, most anaerobic oral species cannot survive in the oral cavity under sufficient oxygen concentrations.54–56 Over the cell culture periods (up to 3–7 days), we monitor the cell densities and distributions in each culture chamber. We investigate the optimal oxygen levels for growths of selected bacteria types, and the effects of oxygen levels on the bacteria growths and auto-aggregation capabilities.
Mold structures for the flow layer was fabricated with a positive photoresist (AZ4620, AZ Electronic Materials, Branchburg, NJ) in order to obtain the required channel geometry for microfluidic pneumatic valves and peristaltic pumps. Before spin-coating the AZ photoresist on a silicon wafer for a thickness of 20 μm, hexamethyldisilazane (Sigma-Aldrich, St. Louis, MO) was applied on the wafer to promote the adhesion between the photoresist and the silicon wafer. Then the wafer was baked on a hotplate for 30 min and exposed under UV (350 nm, 10 mW cm−2, 80 s). Afterwards, the mold was developed in the AZ 400K developer (AZ Electronic Materials, Branchburg, NJ) and reflowed on a hotplate at 140 °C for 1 min to achieve the round-shaped channel profiles.
Before fabricating the multilayer PDMS device, all the molds should be first silanized with a high-molecular-weight trichloro-perfluorooctyl saline (Sigma-Aldrich) to facilitate the polydimethylsiloxane (PDMS) release from the molds during the subsequent device fabrication processes. PDMS monomer and the curing agent (Sylgard 184, Dow Corning, Midland, Michigan) were mixed with a 10:
1 weight ratio and degassed in a vacuum bell jar. The top device layer with gas channel structures was fabricated by pouring the PDMS pre-polymer onto gas channel mold fixed in a Petri dish for a thickness of ∼3 mm, baking the sample in an oven at 80 °C for 20 min, and peeling off the PDMS substrate part from the mold. Holes for oxygen and nitrogen inlets were punched using a Harris punch (Harris Uni-Core, TedPella, Redding, CA) with a diameter of 0.5 mm.
Based on multilayer soft lithography, stacked PDMS layers including the water jacket, the control layer and the flow layer were sequentially fabricated with thicknesses of 60 μm, 300 μm and 40 μm, respectively. In brief, PDMS pre-polymer was spin-coated on the second mold with a thickness of 60 μm and baked in an oven at 80 °C for 14 min. After alignment under a stereo microscope (JSZ-6S, Yee Mau Industrial Co., Hong Kong), the first layer of PDMS with punched holes was bonded with the second layer and baked again at 80 °C for 2 h. Then, the two-layer PDMS substrate was peeled off from the silicon mold, followed by punching holes for the gas outlets. Through-holes between the gas inlet channels and the parallel gas mixer structures were cut using a razor blade (Bard-Parker stainless steel surgical blade, Becton Dickinson and Company) at the overlapping regions (yellow squares in Fig. 2c). With the similar soft lithography procedures, each of the control layer and the flow layer was fabricated sequentially by spin-coating with PDMS on the mold, baking at 80 °C in an oven until partial cure, aligning with the PDMS substrate under a stereo microscope, further baking at 80 °C for 2 h, peeling off from the mold, and punching holes for fluidic connections. Afterwards, the four-layer PDMS should be treated by oxygen plasma (PDC-002, Harrick Plasma, New York) with 29.6 W power for 1 min in order to bond the stacked PDMS onto a glass slide (75 mm (l) × 25 mm (w) × 1 mm (h); Cat # 16004-422, VWR).
We extracted each bacteria sample from the bulk culture and diluted to a targeted seeding density (106–107 cells per ml). We then injected the bacteria sample into the microfluidic oxygenator with a syringe pump (PicoPlus, Harvard Apparatus, Holliston, MA) at a flow rate of 0.05 μl min−1. During the injection process, a microfluidic multiplexor in the device opened up each column of microchambers in the device consecutively. We placed the device in a temperature-controlled water bath at 37 °C for oxygenated cell culture. The cells were incubated under a static condition (without liquid flows) for ∼2 h in order to enable the cell attachment in the saliva-coated culture chamber. Afterwards, nitrogen and oxygen gas sources for the gas mixing were maintained at a constant pressure (1 kPa), meanwhile fresh culture media were periodically flowed into each column of chambers for 10 s every 1 h by a syringe pump (PicoPlus, Harvard Apparatus) at a flow rate of 0.003 μl min−1, until the experiments ended. At different time points during the cell culture, we captured phase-contrast microscopic images at all culture chambers and analyzed for the oxygenated cell growth using a customized Matlab (Mathworks, Natick, Massachusetts) program.
Furthermore, eight gas mixers were fabricated in the gas layer to generate eight independent oxygen concentrations. Each of the mixers consisted of a gas inlet for oxygen, a gas inlet for nitrogen and a gas outlet for the mixed gas with specified oxygen volumetric concentration as shown in Fig. 2a. Because of the fact that all the gas inlets were connected to the common gas sources (i.e. oxygen and nitrogen gas tanks), we adopted a two-layer microchannel structure, in which two inter-connecting microchannels were fabricated in the secondary layer to route all mixer inlets for the same gas type (oxygen or nitrogen) to a common gas port of the device. As shown in Fig. 2c, connections of the gas channels were achieved by cutting through-holes (yellow squares) at the overlapping channel patterns between the two inter-connecting gas lines (purple) and the eight mixers (green). In addition, we located the inter-connecting gas lines in the same layer with the water jackets, in order to eliminate an extra PDMS layer of the fabrication process (Fig. 1a). Each mixed gas with a defined oxygen level will flow along a downstream gas channel, fabricated overhead a water jacket and a column of five culture chambers.
Other than control valves, a microfluidic multiplexor16 was designed in the control layer to selectively enable flows along one column (out of eight columns) of five cell culture chambers. This configuration facilitated accessibility of the cell seeding and the medium replacement processes during the long-term cell culture. Considering also the arrangement of the overhead gas channels, it provided an identical microenvironment in the five chambers for repeating culture experiments. Overall, this device can support high-throughput long-term oxygenated cell culture for the growth analysis with eight independent DO concentrations in each column of the five identical cell culture chambers.
To generalize our oxygenator design, we modeled a gas mixer with cases for different flow resistances of the two upstream channels as illustrated in Fig. 2a. These flow resistances and hence the flow rates of oxygen and nitrogen were controlled by different lengths of the upstream folded channels. In addition, we set the channel dimensions of the downstream mixing folded channel such that the representative scaled Peclet number (Pe*) for the possible range of gas flow rates (10−7–10−6 m3 s−1) was sufficiently small, i.e. Pe* = 10−3–10−1, as shown in Table 1. The scaled Peclet number is defined as Pe* ≈ UW/D × W/L, where L, W, and H are channel length, width and height, respectively; U is the average gas flow velocity (U = Q/(WH)); and D is the diffusivity of oxygen in nitrogen. In our analyses, L, W, H and U should have different values in different channel sections. This condition implied diffusion dominated over the convective effect along the mixing channel. Oxygen and nitrogen were then fully mixed along the downstream channel with a concentration defined by the ratio of the gas flow rates.
Folded channel | Length L (μm) | WidthW (μm) | Height H (μm) | Flow rate (Q) × 10−6 m3 s−1 | Resistance × 108 (Ns m−5) | Re* × 10−3 | Pe* × 10−2 |
---|---|---|---|---|---|---|---|
a Note: scaled Reynolds number: Re* ≈ ρUL/μ × H2/L2, where U = Q/(WH) is the average velocity; scaled Peclet number: Pe* ≈ UW/D × W/L, where D is 2.19 × 10−4 m2 s−1. | |||||||
Oxygen inlet | 0–129![]() |
28 | 20 | 0–1.43 | 0–252.14 | 0.42–16.7 | 0.28–11.38 |
Nitrogen inlet | 0–9000 | 28 | 20 | 0–3.55 | 0–15.76 | 4.39–41.36 | 3.44–32.43 |
Outlet | 1800 | 28 | 20 | 1.16–3.75 | 0.64–3.5 | 13.48–43.71 | 9.99–34.02 |
The corresponding oxygen concentration at the mixer outlet Co (0 ≤ Co ≤ 1) can be estimated based on the conservation of mass,
Co = Q1/(Q1 + Q2), | (1) |
To estimate the channel resistance, we have configured the channel dimensions such that the scaled Reynolds numbers (Re*) for all channel sections in the mixer were in a range of 10−3–10−1. Viscous effects dominated in all the channels and the velocity profiles of the gas flows were fully developed. The scaled Reynolds number is defined as Re* ≈ ρUL/μ × H2/L2, where ρ is the density of gas mixture; μ is viscosity of the gas flowing in the channel. It should be mentioned that viscosity of the gas mixture along the mixing channel can be estimated by
μ ≈ 1/(C1/μO2 + C2/μN2), | (2) |
The fluidic resistance for a flow channel with a rectangular cross-section can then be expressed as
![]() | (3) |
We performed experiments to validate the microfluidic gas mixer for different ratios of flow resistances between the oxygen and nitrogen inlet channels. The channel dimensions and operation parameters are shown in Table 1. Pure oxygen and nitrogen gas tanks were used as gas sources at a common gauge pressure of 1 kPa. The emission intensities from PtOEPK were measurement with multiple oxygen sensing modules we developed previously.42 We connected an oxygen sensing channel embedded with platinum(II) octaethylporphine ketone (PtOEPK) to every outlet from the gas mixers. Briefly, the measurement mechanism of oxygen concentration was based on the change in emission intensity from a PtOEPK sensor under an external excitation light exposure; and the emission intensity reflected the oxygen content in a gas mixture.42 Experimental results (Fig. 2b) show that oxygen concentrations from the device gas outlets for different ratios of flow resistances along gas inlet channels have very good agreements with the analytical values calculated by the method mentioned above. This relation implies that oxygen concentrations can be effective tuned by the dimensions of inlet gas channels in the microfluidic parallel gas mixers as shown in Fig. 2d.
Here, we describe the characterization of the oxygenation process in the long-term oxygenator, by simulating oxygen concentration profiles over the cross sections of individual culture regions configured with different combinations of the design parameters. We applied commercial software (COMSOL Multiphysics 4.2, Burlington, MA) to perform these simulations on a 2D axisymmetric model of an individual culture region (Fig. 3a), which was composed of a cylindrical culture chamber (radius: 500 μm; height: 20 μm), a cylindrical water-jacket chamber (radius: 600 μm; height: 20 μm), and a ring-shaped overhead gas channel. The simulations were based on modifying the three design parameters of the ring-shaped gas perfusion channel from a reference model: (1) height, (2) inner radius and (3) width of the ring-shaped gas perfusion channel. The thicknesses of PDMS layers on the upper and lower sides of the water jacket were 40 μm and 300 μm, respectively. The oxygen profiles for different device configurations were calculated by solving the diffusion equations. Diffusivities of oxygen in PDMS and in water were set as 5.0 × 10−5 cm2 s−1 and 2.0 × 10−5 cm2 s−1, respectively. We considered a normalized oxygen concentration with 100% as the imposed oxygen level in the ring-shaped gas channel and 0% as the oxygen level in the ambient environment. For the boundary conditions, a constant oxygen level (100%) was defined at the boundaries of the ring-shaped gas channel. A zero flux was set at the bottom side of the model because oxygen could not diffuse into the underneath glass slide. In addition, oxygen concentration at the upper boundary of the model was set as 0%. The oxygen concentration profile at the bottom of the culture chamber for each configuration modified from the reference model was considered, because this region represented the cell microenvironment more directly. Effects of the three varying design parameters of the ring-shaped gas perfusion channel: height (10–200 μm), inner radius (0–1000 μm) and width (100–1000 μm), modified from the reference model are shown in Fig. 3b–d, respectively. In summary, these results show that >95% of the oxygen concentration in gas chamber can be regulated at the bottom of the culture chamber for the current microfluidic long-term oxygenator (height: 100 μm; inner radius: 550 μm; width: 500 μm).
We also performed experiments to validate the evaporation reduction of the water jacket layer embedded in the device. The experiments consisted of four cases: (1) applying dry compressed air as the gas sources for both mixer inlets to a device without a water-jacket layer (the PDMS between the chamber and gas layers was then ∼360 μm thick), (2) applying pre-humidified air to mixers without a water-jacket layer, (3) applying dry air with an embedded water jacket, and (4) applying pre-humidified air to mixers with a water-jacket layer. In these experiments, we considered one chamber in the microfluidic oxygenator because configurations of the chambers are identical. We performed at least three sets of independent experiments for each case in order to obtain the average evaporation processes. To begin the experiments, we injected water in every culture chamber and isolated the area by closing the two valves around the chamber, followed by application of the compressed dry air flow. The gas pre-humidification was achieved by passing the air into a bottle of distilled water before the air flowing to the device inlets. The evaporation process in the chamber was recorded by taking time-lapse images under an inverted microscope. Throughout the experiments, an air bubble formed and expanded in the chamber. The bubble formation was due to the gas permeability of PDMS, i.e. external air replaced the evaporated water in the chamber by diffusing via the PDMS substrate of the device. The bubble formation indicated the volumetric reduction of water due to evaporation, as shown in Fig. 4d. Results (see Fig. 4e and S2†) show that the evaporation duration for the case with a water jacket was much longer than the cases without a water jacket. We can observe also that using pre-humidified air (instead of dry air) induced a slower evaporation process. Indeed, applying both the gases with pre-humidification and a water-jacket layer in the oxygenator can further eliminate the medium evaporation in the microchambers for the long-term cell culture applications.
As shown in Fig. 6b, the facultative anaerobic bacteria S. mutans grew in both aerobic and anaerobic environments. Our experimental results have shown also oxygen-tolerance of S. mutans under relatively high DO levels (>8 ppm). This cell behavior was consistent with the previous research.49,58 Nevertheless, the cell growth was not as rapid under a nearly oxygen-saturated environment. Generally, hydrogen peroxide produced by Streptococci in the over-oxygenated (>8 ppm) microenvironment can be a factor to inhibit bacterial growth, resulting from the lack of catalase.49,58 It has been reported that exposure of hydrogen peroxide, especially for longer durations (>10 h), can lead to permanent cell damage and therefore retardation of growth.59 Another possible cause is that oxygen may change gene expressions of bacteria in their long-term growth (>20 h), causing alterations of the energy-generating pathways for carbohydrate metabolism. It has been proven that the oxygen exposure can down-regulate the enzymes involved in production of adhesive glucan exopolysaccharides, hence cell attachment and growth in the culture chambers should be inhibited accordingly.51 Results of A. viscosus show a similar growth trend with S. mutans as A. viscosus is also an facultative anaerobic species.60 Previous research has reported that A. viscosus can alter its metabolic mechanisms to adapt different oxygen levels in their growth environments.60 In addition, F. nucleatum is known to be the strictly anaerobic species,55,56 therefore it can only grow under very low DO levels (up to ∼6 ppm), as also indicated in our experiments. We can also observe in Fig. 6b that under aerobic microenvironments, F. nucleatum still exhibits cell growth, although the growth is very slow. Indeed, it has been reported that cell–cell interactions involved in the cell clusters may enhance the oxygen-tolerance of the entire population.56,61
Considering that the bacterial growth is highly sensitive to DO as demonstrated in our previous experiments, the DO concentration may affect significantly the selected bacteria in this work on their auto-aggregation abilities, as a cell response independent from the cell growth rate. During the cell culture up to several days, the cells in the culture chambers would grow and aggregate simultaneously, mainly initiated by the intercellular communications including migration and cell–cell attachment.62 Therefore, a highly aggregating bacterial species should form bigger cell clusters in the cell populations; whereas a species without noticeable aggregation capability should distribute sparsely while its cell population expands.
Aggregation abilities of the three selected bacterial species (S. mutans, A. viscosus and F. nucleatum) were examined for oxygenations of different DO levels (0–42 ppm). Similar to the cell growth experiments described in the previous section, the cells were first seeded into the saliva-coated chambers. Typically, previous research examined the increments of sizes of cell clusters to quantify the cell aggregation abilities.53,54,68 Based on the same principle, we adopted the aggregation rate, which is defined as the relative increment of cluster area per day, to evaluate the cell aggregation abilities under different DO levels. Image processing was applied to identify the cell clusters in each culture chambers. Results for S. mutans indicate significant auto-aggregation rates under relatively low (≤10 ppm) DO concentrations (Fig. 7, left). For the growth under higher DO levels, S. mutans have expressed low or even negative auto-aggregation rates. This behavior can be explained by the possible harmful effects of the produced hydrogen peroxide59 and the down-regulations of the cell adhesion-related enzyme generation processes51 under an over-oxygenated environment, as mentioned in the previous section. Results for A. viscosus (Fig. 7, middle) have shown the significant aggregation ability under all the oxygenation levels, but there was no clear trend between the oxygen level, cell growth and the aggregation rate. To our best knowledge, the auto-aggregation ability of A. viscosus has not yet been quantitatively characterized in the previous research. On the other hand, F. nucleatum bacteria showed their aggregation abilities with a correlation to the growth under different DO conditions (Fig. 6b, right; and Fig. 7, right). F. nucleatum showed relatively greater auto-aggregation ability compared with S. mutans, as also reported in other related research.54,55 Therefore, it may be concluded that the auto-aggregation of bacteria under different DO microenvironments is highly independent of the cell growth rate, or at a minimum such behavior is species-specific.
Furthermore, the aggregation of multiple bacterial species in a dental biofilm offers the fundamental cell–cell interactions during the biofilm formation. It has been well proven that a bacterial species can aggregate with multiple species, because the species may have different recognition sites (e.g. polysaccharides56) for attachment of other bacterial species. The aggregation provides also preferred microenvironments for multiple species growing simultaneously in the biofilm.54,56 S. mutans, A. viscosus and F. nucleatum have important and irreplaceable roles in formation of the dental biofilm, in which the bacterial aggregation affects a wide range of genes expressions, stimulates metabolic pathways for energy sources, and eventually diversifies the cellular metabolism schemes.55 In the early stage of dental biofilm formation, some bacteria species (mainly Streptococci including S. mutans) adhere to pellicles on tooth surfaces and initiate the attachment of other species throughout the formation processes.49–51 One of these species is Actinomyces sp., such as A. viscosus, that has a great adhesion capability in biofilm formation.69,70 The interaction between Streptococci and Actinomyces forms the primary community of dental biofilm.71 The aggregation ability of F. nucleatum is particularly important in the dental biofilm formation. F. nucleatum is known as a ‘bridging’ species as it can also co-aggregate with most aerobic and anaerobic bacteria species (up to hundreds of known cell types56,72–74), subsequently colonizing and forming microflora as mature dental biofilms in human oral cavities.54–56 Interestingly, as shown in this work, although the growth of S. mutans and A. viscosus are restrained in anaerobic environment, the aggregation abilities for the three bacteria (including also F. nucleatum) are all significant. This observation has a good agreement with our understanding on dental biofilm formation that the bacteria aggregation often occurs more rapidly in a closed oral cavity, in which the DO level is relatively low after the oxygen consumption by the aerobic dental bacteria. This quantified bacteria behavior may provide further insights to the dental biofilm formation and further effective ways to inhibit the formation process.
We applied the oxygenated culture to study the growth characteristics of three dental bacteria species: S. mutans, A. viscosus and F. nucleatum. Our results showed that their growth rates and aggregation capabilities were dependent on the cell type and highly sensitive to the DO levels; and more importantly, the bacterial aggregation was independent of their growths. Interestingly, all the three chosen bacteria showed significant aggregation capabilities in the anaerobic microenvironment. These results may provide important insights to deepen our understanding of the biofilm formation mechanism. In essence, this work has demonstrated that an effective and stable oxygenation strategy, which can provide a defined DO environment for long-term analyses of cell growth and biofilm formation. This strategy can be further applied to general high-throughput studies on cell and biofilm behaviors responding to DO levels, such as aggregations and cell–cell communications.
Footnote |
† Electronic supplementary information (ESI) available. See DOI: 10.1039/c4ra01577k |
This journal is © The Royal Society of Chemistry 2014 |